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2021-07-22[skip ci] minor typo link fix (#62042)Jane Xu1-1/+1
Summary: This is not a functional change but a typo fix where I forgot to update the link to windows_smoke_tests.csv in test_python_first_shard. The windows_smoke_tests.csv is currently the same in pytorch/test-infra and my fork, janeyx99/test-infra, but that will not be the case in the future. Pull Request resolved: https://github.com/pytorch/pytorch/pull/62042 Reviewed By: seemethere Differential Revision: D29851984 Pulled By: janeyx99 fbshipit-source-id: 9bafdf0ba006b9128463e3cf132fdfcddd3d10f2
2021-07-22Add build/.ninja_log to artifacts for Windows (#62035)Jane Xu1-0/+3
Summary: Being able to download the .ninja_log allows for better debugging. There may be a follow-up PR to convert this to a better tracefile. This PR only handles windows as it is already handled for linux here: https://github.com/pytorch/pytorch/blob/master/.jenkins/pytorch/build.sh#L248-L252 Pull Request resolved: https://github.com/pytorch/pytorch/pull/62035 Test Plan: Check the artifacts for a windows job and see if we see .ninja_log Reviewed By: malfet Differential Revision: D29852228 Pulled By: janeyx99 fbshipit-source-id: a3a87b709cd0c84f5b3cdc274ac4a623771c2b5c
2021-07-22Add AVX512 support in ATen & remove AVX support (#61903)imaginary-person1-1/+3
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/61903 ### Remaining Tasks - [ ] Collate results of benchmarks on two Intel Xeon machines (with & without CUDA, to check if CPU throttling causes issues with GPUs) - make graphs, including Roofline model plots (Intel Advisor can't make them with libgomp, though, but with Intel OpenMP). ### Summary 1. This draft PR produces binaries with with 3 types of ATen kernels - default, AVX2, AVX512 . Using the environment variable `ATEN_AVX512_256=TRUE` also results in 3 types of kernels, but the compiler can use 32 ymm registers for AVX2, instead of the default 16. ATen kernels for `CPU_CAPABILITY_AVX` have been removed. 2. `nansum` is not using AVX512 kernel right now, as it has poorer accuracy for Float16, than does AVX2 or DEFAULT, whose respective accuracies aren't very good either (#59415). It was more convenient to disable AVX512 dispatch for all dtypes of `nansum` for now. 3. On Windows , ATen Quantized AVX512 kernels are not being used, as quantization tests are flaky. If `--continue-through-failure` is used, then `test_compare_model_outputs_functional_static` fails. But if this test is skipped, `test_compare_model_outputs_conv_static` fails. If both these tests are skipped, then a third one fails. These are hard to debug right now due to not having access to a Windows machine with AVX512 support, so it was more convenient to disable AVX512 dispatch of all ATen Quantized kernels on Windows for now. 4. One test is currently being skipped - [test_lstm` in `quantization.bc](https://github.com/pytorch/pytorch/issues/59098) - It fails only on Cascade Lake machines, irrespective of the `ATEN_CPU_CAPABILITY` used, because FBGEMM uses `AVX512_VNNI` on machines that support it. The value of `reduce_range` should be used as `False` on such machines. The list of the changes is at https://gist.github.com/imaginary-person/4b4fda660534f0493bf9573d511a878d. Credits to ezyang for proposing `AVX512_256` - these use AVX2 intrinsics but benefit from 32 registers, instead of the 16 ymm registers that AVX2 uses. Credits to limo1996 for the initial proposal, and for optimizing `hsub_pd` & `hadd_pd`, which didn't have direct AVX512 equivalents, and are being used in some kernels. He also refactored `vec/functional.h` to remove duplicated code. Credits to quickwritereader for helping fix 4 failing complex multiplication & division tests. ### Testing 1. `vec_test_all_types` was modified to test basic AVX512 support, as tests already existed for AVX2. Only one test had to be modified, as it was hardcoded for AVX2. 2. `pytorch_linux_bionic_py3_8_gcc9_coverage_test1` & `pytorch_linux_bionic_py3_8_gcc9_coverage_test2` are now using `linux.2xlarge` instances, as they support AVX512. They were used for testing AVX512 kernels, as AVX512 kernels are being used by default in both of the CI checks. Windows CI checks had already been using machines with AVX512 support. ### Would the downclocking caused by AVX512 pose an issue? I think it's important to note that AVX2 causes downclocking as well, and the additional downclocking caused by AVX512 may not hamper performance on some Skylake machines & beyond, because of the double vector-size. I think that [this post with verifiable references is a must-read](https://community.intel.com/t5/Software-Tuning-Performance/Unexpected-power-vs-cores-profile-for-MKL-kernels-on-modern-Xeon/m-p/1133869/highlight/true#M6450). Also, AVX512 would _probably not_ hurt performance on a high-end machine, [but measurements are recommended](https://lemire.me/blog/2018/09/07/avx-512-when-and-how-to-use-these-new-instructions/). In case it does, `ATEN_AVX512_256=TRUE` can be used for