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Adding Multi-GPU Data Parallel Example #855

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merged 12 commits into from
Nov 22, 2022

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@bschifferer bschifferer commented Nov 3, 2022

It requires following PR:#825

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GitHub pull request #855 of commit 33888c1ada8c9a55bcb15e18ff6d48da525373d4, no merge conflicts.
Running as SYSTEM
Setting status of 33888c1ada8c9a55bcb15e18ff6d48da525373d4 to PENDING with url https://10.20.13.93:8080/job/merlin_models/1724/console and message: 'Pending'
Using context: Jenkins
Building on master in workspace /var/jenkins_home/workspace/merlin_models
using credential nvidia-merlin-bot
 > git rev-parse --is-inside-work-tree # timeout=10
Fetching changes from the remote Git repository
 > git config remote.origin.url https://github.com/NVIDIA-Merlin/models/ # timeout=10
Fetching upstream changes from https://github.com/NVIDIA-Merlin/models/
 > git --version # timeout=10
using GIT_ASKPASS to set credentials This is the bot credentials for our CI/CD
 > git fetch --tags --force --progress -- https://github.com/NVIDIA-Merlin/models/ +refs/pull/855/*:refs/remotes/origin/pr/855/* # timeout=10
 > git rev-parse 33888c1ada8c9a55bcb15e18ff6d48da525373d4^{commit} # timeout=10
Checking out Revision 33888c1ada8c9a55bcb15e18ff6d48da525373d4 (detached)
 > git config core.sparsecheckout # timeout=10
 > git checkout -f 33888c1ada8c9a55bcb15e18ff6d48da525373d4 # timeout=10
Commit message: "multi gpu example"
 > git rev-list --no-walk 464f4a663ec1be93f8e19c6faa0ba405e51715e0 # timeout=10
[merlin_models] $ /bin/bash /tmp/jenkins13427896109583048838.sh
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Requirement already satisfied: testbook in /usr/local/lib/python3.8/dist-packages (0.4.2)
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Requirement already satisfied: importlib-resources>=1.4.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (5.9.0)
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Requirement already satisfied: pkgutil-resolve-name>=1.3.10 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (1.3.10)
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Requirement already satisfied: entrypoints in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (0.4)
Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (2.8.2)
Requirement already satisfied: zipp>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from importlib-resources>=1.4.0->jsonschema>=2.6->nbformat>=5.0.4->testbook) (3.8.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.8.2->jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (1.15.0)
GLOB sdist-make: /var/jenkins_home/workspace/merlin_models/models/setup.py
test-gpu inst-nodeps: /var/jenkins_home/workspace/merlin_models/models/.tox/.tmp/package/2/merlin-models-0.9.0+27.g33888c1a.zip
WARNING: Discarding $PYTHONPATH from environment, to override specify PYTHONPATH in 'passenv' in your configuration.
test-gpu installed: absl-py==1.2.0,aiohttp==3.8.1,aiosignal==1.2.0,alabaster==0.7.12,alembic==1.8.1,anyio==3.6.1,appdirs==1.4.4,argon2-cffi==21.3.0,argon2-cffi-bindings==21.2.0,astroid==2.5.6,asttokens==2.0.8,astunparse==1.6.3,asv==0.5.1,asvdb==0.4.2,async-timeout==4.0.2,attrs==22.1.0,autopage==0.5.1,awscli==1.27.1,Babel==2.10.3,backcall==0.2.0,beautifulsoup4==4.11.1,betterproto==1.2.5,black==20.8b1,bleach==5.0.1,boto3==1.24.75,botocore==1.29.1,Brotli==1.0.9,build==0.9.0,cachetools==5.2.0,certifi==2019.11.28,cffi==1.15.1,chardet==3.0.4,charset-normalizer==2.1.1,check-manifest==0.48,clang==5.0,click==8.1.3,cliff==4.0.0,cloudpickle==2.2.0,cmaes==0.8.2,cmake==3.24.1.1,cmd2==2.4.2,colorama==0.4.4,colorlog==6.7.0,contourpy==1.0.5,coverage==6.5.0,cuda-python==11.7.1,cupy-cuda117==10.6.0,cycler==0.11.0,Cython==0.29.32,dask==2022.1.1,dbus-python==1.2.16,debugpy==1.6.3,decorator==5.1.1,defusedxml==0.7.1,dill==0.3.5.1,distlib==0.3.6,distributed==2022.5.1,distro==1.7.0,dm-tree==0.1.6,docker-pycreds==0.4.0,docutils==0.16,emoji==1.7.0,entrypoints==0.4,execnet==1.9.0,executing==1.0.0,faiss==1.7.2,faiss-gpu==1.7.2,fastai==2.7.9,fastapi==0.85.0,fastavro==1.6.1,fastcore==1.5.27,fastdownload==0.0.7,fastjsonschema==2.16.1,fastprogress==1.0.3,fastrlock==0.8,feast==0.19.4,fiddle==0.2.2,filelock==3.8.0,flake8==5.0.4,flatbuffers==1.12,fonttools==4.37.3,frozenlist==1.3.1,fsspec==2022.5.0,gast==0.4.0,gevent==21.12.0,geventhttpclient==2.0.2,gitdb==4.0.9,GitPython==3.1.27,google==3.0.0,google-api-core==2.10.1,google-auth==2.11.1,google-auth-oauthlib==0.4.6,google-pasta==0.2.0,googleapis-common-protos==1.52.0,graphviz==0.20.1,greenlet==1.1.3,grpcio==1.41.0,grpcio-channelz==1.49.0,grpcio-reflection==1.48.1,grpclib==0.4.3,h11==0.13.0,h2==4.1.0,h5py==3.7.0,HeapDict==1.0.1,horovod==0.26.1,hpack==4.0.0,httptools==0.5.0,hugectr2onnx==0.0.0,huggingface-hub==0.9.1,hyperframe==6.0.1,idna==2.8,imagesize==1.4.1,implicit==0.6.1,importlib-metadata==4.12.0,importlib-resources==5.9.0,iniconfig==1.1.1,interrogate==1.5.0,ipykernel==6.15.3,ipython==8.5.0,ipython-genutils==0.2.0,ipywidgets==7.7.0,isort==5.10.1,jedi==0.18.1,Jinja2==3.1.2,jmespath==1.0.1,joblib==1.2.0,json5==0.9.10,jsonschema==4.16.0,jupyter==1.0.0,jupyter-cache==0.4.3,jupyter-console==6.4.4,jupyter-core==4.11.1,jupyter-server==1.18.1,jupyter-server-mathjax==0.2.5,jupyter-sphinx==0.3.2,jupyter_client==7.3.5,jupyterlab==3.4.7,jupyterlab-pygments==0.2.2,jupyterlab-widgets==1.1.0,jupyterlab_server==2.15.1,keras==2.9.0,Keras-Preprocessing==1.1.2,kiwisolver==1.4.4,lazy-object-proxy==1.8.0,libclang==14.0.6,libcst==0.4.7,lightfm==1.16,lightgbm==3.3.2,linkify-it-py==1.0.3,llvmlite==0.39.1,locket==1.0.0,lxml==4.9.1,Mako==1.2.3,Markdown==3.4.1,markdown-it-py==1.1.0,MarkupSafe==2.1.1,matplotlib==3.6.0,matplotlib-inline==0.1.6,mccabe==0.7.0,mdit-py-plugins==0.2.8,merlin-core==0.6.0+1.g5926fcf,merlin-dataloader @ git+https://github.com/NVIDIA-Merlin/dataloader.git@5905283777ff5ebd748a1c91b7c9fde5710ae775,merlin-models==0.9.0+27.g33888c1a,merlin-systems==0.5.0+4.g15074ad,mistune==2.0.4,mmh3==3.0.0,mpi4py==3.1.3,msgpack==1.0.4,multidict==6.0.2,mypy==0.982,mypy-extensions==0.4.3,myst-nb==0.13.2,myst-parser==0.15.2,natsort==8.1.0,nbclassic==0.4.3,nbclient==0.6.8,nbconvert==7.0.0,nbdime==3.1.1,nbformat==5.5.0,nest-asyncio==1.5.5,ninja==1.10.2.3,notebook==6.4.12,notebook-shim==0.1.0,numba==0.56.2,numpy==1.22.4,nvidia-pyindex==1.0.9,# Editable install with no version control (nvtabular==1.4.0+8.g95e12d347),-e /usr/local/lib/python3.8/dist-packages,nvtx==0.2.5,oauthlib==3.2.1,oldest-supported-numpy==2022.8.16,onnx==1.12.0,onnxruntime==1.11.1,opt-einsum==3.3.0,optuna==3.0.3,packaging==21.3,pandas==1.3.5,pandavro==1.5.2,pandocfilters==1.5.0,parso==0.8.3,partd==1.3.0,pathspec==0.10.1,pathtools==0.1.2,pbr==5.11.0,pep517==0.13.0,pexpect==4.8.0,pickleshare==0.7.5,Pillow==9.2.0,pkgutil_resolve_name==1.3.10,platformdirs==2.5.2,plotly==5.11.0,pluggy==1.0.0,prettytable==3.5.0,prometheus-client==0.14.1,promise==2.3,prompt-toolkit==3.0.31,proto-plus==1.19.6,protobuf==3.19.5,psutil==5.9.2,ptyprocess==0.7.0,pure-eval==0.2.2,py==1.11.0,pyarrow==7.0.0,pyasn1==0.4.8,pyasn1-modules==0.2.8,pybind11==2.10.0,pycodestyle==2.9.1,pycparser==2.21,pydantic==1.10.2,pydot==1.4.2,pyflakes==2.5.0,Pygments==2.13.0,PyGObject==3.36.0,pynvml==11.4.1,pyparsing==3.0.9,pyperclip==1.8.2,pyrsistent==0.18.1,pytest==7.1.3,pytest-cov==4.0.0,pytest-xdist==3.0.2,python-apt==2.0.0+ubuntu0.20.4.8,python-dateutil==2.8.2,python-dotenv==0.21.0,python-rapidjson==1.8,pytz==2022.2.1,PyYAML==5.4.1,pyzmq==24.0.0,qtconsole==5.3.2,QtPy==2.2.1,regex==2022.9.13,requests==2.22.0,requests-oauthlib==1.3.1,requests-unixsocket==0.2.0,rsa==4.7.2,s3fs==2022.2.0,s3transfer==0.6.0,sacremoses==0.0.53,scikit-build==0.15.0,scikit-learn==1.1.2,scipy==1.8.1,seedir==0.3.0,Send2Trash==1.8.0,sentry-sdk==1.9.8,setproctitle==1.3.2,setuptools-scm==7.0.5,shortuuid==1.0.9,six==1.15.0,sklearn==0.0,smmap==5.0.0,sniffio==1.3.0,snowballstemmer==2.2.0,sortedcontainers==2.4.0,soupsieve==2.3.2.post1,Sphinx==5.3.0,sphinx-multiversion==0.2.4,sphinx-togglebutton==0.3.1,sphinx_external_toc==0.3.0,sphinxcontrib-applehelp==1.0.2,sphinxcontrib-copydirs @ git+https://github.com/mikemckiernan/sphinxcontrib-copydirs.git@bd8c5d79b3f91cf5f1bb0d6995aeca3fe84b670e,sphinxcontrib-devhelp==1.0.2,sphinxcontrib-htmlhelp==2.0.0,sphinxcontrib-jsmath==1.0.1,sphinxcontrib-qthelp==1.0.3,sphinxcontrib-serializinghtml==1.1.5,SQLAlchemy==1.4.42,stack-data==0.5.0,starlette==0.20.4,stevedore==4.1.0,stringcase==1.2.0,supervisor==4.1.0,tabulate==0.8.10,tblib==1.7.0,tdqm==0.0.1,tenacity==8.0.1,tensorboard==2.9.1,tensorboard-data-server==0.6.1,tensorboard-plugin-wit==1.8.1,tensorflow==2.9.2,tensorflow-estimator==2.9.0,tensorflow-gpu==2.9.2,tensorflow-io-gcs-filesystem==0.27.0,tensorflow-metadata==1.10.0,tensorflow-ranking==0.5.1,tensorflow-serving-api==2.9.2,termcolor==2.0.1,terminado==0.15.0,testbook==0.4.2,threadpoolctl==3.1.0,tinycss2==1.1.1,tokenizers==0.10.3,toml==0.10.2,tomli==2.0.1,toolz==0.12.0,torch==1.12.1+cu113,torchmetrics==0.3.2,tornado==6.2,tox==3.26.0,tqdm==4.64.1,traitlets==5.4.0,transformers==4.12.0,transformers4rec==0.1.12+2.gbcc939255,treelite==2.3.0,treelite-runtime==2.3.0,tritonclient==2.25.0,typed-ast==1.5.4,typing-inspect==0.8.0,typing_extensions==4.3.0,uc-micro-py==1.0.1,urllib3==1.26.12,uvicorn==0.18.3,uvloop==0.17.0,versioneer==0.20,virtualenv==20.16.5,wandb==0.13.3,watchfiles==0.17.0,wcwidth==0.2.5,webencodings==0.5.1,websocket-client==1.4.1,websockets==10.3,Werkzeug==2.2.2,widgetsnbextension==3.6.0,wrapt==1.12.1,xgboost==1.6.2,yarl==1.8.1,zict==2.2.0,zipp==3.8.1,zope.event==4.5.0,zope.interface==5.4.0
test-gpu run-test-pre: PYTHONHASHSEED='774739610'
test-gpu run-test: commands[0] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/core.git
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Collecting git+https://github.com/NVIDIA-Merlin/core.git
  Cloning https://github.com/NVIDIA-Merlin/core.git to /tmp/pip-req-build-kb9zy01h
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/core.git /tmp/pip-req-build-kb9zy01h
  Resolved https://github.com/NVIDIA-Merlin/core.git to commit 563be4bf5ef675940d5fff2b5e4666424a7f7947
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: fsspec==2022.5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+5.g563be4b) (2022.5.0)
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Requirement already satisfied: psutil>=5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/psutil-5.8.0-py3.8-linux-x86_64.egg (from distributed>=2022.3.0->merlin-core==0.8.0+5.g563be4b) (5.8.0)
Requirement already satisfied: tblib>=1.6.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/tblib-1.7.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+5.g563be4b) (1.7.0)
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Requirement already satisfied: zict>=0.1.3 in /var/jenkins_home/.local/lib/python3.8/site-packages/zict-2.0.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+5.g563be4b) (2.0.0)
Requirement already satisfied: llvmlite<0.39,>=0.38.0rc1 in ./.tox/test-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+5.g563be4b) (0.38.1)
Requirement already satisfied: setuptools in ./.tox/test-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+5.g563be4b) (59.8.0)
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[notice] A new release of pip available: 22.2.2 -> 22.3
[notice] To update, run: pip install --upgrade pip
test-gpu run-test: commands[1] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/nvtabular.git
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Collecting git+https://github.com/NVIDIA-Merlin/nvtabular.git
Cloning https://github.com/NVIDIA-Merlin/nvtabular.git to /tmp/pip-req-build-mf_6rtzf
Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/nvtabular.git /tmp/pip-req-build-mf_6rtzf
Resolved https://github.com/NVIDIA-Merlin/nvtabular.git to commit 8e7edbafd3006f56e73efdc0c01c4445ab57d028
Installing build dependencies: started
Installing build dependencies: finished with status 'done'
Getting requirements to build wheel: started
Getting requirements to build wheel: finished with status 'done'
Preparing metadata (pyproject.toml): started
Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: scipy in /usr/local/lib/python3.8/dist-packages (from nvtabular==1.6.0+3.g8e7edbaf) (1.8.1)
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Requirement already satisfied: hpack<5,>=4.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core>=0.2.0->nvtabular==1.6.0+3.g8e7edbaf) (4.0.0)

[notice] A new release of pip available: 22.2.2 -> 22.3
[notice] To update, run: pip install --upgrade pip
test-gpu run-test: commands[2] | python -m pytest --cov-report term --cov merlin -rxs tests/unit
============================= test session starts ==============================
platform linux -- Python 3.8.10, pytest-7.1.3, pluggy-1.0.0
cachedir: .tox/test-gpu/.pytest_cache
rootdir: /var/jenkins_home/workspace/merlin_models/models, configfile: pyproject.toml
plugins: anyio-3.5.0, xdist-3.0.2, cov-4.0.0
collected 836 items

tests/unit/config/test_schema.py .... [ 0%]
tests/unit/datasets/test_advertising.py .s [ 0%]
tests/unit/datasets/test_ecommerce.py ..sss [ 1%]
tests/unit/datasets/test_entertainment.py ....sss. [ 2%]
tests/unit/datasets/test_social.py . [ 2%]
tests/unit/datasets/test_synthetic.py ...... [ 3%]
tests/unit/implicit/test_implicit.py . [ 3%]
tests/unit/lightfm/test_lightfm.py . [ 3%]
tests/unit/tf/test_core.py ...... [ 4%]
tests/unit/tf/test_loader.py ................ [ 5%]
tests/unit/tf/test_public_api.py . [ 6%]
tests/unit/tf/blocks/test_cross.py ........... [ 7%]
tests/unit/tf/blocks/test_dlrm.py .......... [ 8%]
tests/unit/tf/blocks/test_interactions.py ... [ 8%]
tests/unit/tf/blocks/test_mlp.py ................................. [ 12%]
tests/unit/tf/blocks/test_optimizer.py s................................ [ 16%]
..................... [ 19%]
tests/unit/tf/blocks/retrieval/test_base.py . [ 19%]
tests/unit/tf/blocks/retrieval/test_matrix_factorization.py .. [ 19%]
tests/unit/tf/blocks/retrieval/test_two_tower.py ............ [ 21%]
tests/unit/tf/blocks/sampling/test_cross_batch.py . [ 21%]
tests/unit/tf/blocks/sampling/test_in_batch.py . [ 21%]
tests/unit/tf/core/test_aggregation.py ......... [ 22%]
tests/unit/tf/core/test_base.py .. [ 22%]
tests/unit/tf/core/test_combinators.py s..................... [ 25%]
tests/unit/tf/core/test_encoder.py .. [ 25%]
tests/unit/tf/core/test_index.py ... [ 25%]
tests/unit/tf/core/test_prediction.py .. [ 26%]
tests/unit/tf/core/test_tabular.py ...... [ 26%]
tests/unit/tf/examples/test_01_getting_started.py . [ 27%]
tests/unit/tf/examples/test_02_dataschema.py . [ 27%]
tests/unit/tf/examples/test_03_exploring_different_models.py . [ 27%]
tests/unit/tf/examples/test_04_export_ranking_models.py . [ 27%]
tests/unit/tf/examples/test_05_export_retrieval_model.py . [ 27%]
tests/unit/tf/examples/test_06_advanced_own_architecture.py . [ 27%]
tests/unit/tf/examples/test_07_train_traditional_models.py . [ 27%]
tests/unit/tf/examples/test_usecase_accelerate_training_by_lazyadam.py . [ 27%]
[ 27%]
tests/unit/tf/examples/test_usecase_data_parallel.py . [ 27%]
tests/unit/tf/examples/test_usecase_ecommerce_session_based.py . [ 28%]
tests/unit/tf/examples/test_usecase_incremental_training_layer_freezing.py F [ 28%]
[ 28%]
tests/unit/tf/examples/test_usecase_pretrained_embeddings.py . [ 28%]
tests/unit/tf/examples/test_usecase_retrieval_with_hpo.py . [ 28%]
tests/unit/tf/inputs/test_continuous.py ........ [ 29%]
tests/unit/tf/inputs/test_embedding.py ................................. [ 33%]
........ [ 34%]
tests/unit/tf/inputs/test_tabular.py .................. [ 36%]
tests/unit/tf/layers/test_queue.py .............. [ 38%]
tests/unit/tf/losses/test_losses.py ....................... [ 40%]
tests/unit/tf/metrics/test_metrics_popularity.py ..... [ 41%]
tests/unit/tf/metrics/test_metrics_topk.py ......................... [ 44%]
tests/unit/tf/models/test_base.py s........................ [ 47%]
tests/unit/tf/models/test_benchmark.py .. [ 47%]
tests/unit/tf/models/test_ranking.py .................................. [ 51%]
tests/unit/tf/models/test_retrieval.py ................................. [ 55%]
.......................................... [ 60%]
tests/unit/tf/outputs/test_base.py ...... [ 61%]
tests/unit/tf/outputs/test_classification.py ...... [ 62%]
tests/unit/tf/outputs/test_contrastive.py .............. [ 63%]
tests/unit/tf/outputs/test_regression.py .. [ 64%]
tests/unit/tf/outputs/test_sampling.py .... [ 64%]
tests/unit/tf/outputs/test_topk.py . [ 64%]
tests/unit/tf/prediction_tasks/test_classification.py .. [ 64%]
tests/unit/tf/prediction_tasks/test_multi_task.py ................ [ 66%]
tests/unit/tf/prediction_tasks/test_next_item.py ..... [ 67%]
tests/unit/tf/prediction_tasks/test_regression.py ..... [ 68%]
tests/unit/tf/prediction_tasks/test_retrieval.py . [ 68%]
tests/unit/tf/prediction_tasks/test_sampling.py ...... [ 68%]
tests/unit/tf/transformers/test_block.py ..................... [ 71%]
tests/unit/tf/transformers/test_transforms.py .......... [ 72%]
tests/unit/tf/transforms/test_bias.py .. [ 72%]
tests/unit/tf/transforms/test_features.py s............................. [ 76%]
.......................s...... [ 80%]
tests/unit/tf/transforms/test_negative_sampling.py ......... [ 81%]
tests/unit/tf/transforms/test_noise.py ..... [ 81%]
tests/unit/tf/transforms/test_sequence.py .................... [ 84%]
tests/unit/tf/transforms/test_tensor.py ... [ 84%]
tests/unit/tf/utils/test_batch.py .... [ 84%]
tests/unit/tf/utils/test_dataset.py .. [ 85%]
tests/unit/tf/utils/test_tf_utils.py ..... [ 85%]
tests/unit/torch/test_dataset.py ......... [ 86%]
tests/unit/torch/test_public_api.py . [ 86%]
tests/unit/torch/block/test_base.py .... [ 87%]
tests/unit/torch/block/test_mlp.py . [ 87%]
tests/unit/torch/features/test_continuous.py .. [ 87%]
tests/unit/torch/features/test_embedding.py .............. [ 89%]
tests/unit/torch/features/test_tabular.py .... [ 89%]
tests/unit/torch/model/test_head.py ............ [ 91%]
tests/unit/torch/model/test_model.py .. [ 91%]
tests/unit/torch/tabular/test_aggregation.py ........ [ 92%]
tests/unit/torch/tabular/test_tabular.py ... [ 92%]
tests/unit/torch/tabular/test_transformations.py ....... [ 93%]
tests/unit/utils/test_schema_utils.py ................................ [ 97%]
tests/unit/xgb/test_xgboost.py .................... [100%]

=================================== FAILURES ===================================
_______________ test_usecase_incremental_training_layer_freezing _______________

tb = <testbook.client.TestbookNotebookClient object at 0x7f1db6045cd0>

@testbook(
    REPO_ROOT / p,
    timeout=180,
    execute=False,
)
def test_usecase_incremental_training_layer_freezing(tb):
    tb.inject(
        """
        import os
        os.environ["NUM_ROWS"] = "1000"
        """
    )
  tb.execute()

tests/unit/tf/examples/test_usecase_incremental_training_layer_freezing.py:22:


../../../.local/lib/python3.8/site-packages/testbook/client.py:147: in execute
super().execute_cell(cell, index)
../../../.local/lib/python3.8/site-packages/nbclient/util.py:84: in wrapped
return just_run(coro(*args, **kwargs))
../../../.local/lib/python3.8/site-packages/nbclient/util.py:62: in just_run
return loop.run_until_complete(coro)
/usr/lib/python3.8/asyncio/base_events.py:616: in run_until_complete
return future.result()
../../../.local/lib/python3.8/site-packages/nbclient/client.py:965: in async_execute_cell
await self._check_raise_for_error(cell, cell_index, exec_reply)


self = <testbook.client.TestbookNotebookClient object at 0x7f1db6045cd0>
cell = {'cell_type': 'code', 'execution_count': 8, 'id': '791e06ec-c0cb-4c0f-9e41-7e5c8fa1dc4e', 'metadata': {'execution': {'...: 'model.compile(optimizer=tf.keras.optimizers.Adam(learning_rate=0.01))\nmodel.fit(day_1, batch_size=1024, epochs=1)'}
cell_index = 13
exec_reply = {'buffers': [], 'content': {'ename': 'ResourceExhaustedError', 'engine_info': {'engine_id': -1, 'engine_uuid': '3f2fe6...e, 'engine': '3f2fe6e9-2b4f-4724-a6d8-77d8de955f40', 'started': '2022-11-03T14:46:15.169749Z', 'status': 'error'}, ...}

async def _check_raise_for_error(
    self, cell: NotebookNode, cell_index: int, exec_reply: t.Optional[t.Dict]
) -> None:

    if exec_reply is None:
        return None

    exec_reply_content = exec_reply['content']
    if exec_reply_content['status'] != 'error':
        return None

    cell_allows_errors = (not self.force_raise_errors) and (
        self.allow_errors
        or exec_reply_content.get('ename') in self.allow_error_names
        or "raises-exception" in cell.metadata.get("tags", [])
    )
    await run_hook(self.on_cell_error, cell=cell, cell_index=cell_index)
    if not cell_allows_errors:
      raise CellExecutionError.from_cell_and_msg(cell, exec_reply_content)

E nbclient.exceptions.CellExecutionError: An error occurred while executing the following cell:
E ------------------
E model.compile(optimizer=tf.keras.optimizers.Adam(learning_rate=0.01))
E model.fit(day_1, batch_size=1024, epochs=1)
E ------------------
E
E �[0;31m---------------------------------------------------------------------------�[0m
E �[0;31mResourceExhaustedError�[0m Traceback (most recent call last)
E Cell �[0;32mIn [8], line 2�[0m
E �[1;32m 1�[0m model�[38;5;241m.�[39mcompile(optimizer�[38;5;241m=�[39mtf�[38;5;241m.�[39mkeras�[38;5;241m.�[39moptimizers�[38;5;241m.�[39mAdam(learning_rate�[38;5;241m=�[39m�[38;5;241m0.01�[39m))
E �[0;32m----> 2�[0m �[43mmodel�[49m�[38;5;241;43m.�[39;49m�[43mfit�[49m�[43m(�[49m�[43mday_1�[49m�[43m,�[49m�[43m �[49m�[43mbatch_size�[49m�[38;5;241;43m=�[39;49m�[38;5;241;43m1024�[39;49m�[43m,�[49m�[43m �[49m�[43mepochs�[49m�[38;5;241;43m=�[39;49m�[38;5;241;43m1�[39;49m�[43m)�[49m
E
E File �[0;32m~/workspace/merlin_models/models/merlin/models/tf/models/base.py:856�[0m, in �[0;36mBaseModel.fit�[0;34m(self, x, y, batch_size, epochs, verbose, callbacks, validation_split, validation_data, shuffle, class_weight, sample_weight, initial_epoch, steps_per_epoch, validation_steps, validation_batch_size, validation_freq, max_queue_size, workers, use_multiprocessing, train_metrics_steps, pre, **kwargs)�[0m
E �[1;32m 853�[0m �[38;5;28mself�[39m�[38;5;241m.�[39m_reset_compile_cache()
E �[1;32m 854�[0m �[38;5;28mself�[39m�[38;5;241m.�[39mtrain_pre �[38;5;241m=�[39m pre
E �[0;32m--> 856�[0m out �[38;5;241m=�[39m �[38;5;28;43msuper�[39;49m�[43m(�[49m�[43m)�[49m�[38;5;241;43m.�[39;49m�[43mfit�[49m�[43m(�[49m�[38;5;241;43m�[39;49m�[38;5;241;43m�[39;49m�[43mfit_kwargs�[49m�[43m)�[49m
E �[1;32m 858�[0m �[38;5;28;01mif�[39;00m pre:
E �[1;32m 859�[0m �[38;5;28;01mdel�[39;00m �[38;5;28mself�[39m�[38;5;241m.�[39mtrain_pre
E
E File �[0;32m~/.local/lib/python3.8/site-packages/keras/utils/traceback_utils.py:67�[0m, in �[0;36mfilter_traceback..error_handler�[0;34m(*args, **kwargs)�[0m
E �[1;32m 65�[0m �[38;5;28;01mexcept�[39;00m �[38;5;167;01mException�[39;00m �[38;5;28;01mas�[39;00m e: �[38;5;66;03m# pylint: disable=broad-except�[39;00m
E �[1;32m 66�[0m filtered_tb �[38;5;241m=�[39m process_traceback_frames(e�[38;5;241m.�[39m__traceback_)
E �[0;32m---> 67�[0m �[38;5;28;01mraise�[39;00m e�[38;5;241m.�[39mwith_traceback(filtered_tb) �[38;5;28;01mfrom�[39;00m �[38;5;28mNone�[39m
E �[1;32m 68�[0m �[38;5;28;01mfinally�[39;00m:
E �[1;32m 69�[0m �[38;5;28;01mdel�[39;00m filtered_tb
E
E File �[0;32m~/.local/lib/python3.8/site-packages/tensorflow/python/eager/execute.py:54�[0m, in �[0;36mquick_execute�[0;34m(op_name, num_outputs, inputs, attrs, ctx, name)�[0m
E �[1;32m 52�[0m �[38;5;28;01mtry�[39;00m:
E �[1;32m 53�[0m ctx�[38;5;241m.�[39mensure_initialized()
E �[0;32m---> 54�[0m tensors �[38;5;241m=�[39m pywrap_tfe�[38;5;241m.�[39mTFE_Py_Execute(ctx�[38;5;241m.�[39m_handle, device_name, op_name,
E �[1;32m 55�[0m inputs, attrs, num_outputs)
E �[1;32m 56�[0m �[38;5;28;01mexcept�[39;00m core�[38;5;241m.�[39m_NotOkStatusException �[38;5;28;01mas�[39;00m e:
E �[1;32m 57�[0m �[38;5;28;01mif�[39;00m name �[38;5;129;01mis�[39;00m �[38;5;129;01mnot�[39;00m �[38;5;28;01mNone�[39;00m:
E
E �[0;31mResourceExhaustedError�[0m: Graph execution error:
E
E Detected at node 'Adam/Adam/update_19/mul_1' defined at (most recent call last):
E File "/usr/lib/python3.8/runpy.py", line 194, in _run_module_as_main
E return _run_code(code, main_globals, None,
E File "/usr/lib/python3.8/runpy.py", line 87, in _run_code
E exec(code, run_globals)
E File "/usr/local/lib/python3.8/dist-packages/ipykernel_launcher.py", line 17, in
E app.launch_new_instance()
E File "/usr/local/lib/python3.8/dist-packages/traitlets/config/application.py", line 978, in launch_instance
E app.start()
E File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelapp.py", line 712, in start
E self.io_loop.start()
E File "/var/jenkins_home/workspace/merlin_models/models/.tox/test-gpu/lib/python3.8/site-packages/tornado/platform/asyncio.py", line 215, in start
E self.asyncio_loop.run_forever()
E File "/usr/lib/python3.8/asyncio/base_events.py", line 570, in run_forever
E self._run_once()
E File "/usr/lib/python3.8/asyncio/base_events.py", line 1859, in _run_once
E handle._run()
E File "/usr/lib/python3.8/asyncio/events.py", line 81, in _run
E self._context.run(self._callback, *self._args)
E File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 510, in dispatch_queue
E await self.process_one()
E File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 499, in process_one
E await dispatch(*args)
E File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 406, in dispatch_shell
E await result
E File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 730, in execute_request
E reply_content = await reply_content
E File "/usr/local/lib/python3.8/dist-packages/ipykernel/ipkernel.py", line 383, in do_execute
E res = shell.run_cell(
E File "/usr/local/lib/python3.8/dist-packages/ipykernel/zmqshell.py", line 528, in run_cell
E return super().run_cell(*args, **kwargs)
E File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 2885, in run_cell
E result = self._run_cell(
E File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 2940, in _run_cell
E return runner(coro)
E File "/usr/local/lib/python3.8/dist-packages/IPython/core/async_helpers.py", line 129, in pseudo_sync_runner
E coro.send(None)
E File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3139, in run_cell_async
E has_raised = await self.run_ast_nodes(code_ast.body, cell_name,
E File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3318, in run_ast_nodes
E if await self.run_code(code, result, async
=asy):
E File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3378, in run_code
E exec(code_obj, self.user_global_ns, self.user_ns)
E File "/tmp/ipykernel_12416/2071866865.py", line 2, in
E model.fit(day_1, batch_size=1024, epochs=1)
E File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/models/base.py", line 856, in fit
E out = super().fit(**fit_kwargs)
E File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/traceback_utils.py", line 64, in error_handler
E return fn(*args, **kwargs)
E File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1409, in fit
E tmp_logs = self.train_function(iterator)
E File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1051, in train_function
E return step_function(self, iterator)
E File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1040, in step_function
E outputs = model.distribute_strategy.run(run_step, args=(data,))
E File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1030, in run_step
E outputs = model.train_step(data)
E File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/models/base.py", line 683, in train_step
E self.optimizer.minimize(loss, self.trainable_variables, tape=tape)
E File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 539, in minimize
E return self.apply_gradients(grads_and_vars, name=name)
E File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 678, in apply_gradients
E return tf.internal.distribute.interim.maybe_merge_call(
E File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 723, in _distributed_apply
E update_op = distribution.extended.update(
E File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 701, in apply_grad_to_update_var
E return self._resource_apply_sparse_duplicate_indices(
E File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 1326, in _resource_apply_sparse_duplicate_indices
E return self._resource_apply_sparse(summed_grad, handle, unique_indices,
E File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/adam.py", line 206, in _resource_apply_sparse
E m_t = tf.compat.v1.assign(m, m * coefficients['beta_1_t'],
E Node: 'Adam/Adam/update_19/mul_1'
E Detected at node 'Adam/Adam/update_19/mul_1' defined at (most recent call last):
E File "/usr/lib/python3.8/runpy.py", line 194, in _run_module_as_main
E return _run_code(code, main_globals, None,
E File "/usr/lib/python3.8/runpy.py", line 87, in _run_code
E exec(code, run_globals)
E File "/usr/local/lib/python3.8/dist-packages/ipykernel_launcher.py", line 17, in
E app.launch_new_instance()
E File "/usr/local/lib/python3.8/dist-packages/traitlets/config/application.py", line 978, in launch_instance
E app.start()
E File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelapp.py", line 712, in start
E self.io_loop.start()
E File "/var/jenkins_home/workspace/merlin_models/models/.tox/test-gpu/lib/python3.8/site-packages/tornado/platform/asyncio.py", line 215, in start
E self.asyncio_loop.run_forever()
E File "/usr/lib/python3.8/asyncio/base_events.py", line 570, in run_forever
E self._run_once()
E File "/usr/lib/python3.8/asyncio/base_events.py", line 1859, in _run_once
E handle._run()
E File "/usr/lib/python3.8/asyncio/events.py", line 81, in _run
E self._context.run(self._callback, *self._args)
E File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 510, in dispatch_queue
E await self.process_one()
E File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 499, in process_one
E await dispatch(*args)
E File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 406, in dispatch_shell
E await result
E File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 730, in execute_request
E reply_content = await reply_content
E File "/usr/local/lib/python3.8/dist-packages/ipykernel/ipkernel.py", line 383, in do_execute
E res = shell.run_cell(
E File "/usr/local/lib/python3.8/dist-packages/ipykernel/zmqshell.py", line 528, in run_cell
E return super().run_cell(*args, **kwargs)
E File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 2885, in run_cell
E result = self._run_cell(
E File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 2940, in _run_cell
E return runner(coro)
E File "/usr/local/lib/python3.8/dist-packages/IPython/core/async_helpers.py", line 129, in pseudo_sync_runner
E coro.send(None)
E File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3139, in run_cell_async
E has_raised = await self.run_ast_nodes(code_ast.body, cell_name,
E File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3318, in run_ast_nodes
E if await self.run_code(code, result, async
=asy):
E File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3378, in run_code
E exec(code_obj, self.user_global_ns, self.user_ns)
E File "/tmp/ipykernel_12416/2071866865.py", line 2, in
E model.fit(day_1, batch_size=1024, epochs=1)
E File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/models/base.py", line 856, in fit
E out = super().fit(**fit_kwargs)
E File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/traceback_utils.py", line 64, in error_handler
E return fn(*args, **kwargs)
E File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1409, in fit
E tmp_logs = self.train_function(iterator)
E File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1051, in train_function
E return step_function(self, iterator)
E File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1040, in step_function
E outputs = model.distribute_strategy.run(run_step, args=(data,))
E File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1030, in run_step
E outputs = model.train_step(data)
E File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/models/base.py", line 683, in train_step
E self.optimizer.minimize(loss, self.trainable_variables, tape=tape)
E File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 539, in minimize
E return self.apply_gradients(grads_and_vars, name=name)
E File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 678, in apply_gradients
E return tf.internal.distribute.interim.maybe_merge_call(
E File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 723, in _distributed_apply
E update_op = distribution.extended.update(
E File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 701, in apply_grad_to_update_var
E return self._resource_apply_sparse_duplicate_indices(
E File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 1326, in _resource_apply_sparse_duplicate_indices
E return self._resource_apply_sparse(summed_grad, handle, unique_indices,
E File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/adam.py", line 206, in _resource_apply_sparse
E m_t = tf.compat.v1.assign(m, m * coefficients['beta_1_t'],
E Node: 'Adam/Adam/update_19/mul_1'
E 2 root error(s) found.
E (0) RESOURCE_EXHAUSTED: failed to allocate memory
E [[{{node Adam/Adam/update_19/mul_1}}]]
E Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info. This isn't available when running in Eager mode.
E
E [[StatefulPartitionedCall/cond/pivot_t/_131/_53]]
E Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info. This isn't available when running in Eager mode.
E
E (1) RESOURCE_EXHAUSTED: failed to allocate memory
E [[{{node Adam/Adam/update_19/mul_1}}]]
E Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info. This isn't available when running in Eager mode.
E
E 0 successful operations.
E 0 derived errors ignored. [Op:__inference_train_function_4005]
E ResourceExhaustedError: Graph execution error:
E
E Detected at node 'Adam/Adam/update_19/mul_1' defined at (most recent call last):
E File "/usr/lib/python3.8/runpy.py", line 194, in _run_module_as_main
E return _run_code(code, main_globals, None,
E File "/usr/lib/python3.8/runpy.py", line 87, in _run_code
E exec(code, run_globals)
E File "/usr/local/lib/python3.8/dist-packages/ipykernel_launcher.py", line 17, in
E app.launch_new_instance()
E File "/usr/local/lib/python3.8/dist-packages/traitlets/config/application.py", line 978, in launch_instance
E app.start()
E File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelapp.py", line 712, in start
E self.io_loop.start()
E File "/var/jenkins_home/workspace/merlin_models/models/.tox/test-gpu/lib/python3.8/site-packages/tornado/platform/asyncio.py", line 215, in start
E self.asyncio_loop.run_forever()
E File "/usr/lib/python3.8/asyncio/base_events.py", line 570, in run_forever
E self._run_once()
E File "/usr/lib/python3.8/asyncio/base_events.py", line 1859, in _run_once
E handle._run()
E File "/usr/lib/python3.8/asyncio/events.py", line 81, in _run
E self._context.run(self._callback, *self._args)
E File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 510, in dispatch_queue
E await self.process_one()
E File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 499, in process_one
E await dispatch(*args)
E File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 406, in dispatch_shell
E await result
E File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 730, in execute_request
E reply_content = await reply_content
E File "/usr/local/lib/python3.8/dist-packages/ipykernel/ipkernel.py", line 383, in do_execute
E res = shell.run_cell(
E File "/usr/local/lib/python3.8/dist-packages/ipykernel/zmqshell.py", line 528, in run_cell
E return super().run_cell(*args, **kwargs)
E File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 2885, in run_cell
E result = self._run_cell(
E File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 2940, in _run_cell
E return runner(coro)
E File "/usr/local/lib/python3.8/dist-packages/IPython/core/async_helpers.py", line 129, in pseudo_sync_runner
E coro.send(None)
E File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3139, in run_cell_async
E has_raised = await self.run_ast_nodes(code_ast.body, cell_name,
E File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3318, in run_ast_nodes
E if await self.run_code(code, result, async
=asy):
E File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3378, in run_code
E exec(code_obj, self.user_global_ns, self.user_ns)
E File "/tmp/ipykernel_12416/2071866865.py", line 2, in
E model.fit(day_1, batch_size=1024, epochs=1)
E File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/models/base.py", line 856, in fit
E out = super().fit(**fit_kwargs)
E File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/traceback_utils.py", line 64, in error_handler
E return fn(*args, **kwargs)
E File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1409, in fit
E tmp_logs = self.train_function(iterator)
E File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1051, in train_function
E return step_function(self, iterator)
E File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1040, in step_function
E outputs = model.distribute_strategy.run(run_step, args=(data,))
E File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1030, in run_step
E outputs = model.train_step(data)
E File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/models/base.py", line 683, in train_step
E self.optimizer.minimize(loss, self.trainable_variables, tape=tape)
E File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 539, in minimize
E return self.apply_gradients(grads_and_vars, name=name)
E File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 678, in apply_gradients
E return tf.internal.distribute.interim.maybe_merge_call(
E File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 723, in _distributed_apply
E update_op = distribution.extended.update(
E File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 701, in apply_grad_to_update_var
E return self._resource_apply_sparse_duplicate_indices(
E File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 1326, in _resource_apply_sparse_duplicate_indices
E return self._resource_apply_sparse(summed_grad, handle, unique_indices,
E File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/adam.py", line 206, in _resource_apply_sparse
E m_t = tf.compat.v1.assign(m, m * coefficients['beta_1_t'],
E Node: 'Adam/Adam/update_19/mul_1'
E Detected at node 'Adam/Adam/update_19/mul_1' defined at (most recent call last):
E File "/usr/lib/python3.8/runpy.py", line 194, in _run_module_as_main
E return _run_code(code, main_globals, None,
E File "/usr/lib/python3.8/runpy.py", line 87, in _run_code
E exec(code, run_globals)
E File "/usr/local/lib/python3.8/dist-packages/ipykernel_launcher.py", line 17, in
E app.launch_new_instance()
E File "/usr/local/lib/python3.8/dist-packages/traitlets/config/application.py", line 978, in launch_instance
E app.start()
E File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelapp.py", line 712, in start
E self.io_loop.start()
E File "/var/jenkins_home/workspace/merlin_models/models/.tox/test-gpu/lib/python3.8/site-packages/tornado/platform/asyncio.py", line 215, in start
E self.asyncio_loop.run_forever()
E File "/usr/lib/python3.8/asyncio/base_events.py", line 570, in run_forever
E self._run_once()
E File "/usr/lib/python3.8/asyncio/base_events.py", line 1859, in _run_once
E handle._run()
E File "/usr/lib/python3.8/asyncio/events.py", line 81, in _run
E self._context.run(self._callback, *self._args)
E File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 510, in dispatch_queue
E await self.process_one()
E File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 499, in process_one
E await dispatch(*args)
E File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 406, in dispatch_shell
E await result
E File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 730, in execute_request
E reply_content = await reply_content
E File "/usr/local/lib/python3.8/dist-packages/ipykernel/ipkernel.py", line 383, in do_execute
E res = shell.run_cell(
E File "/usr/local/lib/python3.8/dist-packages/ipykernel/zmqshell.py", line 528, in run_cell
E return super().run_cell(*args, **kwargs)
E File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 2885, in run_cell
E result = self._run_cell(
E File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 2940, in _run_cell
E return runner(coro)
E File "/usr/local/lib/python3.8/dist-packages/IPython/core/async_helpers.py", line 129, in pseudo_sync_runner
E coro.send(None)
E File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3139, in run_cell_async
E has_raised = await self.run_ast_nodes(code_ast.body, cell_name,
E File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3318, in run_ast_nodes
E if await self.run_code(code, result, async
=asy):
E File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3378, in run_code
E exec(code_obj, self.user_global_ns, self.user_ns)
E File "/tmp/ipykernel_12416/2071866865.py", line 2, in
E model.fit(day_1, batch_size=1024, epochs=1)
E File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/models/base.py", line 856, in fit
E out = super().fit(**fit_kwargs)
E File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/traceback_utils.py", line 64, in error_handler
E return fn(*args, **kwargs)
E File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1409, in fit
E tmp_logs = self.train_function(iterator)
E File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1051, in train_function
E return step_function(self, iterator)
E File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1040, in step_function
E outputs = model.distribute_strategy.run(run_step, args=(data,))
E File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1030, in run_step
E outputs = model.train_step(data)
E File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/models/base.py", line 683, in train_step
E self.optimizer.minimize(loss, self.trainable_variables, tape=tape)
E File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 539, in minimize
E return self.apply_gradients(grads_and_vars, name=name)
E File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 678, in apply_gradients
E return tf.internal.distribute.interim.maybe_merge_call(
E File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 723, in _distributed_apply
E update_op = distribution.extended.update(
E File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 701, in apply_grad_to_update_var
E return self._resource_apply_sparse_duplicate_indices(
E File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 1326, in _resource_apply_sparse_duplicate_indices
E return self._resource_apply_sparse(summed_grad, handle, unique_indices,
E File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/adam.py", line 206, in _resource_apply_sparse
E m_t = tf.compat.v1.assign(m, m * coefficients['beta_1_t'],
E Node: 'Adam/Adam/update_19/mul_1'
E 2 root error(s) found.
E (0) RESOURCE_EXHAUSTED: failed to allocate memory
E [[{{node Adam/Adam/update_19/mul_1}}]]
E Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info. This isn't available when running in Eager mode.
E
E [[StatefulPartitionedCall/cond/pivot_t/_131/_53]]
E Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info. This isn't available when running in Eager mode.
E
E (1) RESOURCE_EXHAUSTED: failed to allocate memory
E [[{{node Adam/Adam/update_19/mul_1}}]]
E Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info. This isn't available when running in Eager mode.
E
E 0 successful operations.
E 0 derived errors ignored. [Op:__inference_train_function_4005]

../../../.local/lib/python3.8/site-packages/nbclient/client.py:862: CellExecutionError
----------------------------- Captured stderr call -----------------------------
2022-11-03 14:46:09.324625: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: AVX2 FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
2022-11-03 14:46:13.398735: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 0
2022-11-03 14:46:13.398894: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 8139 MB memory: -> device: 0, name: Tesla P100-DGXS-16GB, pci bus id: 0000:07:00.0, compute capability: 6.0
2022-11-03 14:46:13.399599: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 1
2022-11-03 14:46:13.399655: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:1 with 14500 MB memory: -> device: 1, name: Tesla P100-DGXS-16GB, pci bus id: 0000:08:00.0, compute capability: 6.0
2022-11-03 14:46:13.400229: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 2
2022-11-03 14:46:13.400277: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:2 with 14500 MB memory: -> device: 2, name: Tesla P100-DGXS-16GB, pci bus id: 0000:0e:00.0, compute capability: 6.0
2022-11-03 14:46:13.400868: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 3
2022-11-03 14:46:13.400912: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:3 with 14500 MB memory: -> device: 3, name: Tesla P100-DGXS-16GB, pci bus id: 0000:0f:00.0, compute capability: 6.0
2022-11-03 14:46:29.441011: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:288] gpu_async_0 cuMemAllocAsync failed to allocate 1083564064 bytes: CUDA error: out of memory (CUDA_ERROR_OUT_OF_MEMORY)
Reported by CUDA: Free memory/Total memory: 3735552/17069309952
2022-11-03 14:46:29.441076: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:293] Stats: Limit: 8534360064
InUse: 5731279464
MaxInUse: 5731279464
NumAllocs: 294
MaxAllocSize: 1083564064
Reserved: 0
PeakReserved: 0
LargestFreeBlock: 0

2022-11-03 14:46:29.441098: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:56] Histogram of current allocation: (allocation_size_in_bytes, nb_allocation_of_that_sizes), ...;
2022-11-03 14:46:29.441109: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1, 4
2022-11-03 14:46:29.441115: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 4, 36
2022-11-03 14:46:29.441121: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 8, 8
2022-11-03 14:46:29.441127: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 40, 2
2022-11-03 14:46:29.441133: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 128, 10
2022-11-03 14:46:29.441139: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 160, 10
2022-11-03 14:46:29.441145: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 192, 5
2022-11-03 14:46:29.441150: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 256, 7
2022-11-03 14:46:29.441156: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 288, 5
2022-11-03 14:46:29.441162: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 480, 5
2022-11-03 14:46:29.441168: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 512, 6
2022-11-03 14:46:29.441174: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1028, 1
2022-11-03 14:46:29.441204: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 3168, 5
2022-11-03 14:46:29.441211: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 32768, 6
2022-11-03 14:46:29.441217: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 122880, 3
2022-11-03 14:46:29.441223: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 131072, 3
2022-11-03 14:46:29.441229: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 584352, 5
2022-11-03 14:46:29.441235: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 823872, 5
2022-11-03 14:46:29.441241: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 4324736, 5
2022-11-03 14:46:29.441246: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 7426048, 5
2022-11-03 14:46:29.441252: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 15401440, 5
2022-11-03 14:46:29.441258: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 18678720, 5
2022-11-03 14:46:29.441264: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 39970560, 5
2022-11-03 14:46:29.441270: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 56589504, 5
2022-11-03 14:46:29.441276: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 135407776, 5
2022-11-03 14:46:29.441281: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1083564064, 4
2022-11-03 14:46:29.441308: W tensorflow/core/framework/op_kernel.cc:1733] RESOURCE_EXHAUSTED: failed to allocate memory
Error in atexit._run_exitfuncs:
Traceback (most recent call last):
File "/usr/lib/python3.8/logging/init.py", line 2127, in shutdown
h.close()
File "/usr/local/lib/python3.8/dist-packages/absl/logging/init.py", line 934, in close
self.stream.close()
File "/usr/local/lib/python3.8/dist-packages/ipykernel/iostream.py", line 438, in close
self.watch_fd_thread.join()
AttributeError: 'OutStream' object has no attribute 'watch_fd_thread'
=============================== warnings summary ===============================
../../../../../usr/lib/python3/dist-packages/requests/init.py:89
/usr/lib/python3/dist-packages/requests/init.py:89: RequestsDependencyWarning: urllib3 (1.26.12) or chardet (3.0.4) doesn't match a supported version!
warnings.warn("urllib3 ({}) or chardet ({}) doesn't match a supported "

../../../.local/lib/python3.8/site-packages/flatbuffers/compat.py:19
/var/jenkins_home/.local/lib/python3.8/site-packages/flatbuffers/compat.py:19: DeprecationWarning: the imp module is deprecated in favour of importlib; see the module's documentation for alternative uses
import imp

../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36
/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36: DeprecationWarning: NEAREST is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.NEAREST or Dither.NONE instead.
'nearest': pil_image.NEAREST,

../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37
/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37: DeprecationWarning: BILINEAR is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BILINEAR instead.
'bilinear': pil_image.BILINEAR,

../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38
/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38: DeprecationWarning: BICUBIC is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BICUBIC instead.
'bicubic': pil_image.BICUBIC,

../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39
/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39: DeprecationWarning: HAMMING is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.HAMMING instead.
'hamming': pil_image.HAMMING,

../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40
/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40: DeprecationWarning: BOX is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BOX instead.
'box': pil_image.BOX,

../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41
/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41: DeprecationWarning: LANCZOS is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.LANCZOS instead.
'lanczos': pil_image.LANCZOS,

tests/unit/datasets/test_advertising.py: 1 warning
tests/unit/datasets/test_ecommerce.py: 2 warnings
tests/unit/datasets/test_entertainment.py: 4 warnings
tests/unit/datasets/test_social.py: 1 warning
tests/unit/datasets/test_synthetic.py: 6 warnings
tests/unit/implicit/test_implicit.py: 1 warning
tests/unit/lightfm/test_lightfm.py: 1 warning
tests/unit/tf/test_core.py: 6 warnings
tests/unit/tf/test_loader.py: 1 warning
tests/unit/tf/blocks/test_cross.py: 5 warnings
tests/unit/tf/blocks/test_dlrm.py: 9 warnings
tests/unit/tf/blocks/test_interactions.py: 2 warnings
tests/unit/tf/blocks/test_mlp.py: 26 warnings
tests/unit/tf/blocks/test_optimizer.py: 30 warnings
tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings
tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings
tests/unit/tf/core/test_aggregation.py: 6 warnings
tests/unit/tf/core/test_base.py: 2 warnings
tests/unit/tf/core/test_combinators.py: 11 warnings
tests/unit/tf/core/test_encoder.py: 6 warnings
tests/unit/tf/core/test_index.py: 8 warnings
tests/unit/tf/core/test_prediction.py: 2 warnings
tests/unit/tf/inputs/test_continuous.py: 7 warnings
tests/unit/tf/inputs/test_embedding.py: 20 warnings
tests/unit/tf/inputs/test_tabular.py: 18 warnings
tests/unit/tf/models/test_base.py: 27 warnings
tests/unit/tf/models/test_benchmark.py: 2 warnings
tests/unit/tf/models/test_ranking.py: 38 warnings
tests/unit/tf/models/test_retrieval.py: 119 warnings
tests/unit/tf/outputs/test_base.py: 6 warnings
tests/unit/tf/outputs/test_classification.py: 6 warnings
tests/unit/tf/outputs/test_contrastive.py: 19 warnings
tests/unit/tf/outputs/test_regression.py: 2 warnings
tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings
tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings
tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings
tests/unit/tf/prediction_tasks/test_retrieval.py: 1 warning
tests/unit/tf/transformers/test_block.py: 15 warnings
tests/unit/tf/transforms/test_bias.py: 2 warnings
tests/unit/tf/transforms/test_features.py: 10 warnings
tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings
tests/unit/tf/transforms/test_noise.py: 1 warning
tests/unit/tf/transforms/test_sequence.py: 15 warnings
tests/unit/tf/utils/test_batch.py: 9 warnings
tests/unit/tf/utils/test_dataset.py: 2 warnings
tests/unit/torch/block/test_base.py: 4 warnings
tests/unit/torch/block/test_mlp.py: 1 warning
tests/unit/torch/features/test_continuous.py: 1 warning
tests/unit/torch/features/test_embedding.py: 4 warnings
tests/unit/torch/features/test_tabular.py: 4 warnings
tests/unit/torch/model/test_head.py: 12 warnings
tests/unit/torch/model/test_model.py: 2 warnings
tests/unit/torch/tabular/test_aggregation.py: 6 warnings
tests/unit/torch/tabular/test_transformations.py: 3 warnings
tests/unit/xgb/test_xgboost.py: 18 warnings
/var/jenkins_home/workspace/merlin_models/models/.tox/test-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.ITEM_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.ITEM: 'item'>, <Tags.ID: 'id'>].
warnings.warn(

tests/unit/datasets/test_ecommerce.py: 2 warnings
tests/unit/datasets/test_entertainment.py: 4 warnings
tests/unit/datasets/test_social.py: 1 warning
tests/unit/datasets/test_synthetic.py: 5 warnings
tests/unit/implicit/test_implicit.py: 1 warning
tests/unit/lightfm/test_lightfm.py: 1 warning
tests/unit/tf/test_core.py: 6 warnings
tests/unit/tf/test_loader.py: 1 warning
tests/unit/tf/blocks/test_cross.py: 5 warnings
tests/unit/tf/blocks/test_dlrm.py: 9 warnings
tests/unit/tf/blocks/test_interactions.py: 2 warnings
tests/unit/tf/blocks/test_mlp.py: 26 warnings
tests/unit/tf/blocks/test_optimizer.py: 30 warnings
tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings
tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings
tests/unit/tf/core/test_aggregation.py: 6 warnings
tests/unit/tf/core/test_base.py: 2 warnings
tests/unit/tf/core/test_combinators.py: 11 warnings
tests/unit/tf/core/test_encoder.py: 7 warnings
tests/unit/tf/core/test_index.py: 3 warnings
tests/unit/tf/core/test_prediction.py: 2 warnings
tests/unit/tf/inputs/test_continuous.py: 7 warnings
tests/unit/tf/inputs/test_embedding.py: 20 warnings
tests/unit/tf/inputs/test_tabular.py: 18 warnings
tests/unit/tf/models/test_base.py: 27 warnings
tests/unit/tf/models/test_benchmark.py: 2 warnings
tests/unit/tf/models/test_ranking.py: 36 warnings
tests/unit/tf/models/test_retrieval.py: 85 warnings
tests/unit/tf/outputs/test_base.py: 6 warnings
tests/unit/tf/outputs/test_classification.py: 6 warnings
tests/unit/tf/outputs/test_contrastive.py: 19 warnings
tests/unit/tf/outputs/test_regression.py: 2 warnings
tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings
tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings
tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings
tests/unit/tf/transformers/test_block.py: 9 warnings
tests/unit/tf/transforms/test_features.py: 10 warnings
tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings
tests/unit/tf/transforms/test_sequence.py: 15 warnings
tests/unit/tf/utils/test_batch.py: 7 warnings
tests/unit/tf/utils/test_dataset.py: 2 warnings
tests/unit/torch/block/test_base.py: 4 warnings
tests/unit/torch/block/test_mlp.py: 1 warning
tests/unit/torch/features/test_continuous.py: 1 warning
tests/unit/torch/features/test_embedding.py: 4 warnings
tests/unit/torch/features/test_tabular.py: 4 warnings
tests/unit/torch/model/test_head.py: 12 warnings
tests/unit/torch/model/test_model.py: 2 warnings
tests/unit/torch/tabular/test_aggregation.py: 6 warnings
tests/unit/torch/tabular/test_transformations.py: 2 warnings
tests/unit/xgb/test_xgboost.py: 17 warnings
/var/jenkins_home/workspace/merlin_models/models/.tox/test-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.USER_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.USER: 'user'>, <Tags.ID: 'id'>].
warnings.warn(

tests/unit/datasets/test_entertainment.py: 1 warning
tests/unit/implicit/test_implicit.py: 1 warning
tests/unit/lightfm/test_lightfm.py: 1 warning
tests/unit/tf/test_loader.py: 1 warning
tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings
tests/unit/tf/blocks/retrieval/test_two_tower.py: 2 warnings
tests/unit/tf/core/test_combinators.py: 11 warnings
tests/unit/tf/core/test_encoder.py: 2 warnings
tests/unit/tf/core/test_prediction.py: 1 warning
tests/unit/tf/inputs/test_continuous.py: 4 warnings
tests/unit/tf/inputs/test_embedding.py: 9 warnings
tests/unit/tf/inputs/test_tabular.py: 8 warnings
tests/unit/tf/models/test_ranking.py: 20 warnings
tests/unit/tf/models/test_retrieval.py: 10 warnings
tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings
tests/unit/tf/prediction_tasks/test_regression.py: 3 warnings
tests/unit/tf/transforms/test_negative_sampling.py: 9 warnings
tests/unit/xgb/test_xgboost.py: 12 warnings
/var/jenkins_home/workspace/merlin_models/models/.tox/test-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.SESSION_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.SESSION: 'session'>, <Tags.ID: 'id'>].
warnings.warn(

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export
tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export
tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export
tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export
tests/unit/tf/inputs/test_embedding.py::test_embedding_features_exporting_and_loading_pretrained_initializer
/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/inputs/embedding.py:968: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack
embeddings_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(embeddings)))

tests/unit/tf/blocks/retrieval/test_two_tower.py: 1 warning
tests/unit/tf/core/test_index.py: 4 warnings
tests/unit/tf/models/test_retrieval.py: 54 warnings
tests/unit/tf/prediction_tasks/test_next_item.py: 3 warnings
tests/unit/tf/utils/test_batch.py: 2 warnings
/tmp/autograph_generated_filendsyg1pb.py:8: DeprecationWarning: The 'warn' method is deprecated, use 'warning' instead
ag
.converted_call(ag__.ld(warnings).warn, ("The 'warn' method is deprecated, use 'warning' instead", ag__.ld(DeprecationWarning), 2), None, fscope)

tests/unit/tf/core/test_combinators.py::test_parallel_block_select_by_tags
/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/core/tabular.py:602: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated since Python 3.3, and in 3.10 it will stop working
elif isinstance(self.feature_names, collections.Sequence):

tests/unit/tf/core/test_encoder.py: 1 warning
tests/unit/tf/core/test_index.py: 5 warnings
tests/unit/tf/models/test_retrieval.py: 30 warnings
tests/unit/tf/utils/test_batch.py: 4 warnings
tests/unit/tf/utils/test_dataset.py: 1 warning
/var/jenkins_home/workspace/merlin_models/models/merlin/models/utils/dataset.py:75: DeprecationWarning: unique_rows_by_features is deprecated and will be removed in a future version. Please use unique_by_tag instead.
warnings.warn(

tests/unit/tf/models/test_base.py::test_model_pre_post[True]
tests/unit/tf/models/test_base.py::test_model_pre_post[False]
tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.1]
tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.3]
tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.5]
tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.7]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/util/dispatch.py:1082: UserWarning: tf.keras.backend.random_binomial is deprecated, and will be removed in a future version.Please use tf.keras.backend.random_bernoulli instead.
return dispatch_target(*args, **kwargs)

tests/unit/tf/models/test_base.py::test_freeze_parallel_block[True]
tests/unit/tf/models/test_base.py::test_freeze_sequential_block
tests/unit/tf/models/test_base.py::test_freeze_unfreeze
tests/unit/tf/models/test_base.py::test_unfreeze_all_blocks
/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/gradient_descent.py:108: UserWarning: The lr argument is deprecated, use learning_rate instead.
super(SGD, self).init(name, **kwargs)

tests/unit/tf/models/test_base.py::test_retrieval_model_query
tests/unit/tf/models/test_base.py::test_retrieval_model_query
tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_v2_export_embeddings
tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[True]
tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[False]
/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/utils/tf_utils.py:298: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack
tensor_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(tensor)))

tests/unit/tf/models/test_ranking.py::test_deepfm_model_only_categ_feats[False]
tests/unit/tf/models/test_ranking.py::test_deepfm_model_categ_and_continuous_feats[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/models/test_ranking.py::test_wide_deep_model[False]
tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_categorical_one_hot[False]
tests/unit/tf/models/test_ranking.py::test_wide_deep_model_hashed_cross[False]
tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[True]
tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]
/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/transforms/features.py:569: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag
warnings.warn(

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/autograph/impl/api.py:371: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag
return py_builtins.overload_of(f)(*args)

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_onehot_multihot_feature_interaction[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_feature_interaction_multi_optimizer[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask/GatherV2:0", shape=(None, 48), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_3:0", shape=(None,), dtype=int64), values=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_2:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/torch/block/test_mlp.py::test_mlp_block
/var/jenkins_home/workspace/merlin_models/models/tests/unit/torch/_conftest.py:151: UserWarning: Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at ../torch/csrc/utils/tensor_new.cpp:201.)
return {key: torch.tensor(value) for key, value in data.items()}

tests/unit/xgb/test_xgboost.py::test_without_dask_client
tests/unit/xgb/test_xgboost.py::TestXGBoost::test_music_regression
tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs0-DaskDeviceQuantileDMatrix]
tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs1-DaskDMatrix]
tests/unit/xgb/test_xgboost.py::TestEvals::test_multiple
tests/unit/xgb/test_xgboost.py::TestEvals::test_default
tests/unit/xgb/test_xgboost.py::TestEvals::test_train_and_valid
tests/unit/xgb/test_xgboost.py::TestEvals::test_invalid_data
/var/jenkins_home/workspace/merlin_models/models/merlin/models/xgb/init.py:344: UserWarning: Ignoring list columns as inputs to XGBoost model: ['item_genres', 'user_genres'].
warnings.warn(f"Ignoring list columns as inputs to XGBoost model: {list_column_names}.")

tests/unit/xgb/test_xgboost.py::TestXGBoost::test_unsupported_objective
/var/jenkins_home/workspace/merlin_models/models/.tox/test-gpu/lib/python3.8/site-packages/tornado/ioloop.py:350: DeprecationWarning: make_current is deprecated; start the event loop first
self.make_current()

tests/unit/xgb/test_xgboost.py: 14 warnings
/usr/local/lib/python3.8/dist-packages/xgboost/dask.py:884: RuntimeWarning: coroutine 'Client._wait_for_workers' was never awaited
client.wait_for_workers(n_workers)
Enable tracemalloc to get traceback where the object was allocated.
See https://docs.pytest.org/en/stable/how-to/capture-warnings.html#resource-warnings for more info.

tests/unit/xgb/test_xgboost.py: 11 warnings
/usr/local/lib/python3.8/dist-packages/cudf/core/dataframe.py:1183: DeprecationWarning: The default dtype for empty Series will be 'object' instead of 'float64' in a future version. Specify a dtype explicitly to silence this warning.
mask = pd.Series(mask)

-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html

---------- coverage: platform linux, python 3.8.10-final-0 -----------
Name Stmts Miss Cover

merlin/datasets/init.py 2 0 100%
merlin/datasets/advertising/init.py 2 0 100%
merlin/datasets/advertising/criteo/init.py 0 0 100%
merlin/datasets/advertising/criteo/dataset.py 79 60 24%
merlin/datasets/advertising/criteo/transformed/init.py 0 0 100%
merlin/datasets/ecommerce/init.py 3 0 100%
merlin/datasets/ecommerce/aliccp/init.py 0 0 100%
merlin/datasets/ecommerce/aliccp/dataset.py 141 87 38%
merlin/datasets/ecommerce/aliccp/raw/init.py 0 0 100%
merlin/datasets/ecommerce/aliccp/transformed/init.py 0 0 100%
merlin/datasets/ecommerce/dressipi/init.py 0 0 100%
merlin/datasets/ecommerce/dressipi/dataset.py 45 37 18%
merlin/datasets/ecommerce/dressipi/preprocessed/init.py 0 0 100%
merlin/datasets/ecommerce/large/init.py 0 0 100%
merlin/datasets/ecommerce/small/init.py 0 0 100%
merlin/datasets/ecommerce/transactions/init.py 0 0 100%
merlin/datasets/entertainment/init.py 2 0 100%
merlin/datasets/entertainment/movielens/1m-raw/init.py 0 0 100%
merlin/datasets/entertainment/movielens/1m-raw/ratings/init.py 0 0 100%
merlin/datasets/entertainment/movielens/1m/init.py 0 0 100%
merlin/datasets/entertainment/movielens/25m/init.py 0 0 100%
merlin/datasets/entertainment/movielens/100k/init.py 0 0 100%
merlin/datasets/entertainment/movielens/init.py 0 0 100%
merlin/datasets/entertainment/movielens/dataset.py 152 122 20%
merlin/datasets/entertainment/music_streaming/init.py 0 0 100%
merlin/datasets/social/init.py 0 0 100%
merlin/datasets/synthetic.py 147 15 90%
merlin/datasets/testing/init.py 0 0 100%
merlin/datasets/testing/sequence_testing/init.py 0 0 100%
merlin/models/init.py 2 0 100%
merlin/models/_version.py 354 205 42%
merlin/models/api.py 14 5 64%
merlin/models/config/init.py 0 0 100%
merlin/models/config/schema.py 62 0 100%
merlin/models/implicit/init.py 27 4 85%
merlin/models/io.py 15 0 100%
merlin/models/lightfm/init.py 23 0 100%
merlin/models/loader/init.py 0 0 100%
merlin/models/loader/backend.py 379 42 89%
merlin/models/loader/dataframe_iter.py 21 17 19%
merlin/models/loader/tf_utils.py 57 27 53%
merlin/models/loader/utils.py 40 15 62%
merlin/models/tf/init.py 70 0 100%
merlin/models/tf/blocks/init.py 0 0 100%
merlin/models/tf/blocks/cross.py 44 0 100%
merlin/models/tf/blocks/dlrm.py 49 2 96%
merlin/models/tf/blocks/experts.py 99 17 83%
merlin/models/tf/blocks/interaction.py 108 40 63%
merlin/models/tf/blocks/mlp.py 114 10 91%
merlin/models/tf/blocks/optimizer.py 173 13 92%
merlin/models/tf/blocks/retrieval/init.py 0 0 100%
merlin/models/tf/blocks/retrieval/base.py 169 62 63%
merlin/models/tf/blocks/retrieval/matrix_factorization.py 35 1 97%
merlin/models/tf/blocks/retrieval/two_tower.py 30 0 100%
merlin/models/tf/blocks/sampling/init.py 0 0 100%
merlin/models/tf/blocks/sampling/base.py 29 2 93%
merlin/models/tf/blocks/sampling/cross_batch.py 46 2 96%
merlin/models/tf/blocks/sampling/in_batch.py 35 0 100%
merlin/models/tf/blocks/sampling/queue.py 115 12 90%
merlin/models/tf/core/init.py 0 0 100%
merlin/models/tf/core/aggregation.py 241 49 80%
merlin/models/tf/core/base.py 244 55 77%
merlin/models/tf/core/combinators.py 426 53 88%
merlin/models/tf/core/encoder.py 170 29 83%
merlin/models/tf/core/index.py 104 16 85%
merlin/models/tf/core/prediction.py 50 1 98%
merlin/models/tf/core/tabular.py 280 29 90%
merlin/models/tf/inputs/init.py 0 0 100%
merlin/models/tf/inputs/base.py 60 10 83%
merlin/models/tf/inputs/continuous.py 39 3 92%
merlin/models/tf/inputs/embedding.py 458 31 93%
merlin/models/tf/loader.py 245 73 70%
merlin/models/tf/losses/init.py 4 0 100%
merlin/models/tf/losses/base.py 9 0 100%
merlin/models/tf/losses/listwise.py 13 0 100%
merlin/models/tf/losses/pairwise.py 115 1 99%
merlin/models/tf/metrics/init.py 2 0 100%
merlin/models/tf/metrics/evaluation.py 105 48 54%
merlin/models/tf/metrics/topk.py 198 48 76%
merlin/models/tf/models/init.py 0 0 100%
merlin/models/tf/models/base.py 708 77 89%
merlin/models/tf/models/benchmark.py 16 0 100%
merlin/models/tf/models/ranking.py 67 3 96%
merlin/models/tf/models/retrieval.py 78 4 95%
merlin/models/tf/models/utils.py 10 1 90%
merlin/models/tf/outputs/init.py 0 0 100%
merlin/models/tf/outputs/base.py 122 17 86%
merlin/models/tf/outputs/classification.py 91 1 99%
merlin/models/tf/outputs/contrastive.py 147 10 93%
merlin/models/tf/outputs/regression.py 9 0 100%
merlin/models/tf/outputs/sampling/init.py 0 0 100%
merlin/models/tf/outputs/sampling/base.py 78 21 73%
merlin/models/tf/outputs/sampling/in_batch.py 37 1 97%
merlin/models/tf/outputs/sampling/popularity.py 27 1 96%
merlin/models/tf/outputs/topk.py 97 6 94%
merlin/models/tf/prediction_tasks/init.py 0 0 100%
merlin/models/tf/prediction_tasks/base.py 207 37 82%
merlin/models/tf/prediction_tasks/classification.py 68 17 75%
merlin/models/tf/prediction_tasks/multi.py 7 0 100%
merlin/models/tf/prediction_tasks/next_item.py 59 6 90%
merlin/models/tf/prediction_tasks/regression.py 35 2 94%
merlin/models/tf/prediction_tasks/retrieval.py 73 3 96%
merlin/models/tf/transformers/init.py 0 0 100%
merlin/models/tf/transformers/block.py 101 2 98%
merlin/models/tf/transformers/transforms.py 63 0 100%
merlin/models/tf/transforms/init.py 0 0 100%
merlin/models/tf/transforms/bias.py 111 9 92%
merlin/models/tf/transforms/features.py 435 36 92%
merlin/models/tf/transforms/negative_sampling.py 77 3 96%
merlin/models/tf/transforms/noise.py 43 1 98%
merlin/models/tf/transforms/regularization.py 17 1 94%
merlin/models/tf/transforms/sequence.py 282 42 85%
merlin/models/tf/transforms/tensor.py 158 13 92%
merlin/models/tf/typing.py 7 0 100%
merlin/models/tf/utils/init.py 0 0 100%
merlin/models/tf/utils/batch_utils.py 85 4 95%
merlin/models/tf/utils/repr_utils.py 69 4 94%
merlin/models/tf/utils/search_utils.py 34 22 35%
merlin/models/tf/utils/testing_utils.py 206 36 83%
merlin/models/tf/utils/tf_utils.py 209 42 80%
merlin/models/torch/init.py 12 0 100%
merlin/models/torch/block/init.py 0 0 100%
merlin/models/torch/block/base.py 167 32 81%
merlin/models/torch/block/mlp.py 38 5 87%
merlin/models/torch/dataset.py 68 5 93%
merlin/models/torch/features/init.py 0 0 100%
merlin/models/torch/features/base.py 4 0 100%
merlin/models/torch/features/continuous.py 22 0 100%
merlin/models/torch/features/embedding.py 165 12 93%
merlin/models/torch/features/tabular.py 65 8 88%
merlin/models/torch/losses.py 28 28 0%
merlin/models/torch/model/init.py 0 0 100%
merlin/models/torch/model/base.py 286 65 77%
merlin/models/torch/model/prediction_task.py 24 0 100%
merlin/models/torch/tabular/init.py 0 0 100%
merlin/models/torch/tabular/aggregation.py 75 0 100%
merlin/models/torch/tabular/base.py 247 39 84%
merlin/models/torch/tabular/transformations.py 67 3 96%
merlin/models/torch/typing.py 6 0 100%
merlin/models/torch/utils/init.py 0 0 100%
merlin/models/torch/utils/data_utils.py 117 117 0%
merlin/models/torch/utils/examples_utils.py 39 39 0%
merlin/models/torch/utils/torch_utils.py 80 22 72%
merlin/models/utils/init.py 0 0 100%
merlin/models/utils/constants.py 3 0 100%
merlin/models/utils/dataset.py 38 4 89%
merlin/models/utils/dependencies.py 26 19 27%
merlin/models/utils/doc_utils.py 10 0 100%
merlin/models/utils/example_utils.py 31 2 94%
merlin/models/utils/misc_utils.py 118 90 24%
merlin/models/utils/nvt_utils.py 27 24 11%
merlin/models/utils/registry.py 101 29 71%
merlin/models/utils/schema_utils.py 90 19 79%
merlin/models/xgb/init.py 124 4 97%

TOTAL 11357 2231 80%

=========================== short test summary info ============================
SKIPPED [1] tests/unit/datasets/test_advertising.py:20: No data-dir available, pass it through env variable $INPUT_DATA_DIR
SKIPPED [1] tests/unit/datasets/test_ecommerce.py:62: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP
SKIPPED [1] tests/unit/datasets/test_ecommerce.py:78: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP
SKIPPED [1] tests/unit/datasets/test_ecommerce.py:92: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP
SKIPPED [3] tests/unit/datasets/test_entertainment.py:44: No data-dir available, pass it through env variable $INPUT_DATA_DIR
SKIPPED [5] ../../../.local/lib/python3.8/site-packages/tensorflow/python/framework/test_util.py:2746: Not a test.
==== 1 failed, 823 passed, 12 skipped, 1349 warnings in 1595.70s (0:26:35) =====
ERROR: InvocationError for command /var/jenkins_home/workspace/merlin_models/models/.tox/test-gpu/bin/python -m pytest --cov-report term --cov merlin -rxs tests/unit (exited with code 1)
___________________________________ summary ____________________________________
ERROR: test-gpu: commands failed
Build step 'Execute shell' marked build as failure
Performing Post build task...
Match found for : : True
Logical operation result is TRUE
Running script : #!/bin/bash
cd /var/jenkins_home/
CUDA_VISIBLE_DEVICES=1 python test_res_push.py "https://api.GitHub.com/repos/NVIDIA-Merlin/models/issues/$ghprbPullId/comments" "/var/jenkins_home/jobs/$JOB_NAME/builds/$BUILD_NUMBER/log"
[merlin_models] $ /bin/bash /tmp/jenkins18076652252436589317.sh

@nvidia-merlin-bot
Copy link

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GitHub pull request #855 of commit cd44886a68e840e63689fbac5fd5ebc68856e4d7, no merge conflicts.
Running as SYSTEM
Setting status of cd44886a68e840e63689fbac5fd5ebc68856e4d7 to PENDING with url https://10.20.13.93:8080/job/merlin_models/1725/console and message: 'Pending'
Using context: Jenkins
Building on master in workspace /var/jenkins_home/workspace/merlin_models
using credential nvidia-merlin-bot
 > git rev-parse --is-inside-work-tree # timeout=10
Fetching changes from the remote Git repository
 > git config remote.origin.url https://github.com/NVIDIA-Merlin/models/ # timeout=10
Fetching upstream changes from https://github.com/NVIDIA-Merlin/models/
 > git --version # timeout=10
using GIT_ASKPASS to set credentials This is the bot credentials for our CI/CD
 > git fetch --tags --force --progress -- https://github.com/NVIDIA-Merlin/models/ +refs/pull/855/*:refs/remotes/origin/pr/855/* # timeout=10
 > git rev-parse cd44886a68e840e63689fbac5fd5ebc68856e4d7^{commit} # timeout=10
Checking out Revision cd44886a68e840e63689fbac5fd5ebc68856e4d7 (detached)
 > git config core.sparsecheckout # timeout=10
 > git checkout -f cd44886a68e840e63689fbac5fd5ebc68856e4d7 # timeout=10
Commit message: "correct spelling"
 > git rev-list --no-walk 33888c1ada8c9a55bcb15e18ff6d48da525373d4 # timeout=10
[merlin_models] $ /bin/bash /tmp/jenkins15116240229788058407.sh
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Requirement already satisfied: testbook in /usr/local/lib/python3.8/dist-packages (0.4.2)
Requirement already satisfied: nbclient>=0.4.0 in /usr/local/lib/python3.8/dist-packages (from testbook) (0.6.8)
Requirement already satisfied: nbformat>=5.0.4 in /usr/local/lib/python3.8/dist-packages (from testbook) (5.5.0)
Requirement already satisfied: jupyter-client>=6.1.5 in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (7.3.5)
Requirement already satisfied: traitlets>=5.2.2 in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (5.4.0)
Requirement already satisfied: nest-asyncio in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (1.5.5)
Requirement already satisfied: fastjsonschema in /usr/local/lib/python3.8/dist-packages (from nbformat>=5.0.4->testbook) (2.16.1)
Requirement already satisfied: jsonschema>=2.6 in /usr/local/lib/python3.8/dist-packages (from nbformat>=5.0.4->testbook) (4.16.0)
Requirement already satisfied: jupyter_core in /usr/local/lib/python3.8/dist-packages (from nbformat>=5.0.4->testbook) (4.11.1)
Requirement already satisfied: pkgutil-resolve-name>=1.3.10 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (1.3.10)
Requirement already satisfied: importlib-resources>=1.4.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (5.9.0)
Requirement already satisfied: pyrsistent!=0.17.0,!=0.17.1,!=0.17.2,>=0.14.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (0.18.1)
Requirement already satisfied: attrs>=17.4.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (22.1.0)
Requirement already satisfied: entrypoints in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (0.4)
Requirement already satisfied: tornado>=6.2 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (6.2)
Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (2.8.2)
Requirement already satisfied: pyzmq>=23.0 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (24.0.0)
Requirement already satisfied: zipp>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from importlib-resources>=1.4.0->jsonschema>=2.6->nbformat>=5.0.4->testbook) (3.8.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.8.2->jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (1.15.0)
GLOB sdist-make: /var/jenkins_home/workspace/merlin_models/models/setup.py
test-gpu inst-nodeps: /var/jenkins_home/workspace/merlin_models/models/.tox/.tmp/package/2/merlin-models-0.9.0+28.gcd44886a.zip
WARNING: Discarding $PYTHONPATH from environment, to override specify PYTHONPATH in 'passenv' in your configuration.
test-gpu installed: absl-py==1.2.0,aiohttp==3.8.1,aiosignal==1.2.0,alabaster==0.7.12,alembic==1.8.1,anyio==3.6.1,appdirs==1.4.4,argon2-cffi==21.3.0,argon2-cffi-bindings==21.2.0,astroid==2.5.6,asttokens==2.0.8,astunparse==1.6.3,asv==0.5.1,asvdb==0.4.2,async-timeout==4.0.2,attrs==22.1.0,autopage==0.5.1,awscli==1.27.1,Babel==2.10.3,backcall==0.2.0,beautifulsoup4==4.11.1,betterproto==1.2.5,black==20.8b1,bleach==5.0.1,boto3==1.24.75,botocore==1.29.1,Brotli==1.0.9,build==0.9.0,cachetools==5.2.0,certifi==2019.11.28,cffi==1.15.1,chardet==3.0.4,charset-normalizer==2.1.1,check-manifest==0.48,clang==5.0,click==8.1.3,cliff==4.0.0,cloudpickle==2.2.0,cmaes==0.8.2,cmake==3.24.1.1,cmd2==2.4.2,colorama==0.4.4,colorlog==6.7.0,contourpy==1.0.5,coverage==6.5.0,cuda-python==11.7.1,cupy-cuda117==10.6.0,cycler==0.11.0,Cython==0.29.32,dask==2022.1.1,dbus-python==1.2.16,debugpy==1.6.3,decorator==5.1.1,defusedxml==0.7.1,dill==0.3.5.1,distlib==0.3.6,distributed==2022.5.1,distro==1.7.0,dm-tree==0.1.6,docker-pycreds==0.4.0,docutils==0.16,emoji==1.7.0,entrypoints==0.4,execnet==1.9.0,executing==1.0.0,faiss==1.7.2,faiss-gpu==1.7.2,fastai==2.7.9,fastapi==0.85.0,fastavro==1.6.1,fastcore==1.5.27,fastdownload==0.0.7,fastjsonschema==2.16.1,fastprogress==1.0.3,fastrlock==0.8,feast==0.19.4,fiddle==0.2.2,filelock==3.8.0,flake8==5.0.4,flatbuffers==1.12,fonttools==4.37.3,frozenlist==1.3.1,fsspec==2022.5.0,gast==0.4.0,gevent==21.12.0,geventhttpclient==2.0.2,gitdb==4.0.9,GitPython==3.1.27,google==3.0.0,google-api-core==2.10.1,google-auth==2.11.1,google-auth-oauthlib==0.4.6,google-pasta==0.2.0,googleapis-common-protos==1.52.0,graphviz==0.20.1,greenlet==1.1.3,grpcio==1.41.0,grpcio-channelz==1.49.0,grpcio-reflection==1.48.1,grpclib==0.4.3,h11==0.13.0,h2==4.1.0,h5py==3.7.0,HeapDict==1.0.1,horovod==0.26.1,hpack==4.0.0,httptools==0.5.0,hugectr2onnx==0.0.0,huggingface-hub==0.9.1,hyperframe==6.0.1,idna==2.8,imagesize==1.4.1,implicit==0.6.1,importlib-metadata==4.12.0,importlib-resources==5.9.0,iniconfig==1.1.1,interrogate==1.5.0,ipykernel==6.15.3,ipython==8.5.0,ipython-genutils==0.2.0,ipywidgets==7.7.0,isort==5.10.1,jedi==0.18.1,Jinja2==3.1.2,jmespath==1.0.1,joblib==1.2.0,json5==0.9.10,jsonschema==4.16.0,jupyter==1.0.0,jupyter-cache==0.4.3,jupyter-console==6.4.4,jupyter-core==4.11.1,jupyter-server==1.18.1,jupyter-server-mathjax==0.2.5,jupyter-sphinx==0.3.2,jupyter_client==7.3.5,jupyterlab==3.4.7,jupyterlab-pygments==0.2.2,jupyterlab-widgets==1.1.0,jupyterlab_server==2.15.1,keras==2.9.0,Keras-Preprocessing==1.1.2,kiwisolver==1.4.4,lazy-object-proxy==1.8.0,libclang==14.0.6,libcst==0.4.7,lightfm==1.16,lightgbm==3.3.2,linkify-it-py==1.0.3,llvmlite==0.39.1,locket==1.0.0,lxml==4.9.1,Mako==1.2.3,Markdown==3.4.1,markdown-it-py==1.1.0,MarkupSafe==2.1.1,matplotlib==3.6.0,matplotlib-inline==0.1.6,mccabe==0.7.0,mdit-py-plugins==0.2.8,merlin-core==0.6.0+1.g5926fcf,merlin-dataloader @ git+https://github.com/NVIDIA-Merlin/dataloader.git@5905283777ff5ebd748a1c91b7c9fde5710ae775,merlin-models==0.9.0+28.gcd44886a,merlin-systems==0.5.0+4.g15074ad,mistune==2.0.4,mmh3==3.0.0,mpi4py==3.1.3,msgpack==1.0.4,multidict==6.0.2,mypy==0.982,mypy-extensions==0.4.3,myst-nb==0.13.2,myst-parser==0.15.2,natsort==8.1.0,nbclassic==0.4.3,nbclient==0.6.8,nbconvert==7.0.0,nbdime==3.1.1,nbformat==5.5.0,nest-asyncio==1.5.5,ninja==1.10.2.3,notebook==6.4.12,notebook-shim==0.1.0,numba==0.56.2,numpy==1.22.4,nvidia-pyindex==1.0.9,# Editable install with no version control (nvtabular==1.4.0+8.g95e12d347),-e /usr/local/lib/python3.8/dist-packages,nvtx==0.2.5,oauthlib==3.2.1,oldest-supported-numpy==2022.8.16,onnx==1.12.0,onnxruntime==1.11.1,opt-einsum==3.3.0,optuna==3.0.3,packaging==21.3,pandas==1.3.5,pandavro==1.5.2,pandocfilters==1.5.0,parso==0.8.3,partd==1.3.0,pathspec==0.10.1,pathtools==0.1.2,pbr==5.11.0,pep517==0.13.0,pexpect==4.8.0,pickleshare==0.7.5,Pillow==9.2.0,pkgutil_resolve_name==1.3.10,platformdirs==2.5.2,plotly==5.11.0,pluggy==1.0.0,prettytable==3.5.0,prometheus-client==0.14.1,promise==2.3,prompt-toolkit==3.0.31,proto-plus==1.19.6,protobuf==3.19.5,psutil==5.9.2,ptyprocess==0.7.0,pure-eval==0.2.2,py==1.11.0,pyarrow==7.0.0,pyasn1==0.4.8,pyasn1-modules==0.2.8,pybind11==2.10.0,pycodestyle==2.9.1,pycparser==2.21,pydantic==1.10.2,pydot==1.4.2,pyflakes==2.5.0,Pygments==2.13.0,PyGObject==3.36.0,pynvml==11.4.1,pyparsing==3.0.9,pyperclip==1.8.2,pyrsistent==0.18.1,pytest==7.1.3,pytest-cov==4.0.0,pytest-xdist==3.0.2,python-apt==2.0.0+ubuntu0.20.4.8,python-dateutil==2.8.2,python-dotenv==0.21.0,python-rapidjson==1.8,pytz==2022.2.1,PyYAML==5.4.1,pyzmq==24.0.0,qtconsole==5.3.2,QtPy==2.2.1,regex==2022.9.13,requests==2.22.0,requests-oauthlib==1.3.1,requests-unixsocket==0.2.0,rsa==4.7.2,s3fs==2022.2.0,s3transfer==0.6.0,sacremoses==0.0.53,scikit-build==0.15.0,scikit-learn==1.1.2,scipy==1.8.1,seedir==0.3.0,Send2Trash==1.8.0,sentry-sdk==1.9.8,setproctitle==1.3.2,setuptools-scm==7.0.5,shortuuid==1.0.9,six==1.15.0,sklearn==0.0,smmap==5.0.0,sniffio==1.3.0,snowballstemmer==2.2.0,sortedcontainers==2.4.0,soupsieve==2.3.2.post1,Sphinx==5.3.0,sphinx-multiversion==0.2.4,sphinx-togglebutton==0.3.1,sphinx_external_toc==0.3.0,sphinxcontrib-applehelp==1.0.2,sphinxcontrib-copydirs @ git+https://github.com/mikemckiernan/sphinxcontrib-copydirs.git@bd8c5d79b3f91cf5f1bb0d6995aeca3fe84b670e,sphinxcontrib-devhelp==1.0.2,sphinxcontrib-htmlhelp==2.0.0,sphinxcontrib-jsmath==1.0.1,sphinxcontrib-qthelp==1.0.3,sphinxcontrib-serializinghtml==1.1.5,SQLAlchemy==1.4.42,stack-data==0.5.0,starlette==0.20.4,stevedore==4.1.0,stringcase==1.2.0,supervisor==4.1.0,tabulate==0.8.10,tblib==1.7.0,tdqm==0.0.1,tenacity==8.0.1,tensorboard==2.9.1,tensorboard-data-server==0.6.1,tensorboard-plugin-wit==1.8.1,tensorflow==2.9.2,tensorflow-estimator==2.9.0,tensorflow-gpu==2.9.2,tensorflow-io-gcs-filesystem==0.27.0,tensorflow-metadata==1.10.0,tensorflow-ranking==0.5.1,tensorflow-serving-api==2.9.2,termcolor==2.0.1,terminado==0.15.0,testbook==0.4.2,threadpoolctl==3.1.0,tinycss2==1.1.1,tokenizers==0.10.3,toml==0.10.2,tomli==2.0.1,toolz==0.12.0,torch==1.12.1+cu113,torchmetrics==0.3.2,tornado==6.2,tox==3.26.0,tqdm==4.64.1,traitlets==5.4.0,transformers==4.12.0,transformers4rec==0.1.12+2.gbcc939255,treelite==2.3.0,treelite-runtime==2.3.0,tritonclient==2.25.0,typed-ast==1.5.4,typing-inspect==0.8.0,typing_extensions==4.3.0,uc-micro-py==1.0.1,urllib3==1.26.12,uvicorn==0.18.3,uvloop==0.17.0,versioneer==0.20,virtualenv==20.16.5,wandb==0.13.3,watchfiles==0.17.0,wcwidth==0.2.5,webencodings==0.5.1,websocket-client==1.4.1,websockets==10.3,Werkzeug==2.2.2,widgetsnbextension==3.6.0,wrapt==1.12.1,xgboost==1.6.2,yarl==1.8.1,zict==2.2.0,zipp==3.8.1,zope.event==4.5.0,zope.interface==5.4.0
test-gpu run-test-pre: PYTHONHASHSEED='3822105887'
test-gpu run-test: commands[0] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/core.git
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Collecting git+https://github.com/NVIDIA-Merlin/core.git
  Cloning https://github.com/NVIDIA-Merlin/core.git to /tmp/pip-req-build-hhbxtd_9
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/core.git /tmp/pip-req-build-hhbxtd_9
  Resolved https://github.com/NVIDIA-Merlin/core.git to commit 563be4bf5ef675940d5fff2b5e4666424a7f7947
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: packaging in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+5.g563be4b) (21.3)
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[notice] A new release of pip available: 22.2.2 -> 22.3
[notice] To update, run: pip install --upgrade pip
test-gpu run-test: commands[1] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/nvtabular.git
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Collecting git+https://github.com/NVIDIA-Merlin/nvtabular.git
Cloning https://github.com/NVIDIA-Merlin/nvtabular.git to /tmp/pip-req-build-mlgel1e0
Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/nvtabular.git /tmp/pip-req-build-mlgel1e0
Resolved https://github.com/NVIDIA-Merlin/nvtabular.git to commit 8e7edbafd3006f56e73efdc0c01c4445ab57d028
Installing build dependencies: started
Installing build dependencies: finished with status 'done'
Getting requirements to build wheel: started
Getting requirements to build wheel: finished with status 'done'
Preparing metadata (pyproject.toml): started
Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: merlin-dataloader>=0.0.2 in ./.tox/test-gpu/lib/python3.8/site-packages (from nvtabular==1.6.0+3.g8e7edbaf) (0.0.2+1.g5905283)
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Requirement already satisfied: hpack<5,>=4.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core>=0.2.0->nvtabular==1.6.0+3.g8e7edbaf) (4.0.0)

