Jerry Zhang [Sat, 18 Sep 2021 19:49:07 +0000 (12:49 -0700)]
[quant][fx2trt] Generate engine graph for explicit quant/implicit quant and fp16 graph (#65289)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/65289
Turn on VERBOSE logging and use engine visualizer to generate the graph.
Runtime:
```
explicit quant result diff max tensor(0.0771)
implicit quant result diff max tensor(0.1909)
trt fp16 time (ms/iter) 1.
0740923881530762
trt int8 time (ms/iter) 0.
5288887023925781
trt implicit int8 time (ms/iter) 0.
6334662437438965
PyTorch time (CUDA) (ms/iter) 4.
448361396789551
PyTorch time (CPU) (ms/iter) 45.
13296604156494
```
Generated Graphs:
```
explicit int8: https://www.internalfb.com/intern/graphviz/?paste=P458669571
implicit int8: https://www.internalfb.com/intern/graphviz/?paste=P458669656
fp16: https://www.internalfb.com/intern/graphviz/?paste=P458669708
```
Test Plan:
```
buck run mode/opt -c python.package_style=inplace caffe2:fx2trt_quantized_resnet_test 2>log
buck run //deeplearning/trt/fx2trt/tools:engine_layer_visualize -- --log_file log
```
Reviewed By:
842974287
Differential Revision:
D30955035
fbshipit-source-id:
24949458ad9823fb026d56d78a6ee1c6874b6034
Don Jang [Sat, 18 Sep 2021 18:03:17 +0000 (11:03 -0700)]
[Static Runtime] Add perf metrics for number of managed tensors & unmanaged values (#64992)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/64992
This change lets Static Runtime print out number of managed tensors & unmanaged values as performance metrics during profile runs.
We will use /enhance these metrics to guide the effort of managing output tensors.
Test Plan:
Confirmed that a profile run prints out the added metric values on inline_cvr nets:
```
(inline_cvr/local)
...
Total number of managed tensors: 2754
Total number of unmanaged values: 3240
...
(inline_cvr/local_ro)
Total number of managed tensors: 1554
Total number of unmanaged values: 2966
...
(inline_cvr/remote_ro)
Total number of managed tensors: 1439
Total number of unmanaged values: 28
...
```
Reviewed By: hlu1
Differential Revision:
D30926617
fbshipit-source-id:
b86e071003ac941b9663db103eaa7c614466b4e0
Saketh Are [Sat, 18 Sep 2021 16:56:42 +0000 (09:56 -0700)]
Remove incorrect stride assert in Reduce.cuh (#65227)
Summary:
Fixes https://github.com/pytorch/pytorch/issues/37583
Per discussion with ngimel, the condition asserted here may not always hold after TensorIterator's dimension coalescing and reordering. However, the reduction output should still be correct when `sub_iter.strides(0)[0]` is non-zero.
I've verified correctness empirically by:
1. Lowering the threshold ([configured here](https://github.com/pytorch/pytorch/blob/master/aten/src/ATen/TensorIterator.cpp#L1127)) at which iterators are split into sub-iterators, making it easier to trigger.
2. Generating many tensors with random dimensions and randint elements which produce a non-zero `sub_iter.strides(0)[0]` in the CUDA kernel.
3. Verifying that the reduction `t.sum(dim=0)` produces the same results for those tensors on CPU and on CUDA.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/65227
Reviewed By: ngimel
Differential Revision:
D31031406
Pulled By: saketh-are
fbshipit-source-id:
5cbf2001224454c74f6db42455c507365ad1f2b1
Michael Dagitses [Sat, 18 Sep 2021 13:47:20 +0000 (06:47 -0700)]
support using gradients named for outputs in derivatives (#63947)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/63947
Fixes #62196
Test Plan: Imported from OSS
Reviewed By: albanD
Differential Revision:
D30541485
Pulled By: dagitses
fbshipit-source-id:
ea1dd0edd1a51936a295631e52b85e9c022a9c87
Michael Dagitses [Sat, 18 Sep 2021 13:47:20 +0000 (06:47 -0700)]
clarify implementation of check_grad_usage (#64439)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/64439
1) remove unused fully_implemented
2) rename used_grad to uses_grad and make it a boolean
3) rename used_grads to num_grads_uses
4) add comments explaining what some of the checks mean
Test Plan: Imported from OSS
Reviewed By: albanD
Differential Revision:
D30733904
Pulled By: dagitses
fbshipit-source-id:
dccbbef8a4be8713215ef91aa97a34124f06a7a1
Jerry Zhang [Sat, 18 Sep 2021 06:23:29 +0000 (23:23 -0700)]
[quant][fx2trt] Enable comparison with implicit quant mode (#65043)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/65043
Currently got following result, will take a look at the executed graph again:
```
trt fp16 time (ms/iter) 1.
0483217239379883
trt int8 time (ms/iter) 0.
5329632759094238
trt implicit int8 time (ms/iter) 0.
6769704818725586
PyTorch time (ms/iter) 6.
453146934509277
```
Test Plan:
```
python torch/fx/experimental/fx2trt/example/quantized_resnet_test.py
```
Imported from OSS
Reviewed By:
842974287
Differential Revision:
D30954871
fbshipit-source-id:
8d7ff82b8f5d0b7946fbd38a7cddede7d40b28aa
CodemodService Bot [Sat, 18 Sep 2021 02:45:14 +0000 (19:45 -0700)]
[Codemod][FBSourceBlackLinter] Daily `arc lint --take BLACK`
Reviewed By: zertosh
Differential Revision:
D31039372
fbshipit-source-id:
a5e54a9b1d2ef97e9bc206b9e2a82124e5a22a7a
Jane Xu [Sat, 18 Sep 2021 00:27:49 +0000 (17:27 -0700)]
Remove 9.2 related macros for CONSTEXPR (#65066)
Summary:
Removes C10_HOST_CONSTEXPR_EXCEPT_CUDA92 references in the code
Pull Request resolved: https://github.com/pytorch/pytorch/pull/65066
Reviewed By: driazati
Differential Revision:
D31022520
Pulled By: janeyx99
fbshipit-source-id:
f02cdc6caba5b48405575242921f5845ff18f729
zhouzhuojie [Sat, 18 Sep 2021 00:15:36 +0000 (17:15 -0700)]
Make github.com in noproxy list (#65256)
Summary:
Fixes #{issue number}
Attempt to solve some ratelimiting issue we saw from calling GitHub apis
Pull Request resolved: https://github.com/pytorch/pytorch/pull/65256
Reviewed By: seemethere
Differential Revision:
D31035115
Pulled By: zhouzhuojie
fbshipit-source-id:
7efd5d5af7d91805e4bf27b86847791e991b741e
Natalia Gimelshein [Sat, 18 Sep 2021 00:04:34 +0000 (17:04 -0700)]
remove utils.cpp (#65184)
Summary:
Dead code
Pull Request resolved: https://github.com/pytorch/pytorch/pull/65184
Reviewed By: mruberry
Differential Revision:
D31031777
Pulled By: ngimel
fbshipit-source-id:
13633888229a7af8cfd8ea7e55ea2880b2e47273
Shiyan Deng [Fri, 17 Sep 2021 23:32:23 +0000 (16:32 -0700)]
[fx const fold] fix a case when some inputs are unused (#65223)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/65223
If there're unused inputs, they won't appear in `submod_1`. We need to add all the unused inputs so that the model after const fold has the same inputs as the original model.
Reviewed By: jfix71
Differential Revision:
D31021217
fbshipit-source-id:
b7452c90d133b747e0699936a81d3fee14af9cc9
Gisle Dankel [Fri, 17 Sep 2021 23:08:03 +0000 (16:08 -0700)]
[Profiler] Update kineto submodule (#65236)
Summary:
Update to latest kineto revision. See Kineto repo for change log.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/65236
Reviewed By: malfet
Differential Revision:
D31031638
Pulled By: gdankel
fbshipit-source-id:
681655b2e8e151895afa91445ced0fd57a11fa93
Shiyan Deng [Fri, 17 Sep 2021 22:42:57 +0000 (15:42 -0700)]
[fx2trt] re-enable profiler and some miscs for TRTModule (#65072)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/65072
Previously disabled attaching trt profiler to exec context in TRTModule because https://fburl.com/mc33n880 states that `enqueue()` doesn't support profiling. Seems to be a lie though. Re-enable attaching profiler in this diff.
Also added a bunch of checks for dtype and shape, and fixed saving state_dict and loading back.
Test Plan: buck run mode/opt -c python.package_style=inplace -j 40 deeplearning/trt/fx2trt:acc2trt_test
Reviewed By: yinghai
Differential Revision:
D30962757
fbshipit-source-id:
9c664b0500a8169b7952f6f912239a5a05772aea
Michael Suo [Fri, 17 Sep 2021 22:37:26 +0000 (15:37 -0700)]
[package] Make it possible to re-save a PackageImporter module (#65101)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/65101
As title. Previously this was guarded against for implementation
simplicity, as we didn't really think there was a use case for saving a
mangled module name directly.
But people started doing stuff like:
```
exporter.save_module(my_imported_obj.__module__)
```
which implicitly passes along the mangled module name.
This PR makes it so that given `PackageImporter` instance can always
import modules that it created, and changes `PackageExporter` to
properly demangle the resulting module name when writing the package to
the export archive.
Differential Revision:
D30975712
D30975712
Test Plan: Imported from OSS
Pulled By: suo
fbshipit-source-id:
d9e849bf651713890e72dccdcef74fa52d377149
Jason Ansel [Fri, 17 Sep 2021 21:28:38 +0000 (14:28 -0700)]
[FX] Fix tracing of bitwise and/or (#65196)
Summary:
Previously resulted in `AttributeError: module 'operator' has no attribute 'and'`
and/or are python keywords, so they are renamed to `operator.and_` and `operator.or_`
Pull Request resolved: https://github.com/pytorch/pytorch/pull/65196
Reviewed By: Chillee
Differential Revision:
D31020336
Pulled By: jansel
fbshipit-source-id:
51d888151fe78c0c1197ecaf161976b219c59694
Mike Ruberry [Fri, 17 Sep 2021 21:23:25 +0000 (14:23 -0700)]
Revert
D30731191: [pytorch][PR] Torchhub: rewrite commit hash check to avoid using unnecessary GitHub API credits
Test Plan: revert-hammer
Differential Revision:
D30731191 (https://github.com/pytorch/pytorch/commit/
f9bf144a0c5e3627f5fafb256cebf1f02152ab0c)
Original commit changeset:
d1ee7c2ef259
fbshipit-source-id:
5c7207f66c5354ce7b9ac2594e4f5b8307619b0c
BowenBao [Fri, 17 Sep 2021 21:11:27 +0000 (14:11 -0700)]
[ONNX] Deprecate enable_onnx_checker argument in torch.onnx.export() (#61708) (#64369)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/64369
As of now, the "enable_onnx_checker" parameter was described as below:
enable_onnx_checker (bool, default True): If True the ONNX model checker will be run to ensure the exported model is a valid ONNX model.
An invalid ONNX graph is useless to users so such checker should be done for each call.
In this PR, we will still write the model to an ONNX file even it is invalid. And the exception will be thrown after the ONNX file has been created. This enables user output an invalid ONNX graph for debug.
This PR will still keep it in torch.onnx.export() function for backward support while all backend logic has been changed to work as enable_onnx_checker is set to True.
Test Plan: Imported from OSS
Reviewed By: ezyang
Differential Revision:
D30905267
Pulled By: malfet
fbshipit-source-id:
3ad3f68e77fcec012cc7ef674cc9a61755eebc9e
Co-authored-by: fatcat-z <zhang-ji@outlook.com>
Don Jang [Fri, 17 Sep 2021 20:20:33 +0000 (13:20 -0700)]
[Static Runtime] Move MemoryPlanner out into memory_planner.cpp (#65123)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/65123
This change re-reverts
D30883290 (https://github.com/pytorch/pytorch/commit/
0e11454d19e106ba6d5819c1147ca540cbce2943).
D30883290 (https://github.com/pytorch/pytorch/commit/
0e11454d19e106ba6d5819c1147ca540cbce2943) broke the OSS build since the change in this change implicitly removed the default move constructor of `StaticRuntime`.
