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automl / Auto-PyTorch

Automatic architecture search and hyperparameter optimization for PyTorch
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Score fixed #485

Open dengdifan opened 1 year ago

dengdifan commented 1 year ago

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codecov[bot] commented 1 year ago

Codecov Report

Base: 85.49% // Head: 84.50% // Decreases project coverage by -0.98% :warning:

Coverage data is based on head (1e2180b) compared to base (d160903). Patch coverage: 80.00% of modified lines in pull request are covered.

Additional details and impacted files ```diff @@ Coverage Diff @@ ## development #485 +/- ## =============================================== - Coverage 85.49% 84.50% -0.99% =============================================== Files 231 232 +1 Lines 16351 16475 +124 Branches 3028 2734 -294 =============================================== - Hits 13979 13923 -56 - Misses 1533 1675 +142 - Partials 839 877 +38 ``` | [Impacted Files](https://codecov.io/gh/automl/Auto-PyTorch/pull/485?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=automl) | Coverage Δ | | |---|---|---| | [autoPyTorch/datasets/time\_series\_dataset.py](https://codecov.io/gh/automl/Auto-PyTorch/pull/485/diff?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=automl#diff-YXV0b1B5VG9yY2gvZGF0YXNldHMvdGltZV9zZXJpZXNfZGF0YXNldC5weQ==) | `90.63% <ø> (ø)` | | | [setup.py](https://codecov.io/gh/automl/Auto-PyTorch/pull/485/diff?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=automl#diff-c2V0dXAucHk=) | `0.00% <ø> (ø)` | | | [autoPyTorch/api/time\_series\_forecasting.py](https://codecov.io/gh/automl/Auto-PyTorch/pull/485/diff?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=automl#diff-YXV0b1B5VG9yY2gvYXBpL3RpbWVfc2VyaWVzX2ZvcmVjYXN0aW5nLnB5) | `66.29% <77.27%> (+3.60%)` | :arrow_up: | | [autoPyTorch/api/base\_task.py](https://codecov.io/gh/automl/Auto-PyTorch/pull/485/diff?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=automl#diff-YXV0b1B5VG9yY2gvYXBpL2Jhc2VfdGFzay5weQ==) | `82.60% <100.00%> (-1.22%)` | :arrow_down: | | [...luation/time\_series\_forecasting\_train\_evaluator.py](https://codecov.io/gh/automl/Auto-PyTorch/pull/485/diff?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=automl#diff-YXV0b1B5VG9yY2gvZXZhbHVhdGlvbi90aW1lX3Nlcmllc19mb3JlY2FzdGluZ190cmFpbl9ldmFsdWF0b3IucHk=) | `90.62% <100.00%> (-0.18%)` | :arrow_down: | | [autoPyTorch/pipeline/tabular\_regression.py](https://codecov.io/gh/automl/Auto-PyTorch/pull/485/diff?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=automl#diff-YXV0b1B5VG9yY2gvcGlwZWxpbmUvdGFidWxhcl9yZWdyZXNzaW9uLnB5) | `69.30% <0.00%> (-13.87%)` | :arrow_down: | | [autoPyTorch/ensemble/ensemble\_selection.py](https://codecov.io/gh/automl/Auto-PyTorch/pull/485/diff?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=automl#diff-YXV0b1B5VG9yY2gvZW5zZW1ibGUvZW5zZW1ibGVfc2VsZWN0aW9uLnB5) | `85.41% <0.00%> (-11.46%)` | :arrow_down: | | [autoPyTorch/evaluation/abstract\_evaluator.py](https://codecov.io/gh/automl/Auto-PyTorch/pull/485/diff?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=automl#diff-YXV0b1B5VG9yY2gvZXZhbHVhdGlvbi9hYnN0cmFjdF9ldmFsdWF0b3IucHk=) | `66.40% <0.00%> (-11.00%)` | :arrow_down: | | [autoPyTorch/evaluation/utils\_extra.py](https://codecov.io/gh/automl/Auto-PyTorch/pull/485/diff?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=automl#diff-YXV0b1B5VG9yY2gvZXZhbHVhdGlvbi91dGlsc19leHRyYS5weQ==) | `70.58% <0.00%> (-8.83%)` | :arrow_down: | | [autoPyTorch/pipeline/tabular\_classification.py](https://codecov.io/gh/automl/Auto-PyTorch/pull/485/diff?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=automl#diff-YXV0b1B5VG9yY2gvcGlwZWxpbmUvdGFidWxhcl9jbGFzc2lmaWNhdGlvbi5weQ==) | `75.20% <0.00%> (-6.62%)` | :arrow_down: | | ... and [40 more](https://codecov.io/gh/automl/Auto-PyTorch/pull/485/diff?src=pr&el=tree-more&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=automl) | | Help us with your feedback. Take ten seconds to tell us [how you rate us](https://about.codecov.io/nps?utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=automl). Have a feature suggestion? [Share it here.](https://app.codecov.io/gh/feedback/?utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=automl)

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dengdifan commented 1 year ago

Thanks for your changes. I think the tests are failing because we need to update the requirements. Particularly, gluonts version 0.11.4 does not have 'DayOfMonth' from 'gluonts.time_feature'. Could you take a look?

This is fixed. However, I am considering removing all these dependencies (gluonts, pytorch-forecasting) in the future (which might take some time, though).