Commit Graph

124 Commits

Author SHA1 Message Date
fc2cf3d26f Back out "Revert D34805092: Extend _save_for_mobile and _load_for_mobile to support flatbuffer format; Default format is pickle + Change buck targets to support only pickle and pickle + flatbuffer for migration" (#74594)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/74594

Extending `_save_for_mobile` and `_load_for_mobile` to support faltbuffer format with additional optional argument which is set to pick pickle by default.

Adding new binary target with suffix `_pickle_and_flatbuffer` to help migration.

Size test in D34909502 shows the size has regressed by ~40K but after removing pickle and comparing lite_predictors we have ~120K size measure that we will achieve when deprecating pickle and moving to flatbuffer

**BEFORE:**

```lang=mermaid
graph TD;
    torch_core-->torch_mobile_deserialize;

    torch_mobile_core-->torch_mobile_deserialize;

    jit_module_saving-->torch_core;
    jit_module_saving-->torch_mobile_core;

    torch_mobile_deserialize-->caffe2_serialize;
    torch_mobile_deserialize-->torch_mobile_module;

    caffe2_serialize-->miniz;

    flatbuffer_loader-->mobile_bytecode;
    flatbuffer_serializer-->mobile_bytecode;

    mobile_bytecode-->flatbuffer_2.0;

    flatbuffer_loader-->torch_mobile_module;
    flatbuffer_serializer-->torch_mobile_module;
```

**AFTER:**
```lang=mermaid
graph TD;
    torch_core-->torch_mobile_deserialize;

    torch_mobile_core-->torch_mobile_deserialize;

    jit_module_saving-->torch_core;
    jit_module_saving-->torch_mobile_core;

    torch_mobile_deserialize-->caffe2_serialize;
    torch_mobile_deserialize-->torch_mobile_module;

    caffe2_serialize-->miniz;

    flatbuffer_loader-->mobile_bytecode;
    flatbuffer_serializer-->mobile_bytecode;

    mobile_bytecode-->flatbuffer_2.0;

    torch_mobile_deserialize_pickle_and_flatbuffer-->|new| flatbuffer_loader;
    torch_mobile_deserialize_pickle_and_flatbuffer-->|new| torch_mobile_deserialize;
    torch_mobile_core_pickle_and_flatbuffer-->|new| torch_mobile_deserialize_pickle_and_flatbuffer;
    torch_core_pickle_and_flatbuffer-->|new| torch_mobile_deserialize_pickle_and_flatbuffer;

    jit_module_saving_pickle_and_flatbuffer-->|new| torch_core_pickle_and_flatbuffer;
    jit_module_saving_pickle_and_flatbuffer-->|new| torch_mobile_core_pickle_and_flatbuffer;

    flatbuffer_serializer-->torch_mobile_module;

    jit_module_saving_pickle_and_flatbuffer-->|new|jit_module_saving;
    jit_module_saving_pickle_and_flatbuffer-->|new|flatbuffer_serializer;

    flatbuffer_loader-->torch_mobile_module;
```

Original commit changeset: 780dfb6fd6ba

Original Phabricator Diff: D34805092 (284b2b7135)
ghstack-source-id: 152044801

(Note: this ignores all push blocking failures!)

Test Plan:
CI

```
~/fbsource/fbcode] cd ~/fbsource/fbcode/ && buck test -c fbcode.caffe2_enable_flatbuffer=1 //caffe2/test/cpp/jit:jit  -- FlatbufferTest.ExtraFiles
Parsing buck files: finished in 0.9 sec
Building: finished in 5.3 sec (100%) 12992/54304 jobs, 0/54304 updated
  Total time: 6.2 sec
More details at https://www.internalfb.com/intern/buck/build/2b387fff-f813-4cfa-b53f-eb2378630d4e
BUILD SUCCEEDED
Tpx test run coordinator for Facebook. See https://fburl.com/tpx for details.
Running with tpx session id: f93a84d6-e7ce-41a0-a97f-0ef3fa6d199d
Trace available for this run at /tmp/tpx-20220323-134108.766518-f93a84d6-e7ce-41a0-a97f-0ef3fa6d199d/trace.log
RemoteExecution session id: reSessionID-f93a84d6-e7ce-41a0-a97f-0ef3fa6d199d-tpx
Started reporting to test run: https://www.internalfb.com/intern/testinfra/testrun/4503599723101693
    ✓ ListingSuccess: caffe2/test/cpp/jit:jit : 486 tests discovered (19.122)
    ✓ Pass: caffe2/test/cpp/jit:jit - FlatbufferTest.ExtraFiles (0.187)
Summary
  Pass: 1
  ListingSuccess: 1
If you need help understanding your runs, please follow the wiki: https://fburl.com/posting_in_tpx_users
Finished test run: https://www.internalfb.com/intern/testinfra/testrun/4503599723101693
```

Similar Build Deps Dags

```
[pavithran@devvm5216.vll0 /data/users/pavithran/fbsource] buck query 'allpaths(//xplat/caffe2:torch_mobile_all_ops_pickle_and_flatbuffer, //xplat/caffe2:torch_mobile_deserialize_pickle_and_flatbuffer)' --output-format dot-compact  | pastry
P486770901: https://www.internalfb.com/intern/paste/P486770901/

[pavithran@devvm5216.vll0 /data/users/pavithran/fbsource] buck query 'allpaths(//xplat/caffe2:torch_mobile_all_ops, //xplat/caffe2:torch_mobile_deserialize)' --output-format dot-compact  | pastry
P486771278: https://www.internalfb.com/intern/paste/P486771278/
```

pickle_and_flatbuffer: https://www.internalfb.com/intern/dgw/graph/?build_id=P486770901
pickle: https://www.internalfb.com/intern/dgw/graph/?build_id=P486771278

Reviewed By: iseeyuan

Differential Revision: D35067157

fbshipit-source-id: 9044259c17a2e0da79bd6aedb28efbdfd57e23e0
(cherry picked from commit f738069ec3a72e79da56172741d027de514e9e5f)
2022-03-24 21:51:05 +00:00
c53b3ed20f Revert D34805092: Extend _save_for_mobile and _load_for_mobile to support flatbuffer format; Default format is pickle + Change buck targets to support only pickle and pickle + flatbuffer for migration
Test Plan: revert-hammer

