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42 Commits

Author SHA1 Message Date
bc2c6edaf1 Re-enable Windows debug libtorch (#73900) 2022-03-08 10:46:44 -05:00
46f85865c0 Also install c10d headers with .h extension (#73422) (#73497)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/73422

Fixes https://github.com/pytorch/pytorch/issues/73421
ghstack-source-id: 149978120

Test Plan: None

Reviewed By: cbalioglu

Differential Revision: D34475711

fbshipit-source-id: 9e4d1d57021cbff51f53762b32bbfffbf3f81c4c
2022-03-01 10:37:30 -05:00
a556333dfa scatter_reduce documentation (#73125) (#73365)
Summary:
Reland of https://github.com/pytorch/pytorch/issues/68580 (which were milestoned for 1.11) plus partial revert of https://github.com/pytorch/pytorch/pull/72543

Pull Request resolved: https://github.com/pytorch/pytorch/pull/73125

Reviewed By: bdhirsh

Differential Revision: D34355217

Pulled By: malfet

fbshipit-source-id: 325ecdeaf53183d653b44ee5e6e8839ceefd9200
(cherry picked from commit 71db31748a8adcd8f95d5faf04aaa454e9c4c760)
(cherry picked from commit cfb6c942fed64dbb81ccc4f14b2a6650123af2e1)
2022-02-24 11:37:42 -08:00
3c14fe2151 Introduce an environment variable to change c10 log level (#71746) (#73357)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/71746

This PR contains the following improvements:

- It exposes a new environment variable `TORCH_CPP_LOG_LEVEL` that enables users to set the log level of c10 logging facility (supports both GLOG and c10 loggers). Valid values are `INFO`, `WARNING`, `ERROR`, and `FATAL` or their numerical equivalents `0`, `1`, `2`, and `3`.
- It implements an `initLogging()` function and calls it as part of `torch._C` module import to ensure that the underlying logging facility is correctly initialized in Python.

With these changes a user can dynamically set the log level of c10 as in the following example:

```
$ TORCH_CPP_LOG_LEVEL=INFO python my_torch_script.py
```
ghstack-source-id: 149822703

Test Plan: Run existing tests.

Reviewed By: malfet

Differential Revision: D33756252

fbshipit-source-id: 7fd078c03a598595d992de0b474a23cec91838af
(cherry picked from commit 01d6ec6207faedf259ed1368730e9e197cb3e1c6)
2022-02-24 10:46:15 -08:00
055052bf64 Improvements to C10d log (#73358)
* Prefix c10d log messages with `[c10d]` for easier troubleshooting (#73144)

Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/73144

This PR formats c10d log messages written by the `C10D_INFO/WARN/ERROR` macros by prefixing them with the `[c10d]` tag for easier troubleshooting. See #73121 for a specific customer request.

Note though that this is a temporary fix to unblock our users. Ideally our global logging facility should natively support component-based preambles.
ghstack-source-id: 149748943

Test Plan: N/A

Reviewed By: rohan-varma

Differential Revision: D34363975

fbshipit-source-id: 6b8096ac4b2fa344406c866a2e7665541cb60b34
(cherry picked from commit af14aef18d0239f04730545596a05536e0f9c857)

* Refactor TORCH_DISTRIBUTED_DEBUG implementation (#73166)

Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/73166

This PR refactors, cleans up, and optimizes the implementation of `TORCH_DISTRIBUTED_DEBUG`. It also introduces three new user APIs: `get_debug_level()`, `set_debug_level()`, and `set_debug_level_from_env()` to retrieve and modify the debug level after a process has started.
ghstack-source-id: 149778566

Test Plan: Run the existing unit tests.

Reviewed By: rohan-varma

Differential Revision: D34371226

fbshipit-source-id: e18443b411adcbaf39b2ec999178c198052fcd5b
(cherry picked from commit 26d6bb1584b83a0490d8b766482656a5887fa21d)

* Introduce debug and trace log levels in c10d (#73167)

Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/73167

This PR adds `C10D_DEBUG` and `C10D_TRACE` macros to enable fine grained logging in c10d. It also updates some log statements of `socket` to make its output less noisy.
ghstack-source-id: 149778567

Test Plan: Manual testing with different socket conditions.

Reviewed By: rohan-varma

Differential Revision: D34371426

fbshipit-source-id: a852b05ec353b18b0540ce5f803666c3da21ddd7
(cherry picked from commit 4519b06ac57f177dfc086bc10e8e1a746ba0870d)

* Make "server socket not listening" warning logs less noisy (#73149)

Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/73149

This PR improves the handling of the "server socket not yet listening" warning log in c10d `socket`. Instead of outputting it after every failed attempt (meaning every second), it is now written every 20 seconds. Note though that if the log level is set to `INFO`, we keep writing a detailed message every second as before with additional `errno` information.

With log level set to `WARN` the output looks like:
```
[W socket.cpp:598] [c10d] No socket on (127.0.0.1, 29501) is listening yet, will retry.
[W socket.cpp:598] [c10d] No socket on (127.0.0.1, 29501) is listening yet, will retry.
...
[E socket.cpp:726] [c10d] The client socket has timed out after 300s while trying to connect to (127.0.0.1, 29501).
```

With log level set to `INFO` (a.k.a. verbose or debug level) the output looks like:
```
[I socket.cpp:515] [c10d] The client socket will attempt to connect to an IPv6 address of (127.0.0.1, 29501).
[I socket.cpp:582] [c10d] The client socket is attempting to connect to [localhost]:29501.
[I socket.cpp:643] [c10d] The server socket on [localhost]:29501 is not yet listening (errno: 111 - Connection refused), will retry.
[W socket.cpp:598] [c10d] No socket on (127.0.0.1, 29501) is listening yet, will retry.
[I socket.cpp:582] [c10d] The client socket is attempting to connect to [localhost]:29501.
[I socket.cpp:643] [c10d] The server socket on [localhost]:29501 is not yet listening (errno: 111 - Connection refused), will retry.
[I socket.cpp:582] [c10d] The client socket is attempting to connect to [localhost]:29501.
[I socket.cpp:643] [c10d] The server socket on [localhost]:29501 is not yet listening (errno: 111 - Connection refused), will retry.
[I socket.cpp:582] [c10d] The client socket is attempting to connect to [localhost]:29501.
[I socket.cpp:643] [c10d] The server socket on [localhost]:29501 is not yet listening (errno: 111 - Connection refused), will retry.
...
[W socket.cpp:598] [c10d] No socket on (127.0.0.1, 29501) is listening yet, will retry.
...
[E socket.cpp:726] [c10d] The client socket has timed out after 300s while trying to connect to (127.0.0.1, 29501).
```
ghstack-source-id: 149778565

Test Plan: Run manual tests to verify the correctness of the log message.

