* Fix IoU score for classes not present in target or pred
Fixes#3097
- Allow configurable not_present_score for IoU for classes
not present in target or pred. Defaults to 1.0.
- Also allow passing `num_classes` parameter through from iou
metric class down to its underlying functional iou
call.
* Changelog: move IoU not-present score fix to [unreleased]
* IoU: avoid recomputing class presence in target and pred
Use already-computed support, true positives, and false positives to
determine if a class is not present in either target or pred.
* Test IoU against sklearn jaccard_score
Also add TODO to test our IoU's not_present_score against sklearn's
jaccard_score's zero_division when it beecomes available.
* IoU: remove_bg -> ignore_index
Fixes#2736
- Rename IoU metric argument from `remove_bg` -> `ignore_index`.
- Accept an optional int class index to ignore, instead of a bool and
instead of always assuming the background class has index 0.
- If given, ignore the class index when computing the IoU output,
regardless of reduction method.
* Improve documentation for IoU not_present_score
* Update default IoU not_present_score to 0.0
* Add note about IoU division by zero
* Rename IoU not_present_score -> absent_score
* Update IoU absent score changelog wording
* Condense IoU absent_score argument docstring
* Remove unnecessary IoU ignore_index comment
* docstrings
* isort
* flake8
* Fix test of IoU against sklearn jaccard
Use macro instead of micro averaging in sklearn's jaccard score, to
match multi-class IoU, which conventionally takes per-class scores
before averaging.
Co-authored-by: rohitgr7 <rohitgr1998@gmail.com>
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* 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
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* added base tests for tpu
Co-authored-by: Jirka <jirka@pytorchlightning.ai>
Co-authored-by: Jeremy Jordan <13970565+jeremyjordan@users.noreply.github.com>
* 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>
* 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>
Carlos Mocholí