Differential Revision:
D34805092 (284b2b7135)

Original commit changeset: 57f3fc81d68f

Original Phabricator Diff: D34805092 (284b2b7135)

fbshipit-source-id: 780dfb6fd6ba5f9348f24a2fb3c57971b7155541
(cherry picked from commit bebeb8b84e11c34cbde4857d0e1c291731a7c781)
2022-03-22 22:45:50 +00:00
284b2b7135 Extend _save_for_mobile and _load_for_mobile to support flatbuffer format; Default format is pickle + Change buck targets to support only pickle and pickle + flatbuffer for migration (#74209)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/74209

Extending `_save_for_mobile` and `_load_for_mobile` to support faltbuffer format with additional optional argument which is set to pick pickle by default.

Adding new binary target with suffix `_pickle_and_flatbuffer` to help migration.

Size test in D34909502 shows the size has regressed by ~40K but after removing pickle and comparing lite_predictors we have ~120K size measure that we will achieve when deprecating pickle and moving to flatbuffer

**BEFORE:**

```lang=mermaid
graph TD;
    torch_core-->torch_mobile_deserialize;

    torch_mobile_core-->torch_mobile_deserialize;

    jit_module_saving-->torch_core;
    jit_module_saving-->torch_mobile_core;

    torch_mobile_deserialize-->caffe2_serialize;
    torch_mobile_deserialize-->torch_mobile_module;

    caffe2_serialize-->miniz;

    flatbuffer_loader-->mobile_bytecode;
    flatbuffer_serializer-->mobile_bytecode;

    mobile_bytecode-->flatbuffer_2.0;

    flatbuffer_loader-->torch_mobile_module;
    flatbuffer_serializer-->torch_mobile_module;
```

**AFTER:**
```lang=mermaid
graph TD;
    torch_core-->torch_mobile_deserialize;

    torch_mobile_core-->torch_mobile_deserialize;

    jit_module_saving-->torch_core;
    jit_module_saving-->torch_mobile_core;

    torch_mobile_deserialize-->caffe2_serialize;
    torch_mobile_deserialize-->torch_mobile_module;

    caffe2_serialize-->miniz;

    flatbuffer_loader-->mobile_bytecode;
    flatbuffer_serializer-->mobile_bytecode;

    mobile_bytecode-->flatbuffer_2.0;

    torch_mobile_deserialize_pickle_and_flatbuffer-->|new| flatbuffer_loader;
    torch_mobile_deserialize_pickle_and_flatbuffer-->|new| torch_mobile_deserialize;
    torch_mobile_core_pickle_and_flatbuffer-->|new| torch_mobile_deserialize_pickle_and_flatbuffer;
    torch_core_pickle_and_flatbuffer-->|new| torch_mobile_deserialize_pickle_and_flatbuffer;

    jit_module_saving_pickle_and_flatbuffer-->|new| torch_core_pickle_and_flatbuffer;
    jit_module_saving_pickle_and_flatbuffer-->|new| torch_mobile_core_pickle_and_flatbuffer;

    flatbuffer_serializer-->torch_mobile_module;

    jit_module_saving_pickle_and_flatbuffer-->|new|jit_module_saving;
    jit_module_saving_pickle_and_flatbuffer-->|new|flatbuffer_serializer;

    flatbuffer_loader-->torch_mobile_module;
```
ghstack-source-id: 151744258

Test Plan:
Similar Build Deps Dags

```
[pavithran@devvm5216.vll0 /data/users/pavithran/fbsource] buck query 'allpaths(//xplat/caffe2:torch_mobile_all_ops_pickle_and_flatbuffer, //xplat/caffe2:torch_mobile_deserialize_pickle_and_flatbuffer)' --output-format dot-compact  | pastry
P486770901: https://www.internalfb.com/intern/paste/P486770901/

[pavithran@devvm5216.vll0 /data/users/pavithran/fbsource] buck query 'allpaths(//xplat/caffe2:torch_mobile_all_ops, //xplat/caffe2:torch_mobile_deserialize)' --output-format dot-compact  | pastry
P486771278: https://www.internalfb.com/intern/paste/P486771278/
```

pickle_and_flatbuffer: https://www.internalfb.com/intern/dgw/graph/?build_id=P486770901
pickle: https://www.internalfb.com/intern/dgw/graph/?build_id=P486771278

Reviewed By: iseeyuan

Differential Revision: D34805092

fbshipit-source-id: 57f3fc81d68fce941a050c35bd8e6f05951183b3
(cherry picked from commit 671ae4ed29e65b86ffe507a503548d3e86ab0ea4)
2022-03-22 20:00:53 +00:00
0723639b60 Revert D34455360: Multisect successfully blamed D34455360 for test failures
Summary:
This diff is reverting D34455360 (61d6c43864)
D34455360 (61d6c43864) is making the following tests to fail and this revert diff is either the revert of the blame diff or the revert of the stack of diffs that need to be reverted to revert the blame diff

Tests affected:
- https://www.internalfb.com/intern/test/562950004334605/

Multisect link:
https://www.internalfb.com/intern/testinfra/multisect/756170

Test Plan: NA

Reviewed By: zhxchen17

Differential Revision: D34596156

fbshipit-source-id: a465bca0094db3caf6130c80f1ed49eea981359b
(cherry picked from commit ef5e5578c64ce9827570757fb016aafa9c782c6a)
2022-03-08 23:18:54 +00:00
61d6c43864 Make debug_pkl smaller by only emitting unique traces. (#73368)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/73368

debug_pkl file inside of pytorch's .pt file consists of a list of SourceRanges. Each SourceRange points to a Source which is a stack track, filename, and start, end numbers. Those are emitted in debug_pkl file as strings.
Since many SourceRange shares the same source, the string for trace can be deduped.
The newer format saves a set of unique traces in a tuple, then each SourceRange will save the offset of it's trace w.r.t. position in that tuple. (i.e. manually applying dictionary compression).
The above helps with smaller file size. On loading, if we copy each trace to Source as string the runtime memory would still blowup.
To mitigate this, we use SourceView directly instead of source which will take the reference of string inside of Deserializer and make that into string_view. This is safe because Deserializer is hold by Unpickler by shared_ptr, and Unpickler is also hold by shared_ptr by another Source object. That Source object will be alive during the model construction.