Reviewed By: rohan-varma

Differential Revision: D34365217

fbshipit-source-id: 296d01fa8b1ba803432903c10686d8a75145e539
(cherry picked from commit 8ae5aff0c5ffcc3e87d27d2deba6fedf8cef45cd)

* Rename `_get_debug_mode` to `get_debug_level` in distributed.py
2022-02-24 10:37:41 -08:00
68ef2a2188 Documenting cuda 11.5 windows issue (#73013) (#73312)
Summary:
Adding documentation about compiling extension with CUDA 11.5 and Windows

Example of failure: https://github.com/pytorch/pytorch/runs/4408796098?check_suite_focus=true

 Note: Don't use torch/extension.h In CUDA 11.5 under windows in your C++ code:
    Use aten instead of torch interface in all cuda 11.5 code under windows. It has been failing with errors, due to a bug in nvcc.
    Example use:
        >>> #include <ATen/ATen.h>
        >>> at::Tensor SigmoidAlphaBlendForwardCuda(....)
    Instead of:
        >>> #include <torch/extension.h>
        >>> torch::Tensor SigmoidAlphaBlendForwardCuda(...)
    Currently open issue for nvcc bug: https://github.com/pytorch/pytorch/issues/69460
    Complete Workaround code example: cb170ac024

Pull Request resolved: https://github.com/pytorch/pytorch/pull/73013

Reviewed By: malfet, seemethere

Differential Revision: D34306134

Pulled By: atalman

fbshipit-source-id: 3c5b9d7a89c91bd1920dc63dbd356e45dc48a8bd
(cherry picked from commit 87098e7f17fca1b98c90fafe2dde1defb6633f49)
2022-02-24 10:34:39 -08:00
9647fb7d18 Use "large" macos for binary builds
Hopefully it will fix the timeout

Pull Request resolved: https://github.com/pytorch/pytorch/pull/73089

(cherry picked from commit 99427654aa86d052420f18b03ee9aa9abcf7e6d0)
2022-02-24 09:55:15 -08:00
e4944871c8 stop sccache server after building (#72794) (#73122)
Summary:
This is to avoid the directory , where the sccache is installed, couldn't be deleted.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/72794

Reviewed By: H-Huang

Differential Revision: D34222877

Pulled By: janeyx99

fbshipit-source-id: 2765d6f49b375d15598586ed83ae4c5e667e7226
(cherry picked from commit 551e21ca582c80d88a466b7bfe4eda9dee0c9a5f)

Co-authored-by: Yi Zhang <zhanyi@microsoft.com>
2022-02-21 11:08:08 -08:00
bbf2c0e3c6 Disable test history as it's fragile
Related to #73083

Pull Request resolved: https://github.com/pytorch/pytorch/pull/73093

(cherry picked from commit 08510ba5e4ae0b53b67f0fbbc9f53b35aec9902c)
2022-02-18 15:01:40 -08:00
e6e8877bc2 avoiding adding some functions to the public python API before 1.11 release (#72543) (#72913)
cherry-picked for 1.11 release

(cherry picked from commit 6676a0c79a3b2bc1aa95e09e91eb92a6eca6b764)
2022-02-18 14:49:13 -08:00
eaa80c6fd8 [DataPipe] Adding usage examples for IterDataPipes (#73036)
Adding usage examples for IterDataPipes, with additional improvements for description of `groupby`, `IterDataPipe`, `MapDataPipe`.

Differential Revision: [D34313793](https://our.internmc.facebook.com/intern/diff/D34313793)
2022-02-18 14:38:05 -08:00
7fa092949e [NNC] TensorExprKernel state should not be modified on calls to run methods (#73029)
A typical use case for `TensorExprKernel` is to create the kernel once and call it multiple times, possibly in parallel. For the parallel calls to work, we need to ensure that the run() method calls do not change any state in `TensorExprKernel`.

Before this change, the `run()` method was modifying the sizes and strides vectors when dynamic shapes were present. This manifested as a data race when running a model with Static Runtime.
ghstack-source-id: 149398820

Differential Revision: [D34287960](https://our.internmc.facebook.com/intern/diff/D34287960/)

Co-authored-by: Raghavan Raman <raghavanr@fb.com>
2022-02-18 14:31:59 -08:00
74cd18623e Fix doc regressions for various modules and functional forms (#73014) (#73049)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/73014

Fixes #72501
Fixes #72502
Fixes #72503
Fixes #72504
Fixes #72505
Fixes #72506
Fixes #72507
Fixes #72509
Fixes #72510

Test Plan: Imported from OSS

Reviewed By: albanD

Differential Revision: D34305640

Pulled By: jbschlosser

fbshipit-source-id: 62f341633fdb0316eaa346cf7247865290eb830a
(cherry picked from commit 8362d264e7b2c0c2bd5d688a87bf4f8f0bf60f0f)

Co-authored-by: Joel Schlosser <jbschlosser@fb.com>
2022-02-18 08:23:21 -08:00
dad4c2d032 Fix sequence_ops_test (#72844) (#73017) 2022-02-17 11:31:27 -08:00
565742cb63 [CircleCI] Re-enable nightly android builds (#73027)
A stop-gap measure to re-enable publishing of Android maven packages by
CI, see https://github.com/pytorch/pytorch/issues/72902

Pull Request resolved: https://github.com/pytorch/pytorch/pull/72903

(cherry picked from commit 3493646f7636046c603921ef9a8b5c3fc635f39f)
Signed-off-by: Eli Uriegas <eliuriegas@fb.com>