```
ep 15 15:39:57 /var/lib/jenkins/workspace/benchmarks/static_runtime/deep_wide_pt_bench.cc:95:10: error: call to implicitly-deleted copy constructor of 'torch::jit::StaticRuntime'
Sep 15 15:39:57 return torch::jit::StaticRuntime(*smod);
Sep 15 15:39:57 ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Sep 15 15:39:57 /var/lib/jenkins/workspace/torch/csrc/jit/runtime/static/impl.h:321:34: note: copy constructor of 'StaticRuntime' is implicitly deleted because field 'planner_' has a deleted copy constructor
Sep 15 15:39:57 std::unique_ptr<MemoryPlanner> planner_;
Sep 15 15:39:57 ^
Sep 15 15:39:57 /usr/bin/../lib/gcc/x86_64-linux-gnu/5.4.0/../../../../include/c++/5.4.0/bits/unique_ptr.h:356:7: note: 'unique_ptr' has been explicitly marked deleted here
Sep 15 15:39:57 unique_ptr(const unique_ptr&) = delete;
Sep 15 15:39:57 ^
Sep 15 15:39:57 /var/lib/jenkins/workspace/benchmarks/static_runtime/deep_wide_pt_bench.cc:99:9: error: call to implicitly-deleted copy constructor of 'torch::jit::StaticRuntime'
Sep 15 15:39:57 auto sr = getStaticRuntime();
Sep 15 15:39:57 ^ ~~~~~~~~~~~~~~~~~~
Sep 15 15:39:57 /var/lib/jenkins/workspace/torch/csrc/jit/runtime/static/impl.h:321:34: note: copy constructor of 'StaticRuntime' is implicitly deleted because field 'planner_' has a deleted copy constructor
Sep 15 15:39:57 std::unique_ptr<MemoryPlanner> planner_;
Sep 15 15:39:57 ^
Sep 15 15:39:57 /usr/bin/../lib/gcc/x86_64-linux-gnu/5.4.0/../../../../include/c++/5.4.0/bits/unique_ptr.h:356:7: note: 'unique_ptr' has been explicitly marked deleted here
Sep 15 15:39:57 unique_ptr(const unique_ptr&) = delete;
Sep 15 15:39:57 ^
Sep 15 15:39:57 2 errors generated.
```
This change fixes the issue by explicitly defining the default move constructor (courtesy of mikeiovine).
Original Summary:
This change moves `MemoryPlanner` out of impl.cpp into memory_planner.cpp.
`MemoryPlanner` performs an independent sub-task of static analysis of a graph, and creating memory planning, and allocating/deallocating managed Tensors.
This change will reduce merge conflicts as I work on MemoryPlanner more actively for output Tensor support.
Test Plan: - Confirm that OSS build went well (See External Tests section).
Reviewed By: mikeiovine
Differential Revision:
D30983292
fbshipit-source-id:
a59f407fa1123527824157268111144a1bf58116
Mengwei Liu [Fri, 17 Sep 2021 19:57:48 +0000 (12:57 -0700)]
[PyTorch] Extract parseOperator() into a standalone source file (#65179)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/65179
This is following up this PR: https://github.com/pytorch/pytorch/pull/61862. The purpose is to modularize operator parsing so that it can be used as needed without pulling the whole `import.cpp` into build.
Test Plan: Added a unit test in `test_lite_predictor.cpp` called `ParseOperators`, similar to `ParseBytecode`.
Reviewed By: iseeyuan
Differential Revision:
D31006555
fbshipit-source-id:
c38e221800af4cf72963a353c452c5437f56a0ac
Scott Wolchok [Fri, 17 Sep 2021 19:55:47 +0000 (12:55 -0700)]
[PyTorch] Improve OperatorEntry::getKernelForDispatchKey (#64838)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/64838
The returned pointer, if present, could never be nullptr, so there is no reason to wrap it in an optional rather than just using the nullptr state. The repeated calls to kernels_.at() were not getting optimized away, so just use the perfectly good iterator find() already gave us.
ghstack-source-id:
138304429
Test Plan: CI
Reviewed By: bdhirsh
Differential Revision:
D30875748
fbshipit-source-id:
9cbb875715b7a582380c7402155fdbe21944dc85
Scott Wolchok [Fri, 17 Sep 2021 19:55:47 +0000 (12:55 -0700)]
avoid moving Argument in infer_schema (#64822)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/64822
Turns out the suppressed lint message was trying to tell us something: we can construct our Argument in-place rather than create a temporary and move into the argument vector.
ghstack-source-id:
138304423
Test Plan: CI, profile op registration and observe reduced Argument move ctor and dtor costs
Reviewed By: smessmer
Differential Revision:
D30860718
fbshipit-source-id:
c8da45ab7e61b5df9fa1273301896309bca108b5
Scott Wolchok [Fri, 17 Sep 2021 19:55:47 +0000 (12:55 -0700)]
[PyTorch] Fix missing move in Argument ctor (#64821)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/64821
Not moving adds excess refcounting overhead.
ghstack-source-id:
138304432
Test Plan: CI
Reviewed By: dhruvbird
Differential Revision:
D30860720
fbshipit-source-id:
de695e5cdfb1fa314b53a8bcb291343ae4eb87a5
Scott Wolchok [Fri, 17 Sep 2021 19:55:47 +0000 (12:55 -0700)]
[PyTorch] shrink Argument (#64820)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/64820
Putting boolean fields next to each other avoids wasting space for padding.
ghstack-source-id:
138304433
Test Plan: CI
Reviewed By: dhruvbird
Differential Revision:
D30860717
fbshipit-source-id:
ad45c37574a7c857958978aad42fd1333c6b29ee
Scott Wolchok [Fri, 17 Sep 2021 19:55:47 +0000 (12:55 -0700)]
[PyTorch] Compare pointers before calling expensive Type comparison (#64784)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/64784
See code comment for explanation.
ghstack-source-id:
138304431
Test Plan: Reduced overhead in findSchemaDifferences while profiling registration at startup in a case where I forced duplicates to be registered (by looping in RegisterDispatchKey.cpp).
Reviewed By: dhruvbird
Differential Revision:
D30854036
fbshipit-source-id:
568733c3cf449697cdeb74cf57fed0926729fa68
Jane Xu [Fri, 17 Sep 2021 19:32:11 +0000 (12:32 -0700)]
CI: Consolidate Build and Test naming for better stats collection (#65232)
Summary:
All build pytorch steps should now be named "Build" and test steps named "Test" for workflows that test PyTorch on Linux and Windows.
I left the binary stuff alone as that build is different.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/65232
Reviewed By: driazati, seemethere
Differential Revision:
D31024232
Pulled By: janeyx99
fbshipit-source-id:
24b1a1e2b1b25aba70b7adc41603ec8fa4ce7dd6
Rohan Varma [Fri, 17 Sep 2021 19:23:09 +0000 (12:23 -0700)]
Back out "Revert
D30745960: [DDP] Remove SPMD from self.modules_buffers" (#64778)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/64778
Original commit changeset:
d3f3fb813c45
ghstack-source-id:
138326910
Test Plan: ci
Reviewed By: H-Huang
Differential Revision:
D30849443
fbshipit-source-id:
15dab8a959a29d2e2fefac6ad52b8d8168eacc02
Rohan Varma [Fri, 17 Sep 2021 19:23:09 +0000 (12:23 -0700)]
Back out "Revert
D30745961: [DDP] Remove self.modules_params" (#64777)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/64777
Original commit changeset:
59f7cc50d369
ghstack-source-id:
138326909
Test Plan: ci
Reviewed By: H-Huang
Differential Revision:
D30849442
fbshipit-source-id:
bb87ba83935374d8a3ebbc29365df1417dd4f26f
Rohan Varma [Fri, 17 Sep 2021 19:23:09 +0000 (12:23 -0700)]
Back out "Revert
D30745921: [DDP] Fix when buffers are reassigned in module" (#64776)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/64776
Original commit changeset:
343ead86bf1e
ghstack-source-id:
138326914
Test Plan: ci
Reviewed By: H-Huang
Differential Revision:
D30849444
fbshipit-source-id:
9a72805416fe7d6c68e51bdcdb88f6e1fecb614d
Sangbaek Park [Fri, 17 Sep 2021 19:16:10 +0000 (12:16 -0700)]
[xplat][pytorch]: Disabling too many logging. (#65170)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/65170
Disabling too many logging. These are per frame logging
and outputting lots of logs in Skylight command line.
Test Plan:
```
cd ~/fbsource
buck 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"
cd -
```
Reviewed By: SS-JIA
Differential Revision:
D30778852
fbshipit-source-id:
bcf75ec417dfe3e9ce3df92a1894352772bd663d
Michael Dagitses [Fri, 17 Sep 2021 19:07:19 +0000 (12:07 -0700)]
delegate parallelism to Ninja when possible (#64733)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/64733
The previous implementation was wrong when CPU scheduling affinity is
set. In fact, it is still wrong if Ninja is not being used.
When there is CPU scheduling affinity set, the number of processors
available on the system likely exceeds the number of processors that
are usable to the build. We ought to use
`len(os.sched_getaffinity(0))` to determine the effective parallelism.
This change is more minimal and instead just delegates to Ninja (which
handles this correctly) when it is used.
Test Plan:
I verified this worked as correctly using Ninja on a 96-core machine
with 24 cores available for scheduling by checking:
* the cmake command did not specify "-j"
* the number of top-level jobs in top/pstree never exceeded 26 (24 +
2)
And I verified we get the legacy behavior by specifying USE_NINJA=0 on
the build.
Reviewed By: jbschlosser, driazati
Differential Revision:
D30968796
Pulled By: dagitses
fbshipit-source-id:
29547dd378fea793957bcc2f7d52d5def1ecace2
Michael Dagitses [Fri, 17 Sep 2021 19:07:19 +0000 (12:07 -0700)]
add test for number of jobs when building (#65162)
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/65162
Test Plan: Imported from OSS
Reviewed By: driazati
Differential Revision:
D30998006
Pulled By: dagitses
fbshipit-source-id:
8b8d45668acf0e6c0f16df0f705a1af8c6d4f22d
Jane Xu [Fri, 17 Sep 2021 18:45:11 +0000 (11:45 -0700)]
Remove CUDA 9.2 references conditionals and workarounds (#65070)
Summary:
Title says it all
Pull Request resolved: https://github.com/pytorch/pytorch/pull/65070
Reviewed By: malfet
Differential Revision:
D30966464
Pulled By: janeyx99
fbshipit-source-id:
e454906fd5d7d321d390939ba5d237e1d9b150f8
edward-io [Fri, 17 Sep 2021 18:34:36 +0000 (11:34 -0700)]
fix torch.distributed.elastic event docs (#64974)
Summary:
the example code wasn't working for me.
cc pietern mrshenli pritamdamania87 zhaojuanmao satgera rohan-varma gqchen aazzolini osalpekar jiayisuse SciPioneer H-Huang cbalioglu gcramer23
Pull Request resolved: https://github.com/pytorch/pytorch/pull/64974
Reviewed By: kiukchung, cbalioglu
Differential Revision:
D30926481
Pulled By: edward-io
fbshipit-source-id:
f5e32cc2b948b6ee30d84a8247856f39fc786f67
Raghavan Raman [Fri, 17 Sep 2021 17:50:43 +0000 (10:50 -0700)]
[nnc] Updated inlining to handle cases when producer indices are constants after eval (#65044)
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/65044
Test Plan: Imported from OSS
Reviewed By: ZolotukhinM
Differential Revision:
D30954655
Pulled By: navahgar
fbshipit-source-id:
dfaedb5af710b2625ceec3a443a6c4e34158ab16
Raghavan Raman [Fri, 17 Sep 2021 17:50:43 +0000 (10:50 -0700)]
[nnc] Updated inliner to remove assertions and exception (#64719)
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/64719
Test Plan: Imported from OSS
Reviewed By: ZolotukhinM
Differential Revision:
D30828583
Pulled By: navahgar
fbshipit-source-id:
9826a59085a210e44d101a843ff2cae440dfd633
Nikita Shulga [Fri, 17 Sep 2021 17:32:26 +0000 (10:32 -0700)]
[ONNX] Do not use `numpy` in ONNX opsets (#65188)
Summary:
Replace `torch.tensor([numpy.arange(a, b, c)])` with `torch.arange(a, b, c).unsqueeze(0)`
Replace `tuple(numpy.add(a, b))` with `tuple( x + y for (x, y) in zip(a, b)`
As `numpy` is an optional dependency, it shouldn't be used in PyTorch core by default
Pull Request resolved: https://github.com/pytorch/pytorch/pull/65188
Reviewed By: mruberry
Differential Revision:
D31009490
Pulled By: malfet
fbshipit-source-id:
528e48f055bf9ac1de1fd7e94c0be41915df9a0b
Tao Xu [Fri, 17 Sep 2021 17:31:18 +0000 (10:31 -0700)]
[CoreML][OSS] Include Core ML in iOS/MacOS nightlies (#65075)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/65075
Need to drop one line at - https://github.com/pytorch/builder/blob/master/conda/pytorch-nightly/meta.yaml#L65
ghstack-source-id:
138324213
Test Plan:
- Check the iOS nightly builds
- `pod install LibTorch-Lite-Nightly`
Reviewed By: hanton
Differential Revision:
D30912269
fbshipit-source-id:
b07679b75ecf89beae2975c37cf17d2449a3304f
Shiyan Deng [Fri, 17 Sep 2021 17:24:11 +0000 (10:24 -0700)]
add a test case for const fold (#65224)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/65224
Add a test case for the fix
D30996277 (https://github.com/pytorch/pytorch/commit/
8c38d141df429459ea6891847950ce157ac82b2c).