Test Plan:
unit test

Took original file (312271638_930.predictor.disagg.local); loaded with `torch.jit.load` save again with `torch.jit.save`. Unzip both, look at contents:
```
[qihan@devvm5585.vll0 ~]$ du archive -h
4.0K    archive/xl_model_weights
3.7M    archive/extra
8.0K    archive/code/__torch__/caffe2/torch/fb/model_transform/splitting
8.0K    archive/code/__torch__/caffe2/torch/fb/model_transform
8.0K    archive/code/__torch__/caffe2/torch/fb
8.0K    archive/code/__torch__/caffe2/torch
8.0K    archive/code/__torch__/caffe2
20M     archive/code/__torch__/torch/fx/graph_module
20M     archive/code/__torch__/torch/fx
8.0K    archive/code/__torch__/torch/classes
20M     archive/code/__torch__/torch
20M     archive/code/__torch__
20M     archive/code
2.7M    archive/constants
35M     archive
[qihan@devvm5585.vll0 ~]$ du resaved -h
4.0K    resaved/extra
8.0K    resaved/code/__torch__/caffe2/torch/fb/model_transform/splitting
8.0K    resaved/code/__torch__/caffe2/torch/fb/model_transform
8.0K    resaved/code/__torch__/caffe2/torch/fb
8.0K    resaved/code/__torch__/caffe2/torch
8.0K    resaved/code/__torch__/caffe2
1.3M    resaved/code/__torch__/torch/fx/graph_module
1.3M    resaved/code/__torch__/torch/fx
8.0K    resaved/code/__torch__/torch/classes
1.4M    resaved/code/__torch__/torch
1.4M    resaved/code/__torch__
1.4M    resaved/code
2.7M    resaved/constants
13M     resaved
[qihan@devvm5585.vll0 ~]$
```

Reviewed By: gmagogsfm

Differential Revision: D34455360

fbshipit-source-id: 8cc716f9bba7183746b1b4ecc33a2de34ac503b9
(cherry picked from commit f1a04730fc9ac8fdab6c8e4c44cb5529e42090e4)
2022-03-02 08:37:08 +00:00
bbac8c9c48 [ONNX] List of files to consider for mergebot onnx rule (#72297)
Summary:
Based on past PRs, here is an non-exhaustive list of files to consider for extension. The PR is not meant to be final. Based on feedback and discussion, files could be dropped from the list, or PR could be updated to move code around such that extension is no longer needed.

List of files below and description:

* These files are for converting from IR to ONNX proto. These should be used only for ONNX.
```
"torch/csrc/jit/serialization/export.*",
"torch/csrc/jit/serialization/onnx.*",
```

* This file is touched whenever pass signature is updated.
```
"torch/_C/__init__.pyi.in",
```

* These files are touched whenever pass signature is updated. Somehow it's been convention that onnx passes are also added here, but it could be possible to move them. Let me know what you think.
~~"torch/csrc/jit/python/init.cpp",~~
~~"torch/csrc/jit/python/script_init.cpp",~~
Update: Bowen will move onnx passes to files under onnx folder.

* ~~Touched when need new attr::xxx, or onnx::xxx.~~
~~"aten/src/ATen/core/interned_strings.h"~~
Update: Nikita will help separate this file.

malfet

Pull Request resolved: https://github.com/pytorch/pytorch/pull/72297

Reviewed By: H-Huang

Differential Revision: D34254666

Pulled By: malfet

fbshipit-source-id: 032cfa590cbedf4648b7335fe8f09a2380ab14cb
(cherry picked from commit 88653eadbf5b6dfe1f84acec8f1c3256a49f2f68)
2022-02-16 23:01:13 +00:00
bbd42c605a [JIT] Opinfo tests for nnc fusion - retry (#72486)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/72486

Retry #70465.

Test Plan: Imported from OSS

Reviewed By: mikaylagawarecki

Differential Revision: D34061628

Pulled By: davidberard98

fbshipit-source-id: e27ed315bc4ad57cdbfbc9cedffcbb7886004524
(cherry picked from commit 7937808d2ebcc758aad4eac3ae6ffe1056d13fc5)
2022-02-09 19:01:22 +00:00
bb101ec78d Revert D33595240: [JIT] Opinfo tests for nnc fusion
Test Plan: revert-hammer

Differential Revision:
D33595240 (0b57bd4c66)

Original commit changeset: e2e17a921bc3

Original Phabricator Diff: D33595240 (0b57bd4c66)

fbshipit-source-id: 172a3ffd19d180b1b3617956b1f881be62f37bc9
(cherry picked from commit 324cfaea863aafa36a825c066a0b115bbc138890)
2022-02-08 01:28:42 +00:00
0b57bd4c66 [JIT] Opinfo tests for nnc fusion (#70465)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/70465

These tests check to ensure that
(a) the result after nnc fusion (of a single op) is the same as the
unfused op
(b) for certain ops where fusion is expected to occur, ensure that
fusion does actually occur

Test Plan: Imported from OSS

Reviewed By: wenleix

Differential Revision: D33595240

Pulled By: davidberard98

fbshipit-source-id: e2e17a921bc30c313e92e8e5bbc6c1b5fcd14bc1
(cherry picked from commit b1ba221acc72f2d603b8ab0f79501786f65038ad)
2022-02-07 20:56:21 +00:00
c5df294940 Fix bug in upgrader generation in mobile (#71578)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/71578

Use more robust way of extracting upgrader min and max versions

Test Plan: omgitsgreen

Reviewed By: cccclai

Differential Revision: D33690113

fbshipit-source-id: 79a964acb26d7ca1354e104710a285b8da3f46d1
(cherry picked from commit 9e316ee5c12e7bce9b17edebec2eeb38ecabd336)
2022-01-28 18:20:59 +00:00
e849c8b0f2 Move bytecode generation to python (#71681)
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/71681

