* fix result for dp
* fix result for dp
* fix result for dp
* fix result for dp
* fix result for dp
* fix result for dp
* fix result for dp
* fix result for dp
* fix result for dp
* fix result for dp
* fix result for dp
* fix result for dp
* added warning when changing monitor and using results obj
* added warning when changing monitor and using results obj
* added warning when changing monitor and using results obj
* added warning when changing monitor and using results obj
* add ddp script variations
* add ddp test
* rename
* shell
* test
* test
* try call
* try without subprocess
* test
* display the error
* list all variations
* try string
* try copy env
* debug
* pythonpath
* path
* update test
* change
* simple ddp test
* replace
* remove random port
* random port
* str
* clean up
* check run spawn
* clean up
* docs
* docs
* update test
* docs
* changelog
* changelog
* add val step arg to metrics
* add val step arg to metrics
* add val step arg to metrics
* add val step arg to metrics
* add val step arg to metrics
* add val step arg to metrics
* add val step arg to metrics
* add val step arg to metrics
* add val step arg to metrics
* add step metrics
* add step metrics
* override dist backend when using tpus
* added test
* updated doc string
* drop redundant info...
* more redundant info
Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com>
Co-authored-by: rohitgr7 <rohitgr1998@gmail.com>
* Update lr_logger.py
when logging learning_rate, we should provide different choices to log including 'step' and 'epoch'
* Update lr_logger.py
add some type annotations and docstrings
* Update lr_logger.py
fixed a bug where `on_train_batch_start()` can't be triggered, instead, we should use on_batch_start(); add `interval` args so that we can record learning_rates with respect to `global_step` or `current_epoch`.
* Update lr_logger.py
restore _extract_lr()
* suggestion
* Update lr_logger.py
modify _extract_lr(), it no more need to pass `interval` parameter.
* Update test_lr_logger.py
SkafteNicki 's suggetion
* log_interval now supports `None`, `step`, `epoch`
* change `log_interval` to `logging_interval`
* Update test_lr_logger.py
* Update lr_logger.py
* put types check into `on_train_start()`
* cleanup
* docstring typos
* minor changes from suggestions
Co-authored-by: Jirka Borovec <jirka@pytorchlightning.ai>
Co-authored-by: rohitgr7 <rohitgr1998@gmail.com>
Co-authored-by: Adrian Wälchli <aedu.waelchli@gmail.com>
Co-authored-by: mergify[bot] <37929162+mergify[bot]@users.noreply.github.com>
* Add initial tracking of states in Trainer.
* Add INTERRUPTED state, improve tests, move state switching from callback to a trainer.
* Move part of a trainer state switching to a decorator.
* Add documentation.
* Fix docs, rename state enum, restore state to previous on exit if None, add tests for decorator only.
* Fix callback typing.
Co-authored-by: William Falcon <waf2107@columbia.edu>
* Add support to Tensorboard logger for OmegaConf hparams
Address https://github.com/PyTorchLightning/pytorch-lightning/issues/2844
We check if we can import omegaconf, and if the hparams are omegaconf instances. if so, we use OmegaConf.merge to preserve the typing, such that saving hparams to yaml actually triggers the OmegaConf branch
* avalaible
* chlog
* test
Co-authored-by: Jirka Borovec <jirka@pytorchlightning.ai>
* Override the default gather method to support scalars
* add computing average of a list
* bug: change if to elif
* add some tests
* change style
* change documentation
* use apply_to_collection in DP gather
* use apply_to_collection in DP gather
* fix warning msg
* override gather method in DP
* add tests for python scalars
* add python scalars to docstring
* Update message
* override gather method in DP
* formatting
* chlog
Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com>
Co-authored-by: Jirka Borovec <jirka@pytorchlightning.ai>
* add test for none checkpoint in ddp_spawn
* fix code style
* make sure checkpoint_callback is none
* Fix tests
Co-authored-by: Justus Schock <12886177+justusschock@users.noreply.github.com>
* add ddp sync for logging in result step
* pep8
* pep8
* make ddp tests run also on cpu (except windowws)
* create class instance in ddp test
* revert automated formatting
* pep8
* Fix shuffle for distributed sampler
* add test
* test
* chlog
* update test
* update test
* update test
* assertions via callback
* define callback outside for pickling
* skip ddp test on windows
Co-authored-by: Adrian Wälchli <aedu.waelchli@gmail.com>
* Test using torchtext.data.Field with include_lengths=True/False
* Fix issue that Tensors in a Batch generated by torchtext with torchtext.data.Field configured as include_lengths=True
* Add description for fix of issue #2688
* changes to accomodate CodeFactor issues
* Another attemt to make last CodeFactor issue pass (it's a false alarm)
* temporarly disable test of test_grad_tracking to check if testing will pass
* reenable test in test_grad_norm
* Update CHANGELOG.md
Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com>
* Renamed get_torchtext_data_iterator to _get_torchtext_data_iterator as suggested by @borda
* Update pytorch_lightning/utilities/apply_func.py
Co-authored-by: Adrian Wälchli <aedu.waelchli@gmail.com>
* adding tests more specific to batch_move_data_to_device with tochtext Batch
* added check that Tensors were moved to target device
* removed tests using RNN models to be moved into a separate PR
* fixing FLAKE8 errors that showed up after merge from master branch
modified: tests/base/datamodules.py
modified: tests/callbacks/test_model_checkpoint.py
* parameterized test to reduce code duplication
* Added check only if length tensor exist. Removed left over comments.
