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Update test of lazy adam notebook to only run when GPU available #894

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oliverholworthy
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Goals ⚽

Enable tests of Models unit tests to run without errors on CPU in GitHub Actions from other projects (e.g. in Merlin Core).

Implementation Details 🚧 / Testing Details πŸ”

Update test of lazy adam notebook to only run when GPU available

@oliverholworthy oliverholworthy self-assigned this Nov 18, 2022
@oliverholworthy oliverholworthy added this to the Merlin 22.12 milestone Nov 18, 2022
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GitHub pull request #894 of commit b20d10dd29049c62cbe6b420c8bf3c2d1fb57c9c, no merge conflicts.
Running as SYSTEM
Setting status of b20d10dd29049c62cbe6b420c8bf3c2d1fb57c9c to PENDING with url http://merlin-infra1.nvidia.com:8080/job/merlin_models/1882/ 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/894/*:refs/remotes/origin/pr/894/* # timeout=10
 > git rev-parse b20d10dd29049c62cbe6b420c8bf3c2d1fb57c9c^{commit} # timeout=10
Checking out Revision b20d10dd29049c62cbe6b420c8bf3c2d1fb57c9c (detached)
 > git config core.sparsecheckout # timeout=10
 > git checkout -f b20d10dd29049c62cbe6b420c8bf3c2d1fb57c9c # timeout=10
Commit message: "Only run lazy adam test when GPU available"
 > git rev-list --no-walk 686670f5fb398047da1d07c656d29f28effa43e4 # timeout=10
[merlin_models] $ /bin/bash /tmp/jenkins3828658323980943128.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: 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: 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: 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: 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: 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: 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: 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+47.gb20d10dd.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==1.27.12,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==1.29.12,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+47.gb20d10dd,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='1084607171'
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-vodasksf
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/core.git /tmp/pip-req-build-vodasksf
  Resolved https://github.com/NVIDIA-Merlin/core.git to commit aac1dc33cf92cd19f5a065fa7f49cf9b7500cfb2
  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: distributed>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+12.gaac1dc3) (2022.3.0)
Requirement already satisfied: tqdm>=4.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+12.gaac1dc3) (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+12.gaac1dc3) (1.10.0)
Requirement already satisfied: numba>=0.54 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+12.gaac1dc3) (0.55.1)
Requirement already satisfied: packaging in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+12.gaac1dc3) (21.3)
Requirement already satisfied: protobuf>=3.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+12.gaac1dc3) (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+12.gaac1dc3) (2022.5.0)
Requirement already satisfied: betterproto<2.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+12.gaac1dc3) (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+12.gaac1dc3) (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+12.gaac1dc3) (1.3.5)
Requirement already satisfied: pyarrow>=5.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+12.gaac1dc3) (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+12.gaac1dc3) (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+12.gaac1dc3) (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+12.gaac1dc3) (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+12.gaac1dc3) (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+12.gaac1dc3) (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+12.gaac1dc3) (1.2.0)
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+12.gaac1dc3) (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+12.gaac1dc3) (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+12.gaac1dc3) (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+12.gaac1dc3) (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+12.gaac1dc3) (2.0.0)
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+12.gaac1dc3) (2.4.0)
Requirement already satisfied: jinja2 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+12.gaac1dc3) (3.1.2)
Requirement already satisfied: click>=6.6 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+12.gaac1dc3) (8.1.3)
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+12.gaac1dc3) (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+12.gaac1dc3) (1.20.3)
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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+12.gaac1dc3) (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+12.gaac1dc3-py3-none-any.whl size=118622 sha256=dccbcd3afd104ef768e29ed2bc691174c925f8726ec1cc82a6f45f5dc077c210
  Stored in directory: /tmp/pip-ephem-wheel-cache-5jgxukq_/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+12.gaac1dc3
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-l3dvx6hk
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/nvtabular.git /tmp/pip-req-build-l3dvx6hk
  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 1.4 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: 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)
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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: 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: 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: 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=3a39853eff7bb71722196f7655b3b7b2f1f8ef6bca0341dd3aaa5a7c496d6905
  Stored in directory: /tmp/pip-ephem-wheel-cache-zocytq8f/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=58e65a9f443d31dcd1b0dd42012df74f4bf9075d38ed94ba8f29e02f77af30dc
  Stored in directory: /tmp/pip-ephem-wheel-cache-zocytq8f/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_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 . [ 30%]
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 . [ 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_filew1wwyk6e.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 45331 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 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 39 90%
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 2350 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 $INPUT_DATA_DIR
SKIPPED [5] ../../../.local/lib/python3.8/site-packages/tensorflow/python/framework/test_util.py:2746: Not a test.
========= 866 passed, 13 skipped, 1439 warnings in 1857.13s (0:30:57) ==========
/usr/local/lib/python3.8/dist-packages/coverage/data.py:130: CoverageWarning: Data file '/var/jenkins_home/workspace/merlin_models/models/.coverage.10.20.17.231.25302.877932' doesn't seem to be a coverage data file: cannot unpack non-iterable NoneType object
data._warn(str(exc))
___________________________________ summary ____________________________________
py38-gpu: commands succeeded
congratulations :)
Performing Post build task...
Match found for : : True
Logical operation result is TRUE
Running script : #!/bin/bash
cd /var/jenkins_home/
CUDA_VISIBLE_DEVICES=1 python test_res_push.py "https://api.GitHub.com/repos/NVIDIA-Merlin/models/issues/$ghprbPullId/comments" "/var/jenkins_home/jobs/$JOB_NAME/builds/$BUILD_NUMBER/log"
[merlin_models] $ /bin/bash /tmp/jenkins7073483766065794524.sh