Test Plan: Imported from OSS

Reviewed By: gmagogsfm, cccclai

Differential Revision: D33730791

Pulled By: tugsbayasgalan

fbshipit-source-id: e752e9ae20c01a57a3bea270f604215fdcc9182e
(cherry picked from commit 69c9dc0548d794a6b3be8e1f9967e5fd56310a29)
2022-01-28 02:33:00 +00:00
e755a4f124 Update the operator version check logic when generating models for testing upgraders (#71894)
Summary:
The model generation script will check the model version, to ensure the developer run the script before they change operator

Previously, the version use the old model version. However, it's hard for developer to know the old version number. In this change, it use the current max operator version to check. It's less strict, but more developer friendly

Pull Request resolved: https://github.com/pytorch/pytorch/pull/71894

ghstack-source-id: 147769215

Test Plan:
first time run:
```
chenlai@devvm5615:~/fbsource/fbcode(b82243650)$ buck run mode/opt //caffe2/torch/fb/mobile/upgrader_codegen:upgrader_test_models_gen
Parsing buck files: finished in 0.7 sec
Downloaded 0/2 artifacts, 0.00 bytes, 100.0% cache miss (for updated rules)
Building: finished in 21.6 sec (100%) 11547/11547 jobs, 2/11547 updated
  Total time: 22.4 sec
BUILD SUCCEEDED
TestVersionedDivTensorExampleV7() aten::div.Tensor
INFO:test.jit.fixtures_srcs.generate_models:Processing TestVersionedDivTensorExampleV7
INFO:test.jit.fixtures_srcs.generate_models:Generating model test_versioned_div_tensor_example_v7 and it's save to /data/users/chenlai/fbsource/fbcode/caffe2/test/jit/fixtures/test_versioned_div_tensor_example_v7.ptl
chenlai@devvm5615:~/fbsource/fbcode(b82243650)$
```

second time run:
```
chenlai@devvm5615:~/fbsource/fbcode(b82243650)$ rm caffe2/test/jit/fixtures/test_versioned_div_tensor_example_v4.ptl
chenlai@devvm5615:~/fbsource/fbcode(b82243650)$ buck run mode/opt //caffe2/torch/fb/mobile/upgrader_codegen:upgrader_test_models_gen
Action graph will be rebuilt because files have been added or removed.
Parsing buck files: finished in 2.0 sec
Building... 17.4 sec (99%) 9289/9290 jobs, 0/9290 updated
TestVersionedDivTensorExampleV7() aten::div.Tensor
INFO:test.jit.fixtures_srcs.generate_models:Processing TestVersionedDivTensorExampleV7
INFO:test.jit.fixtures_srcs.generate_models:Model test_versioned_div_tensor_example_v7 already exists, skipping
chenlai@devvm5615:~/fbsource/fbcode(b82243650)$ jf s
```

Reviewed By: tugsbayasgalan

Differential Revision: D33804737

fbshipit-source-id: 7424b81a700703bdf896ec606c2dac8df6dbf8a6
(cherry picked from commit 44b4e37d30077a3160b8a92209af339a6f2fc885)
2022-01-27 21:15:32 +00:00
c9bd1c60ed Move upgraders from python to cpp (#70593)
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/70593

Test Plan: Imported from OSS

Reviewed By: gmagogsfm

Differential Revision: D33402543

Pulled By: tugsbayasgalan

fbshipit-source-id: 713c54fbbb2bc4c96d5e3b6084f3090a8923a12d
(cherry picked from commit e72b375264395ac1264c07e9c69dd0dd7adfebb8)
2022-01-22 00:24:24 +00:00
e926360cb8 [Pytorch Edge] Refactor Compatibility Stuff into own directory (#71432)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/71432

Organizing jit/mobile a little more

ghstack-source-id: 147184536

Test Plan: ci.

Reviewed By: iseeyuan

Differential Revision: D33640527

fbshipit-source-id: f3a7884fe0d06d80bb8d9cf141ecaee34b6f88ff
(cherry picked from commit 4c3d1e5435db04a4ca2898ddf0811490f5959555)
2022-01-20 19:38:41 +00:00
b0fdca8855 Bump version number to 7 and compile old operators with old schema (#68358)
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/68358

Test Plan: Imported from OSS

Reviewed By: albanD

Differential Revision: D33433730

Pulled By: tugsbayasgalan

fbshipit-source-id: 202c58365bae13195d3545cefcb0da9162b02151
2022-01-05 23:57:22 -08:00
0ece9a49d7 Revert D33198155: Bump version number to 7 and compile old operators with old schema
Test Plan: revert-hammer

Differential Revision:
D33198155 (d35fc409ad)

Original commit changeset: 38a1185f9ecb

Original Phabricator Diff: D33198155 (d35fc409ad)

fbshipit-source-id: 411aaeb4e047aad9202db50d4d0f2ff35bc51f9d
2022-01-04 13:44:59 -08:00
d35fc409ad Bump version number to 7 and compile old operators with old schema (#68358)
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/68358

Test Plan: Imported from OSS

Reviewed By: samdow

Differential Revision: D33198155

Pulled By: tugsbayasgalan

fbshipit-source-id: 38a1185f9ecb34a33f737ad0b060b3490956300c
2022-01-04 01:31:25 -08:00
fa09099ba3 Codegen: TraceType only includes operators being registered (#68691)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/68691

TraceType is a sharded file, so by only including specific operator
headers, we ensure that changing one (non-method) operator only needs
one shard to be re-compiled.

This also changes all the included autograd and jit headers from
including `ATen/ATen.h` to just including `ATen/core/Tensor.h`.

