Nikita Shulga [Fri, 20 Aug 2021 06:42:24 +0000 (23:42 -0700)]
Update protobuf to 3.13.1 (#62571)
Summary:
Update bazel to 4.10.0
Update ASAN_SYMBOLIZER_PATH to llvm-7
Suppress `vptr` ubsan violations in `test_jit`
Fix ProtoBuf patching for ONNX which caused Windows builds to crash while attempting to free `std::string` allocated on stack
Fixes https://github.com/pytorch/pytorch/issues/62569
Pull Request resolved: https://github.com/pytorch/pytorch/pull/62571
Reviewed By: walterddr
Differential Revision:
D30048685
Pulled By: malfet
fbshipit-source-id:
6462c1bef9c42318551d2cf906bbab41e1d4e1cd
Raghavan Raman [Fri, 20 Aug 2021 05:50:32 +0000 (22:50 -0700)]
[nnc] Updated sliceTail to do inplace mutation (#63532)
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/63532
Test Plan: Imported from OSS
Reviewed By: ZolotukhinM
Differential Revision:
D30412184
Pulled By: navahgar
fbshipit-source-id:
e7669d3b9d24e14501f3feb6505c88d1d42030c6
Raghavan Raman [Fri, 20 Aug 2021 05:50:32 +0000 (22:50 -0700)]
[nnc] Updated sliceHead to do inplace mutation (#63531)
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/63531
Test Plan: Imported from OSS
Reviewed By: ZolotukhinM
Differential Revision:
D30412183
Pulled By: navahgar
fbshipit-source-id:
47ee9482a36e606788d28d22eee4edaca45ffa50
Scott Wolchok [Fri, 20 Aug 2021 01:52:33 +0000 (18:52 -0700)]
[PyTorch] Remove unnecessary iostream includes in headers (#61500)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/61500
libstdc++ defines a static variable called `std::__ioinit` in iostream that adds global constructor size overhead to each translation that includes iostream. To reduce the size overhead from that, we can often include ostream instead.
ghstack-source-id:
136163529
Test Plan: buildsizebot some mobile apps
Reviewed By: dhruvbird
Differential Revision:
D29648016
fbshipit-source-id:
9c3139712c71248513cc5032d21e77f3ecbae8fe
Scott Wolchok [Fri, 20 Aug 2021 01:52:33 +0000 (18:52 -0700)]
[PyTorch] Remove unused dump() methods in vec headers (#63533)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/63533
These methods don't seem to be used, and they use std::cout, which incurs a small code size overhead on platforms using libstdc++ due to std::__ioinit (see #61500). Seems like we can just delete them?
ghstack-source-id:
136163409
Test Plan:
CI
Reviwers: #sentinel, dhruvbird
Reviewed By: dskhudia
Differential Revision:
D30412269
fbshipit-source-id:
380b9aa2f9aabc4107188b6b209d2afc1769c0ee
Pavithran Ramachandran [Fri, 20 Aug 2021 01:39:50 +0000 (18:39 -0700)]
[PyTorch][Edge] Support backtrace symbolication for Android builds (#63339)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/63339
# Context
https://fb.workplace.com/groups/pytorch.dev/permalink/
900474523864362/?comment_id=
901125403799274&reply_comment_id=
905023386742809
##### WHAT IS A STACK TRACE?
A stack trace (also called stack backtrace or stack traceback) is a report of the active stack frames at a certain point in time during the execution of a program.
Typically when an exception is thrown, one would expect to see the code (file:line) that threw the exception, and every intermediate frame up to and including the main function.
We are enabling android stack trace to help debugging on android devices.
Test Plan:
## Steps to test
```
buck build fbsource//xplat/caffe2/mode/aibench_pytorch_android -c pt.enable_qpl=0 -c pt.has_backtraces=1 fbsource//xplat/caffe2/fb/lite_predictor:lite_predictorAndroid#android-x86_64
one_world android emulator android-28
adb push ~/fbsource/buck-out/gen/xplat/caffe2/fb/lite_predictor/lite_predictorAndroid#android-x86_64 /data/local/tmp
cd /data/local/tmp
./lite_predictorAndroid#android-x86_64
./lite_predictorAndroid#android-x86_64 --model ./detect.bc --input_dims "1,3,192,192" --input_type float --warmup 20 --iter 5 --report_pep true
```
## See how model file is not found stack traces is:
### before
```
./lite_predictorAndroid#android-x86_64 --model ./detect.bc --input_dims "1,3,192,192" --input_type float --warmup 20 --iter 5 --report_pep true
Run with 2 threads
Run with 2 threads
Loading model...
terminating with uncaught exception of type c10::Error: open file failed, file path: ./detect.bc
Exception raised from RAIIFile at xplat/caffe2/caffe2/serialize/file_adapter.cc:13 (most recent call first):
(no backtrace available)
Aborted
```
### after
```
134|generic_x86_64:/data/local/tmp $ ./lite_predictorAndroid#android-x86_64 --model ./detect.bc --input_dims "1,3,192,192" --input_type float --warmup 20 --iter 5 --report_pep true
Run with 2 threads
Run with 2 threads
Loading model...
terminating with uncaught exception of type c10::Error: open file failed, file path: ./detect.bc
Exception raised from RAIIFile at xplat/caffe2/caffe2/serialize/file_adapter.cc:13 (most recent call first):
frame #0 c10::get_backtrace(unsigned long, unsigned long, bool)[0x59494274f10e]
frame #1 [0x5949427b1eee]
frame #2 [0x5949427b1eb2]
frame #3 [0x5949427b1cdc]
frame #4 std::__ndk1::function<std::__ndk1::basic_string<char, std::__ndk1::char_traits<char>, std::__ndk1::allocator<char> > ()>::operator()() const[0x5949427afc34]
frame #5 c10::Error::Error(c10::SourceLocation, std::__ndk1::basic_string<char, std::__ndk1::char_traits<char>, std::__ndk1::allocator<char> >)[0x5949427b05b1]
frame #6 c10::detail::torchCheckFail(char const*, char const*, unsigned int, std::__ndk1::basic_string<char, std::__ndk1::char_traits<char>, std::__ndk1::allocator<char> > const&)[0x5949427aca5f]
frame #7 caffe2::serialize::FileAdapter::RAIIFile::RAIIFile(std::__ndk1::basic_string<char, std::__ndk1::char_traits<char>, std::__ndk1::allocator<char> > const&)[0x5949426b37b2]
frame #8 caffe2::serialize::FileAdapter::FileAdapter(std::__ndk1::basic_string<char, std::__ndk1::char_traits<char>, std::__ndk1::allocator<char> > const&)[0x5949426b3903]
frame #9 torch::jit::_load_for_mobile(std::__ndk1::basic_string<char, std::__ndk1::char_traits<char>, std::__ndk1::allocator<char> > const&, c10::optional<c10::Device>, std::__ndk1::unordered_map<std::__ndk1::basic_string<char, std::__ndk1::char_traits<char>, std::__ndk1::allocator<char> >, std::__ndk1::basic_string<char, std::__ndk1::char_traits<char>, std::__ndk1::allocator<char> >, std::__ndk1::hash<std::__ndk1::basic_string<char, std::__ndk1::char_traits<char>, std::__ndk1::allocator<char> > >, std::__ndk1::equal_to<std::__ndk1::basic_string<char, std::__ndk1::char_traits<char>, std::__ndk1::allocator<char> > >, std::__ndk1::allocator<std::__ndk1::pair<std::__ndk1::basic_string<char, std::__ndk1::char_traits<char>, std::__ndk1::allocator<char> > const, std::__ndk1::basic_string<char, std::__ndk1::char_traits<char>, std::__ndk1::allocator<char> > > > >&)[0x5949422737bd]
frame #10 torch::jit::_load_for_mobile(std::__ndk1::basic_string<char, std::__ndk1::char_traits<char>, std::__ndk1::allocator<char> > const&, c10::optional<c10::Device>)[0x594942273769]
frame #11 benchmark(std::__ndk1::basic_string<char, std::__ndk1::char_traits<char>, std::__ndk1::allocator<char> > const&, int, std::__ndk1::basic_string<char, std::__ndk1::char_traits<char>, std::__ndk1::allocator<char> > const&, std::__ndk1::basic_string<char, std::__ndk1::char_traits<char>, std::__ndk1::allocator<char> > const&, std::__ndk1::basic_string<char, std::__ndk1::char_traits<char>, std::__ndk1::allocator<char> > const&, bool, int, int, int, bool, int, bool, int, double, bool, bool, bool, std::__ndk1::basic_string<char, std::__ndk1::char_traits<char>, std::__ndk1::allocator<char> > const&)[0x59494189b21d]
frame #12 main[0x594941882aff]
frame #13 __libc_init[0x7b699d08578d]
```
### what we get for os:linux
```
(base) [pavithran@devvm1803.vll0 /data/users/pavithran/fbsource] ./buck-out/gen/xplat/caffe2/fb/lite_predictor/lite_predictor --model ./detect.bc --input_dims "1,3,192,192" --input_type float --warmup 20 --iter 5 --report_pep true
Run with 24 threads
Run with 24 threads
Loading model...