@@ -12,6 +14,7 @@
timeout=180,
execute=False,
)
@pytest.mark.skipif(not HAS_GPU, reason="No GPU available")
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This notebook seems to require GPU to work, so adding a skip if we don't meet the requirements

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thanks!

@nvidia-merlin-bot
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GitHub pull request #894 of commit fcd46adabb39097643539be23550f4fef7c35eca, no merge conflicts.
Running as SYSTEM
Setting status of fcd46adabb39097643539be23550f4fef7c35eca to PENDING with url http://merlin-infra1.nvidia.com:8080/job/merlin_models/1886/ 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/894/*:refs/remotes/origin/pr/894/* # timeout=10
 > git rev-parse fcd46adabb39097643539be23550f4fef7c35eca^{commit} # timeout=10
Checking out Revision fcd46adabb39097643539be23550f4fef7c35eca (detached)
 > git config core.sparsecheckout # timeout=10
 > git checkout -f fcd46adabb39097643539be23550f4fef7c35eca # timeout=10
Commit message: "Merge branch 'main' into test-lazy-adam-notebook-limit-to-gpu"
 > git rev-list --no-walk 89548ee8ceb28d42c03bb3140330496c45f1c242 # timeout=10
[merlin_models] $ /bin/bash /tmp/jenkins14272262978627163846.sh
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
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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)
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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)
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: 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.gfcd46ada.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==1.27.12,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==1.29.12,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==2022.5.1,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+49.gfcd46ada,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@21117cfc4c113b30036afcb97b6daa5f377996db,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='4233167934'
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-ksomxl5v
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/core.git /tmp/pip-req-build-ksomxl5v
  Resolved https://github.com/NVIDIA-Merlin/core.git to commit b298635ce3991007a4961896e21779f6a45348e0
  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+14.gb298635) (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+14.gb298635) (1.3.5)
Requirement already satisfied: tqdm>=4.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+14.gb298635) (4.64.1)
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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+14.gb298635) (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+14.gb298635) (2022.3.0)
Requirement already satisfied: betterproto<2.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+14.gb298635) (1.2.5)
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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+14.gb298635) (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+14.gb298635) (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+14.gb298635) (1.2.0)
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+14.gb298635) (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+14.gb298635) (5.8.0)
Requirement already satisfied: click>=6.6 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+14.gb298635) (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+14.gb298635) (1.0.4)
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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+14.gb298635) (6.2)
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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==0.8.0+14.gb298635) (2.4.0)
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+14.gb298635) (0.38.1)
Requirement already satisfied: setuptools in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+14.gb298635) (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+14.gb298635) (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+14.gb298635) (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+14.gb298635) (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+14.gb298635) (2022.2.1)
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+14.gb298635) (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==0.8.0+14.gb298635) (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==0.8.0+14.gb298635) (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+14.gb298635) (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+14.gb298635) (1.0.1)
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Requirement already satisfied: multidict in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core==0.8.0+14.gb298635) (6.0.2)
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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+14.gb298635) (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+14.gb298635) (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+14.gb298635-py3-none-any.whl size=118651 sha256=74de524c01e6bc5b21d9fe096a4ed5d5a80960d071c82108d3045627a108bc52
  Stored in directory: /tmp/pip-ephem-wheel-cache-t8ce19yv/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+14.gb298635
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-4oc29y1d
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/nvtabular.git /tmp/pip-req-build-4oc29y1d
  Resolved https://github.com/NVIDIA-Merlin/nvtabular.git to commit 21117cfc4c113b30036afcb97b6daa5f377996db
  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+5.g21117cfc) (0.0.2)
Requirement already satisfied: scipy in /usr/local/lib/python3.8/dist-packages (from nvtabular==1.6.0+5.g21117cfc) (1.8.1)
Requirement already satisfied: merlin-core>=0.2.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from nvtabular==1.6.0+5.g21117cfc) (0.8.0+14.gb298635)
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+5.g21117cfc) (0.55.1)
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Requirement already satisfied: tqdm>=4.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+5.g21117cfc) (4.64.1)
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Requirement already satisfied: packaging in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+5.g21117cfc) (21.3)
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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+5.g21117cfc) (2022.3.0)
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+5.g21117cfc) (2022.5.0)
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+5.g21117cfc) (7.0.0)
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+5.g21117cfc) (2022.3.0)
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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+5.g21117cfc) (1.20.3)
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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+5.g21117cfc) (0.4.3)
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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+5.g21117cfc) (1.2.0)
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>=0.2.0->nvtabular==1.6.0+5.g21117cfc) (2.0.0)
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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+5.g21117cfc) (65.5.1)
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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+5.g21117cfc) (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>=0.2.0->nvtabular==1.6.0+5.g21117cfc) (2022.2.1)
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+5.g21117cfc) (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+5.g21117cfc) (1.2.0)
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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+5.g21117cfc) (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+5.g21117cfc) (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>=0.2.0->nvtabular==1.6.0+5.g21117cfc) (4.1.0)
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+5.g21117cfc) (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>=0.2.0->nvtabular==1.6.0+5.g21117cfc) (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+5.g21117cfc) (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+5.g21117cfc) (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+5.g21117cfc-cp38-cp38-linux_x86_64.whl size=257596 sha256=b52b95d3852a63d507ec4b8314cb39e3f71b41d7aa8f1ca2cc845789238abfe3
  Stored in directory: /tmp/pip-ephem-wheel-cache-f500chnk/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+5.g21117cfc
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_ecommerce_session_based.py . [ 30%]
tests/unit/tf/examples/test_usecase_incremental_training_layer_freezing.py F [ 30%]
[ 30%]
tests/unit/tf/examples/test_usecase_pretrained_embeddings.py . [ 30%]
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 . [ 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%]

