GitLab

Summary:
Pull Request resolved: https://github.com/facebookresearch/d2go/pull/62

Lightning trainer set max step to cfg.SOLVER.MAX_ITER. However, this is the max iteration for all nodes, in multi-node training, we need to scale it down, as well as eval period and other configs.
This diff calls `auto_scale_world_size` before passing the config to trainer.

Reviewed By: wat3rBro

Differential Revision: D28140877

fbshipit-source-id: 2639ae58773a4ec2a0cc59dfefb2f5d9b1afe1a8

Reviewed By: zhanghang1989

Differential Revision: D28346653

fbshipit-source-id: d80a1f824b097c05029edb171739a4928e47e4d8

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

Summary:
Pull Request resolved: https://github.com/facebookresearch/d2go/pull/67

When extending RCNN, sometimes we need to also modify `prepare_for_export/quant`. It might be inconvenient to create new meta-arch just for the purpose of modifying `prepare_for_export/quant`, therefore we create the registry so user can change them via config.

Reviewed By: zhanghang1989

Differential Revision: D28308056

fbshipit-source-id: 4f169eb38292a75d15d3b9f44694480eaa9244e0

Summary: Pull Request resolved: https://github.com/facebookresearch/d2go/pull/66

Reviewed By: zhanghang1989

Differential Revision: D28308297

fbshipit-source-id: 7f6effad7d289546b50f7b16739a04c358a22e21

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

Summary: Add upperbound-model based video evaluation dataset

Reviewed By: yc-fb

Differential Revision: D28122534

fbshipit-source-id: 37cf5ece1c6a5d537b91ae2f7db74a35b97c210d

Summary:
Pull Request resolved: https://github.com/facebookresearch/d2go/pull/63

As titled.

Reviewed By: zhanghang1989

Differential Revision: D27945627

fbshipit-source-id: 58180ace6ab327a5eb025f3227ae6c22601a3580

Summary: build_traceable_model is deprecated, remove it from default runner.

Reviewed By: zhanghang1989

Differential Revision: D28243469

fbshipit-source-id: e09729dcc083dc273329e1c2f731065578d8ea42

Reviewed By: zhanghang1989

Differential Revision: D28243043

fbshipit-source-id: fae5491d8978bcdb096fcee69846c707cda0ac00

Summary: `augment_model_with_bundled_inputs` can compress the tensor when values are constant, however it requires contiguous layout and `zero_like` can return non-contiguous ones

Reviewed By: zhanghang1989

Differential Revision: D28224987

fbshipit-source-id: 32b13728ff8fadd53412dbf2d59c4b46e92af04a

Summary: Add a bounding manipulation tool to padding bounding box data.

Reviewed By: newstzpz

Differential Revision: D28082071

fbshipit-source-id: f168cae48672c4fa5c4ec98697c57ed7833787ab

Summary:
[WIP] Will add pretrained weights and update model url & scores

build mask head using fbnet builder and retrain weights

Reviewed By: wat3rBro

Differential Revision: D27992340

fbshipit-source-id: a216a99954eb3784438d595cd09cbb19e70ec3c3

Reviewed By: newstzpz

Differential Revision: D27747996

fbshipit-source-id: 6ae3b89c3944098828e246e5a4a89209b8e171a1

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

Reviewed By: zhanghang1989

Differential Revision: D28083131

fbshipit-source-id: 8bad642800d3923db3f42047d1b1d85625c01bd9

Reviewed By: zhanghang1989

Differential Revision: D28081681

fbshipit-source-id: 3722f5db668c36c4f23c3fd0c10657a3cf14ad3c

Summary: PointRend mask doesn't work for quantization. Add a patch to disable it.

Reviewed By: wat3rBro

Differential Revision: D27800349

fbshipit-source-id: ae0268ee78b000245ebdb2edbfc679a62c85a59a

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

Summary:
Pull Request resolved: https://github.com/facebookresearch/d2go/pull/54

This arg is being deprecated, and its use case was really only for modules that use functions besides forward for inference.  The new plan is just to optimize every function. Since this script was just created I'm hoping I can edit this without throwing lots of stuff out of wack.

Reviewed By: wat3rBro

Differential Revision: D27954176

fbshipit-source-id: fbe178fcc0404e5d2524d8edb4052e2cd17f43ba

Summary: Customization via `export_predictor` is now deprecated, this diff move the functionality to `FacegenExportMethod`.