* rearranged device parameterization and added pytest.param
* Try to figure out why only one device is tested on Linux machines
* Testing on CPU and GPU devices (GPU test is skip if no cuda device is available.
* added test for TPU device (experimental)
* Adding test parameterization for TPU test (experimental)
* change import statement to limit what is imported for a TPU environment
* made test work with TPU
* Change to trigger CI
* Change to trigger CI
* uncommented TPU test to check CI
* reenabling TPU test
* small change to trigger CI build
* small change to trigger CI build
* small change to trigger CI build
* adding tests/utilities/test_apply_func_torchtext.py to CI TPU test
* try to make test not skipped on CI with TPU
* remove testing on TPU
* undo an accidental change to test_tpu.py (file should not have been touched)
* small change to trigger CI build
* small change to trigger CI build
* Update tests/utilities/test_apply_func_torchtext.py
* Revert to previous version
* Apply suggestions from code review
* Change to trigger CI
Co-authored-by: Thomas Schaaf <tschaaf@mmm.com>
Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com>
Co-authored-by: Adrian Wälchli <aedu.waelchli@gmail.com>
Co-authored-by: Thomas Schaaf <tschaaf@cs.cmu.edu>
* export model to onnx
* prepare data before exporting
* support for dataloaders and tensors
* added tests
* use example_input_array
add to changelog
* updated docstring
* added onnx inference tests
* temp commit
* removed schema valid test
* add onnxruntime to environment.yml
* moved onnxruntime to environment.yml pip
* add example in doc
* add lines between code block
* added PR to changelog
* is file check
Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com>
* remove *
Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com>
* infer example outputs
* added doctest for onnx
* fix windows tests
* moved eval within condition block
* self.forward to self
* added docs
* fixed docs error
* added to toctree
* Update CHANGELOG.md
Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com>
* pt 1.6
* don't use the new zipfile serialization for now
* quick flake8 fixes
* remove unnecessary f
* coalesce strings
* remove comma
* remove extra commas
* Apply suggestions from code review
Co-authored-by: Peter Yu <2057325+yukw777@users.noreply.github.com>
* set _use_new_zipfile_serialization to False only for pytorch 1.6.0
* remove unnecessary comments
* flake8 fixes
* use pkg_resources instead of packaging
* readme
* format
* version
* chlog
Co-authored-by: Peter Yu <peter@asapp.com>
Co-authored-by: Peter Yu <2057325+yukw777@users.noreply.github.com>
The speed up is achieved by:
- Moving the "where" out of the loop (and replacing with min for simplicity).
- Replacing manual sum and pow with torch.norm. Even though this results
in unnessecary computation (computing pow(root)) this is still a lot
faster.
- Preallocating the output gives a slight speed up.
Note that calling .to for all parameters results in a small speed
penalty (~4 ms in my case) but allows parameters on different devices.
Overall this reduces the time used for gradient clipping from 206ms to
74 ms for my model (Resnet50 + few additional vars, all vars on GPU).
* Fix fast_dev_run to run for all val_dataloaders
* fast_dev_run check
* changelog
* explicit
* limit_batches with fast_dev_run in init
* add test
* whitespace and comment fix
* comment and assertion
* added tests
* Fix fast_dev_run to run for all val_dataloaders
* fast_dev_run check
* changelog
* explicit
* limit_batches with fast_dev_run in init
* add test
* whitespace and comment fix
* comment and assertion
* added tests
* added tests
* added tests
* added tests
* update rtol
* Revert "update rtol"
This reverts commit 4320329540.
* added tests
Co-authored-by: William Falcon <waf2107@columbia.edu>
* fix weights_save path and drop ckpt_path
* add tests
* unused import
* update docs
* changelog
* pep8
* fix horovod test
* make backward compatible
* perform same test for all loggers
* fix for when logger=False and weights_save_path is set
* update changelog
* update docs
* update tests
* do not set save dir dynamically
* remove duplicate test
* remove duplicated tests
* update tests
* update tests
* remove remaining ckpt_path references
* move defaults to init as suggested by @Borda
* test deprecation
* reactor into gpu accelerator
* reactor into gpu accelerator
* reactor into gpu accelerator
* reactor into gpu accelerator
* reactor into gpu accelerator
* reactor into gpu accelerator
* reactor into gpu accelerator
* reactor into gpu accelerator
* reactor into gpu accelerator
* reactor into gpu accelerator
* reactor into gpu accelerator
* reactor into gpu accelerator
* reactor into gpu accelerator
* reactor into gpu accelerator
* reactor into gpu accelerator
* reactor into gpu accelerator
* reactor into gpu accelerator
* reactor into gpu accelerator
* reactor into gpu accelerator
* reactor into gpu accelerator
* reactor into gpu accelerator
* 🎨 warn instead of error out on loaders
* 🐛 test misconfiguration should still fail
* 🚧 .
