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65 Commits

Author SHA1 Message Date
6c8c5ad5ea [RelEng] Define BUILD_BUNDLE_PTXAS (#119750) (#119988)
Co-authored-by: Nikita Shulga <nshulga@meta.com>
Fixes https://github.com/pytorch/pytorch/issues/119054
resolved: https://github.com/pytorch/pytorch/pull/119750
2024-02-15 13:19:00 -05:00
f00f0ab0e4 fix compile DTensor.from_local in trace_rule_look up (#119659) (#119941)
resolved: https://github.com/pytorch/pytorch/pull/119659
2024-02-15 12:46:55 -05:00
077791bb6b Revert "Update state_dict.py to propagate cpu offload (#117453)" (#119995) 2024-02-15 12:45:22 -05:00
3eaaeeb45a Update state_dict.py to propagate cpu offload (#117453) (#119916)
resolved: https://github.com/pytorch/pytorch/pull/117453
2024-02-15 10:14:52 -05:00
0aa3fd32fe HSDP + TP integration bug fixes (#119819)
Co-authored-by: Andrew Gu <andgu@fb.com>
resolved: https://github.com/pytorch/pytorch/pull/112435
resolved: https://github.com/pytorch/pytorch/pull/118620
Fixed `device_mesh` and auto wrap (#119064)
fix https://github.com/pytorch/pytorch/issues/118906.
resolved: https://github.com/pytorch/pytorch/pull/119064
resolved: https://github.com/pytorch/pytorch/pull/118638
Fixes https://github.com/pytorch/pytorch/issues/118639.
resolved: https://github.com/pytorch/pytorch/pull/119481
2024-02-14 15:46:31 -05:00
eef51a6bee [Inductor] Skip triton templates for mixedmm on SM70- (#118591) (#119894)
As it results in numerical errors, see https://github.com/pytorch/pytorch/issues/117144

Fixes https://github.com/pytorch/pytorch/issues/117144

Pull Request resolved: https://github.com/pytorch/pytorch/pull/118591
Approved by: https://github.com/jansel

Co-authored-by: Nikita Shulga <nshulga@meta.com>
2024-02-14 12:23:24 -08:00
940358f12f [dtensor] fix dtensor _to_copy op for mix precision (#116426) (#119687)
Co-authored-by: Wanchao Liang <wanchaol@users.noreply.github.com>
fix dtensor _to_copy op for mix precision (#116426)
resolved: https://github.com/pytorch/pytorch/pull/116426
2024-02-14 14:01:54 -05:00
24e4751650 [state_dict] Calls wait() for the DTensor to_local() result (#118197) (#119692)
Co-authored-by: Chien-Chin Huang <chienchin@fb.com>
Co-authored-by: Yue Dong <yoyoyod@meta.com>
resolved: https://github.com/pytorch/pytorch/pull/118197
fix to address numerical correctness concerns identified in PR #118197, and we should only wait on `AsyncCollectiveTensor`.
resolved: https://github.com/pytorch/pytorch/pull/119716
2024-02-14 13:59:06 -05:00
dcaeed36eb [DCP][state_dict] Fix the issue that get_state_dict/set_state_dict ig… (#119807)
Fixes, https://github.com/pytorch/pytorch/issues/119535.
resolved: https://github.com/pytorch/pytorch/pull/119573
2024-02-14 12:14:01 -05:00
4f882a5f32 Properly preserve SymInt input invariant when splitting graphs (#117406) (#118067)
Co-authored-by: Edward Z. Yang <ezyang@meta.com>
Fixes https://github.com/pytorch/pytorch/issues/111636
Fixes https://github.com/pytorch/pytorch/issues/108877
Fixes https://github.com/pytorch/pytorch/issues/116956
resolved: https://github.com/pytorch/pytorch/pull/117406
2024-02-14 11:28:54 -05:00
e80c8c2e98 Correctly formatting the example in get_state_dict (#119532) (#119804)
Co-authored-by: jmarin <diyemti@gmail.com>
Fixes #118837
resolved: https://github.com/pytorch/pytorch/pull/119532
2024-02-14 10:15:46 -05:00
445b0f9b63 [DCP][state_dict] DCP state_dict cannot correctly find FQN when the l… (#119691)
Co-authored-by: Chien-Chin Huang <chienchin@fb.com>
resolved: https://github.com/pytorch/pytorch/pull/115592
2024-02-14 10:07:35 -05:00
95ea4e6648 [FSDP][2D] Fix DTensor Extension Bugs (#119690)
Co-authored-by: Wanchao Liang <wanchaol@users.noreply.github.com>
resolved: https://github.com/pytorch/pytorch/pull/116122
resolved: https://github.com/pytorch/pytorch/pull/117020
fixes https://github.com/pytorch/pytorch/issues/117126
resolved: https://github.com/pytorch/pytorch/pull/117336
2024-02-14 10:04:56 -05:00
bbfcfb0302 [FSDP] enable autograd in forward prefetching (#116792) (#119688)
Co-authored-by: Wei (Will) Feng <134637289+weifengpy@users.noreply.github.com>
resolved: https://github.com/pytorch/pytorch/pull/116792
2024-02-14 10:03:11 -05:00
2304d6bfb1 Fix ColwiseParallel typo (#116151) (#119821)
Pull Request resolved: https://github.com/pytorch/pytorch/pull/116151
Approved by: https://github.com/wanchaol

Co-authored-by: Carlos Mocholí <carlossmocholi@gmail.com>
2024-02-13 16:34:45 -08:00
7b436b0d05 Update oneDNN build option for older systems (#118057) (#119773)
Co-authored-by: yanbing-j <yanbing.jiang@intel.com>
Fixes [#116623](https://github.com/pytorch/pytorch/issues/116623).
resolved: https://github.com/pytorch/pytorch/pull/118057
2024-02-13 15:07:55 -05:00
4ae866593d [EZ] Set maximum supported version of Python as 3.12 (#119743) (#119770)
Co-authored-by: Nikita Shulga <2453524+malfet@users.noreply.github.com>
resolved: https://github.com/pytorch/pytorch/pull/119743
2024-02-13 15:06:38 -05:00
bac09b8555 Fix TCP Store Windows (#118860) (#119769)
Co-authored-by: mantaionut <ionut@janeasystems.com>
Fixes #118737
resolved: https://github.com/pytorch/pytorch/pull/118860
2024-02-13 15:05:56 -05:00
b9814bc525 Updated docs for deprecated torch.set_default_tensor_type (#115041) (#119316)
Fixes #113646.
resolved: https://github.com/pytorch/pytorch/pull/115041
2024-02-12 11:57:30 -05:00
6a3a3df103 Clarified sampling process of torch.randn for complex dtypes. (#118315) (#119315)
Fixes #118269.
resolved: https://github.com/pytorch/pytorch/pull/118315
2024-02-12 11:55:06 -05:00
b126b0d724 Missing docs for CircularPad2d (#119313)
Fixes #118429
resolved: https://github.com/pytorch/pytorch/pull/118465
2024-02-12 11:54:31 -05:00
d65d0e598e Replaced CHECK with TORCH_CHECK in order to not abort, but throw a Ru… (#119301)
…ntimeError instead.

Fixes #117499.

Cherry-pick of  https://github.com/pytorch/pytorch/pull/117653 into release/2.2 
Approved by: https://github.com/antoniojkim, https://github.com/JackCaoG, https://github.com/alanwaketan

Co-authored-by: Tobias Ringwald <github@ringwald.email>
2024-02-12 07:32:37 -08:00
a412db0995 [CI] Explicitly specify read-all permissions on the token (#117290) (#119568)
Co-authored-by: Nikita Shulga <nshulga@meta.com>
Co-authored-by: Nikita Shulga <2453524+malfet@users.noreply.github.com>
resolved: https://github.com/pytorch/pytorch/pull/117290
resolved: https://github.com/pytorch/pytorch/pull/117371
2024-02-09 14:30:18 -05:00
e9956badeb Migrate rocm test to using oidc (#117160) (#119565)
Co-authored-by: Huy Do <huydhn@gmail.com>
resolved: https://github.com/pytorch/pytorch/pull/117160
resolved: https://github.com/pytorch/pytorch/pull/117422
2024-02-09 14:29:13 -05:00
574f46da53 [oidc] Migrate Triton wheel upload to oidc (#117648) (#119564)
Co-authored-by: Nikita Shulga <2453524+malfet@users.noreply.github.com>
resolved: https://github.com/pytorch/pytorch/pull/117648
Fix trition wheels build (take 2) (#117706)
resolved: https://github.com/pytorch/pytorch/pull/117706
2024-02-09 14:28:32 -05:00
55d10abc0f Switch nightly binaries to oidc. Remove aws keys (#117416) (#119560)
resolved: https://github.com/pytorch/pytorch/pull/117416
2024-02-09 14:27:54 -05:00
0cd0631716 Fix typo on torch.frombuffer() documentation (#119388) 2024-02-09 13:13:09 -05:00
44ab785f75 Fix typo on Contribution Guide (#119428) (#119505)
Fixes #119427
resolved: https://github.com/pytorch/pytorch/pull/119428
2024-02-09 13:11:35 -05:00
8ac9b20d4b Run docker release build on final tag (#117131) (#117182)
To be successful, the docker release workflow needs to run on final tag, after the Release to conda and pypi are complete.

Please refer to: https://github.com/pytorch/pytorch/blob/main/Dockerfile#L76

Pull Request resolved: https://github.com/pytorch/pytorch/pull/117131
Approved by: https://github.com/huydhn, https://github.com/seemethere, https://github.com/malfet
2024-01-10 14:17:29 -08:00
2490352430 Fix cuInit test on Windows (#117095)
resolved: https://github.com/pytorch/pytorch/pull/117055
2024-01-10 13:21:27 -05:00
3a44bb713f [CI] Test that cuInit is not called during import (#117043)
By making a driver API call in subprocess and expecting it to return `CUDA_ERROR_NOT_INITIALIZED`

Test Plan: run it on nighties before https://github.com/pytorch/pytorch/pull/116201 got reverted and observe the failure

This is very important for lots of distributed launchers

Fixes https://github.com/pytorch/pytorch/issues/116276

Cherry-pick of  https://github.com/pytorch/pytorch/pull/117010 into release/2.2

Co-authored-by: Nikita Shulga <nshulga@meta.com>
2024-01-09 11:30:03 -08:00
1c8ba3847d [CI] Use jemalloc for CUDA builds (#116900) (#116988)
According to @ptrblck it'll likely mitigate non-deterministic NVCC bug
See https://github.com/pytorch/pytorch/issues/116289 for more detail

Test plan: ssh into one of the cuda builds and make sure that `LD_PRELOAD` is set for the top-level make command

Pull Request resolved: https://github.com/pytorch/pytorch/pull/116900
Approved by: https://github.com/atalman

Co-authored-by: Nikita Shulga <nshulga@meta.com>
2024-01-08 19:53:13 -08:00
96d2ddbafe Store user model to simplify ONNXProgram.{adapt_torch_*,__call__} APIs (#115281) (#115583)
Currently (after https://github.com/pytorch/pytorch/pull/114407), the user has must pass the original user ``model`` to APIs such as ``ONNXProgram.__call__``, ``ONNXProgram.adapt_torch_inputs_to_onnx`` and ``ONNXProgram.adapt_torch_outputs_to_onnx`` APIs.

This was needed because when the model is fakefied, a version of the non-fakefied model is needed so that the Initializers, buffers and constants can be extracted from a real model (and used as input to the ONNX model).
That approach brings an unnecessary usability burden to the user when the model is not fakefied, because the model that was already passed to ``torch.onnx.dynamo_export`` could be used to extract ``state_dict``.

This PR adds ``ONNXProgram._model_torch`` attribute to store the user model and demote ``model`` argument of the aforementioned APIs to optional, only (as opposed to required).

As a result, for the fakefied model scenario, the user still need to pass the required model, but for non fakefied models, the persisted model is implicitly used to extract the model state_dict, making it easier to use.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/115281
Approved by: https://github.com/BowenBao
ghstack dependencies: #114407
2024-01-08 10:16:13 -08:00
738b4a560a Update ONNX's IO Adapter to support FakeTensor with ExportedProgram (#114407) (#115578)
Currently, the ONNX exporter using torch.nn.Module as input can support
FakeTensor because the ONNX model stores all initializers

When using torch.export.ExportedProgram as input, the initializers are
lifted as inputs. In order to execute the ONNX model, we need to pass a
reference to the non-fake model to the
ONNXProgram.adapt_torch_inputs_to_onnx API, so that initializers can be
fetched from the model and fed to the ONNX model as input

ps: https://github.com/pytorch/pytorch/issues/115461 will track the API revision for the cases where additional `model_with_state_dict` are required to produce complete ONNX files exported with fake support. This is also tracked by the umbrella fake tensor issue https://github.com/pytorch/pytorch/issues/105464 FYI @BowenBao
Pull Request resolved: https://github.com/pytorch/pytorch/pull/114407
Approved by: https://github.com/BowenBao
2024-01-05 13:57:50 -08:00
4cf10bf4dc [Cherry-pick] [Quant] [PT2] Enable batchnorm in _move_exported_model_to_eval (#115715) 2024-01-04 15:36:16 -05:00
7e97e4b4b6 [AARCH64] Fall back to GEMM if mkldnn_matmul fails (#115936) (#116666)
- Add call to `at::globalContext().userEnabledMkldnn()` to `apply_mkldnn_matmul_heur`
- Surround calls to `mkldnn_matmul` with `try {} catch {}`
- Print warning and fall back to BLAS (by calling  `at::globalContext().setUserEnabledMkldnn()`) if `mkldnn_matmul()` fails

Test plan: On Linux arm run:
```shell
$ sudo chmod 400 /sys; python -c "import torch;m=torch.nn.Linear(1, 32);print(torch.__version__);print(m(torch.rand(32, 1)))"
Error in cpuinfo: failed to parse the list of possible processors in /sys/devices/system/cpu/possible
Error in cpuinfo: failed to parse the list of present processors in /sys/devices/system/cpu/present
Error in cpuinfo: failed to parse both lists of possible and present processors
2.3.0.dev20231215
bad err=11 in Xbyak::Error
bad err=11 in Xbyak::Error
/home/ubuntu/miniconda3/envs/py311/lib/python3.11/site-packages/torch/nn/modules/linear.py:116: UserWarning: mkldnn_matmul failed, switching to BLAS gemm:internal error (Triggered internally at /pytorch/aten/src/ATen/native/LinearAlgebra.cpp:1509.)
  return F.linear(input, self.weight, self.bias)
tensor([[-0.5183,  0.2279, -0.4035,  ..., -0.3446,  0.0938, -0.2113],
        [-0.5111,  0.2362, -0.3821,  ..., -0.3536,  0.1011, -0.2159],
        [-0.6387,  0.0894, -0.7619,  ..., -0.1939, -0.0282, -0.1344],
        ...,
        [-0.6352,  0.0934, -0.7516,  ..., -0.1983, -0.0247, -0.1366],
        [-0.4790,  0.2733, -0.2862,  ..., -0.3939,  0.1338, -0.2365],
        [-0.5702,  0.1682, -0.5580,  ..., -0.2796,  0.0412, -0.1782]],
       grad_fn=<AddmmBackward0>)
```
Fixes https://github.com/pytorch/pytorch/issues/114750

Pull Request resolved: https://github.com/pytorch/pytorch/pull/115936
Approved by: https://github.com/lezcano

Co-authored-by: Nikita Shulga <nshulga@meta.com>
2024-01-02 20:38:28 -08:00
1a3e3c7cff [CUDA] baddmm should fall back to addmm for batch=1 (#114992) (#116518)
I.e. it feels reasonable to always call `at::cuda::gemm` rather than `at::cuda::bgemm` when num_batches == 1
After the change, benchmarking torch built with CUDA-12 using  [following perf script](https://gist.github.com/malfet/6a17156d7f5663b8b12054a1beff3fe1) on A100  are as follows:
|      Shape     |  bmm_time |  mm_time  | slow down (%) |
| -------------- | --------- | --------- | ------------- |
|    1x1x4096    |   14.18   |   14.31   |     -0.89     |
|    1x1x8192    |   14.37   |   14.37   |     -0.05     |
|   1x1x16384    |   14.03   |   14.12   |     -0.68     |
|   1x1x32768    |   14.19   |   14.24   |     -0.35     |
|   1x1x65536    |   14.85   |   14.52   |     2.30      |
|   1x1x131072   |   14.03   |   14.07   |     -0.33     |
|  128x128x128   |   11.34   |   11.06   |     2.56      |
|  256x256x256   |   14.85   |   14.40   |     3.15      |
|  512x512x512   |   27.22   |   27.22   |     -0.01     |
| 1024x1024x1024 |  129.66   |  129.50   |     0.12      |
| 2048x2048x2048 |  972.18   |  973.24   |     -0.11     |
|  129x127x129   |   11.21   |   11.25   |     -0.39     |
|  257x255x257   |   14.50   |   14.43   |     0.44      |
|  513x511x513   |   29.01   |   29.01   |     0.01      |
| 1025x1023x1025 |  137.65   |  137.64   |     0.01      |
| 2049x2047x2049 |  982.58   |  982.65   |     -0.01     |
|  4097x3x4097   |   86.65   |   86.64   |     0.01      |
|  8193x3x8193   |  384.02   |  383.96   |     0.02      |
| 16385x3x16385  |  1106.73  |  1107.32  |     -0.05     |
| 32769x3x32769  |  4739.49  |  4739.48  |     0.00      |
| 65537x3x65537  | 17377.78  | 17378.74  |     -0.01     |
|  4097x5x4097   |   87.09   |   87.12   |     -0.03     |
|  8193x5x8193   |  301.38   |  301.36   |     0.01      |
| 16385x5x16385  |  1107.38  |  1108.04  |     -0.06     |
| 32769x5x32769  |  4743.73  |  4744.07  |     -0.01     |
| 65537x5x65537  | 17392.32  | 17395.42  |     -0.02     |
|  4097x7x4097   |   87.17   |   87.19   |     -0.02     |
|  8193x7x8193   |  301.94   |  302.00   |     -0.02     |
| 16385x7x16385  |  1107.17  |  1106.79  |     0.03      |
| 32769x7x32769  |  4747.15  |  4747.13  |     0.00      |
| 65537x7x65537  | 17403.85  | 17405.02  |     -0.01     |

Fixes perf problem reported in https://github.com/pytorch/pytorch/issues/114911
Pull Request resolved: https://github.com/pytorch/pytorch/pull/114992
Approved by: https://github.com/Skylion007, https://github.com/eqy

Co-authored-by: Nikita Shulga <nshulga@meta.com>
2024-01-02 16:54:15 -05:00
ab7505f78c Fix broken PyYAML 6.0 on MacOS x86 (#115956) (#116551)
May be we should just get rid of x86 jobs, but that's for another day.  This one should fix the broken build in trunk, i.e. https://github.com/pytorch/pytorch/actions/runs/7227220153/job/19694420117.

I guess that the failure looks flaky depending on the version of default python3 on the GitHub x86 runner.

The issue from PyYAML https://github.com/yaml/pyyaml/issues/601
Pull Request resolved: https://github.com/pytorch/pytorch/pull/115956
Approved by: https://github.com/malfet

(cherry picked from commit 94d28161faccd6e2a2e99bdb22cfadef8a24077e)

Co-authored-by: Huy Do <huydhn@gmail.com>
2023-12-29 21:19:50 -08:00
953c9c0c29 [CI] Fix docker builds (#116549) (#116552)
By pinning lxml to 4.9.4 as 5.0.0 is missing Python-3.9 binaries, see https://pypi.org/project/lxml/5.0.0/#files
<img width="568" alt="image" src="https://github.com/pytorch/pytorch/assets/2453524/fbd64512-b788-4bf6-9c1f-084dcedfd082">

Pull Request resolved: https://github.com/pytorch/pytorch/pull/116549
Approved by: https://github.com/houseroad, https://github.com/aakhundov

(cherry picked from commit bd7d26bb964ef08354771d19fa7d70d539f97c81)
2023-12-29 21:19:16 -08:00
0288d567fb [MPS] aten::erfinv bug fix: add storage offset buffers to handle slicing (#116542)
A bug fix of a recently merged PR per comment: https://github.com/pytorch/pytorch/pull/101507#discussion_r1271393706

The follow test would fail without this bug fix:

```
import torch
def test_erfinv():
    for device in ['cpu', 'mps']:
        x = torch.tensor([0.1, 0.2, 0.3, 0.4, 0.5], device=device)
        y = x[2:].erfinv()

        x2 = torch.tensor([0.3, 0.4, 0.5], device=device)
        y2 = x2.erfinv()

        print(y)
        print(y2)

        torch.testing.assert_close(y, y2)
        print(f"{device} passes.")

test_erfinv()
```

Cherry-pick of  https://github.com/pytorch/pytorch/pull/105801 into release/2.2

Co-authored-by: Peter Pham <peterpham86@gmail.com>
2023-12-29 15:34:30 -08:00
ce29e8f9b1 [RelEng] Missing signal for release branches (#116516) (#116541)
Run slow/periodic and inductor workflows on push to release branches

Right now there are no signal from those jobs on release branches at all.
This will run periodic jobs on every commit to release branch, which is fine, as they are short lived and have a much lower traffic that a regular jobs

Pull Request resolved: https://github.com/pytorch/pytorch/pull/116516
Approved by: https://github.com/clee2000

Co-authored-by: Nikita Shulga <nshulga@meta.com>
2023-12-29 14:53:47 -05:00
444e132b74 Removing HTA documentation (#116513) (#116540)
Removing HTA documentation

Pull Request resolved: https://github.com/pytorch/pytorch/pull/116513
Approved by: https://github.com/aaronenyeshi, https://github.com/malfet, https://github.com/atalman

Co-authored-by: Anupam Bhatnagar <anupamb@meta.com>
2023-12-29 14:53:13 -05:00
596bbaf6fc Fix missing dependency in torch.utils.tensorboard (#115598) (#116517)
Fixes #114591

Version package was removed in this pull request: #114108 but is still used in `torch.utils.tensorboard` causing import errors. The fix removes the import and uses a simpler check.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/115598
Approved by: https://github.com/malfet

Co-authored-by: Sacha <sachahu@hotmail.fr>
2023-12-28 17:28:59 -05:00
be254276d2 Back out "[Kineto] Initialize libkineto profilers during torch init process during pybind set-up (#112623)" (#116201) (#116332)
Summary:
This diff needs to be backed out because TorchBench llama_v2_7b_16h has a cublas init error.
https://github.com/pytorch/benchmark/actions/runs/7266269668/job/19797677485?pr=2095

Test Plan: CI

Differential Revision: D52339142

Pull Request resolved: https://github.com/pytorch/pytorch/pull/116201
Approved by: https://github.com/xuzhao9

(cherry picked from commit a357a0f31519f96cff9839c1672a112539ba98ff)

Co-authored-by: Aaron Shi <aaronshi@meta.com>
2023-12-24 10:39:34 -05:00
9fd518dfdc Fix allowed dtypes for mem_eff attention (#116026) (#116272)
# Summary

Fix issue bug in detecting mem eff capability for cuda devices less than sm80:
https://github.com/pytorch-labs/gpt-fast/issues/49

Pull Request resolved: https://github.com/pytorch/pytorch/pull/116026
Approved by: https://github.com/janeyx99
2023-12-22 23:04:31 -08:00
bc244ee2cd Fix bug in mem_eff kernel with attention mask and MQA (#116301)
# Summary

Found using the repros mentioned in this issue: #112577

After many go rounds with compute-sanitizer and eventual printf debugging I feel pretty confident that this was the underlying issue

Cherry-pick of  https://github.com/pytorch/pytorch/pull/116234 into release/2.2 branch
2023-12-22 07:40:43 -08:00
df3cab83e1 [ROCm] Disabling Kernel Asserts for ROCm by default - fix and clean up and refactoring (#114660) (#116207)
Related to #103973  #110532 #108404 #94891

**Context:**
As commented in 6ae0554d11/cmake/Dependencies.cmake (L1198)
Kernel asserts are enabled by default for CUDA and disabled for ROCm.
However it is somewhat broken, and Kernel assert was still enabled for ROCm.

Disabling kernel assert is also needed for users who do not have PCIe atomics support. These community users have verified that disabling the kernel assert in PyTorch/ROCm platform fixed their pytorch workflow, like torch.sum script, stable-diffusion. (see the related issues)

**Changes:**

This pull request serves the following purposes:
* Refactor and clean up the logic,  make it simpler for ROCm to enable and disable Kernel Asserts
* Fix the bug that Kernel Asserts for ROCm was not disabled by default.

Specifically,
- Renamed `TORCH_DISABLE_GPU_ASSERTS` to `C10_USE_ROCM_KERNEL_ASSERT` for the following reasons:
(1) This variable only applies to ROCm.
(2) The new name is more align with #define CUDA_KERNEL_ASSERT function.
(3) With USE_ in front of the name, we can easily control it with environment variable to turn on and off this feature during build (e.g. `USE_ROCM_KERNEL_ASSERT=1 python setup.py develop` will enable kernel assert for ROCm build).
- Get rid of the `ROCM_FORCE_ENABLE_GPU_ASSERTS' to simplify the logic and make it easier to understand and maintain
- Added `#cmakedefine` to carry over the CMake variable to C++

**Tests:**
(1) build with default mode and verify that USE_ROCM_KERNEL_ASSERT  is OFF(0), and kernel assert is disabled:

```
python setup.py develop
```
Verify CMakeCache.txt has correct value.
```
/xxxx/pytorch/build$ grep USE_ROCM_KERNEL_ASSERT CMakeCache.txt
USE_ROCM_KERNEL_ASSERT:BOOL=0
```
Tested the following code in ROCm build and CUDA build, and expected the return code differently.

```
subprocess.call([sys.executable, '-c', "import torch;torch._assert_async(torch.tensor(0,device='cuda'));torch.cuda.synchronize()"])
```
This piece of code is adapted from below unit test to get around the limitation that this unit test now was skipped for ROCm. (We will check to enable this unit test in the future)

```
python test/test_cuda_expandable_segments.py -k test_fixed_cuda_assert_async
```

Ran the following script, expecting r ==0 since the CUDA_KERNEL_ASSERT is defined as nothing:
```
>> import sys
>>> import subprocess
>>> r=subprocess.call([sys.executable, '-c', "import torch;torch._assert_async(torch.tensor(0,device='cuda'));torch.cuda.synchronize()"])
>>> r
0
```

(2) Enable the kernel assert by building with USE_ROCM_KERNEL_ASSERT=1, or USE_ROCM_KERNEL_ASSERT=ON
```
USE_ROCM_KERNEL_ASSERT=1 python setup.py develop
```

Verify `USE_ROCM_KERNEL_ASSERT` is `1`
```
/xxxx/pytorch/build$ grep USE_ROCM_KERNEL_ASSERT CMakeCache.txt
USE_ROCM_KERNEL_ASSERT:BOOL=1
```

Run the assert test, and expected return code not equal to 0.

```
>> import sys
>>> import subprocess
>>> r=subprocess.call([sys.executable, '-c', "import torch;torch._assert_async(torch.tensor(0,device='cuda'));torch.cuda.synchronize()"])
>>>/xxxx/pytorch/aten/src/ATen/native/hip/TensorCompare.hip:108: _assert_async_cuda_kernel: Device-side assertion `input[0] != 0' failed.
:0:rocdevice.cpp            :2690: 2435301199202 us: [pid:206019 tid:0x7f6cf0a77700] Callback: Queue 0x7f64e8400000 aborting with error : HSA_STATUS_ERROR_EXCEPTION: An HSAIL operation resulted in a hardware exception. code: 0x1016

>>> r
-6
```

Pull Request resolved: https://github.com/pytorch/pytorch/pull/114660
Approved by: https://github.com/jeffdaily, https://github.com/malfet, https://github.com/jithunnair-amd

(cherry picked from commit 66a76516bfc341b2b55bb2056d2faa9c2de46d69)

Co-authored-by: hongxyan <hongxyan@amd.com>
2023-12-21 09:27:14 -05:00
32e1876876 [CherryPick][DeviceMesh] Fix DeviceMesh docs #116053 and #116074 (#116115)
* [DeviceMesh] Rename _device_mesh.py to device_mesh.py to prepare for beta (#115193)

Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/115193

Rename _device_mesh.py to device_mesh.py, update all callsites, add documentation.
We created stubs for public class and methods in torch.distributed.device_mesh so that torch.distributed.device_mesh can be imported with or without distributed is available().

Original diff reverted: D51629761
Original PR reverted: https://github.com/pytorch/pytorch/pull/115099
Prior to landing, CI signals are all passed. Shipit added the "ci/trunk" label to the PR and DID NOT wait for it and went ahead committing. More context can be found in the reverted PR above.

Test Plan: CI.

Differential Revision: D51861018

fbshipit-source-id: dc7b26cea7340d55498730123e82a42cef46ff55

* fix doc

* Update device_mesh.py docs imports
#116074
2023-12-19 19:46:43 -08:00
f9e2b3d8a7 Docker Release builds Include both cuda versions (#115949) (#116065)
* Use matrix generate script for docker release workflows (#115949)

Enable both supported CUDA version builds for docker release. Rather then building only 1 version.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/115949
Approved by: https://github.com/huydhn

* [releng] Docker Official release make sure cuda version is part of image name (#116070)

Follow up on https://github.com/pytorch/pytorch/pull/115949

Change docker build image name:
``pytorch:2.1.2-devel``-> ``2.1.2-cuda12.1-cudnn8-devel and 2.1.2-cuda11.8-cudnn8-devel``

Ref: https://github.com/orgs/pytorch/packages/container/package/pytorch-nightly

Naming will be same as in https://hub.docker.com/r/pytorch/pytorch/tags
Pull Request resolved: https://github.com/pytorch/pytorch/pull/116070
Approved by: https://github.com/huydhn, https://github.com/seemethere

* [releng] Docker release Refactor Push nightly tags step. Move cuda and cudnn version to docker tag rather then name (#116097)

Follow up after : https://github.com/pytorch/pytorch/pull/116070

This PR does 2 things.

1. Refactor Push nightly tags step, don't need to extract CUDA_VERSION anymore. New tag should be in this format: ``${PYTORCH_VERSION}-cuda$(CUDA_VERSION_SHORT)-cudnn$(CUDNN_VERSION)-runtime``
2. Move cuda$(CUDA_VERSION_SHORT)-cudnn$(CUDNN_VERSION) from docker name to tag

Pull Request resolved: https://github.com/pytorch/pytorch/pull/116097
Approved by: https://github.com/jeanschmidt
2023-12-19 17:01:58 -05:00
2ad9cab9b2 [tp] further fix the docs (#115974) (#116119)
some typo result in the note section not rendered properly, can't see
this from the last PR directly as the last PR only show the first commit
documentation :(

Also make the parallelize_module doc example more concrete

Pull Request resolved: https://github.com/pytorch/pytorch/pull/115974
Approved by: https://github.com/wz337
2023-12-19 15:24:40 -05:00
5a4f136340 [Release/2.2] Enable THP for buffer sizes >=2MB (#115990)
The 2MB THP(transparent huge pages) pages provide better allocation latencies compared to the standard 4KB pages. This change has shown substantial improvement for batch mode usecases where the tensor sizes are larger than 100MB.

Only enabled if `THP_MEM_ALLOC_ENABLE` environment variable is set.