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

tb = <testbook.client.TestbookNotebookClient object at 0x7fed053cf580>

@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 0x7fed053cf580>
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': 'fc95ac...e, 'engine': 'fc95aca4-7483-4164-afbf-4ee23814a010', 'started': '2022-11-18T16:05:11.512818Z', '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 οΏ½[0;31m---------------------------------------------------------------------------οΏ½[0m
E οΏ½[0;31mResourceExhaustedErrorοΏ½[0m Traceback (most recent call last)
E Cell οΏ½[0;32mIn [8], line 2οΏ½[0m
E οΏ½[1;32m 1οΏ½[0m modelοΏ½[38;5;241m.οΏ½[39mcompile(optimizerοΏ½[38;5;241m=οΏ½[39mtfοΏ½[38;5;241m.οΏ½[39mkerasοΏ½[38;5;241m.οΏ½[39moptimizersοΏ½[38;5;241m.οΏ½[39mAdam(learning_rateοΏ½[38;5;241m=οΏ½[39mοΏ½[38;5;241m0.01οΏ½[39m))
E οΏ½[0;32m----> 2οΏ½[0m οΏ½[43mmodelοΏ½[49mοΏ½[38;5;241;43m.οΏ½[39;49mοΏ½[43mfitοΏ½[49mοΏ½[43m(οΏ½[49mοΏ½[43mday_1οΏ½[49mοΏ½[43m,οΏ½[49mοΏ½[43m οΏ½[49mοΏ½[43mbatch_sizeοΏ½[49mοΏ½[38;5;241;43m=οΏ½[39;49mοΏ½[38;5;241;43m1024οΏ½[39;49mοΏ½[43m,οΏ½[49mοΏ½[43m οΏ½[49mοΏ½[43mepochsοΏ½[49mοΏ½[38;5;241;43m=οΏ½[39;49mοΏ½[38;5;241;43m1οΏ½[39;49mοΏ½[43m)οΏ½[49m
E
E File οΏ½[0;32m~/workspace/merlin_models/models/merlin/models/tf/models/base.py:910οΏ½[0m, in οΏ½[0;36mBaseModel.fitοΏ½[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)οΏ½[0m
E οΏ½[1;32m 907οΏ½[0m οΏ½[38;5;28mselfοΏ½[39mοΏ½[38;5;241m.οΏ½[39m_reset_compile_cache()
E οΏ½[1;32m 908οΏ½[0m οΏ½[38;5;28mselfοΏ½[39mοΏ½[38;5;241m.οΏ½[39mtrain_pre οΏ½[38;5;241m=οΏ½[39m pre
E οΏ½[0;32m--> 910οΏ½[0m out οΏ½[38;5;241m=οΏ½[39m οΏ½[38;5;28;43msuperοΏ½[39;49mοΏ½[43m(οΏ½[49mοΏ½[43m)οΏ½[49mοΏ½[38;5;241;43m.οΏ½[39;49mοΏ½[43mfitοΏ½[49mοΏ½[43m(οΏ½[49mοΏ½[38;5;241;43mοΏ½[39;49mοΏ½[38;5;241;43mοΏ½[39;49mοΏ½[43mfit_kwargsοΏ½[49mοΏ½[43m)οΏ½[49m
E οΏ½[1;32m 912οΏ½[0m οΏ½[38;5;28;01mifοΏ½[39;00m pre:
E οΏ½[1;32m 913οΏ½[0m οΏ½[38;5;28;01mdelοΏ½[39;00m οΏ½[38;5;28mselfοΏ½[39mοΏ½[38;5;241m.οΏ½[39mtrain_pre
E
E File οΏ½[0;32m~/.local/lib/python3.8/site-packages/keras/utils/traceback_utils.py:67οΏ½[0m, in οΏ½[0;36mfilter_traceback..error_handlerοΏ½[0;34m(*args, **kwargs)οΏ½[0m
E οΏ½[1;32m 65οΏ½[0m οΏ½[38;5;28;01mexceptοΏ½[39;00m οΏ½[38;5;167;01mExceptionοΏ½[39;00m οΏ½[38;5;28;01masοΏ½[39;00m e: οΏ½[38;5;66;03m# pylint: disable=broad-exceptοΏ½[39;00m
E οΏ½[1;32m 66οΏ½[0m filtered_tb οΏ½[38;5;241m=οΏ½[39m process_traceback_frames(eοΏ½[38;5;241m.οΏ½[39m__traceback_)
E οΏ½[0;32m---> 67οΏ½[0m οΏ½[38;5;28;01mraiseοΏ½[39;00m eοΏ½[38;5;241m.οΏ½[39mwith_traceback(filtered_tb) οΏ½[38;5;28;01mfromοΏ½[39;00m οΏ½[38;5;28mNoneοΏ½[39m
E οΏ½[1;32m 68οΏ½[0m οΏ½[38;5;28;01mfinallyοΏ½[39;00m:
E οΏ½[1;32m 69οΏ½[0m οΏ½[38;5;28;01mdelοΏ½[39;00m filtered_tb
E
