* Add dirpath and filename parameter in ModelCheckpoint
* remove old function
* chlog
* codefactor
* update tests
* docs
* fix doctest and added tests
* pathlib dirpath
* dep version and docs
* try fix doctest
* pep
* suggestions
Co-authored-by: carmocca <carlossmocholi@gmail.com>
* suggestions
* fix test
* pep
* trigger tests
* Apply suggestions from code review
Co-authored-by: Carlos Mocholí <carlossmocholi@gmail.com>
* suggestions
* try fix windows test
* add and update some tests
* trigger tests
* Apply suggestions from code review
* Apply suggestions from code review
Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com>
Co-authored-by: Carlos Mocholí <carlossmocholi@gmail.com>
Co-authored-by: Adrian Wälchli <aedu.waelchli@gmail.com>
Co-authored-by: William Falcon <waf2107@columbia.edu>
* make current_epoch and global_step to be same as trainer, after model restore.
* remove assignment here
* test
* minor modification
* merge with parent's master
* [bug-fix]: update trainer properties
* minor comment fix
* minor comment fix
* reset train loader in `on_train_epoch_start` hook
* makes sure the changes work
* minor chane
* update changelog
* adding unit test for reload_dataloaders_every_epoch arg
* modified changelog, to add PR number
* revert imports
* changes to unit test
Co-authored-by: Adrian Wälchli <aedu.waelchli@gmail.com>
* ref: fix metric err
* ref: fix metric err
* ref: fix metric err
* ref: merge
* ref: merge
* ref: merge
* ref: merge
* ref: decoupled ddp2
* ref: decoupled ddp2
* ref: decoupled ddp2
* ref: decoupled ddp2
* ref: decoupled ddp2
* ref: clean up ddp before final fix
* ref: clean up ddp before final fix
* ref: clean up ddp before final fix
* ref: clean up ddp before final fix
* ref: clean up ddp before final fix
* ref: clean up ddp before final fix
* ref: clean up ddp before final fix
* ref: clean up ddp before final fix
* ref: clean up ddp before final fix
* ref: clean up ddp before final fix
* ref: clean up ddp before final fix
* Split out changes from #3563 to make that PR easier to review. This formats the file according to the Black formatter
* Store a reference to the trainer on the datamodule
Fixes#3682
* Update data_connector.py
* Update data_connector.py
* Update test_datamodules.py
* Split out changes from #3563 to make that PR easier to review. This formats the file according to the Black formatter
* support checkpoint hooks for datamodule
refactor on_{save/load}_checkpoint to a separate hook class that both the lightning module and data module inherit
add spots in callback connector to call new datamodule hooks if available
* hooks formatting
* Update hooks.py
* Update checkpoint_connector.py
* Update lightning.py
* update based on upstream/master
checkout upstream/master
* Update checkpoint_connector.py
* add tests
* undo format revert
* Updated CHANGELOG.md
* add checkpoint hooks
* add Dict type
* import CheckpointHooks
* Split out changes from #3563 to make that PR easier to review. This formats the file according to the Black formatter
* Store a reference to the trainer on the datamodule
Fixes#3682
* Update data_connector.py
* Update data_connector.py
* Update test_datamodules.py
* ref: result 1/n (make monitor default to checkpoint_on to simplify result syntax)
* ref: result 1/n (make monitor default to checkpoint_on to simplify result syntax)
* ref: result 1/n (make monitor default to checkpoint_on to simplify result syntax)
* ref: result 1/n (make monitor default to checkpoint_on to simplify result syntax)
* ref: result 1/n (make monitor default to checkpoint_on to simplify result syntax)
* ref: result 1/n (make monitor default to checkpoint_on to simplify result syntax)
* ref: result 1/n (make monitor default to checkpoint_on to simplify result syntax)
* ref: result 1/n (make monitor default to checkpoint_on to simplify result syntax)
* ref: result 1/n (make monitor default to checkpoint_on to simplify result syntax)
* ref: result 1/n (make monitor default to checkpoint_on to simplify result syntax)
* ref: result 1/n (make monitor default to checkpoint_on to simplify result syntax)
* ref: result 1/n (make monitor default to checkpoint_on to simplify result syntax)
* ref: result 1/n (make monitor default to checkpoint_on to simplify result syntax)
* ref: result 1/n (make monitor default to checkpoint_on to simplify result syntax)
* ref: result 1/n (make monitor default to checkpoint_on to simplify result syntax)
* ref: result 1/n (make monitor default to checkpoint_on to simplify result syntax)
* ref: result 1/n (make monitor default to checkpoint_on to simplify result syntax)
* ref: result 1/n (make monitor default to checkpoint_on to simplify result syntax)
* ref: result 1/n (make monitor default to checkpoint_on to simplify result syntax)
* Update pytorch_lightning/callbacks/model_checkpoint.py
Co-authored-by: ananthsub <ananth.subramaniam@gmail.com>
* ref: result 1/n (make monitor default to checkpoint_on to simplify result syntax)
* force crash when max_epochs < epochs in a checkpoint
Co-authored-by: ananthsub <ananth.subramaniam@gmail.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
* 🎨 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>
* 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>
Rohit Gupta