terminate called after throwing an instance of 'c10::Error'
what(): open file failed, file path: ./detect.bc
Exception raised from RAIIFile at xplat/caffe2/caffe2/serialize/file_adapter.cc:13 (most recent call first):
frame #0: ./buck-out/gen/xplat/caffe2/fb/lite_predictor/lite_predictor() [0x20cb7fe]
frame #1: ./buck-out/gen/xplat/caffe2/fb/lite_predictor/lite_predictor() [0x20cb6c6]
frame #2: std::function<std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > ()>::operator()() const + 0x54 (0x20ca4e4 in ./buck-out/gen/xplat/caffe2/fb/lite_predictor/lite_predictor)
frame #3: c10::Error::Error(c10::SourceLocation, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >) + 0x57 (0x20ca9a7 in ./buck-out/gen/xplat/caffe2/fb/lite_predictor/lite_predictor)
frame #4: c10::detail::torchCheckFail(char const*, char const*, unsigned int, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&) + 0x7a (0x20c823a in ./buck-out/gen/xplat/caffe2/fb/lite_predictor/lite_predictor)
frame #5: caffe2::serialize::FileAdapter::RAIIFile::RAIIFile(std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&) + 0x96 (0x206f3d6 in ./buck-out/gen/xplat/caffe2/fb/lite_predictor/lite_predictor)
frame #6: caffe2::serialize::FileAdapter::FileAdapter(std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&) + 0x42 (0x206f502 in ./buck-out/gen/xplat/caffe2/fb/lite_predictor/lite_predictor)
frame #7: torch::jit::_load_for_mobile(std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, c10::optional<c10::Device>, std::unordered_map<std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >, std::hash<std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > >, std::equal_to<std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > >, std::allocator<std::pair<std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > > > >&) + 0x30 (0x1be826c in ./buck-out/gen/xplat/caffe2/fb/lite_predictor/lite_predictor)
frame #8: torch::jit::_load_for_mobile(std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, c10::optional<c10::Device>) + 0x35 (0x1be8214 in ./buck-out/gen/xplat/caffe2/fb/lite_predictor/lite_predictor)
frame #9: benchmark(std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, int, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, bool, int, int, int, bool, int, bool, int, double, bool, bool, bool, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&) + 0x16d (0x12093ad in ./buck-out/gen/xplat/caffe2/fb/lite_predictor/lite_predictor)
frame #10: main + 0x25c (0x11f933c in ./buck-out/gen/xplat/caffe2/fb/lite_predictor/lite_predictor)
frame #11: __libc_start_main + 0x105 (0x7fc7b9f2ed95 in /usr/local/fbcode/platform009/lib/libc.so.6)
frame #12: _start + 0x2a (0x11f902a in ./buck-out/gen/xplat/caffe2/fb/lite_predictor/lite_predictor)
Aborted (core dumped)
````
Reviewed By: dhruvbird
Differential Revision:
D30135947
fbshipit-source-id:
f50c634ef4545843305cad4b4a14a8776b1aec76
Nikita Shulga [Thu, 19 Aug 2021 23:46:31 +0000 (16:46 -0700)]
Revert
D30359218: [pytorch][PR] [doc] pre-commit fix instructions
Test Plan: revert-hammer
Differential Revision:
D30359218 (https://github.com/pytorch/pytorch/commit/
4e1d84ae8fae49995c8966ccbe0f34360978492f)
Original commit changeset:
61771babeac4
fbshipit-source-id:
c2ac0a4a7463fafa03ad0b20bfb0701a8c1476c4
zhouzhuojie [Thu, 19 Aug 2021 22:37:10 +0000 (15:37 -0700)]
Add concurrency group for more workflows (#63606)
Summary:
Fixes unnecessary duplicated workflows runs
Pull Request resolved: https://github.com/pytorch/pytorch/pull/63606
Reviewed By: malfet, mruberry
Differential Revision:
D30436889
Pulled By: zhouzhuojie
fbshipit-source-id:
aafbad1edc45e3ab9bceb00e8f3b4204f18e43d0
Zeina Migeed [Thu, 19 Aug 2021 22:22:52 +0000 (15:22 -0700)]
acc type inference (#63119)
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/63119
Test Plan:
buck run mode/opt-clang caffe2/torch/fb/model_transform/experimental:fx_ir_lower_inline_cvr -- \
--action=lower_and_run \
--filename=inline_cvr_7x_dec_2020.model \
--print_glow_glog=True
Reviewed By: jamesr66a, jfix71, ansley
Differential Revision:
D30235895
fbshipit-source-id:
dab7f96e1799b99eeae0ee519cf0ddd636fddf2e
Sergei Vorobev [Thu, 19 Aug 2021 21:57:00 +0000 (14:57 -0700)]
Replace hardcoded values in IndexKernel.cu (#63372)
Summary:
This is a small change that helps to maintain Cruise pytorch fork, since we use a different hardcoded value.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/63372
Reviewed By: mruberry
Differential Revision:
D30396171
Pulled By: ejguan
fbshipit-source-id:
cc0023f58b5922d3d98c7283495e6dc8d35049b6
Adam J. Stewart [Thu, 19 Aug 2021 21:54:26 +0000 (14:54 -0700)]
DataLoader: allow non-integer Samplers (#63500)
Summary:
Not entirely sure how to use TypeVar but if someone could give me a hint it would be appreciated. Also let me know if you want me to add tests so we can make sure non-integer samplers actually work. It seems like `test/test_dataloader.py` is the correct location but that's a big file.
Fixes https://github.com/pytorch/pytorch/issues/63483
ejguan
Pull Request resolved: https://github.com/pytorch/pytorch/pull/63500
Reviewed By: mruberry
Differential Revision:
D30403689
Pulled By: ejguan
fbshipit-source-id:
464e09e5aad3215b94a29cc5e21cb4b10ec136e3
Kimish Patel [Thu, 19 Aug 2021 20:32:26 +0000 (13:32 -0700)]
[Pytorch] Fix callstack pointer serialization bug (#63576)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/63576
We serialize function name associated with InlinedCallStackPtr. This is derived
via querying Function* stored in InlinedCallStack. However this is a raw
pointer that is not gauranteed to be valid when we serialization happens. On
the other hand we also store function name separately when constructing
InlinedCallStack anyways. So this change just uniformly relies on function_name
instead of Function*
Test Plan: Internal build's asan failure + CI
Reviewed By: larryliu0820
Differential Revision:
D30427029
fbshipit-source-id:
de9617482404785920ed2e67b72f38461590fba3
Charles David Hernandez [Thu, 19 Aug 2021 20:04:48 +0000 (13:04 -0700)]
Updating the names of these functions (#63513)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/63513
updating these names per Jerry's nits in the previous pr
Test Plan: Imported from OSS
Reviewed By: jerryzh168
Differential Revision:
D30406710
fbshipit-source-id:
a9f1577a2b8c4a93f5005e0f6278b7d7348d8b66
Natalia Gimelshein [Thu, 19 Aug 2021 20:00:08 +0000 (13:00 -0700)]
Revert embedding thrust->cub migration (#63451)
Summary:
Fixes https://github.com/pytorch/pytorch/issues/63427
Pull Request resolved: https://github.com/pytorch/pytorch/pull/63451
Reviewed By: mruberry
Differential Revision:
D30398482
Pulled By: ngimel
fbshipit-source-id:
e153786d204215555a6571688eabae712facad7e
Philip Meier [Thu, 19 Aug 2021 19:45:32 +0000 (12:45 -0700)]
Updates internal `assert_allclose` callsites in favor of `assert_close` (#61841)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/61841
Redo of #60863.
Test Plan: Imported from OSS
Reviewed By: ngimel
Differential Revision:
D30408145
Pulled By: mruberry
fbshipit-source-id:
0b34ebc7f23ba38ecd89640b61d8aca59b7eab58
Mike Ruberry [Thu, 19 Aug 2021 19:41:42 +0000 (12:41 -0700)]
Modernizes add and mul documentation (#63309)
Summary:
Fixes https://github.com/pytorch/pytorch/issues/39329.
The documentation for torch.add and torch.mul was sorely out of date and even included deprecated references. This PR modernizes their descriptions consistent with torch.sub.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/63309
Reviewed By: ngimel
Differential Revision:
D30338004
Pulled By: mruberry
fbshipit-source-id:
ee1c2a8106af8341253cafb0003b06e8f652624d
kshitij12345 [Thu, 19 Aug 2021 19:40:37 +0000 (12:40 -0700)]
[special] use __all__ to hide internal imports (#63135)
Summary:
Reference: https://github.com/pytorch/pytorch/issues/50345
Pull Request resolved: https://github.com/pytorch/pytorch/pull/63135
Reviewed By: ngimel
Differential Revision:
D30364287
Pulled By: mruberry
fbshipit-source-id:
20078668943fafa45ce09610634b1d2c424b1922
Yusuo Hu [Thu, 19 Aug 2021 19:37:58 +0000 (12:37 -0700)]
[BF16] Add a missing thread local specifier to autocast_gpu_dtype (#63416)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/63416
Fix a missing thread local specifier introduced by recent PR
https://github.com/pytorch/pytorch/pull/61002
Test Plan: Unit Tests
Reviewed By: ngimel
Differential Revision:
D30376154
fbshipit-source-id:
c70d37ec85c3eba88eb87f766f1c4e7aeff8eaf9
Pritam Damania [Thu, 19 Aug 2021 18:21:26 +0000 (11:21 -0700)]
[7/N] Remove fork tests for RPC. (#63443)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/63443
After https://github.com/pytorch/pytorch/pull/63442, all distributed
tests can run with opt-asan. As a result, we can now remove all of our fork
based tests.
This is the first PR in a stack, which first removes fork based tests from RPC.
ghstack-source-id:
136177744
Test Plan: waitforbuildbot
Reviewed By: lw
Differential Revision:
D30384905
fbshipit-source-id:
86d438aebaa6cb02ae2a966fea244849849a1889
driazati [Thu, 19 Aug 2021 17:38:41 +0000 (10:38 -0700)]
Use CMake for breakpad (#63186)
Summary:
We currently build breakpad from [this fork](https://github.com/driazati/breakpad) to include extra logic to restore signal handlers that were previously present. With some [new additions](https://github.com/google/breakpad/compare/main...driazati:main) this fork now includes a CMake based build, so we can add breakpad as a proper dependency rather than rely on including it in Docker images as a system library which is error prone (we have a bunch of images) and hard to extend to MacOS / Windows. This also includes some changes to the crash handling code to support MacOS / Windows in a similar way to Linux.