* updated docs with new result obj
* updated docs with new result obj
* updated docs with new result obj
* updated docs with new result obj
* updated docs with new result obj
* updated docs with new result obj
* updated docs with new result obj
* updated docs with new result obj
* updated docs with new result obj
* updated docs with new result obj
* updated docs with new result obj
* updated docs with new result obj
* updated docs with new result obj
* updated docs with new result obj
* updated docs with new result obj
* updated docs with new result obj
* updated docs with new result obj
* updated docs with new result obj
* updated docs with new result obj
* updated docs with new result obj
* updated docs with new result obj
* updated docs with new result obj
* updated docs with new result obj
* updated docs with new result obj
* updated docs with new result obj
* updated docs with new result obj
* updated docs with new result obj
* updated docs with new result obj
* updated docs with new result obj
* updated docs with new result obj
* updated docs with new result obj
* updated docs with new result obj
* updated docs with new result obj
* updated docs with new result obj
* updated docs with new result obj
Co-authored-by: William Falcon <waf2107@columbia.edu>
* fix setup call while testing
* changelog
* drop if condition
* add test to check setup call
* flake8
* update test to check model stage
Co-authored-by: William Falcon <waf2107@columbia.edu>
* Horovod: Adjust base LR used by schedulers to match that of the optimizer after scaling by number of workers
* Added unit test
* Removed debug statements
* Updated changelog
* Apply suggestions from code review
Co-authored-by: William Falcon <waf2107@columbia.edu>
Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com>
* metrics: added bleu score and test bleu
* metrics: fixed type hints in bleu
* bleu score moved to metrics/functional/nlp.py
* refactor with torch.Tensor
* Update test_sequence.py
* refactor as Borda requests and nltk==3.2
* locked nltk==3.3
* nltk>=3.3, parametrized smooth argument for test
* fix bleu_score example
* added class BLEUScore metrics and test
* added class BLEUScore metrics and test
* update CHANGELOG
* refactor with torchtext
* torchtext changed to optional import
* fix E501 line too long
* add else: in optional import
* remove pragma: no-cover
* constants changed to CAPITALS
* remove class in tests
* List -> Sequence, conda -> pip, cast with tensor
* add torchtext in test.txt
* remove torchtext from test.txt
* bump torchtext to 0.5.0
* bump torchtext to 0.5.0
* Apply suggestions from code review
* ignore bleu score in doctest, renamed to nlp.py
* back to implementation with torch
* remove --ignore in CI test, proper reference format
* apply justus comment
Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com>
* recursive dtype device apply
* simplify
* simple test
* submodule test
* rename
* explicit
* type hints
* test for dp backend
* fix test skip
* rename
* add ddp_spawn test
* fix None index in test
* try fix ddp_spawn test
* changelog
* move _dtype and _device to mixin
* additional doctest
* r
* r
* r
* patched optimizer closure with sr
* patched optimizer closure with sr
* patched optimizer closure with sr
* added train step structured result
* added train step structured result
* added train step structured result
* added train step structured result
* added train step structured result
* added train step structured result
* added train step structured result
* added train step structured result
* added train step structured result
* added train step structured result
* added train step structured result
* added train step structured result
* added train step structured result
* added train step structured result
* added train step structured result
* added train step structured result
* added train step structured result
* added train step structured result
* added train step structured result
* added train step structured result
* added autoreduce for train step
* added auto reduce on train
* added auto reduce on train
* added auto reduce on train
* added auto reduce on train
* added auto reduce on train
* added auto reduce on train
* added hooks
* added hooks
* added hooks
* added hooks
* added hooks
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* cache
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* Update pytorch_lightning/callbacks/early_stopping.py
Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com>
* Update pytorch_lightning/callbacks/early_stopping.py
Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com>
* Update pytorch_lightning/callbacks/early_stopping.py
Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com>
* Update pytorch_lightning/callbacks/model_checkpoint.py
* Update pytorch_lightning/core/step_result.py
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* Apply suggestions from code review
Co-authored-by: Adrian Wälchli <aedu.waelchli@gmail.com>
Co-authored-by: Justus Schock <12886177+justusschock@users.noreply.github.com>
* Apply suggestions from code review
Co-authored-by: Justus Schock <12886177+justusschock@users.noreply.github.com>
* Apply suggestions from code review
Co-authored-by: Justus Schock <12886177+justusschock@users.noreply.github.com>
* simple
* finished tests for structured results on train epoch
* simple
* simple
* revert
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* Update tests/base/deterministic_model.py
Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com>
* finished tests for structured results on train epoch
* docstring typos
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* finished tests for structured results on train epoch
* Update pytorch_lightning/core/step_result.py
Co-authored-by: Adrian Wälchli <aedu.waelchli@gmail.com>