[notice] A new release of pip available: 22.2.2 -> 22.3
[notice] To update, run: pip install --upgrade pip
test-gpu run-test: commands[2] | python -m pytest --cov-report term --cov merlin -rxs tests/unit
============================= test session starts ==============================
platform linux -- Python 3.8.10, pytest-7.1.3, pluggy-1.0.0
cachedir: .tox/test-gpu/.pytest_cache
rootdir: /var/jenkins_home/workspace/merlin_models/models, configfile: pyproject.toml
plugins: anyio-3.5.0, xdist-3.0.2, cov-4.0.0
collected 836 items

tests/unit/config/test_schema.py .... [ 0%]
tests/unit/datasets/test_advertising.py .s [ 0%]
tests/unit/datasets/test_ecommerce.py ..sss [ 1%]
tests/unit/datasets/test_entertainment.py ....sss. [ 2%]
tests/unit/datasets/test_social.py . [ 2%]
tests/unit/datasets/test_synthetic.py ...... [ 3%]
tests/unit/implicit/test_implicit.py . [ 3%]
tests/unit/lightfm/test_lightfm.py . [ 3%]
tests/unit/tf/test_core.py ...... [ 4%]
tests/unit/tf/test_loader.py ................ [ 5%]
tests/unit/tf/test_public_api.py . [ 6%]
tests/unit/tf/blocks/test_cross.py ........... [ 7%]
tests/unit/tf/blocks/test_dlrm.py .......... [ 8%]
tests/unit/tf/blocks/test_interactions.py ... [ 8%]
tests/unit/tf/blocks/test_mlp.py ................................. [ 12%]
tests/unit/tf/blocks/test_optimizer.py s................................ [ 16%]
..................... [ 19%]
tests/unit/tf/blocks/retrieval/test_base.py . [ 19%]
tests/unit/tf/blocks/retrieval/test_matrix_factorization.py .. [ 19%]
tests/unit/tf/blocks/retrieval/test_two_tower.py ............ [ 21%]
tests/unit/tf/blocks/sampling/test_cross_batch.py . [ 21%]
tests/unit/tf/blocks/sampling/test_in_batch.py . [ 21%]
tests/unit/tf/core/test_aggregation.py ......... [ 22%]
tests/unit/tf/core/test_base.py .. [ 22%]
tests/unit/tf/core/test_combinators.py s..................... [ 25%]
tests/unit/tf/core/test_encoder.py .. [ 25%]
tests/unit/tf/core/test_index.py ... [ 25%]
tests/unit/tf/core/test_prediction.py .. [ 26%]
tests/unit/tf/core/test_tabular.py ...... [ 26%]
tests/unit/tf/examples/test_01_getting_started.py . [ 27%]
tests/unit/tf/examples/test_02_dataschema.py . [ 27%]
tests/unit/tf/examples/test_03_exploring_different_models.py . [ 27%]
tests/unit/tf/examples/test_04_export_ranking_models.py . [ 27%]
tests/unit/tf/examples/test_05_export_retrieval_model.py . [ 27%]
tests/unit/tf/examples/test_06_advanced_own_architecture.py . [ 27%]
tests/unit/tf/examples/test_07_train_traditional_models.py . [ 27%]
tests/unit/tf/examples/test_usecase_accelerate_training_by_lazyadam.py . [ 27%]
[ 27%]
tests/unit/tf/examples/test_usecase_data_parallel.py . [ 27%]
tests/unit/tf/examples/test_usecase_ecommerce_session_based.py . [ 28%]
tests/unit/tf/examples/test_usecase_incremental_training_layer_freezing.py . [ 28%]
[ 28%]
tests/unit/tf/examples/test_usecase_pretrained_embeddings.py . [ 28%]
tests/unit/tf/examples/test_usecase_retrieval_with_hpo.py . [ 28%]
tests/unit/tf/inputs/test_continuous.py ........ [ 29%]
tests/unit/tf/inputs/test_embedding.py ................................. [ 33%]
........ [ 34%]
tests/unit/tf/inputs/test_tabular.py .................. [ 36%]
tests/unit/tf/layers/test_queue.py .............. [ 38%]
tests/unit/tf/losses/test_losses.py ....................... [ 40%]
tests/unit/tf/metrics/test_metrics_popularity.py ..... [ 41%]
tests/unit/tf/metrics/test_metrics_topk.py ......................... [ 44%]
tests/unit/tf/models/test_base.py s........................ [ 47%]
tests/unit/tf/models/test_benchmark.py .. [ 47%]
tests/unit/tf/models/test_ranking.py .................................. [ 51%]
tests/unit/tf/models/test_retrieval.py ................................. [ 55%]
.......................................... [ 60%]
tests/unit/tf/outputs/test_base.py ...... [ 61%]
tests/unit/tf/outputs/test_classification.py ...... [ 62%]
tests/unit/tf/outputs/test_contrastive.py .............. [ 63%]
tests/unit/tf/outputs/test_regression.py .. [ 64%]
tests/unit/tf/outputs/test_sampling.py .... [ 64%]
tests/unit/tf/outputs/test_topk.py . [ 64%]
tests/unit/tf/prediction_tasks/test_classification.py .. [ 64%]
tests/unit/tf/prediction_tasks/test_multi_task.py ................ [ 66%]
tests/unit/tf/prediction_tasks/test_next_item.py ..... [ 67%]
tests/unit/tf/prediction_tasks/test_regression.py ..... [ 68%]
tests/unit/tf/prediction_tasks/test_retrieval.py . [ 68%]
tests/unit/tf/prediction_tasks/test_sampling.py ...... [ 68%]
tests/unit/tf/transformers/test_block.py ..................... [ 71%]
tests/unit/tf/transformers/test_transforms.py .......... [ 72%]
tests/unit/tf/transforms/test_bias.py .. [ 72%]
tests/unit/tf/transforms/test_features.py s............................. [ 76%]
.......................s...... [ 80%]
tests/unit/tf/transforms/test_negative_sampling.py ......... [ 81%]
tests/unit/tf/transforms/test_noise.py ..... [ 81%]
tests/unit/tf/transforms/test_sequence.py .................... [ 84%]
tests/unit/tf/transforms/test_tensor.py ... [ 84%]
tests/unit/tf/utils/test_batch.py .... [ 84%]
tests/unit/tf/utils/test_dataset.py .. [ 85%]
tests/unit/tf/utils/test_tf_utils.py ..... [ 85%]
tests/unit/torch/test_dataset.py ......... [ 86%]
tests/unit/torch/test_public_api.py . [ 86%]
tests/unit/torch/block/test_base.py .... [ 87%]
tests/unit/torch/block/test_mlp.py . [ 87%]
tests/unit/torch/features/test_continuous.py .. [ 87%]
tests/unit/torch/features/test_embedding.py .............. [ 89%]
tests/unit/torch/features/test_tabular.py .... [ 89%]
tests/unit/torch/model/test_head.py ............ [ 91%]
tests/unit/torch/model/test_model.py .. [ 91%]
tests/unit/torch/tabular/test_aggregation.py ........ [ 92%]
tests/unit/torch/tabular/test_tabular.py ... [ 92%]
tests/unit/torch/tabular/test_transformations.py ....... [ 93%]
tests/unit/utils/test_schema_utils.py ................................ [ 97%]
tests/unit/xgb/test_xgboost.py .................... [100%]

=============================== warnings summary ===============================
../../../../../usr/lib/python3/dist-packages/requests/init.py:89
/usr/lib/python3/dist-packages/requests/init.py:89: RequestsDependencyWarning: urllib3 (1.26.12) or chardet (3.0.4) doesn't match a supported version!
warnings.warn("urllib3 ({}) or chardet ({}) doesn't match a supported "

../../../.local/lib/python3.8/site-packages/flatbuffers/compat.py:19
/var/jenkins_home/.local/lib/python3.8/site-packages/flatbuffers/compat.py:19: DeprecationWarning: the imp module is deprecated in favour of importlib; see the module's documentation for alternative uses
import imp

../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36
/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36: DeprecationWarning: NEAREST is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.NEAREST or Dither.NONE instead.
'nearest': pil_image.NEAREST,

../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37
/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37: DeprecationWarning: BILINEAR is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BILINEAR instead.
'bilinear': pil_image.BILINEAR,

../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38
/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38: DeprecationWarning: BICUBIC is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BICUBIC instead.
'bicubic': pil_image.BICUBIC,

../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39
/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39: DeprecationWarning: HAMMING is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.HAMMING instead.
'hamming': pil_image.HAMMING,

../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40
/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40: DeprecationWarning: BOX is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BOX instead.
'box': pil_image.BOX,

../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41
/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41: DeprecationWarning: LANCZOS is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.LANCZOS instead.
'lanczos': pil_image.LANCZOS,

tests/unit/datasets/test_advertising.py: 1 warning
tests/unit/datasets/test_ecommerce.py: 2 warnings
tests/unit/datasets/test_entertainment.py: 4 warnings
tests/unit/datasets/test_social.py: 1 warning
tests/unit/datasets/test_synthetic.py: 6 warnings
tests/unit/implicit/test_implicit.py: 1 warning
tests/unit/lightfm/test_lightfm.py: 1 warning
tests/unit/tf/test_core.py: 6 warnings
tests/unit/tf/test_loader.py: 1 warning
tests/unit/tf/blocks/test_cross.py: 5 warnings
tests/unit/tf/blocks/test_dlrm.py: 9 warnings
tests/unit/tf/blocks/test_interactions.py: 2 warnings
tests/unit/tf/blocks/test_mlp.py: 26 warnings
tests/unit/tf/blocks/test_optimizer.py: 30 warnings
tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings
tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings
tests/unit/tf/core/test_aggregation.py: 6 warnings
tests/unit/tf/core/test_base.py: 2 warnings
tests/unit/tf/core/test_combinators.py: 11 warnings
tests/unit/tf/core/test_encoder.py: 6 warnings
tests/unit/tf/core/test_index.py: 8 warnings
tests/unit/tf/core/test_prediction.py: 2 warnings
tests/unit/tf/inputs/test_continuous.py: 7 warnings
tests/unit/tf/inputs/test_embedding.py: 20 warnings
tests/unit/tf/inputs/test_tabular.py: 18 warnings
tests/unit/tf/models/test_base.py: 27 warnings
tests/unit/tf/models/test_benchmark.py: 2 warnings
tests/unit/tf/models/test_ranking.py: 38 warnings
tests/unit/tf/models/test_retrieval.py: 119 warnings
tests/unit/tf/outputs/test_base.py: 6 warnings
tests/unit/tf/outputs/test_classification.py: 6 warnings
tests/unit/tf/outputs/test_contrastive.py: 19 warnings
tests/unit/tf/outputs/test_regression.py: 2 warnings
tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings
tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings
tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings
tests/unit/tf/prediction_tasks/test_retrieval.py: 1 warning
tests/unit/tf/transformers/test_block.py: 15 warnings
tests/unit/tf/transforms/test_bias.py: 2 warnings
tests/unit/tf/transforms/test_features.py: 10 warnings
tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings
tests/unit/tf/transforms/test_noise.py: 1 warning
tests/unit/tf/transforms/test_sequence.py: 15 warnings
tests/unit/tf/utils/test_batch.py: 9 warnings
tests/unit/tf/utils/test_dataset.py: 2 warnings
tests/unit/torch/block/test_base.py: 4 warnings
tests/unit/torch/block/test_mlp.py: 1 warning
tests/unit/torch/features/test_continuous.py: 1 warning
tests/unit/torch/features/test_embedding.py: 4 warnings
tests/unit/torch/features/test_tabular.py: 4 warnings
tests/unit/torch/model/test_head.py: 12 warnings
tests/unit/torch/model/test_model.py: 2 warnings
tests/unit/torch/tabular/test_aggregation.py: 6 warnings
tests/unit/torch/tabular/test_transformations.py: 3 warnings
tests/unit/xgb/test_xgboost.py: 18 warnings
/var/jenkins_home/workspace/merlin_models/models/.tox/test-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.ITEM_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.ITEM: 'item'>, <Tags.ID: 'id'>].
warnings.warn(

tests/unit/datasets/test_ecommerce.py: 2 warnings
tests/unit/datasets/test_entertainment.py: 4 warnings
tests/unit/datasets/test_social.py: 1 warning
tests/unit/datasets/test_synthetic.py: 5 warnings
tests/unit/implicit/test_implicit.py: 1 warning
tests/unit/lightfm/test_lightfm.py: 1 warning
tests/unit/tf/test_core.py: 6 warnings
tests/unit/tf/test_loader.py: 1 warning
tests/unit/tf/blocks/test_cross.py: 5 warnings
tests/unit/tf/blocks/test_dlrm.py: 9 warnings
tests/unit/tf/blocks/test_interactions.py: 2 warnings
tests/unit/tf/blocks/test_mlp.py: 26 warnings
tests/unit/tf/blocks/test_optimizer.py: 30 warnings
tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings
tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings
tests/unit/tf/core/test_aggregation.py: 6 warnings
tests/unit/tf/core/test_base.py: 2 warnings
tests/unit/tf/core/test_combinators.py: 11 warnings
tests/unit/tf/core/test_encoder.py: 7 warnings
tests/unit/tf/core/test_index.py: 3 warnings
tests/unit/tf/core/test_prediction.py: 2 warnings
tests/unit/tf/inputs/test_continuous.py: 7 warnings
tests/unit/tf/inputs/test_embedding.py: 20 warnings
tests/unit/tf/inputs/test_tabular.py: 18 warnings
tests/unit/tf/models/test_base.py: 27 warnings
tests/unit/tf/models/test_benchmark.py: 2 warnings
tests/unit/tf/models/test_ranking.py: 36 warnings
tests/unit/tf/models/test_retrieval.py: 85 warnings
tests/unit/tf/outputs/test_base.py: 6 warnings
tests/unit/tf/outputs/test_classification.py: 6 warnings
tests/unit/tf/outputs/test_contrastive.py: 19 warnings
tests/unit/tf/outputs/test_regression.py: 2 warnings
tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings
tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings
tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings
tests/unit/tf/transformers/test_block.py: 9 warnings
tests/unit/tf/transforms/test_features.py: 10 warnings
tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings
tests/unit/tf/transforms/test_sequence.py: 15 warnings
tests/unit/tf/utils/test_batch.py: 7 warnings
tests/unit/tf/utils/test_dataset.py: 2 warnings
tests/unit/torch/block/test_base.py: 4 warnings
tests/unit/torch/block/test_mlp.py: 1 warning
tests/unit/torch/features/test_continuous.py: 1 warning
tests/unit/torch/features/test_embedding.py: 4 warnings
tests/unit/torch/features/test_tabular.py: 4 warnings
tests/unit/torch/model/test_head.py: 12 warnings
tests/unit/torch/model/test_model.py: 2 warnings
tests/unit/torch/tabular/test_aggregation.py: 6 warnings
tests/unit/torch/tabular/test_transformations.py: 2 warnings
tests/unit/xgb/test_xgboost.py: 17 warnings
/var/jenkins_home/workspace/merlin_models/models/.tox/test-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.USER_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.USER: 'user'>, <Tags.ID: 'id'>].
warnings.warn(

tests/unit/datasets/test_entertainment.py: 1 warning
tests/unit/implicit/test_implicit.py: 1 warning
tests/unit/lightfm/test_lightfm.py: 1 warning
tests/unit/tf/test_loader.py: 1 warning
tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings
tests/unit/tf/blocks/retrieval/test_two_tower.py: 2 warnings
tests/unit/tf/core/test_combinators.py: 11 warnings
tests/unit/tf/core/test_encoder.py: 2 warnings
tests/unit/tf/core/test_prediction.py: 1 warning
tests/unit/tf/inputs/test_continuous.py: 4 warnings
tests/unit/tf/inputs/test_embedding.py: 9 warnings
tests/unit/tf/inputs/test_tabular.py: 8 warnings
tests/unit/tf/models/test_ranking.py: 20 warnings
tests/unit/tf/models/test_retrieval.py: 10 warnings
tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings
tests/unit/tf/prediction_tasks/test_regression.py: 3 warnings
tests/unit/tf/transforms/test_negative_sampling.py: 9 warnings
tests/unit/xgb/test_xgboost.py: 12 warnings
/var/jenkins_home/workspace/merlin_models/models/.tox/test-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.SESSION_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.SESSION: 'session'>, <Tags.ID: 'id'>].
warnings.warn(

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export
tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export
tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export
tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export
tests/unit/tf/inputs/test_embedding.py::test_embedding_features_exporting_and_loading_pretrained_initializer
/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/inputs/embedding.py:968: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack
embeddings_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(embeddings)))

tests/unit/tf/blocks/retrieval/test_two_tower.py: 1 warning
tests/unit/tf/core/test_index.py: 4 warnings
tests/unit/tf/models/test_retrieval.py: 54 warnings
tests/unit/tf/prediction_tasks/test_next_item.py: 3 warnings
tests/unit/tf/utils/test_batch.py: 2 warnings
/tmp/autograph_generated_file08zs5k0q.py:8: DeprecationWarning: The 'warn' method is deprecated, use 'warning' instead
ag
.converted_call(ag__.ld(warnings).warn, ("The 'warn' method is deprecated, use 'warning' instead", ag__.ld(DeprecationWarning), 2), None, fscope)

tests/unit/tf/core/test_combinators.py::test_parallel_block_select_by_tags
/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/core/tabular.py:602: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated since Python 3.3, and in 3.10 it will stop working
elif isinstance(self.feature_names, collections.Sequence):

tests/unit/tf/core/test_encoder.py: 1 warning
tests/unit/tf/core/test_index.py: 5 warnings
tests/unit/tf/models/test_retrieval.py: 30 warnings
tests/unit/tf/utils/test_batch.py: 4 warnings
tests/unit/tf/utils/test_dataset.py: 1 warning
/var/jenkins_home/workspace/merlin_models/models/merlin/models/utils/dataset.py:75: DeprecationWarning: unique_rows_by_features is deprecated and will be removed in a future version. Please use unique_by_tag instead.
warnings.warn(

tests/unit/tf/models/test_base.py::test_model_pre_post[True]
tests/unit/tf/models/test_base.py::test_model_pre_post[False]
tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.1]
tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.3]
tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.5]
tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.7]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/util/dispatch.py:1082: UserWarning: tf.keras.backend.random_binomial is deprecated, and will be removed in a future version.Please use tf.keras.backend.random_bernoulli instead.
return dispatch_target(*args, **kwargs)

tests/unit/tf/models/test_base.py::test_freeze_parallel_block[True]
tests/unit/tf/models/test_base.py::test_freeze_sequential_block
tests/unit/tf/models/test_base.py::test_freeze_unfreeze
tests/unit/tf/models/test_base.py::test_unfreeze_all_blocks
/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/gradient_descent.py:108: UserWarning: The lr argument is deprecated, use learning_rate instead.
super(SGD, self).init(name, **kwargs)

tests/unit/tf/models/test_base.py::test_retrieval_model_query
tests/unit/tf/models/test_base.py::test_retrieval_model_query
tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_v2_export_embeddings
tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[True]
tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[False]
/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/utils/tf_utils.py:298: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack
tensor_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(tensor)))

tests/unit/tf/models/test_ranking.py::test_deepfm_model_only_categ_feats[False]
tests/unit/tf/models/test_ranking.py::test_deepfm_model_categ_and_continuous_feats[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/models/test_ranking.py::test_wide_deep_model[False]
tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_categorical_one_hot[False]
tests/unit/tf/models/test_ranking.py::test_wide_deep_model_hashed_cross[False]
tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[True]
tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]
/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/transforms/features.py:569: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag
warnings.warn(

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/autograph/impl/api.py:371: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag
return py_builtins.overload_of(f)(*args)

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_onehot_multihot_feature_interaction[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_feature_interaction_multi_optimizer[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask/GatherV2:0", shape=(None, 48), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_3:0", shape=(None,), dtype=int64), values=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_2:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/torch/block/test_mlp.py::test_mlp_block
/var/jenkins_home/workspace/merlin_models/models/tests/unit/torch/_conftest.py:151: UserWarning: Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at ../torch/csrc/utils/tensor_new.cpp:201.)
return {key: torch.tensor(value) for key, value in data.items()}

tests/unit/xgb/test_xgboost.py::test_without_dask_client
tests/unit/xgb/test_xgboost.py::TestXGBoost::test_music_regression
tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs0-DaskDeviceQuantileDMatrix]
tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs1-DaskDMatrix]
tests/unit/xgb/test_xgboost.py::TestEvals::test_multiple
tests/unit/xgb/test_xgboost.py::TestEvals::test_default
tests/unit/xgb/test_xgboost.py::TestEvals::test_train_and_valid
tests/unit/xgb/test_xgboost.py::TestEvals::test_invalid_data
/var/jenkins_home/workspace/merlin_models/models/merlin/models/xgb/init.py:344: UserWarning: Ignoring list columns as inputs to XGBoost model: ['item_genres', 'user_genres'].
warnings.warn(f"Ignoring list columns as inputs to XGBoost model: {list_column_names}.")

tests/unit/xgb/test_xgboost.py::TestXGBoost::test_unsupported_objective
/var/jenkins_home/workspace/merlin_models/models/.tox/test-gpu/lib/python3.8/site-packages/tornado/ioloop.py:350: DeprecationWarning: make_current is deprecated; start the event loop first
self.make_current()

tests/unit/xgb/test_xgboost.py: 14 warnings
/usr/local/lib/python3.8/dist-packages/xgboost/dask.py:884: RuntimeWarning: coroutine 'Client._wait_for_workers' was never awaited
client.wait_for_workers(n_workers)
Enable tracemalloc to get traceback where the object was allocated.
See https://docs.pytest.org/en/stable/how-to/capture-warnings.html#resource-warnings for more info.

tests/unit/xgb/test_xgboost.py: 11 warnings
/usr/local/lib/python3.8/dist-packages/cudf/core/dataframe.py:1183: DeprecationWarning: The default dtype for empty Series will be 'object' instead of 'float64' in a future version. Specify a dtype explicitly to silence this warning.
mask = pd.Series(mask)

-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html

---------- coverage: platform linux, python 3.8.10-final-0 -----------
Name Stmts Miss Cover

merlin/datasets/init.py 2 0 100%
merlin/datasets/advertising/init.py 2 0 100%
merlin/datasets/advertising/criteo/init.py 0 0 100%
merlin/datasets/advertising/criteo/dataset.py 79 60 24%
merlin/datasets/advertising/criteo/transformed/init.py 0 0 100%
merlin/datasets/ecommerce/init.py 3 0 100%
merlin/datasets/ecommerce/aliccp/init.py 0 0 100%
merlin/datasets/ecommerce/aliccp/dataset.py 141 87 38%
merlin/datasets/ecommerce/aliccp/raw/init.py 0 0 100%
merlin/datasets/ecommerce/aliccp/transformed/init.py 0 0 100%
merlin/datasets/ecommerce/dressipi/init.py 0 0 100%
merlin/datasets/ecommerce/dressipi/dataset.py 45 37 18%
merlin/datasets/ecommerce/dressipi/preprocessed/init.py 0 0 100%
merlin/datasets/ecommerce/large/init.py 0 0 100%
merlin/datasets/ecommerce/small/init.py 0 0 100%
merlin/datasets/ecommerce/transactions/init.py 0 0 100%
merlin/datasets/entertainment/init.py 2 0 100%
merlin/datasets/entertainment/movielens/1m-raw/init.py 0 0 100%
merlin/datasets/entertainment/movielens/1m-raw/ratings/init.py 0 0 100%
merlin/datasets/entertainment/movielens/1m/init.py 0 0 100%
merlin/datasets/entertainment/movielens/25m/init.py 0 0 100%
merlin/datasets/entertainment/movielens/100k/init.py 0 0 100%
merlin/datasets/entertainment/movielens/init.py 0 0 100%
merlin/datasets/entertainment/movielens/dataset.py 152 122 20%
merlin/datasets/entertainment/music_streaming/init.py 0 0 100%
merlin/datasets/social/init.py 0 0 100%
merlin/datasets/synthetic.py 147 15 90%
merlin/datasets/testing/init.py 0 0 100%
merlin/datasets/testing/sequence_testing/init.py 0 0 100%
merlin/models/init.py 2 0 100%
merlin/models/_version.py 354 205 42%
merlin/models/api.py 14 5 64%
merlin/models/config/init.py 0 0 100%
merlin/models/config/schema.py 62 0 100%
merlin/models/implicit/init.py 27 4 85%
merlin/models/io.py 15 0 100%
merlin/models/lightfm/init.py 23 0 100%
merlin/models/loader/init.py 0 0 100%
merlin/models/loader/backend.py 379 42 89%
merlin/models/loader/dataframe_iter.py 21 17 19%
merlin/models/loader/tf_utils.py 57 27 53%
merlin/models/loader/utils.py 40 15 62%
merlin/models/tf/init.py 70 0 100%
merlin/models/tf/blocks/init.py 0 0 100%
merlin/models/tf/blocks/cross.py 44 0 100%
merlin/models/tf/blocks/dlrm.py 49 2 96%
merlin/models/tf/blocks/experts.py 99 17 83%
merlin/models/tf/blocks/interaction.py 108 40 63%
merlin/models/tf/blocks/mlp.py 114 10 91%
merlin/models/tf/blocks/optimizer.py 173 13 92%
merlin/models/tf/blocks/retrieval/init.py 0 0 100%
merlin/models/tf/blocks/retrieval/base.py 169 62 63%
merlin/models/tf/blocks/retrieval/matrix_factorization.py 35 1 97%
merlin/models/tf/blocks/retrieval/two_tower.py 30 0 100%
merlin/models/tf/blocks/sampling/init.py 0 0 100%
merlin/models/tf/blocks/sampling/base.py 29 2 93%
merlin/models/tf/blocks/sampling/cross_batch.py 46 2 96%
merlin/models/tf/blocks/sampling/in_batch.py 35 0 100%
merlin/models/tf/blocks/sampling/queue.py 115 12 90%
merlin/models/tf/core/init.py 0 0 100%
merlin/models/tf/core/aggregation.py 241 49 80%
merlin/models/tf/core/base.py 244 55 77%
merlin/models/tf/core/combinators.py 426 53 88%
merlin/models/tf/core/encoder.py 170 29 83%
merlin/models/tf/core/index.py 104 16 85%
merlin/models/tf/core/prediction.py 50 1 98%
merlin/models/tf/core/tabular.py 280 29 90%
merlin/models/tf/inputs/init.py 0 0 100%
merlin/models/tf/inputs/base.py 60 10 83%
merlin/models/tf/inputs/continuous.py 39 3 92%
merlin/models/tf/inputs/embedding.py 458 31 93%
merlin/models/tf/loader.py 245 73 70%
merlin/models/tf/losses/init.py 4 0 100%
merlin/models/tf/losses/base.py 9 0 100%
merlin/models/tf/losses/listwise.py 13 0 100%
merlin/models/tf/losses/pairwise.py 115 1 99%
merlin/models/tf/metrics/init.py 2 0 100%
merlin/models/tf/metrics/evaluation.py 105 48 54%
merlin/models/tf/metrics/topk.py 198 48 76%
merlin/models/tf/models/init.py 0 0 100%
merlin/models/tf/models/base.py 708 75 89%
merlin/models/tf/models/benchmark.py 16 0 100%
merlin/models/tf/models/ranking.py 67 3 96%
merlin/models/tf/models/retrieval.py 78 4 95%
merlin/models/tf/models/utils.py 10 1 90%
merlin/models/tf/outputs/init.py 0 0 100%
merlin/models/tf/outputs/base.py 122 17 86%
merlin/models/tf/outputs/classification.py 91 1 99%
merlin/models/tf/outputs/contrastive.py 147 10 93%
merlin/models/tf/outputs/regression.py 9 0 100%
merlin/models/tf/outputs/sampling/init.py 0 0 100%
merlin/models/tf/outputs/sampling/base.py 78 21 73%
merlin/models/tf/outputs/sampling/in_batch.py 37 1 97%
merlin/models/tf/outputs/sampling/popularity.py 27 1 96%
merlin/models/tf/outputs/topk.py 97 6 94%
merlin/models/tf/prediction_tasks/init.py 0 0 100%
merlin/models/tf/prediction_tasks/base.py 207 37 82%
merlin/models/tf/prediction_tasks/classification.py 68 17 75%
merlin/models/tf/prediction_tasks/multi.py 7 0 100%
merlin/models/tf/prediction_tasks/next_item.py 59 6 90%
merlin/models/tf/prediction_tasks/regression.py 35 2 94%
merlin/models/tf/prediction_tasks/retrieval.py 73 3 96%
merlin/models/tf/transformers/init.py 0 0 100%
merlin/models/tf/transformers/block.py 101 2 98%
merlin/models/tf/transformers/transforms.py 63 0 100%
merlin/models/tf/transforms/init.py 0 0 100%
merlin/models/tf/transforms/bias.py 111 9 92%
merlin/models/tf/transforms/features.py 435 36 92%
merlin/models/tf/transforms/negative_sampling.py 77 3 96%
merlin/models/tf/transforms/noise.py 43 1 98%
merlin/models/tf/transforms/regularization.py 17 1 94%
merlin/models/tf/transforms/sequence.py 282 42 85%
merlin/models/tf/transforms/tensor.py 158 13 92%
merlin/models/tf/typing.py 7 0 100%
merlin/models/tf/utils/init.py 0 0 100%
merlin/models/tf/utils/batch_utils.py 85 4 95%
merlin/models/tf/utils/repr_utils.py 69 4 94%
merlin/models/tf/utils/search_utils.py 34 22 35%
merlin/models/tf/utils/testing_utils.py 206 36 83%
merlin/models/tf/utils/tf_utils.py 209 42 80%
merlin/models/torch/init.py 12 0 100%
merlin/models/torch/block/init.py 0 0 100%
merlin/models/torch/block/base.py 167 32 81%
merlin/models/torch/block/mlp.py 38 5 87%
merlin/models/torch/dataset.py 68 5 93%
merlin/models/torch/features/init.py 0 0 100%
merlin/models/torch/features/base.py 4 0 100%
merlin/models/torch/features/continuous.py 22 0 100%
merlin/models/torch/features/embedding.py 165 12 93%
merlin/models/torch/features/tabular.py 65 8 88%
merlin/models/torch/losses.py 28 28 0%
merlin/models/torch/model/init.py 0 0 100%
merlin/models/torch/model/base.py 286 65 77%
merlin/models/torch/model/prediction_task.py 24 0 100%
merlin/models/torch/tabular/init.py 0 0 100%
merlin/models/torch/tabular/aggregation.py 75 0 100%
merlin/models/torch/tabular/base.py 247 39 84%
merlin/models/torch/tabular/transformations.py 67 3 96%
merlin/models/torch/typing.py 6 0 100%
merlin/models/torch/utils/init.py 0 0 100%
merlin/models/torch/utils/data_utils.py 117 117 0%
merlin/models/torch/utils/examples_utils.py 39 39 0%
merlin/models/torch/utils/torch_utils.py 80 22 72%
merlin/models/utils/init.py 0 0 100%
merlin/models/utils/constants.py 3 0 100%
merlin/models/utils/dataset.py 38 4 89%
merlin/models/utils/dependencies.py 26 19 27%
merlin/models/utils/doc_utils.py 10 0 100%
merlin/models/utils/example_utils.py 31 2 94%
merlin/models/utils/misc_utils.py 118 90 24%
merlin/models/utils/nvt_utils.py 27 24 11%
merlin/models/utils/registry.py 101 29 71%
merlin/models/utils/schema_utils.py 90 19 79%
merlin/models/xgb/init.py 124 4 97%

TOTAL 11357 2229 80%

=========================== short test summary info ============================
SKIPPED [1] tests/unit/datasets/test_advertising.py:20: No data-dir available, pass it through env variable $INPUT_DATA_DIR
SKIPPED [1] tests/unit/datasets/test_ecommerce.py:62: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP
SKIPPED [1] tests/unit/datasets/test_ecommerce.py:78: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP
SKIPPED [1] tests/unit/datasets/test_ecommerce.py:92: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP
SKIPPED [3] tests/unit/datasets/test_entertainment.py:44: No data-dir available, pass it through env variable $INPUT_DATA_DIR
SKIPPED [5] ../../../.local/lib/python3.8/site-packages/tensorflow/python/framework/test_util.py:2746: Not a test.
========= 824 passed, 12 skipped, 1349 warnings in 1613.95s (0:26:53) ==========
___________________________________ summary ____________________________________
test-gpu: commands succeeded
congratulations :)
Performing Post build task...
Match found for : : True
Logical operation result is TRUE
Running script : #!/bin/bash
cd /var/jenkins_home/
CUDA_VISIBLE_DEVICES=1 python test_res_push.py "https://api.GitHub.com/repos/NVIDIA-Merlin/models/issues/$ghprbPullId/comments" "/var/jenkins_home/jobs/$JOB_NAME/builds/$BUILD_NUMBER/log"
[merlin_models] $ /bin/bash /tmp/jenkins10269772837355826908.sh

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typo in it's --> "its batch" is the correct one.

"All model parameters fits on a single GPU. do you mean " in this example we assume that model parameters fits on a single GPU." ?


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Correct spelling

and updating describption

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may be rephrase: import required libraries and set some hyperparameters.


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may be rephrase: We will use the same dataset and preprocessing steps with NVTabular


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this sentence is not clear "The worker with more batches waits for the gradients from the other worker, but it finished the training run.".

which worker finished the training run? the one with more batches or less batches?


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may be rephrase as "We can take a look what required code changes are automatically applied by Merlin Models:"

who is doing scaling the learning rate by number of workers? where and how it is happening? if this is happening under the hood can you please refer to the code base?


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Yes it happens automatically in the background.

I cannot refer to the code, as it isnt merged yet :)

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It is mentioned that hvd.init() is necessary, but could not find it in the script below.

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how do we know we speed up the training? can you do a comparison?


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You can compare the training time.

A benchmark of multi-gpu training is outside the scope for an example. It should be done as part of the implementation to test the efficiency of implementation. I added it to the RMP ticket a few weeks ago.

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rephrase as " if you want to learn about how to scale NVTabular feature engineering workflows to multi-GPU , check out our example."


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@bschifferer bschifferer requested a review from rnyak November 4, 2022 11:19
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GitHub pull request #855 of commit be50ba36745ce354af88b3356278d4d4abad4597, no merge conflicts.
Running as SYSTEM
Setting status of be50ba36745ce354af88b3356278d4d4abad4597 to PENDING with url https://10.20.13.93:8080/job/merlin_models/1738/console and message: 'Pending'
Using context: Jenkins
Building on master in workspace /var/jenkins_home/workspace/merlin_models
using credential nvidia-merlin-bot
 > git rev-parse --is-inside-work-tree # timeout=10
Fetching changes from the remote Git repository
 > git config remote.origin.url https://github.com/NVIDIA-Merlin/models/ # timeout=10
Fetching upstream changes from https://github.com/NVIDIA-Merlin/models/
 > git --version # timeout=10
using GIT_ASKPASS to set credentials This is the bot credentials for our CI/CD
 > git fetch --tags --force --progress -- https://github.com/NVIDIA-Merlin/models/ +refs/pull/855/*:refs/remotes/origin/pr/855/* # timeout=10
 > git rev-parse be50ba36745ce354af88b3356278d4d4abad4597^{commit} # timeout=10
Checking out Revision be50ba36745ce354af88b3356278d4d4abad4597 (detached)
 > git config core.sparsecheckout # timeout=10
 > git checkout -f be50ba36745ce354af88b3356278d4d4abad4597 # timeout=10
Commit message: "update example"
 > git rev-list --no-walk ea11a0632bae9e9120fe8e906fbb99c0dd197aaf # timeout=10
[merlin_models] $ /bin/bash /tmp/jenkins15475426473256011996.sh
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Requirement already satisfied: testbook in /usr/local/lib/python3.8/dist-packages (0.4.2)
Requirement already satisfied: nbclient>=0.4.0 in /usr/local/lib/python3.8/dist-packages (from testbook) (0.6.8)
Requirement already satisfied: nbformat>=5.0.4 in /usr/local/lib/python3.8/dist-packages (from testbook) (5.5.0)
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Requirement already satisfied: tornado>=6.2 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (6.2)
Requirement already satisfied: pyzmq>=23.0 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (24.0.0)
Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (2.8.2)
Requirement already satisfied: zipp>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from importlib-resources>=1.4.0->jsonschema>=2.6->nbformat>=5.0.4->testbook) (3.8.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.8.2->jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (1.15.0)
GLOB sdist-make: /var/jenkins_home/workspace/merlin_models/models/setup.py
test-gpu inst-nodeps: /var/jenkins_home/workspace/merlin_models/models/.tox/.tmp/package/2/merlin-models-0.9.0+29.gbe50ba36.zip
WARNING: Discarding $PYTHONPATH from environment, to override specify PYTHONPATH in 'passenv' in your configuration.
test-gpu installed: absl-py==1.2.0,aiohttp==3.8.1,aiosignal==1.2.0,alabaster==0.7.12,alembic==1.8.1,anyio==3.6.1,appdirs==1.4.4,argon2-cffi==21.3.0,argon2-cffi-bindings==21.2.0,astroid==2.5.6,asttokens==2.0.8,astunparse==1.6.3,asv==0.5.1,asvdb==0.4.2,async-timeout==4.0.2,attrs==22.1.0,autopage==0.5.1,awscli==1.27.2,Babel==2.10.3,backcall==0.2.0,beautifulsoup4==4.11.1,betterproto==1.2.5,black==20.8b1,bleach==5.0.1,boto3==1.24.75,botocore==1.29.2,Brotli==1.0.9,build==0.9.0,cachetools==5.2.0,certifi==2019.11.28,cffi==1.15.1,chardet==3.0.4,charset-normalizer==2.1.1,check-manifest==0.48,clang==5.0,click==8.1.3,cliff==4.0.0,cloudpickle==2.2.0,cmaes==0.8.2,cmake==3.24.1.1,cmd2==2.4.2,colorama==0.4.4,colorlog==6.7.0,contourpy==1.0.5,coverage==6.5.0,cuda-python==11.7.1,cupy-cuda117==10.6.0,cycler==0.11.0,Cython==0.29.32,dask==2022.1.1,dbus-python==1.2.16,debugpy==1.6.3,decorator==5.1.1,defusedxml==0.7.1,dill==0.3.5.1,distlib==0.3.6,distributed==2022.5.1,distro==1.7.0,dm-tree==0.1.6,docker-pycreds==0.4.0,docutils==0.16,emoji==1.7.0,entrypoints==0.4,execnet==1.9.0,executing==1.0.0,faiss==1.7.2,faiss-gpu==1.7.2,fastai==2.7.9,fastapi==0.85.0,fastavro==1.6.1,fastcore==1.5.27,fastdownload==0.0.7,fastjsonschema==2.16.1,fastprogress==1.0.3,fastrlock==0.8,feast==0.19.4,fiddle==0.2.2,filelock==3.8.0,flake8==5.0.4,flatbuffers==1.12,fonttools==4.37.3,frozenlist==1.3.1,fsspec==2022.5.0,gast==0.4.0,gevent==21.12.0,geventhttpclient==2.0.2,gitdb==4.0.9,GitPython==3.1.27,google==3.0.0,google-api-core==2.10.1,google-auth==2.11.1,google-auth-oauthlib==0.4.6,google-pasta==0.2.0,googleapis-common-protos==1.52.0,graphviz==0.20.1,greenlet==1.1.3,grpcio==1.41.0,grpcio-channelz==1.49.0,grpcio-reflection==1.48.1,grpclib==0.4.3,h11==0.13.0,h2==4.1.0,h5py==3.7.0,HeapDict==1.0.1,horovod==0.26.1,hpack==4.0.0,httptools==0.5.0,hugectr2onnx==0.0.0,huggingface-hub==0.9.1,hyperframe==6.0.1,idna==2.8,imagesize==1.4.1,implicit==0.6.1,importlib-metadata==4.12.0,importlib-resources==5.9.0,iniconfig==1.1.1,interrogate==1.5.0,ipykernel==6.15.3,ipython==8.5.0,ipython-genutils==0.2.0,ipywidgets==7.7.0,isort==5.10.1,jedi==0.18.1,Jinja2==3.1.2,jmespath==1.0.1,joblib==1.2.0,json5==0.9.10,jsonschema==4.16.0,jupyter==1.0.0,jupyter-cache==0.4.3,jupyter-console==6.4.4,jupyter-core==4.11.1,jupyter-server==1.18.1,jupyter-server-mathjax==0.2.5,jupyter-sphinx==0.3.2,jupyter_client==7.3.5,jupyterlab==3.4.7,jupyterlab-pygments==0.2.2,jupyterlab-widgets==1.1.0,jupyterlab_server==2.15.1,keras==2.9.0,Keras-Preprocessing==1.1.2,kiwisolver==1.4.4,lazy-object-proxy==1.8.0,libclang==14.0.6,libcst==0.4.7,lightfm==1.16,lightgbm==3.3.2,linkify-it-py==1.0.3,llvmlite==0.39.1,locket==1.0.0,lxml==4.9.1,Mako==1.2.3,Markdown==3.4.1,markdown-it-py==1.1.0,MarkupSafe==2.1.1,matplotlib==3.6.0,matplotlib-inline==0.1.6,mccabe==0.7.0,mdit-py-plugins==0.2.8,merlin-core==0.6.0+1.g5926fcf,merlin-dataloader @ git+https://github.com/NVIDIA-Merlin/dataloader.git@61ca2edae832da4eb2c6b93390c24920e68de1ae,merlin-models==0.9.0+29.gbe50ba36,merlin-systems==0.5.0+4.g15074ad,mistune==2.0.4,mmh3==3.0.0,mpi4py==3.1.3,msgpack==1.0.4,multidict==6.0.2,mypy==0.982,mypy-extensions==0.4.3,myst-nb==0.13.2,myst-parser==0.15.2,natsort==8.1.0,nbclassic==0.4.3,nbclient==0.6.8,nbconvert==7.0.0,nbdime==3.1.1,nbformat==5.5.0,nest-asyncio==1.5.5,ninja==1.10.2.3,notebook==6.4.12,notebook-shim==0.1.0,numba==0.56.2,numpy==1.22.4,nvidia-pyindex==1.0.9,# Editable install with no version control (nvtabular==1.4.0+8.g95e12d347),-e /usr/local/lib/python3.8/dist-packages,nvtx==0.2.5,oauthlib==3.2.1,oldest-supported-numpy==2022.8.16,onnx==1.12.0,onnxruntime==1.11.1,opt-einsum==3.3.0,optuna==3.0.3,packaging==21.3,pandas==1.3.5,pandavro==1.5.2,pandocfilters==1.5.0,parso==0.8.3,partd==1.3.0,pathspec==0.10.1,pathtools==0.1.2,pbr==5.11.0,pep517==0.13.0,pexpect==4.8.0,pickleshare==0.7.5,Pillow==9.2.0,pkgutil_resolve_name==1.3.10,platformdirs==2.5.2,plotly==5.11.0,pluggy==1.0.0,prettytable==3.5.0,prometheus-client==0.14.1,promise==2.3,prompt-toolkit==3.0.31,proto-plus==1.19.6,protobuf==3.19.5,psutil==5.9.2,ptyprocess==0.7.0,pure-eval==0.2.2,py==1.11.0,pyarrow==7.0.0,pyasn1==0.4.8,pyasn1-modules==0.2.8,pybind11==2.10.0,pycodestyle==2.9.1,pycparser==2.21,pydantic==1.10.2,pydot==1.4.2,pyflakes==2.5.0,Pygments==2.13.0,PyGObject==3.36.0,pynvml==11.4.1,pyparsing==3.0.9,pyperclip==1.8.2,pyrsistent==0.18.1,pytest==7.1.3,pytest-cov==4.0.0,pytest-xdist==3.0.2,python-apt==2.0.0+ubuntu0.20.4.8,python-dateutil==2.8.2,python-dotenv==0.21.0,python-rapidjson==1.8,pytz==2022.2.1,PyYAML==5.4.1,pyzmq==24.0.0,qtconsole==5.3.2,QtPy==2.2.1,regex==2022.9.13,requests==2.22.0,requests-oauthlib==1.3.1,requests-unixsocket==0.2.0,rsa==4.7.2,s3fs==2022.2.0,s3transfer==0.6.0,sacremoses==0.0.53,scikit-build==0.15.0,scikit-learn==1.1.2,scipy==1.8.1,seedir==0.3.0,Send2Trash==1.8.0,sentry-sdk==1.9.8,setproctitle==1.3.2,setuptools-scm==7.0.5,shortuuid==1.0.9,six==1.15.0,sklearn==0.0,smmap==5.0.0,sniffio==1.3.0,snowballstemmer==2.2.0,sortedcontainers==2.4.0,soupsieve==2.3.2.post1,Sphinx==5.3.0,sphinx-multiversion==0.2.4,sphinx-togglebutton==0.3.1,sphinx_external_toc==0.3.0,sphinxcontrib-applehelp==1.0.2,sphinxcontrib-copydirs @ git+https://github.com/mikemckiernan/sphinxcontrib-copydirs.git@bd8c5d79b3f91cf5f1bb0d6995aeca3fe84b670e,sphinxcontrib-devhelp==1.0.2,sphinxcontrib-htmlhelp==2.0.0,sphinxcontrib-jsmath==1.0.1,sphinxcontrib-qthelp==1.0.3,sphinxcontrib-serializinghtml==1.1.5,SQLAlchemy==1.4.42,stack-data==0.5.0,starlette==0.20.4,stevedore==4.1.0,stringcase==1.2.0,supervisor==4.1.0,tabulate==0.8.10,tblib==1.7.0,tdqm==0.0.1,tenacity==8.0.1,tensorboard==2.9.1,tensorboard-data-server==0.6.1,tensorboard-plugin-wit==1.8.1,tensorflow==2.9.2,tensorflow-estimator==2.9.0,tensorflow-gpu==2.9.2,tensorflow-io-gcs-filesystem==0.27.0,tensorflow-metadata==1.10.0,tensorflow-ranking==0.5.1,tensorflow-serving-api==2.9.2,termcolor==2.0.1,terminado==0.15.0,testbook==0.4.2,threadpoolctl==3.1.0,tinycss2==1.1.1,tokenizers==0.10.3,toml==0.10.2,tomli==2.0.1,toolz==0.12.0,torch==1.12.1+cu113,torchmetrics==0.3.2,tornado==6.2,tox==3.26.0,tqdm==4.64.1,traitlets==5.4.0,transformers==4.12.0,transformers4rec==0.1.12+2.gbcc939255,treelite==2.3.0,treelite-runtime==2.3.0,tritonclient==2.25.0,typed-ast==1.5.4,typing-inspect==0.8.0,typing_extensions==4.3.0,uc-micro-py==1.0.1,urllib3==1.26.12,uvicorn==0.18.3,uvloop==0.17.0,versioneer==0.20,virtualenv==20.16.5,wandb==0.13.3,watchfiles==0.17.0,wcwidth==0.2.5,webencodings==0.5.1,websocket-client==1.4.1,websockets==10.3,Werkzeug==2.2.2,widgetsnbextension==3.6.0,wrapt==1.12.1,xgboost==1.6.2,yarl==1.8.1,zict==2.2.0,zipp==3.8.1,zope.event==4.5.0,zope.interface==5.4.0
test-gpu run-test-pre: PYTHONHASHSEED='859774119'
test-gpu run-test: commands[0] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/core.git
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Collecting git+https://github.com/NVIDIA-Merlin/core.git
  Cloning https://github.com/NVIDIA-Merlin/core.git to /tmp/pip-req-build-t4189m_3
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/core.git /tmp/pip-req-build-t4189m_3
  Resolved https://github.com/NVIDIA-Merlin/core.git to commit 563be4bf5ef675940d5fff2b5e4666424a7f7947
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: packaging in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+5.g563be4b) (21.3)
Requirement already satisfied: pandas<1.4.0dev0,>=1.2.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+5.g563be4b) (1.3.5)
Requirement already satisfied: protobuf>=3.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+5.g563be4b) (3.19.5)
Requirement already satisfied: fsspec==2022.5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+5.g563be4b) (2022.5.0)
Requirement already satisfied: pyarrow>=5.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+5.g563be4b) (7.0.0)
Requirement already satisfied: distributed>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+5.g563be4b) (2022.3.0)
Requirement already satisfied: tqdm>=4.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+5.g563be4b) (4.64.1)
Requirement already satisfied: tensorflow-metadata>=1.2.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+5.g563be4b) (1.10.0)
Requirement already satisfied: betterproto<2.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+5.g563be4b) (1.2.5)
Requirement already satisfied: numba>=0.54 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+5.g563be4b) (0.55.1)
Requirement already satisfied: dask>=2022.3.0 in ./.tox/test-gpu/lib/python3.8/site-packages (from merlin-core==0.8.0+5.g563be4b) (2022.3.0)
Requirement already satisfied: stringcase in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core==0.8.0+5.g563be4b) (1.2.0)
Requirement already satisfied: grpclib in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core==0.8.0+5.g563be4b) (0.4.3)
Requirement already satisfied: cloudpickle>=1.1.1 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core==0.8.0+5.g563be4b) (2.2.0)
Requirement already satisfied: toolz>=0.8.2 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core==0.8.0+5.g563be4b) (0.12.0)
Requirement already satisfied: partd>=0.3.10 in /var/jenkins_home/.local/lib/python3.8/site-packages/partd-1.2.0-py3.8.egg (from dask>=2022.3.0->merlin-core==0.8.0+5.g563be4b) (1.2.0)
Requirement already satisfied: pyyaml>=5.3.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/PyYAML-5.4.1-py3.8-linux-x86_64.egg (from dask>=2022.3.0->merlin-core==0.8.0+5.g563be4b) (5.4.1)
Requirement already satisfied: click>=6.6 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+5.g563be4b) (8.1.3)
Requirement already satisfied: tornado>=6.0.3 in ./.tox/test-gpu/lib/python3.8/site-packages (from distributed>=2022.3.0->merlin-core==0.8.0+5.g563be4b) (6.2)
Requirement already satisfied: sortedcontainers!=2.0.0,!=2.0.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/sortedcontainers-2.4.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+5.g563be4b) (2.4.0)
Requirement already satisfied: msgpack>=0.6.0 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+5.g563be4b) (1.0.4)
Requirement already satisfied: jinja2 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+5.g563be4b) (3.1.2)
Requirement already satisfied: zict>=0.1.3 in /var/jenkins_home/.local/lib/python3.8/site-packages/zict-2.0.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+5.g563be4b) (2.0.0)
Requirement already satisfied: tblib>=1.6.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/tblib-1.7.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+5.g563be4b) (1.7.0)
Requirement already satisfied: psutil>=5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/psutil-5.8.0-py3.8-linux-x86_64.egg (from distributed>=2022.3.0->merlin-core==0.8.0+5.g563be4b) (5.8.0)
Requirement already satisfied: llvmlite<0.39,>=0.38.0rc1 in ./.tox/test-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+5.g563be4b) (0.38.1)
Requirement already satisfied: setuptools in ./.tox/test-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+5.g563be4b) (59.8.0)
Requirement already satisfied: numpy<1.22,>=1.18 in /var/jenkins_home/.local/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+5.g563be4b) (1.20.3)
Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in /usr/local/lib/python3.8/dist-packages (from packaging->merlin-core==0.8.0+5.g563be4b) (3.0.9)
Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+5.g563be4b) (2.8.2)
Requirement already satisfied: pytz>=2017.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+5.g563be4b) (2022.2.1)
Requirement already satisfied: absl-py<2.0.0,>=0.9 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core==0.8.0+5.g563be4b) (1.2.0)
Requirement already satisfied: googleapis-common-protos<2,>=1.52.0 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core==0.8.0+5.g563be4b) (1.52.0)
Requirement already satisfied: locket in /var/jenkins_home/.local/lib/python3.8/site-packages/locket-0.2.1-py3.8.egg (from partd>=0.3.10->dask>=2022.3.0->merlin-core==0.8.0+5.g563be4b) (0.2.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.7.3->pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+5.g563be4b) (1.15.0)
Requirement already satisfied: heapdict in /var/jenkins_home/.local/lib/python3.8/site-packages/HeapDict-1.0.1-py3.8.egg (from zict>=0.1.3->distributed>=2022.3.0->merlin-core==0.8.0+5.g563be4b) (1.0.1)
Requirement already satisfied: multidict in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core==0.8.0+5.g563be4b) (6.0.2)
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Requirement already satisfied: MarkupSafe>=2.0 in ./.tox/test-gpu/lib/python3.8/site-packages (from jinja2->distributed>=2022.3.0->merlin-core==0.8.0+5.g563be4b) (2.0.1)
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[notice] A new release of pip available: 22.2.2 -> 22.3
[notice] To update, run: pip install --upgrade pip
test-gpu run-test: commands[1] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/nvtabular.git
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Collecting git+https://github.com/NVIDIA-Merlin/nvtabular.git
Cloning https://github.com/NVIDIA-Merlin/nvtabular.git to /tmp/pip-req-build-q51h69r0
Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/nvtabular.git /tmp/pip-req-build-q51h69r0
Resolved https://github.com/NVIDIA-Merlin/nvtabular.git to commit 8e7edbafd3006f56e73efdc0c01c4445ab57d028
Installing build dependencies: started
Installing build dependencies: finished with status 'done'
Getting requirements to build wheel: started
Getting requirements to build wheel: finished with status 'done'
Preparing metadata (pyproject.toml): started
Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: merlin-core>=0.2.0 in ./.tox/test-gpu/lib/python3.8/site-packages (from nvtabular==1.6.0+3.g8e7edbaf) (0.8.0+5.g563be4b)
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[notice] A new release of pip available: 22.2.2 -> 22.3
[notice] To update, run: pip install --upgrade pip
test-gpu run-test: commands[2] | python -m pytest --cov-report term --cov merlin -rxs tests/unit
============================= test session starts ==============================
platform linux -- Python 3.8.10, pytest-7.1.3, pluggy-1.0.0
cachedir: .tox/test-gpu/.pytest_cache
rootdir: /var/jenkins_home/workspace/merlin_models/models, configfile: pyproject.toml
plugins: anyio-3.5.0, xdist-3.0.2, cov-4.0.0
collected 836 items

tests/unit/config/test_schema.py .... [ 0%]
tests/unit/datasets/test_advertising.py .s [ 0%]
tests/unit/datasets/test_ecommerce.py ..sss [ 1%]
tests/unit/datasets/test_entertainment.py ....sss. [ 2%]
tests/unit/datasets/test_social.py . [ 2%]
tests/unit/datasets/test_synthetic.py ...... [ 3%]
tests/unit/implicit/test_implicit.py . [ 3%]
tests/unit/lightfm/test_lightfm.py . [ 3%]
tests/unit/tf/test_core.py ...... [ 4%]
tests/unit/tf/test_loader.py ................ [ 5%]
tests/unit/tf/test_public_api.py . [ 6%]
tests/unit/tf/blocks/test_cross.py ........... [ 7%]
tests/unit/tf/blocks/test_dlrm.py .......... [ 8%]
tests/unit/tf/blocks/test_interactions.py ... [ 8%]
tests/unit/tf/blocks/test_mlp.py ................................. [ 12%]
tests/unit/tf/blocks/test_optimizer.py s................................ [ 16%]
..................... [ 19%]
tests/unit/tf/blocks/retrieval/test_base.py . [ 19%]
tests/unit/tf/blocks/retrieval/test_matrix_factorization.py .. [ 19%]
tests/unit/tf/blocks/retrieval/test_two_tower.py ............ [ 21%]
tests/unit/tf/blocks/sampling/test_cross_batch.py . [ 21%]
tests/unit/tf/blocks/sampling/test_in_batch.py . [ 21%]
tests/unit/tf/core/test_aggregation.py ......... [ 22%]
tests/unit/tf/core/test_base.py .. [ 22%]
tests/unit/tf/core/test_combinators.py s..................... [ 25%]
tests/unit/tf/core/test_encoder.py .. [ 25%]
tests/unit/tf/core/test_index.py ... [ 25%]
tests/unit/tf/core/test_prediction.py .. [ 26%]
tests/unit/tf/core/test_tabular.py ...... [ 26%]
tests/unit/tf/examples/test_01_getting_started.py . [ 27%]
tests/unit/tf/examples/test_02_dataschema.py . [ 27%]
tests/unit/tf/examples/test_03_exploring_different_models.py . [ 27%]
tests/unit/tf/examples/test_04_export_ranking_models.py . [ 27%]
tests/unit/tf/examples/test_05_export_retrieval_model.py . [ 27%]
tests/unit/tf/examples/test_06_advanced_own_architecture.py . [ 27%]
tests/unit/tf/examples/test_07_train_traditional_models.py . [ 27%]
tests/unit/tf/examples/test_usecase_accelerate_training_by_lazyadam.py . [ 27%]
[ 27%]
tests/unit/tf/examples/test_usecase_data_parallel.py . [ 27%]
tests/unit/tf/examples/test_usecase_ecommerce_session_based.py . [ 28%]
tests/unit/tf/examples/test_usecase_incremental_training_layer_freezing.py . [ 28%]
[ 28%]
tests/unit/tf/examples/test_usecase_pretrained_embeddings.py . [ 28%]
tests/unit/tf/examples/test_usecase_retrieval_with_hpo.py . [ 28%]
tests/unit/tf/inputs/test_continuous.py ........ [ 29%]
tests/unit/tf/inputs/test_embedding.py ................................. [ 33%]
........ [ 34%]
tests/unit/tf/inputs/test_tabular.py .................. [ 36%]
tests/unit/tf/layers/test_queue.py .............. [ 38%]
tests/unit/tf/losses/test_losses.py ....................... [ 40%]
tests/unit/tf/metrics/test_metrics_popularity.py ..... [ 41%]
tests/unit/tf/metrics/test_metrics_topk.py ......................... [ 44%]
tests/unit/tf/models/test_base.py s........................ [ 47%]
tests/unit/tf/models/test_benchmark.py .. [ 47%]
tests/unit/tf/models/test_ranking.py .................................. [ 51%]
tests/unit/tf/models/test_retrieval.py ................................. [ 55%]
.......................................... [ 60%]
tests/unit/tf/outputs/test_base.py ...... [ 61%]
tests/unit/tf/outputs/test_classification.py ...... [ 62%]
tests/unit/tf/outputs/test_contrastive.py .............. [ 63%]
tests/unit/tf/outputs/test_regression.py .. [ 64%]
tests/unit/tf/outputs/test_sampling.py .... [ 64%]
tests/unit/tf/outputs/test_topk.py . [ 64%]
tests/unit/tf/prediction_tasks/test_classification.py .. [ 64%]
tests/unit/tf/prediction_tasks/test_multi_task.py ................ [ 66%]
tests/unit/tf/prediction_tasks/test_next_item.py ..... [ 67%]
tests/unit/tf/prediction_tasks/test_regression.py ..... [ 68%]
tests/unit/tf/prediction_tasks/test_retrieval.py . [ 68%]
tests/unit/tf/prediction_tasks/test_sampling.py ...... [ 68%]
tests/unit/tf/transformers/test_block.py ..................... [ 71%]
tests/unit/tf/transformers/test_transforms.py .......... [ 72%]
tests/unit/tf/transforms/test_bias.py .. [ 72%]
tests/unit/tf/transforms/test_features.py s............................. [ 76%]
.......................s...... [ 80%]
tests/unit/tf/transforms/test_negative_sampling.py ......... [ 81%]
tests/unit/tf/transforms/test_noise.py ..... [ 81%]
tests/unit/tf/transforms/test_sequence.py .................... [ 84%]
tests/unit/tf/transforms/test_tensor.py ... [ 84%]
tests/unit/tf/utils/test_batch.py .... [ 84%]
tests/unit/tf/utils/test_dataset.py .. [ 85%]
tests/unit/tf/utils/test_tf_utils.py ..... [ 85%]
tests/unit/torch/test_dataset.py ......... [ 86%]
tests/unit/torch/test_public_api.py . [ 86%]
tests/unit/torch/block/test_base.py .... [ 87%]
tests/unit/torch/block/test_mlp.py . [ 87%]
tests/unit/torch/features/test_continuous.py .. [ 87%]
tests/unit/torch/features/test_embedding.py .............. [ 89%]
tests/unit/torch/features/test_tabular.py .... [ 89%]
tests/unit/torch/model/test_head.py ............ [ 91%]
tests/unit/torch/model/test_model.py .. [ 91%]
tests/unit/torch/tabular/test_aggregation.py ........ [ 92%]
tests/unit/torch/tabular/test_tabular.py ... [ 92%]
tests/unit/torch/tabular/test_transformations.py ....... [ 93%]
tests/unit/utils/test_schema_utils.py ................................ [ 97%]
tests/unit/xgb/test_xgboost.py .................... [100%]

=============================== warnings summary ===============================
../../../../../usr/lib/python3/dist-packages/requests/init.py:89
/usr/lib/python3/dist-packages/requests/init.py:89: RequestsDependencyWarning: urllib3 (1.26.12) or chardet (3.0.4) doesn't match a supported version!
warnings.warn("urllib3 ({}) or chardet ({}) doesn't match a supported "

../../../.local/lib/python3.8/site-packages/flatbuffers/compat.py:19
/var/jenkins_home/.local/lib/python3.8/site-packages/flatbuffers/compat.py:19: DeprecationWarning: the imp module is deprecated in favour of importlib; see the module's documentation for alternative uses
import imp

../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36
/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36: DeprecationWarning: NEAREST is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.NEAREST or Dither.NONE instead.
'nearest': pil_image.NEAREST,

../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37
/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37: DeprecationWarning: BILINEAR is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BILINEAR instead.
'bilinear': pil_image.BILINEAR,

../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38
/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38: DeprecationWarning: BICUBIC is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BICUBIC instead.
'bicubic': pil_image.BICUBIC,

../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39
/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39: DeprecationWarning: HAMMING is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.HAMMING instead.
'hamming': pil_image.HAMMING,

../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40
/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40: DeprecationWarning: BOX is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BOX instead.
'box': pil_image.BOX,

../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41
/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41: DeprecationWarning: LANCZOS is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.LANCZOS instead.
'lanczos': pil_image.LANCZOS,

tests/unit/datasets/test_advertising.py: 1 warning
tests/unit/datasets/test_ecommerce.py: 2 warnings
tests/unit/datasets/test_entertainment.py: 4 warnings
tests/unit/datasets/test_social.py: 1 warning
tests/unit/datasets/test_synthetic.py: 6 warnings
tests/unit/implicit/test_implicit.py: 1 warning
tests/unit/lightfm/test_lightfm.py: 1 warning
tests/unit/tf/test_core.py: 6 warnings
tests/unit/tf/test_loader.py: 1 warning
tests/unit/tf/blocks/test_cross.py: 5 warnings
tests/unit/tf/blocks/test_dlrm.py: 9 warnings
tests/unit/tf/blocks/test_interactions.py: 2 warnings
tests/unit/tf/blocks/test_mlp.py: 26 warnings
tests/unit/tf/blocks/test_optimizer.py: 30 warnings
tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings
tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings
tests/unit/tf/core/test_aggregation.py: 6 warnings
tests/unit/tf/core/test_base.py: 2 warnings
tests/unit/tf/core/test_combinators.py: 11 warnings
tests/unit/tf/core/test_encoder.py: 6 warnings
tests/unit/tf/core/test_index.py: 8 warnings
tests/unit/tf/core/test_prediction.py: 2 warnings
tests/unit/tf/inputs/test_continuous.py: 7 warnings
tests/unit/tf/inputs/test_embedding.py: 20 warnings
tests/unit/tf/inputs/test_tabular.py: 18 warnings
tests/unit/tf/models/test_base.py: 27 warnings
tests/unit/tf/models/test_benchmark.py: 2 warnings
tests/unit/tf/models/test_ranking.py: 38 warnings
tests/unit/tf/models/test_retrieval.py: 119 warnings
tests/unit/tf/outputs/test_base.py: 6 warnings
tests/unit/tf/outputs/test_classification.py: 6 warnings
tests/unit/tf/outputs/test_contrastive.py: 19 warnings
tests/unit/tf/outputs/test_regression.py: 2 warnings
tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings
tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings
tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings
tests/unit/tf/prediction_tasks/test_retrieval.py: 1 warning
tests/unit/tf/transformers/test_block.py: 15 warnings
tests/unit/tf/transforms/test_bias.py: 2 warnings
tests/unit/tf/transforms/test_features.py: 10 warnings
tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings
tests/unit/tf/transforms/test_noise.py: 1 warning
tests/unit/tf/transforms/test_sequence.py: 15 warnings
tests/unit/tf/utils/test_batch.py: 9 warnings
tests/unit/tf/utils/test_dataset.py: 2 warnings
tests/unit/torch/block/test_base.py: 4 warnings
tests/unit/torch/block/test_mlp.py: 1 warning
tests/unit/torch/features/test_continuous.py: 1 warning
tests/unit/torch/features/test_embedding.py: 4 warnings
tests/unit/torch/features/test_tabular.py: 4 warnings
tests/unit/torch/model/test_head.py: 12 warnings
tests/unit/torch/model/test_model.py: 2 warnings
tests/unit/torch/tabular/test_aggregation.py: 6 warnings
tests/unit/torch/tabular/test_transformations.py: 3 warnings
tests/unit/xgb/test_xgboost.py: 18 warnings
/var/jenkins_home/workspace/merlin_models/models/.tox/test-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.ITEM_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.ITEM: 'item'>, <Tags.ID: 'id'>].
warnings.warn(

tests/unit/datasets/test_ecommerce.py: 2 warnings
tests/unit/datasets/test_entertainment.py: 4 warnings
tests/unit/datasets/test_social.py: 1 warning
tests/unit/datasets/test_synthetic.py: 5 warnings
tests/unit/implicit/test_implicit.py: 1 warning
tests/unit/lightfm/test_lightfm.py: 1 warning
tests/unit/tf/test_core.py: 6 warnings
tests/unit/tf/test_loader.py: 1 warning
tests/unit/tf/blocks/test_cross.py: 5 warnings
tests/unit/tf/blocks/test_dlrm.py: 9 warnings
tests/unit/tf/blocks/test_interactions.py: 2 warnings
tests/unit/tf/blocks/test_mlp.py: 26 warnings
tests/unit/tf/blocks/test_optimizer.py: 30 warnings
tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings
tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings
tests/unit/tf/core/test_aggregation.py: 6 warnings
tests/unit/tf/core/test_base.py: 2 warnings
tests/unit/tf/core/test_combinators.py: 11 warnings
tests/unit/tf/core/test_encoder.py: 7 warnings
tests/unit/tf/core/test_index.py: 3 warnings
tests/unit/tf/core/test_prediction.py: 2 warnings
tests/unit/tf/inputs/test_continuous.py: 7 warnings
tests/unit/tf/inputs/test_embedding.py: 20 warnings
tests/unit/tf/inputs/test_tabular.py: 18 warnings
tests/unit/tf/models/test_base.py: 27 warnings
tests/unit/tf/models/test_benchmark.py: 2 warnings
tests/unit/tf/models/test_ranking.py: 36 warnings
tests/unit/tf/models/test_retrieval.py: 85 warnings
tests/unit/tf/outputs/test_base.py: 6 warnings
tests/unit/tf/outputs/test_classification.py: 6 warnings
tests/unit/tf/outputs/test_contrastive.py: 19 warnings
tests/unit/tf/outputs/test_regression.py: 2 warnings
tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings
tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings
tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings
tests/unit/tf/transformers/test_block.py: 9 warnings
tests/unit/tf/transforms/test_features.py: 10 warnings
tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings
tests/unit/tf/transforms/test_sequence.py: 15 warnings
tests/unit/tf/utils/test_batch.py: 7 warnings
tests/unit/tf/utils/test_dataset.py: 2 warnings
tests/unit/torch/block/test_base.py: 4 warnings
tests/unit/torch/block/test_mlp.py: 1 warning
tests/unit/torch/features/test_continuous.py: 1 warning
tests/unit/torch/features/test_embedding.py: 4 warnings
tests/unit/torch/features/test_tabular.py: 4 warnings
tests/unit/torch/model/test_head.py: 12 warnings
tests/unit/torch/model/test_model.py: 2 warnings
tests/unit/torch/tabular/test_aggregation.py: 6 warnings
tests/unit/torch/tabular/test_transformations.py: 2 warnings
tests/unit/xgb/test_xgboost.py: 17 warnings
/var/jenkins_home/workspace/merlin_models/models/.tox/test-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.USER_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.USER: 'user'>, <Tags.ID: 'id'>].
warnings.warn(

tests/unit/datasets/test_entertainment.py: 1 warning
tests/unit/implicit/test_implicit.py: 1 warning
tests/unit/lightfm/test_lightfm.py: 1 warning
tests/unit/tf/test_loader.py: 1 warning
tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings
tests/unit/tf/blocks/retrieval/test_two_tower.py: 2 warnings
tests/unit/tf/core/test_combinators.py: 11 warnings
tests/unit/tf/core/test_encoder.py: 2 warnings
tests/unit/tf/core/test_prediction.py: 1 warning
tests/unit/tf/inputs/test_continuous.py: 4 warnings
tests/unit/tf/inputs/test_embedding.py: 9 warnings
tests/unit/tf/inputs/test_tabular.py: 8 warnings
tests/unit/tf/models/test_ranking.py: 20 warnings
tests/unit/tf/models/test_retrieval.py: 10 warnings
tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings
tests/unit/tf/prediction_tasks/test_regression.py: 3 warnings
tests/unit/tf/transforms/test_negative_sampling.py: 9 warnings
tests/unit/xgb/test_xgboost.py: 12 warnings
/var/jenkins_home/workspace/merlin_models/models/.tox/test-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.SESSION_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.SESSION: 'session'>, <Tags.ID: 'id'>].
warnings.warn(

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export
tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export
tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export
tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export
tests/unit/tf/inputs/test_embedding.py::test_embedding_features_exporting_and_loading_pretrained_initializer
/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/inputs/embedding.py:968: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack
embeddings_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(embeddings)))

tests/unit/tf/blocks/retrieval/test_two_tower.py: 1 warning
tests/unit/tf/core/test_index.py: 4 warnings
tests/unit/tf/models/test_retrieval.py: 54 warnings
tests/unit/tf/prediction_tasks/test_next_item.py: 3 warnings
tests/unit/tf/utils/test_batch.py: 2 warnings
/tmp/autograph_generated_file0vhz5nfj.py:8: DeprecationWarning: The 'warn' method is deprecated, use 'warning' instead
ag
.converted_call(ag__.ld(warnings).warn, ("The 'warn' method is deprecated, use 'warning' instead", ag__.ld(DeprecationWarning), 2), None, fscope)

tests/unit/tf/core/test_combinators.py::test_parallel_block_select_by_tags
/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/core/tabular.py:602: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated since Python 3.3, and in 3.10 it will stop working
elif isinstance(self.feature_names, collections.Sequence):

tests/unit/tf/core/test_encoder.py: 1 warning
tests/unit/tf/core/test_index.py: 5 warnings
tests/unit/tf/models/test_retrieval.py: 30 warnings
tests/unit/tf/utils/test_batch.py: 4 warnings
tests/unit/tf/utils/test_dataset.py: 1 warning
/var/jenkins_home/workspace/merlin_models/models/merlin/models/utils/dataset.py:75: DeprecationWarning: unique_rows_by_features is deprecated and will be removed in a future version. Please use unique_by_tag instead.
warnings.warn(

tests/unit/tf/models/test_base.py::test_model_pre_post[True]
tests/unit/tf/models/test_base.py::test_model_pre_post[False]
tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.1]
tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.3]
tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.5]
tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.7]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/util/dispatch.py:1082: UserWarning: tf.keras.backend.random_binomial is deprecated, and will be removed in a future version.Please use tf.keras.backend.random_bernoulli instead.
return dispatch_target(*args, **kwargs)

tests/unit/tf/models/test_base.py::test_freeze_parallel_block[True]
tests/unit/tf/models/test_base.py::test_freeze_sequential_block
tests/unit/tf/models/test_base.py::test_freeze_unfreeze
tests/unit/tf/models/test_base.py::test_unfreeze_all_blocks
/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/gradient_descent.py:108: UserWarning: The lr argument is deprecated, use learning_rate instead.
super(SGD, self).init(name, **kwargs)

tests/unit/tf/models/test_base.py::test_retrieval_model_query
tests/unit/tf/models/test_base.py::test_retrieval_model_query
tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_v2_export_embeddings
tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[True]
tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[False]
/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/utils/tf_utils.py:298: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack
tensor_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(tensor)))

tests/unit/tf/models/test_ranking.py::test_deepfm_model_only_categ_feats[False]
tests/unit/tf/models/test_ranking.py::test_deepfm_model_categ_and_continuous_feats[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/models/test_ranking.py::test_wide_deep_model[False]
tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_categorical_one_hot[False]
tests/unit/tf/models/test_ranking.py::test_wide_deep_model_hashed_cross[False]
tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[True]
tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]
/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/transforms/features.py:569: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag
warnings.warn(

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/autograph/impl/api.py:371: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag
return py_builtins.overload_of(f)(*args)

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_onehot_multihot_feature_interaction[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_feature_interaction_multi_optimizer[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask/GatherV2:0", shape=(None, 48), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_3:0", shape=(None,), dtype=int64), values=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_2:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/torch/block/test_mlp.py::test_mlp_block
/var/jenkins_home/workspace/merlin_models/models/tests/unit/torch/_conftest.py:151: UserWarning: Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at ../torch/csrc/utils/tensor_new.cpp:201.)
return {key: torch.tensor(value) for key, value in data.items()}

tests/unit/xgb/test_xgboost.py::test_without_dask_client
tests/unit/xgb/test_xgboost.py::TestXGBoost::test_music_regression
tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs0-DaskDeviceQuantileDMatrix]
tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs1-DaskDMatrix]
tests/unit/xgb/test_xgboost.py::TestEvals::test_multiple
tests/unit/xgb/test_xgboost.py::TestEvals::test_default
tests/unit/xgb/test_xgboost.py::TestEvals::test_train_and_valid
tests/unit/xgb/test_xgboost.py::TestEvals::test_invalid_data
/var/jenkins_home/workspace/merlin_models/models/merlin/models/xgb/init.py:344: UserWarning: Ignoring list columns as inputs to XGBoost model: ['item_genres', 'user_genres'].
warnings.warn(f"Ignoring list columns as inputs to XGBoost model: {list_column_names}.")

tests/unit/xgb/test_xgboost.py::TestXGBoost::test_unsupported_objective
/var/jenkins_home/workspace/merlin_models/models/.tox/test-gpu/lib/python3.8/site-packages/tornado/ioloop.py:350: DeprecationWarning: make_current is deprecated; start the event loop first
self.make_current()

tests/unit/xgb/test_xgboost.py: 14 warnings
/usr/local/lib/python3.8/dist-packages/xgboost/dask.py:884: RuntimeWarning: coroutine 'Client._wait_for_workers' was never awaited
client.wait_for_workers(n_workers)
Enable tracemalloc to get traceback where the object was allocated.
See https://docs.pytest.org/en/stable/how-to/capture-warnings.html#resource-warnings for more info.

tests/unit/xgb/test_xgboost.py: 11 warnings
/usr/local/lib/python3.8/dist-packages/cudf/core/dataframe.py:1183: DeprecationWarning: The default dtype for empty Series will be 'object' instead of 'float64' in a future version. Specify a dtype explicitly to silence this warning.
mask = pd.Series(mask)

-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html

---------- coverage: platform linux, python 3.8.10-final-0 -----------
Name Stmts Miss Cover

merlin/datasets/init.py 2 0 100%
merlin/datasets/advertising/init.py 2 0 100%
merlin/datasets/advertising/criteo/init.py 0 0 100%
merlin/datasets/advertising/criteo/dataset.py 79 60 24%
merlin/datasets/advertising/criteo/transformed/init.py 0 0 100%
merlin/datasets/ecommerce/init.py 3 0 100%
merlin/datasets/ecommerce/aliccp/init.py 0 0 100%
merlin/datasets/ecommerce/aliccp/dataset.py 141 87 38%
merlin/datasets/ecommerce/aliccp/raw/init.py 0 0 100%
merlin/datasets/ecommerce/aliccp/transformed/init.py 0 0 100%
merlin/datasets/ecommerce/dressipi/init.py 0 0 100%
merlin/datasets/ecommerce/dressipi/dataset.py 45 37 18%
merlin/datasets/ecommerce/dressipi/preprocessed/init.py 0 0 100%
merlin/datasets/ecommerce/large/init.py 0 0 100%
merlin/datasets/ecommerce/small/init.py 0 0 100%
merlin/datasets/ecommerce/transactions/init.py 0 0 100%
merlin/datasets/entertainment/init.py 2 0 100%
merlin/datasets/entertainment/movielens/1m-raw/init.py 0 0 100%
merlin/datasets/entertainment/movielens/1m-raw/ratings/init.py 0 0 100%
merlin/datasets/entertainment/movielens/1m/init.py 0 0 100%
merlin/datasets/entertainment/movielens/25m/init.py 0 0 100%
merlin/datasets/entertainment/movielens/100k/init.py 0 0 100%
merlin/datasets/entertainment/movielens/init.py 0 0 100%
merlin/datasets/entertainment/movielens/dataset.py 152 122 20%
merlin/datasets/entertainment/music_streaming/init.py 0 0 100%
merlin/datasets/social/init.py 0 0 100%
merlin/datasets/synthetic.py 147 15 90%
merlin/datasets/testing/init.py 0 0 100%
merlin/datasets/testing/sequence_testing/init.py 0 0 100%
merlin/models/init.py 2 0 100%
merlin/models/_version.py 354 205 42%
merlin/models/api.py 14 5 64%
merlin/models/config/init.py 0 0 100%
merlin/models/config/schema.py 62 0 100%
merlin/models/implicit/init.py 27 4 85%
merlin/models/io.py 15 0 100%
merlin/models/lightfm/init.py 23 0 100%
merlin/models/loader/init.py 0 0 100%
merlin/models/loader/backend.py 379 42 89%
merlin/models/loader/dataframe_iter.py 21 17 19%
merlin/models/loader/tf_utils.py 57 27 53%
merlin/models/loader/utils.py 40 15 62%
merlin/models/tf/init.py 70 0 100%
merlin/models/tf/blocks/init.py 0 0 100%
merlin/models/tf/blocks/cross.py 44 0 100%
merlin/models/tf/blocks/dlrm.py 49 2 96%
merlin/models/tf/blocks/experts.py 99 17 83%
merlin/models/tf/blocks/interaction.py 108 40 63%
merlin/models/tf/blocks/mlp.py 114 10 91%
merlin/models/tf/blocks/optimizer.py 173 13 92%
merlin/models/tf/blocks/retrieval/init.py 0 0 100%
merlin/models/tf/blocks/retrieval/base.py 169 62 63%
merlin/models/tf/blocks/retrieval/matrix_factorization.py 35 1 97%
merlin/models/tf/blocks/retrieval/two_tower.py 30 0 100%
merlin/models/tf/blocks/sampling/init.py 0 0 100%
merlin/models/tf/blocks/sampling/base.py 29 2 93%
merlin/models/tf/blocks/sampling/cross_batch.py 46 2 96%
merlin/models/tf/blocks/sampling/in_batch.py 35 0 100%
merlin/models/tf/blocks/sampling/queue.py 115 12 90%
merlin/models/tf/core/init.py 0 0 100%
merlin/models/tf/core/aggregation.py 241 49 80%
merlin/models/tf/core/base.py 244 55 77%
merlin/models/tf/core/combinators.py 426 53 88%
merlin/models/tf/core/encoder.py 170 29 83%
merlin/models/tf/core/index.py 104 16 85%
merlin/models/tf/core/prediction.py 50 1 98%
merlin/models/tf/core/tabular.py 280 29 90%
merlin/models/tf/inputs/init.py 0 0 100%
merlin/models/tf/inputs/base.py 60 10 83%
merlin/models/tf/inputs/continuous.py 39 3 92%
merlin/models/tf/inputs/embedding.py 458 31 93%
merlin/models/tf/loader.py 245 73 70%
merlin/models/tf/losses/init.py 4 0 100%
merlin/models/tf/losses/base.py 9 0 100%
merlin/models/tf/losses/listwise.py 13 0 100%
merlin/models/tf/losses/pairwise.py 115 1 99%
merlin/models/tf/metrics/init.py 2 0 100%
merlin/models/tf/metrics/evaluation.py 105 48 54%
merlin/models/tf/metrics/topk.py 198 48 76%
merlin/models/tf/models/init.py 0 0 100%
merlin/models/tf/models/base.py 708 75 89%
merlin/models/tf/models/benchmark.py 16 0 100%
merlin/models/tf/models/ranking.py 67 3 96%
merlin/models/tf/models/retrieval.py 78 4 95%
merlin/models/tf/models/utils.py 10 1 90%
merlin/models/tf/outputs/init.py 0 0 100%
merlin/models/tf/outputs/base.py 122 17 86%
merlin/models/tf/outputs/classification.py 91 1 99%
merlin/models/tf/outputs/contrastive.py 147 10 93%
merlin/models/tf/outputs/regression.py 9 0 100%
merlin/models/tf/outputs/sampling/init.py 0 0 100%
merlin/models/tf/outputs/sampling/base.py 78 21 73%
merlin/models/tf/outputs/sampling/in_batch.py 37 1 97%
merlin/models/tf/outputs/sampling/popularity.py 27 1 96%
merlin/models/tf/outputs/topk.py 97 6 94%
merlin/models/tf/prediction_tasks/init.py 0 0 100%
merlin/models/tf/prediction_tasks/base.py 207 37 82%
merlin/models/tf/prediction_tasks/classification.py 68 17 75%
merlin/models/tf/prediction_tasks/multi.py 7 0 100%
merlin/models/tf/prediction_tasks/next_item.py 59 6 90%
merlin/models/tf/prediction_tasks/regression.py 35 2 94%
merlin/models/tf/prediction_tasks/retrieval.py 73 3 96%
merlin/models/tf/transformers/init.py 0 0 100%
merlin/models/tf/transformers/block.py 101 2 98%
merlin/models/tf/transformers/transforms.py 63 0 100%
merlin/models/tf/transforms/init.py 0 0 100%
merlin/models/tf/transforms/bias.py 111 9 92%
merlin/models/tf/transforms/features.py 435 36 92%
merlin/models/tf/transforms/negative_sampling.py 77 3 96%
merlin/models/tf/transforms/noise.py 43 1 98%
merlin/models/tf/transforms/regularization.py 17 1 94%
merlin/models/tf/transforms/sequence.py 282 42 85%
merlin/models/tf/transforms/tensor.py 158 13 92%
merlin/models/tf/typing.py 7 0 100%
merlin/models/tf/utils/init.py 0 0 100%
merlin/models/tf/utils/batch_utils.py 85 4 95%
merlin/models/tf/utils/repr_utils.py 69 4 94%
merlin/models/tf/utils/search_utils.py 34 22 35%
merlin/models/tf/utils/testing_utils.py 206 36 83%
merlin/models/tf/utils/tf_utils.py 209 42 80%
merlin/models/torch/init.py 12 0 100%
merlin/models/torch/block/init.py 0 0 100%
merlin/models/torch/block/base.py 167 32 81%
merlin/models/torch/block/mlp.py 38 5 87%
merlin/models/torch/dataset.py 68 5 93%
merlin/models/torch/features/init.py 0 0 100%
merlin/models/torch/features/base.py 4 0 100%
merlin/models/torch/features/continuous.py 22 0 100%
merlin/models/torch/features/embedding.py 165 12 93%
merlin/models/torch/features/tabular.py 65 8 88%
merlin/models/torch/losses.py 28 28 0%
merlin/models/torch/model/init.py 0 0 100%
merlin/models/torch/model/base.py 286 65 77%
merlin/models/torch/model/prediction_task.py 24 0 100%
merlin/models/torch/tabular/init.py 0 0 100%
merlin/models/torch/tabular/aggregation.py 75 0 100%
merlin/models/torch/tabular/base.py 247 39 84%
merlin/models/torch/tabular/transformations.py 67 3 96%
merlin/models/torch/typing.py 6 0 100%
merlin/models/torch/utils/init.py 0 0 100%
merlin/models/torch/utils/data_utils.py 117 117 0%
merlin/models/torch/utils/examples_utils.py 39 39 0%
merlin/models/torch/utils/torch_utils.py 80 22 72%
merlin/models/utils/init.py 0 0 100%
merlin/models/utils/constants.py 3 0 100%
merlin/models/utils/dataset.py 38 4 89%
merlin/models/utils/dependencies.py 26 19 27%
merlin/models/utils/doc_utils.py 10 0 100%
merlin/models/utils/example_utils.py 31 2 94%
merlin/models/utils/misc_utils.py 118 90 24%
merlin/models/utils/nvt_utils.py 27 24 11%
merlin/models/utils/registry.py 101 29 71%
merlin/models/utils/schema_utils.py 90 19 79%
merlin/models/xgb/init.py 124 4 97%

TOTAL 11357 2229 80%

=========================== short test summary info ============================
SKIPPED [1] tests/unit/datasets/test_advertising.py:20: No data-dir available, pass it through env variable $INPUT_DATA_DIR
SKIPPED [1] tests/unit/datasets/test_ecommerce.py:62: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP
SKIPPED [1] tests/unit/datasets/test_ecommerce.py:78: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP
SKIPPED [1] tests/unit/datasets/test_ecommerce.py:92: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP
SKIPPED [3] tests/unit/datasets/test_entertainment.py:44: No data-dir available, pass it through env variable $INPUT_DATA_DIR
SKIPPED [5] ../../../.local/lib/python3.8/site-packages/tensorflow/python/framework/test_util.py:2746: Not a test.
========= 824 passed, 12 skipped, 1349 warnings in 1613.07s (0:26:53) ==========
___________________________________ summary ____________________________________
test-gpu: commands succeeded
congratulations :)
Performing Post build task...
Match found for : : True
Logical operation result is TRUE
Running script : #!/bin/bash
cd /var/jenkins_home/
CUDA_VISIBLE_DEVICES=1 python test_res_push.py "https://api.GitHub.com/repos/NVIDIA-Merlin/models/issues/$ghprbPullId/comments" "/var/jenkins_home/jobs/$JOB_NAME/builds/$BUILD_NUMBER/log"
[merlin_models] $ /bin/bash /tmp/jenkins11027933638706359453.sh

@nvidia-merlin-bot
Copy link

Click to view CI Results
GitHub pull request #855 of commit f33cef0b2fe4296459d0779585c26818728984e5, no merge conflicts.
Running as SYSTEM
Setting status of f33cef0b2fe4296459d0779585c26818728984e5 to PENDING with url https://10.20.13.93:8080/job/merlin_models/1739/console and message: 'Pending'
Using context: Jenkins
Building on master in workspace /var/jenkins_home/workspace/merlin_models
using credential nvidia-merlin-bot
 > git rev-parse --is-inside-work-tree # timeout=10
Fetching changes from the remote Git repository
 > git config remote.origin.url https://github.com/NVIDIA-Merlin/models/ # timeout=10
Fetching upstream changes from https://github.com/NVIDIA-Merlin/models/
 > git --version # timeout=10
using GIT_ASKPASS to set credentials This is the bot credentials for our CI/CD
 > git fetch --tags --force --progress -- https://github.com/NVIDIA-Merlin/models/ +refs/pull/855/*:refs/remotes/origin/pr/855/* # timeout=10
 > git rev-parse f33cef0b2fe4296459d0779585c26818728984e5^{commit} # timeout=10
Checking out Revision f33cef0b2fe4296459d0779585c26818728984e5 (detached)
 > git config core.sparsecheckout # timeout=10
 > git checkout -f f33cef0b2fe4296459d0779585c26818728984e5 # timeout=10
Commit message: "precommit"
 > git rev-list --no-walk be50ba36745ce354af88b3356278d4d4abad4597 # timeout=10
[merlin_models] $ /bin/bash /tmp/jenkins9362342120461176720.sh
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Requirement already satisfied: testbook in /usr/local/lib/python3.8/dist-packages (0.4.2)
Requirement already satisfied: nbformat>=5.0.4 in /usr/local/lib/python3.8/dist-packages (from testbook) (5.5.0)
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Requirement already satisfied: jupyter-client>=6.1.5 in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (7.3.5)
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Requirement already satisfied: pkgutil-resolve-name>=1.3.10 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (1.3.10)
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Requirement already satisfied: entrypoints in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (0.4)
Requirement already satisfied: zipp>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from importlib-resources>=1.4.0->jsonschema>=2.6->nbformat>=5.0.4->testbook) (3.8.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.8.2->jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (1.15.0)
GLOB sdist-make: /var/jenkins_home/workspace/merlin_models/models/setup.py
test-gpu inst-nodeps: /var/jenkins_home/workspace/merlin_models/models/.tox/.tmp/package/2/merlin-models-0.9.0+30.gf33cef0b.zip
WARNING: Discarding $PYTHONPATH from environment, to override specify PYTHONPATH in 'passenv' in your configuration.
test-gpu installed: absl-py==1.2.0,aiohttp==3.8.1,aiosignal==1.2.0,alabaster==0.7.12,alembic==1.8.1,anyio==3.6.1,appdirs==1.4.4,argon2-cffi==21.3.0,argon2-cffi-bindings==21.2.0,astroid==2.5.6,asttokens==2.0.8,astunparse==1.6.3,asv==0.5.1,asvdb==0.4.2,async-timeout==4.0.2,attrs==22.1.0,autopage==0.5.1,awscli==1.27.2,Babel==2.10.3,backcall==0.2.0,beautifulsoup4==4.11.1,betterproto==1.2.5,black==20.8b1,bleach==5.0.1,boto3==1.24.75,botocore==1.29.2,Brotli==1.0.9,build==0.9.0,cachetools==5.2.0,certifi==2019.11.28,cffi==1.15.1,chardet==3.0.4,charset-normalizer==2.1.1,check-manifest==0.48,clang==5.0,click==8.1.3,cliff==4.0.0,cloudpickle==2.2.0,cmaes==0.8.2,cmake==3.24.1.1,cmd2==2.4.2,colorama==0.4.4,colorlog==6.7.0,contourpy==1.0.5,coverage==6.5.0,cuda-python==11.7.1,cupy-cuda117==10.6.0,cycler==0.11.0,Cython==0.29.32,dask==2022.1.1,dbus-python==1.2.16,debugpy==1.6.3,decorator==5.1.1,defusedxml==0.7.1,dill==0.3.5.1,distlib==0.3.6,distributed==2022.5.1,distro==1.7.0,dm-tree==0.1.6,docker-pycreds==0.4.0,docutils==0.16,emoji==1.7.0,entrypoints==0.4,execnet==1.9.0,executing==1.0.0,faiss==1.7.2,faiss-gpu==1.7.2,fastai==2.7.9,fastapi==0.85.0,fastavro==1.6.1,fastcore==1.5.27,fastdownload==0.0.7,fastjsonschema==2.16.1,fastprogress==1.0.3,fastrlock==0.8,feast==0.19.4,fiddle==0.2.2,filelock==3.8.0,flake8==5.0.4,flatbuffers==1.12,fonttools==4.37.3,frozenlist==1.3.1,fsspec==2022.5.0,gast==0.4.0,gevent==21.12.0,geventhttpclient==2.0.2,gitdb==4.0.9,GitPython==3.1.27,google==3.0.0,google-api-core==2.10.1,google-auth==2.11.1,google-auth-oauthlib==0.4.6,google-pasta==0.2.0,googleapis-common-protos==1.52.0,graphviz==0.20.1,greenlet==1.1.3,grpcio==1.41.0,grpcio-channelz==1.49.0,grpcio-reflection==1.48.1,grpclib==0.4.3,h11==0.13.0,h2==4.1.0,h5py==3.7.0,HeapDict==1.0.1,horovod==0.26.1,hpack==4.0.0,httptools==0.5.0,hugectr2onnx==0.0.0,huggingface-hub==0.9.1,hyperframe==6.0.1,idna==2.8,imagesize==1.4.1,implicit==0.6.1,importlib-metadata==4.12.0,importlib-resources==5.9.0,iniconfig==1.1.1,interrogate==1.5.0,ipykernel==6.15.3,ipython==8.5.0,ipython-genutils==0.2.0,ipywidgets==7.7.0,isort==5.10.1,jedi==0.18.1,Jinja2==3.1.2,jmespath==1.0.1,joblib==1.2.0,json5==0.9.10,jsonschema==4.16.0,jupyter==1.0.0,jupyter-cache==0.4.3,jupyter-console==6.4.4,jupyter-core==4.11.1,jupyter-server==1.18.1,jupyter-server-mathjax==0.2.5,jupyter-sphinx==0.3.2,jupyter_client==7.3.5,jupyterlab==3.4.7,jupyterlab-pygments==0.2.2,jupyterlab-widgets==1.1.0,jupyterlab_server==2.15.1,keras==2.9.0,Keras-Preprocessing==1.1.2,kiwisolver==1.4.4,lazy-object-proxy==1.8.0,libclang==14.0.6,libcst==0.4.7,lightfm==1.16,lightgbm==3.3.2,linkify-it-py==1.0.3,llvmlite==0.39.1,locket==1.0.0,lxml==4.9.1,Mako==1.2.3,Markdown==3.4.1,markdown-it-py==1.1.0,MarkupSafe==2.1.1,matplotlib==3.6.0,matplotlib-inline==0.1.6,mccabe==0.7.0,mdit-py-plugins==0.2.8,merlin-core==0.6.0+1.g5926fcf,merlin-dataloader @ git+https://github.com/NVIDIA-Merlin/dataloader.git@61ca2edae832da4eb2c6b93390c24920e68de1ae,merlin-models==0.9.0+30.gf33cef0b,merlin-systems==0.5.0+4.g15074ad,mistune==2.0.4,mmh3==3.0.0,mpi4py==3.1.3,msgpack==1.0.4,multidict==6.0.2,mypy==0.982,mypy-extensions==0.4.3,myst-nb==0.13.2,myst-parser==0.15.2,natsort==8.1.0,nbclassic==0.4.3,nbclient==0.6.8,nbconvert==7.0.0,nbdime==3.1.1,nbformat==5.5.0,nest-asyncio==1.5.5,ninja==1.10.2.3,notebook==6.4.12,notebook-shim==0.1.0,numba==0.56.2,numpy==1.22.4,nvidia-pyindex==1.0.9,# Editable install with no version control (nvtabular==1.4.0+8.g95e12d347),-e /usr/local/lib/python3.8/dist-packages,nvtx==0.2.5,oauthlib==3.2.1,oldest-supported-numpy==2022.8.16,onnx==1.12.0,onnxruntime==1.11.1,opt-einsum==3.3.0,optuna==3.0.3,packaging==21.3,pandas==1.3.5,pandavro==1.5.2,pandocfilters==1.5.0,parso==0.8.3,partd==1.3.0,pathspec==0.10.1,pathtools==0.1.2,pbr==5.11.0,pep517==0.13.0,pexpect==4.8.0,pickleshare==0.7.5,Pillow==9.2.0,pkgutil_resolve_name==1.3.10,platformdirs==2.5.2,plotly==5.11.0,pluggy==1.0.0,prettytable==3.5.0,prometheus-client==0.14.1,promise==2.3,prompt-toolkit==3.0.31,proto-plus==1.19.6,protobuf==3.19.5,psutil==5.9.2,ptyprocess==0.7.0,pure-eval==0.2.2,py==1.11.0,pyarrow==7.0.0,pyasn1==0.4.8,pyasn1-modules==0.2.8,pybind11==2.10.0,pycodestyle==2.9.1,pycparser==2.21,pydantic==1.10.2,pydot==1.4.2,pyflakes==2.5.0,Pygments==2.13.0,PyGObject==3.36.0,pynvml==11.4.1,pyparsing==3.0.9,pyperclip==1.8.2,pyrsistent==0.18.1,pytest==7.1.3,pytest-cov==4.0.0,pytest-xdist==3.0.2,python-apt==2.0.0+ubuntu0.20.4.8,python-dateutil==2.8.2,python-dotenv==0.21.0,python-rapidjson==1.8,pytz==2022.2.1,PyYAML==5.4.1,pyzmq==24.0.0,qtconsole==5.3.2,QtPy==2.2.1,regex==2022.9.13,requests==2.22.0,requests-oauthlib==1.3.1,requests-unixsocket==0.2.0,rsa==4.7.2,s3fs==2022.2.0,s3transfer==0.6.0,sacremoses==0.0.53,scikit-build==0.15.0,scikit-learn==1.1.2,scipy==1.8.1,seedir==0.3.0,Send2Trash==1.8.0,sentry-sdk==1.9.8,setproctitle==1.3.2,setuptools-scm==7.0.5,shortuuid==1.0.9,six==1.15.0,sklearn==0.0,smmap==5.0.0,sniffio==1.3.0,snowballstemmer==2.2.0,sortedcontainers==2.4.0,soupsieve==2.3.2.post1,Sphinx==5.3.0,sphinx-multiversion==0.2.4,sphinx-togglebutton==0.3.1,sphinx_external_toc==0.3.0,sphinxcontrib-applehelp==1.0.2,sphinxcontrib-copydirs @ git+https://github.com/mikemckiernan/sphinxcontrib-copydirs.git@bd8c5d79b3f91cf5f1bb0d6995aeca3fe84b670e,sphinxcontrib-devhelp==1.0.2,sphinxcontrib-htmlhelp==2.0.0,sphinxcontrib-jsmath==1.0.1,sphinxcontrib-qthelp==1.0.3,sphinxcontrib-serializinghtml==1.1.5,SQLAlchemy==1.4.42,stack-data==0.5.0,starlette==0.20.4,stevedore==4.1.0,stringcase==1.2.0,supervisor==4.1.0,tabulate==0.8.10,tblib==1.7.0,tdqm==0.0.1,tenacity==8.0.1,tensorboard==2.9.1,tensorboard-data-server==0.6.1,tensorboard-plugin-wit==1.8.1,tensorflow==2.9.2,tensorflow-estimator==2.9.0,tensorflow-gpu==2.9.2,tensorflow-io-gcs-filesystem==0.27.0,tensorflow-metadata==1.10.0,tensorflow-ranking==0.5.1,tensorflow-serving-api==2.9.2,termcolor==2.0.1,terminado==0.15.0,testbook==0.4.2,threadpoolctl==3.1.0,tinycss2==1.1.1,tokenizers==0.10.3,toml==0.10.2,tomli==2.0.1,toolz==0.12.0,torch==1.12.1+cu113,torchmetrics==0.3.2,tornado==6.2,tox==3.26.0,tqdm==4.64.1,traitlets==5.4.0,transformers==4.12.0,transformers4rec==0.1.12+2.gbcc939255,treelite==2.3.0,treelite-runtime==2.3.0,tritonclient==2.25.0,typed-ast==1.5.4,typing-inspect==0.8.0,typing_extensions==4.3.0,uc-micro-py==1.0.1,urllib3==1.26.12,uvicorn==0.18.3,uvloop==0.17.0,versioneer==0.20,virtualenv==20.16.5,wandb==0.13.3,watchfiles==0.17.0,wcwidth==0.2.5,webencodings==0.5.1,websocket-client==1.4.1,websockets==10.3,Werkzeug==2.2.2,widgetsnbextension==3.6.0,wrapt==1.12.1,xgboost==1.6.2,yarl==1.8.1,zict==2.2.0,zipp==3.8.1,zope.event==4.5.0,zope.interface==5.4.0
test-gpu run-test-pre: PYTHONHASHSEED='2416948510'
test-gpu run-test: commands[0] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/core.git
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Collecting git+https://github.com/NVIDIA-Merlin/core.git
  Cloning https://github.com/NVIDIA-Merlin/core.git to /tmp/pip-req-build-h19ls_lp
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/core.git /tmp/pip-req-build-h19ls_lp
  Resolved https://github.com/NVIDIA-Merlin/core.git to commit 563be4bf5ef675940d5fff2b5e4666424a7f7947
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: numba>=0.54 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+5.g563be4b) (0.55.1)
Requirement already satisfied: dask>=2022.3.0 in ./.tox/test-gpu/lib/python3.8/site-packages (from merlin-core==0.8.0+5.g563be4b) (2022.3.0)
Requirement already satisfied: protobuf>=3.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+5.g563be4b) (3.19.5)
Requirement already satisfied: fsspec==2022.5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+5.g563be4b) (2022.5.0)
Requirement already satisfied: betterproto<2.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+5.g563be4b) (1.2.5)
Requirement already satisfied: pandas<1.4.0dev0,>=1.2.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+5.g563be4b) (1.3.5)
Requirement already satisfied: tqdm>=4.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+5.g563be4b) (4.64.1)
Requirement already satisfied: distributed>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+5.g563be4b) (2022.3.0)
Requirement already satisfied: pyarrow>=5.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+5.g563be4b) (7.0.0)
Requirement already satisfied: packaging in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+5.g563be4b) (21.3)
Requirement already satisfied: tensorflow-metadata>=1.2.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+5.g563be4b) (1.10.0)
Requirement already satisfied: stringcase in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core==0.8.0+5.g563be4b) (1.2.0)
Requirement already satisfied: grpclib in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core==0.8.0+5.g563be4b) (0.4.3)
Requirement already satisfied: partd>=0.3.10 in /var/jenkins_home/.local/lib/python3.8/site-packages/partd-1.2.0-py3.8.egg (from dask>=2022.3.0->merlin-core==0.8.0+5.g563be4b) (1.2.0)
Requirement already satisfied: toolz>=0.8.2 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core==0.8.0+5.g563be4b) (0.12.0)
Requirement already satisfied: pyyaml>=5.3.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/PyYAML-5.4.1-py3.8-linux-x86_64.egg (from dask>=2022.3.0->merlin-core==0.8.0+5.g563be4b) (5.4.1)
Requirement already satisfied: cloudpickle>=1.1.1 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core==0.8.0+5.g563be4b) (2.2.0)
Requirement already satisfied: msgpack>=0.6.0 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+5.g563be4b) (1.0.4)
Requirement already satisfied: click>=6.6 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+5.g563be4b) (8.1.3)
Requirement already satisfied: tornado>=6.0.3 in ./.tox/test-gpu/lib/python3.8/site-packages (from distributed>=2022.3.0->merlin-core==0.8.0+5.g563be4b) (6.2)
Requirement already satisfied: sortedcontainers!=2.0.0,!=2.0.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/sortedcontainers-2.4.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+5.g563be4b) (2.4.0)
Requirement already satisfied: psutil>=5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/psutil-5.8.0-py3.8-linux-x86_64.egg (from distributed>=2022.3.0->merlin-core==0.8.0+5.g563be4b) (5.8.0)
Requirement already satisfied: jinja2 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+5.g563be4b) (3.1.2)
Requirement already satisfied: tblib>=1.6.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/tblib-1.7.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+5.g563be4b) (1.7.0)
Requirement already satisfied: zict>=0.1.3 in /var/jenkins_home/.local/lib/python3.8/site-packages/zict-2.0.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+5.g563be4b) (2.0.0)
Requirement already satisfied: numpy<1.22,>=1.18 in /var/jenkins_home/.local/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+5.g563be4b) (1.20.3)
Requirement already satisfied: setuptools in ./.tox/test-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+5.g563be4b) (59.8.0)
Requirement already satisfied: llvmlite<0.39,>=0.38.0rc1 in ./.tox/test-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+5.g563be4b) (0.38.1)
Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in /usr/local/lib/python3.8/dist-packages (from packaging->merlin-core==0.8.0+5.g563be4b) (3.0.9)
Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+5.g563be4b) (2.8.2)
Requirement already satisfied: pytz>=2017.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+5.g563be4b) (2022.2.1)
Requirement already satisfied: absl-py<2.0.0,>=0.9 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core==0.8.0+5.g563be4b) (1.2.0)
Requirement already satisfied: googleapis-common-protos<2,>=1.52.0 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core==0.8.0+5.g563be4b) (1.52.0)
Requirement already satisfied: locket in /var/jenkins_home/.local/lib/python3.8/site-packages/locket-0.2.1-py3.8.egg (from partd>=0.3.10->dask>=2022.3.0->merlin-core==0.8.0+5.g563be4b) (0.2.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.7.3->pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+5.g563be4b) (1.15.0)
Requirement already satisfied: heapdict in /var/jenkins_home/.local/lib/python3.8/site-packages/HeapDict-1.0.1-py3.8.egg (from zict>=0.1.3->distributed>=2022.3.0->merlin-core==0.8.0+5.g563be4b) (1.0.1)
Requirement already satisfied: multidict in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core==0.8.0+5.g563be4b) (6.0.2)
Requirement already satisfied: h2<5,>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core==0.8.0+5.g563be4b) (4.1.0)
Requirement already satisfied: MarkupSafe>=2.0 in ./.tox/test-gpu/lib/python3.8/site-packages (from jinja2->distributed>=2022.3.0->merlin-core==0.8.0+5.g563be4b) (2.0.1)
Requirement already satisfied: hyperframe<7,>=6.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core==0.8.0+5.g563be4b) (6.0.1)
Requirement already satisfied: hpack<5,>=4.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core==0.8.0+5.g563be4b) (4.0.0)