Relanding https://github.com/pytorch/pytorch/pull/93888 with functionality disabled for Android

Cherry-pick of  https://github.com/pytorch/pytorch/pull/107697 into release/2.2 branch
(cherry-picked from commit 88207b10cab33b08a15a9009630b5c1e7549ea2b)
2023-12-19 09:51:12 -08:00
e8ebe2cfca [export] Update schema version (#115712) (#115952)
Since pytorch 2.1 release we've made some BC breaking changes to the serialized schema. We should update it in time for the 2.2 release. Some of the changes include:

* https://github.com/pytorch/pytorch/pull/114371 - custom class objects / pybinded objects are no longer saved directly to the `ExportedProgram` structure. Instead, the name is serialized inside of the program, and the actual bytes are stored. in a separate location from the exported program, allowing it to be saved to a different location.
* https://github.com/pytorch/pytorch/pull/111204 - `GraphSignature` structure changed and `call_spec` is removed from the `GraphModule` schema
* https://github.com/pytorch/pytorch/pull/111407 - `loss_outout` -> `loss_output`
* https://github.com/pytorch/pytorch/pull/113075 - `example_inputs` removed from the `ExportedProgram` structure (this originally did not store anything), `dialect` added to the `ExportedProgram` structure.
* https://github.com/pytorch/pytorch/pull/113689 - tensor constants are now lifted as inputs to the graph, and their locations are stored in the `GraphSignature`
* https://github.com/pytorch/pytorch/pull/114172 - removed `equality_constraints` and added a `SymExprHint` for all symbolic expressions.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/115712
Approved by: https://github.com/gmagogsfm
2023-12-18 10:53:42 -08:00
da4bf36936 [tp] improve documentation (#115880) (#115939)
Improve the TP documentation in terms of format and descriptions

Pull Request resolved: https://github.com/pytorch/pytorch/pull/115880
Approved by: https://github.com/XilunWu
2023-12-18 11:41:58 -05:00
6ca1983e77 Set _dynamo.config.capture_func_transforms=False (#115267) (#115929)
Due to not all tests in the Dynamo shard actually running in CI, we've
started to bitrot on this implementation. Since our plan is to trace
into the functorch implementations instead of construct a HOP
(which is what capture_func_transforms=True does), let's turn off this
config by default.

Test Plan:
- Tests

Pull Request resolved: https://github.com/pytorch/pytorch/pull/115267
Approved by: https://github.com/voznesenskym, https://github.com/guilhermeleobas
2023-12-15 14:23:11 -05:00
7f55ee7fe8 [Release/2.2] Extend expected fx output types for int, float, bool (#115669)
Fixes exporting ops, such as `aten::_scaled_dot_product_flash_attention` that returns int, float, bool typed outputs.

Cherry-pick of https://github.com/pytorch/pytorch/pull/115431 into release/2.2 branch
Approved by: https://github.com/titaiwangms, https://github.com/thiagocrepaldi
2023-12-14 14:24:34 -08:00
8be26111f9 [Release/2.2] [export] Do not copy state_dict in run_decomp (#115753)
Fixes https://github.com/pytorch/pytorch/issues/114628

Cherry-pick of  https://github.com/pytorch/pytorch/pull/115269 into release/2.2 branch
Approved by: https://github.com/thiagocrepaldi, https://github.com/ydwu4

Co-authored-by: angelayi <yiangela7@gmail.com>
2023-12-14 14:22:37 -08:00
1b70285fcd Fix SDPA for SAM (#115636) (#115667)
Addresses the regression for Segment Anything Fast in https://github.com/pytorch-labs/segment-anything-fast/issues/99
Cherry-pick of  https://github.com/pytorch/pytorch/pull/115636 into release/2.2
Approved by: https://github.com/soulitzer, https://github.com/ani300
2023-12-14 14:20:13 -08:00
1518578b54 [Release/2.2]Rename _device_mesh.py to device_mesh.py (#115600)
Cherry pick of https://github.com/pytorch/pytorch/pull/115193 into release/2.2 branch

Rename `_device_mesh.py` to `device_mesh.py`, update all callsites, add documentation.
We created stubs for public class and methods in torch.distributed.device_mesh so that torch.distributed.device_mesh can be imported with or without distributed is available().

Original diff reverted: D51629761
Original PR reverted: https://github.com/pytorch/pytorch/pull/115099
Prior to landing, CI signals are all passed. Shipit added the "ci/trunk" label to the PR and DID NOT wait for it and went ahead committing. More context can be found in the reverted PR above.

Test Plan: CI.

Differential Revision: D51861018

fbshipit-source-id: dc7b26cea7340d55498730123e82a42cef46ff55
2023-12-12 12:05:40 -08:00
e57f089704 [Release/2.2] Fix NULL dereference in binary CPU ops (#115470)
Targeted fix for https://github.com/pytorch/pytorch/issues/113037

A more fundamental one, where those functions are not even called for
empty tensors are coming later

Cherry-pick of release https://github.com/pytorch/pytorch/pull/115183 into release/2.2 branch

(cherry picked from commit b56b002842dd2bed8ed3ac4aa83c934b19adb931)
2023-12-08 19:33:13 -08:00
44d11579db Checkout release version if we are using python release (#115379)
* Checkout release version if we are using python release

* lint

* lint
2023-12-07 18:14:33 -05:00
0863b4c354 Add reset_storage method to FunctionalTensorWrapper (#115235) (#115320)
In certain edge cases when using lazy tensors, the base tensor stored in the `FunctionalStorageImpl` and the `value_` tensor stored in the `FunctionalTensorWrapper` diverge. For instance, take this simple example
```python
class Model(torch.nn.Module):
    def __init__(self):
        super().__init__()
        self.fc1 = torch.nn.Linear(4, 2, bias=False)

    def forward(self, x):
        return x @ self.fc1.weight.transpose(0, 1)

with torch.device("lazy"):
    model = Model()

    x = torch.ones(4)
    out = model(x)
```
The call to `transpose` on the lazily initialized weight `fc1.weight` applies a view op on the functional tensor which only gets propagated to the functional tensor wrapper and not the base tensor in the storage. Thus, causing them to diverge.

To fix this behaviour, we need to reset the functional tensor's storage. To facilitate this, we add a `_unsafe_reset_storage` method to `FunctionalTensorWrapper` which clears away the old storage and view metas.

Porting over PR from https://github.com/pytorch/pytorch/pull/115235
Cherry-picked: 73c0035160e7b2c5772417bb7206b316bdf34044
2023-12-07 09:47:54 -08:00
12bcfddce5 [releng] Increase triton version for release 2.2 (#115352) 2023-12-07 12:43:05 -05:00
99718eda57 [Release 2.2] Release only changes 3 (#115348) 2023-12-07 10:29:28 -05:00
24397727a8 [Release 2.2] Release only changes 2 (#115318)
* [Release only changes] Follow up

* fix
2023-12-06 21:49:00 -05:00
54aca571d6 [Release 2.2] Release only changes (#115292)
* [Release 2.2] Release only changes

* Release only part 2

* Pin unstable jobs

* fix

* Fix lint
2023-12-06 18:30:25 -05:00
1768 changed files with 51623 additions and 80816 deletions

View File

@ -19,7 +19,6 @@ See `build.sh` for valid build environments (it's the giant switch).
* `ubuntu` -- Dockerfile for Ubuntu image for CPU build and test jobs
* `ubuntu-cuda` -- Dockerfile for Ubuntu image with CUDA support for nvidia-docker
* `ubuntu-rocm` -- Dockerfile for Ubuntu image with ROCm support
* `ubuntu-xpu` -- Dockerfile for Ubuntu image with XPU support
## Usage

View File

@ -71,8 +71,6 @@ if [[ "$image" == *cuda* && "$UBUNTU_VERSION" != "22.04" ]]; then
DOCKERFILE="${OS}-cuda/Dockerfile"
elif [[ "$image" == *rocm* ]]; then
DOCKERFILE="${OS}-rocm/Dockerfile"
elif [[ "$image" == *xpu* ]]; then
DOCKERFILE="${OS}-xpu/Dockerfile"
elif [[ "$image" == *cuda*linter* ]]; then
# Use a separate Dockerfile for linter to keep a small image size
DOCKERFILE="linter-cuda/Dockerfile"
@ -220,16 +218,6 @@ case "$image" in
CONDA_CMAKE=yes
TRITON=yes
;;
pytorch-linux-jammy-xpu-2024.0-py3)
ANACONDA_PYTHON_VERSION=3.8
GCC_VERSION=11
PROTOBUF=yes
DB=yes
VISION=yes
BASEKIT_VERSION=2024.0.0-49522
NINJA_VERSION=1.9.0
CONDA_CMAKE=yes
;;
pytorch-linux-jammy-py3.8-gcc11-inductor-benchmarks)
ANACONDA_PYTHON_VERSION=3.8
GCC_VERSION=11
@ -386,7 +374,6 @@ docker build \
--build-arg "DOCS=${DOCS}" \
--build-arg "INDUCTOR_BENCHMARKS=${INDUCTOR_BENCHMARKS}" \
--build-arg "EXECUTORCH=${EXECUTORCH}" \
--build-arg "BASEKIT_VERSION=${BASEKIT_VERSION}" \
-f $(dirname ${DOCKERFILE})/Dockerfile \
-t "$tmp_tag" \
"$@" \

View File

@ -1 +1 @@
663882fe7dc518c04adf3d2ee5ccb7d99f41ade4
b2f5dfe80704404298467347b8ee3ac229efed47

View File

@ -1 +1 @@
e28a256d71f3cf2bcc7b69d6bda73a9b855e385e
bcad9dabe15021c53b6a88296e9d7a210044f108

View File

@ -75,7 +75,6 @@ install_ubuntu() {
libtool \
vim \
unzip \
gpg-agent \
gdb
# Should resolve issues related to various apt package repository cert issues

View File

@ -2,8 +2,8 @@
if [[ ${CUDNN_VERSION} == 8 ]]; then
# cuDNN license: https://developer.nvidia.com/cudnn/license_agreement
mkdir tmp_cudnn
pushd tmp_cudnn
mkdir tmp_cudnn && cd tmp_cudnn
CUDNN_NAME="cudnn-linux-x86_64-8.3.2.44_cuda11.5-archive"
if [[ ${CUDA_VERSION:0:4} == "12.1" ]]; then
CUDNN_NAME="cudnn-linux-x86_64-8.9.2.26_cuda12-archive"
curl --retry 3 -OLs https://developer.download.nvidia.com/compute/cudnn/redist/cudnn/linux-x86_64/${CUDNN_NAME}.tar.xz
@ -11,14 +11,17 @@ if [[ ${CUDNN_VERSION} == 8 ]]; then
CUDNN_NAME="cudnn-linux-x86_64-8.7.0.84_cuda11-archive"
curl --retry 3 -OLs https://developer.download.nvidia.com/compute/redist/cudnn/v8.7.0/local_installers/11.8/${CUDNN_NAME}.tar.xz
else
print "Unsupported CUDA version ${CUDA_VERSION}"
exit 1
curl --retry 3 -OLs https://developer.download.nvidia.com/compute/redist/cudnn/v8.3.2/local_installers/11.5/${CUDNN_NAME}.tar.xz
fi
tar xf ${CUDNN_NAME}.tar.xz
cp -a ${CUDNN_NAME}/include/* /usr/include/
cp -a ${CUDNN_NAME}/include/* /usr/local/cuda/include/
cp -a ${CUDNN_NAME}/include/* /usr/include/x86_64-linux-gnu/
cp -a ${CUDNN_NAME}/lib/* /usr/local/cuda/lib64/
popd
cp -a ${CUDNN_NAME}/lib/* /usr/lib/x86_64-linux-gnu/
cd ..
rm -rf tmp_cudnn
ldconfig
fi

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@ -1,21 +0,0 @@
#!/bin/bash
set -ex
# cuSPARSELt license: https://docs.nvidia.com/cuda/cusparselt/license.html
mkdir tmp_cusparselt && cd tmp_cusparselt
if [[ ${CUDA_VERSION:0:4} == "12.1" ]]; then
CUSPARSELT_NAME="libcusparse_lt-linux-x86_64-0.5.2.1-archive"
curl --retry 3 -OLs https://developer.download.nvidia.com/compute/cusparselt/redist/libcusparse_lt/linux-x86_64/${CUSPARSELT_NAME}.tar.xz
elif [[ ${CUDA_VERSION:0:4} == "11.8" ]]; then
CUSPARSELT_NAME="libcusparse_lt-linux-x86_64-0.4.0.7-archive"
curl --retry 3 -OLs https://developer.download.nvidia.com/compute/cusparselt/redist/libcusparse_lt/linux-x86_64/${CUSPARSELT_NAME}.tar.xz
fi
tar xf ${CUSPARSELT_NAME}.tar.xz
cp -a ${CUSPARSELT_NAME}/include/* /usr/local/cuda/include/
cp -a ${CUSPARSELT_NAME}/lib/* /usr/local/cuda/lib64/
cd ..
rm -rf tmp_cusparselt
ldconfig

View File

@ -1,115 +0,0 @@
#!/bin/bash
set -xe
# Intel® software for general purpose GPU capabilities.
# Refer to https://dgpu-docs.intel.com/releases/stable_647_21_20230714.html
# Intel® oneAPI Base Toolkit (version 2024.0.0) has been updated to include functional and security updates.
# Refer to https://www.intel.com/content/www/us/en/developer/tools/oneapi/base-toolkit-download.html
# Users should update to the latest version as it becomes available
function install_ubuntu() {
apt-get update -y
apt-get install -y gpg-agent wget
# Set up the repository. To do this, download the key to the system keyring
wget -qO - https://repositories.intel.com/gpu/intel-graphics.key \
| gpg --dearmor --output /usr/share/keyrings/intel-graphics.gpg
wget -O- https://apt.repos.intel.com/intel-gpg-keys/GPG-PUB-KEY-INTEL-SW-PRODUCTS.PUB \
| gpg --dearmor | tee /usr/share/keyrings/oneapi-archive-keyring.gpg > /dev/null
# Add the signed entry to APT sources and configure the APT client to use the Intel repository
echo "deb [arch=amd64 signed-by=/usr/share/keyrings/intel-graphics.gpg] https://repositories.intel.com/gpu/ubuntu jammy/production/2328 unified" \
| tee /etc/apt/sources.list.d/intel-gpu-jammy.list
echo "deb [signed-by=/usr/share/keyrings/oneapi-archive-keyring.gpg] https://apt.repos.intel.com/oneapi all main" \
| tee /etc/apt/sources.list.d/oneAPI.list
# Update the packages list and repository index
apt-get update
# The xpu-smi packages
apt-get install -y flex bison xpu-smi
# Compute and Media Runtimes
apt-get install -y \
intel-opencl-icd intel-level-zero-gpu level-zero \
intel-media-va-driver-non-free libmfx1 libmfxgen1 libvpl2 \
libegl-mesa0 libegl1-mesa libegl1-mesa-dev libgbm1 libgl1-mesa-dev libgl1-mesa-dri \
libglapi-mesa libgles2-mesa-dev libglx-mesa0 libigdgmm12 libxatracker2 mesa-va-drivers \
mesa-vdpau-drivers mesa-vulkan-drivers va-driver-all vainfo hwinfo clinfo
# Development Packages
apt-get install -y libigc-dev intel-igc-cm libigdfcl-dev libigfxcmrt-dev level-zero-dev
# Install Intel® oneAPI Base Toolkit
if [ -n "$BASEKIT_VERSION" ]; then
apt-get install intel-basekit=$BASEKIT_VERSION -y
else
apt-get install intel-basekit -y
fi
# Cleanup
apt-get autoclean && apt-get clean
rm -rf /var/lib/apt/lists/* /tmp/* /var/tmp/*
}
function install_centos() {
dnf install -y 'dnf-command(config-manager)'
dnf config-manager --add-repo \
https://repositories.intel.com/gpu/rhel/8.6/production/2328/unified/intel-gpu-8.6.repo
# To add the EPEL repository needed for DKMS
dnf -y install https://dl.fedoraproject.org/pub/epel/epel-release-latest-8.noarch.rpm
# https://dl.fedoraproject.org/pub/epel/epel-release-latest-9.noarch.rpm
# Create the YUM repository file in the /temp directory as a normal user
tee > /tmp/oneAPI.repo << EOF
[oneAPI]
name=Intel® oneAPI repository
baseurl=https://yum.repos.intel.com/oneapi
enabled=1
gpgcheck=1
repo_gpgcheck=1
gpgkey=https://yum.repos.intel.com/intel-gpg-keys/GPG-PUB-KEY-INTEL-SW-PRODUCTS.PUB
EOF
# Move the newly created oneAPI.repo file to the YUM configuration directory /etc/yum.repos.d
mv /tmp/oneAPI.repo /etc/yum.repos.d
# The xpu-smi packages
dnf install -y flex bison xpu-smi
# Compute and Media Runtimes
dnf install -y \
intel-opencl intel-media intel-mediasdk libmfxgen1 libvpl2\
level-zero intel-level-zero-gpu mesa-dri-drivers mesa-vulkan-drivers \
mesa-vdpau-drivers libdrm mesa-libEGL mesa-libgbm mesa-libGL \
mesa-libxatracker libvpl-tools intel-metrics-discovery \
intel-metrics-library intel-igc-core intel-igc-cm \
libva libva-utils intel-gmmlib libmetee intel-gsc intel-ocloc hwinfo clinfo
# Development packages
dnf install -y --refresh \
intel-igc-opencl-devel level-zero-devel intel-gsc-devel libmetee-devel \
level-zero-devel
# Install Intel® oneAPI Base Toolkit
dnf install intel-basekit -y
# Cleanup
dnf clean all
rm -rf /var/cache/yum
rm -rf /var/lib/yum/yumdb
rm -rf /var/lib/yum/history
}
# The installation depends on the base OS
ID=$(grep -oP '(?<=^ID=).+' /etc/os-release | tr -d '"')
case "$ID" in
ubuntu)
install_ubuntu
;;
centos)
install_centos
;;
*)
echo "Unable to determine OS..."
exit 1
;;
esac

View File

@ -299,7 +299,7 @@ pywavelets==1.4.1
#Pinned versions: 1.4.1
#test that import:
lxml==5.0.0.
lxml==4.9.4
#Description: This is a requirement of unittest-xml-reporting
# have to pin to 4.9.4 because 5.0.0 release on Dec 29th missing
# Python-3.9 binaries

View File

@ -142,12 +142,6 @@ COPY ./common/install_cudnn.sh install_cudnn.sh
RUN if [ "${CUDNN_VERSION}" -eq 8 ]; then bash install_cudnn.sh; fi
RUN rm install_cudnn.sh
# Install CUSPARSELT
ARG CUDA_VERSION
COPY ./common/install_cusparselt.sh install_cusparselt.sh
RUN bash install_cusparselt.sh
RUN rm install_cusparselt.sh
# Delete /usr/local/cuda-11.X/cuda-11.X symlinks
RUN if [ -h /usr/local/cuda-11.6/cuda-11.6 ]; then rm /usr/local/cuda-11.6/cuda-11.6; fi
RUN if [ -h /usr/local/cuda-11.7/cuda-11.7 ]; then rm /usr/local/cuda-11.7/cuda-11.7; fi

View File

@ -1,118 +0,0 @@
ARG UBUNTU_VERSION
FROM ubuntu:${UBUNTU_VERSION}
ARG UBUNTU_VERSION
ENV DEBIAN_FRONTEND noninteractive
ARG CLANG_VERSION
# Install common dependencies (so that this step can be cached separately)
COPY ./common/install_base.sh install_base.sh
RUN bash ./install_base.sh && rm install_base.sh
# Install clang
ARG LLVMDEV
COPY ./common/install_clang.sh install_clang.sh
RUN bash ./install_clang.sh && rm install_clang.sh
# Install user
COPY ./common/install_user.sh install_user.sh
RUN bash ./install_user.sh && rm install_user.sh
# Install katex
ARG KATEX
COPY ./common/install_docs_reqs.sh install_docs_reqs.sh
RUN bash ./install_docs_reqs.sh && rm install_docs_reqs.sh
# Install conda and other packages (e.g., numpy, pytest)
ARG ANACONDA_PYTHON_VERSION
ARG CONDA_CMAKE
ARG DOCS
ENV ANACONDA_PYTHON_VERSION=$ANACONDA_PYTHON_VERSION
ENV PATH /opt/conda/envs/py_$ANACONDA_PYTHON_VERSION/bin:/opt/conda/bin:$PATH
ENV DOCS=$DOCS
COPY requirements-ci.txt requirements-docs.txt /opt/conda/
COPY ./common/install_conda.sh install_conda.sh
COPY ./common/common_utils.sh common_utils.sh
RUN bash ./install_conda.sh && rm install_conda.sh common_utils.sh /opt/conda/requirements-ci.txt /opt/conda/requirements-docs.txt
# Install gcc
ARG GCC_VERSION
COPY ./common/install_gcc.sh install_gcc.sh
RUN bash ./install_gcc.sh && rm install_gcc.sh
# Install lcov for C++ code coverage
COPY ./common/install_lcov.sh install_lcov.sh
RUN bash ./install_lcov.sh && rm install_lcov.sh
COPY ./common/install_openssl.sh install_openssl.sh
RUN bash ./install_openssl.sh
ENV OPENSSL_ROOT_DIR /opt/openssl
ENV OPENSSL_DIR /opt/openssl
RUN rm install_openssl.sh
ARG INDUCTOR_BENCHMARKS
COPY ./common/install_inductor_benchmark_deps.sh install_inductor_benchmark_deps.sh
COPY ./common/common_utils.sh common_utils.sh
COPY ci_commit_pins/huggingface.txt huggingface.txt
COPY ci_commit_pins/timm.txt timm.txt
RUN if [ -n "${INDUCTOR_BENCHMARKS}" ]; then bash ./install_inductor_benchmark_deps.sh; fi
RUN rm install_inductor_benchmark_deps.sh common_utils.sh timm.txt huggingface.txt
ARG TRITON
# Install triton, this needs to be done before sccache because the latter will
# try to reach out to S3, which docker build runners don't have access
COPY ./common/install_triton.sh install_triton.sh
COPY ./common/common_utils.sh common_utils.sh
# TODO: will add triton xpu commit
COPY ci_commit_pins/triton.txt triton.txt
RUN if [ -n "${TRITON}" ]; then bash ./install_triton.sh; fi
RUN rm install_triton.sh common_utils.sh triton.txt
# (optional) Install database packages like LMDB and LevelDB
ARG DB
COPY ./common/install_db.sh install_db.sh
RUN if [ -n "${DB}" ]; then bash ./install_db.sh; fi
RUN rm install_db.sh
ENV INSTALLED_DB ${DB}
# (optional) Install vision packages like OpenCV and ffmpeg
ARG VISION
COPY ./common/install_vision.sh ./common/cache_vision_models.sh ./common/common_utils.sh ./
RUN if [ -n "${VISION}" ]; then bash ./install_vision.sh; fi
RUN rm install_vision.sh cache_vision_models.sh common_utils.sh
ENV INSTALLED_VISION ${VISION}
# Install XPU Dependencies
ARG BASEKIT_VERSION
COPY ./common/install_xpu.sh install_xpu.sh
RUN bash ./install_xpu.sh && rm install_xpu.sh
# (optional) Install non-default CMake version
ARG CMAKE_VERSION
COPY ./common/install_cmake.sh install_cmake.sh
RUN if [ -n "${CMAKE_VERSION}" ]; then bash ./install_cmake.sh; fi
RUN rm install_cmake.sh
# (optional) Install non-default Ninja version
ARG NINJA_VERSION
COPY ./common/install_ninja.sh install_ninja.sh
RUN if [ -n "${NINJA_VERSION}" ]; then bash ./install_ninja.sh; fi
RUN rm install_ninja.sh
# Install ccache/sccache (do this last, so we get priority in PATH)
COPY ./common/install_cache.sh install_cache.sh
ENV PATH /opt/cache/bin:$PATH
RUN bash ./install_cache.sh && rm install_cache.sh
# Include BUILD_ENVIRONMENT environment variable in image
ARG BUILD_ENVIRONMENT
ENV BUILD_ENVIRONMENT ${BUILD_ENVIRONMENT}
# Install LLVM dev version (Defined in the pytorch/builder github repository)
COPY --from=pytorch/llvm:9.0.1 /opt/llvm /opt/llvm
USER jenkins
CMD ["bash"]

View File

@ -153,12 +153,6 @@ if [[ "$BUILD_ENVIRONMENT" == *rocm* ]]; then
python tools/amd_build/build_amd.py
fi
if [[ "$BUILD_ENVIRONMENT" == *xpu* ]]; then
# shellcheck disable=SC1091
source /opt/intel/oneapi/compiler/latest/env/vars.sh
export USE_XPU=1
fi
# sccache will fail for CUDA builds if all cores are used for compiling
# gcc 7 with sccache seems to have intermittent OOM issue if all cores are used
if [ -z "$MAX_JOBS" ]; then

View File

@ -173,7 +173,7 @@ function install_torchrec_and_fbgemm() {
function clone_pytorch_xla() {
if [[ ! -d ./xla ]]; then
git clone --recursive --quiet https://github.com/pytorch/xla.git
git clone --recursive -b r2.2 https://github.com/pytorch/xla.git
pushd xla
# pin the xla hash so that we don't get broken by changes to xla
git checkout "$(cat ../.github/ci_commit_pins/xla.txt)"

View File

@ -18,10 +18,6 @@ BUILD_DIR="build"
BUILD_RENAMED_DIR="build_renamed"
BUILD_BIN_DIR="$BUILD_DIR"/bin
#Set Default values for these variables in case they are not set
SHARD_NUMBER="${SHARD_NUMBER:=1}"
NUM_TEST_SHARDS="${NUM_TEST_SHARDS:=1}"
export VALGRIND=ON
# export TORCH_INDUCTOR_INSTALL_GXX=ON
if [[ "$BUILD_ENVIRONMENT" == *clang9* ]]; then
@ -128,8 +124,6 @@ if [[ "$BUILD_ENVIRONMENT" == *cuda* || "$BUILD_ENVIRONMENT" == *rocm* ]]; then
# mainly used so that we're not spending extra cycles testing cpu
# devices on expensive gpu machines
export PYTORCH_TESTING_DEVICE_ONLY_FOR="cuda"
elif [[ "$BUILD_ENVIRONMENT" == *xpu* ]]; then
export PYTORCH_TESTING_DEVICE_ONLY_FOR="xpu"
fi
if [[ "$TEST_CONFIG" == *crossref* ]]; then
@ -142,15 +136,6 @@ if [[ "$BUILD_ENVIRONMENT" == *rocm* ]]; then
rocminfo | grep -E 'Name:.*\sgfx|Marketing'
fi
if [[ "$BUILD_ENVIRONMENT" == *xpu* ]]; then
# Source Intel oneAPI envrioment script to enable xpu runtime related libraries
# refer to https://www.intel.com/content/www/us/en/docs/oneapi/programming-guide/2024-0/use-the-setvars-and-oneapi-vars-scripts-with-linux.html
# shellcheck disable=SC1091
source /opt/intel/oneapi/compiler/latest/env/vars.sh
# Check XPU status before testing
xpu-smi discovery
fi
if [[ "$BUILD_ENVIRONMENT" != *-bazel-* ]] ; then
# JIT C++ extensions require ninja.
pip_install --user "ninja==1.10.2"
@ -274,7 +259,6 @@ test_dynamo_shard() {
--exclude-jit-executor \
--exclude-distributed-tests \
--exclude \
test_ao_sparsity \
test_autograd \
test_jit \
test_proxy_tensor \
@ -324,10 +308,8 @@ test_inductor() {
# docker build uses bdist_wheel which does not work with test_aot_inductor
# TODO: need a faster way to build
if [[ "$BUILD_ENVIRONMENT" != *rocm* ]]; then
BUILD_AOT_INDUCTOR_TEST=1 python setup.py develop
CPP_TESTS_DIR="${BUILD_BIN_DIR}" LD_LIBRARY_PATH="${TORCH_LIB_DIR}" python test/run_test.py --cpp --verbose -i cpp/test_aot_inductor
fi
BUILD_AOT_INDUCTOR_TEST=1 python setup.py develop
CPP_TESTS_DIR="${BUILD_BIN_DIR}" LD_LIBRARY_PATH="${TORCH_LIB_DIR}" python test/run_test.py --cpp --verbose -i cpp/test_aot_inductor
}
# "Global" flags for inductor benchmarking controlled by TEST_CONFIG
@ -407,8 +389,8 @@ test_perf_for_dashboard() {
--output "$TEST_REPORTS_DIR/${backend}_dynamic_${suite}_${dtype}_${mode}_cuda_${target}.csv"
fi
if [[ "$DASHBOARD_TAG" == *cppwrapper-true* ]] && [[ "$mode" == "inference" ]]; then
TORCHINDUCTOR_CPP_WRAPPER=1 python "benchmarks/dynamo/$suite.py" \
"${target_flag[@]}" --"$mode" --"$dtype" --backend "$backend" --disable-cudagraphs "$@" \
python "benchmarks/dynamo/$suite.py" \
"${target_flag[@]}" --"$mode" --"$dtype" --backend "$backend" --disable-cudagraphs --cpp-wrapper "$@" \
--output "$TEST_REPORTS_DIR/${backend}_cpp_wrapper_${suite}_${dtype}_${mode}_cuda_${target}.csv"
fi
if [[ "$DASHBOARD_TAG" == *freezing_cudagraphs-true* ]] && [[ "$mode" == "inference" ]]; then
@ -509,13 +491,6 @@ test_inductor_torchbench_smoketest_perf() {
TEST_REPORTS_DIR=$(pwd)/test/test-reports
mkdir -p "$TEST_REPORTS_DIR"
# smoke test the cpp_wrapper mode
TORCHINDUCTOR_CPP_WRAPPER=1 python benchmarks/dynamo/torchbench.py --device cuda --accuracy --bfloat16 \
--inference --inductor --only hf_T5 --output "$TEST_REPORTS_DIR/inductor_cpp_wrapper_smoketest.csv"
python benchmarks/dynamo/check_accuracy.py \
--actual "$TEST_REPORTS_DIR/inductor_cpp_wrapper_smoketest.csv" \
--expected "benchmarks/dynamo/ci_expected_accuracy/inductor_torchbench_inference.csv"
python benchmarks/dynamo/torchbench.py --device cuda --performance --backend inductor --float16 --training \
--batch-size-file "$(realpath benchmarks/dynamo/torchbench_models_list.txt)" --only hf_Bert \
--output "$TEST_REPORTS_DIR/inductor_training_smoketest.csv"
@ -525,11 +500,7 @@ test_inductor_torchbench_smoketest_perf() {
python benchmarks/dynamo/torchbench.py --device cuda --performance --bfloat16 --inference \
--export-aot-inductor --only nanogpt --output "$TEST_REPORTS_DIR/inductor_inference_smoketest.csv"
# The threshold value needs to be actively maintained to make this check useful
# The perf number of nanogpt seems not very stable, e.g.
# https://github.com/pytorch/pytorch/actions/runs/7158691360/job/19491437314,
# and thus we lower its threshold to reduce flakiness. If this continues to be a problem,
# we switch to use some other model.
python benchmarks/dynamo/check_perf_csv.py -f "$TEST_REPORTS_DIR/inductor_inference_smoketest.csv" -t 4.9
python benchmarks/dynamo/check_perf_csv.py -f "$TEST_REPORTS_DIR/inductor_inference_smoketest.csv" -t 5.2
# Check memory compression ratio for a few models
for test in hf_Albert timm_vision_transformer; do
@ -689,20 +660,6 @@ test_libtorch_api() {
fi
}
test_xpu_bin(){
TEST_REPORTS_DIR=$(pwd)/test/test-reports
mkdir -p "$TEST_REPORTS_DIR"
for xpu_case in "${BUILD_BIN_DIR}"/*{xpu,sycl}*
do
if [[ "$xpu_case" != *"*"* ]]; then
case_name=$(basename "$xpu_case")
echo "Testing ${case_name} ..."
"$xpu_case" --gtest_output=xml:"$TEST_REPORTS_DIR"/"$case_name".xml
fi
done
}
test_aot_compilation() {
echo "Testing Ahead of Time compilation"
ln -sf "$TORCH_LIB_DIR"/libc10* "$TORCH_BIN_DIR"
@ -1112,7 +1069,7 @@ elif [[ "${TEST_CONFIG}" == *torchbench* ]]; then
# https://github.com/opencv/opencv-python/issues/885
pip_install opencv-python==4.8.0.74
if [[ "${TEST_CONFIG}" == *inductor_torchbench_smoketest_perf* ]]; then
checkout_install_torchbench hf_Bert hf_Albert nanogpt timm_vision_transformer
checkout_install_torchbench hf_Bert hf_Albert timm_vision_transformer
PYTHONPATH=$(pwd)/torchbench test_inductor_torchbench_smoketest_perf
else
checkout_install_torchbench
@ -1128,21 +1085,19 @@ elif [[ "${TEST_CONFIG}" == *inductor* && "${SHARD_NUMBER}" == 1 ]]; then
test_inductor
test_inductor_distributed
elif [[ "${TEST_CONFIG}" == *dynamo* && "${SHARD_NUMBER}" == 1 && $NUM_TEST_SHARDS -gt 1 ]]; then
test_without_numpy
install_torchvision
test_dynamo_shard 1
test_aten
elif [[ "${TEST_CONFIG}" == *dynamo* && $SHARD_NUMBER -gt 1 && $NUM_TEST_SHARDS -gt 1 ]]; then
elif [[ "${TEST_CONFIG}" == *dynamo* && "${SHARD_NUMBER}" == 2 && $NUM_TEST_SHARDS -gt 1 ]]; then
install_torchvision
test_dynamo_shard "${SHARD_NUMBER}"
test_dynamo_shard 2
elif [[ "${SHARD_NUMBER}" == 1 && $NUM_TEST_SHARDS -gt 1 ]]; then
test_without_numpy
install_torchvision
test_python_shard 1
test_aten
test_libtorch 1
if [[ "${BUILD_ENVIRONMENT}" == *xpu* ]]; then
test_xpu_bin
fi
elif [[ "${SHARD_NUMBER}" == 2 && $NUM_TEST_SHARDS -gt 1 ]]; then
install_torchvision
test_python_shard 2
@ -1167,11 +1122,6 @@ elif [[ "${BUILD_ENVIRONMENT}" == *rocm* && -n "$TESTS_TO_INCLUDE" ]]; then
install_torchvision
test_python
test_aten
elif [[ "${BUILD_ENVIRONMENT}" == *xpu* ]]; then
install_torchvision
test_python
test_aten
test_xpu_bin
else
install_torchvision
install_monkeytype

