- 24 Sep, 2021 1 commit
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Yanghan Wang authored
Reviewed By: zhanghang1989 Differential Revision: D31134064 fbshipit-source-id: 825ca14477243a53f84b8521f4430a2b080324bd
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- 15 Sep, 2021 1 commit
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Valentin Andrei authored
Reviewed By: stephenyan1231, zhanghang1989 Differential Revision: D30903817 fbshipit-source-id: 578e6b02a1bd59b1bd841399fc60111d320ae9aa
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- 09 Sep, 2021 1 commit
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Yanghan Wang authored
Summary: https://fb.workplace.com/groups/pythonfoundation/posts/2990917737888352 Remove `mobile-vision` from opt-out list; leaving `mobile-vision/SNPE` opted out because of 3rd-party code. arc lint --take BLACK --apply-patches --paths-cmd 'hg files mobile-vision' allow-large-files Reviewed By: sstsai-adl Differential Revision: D30721093 fbshipit-source-id: 9e5c16d988b315b93a28038443ecfb92efd18ef8
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- 31 Aug, 2021 1 commit
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Yanghan Wang authored
Summary: Enable the inference for boltnn (via running torchscript). - merge rcnn's boltnn test with other export types. - misc fixes. Differential Revision: D30610386 fbshipit-source-id: 7b78136f8ca640b5fc179cb47e3218e709418d71
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- 18 Aug, 2021 2 commits
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Siddharth Shah authored
Summary: A torch version which is batched allows us to avoid CPU <--> GPU copy which gets us ~200ms per iteration saving. This new version of generating boundary weight mask produces identical masks. Reviewed By: wat3rBro Differential Revision: D30176412 fbshipit-source-id: 877f4c6337e7870d3bafd8eb9157ac166ddd588a
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Valentin Andrei authored
Summary: Added multi-tensor optimizer implementation for SGD, from `torch.optim._multi_tensor`. It can potentially provide ~5% QPS improvement by using `foreach` API to speed up the optimizer step. Using it is optional, from the configuration file, by specifying `SGD_MT` in the `SOLVER.OPTIMIZER` setting. Reviewed By: zhanghang1989 Differential Revision: D30377761 fbshipit-source-id: 06107f1b91e9807c1db5d1b0ca6be09fcbb13e67
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- 17 Aug, 2021 1 commit
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Siddharth Shah authored
Summary: The uint8 cast means that the floating point non_bd_weight is never assigned Reviewed By: wat3rBro Differential Revision: D30176377 fbshipit-source-id: 013602bb4313393f220ee0f1510bf1ff83bd56fc
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- 16 Aug, 2021 1 commit
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Hang Zhang authored
Summary: Add FBNAS toolkit for HPO in D2 (https://github.com/facebookresearch/d2go/commit/adf223bdac5b534514a8ba80f6bd61fc9dd8b464)Go Reviewed By: newstzpz Differential Revision: D28672821 fbshipit-source-id: 6a378af2bb43ef6cb556d4158fd1b0d3e363e956
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- 27 Jun, 2021 1 commit
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Yuxin Wu authored
Reviewed By: zhanghang1989 Differential Revision: D29379832 fbshipit-source-id: 9283a8796a1dbee81b51611407c22f7d5a2069dc
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- 25 Jun, 2021 1 commit
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Sam Tsai authored
Summary: "@ [0-9]classes" is appended to datasets to mark whether it is a derived class of the original one and saved as a config. When reloading the config, the derived class name will be used as the source instead of the original source. Adding a check to remove the derived suffix. Reviewed By: wat3rBro Differential Revision: D29315132 fbshipit-source-id: 0cc204d305d2da6c9f1817aaf631270bd874f90d
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- 21 Jun, 2021 1 commit
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Yuxin Wu authored