[notice] A new release of pip available: 22.2.2 -> 22.3
[notice] To update, run: pip install --upgrade pip
test-gpu run-test: commands[1] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/nvtabular.git
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Collecting git+https://github.com/NVIDIA-Merlin/nvtabular.git
Cloning https://github.com/NVIDIA-Merlin/nvtabular.git to /tmp/pip-req-build-7x_vqww3
Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/nvtabular.git /tmp/pip-req-build-7x_vqww3
Resolved https://github.com/NVIDIA-Merlin/nvtabular.git to commit 8e7edbafd3006f56e73efdc0c01c4445ab57d028
Installing build dependencies: started
Installing build dependencies: finished with status 'done'
Getting requirements to build wheel: started
Getting requirements to build wheel: finished with status 'done'
Preparing metadata (pyproject.toml): started
Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: merlin-dataloader>=0.0.2 in ./.tox/test-gpu/lib/python3.8/site-packages (from nvtabular==1.6.0+3.g8e7edbaf) (0.0.2+2.g61ca2ed)
Requirement already satisfied: scipy in /usr/local/lib/python3.8/dist-packages (from nvtabular==1.6.0+3.g8e7edbaf) (1.8.1)
Requirement already satisfied: merlin-core>=0.2.0 in ./.tox/test-gpu/lib/python3.8/site-packages (from nvtabular==1.6.0+3.g8e7edbaf) (0.8.0+5.g563be4b)
Requirement already satisfied: numba>=0.54 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+3.g8e7edbaf) (0.55.1)
Requirement already satisfied: dask>=2022.3.0 in ./.tox/test-gpu/lib/python3.8/site-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+3.g8e7edbaf) (2022.3.0)
Requirement already satisfied: protobuf>=3.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+3.g8e7edbaf) (3.19.5)
Requirement already satisfied: fsspec==2022.5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+3.g8e7edbaf) (2022.5.0)
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[notice] A new release of pip available: 22.2.2 -> 22.3
[notice] To update, run: pip install --upgrade pip
test-gpu run-test: commands[2] | python -m pytest --cov-report term --cov merlin -rxs tests/unit
============================= test session starts ==============================
platform linux -- Python 3.8.10, pytest-7.1.3, pluggy-1.0.0
cachedir: .tox/test-gpu/.pytest_cache
rootdir: /var/jenkins_home/workspace/merlin_models/models, configfile: pyproject.toml
plugins: anyio-3.5.0, xdist-3.0.2, cov-4.0.0
collected 836 items

tests/unit/config/test_schema.py .... [ 0%]
tests/unit/datasets/test_advertising.py .s [ 0%]
tests/unit/datasets/test_ecommerce.py ..sss [ 1%]
tests/unit/datasets/test_entertainment.py ....sss. [ 2%]
tests/unit/datasets/test_social.py . [ 2%]
tests/unit/datasets/test_synthetic.py ...... [ 3%]
tests/unit/implicit/test_implicit.py . [ 3%]
tests/unit/lightfm/test_lightfm.py . [ 3%]
tests/unit/tf/test_core.py ...... [ 4%]
tests/unit/tf/test_loader.py ................ [ 5%]
tests/unit/tf/test_public_api.py . [ 6%]
tests/unit/tf/blocks/test_cross.py ........... [ 7%]
tests/unit/tf/blocks/test_dlrm.py .......... [ 8%]
tests/unit/tf/blocks/test_interactions.py ... [ 8%]
tests/unit/tf/blocks/test_mlp.py ................................. [ 12%]
tests/unit/tf/blocks/test_optimizer.py s................................ [ 16%]
..................... [ 19%]
tests/unit/tf/blocks/retrieval/test_base.py . [ 19%]
tests/unit/tf/blocks/retrieval/test_matrix_factorization.py .. [ 19%]
tests/unit/tf/blocks/retrieval/test_two_tower.py ............ [ 21%]
tests/unit/tf/blocks/sampling/test_cross_batch.py . [ 21%]
tests/unit/tf/blocks/sampling/test_in_batch.py . [ 21%]
tests/unit/tf/core/test_aggregation.py ......... [ 22%]
tests/unit/tf/core/test_base.py .. [ 22%]
tests/unit/tf/core/test_combinators.py s..................... [ 25%]
tests/unit/tf/core/test_encoder.py .. [ 25%]
tests/unit/tf/core/test_index.py ... [ 25%]
tests/unit/tf/core/test_prediction.py .. [ 26%]
tests/unit/tf/core/test_tabular.py ...... [ 26%]
tests/unit/tf/examples/test_01_getting_started.py . [ 27%]
tests/unit/tf/examples/test_02_dataschema.py . [ 27%]
tests/unit/tf/examples/test_03_exploring_different_models.py . [ 27%]
tests/unit/tf/examples/test_04_export_ranking_models.py . [ 27%]
tests/unit/tf/examples/test_05_export_retrieval_model.py . [ 27%]
tests/unit/tf/examples/test_06_advanced_own_architecture.py . [ 27%]
tests/unit/tf/examples/test_07_train_traditional_models.py . [ 27%]
tests/unit/tf/examples/test_usecase_accelerate_training_by_lazyadam.py . [ 27%]
[ 27%]
tests/unit/tf/examples/test_usecase_data_parallel.py . [ 27%]
tests/unit/tf/examples/test_usecase_ecommerce_session_based.py . [ 28%]
tests/unit/tf/examples/test_usecase_incremental_training_layer_freezing.py . [ 28%]
[ 28%]
tests/unit/tf/examples/test_usecase_pretrained_embeddings.py . [ 28%]
tests/unit/tf/examples/test_usecase_retrieval_with_hpo.py . [ 28%]
tests/unit/tf/inputs/test_continuous.py ........ [ 29%]
tests/unit/tf/inputs/test_embedding.py ................................. [ 33%]
........ [ 34%]
tests/unit/tf/inputs/test_tabular.py .................. [ 36%]
tests/unit/tf/layers/test_queue.py .............. [ 38%]
tests/unit/tf/losses/test_losses.py ....................... [ 40%]
tests/unit/tf/metrics/test_metrics_popularity.py ..... [ 41%]
tests/unit/tf/metrics/test_metrics_topk.py ......................... [ 44%]
tests/unit/tf/models/test_base.py s........................ [ 47%]
tests/unit/tf/models/test_benchmark.py .. [ 47%]
tests/unit/tf/models/test_ranking.py .................................. [ 51%]
tests/unit/tf/models/test_retrieval.py ................................. [ 55%]
.......................................... [ 60%]
tests/unit/tf/outputs/test_base.py ...... [ 61%]
tests/unit/tf/outputs/test_classification.py ...... [ 62%]
tests/unit/tf/outputs/test_contrastive.py .............. [ 63%]
tests/unit/tf/outputs/test_regression.py .. [ 64%]
tests/unit/tf/outputs/test_sampling.py .... [ 64%]
tests/unit/tf/outputs/test_topk.py . [ 64%]
tests/unit/tf/prediction_tasks/test_classification.py .. [ 64%]
tests/unit/tf/prediction_tasks/test_multi_task.py ................ [ 66%]
tests/unit/tf/prediction_tasks/test_next_item.py ..... [ 67%]
tests/unit/tf/prediction_tasks/test_regression.py ..... [ 68%]
tests/unit/tf/prediction_tasks/test_retrieval.py . [ 68%]
tests/unit/tf/prediction_tasks/test_sampling.py ...... [ 68%]
tests/unit/tf/transformers/test_block.py ..................... [ 71%]
tests/unit/tf/transformers/test_transforms.py .......... [ 72%]
tests/unit/tf/transforms/test_bias.py .. [ 72%]
tests/unit/tf/transforms/test_features.py s............................. [ 76%]
.......................s...... [ 80%]
tests/unit/tf/transforms/test_negative_sampling.py ......... [ 81%]
tests/unit/tf/transforms/test_noise.py ..... [ 81%]
tests/unit/tf/transforms/test_sequence.py .................... [ 84%]
tests/unit/tf/transforms/test_tensor.py ... [ 84%]
tests/unit/tf/utils/test_batch.py .... [ 84%]
tests/unit/tf/utils/test_dataset.py .. [ 85%]
tests/unit/tf/utils/test_tf_utils.py ..... [ 85%]
tests/unit/torch/test_dataset.py ......... [ 86%]
tests/unit/torch/test_public_api.py . [ 86%]
tests/unit/torch/block/test_base.py .... [ 87%]
tests/unit/torch/block/test_mlp.py . [ 87%]
tests/unit/torch/features/test_continuous.py .. [ 87%]
tests/unit/torch/features/test_embedding.py .............. [ 89%]
tests/unit/torch/features/test_tabular.py .... [ 89%]
tests/unit/torch/model/test_head.py ............ [ 91%]
tests/unit/torch/model/test_model.py .. [ 91%]
tests/unit/torch/tabular/test_aggregation.py ........ [ 92%]
tests/unit/torch/tabular/test_tabular.py ... [ 92%]
tests/unit/torch/tabular/test_transformations.py ....... [ 93%]
tests/unit/utils/test_schema_utils.py ................................ [ 97%]
tests/unit/xgb/test_xgboost.py .................... [100%]

=============================== warnings summary ===============================
../../../../../usr/lib/python3/dist-packages/requests/init.py:89
/usr/lib/python3/dist-packages/requests/init.py:89: RequestsDependencyWarning: urllib3 (1.26.12) or chardet (3.0.4) doesn't match a supported version!
warnings.warn("urllib3 ({}) or chardet ({}) doesn't match a supported "

../../../.local/lib/python3.8/site-packages/flatbuffers/compat.py:19
/var/jenkins_home/.local/lib/python3.8/site-packages/flatbuffers/compat.py:19: DeprecationWarning: the imp module is deprecated in favour of importlib; see the module's documentation for alternative uses
import imp

../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36
/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36: DeprecationWarning: NEAREST is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.NEAREST or Dither.NONE instead.
'nearest': pil_image.NEAREST,

../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37
/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37: DeprecationWarning: BILINEAR is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BILINEAR instead.
'bilinear': pil_image.BILINEAR,

../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38
/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38: DeprecationWarning: BICUBIC is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BICUBIC instead.
'bicubic': pil_image.BICUBIC,

../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39
/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39: DeprecationWarning: HAMMING is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.HAMMING instead.
'hamming': pil_image.HAMMING,

../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40
/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40: DeprecationWarning: BOX is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BOX instead.
'box': pil_image.BOX,

../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41
/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41: DeprecationWarning: LANCZOS is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.LANCZOS instead.
'lanczos': pil_image.LANCZOS,

tests/unit/datasets/test_advertising.py: 1 warning
tests/unit/datasets/test_ecommerce.py: 2 warnings
tests/unit/datasets/test_entertainment.py: 4 warnings
tests/unit/datasets/test_social.py: 1 warning
tests/unit/datasets/test_synthetic.py: 6 warnings
tests/unit/implicit/test_implicit.py: 1 warning
tests/unit/lightfm/test_lightfm.py: 1 warning
tests/unit/tf/test_core.py: 6 warnings
tests/unit/tf/test_loader.py: 1 warning
tests/unit/tf/blocks/test_cross.py: 5 warnings
tests/unit/tf/blocks/test_dlrm.py: 9 warnings
tests/unit/tf/blocks/test_interactions.py: 2 warnings
tests/unit/tf/blocks/test_mlp.py: 26 warnings
tests/unit/tf/blocks/test_optimizer.py: 30 warnings
tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings
tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings
tests/unit/tf/core/test_aggregation.py: 6 warnings
tests/unit/tf/core/test_base.py: 2 warnings
tests/unit/tf/core/test_combinators.py: 11 warnings
tests/unit/tf/core/test_encoder.py: 6 warnings
tests/unit/tf/core/test_index.py: 8 warnings
tests/unit/tf/core/test_prediction.py: 2 warnings
tests/unit/tf/inputs/test_continuous.py: 7 warnings
tests/unit/tf/inputs/test_embedding.py: 20 warnings
tests/unit/tf/inputs/test_tabular.py: 18 warnings
tests/unit/tf/models/test_base.py: 27 warnings
tests/unit/tf/models/test_benchmark.py: 2 warnings
tests/unit/tf/models/test_ranking.py: 38 warnings
tests/unit/tf/models/test_retrieval.py: 119 warnings
tests/unit/tf/outputs/test_base.py: 6 warnings
tests/unit/tf/outputs/test_classification.py: 6 warnings
tests/unit/tf/outputs/test_contrastive.py: 19 warnings
tests/unit/tf/outputs/test_regression.py: 2 warnings
tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings
tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings
tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings
tests/unit/tf/prediction_tasks/test_retrieval.py: 1 warning
tests/unit/tf/transformers/test_block.py: 15 warnings
tests/unit/tf/transforms/test_bias.py: 2 warnings
tests/unit/tf/transforms/test_features.py: 10 warnings
tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings
tests/unit/tf/transforms/test_noise.py: 1 warning
tests/unit/tf/transforms/test_sequence.py: 15 warnings
tests/unit/tf/utils/test_batch.py: 9 warnings
tests/unit/tf/utils/test_dataset.py: 2 warnings
tests/unit/torch/block/test_base.py: 4 warnings
tests/unit/torch/block/test_mlp.py: 1 warning
tests/unit/torch/features/test_continuous.py: 1 warning
tests/unit/torch/features/test_embedding.py: 4 warnings
tests/unit/torch/features/test_tabular.py: 4 warnings
tests/unit/torch/model/test_head.py: 12 warnings
tests/unit/torch/model/test_model.py: 2 warnings
tests/unit/torch/tabular/test_aggregation.py: 6 warnings
tests/unit/torch/tabular/test_transformations.py: 3 warnings
tests/unit/xgb/test_xgboost.py: 18 warnings
/var/jenkins_home/workspace/merlin_models/models/.tox/test-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.ITEM_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.ITEM: 'item'>, <Tags.ID: 'id'>].
warnings.warn(

tests/unit/datasets/test_ecommerce.py: 2 warnings
tests/unit/datasets/test_entertainment.py: 4 warnings
tests/unit/datasets/test_social.py: 1 warning
tests/unit/datasets/test_synthetic.py: 5 warnings
tests/unit/implicit/test_implicit.py: 1 warning
tests/unit/lightfm/test_lightfm.py: 1 warning
tests/unit/tf/test_core.py: 6 warnings
tests/unit/tf/test_loader.py: 1 warning
tests/unit/tf/blocks/test_cross.py: 5 warnings
tests/unit/tf/blocks/test_dlrm.py: 9 warnings
tests/unit/tf/blocks/test_interactions.py: 2 warnings
tests/unit/tf/blocks/test_mlp.py: 26 warnings
tests/unit/tf/blocks/test_optimizer.py: 30 warnings
tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings
tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings
tests/unit/tf/core/test_aggregation.py: 6 warnings
tests/unit/tf/core/test_base.py: 2 warnings
tests/unit/tf/core/test_combinators.py: 11 warnings
tests/unit/tf/core/test_encoder.py: 7 warnings
tests/unit/tf/core/test_index.py: 3 warnings
tests/unit/tf/core/test_prediction.py: 2 warnings
tests/unit/tf/inputs/test_continuous.py: 7 warnings
tests/unit/tf/inputs/test_embedding.py: 20 warnings
tests/unit/tf/inputs/test_tabular.py: 18 warnings
tests/unit/tf/models/test_base.py: 27 warnings
tests/unit/tf/models/test_benchmark.py: 2 warnings
tests/unit/tf/models/test_ranking.py: 36 warnings
tests/unit/tf/models/test_retrieval.py: 85 warnings
tests/unit/tf/outputs/test_base.py: 6 warnings
tests/unit/tf/outputs/test_classification.py: 6 warnings
tests/unit/tf/outputs/test_contrastive.py: 19 warnings
tests/unit/tf/outputs/test_regression.py: 2 warnings
tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings
tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings
tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings
tests/unit/tf/transformers/test_block.py: 9 warnings
tests/unit/tf/transforms/test_features.py: 10 warnings
tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings
tests/unit/tf/transforms/test_sequence.py: 15 warnings
tests/unit/tf/utils/test_batch.py: 7 warnings
tests/unit/tf/utils/test_dataset.py: 2 warnings
tests/unit/torch/block/test_base.py: 4 warnings
tests/unit/torch/block/test_mlp.py: 1 warning
tests/unit/torch/features/test_continuous.py: 1 warning
tests/unit/torch/features/test_embedding.py: 4 warnings
tests/unit/torch/features/test_tabular.py: 4 warnings
tests/unit/torch/model/test_head.py: 12 warnings
tests/unit/torch/model/test_model.py: 2 warnings
tests/unit/torch/tabular/test_aggregation.py: 6 warnings
tests/unit/torch/tabular/test_transformations.py: 2 warnings
tests/unit/xgb/test_xgboost.py: 17 warnings
/var/jenkins_home/workspace/merlin_models/models/.tox/test-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.USER_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.USER: 'user'>, <Tags.ID: 'id'>].
warnings.warn(

tests/unit/datasets/test_entertainment.py: 1 warning
tests/unit/implicit/test_implicit.py: 1 warning
tests/unit/lightfm/test_lightfm.py: 1 warning
tests/unit/tf/test_loader.py: 1 warning
tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings
tests/unit/tf/blocks/retrieval/test_two_tower.py: 2 warnings
tests/unit/tf/core/test_combinators.py: 11 warnings
tests/unit/tf/core/test_encoder.py: 2 warnings
tests/unit/tf/core/test_prediction.py: 1 warning
tests/unit/tf/inputs/test_continuous.py: 4 warnings
tests/unit/tf/inputs/test_embedding.py: 9 warnings
tests/unit/tf/inputs/test_tabular.py: 8 warnings
tests/unit/tf/models/test_ranking.py: 20 warnings
tests/unit/tf/models/test_retrieval.py: 10 warnings
tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings
tests/unit/tf/prediction_tasks/test_regression.py: 3 warnings
tests/unit/tf/transforms/test_negative_sampling.py: 9 warnings
tests/unit/xgb/test_xgboost.py: 12 warnings
/var/jenkins_home/workspace/merlin_models/models/.tox/test-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.SESSION_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.SESSION: 'session'>, <Tags.ID: 'id'>].
warnings.warn(

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export
tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export
tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export
tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export
tests/unit/tf/inputs/test_embedding.py::test_embedding_features_exporting_and_loading_pretrained_initializer
/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/inputs/embedding.py:968: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack
embeddings_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(embeddings)))

tests/unit/tf/blocks/retrieval/test_two_tower.py: 1 warning
tests/unit/tf/core/test_index.py: 4 warnings
tests/unit/tf/models/test_retrieval.py: 54 warnings
tests/unit/tf/prediction_tasks/test_next_item.py: 3 warnings
tests/unit/tf/utils/test_batch.py: 2 warnings
/tmp/autograph_generated_filew0wqybt0.py:8: DeprecationWarning: The 'warn' method is deprecated, use 'warning' instead
ag
.converted_call(ag__.ld(warnings).warn, ("The 'warn' method is deprecated, use 'warning' instead", ag__.ld(DeprecationWarning), 2), None, fscope)

tests/unit/tf/core/test_combinators.py::test_parallel_block_select_by_tags
/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/core/tabular.py:602: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated since Python 3.3, and in 3.10 it will stop working
elif isinstance(self.feature_names, collections.Sequence):

tests/unit/tf/core/test_encoder.py: 1 warning
tests/unit/tf/core/test_index.py: 5 warnings
tests/unit/tf/models/test_retrieval.py: 30 warnings
tests/unit/tf/utils/test_batch.py: 4 warnings
tests/unit/tf/utils/test_dataset.py: 1 warning
/var/jenkins_home/workspace/merlin_models/models/merlin/models/utils/dataset.py:75: DeprecationWarning: unique_rows_by_features is deprecated and will be removed in a future version. Please use unique_by_tag instead.
warnings.warn(

tests/unit/tf/models/test_base.py::test_model_pre_post[True]
tests/unit/tf/models/test_base.py::test_model_pre_post[False]
tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.1]
tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.3]
tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.5]
tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.7]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/util/dispatch.py:1082: UserWarning: tf.keras.backend.random_binomial is deprecated, and will be removed in a future version.Please use tf.keras.backend.random_bernoulli instead.
return dispatch_target(*args, **kwargs)

tests/unit/tf/models/test_base.py::test_freeze_parallel_block[True]
tests/unit/tf/models/test_base.py::test_freeze_sequential_block
tests/unit/tf/models/test_base.py::test_freeze_unfreeze
tests/unit/tf/models/test_base.py::test_unfreeze_all_blocks
/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/gradient_descent.py:108: UserWarning: The lr argument is deprecated, use learning_rate instead.
super(SGD, self).init(name, **kwargs)

tests/unit/tf/models/test_base.py::test_retrieval_model_query
tests/unit/tf/models/test_base.py::test_retrieval_model_query
tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_v2_export_embeddings
tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[True]
tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[False]
/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/utils/tf_utils.py:298: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack
tensor_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(tensor)))

tests/unit/tf/models/test_ranking.py::test_deepfm_model_only_categ_feats[False]
tests/unit/tf/models/test_ranking.py::test_deepfm_model_categ_and_continuous_feats[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/models/test_ranking.py::test_wide_deep_model[False]
tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_categorical_one_hot[False]
tests/unit/tf/models/test_ranking.py::test_wide_deep_model_hashed_cross[False]
tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[True]
tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]
/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/transforms/features.py:569: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag
warnings.warn(

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/autograph/impl/api.py:371: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag
return py_builtins.overload_of(f)(*args)

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_onehot_multihot_feature_interaction[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_feature_interaction_multi_optimizer[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask/GatherV2:0", shape=(None, 48), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_3:0", shape=(None,), dtype=int64), values=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_2:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/torch/block/test_mlp.py::test_mlp_block
/var/jenkins_home/workspace/merlin_models/models/tests/unit/torch/_conftest.py:151: UserWarning: Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at ../torch/csrc/utils/tensor_new.cpp:201.)
return {key: torch.tensor(value) for key, value in data.items()}

tests/unit/xgb/test_xgboost.py::test_without_dask_client
tests/unit/xgb/test_xgboost.py::TestXGBoost::test_music_regression
tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs0-DaskDeviceQuantileDMatrix]
tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs1-DaskDMatrix]
tests/unit/xgb/test_xgboost.py::TestEvals::test_multiple
tests/unit/xgb/test_xgboost.py::TestEvals::test_default
tests/unit/xgb/test_xgboost.py::TestEvals::test_train_and_valid
tests/unit/xgb/test_xgboost.py::TestEvals::test_invalid_data
/var/jenkins_home/workspace/merlin_models/models/merlin/models/xgb/init.py:344: UserWarning: Ignoring list columns as inputs to XGBoost model: ['item_genres', 'user_genres'].
warnings.warn(f"Ignoring list columns as inputs to XGBoost model: {list_column_names}.")

tests/unit/xgb/test_xgboost.py::TestXGBoost::test_unsupported_objective
/var/jenkins_home/workspace/merlin_models/models/.tox/test-gpu/lib/python3.8/site-packages/tornado/ioloop.py:350: DeprecationWarning: make_current is deprecated; start the event loop first
self.make_current()

tests/unit/xgb/test_xgboost.py: 14 warnings
/usr/local/lib/python3.8/dist-packages/xgboost/dask.py:884: RuntimeWarning: coroutine 'Client._wait_for_workers' was never awaited
client.wait_for_workers(n_workers)
Enable tracemalloc to get traceback where the object was allocated.
See https://docs.pytest.org/en/stable/how-to/capture-warnings.html#resource-warnings for more info.

tests/unit/xgb/test_xgboost.py: 11 warnings
/usr/local/lib/python3.8/dist-packages/cudf/core/dataframe.py:1183: DeprecationWarning: The default dtype for empty Series will be 'object' instead of 'float64' in a future version. Specify a dtype explicitly to silence this warning.
mask = pd.Series(mask)

-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html

---------- coverage: platform linux, python 3.8.10-final-0 -----------
Name Stmts Miss Cover

merlin/datasets/init.py 2 0 100%
merlin/datasets/advertising/init.py 2 0 100%
merlin/datasets/advertising/criteo/init.py 0 0 100%
merlin/datasets/advertising/criteo/dataset.py 79 60 24%
merlin/datasets/advertising/criteo/transformed/init.py 0 0 100%
merlin/datasets/ecommerce/init.py 3 0 100%
merlin/datasets/ecommerce/aliccp/init.py 0 0 100%
merlin/datasets/ecommerce/aliccp/dataset.py 141 87 38%
merlin/datasets/ecommerce/aliccp/raw/init.py 0 0 100%
merlin/datasets/ecommerce/aliccp/transformed/init.py 0 0 100%
merlin/datasets/ecommerce/dressipi/init.py 0 0 100%
merlin/datasets/ecommerce/dressipi/dataset.py 45 37 18%
merlin/datasets/ecommerce/dressipi/preprocessed/init.py 0 0 100%
merlin/datasets/ecommerce/large/init.py 0 0 100%
merlin/datasets/ecommerce/small/init.py 0 0 100%
merlin/datasets/ecommerce/transactions/init.py 0 0 100%
merlin/datasets/entertainment/init.py 2 0 100%
merlin/datasets/entertainment/movielens/1m-raw/init.py 0 0 100%
merlin/datasets/entertainment/movielens/1m-raw/ratings/init.py 0 0 100%
merlin/datasets/entertainment/movielens/1m/init.py 0 0 100%
merlin/datasets/entertainment/movielens/25m/init.py 0 0 100%
merlin/datasets/entertainment/movielens/100k/init.py 0 0 100%
merlin/datasets/entertainment/movielens/init.py 0 0 100%
merlin/datasets/entertainment/movielens/dataset.py 152 122 20%
merlin/datasets/entertainment/music_streaming/init.py 0 0 100%
merlin/datasets/social/init.py 0 0 100%
merlin/datasets/synthetic.py 147 15 90%
merlin/datasets/testing/init.py 0 0 100%
merlin/datasets/testing/sequence_testing/init.py 0 0 100%
merlin/models/init.py 2 0 100%
merlin/models/_version.py 354 205 42%
merlin/models/api.py 14 5 64%
merlin/models/config/init.py 0 0 100%
merlin/models/config/schema.py 62 0 100%
merlin/models/implicit/init.py 27 4 85%
merlin/models/io.py 15 0 100%
merlin/models/lightfm/init.py 23 0 100%
merlin/models/loader/init.py 0 0 100%
merlin/models/loader/backend.py 379 42 89%
merlin/models/loader/dataframe_iter.py 21 17 19%
merlin/models/loader/tf_utils.py 57 27 53%
merlin/models/loader/utils.py 40 15 62%
merlin/models/tf/init.py 70 0 100%
merlin/models/tf/blocks/init.py 0 0 100%
merlin/models/tf/blocks/cross.py 44 0 100%
merlin/models/tf/blocks/dlrm.py 49 2 96%
merlin/models/tf/blocks/experts.py 99 17 83%
merlin/models/tf/blocks/interaction.py 108 40 63%
merlin/models/tf/blocks/mlp.py 114 10 91%
merlin/models/tf/blocks/optimizer.py 173 13 92%
merlin/models/tf/blocks/retrieval/init.py 0 0 100%
merlin/models/tf/blocks/retrieval/base.py 169 62 63%
merlin/models/tf/blocks/retrieval/matrix_factorization.py 35 1 97%
merlin/models/tf/blocks/retrieval/two_tower.py 30 0 100%
merlin/models/tf/blocks/sampling/init.py 0 0 100%
merlin/models/tf/blocks/sampling/base.py 29 2 93%
merlin/models/tf/blocks/sampling/cross_batch.py 46 2 96%
merlin/models/tf/blocks/sampling/in_batch.py 35 0 100%
merlin/models/tf/blocks/sampling/queue.py 115 12 90%
merlin/models/tf/core/init.py 0 0 100%
merlin/models/tf/core/aggregation.py 241 49 80%
merlin/models/tf/core/base.py 244 55 77%
merlin/models/tf/core/combinators.py 426 53 88%
merlin/models/tf/core/encoder.py 170 29 83%
merlin/models/tf/core/index.py 104 16 85%
merlin/models/tf/core/prediction.py 50 1 98%
merlin/models/tf/core/tabular.py 280 29 90%
merlin/models/tf/inputs/init.py 0 0 100%
merlin/models/tf/inputs/base.py 60 10 83%
merlin/models/tf/inputs/continuous.py 39 3 92%
merlin/models/tf/inputs/embedding.py 458 31 93%
merlin/models/tf/loader.py 245 73 70%
merlin/models/tf/losses/init.py 4 0 100%
merlin/models/tf/losses/base.py 9 0 100%
merlin/models/tf/losses/listwise.py 13 0 100%
merlin/models/tf/losses/pairwise.py 115 1 99%
merlin/models/tf/metrics/init.py 2 0 100%
merlin/models/tf/metrics/evaluation.py 105 48 54%
merlin/models/tf/metrics/topk.py 198 48 76%
merlin/models/tf/models/init.py 0 0 100%
merlin/models/tf/models/base.py 708 75 89%
merlin/models/tf/models/benchmark.py 16 0 100%
merlin/models/tf/models/ranking.py 67 3 96%
merlin/models/tf/models/retrieval.py 78 4 95%
merlin/models/tf/models/utils.py 10 1 90%
merlin/models/tf/outputs/init.py 0 0 100%
merlin/models/tf/outputs/base.py 122 17 86%
merlin/models/tf/outputs/classification.py 91 1 99%
merlin/models/tf/outputs/contrastive.py 147 10 93%
merlin/models/tf/outputs/regression.py 9 0 100%
merlin/models/tf/outputs/sampling/init.py 0 0 100%
merlin/models/tf/outputs/sampling/base.py 78 21 73%
merlin/models/tf/outputs/sampling/in_batch.py 37 1 97%
merlin/models/tf/outputs/sampling/popularity.py 27 1 96%
merlin/models/tf/outputs/topk.py 97 6 94%
merlin/models/tf/prediction_tasks/init.py 0 0 100%
merlin/models/tf/prediction_tasks/base.py 207 37 82%
merlin/models/tf/prediction_tasks/classification.py 68 17 75%
merlin/models/tf/prediction_tasks/multi.py 7 0 100%
merlin/models/tf/prediction_tasks/next_item.py 59 6 90%
merlin/models/tf/prediction_tasks/regression.py 35 2 94%
merlin/models/tf/prediction_tasks/retrieval.py 73 3 96%
merlin/models/tf/transformers/init.py 0 0 100%
merlin/models/tf/transformers/block.py 101 2 98%
merlin/models/tf/transformers/transforms.py 63 0 100%
merlin/models/tf/transforms/init.py 0 0 100%
merlin/models/tf/transforms/bias.py 111 9 92%
merlin/models/tf/transforms/features.py 435 36 92%
merlin/models/tf/transforms/negative_sampling.py 77 3 96%
merlin/models/tf/transforms/noise.py 43 1 98%
merlin/models/tf/transforms/regularization.py 17 1 94%
merlin/models/tf/transforms/sequence.py 282 42 85%
merlin/models/tf/transforms/tensor.py 158 13 92%
merlin/models/tf/typing.py 7 0 100%
merlin/models/tf/utils/init.py 0 0 100%
merlin/models/tf/utils/batch_utils.py 85 4 95%
merlin/models/tf/utils/repr_utils.py 69 4 94%
merlin/models/tf/utils/search_utils.py 34 22 35%
merlin/models/tf/utils/testing_utils.py 206 36 83%
merlin/models/tf/utils/tf_utils.py 209 42 80%
merlin/models/torch/init.py 12 0 100%
merlin/models/torch/block/init.py 0 0 100%
merlin/models/torch/block/base.py 167 32 81%
merlin/models/torch/block/mlp.py 38 5 87%
merlin/models/torch/dataset.py 68 5 93%
merlin/models/torch/features/init.py 0 0 100%
merlin/models/torch/features/base.py 4 0 100%
merlin/models/torch/features/continuous.py 22 0 100%
merlin/models/torch/features/embedding.py 165 12 93%
merlin/models/torch/features/tabular.py 65 8 88%
merlin/models/torch/losses.py 28 28 0%
merlin/models/torch/model/init.py 0 0 100%
merlin/models/torch/model/base.py 286 65 77%
merlin/models/torch/model/prediction_task.py 24 0 100%
merlin/models/torch/tabular/init.py 0 0 100%
merlin/models/torch/tabular/aggregation.py 75 0 100%
merlin/models/torch/tabular/base.py 247 39 84%
merlin/models/torch/tabular/transformations.py 67 3 96%
merlin/models/torch/typing.py 6 0 100%
merlin/models/torch/utils/init.py 0 0 100%
merlin/models/torch/utils/data_utils.py 117 117 0%
merlin/models/torch/utils/examples_utils.py 39 39 0%
merlin/models/torch/utils/torch_utils.py 80 22 72%
merlin/models/utils/init.py 0 0 100%
merlin/models/utils/constants.py 3 0 100%
merlin/models/utils/dataset.py 38 4 89%
merlin/models/utils/dependencies.py 26 19 27%
merlin/models/utils/doc_utils.py 10 0 100%
merlin/models/utils/example_utils.py 31 2 94%
merlin/models/utils/misc_utils.py 118 90 24%
merlin/models/utils/nvt_utils.py 27 24 11%
merlin/models/utils/registry.py 101 29 71%
merlin/models/utils/schema_utils.py 90 19 79%
merlin/models/xgb/init.py 124 4 97%

TOTAL 11357 2229 80%

=========================== short test summary info ============================
SKIPPED [1] tests/unit/datasets/test_advertising.py:20: No data-dir available, pass it through env variable $INPUT_DATA_DIR
SKIPPED [1] tests/unit/datasets/test_ecommerce.py:62: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP
SKIPPED [1] tests/unit/datasets/test_ecommerce.py:78: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP
SKIPPED [1] tests/unit/datasets/test_ecommerce.py:92: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP
SKIPPED [3] tests/unit/datasets/test_entertainment.py:44: No data-dir available, pass it through env variable $INPUT_DATA_DIR
SKIPPED [5] ../../../.local/lib/python3.8/site-packages/tensorflow/python/framework/test_util.py:2746: Not a test.
========= 824 passed, 12 skipped, 1349 warnings in 1611.95s (0:26:51) ==========
___________________________________ summary ____________________________________
test-gpu: commands succeeded
congratulations :)
Performing Post build task...
Match found for : : True
Logical operation result is TRUE
Running script : #!/bin/bash
cd /var/jenkins_home/
CUDA_VISIBLE_DEVICES=1 python test_res_push.py "https://api.GitHub.com/repos/NVIDIA-Merlin/models/issues/$ghprbPullId/comments" "/var/jenkins_home/jobs/$JOB_NAME/builds/$BUILD_NUMBER/log"
[merlin_models] $ /bin/bash /tmp/jenkins18216966511042839463.sh

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Copy link

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GitHub pull request #855 of commit be39fc1de6ed0508e4f3c36c2c20b8ea61f8fda6, no merge conflicts.
Running as SYSTEM
Setting status of be39fc1de6ed0508e4f3c36c2c20b8ea61f8fda6 to PENDING with url http://merlin-infra1.nvidia.com:8080/job/merlin_models/1852/ and message: 'Pending'
Using context: Jenkins
Building on master in workspace /var/jenkins_home/workspace/merlin_models
using credential nvidia-merlin-bot
 > git rev-parse --is-inside-work-tree # timeout=10
Fetching changes from the remote Git repository
 > git config remote.origin.url https://github.com/NVIDIA-Merlin/models/ # timeout=10
Fetching upstream changes from https://github.com/NVIDIA-Merlin/models/
 > git --version # timeout=10
using GIT_ASKPASS to set credentials This is the bot credentials for our CI/CD
 > git fetch --tags --force --progress -- https://github.com/NVIDIA-Merlin/models/ +refs/pull/855/*:refs/remotes/origin/pr/855/* # timeout=10
 > git rev-parse be39fc1de6ed0508e4f3c36c2c20b8ea61f8fda6^{commit} # timeout=10
Checking out Revision be39fc1de6ed0508e4f3c36c2c20b8ea61f8fda6 (detached)
 > git config core.sparsecheckout # timeout=10
 > git checkout -f be39fc1de6ed0508e4f3c36c2c20b8ea61f8fda6 # timeout=10
Commit message: "Merge branch 'main' into multi-gpu-data-parallel"
 > git rev-list --no-walk 93245fb82ca6b8bd192ce7eb354850312d185406 # timeout=10
[merlin_models] $ /bin/bash /tmp/jenkins13334912282722446357.sh
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Requirement already satisfied: testbook in /usr/local/lib/python3.8/dist-packages (0.4.2)
Requirement already satisfied: nbformat>=5.0.4 in /usr/local/lib/python3.8/dist-packages (from testbook) (5.5.0)
Requirement already satisfied: nbclient>=0.4.0 in /usr/local/lib/python3.8/dist-packages (from testbook) (0.6.8)
Requirement already satisfied: jupyter-client>=6.1.5 in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (7.3.5)
Requirement already satisfied: traitlets>=5.2.2 in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (5.4.0)
Requirement already satisfied: nest-asyncio in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (1.5.5)
Requirement already satisfied: jupyter_core in /usr/local/lib/python3.8/dist-packages (from nbformat>=5.0.4->testbook) (4.11.1)
Requirement already satisfied: jsonschema>=2.6 in /usr/local/lib/python3.8/dist-packages (from nbformat>=5.0.4->testbook) (4.16.0)
Requirement already satisfied: fastjsonschema in /usr/local/lib/python3.8/dist-packages (from nbformat>=5.0.4->testbook) (2.16.1)
Requirement already satisfied: pkgutil-resolve-name>=1.3.10 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (1.3.10)
Requirement already satisfied: attrs>=17.4.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (22.1.0)
Requirement already satisfied: pyrsistent!=0.17.0,!=0.17.1,!=0.17.2,>=0.14.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (0.18.1)
Requirement already satisfied: importlib-resources>=1.4.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (5.9.0)
Requirement already satisfied: tornado>=6.2 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (6.2)
Requirement already satisfied: entrypoints in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (0.4)
Requirement already satisfied: pyzmq>=23.0 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (24.0.0)
Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (2.8.2)
Requirement already satisfied: zipp>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from importlib-resources>=1.4.0->jsonschema>=2.6->nbformat>=5.0.4->testbook) (3.8.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.8.2->jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (1.15.0)
GLOB sdist-make: /var/jenkins_home/workspace/merlin_models/models/setup.py
py38-gpu recreate: /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
py38-gpu installdeps: -rrequirements/dev.txt, tensorflow<2.10
WARNING: Discarding $PYTHONPATH from environment, to override specify PYTHONPATH in 'passenv' in your configuration.
py38-gpu inst: /var/jenkins_home/workspace/merlin_models/models/.tox/.tmp/package/3/merlin-models-0.9.0+49.gbe39fc1d.zip
WARNING: Discarding $PYTHONPATH from environment, to override specify PYTHONPATH in 'passenv' in your configuration.
py38-gpu installed: absl-py==1.2.0,aiohttp==3.8.1,aiosignal==1.2.0,alabaster==0.7.12,alembic==1.8.1,anyio==3.6.1,appdirs==1.4.4,argon2-cffi==21.3.0,argon2-cffi-bindings==21.2.0,astroid==2.5.6,asttokens==2.0.8,astunparse==1.6.3,asv==0.5.1,asvdb==0.4.2,async-timeout==4.0.2,attrs==22.1.0,autopage==0.5.1,awscli==1.27.10,Babel==2.10.3,backcall==0.2.0,beautifulsoup4==4.11.1,betterproto==1.2.5,black==20.8b1,bleach==5.0.1,bokeh==3.0.2,boto3==1.24.75,botocore==1.29.10,Brotli==1.0.9,build==0.9.0,cachetools==5.2.0,certifi==2019.11.28,cffi==1.15.1,chardet==3.0.4,charset-normalizer==2.1.1,check-manifest==0.48,clang==5.0,click==8.1.3,cliff==4.0.0,cloudpickle==2.2.0,cmaes==0.9.0,cmake==3.24.1.1,cmd2==2.4.2,colorama==0.4.4,colorlog==6.7.0,contourpy==1.0.5,coverage==6.5.0,cuda-python==11.7.1,cupy-cuda117==10.6.0,cycler==0.11.0,Cython==0.29.32,dask==2022.1.1,dbus-python==1.2.16,debugpy==1.6.3,decorator==5.1.1,defusedxml==0.7.1,dill==0.3.5.1,distlib==0.3.6,distributed==2022.5.1,distro==1.7.0,dm-tree==0.1.6,docker-pycreds==0.4.0,docutils==0.16,emoji==1.7.0,entrypoints==0.4,execnet==1.9.0,executing==1.0.0,faiss==1.7.2,faiss-gpu==1.7.2,fastai==2.7.9,fastapi==0.85.0,fastavro==1.6.1,fastcore==1.5.27,fastdownload==0.0.7,fastjsonschema==2.16.1,fastprogress==1.0.3,fastrlock==0.8,feast==0.19.4,fiddle==0.2.2,filelock==3.8.0,flake8==5.0.4,flatbuffers==1.12,fonttools==4.37.3,frozenlist==1.3.1,fsspec==2022.5.0,gast==0.4.0,gevent==21.12.0,geventhttpclient==2.0.2,gitdb==4.0.9,GitPython==3.1.27,google==3.0.0,google-api-core==2.10.1,google-auth==2.11.1,google-auth-oauthlib==0.4.6,google-pasta==0.2.0,googleapis-common-protos==1.52.0,graphviz==0.20.1,greenlet==1.1.3,grpcio==1.41.0,grpcio-channelz==1.49.0,grpcio-reflection==1.48.1,grpclib==0.4.3,h11==0.13.0,h2==4.1.0,h5py==3.7.0,HeapDict==1.0.1,horovod==0.26.1,hpack==4.0.0,httptools==0.5.0,hugectr2onnx==0.0.0,huggingface-hub==0.9.1,hyperframe==6.0.1,idna==2.8,imagesize==1.4.1,implicit==0.6.1,importlib-metadata==4.12.0,importlib-resources==5.9.0,iniconfig==1.1.1,interrogate==1.5.0,ipykernel==6.15.3,ipython==8.5.0,ipython-genutils==0.2.0,ipywidgets==7.7.0,isort==5.10.1,jedi==0.18.1,Jinja2==3.1.2,jmespath==1.0.1,joblib==1.2.0,json5==0.9.10,jsonschema==4.16.0,jupyter==1.0.0,jupyter-cache==0.4.3,jupyter-console==6.4.4,jupyter-core==4.11.1,jupyter-server==1.18.1,jupyter-server-mathjax==0.2.5,jupyter-sphinx==0.3.2,jupyter_client==7.3.5,jupyterlab==3.4.7,jupyterlab-pygments==0.2.2,jupyterlab-widgets==1.1.0,jupyterlab_server==2.15.1,keras==2.9.0,Keras-Preprocessing==1.1.2,kiwisolver==1.4.4,lazy-object-proxy==1.8.0,libclang==14.0.6,libcst==0.4.7,lightfm==1.16,lightgbm==3.3.2,linkify-it-py==1.0.3,llvmlite==0.39.1,locket==1.0.0,lxml==4.9.1,Mako==1.2.4,Markdown==3.4.1,markdown-it-py==1.1.0,MarkupSafe==2.1.1,matplotlib==3.6.0,matplotlib-inline==0.1.6,mccabe==0.7.0,mdit-py-plugins==0.2.8,merlin-core==0.6.0+1.g5926fcf,merlin-models==0.9.0+49.gbe39fc1d,merlin-systems==0.5.0+4.g15074ad,mistune==2.0.4,mmh3==3.0.0,mpi4py==3.1.3,msgpack==1.0.4,multidict==6.0.2,mypy==0.991,mypy-extensions==0.4.3,myst-nb==0.13.2,myst-parser==0.15.2,natsort==8.1.0,nbclassic==0.4.3,nbclient==0.6.8,nbconvert==7.0.0,nbdime==3.1.1,nbformat==5.5.0,nest-asyncio==1.5.5,ninja==1.10.2.3,notebook==6.4.12,notebook-shim==0.1.0,numba==0.56.2,numpy==1.22.4,nvidia-pyindex==1.0.9,# Editable install with no version control (nvtabular==1.4.0+8.g95e12d347),-e /usr/local/lib/python3.8/dist-packages,nvtx==0.2.5,oauthlib==3.2.1,oldest-supported-numpy==2022.8.16,onnx==1.12.0,onnxruntime==1.11.1,opt-einsum==3.3.0,optuna==3.0.3,packaging==21.3,pandas==1.3.5,pandavro==1.5.2,pandocfilters==1.5.0,parso==0.8.3,partd==1.3.0,pathspec==0.10.2,pathtools==0.1.2,pbr==5.11.0,pep517==0.13.0,pexpect==4.8.0,pickleshare==0.7.5,Pillow==9.2.0,pkgutil_resolve_name==1.3.10,platformdirs==2.5.2,plotly==5.11.0,pluggy==1.0.0,prettytable==3.5.0,prometheus-client==0.14.1,promise==2.3,prompt-toolkit==3.0.31,proto-plus==1.19.6,protobuf==3.19.5,psutil==5.9.2,ptyprocess==0.7.0,pure-eval==0.2.2,py==1.11.0,pyarrow==7.0.0,pyasn1==0.4.8,pyasn1-modules==0.2.8,pybind11==2.10.0,pycodestyle==2.9.1,pycparser==2.21,pydantic==1.10.2,pydot==1.4.2,pyflakes==2.5.0,Pygments==2.13.0,PyGObject==3.36.0,pynvml==11.4.1,pyparsing==3.0.9,pyperclip==1.8.2,pyrsistent==0.18.1,pytest==7.1.3,pytest-cov==4.0.0,pytest-xdist==3.0.2,python-apt==2.0.0+ubuntu0.20.4.8,python-dateutil==2.8.2,python-dotenv==0.21.0,python-rapidjson==1.8,pytz==2022.2.1,PyYAML==5.4.1,pyzmq==24.0.0,qtconsole==5.4.0,QtPy==2.3.0,regex==2022.9.13,requests==2.22.0,requests-oauthlib==1.3.1,requests-unixsocket==0.2.0,rsa==4.7.2,s3fs==2022.2.0,s3transfer==0.6.0,sacremoses==0.0.53,scikit-build==0.15.0,scikit-learn==1.1.2,scipy==1.8.1,seedir==0.3.0,Send2Trash==1.8.0,sentry-sdk==1.9.8,setproctitle==1.3.2,setuptools-scm==7.0.5,shortuuid==1.0.9,six==1.15.0,sklearn==0.0,smmap==5.0.0,sniffio==1.3.0,snowballstemmer==2.2.0,sortedcontainers==2.4.0,soupsieve==2.3.2.post1,Sphinx==5.3.0,sphinx-multiversion==0.2.4,sphinx-togglebutton==0.3.1,sphinx_external_toc==0.3.0,sphinxcontrib-applehelp==1.0.2,sphinxcontrib-copydirs @ git+https://github.com/mikemckiernan/sphinxcontrib-copydirs.git@bd8c5d79b3f91cf5f1bb0d6995aeca3fe84b670e,sphinxcontrib-devhelp==1.0.2,sphinxcontrib-htmlhelp==2.0.0,sphinxcontrib-jsmath==1.0.1,sphinxcontrib-qthelp==1.0.3,sphinxcontrib-serializinghtml==1.1.5,SQLAlchemy==1.4.44,stack-data==0.5.0,starlette==0.20.4,stevedore==4.1.1,stringcase==1.2.0,supervisor==4.1.0,tabulate==0.8.10,tblib==1.7.0,tdqm==0.0.1,tenacity==8.0.1,tensorboard==2.9.1,tensorboard-data-server==0.6.1,tensorboard-plugin-wit==1.8.1,tensorflow==2.9.2,tensorflow-estimator==2.9.0,tensorflow-gpu==2.9.2,tensorflow-io-gcs-filesystem==0.27.0,tensorflow-metadata==1.10.0,tensorflow-ranking==0.5.1,tensorflow-serving-api==2.9.2,termcolor==2.0.1,terminado==0.15.0,testbook==0.4.2,threadpoolctl==3.1.0,tinycss2==1.1.1,tokenizers==0.10.3,toml==0.10.2,tomli==2.0.1,toolz==0.12.0,torch==1.12.1+cu113,torchmetrics==0.3.2,tornado==6.2,tox==3.26.0,tqdm==4.64.1,traitlets==5.4.0,transformers==4.12.0,transformers4rec==0.1.12+2.gbcc939255,treelite==2.3.0,treelite-runtime==2.3.0,tritonclient==2.25.0,typed-ast==1.5.4,typing-inspect==0.8.0,typing_extensions==4.3.0,uc-micro-py==1.0.1,urllib3==1.26.12,uvicorn==0.18.3,uvloop==0.17.0,versioneer==0.20,virtualenv==20.16.5,wandb==0.13.3,watchfiles==0.17.0,wcwidth==0.2.5,webencodings==0.5.1,websocket-client==1.4.1,websockets==10.3,Werkzeug==2.2.2,widgetsnbextension==3.6.0,wrapt==1.12.1,xgboost==1.6.2,xyzservices==2022.9.0,yarl==1.8.1,zict==2.2.0,zipp==3.8.1,zope.event==4.5.0,zope.interface==5.4.0
py38-gpu run-test-pre: PYTHONHASHSEED='3281247156'
py38-gpu run-test: commands[0] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/core.git
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Collecting git+https://github.com/NVIDIA-Merlin/core.git
  Cloning https://github.com/NVIDIA-Merlin/core.git to /tmp/pip-req-build-ehc22oir
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/core.git /tmp/pip-req-build-ehc22oir
  Resolved https://github.com/NVIDIA-Merlin/core.git to commit eb606d54fa2ddcbb7e4d0e6501ab2eb418c7fba9
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: packaging in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+11.geb606d5) (21.3)
Requirement already satisfied: tqdm>=4.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+11.geb606d5) (4.64.1)
Requirement already satisfied: distributed>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+11.geb606d5) (2022.3.0)
Requirement already satisfied: numba>=0.54 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+11.geb606d5) (0.55.1)
Requirement already satisfied: betterproto<2.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+11.geb606d5) (1.2.5)
Requirement already satisfied: fsspec==2022.5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+11.geb606d5) (2022.5.0)
Requirement already satisfied: pandas<1.4.0dev0,>=1.2.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+11.geb606d5) (1.3.5)
Requirement already satisfied: protobuf>=3.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+11.geb606d5) (3.19.5)
Requirement already satisfied: tensorflow-metadata>=1.2.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+11.geb606d5) (1.10.0)
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Requirement already satisfied: pyarrow>=5.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+11.geb606d5) (7.0.0)
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Requirement already satisfied: grpclib in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core==0.8.0+11.geb606d5) (0.4.3)
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Requirement already satisfied: pyyaml>=5.3.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/PyYAML-5.4.1-py3.8-linux-x86_64.egg (from dask>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (5.4.1)
Requirement already satisfied: partd>=0.3.10 in /var/jenkins_home/.local/lib/python3.8/site-packages/partd-1.2.0-py3.8.egg (from dask>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (1.2.0)
Requirement already satisfied: cloudpickle>=1.1.1 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (2.2.0)
Requirement already satisfied: msgpack>=0.6.0 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (1.0.4)
Requirement already satisfied: tblib>=1.6.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/tblib-1.7.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (1.7.0)
Requirement already satisfied: sortedcontainers!=2.0.0,!=2.0.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/sortedcontainers-2.4.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (2.4.0)
Requirement already satisfied: tornado>=6.0.3 in ./.tox/py38-gpu/lib/python3.8/site-packages (from distributed>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (6.2)
Requirement already satisfied: click>=6.6 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (8.1.3)
Requirement already satisfied: zict>=0.1.3 in /var/jenkins_home/.local/lib/python3.8/site-packages/zict-2.0.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (2.0.0)
Requirement already satisfied: jinja2 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (3.1.2)
Requirement already satisfied: psutil>=5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/psutil-5.8.0-py3.8-linux-x86_64.egg (from distributed>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (5.8.0)
Requirement already satisfied: numpy<1.22,>=1.18 in /var/jenkins_home/.local/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+11.geb606d5) (1.20.3)
Requirement already satisfied: setuptools in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+11.geb606d5) (65.5.1)
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Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in /usr/local/lib/python3.8/dist-packages (from packaging->merlin-core==0.8.0+11.geb606d5) (3.0.9)
Requirement already satisfied: pytz>=2017.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+11.geb606d5) (2022.2.1)
Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+11.geb606d5) (2.8.2)
Requirement already satisfied: absl-py<2.0.0,>=0.9 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core==0.8.0+11.geb606d5) (1.2.0)
Requirement already satisfied: googleapis-common-protos<2,>=1.52.0 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core==0.8.0+11.geb606d5) (1.52.0)
Requirement already satisfied: locket in /var/jenkins_home/.local/lib/python3.8/site-packages/locket-0.2.1-py3.8.egg (from partd>=0.3.10->dask>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (0.2.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.7.3->pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+11.geb606d5) (1.15.0)
Requirement already satisfied: heapdict in /var/jenkins_home/.local/lib/python3.8/site-packages/HeapDict-1.0.1-py3.8.egg (from zict>=0.1.3->distributed>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (1.0.1)
Requirement already satisfied: multidict in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core==0.8.0+11.geb606d5) (6.0.2)
Requirement already satisfied: h2<5,>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core==0.8.0+11.geb606d5) (4.1.0)
Requirement already satisfied: MarkupSafe>=2.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from jinja2->distributed>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (2.0.1)
Requirement already satisfied: hyperframe<7,>=6.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core==0.8.0+11.geb606d5) (6.0.1)
Requirement already satisfied: hpack<5,>=4.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core==0.8.0+11.geb606d5) (4.0.0)
Building wheels for collected packages: merlin-core
  Building wheel for merlin-core (pyproject.toml): started
  Building wheel for merlin-core (pyproject.toml): finished with status 'done'
  Created wheel for merlin-core: filename=merlin_core-0.8.0+11.geb606d5-py3-none-any.whl size=118619 sha256=292341e150b26a307cb5242f7ecc760e7fcb37c4d147d7cade0dad504c52536c
  Stored in directory: /tmp/pip-ephem-wheel-cache-hhjgyh1b/wheels/c8/38/16/a6968787eafcec5fa772148af8408b089562f71af0752e8e84
Successfully built merlin-core
Installing collected packages: merlin-core
  Attempting uninstall: merlin-core
    Found existing installation: merlin-core 0.3.0+12.g78ecddd
    Not uninstalling merlin-core at /var/jenkins_home/.local/lib/python3.8/site-packages, outside environment /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
    Can't uninstall 'merlin-core'. No files were found to uninstall.
Successfully installed merlin-core-0.8.0+11.geb606d5
py38-gpu run-test: commands[1] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/nvtabular.git
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Collecting git+https://github.com/NVIDIA-Merlin/nvtabular.git
  Cloning https://github.com/NVIDIA-Merlin/nvtabular.git to /tmp/pip-req-build-we_otk77
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/nvtabular.git /tmp/pip-req-build-we_otk77
  Resolved https://github.com/NVIDIA-Merlin/nvtabular.git to commit ba4c14159a8e858c8998d4158a4376e65a8fa266
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: merlin-core>=0.2.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from nvtabular==1.6.0+4.gba4c1415) (0.8.0+11.geb606d5)
Collecting merlin-dataloader>=0.0.2
  Downloading merlin-dataloader-0.0.2.tar.gz (44 kB)
     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 44.1/44.1 kB 1.6 MB/s eta 0:00:00
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: scipy in /usr/local/lib/python3.8/dist-packages (from nvtabular==1.6.0+4.gba4c1415) (1.8.1)
Requirement already satisfied: packaging in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (21.3)
Requirement already satisfied: tqdm>=4.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (4.64.1)
Requirement already satisfied: distributed>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (2022.3.0)
Requirement already satisfied: numba>=0.54 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (0.55.1)
Requirement already satisfied: betterproto<2.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (1.2.5)
Requirement already satisfied: fsspec==2022.5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (2022.5.0)
Requirement already satisfied: pandas<1.4.0dev0,>=1.2.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (1.3.5)
Requirement already satisfied: protobuf>=3.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (3.19.5)
Requirement already satisfied: tensorflow-metadata>=1.2.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (1.10.0)
Requirement already satisfied: dask>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (2022.3.0)
Requirement already satisfied: pyarrow>=5.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (7.0.0)
Requirement already satisfied: numpy<1.25.0,>=1.17.3 in /var/jenkins_home/.local/lib/python3.8/site-packages (from scipy->nvtabular==1.6.0+4.gba4c1415) (1.20.3)
Requirement already satisfied: stringcase in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (1.2.0)
Requirement already satisfied: grpclib in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (0.4.3)
Requirement already satisfied: toolz>=0.8.2 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (0.12.0)
Requirement already satisfied: pyyaml>=5.3.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/PyYAML-5.4.1-py3.8-linux-x86_64.egg (from dask>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (5.4.1)
Requirement already satisfied: partd>=0.3.10 in /var/jenkins_home/.local/lib/python3.8/site-packages/partd-1.2.0-py3.8.egg (from dask>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (1.2.0)
Requirement already satisfied: cloudpickle>=1.1.1 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (2.2.0)
Requirement already satisfied: msgpack>=0.6.0 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (1.0.4)
Requirement already satisfied: tblib>=1.6.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/tblib-1.7.0-py3.8.egg (from distributed>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (1.7.0)
Requirement already satisfied: sortedcontainers!=2.0.0,!=2.0.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/sortedcontainers-2.4.0-py3.8.egg (from distributed>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (2.4.0)
Requirement already satisfied: tornado>=6.0.3 in ./.tox/py38-gpu/lib/python3.8/site-packages (from distributed>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (6.2)
Requirement already satisfied: click>=6.6 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (8.1.3)
Requirement already satisfied: zict>=0.1.3 in /var/jenkins_home/.local/lib/python3.8/site-packages/zict-2.0.0-py3.8.egg (from distributed>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (2.0.0)
Requirement already satisfied: jinja2 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (3.1.2)
Requirement already satisfied: psutil>=5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/psutil-5.8.0-py3.8-linux-x86_64.egg (from distributed>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (5.8.0)
Requirement already satisfied: setuptools in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (65.5.1)
Requirement already satisfied: llvmlite<0.39,>=0.38.0rc1 in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (0.38.1)
Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in /usr/local/lib/python3.8/dist-packages (from packaging->merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (3.0.9)
Requirement already satisfied: pytz>=2017.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (2022.2.1)
Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (2.8.2)
Requirement already satisfied: absl-py<2.0.0,>=0.9 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (1.2.0)
Requirement already satisfied: googleapis-common-protos<2,>=1.52.0 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (1.52.0)
Requirement already satisfied: locket in /var/jenkins_home/.local/lib/python3.8/site-packages/locket-0.2.1-py3.8.egg (from partd>=0.3.10->dask>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (0.2.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.7.3->pandas<1.4.0dev0,>=1.2.0->merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (1.15.0)
Requirement already satisfied: heapdict in /var/jenkins_home/.local/lib/python3.8/site-packages/HeapDict-1.0.1-py3.8.egg (from zict>=0.1.3->distributed>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (1.0.1)
Requirement already satisfied: multidict in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (6.0.2)
Requirement already satisfied: h2<5,>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (4.1.0)
Requirement already satisfied: MarkupSafe>=2.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from jinja2->distributed>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (2.0.1)
Requirement already satisfied: hyperframe<7,>=6.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (6.0.1)
Requirement already satisfied: hpack<5,>=4.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (4.0.0)
Building wheels for collected packages: nvtabular, merlin-dataloader
  Building wheel for nvtabular (pyproject.toml): started
  Building wheel for nvtabular (pyproject.toml): finished with status 'done'
  Created wheel for nvtabular: filename=nvtabular-1.6.0+4.gba4c1415-cp38-cp38-linux_x86_64.whl size=257596 sha256=e88327871835bee900caa256dd52e1ae0e416f45454b6c80c3b0ae1bc4fc9c3a
  Stored in directory: /tmp/pip-ephem-wheel-cache-qopxq793/wheels/8f/d9/f9/30f2cdc5bf8787fae6fdfe55afd6e1b493e619ec32c32ec40b
  Building wheel for merlin-dataloader (pyproject.toml): started
  Building wheel for merlin-dataloader (pyproject.toml): finished with status 'done'
  Created wheel for merlin-dataloader: filename=merlin_dataloader-0.0.2-py3-none-any.whl size=29203 sha256=e50e83ddf07c26688ae9f81ea95511a0cc609cce887ef1b4138228b19e71b2ba
  Stored in directory: /tmp/pip-ephem-wheel-cache-qopxq793/wheels/76/ef/ed/cb880e3ef5192ec5940e26fd9442247b569fb0cf8602f97137
Successfully built nvtabular merlin-dataloader
Installing collected packages: merlin-dataloader, nvtabular
  Attempting uninstall: nvtabular
    Found existing installation: nvtabular 1.1.1
    Not uninstalling nvtabular at /var/jenkins_home/.local/lib/python3.8/site-packages, outside environment /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
    Can't uninstall 'nvtabular'. No files were found to uninstall.
Successfully installed merlin-dataloader-0.0.2 nvtabular-1.6.0+4.gba4c1415
py38-gpu run-test: commands[2] | python -m pytest --cov-report term --cov merlin -rxs tests/unit
============================= test session starts ==============================
platform linux -- Python 3.8.10, pytest-7.1.3, pluggy-1.0.0
cachedir: .tox/py38-gpu/.pytest_cache
rootdir: /var/jenkins_home/workspace/merlin_models/models, configfile: pyproject.toml
plugins: anyio-3.5.0, xdist-3.0.2, cov-4.0.0
collected 879 items

tests/unit/config/test_schema.py .... [ 0%]
tests/unit/datasets/test_advertising.py .s [ 0%]
tests/unit/datasets/test_ecommerce.py ..sss.s [ 1%]
tests/unit/datasets/test_entertainment.py ....sss. [ 2%]
tests/unit/datasets/test_social.py . [ 2%]
tests/unit/datasets/test_synthetic.py ...... [ 3%]
tests/unit/implicit/test_implicit.py . [ 3%]
tests/unit/lightfm/test_lightfm.py . [ 3%]
tests/unit/tf/test_core.py ...... [ 4%]
tests/unit/tf/test_loader.py ................ [ 5%]
tests/unit/tf/test_public_api.py . [ 6%]
tests/unit/tf/blocks/test_cross.py ........... [ 7%]
tests/unit/tf/blocks/test_dlrm.py .......... [ 8%]
tests/unit/tf/blocks/test_interactions.py ... [ 8%]
tests/unit/tf/blocks/test_mlp.py ....................................... [ 13%]
............................ [ 16%]
tests/unit/tf/blocks/test_optimizer.py s................................ [ 20%]
..................... [ 22%]
tests/unit/tf/blocks/retrieval/test_base.py . [ 22%]
tests/unit/tf/blocks/retrieval/test_matrix_factorization.py .. [ 22%]
tests/unit/tf/blocks/retrieval/test_two_tower.py ............ [ 24%]
tests/unit/tf/blocks/sampling/test_cross_batch.py . [ 24%]
tests/unit/tf/blocks/sampling/test_in_batch.py . [ 24%]
tests/unit/tf/core/test_aggregation.py ......... [ 25%]
tests/unit/tf/core/test_base.py .. [ 25%]
tests/unit/tf/core/test_combinators.py s..................... [ 28%]
tests/unit/tf/core/test_encoder.py .. [ 28%]
tests/unit/tf/core/test_index.py ... [ 28%]
tests/unit/tf/core/test_prediction.py .. [ 29%]
tests/unit/tf/core/test_tabular.py ...... [ 29%]
tests/unit/tf/examples/test_01_getting_started.py . [ 29%]
tests/unit/tf/examples/test_02_dataschema.py . [ 29%]
tests/unit/tf/examples/test_03_exploring_different_models.py . [ 30%]
tests/unit/tf/examples/test_04_export_ranking_models.py . [ 30%]
tests/unit/tf/examples/test_05_export_retrieval_model.py . [ 30%]
tests/unit/tf/examples/test_06_advanced_own_architecture.py . [ 30%]
tests/unit/tf/examples/test_07_train_traditional_models.py . [ 30%]
tests/unit/tf/examples/test_usecase_accelerate_training_by_lazyadam.py . [ 30%]
[ 30%]
tests/unit/tf/examples/test_usecase_data_parallel.py . [ 30%]
tests/unit/tf/examples/test_usecase_ecommerce_session_based.py . [ 30%]
tests/unit/tf/examples/test_usecase_incremental_training_layer_freezing.py . [ 30%]
[ 30%]
tests/unit/tf/examples/test_usecase_pretrained_embeddings.py . [ 31%]
tests/unit/tf/examples/test_usecase_retrieval_with_hpo.py . [ 31%]
tests/unit/tf/horovod/test_horovod.py ... [ 31%]
tests/unit/tf/inputs/test_base.py . [ 31%]
tests/unit/tf/inputs/test_continuous.py ........ [ 32%]
tests/unit/tf/inputs/test_embedding.py ................................. [ 36%]
........ [ 37%]
tests/unit/tf/inputs/test_tabular.py .................. [ 39%]
tests/unit/tf/layers/test_queue.py .............. [ 40%]
tests/unit/tf/losses/test_losses.py ....................... [ 43%]
tests/unit/tf/metrics/test_metrics_popularity.py ..... [ 44%]
tests/unit/tf/metrics/test_metrics_topk.py ......................... [ 46%]
tests/unit/tf/models/test_base.py s......................... [ 49%]
tests/unit/tf/models/test_benchmark.py .. [ 50%]
tests/unit/tf/models/test_ranking.py .................................. [ 53%]
tests/unit/tf/models/test_retrieval.py ................................. [ 57%]
........................................... [ 62%]
tests/unit/tf/outputs/test_base.py ...... [ 63%]
tests/unit/tf/outputs/test_classification.py ...... [ 63%]
tests/unit/tf/outputs/test_contrastive.py .............. [ 65%]
tests/unit/tf/outputs/test_regression.py .. [ 65%]
tests/unit/tf/outputs/test_sampling.py .... [ 66%]
tests/unit/tf/outputs/test_topk.py . [ 66%]
tests/unit/tf/prediction_tasks/test_classification.py .. [ 66%]
tests/unit/tf/prediction_tasks/test_multi_task.py ................ [ 68%]
tests/unit/tf/prediction_tasks/test_next_item.py ..... [ 68%]
tests/unit/tf/prediction_tasks/test_regression.py ..... [ 69%]
tests/unit/tf/prediction_tasks/test_retrieval.py . [ 69%]
tests/unit/tf/prediction_tasks/test_sampling.py ...... [ 70%]
tests/unit/tf/transformers/test_block.py ...................... [ 72%]
tests/unit/tf/transformers/test_transforms.py .......... [ 73%]
tests/unit/tf/transforms/test_bias.py .. [ 74%]
tests/unit/tf/transforms/test_features.py s............................. [ 77%]
.......................s...... [ 81%]
tests/unit/tf/transforms/test_negative_sampling.py ......... [ 82%]
tests/unit/tf/transforms/test_noise.py ..... [ 82%]
tests/unit/tf/transforms/test_sequence.py .................... [ 84%]
tests/unit/tf/transforms/test_tensor.py ... [ 85%]
tests/unit/tf/utils/test_batch.py .... [ 85%]
tests/unit/tf/utils/test_dataset.py .. [ 85%]
tests/unit/tf/utils/test_tf_utils.py ..... [ 86%]
tests/unit/torch/test_dataset.py ......... [ 87%]
tests/unit/torch/test_public_api.py . [ 87%]
tests/unit/torch/block/test_base.py .... [ 88%]
tests/unit/torch/block/test_mlp.py . [ 88%]
tests/unit/torch/features/test_continuous.py .. [ 88%]
tests/unit/torch/features/test_embedding.py .............. [ 89%]
tests/unit/torch/features/test_tabular.py .... [ 90%]
tests/unit/torch/model/test_head.py ............ [ 91%]
tests/unit/torch/model/test_model.py .. [ 92%]
tests/unit/torch/tabular/test_aggregation.py ........ [ 92%]
tests/unit/torch/tabular/test_tabular.py ... [ 93%]
tests/unit/torch/tabular/test_transformations.py ....... [ 94%]
tests/unit/utils/test_schema_utils.py ................................ [ 97%]
tests/unit/xgb/test_xgboost.py .................... [100%]

=============================== warnings summary ===============================
../../../../../usr/lib/python3/dist-packages/requests/init.py:89
/usr/lib/python3/dist-packages/requests/init.py:89: RequestsDependencyWarning: urllib3 (1.26.12) or chardet (3.0.4) doesn't match a supported version!
warnings.warn("urllib3 ({}) or chardet ({}) doesn't match a supported "

../../../.local/lib/python3.8/site-packages/flatbuffers/compat.py:19
/var/jenkins_home/.local/lib/python3.8/site-packages/flatbuffers/compat.py:19: DeprecationWarning: the imp module is deprecated in favour of importlib; see the module's documentation for alternative uses
import imp

../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36
/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36: DeprecationWarning: NEAREST is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.NEAREST or Dither.NONE instead.
'nearest': pil_image.NEAREST,

../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37
/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37: DeprecationWarning: BILINEAR is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BILINEAR instead.
'bilinear': pil_image.BILINEAR,

../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38
/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38: DeprecationWarning: BICUBIC is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BICUBIC instead.
'bicubic': pil_image.BICUBIC,

../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39
/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39: DeprecationWarning: HAMMING is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.HAMMING instead.
'hamming': pil_image.HAMMING,

../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40
/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40: DeprecationWarning: BOX is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BOX instead.
'box': pil_image.BOX,

../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41
/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41: DeprecationWarning: LANCZOS is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.LANCZOS instead.
'lanczos': pil_image.LANCZOS,

tests/unit/datasets/test_advertising.py: 1 warning
tests/unit/datasets/test_ecommerce.py: 3 warnings
tests/unit/datasets/test_entertainment.py: 4 warnings
tests/unit/datasets/test_social.py: 1 warning
tests/unit/datasets/test_synthetic.py: 6 warnings
tests/unit/implicit/test_implicit.py: 1 warning
tests/unit/lightfm/test_lightfm.py: 1 warning
tests/unit/tf/test_core.py: 6 warnings
tests/unit/tf/test_loader.py: 1 warning
tests/unit/tf/blocks/test_cross.py: 5 warnings
tests/unit/tf/blocks/test_dlrm.py: 9 warnings
tests/unit/tf/blocks/test_interactions.py: 2 warnings
tests/unit/tf/blocks/test_mlp.py: 60 warnings
tests/unit/tf/blocks/test_optimizer.py: 30 warnings
tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings
tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings
tests/unit/tf/core/test_aggregation.py: 6 warnings
tests/unit/tf/core/test_base.py: 2 warnings
tests/unit/tf/core/test_combinators.py: 11 warnings
tests/unit/tf/core/test_encoder.py: 6 warnings
tests/unit/tf/core/test_index.py: 8 warnings
tests/unit/tf/core/test_prediction.py: 2 warnings
tests/unit/tf/horovod/test_horovod.py: 3 warnings
tests/unit/tf/inputs/test_base.py: 1 warning
tests/unit/tf/inputs/test_continuous.py: 7 warnings
tests/unit/tf/inputs/test_embedding.py: 20 warnings
tests/unit/tf/inputs/test_tabular.py: 18 warnings
tests/unit/tf/models/test_base.py: 28 warnings
tests/unit/tf/models/test_benchmark.py: 2 warnings
tests/unit/tf/models/test_ranking.py: 38 warnings
tests/unit/tf/models/test_retrieval.py: 120 warnings
tests/unit/tf/outputs/test_base.py: 6 warnings
tests/unit/tf/outputs/test_classification.py: 6 warnings
tests/unit/tf/outputs/test_contrastive.py: 19 warnings
tests/unit/tf/outputs/test_regression.py: 2 warnings
tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings
tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings
tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings
tests/unit/tf/prediction_tasks/test_retrieval.py: 1 warning
tests/unit/tf/transformers/test_block.py: 16 warnings
tests/unit/tf/transforms/test_bias.py: 2 warnings
tests/unit/tf/transforms/test_features.py: 10 warnings
tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings
tests/unit/tf/transforms/test_noise.py: 1 warning
tests/unit/tf/transforms/test_sequence.py: 15 warnings
tests/unit/tf/utils/test_batch.py: 9 warnings
tests/unit/tf/utils/test_dataset.py: 2 warnings
tests/unit/torch/block/test_base.py: 4 warnings
tests/unit/torch/block/test_mlp.py: 1 warning
tests/unit/torch/features/test_continuous.py: 1 warning
tests/unit/torch/features/test_embedding.py: 4 warnings
tests/unit/torch/features/test_tabular.py: 4 warnings
tests/unit/torch/model/test_head.py: 12 warnings
tests/unit/torch/model/test_model.py: 2 warnings
tests/unit/torch/tabular/test_aggregation.py: 6 warnings
tests/unit/torch/tabular/test_transformations.py: 3 warnings
tests/unit/xgb/test_xgboost.py: 18 warnings
/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.ITEM_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.ITEM: 'item'>, <Tags.ID: 'id'>].
warnings.warn(

tests/unit/datasets/test_ecommerce.py: 3 warnings
tests/unit/datasets/test_entertainment.py: 4 warnings
tests/unit/datasets/test_social.py: 1 warning
tests/unit/datasets/test_synthetic.py: 5 warnings
tests/unit/implicit/test_implicit.py: 1 warning
tests/unit/lightfm/test_lightfm.py: 1 warning
tests/unit/tf/test_core.py: 6 warnings
tests/unit/tf/test_loader.py: 1 warning
tests/unit/tf/blocks/test_cross.py: 5 warnings
tests/unit/tf/blocks/test_dlrm.py: 9 warnings
tests/unit/tf/blocks/test_interactions.py: 2 warnings
tests/unit/tf/blocks/test_mlp.py: 60 warnings
tests/unit/tf/blocks/test_optimizer.py: 30 warnings
tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings
tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings
tests/unit/tf/core/test_aggregation.py: 6 warnings
tests/unit/tf/core/test_base.py: 2 warnings
tests/unit/tf/core/test_combinators.py: 11 warnings
tests/unit/tf/core/test_encoder.py: 7 warnings
tests/unit/tf/core/test_index.py: 3 warnings
tests/unit/tf/core/test_prediction.py: 2 warnings
tests/unit/tf/horovod/test_horovod.py: 1 warning
tests/unit/tf/inputs/test_base.py: 1 warning
tests/unit/tf/inputs/test_continuous.py: 7 warnings
tests/unit/tf/inputs/test_embedding.py: 20 warnings
tests/unit/tf/inputs/test_tabular.py: 18 warnings
tests/unit/tf/models/test_base.py: 28 warnings
tests/unit/tf/models/test_benchmark.py: 2 warnings
tests/unit/tf/models/test_ranking.py: 36 warnings
tests/unit/tf/models/test_retrieval.py: 86 warnings
tests/unit/tf/outputs/test_base.py: 6 warnings
tests/unit/tf/outputs/test_classification.py: 6 warnings
tests/unit/tf/outputs/test_contrastive.py: 19 warnings
tests/unit/tf/outputs/test_regression.py: 2 warnings
tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings
tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings
tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings
tests/unit/tf/transformers/test_block.py: 10 warnings
tests/unit/tf/transforms/test_features.py: 10 warnings
tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings
tests/unit/tf/transforms/test_sequence.py: 15 warnings
tests/unit/tf/utils/test_batch.py: 7 warnings
tests/unit/tf/utils/test_dataset.py: 2 warnings
tests/unit/torch/block/test_base.py: 4 warnings
tests/unit/torch/block/test_mlp.py: 1 warning
tests/unit/torch/features/test_continuous.py: 1 warning
tests/unit/torch/features/test_embedding.py: 4 warnings
tests/unit/torch/features/test_tabular.py: 4 warnings
tests/unit/torch/model/test_head.py: 12 warnings
tests/unit/torch/model/test_model.py: 2 warnings
tests/unit/torch/tabular/test_aggregation.py: 6 warnings
tests/unit/torch/tabular/test_transformations.py: 2 warnings
tests/unit/xgb/test_xgboost.py: 17 warnings
/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.USER_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.USER: 'user'>, <Tags.ID: 'id'>].
warnings.warn(

tests/unit/datasets/test_ecommerce.py: 1 warning
tests/unit/datasets/test_entertainment.py: 1 warning
tests/unit/implicit/test_implicit.py: 1 warning
tests/unit/lightfm/test_lightfm.py: 1 warning
tests/unit/tf/test_loader.py: 1 warning
tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings
tests/unit/tf/blocks/retrieval/test_two_tower.py: 2 warnings
tests/unit/tf/core/test_combinators.py: 11 warnings
tests/unit/tf/core/test_encoder.py: 2 warnings
tests/unit/tf/core/test_prediction.py: 1 warning
tests/unit/tf/horovod/test_horovod.py: 1 warning
tests/unit/tf/inputs/test_continuous.py: 4 warnings
tests/unit/tf/inputs/test_embedding.py: 9 warnings
tests/unit/tf/inputs/test_tabular.py: 8 warnings
tests/unit/tf/models/test_ranking.py: 20 warnings
tests/unit/tf/models/test_retrieval.py: 10 warnings
tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings
tests/unit/tf/prediction_tasks/test_regression.py: 3 warnings
tests/unit/tf/transforms/test_negative_sampling.py: 9 warnings
tests/unit/xgb/test_xgboost.py: 12 warnings
/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.SESSION_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.SESSION: 'session'>, <Tags.ID: 'id'>].
warnings.warn(

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export
tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export
tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export
tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export
tests/unit/tf/inputs/test_embedding.py::test_embedding_features_exporting_and_loading_pretrained_initializer
/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/inputs/embedding.py:970: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack
embeddings_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(embeddings)))

tests/unit/tf/blocks/retrieval/test_two_tower.py: 1 warning
tests/unit/tf/core/test_index.py: 4 warnings
tests/unit/tf/horovod/test_horovod.py: 3 warnings
tests/unit/tf/models/test_retrieval.py: 55 warnings
tests/unit/tf/prediction_tasks/test_next_item.py: 3 warnings
tests/unit/tf/utils/test_batch.py: 2 warnings
/tmp/autograph_generated_file5umqp32x.py:8: DeprecationWarning: The 'warn' method is deprecated, use 'warning' instead
ag
.converted_call(ag__.ld(warnings).warn, ("The 'warn' method is deprecated, use 'warning' instead", ag__.ld(DeprecationWarning), 2), None, fscope)

tests/unit/tf/core/test_combinators.py::test_parallel_block_select_by_tags
/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/core/tabular.py:602: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated since Python 3.3, and in 3.10 it will stop working
elif isinstance(self.feature_names, collections.Sequence):

tests/unit/tf/core/test_encoder.py: 1 warning
tests/unit/tf/core/test_index.py: 5 warnings
tests/unit/tf/models/test_retrieval.py: 30 warnings
tests/unit/tf/utils/test_batch.py: 4 warnings
tests/unit/tf/utils/test_dataset.py: 1 warning
/var/jenkins_home/workspace/merlin_models/models/merlin/models/utils/dataset.py:75: DeprecationWarning: unique_rows_by_features is deprecated and will be removed in a future version. Please use unique_by_tag instead.
warnings.warn(

tests/unit/tf/models/test_base.py::test_model_pre_post[True]
tests/unit/tf/models/test_base.py::test_model_pre_post[False]
tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.1]
tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.3]
tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.5]
tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.7]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/util/dispatch.py:1082: UserWarning: tf.keras.backend.random_binomial is deprecated, and will be removed in a future version.Please use tf.keras.backend.random_bernoulli instead.
return dispatch_target(*args, **kwargs)

tests/unit/tf/models/test_base.py::test_freeze_parallel_block[True]
tests/unit/tf/models/test_base.py::test_freeze_sequential_block
tests/unit/tf/models/test_base.py::test_freeze_unfreeze
tests/unit/tf/models/test_base.py::test_unfreeze_all_blocks
/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/gradient_descent.py:108: UserWarning: The lr argument is deprecated, use learning_rate instead.
super(SGD, self).init(name, **kwargs)

tests/unit/tf/models/test_base.py::test_retrieval_model_query
tests/unit/tf/models/test_base.py::test_retrieval_model_query
tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_v2_export_embeddings
tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[True]
tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[False]
tests/unit/tf/transformers/test_block.py::test_retrieval_transformer[True]
/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/utils/tf_utils.py:298: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack
tensor_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(tensor)))

tests/unit/tf/models/test_ranking.py::test_deepfm_model_only_categ_feats[False]
tests/unit/tf/models/test_ranking.py::test_deepfm_model_categ_and_continuous_feats[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/models/test_ranking.py::test_wide_deep_model[False]
tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_categorical_one_hot[False]
tests/unit/tf/models/test_ranking.py::test_wide_deep_model_hashed_cross[False]
tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[True]
tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]
/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/transforms/features.py:569: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag
warnings.warn(

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/autograph/impl/api.py:371: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag
return py_builtins.overload_of(f)(*args)

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_onehot_multihot_feature_interaction[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_feature_interaction_multi_optimizer[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask/GatherV2:0", shape=(None, 48), dtype=float32), dense_shape=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Reshape_3:0", shape=(None,), dtype=int64), values=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Reshape_2:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask/GatherV2:0", shape=(None, 48), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_3:0", shape=(None,), dtype=int64), values=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_2:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/torch/block/test_mlp.py::test_mlp_block
/var/jenkins_home/workspace/merlin_models/models/tests/unit/torch/_conftest.py:151: UserWarning: Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at ../torch/csrc/utils/tensor_new.cpp:201.)
return {key: torch.tensor(value) for key, value in data.items()}

tests/unit/xgb/test_xgboost.py::test_without_dask_client
tests/unit/xgb/test_xgboost.py::TestXGBoost::test_music_regression
tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs0-DaskDeviceQuantileDMatrix]
tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs1-DaskDMatrix]
tests/unit/xgb/test_xgboost.py::TestEvals::test_multiple
tests/unit/xgb/test_xgboost.py::TestEvals::test_default
tests/unit/xgb/test_xgboost.py::TestEvals::test_train_and_valid
tests/unit/xgb/test_xgboost.py::TestEvals::test_invalid_data
/var/jenkins_home/workspace/merlin_models/models/merlin/models/xgb/init.py:344: UserWarning: Ignoring list columns as inputs to XGBoost model: ['item_genres', 'user_genres'].
warnings.warn(f"Ignoring list columns as inputs to XGBoost model: {list_column_names}.")

tests/unit/xgb/test_xgboost.py::TestXGBoost::test_unsupported_objective
/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/tornado/ioloop.py:350: DeprecationWarning: make_current is deprecated; start the event loop first
self.make_current()

tests/unit/xgb/test_xgboost.py: 14 warnings
/usr/local/lib/python3.8/dist-packages/xgboost/dask.py:884: RuntimeWarning: coroutine 'Client._wait_for_workers' was never awaited
client.wait_for_workers(n_workers)
Enable tracemalloc to get traceback where the object was allocated.
See https://docs.pytest.org/en/stable/how-to/capture-warnings.html#resource-warnings for more info.

tests/unit/xgb/test_xgboost.py: 11 warnings
/usr/local/lib/python3.8/dist-packages/cudf/core/dataframe.py:1183: DeprecationWarning: The default dtype for empty Series will be 'object' instead of 'float64' in a future version. Specify a dtype explicitly to silence this warning.
mask = pd.Series(mask)