Co-authored-by: Nikita Shulga <nshulga@fb.com>
2022-02-17 14:27:55 -05:00
7acb591cf9 Add docstrings to native_channel_shuffle (#72954)
ghstack-source-id: 9288da6390b5e5702c250788a2644ec6ad32df3c
Pull Request resolved: https://github.com/pytorch/pytorch/pull/72919
2022-02-17 08:07:08 -05:00
a5d5a6ad4f Set BLAS_LIBRARIES to ${MKL_LIBRARIES} for MKL case (#72806) (#72959)
This reverts [suggestion](https://github.com/pytorch/pytorch/pull/49647#discussion_r677737470) proposed to https://github.com/pytorch/pytorch/pull/49647

Which is somehow sufficient to workaround symptoms of https://github.com/pytorch/pytorch/issue/72653 

I.e. before this change, `BLAS_LIBRARIES` were set to `caffe2::mkl`
which is an interface library with link property set as follows:
59dd84cab6/cmake/public/mkl.cmake (L10-L12)
2022-02-17 07:54:33 -05:00
ea5089751f [JIT] API Changes for dynamic fusion (#72937)
* Move dyn fusion api to jit/api/module/

ghstack-source-id: 5597012c7381629ed478c10925b1b08eed1a32bf
Pull Request resolved: https://github.com/pytorch/pytorch/pull/72638

* Make fusion strategy api public

ghstack-source-id: b2ede61e046297f9f6132c3afd23e88b33d5b4eb
Pull Request resolved: https://github.com/pytorch/pytorch/pull/72639

Co-authored-by: Elias Ellison <eellison@devfair044.h1.fair>
2022-02-16 15:12:09 -08:00
d216c83667 [release/1.11] Create a CI workflow for XLA tests using the XLA test image (#72938)
* Create a CI workflow for XLA tests using the XLA test image (#72496)

Summary:
This PR resolves https://github.com/pytorch/pytorch/issues/72693

Pull Request resolved: https://github.com/pytorch/pytorch/pull/72496

Reviewed By: H-Huang

Differential Revision: D34255441

Pulled By: seemethere

fbshipit-source-id: fdfd54fbd59ef7266a78c9f729c1d5b6ed25e9d6
(cherry picked from commit ba14f0ee6cfa2fe248784d2dc5d54e427aef6bf7)

* Update .github/workflows/generated-pytorch-xla-linux-bionic-py3.7-clang8.yml

Fixes lint

Co-authored-by: Nikita Shulga <nikita.shulga@gmail.com>
2022-02-16 15:10:16 -08:00
f7e0ca546c add optional encoding argument to fileopener so users can open files in non-default encodings. (#72800)
Co-authored-by: Elijah Rippeth <elijah.rippeth@gmail.com>
Co-authored-by: Nikita Shulga <nshulga@fb.com>
2022-02-16 13:17:11 -08:00
89ee69e173 Rename Typed/UntypedStorage to _Typed/_UntypedStorage (#72540) (#72914)
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/72540

Reviewed By: jbschlosser

Differential Revision: D34216823

Pulled By: bdhirsh

fbshipit-source-id: 1bc9930ab582771ebf02308e035576cd1a0dbe47
(cherry picked from commit 329238f612a9d92586bb0e5b33bcc45a0ec6936b)

Co-authored-by: Kurt Mohler <kmohler@quansight.com>
2022-02-16 12:24:21 -08:00
e0aad8e864 [quant][core][docs] Add docs for torch.quantize_per_tensor_dynamic (#72311) (#72929)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/72311

att

Test Plan:
doc page in github

Imported from OSS

Reviewed By: bdhirsh

Differential Revision: D33996034

fbshipit-source-id: 797f7a55176e9219586d16142ca351c5c9cbe828
2022-02-16 12:22:12 -08:00
28ad47f553 [ONNX] Fix lstm reshape shape inference regression (#72734)
Fixes #72399
Pull Request resolved: https://github.com/pytorch/pytorch/pull/72532

Co-authored-by: BowenBao <bowbao@microsoft.com>
2022-02-15 11:04:47 -08:00
2cc3c2ef38 [1.11][DataPipe] Docs Improvement (#72801)
* [DataPipe] Fixing MapDataPipe docstrings

[ghstack-poisoned]

* [DataPipe] Fixing IterDataPipe docstrings

[ghstack-poisoned]

* [DataPipe] Add docstrings for IterDataPipe and MapDataPipe, along with small doc changes for consistency

[ghstack-poisoned]
2022-02-15 08:24:38 -05:00
b0037f707f pad_sequence: fix regression - support tensor (#72436) (#72697)
Summary:
Fixes https://github.com/pytorch/pytorch/issues/71365

Based on https://github.com/pytorch/pytorch/pull/72343

Thanks jbschlosser

Pull Request resolved: https://github.com/pytorch/pytorch/pull/72436

Reviewed By: bdhirsh

Differential Revision: D34117724

Pulled By: jbschlosser

fbshipit-source-id: e5d6599d0791025e18ab36ae16c417a91554bf64
(cherry picked from commit ffe8a0e41b7906920e392a9588347215ac44f46f)

Co-authored-by: kshitij12345 <kshitijkalambarkar@gmail.com>
2022-02-14 08:44:45 -05:00
b6a3176c1c Cat shape analysis fix for -1 dim (#72678)
ghstack-source-id: b4e1e8b74889653d70b6111de71797c2e10f347d
Pull Request resolved: https://github.com/pytorch/pytorch/pull/72616

Co-authored-by: Elias Ellison <eellison@devfair044.h1.fair>
2022-02-14 08:42:51 -05:00
5fac320809 Fix refcounting in access of saved for forward attribute (#72627) (#72656)
Summary:
fix https://github.com/pytorch/pytorch/issues/72612

Pull Request resolved: https://github.com/pytorch/pytorch/pull/72627

Reviewed By: soulitzer

Differential Revision: D34119834

Pulled By: albanD

fbshipit-source-id: 893a1e88a738eb40072af2106527340aea1d0006
(cherry picked from commit 511a1f16c5e37f4946907bc89b246eb684b89428)

Co-authored-by: albanD <desmaison.alban@gmail.com>
2022-02-14 08:38:16 -05:00
1f406fe91d Pin builder repo for GHA builds to release/1.11 (#72739)
* Builder repo is not pinned in release branch