Summary: 1. save 3 versions of flop count, using both mobile_cv's flop counter and fvcore's flop counter 2. print only a simple short table in terminal, but save others to files The `print_flops` function seems not used anywhere so this diff just replaced it. TODO: enable this feature automatically for train/eval workflows in the next diff Reviewed By: zhanghang1989 Differential Revision: D29182412 fbshipit-source-id: bfa1dfad41b99fcda06b96c4732237b5e753f1bb
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- 16 Jun, 2021 1 commit
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Sam Tsai authored
Summary: Checks for invalid bounding boxes and removes from the being included. Reviewed By: wat3rBro Differential Revision: D28902711 fbshipit-source-id: 1f017d6ccf5c959059bcb94a09ddd81de868feed
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- 14 Jun, 2021 1 commit
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Yanghan Wang authored
Summary: Pull Request resolved: https://github.com/facebookresearch/d2go/pull/83 - Implement `prepare_for_export` for `SemanticSegmentor` - Add unit test comparing numerical matching Reviewed By: zhanghang1989 Differential Revision: D29088421 fbshipit-source-id: ccb86ac4b4b90a63eeebdbf76b2bf31c1da65a8b
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- 01 Jun, 2021 1 commit
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Yanghan Wang authored
Summary: Pull Request resolved: https://github.com/facebookresearch/d2go/pull/77 - Reimplement `get_cfg_diff_table` by reusing other utils - Adding `reorder` option for `flatten_config_dict` - Remove the legacy BC support for `ARCH_DEF`, including `str_wrap_fbnet_arch_def` and customized `merge_from_other_cfg`. - Move `temp_defrost` from `utils.py` to `config.py`, this way there's no more namespace forwarding for `utils.py` - Merge `test_config_utils.py` and `test_configs.py` Reviewed By: zhanghang1989 Differential Revision: D28734493 fbshipit-source-id: 925f5944cf0e9019e4c54462e851ea16a5c94b8c
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- 25 May, 2021 2 commits
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Yanghan Wang authored
Summary: Pull Request resolved: https://github.com/facebookresearch/d2go/pull/75 Refactor the base test case - make test_dir valid throughout the test (rather than under local context), so individual test can load back the export model - refactor the `custom_setup_test` for easier override. - move parameterized into base class to avoid copying naming function Reviewed By: zhanghang1989 Differential Revision: D28651067 fbshipit-source-id: c59a311564f6114039e20ed3a23e5dd9c84f4ae4
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Kai Zhang authored
Summary: Currently when launching a training flow, we read number of processes from resources.num_gpus. To be backward compatible with existing D2 (https://github.com/facebookresearch/d2go/commit/f82d44d3c33e6c781a3c6f2b27b376fdfbaeda53)Go training config, this diff changes to dist_config.num_processes_per_machine instead. Reviewed By: wat3rBro Differential Revision: D28630334 fbshipit-source-id: 3c684cd56e5d2e247c7b82e1d1eeff0f39e59ee4
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- 22 May, 2021 1 commit
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Yanghan Wang authored
Differential Revision: D27881742 (https://github.com/facebookresearch/d2go/commit/90aff5daf608473dd312b300db8615326fa40a37) Original commit changeset: 34a3ab7a88f4 fbshipit-source-id: 42c03b4f2b69c656b26774a4665b84b832262650
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- 21 May, 2021 2 commits
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Sanjeev Kumar authored
Summary: - Enable sdk inference config specification in export step. This enables adding the sdk configuration as part of model file in the export step. The sdk config can be specified as infernece_config.yaml and is zipped together with torchscript model. The main goal of sdk configuration is to control the model inference behavior with model. - SDK inference config design doc: https://docs.google.com/document/d/1j5qx8IrnFg1DJFzTnu4W8WmXFYJ-AgCDfSQHb2ACJsk/edit - One click fblearner pipeline is in next diff on the stack Differential Revision: D27881742 fbshipit-source-id: 34a3ab7a88f456b74841cf671ea1b3f678cdb733
