* 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
* replace ddp spawn with subprocess
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* hot fix
* 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>
William Falcon