-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html

---------- coverage: platform linux, python 3.8.10-final-0 -----------
Name Stmts Miss Cover

merlin/datasets/init.py 2 0 100%
merlin/datasets/advertising/init.py 2 0 100%
merlin/datasets/advertising/criteo/init.py 0 0 100%
merlin/datasets/advertising/criteo/dataset.py 79 49 38%
merlin/datasets/advertising/criteo/transformed/init.py 0 0 100%
merlin/datasets/ecommerce/init.py 4 0 100%
merlin/datasets/ecommerce/aliccp/init.py 0 0 100%
merlin/datasets/ecommerce/aliccp/dataset.py 141 87 38%
merlin/datasets/ecommerce/aliccp/raw/init.py 0 0 100%
merlin/datasets/ecommerce/aliccp/transformed/init.py 0 0 100%
merlin/datasets/ecommerce/booking/init.py 0 0 100%
merlin/datasets/ecommerce/booking/dataset.py 127 100 21%
merlin/datasets/ecommerce/booking/transformed/init.py 0 0 100%
merlin/datasets/ecommerce/dressipi/init.py 0 0 100%
merlin/datasets/ecommerce/dressipi/dataset.py 45 37 18%
merlin/datasets/ecommerce/dressipi/preprocessed/init.py 0 0 100%
merlin/datasets/ecommerce/large/init.py 0 0 100%
merlin/datasets/ecommerce/small/init.py 0 0 100%
merlin/datasets/ecommerce/transactions/init.py 0 0 100%
merlin/datasets/entertainment/init.py 2 0 100%
merlin/datasets/entertainment/movielens/1m-raw/init.py 0 0 100%
merlin/datasets/entertainment/movielens/1m-raw/ratings/init.py 0 0 100%
merlin/datasets/entertainment/movielens/1m/init.py 0 0 100%
merlin/datasets/entertainment/movielens/25m/init.py 0 0 100%
merlin/datasets/entertainment/movielens/100k/init.py 0 0 100%
merlin/datasets/entertainment/movielens/init.py 0 0 100%
merlin/datasets/entertainment/movielens/dataset.py 152 122 20%
merlin/datasets/entertainment/music_streaming/init.py 0 0 100%
merlin/datasets/social/init.py 0 0 100%
merlin/datasets/synthetic.py 147 14 90%
merlin/datasets/testing/init.py 0 0 100%
merlin/datasets/testing/sequence_testing/init.py 0 0 100%
merlin/models/init.py 2 0 100%
merlin/models/_version.py 354 205 42%
merlin/models/api.py 14 5 64%
merlin/models/config/init.py 0 0 100%
merlin/models/config/schema.py 62 0 100%
merlin/models/implicit/init.py 27 4 85%
merlin/models/io.py 15 0 100%
merlin/models/lightfm/init.py 23 0 100%
merlin/models/loader/init.py 0 0 100%
merlin/models/loader/backend.py 379 41 89%
merlin/models/loader/dataframe_iter.py 21 17 19%
merlin/models/loader/tf_utils.py 57 27 53%
merlin/models/loader/utils.py 40 15 62%
merlin/models/tf/init.py 70 0 100%
merlin/models/tf/blocks/init.py 0 0 100%
merlin/models/tf/blocks/cross.py 44 0 100%
merlin/models/tf/blocks/dlrm.py 49 2 96%
merlin/models/tf/blocks/experts.py 99 17 83%
merlin/models/tf/blocks/interaction.py 108 40 63%
merlin/models/tf/blocks/mlp.py 117 7 94%
merlin/models/tf/blocks/optimizer.py 173 12 93%
merlin/models/tf/blocks/retrieval/init.py 0 0 100%
merlin/models/tf/blocks/retrieval/base.py 169 62 63%
merlin/models/tf/blocks/retrieval/matrix_factorization.py 35 1 97%
merlin/models/tf/blocks/retrieval/two_tower.py 30 0 100%
merlin/models/tf/blocks/sampling/init.py 0 0 100%
merlin/models/tf/blocks/sampling/base.py 29 2 93%
merlin/models/tf/blocks/sampling/cross_batch.py 46 2 96%
merlin/models/tf/blocks/sampling/in_batch.py 35 0 100%
merlin/models/tf/blocks/sampling/queue.py 115 12 90%
merlin/models/tf/core/init.py 0 0 100%
merlin/models/tf/core/aggregation.py 241 45 81%
merlin/models/tf/core/base.py 244 50 80%
merlin/models/tf/core/combinators.py 426 53 88%
merlin/models/tf/core/encoder.py 175 28 84%
merlin/models/tf/core/index.py 104 16 85%
merlin/models/tf/core/prediction.py 50 1 98%
merlin/models/tf/core/tabular.py 280 29 90%
merlin/models/tf/distributed/init.py 0 0 100%
merlin/models/tf/distributed/backend.py 9 2 78%
merlin/models/tf/inputs/init.py 0 0 100%
merlin/models/tf/inputs/base.py 60 10 83%
merlin/models/tf/inputs/continuous.py 39 3 92%
merlin/models/tf/inputs/embedding.py 458 32 93%
merlin/models/tf/loader.py 268 94 65%
merlin/models/tf/losses/init.py 4 0 100%
merlin/models/tf/losses/base.py 9 0 100%
merlin/models/tf/losses/listwise.py 13 0 100%
merlin/models/tf/losses/pairwise.py 115 1 99%
merlin/models/tf/metrics/init.py 2 0 100%
merlin/models/tf/metrics/evaluation.py 105 48 54%
merlin/models/tf/metrics/topk.py 198 48 76%
merlin/models/tf/models/init.py 0 0 100%
merlin/models/tf/models/base.py 756 101 87%
merlin/models/tf/models/benchmark.py 16 0 100%
merlin/models/tf/models/ranking.py 67 3 96%
merlin/models/tf/models/retrieval.py 78 4 95%
merlin/models/tf/models/utils.py 10 1 90%
merlin/models/tf/outputs/init.py 0 0 100%
merlin/models/tf/outputs/base.py 123 17 86%
merlin/models/tf/outputs/classification.py 91 1 99%
merlin/models/tf/outputs/contrastive.py 147 10 93%
merlin/models/tf/outputs/regression.py 9 0 100%
merlin/models/tf/outputs/sampling/init.py 0 0 100%
merlin/models/tf/outputs/sampling/base.py 78 21 73%
merlin/models/tf/outputs/sampling/in_batch.py 37 1 97%
merlin/models/tf/outputs/sampling/popularity.py 27 1 96%
merlin/models/tf/outputs/topk.py 98 6 94%
merlin/models/tf/prediction_tasks/init.py 0 0 100%
merlin/models/tf/prediction_tasks/base.py 207 37 82%
merlin/models/tf/prediction_tasks/classification.py 68 17 75%
merlin/models/tf/prediction_tasks/multi.py 7 0 100%
merlin/models/tf/prediction_tasks/next_item.py 59 6 90%
merlin/models/tf/prediction_tasks/regression.py 35 2 94%
merlin/models/tf/prediction_tasks/retrieval.py 73 3 96%
merlin/models/tf/transformers/init.py 0 0 100%
merlin/models/tf/transformers/block.py 101 2 98%
merlin/models/tf/transformers/transforms.py 63 0 100%
merlin/models/tf/transforms/init.py 0 0 100%
merlin/models/tf/transforms/bias.py 111 9 92%
merlin/models/tf/transforms/features.py 435 36 92%
merlin/models/tf/transforms/negative_sampling.py 77 3 96%
merlin/models/tf/transforms/noise.py 43 1 98%
merlin/models/tf/transforms/regularization.py 17 1 94%
merlin/models/tf/transforms/sequence.py 282 42 85%
merlin/models/tf/transforms/tensor.py 158 13 92%
merlin/models/tf/typing.py 7 0 100%
merlin/models/tf/utils/init.py 0 0 100%
merlin/models/tf/utils/batch_utils.py 85 4 95%
merlin/models/tf/utils/repr_utils.py 69 4 94%
merlin/models/tf/utils/search_utils.py 34 22 35%
merlin/models/tf/utils/testing_utils.py 206 36 83%
merlin/models/tf/utils/tf_utils.py 209 42 80%
merlin/models/torch/init.py 12 0 100%
merlin/models/torch/block/init.py 0 0 100%
merlin/models/torch/block/base.py 167 32 81%
merlin/models/torch/block/mlp.py 38 5 87%
merlin/models/torch/dataset.py 68 5 93%
merlin/models/torch/features/init.py 0 0 100%
merlin/models/torch/features/base.py 4 0 100%
merlin/models/torch/features/continuous.py 22 0 100%
merlin/models/torch/features/embedding.py 165 12 93%
merlin/models/torch/features/tabular.py 65 8 88%
merlin/models/torch/losses.py 28 28 0%
merlin/models/torch/model/init.py 0 0 100%
merlin/models/torch/model/base.py 286 65 77%
merlin/models/torch/model/prediction_task.py 24 0 100%
merlin/models/torch/tabular/init.py 0 0 100%
merlin/models/torch/tabular/aggregation.py 75 0 100%
merlin/models/torch/tabular/base.py 247 39 84%
merlin/models/torch/tabular/transformations.py 67 3 96%
merlin/models/torch/typing.py 6 0 100%
merlin/models/torch/utils/init.py 0 0 100%
merlin/models/torch/utils/data_utils.py 117 117 0%
merlin/models/torch/utils/examples_utils.py 39 39 0%
merlin/models/torch/utils/torch_utils.py 80 22 72%
merlin/models/utils/init.py 0 0 100%
merlin/models/utils/constants.py 3 0 100%
merlin/models/utils/dataset.py 38 4 89%
merlin/models/utils/dependencies.py 26 19 27%
merlin/models/utils/doc_utils.py 10 0 100%
merlin/models/utils/example_utils.py 31 2 94%
merlin/models/utils/misc_utils.py 118 90 24%
merlin/models/utils/nvt_utils.py 27 24 11%
merlin/models/utils/registry.py 101 29 71%
merlin/models/utils/schema_utils.py 90 19 79%
merlin/models/xgb/init.py 124 4 97%

TOTAL 11575 2352 80%

=========================== short test summary info ============================
SKIPPED [1] tests/unit/datasets/test_advertising.py:20: No data-dir available, pass it through env variable $INPUT_DATA_DIR
SKIPPED [1] tests/unit/datasets/test_ecommerce.py:64: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP
SKIPPED [1] tests/unit/datasets/test_ecommerce.py:80: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP
SKIPPED [1] tests/unit/datasets/test_ecommerce.py:94: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP
SKIPPED [1] tests/unit/datasets/test_ecommerce.py:115: No data-dir available, pass it through env variable $INPUT_DATA_DIR
SKIPPED [3] tests/unit/datasets/test_entertainment.py:44: No data-dir available, pass it through env variable $INPUT_DATA_DIR
SKIPPED [5] ../../../.local/lib/python3.8/site-packages/tensorflow/python/framework/test_util.py:2746: Not a test.
========= 866 passed, 13 skipped, 1438 warnings in 1733.50s (0:28:53) ==========
___________________________________ summary ____________________________________
py38-gpu: commands succeeded
congratulations :)
Performing Post build task...
Match found for : : True
Logical operation result is TRUE
Running script : #!/bin/bash
cd /var/jenkins_home/
CUDA_VISIBLE_DEVICES=1 python test_res_push.py "https://api.GitHub.com/repos/NVIDIA-Merlin/models/issues/$ghprbPullId/comments" "/var/jenkins_home/jobs/$JOB_NAME/builds/$BUILD_NUMBER/log"
[merlin_models] $ /bin/bash /tmp/jenkins6777933211502142716.sh

@nvidia-merlin-bot
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GitHub pull request #855 of commit 16ac9cdeee360232e51bc308fd1572be5672f5c4, no merge conflicts.
Running as SYSTEM
Setting status of 16ac9cdeee360232e51bc308fd1572be5672f5c4 to PENDING with url http://merlin-infra1.nvidia.com:8080/job/merlin_models/1853/ and message: 'Pending'
Using context: Jenkins
Building on master in workspace /var/jenkins_home/workspace/merlin_models
using credential nvidia-merlin-bot
 > git rev-parse --is-inside-work-tree # timeout=10
Fetching changes from the remote Git repository
 > git config remote.origin.url https://github.com/NVIDIA-Merlin/models/ # timeout=10
Fetching upstream changes from https://github.com/NVIDIA-Merlin/models/
 > git --version # timeout=10
using GIT_ASKPASS to set credentials This is the bot credentials for our CI/CD
 > git fetch --tags --force --progress -- https://github.com/NVIDIA-Merlin/models/ +refs/pull/855/*:refs/remotes/origin/pr/855/* # timeout=10
 > git rev-parse 16ac9cdeee360232e51bc308fd1572be5672f5c4^{commit} # timeout=10
Checking out Revision 16ac9cdeee360232e51bc308fd1572be5672f5c4 (detached)
 > git config core.sparsecheckout # timeout=10
 > git checkout -f 16ac9cdeee360232e51bc308fd1572be5672f5c4 # timeout=10
Commit message: "Merge branch 'multi-gpu-data-parallel' of https://github.com/bschifferer/models-1 into multi-gpu-data-parallel"
 > git rev-list --no-walk be39fc1de6ed0508e4f3c36c2c20b8ea61f8fda6 # timeout=10
[merlin_models] $ /bin/bash /tmp/jenkins12300731286798510711.sh
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Requirement already satisfied: testbook in /usr/local/lib/python3.8/dist-packages (0.4.2)
Requirement already satisfied: nbclient>=0.4.0 in /usr/local/lib/python3.8/dist-packages (from testbook) (0.6.8)
Requirement already satisfied: nbformat>=5.0.4 in /usr/local/lib/python3.8/dist-packages (from testbook) (5.5.0)
Requirement already satisfied: nest-asyncio in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (1.5.5)
Requirement already satisfied: traitlets>=5.2.2 in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (5.4.0)
Requirement already satisfied: jupyter-client>=6.1.5 in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (7.3.5)
Requirement already satisfied: fastjsonschema in /usr/local/lib/python3.8/dist-packages (from nbformat>=5.0.4->testbook) (2.16.1)
Requirement already satisfied: jupyter_core in /usr/local/lib/python3.8/dist-packages (from nbformat>=5.0.4->testbook) (4.11.1)
Requirement already satisfied: jsonschema>=2.6 in /usr/local/lib/python3.8/dist-packages (from nbformat>=5.0.4->testbook) (4.16.0)
Requirement already satisfied: pkgutil-resolve-name>=1.3.10 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (1.3.10)
Requirement already satisfied: pyrsistent!=0.17.0,!=0.17.1,!=0.17.2,>=0.14.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (0.18.1)
Requirement already satisfied: attrs>=17.4.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (22.1.0)
Requirement already satisfied: importlib-resources>=1.4.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (5.9.0)
Requirement already satisfied: pyzmq>=23.0 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (24.0.0)
Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (2.8.2)
Requirement already satisfied: tornado>=6.2 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (6.2)
Requirement already satisfied: entrypoints in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (0.4)
Requirement already satisfied: zipp>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from importlib-resources>=1.4.0->jsonschema>=2.6->nbformat>=5.0.4->testbook) (3.8.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.8.2->jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (1.15.0)
GLOB sdist-make: /var/jenkins_home/workspace/merlin_models/models/setup.py
py38-gpu recreate: /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
py38-gpu installdeps: -rrequirements/dev.txt, tensorflow<2.10
WARNING: Discarding $PYTHONPATH from environment, to override specify PYTHONPATH in 'passenv' in your configuration.
py38-gpu inst: /var/jenkins_home/workspace/merlin_models/models/.tox/.tmp/package/3/merlin-models-0.9.0+51.g16ac9cde.zip
WARNING: Discarding $PYTHONPATH from environment, to override specify PYTHONPATH in 'passenv' in your configuration.
py38-gpu installed: absl-py==1.2.0,aiohttp==3.8.1,aiosignal==1.2.0,alabaster==0.7.12,alembic==1.8.1,anyio==3.6.1,appdirs==1.4.4,argon2-cffi==21.3.0,argon2-cffi-bindings==21.2.0,astroid==2.5.6,asttokens==2.0.8,astunparse==1.6.3,asv==0.5.1,asvdb==0.4.2,async-timeout==4.0.2,attrs==22.1.0,autopage==0.5.1,awscli==1.27.10,Babel==2.10.3,backcall==0.2.0,beautifulsoup4==4.11.1,betterproto==1.2.5,black==20.8b1,bleach==5.0.1,bokeh==3.0.2,boto3==1.24.75,botocore==1.29.10,Brotli==1.0.9,build==0.9.0,cachetools==5.2.0,certifi==2019.11.28,cffi==1.15.1,chardet==3.0.4,charset-normalizer==2.1.1,check-manifest==0.48,clang==5.0,click==8.1.3,cliff==4.0.0,cloudpickle==2.2.0,cmaes==0.9.0,cmake==3.24.1.1,cmd2==2.4.2,colorama==0.4.4,colorlog==6.7.0,contourpy==1.0.5,coverage==6.5.0,cuda-python==11.7.1,cupy-cuda117==10.6.0,cycler==0.11.0,Cython==0.29.32,dask==2022.1.1,dbus-python==1.2.16,debugpy==1.6.3,decorator==5.1.1,defusedxml==0.7.1,dill==0.3.5.1,distlib==0.3.6,distributed==2022.5.1,distro==1.7.0,dm-tree==0.1.6,docker-pycreds==0.4.0,docutils==0.16,emoji==1.7.0,entrypoints==0.4,execnet==1.9.0,executing==1.0.0,faiss==1.7.2,faiss-gpu==1.7.2,fastai==2.7.9,fastapi==0.85.0,fastavro==1.6.1,fastcore==1.5.27,fastdownload==0.0.7,fastjsonschema==2.16.1,fastprogress==1.0.3,fastrlock==0.8,feast==0.19.4,fiddle==0.2.2,filelock==3.8.0,flake8==5.0.4,flatbuffers==1.12,fonttools==4.37.3,frozenlist==1.3.1,fsspec==2022.5.0,gast==0.4.0,gevent==21.12.0,geventhttpclient==2.0.2,gitdb==4.0.9,GitPython==3.1.27,google==3.0.0,google-api-core==2.10.1,google-auth==2.11.1,google-auth-oauthlib==0.4.6,google-pasta==0.2.0,googleapis-common-protos==1.52.0,graphviz==0.20.1,greenlet==1.1.3,grpcio==1.41.0,grpcio-channelz==1.49.0,grpcio-reflection==1.48.1,grpclib==0.4.3,h11==0.13.0,h2==4.1.0,h5py==3.7.0,HeapDict==1.0.1,horovod==0.26.1,hpack==4.0.0,httptools==0.5.0,hugectr2onnx==0.0.0,huggingface-hub==0.9.1,hyperframe==6.0.1,idna==2.8,imagesize==1.4.1,implicit==0.6.1,importlib-metadata==4.12.0,importlib-resources==5.9.0,iniconfig==1.1.1,interrogate==1.5.0,ipykernel==6.15.3,ipython==8.5.0,ipython-genutils==0.2.0,ipywidgets==7.7.0,isort==5.10.1,jedi==0.18.1,Jinja2==3.1.2,jmespath==1.0.1,joblib==1.2.0,json5==0.9.10,jsonschema==4.16.0,jupyter==1.0.0,jupyter-cache==0.4.3,jupyter-console==6.4.4,jupyter-core==4.11.1,jupyter-server==1.18.1,jupyter-server-mathjax==0.2.5,jupyter-sphinx==0.3.2,jupyter_client==7.3.5,jupyterlab==3.4.7,jupyterlab-pygments==0.2.2,jupyterlab-widgets==1.1.0,jupyterlab_server==2.15.1,keras==2.9.0,Keras-Preprocessing==1.1.2,kiwisolver==1.4.4,lazy-object-proxy==1.8.0,libclang==14.0.6,libcst==0.4.7,lightfm==1.16,lightgbm==3.3.2,linkify-it-py==1.0.3,llvmlite==0.39.1,locket==1.0.0,lxml==4.9.1,Mako==1.2.4,Markdown==3.4.1,markdown-it-py==1.1.0,MarkupSafe==2.1.1,matplotlib==3.6.0,matplotlib-inline==0.1.6,mccabe==0.7.0,mdit-py-plugins==0.2.8,merlin-core==0.6.0+1.g5926fcf,merlin-models==0.9.0+51.g16ac9cde,merlin-systems==0.5.0+4.g15074ad,mistune==2.0.4,mmh3==3.0.0,mpi4py==3.1.3,msgpack==1.0.4,multidict==6.0.2,mypy==0.991,mypy-extensions==0.4.3,myst-nb==0.13.2,myst-parser==0.15.2,natsort==8.1.0,nbclassic==0.4.3,nbclient==0.6.8,nbconvert==7.0.0,nbdime==3.1.1,nbformat==5.5.0,nest-asyncio==1.5.5,ninja==1.10.2.3,notebook==6.4.12,notebook-shim==0.1.0,numba==0.56.2,numpy==1.22.4,nvidia-pyindex==1.0.9,# Editable install with no version control (nvtabular==1.4.0+8.g95e12d347),-e /usr/local/lib/python3.8/dist-packages,nvtx==0.2.5,oauthlib==3.2.1,oldest-supported-numpy==2022.8.16,onnx==1.12.0,onnxruntime==1.11.1,opt-einsum==3.3.0,optuna==3.0.3,packaging==21.3,pandas==1.3.5,pandavro==1.5.2,pandocfilters==1.5.0,parso==0.8.3,partd==1.3.0,pathspec==0.10.2,pathtools==0.1.2,pbr==5.11.0,pep517==0.13.0,pexpect==4.8.0,pickleshare==0.7.5,Pillow==9.2.0,pkgutil_resolve_name==1.3.10,platformdirs==2.5.2,plotly==5.11.0,pluggy==1.0.0,prettytable==3.5.0,prometheus-client==0.14.1,promise==2.3,prompt-toolkit==3.0.31,proto-plus==1.19.6,protobuf==3.19.5,psutil==5.9.2,ptyprocess==0.7.0,pure-eval==0.2.2,py==1.11.0,pyarrow==7.0.0,pyasn1==0.4.8,pyasn1-modules==0.2.8,pybind11==2.10.0,pycodestyle==2.9.1,pycparser==2.21,pydantic==1.10.2,pydot==1.4.2,pyflakes==2.5.0,Pygments==2.13.0,PyGObject==3.36.0,pynvml==11.4.1,pyparsing==3.0.9,pyperclip==1.8.2,pyrsistent==0.18.1,pytest==7.1.3,pytest-cov==4.0.0,pytest-xdist==3.0.2,python-apt==2.0.0+ubuntu0.20.4.8,python-dateutil==2.8.2,python-dotenv==0.21.0,python-rapidjson==1.8,pytz==2022.2.1,PyYAML==5.4.1,pyzmq==24.0.0,qtconsole==5.4.0,QtPy==2.3.0,regex==2022.9.13,requests==2.22.0,requests-oauthlib==1.3.1,requests-unixsocket==0.2.0,rsa==4.7.2,s3fs==2022.2.0,s3transfer==0.6.0,sacremoses==0.0.53,scikit-build==0.15.0,scikit-learn==1.1.2,scipy==1.8.1,seedir==0.3.0,Send2Trash==1.8.0,sentry-sdk==1.9.8,setproctitle==1.3.2,setuptools-scm==7.0.5,shortuuid==1.0.9,six==1.15.0,sklearn==0.0,smmap==5.0.0,sniffio==1.3.0,snowballstemmer==2.2.0,sortedcontainers==2.4.0,soupsieve==2.3.2.post1,Sphinx==5.3.0,sphinx-multiversion==0.2.4,sphinx-togglebutton==0.3.1,sphinx_external_toc==0.3.0,sphinxcontrib-applehelp==1.0.2,sphinxcontrib-copydirs @ git+https://github.com/mikemckiernan/sphinxcontrib-copydirs.git@bd8c5d79b3f91cf5f1bb0d6995aeca3fe84b670e,sphinxcontrib-devhelp==1.0.2,sphinxcontrib-htmlhelp==2.0.0,sphinxcontrib-jsmath==1.0.1,sphinxcontrib-qthelp==1.0.3,sphinxcontrib-serializinghtml==1.1.5,SQLAlchemy==1.4.44,stack-data==0.5.0,starlette==0.20.4,stevedore==4.1.1,stringcase==1.2.0,supervisor==4.1.0,tabulate==0.8.10,tblib==1.7.0,tdqm==0.0.1,tenacity==8.0.1,tensorboard==2.9.1,tensorboard-data-server==0.6.1,tensorboard-plugin-wit==1.8.1,tensorflow==2.9.2,tensorflow-estimator==2.9.0,tensorflow-gpu==2.9.2,tensorflow-io-gcs-filesystem==0.27.0,tensorflow-metadata==1.10.0,tensorflow-ranking==0.5.1,tensorflow-serving-api==2.9.2,termcolor==2.0.1,terminado==0.15.0,testbook==0.4.2,threadpoolctl==3.1.0,tinycss2==1.1.1,tokenizers==0.10.3,toml==0.10.2,tomli==2.0.1,toolz==0.12.0,torch==1.12.1+cu113,torchmetrics==0.3.2,tornado==6.2,tox==3.26.0,tqdm==4.64.1,traitlets==5.4.0,transformers==4.12.0,transformers4rec==0.1.12+2.gbcc939255,treelite==2.3.0,treelite-runtime==2.3.0,tritonclient==2.25.0,typed-ast==1.5.4,typing-inspect==0.8.0,typing_extensions==4.3.0,uc-micro-py==1.0.1,urllib3==1.26.12,uvicorn==0.18.3,uvloop==0.17.0,versioneer==0.20,virtualenv==20.16.5,wandb==0.13.3,watchfiles==0.17.0,wcwidth==0.2.5,webencodings==0.5.1,websocket-client==1.4.1,websockets==10.3,Werkzeug==2.2.2,widgetsnbextension==3.6.0,wrapt==1.12.1,xgboost==1.6.2,xyzservices==2022.9.0,yarl==1.8.1,zict==2.2.0,zipp==3.8.1,zope.event==4.5.0,zope.interface==5.4.0
py38-gpu run-test-pre: PYTHONHASHSEED='15692844'
py38-gpu run-test: commands[0] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/core.git
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Collecting git+https://github.com/NVIDIA-Merlin/core.git
  Cloning https://github.com/NVIDIA-Merlin/core.git to /tmp/pip-req-build-ihrffwoy
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/core.git /tmp/pip-req-build-ihrffwoy
  Resolved https://github.com/NVIDIA-Merlin/core.git to commit eb606d54fa2ddcbb7e4d0e6501ab2eb418c7fba9
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: protobuf>=3.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+11.geb606d5) (3.19.5)
Requirement already satisfied: distributed>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+11.geb606d5) (2022.3.0)
Requirement already satisfied: tqdm>=4.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+11.geb606d5) (4.64.1)
Requirement already satisfied: dask>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+11.geb606d5) (2022.3.0)
Requirement already satisfied: packaging in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+11.geb606d5) (21.3)
Requirement already satisfied: numba>=0.54 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+11.geb606d5) (0.55.1)
Requirement already satisfied: pandas<1.4.0dev0,>=1.2.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+11.geb606d5) (1.3.5)
Requirement already satisfied: pyarrow>=5.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+11.geb606d5) (7.0.0)
Requirement already satisfied: tensorflow-metadata>=1.2.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+11.geb606d5) (1.10.0)
Requirement already satisfied: betterproto<2.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+11.geb606d5) (1.2.5)
Requirement already satisfied: fsspec==2022.5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+11.geb606d5) (2022.5.0)
Requirement already satisfied: grpclib in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core==0.8.0+11.geb606d5) (0.4.3)
Requirement already satisfied: stringcase in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core==0.8.0+11.geb606d5) (1.2.0)
Requirement already satisfied: pyyaml>=5.3.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/PyYAML-5.4.1-py3.8-linux-x86_64.egg (from dask>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (5.4.1)
Requirement already satisfied: cloudpickle>=1.1.1 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (2.2.0)
Requirement already satisfied: partd>=0.3.10 in /var/jenkins_home/.local/lib/python3.8/site-packages/partd-1.2.0-py3.8.egg (from dask>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (1.2.0)
Requirement already satisfied: toolz>=0.8.2 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core==0.8.0+11.geb606d5) (0.12.0)
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Building wheels for collected packages: merlin-core
  Building wheel for merlin-core (pyproject.toml): started
  Building wheel for merlin-core (pyproject.toml): finished with status 'done'
  Created wheel for merlin-core: filename=merlin_core-0.8.0+11.geb606d5-py3-none-any.whl size=118619 sha256=66368cf9bdbe44a4f30ccccc84e901170276dda161174cd53710b8ea956f2437
  Stored in directory: /tmp/pip-ephem-wheel-cache-2tqw127t/wheels/c8/38/16/a6968787eafcec5fa772148af8408b089562f71af0752e8e84
Successfully built merlin-core
Installing collected packages: merlin-core
  Attempting uninstall: merlin-core
    Found existing installation: merlin-core 0.3.0+12.g78ecddd
    Not uninstalling merlin-core at /var/jenkins_home/.local/lib/python3.8/site-packages, outside environment /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
    Can't uninstall 'merlin-core'. No files were found to uninstall.
Successfully installed merlin-core-0.8.0+11.geb606d5
py38-gpu run-test: commands[1] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/nvtabular.git
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Collecting git+https://github.com/NVIDIA-Merlin/nvtabular.git
  Cloning https://github.com/NVIDIA-Merlin/nvtabular.git to /tmp/pip-req-build-wpsyncq5
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/nvtabular.git /tmp/pip-req-build-wpsyncq5
  Resolved https://github.com/NVIDIA-Merlin/nvtabular.git to commit ba4c14159a8e858c8998d4158a4376e65a8fa266
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Collecting merlin-dataloader>=0.0.2
  Downloading merlin-dataloader-0.0.2.tar.gz (44 kB)
     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 44.1/44.1 kB 1.7 MB/s eta 0:00:00
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: scipy in /usr/local/lib/python3.8/dist-packages (from nvtabular==1.6.0+4.gba4c1415) (1.8.1)
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Requirement already satisfied: setuptools in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (65.5.1)
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Requirement already satisfied: googleapis-common-protos<2,>=1.52.0 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (1.52.0)
Requirement already satisfied: absl-py<2.0.0,>=0.9 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (1.2.0)
Requirement already satisfied: locket in /var/jenkins_home/.local/lib/python3.8/site-packages/locket-0.2.1-py3.8.egg (from partd>=0.3.10->dask>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (0.2.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.7.3->pandas<1.4.0dev0,>=1.2.0->merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (1.15.0)
Requirement already satisfied: heapdict in /var/jenkins_home/.local/lib/python3.8/site-packages/HeapDict-1.0.1-py3.8.egg (from zict>=0.1.3->distributed>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (1.0.1)
Requirement already satisfied: multidict in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (6.0.2)
Requirement already satisfied: h2<5,>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (4.1.0)
Requirement already satisfied: MarkupSafe>=2.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from jinja2->distributed>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (2.0.1)
Requirement already satisfied: hpack<5,>=4.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (4.0.0)
Requirement already satisfied: hyperframe<7,>=6.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (6.0.1)
Building wheels for collected packages: nvtabular, merlin-dataloader
  Building wheel for nvtabular (pyproject.toml): started
  Building wheel for nvtabular (pyproject.toml): finished with status 'done'
  Created wheel for nvtabular: filename=nvtabular-1.6.0+4.gba4c1415-cp38-cp38-linux_x86_64.whl size=257596 sha256=62c797985ad00832c6bfb2a015e60ca2923dcb159f47b88f8e85d1eebb05055e
  Stored in directory: /tmp/pip-ephem-wheel-cache-wvxa265i/wheels/8f/d9/f9/30f2cdc5bf8787fae6fdfe55afd6e1b493e619ec32c32ec40b
  Building wheel for merlin-dataloader (pyproject.toml): started
  Building wheel for merlin-dataloader (pyproject.toml): finished with status 'done'
  Created wheel for merlin-dataloader: filename=merlin_dataloader-0.0.2-py3-none-any.whl size=29203 sha256=3a00a61865f487d0c8b31dc38c13862c1dd8202eb4fcab2174541e7a26012c2a
  Stored in directory: /tmp/pip-ephem-wheel-cache-wvxa265i/wheels/76/ef/ed/cb880e3ef5192ec5940e26fd9442247b569fb0cf8602f97137
Successfully built nvtabular merlin-dataloader
Installing collected packages: merlin-dataloader, nvtabular
  Attempting uninstall: nvtabular
    Found existing installation: nvtabular 1.1.1
    Not uninstalling nvtabular at /var/jenkins_home/.local/lib/python3.8/site-packages, outside environment /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
    Can't uninstall 'nvtabular'. No files were found to uninstall.
Successfully installed merlin-dataloader-0.0.2 nvtabular-1.6.0+4.gba4c1415
py38-gpu run-test: commands[2] | python -m pytest --cov-report term --cov merlin -rxs tests/unit
============================= test session starts ==============================
platform linux -- Python 3.8.10, pytest-7.1.3, pluggy-1.0.0
cachedir: .tox/py38-gpu/.pytest_cache
rootdir: /var/jenkins_home/workspace/merlin_models/models, configfile: pyproject.toml
plugins: anyio-3.5.0, xdist-3.0.2, cov-4.0.0
collected 879 items

tests/unit/config/test_schema.py .... [ 0%]
tests/unit/datasets/test_advertising.py .s [ 0%]
tests/unit/datasets/test_ecommerce.py ..sss.s [ 1%]
tests/unit/datasets/test_entertainment.py ....sss. [ 2%]
tests/unit/datasets/test_social.py . [ 2%]
tests/unit/datasets/test_synthetic.py ...... [ 3%]
tests/unit/implicit/test_implicit.py . [ 3%]
tests/unit/lightfm/test_lightfm.py . [ 3%]
tests/unit/tf/test_core.py ...... [ 4%]
tests/unit/tf/test_loader.py ................ [ 5%]
tests/unit/tf/test_public_api.py . [ 6%]
tests/unit/tf/blocks/test_cross.py ........... [ 7%]
tests/unit/tf/blocks/test_dlrm.py .......... [ 8%]
tests/unit/tf/blocks/test_interactions.py ... [ 8%]
tests/unit/tf/blocks/test_mlp.py ....................................... [ 13%]
............................ [ 16%]
tests/unit/tf/blocks/test_optimizer.py s................................ [ 20%]
..................... [ 22%]
tests/unit/tf/blocks/retrieval/test_base.py . [ 22%]
tests/unit/tf/blocks/retrieval/test_matrix_factorization.py .. [ 22%]
tests/unit/tf/blocks/retrieval/test_two_tower.py ............ [ 24%]
tests/unit/tf/blocks/sampling/test_cross_batch.py . [ 24%]
tests/unit/tf/blocks/sampling/test_in_batch.py . [ 24%]
tests/unit/tf/core/test_aggregation.py ......... [ 25%]
tests/unit/tf/core/test_base.py .. [ 25%]
tests/unit/tf/core/test_combinators.py s..................... [ 28%]
tests/unit/tf/core/test_encoder.py .. [ 28%]
tests/unit/tf/core/test_index.py ... [ 28%]
tests/unit/tf/core/test_prediction.py .. [ 29%]
tests/unit/tf/core/test_tabular.py ...... [ 29%]
tests/unit/tf/examples/test_01_getting_started.py . [ 29%]
tests/unit/tf/examples/test_02_dataschema.py . [ 29%]
tests/unit/tf/examples/test_03_exploring_different_models.py . [ 30%]
tests/unit/tf/examples/test_04_export_ranking_models.py . [ 30%]
tests/unit/tf/examples/test_05_export_retrieval_model.py . [ 30%]
tests/unit/tf/examples/test_06_advanced_own_architecture.py . [ 30%]
tests/unit/tf/examples/test_07_train_traditional_models.py . [ 30%]
tests/unit/tf/examples/test_usecase_accelerate_training_by_lazyadam.py . [ 30%]
[ 30%]
tests/unit/tf/examples/test_usecase_data_parallel.py . [ 30%]
tests/unit/tf/examples/test_usecase_ecommerce_session_based.py . [ 30%]
tests/unit/tf/examples/test_usecase_incremental_training_layer_freezing.py . [ 30%]
[ 30%]
tests/unit/tf/examples/test_usecase_pretrained_embeddings.py . [ 31%]
tests/unit/tf/examples/test_usecase_retrieval_with_hpo.py . [ 31%]
tests/unit/tf/horovod/test_horovod.py ... [ 31%]
tests/unit/tf/inputs/test_base.py . [ 31%]
tests/unit/tf/inputs/test_continuous.py ........ [ 32%]
tests/unit/tf/inputs/test_embedding.py ................................. [ 36%]
........ [ 37%]
tests/unit/tf/inputs/test_tabular.py .................. [ 39%]
tests/unit/tf/layers/test_queue.py .............. [ 40%]
tests/unit/tf/losses/test_losses.py ....................... [ 43%]
tests/unit/tf/metrics/test_metrics_popularity.py ..... [ 44%]
tests/unit/tf/metrics/test_metrics_topk.py ......................... [ 46%]
tests/unit/tf/models/test_base.py s......................... [ 49%]
tests/unit/tf/models/test_benchmark.py .. [ 50%]
tests/unit/tf/models/test_ranking.py .................................. [ 53%]
tests/unit/tf/models/test_retrieval.py ................................. [ 57%]
........................................... [ 62%]
tests/unit/tf/outputs/test_base.py ...... [ 63%]
tests/unit/tf/outputs/test_classification.py ...... [ 63%]
tests/unit/tf/outputs/test_contrastive.py .............. [ 65%]
tests/unit/tf/outputs/test_regression.py .. [ 65%]
tests/unit/tf/outputs/test_sampling.py .... [ 66%]
tests/unit/tf/outputs/test_topk.py . [ 66%]
tests/unit/tf/prediction_tasks/test_classification.py .. [ 66%]
tests/unit/tf/prediction_tasks/test_multi_task.py ................ [ 68%]
tests/unit/tf/prediction_tasks/test_next_item.py ..... [ 68%]
tests/unit/tf/prediction_tasks/test_regression.py ..... [ 69%]
tests/unit/tf/prediction_tasks/test_retrieval.py . [ 69%]
tests/unit/tf/prediction_tasks/test_sampling.py ...... [ 70%]
tests/unit/tf/transformers/test_block.py ...................... [ 72%]
tests/unit/tf/transformers/test_transforms.py .......... [ 73%]
tests/unit/tf/transforms/test_bias.py .. [ 74%]
tests/unit/tf/transforms/test_features.py s............................. [ 77%]
.......................s...... [ 81%]
tests/unit/tf/transforms/test_negative_sampling.py ......... [ 82%]
tests/unit/tf/transforms/test_noise.py ..... [ 82%]
tests/unit/tf/transforms/test_sequence.py .................... [ 84%]
tests/unit/tf/transforms/test_tensor.py ... [ 85%]
tests/unit/tf/utils/test_batch.py .... [ 85%]
tests/unit/tf/utils/test_dataset.py .. [ 85%]
tests/unit/tf/utils/test_tf_utils.py ..... [ 86%]
tests/unit/torch/test_dataset.py ......... [ 87%]
tests/unit/torch/test_public_api.py . [ 87%]
tests/unit/torch/block/test_base.py .... [ 88%]
tests/unit/torch/block/test_mlp.py . [ 88%]
tests/unit/torch/features/test_continuous.py .. [ 88%]
tests/unit/torch/features/test_embedding.py .............. [ 89%]
tests/unit/torch/features/test_tabular.py .... [ 90%]
tests/unit/torch/model/test_head.py ............ [ 91%]
tests/unit/torch/model/test_model.py .. [ 92%]
tests/unit/torch/tabular/test_aggregation.py ........ [ 92%]
tests/unit/torch/tabular/test_tabular.py ... [ 93%]
tests/unit/torch/tabular/test_transformations.py ....... [ 94%]
tests/unit/utils/test_schema_utils.py ................................ [ 97%]
tests/unit/xgb/test_xgboost.py .................... [100%]

=============================== warnings summary ===============================
../../../../../usr/lib/python3/dist-packages/requests/init.py:89
/usr/lib/python3/dist-packages/requests/init.py:89: RequestsDependencyWarning: urllib3 (1.26.12) or chardet (3.0.4) doesn't match a supported version!
warnings.warn("urllib3 ({}) or chardet ({}) doesn't match a supported "

../../../.local/lib/python3.8/site-packages/flatbuffers/compat.py:19
/var/jenkins_home/.local/lib/python3.8/site-packages/flatbuffers/compat.py:19: DeprecationWarning: the imp module is deprecated in favour of importlib; see the module's documentation for alternative uses
import imp

../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36
/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36: DeprecationWarning: NEAREST is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.NEAREST or Dither.NONE instead.
'nearest': pil_image.NEAREST,

../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37
/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37: DeprecationWarning: BILINEAR is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BILINEAR instead.
'bilinear': pil_image.BILINEAR,

../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38
/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38: DeprecationWarning: BICUBIC is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BICUBIC instead.
'bicubic': pil_image.BICUBIC,

../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39
/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39: DeprecationWarning: HAMMING is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.HAMMING instead.
'hamming': pil_image.HAMMING,

../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40
/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40: DeprecationWarning: BOX is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BOX instead.
'box': pil_image.BOX,

../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41
/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41: DeprecationWarning: LANCZOS is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.LANCZOS instead.
'lanczos': pil_image.LANCZOS,

tests/unit/datasets/test_advertising.py: 1 warning
tests/unit/datasets/test_ecommerce.py: 3 warnings
tests/unit/datasets/test_entertainment.py: 4 warnings
tests/unit/datasets/test_social.py: 1 warning
tests/unit/datasets/test_synthetic.py: 6 warnings
tests/unit/implicit/test_implicit.py: 1 warning
tests/unit/lightfm/test_lightfm.py: 1 warning
tests/unit/tf/test_core.py: 6 warnings
tests/unit/tf/test_loader.py: 1 warning
tests/unit/tf/blocks/test_cross.py: 5 warnings
tests/unit/tf/blocks/test_dlrm.py: 9 warnings
tests/unit/tf/blocks/test_interactions.py: 2 warnings
tests/unit/tf/blocks/test_mlp.py: 60 warnings
tests/unit/tf/blocks/test_optimizer.py: 30 warnings
tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings
tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings
tests/unit/tf/core/test_aggregation.py: 6 warnings
tests/unit/tf/core/test_base.py: 2 warnings
tests/unit/tf/core/test_combinators.py: 11 warnings
tests/unit/tf/core/test_encoder.py: 6 warnings
tests/unit/tf/core/test_index.py: 8 warnings
tests/unit/tf/core/test_prediction.py: 2 warnings
tests/unit/tf/horovod/test_horovod.py: 3 warnings
tests/unit/tf/inputs/test_base.py: 1 warning
tests/unit/tf/inputs/test_continuous.py: 7 warnings
tests/unit/tf/inputs/test_embedding.py: 20 warnings
tests/unit/tf/inputs/test_tabular.py: 18 warnings
tests/unit/tf/models/test_base.py: 28 warnings
tests/unit/tf/models/test_benchmark.py: 2 warnings
tests/unit/tf/models/test_ranking.py: 38 warnings
tests/unit/tf/models/test_retrieval.py: 120 warnings
tests/unit/tf/outputs/test_base.py: 6 warnings
tests/unit/tf/outputs/test_classification.py: 6 warnings
tests/unit/tf/outputs/test_contrastive.py: 19 warnings
tests/unit/tf/outputs/test_regression.py: 2 warnings
tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings
tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings
tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings
tests/unit/tf/prediction_tasks/test_retrieval.py: 1 warning
tests/unit/tf/transformers/test_block.py: 16 warnings
tests/unit/tf/transforms/test_bias.py: 2 warnings
tests/unit/tf/transforms/test_features.py: 10 warnings
tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings
tests/unit/tf/transforms/test_noise.py: 1 warning
tests/unit/tf/transforms/test_sequence.py: 15 warnings
tests/unit/tf/utils/test_batch.py: 9 warnings
tests/unit/tf/utils/test_dataset.py: 2 warnings
tests/unit/torch/block/test_base.py: 4 warnings
tests/unit/torch/block/test_mlp.py: 1 warning
tests/unit/torch/features/test_continuous.py: 1 warning
tests/unit/torch/features/test_embedding.py: 4 warnings
tests/unit/torch/features/test_tabular.py: 4 warnings
tests/unit/torch/model/test_head.py: 12 warnings
tests/unit/torch/model/test_model.py: 2 warnings
tests/unit/torch/tabular/test_aggregation.py: 6 warnings
tests/unit/torch/tabular/test_transformations.py: 3 warnings
tests/unit/xgb/test_xgboost.py: 18 warnings
/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.ITEM_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.ITEM: 'item'>, <Tags.ID: 'id'>].
warnings.warn(

tests/unit/datasets/test_ecommerce.py: 3 warnings
tests/unit/datasets/test_entertainment.py: 4 warnings
tests/unit/datasets/test_social.py: 1 warning
tests/unit/datasets/test_synthetic.py: 5 warnings
tests/unit/implicit/test_implicit.py: 1 warning
tests/unit/lightfm/test_lightfm.py: 1 warning
tests/unit/tf/test_core.py: 6 warnings
tests/unit/tf/test_loader.py: 1 warning
tests/unit/tf/blocks/test_cross.py: 5 warnings
tests/unit/tf/blocks/test_dlrm.py: 9 warnings
tests/unit/tf/blocks/test_interactions.py: 2 warnings
tests/unit/tf/blocks/test_mlp.py: 60 warnings
tests/unit/tf/blocks/test_optimizer.py: 30 warnings
tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings
tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings
tests/unit/tf/core/test_aggregation.py: 6 warnings
tests/unit/tf/core/test_base.py: 2 warnings
tests/unit/tf/core/test_combinators.py: 11 warnings
tests/unit/tf/core/test_encoder.py: 7 warnings
tests/unit/tf/core/test_index.py: 3 warnings
tests/unit/tf/core/test_prediction.py: 2 warnings
tests/unit/tf/horovod/test_horovod.py: 1 warning
tests/unit/tf/inputs/test_base.py: 1 warning
tests/unit/tf/inputs/test_continuous.py: 7 warnings
tests/unit/tf/inputs/test_embedding.py: 20 warnings
tests/unit/tf/inputs/test_tabular.py: 18 warnings
tests/unit/tf/models/test_base.py: 28 warnings
tests/unit/tf/models/test_benchmark.py: 2 warnings
tests/unit/tf/models/test_ranking.py: 36 warnings
tests/unit/tf/models/test_retrieval.py: 86 warnings
tests/unit/tf/outputs/test_base.py: 6 warnings
tests/unit/tf/outputs/test_classification.py: 6 warnings
tests/unit/tf/outputs/test_contrastive.py: 19 warnings
tests/unit/tf/outputs/test_regression.py: 2 warnings
tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings
tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings
tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings
tests/unit/tf/transformers/test_block.py: 10 warnings
tests/unit/tf/transforms/test_features.py: 10 warnings
tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings
tests/unit/tf/transforms/test_sequence.py: 15 warnings
tests/unit/tf/utils/test_batch.py: 7 warnings
tests/unit/tf/utils/test_dataset.py: 2 warnings
tests/unit/torch/block/test_base.py: 4 warnings
tests/unit/torch/block/test_mlp.py: 1 warning
tests/unit/torch/features/test_continuous.py: 1 warning
tests/unit/torch/features/test_embedding.py: 4 warnings
tests/unit/torch/features/test_tabular.py: 4 warnings
tests/unit/torch/model/test_head.py: 12 warnings
tests/unit/torch/model/test_model.py: 2 warnings
tests/unit/torch/tabular/test_aggregation.py: 6 warnings
tests/unit/torch/tabular/test_transformations.py: 2 warnings
tests/unit/xgb/test_xgboost.py: 17 warnings
/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.USER_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.USER: 'user'>, <Tags.ID: 'id'>].
warnings.warn(

tests/unit/datasets/test_ecommerce.py: 1 warning
tests/unit/datasets/test_entertainment.py: 1 warning
tests/unit/implicit/test_implicit.py: 1 warning
tests/unit/lightfm/test_lightfm.py: 1 warning
tests/unit/tf/test_loader.py: 1 warning
tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings
tests/unit/tf/blocks/retrieval/test_two_tower.py: 2 warnings
tests/unit/tf/core/test_combinators.py: 11 warnings
tests/unit/tf/core/test_encoder.py: 2 warnings
tests/unit/tf/core/test_prediction.py: 1 warning
tests/unit/tf/horovod/test_horovod.py: 1 warning
tests/unit/tf/inputs/test_continuous.py: 4 warnings
tests/unit/tf/inputs/test_embedding.py: 9 warnings
tests/unit/tf/inputs/test_tabular.py: 8 warnings
tests/unit/tf/models/test_ranking.py: 20 warnings
tests/unit/tf/models/test_retrieval.py: 10 warnings
tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings
tests/unit/tf/prediction_tasks/test_regression.py: 3 warnings
tests/unit/tf/transforms/test_negative_sampling.py: 9 warnings
tests/unit/xgb/test_xgboost.py: 12 warnings
/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.SESSION_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.SESSION: 'session'>, <Tags.ID: 'id'>].
warnings.warn(

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export
tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export
tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export
tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export
tests/unit/tf/inputs/test_embedding.py::test_embedding_features_exporting_and_loading_pretrained_initializer
/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/inputs/embedding.py:970: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack
embeddings_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(embeddings)))

tests/unit/tf/blocks/retrieval/test_two_tower.py: 1 warning
tests/unit/tf/core/test_index.py: 4 warnings
tests/unit/tf/horovod/test_horovod.py: 3 warnings
tests/unit/tf/models/test_retrieval.py: 55 warnings
tests/unit/tf/prediction_tasks/test_next_item.py: 3 warnings
tests/unit/tf/utils/test_batch.py: 2 warnings
/tmp/autograph_generated_filewjmhpvzm.py:8: DeprecationWarning: The 'warn' method is deprecated, use 'warning' instead
ag
.converted_call(ag__.ld(warnings).warn, ("The 'warn' method is deprecated, use 'warning' instead", ag__.ld(DeprecationWarning), 2), None, fscope)

tests/unit/tf/core/test_combinators.py::test_parallel_block_select_by_tags
/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/core/tabular.py:602: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated since Python 3.3, and in 3.10 it will stop working
elif isinstance(self.feature_names, collections.Sequence):

tests/unit/tf/core/test_encoder.py: 1 warning
tests/unit/tf/core/test_index.py: 5 warnings
tests/unit/tf/models/test_retrieval.py: 30 warnings
tests/unit/tf/utils/test_batch.py: 4 warnings
tests/unit/tf/utils/test_dataset.py: 1 warning
/var/jenkins_home/workspace/merlin_models/models/merlin/models/utils/dataset.py:75: DeprecationWarning: unique_rows_by_features is deprecated and will be removed in a future version. Please use unique_by_tag instead.
warnings.warn(

tests/unit/tf/models/test_base.py::test_model_pre_post[True]
tests/unit/tf/models/test_base.py::test_model_pre_post[False]
tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.1]
tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.3]
tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.5]
tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.7]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/util/dispatch.py:1082: UserWarning: tf.keras.backend.random_binomial is deprecated, and will be removed in a future version.Please use tf.keras.backend.random_bernoulli instead.
return dispatch_target(*args, **kwargs)

tests/unit/tf/models/test_base.py::test_freeze_parallel_block[True]
tests/unit/tf/models/test_base.py::test_freeze_sequential_block
tests/unit/tf/models/test_base.py::test_freeze_unfreeze
tests/unit/tf/models/test_base.py::test_unfreeze_all_blocks
/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/gradient_descent.py:108: UserWarning: The lr argument is deprecated, use learning_rate instead.
super(SGD, self).init(name, **kwargs)

tests/unit/tf/models/test_base.py::test_retrieval_model_query
tests/unit/tf/models/test_base.py::test_retrieval_model_query
tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_v2_export_embeddings
tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[True]
tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[False]
tests/unit/tf/transformers/test_block.py::test_retrieval_transformer[True]
/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/utils/tf_utils.py:298: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack
tensor_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(tensor)))

tests/unit/tf/models/test_ranking.py::test_deepfm_model_only_categ_feats[False]
tests/unit/tf/models/test_ranking.py::test_deepfm_model_categ_and_continuous_feats[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/models/test_ranking.py::test_wide_deep_model[False]
tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_categorical_one_hot[False]
tests/unit/tf/models/test_ranking.py::test_wide_deep_model_hashed_cross[False]
tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[True]
tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]
/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/transforms/features.py:569: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag
warnings.warn(

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/autograph/impl/api.py:371: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag
return py_builtins.overload_of(f)(*args)

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_onehot_multihot_feature_interaction[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_feature_interaction_multi_optimizer[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask/GatherV2:0", shape=(None, 48), dtype=float32), dense_shape=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Reshape_3:0", shape=(None,), dtype=int64), values=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Reshape_2:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask/GatherV2:0", shape=(None, 48), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_3:0", shape=(None,), dtype=int64), values=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_2:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/torch/block/test_mlp.py::test_mlp_block
/var/jenkins_home/workspace/merlin_models/models/tests/unit/torch/_conftest.py:151: UserWarning: Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at ../torch/csrc/utils/tensor_new.cpp:201.)
return {key: torch.tensor(value) for key, value in data.items()}

tests/unit/xgb/test_xgboost.py::test_without_dask_client
tests/unit/xgb/test_xgboost.py::TestXGBoost::test_music_regression
tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs0-DaskDeviceQuantileDMatrix]
tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs1-DaskDMatrix]
tests/unit/xgb/test_xgboost.py::TestEvals::test_multiple
tests/unit/xgb/test_xgboost.py::TestEvals::test_default
tests/unit/xgb/test_xgboost.py::TestEvals::test_train_and_valid
tests/unit/xgb/test_xgboost.py::TestEvals::test_invalid_data
/var/jenkins_home/workspace/merlin_models/models/merlin/models/xgb/init.py:344: UserWarning: Ignoring list columns as inputs to XGBoost model: ['item_genres', 'user_genres'].
warnings.warn(f"Ignoring list columns as inputs to XGBoost model: {list_column_names}.")

tests/unit/xgb/test_xgboost.py::TestXGBoost::test_unsupported_objective
/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/tornado/ioloop.py:350: DeprecationWarning: make_current is deprecated; start the event loop first
self.make_current()

tests/unit/xgb/test_xgboost.py: 14 warnings
/usr/local/lib/python3.8/dist-packages/xgboost/dask.py:884: RuntimeWarning: coroutine 'Client._wait_for_workers' was never awaited
client.wait_for_workers(n_workers)
Enable tracemalloc to get traceback where the object was allocated.
See https://docs.pytest.org/en/stable/how-to/capture-warnings.html#resource-warnings for more info.

tests/unit/xgb/test_xgboost.py: 11 warnings
/usr/local/lib/python3.8/dist-packages/cudf/core/dataframe.py:1183: DeprecationWarning: The default dtype for empty Series will be 'object' instead of 'float64' in a future version. Specify a dtype explicitly to silence this warning.
mask = pd.Series(mask)

-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html

---------- coverage: platform linux, python 3.8.10-final-0 -----------
Name Stmts Miss Cover

merlin/datasets/init.py 2 0 100%
merlin/datasets/advertising/init.py 2 0 100%
merlin/datasets/advertising/criteo/init.py 0 0 100%
merlin/datasets/advertising/criteo/dataset.py 79 49 38%
merlin/datasets/advertising/criteo/transformed/init.py 0 0 100%
merlin/datasets/ecommerce/init.py 4 0 100%
merlin/datasets/ecommerce/aliccp/init.py 0 0 100%
merlin/datasets/ecommerce/aliccp/dataset.py 141 87 38%
merlin/datasets/ecommerce/aliccp/raw/init.py 0 0 100%
merlin/datasets/ecommerce/aliccp/transformed/init.py 0 0 100%
merlin/datasets/ecommerce/booking/init.py 0 0 100%
merlin/datasets/ecommerce/booking/dataset.py 127 100 21%
merlin/datasets/ecommerce/booking/transformed/init.py 0 0 100%
merlin/datasets/ecommerce/dressipi/init.py 0 0 100%
merlin/datasets/ecommerce/dressipi/dataset.py 45 37 18%
merlin/datasets/ecommerce/dressipi/preprocessed/init.py 0 0 100%
merlin/datasets/ecommerce/large/init.py 0 0 100%
merlin/datasets/ecommerce/small/init.py 0 0 100%
merlin/datasets/ecommerce/transactions/init.py 0 0 100%
merlin/datasets/entertainment/init.py 2 0 100%
merlin/datasets/entertainment/movielens/1m-raw/init.py 0 0 100%
merlin/datasets/entertainment/movielens/1m-raw/ratings/init.py 0 0 100%
merlin/datasets/entertainment/movielens/1m/init.py 0 0 100%
merlin/datasets/entertainment/movielens/25m/init.py 0 0 100%
merlin/datasets/entertainment/movielens/100k/init.py 0 0 100%
merlin/datasets/entertainment/movielens/init.py 0 0 100%
merlin/datasets/entertainment/movielens/dataset.py 152 122 20%
merlin/datasets/entertainment/music_streaming/init.py 0 0 100%
merlin/datasets/social/init.py 0 0 100%
merlin/datasets/synthetic.py 147 14 90%
merlin/datasets/testing/init.py 0 0 100%
merlin/datasets/testing/sequence_testing/init.py 0 0 100%
merlin/models/init.py 2 0 100%
merlin/models/_version.py 354 205 42%
merlin/models/api.py 14 5 64%
merlin/models/config/init.py 0 0 100%
merlin/models/config/schema.py 62 0 100%
merlin/models/implicit/init.py 27 4 85%
merlin/models/io.py 15 0 100%
merlin/models/lightfm/init.py 23 0 100%
merlin/models/loader/init.py 0 0 100%
merlin/models/loader/backend.py 379 41 89%
merlin/models/loader/dataframe_iter.py 21 17 19%
merlin/models/loader/tf_utils.py 57 27 53%
merlin/models/loader/utils.py 40 15 62%
merlin/models/tf/init.py 70 0 100%
merlin/models/tf/blocks/init.py 0 0 100%
merlin/models/tf/blocks/cross.py 44 0 100%
merlin/models/tf/blocks/dlrm.py 49 2 96%
merlin/models/tf/blocks/experts.py 99 17 83%
merlin/models/tf/blocks/interaction.py 108 40 63%
merlin/models/tf/blocks/mlp.py 117 7 94%
merlin/models/tf/blocks/optimizer.py 173 12 93%
merlin/models/tf/blocks/retrieval/init.py 0 0 100%
merlin/models/tf/blocks/retrieval/base.py 169 62 63%
merlin/models/tf/blocks/retrieval/matrix_factorization.py 35 1 97%
merlin/models/tf/blocks/retrieval/two_tower.py 30 0 100%
merlin/models/tf/blocks/sampling/init.py 0 0 100%
merlin/models/tf/blocks/sampling/base.py 29 2 93%
merlin/models/tf/blocks/sampling/cross_batch.py 46 2 96%
merlin/models/tf/blocks/sampling/in_batch.py 35 0 100%
merlin/models/tf/blocks/sampling/queue.py 115 12 90%
merlin/models/tf/core/init.py 0 0 100%
merlin/models/tf/core/aggregation.py 241 45 81%
merlin/models/tf/core/base.py 244 50 80%
merlin/models/tf/core/combinators.py 426 53 88%
merlin/models/tf/core/encoder.py 175 28 84%
merlin/models/tf/core/index.py 104 16 85%
merlin/models/tf/core/prediction.py 50 1 98%
merlin/models/tf/core/tabular.py 280 29 90%
merlin/models/tf/distributed/init.py 0 0 100%
merlin/models/tf/distributed/backend.py 9 2 78%
merlin/models/tf/inputs/init.py 0 0 100%
merlin/models/tf/inputs/base.py 60 10 83%
merlin/models/tf/inputs/continuous.py 39 3 92%
merlin/models/tf/inputs/embedding.py 458 32 93%
merlin/models/tf/loader.py 268 94 65%
merlin/models/tf/losses/init.py 4 0 100%
merlin/models/tf/losses/base.py 9 0 100%
merlin/models/tf/losses/listwise.py 13 0 100%
merlin/models/tf/losses/pairwise.py 115 1 99%
merlin/models/tf/metrics/init.py 2 0 100%
merlin/models/tf/metrics/evaluation.py 105 48 54%
merlin/models/tf/metrics/topk.py 198 48 76%
merlin/models/tf/models/init.py 0 0 100%
merlin/models/tf/models/base.py 756 101 87%
merlin/models/tf/models/benchmark.py 16 0 100%
merlin/models/tf/models/ranking.py 67 3 96%
merlin/models/tf/models/retrieval.py 78 4 95%
merlin/models/tf/models/utils.py 10 1 90%
merlin/models/tf/outputs/init.py 0 0 100%
merlin/models/tf/outputs/base.py 123 17 86%
merlin/models/tf/outputs/classification.py 91 1 99%
merlin/models/tf/outputs/contrastive.py 147 10 93%
merlin/models/tf/outputs/regression.py 9 0 100%
merlin/models/tf/outputs/sampling/init.py 0 0 100%
merlin/models/tf/outputs/sampling/base.py 78 21 73%
merlin/models/tf/outputs/sampling/in_batch.py 37 1 97%
merlin/models/tf/outputs/sampling/popularity.py 27 1 96%
merlin/models/tf/outputs/topk.py 98 6 94%
merlin/models/tf/prediction_tasks/init.py 0 0 100%
merlin/models/tf/prediction_tasks/base.py 207 37 82%
merlin/models/tf/prediction_tasks/classification.py 68 17 75%
merlin/models/tf/prediction_tasks/multi.py 7 0 100%
merlin/models/tf/prediction_tasks/next_item.py 59 6 90%
merlin/models/tf/prediction_tasks/regression.py 35 2 94%
merlin/models/tf/prediction_tasks/retrieval.py 73 3 96%
merlin/models/tf/transformers/init.py 0 0 100%
merlin/models/tf/transformers/block.py 101 2 98%
merlin/models/tf/transformers/transforms.py 63 0 100%
merlin/models/tf/transforms/init.py 0 0 100%
merlin/models/tf/transforms/bias.py 111 9 92%
merlin/models/tf/transforms/features.py 435 36 92%
merlin/models/tf/transforms/negative_sampling.py 77 3 96%
merlin/models/tf/transforms/noise.py 43 1 98%
merlin/models/tf/transforms/regularization.py 17 1 94%
merlin/models/tf/transforms/sequence.py 282 42 85%
merlin/models/tf/transforms/tensor.py 158 13 92%
merlin/models/tf/typing.py 7 0 100%
merlin/models/tf/utils/init.py 0 0 100%
merlin/models/tf/utils/batch_utils.py 85 4 95%
merlin/models/tf/utils/repr_utils.py 69 4 94%
merlin/models/tf/utils/search_utils.py 34 22 35%
merlin/models/tf/utils/testing_utils.py 206 36 83%
merlin/models/tf/utils/tf_utils.py 209 42 80%
merlin/models/torch/init.py 12 0 100%
merlin/models/torch/block/init.py 0 0 100%
merlin/models/torch/block/base.py 167 32 81%
merlin/models/torch/block/mlp.py 38 5 87%
merlin/models/torch/dataset.py 68 5 93%
merlin/models/torch/features/init.py 0 0 100%
merlin/models/torch/features/base.py 4 0 100%
merlin/models/torch/features/continuous.py 22 0 100%
merlin/models/torch/features/embedding.py 165 12 93%
merlin/models/torch/features/tabular.py 65 8 88%
merlin/models/torch/losses.py 28 28 0%
merlin/models/torch/model/init.py 0 0 100%
merlin/models/torch/model/base.py 286 65 77%
merlin/models/torch/model/prediction_task.py 24 0 100%
merlin/models/torch/tabular/init.py 0 0 100%
merlin/models/torch/tabular/aggregation.py 75 0 100%
merlin/models/torch/tabular/base.py 247 39 84%
merlin/models/torch/tabular/transformations.py 67 3 96%
merlin/models/torch/typing.py 6 0 100%
merlin/models/torch/utils/init.py 0 0 100%
merlin/models/torch/utils/data_utils.py 117 117 0%
merlin/models/torch/utils/examples_utils.py 39 39 0%
merlin/models/torch/utils/torch_utils.py 80 22 72%
merlin/models/utils/init.py 0 0 100%
merlin/models/utils/constants.py 3 0 100%
merlin/models/utils/dataset.py 38 4 89%
merlin/models/utils/dependencies.py 26 19 27%
merlin/models/utils/doc_utils.py 10 0 100%
merlin/models/utils/example_utils.py 31 2 94%
merlin/models/utils/misc_utils.py 118 90 24%
merlin/models/utils/nvt_utils.py 27 24 11%
merlin/models/utils/registry.py 101 29 71%
merlin/models/utils/schema_utils.py 90 19 79%
merlin/models/xgb/init.py 124 4 97%

TOTAL 11575 2352 80%

=========================== short test summary info ============================
SKIPPED [1] tests/unit/datasets/test_advertising.py:20: No data-dir available, pass it through env variable $INPUT_DATA_DIR
SKIPPED [1] tests/unit/datasets/test_ecommerce.py:64: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP
SKIPPED [1] tests/unit/datasets/test_ecommerce.py:80: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP
SKIPPED [1] tests/unit/datasets/test_ecommerce.py:94: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP
SKIPPED [1] tests/unit/datasets/test_ecommerce.py:115: No data-dir available, pass it through env variable $INPUT_DATA_DIR
SKIPPED [3] tests/unit/datasets/test_entertainment.py:44: No data-dir available, pass it through env variable $INPUT_DATA_DIR
SKIPPED [5] ../../../.local/lib/python3.8/site-packages/tensorflow/python/framework/test_util.py:2746: Not a test.
========= 866 passed, 13 skipped, 1438 warnings in 1728.20s (0:28:48) ==========
___________________________________ summary ____________________________________
py38-gpu: commands succeeded
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[merlin_models] $ /bin/bash /tmp/jenkins10302955914395132062.sh

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 > git fetch --tags --force --progress -- https://github.com/NVIDIA-Merlin/models/ +refs/pull/855/*:refs/remotes/origin/pr/855/* # timeout=10
 > git rev-parse 191e3fb8d89c5c31d497296aff3ec8cc2096c821^{commit} # timeout=10
Checking out Revision 191e3fb8d89c5c31d497296aff3ec8cc2096c821 (detached)
 > git config core.sparsecheckout # timeout=10
 > git checkout -f 191e3fb8d89c5c31d497296aff3ec8cc2096c821 # timeout=10
Commit message: "Merge branch 'main' into multi-gpu-data-parallel"
 > git rev-list --no-walk 66fb21cb6821243bc9db6884eb74bc75b981fa54 # timeout=10
[merlin_models] $ /bin/bash /tmp/jenkins13600309656182568956.sh
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Requirement already satisfied: testbook in /usr/local/lib/python3.8/dist-packages (0.4.2)
Requirement already satisfied: nbformat>=5.0.4 in /usr/local/lib/python3.8/dist-packages (from testbook) (5.5.0)
Requirement already satisfied: nbclient>=0.4.0 in /usr/local/lib/python3.8/dist-packages (from testbook) (0.6.8)
Requirement already satisfied: traitlets>=5.2.2 in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (5.4.0)
Requirement already satisfied: nest-asyncio in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (1.5.5)
Requirement already satisfied: jupyter-client>=6.1.5 in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (7.3.5)
Requirement already satisfied: jsonschema>=2.6 in /usr/local/lib/python3.8/dist-packages (from nbformat>=5.0.4->testbook) (4.16.0)
Requirement already satisfied: fastjsonschema in /usr/local/lib/python3.8/dist-packages (from nbformat>=5.0.4->testbook) (2.16.1)
Requirement already satisfied: jupyter_core in /usr/local/lib/python3.8/dist-packages (from nbformat>=5.0.4->testbook) (4.11.1)
Requirement already satisfied: pkgutil-resolve-name>=1.3.10 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (1.3.10)
Requirement already satisfied: importlib-resources>=1.4.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (5.9.0)
Requirement already satisfied: pyrsistent!=0.17.0,!=0.17.1,!=0.17.2,>=0.14.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (0.18.1)
Requirement already satisfied: attrs>=17.4.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (22.1.0)
Requirement already satisfied: entrypoints in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (0.4)
Requirement already satisfied: pyzmq>=23.0 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (24.0.0)
Requirement already satisfied: tornado>=6.2 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (6.2)
Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (2.8.2)
Requirement already satisfied: zipp>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from importlib-resources>=1.4.0->jsonschema>=2.6->nbformat>=5.0.4->testbook) (3.8.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.8.2->jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (1.15.0)
GLOB sdist-make: /var/jenkins_home/workspace/merlin_models/models/setup.py
py38-gpu recreate: /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
py38-gpu installdeps: -rrequirements/dev.txt, tensorflow<2.10
WARNING: Discarding $PYTHONPATH from environment, to override specify PYTHONPATH in 'passenv' in your configuration.
py38-gpu inst: /var/jenkins_home/workspace/merlin_models/models/.tox/.tmp/package/4/merlin-models-0.9.0+58.g191e3fb8.zip
WARNING: Discarding $PYTHONPATH from environment, to override specify PYTHONPATH in 'passenv' in your configuration.
py38-gpu installed: absl-py==1.2.0,aiohttp==3.8.1,aiosignal==1.2.0,alabaster==0.7.12,alembic==1.8.1,anyio==3.6.1,appdirs==1.4.4,argon2-cffi==21.3.0,argon2-cffi-bindings==21.2.0,astroid==2.5.6,asttokens==2.0.8,astunparse==1.6.3,asv==0.5.1,asvdb==0.4.2,async-timeout==4.0.2,attrs==22.1.0,autopage==0.5.1,awscli==1.27.13,Babel==2.10.3,backcall==0.2.0,beautifulsoup4==4.11.1,betterproto==1.2.5,black==20.8b1,bleach==5.0.1,bokeh==3.0.2,boto3==1.24.75,botocore==1.29.13,Brotli==1.0.9,build==0.9.0,cachetools==5.2.0,certifi==2019.11.28,cffi==1.15.1,chardet==3.0.4,charset-normalizer==2.1.1,check-manifest==0.48,clang==5.0,click==8.1.3,cliff==4.1.0,cloudpickle==2.2.0,cmaes==0.9.0,cmake==3.24.1.1,cmd2==2.4.2,colorama==0.4.4,colorlog==6.7.0,contourpy==1.0.5,coverage==6.5.0,cuda-python==11.7.1,cupy-cuda117==10.6.0,cycler==0.11.0,Cython==0.29.32,dask==2022.5.1,dbus-python==1.2.16,debugpy==1.6.3,decorator==5.1.1,defusedxml==0.7.1,dill==0.3.5.1,distlib==0.3.6,distributed==2022.5.1,distro==1.7.0,dm-tree==0.1.6,docker-pycreds==0.4.0,docutils==0.16,emoji==1.7.0,entrypoints==0.4,execnet==1.9.0,executing==1.0.0,faiss==1.7.2,faiss-gpu==1.7.2,fastai==2.7.9,fastapi==0.85.0,fastavro==1.6.1,fastcore==1.5.27,fastdownload==0.0.7,fastjsonschema==2.16.1,fastprogress==1.0.3,fastrlock==0.8,feast==0.19.4,fiddle==0.2.2,filelock==3.8.0,flake8==5.0.4,flatbuffers==1.12,fonttools==4.37.3,frozenlist==1.3.1,fsspec==2022.5.0,gast==0.4.0,gevent==21.12.0,geventhttpclient==2.0.2,gitdb==4.0.9,GitPython==3.1.27,google==3.0.0,google-api-core==2.10.1,google-auth==2.11.1,google-auth-oauthlib==0.4.6,google-pasta==0.2.0,googleapis-common-protos==1.52.0,graphviz==0.20.1,greenlet==1.1.3,grpcio==1.41.0,grpcio-channelz==1.49.0,grpcio-reflection==1.48.1,grpclib==0.4.3,h11==0.13.0,h2==4.1.0,h5py==3.7.0,HeapDict==1.0.1,horovod==0.26.1,hpack==4.0.0,httptools==0.5.0,hugectr2onnx==0.0.0,huggingface-hub==0.9.1,hyperframe==6.0.1,idna==2.8,imagesize==1.4.1,implicit==0.6.1,importlib-metadata==4.12.0,importlib-resources==5.9.0,iniconfig==1.1.1,interrogate==1.5.0,ipykernel==6.15.3,ipython==8.5.0,ipython-genutils==0.2.0,ipywidgets==7.7.0,isort==5.10.1,jedi==0.18.1,Jinja2==3.1.2,jmespath==1.0.1,joblib==1.2.0,json5==0.9.10,jsonschema==4.16.0,jupyter==1.0.0,jupyter-cache==0.4.3,jupyter-console==6.4.4,jupyter-core==4.11.1,jupyter-server==1.18.1,jupyter-server-mathjax==0.2.5,jupyter-sphinx==0.3.2,jupyter_client==7.3.5,jupyterlab==3.4.7,jupyterlab-pygments==0.2.2,jupyterlab-widgets==1.1.0,jupyterlab_server==2.15.1,keras==2.9.0,Keras-Preprocessing==1.1.2,kiwisolver==1.4.4,lazy-object-proxy==1.8.0,libclang==14.0.6,libcst==0.4.7,lightfm==1.16,lightgbm==3.3.2,linkify-it-py==1.0.3,llvmlite==0.39.1,locket==1.0.0,lxml==4.9.1,Mako==1.2.4,Markdown==3.4.1,markdown-it-py==1.1.0,MarkupSafe==2.1.1,matplotlib==3.6.0,matplotlib-inline==0.1.6,mccabe==0.7.0,mdit-py-plugins==0.2.8,merlin-core==0.6.0+1.g5926fcf,merlin-dataloader==0.0.2,merlin-models==0.9.0+58.g191e3fb8,merlin-systems==0.5.0+4.g15074ad,mistune==2.0.4,mmh3==3.0.0,mpi4py==3.1.3,msgpack==1.0.4,multidict==6.0.2,mypy==0.991,mypy-extensions==0.4.3,myst-nb==0.13.2,myst-parser==0.15.2,natsort==8.1.0,nbclassic==0.4.3,nbclient==0.6.8,nbconvert==7.0.0,nbdime==3.1.1,nbformat==5.5.0,nest-asyncio==1.5.5,ninja==1.10.2.3,notebook==6.4.12,notebook-shim==0.1.0,numba==0.56.2,numpy==1.22.4,nvidia-pyindex==1.0.9,nvtabular @ git+https://github.com/NVIDIA-Merlin/NVTabular.git@e5b7351deb9e4885c4038aa0bbc9f146d8477a0e,nvtx==0.2.5,oauthlib==3.2.1,oldest-supported-numpy==2022.8.16,onnx==1.12.0,onnxruntime==1.11.1,opt-einsum==3.3.0,optuna==3.0.3,packaging==21.3,pandas==1.3.5,pandavro==1.5.2,pandocfilters==1.5.0,parso==0.8.3,partd==1.3.0,pathspec==0.10.2,pathtools==0.1.2,pbr==5.11.0,pep517==0.13.0,pexpect==4.8.0,pickleshare==0.7.5,Pillow==9.2.0,pkgutil_resolve_name==1.3.10,platformdirs==2.5.2,plotly==5.11.0,pluggy==1.0.0,prettytable==3.5.0,prometheus-client==0.14.1,promise==2.3,prompt-toolkit==3.0.31,proto-plus==1.19.6,protobuf==3.19.5,psutil==5.9.2,ptyprocess==0.7.0,pure-eval==0.2.2,py==1.11.0,pyarrow==7.0.0,pyasn1==0.4.8,pyasn1-modules==0.2.8,pybind11==2.10.0,pycodestyle==2.9.1,pycparser==2.21,pydantic==1.10.2,pydot==1.4.2,pyflakes==2.5.0,Pygments==2.13.0,PyGObject==3.36.0,pynvml==11.4.1,pyparsing==3.0.9,pyperclip==1.8.2,pyrsistent==0.18.1,pytest==7.1.3,pytest-cov==4.0.0,pytest-xdist==3.0.2,python-apt==2.0.0+ubuntu0.20.4.8,python-dateutil==2.8.2,python-dotenv==0.21.0,python-rapidjson==1.8,pytz==2022.2.1,PyYAML==5.4.1,pyzmq==24.0.0,qtconsole==5.4.0,QtPy==2.3.0,regex==2022.9.13,requests==2.22.0,requests-oauthlib==1.3.1,requests-unixsocket==0.2.0,rsa==4.7.2,s3fs==2022.2.0,s3transfer==0.6.0,sacremoses==0.0.53,scikit-build==0.15.0,scikit-learn==1.1.2,scipy==1.8.1,seedir==0.3.0,Send2Trash==1.8.0,sentry-sdk==1.9.8,setproctitle==1.3.2,setuptools-scm==7.0.5,shortuuid==1.0.9,six==1.15.0,sklearn==0.0,smmap==5.0.0,sniffio==1.3.0,snowballstemmer==2.2.0,sortedcontainers==2.4.0,soupsieve==2.3.2.post1,Sphinx==5.3.0,sphinx-multiversion==0.2.4,sphinx-togglebutton==0.3.1,sphinx_external_toc==0.3.0,sphinxcontrib-applehelp==1.0.2,sphinxcontrib-copydirs @ git+https://github.com/mikemckiernan/sphinxcontrib-copydirs.git@bd8c5d79b3f91cf5f1bb0d6995aeca3fe84b670e,sphinxcontrib-devhelp==1.0.2,sphinxcontrib-htmlhelp==2.0.0,sphinxcontrib-jsmath==1.0.1,sphinxcontrib-qthelp==1.0.3,sphinxcontrib-serializinghtml==1.1.5,SQLAlchemy==1.4.44,stack-data==0.5.0,starlette==0.20.4,stevedore==4.1.1,stringcase==1.2.0,supervisor==4.1.0,tabulate==0.8.10,tblib==1.7.0,tdqm==0.0.1,tenacity==8.0.1,tensorboard==2.9.1,tensorboard-data-server==0.6.1,tensorboard-plugin-wit==1.8.1,tensorflow==2.9.2,tensorflow-estimator==2.9.0,tensorflow-gpu==2.9.2,tensorflow-io-gcs-filesystem==0.27.0,tensorflow-metadata==1.10.0,termcolor==2.0.1,terminado==0.15.0,testbook==0.4.2,threadpoolctl==3.1.0,tinycss2==1.1.1,tokenizers==0.10.3,toml==0.10.2,tomli==2.0.1,toolz==0.12.0,torch==1.12.1+cu113,torchmetrics==0.3.2,tornado==6.2,tox==3.26.0,tqdm==4.64.1,traitlets==5.4.0,transformers==4.12.0,transformers4rec==0.1.12+2.gbcc939255,treelite==2.3.0,treelite-runtime==2.3.0,tritonclient==2.25.0,typed-ast==1.5.4,typing-inspect==0.8.0,typing_extensions==4.3.0,uc-micro-py==1.0.1,urllib3==1.26.12,uvicorn==0.18.3,uvloop==0.17.0,versioneer==0.20,virtualenv==20.16.5,wandb==0.13.3,watchfiles==0.17.0,wcwidth==0.2.5,webencodings==0.5.1,websocket-client==1.4.1,websockets==10.3,Werkzeug==2.2.2,widgetsnbextension==3.6.0,wrapt==1.12.1,xgboost==1.6.2,xyzservices==2022.9.0,yarl==1.8.1,zict==2.2.0,zipp==3.8.1,zope.event==4.5.0,zope.interface==5.4.0
py38-gpu run-test-pre: PYTHONHASHSEED='16364101'
py38-gpu run-test: commands[0] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/core.git
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Collecting git+https://github.com/NVIDIA-Merlin/core.git
  Cloning https://github.com/NVIDIA-Merlin/core.git to /tmp/pip-req-build-ick4jniz
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/core.git /tmp/pip-req-build-ick4jniz
  Resolved https://github.com/NVIDIA-Merlin/core.git to commit 04ff5225cee6af90b6b08070493677ac53b96836
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: protobuf>=3.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+16.g04ff522) (3.19.5)
Requirement already satisfied: distributed>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+16.g04ff522) (2022.3.0)
Requirement already satisfied: packaging in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+16.g04ff522) (21.3)
Requirement already satisfied: pandas<1.4.0dev0,>=1.2.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+16.g04ff522) (1.3.5)
Requirement already satisfied: tensorflow-metadata>=1.2.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+16.g04ff522) (1.10.0)
Requirement already satisfied: pyarrow>=5.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+16.g04ff522) (7.0.0)
Requirement already satisfied: betterproto<2.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+16.g04ff522) (1.2.5)
Requirement already satisfied: dask>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+16.g04ff522) (2022.3.0)
Requirement already satisfied: fsspec==2022.5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+16.g04ff522) (2022.5.0)
Requirement already satisfied: numba>=0.54 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+16.g04ff522) (0.55.1)
Requirement already satisfied: tqdm>=4.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+16.g04ff522) (4.64.1)
Requirement already satisfied: grpclib in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core==0.8.0+16.g04ff522) (0.4.3)
Requirement already satisfied: stringcase in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core==0.8.0+16.g04ff522) (1.2.0)
Requirement already satisfied: cloudpickle>=1.1.1 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (2.2.0)
Requirement already satisfied: toolz>=0.8.2 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (0.12.0)
Requirement already satisfied: partd>=0.3.10 in /var/jenkins_home/.local/lib/python3.8/site-packages/partd-1.2.0-py3.8.egg (from dask>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (1.2.0)
Requirement already satisfied: pyyaml>=5.3.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/PyYAML-5.4.1-py3.8-linux-x86_64.egg (from dask>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (5.4.1)
Requirement already satisfied: sortedcontainers!=2.0.0,!=2.0.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/sortedcontainers-2.4.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (2.4.0)
Requirement already satisfied: zict>=0.1.3 in /var/jenkins_home/.local/lib/python3.8/site-packages/zict-2.0.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (2.0.0)
Requirement already satisfied: psutil>=5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/psutil-5.8.0-py3.8-linux-x86_64.egg (from distributed>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (5.8.0)
Requirement already satisfied: msgpack>=0.6.0 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (1.0.4)
Requirement already satisfied: tblib>=1.6.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/tblib-1.7.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (1.7.0)
Requirement already satisfied: click>=6.6 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (8.1.3)
Requirement already satisfied: tornado>=6.0.3 in ./.tox/py38-gpu/lib/python3.8/site-packages (from distributed>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (6.2)
Requirement already satisfied: jinja2 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (3.1.2)
Requirement already satisfied: setuptools in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+16.g04ff522) (65.5.1)
Requirement already satisfied: numpy<1.22,>=1.18 in /var/jenkins_home/.local/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+16.g04ff522) (1.20.3)
Requirement already satisfied: llvmlite<0.39,>=0.38.0rc1 in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+16.g04ff522) (0.38.1)
Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in /usr/local/lib/python3.8/dist-packages (from packaging->merlin-core==0.8.0+16.g04ff522) (3.0.9)
Requirement already satisfied: pytz>=2017.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+16.g04ff522) (2022.2.1)
Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+16.g04ff522) (2.8.2)
Requirement already satisfied: absl-py<2.0.0,>=0.9 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core==0.8.0+16.g04ff522) (1.2.0)
Requirement already satisfied: googleapis-common-protos<2,>=1.52.0 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core==0.8.0+16.g04ff522) (1.52.0)
Requirement already satisfied: locket in /var/jenkins_home/.local/lib/python3.8/site-packages/locket-0.2.1-py3.8.egg (from partd>=0.3.10->dask>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (0.2.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.7.3->pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+16.g04ff522) (1.15.0)
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Requirement already satisfied: hpack<5,>=4.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core==0.8.0+16.g04ff522) (4.0.0)
Requirement already satisfied: hyperframe<7,>=6.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core==0.8.0+16.g04ff522) (6.0.1)
Building wheels for collected packages: merlin-core
  Building wheel for merlin-core (pyproject.toml): started
  Building wheel for merlin-core (pyproject.toml): finished with status 'done'
  Created wheel for merlin-core: filename=merlin_core-0.8.0+16.g04ff522-py3-none-any.whl size=118833 sha256=412eaf2a89ffb36b37c6efce22218e0379a6998651dde7ee99770789a2210407
  Stored in directory: /tmp/pip-ephem-wheel-cache-1g3qb7lc/wheels/c8/38/16/a6968787eafcec5fa772148af8408b089562f71af0752e8e84
Successfully built merlin-core
Installing collected packages: merlin-core
  Attempting uninstall: merlin-core
    Found existing installation: merlin-core 0.3.0+12.g78ecddd
    Not uninstalling merlin-core at /var/jenkins_home/.local/lib/python3.8/site-packages, outside environment /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
    Can't uninstall 'merlin-core'. No files were found to uninstall.
Successfully installed merlin-core-0.8.0+16.g04ff522
py38-gpu run-test: commands[1] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/nvtabular.git
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Collecting git+https://github.com/NVIDIA-Merlin/nvtabular.git
  Cloning https://github.com/NVIDIA-Merlin/nvtabular.git to /tmp/pip-req-build-07pz75af
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/nvtabular.git /tmp/pip-req-build-07pz75af
  Resolved https://github.com/NVIDIA-Merlin/nvtabular.git to commit e5b7351deb9e4885c4038aa0bbc9f146d8477a0e
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: merlin-core>=0.2.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from nvtabular==1.6.0+6.ge5b7351d) (0.8.0+16.g04ff522)
Requirement already satisfied: merlin-dataloader>=0.0.2 in /usr/local/lib/python3.8/dist-packages (from nvtabular==1.6.0+6.ge5b7351d) (0.0.2)
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Requirement already satisfied: distributed>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+6.ge5b7351d) (2022.3.0)
Requirement already satisfied: packaging in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+6.ge5b7351d) (21.3)
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Requirement already satisfied: numpy<1.25.0,>=1.17.3 in /var/jenkins_home/.local/lib/python3.8/site-packages (from scipy->nvtabular==1.6.0+6.ge5b7351d) (1.20.3)
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Requirement already satisfied: sortedcontainers!=2.0.0,!=2.0.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/sortedcontainers-2.4.0-py3.8.egg (from distributed>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+6.ge5b7351d) (2.4.0)
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Requirement already satisfied: tblib>=1.6.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/tblib-1.7.0-py3.8.egg (from distributed>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+6.ge5b7351d) (1.7.0)
Requirement already satisfied: click>=6.6 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+6.ge5b7351d) (8.1.3)
Requirement already satisfied: tornado>=6.0.3 in ./.tox/py38-gpu/lib/python3.8/site-packages (from distributed>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+6.ge5b7351d) (6.2)
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Requirement already satisfied: setuptools in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core>=0.2.0->nvtabular==1.6.0+6.ge5b7351d) (65.5.1)
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Requirement already satisfied: pytz>=2017.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core>=0.2.0->nvtabular==1.6.0+6.ge5b7351d) (2022.2.1)
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Requirement already satisfied: googleapis-common-protos<2,>=1.52.0 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core>=0.2.0->nvtabular==1.6.0+6.ge5b7351d) (1.52.0)
Requirement already satisfied: locket in /var/jenkins_home/.local/lib/python3.8/site-packages/locket-0.2.1-py3.8.egg (from partd>=0.3.10->dask>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+6.ge5b7351d) (0.2.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.7.3->pandas<1.4.0dev0,>=1.2.0->merlin-core>=0.2.0->nvtabular==1.6.0+6.ge5b7351d) (1.15.0)
Requirement already satisfied: heapdict in /var/jenkins_home/.local/lib/python3.8/site-packages/HeapDict-1.0.1-py3.8.egg (from zict>=0.1.3->distributed>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+6.ge5b7351d) (1.0.1)
Requirement already satisfied: multidict in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core>=0.2.0->nvtabular==1.6.0+6.ge5b7351d) (6.0.2)
Requirement already satisfied: h2<5,>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core>=0.2.0->nvtabular==1.6.0+6.ge5b7351d) (4.1.0)
Requirement already satisfied: MarkupSafe>=2.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from jinja2->distributed>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+6.ge5b7351d) (2.0.1)
Requirement already satisfied: hpack<5,>=4.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core>=0.2.0->nvtabular==1.6.0+6.ge5b7351d) (4.0.0)
Requirement already satisfied: hyperframe<7,>=6.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core>=0.2.0->nvtabular==1.6.0+6.ge5b7351d) (6.0.1)
Building wheels for collected packages: nvtabular
  Building wheel for nvtabular (pyproject.toml): started
  Building wheel for nvtabular (pyproject.toml): finished with status 'done'
  Created wheel for nvtabular: filename=nvtabular-1.6.0+6.ge5b7351d-cp38-cp38-linux_x86_64.whl size=257597 sha256=64f64c9f37c41c743c63a0d77ac76e7757c86eaf9ab754de5129a6dca9a499c4
  Stored in directory: /tmp/pip-ephem-wheel-cache-lpi3k35_/wheels/8f/d9/f9/30f2cdc5bf8787fae6fdfe55afd6e1b493e619ec32c32ec40b
Successfully built nvtabular
Installing collected packages: nvtabular
  Attempting uninstall: nvtabular
    Found existing installation: nvtabular 1.1.1
    Not uninstalling nvtabular at /var/jenkins_home/.local/lib/python3.8/site-packages, outside environment /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
    Can't uninstall 'nvtabular'. No files were found to uninstall.
Successfully installed nvtabular-1.6.0+6.ge5b7351d
py38-gpu run-test: commands[2] | python -m pytest --cov-report term --cov merlin -rxs tests/unit
============================= test session starts ==============================
platform linux -- Python 3.8.10, pytest-7.1.3, pluggy-1.0.0
cachedir: .tox/py38-gpu/.pytest_cache
rootdir: /var/jenkins_home/workspace/merlin_models/models, configfile: pyproject.toml
plugins: anyio-3.5.0, xdist-3.0.2, cov-4.0.0
collected 884 items

tests/unit/config/test_schema.py .... [ 0%]
tests/unit/datasets/test_advertising.py .s [ 0%]
tests/unit/datasets/test_ecommerce.py ..sss.s [ 1%]
tests/unit/datasets/test_entertainment.py ....sss. [ 2%]
tests/unit/datasets/test_social.py . [ 2%]
tests/unit/datasets/test_synthetic.py .......... [ 3%]
tests/unit/implicit/test_implicit.py . [ 3%]
tests/unit/lightfm/test_lightfm.py . [ 3%]
tests/unit/tf/test_core.py ...... [ 4%]
tests/unit/tf/test_loader.py ................ [ 6%]
tests/unit/tf/test_public_api.py . [ 6%]
tests/unit/tf/blocks/test_cross.py ........... [ 7%]
tests/unit/tf/blocks/test_dlrm.py .......... [ 8%]
tests/unit/tf/blocks/test_interactions.py ... [ 9%]
tests/unit/tf/blocks/test_mlp.py ....................................... [ 13%]
............................ [ 16%]
tests/unit/tf/blocks/test_optimizer.py s................................ [ 20%]
..................... [ 22%]
tests/unit/tf/blocks/retrieval/test_base.py . [ 22%]
tests/unit/tf/blocks/retrieval/test_matrix_factorization.py .. [ 23%]
tests/unit/tf/blocks/retrieval/test_two_tower.py ............ [ 24%]
tests/unit/tf/blocks/sampling/test_cross_batch.py . [ 24%]
tests/unit/tf/blocks/sampling/test_in_batch.py . [ 24%]
tests/unit/tf/core/test_aggregation.py ......... [ 25%]
tests/unit/tf/core/test_base.py .. [ 26%]
tests/unit/tf/core/test_combinators.py s..................... [ 28%]
tests/unit/tf/core/test_encoder.py .. [ 28%]
tests/unit/tf/core/test_index.py ... [ 29%]
tests/unit/tf/core/test_prediction.py .. [ 29%]
tests/unit/tf/core/test_tabular.py ...... [ 29%]
tests/unit/tf/examples/test_01_getting_started.py . [ 30%]
tests/unit/tf/examples/test_02_dataschema.py . [ 30%]
tests/unit/tf/examples/test_03_exploring_different_models.py . [ 30%]
tests/unit/tf/examples/test_04_export_ranking_models.py . [ 30%]
tests/unit/tf/examples/test_05_export_retrieval_model.py . [ 30%]
tests/unit/tf/examples/test_06_advanced_own_architecture.py . [ 30%]
tests/unit/tf/examples/test_07_train_traditional_models.py . [ 30%]
tests/unit/tf/examples/test_usecase_accelerate_training_by_lazyadam.py . [ 30%]
[ 30%]
tests/unit/tf/examples/test_usecase_data_parallel.py . [ 30%]
tests/unit/tf/examples/test_usecase_ecommerce_session_based.py . [ 31%]
tests/unit/tf/examples/test_usecase_incremental_training_layer_freezing.py . [ 31%]
[ 31%]
tests/unit/tf/examples/test_usecase_pretrained_embeddings.py . [ 31%]
tests/unit/tf/examples/test_usecase_retrieval_with_hpo.py . [ 31%]
tests/unit/tf/examples/test_usecase_transformers_next_item_prediction.py . [ 31%]
[ 31%]
tests/unit/tf/horovod/test_horovod.py ... [ 31%]
tests/unit/tf/inputs/test_base.py . [ 32%]
tests/unit/tf/inputs/test_continuous.py ........ [ 32%]
tests/unit/tf/inputs/test_embedding.py ................................. [ 36%]
........ [ 37%]
tests/unit/tf/inputs/test_tabular.py .................. [ 39%]
tests/unit/tf/layers/test_queue.py .............. [ 41%]
tests/unit/tf/losses/test_losses.py ....................... [ 43%]
tests/unit/tf/metrics/test_metrics_popularity.py ..... [ 44%]
tests/unit/tf/metrics/test_metrics_topk.py ......................... [ 47%]
tests/unit/tf/models/test_base.py s......................... [ 50%]
tests/unit/tf/models/test_benchmark.py .. [ 50%]
tests/unit/tf/models/test_ranking.py .................................. [ 54%]
tests/unit/tf/models/test_retrieval.py ................................. [ 57%]
........................................... [ 62%]
tests/unit/tf/outputs/test_base.py ...... [ 63%]
tests/unit/tf/outputs/test_classification.py ...... [ 64%]
tests/unit/tf/outputs/test_contrastive.py .............. [ 65%]
tests/unit/tf/outputs/test_regression.py .. [ 65%]
tests/unit/tf/outputs/test_sampling.py .... [ 66%]
tests/unit/tf/outputs/test_topk.py . [ 66%]
tests/unit/tf/prediction_tasks/test_classification.py .. [ 66%]
tests/unit/tf/prediction_tasks/test_multi_task.py ................ [ 68%]
tests/unit/tf/prediction_tasks/test_next_item.py ..... [ 69%]
tests/unit/tf/prediction_tasks/test_regression.py ..... [ 69%]
tests/unit/tf/prediction_tasks/test_retrieval.py . [ 69%]
tests/unit/tf/prediction_tasks/test_sampling.py ...... [ 70%]
tests/unit/tf/transformers/test_block.py ...................... [ 72%]
tests/unit/tf/transformers/test_transforms.py .......... [ 74%]
tests/unit/tf/transforms/test_bias.py .. [ 74%]
tests/unit/tf/transforms/test_features.py s............................. [ 77%]
.......................s...... [ 81%]
tests/unit/tf/transforms/test_negative_sampling.py ......... [ 82%]
tests/unit/tf/transforms/test_noise.py ..... [ 82%]
tests/unit/tf/transforms/test_sequence.py .................... [ 84%]
tests/unit/tf/transforms/test_tensor.py ... [ 85%]
tests/unit/tf/utils/test_batch.py .... [ 85%]
tests/unit/tf/utils/test_dataset.py .. [ 85%]
tests/unit/tf/utils/test_tf_utils.py ..... [ 86%]
tests/unit/torch/test_dataset.py ......... [ 87%]
tests/unit/torch/test_public_api.py . [ 87%]
tests/unit/torch/block/test_base.py .... [ 88%]
tests/unit/torch/block/test_mlp.py . [ 88%]
tests/unit/torch/features/test_continuous.py .. [ 88%]
tests/unit/torch/features/test_embedding.py .............. [ 90%]
tests/unit/torch/features/test_tabular.py .... [ 90%]
tests/unit/torch/model/test_head.py ............ [ 91%]
tests/unit/torch/model/test_model.py .. [ 92%]
tests/unit/torch/tabular/test_aggregation.py ........ [ 92%]
tests/unit/torch/tabular/test_tabular.py ... [ 93%]
tests/unit/torch/tabular/test_transformations.py ....... [ 94%]
tests/unit/utils/test_schema_utils.py ................................ [ 97%]
tests/unit/xgb/test_xgboost.py .................... [100%]