E File οΏ½[0;32m~/.local/lib/python3.8/site-packages/tensorflow/python/eager/execute.py:54οΏ½[0m, in οΏ½[0;36mquick_executeοΏ½[0;34m(op_name, num_outputs, inputs, attrs, ctx, name)οΏ½[0m
E οΏ½[1;32m 52οΏ½[0m οΏ½[38;5;28;01mtryοΏ½[39;00m:
E οΏ½[1;32m 53οΏ½[0m ctxοΏ½[38;5;241m.οΏ½[39mensure_initialized()
E οΏ½[0;32m---> 54οΏ½[0m tensors οΏ½[38;5;241m=οΏ½[39m pywrap_tfeοΏ½[38;5;241m.οΏ½[39mTFE_Py_Execute(ctxοΏ½[38;5;241m.οΏ½[39m_handle, device_name, op_name,
E οΏ½[1;32m 55οΏ½[0m inputs, attrs, num_outputs)
E οΏ½[1;32m 56οΏ½[0m οΏ½[38;5;28;01mexceptοΏ½[39;00m coreοΏ½[38;5;241m.οΏ½[39m_NotOkStatusException οΏ½[38;5;28;01masοΏ½[39;00m e:
E οΏ½[1;32m 57οΏ½[0m οΏ½[38;5;28;01mifοΏ½[39;00m name οΏ½[38;5;129;01misοΏ½[39;00m οΏ½[38;5;129;01mnotοΏ½[39;00m οΏ½[38;5;28;01mNoneοΏ½[39;00m:
E
E οΏ½[0;31mResourceExhaustedErrorοΏ½[0m: Graph execution error:
E
E Detected at node 'Adam/Adam/update_21/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/py38-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_4578/2071866865.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 910, 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 724, 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_21/mul_1'
E Detected at node 'Adam/Adam/update_21/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/py38-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_4578/2071866865.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 910, 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 724, 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_21/mul_1'
E 2 root error(s) found.
E (0) RESOURCE_EXHAUSTED: failed to allocate memory
E [[{{node Adam/Adam/update_21/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_21/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_4007]
E ResourceExhaustedError: Graph execution error:
E
E Detected at node 'Adam/Adam/update_21/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/py38-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_4578/2071866865.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 910, 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 724, 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_21/mul_1'
E Detected at node 'Adam/Adam/update_21/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/py38-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_4578/2071866865.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 910, 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 724, 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_21/mul_1'
E 2 root error(s) found.
E (0) RESOURCE_EXHAUSTED: failed to allocate memory
E [[{{node Adam/Adam/update_21/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_21/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_4007]