* Updated workflows
2022-02-11 15:29:26 -05:00
6a46b2e2aa Fix for builder repo not pinned in release branch (#72719) (#72732)
Summary:
Fixes https://github.com/pytorch/pytorch/issues/72655

Please note: Readme.md file change will be done after this change is performed and release specific change is done, so that I will reference the commit of the release specific change in the readme as an example

Pull Request resolved: https://github.com/pytorch/pytorch/pull/72719

Reviewed By: seemethere

Differential Revision: D34177045

Pulled By: atalman

fbshipit-source-id: 2abb7af8cf1337704933c19c0d06022034ec77b4
(cherry picked from commit 31ff276d5e2cacc0e0592d624f3d486d5e8cfd1c)
2022-02-11 11:41:24 -08:00
503a0923d3 Fix tagged build detection for binary builds (#72628) (#72652)
Summary:
Should fix the following [error](https://github.com/pytorch/pytorch/runs/5058514346#step:13:88):
```
+ git --git-dir /pytorch/pytorch/.git describe --tags --match 'v[0-9]*.[0-9]*.[0-9]*' --exact
fatal: not a git repository: '/pytorch/pytorch/.git'
```
By setting `workdir` correctly for GHA linux and Windows builds

Also, abort `tagged_version` if GIT_DIR does not exist (as this script should only be executed in context of git folder.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/72628

Reviewed By: atalman

Differential Revision: D34120721

Pulled By: malfet

fbshipit-source-id: 035e93e243e601f9c24659cd247f9c029210fba5
(cherry picked from commit 3a6c97b6ddb185d706494f64423a761fee8fce09)
(cherry picked from commit b6df02bbbb5b786b198938ffb5d90fa5251df3eb)
2022-02-10 07:17:32 -08:00
6641e9b75f Fix SVD error code handling for OpenBLAS 0.3.15+ and MKL 2022+ (again) (#72357) (#72513)
Summary:
This PR was opened as copy of https://github.com/pytorch/pytorch/pull/68812 by request https://github.com/pytorch/pytorch/pull/68812#issuecomment-1030215862.

-----

Fixes https://github.com/pytorch/pytorch/issues/67693.

Reference LAPACK (used in OpenBLAS) changed info error code for svd when inputs contain non-finite numbers. In PyTorch, we raise an internal assert error for negative `info` error codes because usually, it would indicate the wrong implementation. However, this is not the case with SVD now in newer versions of LAPACK. MKL (tried 2021.4.0) still gives a positive error code for this kind of input. This change aligns with the OpenBLAS and MKL behavior in our code.

MKL 2022 has uses the latest reference LAPACK behavior and returns the same `info` as OpenBLAS 0.3.15+
This PR also fixes https://github.com/pytorch/pytorch/issues/71645 that is due to the updated MKL version in CI.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/72357

Reviewed By: albanD

Differential Revision: D34012245

Pulled By: ngimel

fbshipit-source-id: 2b66c173cc3458d8c766b542d0d569191cdce310
(cherry picked from commit fa29e65611ea5028bf6d2d3c151d79e6c9e4ffef)
2022-02-09 18:58:00 -05:00
4f9f0e7a13 Fix doc build for release branches (#72567) (#72635)
Summary:
Add "v[0-9]+.[0-9]+.[0-9]+-rc[0-9]+" wildcard to tag triggers
Add similar `startsWith(github.event.ref, 'refs/tags/v1.')` for push
conditions

Fixes https://github.com/pytorch/pytorch/issues/72519

Pull Request resolved: https://github.com/pytorch/pytorch/pull/72567

Reviewed By: atalman

Differential Revision: D34116048

Pulled By: malfet

fbshipit-source-id: 7ef6ae3972ff7eba213ae9c4eb4afea5a7e11827
(cherry picked from commit 3785553532ccf636e389c97713f2c5bbfec836ba)
2022-02-09 15:55:24 -08:00
0ea924fc98 Disable complex32 (#72604) 2022-02-09 15:51:37 -08:00
5a78725c29 Add missing entry for sampled_addmm in sparse.rst (#72312) (#72514)
Summary:
Let's make the documentation for `torch.sparse.sampled_addmm` searchable in the PyTorch documentation.
This PR shall be cherry-picked for the next 1.11 release.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/72312

Reviewed By: davidberard98

Differential Revision: D34045230

Pulled By: cpuhrsch

fbshipit-source-id: c1b1dc907443284857f48c8ce1efab22c6701bbe
(cherry picked from commit 225929ecf20eb369f862b091818f5af16ee78f88)
2022-02-08 10:25:15 -08:00
f72151b900 [ONNX] Resolve attribute error in CI (#72350) (#72439)
Summary:
Tests under `test/onnx/test_models_onnxruntime.py` complains `AttributeError: 'TestModels' object has no attribute 'onnx_shape_inference'`.

This failure in CI appears suddenly without any code changes to related files. It is likely due to different test case run order. The test code was badly written such that test class `TestModels_new_jit_API`, if called first, will assign `TestModels.onnx_shape_inference = True`, circumventing this problem. On the other hand, if `TestModels` is called first, `AttributeError` will be raised.

Fixes https://github.com/pytorch/pytorch/issues/72337

Pull Request resolved: https://github.com/pytorch/pytorch/pull/72350

Reviewed By: jbschlosser, seemethere, janeyx99

Differential Revision: D34010794

Pulled By: malfet

fbshipit-source-id: 816f7bee89ea0251bb5df8f482b68f8dc4823997
(cherry picked from commit b39b23bec5dfd3f2fd24a0d781757c20ff94b1db)

Co-authored-by: BowenBao <bowbao@microsoft.com>
2022-02-07 12:35:32 -08:00
8380187819 Pin librosa (#72440)
Should mitigate https://github.com/pytorch/pytorch/issues/72432
Pull Request resolved: https://github.com/pytorch/pytorch/pull/72433

Co-authored-by: Jane Xu <janeyx@fb.com>
2022-02-07 10:06:57 -08:00
7cc129e60c Remove forcing CUDNN_STATIC when CAFFE2_STATIC_LINK_CUDA (#72290) (#72356)
Summary:
Remove forcing CUDNN_STATIC when CAFFE2_STATIC_LINK_CUDA is set
Since we are transitioning to using dynamic loading for multiple pytorch dependecies  and CUDNN is the first step in this transition,  hence we want to remove forcing CUDNN to statically load, and instead load it dynamically.