* Update pytorch_lightning/overrides/data_parallel.py
Co-authored-by: Adrian Wälchli <aedu.waelchli@gmail.com>
Co-authored-by: Jirka <jirka@pytorchlightning.ai>
Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com>
Co-authored-by: Adrian Wälchli <aedu.waelchli@gmail.com>
Co-authored-by: Justus Schock <12886177+justusschock@users.noreply.github.com>
* add tests for single scalar return from training
* add tests for single scalar return from training
* add tests for single scalar return from training
* fixing val step only
* fixing val step only
* fixing val step only
* fixing val step only
* fixing val step only
* fixing val step only
* fixing val step only
* fixing val step only
* fixing val step only
* fixing val step only
* fixing val step only
* fixing val step only
* fixing val step only
* fixing val step only
* fixing val step only
* fixing val step only
* fixing val step only
* fixing val step only
* fixing val step only
* fixing val step only
* fixing val step only
* fixing val step only
* add tests for single scalar return from training
* add tests for single scalar return from training
* add tests for single scalar return from training
* add tests for single scalar return from training
* add tests for single scalar return from training
* mlflow rework
* logger save_dir
* folder
* mlflow
* simplify
* fix test
* add a test for file dir contents
* new line
* changelog
* docs
* Update CHANGELOG.md
Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com>
* test for comet logger
* improve mlflow checkpoint test
* prevent commet logger error on pytest exit
* test tensorboard save dir structure
* wandb save dir test
* skip test on windows
* add mlflow to pickle tests
* wandb
* code factor
* remove unused imports
* remove unused setter
* wandb mock
* wip mock
* wip mock
* wandb tests with mocking
* clean up
* clean up
* comments
* include wandblogger in test
* clean up
* missing argument
Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com>
* skip ckpt test on rank > 0
* fx test
* add extra assert
* code factor
* add back removed
* add old loading code
* add back old
* unused import
* add same skip to run_model_without_loggers
* test if horovod now works with python 3.8
* test remove all 3.8 skips
* remove spawn
* fix
* fix test
* move load check up
* fix test multigpu
* rename
* fix gpu mode
* on gpu fix when on cpu
* move
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* fix deprecation warnings
* added base tests for tpu
* added base tests for tpu
* Update pytorch_lightning/trainer/trainer.py
Co-authored-by: Jeremy Jordan <13970565+jeremyjordan@users.noreply.github.com>
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
* added base tests for tpu
Co-authored-by: Jirka <jirka@pytorchlightning.ai>
Co-authored-by: Jeremy Jordan <13970565+jeremyjordan@users.noreply.github.com>
* fix tpu hang
* fix tpu hang
* fix tpu hang
* fix tpu hang
* fix tpu hang
* fix tpu hang
* fix tpu hang
* fix tpu hang
* fix tpu hang
* fix tpu hang
* fix tpu hang
* fix tpu hang
* fix tpu hang
* fix tpu hang
* fix tpu hang
* fix tpu hang
* fix tpu hang
* fix tpu hang
* fix tpu hang
* fix tpu hang
* fix tpu hang
* fix tpu hang
* fix tpu hang
* fix tpu hang
* fix tpu hang
* fix tpu hang
* fix tpu hang
* fix tpu hang
* fix tpu hang
* fix tpu hang
* fix tpu hang
* fix tpu hang
* fix tpu hang
* fix tpu hang
* fix tpu hang
* fix tpu hang
* fix tpu hang
* fix tpu hang
* fix tpu hang
* fix tpu hang
* Fixes#2455
* Fixes#2455
* Fixes#2455
* Fixes#2455
* Fixes#2455
* Fixes#2455
* Fixes#2455
* Fixes#2455
* Fixes#2455
* Fixes#2455
* Fixes#2455
* Fixes#2455
* Fixes#2455
* Fixes#2455
* Fixes#2455
* Fixes#2455
* Fixes#2455
* Fixes#2455
* Fixes#2455
* Fixes#2455
* Fixes#2455
* Fixes#2455
* Fixes#2455
* Fixes#2455
* Fixes#2455
* Fixes#2455
* Fixes#2455
* added early stop tpu test
* added early stop tpu test
* added early stop tpu test
* added early stop tpu test
* added early stop tpu test
* added early stop tpu test
* added early stop tpu test
* added early stop tpu test
* added early stop tpu test
* added early stop tpu test
* added early stop tpu test
* added early stop tpu test
* added early stop tpu test
* added early stop tpu test
* added early stop tpu test
* added early stop tpu test
* added early stop tpu test
* added early stop tpu test
* added early stop tpu test
* added early stop tpu test
* added early stop tpu test
* added early stop tpu test
* fix and test for ddp block logging rank > 0
* rename
* use the dummy logger
* dummy logger test
* set the logger in model
* decorator for rank zero experiment
* simplify check
* simplify
* fix problem with None in checkpoint path
* revert configure logger
* unused import
* offline
* try rank 0 decorator in checkpoint
* try fix test
* imgs
* add asserts to make sure log zero only saves checkpoints
* add asserts to make sure log zero only saves checkpoints
* add asserts to make sure log zero only saves checkpoints
* add asserts to make sure log zero only saves checkpoints
* add asserts to make sure log zero only saves checkpoints
* fix tpu tests
* fix tpu tests
Co-authored-by: William Falcon <waf2107@columbia.edu>
* add state_dict for early stopping
* move best attr after monitor_op defined
* improve early stopping and model checkpoint callbacks
* fix formatting
* fix attr init order
* clean up setting of default_root_dir attr
* logger needs default root dir set first
* reorg trainer init
* remove direct references to checkpoint callback
* more fixes
* more bugfixes
* run callbacks at epoch end
* update tests to use on epoch end
* PR cleanup
* address failing tests
* refactor for homogeneity
* fix merge conflict
* separate tests
* tests for early stopping bug regressions
* small fixes
* revert model checkpoint change
* typo fix
* fix tests
* update train loop
* cannot pass an int as default_save_path
