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  1. 18 Aug, 2021 1 commit
    • Valentin Andrei's avatar
      Add multi-tensor optimizer version for SGD · 918abe42
      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
      918abe42
  3. 17 Aug, 2021 1 commit
  5. 16 Aug, 2021 2 commits
  7. 13 Aug, 2021 1 commit
    • Valentin Andrei's avatar
      Reduce number of parameter groups to make optimizer more efficient · 737d099b
      Valentin Andrei authored 
      Summary:
`torch.optim._multi_tensor` provides faster Optimizer implementations as it uses foreach APIs. We can enable it by modifying from `OPTIMIZER: "ADAMW"` to `OPTIMIZER: "ADAMW_MT"` in the config file.

In order to profit from the speedup, we need to reduce the number of parameter groups as suggested in this post: https://fb.workplace.com/groups/1405155842844877/permalink/4971600462867046/

The current implementation uses one parameter group per parameter which is not optimal. The proposed change groups parameters by learning rate and weight decay combinations.

Reviewed By: zhanghang1989

Differential Revision: D30272112

fbshipit-source-id: d8d24298a59b52c2fc2930f7d614a0c6380a432f
      737d099b
  9. 11 Aug, 2021 3 commits
  11. 06 Aug, 2021 2 commits
  13. 05 Aug, 2021 2 commits
    • Abduallah Mohamed's avatar
      Clarifying the use of do_test function · 610d2d03
      Abduallah Mohamed authored 
      Summary: The `do_test` method might be used to perform testing outside the training process. One might think it will load the weights of the models before testing similar to `do_train` method. This diff adds a comment that clarifies this confusion.

Reviewed By: ppwwyyxx

Differential Revision: D29082338

fbshipit-source-id: 6ec7d7f7f243503414fa904f4eb8856e62e9ed6d
      610d2d03
    • Yuxin Wu's avatar
      avoid warnings of NCCL · 30d5ca55
      Yuxin Wu authored 
      Summary:
Pull Request resolved: https://github.com/facebookresearch/detectron2/pull/3322

avoid warnings like the following:
```
[W ProcessGroupNCCL.cpp:1569] Rank 0 using best-guess GPU 0 to perform barrier as devices used by
this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is
incorrect. Specify device_ids in barrier() to force use of a particular device.
```

maybe can fix the hang in https://github.com/facebookresearch/detectron2/issues/3319

Reviewed By: vaibhava0

Differential Revision: D30077957

fbshipit-source-id: b8827e66c5eecc06b650acde2e7ff44106327f69
      30d5ca55
  15. 04 Aug, 2021 1 commit
  17. 03 Aug, 2021 3 commits
  19. 01 Aug, 2021 1 commit
    • Zhicheng Yan's avatar
      stabilize deformable DETR training · a4f06b88
      Zhicheng Yan authored 
      Summary:
Deformable DETR training can be unstable due to iterative box refinement in the transformer decoder. To stabilize the training, introduce two changes
- Remove the unnecessary use of inverse sigmoid.
It is possible to completely avoid using inverse sigmoid when box refinement is turned on.
- In `DeformableTransformer` class, detach `init_reference_out` before passing it into decoder to update memory and computer per-decoder-layer reference points/

Reviewed By: zhanghang1989

Differential Revision: D29903599

fbshipit-source-id: a374ba161be0d7bcdfb42553044c4c6700e92623
      a4f06b88
  21. 29 Jul, 2021 1 commit
  23. 21 Jul, 2021 1 commit
    • Xi Yin's avatar
      fix bug in valid_bbox check · b4d9aad9
      Xi Yin authored 
      Summary: In case the height/width is None, the original version will cause a crash. So adding additional check to bypass this issue.

Reviewed By: ppwwyyxx

Differential Revision: D29807853

fbshipit-source-id: b2b1a7edb52b7911da79a11329d4cf93f343c279
      b4d9aad9
  25. 14 Jul, 2021 1 commit
  27. 09 Jul, 2021 2 commits
    • Mircea Cimpoi's avatar
      Add tests for exporter / boltnn export via torch delegate · d0c38c43
      Mircea Cimpoi authored 
      Summary:
Adding test for previous diff.
Boltnn backend is supported on device -- so this test only checks if the conversion takes place and the output file is present.