=============================== warnings summary ===============================
../../../../../usr/lib/python3/dist-packages/requests/init.py:89
/usr/lib/python3/dist-packages/requests/init.py:89: RequestsDependencyWarning: urllib3 (1.26.12) or chardet (3.0.4) doesn't match a supported version!
warnings.warn("urllib3 ({}) or chardet ({}) doesn't match a supported "

../../../.local/lib/python3.8/site-packages/flatbuffers/compat.py:19
/var/jenkins_home/.local/lib/python3.8/site-packages/flatbuffers/compat.py:19: DeprecationWarning: the imp module is deprecated in favour of importlib; see the module's documentation for alternative uses
import imp

../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36
/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36: DeprecationWarning: NEAREST is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.NEAREST or Dither.NONE instead.
'nearest': pil_image.NEAREST,

../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37
/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37: DeprecationWarning: BILINEAR is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BILINEAR instead.
'bilinear': pil_image.BILINEAR,

../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38
/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38: DeprecationWarning: BICUBIC is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BICUBIC instead.
'bicubic': pil_image.BICUBIC,

../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39
/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39: DeprecationWarning: HAMMING is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.HAMMING instead.
'hamming': pil_image.HAMMING,

../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40
/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40: DeprecationWarning: BOX is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BOX instead.
'box': pil_image.BOX,

../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41
/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41: DeprecationWarning: LANCZOS is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.LANCZOS instead.
'lanczos': pil_image.LANCZOS,

tests/unit/datasets/test_advertising.py: 1 warning
tests/unit/datasets/test_ecommerce.py: 3 warnings
tests/unit/datasets/test_entertainment.py: 4 warnings
tests/unit/datasets/test_social.py: 1 warning
tests/unit/datasets/test_synthetic.py: 10 warnings
tests/unit/implicit/test_implicit.py: 1 warning
tests/unit/lightfm/test_lightfm.py: 1 warning
tests/unit/tf/test_core.py: 6 warnings
tests/unit/tf/test_loader.py: 1 warning
tests/unit/tf/blocks/test_cross.py: 5 warnings
tests/unit/tf/blocks/test_dlrm.py: 9 warnings
tests/unit/tf/blocks/test_interactions.py: 2 warnings
tests/unit/tf/blocks/test_mlp.py: 60 warnings
tests/unit/tf/blocks/test_optimizer.py: 30 warnings
tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings
tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings
tests/unit/tf/core/test_aggregation.py: 6 warnings
tests/unit/tf/core/test_base.py: 2 warnings
tests/unit/tf/core/test_combinators.py: 11 warnings
tests/unit/tf/core/test_encoder.py: 6 warnings
tests/unit/tf/core/test_index.py: 8 warnings
tests/unit/tf/core/test_prediction.py: 2 warnings
tests/unit/tf/horovod/test_horovod.py: 3 warnings
tests/unit/tf/inputs/test_base.py: 1 warning
tests/unit/tf/inputs/test_continuous.py: 7 warnings
tests/unit/tf/inputs/test_embedding.py: 20 warnings
tests/unit/tf/inputs/test_tabular.py: 18 warnings
tests/unit/tf/models/test_base.py: 28 warnings
tests/unit/tf/models/test_benchmark.py: 2 warnings
tests/unit/tf/models/test_ranking.py: 38 warnings
tests/unit/tf/models/test_retrieval.py: 120 warnings
tests/unit/tf/outputs/test_base.py: 6 warnings
tests/unit/tf/outputs/test_classification.py: 6 warnings
tests/unit/tf/outputs/test_contrastive.py: 19 warnings
tests/unit/tf/outputs/test_regression.py: 2 warnings
tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings
tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings
tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings
tests/unit/tf/prediction_tasks/test_retrieval.py: 1 warning
tests/unit/tf/transformers/test_block.py: 16 warnings
tests/unit/tf/transforms/test_bias.py: 2 warnings
tests/unit/tf/transforms/test_features.py: 10 warnings
tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings
tests/unit/tf/transforms/test_noise.py: 1 warning
tests/unit/tf/transforms/test_sequence.py: 15 warnings
tests/unit/tf/utils/test_batch.py: 9 warnings
tests/unit/tf/utils/test_dataset.py: 2 warnings
tests/unit/torch/block/test_base.py: 4 warnings
tests/unit/torch/block/test_mlp.py: 1 warning
tests/unit/torch/features/test_continuous.py: 1 warning
tests/unit/torch/features/test_embedding.py: 4 warnings
tests/unit/torch/features/test_tabular.py: 4 warnings
tests/unit/torch/model/test_head.py: 12 warnings
tests/unit/torch/model/test_model.py: 2 warnings
tests/unit/torch/tabular/test_aggregation.py: 6 warnings
tests/unit/torch/tabular/test_transformations.py: 3 warnings
tests/unit/xgb/test_xgboost.py: 18 warnings
/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.ITEM_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.ITEM: 'item'>, <Tags.ID: 'id'>].
warnings.warn(

tests/unit/datasets/test_ecommerce.py: 3 warnings
tests/unit/datasets/test_entertainment.py: 4 warnings
tests/unit/datasets/test_social.py: 1 warning
tests/unit/datasets/test_synthetic.py: 9 warnings
tests/unit/implicit/test_implicit.py: 1 warning
tests/unit/lightfm/test_lightfm.py: 1 warning
tests/unit/tf/test_core.py: 6 warnings
tests/unit/tf/test_loader.py: 1 warning
tests/unit/tf/blocks/test_cross.py: 5 warnings
tests/unit/tf/blocks/test_dlrm.py: 9 warnings
tests/unit/tf/blocks/test_interactions.py: 2 warnings
tests/unit/tf/blocks/test_mlp.py: 60 warnings
tests/unit/tf/blocks/test_optimizer.py: 30 warnings
tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings
tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings
tests/unit/tf/core/test_aggregation.py: 6 warnings
tests/unit/tf/core/test_base.py: 2 warnings
tests/unit/tf/core/test_combinators.py: 11 warnings
tests/unit/tf/core/test_encoder.py: 7 warnings
tests/unit/tf/core/test_index.py: 3 warnings
tests/unit/tf/core/test_prediction.py: 2 warnings
tests/unit/tf/horovod/test_horovod.py: 1 warning
tests/unit/tf/inputs/test_base.py: 1 warning
tests/unit/tf/inputs/test_continuous.py: 7 warnings
tests/unit/tf/inputs/test_embedding.py: 20 warnings
tests/unit/tf/inputs/test_tabular.py: 18 warnings
tests/unit/tf/models/test_base.py: 28 warnings
tests/unit/tf/models/test_benchmark.py: 2 warnings
tests/unit/tf/models/test_ranking.py: 36 warnings
tests/unit/tf/models/test_retrieval.py: 86 warnings
tests/unit/tf/outputs/test_base.py: 6 warnings
tests/unit/tf/outputs/test_classification.py: 6 warnings
tests/unit/tf/outputs/test_contrastive.py: 19 warnings
tests/unit/tf/outputs/test_regression.py: 2 warnings
tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings
tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings
tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings
tests/unit/tf/transformers/test_block.py: 10 warnings
tests/unit/tf/transforms/test_features.py: 10 warnings
tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings
tests/unit/tf/transforms/test_sequence.py: 15 warnings
tests/unit/tf/utils/test_batch.py: 7 warnings
tests/unit/tf/utils/test_dataset.py: 2 warnings
tests/unit/torch/block/test_base.py: 4 warnings
tests/unit/torch/block/test_mlp.py: 1 warning
tests/unit/torch/features/test_continuous.py: 1 warning
tests/unit/torch/features/test_embedding.py: 4 warnings
tests/unit/torch/features/test_tabular.py: 4 warnings
tests/unit/torch/model/test_head.py: 12 warnings
tests/unit/torch/model/test_model.py: 2 warnings
tests/unit/torch/tabular/test_aggregation.py: 6 warnings
tests/unit/torch/tabular/test_transformations.py: 2 warnings
tests/unit/xgb/test_xgboost.py: 17 warnings
/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.USER_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.USER: 'user'>, <Tags.ID: 'id'>].
warnings.warn(

tests/unit/datasets/test_ecommerce.py: 1 warning
tests/unit/datasets/test_entertainment.py: 1 warning
tests/unit/implicit/test_implicit.py: 1 warning
tests/unit/lightfm/test_lightfm.py: 1 warning
tests/unit/tf/test_loader.py: 1 warning
tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings
tests/unit/tf/blocks/retrieval/test_two_tower.py: 2 warnings
tests/unit/tf/core/test_combinators.py: 11 warnings
tests/unit/tf/core/test_encoder.py: 2 warnings
tests/unit/tf/core/test_prediction.py: 1 warning
tests/unit/tf/horovod/test_horovod.py: 1 warning
tests/unit/tf/inputs/test_continuous.py: 4 warnings
tests/unit/tf/inputs/test_embedding.py: 9 warnings
tests/unit/tf/inputs/test_tabular.py: 8 warnings
tests/unit/tf/models/test_ranking.py: 20 warnings
tests/unit/tf/models/test_retrieval.py: 10 warnings
tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings
tests/unit/tf/prediction_tasks/test_regression.py: 3 warnings
tests/unit/tf/transforms/test_negative_sampling.py: 9 warnings
tests/unit/xgb/test_xgboost.py: 12 warnings
/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.SESSION_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.SESSION: 'session'>, <Tags.ID: 'id'>].
warnings.warn(

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export
tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export
tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export
tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export
tests/unit/tf/inputs/test_embedding.py::test_embedding_features_exporting_and_loading_pretrained_initializer
/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/inputs/embedding.py:970: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack
embeddings_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(embeddings)))

tests/unit/tf/blocks/retrieval/test_two_tower.py: 1 warning
tests/unit/tf/core/test_index.py: 4 warnings
tests/unit/tf/horovod/test_horovod.py: 3 warnings
tests/unit/tf/models/test_retrieval.py: 55 warnings
tests/unit/tf/prediction_tasks/test_next_item.py: 3 warnings
tests/unit/tf/utils/test_batch.py: 2 warnings
/tmp/autograph_generated_fileh40qw9q1.py:8: DeprecationWarning: The 'warn' method is deprecated, use 'warning' instead
ag
.converted_call(ag__.ld(warnings).warn, ("The 'warn' method is deprecated, use 'warning' instead", ag__.ld(DeprecationWarning), 2), None, fscope)

tests/unit/tf/core/test_combinators.py::test_parallel_block_select_by_tags
/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/core/tabular.py:602: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated since Python 3.3, and in 3.10 it will stop working
elif isinstance(self.feature_names, collections.Sequence):

tests/unit/tf/core/test_encoder.py: 1 warning
tests/unit/tf/core/test_index.py: 5 warnings
tests/unit/tf/models/test_retrieval.py: 30 warnings
tests/unit/tf/utils/test_batch.py: 4 warnings
tests/unit/tf/utils/test_dataset.py: 1 warning
/var/jenkins_home/workspace/merlin_models/models/merlin/models/utils/dataset.py:75: DeprecationWarning: unique_rows_by_features is deprecated and will be removed in a future version. Please use unique_by_tag instead.
warnings.warn(

tests/unit/tf/models/test_base.py::test_model_pre_post[True]
tests/unit/tf/models/test_base.py::test_model_pre_post[False]
tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.1]
tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.3]
tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.5]
tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.7]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/util/dispatch.py:1082: UserWarning: tf.keras.backend.random_binomial is deprecated, and will be removed in a future version.Please use tf.keras.backend.random_bernoulli instead.
return dispatch_target(*args, **kwargs)

tests/unit/tf/models/test_base.py::test_freeze_parallel_block[True]
tests/unit/tf/models/test_base.py::test_freeze_sequential_block
tests/unit/tf/models/test_base.py::test_freeze_unfreeze
tests/unit/tf/models/test_base.py::test_unfreeze_all_blocks
/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/gradient_descent.py:108: UserWarning: The lr argument is deprecated, use learning_rate instead.
super(SGD, self).init(name, **kwargs)

tests/unit/tf/models/test_base.py::test_retrieval_model_query
tests/unit/tf/models/test_base.py::test_retrieval_model_query
tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_v2_export_embeddings
tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[True]
tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[False]
tests/unit/tf/transformers/test_block.py::test_retrieval_transformer[True]
/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/utils/tf_utils.py:298: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack
tensor_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(tensor)))

tests/unit/tf/models/test_ranking.py::test_deepfm_model_only_categ_feats[False]
tests/unit/tf/models/test_ranking.py::test_deepfm_model_categ_and_continuous_feats[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/models/test_ranking.py::test_wide_deep_model[False]
tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_categorical_one_hot[False]
tests/unit/tf/models/test_ranking.py::test_wide_deep_model_hashed_cross[False]
tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[True]
tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]
/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/transforms/features.py:569: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag
warnings.warn(

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/autograph/impl/api.py:371: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag
return py_builtins.overload_of(f)(*args)

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_onehot_multihot_feature_interaction[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_feature_interaction_multi_optimizer[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask/GatherV2:0", shape=(None, 48), dtype=float32), dense_shape=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Reshape_3:0", shape=(None,), dtype=int64), values=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Reshape_2:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask/GatherV2:0", shape=(None, 48), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_3:0", shape=(None,), dtype=int64), values=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_2:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/torch/block/test_mlp.py::test_mlp_block
/var/jenkins_home/workspace/merlin_models/models/tests/unit/torch/_conftest.py:151: UserWarning: Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at ../torch/csrc/utils/tensor_new.cpp:201.)
return {key: torch.tensor(value) for key, value in data.items()}

tests/unit/xgb/test_xgboost.py::test_without_dask_client
tests/unit/xgb/test_xgboost.py::TestXGBoost::test_music_regression
tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs0-DaskDeviceQuantileDMatrix]
tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs1-DaskDMatrix]
tests/unit/xgb/test_xgboost.py::TestEvals::test_multiple
tests/unit/xgb/test_xgboost.py::TestEvals::test_default
tests/unit/xgb/test_xgboost.py::TestEvals::test_train_and_valid
tests/unit/xgb/test_xgboost.py::TestEvals::test_invalid_data
/var/jenkins_home/workspace/merlin_models/models/merlin/models/xgb/init.py:344: UserWarning: Ignoring list columns as inputs to XGBoost model: ['item_genres', 'user_genres'].
warnings.warn(f"Ignoring list columns as inputs to XGBoost model: {list_column_names}.")

tests/unit/xgb/test_xgboost.py::TestXGBoost::test_unsupported_objective
/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/tornado/ioloop.py:350: DeprecationWarning: make_current is deprecated; start the event loop first
self.make_current()

tests/unit/xgb/test_xgboost.py: 14 warnings
/usr/local/lib/python3.8/dist-packages/xgboost/dask.py:884: RuntimeWarning: coroutine 'Client._wait_for_workers' was never awaited
client.wait_for_workers(n_workers)
Enable tracemalloc to get traceback where the object was allocated.
See https://docs.pytest.org/en/stable/how-to/capture-warnings.html#resource-warnings for more info.

tests/unit/xgb/test_xgboost.py: 11 warnings
/usr/local/lib/python3.8/dist-packages/cudf/core/dataframe.py:1183: DeprecationWarning: The default dtype for empty Series will be 'object' instead of 'float64' in a future version. Specify a dtype explicitly to silence this warning.
mask = pd.Series(mask)

-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html

---------- coverage: platform linux, python 3.8.10-final-0 -----------
Name Stmts Miss Cover

merlin/datasets/init.py 2 0 100%
merlin/datasets/advertising/init.py 2 0 100%
merlin/datasets/advertising/criteo/init.py 0 0 100%
merlin/datasets/advertising/criteo/dataset.py 79 49 38%
merlin/datasets/advertising/criteo/transformed/init.py 0 0 100%
merlin/datasets/ecommerce/init.py 4 0 100%
merlin/datasets/ecommerce/aliccp/init.py 0 0 100%
merlin/datasets/ecommerce/aliccp/dataset.py 141 87 38%
merlin/datasets/ecommerce/aliccp/raw/init.py 0 0 100%
merlin/datasets/ecommerce/aliccp/transformed/init.py 0 0 100%
merlin/datasets/ecommerce/booking/init.py 0 0 100%
merlin/datasets/ecommerce/booking/dataset.py 127 100 21%
merlin/datasets/ecommerce/booking/raw/init.py 0 0 100%
merlin/datasets/ecommerce/booking/transformed/init.py 0 0 100%
merlin/datasets/ecommerce/dressipi/init.py 0 0 100%
merlin/datasets/ecommerce/dressipi/dataset.py 45 37 18%
merlin/datasets/ecommerce/dressipi/preprocessed/init.py 0 0 100%
merlin/datasets/ecommerce/large/init.py 0 0 100%
merlin/datasets/ecommerce/small/init.py 0 0 100%
merlin/datasets/ecommerce/transactions/init.py 0 0 100%
merlin/datasets/entertainment/init.py 2 0 100%
merlin/datasets/entertainment/movielens/1m-raw/init.py 0 0 100%
merlin/datasets/entertainment/movielens/1m-raw/ratings/init.py 0 0 100%
merlin/datasets/entertainment/movielens/1m/init.py 0 0 100%
merlin/datasets/entertainment/movielens/25m/init.py 0 0 100%
merlin/datasets/entertainment/movielens/100k/init.py 0 0 100%
merlin/datasets/entertainment/movielens/init.py 0 0 100%
merlin/datasets/entertainment/movielens/dataset.py 152 122 20%
merlin/datasets/entertainment/music_streaming/init.py 0 0 100%
merlin/datasets/social/init.py 0 0 100%
merlin/datasets/synthetic.py 147 8 95%
merlin/datasets/testing/init.py 0 0 100%
merlin/datasets/testing/sequence_testing/init.py 0 0 100%
merlin/models/init.py 2 0 100%
merlin/models/_version.py 354 205 42%
merlin/models/api.py 14 5 64%
merlin/models/config/init.py 0 0 100%
merlin/models/config/schema.py 62 0 100%
merlin/models/implicit/init.py 27 4 85%
merlin/models/io.py 15 0 100%
merlin/models/lightfm/init.py 23 0 100%
merlin/models/loader/init.py 0 0 100%
merlin/models/loader/backend.py 379 41 89%
merlin/models/loader/dataframe_iter.py 21 17 19%
merlin/models/loader/tf_utils.py 57 27 53%
merlin/models/loader/utils.py 40 15 62%
merlin/models/tf/init.py 70 0 100%
merlin/models/tf/blocks/init.py 0 0 100%
merlin/models/tf/blocks/cross.py 44 0 100%
merlin/models/tf/blocks/dlrm.py 49 2 96%
merlin/models/tf/blocks/experts.py 99 17 83%
merlin/models/tf/blocks/interaction.py 108 40 63%
merlin/models/tf/blocks/mlp.py 117 7 94%
merlin/models/tf/blocks/optimizer.py 173 12 93%
merlin/models/tf/blocks/retrieval/init.py 0 0 100%
merlin/models/tf/blocks/retrieval/base.py 169 62 63%
merlin/models/tf/blocks/retrieval/matrix_factorization.py 35 1 97%
merlin/models/tf/blocks/retrieval/two_tower.py 30 0 100%
merlin/models/tf/blocks/sampling/init.py 0 0 100%
merlin/models/tf/blocks/sampling/base.py 29 2 93%
merlin/models/tf/blocks/sampling/cross_batch.py 46 2 96%
merlin/models/tf/blocks/sampling/in_batch.py 35 0 100%
merlin/models/tf/blocks/sampling/queue.py 115 12 90%
merlin/models/tf/core/init.py 0 0 100%
merlin/models/tf/core/aggregation.py 241 45 81%
merlin/models/tf/core/base.py 244 50 80%
merlin/models/tf/core/combinators.py 426 53 88%
merlin/models/tf/core/encoder.py 175 28 84%
merlin/models/tf/core/index.py 104 16 85%
merlin/models/tf/core/prediction.py 50 1 98%
merlin/models/tf/core/tabular.py 280 29 90%
merlin/models/tf/distributed/init.py 0 0 100%
merlin/models/tf/distributed/backend.py 9 2 78%
merlin/models/tf/inputs/init.py 0 0 100%
merlin/models/tf/inputs/base.py 60 10 83%
merlin/models/tf/inputs/continuous.py 39 3 92%
merlin/models/tf/inputs/embedding.py 458 32 93%
merlin/models/tf/loader.py 268 94 65%
merlin/models/tf/losses/init.py 4 0 100%
merlin/models/tf/losses/base.py 9 0 100%
merlin/models/tf/losses/listwise.py 13 0 100%
merlin/models/tf/losses/pairwise.py 115 1 99%
merlin/models/tf/metrics/init.py 2 0 100%
merlin/models/tf/metrics/evaluation.py 105 48 54%
merlin/models/tf/metrics/topk.py 198 48 76%
merlin/models/tf/models/init.py 0 0 100%
merlin/models/tf/models/base.py 756 101 87%
merlin/models/tf/models/benchmark.py 16 0 100%
merlin/models/tf/models/ranking.py 67 3 96%
merlin/models/tf/models/retrieval.py 78 4 95%
merlin/models/tf/models/utils.py 10 1 90%
merlin/models/tf/outputs/init.py 0 0 100%
merlin/models/tf/outputs/base.py 123 17 86%
merlin/models/tf/outputs/classification.py 91 1 99%
merlin/models/tf/outputs/contrastive.py 147 10 93%
merlin/models/tf/outputs/regression.py 9 0 100%
merlin/models/tf/outputs/sampling/init.py 0 0 100%
merlin/models/tf/outputs/sampling/base.py 78 21 73%
merlin/models/tf/outputs/sampling/in_batch.py 37 1 97%
merlin/models/tf/outputs/sampling/popularity.py 27 1 96%
merlin/models/tf/outputs/topk.py 98 6 94%
merlin/models/tf/prediction_tasks/init.py 0 0 100%
merlin/models/tf/prediction_tasks/base.py 207 37 82%
merlin/models/tf/prediction_tasks/classification.py 68 17 75%
merlin/models/tf/prediction_tasks/multi.py 7 0 100%
merlin/models/tf/prediction_tasks/next_item.py 59 6 90%
merlin/models/tf/prediction_tasks/regression.py 35 2 94%
merlin/models/tf/prediction_tasks/retrieval.py 73 3 96%
merlin/models/tf/transformers/init.py 0 0 100%
merlin/models/tf/transformers/block.py 101 2 98%
merlin/models/tf/transformers/transforms.py 63 0 100%
merlin/models/tf/transforms/init.py 0 0 100%
merlin/models/tf/transforms/bias.py 111 9 92%
merlin/models/tf/transforms/features.py 435 36 92%
merlin/models/tf/transforms/negative_sampling.py 77 3 96%
merlin/models/tf/transforms/noise.py 43 1 98%
merlin/models/tf/transforms/regularization.py 17 1 94%
merlin/models/tf/transforms/sequence.py 282 42 85%
merlin/models/tf/transforms/tensor.py 158 13 92%
merlin/models/tf/typing.py 7 0 100%
merlin/models/tf/utils/init.py 0 0 100%
merlin/models/tf/utils/batch_utils.py 85 4 95%
merlin/models/tf/utils/repr_utils.py 69 4 94%
merlin/models/tf/utils/search_utils.py 34 22 35%
merlin/models/tf/utils/testing_utils.py 206 36 83%
merlin/models/tf/utils/tf_utils.py 209 42 80%
merlin/models/torch/init.py 12 0 100%
merlin/models/torch/block/init.py 0 0 100%
merlin/models/torch/block/base.py 167 32 81%
merlin/models/torch/block/mlp.py 38 5 87%
merlin/models/torch/dataset.py 68 5 93%
merlin/models/torch/features/init.py 0 0 100%
merlin/models/torch/features/base.py 4 0 100%
merlin/models/torch/features/continuous.py 22 0 100%
merlin/models/torch/features/embedding.py 165 12 93%
merlin/models/torch/features/tabular.py 65 8 88%
merlin/models/torch/losses.py 28 28 0%
merlin/models/torch/model/init.py 0 0 100%
merlin/models/torch/model/base.py 286 65 77%
merlin/models/torch/model/prediction_task.py 24 0 100%
merlin/models/torch/tabular/init.py 0 0 100%
merlin/models/torch/tabular/aggregation.py 75 0 100%
merlin/models/torch/tabular/base.py 247 39 84%
merlin/models/torch/tabular/transformations.py 67 3 96%
merlin/models/torch/typing.py 6 0 100%
merlin/models/torch/utils/init.py 0 0 100%
merlin/models/torch/utils/data_utils.py 117 117 0%
merlin/models/torch/utils/examples_utils.py 39 39 0%
merlin/models/torch/utils/torch_utils.py 80 22 72%
merlin/models/utils/init.py 0 0 100%
merlin/models/utils/constants.py 3 0 100%
merlin/models/utils/dataset.py 38 4 89%
merlin/models/utils/dependencies.py 26 19 27%
merlin/models/utils/doc_utils.py 10 0 100%
merlin/models/utils/example_utils.py 31 2 94%
merlin/models/utils/misc_utils.py 118 90 24%
merlin/models/utils/nvt_utils.py 27 24 11%
merlin/models/utils/registry.py 101 29 71%
merlin/models/utils/schema_utils.py 90 19 79%
merlin/models/xgb/init.py 124 4 97%

TOTAL 11575 2346 80%

=========================== short test summary info ============================
SKIPPED [1] tests/unit/datasets/test_advertising.py:20: No data-dir available, pass it through env variable $INPUT_DATA_DIR
SKIPPED [1] tests/unit/datasets/test_ecommerce.py:64: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP
SKIPPED [1] tests/unit/datasets/test_ecommerce.py:80: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP
SKIPPED [1] tests/unit/datasets/test_ecommerce.py:94: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP
SKIPPED [1] tests/unit/datasets/test_ecommerce.py:115: No data-dir available, pass it through env variable $INPUT_DATA_DIR
SKIPPED [3] tests/unit/datasets/test_entertainment.py:44: No data-dir available, pass it through env variable $INPUT_DATA_DIR
SKIPPED [5] ../../../.local/lib/python3.8/site-packages/tensorflow/python/framework/test_util.py:2746: Not a test.
========= 871 passed, 13 skipped, 1446 warnings in 1821.35s (0:30:21) ==========
/usr/local/lib/python3.8/dist-packages/coverage/data.py:130: CoverageWarning: Couldn't use data file '/var/jenkins_home/workspace/merlin_models/models/.coverage.10.20.17.231.31009.053389': database disk image is malformed
data._warn(str(exc))
___________________________________ summary ____________________________________
py38-gpu: commands succeeded
congratulations :)
Performing Post build task...
Match found for : : True
Logical operation result is TRUE
Running script : #!/bin/bash
cd /var/jenkins_home/
CUDA_VISIBLE_DEVICES=1 python test_res_push.py "https://api.GitHub.com/repos/NVIDIA-Merlin/models/issues/$ghprbPullId/comments" "/var/jenkins_home/jobs/$JOB_NAME/builds/$BUILD_NUMBER/log"
[merlin_models] $ /bin/bash /tmp/jenkins15329448368483679737.sh

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take a look on --> take a look at


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take a look on --> take a look at.

what'd happen if we have a super large dataset and only 2 gpus? how we would set out_files_per_proc arg then? can it be multiply of the num_gpus like 4, 6 etc? the reason I ask this, if we have a large set, we might want to output several parquet files..


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what'd happen if we have a super large dataset and only 2 gpus? how we would set out_files_per_proc arg then? can it be multiply of the num_gpus like 4, 6 etc? the reason I ask this, if we have a large set, we might want to output several parquet files..

That is correct

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where is hvd.init() command? is it happening under the hood?


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Yes it happens under the hood

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Line #5.    MPI_SIZE = int(os.getenv("OMPI_COMM_WORLD_SIZE"))

I get error when I type this in a notebook..


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It requires to use horovodrun

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GitHub pull request #855 of commit 80c3648e4be928268c933dbed48c5439f46f1798, no merge conflicts.
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Setting status of 80c3648e4be928268c933dbed48c5439f46f1798 to PENDING with url http://merlin-infra1.nvidia.com:8080/job/merlin_models/1915/ and message: 'Pending'
Using context: Jenkins
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using credential nvidia-merlin-bot
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Commit message: "Merge branch 'main' into multi-gpu-data-parallel"
 > git rev-list --no-walk fa2c6ac322a98dbfbb36bef3ea8ddf6b53c6690f # timeout=10
[merlin_models] $ /bin/bash /tmp/jenkins2177760339800247759.sh
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Requirement already satisfied: tornado>=6.2 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (6.2)
Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (2.8.2)
Requirement already satisfied: pyzmq>=23.0 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (24.0.0)
Requirement already satisfied: entrypoints in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (0.4)
Requirement already satisfied: zipp>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from importlib-resources>=1.4.0->jsonschema>=2.6->nbformat>=5.0.4->testbook) (3.8.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.8.2->jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (1.15.0)
GLOB sdist-make: /var/jenkins_home/workspace/merlin_models/models/setup.py
py38-gpu recreate: /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
py38-gpu installdeps: -rrequirements/dev.txt, tensorflow<2.10
WARNING: Discarding $PYTHONPATH from environment, to override specify PYTHONPATH in 'passenv' in your configuration.
py38-gpu inst: /var/jenkins_home/workspace/merlin_models/models/.tox/.tmp/package/4/merlin-models-0.9.0+60.g80c3648e.zip
WARNING: Discarding $PYTHONPATH from environment, to override specify PYTHONPATH in 'passenv' in your configuration.
py38-gpu installed: absl-py==1.2.0,aiohttp==3.8.1,aiosignal==1.2.0,alabaster==0.7.12,alembic==1.8.1,anyio==3.6.1,appdirs==1.4.4,argon2-cffi==21.3.0,argon2-cffi-bindings==21.2.0,astroid==2.5.6,asttokens==2.0.8,astunparse==1.6.3,asv==0.5.1,asvdb==0.4.2,async-timeout==4.0.2,attrs==22.1.0,autopage==0.5.1,awscli==1.27.13,Babel==2.10.3,backcall==0.2.0,beautifulsoup4==4.11.1,betterproto==1.2.5,black==20.8b1,bleach==5.0.1,bokeh==3.0.2,boto3==1.24.75,botocore==1.29.13,Brotli==1.0.9,build==0.9.0,cachetools==5.2.0,certifi==2019.11.28,cffi==1.15.1,chardet==3.0.4,charset-normalizer==2.1.1,check-manifest==0.48,clang==5.0,click==8.1.3,cliff==4.1.0,cloudpickle==2.2.0,cmaes==0.9.0,cmake==3.24.1.1,cmd2==2.4.2,colorama==0.4.4,colorlog==6.7.0,contourpy==1.0.5,coverage==6.5.0,cuda-python==11.7.1,cupy-cuda117==10.6.0,cycler==0.11.0,Cython==0.29.32,dask==2022.5.1,dbus-python==1.2.16,debugpy==1.6.3,decorator==5.1.1,defusedxml==0.7.1,dill==0.3.5.1,distlib==0.3.6,distributed==2022.5.1,distro==1.7.0,dm-tree==0.1.6,docker-pycreds==0.4.0,docutils==0.16,emoji==1.7.0,entrypoints==0.4,execnet==1.9.0,executing==1.0.0,faiss==1.7.2,faiss-gpu==1.7.2,fastai==2.7.9,fastapi==0.85.0,fastavro==1.6.1,fastcore==1.5.27,fastdownload==0.0.7,fastjsonschema==2.16.1,fastprogress==1.0.3,fastrlock==0.8,feast==0.19.4,fiddle==0.2.2,filelock==3.8.0,flake8==5.0.4,flatbuffers==1.12,fonttools==4.37.3,frozenlist==1.3.1,fsspec==2022.5.0,gast==0.4.0,gevent==21.12.0,geventhttpclient==2.0.2,gitdb==4.0.9,GitPython==3.1.27,google==3.0.0,google-api-core==2.10.1,google-auth==2.11.1,google-auth-oauthlib==0.4.6,google-pasta==0.2.0,googleapis-common-protos==1.52.0,graphviz==0.20.1,greenlet==1.1.3,grpcio==1.41.0,grpcio-channelz==1.49.0,grpcio-reflection==1.48.1,grpclib==0.4.3,h11==0.13.0,h2==4.1.0,h5py==3.7.0,HeapDict==1.0.1,horovod==0.26.1,hpack==4.0.0,httptools==0.5.0,hugectr2onnx==0.0.0,huggingface-hub==0.9.1,hyperframe==6.0.1,idna==2.8,imagesize==1.4.1,implicit==0.6.1,importlib-metadata==4.12.0,importlib-resources==5.9.0,iniconfig==1.1.1,interrogate==1.5.0,ipykernel==6.15.3,ipython==8.5.0,ipython-genutils==0.2.0,ipywidgets==7.7.0,isort==5.10.1,jedi==0.18.1,Jinja2==3.1.2,jmespath==1.0.1,joblib==1.2.0,json5==0.9.10,jsonschema==4.16.0,jupyter==1.0.0,jupyter-cache==0.4.3,jupyter-console==6.4.4,jupyter-core==4.11.1,jupyter-server==1.18.1,jupyter-server-mathjax==0.2.5,jupyter-sphinx==0.3.2,jupyter_client==7.3.5,jupyterlab==3.4.7,jupyterlab-pygments==0.2.2,jupyterlab-widgets==1.1.0,jupyterlab_server==2.15.1,keras==2.9.0,Keras-Preprocessing==1.1.2,kiwisolver==1.4.4,lazy-object-proxy==1.8.0,libclang==14.0.6,libcst==0.4.7,lightfm==1.16,lightgbm==3.3.2,linkify-it-py==1.0.3,llvmlite==0.39.1,locket==1.0.0,lxml==4.9.1,Mako==1.2.4,Markdown==3.4.1,markdown-it-py==1.1.0,MarkupSafe==2.1.1,matplotlib==3.6.0,matplotlib-inline==0.1.6,mccabe==0.7.0,mdit-py-plugins==0.2.8,merlin-core==0.6.0+1.g5926fcf,merlin-dataloader==0.0.2,merlin-models==0.9.0+60.g80c3648e,merlin-systems==0.5.0+4.g15074ad,mistune==2.0.4,mmh3==3.0.0,mpi4py==3.1.3,msgpack==1.0.4,multidict==6.0.2,mypy==0.991,mypy-extensions==0.4.3,myst-nb==0.13.2,myst-parser==0.15.2,natsort==8.1.0,nbclassic==0.4.3,nbclient==0.6.8,nbconvert==7.0.0,nbdime==3.1.1,nbformat==5.5.0,nest-asyncio==1.5.5,ninja==1.10.2.3,notebook==6.4.12,notebook-shim==0.1.0,numba==0.56.2,numpy==1.22.4,nvidia-pyindex==1.0.9,nvtabular @ git+https://github.com/NVIDIA-Merlin/NVTabular.git@e5b7351deb9e4885c4038aa0bbc9f146d8477a0e,nvtx==0.2.5,oauthlib==3.2.1,oldest-supported-numpy==2022.8.16,onnx==1.12.0,onnxruntime==1.11.1,opt-einsum==3.3.0,optuna==3.0.3,packaging==21.3,pandas==1.3.5,pandavro==1.5.2,pandocfilters==1.5.0,parso==0.8.3,partd==1.3.0,pathspec==0.10.2,pathtools==0.1.2,pbr==5.11.0,pep517==0.13.0,pexpect==4.8.0,pickleshare==0.7.5,Pillow==9.2.0,pkgutil_resolve_name==1.3.10,platformdirs==2.5.2,plotly==5.11.0,pluggy==1.0.0,prettytable==3.5.0,prometheus-client==0.14.1,promise==2.3,prompt-toolkit==3.0.31,proto-plus==1.19.6,protobuf==3.19.5,psutil==5.9.2,ptyprocess==0.7.0,pure-eval==0.2.2,py==1.11.0,pyarrow==7.0.0,pyasn1==0.4.8,pyasn1-modules==0.2.8,pybind11==2.10.0,pycodestyle==2.9.1,pycparser==2.21,pydantic==1.10.2,pydot==1.4.2,pyflakes==2.5.0,Pygments==2.13.0,PyGObject==3.36.0,pynvml==11.4.1,pyparsing==3.0.9,pyperclip==1.8.2,pyrsistent==0.18.1,pytest==7.1.3,pytest-cov==4.0.0,pytest-xdist==3.0.2,python-apt==2.0.0+ubuntu0.20.4.8,python-dateutil==2.8.2,python-dotenv==0.21.0,python-rapidjson==1.8,pytz==2022.2.1,PyYAML==5.4.1,pyzmq==24.0.0,qtconsole==5.4.0,QtPy==2.3.0,regex==2022.9.13,requests==2.22.0,requests-oauthlib==1.3.1,requests-unixsocket==0.2.0,rsa==4.7.2,s3fs==2022.2.0,s3transfer==0.6.0,sacremoses==0.0.53,scikit-build==0.15.0,scikit-learn==1.1.2,scipy==1.8.1,seedir==0.3.0,Send2Trash==1.8.0,sentry-sdk==1.9.8,setproctitle==1.3.2,setuptools-scm==7.0.5,shortuuid==1.0.9,six==1.15.0,sklearn==0.0,smmap==5.0.0,sniffio==1.3.0,snowballstemmer==2.2.0,sortedcontainers==2.4.0,soupsieve==2.3.2.post1,Sphinx==5.3.0,sphinx-multiversion==0.2.4,sphinx-togglebutton==0.3.1,sphinx_external_toc==0.3.0,sphinxcontrib-applehelp==1.0.2,sphinxcontrib-copydirs @ git+https://github.com/mikemckiernan/sphinxcontrib-copydirs.git@bd8c5d79b3f91cf5f1bb0d6995aeca3fe84b670e,sphinxcontrib-devhelp==1.0.2,sphinxcontrib-htmlhelp==2.0.0,sphinxcontrib-jsmath==1.0.1,sphinxcontrib-qthelp==1.0.3,sphinxcontrib-serializinghtml==1.1.5,SQLAlchemy==1.4.44,stack-data==0.5.0,starlette==0.20.4,stevedore==4.1.1,stringcase==1.2.0,supervisor==4.1.0,tabulate==0.8.10,tblib==1.7.0,tdqm==0.0.1,tenacity==8.0.1,tensorboard==2.9.1,tensorboard-data-server==0.6.1,tensorboard-plugin-wit==1.8.1,tensorflow==2.9.2,tensorflow-estimator==2.9.0,tensorflow-gpu==2.9.2,tensorflow-io-gcs-filesystem==0.27.0,tensorflow-metadata==1.10.0,termcolor==2.0.1,terminado==0.15.0,testbook==0.4.2,threadpoolctl==3.1.0,tinycss2==1.1.1,tokenizers==0.10.3,toml==0.10.2,tomli==2.0.1,toolz==0.12.0,torch==1.12.1+cu113,torchmetrics==0.3.2,tornado==6.2,tox==3.26.0,tqdm==4.64.1,traitlets==5.4.0,transformers==4.12.0,transformers4rec==0.1.12+2.gbcc939255,treelite==2.3.0,treelite-runtime==2.3.0,tritonclient==2.25.0,typed-ast==1.5.4,typing-inspect==0.8.0,typing_extensions==4.3.0,uc-micro-py==1.0.1,urllib3==1.26.12,uvicorn==0.18.3,uvloop==0.17.0,versioneer==0.20,virtualenv==20.16.5,wandb==0.13.3,watchfiles==0.17.0,wcwidth==0.2.5,webencodings==0.5.1,websocket-client==1.4.1,websockets==10.3,Werkzeug==2.2.2,widgetsnbextension==3.6.0,wrapt==1.12.1,xgboost==1.6.2,xyzservices==2022.9.0,yarl==1.8.1,zict==2.2.0,zipp==3.8.1,zope.event==4.5.0,zope.interface==5.4.0
py38-gpu run-test-pre: PYTHONHASHSEED='3548183598'
py38-gpu run-test: commands[0] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/core.git
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Collecting git+https://github.com/NVIDIA-Merlin/core.git
  Cloning https://github.com/NVIDIA-Merlin/core.git to /tmp/pip-req-build-m6enjpoy
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/core.git /tmp/pip-req-build-m6enjpoy
  Resolved https://github.com/NVIDIA-Merlin/core.git to commit 04ff5225cee6af90b6b08070493677ac53b96836
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: protobuf>=3.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+16.g04ff522) (3.19.5)
Requirement already satisfied: distributed>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+16.g04ff522) (2022.3.0)
Requirement already satisfied: pandas<1.4.0dev0,>=1.2.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+16.g04ff522) (1.3.5)
Requirement already satisfied: pyarrow>=5.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+16.g04ff522) (7.0.0)
Requirement already satisfied: betterproto<2.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+16.g04ff522) (1.2.5)
Requirement already satisfied: packaging in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+16.g04ff522) (21.3)
Requirement already satisfied: tensorflow-metadata>=1.2.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+16.g04ff522) (1.10.0)
Requirement already satisfied: fsspec==2022.5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+16.g04ff522) (2022.5.0)
Requirement already satisfied: tqdm>=4.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+16.g04ff522) (4.64.1)
Requirement already satisfied: numba>=0.54 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+16.g04ff522) (0.55.1)
Requirement already satisfied: dask>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+16.g04ff522) (2022.3.0)
Requirement already satisfied: grpclib in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core==0.8.0+16.g04ff522) (0.4.3)
Requirement already satisfied: stringcase in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core==0.8.0+16.g04ff522) (1.2.0)
Requirement already satisfied: toolz>=0.8.2 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (0.12.0)
Requirement already satisfied: partd>=0.3.10 in /var/jenkins_home/.local/lib/python3.8/site-packages/partd-1.2.0-py3.8.egg (from dask>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (1.2.0)
Requirement already satisfied: cloudpickle>=1.1.1 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (2.2.0)
Requirement already satisfied: pyyaml>=5.3.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/PyYAML-5.4.1-py3.8-linux-x86_64.egg (from dask>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (5.4.1)
Requirement already satisfied: tblib>=1.6.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/tblib-1.7.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (1.7.0)
Requirement already satisfied: sortedcontainers!=2.0.0,!=2.0.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/sortedcontainers-2.4.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (2.4.0)
Requirement already satisfied: psutil>=5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/psutil-5.8.0-py3.8-linux-x86_64.egg (from distributed>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (5.8.0)
Requirement already satisfied: zict>=0.1.3 in /var/jenkins_home/.local/lib/python3.8/site-packages/zict-2.0.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (2.0.0)
Requirement already satisfied: msgpack>=0.6.0 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (1.0.4)
Requirement already satisfied: tornado>=6.0.3 in ./.tox/py38-gpu/lib/python3.8/site-packages (from distributed>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (6.2)
Requirement already satisfied: click>=6.6 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (8.1.3)
Requirement already satisfied: jinja2 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (3.1.2)
Requirement already satisfied: llvmlite<0.39,>=0.38.0rc1 in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+16.g04ff522) (0.38.1)
Requirement already satisfied: numpy<1.22,>=1.18 in /var/jenkins_home/.local/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+16.g04ff522) (1.20.3)
Requirement already satisfied: setuptools in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+16.g04ff522) (65.5.1)
Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in /usr/local/lib/python3.8/dist-packages (from packaging->merlin-core==0.8.0+16.g04ff522) (3.0.9)
Requirement already satisfied: pytz>=2017.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+16.g04ff522) (2022.2.1)
Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+16.g04ff522) (2.8.2)
Requirement already satisfied: absl-py<2.0.0,>=0.9 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core==0.8.0+16.g04ff522) (1.2.0)
Requirement already satisfied: googleapis-common-protos<2,>=1.52.0 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core==0.8.0+16.g04ff522) (1.52.0)
Requirement already satisfied: locket in /var/jenkins_home/.local/lib/python3.8/site-packages/locket-0.2.1-py3.8.egg (from partd>=0.3.10->dask>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (0.2.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.7.3->pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+16.g04ff522) (1.15.0)
Requirement already satisfied: heapdict in /var/jenkins_home/.local/lib/python3.8/site-packages/HeapDict-1.0.1-py3.8.egg (from zict>=0.1.3->distributed>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (1.0.1)
Requirement already satisfied: multidict in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core==0.8.0+16.g04ff522) (6.0.2)
Requirement already satisfied: h2<5,>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core==0.8.0+16.g04ff522) (4.1.0)
Requirement already satisfied: MarkupSafe>=2.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from jinja2->distributed>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (2.0.1)
Requirement already satisfied: hyperframe<7,>=6.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core==0.8.0+16.g04ff522) (6.0.1)
Requirement already satisfied: hpack<5,>=4.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core==0.8.0+16.g04ff522) (4.0.0)
Building wheels for collected packages: merlin-core
  Building wheel for merlin-core (pyproject.toml): started
  Building wheel for merlin-core (pyproject.toml): finished with status 'done'
  Created wheel for merlin-core: filename=merlin_core-0.8.0+16.g04ff522-py3-none-any.whl size=118833 sha256=e1287351b4d08bf0a7c973c3d8a2bd4a6d3220c31ac4cf5fec2e117c5617f029
  Stored in directory: /tmp/pip-ephem-wheel-cache-k4oqos3p/wheels/c8/38/16/a6968787eafcec5fa772148af8408b089562f71af0752e8e84
Successfully built merlin-core
Installing collected packages: merlin-core
  Attempting uninstall: merlin-core
    Found existing installation: merlin-core 0.3.0+12.g78ecddd
    Not uninstalling merlin-core at /var/jenkins_home/.local/lib/python3.8/site-packages, outside environment /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
    Can't uninstall 'merlin-core'. No files were found to uninstall.
Successfully installed merlin-core-0.8.0+16.g04ff522
py38-gpu run-test: commands[1] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/nvtabular.git
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Collecting git+https://github.com/NVIDIA-Merlin/nvtabular.git
  Cloning https://github.com/NVIDIA-Merlin/nvtabular.git to /tmp/pip-req-build-otq2b00m
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/nvtabular.git /tmp/pip-req-build-otq2b00m
  Resolved https://github.com/NVIDIA-Merlin/nvtabular.git to commit e5b7351deb9e4885c4038aa0bbc9f146d8477a0e
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: merlin-dataloader>=0.0.2 in /usr/local/lib/python3.8/dist-packages (from nvtabular==1.6.0+6.ge5b7351d) (0.0.2)
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Requirement already satisfied: hpack<5,>=4.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core>=0.2.0->nvtabular==1.6.0+6.ge5b7351d) (4.0.0)
Building wheels for collected packages: nvtabular
  Building wheel for nvtabular (pyproject.toml): started
  Building wheel for nvtabular (pyproject.toml): finished with status 'done'
  Created wheel for nvtabular: filename=nvtabular-1.6.0+6.ge5b7351d-cp38-cp38-linux_x86_64.whl size=257597 sha256=74b8a8719530a2d34f9a3e536477175dbf816533528b689f9c5b41797cd1d56e
  Stored in directory: /tmp/pip-ephem-wheel-cache-6s_qwlyz/wheels/8f/d9/f9/30f2cdc5bf8787fae6fdfe55afd6e1b493e619ec32c32ec40b
Successfully built nvtabular
Installing collected packages: nvtabular
  Attempting uninstall: nvtabular
    Found existing installation: nvtabular 1.1.1
    Not uninstalling nvtabular at /var/jenkins_home/.local/lib/python3.8/site-packages, outside environment /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
    Can't uninstall 'nvtabular'. No files were found to uninstall.
Successfully installed nvtabular-1.6.0+6.ge5b7351d
py38-gpu run-test: commands[2] | python -m pytest --cov-report term --cov merlin -rxs tests/unit
============================= test session starts ==============================
platform linux -- Python 3.8.10, pytest-7.1.3, pluggy-1.0.0
cachedir: .tox/py38-gpu/.pytest_cache
rootdir: /var/jenkins_home/workspace/merlin_models/models, configfile: pyproject.toml
plugins: anyio-3.5.0, xdist-3.0.2, cov-4.0.0
collected 884 items

tests/unit/config/test_schema.py .... [ 0%]
tests/unit/datasets/test_advertising.py .s [ 0%]
tests/unit/datasets/test_ecommerce.py ..sss.s [ 1%]
tests/unit/datasets/test_entertainment.py ....sss. [ 2%]
tests/unit/datasets/test_social.py . [ 2%]
tests/unit/datasets/test_synthetic.py .......... [ 3%]
tests/unit/implicit/test_implicit.py . [ 3%]
tests/unit/lightfm/test_lightfm.py . [ 3%]
tests/unit/tf/test_core.py ...... [ 4%]
tests/unit/tf/test_loader.py ................ [ 6%]
tests/unit/tf/test_public_api.py . [ 6%]
tests/unit/tf/blocks/test_cross.py ........... [ 7%]
tests/unit/tf/blocks/test_dlrm.py .......... [ 8%]
tests/unit/tf/blocks/test_interactions.py ... [ 9%]
tests/unit/tf/blocks/test_mlp.py ....................................... [ 13%]
............................ [ 16%]
tests/unit/tf/blocks/test_optimizer.py s................................ [ 20%]
..................... [ 22%]
tests/unit/tf/blocks/retrieval/test_base.py . [ 22%]
tests/unit/tf/blocks/retrieval/test_matrix_factorization.py .. [ 23%]
tests/unit/tf/blocks/retrieval/test_two_tower.py ............ [ 24%]
tests/unit/tf/blocks/sampling/test_cross_batch.py . [ 24%]
tests/unit/tf/blocks/sampling/test_in_batch.py . [ 24%]
tests/unit/tf/core/test_aggregation.py ......... [ 25%]
tests/unit/tf/core/test_base.py .. [ 26%]
tests/unit/tf/core/test_combinators.py s..................... [ 28%]
tests/unit/tf/core/test_encoder.py .. [ 28%]
tests/unit/tf/core/test_index.py ... [ 29%]
tests/unit/tf/core/test_prediction.py .. [ 29%]
tests/unit/tf/core/test_tabular.py ...... [ 29%]
tests/unit/tf/examples/test_01_getting_started.py . [ 30%]
tests/unit/tf/examples/test_02_dataschema.py . [ 30%]
tests/unit/tf/examples/test_03_exploring_different_models.py . [ 30%]
tests/unit/tf/examples/test_04_export_ranking_models.py . [ 30%]
tests/unit/tf/examples/test_05_export_retrieval_model.py . [ 30%]
tests/unit/tf/examples/test_06_advanced_own_architecture.py . [ 30%]
tests/unit/tf/examples/test_07_train_traditional_models.py . [ 30%]
tests/unit/tf/examples/test_usecase_accelerate_training_by_lazyadam.py . [ 30%]
[ 30%]
tests/unit/tf/examples/test_usecase_data_parallel.py . [ 30%]
tests/unit/tf/examples/test_usecase_ecommerce_session_based.py . [ 31%]
tests/unit/tf/examples/test_usecase_incremental_training_layer_freezing.py . [ 31%]
[ 31%]
tests/unit/tf/examples/test_usecase_pretrained_embeddings.py . [ 31%]
tests/unit/tf/examples/test_usecase_retrieval_with_hpo.py . [ 31%]
tests/unit/tf/examples/test_usecase_transformers_next_item_prediction.py . [ 31%]
[ 31%]
tests/unit/tf/horovod/test_horovod.py ... [ 31%]
tests/unit/tf/inputs/test_base.py . [ 32%]
tests/unit/tf/inputs/test_continuous.py ........ [ 32%]
tests/unit/tf/inputs/test_embedding.py ................................. [ 36%]
........ [ 37%]
tests/unit/tf/inputs/test_tabular.py .................. [ 39%]
tests/unit/tf/layers/test_queue.py .............. [ 41%]
tests/unit/tf/losses/test_losses.py ....................... [ 43%]
tests/unit/tf/metrics/test_metrics_popularity.py ..... [ 44%]
tests/unit/tf/metrics/test_metrics_topk.py ......................... [ 47%]
tests/unit/tf/models/test_base.py s......................... [ 50%]
tests/unit/tf/models/test_benchmark.py .. [ 50%]
tests/unit/tf/models/test_ranking.py .................................. [ 54%]
tests/unit/tf/models/test_retrieval.py ................................. [ 57%]
........................................... [ 62%]
tests/unit/tf/outputs/test_base.py ...... [ 63%]
tests/unit/tf/outputs/test_classification.py ...... [ 64%]
tests/unit/tf/outputs/test_contrastive.py .............. [ 65%]
tests/unit/tf/outputs/test_regression.py .. [ 65%]
tests/unit/tf/outputs/test_sampling.py .... [ 66%]
tests/unit/tf/outputs/test_topk.py . [ 66%]
tests/unit/tf/prediction_tasks/test_classification.py .. [ 66%]
tests/unit/tf/prediction_tasks/test_multi_task.py ................ [ 68%]
tests/unit/tf/prediction_tasks/test_next_item.py ..... [ 69%]
tests/unit/tf/prediction_tasks/test_regression.py ..... [ 69%]
tests/unit/tf/prediction_tasks/test_retrieval.py . [ 69%]
tests/unit/tf/prediction_tasks/test_sampling.py ...... [ 70%]
tests/unit/tf/transformers/test_block.py ...................... [ 72%]
tests/unit/tf/transformers/test_transforms.py .......... [ 74%]
tests/unit/tf/transforms/test_bias.py .. [ 74%]
tests/unit/tf/transforms/test_features.py s............................. [ 77%]
.......................s...... [ 81%]
tests/unit/tf/transforms/test_negative_sampling.py ......... [ 82%]
tests/unit/tf/transforms/test_noise.py ..... [ 82%]
tests/unit/tf/transforms/test_sequence.py .................... [ 84%]
tests/unit/tf/transforms/test_tensor.py ... [ 85%]
tests/unit/tf/utils/test_batch.py .... [ 85%]
tests/unit/tf/utils/test_dataset.py .. [ 85%]
tests/unit/tf/utils/test_tf_utils.py ..... [ 86%]
tests/unit/torch/test_dataset.py ......... [ 87%]
tests/unit/torch/test_public_api.py . [ 87%]
tests/unit/torch/block/test_base.py .... [ 88%]
tests/unit/torch/block/test_mlp.py . [ 88%]
tests/unit/torch/features/test_continuous.py .. [ 88%]
tests/unit/torch/features/test_embedding.py .............. [ 90%]
tests/unit/torch/features/test_tabular.py .... [ 90%]
tests/unit/torch/model/test_head.py ............ [ 91%]
tests/unit/torch/model/test_model.py .. [ 92%]
tests/unit/torch/tabular/test_aggregation.py ........ [ 92%]
tests/unit/torch/tabular/test_tabular.py ... [ 93%]
tests/unit/torch/tabular/test_transformations.py ....... [ 94%]
tests/unit/utils/test_schema_utils.py ................................ [ 97%]
tests/unit/xgb/test_xgboost.py .................... [100%]

=============================== warnings summary ===============================
../../../../../usr/lib/python3/dist-packages/requests/init.py:89
/usr/lib/python3/dist-packages/requests/init.py:89: RequestsDependencyWarning: urllib3 (1.26.12) or chardet (3.0.4) doesn't match a supported version!
warnings.warn("urllib3 ({}) or chardet ({}) doesn't match a supported "

../../../.local/lib/python3.8/site-packages/flatbuffers/compat.py:19
/var/jenkins_home/.local/lib/python3.8/site-packages/flatbuffers/compat.py:19: DeprecationWarning: the imp module is deprecated in favour of importlib; see the module's documentation for alternative uses
import imp

../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36
/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36: DeprecationWarning: NEAREST is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.NEAREST or Dither.NONE instead.
'nearest': pil_image.NEAREST,

../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37
/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37: DeprecationWarning: BILINEAR is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BILINEAR instead.
'bilinear': pil_image.BILINEAR,

../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38
/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38: DeprecationWarning: BICUBIC is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BICUBIC instead.
'bicubic': pil_image.BICUBIC,

../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39
/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39: DeprecationWarning: HAMMING is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.HAMMING instead.
'hamming': pil_image.HAMMING,

../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40
/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40: DeprecationWarning: BOX is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BOX instead.
'box': pil_image.BOX,

../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41
/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41: DeprecationWarning: LANCZOS is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.LANCZOS instead.
'lanczos': pil_image.LANCZOS,

tests/unit/datasets/test_advertising.py: 1 warning
tests/unit/datasets/test_ecommerce.py: 3 warnings
tests/unit/datasets/test_entertainment.py: 4 warnings
tests/unit/datasets/test_social.py: 1 warning
tests/unit/datasets/test_synthetic.py: 10 warnings
tests/unit/implicit/test_implicit.py: 1 warning
tests/unit/lightfm/test_lightfm.py: 1 warning
tests/unit/tf/test_core.py: 6 warnings
tests/unit/tf/test_loader.py: 1 warning
tests/unit/tf/blocks/test_cross.py: 5 warnings
tests/unit/tf/blocks/test_dlrm.py: 9 warnings
tests/unit/tf/blocks/test_interactions.py: 2 warnings
tests/unit/tf/blocks/test_mlp.py: 60 warnings
tests/unit/tf/blocks/test_optimizer.py: 30 warnings
tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings
tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings
tests/unit/tf/core/test_aggregation.py: 6 warnings
tests/unit/tf/core/test_base.py: 2 warnings
tests/unit/tf/core/test_combinators.py: 11 warnings
tests/unit/tf/core/test_encoder.py: 6 warnings
tests/unit/tf/core/test_index.py: 8 warnings
tests/unit/tf/core/test_prediction.py: 2 warnings
tests/unit/tf/horovod/test_horovod.py: 3 warnings
tests/unit/tf/inputs/test_base.py: 1 warning
tests/unit/tf/inputs/test_continuous.py: 7 warnings
tests/unit/tf/inputs/test_embedding.py: 20 warnings
tests/unit/tf/inputs/test_tabular.py: 18 warnings
tests/unit/tf/models/test_base.py: 28 warnings
tests/unit/tf/models/test_benchmark.py: 2 warnings
tests/unit/tf/models/test_ranking.py: 38 warnings
tests/unit/tf/models/test_retrieval.py: 120 warnings
tests/unit/tf/outputs/test_base.py: 6 warnings
tests/unit/tf/outputs/test_classification.py: 6 warnings
tests/unit/tf/outputs/test_contrastive.py: 19 warnings
tests/unit/tf/outputs/test_regression.py: 2 warnings
tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings
tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings
tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings
tests/unit/tf/prediction_tasks/test_retrieval.py: 1 warning
tests/unit/tf/transformers/test_block.py: 16 warnings
tests/unit/tf/transforms/test_bias.py: 2 warnings
tests/unit/tf/transforms/test_features.py: 10 warnings
tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings
tests/unit/tf/transforms/test_noise.py: 1 warning
tests/unit/tf/transforms/test_sequence.py: 15 warnings
tests/unit/tf/utils/test_batch.py: 9 warnings
tests/unit/tf/utils/test_dataset.py: 2 warnings
tests/unit/torch/block/test_base.py: 4 warnings
tests/unit/torch/block/test_mlp.py: 1 warning
tests/unit/torch/features/test_continuous.py: 1 warning
tests/unit/torch/features/test_embedding.py: 4 warnings
tests/unit/torch/features/test_tabular.py: 4 warnings
tests/unit/torch/model/test_head.py: 12 warnings
tests/unit/torch/model/test_model.py: 2 warnings
tests/unit/torch/tabular/test_aggregation.py: 6 warnings
tests/unit/torch/tabular/test_transformations.py: 3 warnings
tests/unit/xgb/test_xgboost.py: 18 warnings
/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.ITEM_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.ITEM: 'item'>, <Tags.ID: 'id'>].
warnings.warn(

tests/unit/datasets/test_ecommerce.py: 3 warnings
tests/unit/datasets/test_entertainment.py: 4 warnings
tests/unit/datasets/test_social.py: 1 warning
tests/unit/datasets/test_synthetic.py: 9 warnings
tests/unit/implicit/test_implicit.py: 1 warning
tests/unit/lightfm/test_lightfm.py: 1 warning
tests/unit/tf/test_core.py: 6 warnings
tests/unit/tf/test_loader.py: 1 warning
tests/unit/tf/blocks/test_cross.py: 5 warnings
tests/unit/tf/blocks/test_dlrm.py: 9 warnings
tests/unit/tf/blocks/test_interactions.py: 2 warnings
tests/unit/tf/blocks/test_mlp.py: 60 warnings
tests/unit/tf/blocks/test_optimizer.py: 30 warnings
tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings
tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings
tests/unit/tf/core/test_aggregation.py: 6 warnings
tests/unit/tf/core/test_base.py: 2 warnings
tests/unit/tf/core/test_combinators.py: 11 warnings
tests/unit/tf/core/test_encoder.py: 7 warnings
tests/unit/tf/core/test_index.py: 3 warnings
tests/unit/tf/core/test_prediction.py: 2 warnings
tests/unit/tf/horovod/test_horovod.py: 1 warning
tests/unit/tf/inputs/test_base.py: 1 warning
tests/unit/tf/inputs/test_continuous.py: 7 warnings
tests/unit/tf/inputs/test_embedding.py: 20 warnings
tests/unit/tf/inputs/test_tabular.py: 18 warnings
tests/unit/tf/models/test_base.py: 28 warnings
tests/unit/tf/models/test_benchmark.py: 2 warnings
tests/unit/tf/models/test_ranking.py: 36 warnings
tests/unit/tf/models/test_retrieval.py: 86 warnings
tests/unit/tf/outputs/test_base.py: 6 warnings
tests/unit/tf/outputs/test_classification.py: 6 warnings
tests/unit/tf/outputs/test_contrastive.py: 19 warnings
tests/unit/tf/outputs/test_regression.py: 2 warnings
tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings
tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings
tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings
tests/unit/tf/transformers/test_block.py: 10 warnings
tests/unit/tf/transforms/test_features.py: 10 warnings
tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings
tests/unit/tf/transforms/test_sequence.py: 15 warnings
tests/unit/tf/utils/test_batch.py: 7 warnings
tests/unit/tf/utils/test_dataset.py: 2 warnings
tests/unit/torch/block/test_base.py: 4 warnings
tests/unit/torch/block/test_mlp.py: 1 warning
tests/unit/torch/features/test_continuous.py: 1 warning
tests/unit/torch/features/test_embedding.py: 4 warnings
tests/unit/torch/features/test_tabular.py: 4 warnings
tests/unit/torch/model/test_head.py: 12 warnings
tests/unit/torch/model/test_model.py: 2 warnings
tests/unit/torch/tabular/test_aggregation.py: 6 warnings
tests/unit/torch/tabular/test_transformations.py: 2 warnings
tests/unit/xgb/test_xgboost.py: 17 warnings
/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.USER_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.USER: 'user'>, <Tags.ID: 'id'>].
warnings.warn(

tests/unit/datasets/test_ecommerce.py: 1 warning
tests/unit/datasets/test_entertainment.py: 1 warning
tests/unit/implicit/test_implicit.py: 1 warning
tests/unit/lightfm/test_lightfm.py: 1 warning
tests/unit/tf/test_loader.py: 1 warning
tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings
tests/unit/tf/blocks/retrieval/test_two_tower.py: 2 warnings
tests/unit/tf/core/test_combinators.py: 11 warnings
tests/unit/tf/core/test_encoder.py: 2 warnings
tests/unit/tf/core/test_prediction.py: 1 warning
tests/unit/tf/horovod/test_horovod.py: 1 warning
tests/unit/tf/inputs/test_continuous.py: 4 warnings
tests/unit/tf/inputs/test_embedding.py: 9 warnings
tests/unit/tf/inputs/test_tabular.py: 8 warnings
tests/unit/tf/models/test_ranking.py: 20 warnings
tests/unit/tf/models/test_retrieval.py: 10 warnings
tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings
tests/unit/tf/prediction_tasks/test_regression.py: 3 warnings
tests/unit/tf/transforms/test_negative_sampling.py: 9 warnings
tests/unit/xgb/test_xgboost.py: 12 warnings
/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.SESSION_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.SESSION: 'session'>, <Tags.ID: 'id'>].
warnings.warn(

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export
tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export
tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export
tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export
tests/unit/tf/inputs/test_embedding.py::test_embedding_features_exporting_and_loading_pretrained_initializer
/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/inputs/embedding.py:970: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack
embeddings_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(embeddings)))

tests/unit/tf/blocks/retrieval/test_two_tower.py: 1 warning
tests/unit/tf/core/test_index.py: 4 warnings
tests/unit/tf/horovod/test_horovod.py: 3 warnings
tests/unit/tf/models/test_retrieval.py: 55 warnings
tests/unit/tf/prediction_tasks/test_next_item.py: 3 warnings
tests/unit/tf/utils/test_batch.py: 2 warnings
/tmp/autograph_generated_filejeaoty5p.py:8: DeprecationWarning: The 'warn' method is deprecated, use 'warning' instead
ag
.converted_call(ag__.ld(warnings).warn, ("The 'warn' method is deprecated, use 'warning' instead", ag__.ld(DeprecationWarning), 2), None, fscope)

tests/unit/tf/core/test_combinators.py::test_parallel_block_select_by_tags
/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/core/tabular.py:602: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated since Python 3.3, and in 3.10 it will stop working
elif isinstance(self.feature_names, collections.Sequence):

tests/unit/tf/core/test_encoder.py: 1 warning
tests/unit/tf/core/test_index.py: 5 warnings
tests/unit/tf/models/test_retrieval.py: 30 warnings
tests/unit/tf/utils/test_batch.py: 4 warnings
tests/unit/tf/utils/test_dataset.py: 1 warning
/var/jenkins_home/workspace/merlin_models/models/merlin/models/utils/dataset.py:75: DeprecationWarning: unique_rows_by_features is deprecated and will be removed in a future version. Please use unique_by_tag instead.
warnings.warn(

tests/unit/tf/models/test_base.py::test_model_pre_post[True]
tests/unit/tf/models/test_base.py::test_model_pre_post[False]
tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.1]
tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.3]
tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.5]
tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.7]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/util/dispatch.py:1082: UserWarning: tf.keras.backend.random_binomial is deprecated, and will be removed in a future version.Please use tf.keras.backend.random_bernoulli instead.
return dispatch_target(*args, **kwargs)

tests/unit/tf/models/test_base.py::test_freeze_parallel_block[True]
tests/unit/tf/models/test_base.py::test_freeze_sequential_block
tests/unit/tf/models/test_base.py::test_freeze_unfreeze
tests/unit/tf/models/test_base.py::test_unfreeze_all_blocks
/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/gradient_descent.py:108: UserWarning: The lr argument is deprecated, use learning_rate instead.
super(SGD, self).init(name, **kwargs)

tests/unit/tf/models/test_base.py::test_retrieval_model_query
tests/unit/tf/models/test_base.py::test_retrieval_model_query
tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_v2_export_embeddings
tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[True]
tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[False]
tests/unit/tf/transformers/test_block.py::test_retrieval_transformer[True]
/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/utils/tf_utils.py:298: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack
tensor_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(tensor)))

tests/unit/tf/models/test_ranking.py::test_deepfm_model_only_categ_feats[False]
tests/unit/tf/models/test_ranking.py::test_deepfm_model_categ_and_continuous_feats[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/models/test_ranking.py::test_wide_deep_model[False]
tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_categorical_one_hot[False]
tests/unit/tf/models/test_ranking.py::test_wide_deep_model_hashed_cross[False]
tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[True]
tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]
/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/transforms/features.py:569: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag
warnings.warn(

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/autograph/impl/api.py:371: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag
return py_builtins.overload_of(f)(*args)

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_onehot_multihot_feature_interaction[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_feature_interaction_multi_optimizer[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask/GatherV2:0", shape=(None, 48), dtype=float32), dense_shape=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Reshape_3:0", shape=(None,), dtype=int64), values=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Reshape_2:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask/GatherV2:0", shape=(None, 48), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_3:0", shape=(None,), dtype=int64), values=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_2:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/torch/block/test_mlp.py::test_mlp_block
/var/jenkins_home/workspace/merlin_models/models/tests/unit/torch/_conftest.py:151: UserWarning: Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at ../torch/csrc/utils/tensor_new.cpp:201.)
return {key: torch.tensor(value) for key, value in data.items()}

tests/unit/xgb/test_xgboost.py::test_without_dask_client
tests/unit/xgb/test_xgboost.py::TestXGBoost::test_music_regression
tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs0-DaskDeviceQuantileDMatrix]
tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs1-DaskDMatrix]
tests/unit/xgb/test_xgboost.py::TestEvals::test_multiple
tests/unit/xgb/test_xgboost.py::TestEvals::test_default
tests/unit/xgb/test_xgboost.py::TestEvals::test_train_and_valid
tests/unit/xgb/test_xgboost.py::TestEvals::test_invalid_data
/var/jenkins_home/workspace/merlin_models/models/merlin/models/xgb/init.py:344: UserWarning: Ignoring list columns as inputs to XGBoost model: ['item_genres', 'user_genres'].
warnings.warn(f"Ignoring list columns as inputs to XGBoost model: {list_column_names}.")

tests/unit/xgb/test_xgboost.py::TestXGBoost::test_unsupported_objective
/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/tornado/ioloop.py:350: DeprecationWarning: make_current is deprecated; start the event loop first
self.make_current()

tests/unit/xgb/test_xgboost.py: 14 warnings
/usr/local/lib/python3.8/dist-packages/xgboost/dask.py:884: RuntimeWarning: coroutine 'Client._wait_for_workers' was never awaited
client.wait_for_workers(n_workers)
Enable tracemalloc to get traceback where the object was allocated.
See https://docs.pytest.org/en/stable/how-to/capture-warnings.html#resource-warnings for more info.

tests/unit/xgb/test_xgboost.py: 11 warnings
/usr/local/lib/python3.8/dist-packages/cudf/core/dataframe.py:1183: DeprecationWarning: The default dtype for empty Series will be 'object' instead of 'float64' in a future version. Specify a dtype explicitly to silence this warning.
mask = pd.Series(mask)

-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html

---------- coverage: platform linux, python 3.8.10-final-0 -----------
Name Stmts Miss Cover

merlin/datasets/init.py 2 0 100%
merlin/datasets/advertising/init.py 2 0 100%
merlin/datasets/advertising/criteo/init.py 0 0 100%
merlin/datasets/advertising/criteo/dataset.py 79 49 38%
merlin/datasets/advertising/criteo/transformed/init.py 0 0 100%
merlin/datasets/ecommerce/init.py 4 0 100%
merlin/datasets/ecommerce/aliccp/init.py 0 0 100%
merlin/datasets/ecommerce/aliccp/dataset.py 141 87 38%
merlin/datasets/ecommerce/aliccp/raw/init.py 0 0 100%
merlin/datasets/ecommerce/aliccp/transformed/init.py 0 0 100%
merlin/datasets/ecommerce/booking/init.py 0 0 100%
merlin/datasets/ecommerce/booking/dataset.py 127 100 21%
merlin/datasets/ecommerce/booking/raw/init.py 0 0 100%
merlin/datasets/ecommerce/booking/transformed/init.py 0 0 100%
merlin/datasets/ecommerce/dressipi/init.py 0 0 100%
merlin/datasets/ecommerce/dressipi/dataset.py 45 37 18%
merlin/datasets/ecommerce/dressipi/preprocessed/init.py 0 0 100%
merlin/datasets/ecommerce/large/init.py 0 0 100%
merlin/datasets/ecommerce/small/init.py 0 0 100%
merlin/datasets/ecommerce/transactions/init.py 0 0 100%
merlin/datasets/entertainment/init.py 2 0 100%
merlin/datasets/entertainment/movielens/1m-raw/init.py 0 0 100%
merlin/datasets/entertainment/movielens/1m-raw/ratings/init.py 0 0 100%
merlin/datasets/entertainment/movielens/1m/init.py 0 0 100%
merlin/datasets/entertainment/movielens/25m/init.py 0 0 100%
merlin/datasets/entertainment/movielens/100k/init.py 0 0 100%
merlin/datasets/entertainment/movielens/init.py 0 0 100%
merlin/datasets/entertainment/movielens/dataset.py 152 122 20%
merlin/datasets/entertainment/music_streaming/init.py 0 0 100%
merlin/datasets/social/init.py 0 0 100%
merlin/datasets/synthetic.py 147 8 95%
merlin/datasets/testing/init.py 0 0 100%
merlin/datasets/testing/sequence_testing/init.py 0 0 100%
merlin/models/init.py 2 0 100%
merlin/models/_version.py 354 205 42%
merlin/models/api.py 14 5 64%
merlin/models/config/init.py 0 0 100%
merlin/models/config/schema.py 62 0 100%
merlin/models/implicit/init.py 27 4 85%
merlin/models/io.py 15 0 100%
merlin/models/lightfm/init.py 23 0 100%
merlin/models/loader/init.py 0 0 100%
merlin/models/loader/backend.py 379 41 89%
merlin/models/loader/dataframe_iter.py 21 17 19%
merlin/models/loader/tf_utils.py 57 27 53%
merlin/models/loader/utils.py 40 15 62%
merlin/models/tf/init.py 70 0 100%
merlin/models/tf/blocks/init.py 0 0 100%
merlin/models/tf/blocks/cross.py 44 0 100%
merlin/models/tf/blocks/dlrm.py 49 2 96%
merlin/models/tf/blocks/experts.py 99 17 83%
merlin/models/tf/blocks/interaction.py 108 40 63%
merlin/models/tf/blocks/mlp.py 117 7 94%
merlin/models/tf/blocks/optimizer.py 173 12 93%
merlin/models/tf/blocks/retrieval/init.py 0 0 100%
merlin/models/tf/blocks/retrieval/base.py 169 62 63%
merlin/models/tf/blocks/retrieval/matrix_factorization.py 35 1 97%
merlin/models/tf/blocks/retrieval/two_tower.py 30 0 100%
merlin/models/tf/blocks/sampling/init.py 0 0 100%
merlin/models/tf/blocks/sampling/base.py 29 2 93%
merlin/models/tf/blocks/sampling/cross_batch.py 46 2 96%
merlin/models/tf/blocks/sampling/in_batch.py 35 0 100%
merlin/models/tf/blocks/sampling/queue.py 115 12 90%
merlin/models/tf/core/init.py 0 0 100%
merlin/models/tf/core/aggregation.py 241 45 81%
merlin/models/tf/core/base.py 244 50 80%
merlin/models/tf/core/combinators.py 426 53 88%
merlin/models/tf/core/encoder.py 175 28 84%
merlin/models/tf/core/index.py 104 16 85%
merlin/models/tf/core/prediction.py 50 1 98%
merlin/models/tf/core/tabular.py 280 29 90%
merlin/models/tf/distributed/init.py 0 0 100%
merlin/models/tf/distributed/backend.py 9 2 78%
merlin/models/tf/inputs/init.py 0 0 100%
merlin/models/tf/inputs/base.py 60 10 83%
merlin/models/tf/inputs/continuous.py 39 3 92%
merlin/models/tf/inputs/embedding.py 458 32 93%
merlin/models/tf/loader.py 268 94 65%
merlin/models/tf/losses/init.py 4 0 100%
merlin/models/tf/losses/base.py 9 0 100%
merlin/models/tf/losses/listwise.py 13 0 100%
merlin/models/tf/losses/pairwise.py 115 1 99%
merlin/models/tf/metrics/init.py 2 0 100%
merlin/models/tf/metrics/evaluation.py 105 48 54%
merlin/models/tf/metrics/topk.py 198 48 76%
merlin/models/tf/models/init.py 0 0 100%
merlin/models/tf/models/base.py 756 101 87%
merlin/models/tf/models/benchmark.py 16 0 100%
merlin/models/tf/models/ranking.py 67 3 96%
merlin/models/tf/models/retrieval.py 78 4 95%
merlin/models/tf/models/utils.py 10 1 90%
merlin/models/tf/outputs/init.py 0 0 100%
merlin/models/tf/outputs/base.py 123 17 86%
merlin/models/tf/outputs/classification.py 91 1 99%
merlin/models/tf/outputs/contrastive.py 147 10 93%
merlin/models/tf/outputs/regression.py 9 0 100%
merlin/models/tf/outputs/sampling/init.py 0 0 100%
merlin/models/tf/outputs/sampling/base.py 78 21 73%
merlin/models/tf/outputs/sampling/in_batch.py 37 1 97%
merlin/models/tf/outputs/sampling/popularity.py 27 1 96%
merlin/models/tf/outputs/topk.py 98 6 94%
merlin/models/tf/prediction_tasks/init.py 0 0 100%
merlin/models/tf/prediction_tasks/base.py 207 37 82%
merlin/models/tf/prediction_tasks/classification.py 68 17 75%
merlin/models/tf/prediction_tasks/multi.py 7 0 100%
merlin/models/tf/prediction_tasks/next_item.py 59 6 90%
merlin/models/tf/prediction_tasks/regression.py 35 2 94%
merlin/models/tf/prediction_tasks/retrieval.py 73 3 96%
merlin/models/tf/transformers/init.py 0 0 100%
merlin/models/tf/transformers/block.py 101 2 98%
merlin/models/tf/transformers/transforms.py 63 0 100%
merlin/models/tf/transforms/init.py 0 0 100%
merlin/models/tf/transforms/bias.py 111 9 92%
merlin/models/tf/transforms/features.py 435 36 92%
merlin/models/tf/transforms/negative_sampling.py 77 3 96%
merlin/models/tf/transforms/noise.py 43 1 98%
merlin/models/tf/transforms/regularization.py 17 1 94%
merlin/models/tf/transforms/sequence.py 282 42 85%
merlin/models/tf/transforms/tensor.py 158 13 92%
merlin/models/tf/typing.py 7 0 100%
merlin/models/tf/utils/init.py 0 0 100%
merlin/models/tf/utils/batch_utils.py 85 4 95%
merlin/models/tf/utils/repr_utils.py 69 4 94%
merlin/models/tf/utils/search_utils.py 34 22 35%
merlin/models/tf/utils/testing_utils.py 206 36 83%
merlin/models/tf/utils/tf_utils.py 209 42 80%
merlin/models/torch/init.py 12 0 100%
merlin/models/torch/block/init.py 0 0 100%
merlin/models/torch/block/base.py 167 32 81%
merlin/models/torch/block/mlp.py 38 5 87%
merlin/models/torch/dataset.py 68 5 93%
merlin/models/torch/features/init.py 0 0 100%
merlin/models/torch/features/base.py 4 0 100%
merlin/models/torch/features/continuous.py 22 0 100%
merlin/models/torch/features/embedding.py 165 12 93%
merlin/models/torch/features/tabular.py 65 8 88%
merlin/models/torch/losses.py 28 28 0%
merlin/models/torch/model/init.py 0 0 100%
merlin/models/torch/model/base.py 286 65 77%
merlin/models/torch/model/prediction_task.py 24 0 100%
merlin/models/torch/tabular/init.py 0 0 100%
merlin/models/torch/tabular/aggregation.py 75 0 100%
merlin/models/torch/tabular/base.py 247 39 84%
merlin/models/torch/tabular/transformations.py 67 3 96%
merlin/models/torch/typing.py 6 0 100%
merlin/models/torch/utils/init.py 0 0 100%
merlin/models/torch/utils/data_utils.py 117 117 0%
merlin/models/torch/utils/examples_utils.py 39 39 0%
merlin/models/torch/utils/torch_utils.py 80 22 72%
merlin/models/utils/init.py 0 0 100%
merlin/models/utils/constants.py 3 0 100%
merlin/models/utils/dataset.py 38 4 89%
merlin/models/utils/dependencies.py 26 19 27%
merlin/models/utils/doc_utils.py 10 0 100%
merlin/models/utils/example_utils.py 31 2 94%
merlin/models/utils/misc_utils.py 118 90 24%
merlin/models/utils/nvt_utils.py 27 24 11%
merlin/models/utils/registry.py 101 29 71%
merlin/models/utils/schema_utils.py 90 19 79%
merlin/models/xgb/init.py 124 4 97%

TOTAL 11575 2346 80%

=========================== short test summary info ============================
SKIPPED [1] tests/unit/datasets/test_advertising.py:20: No data-dir available, pass it through env variable $INPUT_DATA_DIR
SKIPPED [1] tests/unit/datasets/test_ecommerce.py:64: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP
SKIPPED [1] tests/unit/datasets/test_ecommerce.py:80: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP
SKIPPED [1] tests/unit/datasets/test_ecommerce.py:94: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP
SKIPPED [1] tests/unit/datasets/test_ecommerce.py:115: No data-dir available, pass it through env variable $INPUT_DATA_DIR
SKIPPED [3] tests/unit/datasets/test_entertainment.py:44: No data-dir available, pass it through env variable $INPUT_DATA_DIR
SKIPPED [5] ../../../.local/lib/python3.8/site-packages/tensorflow/python/framework/test_util.py:2746: Not a test.
========= 871 passed, 13 skipped, 1446 warnings in 1776.20s (0:29:36) ==========
___________________________________ summary ____________________________________
py38-gpu: commands succeeded
congratulations :)
Performing Post build task...
Match found for : : True
Logical operation result is TRUE
Running script : #!/bin/bash
cd /var/jenkins_home/
CUDA_VISIBLE_DEVICES=1 python test_res_push.py "https://api.GitHub.com/repos/NVIDIA-Merlin/models/issues/$ghprbPullId/comments" "/var/jenkins_home/jobs/$JOB_NAME/builds/$BUILD_NUMBER/log"
[merlin_models] $ /bin/bash /tmp/jenkins13676112627107191314.sh

