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* Patch for issue 1815, which will allow EarlyStopping to work on precision=16
* Added a whitespace to the end of the line so CICD can rerun. No reason for the latest macos test to have been cancelled.
* Format.
* Add an additional attribute to ModelCheckpoint to keep track of the best model's path
Currently, only the best metric value is directly tracked. This new attribute will help in uses cases where the trained model needs to be used or tracked right after training.
* Add small description and usage example to docs
* Fix PEP8 issues
* Fix doctest example
* Fix expected output in doctest
* Apply suggestions from code review
* Show example as code block instead of doctest
* Apply suggestions from code review
* Update CHANGELOG.md
* Rename `ModelCheckpoint.best` to `ModelCheckpoint.best_model_score`
Also rename `ModelCheckpoint.best_model` (added in this PR) to `ModelCheckpoint.best_model_path`, for consistency, and `kth_best_model` to `kth_best_model_path`.
* Update pytorch_lightning/trainer/training_io.py
Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com>
* Apply suggestions from code review
Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com>
* Add warning when loading checkpoint from an old version
Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com>
* fix chlog
* test for #1729
* hist
* update
* Document use case of passing test dataloaders to Trainer.test() (#1992)
* Issue 1990 Doc patch.
* Codeblock directive.
* Update to reflect current state of pytorch-lightning
* Final grammar cleaning. I hope these commits are squashed.
* Apply suggestions from code review
* Apply suggestions from code review
Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com>
Co-authored-by: Adrian Wälchli <aedu.waelchli@gmail.com>
Co-authored-by: authman <uapatira@gmail.com>
Co-authored-by: Adrian Wälchli <aedu.waelchli@gmail.com>
* fixed undesired behaviour due to dict.fromkeys
* a test for log length consistency
* runtime-warn if no schedulers are configured
* chlog
* move
Co-authored-by: Jirka <jirka@pytorchlightning.ai>
* filter valid args
* error on unknown manual args
* added test
* changelog
* update docs and doctest
* simplify
* doctest
* doctest
* doctest
* better test with mock check for init call
* fstring
* extend test
* skip test on 3.6 not working
Co-authored-by: William Falcon <waf2107@columbia.edu>
* FixesPyTorchLightning/pytorch-lightning#490
`EarlyStopping` should check the metric of interest `on_validation_end` rather than `on_epoch_end`.
In a normal scenario, this does not cause a problem, but in combination with `check_val_every_n_epoch>1` in the `Trainer` it results in a warning or in a `RuntimeError` depending on `strict`.
* Highlighted that ES callback runs on val epochs in docstring
* Updated EarlyStopping in rst doc
* Update early_stopping.py
* Update early_stopping.rst
* Update early_stopping.rst
* Update early_stopping.rst
* Update early_stopping.rst
* Apply suggestions from code review
Co-authored-by: Adrian Wälchli <aedu.waelchli@gmail.com>
* Update docs/source/early_stopping.rst
* fix doctest indentation warning
* Train loop calls early_stop.on_validation_end
* chlog
Co-authored-by: William Falcon <waf2107@columbia.edu>
Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com>
Co-authored-by: Adrian Wälchli <aedu.waelchli@gmail.com>
Co-authored-by: Jirka <jirka@pytorchlightning.ai>
* Allow dataloaders without sampler field present
Sometimes we have a custom dataloader that doesn't have a sampler, better to check that the field is there before reading it.
* chlog
Co-authored-by: Jirka <jirka@pytorchlightning.ai>
* Add flag to `dump_checkpoint` for only including weights
`ModelCheckpoint` then passes `self.save_weights_only` to the save function.
* Fix tests and add changelog entry
* Add check and descriptive message when training state is restored from a weights only checkpoint
Also add a test for making sure `ModelCheckpoint.save_weights_only` works as expected.
* Fix weights-only test to properly match expected exception
* Apply suggestions from code review
Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com>
Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com>
* Fix test configuration check and testing
* Fix test configuration check and testing
* Remove check_testing_configuration during test
* Fix docstring
* fix function name
* remove conflicts
The intention of the code is to output a warning message when `hparams`
is null or not set. Instead the code now fatals when
`model.hparams = None`. Prevent that.
William Falcon