Test Plan: buck test mode/opt -c python.package_style=inplace -c fbcode.nvcc_arch=v100,a100 -c fbcode.enable_gpu_sections=true -j 40 caffe2/test:fx_const_fold -- test_const_fold_module_attr
Reviewed By: jfix71
Differential Revision:
D31000386
fbshipit-source-id:
f444361839decc583bf93ac946cfe2049376719e
Pavithran Ramachandran [Fri, 17 Sep 2021 17:22:41 +0000 (10:22 -0700)]
[PyTorchEdge] promote prim ops by using ops table for mobile runtime (#64816)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/64816
## Context:
Promoting prim ops:
Certain prim ops are frequent than others (like tupleIndex, raiseException, ...). These ops are frequent that they are chosen to be promoted as first class instructions. To promote it requires multiple steps and support from TS team as it changes how the bytecode is serialized and deserialized. So to prevent multiple bytecode version bumps and provided stability while these changes happen, an iterim iterative process is proposed which uses a table to lookup for "promoted" op's function. This allows us to rapidly update the ops list and test on production model without having to change the bytecode. In case of failure, we can quickly revert this change.
## Observation
The ops are chosen based on the notebook N1135657 which examines the top frequent ops.
## Fix
An iterim solution of having a static table, which when given a prim op name returns a function to be applied on the stack. This helps us check in `function.cpp` to get the "promoted" op. As a fall back, the "promoted" op still resides in `register_prim_ops.cpp` so that the function of prim op is never missed.
ghstack-source-id:
138261338
Test Plan:
```
[pavithran@67109.od ~/fbsource/fbcode (
eddab7da6)]$ buck test caffe2/test/cpp/jit:jit -- BackendTest.TestComposite
Building: finished in 5.4 sec (100%) 7284/7284 jobs, 0/7284 updated
Total time: 5.8 sec
More details at https://www.internalfb.com/intern/buck/build/
480191aa-a1ba-42ca-99e9-
ee4bf2b06d65
Tpx test run coordinator for Facebook. See https://fburl.com/tpx for details.
Running with tpx session id:
867382eb-327f-43d7-a45c-
875b7f484b15
Trace available for this run at /tmp/tpx-
20210914-100224.283682/trace.log
Started reporting to test run: https://www.internalfb.com/intern/testinfra/testrun/
844425134506115
✓ ListingSuccess: caffe2/test/cpp/jit:jit - main (12.159)
✓ Pass: caffe2/test/cpp/jit:jit - BackendTest.TestCompositeWithSetStates (0.797)
✓ Pass: caffe2/test/cpp/jit:jit - BackendTest.TestComposite (0.779)
Summary
Pass: 2
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/
844425134506115
```
{
F663491347}
Reviewed By: iseeyuan
Differential Revision:
D30819926
fbshipit-source-id:
4cbe05d5761bdc9d62ef08e18172dcf64cb49526
Michael Suo [Fri, 17 Sep 2021 17:21:43 +0000 (10:21 -0700)]
Revert
D30993855: [pytorch][PR] OpInfo: nn.functional.conv2d
Test Plan: revert-hammer
Differential Revision:
D30993855 (https://github.com/pytorch/pytorch/commit/
873255c6d95342d144e9d1b633c16410844b934e)
Original commit changeset:
7402f99addb4
fbshipit-source-id:
b0539daa195dc6a3739bce5c264cb2177b7721ff
Tao Xu [Fri, 17 Sep 2021 17:14:40 +0000 (10:14 -0700)]
[CoreML][OSS] Integrate with CMake (#64523)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/64523
- Build Pytorch with CoreML delegate - ` USE_PYTORCH_METAL=ON python setup.py install --cmake`
- Build iOS static libs - `IOS_PLATFORM=SIMULATOR USE_COREML_DELEGATE=1 ./scripts/build_ios.sh`
ghstack-source-id:
138324216
Test Plan:
- Test the Helloword example
{
F657778559}
Reviewed By: iseeyuan
Differential Revision:
D30594041
fbshipit-source-id:
8cece0b2d4b3ef82d3ef4da8c1054919148beb16
Yi Wang [Fri, 17 Sep 2021 17:00:13 +0000 (10:00 -0700)]
[Reland] [Model Averaging] Simplify PostLocalSGD Optimizer API (#65197)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/65197
1. The constructor accepts a local optimizer instance instead of the inputs of local optimizer constructor and the class type.
2. The parameters are read from local optimizer's param_groups instead of a separate input.
Proposal: https://github.com/pytorch/pytorch/issues/59699
ghstack-source-id:
138307226
Test Plan: buck test mode/dev-nosan //caffe2/test/distributed:distributed_nccl_spawn -- test_post_localSGD_optimizer_parity
Reviewed By: rohan-varma
Differential Revision:
D31007439
fbshipit-source-id:
bbb0526e6763ef76775b85088571506b3942c722
haozhe.zhu [Fri, 17 Sep 2021 16:52:47 +0000 (09:52 -0700)]
Bf16 matmul (#64619)
Summary:
Re-create PR to fix https://github.com/pytorch/pytorch/pull/61891.
Drop the support for addbmm.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/64619
Reviewed By: jbschlosser
Differential Revision:
D30902995
Pulled By: VitalyFedyunin
fbshipit-source-id:
dc318d73adff8f6974c9752d0d097e69276f8206
Nicolas Hug [Fri, 17 Sep 2021 16:49:46 +0000 (09:49 -0700)]
Torchhub: rewrite commit hash check to avoid using unnecessary GitHub API credits (#64362)
Summary:
This PR adds more detailed error messages to torchhub if the commit hash validation goes wrong, providing suggestions to the users on how to resolve the issue.
It also documents why such validation is important.
EDIT: it also avoids validatating some stuff when we know "stuff" isn't a commit since there's no risk in this case
CC malfet mthrok
cc nairbv NicolasHug
Pull Request resolved: https://github.com/pytorch/pytorch/pull/64362
Reviewed By: gchanan, malfet
Differential Revision:
D30731191
Pulled By: NicolasHug
fbshipit-source-id:
d1ee7c2ef2591dd7a5291977af1635ada2552d1b
James Reed [Fri, 17 Sep 2021 16:26:37 +0000 (09:26 -0700)]
[FX] Ensure BC coverage for all of torch.fx.passes (#65081)
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/65081
Test Plan: Imported from OSS
Reviewed By: jbschlosser, khabinov
Differential Revision:
D30967428
Pulled By: jamesr66a
fbshipit-source-id:
2ff83da728dc469f086cf504e71b43396db612d8
James Reed [Fri, 17 Sep 2021 16:26:37 +0000 (09:26 -0700)]
[FX] Move graph_manipulation and param_fetch out of experimental and into passes (#65183)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/65183
ghstack-source-id:
138309655
Test Plan: waitforsadcastle
Reviewed By: protonu
Differential Revision:
D31007630
fbshipit-source-id:
77d14b284737aabbe2b9e6394177a0c2e40aafba
Shiyan Deng [Fri, 17 Sep 2021 16:23:05 +0000 (09:23 -0700)]
[fx2trt] make gpu trace better (#65168)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/65168
Add record_function to TRTModule and EngineHolder so each parts would appear on gpu trace.
Test Plan: CI
Reviewed By: wushirong
Differential Revision:
D30997968
fbshipit-source-id:
b90662f20a8c0d321846c222f3e8c8eb7e010eba
Tao Xu [Fri, 17 Sep 2021 16:16:39 +0000 (09:16 -0700)]
[CoreML][iOS/MacOS] Add the CoreML executor (#64522)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/64522
The `PTMCoreMLExecutor` serves as a bridge between the delegate APIs and Core ML runtime.
ghstack-source-id:
138324217
allow-large-files
Test Plan:
iOS:
Run the CoreML tests in the playground app
MacOS:
```
buck test pp-macos
PASS 633ms 1 Passed 0 Skipped 0 Failed CoreMLTests
```
{
F657776101}
Reviewed By: raziel, iseeyuan
Differential Revision:
D30594042
fbshipit-source-id:
a42a5307a24c2f364333829f3a84f7b9a51e1b3e
Elias Ellison [Fri, 17 Sep 2021 15:32:05 +0000 (08:32 -0700)]
Allow extra unused arguments in symbolic shape function (#65095)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/65095
The reason I didn't do this initially was because I was worried that matching one schema to another schema with an extra argument might change semantics, e.g. Add(Tensor, Tensor) to Add(Tensor, Tensor, Tensor) might be different. However we don't actually need to worry about this because the graph schema isn't used for node matching, unlike symbolic_script.cpp
Test Plan: Imported from OSS
Reviewed By: navahgar
Differential Revision:
D30972081
Pulled By: eellison
fbshipit-source-id:
d4089e8feafc330df2ca158866fe779a7da0b073
albanD [Fri, 17 Sep 2021 15:01:33 +0000 (08:01 -0700)]
Actually deprecate __torch_function__ as plain methods (#64843)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/64843
Fix for https://github.com/pytorch/pytorch/issues/63767
Test Plan: Imported from OSS
Reviewed By: heitorschueroff
Differential Revision:
D30991425
Pulled By: albanD
fbshipit-source-id:
1214143b8aea87e6ff406c7fc13096bd15d1a768
albanD [Fri, 17 Sep 2021 15:01:33 +0000 (08:01 -0700)]
Update fx proxy to use classmethod for __torch_function__ (#64842)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/64842
Change the `__torch_function__` to follow best guidelines of using classmethods.
I am not sure how to handle the case where multiple tracer objects are given as input but given that before we were getting an arbitrary tracer from there based on the "self" that was arbitrarily chosen by the torch_function caller, the new implementation is not worst?
Let me know what you think!
Test Plan: Imported from OSS
Reviewed By: heitorschueroff
Differential Revision:
D30991423
Pulled By: albanD
fbshipit-source-id:
d28940df230b543952b278a0eb2d61cf7ae123ce
albanD [Fri, 17 Sep 2021 15:01:33 +0000 (08:01 -0700)]
Use classmethods for overrides (#64841)
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/64841
Test Plan: Imported from OSS
Reviewed By: heitorschueroff
Differential Revision:
D30991424
Pulled By: albanD
fbshipit-source-id:
551e2119768f3a4292713f3bfa83930f5506adbd
Howard Huang [Fri, 17 Sep 2021 14:55:01 +0000 (07:55 -0700)]
Fix port allocation race condition for elastic test (#65149)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/65149
Fixes #64789
There is a race condition between when the free port is acquired to when it is used to create the store in which it may have been used. Since this test only tests that timeout is triggered for tcpstore, we can bind to any port on tcpstore creation.
This only affects the test on the server (since that is where the port is used), but I changed both tests for clarity
cc pietern mrshenli pritamdamania87 zhaojuanmao satgera rohan-varma gqchen aazzolini osalpekar jiayisuse SciPioneer H-Huang cbalioglu gcramer23
Test Plan: Imported from OSS
Reviewed By: mrshenli
Differential Revision:
D30993166
Pulled By: H-Huang
fbshipit-source-id:
eac4f28d641ac87c4ebee89df83f90955144f2f1
Stephen Jia [Fri, 17 Sep 2021 14:48:04 +0000 (07:48 -0700)]
Small improvements to compare_models_torch binary (#65171)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/65171
Add the model comparison binary to BUCK, and also add some quality of life features such as controlling the input range.