Tested using following workflow:
https://github.com/pytorch/pytorch/actions/runs/1790666862

Pull Request resolved: https://github.com/pytorch/pytorch/pull/72290

Reviewed By: albanD

Differential Revision: D34003793

Pulled By: atalman

fbshipit-source-id: 41bda7ac019a612ee53ceb18d1e372b1bb3cb68e
(cherry picked from commit 4a01940e681f996017d924b08946188ef352ef41)

Co-authored-by: Andrey Talman <atalman@fb.com>
2022-02-04 14:56:08 -05:00
ff6c348762 Revert "Bump torch version to 1.12 (#72221)"
This reverts commit 0ca0e02685a9d033ac4f04e2fa5c8ba6dbc5ae50.
2022-02-04 11:38:35 -08:00
03a283b2b1 Fix persistent worker exits before pin_memory thread (#72269)
* release 1.11 Install torch from test channel, Pin builder and xla repo (#72217)

* Fix persistent worker exits before pin_memory thread

ghstack-source-id: 2d15b14df2e2d84b309081dffbedc4836495ae95
Pull Request resolved: https://github.com/pytorch/pytorch/pull/71579

Co-authored-by: Andrey Talman <atalman@fb.com>
2022-02-04 11:31:16 -08:00
614e765575 [1.11] Make svd / svdvals fully functorch compatible (#72181) (#72274)
* release 1.11 Install torch from test channel, Pin builder and xla repo (#72217)

* Make svd / svdvals fully functorch compatible (#72181)

Summary:
This should (hopefully) make all the CI from `functorch` go green (including jvp's!) after changing `VARIADIC_BDIMS_BOXED(_svd_helper);` with `VARIADIC_BDIMS_BOXED(_linalg_svd);` and removing all the skip and xfails associated to `linalg.svdvals`.

Locally, there's just one test that started failing because of this, and that is `test_vmapjvpall_norm_nuc_cpu_float32`. I have no idea what's going on here, but it's a jvp product, so not a regression, and it might very well be caused by the jvp of other operation within `norm_nuc` as this is a composite operation.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/72181

Reviewed By: ngimel

Differential Revision: D33952744

Pulled By: zou3519

fbshipit-source-id: 2a2510d97eed4a0bfc25615264ddd36e38856efe
(cherry picked from commit 5805fa107c3a91c58f8ecc9778cfc87aa7f64233)

Co-authored-by: Andrey Talman <atalman@fb.com>
Co-authored-by: lezcano <lezcano-93@hotmail.com>
2022-02-04 14:29:02 -05:00
7b0e140ecc [1.11] Remove torch.vmap (#65496) (#72275)
* release 1.11 Install torch from test channel, Pin builder and xla repo (#72217)

* [1.11] Remove torch.vmap (#65496)

torch.vmap is a prototype feature and should not be in the stable
binary. This PR:
- Removes the torch.vmap API
- Removes the documentation entry for torch.vmap
- Changes the vmap tests to use an internal API instead of torch.vmap.

Test Plan:
- Tested locally (test_torch, test_autograd, test_type_hints, test_vmap),
but also wait for CI.

Co-authored-by: Andrey Talman <atalman@fb.com>
2022-02-04 11:23:44 -08:00
3fab33e1c9 release 1.11 Install torch from test channel, Pin builder and xla repo (#72217) 2022-02-04 11:15:10 -08:00
18463 changed files with 1125478 additions and 1988425 deletions

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# PyTorch CI Builds Pipeline on Azure DevOps
#
# This pipeline:
# 1) builds PyTorch on select configurations
# 2) runs only TestTorch unit tests.
stages:
- stage: 'Build'
displayName: 'Build PyTorch'
jobs:
- template: job_templates/build-verify-publish-template-unix.yml
parameters:
name: ubuntu_1804_CPU_docker
pool: 'PyTorch-Linux-CPU'
container_endpoint: pytorchms.azurecr.io
build_stage: True
is_ci_build: True
os: ubuntu
cuda: cpu
customMatrixes:
Py_38:
configuration: ubuntu_1804_py_38_cpu
container_image: pytorchms.azurecr.io/ubuntu_1804_py_38_cpu_dev
- template: job_templates/build-verify-publish-template-unix.yml
parameters:
name: ubuntu_1804_GPU_docker
pool: 'PyTorch-Linux-GPU'
container_endpoint: pytorchms.azurecr.io
build_stage: True
is_ci_build: True
os: ubuntu
cuda: gpu
customMatrixes:
Py_39_CUDA_112_cuDNN_810:
configuration: ubuntu_1804_py_39_cuda_112_cudnn_810
container_image: pytorchms.azurecr.io/ubuntu_1804_py_39_cuda_112_cudnn_8_dev
CUDA_VERSION: 112
- template: job_templates/build-verify-publish-template-win.yml
parameters:
name: windows_2019_CPU
pool: 'PyTorch-Win-CPU'
build_stage: True
is_ci_build: True
os: windows
cuda: cpu
customMatrixes:
Py_37:
configuration: windows_2019_py_37_cpu
- template: job_templates/build-verify-publish-template-win.yml
parameters:
name: windows_2019_GPU
pool: 'PyTorch-Win-GPU'
build_stage: True
is_ci_build: True
os: windows
cuda: gpu
customMatrixes:
Py_38_CUDA_102_cuDNN_765:
configuration: windows_2019_py_38_cuda_102_cudnn_765
CUDA_VERSION: 102

