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jrzaurin / pytorch-widedeep

A flexible package for multimodal-deep-learning to combine tabular data with text and images using Wide and Deep models in Pytorch
Apache License 2.0
1.3k stars 190 forks source link

Mps backened support #235

Closed jrzaurin closed 2 weeks ago

jrzaurin commented 2 weeks ago

The name of this PR is a bit misleading, since a number of things have happened here

  1. Added support for MPS backened
  2. Added a series of models to the rec module: DCN, DCNv2, GDCN, AutoInt, AutoIntPlus
  3. Added a DIN preprocessor
  4. Reviewed the docs
  5. Reviewed the examples
  6. Other (minor and not so minor) fixes
codecov[bot] commented 2 weeks ago

Codecov Report

Attention: Patch coverage is 95.03476% with 50 lines in your changes missing coverage. Please review.

Project coverage is 94.87%. Comparing base (9df6585) to head (278c72f). Report is 25 commits behind head on master.

Files with missing lines Patch % Lines
pytorch_widedeep/utils/general_utils.py 38.70% 19 Missing :warning:
pytorch_widedeep/dataloaders.py 80.55% 7 Missing :warning:
pytorch_widedeep/preprocessing/din_preprocessor.py 97.26% 5 Missing :warning:
pytorch_widedeep/training/trainer.py 93.33% 5 Missing :warning:
pytorch_widedeep/metrics.py 98.33% 3 Missing :warning:
pytorch_widedeep/losses.py 81.81% 2 Missing :warning:
pytorch_widedeep/models/model_fusion.py 96.42% 2 Missing :warning:
pytorch_widedeep/models/rec/autoint_plus.py 97.26% 2 Missing :warning:
pytorch_widedeep/tab2vec.py 66.66% 2 Missing :warning:
pytorch_widedeep/training/bayesian_trainer.py 77.77% 2 Missing :warning:
... and 1 more
Additional details and impacted files ```diff @@ Coverage Diff @@ ## master #235 +/- ## ========================================== + Coverage 94.80% 94.87% +0.07% ========================================== Files 121 126 +5 Lines 7579 8277 +698 ========================================== + Hits 7185 7853 +668 - Misses 394 424 +30 ``` | [Flag](https://app.codecov.io/gh/jrzaurin/pytorch-widedeep/pull/235/flags?src=pr&el=flags&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=Javier) | Coverage Δ | | |---|---|---| | [unittests](https://app.codecov.io/gh/jrzaurin/pytorch-widedeep/pull/235/flags?src=pr&el=flag&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=Javier) | `94.87% <95.03%> (+0.07%)` | :arrow_up: | Flags with carried forward coverage won't be shown. [Click here](https://docs.codecov.io/docs/carryforward-flags?utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=Javier#carryforward-flags-in-the-pull-request-comment) to find out more.

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