../../../.local/lib/python3.8/site-packages/nbclient/client.py:862: CellExecutionError
----------------------------- Captured stderr call -----------------------------
2022-11-18 16:05:04.541000: 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.
2022-11-18 16:05:08.695505: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 0
2022-11-18 16:05:08.695611: 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
2022-11-18 16:05:08.696280: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 1
2022-11-18 16:05:08.696337: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:1 with 13875 MB memory: -> device: 1, name: Tesla P100-DGXS-16GB, pci bus id: 0000:08:00.0, compute capability: 6.0
2022-11-18 16:05:08.696946: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 2
2022-11-18 16:05:08.696998: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:2 with 13875 MB memory: -> device: 2, name: Tesla P100-DGXS-16GB, pci bus id: 0000:0e:00.0, compute capability: 6.0
2022-11-18 16:05:08.697935: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 3
2022-11-18 16:05:08.697986: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:3 with 13875 MB memory: -> device: 3, name: Tesla P100-DGXS-16GB, pci bus id: 0000:0f:00.0, compute capability: 6.0
2022-11-18 16:05:25.793418: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:288] gpu_async_0 cuMemAllocAsync failed to allocate 135407776 bytes: CUDA error: out of memory (CUDA_ERROR_OUT_OF_MEMORY)
Reported by CUDA: Free memory/Total memory: 3735552/17069309952
2022-11-18 16:05:25.793478: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:293] Stats: Limit: 8534360064
InUse: 5418839144
MaxInUse: 5418839144
NumAllocs: 286
MaxAllocSize: 1083564064
Reserved: 0
PeakReserved: 0
LargestFreeBlock: 0