View File

@ -0,0 +1,198 @@
"""
This module models the tree of configuration variants
for "smoketest" builds.
Each subclass of ConfigNode represents a layer of the configuration hierarchy.
These tree nodes encapsulate the logic for whether a branch of the hierarchy
should be "pruned".
"""
from collections import OrderedDict
import cimodel.data.dimensions as dimensions
from cimodel.lib.conf_tree import ConfigNode
LINKING_DIMENSIONS = [
"shared",
"static",
]
DEPS_INCLUSION_DIMENSIONS = [
"with-deps",
"without-deps",
]
def get_processor_arch_name(gpu_version):
return (
"cpu"
if not gpu_version
else (
"cu" + gpu_version.strip("cuda")
if gpu_version.startswith("cuda")
else gpu_version
)
)
CONFIG_TREE_DATA = OrderedDict()
# GCC config variants:
#
# All the nightlies (except libtorch with new gcc ABI) are built with devtoolset7,
# which can only build with old gcc ABI. It is better than devtoolset3
# because it understands avx512, which is needed for good fbgemm performance.
#
# Libtorch with new gcc ABI is built with gcc 5.4 on Ubuntu 16.04.
LINUX_GCC_CONFIG_VARIANTS = OrderedDict(
manywheel=["devtoolset7"],
conda=["devtoolset7"],
libtorch=[
"devtoolset7",
"gcc5.4_cxx11-abi",
],
)
WINDOWS_LIBTORCH_CONFIG_VARIANTS = [
"debug",
"release",
]
class TopLevelNode(ConfigNode):
def __init__(self, node_name, config_tree_data, smoke):
super().__init__(None, node_name)
self.config_tree_data = config_tree_data
self.props["smoke"] = smoke
def get_children(self):
return [
OSConfigNode(self, x, c, p) for (x, (c, p)) in self.config_tree_data.items()
]
class OSConfigNode(ConfigNode):
def __init__(self, parent, os_name, gpu_versions, py_tree):
super().__init__(parent, os_name)
self.py_tree = py_tree
self.props["os_name"] = os_name
self.props["gpu_versions"] = gpu_versions
def get_children(self):
return [PackageFormatConfigNode(self, k, v) for k, v in self.py_tree.items()]
class PackageFormatConfigNode(ConfigNode):
def __init__(self, parent, package_format, python_versions):
super().__init__(parent, package_format)
self.props["python_versions"] = python_versions
self.props["package_format"] = package_format
def get_children(self):
if self.find_prop("os_name") == "linux":
return [
LinuxGccConfigNode(self, v)
for v in LINUX_GCC_CONFIG_VARIANTS[self.find_prop("package_format")]
]
elif (
self.find_prop("os_name") == "windows"
and self.find_prop("package_format") == "libtorch"
):
return [
WindowsLibtorchConfigNode(self, v)
for v in WINDOWS_LIBTORCH_CONFIG_VARIANTS
]
else:
return [ArchConfigNode(self, v) for v in self.find_prop("gpu_versions")]
class LinuxGccConfigNode(ConfigNode):
def __init__(self, parent, gcc_config_variant):
super().__init__(parent, "GCC_CONFIG_VARIANT=" + str(gcc_config_variant))
self.props["gcc_config_variant"] = gcc_config_variant
def get_children(self):
gpu_versions = self.find_prop("gpu_versions")
# XXX devtoolset7 on CUDA 9.0 is temporarily disabled
# see https://github.com/pytorch/pytorch/issues/20066
if self.find_prop("gcc_config_variant") == "devtoolset7":
gpu_versions = filter(lambda x: x != "cuda_90", gpu_versions)
# XXX disabling conda rocm build since docker images are not there
if self.find_prop("package_format") == "conda":
gpu_versions = filter(
lambda x: x not in dimensions.ROCM_VERSION_LABELS, gpu_versions
)
# XXX libtorch rocm build is temporarily disabled
if self.find_prop("package_format") == "libtorch":
gpu_versions = filter(
lambda x: x not in dimensions.ROCM_VERSION_LABELS, gpu_versions
)
return [ArchConfigNode(self, v) for v in gpu_versions]
class WindowsLibtorchConfigNode(ConfigNode):
def __init__(self, parent, libtorch_config_variant):
super().__init__(
parent, "LIBTORCH_CONFIG_VARIANT=" + str(libtorch_config_variant)
)
self.props["libtorch_config_variant"] = libtorch_config_variant
def get_children(self):
return [ArchConfigNode(self, v) for v in self.find_prop("gpu_versions")]
class ArchConfigNode(ConfigNode):
def __init__(self, parent, gpu):
super().__init__(parent, get_processor_arch_name(gpu))
self.props["gpu"] = gpu
def get_children(self):
return [PyVersionConfigNode(self, v) for v in self.find_prop("python_versions")]
class PyVersionConfigNode(ConfigNode):
def __init__(self, parent, pyver):
super().__init__(parent, pyver)
self.props["pyver"] = pyver
def get_children(self):
package_format = self.find_prop("package_format")
os_name = self.find_prop("os_name")
has_libtorch_variants = package_format == "libtorch" and os_name == "linux"
linking_variants = LINKING_DIMENSIONS if has_libtorch_variants else []
return [LinkingVariantConfigNode(self, v) for v in linking_variants]
class LinkingVariantConfigNode(ConfigNode):
def __init__(self, parent, linking_variant):
super().__init__(parent, linking_variant)
def get_children(self):
return [
DependencyInclusionConfigNode(self, v) for v in DEPS_INCLUSION_DIMENSIONS
]
class DependencyInclusionConfigNode(ConfigNode):
def __init__(self, parent, deps_variant):
super().__init__(parent, deps_variant)
self.props["libtorch_variant"] = "-".join(
[self.parent.get_label(), self.get_label()]
)

View File

@ -0,0 +1,275 @@
from collections import OrderedDict
import cimodel.data.binary_build_data as binary_build_data
import cimodel.data.simple.util.branch_filters as branch_filters
import cimodel.lib.conf_tree as conf_tree
import cimodel.lib.miniutils as miniutils
class Conf:
def __init__(
self,
os,
gpu_version,
pydistro,
parms,
smoke,
libtorch_variant,
gcc_config_variant,
libtorch_config_variant,
):
self.os = os
self.gpu_version = gpu_version
self.pydistro = pydistro
self.parms = parms
self.smoke = smoke
self.libtorch_variant = libtorch_variant
self.gcc_config_variant = gcc_config_variant
self.libtorch_config_variant = libtorch_config_variant
def gen_build_env_parms(self):
elems = (
[self.pydistro]
+ self.parms
+ [binary_build_data.get_processor_arch_name(self.gpu_version)]
)
if self.gcc_config_variant is not None:
elems.append(str(self.gcc_config_variant))
if self.libtorch_config_variant is not None:
elems.append(str(self.libtorch_config_variant))
return elems
def gen_docker_image(self):
if self.gcc_config_variant == "gcc5.4_cxx11-abi":
if self.gpu_version is None:
return miniutils.quote("pytorch/libtorch-cxx11-builder:cpu")
else:
return miniutils.quote(
f"pytorch/libtorch-cxx11-builder:{self.gpu_version}"
)
if self.pydistro == "conda":
if self.gpu_version is None:
return miniutils.quote("pytorch/conda-builder:cpu")
else:
return miniutils.quote(f"pytorch/conda-builder:{self.gpu_version}")
docker_word_substitution = {
"manywheel": "manylinux",
"libtorch": "manylinux",
}
docker_distro_prefix = miniutils.override(
self.pydistro, docker_word_substitution
)
# The cpu nightlies are built on the pytorch/manylinux-cuda102 docker image
# TODO cuda images should consolidate into tag-base images similar to rocm
alt_docker_suffix = (
"cuda102"
if not self.gpu_version
else (
"rocm:" + self.gpu_version.strip("rocm")
if self.gpu_version.startswith("rocm")
else self.gpu_version
)
)
docker_distro_suffix = (
alt_docker_suffix
if self.pydistro != "conda"
else ("cuda" if alt_docker_suffix.startswith("cuda") else "rocm")
)
return miniutils.quote(
"pytorch/" + docker_distro_prefix + "-" + docker_distro_suffix
)
def get_name_prefix(self):
return "smoke" if self.smoke else "binary"
def gen_build_name(self, build_or_test, nightly):
parts = [self.get_name_prefix(), self.os] + self.gen_build_env_parms()
if nightly:
parts.append("nightly")
if self.libtorch_variant:
parts.append(self.libtorch_variant)
if not self.smoke:
parts.append(build_or_test)
joined = "_".join(parts)
return joined.replace(".", "_")
def gen_workflow_job(self, phase, upload_phase_dependency=None, nightly=False):
job_def = OrderedDict()
job_def["name"] = self.gen_build_name(phase, nightly)
job_def["build_environment"] = miniutils.quote(
" ".join(self.gen_build_env_parms())
)
if self.smoke:
job_def["requires"] = [
"update_s3_htmls",
]
job_def["filters"] = branch_filters.gen_filter_dict(
branches_list=["postnightly"],
)
else:
filter_branch = r"/.*/"
job_def["filters"] = branch_filters.gen_filter_dict(
branches_list=[filter_branch],
tags_list=[branch_filters.RC_PATTERN],
)
if self.libtorch_variant:
job_def["libtorch_variant"] = miniutils.quote(self.libtorch_variant)
if phase == "test":
if not self.smoke:
job_def["requires"] = [self.gen_build_name("build", nightly)]
if not (self.smoke and self.os == "macos") and self.os != "windows":
job_def["docker_image"] = self.gen_docker_image()
# fix this. only works on cuda not rocm
if self.os != "windows" and self.gpu_version:
job_def["use_cuda_docker_runtime"] = miniutils.quote("1")
else:
if self.os == "linux" and phase != "upload":
job_def["docker_image"] = self.gen_docker_image()
if phase == "test":
if self.gpu_version:
if self.os == "windows":
job_def["executor"] = "windows-with-nvidia-gpu"
else:
job_def["resource_class"] = "gpu.medium"
os_name = miniutils.override(self.os, {"macos": "mac"})
job_name = "_".join([self.get_name_prefix(), os_name, phase])
return {job_name: job_def}
def gen_upload_job(self, phase, requires_dependency):
"""Generate binary_upload job for configuration
Output looks similar to:
- binary_upload:
name: binary_linux_manywheel_3_7m_cu113_devtoolset7_nightly_upload
context: org-member
requires: binary_linux_manywheel_3_7m_cu113_devtoolset7_nightly_test
filters:
branches:
only:
- nightly
tags:
only: /v[0-9]+(\\.[0-9]+)*-rc[0-9]+/
package_type: manywheel
upload_subfolder: cu113
"""
return {
"binary_upload": OrderedDict(
{
"name": self.gen_build_name(phase, nightly=True),
"context": "org-member",
"requires": [
self.gen_build_name(requires_dependency, nightly=True)
],
"filters": branch_filters.gen_filter_dict(
branches_list=["nightly"],
tags_list=[branch_filters.RC_PATTERN],
),
"package_type": self.pydistro,
"upload_subfolder": binary_build_data.get_processor_arch_name(
self.gpu_version,
),
}
)
}
def get_root(smoke, name):
return binary_build_data.TopLevelNode(
name,
binary_build_data.CONFIG_TREE_DATA,
smoke,
)
def gen_build_env_list(smoke):
root = get_root(smoke, "N/A")
config_list = conf_tree.dfs(root)
newlist = []
for c in config_list:
conf = Conf(
c.find_prop("os_name"),
c.find_prop("gpu"),
c.find_prop("package_format"),
[c.find_prop("pyver")],
c.find_prop("smoke")
and not (c.find_prop("os_name") == "macos_arm64"), # don't test arm64
c.find_prop("libtorch_variant"),
c.find_prop("gcc_config_variant"),
c.find_prop("libtorch_config_variant"),
)
newlist.append(conf)
return newlist
def predicate_exclude_macos(config):
return config.os == "linux" or config.os == "windows"
def get_nightly_uploads():
configs = gen_build_env_list(False)
mylist = []
for conf in configs:
phase_dependency = "test" if predicate_exclude_macos(conf) else "build"
mylist.append(conf.gen_upload_job("upload", phase_dependency))
return mylist
def get_post_upload_jobs():
return [
{
"update_s3_htmls": {
"name": "update_s3_htmls",
"context": "org-member",
"filters": branch_filters.gen_filter_dict(
branches_list=["postnightly"],
),
},
},
]
def get_nightly_tests():
configs = gen_build_env_list(False)
filtered_configs = filter(predicate_exclude_macos, configs)
tests = []
for conf_options in filtered_configs:
yaml_item = conf_options.gen_workflow_job("test", nightly=True)
tests.append(yaml_item)
return tests
def get_jobs(toplevel_key, smoke):
jobs_list = []
configs = gen_build_env_list(smoke)
phase = "build" if toplevel_key == "binarybuilds" else "test"
for build_config in configs:
# don't test for macos_arm64 as it's cross compiled
if phase != "test" or build_config.os != "macos_arm64":
jobs_list.append(build_config.gen_workflow_job(phase, nightly=True))
return jobs_list
def get_binary_build_jobs():
return get_jobs("binarybuilds", False)
def get_binary_smoke_test_jobs():
return get_jobs("binarysmoketests", True)

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PHASES = ["build", "test"]
CUDA_VERSIONS = [
"102",
"113",
"116",
"117",
]
ROCM_VERSIONS = [
"4.3.1",
"4.5.2",
]
ROCM_VERSION_LABELS = ["rocm" + v for v in ROCM_VERSIONS]
GPU_VERSIONS = [None] + ["cuda" + v for v in CUDA_VERSIONS] + ROCM_VERSION_LABELS
STANDARD_PYTHON_VERSIONS = ["3.7", "3.8", "3.9", "3.10"]

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from cimodel.lib.conf_tree import ConfigNode
CONFIG_TREE_DATA = []
def get_major_pyver(dotted_version):
parts = dotted_version.split(".")
return "py" + parts[0]
class TreeConfigNode(ConfigNode):
def __init__(self, parent, node_name, subtree):
super().__init__(parent, self.modify_label(node_name))
self.subtree = subtree
self.init2(node_name)
def modify_label(self, label):
return label
def init2(self, node_name):
pass
def get_children(self):
return [self.child_constructor()(self, k, v) for (k, v) in self.subtree]
class TopLevelNode(TreeConfigNode):
def __init__(self, node_name, subtree):
super().__init__(None, node_name, subtree)
# noinspection PyMethodMayBeStatic
def child_constructor(self):
return DistroConfigNode
class DistroConfigNode(TreeConfigNode):
def init2(self, node_name):
self.props["distro_name"] = node_name
def child_constructor(self):
distro = self.find_prop("distro_name")
next_nodes = {
"xenial": XenialCompilerConfigNode,
"bionic": BionicCompilerConfigNode,
}
return next_nodes[distro]
class PyVerConfigNode(TreeConfigNode):
def init2(self, node_name):
self.props["pyver"] = node_name
self.props["abbreviated_pyver"] = get_major_pyver(node_name)
if node_name == "3.9":
self.props["abbreviated_pyver"] = "py3.9"
# noinspection PyMethodMayBeStatic
def child_constructor(self):
return ExperimentalFeatureConfigNode
class ExperimentalFeatureConfigNode(TreeConfigNode):
def init2(self, node_name):
self.props["experimental_feature"] = node_name
def child_constructor(self):
experimental_feature = self.find_prop("experimental_feature")
next_nodes = {
"asan": AsanConfigNode,
"xla": XlaConfigNode,
"mps": MPSConfigNode,
"vulkan": VulkanConfigNode,
"parallel_tbb": ParallelTBBConfigNode,
"crossref": CrossRefConfigNode,
"dynamo": DynamoConfigNode,
"parallel_native": ParallelNativeConfigNode,
"onnx": ONNXConfigNode,
"libtorch": LibTorchConfigNode,
"important": ImportantConfigNode,
"build_only": BuildOnlyConfigNode,
"shard_test": ShardTestConfigNode,
"cuda_gcc_override": CudaGccOverrideConfigNode,
"pure_torch": PureTorchConfigNode,
"slow_gradcheck": SlowGradcheckConfigNode,
}
return next_nodes[experimental_feature]
class SlowGradcheckConfigNode(TreeConfigNode):
def init2(self, node_name):
self.props["is_slow_gradcheck"] = True
def child_constructor(self):
return ExperimentalFeatureConfigNode
class PureTorchConfigNode(TreeConfigNode):
def modify_label(self, label):
return "PURE_TORCH=" + str(label)
def init2(self, node_name):
self.props["is_pure_torch"] = node_name
def child_constructor(self):
return ImportantConfigNode
class XlaConfigNode(TreeConfigNode):
def modify_label(self, label):
return "XLA=" + str(label)
def init2(self, node_name):
self.props["is_xla"] = node_name
def child_constructor(self):
return ImportantConfigNode
class MPSConfigNode(TreeConfigNode):
def modify_label(self, label):
return "MPS=" + str(label)
def init2(self, node_name):
self.props["is_mps"] = node_name
def child_constructor(self):
return ImportantConfigNode
class AsanConfigNode(TreeConfigNode):
def modify_label(self, label):
return "Asan=" + str(label)
def init2(self, node_name):
self.props["is_asan"] = node_name
def child_constructor(self):
return ExperimentalFeatureConfigNode
class ONNXConfigNode(TreeConfigNode):
def modify_label(self, label):
return "Onnx=" + str(label)
def init2(self, node_name):
self.props["is_onnx"] = node_name
def child_constructor(self):
return ImportantConfigNode
class VulkanConfigNode(TreeConfigNode):
def modify_label(self, label):
return "Vulkan=" + str(label)
def init2(self, node_name):
self.props["is_vulkan"] = node_name
def child_constructor(self):
return ImportantConfigNode
class ParallelTBBConfigNode(TreeConfigNode):
def modify_label(self, label):
return "PARALLELTBB=" + str(label)
def init2(self, node_name):
self.props["parallel_backend"] = "paralleltbb"
def child_constructor(self):
return ImportantConfigNode
class CrossRefConfigNode(TreeConfigNode):
def init2(self, node_name):
self.props["is_crossref"] = node_name
def child_constructor(self):
return ImportantConfigNode
class DynamoConfigNode(TreeConfigNode):
def init2(self, node_name):
self.props["is_dynamo"] = node_name
def child_constructor(self):
return ImportantConfigNode
class ParallelNativeConfigNode(TreeConfigNode):
def modify_label(self, label):
return "PARALLELNATIVE=" + str(label)
def init2(self, node_name):
self.props["parallel_backend"] = "parallelnative"
def child_constructor(self):
return ImportantConfigNode
class LibTorchConfigNode(TreeConfigNode):
def modify_label(self, label):
return "BUILD_TEST_LIBTORCH=" + str(label)
def init2(self, node_name):
self.props["is_libtorch"] = node_name
def child_constructor(self):
return ExperimentalFeatureConfigNode
class CudaGccOverrideConfigNode(TreeConfigNode):
def init2(self, node_name):
self.props["cuda_gcc_override"] = node_name
def child_constructor(self):
return ExperimentalFeatureConfigNode
class BuildOnlyConfigNode(TreeConfigNode):
def init2(self, node_name):
self.props["build_only"] = node_name
def child_constructor(self):
return ExperimentalFeatureConfigNode
class ShardTestConfigNode(TreeConfigNode):
def init2(self, node_name):
self.props["shard_test"] = node_name
def child_constructor(self):
return ImportantConfigNode
class ImportantConfigNode(TreeConfigNode):
def modify_label(self, label):
return "IMPORTANT=" + str(label)
def init2(self, node_name):
self.props["is_important"] = node_name
def get_children(self):
return []
class XenialCompilerConfigNode(TreeConfigNode):
def modify_label(self, label):
return label or "<unspecified>"
def init2(self, node_name):
self.props["compiler_name"] = node_name
# noinspection PyMethodMayBeStatic
def child_constructor(self):
return (
XenialCompilerVersionConfigNode
if self.props["compiler_name"]
else PyVerConfigNode
)
class BionicCompilerConfigNode(TreeConfigNode):
def modify_label(self, label):
return label or "<unspecified>"
def init2(self, node_name):
self.props["compiler_name"] = node_name
# noinspection PyMethodMayBeStatic
def child_constructor(self):
return (
BionicCompilerVersionConfigNode
if self.props["compiler_name"]
else PyVerConfigNode
)
class XenialCompilerVersionConfigNode(TreeConfigNode):
def init2(self, node_name):
self.props["compiler_version"] = node_name
# noinspection PyMethodMayBeStatic
def child_constructor(self):
return PyVerConfigNode
class BionicCompilerVersionConfigNode(TreeConfigNode):
def init2(self, node_name):
self.props["compiler_version"] = node_name
# noinspection PyMethodMayBeStatic
def child_constructor(self):
return PyVerConfigNode

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from collections import OrderedDict
from dataclasses import dataclass, field
from typing import List, Optional
import cimodel.data.dimensions as dimensions
import cimodel.lib.conf_tree as conf_tree
import cimodel.lib.miniutils as miniutils
from cimodel.data.pytorch_build_data import CONFIG_TREE_DATA, TopLevelNode
from cimodel.data.simple.util.branch_filters import gen_filter_dict, RC_PATTERN
from cimodel.data.simple.util.docker_constants import gen_docker_image
@dataclass
class Conf:
distro: str
parms: List[str]
parms_list_ignored_for_docker_image: Optional[List[str]] = None
pyver: Optional[str] = None
cuda_version: Optional[str] = None
rocm_version: Optional[str] = None
# TODO expand this to cover all the USE_* that we want to test for
# tesnrorrt, leveldb, lmdb, redis, opencv, mkldnn, ideep, etc.
# (from https://github.com/pytorch/pytorch/pull/17323#discussion_r259453608)
is_xla: bool = False
is_vulkan: bool = False
is_pure_torch: bool = False
restrict_phases: Optional[List[str]] = None
gpu_resource: Optional[str] = None
dependent_tests: List = field(default_factory=list)
parent_build: Optional["Conf"] = None
is_libtorch: bool = False
is_important: bool = False
parallel_backend: Optional[str] = None
build_only: bool = False
@staticmethod
def is_test_phase(phase):
return "test" in phase
# TODO: Eliminate the special casing for docker paths
# In the short term, we *will* need to support special casing as docker images are merged for caffe2 and pytorch
def get_parms(self, for_docker):
leading = []
# We just don't run non-important jobs on pull requests;
# previously we also named them in a way to make it obvious
# if self.is_important and not for_docker:
# leading.append("AAA")
leading.append("pytorch")
if self.is_xla and not for_docker:
leading.append("xla")
if self.is_vulkan and not for_docker:
leading.append("vulkan")
if self.is_libtorch and not for_docker:
leading.append("libtorch")
if self.is_pure_torch and not for_docker:
leading.append("pure_torch")
if self.parallel_backend is not None and not for_docker:
leading.append(self.parallel_backend)
cuda_parms = []
if self.cuda_version:
cudnn = "cudnn8" if self.cuda_version.startswith("11.") else "cudnn7"
cuda_parms.extend(["cuda" + self.cuda_version, cudnn])
if self.rocm_version:
cuda_parms.extend([f"rocm{self.rocm_version}"])
result = leading + ["linux", self.distro] + cuda_parms + self.parms
if not for_docker and self.parms_list_ignored_for_docker_image is not None:
result = result + self.parms_list_ignored_for_docker_image
return result
def gen_docker_image_path(self):
parms_source = self.parent_build or self
base_build_env_name = "-".join(parms_source.get_parms(True))
image_name, _ = gen_docker_image(base_build_env_name)
return miniutils.quote(image_name)
def gen_docker_image_requires(self):
parms_source = self.parent_build or self
base_build_env_name = "-".join(parms_source.get_parms(True))
_, requires = gen_docker_image(base_build_env_name)
return miniutils.quote(requires)
def get_build_job_name_pieces(self, build_or_test):
return self.get_parms(False) + [build_or_test]
def gen_build_name(self, build_or_test):
return (
("_".join(map(str, self.get_build_job_name_pieces(build_or_test))))
.replace(".", "_")
.replace("-", "_")
)
def get_dependents(self):
return self.dependent_tests or []
def gen_workflow_params(self, phase):
parameters = OrderedDict()
build_job_name_pieces = self.get_build_job_name_pieces(phase)
build_env_name = "-".join(map(str, build_job_name_pieces))
parameters["build_environment"] = miniutils.quote(build_env_name)
parameters["docker_image"] = self.gen_docker_image_path()
if Conf.is_test_phase(phase) and self.gpu_resource:
parameters["use_cuda_docker_runtime"] = miniutils.quote("1")
if Conf.is_test_phase(phase):
resource_class = "large"
if self.gpu_resource:
resource_class = "gpu." + self.gpu_resource
if self.rocm_version is not None:
resource_class = "pytorch/amd-gpu"
parameters["resource_class"] = resource_class
if phase == "build" and self.rocm_version is not None:
parameters["resource_class"] = "xlarge"
if hasattr(self, "filters"):
parameters["filters"] = self.filters
if self.build_only:
parameters["build_only"] = miniutils.quote(str(int(True)))
return parameters
def gen_workflow_job(self, phase):
job_def = OrderedDict()
job_def["name"] = self.gen_build_name(phase)
if Conf.is_test_phase(phase):
# TODO When merging the caffe2 and pytorch jobs, it might be convenient for a while to make a
# caffe2 test job dependent on a pytorch build job. This way we could quickly dedup the repeated
# build of pytorch in the caffe2 build job, and just run the caffe2 tests off of a completed
# pytorch build job (from https://github.com/pytorch/pytorch/pull/17323#discussion_r259452641)
dependency_build = self.parent_build or self
job_def["requires"] = [dependency_build.gen_build_name("build")]
job_name = "pytorch_linux_test"
else:
job_name = "pytorch_linux_build"
job_def["requires"] = [self.gen_docker_image_requires()]
if not self.is_important:
job_def["filters"] = gen_filter_dict()
job_def.update(self.gen_workflow_params(phase))
return {job_name: job_def}
# TODO This is a hack to special case some configs just for the workflow list
class HiddenConf:
def __init__(self, name, parent_build=None, filters=None):
self.name = name
self.parent_build = parent_build
self.filters = filters
def gen_workflow_job(self, phase):
return {
self.gen_build_name(phase): {
"requires": [self.parent_build.gen_build_name("build")],
"filters": self.filters,
}
}
def gen_build_name(self, _):
return self.name
class DocPushConf:
def __init__(self, name, parent_build=None, branch="master"):
self.name = name
self.parent_build = parent_build
self.branch = branch
def gen_workflow_job(self, phase):
return {
"pytorch_doc_push": {
"name": self.name,
"branch": self.branch,
"requires": [self.parent_build],
"context": "org-member",
"filters": gen_filter_dict(
branches_list=["nightly"], tags_list=RC_PATTERN
),
}
}
def gen_docs_configs(xenial_parent_config):
configs = []
configs.append(
HiddenConf(
"pytorch_python_doc_build",
parent_build=xenial_parent_config,
filters=gen_filter_dict(
branches_list=["master", "main", "nightly"], tags_list=RC_PATTERN
),
)
)
configs.append(
DocPushConf(
"pytorch_python_doc_push",
parent_build="pytorch_python_doc_build",
branch="site",
)
)
configs.append(
HiddenConf(
"pytorch_cpp_doc_build",
parent_build=xenial_parent_config,
filters=gen_filter_dict(
branches_list=["master", "main", "nightly"], tags_list=RC_PATTERN
),
)
)
configs.append(
DocPushConf(
"pytorch_cpp_doc_push",
parent_build="pytorch_cpp_doc_build",
branch="master",
)
)
return configs
def get_root():
return TopLevelNode("PyTorch Builds", CONFIG_TREE_DATA)
def gen_tree():
root = get_root()
configs_list = conf_tree.dfs(root)
return configs_list
def instantiate_configs(only_slow_gradcheck):
config_list = []
root = get_root()
found_configs = conf_tree.dfs(root)
for fc in found_configs:
restrict_phases = None
distro_name = fc.find_prop("distro_name")
compiler_name = fc.find_prop("compiler_name")
compiler_version = fc.find_prop("compiler_version")
is_xla = fc.find_prop("is_xla") or False
is_asan = fc.find_prop("is_asan") or False
is_crossref = fc.find_prop("is_crossref") or False
is_dynamo = fc.find_prop("is_dynamo") or False
is_onnx = fc.find_prop("is_onnx") or False
is_pure_torch = fc.find_prop("is_pure_torch") or False
is_vulkan = fc.find_prop("is_vulkan") or False
is_slow_gradcheck = fc.find_prop("is_slow_gradcheck") or False
parms_list_ignored_for_docker_image = []
if only_slow_gradcheck ^ is_slow_gradcheck:
continue
python_version = None
if compiler_name == "cuda" or compiler_name == "android":
python_version = fc.find_prop("pyver")
parms_list = [fc.find_prop("abbreviated_pyver")]
else:
parms_list = ["py" + fc.find_prop("pyver")]
cuda_version = None
rocm_version = None
if compiler_name == "cuda":
cuda_version = fc.find_prop("compiler_version")
elif compiler_name == "rocm":
rocm_version = fc.find_prop("compiler_version")
restrict_phases = ["build", "test1", "test2", "caffe2_test"]
elif compiler_name == "android":
android_ndk_version = fc.find_prop("compiler_version")
# TODO: do we need clang to compile host binaries like protoc?
parms_list.append("clang5")
parms_list.append("android-ndk-" + android_ndk_version)
android_abi = fc.find_prop("android_abi")
parms_list_ignored_for_docker_image.append(android_abi)
restrict_phases = ["build"]
elif compiler_name:
gcc_version = compiler_name + (fc.find_prop("compiler_version") or "")
parms_list.append(gcc_version)
if is_asan:
parms_list.append("asan")
python_version = fc.find_prop("pyver")
parms_list[0] = fc.find_prop("abbreviated_pyver")
if is_crossref:
parms_list_ignored_for_docker_image.append("crossref")
if is_dynamo:
parms_list_ignored_for_docker_image.append("dynamo")
if is_onnx:
parms_list.append("onnx")
python_version = fc.find_prop("pyver")
parms_list[0] = fc.find_prop("abbreviated_pyver")
restrict_phases = ["build", "ort_test1", "ort_test2"]
if cuda_version:
cuda_gcc_version = fc.find_prop("cuda_gcc_override") or "gcc7"
parms_list.append(cuda_gcc_version)
is_libtorch = fc.find_prop("is_libtorch") or False
is_important = fc.find_prop("is_important") or False
parallel_backend = fc.find_prop("parallel_backend") or None
build_only = fc.find_prop("build_only") or False
shard_test = fc.find_prop("shard_test") or False
# TODO: fix pure_torch python test packaging issue.
if shard_test:
restrict_phases = ["build"] if restrict_phases is None else restrict_phases
restrict_phases.extend(["test1", "test2"])
if build_only or is_pure_torch:
restrict_phases = ["build"]
if is_slow_gradcheck:
parms_list_ignored_for_docker_image.append("old")
parms_list_ignored_for_docker_image.append("gradcheck")
gpu_resource = None
if cuda_version and cuda_version != "10":
gpu_resource = "medium"
c = Conf(
distro_name,
parms_list,
parms_list_ignored_for_docker_image,
python_version,
cuda_version,
rocm_version,
is_xla,
is_vulkan,
is_pure_torch,
restrict_phases,
gpu_resource,
is_libtorch=is_libtorch,
is_important=is_important,
parallel_backend=parallel_backend,
build_only=build_only,
)
# run docs builds on "pytorch-linux-xenial-py3.7-gcc5.4". Docs builds
# should run on a CPU-only build that runs on all PRs.
# XXX should this be updated to a more modern build?
if (
distro_name == "xenial"
and fc.find_prop("pyver") == "3.7"
and cuda_version is None
and parallel_backend is None
and not is_vulkan
and not is_pure_torch
and compiler_name == "gcc"
and fc.find_prop("compiler_version") == "5.4"
):
c.filters = gen_filter_dict(branches_list=r"/.*/", tags_list=RC_PATTERN)
c.dependent_tests = gen_docs_configs(c)
config_list.append(c)
return config_list
def get_workflow_jobs(only_slow_gradcheck=False):
config_list = instantiate_configs(only_slow_gradcheck)
x = []
for conf_options in config_list:
phases = conf_options.restrict_phases or dimensions.PHASES
for phase in phases:
# TODO why does this not have a test?
if Conf.is_test_phase(phase) and conf_options.cuda_version == "10":
continue
x.append(conf_options.gen_workflow_job(phase))
# TODO convert to recursion
for conf in conf_options.get_dependents():
x.append(conf.gen_workflow_job("test"))
return x

