Fix loading of `TwoTowerModel` with context query variable #887

oliverholworthy · 2022-11-16T11:57:30Z

Goals ⚽

Enable re-loading of a saved TwoTowerModel.

Implementation Details 🚧

Reloading a saved TwoTowerModel has been failing due to an assertion about unbound variables

AssertionError: Found 1 Python objects that were not bound to checkpointed values, likely due to changes in the Python program. Showing 1 of 1 unmatched objects: [<tf.Variable 'query:0' shape=(None, 4) dtype=float32, numpy=array([[0., 0., 0., 0.]], dtype=float32)>]

Using the keras add_weight method to create the variable intead of creating a tf.Variable instance and assigning as an attrribute allows this to bind correctly and be saved/reloaded.

Testing Details 🔍

Updated existing test for saving two tower model that has been failing when reload_model=True

sararb · 2022-11-16T15:17:23Z

Thank you for your PR! In fact, I tried replacing the add_variable with add_weights in the past to resolve the issue. However, it didn't work because the add_weights required the variable to be of a fixed shape while the context query varies with the batch size.

I also have a question regarding your comment Unblock Save output schema of model and add save method to Encoder #886, is the error specific to using the old version of RetirevalModel / TwoTower for the test? Or is there a problem with the new RetrievalModelV2/TwoTowerV2 as well? I am asking because the context variable has been removed in the newer version, so saving/reloading a retrieval model is no longer an issue in the new API.

oliverholworthy · 2022-11-16T16:59:58Z

replacing the add_variable with add_weights [...] didn't work because the add_weights required the variable to be of a fixed shape while the context query varies with the batch size.

I've added a commit that might work around this issue by padding with zeros. However, there might be an edge case where if you want to fit the same model a second time with a larger batch size this might break. Maybe an ok trade-off to make given we plan to migrate to the TwoTowerModelV2.

oliverholworthy · 2022-11-16T17:03:35Z

Re: Unblock Save output schema of model and add save method to Encoder #886, is the error specific to using the old version of RetirevalModel / TwoTower for the test? Or is there a problem with the new RetrievalModelV2/TwoTowerV2 as well?

This is because #886 currently re-loads the model after saving, so the tests that currently trigger TwoTowerModel to be saved fail with that change.

There was a recent test added for Horovod in #825 that used the TwoTowerModel

nvidia-merlin-bot · 2022-11-16T21:10:28Z

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GitHub pull request #887 of commit 46b3b17687b62f5c374ac48cbc5bf1df56c292c1, no merge conflicts.
Running as SYSTEM
Setting status of 46b3b17687b62f5c374ac48cbc5bf1df56c292c1 to PENDING with url http://merlin-infra1.nvidia.com:8080/job/merlin_models/1867/ and message: 'Pending'
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Commit message: "Use tf.shape instead of .shape to get dims"
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[merlin_models] $ /bin/bash /tmp/jenkins8260607546425798595.sh
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
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GLOB sdist-make: /var/jenkins_home/workspace/merlin_models/models/setup.py
py38-gpu recreate: /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
py38-gpu installdeps: -rrequirements/dev.txt, tensorflow<2.10
WARNING: Discarding $PYTHONPATH from environment, to override specify PYTHONPATH in 'passenv' in your configuration.
py38-gpu inst: /var/jenkins_home/workspace/merlin_models/models/.tox/.tmp/package/3/merlin-models-0.9.0+51.g46b3b176.zip
WARNING: Discarding $PYTHONPATH from environment, to override specify PYTHONPATH in 'passenv' in your configuration.
py38-gpu installed: 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Building wheels for collected packages: merlin-core
  Building wheel for merlin-core (pyproject.toml): started
  Building wheel for merlin-core (pyproject.toml): finished with status 'done'
  Created wheel for merlin-core: filename=merlin_core-0.8.0+12.gaac1dc3-py3-none-any.whl size=118622 sha256=b012ccb8807add341daa9c5da5ea93b4638e42aa483f08974a4d5cee25b47f8d
  Stored in directory: /tmp/pip-ephem-wheel-cache-ag3qdryf/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-rj__hz36
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/nvtabular.git /tmp/pip-req-build-rj__hz36
  Resolved https://github.com/NVIDIA-Merlin/nvtabular.git to commit ba4c14159a8e858c8998d4158a4376e65a8fa266
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: merlin-core>=0.2.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from nvtabular==1.6.0+4.gba4c1415) (0.8.0+12.gaac1dc3)
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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)
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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+4.gba4c1415) (1.15.0)
Requirement already satisfied: heapdict in /var/jenkins_home/.local/lib/python3.8/site-packages/HeapDict-1.0.1-py3.8.egg (from zict>=0.1.3->distributed>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (1.0.1)
Requirement already satisfied: multidict in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (6.0.2)
Requirement already satisfied: h2<5,>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (4.1.0)
Requirement already satisfied: MarkupSafe>=2.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from jinja2->distributed>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (2.0.1)
Requirement already satisfied: hpack<5,>=4.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (4.0.0)
Requirement already satisfied: hyperframe<7,>=6.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (6.0.1)
Building wheels for collected packages: nvtabular
  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=58f02d8d6800d71240702398c3be5cbe9b285b034896db2bb0d4f96de082922f
  Stored in directory: /tmp/pip-ephem-wheel-cache-44b7o4ws/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+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 878 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%]

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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/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 .....                   [ 43%]

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......                                           [ 80%]

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: 121 warnings

tests/unit/tf/outputs/test_base.py: 6 warnings

tests/unit/tf/outputs/test_classification.py: 6 warnings

tests/unit/tf/outputs/test_contrastive.py: 19 warnings

tests/unit/tf/outputs/test_regression.py: 2 warnings

tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings

tests/unit/tf/prediction_tasks/test_retrieval.py: 1 warning

tests/unit/tf/transformers/test_block.py: 16 warnings

tests/unit/tf/transforms/test_bias.py: 2 warnings

tests/unit/tf/transforms/test_features.py: 10 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings

tests/unit/tf/transforms/test_noise.py: 1 warning

tests/unit/tf/transforms/test_sequence.py: 15 warnings

tests/unit/tf/utils/test_batch.py: 9 warnings

tests/unit/tf/utils/test_dataset.py: 2 warnings

tests/unit/torch/block/test_base.py: 4 warnings

tests/unit/torch/block/test_mlp.py: 1 warning

tests/unit/torch/features/test_continuous.py: 1 warning

tests/unit/torch/features/test_embedding.py: 4 warnings

tests/unit/torch/features/test_tabular.py: 4 warnings

tests/unit/torch/model/test_head.py: 12 warnings

tests/unit/torch/model/test_model.py: 2 warnings

tests/unit/torch/tabular/test_aggregation.py: 6 warnings

tests/unit/torch/tabular/test_transformations.py: 3 warnings

tests/unit/xgb/test_xgboost.py: 18 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.ITEM_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.ITEM: 'item'>, <Tags.ID: 'id'>].

warnings.warn(
tests/unit/datasets/test_ecommerce.py: 3 warnings

tests/unit/datasets/test_entertainment.py: 4 warnings

tests/unit/datasets/test_social.py: 1 warning

tests/unit/datasets/test_synthetic.py: 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: 87 warnings

tests/unit/tf/outputs/test_base.py: 6 warnings

tests/unit/tf/outputs/test_classification.py: 6 warnings

tests/unit/tf/outputs/test_contrastive.py: 19 warnings

tests/unit/tf/outputs/test_regression.py: 2 warnings

tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings

tests/unit/tf/transformers/test_block.py: 10 warnings

tests/unit/tf/transforms/test_features.py: 10 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings

tests/unit/tf/transforms/test_sequence.py: 15 warnings

tests/unit/tf/utils/test_batch.py: 7 warnings

tests/unit/tf/utils/test_dataset.py: 2 warnings

tests/unit/torch/block/test_base.py: 4 warnings

tests/unit/torch/block/test_mlp.py: 1 warning

tests/unit/torch/features/test_continuous.py: 1 warning

tests/unit/torch/features/test_embedding.py: 4 warnings

tests/unit/torch/features/test_tabular.py: 4 warnings

tests/unit/torch/model/test_head.py: 12 warnings

tests/unit/torch/model/test_model.py: 2 warnings

tests/unit/torch/tabular/test_aggregation.py: 6 warnings

tests/unit/torch/tabular/test_transformations.py: 2 warnings

tests/unit/xgb/test_xgboost.py: 17 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.USER_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.USER: 'user'>, <Tags.ID: 'id'>].

warnings.warn(
tests/unit/datasets/test_ecommerce.py: 1 warning

tests/unit/datasets/test_entertainment.py: 1 warning

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 2 warnings

tests/unit/tf/core/test_prediction.py: 1 warning

tests/unit/tf/horovod/test_horovod.py: 1 warning

tests/unit/tf/inputs/test_continuous.py: 4 warnings

tests/unit/tf/inputs/test_embedding.py: 9 warnings

tests/unit/tf/inputs/test_tabular.py: 8 warnings

tests/unit/tf/models/test_ranking.py: 20 warnings

tests/unit/tf/models/test_retrieval.py: 10 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 3 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 9 warnings

tests/unit/xgb/test_xgboost.py: 12 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.SESSION_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.SESSION: 'session'>, <Tags.ID: 'id'>].

warnings.warn(
tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export

tests/unit/tf/inputs/test_embedding.py::test_embedding_features_exporting_and_loading_pretrained_initializer

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/inputs/embedding.py:970: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack

embeddings_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(embeddings)))
tests/unit/tf/blocks/retrieval/test_two_tower.py: 1 warning

tests/unit/tf/core/test_index.py: 4 warnings

tests/unit/tf/horovod/test_horovod.py: 3 warnings

tests/unit/tf/models/test_retrieval.py: 59 warnings

tests/unit/tf/prediction_tasks/test_next_item.py: 3 warnings

tests/unit/tf/utils/test_batch.py: 2 warnings

/tmp/autograph_generated_filedw7dye5o.py:8: DeprecationWarning: The 'warn' method is deprecated, use 'warning' instead

ag.converted_call(ag__.ld(warnings).warn, ("The 'warn' method is deprecated, use 'warning' instead", ag__.ld(DeprecationWarning), 2), None, fscope)
tests/unit/tf/core/test_combinators.py::test_parallel_block_select_by_tags

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/core/tabular.py:602: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated since Python 3.3, and in 3.10 it will stop working

elif isinstance(self.feature_names, collections.Sequence):
tests/unit/tf/core/test_encoder.py: 1 warning

tests/unit/tf/core/test_index.py: 5 warnings

tests/unit/tf/models/test_retrieval.py: 30 warnings

tests/unit/tf/utils/test_batch.py: 4 warnings

tests/unit/tf/utils/test_dataset.py: 1 warning

/var/jenkins_home/workspace/merlin_models/models/merlin/models/utils/dataset.py:75: DeprecationWarning: unique_rows_by_features is deprecated and will be removed in a future version. Please use unique_by_tag instead.

warnings.warn(
tests/unit/tf/models/test_base.py::test_model_pre_post[True]

tests/unit/tf/models/test_base.py::test_model_pre_post[False]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.1]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.3]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.5]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.7]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/util/dispatch.py:1082: UserWarning: tf.keras.backend.random_binomial is deprecated, and will be removed in a future version.Please use tf.keras.backend.random_bernoulli instead.

return dispatch_target(*args, **kwargs)
tests/unit/tf/models/test_base.py::test_freeze_parallel_block[True]

tests/unit/tf/models/test_base.py::test_freeze_sequential_block

tests/unit/tf/models/test_base.py::test_freeze_unfreeze

tests/unit/tf/models/test_base.py::test_unfreeze_all_blocks

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/gradient_descent.py:108: UserWarning: The lr argument is deprecated, use learning_rate instead.

super(SGD, self).init(name, **kwargs)
tests/unit/tf/models/test_base.py::test_retrieval_model_query

tests/unit/tf/models/test_base.py::test_retrieval_model_query

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_v2_export_embeddings

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[True]

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[False]

tests/unit/tf/transformers/test_block.py::test_retrieval_transformer[True]

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/utils/tf_utils.py:298: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack

tensor_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(tensor)))
tests/unit/tf/models/test_ranking.py::test_deepfm_model_only_categ_feats[False]

tests/unit/tf/models/test_ranking.py::test_deepfm_model_categ_and_continuous_feats[False]

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

warnings.warn(
tests/unit/tf/models/test_ranking.py::test_wide_deep_model[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_categorical_one_hot[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_hashed_cross[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

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

warnings.warn(
tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[True]

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/transforms/features.py:569: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag

warnings.warn(
tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/autograph/impl/api.py:371: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag

return py_builtins.overload_of(f)(*args)
tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_onehot_multihot_feature_interaction[False]

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

warnings.warn(
tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_feature_interaction_multi_optimizer[False]

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

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]

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

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]

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

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]

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

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]

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

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

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

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

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

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

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

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

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

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

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

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

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

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

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

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

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

warnings.warn(
tests/unit/torch/block/test_mlp.py::test_mlp_block

/var/jenkins_home/workspace/merlin_models/models/tests/unit/torch/_conftest.py:151: UserWarning: Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

return {key: torch.tensor(value) for key, value in data.items()}
tests/unit/xgb/test_xgboost.py::test_without_dask_client

tests/unit/xgb/test_xgboost.py::TestXGBoost::test_music_regression

tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs0-DaskDeviceQuantileDMatrix]

tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs1-DaskDMatrix]

tests/unit/xgb/test_xgboost.py::TestEvals::test_multiple

tests/unit/xgb/test_xgboost.py::TestEvals::test_default

tests/unit/xgb/test_xgboost.py::TestEvals::test_train_and_valid

tests/unit/xgb/test_xgboost.py::TestEvals::test_invalid_data

/var/jenkins_home/workspace/merlin_models/models/merlin/models/xgb/init.py:344: UserWarning: Ignoring list columns as inputs to XGBoost model: ['item_genres', 'user_genres'].

warnings.warn(f"Ignoring list columns as inputs to XGBoost model: {list_column_names}.")
tests/unit/xgb/test_xgboost.py::TestXGBoost::test_unsupported_objective

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/tornado/ioloop.py:350: DeprecationWarning: make_current is deprecated; start the event loop first

self.make_current()
tests/unit/xgb/test_xgboost.py: 14 warnings

/usr/local/lib/python3.8/dist-packages/xgboost/dask.py:884: RuntimeWarning: coroutine 'Client._wait_for_workers' was never awaited

client.wait_for_workers(n_workers)

Enable tracemalloc to get traceback where the object was allocated.

See https://docs.pytest.org/en/stable/how-to/capture-warnings.html#resource-warnings for more info.
tests/unit/xgb/test_xgboost.py: 11 warnings

/usr/local/lib/python3.8/dist-packages/cudf/core/dataframe.py:1183: DeprecationWarning: The default dtype for empty Series will be 'object' instead of 'float64' in a future version. Specify a dtype explicitly to silence this warning.

mask = pd.Series(mask)
-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html
---------- coverage: platform linux, python 3.8.10-final-0 -----------

Name                                                                 Stmts   Miss  Cover
merlin/datasets/init.py                                              2      0   100%

merlin/datasets/advertising/init.py                                  2      0   100%

merlin/datasets/advertising/criteo/init.py                           0      0   100%

merlin/datasets/advertising/criteo/dataset.py                           79     49    38%

merlin/datasets/advertising/criteo/transformed/init.py               0      0   100%

merlin/datasets/ecommerce/init.py                                    4      0   100%

merlin/datasets/ecommerce/aliccp/init.py                             0      0   100%

merlin/datasets/ecommerce/aliccp/dataset.py                            141     87    38%

merlin/datasets/ecommerce/aliccp/raw/init.py                         0      0   100%

merlin/datasets/ecommerce/aliccp/transformed/init.py                 0      0   100%

merlin/datasets/ecommerce/booking/init.py                            0      0   100%

merlin/datasets/ecommerce/booking/dataset.py                           127    100    21%

merlin/datasets/ecommerce/booking/transformed/init.py                0      0   100%

merlin/datasets/ecommerce/dressipi/init.py                           0      0   100%

merlin/datasets/ecommerce/dressipi/dataset.py                           45     37    18%

merlin/datasets/ecommerce/dressipi/preprocessed/init.py              0      0   100%

merlin/datasets/ecommerce/large/init.py                              0      0   100%

merlin/datasets/ecommerce/small/init.py                              0      0   100%

merlin/datasets/ecommerce/transactions/init.py                       0      0   100%

merlin/datasets/entertainment/init.py                                2      0   100%

merlin/datasets/entertainment/movielens/1m-raw/init.py               0      0   100%

merlin/datasets/entertainment/movielens/1m-raw/ratings/init.py       0      0   100%

merlin/datasets/entertainment/movielens/1m/init.py                   0      0   100%

merlin/datasets/entertainment/movielens/25m/init.py                  0      0   100%

merlin/datasets/entertainment/movielens/100k/init.py                 0      0   100%

merlin/datasets/entertainment/movielens/init.py                      0      0   100%

merlin/datasets/entertainment/movielens/dataset.py                     152    122    20%

merlin/datasets/entertainment/music_streaming/init.py                0      0   100%

merlin/datasets/social/init.py                                       0      0   100%

merlin/datasets/synthetic.py                                           147     14    90%

merlin/datasets/testing/init.py                                      0      0   100%

merlin/datasets/testing/sequence_testing/init.py                     0      0   100%

merlin/models/init.py                                                2      0   100%

merlin/models/_version.py                                              354    205    42%

merlin/models/api.py                                                    14      5    64%

merlin/models/config/init.py                                         0      0   100%

merlin/models/config/schema.py                                          62      0   100%

merlin/models/implicit/init.py                                      27      4    85%

merlin/models/io.py                                                     15      0   100%

merlin/models/lightfm/init.py                                       23      0   100%

merlin/models/loader/init.py                                         0      0   100%

merlin/models/loader/backend.py                                        379     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                              175     62    65%

merlin/models/tf/blocks/retrieval/matrix_factorization.py               35      1    97%

merlin/models/tf/blocks/retrieval/two_tower.py                          30      0   100%

merlin/models/tf/blocks/sampling/init.py                             0      0   100%

merlin/models/tf/blocks/sampling/base.py                                29      2    93%

merlin/models/tf/blocks/sampling/cross_batch.py                         46      2    96%

merlin/models/tf/blocks/sampling/in_batch.py                            35      0   100%

merlin/models/tf/blocks/sampling/queue.py                              115     12    90%

merlin/models/tf/core/init.py                                        0      0   100%

merlin/models/tf/core/aggregation.py                                   241     45    81%

merlin/models/tf/core/base.py                                          242     50    79%

merlin/models/tf/core/combinators.py                                   426     53    88%

merlin/models/tf/core/encoder.py                                       175     28    84%

merlin/models/tf/core/index.py                                         106     16    85%

merlin/models/tf/core/prediction.py                                     50      1    98%

merlin/models/tf/core/tabular.py                                       280     29    90%

merlin/models/tf/distributed/init.py                                 0      0   100%

merlin/models/tf/distributed/backend.py                                  9      2    78%

merlin/models/tf/inputs/init.py                                      0      0   100%

merlin/models/tf/inputs/base.py                                         60     10    83%

merlin/models/tf/inputs/continuous.py                                   39      3    92%

merlin/models/tf/inputs/embedding.py                                   458     32    93%

merlin/models/tf/loader.py                                             268     94    65%

merlin/models/tf/losses/init.py                                      4      0   100%

merlin/models/tf/losses/base.py                                          9      0   100%

merlin/models/tf/losses/listwise.py                                     13      0   100%

merlin/models/tf/losses/pairwise.py                                    115      1    99%

merlin/models/tf/metrics/init.py                                     2      0   100%

merlin/models/tf/metrics/evaluation.py                                 105     48    54%

merlin/models/tf/metrics/topk.py                                       198     48    76%

merlin/models/tf/models/init.py                                      0      0   100%

merlin/models/tf/models/base.py                                        756    101    87%

merlin/models/tf/models/benchmark.py                                    16      0   100%

merlin/models/tf/models/ranking.py                                      67      3    96%

merlin/models/tf/models/retrieval.py                                    78      4    95%

merlin/models/tf/models/utils.py                                        10      1    90%

merlin/models/tf/outputs/init.py                                     0      0   100%

merlin/models/tf/outputs/base.py                                       123     17    86%

merlin/models/tf/outputs/classification.py                              91      1    99%

merlin/models/tf/outputs/contrastive.py                                147     10    93%

merlin/models/tf/outputs/regression.py                                   9      0   100%

merlin/models/tf/outputs/sampling/init.py                            0      0   100%

merlin/models/tf/outputs/sampling/base.py                               78     21    73%

merlin/models/tf/outputs/sampling/in_batch.py                           37      1    97%

merlin/models/tf/outputs/sampling/popularity.py                         27      1    96%

merlin/models/tf/outputs/topk.py                                        98      6    94%

merlin/models/tf/prediction_tasks/init.py                            0      0   100%

merlin/models/tf/prediction_tasks/base.py                              207     37    82%

merlin/models/tf/prediction_tasks/classification.py                     68     17    75%

merlin/models/tf/prediction_tasks/multi.py                               7      0   100%

merlin/models/tf/prediction_tasks/next_item.py                          59      6    90%

merlin/models/tf/prediction_tasks/regression.py                         35      2    94%

merlin/models/tf/prediction_tasks/retrieval.py                          73      3    96%

merlin/models/tf/transformers/init.py                                0      0   100%

merlin/models/tf/transformers/block.py                                 101      2    98%

merlin/models/tf/transformers/transforms.py                             63      0   100%

merlin/models/tf/transforms/init.py                                  0      0   100%

merlin/models/tf/transforms/bias.py                                    111      9    92%

merlin/models/tf/transforms/features.py                                435     36    92%

merlin/models/tf/transforms/negative_sampling.py                        77      3    96%

merlin/models/tf/transforms/noise.py                                    43      1    98%

merlin/models/tf/transforms/regularization.py                           17      1    94%

merlin/models/tf/transforms/sequence.py                                282     42    85%

merlin/models/tf/transforms/tensor.py                                  158     13    92%

merlin/models/tf/typing.py                                               7      0   100%

merlin/models/tf/utils/init.py                                       0      0   100%

merlin/models/tf/utils/batch_utils.py                                   85      4    95%

merlin/models/tf/utils/repr_utils.py                                    69      4    94%

merlin/models/tf/utils/search_utils.py                                  34     22    35%

merlin/models/tf/utils/testing_utils.py                                206     36    83%

merlin/models/tf/utils/tf_utils.py                                     209     42    80%

merlin/models/torch/init.py                                         12      0   100%

merlin/models/torch/block/init.py                                    0      0   100%

merlin/models/torch/block/base.py                                      167     32    81%

merlin/models/torch/block/mlp.py                                        38      5    87%

merlin/models/torch/dataset.py                                          68      5    93%

merlin/models/torch/features/init.py                                 0      0   100%

merlin/models/torch/features/base.py                                     4      0   100%

merlin/models/torch/features/continuous.py                              22      0   100%

merlin/models/torch/features/embedding.py                              165     12    93%

merlin/models/torch/features/tabular.py                                 65      8    88%

merlin/models/torch/losses.py                                           28     28     0%

merlin/models/torch/model/init.py                                    0      0   100%

merlin/models/torch/model/base.py                                      286     65    77%

merlin/models/torch/model/prediction_task.py                            24      0   100%

merlin/models/torch/tabular/init.py                                  0      0   100%

merlin/models/torch/tabular/aggregation.py                              75      0   100%

merlin/models/torch/tabular/base.py                                    247     39    84%

merlin/models/torch/tabular/transformations.py                          67      3    96%

merlin/models/torch/typing.py                                            6      0   100%

merlin/models/torch/utils/init.py                                    0      0   100%

merlin/models/torch/utils/data_utils.py                                117    117     0%

merlin/models/torch/utils/examples_utils.py                             39     39     0%

merlin/models/torch/utils/torch_utils.py                                80     22    72%

merlin/models/utils/init.py                                          0      0   100%

merlin/models/utils/constants.py                                         3      0   100%

merlin/models/utils/dataset.py                                          38      4    89%

merlin/models/utils/dependencies.py                                     26     19    27%

merlin/models/utils/doc_utils.py                                        10      0   100%

merlin/models/utils/example_utils.py                                    31      2    94%

merlin/models/utils/misc_utils.py                                      118     90    24%

merlin/models/utils/nvt_utils.py                                        27     24    11%

merlin/models/utils/registry.py                                        101     29    71%

merlin/models/utils/schema_utils.py                                     90     19    79%

merlin/models/xgb/init.py                                          124      4    97%
TOTAL                                                                11581   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.