2022-11-18 16:05:25.793496: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:56] Histogram of current allocation: (allocation_size_in_bytes, nb_allocation_of_that_sizes), ...;
2022-11-18 16:05:25.793505: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1, 4
2022-11-18 16:05:25.793511: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 4, 36
2022-11-18 16:05:25.793517: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 8, 8
2022-11-18 16:05:25.793523: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 40, 2
2022-11-18 16:05:25.793530: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 128, 9
2022-11-18 16:05:25.793536: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 160, 10
2022-11-18 16:05:25.793542: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 192, 5
2022-11-18 16:05:25.793548: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 256, 7
2022-11-18 16:05:25.793553: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 288, 5
2022-11-18 16:05:25.793559: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 480, 5
2022-11-18 16:05:25.793565: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 512, 6
2022-11-18 16:05:25.793571: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1028, 1
2022-11-18 16:05:25.793600: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 3168, 3
2022-11-18 16:05:25.793608: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 32768, 6
2022-11-18 16:05:25.793614: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 122880, 3
2022-11-18 16:05:25.793620: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 131072, 3
2022-11-18 16:05:25.793626: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 584352, 5
2022-11-18 16:05:25.793632: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 823872, 3
2022-11-18 16:05:25.793638: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 4324736, 5
2022-11-18 16:05:25.793644: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 7426048, 5
2022-11-18 16:05:25.793650: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 15401440, 5
2022-11-18 16:05:25.793656: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 18678720, 5
2022-11-18 16:05:25.793661: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 39970560, 4
2022-11-18 16:05:25.793667: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 56589504, 5
2022-11-18 16:05:25.793673: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 135407776, 3
2022-11-18 16:05:25.793679: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1083564064, 4
2022-11-18 16:05:25.793706: W tensorflow/core/framework/op_kernel.cc:1733] RESOURCE_EXHAUSTED: failed to allocate memory
2022-11-18 16:05:25.795204: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:288] gpu_async_0 cuMemAllocAsync failed to allocate 135407776 bytes: CUDA error: out of memory (CUDA_ERROR_OUT_OF_MEMORY)
Reported by CUDA: Free memory/Total memory: 3735552/17069309952
2022-11-18 16:05:25.795226: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:293] Stats: Limit: 8534360064
InUse: 5458809832
MaxInUse: 5458809832
NumAllocs: 288
MaxAllocSize: 1083564064
Reserved: 0
PeakReserved: 0
LargestFreeBlock: 0

2022-11-18 16:05:25.795241: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:56] Histogram of current allocation: (allocation_size_in_bytes, nb_allocation_of_that_sizes), ...;
2022-11-18 16:05:25.795248: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1, 4
2022-11-18 16:05:25.795255: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 4, 36
2022-11-18 16:05:25.795261: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 8, 8
2022-11-18 16:05:25.795267: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 40, 2
2022-11-18 16:05:25.795273: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 128, 10
2022-11-18 16:05:25.795279: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 160, 10
2022-11-18 16:05:25.795284: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 192, 5
2022-11-18 16:05:25.795290: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 256, 7
2022-11-18 16:05:25.795296: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 288, 5
2022-11-18 16:05:25.795302: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 480, 5
2022-11-18 16:05:25.795308: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 512, 6
2022-11-18 16:05:25.795314: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1028, 1
2022-11-18 16:05:25.795320: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 3168, 3
2022-11-18 16:05:25.795326: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 32768, 6
2022-11-18 16:05:25.795345: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 122880, 3
2022-11-18 16:05:25.795352: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 131072, 3
2022-11-18 16:05:25.795358: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 584352, 5
2022-11-18 16:05:25.795364: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 823872, 3
2022-11-18 16:05:25.795370: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 4324736, 5
2022-11-18 16:05:25.795376: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 7426048, 5
2022-11-18 16:05:25.795382: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 15401440, 5
2022-11-18 16:05:25.795388: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 18678720, 5
2022-11-18 16:05:25.795394: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 39970560, 5
2022-11-18 16:05:25.795400: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 56589504, 5
2022-11-18 16:05:25.795406: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 135407776, 3
2022-11-18 16:05:25.795412: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1083564064, 4
2022-11-18 16:05:25.795421: W tensorflow/core/framework/op_kernel.cc:1733] RESOURCE_EXHAUSTED: failed to allocate memory
2022-11-18 16:05:25.795944: 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
2022-11-18 16:05:25.795962: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:293] Stats: Limit: 8534360064
InUse: 5460463912
MaxInUse: 5460463912
NumAllocs: 292
MaxAllocSize: 1083564064
Reserved: 0
PeakReserved: 0
LargestFreeBlock: 0