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from collections import OrderedDict
from cimodel.data.simple.util.branch_filters import gen_filter_dict, RC_PATTERN
from cimodel.lib.miniutils import quote
# NOTE: All hardcoded docker image builds have been migrated to GHA
IMAGE_NAMES = []
# This entry should be an element from the list above
# This should contain the image matching the "slow_gradcheck" entry in
# pytorch_build_data.py
SLOW_GRADCHECK_IMAGE_NAME = "pytorch-linux-xenial-cuda10.2-cudnn7-py3-gcc7"
def get_workflow_jobs(images=IMAGE_NAMES, only_slow_gradcheck=False):
"""Generates a list of docker image build definitions"""
ret = []
for image_name in images:
if image_name.startswith("docker-"):
image_name = image_name.lstrip("docker-")
if only_slow_gradcheck and image_name is not SLOW_GRADCHECK_IMAGE_NAME:
continue
parameters = OrderedDict(
{
"name": quote(f"docker-{image_name}"),
"image_name": quote(image_name),
}
)
if image_name == "pytorch-linux-xenial-py3.7-gcc5.4":
# pushing documentation on tags requires CircleCI to also
# build all the dependencies on tags, including this docker image
parameters["filters"] = gen_filter_dict(
branches_list=r"/.*/", tags_list=RC_PATTERN
)
ret.append(OrderedDict({"docker_build_job": parameters}))
return ret

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import cimodel.lib.miniutils as miniutils
from cimodel.data.simple.util.branch_filters import gen_filter_dict_exclude
from cimodel.data.simple.util.versions import MultiPartVersion
XCODE_VERSION = MultiPartVersion([12, 5, 1])
class ArchVariant:
def __init__(self, name, custom_build_name=""):
self.name = name
self.custom_build_name = custom_build_name
def render(self):
extra_parts = (
[self.custom_build_name] if len(self.custom_build_name) > 0 else []
)
return "-".join([self.name] + extra_parts).replace("_", "-")
def get_platform(arch_variant_name):
return "SIMULATOR" if arch_variant_name == "x86_64" else "OS"
class IOSJob:
def __init__(
self, xcode_version, arch_variant, is_org_member_context=True, extra_props=None
):
self.xcode_version = xcode_version
self.arch_variant = arch_variant
self.is_org_member_context = is_org_member_context
self.extra_props = extra_props
def gen_name_parts(self):
version_parts = self.xcode_version.render_dots_or_parts("-")
build_variant_suffix = self.arch_variant.render()
return (
[
"ios",
]
+ version_parts
+ [
build_variant_suffix,
]
)
def gen_job_name(self):
return "-".join(self.gen_name_parts())
def gen_tree(self):
platform_name = get_platform(self.arch_variant.name)
props_dict = {
"name": self.gen_job_name(),
"build_environment": self.gen_job_name(),
"ios_arch": self.arch_variant.name,
"ios_platform": platform_name,
}
if self.is_org_member_context:
props_dict["context"] = "org-member"
if self.extra_props:
props_dict.update(self.extra_props)
props_dict["filters"] = gen_filter_dict_exclude()
return [{"pytorch_ios_build": props_dict}]
WORKFLOW_DATA = [
IOSJob(
XCODE_VERSION,
ArchVariant("x86_64"),
is_org_member_context=False,
extra_props={"lite_interpreter": miniutils.quote(str(int(True)))},
),
# IOSJob(XCODE_VERSION, ArchVariant("arm64"), extra_props={
# "lite_interpreter": miniutils.quote(str(int(True)))}),
# IOSJob(XCODE_VERSION, ArchVariant("arm64", "metal"), extra_props={
# "use_metal": miniutils.quote(str(int(True))),
# "lite_interpreter": miniutils.quote(str(int(True)))}),
# IOSJob(XCODE_VERSION, ArchVariant("arm64", "custom-ops"), extra_props={
# "op_list": "mobilenetv2.yaml",
# "lite_interpreter": miniutils.quote(str(int(True)))}),
IOSJob(
XCODE_VERSION,
ArchVariant("x86_64", "coreml"),
is_org_member_context=False,
extra_props={
"use_coreml": miniutils.quote(str(int(True))),
"lite_interpreter": miniutils.quote(str(int(True))),
},
),
# IOSJob(XCODE_VERSION, ArchVariant("arm64", "coreml"), extra_props={
# "use_coreml": miniutils.quote(str(int(True))),
# "lite_interpreter": miniutils.quote(str(int(True)))}),
]
def get_workflow_jobs():
return [item.gen_tree() for item in WORKFLOW_DATA]

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class MacOsJob:
def __init__(self, os_version, is_build=False, is_test=False, extra_props=tuple()):
# extra_props is tuple type, because mutable data structures for argument defaults
# is not recommended.
self.os_version = os_version
self.is_build = is_build
self.is_test = is_test
self.extra_props = dict(extra_props)
def gen_tree(self):
non_phase_parts = ["pytorch", "macos", self.os_version, "py3"]
extra_name_list = [name for name, exist in self.extra_props.items() if exist]
full_job_name_list = (
non_phase_parts
+ extra_name_list
+ [
"build" if self.is_build else None,
"test" if self.is_test else None,
]
)
full_job_name = "_".join(list(filter(None, full_job_name_list)))
test_build_dependency = "_".join(non_phase_parts + ["build"])
extra_dependencies = [test_build_dependency] if self.is_test else []
job_dependencies = extra_dependencies
# Yes we name the job after itself, it needs a non-empty value in here
# for the YAML output to work.
props_dict = {"requires": job_dependencies, "name": full_job_name}
return [{full_job_name: props_dict}]
WORKFLOW_DATA = [
MacOsJob("10_15", is_build=True),
MacOsJob("10_13", is_build=True),
MacOsJob(
"10_13",
is_build=False,
is_test=True,
),
MacOsJob(
"10_13",
is_build=True,
is_test=True,
extra_props=tuple({"lite_interpreter": True}.items()),
),
]
def get_workflow_jobs():
return [item.gen_tree() for item in WORKFLOW_DATA]

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"""
PyTorch Mobile PR builds (use linux host toolchain + mobile build options)
"""
import cimodel.data.simple.util.branch_filters
import cimodel.lib.miniutils as miniutils
class MobileJob:
def __init__(
self, docker_image, docker_requires, variant_parts, is_master_only=False
):
self.docker_image = docker_image
self.docker_requires = docker_requires
self.variant_parts = variant_parts
self.is_master_only = is_master_only
def gen_tree(self):
non_phase_parts = [
"pytorch",
"linux",
"xenial",
"py3",
"clang5",
"mobile",
] + self.variant_parts
full_job_name = "_".join(non_phase_parts)
build_env_name = "-".join(non_phase_parts)
props_dict = {
"build_environment": build_env_name,
"build_only": miniutils.quote(str(int(True))),
"docker_image": self.docker_image,
"requires": self.docker_requires,
"name": full_job_name,
}
if self.is_master_only:
props_dict[
"filters"
] = cimodel.data.simple.util.branch_filters.gen_filter_dict()
return [{"pytorch_linux_build": props_dict}]
WORKFLOW_DATA = []
def get_workflow_jobs():
return [item.gen_tree() for item in WORKFLOW_DATA]

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import cimodel.data.simple.ios_definitions as ios_definitions
import cimodel.lib.miniutils as miniutils
class IOSNightlyJob:
def __init__(self, variant, is_full_jit=False, is_upload=False):
self.variant = variant
self.is_full_jit = is_full_jit
self.is_upload = is_upload
def get_phase_name(self):
return "upload" if self.is_upload else "build"
def get_common_name_pieces(self, sep):
extra_name_suffix = [self.get_phase_name()] if self.is_upload else []
extra_name = ["full_jit"] if self.is_full_jit else []
common_name_pieces = (
[
"ios",
]
+ extra_name
+ []
+ ios_definitions.XCODE_VERSION.render_dots_or_parts(sep)
+ [
"nightly",
self.variant,
"build",
]
+ extra_name_suffix
)
return common_name_pieces
def gen_job_name(self):
return "_".join(["pytorch"] + self.get_common_name_pieces(None))
def gen_tree(self):
build_configs = BUILD_CONFIGS_FULL_JIT if self.is_full_jit else BUILD_CONFIGS
extra_requires = (
[x.gen_job_name() for x in build_configs] if self.is_upload else []
)
props_dict = {
"build_environment": "-".join(
["libtorch"] + self.get_common_name_pieces(".")
),
"requires": extra_requires,
"context": "org-member",
"filters": {"branches": {"only": "nightly"}},
}
if not self.is_upload:
props_dict["ios_arch"] = self.variant
props_dict["ios_platform"] = ios_definitions.get_platform(self.variant)
props_dict["name"] = self.gen_job_name()
props_dict["use_metal"] = miniutils.quote(str(int(True)))
props_dict["use_coreml"] = miniutils.quote(str(int(True)))
if self.is_full_jit:
props_dict["lite_interpreter"] = miniutils.quote(str(int(False)))
template_name = "_".join(
[
"binary",
"ios",
self.get_phase_name(),
]
)
return [{template_name: props_dict}]
BUILD_CONFIGS = [
IOSNightlyJob("x86_64"),
IOSNightlyJob("arm64"),
]
BUILD_CONFIGS_FULL_JIT = [
IOSNightlyJob("x86_64", is_full_jit=True),
IOSNightlyJob("arm64", is_full_jit=True),
]
WORKFLOW_DATA = (
BUILD_CONFIGS
+ BUILD_CONFIGS_FULL_JIT
+ [
IOSNightlyJob("binary", is_full_jit=False, is_upload=True),
IOSNightlyJob("binary", is_full_jit=True, is_upload=True),
]
)
def get_workflow_jobs():
return [item.gen_tree() for item in WORKFLOW_DATA]

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NON_PR_BRANCH_LIST = [
"main",
"master",
r"/ci-all\/.*/",
r"/release\/.*/",
]
PR_BRANCH_LIST = [
r"/gh\/.*\/head/",
r"/pull\/.*/",
]
RC_PATTERN = r"/v[0-9]+(\.[0-9]+)*-rc[0-9]+/"
MAC_IOS_EXCLUSION_LIST = ["nightly", "postnightly"]
def gen_filter_dict(branches_list=NON_PR_BRANCH_LIST, tags_list=None):
"""Generates a filter dictionary for use with CircleCI's job filter"""
filter_dict = {
"branches": {
"only": branches_list,
},
}
if tags_list is not None:
filter_dict["tags"] = {"only": tags_list}
return filter_dict
def gen_filter_dict_exclude(branches_list=MAC_IOS_EXCLUSION_LIST):
return {
"branches": {
"ignore": branches_list,
},
}

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AWS_DOCKER_HOST = "308535385114.dkr.ecr.us-east-1.amazonaws.com"
def gen_docker_image(container_type):
return (
"/".join([AWS_DOCKER_HOST, "pytorch", container_type]),
f"docker-{container_type}",
)
def gen_docker_image_requires(image_name):
return [f"docker-{image_name}"]
DOCKER_IMAGE_BASIC, DOCKER_REQUIREMENT_BASE = gen_docker_image(
"pytorch-linux-xenial-py3.7-gcc5.4"
)
DOCKER_IMAGE_CUDA_10_2, DOCKER_REQUIREMENT_CUDA_10_2 = gen_docker_image(
"pytorch-linux-xenial-cuda10.2-cudnn7-py3-gcc7"
)
DOCKER_IMAGE_GCC7, DOCKER_REQUIREMENT_GCC7 = gen_docker_image(
"pytorch-linux-xenial-py3.7-gcc7"
)
def gen_mobile_docker(specifier):
container_type = "pytorch-linux-xenial-py3-clang5-" + specifier
return gen_docker_image(container_type)
DOCKER_IMAGE_ASAN, DOCKER_REQUIREMENT_ASAN = gen_mobile_docker("asan")
DOCKER_IMAGE_NDK, DOCKER_REQUIREMENT_NDK = gen_mobile_docker("android-ndk-r21e")

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from typing import Optional
class MultiPartVersion:
def __init__(self, parts, prefix=""):
self.parts = parts
self.prefix = prefix
def prefixed_parts(self):
"""
Prepends the first element of the version list
with the prefix string.
"""
if self.parts:
return [self.prefix + str(self.parts[0])] + [
str(part) for part in self.parts[1:]
]
else:
return [self.prefix]
def render_dots_or_parts(self, sep: Optional[str] = None):
if sep is None:
return self.prefixed_parts()
else:
return [sep.join(self.prefixed_parts())]
class CudaVersion(MultiPartVersion):
def __init__(self, major, minor):
self.major = major
self.minor = minor
super().__init__([self.major, self.minor], "cuda")
def __str__(self):
return f"{self.major}.{self.minor}"

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from dataclasses import dataclass, field
from typing import Dict, Optional
def X(val):
"""
Compact way to write a leaf node
"""
return val, []
def XImportant(name):
"""Compact way to write an important (run on PRs) leaf node"""
return (name, [("important", [X(True)])])
@dataclass
class Ver:
"""
Represents a product with a version number
"""
name: str
version: str = ""
def __str__(self):
return self.name + self.version
@dataclass
class ConfigNode:
parent: Optional["ConfigNode"]
node_name: str
props: Dict[str, str] = field(default_factory=dict)
def get_label(self):
return self.node_name
# noinspection PyMethodMayBeStatic
def get_children(self):
return []
def get_parents(self):
return (
(self.parent.get_parents() + [self.parent.get_label()])
if self.parent
else []
)
def get_depth(self):
return len(self.get_parents())
def get_node_key(self):
return "%".join(self.get_parents() + [self.get_label()])
def find_prop(self, propname, searched=None):
"""
Checks if its own dictionary has
the property, otherwise asks parent node.
"""
if searched is None:
searched = []
searched.append(self.node_name)
if propname in self.props:
return self.props[propname]
elif self.parent:
return self.parent.find_prop(propname, searched)
else:
# raise Exception('Property "%s" does not exist anywhere in the tree! Searched: %s' % (propname, searched))
return None
def dfs_recurse(
node,
leaf_callback=lambda x: None,
discovery_callback=lambda x, y, z: None,
child_callback=lambda x, y: None,
sibling_index=0,
sibling_count=1,
):
discovery_callback(node, sibling_index, sibling_count)
node_children = node.get_children()
if node_children:
for i, child in enumerate(node_children):
child_callback(node, child)
dfs_recurse(
child,
leaf_callback,
discovery_callback,
child_callback,
i,
len(node_children),
)
else:
leaf_callback(node)
def dfs(toplevel_config_node):
config_list = []
def leaf_callback(node):
config_list.append(node)
dfs_recurse(toplevel_config_node, leaf_callback)
return config_list

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def quote(s):
return sandwich('"', s)
def sandwich(bread, jam):
return bread + jam + bread
def override(word, substitutions):
return substitutions.get(word, word)

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from collections import OrderedDict
import cimodel.lib.miniutils as miniutils
LIST_MARKER = "- "
INDENTATION_WIDTH = 2
def is_dict(data):
return type(data) in [dict, OrderedDict]
def is_collection(data):
return is_dict(data) or type(data) is list
def render(fh, data, depth, is_list_member=False):
"""
PyYaml does not allow precise control over the quoting
behavior, especially for merge references.
Therefore, we use this custom YAML renderer.
"""
indentation = " " * INDENTATION_WIDTH * depth
if is_dict(data):
tuples = list(data.items())
if type(data) is not OrderedDict:
tuples.sort()
for i, (k, v) in enumerate(tuples):
if not v:
continue
# If this dict is itself a list member, the first key gets prefixed with a list marker
list_marker_prefix = LIST_MARKER if is_list_member and not i else ""
trailing_whitespace = "\n" if is_collection(v) else " "
fh.write(indentation + list_marker_prefix + k + ":" + trailing_whitespace)
render(fh, v, depth + 1 + int(is_list_member))
elif type(data) is list:
for v in data:
render(fh, v, depth, True)
else:
# use empty quotes to denote an empty string value instead of blank space
modified_data = miniutils.quote(data) if data == "" else data
list_member_prefix = indentation + LIST_MARKER if is_list_member else ""
fh.write(list_member_prefix + str(modified_data) + "\n")

1388
.circleci/config.yml generated Normal file

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41
.circleci/ensure-consistency.py Executable file
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#!/usr/bin/env python3
import os
import subprocess
import sys
import tempfile
import generate_config_yml
CHECKED_IN_FILE = "config.yml"
REGENERATION_SCRIPT = "regenerate.sh"
PARENT_DIR = os.path.basename(os.path.dirname(os.path.abspath(__file__)))
README_PATH = os.path.join(PARENT_DIR, "README.md")
ERROR_MESSAGE_TEMPLATE = """
The checked-in CircleCI "%s" file does not match what was generated by the scripts.
Please re-run the "%s" script in the "%s" directory and commit the result. See "%s" for more information.
"""
def check_consistency():
_, temp_filename = tempfile.mkstemp("-generated-config.yml")
with open(temp_filename, "w") as fh:
generate_config_yml.stitch_sources(fh)
try:
subprocess.check_call(["cmp", temp_filename, CHECKED_IN_FILE])
except subprocess.CalledProcessError:
sys.exit(
ERROR_MESSAGE_TEMPLATE
% (CHECKED_IN_FILE, REGENERATION_SCRIPT, PARENT_DIR, README_PATH)
)
finally:
os.remove(temp_filename)
if __name__ == "__main__":
check_consistency()

196
.circleci/generate_config_yml.py Executable file
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#!/usr/bin/env python3
"""
This script is the source of truth for config.yml.
Please see README.md in this directory for details.
"""
import os
import shutil
import sys
from collections import namedtuple
import cimodel.data.simple.docker_definitions
import cimodel.data.simple.mobile_definitions
import cimodel.data.simple.nightly_ios
import cimodel.lib.miniutils as miniutils
import cimodel.lib.miniyaml as miniyaml
class File:
"""
Verbatim copy the contents of a file into config.yml
"""
def __init__(self, filename):
self.filename = filename
def write(self, output_filehandle):
with open(os.path.join("verbatim-sources", self.filename)) as fh:
shutil.copyfileobj(fh, output_filehandle)
class FunctionGen(namedtuple("FunctionGen", "function depth")):
__slots__ = ()
class Treegen(FunctionGen):
"""
Insert the content of a YAML tree into config.yml
"""
def write(self, output_filehandle):
miniyaml.render(output_filehandle, self.function(), self.depth)
class Listgen(FunctionGen):
"""
Insert the content of a YAML list into config.yml
"""
def write(self, output_filehandle):
miniyaml.render(output_filehandle, self.function(), self.depth)
def horizontal_rule():
return "".join("#" * 78)
class Header:
def __init__(self, title, summary=None):
self.title = title
self.summary_lines = summary or []
def write(self, output_filehandle):
text_lines = [self.title] + self.summary_lines
comment_lines = ["# " + x for x in text_lines]
lines = miniutils.sandwich([horizontal_rule()], comment_lines)
for line in filter(None, lines):
output_filehandle.write(line + "\n")
def _for_all_items(items, functor) -> None:
if isinstance(items, list):
for item in items:
_for_all_items(item, functor)
if isinstance(items, dict) and len(items) == 1:
item_type, item = next(iter(items.items()))
functor(item_type, item)
def filter_master_only_jobs(items):
def _is_main_or_master_item(item):
filters = item.get("filters", None)
branches = filters.get("branches", None) if filters is not None else None
branches_only = branches.get("only", None) if branches is not None else None
return (
("main" in branches_only or "master" in branches_only)
if branches_only is not None
else False
)
master_deps = set()
def _save_requires_if_master(item_type, item):
requires = item.get("requires", None)
item_name = item.get("name", None)
if not isinstance(requires, list):
return
if _is_main_or_master_item(item) or item_name in master_deps:
master_deps.update([n.strip('"') for n in requires])
def _do_filtering(items):
if isinstance(items, list):
rc = [_do_filtering(item) for item in items]
return [item for item in rc if len(item if item is not None else []) > 0]
assert isinstance(items, dict) and len(items) == 1
item_type, item = next(iter(items.items()))
item_name = item.get("name", None)
item_name = item_name.strip('"') if item_name is not None else None
if not _is_main_or_master_item(item) and item_name not in master_deps:
return None
if "filters" in item:
item = item.copy()
item.pop("filters")
return {item_type: item}
# Scan of dependencies twice to pick up nested required jobs
# I.e. jobs depending on jobs that main-only job depend on
_for_all_items(items, _save_requires_if_master)
_for_all_items(items, _save_requires_if_master)
return _do_filtering(items)
def generate_required_docker_images(items):
required_docker_images = set()
def _requires_docker_image(item_type, item):
requires = item.get("requires", None)
if not isinstance(requires, list):
return
for requirement in requires:
requirement = requirement.replace('"', "")
if requirement.startswith("docker-"):
required_docker_images.add(requirement)
_for_all_items(items, _requires_docker_image)
return required_docker_images
def gen_build_workflows_tree():
build_workflows_functions = [
cimodel.data.simple.mobile_definitions.get_workflow_jobs,
cimodel.data.simple.nightly_ios.get_workflow_jobs,
]
build_jobs = [f() for f in build_workflows_functions]
build_jobs.extend(
cimodel.data.simple.docker_definitions.get_workflow_jobs(
# sort for consistency
sorted(generate_required_docker_images(build_jobs))
)
)
master_build_jobs = filter_master_only_jobs(build_jobs)
rc = {
"workflows": {
"build": {
"when": r"<< pipeline.parameters.run_build >>",
"jobs": build_jobs,
},
}
}
if len(master_build_jobs) > 0:
rc["workflows"]["master_build"] = {
"when": r"<< pipeline.parameters.run_master_build >>",
"jobs": master_build_jobs,
}
return rc
# Order of this list matters to the generated config.yml.
YAML_SOURCES = [
File("header-section.yml"),
File("commands.yml"),
File("nightly-binary-build-defaults.yml"),
Header("Build parameters"),
File("build-parameters/pytorch-build-params.yml"),
File("build-parameters/binary-build-params.yml"),
Header("Job specs"),
File("job-specs/binary-job-specs.yml"),
File("job-specs/job-specs-custom.yml"),
File("job-specs/binary_update_htmls.yml"),
File("job-specs/binary-build-tests.yml"),
File("job-specs/docker_jobs.yml"),
Header("Workflows"),
Treegen(gen_build_workflows_tree, 0),
]
def stitch_sources(output_filehandle):
for f in YAML_SOURCES:
f.write(output_filehandle)
if __name__ == "__main__":
stitch_sources(sys.stdout)

5
.circleci/regenerate.ps1 Normal file
View File

@ -0,0 +1,5 @@
cd $PSScriptRoot;
$NewFile = New-TemporaryFile;
python generate_config_yml.py > $NewFile.name
(Get-Content $NewFile.name -Raw).TrimEnd().Replace("`r`n","`n") | Set-Content config.yml -Force
Remove-Item $NewFile.name

17
.circleci/regenerate.sh Executable file
View File

@ -0,0 +1,17 @@
#!/bin/bash -e
# Allows this script to be invoked from any directory:
cd "$(dirname "$0")"
UNCOMMIT_CHANGE=$(git status -s | grep " config.yml" | wc -l | xargs)
if [[ $UNCOMMIT_CHANGE != 0 ]]; then
OLD_FILE=$(mktemp)
cp config.yml "$OLD_FILE"
echo "Uncommitted change detected in .circleci/config.yml"
echo "It has been backed up to $OLD_FILE"
fi
NEW_FILE=$(mktemp)
./generate_config_yml.py > "$NEW_FILE"
cp "$NEW_FILE" config.yml
echo "New config generated in .circleci/config.yml"

View File

@ -58,7 +58,8 @@ fi
PIP_UPLOAD_FOLDER='nightly/'
# We put this here so that OVERRIDE_PACKAGE_VERSION below can read from it
export DATE="$(date -u +%Y%m%d)"
BASE_BUILD_VERSION="$(cat ${PYTORCH_ROOT}/version.txt|cut -da -f1).dev${DATE}"
#TODO: We should be pulling semver version from the base version.txt
BASE_BUILD_VERSION="2.2.0.dev$DATE"
# Change BASE_BUILD_VERSION to git tag when on a git tag
# Use 'git -C' to make doubly sure we're in the correct directory for checking
# the git tag

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@ -0,0 +1,65 @@
binary_linux_build_params: &binary_linux_build_params
parameters:
build_environment:
type: string
default: ""
docker_image:
type: string
default: ""
libtorch_variant:
type: string
default: ""
resource_class:
type: string
default: "2xlarge+"
environment:
BUILD_ENVIRONMENT: << parameters.build_environment >>
LIBTORCH_VARIANT: << parameters.libtorch_variant >>
ANACONDA_USER: pytorch
resource_class: << parameters.resource_class >>
docker:
- image: << parameters.docker_image >>
binary_linux_test_upload_params: &binary_linux_test_upload_params
parameters:
build_environment:
type: string
default: ""
docker_image:
type: string
default: ""
libtorch_variant:
type: string
default: ""
resource_class:
type: string
default: "medium"
use_cuda_docker_runtime:
type: string
default: ""
environment:
BUILD_ENVIRONMENT: << parameters.build_environment >>
DOCKER_IMAGE: << parameters.docker_image >>
USE_CUDA_DOCKER_RUNTIME: << parameters.use_cuda_docker_runtime >>
LIBTORCH_VARIANT: << parameters.libtorch_variant >>
resource_class: << parameters.resource_class >>
binary_mac_params: &binary_mac_params
parameters:
build_environment:
type: string
default: ""
environment:
BUILD_ENVIRONMENT: << parameters.build_environment >>
binary_windows_params: &binary_windows_params
parameters:
build_environment:
type: string
default: ""
executor:
type: string
default: "windows-xlarge-cpu-with-nvidia-cuda"
environment:
BUILD_ENVIRONMENT: << parameters.build_environment >>
JOB_EXECUTOR: <<parameters.executor>>

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@ -0,0 +1,105 @@
pytorch_params: &pytorch_params
parameters:
build_environment:
type: string
default: ""
docker_image:
type: string
default: ""
resource_class:
type: string
default: "large"
use_cuda_docker_runtime:
type: string
default: ""
build_only:
type: string
default: ""
ci_master:
type: string
default: ""
environment:
BUILD_ENVIRONMENT: << parameters.build_environment >>
DOCKER_IMAGE: << parameters.docker_image >>
USE_CUDA_DOCKER_RUNTIME: << parameters.use_cuda_docker_runtime >>
BUILD_ONLY: << parameters.build_only >>
CI_MASTER: << pipeline.parameters.run_master_build >>
resource_class: << parameters.resource_class >>
pytorch_ios_params: &pytorch_ios_params
parameters:
build_environment:
type: string
default: ""
ios_arch:
type: string
default: ""
ios_platform:
type: string
default: ""
op_list:
type: string
default: ""
use_metal:
type: string
default: "0"
lite_interpreter:
type: string
default: "1"
use_coreml:
type: string
default: "0"
environment:
BUILD_ENVIRONMENT: << parameters.build_environment >>
IOS_ARCH: << parameters.ios_arch >>
IOS_PLATFORM: << parameters.ios_platform >>
SELECTED_OP_LIST: << parameters.op_list >>
USE_PYTORCH_METAL: << parameters.use_metal >>
BUILD_LITE_INTERPRETER: << parameters.lite_interpreter >>
USE_COREML_DELEGATE: << parameters.use_coreml >>
pytorch_windows_params: &pytorch_windows_params
parameters:
executor:
type: string
default: "windows-xlarge-cpu-with-nvidia-cuda"
build_environment:
type: string
default: ""
test_name:
type: string
default: ""
cuda_version:
type: string
default: "10.1"
python_version:
type: string
default: "3.8"
vs_version:
type: string
default: "16.8.6"
vc_version:
type: string
default: "14.16"
vc_year:
type: string
default: "2019"
vc_product:
type: string
default: "BuildTools"
use_cuda:
type: string
default: ""
environment:
BUILD_ENVIRONMENT: <<parameters.build_environment>>
SCCACHE_BUCKET: "ossci-compiler-cache"
CUDA_VERSION: <<parameters.cuda_version>>
PYTHON_VERSION: <<parameters.python_version>>
VS_VERSION: <<parameters.vs_version>>
VC_VERSION: <<parameters.vc_version>>
VC_YEAR: <<parameters.vc_year>>
VC_PRODUCT: <<parameters.vc_product>>
USE_CUDA: <<parameters.use_cuda>>
TORCH_CUDA_ARCH_LIST: "5.2 7.5"
JOB_BASE_NAME: <<parameters.test_name>>
JOB_EXECUTOR: <<parameters.executor>>

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@ -0,0 +1,134 @@
commands:
calculate_docker_image_tag:
description: "Calculates the docker image tag"
steps:
- run:
name: "Calculate docker image hash"
command: |
DOCKER_TAG=$(git rev-parse HEAD:.ci/docker)
echo "DOCKER_TAG=${DOCKER_TAG}" >> "${BASH_ENV}"
designate_upload_channel:
description: "inserts the correct upload channel into ${BASH_ENV}"
steps:
- run:
name: adding UPLOAD_CHANNEL to BASH_ENV
command: |
our_upload_channel=nightly
# On tags upload to test instead
if [[ -n "${CIRCLE_TAG}" ]]; then
our_upload_channel=test
fi
echo "export UPLOAD_CHANNEL=${our_upload_channel}" >> ${BASH_ENV}
# This system setup script is meant to run before the CI-related scripts, e.g.,
# installing Git client, checking out code, setting up CI env, and
# building/testing.
setup_linux_system_environment:
steps:
- run:
name: Set Up System Environment
no_output_timeout: "1h"
command: .circleci/scripts/setup_linux_system_environment.sh
setup_ci_environment:
steps:
- run:
name: Set Up CI Environment After attach_workspace
no_output_timeout: "1h"
command: .circleci/scripts/setup_ci_environment.sh
brew_update:
description: "Update Homebrew and install base formulae"
steps:
- run:
name: Update Homebrew
no_output_timeout: "10m"
command: |
set -ex
# Update repositories manually.
# Running `brew update` produces a comparison between the
# current checkout and the updated checkout, which takes a
# very long time because the existing checkout is 2y old.
for path in $(find /usr/local/Homebrew -type d -name .git)
do
cd $path/..
git fetch --depth=1 origin
git reset --hard origin/master
done
export HOMEBREW_NO_AUTO_UPDATE=1
# Install expect and moreutils so that we can call `unbuffer` and `ts`.
# moreutils installs a `parallel` executable by default, which conflicts
# with the executable from the GNU `parallel`, so we must unlink GNU
# `parallel` first, and relink it afterwards.
brew unlink parallel
brew install moreutils
brew link parallel --overwrite
brew install expect
brew_install:
description: "Install Homebrew formulae"
parameters:
formulae:
type: string
default: ""
steps:
- run:
name: Install << parameters.formulae >>
no_output_timeout: "10m"
command: |
set -ex
export HOMEBREW_NO_AUTO_UPDATE=1
brew install << parameters.formulae >>
run_brew_for_macos_build:
steps:
- brew_update
- brew_install:
formulae: libomp
run_brew_for_ios_build:
steps:
- brew_update
- brew_install:
formulae: libtool
optional_merge_target_branch:
steps:
- run:
name: (Optional) Merge target branch
no_output_timeout: "10m"
command: |
if [[ -n "$CIRCLE_PULL_REQUEST" && "$CIRCLE_BRANCH" != "nightly" ]]; then
PR_NUM=$(basename $CIRCLE_PULL_REQUEST)
CIRCLE_PR_BASE_BRANCH=$(curl -s https://api.github.com/repos/$CIRCLE_PROJECT_USERNAME/$CIRCLE_PROJECT_REPONAME/pulls/$PR_NUM | jq -r '.base.ref')
if [[ "${BUILD_ENVIRONMENT}" == *"xla"* || "${BUILD_ENVIRONMENT}" == *"gcc5"* ]] ; then
set -x
git config --global user.email "circleci.ossci@gmail.com"
git config --global user.name "CircleCI"
git config remote.origin.url https://github.com/pytorch/pytorch.git
git config --add remote.origin.fetch +refs/heads/master:refs/remotes/origin/master
git fetch --tags --progress https://github.com/pytorch/pytorch.git +refs/heads/master:refs/remotes/origin/master --depth=100 --quiet
# PRs generated from ghstack has format CIRCLE_PR_BASE_BRANCH=gh/xxx/1234/base
if [[ "${CIRCLE_PR_BASE_BRANCH}" == "gh/"* ]]; then
CIRCLE_PR_BASE_BRANCH=master
fi
export GIT_MERGE_TARGET=`git log -n 1 --pretty=format:"%H" origin/$CIRCLE_PR_BASE_BRANCH`
echo "GIT_MERGE_TARGET: " ${GIT_MERGE_TARGET}
export GIT_COMMIT=${CIRCLE_SHA1}
echo "GIT_COMMIT: " ${GIT_COMMIT}
git checkout -f ${GIT_COMMIT}
git reset --hard ${GIT_COMMIT}
git merge --allow-unrelated-histories --no-edit --no-ff ${GIT_MERGE_TARGET}
echo "Merged $CIRCLE_PR_BASE_BRANCH branch before building in environment $BUILD_ENVIRONMENT"
set +x
else
echo "No need to merge with $CIRCLE_PR_BASE_BRANCH, skipping..."
fi
else
echo "This is not a pull request, skipping..."
fi