```python
import torch
# On Windows this writes crashes to C:\Users\<user>\AppData\pytorch_crashes
# On MacOS/Linux this writes crashes to /tmp/pytorch_crashes
torch.utils._crash_handler.enable_minidumps()
# Easy way to cause a segfault and trigger the handler
torch.bincount(input=torch.tensor([
9223372036854775807]))
```
Pull Request resolved: https://github.com/pytorch/pytorch/pull/63186
Reviewed By: malfet, seemethere
Differential Revision:
D30318404
Pulled By: driazati
fbshipit-source-id:
0d7daf3701cfaba5451cc529a0730272ab1eb1dc
Scott Wolchok [Thu, 19 Aug 2021 17:37:31 +0000 (10:37 -0700)]
[easy] Fix missing move in TupleType::createNamed (#61572)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/61572
ghstack-source-id:
136161829
Test Plan: CI
Reviewed By: SplitInfinity
Differential Revision:
D29672872
fbshipit-source-id:
d8ba2d54f7914dbeb3fc52aa21dd77025951c4b5
Shiyan Deng [Thu, 19 Aug 2021 17:16:26 +0000 (10:16 -0700)]
[hpc] use fx2trt for exploration track (#63535)
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/63535
Reviewed By: yinghai, jianyuh
Differential Revision:
D30272810
fbshipit-source-id:
61f3edf2a2282cd8c268a92acf92feb05a6ae3e1
Shiyan Deng [Thu, 19 Aug 2021 17:16:26 +0000 (10:16 -0700)]
Add permute021 fx2trt converter (#63238)
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/63238
Reviewed By: yinghai
Differential Revision:
D30295373
fbshipit-source-id:
2a189fe485edaa978fd03e4b8d8582edb34ec648
Scott Wolchok [Thu, 19 Aug 2021 16:49:12 +0000 (09:49 -0700)]
[PyTorch] Test IValue move/copy/assign/swap more (#54717)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/54717
Hit more tags in these tests
ghstack-source-id:
136140508
Test Plan: buck test //caffe2/aten:ivalue_test
Reviewed By: anjali411
Differential Revision:
D27339736
fbshipit-source-id:
610c8e92846bb70ba725ab117440326ab50af5ce
David Esiobu [Thu, 19 Aug 2021 16:15:34 +0000 (09:15 -0700)]
Use linecache.lazycache to cache generated code. (#63453)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/63453
Instead of patching linecache.getlines, use linecache.lazycache and
parts of the loader protocol described in PEP-302
Test Plan:
python3 test/test_fx.py
Imported from OSS
Reviewed By: suo
Differential Revision:
D30388176
fbshipit-source-id:
92933711ecf3a21a07e1d6b0d1185ab0efd8341c
anjali411 [Thu, 19 Aug 2021 15:41:08 +0000 (08:41 -0700)]
Add fastpath for dot and vdot when the inputs have conj bit set to True (#62915)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/62915
As much as 45% and 20% perf improvement on CUDA and CPU respectively.
consistent improvement in perf for all cases -- see perf numbers in comments below
Test Plan: Imported from OSS
Reviewed By: heitorschueroff
Differential Revision:
D30404006
Pulled By: anjali411
fbshipit-source-id:
565940da28c7761d993cf43346932c24292e8a4d
Till Hoffmann [Thu, 19 Aug 2021 15:28:55 +0000 (08:28 -0700)]
Poisson zero rate (#61511)
Summary:
This PR fixes https://github.com/pytorch/pytorch/issues/53485 by allowing zero rates for the Poisson distribution. This implementation is consistent with `scipy.stats.poisson` which admits zero rates. In addition to addressing the aforementioned issue, this PR makes two supporting changes:
1. add a `nonnegative` constraint to enforce non-negative rates for the Poisson distribution.
2. adjust the evaluation of the gradient of `xlogy` such that it is well defined for `x == 0 and y == 0`.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/61511
Reviewed By: ejguan
Differential Revision:
D30352917
Pulled By: albanD
fbshipit-source-id:
f3d33da58360e80d75eb83519f199b93232a2a2d
Jeff Daily [Thu, 19 Aug 2021 14:49:43 +0000 (07:49 -0700)]
add distributed/_sharded_tensor/test_sharded_tensor to ROCM_BLOCKLIST (#63508)
Summary:
Fixes current ROCm CI test2 brokenness until tensorpipe is fully supported by ROCm.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/63508
Reviewed By: ejguan
Differential Revision:
D30406450
Pulled By: walterddr
fbshipit-source-id:
c07509271d5d33901f3eaf7ffb916dc3626e1f9a
Ilqar Ramazanli [Thu, 19 Aug 2021 14:15:16 +0000 (07:15 -0700)]
To fix the chainability at epoch zero for some schedulers (#63457)
Summary:
It has been discussed in the https://github.com/pytorch/pytorch/pull/60836#issuecomment-
899084092 that we have observed an obstacle to chain some type of learning rate schedulers. In particular we observed
* some of the learning rate schedulers returns initial learning rates at epoch 0 as
```
return self.base_lrs`
```
* This can be a problem when two schedulers called as chained as
```
scheduler1.step()
scheduler2.step()
```
in particular, we completely ignore the effect of scheduler1 at epoch 0. This could not be an issue if at epoch 0, scheduler1 was ineffective as in many schedulers, however for schedulers as WarmUp Schedulers, where at epoch 0 schedulers multiplicative value is smaller than 1 this could lead to undesired behaviors.
The following code snippet illustrates the problem better
## Reproducing the bug
```python
import torch
from torch.nn import Parameter
from torch.optim import SGD
from torch.optim.lr_scheduler import WarmUpLR, ExponentialLR
model = [Parameter(torch.randn(2, 2, requires_grad=True))]
optimizer = SGD(model, 1.0)
scheduler1 = WarmUpLR(optimizer, warmup_factor=0.1, warmup_iters=5, warmup_method="constant")
scheduler2 = ExponentialLR(optimizer, gamma=0.9)
for epoch in range(10):
print(epoch, scheduler2.get_last_lr()[0])
optimizer.step()
scheduler1.step()
scheduler2.step()
```
### Current Result
```
0 1.0
1 0.9
2 0.81
3 0.
7290000000000001
4 0.
6561000000000001
5 5.
904900000000001
6 5.
314410000000001
7 4.
782969000000001
8 4.
304672100000001
9 3.
874204890000001
```
### Expected Result
```
0 1.0
1 0.9
2 0.81
3 0.
7290000000000001
4 0.
6561000000000001
5 0.
5904900000000001
6 0.
5314410000000001
7 0.
4782969000000001
8 0.
4304672100000001
9 0.
3874204890000001
```
Pull Request resolved: https://github.com/pytorch/pytorch/pull/63457
Reviewed By: datumbox
Differential Revision:
D30424160
Pulled By: iramazanli
fbshipit-source-id:
3e15af8d278c872cd6f53406b55f4d3ce5002867
Alban Desmaison [Thu, 19 Aug 2021 13:47:31 +0000 (06:47 -0700)]
Update full backward hook doc with not-same-object note (#63245)
Summary:
Fixes https://github.com/pytorch/pytorch/issues/61446
Pull Request resolved: https://github.com/pytorch/pytorch/pull/63245
Reviewed By: ejguan
Differential Revision:
D30352656
Pulled By: albanD
fbshipit-source-id:
7000ecb54a80f2da968ec7600b98574b608578ae
Mike Iovine [Thu, 19 Aug 2021 13:37:44 +0000 (06:37 -0700)]
[Static Runtime] Support __getitem__ for lists (#63398)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/63398
This change provides a native `__getitem__` implementation for lists to avoid overhead associated with falling back to the JIT interpreter.
Test Plan: Unit tests: `buck test //caffe2/benchmarks/static_runtime:static_runtime_cpptest`
Reviewed By: hlu1
Differential Revision:
D30368464
fbshipit-source-id:
e0e0971508cd5d9bcf6025606993dc24ecbf6764
Alban Desmaison [Thu, 19 Aug 2021 13:19:20 +0000 (06:19 -0700)]
Revert
D29399533: Hoisting common expressions out of If blocks
Test Plan: revert-hammer
Differential Revision:
D29399533 (https://github.com/pytorch/pytorch/commit/
9477211e7d609ce382c0e22d7721c14c36d083de)
Original commit changeset:
9336b9dc48c0
fbshipit-source-id:
f081c7280203f40328bcbb0c03a7c6a007acedb7
Chen Lai [Thu, 19 Aug 2021 09:12:44 +0000 (02:12 -0700)]
Fix interpreter debug logging message (#63499)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/63499
https://github.com/pytorch/pytorch/pull/62418 combine the instruction and debug handle. This change fix the debugging message.
ghstack-source-id:
136184053
Test Plan: Uncomment and it works
Reviewed By: kimishpatel, raziel
Differential Revision:
D30390699
fbshipit-source-id:
e32b7b297ad3b7d8bffebd025d15519083a244c4
Nikolay Korovaiko [Thu, 19 Aug 2021 05:59:40 +0000 (22:59 -0700)]
layernom inplace (#63437)
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/63437
Test Plan: Imported from OSS
Reviewed By: ngimel
Differential Revision:
D30388824
Pulled By: Krovatkin
fbshipit-source-id:
852d19bf238544c5de177ed5854dcd01c7ae5572
Nikolay Korovaiko [Thu, 19 Aug 2021 05:59:40 +0000 (22:59 -0700)]
layernorm (#63436)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/63436
use MKLDNN layernorm
use mkldnn version 2
address Elias feedback
fix build CI errors
Test Plan: Imported from OSS
Reviewed By: ngimel
Differential Revision:
D30388825
Pulled By: Krovatkin
fbshipit-source-id:
fb909bfbf53cb8567a43aac40f51c491daeec908
Mikhail Zolotukhin [Thu, 19 Aug 2021 05:56:47 +0000 (22:56 -0700)]
[TensorExpr] Make CacheReplacer and IndexFlattener mutate stmts/exprs inplace. (#63527)
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/63527
Test Plan: Imported from OSS
Reviewed By: navahgar
Differential Revision:
D30411411
Pulled By: ZolotukhinM
fbshipit-source-id:
efb14ee57b36537fa4fefa89bdd6bafe7151c012
Mikhail Zolotukhin [Thu, 19 Aug 2021 05:56:47 +0000 (22:56 -0700)]
[TensorExpr] Speedup ExternalCall.ComputeInterop test by reducing tensor sizes. (#63526)
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/63526
Test Plan: Imported from OSS
Reviewed By: navahgar
Differential Revision:
D30411410
Pulled By: ZolotukhinM
fbshipit-source-id:
d9a99afac14d2238b5100c98ae9ed4467f9f05ea
Michael Dagitses [Thu, 19 Aug 2021 04:39:18 +0000 (21:39 -0700)]
support optional comparisons with different but comparable types (#62890)
Summary:
Fixes https://github.com/pytorch/pytorch/issues/62565
Pull Request resolved: https://github.com/pytorch/pytorch/pull/62890
Reviewed By: ejguan
Differential Revision:
D30396008
Pulled By: dagitses
fbshipit-source-id:
fca02207509f882973d54484f89c4d116505fc66
Edward Yang [Thu, 19 Aug 2021 03:56:25 +0000 (20:56 -0700)]
Beef up comment in AccumulateType (#63503)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/63503
Signed-off-by: Edward Z. Yang <ezyang@fb.com>
Test Plan: Imported from OSS
Reviewed By: ngimel
Differential Revision:
D30403160
Pulled By: ezyang
fbshipit-source-id:
6cb24418152d9fb146f86b6f973ec50f1a397a58
Yinbin Ma [Thu, 19 Aug 2021 03:52:17 +0000 (20:52 -0700)]
BF16 allreduce hook (#63260)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/63260
Add BF16 all-reduce communication hook. Skip if CUDA version < 11 or NCCL version < 2.9.7.