2022-11-18 16:05:25.795976: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:56] Histogram of current allocation: (allocation_size_in_bytes, nb_allocation_of_that_sizes), ...;
2022-11-18 16:05:25.795983: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1, 4
2022-11-18 16:05:25.795989: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 4, 36
2022-11-18 16:05:25.795995: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 8, 8
2022-11-18 16:05:25.796001: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 40, 2
2022-11-18 16:05:25.796007: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 128, 10
2022-11-18 16:05:25.796013: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 160, 10
2022-11-18 16:05:25.796019: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 192, 5
2022-11-18 16:05:25.796038: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 256, 7
2022-11-18 16:05:25.796045: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 288, 5
2022-11-18 16:05:25.796051: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 480, 5
2022-11-18 16:05:25.796057: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 512, 6
2022-11-18 16:05:25.796063: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1028, 1
2022-11-18 16:05:25.796069: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 3168, 5
2022-11-18 16:05:25.796075: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 32768, 6
2022-11-18 16:05:25.796081: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 122880, 3
2022-11-18 16:05:25.796097: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 131072, 3
2022-11-18 16:05:25.796104: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 584352, 5
2022-11-18 16:05:25.796110: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 823872, 5
2022-11-18 16:05:25.796116: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 4324736, 5
2022-11-18 16:05:25.796122: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 7426048, 5
2022-11-18 16:05:25.796128: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 15401440, 5
2022-11-18 16:05:25.796134: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 18678720, 5
2022-11-18 16:05:25.796140: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 39970560, 5
2022-11-18 16:05:25.796146: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 56589504, 5
2022-11-18 16:05:25.796152: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 135407776, 3
2022-11-18 16:05:25.796158: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1083564064, 4
2022-11-18 16:05:25.796167: 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: 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_file8iaerbvr.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 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 756 103 86%
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 2354 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 $INPUT_DATA_DIR
SKIPPED [5] ../../../.local/lib/python3.8/site-packages/tensorflow/python/framework/test_util.py:2746: Not a test.
==== 1 failed, 865 passed, 13 skipped, 1438 warnings in 1764.96s (0:29:24) =====
ERROR: InvocationError for command /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/bin/python -m pytest --cov-report term --cov merlin -rxs tests/unit (exited with code 1)
___________________________________ summary ____________________________________
ERROR: py38-gpu: commands failed
Build step 'Execute shell' marked build as failure
Performing Post build task...
Match found for : : True
Logical operation result is TRUE
Running script : #!/bin/bash
cd /var/jenkins_home/
CUDA_VISIBLE_DEVICES=1 python test_res_push.py "https://api.GitHub.com/repos/NVIDIA-Merlin/models/issues/$ghprbPullId/comments" "/var/jenkins_home/jobs/$JOB_NAME/builds/$BUILD_NUMBER/log"
[merlin_models] $ /bin/bash /tmp/jenkins7920143410802983780.sh