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Sam Tsai authored
Summary: Option to change only bounding boxes, others remain the same. Differential Revision: D28339388 fbshipit-source-id: 7a6d4c5153cf10c473992119f4c684e0b9159b44
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- 17 May, 2021 1 commit
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Kai Zhang authored
Summary: Add dataset visualization so that we could visualize test results in Tensorboard. Reviewed By: zhanghang1989 Differential Revision: D28457363 fbshipit-source-id: 4c2fd9dce349c6fb9e1cec51c9138cf0abb45d7b
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- 12 May, 2021 1 commit
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Luis Perez authored
Synchronize PyTorchLightning/pytorch-lightning (revision 7b283e3c@master) to github/third-party/PyTorchLightning/pytorch-lightning Summary: # Manual - remove fixme's in `model_checkpoint.py`, `parameter_monitor.py`, `test_quantization.py`, and `speed_monitor.py` now that `Trainer` is properly annotated. - update `test_quantization.py` to `trainer.train_loop.global_step` instead of `trainer.global_step` which is a read-only. - update `loop_callback.py` to read from `train_loop` for `batch_idx` (which is no longer available). # Automatic ### New commit log messages 7b283e3c Bugfix/Multiple dataloaders (#7433) d7c44cc6 Docs: sync chlog 1.3.1 (#7478) fdf50a5e Mark certain Trainer APIs as protected (#7420) ad9118f0 remove trainer hidden state | sanity refactor [1 / n] (#7437) 4a1134db Log epoch metrics before firing the `on_evaluation_end` hook (#7272) b65ae794 Automatically check `DataModule.has_{setup,teardown,prepare_data}` [2/2] (#7238) 8660d8cf [pre-commit.ci] pre-commit autoupdate (#7475) f6fe715e Fix Sphinx argument deprecation (#7464) Reviewed By: shuyingsunshine21 Differential Revision: D28353491 fbshipit-source-id: 98b87d99e2f09b47b07270858fcbdb5d5299730b
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- 07 May, 2021 1 commit
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Hang Zhang authored
Summary: Pull Request resolved: https://github.com/facebookresearch/d2go/pull/59 * We have an internal dependency: ``` d2go/export/logfiledb.py", line 8, in <module> from mobile_cv.torch.utils_caffe2.ws_utils import ScopedWS ModuleNotFoundError: No module named 'mobile_cv.torch' ``` This cause the failure of unittest on GitHub https://github.com/facebookresearch/d2go/pull/58/checks?check_run_id=2471727763 * use python 3.8 because another unittest failure on github ci ``` from typing import final ImportError: cannot import name 'final' from 'typing' (/usr/share/miniconda/lib/python3.7/typing.py) ``` Reviewed By: wat3rBro Differential Revision: D28109444 fbshipit-source-id: 95e9774bdaa94f622267aeaac06d7448f37a103f
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- 05 May, 2021 1 commit
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Sam Tsai authored
Summary: Add a bounding manipulation tool to padding bounding box data. Reviewed By: newstzpz Differential Revision: D28082071 fbshipit-source-id: f168cae48672c4fa5c4ec98697c57ed7833787ab
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- 04 May, 2021 1 commit
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Yanghan Wang authored
Reviewed By: newstzpz Differential Revision: D27747996 fbshipit-source-id: 6ae3b89c3944098828e246e5a4a89209b8e171a1
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- 30 Apr, 2021 1 commit
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Sam Tsai authored
Summary: 1. Add a keypoint metadata registry for registering different keypoint metadata 2. Add option to inject_coco_dataset for adding keypoint metadata Reviewed By: newstzpz Differential Revision: D27730541 fbshipit-source-id: c6ba97f60664fce4dcbb0de80222df7490bc6d5d
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- 28 Apr, 2021 1 commit
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Ananth Subramaniam authored