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# PyTorch Daily Builds Pipeline on Azure DevOps
#
# This pipeline:
# 1) builds PyTorch on all available configurations
# 2) runs all PyTorch unit tests
stages:
- stage: 'BuildTest'
displayName: 'Build and Test PyTorch'
jobs:
- template: job_templates/build-verify-publish-template-unix.yml
parameters:
name: ubuntu_1804_CPU_docker
pool: 'PyTorch-Linux-CPU'
container_endpoint: pytorchms.azurecr.io
build_stage: True
is_daily_build: True
os: ubuntu
cuda: cpu
customMatrixes:
Py_38:
configuration: ubuntu_1804_py_38_cpu
container_image: pytorchms.azurecr.io/ubuntu_1804_py_38_cpu_dev
Py_37:
configuration: ubuntu_1804_py_37_cpu
container_image: pytorchms.azurecr.io/ubuntu_1804_py_37_cpu_dev
- template: job_templates/build-verify-publish-template-unix.yml
parameters:
name: ubuntu_1804_GPU_docker
pool: 'PyTorch-Linux-GPU'
container_endpoint: pytorchms.azurecr.io
build_stage: True
is_daily_build: True
os: ubuntu
cuda: gpu
customMatrixes:
Py_39_CUDA_112_cuDNN_810:
configuration: ubuntu_1804_py_39_cuda_112_cudnn_810
container_image: pytorchms.azurecr.io/ubuntu_1804_py_39_cuda_112_cudnn_8_dev
CUDA_VERSION: 112
Py_38_CUDA_102_cuDNN_810:
configuration: ubuntu_1804_py_38_cuda_102_cudnn_810
container_image: pytorchms.azurecr.io/ubuntu_1804_py_38_cuda_102_cudnn_8_dev
CUDA_VERSION: 102
Py_37_CUDA_101_cuDNN_765:
configuration: ubuntu_1804_py_37_cuda_101_cudnn_765
container_image: pytorchms.azurecr.io/ubuntu_1804_py_37_cuda_101_cudnn_7_dev
CUDA_VERSION: 101
- template: job_templates/build-verify-publish-template-win.yml
parameters:
name: windows_2019_CPU
pool: 'PyTorch-Win-CPU'
build_stage: True
is_daily_build: True
os: windows
cuda: cpu
customMatrixes:
Py_38:
configuration: windows_2019_py_38_cpu
Py_37:
configuration: windows_2019_py_37_cpu
- template: job_templates/build-verify-publish-template-win.yml
parameters:
name: windows_2019_GPU
pool: 'PyTorch-Win-GPU'
build_stage: True
is_daily_build: True
os: windows
cuda: gpu
customMatrixes:
Py_39_CUDA_112_cuDNN_810:
configuration: windows_2019_py_39_cuda_112_cudnn_810
CUDA_VERSION: 112
Py_38_CUDA_102_cuDNN_765:
configuration: windows_2019_py_38_cuda_102_cudnn_765
CUDA_VERSION: 102
Py_37_CUDA_101_cuDNN_764:
configuration: windows_2019_py_37_cuda_101_cudnn_764
CUDA_VERSION: 101

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# PyTorch build steps template with Unix images Azure DevOps Instances
#
# This build depends on 3 parameters set as environment variables in the pipeline:
# - AZURE_DEVOPS_CLI_PAT: Secret var for authenticating to Azure DevOps
# - AZURE_DEVOPS_ARTIFACTS_ORGANIZATION: Azure Artifacts Organization name to publish artifacts
# - AZURE_DEVOPS_ARTIFACTS_PROJECT: Azure Artifacts Project name to publish artifacts
parameters:
name: ''
pool: ''
container_endpoint: ''
os: ''
cuda: ''
is_ci_build: False
is_official_build: False
is_daily_build: False
build_stage: False
verify_stage: False
publish_stage: False
customMatrixes: ''
jobs:
- job: ${{parameters.name}}
timeoutInMinutes: 300
strategy:
matrix:
${{ insert }}: ${{parameters.customMatrixes}}
pool:
name: ${{ parameters.pool}}
variables:
DECODE_PERCENTS: false
container:
image: $[variables['container_image']]
endpoint: ${{parameters.container_endpoint}}
steps:
# Build stage
- ${{ if eq(parameters.build_stage, 'True') }}:
# Set up environment variables for specific pipeline build
- template: set-environment-variables.yml
parameters:
os: ${{ parameters.os}}
cuda: ${{ parameters.cuda}}
is_official_build: ${{ parameters.is_official_build}}
# Sync and update PyTorch submodules
- bash: git submodule update --init --recursive --jobs 0
displayName: Update PyTorch submodules
# Build PyTorch and run unit tests - no packaging
- ${{ if or(eq(parameters.is_ci_build, 'True'), eq(parameters.is_daily_build, 'True')) }}:
# Build PyTorch from source in develop mode
- bash: python setup.py develop
displayName: Build PyTorch from source
- ${{ if eq(parameters.is_ci_build, 'True') }}:
# Run TestTorch unit tests to demonstrate successful PyTorch build
- bash: python test/test_torch.py TestTorch
displayName: Run TestTorch unit tests
- ${{ if eq(parameters.is_daily_build, 'True') }}:
# Run all unit tests to demonstrate successful PyTorch build
- bash: python test/run_test.py --continue-through-error --exclude-jit-executor --verbose
displayName: Run all unit tests
# Run ComponentGovernance
- task: ComponentGovernanceComponentDetection@0
inputs:
scanType: 'Register'
verbosity: 'Verbose'
alertWarningLevel: 'High'
# Build PyTorch and produce artifacts for verification stage
- ${{ if eq(parameters.is_official_build, 'True') }}:
# Build PyTorch from source in install mode and exclude test binaries
- bash: python setup.py install
displayName: Build PyTorch from source without test binaries
# Package PyTorch Wheel
- bash: python setup.py bdist_wheel
displayName: Package PyTorch Wheel
# Publish PyTorch Wheel
- task: PublishPipelineArtifact@1
inputs:
targetPath: $(Build.SourcesDirectory)/dist/
artifactName: Build_$(Build.BuildNumber)_$(configuration)
displayName: Publish PyTorch Wheel to Pipeline Artifacts
# Verification stage
- ${{ if eq(parameters.verify_stage, 'True') }}:
# Download PyTorch Wheel
- task: DownloadPipelineArtifact@2
inputs:
artifact: Build_$(Build.BuildNumber)_$(configuration)
path: $(Build.SourcesDirectory)/verify
displayName: Download PyTorch Wheel
# Install PyTorch Wheel on Windows
- bash: python -m pip install $(Build.SourcesDirectory)/verify/torch*linux*.whl
displayName: Install PyTorch Wheel
# Ensure PyTorch installed correctly from produced wheel
- bash: |
cd $(Build.SourcesDirectory)/verify
python -c "import torch; print('Installed Torch version: ' + torch.__version__)"
displayName: Check PyTorch correctly installed from wheel
# Publishing stage
- ${{ if eq(parameters.publish_stage, 'True') }}:
# Download PyTorch Wheel
- task: DownloadPipelineArtifact@2
inputs:
artifact: Build_$(Build.BuildNumber)_$(configuration)
path: $(Build.SourcesDirectory)/publish
displayName: Download PyTorch Wheel
# Publish wheel to Azure Artifacts
# The flag continueOnError=true is needed as the artifact to be published
# may already exist, because the artifact is differentiated based on the
# last commit date.
- bash: |
export TORCH_VERSION=$(head -c 5 ./version.txt)
export LAST_COMMIT=$(git rev-parse --short HEAD)
export LAST_COMMIT_DATE=$(git log -1 --pretty=%ad --date=format:%Y%m%d)
cd $(Build.SourcesDirectory)/publish
export TORCH_WHEEL=$(echo torch*linux*whl)
az extension add -n azure-devops
echo $ADOTOKEN | az devops login
az artifacts universal publish --organization $AZURE_DEVOPS_ARTIFACTS_ORGANIZATION --project $AZURE_DEVOPS_ARTIFACTS_PROJECT --scope project --feed "PyTorch" --name $TORCH_WHEEL --description "PyTorch Official Build Artifact" --version $TORCH_VERSION-$LAST_COMMIT_DATE-$LAST_COMMIT --path .
env:
ADOTOKEN: $(AZURE_DEVOPS_CLI_PAT)
continueOnError: true
displayName: Upload PyTorch Official Build package to Azure Artifacts