building PyTorch, as AVX2 can then use 32 ymm registers instead of the default 16. [FBGEMM uses `AVX512_256` only on Xeon D processors](https://github.com/pytorch/FBGEMM/pull/209), which are said to have poor AVX512 performance. This [official data](https://www.intel.com/content/dam/www/public/us/en/documents/specification-updates/xeon-scalable-spec-update.pdf) is for the Intel Skylake family, and the first link helps understand its significance. Cascade Lake & Ice Lake SP Xeon processors are said to be even better when it comes to AVX512 performance. Here is the corresponding data for [Cascade Lake](https://cdrdv2.intel.com/v1/dl/getContent/338848) - ![CASCADE LAKE AVX2](https://user-images.githubusercontent.com/76181208/120666172-ffec3f80-c451-11eb-8ea1-8933ccc12a1b.PNG) ![CASCADE LAKE AVX512](https://user-images.githubusercontent.com/76181208/120666190-04b0f380-c452-11eb-9faa-38d233c874c8.PNG) The corresponding data isn't publicly available for Intel Xeon SP 3rd gen (Ice Lake SP), but [Intel mentioned that the 3rd gen has frequency improvements pertaining to AVX512](https://newsroom.intel.com/wp-content/uploads/sites/11/2021/04/3rd-Gen-Intel-Xeon-Scalable-Platform-Press-Presentation-281884.pdf). Ice Lake SP machines also have 48 KB L1D caches, so that's another reason for AVX512 performance to be better on them. ### Is PyTorch always faster with AVX512? No, but then PyTorch is not always faster with AVX2 either. Please refer to #60202. The benefit from vectorization is apparent with with small tensors that fit in caches or in kernels that are more compute heavy. For instance, AVX512 or AVX2 would yield no benefit for adding two 64 MB tensors, but adding two 1 MB tensors would do well with AVX2, and even more so with AVX512. It seems that memory-bound computations, such as adding two 64 MB tensors can be slow with vectorization (depending upon the number of threads used), as the effects of downclocking can then be observed. Original pull request: https://github.com/pytorch/pytorch/pull/56992 Reviewed By: soulitzer Differential Revision: D29266289 Pulled By: ezyang fbshipit-source-id: 2d5e8d1c2307252f22423bbc14f136c67c3e6184
2021-07-21Run Windows smoke tests with gflags in test dir (#61967)Jane Xu1-1/+2
Summary: Previous testing yielded the torch.version ModuleNotFound error when I ran the smoke tests from the pytorch root directory. This PR simply reorders the commands to run the smoke tests within the test directory, which passes in this series of runs: https://github.com/seemethere/test-repo/actions/runs/1050734298 (the failures are due to missing credentials during uploading stats, which we don't need here) Pull Request resolved: https://github.com/pytorch/pytorch/pull/61967 Reviewed By: samestep Differential Revision: D29820985 Pulled By: janeyx99 fbshipit-source-id: 363ef321c32cfaf4446ceeb6117ea26abc311816
2021-07-19Fix benchmark's import module and remove its usage of tools.stats.scribe ↵zhouzhuojie1-3/+3
(#61808) Summary: There're a few convoluted logic here to fix the `benchmarks`'s import module for pytest. - On one hand, if we want to use `tools.stats.scribe` from `benchmarks`, we will need to add `benchmarks/__init__.py` - On the other hand, if we add `benchmarks/__init__.py`, it breaks how `pytest` is working on searching what is the system built `torch` instead of the local source module `../torch` - That's why we are seeing errors like ``` ImportError while loading conftest '/var/lib/jenkins/workspace/benchmarks/fastrnns/conftest.py'. benchmarks/fastrnns/__init__.py:1: in <module> from .cells import * # noqa: F403 benchmarks/fastrnns/cells.py:1: in <module> import torch torch/__init__.py:29: in <module> from .torch_version import __version__ as __version__ torch/torch_version.py:9: in <module> from .version import __version__ as internal_version E ModuleNotFoundError: No module named 'torch.version' ``` Instead, this PR changed the usage of `upload_scribe.py` back to its original form using HTTP request, and only circleci for now will continue the this path using the `python benchmarks/upload_scribe.py`, which is gated by `if [[ -z "${GITHUB_ACTIONS}" ]];` Pull Request resolved: https://github.com/pytorch/pytorch/pull/61808 Reviewed By: seemethere Differential Revision: D29750188 Pulled By: zhouzhuojie fbshipit-source-id: 3b842b21978f2159001e9c6c1cdc96c5a0515f2e
2021-07-16Fix scribe logs again (#61768)zhouzhuojie1-3/+3