* refactor log message
* fix test case
* appease the linter
* fix some doctests
* move config to callback
* fixes from rebase
* fixes from rebase
* chlog
* docs
* reformat
* formatting
* fix
* fix
* fixes from rebase
* add new test for patience
* Update pytorch_lightning/callbacks/model_checkpoint.py
Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com>
* Update pytorch_lightning/callbacks/model_checkpoint.py
Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com>
* Update tests/callbacks/test_early_stopping.py
Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com>
* fix formatting
* remove enable_early_stop attribute
* add state_dict for early stopping
* move best attr after monitor_op defined
* improve early stopping and model checkpoint callbacks
* fix formatting
* fix attr init order
* clean up setting of default_root_dir attr
* logger needs default root dir set first
* reorg trainer init
* remove direct references to checkpoint callback
* more fixes
* more bugfixes
* run callbacks at epoch end
* update tests to use on epoch end
* PR cleanup
* address failing tests
* refactor for homogeneity
* fix merge conflict
* separate tests
* tests for early stopping bug regressions
* small fixes
* revert model checkpoint change
* typo fix
* fix tests
* update train loop
* fix test case
* appease the linter
* fix some doctests
* move config to callback
* fixes from rebase
* fixes from rebase
* chlog
* docs
* reformat
* formatting
* fix
* fix
* fixes from rebase
* add new test for patience
* Update pytorch_lightning/callbacks/model_checkpoint.py
Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com>
* Update pytorch_lightning/callbacks/model_checkpoint.py
Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com>
* Update tests/callbacks/test_early_stopping.py
Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com>
* fix formatting
* remove enable_early_stop attribute
* fix test with new epoch indexing
* fix progress bar totals
* fix off by one error (see #2289) epoch starts at 0 now
* added missing imports
* fix hpc_save folderpath
* fix formatting
* fix tests
* small fixes from a rebase
* fix
* tmpdir
* tmpdir
* tmpdir
* wandb
* fix merge conflict
* add back evaluation after training
* test_resume_early_stopping_from_checkpoint TODO
* undo the horovod check
* update changelog
* remove a duplicate test from merge error
* try fix dp_resume test
* add the logger fix from master
* try remove default_root_dir
* try mocking numpy
* try import numpy in docs test
* fix wandb test
* pep 8 fix
* skip if no amp
* dont mock when doctesting
* install extra
* fix the resume ES test
* undo conf.py changes
* revert remove comet pickle from test
* Update CHANGELOG.md
Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com>
* Update weights_loading.rst
* Update weights_loading.rst
* Update weights_loading.rst
* renamed flag
* renamed flag
* revert the None check in logger experiment name/version
* add the old comments
* _experiment
* test chckpointing on DDP
* skip the ddp test on windows
* cloudpickle
* renamed flag
* renamed flag
* parentheses for clarity
* apply suggestion max epochs
Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com>
Co-authored-by: Jeremy Jordan <jtjordan@ncsu.edu>
Co-authored-by: Jirka <jirka@pytorchlightning.ai>
Co-authored-by: Jeremy Jordan <13970565+jeremyjordan@users.noreply.github.com>
Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com>
Co-authored-by: William Falcon <waf2107@columbia.edu>
* no cov
* no cov
* ReduceOp
* group
* reduce_op.sum
* Update sklearns.py
* formatting
* horovod
* Apply suggestions from code review
* horovod
* horovod
* horovod
* horovod
* ci
* print
* ci
* timeout
* timeout
* time
* fix
* distributed cpu
* pipes
* time
* cpu
* spawn
* spawn
* spawn
* tp
* separate
* os
* os
* npm
* Fix load_from_checkpoint() not working with URL on Windows
* Update CHANGELOG
* Update CHANGELOG.md
Co-authored-by: Peter Yu <2057325+yukw777@users.noreply.github.com>
* Apply suggestions from code review
* fix
* fix meta tags creating empty lines
* pyright
* node
* fix httpserver address
* drop tutils.default_trainer_options
* imports
* Better fix for load_from_checkpoint() not working with absolute path on Windows (#2294)
* Fix load_from_checkpoint() not working with URL on Windows
* Update CHANGELOG
* Update CHANGELOG.md
Co-authored-by: Peter Yu <2057325+yukw777@users.noreply.github.com>
* Apply suggestions from code review
Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com>
Co-authored-by: Peter Yu <2057325+yukw777@users.noreply.github.com>
* drop duplicate
Co-authored-by: Justus Schock <12886177+justusschock@users.noreply.github.com>
Co-authored-by: airium <airium@outlook.com>
Co-authored-by: Peter Yu <2057325+yukw777@users.noreply.github.com>
Co-authored-by: Adrian Wälchli <aedu.waelchli@gmail.com>
Co-authored-by: AIRIUM <38249940+airium@users.noreply.github.com>
* deal with NotImplementedError raised by torchtext
* deal with NotImplementedError raised by torchtext
* Added tests for dataloader which raise NotImplementedError in __len__()
* Fixed some typos
* enabled tests for dataloader raising NotImplementedError in __len__ and corrected match string for raised exception
* deleted empty line for style compliance
* refactored CustomNotImplementedErrorDataloader to derive from CustomInfDataloader
* enabled reduced number of not_implemented_error dataloader test to reduce runtime for continuous integration
* reduced test number of not_implemented_error dataloader test further to reduce test time
* reduced test number of not_implemented_error dataloader test to one to reduce test time
* disabled all not_implemented_error dataloader test to see if test pass in time
* added __next__ with a reduced number (5) of elements after which CustomNotImplementedErrorDataloader stops to speedup test.
