* 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>
* remove error when test dataloader used in test
* remove error when test dataloader used in test
* remove error when test dataloader used in test
* remove error when test dataloader used in test
* remove error when test dataloader used in test
* remove error when test dataloader used in test
* fix lost model reference
* remove error when test dataloader used in test
* fix lost model reference
* moved optimizer types
* moved optimizer types
* moved optimizer types
* moved optimizer types
* moved optimizer types
* moved optimizer types
* moved optimizer types
* moved optimizer types
* added tests for warning
* fix lost model reference
* fix lost model reference
* added tests for warning
* added tests for warning
* refactoring
* refactoring
* fix imports
* refactoring
* fix imports
* refactoring
* fix tests
* fix mnist
* flake8
* review
Co-authored-by: J. Borovec <jirka.borovec@seznam.cz>
* adding test
* adding test
* added base parity model
* added base parity model
* added parity test
* added parity test
* added parity test
* added parity test
* added parity test
* added parity test
* added parity test
* added parity test
* added parity test
* added parity test
* added parity test
* added parity test
* added parity test
* added parity test
* added parity test
* move parity to benchmark
* formatting
* fixed gradient acc sched
* move parity to benchmark
* formatting
* fixed gradient acc sched
* skip for CPU
* call last
Co-authored-by: J. Borovec <jirka.borovec@seznam.cz>
kumuji