View File

@ -0,0 +1,41 @@
# WARNING: DO NOT EDIT THIS FILE DIRECTLY!!!
# See the README.md in this directory.
# IMPORTANT: To update Docker image version, please follow
# the instructions at
# https://github.com/pytorch/pytorch/wiki/Docker-image-build-on-CircleCI
version: 2.1
parameters:
run_binary_tests:
type: boolean
default: false
run_build:
type: boolean
default: true
run_master_build:
type: boolean
default: false
run_slow_gradcheck_build:
type: boolean
default: false
executors:
windows-with-nvidia-gpu:
machine:
resource_class: windows.gpu.nvidia.medium
image: windows-server-2019-nvidia:previous
shell: bash.exe
windows-xlarge-cpu-with-nvidia-cuda:
machine:
resource_class: windows.xlarge
image: windows-server-2019-vs2019:stable
shell: bash.exe
windows-medium-cpu-with-nvidia-cuda:
machine:
resource_class: windows.medium
image: windows-server-2019-vs2019:stable
shell: bash.exe

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@ -0,0 +1,14 @@
# There is currently no testing for libtorch TODO
# binary_linux_libtorch_3.6m_cpu_test:
# environment:
# BUILD_ENVIRONMENT: "libtorch 3.6m cpu"
# resource_class: gpu.nvidia.small
# <<: *binary_linux_test
#
# binary_linux_libtorch_3.6m_cu90_test:
# environment:
# BUILD_ENVIRONMENT: "libtorch 3.6m cu90"
# resource_class: gpu.nvidia.small
# <<: *binary_linux_test
#

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@ -0,0 +1,44 @@
jobs:
binary_ios_build:
<<: *pytorch_ios_params
macos:
xcode: "12.5.1"
steps:
- attach_workspace:
at: ~/workspace
- checkout
- run_brew_for_ios_build
- run:
name: Build
no_output_timeout: "1h"
command: |
script="/Users/distiller/project/.circleci/scripts/binary_ios_build.sh"
cat "$script"
source "$script"
- run:
name: Test
no_output_timeout: "30m"
command: |
script="/Users/distiller/project/.circleci/scripts/binary_ios_test.sh"
cat "$script"
source "$script"
- persist_to_workspace:
root: /Users/distiller/workspace/
paths: ios
binary_ios_upload:
<<: *pytorch_ios_params
macos:
xcode: "12.5.1"
steps:
- attach_workspace:
at: ~/workspace
- checkout
- run_brew_for_ios_build
- run:
name: Upload
no_output_timeout: "1h"
command: |
script="/Users/distiller/project/.circleci/scripts/binary_ios_upload.sh"
cat "$script"
source "$script"

View File

@ -0,0 +1,53 @@
# update_s3_htmls job
# These jobs create html files for every cpu/cu## folder in s3. The html
# files just store the names of all the files in that folder (which are
# binary files (.whl files)). This is to allow pip installs of the latest
# version in a folder without having to know the latest date. Pip has a flag
# -f that you can pass an html file listing a bunch of packages, and pip will
# then install the one with the most recent version.
update_s3_htmls: &update_s3_htmls
machine:
image: ubuntu-2004:202104-01
resource_class: medium
steps:
- checkout
- setup_linux_system_environment
- run:
<<: *binary_checkout
# N.B. we do not run binary_populate_env. The only variable we need is
# PIP_UPLOAD_FOLDER (which is 'nightly/' for the nightlies and '' for
# releases, and sometimes other things for special cases). Instead we
# expect PIP_UPLOAD_FOLDER to be passed directly in the env. This is
# because, unlike all the other binary jobs, these jobs only get run once,
# in a separate workflow. They are not a step in other binary jobs like
# build, test, upload.
#
# You could attach this to every job, or include it in the upload step if
# you wanted. You would need to add binary_populate_env in this case to
# make sure it has the same upload folder as the job it's attached to. This
# function is idempotent, so it won't hurt anything; it's just a little
# unnescessary"
- run:
name: define PIP_UPLOAD_FOLDER
command: |
our_upload_folder=nightly/
# On tags upload to test instead
if [[ -n "${CIRCLE_TAG}" ]]; then
our_upload_folder=test/
fi
echo "export PIP_UPLOAD_FOLDER=${our_upload_folder}" >> ${BASH_ENV}
- run:
name: Update s3 htmls
no_output_timeout: "1h"
command: |
set +x
echo "declare -x \"AWS_ACCESS_KEY_ID=${PYTORCH_BINARY_AWS_ACCESS_KEY_ID}\"" >> /home/circleci/project/env
echo "declare -x \"AWS_SECRET_ACCESS_KEY=${PYTORCH_BINARY_AWS_SECRET_ACCESS_KEY}\"" >> /home/circleci/project/env
source /home/circleci/project/env
set -eux -o pipefail
retry () {
$* || (sleep 1 && $*) || (sleep 2 && $*) || (sleep 4 && $*) || (sleep 8 && $*)
}
retry pip install awscli==1.6
"/home/circleci/project/builder/cron/update_s3_htmls.sh"

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@ -0,0 +1,56 @@
docker_build_job:
parameters:
image_name:
type: string
default: ""
machine:
image: ubuntu-2004:202104-01
resource_class: large
environment:
IMAGE_NAME: << parameters.image_name >>
# Enable 'docker manifest'
DOCKER_CLI_EXPERIMENTAL: "enabled"
DOCKER_BUILDKIT: 1
steps:
- checkout
- calculate_docker_image_tag
- run:
name: Check if image should be built
command: |
set +x
export AWS_ACCESS_KEY_ID=${CIRCLECI_AWS_ACCESS_KEY_FOR_DOCKER_BUILDER_V1}
export AWS_SECRET_ACCESS_KEY=${CIRCLECI_AWS_SECRET_KEY_FOR_DOCKER_BUILDER_V1}
export AWS_ACCOUNT_ID=$(aws sts get-caller-identity|grep Account|cut -f4 -d\")
export AWS_REGION=us-east-1
aws ecr get-login-password --region $AWS_REGION|docker login --username AWS \
--password-stdin $AWS_ACCOUNT_ID.dkr.ecr.$AWS_REGION.amazonaws.com
set -x
# Check if image already exists, if it does then skip building it
if docker manifest inspect "308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/${IMAGE_NAME}:${DOCKER_TAG}"; then
circleci-agent step halt
# circleci-agent step halt doesn't actually halt the step so we need to
# explicitly exit the step here ourselves before it causes too much trouble
exit 0
fi
# Covers the case where a previous tag doesn't exist for the tree
# this is only really applicable on trees that don't have `.ci/docker` at its merge base, i.e. nightly
if ! git rev-parse "$(git merge-base HEAD << pipeline.git.base_revision >>):.ci/docker"; then
echo "Directory '.ci/docker' not found in tree << pipeline.git.base_revision >>, you should probably rebase onto a more recent commit"
exit 1
fi
PREVIOUS_DOCKER_TAG=$(git rev-parse "$(git merge-base HEAD << pipeline.git.base_revision >>):ci/docker")
# If no image exists but the hash is the same as the previous hash then we should error out here
if [[ "${PREVIOUS_DOCKER_TAG}" = "${DOCKER_TAG}" ]]; then
echo "ERROR: Something has gone wrong and the previous image isn't available for the merge-base of your branch"
echo " contact the PyTorch team to restore the original images"
exit 1
fi
- run:
name: build_docker_image_<< parameters.image_name >>
no_output_timeout: "1h"
command: |
set +x
export AWS_ACCESS_KEY_ID=${CIRCLECI_AWS_ACCESS_KEY_FOR_DOCKER_BUILDER_V1}
export AWS_SECRET_ACCESS_KEY=${CIRCLECI_AWS_SECRET_KEY_FOR_DOCKER_BUILDER_V1}
set -x
cd .ci/docker && ./build_docker.sh

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@ -0,0 +1,747 @@
pytorch_doc_push:
resource_class: medium
machine:
image: ubuntu-2004:202104-01
parameters:
branch:
type: string
default: "main"
steps:
- attach_workspace:
at: /tmp/workspace
- run:
name: Generate netrc
command: |
# set credentials for https pushing
cat > ~/.netrc \<<DONE
machine github.com
login pytorchbot
password ${GITHUB_PYTORCHBOT_TOKEN}
DONE
- run:
name: Docs push
command: |
pushd /tmp/workspace
git push -u origin "<< parameters.branch >>"
pytorch_macos_10_15_py3_build:
environment:
BUILD_ENVIRONMENT: pytorch-macos-10.15-py3-arm64-build
macos:
xcode: "12.3.0"
steps:
- checkout
- run_brew_for_macos_build
- run:
name: Build
no_output_timeout: "1h"
command: |
set -e
export CROSS_COMPILE_ARM64=1
export JOB_BASE_NAME=$CIRCLE_JOB
# Install sccache
sudo curl --retry 3 https://s3.amazonaws.com/ossci-macos/sccache_v2.15 --output /usr/local/bin/sccache
sudo chmod +x /usr/local/bin/sccache
export SCCACHE_BUCKET=ossci-compiler-cache-circleci-v2
# This IAM user allows write access to S3 bucket for sccache
set +x
export AWS_ACCESS_KEY_ID=${CIRCLECI_AWS_ACCESS_KEY_FOR_SCCACHE_S3_BUCKET_V4}
export AWS_SECRET_ACCESS_KEY=${CIRCLECI_AWS_SECRET_KEY_FOR_SCCACHE_S3_BUCKET_V4}
set -x
chmod a+x .ci/pytorch/macos-build.sh
unbuffer .ci/pytorch/macos-build.sh 2>&1 | ts
- persist_to_workspace:
root: /Users/distiller/workspace/
paths:
- miniconda3
- store_artifacts:
path: /Users/distiller/project/dist
pytorch_macos_10_13_py3_build:
environment:
BUILD_ENVIRONMENT: pytorch-macos-10.13-py3-build
macos:
xcode: "12.0"
steps:
- checkout
- run_brew_for_macos_build
- run:
name: Build
no_output_timeout: "1h"
command: |
set -e
export JOB_BASE_NAME=$CIRCLE_JOB
# Install sccache
sudo curl --retry 3 https://s3.amazonaws.com/ossci-macos/sccache_v2.15 --output /usr/local/bin/sccache
sudo chmod +x /usr/local/bin/sccache
export SCCACHE_BUCKET=ossci-compiler-cache-circleci-v2
# This IAM user allows write access to S3 bucket for sccache
set +x
export AWS_ACCESS_KEY_ID=${CIRCLECI_AWS_ACCESS_KEY_FOR_SCCACHE_S3_BUCKET_V4}
export AWS_SECRET_ACCESS_KEY=${CIRCLECI_AWS_SECRET_KEY_FOR_SCCACHE_S3_BUCKET_V4}
set -x
chmod a+x .ci/pytorch/macos-build.sh
unbuffer .ci/pytorch/macos-build.sh 2>&1 | ts
- persist_to_workspace:
root: /Users/distiller/workspace/
paths:
- miniconda3
mac_build:
parameters:
build-environment:
type: string
description: Top-level label for what's being built/tested.
xcode-version:
type: string
default: "13.3.1"
description: What xcode version to build with.
build-generates-artifacts:
type: boolean
default: true
description: if the build generates build artifacts
python-version:
type: string
default: "3.8"
macos:
xcode: << parameters.xcode-version >>
resource_class: medium
environment:
BUILD_ENVIRONMENT: << parameters.build-environment >>
AWS_REGION: us-east-1
steps:
- checkout
- run_brew_for_macos_build
- run:
name: Install sccache
command: |
sudo curl --retry 3 https://s3.amazonaws.com/ossci-macos/sccache_v2.15 --output /usr/local/bin/sccache
sudo chmod +x /usr/local/bin/sccache
echo "export SCCACHE_BUCKET=ossci-compiler-cache-circleci-v2" >> "${BASH_ENV}"
echo "export SCCACHE_S3_KEY_PREFIX=${GITHUB_WORKFLOW}" >> "${BASH_ENV}"
set +x
echo "export AWS_ACCESS_KEY_ID=${CIRCLECI_AWS_ACCESS_KEY_FOR_SCCACHE_S3_BUCKET_V4}" >> "${BASH_ENV}"
echo "export AWS_SECRET_ACCESS_KEY=${CIRCLECI_AWS_SECRET_KEY_FOR_SCCACHE_S3_BUCKET_V4}" >> "${BASH_ENV}"
set -x
- run:
name: Get workflow job id
command: |
echo "export OUR_GITHUB_JOB_ID=${CIRCLE_WORKFLOW_JOB_ID}" >> "${BASH_ENV}"
- run:
name: Build
command: |
set -x
git submodule sync
git submodule update --init --recursive --depth 1 --jobs 0
export PATH="/usr/local/bin:$PATH"
export WORKSPACE_DIR="${HOME}/workspace"
mkdir -p "${WORKSPACE_DIR}"
MINICONDA_URL="https://repo.anaconda.com/miniconda/Miniconda3-py38_4.12.0-MacOSX-x86_64.sh"
if [ << parameters.python-version >> == 3.9.12 ]; then
MINICONDA_URL="https://repo.anaconda.com/miniconda/Miniconda3-py39_4.12.0-MacOSX-x86_64.sh"
fi
# If a local installation of conda doesn't exist, we download and install conda
if [ ! -d "${WORKSPACE_DIR}/miniconda3" ]; then
mkdir -p "${WORKSPACE_DIR}"
curl --retry 3 ${MINICONDA_URL} -o "${WORKSPACE_DIR}"/miniconda3.sh
bash "${WORKSPACE_DIR}"/miniconda3.sh -b -p "${WORKSPACE_DIR}"/miniconda3
fi
export PATH="${WORKSPACE_DIR}/miniconda3/bin:$PATH"
# shellcheck disable=SC1091
source "${WORKSPACE_DIR}"/miniconda3/bin/activate
brew link --force libomp
echo "export CMAKE_PREFIX_PATH=${CONDA_PREFIX:-"$(dirname "$(which conda)")/../"}" >> "${BASH_ENV}"
.ci/pytorch/macos-build.sh
- when:
condition: << parameters.build-generates-artifacts >>
steps:
- run:
name: Archive artifacts into zip
command: |
zip -1 -r artifacts.zip dist/ build/.ninja_log build/compile_commands.json .additional_ci_files
cp artifacts.zip /Users/distiller/workspace
- persist_to_workspace:
root: /Users/distiller/workspace/
paths:
- miniconda3
- artifacts.zip
- store_artifacts:
path: /Users/distiller/project/artifacts.zip
mac_test:
parameters:
build-environment:
type: string
shard-number:
type: string
num-test-shards:
type: string
xcode-version:
type: string
test-config:
type: string
default: 'default'
macos:
xcode: << parameters.xcode-version >>
environment:
GIT_DEFAULT_BRANCH: 'master'
BUILD_ENVIRONMENT: << parameters.build-environment >>
TEST_CONFIG: << parameters.test-config >>
SHARD_NUMBER: << parameters.shard-number >>
NUM_TEST_SHARDS: << parameters.num-test-shards >>
PYTORCH_RETRY_TEST_CASES: 1
PYTORCH_OVERRIDE_FLAKY_SIGNAL: 1
steps:
- checkout
- attach_workspace:
at: ~/workspace
- run_brew_for_macos_build
- run:
name: Test
no_output_timeout: "2h"
command: |
set -x
git submodule sync --recursive
git submodule update --init --recursive
mv ~/workspace/artifacts.zip .
unzip artifacts.zip
export IN_CI=1
COMMIT_MESSAGES=$(git cherry -v "origin/${GIT_DEFAULT_BRANCH:-master}")
export PATH="/usr/local/bin:$PATH"
export WORKSPACE_DIR="${HOME}/workspace"
mkdir -p "${WORKSPACE_DIR}"
export PATH="${WORKSPACE_DIR}/miniconda3/bin:$PATH"
source "${WORKSPACE_DIR}"/miniconda3/bin/activate
# sanitize the input commit message and PR body here:
# trim all new lines from commit messages to avoid issues with batch environment
# variable copying. see https://github.com/pytorch/pytorch/pull/80043#issuecomment-1167796028
COMMIT_MESSAGES="${COMMIT_MESSAGES//[$'\n\r']}"
# then trim all special characters like single and double quotes to avoid unescaped inputs to
# wreak havoc internally
export COMMIT_MESSAGES="${COMMIT_MESSAGES//[\'\"]}"
python3 -mpip install dist/*.whl
.ci/pytorch/macos-test.sh
- run:
name: Copy files for uploading test stats
command: |
# copy into a parent folder test-reports because we can't use CIRCLEI_BUILD_NUM in path when persisting to workspace
mkdir -p test-reports/test-reports_${CIRCLE_BUILD_NUM}/test/test-reports
cp -r test/test-reports test-reports/test-reports_${CIRCLE_BUILD_NUM}/test/test-reports
- store_test_results:
path: test/test-reports
- persist_to_workspace:
root: /Users/distiller/project/
paths:
- test-reports
upload_test_stats:
machine: # executor type
image: ubuntu-2004:202010-01 # # recommended linux image - includes Ubuntu 20.04, docker 19.03.13, docker-compose 1.27.4
steps:
- checkout
- attach_workspace:
at: ~/workspace
- run:
name: upload
command: |
set -ex
if [ -z ${AWS_ACCESS_KEY_FOR_OSSCI_ARTIFACT_UPLOAD} ]; then
echo "No credentials found, cannot upload test stats (are you on a fork?)"
exit 0
fi
cp -r ~/workspace/test-reports/* ~/project
pip3 install requests==2.26 rockset==1.0.3 boto3==1.19.12
export AWS_ACCESS_KEY_ID=${AWS_ACCESS_KEY_FOR_OSSCI_ARTIFACT_UPLOAD}
export AWS_SECRET_ACCESS_KEY=${AWS_SECRET_KEY_FOR_OSSCI_ARTIFACT_UPLOAD}
# i dont know how to get the run attempt number for reruns so default to 1
python3 -m tools.stats.upload_test_stats --workflow-run-id "${CIRCLE_WORKFLOW_JOB_ID}" --workflow-run-attempt 1 --head-branch << pipeline.git.branch >> --circleci
pytorch_macos_10_13_py3_test:
environment:
BUILD_ENVIRONMENT: pytorch-macos-10.13-py3-test
macos:
xcode: "12.0"
steps:
- checkout
- attach_workspace:
at: ~/workspace
- run_brew_for_macos_build
- run:
name: Test
no_output_timeout: "1h"
command: |
set -e
export JOB_BASE_NAME=$CIRCLE_JOB
chmod a+x .ci/pytorch/macos-test.sh
unbuffer .ci/pytorch/macos-test.sh 2>&1 | ts
- store_test_results:
path: test/test-reports
pytorch_macos_10_13_py3_lite_interpreter_build_test:
environment:
BUILD_ENVIRONMENT: pytorch-macos-10.13-py3-test
macos:
xcode: "12.0"
steps:
- checkout
- attach_workspace:
at: ~/workspace
- run_brew_for_macos_build
- run:
name: Test
no_output_timeout: "1h"
command: |
set -e
export BUILD_LITE_INTERPRETER=1
export JOB_BASE_NAME=$CIRCLE_JOB
chmod a+x ${HOME}/project/.ci/pytorch/macos-lite-interpreter-build-test.sh
unbuffer ${HOME}/project/.ci/pytorch/macos-lite-interpreter-build-test.sh 2>&1 | ts
- store_test_results:
path: test/test-reports
pytorch_android_gradle_build:
environment:
BUILD_ENVIRONMENT: pytorch-linux-xenial-py3-clang5-android-ndk-r19c-gradle-build
DOCKER_IMAGE: "308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/pytorch-linux-xenial-py3-clang5-android-ndk-r19c"
PYTHON_VERSION: "3.7"
resource_class: large
machine:
image: ubuntu-2004:202104-01
steps:
- checkout
- calculate_docker_image_tag
- setup_linux_system_environment
- setup_ci_environment
- run:
name: pytorch android gradle build
no_output_timeout: "1h"
command: |
set -eux
docker_image_commit=${DOCKER_IMAGE}:build-${DOCKER_TAG}-${CIRCLE_SHA1}
docker_image_libtorch_android_x86_32=${docker_image_commit}-android-x86_32
docker_image_libtorch_android_x86_64=${docker_image_commit}-android-x86_64
docker_image_libtorch_android_arm_v7a=${docker_image_commit}-android-arm-v7a
docker_image_libtorch_android_arm_v8a=${docker_image_commit}-android-arm-v8a
echo "docker_image_commit: "${docker_image_commit}
echo "docker_image_libtorch_android_x86_32: "${docker_image_libtorch_android_x86_32}
echo "docker_image_libtorch_android_x86_64: "${docker_image_libtorch_android_x86_64}
echo "docker_image_libtorch_android_arm_v7a: "${docker_image_libtorch_android_arm_v7a}
echo "docker_image_libtorch_android_arm_v8a: "${docker_image_libtorch_android_arm_v8a}
# x86_32
time docker pull ${docker_image_libtorch_android_x86_32} >/dev/null
export id_x86_32=$(docker run --env-file "${BASH_ENV}" -e GRADLE_OFFLINE=1 --cap-add=SYS_PTRACE --security-opt seccomp=unconfined -t -d -w /var/lib/jenkins ${docker_image_libtorch_android_x86_32})
export COMMAND='((echo "sudo chown -R jenkins workspace") | docker exec -u jenkins -i "$id_x86_32" bash) 2>&1'
echo ${COMMAND} > ./command.sh && unbuffer bash ./command.sh | ts
# arm-v7a
time docker pull ${docker_image_libtorch_android_arm_v7a} >/dev/null
export id_arm_v7a=$(docker run --env-file "${BASH_ENV}" --cap-add=SYS_PTRACE --security-opt seccomp=unconfined -t -d -w /var/lib/jenkins ${docker_image_libtorch_android_arm_v7a})
export COMMAND='((echo "sudo chown -R jenkins workspace") | docker exec -u jenkins -i "$id_arm_v7a" bash) 2>&1'
echo ${COMMAND} > ./command.sh && unbuffer bash ./command.sh | ts
mkdir -p ~/workspace/build_android_install_arm_v7a
docker cp $id_arm_v7a:/var/lib/jenkins/workspace/build_android/install ~/workspace/build_android_install_arm_v7a
# x86_64
time docker pull ${docker_image_libtorch_android_x86_64} >/dev/null
export id_x86_64=$(docker run --env-file "${BASH_ENV}" --cap-add=SYS_PTRACE --security-opt seccomp=unconfined -t -d -w /var/lib/jenkins ${docker_image_libtorch_android_x86_64})
export COMMAND='((echo "sudo chown -R jenkins workspace") | docker exec -u jenkins -i "$id_x86_64" bash) 2>&1'
echo ${COMMAND} > ./command.sh && unbuffer bash ./command.sh | ts
mkdir -p ~/workspace/build_android_install_x86_64
docker cp $id_x86_64:/var/lib/jenkins/workspace/build_android/install ~/workspace/build_android_install_x86_64
# arm-v8a
time docker pull ${docker_image_libtorch_android_arm_v8a} >/dev/null
export id_arm_v8a=$(docker run --env-file "${BASH_ENV}" --cap-add=SYS_PTRACE --security-opt seccomp=unconfined -t -d -w /var/lib/jenkins ${docker_image_libtorch_android_arm_v8a})
export COMMAND='((echo "sudo chown -R jenkins workspace") | docker exec -u jenkins -i "$id_arm_v8a" bash) 2>&1'
echo ${COMMAND} > ./command.sh && unbuffer bash ./command.sh | ts
mkdir -p ~/workspace/build_android_install_arm_v8a
docker cp $id_arm_v8a:/var/lib/jenkins/workspace/build_android/install ~/workspace/build_android_install_arm_v8a
docker cp ~/workspace/build_android_install_arm_v7a $id_x86_32:/var/lib/jenkins/workspace/build_android_install_arm_v7a
docker cp ~/workspace/build_android_install_x86_64 $id_x86_32:/var/lib/jenkins/workspace/build_android_install_x86_64
docker cp ~/workspace/build_android_install_arm_v8a $id_x86_32:/var/lib/jenkins/workspace/build_android_install_arm_v8a
# run gradle buildRelease
export COMMAND='((echo "sudo chown -R jenkins workspace && cd workspace && ./.circleci/scripts/build_android_gradle.sh") | docker exec -u jenkins -i "$id_x86_32" bash) 2>&1'
echo ${COMMAND} > ./command.sh && unbuffer bash ./command.sh | ts
mkdir -p ~/workspace/build_android_artifacts
docker cp $id_x86_32:/var/lib/jenkins/workspace/android/artifacts.tgz ~/workspace/build_android_artifacts/
output_image=$docker_image_libtorch_android_x86_32-gradle
docker commit "$id_x86_32" ${output_image}
time docker push ${output_image}
- store_artifacts:
path: ~/workspace/build_android_artifacts/artifacts.tgz
destination: artifacts.tgz
pytorch_android_publish_snapshot:
environment:
BUILD_ENVIRONMENT: pytorch-linux-xenial-py3-clang5-android-ndk-r19c-gradle-publish-snapshot
DOCKER_IMAGE: "308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/pytorch-linux-xenial-py3-clang5-android-ndk-r19c"
PYTHON_VERSION: "3.7"
resource_class: large
machine:
image: ubuntu-2004:202104-01
steps:
- checkout
- calculate_docker_image_tag
- setup_linux_system_environment
- setup_ci_environment
- run:
name: pytorch android gradle build
no_output_timeout: "1h"
command: |
set -eux
docker_image_commit=${DOCKER_IMAGE}:build-${DOCKER_TAG}-${CIRCLE_SHA1}
docker_image_libtorch_android_x86_32_gradle=${docker_image_commit}-android-x86_32-gradle
echo "docker_image_commit: "${docker_image_commit}
echo "docker_image_libtorch_android_x86_32_gradle: "${docker_image_libtorch_android_x86_32_gradle}
# x86_32
time docker pull ${docker_image_libtorch_android_x86_32_gradle} >/dev/null
export id_x86_32=$(docker run --env-file "${BASH_ENV}" --cap-add=SYS_PTRACE --security-opt seccomp=unconfined -t -d -w /var/lib/jenkins ${docker_image_libtorch_android_x86_32_gradle})
export COMMAND='((echo "sudo chown -R jenkins workspace" && echo "export BUILD_ENVIRONMENT=${BUILD_ENVIRONMENT}" && echo "export SONATYPE_NEXUS_USERNAME=${SONATYPE_NEXUS_USERNAME}" && echo "export SONATYPE_NEXUS_PASSWORD=${SONATYPE_NEXUS_PASSWORD}" && echo "export ANDROID_SIGN_KEY=${ANDROID_SIGN_KEY}" && echo "export ANDROID_SIGN_PASS=${ANDROID_SIGN_PASS}" && echo "sudo chown -R jenkins workspace && cd workspace && ./.circleci/scripts/publish_android_snapshot.sh") | docker exec -u jenkins -i "$id_x86_32" bash) 2>&1'
echo ${COMMAND} > ./command.sh && unbuffer bash ./command.sh | ts
output_image=${docker_image_libtorch_android_x86_32_gradle}-publish-snapshot
docker commit "$id_x86_32" ${output_image}
time docker push ${output_image}
pytorch_android_gradle_build-x86_32:
environment:
BUILD_ENVIRONMENT: pytorch-linux-xenial-py3-clang5-android-ndk-r19c-gradle-build-only-x86_32
DOCKER_IMAGE: "308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/pytorch-linux-xenial-py3-clang5-android-ndk-r19c"
PYTHON_VERSION: "3.7"
resource_class: large
machine:
image: ubuntu-2004:202104-01
steps:
- checkout
- calculate_docker_image_tag
- setup_linux_system_environment
- checkout
- setup_ci_environment
- run:
name: pytorch android gradle build only x86_32 (for PR)
no_output_timeout: "1h"
command: |
set -e
docker_image_libtorch_android_x86_32=${DOCKER_IMAGE}:build-${DOCKER_TAG}-${CIRCLE_SHA1}-android-x86_32
echo "docker_image_libtorch_android_x86_32: "${docker_image_libtorch_android_x86_32}
# x86
time docker pull ${docker_image_libtorch_android_x86_32} >/dev/null
export id=$(docker run --env-file "${BASH_ENV}" --cap-add=SYS_PTRACE --security-opt seccomp=unconfined -t -d -w /var/lib/jenkins ${docker_image_libtorch_android_x86_32})
export COMMAND='((echo "export BUILD_ENVIRONMENT=${BUILD_ENVIRONMENT}" && echo "export GRADLE_OFFLINE=1" && echo "sudo chown -R jenkins workspace && cd workspace && ./.circleci/scripts/build_android_gradle.sh") | docker exec -u jenkins -i "$id" bash) 2>&1'
echo ${COMMAND} > ./command.sh && unbuffer bash ./command.sh | ts
mkdir -p ~/workspace/build_android_x86_32_artifacts
docker cp $id:/var/lib/jenkins/workspace/android/artifacts.tgz ~/workspace/build_android_x86_32_artifacts/
output_image=${docker_image_libtorch_android_x86_32}-gradle
docker commit "$id" ${output_image}
time docker push ${output_image}
- store_artifacts:
path: ~/workspace/build_android_x86_32_artifacts/artifacts.tgz
destination: artifacts.tgz
pytorch_ios_build:
<<: *pytorch_ios_params
macos:
xcode: "12.5.1"
steps:
- run:
name: checkout with retry
command: |
checkout() {
set -ex
# Workaround old docker images with incorrect $HOME
# check https://github.com/docker/docker/issues/2968 for details
if [ "${HOME}" = "/" ]
then
export HOME=$(getent passwd $(id -un) | cut -d: -f6)
fi
mkdir -p ~/.ssh
echo 'github.com ssh-rsa AAAAB3NzaC1yc2EAAAABIwAAAQEAq2A7hRGmdnm9tUDbO9IDSwBK6TbQa+PXYPCPy6rbTrTtw7PHkccKrpp0yVhp5HdEIcKr6pLlVDBfOLX9QUsyCOV0wzfjIJNlGEYsdlLJizHhbn2mUjvSAHQqZETYP81eFzLQNnPHt4EVVUh7VfDESU84KezmD5QlWpXLmvU31/yMf+Se8xhHTvKSCZIFImWwoG6mbUoWf9nzpIoaSjB+weqqUUmpaaasXVal72J+UX2B+2RPW3RcT0eOzQgqlJL3RKrTJvdsjE3JEAvGq3lGHSZXy28G3skua2SmVi/w4yCE6gbODqnTWlg7+wC604ydGXA8VJiS5ap43JXiUFFAaQ==
' >> ~/.ssh/known_hosts
# use git+ssh instead of https
git config --global url."ssh://git@github.com".insteadOf "https://github.com" || true
git config --global gc.auto 0 || true
echo 'Cloning git repository'
mkdir -p '/Users/distiller/project'
cd '/Users/distiller/project'
git clone "$CIRCLE_REPOSITORY_URL" .
echo 'Checking out branch'
git checkout --force -B "$CIRCLE_BRANCH" "$CIRCLE_SHA1"
git --no-pager log --no-color -n 1 --format='HEAD is now at %h %s'
}
retry () {
$* || (sleep 1 && $*) || (sleep 2 && $*) || (sleep 4 && $*) || (sleep 8 && $*)
}
retry checkout
- run_brew_for_ios_build
- run:
name: Setup Fastlane
no_output_timeout: "1h"
command: |
set -e
PROJ_ROOT=/Users/distiller/project
cd ${PROJ_ROOT}/ios/TestApp
# install fastlane
sudo gem install bundler && bundle install
- run:
name: Build
no_output_timeout: "1h"
command: |
set -e
WORKSPACE=/Users/distiller/workspace
PROJ_ROOT=/Users/distiller/project
export TCLLIBPATH="/usr/local/lib"
# Install conda
curl --retry 3 -o ~/conda.sh https://repo.anaconda.com/miniconda/Miniconda3-py39_4.12.0-MacOSX-x86_64.sh
chmod +x ~/conda.sh
/bin/bash ~/conda.sh -b -p ~/anaconda
export PATH="~/anaconda/bin:${PATH}"
source ~/anaconda/bin/activate
# Install dependencies
retry () {
$* || (sleep 1 && $*) || (sleep 2 && $*) || (sleep 4 && $*) || (sleep 8 && $*)
}
retry conda install numpy ninja pyyaml mkl mkl-include setuptools cmake requests typing-extensions --yes
# sync submodules
cd ${PROJ_ROOT}
git submodule sync
git submodule update --init --recursive --depth 1 --jobs 0
# export
export CMAKE_PREFIX_PATH=${CONDA_PREFIX:-"$(dirname $(which conda))/../"}
# run build script
chmod a+x ${PROJ_ROOT}/scripts/build_ios.sh
echo "IOS_ARCH: ${IOS_ARCH}"
echo "IOS_PLATFORM: ${IOS_PLATFORM}"
echo "USE_PYTORCH_METAL": "${USE_METAL}"
echo "BUILD_LITE_INTERPRETER": "${BUILD_LITE_INTERPRETER}"
echo "USE_COREML_DELEGATE": "${USE_COREML_DELEGATE}"
#check the custom build flag
echo "SELECTED_OP_LIST: ${SELECTED_OP_LIST}"
if [ -n "${SELECTED_OP_LIST}" ]; then
export SELECTED_OP_LIST="${PROJ_ROOT}/ios/TestApp/custom_build/${SELECTED_OP_LIST}"
fi
export IOS_ARCH=${IOS_ARCH}
export IOS_PLATFORM=${IOS_PLATFORM}
export USE_COREML_DELEGATE=${USE_COREML_DELEGATE}
if [ ${IOS_PLATFORM} != "SIMULATOR" ]; then
export USE_PYTORCH_METAL=${USE_METAL}
fi
unbuffer ${PROJ_ROOT}/scripts/build_ios.sh 2>&1 | ts
- run:
name: Run Build Test
no_output_timeout: "30m"
command: |
set -e
PROJ_ROOT=/Users/distiller/project
# run the ruby build script
if ! [ -x "$(command -v xcodebuild)" ]; then
echo 'Error: xcodebuild is not installed.'
exit 1
fi
ruby ${PROJ_ROOT}/scripts/xcode_build.rb -i ${PROJ_ROOT}/build_ios/install -x ${PROJ_ROOT}/ios/TestApp/TestApp.xcodeproj -p ${IOS_PLATFORM}
if ! [ "$?" -eq "0" ]; then
echo 'xcodebuild failed!'
exit 1
fi
- run:
name: Run Simulator Tests
no_output_timeout: "2h"
command: |
set -e
if [ ${IOS_PLATFORM} != "SIMULATOR" ]; then
echo "not SIMULATOR build, skip it."
exit 0
fi
WORKSPACE=/Users/distiller/workspace
PROJ_ROOT=/Users/distiller/project
source ~/anaconda/bin/activate
# use the pytorch nightly build to generate models
pip3 install --pre torch torchvision torchaudio -f https://download.pytorch.org/whl/nightly/cpu/torch_nightly.html
# generate models for differnet backends
cd ${PROJ_ROOT}/ios/TestApp/benchmark
mkdir -p ../models
if [ ${USE_COREML_DELEGATE} == 1 ]; then
pip install coremltools==5.0b5 protobuf==3.20.1
python coreml_backend.py
else
cd "${PROJ_ROOT}"
python test/mobile/model_test/gen_test_model.py ios-test
fi
cd "${PROJ_ROOT}/ios/TestApp/benchmark"
if [ ${BUILD_LITE_INTERPRETER} == 1 ]; then
echo "Setting up the TestApp for LiteInterpreter"
ruby setup.rb --lite 1
else
echo "Setting up the TestApp for Full JIT"
ruby setup.rb
fi
cd "${PROJ_ROOT}/ios/TestApp"
# instruments -s -devices
if [ "${BUILD_LITE_INTERPRETER}" == 1 ]; then
if [ "${USE_COREML_DELEGATE}" == 1 ]; then
fastlane scan --only_testing TestAppTests/TestAppTests/testCoreML
else
fastlane scan --only_testing TestAppTests/TestAppTests/testLiteInterpreter
fi
else
fastlane scan --only_testing TestAppTests/TestAppTests/testFullJIT
fi
pytorch_linux_bazel_build:
<<: *pytorch_params
machine:
image: ubuntu-2004:202104-01
steps:
- checkout
- calculate_docker_image_tag
- setup_linux_system_environment
- setup_ci_environment
- run:
name: Bazel Build
no_output_timeout: "1h"
command: |
set -e
# Pull Docker image and run build
echo "DOCKER_IMAGE: "${DOCKER_IMAGE}:${DOCKER_TAG}
time docker pull ${DOCKER_IMAGE}:${DOCKER_TAG} >/dev/null
export id=$(docker run --env-file "${BASH_ENV}" --cap-add=SYS_PTRACE --security-opt seccomp=unconfined --cap-add=SYS_PTRACE --security-opt seccomp=unconfined -t -d -w /var/lib/jenkins ${DOCKER_IMAGE}:${DOCKER_TAG})
echo "Do NOT merge main branch into $CIRCLE_BRANCH in environment $BUILD_ENVIRONMENT"
git submodule sync && git submodule update -q --init --recursive --depth 1 --jobs 0
docker cp /home/circleci/project/. $id:/var/lib/jenkins/workspace
export COMMAND='((echo "sudo chown -R jenkins workspace && cd workspace && .ci/pytorch/build.sh") | docker exec -u jenkins -i "$id" bash) 2>&1'
echo ${COMMAND} > ./command.sh && unbuffer bash ./command.sh | ts
# Push intermediate Docker image for next phase to use
if [ -z "${BUILD_ONLY}" ]; then
# Augment our output image name with bazel to avoid collisions
output_image=${DOCKER_IMAGE}:build-${DOCKER_TAG}-bazel-${CIRCLE_SHA1}
export COMMIT_DOCKER_IMAGE=$output_image
docker commit "$id" ${COMMIT_DOCKER_IMAGE}
time docker push ${COMMIT_DOCKER_IMAGE}
fi
pytorch_linux_bazel_test:
<<: *pytorch_params
machine:
image: ubuntu-2004:202104-01
steps:
- checkout
- calculate_docker_image_tag
- setup_linux_system_environment
- setup_ci_environment
- run:
name: Test
no_output_timeout: "90m"
command: |
set -e
output_image=${DOCKER_IMAGE}:build-${DOCKER_TAG}-bazel-${CIRCLE_SHA1}
export COMMIT_DOCKER_IMAGE=$output_image
echo "DOCKER_IMAGE: "${COMMIT_DOCKER_IMAGE}
time docker pull ${COMMIT_DOCKER_IMAGE} >/dev/null
if [ -n "${USE_CUDA_DOCKER_RUNTIME}" ]; then
export id=$(docker run --env-file "${BASH_ENV}" --cap-add=SYS_PTRACE --security-opt seccomp=unconfined --gpus all -t -d -w /var/lib/jenkins ${COMMIT_DOCKER_IMAGE})
else
export id=$(docker run --env-file "${BASH_ENV}" --cap-add=SYS_PTRACE --security-opt seccomp=unconfined -t -d -w /var/lib/jenkins ${COMMIT_DOCKER_IMAGE})
fi
retrieve_test_reports() {
echo "retrieving test reports"
docker cp -L $id:/var/lib/jenkins/workspace/bazel-testlogs ./ || echo 'No test reports found!'
}
trap "retrieve_test_reports" ERR
if [[ ${BUILD_ENVIRONMENT} == *"multigpu"* ]]; then
export COMMAND='((echo "sudo chown -R jenkins workspace && cd workspace && .ci/pytorch/multigpu-test.sh") | docker exec -u jenkins -i "$id" bash) 2>&1'
else
export COMMAND='((echo "sudo chown -R jenkins workspace && cd workspace && .ci/pytorch/test.sh") | docker exec -u jenkins -i "$id" bash) 2>&1'
fi
echo ${COMMAND} > ./command.sh && unbuffer bash ./command.sh | ts
retrieve_test_reports
docker stats --all --no-stream
- store_test_results:
path: bazel-testlogs
pytorch_windows_test_multigpu:
machine:
image: ubuntu-2004:202104-01
steps:
- checkout
- run:
name: Test
no_output_timeout: "90m"
command: |
set -e
python3 -m pip install requests
python3 ./.circleci/scripts/trigger_azure_pipeline.py