Differential Revision: D29589245

fbshipit-source-id: ba66a733295304531d177086ce6459a50cfbaa07
      d0c38c43
    • Mircea Cimpoi's avatar
      Add BoltNN conversion to d2go exporter · ecf832da
      Mircea Cimpoi authored 
      Summary:
Added predictor_type `boltnn_int8` to export to BoltNN via torch delegate.

- `int8` needs to be in the name, otherwise the post-train quantization won't happen;

```
cfg.QUANTIZATION.BACKEND = "qnnpack"
// cfg.QUANTIZATION.CUSTOM_QSCHEME = "per_tensor_affine"
```

Seems that ` QUANTIZATION.CUSTOM_QSCHEME per_tensor_affine` is not needed - likely covered by "qnnpack".

Reviewed By: wat3rBro

Differential Revision: D29106043

fbshipit-source-id: 865ac5af86919fe7b4530b48433a1bd11e295bf4
      ecf832da
  29. 08 Jul, 2021 3 commits
    • Zhicheng Yan's avatar
      fix a bug in D2GoDatasetMapper · abf2f327
      Zhicheng Yan authored 
      Summary:
Pull Request resolved: https://github.com/facebookresearch/d2go/pull/101

In D2 (https://github.com/facebookresearch/d2go/commit/4f3f3401173ee842995ec69a7ce2635e2deb178a)GoDatasetMapper, when crop transform is applied to the image. "Inputs" should be updated to use the cropped images before other transforms are applied later.

Reviewed By: zhanghang1989

Differential Revision: D29551488

fbshipit-source-id: 48917ffc91c8a80286d61ba3ae8391541ec2c930
      abf2f327
    • Zhicheng Yan's avatar
      remove redundant build_optimizer() · b1e2cc56
      Zhicheng Yan authored 
      Summary:
Pull Request resolved: https://github.com/facebookresearch/d2go/pull/96

In `DETRRunner`, the method `build_optimizer` customized the following logics, which are actually redundant to parent class implementation and can be removed.
- Discount LR for certain modules, such as those with name `reference_points`, `backbone`, and `sampling_offsets`.
  - Those can be achieved by `SOLVER.LR_MULTIPLIER_OVERWRITE` after we update `get_default_optimizer_params` in `mobile-vision/d2go/d2go/optimizer/build.py`.
- Full model gradient clipping
  - This is also implemented in `mobile-vision/d2go/d2go/optimizer/build.py`

It also has minor issues
- It ignores `SOLVER.WEIGHT_DECAY_NORM` which can set a different weight decay for affine parameters in the norm modules.

Reviewed By: zhanghang1989

Differential Revision: D29420642

fbshipit-source-id: deeb9348c9d282231c540dde6161acedd8e3a119
      b1e2cc56
    • Sam Tsai's avatar
      fix extended coco load missing comma · 4f3f3401
      Sam Tsai authored 
      Summary: Fix missing comma for extended coco load, which would ignore bbox_mode and keypoints field.

Reviewed By: zhanghang1989

Differential Revision: D29608815

fbshipit-source-id: 8c737df1dfef7f88494f7de25e06b0c37742ac30
      4f3f3401
  31. 07 Jul, 2021 1 commit
  33. 06 Jul, 2021 1 commit
    • Cheng-Yang Fu's avatar
      Add the fields which will be used in point-based modeling. · 80c18641
      Cheng-Yang Fu authored 
      Summary:
Add the fields which will be used in point-based modeling.
- `point_coords` : indicates the point_coords in the image.
- `point_labels`: indicates the foreground or background points.