Reviewed By: SciPioneer
Differential Revision:
D30238317
fbshipit-source-id:
bad35bf7d43f10f1c40997a282b831b61ef592bb
John Clow [Wed, 18 Aug 2021 23:28:02 +0000 (16:28 -0700)]
Hoisting common expressions out of If blocks (#59492)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/59492
Adding code to find common expressions from the two subblocks of an if
operation and hoist them before the if block.
This also allows Dead Code Elimination to
then eliminate some if blocks.
Also eliminated some dead code in the codebase.
Test Plan:
python test_jit.py TestIfHoisting
Imported from OSS
Reviewed By: ngimel
Differential Revision:
D29399533
fbshipit-source-id:
9336b9dc48c02c38862f98f98cd72fc1767a1802
Amy He [Wed, 18 Aug 2021 23:23:48 +0000 (16:23 -0700)]
Nnapi Delegation: Quick improvements (#63489)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/63489
A few quick improvements to the Android NNAPI Delegate, some of which were discussed here https://github.com/pytorch/pytorch/pull/62272:
1) `throw std::exception` replaced with `TORCH_CHECK` to reduce runtime
size (nnapi_backend_lib.cpp)
2) weights processing moved from compile to preprocess step, since it can
be done AOT (nnapi_backend_lib.cpp & nnapi_backend_preprocess.cpp)
3) `ser_model_` and `shape_compute_module_` member variables removed, since they are never used after
`init()`, so they are not needed (nnapi_backend_lib.cpp)
Test Plan:
Unit tests: `python test/test_jit.py TestNnapiBackend`
Run SparkAR segmentation with delegated NNAPI as done here
D30259033 (can use `jf download GAekdAwsyGKXhggFALN4LnSBTzcubsIXAAAz --file "v303-nnd-mod.ptl"` to get a preprocessed model from these changes)
Imported from OSS
Reviewed By: raziel, iseeyuan
Differential Revision:
D30398880
fbshipit-source-id:
b6872e1e9ccd583622b80659da00c83fdd82580e
kshitij12345 [Wed, 18 Aug 2021 23:08:48 +0000 (16:08 -0700)]
[fix] tensor_split : non-contiguous indices tensor (#63390)
Summary:
Fixes https://github.com/pytorch/pytorch/issues/63281
Pull Request resolved: https://github.com/pytorch/pytorch/pull/63390
Reviewed By: ejguan
Differential Revision:
D30362649
Pulled By: mruberry
fbshipit-source-id:
3ea3ad02199e4345beb0b580d056babd56112309
Sangbaek Park [Wed, 18 Aug 2021 22:50:33 +0000 (15:50 -0700)]
[Vulkan] Fix incorrect input range for Hardshrink tests (#63515)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/63515
Fixed inappropriate input range for Hardshrink tests:
The range -10 ~ +10 for input tensors is more proper when we use the test set of lambda {-4.2, -1.0, -0.42, 0.0, 0.42, 1.0, 4.2, 42.42}.
ghstack-source-id:
136141416
Test Plan:
```build -c ndk.custom_libcxx=false -c pt.enable_qpl=0 //xplat/caffe2:pt_vulkan_api_test_binAndroid\#android-arm64 --show-output
adb push buck-out/gen/xplat/caffe2/pt_vulkan_api_test_binAndroid\#android-arm64 /data/local/tmp/vulkan_api_test
adb shell "/data/local/tmp/vulkan_api_test"
```
Note that the test can fail sporadically due to the precision loss by FP16(Vulkan)/FP32(CPU). This issue will be handled separately after some design discussions.
Reviewed By: SS-JIA
Differential Revision:
D30389646
fbshipit-source-id:
7224bd8ba4e4972f5fc147df8a0cb84808f8c62e
Rong Rong (AI Infra) [Wed, 18 Aug 2021 22:02:05 +0000 (15:02 -0700)]
using PR number instead of IN_PULL_REQUEST (#63360)
Summary:
PR numbers should be available on GHA after this.
This fixes some target determinator not working issue discovered when manually running: https://github.com/pytorch/pytorch/issues/63412.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/63360
Reviewed By: malfet, zhouzhuojie, seemethere
Differential Revision:
D30374615
Pulled By: walterddr
fbshipit-source-id:
eee8d8bb7aa4308a6a50cfdcd4423a96d846777f
Mike Iovine [Wed, 18 Aug 2021 21:56:51 +0000 (14:56 -0700)]
[Static Runtime] Benchmark reports native nodes (#63346)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/63346
We have seen that we can get significant perf wins essentially for free by implementing native ops for ops that we cannot write out variants for (e.g. TupleUnpack
D30306955 (https://github.com/pytorch/pytorch/commit/
078b8004a62a51f75e1fbd8d08eea359af6bb1d7), append
D30326461 (https://github.com/pytorch/pytorch/commit/
9d9e7a8d7294834ddad957ddb1f4cd5a0e741e55)). Therefore, whether or not SR is using a native implementation is valuable information. By capturing this in the benchmarking suite, we can hopefully avoid wasting time profiling/manually inspecting `native_ops.cpp`
Reviewed By: hlu1
Differential Revision:
D30346752
fbshipit-source-id:
205b090513b6a5a6ce4cb92f75ab0395b15d08f9
Mostafa Elhoushi [Wed, 18 Aug 2021 21:47:40 +0000 (14:47 -0700)]
[FX] make ASTReriter patch wrapped functions properly (#62987)
Summary:
reference the same global namespace (instead of copying it) in ASTRewriter to patch wrapped functions properly
Fixes #{62071}
Pull Request resolved: https://github.com/pytorch/pytorch/pull/62987
Test Plan:
To test it you may write this snippet and ensure the results are as shown in the comments:
```
import torch
import torch.fx
torch.fx.wrap
def to_be_wrapped(x):
return torch.relu(x)
class Foo(torch.nn.Module):
def forward(self, x):
return to_be_wrapped(x)
traced = torch.fx.symbolic_trace(Foo())
print(traced.graph)
"""
graph():
%x : [#users=1] = placeholder[target=x]
%to_be_wrapped : [#users=1] = call_function[target=__main__.to_be_wrapped](args = (%x,), kwargs = {})
return to_be_wrapped
"""
from torch.fx.experimental.rewriter import RewritingTracer
rt = RewritingTracer()
graph = rt.trace(Foo())
print(graph)
"""
### AFTER FIX (CORRECT):
graph():
%x : [#users=1] = placeholder[target=x]
%to_be_wrapped : [#users=1] = call_function[target=__main__.to_be_wrapped](args = (%x,), kwargs = {})
return to_be_wrapped
### BEFORE FIX (WRONG):
graph():
%x : [#users=1] = placeholder[target=x]
%relu : [#users=1] = call_function[target=torch.relu](args = (%x,), kwargs = {})
return relu
"""
```
Reviewed By: ansley
Differential Revision:
D30396176
Pulled By: mostafaelhoushi
fbshipit-source-id:
f61eddf32e9ef42b5f5c3ce21d559945214ee833
Dhruv Matani [Wed, 18 Aug 2021 21:47:19 +0000 (14:47 -0700)]
[PyTorch] Avoid using std::regex for device string parsing in Device.cpp (#63464)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/63464
This was previously committed as
D30281388 (https://github.com/pytorch/pytorch/commit/
4d6f98ecada2d85b2474b023838debad4305316d), but was reverted due to t98478641. jnkwok1 confirmed that this change was not the root cause, so trying to land it again.
Currently, `std::regex` is used for parsing device strings. This is undesirable for a few reasons.
1. Increases binary size
2. Slows down model loading
3. Potentially uses more memory at runtime
4. Takes marginally longer time to build code that uses std::regex v/s not using std::regex
This change avoids the use of `std::regex` for parsing the device string since we don't need to.
ghstack-source-id:
136006963
ghstack-source-id:
136081898
Test Plan:
### AI Bench Runs
**Before this change:**
1. Model Load time: [252ms](https://www.internalfb.com/intern/aibench/details/
332471502816548)
2. Model unload time: 3.5ms
**After this change:**
1. Model Load time: [240ms](https://www.internalfb.com/intern/aibench/details/
652195589031318), which is an approx 5% reduction for the current model. I suspect percentage wise, it will be larger for smaller models since this is a fixed cost reduction.
2. Model unload time: 3.3ms (probably too small to be meaningfully impactful to an end user).
### BSB Results
```
D30281388 (https://github.com/pytorch/pytorch/commit/
4d6f98ecada2d85b2474b023838debad4305316d)-V1 (https://www.internalfb.com/intern/diff/
D30281388 (https://github.com/pytorch/pytorch/commit/
4d6f98ecada2d85b2474b023838debad4305316d)/?dest_number=
135713848)
messenger-pika-optimized-device: Succeeded
Change in Download Size for arm64 + 3x assets variation: -7.1 KiB
Change in Uncompressed Size for arm64 + 3x assets variation: -17.6 KiB
Mbex Comparison: https://our.intern.facebook.com/intern/mbex/bsb:
551399955987465@base/bsb:
551399955987465@diff/
```
Reviewed By: raziel, pavithranrao
Differential Revision:
D30388269
fbshipit-source-id:
10942e7aa56f9ea47aa479a8f50187f2ce2899bf
Mikhail Zolotukhin [Wed, 18 Aug 2021 21:46:25 +0000 (14:46 -0700)]
[TensorExpr] IRSimplifier: sort terms in polynomials, terms, minterms, maxterms. (#63197)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/63197
This solves non-determinism from using hash values in sort methods.
Changes in tests are mostly mechanical.