* enabling all not_implemented_error dataloader test
* added brief description of change and relation of torchtext
* CustomNotImplementedErrorDataloader reduced number of batches served to 2.
* Update CHANGELOG.md
Co-authored-by: Adrian Wälchli <aedu.waelchli@gmail.com>
* Apply suggestions from code review
* Update CHANGELOG.md
Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com>
* Disable parallelism in dataloader
Suspect that it might cause pytest to hang more frequent
* added max_steps=None to Trainer in not_implemented_error dataloader tests
* rearranged not_implemented_error test in file to group them together
* disabled parallel data loading
Reason: testing if that stops the test framework from hanging.
* Apply suggestions from code review
* Apply suggestions from code review
Co-authored-by: Thomas Schaaf <tschaaf@cs.cmu.edu>
Co-authored-by: Adrian Wälchli <aedu.waelchli@gmail.com>
Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com>
* added tpu params test
* added tests
* removed xla imports
* added test cases for TPU
* fix pep 8 issues
* refactorings and comments
* add message to MisconfigurationException
Co-authored-by: Adrian Wälchli <aedu.waelchli@gmail.com>
* test if device is set correctly
* added TPU device check
removed mark.spawn
* removed device selection
* remove xla_device call
* readded spawn due to test failures
* add TODO for tpu check
* Apply suggestions from code review
* Apply suggestions from code review
* flake8
* added tpu args to cli tests
* added support for tpu_core selection via cli
* fixed flake formatting
* replaced default_save_path with default_root_dir
* added check for data type for tpu_cores
* fixed flake indent
* protected
* protected
* added tpu params test
* added tests
* removed xla imports
* test if device is set correctly
* added support for tpu_core selection via cli
* replaced default_save_path with default_root_dir
* added check for data type for tpu_cores
* chlog
* fixed tpu cores error
* rebased with latest changes
* flake fix
* Update pytorch_lightning/trainer/distrib_parts.py
added suggesstion
Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com>
Co-authored-by: Adrian Wälchli <aedu.waelchli@gmail.com>
Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com>
Co-authored-by: Jirka <jirka@pytorchlightning.ai>
* Init fix num_batches
* Fix num_batches in case of multiple dataloaders
* Apply suggestions from code review
* Changes based on suggestions
* Flake8
* Add test to check num_batches
* generalize dataloader percent check test
* fix formatting
* remove hparams
* tests
* CHANGELOG
* Update CHANGELOG.md
* max_batches can be int
* conflict and rebase
* add back the test
fix
fix message
0.0 works
Revert "fix message"
This reverts commit 839cacf8b8610f4e697e654ef6f3d2501bf23984.
* update changelog
* Update CHANGELOG.md
* Fix num batches in case of multiple dataloaders and percent_check (#1920)
* git conflict
Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com>
Co-authored-by: Adrian Wälchli <aedu.waelchli@gmail.com>
* missing union
* doc update suggestion by @rohitgr7
* extend test
* changelog
* docs add note about multiple loaders
* update changelog
* remove unused variable
Co-authored-by: rohitgr7 <rohitgr1998@gmail.com>
Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com>
* Fixed average_precision metric, parenthesis were missing. Added test test that failed with the old implementation
* Modified CHANGELOG.md
* Update CHANGELOG.md
Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com>
Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com>
* Revert "deprecated: epoch indexing from 1 (#2206)"
This reverts commit f94b919b
* chlog
* grad index
* Apply suggestions from code review
* tests
* fix
* test
* deal with NotImplementedError raised by torchtext
* deal with NotImplementedError raised by torchtext
* Added tests for dataloader which raise NotImplementedError in __len__()
* Fixed some typos
Co-authored-by: Thomas Schaaf <tschaaf@cs.cmu.edu>
* Fixed the load_from_checkpoint path detected as URL bug
* Fixed the load_from_checkpoint path detected as URL bug
* fixed Caps lock typo
* Added .absolute() to checkpoint path to force hard drive prefix in string
* drop train_percent_check
* drop train_percent_check
* drop train_percent_check
* drop train_percent_check
* drop train_percent_check
* drop train_percent_check
* drop train_percent_check
* drop train_percent_check
* drop train_percent_check
* drop train_percent_check
* drop train_percent_check
* drop train_percent_check
* drop train_percent_check
* drop train_percent_check
* drop train_percent_check
* drop train_percent_check
* drop train_percent_check
* chlog
* deprecated
* deprecated
* deprecated
* tests
* tests
* Apply suggestions from code review
* tests
* hydra support
* tests
* hydra support
* hydra support
* hydra support
* tests
* typo
* typo
* Update test_dataloaders.py
* docs
* docs
* docs
* docs
Co-authored-by: Jirka <jirka@pytorchlightning.ai>
Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com>