Test Plan:
```
# Build the binary
cd ~/fbsource
buck build -c ndk.custom_libcxx=false -c pt.enable_qpl=0 //xplat/caffe2:ptmobile_compareAndroid\#android-arm64 --show-ou
# Push it to the device
adb push buck-out/gen/xplat/caffe2/ptmobile_compareAndroid\#android-arm64 /data/local/tmp/compare_models
# Run the benchmark binary
BENCH_CMD="/data/local/tmp/compare_models"
BENCH_CMD+=" --model=$PATH_TO_MODEL"
BENCH_CMD+=" --refmodel=$PATH_TO_REFERENCE_MODEL"
BENCH_CMD+=" --input_type=float --input_dims=$MODEL_INPUT_SIZE"
BENCH_CMD+=" --iter=100"
BENCH_CMD+=" --tolerance 1e-5"
```
Reviewed By: beback4u
Differential Revision:
D30371322
fbshipit-source-id:
5e520aaf119c90985a1d5a135f76e4057148333b
Edward Yang [Fri, 17 Sep 2021 14:40:59 +0000 (07:40 -0700)]
Disable autograd fallback tests on Windows (#65147)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/65147
I think they trigger an MSVC bug per https://github.com/pytorch/pytorch/issues/48763
ghstack-source-id:
138247203
Test Plan: breakpointed https://www.internalfb.com/intern/sandcastle/job/
9007199738584981/ and sush'ed into the host and ran `buck build arvr/mode/win/opt //xplat/caffe2:autograd_libtorch_test_ovrsource` in `/cygdrive/d/ovrsource-null-hg`
Reviewed By: soulitzer
Differential Revision:
D30992685
fbshipit-source-id:
06c6fb2c18d55490f89fc91ee5b7a4c5a7faf1c6
Michael Dagitses [Fri, 17 Sep 2021 14:32:32 +0000 (07:32 -0700)]
implement "xy" indexing for torch.meshgrid (#62724)
Summary:
This is step 4/7 of https://github.com/pytorch/pytorch/issues/50276. This allows the use of `"xy"` indexing but doesn't change any defaults.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/62724
Reviewed By: heitorschueroff
Differential Revision:
D30995290
Pulled By: dagitses
fbshipit-source-id:
08a6a6144b20bc019f68bc3c52e3bbf967976d8f
Alban Desmaison [Fri, 17 Sep 2021 13:28:41 +0000 (06:28 -0700)]
Allow parametrization to be nested (#65167)
Summary:
Fixes https://github.com/pytorch/pytorch/issues/65163
Pull Request resolved: https://github.com/pytorch/pytorch/pull/65167
Reviewed By: jbschlosser
Differential Revision:
D31002318
Pulled By: albanD
fbshipit-source-id:
b1f1c6c9efa9e83af9789ed13efc133f777f418e
Nicolas Hug [Fri, 17 Sep 2021 10:27:23 +0000 (03:27 -0700)]
Pass GITHUB_TOKEN to linux CI jobs and avoid skipping torchhub tests (#64807)
Summary:
Fixes https://github.com/pytorch/pytorch/issues/64760
This should hopefully put the torchhub tests back.
This also avoids skipping the torchhub tests: currently the tests are skipped if they fail, which pretty much defeats the purpose of having a test in the first place since we're never notified when they do fail.
cc ezyang seemethere malfet lg20987 pytorch/pytorch-dev-infra nairbv NicolasHug
Pull Request resolved: https://github.com/pytorch/pytorch/pull/64807
Reviewed By: seemethere
Differential Revision:
D30994585
Pulled By: NicolasHug
fbshipit-source-id:
561782c22462b5cfec99cca153eb59623db5660a
Tao Xu [Fri, 17 Sep 2021 07:19:36 +0000 (00:19 -0700)]
[CoreML][fbcode] Add the `preprocess` python APIs (#64521)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/64521
Add the preprocess part for the coreml delegate. Check out the `example.py` for the usage.
ghstack-source-id:
138324214
Test Plan:
```
(base) [taox@devvm2780.vll0 ~/fbsource/fbcode/caffe2/fb] buck run coreml:example -- --model="/home/taox/mobilenetv2/mobilenetv2.pt" --out="/home/taox/mobilenetv2/mobilenetv2_coreml.pt"
Parsing buck files: finished in 0.5 sec
Downloaded 0/1 artifacts, 0.00 bytes, 100.0% cache miss (for updated rules)
Building: finished in 10.6 sec (100%) 12611/57623 jobs, 1/57623 updated
Total time: 11.1 sec
Converting Frontend ==> MIL Ops: 100%|██████████████████████████████████████████▉| 382/383 [00:00<00:00, 692.58 ops/s]
Running MIL optimization passes: 100%|███████████████████████████████████████████| 18/18 [00:00<00:00, 45.55 passes/s]
Translating MIL ==> MLModel Ops: 100%|███████████████████████████████████████████| 704/704 [00:01<00:00, 468.56 ops/s]
input {
name: "input_0"
type {
multiArrayType {
shape: 1
shape: 3
shape: 224
shape: 224
dataType: FLOAT32
}
}
}
output {
name: "645"
type {
multiArrayType {
dataType: FLOAT32
}
}
}
metadata {
userDefined {
key: "com.github.apple.coremltools.source"
value: "torch==1.10.0a0+fb"
}
userDefined {
key: "com.github.apple.coremltools.version"
value: "4.1"
}
}
{'inputs': '[["input_0", "0", "[1, 3, 224, 224]"]]', 'outputs': '[["645", "0", "[1, 1000]"]]', 'config': '{"spec_ver": "4", "backend": "cpu", "allow_low_precision": "True"}', 'metadata': '{"coremltool_ver": "4.1", "torch_ver": "torch==1.10.0a0+fb"}'}
WARNING: Logging before InitGoogleLogging() is written to STDERR
W0826 13:27:12.690302 2477051 backend_detail.cpp:376] Warning: Backend [coreml] is not available. Execution of this Module is still possible by saving and loading on a device where the backend is available. (function codegen_backend_module)
graph(%self.1 : torch.jit.LoweredModule.coreml.__torch__.torchvision.models.mobilenetv2.MobileNetV2,
%x.1 : Tensor):
%51 : str = prim::Constant[value="Exception: Backend is not available."]()
%50 : str = prim::Constant[value="AssertionError: "]()
%14 : str = prim::Constant[value="forward"]() # <string>:5:62
%48 : Tensor = prim::Uninitialized()
%44 : Tensor = prim::Uninitialized()
%typed_inputs.1 : Any[] = prim::ListConstruct(%x.1)
%__backend.3 : __torch__.torch.classes.__backends__.coreml = prim::GetAttr[name="__backend"](%self.1)
%8 : bool = prim::CallMethod[name="is_available"](%__backend.3) # <string>:4:19
%49 : Tensor = prim::If(%8) # <string>:4:16
block0():
%__backend : __torch__.torch.classes.__backends__.coreml = prim::GetAttr[name="__backend"](%self.1)
%__handles : Dict(str, Any) = prim::GetAttr[name="__handles"](%self.1)
%15 : Any = aten::__getitem__(%__handles, %14) # <string>:5:47
%17 : Any[] = prim::CallMethod[name="execute"](%__backend, %15, %typed_inputs.1) # <string>:5:24
%18 : Any = prim::ListUnpack(%17)
%20 : bool = prim::isinstance[types=[Tensor]](%18)
%39 : Tensor = prim::If(%20) # <string>:6:18
block0():
%22 : Tensor = prim::unchecked_cast(%18)
-> (%22)
block1():
= prim::RaiseException(%50) # <string>:6:18
-> (%44)
-> (%39)
block1():
= prim::RaiseException(%51) # <string>:9:18
-> (%48)
return (%49)
```
Reviewed By: raziel
Differential Revision:
D30585154
fbshipit-source-id:
66c7d2e931be6eaa3c43a0ee131ea8046452449d
Don Jang [Fri, 17 Sep 2021 05:32:23 +0000 (22:32 -0700)]
[Static Runtime] Introduce static_runtime::dict_unpack (#64771)
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/64771
Test Plan:
- Added `StaticRuntime.RemoveImmutableInputDictLookupsWithImmutableInputDict`
- Added `StaticRuntime.RemoveImmutableInputDictLookupsWithMutableInputDict`
- TBD: Perf impact measurement
Reviewed By: mikeiovine
Differential Revision:
D30685083
fbshipit-source-id:
050a92ef3b3ed0fdc0ab7a13a4b5dbfede9342a9
BowenBao [Fri, 17 Sep 2021 04:39:10 +0000 (21:39 -0700)]
[ONNX] Update submodule to 1.10.1 (#63716) (#64576)
Summary:
Stack from [ghstack](https://github.com/ezyang/ghstack):
* **https://github.com/pytorch/pytorch/issues/64576 [ONNX] Update submodule to 1.10.1 (https://github.com/pytorch/pytorch/issues/63716)**
* [ONNX] Update IR version to 7
* [ONNX] update submodule to 1.10.1
* Disable some tests in caffe2 that fail b/c caffe2 doesn't support the
new ops.
* Update Bazel file.
* Update expect files for new ONNX IR version
Pull Request resolved: https://github.com/pytorch/pytorch/pull/64576
Reviewed By: jansel
Differential Revision:
D31006896
Pulled By: msaroufim
fbshipit-source-id:
f3bf97709f23a5a2cd49c708e7363231f2c1961a
James Reed [Fri, 17 Sep 2021 03:31:03 +0000 (20:31 -0700)]
[FX} Add torch.ops.profiler._record_function_{enter,exit} as stateful ops for DCE (#65180)
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/65180
Test Plan: Imported from OSS
Reviewed By: jansel
Differential Revision:
D31007115
Pulled By: jamesr66a
fbshipit-source-id:
823b15db712a382a4f2a4fd409983d47bc067150
Zafar Takhirov [Fri, 17 Sep 2021 03:29:05 +0000 (20:29 -0700)]
[quant] AO migration of the `torch/quantization/utils.py` (phase 1) (#64919)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/64919
AO Team is migrating the existing torch.quantization into torch.ao.quantization. We are doing it one file at a time to make sure that the internal callsites are updated properly. This migrates the quantization utilities.
ghstack-source-id:
138303325
Test Plan: `buck test mode/dev //caffe2/test:quantization`
Reviewed By: jerryzh168
Differential Revision:
D30899082
fbshipit-source-id:
85eb38c419e417147e71758b682cd095308dd0c9
Jordan Fix [Fri, 17 Sep 2021 02:55:46 +0000 (19:55 -0700)]
[acc_utils] Add print_model_info (#65045)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/65045
This is a useful tool for printing out all of the ops that are found in a model after acc_tracer. It assumes the provided model has no `call_module` or `call_method`, which is generally a reasonable assumption assuming a model has been successfully traced by the acc_tracer.
Test Plan:
Tested locally. Sample output:
```
Model Info:
> placeholder: 1184
> get_attr: 655
> output: 2
> torch.fx.experimental.fx_acc.acc_ops.add: 2
> torch.fx.experimental.fx_acc.acc_ops.cat: 23
> torch.fx.experimental.fx_acc.acc_ops.embedding_bag: 576
> torch.fx.experimental.fx_acc.acc_ops.layer_norm: 15
> torch.fx.experimental.fx_acc.acc_ops.linear: 27
> torch.fx.experimental.fx_acc.acc_ops.matmul: 3
> torch.fx.experimental.fx_acc.acc_ops.mul: 17
> torch.fx.experimental.fx_acc.acc_ops.permute: 2
> torch.fx.experimental.fx_acc.acc_ops.reshape: 419
> torch.fx.experimental.fx_acc.acc_ops.sigmoid: 16
> torch.fx.experimental.fx_acc.acc_ops.slice_tensor: 630
> torch.fx.experimental.fx_acc.acc_ops.sum: 4
> torch.fx.experimental.fx_acc.acc_ops.tanh: 315
```
Reviewed By:
842974287
Differential Revision:
D30954829
fbshipit-source-id:
5c4f0770667b72859b74099d9f4575284fc48bd2
Yinghai Lu [Fri, 17 Sep 2021 02:26:36 +0000 (19:26 -0700)]
Add back the owning_module fix (#65159)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/65159
This was a legit fix originally introduced in
D30905949 (https://github.com/pytorch/pytorch/commit/
446d95a7f64cb464d28d27c4c87c48900a9fde79). But we hesitated and removed it for some reason. Putting it back.
Reviewed By:
842974287
Differential Revision:
D30996277
fbshipit-source-id:
3f5eede11dba2072e7cd5ae6ca7ac81d55fb75fa
Rui Zhu [Fri, 17 Sep 2021 01:08:00 +0000 (18:08 -0700)]
Add dropout shape inference as no-op in acc_tracer (#65113)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/65113
Register dropout as no-op in acc_tracer & Add shape inference for no-op
Test Plan:
buck test glow/fb/fx/acc_tracer:test_acc_shape_inference --- test_unary_15_dropout_no_op
buck test glow/fb/fx/oss_acc_tracer:test_acc_tracer -- test_dropout
Reviewed By: jfix71
Differential Revision:
D30880679
fbshipit-source-id:
592fe50e17137c94c12727658191dedf08daf8cf
Nikita Shulga [Fri, 17 Sep 2021 00:36:14 +0000 (17:36 -0700)]
Pin SciPy to 1.6.2 on Windows (#65017)
Summary:
Re-enable previously disabled test_distributions
Note: conda does not have ScipPy-1.6.3, only 1.6.2
Pull Request resolved: https://github.com/pytorch/pytorch/pull/65017
Reviewed By: seemethere
Differential Revision:
D31003199
Pulled By: malfet
fbshipit-source-id:
96b9d2a833f703008bb1f4df9361db8ec6f8ccc6
Avery Wang [Thu, 16 Sep 2021 23:37:52 +0000 (16:37 -0700)]
Added logging for the Reducer's non-member functions. (#65023)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/65023
Added an optional logging parameter for non-member functions `compute_bucket_assignment_by_size` and `verify_replica0_across_processes`. If a logger is provided then `TORCH_CHECK` assertions are replaced with a wrapper that logs the error to the DDP reducer's logger before calling `TORCH_CHECK`. If a logger is not provided `TORCH_CHECK` is still called.