========= 865 passed, 13 skipped, 1444 warnings in 1724.87s (0:28:44) ==========

___________________________________ 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/jenkins10810842973521909202.sh

nvidia-merlin-bot · 2022-11-18T18:58:21Z

Click to view CI Results

GitHub pull request #887 of commit a2e1714b72b1a42c5c17e4a1fa4a44a2c86034d9, no merge conflicts.
Running as SYSTEM
Setting status of a2e1714b72b1a42c5c17e4a1fa4a44a2c86034d9 to PENDING with url http://merlin-infra1.nvidia.com:8080/job/merlin_models/1891/ 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/887/*:refs/remotes/origin/pr/887/* # timeout=10
 > git rev-parse a2e1714b72b1a42c5c17e4a1fa4a44a2c86034d9^{commit} # timeout=10
Checking out Revision a2e1714b72b1a42c5c17e4a1fa4a44a2c86034d9 (detached)
 > git config core.sparsecheckout # timeout=10
 > git checkout -f a2e1714b72b1a42c5c17e4a1fa4a44a2c86034d9 # timeout=10
Commit message: "Merge branch 'main' into fix-two-tower-model-load-context-variable"
 > git rev-list --no-walk 8e5c9f4f028421879bcffd7bef326940777f0fd3 # timeout=10
[merlin_models] $ /bin/bash /tmp/jenkins11473624751751404004.sh
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Requirement already satisfied: testbook in /usr/local/lib/python3.8/dist-packages (0.4.2)
Requirement already satisfied: nbformat>=5.0.4 in /usr/local/lib/python3.8/dist-packages (from testbook) (5.5.0)
Requirement already satisfied: nbclient>=0.4.0 in /usr/local/lib/python3.8/dist-packages (from testbook) (0.6.8)
Requirement already satisfied: traitlets>=5.2.2 in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (5.4.0)
Requirement already satisfied: nest-asyncio in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (1.5.5)
Requirement already satisfied: jupyter-client>=6.1.5 in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (7.3.5)
Requirement already satisfied: jupyter_core in /usr/local/lib/python3.8/dist-packages (from nbformat>=5.0.4->testbook) (4.11.1)
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: 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: 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: pyzmq>=23.0 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (24.0.0)
Requirement already satisfied: entrypoints in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (0.4)
Requirement already satisfied: tornado>=6.2 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (6.2)
Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (2.8.2)
Requirement already satisfied: zipp>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from importlib-resources>=1.4.0->jsonschema>=2.6->nbformat>=5.0.4->testbook) (3.8.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.8.2->jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (1.15.0)
GLOB sdist-make: /var/jenkins_home/workspace/merlin_models/models/setup.py
py38-gpu recreate: /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
py38-gpu installdeps: -rrequirements/dev.txt, tensorflow<2.10
WARNING: Discarding $PYTHONPATH from environment, to override specify PYTHONPATH in 'passenv' in your configuration.
py38-gpu inst: /var/jenkins_home/workspace/merlin_models/models/.tox/.tmp/package/3/merlin-models-0.9.0+54.ga2e1714b.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+54.ga2e1714b,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='1025493637'
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-xd7l2vf8
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/core.git /tmp/pip-req-build-xd7l2vf8
  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: pyarrow>=5.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+14.gb298635) (7.0.0)
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Requirement already satisfied: dask>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+14.gb298635) (2022.3.0)
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Requirement already satisfied: packaging in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+14.gb298635) (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==0.8.0+14.gb298635) (2022.3.0)
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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==0.8.0+14.gb298635) (1.2.0)
Requirement already satisfied: cloudpickle>=1.1.1 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core==0.8.0+14.gb298635) (2.2.0)
Requirement already satisfied: toolz>=0.8.2 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core==0.8.0+14.gb298635) (0.12.0)
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+14.gb298635) (1.7.0)
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+14.gb298635) (6.2)
Requirement already satisfied: sortedcontainers!=2.0.0,!=2.0.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/sortedcontainers-2.4.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+14.gb298635) (2.4.0)
Requirement already satisfied: psutil>=5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/psutil-5.8.0-py3.8-linux-x86_64.egg (from distributed>=2022.3.0->merlin-core==0.8.0+14.gb298635) (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+14.gb298635) (1.0.4)
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Requirement already satisfied: jinja2 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+14.gb298635) (3.1.2)
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: 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: 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: 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: 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: 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)
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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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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=6d44b7f98ed90a21356c6d91a0e574fbe6de96338d590853c096bb27c478fc09
  Stored in directory: /tmp/pip-ephem-wheel-cache-tv4cidaz/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-pytn3tyo
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/nvtabular.git /tmp/pip-req-build-pytn3tyo
  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)
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Requirement already satisfied: hpack<5,>=4.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core>=0.2.0->nvtabular==1.6.0+5.g21117cfc) (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+5.g21117cfc) (6.0.1)
Building wheels for collected packages: nvtabular
  Building wheel for nvtabular (pyproject.toml): started
  Building wheel for nvtabular (pyproject.toml): finished with status 'done'
  Created wheel for nvtabular: filename=nvtabular-1.6.0+5.g21117cfc-cp38-cp38-linux_x86_64.whl size=257596 sha256=b51fd7e1d504924bb26f3cf2eeed0b268bb58526eba61dbf8bdec8f4b9c64af8
  Stored in directory: /tmp/pip-ephem-wheel-cache-ktt4p33z/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%]

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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%]

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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: 121 warnings

tests/unit/tf/outputs/test_base.py: 6 warnings

tests/unit/tf/outputs/test_classification.py: 6 warnings

tests/unit/tf/outputs/test_contrastive.py: 19 warnings

tests/unit/tf/outputs/test_regression.py: 2 warnings

tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings

tests/unit/tf/prediction_tasks/test_retrieval.py: 1 warning

tests/unit/tf/transformers/test_block.py: 16 warnings

tests/unit/tf/transforms/test_bias.py: 2 warnings

tests/unit/tf/transforms/test_features.py: 10 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings

tests/unit/tf/transforms/test_noise.py: 1 warning

tests/unit/tf/transforms/test_sequence.py: 15 warnings

tests/unit/tf/utils/test_batch.py: 9 warnings

tests/unit/tf/utils/test_dataset.py: 2 warnings

tests/unit/torch/block/test_base.py: 4 warnings

tests/unit/torch/block/test_mlp.py: 1 warning

tests/unit/torch/features/test_continuous.py: 1 warning

tests/unit/torch/features/test_embedding.py: 4 warnings

tests/unit/torch/features/test_tabular.py: 4 warnings

tests/unit/torch/model/test_head.py: 12 warnings

tests/unit/torch/model/test_model.py: 2 warnings

tests/unit/torch/tabular/test_aggregation.py: 6 warnings

tests/unit/torch/tabular/test_transformations.py: 3 warnings

tests/unit/xgb/test_xgboost.py: 18 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.ITEM_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.ITEM: 'item'>, <Tags.ID: 'id'>].

warnings.warn(
tests/unit/datasets/test_ecommerce.py: 3 warnings

tests/unit/datasets/test_entertainment.py: 4 warnings

tests/unit/datasets/test_social.py: 1 warning

tests/unit/datasets/test_synthetic.py: 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: 87 warnings

tests/unit/tf/outputs/test_base.py: 6 warnings

tests/unit/tf/outputs/test_classification.py: 6 warnings

tests/unit/tf/outputs/test_contrastive.py: 19 warnings

tests/unit/tf/outputs/test_regression.py: 2 warnings

tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings

tests/unit/tf/transformers/test_block.py: 10 warnings

tests/unit/tf/transforms/test_features.py: 10 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings

tests/unit/tf/transforms/test_sequence.py: 15 warnings

tests/unit/tf/utils/test_batch.py: 7 warnings

tests/unit/tf/utils/test_dataset.py: 2 warnings

tests/unit/torch/block/test_base.py: 4 warnings

tests/unit/torch/block/test_mlp.py: 1 warning

tests/unit/torch/features/test_continuous.py: 1 warning

tests/unit/torch/features/test_embedding.py: 4 warnings

tests/unit/torch/features/test_tabular.py: 4 warnings

tests/unit/torch/model/test_head.py: 12 warnings

tests/unit/torch/model/test_model.py: 2 warnings

tests/unit/torch/tabular/test_aggregation.py: 6 warnings

tests/unit/torch/tabular/test_transformations.py: 2 warnings

tests/unit/xgb/test_xgboost.py: 17 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.USER_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.USER: 'user'>, <Tags.ID: 'id'>].

warnings.warn(
tests/unit/datasets/test_ecommerce.py: 1 warning

tests/unit/datasets/test_entertainment.py: 1 warning

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 2 warnings

tests/unit/tf/core/test_prediction.py: 1 warning

tests/unit/tf/horovod/test_horovod.py: 1 warning

tests/unit/tf/inputs/test_continuous.py: 4 warnings

tests/unit/tf/inputs/test_embedding.py: 9 warnings

tests/unit/tf/inputs/test_tabular.py: 8 warnings

tests/unit/tf/models/test_ranking.py: 20 warnings

tests/unit/tf/models/test_retrieval.py: 10 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 3 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 9 warnings

tests/unit/xgb/test_xgboost.py: 12 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.SESSION_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.SESSION: 'session'>, <Tags.ID: 'id'>].

warnings.warn(
tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export

tests/unit/tf/inputs/test_embedding.py::test_embedding_features_exporting_and_loading_pretrained_initializer

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/inputs/embedding.py:970: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack

embeddings_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(embeddings)))
tests/unit/tf/blocks/retrieval/test_two_tower.py: 1 warning

tests/unit/tf/core/test_index.py: 4 warnings

tests/unit/tf/horovod/test_horovod.py: 3 warnings

tests/unit/tf/models/test_retrieval.py: 59 warnings

tests/unit/tf/prediction_tasks/test_next_item.py: 3 warnings

tests/unit/tf/utils/test_batch.py: 2 warnings

/tmp/autograph_generated_file1fdfq17j.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                              175     62    65%

merlin/models/tf/blocks/retrieval/matrix_factorization.py               35      1    97%

merlin/models/tf/blocks/retrieval/two_tower.py                          30      0   100%

merlin/models/tf/blocks/sampling/init.py                             0      0   100%

merlin/models/tf/blocks/sampling/base.py                                29      2    93%

merlin/models/tf/blocks/sampling/cross_batch.py                         46      2    96%

merlin/models/tf/blocks/sampling/in_batch.py                            35      0   100%

merlin/models/tf/blocks/sampling/queue.py                              115     12    90%

merlin/models/tf/core/init.py                                        0      0   100%

merlin/models/tf/core/aggregation.py                                   241     45    81%

merlin/models/tf/core/base.py                                          242     50    79%

merlin/models/tf/core/combinators.py                                   426     53    88%

merlin/models/tf/core/encoder.py                                       175     28    84%

merlin/models/tf/core/index.py                                         106     16    85%

merlin/models/tf/core/prediction.py                                     50      1    98%

merlin/models/tf/core/tabular.py                                       280     29    90%

merlin/models/tf/distributed/init.py                                 0      0   100%

merlin/models/tf/distributed/backend.py                                  9      2    78%

merlin/models/tf/inputs/init.py                                      0      0   100%

merlin/models/tf/inputs/base.py                                         60     10    83%

merlin/models/tf/inputs/continuous.py                                   39      3    92%

merlin/models/tf/inputs/embedding.py                                   458     32    93%

merlin/models/tf/loader.py                                             268     94    65%

merlin/models/tf/losses/init.py                                      4      0   100%

merlin/models/tf/losses/base.py                                          9      0   100%

merlin/models/tf/losses/listwise.py                                     13      0   100%

merlin/models/tf/losses/pairwise.py                                    115      1    99%

merlin/models/tf/metrics/init.py                                     2      0   100%

merlin/models/tf/metrics/evaluation.py                                 105     48    54%

merlin/models/tf/metrics/topk.py                                       198     48    76%

merlin/models/tf/models/init.py                                      0      0   100%

merlin/models/tf/models/base.py                                        756    101    87%

merlin/models/tf/models/benchmark.py                                    16      0   100%

merlin/models/tf/models/ranking.py                                      67      3    96%

merlin/models/tf/models/retrieval.py                                    78      4    95%

merlin/models/tf/models/utils.py                                        10      1    90%

merlin/models/tf/outputs/init.py                                     0      0   100%

merlin/models/tf/outputs/base.py                                       123     17    86%

merlin/models/tf/outputs/classification.py                              91      1    99%

merlin/models/tf/outputs/contrastive.py                                147     10    93%

merlin/models/tf/outputs/regression.py                                   9      0   100%

merlin/models/tf/outputs/sampling/init.py                            0      0   100%

merlin/models/tf/outputs/sampling/base.py                               78     21    73%

merlin/models/tf/outputs/sampling/in_batch.py                           37      1    97%

merlin/models/tf/outputs/sampling/popularity.py                         27      1    96%

merlin/models/tf/outputs/topk.py                                        98      6    94%

merlin/models/tf/prediction_tasks/init.py                            0      0   100%

merlin/models/tf/prediction_tasks/base.py                              207     37    82%

merlin/models/tf/prediction_tasks/classification.py                     68     17    75%

merlin/models/tf/prediction_tasks/multi.py                               7      0   100%

merlin/models/tf/prediction_tasks/next_item.py                          59      6    90%

merlin/models/tf/prediction_tasks/regression.py                         35      2    94%

merlin/models/tf/prediction_tasks/retrieval.py                          73      3    96%

merlin/models/tf/transformers/init.py                                0      0   100%

merlin/models/tf/transformers/block.py                                 101      2    98%

merlin/models/tf/transformers/transforms.py                             63      0   100%

merlin/models/tf/transforms/init.py                                  0      0   100%

merlin/models/tf/transforms/bias.py                                    111      9    92%

merlin/models/tf/transforms/features.py                                435     36    92%

merlin/models/tf/transforms/negative_sampling.py                        77      3    96%

merlin/models/tf/transforms/noise.py                                    43      1    98%

merlin/models/tf/transforms/regularization.py                           17      1    94%

merlin/models/tf/transforms/sequence.py                                282     42    85%

merlin/models/tf/transforms/tensor.py                                  158     13    92%

merlin/models/tf/typing.py                                               7      0   100%

merlin/models/tf/utils/init.py                                       0      0   100%

merlin/models/tf/utils/batch_utils.py                                   85      4    95%

merlin/models/tf/utils/repr_utils.py                                    69      4    94%

merlin/models/tf/utils/search_utils.py                                  34     22    35%

merlin/models/tf/utils/testing_utils.py                                206     36    83%

merlin/models/tf/utils/tf_utils.py                                     209     42    80%

merlin/models/torch/init.py                                         12      0   100%

merlin/models/torch/block/init.py                                    0      0   100%

merlin/models/torch/block/base.py                                      167     32    81%

merlin/models/torch/block/mlp.py                                        38      5    87%

merlin/models/torch/dataset.py                                          68      5    93%

merlin/models/torch/features/init.py                                 0      0   100%

merlin/models/torch/features/base.py                                     4      0   100%

merlin/models/torch/features/continuous.py                              22      0   100%

merlin/models/torch/features/embedding.py                              165     12    93%

merlin/models/torch/features/tabular.py                                 65      8    88%

merlin/models/torch/losses.py                                           28     28     0%

merlin/models/torch/model/init.py                                    0      0   100%

merlin/models/torch/model/base.py                                      286     65    77%

merlin/models/torch/model/prediction_task.py                            24      0   100%

merlin/models/torch/tabular/init.py                                  0      0   100%

merlin/models/torch/tabular/aggregation.py                              75      0   100%

merlin/models/torch/tabular/base.py                                    247     39    84%

merlin/models/torch/tabular/transformations.py                          67      3    96%

merlin/models/torch/typing.py                                            6      0   100%

merlin/models/torch/utils/init.py                                    0      0   100%

merlin/models/torch/utils/data_utils.py                                117    117     0%

merlin/models/torch/utils/examples_utils.py                             39     39     0%

merlin/models/torch/utils/torch_utils.py                                80     22    72%

merlin/models/utils/init.py                                          0      0   100%

merlin/models/utils/constants.py                                         3      0   100%

merlin/models/utils/dataset.py                                          38      4    89%

merlin/models/utils/dependencies.py                                     26     19    27%

merlin/models/utils/doc_utils.py                                        10      0   100%

merlin/models/utils/example_utils.py                                    31      2    94%

merlin/models/utils/misc_utils.py                                      118     90    24%

merlin/models/utils/nvt_utils.py                                        27     24    11%

merlin/models/utils/registry.py                                        101     29    71%

merlin/models/utils/schema_utils.py                                     90     19    79%

merlin/models/xgb/init.py                                          124      4    97%
TOTAL                                                                11581   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, 1444 warnings in 1779.46s (0:29:39) ==========

___________________________________ 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/jenkins8357522071767211199.sh

nvidia-merlin-bot · 2022-11-21T15:43:26Z

Click to view CI Results

GitHub pull request #887 of commit 904d91167ec0258717fa2e1843c92119bbe87308, no merge conflicts.
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Checking out Revision 904d91167ec0258717fa2e1843c92119bbe87308 (detached)
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Commit message: "Merge branch 'main' into fix-two-tower-model-load-context-variable"
 > git rev-list --no-walk 689bdccc1ec3055ede7e4ddd7d3e4429936664bb # timeout=10
[merlin_models] $ /bin/bash /tmp/jenkins11359497214191255540.sh
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
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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: 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+56.g904d9116.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+56.g904d9116,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='904443055'
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-g0fsf3b2
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/core.git /tmp/pip-req-build-g0fsf3b2
  Resolved https://github.com/NVIDIA-Merlin/core.git to commit 04ff5225cee6af90b6b08070493677ac53b96836
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: tensorflow-metadata>=1.2.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+16.g04ff522) (1.10.0)
Requirement already satisfied: distributed>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+16.g04ff522) (2022.3.0)
Requirement already satisfied: pandas<1.4.0dev0,>=1.2.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+16.g04ff522) (1.3.5)
Requirement already satisfied: dask>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+16.g04ff522) (2022.3.0)
Requirement already satisfied: pyarrow>=5.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+16.g04ff522) (7.0.0)
Requirement already satisfied: protobuf>=3.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+16.g04ff522) (3.19.5)
Requirement already satisfied: numba>=0.54 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+16.g04ff522) (0.55.1)
Requirement already satisfied: packaging in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+16.g04ff522) (21.3)
Requirement already satisfied: fsspec==2022.5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+16.g04ff522) (2022.5.0)
Requirement already satisfied: tqdm>=4.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+16.g04ff522) (4.64.1)
Requirement already satisfied: betterproto<2.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+16.g04ff522) (1.2.5)
Requirement already satisfied: grpclib in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core==0.8.0+16.g04ff522) (0.4.3)
Requirement already satisfied: stringcase in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core==0.8.0+16.g04ff522) (1.2.0)
Requirement already satisfied: toolz>=0.8.2 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (0.12.0)
Requirement already satisfied: pyyaml>=5.3.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/PyYAML-5.4.1-py3.8-linux-x86_64.egg (from dask>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (5.4.1)
Requirement already satisfied: partd>=0.3.10 in /var/jenkins_home/.local/lib/python3.8/site-packages/partd-1.2.0-py3.8.egg (from dask>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (1.2.0)
Requirement already satisfied: cloudpickle>=1.1.1 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (2.2.0)
Requirement already satisfied: psutil>=5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/psutil-5.8.0-py3.8-linux-x86_64.egg (from distributed>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (5.8.0)
Requirement already satisfied: msgpack>=0.6.0 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (1.0.4)
Requirement already satisfied: click>=6.6 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (8.1.3)
Requirement already satisfied: jinja2 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (3.1.2)
Requirement already satisfied: sortedcontainers!=2.0.0,!=2.0.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/sortedcontainers-2.4.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (2.4.0)
Requirement already satisfied: tblib>=1.6.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/tblib-1.7.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (1.7.0)
Requirement already satisfied: tornado>=6.0.3 in ./.tox/py38-gpu/lib/python3.8/site-packages (from distributed>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (6.2)
Requirement already satisfied: zict>=0.1.3 in /var/jenkins_home/.local/lib/python3.8/site-packages/zict-2.0.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (2.0.0)
Requirement already satisfied: llvmlite<0.39,>=0.38.0rc1 in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+16.g04ff522) (0.38.1)
Requirement already satisfied: setuptools in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+16.g04ff522) (65.5.1)
Requirement already satisfied: numpy<1.22,>=1.18 in /var/jenkins_home/.local/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+16.g04ff522) (1.20.3)
Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in /usr/local/lib/python3.8/dist-packages (from packaging->merlin-core==0.8.0+16.g04ff522) (3.0.9)
Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+16.g04ff522) (2.8.2)
Requirement already satisfied: pytz>=2017.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+16.g04ff522) (2022.2.1)
Requirement already satisfied: absl-py<2.0.0,>=0.9 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core==0.8.0+16.g04ff522) (1.2.0)
Requirement already satisfied: googleapis-common-protos<2,>=1.52.0 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core==0.8.0+16.g04ff522) (1.52.0)
Requirement already satisfied: locket in /var/jenkins_home/.local/lib/python3.8/site-packages/locket-0.2.1-py3.8.egg (from partd>=0.3.10->dask>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (0.2.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.7.3->pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+16.g04ff522) (1.15.0)
Requirement already satisfied: heapdict in /var/jenkins_home/.local/lib/python3.8/site-packages/HeapDict-1.0.1-py3.8.egg (from zict>=0.1.3->distributed>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (1.0.1)
Requirement already satisfied: h2<5,>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core==0.8.0+16.g04ff522) (4.1.0)
Requirement already satisfied: multidict in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core==0.8.0+16.g04ff522) (6.0.2)
Requirement already satisfied: MarkupSafe>=2.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from jinja2->distributed>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (2.0.1)
Requirement already satisfied: hyperframe<7,>=6.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core==0.8.0+16.g04ff522) (6.0.1)
Requirement already satisfied: hpack<5,>=4.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core==0.8.0+16.g04ff522) (4.0.0)
Building wheels for collected packages: merlin-core
  Building wheel for merlin-core (pyproject.toml): started
  Building wheel for merlin-core (pyproject.toml): finished with status 'done'
  Created wheel for merlin-core: filename=merlin_core-0.8.0+16.g04ff522-py3-none-any.whl size=118833 sha256=76a050813c065eb81f933f5937e84f0b412c7a171c8ef15fba1bb1e483593c7f
  Stored in directory: /tmp/pip-ephem-wheel-cache-8p37k_al/wheels/c8/38/16/a6968787eafcec5fa772148af8408b089562f71af0752e8e84
Successfully built merlin-core
Installing collected packages: merlin-core
  Attempting uninstall: merlin-core
    Found existing installation: merlin-core 0.3.0+12.g78ecddd
    Not uninstalling merlin-core at /var/jenkins_home/.local/lib/python3.8/site-packages, outside environment /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
    Can't uninstall 'merlin-core'. No files were found to uninstall.
Successfully installed merlin-core-0.8.0+16.g04ff522
py38-gpu run-test: commands[1] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/nvtabular.git
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Collecting git+https://github.com/NVIDIA-Merlin/nvtabular.git
  Cloning https://github.com/NVIDIA-Merlin/nvtabular.git to /tmp/pip-req-build-lqftvmrj
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/nvtabular.git /tmp/pip-req-build-lqftvmrj
  Resolved https://github.com/NVIDIA-Merlin/nvtabular.git to commit e5b7351deb9e4885c4038aa0bbc9f146d8477a0e
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Collecting merlin-dataloader>=0.0.2
  Downloading merlin-dataloader-0.0.2.tar.gz (44 kB)
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Building wheels for collected packages: nvtabular, merlin-dataloader
  Building wheel for nvtabular (pyproject.toml): started
  Building wheel for nvtabular (pyproject.toml): finished with status 'done'
  Created wheel for nvtabular: filename=nvtabular-1.6.0+6.ge5b7351d-cp38-cp38-linux_x86_64.whl size=257597 sha256=b2cfaa013e3dd8e9b16d9dbb006dc1a394ab44ad634f31e8379251067da4b969
  Stored in directory: /tmp/pip-ephem-wheel-cache-a0tpw9d6/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=d3f6415105553052ab7082a030d90f1997085400114e571a7d9b347420bf3f29
  Stored in directory: /tmp/pip-ephem-wheel-cache-a0tpw9d6/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
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tests/unit/tf/metrics/test_metrics_popularity.py .....                   [ 44%]

tests/unit/tf/metrics/test_metrics_topk.py .........................     [ 46%]

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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%]

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tests/unit/torch/tabular/test_aggregation.py ........                    [ 92%]

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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_accelerate_training_by_lazyadam _________________
tb = <testbook.client.TestbookNotebookClient object at 0x7f8f100c8ac0>
@testbook(
    REPO_ROOT / p,
    timeout=180,
    execute=False,
)
@pytest.mark.skipif(not HAS_GPU, reason="No GPU available")
def test_usecase_accelerate_training_by_lazyadam(tb):
    tb.inject(
        """
        import os
        os.environ["NUM_ROWS"] = "1000"
        """
    )


  tb.execute()


tests/unit/tf/examples/test_usecase_accelerate_training_by_lazyadam.py:25:

../../../.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 0x7f8f100c8ac0>

cell = {'cell_type': 'code', 'execution_count': 7, 'id': '0500ad25-29e0-40c8-85bc-6e3864107c6a', 'metadata': {'execution': {'...e_train_function_3861]']}], 'source': 'model1.compile(optimizer="adam")\nmodel1.fit(train, batch_size=1024, epochs=1)'}

cell_index = 12

exec_reply = {'buffers': [], 'content': {'ename': 'ResourceExhaustedError', 'engine_info': {'engine_id': -1, 'engine_uuid': 'b6949b...e, 'engine': 'b6949b7f-40c0-487c-ad33-68a3ef7e3ea6', 'started': '2022-11-21T15:20:55.167521Z', '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           model1.compile(optimizer="adam")

E           model1.fit(train, batch_size=1024, epochs=1)

E           ------------------

E

E           �[0;31m---------------------------------------------------------------------------�[0m

E           �[0;31mResourceExhaustedError�[0m                    Traceback (most recent call last)

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E           �[1;32m    907�[0m     �[38;5;28mself�[39m�[38;5;241m.�[39m_reset_compile_cache()

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E           File �[0;32m~/.local/lib/python3.8/site-packages/keras/utils/traceback_utils.py:67�[0m, in �[0;36mfilter_traceback..error_handler�[0;34m(*args, **kwargs)�[0m

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E           �[1;32m     68�[0m �[38;5;28;01mfinally�[39;00m:

E           �[1;32m     69�[0m   �[38;5;28;01mdel�[39;00m filtered_tb

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E           File �[0;32m~/.local/lib/python3.8/site-packages/tensorflow/python/eager/execute.py:54�[0m, in �[0;36mquick_execute�[0;34m(op_name, num_outputs, inputs, attrs, ctx, name)�[0m

E           �[1;32m     52�[0m �[38;5;28;01mtry�[39;00m:

E           �[1;32m     53�[0m   ctx�[38;5;241m.�[39mensure_initialized()

E           �[0;32m---> 54�[0m   tensors �[38;5;241m=�[39m pywrap_tfe�[38;5;241m.�[39mTFE_Py_Execute(ctx�[38;5;241m.�[39m_handle, device_name, op_name,

E           �[1;32m     55�[0m                                       inputs, attrs, num_outputs)

E           �[1;32m     56�[0m �[38;5;28;01mexcept�[39;00m core�[38;5;241m.�[39m_NotOkStatusException �[38;5;28;01mas�[39;00m e:

E           �[1;32m     57�[0m   �[38;5;28;01mif�[39;00m name �[38;5;129;01mis�[39;00m �[38;5;129;01mnot�[39;00m �[38;5;28;01mNone�[39;00m:

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E           �[0;31mResourceExhaustedError�[0m: Graph execution error:

E

E           Detected at node 'Adam/Adam/update_8/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_28641/3741080137.py", line 2, in 

E                 model1.fit(train, 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_8/mul_1'

E           Detected at node 'Adam/Adam/update_8/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_28641/3741080137.py", line 2, in 

E                 model1.fit(train, 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_8/mul_1'

E           2 root error(s) found.