Synchronize PyTorchLightning/pytorch-lightning (revision 7fe8d184@master) to github/third-party/PyTorchLightning/pytorch-lightning Summary: ### New commit log messages 7fe8d184 Do not `shuffle` in `LightningDataModule.from_datasets` for `IterableDataset` (#7053) bab72255 [fix] Add barriers before and after setup hook is run (#7202) f920ba29 [bugfix] Metric not logged properly in manual optimization (#7228) e147127c [feat] Add better support for predict + ddp 2/3 (#7215) ca6c87ff Add back `clip_gradients(model)` (#7231) 3b36d81c Fixed `num_sanity_val_steps` affecting reproducibility of training data shuffling (#7014) 5cf9afa1 Add fairscale install msg for Sharded Plugins (#7213) 52a5cee0 Set smarter default for DDP sharded for performance optimization (#6937) dd5ec75e Deprecate save_function from model checkpoint callback (#7201) ac7d6a35 Fix `NeptuneLogger.log_text(step=None)` (#7194) 6be0a859 Update teardown for TPU acc (#7211) bc3f08b0 [fix] Add barrier to accelerator's teardown (#6814) 68eac4d9 Enforce Lightning module as source of truth for automatic optimization (#7130) 44d775fc Update Error message for ProfileConnector (#7204) 31fcd7d0 Deprecate write_predictions on the LightningModule (#7066) 591b9cee make bug_report_model minimal (#7191) b3fe8366 Move metrics_to_scalars to a dedicated utilities file (#7180) f58865aa Properly set `LightningModule.device` after model replacement (#7188) 8439aead Update FairScale on CI (#7017) 92af3632 Fix `lr_finder` suggesting too high learning rates (#7076) d534e53e add missing predict docs (#7150) Reviewed By: kazhang Differential Revision: D28032962 fbshipit-source-id: 18cd01e8ecc13fe25f0890ac0f4b20c3c3e1fed3
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- 21 Apr, 2021 1 commit
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Kai Zhang authored
Summary: Pull Request resolved: https://github.com/facebookresearch/d2go/pull/46 As titled. The test is flaky because the tensorboard logger might still be writing to temporary folder when we tear down the folder. Reviewed By: ananthsub Differential Revision: D27844504 fbshipit-source-id: 3987f9ec3cd05b2f193e75cd4d85109a46f4ee71
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- 20 Apr, 2021 1 commit
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Kai Zhang authored
Summary: Pull Request resolved: https://github.com/facebookresearch/d2go/pull/49 Reviewed By: wat3rBro Differential Revision: D27875007 fbshipit-source-id: 2f61a4a3de29f3583a54adc914ee5a7eb605a823
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- 19 Apr, 2021 1 commit
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Peizhao Zhang authored
Summary: * Added a registry to register functions that could be used to register hooks for training. * TRAINER_HOOKS_REGISTRY: List of functions to add hooks for trainer, all functions in the registry will be called to add hooks * `func(hooks: List[HookBase]) -> None` Reviewed By: zhanghang1989 Differential Revision: D27560806 fbshipit-source-id: fcfa02623bfd08508b6083db2d318d08f7e3c0b8
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- 17 Apr, 2021 1 commit
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Kai Zhang authored
Summary: Delegate FX quantization callback's customization to model. Reviewed By: wat3rBro Differential Revision: D27669212 fbshipit-source-id: 2715546cf03134896da6f95ecddaf8503ff95d0b
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- 15 Apr, 2021 1 commit
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Yanghan Wang authored
Reviewed By: zhanghang1989 Differential Revision: D27783989 fbshipit-source-id: f05c11e396a2f62366721b365929b29f05d5bc02
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- 14 Apr, 2021 1 commit
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Ananth Subramaniam authored