Modified python-side calls to `_compute_bucket_assignment_by_size` and `_verify_model_across_ranks` to include a logger whenever possible. A notable exception is when these non-member functions are called in DDP's constructor - we cannot pass in a logger as they may have not been initialized yet.
We also added 4 new tests: `test_compute_bucket_assignment_by_size_sparse_error_{with, without}_logger` which tests the `_compute_bucket_assignment_by_size` function to ensure that sparse tensors are rejected and the errors are logged. `test_verify_model_across_rank_{with, without}_logger` calls `_verify_model_across_ranks` to ensure that ill-formed models (different ranks have different number of parameters compared to rank 0) are rejected and the errors are logged. The test `test_ddp_model_diff_across_ranks` remains unchanged - while it does construct a ill-formed DDP instance which triggers the error in `_verify_model_across_ranks`, we cannot check the logger because this error appears in the constructor.
Lastly, did some cleanup of the `test_ddp_model_diff_across_ranks` function to make the logic of choosing which context manager and error message to use more clean.
Test Plan:
**Build commands**
`buck build mode/dev-nosan //caffe2/test/distributed:distributed_nccl_spawn --keep-going`
`buck build mode/dev-nosan //caffe2/test/distributed:distributed_gloo_spawn --keep-going`
**Test commands**
Test for `_compute_bucket_assignment_by_size` (Python)/ `compute_bucket_assignment_by_size` (C++)
`BACKEND={nccl, gloo} WORLD_SIZE=2 ../buck-out/dev/gen/caffe2/test/distributed/distributed_{nccl, gloo}_spawn#binary.par -r test_compute_bucket_assignment_by_size_sparse_error_{with, without}_logger`
Test for `_verify_model_across_ranks` (Python)/`verify_replicas0_across_process` (C++)
`BACKEND={nccl, gloo} WORLD_SIZE=2 ../buck-out/dev/gen/caffe2/test/distributed/distributed_{nccl, gloo}_spawn#binary.par -r test_verify_model_across_ranks_{with, without}_logger`
Test that constructs an ill-formed DDP instance. Only did cleanup of this function.
`BACKEND={nccl, gloo} WORLD_SIZE=2 ../buck-out/dev/gen/caffe2/test/distributed/distributed_{nccl, gloo}_spawn#binary.par -r test_ddp_model_diff_across_ranks`
Reviewed By: rohan-varma
Differential Revision:
D30924790
fbshipit-source-id:
dae6fa82485a204a6a4b022f2d073417d07ebb2f
kshitij12345 [Thu, 16 Sep 2021 21:20:43 +0000 (14:20 -0700)]
OpInfo: nn.functional.conv2d (#63517)
Summary:
Reference: https://github.com/pytorch/pytorch/issues/54261
Reference: https://github.com/facebookresearch/functorch/issues/78
Mostly inspired from https://github.com/pytorch/pytorch/issues/62882
Pull Request resolved: https://github.com/pytorch/pytorch/pull/63517
Reviewed By: heitorschueroff
Differential Revision:
D30993855
Pulled By: zou3519
fbshipit-source-id:
7402f99addb4ef8f19c2ce1a09ed9006e737cc7e
Jane Xu [Thu, 16 Sep 2021 20:22:02 +0000 (13:22 -0700)]
Remove old references to 9.2 in documentation (#65059)
Summary:
Removes references in .rst and README.md and comments in the Dockerfile
Pull Request resolved: https://github.com/pytorch/pytorch/pull/65059
Reviewed By: malfet
Differential Revision:
D30961110
Pulled By: janeyx99
fbshipit-source-id:
702a9a81bf08125ec4ac38bc656fc2c128c30018
Kefei Lu [Thu, 16 Sep 2021 20:14:12 +0000 (13:14 -0700)]
Provide function interface for `remove_duplicate_output_args` (#65134)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/65134
So that its implementation can be abstracted and replaced
Test Plan: Run linter, CI
Reviewed By:
842974287
Differential Revision:
D30966916
fbshipit-source-id:
92ec78c7410d0be14faecb0ba1eafdc74bab5a5d
Kefei Lu [Thu, 16 Sep 2021 20:14:12 +0000 (13:14 -0700)]
Add type annotation for `TRTInterpreter.run` (#65135)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/65135
Opportunistically adding type annotation as I work through fx2trt code base.
Test Plan: run linter and CI
Reviewed By: houseroad,
842974287
Differential Revision:
D30903185
fbshipit-source-id:
3f700b57f4433f2d312c1ff2e6b99948e3c8845c
Charles David Hernandez [Thu, 16 Sep 2021 19:55:55 +0000 (12:55 -0700)]
[quant]ao migration for quantization mappings and fuser method mappings hg mv (#64985)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/64985
moving quantization_mappings.py and fuser_method_mappings.py to the ao folder while retaining backwards compatibility
also added dict test
ghstack-source-id:
138215312
Test Plan:
buck test mode/dev //caffe2/test:quantization
https://www.internalfb.com/intern/testinfra/testrun/
7036874471986444
buck test mode/dev //caffe2/test:quantization -- TestAOMigrationQuantization
https://www.internalfb.com/intern/testinfra/testrun/
5348024625792701
Reviewed By: z-a-f
Differential Revision:
D30982551
fbshipit-source-id:
00f53bd44009d6012a7de852000aad6885131edb
Jane Xu [Thu, 16 Sep 2021 19:53:12 +0000 (12:53 -0700)]
Remove CUDA 9.2 and older references from our cmake (#65065)
Summary:
Removes old CUDA references in our cuda.cmake
Pull Request resolved: https://github.com/pytorch/pytorch/pull/65065
Reviewed By: malfet
Differential Revision:
D30992673
Pulled By: janeyx99
fbshipit-source-id:
85b524089ed57e5acbc71720267cf05e24a8c20a
Nikita Shulga [Thu, 16 Sep 2021 19:37:10 +0000 (12:37 -0700)]
Disable ParallelTBB (#65092)
Summary:
As ParallelTBB's `at::get_thread_num` is not compatible with general model used by OpenMP and ParallelNative (where it is an contiguous thread index within parallel loop), see https://github.com/pytorch/pytorch/issues/64571#issuecomment-
914691883
More examples of similar regressions: https://github.com/pytorch/pytorch/runs/
3612142217
Pull Request resolved: https://github.com/pytorch/pytorch/pull/65092
Reviewed By: zhouzhuojie
Differential Revision:
D30995936
Pulled By: malfet
fbshipit-source-id:
db145b6a850d794f2c954f59f30249b291473e36
Zhengxu Chen [Thu, 16 Sep 2021 18:23:11 +0000 (11:23 -0700)]
Introduce tensorRT as builtin module for torch::deploy. (#63818)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/63818
ghstack-source-id:
138156957
Test Plan: next diff
Reviewed By: wconstab
Differential Revision:
D30499309
fbshipit-source-id:
4ab1bc9896243c0c1503afb18fbfb196fc37404e
David Berard [Thu, 16 Sep 2021 17:44:33 +0000 (10:44 -0700)]
[JIT] Improve BatchMM mutability handling (#65097)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/65097
Previously, BatchMM would skip any block containing any mutable
operators. Now it will avoid batching any operation whose inputs or
outputs are ever mutated. Specifically: consider a tree of ADD, T,
and MM nodes rooted at an ADD node. If any input or output to any
node in the tree is ever mutated, then the entire tree will be ignored
by BatchMM.
Test Plan: python test/test_jit.py TestBatchMM
Reviewed By: eellison
Differential Revision:
D30973515
Pulled By: davidberard98
fbshipit-source-id:
9d836faa1ef0c9e3fefe0ffc0bd265f275471f48
Charles David Hernandez [Thu, 16 Sep 2021 17:31:21 +0000 (10:31 -0700)]
[quant] ao migration of observer and qconfig (#64982)
Summary:
(Had to recreate this diff so it wasn't dependent on the stack)
Pull Request resolved: https://github.com/pytorch/pytorch/pull/64982
migration of qconfig.py and observer.py to torch/ao/quantization using new test format
ghstack-source-id:
138215256
Test Plan:
buck test mode/opt //caffe2/test:quantization
https://www.internalfb.com/intern/testinfra/testconsole/testrun/
8444249354294701/
buck test mode/dev //caffe2/test:quantization -- TestAOMigrationQuantization
https://www.internalfb.com/intern/testinfra/testrun/
3940649742829796
Reviewed By: z-a-f
Differential Revision:
D30982534
fbshipit-source-id:
48d08969b1984311ceb036eac0877c811cd6add9
Kushashwa Ravi Shrimali [Thu, 16 Sep 2021 17:12:50 +0000 (10:12 -0700)]
[Fix] Raise error when empty index tensor is passed (gather) (#65006)
Summary:
See https://github.com/pytorch/pytorch/pull/63312#issuecomment-
919330081 for context.
cc: ezyang ysiraichi
Pull Request resolved: https://github.com/pytorch/pytorch/pull/65006
Reviewed By: mruberry
Differential Revision:
D30937730
Pulled By: ezyang
fbshipit-source-id:
a8f77b1f40d07e7e3bef6caaafa119685f297638
James Reed [Thu, 16 Sep 2021 17:00:59 +0000 (10:00 -0700)]
[FX] Gate FXGraphDrawer on whether pydot is installed (#65088)
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/65088
Test Plan: Imported from OSS
Reviewed By: khabinov
Differential Revision:
D30967951
Pulled By: jamesr66a
fbshipit-source-id:
dba2f13a47889b3d4187de925b4fe74ee90b7f79
Michael Dagitses [Thu, 16 Sep 2021 16:58:09 +0000 (09:58 -0700)]
add support for indexing to meshgrid (#62722)
Summary:
This is step 3/7 of https://github.com/pytorch/pytorch/issues/50276. It only adds support for the argument but doesn't implement new indexing modes yet.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/62722
Test Plan:
Verified this is not FC breaking by adding logging to both meshgrid
overloads and then called meshgrid twice:
`meshgrid(*tensors)`
and
`meshgrid(*tensors, indexing='ij')`
This confirmed that the former signature triggered the original native
function and the latter signature triggered the new native function.
Reviewed By: H-Huang
Differential Revision:
D30394313
Pulled By: dagitses
fbshipit-source-id:
e265cb114d8caae414ee2305dc463b34fdb57fa6
Richard Zou [Thu, 16 Sep 2021 16:00:34 +0000 (09:00 -0700)]
[Reland] Add python mode (#64360)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/64360
This PR adds a (private) enable_python_mode context manager.
(see torch/utils/_python_dispatch.py).
enable_python_mode accepts the type of a __torch_dispatch__ object
as its argument. Whenever an operator gets called inside of the
context manager, it dispatches to the __torch_dispatch__ of
the passed-in type.
Example usage:
```
with enable_python_mode(LoggingTensor):
z = torch.empty([])
assert isinstance(z, LoggingTensor)
```
There are quite a few changes that were made to support this.
First, we added TorchDispatchTypeObject, a C++ struct that represents the
type of a `__torch_dispatch__` object (e.g. LoggingTensor).
It holds both the PyObject* representing the class and a PyInterpreter*
so we know which Python interpreter it came from.
Next, we updated the concrete_dispatch_fn in python_variable.cpp to accept
a `const std::shared_ptr<TorchDispatchTypeObject>&` argument. When this
is null, dispatching happens as usual. When it is non-null, we prepend
the TorchDispatchTypeObject's PyObject* to the overloaded args list so that
it is considered first for dispatch.
To get that to work, we changed how `handle_torch_dispatch_no_python_arg_parser`
works. The "overloaded args list" previously only consisted of Tensor PyObjects,
but now it can have types in addition to Tensors!
- We renamed `append_overloaded_arg` to `append_overloaded_arg`
- We added a new `append_overloaded_type` that appends a type to
overloaded_args
- We added special handling in `handle_torch_dispatch_no_python_arg_parser`
and `append_overloaded_arg` to handle types in addition to Tensors.
Then, there is PythonMode and PythonModeTLS.
- We reuse the DispatchKey::Python dispatch key as a mode key
- We use PythonMode::enter and PythonMode::exit to enable/disable
DispatchKey::Python and set the PythonModeTLS.
- PythonModeTLS stores a TorchDispatchTypeObject as metadata.
- PythonMode is in libtorch_python, and PythonModeTLS is in ATen.
This split is due to the libtorch_python library boundary (because we need
to save TLS in ATen/ThreadLocalState)
- We modify the PythonFallbackKernel to look up
the relevant TorchDispatchTypeObject (if Python Mode is active) and
dispatch using it.
There are two more miscellaneous changes:
- internal_new_from_data (torch/csrc/utils/tensor_new.cpp) gets an
exclude guard. enable_python_mode currently does not handle
torch.tensor and the exclude guard is to prevent a bug.
Future:
- This PR does not allow for the nesting of Python modes. In the future we
should be able to enable this with a more sane no_dispatch API and by changing
the TLS to a stack. For now I did not need this for CompositeImplicitAutograd testing.