Summary: revert the revert of 3624d75 with additional fix in https://github.com/pytorch/pytorch/pull/61764 Got the corrent logs sent to lambda ``` ... ,"21721":"OK","21722":"OK","21723":"OK","21724":"OK","21725":"OK","21726":"OK","21727":"OK","21728":"OK","21729":"OK","21730":"OK","21731":"OK","21732":"OK","21733":"OK","21734":"OK","21735":"OK","21736":"OK","21737":"OK","21738":"OK","21739":"OK","21740":"OK","21741":"OK","21742":"OK","21743":"OK","21744":"OK","21745":"OK","21746":"OK","21747":"OK","21748":"OK","21749":"OK","21750":"OK","21751":"OK","21752":"OK","21753":"OK","21754":"OK","21755":"OK","21756":"OK","21757":"OK","21758":"OK","21759":"OK","21760":"OK","21761":"OK","21762":"OK","21763":"OK","21764":"OK","21765":"OK","21766":"OK","21767":"OK","21768":"OK","21769":"OK","21770":"OK","21771":"OK","21772":"OK","21773":"OK","21774":"OK","21775":"OK","21776":"OK","21777":"OK","21778":"OK","21779":"OK","21780":"OK","21781":"OK","21782":"OK","21783":"OK","21784":"OK","21785":"OK","21786":"OK","21787":"OK","21788":"OK","21789":"OK","21790":"OK","21791":"OK","21792":"OK","21793":"OK","21794":"OK","21795":"OK","21796":"OK","21797":"OK","21798":"OK","21799":"OK","21800":"OK","21801":"OK","21802":"OK","21803":"OK","21804":"OK","21805":"OK","21806":"OK","21807":"OK","21808":"OK","21809":"OK","21810":"OK","21811":"OK","21812":"OK","21813":"OK","21814":"OK","21815":"OK","21816":"OK","21817":"OK","21818":"OK","21819":"OK","21820":"OK","21821":"OK","21822":"OK","21823":"OK","21824":"OK","21825":"OK","21826":"OK"}} class StartProcessesTest: tests: 14 failed: 0 skipped: 0 errored: 0 run_time: 4.86 seconds avg_time: 0.35 seconds median_time: 0.01 seconds 3 longest tests: test_function_large_ret_val time: 1.55 seconds test_pcontext_wait time: 1.11 seconds test_void_function time: 1.03 seconds ... ``` Pull Request resolved: https://github.com/pytorch/pytorch/pull/61768 Reviewed By: janeyx99 Differential Revision: D29735781 Pulled By: zhouzhuojie fbshipit-source-id: 6882e334f5108d20773ad66d5300cd37eb509ded
2021-07-16Pin macos mkl conda version to fix the cmake build (#61773)zhouzhuojie1-1/+7
Summary: Fixes macos build error in master, recently mkl had a upgrade. CircleCI error: https://app.circleci.com/pipelines/github/pytorch/pytorch/351645/workflows/d22421c1-bb8f-48fd-9efd-7c0d77f0b083/jobs/14815607 ``` Jul 16 11:43:05 CMake Error at /Users/distiller/workspace/miniconda3/lib/cmake/mkl/MKLConfig.cmake:456 (list): Jul 16 11:43:05 list does not recognize sub-command PREPEND Jul 16 11:43:05 Call Stack (most recent call first): Jul 16 11:43:05 /Users/distiller/workspace/miniconda3/lib/python3.7/site-packages/torch/share/cmake/Caffe2/public/mkl.cmake:1 (find_package) Jul 16 11:43:05 /Users/distiller/workspace/miniconda3/lib/python3.7/site-packages/torch/share/cmake/Caffe2/Caffe2Config.cmake:109 (include) Jul 16 11:43:05 /Users/distiller/workspace/miniconda3/lib/python3.7/site-packages/torch/share/cmake/Torch/TorchConfig.cmake:68 (find_package) Jul 16 11:43:05 CMakeLists.txt:5 (find_package) ``` Pull Request resolved: https://github.com/pytorch/pytorch/pull/61773 Reviewed By: soulitzer Differential Revision: D29736742 Pulled By: zhouzhuojie fbshipit-source-id: 68c5244196f7f7562a6c202157c4ccdcfcb64337
2021-07-09Add other Linux GPU auxiliary test jobs (#61055)Sam Estep1-5/+5
Summary: - [x] add the jobs to the matrix - [x] `jit_legacy` - [x] `nogpu_NO_AVX` - [x] `nogpu_NO_AVX2` - [x] `slow` - [x] use the test config properly to enable the different test conditions - [x] validate that it works - [x] disable on pull requests before merging Pull Request resolved: https://github.com/pytorch/pytorch/pull/61055 Test Plan: CI. Example run: https://github.com/pytorch/pytorch/actions/runs/1013240987 Reviewed By: walterddr Differential Revision: D29594080 Pulled By: samestep fbshipit-source-id: 02c531ebc42feae81ecaea0785915f95e0f53ed7
2021-07-08.github: Ensure build-results per job is unique (#61005)Eli Uriegas1-1/+1
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/61005 build-results have the potential to be tainted between jobs since runs are not ephemeral Signed-off-by: Eli Uriegas <seemethere101@gmail.com> Test Plan: Imported from OSS Reviewed By: VitalyFedyunin Differential Revision: D29526747 Pulled By: seemethere fbshipit-source-id: f8c5bc5f647b771a059cbe380d694ce6dc535ae4
2021-07-07Add --jobs 0 for git submodule update (#61311)zhouzhuojie3-3/+3
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/61311 Pull Request resolved: https://github.com/pytorch/pytorch/pull/61152 Some related docs about `submodule.fetchJobs` https://git-scm.com/docs/git-config#Documentation/git-config.txt-submodulefetchJobs ``` time git submodule update --init --recursive ________________________________________________________ Executed in 243.20 secs fish external usr time 49.64 secs 213.00 micros 49.64 secs sys time 29.27 secs 795.00 micros 29.27 secs ``` ``` time git submodule update --init --recursive --jobs 4 ________________________________________________________ Executed in 143.04 secs fish external usr time 51.06 secs 246.00 micros 51.06 secs sys time 30.96 secs 742.00 micros 30.96 secs ``` ``` time git submodule update --init --recursive --jobs 8 ________________________________________________________ Executed in 124.64 secs fish external usr time 51.76 secs 264.00 micros 51.76 secs sys time 30.49 secs 739.00 micros 30.49 secs ``` ``` time git submodule update --init --recursive --jobs 0 # use all online cpus ________________________________________________________ Executed in 129.75 secs fish external usr time 51.64 secs 181.00 micros 51.64 secs sys time 31.49 secs 781.00 micros 31.49 secs ``` Test Plan: Imported from OSS Reviewed By: 1ntEgr8 Differential Revision: D29560875 Pulled By: zhouzhuojie fbshipit-source-id: 556027dffe744c66428075a8a1bf64683930aaaf