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rerun tests

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GitHub pull request #855 of commit 7060fc72a6ca435c9eb2fd6a9d0c145a88d327d7, no merge conflicts.
Running as SYSTEM
Setting status of 7060fc72a6ca435c9eb2fd6a9d0c145a88d327d7 to PENDING with url http://merlin-infra1.nvidia.com:8080/job/merlin_models/1919/ and message: 'Pending'
Using context: Jenkins
Building on master in workspace /var/jenkins_home/workspace/merlin_models
using credential nvidia-merlin-bot
 > git rev-parse --is-inside-work-tree # timeout=10
Fetching changes from the remote Git repository
 > git config remote.origin.url https://github.com/NVIDIA-Merlin/models/ # timeout=10
Fetching upstream changes from https://github.com/NVIDIA-Merlin/models/
 > git --version # timeout=10
using GIT_ASKPASS to set credentials This is the bot credentials for our CI/CD
 > git fetch --tags --force --progress -- https://github.com/NVIDIA-Merlin/models/ +refs/pull/855/*:refs/remotes/origin/pr/855/* # timeout=10
 > git rev-parse 7060fc72a6ca435c9eb2fd6a9d0c145a88d327d7^{commit} # timeout=10
Checking out Revision 7060fc72a6ca435c9eb2fd6a9d0c145a88d327d7 (detached)
 > git config core.sparsecheckout # timeout=10
 > git checkout -f 7060fc72a6ca435c9eb2fd6a9d0c145a88d327d7 # timeout=10
Commit message: "Merge branch 'main' into multi-gpu-data-parallel"
 > git rev-list --no-walk 7d243a8de53496f6af49605d3b1bf1b8d5730b00 # timeout=10
[merlin_models] $ /bin/bash /tmp/jenkins13046411143514271898.sh
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Requirement already satisfied: testbook in /usr/local/lib/python3.8/dist-packages (0.4.2)
Requirement already satisfied: nbclient>=0.4.0 in /usr/local/lib/python3.8/dist-packages (from testbook) (0.6.8)
Requirement already satisfied: nbformat>=5.0.4 in /usr/local/lib/python3.8/dist-packages (from testbook) (5.5.0)
Requirement already satisfied: nest-asyncio in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (1.5.5)
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Requirement already satisfied: zipp>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from importlib-resources>=1.4.0->jsonschema>=2.6->nbformat>=5.0.4->testbook) (3.8.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.8.2->jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (1.15.0)
GLOB sdist-make: /var/jenkins_home/workspace/merlin_models/models/setup.py
py38-gpu recreate: /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
py38-gpu installdeps: -rrequirements/dev.txt, tensorflow<2.10
WARNING: Discarding $PYTHONPATH from environment, to override specify PYTHONPATH in 'passenv' in your configuration.
py38-gpu inst: /var/jenkins_home/workspace/merlin_models/models/.tox/.tmp/package/4/merlin-models-0.9.0+62.g7060fc72.zip
WARNING: Discarding $PYTHONPATH from environment, to override specify PYTHONPATH in 'passenv' in your configuration.
py38-gpu installed: absl-py==1.2.0,aiohttp==3.8.1,aiosignal==1.2.0,alabaster==0.7.12,alembic==1.8.1,anyio==3.6.1,appdirs==1.4.4,argon2-cffi==21.3.0,argon2-cffi-bindings==21.2.0,astroid==2.5.6,asttokens==2.0.8,astunparse==1.6.3,asv==0.5.1,asvdb==0.4.2,async-timeout==4.0.2,attrs==22.1.0,autopage==0.5.1,awscli==1.27.14,Babel==2.10.3,backcall==0.2.0,beautifulsoup4==4.11.1,betterproto==1.2.5,black==20.8b1,bleach==5.0.1,bokeh==3.0.2,boto3==1.24.75,botocore==1.29.14,Brotli==1.0.9,build==0.9.0,cachetools==5.2.0,certifi==2019.11.28,cffi==1.15.1,chardet==3.0.4,charset-normalizer==2.1.1,check-manifest==0.48,clang==5.0,click==8.1.3,cliff==4.1.0,cloudpickle==2.2.0,cmaes==0.9.0,cmake==3.24.1.1,cmd2==2.4.2,colorama==0.4.4,colorlog==6.7.0,contourpy==1.0.5,coverage==6.5.0,cuda-python==11.7.1,cupy-cuda117==10.6.0,cycler==0.11.0,Cython==0.29.32,dask==2022.1.1,dbus-python==1.2.16,debugpy==1.6.3,decorator==5.1.1,defusedxml==0.7.1,dill==0.3.5.1,distlib==0.3.6,distributed==2022.5.1,distro==1.7.0,dm-tree==0.1.6,docker-pycreds==0.4.0,docutils==0.16,emoji==1.7.0,entrypoints==0.4,execnet==1.9.0,executing==1.0.0,faiss==1.7.2,faiss-gpu==1.7.2,fastai==2.7.9,fastapi==0.85.0,fastavro==1.6.1,fastcore==1.5.27,fastdownload==0.0.7,fastjsonschema==2.16.1,fastprogress==1.0.3,fastrlock==0.8,feast==0.19.4,fiddle==0.2.2,filelock==3.8.0,flake8==5.0.4,flatbuffers==1.12,fonttools==4.37.3,frozenlist==1.3.1,fsspec==2022.5.0,gast==0.4.0,gevent==21.12.0,geventhttpclient==2.0.2,gitdb==4.0.9,GitPython==3.1.27,google==3.0.0,google-api-core==2.10.1,google-auth==2.11.1,google-auth-oauthlib==0.4.6,google-pasta==0.2.0,googleapis-common-protos==1.52.0,graphviz==0.20.1,greenlet==1.1.3,grpcio==1.41.0,grpcio-channelz==1.49.0,grpcio-reflection==1.48.1,grpclib==0.4.3,h11==0.13.0,h2==4.1.0,h5py==3.7.0,HeapDict==1.0.1,horovod==0.26.1,hpack==4.0.0,httptools==0.5.0,hugectr2onnx==0.0.0,huggingface-hub==0.9.1,hyperframe==6.0.1,idna==2.8,imagesize==1.4.1,implicit==0.6.1,importlib-metadata==4.12.0,importlib-resources==5.9.0,iniconfig==1.1.1,interrogate==1.5.0,ipykernel==6.15.3,ipython==8.5.0,ipython-genutils==0.2.0,ipywidgets==7.7.0,isort==5.10.1,jedi==0.18.1,Jinja2==3.1.2,jmespath==1.0.1,joblib==1.2.0,json5==0.9.10,jsonschema==4.16.0,jupyter==1.0.0,jupyter-cache==0.4.3,jupyter-console==6.4.4,jupyter-core==4.11.1,jupyter-server==1.18.1,jupyter-server-mathjax==0.2.5,jupyter-sphinx==0.3.2,jupyter_client==7.3.5,jupyterlab==3.4.7,jupyterlab-pygments==0.2.2,jupyterlab-widgets==1.1.0,jupyterlab_server==2.15.1,keras==2.9.0,Keras-Preprocessing==1.1.2,kiwisolver==1.4.4,lazy-object-proxy==1.8.0,libclang==14.0.6,libcst==0.4.7,lightfm==1.16,lightgbm==3.3.2,linkify-it-py==1.0.3,llvmlite==0.39.1,locket==1.0.0,lxml==4.9.1,Mako==1.2.4,Markdown==3.4.1,markdown-it-py==1.1.0,MarkupSafe==2.1.1,matplotlib==3.6.0,matplotlib-inline==0.1.6,mccabe==0.7.0,mdit-py-plugins==0.2.8,merlin-core==0.6.0+1.g5926fcf,merlin-models==0.9.0+62.g7060fc72,merlin-systems==0.5.0+4.g15074ad,mistune==2.0.4,mmh3==3.0.0,mpi4py==3.1.3,msgpack==1.0.4,multidict==6.0.2,mypy==0.991,mypy-extensions==0.4.3,myst-nb==0.13.2,myst-parser==0.15.2,natsort==8.1.0,nbclassic==0.4.3,nbclient==0.6.8,nbconvert==7.0.0,nbdime==3.1.1,nbformat==5.5.0,nest-asyncio==1.5.5,ninja==1.10.2.3,notebook==6.4.12,notebook-shim==0.1.0,numba==0.56.2,numpy==1.22.4,nvidia-pyindex==1.0.9,# Editable install with no version control (nvtabular==1.4.0+8.g95e12d347),-e /usr/local/lib/python3.8/dist-packages,nvtx==0.2.5,oauthlib==3.2.1,oldest-supported-numpy==2022.8.16,onnx==1.12.0,onnxruntime==1.11.1,opt-einsum==3.3.0,optuna==3.0.3,packaging==21.3,pandas==1.3.5,pandavro==1.5.2,pandocfilters==1.5.0,parso==0.8.3,partd==1.3.0,pathspec==0.10.2,pathtools==0.1.2,pbr==5.11.0,pep517==0.13.0,pexpect==4.8.0,pickleshare==0.7.5,Pillow==9.2.0,pkgutil_resolve_name==1.3.10,platformdirs==2.5.2,plotly==5.11.0,pluggy==1.0.0,prettytable==3.5.0,prometheus-client==0.14.1,promise==2.3,prompt-toolkit==3.0.31,proto-plus==1.19.6,protobuf==3.19.5,psutil==5.9.2,ptyprocess==0.7.0,pure-eval==0.2.2,py==1.11.0,pyarrow==7.0.0,pyasn1==0.4.8,pyasn1-modules==0.2.8,pybind11==2.10.0,pycodestyle==2.9.1,pycparser==2.21,pydantic==1.10.2,pydot==1.4.2,pyflakes==2.5.0,Pygments==2.13.0,PyGObject==3.36.0,pynvml==11.4.1,pyparsing==3.0.9,pyperclip==1.8.2,pyrsistent==0.18.1,pytest==7.1.3,pytest-cov==4.0.0,pytest-xdist==3.0.2,python-apt==2.0.0+ubuntu0.20.4.8,python-dateutil==2.8.2,python-dotenv==0.21.0,python-rapidjson==1.8,pytz==2022.2.1,PyYAML==5.4.1,pyzmq==24.0.0,qtconsole==5.4.0,QtPy==2.3.0,regex==2022.9.13,requests==2.22.0,requests-oauthlib==1.3.1,requests-unixsocket==0.2.0,rsa==4.7.2,s3fs==2022.2.0,s3transfer==0.6.0,sacremoses==0.0.53,scikit-build==0.15.0,scikit-learn==1.1.2,scipy==1.8.1,seedir==0.3.0,Send2Trash==1.8.0,sentry-sdk==1.9.8,setproctitle==1.3.2,setuptools-scm==7.0.5,shortuuid==1.0.9,six==1.15.0,sklearn==0.0,smmap==5.0.0,sniffio==1.3.0,snowballstemmer==2.2.0,sortedcontainers==2.4.0,soupsieve==2.3.2.post1,Sphinx==5.3.0,sphinx-multiversion==0.2.4,sphinx-togglebutton==0.3.1,sphinx_external_toc==0.3.0,sphinxcontrib-applehelp==1.0.2,sphinxcontrib-copydirs @ git+https://github.com/mikemckiernan/sphinxcontrib-copydirs.git@bd8c5d79b3f91cf5f1bb0d6995aeca3fe84b670e,sphinxcontrib-devhelp==1.0.2,sphinxcontrib-htmlhelp==2.0.0,sphinxcontrib-jsmath==1.0.1,sphinxcontrib-qthelp==1.0.3,sphinxcontrib-serializinghtml==1.1.5,SQLAlchemy==1.4.44,stack-data==0.5.0,starlette==0.20.4,stevedore==4.1.1,stringcase==1.2.0,supervisor==4.1.0,tabulate==0.8.10,tblib==1.7.0,tdqm==0.0.1,tenacity==8.0.1,tensorboard==2.9.1,tensorboard-data-server==0.6.1,tensorboard-plugin-wit==1.8.1,tensorflow==2.9.2,tensorflow-estimator==2.9.0,tensorflow-gpu==2.9.2,tensorflow-io-gcs-filesystem==0.27.0,tensorflow-metadata==1.10.0,termcolor==2.0.1,terminado==0.15.0,testbook==0.4.2,threadpoolctl==3.1.0,tinycss2==1.1.1,tokenizers==0.10.3,toml==0.10.2,tomli==2.0.1,toolz==0.12.0,torch==1.12.1+cu113,torchmetrics==0.3.2,tornado==6.2,tox==3.26.0,tqdm==4.64.1,traitlets==5.4.0,transformers==4.12.0,transformers4rec==0.1.12+2.gbcc939255,treelite==2.3.0,treelite-runtime==2.3.0,tritonclient==2.25.0,typed-ast==1.5.4,typing-inspect==0.8.0,typing_extensions==4.3.0,uc-micro-py==1.0.1,urllib3==1.26.12,uvicorn==0.18.3,uvloop==0.17.0,versioneer==0.20,virtualenv==20.16.5,wandb==0.13.3,watchfiles==0.17.0,wcwidth==0.2.5,webencodings==0.5.1,websocket-client==1.4.1,websockets==10.3,Werkzeug==2.2.2,widgetsnbextension==3.6.0,wrapt==1.12.1,xgboost==1.6.2,xyzservices==2022.9.0,yarl==1.8.1,zict==2.2.0,zipp==3.8.1,zope.event==4.5.0,zope.interface==5.4.0
py38-gpu run-test-pre: PYTHONHASHSEED='2241316882'
py38-gpu run-test: commands[0] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/core.git
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Collecting git+https://github.com/NVIDIA-Merlin/core.git
  Cloning https://github.com/NVIDIA-Merlin/core.git to /tmp/pip-req-build-bw5r8v4x
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/core.git /tmp/pip-req-build-bw5r8v4x
  Resolved https://github.com/NVIDIA-Merlin/core.git to commit 04ff5225cee6af90b6b08070493677ac53b96836
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: fsspec==2022.5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+16.g04ff522) (2022.5.0)
Requirement already satisfied: pandas<1.4.0dev0,>=1.2.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+16.g04ff522) (1.3.5)
Requirement already satisfied: protobuf>=3.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+16.g04ff522) (3.19.5)
Requirement already satisfied: tqdm>=4.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+16.g04ff522) (4.64.1)
Requirement already satisfied: dask>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+16.g04ff522) (2022.3.0)
Requirement already satisfied: packaging in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+16.g04ff522) (21.3)
Requirement already satisfied: distributed>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+16.g04ff522) (2022.3.0)
Requirement already satisfied: numba>=0.54 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+16.g04ff522) (0.55.1)
Requirement already satisfied: tensorflow-metadata>=1.2.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+16.g04ff522) (1.10.0)
Requirement already satisfied: betterproto<2.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+16.g04ff522) (1.2.5)
Requirement already satisfied: pyarrow>=5.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+16.g04ff522) (7.0.0)
Requirement already satisfied: stringcase in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core==0.8.0+16.g04ff522) (1.2.0)
Requirement already satisfied: grpclib in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core==0.8.0+16.g04ff522) (0.4.3)
Requirement already satisfied: pyyaml>=5.3.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/PyYAML-5.4.1-py3.8-linux-x86_64.egg (from dask>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (5.4.1)
Requirement already satisfied: toolz>=0.8.2 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (0.12.0)
Requirement already satisfied: partd>=0.3.10 in /var/jenkins_home/.local/lib/python3.8/site-packages/partd-1.2.0-py3.8.egg (from dask>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (1.2.0)
Requirement already satisfied: cloudpickle>=1.1.1 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (2.2.0)
Requirement already satisfied: tblib>=1.6.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/tblib-1.7.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (1.7.0)
Requirement already satisfied: sortedcontainers!=2.0.0,!=2.0.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/sortedcontainers-2.4.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (2.4.0)
Requirement already satisfied: msgpack>=0.6.0 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (1.0.4)
Requirement already satisfied: tornado>=6.0.3 in ./.tox/py38-gpu/lib/python3.8/site-packages (from distributed>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (6.2)
Requirement already satisfied: psutil>=5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/psutil-5.8.0-py3.8-linux-x86_64.egg (from distributed>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (5.8.0)
Requirement already satisfied: jinja2 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (3.1.2)
Requirement already satisfied: zict>=0.1.3 in /var/jenkins_home/.local/lib/python3.8/site-packages/zict-2.0.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (2.0.0)
Requirement already satisfied: click>=6.6 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (8.1.3)
Requirement already satisfied: setuptools in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+16.g04ff522) (65.5.1)
Requirement already satisfied: numpy<1.22,>=1.18 in /var/jenkins_home/.local/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+16.g04ff522) (1.20.3)
Requirement already satisfied: llvmlite<0.39,>=0.38.0rc1 in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+16.g04ff522) (0.38.1)
Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in /usr/local/lib/python3.8/dist-packages (from packaging->merlin-core==0.8.0+16.g04ff522) (3.0.9)
Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+16.g04ff522) (2.8.2)
Requirement already satisfied: pytz>=2017.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+16.g04ff522) (2022.2.1)
Requirement already satisfied: absl-py<2.0.0,>=0.9 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core==0.8.0+16.g04ff522) (1.2.0)
Requirement already satisfied: googleapis-common-protos<2,>=1.52.0 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core==0.8.0+16.g04ff522) (1.52.0)
Requirement already satisfied: locket in /var/jenkins_home/.local/lib/python3.8/site-packages/locket-0.2.1-py3.8.egg (from partd>=0.3.10->dask>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (0.2.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.7.3->pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+16.g04ff522) (1.15.0)
Requirement already satisfied: heapdict in /var/jenkins_home/.local/lib/python3.8/site-packages/HeapDict-1.0.1-py3.8.egg (from zict>=0.1.3->distributed>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (1.0.1)
Requirement already satisfied: h2<5,>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core==0.8.0+16.g04ff522) (4.1.0)
Requirement already satisfied: multidict in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core==0.8.0+16.g04ff522) (6.0.2)
Requirement already satisfied: MarkupSafe>=2.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from jinja2->distributed>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (2.0.1)
Requirement already satisfied: hpack<5,>=4.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core==0.8.0+16.g04ff522) (4.0.0)
Requirement already satisfied: hyperframe<7,>=6.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core==0.8.0+16.g04ff522) (6.0.1)
Building wheels for collected packages: merlin-core
  Building wheel for merlin-core (pyproject.toml): started
  Building wheel for merlin-core (pyproject.toml): finished with status 'done'
  Created wheel for merlin-core: filename=merlin_core-0.8.0+16.g04ff522-py3-none-any.whl size=118833 sha256=b22f1f9dc263393d9479dc579a41299fec047312781dcde85b9d54926d704202
  Stored in directory: /tmp/pip-ephem-wheel-cache-sovqzes0/wheels/c8/38/16/a6968787eafcec5fa772148af8408b089562f71af0752e8e84
Successfully built merlin-core
Installing collected packages: merlin-core
  Attempting uninstall: merlin-core
    Found existing installation: merlin-core 0.3.0+12.g78ecddd
    Not uninstalling merlin-core at /var/jenkins_home/.local/lib/python3.8/site-packages, outside environment /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
    Can't uninstall 'merlin-core'. No files were found to uninstall.
Successfully installed merlin-core-0.8.0+16.g04ff522
py38-gpu run-test: commands[1] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/nvtabular.git
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Collecting git+https://github.com/NVIDIA-Merlin/nvtabular.git
  Cloning https://github.com/NVIDIA-Merlin/nvtabular.git to /tmp/pip-req-build-qcb87la2
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/nvtabular.git /tmp/pip-req-build-qcb87la2
  Resolved https://github.com/NVIDIA-Merlin/nvtabular.git to commit e5b7351deb9e4885c4038aa0bbc9f146d8477a0e
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: merlin-core>=0.2.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from nvtabular==1.6.0+6.ge5b7351d) (0.8.0+16.g04ff522)
Requirement already satisfied: scipy in /usr/local/lib/python3.8/dist-packages (from nvtabular==1.6.0+6.ge5b7351d) (1.8.1)
Collecting merlin-dataloader>=0.0.2
  Downloading merlin-dataloader-0.0.2.tar.gz (44 kB)
     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 44.1/44.1 kB 1.6 MB/s eta 0:00:00
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
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Building wheels for collected packages: nvtabular, merlin-dataloader
  Building wheel for nvtabular (pyproject.toml): started
  Building wheel for nvtabular (pyproject.toml): finished with status 'done'
  Created wheel for nvtabular: filename=nvtabular-1.6.0+6.ge5b7351d-cp38-cp38-linux_x86_64.whl size=257597 sha256=b94594b12dc25c85bcd69fb5940b977dffab168f5c6f1508fe6302a3ed1c5b7d
  Stored in directory: /tmp/pip-ephem-wheel-cache-tydqh1vt/wheels/8f/d9/f9/30f2cdc5bf8787fae6fdfe55afd6e1b493e619ec32c32ec40b
  Building wheel for merlin-dataloader (pyproject.toml): started
  Building wheel for merlin-dataloader (pyproject.toml): finished with status 'done'
  Created wheel for merlin-dataloader: filename=merlin_dataloader-0.0.2-py3-none-any.whl size=29203 sha256=3eca694ca80df818421bc3b9e6efce4c31aebe53e79eca69c47b7ad973cf4a80
  Stored in directory: /tmp/pip-ephem-wheel-cache-tydqh1vt/wheels/76/ef/ed/cb880e3ef5192ec5940e26fd9442247b569fb0cf8602f97137
Successfully built nvtabular merlin-dataloader
Installing collected packages: merlin-dataloader, nvtabular
  Attempting uninstall: nvtabular
    Found existing installation: nvtabular 1.1.1
    Not uninstalling nvtabular at /var/jenkins_home/.local/lib/python3.8/site-packages, outside environment /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
    Can't uninstall 'nvtabular'. No files were found to uninstall.
Successfully installed merlin-dataloader-0.0.2 nvtabular-1.6.0+6.ge5b7351d
py38-gpu run-test: commands[2] | python -m pytest --cov-report term --cov merlin -rxs tests/unit
============================= test session starts ==============================
platform linux -- Python 3.8.10, pytest-7.1.3, pluggy-1.0.0
cachedir: .tox/py38-gpu/.pytest_cache
rootdir: /var/jenkins_home/workspace/merlin_models/models, configfile: pyproject.toml
plugins: anyio-3.5.0, xdist-3.0.2, cov-4.0.0
collected 884 items

tests/unit/config/test_schema.py .... [ 0%]
tests/unit/datasets/test_advertising.py .s [ 0%]
tests/unit/datasets/test_ecommerce.py ..sss.s [ 1%]
tests/unit/datasets/test_entertainment.py ....sss. [ 2%]
tests/unit/datasets/test_social.py . [ 2%]
tests/unit/datasets/test_synthetic.py .......... [ 3%]
tests/unit/implicit/test_implicit.py . [ 3%]
tests/unit/lightfm/test_lightfm.py . [ 3%]
tests/unit/tf/test_core.py ...... [ 4%]
tests/unit/tf/test_loader.py ................ [ 6%]
tests/unit/tf/test_public_api.py . [ 6%]
tests/unit/tf/blocks/test_cross.py ........... [ 7%]
tests/unit/tf/blocks/test_dlrm.py .......... [ 8%]
tests/unit/tf/blocks/test_interactions.py ... [ 9%]
tests/unit/tf/blocks/test_mlp.py ....................................... [ 13%]
............................ [ 16%]
tests/unit/tf/blocks/test_optimizer.py s................................ [ 20%]
..................... [ 22%]
tests/unit/tf/blocks/retrieval/test_base.py . [ 22%]
tests/unit/tf/blocks/retrieval/test_matrix_factorization.py .. [ 23%]
tests/unit/tf/blocks/retrieval/test_two_tower.py ............ [ 24%]
tests/unit/tf/blocks/sampling/test_cross_batch.py . [ 24%]
tests/unit/tf/blocks/sampling/test_in_batch.py . [ 24%]
tests/unit/tf/core/test_aggregation.py ......... [ 25%]
tests/unit/tf/core/test_base.py .. [ 26%]
tests/unit/tf/core/test_combinators.py s..................... [ 28%]
tests/unit/tf/core/test_encoder.py .. [ 28%]
tests/unit/tf/core/test_index.py ... [ 29%]
tests/unit/tf/core/test_prediction.py .. [ 29%]
tests/unit/tf/core/test_tabular.py ...... [ 29%]
tests/unit/tf/examples/test_01_getting_started.py . [ 30%]
tests/unit/tf/examples/test_02_dataschema.py . [ 30%]
tests/unit/tf/examples/test_03_exploring_different_models.py . [ 30%]
tests/unit/tf/examples/test_04_export_ranking_models.py . [ 30%]
tests/unit/tf/examples/test_05_export_retrieval_model.py . [ 30%]
tests/unit/tf/examples/test_06_advanced_own_architecture.py . [ 30%]
tests/unit/tf/examples/test_07_train_traditional_models.py . [ 30%]
tests/unit/tf/examples/test_usecase_accelerate_training_by_lazyadam.py . [ 30%]
[ 30%]
tests/unit/tf/examples/test_usecase_data_parallel.py . [ 30%]
tests/unit/tf/examples/test_usecase_ecommerce_session_based.py . [ 31%]
tests/unit/tf/examples/test_usecase_incremental_training_layer_freezing.py . [ 31%]
[ 31%]
tests/unit/tf/examples/test_usecase_pretrained_embeddings.py . [ 31%]
tests/unit/tf/examples/test_usecase_retrieval_with_hpo.py . [ 31%]
tests/unit/tf/examples/test_usecase_transformers_next_item_prediction.py . [ 31%]
[ 31%]
tests/unit/tf/horovod/test_horovod.py ... [ 31%]
tests/unit/tf/inputs/test_base.py . [ 32%]
tests/unit/tf/inputs/test_continuous.py ........ [ 32%]
tests/unit/tf/inputs/test_embedding.py ................................. [ 36%]
........ [ 37%]
tests/unit/tf/inputs/test_tabular.py .................. [ 39%]
tests/unit/tf/layers/test_queue.py .............. [ 41%]
tests/unit/tf/losses/test_losses.py ....................... [ 43%]
tests/unit/tf/metrics/test_metrics_popularity.py ..... [ 44%]
tests/unit/tf/metrics/test_metrics_topk.py ......................... [ 47%]
tests/unit/tf/models/test_base.py s......................... [ 50%]
tests/unit/tf/models/test_benchmark.py .. [ 50%]
tests/unit/tf/models/test_ranking.py .................................. [ 54%]
tests/unit/tf/models/test_retrieval.py ................................. [ 57%]
........................................... [ 62%]
tests/unit/tf/outputs/test_base.py ...... [ 63%]
tests/unit/tf/outputs/test_classification.py ...... [ 64%]
tests/unit/tf/outputs/test_contrastive.py .............. [ 65%]
tests/unit/tf/outputs/test_regression.py .. [ 65%]
tests/unit/tf/outputs/test_sampling.py .... [ 66%]
tests/unit/tf/outputs/test_topk.py . [ 66%]
tests/unit/tf/prediction_tasks/test_classification.py .. [ 66%]
tests/unit/tf/prediction_tasks/test_multi_task.py ................ [ 68%]
tests/unit/tf/prediction_tasks/test_next_item.py ..... [ 69%]
tests/unit/tf/prediction_tasks/test_regression.py ..... [ 69%]
tests/unit/tf/prediction_tasks/test_retrieval.py . [ 69%]
tests/unit/tf/prediction_tasks/test_sampling.py ...... [ 70%]
tests/unit/tf/transformers/test_block.py ...................... [ 72%]
tests/unit/tf/transformers/test_transforms.py .......... [ 74%]
tests/unit/tf/transforms/test_bias.py .. [ 74%]
tests/unit/tf/transforms/test_features.py s............................. [ 77%]
.......................s...... [ 81%]
tests/unit/tf/transforms/test_negative_sampling.py ......... [ 82%]
tests/unit/tf/transforms/test_noise.py ..... [ 82%]
tests/unit/tf/transforms/test_sequence.py .................... [ 84%]
tests/unit/tf/transforms/test_tensor.py ... [ 85%]
tests/unit/tf/utils/test_batch.py .... [ 85%]
tests/unit/tf/utils/test_dataset.py .. [ 85%]
tests/unit/tf/utils/test_tf_utils.py ..... [ 86%]
tests/unit/torch/test_dataset.py ......... [ 87%]
tests/unit/torch/test_public_api.py . [ 87%]
tests/unit/torch/block/test_base.py .... [ 88%]
tests/unit/torch/block/test_mlp.py . [ 88%]
tests/unit/torch/features/test_continuous.py .. [ 88%]
tests/unit/torch/features/test_embedding.py .............. [ 90%]
tests/unit/torch/features/test_tabular.py .... [ 90%]
tests/unit/torch/model/test_head.py ............ [ 91%]
tests/unit/torch/model/test_model.py .. [ 92%]
tests/unit/torch/tabular/test_aggregation.py ........ [ 92%]
tests/unit/torch/tabular/test_tabular.py ... [ 93%]
tests/unit/torch/tabular/test_transformations.py ....... [ 94%]
tests/unit/utils/test_schema_utils.py ................................ [ 97%]
tests/unit/xgb/test_xgboost.py .................... [100%]

=============================== warnings summary ===============================
../../../../../usr/lib/python3/dist-packages/requests/init.py:89
/usr/lib/python3/dist-packages/requests/init.py:89: RequestsDependencyWarning: urllib3 (1.26.12) or chardet (3.0.4) doesn't match a supported version!
warnings.warn("urllib3 ({}) or chardet ({}) doesn't match a supported "

../../../.local/lib/python3.8/site-packages/flatbuffers/compat.py:19
/var/jenkins_home/.local/lib/python3.8/site-packages/flatbuffers/compat.py:19: DeprecationWarning: the imp module is deprecated in favour of importlib; see the module's documentation for alternative uses
import imp

../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36
/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36: DeprecationWarning: NEAREST is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.NEAREST or Dither.NONE instead.
'nearest': pil_image.NEAREST,

../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37
/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37: DeprecationWarning: BILINEAR is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BILINEAR instead.
'bilinear': pil_image.BILINEAR,

../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38
/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38: DeprecationWarning: BICUBIC is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BICUBIC instead.
'bicubic': pil_image.BICUBIC,

../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39
/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39: DeprecationWarning: HAMMING is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.HAMMING instead.
'hamming': pil_image.HAMMING,

../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40
/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40: DeprecationWarning: BOX is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BOX instead.
'box': pil_image.BOX,

../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41
/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41: DeprecationWarning: LANCZOS is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.LANCZOS instead.
'lanczos': pil_image.LANCZOS,

tests/unit/datasets/test_advertising.py: 1 warning
tests/unit/datasets/test_ecommerce.py: 3 warnings
tests/unit/datasets/test_entertainment.py: 4 warnings
tests/unit/datasets/test_social.py: 1 warning
tests/unit/datasets/test_synthetic.py: 10 warnings
tests/unit/implicit/test_implicit.py: 1 warning
tests/unit/lightfm/test_lightfm.py: 1 warning
tests/unit/tf/test_core.py: 6 warnings
tests/unit/tf/test_loader.py: 1 warning
tests/unit/tf/blocks/test_cross.py: 5 warnings
tests/unit/tf/blocks/test_dlrm.py: 9 warnings
tests/unit/tf/blocks/test_interactions.py: 2 warnings
tests/unit/tf/blocks/test_mlp.py: 60 warnings
tests/unit/tf/blocks/test_optimizer.py: 30 warnings
tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings
tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings
tests/unit/tf/core/test_aggregation.py: 6 warnings
tests/unit/tf/core/test_base.py: 2 warnings
tests/unit/tf/core/test_combinators.py: 11 warnings
tests/unit/tf/core/test_encoder.py: 6 warnings
tests/unit/tf/core/test_index.py: 8 warnings
tests/unit/tf/core/test_prediction.py: 2 warnings
tests/unit/tf/horovod/test_horovod.py: 3 warnings
tests/unit/tf/inputs/test_base.py: 1 warning
tests/unit/tf/inputs/test_continuous.py: 7 warnings
tests/unit/tf/inputs/test_embedding.py: 20 warnings
tests/unit/tf/inputs/test_tabular.py: 18 warnings
tests/unit/tf/models/test_base.py: 28 warnings
tests/unit/tf/models/test_benchmark.py: 2 warnings
tests/unit/tf/models/test_ranking.py: 38 warnings
tests/unit/tf/models/test_retrieval.py: 121 warnings
tests/unit/tf/outputs/test_base.py: 6 warnings
tests/unit/tf/outputs/test_classification.py: 6 warnings
tests/unit/tf/outputs/test_contrastive.py: 19 warnings
tests/unit/tf/outputs/test_regression.py: 2 warnings
tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings
tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings
tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings
tests/unit/tf/prediction_tasks/test_retrieval.py: 1 warning
tests/unit/tf/transformers/test_block.py: 16 warnings
tests/unit/tf/transforms/test_bias.py: 2 warnings
tests/unit/tf/transforms/test_features.py: 10 warnings
tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings
tests/unit/tf/transforms/test_noise.py: 1 warning
tests/unit/tf/transforms/test_sequence.py: 15 warnings
tests/unit/tf/utils/test_batch.py: 9 warnings
tests/unit/tf/utils/test_dataset.py: 2 warnings
tests/unit/torch/block/test_base.py: 4 warnings
tests/unit/torch/block/test_mlp.py: 1 warning
tests/unit/torch/features/test_continuous.py: 1 warning
tests/unit/torch/features/test_embedding.py: 4 warnings
tests/unit/torch/features/test_tabular.py: 4 warnings
tests/unit/torch/model/test_head.py: 12 warnings
tests/unit/torch/model/test_model.py: 2 warnings
tests/unit/torch/tabular/test_aggregation.py: 6 warnings
tests/unit/torch/tabular/test_transformations.py: 3 warnings
tests/unit/xgb/test_xgboost.py: 18 warnings
/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.ITEM_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.ITEM: 'item'>, <Tags.ID: 'id'>].
warnings.warn(

tests/unit/datasets/test_ecommerce.py: 3 warnings
tests/unit/datasets/test_entertainment.py: 4 warnings
tests/unit/datasets/test_social.py: 1 warning
tests/unit/datasets/test_synthetic.py: 9 warnings
tests/unit/implicit/test_implicit.py: 1 warning
tests/unit/lightfm/test_lightfm.py: 1 warning
tests/unit/tf/test_core.py: 6 warnings
tests/unit/tf/test_loader.py: 1 warning
tests/unit/tf/blocks/test_cross.py: 5 warnings
tests/unit/tf/blocks/test_dlrm.py: 9 warnings
tests/unit/tf/blocks/test_interactions.py: 2 warnings
tests/unit/tf/blocks/test_mlp.py: 60 warnings
tests/unit/tf/blocks/test_optimizer.py: 30 warnings
tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings
tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings
tests/unit/tf/core/test_aggregation.py: 6 warnings
tests/unit/tf/core/test_base.py: 2 warnings
tests/unit/tf/core/test_combinators.py: 11 warnings
tests/unit/tf/core/test_encoder.py: 7 warnings
tests/unit/tf/core/test_index.py: 3 warnings
tests/unit/tf/core/test_prediction.py: 2 warnings
tests/unit/tf/horovod/test_horovod.py: 1 warning
tests/unit/tf/inputs/test_base.py: 1 warning
tests/unit/tf/inputs/test_continuous.py: 7 warnings
tests/unit/tf/inputs/test_embedding.py: 20 warnings
tests/unit/tf/inputs/test_tabular.py: 18 warnings
tests/unit/tf/models/test_base.py: 28 warnings
tests/unit/tf/models/test_benchmark.py: 2 warnings
tests/unit/tf/models/test_ranking.py: 36 warnings
tests/unit/tf/models/test_retrieval.py: 87 warnings
tests/unit/tf/outputs/test_base.py: 6 warnings
tests/unit/tf/outputs/test_classification.py: 6 warnings
tests/unit/tf/outputs/test_contrastive.py: 19 warnings
tests/unit/tf/outputs/test_regression.py: 2 warnings
tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings
tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings
tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings
tests/unit/tf/transformers/test_block.py: 10 warnings
tests/unit/tf/transforms/test_features.py: 10 warnings
tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings
tests/unit/tf/transforms/test_sequence.py: 15 warnings
tests/unit/tf/utils/test_batch.py: 7 warnings
tests/unit/tf/utils/test_dataset.py: 2 warnings
tests/unit/torch/block/test_base.py: 4 warnings
tests/unit/torch/block/test_mlp.py: 1 warning
tests/unit/torch/features/test_continuous.py: 1 warning
tests/unit/torch/features/test_embedding.py: 4 warnings
tests/unit/torch/features/test_tabular.py: 4 warnings
tests/unit/torch/model/test_head.py: 12 warnings
tests/unit/torch/model/test_model.py: 2 warnings
tests/unit/torch/tabular/test_aggregation.py: 6 warnings
tests/unit/torch/tabular/test_transformations.py: 2 warnings
tests/unit/xgb/test_xgboost.py: 17 warnings
/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.USER_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.USER: 'user'>, <Tags.ID: 'id'>].
warnings.warn(

tests/unit/datasets/test_ecommerce.py: 1 warning
tests/unit/datasets/test_entertainment.py: 1 warning
tests/unit/implicit/test_implicit.py: 1 warning
tests/unit/lightfm/test_lightfm.py: 1 warning
tests/unit/tf/test_loader.py: 1 warning
tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings
tests/unit/tf/blocks/retrieval/test_two_tower.py: 2 warnings
tests/unit/tf/core/test_combinators.py: 11 warnings
tests/unit/tf/core/test_encoder.py: 2 warnings
tests/unit/tf/core/test_prediction.py: 1 warning
tests/unit/tf/horovod/test_horovod.py: 1 warning
tests/unit/tf/inputs/test_continuous.py: 4 warnings
tests/unit/tf/inputs/test_embedding.py: 9 warnings
tests/unit/tf/inputs/test_tabular.py: 8 warnings
tests/unit/tf/models/test_ranking.py: 20 warnings
tests/unit/tf/models/test_retrieval.py: 10 warnings
tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings
tests/unit/tf/prediction_tasks/test_regression.py: 3 warnings
tests/unit/tf/transforms/test_negative_sampling.py: 9 warnings
tests/unit/xgb/test_xgboost.py: 12 warnings
/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.SESSION_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.SESSION: 'session'>, <Tags.ID: 'id'>].
warnings.warn(

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export
tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export
tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export
tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export
tests/unit/tf/inputs/test_embedding.py::test_embedding_features_exporting_and_loading_pretrained_initializer
/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/inputs/embedding.py:970: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack
embeddings_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(embeddings)))

tests/unit/tf/blocks/retrieval/test_two_tower.py: 1 warning
tests/unit/tf/core/test_index.py: 4 warnings
tests/unit/tf/horovod/test_horovod.py: 3 warnings
tests/unit/tf/models/test_retrieval.py: 59 warnings
tests/unit/tf/prediction_tasks/test_next_item.py: 3 warnings
tests/unit/tf/utils/test_batch.py: 2 warnings
/tmp/autograph_generated_fileuguxsh42.py:8: DeprecationWarning: The 'warn' method is deprecated, use 'warning' instead
ag
.converted_call(ag__.ld(warnings).warn, ("The 'warn' method is deprecated, use 'warning' instead", ag__.ld(DeprecationWarning), 2), None, fscope)

tests/unit/tf/core/test_combinators.py::test_parallel_block_select_by_tags
/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/core/tabular.py:602: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated since Python 3.3, and in 3.10 it will stop working
elif isinstance(self.feature_names, collections.Sequence):

tests/unit/tf/core/test_encoder.py: 1 warning
tests/unit/tf/core/test_index.py: 5 warnings
tests/unit/tf/models/test_retrieval.py: 30 warnings
tests/unit/tf/utils/test_batch.py: 4 warnings
tests/unit/tf/utils/test_dataset.py: 1 warning
/var/jenkins_home/workspace/merlin_models/models/merlin/models/utils/dataset.py:75: DeprecationWarning: unique_rows_by_features is deprecated and will be removed in a future version. Please use unique_by_tag instead.
warnings.warn(

tests/unit/tf/models/test_base.py::test_model_pre_post[True]
tests/unit/tf/models/test_base.py::test_model_pre_post[False]
tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.1]
tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.3]
tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.5]
tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.7]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/util/dispatch.py:1082: UserWarning: tf.keras.backend.random_binomial is deprecated, and will be removed in a future version.Please use tf.keras.backend.random_bernoulli instead.
return dispatch_target(*args, **kwargs)

tests/unit/tf/models/test_base.py::test_freeze_parallel_block[True]
tests/unit/tf/models/test_base.py::test_freeze_sequential_block
tests/unit/tf/models/test_base.py::test_freeze_unfreeze
tests/unit/tf/models/test_base.py::test_unfreeze_all_blocks
/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/gradient_descent.py:108: UserWarning: The lr argument is deprecated, use learning_rate instead.
super(SGD, self).init(name, **kwargs)

tests/unit/tf/models/test_base.py::test_retrieval_model_query
tests/unit/tf/models/test_base.py::test_retrieval_model_query
tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_v2_export_embeddings
tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[True]
tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[False]
tests/unit/tf/transformers/test_block.py::test_retrieval_transformer[True]
/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/utils/tf_utils.py:298: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack
tensor_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(tensor)))

tests/unit/tf/models/test_ranking.py::test_deepfm_model_only_categ_feats[False]
tests/unit/tf/models/test_ranking.py::test_deepfm_model_categ_and_continuous_feats[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/models/test_ranking.py::test_wide_deep_model[False]
tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_categorical_one_hot[False]
tests/unit/tf/models/test_ranking.py::test_wide_deep_model_hashed_cross[False]
tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[True]
tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]
/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/transforms/features.py:569: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag
warnings.warn(

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/autograph/impl/api.py:371: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag
return py_builtins.overload_of(f)(*args)

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_onehot_multihot_feature_interaction[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_feature_interaction_multi_optimizer[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask/GatherV2:0", shape=(None, 48), dtype=float32), dense_shape=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Reshape_3:0", shape=(None,), dtype=int64), values=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Reshape_2:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask/GatherV2:0", shape=(None, 48), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_3:0", shape=(None,), dtype=int64), values=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_2:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/torch/block/test_mlp.py::test_mlp_block
/var/jenkins_home/workspace/merlin_models/models/tests/unit/torch/_conftest.py:151: UserWarning: Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at ../torch/csrc/utils/tensor_new.cpp:201.)
return {key: torch.tensor(value) for key, value in data.items()}

tests/unit/xgb/test_xgboost.py::test_without_dask_client
tests/unit/xgb/test_xgboost.py::TestXGBoost::test_music_regression
tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs0-DaskDeviceQuantileDMatrix]
tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs1-DaskDMatrix]
tests/unit/xgb/test_xgboost.py::TestEvals::test_multiple
tests/unit/xgb/test_xgboost.py::TestEvals::test_default
tests/unit/xgb/test_xgboost.py::TestEvals::test_train_and_valid
tests/unit/xgb/test_xgboost.py::TestEvals::test_invalid_data
/var/jenkins_home/workspace/merlin_models/models/merlin/models/xgb/init.py:344: UserWarning: Ignoring list columns as inputs to XGBoost model: ['item_genres', 'user_genres'].
warnings.warn(f"Ignoring list columns as inputs to XGBoost model: {list_column_names}.")

tests/unit/xgb/test_xgboost.py::TestXGBoost::test_unsupported_objective
/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/tornado/ioloop.py:350: DeprecationWarning: make_current is deprecated; start the event loop first
self.make_current()

tests/unit/xgb/test_xgboost.py: 14 warnings
/usr/local/lib/python3.8/dist-packages/xgboost/dask.py:884: RuntimeWarning: coroutine 'Client._wait_for_workers' was never awaited
client.wait_for_workers(n_workers)
Enable tracemalloc to get traceback where the object was allocated.
See https://docs.pytest.org/en/stable/how-to/capture-warnings.html#resource-warnings for more info.

tests/unit/xgb/test_xgboost.py: 11 warnings
/usr/local/lib/python3.8/dist-packages/cudf/core/dataframe.py:1183: DeprecationWarning: The default dtype for empty Series will be 'object' instead of 'float64' in a future version. Specify a dtype explicitly to silence this warning.
mask = pd.Series(mask)

-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html

---------- coverage: platform linux, python 3.8.10-final-0 -----------
Name Stmts Miss Cover

merlin/datasets/init.py 2 0 100%
merlin/datasets/advertising/init.py 2 0 100%
merlin/datasets/advertising/criteo/init.py 0 0 100%
merlin/datasets/advertising/criteo/dataset.py 79 49 38%
merlin/datasets/advertising/criteo/transformed/init.py 0 0 100%
merlin/datasets/ecommerce/init.py 4 0 100%
merlin/datasets/ecommerce/aliccp/init.py 0 0 100%
merlin/datasets/ecommerce/aliccp/dataset.py 141 87 38%
merlin/datasets/ecommerce/aliccp/raw/init.py 0 0 100%
merlin/datasets/ecommerce/aliccp/transformed/init.py 0 0 100%
merlin/datasets/ecommerce/booking/init.py 0 0 100%
merlin/datasets/ecommerce/booking/dataset.py 127 100 21%
merlin/datasets/ecommerce/booking/raw/init.py 0 0 100%
merlin/datasets/ecommerce/booking/transformed/init.py 0 0 100%
merlin/datasets/ecommerce/dressipi/init.py 0 0 100%
merlin/datasets/ecommerce/dressipi/dataset.py 45 37 18%
merlin/datasets/ecommerce/dressipi/preprocessed/init.py 0 0 100%
merlin/datasets/ecommerce/large/init.py 0 0 100%
merlin/datasets/ecommerce/small/init.py 0 0 100%
merlin/datasets/ecommerce/transactions/init.py 0 0 100%
merlin/datasets/entertainment/init.py 2 0 100%
merlin/datasets/entertainment/movielens/1m-raw/init.py 0 0 100%
merlin/datasets/entertainment/movielens/1m-raw/ratings/init.py 0 0 100%
merlin/datasets/entertainment/movielens/1m/init.py 0 0 100%
merlin/datasets/entertainment/movielens/25m/init.py 0 0 100%
merlin/datasets/entertainment/movielens/100k/init.py 0 0 100%
merlin/datasets/entertainment/movielens/init.py 0 0 100%
merlin/datasets/entertainment/movielens/dataset.py 152 122 20%
merlin/datasets/entertainment/music_streaming/init.py 0 0 100%
merlin/datasets/social/init.py 0 0 100%
merlin/datasets/synthetic.py 147 8 95%
merlin/datasets/testing/init.py 0 0 100%
merlin/datasets/testing/sequence_testing/init.py 0 0 100%
merlin/models/init.py 2 0 100%
merlin/models/_version.py 354 205 42%
merlin/models/api.py 14 5 64%
merlin/models/config/init.py 0 0 100%
merlin/models/config/schema.py 62 0 100%
merlin/models/implicit/init.py 27 4 85%
merlin/models/io.py 15 0 100%
merlin/models/lightfm/init.py 23 0 100%
merlin/models/loader/init.py 0 0 100%
merlin/models/loader/backend.py 379 41 89%
merlin/models/loader/dataframe_iter.py 21 17 19%
merlin/models/loader/tf_utils.py 57 27 53%
merlin/models/loader/utils.py 40 15 62%
merlin/models/tf/init.py 70 0 100%
merlin/models/tf/blocks/init.py 0 0 100%
merlin/models/tf/blocks/cross.py 44 0 100%
merlin/models/tf/blocks/dlrm.py 49 2 96%
merlin/models/tf/blocks/experts.py 99 17 83%
merlin/models/tf/blocks/interaction.py 108 40 63%
merlin/models/tf/blocks/mlp.py 117 7 94%
merlin/models/tf/blocks/optimizer.py 173 12 93%
merlin/models/tf/blocks/retrieval/init.py 0 0 100%
merlin/models/tf/blocks/retrieval/base.py 175 62 65%
merlin/models/tf/blocks/retrieval/matrix_factorization.py 35 1 97%
merlin/models/tf/blocks/retrieval/two_tower.py 30 0 100%
merlin/models/tf/blocks/sampling/init.py 0 0 100%
merlin/models/tf/blocks/sampling/base.py 29 2 93%
merlin/models/tf/blocks/sampling/cross_batch.py 46 2 96%
merlin/models/tf/blocks/sampling/in_batch.py 35 0 100%
merlin/models/tf/blocks/sampling/queue.py 115 12 90%
merlin/models/tf/core/init.py 0 0 100%
merlin/models/tf/core/aggregation.py 241 45 81%
merlin/models/tf/core/base.py 242 50 79%
merlin/models/tf/core/combinators.py 426 53 88%
merlin/models/tf/core/encoder.py 175 28 84%
merlin/models/tf/core/index.py 106 16 85%
merlin/models/tf/core/prediction.py 50 1 98%
merlin/models/tf/core/tabular.py 280 29 90%
merlin/models/tf/distributed/init.py 0 0 100%
merlin/models/tf/distributed/backend.py 9 2 78%
merlin/models/tf/inputs/init.py 0 0 100%
merlin/models/tf/inputs/base.py 60 10 83%
merlin/models/tf/inputs/continuous.py 39 3 92%
merlin/models/tf/inputs/embedding.py 458 32 93%
merlin/models/tf/loader.py 268 94 65%
merlin/models/tf/losses/init.py 4 0 100%
merlin/models/tf/losses/base.py 9 0 100%
merlin/models/tf/losses/listwise.py 13 0 100%
merlin/models/tf/losses/pairwise.py 115 1 99%
merlin/models/tf/metrics/init.py 2 0 100%
merlin/models/tf/metrics/evaluation.py 105 48 54%
merlin/models/tf/metrics/topk.py 198 48 76%
merlin/models/tf/models/init.py 0 0 100%
merlin/models/tf/models/base.py 756 101 87%
merlin/models/tf/models/benchmark.py 16 0 100%
merlin/models/tf/models/ranking.py 67 3 96%
merlin/models/tf/models/retrieval.py 78 4 95%
merlin/models/tf/models/utils.py 10 1 90%
merlin/models/tf/outputs/init.py 0 0 100%
merlin/models/tf/outputs/base.py 123 17 86%
merlin/models/tf/outputs/classification.py 91 1 99%
merlin/models/tf/outputs/contrastive.py 147 10 93%
merlin/models/tf/outputs/regression.py 9 0 100%
merlin/models/tf/outputs/sampling/init.py 0 0 100%
merlin/models/tf/outputs/sampling/base.py 78 21 73%
merlin/models/tf/outputs/sampling/in_batch.py 37 1 97%
merlin/models/tf/outputs/sampling/popularity.py 27 1 96%
merlin/models/tf/outputs/topk.py 98 6 94%
merlin/models/tf/prediction_tasks/init.py 0 0 100%
merlin/models/tf/prediction_tasks/base.py 207 37 82%
merlin/models/tf/prediction_tasks/classification.py 68 17 75%
merlin/models/tf/prediction_tasks/multi.py 7 0 100%
merlin/models/tf/prediction_tasks/next_item.py 59 6 90%
merlin/models/tf/prediction_tasks/regression.py 35 2 94%
merlin/models/tf/prediction_tasks/retrieval.py 73 3 96%
merlin/models/tf/transformers/init.py 0 0 100%
merlin/models/tf/transformers/block.py 101 2 98%
merlin/models/tf/transformers/transforms.py 63 0 100%
merlin/models/tf/transforms/init.py 0 0 100%
merlin/models/tf/transforms/bias.py 111 9 92%
merlin/models/tf/transforms/features.py 435 36 92%
merlin/models/tf/transforms/negative_sampling.py 77 3 96%
merlin/models/tf/transforms/noise.py 43 1 98%
merlin/models/tf/transforms/regularization.py 17 1 94%
merlin/models/tf/transforms/sequence.py 282 42 85%
merlin/models/tf/transforms/tensor.py 158 13 92%
merlin/models/tf/typing.py 7 0 100%
merlin/models/tf/utils/init.py 0 0 100%
merlin/models/tf/utils/batch_utils.py 85 4 95%
merlin/models/tf/utils/repr_utils.py 69 4 94%
merlin/models/tf/utils/search_utils.py 34 22 35%
merlin/models/tf/utils/testing_utils.py 206 36 83%
merlin/models/tf/utils/tf_utils.py 209 42 80%
merlin/models/torch/init.py 12 0 100%
merlin/models/torch/block/init.py 0 0 100%
merlin/models/torch/block/base.py 167 32 81%
merlin/models/torch/block/mlp.py 38 5 87%
merlin/models/torch/dataset.py 68 5 93%
merlin/models/torch/features/init.py 0 0 100%
merlin/models/torch/features/base.py 4 0 100%
merlin/models/torch/features/continuous.py 22 0 100%
merlin/models/torch/features/embedding.py 165 12 93%
merlin/models/torch/features/tabular.py 65 8 88%
merlin/models/torch/losses.py 28 28 0%
merlin/models/torch/model/init.py 0 0 100%
merlin/models/torch/model/base.py 286 65 77%
merlin/models/torch/model/prediction_task.py 24 0 100%
merlin/models/torch/tabular/init.py 0 0 100%
merlin/models/torch/tabular/aggregation.py 75 0 100%
merlin/models/torch/tabular/base.py 247 39 84%
merlin/models/torch/tabular/transformations.py 67 3 96%
merlin/models/torch/typing.py 6 0 100%
merlin/models/torch/utils/init.py 0 0 100%
merlin/models/torch/utils/data_utils.py 117 117 0%
merlin/models/torch/utils/examples_utils.py 39 39 0%
merlin/models/torch/utils/torch_utils.py 80 22 72%
merlin/models/utils/init.py 0 0 100%
merlin/models/utils/constants.py 3 0 100%
merlin/models/utils/dataset.py 38 4 89%
merlin/models/utils/dependencies.py 26 19 27%
merlin/models/utils/doc_utils.py 10 0 100%
merlin/models/utils/example_utils.py 31 2 94%
merlin/models/utils/misc_utils.py 118 90 24%
merlin/models/utils/nvt_utils.py 27 24 11%
merlin/models/utils/registry.py 101 29 71%
merlin/models/utils/schema_utils.py 90 19 79%
merlin/models/xgb/init.py 124 4 97%

TOTAL 11581 2346 80%

=========================== short test summary info ============================
SKIPPED [1] tests/unit/datasets/test_advertising.py:20: No data-dir available, pass it through env variable $INPUT_DATA_DIR
SKIPPED [1] tests/unit/datasets/test_ecommerce.py:64: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP
SKIPPED [1] tests/unit/datasets/test_ecommerce.py:80: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP
SKIPPED [1] tests/unit/datasets/test_ecommerce.py:94: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP
SKIPPED [1] tests/unit/datasets/test_ecommerce.py:115: No data-dir available, pass it through env variable $INPUT_DATA_DIR
SKIPPED [3] tests/unit/datasets/test_entertainment.py:44: No data-dir available, pass it through env variable $INPUT_DATA_DIR
SKIPPED [5] ../../../.local/lib/python3.8/site-packages/tensorflow/python/framework/test_util.py:2746: Not a test.
========= 871 passed, 13 skipped, 1452 warnings in 1830.30s (0:30:30) ==========
___________________________________ summary ____________________________________
py38-gpu: commands succeeded
congratulations :)
Performing Post build task...
Match found for : : True
Logical operation result is TRUE
Running script : #!/bin/bash
cd /var/jenkins_home/
CUDA_VISIBLE_DEVICES=1 python test_res_push.py "https://api.GitHub.com/repos/NVIDIA-Merlin/models/issues/$ghprbPullId/comments" "/var/jenkins_home/jobs/$JOB_NAME/builds/$BUILD_NUMBER/log"
[merlin_models] $ /bin/bash /tmp/jenkins13842193101511140170.sh

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rerun tests

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GitHub pull request #855 of commit c64d8bf5e3592d680f74b234548cd5b2f507714a, no merge conflicts.
Running as SYSTEM
Setting status of c64d8bf5e3592d680f74b234548cd5b2f507714a to PENDING with url http://merlin-infra1.nvidia.com:8080/job/merlin_models/1920/ and message: 'Pending'
Using context: Jenkins
Building on master in workspace /var/jenkins_home/workspace/merlin_models
using credential nvidia-merlin-bot
 > git rev-parse --is-inside-work-tree # timeout=10
Fetching changes from the remote Git repository
 > git config remote.origin.url https://github.com/NVIDIA-Merlin/models/ # timeout=10
Fetching upstream changes from https://github.com/NVIDIA-Merlin/models/
 > git --version # timeout=10
using GIT_ASKPASS to set credentials This is the bot credentials for our CI/CD
 > git fetch --tags --force --progress -- https://github.com/NVIDIA-Merlin/models/ +refs/pull/855/*:refs/remotes/origin/pr/855/* # timeout=10
 > git rev-parse c64d8bf5e3592d680f74b234548cd5b2f507714a^{commit} # timeout=10
Checking out Revision c64d8bf5e3592d680f74b234548cd5b2f507714a (detached)
 > git config core.sparsecheckout # timeout=10
 > git checkout -f c64d8bf5e3592d680f74b234548cd5b2f507714a # timeout=10
Commit message: "update notebook based on comments"
 > git rev-list --no-walk 7060fc72a6ca435c9eb2fd6a9d0c145a88d327d7 # timeout=10
[merlin_models] $ /bin/bash /tmp/jenkins5273405347246421092.sh
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Requirement already satisfied: testbook in /usr/local/lib/python3.8/dist-packages (0.4.2)
Requirement already satisfied: nbformat>=5.0.4 in /usr/local/lib/python3.8/dist-packages (from testbook) (5.5.0)
Requirement already satisfied: nbclient>=0.4.0 in /usr/local/lib/python3.8/dist-packages (from testbook) (0.6.8)
Requirement already satisfied: nest-asyncio in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (1.5.5)
Requirement already satisfied: traitlets>=5.2.2 in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (5.4.0)
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Requirement already satisfied: pkgutil-resolve-name>=1.3.10 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (1.3.10)
Requirement already satisfied: pyrsistent!=0.17.0,!=0.17.1,!=0.17.2,>=0.14.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (0.18.1)
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Requirement already satisfied: pyzmq>=23.0 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (24.0.0)
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Requirement already satisfied: zipp>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from importlib-resources>=1.4.0->jsonschema>=2.6->nbformat>=5.0.4->testbook) (3.8.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.8.2->jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (1.15.0)
GLOB sdist-make: /var/jenkins_home/workspace/merlin_models/models/setup.py
py38-gpu recreate: /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
py38-gpu installdeps: -rrequirements/dev.txt, tensorflow<2.10
WARNING: Discarding $PYTHONPATH from environment, to override specify PYTHONPATH in 'passenv' in your configuration.
py38-gpu inst: /var/jenkins_home/workspace/merlin_models/models/.tox/.tmp/package/4/merlin-models-0.9.0+63.gc64d8bf5.zip
WARNING: Discarding $PYTHONPATH from environment, to override specify PYTHONPATH in 'passenv' in your configuration.
py38-gpu installed: absl-py==1.2.0,aiohttp==3.8.1,aiosignal==1.2.0,alabaster==0.7.12,alembic==1.8.1,anyio==3.6.1,appdirs==1.4.4,argon2-cffi==21.3.0,argon2-cffi-bindings==21.2.0,astroid==2.5.6,asttokens==2.0.8,astunparse==1.6.3,asv==0.5.1,asvdb==0.4.2,async-timeout==4.0.2,attrs==22.1.0,autopage==0.5.1,awscli==1.27.14,Babel==2.10.3,backcall==0.2.0,beautifulsoup4==4.11.1,betterproto==1.2.5,black==20.8b1,bleach==5.0.1,bokeh==3.0.2,boto3==1.24.75,botocore==1.29.14,Brotli==1.0.9,build==0.9.0,cachetools==5.2.0,certifi==2019.11.28,cffi==1.15.1,chardet==3.0.4,charset-normalizer==2.1.1,check-manifest==0.48,clang==5.0,click==8.1.3,cliff==4.1.0,cloudpickle==2.2.0,cmaes==0.9.0,cmake==3.24.1.1,cmd2==2.4.2,colorama==0.4.4,colorlog==6.7.0,contourpy==1.0.5,coverage==6.5.0,cuda-python==11.7.1,cupy-cuda117==10.6.0,cycler==0.11.0,Cython==0.29.32,dask==2022.1.1,dbus-python==1.2.16,debugpy==1.6.3,decorator==5.1.1,defusedxml==0.7.1,dill==0.3.5.1,distlib==0.3.6,distributed==2022.5.1,distro==1.7.0,dm-tree==0.1.6,docker-pycreds==0.4.0,docutils==0.16,emoji==1.7.0,entrypoints==0.4,execnet==1.9.0,executing==1.0.0,faiss==1.7.2,faiss-gpu==1.7.2,fastai==2.7.9,fastapi==0.85.0,fastavro==1.6.1,fastcore==1.5.27,fastdownload==0.0.7,fastjsonschema==2.16.1,fastprogress==1.0.3,fastrlock==0.8,feast==0.19.4,fiddle==0.2.2,filelock==3.8.0,flake8==5.0.4,flatbuffers==1.12,fonttools==4.37.3,frozenlist==1.3.1,fsspec==2022.5.0,gast==0.4.0,gevent==21.12.0,geventhttpclient==2.0.2,gitdb==4.0.9,GitPython==3.1.27,google==3.0.0,google-api-core==2.10.1,google-auth==2.11.1,google-auth-oauthlib==0.4.6,google-pasta==0.2.0,googleapis-common-protos==1.52.0,graphviz==0.20.1,greenlet==1.1.3,grpcio==1.41.0,grpcio-channelz==1.49.0,grpcio-reflection==1.48.1,grpclib==0.4.3,h11==0.13.0,h2==4.1.0,h5py==3.7.0,HeapDict==1.0.1,horovod==0.26.1,hpack==4.0.0,httptools==0.5.0,hugectr2onnx==0.0.0,huggingface-hub==0.9.1,hyperframe==6.0.1,idna==2.8,imagesize==1.4.1,implicit==0.6.1,importlib-metadata==4.12.0,importlib-resources==5.9.0,iniconfig==1.1.1,interrogate==1.5.0,ipykernel==6.15.3,ipython==8.5.0,ipython-genutils==0.2.0,ipywidgets==7.7.0,isort==5.10.1,jedi==0.18.1,Jinja2==3.1.2,jmespath==1.0.1,joblib==1.2.0,json5==0.9.10,jsonschema==4.16.0,jupyter==1.0.0,jupyter-cache==0.4.3,jupyter-console==6.4.4,jupyter-core==4.11.1,jupyter-server==1.18.1,jupyter-server-mathjax==0.2.5,jupyter-sphinx==0.3.2,jupyter_client==7.3.5,jupyterlab==3.4.7,jupyterlab-pygments==0.2.2,jupyterlab-widgets==1.1.0,jupyterlab_server==2.15.1,keras==2.9.0,Keras-Preprocessing==1.1.2,kiwisolver==1.4.4,lazy-object-proxy==1.8.0,libclang==14.0.6,libcst==0.4.7,lightfm==1.16,lightgbm==3.3.2,linkify-it-py==1.0.3,llvmlite==0.39.1,locket==1.0.0,lxml==4.9.1,Mako==1.2.4,Markdown==3.4.1,markdown-it-py==1.1.0,MarkupSafe==2.1.1,matplotlib==3.6.0,matplotlib-inline==0.1.6,mccabe==0.7.0,mdit-py-plugins==0.2.8,merlin-core==0.6.0+1.g5926fcf,merlin-models==0.9.0+63.gc64d8bf5,merlin-systems==0.5.0+4.g15074ad,mistune==2.0.4,mmh3==3.0.0,mpi4py==3.1.3,msgpack==1.0.4,multidict==6.0.2,mypy==0.991,mypy-extensions==0.4.3,myst-nb==0.13.2,myst-parser==0.15.2,natsort==8.1.0,nbclassic==0.4.3,nbclient==0.6.8,nbconvert==7.0.0,nbdime==3.1.1,nbformat==5.5.0,nest-asyncio==1.5.5,ninja==1.10.2.3,notebook==6.4.12,notebook-shim==0.1.0,numba==0.56.2,numpy==1.22.4,nvidia-pyindex==1.0.9,# Editable install with no version control (nvtabular==1.4.0+8.g95e12d347),-e /usr/local/lib/python3.8/dist-packages,nvtx==0.2.5,oauthlib==3.2.1,oldest-supported-numpy==2022.8.16,onnx==1.12.0,onnxruntime==1.11.1,opt-einsum==3.3.0,optuna==3.0.3,packaging==21.3,pandas==1.3.5,pandavro==1.5.2,pandocfilters==1.5.0,parso==0.8.3,partd==1.3.0,pathspec==0.10.2,pathtools==0.1.2,pbr==5.11.0,pep517==0.13.0,pexpect==4.8.0,pickleshare==0.7.5,Pillow==9.2.0,pkgutil_resolve_name==1.3.10,platformdirs==2.5.2,plotly==5.11.0,pluggy==1.0.0,prettytable==3.5.0,prometheus-client==0.14.1,promise==2.3,prompt-toolkit==3.0.31,proto-plus==1.19.6,protobuf==3.19.5,psutil==5.9.2,ptyprocess==0.7.0,pure-eval==0.2.2,py==1.11.0,pyarrow==7.0.0,pyasn1==0.4.8,pyasn1-modules==0.2.8,pybind11==2.10.0,pycodestyle==2.9.1,pycparser==2.21,pydantic==1.10.2,pydot==1.4.2,pyflakes==2.5.0,Pygments==2.13.0,PyGObject==3.36.0,pynvml==11.4.1,pyparsing==3.0.9,pyperclip==1.8.2,pyrsistent==0.18.1,pytest==7.1.3,pytest-cov==4.0.0,pytest-xdist==3.0.2,python-apt==2.0.0+ubuntu0.20.4.8,python-dateutil==2.8.2,python-dotenv==0.21.0,python-rapidjson==1.8,pytz==2022.2.1,PyYAML==5.4.1,pyzmq==24.0.0,qtconsole==5.4.0,QtPy==2.3.0,regex==2022.9.13,requests==2.22.0,requests-oauthlib==1.3.1,requests-unixsocket==0.2.0,rsa==4.7.2,s3fs==2022.2.0,s3transfer==0.6.0,sacremoses==0.0.53,scikit-build==0.15.0,scikit-learn==1.1.2,scipy==1.8.1,seedir==0.3.0,Send2Trash==1.8.0,sentry-sdk==1.9.8,setproctitle==1.3.2,setuptools-scm==7.0.5,shortuuid==1.0.9,six==1.15.0,sklearn==0.0,smmap==5.0.0,sniffio==1.3.0,snowballstemmer==2.2.0,sortedcontainers==2.4.0,soupsieve==2.3.2.post1,Sphinx==5.3.0,sphinx-multiversion==0.2.4,sphinx-togglebutton==0.3.1,sphinx_external_toc==0.3.0,sphinxcontrib-applehelp==1.0.2,sphinxcontrib-copydirs @ git+https://github.com/mikemckiernan/sphinxcontrib-copydirs.git@bd8c5d79b3f91cf5f1bb0d6995aeca3fe84b670e,sphinxcontrib-devhelp==1.0.2,sphinxcontrib-htmlhelp==2.0.0,sphinxcontrib-jsmath==1.0.1,sphinxcontrib-qthelp==1.0.3,sphinxcontrib-serializinghtml==1.1.5,SQLAlchemy==1.4.44,stack-data==0.5.0,starlette==0.20.4,stevedore==4.1.1,stringcase==1.2.0,supervisor==4.1.0,tabulate==0.8.10,tblib==1.7.0,tdqm==0.0.1,tenacity==8.0.1,tensorboard==2.9.1,tensorboard-data-server==0.6.1,tensorboard-plugin-wit==1.8.1,tensorflow==2.9.2,tensorflow-estimator==2.9.0,tensorflow-gpu==2.9.2,tensorflow-io-gcs-filesystem==0.27.0,tensorflow-metadata==1.10.0,termcolor==2.0.1,terminado==0.15.0,testbook==0.4.2,threadpoolctl==3.1.0,tinycss2==1.1.1,tokenizers==0.10.3,toml==0.10.2,tomli==2.0.1,toolz==0.12.0,torch==1.12.1+cu113,torchmetrics==0.3.2,tornado==6.2,tox==3.26.0,tqdm==4.64.1,traitlets==5.4.0,transformers==4.12.0,transformers4rec==0.1.12+2.gbcc939255,treelite==2.3.0,treelite-runtime==2.3.0,tritonclient==2.25.0,typed-ast==1.5.4,typing-inspect==0.8.0,typing_extensions==4.3.0,uc-micro-py==1.0.1,urllib3==1.26.12,uvicorn==0.18.3,uvloop==0.17.0,versioneer==0.20,virtualenv==20.16.5,wandb==0.13.3,watchfiles==0.17.0,wcwidth==0.2.5,webencodings==0.5.1,websocket-client==1.4.1,websockets==10.3,Werkzeug==2.2.2,widgetsnbextension==3.6.0,wrapt==1.12.1,xgboost==1.6.2,xyzservices==2022.9.0,yarl==1.8.1,zict==2.2.0,zipp==3.8.1,zope.event==4.5.0,zope.interface==5.4.0
py38-gpu run-test-pre: PYTHONHASHSEED='21341215'
py38-gpu run-test: commands[0] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/core.git
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Collecting git+https://github.com/NVIDIA-Merlin/core.git
  Cloning https://github.com/NVIDIA-Merlin/core.git to /tmp/pip-req-build-jgb_ndkn
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/core.git /tmp/pip-req-build-jgb_ndkn
  Resolved https://github.com/NVIDIA-Merlin/core.git to commit 04ff5225cee6af90b6b08070493677ac53b96836
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: tqdm>=4.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+16.g04ff522) (4.64.1)
Requirement already satisfied: protobuf>=3.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+16.g04ff522) (3.19.5)
Requirement already satisfied: numba>=0.54 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+16.g04ff522) (0.55.1)
Requirement already satisfied: betterproto<2.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+16.g04ff522) (1.2.5)
Requirement already satisfied: pandas<1.4.0dev0,>=1.2.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+16.g04ff522) (1.3.5)
Requirement already satisfied: fsspec==2022.5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+16.g04ff522) (2022.5.0)
Requirement already satisfied: distributed>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+16.g04ff522) (2022.3.0)
Requirement already satisfied: dask>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+16.g04ff522) (2022.3.0)
Requirement already satisfied: packaging in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+16.g04ff522) (21.3)
Requirement already satisfied: tensorflow-metadata>=1.2.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+16.g04ff522) (1.10.0)
Requirement already satisfied: pyarrow>=5.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+16.g04ff522) (7.0.0)
Requirement already satisfied: grpclib in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core==0.8.0+16.g04ff522) (0.4.3)
Requirement already satisfied: stringcase in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core==0.8.0+16.g04ff522) (1.2.0)
Requirement already satisfied: partd>=0.3.10 in /var/jenkins_home/.local/lib/python3.8/site-packages/partd-1.2.0-py3.8.egg (from dask>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (1.2.0)
Requirement already satisfied: pyyaml>=5.3.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/PyYAML-5.4.1-py3.8-linux-x86_64.egg (from dask>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (5.4.1)
Requirement already satisfied: toolz>=0.8.2 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (0.12.0)
Requirement already satisfied: cloudpickle>=1.1.1 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (2.2.0)
Requirement already satisfied: sortedcontainers!=2.0.0,!=2.0.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/sortedcontainers-2.4.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (2.4.0)
Requirement already satisfied: msgpack>=0.6.0 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (1.0.4)
Requirement already satisfied: psutil>=5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/psutil-5.8.0-py3.8-linux-x86_64.egg (from distributed>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (5.8.0)
Requirement already satisfied: zict>=0.1.3 in /var/jenkins_home/.local/lib/python3.8/site-packages/zict-2.0.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (2.0.0)
Requirement already satisfied: click>=6.6 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (8.1.3)
Requirement already satisfied: jinja2 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (3.1.2)
Requirement already satisfied: tornado>=6.0.3 in ./.tox/py38-gpu/lib/python3.8/site-packages (from distributed>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (6.2)
Requirement already satisfied: tblib>=1.6.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/tblib-1.7.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (1.7.0)
Requirement already satisfied: llvmlite<0.39,>=0.38.0rc1 in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+16.g04ff522) (0.38.1)
Requirement already satisfied: numpy<1.22,>=1.18 in /var/jenkins_home/.local/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+16.g04ff522) (1.20.3)
Requirement already satisfied: setuptools in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+16.g04ff522) (65.5.1)
Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in /usr/local/lib/python3.8/dist-packages (from packaging->merlin-core==0.8.0+16.g04ff522) (3.0.9)
Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+16.g04ff522) (2.8.2)
Requirement already satisfied: pytz>=2017.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+16.g04ff522) (2022.2.1)
Requirement already satisfied: absl-py<2.0.0,>=0.9 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core==0.8.0+16.g04ff522) (1.2.0)
Requirement already satisfied: googleapis-common-protos<2,>=1.52.0 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core==0.8.0+16.g04ff522) (1.52.0)
Requirement already satisfied: locket in /var/jenkins_home/.local/lib/python3.8/site-packages/locket-0.2.1-py3.8.egg (from partd>=0.3.10->dask>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (0.2.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.7.3->pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+16.g04ff522) (1.15.0)
Requirement already satisfied: heapdict in /var/jenkins_home/.local/lib/python3.8/site-packages/HeapDict-1.0.1-py3.8.egg (from zict>=0.1.3->distributed>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (1.0.1)
Requirement already satisfied: h2<5,>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core==0.8.0+16.g04ff522) (4.1.0)
Requirement already satisfied: multidict in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core==0.8.0+16.g04ff522) (6.0.2)
Requirement already satisfied: MarkupSafe>=2.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from jinja2->distributed>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (2.0.1)
Requirement already satisfied: hpack<5,>=4.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core==0.8.0+16.g04ff522) (4.0.0)
Requirement already satisfied: hyperframe<7,>=6.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core==0.8.0+16.g04ff522) (6.0.1)
Building wheels for collected packages: merlin-core
  Building wheel for merlin-core (pyproject.toml): started
  Building wheel for merlin-core (pyproject.toml): finished with status 'done'
  Created wheel for merlin-core: filename=merlin_core-0.8.0+16.g04ff522-py3-none-any.whl size=118833 sha256=350c422a6fbbc63729c9acc78b129f52dbecdb792944c8ec6c2027707cdd5d82
  Stored in directory: /tmp/pip-ephem-wheel-cache-z7cllna2/wheels/c8/38/16/a6968787eafcec5fa772148af8408b089562f71af0752e8e84
Successfully built merlin-core
Installing collected packages: merlin-core
  Attempting uninstall: merlin-core
    Found existing installation: merlin-core 0.3.0+12.g78ecddd
    Not uninstalling merlin-core at /var/jenkins_home/.local/lib/python3.8/site-packages, outside environment /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
    Can't uninstall 'merlin-core'. No files were found to uninstall.
Successfully installed merlin-core-0.8.0+16.g04ff522
py38-gpu run-test: commands[1] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/nvtabular.git
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Collecting git+https://github.com/NVIDIA-Merlin/nvtabular.git
  Cloning https://github.com/NVIDIA-Merlin/nvtabular.git to /tmp/pip-req-build-x12lb54s
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/nvtabular.git /tmp/pip-req-build-x12lb54s
  Resolved https://github.com/NVIDIA-Merlin/nvtabular.git to commit e5b7351deb9e4885c4038aa0bbc9f146d8477a0e
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Collecting merlin-dataloader>=0.0.2
  Downloading merlin-dataloader-0.0.2.tar.gz (44 kB)
     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 44.1/44.1 kB 1.7 MB/s eta 0:00:00
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: merlin-core>=0.2.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from nvtabular==1.6.0+6.ge5b7351d) (0.8.0+16.g04ff522)
Requirement already satisfied: scipy in /usr/local/lib/python3.8/dist-packages (from nvtabular==1.6.0+6.ge5b7351d) (1.8.1)
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Building wheels for collected packages: nvtabular, merlin-dataloader
  Building wheel for nvtabular (pyproject.toml): started
  Building wheel for nvtabular (pyproject.toml): finished with status 'done'
  Created wheel for nvtabular: filename=nvtabular-1.6.0+6.ge5b7351d-cp38-cp38-linux_x86_64.whl size=257597 sha256=876c29ba21c2d0cd28437144254631d6710e5bb3aa7c221441a5385c90f4a9b1
  Stored in directory: /tmp/pip-ephem-wheel-cache-5tp01lve/wheels/8f/d9/f9/30f2cdc5bf8787fae6fdfe55afd6e1b493e619ec32c32ec40b
  Building wheel for merlin-dataloader (pyproject.toml): started
  Building wheel for merlin-dataloader (pyproject.toml): finished with status 'done'
  Created wheel for merlin-dataloader: filename=merlin_dataloader-0.0.2-py3-none-any.whl size=29203 sha256=bf70c404ef074f743e7dcfa5f5c8a15d976f9d36509ce13097f64bc6db7334d6
  Stored in directory: /tmp/pip-ephem-wheel-cache-5tp01lve/wheels/76/ef/ed/cb880e3ef5192ec5940e26fd9442247b569fb0cf8602f97137
Successfully built nvtabular merlin-dataloader
Installing collected packages: merlin-dataloader, nvtabular
  Attempting uninstall: nvtabular
    Found existing installation: nvtabular 1.1.1
    Not uninstalling nvtabular at /var/jenkins_home/.local/lib/python3.8/site-packages, outside environment /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
    Can't uninstall 'nvtabular'. No files were found to uninstall.
Successfully installed merlin-dataloader-0.0.2 nvtabular-1.6.0+6.ge5b7351d
py38-gpu run-test: commands[2] | python -m pytest --cov-report term --cov merlin -rxs tests/unit
============================= test session starts ==============================
platform linux -- Python 3.8.10, pytest-7.1.3, pluggy-1.0.0
cachedir: .tox/py38-gpu/.pytest_cache
rootdir: /var/jenkins_home/workspace/merlin_models/models, configfile: pyproject.toml
plugins: anyio-3.5.0, xdist-3.0.2, cov-4.0.0
collected 884 items

tests/unit/config/test_schema.py .... [ 0%]
tests/unit/datasets/test_advertising.py .s [ 0%]
tests/unit/datasets/test_ecommerce.py ..sss.s [ 1%]
tests/unit/datasets/test_entertainment.py ....sss. [ 2%]
tests/unit/datasets/test_social.py . [ 2%]
tests/unit/datasets/test_synthetic.py .......... [ 3%]
tests/unit/implicit/test_implicit.py . [ 3%]
tests/unit/lightfm/test_lightfm.py . [ 3%]
tests/unit/tf/test_core.py ...... [ 4%]
tests/unit/tf/test_loader.py ................ [ 6%]
tests/unit/tf/test_public_api.py . [ 6%]
tests/unit/tf/blocks/test_cross.py ........... [ 7%]
tests/unit/tf/blocks/test_dlrm.py .......... [ 8%]
tests/unit/tf/blocks/test_interactions.py ... [ 9%]
tests/unit/tf/blocks/test_mlp.py ....................................... [ 13%]
............................ [ 16%]
tests/unit/tf/blocks/test_optimizer.py s................................ [ 20%]
..................... [ 22%]
tests/unit/tf/blocks/retrieval/test_base.py . [ 22%]
tests/unit/tf/blocks/retrieval/test_matrix_factorization.py .. [ 23%]
tests/unit/tf/blocks/retrieval/test_two_tower.py ............ [ 24%]
tests/unit/tf/blocks/sampling/test_cross_batch.py . [ 24%]
tests/unit/tf/blocks/sampling/test_in_batch.py . [ 24%]
tests/unit/tf/core/test_aggregation.py ......... [ 25%]
tests/unit/tf/core/test_base.py .. [ 26%]
tests/unit/tf/core/test_combinators.py s..................... [ 28%]
tests/unit/tf/core/test_encoder.py .. [ 28%]
tests/unit/tf/core/test_index.py ... [ 29%]
tests/unit/tf/core/test_prediction.py .. [ 29%]
tests/unit/tf/core/test_tabular.py ...... [ 29%]
tests/unit/tf/examples/test_01_getting_started.py . [ 30%]
tests/unit/tf/examples/test_02_dataschema.py . [ 30%]
tests/unit/tf/examples/test_03_exploring_different_models.py . [ 30%]
tests/unit/tf/examples/test_04_export_ranking_models.py . [ 30%]
tests/unit/tf/examples/test_05_export_retrieval_model.py . [ 30%]
tests/unit/tf/examples/test_06_advanced_own_architecture.py . [ 30%]
tests/unit/tf/examples/test_07_train_traditional_models.py . [ 30%]
tests/unit/tf/examples/test_usecase_accelerate_training_by_lazyadam.py . [ 30%]
[ 30%]
tests/unit/tf/examples/test_usecase_data_parallel.py . [ 30%]
tests/unit/tf/examples/test_usecase_ecommerce_session_based.py . [ 31%]
tests/unit/tf/examples/test_usecase_incremental_training_layer_freezing.py . [ 31%]
[ 31%]
tests/unit/tf/examples/test_usecase_pretrained_embeddings.py . [ 31%]
tests/unit/tf/examples/test_usecase_retrieval_with_hpo.py . [ 31%]
tests/unit/tf/examples/test_usecase_transformers_next_item_prediction.py . [ 31%]
[ 31%]
tests/unit/tf/horovod/test_horovod.py ... [ 31%]
tests/unit/tf/inputs/test_base.py . [ 32%]
tests/unit/tf/inputs/test_continuous.py ........ [ 32%]
tests/unit/tf/inputs/test_embedding.py ................................. [ 36%]
........ [ 37%]
tests/unit/tf/inputs/test_tabular.py .................. [ 39%]
tests/unit/tf/layers/test_queue.py .............. [ 41%]
tests/unit/tf/losses/test_losses.py ....................... [ 43%]
tests/unit/tf/metrics/test_metrics_popularity.py ..... [ 44%]
tests/unit/tf/metrics/test_metrics_topk.py ......................... [ 47%]
tests/unit/tf/models/test_base.py s......................... [ 50%]
tests/unit/tf/models/test_benchmark.py .. [ 50%]
tests/unit/tf/models/test_ranking.py .................................. [ 54%]
tests/unit/tf/models/test_retrieval.py ................................. [ 57%]
........................................... [ 62%]
tests/unit/tf/outputs/test_base.py ...... [ 63%]
tests/unit/tf/outputs/test_classification.py ...... [ 64%]
tests/unit/tf/outputs/test_contrastive.py .............. [ 65%]
tests/unit/tf/outputs/test_regression.py .. [ 65%]
tests/unit/tf/outputs/test_sampling.py .... [ 66%]
tests/unit/tf/outputs/test_topk.py . [ 66%]
tests/unit/tf/prediction_tasks/test_classification.py .. [ 66%]
tests/unit/tf/prediction_tasks/test_multi_task.py ................ [ 68%]
tests/unit/tf/prediction_tasks/test_next_item.py ..... [ 69%]
tests/unit/tf/prediction_tasks/test_regression.py ..... [ 69%]
tests/unit/tf/prediction_tasks/test_retrieval.py . [ 69%]
tests/unit/tf/prediction_tasks/test_sampling.py ...... [ 70%]
tests/unit/tf/transformers/test_block.py ...................... [ 72%]
tests/unit/tf/transformers/test_transforms.py .......... [ 74%]
tests/unit/tf/transforms/test_bias.py .. [ 74%]
tests/unit/tf/transforms/test_features.py s............................. [ 77%]
.......................s...... [ 81%]
tests/unit/tf/transforms/test_negative_sampling.py ......... [ 82%]
tests/unit/tf/transforms/test_noise.py ..... [ 82%]
tests/unit/tf/transforms/test_sequence.py .................... [ 84%]
tests/unit/tf/transforms/test_tensor.py ... [ 85%]
tests/unit/tf/utils/test_batch.py .... [ 85%]
tests/unit/tf/utils/test_dataset.py .. [ 85%]
tests/unit/tf/utils/test_tf_utils.py ..... [ 86%]
tests/unit/torch/test_dataset.py ......... [ 87%]
tests/unit/torch/test_public_api.py . [ 87%]
tests/unit/torch/block/test_base.py .... [ 88%]
tests/unit/torch/block/test_mlp.py . [ 88%]
tests/unit/torch/features/test_continuous.py .. [ 88%]
tests/unit/torch/features/test_embedding.py .............. [ 90%]
tests/unit/torch/features/test_tabular.py .... [ 90%]
tests/unit/torch/model/test_head.py ............ [ 91%]
tests/unit/torch/model/test_model.py .. [ 92%]
tests/unit/torch/tabular/test_aggregation.py ........ [ 92%]
tests/unit/torch/tabular/test_tabular.py ... [ 93%]
tests/unit/torch/tabular/test_transformations.py ....... [ 94%]
tests/unit/utils/test_schema_utils.py ................................ [ 97%]
tests/unit/xgb/test_xgboost.py .................... [100%]

=============================== warnings summary ===============================
../../../../../usr/lib/python3/dist-packages/requests/init.py:89
/usr/lib/python3/dist-packages/requests/init.py:89: RequestsDependencyWarning: urllib3 (1.26.12) or chardet (3.0.4) doesn't match a supported version!
warnings.warn("urllib3 ({}) or chardet ({}) doesn't match a supported "

../../../.local/lib/python3.8/site-packages/flatbuffers/compat.py:19
/var/jenkins_home/.local/lib/python3.8/site-packages/flatbuffers/compat.py:19: DeprecationWarning: the imp module is deprecated in favour of importlib; see the module's documentation for alternative uses
import imp

../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36
/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36: DeprecationWarning: NEAREST is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.NEAREST or Dither.NONE instead.
'nearest': pil_image.NEAREST,

../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37
/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37: DeprecationWarning: BILINEAR is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BILINEAR instead.
'bilinear': pil_image.BILINEAR,

../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38
/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38: DeprecationWarning: BICUBIC is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BICUBIC instead.
'bicubic': pil_image.BICUBIC,

../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39
/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39: DeprecationWarning: HAMMING is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.HAMMING instead.
'hamming': pil_image.HAMMING,

../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40
/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40: DeprecationWarning: BOX is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BOX instead.
'box': pil_image.BOX,

../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41
/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41: DeprecationWarning: LANCZOS is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.LANCZOS instead.
'lanczos': pil_image.LANCZOS,

tests/unit/datasets/test_advertising.py: 1 warning
tests/unit/datasets/test_ecommerce.py: 3 warnings
tests/unit/datasets/test_entertainment.py: 4 warnings
tests/unit/datasets/test_social.py: 1 warning
tests/unit/datasets/test_synthetic.py: 10 warnings
tests/unit/implicit/test_implicit.py: 1 warning
tests/unit/lightfm/test_lightfm.py: 1 warning
tests/unit/tf/test_core.py: 6 warnings
tests/unit/tf/test_loader.py: 1 warning
tests/unit/tf/blocks/test_cross.py: 5 warnings
tests/unit/tf/blocks/test_dlrm.py: 9 warnings
tests/unit/tf/blocks/test_interactions.py: 2 warnings
tests/unit/tf/blocks/test_mlp.py: 60 warnings
tests/unit/tf/blocks/test_optimizer.py: 30 warnings
tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings
tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings
tests/unit/tf/core/test_aggregation.py: 6 warnings
tests/unit/tf/core/test_base.py: 2 warnings
tests/unit/tf/core/test_combinators.py: 11 warnings
tests/unit/tf/core/test_encoder.py: 6 warnings
tests/unit/tf/core/test_index.py: 8 warnings
tests/unit/tf/core/test_prediction.py: 2 warnings
tests/unit/tf/horovod/test_horovod.py: 3 warnings
tests/unit/tf/inputs/test_base.py: 1 warning
tests/unit/tf/inputs/test_continuous.py: 7 warnings
tests/unit/tf/inputs/test_embedding.py: 20 warnings
tests/unit/tf/inputs/test_tabular.py: 18 warnings
tests/unit/tf/models/test_base.py: 28 warnings
tests/unit/tf/models/test_benchmark.py: 2 warnings
tests/unit/tf/models/test_ranking.py: 38 warnings
tests/unit/tf/models/test_retrieval.py: 121 warnings
tests/unit/tf/outputs/test_base.py: 6 warnings
tests/unit/tf/outputs/test_classification.py: 6 warnings
tests/unit/tf/outputs/test_contrastive.py: 19 warnings
tests/unit/tf/outputs/test_regression.py: 2 warnings
tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings
tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings
tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings
tests/unit/tf/prediction_tasks/test_retrieval.py: 1 warning
tests/unit/tf/transformers/test_block.py: 16 warnings
tests/unit/tf/transforms/test_bias.py: 2 warnings
tests/unit/tf/transforms/test_features.py: 10 warnings
tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings
tests/unit/tf/transforms/test_noise.py: 1 warning
tests/unit/tf/transforms/test_sequence.py: 15 warnings
tests/unit/tf/utils/test_batch.py: 9 warnings
tests/unit/tf/utils/test_dataset.py: 2 warnings
tests/unit/torch/block/test_base.py: 4 warnings
tests/unit/torch/block/test_mlp.py: 1 warning
tests/unit/torch/features/test_continuous.py: 1 warning
tests/unit/torch/features/test_embedding.py: 4 warnings
tests/unit/torch/features/test_tabular.py: 4 warnings
tests/unit/torch/model/test_head.py: 12 warnings
tests/unit/torch/model/test_model.py: 2 warnings
tests/unit/torch/tabular/test_aggregation.py: 6 warnings
tests/unit/torch/tabular/test_transformations.py: 3 warnings
tests/unit/xgb/test_xgboost.py: 18 warnings
/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.ITEM_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.ITEM: 'item'>, <Tags.ID: 'id'>].
warnings.warn(

tests/unit/datasets/test_ecommerce.py: 3 warnings
tests/unit/datasets/test_entertainment.py: 4 warnings
tests/unit/datasets/test_social.py: 1 warning
tests/unit/datasets/test_synthetic.py: 9 warnings
tests/unit/implicit/test_implicit.py: 1 warning
tests/unit/lightfm/test_lightfm.py: 1 warning
tests/unit/tf/test_core.py: 6 warnings
tests/unit/tf/test_loader.py: 1 warning
tests/unit/tf/blocks/test_cross.py: 5 warnings
tests/unit/tf/blocks/test_dlrm.py: 9 warnings
tests/unit/tf/blocks/test_interactions.py: 2 warnings
tests/unit/tf/blocks/test_mlp.py: 60 warnings
tests/unit/tf/blocks/test_optimizer.py: 30 warnings
tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings
tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings
tests/unit/tf/core/test_aggregation.py: 6 warnings
tests/unit/tf/core/test_base.py: 2 warnings
tests/unit/tf/core/test_combinators.py: 11 warnings
tests/unit/tf/core/test_encoder.py: 7 warnings
tests/unit/tf/core/test_index.py: 3 warnings
tests/unit/tf/core/test_prediction.py: 2 warnings
tests/unit/tf/horovod/test_horovod.py: 1 warning
tests/unit/tf/inputs/test_base.py: 1 warning
tests/unit/tf/inputs/test_continuous.py: 7 warnings
tests/unit/tf/inputs/test_embedding.py: 20 warnings
tests/unit/tf/inputs/test_tabular.py: 18 warnings
tests/unit/tf/models/test_base.py: 28 warnings
tests/unit/tf/models/test_benchmark.py: 2 warnings
tests/unit/tf/models/test_ranking.py: 36 warnings
tests/unit/tf/models/test_retrieval.py: 87 warnings
tests/unit/tf/outputs/test_base.py: 6 warnings
tests/unit/tf/outputs/test_classification.py: 6 warnings
tests/unit/tf/outputs/test_contrastive.py: 19 warnings
tests/unit/tf/outputs/test_regression.py: 2 warnings
tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings
tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings
tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings
tests/unit/tf/transformers/test_block.py: 10 warnings
tests/unit/tf/transforms/test_features.py: 10 warnings
tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings
tests/unit/tf/transforms/test_sequence.py: 15 warnings
tests/unit/tf/utils/test_batch.py: 7 warnings
tests/unit/tf/utils/test_dataset.py: 2 warnings
tests/unit/torch/block/test_base.py: 4 warnings
tests/unit/torch/block/test_mlp.py: 1 warning
tests/unit/torch/features/test_continuous.py: 1 warning
tests/unit/torch/features/test_embedding.py: 4 warnings
tests/unit/torch/features/test_tabular.py: 4 warnings
tests/unit/torch/model/test_head.py: 12 warnings
tests/unit/torch/model/test_model.py: 2 warnings
tests/unit/torch/tabular/test_aggregation.py: 6 warnings
tests/unit/torch/tabular/test_transformations.py: 2 warnings
tests/unit/xgb/test_xgboost.py: 17 warnings
/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.USER_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.USER: 'user'>, <Tags.ID: 'id'>].
warnings.warn(

tests/unit/datasets/test_ecommerce.py: 1 warning
tests/unit/datasets/test_entertainment.py: 1 warning
tests/unit/implicit/test_implicit.py: 1 warning
tests/unit/lightfm/test_lightfm.py: 1 warning
tests/unit/tf/test_loader.py: 1 warning
tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings
tests/unit/tf/blocks/retrieval/test_two_tower.py: 2 warnings
tests/unit/tf/core/test_combinators.py: 11 warnings
tests/unit/tf/core/test_encoder.py: 2 warnings
tests/unit/tf/core/test_prediction.py: 1 warning
tests/unit/tf/horovod/test_horovod.py: 1 warning
tests/unit/tf/inputs/test_continuous.py: 4 warnings
tests/unit/tf/inputs/test_embedding.py: 9 warnings
tests/unit/tf/inputs/test_tabular.py: 8 warnings
tests/unit/tf/models/test_ranking.py: 20 warnings
tests/unit/tf/models/test_retrieval.py: 10 warnings
tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings
tests/unit/tf/prediction_tasks/test_regression.py: 3 warnings
tests/unit/tf/transforms/test_negative_sampling.py: 9 warnings
tests/unit/xgb/test_xgboost.py: 12 warnings
/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.SESSION_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.SESSION: 'session'>, <Tags.ID: 'id'>].
warnings.warn(

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export
tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export
tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export
tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export
tests/unit/tf/inputs/test_embedding.py::test_embedding_features_exporting_and_loading_pretrained_initializer
/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/inputs/embedding.py:970: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack
embeddings_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(embeddings)))

tests/unit/tf/blocks/retrieval/test_two_tower.py: 1 warning
tests/unit/tf/core/test_index.py: 4 warnings
tests/unit/tf/horovod/test_horovod.py: 3 warnings
tests/unit/tf/models/test_retrieval.py: 59 warnings
tests/unit/tf/prediction_tasks/test_next_item.py: 3 warnings
tests/unit/tf/utils/test_batch.py: 2 warnings
/tmp/autograph_generated_file7f7ww4lj.py:8: DeprecationWarning: The 'warn' method is deprecated, use 'warning' instead
ag
.converted_call(ag__.ld(warnings).warn, ("The 'warn' method is deprecated, use 'warning' instead", ag__.ld(DeprecationWarning), 2), None, fscope)

tests/unit/tf/core/test_combinators.py::test_parallel_block_select_by_tags
/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/core/tabular.py:602: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated since Python 3.3, and in 3.10 it will stop working
elif isinstance(self.feature_names, collections.Sequence):

tests/unit/tf/core/test_encoder.py: 1 warning
tests/unit/tf/core/test_index.py: 5 warnings
tests/unit/tf/models/test_retrieval.py: 30 warnings
tests/unit/tf/utils/test_batch.py: 4 warnings
tests/unit/tf/utils/test_dataset.py: 1 warning
/var/jenkins_home/workspace/merlin_models/models/merlin/models/utils/dataset.py:75: DeprecationWarning: unique_rows_by_features is deprecated and will be removed in a future version. Please use unique_by_tag instead.
warnings.warn(

tests/unit/tf/models/test_base.py::test_model_pre_post[True]
tests/unit/tf/models/test_base.py::test_model_pre_post[False]
tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.1]
tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.3]
tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.5]
tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.7]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/util/dispatch.py:1082: UserWarning: tf.keras.backend.random_binomial is deprecated, and will be removed in a future version.Please use tf.keras.backend.random_bernoulli instead.
return dispatch_target(*args, **kwargs)

tests/unit/tf/models/test_base.py::test_freeze_parallel_block[True]
tests/unit/tf/models/test_base.py::test_freeze_sequential_block
tests/unit/tf/models/test_base.py::test_freeze_unfreeze
tests/unit/tf/models/test_base.py::test_unfreeze_all_blocks
/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/gradient_descent.py:108: UserWarning: The lr argument is deprecated, use learning_rate instead.
super(SGD, self).init(name, **kwargs)

tests/unit/tf/models/test_base.py::test_retrieval_model_query
tests/unit/tf/models/test_base.py::test_retrieval_model_query
tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_v2_export_embeddings
tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[True]
tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[False]
tests/unit/tf/transformers/test_block.py::test_retrieval_transformer[True]
/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/utils/tf_utils.py:298: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack
tensor_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(tensor)))

tests/unit/tf/models/test_ranking.py::test_deepfm_model_only_categ_feats[False]
tests/unit/tf/models/test_ranking.py::test_deepfm_model_categ_and_continuous_feats[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/models/test_ranking.py::test_wide_deep_model[False]
tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_categorical_one_hot[False]
tests/unit/tf/models/test_ranking.py::test_wide_deep_model_hashed_cross[False]
tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[True]
tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]
/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/transforms/features.py:569: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag
warnings.warn(

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/autograph/impl/api.py:371: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag
return py_builtins.overload_of(f)(*args)

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_onehot_multihot_feature_interaction[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_feature_interaction_multi_optimizer[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask/GatherV2:0", shape=(None, 48), dtype=float32), dense_shape=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Reshape_3:0", shape=(None,), dtype=int64), values=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Reshape_2:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask/GatherV2:0", shape=(None, 48), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_3:0", shape=(None,), dtype=int64), values=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_2:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/torch/block/test_mlp.py::test_mlp_block
/var/jenkins_home/workspace/merlin_models/models/tests/unit/torch/_conftest.py:151: UserWarning: Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at ../torch/csrc/utils/tensor_new.cpp:201.)
return {key: torch.tensor(value) for key, value in data.items()}

tests/unit/xgb/test_xgboost.py::test_without_dask_client
tests/unit/xgb/test_xgboost.py::TestXGBoost::test_music_regression
tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs0-DaskDeviceQuantileDMatrix]
tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs1-DaskDMatrix]
tests/unit/xgb/test_xgboost.py::TestEvals::test_multiple
tests/unit/xgb/test_xgboost.py::TestEvals::test_default
tests/unit/xgb/test_xgboost.py::TestEvals::test_train_and_valid
tests/unit/xgb/test_xgboost.py::TestEvals::test_invalid_data
/var/jenkins_home/workspace/merlin_models/models/merlin/models/xgb/init.py:344: UserWarning: Ignoring list columns as inputs to XGBoost model: ['item_genres', 'user_genres'].
warnings.warn(f"Ignoring list columns as inputs to XGBoost model: {list_column_names}.")

tests/unit/xgb/test_xgboost.py::TestXGBoost::test_unsupported_objective
/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/tornado/ioloop.py:350: DeprecationWarning: make_current is deprecated; start the event loop first
self.make_current()

tests/unit/xgb/test_xgboost.py: 14 warnings
/usr/local/lib/python3.8/dist-packages/xgboost/dask.py:884: RuntimeWarning: coroutine 'Client._wait_for_workers' was never awaited
client.wait_for_workers(n_workers)
Enable tracemalloc to get traceback where the object was allocated.
See https://docs.pytest.org/en/stable/how-to/capture-warnings.html#resource-warnings for more info.

tests/unit/xgb/test_xgboost.py: 11 warnings
/usr/local/lib/python3.8/dist-packages/cudf/core/dataframe.py:1183: DeprecationWarning: The default dtype for empty Series will be 'object' instead of 'float64' in a future version. Specify a dtype explicitly to silence this warning.
mask = pd.Series(mask)

-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html

---------- coverage: platform linux, python 3.8.10-final-0 -----------
Name Stmts Miss Cover

merlin/datasets/init.py 2 0 100%
merlin/datasets/advertising/init.py 2 0 100%
merlin/datasets/advertising/criteo/init.py 0 0 100%
merlin/datasets/advertising/criteo/dataset.py 79 49 38%
merlin/datasets/advertising/criteo/transformed/init.py 0 0 100%
merlin/datasets/ecommerce/init.py 4 0 100%
merlin/datasets/ecommerce/aliccp/init.py 0 0 100%
merlin/datasets/ecommerce/aliccp/dataset.py 141 87 38%
merlin/datasets/ecommerce/aliccp/raw/init.py 0 0 100%
merlin/datasets/ecommerce/aliccp/transformed/init.py 0 0 100%
merlin/datasets/ecommerce/booking/init.py 0 0 100%
merlin/datasets/ecommerce/booking/dataset.py 127 100 21%
merlin/datasets/ecommerce/booking/raw/init.py 0 0 100%
merlin/datasets/ecommerce/booking/transformed/init.py 0 0 100%
merlin/datasets/ecommerce/dressipi/init.py 0 0 100%
merlin/datasets/ecommerce/dressipi/dataset.py 45 37 18%
merlin/datasets/ecommerce/dressipi/preprocessed/init.py 0 0 100%
merlin/datasets/ecommerce/large/init.py 0 0 100%
merlin/datasets/ecommerce/small/init.py 0 0 100%
merlin/datasets/ecommerce/transactions/init.py 0 0 100%
merlin/datasets/entertainment/init.py 2 0 100%
merlin/datasets/entertainment/movielens/1m-raw/init.py 0 0 100%
merlin/datasets/entertainment/movielens/1m-raw/ratings/init.py 0 0 100%
merlin/datasets/entertainment/movielens/1m/init.py 0 0 100%
merlin/datasets/entertainment/movielens/25m/init.py 0 0 100%
merlin/datasets/entertainment/movielens/100k/init.py 0 0 100%
merlin/datasets/entertainment/movielens/init.py 0 0 100%
merlin/datasets/entertainment/movielens/dataset.py 152 122 20%
merlin/datasets/entertainment/music_streaming/init.py 0 0 100%
merlin/datasets/social/init.py 0 0 100%
merlin/datasets/synthetic.py 147 8 95%
merlin/datasets/testing/init.py 0 0 100%
merlin/datasets/testing/sequence_testing/init.py 0 0 100%
merlin/models/init.py 2 0 100%
merlin/models/_version.py 354 205 42%
merlin/models/api.py 14 5 64%
merlin/models/config/init.py 0 0 100%
merlin/models/config/schema.py 62 0 100%
merlin/models/implicit/init.py 27 4 85%
merlin/models/io.py 15 0 100%
merlin/models/lightfm/init.py 23 0 100%
merlin/models/loader/init.py 0 0 100%
merlin/models/loader/backend.py 379 41 89%
merlin/models/loader/dataframe_iter.py 21 17 19%
merlin/models/loader/tf_utils.py 57 27 53%
merlin/models/loader/utils.py 40 15 62%
merlin/models/tf/init.py 70 0 100%
merlin/models/tf/blocks/init.py 0 0 100%
merlin/models/tf/blocks/cross.py 44 0 100%
merlin/models/tf/blocks/dlrm.py 49 2 96%
merlin/models/tf/blocks/experts.py 99 17 83%
merlin/models/tf/blocks/interaction.py 108 40 63%
merlin/models/tf/blocks/mlp.py 117 7 94%
merlin/models/tf/blocks/optimizer.py 173 12 93%
merlin/models/tf/blocks/retrieval/init.py 0 0 100%
merlin/models/tf/blocks/retrieval/base.py 175 62 65%
merlin/models/tf/blocks/retrieval/matrix_factorization.py 35 1 97%
merlin/models/tf/blocks/retrieval/two_tower.py 30 0 100%
merlin/models/tf/blocks/sampling/init.py 0 0 100%
merlin/models/tf/blocks/sampling/base.py 29 2 93%
merlin/models/tf/blocks/sampling/cross_batch.py 46 2 96%
merlin/models/tf/blocks/sampling/in_batch.py 35 0 100%
merlin/models/tf/blocks/sampling/queue.py 115 12 90%
merlin/models/tf/core/init.py 0 0 100%
merlin/models/tf/core/aggregation.py 241 45 81%
merlin/models/tf/core/base.py 242 50 79%
merlin/models/tf/core/combinators.py 426 53 88%
merlin/models/tf/core/encoder.py 175 28 84%
merlin/models/tf/core/index.py 106 16 85%
merlin/models/tf/core/prediction.py 50 1 98%
merlin/models/tf/core/tabular.py 280 29 90%
merlin/models/tf/distributed/init.py 0 0 100%
merlin/models/tf/distributed/backend.py 9 2 78%
merlin/models/tf/inputs/init.py 0 0 100%
merlin/models/tf/inputs/base.py 60 10 83%
merlin/models/tf/inputs/continuous.py 39 3 92%
merlin/models/tf/inputs/embedding.py 458 32 93%
merlin/models/tf/loader.py 268 94 65%
merlin/models/tf/losses/init.py 4 0 100%
merlin/models/tf/losses/base.py 9 0 100%
merlin/models/tf/losses/listwise.py 13 0 100%
merlin/models/tf/losses/pairwise.py 115 1 99%
merlin/models/tf/metrics/init.py 2 0 100%
merlin/models/tf/metrics/evaluation.py 105 48 54%
merlin/models/tf/metrics/topk.py 198 48 76%
merlin/models/tf/models/init.py 0 0 100%
merlin/models/tf/models/base.py 756 101 87%
merlin/models/tf/models/benchmark.py 16 0 100%
merlin/models/tf/models/ranking.py 67 3 96%
merlin/models/tf/models/retrieval.py 78 4 95%
merlin/models/tf/models/utils.py 10 1 90%
merlin/models/tf/outputs/init.py 0 0 100%
merlin/models/tf/outputs/base.py 123 17 86%
merlin/models/tf/outputs/classification.py 91 1 99%
merlin/models/tf/outputs/contrastive.py 147 10 93%
merlin/models/tf/outputs/regression.py 9 0 100%
merlin/models/tf/outputs/sampling/init.py 0 0 100%
merlin/models/tf/outputs/sampling/base.py 78 21 73%
merlin/models/tf/outputs/sampling/in_batch.py 37 1 97%
merlin/models/tf/outputs/sampling/popularity.py 27 1 96%
merlin/models/tf/outputs/topk.py 98 6 94%
merlin/models/tf/prediction_tasks/init.py 0 0 100%
merlin/models/tf/prediction_tasks/base.py 207 37 82%
merlin/models/tf/prediction_tasks/classification.py 68 17 75%
merlin/models/tf/prediction_tasks/multi.py 7 0 100%
merlin/models/tf/prediction_tasks/next_item.py 59 6 90%
merlin/models/tf/prediction_tasks/regression.py 35 2 94%
merlin/models/tf/prediction_tasks/retrieval.py 73 3 96%
merlin/models/tf/transformers/init.py 0 0 100%
merlin/models/tf/transformers/block.py 101 2 98%
merlin/models/tf/transformers/transforms.py 63 0 100%
merlin/models/tf/transforms/init.py 0 0 100%
merlin/models/tf/transforms/bias.py 111 9 92%
merlin/models/tf/transforms/features.py 435 36 92%
merlin/models/tf/transforms/negative_sampling.py 77 3 96%
merlin/models/tf/transforms/noise.py 43 1 98%
merlin/models/tf/transforms/regularization.py 17 1 94%
merlin/models/tf/transforms/sequence.py 282 42 85%
merlin/models/tf/transforms/tensor.py 158 13 92%
merlin/models/tf/typing.py 7 0 100%
merlin/models/tf/utils/init.py 0 0 100%
merlin/models/tf/utils/batch_utils.py 85 4 95%
merlin/models/tf/utils/repr_utils.py 69 4 94%
merlin/models/tf/utils/search_utils.py 34 22 35%
merlin/models/tf/utils/testing_utils.py 206 36 83%
merlin/models/tf/utils/tf_utils.py 209 42 80%
merlin/models/torch/init.py 12 0 100%
merlin/models/torch/block/init.py 0 0 100%
merlin/models/torch/block/base.py 167 32 81%
merlin/models/torch/block/mlp.py 38 5 87%
merlin/models/torch/dataset.py 68 5 93%
merlin/models/torch/features/init.py 0 0 100%
merlin/models/torch/features/base.py 4 0 100%
merlin/models/torch/features/continuous.py 22 0 100%
merlin/models/torch/features/embedding.py 165 12 93%
merlin/models/torch/features/tabular.py 65 8 88%
merlin/models/torch/losses.py 28 28 0%
merlin/models/torch/model/init.py 0 0 100%
merlin/models/torch/model/base.py 286 65 77%
merlin/models/torch/model/prediction_task.py 24 0 100%
merlin/models/torch/tabular/init.py 0 0 100%
merlin/models/torch/tabular/aggregation.py 75 0 100%
merlin/models/torch/tabular/base.py 247 39 84%
merlin/models/torch/tabular/transformations.py 67 3 96%
merlin/models/torch/typing.py 6 0 100%
merlin/models/torch/utils/init.py 0 0 100%
merlin/models/torch/utils/data_utils.py 117 117 0%
merlin/models/torch/utils/examples_utils.py 39 39 0%
merlin/models/torch/utils/torch_utils.py 80 22 72%
merlin/models/utils/init.py 0 0 100%
merlin/models/utils/constants.py 3 0 100%
merlin/models/utils/dataset.py 38 4 89%
merlin/models/utils/dependencies.py 26 19 27%
merlin/models/utils/doc_utils.py 10 0 100%
merlin/models/utils/example_utils.py 31 2 94%
merlin/models/utils/misc_utils.py 118 90 24%
merlin/models/utils/nvt_utils.py 27 24 11%
merlin/models/utils/registry.py 101 29 71%
merlin/models/utils/schema_utils.py 90 19 79%
merlin/models/xgb/init.py 124 4 97%