Synchronize PyTorchLightning/pytorch-lightning (revision 0b843848@master) to github/third-party/PyTorchLightning/pytorch-lightning Summary: ### New commit log messages ## [UnReleased] - 2021-MM-DD ### Added - Added more explicit exception message when trying to execute `trainer.test()` or `trainer.validate()` with `fast_dev_run=True` ([#6667](https://github.com/PyTorchLightning/pytorch-lightning/pull/6667)) - Added `LightningCLI` class to provide simple reproducibility with minimum boilerplate training cli. ([#4492](https://github.com/PyTorchLightning/pytorch-lightning/pull/4492)) - Trigger warning when non-metric logged value with multi processes hasn't been reduced ([#6417](https://github.com/PyTorchLightning/pytorch-lightning/pull/6417)) - Added `gradient_clip_algorithm` argument to Trainer for gradient clipping by value ([#6123](https://github.com/PyTorchLightning/pytorch-lightning/pull/6123)). - Added a way to print to terminal without breaking up the progress bar ([#5470](https://github.com/PyTorchLightning/pytorch-lightning/pull/5470)) - Added support to checkpoint after training steps in `ModelCheckpoint` callback ([#6146](https://github.com/PyTorchLightning/pytorch-lightning/pull/6146)) - Added `checkpoint` parameter to callback's `on_save_checkpoint` hook ([#6072](https://github.com/PyTorchLightning/pytorch-lightning/pull/6072)) - Added `RunningStage.SANITY_CHECKING` ([#4945](https://github.com/PyTorchLightning/pytorch-lightning/pull/4945)) - Added `TrainerState.{FITTING,VALIDATING,TESTING,PREDICTING,TUNING}` ([#4945](https://github.com/PyTorchLightning/pytorch-lightning/pull/4945)) - Added `Trainer.validate()` method to perform one evaluation epoch over the validation set ([#4948](https://github.com/PyTorchLightning/pytorch-lightning/pull/4948)) - Added `LightningEnvironment` for Lightning-specific DDP ([#5915](https://github.com/PyTorchLightning/pytorch-lightning/pull/5915)) - Added `teardown()` hook to LightningDataModule ([#4673](https://github.com/PyTorchLightning/pytorch-lightning/pull/4673)) - Added `auto_insert_metric_name` parameter to `ModelCheckpoint` ([#6277](https://github.com/PyTorchLightning/pytorch-lightning/pull/6277)) - Added arg to `self.log` that enables users to give custom names when dealing with multiple dataloaders ([#6274](https://github.com/PyTorchLightning/pytorch-lightning/pull/6274)) - Added `teardown` method to `BaseProfiler` to enable subclasses defining post-profiling steps outside of `__del__` ([#6370](https://github.com/PyTorchLightning/pytorch-lightning/pull/6370)) - Added `setup` method to `BaseProfiler` to enable subclasses defining pre-profiling steps for every process ([#6633](https://github.com/PyTorchLightning/pytorch-lightning/pull/6633)) - Added no return warning to predict ([#6139](https://github.com/PyTorchLightning/pytorch-lightning/pull/6139)) - Added `Trainer.predict` config validation ([#6543](https://github.com/PyTorchLightning/pytorch-lightning/pull/6543)) - Added `AbstractProfiler` interface ([#6621](https://github.com/PyTorchLightning/pytorch-lightning/pull/6621)) - Added support for including module names for forward in the autograd trace of `PyTorchProfiler` ([#6349](https://github.com/PyTorchLightning/pytorch-lightning/pull/6349)) - Added support for the PyTorch 1.8.1 autograd profiler ([#6618](https://github.com/PyTorchLightning/pytorch-lightning/pull/6618)) - Added `outputs` parameter to callback's `on_validation_epoch_end` & `on_test_epoch_end` hooks ([#6120](https://github.com/PyTorchLightning/pytorch-lightning/pull/6120)) - Added `configure_sharded_model` hook ([#6679](https://github.com/PyTorchLightning/pytorch-lightning/pull/6679)) - Added support for `precision=64`, enabling training with double precision ([#6595](https://github.com/PyTorchLightning/pytorch-lightning/pull/6595)) - Added support for DDP communication hooks ([#6736](https://github.com/PyTorchLightning/pytorch-lightning/issues/6736)) - Added `artifact_location` argument to `MLFlowLogger` which will be passed to the `MlflowClient.create_experiment` call ([#6677](https://github.com/PyTorchLightning/pytorch-lightning/pull/6677)) - Added `model` parameter to precision plugins' `clip_gradients` signature ([#6764](https://github.com/PyTorchLightning/pytorch-lightning/pull/6764)) ### Changed - Renamed `pytorch_lightning.callbacks.swa` to `pytorch_lightning.callbacks.stochastic_weight_avg` ([#6259](https://github.com/PyTorchLightning/pytorch-lightning/pull/6259)) - Refactor `RunningStage` and `TrainerState` usage ([#4945](https://github.com/PyTorchLightning/pytorch-lightning/pull/4945)) - Changed `trainer.evaluating` to return `True` if validating or testing ([#4945](https://github.com/PyTorchLightning/pytorch-lightning/pull/4945)) - Changed `setup()` and `teardown()` stage argument to take any of `{fit,validate,test,predict}` ([#6386](https://github.com/PyTorchLightning/pytorch-lightning/pull/6386)) - Changed profilers to save separate report files per state and rank ([#6621](https://github.com/PyTorchLightning/pytorch-lightning/pull/6621)) - Changed `PyTorchProfiler` to use `torch.autograd.profiler.record_function` to record functions ([#6349](https://github.com/PyTorchLightning/pytorch-lightning/pull/6349)) ### Deprecated - `period` has been deprecated in favor of `every_n_val_epochs` in the `ModelCheckpoint` callback ([#6146](https://github.com/PyTorchLightning/pytorch-lightning/pull/6146)) - Deprecated `trainer.running_sanity_check` in favor of `trainer.sanity_checking` ([#4945](https://github.com/PyTorchLightning/pytorch-lightning/pull/4945)) - Deprecated `Profiler(output_filename)` in favor of `dirpath` and `filename` ([#6621](https://github.com/PyTorchLightning/pytorch-lightning/pull/6621)) - Deprecated `PytorchProfiler(profiled_functions)` in favor of `record_functions` ([#6349](https://github.com/PyTorchLightning/pytorch-lightning/pull/6349)) - Deprecated metrics in favor of `torchmetrics` ([#6505](https://github.com/PyTorchLightning/pytorch-lightning/pull/6505), [#6530](https://github.com/PyTorchLightning/pytorch-lightning/pull/6530), [#6540](https://github.com/PyTorchLightning/pytorch-lightning/pull/6540), [#6547](https://github.com/PyTorchLightning/pytorch-lightning/pull/6547), [#6515](https://github.com/PyTorchLightning/pytorch-lightning/pull/6515), [#6572](https://github.com/PyTorchLightning/pytorch-lightning/pull/6572), [#6573](https://github.com/PyTorchLightning/pytorch-lightning/pull/6573), [#6584](https://github.com/PyTorchLightning/pytorch-lightning/pull/6584), [#6636](https://github.com/PyTorchLightning/pytorch-lightning/pull/6636), [#6637](https://github.com/PyTorchLightning/pytorch-lightning/pull/6637), [#6649](https://github.com/PyTorchLightning/pytorch-lightning/pull/6649), [#6659](https://github.com/PyTorchLightning/pytorch-lightning/pull/6659), ) ### Removed - Removed support for passing a bool value to `profiler` argument of Trainer ([#6164](https://github.com/PyTorchLightning/pytorch-lightning/pull/6164)) - Removed no return warning from val/test step ([#6139](https://github.com/PyTorchLightning/pytorch-lightning/pull/6139)) - Removed passing a `ModelCheckpoint` instance to `Trainer(checkpoint_callback)` ([#6166](https://github.com/PyTorchLightning/pytorch-lightning/pull/6166)) - Removed deprecated Trainer argument `enable_pl_optimizer` and `automatic_optimization` ([#6163](https://github.com/PyTorchLightning/pytorch-lightning/pull/6163)) - Removed deprecated metrics ([#6161](https://github.com/PyTorchLightning/pytorch-lightning/pull/6161)) * from `pytorch_lightning.metrics.functional.classification` removed `to_onehot`, `to_categorical`, `get_num_classes`, `roc`, `multiclass_roc`, `average_precision`, `precision_recall_curve`, `multiclass_precision_recall_curve` * from `pytorch_lightning.metrics.functional.reduction` removed `reduce`, `class_reduce` - Removed deprecated `ModelCheckpoint` arguments `prefix`, `mode="auto"` ([#6162](https://github.com/PyTorchLightning/pytorch-lightning/pull/6162)) - Removed `mode='auto'` from `EarlyStopping` ([#6167](https://github.com/PyTorchLightning/pytorch-lightning/pull/6167)) - Removed legacy references for magic keys in the `Result` object ([#6016](https://github.com/PyTorchLightning/pytorch-lightning/pull/6016)) - Removed deprecated `LightningModule` `hparams` setter ([#6207](https://github.com/PyTorchLightning/pytorch-lightning/pull/6207)) - Removed legacy code to log or include metrics in the progress bar by returning them in a dict with the `"log"/"progress_bar"` magic keys. Use `self.log` instead ([#6734](https://github.com/PyTorchLightning/pytorch-lightning/pull/6734)) - Removed `optimizer_idx` argument from `training_step` in manual optimization ([#6093](https://github.com/PyTorchLightning/pytorch-lightning/pull/6093)) ### Fixed - Set better defaults for `rank_zero_only.rank` when training is launched with SLURM and torchelastic ([#6802](https://github.com/PyTorchLightning/pytorch-lightning/pull/6802/)) - Made the `Plugin.reduce` method more consistent across all Plugins to reflect a mean-reduction by