Differential Revision: D29532103

fbshipit-source-id: 9af6c9b049e1d05fd0d77909b09de1feec391ce9
      80c18641
  35. 02 Jul, 2021 1 commit
    • Zhicheng Yan's avatar
      revert D29048363 · e69e0ffe
      Zhicheng Yan authored 
      Summary:
In D29048363 (https://github.com/facebookresearch/d2go/commit/c480d4e4e213a850cced7758f7b62c20caad8820) we make the detaching of `reference_points` earlier in the hope of allowing more gradient flow to update weights in `self.bbox_embed`.
In this diff, we revert the changes as i) it does not improve box AP ii) it may potential cause in-stable optimization when iterative box refinement is turned on.

Reviewed By: zhanghang1989

Differential Revision: D29530735

fbshipit-source-id: 3217c863343836e129d53e07c0eedb2db8164fe6
      e69e0ffe
  37. 01 Jul, 2021 1 commit
  39. 30 Jun, 2021 3 commits
  41. 29 Jun, 2021 3 commits
  43. 27 Jun, 2021 2 commits
    • Kai Zhang's avatar
      Move EMA weights to current device before training · 9d9f438b
      Kai Zhang authored 
      Summary:
Currently we move EMA weights to expected device right after loading from checkpoint.
However, by the time on_load_checkpoint hook is called, current GPU device has not been assigned. This could lead to EMA weights on cuda:0 while the model is on cuda:1.
This diff move EMA weights to device in `on_pretrain_routine_end` instead.

Reviewed By: zhanghang1989

Differential Revision: D28429843

fbshipit-source-id: d864fb3687eb6958872300c5ec0af7ce90591f83
      9d9f438b
    • Yuxin Wu's avatar
      enable flop printing & logging at the beginning of train & test · 5509a138
      Yuxin Wu authored 
      Reviewed By: zhanghang1989

Differential Revision: D29379832

fbshipit-source-id: 9283a8796a1dbee81b51611407c22f7d5a2069dc
      5509a138
  45. 26 Jun, 2021 1 commit
    • Kai Zhang's avatar
      Fix quantization test failure · 1894f8a3
      Kai Zhang authored 
      Summary:
# Context
In post training quantization callback, we make a deepcopy of the Lightning module before validation start and prepare the copy with FX quantization API. The callback keeps the prepared model inside it.

# The problem
By the second time we run the validation epoch, we try to make a copy of the Lightning module, which has a reference to trainer, which has a reference to quantization callback, which has a prepared model, which is not deepcopiable.

# Mitigation
Delete the trainer before making a deepcopy.
We're already doing that in stl/callbacks/quantization, but the changes were not ported into D2 (https://github.com/facebookresearch/d2go/commit/4169abc18ec539a24081b179fcbbc5a5754d102b)Go.

Reviewed By: zhanghang1989

Differential Revision: D29409085

fbshipit-source-id: 24550124181673b2e567b2a04563bcdfb440e145
      1894f8a3
  47. 25 Jun, 2021 2 commits
    • Haricharan Lakshman's avatar
      Freeze matched bn layers · 4169abc1
      Haricharan Lakshman authored 
      Summary:
Convert the batchnorm layers that match the specified regular expressions to FrozenBatchNorm2d.

If module is an instance of batchnorm and it matches the reg exps, returns a new FrozenBatchNorm2d module.

Otherwise, in-place converts the matching batchnorm child modules to FrozenBatchNorm2d
and returns the main module.

Reviewed By: ppwwyyxx

Differential Revision: D29286500

fbshipit-source-id: 3a20f5eeff59ddff50c42fe297eedf0ce2b909bc
      4169abc1
    • Luming Ma's avatar
      read "bbox_mode" from annotation when filtering out images with invalid bbox · 77ef0db7
      Luming Ma authored 
      Summary: Some annotations are using XYXY_ABS for bbox mode so that many images were incorrectly filtered out by assuming XYWH_ABS mode. This diff read bbox_mode from annotation and convert bbox to XYWH_ABS before checking invalid bbox.

Differential Revision: D29365700

fbshipit-source-id: 355346b6826f401f504691090631997e169ead4a
      77ef0db7