E             (0) RESOURCE_EXHAUSTED:  failed to allocate memory

E           	 [[{{node Adam/Adam/update_8/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_8/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_3861]

E           ResourceExhaustedError: Graph execution error:

E

E           Detected at node 'Adam/Adam/update_8/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_28641/3741080137.py", line 2, in 

E                 model1.fit(train, 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_8/mul_1'

E           Detected at node 'Adam/Adam/update_8/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_28641/3741080137.py", line 2, in 

E                 model1.fit(train, 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_8/mul_1'

E           2 root error(s) found.

E             (0) RESOURCE_EXHAUSTED:  failed to allocate memory

E           	 [[{{node Adam/Adam/update_8/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_8/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_3861]
../../../.local/lib/python3.8/site-packages/nbclient/client.py:862: CellExecutionError

----------------------------- Captured stderr call -----------------------------

2022-11-21 15:20:48.080040: 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.

2022-11-21 15:20:52.309357: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 0

2022-11-21 15:20:52.309460: 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

2022-11-21 15:20:52.310165: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 1

2022-11-21 15:20:52.310227: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:1 with 13851 MB memory:  -> device: 1, name: Tesla P100-DGXS-16GB, pci bus id: 0000:08:00.0, compute capability: 6.0

2022-11-21 15:20:52.310834: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 2

2022-11-21 15:20:52.310885: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:2 with 13851 MB memory:  -> device: 2, name: Tesla P100-DGXS-16GB, pci bus id: 0000:0e:00.0, compute capability: 6.0

2022-11-21 15:20:52.311480: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 3

2022-11-21 15:20:52.311530: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:3 with 13851 MB memory:  -> device: 3, name: Tesla P100-DGXS-16GB, pci bus id: 0000:0f:00.0, compute capability: 6.0

2022-11-21 15:21:09.561288: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:288] gpu_async_0 cuMemAllocAsync failed to allocate 56589504 bytes: CUDA error: out of memory (CUDA_ERROR_OUT_OF_MEMORY)

Reported by CUDA: Free memory/Total memory: 28901376/17069309952

2022-11-21 15:21:09.561343: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:293] Stats: Limit:                      8534360064

InUse:                      4377834944

MaxInUse:                   4377834944

NumAllocs:                         255

MaxAllocSize:               1083564064

Reserved:                            0

PeakReserved:                        0

LargestFreeBlock:                    0
2022-11-21 15:21:09.561366: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:56] Histogram of current allocation: (allocation_size_in_bytes, nb_allocation_of_that_sizes), ...;

2022-11-21 15:21:09.561376: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1, 4

2022-11-21 15:21:09.561384: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 4, 34

2022-11-21 15:21:09.561392: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 8, 8

2022-11-21 15:21:09.561399: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 40, 2

2022-11-21 15:21:09.561406: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 128, 8

2022-11-21 15:21:09.561413: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 160, 10

2022-11-21 15:21:09.561420: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 192, 4

2022-11-21 15:21:09.561427: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 256, 6

2022-11-21 15:21:09.561434: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 288, 5

2022-11-21 15:21:09.561441: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 480, 5

2022-11-21 15:21:09.561450: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1028, 1

2022-11-21 15:21:09.561457: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 3168, 3

2022-11-21 15:21:09.561488: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 61440, 3

2022-11-21 15:21:09.561497: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 65536, 3

2022-11-21 15:21:09.561505: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 204800, 1

2022-11-21 15:21:09.561512: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 584352, 4

2022-11-21 15:21:09.561519: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 823872, 3

2022-11-21 15:21:09.561526: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 4324736, 5

2022-11-21 15:21:09.561533: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 7426048, 5

2022-11-21 15:21:09.561540: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 15401440, 5

2022-11-21 15:21:09.561547: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 18678720, 4

2022-11-21 15:21:09.561555: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 39970560, 5

2022-11-21 15:21:09.561562: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 56589504, 3

2022-11-21 15:21:09.561569: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 135407776, 4

2022-11-21 15:21:09.561576: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1083564064, 3

2022-11-21 15:21:09.561601: W tensorflow/core/framework/op_kernel.cc:1733] RESOURCE_EXHAUSTED: failed to allocate memory

2022-11-21 15:21:09.562282: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:288] gpu_async_0 cuMemAllocAsync failed to allocate 56589504 bytes: CUDA error: out of memory (CUDA_ERROR_OUT_OF_MEMORY)

Reported by CUDA: Free memory/Total memory: 28901376/17069309952

2022-11-21 15:21:09.562304: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:293] Stats: Limit:                      8534360064

InUse:                      4378419296

MaxInUse:                   4378419296

NumAllocs:                         256

MaxAllocSize:               1083564064

Reserved:                            0

PeakReserved:                        0

LargestFreeBlock:                    0
2022-11-21 15:21:09.562320: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:56] Histogram of current allocation: (allocation_size_in_bytes, nb_allocation_of_that_sizes), ...;

2022-11-21 15:21:09.562329: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1, 4

2022-11-21 15:21:09.562336: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 4, 34

2022-11-21 15:21:09.562343: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 8, 8

2022-11-21 15:21:09.562350: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 40, 2

2022-11-21 15:21:09.562357: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 128, 8

2022-11-21 15:21:09.562365: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 160, 10

2022-11-21 15:21:09.562372: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 192, 4

2022-11-21 15:21:09.562379: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 256, 6

2022-11-21 15:21:09.562386: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 288, 5

2022-11-21 15:21:09.562393: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 480, 5

2022-11-21 15:21:09.562400: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1028, 1

2022-11-21 15:21:09.562407: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 3168, 3

2022-11-21 15:21:09.562414: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 61440, 3

2022-11-21 15:21:09.562421: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 65536, 3

2022-11-21 15:21:09.562429: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 204800, 1

2022-11-21 15:21:09.562450: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 584352, 5

2022-11-21 15:21:09.562458: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 823872, 3

2022-11-21 15:21:09.562466: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 4324736, 5

2022-11-21 15:21:09.562473: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 7426048, 5

2022-11-21 15:21:09.562480: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 15401440, 5

2022-11-21 15:21:09.562487: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 18678720, 4

2022-11-21 15:21:09.562494: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 39970560, 5

2022-11-21 15:21:09.562501: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 56589504, 3

2022-11-21 15:21:09.562509: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 135407776, 4

2022-11-21 15:21:09.562516: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1083564064, 3

2022-11-21 15:21:09.562526: W tensorflow/core/framework/op_kernel.cc:1733] RESOURCE_EXHAUSTED: failed to allocate memory

2022-11-21 15:21:09.563103: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:288] gpu_async_0 cuMemAllocAsync failed to allocate 18678720 bytes: CUDA error: out of memory (CUDA_ERROR_OUT_OF_MEMORY)

Reported by CUDA: Free memory/Total memory: 28901376/17069309952

2022-11-21 15:21:09.563122: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:293] Stats: Limit:                      8534360064

InUse:                      4380067168

MaxInUse:                   4380067168

NumAllocs:                         259

MaxAllocSize:               1083564064

Reserved:                            0

PeakReserved:                        0

LargestFreeBlock:                    0
2022-11-21 15:21:09.563137: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:56] Histogram of current allocation: (allocation_size_in_bytes, nb_allocation_of_that_sizes), ...;

2022-11-21 15:21:09.563146: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1, 4

2022-11-21 15:21:09.563153: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 4, 34

2022-11-21 15:21:09.563160: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 8, 8

2022-11-21 15:21:09.563167: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 40, 2

2022-11-21 15:21:09.563174: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 128, 9

2022-11-21 15:21:09.563182: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 160, 10

2022-11-21 15:21:09.563189: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 192, 4

2022-11-21 15:21:09.563196: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 256, 6

2022-11-21 15:21:09.563203: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 288, 5

2022-11-21 15:21:09.563210: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 480, 5

2022-11-21 15:21:09.563217: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1028, 1

2022-11-21 15:21:09.563224: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 3168, 3

2022-11-21 15:21:09.563231: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 61440, 3

2022-11-21 15:21:09.563238: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 65536, 3

2022-11-21 15:21:09.563245: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 204800, 1

2022-11-21 15:21:09.563252: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 584352, 5

2022-11-21 15:21:09.563259: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 823872, 5

2022-11-21 15:21:09.563278: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 4324736, 5

2022-11-21 15:21:09.563286: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 7426048, 5

2022-11-21 15:21:09.563293: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 15401440, 5

2022-11-21 15:21:09.563300: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 18678720, 4

2022-11-21 15:21:09.563307: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 39970560, 5

2022-11-21 15:21:09.563314: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 56589504, 3

2022-11-21 15:21:09.563321: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 135407776, 4

2022-11-21 15:21:09.563328: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1083564064, 3

2022-11-21 15:21:09.563338: W tensorflow/core/framework/op_kernel.cc:1733] RESOURCE_EXHAUSTED: failed to allocate memory

2022-11-21 15:21:09.563881: 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: 28901376/17069309952

2022-11-21 15:21:09.563898: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:293] Stats: Limit:                      8534360064

InUse:                      4380067168

MaxInUse:                   4380067168

NumAllocs:                         259

MaxAllocSize:               1083564064

Reserved:                            0

PeakReserved:                        0

LargestFreeBlock:                    0
2022-11-21 15:21:09.563911: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:56] Histogram of current allocation: (allocation_size_in_bytes, nb_allocation_of_that_sizes), ...;

2022-11-21 15:21:09.563919: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1, 4

2022-11-21 15:21:09.563927: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 4, 34

2022-11-21 15:21:09.563934: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 8, 8

2022-11-21 15:21:09.563941: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 40, 2

2022-11-21 15:21:09.563948: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 128, 9

2022-11-21 15:21:09.563955: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 160, 10

2022-11-21 15:21:09.563962: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 192, 4

2022-11-21 15:21:09.563969: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 256, 6

2022-11-21 15:21:09.563976: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 288, 5

2022-11-21 15:21:09.563983: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 480, 5

2022-11-21 15:21:09.563990: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1028, 1

2022-11-21 15:21:09.563997: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 3168, 3

2022-11-21 15:21:09.564004: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 61440, 3

2022-11-21 15:21:09.564011: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 65536, 3

2022-11-21 15:21:09.564018: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 204800, 1

2022-11-21 15:21:09.564038: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 584352, 5

2022-11-21 15:21:09.564050: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 823872, 5

2022-11-21 15:21:09.564057: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 4324736, 5

2022-11-21 15:21:09.564064: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 7426048, 5

2022-11-21 15:21:09.564071: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 15401440, 5

2022-11-21 15:21:09.564089: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 18678720, 4

2022-11-21 15:21:09.564097: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 39970560, 5

2022-11-21 15:21:09.564104: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 56589504, 3

2022-11-21 15:21:09.564111: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 135407776, 4

2022-11-21 15:21:09.564118: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1083564064, 3

2022-11-21 15:21:09.564128: W tensorflow/core/framework/op_kernel.cc:1733] RESOURCE_EXHAUSTED: failed to allocate memory

2022-11-21 15:21:09.564698: 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: 28901376/17069309952

2022-11-21 15:21:09.564717: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:293] Stats: Limit:                      8534360064

InUse:                      4380070464

MaxInUse:                   4380070464

NumAllocs:                         261

MaxAllocSize:               1083564064

Reserved:                            0

PeakReserved:                        0

LargestFreeBlock:                    0
2022-11-21 15:21:09.564734: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:56] Histogram of current allocation: (allocation_size_in_bytes, nb_allocation_of_that_sizes), ...;

2022-11-21 15:21:09.564742: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1, 4

2022-11-21 15:21:09.564749: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 4, 34

2022-11-21 15:21:09.564756: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 8, 8

2022-11-21 15:21:09.564763: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 40, 2

2022-11-21 15:21:09.564770: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 128, 10

2022-11-21 15:21:09.564777: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 160, 10

2022-11-21 15:21:09.564784: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 192, 4

2022-11-21 15:21:09.564791: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 256, 6

2022-11-21 15:21:09.564798: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 288, 5

2022-11-21 15:21:09.564805: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 480, 5

2022-11-21 15:21:09.564812: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1028, 1

2022-11-21 15:21:09.564819: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 3168, 4

2022-11-21 15:21:09.564826: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 61440, 3

2022-11-21 15:21:09.564833: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 65536, 3

2022-11-21 15:21:09.564841: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 204800, 1

2022-11-21 15:21:09.564848: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 584352, 5

2022-11-21 15:21:09.564855: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 823872, 5

2022-11-21 15:21:09.564862: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 4324736, 5

2022-11-21 15:21:09.564869: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 7426048, 5

2022-11-21 15:21:09.564876: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 15401440, 5

2022-11-21 15:21:09.564883: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 18678720, 4

2022-11-21 15:21:09.564890: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 39970560, 5

2022-11-21 15:21:09.564897: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 56589504, 3

2022-11-21 15:21:09.564915: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 135407776, 4

2022-11-21 15:21:09.564923: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1083564064, 3

2022-11-21 15:21:09.564934: W tensorflow/core/framework/op_kernel.cc:1733] RESOURCE_EXHAUSTED: failed to allocate memory

2022-11-21 15:21:09.565491: 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: 28901376/17069309952

2022-11-21 15:21:09.565509: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:293] Stats: Limit:                      8534360064

InUse:                      4380073632

MaxInUse:                   4380073632

NumAllocs:                         262

MaxAllocSize:               1083564064

Reserved:                            0

PeakReserved:                        0

LargestFreeBlock:                    0
2022-11-21 15:21:09.565524: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:56] Histogram of current allocation: (allocation_size_in_bytes, nb_allocation_of_that_sizes), ...;

2022-11-21 15:21:09.565532: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1, 4

2022-11-21 15:21:09.565539: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 4, 34

2022-11-21 15:21:09.565546: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 8, 8

2022-11-21 15:21:09.565553: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 40, 2

2022-11-21 15:21:09.565560: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 128, 10

2022-11-21 15:21:09.565567: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 160, 10

2022-11-21 15:21:09.565574: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 192, 4

2022-11-21 15:21:09.565581: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 256, 6

2022-11-21 15:21:09.565588: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 288, 5

2022-11-21 15:21:09.565595: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 480, 5

2022-11-21 15:21:09.565602: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1028, 1

2022-11-21 15:21:09.565609: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 3168, 5

2022-11-21 15:21:09.565616: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 61440, 3

2022-11-21 15:21:09.565623: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 65536, 3

2022-11-21 15:21:09.565630: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 204800, 1

2022-11-21 15:21:09.565637: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 584352, 5

2022-11-21 15:21:09.565644: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 823872, 5

2022-11-21 15:21:09.565651: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 4324736, 5

2022-11-21 15:21:09.565658: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 7426048, 5

2022-11-21 15:21:09.565665: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 15401440, 5

2022-11-21 15:21:09.565672: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 18678720, 4

2022-11-21 15:21:09.565679: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 39970560, 5

2022-11-21 15:21:09.565686: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 56589504, 3

2022-11-21 15:21:09.565693: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 135407776, 4

2022-11-21 15:21:09.565700: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1083564064, 3

2022-11-21 15:21:09.565720: 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'

_______________ test_usecase_incremental_training_layer_freezing _______________
tb = <testbook.client.TestbookNotebookClient object at 0x7f8f100503d0>
@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 0x7f8f100503d0>

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': '8c34c1...e, 'engine': '8c34c13b-5dd7-4bef-9370-a8ba447c988a', 'started': '2022-11-21T15:22:13.019740Z', 'status': 'error'}, ...}
async def _check_raise_for_error(
    self, cell: NotebookNode, cell_index: int, exec_reply: t.Optional[t.Dict]
) -> None:

    if exec_reply is None:
        return None

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

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


      raise CellExecutionError.from_cell_and_msg(cell, exec_reply_content)


E           nbclient.exceptions.CellExecutionError: An error occurred while executing the following cell:

E           ------------------

E           model.compile(optimizer=tf.keras.optimizers.Adam(learning_rate=0.01))

E           model.fit(day_1, batch_size=1024, epochs=1)

E           ------------------

E

E           �[0;31m---------------------------------------------------------------------------�[0m

E           �[0;31mResourceExhaustedError�[0m                    Traceback (most recent call last)

E           Cell �[0;32mIn [8], line 2�[0m

E           �[1;32m      1�[0m model�[38;5;241m.�[39mcompile(optimizer�[38;5;241m=�[39mtf�[38;5;241m.�[39mkeras�[38;5;241m.�[39moptimizers�[38;5;241m.�[39mAdam(learning_rate�[38;5;241m=�[39m�[38;5;241m0.01�[39m))

E           �[0;32m----> 2�[0m �[43mmodel�[49m�[38;5;241;43m.�[39;49m�[43mfit�[49m�[43m(�[49m�[43mday_1�[49m�[43m,�[49m�[43m �[49m�[43mbatch_size�[49m�[38;5;241;43m=�[39;49m�[38;5;241;43m1024�[39;49m�[43m,�[49m�[43m �[49m�[43mepochs�[49m�[38;5;241;43m=�[39;49m�[38;5;241;43m1�[39;49m�[43m)�[49m

E

E           File �[0;32m~/workspace/merlin_models/models/merlin/models/tf/models/base.py:910�[0m, in �[0;36mBaseModel.fit�[0;34m(self, x, y, batch_size, epochs, verbose, callbacks, validation_split, validation_data, shuffle, class_weight, sample_weight, initial_epoch, steps_per_epoch, validation_steps, validation_batch_size, validation_freq, max_queue_size, workers, use_multiprocessing, train_metrics_steps, pre, **kwargs)�[0m

E           �[1;32m    907�[0m     �[38;5;28mself�[39m�[38;5;241m.�[39m_reset_compile_cache()

E           �[1;32m    908�[0m     �[38;5;28mself�[39m�[38;5;241m.�[39mtrain_pre �[38;5;241m=�[39m pre

E           �[0;32m--> 910�[0m out �[38;5;241m=�[39m �[38;5;28;43msuper�[39;49m�[43m(�[49m�[43m)�[49m�[38;5;241;43m.�[39;49m�[43mfit�[49m�[43m(�[49m�[38;5;241;43m�[39;49m�[38;5;241;43m�[39;49m�[43mfit_kwargs�[49m�[43m)�[49m

E           �[1;32m    912�[0m �[38;5;28;01mif�[39;00m pre:

E           �[1;32m    913�[0m     �[38;5;28;01mdel�[39;00m �[38;5;28mself�[39m�[38;5;241m.�[39mtrain_pre

E

E           File �[0;32m~/.local/lib/python3.8/site-packages/keras/utils/traceback_utils.py:67�[0m, in �[0;36mfilter_traceback..error_handler�[0;34m(*args, **kwargs)�[0m

E           �[1;32m     65�[0m �[38;5;28;01mexcept�[39;00m �[38;5;167;01mException�[39;00m �[38;5;28;01mas�[39;00m e:  �[38;5;66;03m# pylint: disable=broad-except�[39;00m

E           �[1;32m     66�[0m   filtered_tb �[38;5;241m=�[39m process_traceback_frames(e�[38;5;241m.�[39m__traceback_)

E           �[0;32m---> 67�[0m   �[38;5;28;01mraise�[39;00m e�[38;5;241m.�[39mwith_traceback(filtered_tb) �[38;5;28;01mfrom�[39;00m �[38;5;28mNone�[39m

E           �[1;32m     68�[0m �[38;5;28;01mfinally�[39;00m:

E           �[1;32m     69�[0m   �[38;5;28;01mdel�[39;00m filtered_tb

E

E           File �[0;32m~/.local/lib/python3.8/site-packages/tensorflow/python/framework/func_graph.py:1127�[0m, in �[0;36mfunc_graph_from_py_func..autograph_handler�[0;34m(*args, **kwargs)�[0m

E           �[1;32m   1125�[0m �[38;5;28;01mexcept�[39;00m �[38;5;167;01mException�[39;00m �[38;5;28;01mas�[39;00m e:  �[38;5;66;03m# pylint:disable=broad-except�[39;00m

E           �[1;32m   1126�[0m   �[38;5;28;01mif�[39;00m �[38;5;28mhasattr�[39m(e, �[38;5;124m"�[39m�[38;5;124mag_error_metadata�[39m�[38;5;124m"�[39m):

E           �[0;32m-> 1127�[0m     �[38;5;28;01mraise�[39;00m e�[38;5;241m.�[39mag_error_metadata�[38;5;241m.�[39mto_exception(e)

E           �[1;32m   1128�[0m   �[38;5;28;01melse�[39;00m:

E           �[1;32m   1129�[0m     �[38;5;28;01mraise�[39;00m

E

E           �[0;31mResourceExhaustedError�[0m: in user code:

E

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 646, in apply_gradients

E                   self._create_all_weights(var_list)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 860, in _create_all_weights

E                   self._create_slots(var_list)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/adam.py", line 124, in _create_slots

E                   self.add_slot(var, 'v')

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 946, in add_slot

E                   weight = tf.Variable(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/initializers/initializers_v2.py", line 152, in call

E                   return tf.zeros(shape, dtype)

E

E               ResourceExhaustedError: OOM when allocating tensor with shape[604499,56] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator gpu_async_0 [Op:Fill]

E

E           ResourceExhaustedError: in user code:

E

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 646, in apply_gradients

E                   self._create_all_weights(var_list)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 860, in _create_all_weights

E                   self._create_slots(var_list)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/adam.py", line 124, in _create_slots

E                   self.add_slot(var, 'v')

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 946, in add_slot

E                   weight = tf.Variable(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/initializers/initializers_v2.py", line 152, in call

E                   return tf.zeros(shape, dtype)

E

E               ResourceExhaustedError: OOM when allocating tensor with shape[604499,56] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator gpu_async_0 [Op:Fill]
../../../.local/lib/python3.8/site-packages/nbclient/client.py:862: CellExecutionError

----------------------------- Captured stderr call -----------------------------

2022-11-21 15:22:05.948330: 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.