default ([#6011](https://github.com/PyTorchLightning/pytorch-lightning/pull/6011)) - Move lightning module to correct device type when using LightningDistributedWrapper ([#6070](https://github.com/PyTorchLightning/pytorch-lightning/pull/6070)) - Do not print top-k verbose log with `ModelCheckpoint(monitor=None)` ([#6109](https://github.com/PyTorchLightning/pytorch-lightning/pull/6109)) - Fixed csv extension check ([#6436](https://github.com/PyTorchLightning/pytorch-lightning/pull/6436)) - Fixed `ModelCheckpoint(monitor=None, save_last=True)` not saving checkpoints ([#6136](https://github.com/PyTorchLightning/pytorch-lightning/pull/6136)) - Fixed `ModelCheckpoint(save_top_k=0, save_last=True)` not saving the `last` checkpoint ([#6136](https://github.com/PyTorchLightning/pytorch-lightning/pull/6136)) - Fixed `.teardown(stage='fit')` getting called during `trainer.test` ([#6386](https://github.com/PyTorchLightning/pytorch-lightning/pull/6386)) - Fixed `.on_fit_{start,end}()` getting called during `trainer.test` ([#6386](https://github.com/PyTorchLightning/pytorch-lightning/pull/6386)) - Fixed LightningModule `all_gather` on cpu tensors ([#6416](https://github.com/PyTorchLightning/pytorch-lightning/pull/6416)) - Fixed torch distributed not available in setup hook for DDP ([#6506](https://github.com/PyTorchLightning/pytorch-lightning/pull/6506)) - Fixed `EarlyStopping` logic when `min_epochs` or `min_steps` requirement is not met ([#6705](https://github.com/PyTorchLightning/pytorch-lightning/pull/6705)) ## [1.2.7] - 2021-04-06 ### Fixed - Fixed resolve a bug with omegaconf and xm.save ([#6741](https://github.com/PyTorchLightning/pytorch-lightning/pull/6741)) - Fixed an issue with IterableDataset when __len__ is not defined ([#6828](https://github.com/PyTorchLightning/pytorch-lightning/pull/6828)) - Sanitize None params during pruning ([#6836](https://github.com/PyTorchLightning/pytorch-lightning/pull/6836)) - Enforce an epoch scheduler interval when using SWA ([#6588](https://github.com/PyTorchLightning/pytorch-lightning/pull/6588)) - Fixed TPU Colab hang issue, post training ([#6816](https://github.com/PyTorchLightning/pytorch-lightning/pull/6816)) - Fixed a bug where `TensorBoardLogger` would give a warning and not log correctly to a symbolic link `save_dir` ([#6730](https://github.com/PyTorchLightning/pytorch-lightning/pull/6730)) ## [1.2.6] - 2021-03-30 ### Changed - Changed the behavior of `on_epoch_start` to run at the beginning of validation & test epoch ([#6498](https://github.com/PyTorchLightning/pytorch-lightning/pull/6498)) ### Removed - Removed legacy code to include `step` dictionary returns in `callback_metrics`. Use `self.log_dict` instead. ([#6682](https://github.com/PyTorchLightning/pytorch-lightning/pull/6682)) ### Fixed - Fixed `DummyLogger.log_hyperparams` raising a `TypeError` when running with `fast_dev_run=True` ([#6398](https://github.com/PyTorchLightning/pytorch-lightning/pull/6398)) - Fixed error on TPUs when there was no `ModelCheckpoint` ([#6654](https://github.com/PyTorchLightning/pytorch-lightning/pull/6654)) - Fixed `trainer.test` freeze on TPUs ([#6654](https://github.com/PyTorchLightning/pytorch-lightning/pull/6654)) - Fixed a bug where gradients were disabled after calling `Trainer.predict` ([#6657](https://github.com/PyTorchLightning/pytorch-lightning/pull/6657)) - Fixed bug where no TPUs were detected in a TPU pod env ([#6719](https://github.com/PyTorchLightning/pytorch-lightning/pull/6719)) ## [1.2.5] - 2021-03-23 ### Changed - Update Gradient Clipping for the TPU Accelerator ([#6576](https://github.com/PyTorchLightning/pytorch-lightning/pull/6576)) - Refactored setup for typing friendly ([#6590](https://github.com/PyTorchLightning/pytorch-lightning/pull/6590)) ### Fixed - Fixed a bug where `all_gather` would not work correctly with `tpu_cores=8` ([#6587](https://github.com/PyTorchLightning/pytorch-lightning/pull/6587)) - Fixed comparing required versions ([#6434](https://github.com/PyTorchLightning/pytorch-lightning/pull/6434)) - Fixed duplicate logs appearing in console when using the python logging module ([#6275](https://github.com/PyTorchLightning/pytorch-lightning/pull/6275)) - Added Autocast in validation, test and predict modes for Native AMP ([#6565](https://github.com/PyTorchLightning/pytorch-lightning/pull/6565)) Reviewed By: shuyingsunshine21 Differential Revision: D27528929 fbshipit-source-id: 311c88f71461c2c79bbf185e28d7a6d683ccc26f