Test Plan: Imported from OSS

Reviewed By: gchanan

Differential Revision: D33336948

Pulled By: albanD

fbshipit-source-id: 4e40371592b9a5a7e7fcd1d8cecae11ffb873113
2022-01-02 13:09:19 -08:00
5c7817fd43 Add test operator in upgrader entry (#69427)
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/69427

Test Plan: Imported from OSS

Reviewed By: gmagogsfm

Differential Revision: D32867984

Pulled By: tugsbayasgalan

fbshipit-source-id: 25810fc2fd4b943911f950618968af067c04da5c
2021-12-15 00:40:05 -08:00
20f7c893c1 Populate runtime with upgrader graph (#68773)
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/68773

Test Plan: Imported from OSS

Reviewed By: qihqi, gmagogsfm

Differential Revision: D32603258

Pulled By: tugsbayasgalan

fbshipit-source-id: 6fa0b7ee4ebe46c9aa148923c6ef3e1de106ad13
2021-12-11 13:44:24 -08:00
17f3179d60 Back out "[pytorch][PR] Add ability for a mobile::Module to save as flatbuffer" (#69796)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/69796

(Note: this ignores all push blocking failures!)

Test Plan: External CI + Sandcastle

Reviewed By: zhxchen17

Differential Revision: D33032671

fbshipit-source-id: dbf6690e960e25d6a5f19043cbe792add2acd7ef
2021-12-10 21:29:53 -08:00
d3649309e6 [pytorch][PR] Add ability for a mobile::Module to save as flatbuffer (#69306)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/69306

Included functions:

save_mobile_module -> saves a mobile::Module to flatbuffer
load_mobile_module_from_file -> loads a flatbuffer into mobile::Module
parse_mobile_module -> parses from bytes or deserialized flatbuffer
Module object

Test Plan: unittests

Reviewed By: gmagogsfm

Differential Revision: D32806835

fbshipit-source-id: 71913c6650e225634f878946bd16960d377a7f57
2021-12-09 14:53:31 -08:00
945d2e380c [AutoAccept][Codemod][FBSourceClangFormatLinter] Daily arc lint --take CLANGFORMAT
Reviewed By: zertosh

Differential Revision: D32910817

fbshipit-source-id: 60d0cb10412e1a37a0249bb223b75855c5596dbd
2021-12-07 08:11:09 -08:00
bc89528931 Initialize upgrader and operator version files (#68772)
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/68772

Test Plan: Imported from OSS

Reviewed By: gmagogsfm

Differential Revision: D32603257

Pulled By: tugsbayasgalan

fbshipit-source-id: 5a3d9ba4d0a01ddff4ff6ebdf7bb88ec125765b0
2021-12-06 16:27:52 -08:00
dde801686b Expose MobileCode to python (#66592)
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/66592

Test Plan: Imported from OSS

Reviewed By: samdow

Differential Revision: D31632600

Pulled By: tugsbayasgalan

fbshipit-source-id: 46a7ac20ddb6b433bd037280ed020481901a15c9
2021-12-02 13:18:46 -08:00
00ebbd5ef6 Revert D32010095: [pytorch][PR] Add ability for a mobile::Module to save as flatbuffer
Test Plan: revert-hammer

Differential Revision:
D32010095 (41d35dc201)

Original commit changeset: d763b0557780

fbshipit-source-id: bf746a0389135c9f5f67f00f449435ce08fb5f6d
2021-12-02 06:41:40 -08:00
41d35dc201 Add ability for a mobile::Module to save as flatbuffer (#67351)
Summary:
Included functions:

* save_mobile_module -> saves a mobile::Module to flatbuffer
* load_mobile_module_from_file -> loads a flatbuffer into mobile::Module
* parse_mobile_module -> parses from bytes or deserialized flatbuffer
      Module object

Fixes #{issue number}

Pull Request resolved: https://github.com/pytorch/pytorch/pull/67351

Reviewed By: iseeyuan

Differential Revision: D32010095

Pulled By: qihqi

fbshipit-source-id: d763b0557780f7c2661b6485105b045e41a5e8f1
2021-12-01 23:58:15 -08:00
5ef62c88a9 [jit] Replace get_executor() with call() in abstract Function interface. (#65969)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/65969

ghstack-source-id: 141759210

Test Plan: no behavior change.

Reviewed By: anjali411

Differential Revision: D31326151

fbshipit-source-id: 201f6dc4c23fdb2531f6b8c73d26127f9e212de4
2021-10-28 13:11:29 -07:00
b55a2500d2 [jit] Remove graph() call from abstract Function interface. (#65967)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/65967

Graph is an implementation detail. If user wants to get access to the
underlying graph, they should be able to explicitly dynamic cast instead.
ghstack-source-id: 141659819

Test Plan: no behavior change.

Reviewed By: gmagogsfm

Differential Revision: D31326153

fbshipit-source-id: a0e984f57c6013494b92a7095bf5bb660035eb84
2021-10-27 11:54:26 -07:00
f510193e22 [jit][edge] Export maybe-used interface methods from modules. (#65966)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/65966

ghstack-source-id: 141594521

Support exportation of "interface methods" from submodule to a mobile module. "Interface methods" are defined as methods which might be dynamically called in a module therefore need to be exported anyway, like virtual functions in C++.

Before this change the algorithm of exportation is a simple iteration through all toplevel methods. Now since we have indirect calls, we need to recursively walkthrough the call graph to find all potentially used methods, which means the order we export methods might break in old runtimes, to guarantee forward compatibility we need to export toplevel methods first, then extra methods, in this order toplevel methods will always be found first.

NOTE that interface methods exportations are disabled by default in this diff. We need to call torch._C._enable_mobile_interface_call_export to actaully enable it.