* fixed percent check for val/test
* fixed percent check for val/test
* fixed percent check for val/test
* fixed percent check for val/test
* overfit_pct now uses train loaders for val and test and does not shuffle
* overfit_pct now uses train loaders for val and test and does not shuffle
* overfit_pct now uses train loaders for val and test and does not shuffle
* overfit_pct now uses train loaders for val and test and does not shuffle
* overfit_pct now uses train loaders for val and test and does not shuffle
* overfit_pct now uses train loaders for val and test and does not shuffle
* overfit_pct now uses train loaders for val and test and does not shuffle
* overfit_pct now uses train loaders for val and test and does not shuffle
* overfit_pct now uses train loaders for val and test and does not shuffle
* overfit_pct now uses train loaders for val and test and does not shuffle
* overfit_pct now uses train loaders for val and test and does not shuffle
* overfit_pct now uses train loaders for val and test and does not shuffle
* overfit_pct now uses train loaders for val and test and does not shuffle
* overfit_pct now uses train loaders for val and test and does not shuffle
* overfit_pct now uses train loaders for val and test and does not shuffle
* overfit_pct now uses train loaders for val and test and does not shuffle
* overfit_pct now uses train loaders for val and test and does not shuffle
* overfit_pct now uses train loaders for val and test and does not shuffle
* overfit_pct now uses train loaders for val and test and does not shuffle
* overfit_pct now uses train loaders for val and test and does not shuffle
* overfit_pct now uses train loaders for val and test and does not shuffle
* overfit_pct now uses train loaders for val and test and does not shuffle
* overfit_pct now uses train loaders for val and test and does not shuffle
* add on fit_start on fit_end hooks
* add on fit_start on fit_end hooks
* add on fit_start on fit_end hooks
Co-authored-by: Adrian Wälchli <aedu.waelchli@gmail.com>
Co-authored-by: Rohit Gupta <rohitgr1998@gmail.com>
Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com>
* First attempt at auto-moving data for inference
* Correct my copypaste errors
* Correct for if device is CPU
* Get rid of the WIP code I accidentally added
* Add tests
* Make tests more foolproof
* Make sure we stick with pep8 formatting
* Clarify docs a little
* Apply suggestions from code review
* Get everything working again hopefully
* refactor and added hook
variant a
variant b
add test
revert rename
add changelog
docs
* move changelog entry to top
* Move data transfer to utilities
* Add back in warnings for autotransfer
* Get rid of the test code I ended up accidentally commiting again
* Add docs any changelog
* Correct PR number in Changelog
* Correct changelog
* Update data.py
* Update test_cpu.py
* make a decorator
* type hint
* changelog
* changelog
* remove old function
* import
* test for decorator
* fix test
* remove old test
* doctest
* apply decorator directly
* convert doctest to code block
* prevent side effects in tests
* fix merge
* update forward docs
* update docs
* added docs in section "deployment / prediction"
* update changelog
Co-authored-by: Hengjian Jia <henryjia18@gmail.com>
Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com>
Co-authored-by: William Falcon <waf2107@columbia.edu>
* Add ckpt_path option to LightningModule.test()
If ckpt_path is "best" (default), it loads the best weights saved by ModelCheckpoint for the test loop.
If ckpt_path is a path to a checkpoint file, it loads the weights from the file for the test loop.
If ckpt_path is None, it uses the weights from the end of training for the test loop.
If model parameter is set, ckpt_path is ignored.
* Update test_set.rst
Co-authored-by: William Falcon <waf2107@columbia.edu>
* past checkpoints
* omegaConf save
* enforce type
* resolve=True
Co-authored-by: Omry Yadan <omry@fb.com>
* test omegaconf
* tests
* test past
Co-authored-by: Omry Yadan <omry@fb.com>
* allow loading checkpoints from urls
* tmpdir_server fixture
* test cases for loading checkpoints from url
* dir => root_dir
* default map_location to None
* test case for resume_from_checkpoint
* changelog
* doc update
* monkeypatch TORCH_HOME to avoid caching
* Use a threading server with random ports so that it is easier to clean up
* test fixes
* pep8 fix
* ThreadingHTTPServer support in 3.6
* pep8 fix
* fix changelog
* separate tests for urls
* typo
Co-authored-by: Peter Yu <2057325+yukw777@users.noreply.github.com>
* Apply suggestions from code review
Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com>
* do not include local vars in auto collection
* add test
* add test for model with "self" renamed to "obj"
* skip decorator
* changelog
* changelog
* update docs
* remove obsolete child collection
* generalize **args, **kwargs names
* docs
* also update varargs passed in
* Revert "also update varargs passed in"
This reverts commit 3d7a30dbee07a513ee13e1cc3e08ca5ccdb85734.