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- 09 Apr, 2021 2 commits
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Ananth Subramaniam authored
Summary: `checkpoint_callback` now only accepts boolean values: https://github.com/PyTorchLightning/pytorch-lightning/blob/19e67d18c472c3a03dec4dd9bfcef031e9ca8719/pytorch_lightning/trainer/connectors/callback_connector.py#L65-L73 Reviewed By: shuyingsunshine21 Differential Revision: D27682178 fbshipit-source-id: 9e863aad7a23a76dee8ae5df9f5a78e7a94bfe8a
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Ananth Subramaniam authored
Summary: Before: this test would assume only 2 checkpoints were stored: `last.ckpt`, and `FINAL_MODEL_CKPT` Now: this test asserts that at least these 2 checkpoints are stored. In case the config specifies `save_top_k=-1` for instance, we'd save more checkpoints, causing this test to fail Since this test is only loading the last and the final outputs, I'm changing the behavior to assert that these checkpoints must be saved and ignoring other checkpoint files that could be generated. Reviewed By: kazhang Differential Revision: D27671284 fbshipit-source-id: 0419fb46856d048e7b6eba3ff1dc65b7280a9a90
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- 05 Apr, 2021 1 commit
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Owen Wang authored
Summary: Prediction count evaluator needs to gather it's state before computing metrics, otherwise when parallelized across N GPUs, we only get metrics computed from 1/N of the dataset, increasing our eval signal's variance. Reviewed By: wat3rBro Differential Revision: D27416864 fbshipit-source-id: b2c5334cd5a38bebcd06c6ace1627a6b71645fdd
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- 31 Mar, 2021 2 commits
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Kai Zhang authored
Reviewed By: newstzpz Differential Revision: D27255960 fbshipit-source-id: 1699ff23d2bc610dffc0215a90a7c1c17e3783c3
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Sam Tsai authored
Summary: Fixing unit test that was not listed due to rebase error. Reviewed By: newstzpz, wat3rBro Differential Revision: D27456322 fbshipit-source-id: 519c5c086adfb19104ed99234f4f476eb34a79bc
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- 30 Mar, 2021 1 commit
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Sam Tsai authored
Summary: Separate unit tests into individual folder based on functionality. Reviewed By: wat3rBro Differential Revision: D27132567 fbshipit-source-id: 9a8200be530ca14c7ef42191d59795b05b9800cc
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- 24 Mar, 2021 2 commits
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Kai Zhang authored
Summary: Evaluate the predictor generated by previous step. This diff modify the lightning_train_net to reuse the evaluation logic by adding a `predictor_path` param. This diff also makes Lightning training backend depends on `cfg.MODEL.DEVICE` so that in evaluate_predictor step, user could set backend by changing model device. This is useful for evaluating int8 quantized model. Reviewed By: newstzpz Differential Revision: D27150609 fbshipit-source-id: fb72da3e81db932c0fa479350150720143e09a3e
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Kai Zhang authored
Summary: Given that the way to create D2 (https://github.com/facebookresearch/d2go/commit/465cdb842513eb910aa20fcedea1d2edd15dc7b7)go runner and Lightning task are different, get_class was introduced so that in application we could do: ``` if is Lightning: task_cls = get_class(classname) task = task_cls(cfg) else: runner = create_runner(classname) ``` It turns out that we could need to do that in many places: workflow, binaries. This diff revert `get_class` and return class in `create_runner` if the class is a Lightning module. Reviewed By: newstzpz Differential Revision: D26676595 fbshipit-source-id: c3ce2016d09fe073af4c2dd9f98eea4e59ca621b
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