Test Plan: - new tests
Reviewed By: ezyang
Differential Revision:
D30698082
Pulled By: zou3519
fbshipit-source-id:
7094a90eee6aa51f8b71bc4d91cfb6f49e9691f8
Alban Desmaison [Thu, 16 Sep 2021 13:36:29 +0000 (06:36 -0700)]
Revert
D30888794: [Model Averaging] Simplify PostLocalSGD Optimizer API
Test Plan: revert-hammer
Differential Revision:
D30888794 (https://github.com/pytorch/pytorch/commit/
3d312b3b8ee90f8b289c7d5601a13d0521b46b7e)
Original commit changeset:
21261b480f6b
fbshipit-source-id:
87abb7e8cd9ecaac909ec6c3ee053fa7c4ae1975
Rodrigo Berriel [Thu, 16 Sep 2021 13:33:40 +0000 (06:33 -0700)]
Improve LSTM documentation for proj_size > 0 (#65102)
Summary:
Fixes https://github.com/pytorch/pytorch/issues/65053. Although the documentation states that:
https://github.com/pytorch/pytorch/blob/
fe0f9d1dafb9791cb08635636a01128850d17538/torch/nn/modules/rnn.py#L500-L506
It seems that the definition of `weight_ih_l[k]` could be improved by specifying what happens when `k > 0` and `proj_size > 0`. As `proj_size` is only used in LSTM, no changes are needed for the other RNNs.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/65102
Reviewed By: supriyar
Differential Revision:
D30975781
Pulled By: jbschlosser
fbshipit-source-id:
12df06e5e6a8d5de0ad10fb15e33c3e6311c11d3
Scott Wolchok [Thu, 16 Sep 2021 04:43:09 +0000 (21:43 -0700)]
[Static Runtime] Use FastSet instead of std::set everywhere (#65114)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/65114
There doesn't seem to be any reason to use std::set for sets of pointers, right?
ghstack-source-id:
138198504
Reviewed By: hlu1
Differential Revision:
D30978450
fbshipit-source-id:
4599c6249fda3a89959f839d3bf6400c5891f82c
Amr Elshennawy [Thu, 16 Sep 2021 04:19:03 +0000 (21:19 -0700)]
Reduce PyToch Warnings - Cast fixes from
D26624430 (#65015)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/65015
Split out the existing fixes into a diff we can land separately.
Test Plan:
pooled_embeddings_modules_test
Parsing buck files: finished in 8.3 sec
Creating action graph: finished in 38.3 sec
[RE] Metadata: Session ID=[https://fburl.com/b/reSessionID-
9bea421c-875e-4168-9e00-
7d67479b1a9f]
[RE] Waiting on 46 remote actions. Completed 905 actions remotely, action cache hit rate: 5.08%.
Downloaded 7002/8869 artifacts, 560.00 Mbytes, 11.6% cache miss (for updated rules)
Building: finished in 13:12.4 min (100%) 31964/31964 jobs, 17344/31964 updated
Total time: 13:59.1 min
More details at https://www.internalfb.com/intern/buck/build/
b9a58bba-e0aa-4c2b-8824-
a0c4074b0954
Tpx test run coordinator for Facebook. See https://fburl.com/tpx for details.
Running with tpx session id:
28cbe2b1-6fbc-450c-91c9-
c06a7ff1d53b
Trace available for this run at /tmp/tpx-
20210914-114921.005504/trace.log
Started reporting to test run: https://www.internalfb.com/intern/testinfra/testrun/
1407375088325000
✓ ListingSuccess: caffe2/torch/fb/sparsenn:pooled_embeddings_modules_test - main (23.849)
{emoji:2702} Omit: caffe2/torch/fb/sparsenn:pooled_embeddings_modules_test - test_permutation (caffe2.torch.fb.sparsenn.tests.pooled_embeddings_modules_test.PooledEmbeddingModulesTest_1_cuda)
Test output:
> This test was disabled.
To run this test locally, add the command line flag --run-disabled to your test command (prefix with -- if using buck).
To view why this is disabled or re-enable this test in the test console, visit https://our.intern.facebook.com/intern/testinfra/testdetail/
562949981577936
↻ Skip: caffe2/torch/fb/sparsenn:pooled_embeddings_modules_test - test_permutation (caffe2.torch.fb.sparsenn.tests.pooled_embeddings_modules_test.PooledEmbeddingModulesTest_0_cpu) (13.201)
Test output:
> Repro command : $(cat "/tmp/tpx-
20210914-114921.005504/
dc174692-8d92-4459-8b8f-
201643c6ab7d/execution_command")
Skipped: CUDA is not available or no GPUs detected
stdout:
stderr:
↻ Skip: caffe2/torch/fb/sparsenn:pooled_embeddings_modules_test - test_permutation_autograd (caffe2.torch.fb.sparsenn.tests.pooled_embeddings_modules_test.PooledEmbeddingModulesTest_1_cuda) (13.201)
Test output:
> Repro command : $(cat "/tmp/tpx-
20210914-114921.005504/
dc174692-8d92-4459-8b8f-
201643c6ab7d/execution_command")
Skipped: CUDA is not available or no GPUs detected
stdout:
stderr:
✓ Pass: caffe2/torch/fb/sparsenn:pooled_embeddings_modules_test - test_compatibility (caffe2.torch.fb.sparsenn.tests.pooled_embeddings_modules_test.PooledEmbeddingModulesTest_1_cuda) (13.201)
↻ Skip: caffe2/torch/fb/sparsenn:pooled_embeddings_modules_test - test_permutation_autograd (caffe2.torch.fb.sparsenn.tests.pooled_embeddings_modules_test.PooledEmbeddingModulesTest_0_cpu) (13.201)
Test output:
> Repro command : $(cat "/tmp/tpx-
20210914-114921.005504/
dc174692-8d92-4459-8b8f-
201643c6ab7d/execution_command")
Skipped: CUDA is not available or no GPUs detected
stdout:
stderr:
✓ Pass: caffe2/torch/fb/sparsenn:pooled_embeddings_modules_test - test_compatibility (caffe2.torch.fb.sparsenn.tests.pooled_embeddings_modules_test.PooledEmbeddingModulesTest_0_cpu) (13.201)
✓ Pass: caffe2/torch/fb/sparsenn:pooled_embeddings_modules_test - main (13.201)
Summary
Pass: 3
Skip: 3
↻ caffe2/torch/fb/sparsenn:pooled_embeddings_modules_test - test_permutation (caffe2.torch.fb.sparsenn.tests.pooled_embeddings_modules_test.PooledEmbeddingModulesTest_0_cpu)
↻ caffe2/torch/fb/sparsenn:pooled_embeddings_modules_test - test_permutation_autograd (caffe2.torch.fb.sparsenn.tests.pooled_embeddings_modules_test.PooledEmbeddingModulesTest_1_cuda)
↻ caffe2/torch/fb/sparsenn:pooled_embeddings_modules_test - test_permutation_autograd (caffe2.torch.fb.sparsenn.tests.pooled_embeddings_modules_test.PooledEmbeddingModulesTest_0_cpu)
Omit: 1
{emoji:2702} caffe2/torch/fb/sparsenn:pooled_embeddings_modules_test - test_permutation (caffe2.torch.fb.sparsenn.tests.pooled_embeddings_modules_test.PooledEmbeddingModulesTest_1_cuda)
ListingSuccess: 1
shape_inference_mode_test
[amrelshennawy@devvm855.ftw0 /data/users/amrelshennawy/fbsource/fbcode] buck test caffe2/torch/fb/sparsenn:shape_inference_mode_test
Downloaded 6/18 artifacts, 11.69 Kbytes, 53.8% cache miss (for updated rules)
Building: finished in 1.6 sec (100%) 110/110 jobs, 26/110 updated
Total time: 1.8 sec
More details at https://www.internalfb.com/intern/buck/build/
0e5f45b2-5777-49e9-a3b0-
09bd05687b2b
Tpx test run coordinator for Facebook. See https://fburl.com/tpx for details.
Running with tpx session id:
99509108-5ff3-4b1a-b7b3-
2f43c4036209
Trace available for this run at /tmp/tpx-
20210914-120119.723607/trace.log
Started reporting to test run: https://www.internalfb.com/intern/testinfra/testrun/
6192449502564504
✓ ListingSuccess: caffe2/torch/fb/sparsenn:shape_inference_mode_test - main (0.374)
✓ Pass: caffe2/torch/fb/sparsenn:shape_inference_mode_test - test_set_upper_bound_mode (torch.python.fb.shape_inference_mode_test.TestShapeInferenceMode) (0.249)
✓ Pass: caffe2/torch/fb/sparsenn:shape_inference_mode_test - test_set_upper_bound_settings (torch.python.fb.shape_inference_mode_test.TestShapeInferenceMode) (0.253)
Summary
Pass: 2
ListingSuccess: 1
test
[amrelshennawy@devvm855.ftw0 /data/users/amrelshennawy/fbsource/fbcode] buck test caffe2/torch/fb/sparsenn:test
Parsing buck files: finished in 1.1 sec
Creating action graph: finished in 38.6 sec
Downloaded 6/30 artifacts, 11.29 Kbytes, 66.7% cache miss (for updated rules)
Building: finished in 41.6 sec (100%) 26783/26783 jobs, 43/26783 updated
Total time: 01:21.4 min
More details at https://www.internalfb.com/intern/buck/build/
8f794eb0-3d3c-4ee3-9aec-
5ec5cec1b0f4
Tpx test run coordinator for Facebook. See https://fburl.com/tpx for details.