2022-11-21 15:22:10.105754: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 0

2022-11-21 15:22:10.105855: 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

2022-11-21 15:22:10.106607: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 1

2022-11-21 15:22:10.106667: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:1 with 13851 MB memory:  -> device: 1, name: Tesla P100-DGXS-16GB, pci bus id: 0000:08:00.0, compute capability: 6.0

2022-11-21 15:22:10.107316: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 2

2022-11-21 15:22:10.107364: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:2 with 13851 MB memory:  -> device: 2, name: Tesla P100-DGXS-16GB, pci bus id: 0000:0e:00.0, compute capability: 6.0

2022-11-21 15:22:10.108004: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 3

2022-11-21 15:22:10.108063: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:3 with 13851 MB memory:  -> device: 3, name: Tesla P100-DGXS-16GB, pci bus id: 0000:0f:00.0, compute capability: 6.0

2022-11-21 15:22:22.052018: 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: 32047104/17069309952

2022-11-21 15:22:22.052071: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:293] Stats: Limit:                      8534360064

InUse:                      3953864374

MaxInUse:                   3953864374

NumAllocs:                         235

MaxAllocSize:               1083564064

Reserved:                            0

PeakReserved:                        0

LargestFreeBlock:                    0
2022-11-21 15:22:22.052088: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:56] Histogram of current allocation: (allocation_size_in_bytes, nb_allocation_of_that_sizes), ...;

2022-11-21 15:22:22.052097: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1, 2

2022-11-21 15:22:22.052104: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 4, 26

2022-11-21 15:22:22.052110: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 8, 3

2022-11-21 15:22:22.052116: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 128, 6

2022-11-21 15:22:22.052122: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 160, 6

2022-11-21 15:22:22.052127: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 192, 3

2022-11-21 15:22:22.052133: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 256, 5

2022-11-21 15:22:22.052139: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 288, 3

2022-11-21 15:22:22.052145: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 480, 3

2022-11-21 15:22:22.052151: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 512, 5

2022-11-21 15:22:22.052157: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1028, 1

2022-11-21 15:22:22.052163: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 3168, 3

2022-11-21 15:22:22.052191: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 32768, 5

2022-11-21 15:22:22.052199: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 60720, 1

2022-11-21 15:22:22.052206: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 84480, 1

2022-11-21 15:22:22.052212: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 122880, 3

2022-11-21 15:22:22.052217: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 131072, 2

2022-11-21 15:22:22.052223: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 584352, 3

2022-11-21 15:22:22.052229: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 823872, 3

2022-11-21 15:22:22.052235: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 4324736, 3

2022-11-21 15:22:22.052241: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 7426048, 3

2022-11-21 15:22:22.052247: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 15401440, 3

2022-11-21 15:22:22.052253: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 18678720, 3

2022-11-21 15:22:22.052259: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 39970560, 3

2022-11-21 15:22:22.052265: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 56589504, 3

2022-11-21 15:22:22.052270: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 135407776, 2

2022-11-21 15:22:22.052276: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1083564064, 3

2022-11-21 15:22:22.052309: W tensorflow/core/framework/op_kernel.cc:1745] OP_REQUIRES failed at constant_op.cc:175 : RESOURCE_EXHAUSTED: OOM when allocating tensor with shape[604499,56] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator gpu_async_0

Error in atexit._run_exitfuncs:

Traceback (most recent call last):

File "/usr/lib/python3.8/logging/init.py", line 2127, in shutdown

h.close()

File "/usr/local/lib/python3.8/dist-packages/absl/logging/init.py", line 934, in close

self.stream.close()

File "/usr/local/lib/python3.8/dist-packages/ipykernel/iostream.py", line 438, in close

self.watch_fd_thread.join()

AttributeError: 'OutStream' object has no attribute 'watch_fd_thread'

=============================== warnings summary ===============================

../../../../../usr/lib/python3/dist-packages/requests/init.py:89

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

warnings.warn("urllib3 ({}) or chardet ({}) doesn't match a supported "
../../../.local/lib/python3.8/site-packages/flatbuffers/compat.py:19

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

import imp
../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36

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

'nearest': pil_image.NEAREST,
../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37

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

'bilinear': pil_image.BILINEAR,
../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38

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

'bicubic': pil_image.BICUBIC,
../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39

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

'hamming': pil_image.HAMMING,
../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40

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

'box': pil_image.BOX,
../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41

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

'lanczos': pil_image.LANCZOS,
tests/unit/datasets/test_advertising.py: 1 warning

tests/unit/datasets/test_ecommerce.py: 3 warnings

tests/unit/datasets/test_entertainment.py: 4 warnings

tests/unit/datasets/test_social.py: 1 warning

tests/unit/datasets/test_synthetic.py: 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: 121 warnings

tests/unit/tf/outputs/test_base.py: 6 warnings

tests/unit/tf/outputs/test_classification.py: 6 warnings

tests/unit/tf/outputs/test_contrastive.py: 19 warnings

tests/unit/tf/outputs/test_regression.py: 2 warnings

tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings

tests/unit/tf/prediction_tasks/test_retrieval.py: 1 warning

tests/unit/tf/transformers/test_block.py: 16 warnings

tests/unit/tf/transforms/test_bias.py: 2 warnings

tests/unit/tf/transforms/test_features.py: 10 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings

tests/unit/tf/transforms/test_noise.py: 1 warning

tests/unit/tf/transforms/test_sequence.py: 15 warnings

tests/unit/tf/utils/test_batch.py: 9 warnings

tests/unit/tf/utils/test_dataset.py: 2 warnings

tests/unit/torch/block/test_base.py: 4 warnings

tests/unit/torch/block/test_mlp.py: 1 warning

tests/unit/torch/features/test_continuous.py: 1 warning

tests/unit/torch/features/test_embedding.py: 4 warnings

tests/unit/torch/features/test_tabular.py: 4 warnings

tests/unit/torch/model/test_head.py: 12 warnings

tests/unit/torch/model/test_model.py: 2 warnings

tests/unit/torch/tabular/test_aggregation.py: 6 warnings

tests/unit/torch/tabular/test_transformations.py: 3 warnings

tests/unit/xgb/test_xgboost.py: 18 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.ITEM_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.ITEM: 'item'>, <Tags.ID: 'id'>].

warnings.warn(
tests/unit/datasets/test_ecommerce.py: 3 warnings

tests/unit/datasets/test_entertainment.py: 4 warnings

tests/unit/datasets/test_social.py: 1 warning

tests/unit/datasets/test_synthetic.py: 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: 87 warnings

tests/unit/tf/outputs/test_base.py: 6 warnings

tests/unit/tf/outputs/test_classification.py: 6 warnings

tests/unit/tf/outputs/test_contrastive.py: 19 warnings

tests/unit/tf/outputs/test_regression.py: 2 warnings

tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings

tests/unit/tf/transformers/test_block.py: 10 warnings

tests/unit/tf/transforms/test_features.py: 10 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings

tests/unit/tf/transforms/test_sequence.py: 15 warnings

tests/unit/tf/utils/test_batch.py: 7 warnings

tests/unit/tf/utils/test_dataset.py: 2 warnings

tests/unit/torch/block/test_base.py: 4 warnings

tests/unit/torch/block/test_mlp.py: 1 warning

tests/unit/torch/features/test_continuous.py: 1 warning

tests/unit/torch/features/test_embedding.py: 4 warnings

tests/unit/torch/features/test_tabular.py: 4 warnings

tests/unit/torch/model/test_head.py: 12 warnings

tests/unit/torch/model/test_model.py: 2 warnings

tests/unit/torch/tabular/test_aggregation.py: 6 warnings

tests/unit/torch/tabular/test_transformations.py: 2 warnings

tests/unit/xgb/test_xgboost.py: 17 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.USER_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.USER: 'user'>, <Tags.ID: 'id'>].

warnings.warn(
tests/unit/datasets/test_ecommerce.py: 1 warning

tests/unit/datasets/test_entertainment.py: 1 warning

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 2 warnings

tests/unit/tf/core/test_prediction.py: 1 warning

tests/unit/tf/horovod/test_horovod.py: 1 warning

tests/unit/tf/inputs/test_continuous.py: 4 warnings

tests/unit/tf/inputs/test_embedding.py: 9 warnings

tests/unit/tf/inputs/test_tabular.py: 8 warnings

tests/unit/tf/models/test_ranking.py: 20 warnings

tests/unit/tf/models/test_retrieval.py: 10 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 3 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 9 warnings

tests/unit/xgb/test_xgboost.py: 12 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.SESSION_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.SESSION: 'session'>, <Tags.ID: 'id'>].

warnings.warn(
tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export

tests/unit/tf/inputs/test_embedding.py::test_embedding_features_exporting_and_loading_pretrained_initializer

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/inputs/embedding.py:970: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack

embeddings_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(embeddings)))
tests/unit/tf/blocks/retrieval/test_two_tower.py: 1 warning

tests/unit/tf/core/test_index.py: 4 warnings

tests/unit/tf/horovod/test_horovod.py: 3 warnings

tests/unit/tf/models/test_retrieval.py: 59 warnings

tests/unit/tf/prediction_tasks/test_next_item.py: 3 warnings

tests/unit/tf/utils/test_batch.py: 2 warnings

/tmp/autograph_generated_filemz_t5w0l.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 41497 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                              175     62    65%

merlin/models/tf/blocks/retrieval/matrix_factorization.py               35      1    97%

merlin/models/tf/blocks/retrieval/two_tower.py                          30      0   100%

merlin/models/tf/blocks/sampling/init.py                             0      0   100%

merlin/models/tf/blocks/sampling/base.py                                29      2    93%

merlin/models/tf/blocks/sampling/cross_batch.py                         46      2    96%

merlin/models/tf/blocks/sampling/in_batch.py                            35      0   100%

merlin/models/tf/blocks/sampling/queue.py                              115     12    90%

merlin/models/tf/core/init.py                                        0      0   100%

merlin/models/tf/core/aggregation.py                                   241     45    81%

merlin/models/tf/core/base.py                                          242     50    79%

merlin/models/tf/core/combinators.py                                   426     54    87%

merlin/models/tf/core/encoder.py                                       175     28    84%

merlin/models/tf/core/index.py                                         106     16    85%

merlin/models/tf/core/prediction.py                                     50      1    98%

merlin/models/tf/core/tabular.py                                       280     32    89%

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      7    90%

merlin/models/tf/utils/search_utils.py                                  34     22    35%

merlin/models/tf/utils/testing_utils.py                                206     36    83%

merlin/models/tf/utils/tf_utils.py                                     209     42    80%

merlin/models/torch/init.py                                         12      0   100%

merlin/models/torch/block/init.py                                    0      0   100%

merlin/models/torch/block/base.py                                      167     32    81%

merlin/models/torch/block/mlp.py                                        38      5    87%

merlin/models/torch/dataset.py                                          68      5    93%

merlin/models/torch/features/init.py                                 0      0   100%

merlin/models/torch/features/base.py                                     4      0   100%

merlin/models/torch/features/continuous.py                              22      0   100%

merlin/models/torch/features/embedding.py                              165     12    93%

merlin/models/torch/features/tabular.py                                 65      8    88%

merlin/models/torch/losses.py                                           28     28     0%

merlin/models/torch/model/init.py                                    0      0   100%

merlin/models/torch/model/base.py                                      286     65    77%

merlin/models/torch/model/prediction_task.py                            24      0   100%

merlin/models/torch/tabular/init.py                                  0      0   100%

merlin/models/torch/tabular/aggregation.py                              75      0   100%

merlin/models/torch/tabular/base.py                                    247     39    84%

merlin/models/torch/tabular/transformations.py                          67      3    96%

merlin/models/torch/typing.py                                            6      0   100%

merlin/models/torch/utils/init.py                                    0      0   100%

merlin/models/torch/utils/data_utils.py                                117    117     0%

merlin/models/torch/utils/examples_utils.py                             39     39     0%

merlin/models/torch/utils/torch_utils.py                                80     22    72%

merlin/models/utils/init.py                                          0      0   100%

merlin/models/utils/constants.py                                         3      0   100%

merlin/models/utils/dataset.py                                          38      4    89%

merlin/models/utils/dependencies.py                                     26     19    27%

merlin/models/utils/doc_utils.py                                        10      0   100%

merlin/models/utils/example_utils.py                                    31      2    94%

merlin/models/utils/misc_utils.py                                      118     90    24%

merlin/models/utils/nvt_utils.py                                        27     24    11%

merlin/models/utils/registry.py                                        101     29    71%

merlin/models/utils/schema_utils.py                                     90     19    79%

merlin/models/xgb/init.py                                          124      4    97%
TOTAL                                                                11581   2361    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.

==== 2 failed, 864 passed, 13 skipped, 1445 warnings in 1914.57s (0:31:54) =====

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/jenkins9990628613375689505.sh

nvidia-merlin-bot · 2022-11-21T18:20:20Z

Click to view CI Results

GitHub pull request #887 of commit 8ab76c1fc5b27010c55f59539987413fa0dcaf38, no merge conflicts.
Running as SYSTEM
Setting status of 8ab76c1fc5b27010c55f59539987413fa0dcaf38 to PENDING with url http://merlin-infra1.nvidia.com:8080/job/merlin_models/1907/ 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/887/*:refs/remotes/origin/pr/887/* # timeout=10
 > git rev-parse 8ab76c1fc5b27010c55f59539987413fa0dcaf38^{commit} # timeout=10
Checking out Revision 8ab76c1fc5b27010c55f59539987413fa0dcaf38 (detached)
 > git config core.sparsecheckout # timeout=10
 > git checkout -f 8ab76c1fc5b27010c55f59539987413fa0dcaf38 # timeout=10
Commit message: "Merge branch 'main' into fix-two-tower-model-load-context-variable"
 > git rev-list --no-walk fe90b697eb390ff84f54d23b2589405d0d94f4fa # timeout=10
[merlin_models] $ /bin/bash /tmp/jenkins3521288534432761086.sh
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Requirement already satisfied: testbook in /usr/local/lib/python3.8/dist-packages (0.4.2)
Requirement already satisfied: nbclient>=0.4.0 in /usr/local/lib/python3.8/dist-packages (from testbook) (0.6.8)
Requirement already satisfied: nbformat>=5.0.4 in /usr/local/lib/python3.8/dist-packages (from testbook) (5.5.0)
Requirement already satisfied: jupyter-client>=6.1.5 in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (7.3.5)
Requirement already satisfied: traitlets>=5.2.2 in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (5.4.0)
Requirement already satisfied: nest-asyncio in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (1.5.5)
Requirement already satisfied: jsonschema>=2.6 in /usr/local/lib/python3.8/dist-packages (from nbformat>=5.0.4->testbook) (4.16.0)
Requirement already satisfied: fastjsonschema in /usr/local/lib/python3.8/dist-packages (from nbformat>=5.0.4->testbook) (2.16.1)
Requirement already satisfied: jupyter_core in /usr/local/lib/python3.8/dist-packages (from nbformat>=5.0.4->testbook) (4.11.1)
Requirement already satisfied: pyrsistent!=0.17.0,!=0.17.1,!=0.17.2,>=0.14.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (0.18.1)
Requirement already satisfied: attrs>=17.4.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (22.1.0)
Requirement already satisfied: importlib-resources>=1.4.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (5.9.0)
Requirement already satisfied: 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: 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: entrypoints in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (0.4)
Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (2.8.2)
Requirement already satisfied: zipp>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from importlib-resources>=1.4.0->jsonschema>=2.6->nbformat>=5.0.4->testbook) (3.8.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.8.2->jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (1.15.0)
GLOB sdist-make: /var/jenkins_home/workspace/merlin_models/models/setup.py
py38-gpu recreate: /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
py38-gpu installdeps: -rrequirements/dev.txt, tensorflow<2.10
WARNING: Discarding $PYTHONPATH from environment, to override specify PYTHONPATH in 'passenv' in your configuration.
py38-gpu inst: /var/jenkins_home/workspace/merlin_models/models/.tox/.tmp/package/4/merlin-models-0.9.0+58.g8ab76c1f.zip
WARNING: Discarding $PYTHONPATH from environment, to override specify PYTHONPATH in 'passenv' in your configuration.
py38-gpu installed: absl-py==1.2.0,aiohttp==3.8.1,aiosignal==1.2.0,alabaster==0.7.12,alembic==1.8.1,anyio==3.6.1,appdirs==1.4.4,argon2-cffi==21.3.0,argon2-cffi-bindings==21.2.0,astroid==2.5.6,asttokens==2.0.8,astunparse==1.6.3,asv==0.5.1,asvdb==0.4.2,async-timeout==4.0.2,attrs==22.1.0,autopage==0.5.1,awscli==1.27.13,Babel==2.10.3,backcall==0.2.0,beautifulsoup4==4.11.1,betterproto==1.2.5,black==20.8b1,bleach==5.0.1,bokeh==3.0.2,boto3==1.24.75,botocore==1.29.13,Brotli==1.0.9,build==0.9.0,cachetools==5.2.0,certifi==2019.11.28,cffi==1.15.1,chardet==3.0.4,charset-normalizer==2.1.1,check-manifest==0.48,clang==5.0,click==8.1.3,cliff==4.1.0,cloudpickle==2.2.0,cmaes==0.9.0,cmake==3.24.1.1,cmd2==2.4.2,colorama==0.4.4,colorlog==6.7.0,contourpy==1.0.5,coverage==6.5.0,cuda-python==11.7.1,cupy-cuda117==10.6.0,cycler==0.11.0,Cython==0.29.32,dask==2022.5.1,dbus-python==1.2.16,debugpy==1.6.3,decorator==5.1.1,defusedxml==0.7.1,dill==0.3.5.1,distlib==0.3.6,distributed==2022.5.1,distro==1.7.0,dm-tree==0.1.6,docker-pycreds==0.4.0,docutils==0.16,emoji==1.7.0,entrypoints==0.4,execnet==1.9.0,executing==1.0.0,faiss==1.7.2,faiss-gpu==1.7.2,fastai==2.7.9,fastapi==0.85.0,fastavro==1.6.1,fastcore==1.5.27,fastdownload==0.0.7,fastjsonschema==2.16.1,fastprogress==1.0.3,fastrlock==0.8,feast==0.19.4,fiddle==0.2.2,filelock==3.8.0,flake8==5.0.4,flatbuffers==1.12,fonttools==4.37.3,frozenlist==1.3.1,fsspec==2022.5.0,gast==0.4.0,gevent==21.12.0,geventhttpclient==2.0.2,gitdb==4.0.9,GitPython==3.1.27,google==3.0.0,google-api-core==2.10.1,google-auth==2.11.1,google-auth-oauthlib==0.4.6,google-pasta==0.2.0,googleapis-common-protos==1.52.0,graphviz==0.20.1,greenlet==1.1.3,grpcio==1.41.0,grpcio-channelz==1.49.0,grpcio-reflection==1.48.1,grpclib==0.4.3,h11==0.13.0,h2==4.1.0,h5py==3.7.0,HeapDict==1.0.1,horovod==0.26.1,hpack==4.0.0,httptools==0.5.0,hugectr2onnx==0.0.0,huggingface-hub==0.9.1,hyperframe==6.0.1,idna==2.8,imagesize==1.4.1,implicit==0.6.1,importlib-metadata==4.12.0,importlib-resources==5.9.0,iniconfig==1.1.1,interrogate==1.5.0,ipykernel==6.15.3,ipython==8.5.0,ipython-genutils==0.2.0,ipywidgets==7.7.0,isort==5.10.1,jedi==0.18.1,Jinja2==3.1.2,jmespath==1.0.1,joblib==1.2.0,json5==0.9.10,jsonschema==4.16.0,jupyter==1.0.0,jupyter-cache==0.4.3,jupyter-console==6.4.4,jupyter-core==4.11.1,jupyter-server==1.18.1,jupyter-server-mathjax==0.2.5,jupyter-sphinx==0.3.2,jupyter_client==7.3.5,jupyterlab==3.4.7,jupyterlab-pygments==0.2.2,jupyterlab-widgets==1.1.0,jupyterlab_server==2.15.1,keras==2.9.0,Keras-Preprocessing==1.1.2,kiwisolver==1.4.4,lazy-object-proxy==1.8.0,libclang==14.0.6,libcst==0.4.7,lightfm==1.16,lightgbm==3.3.2,linkify-it-py==1.0.3,llvmlite==0.39.1,locket==1.0.0,lxml==4.9.1,Mako==1.2.4,Markdown==3.4.1,markdown-it-py==1.1.0,MarkupSafe==2.1.1,matplotlib==3.6.0,matplotlib-inline==0.1.6,mccabe==0.7.0,mdit-py-plugins==0.2.8,merlin-core==0.6.0+1.g5926fcf,merlin-dataloader==0.0.2,merlin-models==0.9.0+58.g8ab76c1f,merlin-systems==0.5.0+4.g15074ad,mistune==2.0.4,mmh3==3.0.0,mpi4py==3.1.3,msgpack==1.0.4,multidict==6.0.2,mypy==0.991,mypy-extensions==0.4.3,myst-nb==0.13.2,myst-parser==0.15.2,natsort==8.1.0,nbclassic==0.4.3,nbclient==0.6.8,nbconvert==7.0.0,nbdime==3.1.1,nbformat==5.5.0,nest-asyncio==1.5.5,ninja==1.10.2.3,notebook==6.4.12,notebook-shim==0.1.0,numba==0.56.2,numpy==1.22.4,nvidia-pyindex==1.0.9,nvtabular @ git+https://github.com/NVIDIA-Merlin/NVTabular.git@e5b7351deb9e4885c4038aa0bbc9f146d8477a0e,nvtx==0.2.5,oauthlib==3.2.1,oldest-supported-numpy==2022.8.16,onnx==1.12.0,onnxruntime==1.11.1,opt-einsum==3.3.0,optuna==3.0.3,packaging==21.3,pandas==1.3.5,pandavro==1.5.2,pandocfilters==1.5.0,parso==0.8.3,partd==1.3.0,pathspec==0.10.2,pathtools==0.1.2,pbr==5.11.0,pep517==0.13.0,pexpect==4.8.0,pickleshare==0.7.5,Pillow==9.2.0,pkgutil_resolve_name==1.3.10,platformdirs==2.5.2,plotly==5.11.0,pluggy==1.0.0,prettytable==3.5.0,prometheus-client==0.14.1,promise==2.3,prompt-toolkit==3.0.31,proto-plus==1.19.6,protobuf==3.19.5,psutil==5.9.2,ptyprocess==0.7.0,pure-eval==0.2.2,py==1.11.0,pyarrow==7.0.0,pyasn1==0.4.8,pyasn1-modules==0.2.8,pybind11==2.10.0,pycodestyle==2.9.1,pycparser==2.21,pydantic==1.10.2,pydot==1.4.2,pyflakes==2.5.0,Pygments==2.13.0,PyGObject==3.36.0,pynvml==11.4.1,pyparsing==3.0.9,pyperclip==1.8.2,pyrsistent==0.18.1,pytest==7.1.3,pytest-cov==4.0.0,pytest-xdist==3.0.2,python-apt==2.0.0+ubuntu0.20.4.8,python-dateutil==2.8.2,python-dotenv==0.21.0,python-rapidjson==1.8,pytz==2022.2.1,PyYAML==5.4.1,pyzmq==24.0.0,qtconsole==5.4.0,QtPy==2.3.0,regex==2022.9.13,requests==2.22.0,requests-oauthlib==1.3.1,requests-unixsocket==0.2.0,rsa==4.7.2,s3fs==2022.2.0,s3transfer==0.6.0,sacremoses==0.0.53,scikit-build==0.15.0,scikit-learn==1.1.2,scipy==1.8.1,seedir==0.3.0,Send2Trash==1.8.0,sentry-sdk==1.9.8,setproctitle==1.3.2,setuptools-scm==7.0.5,shortuuid==1.0.9,six==1.15.0,sklearn==0.0,smmap==5.0.0,sniffio==1.3.0,snowballstemmer==2.2.0,sortedcontainers==2.4.0,soupsieve==2.3.2.post1,Sphinx==5.3.0,sphinx-multiversion==0.2.4,sphinx-togglebutton==0.3.1,sphinx_external_toc==0.3.0,sphinxcontrib-applehelp==1.0.2,sphinxcontrib-copydirs @ git+https://github.com/mikemckiernan/sphinxcontrib-copydirs.git@bd8c5d79b3f91cf5f1bb0d6995aeca3fe84b670e,sphinxcontrib-devhelp==1.0.2,sphinxcontrib-htmlhelp==2.0.0,sphinxcontrib-jsmath==1.0.1,sphinxcontrib-qthelp==1.0.3,sphinxcontrib-serializinghtml==1.1.5,SQLAlchemy==1.4.44,stack-data==0.5.0,starlette==0.20.4,stevedore==4.1.1,stringcase==1.2.0,supervisor==4.1.0,tabulate==0.8.10,tblib==1.7.0,tdqm==0.0.1,tenacity==8.0.1,tensorboard==2.9.1,tensorboard-data-server==0.6.1,tensorboard-plugin-wit==1.8.1,tensorflow==2.9.2,tensorflow-estimator==2.9.0,tensorflow-gpu==2.9.2,tensorflow-io-gcs-filesystem==0.27.0,tensorflow-metadata==1.10.0,termcolor==2.0.1,terminado==0.15.0,testbook==0.4.2,threadpoolctl==3.1.0,tinycss2==1.1.1,tokenizers==0.10.3,toml==0.10.2,tomli==2.0.1,toolz==0.12.0,torch==1.12.1+cu113,torchmetrics==0.3.2,tornado==6.2,tox==3.26.0,tqdm==4.64.1,traitlets==5.4.0,transformers==4.12.0,transformers4rec==0.1.12+2.gbcc939255,treelite==2.3.0,treelite-runtime==2.3.0,tritonclient==2.25.0,typed-ast==1.5.4,typing-inspect==0.8.0,typing_extensions==4.3.0,uc-micro-py==1.0.1,urllib3==1.26.12,uvicorn==0.18.3,uvloop==0.17.0,versioneer==0.20,virtualenv==20.16.5,wandb==0.13.3,watchfiles==0.17.0,wcwidth==0.2.5,webencodings==0.5.1,websocket-client==1.4.1,websockets==10.3,Werkzeug==2.2.2,widgetsnbextension==3.6.0,wrapt==1.12.1,xgboost==1.6.2,xyzservices==2022.9.0,yarl==1.8.1,zict==2.2.0,zipp==3.8.1,zope.event==4.5.0,zope.interface==5.4.0
py38-gpu run-test-pre: PYTHONHASHSEED='2689491823'
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-tk4b3x4z
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/core.git /tmp/pip-req-build-tk4b3x4z
  Resolved https://github.com/NVIDIA-Merlin/core.git to commit 04ff5225cee6af90b6b08070493677ac53b96836
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: betterproto<2.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+16.g04ff522) (1.2.5)
Requirement already satisfied: tensorflow-metadata>=1.2.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+16.g04ff522) (1.10.0)
Requirement already satisfied: numba>=0.54 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+16.g04ff522) (0.55.1)
Requirement already satisfied: dask>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+16.g04ff522) (2022.3.0)
Requirement already satisfied: distributed>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+16.g04ff522) (2022.3.0)
Requirement already satisfied: protobuf>=3.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+16.g04ff522) (3.19.5)
Requirement already satisfied: pyarrow>=5.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+16.g04ff522) (7.0.0)
Requirement already satisfied: tqdm>=4.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+16.g04ff522) (4.64.1)
Requirement already satisfied: fsspec==2022.5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+16.g04ff522) (2022.5.0)
Requirement already satisfied: packaging in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+16.g04ff522) (21.3)
Requirement already satisfied: pandas<1.4.0dev0,>=1.2.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+16.g04ff522) (1.3.5)
Requirement already satisfied: grpclib in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core==0.8.0+16.g04ff522) (0.4.3)
Requirement already satisfied: stringcase in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core==0.8.0+16.g04ff522) (1.2.0)
Requirement already satisfied: toolz>=0.8.2 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (0.12.0)
Requirement already satisfied: cloudpickle>=1.1.1 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (2.2.0)
Requirement already satisfied: pyyaml>=5.3.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/PyYAML-5.4.1-py3.8-linux-x86_64.egg (from dask>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (5.4.1)
Requirement already satisfied: partd>=0.3.10 in /var/jenkins_home/.local/lib/python3.8/site-packages/partd-1.2.0-py3.8.egg (from dask>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (1.2.0)
Requirement already satisfied: click>=6.6 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (8.1.3)
Requirement already satisfied: jinja2 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (3.1.2)
Requirement already satisfied: tblib>=1.6.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/tblib-1.7.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (1.7.0)
Requirement already satisfied: tornado>=6.0.3 in ./.tox/py38-gpu/lib/python3.8/site-packages (from distributed>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (6.2)
Requirement already satisfied: msgpack>=0.6.0 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (1.0.4)
Requirement already satisfied: sortedcontainers!=2.0.0,!=2.0.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/sortedcontainers-2.4.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (2.4.0)
Requirement already satisfied: psutil>=5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/psutil-5.8.0-py3.8-linux-x86_64.egg (from distributed>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (5.8.0)
Requirement already satisfied: zict>=0.1.3 in /var/jenkins_home/.local/lib/python3.8/site-packages/zict-2.0.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (2.0.0)
Requirement already satisfied: setuptools in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+16.g04ff522) (65.5.1)
Requirement already satisfied: numpy<1.22,>=1.18 in /var/jenkins_home/.local/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+16.g04ff522) (1.20.3)
Requirement already satisfied: llvmlite<0.39,>=0.38.0rc1 in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+16.g04ff522) (0.38.1)
Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in /usr/local/lib/python3.8/dist-packages (from packaging->merlin-core==0.8.0+16.g04ff522) (3.0.9)
Requirement already satisfied: pytz>=2017.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+16.g04ff522) (2022.2.1)
Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+16.g04ff522) (2.8.2)
Requirement already satisfied: googleapis-common-protos<2,>=1.52.0 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core==0.8.0+16.g04ff522) (1.52.0)
Requirement already satisfied: absl-py<2.0.0,>=0.9 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core==0.8.0+16.g04ff522) (1.2.0)
Requirement already satisfied: locket in /var/jenkins_home/.local/lib/python3.8/site-packages/locket-0.2.1-py3.8.egg (from partd>=0.3.10->dask>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (0.2.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.7.3->pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+16.g04ff522) (1.15.0)
Requirement already satisfied: heapdict in /var/jenkins_home/.local/lib/python3.8/site-packages/HeapDict-1.0.1-py3.8.egg (from zict>=0.1.3->distributed>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (1.0.1)
Requirement already satisfied: h2<5,>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core==0.8.0+16.g04ff522) (4.1.0)
Requirement already satisfied: multidict in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core==0.8.0+16.g04ff522) (6.0.2)
Requirement already satisfied: MarkupSafe>=2.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from jinja2->distributed>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (2.0.1)
Requirement already satisfied: hpack<5,>=4.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core==0.8.0+16.g04ff522) (4.0.0)
Requirement already satisfied: hyperframe<7,>=6.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core==0.8.0+16.g04ff522) (6.0.1)
Building wheels for collected packages: merlin-core
  Building wheel for merlin-core (pyproject.toml): started
  Building wheel for merlin-core (pyproject.toml): finished with status 'done'
  Created wheel for merlin-core: filename=merlin_core-0.8.0+16.g04ff522-py3-none-any.whl size=118833 sha256=d81beafae98c237076b7337eb6cf3be691b265c42cf14701f1fc107f6cbb603d
  Stored in directory: /tmp/pip-ephem-wheel-cache-uf1hrq6j/wheels/c8/38/16/a6968787eafcec5fa772148af8408b089562f71af0752e8e84
Successfully built merlin-core
Installing collected packages: merlin-core
  Attempting uninstall: merlin-core
    Found existing installation: merlin-core 0.3.0+12.g78ecddd
    Not uninstalling merlin-core at /var/jenkins_home/.local/lib/python3.8/site-packages, outside environment /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
    Can't uninstall 'merlin-core'. No files were found to uninstall.
Successfully installed merlin-core-0.8.0+16.g04ff522
py38-gpu run-test: commands[1] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/nvtabular.git
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Collecting git+https://github.com/NVIDIA-Merlin/nvtabular.git
  Cloning https://github.com/NVIDIA-Merlin/nvtabular.git to /tmp/pip-req-build-t6w6rcg1
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/nvtabular.git /tmp/pip-req-build-t6w6rcg1
  Resolved https://github.com/NVIDIA-Merlin/nvtabular.git to commit e5b7351deb9e4885c4038aa0bbc9f146d8477a0e
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: merlin-dataloader>=0.0.2 in /usr/local/lib/python3.8/dist-packages (from nvtabular==1.6.0+6.ge5b7351d) (0.0.2)
Requirement already satisfied: scipy in /usr/local/lib/python3.8/dist-packages (from nvtabular==1.6.0+6.ge5b7351d) (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+6.ge5b7351d) (0.8.0+16.g04ff522)
Requirement already satisfied: betterproto<2.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+6.ge5b7351d) (1.2.5)
Requirement already satisfied: tensorflow-metadata>=1.2.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+6.ge5b7351d) (1.10.0)
Requirement already satisfied: numba>=0.54 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+6.ge5b7351d) (0.55.1)
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+6.ge5b7351d) (2022.3.0)
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+6.ge5b7351d) (2022.3.0)
Requirement already satisfied: protobuf>=3.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+6.ge5b7351d) (3.19.5)
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+6.ge5b7351d) (7.0.0)
Requirement already satisfied: tqdm>=4.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+6.ge5b7351d) (4.64.1)
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: packaging in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+6.ge5b7351d) (21.3)
Requirement already satisfied: pandas<1.4.0dev0,>=1.2.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+6.ge5b7351d) (1.3.5)
Requirement already satisfied: numpy<1.25.0,>=1.17.3 in /var/jenkins_home/.local/lib/python3.8/site-packages (from scipy->nvtabular==1.6.0+6.ge5b7351d) (1.20.3)
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+6.ge5b7351d) (0.4.3)
Requirement already satisfied: stringcase in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core>=0.2.0->nvtabular==1.6.0+6.ge5b7351d) (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>=0.2.0->nvtabular==1.6.0+6.ge5b7351d) (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>=0.2.0->nvtabular==1.6.0+6.ge5b7351d) (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>=0.2.0->nvtabular==1.6.0+6.ge5b7351d) (5.4.1)
Requirement already satisfied: partd>=0.3.10 in /var/jenkins_home/.local/lib/python3.8/site-packages/partd-1.2.0-py3.8.egg (from dask>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+6.ge5b7351d) (1.2.0)
Requirement already satisfied: click>=6.6 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+6.ge5b7351d) (8.1.3)
Requirement already satisfied: jinja2 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+6.ge5b7351d) (3.1.2)
Requirement already satisfied: tblib>=1.6.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/tblib-1.7.0-py3.8.egg (from distributed>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+6.ge5b7351d) (1.7.0)
Requirement already satisfied: tornado>=6.0.3 in ./.tox/py38-gpu/lib/python3.8/site-packages (from distributed>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+6.ge5b7351d) (6.2)
Requirement already satisfied: msgpack>=0.6.0 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+6.ge5b7351d) (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>=0.2.0->nvtabular==1.6.0+6.ge5b7351d) (2.4.0)
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Building wheels for collected packages: nvtabular
  Building wheel for nvtabular (pyproject.toml): started
  Building wheel for nvtabular (pyproject.toml): finished with status 'done'
  Created wheel for nvtabular: filename=nvtabular-1.6.0+6.ge5b7351d-cp38-cp38-linux_x86_64.whl size=257597 sha256=73f6bca5020cd9fddccfde8f76c08e1104231facc92510ce40260a31e8051744
  Stored in directory: /tmp/pip-ephem-wheel-cache-51dh23m8/wheels/8f/d9/f9/30f2cdc5bf8787fae6fdfe55afd6e1b493e619ec32c32ec40b
Successfully built nvtabular
Installing collected packages: nvtabular
  Attempting uninstall: nvtabular
    Found existing installation: nvtabular 1.1.1
    Not uninstalling nvtabular at /var/jenkins_home/.local/lib/python3.8/site-packages, outside environment /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
    Can't uninstall 'nvtabular'. No files were found to uninstall.
Successfully installed nvtabular-1.6.0+6.ge5b7351d
py38-gpu run-test: commands[2] | python -m pytest --cov-report term --cov merlin -rxs tests/unit
============================= test session starts ==============================
platform linux -- Python 3.8.10, pytest-7.1.3, pluggy-1.0.0
cachedir: .tox/py38-gpu/.pytest_cache
rootdir: /var/jenkins_home/workspace/merlin_models/models, configfile: pyproject.toml
plugins: anyio-3.5.0, xdist-3.0.2, cov-4.0.0
collected 883 items
tests/unit/config/test_schema.py ....                                    [  0%]