2021-06-30[ROCm] allow user to override PYTORCH_ROCM_ARCH (#60602)Jeff Daily2-4/+4
Summary: Restores the ability of a user to call .jenkins/pytorch/build.sh while also setting PYTORCH_ROCM_ARCH. Otherwise, with IN_CI=1 as the new default, it will forcibly ignore user settings when build.sh is used outside of CI. Pull Request resolved: https://github.com/pytorch/pytorch/pull/60602 Reviewed By: samestep Differential Revision: D29490791 Pulled By: janeyx99 fbshipit-source-id: b5e8a529b8e0b5020b260b4bf027a37e0c1df8d5
2021-06-28Use expecttest from PyPI (#60658)Sam Estep3-3/+3
Summary: This PR removes `torch/testing/_internal/expecttest.py` in favor of https://github.com/ezyang/expecttest. See also https://github.com/ezyang/ghstack/pull/71. Pull Request resolved: https://github.com/pytorch/pytorch/pull/60658 Test Plan: CI. Reviewed By: ezyang Differential Revision: D29430763 Pulled By: samestep fbshipit-source-id: b7cdc7ba37330176149fd465312118e2254ae92e
2021-06-28Enable bionic-cuda10.2-cudnn7-py3.9-gcc7 in GHA (#60204)Sam Estep1-1/+3
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/60204 Test Plan: Imported from OSS Reviewed By: malfet Differential Revision: D29430679 Pulled By: samestep fbshipit-source-id: 9380f5535cd370ec7aabf609a6170c8cb4df505d
2021-06-26fix cuda mem leak check not properly run on master_builds (#60742)Rong Rong (AI Infra)1-1/+2
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/60742 improved CI_MASTER flag check logic, since it can be unset, true or false Test Plan: search for `PYTORCH_TEST_SKIP_CUDA_MEM_LEAK_CHECK` in logs below: - Before adding ci/master: - build workflow (`PYTORCH_TEST_SKIP_CUDA_MEM_LEAK_CHECK=1`): https://circleci.com/api/v1.1/project/github/pytorch/pytorch/14394913/output/107/0?file=true&allocation-id=60d5fd2fa55ae50282aec997-0-build%2F10295B30 - After adding ci/master label: - build workflow (`PYTORCH_TEST_SKIP_CUDA_MEM_LEAK_CHECK=0`): https://circleci.com/api/v1.1/project/github/pytorch/pytorch/14398213/output/107/0?file=true&allocation-id=60d61cf8bb9d097afc7a11aa-0-build%2F400138F1 - master build workflow (`PYTORCH_TEST_SKIP_CUDA_MEM_LEAK_CHECK=0`): https://circleci.com/api/v1.1/project/github/pytorch/pytorch/14398198/output/107/0?file=true&allocation-id=60d61ca3467438480c963290-0-build%2F2999C909 Reviewed By: ngimel Differential Revision: D29405732 Pulled By: walterddr fbshipit-source-id: 09dd653cbb47ca61b1f8872851bda6db8db671b9
2021-06-24Adjust path to distributed cpp tests (#60705)Nikita Shulga1-7/+7
Summary: After https://github.com/pytorch/pytorch/issues/60543 they are installed in the same folder as the rest of the tests Pull Request resolved: https://github.com/pytorch/pytorch/pull/60705 Reviewed By: driazati Differential Revision: D29380670 Pulled By: malfet fbshipit-source-id: a432d26c731e9220e00d8c800b1429b37d51655b
2021-06-24Move torch/lib/c10d to torch/csrc/distributed/c10d (#60543)Luca Wehrstedt1-7/+7
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/60543 Since now c10d is part of libtorch, it would also be nice if the sources lived all in one place. ghstack-source-id: 132306292 Test Plan: It builds Reviewed By: cbalioglu Differential Revision: D29062002 fbshipit-source-id: d9e1301e9d73e1643fa0f0119cd2d618f1ad52e6
2021-06-23Add back smoke tests for windows shard 1 for CircleCI (#60571)Jane Xu1-2/+12
Summary: The reason I removed the smoke tests here were because we didn't have gflags on our GHA runners and we wanted to get sharding done sooner rather than later. However, we shouldn't remove these tests for windows as they are important for debugging linker issues with torch. Thus, this is step 1 in adding the tests back. Next step: - add gflags to base ami - remove the exist check Pull Request resolved: https://github.com/pytorch/pytorch/pull/60571 Test Plan: CI shouldn't break Reviewed By: walterddr Differential Revision: D29341850 Pulled By: janeyx99 fbshipit-source-id: 7e0c98887534d096f867e28a5482b32aa493b132
2021-06-23Disable group group backend rpc tests from running on CI (#60407)Howard Huang1-1/+0
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/60407 Test Plan: Imported from OSS Reviewed By: mrshenli Differential Revision: D29278179 Pulled By: H-Huang fbshipit-source-id: ee78085eeb04d81842c95236b8c3a33de7142a3a
2021-06-23Adding windows CUDA smoke tests on PRs (#59686)Jane Xu4-11/+54
Summary: Adding windows CUDA smoke tests on PRs (master should run the full suite). Next step: - Automate data update so we get a new smoke test list without manual effort Pull Request resolved: https://github.com/pytorch/pytorch/pull/59686 Test Plan: https://github.com/pytorch/pytorch/actions/runs/958296267 The sharded smoke tests take long still because of dependencies installation Reviewed By: walterddr Differential Revision: D29243533 Pulled By: janeyx99 fbshipit-source-id: dde7ba127fa15c95bda0e833cc5311598fb85e2b
2021-06-21restore JOB_BASE_NAME for test1 and test2 in test.sh (#60409)Jeff Daily1-2/+2