Running with tpx session id:
a06164b5-d7d7-444c-a4ff-
e312cb9970d9
Trace available for this run at /tmp/tpx-
20210914-120428.464799/trace.log
Started reporting to test run: https://www.internalfb.com/intern/testinfra/testrun/
3377699789132066
✓ ListingSuccess: caffe2/torch/fb/sparsenn:test - main (16.637)
✓ Pass: caffe2/torch/fb/sparsenn:test - test_dense_mlp_quantize_ops (caffe2.torch.fb.sparsenn.tests.sparsenn_operators_test.SparseNNOperatorsTest) (17.870)
✓ Pass: caffe2/torch/fb/sparsenn:test - test_clip_ranges_shape_inference_mode (caffe2.torch.fb.sparsenn.tests.sparsenn_operators_test.SparseNNOperatorsTest) (17.922)
✓ Pass: caffe2/torch/fb/sparsenn:test - test_gather_ranges_to_dense_caffe2 (caffe2.torch.fb.sparsenn.tests.sparsenn_operators_test.SparseNNOperatorsTest) (18.348)
✓ Pass: caffe2/torch/fb/sparsenn:test - test_self_binning_histogram_quantile_simple (caffe2.torch.fb.sparsenn.tests.sparsenn_operators_test.SparseNNOperatorsTest) (18.370)
✓ Pass: caffe2/torch/fb/sparsenn:test - test_recat_embedding_grad_output_mixed_D_batch (caffe2.torch.fb.sparsenn.tests.sparsenn_operators_test.SparseNNOperatorsTest) (18.516)
✓ Pass: caffe2/torch/fb/sparsenn:test - test_xl_embedding_bag_byte_rowwise_offsets (caffe2.torch.fb.sparsenn.tests.sparsenn_operators_test.SparseNNOperatorsTest) (18.515)
✓ Pass: caffe2/torch/fb/sparsenn:test - test_offsets_to_ranges (caffe2.torch.fb.sparsenn.tests.sigrid_transforms_test.SigridTransformsOpsTest) (18.861)
✓ Pass: caffe2/torch/fb/sparsenn:test - test_xl_embedding_bags (caffe2.torch.fb.sparsenn.tests.sparsenn_operators_test.SparseNNOperatorsTest) (18.873)
✓ Pass: caffe2/torch/fb/sparsenn:test - test_offsets_to_ranges_out (caffe2.torch.fb.sparsenn.tests.sigrid_transforms_test.SigridTransformsOpsTest) (18.969)
✓ Pass: caffe2/torch/fb/sparsenn:test - test_pack_segments_pad_minf (caffe2.torch.fb.sparsenn.tests.sparsenn_operators_test.SparseNNOperatorsTest) (19.104)
✓ Pass: caffe2/torch/fb/sparsenn:test - test_deprecated_multiple_runs (caffe2.torch.fb.sparsenn.tests.sigrid_transforms_test.SigridTransformsOpsTest) (19.342)
✓ Pass: caffe2/torch/fb/sparsenn:test - test_deprecated_sigrid_transform (caffe2.torch.fb.sparsenn.tests.sigrid_transforms_test.SigridTransformsOpsTest) (19.664)
✓ Pass: caffe2/torch/fb/sparsenn:test - test_offsets_to_ranges_out_empty_batch (caffe2.torch.fb.sparsenn.tests.sigrid_transforms_test.SigridTransformsOpsTest) (19.745)
✓ Pass: caffe2/torch/fb/sparsenn:test - test_clip_lengths (caffe2.torch.fb.sparsenn.tests.sparsenn_operators_test.SparseNNOperatorsTest) (19.771)
✓ Pass: caffe2/torch/fb/sparsenn:test - test_multiple_runs_torch_bind (caffe2.torch.fb.sparsenn.tests.sigrid_transforms_test.SigridTransformsOpsTest) (19.944)
✓ Pass: caffe2/torch/fb/sparsenn:test - test_offsets_to_ranges_empty_batch (caffe2.torch.fb.sparsenn.tests.sigrid_transforms_test.SigridTransformsOpsTest) (19.944)
✓ Pass: caffe2/torch/fb/sparsenn:test - test_gather_ranges_shape_inference_mode (caffe2.torch.fb.sparsenn.tests.sparsenn_operators_test.SparseNNOperatorsTest) (20.245)
✓ Pass: caffe2/torch/fb/sparsenn:test - test_prior_correction_calibration_prediction_nonbinary (caffe2.torch.fb.sparsenn.tests.sparsenn_operators_test.SparseNNOperatorsTest) (20.328)
✓ Pass: caffe2/torch/fb/sparsenn:test - test_8bitfakefused (caffe2.torch.fb.sparsenn.tests.sparsenn_operators_test.SparseNNOperatorsTest) (20.501)
✓ Pass: caffe2/torch/fb/sparsenn:test - test_deprecated_ranges (caffe2.torch.fb.sparsenn.tests.sigrid_transforms_test.SigridTransformsOpsTest) (20.608)
✓ Pass: caffe2/torch/fb/sparsenn:test - test_clip_lengths_inference_tests (caffe2.torch.fb.sparsenn.tests.sparsenn_operators_test.SparseNNOperatorsTest) (22.403)
✓ Pass: caffe2/torch/fb/sparsenn:test - test_broadcast_cat_out (caffe2.torch.fb.sparsenn.tests.sparsenn_operators_test.SparseNNOperatorsTest) (23.025)
✓ Pass: caffe2/torch/fb/sparsenn:test - test_clip_lengths_negatives_tests (caffe2.torch.fb.sparsenn.tests.sparsenn_operators_test.SparseNNOperatorsTest) (23.956)
✓ Pass: caffe2/torch/fb/sparsenn:test - test_broadcast_cat (caffe2.torch.fb.sparsenn.tests.sparsenn_operators_test.SparseNNOperatorsTest) (24.100)
✓ Pass: caffe2/torch/fb/sparsenn:test - test_transform_torch_bind (caffe2.torch.fb.sparsenn.tests.sigrid_transforms_test.SigridTransformsOpsTest) (17.384)
✓ Pass: caffe2/torch/fb/sparsenn:test - test_expand_values_scores_tensor (caffe2.torch.fb.sparsenn.tests.sigrid_transforms_test.SigridTransformsOpsTest) (18.672)
✓ Pass: caffe2/torch/fb/sparsenn:test - test_expand_empty_values_scores_tensor (caffe2.torch.fb.sparsenn.tests.sigrid_transforms_test.SigridTransformsOpsTest) (18.679)
✓ Pass: caffe2/torch/fb/sparsenn:test - test_pack_segments (caffe2.torch.fb.sparsenn.tests.sparsenn_operators_test.SparseNNOperatorsTest) (17.726)
✓ Pass: caffe2/torch/fb/sparsenn:test - test_expand_ranges_tensor (caffe2.torch.fb.sparsenn.tests.sigrid_transforms_test.SigridTransformsOpsTest) (17.567)
✓ Pass: caffe2/torch/fb/sparsenn:test - test_batch_box_cox_all_zeros (caffe2.torch.fb.sparsenn.tests.sparsenn_operators_test.SparseNNOperatorsTest) (19.036)
✓ Pass: caffe2/torch/fb/sparsenn:test - test_rowwise_prune_op_32bit_indices (caffe2.torch.fb.sparsenn.tests.sparsenn_operators_test.SparseNNOperatorsTest) (18.430)
✓ Pass: caffe2/torch/fb/sparsenn:test - test_transform_torch_bind_upper_bound (caffe2.torch.fb.sparsenn.tests.sigrid_transforms_test.SigridTransformsOpsTest) (18.176)
✓ Pass: caffe2/torch/fb/sparsenn:test - test_expand_dense_feature_tensor (caffe2.torch.fb.sparsenn.tests.sigrid_transforms_test.SigridTransformsOpsTest) (19.006)
✓ Pass: caffe2/torch/fb/sparsenn:test - test_clip_ranges_gather (caffe2.torch.fb.sparsenn.tests.sparsenn_operators_test.SparseNNOperatorsTest) (18.555)
✓ Pass: caffe2/torch/fb/sparsenn:test - test_xl_int_nbit_split_embedding_codegen_lookup_function (caffe2.torch.fb.sparsenn.tests.sparsenn_operators_test.SparseNNOperatorsTest) (18.791)
✓ Pass: caffe2/torch/fb/sparsenn:test - test_pack_segments_smaller_max_len (caffe2.torch.fb.sparsenn.tests.sparsenn_operators_test.SparseNNOperatorsTest) (18.737)
✓ Pass: caffe2/torch/fb/sparsenn:test - test_self_binning_histogram_quantile_pos (caffe2.torch.fb.sparsenn.tests.sparsenn_operators_test.SparseNNOperatorsTest) (20.212)
✓ Pass: caffe2/torch/fb/sparsenn:test - test_xl_embedding_bag_2bit_rowwise_offsets (caffe2.torch.fb.sparsenn.tests.sparsenn_operators_test.SparseNNOperatorsTest) (18.612)
✓ Pass: caffe2/torch/fb/sparsenn:test - test_prior_correction_calibration_prediction_binary (caffe2.torch.fb.sparsenn.tests.sparsenn_operators_test.SparseNNOperatorsTest) (20.858)
✓ Pass: caffe2/torch/fb/sparsenn:test - test_tracing_torch_bind_upper_bound (caffe2.torch.fb.sparsenn.tests.sigrid_transforms_test.SigridTransformsOpsTest) (19.002)
✓ Pass: caffe2/torch/fb/sparsenn:test - test_deprecated_tracing (caffe2.torch.fb.sparsenn.tests.sigrid_transforms_test.SigridTransformsOpsTest) (20.824)
✓ Pass: caffe2/torch/fb/sparsenn:test - test_self_binning_histogram_quantile_1d_counts (caffe2.torch.fb.sparsenn.tests.sparsenn_operators_test.SparseNNOperatorsTest) (18.976)
✓ Pass: caffe2/torch/fb/sparsenn:test - test_recat_embedding_grad_output_mixed_D (caffe2.torch.fb.sparsenn.tests.sparsenn_operators_test.SparseNNOperatorsTest) (19.832)
✓ Pass: caffe2/torch/fb/sparsenn:test - test_batch_one_hot_lengths (caffe2.torch.fb.sparsenn.tests.sparsenn_operators_test.SparseNNOperatorsTest) (19.844)
✓ Pass: caffe2/torch/fb/sparsenn:test - test_clip_ranges (caffe2.torch.fb.sparsenn.tests.sparsenn_operators_test.SparseNNOperatorsTest) (18.558)
✓ Pass: caffe2/torch/fb/sparsenn:test - test_batch_box_cox_non_zeros (caffe2.torch.fb.sparsenn.tests.sparsenn_operators_test.SparseNNOperatorsTest) (19.418)
✓ Pass: caffe2/torch/fb/sparsenn:test - test_prior_correction_calibration_accumulate (caffe2.torch.fb.sparsenn.tests.sparsenn_operators_test.SparseNNOperatorsTest) (19.222)
✓ Pass: caffe2/torch/fb/sparsenn:test - test_unsqueeze_vector (caffe2.torch.fb.sparsenn.tests.sparsenn_operators_test.SparseNNOperatorsTest) (19.327)
✓ Pass: caffe2/torch/fb/sparsenn:test - test_xl_embedding_bag_4bit_rowwise_offsets (caffe2.torch.fb.sparsenn.tests.sparsenn_operators_test.SparseNNOperatorsTest) (17.772)
✓ Pass: caffe2/torch/fb/sparsenn:test - test_self_binning_histogram_quantile (caffe2.torch.fb.sparsenn.tests.sparsenn_operators_test.SparseNNOperatorsTest) (18.425)
✓ Pass: caffe2/torch/fb/sparsenn:test - test_broadcast_cat_backward (caffe2.torch.fb.sparsenn.tests.sparsenn_operators_test.SparseNNOperatorsTest) (17.956)
✓ Pass: caffe2/torch/fb/sparsenn:test - test_expand_offsets_tensor (caffe2.torch.fb.sparsenn.tests.sigrid_transforms_test.SigridTransformsOpsTest) (19.320)
✓ Pass: caffe2/torch/fb/sparsenn:test - test_gather_ranges (caffe2.torch.fb.sparsenn.tests.sparsenn_operators_test.SparseNNOperatorsTest) (17.923)
✓ Pass: caffe2/torch/fb/sparsenn:test - test_batch_one_hot (caffe2.torch.fb.sparsenn.tests.sparsenn_operators_test.SparseNNOperatorsTest) (18.549)
✓ Pass: caffe2/torch/fb/sparsenn:test - test_deprecated_sigrid_transforms_create (caffe2.torch.fb.sparsenn.tests.sigrid_transforms_test.SigridTransformsOpsTest) (18.932)
✓ Pass: caffe2/torch/fb/sparsenn:test - test_clip_ranges_gather_lengths_to_offsets (caffe2.torch.fb.sparsenn.tests.sparsenn_operators_test.SparseNNOperatorsTest) (18.807)
✓ Pass: caffe2/torch/fb/sparsenn:test - test_length_to_row_idx (caffe2.torch.fb.sparsenn.tests.sparsenn_operators_test.SparseNNOperatorsTest) (17.738)
✓ Pass: caffe2/torch/fb/sparsenn:test - test_tracing_torch_bind (caffe2.torch.fb.sparsenn.tests.sigrid_transforms_test.SigridTransformsOpsTest) (20.175)
✓ Pass: caffe2/torch/fb/sparsenn:test - test_batch_box_cox_mixed (caffe2.torch.fb.sparsenn.tests.sparsenn_operators_test.SparseNNOperatorsTest) (18.116)
✓ Pass: caffe2/torch/fb/sparsenn:test - test_self_binning_histogram_quantile_1d_bins (caffe2.torch.fb.sparsenn.tests.sparsenn_operators_test.SparseNNOperatorsTest) (18.671)
✓ Pass: caffe2/torch/fb/sparsenn:test - test_permute_out (caffe2.torch.fb.sparsenn.tests.sparsenn_operators_test.SparseNNOperatorsTest) (19.002)
✓ Pass: caffe2/torch/fb/sparsenn:test - test_create_sigrid_transforms_torch_bind (caffe2.torch.fb.sparsenn.tests.sigrid_transforms_test.SigridTransformsOpsTest) (18.151)
✓ Pass: caffe2/torch/fb/sparsenn:test - test_ranges_torch_bind (caffe2.torch.fb.sparsenn.tests.sigrid_transforms_test.SigridTransformsOpsTest) (16.780)
✓ Pass: caffe2/torch/fb/sparsenn:test - test_self_binning_histogram_quantile_no_bins (caffe2.torch.fb.sparsenn.tests.sparsenn_operators_test.SparseNNOperatorsTest) (19.185)
✓ Pass: caffe2/torch/fb/sparsenn:test - test_cumsum (caffe2.torch.fb.sparsenn.tests.sparsenn_operators_test.SparseNNOperatorsTest) (19.242)
✓ Pass: caffe2/torch/fb/sparsenn:test - test_self_binning_histogram_quantile_le_one (caffe2.torch.fb.sparsenn.tests.sparsenn_operators_test.SparseNNOperatorsTest) (19.876)
✓ Pass: caffe2/torch/fb/sparsenn:test - test_pack_and_unpack_segments (caffe2.torch.fb.sparsenn.tests.sparsenn_operators_test.SparseNNOperatorsTest) (19.222)
✓ Pass: caffe2/torch/fb/sparsenn:test - test_self_binning_histogram_quantile_dims (caffe2.torch.fb.sparsenn.tests.sparsenn_operators_test.SparseNNOperatorsTest) (20.007)
✓ Pass: caffe2/torch/fb/sparsenn:test - test_sigrid_hash_op (caffe2.torch.fb.sparsenn.tests.sparsenn_operators_test.SparseNNOperatorsTest) (18.959)
✓ Pass: caffe2/torch/fb/sparsenn:test - test_rowwise_prune_op_64bit_indices (caffe2.torch.fb.sparsenn.tests.sparsenn_operators_test.SparseNNOperatorsTest) (18.601)
✓ Pass: caffe2/torch/fb/sparsenn:test - test_ranges_torch_bind_upper_bound (caffe2.torch.fb.sparsenn.tests.sigrid_transforms_test.SigridTransformsOpsTest) (17.977)
✓ Pass: caffe2/torch/fb/sparsenn:test - test_broadcast_stack (caffe2.torch.fb.sparsenn.tests.sparsenn_operators_test.SparseNNOperatorsTest) (22.588)
✓ Pass: caffe2/torch/fb/sparsenn:test - test_multiple_runs_torch_bind_upper_bound (caffe2.torch.fb.sparsenn.tests.sigrid_transforms_test.SigridTransformsOpsTest) (15.342)
Summary
Pass: 73
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/
3377699789132066
Did not run (no GPU on my devserver):
gpu_test
cpp_gpu_test
Reviewed By: r-barnes
Differential Revision:
D30940399
fbshipit-source-id:
d867ca646723340775a49c1b983cdab64f2d67d8
Priya Ramani [Thu, 16 Sep 2021 03:03:38 +0000 (20:03 -0700)]
Bug fix (#65105)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/65105
Using buildErrorMessage in external_functions.cpp was breaking build target nnc_cpu_backend_lib as buildErrorMessage is defined in tensorexpr/kernel.cpp which is not included in mobile builds and we don't want to include it in mobile builds.