Test Plan: Imported from OSS
Reviewed By: navahgar
Differential Revision:
D30292776
Pulled By: ZolotukhinM
fbshipit-source-id:
74f57b53c3afc9d4be45715fd74781271373e055
Mikhail Zolotukhin [Wed, 18 Aug 2021 21:46:25 +0000 (14:46 -0700)]
[TensorExpr] Add debug logging to LoopNest::computeInline. (#63196)
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/63196
Test Plan: Imported from OSS
Reviewed By: navahgar
Differential Revision:
D30292778
Pulled By: ZolotukhinM
fbshipit-source-id:
d8a111b75466a9354f6d048119cc6f814c9d5abb
Michael Dagitses [Wed, 18 Aug 2021 20:43:54 +0000 (13:43 -0700)]
clarify that `torch.finfo.tiny` is the smallest normal number (#63241)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/63241
This is a common source of confusion, but it matches the NumPy
behavior.
Fixes #44010
Fixes #59526
Test Plan: Imported from OSS
Reviewed By: ejguan
Differential Revision:
D30307646
Pulled By: dagitses
fbshipit-source-id:
d848140ba267560387d83f3e7acba8c3cdc53d82
Alexander Grund [Wed, 18 Aug 2021 20:33:36 +0000 (13:33 -0700)]
Fix segmentation fault due to access to destroyed CudaIPCGlobalEntities instance (#56141)
Summary:
There is an instance of the static destruction order fiasco where cuda_ipc_global_entities may be accessed after it is destroyed. See https://github.com/pytorch/pytorch/issues/51961
This change uses a flag and avoids accesses to the destroyed class when it is set to false.
Fixes https://github.com/pytorch/pytorch/issues/51961
This removes the function to clear shared_blocks introduced by https://github.com/pytorch/pytorch/issues/53080 which had multiple issues: Unprotected access to a shared structure and modification of the vector which is being cleared by the destructors of the objects contained.
I.e. what happened was:
- `CudaIPCSentDataLimbo_.clear_shared_blocks();` is called from the destructor of CudaIPCGlobalEntities as of your PR
- This deletes instances of `CudaIPCSentData` which hold `at::DataPtr` created by `GetNewRefCountedSentData`
- This means `CudaIPCSentDataDelete` is called with still active pointers
- Hence `CudaIPCSentDataLimbo_.add` is called adding a new value to `shared_blocks_`
Pull Request resolved: https://github.com/pytorch/pytorch/pull/56141
Reviewed By: ejguan
Differential Revision:
D30397279
Pulled By: VitalyFedyunin
fbshipit-source-id:
ce4b8b90fa1c90d275e5eca93ba84321cbc6140a
Charles David Hernandez [Wed, 18 Aug 2021 20:30:35 +0000 (13:30 -0700)]
Bugfix for fuse qconfig comparison (#63384)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/63384
In some cases the changes to qconfig on module would cause the
fusions to fail. This bugfix solves that problem by adding a
qconfig_function_comparison that compares the functions within the
qconfig rather than the modules the qconfigs are on. The comparison
looks at the partial object within QConfig.activation/weight.p and
compares args, keywords and func. This is necessary to do mannually
because partial doesn't have __eq__ implemented and so == reverts to is.
Test Plan:
python test/test_quantization.py
TestFuseFx.test_problematic_fuse_example
Imported from OSS
Reviewed By: supriyar, ejguan
Differential Revision:
D30386264
fbshipit-source-id:
51e358c021c39d6f48dc12ad2a82b2838677b9de
BowenBao [Wed, 18 Aug 2021 20:25:19 +0000 (13:25 -0700)]
[ONNX] Fix for batchnorm training op mode (#52758) (#62760)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/62760
* Rebase
# Conflicts:
# torch/csrc/jit/passes/onnx/eval_peephole.cpp
# Conflicts:
# test/onnx/test_utility_funs.py
# torch/onnx/symbolic_opset9.py
* Update symbolic_opset12.py
* Update test.sh
# Conflicts:
# .jenkins/caffe2/test.sh
* Merge
* Fix utility tests
# Conflicts:
# test/onnx/test_pytorch_onnx_onnxruntime.py
# test/onnx/test_utility_funs.py
* Fix for comment
* Enable BN tests
* Fix for test
* Update test_pytorch_onnx_onnxruntime.py
* Update test_pytorch_onnx_onnxruntime.py
* Update test_utility_funs.py
* Update test_pytorch_onnx_onnxruntime.py
Test Plan: Imported from OSS
Reviewed By: SplitInfinity
Differential Revision:
D30349060
Pulled By: msaroufim
fbshipit-source-id:
93312c17607974731c17099ae181acb6e4c1c409
BowenBao [Wed, 18 Aug 2021 20:25:19 +0000 (13:25 -0700)]
[ONNX] Remove aten parameter (#61652) (#62759)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/62759
* remove aten argument in export()
* add export_to_pretty_string default value OperatorExportTypes.ONNX
* add DPYTORCH_ONNX_CAFFE2_BUNDLE description
Test Plan: Imported from OSS
Reviewed By: SplitInfinity
Differential Revision:
D30349062
Pulled By: msaroufim
fbshipit-source-id:
d9738f3aa8b80eac54548d0b9494f9f1e544f20f
Co-authored-by: Gary Miguel <garymiguel@microsoft.com>
BowenBao [Wed, 18 Aug 2021 20:25:19 +0000 (13:25 -0700)]
[ONNX] Add support for opset14 in PT-ONNX exporter (#59486) (#62758)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/62758
* Add initial changes for opset14
* Fixed flake
* Add onnx submodule changes and removed utility func tests
* Add updated batchNorm symbolic
* Add triu/tril symbolics
* Fix lint
* Fixed test failures
* Add reshape with allowzero
* Added tests/refactored opset versioning
* Bump onnxruntime version
* Fix clang/lint failures
* Add reshape shape inference for opset 14
* Changes for allowzero
* Fix lint/clang and test failures
* Updated PR
* Flake fixes
* Fix flake
* Remove new_jit_api tests
* Add opset14 models
* Update allowzero
* Fix test failures
Test Plan: Imported from OSS
Reviewed By: SplitInfinity
Differential Revision:
D30349063
Pulled By: msaroufim
fbshipit-source-id:
54724246149b01a2f627c43d7396253a7e9c9eb9
Co-authored-by: Shubham Bhokare <sbhokare@OrtTrainingDev3.af05slrtruoetgaxwwjv5nsq5e.px.internal.cloudapp.net>
BowenBao [Wed, 18 Aug 2021 20:25:19 +0000 (13:25 -0700)]
[ONNX] Support lstm_cell symbolic (#61476) (#62757)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/62757
Support lstm_cell symbolic
Test Plan: Imported from OSS
Reviewed By: SplitInfinity
Differential Revision:
D30349061
Pulled By: msaroufim
fbshipit-source-id:
f236177e3e5c62a30b7e4d91a623bcaef21b5eb1
Co-authored-by: jiafatom <jiafa@microsoft.com>
James Reed [Wed, 18 Aug 2021 20:16:01 +0000 (13:16 -0700)]
[FX] Fix GraphModule deepcopy to use deepcopied graph (#63090)
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/63090
Test Plan: Imported from OSS
Reviewed By: ansley
Differential Revision:
D30252471
Pulled By: jamesr66a
fbshipit-source-id:
cafd7d7917935a5ea6ffa2a7fe9e9b2a9578b3e3
Basil Hosmer [Wed, 18 Aug 2021 19:06:53 +0000 (12:06 -0700)]
MaybeOwned page for dev wiki (#63450)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/63450
Brief guide to understanding `MaybeOwned<Tensor>`, aimed at C++ PT devs who are obliged to interact with existing uses of it, rather than encouraging new usage.
For reviewers: I haven't yet added a link to this page from anywhere. I'm thinking the right place is the [dev wiki main page C++ section](https://github.com/pytorch/pytorch/wiki#c) but happy to put it wherever makes sense, suggestions welcome.
Test Plan: Imported from OSS
Reviewed By: navahgar
Differential Revision:
D30402313
Pulled By: bhosmer
fbshipit-source-id:
69b15909ecafcd8d88e44f664f88c3ad4eb26d84
peterjc123 [Wed, 18 Aug 2021 18:41:42 +0000 (11:41 -0700)]
Disable RDYNAMIC check with MSVC (#62949)
Summary:
When testing with clang-cl, the flag is added though it is unsupported and that generates a few warnings. Tried a few alternatives like https://cmake.org/cmake/help/latest/module/CheckLinkerFlag.html, but they just don't work.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/62949
Reviewed By: zhouzhuojie, driazati
Differential Revision:
D30359206
Pulled By: malfet
fbshipit-source-id:
1bd27ad5772fe6757fa8c3a4bddf904f88d70b7b
Michael Dagitses [Wed, 18 Aug 2021 18:39:12 +0000 (11:39 -0700)]
document why wrappers exist in `torch.functional` (#62847)
Summary:
Fixes https://github.com/pytorch/pytorch/issues/62844.
These wrappers are not super obvious, but ultimately stem from the lack of support for functions with variadic args in native_functions.yaml. https://github.com/pytorch/pytorch/issues/62845 tracks that issue.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/62847
Reviewed By: VitalyFedyunin
Differential Revision:
D30305016
Pulled By: dagitses
fbshipit-source-id:
716fcecb0417b770bc92cfd8c54f7ead89070896
Rohan Varma [Wed, 18 Aug 2021 18:38:11 +0000 (11:38 -0700)]
[DDP] Add a debug check in cpp fp16 compress (#63379)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/63379
this codepath has been prone to bugs as seen in the below diff, this
will help ensure against changes/refactors that touch this, as a basic sanity
check. Enabled it in debug-only builds to not affect the perf.
ghstack-source-id:
136056093
Test Plan: CI
Reviewed By: SciPioneer
Differential Revision:
D30358440
fbshipit-source-id:
e1b3893a223722c2593ceed8696a09c7d07d47c1
Rohan Varma [Wed, 18 Aug 2021 18:38:11 +0000 (11:38 -0700)]
[DDP][Grad compression] Fix fp16 cpp hook (#63375)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/63375
I think tensor.copy_(tensor.to(torch::kFloat16)); will keep it as
float32.