tests/unit/datasets/test_advertising.py .s                               [  0%]

tests/unit/datasets/test_ecommerce.py ..sss.s                            [  1%]

tests/unit/datasets/test_entertainment.py ....sss.                       [  2%]

tests/unit/datasets/test_social.py .                                     [  2%]

tests/unit/datasets/test_synthetic.py ..........                         [  3%]

tests/unit/implicit/test_implicit.py .                                   [  3%]

tests/unit/lightfm/test_lightfm.py .                                     [  3%]

tests/unit/tf/test_core.py ......                                        [  4%]

tests/unit/tf/test_loader.py ................                            [  6%]

tests/unit/tf/test_public_api.py .                                       [  6%]

tests/unit/tf/blocks/test_cross.py ...........                           [  7%]

tests/unit/tf/blocks/test_dlrm.py ..........                             [  8%]

tests/unit/tf/blocks/test_interactions.py ...                            [  9%]

tests/unit/tf/blocks/test_mlp.py ....................................... [ 13%]

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tests/unit/tf/blocks/test_optimizer.py s................................ [ 20%]

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tests/unit/tf/blocks/retrieval/test_base.py .                            [ 22%]

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py ..           [ 23%]

tests/unit/tf/blocks/retrieval/test_two_tower.py ............            [ 24%]

tests/unit/tf/blocks/sampling/test_cross_batch.py .                      [ 24%]

tests/unit/tf/blocks/sampling/test_in_batch.py .                         [ 24%]

tests/unit/tf/core/test_aggregation.py .........                         [ 25%]

tests/unit/tf/core/test_base.py ..                                       [ 26%]

tests/unit/tf/core/test_combinators.py s.....................            [ 28%]

tests/unit/tf/core/test_encoder.py ..                                    [ 28%]

tests/unit/tf/core/test_index.py ...                                     [ 29%]

tests/unit/tf/core/test_prediction.py ..                                 [ 29%]

tests/unit/tf/core/test_tabular.py ......                                [ 30%]

tests/unit/tf/examples/test_01_getting_started.py .                      [ 30%]

tests/unit/tf/examples/test_02_dataschema.py .                           [ 30%]

tests/unit/tf/examples/test_03_exploring_different_models.py .           [ 30%]

tests/unit/tf/examples/test_04_export_ranking_models.py .                [ 30%]

tests/unit/tf/examples/test_05_export_retrieval_model.py .               [ 30%]

tests/unit/tf/examples/test_06_advanced_own_architecture.py .            [ 30%]

tests/unit/tf/examples/test_07_train_traditional_models.py .             [ 30%]

tests/unit/tf/examples/test_usecase_accelerate_training_by_lazyadam.py . [ 30%]

[ 30%]

tests/unit/tf/examples/test_usecase_ecommerce_session_based.py .         [ 31%]

tests/unit/tf/examples/test_usecase_incremental_training_layer_freezing.py . [ 31%]

[ 31%]

tests/unit/tf/examples/test_usecase_pretrained_embeddings.py .           [ 31%]

tests/unit/tf/examples/test_usecase_retrieval_with_hpo.py .              [ 31%]

tests/unit/tf/examples/test_usecase_transformers_next_item_prediction.py . [ 31%]

[ 31%]

tests/unit/tf/horovod/test_horovod.py ...                                [ 31%]

tests/unit/tf/inputs/test_base.py .                                      [ 31%]

tests/unit/tf/inputs/test_continuous.py ........                         [ 32%]

tests/unit/tf/inputs/test_embedding.py ................................. [ 36%]

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tests/unit/tf/inputs/test_tabular.py ..................                  [ 39%]

tests/unit/tf/layers/test_queue.py ..............                        [ 41%]

tests/unit/tf/losses/test_losses.py .......................              [ 43%]

tests/unit/tf/metrics/test_metrics_popularity.py .....                   [ 44%]

tests/unit/tf/metrics/test_metrics_topk.py .........................     [ 47%]

tests/unit/tf/models/test_base.py s.........................             [ 50%]

tests/unit/tf/models/test_benchmark.py ..                                [ 50%]

tests/unit/tf/models/test_ranking.py ..................................  [ 54%]

tests/unit/tf/models/test_retrieval.py ................................. [ 57%]

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tests/unit/tf/outputs/test_base.py ......                                [ 63%]

tests/unit/tf/outputs/test_classification.py ......                      [ 64%]

tests/unit/tf/outputs/test_contrastive.py ..............                 [ 65%]

tests/unit/tf/outputs/test_regression.py ..                              [ 65%]

tests/unit/tf/outputs/test_sampling.py ....                              [ 66%]

tests/unit/tf/outputs/test_topk.py .                                     [ 66%]

tests/unit/tf/prediction_tasks/test_classification.py ..                 [ 66%]

tests/unit/tf/prediction_tasks/test_multi_task.py ................       [ 68%]

tests/unit/tf/prediction_tasks/test_next_item.py .....                   [ 69%]

tests/unit/tf/prediction_tasks/test_regression.py .....                  [ 69%]

tests/unit/tf/prediction_tasks/test_retrieval.py .                       [ 69%]

tests/unit/tf/prediction_tasks/test_sampling.py ......                   [ 70%]

tests/unit/tf/transformers/test_block.py ......................          [ 72%]

tests/unit/tf/transformers/test_transforms.py ..........                 [ 74%]

tests/unit/tf/transforms/test_bias.py ..                                 [ 74%]

tests/unit/tf/transforms/test_features.py s............................. [ 77%]

.......................s......                                           [ 81%]

tests/unit/tf/transforms/test_negative_sampling.py .........             [ 82%]

tests/unit/tf/transforms/test_noise.py .....                             [ 82%]

tests/unit/tf/transforms/test_sequence.py ....................           [ 84%]

tests/unit/tf/transforms/test_tensor.py ...                              [ 85%]

tests/unit/tf/utils/test_batch.py ....                                   [ 85%]

tests/unit/tf/utils/test_dataset.py ..                                   [ 85%]

tests/unit/tf/utils/test_tf_utils.py .....                               [ 86%]

tests/unit/torch/test_dataset.py .........                               [ 87%]

tests/unit/torch/test_public_api.py .                                    [ 87%]

tests/unit/torch/block/test_base.py ....                                 [ 88%]

tests/unit/torch/block/test_mlp.py .                                     [ 88%]

tests/unit/torch/features/test_continuous.py ..                          [ 88%]

tests/unit/torch/features/test_embedding.py ..............               [ 90%]

tests/unit/torch/features/test_tabular.py ....                           [ 90%]

tests/unit/torch/model/test_head.py ............                         [ 91%]

tests/unit/torch/model/test_model.py ..                                  [ 92%]

tests/unit/torch/tabular/test_aggregation.py ........                    [ 92%]

tests/unit/torch/tabular/test_tabular.py ...                             [ 93%]

tests/unit/torch/tabular/test_transformations.py .......                 [ 94%]

tests/unit/utils/test_schema_utils.py ................................   [ 97%]

tests/unit/xgb/test_xgboost.py ....................                      [100%]
=============================== warnings summary ===============================

../../../../../usr/lib/python3/dist-packages/requests/init.py:89

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

warnings.warn("urllib3 ({}) or chardet ({}) doesn't match a supported "
../../../.local/lib/python3.8/site-packages/flatbuffers/compat.py:19

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

import imp
../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36

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

'nearest': pil_image.NEAREST,
../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37

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

'bilinear': pil_image.BILINEAR,
../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38

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

'bicubic': pil_image.BICUBIC,
../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39

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

'hamming': pil_image.HAMMING,
../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40

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

'box': pil_image.BOX,
../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41

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

'lanczos': pil_image.LANCZOS,
tests/unit/datasets/test_advertising.py: 1 warning

tests/unit/datasets/test_ecommerce.py: 3 warnings

tests/unit/datasets/test_entertainment.py: 4 warnings

tests/unit/datasets/test_social.py: 1 warning

tests/unit/datasets/test_synthetic.py: 10 warnings

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_core.py: 6 warnings

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/test_cross.py: 5 warnings

tests/unit/tf/blocks/test_dlrm.py: 9 warnings

tests/unit/tf/blocks/test_interactions.py: 2 warnings

tests/unit/tf/blocks/test_mlp.py: 60 warnings

tests/unit/tf/blocks/test_optimizer.py: 30 warnings

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings

tests/unit/tf/core/test_aggregation.py: 6 warnings

tests/unit/tf/core/test_base.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 6 warnings

tests/unit/tf/core/test_index.py: 8 warnings

tests/unit/tf/core/test_prediction.py: 2 warnings

tests/unit/tf/horovod/test_horovod.py: 3 warnings

tests/unit/tf/inputs/test_base.py: 1 warning

tests/unit/tf/inputs/test_continuous.py: 7 warnings

tests/unit/tf/inputs/test_embedding.py: 20 warnings

tests/unit/tf/inputs/test_tabular.py: 18 warnings

tests/unit/tf/models/test_base.py: 28 warnings

tests/unit/tf/models/test_benchmark.py: 2 warnings

tests/unit/tf/models/test_ranking.py: 38 warnings

tests/unit/tf/models/test_retrieval.py: 121 warnings

tests/unit/tf/outputs/test_base.py: 6 warnings

tests/unit/tf/outputs/test_classification.py: 6 warnings

tests/unit/tf/outputs/test_contrastive.py: 19 warnings

tests/unit/tf/outputs/test_regression.py: 2 warnings

tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings

tests/unit/tf/prediction_tasks/test_retrieval.py: 1 warning

tests/unit/tf/transformers/test_block.py: 16 warnings

tests/unit/tf/transforms/test_bias.py: 2 warnings

tests/unit/tf/transforms/test_features.py: 10 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings

tests/unit/tf/transforms/test_noise.py: 1 warning

tests/unit/tf/transforms/test_sequence.py: 15 warnings

tests/unit/tf/utils/test_batch.py: 9 warnings

tests/unit/tf/utils/test_dataset.py: 2 warnings

tests/unit/torch/block/test_base.py: 4 warnings

tests/unit/torch/block/test_mlp.py: 1 warning

tests/unit/torch/features/test_continuous.py: 1 warning

tests/unit/torch/features/test_embedding.py: 4 warnings

tests/unit/torch/features/test_tabular.py: 4 warnings

tests/unit/torch/model/test_head.py: 12 warnings

tests/unit/torch/model/test_model.py: 2 warnings

tests/unit/torch/tabular/test_aggregation.py: 6 warnings

tests/unit/torch/tabular/test_transformations.py: 3 warnings

tests/unit/xgb/test_xgboost.py: 18 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.ITEM_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.ITEM: 'item'>, <Tags.ID: 'id'>].

warnings.warn(
tests/unit/datasets/test_ecommerce.py: 3 warnings

tests/unit/datasets/test_entertainment.py: 4 warnings

tests/unit/datasets/test_social.py: 1 warning

tests/unit/datasets/test_synthetic.py: 9 warnings

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_core.py: 6 warnings

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/test_cross.py: 5 warnings

tests/unit/tf/blocks/test_dlrm.py: 9 warnings

tests/unit/tf/blocks/test_interactions.py: 2 warnings

tests/unit/tf/blocks/test_mlp.py: 60 warnings

tests/unit/tf/blocks/test_optimizer.py: 30 warnings

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings

tests/unit/tf/core/test_aggregation.py: 6 warnings

tests/unit/tf/core/test_base.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 7 warnings

tests/unit/tf/core/test_index.py: 3 warnings

tests/unit/tf/core/test_prediction.py: 2 warnings

tests/unit/tf/horovod/test_horovod.py: 1 warning

tests/unit/tf/inputs/test_base.py: 1 warning

tests/unit/tf/inputs/test_continuous.py: 7 warnings

tests/unit/tf/inputs/test_embedding.py: 20 warnings

tests/unit/tf/inputs/test_tabular.py: 18 warnings

tests/unit/tf/models/test_base.py: 28 warnings

tests/unit/tf/models/test_benchmark.py: 2 warnings

tests/unit/tf/models/test_ranking.py: 36 warnings

tests/unit/tf/models/test_retrieval.py: 87 warnings

tests/unit/tf/outputs/test_base.py: 6 warnings

tests/unit/tf/outputs/test_classification.py: 6 warnings

tests/unit/tf/outputs/test_contrastive.py: 19 warnings

tests/unit/tf/outputs/test_regression.py: 2 warnings

tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings

tests/unit/tf/transformers/test_block.py: 10 warnings

tests/unit/tf/transforms/test_features.py: 10 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings

tests/unit/tf/transforms/test_sequence.py: 15 warnings

tests/unit/tf/utils/test_batch.py: 7 warnings

tests/unit/tf/utils/test_dataset.py: 2 warnings

tests/unit/torch/block/test_base.py: 4 warnings

tests/unit/torch/block/test_mlp.py: 1 warning

tests/unit/torch/features/test_continuous.py: 1 warning

tests/unit/torch/features/test_embedding.py: 4 warnings

tests/unit/torch/features/test_tabular.py: 4 warnings

tests/unit/torch/model/test_head.py: 12 warnings

tests/unit/torch/model/test_model.py: 2 warnings

tests/unit/torch/tabular/test_aggregation.py: 6 warnings

tests/unit/torch/tabular/test_transformations.py: 2 warnings

tests/unit/xgb/test_xgboost.py: 17 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.USER_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.USER: 'user'>, <Tags.ID: 'id'>].

