GitLab

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

Summary:
1. Add changes to support variation of datasets
2. Fix runner to support torchscript export

Reviewed By: wat3rBro

Differential Revision: D26871461

fbshipit-source-id: ec46f7e0d2c14c9b802aec22d78b2a089e962a2f

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

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

Summary: fbgs register_uri_image_loader, UniversalResourceLoader, _IMAGE_LOADER_REGISTRY returns no results other than this file

Reviewed By: newstzpz

Differential Revision: D27639902

fbshipit-source-id: 52e3bb77dbb547334938b8537d6e1c173405d12d

Summary:
we need to load the [config file](https://github.com/facebookresearch/d2go/blob/master/tests/misc/test_configs.py#L35) during the unittest.

The `get_resource_path` need to use `d2go.tests`
https://fburl.com/whn41ma0

The test fail at
https://github.com/facebookresearch/d2go/runs/2272258836

Pull Request resolved: https://github.com/facebookresearch/d2go/pull/35

Reviewed By: wat3rBro

Differential Revision: D27578008

Pulled By: zhanghang1989

fbshipit-source-id: 5fa24c7f74bc3e59ffee98d57f02a2a558c2a4b0

Summary: TorchVision recently upgrade their version to 0.10.0 which causes issues in the version check in detr.

Reviewed By: wat3rBro

Differential Revision: D27575085

fbshipit-source-id: 75f459fe7a711161e908609fcf2f2d28a01a6c74

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

Summary: Add typing to transform.

Reviewed By: wat3rBro

Differential Revision: D27145140

fbshipit-source-id: 8556427b421bf91a05692a590db175c68c4d6890

Summary:
Make data and evaluation visualization optional.
* could return None.

Reviewed By: zhanghang1989, wat3rBro

Differential Revision: D27316632

fbshipit-source-id: 2a85db4815cbf3407a20a74c125dcd52d75167fa

Summary:
Format changes.
* [Option] + [Shift] + [F]

Reviewed By: mattcyu1, zhanghang1989, wat3rBro

Differential Revision: D27316555

fbshipit-source-id: 0fc3396eb34d964478cb3551dc73b47412089ccb

Summary:
#Facebook:

`build_d2go_train_loader` will replace `runner.build_detection_train_loader`, currently we call `build_d2go_train_loader` from `runner.build_detection_train_loader` since some runner has there own implementation, we will solve those cases and remove the `runner.build_detection_train_loader` API.

Currently `build_d2go_train_loader` uses `_MAPPED_TRAIN_LOADER_BUILDER_REGISTRY` to support different versions between OSS and FB, not sure if this is a good pattern or not, please comment in the diff if you have better idea.

Reviewed By: zhanghang1989

Differential Revision: D27505681

fbshipit-source-id: b5caf7280a88c2ebccb498097c0b7af51c966fc6

Reviewed By: newstzpz

Differential Revision: D27255960

fbshipit-source-id: 1699ff23d2bc610dffc0215a90a7c1c17e3783c3

Summary: Fixing unit test that was not listed due to rebase error.

Reviewed By: newstzpz, wat3rBro

Differential Revision: D27456322

fbshipit-source-id: 519c5c086adfb19104ed99234f4f476eb34a79bc

Summary: Train a pix2pix model on the paired dataset. During inference, it can transfer an source image to the target image.

Reviewed By: newstzpz

Differential Revision: D27371290

fbshipit-source-id: 3141bc6d9e4fe0013f6ea3de3cf998163d286168