TOTAL 11581 2346 80%

=========================== short test summary info ============================
SKIPPED [1] tests/unit/datasets/test_advertising.py:20: No data-dir available, pass it through env variable $INPUT_DATA_DIR
SKIPPED [1] tests/unit/datasets/test_ecommerce.py:64: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP
SKIPPED [1] tests/unit/datasets/test_ecommerce.py:80: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP
SKIPPED [1] tests/unit/datasets/test_ecommerce.py:94: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP
SKIPPED [1] tests/unit/datasets/test_ecommerce.py:115: No data-dir available, pass it through env variable $INPUT_DATA_DIR
SKIPPED [3] tests/unit/datasets/test_entertainment.py:44: No data-dir available, pass it through env variable $INPUT_DATA_DIR
SKIPPED [5] ../../../.local/lib/python3.8/site-packages/tensorflow/python/framework/test_util.py:2746: Not a test.
========= 871 passed, 13 skipped, 1452 warnings in 1847.91s (0:30:47) ==========
___________________________________ summary ____________________________________
py38-gpu: commands succeeded
congratulations :)
Performing Post build task...
Match found for : : True
Logical operation result is TRUE
Running script : #!/bin/bash
cd /var/jenkins_home/
CUDA_VISIBLE_DEVICES=1 python test_res_push.py "https://api.GitHub.com/repos/NVIDIA-Merlin/models/issues/$ghprbPullId/comments" "/var/jenkins_home/jobs/$JOB_NAME/builds/$BUILD_NUMBER/log"
[merlin_models] $ /bin/bash /tmp/jenkins17423499489099404949.sh

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GitHub pull request #855 of commit c64d8bf5e3592d680f74b234548cd5b2f507714a, no merge conflicts.
Running as SYSTEM
Setting status of c64d8bf5e3592d680f74b234548cd5b2f507714a to PENDING with url http://merlin-infra1.nvidia.com:8080/job/merlin_models/1924/ and message: 'Pending'
Using context: Jenkins
Building on master in workspace /var/jenkins_home/workspace/merlin_models
using credential nvidia-merlin-bot
 > git rev-parse --is-inside-work-tree # timeout=10
Fetching changes from the remote Git repository
 > git config remote.origin.url https://github.com/NVIDIA-Merlin/models/ # timeout=10
Fetching upstream changes from https://github.com/NVIDIA-Merlin/models/
 > git --version # timeout=10
using GIT_ASKPASS to set credentials This is the bot credentials for our CI/CD
 > git fetch --tags --force --progress -- https://github.com/NVIDIA-Merlin/models/ +refs/pull/855/*:refs/remotes/origin/pr/855/* # timeout=10
 > git rev-parse c64d8bf5e3592d680f74b234548cd5b2f507714a^{commit} # timeout=10
Checking out Revision c64d8bf5e3592d680f74b234548cd5b2f507714a (detached)
 > git config core.sparsecheckout # timeout=10
 > git checkout -f c64d8bf5e3592d680f74b234548cd5b2f507714a # timeout=10
Commit message: "update notebook based on comments"
 > git rev-list --no-walk 76d4d68f80a9c3532ab9ad9c39c4d8636c9e782a # timeout=10
[merlin_models] $ /bin/bash /tmp/jenkins3572347515765437120.sh
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
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Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.8.2->jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (1.15.0)
GLOB sdist-make: /var/jenkins_home/workspace/merlin_models/models/setup.py
py38-gpu recreate: /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
py38-gpu installdeps: -rrequirements/dev.txt, tensorflow<2.10
WARNING: Discarding $PYTHONPATH from environment, to override specify PYTHONPATH in 'passenv' in your configuration.
py38-gpu inst: /var/jenkins_home/workspace/merlin_models/models/.tox/.tmp/package/4/merlin-models-0.9.0+63.gc64d8bf5.zip
WARNING: Discarding $PYTHONPATH from environment, to override specify PYTHONPATH in 'passenv' in your configuration.
py38-gpu installed: absl-py==1.2.0,aiohttp==3.8.1,aiosignal==1.2.0,alabaster==0.7.12,alembic==1.8.1,anyio==3.6.1,appdirs==1.4.4,argon2-cffi==21.3.0,argon2-cffi-bindings==21.2.0,astroid==2.5.6,asttokens==2.0.8,astunparse==1.6.3,asv==0.5.1,asvdb==0.4.2,async-timeout==4.0.2,attrs==22.1.0,autopage==0.5.1,awscli==1.27.14,Babel==2.10.3,backcall==0.2.0,beautifulsoup4==4.11.1,betterproto==1.2.5,black==20.8b1,bleach==5.0.1,bokeh==3.0.2,boto3==1.24.75,botocore==1.29.14,Brotli==1.0.9,build==0.9.0,cachetools==5.2.0,certifi==2019.11.28,cffi==1.15.1,chardet==3.0.4,charset-normalizer==2.1.1,check-manifest==0.48,clang==5.0,click==8.1.3,cliff==4.1.0,cloudpickle==2.2.0,cmaes==0.9.0,cmake==3.24.1.1,cmd2==2.4.2,colorama==0.4.4,colorlog==6.7.0,contourpy==1.0.5,coverage==6.5.0,cuda-python==11.7.1,cupy-cuda117==10.6.0,cycler==0.11.0,Cython==0.29.32,dask==2022.1.1,dbus-python==1.2.16,debugpy==1.6.3,decorator==5.1.1,defusedxml==0.7.1,dill==0.3.5.1,distlib==0.3.6,distributed==2022.5.1,distro==1.7.0,dm-tree==0.1.6,docker-pycreds==0.4.0,docutils==0.16,emoji==1.7.0,entrypoints==0.4,execnet==1.9.0,executing==1.0.0,faiss==1.7.2,faiss-gpu==1.7.2,fastai==2.7.9,fastapi==0.85.0,fastavro==1.6.1,fastcore==1.5.27,fastdownload==0.0.7,fastjsonschema==2.16.1,fastprogress==1.0.3,fastrlock==0.8,feast==0.19.4,fiddle==0.2.2,filelock==3.8.0,flake8==5.0.4,flatbuffers==1.12,fonttools==4.37.3,frozenlist==1.3.1,fsspec==2022.5.0,gast==0.4.0,gevent==21.12.0,geventhttpclient==2.0.2,gitdb==4.0.9,GitPython==3.1.27,google==3.0.0,google-api-core==2.10.1,google-auth==2.11.1,google-auth-oauthlib==0.4.6,google-pasta==0.2.0,googleapis-common-protos==1.52.0,graphviz==0.20.1,greenlet==1.1.3,grpcio==1.41.0,grpcio-channelz==1.49.0,grpcio-reflection==1.48.1,grpclib==0.4.3,h11==0.13.0,h2==4.1.0,h5py==3.7.0,HeapDict==1.0.1,horovod==0.26.1,hpack==4.0.0,httptools==0.5.0,hugectr2onnx==0.0.0,huggingface-hub==0.9.1,hyperframe==6.0.1,idna==2.8,imagesize==1.4.1,implicit==0.6.1,importlib-metadata==4.12.0,importlib-resources==5.9.0,iniconfig==1.1.1,interrogate==1.5.0,ipykernel==6.15.3,ipython==8.5.0,ipython-genutils==0.2.0,ipywidgets==7.7.0,isort==5.10.1,jedi==0.18.1,Jinja2==3.1.2,jmespath==1.0.1,joblib==1.2.0,json5==0.9.10,jsonschema==4.16.0,jupyter==1.0.0,jupyter-cache==0.4.3,jupyter-console==6.4.4,jupyter-core==4.11.1,jupyter-server==1.18.1,jupyter-server-mathjax==0.2.5,jupyter-sphinx==0.3.2,jupyter_client==7.3.5,jupyterlab==3.4.7,jupyterlab-pygments==0.2.2,jupyterlab-widgets==1.1.0,jupyterlab_server==2.15.1,keras==2.9.0,Keras-Preprocessing==1.1.2,kiwisolver==1.4.4,lazy-object-proxy==1.8.0,libclang==14.0.6,libcst==0.4.7,lightfm==1.16,lightgbm==3.3.2,linkify-it-py==1.0.3,llvmlite==0.39.1,locket==1.0.0,lxml==4.9.1,Mako==1.2.4,Markdown==3.4.1,markdown-it-py==1.1.0,MarkupSafe==2.1.1,matplotlib==3.6.0,matplotlib-inline==0.1.6,mccabe==0.7.0,mdit-py-plugins==0.2.8,merlin-core==0.6.0+1.g5926fcf,merlin-models==0.9.0+63.gc64d8bf5,merlin-systems==0.5.0+4.g15074ad,mistune==2.0.4,mmh3==3.0.0,mpi4py==3.1.3,msgpack==1.0.4,multidict==6.0.2,mypy==0.991,mypy-extensions==0.4.3,myst-nb==0.13.2,myst-parser==0.15.2,natsort==8.1.0,nbclassic==0.4.3,nbclient==0.6.8,nbconvert==7.0.0,nbdime==3.1.1,nbformat==5.5.0,nest-asyncio==1.5.5,ninja==1.10.2.3,notebook==6.4.12,notebook-shim==0.1.0,numba==0.56.2,numpy==1.22.4,nvidia-pyindex==1.0.9,# Editable install with no version control (nvtabular==1.4.0+8.g95e12d347),-e /usr/local/lib/python3.8/dist-packages,nvtx==0.2.5,oauthlib==3.2.1,oldest-supported-numpy==2022.8.16,onnx==1.12.0,onnxruntime==1.11.1,opt-einsum==3.3.0,optuna==3.0.3,packaging==21.3,pandas==1.3.5,pandavro==1.5.2,pandocfilters==1.5.0,parso==0.8.3,partd==1.3.0,pathspec==0.10.2,pathtools==0.1.2,pbr==5.11.0,pep517==0.13.0,pexpect==4.8.0,pickleshare==0.7.5,Pillow==9.2.0,pkgutil_resolve_name==1.3.10,platformdirs==2.5.2,plotly==5.11.0,pluggy==1.0.0,prettytable==3.5.0,prometheus-client==0.14.1,promise==2.3,prompt-toolkit==3.0.31,proto-plus==1.19.6,protobuf==3.19.5,psutil==5.9.2,ptyprocess==0.7.0,pure-eval==0.2.2,py==1.11.0,pyarrow==7.0.0,pyasn1==0.4.8,pyasn1-modules==0.2.8,pybind11==2.10.0,pycodestyle==2.9.1,pycparser==2.21,pydantic==1.10.2,pydot==1.4.2,pyflakes==2.5.0,Pygments==2.13.0,PyGObject==3.36.0,pynvml==11.4.1,pyparsing==3.0.9,pyperclip==1.8.2,pyrsistent==0.18.1,pytest==7.1.3,pytest-cov==4.0.0,pytest-xdist==3.0.2,python-apt==2.0.0+ubuntu0.20.4.8,python-dateutil==2.8.2,python-dotenv==0.21.0,python-rapidjson==1.8,pytz==2022.2.1,PyYAML==5.4.1,pyzmq==24.0.0,qtconsole==5.4.0,QtPy==2.3.0,regex==2022.9.13,requests==2.22.0,requests-oauthlib==1.3.1,requests-unixsocket==0.2.0,rsa==4.7.2,s3fs==2022.2.0,s3transfer==0.6.0,sacremoses==0.0.53,scikit-build==0.15.0,scikit-learn==1.1.2,scipy==1.8.1,seedir==0.3.0,Send2Trash==1.8.0,sentry-sdk==1.9.8,setproctitle==1.3.2,setuptools-scm==7.0.5,shortuuid==1.0.9,six==1.15.0,sklearn==0.0,smmap==5.0.0,sniffio==1.3.0,snowballstemmer==2.2.0,sortedcontainers==2.4.0,soupsieve==2.3.2.post1,Sphinx==5.3.0,sphinx-multiversion==0.2.4,sphinx-togglebutton==0.3.1,sphinx_external_toc==0.3.0,sphinxcontrib-applehelp==1.0.2,sphinxcontrib-copydirs @ git+https://github.com/mikemckiernan/sphinxcontrib-copydirs.git@bd8c5d79b3f91cf5f1bb0d6995aeca3fe84b670e,sphinxcontrib-devhelp==1.0.2,sphinxcontrib-htmlhelp==2.0.0,sphinxcontrib-jsmath==1.0.1,sphinxcontrib-qthelp==1.0.3,sphinxcontrib-serializinghtml==1.1.5,SQLAlchemy==1.4.44,stack-data==0.5.0,starlette==0.20.4,stevedore==4.1.1,stringcase==1.2.0,supervisor==4.1.0,tabulate==0.8.10,tblib==1.7.0,tdqm==0.0.1,tenacity==8.0.1,tensorboard==2.9.1,tensorboard-data-server==0.6.1,tensorboard-plugin-wit==1.8.1,tensorflow==2.9.2,tensorflow-estimator==2.9.0,tensorflow-gpu==2.9.2,tensorflow-io-gcs-filesystem==0.27.0,tensorflow-metadata==1.10.0,termcolor==2.0.1,terminado==0.15.0,testbook==0.4.2,threadpoolctl==3.1.0,tinycss2==1.1.1,tokenizers==0.10.3,toml==0.10.2,tomli==2.0.1,toolz==0.12.0,torch==1.12.1+cu113,torchmetrics==0.3.2,tornado==6.2,tox==3.26.0,tqdm==4.64.1,traitlets==5.4.0,transformers==4.12.0,transformers4rec==0.1.12+2.gbcc939255,treelite==2.3.0,treelite-runtime==2.3.0,tritonclient==2.25.0,typed-ast==1.5.4,typing-inspect==0.8.0,typing_extensions==4.3.0,uc-micro-py==1.0.1,urllib3==1.26.12,uvicorn==0.18.3,uvloop==0.17.0,versioneer==0.20,virtualenv==20.16.5,wandb==0.13.3,watchfiles==0.17.0,wcwidth==0.2.5,webencodings==0.5.1,websocket-client==1.4.1,websockets==10.3,Werkzeug==2.2.2,widgetsnbextension==3.6.0,wrapt==1.12.1,xgboost==1.6.2,xyzservices==2022.9.0,yarl==1.8.1,zict==2.2.0,zipp==3.8.1,zope.event==4.5.0,zope.interface==5.4.0
py38-gpu run-test-pre: PYTHONHASHSEED='3904827835'
py38-gpu run-test: commands[0] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/core.git
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Collecting git+https://github.com/NVIDIA-Merlin/core.git
  Cloning https://github.com/NVIDIA-Merlin/core.git to /tmp/pip-req-build-icpsyooq
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/core.git /tmp/pip-req-build-icpsyooq
  Resolved https://github.com/NVIDIA-Merlin/core.git to commit 72f967a00a9f107b328a26afbbfe63512a5a5da9
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: tensorflow-metadata>=1.2.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+18.g72f967a) (1.10.0)
Requirement already satisfied: dask>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+18.g72f967a) (2022.3.0)
Requirement already satisfied: betterproto<2.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+18.g72f967a) (1.2.5)
Requirement already satisfied: distributed>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+18.g72f967a) (2022.3.0)
Requirement already satisfied: numba>=0.54 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+18.g72f967a) (0.55.1)
Requirement already satisfied: packaging in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+18.g72f967a) (21.3)
Requirement already satisfied: protobuf>=3.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+18.g72f967a) (3.19.5)
Requirement already satisfied: pyarrow>=5.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+18.g72f967a) (7.0.0)
Requirement already satisfied: pandas<1.4.0dev0,>=1.2.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+18.g72f967a) (1.3.5)
Requirement already satisfied: fsspec==2022.5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+18.g72f967a) (2022.5.0)
Requirement already satisfied: tqdm>=4.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+18.g72f967a) (4.64.1)
Requirement already satisfied: stringcase in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core==0.8.0+18.g72f967a) (1.2.0)
Requirement already satisfied: grpclib in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core==0.8.0+18.g72f967a) (0.4.3)
Requirement already satisfied: toolz>=0.8.2 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core==0.8.0+18.g72f967a) (0.12.0)
Requirement already satisfied: partd>=0.3.10 in /var/jenkins_home/.local/lib/python3.8/site-packages/partd-1.2.0-py3.8.egg (from dask>=2022.3.0->merlin-core==0.8.0+18.g72f967a) (1.2.0)
Requirement already satisfied: pyyaml>=5.3.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/PyYAML-5.4.1-py3.8-linux-x86_64.egg (from dask>=2022.3.0->merlin-core==0.8.0+18.g72f967a) (5.4.1)
Requirement already satisfied: cloudpickle>=1.1.1 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core==0.8.0+18.g72f967a) (2.2.0)
Requirement already satisfied: tblib>=1.6.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/tblib-1.7.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+18.g72f967a) (1.7.0)
Requirement already satisfied: msgpack>=0.6.0 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+18.g72f967a) (1.0.4)
Requirement already satisfied: zict>=0.1.3 in /var/jenkins_home/.local/lib/python3.8/site-packages/zict-2.0.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+18.g72f967a) (2.0.0)
Requirement already satisfied: click>=6.6 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+18.g72f967a) (8.1.3)
Requirement already satisfied: sortedcontainers!=2.0.0,!=2.0.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/sortedcontainers-2.4.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+18.g72f967a) (2.4.0)
Requirement already satisfied: tornado>=6.0.3 in ./.tox/py38-gpu/lib/python3.8/site-packages (from distributed>=2022.3.0->merlin-core==0.8.0+18.g72f967a) (6.2)
Requirement already satisfied: jinja2 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+18.g72f967a) (3.1.2)
Requirement already satisfied: psutil>=5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/psutil-5.8.0-py3.8-linux-x86_64.egg (from distributed>=2022.3.0->merlin-core==0.8.0+18.g72f967a) (5.8.0)
Requirement already satisfied: numpy<1.22,>=1.18 in /var/jenkins_home/.local/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+18.g72f967a) (1.20.3)
Requirement already satisfied: setuptools in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+18.g72f967a) (65.5.1)
Requirement already satisfied: llvmlite<0.39,>=0.38.0rc1 in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+18.g72f967a) (0.38.1)
Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in /usr/local/lib/python3.8/dist-packages (from packaging->merlin-core==0.8.0+18.g72f967a) (3.0.9)
Requirement already satisfied: pytz>=2017.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+18.g72f967a) (2022.2.1)
Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+18.g72f967a) (2.8.2)
Requirement already satisfied: absl-py<2.0.0,>=0.9 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core==0.8.0+18.g72f967a) (1.2.0)
Requirement already satisfied: googleapis-common-protos<2,>=1.52.0 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core==0.8.0+18.g72f967a) (1.52.0)
Requirement already satisfied: locket in /var/jenkins_home/.local/lib/python3.8/site-packages/locket-0.2.1-py3.8.egg (from partd>=0.3.10->dask>=2022.3.0->merlin-core==0.8.0+18.g72f967a) (0.2.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.7.3->pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+18.g72f967a) (1.15.0)
Requirement already satisfied: heapdict in /var/jenkins_home/.local/lib/python3.8/site-packages/HeapDict-1.0.1-py3.8.egg (from zict>=0.1.3->distributed>=2022.3.0->merlin-core==0.8.0+18.g72f967a) (1.0.1)
Requirement already satisfied: multidict in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core==0.8.0+18.g72f967a) (6.0.2)
Requirement already satisfied: h2<5,>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core==0.8.0+18.g72f967a) (4.1.0)
Requirement already satisfied: MarkupSafe>=2.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from jinja2->distributed>=2022.3.0->merlin-core==0.8.0+18.g72f967a) (2.0.1)
Requirement already satisfied: hpack<5,>=4.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core==0.8.0+18.g72f967a) (4.0.0)
Requirement already satisfied: hyperframe<7,>=6.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core==0.8.0+18.g72f967a) (6.0.1)
Building wheels for collected packages: merlin-core
  Building wheel for merlin-core (pyproject.toml): started
  Building wheel for merlin-core (pyproject.toml): finished with status 'done'
  Created wheel for merlin-core: filename=merlin_core-0.8.0+18.g72f967a-py3-none-any.whl size=118899 sha256=85de7403317831ed9fd76e97eeb580f98bd00753e71360d9823203705725b1df
  Stored in directory: /tmp/pip-ephem-wheel-cache-dvzy3_m4/wheels/c8/38/16/a6968787eafcec5fa772148af8408b089562f71af0752e8e84
Successfully built merlin-core
Installing collected packages: merlin-core
  Attempting uninstall: merlin-core
    Found existing installation: merlin-core 0.3.0+12.g78ecddd
    Not uninstalling merlin-core at /var/jenkins_home/.local/lib/python3.8/site-packages, outside environment /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
    Can't uninstall 'merlin-core'. No files were found to uninstall.
Successfully installed merlin-core-0.8.0+18.g72f967a
py38-gpu run-test: commands[1] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/nvtabular.git
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Collecting git+https://github.com/NVIDIA-Merlin/nvtabular.git
  Cloning https://github.com/NVIDIA-Merlin/nvtabular.git to /tmp/pip-req-build-z6xklony
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/nvtabular.git /tmp/pip-req-build-z6xklony
  Resolved https://github.com/NVIDIA-Merlin/nvtabular.git to commit e5b7351deb9e4885c4038aa0bbc9f146d8477a0e
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: merlin-core>=0.2.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from nvtabular==1.6.0+6.ge5b7351d) (0.8.0+18.g72f967a)
Requirement already satisfied: scipy in /usr/local/lib/python3.8/dist-packages (from nvtabular==1.6.0+6.ge5b7351d) (1.8.1)
Collecting merlin-dataloader>=0.0.2
  Downloading merlin-dataloader-0.0.2.tar.gz (44 kB)
     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 44.1/44.1 kB 1.8 MB/s eta 0:00:00
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
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Building wheels for collected packages: nvtabular, merlin-dataloader
  Building wheel for nvtabular (pyproject.toml): started
  Building wheel for nvtabular (pyproject.toml): finished with status 'done'
  Created wheel for nvtabular: filename=nvtabular-1.6.0+6.ge5b7351d-cp38-cp38-linux_x86_64.whl size=257597 sha256=c6cdebe4259eebf7d02d7e44354528a823976ba8785e218f35151fd919812952
  Stored in directory: /tmp/pip-ephem-wheel-cache-0nh5lw01/wheels/8f/d9/f9/30f2cdc5bf8787fae6fdfe55afd6e1b493e619ec32c32ec40b
  Building wheel for merlin-dataloader (pyproject.toml): started
  Building wheel for merlin-dataloader (pyproject.toml): finished with status 'done'
  Created wheel for merlin-dataloader: filename=merlin_dataloader-0.0.2-py3-none-any.whl size=29203 sha256=8d7b266bbdb03307133fb6f339e876bda00ed57b998d8e8f75fba477487fd70c
  Stored in directory: /tmp/pip-ephem-wheel-cache-0nh5lw01/wheels/76/ef/ed/cb880e3ef5192ec5940e26fd9442247b569fb0cf8602f97137
Successfully built nvtabular merlin-dataloader
Installing collected packages: merlin-dataloader, nvtabular
  Attempting uninstall: nvtabular
    Found existing installation: nvtabular 1.1.1
    Not uninstalling nvtabular at /var/jenkins_home/.local/lib/python3.8/site-packages, outside environment /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
    Can't uninstall 'nvtabular'. No files were found to uninstall.
Successfully installed merlin-dataloader-0.0.2 nvtabular-1.6.0+6.ge5b7351d
py38-gpu run-test: commands[2] | python -m pytest --cov-report term --cov merlin -rxs tests/unit
============================= test session starts ==============================
platform linux -- Python 3.8.10, pytest-7.1.3, pluggy-1.0.0
cachedir: .tox/py38-gpu/.pytest_cache
rootdir: /var/jenkins_home/workspace/merlin_models/models, configfile: pyproject.toml
plugins: anyio-3.5.0, xdist-3.0.2, cov-4.0.0
collected 884 items

tests/unit/config/test_schema.py .... [ 0%]
tests/unit/datasets/test_advertising.py .s [ 0%]
tests/unit/datasets/test_ecommerce.py ..sss.s [ 1%]
tests/unit/datasets/test_entertainment.py ....sss. [ 2%]
tests/unit/datasets/test_social.py . [ 2%]
tests/unit/datasets/test_synthetic.py .......... [ 3%]
tests/unit/implicit/test_implicit.py . [ 3%]
tests/unit/lightfm/test_lightfm.py . [ 3%]
tests/unit/tf/test_core.py ...... [ 4%]
tests/unit/tf/test_loader.py ................ [ 6%]
tests/unit/tf/test_public_api.py . [ 6%]
tests/unit/tf/blocks/test_cross.py ........... [ 7%]
tests/unit/tf/blocks/test_dlrm.py .......... [ 8%]
tests/unit/tf/blocks/test_interactions.py ... [ 9%]
tests/unit/tf/blocks/test_mlp.py ....................................... [ 13%]
............................ [ 16%]
tests/unit/tf/blocks/test_optimizer.py s................................ [ 20%]
..................... [ 22%]
tests/unit/tf/blocks/retrieval/test_base.py . [ 22%]
tests/unit/tf/blocks/retrieval/test_matrix_factorization.py .. [ 23%]
tests/unit/tf/blocks/retrieval/test_two_tower.py ............ [ 24%]
tests/unit/tf/blocks/sampling/test_cross_batch.py . [ 24%]
tests/unit/tf/blocks/sampling/test_in_batch.py . [ 24%]
tests/unit/tf/core/test_aggregation.py ......... [ 25%]
tests/unit/tf/core/test_base.py .. [ 26%]
tests/unit/tf/core/test_combinators.py s..................... [ 28%]
tests/unit/tf/core/test_encoder.py .. [ 28%]
tests/unit/tf/core/test_index.py ... [ 29%]
tests/unit/tf/core/test_prediction.py .. [ 29%]
tests/unit/tf/core/test_tabular.py ...... [ 29%]
tests/unit/tf/examples/test_01_getting_started.py F [ 30%]
tests/unit/tf/examples/test_02_dataschema.py F [ 30%]
tests/unit/tf/examples/test_03_exploring_different_models.py F [ 30%]
tests/unit/tf/examples/test_04_export_ranking_models.py F [ 30%]
tests/unit/tf/examples/test_05_export_retrieval_model.py . [ 30%]
tests/unit/tf/examples/test_06_advanced_own_architecture.py . [ 30%]
tests/unit/tf/examples/test_07_train_traditional_models.py . [ 30%]
tests/unit/tf/examples/test_usecase_accelerate_training_by_lazyadam.py . [ 30%]
[ 30%]
tests/unit/tf/examples/test_usecase_data_parallel.py . [ 30%]
tests/unit/tf/examples/test_usecase_ecommerce_session_based.py . [ 31%]
tests/unit/tf/examples/test_usecase_incremental_training_layer_freezing.py . [ 31%]
[ 31%]
tests/unit/tf/examples/test_usecase_pretrained_embeddings.py . [ 31%]
tests/unit/tf/examples/test_usecase_retrieval_with_hpo.py . [ 31%]
tests/unit/tf/examples/test_usecase_transformers_next_item_prediction.py . [ 31%]
[ 31%]
tests/unit/tf/horovod/test_horovod.py ... [ 31%]
tests/unit/tf/inputs/test_base.py . [ 32%]
tests/unit/tf/inputs/test_continuous.py ........ [ 32%]
tests/unit/tf/inputs/test_embedding.py ................................. [ 36%]
........ [ 37%]
tests/unit/tf/inputs/test_tabular.py .................. [ 39%]
tests/unit/tf/layers/test_queue.py .............. [ 41%]
tests/unit/tf/losses/test_losses.py ....................... [ 43%]
tests/unit/tf/metrics/test_metrics_popularity.py ..... [ 44%]
tests/unit/tf/metrics/test_metrics_topk.py ......................... [ 47%]
tests/unit/tf/models/test_base.py s......................... [ 50%]
tests/unit/tf/models/test_benchmark.py .. [ 50%]
tests/unit/tf/models/test_ranking.py .................................. [ 54%]
tests/unit/tf/models/test_retrieval.py ................................. [ 57%]
........................................... [ 62%]
tests/unit/tf/outputs/test_base.py ...... [ 63%]
tests/unit/tf/outputs/test_classification.py ...... [ 64%]
tests/unit/tf/outputs/test_contrastive.py .............. [ 65%]
tests/unit/tf/outputs/test_regression.py .. [ 65%]
tests/unit/tf/outputs/test_sampling.py .... [ 66%]
tests/unit/tf/outputs/test_topk.py . [ 66%]
tests/unit/tf/prediction_tasks/test_classification.py .. [ 66%]
tests/unit/tf/prediction_tasks/test_multi_task.py ................ [ 68%]
tests/unit/tf/prediction_tasks/test_next_item.py ..... [ 69%]
tests/unit/tf/prediction_tasks/test_regression.py ..... [ 69%]
tests/unit/tf/prediction_tasks/test_retrieval.py . [ 69%]
tests/unit/tf/prediction_tasks/test_sampling.py ...... [ 70%]
tests/unit/tf/transformers/test_block.py ...................... [ 72%]
tests/unit/tf/transformers/test_transforms.py .......... [ 74%]
tests/unit/tf/transforms/test_bias.py .. [ 74%]
tests/unit/tf/transforms/test_features.py s............................. [ 77%]
.......................s...... [ 81%]
tests/unit/tf/transforms/test_negative_sampling.py ......... [ 82%]
tests/unit/tf/transforms/test_noise.py ..... [ 82%]
tests/unit/tf/transforms/test_sequence.py .................... [ 84%]
tests/unit/tf/transforms/test_tensor.py ... [ 85%]
tests/unit/tf/utils/test_batch.py .... [ 85%]
tests/unit/tf/utils/test_dataset.py .. [ 85%]
tests/unit/tf/utils/test_tf_utils.py ..... [ 86%]
tests/unit/torch/test_dataset.py ......... [ 87%]
tests/unit/torch/test_public_api.py . [ 87%]
tests/unit/torch/block/test_base.py .... [ 88%]
tests/unit/torch/block/test_mlp.py . [ 88%]
tests/unit/torch/features/test_continuous.py .. [ 88%]
tests/unit/torch/features/test_embedding.py .............. [ 90%]
tests/unit/torch/features/test_tabular.py .... [ 90%]
tests/unit/torch/model/test_head.py ............ [ 91%]
tests/unit/torch/model/test_model.py .. [ 92%]
tests/unit/torch/tabular/test_aggregation.py ........ [ 92%]
tests/unit/torch/tabular/test_tabular.py ... [ 93%]
tests/unit/torch/tabular/test_transformations.py ....... [ 94%]
tests/unit/utils/test_schema_utils.py ................................ [ 97%]
tests/unit/xgb/test_xgboost.py .................... [100%]

=================================== FAILURES ===================================
_______________________ test_example_01_getting_started ________________________

tb = <testbook.client.TestbookNotebookClient object at 0x7eff20357460>

@testbook(REPO_ROOT / "examples/01-Getting-started.ipynb", execute=False)
def test_example_01_getting_started(tb):
    tb.inject(
        """
        from unittest.mock import patch
        from merlin.datasets.synthetic import generate_data
        mock_train, mock_valid = generate_data(
            input="movielens-1m",
            num_rows=1000,
            set_sizes=(0.8, 0.2)
        )
        p1 = patch(
            "merlin.datasets.entertainment.get_movielens",
            return_value=[mock_train, mock_valid]
        )
        p1.start()
        """
    )
  tb.execute()

tests/unit/tf/examples/test_01_getting_started.py:40:


../../../.local/lib/python3.8/site-packages/testbook/client.py:147: in execute
super().execute_cell(cell, index)
../../../.local/lib/python3.8/site-packages/nbclient/util.py:84: in wrapped
return just_run(coro(*args, **kwargs))
../../../.local/lib/python3.8/site-packages/nbclient/util.py:62: in just_run
return loop.run_until_complete(coro)
/usr/lib/python3.8/asyncio/base_events.py:616: in run_until_complete
return future.result()
../../../.local/lib/python3.8/site-packages/nbclient/client.py:965: in async_execute_cell
await self._check_raise_for_error(cell, cell_index, exec_reply)


self = <testbook.client.TestbookNotebookClient object at 0x7eff20357460>
cell = {'cell_type': 'code', 'execution_count': 3, 'id': '60653f70', 'metadata': {'execution': {'iopub.status.busy': '2022-11...0']}], 'source': 'import os\nimport merlin.models.tf as mm\n\nfrom merlin.datasets.entertainment import get_movielens'}
cell_index = 3
exec_reply = {'buffers': [], 'content': {'ename': 'FailedPreconditionError', 'engine_info': {'engine_id': -1, 'engine_uuid': '12069...e, 'engine': '1206943d-b8ef-4695-ad26-494e1589733e', 'started': '2022-11-22T15:44:29.259322Z', 'status': 'error'}, ...}

async def _check_raise_for_error(
    self, cell: NotebookNode, cell_index: int, exec_reply: t.Optional[t.Dict]
) -> None:

    if exec_reply is None:
        return None

    exec_reply_content = exec_reply['content']
    if exec_reply_content['status'] != 'error':
        return None

    cell_allows_errors = (not self.force_raise_errors) and (
        self.allow_errors
        or exec_reply_content.get('ename') in self.allow_error_names
        or "raises-exception" in cell.metadata.get("tags", [])
    )
    await run_hook(self.on_cell_error, cell=cell, cell_index=cell_index)
    if not cell_allows_errors:
      raise CellExecutionError.from_cell_and_msg(cell, exec_reply_content)

E nbclient.exceptions.CellExecutionError: An error occurred while executing the following cell:
E ------------------
E import os
E import merlin.models.tf as mm
E
E from merlin.datasets.entertainment import get_movielens
E ------------------
E
E �[0;31m---------------------------------------------------------------------------�[0m
E �[0;31mFailedPreconditionError�[0m Traceback (most recent call last)
E Cell �[0;32mIn [3], line 2�[0m
E �[1;32m 1�[0m �[38;5;28;01mimport�[39;00m �[38;5;21;01mos�[39;00m
E �[0;32m----> 2�[0m �[38;5;28;01mimport�[39;00m �[38;5;21;01mmerlin�[39;00m�[38;5;21;01m.�[39;00m�[38;5;21;01mmodels�[39;00m�[38;5;21;01m.�[39;00m�[38;5;21;01mtf�[39;00m �[38;5;28;01mas�[39;00m �[38;5;21;01mmm�[39;00m
E �[1;32m 4�[0m �[38;5;28;01mfrom�[39;00m �[38;5;21;01mmerlin�[39;00m�[38;5;21;01m.�[39;00m�[38;5;21;01mdatasets�[39;00m�[38;5;21;01m.�[39;00m�[38;5;21;01mentertainment�[39;00m �[38;5;28;01mimport�[39;00m get_movielens
E
E File �[0;32m~/workspace/merlin_models/models/merlin/models/tf/init.py:105�[0m
E �[1;32m 103�[0m �[38;5;28;01mfrom�[39;00m �[38;5;21;01mmerlin�[39;00m�[38;5;21;01m.�[39;00m�[38;5;21;01mmodels�[39;00m�[38;5;21;01m.�[39;00m�[38;5;21;01mtf�[39;00m�[38;5;21;01m.�[39;00m�[38;5;21;01mmodels�[39;00m�[38;5;21;01m.�[39;00m�[38;5;21;01mbase�[39;00m �[38;5;28;01mimport�[39;00m BaseModel, Model, RetrievalModel, RetrievalModelV2
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E �[1;32m 34�[0m �[38;5;124;03m"""Prediction-task for item-retrieval.�[39;00m
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E File �[0;32m~/workspace/merlin_models/models/merlin/models/tf/prediction_tasks/retrieval.py:65�[0m, in �[0;36mItemRetrievalTask�[0;34m()�[0m
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E File �[0;32m~/.local/lib/python3.8/site-packages/keras/engine/base_layer.py:665�[0m, in �[0;36mLayer.add_weight�[0;34m(self, name, shape, dtype, initializer, regularizer, trainable, constraint, use_resource, synchronization, aggregation, **kwargs)�[0m
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E �[1;32m 668�[0m �[43m �[49m�[38;5;66;43;03m# TODO(allenl): a make_variable equivalent should be added as a�[39;49;00m
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E �[1;32m 671�[0m �[43m �[49m�[38;5;66;43;03m# Manage errors in Layer rather than Trackable.�[39;49;00m
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E �[1;32m 673�[0m �[43m �[49m�[43minitializer�[49m�[38;5;241;43m=�[39;49m�[43minitializer�[49m�[43m,�[49m
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E �[1;32m 682�[0m �[38;5;28;01mif�[39;00m regularizer �[38;5;129;01mis�[39;00m �[38;5;129;01mnot�[39;00m �[38;5;28;01mNone�[39;00m:
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E
E File �[0;32m~/.local/lib/python3.8/site-packages/tensorflow/python/training/tracking/base.py:873�[0m, in �[0;36mTrackable._add_variable_with_custom_getter�[0;34m(self, name, shape, dtype, initializer, getter, overwrite, **kwargs_for_getter)�[0m
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E File �[0;32m~/.local/lib/python3.8/site-packages/keras/engine/base_layer_utils.py:126�[0m, in �[0;36mmake_variable�[0;34m(name, shape, dtype, initializer, trainable, caching_device, validate_shape, constraint, use_resource, collections, synchronization, aggregation, partitioner, layout)�[0m
E �[1;32m 119�[0m use_resource �[38;5;241m=�[39m �[38;5;28;01mTrue�[39;00m
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E FailedPreconditionError: Failed to allocate scratch buffer for device 0

../../../.local/lib/python3.8/site-packages/nbclient/client.py:862: CellExecutionError
----------------------------- Captured stderr call -----------------------------
2022-11-22 15:44:31.939546: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: AVX2 FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
2022-11-22 15:44:35.409977: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 0
2022-11-22 15:44:35.410082: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 8139 MB memory: -> device: 0, name: Tesla P100-DGXS-16GB, pci bus id: 0000:07:00.0, compute capability: 6.0
2022-11-22 15:44:35.410808: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 1
2022-11-22 15:44:35.410868: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:1 with 13851 MB memory: -> device: 1, name: Tesla P100-DGXS-16GB, pci bus id: 0000:08:00.0, compute capability: 6.0
2022-11-22 15:44:35.411457: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 2
2022-11-22 15:44:35.411508: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:2 with 13851 MB memory: -> device: 2, name: Tesla P100-DGXS-16GB, pci bus id: 0000:0e:00.0, compute capability: 6.0
2022-11-22 15:44:35.412077: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 3
2022-11-22 15:44:35.412130: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:3 with 13851 MB memory: -> device: 3, name: Tesla P100-DGXS-16GB, pci bus id: 0000:0f:00.0, compute capability: 6.0
2022-11-22 15:44:35.423668: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:288] gpu_async_0 cuMemAllocAsync failed to allocate 1028 bytes: CUDA error: out of memory (CUDA_ERROR_OUT_OF_MEMORY)
Reported by CUDA: Free memory/Total memory: 6881280/17069309952
2022-11-22 15:44:35.423712: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:293] Stats: Limit: 8534360064
InUse: 0
MaxInUse: 0
NumAllocs: 0
MaxAllocSize: 0
Reserved: 0
PeakReserved: 0
LargestFreeBlock: 0

2022-11-22 15:44:35.423722: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:56] Histogram of current allocation: (allocation_size_in_bytes, nb_allocation_of_that_sizes), ...;
Error in atexit._run_exitfuncs:
Traceback (most recent call last):
File "/usr/lib/python3.8/logging/init.py", line 2127, in shutdown
h.close()
File "/usr/local/lib/python3.8/dist-packages/absl/logging/init.py", line 934, in close
self.stream.close()
File "/usr/local/lib/python3.8/dist-packages/ipykernel/iostream.py", line 438, in close
self.watch_fd_thread.join()
AttributeError: 'OutStream' object has no attribute 'watch_fd_thread'
_______________________ test_example_02_nvt_integration ________________________

self = <testbook.client.TestbookNotebookClient object at 0x7eff20071850>
cell = [50], kwargs = {}, cell_indexes = [50], executed_cells = [], idx = 50

def execute_cell(self, cell, **kwargs) -> Union[Dict, List[Dict]]:
    """
    Executes a cell or list of cells
    """
    if isinstance(cell, slice):
        start, stop = self._cell_index(cell.start), self._cell_index(cell.stop)
        if cell.step is not None:
            raise TestbookError('testbook does not support step argument')

        cell = range(start, stop + 1)
    elif isinstance(cell, str) or isinstance(cell, int):
        cell = [cell]

    cell_indexes = cell

    if all(isinstance(x, str) for x in cell):
        cell_indexes = [self._cell_index(tag) for tag in cell]

    executed_cells = []
    for idx in cell_indexes:
        try:
          cell = super().execute_cell(self.nb['cells'][idx], idx, **kwargs)

../../../.local/lib/python3.8/site-packages/testbook/client.py:133:


args = (<testbook.client.TestbookNotebookClient object at 0x7eff20071850>, {'id': '71e14f59', 'cell_type': 'code', 'metadata'...\x1b[0m: CUDA error encountered at: ../src/bitmask/null_mask.cu:93: 2 cudaErrorMemoryAllocation out of memory']}]}, 50)
kwargs = {}

def wrapped(*args, **kwargs):
  return just_run(coro(*args, **kwargs))

../../../.local/lib/python3.8/site-packages/nbclient/util.py:84:


coro = <coroutine object NotebookClient.async_execute_cell at 0x7efdc00d3ac0>

def just_run(coro: Awaitable) -> Any:
    """Make the coroutine run, even if there is an event loop running (using nest_asyncio)"""
    # original from vaex/asyncio.py
    loop = asyncio._get_running_loop()
    if loop is None:
        had_running_loop = False
        try:
            loop = asyncio.get_event_loop()
        except RuntimeError:
            # we can still get 'There is no current event loop in ...'
            loop = asyncio.new_event_loop()
            asyncio.set_event_loop(loop)
    else:
        had_running_loop = True
    if had_running_loop:
        # if there is a running loop, we patch using nest_asyncio
        # to have reentrant event loops
        check_ipython()
        import nest_asyncio

        nest_asyncio.apply()
        check_patch_tornado()
  return loop.run_until_complete(coro)

../../../.local/lib/python3.8/site-packages/nbclient/util.py:62:


self = <_UnixSelectorEventLoop running=False closed=False debug=False>
future = <Task finished name='Task-24' coro=<NotebookClient.async_execute_cell() done, defined at /var/jenkins_home/.local/lib/...RuntimeError: CUDA error encountered at: ../src/bitmask/null_mask.cu:93: 2 cudaErrorMemoryAllocation out of memory\n')>

def run_until_complete(self, future):
    """Run until the Future is done.

    If the argument is a coroutine, it is wrapped in a Task.

    WARNING: It would be disastrous to call run_until_complete()
    with the same coroutine twice -- it would wrap it in two
    different Tasks and that can't be good.

    Return the Future's result, or raise its exception.
    """
    self._check_closed()
    self._check_running()

    new_task = not futures.isfuture(future)
    future = tasks.ensure_future(future, loop=self)
    if new_task:
        # An exception is raised if the future didn't complete, so there
        # is no need to log the "destroy pending task" message
        future._log_destroy_pending = False

    future.add_done_callback(_run_until_complete_cb)
    try:
        self.run_forever()
    except:
        if new_task and future.done() and not future.cancelled():
            # The coroutine raised a BaseException. Consume the exception
            # to not log a warning, the caller doesn't have access to the
            # local task.
            future.exception()
        raise
    finally:
        future.remove_done_callback(_run_until_complete_cb)
    if not future.done():
        raise RuntimeError('Event loop stopped before Future completed.')
  return future.result()

/usr/lib/python3.8/asyncio/base_events.py:616:


self = <testbook.client.TestbookNotebookClient object at 0x7eff20071850>
cell = {'id': '71e14f59', 'cell_type': 'code', 'metadata': {'execution': {'iopub.status.busy': '2022-11-22T15:44:42.140650Z',...Error\x1b[0m: CUDA error encountered at: ../src/bitmask/null_mask.cu:93: 2 cudaErrorMemoryAllocation out of memory']}]}
cell_index = 50, execution_count = None, store_history = True

async def async_execute_cell(
    self,
    cell: NotebookNode,
    cell_index: int,
    execution_count: t.Optional[int] = None,
    store_history: bool = True,
) -> NotebookNode:
    """
    Executes a single code cell.

    To execute all cells see :meth:`execute`.

    Parameters
    ----------
    cell : nbformat.NotebookNode
        The cell which is currently being processed.
    cell_index : int
        The position of the cell within the notebook object.
    execution_count : int
        The execution count to be assigned to the cell (default: Use kernel response)
    store_history : bool
        Determines if history should be stored in the kernel (default: False).
        Specific to ipython kernels, which can store command histories.

    Returns
    -------
    output : dict
        The execution output payload (or None for no output).

    Raises
    ------
    CellExecutionError
        If execution failed and should raise an exception, this will be raised
        with defaults about the failure.

    Returns
    -------
    cell : NotebookNode
        The cell which was just processed.
    """
    assert self.kc is not None

    await run_hook(self.on_cell_start, cell=cell, cell_index=cell_index)

    if cell.cell_type != 'code' or not cell.source.strip():
        self.log.debug("Skipping non-executing cell %s", cell_index)
        return cell

    if self.skip_cells_with_tag in cell.metadata.get("tags", []):
        self.log.debug("Skipping tagged cell %s", cell_index)
        return cell

    if self.record_timing:  # clear execution metadata prior to execution
        cell['metadata']['execution'] = {}

    self.log.debug("Executing cell:\n%s", cell.source)

    cell_allows_errors = (not self.force_raise_errors) and (
        self.allow_errors or "raises-exception" in cell.metadata.get("tags", [])
    )

    await run_hook(self.on_cell_execute, cell=cell, cell_index=cell_index)
    parent_msg_id = await ensure_async(
        self.kc.execute(
            cell.source, store_history=store_history, stop_on_error=not cell_allows_errors
        )
    )
    await run_hook(self.on_cell_complete, cell=cell, cell_index=cell_index)
    # We launched a code cell to execute
    self.code_cells_executed += 1
    exec_timeout = self._get_timeout(cell)

    cell.outputs = []
    self.clear_before_next_output = False

    task_poll_kernel_alive = asyncio.ensure_future(self._async_poll_kernel_alive())
    task_poll_output_msg = asyncio.ensure_future(
        self._async_poll_output_msg(parent_msg_id, cell, cell_index)
    )
    self.task_poll_for_reply = asyncio.ensure_future(
        self._async_poll_for_reply(
            parent_msg_id, cell, exec_timeout, task_poll_output_msg, task_poll_kernel_alive
        )
    )
    try:
        exec_reply = await self.task_poll_for_reply
    except asyncio.CancelledError:
        # can only be cancelled by task_poll_kernel_alive when the kernel is dead
        task_poll_output_msg.cancel()
        raise DeadKernelError("Kernel died")
    except Exception as e:
        # Best effort to cancel request if it hasn't been resolved
        try:
            # Check if the task_poll_output is doing the raising for us
            if not isinstance(e, CellControlSignal):
                task_poll_output_msg.cancel()
        finally:
            raise

    if execution_count:
        cell['execution_count'] = execution_count
  await self._check_raise_for_error(cell, cell_index, exec_reply)

../../../.local/lib/python3.8/site-packages/nbclient/client.py:965:


self = <testbook.client.TestbookNotebookClient object at 0x7eff20071850>
cell = {'id': '71e14f59', 'cell_type': 'code', 'metadata': {'execution': {'iopub.status.busy': '2022-11-22T15:44:42.140650Z',...Error\x1b[0m: CUDA error encountered at: ../src/bitmask/null_mask.cu:93: 2 cudaErrorMemoryAllocation out of memory']}]}
cell_index = 50
exec_reply = {'buffers': [], 'content': {'ename': 'RuntimeError', 'engine_info': {'engine_id': -1, 'engine_uuid': '17b99cb8-a4ed-41...e, 'engine': '17b99cb8-a4ed-41b7-8267-06ff793aa501', 'started': '2022-11-22T15:44:42.141379Z', 'status': 'error'}, ...}

async def _check_raise_for_error(
    self, cell: NotebookNode, cell_index: int, exec_reply: t.Optional[t.Dict]
) -> None:

    if exec_reply is None:
        return None

    exec_reply_content = exec_reply['content']
    if exec_reply_content['status'] != 'error':
        return None

    cell_allows_errors = (not self.force_raise_errors) and (
        self.allow_errors
        or exec_reply_content.get('ename') in self.allow_error_names
        or "raises-exception" in cell.metadata.get("tags", [])
    )
    await run_hook(self.on_cell_error, cell=cell, cell_index=cell_index)
    if not cell_allows_errors:
      raise CellExecutionError.from_cell_and_msg(cell, exec_reply_content)

E nbclient.exceptions.CellExecutionError: An error occurred while executing the following cell:
E ------------------
E
E import os
E os.environ["INPUT_DATA_DIR"] = "/tmp/pytest-of-jenkins/pytest-24/test_example_02_nvt_integratio0"
E from unittest.mock import patch
E from merlin.datasets.synthetic import generate_data
E mock_train, mock_valid = generate_data(
E input="movielens-1m",
E num_rows=1000,
E set_sizes=(0.8, 0.2)
E )
E p1 = patch(
E "merlin.datasets.entertainment.get_movielens",
E return_value=[mock_train, mock_valid]
E )
E p1.start()
E p2 = patch(
E "merlin.core.utils.download_file",
E return_value=[]
E )
E p2.start()
E import numpy as np
E import pandas
E from pathlib import Path
E from merlin.datasets.synthetic import generate_data
E mock_data = generate_data(
E input="movielens-1m-raw-ratings",
E num_rows=1000
E )
E mock_data = mock_data.to_ddf().compute()
E if not isinstance(mock_data, pandas.core.frame.DataFrame):
E mock_data = mock_data.to_pandas()
E input_path = os.environ.get(
E "INPUT_DATA_DIR",
E "/tmp/pytest-of-jenkins/pytest-24/test_example_02_nvt_integratio0"
E )
E path = Path(input_path) / "ml-1m"
E path.mkdir(parents=True, exist_ok=True)
E np.savetxt(
E str(path / "ratings.dat"),
E mock_data.values,
E delimiter='::',
E fmt='%s',
E encoding='utf-8'
E )
E
E ------------------
E
E �[0;31m---------------------------------------------------------------------------�[0m
E �[0;31mRuntimeError�[0m Traceback (most recent call last)
E Cell �[0;32mIn [1], line 5�[0m
E �[1;32m 3�[0m �[38;5;28;01mfrom�[39;00m �[38;5;21;01munittest�[39;00m�[38;5;21;01m.�[39;00m�[38;5;21;01mmock�[39;00m �[38;5;28;01mimport�[39;00m patch
E �[1;32m 4�[0m �[38;5;28;01mfrom�[39;00m �[38;5;21;01mmerlin�[39;00m�[38;5;21;01m.�[39;00m�[38;5;21;01mdatasets�[39;00m�[38;5;21;01m.�[39;00m�[38;5;21;01msynthetic�[39;00m �[38;5;28;01mimport�[39;00m generate_data
E �[0;32m----> 5�[0m mock_train, mock_valid �[38;5;241m=�[39m �[43mgenerate_data�[49m�[43m(�[49m
E �[1;32m 6�[0m �[43m �[49m�[38;5;28;43minput�[39;49m�[38;5;241;43m=�[39;49m�[38;5;124;43m"�[39;49m�[38;5;124;43mmovielens-1m�[39;49m�[38;5;124;43m"�[39;49m�[43m,�[49m
E �[1;32m 7�[0m �[43m �[49m�[43mnum_rows�[49m�[38;5;241;43m=�[39;49m�[38;5;241;43m1000�[39;49m�[43m,�[49m
E �[1;32m 8�[0m �[43m �[49m�[43mset_sizes�[49m�[38;5;241;43m=�[39;49m�[43m(�[49m�[38;5;241;43m0.8�[39;49m�[43m,�[49m�[43m �[49m�[38;5;241;43m0.2�[39;49m�[43m)�[49m
E �[1;32m 9�[0m �[43m)�[49m
E �[1;32m 10�[0m p1 �[38;5;241m=�[39m patch(
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E �[1;32m 12�[0m return_value�[38;5;241m=�[39m[mock_train, mock_valid]
E �[1;32m 13�[0m )
E �[1;32m 14�[0m p1�[38;5;241m.�[39mstart()
E
E File �[0;32m~/workspace/merlin_models/models/merlin/datasets/synthetic.py:134�[0m, in �[0;36mgenerate_data�[0;34m(input, num_rows, set_sizes, min_session_length, max_session_length, device)�[0m
E �[1;32m 131�[0m start_i �[38;5;241m=�[39m end_i
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E �[1;32m 136�[0m �[38;5;28;01mreturn�[39;00m merlin�[38;5;241m.�[39mio�[38;5;241m.�[39mDataset(df, schema�[38;5;241m=�[39mschema)
E
E File �[0;32m~/workspace/merlin_models/models/merlin/datasets/synthetic.py:134�[0m, in �[0;36m�[0;34m(.0)�[0m
E �[1;32m 131�[0m start_i �[38;5;241m=�[39m end_i
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E �[1;32m 136�[0m �[38;5;28;01mreturn�[39;00m merlin�[38;5;241m.�[39mio�[38;5;241m.�[39mDataset(df, schema�[38;5;241m=�[39mschema)
E
E File �[0;32m~/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/io/dataset.py:267�[0m, in �[0;36mDataset.__init__�[0;34m(self, path_or_source, engine, npartitions, part_size, part_mem_fraction, storage_options, dtypes, client, cpu, base_dataset, schema, **kwargs)�[0m
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E �[1;32m 262�[0m �[38;5;28;01mif�[39;00m �[38;5;28misinstance�[39m(path_or_source, dask�[38;5;241m.�[39mdataframe�[38;5;241m.�[39mDataFrame) �[38;5;129;01mor�[39;00m is_dataframe_object(
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E �[1;32m 266�[0m �[38;5;66;03m# Use DataFrameDatasetEngine�[39;00m
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E �[1;32m 269�[0m �[43m �[49m�[43m)�[49m
E �[1;32m 270�[0m �[38;5;66;03m# Check if this is a collection that has now moved between host <-> device�[39;00m
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E File �[0;32m/usr/local/lib/python3.8/dist-packages/nvtx/nvtx.py:101�[0m, in �[0;36mannotate.call..inner�[0;34m(args, **kwargs)�[0m
E �[1;32m 98�[0m �[38;5;129m@wraps�[39m(func)
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E File �[0;32m/usr/local/lib/python3.8/dist-packages/cudf/core/dataframe.py:4547�[0m, in �[0;36mDataFrame.from_pandas�[0;34m(cls, dataframe, nan_as_null)�[0m
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E �[1;32m 1968�[0m �[43m �[49m�[43marbitrary�[49m�[43m,�[49m
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E �[1;32m 1974�[0m data �[38;5;241m=�[39m data�[38;5;241m.�[39mastype(dtype)
E
E File �[0;32m/usr/local/lib/python3.8/dist-packages/cudf/core/column/column.py:1760�[0m, in �[0;36mas_column�[0;34m(arbitrary, nan_as_null, dtype, length)�[0m
E �[1;32m 1754�[0m �[38;5;28;01mif�[39;00m �[38;5;28misinstance�[39m(arbitrary, pa�[38;5;241m.�[39mlib�[38;5;241m.�[39mHalfFloatArray):
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E �[1;32m 1757�[0m �[38;5;124m"�[39m�[38;5;124myet supported in pyarrow, see: �[39m�[38;5;124m"�[39m
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E
E File �[0;32m/usr/local/lib/python3.8/dist-packages/cudf/core/column/column.py:297�[0m, in �[0;36mColumnBase.from_arrow�[0;34m(cls, array)�[0m
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E
E File �[0;32mcudf/_lib/interop.pyx:150�[0m, in �[0;36mcudf._lib.interop.from_arrow�[0;34m()�[0m
E
E �[0;31mRuntimeError�[0m: CUDA error encountered at: ../src/bitmask/null_mask.cu:93: 2 cudaErrorMemoryAllocation out of memory
E RuntimeError: CUDA error encountered at: ../src/bitmask/null_mask.cu:93: 2 cudaErrorMemoryAllocation out of memory

../../../.local/lib/python3.8/site-packages/nbclient/client.py:862: CellExecutionError

During handling of the above exception, another exception occurred:

tb = <testbook.client.TestbookNotebookClient object at 0x7eff20071850>
tmpdir = local('/tmp/pytest-of-jenkins/pytest-24/test_example_02_nvt_integratio0')

@testbook(REPO_ROOT / "examples/02-Merlin-Models-and-NVTabular-integration.ipynb", execute=False)
def test_example_02_nvt_integration(tb, tmpdir):
  tb.inject(
        f"""
        import os
        os.environ["INPUT_DATA_DIR"] = "{tmpdir}"
        from unittest.mock import patch
        from merlin.datasets.synthetic import generate_data
        mock_train, mock_valid = generate_data(
            input="movielens-1m",
            num_rows=1000,
            set_sizes=(0.8, 0.2)
        )
        p1 = patch(
            "merlin.datasets.entertainment.get_movielens",
            return_value=[mock_train, mock_valid]
        )
        p1.start()
        p2 = patch(
            "merlin.core.utils.download_file",
            return_value=[]
        )
        p2.start()
        import numpy as np
        import pandas
        from pathlib import Path
        from merlin.datasets.synthetic import generate_data
        mock_data = generate_data(
            input="movielens-1m-raw-ratings",
            num_rows=1000
        )
        mock_data = mock_data.to_ddf().compute()
        if not isinstance(mock_data, pandas.core.frame.DataFrame):
            mock_data = mock_data.to_pandas()
        input_path = os.environ.get(
            "INPUT_DATA_DIR",
            "{tmpdir}"
        )
        path = Path(input_path) / "ml-1m"
        path.mkdir(parents=True, exist_ok=True)
        np.savetxt(
            str(path / "ratings.dat"),
            mock_data.values,
            delimiter='::',
            fmt='%s',
            encoding='utf-8'
        )
        """
    )

tests/unit/tf/examples/test_02_dataschema.py:8:


../../../.local/lib/python3.8/site-packages/testbook/client.py:237: in inject
cell = TestbookNode(self.execute_cell(inject_idx)) if run else TestbookNode(code_cell)


self = <testbook.client.TestbookNotebookClient object at 0x7eff20071850>
cell = [50], kwargs = {}, cell_indexes = [50], executed_cells = [], idx = 50

def execute_cell(self, cell, **kwargs) -> Union[Dict, List[Dict]]:
    """
    Executes a cell or list of cells
    """
    if isinstance(cell, slice):
        start, stop = self._cell_index(cell.start), self._cell_index(cell.stop)
        if cell.step is not None:
            raise TestbookError('testbook does not support step argument')

        cell = range(start, stop + 1)
    elif isinstance(cell, str) or isinstance(cell, int):
        cell = [cell]

    cell_indexes = cell

    if all(isinstance(x, str) for x in cell):
        cell_indexes = [self._cell_index(tag) for tag in cell]

    executed_cells = []
    for idx in cell_indexes:
        try:
            cell = super().execute_cell(self.nb['cells'][idx], idx, **kwargs)
        except CellExecutionError as ce:
          raise TestbookRuntimeError(ce.evalue, ce, self._get_error_class(ce.ename))

E testbook.exceptions.TestbookRuntimeError: An error occurred while executing the following cell:
E ------------------
E
E import os
E os.environ["INPUT_DATA_DIR"] = "/tmp/pytest-of-jenkins/pytest-24/test_example_02_nvt_integratio0"
E from unittest.mock import patch
E from merlin.datasets.synthetic import generate_data
E mock_train, mock_valid = generate_data(
E input="movielens-1m",
E num_rows=1000,
E set_sizes=(0.8, 0.2)
E )
E p1 = patch(
E "merlin.datasets.entertainment.get_movielens",
E return_value=[mock_train, mock_valid]
E )
E p1.start()
E p2 = patch(
E "merlin.core.utils.download_file",
E return_value=[]
E )
E p2.start()
E import numpy as np
E import pandas
E from pathlib import Path
E from merlin.datasets.synthetic import generate_data
E mock_data = generate_data(
E input="movielens-1m-raw-ratings",
E num_rows=1000
E )
E mock_data = mock_data.to_ddf().compute()
E if not isinstance(mock_data, pandas.core.frame.DataFrame):
E mock_data = mock_data.to_pandas()
E input_path = os.environ.get(
E "INPUT_DATA_DIR",
E "/tmp/pytest-of-jenkins/pytest-24/test_example_02_nvt_integratio0"
E )
E path = Path(input_path) / "ml-1m"
E path.mkdir(parents=True, exist_ok=True)
E np.savetxt(
E str(path / "ratings.dat"),
E mock_data.values,
E delimiter='::',
E fmt='%s',
E encoding='utf-8'
E )
E
E ------------------
E
E �[0;31m---------------------------------------------------------------------------�[0m
E �[0;31mRuntimeError�[0m Traceback (most recent call last)
E Cell �[0;32mIn [1], line 5�[0m
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E
E File �[0;32m~/workspace/merlin_models/models/merlin/datasets/synthetic.py:134�[0m, in �[0;36mgenerate_data�[0;34m(input, num_rows, set_sizes, min_session_length, max_session_length, device)�[0m
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E
E File �[0;32m~/workspace/merlin_models/models/merlin/datasets/synthetic.py:134�[0m, in �[0;36m�[0;34m(.0)�[0m
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E File �[0;32m~/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/io/dataset.py:267�[0m, in �[0;36mDataset.__init__�[0;34m(self, path_or_source, engine, npartitions, part_size, part_mem_fraction, storage_options, dtypes, client, cpu, base_dataset, schema, **kwargs)�[0m
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E �[1;32m 263�[0m path_or_source
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E �[1;32m 269�[0m �[43m �[49m�[43m)�[49m
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E �[1;32m 273�[0m )
E
E File �[0;32m~/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/core/dispatch.py:579�[0m, in �[0;36mconvert_data�[0;34m(x, cpu, to_collection, npartitions)�[0m
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E
E File �[0;32m/usr/local/lib/python3.8/dist-packages/cudf/core/column/column.py:1966�[0m, in �[0;36mas_column�[0;34m(arbitrary, nan_as_null, dtype, length)�[0m
E �[1;32m 1964�[0m data �[38;5;241m=�[39m as_column(pa�[38;5;241m.�[39mArray�[38;5;241m.�[39mfrom_pandas(arbitrary), dtype�[38;5;241m=�[39marb_dtype)
E �[1;32m 1965�[0m �[38;5;28;01melse�[39;00m:
E �[0;32m-> 1966�[0m data �[38;5;241m=�[39m �[43mas_column�[49m�[43m(�[49m
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E �[1;32m 1968�[0m �[43m �[49m�[43marbitrary�[49m�[43m,�[49m
E �[1;32m 1969�[0m �[43m �[49m�[43mfrom_pandas�[49m�[38;5;241;43m=�[39;49m�[38;5;28;43;01mTrue�[39;49;00m�[43m �[49m�[38;5;28;43;01mif�[39;49;00m�[43m �[49m�[43mnan_as_null�[49m�[43m �[49m�[38;5;129;43;01mis�[39;49;00m�[43m �[49m�[38;5;28;43;01mNone�[39;49;00m�[43m �[49m�[38;5;28;43;01melse�[39;49;00m�[43m �[49m�[43mnan_as_null�[49m�[43m,�[49m
E �[1;32m 1970�[0m �[43m �[49m�[43m)�[49m�[43m,�[49m
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E �[1;32m 1972�[0m �[43m �[49m�[43m)�[49m
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E �[1;32m 1974�[0m data �[38;5;241m=�[39m data�[38;5;241m.�[39mastype(dtype)
E
E File �[0;32m/usr/local/lib/python3.8/dist-packages/cudf/core/column/column.py:1760�[0m, in �[0;36mas_column�[0;34m(arbitrary, nan_as_null, dtype, length)�[0m
E �[1;32m 1754�[0m �[38;5;28;01mif�[39;00m �[38;5;28misinstance�[39m(arbitrary, pa�[38;5;241m.�[39mlib�[38;5;241m.�[39mHalfFloatArray):
E �[1;32m 1755�[0m �[38;5;28;01mraise�[39;00m �[38;5;167;01mNotImplementedError�[39;00m(
E �[1;32m 1756�[0m �[38;5;124m"�[39m�[38;5;124mType casting from float16 to float32 is not �[39m�[38;5;124m"�[39m
E �[1;32m 1757�[0m �[38;5;124m"�[39m�[38;5;124myet supported in pyarrow, see: �[39m�[38;5;124m"�[39m
E �[1;32m 1758�[0m �[38;5;124m"�[39m�[38;5;124mhttps://issues.apache.org/jira/browse/ARROW-3802�[39m�[38;5;124m"�[39m
E �[1;32m 1759�[0m )
E �[0;32m-> 1760�[0m col �[38;5;241m=�[39m �[43mColumnBase�[49m�[38;5;241;43m.�[39;49m�[43mfrom_arrow�[49m�[43m(�[49m�[43marbitrary�[49m�[43m)�[49m
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E
E File �[0;32m/usr/local/lib/python3.8/dist-packages/cudf/core/column/column.py:297�[0m, in �[0;36mColumnBase.from_arrow�[0;34m(cls, array)�[0m
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E �[0;32m--> 297�[0m result �[38;5;241m=�[39m �[43mlibcudf�[49m�[38;5;241;43m.�[39;49m�[43minterop�[49m�[38;5;241;43m.�[39;49m�[43mfrom_arrow�[49m�[43m(�[49m�[43mdata�[49m�[43m)�[49m[�[38;5;241m0�[39m]
E �[1;32m 299�[0m �[38;5;28;01mreturn�[39;00m result�[38;5;241m.�[39m_with_type_metadata(cudf_dtype_from_pa_type(array�[38;5;241m.�[39mtype))
E
E File �[0;32mcudf/_lib/interop.pyx:150�[0m, in �[0;36mcudf._lib.interop.from_arrow�[0;34m()�[0m
E
E �[0;31mRuntimeError�[0m: CUDA error encountered at: ../src/bitmask/null_mask.cu:93: 2 cudaErrorMemoryAllocation out of memory
E RuntimeError: CUDA error encountered at: ../src/bitmask/null_mask.cu:93: 2 cudaErrorMemoryAllocation out of memory

../../../.local/lib/python3.8/site-packages/testbook/client.py:135: TestbookRuntimeError
__________________ test_example_03_exploring_different_models __________________

self = <testbook.client.TestbookNotebookClient object at 0x7eff20026e50>
cell = {'cell_type': 'markdown', 'id': 'e75faa3b', 'metadata': {'pycharm': {'name': '#%% md\n'}}, 'source': 'When we work on ...we define our input and output paths. We will use the parquet files in the test folder to validate our trained model.'}
kwargs = {}, cell_indexes = [0, 1, 2, 3, 4, 5, ...]
executed_cells = [{'cell_type': 'code', 'execution_count': 2, 'id': '5f49a48e', 'metadata': {'pycharm': {'name': '#%%\n'}, 'execution':...d': '2dd02301', 'metadata': {'pycharm': {'name': '#%% md\n'}}, 'source': '## Feature Engineering with NVTabular'}, ...]
idx = 7

def execute_cell(self, cell, **kwargs) -> Union[Dict, List[Dict]]:
    """
    Executes a cell or list of cells
    """
    if isinstance(cell, slice):
        start, stop = self._cell_index(cell.start), self._cell_index(cell.stop)
        if cell.step is not None:
            raise TestbookError('testbook does not support step argument')

        cell = range(start, stop + 1)
    elif isinstance(cell, str) or isinstance(cell, int):
        cell = [cell]

    cell_indexes = cell

    if all(isinstance(x, str) for x in cell):
        cell_indexes = [self._cell_index(tag) for tag in cell]

    executed_cells = []
    for idx in cell_indexes:
        try:
          cell = super().execute_cell(self.nb['cells'][idx], idx, **kwargs)

../../../.local/lib/python3.8/site-packages/testbook/client.py:133:


args = (<testbook.client.TestbookNotebookClient object at 0x7eff20026e50>, {'cell_type': 'code', 'execution_count': 4, 'id': ...to_parquet(os.path.join(DATA_FOLDER, "train"))\n valid.to_ddf().to_parquet(os.path.join(DATA_FOLDER, "valid"))'}, 7)
kwargs = {}

def wrapped(*args, **kwargs):
  return just_run(coro(*args, **kwargs))

../../../.local/lib/python3.8/site-packages/nbclient/util.py:84:


coro = <coroutine object NotebookClient.async_execute_cell at 0x7efdd428cbc0>

def just_run(coro: Awaitable) -> Any:
    """Make the coroutine run, even if there is an event loop running (using nest_asyncio)"""
    # original from vaex/asyncio.py
    loop = asyncio._get_running_loop()
    if loop is None:
        had_running_loop = False
        try:
            loop = asyncio.get_event_loop()
        except RuntimeError:
            # we can still get 'There is no current event loop in ...'
            loop = asyncio.new_event_loop()
            asyncio.set_event_loop(loop)
    else:
        had_running_loop = True
    if had_running_loop:
        # if there is a running loop, we patch using nest_asyncio
        # to have reentrant event loops
        check_ipython()
        import nest_asyncio

        nest_asyncio.apply()
        check_patch_tornado()
  return loop.run_until_complete(coro)

../../../.local/lib/python3.8/site-packages/nbclient/util.py:62:


self = <_UnixSelectorEventLoop running=False closed=False debug=False>
future = <Task finished name='Task-51' coro=<NotebookClient.async_execute_cell() done, defined at /var/jenkins_home/.local/lib/...RuntimeError: CUDA error encountered at: ../src/bitmask/null_mask.cu:93: 2 cudaErrorMemoryAllocation out of memory\n')>

def run_until_complete(self, future):
    """Run until the Future is done.

    If the argument is a coroutine, it is wrapped in a Task.

    WARNING: It would be disastrous to call run_until_complete()
    with the same coroutine twice -- it would wrap it in two
    different Tasks and that can't be good.

    Return the Future's result, or raise its exception.
    """
    self._check_closed()
    self._check_running()

    new_task = not futures.isfuture(future)
    future = tasks.ensure_future(future, loop=self)
    if new_task:
        # An exception is raised if the future didn't complete, so there
        # is no need to log the "destroy pending task" message
        future._log_destroy_pending = False

    future.add_done_callback(_run_until_complete_cb)
    try:
        self.run_forever()
    except:
        if new_task and future.done() and not future.cancelled():
            # The coroutine raised a BaseException. Consume the exception
            # to not log a warning, the caller doesn't have access to the
            # local task.
            future.exception()
        raise
    finally:
        future.remove_done_callback(_run_until_complete_cb)
    if not future.done():
        raise RuntimeError('Event loop stopped before Future completed.')
  return future.result()

/usr/lib/python3.8/asyncio/base_events.py:616:


self = <testbook.client.TestbookNotebookClient object at 0x7eff20026e50>
cell = {'cell_type': 'code', 'execution_count': 4, 'id': 'abdb2c78', 'metadata': {'pycharm': {'name': '#%%\n'}, 'execution': ...f().to_parquet(os.path.join(DATA_FOLDER, "train"))\n valid.to_ddf().to_parquet(os.path.join(DATA_FOLDER, "valid"))'}
cell_index = 7, execution_count = None, store_history = True

async def async_execute_cell(
    self,
    cell: NotebookNode,
    cell_index: int,
    execution_count: t.Optional[int] = None,
    store_history: bool = True,
) -> NotebookNode:
    """
    Executes a single code cell.

    To execute all cells see :meth:`execute`.

    Parameters
    ----------
    cell : nbformat.NotebookNode
        The cell which is currently being processed.
    cell_index : int
        The position of the cell within the notebook object.
    execution_count : int
        The execution count to be assigned to the cell (default: Use kernel response)
    store_history : bool
        Determines if history should be stored in the kernel (default: False).
        Specific to ipython kernels, which can store command histories.

    Returns
    -------
    output : dict
        The execution output payload (or None for no output).

    Raises
    ------
    CellExecutionError
        If execution failed and should raise an exception, this will be raised
        with defaults about the failure.

    Returns
    -------
    cell : NotebookNode
        The cell which was just processed.
    """
    assert self.kc is not None

    await run_hook(self.on_cell_start, cell=cell, cell_index=cell_index)

    if cell.cell_type != 'code' or not cell.source.strip():
        self.log.debug("Skipping non-executing cell %s", cell_index)
        return cell

    if self.skip_cells_with_tag in cell.metadata.get("tags", []):
        self.log.debug("Skipping tagged cell %s", cell_index)
        return cell

    if self.record_timing:  # clear execution metadata prior to execution
        cell['metadata']['execution'] = {}

    self.log.debug("Executing cell:\n%s", cell.source)

    cell_allows_errors = (not self.force_raise_errors) and (
        self.allow_errors or "raises-exception" in cell.metadata.get("tags", [])
    )

    await run_hook(self.on_cell_execute, cell=cell, cell_index=cell_index)
    parent_msg_id = await ensure_async(
        self.kc.execute(
            cell.source, store_history=store_history, stop_on_error=not cell_allows_errors
        )
    )
    await run_hook(self.on_cell_complete, cell=cell, cell_index=cell_index)
    # We launched a code cell to execute
    self.code_cells_executed += 1
    exec_timeout = self._get_timeout(cell)

    cell.outputs = []
    self.clear_before_next_output = False

    task_poll_kernel_alive = asyncio.ensure_future(self._async_poll_kernel_alive())
    task_poll_output_msg = asyncio.ensure_future(
        self._async_poll_output_msg(parent_msg_id, cell, cell_index)
    )
    self.task_poll_for_reply = asyncio.ensure_future(
        self._async_poll_for_reply(
            parent_msg_id, cell, exec_timeout, task_poll_output_msg, task_poll_kernel_alive
        )
    )
    try:
        exec_reply = await self.task_poll_for_reply
    except asyncio.CancelledError:
        # can only be cancelled by task_poll_kernel_alive when the kernel is dead
        task_poll_output_msg.cancel()
        raise DeadKernelError("Kernel died")
    except Exception as e:
        # Best effort to cancel request if it hasn't been resolved
        try:
            # Check if the task_poll_output is doing the raising for us
            if not isinstance(e, CellControlSignal):
                task_poll_output_msg.cancel()
        finally:
            raise

    if execution_count:
        cell['execution_count'] = execution_count
  await self._check_raise_for_error(cell, cell_index, exec_reply)

../../../.local/lib/python3.8/site-packages/nbclient/client.py:965:


self = <testbook.client.TestbookNotebookClient object at 0x7eff20026e50>
cell = {'cell_type': 'code', 'execution_count': 4, 'id': 'abdb2c78', 'metadata': {'pycharm': {'name': '#%%\n'}, 'execution': ...f().to_parquet(os.path.join(DATA_FOLDER, "train"))\n valid.to_ddf().to_parquet(os.path.join(DATA_FOLDER, "valid"))'}
cell_index = 7
exec_reply = {'buffers': [], 'content': {'ename': 'RuntimeError', 'engine_info': {'engine_id': -1, 'engine_uuid': '476c9d1b-fca2-4e...e, 'engine': '476c9d1b-fca2-4ee9-9c22-4035fdcf2e54', 'started': '2022-11-22T15:45:02.264924Z', 'status': 'error'}, ...}

async def _check_raise_for_error(
    self, cell: NotebookNode, cell_index: int, exec_reply: t.Optional[t.Dict]
) -> None:

    if exec_reply is None:
        return None

    exec_reply_content = exec_reply['content']
    if exec_reply_content['status'] != 'error':
        return None

    cell_allows_errors = (not self.force_raise_errors) and (
        self.allow_errors
        or exec_reply_content.get('ename') in self.allow_error_names
        or "raises-exception" in cell.metadata.get("tags", [])
    )
    await run_hook(self.on_cell_error, cell=cell, cell_index=cell_index)
    if not cell_allows_errors:
      raise CellExecutionError.from_cell_and_msg(cell, exec_reply_content)

E nbclient.exceptions.CellExecutionError: An error occurred while executing the following cell:
E ------------------
E from merlin.datasets.synthetic import generate_data
E
E DATA_FOLDER = os.environ.get("DATA_FOLDER", "/workspace/data/")
E
E NUM_ROWS = os.environ.get("NUM_ROWS", 1000000)
E SYNTHETIC_DATA = eval(os.environ.get("SYNTHETIC_DATA", "True"))
E
E if SYNTHETIC_DATA:
E train, valid = generate_data("aliccp-raw", int(NUM_ROWS), set_sizes=(0.7, 0.3))
E # save the datasets as parquet files
E train.to_ddf().to_parquet(os.path.join(DATA_FOLDER, "train"))
E valid.to_ddf().to_parquet(os.path.join(DATA_FOLDER, "valid"))
E ------------------
E
E �[0;31m---------------------------------------------------------------------------�[0m
E �[0;31mRuntimeError�[0m Traceback (most recent call last)
E Cell �[0;32mIn [4], line 9�[0m
E �[1;32m 6�[0m SYNTHETIC_DATA �[38;5;241m=�[39m �[38;5;28meval�[39m(os�[38;5;241m.�[39menviron�[38;5;241m.�[39mget(�[38;5;124m"�[39m�[38;5;124mSYNTHETIC_DATA�[39m�[38;5;124m"�[39m, �[38;5;124m"�[39m�[38;5;124mTrue�[39m�[38;5;124m"�[39m))
E �[1;32m 8�[0m �[38;5;28;01mif�[39;00m SYNTHETIC_DATA:
E �[0;32m----> 9�[0m train, valid �[38;5;241m=�[39m �[43mgenerate_data�[49m�[43m(�[49m�[38;5;124;43m"�[39;49m�[38;5;124;43maliccp-raw�[39;49m�[38;5;124;43m"�[39;49m�[43m,�[49m�[43m �[49m�[38;5;28;43mint�[39;49m�[43m(�[49m�[43mNUM_ROWS�[49m�[43m)�[49m�[43m,�[49m�[43m �[49m�[43mset_sizes�[49m�[38;5;241;43m=�[39;49m�[43m(�[49m�[38;5;241;43m0.7�[39;49m�[43m,�[49m�[43m �[49m�[38;5;241;43m0.3�[39;49m�[43m)�[49m�[43m)�[49m
E �[1;32m 10�[0m �[38;5;66;03m# save the datasets as parquet files�[39;00m
E �[1;32m 11�[0m train�[38;5;241m.�[39mto_ddf()�[38;5;241m.�[39mto_parquet(os�[38;5;241m.�[39mpath�[38;5;241m.�[39mjoin(DATA_FOLDER, �[38;5;124m"�[39m�[38;5;124mtrain�[39m�[38;5;124m"�[39m))
E
E File �[0;32m~/workspace/merlin_models/models/merlin/datasets/synthetic.py:134�[0m, in �[0;36mgenerate_data�[0;34m(input, num_rows, set_sizes, min_session_length, max_session_length, device)�[0m
E �[1;32m 131�[0m start_i �[38;5;241m=�[39m end_i
E �[1;32m 132�[0m output_datasets�[38;5;241m.�[39mappend(set_df)
E �[0;32m--> 134�[0m �[38;5;28;01mreturn�[39;00m �[38;5;28mtuple�[39m([merlin�[38;5;241m.�[39mio�[38;5;241m.�[39mDataset(d, schema�[38;5;241m=�[39mschema) �[38;5;28;01mfor�[39;00m d �[38;5;129;01min�[39;00m output_datasets])
E �[1;32m 136�[0m �[38;5;28;01mreturn�[39;00m merlin�[38;5;241m.�[39mio�[38;5;241m.�[39mDataset(df, schema�[38;5;241m=�[39mschema)
E
E File �[0;32m~/workspace/merlin_models/models/merlin/datasets/synthetic.py:134�[0m, in �[0;36m�[0;34m(.0)�[0m
E �[1;32m 131�[0m start_i �[38;5;241m=�[39m end_i
E �[1;32m 132�[0m output_datasets�[38;5;241m.�[39mappend(set_df)
E �[0;32m--> 134�[0m �[38;5;28;01mreturn�[39;00m �[38;5;28mtuple�[39m([�[43mmerlin�[49m�[38;5;241;43m.�[39;49m�[43mio�[49m�[38;5;241;43m.�[39;49m�[43mDataset�[49m�[43m(�[49m�[43md�[49m�[43m,�[49m�[43m �[49m�[43mschema�[49m�[38;5;241;43m=�[39;49m�[43mschema�[49m�[43m)�[49m �[38;5;28;01mfor�[39;00m d �[38;5;129;01min�[39;00m output_datasets])
E �[1;32m 136�[0m �[38;5;28;01mreturn�[39;00m merlin�[38;5;241m.�[39mio�[38;5;241m.�[39mDataset(df, schema�[38;5;241m=�[39mschema)
E
E File �[0;32m~/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/io/dataset.py:267�[0m, in �[0;36mDataset.__init__�[0;34m(self, path_or_source, engine, npartitions, part_size, part_mem_fraction, storage_options, dtypes, client, cpu, base_dataset, schema, **kwargs)�[0m
E �[1;32m 261�[0m npartitions �[38;5;241m=�[39m npartitions �[38;5;129;01mor�[39;00m �[38;5;241m1�[39m
E �[1;32m 262�[0m �[38;5;28;01mif�[39;00m �[38;5;28misinstance�[39m(path_or_source, dask�[38;5;241m.�[39mdataframe�[38;5;241m.�[39mDataFrame) �[38;5;129;01mor�[39;00m is_dataframe_object(
E �[1;32m 263�[0m path_or_source
E �[1;32m 264�[0m ):
E �[1;32m 265�[0m �[38;5;66;03m# User is passing in a <dask.dataframe|cudf|pd>.DataFrame�[39;00m
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E �[1;32m 269�[0m �[43m �[49m�[43m)�[49m
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E File �[0;32m~/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/core/dispatch.py:579�[0m, in �[0;36mconvert_data�[0;34m(x, cpu, to_collection, npartitions)�[0m
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E �[1;32m 583�[0m �[38;5;28;01mif�[39;00m to_collection
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E File �[0;32m/usr/local/lib/python3.8/dist-packages/nvtx/nvtx.py:101�[0m, in �[0;36mannotate.call..inner�[0;34m(args, **kwargs)�[0m
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E �[0;32m--> 101�[0m result �[38;5;241m=�[39m �[43mfunc�[49m�[43m(�[49m�[38;5;241;43m�[39;49m�[43margs�[49m�[43m,�[49m�[43m �[49m�[38;5;241;43m�[39;49m�[38;5;241;43m*�[39;49m�[43mkwargs�[49m�[43m)�[49m
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E File �[0;32m/usr/local/lib/python3.8/dist-packages/cudf/core/dataframe.py:4547�[0m, in �[0;36mDataFrame.from_pandas�[0;34m(cls, dataframe, nan_as_null)�[0m
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E File �[0;32m/usr/local/lib/python3.8/dist-packages/cudf/core/column/column.py:1966�[0m, in �[0;36mas_column�[0;34m(arbitrary, nan_as_null, dtype, length)�[0m
E �[1;32m 1964�[0m data �[38;5;241m=�[39m as_column(pa�[38;5;241m.�[39mArray�[38;5;241m.�[39mfrom_pandas(arbitrary), dtype�[38;5;241m=�[39marb_dtype)
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E
E �[0;31mRuntimeError�[0m: CUDA error encountered at: ../src/bitmask/null_mask.cu:93: 2 cudaErrorMemoryAllocation out of memory
E RuntimeError: CUDA error encountered at: ../src/bitmask/null_mask.cu:93: 2 cudaErrorMemoryAllocation out of memory

../../../.local/lib/python3.8/site-packages/nbclient/client.py:862: CellExecutionError

During handling of the above exception, another exception occurred:

tb = <testbook.client.TestbookNotebookClient object at 0x7eff20026e50>
tmpdir = local('/tmp/pytest-of-jenkins/pytest-24/test_example_03_exploring_diff0')

@testbook(REPO_ROOT / "examples/03-Exploring-different-models.ipynb", execute=False)
def test_example_03_exploring_different_models(tb, tmpdir):
    tb.inject(
        f"""
        import os
        os.environ["DATA_FOLDER"] = "{tmpdir}"
        os.environ["NUM_ROWS"] = "999"
        """
    )
    NUM_OF_CELLS = len(tb.cells)
  tb.execute_cell(list(range(0, NUM_OF_CELLS - 5)))

tests/unit/tf/examples/test_03_exploring_different_models.py:18:


self = <testbook.client.TestbookNotebookClient object at 0x7eff20026e50>
cell = {'cell_type': 'markdown', 'id': 'e75faa3b', 'metadata': {'pycharm': {'name': '#%% md\n'}}, 'source': 'When we work on ...we define our input and output paths. We will use the parquet files in the test folder to validate our trained model.'}
kwargs = {}, cell_indexes = [0, 1, 2, 3, 4, 5, ...]
executed_cells = [{'cell_type': 'code', 'execution_count': 2, 'id': '5f49a48e', 'metadata': {'pycharm': {'name': '#%%\n'}, 'execution':...d': '2dd02301', 'metadata': {'pycharm': {'name': '#%% md\n'}}, 'source': '## Feature Engineering with NVTabular'}, ...]
idx = 7

def execute_cell(self, cell, **kwargs) -> Union[Dict, List[Dict]]:
    """
    Executes a cell or list of cells
    """
    if isinstance(cell, slice):
        start, stop = self._cell_index(cell.start), self._cell_index(cell.stop)
        if cell.step is not None:
            raise TestbookError('testbook does not support step argument')

        cell = range(start, stop + 1)
    elif isinstance(cell, str) or isinstance(cell, int):
        cell = [cell]

    cell_indexes = cell

    if all(isinstance(x, str) for x in cell):
        cell_indexes = [self._cell_index(tag) for tag in cell]

    executed_cells = []
    for idx in cell_indexes:
        try:
            cell = super().execute_cell(self.nb['cells'][idx], idx, **kwargs)
        except CellExecutionError as ce:
          raise TestbookRuntimeError(ce.evalue, ce, self._get_error_class(ce.ename))

E testbook.exceptions.TestbookRuntimeError: An error occurred while executing the following cell:
E ------------------
E from merlin.datasets.synthetic import generate_data
E
E DATA_FOLDER = os.environ.get("DATA_FOLDER", "/workspace/data/")
E
E NUM_ROWS = os.environ.get("NUM_ROWS", 1000000)
E SYNTHETIC_DATA = eval(os.environ.get("SYNTHETIC_DATA", "True"))
E
E if SYNTHETIC_DATA:
E train, valid = generate_data("aliccp-raw", int(NUM_ROWS), set_sizes=(0.7, 0.3))
E # save the datasets as parquet files
E train.to_ddf().to_parquet(os.path.join(DATA_FOLDER, "train"))
E valid.to_ddf().to_parquet(os.path.join(DATA_FOLDER, "valid"))
E ------------------
E
E �[0;31m---------------------------------------------------------------------------�[0m
E �[0;31mRuntimeError�[0m Traceback (most recent call last)
E Cell �[0;32mIn [4], line 9�[0m
E �[1;32m 6�[0m SYNTHETIC_DATA �[38;5;241m=�[39m �[38;5;28meval�[39m(os�[38;5;241m.�[39menviron�[38;5;241m.�[39mget(�[38;5;124m"�[39m�[38;5;124mSYNTHETIC_DATA�[39m�[38;5;124m"�[39m, �[38;5;124m"�[39m�[38;5;124mTrue�[39m�[38;5;124m"�[39m))
E �[1;32m 8�[0m �[38;5;28;01mif�[39;00m SYNTHETIC_DATA:
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E �[1;32m 10�[0m �[38;5;66;03m# save the datasets as parquet files�[39;00m
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E
E File �[0;32m~/workspace/merlin_models/models/merlin/datasets/synthetic.py:134�[0m, in �[0;36mgenerate_data�[0;34m(input, num_rows, set_sizes, min_session_length, max_session_length, device)�[0m
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E
E File �[0;32m~/workspace/merlin_models/models/merlin/datasets/synthetic.py:134�[0m, in �[0;36m�[0;34m(.0)�[0m
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E
E File �[0;32m~/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/io/dataset.py:267�[0m, in �[0;36mDataset.__init__�[0;34m(self, path_or_source, engine, npartitions, part_size, part_mem_fraction, storage_options, dtypes, client, cpu, base_dataset, schema, **kwargs)�[0m
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E �[1;32m 266�[0m �[38;5;66;03m# Use DataFrameDatasetEngine�[39;00m
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E �[1;32m 269�[0m �[43m �[49m�[43m)�[49m
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E �[1;32m 273�[0m )
E
E File �[0;32m~/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/core/dispatch.py:579�[0m, in �[0;36mconvert_data�[0;34m(x, cpu, to_collection, npartitions)�[0m
E �[1;32m 577�[0m _x �[38;5;241m=�[39m cudf�[38;5;241m.�[39mDataFrame�[38;5;241m.�[39mfrom_arrow(x)
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E �[1;32m 583�[0m �[38;5;28;01mif�[39;00m to_collection
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E File �[0;32m/usr/local/lib/python3.8/dist-packages/nvtx/nvtx.py:101�[0m, in �[0;36mannotate.call..inner�[0;34m(args, **kwargs)�[0m
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E File �[0;32m/usr/local/lib/python3.8/dist-packages/cudf/core/dataframe.py:4547�[0m, in �[0;36mDataFrame.from_pandas�[0;34m(cls, dataframe, nan_as_null)�[0m
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E File �[0;32m/usr/local/lib/python3.8/dist-packages/cudf/core/column/column.py:1966�[0m, in �[0;36mas_column�[0;34m(arbitrary, nan_as_null, dtype, length)�[0m
E �[1;32m 1964�[0m data �[38;5;241m=�[39m as_column(pa�[38;5;241m.�[39mArray�[38;5;241m.�[39mfrom_pandas(arbitrary), dtype�[38;5;241m=�[39marb_dtype)
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E
E �[0;31mRuntimeError�[0m: CUDA error encountered at: ../src/bitmask/null_mask.cu:93: 2 cudaErrorMemoryAllocation out of memory
E RuntimeError: CUDA error encountered at: ../src/bitmask/null_mask.cu:93: 2 cudaErrorMemoryAllocation out of memory