Test Plan: buck test mode/dev //caffe2/test:jit -- --exact 'caffe2/test:jit - test_export_opnames_interface (jit.test_misc.TestMisc)'

Reviewed By: qihqi, iseeyuan

Differential Revision: D31326155

fbshipit-source-id: 5be7234cca07691f62648a85133b6db65e427b53
2021-10-26 16:35:15 -07:00
a5895f85be [PyTorch Edge][type] Add type check in compatibility api (#63129)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/63129

1. Add an api to get `supported_types` from runtime, expose in c++ only.
2. Add an api to get `contained_types` from model, expose in both c++ and PyThon.
3. Add a field `contained_types_` in `type_parser.cpp` to track the contained types when parsing python string.
4. Expand `is_compatible` api to check type. When checking type, it will check the contained type list from the model with the support type list from runtime.
5. Expand the unittest for compatibility to cover type
6. Add unit test in python to check type list
ghstack-source-id: 139826944

Test Plan:
```
buck test mode/dev //caffe2/test/cpp/jit:jit -- --exact 'caffe2/test/cpp/jit:jit - LiteInterpreterTest.GetContainTypes'

buck test mode/dev //caffe2/test/cpp/jit:jit -- --exact 'caffe2/test/cpp/jit:jit - LiteInterpreterTest.isCompatibleSuccess'
buck test mode/dev //caffe2/test/cpp/jit:jit -- --exact 'caffe2/test/cpp/jit:jit - LiteInterpreterTest.isCompatibleFail'

buck test //caffe2/test:mobile
```

Reviewed By: iseeyuan

Differential Revision: D30231419

fbshipit-source-id: 8427f423ec28cc5de56411f15fd960d8595d6947
2021-10-06 02:23:44 -07:00
9e77113e85 irange-ify 11 (#62121)
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/62121

Test Plan: Sandcastle

Reviewed By: ngimel

Differential Revision: D29879701

fbshipit-source-id: 5c51879c88fa6a5790db241c8b33ec0dc4b177ca
2021-07-28 13:32:09 -07:00
04043d681e [package] fix storage serialization collision (#61806)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/61806

Currently, if you do `save_pickle` on a ScriptModule, then `save_pickle`
on a tensor, this would result in a `0.storage` tensor being written
*twice* to the zip archive. This would cause weird bugs on the
serializing side (this presented as a ASAN-detected heap buffer overflow
because we tried to read more memory from a tensor than we actually
had).

Turns out this was because when we did:
```
self.storage_context = self.script_module_serializer.storage_context()
```
it returned a new copy of the storage context, so we weren't actually
assigning unique names to tensors!!

This PR fixes the issue by making `(De)SerializationStorageContext`
non-copyable and fixing up the parts of the bindings that returned by
copy.

Differential Revision:
D29748969
D29748969

Test Plan: Imported from OSS

Reviewed By: Lilyjjo

Pulled By: suo

fbshipit-source-id: c2f89ab270e07e7a111fb35c545b5e07b804dc3c
2021-07-19 18:22:36 -07:00
4a2e8b53bb [JIT] Add torch._C.ScriptList` (#52832)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/52832

**Summary**
This commit adds `torch._C.ScriptList`, a list type that has reference
semantics across the Python/TorchScript boundary. That is, modifications
made in TorchScript to instances of `torch._C.ScriptList`
are visible in Python even when it is not returned from the function.

`torch._C.ScriptList` is implemented using a modified version of pybind's
`stl_bind.h`-style bindings attached to `ScriptList` and `ScriptListIterator`,
wrapper classes around `c10::impl::GenericList` and
`c10::impl::GenericList::iterator`. These bindings allow instances of
`torch._C.ScriptList` to be used as if it were a
regular `list` in Python. Reference semantics are achieved by simply
retrieving the `IValue` contained in `ScriptList` in `toIValue` (invoked
when converting Python arguments to `IValues` before calling TorchScript
code).

**Test Plan**
This commit adds `TestScriptList` to `test_list_dict.py`, a set of tests
that check that all of the common list operations are supported
and that instances have reference semantics across the
Python/TorchScript boundary.

Test Plan: Imported from OSS

Reviewed By: gmagogsfm

Differential Revision: D29478121

Pulled By: SplitInfinity

fbshipit-source-id: 652cc25cfa37debe28db9527504846f22abd8b54
2021-07-01 20:28:13 -07:00
6c1c1111de [JIT] Add reference semantics to TorchScript classes (#44324)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/44324

**Summary**
This commit adds reference semantics to TorchScript class types;
modifications made to them within TorchScript will be visible in Python.

**Test Plan**
This commit adds a unit test to `TestClassType` that checks that
modifications made to a class type instance passed into TorchScript are
visible in Python after executing the scripted function or module.

**Fixes**
This commit closes #41421.

Test Plan: Imported from OSS

Reviewed By: gmagogsfm

Differential Revision: D24912807

Pulled By: SplitInfinity

fbshipit-source-id: d64ac6211012425b040b987e3358253016e84ca0
2021-06-30 14:27:17 -07:00
0dd90cceaf [package] track storages across lifetime of PackageExporter (#59735)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/59735

1. Fixes ABA storage identity problem during serialization for `torch.package` by keeping reference of serialized storages through lifetime of `PackageExporter` to prevent reuse of memory address. Achieved by extending logic used in solution to mobile's same issue.
2. Adds determinism to naming scheme of serialized storages in export code paths which utilize `tensor_cdata_naming_scheme`(introduced 2nd mapping in `StorageContext`, now maps `storage cdata ptr` -> `unique id`, `unique id` -> `c10::Storage`)
3. Additionally uses presence of a storage in the `StorageContext` instance as marker for if a storage has been serialized or not, removing the need to scan the `PythonStreamWriter` for presence of the storage's serialization file

Test Plan: Imported from OSS

Reviewed By: suo

Differential Revision: D29075276

Pulled By: Lilyjjo

fbshipit-source-id: 15a5c30b1de99c5bd7079388f2db9b6ece2eca12
2021-06-29 14:16:54 -07:00
b14c3205fd [JIT] Add torch._C.ScriptDict (#52659)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/52659

**Summary**
This commit adds `torch._C.ScriptDict`, a dictionary type that has reference
semantics across the Python/TorchScript boundary. That is, modifications
made to instances of `torch._C.ScriptDict` in TorchScript are visible in
Python even when it is not returned from the function. Instances can be
constructed by passing an instance of a Python dictionary to
`torch.jit.script`. In the case of an empty dictionary, its type is
assumed to be `Dict[str, Tensor]` to be consistent with the handling of
empty dictionaries in TorchScript source code.