Reviewed By: danthe3rd

Differential Revision: D27935492

fbshipit-source-id: 4f35cff7f3709eff290edefce570cfeea47e687d

Summary:
This diff cleans up the process of exporting RCNN to predictor by tracing.
- Implement a new `D2 (https://github.com/facebookresearch/d2go/commit/d86ecc92eb97f14fcd97d626185f61c6817351e4)TorchscriptTracingExport` which utilizes D2 (https://github.com/facebookresearch/d2go/commit/d86ecc92eb97f14fcd97d626185f61c6817351e4)'s `TracingAdapter`. It's capable to handle more complicated input/output data structures, for example the `MultiDictInMultiDictOut` in unit test. Some duplicated code for serializing can also be removed.
- Later on we'll move `DefaultTorchscriptExport` to `mobile_cv.predictor` which doesn't have D2 (https://github.com/facebookresearch/d2go/commit/d86ecc92eb97f14fcd97d626185f61c6817351e4) dependency, while keep `D2 (https://github.com/facebookresearch/d2go/commit/d86ecc92eb97f14fcd97d626185f61c6817351e4)TorchscriptTracingExport` in D2 (https://github.com/facebookresearch/d2go/commit/d86ecc92eb97f14fcd97d626185f61c6817351e4)Go as a more advanced version.
- Using `D2 (https://github.com/facebookresearch/d2go/commit/d86ecc92eb97f14fcd97d626185f61c6817351e4)TorchscriptTracingExport` we can simply the `prepare_for_export` quite a bit and remove hacky code.

Reviewed By: zhanghang1989

Differential Revision: D27931029

fbshipit-source-id: 4a8d5e5ee3f10e29d98fca63e0e1c68bbda22745

Reviewed By: zhanghang1989

Differential Revision: D27916281

fbshipit-source-id: 7ea01e99e9c2a9b19992f458abc786713ba5a4cd

Reviewed By: zhanghang1989

Differential Revision: D27805428

fbshipit-source-id: c588bdb456e606ca333c2f99eb5c3668edddcbfa

Reviewed By: zhanghang1989

Differential Revision: D27898376

fbshipit-source-id: 87549b0cc24bd38f114977503f4eba97e9166ab8

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

Summary:
Pull Request resolved: https://github.com/facebookresearch/d2go/pull/51

As titled. Group the D2 (https://github.com/facebookresearch/d2go/commit/788cf41206fcd761da1974747f0c2c6c671ce871)go runner methods together.

Reviewed By: zhanghang1989, wat3rBro

Differential Revision: D27777726

fbshipit-source-id: f300bce444a401b61ff2adfb45b0c640b1f14855

Summary:
Pull Request resolved: https://github.com/facebookresearch/d2go/pull/50

Found a few custom runners override this method of default runner.

Reviewed By: zhanghang1989, wat3rBro

Differential Revision: D27777505

fbshipit-source-id: 0463cc36bad4af4cbfbe09ab46962cfc1dafbd5d

Summary: model to export is either `nn.Module` and or dict of `nn.Module`

Reviewed By: zhanghang1989

Differential Revision: D27835097

fbshipit-source-id: 869446b36d3e8cc30d6d947f1fc8970cc9ba6c12

Summary: Pull Request resolved: https://github.com/facebookresearch/d2go/pull/49

Reviewed By: wat3rBro

Differential Revision: D27875007

fbshipit-source-id: 2f61a4a3de29f3583a54adc914ee5a7eb605a823

Summary: Add the API to log graph in tensorboard

Reviewed By: wat3rBro

Differential Revision: D27855774

fbshipit-source-id: 415c469c5de0c56fc828d1b95f4be697e0acac84

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

Summary: Delegate FX quantization callback's customization to model.

Reviewed By: wat3rBro

Differential Revision: D27669212

fbshipit-source-id: 2715546cf03134896da6f95ecddaf8503ff95d0b

Summary:
As per title and sanity test E2E QAT workflow on Lightning Trainer.

- add `post_training_opts`. This is required to use `all_steps_qat.json` with Lightning. We don't actually support the post_training_opts in this diff though - we leave it part of T83437359.
- Update .yaml to specify the Quantize-able modules.
- Update `lightning_train_net.py` to use the QuantizationAwareTraining callback.

Reviewed By: kandluis

Differential Revision: D26304879

fbshipit-source-id: 948bef4817d385d8a0969e4990d7f17ecd6994b7

Reviewed By: zhanghang1989

Differential Revision: D27710199

fbshipit-source-id: 178a28972dcc06350e99263f4b38f284cf10c890

Reviewed By: zhanghang1989

Differential Revision: D27783989

fbshipit-source-id: f05c11e396a2f62366721b365929b29f05d5bc02

Summary:
Fix typos in exporter

Pull Request resolved: https://github.com/facebookresearch/d2go/pull/45

Reviewed By: wat3rBro

Differential Revision: D27779963

Pulled By: zhanghang1989

fbshipit-source-id: bcf7922afe6d4cccc074615069538eb5a6098b98

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

Summary:
Pull Request resolved: https://github.com/facebookresearch/d2go/pull/43

- move some of `test_meta_arch_rcnn.py` to oss
- `create_fake_detection_data_loader` doesn't give correct resolution, fix it
- set pooler resolution for faster test

Reviewed By: zhanghang1989

Differential Revision: D27726476

fbshipit-source-id: 063c0a01e95df10f91b58b0692da0546e21c115c

Summary:
- store expiration in meta data when loading dat

- use before_train_hook to rebuild data loader when expiration condition is met.

Reviewed By: zisting

Differential Revision: D27683164

fbshipit-source-id: e3e3c6c15eee7c02c7a1bfed5f4d4d0e67d61a4f