../../../.local/lib/python3.8/site-packages/testbook/client.py:135: TestbookRuntimeError
----------------------------- Captured stderr call -----------------------------
2022-11-22 15:44:57.049084: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: AVX2 FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
2022-11-22 15:45:01.351207: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 0
2022-11-22 15:45:01.351328: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 8139 MB memory: -> device: 0, name: Tesla P100-DGXS-16GB, pci bus id: 0000:07:00.0, compute capability: 6.0
2022-11-22 15:45:01.352273: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 1
2022-11-22 15:45:01.352337: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:1 with 13851 MB memory: -> device: 1, name: Tesla P100-DGXS-16GB, pci bus id: 0000:08:00.0, compute capability: 6.0
2022-11-22 15:45:01.352939: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 2
2022-11-22 15:45:01.352991: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:2 with 13851 MB memory: -> device: 2, name: Tesla P100-DGXS-16GB, pci bus id: 0000:0e:00.0, compute capability: 6.0
2022-11-22 15:45:01.354060: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 3
2022-11-22 15:45:01.354194: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:3 with 13851 MB memory: -> device: 3, name: Tesla P100-DGXS-16GB, pci bus id: 0000:0f:00.0, compute capability: 6.0
Error in atexit._run_exitfuncs:
Traceback (most recent call last):
File "/usr/lib/python3.8/logging/init.py", line 2127, in shutdown
h.close()
File "/usr/local/lib/python3.8/dist-packages/absl/logging/init.py", line 934, in close
self.stream.close()
File "/usr/local/lib/python3.8/dist-packages/ipykernel/iostream.py", line 438, in close
self.watch_fd_thread.join()
AttributeError: 'OutStream' object has no attribute 'watch_fd_thread'
___________________ test_example_04_exporting_ranking_models ___________________

tb = <testbook.client.TestbookNotebookClient object at 0x7efe44bdb670>
tmpdir = local('/tmp/pytest-of-jenkins/pytest-24/test_example_04_exporting_rank0')

@testbook(REPO_ROOT / "examples/04-Exporting-ranking-models.ipynb", execute=False)
def test_example_04_exporting_ranking_models(tb, tmpdir):
    tb.inject(
        f"""
        import os
        os.environ["DATA_FOLDER"] = "{tmpdir}"
        os.environ["NUM_ROWS"] = "999"
        """
    )
  tb.execute()

tests/unit/tf/examples/test_04_export_ranking_models.py:17:


../../../.local/lib/python3.8/site-packages/testbook/client.py:147: in execute
super().execute_cell(cell, index)
../../../.local/lib/python3.8/site-packages/nbclient/util.py:84: in wrapped
return just_run(coro(*args, **kwargs))
../../../.local/lib/python3.8/site-packages/nbclient/util.py:62: in just_run
return loop.run_until_complete(coro)
/usr/lib/python3.8/asyncio/base_events.py:616: in run_until_complete
return future.result()
../../../.local/lib/python3.8/site-packages/nbclient/client.py:965: in async_execute_cell
await self._check_raise_for_error(cell, cell_index, exec_reply)


self = <testbook.client.TestbookNotebookClient object at 0x7efe44bdb670>
cell = {'cell_type': 'code', 'execution_count': 4, 'id': 'b6651cc8', 'metadata': {'pycharm': {'name': '#%%\n'}, 'execution': ...f().to_parquet(os.path.join(DATA_FOLDER, "train"))\n valid.to_ddf().to_parquet(os.path.join(DATA_FOLDER, "valid"))'}
cell_index = 7
exec_reply = {'buffers': [], 'content': {'ename': 'RuntimeError', 'engine_info': {'engine_id': -1, 'engine_uuid': '26693100-3991-45...e, 'engine': '26693100-3991-4568-bd6f-8061a2f3a87c', 'started': '2022-11-22T15:45:22.501561Z', 'status': 'error'}, ...}

async def _check_raise_for_error(
    self, cell: NotebookNode, cell_index: int, exec_reply: t.Optional[t.Dict]
) -> None:

    if exec_reply is None:
        return None

    exec_reply_content = exec_reply['content']
    if exec_reply_content['status'] != 'error':
        return None

    cell_allows_errors = (not self.force_raise_errors) and (
        self.allow_errors
        or exec_reply_content.get('ename') in self.allow_error_names
        or "raises-exception" in cell.metadata.get("tags", [])
    )
    await run_hook(self.on_cell_error, cell=cell, cell_index=cell_index)
    if not cell_allows_errors:
      raise CellExecutionError.from_cell_and_msg(cell, exec_reply_content)

E nbclient.exceptions.CellExecutionError: An error occurred while executing the following cell:
E ------------------
E from merlin.datasets.synthetic import generate_data
E
E DATA_FOLDER = os.environ.get("DATA_FOLDER", "workspace/data/")
E NUM_ROWS = os.environ.get("NUM_ROWS", 1000000)
E SYNTHETIC_DATA = eval(os.environ.get("SYNTHETIC_DATA", "True"))
E BATCH_SIZE = int(os.environ.get("BATCH_SIZE", 512))
E
E if SYNTHETIC_DATA:
E train, valid = generate_data("aliccp-raw", int(NUM_ROWS), set_sizes=(0.7, 0.3))
E # save the datasets as parquet files
E train.to_ddf().to_parquet(os.path.join(DATA_FOLDER, "train"))
E valid.to_ddf().to_parquet(os.path.join(DATA_FOLDER, "valid"))
E ------------------
E
E �[0;31m---------------------------------------------------------------------------�[0m
E �[0;31mRuntimeError�[0m Traceback (most recent call last)
E Cell �[0;32mIn [4], line 9�[0m
E �[1;32m 6�[0m BATCH_SIZE �[38;5;241m=�[39m �[38;5;28mint�[39m(os�[38;5;241m.�[39menviron�[38;5;241m.�[39mget(�[38;5;124m"�[39m�[38;5;124mBATCH_SIZE�[39m�[38;5;124m"�[39m, �[38;5;241m512�[39m))
E �[1;32m 8�[0m �[38;5;28;01mif�[39;00m SYNTHETIC_DATA:
E �[0;32m----> 9�[0m train, valid �[38;5;241m=�[39m �[43mgenerate_data�[49m�[43m(�[49m�[38;5;124;43m"�[39;49m�[38;5;124;43maliccp-raw�[39;49m�[38;5;124;43m"�[39;49m�[43m,�[49m�[43m �[49m�[38;5;28;43mint�[39;49m�[43m(�[49m�[43mNUM_ROWS�[49m�[43m)�[49m�[43m,�[49m�[43m �[49m�[43mset_sizes�[49m�[38;5;241;43m=�[39;49m�[43m(�[49m�[38;5;241;43m0.7�[39;49m�[43m,�[49m�[43m �[49m�[38;5;241;43m0.3�[39;49m�[43m)�[49m�[43m)�[49m
E �[1;32m 10�[0m �[38;5;66;03m# save the datasets as parquet files�[39;00m
E �[1;32m 11�[0m train�[38;5;241m.�[39mto_ddf()�[38;5;241m.�[39mto_parquet(os�[38;5;241m.�[39mpath�[38;5;241m.�[39mjoin(DATA_FOLDER, �[38;5;124m"�[39m�[38;5;124mtrain�[39m�[38;5;124m"�[39m))
E
E File �[0;32m~/workspace/merlin_models/models/merlin/datasets/synthetic.py:134�[0m, in �[0;36mgenerate_data�[0;34m(input, num_rows, set_sizes, min_session_length, max_session_length, device)�[0m
E �[1;32m 131�[0m start_i �[38;5;241m=�[39m end_i
E �[1;32m 132�[0m output_datasets�[38;5;241m.�[39mappend(set_df)
E �[0;32m--> 134�[0m �[38;5;28;01mreturn�[39;00m �[38;5;28mtuple�[39m([merlin�[38;5;241m.�[39mio�[38;5;241m.�[39mDataset(d, schema�[38;5;241m=�[39mschema) �[38;5;28;01mfor�[39;00m d �[38;5;129;01min�[39;00m output_datasets])
E �[1;32m 136�[0m �[38;5;28;01mreturn�[39;00m merlin�[38;5;241m.�[39mio�[38;5;241m.�[39mDataset(df, schema�[38;5;241m=�[39mschema)
E
E File �[0;32m~/workspace/merlin_models/models/merlin/datasets/synthetic.py:134�[0m, in �[0;36m�[0;34m(.0)�[0m
E �[1;32m 131�[0m start_i �[38;5;241m=�[39m end_i
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../../../.local/lib/python3.8/site-packages/nbclient/client.py:862: CellExecutionError
----------------------------- Captured stderr call -----------------------------
2022-11-22 15:45:17.330823: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: AVX2 FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
2022-11-22 15:45:21.574052: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 0
2022-11-22 15:45:21.574152: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 8139 MB memory: -> device: 0, name: Tesla P100-DGXS-16GB, pci bus id: 0000:07:00.0, compute capability: 6.0
2022-11-22 15:45:21.574846: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 1
2022-11-22 15:45:21.574908: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:1 with 13851 MB memory: -> device: 1, name: Tesla P100-DGXS-16GB, pci bus id: 0000:08:00.0, compute capability: 6.0
2022-11-22 15:45:21.575504: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 2
2022-11-22 15:45:21.575551: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:2 with 13851 MB memory: -> device: 2, name: Tesla P100-DGXS-16GB, pci bus id: 0000:0e:00.0, compute capability: 6.0
2022-11-22 15:45:21.576094: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 3
2022-11-22 15:45:21.576148: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:3 with 13851 MB memory: -> device: 3, name: Tesla P100-DGXS-16GB, pci bus id: 0000:0f:00.0, compute capability: 6.0
Error in atexit._run_exitfuncs:
Traceback (most recent call last):
File "/usr/lib/python3.8/logging/init.py", line 2127, in shutdown
h.close()
File "/usr/local/lib/python3.8/dist-packages/absl/logging/init.py", line 934, in close
self.stream.close()
File "/usr/local/lib/python3.8/dist-packages/ipykernel/iostream.py", line 438, in close
self.watch_fd_thread.join()
AttributeError: 'OutStream' object has no attribute 'watch_fd_thread'
=============================== warnings summary ===============================
../../../../../usr/lib/python3/dist-packages/requests/init.py:89
/usr/lib/python3/dist-packages/requests/init.py:89: RequestsDependencyWarning: urllib3 (1.26.12) or chardet (3.0.4) doesn't match a supported version!
warnings.warn("urllib3 ({}) or chardet ({}) doesn't match a supported "

../../../.local/lib/python3.8/site-packages/flatbuffers/compat.py:19
/var/jenkins_home/.local/lib/python3.8/site-packages/flatbuffers/compat.py:19: DeprecationWarning: the imp module is deprecated in favour of importlib; see the module's documentation for alternative uses
import imp

../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36
/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36: DeprecationWarning: NEAREST is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.NEAREST or Dither.NONE instead.
'nearest': pil_image.NEAREST,

../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37
/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37: DeprecationWarning: BILINEAR is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BILINEAR instead.
'bilinear': pil_image.BILINEAR,

../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38
/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38: DeprecationWarning: BICUBIC is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BICUBIC instead.
'bicubic': pil_image.BICUBIC,

../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39
/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39: DeprecationWarning: HAMMING is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.HAMMING instead.
'hamming': pil_image.HAMMING,

../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40
/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40: DeprecationWarning: BOX is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BOX instead.
'box': pil_image.BOX,

../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41
/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41: DeprecationWarning: LANCZOS is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.LANCZOS instead.
'lanczos': pil_image.LANCZOS,

tests/unit/datasets/test_advertising.py: 1 warning
tests/unit/datasets/test_ecommerce.py: 3 warnings
tests/unit/datasets/test_entertainment.py: 4 warnings
tests/unit/datasets/test_social.py: 1 warning
tests/unit/datasets/test_synthetic.py: 10 warnings
tests/unit/implicit/test_implicit.py: 1 warning
tests/unit/lightfm/test_lightfm.py: 1 warning
tests/unit/tf/test_core.py: 6 warnings
tests/unit/tf/test_loader.py: 1 warning
tests/unit/tf/blocks/test_cross.py: 5 warnings
tests/unit/tf/blocks/test_dlrm.py: 9 warnings
tests/unit/tf/blocks/test_interactions.py: 2 warnings
tests/unit/tf/blocks/test_mlp.py: 60 warnings
tests/unit/tf/blocks/test_optimizer.py: 30 warnings
tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings
tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings
tests/unit/tf/core/test_aggregation.py: 6 warnings
tests/unit/tf/core/test_base.py: 2 warnings
tests/unit/tf/core/test_combinators.py: 11 warnings
tests/unit/tf/core/test_encoder.py: 6 warnings
tests/unit/tf/core/test_index.py: 8 warnings
tests/unit/tf/core/test_prediction.py: 2 warnings
tests/unit/tf/horovod/test_horovod.py: 3 warnings
tests/unit/tf/inputs/test_base.py: 1 warning
tests/unit/tf/inputs/test_continuous.py: 7 warnings
tests/unit/tf/inputs/test_embedding.py: 20 warnings
tests/unit/tf/inputs/test_tabular.py: 18 warnings
tests/unit/tf/models/test_base.py: 28 warnings
tests/unit/tf/models/test_benchmark.py: 2 warnings
tests/unit/tf/models/test_ranking.py: 38 warnings
tests/unit/tf/models/test_retrieval.py: 121 warnings
tests/unit/tf/outputs/test_base.py: 6 warnings
tests/unit/tf/outputs/test_classification.py: 6 warnings
tests/unit/tf/outputs/test_contrastive.py: 19 warnings
tests/unit/tf/outputs/test_regression.py: 2 warnings
tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings
tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings
tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings
tests/unit/tf/prediction_tasks/test_retrieval.py: 1 warning
tests/unit/tf/transformers/test_block.py: 16 warnings
tests/unit/tf/transforms/test_bias.py: 2 warnings
tests/unit/tf/transforms/test_features.py: 10 warnings
tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings
tests/unit/tf/transforms/test_noise.py: 1 warning
tests/unit/tf/transforms/test_sequence.py: 15 warnings
tests/unit/tf/utils/test_batch.py: 9 warnings
tests/unit/tf/utils/test_dataset.py: 2 warnings
tests/unit/torch/block/test_base.py: 4 warnings
tests/unit/torch/block/test_mlp.py: 1 warning
tests/unit/torch/features/test_continuous.py: 1 warning
tests/unit/torch/features/test_embedding.py: 4 warnings
tests/unit/torch/features/test_tabular.py: 4 warnings
tests/unit/torch/model/test_head.py: 12 warnings
tests/unit/torch/model/test_model.py: 2 warnings
tests/unit/torch/tabular/test_aggregation.py: 6 warnings
tests/unit/torch/tabular/test_transformations.py: 3 warnings
tests/unit/xgb/test_xgboost.py: 18 warnings
/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.ITEM_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.ITEM: 'item'>, <Tags.ID: 'id'>].
warnings.warn(

tests/unit/datasets/test_ecommerce.py: 3 warnings
tests/unit/datasets/test_entertainment.py: 4 warnings
tests/unit/datasets/test_social.py: 1 warning
tests/unit/datasets/test_synthetic.py: 9 warnings
tests/unit/implicit/test_implicit.py: 1 warning
tests/unit/lightfm/test_lightfm.py: 1 warning
tests/unit/tf/test_core.py: 6 warnings
tests/unit/tf/test_loader.py: 1 warning
tests/unit/tf/blocks/test_cross.py: 5 warnings
tests/unit/tf/blocks/test_dlrm.py: 9 warnings
tests/unit/tf/blocks/test_interactions.py: 2 warnings
tests/unit/tf/blocks/test_mlp.py: 60 warnings
tests/unit/tf/blocks/test_optimizer.py: 30 warnings
tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings
tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings
tests/unit/tf/core/test_aggregation.py: 6 warnings
tests/unit/tf/core/test_base.py: 2 warnings
tests/unit/tf/core/test_combinators.py: 11 warnings
tests/unit/tf/core/test_encoder.py: 7 warnings
tests/unit/tf/core/test_index.py: 3 warnings
tests/unit/tf/core/test_prediction.py: 2 warnings
tests/unit/tf/horovod/test_horovod.py: 1 warning
tests/unit/tf/inputs/test_base.py: 1 warning
tests/unit/tf/inputs/test_continuous.py: 7 warnings
tests/unit/tf/inputs/test_embedding.py: 20 warnings
tests/unit/tf/inputs/test_tabular.py: 18 warnings
tests/unit/tf/models/test_base.py: 28 warnings
tests/unit/tf/models/test_benchmark.py: 2 warnings
tests/unit/tf/models/test_ranking.py: 36 warnings
tests/unit/tf/models/test_retrieval.py: 87 warnings
tests/unit/tf/outputs/test_base.py: 6 warnings
tests/unit/tf/outputs/test_classification.py: 6 warnings
tests/unit/tf/outputs/test_contrastive.py: 19 warnings
tests/unit/tf/outputs/test_regression.py: 2 warnings
tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings
tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings
tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings
tests/unit/tf/transformers/test_block.py: 10 warnings
tests/unit/tf/transforms/test_features.py: 10 warnings
tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings
tests/unit/tf/transforms/test_sequence.py: 15 warnings
tests/unit/tf/utils/test_batch.py: 7 warnings
tests/unit/tf/utils/test_dataset.py: 2 warnings
tests/unit/torch/block/test_base.py: 4 warnings
tests/unit/torch/block/test_mlp.py: 1 warning
tests/unit/torch/features/test_continuous.py: 1 warning
tests/unit/torch/features/test_embedding.py: 4 warnings
tests/unit/torch/features/test_tabular.py: 4 warnings
tests/unit/torch/model/test_head.py: 12 warnings
tests/unit/torch/model/test_model.py: 2 warnings
tests/unit/torch/tabular/test_aggregation.py: 6 warnings
tests/unit/torch/tabular/test_transformations.py: 2 warnings
tests/unit/xgb/test_xgboost.py: 17 warnings
/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.USER_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.USER: 'user'>, <Tags.ID: 'id'>].
warnings.warn(

tests/unit/datasets/test_ecommerce.py: 1 warning
tests/unit/datasets/test_entertainment.py: 1 warning
tests/unit/implicit/test_implicit.py: 1 warning
tests/unit/lightfm/test_lightfm.py: 1 warning
tests/unit/tf/test_loader.py: 1 warning
tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings
tests/unit/tf/blocks/retrieval/test_two_tower.py: 2 warnings
tests/unit/tf/core/test_combinators.py: 11 warnings
tests/unit/tf/core/test_encoder.py: 2 warnings
tests/unit/tf/core/test_prediction.py: 1 warning
tests/unit/tf/horovod/test_horovod.py: 1 warning
tests/unit/tf/inputs/test_continuous.py: 4 warnings
tests/unit/tf/inputs/test_embedding.py: 9 warnings
tests/unit/tf/inputs/test_tabular.py: 8 warnings
tests/unit/tf/models/test_ranking.py: 20 warnings
tests/unit/tf/models/test_retrieval.py: 10 warnings
tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings
tests/unit/tf/prediction_tasks/test_regression.py: 3 warnings
tests/unit/tf/transforms/test_negative_sampling.py: 9 warnings
tests/unit/xgb/test_xgboost.py: 12 warnings
/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.SESSION_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.SESSION: 'session'>, <Tags.ID: 'id'>].
warnings.warn(

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export
tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export
tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export
tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export
tests/unit/tf/inputs/test_embedding.py::test_embedding_features_exporting_and_loading_pretrained_initializer
/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/inputs/embedding.py:970: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack
embeddings_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(embeddings)))

tests/unit/tf/blocks/retrieval/test_two_tower.py: 1 warning
tests/unit/tf/core/test_index.py: 4 warnings
tests/unit/tf/horovod/test_horovod.py: 3 warnings
tests/unit/tf/models/test_retrieval.py: 59 warnings
tests/unit/tf/prediction_tasks/test_next_item.py: 3 warnings
tests/unit/tf/utils/test_batch.py: 2 warnings
/tmp/autograph_generated_file32y8p8cw.py:8: DeprecationWarning: The 'warn' method is deprecated, use 'warning' instead
ag
.converted_call(ag__.ld(warnings).warn, ("The 'warn' method is deprecated, use 'warning' instead", ag__.ld(DeprecationWarning), 2), None, fscope)

tests/unit/tf/core/test_combinators.py::test_parallel_block_select_by_tags
/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/core/tabular.py:602: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated since Python 3.3, and in 3.10 it will stop working
elif isinstance(self.feature_names, collections.Sequence):

tests/unit/tf/core/test_encoder.py: 1 warning
tests/unit/tf/core/test_index.py: 5 warnings
tests/unit/tf/models/test_retrieval.py: 30 warnings
tests/unit/tf/utils/test_batch.py: 4 warnings
tests/unit/tf/utils/test_dataset.py: 1 warning
/var/jenkins_home/workspace/merlin_models/models/merlin/models/utils/dataset.py:75: DeprecationWarning: unique_rows_by_features is deprecated and will be removed in a future version. Please use unique_by_tag instead.
warnings.warn(

tests/unit/tf/models/test_base.py::test_model_pre_post[True]
tests/unit/tf/models/test_base.py::test_model_pre_post[False]
tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.1]
tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.3]
tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.5]
tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.7]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/util/dispatch.py:1082: UserWarning: tf.keras.backend.random_binomial is deprecated, and will be removed in a future version.Please use tf.keras.backend.random_bernoulli instead.
return dispatch_target(*args, **kwargs)

tests/unit/tf/models/test_base.py::test_freeze_parallel_block[True]
tests/unit/tf/models/test_base.py::test_freeze_sequential_block
tests/unit/tf/models/test_base.py::test_freeze_unfreeze
tests/unit/tf/models/test_base.py::test_unfreeze_all_blocks
/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/gradient_descent.py:108: UserWarning: The lr argument is deprecated, use learning_rate instead.
super(SGD, self).init(name, **kwargs)

tests/unit/tf/models/test_base.py::test_retrieval_model_query
tests/unit/tf/models/test_base.py::test_retrieval_model_query
tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_v2_export_embeddings
tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[True]
tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[False]
tests/unit/tf/transformers/test_block.py::test_retrieval_transformer[True]
/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/utils/tf_utils.py:298: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack
tensor_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(tensor)))

tests/unit/tf/models/test_ranking.py::test_deepfm_model_only_categ_feats[False]
tests/unit/tf/models/test_ranking.py::test_deepfm_model_categ_and_continuous_feats[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/models/test_ranking.py::test_wide_deep_model[False]
tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_categorical_one_hot[False]
tests/unit/tf/models/test_ranking.py::test_wide_deep_model_hashed_cross[False]
tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[True]
tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]
/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/transforms/features.py:569: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag
warnings.warn(

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/autograph/impl/api.py:371: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag
return py_builtins.overload_of(f)(*args)

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_onehot_multihot_feature_interaction[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_feature_interaction_multi_optimizer[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask/GatherV2:0", shape=(None, 48), dtype=float32), dense_shape=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Reshape_3:0", shape=(None,), dtype=int64), values=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Reshape_2:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask/GatherV2:0", shape=(None, 48), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_3:0", shape=(None,), dtype=int64), values=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_2:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/torch/block/test_mlp.py::test_mlp_block
/var/jenkins_home/workspace/merlin_models/models/tests/unit/torch/_conftest.py:151: UserWarning: Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at ../torch/csrc/utils/tensor_new.cpp:201.)
return {key: torch.tensor(value) for key, value in data.items()}

tests/unit/xgb/test_xgboost.py::test_without_dask_client
tests/unit/xgb/test_xgboost.py::TestXGBoost::test_music_regression
tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs0-DaskDeviceQuantileDMatrix]
tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs1-DaskDMatrix]
tests/unit/xgb/test_xgboost.py::TestEvals::test_multiple
tests/unit/xgb/test_xgboost.py::TestEvals::test_default
tests/unit/xgb/test_xgboost.py::TestEvals::test_train_and_valid
tests/unit/xgb/test_xgboost.py::TestEvals::test_invalid_data
/var/jenkins_home/workspace/merlin_models/models/merlin/models/xgb/init.py:344: UserWarning: Ignoring list columns as inputs to XGBoost model: ['item_genres', 'user_genres'].
warnings.warn(f"Ignoring list columns as inputs to XGBoost model: {list_column_names}.")

tests/unit/xgb/test_xgboost.py::TestXGBoost::test_unsupported_objective
/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/tornado/ioloop.py:350: DeprecationWarning: make_current is deprecated; start the event loop first
self.make_current()

tests/unit/xgb/test_xgboost.py::TestXGBoost::test_unsupported_objective
/var/jenkins_home/.local/lib/python3.8/site-packages/distributed/node.py:180: UserWarning: Port 8787 is already in use.
Perhaps you already have a cluster running?
Hosting the HTTP server on port 40953 instead
warnings.warn(

tests/unit/xgb/test_xgboost.py: 14 warnings
/usr/local/lib/python3.8/dist-packages/xgboost/dask.py:884: RuntimeWarning: coroutine 'Client._wait_for_workers' was never awaited
client.wait_for_workers(n_workers)
Enable tracemalloc to get traceback where the object was allocated.
See https://docs.pytest.org/en/stable/how-to/capture-warnings.html#resource-warnings for more info.

tests/unit/xgb/test_xgboost.py: 11 warnings
/usr/local/lib/python3.8/dist-packages/cudf/core/dataframe.py:1183: DeprecationWarning: The default dtype for empty Series will be 'object' instead of 'float64' in a future version. Specify a dtype explicitly to silence this warning.
mask = pd.Series(mask)

-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html

---------- coverage: platform linux, python 3.8.10-final-0 -----------
Name Stmts Miss Cover

merlin/datasets/init.py 2 0 100%
merlin/datasets/advertising/init.py 2 0 100%
merlin/datasets/advertising/criteo/init.py 0 0 100%
merlin/datasets/advertising/criteo/dataset.py 79 49 38%
merlin/datasets/advertising/criteo/transformed/init.py 0 0 100%
merlin/datasets/ecommerce/init.py 4 0 100%
merlin/datasets/ecommerce/aliccp/init.py 0 0 100%
merlin/datasets/ecommerce/aliccp/dataset.py 141 87 38%
merlin/datasets/ecommerce/aliccp/raw/init.py 0 0 100%
merlin/datasets/ecommerce/aliccp/transformed/init.py 0 0 100%
merlin/datasets/ecommerce/booking/init.py 0 0 100%
merlin/datasets/ecommerce/booking/dataset.py 127 100 21%
merlin/datasets/ecommerce/booking/raw/init.py 0 0 100%
merlin/datasets/ecommerce/booking/transformed/init.py 0 0 100%
merlin/datasets/ecommerce/dressipi/init.py 0 0 100%
merlin/datasets/ecommerce/dressipi/dataset.py 45 37 18%
merlin/datasets/ecommerce/dressipi/preprocessed/init.py 0 0 100%
merlin/datasets/ecommerce/large/init.py 0 0 100%
merlin/datasets/ecommerce/small/init.py 0 0 100%
merlin/datasets/ecommerce/transactions/init.py 0 0 100%
merlin/datasets/entertainment/init.py 2 0 100%
merlin/datasets/entertainment/movielens/1m-raw/init.py 0 0 100%
merlin/datasets/entertainment/movielens/1m-raw/ratings/init.py 0 0 100%
merlin/datasets/entertainment/movielens/1m/init.py 0 0 100%
merlin/datasets/entertainment/movielens/25m/init.py 0 0 100%
merlin/datasets/entertainment/movielens/100k/init.py 0 0 100%
merlin/datasets/entertainment/movielens/init.py 0 0 100%
merlin/datasets/entertainment/movielens/dataset.py 152 122 20%
merlin/datasets/entertainment/music_streaming/init.py 0 0 100%
merlin/datasets/social/init.py 0 0 100%
merlin/datasets/synthetic.py 147 8 95%
merlin/datasets/testing/init.py 0 0 100%
merlin/datasets/testing/sequence_testing/init.py 0 0 100%
merlin/models/init.py 2 0 100%
merlin/models/_version.py 354 205 42%
merlin/models/api.py 14 5 64%
merlin/models/config/init.py 0 0 100%
merlin/models/config/schema.py 62 0 100%
merlin/models/implicit/init.py 27 4 85%
merlin/models/io.py 15 0 100%
merlin/models/lightfm/init.py 23 0 100%
merlin/models/loader/init.py 0 0 100%
merlin/models/loader/backend.py 379 41 89%
merlin/models/loader/dataframe_iter.py 21 17 19%
merlin/models/loader/tf_utils.py 57 27 53%
merlin/models/loader/utils.py 40 15 62%
merlin/models/tf/init.py 70 0 100%
merlin/models/tf/blocks/init.py 0 0 100%
merlin/models/tf/blocks/cross.py 44 0 100%
merlin/models/tf/blocks/dlrm.py 49 2 96%
merlin/models/tf/blocks/experts.py 99 17 83%
merlin/models/tf/blocks/interaction.py 108 40 63%
merlin/models/tf/blocks/mlp.py 117 7 94%
merlin/models/tf/blocks/optimizer.py 173 12 93%
merlin/models/tf/blocks/retrieval/init.py 0 0 100%
merlin/models/tf/blocks/retrieval/base.py 175 62 65%
merlin/models/tf/blocks/retrieval/matrix_factorization.py 35 1 97%
merlin/models/tf/blocks/retrieval/two_tower.py 30 0 100%
merlin/models/tf/blocks/sampling/init.py 0 0 100%
merlin/models/tf/blocks/sampling/base.py 29 2 93%
merlin/models/tf/blocks/sampling/cross_batch.py 46 2 96%
merlin/models/tf/blocks/sampling/in_batch.py 35 0 100%
merlin/models/tf/blocks/sampling/queue.py 115 12 90%
merlin/models/tf/core/init.py 0 0 100%
merlin/models/tf/core/aggregation.py 241 45 81%
merlin/models/tf/core/base.py 242 50 79%
merlin/models/tf/core/combinators.py 426 53 88%
merlin/models/tf/core/encoder.py 175 28 84%
merlin/models/tf/core/index.py 106 16 85%
merlin/models/tf/core/prediction.py 50 1 98%
merlin/models/tf/core/tabular.py 280 29 90%
merlin/models/tf/distributed/init.py 0 0 100%
merlin/models/tf/distributed/backend.py 9 2 78%
merlin/models/tf/inputs/init.py 0 0 100%
merlin/models/tf/inputs/base.py 60 10 83%
merlin/models/tf/inputs/continuous.py 39 3 92%
merlin/models/tf/inputs/embedding.py 458 32 93%
merlin/models/tf/loader.py 268 94 65%
merlin/models/tf/losses/init.py 4 0 100%
merlin/models/tf/losses/base.py 9 0 100%
merlin/models/tf/losses/listwise.py 13 0 100%
merlin/models/tf/losses/pairwise.py 115 1 99%
merlin/models/tf/metrics/init.py 2 0 100%
merlin/models/tf/metrics/evaluation.py 105 48 54%
merlin/models/tf/metrics/topk.py 198 48 76%
merlin/models/tf/models/init.py 0 0 100%
merlin/models/tf/models/base.py 756 101 87%
merlin/models/tf/models/benchmark.py 16 0 100%
merlin/models/tf/models/ranking.py 67 3 96%
merlin/models/tf/models/retrieval.py 78 4 95%
merlin/models/tf/models/utils.py 10 1 90%
merlin/models/tf/outputs/init.py 0 0 100%
merlin/models/tf/outputs/base.py 123 17 86%
merlin/models/tf/outputs/classification.py 91 1 99%
merlin/models/tf/outputs/contrastive.py 147 10 93%
merlin/models/tf/outputs/regression.py 9 0 100%
merlin/models/tf/outputs/sampling/init.py 0 0 100%
merlin/models/tf/outputs/sampling/base.py 78 21 73%
merlin/models/tf/outputs/sampling/in_batch.py 37 1 97%
merlin/models/tf/outputs/sampling/popularity.py 27 1 96%
merlin/models/tf/outputs/topk.py 98 6 94%
merlin/models/tf/prediction_tasks/init.py 0 0 100%
merlin/models/tf/prediction_tasks/base.py 207 37 82%
merlin/models/tf/prediction_tasks/classification.py 68 17 75%
merlin/models/tf/prediction_tasks/multi.py 7 0 100%
merlin/models/tf/prediction_tasks/next_item.py 59 6 90%
merlin/models/tf/prediction_tasks/regression.py 35 2 94%
merlin/models/tf/prediction_tasks/retrieval.py 73 3 96%
merlin/models/tf/transformers/init.py 0 0 100%
merlin/models/tf/transformers/block.py 101 2 98%
merlin/models/tf/transformers/transforms.py 63 0 100%
merlin/models/tf/transforms/init.py 0 0 100%
merlin/models/tf/transforms/bias.py 111 9 92%
merlin/models/tf/transforms/features.py 435 36 92%
merlin/models/tf/transforms/negative_sampling.py 77 3 96%
merlin/models/tf/transforms/noise.py 43 1 98%
merlin/models/tf/transforms/regularization.py 17 1 94%
merlin/models/tf/transforms/sequence.py 282 42 85%
merlin/models/tf/transforms/tensor.py 158 13 92%
merlin/models/tf/typing.py 7 0 100%
merlin/models/tf/utils/init.py 0 0 100%
merlin/models/tf/utils/batch_utils.py 85 4 95%
merlin/models/tf/utils/repr_utils.py 69 4 94%
merlin/models/tf/utils/search_utils.py 34 22 35%
merlin/models/tf/utils/testing_utils.py 206 36 83%
merlin/models/tf/utils/tf_utils.py 209 42 80%
merlin/models/torch/init.py 12 0 100%
merlin/models/torch/block/init.py 0 0 100%
merlin/models/torch/block/base.py 167 32 81%
merlin/models/torch/block/mlp.py 38 5 87%
merlin/models/torch/dataset.py 68 5 93%
merlin/models/torch/features/init.py 0 0 100%
merlin/models/torch/features/base.py 4 0 100%
merlin/models/torch/features/continuous.py 22 0 100%
merlin/models/torch/features/embedding.py 165 12 93%
merlin/models/torch/features/tabular.py 65 8 88%
merlin/models/torch/losses.py 28 28 0%
merlin/models/torch/model/init.py 0 0 100%
merlin/models/torch/model/base.py 286 65 77%
merlin/models/torch/model/prediction_task.py 24 0 100%
merlin/models/torch/tabular/init.py 0 0 100%
merlin/models/torch/tabular/aggregation.py 75 0 100%
merlin/models/torch/tabular/base.py 247 39 84%
merlin/models/torch/tabular/transformations.py 67 3 96%
merlin/models/torch/typing.py 6 0 100%
merlin/models/torch/utils/init.py 0 0 100%
merlin/models/torch/utils/data_utils.py 117 117 0%
merlin/models/torch/utils/examples_utils.py 39 39 0%
merlin/models/torch/utils/torch_utils.py 80 22 72%
merlin/models/utils/init.py 0 0 100%
merlin/models/utils/constants.py 3 0 100%
merlin/models/utils/dataset.py 38 4 89%
merlin/models/utils/dependencies.py 26 19 27%
merlin/models/utils/doc_utils.py 10 0 100%
merlin/models/utils/example_utils.py 31 8 74%
merlin/models/utils/misc_utils.py 118 90 24%
merlin/models/utils/nvt_utils.py 27 24 11%
merlin/models/utils/registry.py 101 29 71%
merlin/models/utils/schema_utils.py 90 19 79%
merlin/models/xgb/init.py 124 4 97%

TOTAL 11581 2352 80%

=========================== short test summary info ============================
SKIPPED [1] tests/unit/datasets/test_advertising.py:20: No data-dir available, pass it through env variable $INPUT_DATA_DIR
SKIPPED [1] tests/unit/datasets/test_ecommerce.py:64: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP
SKIPPED [1] tests/unit/datasets/test_ecommerce.py:80: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP
SKIPPED [1] tests/unit/datasets/test_ecommerce.py:94: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP
SKIPPED [1] tests/unit/datasets/test_ecommerce.py:115: No data-dir available, pass it through env variable $INPUT_DATA_DIR
SKIPPED [3] tests/unit/datasets/test_entertainment.py:44: No data-dir available, pass it through env variable $INPUT_DATA_DIR
SKIPPED [5] ../../../.local/lib/python3.8/site-packages/tensorflow/python/framework/test_util.py:2746: Not a test.
==== 4 failed, 867 passed, 13 skipped, 1453 warnings in 1830.49s (0:30:30) =====
ERROR: InvocationError for command /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/bin/python -m pytest --cov-report term --cov merlin -rxs tests/unit (exited with code 1)
___________________________________ summary ____________________________________
ERROR: py38-gpu: commands failed
Build step 'Execute shell' marked build as failure
Performing Post build task...
Match found for : : True
Logical operation result is TRUE
Running script : #!/bin/bash
cd /var/jenkins_home/
CUDA_VISIBLE_DEVICES=1 python test_res_push.py "https://api.GitHub.com/repos/NVIDIA-Merlin/models/issues/$ghprbPullId/comments" "/var/jenkins_home/jobs/$JOB_NAME/builds/$BUILD_NUMBER/log"
[merlin_models] $ /bin/bash /tmp/jenkins2437037306233921613.sh

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GitHub pull request #855 of commit c64d8bf5e3592d680f74b234548cd5b2f507714a, no merge conflicts.
Running as SYSTEM
Setting status of c64d8bf5e3592d680f74b234548cd5b2f507714a to PENDING with url http://merlin-infra1.nvidia.com:8080/job/merlin_models/1925/ and message: 'Pending'
Using context: Jenkins
Building on master in workspace /var/jenkins_home/workspace/merlin_models
using credential nvidia-merlin-bot
 > git rev-parse --is-inside-work-tree # timeout=10
Fetching changes from the remote Git repository
 > git config remote.origin.url https://github.com/NVIDIA-Merlin/models/ # timeout=10
Fetching upstream changes from https://github.com/NVIDIA-Merlin/models/
 > git --version # timeout=10
using GIT_ASKPASS to set credentials This is the bot credentials for our CI/CD
 > git fetch --tags --force --progress -- https://github.com/NVIDIA-Merlin/models/ +refs/pull/855/*:refs/remotes/origin/pr/855/* # timeout=10
 > git rev-parse c64d8bf5e3592d680f74b234548cd5b2f507714a^{commit} # timeout=10
Checking out Revision c64d8bf5e3592d680f74b234548cd5b2f507714a (detached)
 > git config core.sparsecheckout # timeout=10
 > git checkout -f c64d8bf5e3592d680f74b234548cd5b2f507714a # timeout=10
Commit message: "update notebook based on comments"
 > git rev-list --no-walk c64d8bf5e3592d680f74b234548cd5b2f507714a # timeout=10
[merlin_models] $ /bin/bash /tmp/jenkins2228489495711406818.sh
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
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Requirement already satisfied: nbclient>=0.4.0 in /usr/local/lib/python3.8/dist-packages (from testbook) (0.6.8)
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Requirement already satisfied: pyrsistent!=0.17.0,!=0.17.1,!=0.17.2,>=0.14.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (0.18.1)
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Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.8.2->jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (1.15.0)
GLOB sdist-make: /var/jenkins_home/workspace/merlin_models/models/setup.py
py38-gpu recreate: /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
py38-gpu installdeps: -rrequirements/dev.txt, tensorflow<2.10
WARNING: Discarding $PYTHONPATH from environment, to override specify PYTHONPATH in 'passenv' in your configuration.
py38-gpu inst: /var/jenkins_home/workspace/merlin_models/models/.tox/.tmp/package/4/merlin-models-0.9.0+63.gc64d8bf5.zip
WARNING: Discarding $PYTHONPATH from environment, to override specify PYTHONPATH in 'passenv' in your configuration.
py38-gpu installed: absl-py==1.2.0,aiohttp==3.8.1,aiosignal==1.2.0,alabaster==0.7.12,alembic==1.8.1,anyio==3.6.1,appdirs==1.4.4,argon2-cffi==21.3.0,argon2-cffi-bindings==21.2.0,astroid==2.5.6,asttokens==2.0.8,astunparse==1.6.3,asv==0.5.1,asvdb==0.4.2,async-timeout==4.0.2,attrs==22.1.0,autopage==0.5.1,awscli==1.27.14,Babel==2.10.3,backcall==0.2.0,beautifulsoup4==4.11.1,betterproto==1.2.5,black==20.8b1,bleach==5.0.1,bokeh==3.0.2,boto3==1.24.75,botocore==1.29.14,Brotli==1.0.9,build==0.9.0,cachetools==5.2.0,certifi==2019.11.28,cffi==1.15.1,chardet==3.0.4,charset-normalizer==2.1.1,check-manifest==0.48,clang==5.0,click==8.1.3,cliff==4.1.0,cloudpickle==2.2.0,cmaes==0.9.0,cmake==3.24.1.1,cmd2==2.4.2,colorama==0.4.4,colorlog==6.7.0,contourpy==1.0.5,coverage==6.5.0,cuda-python==11.7.1,cupy-cuda117==10.6.0,cycler==0.11.0,Cython==0.29.32,dask==2022.1.1,dbus-python==1.2.16,debugpy==1.6.3,decorator==5.1.1,defusedxml==0.7.1,dill==0.3.5.1,distlib==0.3.6,distributed==2022.5.1,distro==1.7.0,dm-tree==0.1.6,docker-pycreds==0.4.0,docutils==0.16,emoji==1.7.0,entrypoints==0.4,execnet==1.9.0,executing==1.0.0,faiss==1.7.2,faiss-gpu==1.7.2,fastai==2.7.9,fastapi==0.85.0,fastavro==1.6.1,fastcore==1.5.27,fastdownload==0.0.7,fastjsonschema==2.16.1,fastprogress==1.0.3,fastrlock==0.8,feast==0.19.4,fiddle==0.2.2,filelock==3.8.0,flake8==5.0.4,flatbuffers==1.12,fonttools==4.37.3,frozenlist==1.3.1,fsspec==2022.5.0,gast==0.4.0,gevent==21.12.0,geventhttpclient==2.0.2,gitdb==4.0.9,GitPython==3.1.27,google==3.0.0,google-api-core==2.10.1,google-auth==2.11.1,google-auth-oauthlib==0.4.6,google-pasta==0.2.0,googleapis-common-protos==1.52.0,graphviz==0.20.1,greenlet==1.1.3,grpcio==1.41.0,grpcio-channelz==1.49.0,grpcio-reflection==1.48.1,grpclib==0.4.3,h11==0.13.0,h2==4.1.0,h5py==3.7.0,HeapDict==1.0.1,horovod==0.26.1,hpack==4.0.0,httptools==0.5.0,hugectr2onnx==0.0.0,huggingface-hub==0.9.1,hyperframe==6.0.1,idna==2.8,imagesize==1.4.1,implicit==0.6.1,importlib-metadata==4.12.0,importlib-resources==5.9.0,iniconfig==1.1.1,interrogate==1.5.0,ipykernel==6.15.3,ipython==8.5.0,ipython-genutils==0.2.0,ipywidgets==7.7.0,isort==5.10.1,jedi==0.18.1,Jinja2==3.1.2,jmespath==1.0.1,joblib==1.2.0,json5==0.9.10,jsonschema==4.16.0,jupyter==1.0.0,jupyter-cache==0.4.3,jupyter-console==6.4.4,jupyter-core==4.11.1,jupyter-server==1.18.1,jupyter-server-mathjax==0.2.5,jupyter-sphinx==0.3.2,jupyter_client==7.3.5,jupyterlab==3.4.7,jupyterlab-pygments==0.2.2,jupyterlab-widgets==1.1.0,jupyterlab_server==2.15.1,keras==2.9.0,Keras-Preprocessing==1.1.2,kiwisolver==1.4.4,lazy-object-proxy==1.8.0,libclang==14.0.6,libcst==0.4.7,lightfm==1.16,lightgbm==3.3.2,linkify-it-py==1.0.3,llvmlite==0.39.1,locket==1.0.0,lxml==4.9.1,Mako==1.2.4,Markdown==3.4.1,markdown-it-py==1.1.0,MarkupSafe==2.1.1,matplotlib==3.6.0,matplotlib-inline==0.1.6,mccabe==0.7.0,mdit-py-plugins==0.2.8,merlin-core==0.6.0+1.g5926fcf,merlin-models==0.9.0+63.gc64d8bf5,merlin-systems==0.5.0+4.g15074ad,mistune==2.0.4,mmh3==3.0.0,mpi4py==3.1.3,msgpack==1.0.4,multidict==6.0.2,mypy==0.991,mypy-extensions==0.4.3,myst-nb==0.13.2,myst-parser==0.15.2,natsort==8.1.0,nbclassic==0.4.3,nbclient==0.6.8,nbconvert==7.0.0,nbdime==3.1.1,nbformat==5.5.0,nest-asyncio==1.5.5,ninja==1.10.2.3,notebook==6.4.12,notebook-shim==0.1.0,numba==0.56.2,numpy==1.22.4,nvidia-pyindex==1.0.9,# Editable install with no version control (nvtabular==1.4.0+8.g95e12d347),-e /usr/local/lib/python3.8/dist-packages,nvtx==0.2.5,oauthlib==3.2.1,oldest-supported-numpy==2022.8.16,onnx==1.12.0,onnxruntime==1.11.1,opt-einsum==3.3.0,optuna==3.0.3,packaging==21.3,pandas==1.3.5,pandavro==1.5.2,pandocfilters==1.5.0,parso==0.8.3,partd==1.3.0,pathspec==0.10.2,pathtools==0.1.2,pbr==5.11.0,pep517==0.13.0,pexpect==4.8.0,pickleshare==0.7.5,Pillow==9.2.0,pkgutil_resolve_name==1.3.10,platformdirs==2.5.2,plotly==5.11.0,pluggy==1.0.0,prettytable==3.5.0,prometheus-client==0.14.1,promise==2.3,prompt-toolkit==3.0.31,proto-plus==1.19.6,protobuf==3.19.5,psutil==5.9.2,ptyprocess==0.7.0,pure-eval==0.2.2,py==1.11.0,pyarrow==7.0.0,pyasn1==0.4.8,pyasn1-modules==0.2.8,pybind11==2.10.0,pycodestyle==2.9.1,pycparser==2.21,pydantic==1.10.2,pydot==1.4.2,pyflakes==2.5.0,Pygments==2.13.0,PyGObject==3.36.0,pynvml==11.4.1,pyparsing==3.0.9,pyperclip==1.8.2,pyrsistent==0.18.1,pytest==7.1.3,pytest-cov==4.0.0,pytest-xdist==3.0.2,python-apt==2.0.0+ubuntu0.20.4.8,python-dateutil==2.8.2,python-dotenv==0.21.0,python-rapidjson==1.8,pytz==2022.2.1,PyYAML==5.4.1,pyzmq==24.0.0,qtconsole==5.4.0,QtPy==2.3.0,regex==2022.9.13,requests==2.22.0,requests-oauthlib==1.3.1,requests-unixsocket==0.2.0,rsa==4.7.2,s3fs==2022.2.0,s3transfer==0.6.0,sacremoses==0.0.53,scikit-build==0.15.0,scikit-learn==1.1.2,scipy==1.8.1,seedir==0.3.0,Send2Trash==1.8.0,sentry-sdk==1.9.8,setproctitle==1.3.2,setuptools-scm==7.0.5,shortuuid==1.0.9,six==1.15.0,sklearn==0.0,smmap==5.0.0,sniffio==1.3.0,snowballstemmer==2.2.0,sortedcontainers==2.4.0,soupsieve==2.3.2.post1,Sphinx==5.3.0,sphinx-multiversion==0.2.4,sphinx-togglebutton==0.3.1,sphinx_external_toc==0.3.0,sphinxcontrib-applehelp==1.0.2,sphinxcontrib-copydirs @ git+https://github.com/mikemckiernan/sphinxcontrib-copydirs.git@bd8c5d79b3f91cf5f1bb0d6995aeca3fe84b670e,sphinxcontrib-devhelp==1.0.2,sphinxcontrib-htmlhelp==2.0.0,sphinxcontrib-jsmath==1.0.1,sphinxcontrib-qthelp==1.0.3,sphinxcontrib-serializinghtml==1.1.5,SQLAlchemy==1.4.44,stack-data==0.5.0,starlette==0.20.4,stevedore==4.1.1,stringcase==1.2.0,supervisor==4.1.0,tabulate==0.8.10,tblib==1.7.0,tdqm==0.0.1,tenacity==8.0.1,tensorboard==2.9.1,tensorboard-data-server==0.6.1,tensorboard-plugin-wit==1.8.1,tensorflow==2.9.2,tensorflow-estimator==2.9.0,tensorflow-gpu==2.9.2,tensorflow-io-gcs-filesystem==0.27.0,tensorflow-metadata==1.10.0,termcolor==2.0.1,terminado==0.15.0,testbook==0.4.2,threadpoolctl==3.1.0,tinycss2==1.1.1,tokenizers==0.10.3,toml==0.10.2,tomli==2.0.1,toolz==0.12.0,torch==1.12.1+cu113,torchmetrics==0.3.2,tornado==6.2,tox==3.26.0,tqdm==4.64.1,traitlets==5.4.0,transformers==4.12.0,transformers4rec==0.1.12+2.gbcc939255,treelite==2.3.0,treelite-runtime==2.3.0,tritonclient==2.25.0,typed-ast==1.5.4,typing-inspect==0.8.0,typing_extensions==4.3.0,uc-micro-py==1.0.1,urllib3==1.26.12,uvicorn==0.18.3,uvloop==0.17.0,versioneer==0.20,virtualenv==20.16.5,wandb==0.13.3,watchfiles==0.17.0,wcwidth==0.2.5,webencodings==0.5.1,websocket-client==1.4.1,websockets==10.3,Werkzeug==2.2.2,widgetsnbextension==3.6.0,wrapt==1.12.1,xgboost==1.6.2,xyzservices==2022.9.0,yarl==1.8.1,zict==2.2.0,zipp==3.8.1,zope.event==4.5.0,zope.interface==5.4.0
py38-gpu run-test-pre: PYTHONHASHSEED='1917975477'
py38-gpu run-test: commands[0] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/core.git
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Collecting git+https://github.com/NVIDIA-Merlin/core.git
  Cloning https://github.com/NVIDIA-Merlin/core.git to /tmp/pip-req-build-mj84ltr3
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/core.git /tmp/pip-req-build-mj84ltr3
  Resolved https://github.com/NVIDIA-Merlin/core.git to commit 72f967a00a9f107b328a26afbbfe63512a5a5da9
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: packaging in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+18.g72f967a) (21.3)
Requirement already satisfied: dask>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+18.g72f967a) (2022.3.0)
Requirement already satisfied: protobuf>=3.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+18.g72f967a) (3.19.5)
Requirement already satisfied: fsspec==2022.5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+18.g72f967a) (2022.5.0)
Requirement already satisfied: numba>=0.54 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+18.g72f967a) (0.55.1)
Requirement already satisfied: tqdm>=4.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+18.g72f967a) (4.64.1)
Requirement already satisfied: pandas<1.4.0dev0,>=1.2.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+18.g72f967a) (1.3.5)
Requirement already satisfied: pyarrow>=5.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+18.g72f967a) (7.0.0)
Requirement already satisfied: betterproto<2.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+18.g72f967a) (1.2.5)
Requirement already satisfied: tensorflow-metadata>=1.2.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+18.g72f967a) (1.10.0)
Requirement already satisfied: distributed>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+18.g72f967a) (2022.3.0)
Requirement already satisfied: grpclib in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core==0.8.0+18.g72f967a) (0.4.3)
Requirement already satisfied: stringcase in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core==0.8.0+18.g72f967a) (1.2.0)
Requirement already satisfied: toolz>=0.8.2 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core==0.8.0+18.g72f967a) (0.12.0)
Requirement already satisfied: pyyaml>=5.3.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/PyYAML-5.4.1-py3.8-linux-x86_64.egg (from dask>=2022.3.0->merlin-core==0.8.0+18.g72f967a) (5.4.1)
Requirement already satisfied: partd>=0.3.10 in /var/jenkins_home/.local/lib/python3.8/site-packages/partd-1.2.0-py3.8.egg (from dask>=2022.3.0->merlin-core==0.8.0+18.g72f967a) (1.2.0)
Requirement already satisfied: cloudpickle>=1.1.1 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core==0.8.0+18.g72f967a) (2.2.0)
Requirement already satisfied: tblib>=1.6.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/tblib-1.7.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+18.g72f967a) (1.7.0)
Requirement already satisfied: sortedcontainers!=2.0.0,!=2.0.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/sortedcontainers-2.4.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+18.g72f967a) (2.4.0)
Requirement already satisfied: psutil>=5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/psutil-5.8.0-py3.8-linux-x86_64.egg (from distributed>=2022.3.0->merlin-core==0.8.0+18.g72f967a) (5.8.0)
Requirement already satisfied: zict>=0.1.3 in /var/jenkins_home/.local/lib/python3.8/site-packages/zict-2.0.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+18.g72f967a) (2.0.0)
Requirement already satisfied: jinja2 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+18.g72f967a) (3.1.2)
Requirement already satisfied: tornado>=6.0.3 in ./.tox/py38-gpu/lib/python3.8/site-packages (from distributed>=2022.3.0->merlin-core==0.8.0+18.g72f967a) (6.2)
Requirement already satisfied: click>=6.6 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+18.g72f967a) (8.1.3)
Requirement already satisfied: msgpack>=0.6.0 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+18.g72f967a) (1.0.4)
Requirement already satisfied: llvmlite<0.39,>=0.38.0rc1 in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+18.g72f967a) (0.38.1)
Requirement already satisfied: numpy<1.22,>=1.18 in /var/jenkins_home/.local/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+18.g72f967a) (1.20.3)
Requirement already satisfied: setuptools in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+18.g72f967a) (65.5.1)
Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in /usr/local/lib/python3.8/dist-packages (from packaging->merlin-core==0.8.0+18.g72f967a) (3.0.9)
Requirement already satisfied: pytz>=2017.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+18.g72f967a) (2022.2.1)
Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+18.g72f967a) (2.8.2)
Requirement already satisfied: absl-py<2.0.0,>=0.9 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core==0.8.0+18.g72f967a) (1.2.0)
Requirement already satisfied: googleapis-common-protos<2,>=1.52.0 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core==0.8.0+18.g72f967a) (1.52.0)
Requirement already satisfied: locket in /var/jenkins_home/.local/lib/python3.8/site-packages/locket-0.2.1-py3.8.egg (from partd>=0.3.10->dask>=2022.3.0->merlin-core==0.8.0+18.g72f967a) (0.2.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.7.3->pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+18.g72f967a) (1.15.0)
Requirement already satisfied: heapdict in /var/jenkins_home/.local/lib/python3.8/site-packages/HeapDict-1.0.1-py3.8.egg (from zict>=0.1.3->distributed>=2022.3.0->merlin-core==0.8.0+18.g72f967a) (1.0.1)
Requirement already satisfied: multidict in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core==0.8.0+18.g72f967a) (6.0.2)
Requirement already satisfied: h2<5,>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core==0.8.0+18.g72f967a) (4.1.0)
Requirement already satisfied: MarkupSafe>=2.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from jinja2->distributed>=2022.3.0->merlin-core==0.8.0+18.g72f967a) (2.0.1)
Requirement already satisfied: hpack<5,>=4.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core==0.8.0+18.g72f967a) (4.0.0)
Requirement already satisfied: hyperframe<7,>=6.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core==0.8.0+18.g72f967a) (6.0.1)
Building wheels for collected packages: merlin-core
  Building wheel for merlin-core (pyproject.toml): started
  Building wheel for merlin-core (pyproject.toml): finished with status 'done'
  Created wheel for merlin-core: filename=merlin_core-0.8.0+18.g72f967a-py3-none-any.whl size=118899 sha256=5fa7610f6049505bf05b5de3f88afce3e5fc60c8b6511febf9d83357a43f599d
  Stored in directory: /tmp/pip-ephem-wheel-cache-v8ny3ucw/wheels/c8/38/16/a6968787eafcec5fa772148af8408b089562f71af0752e8e84
Successfully built merlin-core
Installing collected packages: merlin-core
  Attempting uninstall: merlin-core
    Found existing installation: merlin-core 0.3.0+12.g78ecddd
    Not uninstalling merlin-core at /var/jenkins_home/.local/lib/python3.8/site-packages, outside environment /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
    Can't uninstall 'merlin-core'. No files were found to uninstall.
Successfully installed merlin-core-0.8.0+18.g72f967a
py38-gpu run-test: commands[1] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/nvtabular.git
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Collecting git+https://github.com/NVIDIA-Merlin/nvtabular.git
  Cloning https://github.com/NVIDIA-Merlin/nvtabular.git to /tmp/pip-req-build-de8e9xuv
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/nvtabular.git /tmp/pip-req-build-de8e9xuv
  Resolved https://github.com/NVIDIA-Merlin/nvtabular.git to commit e5b7351deb9e4885c4038aa0bbc9f146d8477a0e
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: merlin-core>=0.2.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from nvtabular==1.6.0+6.ge5b7351d) (0.8.0+18.g72f967a)
Requirement already satisfied: scipy in /usr/local/lib/python3.8/dist-packages (from nvtabular==1.6.0+6.ge5b7351d) (1.8.1)
Collecting merlin-dataloader>=0.0.2
  Downloading merlin-dataloader-0.0.2.tar.gz (44 kB)
     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 44.1/44.1 kB 1.7 MB/s eta 0:00:00
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
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Building wheels for collected packages: nvtabular, merlin-dataloader
  Building wheel for nvtabular (pyproject.toml): started
  Building wheel for nvtabular (pyproject.toml): finished with status 'done'
  Created wheel for nvtabular: filename=nvtabular-1.6.0+6.ge5b7351d-cp38-cp38-linux_x86_64.whl size=257597 sha256=05b1e2f52237c6dfcbb70f718cb38f5265157a80454f027fc99a0ddbb3c0f1f0
  Stored in directory: /tmp/pip-ephem-wheel-cache-0sa2scy2/wheels/8f/d9/f9/30f2cdc5bf8787fae6fdfe55afd6e1b493e619ec32c32ec40b
  Building wheel for merlin-dataloader (pyproject.toml): started
  Building wheel for merlin-dataloader (pyproject.toml): finished with status 'done'
  Created wheel for merlin-dataloader: filename=merlin_dataloader-0.0.2-py3-none-any.whl size=29203 sha256=a6fe0eba592d9e399c5689417ee4a95a5282a3165e04857ead0ff8eac647cd0e
  Stored in directory: /tmp/pip-ephem-wheel-cache-0sa2scy2/wheels/76/ef/ed/cb880e3ef5192ec5940e26fd9442247b569fb0cf8602f97137
Successfully built nvtabular merlin-dataloader
Installing collected packages: merlin-dataloader, nvtabular
  Attempting uninstall: nvtabular
    Found existing installation: nvtabular 1.1.1
    Not uninstalling nvtabular at /var/jenkins_home/.local/lib/python3.8/site-packages, outside environment /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
    Can't uninstall 'nvtabular'. No files were found to uninstall.
Successfully installed merlin-dataloader-0.0.2 nvtabular-1.6.0+6.ge5b7351d
py38-gpu run-test: commands[2] | python -m pytest --cov-report term --cov merlin -rxs tests/unit
============================= test session starts ==============================
platform linux -- Python 3.8.10, pytest-7.1.3, pluggy-1.0.0
cachedir: .tox/py38-gpu/.pytest_cache
rootdir: /var/jenkins_home/workspace/merlin_models/models, configfile: pyproject.toml
plugins: anyio-3.5.0, xdist-3.0.2, cov-4.0.0
collected 884 items

tests/unit/config/test_schema.py .... [ 0%]
tests/unit/datasets/test_advertising.py .s [ 0%]
tests/unit/datasets/test_ecommerce.py ..sss.s [ 1%]
tests/unit/datasets/test_entertainment.py ....sss. [ 2%]
tests/unit/datasets/test_social.py . [ 2%]
tests/unit/datasets/test_synthetic.py .......... [ 3%]
tests/unit/implicit/test_implicit.py . [ 3%]
tests/unit/lightfm/test_lightfm.py . [ 3%]
tests/unit/tf/test_core.py ...... [ 4%]
tests/unit/tf/test_loader.py ................ [ 6%]
tests/unit/tf/test_public_api.py . [ 6%]
tests/unit/tf/blocks/test_cross.py ........... [ 7%]
tests/unit/tf/blocks/test_dlrm.py .......... [ 8%]
tests/unit/tf/blocks/test_interactions.py ... [ 9%]
tests/unit/tf/blocks/test_mlp.py ....................................... [ 13%]
............................ [ 16%]
tests/unit/tf/blocks/test_optimizer.py s................................ [ 20%]
..................... [ 22%]
tests/unit/tf/blocks/retrieval/test_base.py . [ 22%]
tests/unit/tf/blocks/retrieval/test_matrix_factorization.py .. [ 23%]
tests/unit/tf/blocks/retrieval/test_two_tower.py ............ [ 24%]
tests/unit/tf/blocks/sampling/test_cross_batch.py . [ 24%]
tests/unit/tf/blocks/sampling/test_in_batch.py . [ 24%]
tests/unit/tf/core/test_aggregation.py ......... [ 25%]
tests/unit/tf/core/test_base.py .. [ 26%]
tests/unit/tf/core/test_combinators.py s..................... [ 28%]
tests/unit/tf/core/test_encoder.py .. [ 28%]
tests/unit/tf/core/test_index.py ... [ 29%]
tests/unit/tf/core/test_prediction.py .. [ 29%]
tests/unit/tf/core/test_tabular.py ...... [ 29%]
tests/unit/tf/examples/test_01_getting_started.py . [ 30%]
tests/unit/tf/examples/test_02_dataschema.py . [ 30%]
tests/unit/tf/examples/test_03_exploring_different_models.py . [ 30%]
tests/unit/tf/examples/test_04_export_ranking_models.py . [ 30%]
tests/unit/tf/examples/test_05_export_retrieval_model.py . [ 30%]
tests/unit/tf/examples/test_06_advanced_own_architecture.py . [ 30%]
tests/unit/tf/examples/test_07_train_traditional_models.py . [ 30%]
tests/unit/tf/examples/test_usecase_accelerate_training_by_lazyadam.py . [ 30%]
[ 30%]
tests/unit/tf/examples/test_usecase_data_parallel.py . [ 30%]
tests/unit/tf/examples/test_usecase_ecommerce_session_based.py . [ 31%]
tests/unit/tf/examples/test_usecase_incremental_training_layer_freezing.py . [ 31%]
[ 31%]
tests/unit/tf/examples/test_usecase_pretrained_embeddings.py . [ 31%]
tests/unit/tf/examples/test_usecase_retrieval_with_hpo.py . [ 31%]
tests/unit/tf/examples/test_usecase_transformers_next_item_prediction.py . [ 31%]
[ 31%]
tests/unit/tf/horovod/test_horovod.py ... [ 31%]
tests/unit/tf/inputs/test_base.py . [ 32%]
tests/unit/tf/inputs/test_continuous.py ........ [ 32%]
tests/unit/tf/inputs/test_embedding.py ................................. [ 36%]
........ [ 37%]
tests/unit/tf/inputs/test_tabular.py .................. [ 39%]
tests/unit/tf/layers/test_queue.py .............. [ 41%]
tests/unit/tf/losses/test_losses.py ....................... [ 43%]
tests/unit/tf/metrics/test_metrics_popularity.py ..... [ 44%]
tests/unit/tf/metrics/test_metrics_topk.py ......................... [ 47%]
tests/unit/tf/models/test_base.py s......................... [ 50%]
tests/unit/tf/models/test_benchmark.py .. [ 50%]
tests/unit/tf/models/test_ranking.py .................................. [ 54%]
tests/unit/tf/models/test_retrieval.py ................................. [ 57%]
........................................... [ 62%]
tests/unit/tf/outputs/test_base.py ...... [ 63%]
tests/unit/tf/outputs/test_classification.py ...... [ 64%]
tests/unit/tf/outputs/test_contrastive.py .............. [ 65%]
tests/unit/tf/outputs/test_regression.py .. [ 65%]
tests/unit/tf/outputs/test_sampling.py .... [ 66%]
tests/unit/tf/outputs/test_topk.py . [ 66%]
tests/unit/tf/prediction_tasks/test_classification.py .. [ 66%]
tests/unit/tf/prediction_tasks/test_multi_task.py ................ [ 68%]
tests/unit/tf/prediction_tasks/test_next_item.py ..... [ 69%]
tests/unit/tf/prediction_tasks/test_regression.py ..... [ 69%]
tests/unit/tf/prediction_tasks/test_retrieval.py . [ 69%]
tests/unit/tf/prediction_tasks/test_sampling.py ...... [ 70%]
tests/unit/tf/transformers/test_block.py ...................... [ 72%]
tests/unit/tf/transformers/test_transforms.py .......... [ 74%]
tests/unit/tf/transforms/test_bias.py .. [ 74%]
tests/unit/tf/transforms/test_features.py s............................. [ 77%]
.......................s...... [ 81%]
tests/unit/tf/transforms/test_negative_sampling.py ......... [ 82%]
tests/unit/tf/transforms/test_noise.py ..... [ 82%]
tests/unit/tf/transforms/test_sequence.py .................... [ 84%]
tests/unit/tf/transforms/test_tensor.py ... [ 85%]
tests/unit/tf/utils/test_batch.py .... [ 85%]
tests/unit/tf/utils/test_dataset.py .. [ 85%]
tests/unit/tf/utils/test_tf_utils.py ..... [ 86%]
tests/unit/torch/test_dataset.py ......... [ 87%]
tests/unit/torch/test_public_api.py . [ 87%]
tests/unit/torch/block/test_base.py .... [ 88%]
tests/unit/torch/block/test_mlp.py . [ 88%]
tests/unit/torch/features/test_continuous.py .. [ 88%]
tests/unit/torch/features/test_embedding.py .............. [ 90%]
tests/unit/torch/features/test_tabular.py .... [ 90%]
tests/unit/torch/model/test_head.py ............ [ 91%]
tests/unit/torch/model/test_model.py .. [ 92%]
tests/unit/torch/tabular/test_aggregation.py ........ [ 92%]
tests/unit/torch/tabular/test_tabular.py ... [ 93%]
tests/unit/torch/tabular/test_transformations.py ....... [ 94%]
tests/unit/utils/test_schema_utils.py ................................ [ 97%]
tests/unit/xgb/test_xgboost.py .................... [100%]

=============================== warnings summary ===============================
../../../../../usr/lib/python3/dist-packages/requests/init.py:89
/usr/lib/python3/dist-packages/requests/init.py:89: RequestsDependencyWarning: urllib3 (1.26.12) or chardet (3.0.4) doesn't match a supported version!
warnings.warn("urllib3 ({}) or chardet ({}) doesn't match a supported "

../../../.local/lib/python3.8/site-packages/flatbuffers/compat.py:19
/var/jenkins_home/.local/lib/python3.8/site-packages/flatbuffers/compat.py:19: DeprecationWarning: the imp module is deprecated in favour of importlib; see the module's documentation for alternative uses
import imp

../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36
/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36: DeprecationWarning: NEAREST is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.NEAREST or Dither.NONE instead.
'nearest': pil_image.NEAREST,

../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37
/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37: DeprecationWarning: BILINEAR is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BILINEAR instead.
'bilinear': pil_image.BILINEAR,

../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38
/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38: DeprecationWarning: BICUBIC is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BICUBIC instead.
'bicubic': pil_image.BICUBIC,

../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39
/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39: DeprecationWarning: HAMMING is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.HAMMING instead.
'hamming': pil_image.HAMMING,

../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40
/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40: DeprecationWarning: BOX is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BOX instead.
'box': pil_image.BOX,

../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41
/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41: DeprecationWarning: LANCZOS is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.LANCZOS instead.
'lanczos': pil_image.LANCZOS,

tests/unit/datasets/test_advertising.py: 1 warning
tests/unit/datasets/test_ecommerce.py: 3 warnings
tests/unit/datasets/test_entertainment.py: 4 warnings
tests/unit/datasets/test_social.py: 1 warning
tests/unit/datasets/test_synthetic.py: 10 warnings
tests/unit/implicit/test_implicit.py: 1 warning
tests/unit/lightfm/test_lightfm.py: 1 warning
tests/unit/tf/test_core.py: 6 warnings
tests/unit/tf/test_loader.py: 1 warning
tests/unit/tf/blocks/test_cross.py: 5 warnings
tests/unit/tf/blocks/test_dlrm.py: 9 warnings
tests/unit/tf/blocks/test_interactions.py: 2 warnings
tests/unit/tf/blocks/test_mlp.py: 60 warnings
tests/unit/tf/blocks/test_optimizer.py: 30 warnings
tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings
tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings
tests/unit/tf/core/test_aggregation.py: 6 warnings
tests/unit/tf/core/test_base.py: 2 warnings
tests/unit/tf/core/test_combinators.py: 11 warnings
tests/unit/tf/core/test_encoder.py: 6 warnings
tests/unit/tf/core/test_index.py: 8 warnings
tests/unit/tf/core/test_prediction.py: 2 warnings
tests/unit/tf/horovod/test_horovod.py: 3 warnings
tests/unit/tf/inputs/test_base.py: 1 warning
tests/unit/tf/inputs/test_continuous.py: 7 warnings
tests/unit/tf/inputs/test_embedding.py: 20 warnings
tests/unit/tf/inputs/test_tabular.py: 18 warnings
tests/unit/tf/models/test_base.py: 28 warnings
tests/unit/tf/models/test_benchmark.py: 2 warnings
tests/unit/tf/models/test_ranking.py: 38 warnings
tests/unit/tf/models/test_retrieval.py: 121 warnings
tests/unit/tf/outputs/test_base.py: 6 warnings
tests/unit/tf/outputs/test_classification.py: 6 warnings
tests/unit/tf/outputs/test_contrastive.py: 19 warnings
tests/unit/tf/outputs/test_regression.py: 2 warnings
tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings
tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings
tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings
tests/unit/tf/prediction_tasks/test_retrieval.py: 1 warning
tests/unit/tf/transformers/test_block.py: 16 warnings
tests/unit/tf/transforms/test_bias.py: 2 warnings
tests/unit/tf/transforms/test_features.py: 10 warnings
tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings
tests/unit/tf/transforms/test_noise.py: 1 warning
tests/unit/tf/transforms/test_sequence.py: 15 warnings
tests/unit/tf/utils/test_batch.py: 9 warnings
tests/unit/tf/utils/test_dataset.py: 2 warnings
tests/unit/torch/block/test_base.py: 4 warnings
tests/unit/torch/block/test_mlp.py: 1 warning
tests/unit/torch/features/test_continuous.py: 1 warning
tests/unit/torch/features/test_embedding.py: 4 warnings
tests/unit/torch/features/test_tabular.py: 4 warnings
tests/unit/torch/model/test_head.py: 12 warnings
tests/unit/torch/model/test_model.py: 2 warnings
tests/unit/torch/tabular/test_aggregation.py: 6 warnings
tests/unit/torch/tabular/test_transformations.py: 3 warnings
tests/unit/xgb/test_xgboost.py: 18 warnings
/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.ITEM_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.ITEM: 'item'>, <Tags.ID: 'id'>].
warnings.warn(

tests/unit/datasets/test_ecommerce.py: 3 warnings
tests/unit/datasets/test_entertainment.py: 4 warnings
tests/unit/datasets/test_social.py: 1 warning
tests/unit/datasets/test_synthetic.py: 9 warnings
tests/unit/implicit/test_implicit.py: 1 warning
tests/unit/lightfm/test_lightfm.py: 1 warning
tests/unit/tf/test_core.py: 6 warnings
tests/unit/tf/test_loader.py: 1 warning
tests/unit/tf/blocks/test_cross.py: 5 warnings
tests/unit/tf/blocks/test_dlrm.py: 9 warnings
tests/unit/tf/blocks/test_interactions.py: 2 warnings
tests/unit/tf/blocks/test_mlp.py: 60 warnings
tests/unit/tf/blocks/test_optimizer.py: 30 warnings
tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings
tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings
tests/unit/tf/core/test_aggregation.py: 6 warnings
tests/unit/tf/core/test_base.py: 2 warnings
tests/unit/tf/core/test_combinators.py: 11 warnings
tests/unit/tf/core/test_encoder.py: 7 warnings
tests/unit/tf/core/test_index.py: 3 warnings
tests/unit/tf/core/test_prediction.py: 2 warnings
tests/unit/tf/horovod/test_horovod.py: 1 warning
tests/unit/tf/inputs/test_base.py: 1 warning
tests/unit/tf/inputs/test_continuous.py: 7 warnings
tests/unit/tf/inputs/test_embedding.py: 20 warnings
tests/unit/tf/inputs/test_tabular.py: 18 warnings
tests/unit/tf/models/test_base.py: 28 warnings
tests/unit/tf/models/test_benchmark.py: 2 warnings
tests/unit/tf/models/test_ranking.py: 36 warnings
tests/unit/tf/models/test_retrieval.py: 87 warnings
tests/unit/tf/outputs/test_base.py: 6 warnings
tests/unit/tf/outputs/test_classification.py: 6 warnings
tests/unit/tf/outputs/test_contrastive.py: 19 warnings
tests/unit/tf/outputs/test_regression.py: 2 warnings
tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings
tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings
tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings
tests/unit/tf/transformers/test_block.py: 10 warnings
tests/unit/tf/transforms/test_features.py: 10 warnings
tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings
tests/unit/tf/transforms/test_sequence.py: 15 warnings
tests/unit/tf/utils/test_batch.py: 7 warnings
tests/unit/tf/utils/test_dataset.py: 2 warnings
tests/unit/torch/block/test_base.py: 4 warnings
tests/unit/torch/block/test_mlp.py: 1 warning
tests/unit/torch/features/test_continuous.py: 1 warning
tests/unit/torch/features/test_embedding.py: 4 warnings
tests/unit/torch/features/test_tabular.py: 4 warnings
tests/unit/torch/model/test_head.py: 12 warnings
tests/unit/torch/model/test_model.py: 2 warnings
tests/unit/torch/tabular/test_aggregation.py: 6 warnings
tests/unit/torch/tabular/test_transformations.py: 2 warnings
tests/unit/xgb/test_xgboost.py: 17 warnings
/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.USER_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.USER: 'user'>, <Tags.ID: 'id'>].
warnings.warn(

tests/unit/datasets/test_ecommerce.py: 1 warning
tests/unit/datasets/test_entertainment.py: 1 warning
tests/unit/implicit/test_implicit.py: 1 warning
tests/unit/lightfm/test_lightfm.py: 1 warning
tests/unit/tf/test_loader.py: 1 warning
tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings
tests/unit/tf/blocks/retrieval/test_two_tower.py: 2 warnings
tests/unit/tf/core/test_combinators.py: 11 warnings
tests/unit/tf/core/test_encoder.py: 2 warnings
tests/unit/tf/core/test_prediction.py: 1 warning
tests/unit/tf/horovod/test_horovod.py: 1 warning
tests/unit/tf/inputs/test_continuous.py: 4 warnings
tests/unit/tf/inputs/test_embedding.py: 9 warnings
tests/unit/tf/inputs/test_tabular.py: 8 warnings
tests/unit/tf/models/test_ranking.py: 20 warnings
tests/unit/tf/models/test_retrieval.py: 10 warnings
tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings
tests/unit/tf/prediction_tasks/test_regression.py: 3 warnings
tests/unit/tf/transforms/test_negative_sampling.py: 9 warnings
tests/unit/xgb/test_xgboost.py: 12 warnings
/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.SESSION_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.SESSION: 'session'>, <Tags.ID: 'id'>].
warnings.warn(

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export
tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export
tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export
tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export
tests/unit/tf/inputs/test_embedding.py::test_embedding_features_exporting_and_loading_pretrained_initializer
/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/inputs/embedding.py:970: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack
embeddings_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(embeddings)))

tests/unit/tf/blocks/retrieval/test_two_tower.py: 1 warning
tests/unit/tf/core/test_index.py: 4 warnings
tests/unit/tf/horovod/test_horovod.py: 3 warnings
tests/unit/tf/models/test_retrieval.py: 59 warnings
tests/unit/tf/prediction_tasks/test_next_item.py: 3 warnings
tests/unit/tf/utils/test_batch.py: 2 warnings
/tmp/autograph_generated_filefzyiz3tw.py:8: DeprecationWarning: The 'warn' method is deprecated, use 'warning' instead
ag
.converted_call(ag__.ld(warnings).warn, ("The 'warn' method is deprecated, use 'warning' instead", ag__.ld(DeprecationWarning), 2), None, fscope)

tests/unit/tf/core/test_combinators.py::test_parallel_block_select_by_tags
/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/core/tabular.py:602: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated since Python 3.3, and in 3.10 it will stop working
elif isinstance(self.feature_names, collections.Sequence):

tests/unit/tf/core/test_encoder.py: 1 warning
tests/unit/tf/core/test_index.py: 5 warnings
tests/unit/tf/models/test_retrieval.py: 30 warnings
tests/unit/tf/utils/test_batch.py: 4 warnings
tests/unit/tf/utils/test_dataset.py: 1 warning
/var/jenkins_home/workspace/merlin_models/models/merlin/models/utils/dataset.py:75: DeprecationWarning: unique_rows_by_features is deprecated and will be removed in a future version. Please use unique_by_tag instead.
warnings.warn(

tests/unit/tf/models/test_base.py::test_model_pre_post[True]
tests/unit/tf/models/test_base.py::test_model_pre_post[False]
tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.1]
tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.3]
tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.5]
tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.7]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/util/dispatch.py:1082: UserWarning: tf.keras.backend.random_binomial is deprecated, and will be removed in a future version.Please use tf.keras.backend.random_bernoulli instead.
return dispatch_target(*args, **kwargs)

tests/unit/tf/models/test_base.py::test_freeze_parallel_block[True]
tests/unit/tf/models/test_base.py::test_freeze_sequential_block
tests/unit/tf/models/test_base.py::test_freeze_unfreeze
tests/unit/tf/models/test_base.py::test_unfreeze_all_blocks
/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/gradient_descent.py:108: UserWarning: The lr argument is deprecated, use learning_rate instead.
super(SGD, self).init(name, **kwargs)

tests/unit/tf/models/test_base.py::test_retrieval_model_query
tests/unit/tf/models/test_base.py::test_retrieval_model_query
tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_v2_export_embeddings
tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[True]
tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[False]
tests/unit/tf/transformers/test_block.py::test_retrieval_transformer[True]
/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/utils/tf_utils.py:298: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack
tensor_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(tensor)))

tests/unit/tf/models/test_ranking.py::test_deepfm_model_only_categ_feats[False]
tests/unit/tf/models/test_ranking.py::test_deepfm_model_categ_and_continuous_feats[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/models/test_ranking.py::test_wide_deep_model[False]
tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_categorical_one_hot[False]
tests/unit/tf/models/test_ranking.py::test_wide_deep_model_hashed_cross[False]
tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[True]
tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]
/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/transforms/features.py:569: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag
warnings.warn(

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/autograph/impl/api.py:371: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag
return py_builtins.overload_of(f)(*args)

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_onehot_multihot_feature_interaction[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_feature_interaction_multi_optimizer[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask/GatherV2:0", shape=(None, 48), dtype=float32), dense_shape=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Reshape_3:0", shape=(None,), dtype=int64), values=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Reshape_2:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask/GatherV2:0", shape=(None, 48), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_3:0", shape=(None,), dtype=int64), values=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_2:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]
/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.
warnings.warn(

tests/unit/torch/block/test_mlp.py::test_mlp_block
/var/jenkins_home/workspace/merlin_models/models/tests/unit/torch/_conftest.py:151: UserWarning: Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at ../torch/csrc/utils/tensor_new.cpp:201.)
return {key: torch.tensor(value) for key, value in data.items()}

tests/unit/xgb/test_xgboost.py::test_without_dask_client
tests/unit/xgb/test_xgboost.py::TestXGBoost::test_music_regression
tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs0-DaskDeviceQuantileDMatrix]
tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs1-DaskDMatrix]
tests/unit/xgb/test_xgboost.py::TestEvals::test_multiple
tests/unit/xgb/test_xgboost.py::TestEvals::test_default
tests/unit/xgb/test_xgboost.py::TestEvals::test_train_and_valid
tests/unit/xgb/test_xgboost.py::TestEvals::test_invalid_data
/var/jenkins_home/workspace/merlin_models/models/merlin/models/xgb/init.py:344: UserWarning: Ignoring list columns as inputs to XGBoost model: ['item_genres', 'user_genres'].
warnings.warn(f"Ignoring list columns as inputs to XGBoost model: {list_column_names}.")

tests/unit/xgb/test_xgboost.py::TestXGBoost::test_unsupported_objective
/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/tornado/ioloop.py:350: DeprecationWarning: make_current is deprecated; start the event loop first
self.make_current()

tests/unit/xgb/test_xgboost.py: 14 warnings
/usr/local/lib/python3.8/dist-packages/xgboost/dask.py:884: RuntimeWarning: coroutine 'Client._wait_for_workers' was never awaited
client.wait_for_workers(n_workers)
Enable tracemalloc to get traceback where the object was allocated.
See https://docs.pytest.org/en/stable/how-to/capture-warnings.html#resource-warnings for more info.

tests/unit/xgb/test_xgboost.py: 11 warnings
/usr/local/lib/python3.8/dist-packages/cudf/core/dataframe.py:1183: DeprecationWarning: The default dtype for empty Series will be 'object' instead of 'float64' in a future version. Specify a dtype explicitly to silence this warning.
mask = pd.Series(mask)

-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html

---------- coverage: platform linux, python 3.8.10-final-0 -----------
Name Stmts Miss Cover

merlin/datasets/init.py 2 0 100%
merlin/datasets/advertising/init.py 2 0 100%
merlin/datasets/advertising/criteo/init.py 0 0 100%
merlin/datasets/advertising/criteo/dataset.py 79 49 38%
merlin/datasets/advertising/criteo/transformed/init.py 0 0 100%
merlin/datasets/ecommerce/init.py 4 0 100%
merlin/datasets/ecommerce/aliccp/init.py 0 0 100%
merlin/datasets/ecommerce/aliccp/dataset.py 141 87 38%
merlin/datasets/ecommerce/aliccp/raw/init.py 0 0 100%
merlin/datasets/ecommerce/aliccp/transformed/init.py 0 0 100%
merlin/datasets/ecommerce/booking/init.py 0 0 100%
merlin/datasets/ecommerce/booking/dataset.py 127 100 21%
merlin/datasets/ecommerce/booking/raw/init.py 0 0 100%
merlin/datasets/ecommerce/booking/transformed/init.py 0 0 100%
merlin/datasets/ecommerce/dressipi/init.py 0 0 100%
merlin/datasets/ecommerce/dressipi/dataset.py 45 37 18%
merlin/datasets/ecommerce/dressipi/preprocessed/init.py 0 0 100%
merlin/datasets/ecommerce/large/init.py 0 0 100%
merlin/datasets/ecommerce/small/init.py 0 0 100%
merlin/datasets/ecommerce/transactions/init.py 0 0 100%
merlin/datasets/entertainment/init.py 2 0 100%
merlin/datasets/entertainment/movielens/1m-raw/init.py 0 0 100%
merlin/datasets/entertainment/movielens/1m-raw/ratings/init.py 0 0 100%
merlin/datasets/entertainment/movielens/1m/init.py 0 0 100%
merlin/datasets/entertainment/movielens/25m/init.py 0 0 100%
merlin/datasets/entertainment/movielens/100k/init.py 0 0 100%
merlin/datasets/entertainment/movielens/init.py 0 0 100%
merlin/datasets/entertainment/movielens/dataset.py 152 122 20%
merlin/datasets/entertainment/music_streaming/init.py 0 0 100%
merlin/datasets/social/init.py 0 0 100%
merlin/datasets/synthetic.py 147 8 95%
merlin/datasets/testing/init.py 0 0 100%
merlin/datasets/testing/sequence_testing/init.py 0 0 100%
merlin/models/init.py 2 0 100%
merlin/models/_version.py 354 205 42%
merlin/models/api.py 14 5 64%
merlin/models/config/init.py 0 0 100%
merlin/models/config/schema.py 62 0 100%
merlin/models/implicit/init.py 27 4 85%
merlin/models/io.py 15 0 100%
merlin/models/lightfm/init.py 23 0 100%
merlin/models/loader/init.py 0 0 100%
merlin/models/loader/backend.py 379 41 89%
merlin/models/loader/dataframe_iter.py 21 17 19%
merlin/models/loader/tf_utils.py 57 27 53%
merlin/models/loader/utils.py 40 15 62%
merlin/models/tf/init.py 70 0 100%
merlin/models/tf/blocks/init.py 0 0 100%
merlin/models/tf/blocks/cross.py 44 0 100%
merlin/models/tf/blocks/dlrm.py 49 2 96%
merlin/models/tf/blocks/experts.py 99 17 83%
merlin/models/tf/blocks/interaction.py 108 40 63%
merlin/models/tf/blocks/mlp.py 117 7 94%
merlin/models/tf/blocks/optimizer.py 173 12 93%
merlin/models/tf/blocks/retrieval/init.py 0 0 100%
merlin/models/tf/blocks/retrieval/base.py 175 62 65%
merlin/models/tf/blocks/retrieval/matrix_factorization.py 35 1 97%
merlin/models/tf/blocks/retrieval/two_tower.py 30 0 100%
merlin/models/tf/blocks/sampling/init.py 0 0 100%
merlin/models/tf/blocks/sampling/base.py 29 2 93%
merlin/models/tf/blocks/sampling/cross_batch.py 46 2 96%
merlin/models/tf/blocks/sampling/in_batch.py 35 0 100%
merlin/models/tf/blocks/sampling/queue.py 115 12 90%
merlin/models/tf/core/init.py 0 0 100%
merlin/models/tf/core/aggregation.py 241 45 81%
merlin/models/tf/core/base.py 242 50 79%
merlin/models/tf/core/combinators.py 426 53 88%
merlin/models/tf/core/encoder.py 175 28 84%
merlin/models/tf/core/index.py 106 16 85%
merlin/models/tf/core/prediction.py 50 1 98%
merlin/models/tf/core/tabular.py 280 29 90%
merlin/models/tf/distributed/init.py 0 0 100%
merlin/models/tf/distributed/backend.py 9 2 78%
merlin/models/tf/inputs/init.py 0 0 100%
merlin/models/tf/inputs/base.py 60 10 83%
merlin/models/tf/inputs/continuous.py 39 3 92%
merlin/models/tf/inputs/embedding.py 458 32 93%
merlin/models/tf/loader.py 268 94 65%
merlin/models/tf/losses/init.py 4 0 100%
merlin/models/tf/losses/base.py 9 0 100%
merlin/models/tf/losses/listwise.py 13 0 100%
merlin/models/tf/losses/pairwise.py 115 1 99%
merlin/models/tf/metrics/init.py 2 0 100%
merlin/models/tf/metrics/evaluation.py 105 48 54%
merlin/models/tf/metrics/topk.py 198 48 76%
merlin/models/tf/models/init.py 0 0 100%
merlin/models/tf/models/base.py 756 101 87%
merlin/models/tf/models/benchmark.py 16 0 100%
merlin/models/tf/models/ranking.py 67 3 96%
merlin/models/tf/models/retrieval.py 78 4 95%
merlin/models/tf/models/utils.py 10 1 90%
merlin/models/tf/outputs/init.py 0 0 100%
merlin/models/tf/outputs/base.py 123 17 86%
merlin/models/tf/outputs/classification.py 91 1 99%
merlin/models/tf/outputs/contrastive.py 147 10 93%
merlin/models/tf/outputs/regression.py 9 0 100%
merlin/models/tf/outputs/sampling/init.py 0 0 100%
merlin/models/tf/outputs/sampling/base.py 78 21 73%
merlin/models/tf/outputs/sampling/in_batch.py 37 1 97%
merlin/models/tf/outputs/sampling/popularity.py 27 1 96%
merlin/models/tf/outputs/topk.py 98 6 94%
merlin/models/tf/prediction_tasks/init.py 0 0 100%
merlin/models/tf/prediction_tasks/base.py 207 37 82%
merlin/models/tf/prediction_tasks/classification.py 68 17 75%
merlin/models/tf/prediction_tasks/multi.py 7 0 100%
merlin/models/tf/prediction_tasks/next_item.py 59 6 90%
merlin/models/tf/prediction_tasks/regression.py 35 2 94%
merlin/models/tf/prediction_tasks/retrieval.py 73 3 96%
merlin/models/tf/transformers/init.py 0 0 100%
merlin/models/tf/transformers/block.py 101 2 98%
merlin/models/tf/transformers/transforms.py 63 0 100%
merlin/models/tf/transforms/init.py 0 0 100%
merlin/models/tf/transforms/bias.py 111 9 92%
merlin/models/tf/transforms/features.py 435 36 92%
merlin/models/tf/transforms/negative_sampling.py 77 3 96%
merlin/models/tf/transforms/noise.py 43 1 98%
merlin/models/tf/transforms/regularization.py 17 1 94%
merlin/models/tf/transforms/sequence.py 282 42 85%
merlin/models/tf/transforms/tensor.py 158 13 92%
merlin/models/tf/typing.py 7 0 100%
merlin/models/tf/utils/init.py 0 0 100%
merlin/models/tf/utils/batch_utils.py 85 4 95%
merlin/models/tf/utils/repr_utils.py 69 4 94%
merlin/models/tf/utils/search_utils.py 34 22 35%
merlin/models/tf/utils/testing_utils.py 206 36 83%
merlin/models/tf/utils/tf_utils.py 209 42 80%
merlin/models/torch/init.py 12 0 100%
merlin/models/torch/block/init.py 0 0 100%
merlin/models/torch/block/base.py 167 32 81%
merlin/models/torch/block/mlp.py 38 5 87%
merlin/models/torch/dataset.py 68 5 93%
merlin/models/torch/features/init.py 0 0 100%
merlin/models/torch/features/base.py 4 0 100%
merlin/models/torch/features/continuous.py 22 0 100%
merlin/models/torch/features/embedding.py 165 12 93%
merlin/models/torch/features/tabular.py 65 8 88%
merlin/models/torch/losses.py 28 28 0%
merlin/models/torch/model/init.py 0 0 100%
merlin/models/torch/model/base.py 286 65 77%
merlin/models/torch/model/prediction_task.py 24 0 100%
merlin/models/torch/tabular/init.py 0 0 100%
merlin/models/torch/tabular/aggregation.py 75 0 100%
merlin/models/torch/tabular/base.py 247 39 84%
merlin/models/torch/tabular/transformations.py 67 3 96%
merlin/models/torch/typing.py 6 0 100%
merlin/models/torch/utils/init.py 0 0 100%
merlin/models/torch/utils/data_utils.py 117 117 0%
merlin/models/torch/utils/examples_utils.py 39 39 0%
merlin/models/torch/utils/torch_utils.py 80 22 72%
merlin/models/utils/init.py 0 0 100%
merlin/models/utils/constants.py 3 0 100%
merlin/models/utils/dataset.py 38 4 89%
merlin/models/utils/dependencies.py 26 19 27%
merlin/models/utils/doc_utils.py 10 0 100%
merlin/models/utils/example_utils.py 31 2 94%
merlin/models/utils/misc_utils.py 118 90 24%
merlin/models/utils/nvt_utils.py 27 24 11%
merlin/models/utils/registry.py 101 29 71%
merlin/models/utils/schema_utils.py 90 19 79%
merlin/models/xgb/init.py 124 4 97%

TOTAL 11581 2346 80%

=========================== short test summary info ============================
SKIPPED [1] tests/unit/datasets/test_advertising.py:20: No data-dir available, pass it through env variable $INPUT_DATA_DIR
SKIPPED [1] tests/unit/datasets/test_ecommerce.py:64: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP
SKIPPED [1] tests/unit/datasets/test_ecommerce.py:80: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP
SKIPPED [1] tests/unit/datasets/test_ecommerce.py:94: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP
SKIPPED [1] tests/unit/datasets/test_ecommerce.py:115: No data-dir available, pass it through env variable $INPUT_DATA_DIR
SKIPPED [3] tests/unit/datasets/test_entertainment.py:44: No data-dir available, pass it through env variable $INPUT_DATA_DIR
SKIPPED [5] ../../../.local/lib/python3.8/site-packages/tensorflow/python/framework/test_util.py:2746: Not a test.
========= 871 passed, 13 skipped, 1452 warnings in 1854.98s (0:30:54) ==========
___________________________________ summary ____________________________________
py38-gpu: commands succeeded
congratulations :)
Performing Post build task...
Match found for : : True
Logical operation result is TRUE
Running script : #!/bin/bash
cd /var/jenkins_home/
CUDA_VISIBLE_DEVICES=1 python test_res_push.py "https://api.GitHub.com/repos/NVIDIA-Merlin/models/issues/$ghprbPullId/comments" "/var/jenkins_home/jobs/$JOB_NAME/builds/$BUILD_NUMBER/log"
[merlin_models] $ /bin/bash /tmp/jenkins1529663036354268733.sh

@bschifferer bschifferer merged commit 634edfd into NVIDIA-Merlin:main Nov 22, 2022
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Add example for multi-gpu training with Merlin Models
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