Tested by add the following line:
```
LOG(INFO) << "Type is: " << compressed_tensor.scalar_type();
```
before:
```
I0816 17:03:09.823688 364141 default_comm_hooks.cpp:21] Type is: Float
```
after:
```
I0816 17:01:16.779052 353924 default_comm_hooks.cpp:21] Type is: Half
```
ghstack-source-id:
136056092
Test Plan: ci
Reviewed By: SciPioneer
Differential Revision:
D30356256
fbshipit-source-id:
8208a705acd7628541cd43c8bf61d007dfdd2435
Stas Bekman [Wed, 18 Aug 2021 18:37:07 +0000 (11:37 -0700)]
[doc] pre-commit fix instructions (#61717)
Summary:
fix invalid instruction
Pull Request resolved: https://github.com/pytorch/pytorch/pull/61717
Reviewed By: zhouzhuojie, driazati
Differential Revision:
D30359218
Pulled By: malfet
fbshipit-source-id:
61771babeac4d34425a61ce49f38a7099b521eec
Heitor Schueroff [Wed, 18 Aug 2021 18:30:44 +0000 (11:30 -0700)]
Make SkipInfo with expected_failure an XFAIL (#63481)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/63481
This PR changes the SkipInfo decorators to use unittest.expectedFailure so that the test reports as XFAIL as opposed to PASSED.
Note that changing the expectedFailure here https://github.com/pytorch/pytorch/blob/
30e1c74dc19ae2b622b46ebcdb7972c42775ac80/torch/testing/_internal/common_device_type.py#L879 to an XFAIL is not possible because the decision of whether to decorate is delayed until the wrapper function is called.
fixes https://github.com/pytorch/pytorch/issues/63363
Test Plan: Imported from OSS
Reviewed By: ZolotukhinM
Differential Revision:
D30397154
Pulled By: heitorschueroff
fbshipit-source-id:
c5e4911969ad8667763eec4203dbbc6a51178592
soulitzer [Wed, 18 Aug 2021 18:29:51 +0000 (11:29 -0700)]
Improve custom function docs (#60312)
Summary:
- Adds some code examples for `ctx` methods and make requirements of arguments more clear
- Type annotations for `save_for_backward`, `mark_dirty`, `mark_non_differentiable`, and `set_materialize_grads` (BC-breaking?)
- Refactor `torch.autograd.Function` doc
Pull Request resolved: https://github.com/pytorch/pytorch/pull/60312
Reviewed By: VitalyFedyunin
Differential Revision:
D30314961
Pulled By: soulitzer
fbshipit-source-id:
a284314b65662e26390417bd2b6b12cd85e68dc8
Pritam Damania [Wed, 18 Aug 2021 17:46:09 +0000 (10:46 -0700)]
[6/N] Enable opt-asan for elastic and launcher tests. (#63442)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/63442
Continuation of https://github.com/pytorch/pytorch/pull/62051, I've
enabled elastic and launcher tests to run in opt-asan mode which is supported
with spawn multiprocessing.
This allows us to completely get rid of fork based tests from torch.distributed
and have all tests run in spawn mode.
ghstack-source-id:
136057123
Test Plan: waitforbuildbot
Reviewed By: cbalioglu
Differential Revision:
D30384267
fbshipit-source-id:
ad3447cfb9d6e31e7ec8332d64c8ff1054858dcb
Shirong Wu [Wed, 18 Aug 2021 17:39:53 +0000 (10:39 -0700)]
Add validation check in fx2trt interpreter (#63424)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/63424
Add validation check in fx2trt for missing converter operators. If any op missing, interpreter init will report missing operators.
Test Plan:
for call_function and call_method:
manual test with feeds benchmark and verify init failed with expected message.
{
F642390780}
for call_module:
specify a module as leaf node and make acc_tracer trace it as a node; then in fx2trt.py, in CONVERTER initialize stage make it skip recording all modules; initialize interpreter and call validator function, verify the output includes the missing module name, return value print as screenshot below.
{
F643458718}
Reviewed By:
842974287
Differential Revision:
D30294832
fbshipit-source-id:
243dca3fdfc6a174ded65248938e2a234aec19c6
John Shen [Wed, 18 Aug 2021 17:35:55 +0000 (10:35 -0700)]
[pytorch] Make qconv forward() thread safe (#63432)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/63432
There's a race condition in quantized models when multiple threads call forward() due to qnnpack packing the weights the first time the operator is called. This locks the entire apply_impl function.
Test Plan:
https://github.com/pytorch/pytorch/issues/58055
Ran the script before and after, original crashes went away
Reviewed By: kimishpatel
Differential Revision:
D30229520
fbshipit-source-id:
d06cabe24199a80325cd57f24a7fd60624be2cf7
Masaki Kozuki [Wed, 18 Aug 2021 16:42:14 +0000 (09:42 -0700)]
Use `fastAtomicAdd` in EmbeddingBag (mode "max") backward (#63298)
Summary:
Rel: https://github.com/pytorch/pytorch/issues/62695
### This PR
| n_tokens | num_embeddings | embedding_dim | mode | bwd_fp32 | bwd_fp16 |
|-----------:|-----------------:|----------------:|:-------|------------:|------------:|
| 4096 | 4096 | 4096 | max | 0.
000326228 | 0.
000181448 |
| 4096 | 4096 | 16384 | max | 0.
00102805 | 0.
000618136 |
| 4096 | 16384 | 4096 | max | 0.
000907326 | 0.
000530422 |
| 4096 | 16384 | 16384 | max | 0.
00334988 | 0.
00264645 |
| 16384 | 4096 | 4096 | max | 0.
000366449 | 0.
000320232 |
| 16384 | 4096 | 16384 | max | 0.
00126421 | 0.
00104183 |
| 16384 | 16384 | 4096 | max | 0.
00087738 | 0.
00065068 |
| 16384 | 16384 | 16384 | max | 0.
00379229 | 0.
00298201 |
### Original
| n_tokens | num_embeddings | embedding_dim | mode | bwd_fp32 | bwd_fp16 |
|-----------:|-----------------:|----------------:|:-------|------------:|------------:|
| 4096 | 4096 | 4096 | max | 0.
00032407 | 0.
000188231 |
| 4096 | 4096 | 16384 | max | 0.
00104356 | 0.
000624001 |
| 4096 | 16384 | 4096 | max | 0.
000902069 | 0.
000527382 |
| 4096 | 16384 | 16384 | max | 0.
00302202 | 0.
00255153 |
| 16384 | 4096 | 4096 | max | 0.
000384343 | 0.
000403249 |
| 16384 | 4096 | 16384 | max | 0.
00126445 | 0.
00135069 |
| 16384 | 16384 | 4096 | max | 0.
000880814 | 0.
000825679 |
| 16384 | 16384 | 16384 | max | 0.
00337611 | 0.
00319515 |
cc xwang233 ptrblck ngimel
Pull Request resolved: https://github.com/pytorch/pytorch/pull/63298
Reviewed By: mruberry
Differential Revision:
D30383583
Pulled By: ngimel
fbshipit-source-id:
14dd9d67002c53a153721812709033c198f68c1e
Rishi Puri [Wed, 18 Aug 2021 16:41:37 +0000 (09:41 -0700)]
Reverting launch bounds change in topK that induced a regression in perf (#63431)
Summary:
[topkwsyncs.zip](https://github.com/pytorch/pytorch/files/7003077/topkwsyncs.zip)
Running this script on nvidia containers 21.08 vs 21.07 we see the following perf drops:
topk(input=(dtype=torch.float16,shape=[60, 201600]), k=2000, dim=1, sorted=True) - 0.63
topk(input=(dtype=torch.float32,shape=[120000]), k=12000, dim=0, sorted=False) - 0.55
topk(input=(dtype=torch.float16,shape=[5, 201600]), k=2000, dim=1, sorted=True) - 0.55
topk(input=(dtype=torch.float32,shape=[1, 10000]), k=1000, dim=1, sorted=False) - 0.33
The relative perf drop is reported as (21.08_time - 21.07_time) / 21.07_time
I narrowed down the source of the regression to this commit: https://github.com/pytorch/pytorch/pull/60314
which reduced launch bounds from 1024 to 512.
The perf did not seem to regress in the original evidence provided to change 1024 to 512 due to the input shapes in the benchmark being a lot smaller than the input shapes of the tensors which I am witnessing perf regression in. I suggest reverting back to 1024 as with 512 there was no considerable improvement in perf for small inputs and a major regression in perf for large tensors.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/63431
Reviewed By: mruberry
Differential Revision:
D30384087
Pulled By: ngimel
fbshipit-source-id:
11eecbba82a069b1d4579d674c3f644ab8060ad2
Erjia Guan [Wed, 18 Aug 2021 15:47:27 +0000 (08:47 -0700)]
Make DataChunk support list in-place ops (#63422)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/63422
Fixes #63095
Make `DataChunk` delegate to list method. Then it will support in-place operations:
- `sort`
- `reverse`
- `append`
- `extend`
- `random.shuffle`
Test Plan: Imported from OSS
Reviewed By: ngimel
Differential Revision:
D30379027
Pulled By: ejguan
fbshipit-source-id:
d176bd0cc8b89b915c7bb184ff243ab1f605616d
cyy [Wed, 18 Aug 2021 15:04:08 +0000 (08:04 -0700)]
A tiny fix in MT19937RNGEngine (#63219)
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/63219
Reviewed By: VitalyFedyunin
Differential Revision:
D30341484
Pulled By: ezyang
fbshipit-source-id:
0ff4499d0f4a3dfeb991c0f10fe3248c6ca1c992
Edward Yang [Wed, 18 Aug 2021 14:45:45 +0000 (07:45 -0700)]
Implement subclass priority for __torch_dispatch__ (#63411)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/63411
In order to get this behavior, you have to use append_overloaded,
which I forgot to use in the previous implementation. I exposed
an internal helper function which is more appropriate for dispatch
to Python where we know that an argument is definitely a Tensor (and
this test no longer needs to be done).