Summary: JOB_BASE_NAME for test1 and test2 were removed by https://github.com/pytorch/pytorch/issues/60124. This caused the ROCm CI to run all tests for both test1 and test2. Restore the use of JOB_BASE_NAME. Fixes https://github.com/pytorch/pytorch/issues/60377. Pull Request resolved: https://github.com/pytorch/pytorch/pull/60409 Reviewed By: anjali411 Differential Revision: D29277560 Pulled By: walterddr fbshipit-source-id: ddf01466492a9a626ce1b6adf87cd102d8f1fe35
2021-06-21Enable sharding for Windows GHA CI (#59970)Jane Xu1-10/+0
Summary: Enables sharding for Windows on CI. To make that possible, we currently remove the smoke tests tested in shard 1 which don't seem all that important as they are 1. tested on nightlies 2. seems to be tested anyway by running the test suite Pull Request resolved: https://github.com/pytorch/pytorch/pull/59970 Reviewed By: seemethere Differential Revision: D29268484 Pulled By: janeyx99 fbshipit-source-id: 7f90d73037cfeb2c267b28714550316eb471b4dd
2021-06-20[BE] clean up IS_PYTORCH_CI and IN_CI (#60279)Rong Rong (AI Infra)1-1/+4
Summary: `IS_PYTORCH_CI` and `IN_CI` are used randomly, however in some cases IN_CI is not currently set because it only exist in .circleci/scripts/setup_ci_environment.sh. This cleans up the 2 flags and only use IN_CI Pull Request resolved: https://github.com/pytorch/pytorch/pull/60279 Test Plan: CI Reviewed By: seemethere Differential Revision: D29239545 Pulled By: walterddr fbshipit-source-id: a069424a2bb8790a3adfdaf0dc460301026bf8c7
2021-06-19[pytorch][nnc] support custom class parameters (#59466)Jiakai Liu3-2/+1
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/59466 Change saved parameter type from at::Tensor to at::IValue to support custom class parameters, e.g. `__torch__.torch.classes.xnnpack.Conv2dOpContext`. The NNC produced kernels won't deal with custom class parameters directly. They simply pass through to the external operators that take these custom class parameters, e.g. `prepacked::conv2d_clamp_run`. It will reuse the `__getstate__` and `__setstate__` methods on the custom class to persist and restore the state of the parameters. When calling into the kernel, it will pass in the untyped raw pointer of the custom class objects to the kernel as `void*`. It's similar to the regular tensor parameters, for which it will pass in the raw data pointer of the tensor storage. The generated kernel needs to hardcode the expected type for each parameter and cast before calling the external ops. ghstack-source-id: 131897904 Test Plan: - unit tests Reviewed By: kimishpatel Differential Revision: D28902496 fbshipit-source-id: 4b2c0895dd28f0b7d344aa08183d42ad6a355dae
2021-06-17Enable GHA sharding on linux (#60124)Jane Xu2-5/+5
Summary: This is branch off of https://github.com/pytorch/pytorch/issues/59970 to only shard on linux so far (we're running in issues with windows gflags). This would enable sharding of tests on a few Linux jobs on GHA, allowing tts to be essentially halved. Pull Request resolved: https://github.com/pytorch/pytorch/pull/60124 Reviewed By: zou3519 Differential Revision: D29204211 Pulled By: janeyx99 fbshipit-source-id: 1cc31d1eccd564d96e2aef14c0acae96a3f0fcd0
2021-06-17only runs mem leak check on master (#60023)Rong Rong (AI Infra)1-5/+12
Summary: setting environment variable to only do cuda mem leak check on master CI jobs. See discussion in https://github.com/pytorch/pytorch/pull/59402#issuecomment-860773034 See stats before/after disabling mem leak check: https://github.com/pytorch/pytorch/pull/59942#issuecomment-860947095 Pull Request resolved: https://github.com/pytorch/pytorch/pull/60023 Test Plan: https://github.com/pytorch/pytorch/issues/60108 https://github.com/pytorch/pytorch/issues/60116 Reviewed By: janeyx99 Differential Revision: D29164182 Pulled By: walterddr fbshipit-source-id: dfe88c2c1275b6eb35f18b58aacdc220f34ccb59
2021-06-16ci: Add note about file_diff_from_base for GHA (#60110)Eli Uriegas3-2/+6
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/60110 file_diff_from_base is currently bugged for ghstack PRs since it fails to find a merge base Signed-off-by: Eli Uriegas <eliuriegas@fb.com> Test Plan: Imported from OSS Reviewed By: driazati Differential Revision: D29168767 Pulled By: seemethere fbshipit-source-id: 580a909aa392541769cbbfdc6acce1e6c5d1c341
2021-06-16Revert D29148233: [pytorch][PR] Add GITHUB_HEAD_REF in check for IN_PULL_REQUESTRong Rong (AI Infra)2-2/+2
Test Plan: revert-hammer Differential Revision: D29148233 (https://github.com/pytorch/pytorch/commit/241aac3ef81358577df40a38348c6a5744bed317) Original commit changeset: 7c8c1866f39c fbshipit-source-id: f32c6c6decd737ef290d3e83c9d021475aabaab0
2021-06-16Add GITHUB_HEAD_REF in check for IN_PULL_REQUEST (#60047)Jane Xu2-2/+2
Summary: I believe IN_PULL_REQUEST is unset for some GHA test runs because we don't also check GITHUB_HEAD_REF. This PR is a small fix for that. Example: https://github.com/pytorch/pytorch/pull/60023/checks?check_run_id=2831813860 doesn't set it properly Pull Request resolved: https://github.com/pytorch/pytorch/pull/60047 Reviewed By: walterddr Differential Revision: D29148233 Pulled By: janeyx99 fbshipit-source-id: 7c8c1866f39ce8af8d13c34ddc0c5786a829321e