warnings.warn(
tests/unit/datasets/test_ecommerce.py: 1 warning

tests/unit/datasets/test_entertainment.py: 1 warning

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 2 warnings

tests/unit/tf/core/test_prediction.py: 1 warning

tests/unit/tf/horovod/test_horovod.py: 1 warning

tests/unit/tf/inputs/test_continuous.py: 4 warnings

tests/unit/tf/inputs/test_embedding.py: 9 warnings

tests/unit/tf/inputs/test_tabular.py: 8 warnings

tests/unit/tf/models/test_ranking.py: 20 warnings

tests/unit/tf/models/test_retrieval.py: 10 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 3 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 9 warnings

tests/unit/xgb/test_xgboost.py: 12 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.SESSION_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.SESSION: 'session'>, <Tags.ID: 'id'>].

warnings.warn(
tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export

tests/unit/tf/inputs/test_embedding.py::test_embedding_features_exporting_and_loading_pretrained_initializer

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/inputs/embedding.py:970: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack

embeddings_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(embeddings)))
tests/unit/tf/blocks/retrieval/test_two_tower.py: 1 warning

tests/unit/tf/core/test_index.py: 4 warnings

tests/unit/tf/horovod/test_horovod.py: 3 warnings

tests/unit/tf/models/test_retrieval.py: 59 warnings

tests/unit/tf/prediction_tasks/test_next_item.py: 3 warnings

tests/unit/tf/utils/test_batch.py: 2 warnings

/tmp/autograph_generated_file1jhy_is0.py:8: DeprecationWarning: The 'warn' method is deprecated, use 'warning' instead

ag.converted_call(ag__.ld(warnings).warn, ("The 'warn' method is deprecated, use 'warning' instead", ag__.ld(DeprecationWarning), 2), None, fscope)
tests/unit/tf/core/test_combinators.py::test_parallel_block_select_by_tags

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/core/tabular.py:602: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated since Python 3.3, and in 3.10 it will stop working

elif isinstance(self.feature_names, collections.Sequence):
tests/unit/tf/core/test_encoder.py: 1 warning

tests/unit/tf/core/test_index.py: 5 warnings

tests/unit/tf/models/test_retrieval.py: 30 warnings

tests/unit/tf/utils/test_batch.py: 4 warnings

tests/unit/tf/utils/test_dataset.py: 1 warning

/var/jenkins_home/workspace/merlin_models/models/merlin/models/utils/dataset.py:75: DeprecationWarning: unique_rows_by_features is deprecated and will be removed in a future version. Please use unique_by_tag instead.

warnings.warn(
tests/unit/tf/models/test_base.py::test_model_pre_post[True]

tests/unit/tf/models/test_base.py::test_model_pre_post[False]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.1]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.3]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.5]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.7]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/util/dispatch.py:1082: UserWarning: tf.keras.backend.random_binomial is deprecated, and will be removed in a future version.Please use tf.keras.backend.random_bernoulli instead.

return dispatch_target(*args, **kwargs)
tests/unit/tf/models/test_base.py::test_freeze_parallel_block[True]

tests/unit/tf/models/test_base.py::test_freeze_sequential_block

tests/unit/tf/models/test_base.py::test_freeze_unfreeze

tests/unit/tf/models/test_base.py::test_unfreeze_all_blocks

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/gradient_descent.py:108: UserWarning: The lr argument is deprecated, use learning_rate instead.

super(SGD, self).init(name, **kwargs)
tests/unit/tf/models/test_base.py::test_retrieval_model_query

tests/unit/tf/models/test_base.py::test_retrieval_model_query

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_v2_export_embeddings

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[True]

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[False]

tests/unit/tf/transformers/test_block.py::test_retrieval_transformer[True]

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/utils/tf_utils.py:298: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack

tensor_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(tensor)))
tests/unit/tf/models/test_ranking.py::test_deepfm_model_only_categ_feats[False]

tests/unit/tf/models/test_ranking.py::test_deepfm_model_categ_and_continuous_feats[False]

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

warnings.warn(
tests/unit/tf/models/test_ranking.py::test_wide_deep_model[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_categorical_one_hot[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_hashed_cross[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

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

warnings.warn(
tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[True]

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/transforms/features.py:569: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag

warnings.warn(
tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/autograph/impl/api.py:371: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag

return py_builtins.overload_of(f)(*args)
tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_onehot_multihot_feature_interaction[False]

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

warnings.warn(
tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_feature_interaction_multi_optimizer[False]

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

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]

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

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]

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

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]

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

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]

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

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

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

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

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

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

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

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

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

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

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

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

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

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

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

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

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

warnings.warn(
tests/unit/torch/block/test_mlp.py::test_mlp_block

/var/jenkins_home/workspace/merlin_models/models/tests/unit/torch/_conftest.py:151: UserWarning: Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

return {key: torch.tensor(value) for key, value in data.items()}
tests/unit/xgb/test_xgboost.py::test_without_dask_client

tests/unit/xgb/test_xgboost.py::TestXGBoost::test_music_regression

tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs0-DaskDeviceQuantileDMatrix]

tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs1-DaskDMatrix]

tests/unit/xgb/test_xgboost.py::TestEvals::test_multiple

tests/unit/xgb/test_xgboost.py::TestEvals::test_default

tests/unit/xgb/test_xgboost.py::TestEvals::test_train_and_valid

tests/unit/xgb/test_xgboost.py::TestEvals::test_invalid_data

/var/jenkins_home/workspace/merlin_models/models/merlin/models/xgb/init.py:344: UserWarning: Ignoring list columns as inputs to XGBoost model: ['item_genres', 'user_genres'].

warnings.warn(f"Ignoring list columns as inputs to XGBoost model: {list_column_names}.")
tests/unit/xgb/test_xgboost.py::TestXGBoost::test_unsupported_objective

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/tornado/ioloop.py:350: DeprecationWarning: make_current is deprecated; start the event loop first

self.make_current()
tests/unit/xgb/test_xgboost.py: 14 warnings

/usr/local/lib/python3.8/dist-packages/xgboost/dask.py:884: RuntimeWarning: coroutine 'Client._wait_for_workers' was never awaited

client.wait_for_workers(n_workers)

Enable tracemalloc to get traceback where the object was allocated.

See https://docs.pytest.org/en/stable/how-to/capture-warnings.html#resource-warnings for more info.
tests/unit/xgb/test_xgboost.py: 11 warnings

/usr/local/lib/python3.8/dist-packages/cudf/core/dataframe.py:1183: DeprecationWarning: The default dtype for empty Series will be 'object' instead of 'float64' in a future version. Specify a dtype explicitly to silence this warning.

mask = pd.Series(mask)
-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html
---------- coverage: platform linux, python 3.8.10-final-0 -----------

Name                                                                 Stmts   Miss  Cover
merlin/datasets/init.py                                              2      0   100%

merlin/datasets/advertising/init.py                                  2      0   100%

merlin/datasets/advertising/criteo/init.py                           0      0   100%

merlin/datasets/advertising/criteo/dataset.py                           79     49    38%

merlin/datasets/advertising/criteo/transformed/init.py               0      0   100%

merlin/datasets/ecommerce/init.py                                    4      0   100%

merlin/datasets/ecommerce/aliccp/init.py                             0      0   100%

merlin/datasets/ecommerce/aliccp/dataset.py                            141     87    38%

merlin/datasets/ecommerce/aliccp/raw/init.py                         0      0   100%

merlin/datasets/ecommerce/aliccp/transformed/init.py                 0      0   100%

merlin/datasets/ecommerce/booking/init.py                            0      0   100%

merlin/datasets/ecommerce/booking/dataset.py                           127    100    21%

merlin/datasets/ecommerce/booking/raw/init.py                        0      0   100%

merlin/datasets/ecommerce/booking/transformed/init.py                0      0   100%

merlin/datasets/ecommerce/dressipi/init.py                           0      0   100%

merlin/datasets/ecommerce/dressipi/dataset.py                           45     37    18%

merlin/datasets/ecommerce/dressipi/preprocessed/init.py              0      0   100%

merlin/datasets/ecommerce/large/init.py                              0      0   100%

merlin/datasets/ecommerce/small/init.py                              0      0   100%

merlin/datasets/ecommerce/transactions/init.py                       0      0   100%

merlin/datasets/entertainment/init.py                                2      0   100%

merlin/datasets/entertainment/movielens/1m-raw/init.py               0      0   100%

merlin/datasets/entertainment/movielens/1m-raw/ratings/init.py       0      0   100%

merlin/datasets/entertainment/movielens/1m/init.py                   0      0   100%

merlin/datasets/entertainment/movielens/25m/init.py                  0      0   100%

merlin/datasets/entertainment/movielens/100k/init.py                 0      0   100%

merlin/datasets/entertainment/movielens/init.py                      0      0   100%

merlin/datasets/entertainment/movielens/dataset.py                     152    122    20%

merlin/datasets/entertainment/music_streaming/init.py                0      0   100%

merlin/datasets/social/init.py                                       0      0   100%

merlin/datasets/synthetic.py                                           147      8    95%

merlin/datasets/testing/init.py                                      0      0   100%

merlin/datasets/testing/sequence_testing/init.py                     0      0   100%

merlin/models/init.py                                                2      0   100%

merlin/models/_version.py                                              354    205    42%

merlin/models/api.py                                                    14      5    64%

merlin/models/config/init.py                                         0      0   100%

merlin/models/config/schema.py                                          62      0   100%

merlin/models/implicit/init.py                                      27      4    85%

merlin/models/io.py                                                     15      0   100%

merlin/models/lightfm/init.py                                       23      0   100%

merlin/models/loader/init.py                                         0      0   100%

merlin/models/loader/backend.py                                        379     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                              175     62    65%

merlin/models/tf/blocks/retrieval/matrix_factorization.py               35      1    97%

merlin/models/tf/blocks/retrieval/two_tower.py                          30      0   100%

merlin/models/tf/blocks/sampling/init.py                             0      0   100%

merlin/models/tf/blocks/sampling/base.py                                29      2    93%

merlin/models/tf/blocks/sampling/cross_batch.py                         46      2    96%

merlin/models/tf/blocks/sampling/in_batch.py                            35      0   100%

merlin/models/tf/blocks/sampling/queue.py                              115     12    90%

merlin/models/tf/core/init.py                                        0      0   100%

merlin/models/tf/core/aggregation.py                                   241     45    81%

merlin/models/tf/core/base.py                                          242     50    79%

merlin/models/tf/core/combinators.py                                   426     53    88%

merlin/models/tf/core/encoder.py                                       175     28    84%

merlin/models/tf/core/index.py                                         106     16    85%

merlin/models/tf/core/prediction.py                                     50      1    98%

merlin/models/tf/core/tabular.py                                       280     29    90%

merlin/models/tf/distributed/init.py                                 0      0   100%

merlin/models/tf/distributed/backend.py                                  9      2    78%

merlin/models/tf/inputs/init.py                                      0      0   100%

merlin/models/tf/inputs/base.py                                         60     10    83%

merlin/models/tf/inputs/continuous.py                                   39      3    92%

merlin/models/tf/inputs/embedding.py                                   458     32    93%

merlin/models/tf/loader.py                                             268     94    65%

merlin/models/tf/losses/init.py                                      4      0   100%

merlin/models/tf/losses/base.py                                          9      0   100%

merlin/models/tf/losses/listwise.py                                     13      0   100%

merlin/models/tf/losses/pairwise.py                                    115      1    99%

merlin/models/tf/metrics/init.py                                     2      0   100%

merlin/models/tf/metrics/evaluation.py                                 105     48    54%

merlin/models/tf/metrics/topk.py                                       198     48    76%

merlin/models/tf/models/init.py                                      0      0   100%

merlin/models/tf/models/base.py                                        756    101    87%

merlin/models/tf/models/benchmark.py                                    16      0   100%

merlin/models/tf/models/ranking.py                                      67      3    96%

merlin/models/tf/models/retrieval.py                                    78      4    95%

merlin/models/tf/models/utils.py                                        10      1    90%

merlin/models/tf/outputs/init.py                                     0      0   100%

merlin/models/tf/outputs/base.py                                       123     17    86%

merlin/models/tf/outputs/classification.py                              91      1    99%

merlin/models/tf/outputs/contrastive.py                                147     10    93%

merlin/models/tf/outputs/regression.py                                   9      0   100%

merlin/models/tf/outputs/sampling/init.py                            0      0   100%

merlin/models/tf/outputs/sampling/base.py                               78     21    73%

merlin/models/tf/outputs/sampling/in_batch.py                           37      1    97%

merlin/models/tf/outputs/sampling/popularity.py                         27      1    96%

merlin/models/tf/outputs/topk.py                                        98      6    94%

merlin/models/tf/prediction_tasks/init.py                            0      0   100%

merlin/models/tf/prediction_tasks/base.py                              207     37    82%

merlin/models/tf/prediction_tasks/classification.py                     68     17    75%

merlin/models/tf/prediction_tasks/multi.py                               7      0   100%

merlin/models/tf/prediction_tasks/next_item.py                          59      6    90%

merlin/models/tf/prediction_tasks/regression.py                         35      2    94%

merlin/models/tf/prediction_tasks/retrieval.py                          73      3    96%

merlin/models/tf/transformers/init.py                                0      0   100%

merlin/models/tf/transformers/block.py                                 101      2    98%

merlin/models/tf/transformers/transforms.py                             63      0   100%

merlin/models/tf/transforms/init.py                                  0      0   100%

merlin/models/tf/transforms/bias.py                                    111      9    92%

merlin/models/tf/transforms/features.py                                435     36    92%

merlin/models/tf/transforms/negative_sampling.py                        77      3    96%

merlin/models/tf/transforms/noise.py                                    43      1    98%

merlin/models/tf/transforms/regularization.py                           17      1    94%

merlin/models/tf/transforms/sequence.py                                282     42    85%

merlin/models/tf/transforms/tensor.py                                  158     13    92%

merlin/models/tf/typing.py                                               7      0   100%

merlin/models/tf/utils/init.py                                       0      0   100%

merlin/models/tf/utils/batch_utils.py                                   85      4    95%

merlin/models/tf/utils/repr_utils.py                                    69      4    94%

merlin/models/tf/utils/search_utils.py                                  34     22    35%

merlin/models/tf/utils/testing_utils.py                                206     36    83%

merlin/models/tf/utils/tf_utils.py                                     209     42    80%

merlin/models/torch/init.py                                         12      0   100%

merlin/models/torch/block/init.py                                    0      0   100%

merlin/models/torch/block/base.py                                      167     32    81%

merlin/models/torch/block/mlp.py                                        38      5    87%

merlin/models/torch/dataset.py                                          68      5    93%

merlin/models/torch/features/init.py                                 0      0   100%

merlin/models/torch/features/base.py                                     4      0   100%

merlin/models/torch/features/continuous.py                              22      0   100%

merlin/models/torch/features/embedding.py                              165     12    93%

merlin/models/torch/features/tabular.py                                 65      8    88%

merlin/models/torch/losses.py                                           28     28     0%

merlin/models/torch/model/init.py                                    0      0   100%

merlin/models/torch/model/base.py                                      286     65    77%

merlin/models/torch/model/prediction_task.py                            24      0   100%

merlin/models/torch/tabular/init.py                                  0      0   100%

merlin/models/torch/tabular/aggregation.py                              75      0   100%

merlin/models/torch/tabular/base.py                                    247     39    84%

merlin/models/torch/tabular/transformations.py                          67      3    96%

merlin/models/torch/typing.py                                            6      0   100%

merlin/models/torch/utils/init.py                                    0      0   100%

merlin/models/torch/utils/data_utils.py                                117    117     0%

merlin/models/torch/utils/examples_utils.py                             39     39     0%

merlin/models/torch/utils/torch_utils.py                                80     22    72%

merlin/models/utils/init.py                                          0      0   100%

merlin/models/utils/constants.py                                         3      0   100%

merlin/models/utils/dataset.py                                          38      4    89%

merlin/models/utils/dependencies.py                                     26     19    27%

merlin/models/utils/doc_utils.py                                        10      0   100%

merlin/models/utils/example_utils.py                                    31      2    94%

merlin/models/utils/misc_utils.py                                      118     90    24%

merlin/models/utils/nvt_utils.py                                        27     24    11%

merlin/models/utils/registry.py                                        101     29    71%

merlin/models/utils/schema_utils.py                                     90     19    79%

merlin/models/xgb/init.py                                          124      4    97%
TOTAL                                                                11581   2344    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.