`torch._C.ScriptDict` is implemented using a modified version of pybind's `stl_bind.h`-style bindings attached to `ScriptDict`, `ScriptDictIterator` and `ScriptDictKeyIterator`, wrapper classes around `c10::impl::GenericDict` and `c10::impl::GenericDict::iterator`. These bindings allow instances of `torch._C.ScriptDict` to be used as if it were a regular `dict` Python. Reference semantics are achieved by simply retrieving the `IValue` contained in `ScriptDict` in `toIValue` (invoked when converting Python arguments to `IValues` before calling TorchScript code).

**Test Plan**
This commit adds `TestScriptDict` to `test_list_dict.py`, a set of tests
that check that all of the common dictionary operations are supported
and that instances have reference semantics across the
Python/TorchScript boundary.

Differential Revision:
D27211605
D27211605

Test Plan: Imported from OSS

Reviewed By: gmagogsfm

Pulled By: SplitInfinity

fbshipit-source-id: 446d4e5328375791aa73eb9e8b04dfe3465af960
2021-05-27 10:25:30 -07:00
5268b5a29a Add parsing logic for Tuple[()] annotation (#58340)
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/58340

Test Plan: Imported from OSS

Reviewed By: jamesr66a

Differential Revision: D28459502

Pulled By: ansley

fbshipit-source-id: 4bb188448d66269b42b068858b895debac86e9ee
2021-05-25 12:12:43 -07:00
2b0ec9c3cf Reapply "[jit] Implement ScriptProfile to collect instruction profiles." (#58783)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/58783

This reverts commit fc804b5def5e7d7ecad24c4d1ca4ac575e588ae8.

Test Plan: Imported from OSS

Reviewed By: gmagogsfm

Differential Revision: D28617037

Pulled By: zhxchen17

fbshipit-source-id: 645de2ede20500a5c218d6ec3c7faae94de37a14
2021-05-24 18:23:21 -07:00
1c5f63d86d [Pytorch Edge] Model Ops compatibility api (#57501)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/57501

Add an api _get_model_ops_and_info to get root operators and versioning info of a model in both cxx and python, and the input can be from a file path or buffer.
ghstack-source-id: 129620112

Test Plan: unit test.

Reviewed By: xcheng16, raziel

Differential Revision: D28162765

fbshipit-source-id: 4413c1e906b8a872e4a717d849da37347adbbea4
2021-05-24 12:00:06 -07:00
fc804b5def Revert D28133579: [jit] Implement ScriptProfile to collect instruction profiles.
Test Plan: revert-hammer

Differential Revision:
D28133579 (034a238bab)

Original commit changeset: e7e30e961513

fbshipit-source-id: 5a7756468b4f2eeed24d2abb7b52ab46d081a95e
2021-05-21 08:18:40 -07:00
034a238bab [jit] Implement ScriptProfile to collect instruction profiles. (#57397)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/57397

Introduces two main classes in C++ runtime:

ScriptProfile is the implementation for enalbing and disabling interpreter
profiling in C++. This should be only used from Python, and we will add
corresponding Python API in the next diff.

InstructionSpan is a utility class to instrument execution of each single
instruction. A start timestamp is recorded in the consturctor, and an end
timestamp is recorded in the destructor. During destruction, this will send
runtime data to all enabled ScriptProfile instances.

Test Plan:
build/bin/test_jit --gtest_filter='ScriptProfileTest.Basic'

Imported from OSS

Reviewed By: gmagogsfm

Differential Revision: D28133579

fbshipit-source-id: e7e30e96151367022793ab3ad323f01c51ad4a3b
2021-05-20 14:11:03 -07:00
9403fe17ce [torch.package/TorchScript] logic to enable sharing of tensors on load (#57573)
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/57573

Test Plan: Imported from OSS

Reviewed By: suo

Differential Revision: D28226975

Pulled By: Lilyjjo

fbshipit-source-id: bc8cb3e8052fa18336c437e0601d8b0028fd1895
2021-05-14 08:21:43 -07:00
3ad11803f7 [torch.Package/TorchScript] ScriptModuleSerializer add unified format (#56299)
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/56299

Test Plan: Imported from OSS

Reviewed By: suo

Differential Revision: D27832545

Pulled By: Lilyjjo

fbshipit-source-id: 1b2880a8458f99bd66a8c9656c5ca700f43cffe8
2021-05-14 08:21:40 -07:00
07de11c26d [torch.Package/TorchScript] TS serialization importer to handle unified format (#54891)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/54891

Changed TorchScript's jit/serialization importer logic to handle both original TS serialization format and new unified TS format

Original TS file format:
```
resnet.pt
├── data  # tensor data
│   ├── 94286146172688
│   ├── 94286146172784
│   └── ...
├── code/  # TorchScript code
│   ├── __torch__
│   │   ├── torch
│   │   │   └── nn ...
│   │   └── torchvision ...
│   ├── __torch__.py
│   └── __torch__.py.debug_pkl
├── data.pkl  # the ScriptModule object, pickled by the TS pickler
├── version  # version metadata
├── constants.pkl  # any tensor constants present in the TS code
└── extra
     ├── name_of_file
     └── foo
```

Unified file format:
```
─── package_name.pt
    ├── .data
    │   ├── ts_code # code shared between models
    │   │   ├── 0
    │   │   │   ├── constants.pkl
    │   │   │   └── data.pkl
    │   │   ├── 1
    │   │   │   ├── constants.pkl
    │   │   │   └── data.pkl
    │   │   └── code
    │   │       ├── __torch__
    │   │       │   ├── torch
    │   │       │   │   └── nn ...
    │   │       │   └── torchvision ...
    │   │       ├── __torch__.py
    │   │       └── __torch__.py.debug_pkl
    │   ├── 0.storage
    │   ├── 1.storage
    │   ├── <many more storages>
    │   ├── 201.storage
    │   ├── extern_modules
    │   └── version
    └── res
        ├── mod.pkl  # maps to ts_id 0 and .data/ts_code/0
        └── mod2.pkl # maps to ts_id 1 and .data/ts_code/1
```