Signed-off-by: Edward Z. Yang <ezyang@fb.com>
Test Plan: Imported from OSS
Reviewed By: zou3519
Differential Revision:
D30374489
Pulled By: ezyang
fbshipit-source-id:
43b08c00d1958c9b26d82a025d19f0b67bb85590
Jerry Zhang [Wed, 18 Aug 2021 14:36:47 +0000 (07:36 -0700)]
[fx2trt] Add dequantize support (#63448)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/63448
Only available after TensorRT 8.0
Test Plan: buck run mode/opt caffe2/torch/fb/fx2trt:test_dequantize
Reviewed By:
842974287
Differential Revision:
D30296863
fbshipit-source-id:
44b9630ef0d210e7f20e650dc81c519f7e41f5f3
Philip Meier [Wed, 18 Aug 2021 14:36:22 +0000 (07:36 -0700)]
add `OpInfo` for `torch.linalg.tensorinv` (#62326)
Summary:
Fixes https://github.com/pytorch/pytorch/issues/53739.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/62326
Reviewed By: H-Huang
Differential Revision:
D30136376
Pulled By: zou3519
fbshipit-source-id:
04ec9450e8866667649af401c7559b96ddc91491
JackCaoG [Wed, 18 Aug 2021 13:42:51 +0000 (06:42 -0700)]
Update cuda amp to also check xla device (#63413)
Summary:
Fixes https://github.com/pytorch/xla/issues/3086. Pytorch/XLA:GPU also use cuda amp. I verified the pt/xla `test_autocast` with this fix and all test passed.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/63413
Reviewed By: ngimel
Differential Revision:
D30380785
Pulled By: bdhirsh
fbshipit-source-id:
fd1a1de7d224c616fc3fa90b80a688a21f6b1ecc
CodemodService FBSourceClangFormatLinterBot [Wed, 18 Aug 2021 11:18:47 +0000 (04:18 -0700)]
[AutoAccept][Codemod][FBSourceClangFormatLinter] Daily `arc lint --take CLANGFORMAT`
Reviewed By: zertosh
Differential Revision:
D30391472
fbshipit-source-id:
d4eb1e7debea8905e7fee5f026c082bee65e78f3
Michael Dagitses [Wed, 18 Aug 2021 11:04:43 +0000 (04:04 -0700)]
enhance comparison tests for c10::optional (#62887)
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/62887
Reviewed By: VitalyFedyunin
Differential Revision:
D30305044
Pulled By: dagitses
fbshipit-source-id:
d0a3a9e4ea186915ef087543aaf81a606f943380
Michael Dagitses [Wed, 18 Aug 2021 10:59:51 +0000 (03:59 -0700)]
clarify the documentation of `torch.meshgrid` (#62977)
Summary:
Also warn about the behavior differences from `numpy.meshgrid`.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/62977
Reviewed By: mruberry, ngimel
Differential Revision:
D30220930
Pulled By: dagitses
fbshipit-source-id:
ae6587b41792721cae2135376c58121b4634e296
Pritam Damania [Wed, 18 Aug 2021 08:58:05 +0000 (01:58 -0700)]
[5/N] Run opt-asan with detect_leaks=0 (#63361)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/63361
Python multiprocessing doesn't support LSAN and causes false positives
instead. As a result, disabling LSAN for these tests so that we can still run
with opt-asan
ghstack-source-id:
135962489
Test Plan: waitforbuildbot
Reviewed By: rohan-varma
Differential Revision:
D30352269
fbshipit-source-id:
f6ab5abce7bdef00cd5e1f5977424d2b151174af
Wanchao Liang [Wed, 18 Aug 2021 06:10:48 +0000 (23:10 -0700)]
[sharded_tensor] fix typing issue for placement (#63426)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/63426
placement should either be a string or a _remote_device, this fixes the type to match the behaviors
ghstack-source-id:
136041125
Reviewed By: pritamdamania87
Differential Revision:
D30379702
fbshipit-source-id:
34e226494240923b433e3a39cc08c84d42cdad6b
Pavithran Ramachandran [Wed, 18 Aug 2021 05:26:22 +0000 (22:26 -0700)]
[easy][PyTorchEdge] print error message when failing to load model file (#63404)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/63404
# Context
Loading a model file using `fopen` might error out for multiple reasons. Repro'ing the error on devices takes some time and efforts. Logging the error no# will help in debugging and fixing the error quickly.
# Mitigation
Printout the error message of the `fopen` to help users debug the issue.
Test Plan:
```
(base) [pavithran@devvm1803.vll0 /data/users/pavithran/fbsource] buck run xplat/caffe2/fb/lite_predictor:lite_predictor -- --model=/home/pavithran/models/prod/GAaNhAoTIV6cIvgJAHn30m8NR1QgbmQwAAAA.ptl --use_bundled_input=0
Building: finished in 0.5 sec (100%) 354/354 jobs, 0/354 updated
Total time: 0.6 sec
Run with 24 threads
Run with 24 threads
Loading model...
terminate called after throwing an instance of 'c10::Error'
what(): open file failed because of errno 2 on fopen: No such file or directory, file path: /home/pavithran/models/prod/GAaNhAoTIV6cIvgJAHn30m8NR1QgbmQwAAAA.ptl
Exception raised from RAIIFile at xplat/caffe2/caffe2/serialize/file_adapter.cc:15 (most recent call first):
(no backtrace available)
```
Reviewed By: dhruvbird
Differential Revision:
D30372308
fbshipit-source-id:
5346e828f53f6bc5d871b403586566a3332a389a
Jerry Zhang [Wed, 18 Aug 2021 04:35:55 +0000 (21:35 -0700)]
[fx2trt] Add quantize_per_tensor support (#63447)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/63447
Only available in TRT 8.0 and above
Test Plan: buck run mode/opt caffe2/torch/fb/fx2trt:test_quantize_per_tensor
Reviewed By:
842974287
Differential Revision:
D30322844
fbshipit-source-id:
dfd925e3432de128f2925b1aa55d6125e63359af
Shen Li [Wed, 18 Aug 2021 03:12:51 +0000 (20:12 -0700)]
Fix RPC Python User Function Error Handling (#63406)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/63406
The `RemoteException` will be thrown on the caller side when converting
the response message to IValue. Since it is a Python error, the error
message needs to be extracted explicitly and clear the `PyErr`.
Test Plan: Imported from OSS
Reviewed By: rohan-varma, ngimel
Differential Revision:
D30372741
Pulled By: mrshenli
fbshipit-source-id:
1f72a7ee0c39cc2ef070f99884c142f7b3e0543d
Aliaksandr Ivanou [Wed, 18 Aug 2021 02:54:30 +0000 (19:54 -0700)]
[torch] Set default log level for torch elastic (#63214)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/63214
The default log level in fb and oss is different: in oss we use WARNING and in fb we use INFO.
Test Plan: unittests,
f291441502
Reviewed By: cbalioglu
Differential Revision:
D30296298
fbshipit-source-id:
89067352be767255fbc66e790ec333582de64c6c
Rohan Varma [Wed, 18 Aug 2021 00:12:32 +0000 (17:12 -0700)]
[BE] remove _SUPPORTED_OPTIM_MAP from tests (#63383)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/63383
Per title
ghstack-source-id:
135966157
Test Plan: CI
Reviewed By: SciPioneer
Differential Revision:
D30358921
fbshipit-source-id:
965e054e525194b1ee55980340df275bab355c9b
Rohan Varma [Wed, 18 Aug 2021 00:12:32 +0000 (17:12 -0700)]
[DDP] Support step_param for AdamW (#63382)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/63382
Per title
ghstack-source-id:
135966156
Test Plan: CI
Reviewed By: SciPioneer
Differential Revision:
D30255446
fbshipit-source-id:
e6ffbf339db0bc5b4702d02b74a462309df07c75
Jerry Zhang [Tue, 17 Aug 2021 23:54:09 +0000 (16:54 -0700)]
[quant][graphmode][fx][fix] Fix quantization for tuple arguments (#63376)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/63376
Previously when tuple is an argument for a quantizable op it would be transformed to a list by mistake,
this PR fixes that.
Test Plan:
python test/test_quantization.py TestQuantizeFx.test_preserve_tuple
Imported from OSS
Reviewed By: raghuramank100
Differential Revision:
D30357642
fbshipit-source-id:
82d10805d9c00c003cc99983dca68b6455ff7b2e
zhouzhuojie [Tue, 17 Aug 2021 23:53:08 +0000 (16:53 -0700)]
Add more ciflow labels for more workflows (#63410)
Summary:
- Add more ciflow labels and enable it for more workflows.
- Only the 'ciflow/default' workflows are run by default on pull_request time
- Other labels can be manually triggered by (adding the labels + unassign pytorchbot), OR wait for pytorchbot's comment opt-in rollout
- The label design is a logical operator `OR`, i.e. adding ('ciflow/cuda' + 'ciflow/win') will trigger the union of them. (design feedback is needed here)
Typical default workflows for normal PRs.