View File

@ -0,0 +1,18 @@
promote_s3:
<<: *promote_common
steps:
- checkout
- run:
name: Running promote script
command: |
scripts/release/promote/wheel_to_s3.sh
promote_conda:
<<: *promote_common
steps:
- checkout
- run:
name: Running promote script
command: |
scripts/release/promote/conda_to_conda.sh

View File

@ -0,0 +1,29 @@
setup:
docker:
- image: circleci/python:3.7.3
steps:
- checkout
- run:
name: Save commit message
command: git log --format='%B' -n 1 HEAD > .circleci/scripts/COMMIT_MSG
# Note [Workspace for CircleCI scripts]
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# In the beginning, you wrote your CI scripts in a
# .circleci/config.yml file, and life was good. Your CI
# configurations flourished and multiplied.
#
# Then one day, CircleCI cometh down high and say, "Your YAML file
# is too biggeth, it stresses our servers so." And thus they
# asketh us to smite the scripts in the yml file.
#
# But you can't just put the scripts in the .circleci folder,
# because in some jobs, you don't ever actually checkout the
# source repository. Where you gonna get the scripts from?
#
# Here's how you do it: you persist .circleci/scripts into a
# workspace, attach the workspace in your subjobs, and run all
# your scripts from there.
- persist_to_workspace:
root: .
paths: .circleci/scripts

View File

@ -0,0 +1,51 @@
##############################################################################
# Binary build (nightlies nightly build) defaults
# The binary builds use the docker executor b/c at time of writing the machine
# executor is limited to only two cores and is painfully slow (4.5+ hours per
# GPU build). But the docker executor cannot be run with --runtime=nvidia, and
# so the binary test/upload jobs must run on a machine executor. The package
# built in the build job is persisted to the workspace, which the test jobs
# expect. The test jobs just run a few quick smoke tests (very similar to the
# second-round-user-facing smoke tests above) and then upload the binaries to
# their final locations. The upload part requires credentials that should only
# be available to org-members.
#
# binary_checkout MUST be run before other commands here. This is because the
# other commands are written in .circleci/scripts/*.sh , so the pytorch source
# code must be downloaded on the machine before they can be run. We cannot
# inline all the code into this file, since that would cause the yaml size to
# explode past 4 MB (all the code in the command section is just copy-pasted to
# everywhere in the .circleci/config.yml file where it appears).
##############################################################################
# Checks out the Pytorch and Builder repos (always both of them), and places
# them in the right place depending on what executor we're running on. We curl
# our .sh file from the interweb to avoid yaml size bloat. Note that many jobs
# do not need both the pytorch and builder repos, so this is a little wasteful
# (smoke tests and upload jobs do not need the pytorch repo).
binary_checkout: &binary_checkout
name: Checkout pytorch/builder repo
no_output_timeout: "30m"
command: .circleci/scripts/binary_checkout.sh
# Parses circleci arguments in a consistent way, essentially routing to the
# correct pythonXgccXcudaXos build we want
binary_populate_env: &binary_populate_env
name: Set up binary env variables
command: .circleci/scripts/binary_populate_env.sh
binary_install_miniconda: &binary_install_miniconda
name: Install miniconda
no_output_timeout: "1h"
command: .circleci/scripts/binary_install_miniconda.sh
# This section is used in the binary_test and smoke_test jobs. It expects
# 'binary_populate_env' to have populated /home/circleci/project/env and it
# expects another section to populate /home/circleci/project/ci_test_script.sh
# with the code to run in the docker
binary_run_in_docker: &binary_run_in_docker
name: Run in docker
# This step only runs on circleci linux machine executors that themselves
# need to start docker images
command: .circleci/scripts/binary_run_in_docker.sh

View File

@ -0,0 +1,8 @@
#- binary_linux_libtorch_3.6m_cpu_test:
# requires:
# - binary_linux_libtorch_3.6m_cpu_build
#- binary_linux_libtorch_3.6m_cu90_test:
# requires:
# - binary_linux_libtorch_3.6m_cu90_build
# Nightly uploads

View File

@ -52,13 +52,6 @@ modernize-*,
-modernize-use-nodiscard,
performance-*,
readability-container-size-empty,
readability-delete-null-pointer,
readability-duplicate-include
readability-misplaced-array-index,
readability-redundant-function-ptr-dereference,
readability-redundant-smartptr-get,
readability-simplify-subscript-expr,
readability-string-compare,
'
HeaderFilterRegex: '^(aten/|c10/|torch/).*$'
AnalyzeTemporaryDtors: false

View File

@ -7,7 +7,9 @@ max-line-length = 120
# C408 ignored because we like the dict keyword argument syntax
# E501 is not flexible enough, we're using B950 instead
ignore =
E203,E305,E402,E501,E721,E741,F405,F841,F999,W503,W504,C408,E302,W291,E303,
E203,E305,E402,E501,E721,E741,F405,F821,F841,F999,W503,W504,C408,E302,W291,E303,
# fix these lints in the future
E275,
# shebang has extra meaning in fbcode lints, so I think it's not worth trying
# to line this up with executable bit
EXE001,
@ -29,8 +31,6 @@ ignore =
TOR102,
per-file-ignores =
__init__.py: F401
test/**: F821
test/**/__init__.py: F401,F821
torch/utils/cpp_extension.py: B950
torchgen/api/types/__init__.py: F401,F403
torchgen/executorch/api/types/__init__.py: F401,F403

View File

@ -38,5 +38,3 @@ f70844bec783bfce43c950ccf180dc494e86f2bf
e6ec0efaf87703c5f889cfc20b29be455885d58d
# 2023-07-31 [optim][BE] split test file into logical parts: SWA, LR, optim
a53cda1ddc15336dc1ff0ce1eff2a49cdc5f882e
# 2024-01-02 clangformat: fused adam #116583
9dc68d1aa9e554d09344a10fff69f7b50b2d23a0

View File

@ -3,7 +3,6 @@ self-hosted-runner:
- linux.20_04.4x
- linux.20_04.16x
- linux.large
- linux.large.arc
- linux.2xlarge
- linux.4xlarge
- linux.12xlarge

View File

@ -1,67 +0,0 @@
name: Setup XPU host
description: Set up XPU host for CI
runs:
using: composite
steps:
- name: Clean all stopped docker containers
if: always()
shell: bash
run: |
# Prune all stopped containers.
# If other runner is pruning on this node, will skip.
nprune=$(ps -ef | grep -c "docker container prune")
if [[ $nprune -eq 1 ]]; then
docker container prune -f
fi
- name: Runner health check system info
if: always()
shell: bash
run: |
cat /etc/os-release || true
cat /etc/apt/sources.list.d/oneAPI.list || true
cat /etc/apt/sources.list.d/intel-gpu-jammy.list || true
whoami
- name: Runner health check xpu-smi
if: always()
shell: bash
run: |
xpu-smi discovery
- name: Runner health check GPU count
if: always()
shell: bash
run: |
ngpu=$(xpu-smi discovery | grep -c -E 'Device Name')
msg="Please file an issue on pytorch/pytorch reporting the faulty runner. Include a link to the runner logs so the runner can be identified"
if [[ $ngpu -eq 0 ]]; then
echo "Error: Failed to detect any GPUs on the runner"
echo "$msg"
exit 1
fi
- name: Runner diskspace health check
uses: ./.github/actions/diskspace-cleanup
if: always()
- name: Runner health check disconnect on failure
if: ${{ failure() }}
shell: bash
run: |
killall runsvc.sh
- name: Preserve github env variables for use in docker
shell: bash
run: |
env | grep '^GITHUB' >> "/tmp/github_env_${GITHUB_RUN_ID}"
env | grep '^CI' >> "/tmp/github_env_${GITHUB_RUN_ID}"
- name: XPU set GPU_FLAG
shell: bash
run: |
# Add render group for container creation.
render_gid=`cat /etc/group | grep render | cut -d: -f3`
echo "GPU_FLAG=--device=/dev/mem --device=/dev/dri --group-add video --group-add $render_gid" >> "${GITHUB_ENV}"

View File

@ -1,20 +0,0 @@
name: Teardown XPU host
description: Tear down XPU host for CI
runs:
using: composite
steps:
- name: Teardown XPU
if: always()
shell: bash
run: |
# Prune all stopped containers.
# If other runner is pruning on this node, will skip.
nprune=$(ps -ef | grep -c "docker container prune")
if [[ $nprune -eq 1 ]]; then
docker container prune -f
fi
- name: Runner diskspace health check
uses: ./.github/actions/diskspace-cleanup
if: always()

View File

@ -12,6 +12,7 @@ reviewers:
symbolic-shapes:
- symbolic-shapes
- antoniojkim
- wconstab
- SherlockNoMad
Chillee:
- ezyang

View File

@ -1 +1 @@
e3efbc2d9094685dd2d4ae143853941f82f167af
6518fa9b2c74e84d7eb1fc6e3eb51e43213f0c05

View File

@ -1 +1 @@
d23430765b5df76cd1267f438f129f51b7d6e3e1
c1e2095c3a16fbe7db25b9e2f206025488c2c203

View File

@ -1 +1 @@
e1c94dfa5a74331a376537c23bf74a2c367f24bd
r2.2

13
.github/labeler.yml vendored
View File

@ -8,6 +8,10 @@
- torch/_inductor/**
- test/inductor/**
"module: export":
- torch/_export/**
- test/export/**
"ciflow/inductor":
- torch/_decomp/**
- torch/_dynamo/**
@ -19,9 +23,8 @@
- torch/_subclasses/meta_utils.py
- test/distributed/test_dynamo_distributed.py
- test/distributed/test_inductor_collectives.py
- torch/_functorch/_aot_autograd/**
- torch/_functorch/aot_autograd.py
- torch/_functorch/partitioners.py
- torch/_functorch/aot_autograd.py
- .ci/docker/ci_commit_pins/**
- .github/ci_commit_pins/**
- c10/core/Sym*
@ -69,13 +72,9 @@
"ciflow/trunk":
- .ci/docker/ci_commit_pins/triton.txt
"oncall: distributed":
"module: distributed":
- torch/csrc/distributed/**
- torch/distributed/**
- torch/nn/parallel/**
- test/distributed/**
- torch/testing/_internal/distributed/**
"module: distributed_checkpoint":
- torch/distributed/checkpoint/**
- test/distributed/checkpoint/**

View File

@ -285,7 +285,6 @@
- yhcharles
- kiukchung
- d4l3k
- shuqiangzhang
mandatory_checks_name:
- EasyCLA
- Lint
@ -352,22 +351,16 @@
- Lint
- pull
- name: CPU inductor
- name: x86 CPU quantization
patterns:
- torch/_inductor/fx_passes/mkldnn_fusion.py
- torch/_inductor/fx_passes/quantization.py
- torch/_inductor/codegen/cpp.py
- test/inductor/test_mkldnn_pattern_matcher.py
- test/inductor/test_cpu_repo.py
- test/inductor/test_cpu_cpp_wrapper.py
- aten/src/ATen/native/quantized/cpu/**
- test/quantization/core/test_quantized_op.py
- torch/ao/quantization/quantizer/x86_inductor_quantizer.py
- torch/_inductor/fx_passes/quantization.py
- test/quantization/core/test_quantized_op.py
- test/inductor/test_mkldnn_pattern_matcher.py
- test/quantization/pt2e/test_x86inductor_quantizer.py
approved_by:
- leslie-fang-intel
- jgong5
- EikanWang
mandatory_checks_name:
- EasyCLA
- Lint

View File

@ -14,7 +14,6 @@ ciflow_push_tags:
- ciflow/slow
- ciflow/trunk
- ciflow/unstable
- ciflow/xpu
retryable_workflows:
- lint
- pull

View File

@ -10,9 +10,6 @@ from typing import Optional
SCRIPT_DIR = Path(__file__).parent
REPO_DIR = SCRIPT_DIR.parent.parent
# TODO: Remove me once Triton version is again in sync for vanilla and ROCm
ROCM_TRITION_VERSION = "2.1.0"
def read_triton_pin(rocm_hash: bool = False) -> str:
triton_file = "triton.txt" if not rocm_hash else "triton-rocm.txt"
@ -32,37 +29,25 @@ def check_and_replace(inp: str, src: str, dst: str) -> str:
return inp.replace(src, dst)
def patch_setup_py(
path: Path,
*,
version: str,
name: str = "triton",
expected_version: Optional[str] = None,
) -> None:
def patch_setup_py(path: Path, *, version: str, name: str = "triton") -> None:
with open(path) as f:
orig = f.read()
# Replace name
orig = check_and_replace(orig, 'name="triton",', f'name="{name}",')
# Replace version
if not expected_version:
expected_version = read_triton_version()
orig = check_and_replace(
orig, f'version="{expected_version}",', f'version="{version}",'
orig, f'version="{read_triton_version()}",', f'version="{version}",'
)
with open(path, "w") as f:
f.write(orig)
def patch_init_py(
path: Path, *, version: str, expected_version: Optional[str] = None
) -> None:
if not expected_version:
expected_version = read_triton_version()
def patch_init_py(path: Path, *, version: str) -> None:
with open(path) as f:
orig = f.read()
# Replace version
orig = check_and_replace(
orig, f"__version__ = '{expected_version}'", f'__version__ = "{version}"'
orig, f"__version__ = '{read_triton_version()}'", f'__version__ = "{version}"'
)
with open(path, "w") as f:
f.write(orig)
@ -99,7 +84,14 @@ def build_triton(
triton_repo = "https://github.com/openai/triton"
triton_pkg_name = "pytorch-triton"
check_call(["git", "clone", triton_repo], cwd=tmpdir)
check_call(["git", "checkout", commit_hash], cwd=triton_basedir)
if release:
ver, rev, patch = version.split(".")
check_call(
["git", "checkout", f"release/{ver}.{rev}.x"], cwd=triton_basedir
)
else:
check_call(["git", "checkout", commit_hash], cwd=triton_basedir)
if build_conda:
with open(triton_basedir / "meta.yaml", "w") as meta:
print(
@ -145,7 +137,7 @@ def build_triton(
cwd=triton_basedir,
env=env,
)
conda_path = next(iter(Path(tmpdir).glob("linux-64/torchtriton*.bz2")))
conda_path = list(Path(tmpdir).glob("linux-64/torchtriton*.bz2"))[0]
shutil.copy(conda_path, Path.cwd())
return Path.cwd() / conda_path.name
@ -155,7 +147,6 @@ def build_triton(
patch_init_py(
triton_pythondir / "triton" / "__init__.py",
version=f"{version}",
expected_version=ROCM_TRITION_VERSION if build_rocm else None,
)
if build_rocm:
@ -164,7 +155,6 @@ def build_triton(
triton_pythondir / "setup.py",
name=triton_pkg_name,
version=f"{version}",
expected_version=ROCM_TRITION_VERSION,
)
check_call("scripts/amd/setup_rocm_libs.sh", cwd=triton_basedir, shell=True)
print("ROCm libraries setup for triton installation...")
@ -173,7 +163,7 @@ def build_triton(
[sys.executable, "setup.py", "bdist_wheel"], cwd=triton_pythondir, env=env
)
whl_path = next(iter((triton_pythondir / "dist").glob("*.whl")))
whl_path = list((triton_pythondir / "dist").glob("*.whl"))[0]
shutil.copy(whl_path, Path.cwd())
if build_rocm:

Binary file not shown.

View File

@ -62,9 +62,9 @@ SUPPORTED_PERIODICAL_MODES: Dict[str, Callable[[Optional[str]], bool]] = {
}
# The link to the published list of disabled jobs
DISABLED_JOBS_URL = "https://ossci-metrics.s3.amazonaws.com/disabled-jobs.json"
DISABLED_JOBS_URL = "https://ossci-metrics.s3.amazonaws.com/disabled-jobs.json?versionId=jbbJUxI_SSZFssBBGCU6ybH9sxHitHLY"
# and unstable jobs
UNSTABLE_JOBS_URL = "https://ossci-metrics.s3.amazonaws.com/unstable-jobs.json"
UNSTABLE_JOBS_URL = "https://ossci-metrics.s3.amazonaws.com/unstable-jobs.json?versionId=hUtTalgnWb1m3AtJyVLUdu7DBrnddRkp"
# Some constants used to handle disabled and unstable jobs
JOB_NAME_SEP = "/"

View File

@ -93,9 +93,7 @@ def get_nccl_wheel_version(arch_version: str) -> str:
requirements = map(
str.strip, re.split("[;|]", PYTORCH_EXTRA_INSTALL_REQUIREMENTS[arch_version])
)
return next(x for x in requirements if x.startswith("nvidia-nccl-cu")).split("==")[
1
]
return [x for x in requirements if x.startswith("nvidia-nccl-cu")][0].split("==")[1]
def validate_nccl_dep_consistency(arch_version: str) -> None:

View File

@ -145,16 +145,6 @@ class GitRepo:
rc = self._run_git("rev-list", revision_range, "--", ".").strip()
return rc.split("\n") if len(rc) > 0 else []
def branches_containing_ref(
self, ref: str, *, include_remote: bool = True
) -> List[str]:
rc = (
self._run_git("branch", "--remote", "--contains", ref)
if include_remote
else self._run_git("branch", "--contains", ref)
)
return [x.strip() for x in rc.split("\n") if x.strip()] if len(rc) > 0 else []
def current_branch(self) -> str:
return self._run_git("symbolic-ref", "--short", "HEAD").strip()
@ -397,28 +387,13 @@ def _shasum(value: str) -> str:
return m.hexdigest()
def is_commit_hash(ref: str) -> bool:
"True if ref is hexadecimal number, else false"
try:
int(ref, 16)
except ValueError:
return False
return True
def are_ghstack_branches_in_sync(
repo: GitRepo, head_ref: str, base_ref: Optional[str] = None
) -> bool:
def are_ghstack_branches_in_sync(repo: GitRepo, head_ref: str) -> bool:
"""Checks that diff between base and head is the same as diff between orig and its parent"""
orig_ref = re.sub(r"/head$", "/orig", head_ref)
if base_ref is None:
base_ref = re.sub(r"/head$", "/base", head_ref)
base_ref = re.sub(r"/head$", "/base", head_ref)
orig_diff_sha = _shasum(repo.diff(f"{repo.remote}/{orig_ref}"))
head_diff_sha = _shasum(
repo.diff(
base_ref if is_commit_hash(base_ref) else f"{repo.remote}/{base_ref}",
f"{repo.remote}/{head_ref}",
)
repo.diff(f"{repo.remote}/{base_ref}", f"{repo.remote}/{head_ref}")
)
return orig_diff_sha == head_diff_sha

Binary file not shown.