Also buildErrorMessage wraps error messages for fuser whereas nnc_aten_conv2d is now only used in AOT workflow and not called by the fuser. So wrapping assertion failures with fuser error message would be misleading for AOT workflow.
Test Plan:
Before fix:
```
+ buck build //xplat/caffe2/fb/lite_predictor:lite_predictor_nnc
Downloading... 3/3 artifacts, 24.81 Kbytes, 0.0% cache miss (for updated rules)
Building... 1.7 sec (99%) 4639/4641 jobs, 3/4641 updated
- //xplat/caffe2/fb/lite_predictor:lite_predictor_nnc#binary... 0.7 sec (running c++ link[0.6 sec])
Command failed with exit code 1.
command: [/data/users/priyaramani/fbsource/buck-out/cells/fbcode/gen/
aab7ed39/tools/build/buck/wrappers/__ld__/ld.sh, --ld=/data/users/priyaramani/fbsource/fbcode/third-party-buck/platform009/build/llvm-fb/9.0.0/bin/clang++, --cc=/data/users/priyaramani/fbsource/buck-out/cells/fbcode/gen/
aab7ed39/tools/build/buck/wrappers/__fbc...
<truncated>
...
stderr: clang-9: warning: argument unused during compilation: '-pthread' [-Wunused-command-line-argument]
ld.lld: error: undefined symbol: torch::jit::tensorexpr::buildErrorMessage(std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&)
>>> referenced by external_functions.cpp:69 (xplat/caffe2/torch/csrc/jit/tensorexpr/external_functions.cpp:69)
>>> ../nnc_cpu_backend_lib#compile-external_functions.cpp.o50e02bc2,platform009-clang/torch/csrc/jit/tensorexpr/external_functions.cpp.o:(nnc_aten_conv2d) in archive /data/users/priyaramani/fbsource/buck-out/gen/
aab7ed39/xplat/caffe2/nnc_cpu_backend_lib#platform009-clang,static/libnnc_cpu_backend_lib.a
clang-9: error: linker command failed with exit code 1 (use -v to see invocation)
When running <c++ link>.
When building rule //xplat/caffe2/fb/lite_predictor:lite_predictor_nnc#binary (ovr_config//platform/linux:x86_64-fbcode).
clang-9: warning: argument unused during compilation: '-pthread' [-Wunused-command-line-argument]
ld.lld: error: undefined symbol: torch::jit::tensorexpr::buildErrorMessage(std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&)
>>> referenced by external_functions.cpp:69 (xplat/caffe2/torch/csrc/jit/tensorexpr/external_functions.cpp:69)
>>> ../nnc_cpu_backend_lib#compile-external_functions.cpp.o50e02bc2,platform009-clang/torch/csrc/jit/tensorexpr/external_functions.cpp.o:(nnc_aten_conv2d) in archive /data/users/priyaramani/fbsource/buck-out/gen/
aab7ed39/xplat/caffe2/nnc_cpu_backend_lib#platform009-clang,static/libnnc_cpu_backend_lib.a
clang-9: error: linker command failed with exit code 1 (use -v to see invocation)
Command failed with exit code 1.
command: [/data/users/priyaramani/fbsource/buck-out/cells/fbcode/gen/
aab7ed39/tools/build/buck/wrappers/__ld__/ld.sh, --ld=/data/users/priyaramani/fbsource/fbcode/third-party-buck/platform009/build/llvm-fb/9.0.0[DEBUG kernel.cpp:2766] }
```
After fix:
```
+ buck build //xplat/caffe2/fb/lite_predictor:lite_predictor_nnc
Action graph will be rebuilt because files have been added or removed.
clang-9: warning: argument unused during compilation: '-pthread' [-Wunused-command-line-argument]
Downloaded 11/15 artifacts, 78.37 Kbytes, 15.4% cache miss (for updated rules)
Building: finished in 7.4 sec (100%) 4718/4718 jobs, 46/4718 updated
Total time: 7.5 sec
More details at https://www.internalfb.com/intern/buck/build/
b87be016-340c-49f8-b832-
0c1de70aae9e
```
Reviewed By: ZolotukhinM
Differential Revision:
D30975952
fbshipit-source-id:
85c028cc6af63c03b505b51302f5158c23e1a047
Jordan Fix [Thu, 16 Sep 2021 02:39:41 +0000 (19:39 -0700)]
[acc_ops] Add support for torch variants of squeeze and mul (#65037)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/65037
att
Test Plan: updated unit tests
Reviewed By: yuhc
Differential Revision:
D30952224
fbshipit-source-id:
aaf75b27b4fc6c0436ba7bfcf324f761b900171b
Priya Ramani [Thu, 16 Sep 2021 02:12:47 +0000 (19:12 -0700)]
Add NNC AOT Compiler executable (#63994)
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/63994
Test Plan: Imported from OSS
Reviewed By: bertmaher
Differential Revision:
D30582149
Pulled By: priyaramani
fbshipit-source-id:
3bbf085428824c3cb308e006c18bb0a57f50fef6
Zafar Takhirov [Thu, 16 Sep 2021 01:13:53 +0000 (18:13 -0700)]
[quant] AO migration of the `_correct_bias.py`, `_equalize.py`, and `_learnable_fake_quantize.py` (#64917)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/64917
AO Team is migrating the existing torch.quantization into torch.ao.quantization. We are doing it one file at a time to make sure that the internal callsites are updated properly.
This migrates from torch.quantization to torch.ao.quantization the following files:
- `_correct_bias.py`
- `_equalize.py`
- `_learnable_fake_quantize.py`
**Note:** These file are migrated completely without any warning. The old location is thus silently deprecated.
Test Plan: `buck test mode/dev //caffe2/test:quantization -- TestBiasCorrection`
Reviewed By: vkuzo
Differential Revision:
D30898565
fbshipit-source-id:
1d39be2539dd1adfcb42e16bdcc0daf5c8316bbd
Jane Xu [Thu, 16 Sep 2021 01:03:19 +0000 (18:03 -0700)]
.circleci/.jenkins: Remove 9.2 references in CI (#65024)
Summary:
Removes 9.2 references in CI scripts and configs.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/65024
Reviewed By: driazati
Differential Revision:
D30945948
Pulled By: janeyx99
fbshipit-source-id:
77890a00520c61500a934a90a74e3fcca84c09b5
Jane Xu [Thu, 16 Sep 2021 01:00:24 +0000 (18:00 -0700)]
.github: GHA add retry for docker run in chown workspace step (#65104)
Summary:
This should help prevent further errors in GHA workflows during the Chown Workspace step such as https://github.com/pytorch/pytorch/runs/
3614067053
I did not add retries to other steps with docker run
Pull Request resolved: https://github.com/pytorch/pytorch/pull/65104
Reviewed By: seemethere
Differential Revision:
D30976330
Pulled By: janeyx99
fbshipit-source-id:
e403008548aa01c9a0a4ccebe56df0e889dd045c
Eli Uriegas [Thu, 16 Sep 2021 00:37:10 +0000 (17:37 -0700)]
Revert
D30752939: [pytorch][PR] nvfuser update
Test Plan: revert-hammer
Differential Revision:
D30752939 (https://github.com/pytorch/pytorch/commit/
cfaecaf40bd6cabd3f4e0ef0d8c7252655349b61)
Original commit changeset:
ce122e80f01b
fbshipit-source-id:
57685df8f9946032a06eff1de8a3d1498500d2d2
Zafar Takhirov [Thu, 16 Sep 2021 00:24:09 +0000 (17:24 -0700)]
[quant] AO migration of the `quant_types.py` (phase 1) (#64916)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/64916
AO Team is migrating the existing torch.quantization into torch.ao.quantization. We are doing it one file at a time to make sure that the internal callsites are updated properly.
This migrates the quant_type.py from torch.quantization to torch.ao.quantization.
At this point both locations will be supported. Eventually the torch.quantization will be deprecated.
Test Plan: `buck test mode/dev //caffe2/test:quantization -- TestAOMigrationQuantization`
Reviewed By: vkuzo
Differential Revision:
D30898422
fbshipit-source-id:
3e6126b49f0565a4136d6928cea9eb25368927ff
Zafar Takhirov [Thu, 16 Sep 2021 00:24:09 +0000 (17:24 -0700)]
[quant] AO migration of the `fuse_modules.py` (phase 1) (#64913)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/64913
AO Team is migrating the existing torch.quantization into torch.ao.quantization. We are doing it one file at a time to make sure that the internal callsites are updated properly.
This migrates the fuse_module.py from torch.quantization to torch.ao.quantization.
At this point both locations will be supported. Eventually the torch.quantization will be deprecated.
Test Plan: `buck test mode/dev //caffe2/test:quantization`
Reviewed By: vkuzo
Differential Revision:
D30882819
fbshipit-source-id:
1926ad6aa49136aceb5b625dcef4bfde3a2860d4
Mikhail Zolotukhin [Thu, 16 Sep 2021 00:13:48 +0000 (17:13 -0700)]
[TensorExpr] Add a method for sanitizing Var and Buf names in Stmt. (#65010)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/65010
This pass ensures all names are legal and not-duplicated.
Fixes #52727.
Test Plan: Imported from OSS
Reviewed By: bertmaher, navahgar
Differential Revision:
D30939717
Pulled By: ZolotukhinM
fbshipit-source-id:
7dbe7f937de41f22ad49137a5e067d698443ed63
Eli Uriegas [Wed, 15 Sep 2021 23:51:34 +0000 (16:51 -0700)]
.github: Enable only specific workflows for canary (#65099)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/65099
Utilizes ciflow to enable only specific workflows for
pytorch/pytorch-canary to reduce noise on that specific repository
Signed-off-by: Eli Uriegas <eliuriegas@fb.com>
Test Plan: Imported from OSS
Reviewed By: jbschlosser
Differential Revision:
D30973691
Pulled By: seemethere
fbshipit-source-id:
371765535b42a00bd72c2551c4faebf733d759f0
Eli Uriegas [Wed, 15 Sep 2021 23:09:57 +0000 (16:09 -0700)]
ci: Disable jit legacy on circleci, enable on gha (#65106)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/65106
Signed-off-by: Eli Uriegas <eliuriegas@fb.com>
cc ezyang seemethere malfet lg20987 pytorch/pytorch-dev-infra
Test Plan: Imported from OSS
Reviewed By: malfet, janeyx99
Differential Revision:
D30976186
Pulled By: seemethere
fbshipit-source-id:
8958f821eab9aa284496c57915894ed70f6b2fff
Jane Xu [Wed, 15 Sep 2021 22:59:21 +0000 (15:59 -0700)]
CI: Upgrade windows 10.1 jobs to 10.2 (#65080)
Summary:
This is first 2 steps in the following task:
1. Upgrade 10.1 to 10.2
2. Migrate force_on_cpu job to GHA
Pull Request resolved: https://github.com/pytorch/pytorch/pull/65080
Test Plan: https://github.com/pytorch/pytorch/pull/65086
Reviewed By: seemethere
Differential Revision:
D30973655
Pulled By: janeyx99
fbshipit-source-id:
67ab69ea99ff9e0336400a7173efef6d7daac07c
Jane Xu [Wed, 15 Sep 2021 22:59:06 +0000 (15:59 -0700)]
Replace windows 10.2 smoke tests on PRs to be 11.3 (#65090)
Summary:
As we default to linux CUDA 11.3 on PRs, we should do the same thing with Windows (instead of having 10.2 be the default). This means that 10.2 will now be master only, and 11.3 windows smoke tests will run on every PR.
This also copies over the "run smoke tests only" config--removing that will be in a separate PR once there's more certain decision making.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/65090
Reviewed By: seemethere
Differential Revision:
D30968382
Pulled By: janeyx99
fbshipit-source-id:
c73f9a2cc800b678909365c4d80627d29fc09f94