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GitHub pull request #894 of commit fcd46adabb39097643539be23550f4fef7c35eca, no merge conflicts.
Running as SYSTEM
Setting status of fcd46adabb39097643539be23550f4fef7c35eca to PENDING with url http://merlin-infra1.nvidia.com:8080/job/merlin_models/1900/ 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/894/*:refs/remotes/origin/pr/894/* # timeout=10
 > git rev-parse fcd46adabb39097643539be23550f4fef7c35eca^{commit} # timeout=10
Checking out Revision fcd46adabb39097643539be23550f4fef7c35eca (detached)
 > git config core.sparsecheckout # timeout=10
 > git checkout -f fcd46adabb39097643539be23550f4fef7c35eca # timeout=10
Commit message: "Merge branch 'main' into test-lazy-adam-notebook-limit-to-gpu"
 > git rev-list --no-walk 16ac9cdeee360232e51bc308fd1572be5672f5c4 # timeout=10
[merlin_models] $ /bin/bash /tmp/jenkins8121923980944787601.sh
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
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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: 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: 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: 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/4/merlin-models-0.9.0+49.gfcd46ada.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==2022.1.1,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.gfcd46ada,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='2587000622'
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-tl9l2h7z
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/core.git /tmp/pip-req-build-tl9l2h7z
  Resolved https://github.com/NVIDIA-Merlin/core.git to commit 91e52476a44e725ffb9ad580c3f2b12031d1631e
  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+15.g91e5247) (0.55.1)
Requirement already satisfied: fsspec==2022.5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+15.g91e5247) (2022.5.0)
Requirement already satisfied: tensorflow-metadata>=1.2.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+15.g91e5247) (1.10.0)
Requirement already satisfied: packaging in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+15.g91e5247) (21.3)
Requirement already satisfied: pyarrow>=5.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+15.g91e5247) (7.0.0)
Requirement already satisfied: betterproto<2.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+15.g91e5247) (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+15.g91e5247) (2022.3.0)
Requirement already satisfied: tqdm>=4.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+15.g91e5247) (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+15.g91e5247) (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+15.g91e5247) (1.3.5)
Requirement already satisfied: protobuf>=3.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+15.g91e5247) (3.19.5)
Requirement already satisfied: stringcase in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core==0.8.0+15.g91e5247) (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+15.g91e5247) (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+15.g91e5247) (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+15.g91e5247) (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+15.g91e5247) (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+15.g91e5247) (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+15.g91e5247) (1.0.4)
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+15.g91e5247) (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+15.g91e5247) (6.2)
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+15.g91e5247) (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+15.g91e5247) (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+15.g91e5247) (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+15.g91e5247) (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+15.g91e5247) (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+15.g91e5247) (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+15.g91e5247) (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+15.g91e5247) (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+15.g91e5247) (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+15.g91e5247) (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+15.g91e5247) (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+15.g91e5247) (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+15.g91e5247) (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+15.g91e5247) (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+15.g91e5247) (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+15.g91e5247) (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+15.g91e5247) (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+15.g91e5247) (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+15.g91e5247) (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+15.g91e5247) (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+15.g91e5247) (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+15.g91e5247-py3-none-any.whl size=118826 sha256=fb1bc76f3d3f44af8781762dee3f58a871722e27bf70d2f061216adbe454b511
  Stored in directory: /tmp/pip-ephem-wheel-cache-zs7zofrz/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+15.g91e5247
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-xcza2gy3
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/nvtabular.git /tmp/pip-req-build-xcza2gy3
  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: 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'
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+15.g91e5247)
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+6.ge5b7351d) (0.55.1)
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+6.ge5b7351d) (2022.5.0)
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+6.ge5b7351d) (1.10.0)
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: 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)
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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)
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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)
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+6.ge5b7351d) (0.38.1)
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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: 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: 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: 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: 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, 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=9f0fa4b9c0eba0d7175baf1abf4285dce6ff855875a4d722de20a017e14f0730
  Stored in directory: /tmp/pip-ephem-wheel-cache-w79mubv7/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=2b8fcfe3f38843c45f3cdbf87162d113ee496f51765a62f18c4a7c521827af55
  Stored in directory: /tmp/pip-ephem-wheel-cache-w79mubv7/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 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_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 . [ 30%]
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 . [ 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_file__dlgm6e.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 42141 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 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 $INPUT_DATA_DIR
SKIPPED [5] ../../../.local/lib/python3.8/site-packages/tensorflow/python/framework/test_util.py:2746: Not a test.
========= 866 passed, 13 skipped, 1439 warnings in 1867.50s (0:31:07) ==========
___________________________________ summary ____________________________________
py38-gpu: commands succeeded
congratulations :)
Performing Post build task...
Match found for : : True
Logical operation result is TRUE
Running script : #!/bin/bash
cd /var/jenkins_home/
CUDA_VISIBLE_DEVICES=1 python test_res_push.py "https://api.GitHub.com/repos/NVIDIA-Merlin/models/issues/$ghprbPullId/comments" "/var/jenkins_home/jobs/$JOB_NAME/builds/$BUILD_NUMBER/log"
[merlin_models] $ /bin/bash /tmp/jenkins382192504592117565.sh

@oliverholworthy oliverholworthy merged commit ccd7c2c into NVIDIA-Merlin:main Nov 21, 2022
@oliverholworthy oliverholworthy deleted the test-lazy-adam-notebook-limit-to-gpu branch November 21, 2022 15:01
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