========= 870 passed, 13 skipped, 1452 warnings in 1780.50s (0:29:40) ==========

___________________________________ 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/jenkins6595613063681890580.sh

nvidia-merlin-bot · 2022-11-21T22:19:18Z

Click to view CI Results

GitHub pull request #887 of commit fa2c6ac322a98dbfbb36bef3ea8ddf6b53c6690f, no merge conflicts.
Running as SYSTEM
Setting status of fa2c6ac322a98dbfbb36bef3ea8ddf6b53c6690f to PENDING with url http://merlin-infra1.nvidia.com:8080/job/merlin_models/1914/ 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/887/*:refs/remotes/origin/pr/887/* # timeout=10
 > git rev-parse fa2c6ac322a98dbfbb36bef3ea8ddf6b53c6690f^{commit} # timeout=10
Checking out Revision fa2c6ac322a98dbfbb36bef3ea8ddf6b53c6690f (detached)
 > git config core.sparsecheckout # timeout=10
 > git checkout -f fa2c6ac322a98dbfbb36bef3ea8ddf6b53c6690f # timeout=10
Commit message: "Merge branch 'main' into fix-two-tower-model-load-context-variable"
 > git rev-list --no-walk 09cc67486c387e9b20a6ae47814195cd3f474d94 # timeout=10
[merlin_models] $ /bin/bash /tmp/jenkins8688626355095403708.sh
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Requirement already satisfied: testbook in /usr/local/lib/python3.8/dist-packages (0.4.2)
Requirement already satisfied: nbclient>=0.4.0 in /usr/local/lib/python3.8/dist-packages (from testbook) (0.6.8)
Requirement already satisfied: nbformat>=5.0.4 in /usr/local/lib/python3.8/dist-packages (from testbook) (5.5.0)
Requirement already satisfied: nest-asyncio in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (1.5.5)
Requirement already satisfied: traitlets>=5.2.2 in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (5.4.0)
Requirement already satisfied: jupyter-client>=6.1.5 in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (7.3.5)
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Requirement already satisfied: jupyter_core in /usr/local/lib/python3.8/dist-packages (from nbformat>=5.0.4->testbook) (4.11.1)
Requirement already satisfied: pkgutil-resolve-name>=1.3.10 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (1.3.10)
Requirement already satisfied: importlib-resources>=1.4.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (5.9.0)
Requirement already satisfied: pyrsistent!=0.17.0,!=0.17.1,!=0.17.2,>=0.14.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (0.18.1)
Requirement already satisfied: attrs>=17.4.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (22.1.0)
Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (2.8.2)
Requirement already satisfied: tornado>=6.2 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (6.2)
Requirement already satisfied: entrypoints in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (0.4)
Requirement already satisfied: pyzmq>=23.0 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (24.0.0)
Requirement already satisfied: zipp>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from importlib-resources>=1.4.0->jsonschema>=2.6->nbformat>=5.0.4->testbook) (3.8.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.8.2->jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (1.15.0)
GLOB sdist-make: /var/jenkins_home/workspace/merlin_models/models/setup.py
py38-gpu recreate: /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
py38-gpu installdeps: -rrequirements/dev.txt, tensorflow<2.10
WARNING: Discarding $PYTHONPATH from environment, to override specify PYTHONPATH in 'passenv' in your configuration.
py38-gpu inst: /var/jenkins_home/workspace/merlin_models/models/.tox/.tmp/package/4/merlin-models-0.9.0+60.gfa2c6ac3.zip
WARNING: Discarding $PYTHONPATH from environment, to override specify PYTHONPATH in 'passenv' in your configuration.
py38-gpu installed: absl-py==1.2.0,aiohttp==3.8.1,aiosignal==1.2.0,alabaster==0.7.12,alembic==1.8.1,anyio==3.6.1,appdirs==1.4.4,argon2-cffi==21.3.0,argon2-cffi-bindings==21.2.0,astroid==2.5.6,asttokens==2.0.8,astunparse==1.6.3,asv==0.5.1,asvdb==0.4.2,async-timeout==4.0.2,attrs==22.1.0,autopage==0.5.1,awscli==1.27.13,Babel==2.10.3,backcall==0.2.0,beautifulsoup4==4.11.1,betterproto==1.2.5,black==20.8b1,bleach==5.0.1,bokeh==3.0.2,boto3==1.24.75,botocore==1.29.13,Brotli==1.0.9,build==0.9.0,cachetools==5.2.0,certifi==2019.11.28,cffi==1.15.1,chardet==3.0.4,charset-normalizer==2.1.1,check-manifest==0.48,clang==5.0,click==8.1.3,cliff==4.1.0,cloudpickle==2.2.0,cmaes==0.9.0,cmake==3.24.1.1,cmd2==2.4.2,colorama==0.4.4,colorlog==6.7.0,contourpy==1.0.5,coverage==6.5.0,cuda-python==11.7.1,cupy-cuda117==10.6.0,cycler==0.11.0,Cython==0.29.32,dask==2022.5.1,dbus-python==1.2.16,debugpy==1.6.3,decorator==5.1.1,defusedxml==0.7.1,dill==0.3.5.1,distlib==0.3.6,distributed==2022.5.1,distro==1.7.0,dm-tree==0.1.6,docker-pycreds==0.4.0,docutils==0.16,emoji==1.7.0,entrypoints==0.4,execnet==1.9.0,executing==1.0.0,faiss==1.7.2,faiss-gpu==1.7.2,fastai==2.7.9,fastapi==0.85.0,fastavro==1.6.1,fastcore==1.5.27,fastdownload==0.0.7,fastjsonschema==2.16.1,fastprogress==1.0.3,fastrlock==0.8,feast==0.19.4,fiddle==0.2.2,filelock==3.8.0,flake8==5.0.4,flatbuffers==1.12,fonttools==4.37.3,frozenlist==1.3.1,fsspec==2022.5.0,gast==0.4.0,gevent==21.12.0,geventhttpclient==2.0.2,gitdb==4.0.9,GitPython==3.1.27,google==3.0.0,google-api-core==2.10.1,google-auth==2.11.1,google-auth-oauthlib==0.4.6,google-pasta==0.2.0,googleapis-common-protos==1.52.0,graphviz==0.20.1,greenlet==1.1.3,grpcio==1.41.0,grpcio-channelz==1.49.0,grpcio-reflection==1.48.1,grpclib==0.4.3,h11==0.13.0,h2==4.1.0,h5py==3.7.0,HeapDict==1.0.1,horovod==0.26.1,hpack==4.0.0,httptools==0.5.0,hugectr2onnx==0.0.0,huggingface-hub==0.9.1,hyperframe==6.0.1,idna==2.8,imagesize==1.4.1,implicit==0.6.1,importlib-metadata==4.12.0,importlib-resources==5.9.0,iniconfig==1.1.1,interrogate==1.5.0,ipykernel==6.15.3,ipython==8.5.0,ipython-genutils==0.2.0,ipywidgets==7.7.0,isort==5.10.1,jedi==0.18.1,Jinja2==3.1.2,jmespath==1.0.1,joblib==1.2.0,json5==0.9.10,jsonschema==4.16.0,jupyter==1.0.0,jupyter-cache==0.4.3,jupyter-console==6.4.4,jupyter-core==4.11.1,jupyter-server==1.18.1,jupyter-server-mathjax==0.2.5,jupyter-sphinx==0.3.2,jupyter_client==7.3.5,jupyterlab==3.4.7,jupyterlab-pygments==0.2.2,jupyterlab-widgets==1.1.0,jupyterlab_server==2.15.1,keras==2.9.0,Keras-Preprocessing==1.1.2,kiwisolver==1.4.4,lazy-object-proxy==1.8.0,libclang==14.0.6,libcst==0.4.7,lightfm==1.16,lightgbm==3.3.2,linkify-it-py==1.0.3,llvmlite==0.39.1,locket==1.0.0,lxml==4.9.1,Mako==1.2.4,Markdown==3.4.1,markdown-it-py==1.1.0,MarkupSafe==2.1.1,matplotlib==3.6.0,matplotlib-inline==0.1.6,mccabe==0.7.0,mdit-py-plugins==0.2.8,merlin-core==0.6.0+1.g5926fcf,merlin-dataloader==0.0.2,merlin-models==0.9.0+60.gfa2c6ac3,merlin-systems==0.5.0+4.g15074ad,mistune==2.0.4,mmh3==3.0.0,mpi4py==3.1.3,msgpack==1.0.4,multidict==6.0.2,mypy==0.991,mypy-extensions==0.4.3,myst-nb==0.13.2,myst-parser==0.15.2,natsort==8.1.0,nbclassic==0.4.3,nbclient==0.6.8,nbconvert==7.0.0,nbdime==3.1.1,nbformat==5.5.0,nest-asyncio==1.5.5,ninja==1.10.2.3,notebook==6.4.12,notebook-shim==0.1.0,numba==0.56.2,numpy==1.22.4,nvidia-pyindex==1.0.9,nvtabular @ git+https://github.com/NVIDIA-Merlin/NVTabular.git@e5b7351deb9e4885c4038aa0bbc9f146d8477a0e,nvtx==0.2.5,oauthlib==3.2.1,oldest-supported-numpy==2022.8.16,onnx==1.12.0,onnxruntime==1.11.1,opt-einsum==3.3.0,optuna==3.0.3,packaging==21.3,pandas==1.3.5,pandavro==1.5.2,pandocfilters==1.5.0,parso==0.8.3,partd==1.3.0,pathspec==0.10.2,pathtools==0.1.2,pbr==5.11.0,pep517==0.13.0,pexpect==4.8.0,pickleshare==0.7.5,Pillow==9.2.0,pkgutil_resolve_name==1.3.10,platformdirs==2.5.2,plotly==5.11.0,pluggy==1.0.0,prettytable==3.5.0,prometheus-client==0.14.1,promise==2.3,prompt-toolkit==3.0.31,proto-plus==1.19.6,protobuf==3.19.5,psutil==5.9.2,ptyprocess==0.7.0,pure-eval==0.2.2,py==1.11.0,pyarrow==7.0.0,pyasn1==0.4.8,pyasn1-modules==0.2.8,pybind11==2.10.0,pycodestyle==2.9.1,pycparser==2.21,pydantic==1.10.2,pydot==1.4.2,pyflakes==2.5.0,Pygments==2.13.0,PyGObject==3.36.0,pynvml==11.4.1,pyparsing==3.0.9,pyperclip==1.8.2,pyrsistent==0.18.1,pytest==7.1.3,pytest-cov==4.0.0,pytest-xdist==3.0.2,python-apt==2.0.0+ubuntu0.20.4.8,python-dateutil==2.8.2,python-dotenv==0.21.0,python-rapidjson==1.8,pytz==2022.2.1,PyYAML==5.4.1,pyzmq==24.0.0,qtconsole==5.4.0,QtPy==2.3.0,regex==2022.9.13,requests==2.22.0,requests-oauthlib==1.3.1,requests-unixsocket==0.2.0,rsa==4.7.2,s3fs==2022.2.0,s3transfer==0.6.0,sacremoses==0.0.53,scikit-build==0.15.0,scikit-learn==1.1.2,scipy==1.8.1,seedir==0.3.0,Send2Trash==1.8.0,sentry-sdk==1.9.8,setproctitle==1.3.2,setuptools-scm==7.0.5,shortuuid==1.0.9,six==1.15.0,sklearn==0.0,smmap==5.0.0,sniffio==1.3.0,snowballstemmer==2.2.0,sortedcontainers==2.4.0,soupsieve==2.3.2.post1,Sphinx==5.3.0,sphinx-multiversion==0.2.4,sphinx-togglebutton==0.3.1,sphinx_external_toc==0.3.0,sphinxcontrib-applehelp==1.0.2,sphinxcontrib-copydirs @ git+https://github.com/mikemckiernan/sphinxcontrib-copydirs.git@bd8c5d79b3f91cf5f1bb0d6995aeca3fe84b670e,sphinxcontrib-devhelp==1.0.2,sphinxcontrib-htmlhelp==2.0.0,sphinxcontrib-jsmath==1.0.1,sphinxcontrib-qthelp==1.0.3,sphinxcontrib-serializinghtml==1.1.5,SQLAlchemy==1.4.44,stack-data==0.5.0,starlette==0.20.4,stevedore==4.1.1,stringcase==1.2.0,supervisor==4.1.0,tabulate==0.8.10,tblib==1.7.0,tdqm==0.0.1,tenacity==8.0.1,tensorboard==2.9.1,tensorboard-data-server==0.6.1,tensorboard-plugin-wit==1.8.1,tensorflow==2.9.2,tensorflow-estimator==2.9.0,tensorflow-gpu==2.9.2,tensorflow-io-gcs-filesystem==0.27.0,tensorflow-metadata==1.10.0,termcolor==2.0.1,terminado==0.15.0,testbook==0.4.2,threadpoolctl==3.1.0,tinycss2==1.1.1,tokenizers==0.10.3,toml==0.10.2,tomli==2.0.1,toolz==0.12.0,torch==1.12.1+cu113,torchmetrics==0.3.2,tornado==6.2,tox==3.26.0,tqdm==4.64.1,traitlets==5.4.0,transformers==4.12.0,transformers4rec==0.1.12+2.gbcc939255,treelite==2.3.0,treelite-runtime==2.3.0,tritonclient==2.25.0,typed-ast==1.5.4,typing-inspect==0.8.0,typing_extensions==4.3.0,uc-micro-py==1.0.1,urllib3==1.26.12,uvicorn==0.18.3,uvloop==0.17.0,versioneer==0.20,virtualenv==20.16.5,wandb==0.13.3,watchfiles==0.17.0,wcwidth==0.2.5,webencodings==0.5.1,websocket-client==1.4.1,websockets==10.3,Werkzeug==2.2.2,widgetsnbextension==3.6.0,wrapt==1.12.1,xgboost==1.6.2,xyzservices==2022.9.0,yarl==1.8.1,zict==2.2.0,zipp==3.8.1,zope.event==4.5.0,zope.interface==5.4.0
py38-gpu run-test-pre: PYTHONHASHSEED='2258835642'
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-oa3t_2rd
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/core.git /tmp/pip-req-build-oa3t_2rd
  Resolved https://github.com/NVIDIA-Merlin/core.git to commit 04ff5225cee6af90b6b08070493677ac53b96836
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: packaging in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+16.g04ff522) (21.3)
Requirement already satisfied: distributed>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+16.g04ff522) (2022.3.0)
Requirement already satisfied: numba>=0.54 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+16.g04ff522) (0.55.1)
Requirement already satisfied: dask>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+16.g04ff522) (2022.3.0)
Requirement already satisfied: betterproto<2.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+16.g04ff522) (1.2.5)
Requirement already satisfied: fsspec==2022.5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+16.g04ff522) (2022.5.0)
Requirement already satisfied: tensorflow-metadata>=1.2.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+16.g04ff522) (1.10.0)
Requirement already satisfied: tqdm>=4.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+16.g04ff522) (4.64.1)
Requirement already satisfied: protobuf>=3.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+16.g04ff522) (3.19.5)
Requirement already satisfied: pandas<1.4.0dev0,>=1.2.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+16.g04ff522) (1.3.5)
Requirement already satisfied: pyarrow>=5.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+16.g04ff522) (7.0.0)
Requirement already satisfied: grpclib in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core==0.8.0+16.g04ff522) (0.4.3)
Requirement already satisfied: stringcase in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core==0.8.0+16.g04ff522) (1.2.0)
Requirement already satisfied: cloudpickle>=1.1.1 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (2.2.0)
Requirement already satisfied: partd>=0.3.10 in /var/jenkins_home/.local/lib/python3.8/site-packages/partd-1.2.0-py3.8.egg (from dask>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (1.2.0)
Requirement already satisfied: pyyaml>=5.3.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/PyYAML-5.4.1-py3.8-linux-x86_64.egg (from dask>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (5.4.1)
Requirement already satisfied: toolz>=0.8.2 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (0.12.0)
Requirement already satisfied: tornado>=6.0.3 in ./.tox/py38-gpu/lib/python3.8/site-packages (from distributed>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (6.2)
Requirement already satisfied: zict>=0.1.3 in /var/jenkins_home/.local/lib/python3.8/site-packages/zict-2.0.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (2.0.0)
Requirement already satisfied: jinja2 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (3.1.2)
Requirement already satisfied: psutil>=5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/psutil-5.8.0-py3.8-linux-x86_64.egg (from distributed>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (5.8.0)
Requirement already satisfied: click>=6.6 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (8.1.3)
Requirement already satisfied: tblib>=1.6.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/tblib-1.7.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (1.7.0)
Requirement already satisfied: sortedcontainers!=2.0.0,!=2.0.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/sortedcontainers-2.4.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (2.4.0)
Requirement already satisfied: msgpack>=0.6.0 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (1.0.4)
Requirement already satisfied: llvmlite<0.39,>=0.38.0rc1 in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+16.g04ff522) (0.38.1)
Requirement already satisfied: numpy<1.22,>=1.18 in /var/jenkins_home/.local/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+16.g04ff522) (1.20.3)
Requirement already satisfied: setuptools in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+16.g04ff522) (65.5.1)
Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in /usr/local/lib/python3.8/dist-packages (from packaging->merlin-core==0.8.0+16.g04ff522) (3.0.9)
Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+16.g04ff522) (2.8.2)
Requirement already satisfied: pytz>=2017.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+16.g04ff522) (2022.2.1)
Requirement already satisfied: googleapis-common-protos<2,>=1.52.0 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core==0.8.0+16.g04ff522) (1.52.0)
Requirement already satisfied: absl-py<2.0.0,>=0.9 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core==0.8.0+16.g04ff522) (1.2.0)
Requirement already satisfied: locket in /var/jenkins_home/.local/lib/python3.8/site-packages/locket-0.2.1-py3.8.egg (from partd>=0.3.10->dask>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (0.2.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.7.3->pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+16.g04ff522) (1.15.0)
Requirement already satisfied: heapdict in /var/jenkins_home/.local/lib/python3.8/site-packages/HeapDict-1.0.1-py3.8.egg (from zict>=0.1.3->distributed>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (1.0.1)
Requirement already satisfied: h2<5,>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core==0.8.0+16.g04ff522) (4.1.0)
Requirement already satisfied: multidict in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core==0.8.0+16.g04ff522) (6.0.2)
Requirement already satisfied: MarkupSafe>=2.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from jinja2->distributed>=2022.3.0->merlin-core==0.8.0+16.g04ff522) (2.0.1)
Requirement already satisfied: hpack<5,>=4.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core==0.8.0+16.g04ff522) (4.0.0)
Requirement already satisfied: hyperframe<7,>=6.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core==0.8.0+16.g04ff522) (6.0.1)
Building wheels for collected packages: merlin-core
  Building wheel for merlin-core (pyproject.toml): started
  Building wheel for merlin-core (pyproject.toml): finished with status 'done'
  Created wheel for merlin-core: filename=merlin_core-0.8.0+16.g04ff522-py3-none-any.whl size=118833 sha256=48e526d9ba994227775b22691e3a7cb0588086bd42b2cb7379656875a2dc90ff
  Stored in directory: /tmp/pip-ephem-wheel-cache-jymsoyn5/wheels/c8/38/16/a6968787eafcec5fa772148af8408b089562f71af0752e8e84
Successfully built merlin-core
Installing collected packages: merlin-core
  Attempting uninstall: merlin-core
    Found existing installation: merlin-core 0.3.0+12.g78ecddd
    Not uninstalling merlin-core at /var/jenkins_home/.local/lib/python3.8/site-packages, outside environment /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
    Can't uninstall 'merlin-core'. No files were found to uninstall.
Successfully installed merlin-core-0.8.0+16.g04ff522
py38-gpu run-test: commands[1] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/nvtabular.git
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Collecting git+https://github.com/NVIDIA-Merlin/nvtabular.git
  Cloning https://github.com/NVIDIA-Merlin/nvtabular.git to /tmp/pip-req-build-_cqjsupn
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/nvtabular.git /tmp/pip-req-build-_cqjsupn
  Resolved https://github.com/NVIDIA-Merlin/nvtabular.git to commit e5b7351deb9e4885c4038aa0bbc9f146d8477a0e
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: merlin-dataloader>=0.0.2 in /usr/local/lib/python3.8/dist-packages (from nvtabular==1.6.0+6.ge5b7351d) (0.0.2)
Requirement already satisfied: scipy in /usr/local/lib/python3.8/dist-packages (from nvtabular==1.6.0+6.ge5b7351d) (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+6.ge5b7351d) (0.8.0+16.g04ff522)
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)
Requirement already satisfied: distributed>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+6.ge5b7351d) (2022.3.0)
Requirement already satisfied: 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: dask>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+6.ge5b7351d) (2022.3.0)
Requirement already satisfied: betterproto<2.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+6.ge5b7351d) (1.2.5)
Requirement already satisfied: fsspec==2022.5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+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: tqdm>=4.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+6.ge5b7351d) (4.64.1)
Requirement already satisfied: protobuf>=3.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+6.ge5b7351d) (3.19.5)
Requirement already satisfied: pandas<1.4.0dev0,>=1.2.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+6.ge5b7351d) (1.3.5)
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+6.ge5b7351d) (7.0.0)
Requirement already satisfied: numpy<1.25.0,>=1.17.3 in /var/jenkins_home/.local/lib/python3.8/site-packages (from scipy->nvtabular==1.6.0+6.ge5b7351d) (1.20.3)
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+6.ge5b7351d) (0.4.3)
Requirement already satisfied: stringcase in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core>=0.2.0->nvtabular==1.6.0+6.ge5b7351d) (1.2.0)
Requirement already satisfied: cloudpickle>=1.1.1 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+6.ge5b7351d) (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>=0.2.0->nvtabular==1.6.0+6.ge5b7351d) (1.2.0)
Requirement already satisfied: pyyaml>=5.3.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/PyYAML-5.4.1-py3.8-linux-x86_64.egg (from dask>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+6.ge5b7351d) (5.4.1)
Requirement already satisfied: toolz>=0.8.2 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+6.ge5b7351d) (0.12.0)
Requirement already satisfied: tornado>=6.0.3 in ./.tox/py38-gpu/lib/python3.8/site-packages (from distributed>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+6.ge5b7351d) (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>=0.2.0->nvtabular==1.6.0+6.ge5b7351d) (2.0.0)
Requirement already satisfied: jinja2 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+6.ge5b7351d) (3.1.2)
Requirement already satisfied: psutil>=5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/psutil-5.8.0-py3.8-linux-x86_64.egg (from distributed>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+6.ge5b7351d) (5.8.0)
Requirement already satisfied: click>=6.6 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+6.ge5b7351d) (8.1.3)
Requirement already satisfied: tblib>=1.6.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/tblib-1.7.0-py3.8.egg (from distributed>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+6.ge5b7351d) (1.7.0)
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Building wheels for collected packages: nvtabular
  Building wheel for nvtabular (pyproject.toml): started
  Building wheel for nvtabular (pyproject.toml): finished with status 'done'
  Created wheel for nvtabular: filename=nvtabular-1.6.0+6.ge5b7351d-cp38-cp38-linux_x86_64.whl size=257597 sha256=15157cf748ae202e10e383c5bec8398dbc59cc490a886ca61225b746c9ba1b50
  Stored in directory: /tmp/pip-ephem-wheel-cache-dab4jbee/wheels/8f/d9/f9/30f2cdc5bf8787fae6fdfe55afd6e1b493e619ec32c32ec40b
Successfully built nvtabular
Installing collected packages: nvtabular
  Attempting uninstall: nvtabular
    Found existing installation: nvtabular 1.1.1
    Not uninstalling nvtabular at /var/jenkins_home/.local/lib/python3.8/site-packages, outside environment /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
    Can't uninstall 'nvtabular'. No files were found to uninstall.
Successfully installed nvtabular-1.6.0+6.ge5b7351d
py38-gpu run-test: commands[2] | python -m pytest --cov-report term --cov merlin -rxs tests/unit
============================= test session starts ==============================
platform linux -- Python 3.8.10, pytest-7.1.3, pluggy-1.0.0
cachedir: .tox/py38-gpu/.pytest_cache
rootdir: /var/jenkins_home/workspace/merlin_models/models, configfile: pyproject.toml
plugins: anyio-3.5.0, xdist-3.0.2, cov-4.0.0
collected 883 items
tests/unit/config/test_schema.py ....                                    [  0%]

tests/unit/datasets/test_advertising.py .s                               [  0%]

tests/unit/datasets/test_ecommerce.py ..sss.s                            [  1%]

tests/unit/datasets/test_entertainment.py ....sss.                       [  2%]

tests/unit/datasets/test_social.py .                                     [  2%]

tests/unit/datasets/test_synthetic.py ..........                         [  3%]

tests/unit/implicit/test_implicit.py .                                   [  3%]

tests/unit/lightfm/test_lightfm.py .                                     [  3%]

tests/unit/tf/test_core.py ......                                        [  4%]

tests/unit/tf/test_loader.py ................                            [  6%]

tests/unit/tf/test_public_api.py .                                       [  6%]

tests/unit/tf/blocks/test_cross.py ...........                           [  7%]

tests/unit/tf/blocks/test_dlrm.py ..........                             [  8%]

tests/unit/tf/blocks/test_interactions.py ...                            [  9%]

tests/unit/tf/blocks/test_mlp.py ....................................... [ 13%]

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tests/unit/tf/blocks/test_optimizer.py s................................ [ 20%]

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tests/unit/tf/blocks/retrieval/test_base.py .                            [ 22%]

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py ..           [ 23%]

tests/unit/tf/blocks/retrieval/test_two_tower.py ............            [ 24%]

tests/unit/tf/blocks/sampling/test_cross_batch.py .                      [ 24%]

tests/unit/tf/blocks/sampling/test_in_batch.py .                         [ 24%]

tests/unit/tf/core/test_aggregation.py .........                         [ 25%]

tests/unit/tf/core/test_base.py ..                                       [ 26%]

tests/unit/tf/core/test_combinators.py s.....................            [ 28%]

tests/unit/tf/core/test_encoder.py ..                                    [ 28%]

tests/unit/tf/core/test_index.py ...                                     [ 29%]

tests/unit/tf/core/test_prediction.py ..                                 [ 29%]

tests/unit/tf/core/test_tabular.py ......                                [ 30%]

tests/unit/tf/examples/test_01_getting_started.py .                      [ 30%]

tests/unit/tf/examples/test_02_dataschema.py .                           [ 30%]

tests/unit/tf/examples/test_03_exploring_different_models.py .           [ 30%]

tests/unit/tf/examples/test_04_export_ranking_models.py .                [ 30%]

tests/unit/tf/examples/test_05_export_retrieval_model.py .               [ 30%]

tests/unit/tf/examples/test_06_advanced_own_architecture.py .            [ 30%]

tests/unit/tf/examples/test_07_train_traditional_models.py .             [ 30%]

tests/unit/tf/examples/test_usecase_accelerate_training_by_lazyadam.py . [ 30%]

[ 30%]

tests/unit/tf/examples/test_usecase_ecommerce_session_based.py .         [ 31%]

tests/unit/tf/examples/test_usecase_incremental_training_layer_freezing.py . [ 31%]

[ 31%]

tests/unit/tf/examples/test_usecase_pretrained_embeddings.py .           [ 31%]

tests/unit/tf/examples/test_usecase_retrieval_with_hpo.py .              [ 31%]

tests/unit/tf/examples/test_usecase_transformers_next_item_prediction.py . [ 31%]

[ 31%]

tests/unit/tf/horovod/test_horovod.py ...                                [ 31%]

tests/unit/tf/inputs/test_base.py .                                      [ 31%]

tests/unit/tf/inputs/test_continuous.py ........                         [ 32%]

tests/unit/tf/inputs/test_embedding.py ................................. [ 36%]

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tests/unit/tf/inputs/test_tabular.py ..................                  [ 39%]

tests/unit/tf/layers/test_queue.py ..............                        [ 41%]

tests/unit/tf/losses/test_losses.py .......................              [ 43%]

tests/unit/tf/metrics/test_metrics_popularity.py .....                   [ 44%]

tests/unit/tf/metrics/test_metrics_topk.py .........................     [ 47%]

tests/unit/tf/models/test_base.py s.........................             [ 50%]

tests/unit/tf/models/test_benchmark.py ..                                [ 50%]

tests/unit/tf/models/test_ranking.py ..................................  [ 54%]

tests/unit/tf/models/test_retrieval.py ................................. [ 57%]

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tests/unit/tf/outputs/test_base.py ......                                [ 63%]

tests/unit/tf/outputs/test_classification.py ......                      [ 64%]

tests/unit/tf/outputs/test_contrastive.py ..............                 [ 65%]

tests/unit/tf/outputs/test_regression.py ..                              [ 65%]

tests/unit/tf/outputs/test_sampling.py ....                              [ 66%]

tests/unit/tf/outputs/test_topk.py .                                     [ 66%]

tests/unit/tf/prediction_tasks/test_classification.py ..                 [ 66%]

tests/unit/tf/prediction_tasks/test_multi_task.py ................       [ 68%]

tests/unit/tf/prediction_tasks/test_next_item.py .....                   [ 69%]

tests/unit/tf/prediction_tasks/test_regression.py .....                  [ 69%]

tests/unit/tf/prediction_tasks/test_retrieval.py .                       [ 69%]

tests/unit/tf/prediction_tasks/test_sampling.py ......                   [ 70%]

tests/unit/tf/transformers/test_block.py ......................          [ 72%]

tests/unit/tf/transformers/test_transforms.py ..........                 [ 74%]

tests/unit/tf/transforms/test_bias.py ..                                 [ 74%]

tests/unit/tf/transforms/test_features.py s............................. [ 77%]

.......................s......                                           [ 81%]

tests/unit/tf/transforms/test_negative_sampling.py .........             [ 82%]

tests/unit/tf/transforms/test_noise.py .....                             [ 82%]

tests/unit/tf/transforms/test_sequence.py ....................           [ 84%]

tests/unit/tf/transforms/test_tensor.py ...                              [ 85%]

tests/unit/tf/utils/test_batch.py ....                                   [ 85%]

tests/unit/tf/utils/test_dataset.py ..                                   [ 85%]

tests/unit/tf/utils/test_tf_utils.py .....                               [ 86%]

tests/unit/torch/test_dataset.py .........                               [ 87%]

tests/unit/torch/test_public_api.py .                                    [ 87%]

tests/unit/torch/block/test_base.py ....                                 [ 88%]

tests/unit/torch/block/test_mlp.py .                                     [ 88%]

tests/unit/torch/features/test_continuous.py ..                          [ 88%]

tests/unit/torch/features/test_embedding.py ..............               [ 90%]

tests/unit/torch/features/test_tabular.py ....                           [ 90%]

tests/unit/torch/model/test_head.py ............                         [ 91%]

tests/unit/torch/model/test_model.py ..                                  [ 92%]

tests/unit/torch/tabular/test_aggregation.py ........                    [ 92%]

tests/unit/torch/tabular/test_tabular.py ...                             [ 93%]

tests/unit/torch/tabular/test_transformations.py .......                 [ 94%]

tests/unit/utils/test_schema_utils.py ................................   [ 97%]

tests/unit/xgb/test_xgboost.py ....................                      [100%]
=============================== warnings summary ===============================

../../../../../usr/lib/python3/dist-packages/requests/init.py:89

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

warnings.warn("urllib3 ({}) or chardet ({}) doesn't match a supported "
../../../.local/lib/python3.8/site-packages/flatbuffers/compat.py:19

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

import imp
../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36

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

'nearest': pil_image.NEAREST,
../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37

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

'bilinear': pil_image.BILINEAR,
../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38

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

'bicubic': pil_image.BICUBIC,
../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39

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

'hamming': pil_image.HAMMING,
../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40