<details>
<summary>Generated label rules</summary>
```
{
"label_rules": {
"ciflow/all": [
"libtorch-linux-xenial-cuda10.2-py3.6-gcc7",
"libtorch-linux-xenial-cuda11.1-py3.6-gcc7",
"linux-bionic-cuda10.2-py3.9-gcc7",
"linux-bionic-py3.8-gcc9-coverage",
"linux-xenial-cuda10.2-py3.6-gcc7",
"linux-xenial-cuda11.1-py3.6-gcc7",
"linux-xenial-py3.6-gcc5.4",
"linux-xenial-py3.6-gcc7-bazel-test",
"periodic-libtorch-linux-xenial-cuda11.3-py3.6-gcc7",
"periodic-linux-xenial-cuda11.3-py3.6-gcc7",
"periodic-win-vs2019-cuda11.3-py3",
"win-vs2019-cpu-py3",
"win-vs2019-cuda10.1-py3",
"win-vs2019-cuda11.1-py3"
],
"ciflow/bazel": [
"linux-xenial-py3.6-gcc7-bazel-test"
],
"ciflow/coverage": [
"linux-bionic-py3.8-gcc9-coverage"
],
"ciflow/cpu": [
"linux-bionic-py3.8-gcc9-coverage",
"linux-xenial-py3.6-gcc5.4",
"linux-xenial-py3.6-gcc7-bazel-test",
"win-vs2019-cpu-py3"
],
"ciflow/cuda": [
"libtorch-linux-xenial-cuda10.2-py3.6-gcc7",
"libtorch-linux-xenial-cuda11.1-py3.6-gcc7",
"linux-bionic-cuda10.2-py3.9-gcc7",
"linux-xenial-cuda10.2-py3.6-gcc7",
"linux-xenial-cuda11.1-py3.6-gcc7",
"periodic-libtorch-linux-xenial-cuda11.3-py3.6-gcc7",
"periodic-linux-xenial-cuda11.3-py3.6-gcc7",
"periodic-win-vs2019-cuda11.3-py3",
"win-vs2019-cuda10.1-py3",
"win-vs2019-cuda11.1-py3"
],
"ciflow/default": [
"linux-bionic-py3.8-gcc9-coverage",
"linux-xenial-cuda11.1-py3.6-gcc7",
"linux-xenial-py3.6-gcc5.4",
"linux-xenial-py3.6-gcc7-bazel-test",
"win-vs2019-cpu-py3",
"win-vs2019-cuda10.1-py3"
],
"ciflow/libtorch": [
"libtorch-linux-xenial-cuda10.2-py3.6-gcc7",
"libtorch-linux-xenial-cuda11.1-py3.6-gcc7",
"periodic-libtorch-linux-xenial-cuda11.3-py3.6-gcc7"
],
"ciflow/linux": [
"libtorch-linux-xenial-cuda10.2-py3.6-gcc7",
"libtorch-linux-xenial-cuda11.1-py3.6-gcc7",
"linux-bionic-cuda10.2-py3.9-gcc7",
"linux-bionic-py3.8-gcc9-coverage",
"linux-xenial-cuda10.2-py3.6-gcc7",
"linux-xenial-cuda11.1-py3.6-gcc7",
"linux-xenial-py3.6-gcc5.4",
"linux-xenial-py3.6-gcc7-bazel-test",
"periodic-libtorch-linux-xenial-cuda11.3-py3.6-gcc7",
"periodic-linux-xenial-cuda11.3-py3.6-gcc7"
],
"ciflow/scheduled": [
"periodic-libtorch-linux-xenial-cuda11.3-py3.6-gcc7",
"periodic-linux-xenial-cuda11.3-py3.6-gcc7",
"periodic-win-vs2019-cuda11.3-py3"
],
"ciflow/slow": [
"linux-bionic-cuda10.2-py3.9-gcc7",
"linux-xenial-cuda10.2-py3.6-gcc7"
],
"ciflow/win": [
"periodic-win-vs2019-cuda11.3-py3",
"win-vs2019-cpu-py3",
"win-vs2019-cuda10.1-py3",
"win-vs2019-cuda11.1-py3"
]
},
"version": "v1"
}
```
</details>
Pull Request resolved: https://github.com/pytorch/pytorch/pull/63410
Reviewed By: ngimel
Differential Revision:
D30378553
Pulled By: zhouzhuojie
fbshipit-source-id:
4e0953740793e5e72b95018f8ab2ce4a6a364c38
Masaki Kozuki [Tue, 17 Aug 2021 23:51:34 +0000 (16:51 -0700)]
`F.avg_pool3` CUDA backward: gpuAtomicAddNoReturn -> fastAtomicAdd (#63387)
Summary:
Rel: https://github.com/pytorch/pytorch/issues/62695
In the following two tables, I set `kernel_size` to 3 and `stride` to 2.
In benchmark, input tensors have the shape of (N, C, n_features, n_features, n_features).
Tested on RTX3080 w/ CUDA11.4 Update 1.
## This PR
| N | C | n_features | dtype | time |
|----:|----:|-------------:|:--------------|------------:|
| 32 | 3 | 8 | torch.float16 | 7.46846e-05 |
| 32 | 3 | 8 | torch.float32 | 8.18968e-05 |
| 32 | 3 | 32 | torch.float16 | 0.
000156748 |
| 32 | 3 | 32 | torch.float32 | 0.
000165236 |
| 32 | 3 | 128 | torch.float16 | 0.
00549854 |
| 32 | 3 | 128 | torch.float32 | 0.008926 |
## master (6acd87f)
| N | C | n_features | dtype | time |
|----:|----:|-------------:|:--------------|------------:|
| 32 | 3 | 8 | torch.float16 | 7.60436e-05 |
| 32 | 3 | 8 | torch.float32 | 7.55072e-05 |
| 32 | 3 | 32 | torch.float16 | 0.
000189292 |
| 32 | 3 | 32 | torch.float32 | 0.
000168645 |
| 32 | 3 | 128 | torch.float16 | 0.
00699538 |
| 32 | 3 | 128 | torch.float32 | 0.
00890226 |
master's time divided by PR's time is as follows:
| N | C | n_features | master / PR |
|---:|---:|---------------:|----------------:|
| 32 | 3 | 8 | 1.018 |
| 32 | 3 | 32 | 1.208 |
| 32 | 3 | 128 | 1.272|
cc: xwang233 ptrblck ngimel
Pull Request resolved: https://github.com/pytorch/pytorch/pull/63387
Reviewed By: mruberry
Differential Revision:
D30381434
Pulled By: ngimel
fbshipit-source-id:
3b97aee4b0d457a0277a0d31ac56d4151134c099
Nikita Shulga [Tue, 17 Aug 2021 22:28:45 +0000 (15:28 -0700)]
Add pocketfft as submodule (#62841)
Summary:
Using https://github.com/mreineck/pocketfft
Also delete explicit installation of pocketfft during the build as it will be available via submodule
Limit PocketFFT support to cmake-3.10 or newer, as `set_source_files_properties` does not seem to work as expected with cmake-3.5
Partially addresses https://github.com/pytorch/pytorch/issues/62821
Pull Request resolved: https://github.com/pytorch/pytorch/pull/62841
Reviewed By: seemethere
Differential Revision:
D30140441
Pulled By: malfet
fbshipit-source-id:
d1a1cf1b43375321f5ec5b3d0b538f58082f7825
Rohan Varma [Tue, 17 Aug 2021 22:01:21 +0000 (15:01 -0700)]
[wip] Move smallest bucket to end after rebuild buckets (#62279)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/62279
Before rebuild buckets, `kDefaultFirstBucketBytes` is actually misleading because we reverse the parameter indices when initialize reducer so it is actually the size of the last bucket.
Currently rebuild buckets sets this to be the first bucket size, but seeing if keeping it as last can help perf.
This is currently experimental only and don't plan to land it unless experiments show a clear win.
ghstack-source-id:
135966897
Test Plan: CI
Reviewed By: SciPioneer
Differential Revision:
D29927931
fbshipit-source-id:
55b949986fa2c3bade6fcb4bf5b513461bf0f490
Kevin Tse [Tue, 17 Aug 2021 21:46:22 +0000 (14:46 -0700)]
adding a note to the documentation of polar (#63259)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/63259
Fix #52919
Test Plan: Imported from OSS
Reviewed By: anjali411
Differential Revision:
D30342536
Pulled By: NivekT
fbshipit-source-id:
4c61a86f96a6370cc64652bf652c4ae25c9f4601
Jerry Zhang [Tue, 17 Aug 2021 21:40:19 +0000 (14:40 -0700)]
[quant][graphmode][fx][bc-breaking] Support for reference pattern for fixqparam ops in eval mode (#62608)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/62608
Insert extra fixeqparam fake quant in the output of fixed qparam ops in fbgemm e.g. sigmoid
so that we can produce reference patterns for these ops
Test Plan:
python test/test_quantization.py TestQuantizeFx
python test/test_quantization.py TestQuantizeFxOps
Imported from OSS
Reviewed By: iramazanli
Differential Revision:
D30053978
fbshipit-source-id:
c527944b6e791bb4d45ebe96265af52794203695
Dhruv Matani [Tue, 17 Aug 2021 21:39:04 +0000 (14:39 -0700)]
Revert
D30281388: [PyTorch] Avoid using std::regex for device string parsing in Device.cpp
Test Plan: revert-hammer
Differential Revision:
D30281388 (https://github.com/pytorch/pytorch/commit/
4d6f98ecada2d85b2474b023838debad4305316d)
Original commit changeset:
4d998e9f313e
fbshipit-source-id:
11134b3400cc3e851155c9c1b6fb59308ff1567b
Richard Zou [Tue, 17 Aug 2021 20:39:52 +0000 (13:39 -0700)]
Fix zero-dim handling in torch.matmul (#63359)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/63359
Fixes #63352. The problem was that in e.g. `torch.matmul(A, B)` with A,
B having shapes [3, 2, 0] and [0, 2], the code attempts to call
`A.view(-1, 0)` which fails due to "-1 being ambiguous". The solution is
to manually compute what we want the shape of the view to be.
Test Plan: - new tests
Reviewed By: ngimel
Differential Revision:
D30351583
Pulled By: zou3519
fbshipit-source-id:
7625691fe8b85d96a4073409596a932c303e3e8c
Mikhail Zolotukhin [Tue, 17 Aug 2021 20:39:36 +0000 (13:39 -0700)]
[TensorExpr] Add a wrapper for all expr and stmt pointers. (#63195)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/63195
This helps us to later switch from using KernelArena with raw pointers
to shared pointers without having to change all our source files at
once.
The changes are mechanical and should not affect any functionality.
With this PR, we're changing the following:
* `Add*` --> `AddPtr`
* `new Add(...)` --> `alloc<Add>(...)`
* `dynamic_cast<Add*>` --> `to<Add>`
* `static_cast<Add*>` --> `static_to<Add>`
Due to some complications with args forwarding, some places became more
verbose, e.g.:
* `new Block({})` --> `new Block(std::vector<ExprPtr>())`
Test Plan: Imported from OSS
Reviewed By: navahgar
Differential Revision:
D30292779
Pulled By: ZolotukhinM
fbshipit-source-id:
150301c7d2df56b608b035827b6a9a87f5e2d9e9
Kushashwa Ravi Shrimali [Tue, 17 Aug 2021 20:35:32 +0000 (13:35 -0700)]
OpInfo fix: `conv_transpose2d` (#63389)
Summary:
Addresses comment: https://github.com/pytorch/pytorch/pull/62882#issuecomment-
899679606.
cc: mruberry ngimel
Pull Request resolved: https://github.com/pytorch/pytorch/pull/63389
Reviewed By: mruberry
Differential Revision:
D30377481
Pulled By: ngimel
fbshipit-source-id:
0fa21acc3503c259c9b27463e8555247c43d9e2e
Mike Iovine [Tue, 17 Aug 2021 20:34:44 +0000 (13:34 -0700)]
[Static Runtime] Implement aten::append (#63350)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/63350
Add a native implementation for `aten::append`, the list append op.
Test Plan: New unit test: `buck test caffe2/benchmarks/static_runtime:static_runtime_cpptest -- Append`
Reviewed By: hlu1
Differential Revision:
D30326461
fbshipit-source-id:
0dbdf6cc82e78c7c36db39583256f6b87385e3d3
projects / platform / upstream / pytorch.git / log