View File

@ -44,10 +44,6 @@ def get_last_page_num_from_header(header: Any) -> int:
# Link info looks like: <https://api.github.com/repositories/65600975/labels?per_page=100&page=2>;
# rel="next", <https://api.github.com/repositories/65600975/labels?per_page=100&page=3>; rel="last"
link_info = header["link"]
# Docs does not specify that it should be present for projects with just few labels
# And https://github.com/malfet/deleteme/actions/runs/7334565243/job/19971396887 it's not the case
if link_info is None:
return 1
prefix = "&page="
suffix = ">;"
return int(

View File

@ -32,6 +32,7 @@ from trymerge import (
main as trymerge_main,
MandatoryChecksMissingError,
MergeRule,
PostCommentError,
RE_GHSTACK_DESC,
read_merge_rules,
remove_job_name_suffix,
@ -221,31 +222,6 @@ def mocked_read_merge_rules(repo: Any, org: str, project: str) -> List[MergeRule
]
def mocked_read_merge_rules_approvers(
repo: Any, org: str, project: str
) -> List[MergeRule]:
return [
MergeRule(
name="Core Reviewers",
patterns=["*"],
approved_by=["1", "2", "3", "4", "5", "6"],
mandatory_checks_name=[
"Lint",
"pull",
],
),
MergeRule(
name="Core Maintainers",
patterns=["*"],
approved_by=["1", "2", "malfet"],
mandatory_checks_name=[
"Lint",
"pull",
],
),
]
def mocked_read_merge_rules_raise(repo: Any, org: str, project: str) -> List[MergeRule]:
raise RuntimeError("testing")
@ -311,27 +287,6 @@ class TestTryMerge(TestCase):
RuntimeError, "testing", lambda: find_matching_merge_rule(pr, repo)
)
@mock.patch(
"trymerge.read_merge_rules", side_effect=mocked_read_merge_rules_approvers
)
def test_match_rules_approvers(self, *args: Any) -> None:
"Tests that PR has the necessary approvers"
repo = DummyGitRepo()
pr = GitHubPR("pytorch", "pytorch", 115329)
# Test that all potential approvers across all rules are listed if the
# PR doesn't have one of them
for mock_rule in ["Core Reviewers", "Core Maintainers"]:
self.assertRaisesRegex(
RuntimeError,
mock_rule,
lambda: find_matching_merge_rule(pr, repo),
)
pr = GitHubPR("pytorch", "pytorch", 115495)
# Test that PR with the correct approvers doesn't raise any exception
self.assertTrue(find_matching_merge_rule(pr, repo) is not None)
@mock.patch("trymerge.read_merge_rules", side_effect=mocked_read_merge_rules)
def test_lint_fails(self, *args: Any) -> None:
"Tests that PR fails mandatory lint check"
@ -515,6 +470,20 @@ class TestTryMerge(TestCase):
self.assertEqual(len(changed_files), pr.get_changed_files_count())
def test_revert_codev_fails(self, *args: Any) -> None:
pr = GitHubPR("pytorch", "pytorch", 91340)
class GitRepoCoDev(DummyGitRepo):
def commit_message(self, ref: str) -> str:
return pr.get_body()
repo = GitRepoCoDev()
self.assertRaisesRegex(
PostCommentError,
"landed via phabricator",
lambda: validate_revert(repo, pr, comment_id=1372496233),
)
def test_revert_codev_abandoned_diff_succeeds(self, *args: Any) -> None:
pr = GitHubPR("pytorch", "pytorch", 100652)

View File

@ -20,18 +20,7 @@ from collections import defaultdict
from dataclasses import dataclass
from functools import lru_cache
from pathlib import Path
from typing import (
Any,
Callable,
cast,
Dict,
Iterable,
List,
NamedTuple,
Optional,
Pattern,
Tuple,
)
from typing import Any, Callable, cast, Dict, List, NamedTuple, Optional, Pattern, Tuple
from warnings import warn
import yaml
@ -623,14 +612,19 @@ def can_skip_internal_checks(pr: "GitHubPR", comment_id: Optional[int] = None) -
return comment.author_login == "facebook-github-bot"
def _revlist_to_prs(
repo: GitRepo,
pr: "GitHubPR",
rev_list: Iterable[str],
should_skip: Optional[Callable[[int, "GitHubPR"], bool]] = None,
def get_ghstack_prs(
repo: GitRepo, pr: "GitHubPR", open_only: bool = True
) -> List[Tuple["GitHubPR", str]]:
rc: List[Tuple[GitHubPR, str]] = []
for idx, rev in enumerate(rev_list):
"""
Get the PRs in the stack that are below this PR (inclusive). Throws error if any of the open PRs are out of sync.
@:param open_only: Only return open PRs
"""
assert pr.is_ghstack_pr()
entire_stack: List[Tuple[GitHubPR, str]] = []
# For ghstack, cherry-pick commits based from origin
orig_ref = f"{repo.remote}/{re.sub(r'/head$', '/orig', pr.head_ref())}"
rev_list = repo.revlist(f"{pr.default_branch()}..{orig_ref}")
for idx, rev in enumerate(reversed(rev_list)):
msg = repo.commit_message(rev)
m = RE_PULL_REQUEST_RESOLVED.search(msg)
if m is None:
@ -641,48 +635,25 @@ def _revlist_to_prs(
raise RuntimeError(
f"PR {m.group('number')} resolved to wrong owner/repo pair"
)
pr_num = int(m.group("number"))
candidate = GitHubPR(pr.org, pr.project, pr_num) if pr_num != pr.pr_num else pr
if should_skip is not None and should_skip(idx, candidate):
continue
rc.append((candidate, rev))
return rc
def get_ghstack_prs(
repo: GitRepo, pr: "GitHubPR", open_only: bool = True
) -> List[Tuple["GitHubPR", str]]:
"""
Get the PRs in the stack that are below this PR (inclusive). Throws error if any of the open PRs are out of sync.
@:param open_only: Only return open PRs
"""
# For ghstack, cherry-pick commits based from origin
orig_ref = f"{repo.remote}/{pr.get_ghstack_orig_ref()}"
rev_list = repo.revlist(f"{pr.default_branch()}..{orig_ref}")
def skip_func(idx: int, candidate: "GitHubPR") -> bool:
if not open_only or not candidate.is_closed():
return False
print(
f"Skipping {idx+1} of {len(rev_list)} PR (#{candidate.pr_num}) as its already been merged"
)
return True
assert pr.is_ghstack_pr()
entire_stack = _revlist_to_prs(repo, pr, reversed(rev_list), skip_func)
stacked_pr_num = int(m.group("number"))
if stacked_pr_num != pr.pr_num:
stacked_pr = GitHubPR(pr.org, pr.project, stacked_pr_num)
if open_only and stacked_pr.is_closed():
print(
f"Skipping {idx+1} of {len(rev_list)} PR (#{stacked_pr_num}) as its already been merged"
)
continue
entire_stack.append((stacked_pr, rev))
else:
entire_stack.append((pr, rev))
for stacked_pr, rev in entire_stack:
if stacked_pr.is_closed():
continue
base_ref = stacked_pr.base_ref()
if base_ref == pr.default_branch():
base_ref = repo.get_merge_base(
f"{repo.remote}/{base_ref}", f"{repo.remote}/{stacked_pr.head_ref()}"
)
if not are_ghstack_branches_in_sync(repo, stacked_pr.head_ref(), base_ref):
if not are_ghstack_branches_in_sync(repo, stacked_pr.head_ref()):
raise RuntimeError(
f"PR {stacked_pr.pr_num} is out of sync with the corresponding revision {rev} on "
+ f"branch {stacked_pr.get_ghstack_orig_ref()} that would be merged into {stacked_pr.default_branch()}. "
+ f"branch {orig_ref} that would be merged into main. "
+ "This usually happens because there is a non ghstack change in the PR. "
+ f"Please sync them and try again (ex. make the changes on {orig_ref} and run ghstack)."
)
@ -723,10 +694,6 @@ class GitHubPR:
def is_ghstack_pr(self) -> bool:
return RE_GHSTACK_HEAD_REF.match(self.head_ref()) is not None
def get_ghstack_orig_ref(self) -> str:
assert self.is_ghstack_pr()
return re.sub(r"/head$", "/orig", self.head_ref())
def is_base_repo_private(self) -> bool:
return bool(self.info["baseRepository"]["isPrivate"])
@ -1321,9 +1288,6 @@ def find_matching_merge_rule(
ignore_current_checks=ignore_current_checks,
)
# This keeps the list of all approvers that could stamp the change
all_rule_approvers = {}
# PRs can fail multiple merge rules, but it only needs to pass one rule to be approved.
# If it fails all rules, we need to find the rule that it came closest to passing and report
# that to the dev.
@ -1367,31 +1331,24 @@ def find_matching_merge_rule(
continue
# Does the PR have the required approvals for this rule?
rule_approvers = set()
rule_approvers_set = set()
for approver in rule.approved_by:
if "/" in approver:
org, name = approver.split("/")
rule_approvers.update(gh_get_team_members(org, name))
rule_approvers_set.update(gh_get_team_members(org, name))
else:
rule_approvers.add(approver)
approvers_intersection = approved_by.intersection(rule_approvers)
rule_approvers_set.add(approver)
approvers_intersection = approved_by.intersection(rule_approvers_set)
# If rule requires approvers but they aren't the ones that reviewed PR
if len(approvers_intersection) == 0 and len(rule_approvers) > 0:
# Less than or equal is intentionally used here to gather all potential
# approvers
if reject_reason_score <= 10000:
if len(approvers_intersection) == 0 and len(rule_approvers_set) > 0:
if reject_reason_score < 10000:
reject_reason_score = 10000
all_rule_approvers[rule.name] = rule.approved_by
# Prepare the reject reason
all_rule_approvers_msg = [
f"- {name} ({', '.join(approved_by[:5])}{', ...' if len(approved_by) > 5 else ''})"
for name, approved_by in all_rule_approvers.items()
]
reject_reason = "Approvers from one of the following sets are needed:\n"
reject_reason += "\n".join(all_rule_approvers_msg)
reject_reason = "\n".join(
(
"Approval needed from one of the following:",
f"{', '.join(list(rule_approvers_set)[:5])}{', ...' if len(rule_approvers_set) > 5 else ''}",
)
)
continue
# Does the PR pass the checks required by this rule?
@ -1765,16 +1722,6 @@ def filter_checks_with_lambda(
return [check for check in checks.values() if status_filter(check.status)]
def get_pr_commit_sha(repo: GitRepo, pr: GitHubPR) -> str:
commit_sha = pr.get_merge_commit()
if commit_sha is not None:
return commit_sha
commits = repo.commits_resolving_gh_pr(pr.pr_num)
if len(commits) == 0:
raise PostCommentError("Can't find any commits resolving PR")
return commits[0]
def validate_revert(
repo: GitRepo, pr: GitHubPR, *, comment_id: Optional[int] = None
) -> Tuple[str, str]:
@ -1796,98 +1743,32 @@ def validate_revert(
f"Will not revert as @{author_login} is not one of "
f"[{', '.join(allowed_reverters)}], but instead is {author_association}."
)
skip_internal_checks = can_skip_internal_checks(pr, comment_id)
# Ignore associated diff it PR does not have internal changes
if pr.has_no_connected_diff():
skip_internal_checks = True
# Raises exception if matching rule is not found, but ignores all status checks
find_matching_merge_rule(
pr, repo, skip_mandatory_checks=True, skip_internal_checks=True
pr, repo, skip_mandatory_checks=True, skip_internal_checks=skip_internal_checks
)
commit_sha = get_pr_commit_sha(repo, pr)
commit_sha = pr.get_merge_commit()
if commit_sha is None:
commits = repo.commits_resolving_gh_pr(pr.pr_num)
if len(commits) == 0:
raise PostCommentError("Can't find any commits resolving PR")
commit_sha = commits[0]
msg = repo.commit_message(commit_sha)
rc = RE_DIFF_REV.search(msg)
if rc is not None and not skip_internal_checks:
raise PostCommentError(
f"Can't revert PR that was landed via phabricator as {rc.group(1)}. "
+ "Please revert by going to the internal diff and clicking Unland."
)
return (author_login, commit_sha)
def get_ghstack_dependent_prs(
repo: GitRepo, pr: GitHubPR, only_closed: bool = True
) -> List[Tuple[str, GitHubPR]]:
"""
Get the PRs in the stack that are above this PR (inclusive).
Throws error if stack have branched or original branches are gone
"""
assert pr.is_ghstack_pr()
orig_ref = f"{repo.remote}/{pr.get_ghstack_orig_ref()}"
rev_list = repo.revlist(f"{pr.default_branch()}..{orig_ref}")
if len(rev_list) == 0:
raise RuntimeError(
f"PR {pr.pr_num} does not have any revisions associated with it"
)
skip_len = len(rev_list) - 1
for branch in repo.branches_containing_ref(orig_ref):
candidate = repo.revlist(f"{pr.default_branch()}..{branch}")
# Pick longest candidate
if len(candidate) > len(rev_list):
candidate, rev_list = rev_list, candidate
# Validate that candidate always ends rev-list
if rev_list[-len(candidate) :] != candidate:
raise RuntimeError(
f"Branch {branch} revlist {', '.join(candidate)} is not a subset of {', '.join(rev_list)}"
)
# Remove commits original PR depends on
if skip_len > 0:
rev_list = rev_list[:-skip_len]
rc: List[Tuple[str, GitHubPR]] = []
for pr_, sha in _revlist_to_prs(repo, pr, rev_list):
if not pr_.is_closed():
if not only_closed:
rc.append(("", pr_))
continue
commit_sha = get_pr_commit_sha(repo, pr_)
rc.append((commit_sha, pr_))
return rc
def do_revert_prs(
repo: GitRepo,
shas_and_prs: List[Tuple[str, GitHubPR]],
*,
author_login: str,
extra_msg: str = "",
skip_internal_checks: bool = False,
dry_run: bool = False,
) -> None:
# Prepare and push revert commits
commit_shas: List[str] = []
for commit_sha, pr in shas_and_prs:
revert_msg = f"\nReverted {pr.get_pr_url()} on behalf of {prefix_with_github_url(author_login)}"
revert_msg += extra_msg
repo.checkout(pr.default_branch())
repo.revert(commit_sha)
msg = repo.commit_message("HEAD")
msg = re.sub(RE_PULL_REQUEST_RESOLVED, "", msg)
msg += revert_msg
repo.amend_commit_message(msg)
repo.push(shas_and_prs[0][1].default_branch(), dry_run)
# Comment/reopen PRs
for commit_sha, pr in shas_and_prs:
revert_message = (
f"@{pr.get_pr_creator_login()} your PR has been successfully reverted."
)
if (
pr.has_internal_changes()
and not pr.has_no_connected_diff()
and not skip_internal_checks
):
revert_message += "\n:warning: This PR might contain internal changes"
revert_message += "\ncc: @pytorch/pytorch-dev-infra"
gh_post_pr_comment(
pr.org, pr.project, pr.pr_num, revert_message, dry_run=dry_run
)
if not dry_run:
pr.add_numbered_label("reverted")
gh_post_commit_comment(pr.org, pr.project, commit_sha, revert_msg)
gh_update_pr_state(pr.org, pr.project, pr.pr_num)
def try_revert(
repo: GitRepo,
pr: GitHubPR,
@ -1896,37 +1777,34 @@ def try_revert(
comment_id: Optional[int] = None,
reason: Optional[str] = None,
) -> None:
def post_comment(msg: str) -> None:
gh_post_pr_comment(pr.org, pr.project, pr.pr_num, msg, dry_run=dry_run)
try:
author_login, commit_sha = validate_revert(repo, pr, comment_id=comment_id)
except PostCommentError as e:
gh_post_pr_comment(pr.org, pr.project, pr.pr_num, str(e), dry_run=dry_run)
return
extra_msg = f" due to {reason}" if reason is not None else ""
extra_msg += (
return post_comment(str(e))
revert_msg = f"\nReverted {pr.get_pr_url()} on behalf of {prefix_with_github_url(author_login)}"
revert_msg += f" due to {reason}" if reason is not None else ""
revert_msg += (
f" ([comment]({pr.get_comment_by_id(comment_id).url}))\n"
if comment_id is not None
else "\n"
)
shas_and_prs = [(commit_sha, pr)]
if pr.is_ghstack_pr():
try:
shas_and_prs = get_ghstack_dependent_prs(repo, pr)
prs_to_revert = " ".join([t[1].get_pr_url() for t in shas_and_prs])
print(f"About to stack of PRs: {prs_to_revert}")
except Exception as e:
print(
f"Failed to fetch dependent PRs: {str(e)}, fall over to single revert"
)
do_revert_prs(
repo,
shas_and_prs,
author_login=author_login,
extra_msg=extra_msg,
dry_run=dry_run,
skip_internal_checks=can_skip_internal_checks(pr, comment_id),
repo.checkout(pr.default_branch())
repo.revert(commit_sha)
msg = repo.commit_message("HEAD")
msg = re.sub(RE_PULL_REQUEST_RESOLVED, "", msg)
msg += revert_msg
repo.amend_commit_message(msg)
repo.push(pr.default_branch(), dry_run)
post_comment(
f"@{pr.get_pr_creator_login()} your PR has been successfully reverted."
)
if not dry_run:
pr.add_numbered_label("reverted")
gh_post_commit_comment(pr.org, pr.project, commit_sha, revert_msg)
gh_update_pr_state(pr.org, pr.project, pr.pr_num)
def prefix_with_github_url(suffix_str: str) -> str:

View File

@ -8,7 +8,7 @@
# NOTE: If testing pytorch/builder changes you can change this variable to change what pytorch/builder reference
# the binary builds will check out
{%- set builder_repo = "pytorch/builder" -%}
{%- set builder_branch = "main" -%}
{%- set builder_branch = "release/2.2" -%}
{%- macro concurrency(build_environment) -%}
concurrency:
@ -36,7 +36,7 @@ concurrency:
{%- macro setup_ec2_windows() -%}
!{{ display_ec2_information() }}
- name: "[FB EMPLOYEES] Enable SSH (Click me for login details)"
uses: pytorch/test-infra/.github/actions/setup-ssh@main
uses: pytorch/test-infra/.github/actions/setup-ssh@release/2.2
continue-on-error: true
with:
github-secret: ${{ secrets.GITHUB_TOKEN }}

View File

@ -7,6 +7,7 @@
name: !{{ build_environment }}
{%- endblock %}
on:
push:
{%- if branches == "nightly" %}
@ -99,13 +100,13 @@ jobs:
with:
name: !{{ config["build_name"] }}
path: "${{ runner.temp }}/artifacts/"
!{{ common.checkout(deep_clone=False, directory="pytorch") }}
!{{ common.checkout(deep_clone=False, directory="builder", repository=common.builder_repo, branch=common.builder_branch) }}
!{{ common.checkout(deep_clone=False, directory="pytorch", checkout_pr_head=False) }}
!{{ common.checkout(deep_clone=False, directory="builder", repository=common.builder_repo, branch=common.builder_branch, checkout_pr_head=False) }}
- name: ROCm set GPU_FLAG
run: |
echo "GPU_FLAG=--device=/dev/mem --device=/dev/kfd --device=/dev/dri --group-add video --group-add daemon" >> "${GITHUB_ENV}"
- name: Pull Docker image
uses: pytorch/test-infra/.github/actions/pull-docker-image@main
uses: pytorch/test-infra/.github/actions/pull-docker-image@release/2.2
with:
docker-image: !{{ config["container_image"] }}
- name: Test Pytorch binary

View File

@ -81,8 +81,8 @@ jobs:
elif [ -d "/Applications/Xcode_13.3.1.app" ]; then
echo "DEVELOPER_DIR=/Applications/Xcode_13.3.1.app/Contents/Developer" >> "${GITHUB_ENV}"
fi
!{{ common.checkout(deep_clone=False, directory="pytorch") }}
!{{ common.checkout(deep_clone=False, directory="builder", repository=common.builder_repo, branch=common.builder_branch) }}
!{{ common.checkout(deep_clone=False, directory="pytorch", checkout_pr_head=False) }}
!{{ common.checkout(deep_clone=False, directory="builder", repository=common.builder_repo, branch=common.builder_branch, checkout_pr_head=False) }}
- name: Install sccache (only for non-forked PRs, and pushes to trunk)
uses: nick-fields/retry@v2.8.2
if: ${{ github.event_name == 'push' || github.event.pull_request.head.repo.full_name == github.repository }}

View File

@ -53,6 +53,9 @@
{%- macro upload_binaries(config, is_windows=False, has_test=True, use_s3=True) -%}
!{{ config["build_name"] }}-upload: # Uploading
if: ${{ github.repository_owner == 'pytorch' }}
permissions:
id-token: write
contents: read
{%- if has_test %}
needs: !{{ config["build_name"] }}-test
{%- else %}
@ -65,8 +68,6 @@
{%- endif %}
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
aws-pytorch-uploader-access-key-id: ${{ secrets.AWS_PYTORCH_UPLOADER_ACCESS_KEY_ID }}
aws-pytorch-uploader-secret-access-key: ${{ secrets.AWS_PYTORCH_UPLOADER_SECRET_ACCESS_KEY }}
conda-pytorchbot-token: ${{ secrets.CONDA_PYTORCHBOT_TOKEN }}
conda-pytorchbot-token-test: ${{ secrets.CONDA_PYTORCHBOT_TOKEN_TEST }}
uses: ./.github/workflows/_binary-upload.yml

View File

@ -65,8 +65,8 @@ jobs:
steps:
!{{ common.setup_ec2_windows() }}
!{{ set_runner_specific_vars() }}
!{{ common.checkout(deep_clone=False, directory="pytorch") }}
!{{ common.checkout(deep_clone=False, directory="builder", repository=common.builder_repo, branch=common.builder_branch) }}
!{{ common.checkout(deep_clone=False, directory="pytorch", checkout_pr_head=False) }}
!{{ common.checkout(deep_clone=False, directory="builder", repository=common.builder_repo, branch=common.builder_branch, checkout_pr_head=False) }}
- name: Populate binary env
shell: bash
run: |
@ -105,8 +105,8 @@ jobs:
with:
name: !{{ config["build_name"] }}
path: "${{ env.PYTORCH_FINAL_PACKAGE_DIR }}"
!{{ common.checkout(deep_clone=False, directory="pytorch") }}
!{{ common.checkout(deep_clone=False, directory="builder", repository=common.builder_repo, branch=common.builder_branch) }}
!{{ common.checkout(deep_clone=False, directory="pytorch", checkout_pr_head=False) }}
!{{ common.checkout(deep_clone=False, directory="builder", repository=common.builder_repo, branch=common.builder_branch, checkout_pr_head=False) }}
- name: Populate binary env
shell: bash
run: |

View File

@ -29,7 +29,6 @@ env:
jobs:
filter:
if: github.repository_owner == 'pytorch'
runs-on: [self-hosted, linux.large]
outputs:
test-matrix: ${{ steps.filter.outputs.test-matrix }}
@ -37,7 +36,7 @@ jobs:
keep-going: ${{ steps.filter.outputs.keep-going }}
steps:
- name: Checkout PyTorch
uses: pytorch/pytorch/.github/actions/checkout-pytorch@main
uses: pytorch/pytorch/.github/actions/checkout-pytorch@release/2.2
with:
fetch-depth: 1
submodules: false
@ -59,25 +58,25 @@ jobs:
runs-on: ${{ matrix.runner }}
steps:
- name: Setup SSH (Click me for login details)
uses: pytorch/test-infra/.github/actions/setup-ssh@main
uses: pytorch/test-infra/.github/actions/setup-ssh@release/2.2
with:
github-secret: ${{ secrets.GITHUB_TOKEN }}
# [see note: pytorch repo ref]
- name: Checkout PyTorch
uses: pytorch/pytorch/.github/actions/checkout-pytorch@main
uses: pytorch/pytorch/.github/actions/checkout-pytorch@release/2.2
- name: Setup Linux
uses: ./.github/actions/setup-linux
- name: Calculate docker image
id: calculate-docker-image
uses: pytorch/test-infra/.github/actions/calculate-docker-image@main
uses: pytorch/test-infra/.github/actions/calculate-docker-image@release/2.2
with:
docker-image-name: ${{ inputs.docker-image-name }}
- name: Pull docker image
uses: pytorch/test-infra/.github/actions/pull-docker-image@main
uses: pytorch/test-infra/.github/actions/pull-docker-image@release/2.2
with:
docker-image: ${{ steps.calculate-docker-image.outputs.docker-image }}
@ -141,5 +140,5 @@ jobs:
if: always()
- name: Teardown Linux
uses: pytorch/test-infra/.github/actions/teardown-linux@main
uses: pytorch/test-infra/.github/actions/teardown-linux@release/2.2
if: always()

View File

@ -29,7 +29,6 @@ env:
jobs:
filter:
if: github.repository_owner == 'pytorch'
runs-on: [self-hosted, linux.large]
outputs:
test-matrix: ${{ steps.filter.outputs.test-matrix }}
@ -37,7 +36,7 @@ jobs:
keep-going: ${{ steps.filter.outputs.keep-going }}
steps:
- name: Checkout PyTorch
uses: pytorch/pytorch/.github/actions/checkout-pytorch@main
uses: pytorch/pytorch/.github/actions/checkout-pytorch@release/2.2
with:
fetch-depth: 1
submodules: false
@ -59,25 +58,25 @@ jobs:
runs-on: ${{ matrix.runner }}
steps:
- name: Setup SSH (Click me for login details)
uses: pytorch/test-infra/.github/actions/setup-ssh@main
uses: pytorch/test-infra/.github/actions/setup-ssh@release/2.2
with:
github-secret: ${{ secrets.GITHUB_TOKEN }}
# [see note: pytorch repo ref]
- name: Checkout PyTorch
uses: pytorch/pytorch/.github/actions/checkout-pytorch@main
uses: pytorch/pytorch/.github/actions/checkout-pytorch@release/2.2
- name: Setup Linux
uses: ./.github/actions/setup-linux
- name: Calculate docker image
id: calculate-docker-image
uses: pytorch/test-infra/.github/actions/calculate-docker-image@main
uses: pytorch/test-infra/.github/actions/calculate-docker-image@release/2.2
with:
docker-image-name: ${{ inputs.docker-image-name }}
- name: Pull docker image
uses: pytorch/test-infra/.github/actions/pull-docker-image@main
uses: pytorch/test-infra/.github/actions/pull-docker-image@release/2.2
with:
docker-image: ${{ steps.calculate-docker-image.outputs.docker-image }}
@ -186,5 +185,5 @@ jobs:
if: always()
- name: Teardown Linux
uses: pytorch/test-infra/.github/actions/teardown-linux@main
uses: pytorch/test-infra/.github/actions/teardown-linux@release/2.2
if: always()

View File

@ -33,7 +33,6 @@ env:
jobs:
filter:
if: github.repository_owner == 'pytorch'
runs-on: [self-hosted, linux.large]
outputs:
test-matrix: ${{ steps.filter.outputs.test-matrix }}
@ -42,7 +41,7 @@ jobs:
reenabled-issues: ${{ steps.filter.outputs.reenabled-issues }}
steps:
- name: Checkout PyTorch
uses: pytorch/pytorch/.github/actions/checkout-pytorch@main
uses: pytorch/pytorch/.github/actions/checkout-pytorch@release/2.2
with:
fetch-depth: 1
submodules: false
@ -64,30 +63,30 @@ jobs:
runs-on: ${{ matrix.runner }}
steps:
- name: Setup SSH (Click me for login details)
uses: pytorch/test-infra/.github/actions/setup-ssh@main
uses: pytorch/test-infra/.github/actions/setup-ssh@release/2.2
with:
github-secret: ${{ secrets.GITHUB_TOKEN }}
# [see note: pytorch repo ref]
- name: Checkout PyTorch
uses: pytorch/pytorch/.github/actions/checkout-pytorch@main
uses: pytorch/pytorch/.github/actions/checkout-pytorch@release/2.2
- name: Setup Linux
uses: ./.github/actions/setup-linux
- name: Calculate docker image
id: calculate-docker-image
uses: pytorch/test-infra/.github/actions/calculate-docker-image@main
uses: pytorch/test-infra/.github/actions/calculate-docker-image@release/2.2
with:
docker-image-name: ${{ inputs.docker-image-name }}
- name: Pull docker image
uses: pytorch/test-infra/.github/actions/pull-docker-image@main
uses: pytorch/test-infra/.github/actions/pull-docker-image@release/2.2
with:
docker-image: ${{ steps.calculate-docker-image.outputs.docker-image }}
- name: Install nvidia driver, nvidia-docker runtime, set GPU_FLAG
uses: pytorch/test-infra/.github/actions/setup-nvidia@main
uses: pytorch/test-infra/.github/actions/setup-nvidia@release/2.2
if: ${{ inputs.cuda-version != 'cpu' }}
- name: Output disk space left
@ -122,6 +121,8 @@ jobs:
GITHUB_RUN_NUMBER: ${{ github.run_number }}
GITHUB_RUN_ATTEMPT: ${{ github.run_attempt }}
JOB_ID: ${{ steps.get-job-id.outputs.job-id }}
PYTORCH_RETRY_TEST_CASES: 1
PYTORCH_OVERRIDE_FLAKY_SIGNAL: 1
REENABLED_ISSUES: ${{ needs.filter.outputs.reenabled-issues }}
# TODO duplicated
AWS_DEFAULT_REGION: us-east-1
@ -158,6 +159,8 @@ jobs:
-e TORCH_CUDA_ARCH_LIST \
-e OUR_GITHUB_JOB_ID \
-e CUDA_VERSION \
-e PYTORCH_RETRY_TEST_CASES \
-e PYTORCH_OVERRIDE_FLAKY_SIGNAL \
--env-file="/tmp/github_env_${GITHUB_RUN_ID}" \
--security-opt seccomp=unconfined \
--cap-add=SYS_PTRACE \
@ -196,5 +199,5 @@ jobs:
file-suffix: bazel-${{ github.job }}_${{ steps.get-job-id.outputs.job-id }}
- name: Teardown Linux
uses: pytorch/test-infra/.github/actions/teardown-linux@main
uses: pytorch/test-infra/.github/actions/teardown-linux@release/2.2
if: always()

View File

@ -139,13 +139,13 @@ jobs:
run: env
- name: "[FB EMPLOYEES] Enable SSH (Click me for login details)"
uses: pytorch/test-infra/.github/actions/setup-ssh@main
uses: pytorch/test-infra/.github/actions/setup-ssh@release/2.2
continue-on-error: true
with:
github-secret: ${{ secrets.github-token }}
- name: Checkout PyTorch
uses: pytorch/pytorch/.github/actions/checkout-pytorch@main
uses: pytorch/pytorch/.github/actions/checkout-pytorch@release/2.2
with:
no-sudo: ${{ inputs.build_environment == 'linux-aarch64-binary-manywheel' }}
@ -173,7 +173,6 @@ jobs:
- name: Checkout PyTorch to pytorch dir
uses: malfet/checkout@silent-checkout
with:
ref: ${{ github.event_name == 'pull_request' && github.event.pull_request.head.sha || github.sha }}
submodules: recursive
path: pytorch
quiet-checkout: true
@ -187,7 +186,7 @@ jobs:
- name: Checkout pytorch/builder to builder dir
uses: malfet/checkout@silent-checkout
with:
ref: main
ref: release/2.2
submodules: recursive
repository: pytorch/builder
path: builder
@ -213,7 +212,7 @@ jobs:
- name: Pull Docker image
if: ${{ steps.filter.outputs.is-test-matrix-empty == 'False' }}
uses: pytorch/test-infra/.github/actions/pull-docker-image@main
uses: pytorch/test-infra/.github/actions/pull-docker-image@release/2.2
with:
docker-image: ${{ inputs.DOCKER_IMAGE }}
@ -270,7 +269,7 @@ jobs:
- name: Teardown Linux
if: always()
uses: pytorch/test-infra/.github/actions/teardown-linux@main
uses: pytorch/test-infra/.github/actions/teardown-linux@release/2.2
- name: Chown workspace
if: always()

View File

@ -127,14 +127,14 @@ jobs:
} >> "${GITHUB_ENV} }}"
- name: "[FB EMPLOYEES] Enable SSH (Click me for login details)"
uses: pytorch/test-infra/.github/actions/setup-ssh@main
uses: pytorch/test-infra/.github/actions/setup-ssh@release/2.2
continue-on-error: true
with:
github-secret: ${{ secrets.github-token }}
# Setup the environment
- name: Checkout PyTorch
uses: pytorch/pytorch/.github/actions/checkout-pytorch@main
uses: pytorch/pytorch/.github/actions/checkout-pytorch@release/2.2
with:
no-sudo: ${{ inputs.build_environment == 'linux-aarch64-binary-manywheel' }}
@ -155,7 +155,6 @@ jobs:
- name: Checkout PyTorch to pytorch dir
uses: malfet/checkout@silent-checkout
with:
ref: ${{ github.event_name == 'pull_request' && github.event.pull_request.head.sha || github.sha }}
submodules: recursive
path: pytorch
@ -168,7 +167,7 @@ jobs:
- name: Checkout pytorch/builder to builder dir
uses: malfet/checkout@silent-checkout
with:
ref: main
ref: release/2.2
submodules: recursive
repository: pytorch/builder
path: builder
@ -199,12 +198,12 @@ jobs:
path: "${{ runner.temp }}/artifacts/"
- name: Install nvidia driver, nvidia-docker runtime, set GPU_FLAG
uses: pytorch/test-infra/.github/actions/setup-nvidia@main
uses: pytorch/test-infra/.github/actions/setup-nvidia@release/2.2
if: ${{ inputs.GPU_ARCH_TYPE == 'cuda' && steps.filter.outputs.is-test-matrix-empty == 'False' }}
- name: Pull Docker image
if: ${{ steps.filter.outputs.is-test-matrix-empty == 'False' }}
uses: pytorch/test-infra/.github/actions/pull-docker-image@main
uses: pytorch/test-infra/.github/actions/pull-docker-image@release/2.2
with:
docker-image: ${{ inputs.DOCKER_IMAGE }}
@ -214,7 +213,7 @@ jobs:
- name: Teardown Linux
if: always()
uses: pytorch/test-infra/.github/actions/teardown-linux@main
uses: pytorch/test-infra/.github/actions/teardown-linux@release/2.2
- name: Chown workspace
if: always()

View File

@ -59,18 +59,13 @@ on:
github-token:
required: true
description: Github Token
aws-pytorch-uploader-access-key-id:
required: true
description: AWS access key id
aws-pytorch-uploader-secret-access-key:
required: true
description: AWS secret access key
conda-pytorchbot-token:
required: true
description: Conda PyTorchBot token
conda-pytorchbot-token-test:
required: true
description: Conda PyTorchBot token
jobs:
upload:
runs-on: ubuntu-22.04
@ -100,10 +95,24 @@ jobs:
SHA1: ${{ github.event.pull_request.head.sha || github.sha }}
steps:
- name: Checkout PyTorch
uses: pytorch/pytorch/.github/actions/checkout-pytorch@main
uses: pytorch/pytorch/.github/actions/checkout-pytorch@release/2.2
with:
no-sudo: true
- name: Configure AWS credentials(PyTorch account) for nightly
if: ${{ github.event_name == 'push' && github.event.ref == 'refs/heads/nightly' }}
uses: aws-actions/configure-aws-credentials@v3
with:
role-to-assume: arn:aws:iam::749337293305:role/gha_workflow_nightly_build_wheels
aws-region: us-east-1
- name: Configure AWS credentials(PyTorch account) for RC builds
if: ${{ github.event_name == 'push' && (startsWith(github.event.ref, 'refs/tags/') && !startsWith(github.event.ref, 'refs/tags/ciflow/')) }}
uses: aws-actions/configure-aws-credentials@v3
with:
role-to-assume: arn:aws:iam::749337293305:role/gha_workflow_test_build_wheels
aws-region: us-east-1
- name: Download Build Artifacts
id: download-artifacts
# NB: When the previous build job is skipped, there won't be any artifacts and
@ -135,8 +144,6 @@ jobs:
PKG_DIR: "${{ runner.temp }}/artifacts"
UPLOAD_SUBFOLDER: "${{ env.DESIRED_CUDA }}"
# When running these on pull_request events these should be blank
AWS_ACCESS_KEY_ID: ${{ secrets.aws-pytorch-uploader-access-key-id }}
AWS_SECRET_ACCESS_KEY: ${{ secrets.aws-pytorch-uploader-secret-access-key }}
CONDA_PYTORCHBOT_TOKEN: ${{ secrets.conda-pytorchbot-token }}
CONDA_PYTORCHBOT_TOKEN_TEST: ${{ secrets.conda-pytorchbot-token-test }}
BUILD_NAME: ${{ inputs.build_name }}