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

'box': pil_image.BOX,
../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41

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

'lanczos': pil_image.LANCZOS,
tests/unit/datasets/test_advertising.py: 1 warning

tests/unit/datasets/test_ecommerce.py: 3 warnings

tests/unit/datasets/test_entertainment.py: 4 warnings

tests/unit/datasets/test_social.py: 1 warning

tests/unit/datasets/test_synthetic.py: 10 warnings

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_core.py: 6 warnings

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/test_cross.py: 5 warnings

tests/unit/tf/blocks/test_dlrm.py: 9 warnings

tests/unit/tf/blocks/test_interactions.py: 2 warnings

tests/unit/tf/blocks/test_mlp.py: 60 warnings

tests/unit/tf/blocks/test_optimizer.py: 30 warnings

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings

tests/unit/tf/core/test_aggregation.py: 6 warnings

tests/unit/tf/core/test_base.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 6 warnings

tests/unit/tf/core/test_index.py: 8 warnings

tests/unit/tf/core/test_prediction.py: 2 warnings

tests/unit/tf/horovod/test_horovod.py: 3 warnings

tests/unit/tf/inputs/test_base.py: 1 warning

tests/unit/tf/inputs/test_continuous.py: 7 warnings

tests/unit/tf/inputs/test_embedding.py: 20 warnings

tests/unit/tf/inputs/test_tabular.py: 18 warnings

tests/unit/tf/models/test_base.py: 28 warnings

tests/unit/tf/models/test_benchmark.py: 2 warnings

tests/unit/tf/models/test_ranking.py: 38 warnings

tests/unit/tf/models/test_retrieval.py: 121 warnings

tests/unit/tf/outputs/test_base.py: 6 warnings

tests/unit/tf/outputs/test_classification.py: 6 warnings

tests/unit/tf/outputs/test_contrastive.py: 19 warnings

tests/unit/tf/outputs/test_regression.py: 2 warnings

tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings

tests/unit/tf/prediction_tasks/test_retrieval.py: 1 warning

tests/unit/tf/transformers/test_block.py: 16 warnings

tests/unit/tf/transforms/test_bias.py: 2 warnings

tests/unit/tf/transforms/test_features.py: 10 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings

tests/unit/tf/transforms/test_noise.py: 1 warning

tests/unit/tf/transforms/test_sequence.py: 15 warnings

tests/unit/tf/utils/test_batch.py: 9 warnings

tests/unit/tf/utils/test_dataset.py: 2 warnings

tests/unit/torch/block/test_base.py: 4 warnings

tests/unit/torch/block/test_mlp.py: 1 warning

tests/unit/torch/features/test_continuous.py: 1 warning

tests/unit/torch/features/test_embedding.py: 4 warnings

tests/unit/torch/features/test_tabular.py: 4 warnings

tests/unit/torch/model/test_head.py: 12 warnings

tests/unit/torch/model/test_model.py: 2 warnings

tests/unit/torch/tabular/test_aggregation.py: 6 warnings

tests/unit/torch/tabular/test_transformations.py: 3 warnings

tests/unit/xgb/test_xgboost.py: 18 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.ITEM_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.ITEM: 'item'>, <Tags.ID: 'id'>].

warnings.warn(
tests/unit/datasets/test_ecommerce.py: 3 warnings

tests/unit/datasets/test_entertainment.py: 4 warnings

tests/unit/datasets/test_social.py: 1 warning

tests/unit/datasets/test_synthetic.py: 9 warnings

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_core.py: 6 warnings

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/test_cross.py: 5 warnings

tests/unit/tf/blocks/test_dlrm.py: 9 warnings

tests/unit/tf/blocks/test_interactions.py: 2 warnings

tests/unit/tf/blocks/test_mlp.py: 60 warnings

tests/unit/tf/blocks/test_optimizer.py: 30 warnings

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings

tests/unit/tf/core/test_aggregation.py: 6 warnings

tests/unit/tf/core/test_base.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 7 warnings

tests/unit/tf/core/test_index.py: 3 warnings

tests/unit/tf/core/test_prediction.py: 2 warnings

tests/unit/tf/horovod/test_horovod.py: 1 warning

tests/unit/tf/inputs/test_base.py: 1 warning

tests/unit/tf/inputs/test_continuous.py: 7 warnings

tests/unit/tf/inputs/test_embedding.py: 20 warnings

tests/unit/tf/inputs/test_tabular.py: 18 warnings

tests/unit/tf/models/test_base.py: 28 warnings

tests/unit/tf/models/test_benchmark.py: 2 warnings

tests/unit/tf/models/test_ranking.py: 36 warnings

tests/unit/tf/models/test_retrieval.py: 87 warnings

tests/unit/tf/outputs/test_base.py: 6 warnings

tests/unit/tf/outputs/test_classification.py: 6 warnings

tests/unit/tf/outputs/test_contrastive.py: 19 warnings

tests/unit/tf/outputs/test_regression.py: 2 warnings

tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings

tests/unit/tf/transformers/test_block.py: 10 warnings

tests/unit/tf/transforms/test_features.py: 10 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings

tests/unit/tf/transforms/test_sequence.py: 15 warnings

tests/unit/tf/utils/test_batch.py: 7 warnings

tests/unit/tf/utils/test_dataset.py: 2 warnings

tests/unit/torch/block/test_base.py: 4 warnings

tests/unit/torch/block/test_mlp.py: 1 warning

tests/unit/torch/features/test_continuous.py: 1 warning

tests/unit/torch/features/test_embedding.py: 4 warnings

tests/unit/torch/features/test_tabular.py: 4 warnings

tests/unit/torch/model/test_head.py: 12 warnings

tests/unit/torch/model/test_model.py: 2 warnings

tests/unit/torch/tabular/test_aggregation.py: 6 warnings

tests/unit/torch/tabular/test_transformations.py: 2 warnings

tests/unit/xgb/test_xgboost.py: 17 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.USER_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.USER: 'user'>, <Tags.ID: 'id'>].

warnings.warn(
tests/unit/datasets/test_ecommerce.py: 1 warning

tests/unit/datasets/test_entertainment.py: 1 warning

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 2 warnings

tests/unit/tf/core/test_prediction.py: 1 warning

tests/unit/tf/horovod/test_horovod.py: 1 warning

tests/unit/tf/inputs/test_continuous.py: 4 warnings

tests/unit/tf/inputs/test_embedding.py: 9 warnings

tests/unit/tf/inputs/test_tabular.py: 8 warnings

tests/unit/tf/models/test_ranking.py: 20 warnings

tests/unit/tf/models/test_retrieval.py: 10 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 3 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 9 warnings

tests/unit/xgb/test_xgboost.py: 12 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.SESSION_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.SESSION: 'session'>, <Tags.ID: 'id'>].

warnings.warn(
tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export

tests/unit/tf/inputs/test_embedding.py::test_embedding_features_exporting_and_loading_pretrained_initializer

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/inputs/embedding.py:970: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack

embeddings_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(embeddings)))
tests/unit/tf/blocks/retrieval/test_two_tower.py: 1 warning

tests/unit/tf/core/test_index.py: 4 warnings

tests/unit/tf/horovod/test_horovod.py: 3 warnings

tests/unit/tf/models/test_retrieval.py: 59 warnings

tests/unit/tf/prediction_tasks/test_next_item.py: 3 warnings

tests/unit/tf/utils/test_batch.py: 2 warnings

/tmp/autograph_generated_file117a4gdu.py:8: DeprecationWarning: The 'warn' method is deprecated, use 'warning' instead

ag.converted_call(ag__.ld(warnings).warn, ("The 'warn' method is deprecated, use 'warning' instead", ag__.ld(DeprecationWarning), 2), None, fscope)
tests/unit/tf/core/test_combinators.py::test_parallel_block_select_by_tags

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/core/tabular.py:602: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated since Python 3.3, and in 3.10 it will stop working

elif isinstance(self.feature_names, collections.Sequence):
tests/unit/tf/core/test_encoder.py: 1 warning

tests/unit/tf/core/test_index.py: 5 warnings

tests/unit/tf/models/test_retrieval.py: 30 warnings

tests/unit/tf/utils/test_batch.py: 4 warnings

tests/unit/tf/utils/test_dataset.py: 1 warning

/var/jenkins_home/workspace/merlin_models/models/merlin/models/utils/dataset.py:75: DeprecationWarning: unique_rows_by_features is deprecated and will be removed in a future version. Please use unique_by_tag instead.

warnings.warn(
tests/unit/tf/models/test_base.py::test_model_pre_post[True]

tests/unit/tf/models/test_base.py::test_model_pre_post[False]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.1]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.3]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.5]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.7]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/util/dispatch.py:1082: UserWarning: tf.keras.backend.random_binomial is deprecated, and will be removed in a future version.Please use tf.keras.backend.random_bernoulli instead.

return dispatch_target(*args, **kwargs)
tests/unit/tf/models/test_base.py::test_freeze_parallel_block[True]

tests/unit/tf/models/test_base.py::test_freeze_sequential_block

tests/unit/tf/models/test_base.py::test_freeze_unfreeze

tests/unit/tf/models/test_base.py::test_unfreeze_all_blocks

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/gradient_descent.py:108: UserWarning: The lr argument is deprecated, use learning_rate instead.

super(SGD, self).init(name, **kwargs)
tests/unit/tf/models/test_base.py::test_retrieval_model_query

tests/unit/tf/models/test_base.py::test_retrieval_model_query

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_v2_export_embeddings

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[True]

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[False]

tests/unit/tf/transformers/test_block.py::test_retrieval_transformer[True]

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/utils/tf_utils.py:298: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack

tensor_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(tensor)))
tests/unit/tf/models/test_ranking.py::test_deepfm_model_only_categ_feats[False]

tests/unit/tf/models/test_ranking.py::test_deepfm_model_categ_and_continuous_feats[False]

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

warnings.warn(
tests/unit/tf/models/test_ranking.py::test_wide_deep_model[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_categorical_one_hot[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_hashed_cross[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

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

warnings.warn(
tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[True]

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/transforms/features.py:569: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag

warnings.warn(
tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/autograph/impl/api.py:371: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag

return py_builtins.overload_of(f)(*args)
tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_onehot_multihot_feature_interaction[False]

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

warnings.warn(
tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_feature_interaction_multi_optimizer[False]

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

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]

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

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]

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

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]

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

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]

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

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

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

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

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

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

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

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

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

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

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

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

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

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

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

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

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

warnings.warn(
tests/unit/torch/block/test_mlp.py::test_mlp_block

/var/jenkins_home/workspace/merlin_models/models/tests/unit/torch/_conftest.py:151: UserWarning: Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

return {key: torch.tensor(value) for key, value in data.items()}
tests/unit/xgb/test_xgboost.py::test_without_dask_client

tests/unit/xgb/test_xgboost.py::TestXGBoost::test_music_regression

tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs0-DaskDeviceQuantileDMatrix]

tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs1-DaskDMatrix]

tests/unit/xgb/test_xgboost.py::TestEvals::test_multiple

tests/unit/xgb/test_xgboost.py::TestEvals::test_default

tests/unit/xgb/test_xgboost.py::TestEvals::test_train_and_valid

tests/unit/xgb/test_xgboost.py::TestEvals::test_invalid_data

/var/jenkins_home/workspace/merlin_models/models/merlin/models/xgb/init.py:344: UserWarning: Ignoring list columns as inputs to XGBoost model: ['item_genres', 'user_genres'].

warnings.warn(f"Ignoring list columns as inputs to XGBoost model: {list_column_names}.")
tests/unit/xgb/test_xgboost.py::TestXGBoost::test_unsupported_objective

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/tornado/ioloop.py:350: DeprecationWarning: make_current is deprecated; start the event loop first

self.make_current()
tests/unit/xgb/test_xgboost.py: 14 warnings

/usr/local/lib/python3.8/dist-packages/xgboost/dask.py:884: RuntimeWarning: coroutine 'Client._wait_for_workers' was never awaited

client.wait_for_workers(n_workers)

Enable tracemalloc to get traceback where the object was allocated.

See https://docs.pytest.org/en/stable/how-to/capture-warnings.html#resource-warnings for more info.
tests/unit/xgb/test_xgboost.py: 11 warnings

/usr/local/lib/python3.8/dist-packages/cudf/core/dataframe.py:1183: DeprecationWarning: The default dtype for empty Series will be 'object' instead of 'float64' in a future version. Specify a dtype explicitly to silence this warning.

mask = pd.Series(mask)
-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html
---------- coverage: platform linux, python 3.8.10-final-0 -----------

Name                                                                 Stmts   Miss  Cover
merlin/datasets/init.py                                              2      0   100%

merlin/datasets/advertising/init.py                                  2      0   100%

merlin/datasets/advertising/criteo/init.py                           0      0   100%

merlin/datasets/advertising/criteo/dataset.py                           79     49    38%

merlin/datasets/advertising/criteo/transformed/init.py               0      0   100%

merlin/datasets/ecommerce/init.py                                    4      0   100%

merlin/datasets/ecommerce/aliccp/init.py                             0      0   100%

merlin/datasets/ecommerce/aliccp/dataset.py                            141     87    38%

merlin/datasets/ecommerce/aliccp/raw/init.py                         0      0   100%

merlin/datasets/ecommerce/aliccp/transformed/init.py                 0      0   100%

merlin/datasets/ecommerce/booking/init.py                            0      0   100%

merlin/datasets/ecommerce/booking/dataset.py                           127    100    21%

merlin/datasets/ecommerce/booking/raw/init.py                        0      0   100%

merlin/datasets/ecommerce/booking/transformed/init.py                0      0   100%

merlin/datasets/ecommerce/dressipi/init.py                           0      0   100%

merlin/datasets/ecommerce/dressipi/dataset.py                           45     37    18%

merlin/datasets/ecommerce/dressipi/preprocessed/init.py              0      0   100%

merlin/datasets/ecommerce/large/init.py                              0      0   100%

merlin/datasets/ecommerce/small/init.py                              0      0   100%

merlin/datasets/ecommerce/transactions/init.py                       0      0   100%

merlin/datasets/entertainment/init.py                                2      0   100%

merlin/datasets/entertainment/movielens/1m-raw/init.py               0      0   100%

merlin/datasets/entertainment/movielens/1m-raw/ratings/init.py       0      0   100%

merlin/datasets/entertainment/movielens/1m/init.py                   0      0   100%

merlin/datasets/entertainment/movielens/25m/init.py                  0      0   100%

merlin/datasets/entertainment/movielens/100k/init.py                 0      0   100%

merlin/datasets/entertainment/movielens/init.py                      0      0   100%

merlin/datasets/entertainment/movielens/dataset.py                     152    122    20%

merlin/datasets/entertainment/music_streaming/init.py                0      0   100%

merlin/datasets/social/init.py                                       0      0   100%

merlin/datasets/synthetic.py                                           147      8    95%

merlin/datasets/testing/init.py                                      0      0   100%

merlin/datasets/testing/sequence_testing/init.py                     0      0   100%

merlin/models/init.py                                                2      0   100%

merlin/models/_version.py                                              354    205    42%

merlin/models/api.py                                                    14      5    64%

merlin/models/config/init.py                                         0      0   100%

merlin/models/config/schema.py                                          62      0   100%

merlin/models/implicit/init.py                                      27      4    85%

merlin/models/io.py                                                     15      0   100%

merlin/models/lightfm/init.py                                       23      0   100%

merlin/models/loader/init.py                                         0      0   100%

merlin/models/loader/backend.py                                        379     41    89%

merlin/models/loader/dataframe_iter.py                                  21     17    19%

merlin/models/loader/tf_utils.py                                        57     27    53%

merlin/models/loader/utils.py                                           40     15    62%

merlin/models/tf/init.py                                            70      0   100%

merlin/models/tf/blocks/init.py                                      0      0   100%

merlin/models/tf/blocks/cross.py                                        44      0   100%

merlin/models/tf/blocks/dlrm.py                                         49      2    96%

merlin/models/tf/blocks/experts.py                                      99     17    83%

merlin/models/tf/blocks/interaction.py                                 108     40    63%

merlin/models/tf/blocks/mlp.py                                         117      7    94%

merlin/models/tf/blocks/optimizer.py                                   173     12    93%

merlin/models/tf/blocks/retrieval/init.py                            0      0   100%

merlin/models/tf/blocks/retrieval/base.py                              175     62    65%

merlin/models/tf/blocks/retrieval/matrix_factorization.py               35      1    97%

merlin/models/tf/blocks/retrieval/two_tower.py                          30      0   100%

merlin/models/tf/blocks/sampling/init.py                             0      0   100%

merlin/models/tf/blocks/sampling/base.py                                29      2    93%

merlin/models/tf/blocks/sampling/cross_batch.py                         46      2    96%

merlin/models/tf/blocks/sampling/in_batch.py                            35      0   100%

merlin/models/tf/blocks/sampling/queue.py                              115     12    90%

merlin/models/tf/core/init.py                                        0      0   100%

merlin/models/tf/core/aggregation.py                                   241     45    81%

merlin/models/tf/core/base.py                                          242     50    79%

merlin/models/tf/core/combinators.py                                   426     53    88%

merlin/models/tf/core/encoder.py                                       175     28    84%

merlin/models/tf/core/index.py                                         106     16    85%

merlin/models/tf/core/prediction.py                                     50      1    98%

merlin/models/tf/core/tabular.py                                       280     29    90%

merlin/models/tf/distributed/init.py                                 0      0   100%

merlin/models/tf/distributed/backend.py                                  9      2    78%

merlin/models/tf/inputs/init.py                                      0      0   100%

merlin/models/tf/inputs/base.py                                         60     10    83%

merlin/models/tf/inputs/continuous.py                                   39      3    92%

merlin/models/tf/inputs/embedding.py                                   458     32    93%

merlin/models/tf/loader.py                                             268     94    65%

merlin/models/tf/losses/init.py                                      4      0   100%

merlin/models/tf/losses/base.py                                          9      0   100%

merlin/models/tf/losses/listwise.py                                     13      0   100%

merlin/models/tf/losses/pairwise.py                                    115      1    99%

merlin/models/tf/metrics/init.py                                     2      0   100%

merlin/models/tf/metrics/evaluation.py                                 105     48    54%

merlin/models/tf/metrics/topk.py                                       198     48    76%

merlin/models/tf/models/init.py                                      0      0   100%

merlin/models/tf/models/base.py                                        756    101    87%

merlin/models/tf/models/benchmark.py                                    16      0   100%

merlin/models/tf/models/ranking.py                                      67      3    96%

merlin/models/tf/models/retrieval.py                                    78      4    95%

merlin/models/tf/models/utils.py                                        10      1    90%

merlin/models/tf/outputs/init.py                                     0      0   100%

merlin/models/tf/outputs/base.py                                       123     17    86%

merlin/models/tf/outputs/classification.py                              91      1    99%

merlin/models/tf/outputs/contrastive.py                                147     10    93%

merlin/models/tf/outputs/regression.py                                   9      0   100%

merlin/models/tf/outputs/sampling/init.py                            0      0   100%

merlin/models/tf/outputs/sampling/base.py                               78     21    73%

merlin/models/tf/outputs/sampling/in_batch.py                           37      1    97%

merlin/models/tf/outputs/sampling/popularity.py                         27      1    96%

merlin/models/tf/outputs/topk.py                                        98      6    94%

merlin/models/tf/prediction_tasks/init.py                            0      0   100%

merlin/models/tf/prediction_tasks/base.py                              207     37    82%

merlin/models/tf/prediction_tasks/classification.py                     68     17    75%

merlin/models/tf/prediction_tasks/multi.py                               7      0   100%

merlin/models/tf/prediction_tasks/next_item.py                          59      6    90%

merlin/models/tf/prediction_tasks/regression.py                         35      2    94%

merlin/models/tf/prediction_tasks/retrieval.py                          73      3    96%

merlin/models/tf/transformers/init.py                                0      0   100%

merlin/models/tf/transformers/block.py                                 101      2    98%

merlin/models/tf/transformers/transforms.py                             63      0   100%

merlin/models/tf/transforms/init.py                                  0      0   100%

merlin/models/tf/transforms/bias.py                                    111      9    92%

merlin/models/tf/transforms/features.py                                435     36    92%

merlin/models/tf/transforms/negative_sampling.py                        77      3    96%

merlin/models/tf/transforms/noise.py                                    43      1    98%

merlin/models/tf/transforms/regularization.py                           17      1    94%

merlin/models/tf/transforms/sequence.py                                282     42    85%

merlin/models/tf/transforms/tensor.py                                  158     13    92%

merlin/models/tf/typing.py                                               7      0   100%

merlin/models/tf/utils/init.py                                       0      0   100%

merlin/models/tf/utils/batch_utils.py                                   85      4    95%

merlin/models/tf/utils/repr_utils.py                                    69      4    94%

merlin/models/tf/utils/search_utils.py                                  34     22    35%

merlin/models/tf/utils/testing_utils.py                                206     36    83%

merlin/models/tf/utils/tf_utils.py                                     209     42    80%

merlin/models/torch/init.py                                         12      0   100%

merlin/models/torch/block/init.py                                    0      0   100%

merlin/models/torch/block/base.py                                      167     32    81%

merlin/models/torch/block/mlp.py                                        38      5    87%

merlin/models/torch/dataset.py                                          68      5    93%

merlin/models/torch/features/init.py                                 0      0   100%

merlin/models/torch/features/base.py                                     4      0   100%

merlin/models/torch/features/continuous.py                              22      0   100%

merlin/models/torch/features/embedding.py                              165     12    93%

merlin/models/torch/features/tabular.py                                 65      8    88%

merlin/models/torch/losses.py                                           28     28     0%

merlin/models/torch/model/init.py                                    0      0   100%

merlin/models/torch/model/base.py                                      286     65    77%

merlin/models/torch/model/prediction_task.py                            24      0   100%

merlin/models/torch/tabular/init.py                                  0      0   100%

merlin/models/torch/tabular/aggregation.py                              75      0   100%

merlin/models/torch/tabular/base.py                                    247     39    84%

merlin/models/torch/tabular/transformations.py                          67      3    96%

merlin/models/torch/typing.py                                            6      0   100%

merlin/models/torch/utils/init.py                                    0      0   100%

merlin/models/torch/utils/data_utils.py                                117    117     0%

merlin/models/torch/utils/examples_utils.py                             39     39     0%

merlin/models/torch/utils/torch_utils.py                                80     22    72%

merlin/models/utils/init.py                                          0      0   100%

merlin/models/utils/constants.py                                         3      0   100%

merlin/models/utils/dataset.py                                          38      4    89%

merlin/models/utils/dependencies.py                                     26     19    27%

merlin/models/utils/doc_utils.py                                        10      0   100%

merlin/models/utils/example_utils.py                                    31      2    94%

merlin/models/utils/misc_utils.py                                      118     90    24%

merlin/models/utils/nvt_utils.py                                        27     24    11%

merlin/models/utils/registry.py                                        101     29    71%

merlin/models/utils/schema_utils.py                                     90     19    79%

merlin/models/xgb/init.py                                          124      4    97%
TOTAL                                                                11581   2346    80%
=========================== short test summary info ============================

SKIPPED [1] tests/unit/datasets/test_advertising.py:20: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:64: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:80: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:94: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:115: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [3] tests/unit/datasets/test_entertainment.py:44: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [5] ../../../.local/lib/python3.8/site-packages/tensorflow/python/framework/test_util.py:2746: Not a test.

========= 870 passed, 13 skipped, 1452 warnings in 1757.43s (0:29:17) ==========

___________________________________ 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/jenkins2601778415196822163.sh

oliverholworthy added 3 commits November 16, 2022 11:52

Use add_weight instead of add_variable on ModelContext

1e0e4e8

Remove the now unused method add_variable on ModelContext

234dcc4

Update two tower save test to reload model

64da9d7

oliverholworthy added the bug Something isn't working label Nov 16, 2022

oliverholworthy added this to the Merlin 22.12 milestone Nov 16, 2022

oliverholworthy self-assigned this Nov 16, 2022

oliverholworthy changed the title ~~Fix two tower model load context variable~~ Fix loading of TwoTowerModel with context query variable Nov 16, 2022

rnyak requested a review from sararb November 16, 2022 14:30

Pad queries with zeros when batch size is different from first batch

0ba7d37

oliverholworthy added 2 commits November 16, 2022 17:03

Merge branch 'main' into fix-two-tower-model-load-context-variable

eedba24

Use tf.shape instead of .shape to get dims

46b3b17

Merge branch 'main' into fix-two-tower-model-load-context-variable

a2e1714

Merge branch 'main' into fix-two-tower-model-load-context-variable

904d911

Merge branch 'main' into fix-two-tower-model-load-context-variable

8ab76c1

sararb approved these changes Nov 21, 2022

View reviewed changes

Merge branch 'main' into fix-two-tower-model-load-context-variable

fa2c6ac

oliverholworthy merged commit 7a1227d into NVIDIA-Merlin:main Nov 22, 2022

oliverholworthy deleted the fix-two-tower-model-load-context-variable branch November 22, 2022 10:52

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Fix loading of `TwoTowerModel` with context query variable #887

Fix loading of `TwoTowerModel` with context query variable #887

oliverholworthy commented Nov 16, 2022

sararb commented Nov 16, 2022

oliverholworthy commented Nov 16, 2022

oliverholworthy commented Nov 16, 2022

nvidia-merlin-bot commented Nov 16, 2022

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---------- coverage: platform linux, python 3.8.10-final-0 -----------
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---------- coverage: platform linux, python 3.8.10-final-0 -----------
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nvidia-merlin-bot commented Nov 21, 2022

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

nvidia-merlin-bot commented Nov 21, 2022

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

Fix loading of TwoTowerModel with context query variable #887

Fix loading of TwoTowerModel with context query variable #887

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oliverholworthy commented Nov 16, 2022

Goals ⚽

Implementation Details 🚧

Testing Details 🔍

sararb commented Nov 16, 2022

oliverholworthy commented Nov 16, 2022

oliverholworthy commented Nov 16, 2022

nvidia-merlin-bot commented Nov 16, 2022

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

nvidia-merlin-bot commented Nov 18, 2022

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

nvidia-merlin-bot commented Nov 21, 2022

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

nvidia-merlin-bot commented Nov 21, 2022

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

nvidia-merlin-bot commented Nov 21, 2022

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

Fix loading of `TwoTowerModel` with context query variable #887

Fix loading of `TwoTowerModel` with context query variable #887

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

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

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

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

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