2021-06-15Reuse build_torch_xla from pytorch/xla repo. (#59989)Ailing Zhang2-32/+12
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/59989 Test Plan: Imported from OSS Reviewed By: samestep Differential Revision: D29138211 Pulled By: ailzhang fbshipit-source-id: 349d307c510e7fad266822e320f0d6904fa00239
2021-06-15Reuse run_torch_xla_tests from pytorch/xla (#59888)Ailing Zhang1-19/+3
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/59888 Test Plan: Imported from OSS Reviewed By: samestep Differential Revision: D29114274 Pulled By: ailzhang fbshipit-source-id: d2845c7fc95d038cd68c10e22b68be8ad3cae736
2021-06-14[c10d] Move pg wrapper tests to their own file. (#59840)Rohan Varma2-0/+4
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/59840 moving these tests to their own standalone file. No meaningful code changes. ghstack-source-id: 131359162 Test Plan: CI Reviewed By: cbalioglu Differential Revision: D29012664 fbshipit-source-id: 348870016509a6ed7e69240fa82bccef4a12d674
2021-06-11Upgrade Windows CI Python to 3.8 (#59729)Jane Xu1-3/+1
Summary: Python 3.6 EOL is end of this year--we should use newer Python in CI. Pull Request resolved: https://github.com/pytorch/pytorch/pull/59729 Reviewed By: bdhirsh Differential Revision: D29006807 Pulled By: janeyx99 fbshipit-source-id: c79214b02a72656058ba5d199141f8838212b3b6
2021-06-10.jenkins: Ignore exit code of nvidia-smi (#59826)Eli Uriegas1-1/+1
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/59826 It's only informational and will run on Windows CPU executors as well Fixes issues found in https://github.com/pytorch/pytorch/runs/2797531966 Signed-off-by: Eli Uriegas <eliuriegas@fb.com> Test Plan: Imported from OSS Reviewed By: janeyx99 Differential Revision: D29042951 Pulled By: seemethere fbshipit-source-id: 862094e53417c0a59d7728bf680be37b806b5a6f
2021-06-10[reland] .github: Add Windows GPU workflow (#58782) (#59752)Eli Uriegas1-3/+3
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/59752 Signed-off-by: Eli Uriegas <eliuriegas@fb.com> Test Plan: Imported from OSS Reviewed By: samestep Differential Revision: D29009775 Pulled By: seemethere fbshipit-source-id: 5be1b818b5653a4fdbfe4a79731317068dc1a5d1
2021-06-09Magma isn't needed in cpu build (#59619)Yi Zhang2-0/+14
Summary: Fix incorrect logic in windows CPU build script VERSION_SUFFIX shouldn't be cpu https://github.com/pytorch/pytorch/pull/59618/checks?check_run_id=2771591019 ![image](https://user-images.githubusercontent.com/16190118/121158840-3f18f700-c87d-11eb-9c03-277856afb1b2.png) Pull Request resolved: https://github.com/pytorch/pytorch/pull/59619 Reviewed By: samestep Differential Revision: D29000213 Pulled By: seemethere fbshipit-source-id: fcc474967e281fbf9be69f14c0aedfd01820573f
2021-06-09Revert D28981443: reland D28645531: .github: Add Windows GPU workflowEli Uriegas1-5/+4
Test Plan: revert-hammer Differential Revision: D28981443 (https://github.com/pytorch/pytorch/commit/21121675b3ebaf40738535dabf2e0bdf69670700) Original commit changeset: 5d24cccfb8c8 fbshipit-source-id: 14e5b610978882bace2f834f61e5457f62b11290
2021-06-09reland D28645531: .github: Add Windows GPU workflow (#59678)Eli Uriegas1-4/+5
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/59678 This reverts commit 2956bbaf2388d424ef986c22fac8287f7c345978. Reland of https://github.com/pytorch/pytorch/pull/58782 Signed-off-by: Eli Uriegas <eliuriegas@fb.com> Test Plan: Imported from OSS Reviewed By: samestep Differential Revision: D28981443 Pulled By: seemethere fbshipit-source-id: 5d24cccfb8c87832fa0233d0b524575dc04f8f05
2021-06-08Revert D28645531: .github: Add Windows GPU workflowEli Uriegas1-3/+3
Test Plan: revert-hammer Differential Revision: D28645531 (https://github.com/pytorch/pytorch/commit/51884c647965d704bd25150784729f8449459264) Original commit changeset: 6ed1a2dead9c fbshipit-source-id: e082d7d50de77d0572596111e95a3da3a350a319
2021-06-08[Reland] Adding run specified tests option to run_test.py (#59649)Jane Xu4-4/+4
Summary: Reland of https://github.com/pytorch/pytorch/issues/59487 Pull Request resolved: https://github.com/pytorch/pytorch/pull/59649 Reviewed By: samestep Differential Revision: D28970751 Pulled By: janeyx99 fbshipit-source-id: 6e28d4dcfdab8a49da4b6a02c57516b08bacd7b5
2021-06-08.github: Add Windows GPU workflow (#58782)Eli Uriegas1-3/+3
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/58782 [skip ci] Signed-off-by: Eli Uriegas <eliuriegas@fb.com> Test Plan: Imported from OSS Reviewed By: samestep Differential Revision: D28645531 Pulled By: seemethere fbshipit-source-id: 6ed1a2dead9cca29e26e613afdbcf46ba7cee88c
2021-06-08Revert D28961233: [pytorch][PR] Adding run-specified-test-cases option in ↵Jane Xu4-4/+4
run_test.py Test Plan: revert-hammer Differential Revision: D28961233 (https://github.com/pytorch/pytorch/commit/a6c9483c2f65e35a01bd5649caf45903f3c6845d) Original commit changeset: 6b7ddc6e6185 fbshipit-source-id: 4f8471df987a03d5c928a04f989d5d43f9cc47e9