View File

@ -15,7 +15,6 @@ defaults:
jobs:
filter:
if: github.repository_owner == 'pytorch'
runs-on: [self-hosted, linux.large]
outputs:
test-matrix: ${{ steps.filter.outputs.test-matrix }}
@ -23,7 +22,7 @@ jobs:
keep-going: ${{ steps.filter.outputs.keep-going }}
steps:
- name: Checkout PyTorch
uses: pytorch/pytorch/.github/actions/checkout-pytorch@main
uses: pytorch/pytorch/.github/actions/checkout-pytorch@release/2.2
with:
fetch-depth: 1
submodules: false
@ -44,7 +43,7 @@ jobs:
runs-on: ${{ matrix.runner }}
steps:
- name: Checkout PyTorch
uses: pytorch/pytorch/.github/actions/checkout-pytorch@main
uses: pytorch/pytorch/.github/actions/checkout-pytorch@release/2.2
- name: Set up JDK 8
uses: actions/setup-java@v3
@ -53,7 +52,7 @@ jobs:
distribution: 'temurin'
- name: Setup miniconda
uses: pytorch/test-infra/.github/actions/setup-miniconda@main
uses: pytorch/test-infra/.github/actions/setup-miniconda@release/2.2
with:
python-version: 3.8
environment-file: .github/requirements/conda-env-${{ runner.os }}-${{ runner.arch }}

View File

@ -66,7 +66,7 @@ jobs:
name: build-docs-${{ matrix.docs_type }}-${{ inputs.push }}
steps:
- name: Setup SSH (Click me for login details)
uses: pytorch/test-infra/.github/actions/setup-ssh@main
uses: pytorch/test-infra/.github/actions/setup-ssh@release/2.2
with:
github-secret: ${{ secrets.GITHUB_TOKEN }}
instructions: |
@ -77,19 +77,19 @@ jobs:
# [see note: pytorch repo ref]
- name: Checkout PyTorch
uses: pytorch/pytorch/.github/actions/checkout-pytorch@main
uses: pytorch/pytorch/.github/actions/checkout-pytorch@release/2.2
- name: Setup Linux
uses: ./.github/actions/setup-linux
- name: Calculate docker image
id: calculate-docker-image
uses: pytorch/test-infra/.github/actions/calculate-docker-image@main
uses: pytorch/test-infra/.github/actions/calculate-docker-image@release/2.2
with:
docker-image-name: ${{ inputs.docker-image }}
- name: Pull docker image
uses: pytorch/test-infra/.github/actions/pull-docker-image@main
uses: pytorch/test-infra/.github/actions/pull-docker-image@release/2.2
with:
docker-image: ${{ steps.calculate-docker-image.outputs.docker-image }}
@ -187,5 +187,5 @@ jobs:
s3-prefix: pytorch/pytorch/${{ github.event.pull_request.number }}/functorchdocs
- name: Teardown Linux
uses: pytorch/test-infra/.github/actions/teardown-linux@main
uses: pytorch/test-infra/.github/actions/teardown-linux@release/2.2
if: always()

View File

@ -38,7 +38,6 @@ env:
jobs:
filter:
if: github.repository_owner == 'pytorch'
runs-on: [self-hosted, linux.large]
outputs:
test-matrix: ${{ steps.filter.outputs.test-matrix }}
@ -46,7 +45,7 @@ jobs:
keep-going: ${{ steps.filter.outputs.keep-going }}
steps:
- name: Checkout PyTorch
uses: pytorch/pytorch/.github/actions/checkout-pytorch@main
uses: pytorch/pytorch/.github/actions/checkout-pytorch@release/2.2
with:
fetch-depth: 1
submodules: false
@ -80,7 +79,7 @@ jobs:
steps:
# [see note: pytorch repo ref]
- name: Checkout PyTorch
uses: pytorch/pytorch/.github/actions/checkout-pytorch@main
uses: pytorch/pytorch/.github/actions/checkout-pytorch@release/2.2
- name: Populate CI build options
shell: bash
@ -102,7 +101,7 @@ jobs:
brew install libtool
- name: Setup miniconda for iOS
uses: pytorch/test-infra/.github/actions/setup-miniconda@main
uses: pytorch/test-infra/.github/actions/setup-miniconda@release/2.2
with:
python-version: "3.9"
environment-file: .github/requirements/conda-env-iOS.txt

View File

@ -73,7 +73,7 @@ jobs:
test-matrix: ${{ steps.filter.outputs.test-matrix }}
steps:
- name: Setup SSH (Click me for login details)
uses: pytorch/test-infra/.github/actions/setup-ssh@main
uses: pytorch/test-infra/.github/actions/setup-ssh@release/2.2
with:
github-secret: ${{ secrets.GITHUB_TOKEN }}
@ -82,14 +82,14 @@ jobs:
# checkout because when we run this action we don't *have* a local
# checkout. In other cases you should prefer a local checkout.
- name: Checkout PyTorch
uses: pytorch/pytorch/.github/actions/checkout-pytorch@main
uses: pytorch/pytorch/.github/actions/checkout-pytorch@release/2.2
- name: Setup Linux
uses: ./.github/actions/setup-linux
- name: Calculate docker image
id: calculate-docker-image
uses: pytorch/test-infra/.github/actions/calculate-docker-image@main
uses: pytorch/test-infra/.github/actions/calculate-docker-image@release/2.2
with:
docker-image-name: ${{ inputs.docker-image-name }}
@ -103,7 +103,7 @@ jobs:
echo "docker pull ghcr.io/pytorch/ci-image:${tag/:/-}"
- name: Pull docker image
uses: pytorch/test-infra/.github/actions/pull-docker-image@main
uses: pytorch/test-infra/.github/actions/pull-docker-image@release/2.2
with:
docker-image: ${{ steps.calculate-docker-image.outputs.docker-image }}
@ -209,5 +209,5 @@ jobs:
path: sccache-stats-*.json
- name: Teardown Linux
uses: pytorch/test-infra/.github/actions/teardown-linux@main
uses: pytorch/test-infra/.github/actions/teardown-linux@release/2.2
if: always()

View File

@ -57,7 +57,7 @@ jobs:
timeout-minutes: ${{ matrix.mem_leak_check == 'mem_leak_check' && 600 || inputs.timeout-minutes }}
steps:
- name: Setup SSH (Click me for login details)
uses: pytorch/test-infra/.github/actions/setup-ssh@main
uses: pytorch/test-infra/.github/actions/setup-ssh@release/2.2
if: ${{ !contains(matrix.runner, 'gcp.a100') }}
with:
github-secret: ${{ secrets.GITHUB_TOKEN }}
@ -66,14 +66,14 @@ jobs:
docker exec -it $(docker container ps --format '{{.ID}}') bash
- name: Checkout PyTorch
uses: pytorch/pytorch/.github/actions/checkout-pytorch@main
uses: pytorch/pytorch/.github/actions/checkout-pytorch@release/2.2
- name: Setup Linux
uses: ./.github/actions/setup-linux
- name: Calculate docker image
id: calculate-docker-image
uses: pytorch/test-infra/.github/actions/calculate-docker-image@main
uses: pytorch/test-infra/.github/actions/calculate-docker-image@release/2.2
with:
docker-image-name: ${{ inputs.docker-image }}
@ -87,13 +87,13 @@ jobs:
echo "docker pull ghcr.io/pytorch/ci-image:${tag/:/-}"
- name: Pull docker image
uses: pytorch/test-infra/.github/actions/pull-docker-image@main
uses: pytorch/test-infra/.github/actions/pull-docker-image@release/2.2
with:
docker-image: ${{ steps.calculate-docker-image.outputs.docker-image }}
- name: Install nvidia driver, nvidia-docker runtime, set GPU_FLAG
id: install-nvidia-driver
uses: pytorch/test-infra/.github/actions/setup-nvidia@main
uses: pytorch/test-infra/.github/actions/setup-nvidia@release/2.2
if: contains(inputs.build-environment, 'cuda') && !contains(matrix.config, 'nogpu')
- name: Lock NVIDIA A100 40GB Frequency
@ -164,6 +164,8 @@ jobs:
BRANCH: ${{ steps.parse-ref.outputs.branch }}
SHA1: ${{ github.event.pull_request.head.sha || github.sha }}
BASE_SHA: ${{ github.event.pull_request.base.sha || github.sha }}
PYTORCH_RETRY_TEST_CASES: 1
PYTORCH_OVERRIDE_FLAKY_SIGNAL: 1
TEST_CONFIG: ${{ matrix.config }}
SHARD_NUMBER: ${{ matrix.shard }}
NUM_TEST_SHARDS: ${{ matrix.num_shards }}
@ -207,7 +209,6 @@ jobs:
-e GITHUB_RUN_NUMBER \
-e GITHUB_RUN_ATTEMPT \
-e JOB_ID \
-e JOB_NAME \
-e BASE_SHA \
-e BRANCH \
-e SHA1 \
@ -218,6 +219,8 @@ jobs:
-e NUM_TEST_SHARDS \
-e REENABLED_ISSUES \
-e CONTINUE_THROUGH_ERROR \
-e PYTORCH_RETRY_TEST_CASES \
-e PYTORCH_OVERRIDE_FLAKY_SIGNAL \
-e PR_LABELS \
-e MAX_JOBS="$(nproc --ignore=2)" \
-e SCCACHE_BUCKET \
@ -297,7 +300,7 @@ jobs:
path: ./**/core.[1-9]*
- name: Teardown Linux
uses: pytorch/test-infra/.github/actions/teardown-linux@main
uses: pytorch/test-infra/.github/actions/teardown-linux@release/2.2
if: always()
# NB: We are currently having an intermittent GPU-related issue on G5 runners with

View File

@ -71,11 +71,11 @@ jobs:
test-matrix: ${{ steps.filter.outputs.test-matrix }}
steps:
- name: Clean up disk space before running MacOS workflow
uses: pytorch/test-infra/.github/actions/check-disk-space@main
uses: pytorch/test-infra/.github/actions/check-disk-space@release/2.2
# [see note: pytorch repo ref]
- name: Checkout PyTorch
uses: pytorch/pytorch/.github/actions/checkout-pytorch@main
uses: pytorch/pytorch/.github/actions/checkout-pytorch@release/2.2
- name: Set xcode version
env:
@ -87,7 +87,7 @@ jobs:
- name: Setup miniconda
if: inputs.environment-file == ''
uses: pytorch/test-infra/.github/actions/setup-miniconda@main
uses: pytorch/test-infra/.github/actions/setup-miniconda@release/2.2
with:
python-version: ${{ inputs.python-version }}
environment-file: .github/requirements/conda-env-${{ runner.os }}-${{ runner.arch }}
@ -97,7 +97,7 @@ jobs:
# environment even though the arch is x86-64
- name: Setup miniconda using the provided environment file
if: inputs.environment-file != ''
uses: pytorch/test-infra/.github/actions/setup-miniconda@main
uses: pytorch/test-infra/.github/actions/setup-miniconda@release/2.2
with:
python-version: ${{ inputs.python-version }}
environment-file: ${{ inputs.environment-file }}
@ -207,4 +207,4 @@ jobs:
- name: Clean up disk space
if: always()
continue-on-error: true
uses: pytorch/test-infra/.github/actions/check-disk-space@main
uses: pytorch/test-infra/.github/actions/check-disk-space@release/2.2

View File

@ -28,7 +28,6 @@ on:
jobs:
filter:
if: github.repository_owner == 'pytorch'
runs-on: [self-hosted, linux.large]
outputs:
test-matrix: ${{ steps.filter.outputs.test-matrix }}
@ -37,7 +36,7 @@ jobs:
reenabled-issues: ${{ steps.filter.outputs.reenabled-issues }}
steps:
- name: Checkout PyTorch
uses: pytorch/pytorch/.github/actions/checkout-pytorch@main
uses: pytorch/pytorch/.github/actions/checkout-pytorch@release/2.2
with:
fetch-depth: 1
submodules: false
@ -59,6 +58,7 @@ jobs:
runs-on: ${{ matrix.runner }}
steps:
- name: Print runner OS/HW info
shell: arch -arch arm64 bash {0}
run: |
sysctl machdep.cpu.brand_string kern.osproductversion
@ -69,6 +69,7 @@ jobs:
quiet-checkout: true
- name: Clean checkout
shell: arch -arch arm64 bash {0}
run: |
git clean -fxd
@ -79,7 +80,7 @@ jobs:
use-gha: true
- name: Setup miniconda
uses: pytorch/test-infra/.github/actions/setup-miniconda@main
uses: pytorch/test-infra/.github/actions/setup-miniconda@release/2.2
with:
python-version: ${{ inputs.python-version }}
environment-file: .github/requirements/conda-env-${{ runner.os }}-${{ runner.arch }}
@ -94,9 +95,12 @@ jobs:
ENV_NAME: conda-test-env-${{ github.run_id }}
PY_VERS: 3.9
PR_BODY: ${{ github.event.pull_request.body }}
PYTORCH_RETRY_TEST_CASES: 1
PYTORCH_OVERRIDE_FLAKY_SIGNAL: 1
CONTINUE_THROUGH_ERROR: ${{ needs.filter.outputs.keep-going }}
PIP_REQUIREMENTS_FILE: .github/requirements/pip-requirements-${{ runner.os }}.txt
REENABLED_ISSUES: ${{ needs.filter.outputs.reenabled-issues }}
shell: arch -arch arm64 bash {0}
run: |
# shellcheck disable=SC1090
set -ex
@ -154,4 +158,4 @@ jobs:
- name: Clean up disk space
if: always()
continue-on-error: true
uses: pytorch/test-infra/.github/actions/check-disk-space@main
uses: pytorch/test-infra/.github/actions/check-disk-space@release/2.2

View File

@ -57,11 +57,9 @@ jobs:
SHARD_NUMBER: ${{ matrix.shard }}
NUM_TEST_SHARDS: ${{ matrix.num_shards }}
PR_BODY: ${{ github.event.pull_request.body }}
PYTORCH_RETRY_TEST_CASES: 1
PYTORCH_OVERRIDE_FLAKY_SIGNAL: 1
steps:
- name: Print runner OS/HW info
run: |
sysctl machdep.cpu.brand_string kern.osproductversion
- name: Clean up leftover processes on MacOS pet runner
continue-on-error: true
run: |
@ -78,12 +76,14 @@ jobs:
rm -rf "${dir}"
done
- name: Clean up disk space before running MacOS workflow
uses: pytorch/test-infra/.github/actions/check-disk-space@main
uses: pytorch/test-infra/.github/actions/check-disk-space@release/2.2
# [see note: pytorch repo ref]
- name: Checkout PyTorch
uses: pytorch/pytorch/.github/actions/checkout-pytorch@main
uses: pytorch/pytorch/.github/actions/checkout-pytorch@release/2.2
- name: Download build artifacts
uses: ./.github/actions/download-build-artifacts
@ -92,7 +92,7 @@ jobs:
use-gha: true
- name: Setup miniconda
uses: pytorch/test-infra/.github/actions/setup-miniconda@main
uses: pytorch/test-infra/.github/actions/setup-miniconda@release/2.2
with:
python-version: ${{ inputs.python-version }}
environment-file: .github/requirements/conda-env-${{ runner.os }}-${{ runner.arch }}
@ -218,4 +218,4 @@ jobs:
- name: Clean up disk space
if: always()
continue-on-error: true
uses: pytorch/test-infra/.github/actions/check-disk-space@main
uses: pytorch/test-infra/.github/actions/check-disk-space@release/2.2

View File

@ -42,6 +42,10 @@ on:
env:
GIT_DEFAULT_BRANCH: ${{ github.event.repository.default_branch }}
permissions:
id-token: write
contents: read
jobs:
test:
# Don't run on forked repos or empty test matrix
@ -54,21 +58,32 @@ jobs:
steps:
# [see note: pytorch repo ref]
- name: Checkout PyTorch
uses: pytorch/pytorch/.github/actions/checkout-pytorch@main
uses: pytorch/pytorch/.github/actions/checkout-pytorch@release/2.2
with:
no-sudo: true
- name: Setup ROCm
uses: ./.github/actions/setup-rocm
- name: configure aws credentials
id: aws_creds
uses: aws-actions/configure-aws-credentials@v4
with:
role-to-assume: arn:aws:iam::308535385114:role/gha_workflow_s3_and_ecr_read_only
aws-region: us-east-1
- name: Login to Amazon ECR
id: login-ecr
uses: aws-actions/amazon-ecr-login@v2
- name: Calculate docker image
id: calculate-docker-image
uses: pytorch/test-infra/.github/actions/calculate-docker-image@main
uses: pytorch/test-infra/.github/actions/calculate-docker-image@release/2.2
with:
docker-image-name: ${{ inputs.docker-image }}
- name: Pull docker image
uses: pytorch/test-infra/.github/actions/pull-docker-image@main
uses: pytorch/test-infra/.github/actions/pull-docker-image@release/2.2
with:
docker-image: ${{ steps.calculate-docker-image.outputs.docker-image }}
@ -131,6 +146,8 @@ jobs:
JOB_NAME: ${{ steps.get-job-id.outputs.job-name }}
BRANCH: ${{ steps.parse-ref.outputs.branch }}
SHA1: ${{ github.event.pull_request.head.sha || github.sha }}
PYTORCH_RETRY_TEST_CASES: 1
PYTORCH_OVERRIDE_FLAKY_SIGNAL: 1
CONTINUE_THROUGH_ERROR: ${{ steps.keep-going.outputs.keep-going }}
TEST_CONFIG: ${{ matrix.config }}
SHARD_NUMBER: ${{ matrix.shard }}
@ -170,7 +187,6 @@ jobs:
-e GITHUB_RUN_NUMBER \
-e GITHUB_RUN_ATTEMPT \
-e JOB_ID \
-e JOB_NAME \
-e BRANCH \
-e SHA1 \
-e AWS_DEFAULT_REGION \
@ -179,6 +195,8 @@ jobs:
-e TEST_CONFIG \
-e NUM_TEST_SHARDS \
-e REENABLED_ISSUES \
-e PYTORCH_RETRY_TEST_CASES \
-e PYTORCH_OVERRIDE_FLAKY_SIGNAL \
-e CONTINUE_THROUGH_ERROR \
-e MAX_JOBS="$(nproc --ignore=2)" \
-e SCCACHE_BUCKET \

View File

@ -15,7 +15,6 @@ defaults:
jobs:
filter:
if: github.repository_owner == 'pytorch'
runs-on: [self-hosted, linux.large]
outputs:
test-matrix: ${{ steps.filter.outputs.test-matrix }}
@ -23,7 +22,7 @@ jobs:
keep-going: ${{ steps.filter.outputs.keep-going }}
steps:
- name: Checkout PyTorch
uses: pytorch/pytorch/.github/actions/checkout-pytorch@main
uses: pytorch/pytorch/.github/actions/checkout-pytorch@release/2.2
with:
fetch-depth: 1
submodules: false
@ -54,10 +53,10 @@ jobs:
SUPPORT_ABI: '${{ matrix.support_abi }}'
steps:
- name: Checkout PyTorch
uses: pytorch/pytorch/.github/actions/checkout-pytorch@main
uses: pytorch/pytorch/.github/actions/checkout-pytorch@release/2.2
- name: Setup miniconda
uses: pytorch/test-infra/.github/actions/setup-miniconda@main
uses: pytorch/test-infra/.github/actions/setup-miniconda@release/2.2
with:
python-version: 3.8
environment-file: .github/requirements/conda-env-${{ runner.os }}-${{ runner.arch }}.txt

View File

@ -60,10 +60,10 @@ jobs:
git config --global core.fsmonitor false
- name: Clean up leftover processes on non-ephemeral Windows runner
uses: pytorch/test-infra/.github/actions/cleanup-runner@main
uses: pytorch/test-infra/.github/actions/cleanup-runner@release/2.2
- name: Setup SSH (Click me for login details)
uses: pytorch/test-infra/.github/actions/setup-ssh@main
uses: pytorch/test-infra/.github/actions/setup-ssh@release/2.2
with:
github-secret: ${{ secrets.GITHUB_TOKEN }}
instructions: |
@ -78,7 +78,7 @@ jobs:
# [see note: pytorch repo ref]
- name: Checkout PyTorch
uses: pytorch/pytorch/.github/actions/checkout-pytorch@main
uses: pytorch/pytorch/.github/actions/checkout-pytorch@release/2.2
with:
no-sudo: true

View File

@ -54,10 +54,10 @@ jobs:
git config --global core.fsmonitor false
- name: Clean up leftover processes on non-ephemeral Windows runner
uses: pytorch/test-infra/.github/actions/cleanup-runner@main
uses: pytorch/test-infra/.github/actions/cleanup-runner@release/2.2
- name: Setup SSH (Click me for login details)
uses: pytorch/test-infra/.github/actions/setup-ssh@main
uses: pytorch/test-infra/.github/actions/setup-ssh@release/2.2
with:
github-secret: ${{ secrets.GITHUB_TOKEN }}
instructions: |
@ -73,7 +73,7 @@ jobs:
# [see note: pytorch repo ref]
- name: Checkout PyTorch
uses: pytorch/pytorch/.github/actions/checkout-pytorch@main
uses: pytorch/pytorch/.github/actions/checkout-pytorch@release/2.2
with:
no-sudo: true
@ -139,6 +139,8 @@ jobs:
USE_CUDA: ${{ inputs.cuda-version != 'cpu' && '1' || '0' }}
INSTALL_WINDOWS_SDK: 1
PYTHON_VERSION: 3.8
PYTORCH_RETRY_TEST_CASES: 1
PYTORCH_OVERRIDE_FLAKY_SIGNAL: 1
CONTINUE_THROUGH_ERROR: ${{ steps.keep-going.outputs.keep-going }}
VC_PRODUCT: "BuildTools"
VC_VERSION: ""

View File

@ -1,269 +0,0 @@
# TODO: this looks sort of similar to _linux-test, but there are like a dozen
# places where you would have to insert an if statement. Probably it's better to
# just use a different workflow altogether
name: xpu-test
on:
workflow_call:
inputs:
build-environment:
required: true
type: string
description: Top-level label for what's being built/tested.
test-matrix:
required: true
type: string
description: JSON description of what test configs to run.
docker-image:
required: true
type: string
description: Docker image to run in.
sync-tag:
required: false
type: string
default: ""
description: |
If this is set, our linter will use this to make sure that every other
job with the same `sync-tag` is identical.
timeout-minutes:
required: false
type: number
default: 300
description: |
Set the maximum (in minutes) how long the workflow should take to finish
tests-to-include:
required: false
type: string
default: ""
description: |
List of tests to include (empty string implies default list)
env:
GIT_DEFAULT_BRANCH: ${{ github.event.repository.default_branch }}
permissions:
id-token: write
contents: read
jobs:
test:
# Don't run on forked repos or empty test matrix
if: github.repository_owner == 'pytorch' && toJSON(fromJSON(inputs.test-matrix).include) != '[]'
strategy:
matrix: ${{ fromJSON(inputs.test-matrix) }}
fail-fast: false
timeout-minutes: ${{ matrix.mem_leak_check == 'mem_leak_check' && 600 || inputs.timeout-minutes }}
runs-on: ${{ matrix.runner }}
steps:
# [see note: pytorch repo ref]
- name: Checkout PyTorch
uses: pytorch/pytorch/.github/actions/checkout-pytorch@main
- name: Setup XPU
uses: ./.github/actions/setup-xpu
- name: configure aws credentials
id: aws_creds
uses: aws-actions/configure-aws-credentials@v1.7.0
with:
role-to-assume: arn:aws:iam::308535385114:role/gha_workflow_pytorch_artifacts
aws-region: us-east-1
- name: Login to Amazon ECR
id: login-ecr
uses: aws-actions/amazon-ecr-login@v2
- name: Calculate docker image
id: calculate-docker-image
uses: pytorch/test-infra/.github/actions/calculate-docker-image@main
with:
docker-image-name: ${{ inputs.docker-image }}
- name: Pull docker image
uses: pytorch/test-infra/.github/actions/pull-docker-image@main
with:
docker-image: ${{ steps.calculate-docker-image.outputs.docker-image }}
- name: Start monitoring script
id: monitor-script
shell: bash
continue-on-error: true
run: |
python3 -m pip install psutil==5.9.1 nvidia-ml-py==11.525.84
python3 -m tools.stats.monitor > usage_log.txt 2>&1 &
echo "monitor-script-pid=${!}" >> "${GITHUB_OUTPUT}"
- name: Download build artifacts
uses: ./.github/actions/download-build-artifacts
with:
name: ${{ inputs.build-environment }}
- name: Parse ref
id: parse-ref
run: .github/scripts/parse_ref.py
- name: Get workflow job id
id: get-job-id
uses: ./.github/actions/get-workflow-job-id
if: always()
with:
github-token: ${{ secrets.GITHUB_TOKEN }}
- name: Check for keep-going label and re-enabled test issues
# This uses the filter-test-configs action because it conviniently
# checks for labels and re-enabled test issues. It does not actually do
# any filtering. All filtering is done in the build step.
id: keep-going
uses: ./.github/actions/filter-test-configs
with:
github-token: ${{ secrets.GITHUB_TOKEN }}
test-matrix: ${{ inputs.test-matrix }}
job-name: ${{ steps.get-job-id.outputs.job-name }}
- name: Set Test step time
id: test-timeout
shell: bash
env:
JOB_TIMEOUT: ${{ matrix.mem_leak_check == 'mem_leak_check' && 600 || inputs.timeout-minutes }}
run: |
echo "timeout=$((JOB_TIMEOUT-30))" >> "${GITHUB_OUTPUT}"
- name: Test
id: test
env:
BUILD_ENVIRONMENT: ${{ inputs.build-environment }}
PR_NUMBER: ${{ github.event.pull_request.number }}
GITHUB_REPOSITORY: ${{ github.repository }}
GITHUB_WORKFLOW: ${{ github.workflow }}
GITHUB_JOB: ${{ github.job }}
GITHUB_RUN_ID: ${{ github.run_id }}
GITHUB_RUN_NUMBER: ${{ github.run_number }}
GITHUB_RUN_ATTEMPT: ${{ github.run_attempt }}
JOB_ID: ${{ steps.get-job-id.outputs.job-id }}
JOB_NAME: ${{ steps.get-job-id.outputs.job-name }}
BRANCH: ${{ steps.parse-ref.outputs.branch }}
SHA1: ${{ github.event.pull_request.head.sha || github.sha }}
PYTORCH_RETRY_TEST_CASES: 1
PYTORCH_OVERRIDE_FLAKY_SIGNAL: 1
CONTINUE_THROUGH_ERROR: ${{ steps.keep-going.outputs.keep-going }}
TEST_CONFIG: ${{ matrix.config }}
SHARD_NUMBER: ${{ matrix.shard }}
NUM_TEST_SHARDS: ${{ matrix.num_shards }}
REENABLED_ISSUES: ${{ steps.keep-going.outputs.reenabled-issues }}
SCCACHE_BUCKET: ossci-compiler-cache-circleci-v2
DOCKER_IMAGE: ${{ inputs.docker-image }}
XLA_CLANG_CACHE_S3_BUCKET_NAME: ossci-compiler-clang-cache-circleci-xla
PYTORCH_TEST_CUDA_MEM_LEAK_CHECK: ${{ matrix.mem_leak_check && '1' || '0' }}
PYTORCH_TEST_RERUN_DISABLED_TESTS: ${{ matrix.rerun_disabled_tests && '1' || '0' }}
TESTS_TO_INCLUDE: ${{ inputs.tests-to-include }}
timeout-minutes: ${{ fromJson(steps.test-timeout.outputs.timeout) }}
run: |
set -x
TEST_COMMAND=.ci/pytorch/test.sh
# detached container should get cleaned up by teardown_ec2_linux
# Used for GPU_FLAG since that doesn't play nice
# shellcheck disable=SC2086,SC2090
container_name=$(docker run \
${GPU_FLAG:-} \
-e BUILD_ENVIRONMENT \
-e PR_NUMBER \
-e GITHUB_ACTIONS \
-e GITHUB_REPOSITORY \
-e GITHUB_WORKFLOW \
-e GITHUB_JOB \
-e GITHUB_RUN_ID \
-e GITHUB_RUN_NUMBER \
-e GITHUB_RUN_ATTEMPT \
-e JOB_ID \
-e BRANCH \
-e SHA1 \
-e AWS_DEFAULT_REGION \
-e IN_WHEEL_TEST \
-e SHARD_NUMBER \
-e TEST_CONFIG \
-e NUM_TEST_SHARDS \
-e REENABLED_ISSUES \
-e PYTORCH_RETRY_TEST_CASES \
-e PYTORCH_OVERRIDE_FLAKY_SIGNAL \
-e CONTINUE_THROUGH_ERROR \
-e MAX_JOBS="$(nproc --ignore=2)" \
-e SCCACHE_BUCKET \
-e XLA_CLANG_CACHE_S3_BUCKET_NAME \
-e PYTORCH_TEST_CUDA_MEM_LEAK_CHECK \
-e PYTORCH_TEST_RERUN_DISABLED_TESTS \
-e TESTS_TO_INCLUDE \
-e ZE_AFFINITY_MASK \
--env-file="/tmp/github_env_${GITHUB_RUN_ID}" \
--ulimit stack=10485760:83886080 \
--ulimit core=0 \
--security-opt seccomp=unconfined \
--cap-add=SYS_PTRACE \
--shm-size="8g" \
--tty \
--detach \
--name="${container_name}" \
--user jenkins \
--privileged \
-v "${GITHUB_WORKSPACE}:/var/lib/jenkins/workspace" \
-w /var/lib/jenkins/workspace \
"${DOCKER_IMAGE}"
)
# save container name for later step
echo "CONTAINER_NAME=${container_name}" >> "$GITHUB_ENV"
# jenkins user does not have write permission to mounted workspace; work-around by copying within container to jenkins home
docker exec -t "${container_name}" sh -c "cd .. && cp -R workspace pytorch && cd pytorch && pip install dist/*.whl && ${TEST_COMMAND}"
- name: Save test results
if: always()
run: |
# copy test results back to the mounted workspace, needed sudo, resulting permissions were correct
docker exec -t "${{ env.CONTAINER_NAME }}" sh -c "cd ../pytorch && sudo cp -R test/test-reports ../workspace/test"
- name: Print remaining test logs
shell: bash
if: always() && steps.test.conclusion
run: |
cat test/**/*_toprint.log || true
- name: Stop monitoring script
if: always() && steps.monitor-script.outputs.monitor-script-pid
shell: bash
continue-on-error: true
env:
MONITOR_SCRIPT_PID: ${{ steps.monitor-script.outputs.monitor-script-pid }}
run: |
kill "$MONITOR_SCRIPT_PID"
- name: Upload test artifacts
uses: ./.github/actions/upload-test-artifacts
if: always() && steps.test.conclusion && steps.test.conclusion != 'skipped'
with:
use-gha: true
file-suffix: ${{ github.job }}-${{ matrix.config }}-${{ matrix.shard }}-${{ matrix.num_shards }}-${{ matrix.runner }}_${{ steps.get-job-id.outputs.job-id }}
- name: Collect backtraces from coredumps (if any)
if: always()
run: |
# shellcheck disable=SC2156
find . -iname "core.[1-9]*" -exec docker exec "${CONTAINER_NAME}" sh -c "gdb python {} -ex 'bt' -ex 'q'" \;
- name: Stop container before exit
if: always()
run: |
# Workaround for multiple runners on same IDC node
docker stop "${{ env.CONTAINER_NAME }}"
- name: Store Core dumps on GitHub
uses: actions/upload-artifact@v3
if: failure()
with:
name: coredumps-${{ matrix.config }}-${{ matrix.shard }}-${{ matrix.num_shards }}-${{ matrix.runner }}
retention-days: 14
if-no-files-found: ignore
path: ./**/core.[1-9]*
- name: Teardown XPU
uses: ./.github/actions/teardown-xpu

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