* update test
* black
Added throught black.toml other options are hard so far
No caching for black github action
Moved from black.toml to pyproject.toml
Exclude not only yml but also yaml
Update pyproject.toml
Co-authored-by: Thomas Johansen <thomasjo@gmail.com>
Update .github/workflows/code-formatting-check.yml
mergify
Remove formating check
E231 error ignoring because of black formating
Updated CONTRIBUTING to the master
* Update .github/workflows/code-formatting-check.yml
* Bump black to 19.10b0 version
* resolved incorrect merge of CONTRIBUTING,
Black skipping string normalization
* Minor fixes in CONTRIBUTING, two typos
* Update setup.cfg
* chlog
Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com>
Co-authored-by: Jirka <jirka@pytorchlightning.ai>
* refactor and added hook
variant a
variant b
add test
revert rename
add changelog
docs
* resolve merge duplication
* overridden typo
* fix test
* tpu id
* raise if TPU not available
* re-use apply_to_collection function for parsing collections
* comment
* make utility function available to user
* documentation
* move changelog entry to top
* fix tpu transfer call
* fix call
* remove hardcoded string
* improve test
* call model hook by default
* Apply suggestions from code review
* rename utility function
Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com>
* Raise an error when lightning replaces an existing sampler
Currently, Trainer replaces the existing sampler with DistributedSampler
if running distributing training and `replace_sampler_ddp=True` (default
behaviour). If a user has configured an existing sampler, this would
lead to widely different results if running a distributed vs
non-distributed training.
This PR fixes this by raising an Error if user has configured a sampler
and uses `replace_sampler_ddp=True`. The recommended behavior from now
on is to either remove the sampler or set `replace_sampler_ddp=False`
* Fix tests
* Simpler fix
* Fix tests
* Make inner method protected
* Apply suggestions from code review
Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com>
* fix grad norm formula
* grad-norm tracker test
* fixed seed and explicit rtol in grad norm tracking test
* a docstring for grad-norms and forced cast to float of norm_type
* support for inf-norm
* renamed the grad norm test
* docs
* fixed language in docstring
* Apply suggestions from code review
Co-authored-by: Jirka <jirka@pytorchlightning.ai>
Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com>
* fix(wandb): use same logger on multiple training loops
New training loops reset step to 0 which would previously try to overwrite logs
fix#2015
* docs(changelog.md): add reference to PR 2055
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* 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>
* saves model every epoch
* implement test for save_last
* Update CHANGELOG.md
* Update CHANGELOG.md
* changes test description
Co-authored-by: Jeremy Jordan <13970565+jeremyjordan@users.noreply.github.com>
Co-authored-by: Jeremy Jordan <13970565+jeremyjordan@users.noreply.github.com>
* 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>
* Option to provide seed to random generators to ensure reproducibility
I added small function in utilities which imports torch, numpy, python
random and sets seed for all of the libraries to ensure reproducibility
of results.
* Apply recommendations from core contributors on seeding
1. Moved the seeding code to another file
2. Make deterministic as a parameter for trainer class
3. Add assertions for seeding numpy
4. Added warnings
5. torch.manual_seed should be enough for seeding torch
* Revert "Apply recommendations from core contributors on seeding"
This reverts commit a213c8e6882eec8a9e7408b9418926d2db7c5461.
* Revert "Revert "Apply recommendations from core contributors on seeding""
This reverts commit 59b2da53c62878de7aab0aa3feb3115e105eea06.
* Change in test, for correct seeding
* Allow seed equal to 0
* Allow seed to be uint32.max
* Added deterministic to benchmarks
* Cuda manual seed as in benchmark seeding
* Seeding should be done before model initialization
* cuda manual_seed is not necessary
* Fixing seed test_cpu_lbfgs
On some seeds seems like lbfgs doesn't converge.
So I fixed the seed during testing.
* rebasing issue with old reproducibility.py
* Improved documentation and ability to seed before initializing Train
class
* Change in docs
* Removed seed from trainer, update for documentation
* Typo in the docs
* Added seed_everything to _all_
* Fixing old changes
* Model initialization should be earlier then Trainer
* Update pytorch_lightning/trainer/__init__.py
From Example to testcode
Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com>
* Fixing according to the contributors suggestions
* Moving horovod deterministic to Trainer class
* deterministic flag affects horovod docs update
* Improved static typing
* Added deterministic to test runners of horovod
It is failing on some versions, not very predictable
* static seeds for horovod tests
* Change for reset_seed function in tests
* Seeding horovod using reset_seed from tutils
* Update pytorch_lightning/trainer/__init__.py
* chlog
* Update trainer.py
* change "testcode" to "Example" in trainer init documentation
* Update pytorch_lightning/trainer/seed.py, first line in comment
Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com>
Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com>
Co-authored-by: Jirka <jirka.borovec@seznam.cz>
Co-authored-by: William Falcon <waf2107@columbia.edu>
* missing
* RC
* tol
* Apply suggestions from code review
Co-authored-by: Adrian Wälchli <aedu.waelchli@gmail.com>
* test
Co-authored-by: Adrian Wälchli <aedu.waelchli@gmail.com>
* update prog. bar metrics on train epoch end
* changelog
* wip test
* more thorough testing
* comments
* update docs
* move test
Co-authored-by: Jirka <jirka.borovec@seznam.cz>
Nicki Skafte