2021-06-08ninja 1.9.0 couldn't be installed, CI might be broken (#59625)Yi Zhang1-1/+5
Summary: I suddenly find that `pip install ninja==1.9.0 ` failed in CI. And I tested locally and on another colleague's machine. It looks it conflicts with cmake installed in conda. https://app.circleci.com/pipelines/github/pytorch/pytorch/332470/workflows/d8b6ed30-1c7e-4863-898a-7f067c6202e1/jobs/13972409 ![image](https://user-images.githubusercontent.com/16190118/121175743-02a1c700-c88e-11eb-9596-97b903b727f9.png) 1.10.0 couldn't be installed either. ![image](https://user-images.githubusercontent.com/16190118/121176606-fbc78400-c88e-11eb-931c-aa65bad080f8.png) Pull Request resolved: https://github.com/pytorch/pytorch/pull/59625 Reviewed By: jbschlosser Differential Revision: D28966699 Pulled By: seemethere fbshipit-source-id: a1150e411ba3b4ab65448a087aa65f4ebe6c3596
2021-06-08Adding run-specified-test-cases option in run_test.py (#59487)Jane Xu4-4/+4
Summary: The run-specified-test-cases option would allow us to specify a list of test cases to run by having a CSV with minimally two columns: test_filename and test_case_name. This PR also adds .json to some files we use for better clarity. Usage: `python test/run_test.py --run-specified-test-cases <csv_file>` where the csv file can look like: ``` test_filename,test_case_name,test_total_time,windows_only_failure_sha_count,total_sha_count,windows_failure_count,linux_failure_count,windows_total_count,linux_total_count test_cuda,test_cudnn_multiple_threads_same_device,8068.8409659525,46,3768,53,0,2181,6750 test_utils,test_load_standalone,8308.8062920459,14,4630,65,0,2718,8729 test_ops,test_forward_mode_AD_acosh_cuda_complex128,91.652619369806,11,1971,26,1,1197,3825 test_ops,test_forward_mode_AD_acos_cuda_complex128,91.825633094915,11,1971,26,1,1197,3825 test_profiler,test_source,60.93786725749,9,4656,21,3,2742,8805 test_profiler,test_profiler_tracing,203.09352795241,9,4662,21,3,2737,8807 ``` Pull Request resolved: https://github.com/pytorch/pytorch/pull/59487 Test Plan: Without specifying the option, everything should be as they were before. Running `python test/run_test.py --run-specified-test-cases windows_smoke_tests.csv` resulted in this paste P420276949 (you can see internally). A snippet looks like: ``` (pytorch) janeyx@janeyx-mbp pytorch % python test/run_test.py --run-specified-test-cases windows_smoke_tests.csv Loading specified test cases to run from windows_smoke_tests.csv. Processed 28 test cases. Running test_cpp_extensions_jit ... [2021-06-04 17:24:41.213644] Executing ['/Users/janeyx/miniconda3/envs/pytorch/bin/python', 'test_cpp_extensions_jit.py', '-k', 'test_jit_cuda_archflags'] ... [2021-06-04 17:24:41.213781] s ---------------------------------------------------------------------- Ran 1 test in 0.000s OK (skipped=1) ... ``` With pytest, an example executable would be: `Running test_dataloader ... [2021-06-04 17:37:57.643039] Executing ['/Users/janeyx/miniconda3/envs/pytorch/bin/python', '-m', 'pytest', 'test_dataloader.py', '-v', '-k', 'test_segfault or test_timeout'] ... [2021-06-04 17:37:57.643327]` Reviewed By: jbschlosser Differential Revision: D28961233 Pulled By: janeyx99 fbshipit-source-id: 6b7ddc6e61856aa0002e1a0afc845770e4f8400b
2021-06-03Extract c10d Store tests to dedicated test file (#59271)Andrew Gu2-0/+4
Summary: Partially addresses https://github.com/pytorch/pytorch/issues/55340 **Overview** This factors out `FileStoreTest`, `HashStoreTest`, `PrefixFileStoreTest`, `TCPStoreTest`, `PrefixTCPStoreTest`, `PythonStoreTest`, `RendezvousTest`, `RendezvousEnvTest`, `RendezvousFileTest`, and `RendezvousTCPTest` from `test_c10d_common.py` to a new file `test_store.py`. Additionally, unused import/initialization statements are removed from `test_c10d_common.py`, and the minimal set of import/initialization statements are used for `test_store.py`. Also, this changes `.jenkins/pytorch/multigpu-test.sh`, `.jenkins/pytorch/win-test-helpers/test_distributed.bat`, and `test/run_test.py` to include the new `test_store.py`. **Testing** All commands shown are run on an AI AWS cluster. I check the Store tests: ``` python test/distributed/test_store.py ``` I also check `test_c10d_common.py` since it is the source of the refactored code. In addition, I check `test_c10d_nccl.py` and `test_c10d_gloo.py` since they import from `test_c10d_common.py`; those two should be the only test files depending on `test_c10d_common.py`. ``` python test/distributed/test_c10d_common.py python test/distributed/test_c10d_nccl.py python test/distributed/test_c10d_gloo.py ``` `test_c10d_gloo.py` produces warnings about how using sparse tensors in TorchScript is experimental, but the warnings do not result from this PR's changes. **Testing Issues** (To Be Revisited) ``` WORLD_SIZE=4 BACKEND=gloo gpurun pytest test/distributed/test_c10d_gloo.py ``` Running the above command fails three tests (written as `[Test]`: `[Error]`): - `ProcessGroupGlooWrapperTest.test_collective_hang`: `RuntimeError: [../third_party/gloo/gloo/transport/tcp/pair.cc:598] Connection closed by peer [10.200.24.101]:15580` - `CommTest.test_broadcast_coalesced_gloo_cuda`: `RuntimeError: cuda runtime error (3) : initialization error at ../aten/src/THC/THCGeneral.cpp:54` - `CommTest.test_sequence_num_incremented_gloo_default`: `RuntimeError: cuda runtime error (3) : initialization error at ../aten/src/THC/THCGeneral.cpp:54` However, running each of the following yields no errors: ``` WORLD_SIZE=4 BACKEND=gloo gpurun pytest test/distributed/test_c10d_gloo.py -k test_collective_hang WORLD_SIZE=4 BACKEND=gloo gpurun pytest test/distributed/test_c10d_gloo.py -k test_broadcast_coalesced_gloo_cuda WORLD_SIZE=4 BACKEND=gloo gpurun pytest test/distributed/test_c10d_gloo.py -k test_sequence_num_incremented_gloo_default ``` This suggests the existence of some inadvertent state dependency between tests (e.g. improper cleanup). I have not explored this further yet. In particular, I do not have a solid understanding of the tests to be able to explain why using `pytest` and `gpurun` induces the failure (since notably, running the `.py` directly shows no issue). Similarly, running the following yields 47 errors: ``` WORLD_SIZE=4 BACKEND=nccl gpurun pytest test/distributed/test_c10d_nccl.py ``` The errors seem to all be simply complaining about the usage of `fork()` instead of `spawn()` for CUDA multiprocessing. Though, most of the tests in `test_c10d_nccl.py` ask for at least 2 CUDA devices, so I think that the `gpurun` is warranted (assuming that the test file does not need to be run partially on different machines). Both `test_c10d_common.py` and `test_store.py` work fine with `pytest`. **Other Notes** I noticed that `torch.distributed` is imported both as `dist` and as `c10d` and that `c10d` is used throughout the Store tests. I was curious if this is intentional (as opposed to using `dist` to refer to `torch.distributed`). Also, the original [issue](https://github.com/pytorch/pytorch/issues/55340) suggests that the Store tests do not use multiprocessing, but I saw that `torch.multiprocessing` is still used in `TCPStoreTest`. The links for the Store files in the `CONTRIBUTING.md` [file](https://github.com/pytorch/pytorch/blob/master/torch/distributed/CONTRIBUTING.md) are broken. This can fixed in a separate PR. Pull Request resolved: https://github.com/pytorch/pytorch/pull/59271 Reviewed By: jbschlosser, mrshenli Differential Revision: D28856920 Pulled By: andwgu fbshipit-source-id: 630950cba18d34e6b5de661f5a748f2cddc1b446
2021-05-25Re-enable torchdeploy oss tests and move to per-PR cuda11 job (#58872)Will Constable2-2/+2
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/58872 Test Plan: verify tests running on CI as expected Reviewed By: suo Differential Revision: D28646660 fbshipit-source-id: eb7d784844fb7bc447b4232e2f1e479d4d5aa72f
2021-05-24Fix failing torch deploy tests and reenable. (#58871)Edward Yang1-4/+3
Summary: Fix is simple; alias inputs before feeding them to distinct torchdeploy interpreters. Signed-off-by: Edward Z. Yang <ezyang@fb.com> Fixes https://github.com/pytorch/pytorch/issues/58832 Pull Request resolved: https://github.com/pytorch/pytorch/pull/58871 Reviewed By: wconstab, zou3519 Differential Revision: D28646784 Pulled By: ezyang fbshipit-source-id: 6d2850f3226b5b99468d1465723b421ce4d7ab89
2021-05-23[deploy] temporarily disable deploy tests (#58832)Michael Suo1-3/+4
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/58832 While we investigate breakage. Differential Revision: D28631469 D28631469 Test Plan: Imported from OSS Reviewed By: SplitInfinity Pulled By: suo fbshipit-source-id: 43d51c1c9d81e951074824ccf624e42f6bec4242
2021-05-17.github: Add intial Windows CPU GHA workflow (#58199)Eli Uriegas1-5/+3
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/58199 Signed-off-by: Eli Uriegas <eliuriegas@fb.com> Test Plan: Imported from OSS Reviewed By: malfet Differential Revision: D28465272 Pulled By: seemethere fbshipit-source-id: d221ad71d160088883896e018c58800dae85ff2c
2021-05-17Stop installing libuv on Windows (#51936)peter1-1/+1
Summary: Fixes #{issue number} gunandrose4u Pull Request resolved: https://github.com/pytorch/pytorch/pull/51936 Reviewed By: malfet Differential Revision: D28467662 Pulled By: seemethere fbshipit-source-id: 28d203ee3af13d6a3158f188c2e889e310ee6010
2021-05-14Disallow versionless Python shebangs (#58275)Sam Estep1-1/+1
Summary: Some machines don't have a versionless `python` on their PATH, which breaks these existing shebangs. I'm assuming that all the existing versionless `python` shebangs are meant to be `python3` and not `python2`; please let me know if my assumption was incorrect for any of these. Pull Request resolved: https://github.com/pytorch/pytorch/pull/58275 Test Plan: CI. Reviewed By: zhouzhuojie Differential Revision: D28428143 Pulled By: samestep fbshipit-source-id: 6562be3d12924db72a92a0207b060ef740f61ebf
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