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# PyTorch build steps template with Windows images Azure DevOps Instances
#
# This build depends on 3 parameters set as environment variables in the pipeline:
# - AZURE_DEVOPS_CLI_PAT: Secret var for authenticating to Azure DevOps
# - AZURE_DEVOPS_ARTIFACTS_ORGANIZATION: Azure Artifacts Organization name to publish artifacts
# - AZURE_DEVOPS_ARTIFACTS_PROJECT: Azure Artifacts Project name to publish artifacts
parameters:
name: ''
pool: ''
os: ''
cuda: ''
is_ci_build: False
is_official_build: False
is_daily_build: False
build_stage: False
verify_stage: False
publish_stage: False
customMatrixes: ''
jobs:
- job: ${{parameters.name}}
timeoutInMinutes: 300
strategy:
matrix:
${{ insert }}: ${{parameters.customMatrixes}}
pool:
name: ${{ parameters.pool}}
variables:
CMAKE_GENERATOR: Ninja
PACKAGE_PDBS: 0
steps:
# Prepare for PyTorch build on Windows
- template: prepare-build-template.yml
parameters:
configuration: $(configuration)
build_stage: ${{ parameters.build_stage}}
# Build Stage
- ${{ if eq(parameters.build_stage, 'True') }}:
# Set up environment variables for specific pipeline build
- template: set-environment-variables.yml
parameters:
os: ${{ parameters.os}}
cuda: ${{ parameters.cuda}}
is_official_build: ${{ parameters.is_official_build}}
# Sync and update PyTorch submodules
- script: git submodule update --init --recursive --jobs 0
displayName: Update PyTorch submodules
# Build PyTorch and run unit tests - no packaging
- ${{ if or(eq(parameters.is_ci_build, 'True'), eq(parameters.is_daily_build, 'True')) }}:
# Build PyTorch from source in develop mode with Ninja
- script: call activate $(configuration) && python setup.py develop
displayName: Build PyTorch from source
- ${{ if eq(parameters.is_ci_build, 'True') }}:
# Run TestTorch unit tests to demonstrate successful PyTorch build
- script: call activate $(configuration) && python test\test_torch.py TestTorch
displayName: Run TestTorch unit tests
- ${{ if eq(parameters.is_daily_build, 'True') }}:
# Run all unit tests to demonstrate successful PyTorch build
- script: call activate $(configuration) && python test/run_test.py --continue-through-error --exclude-jit-executor --verbose
displayName: Run all unit tests
# Run ComponentGovernance
- task: ComponentGovernanceComponentDetection@0
inputs:
scanType: 'Register'
verbosity: 'Verbose'
alertWarningLevel: 'High'
# Build PyTorch and produce artifacts for verification stage
- ${{ if eq(parameters.is_official_build, 'True') }}:
# Build PyTorch from source in install mode with Ninja and exclude test binaries
- script: call activate $(configuration) && python setup.py install
displayName: Build PyTorch from source without test binaries
# Package PyTorch Wheel
- script: call activate $(configuration) && python setup.py bdist_wheel
displayName: Package PyTorch Wheel
# Publish PyTorch Wheel
- task: PublishPipelineArtifact@1
inputs:
targetPath: $(Build.SourcesDirectory)\dist\
artifactName: Build_$(Build.BuildNumber)_$(configuration)
displayName: Publish PyTorch Wheel to Pipeline Artifacts
# Verification Stage
- ${{ if eq(parameters.verify_stage, 'True') }}:
# Download PyTorch Wheel
- task: DownloadPipelineArtifact@2
inputs:
artifact: Build_$(Build.BuildNumber)_$(configuration)
path: $(Build.SourcesDirectory)\verify
displayName: Download PyTorch Wheel
# Install PyTorch Wheel on Windows
- script: |
call activate $(configuration)
cd $(Build.SourcesDirectory)\verify
dir torch*win*.whl /b > whl.txt
set /p whl= < whl.txt
python -m pip install %whl%
displayName: Install PyTorch Wheel
# Ensure PyTorch installed correctly from produced wheel
- script: |
call activate $(configuration)
cd $(Build.SourcesDirectory)\verify
python -c "import torch; print('Installed Torch version: ' + torch.__version__)"
displayName: Check PyTorch correctly installed from wheel
# Publishing stage
- ${{ if eq(parameters.publish_stage, 'True') }}:
# Download PyTorch Wheel
- task: DownloadPipelineArtifact@2
inputs:
artifact: Build_$(Build.BuildNumber)_$(configuration)
path: $(Build.SourcesDirectory)\publish
displayName: Download PyTorch Wheel
# Set up Azure Artifacts for Windows
# The pip install --upgrade command is a bug fix for Azure CLI on Windows
# More info: https://github.com/Azure/azure-cli/issues/16858
- script: |
pip install --upgrade pip --target \opt\az\lib\python3.6\site-packages\
az extension add -n azure-devops
displayName: Set up Azure Artifacts download on Windows
# Publish wheel to Azure Artifacts
# The flag continueOnError=true is needed as the artifact to be published
# may already exist, because the artifact is differentiated based on the
# last commit date.
- script: |
set /p TORCH_VERSION= < version.txt
cd $(Build.SourcesDirectory)\publish
git rev-parse --short HEAD > last_commit.txt && set /p LAST_COMMIT= < last_commit.txt
git log -1 --pretty=%ad --date=format:%Y%m%d > last_commit_date.txt && set /p LAST_COMMIT_DATE= < last_commit_date.txt
dir torch*win*.whl /b > whl.txt && set /p TORCH_WHEEL= < whl.txt
echo %ADOTOKEN% | az devops login
az artifacts universal publish --organization %AZURE_DEVOPS_ARTIFACTS_ORGANIZATION% --project %AZURE_DEVOPS_ARTIFACTS_PROJECT% --scope project --feed "PyTorch" --name %TORCH_WHEEL% --description "PyTorch Official Build Artifact" --version %TORCH_VERSION:~0,5%-%LAST_COMMIT_DATE%-%LAST_COMMIT% --path .
env:
ADOTOKEN: $(AZURE_DEVOPS_CLI_PAT)
continueOnError: true
displayName: Upload PyTorch nigthly package to Azure Artifacts