Test Plan: Imported from OSS

Reviewed By: suo

Differential Revision: D27832548

Pulled By: Lilyjjo

fbshipit-source-id: 4a6e84c3a9bac8eed6a4e4afc2ac76dd691858b0
2021-05-14 08:20:34 -07:00
1de3525ca8 [ONNX] Handle PackedParams inputs for _propagate_and_assign_input_shapes (#56449) (#57079)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/57079

Testing onnx 1.9 release, we see that the old bug is triggered for the caffe2 test:
`pytest test/onnx/test_pytorch_onnx_caffe2_quantized.py::TestQuantizedOps::test_small_model`
This is because the graph inputs
```python
graph(%x.1 : Tensor,
      %conv1._packed_params : __torch__.torch.classes.quantized.Conv2dPackedParamsBase,
      %conv2._packed_params : __torch__.torch.classes.quantized.Conv2dPackedParamsBase,
      %fc.bias : Float(10, strides=[1], requires_grad=0, device=cpu),
      %fc.weight : Float(10, 72, strides=[72, 1], requires_grad=0, device=cpu)):
```
contains `Conv2dPackedParamsBase` which is a PackedParams.
When we do flatten, we will flatten to several tensors, then the shape inference for input misaligned.
This PR record how may tensors got flattened in PackeParams, and skip by these number rather than 1, then the UT passed.
Note that tuple case should still follow the original logic.

Test Plan: Imported from OSS

Reviewed By: SplitInfinity

Differential Revision: D28393949

Pulled By: malfet

fbshipit-source-id: 98d48aad27e5ca03fb10d260f8e625478d996ee2

Co-authored-by: David <jiafa@microsoft.com>
2021-05-12 15:20:26 -07:00
8c04593c0a [PyTorch Edge] Add backport to export old bytecode models (#56802)
Summary:
Add an api to backport a model vn to model vi. It accept an input model (file or buffer) and output a model (file or buffer) with an expected bytecode version.

In this change, the input is a model and it can come from a file or buffer. The output is a model and can be either file path or buffer.

When backport fails, function return false with a warning message :
```
/Users/chenlai/pytorch/cmake-build-debug/bin/test_jit --gtest_filter=LiteInterpreterTest.BackPortByteCodeModelV4:LiteInterpreterTest/*.BackPortByteCodeModelV4:*/LiteInterpreterTest.BackPortByteCodeModelV4/*:*/LiteInterpreterTest/*.BackPortByteCodeModelV4 --gtest_color=no
Testing started at 2:32 PM ...
CUDA not available. Disabling CUDA and MultiCUDA tests

[W backport.cpp:419] Warning: Backport doesn't support backport to version3 (function _backport_for_mobile_impl)
Process finished with exit code 0
```

## Test
1. Run both `caffe2/test/cpp/jit/test_lite_interpreter.cpp` and `caffe2/test/mobile/test_bytecode.py`.
2. Run all prod models with backport api.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/56802

ghstack-source-id: 128425510

Test Plan: CI

Reviewed By: raziel, iseeyuan

Differential Revision: D27844651

fbshipit-source-id: 8a803cf6c76433ee0a3049b1a5570585d569f8d6
2021-05-07 18:14:33 -07:00
fb9a32b7b4 [PyTorch][Edge] Add api to get bytecode model version (#56801)
Summary:
Add an api `_get_bytecode_version` to get version number given a bytecode model in both cxx and python, and the input can be both from file path and buffer.
## Test
CI (new added unit test will run as part of `pytorch_core-buck`)

1. run test_lite_interpreter.cpp
2. `python test/mobile/test_bytecode.py`

Pull Request resolved: https://github.com/pytorch/pytorch/pull/56801

ghstack-source-id: 128169647

Test Plan:
CI (new added unit test will run as part of `pytorch_core-buck`)

1. run test_lite_interpreter.cpp
2. `python test/mobile/test_bytecode.py`

Reviewed By: iseeyuan

Differential Revision: D27961417

fbshipit-source-id: f786cc9573d855feecff0b4fe8e5363e25f5728c
2021-05-05 09:17:26 -07:00
4cb534f92e Make PyTorch code-base clang-tidy compliant (#56892)
Summary:
This is an automatic change generated by the following script:
```
#!/usr/bin/env python3
from subprocess import check_output, check_call
import os

def get_compiled_files_list():
    import json
    with open("build/compile_commands.json") as f:
        data = json.load(f)
    files = [os.path.relpath(node['file']) for node in data]
    for idx, fname in enumerate(files):
        if fname.startswith('build/') and fname.endswith('.DEFAULT.cpp'):
            files[idx] = fname[len('build/'):-len('.DEFAULT.cpp')]
    return files

def run_clang_tidy(fname):
    check_call(["python3", "tools/clang_tidy.py", "-c", "build", "-x", fname,"-s"])
    changes = check_output(["git", "ls-files", "-m"])
    if len(changes) == 0:
        return
    check_call(["git", "commit","--all", "-m", f"NOLINT stubs for {fname}"])

def main():
    git_files = check_output(["git", "ls-files"]).decode("ascii").split("\n")
    compiled_files = get_compiled_files_list()
    for idx, fname in enumerate(git_files):
        if fname not in compiled_files:
            continue
        if fname.startswith("caffe2/contrib/aten/"):
            continue
        print(f"[{idx}/{len(git_files)}] Processing {fname}")
        run_clang_tidy(fname)

if __name__ == "__main__":
    main()
```

Pull Request resolved: https://github.com/pytorch/pytorch/pull/56892

Reviewed By: H-Huang

Differential Revision: D27991944

Pulled By: malfet

fbshipit-source-id: 5415e1eb2c1b34319a4f03024bfaa087007d7179
2021-04-28 14:10:25 -07:00
9986b109d2 [ONNX] Fix assign input shape for tuple inputs & primitive type inputs (#54112) (#56164)
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/56164

Test Plan: Imported from OSS

Reviewed By: pbelevich

Differential Revision: D27866139

Pulled By: SplitInfinity

fbshipit-source-id: c59f5a07df685e1ccdc4860d603ec422ec80d188
2021-04-20 23:00:37 -07:00