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dependencies:
- python=PYTHON_VERSION
- numpy
- ninja
- pyyaml
- mkl
- mkl-include
- setuptools
- cmake
- cffi
- typing_extensions
- future
- six
- requests
- dataclasses
- pip:
- -r ../../requirements.txt

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parameters:
name: ''
pool: ''
customMatrixes: ''
jobs:
- job: ${{parameters.name}}
timeoutInMinutes: 600
strategy:
matrix:
${{ insert }}: ${{parameters.customMatrixes}}
pool:
name: ${{ parameters.pool}}
steps:
# Clone PyTorch Tests repository
- bash: |
B64_PAT=$(echo -n ":$_ADOTOKEN" | base64)
git -c http.extraHeader="Authorization: Basic ${B64_PAT}" clone $(AZURE_DEVOPS_PYTORCH_TESTS_REPO_URL)
cd pytorch_tests
git checkout $(PYTORCH_TESTS_CHECKOUT_BRANCH)
env:
_ADOTOKEN: $(AZURE_DEVOPS_CLI_PAT)
displayName: Clone PyTorch Tests repo
- bash: |
bash $(Build.SourcesDirectory)/pytorch_tests/webapp/notify_webapp.sh
displayName: Notify Webapp

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# Build prepare steps for PyTorch on Azure DevOps to build from source.
# These steps share between normal build process and semmle security scan tasks
parameters:
build_stage: False
configuration: ''
steps:
# End Python tasks that may be lingering over from previous runs
# Note: If python.exe isn't currently running, exit code becomes 128,
# which fails the run. Here exit code is set to 0 to avoid failed run.
- script: |
taskkill /f /im python.exe
IF %ERRORLEVEL% EQU 128 exit 0
displayName: End previous Python processes
# Clean up env directory in conda for fresh builds and set up conda environment YAML
- powershell: |
Remove-Item 'C:\Miniconda\envs' -Recurse -ErrorAction Ignore
$env:PYTHON_VERSION = $env:SYSTEM_JOBNAME.Substring(3,1) + '.' + $env:SYSTEM_JOBNAME.Substring(4,1)
(Get-Content .azure_pipelines\job_templates\common-packages.yml) -replace 'PYTHON_VERSION', $env:PYTHON_VERSION | Out-File -encoding ASCII .azure_pipelines\job_templates\common-packages.yml
displayName: Clean up previous environments and Set up conda environment YAML
# Make conda environment and install required packages
- script: |
call conda clean --all -y
call conda env create -n $(configuration) --file .azure_pipelines\job_templates\common-packages.yml
call activate $(configuration)
call conda install -c conda-forge libuv=1.39
displayName: Set up conda environment for building from source
- ${{ if eq(parameters.build_stage, 'True') }}:
# Install MKL
- script: |
rmdir /s /q mkl
del mkl_2020.2.254.7z
curl https://s3.amazonaws.com/ossci-windows/mkl_2020.2.254.7z -k -O
7z x -aoa mkl_2020.2.254.7z -omkl
displayName: Install MKL
# Install sccache and randomtemp
# Related PyTorch GitHub issue: https://github.com/pytorch/pytorch/issues/25393
# Related fix: https://github.com/pytorch/builder/pull/448/
- script: |
mkdir .\tmp_bin
curl -k https://s3.amazonaws.com/ossci-windows/sccache.exe --output .\tmp_bin\sccache.exe
curl -k https://s3.amazonaws.com/ossci-windows/sccache-cl.exe --output .\tmp_bin\sccache-cl.exe
copy .\tmp_bin\sccache.exe .\tmp_bin\nvcc.exe
curl -kL https://github.com/peterjc123/randomtemp-rust/releases/download/v0.4/randomtemp.exe --output .\tmp_bin\randomtemp.exe
displayName: Install sccache and randomtemp
condition: not(eq(variables.CUDA_VERSION, ''))
# CUDA 11.2's CUB directory conflicts with CUDA 10.2 and 10.1
# builds, where CUDA 11.2's CUB is injected into non-CUDA
# 11.2 builds.
- powershell: Remove-Item "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.2\include\cub" -Recurse -ErrorAction Ignore
displayName: Remove conflicting CUB from CUDA installation
condition: not(eq(variables.CUDA_VERSION, ''))
- powershell: Copy-Item -Path "F:\cuda_11_2\cub\" -Destination "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.2\include" -Recurse
displayName: Copy CUDA CUB for CUDA 11.2 build
condition: eq(variables.CUDA_VERSION, '112')

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# PyTorch build steps template with Unix images Azure DevOps Instances
#
# This build depends on 5 parameters set as an environment variables in the pipeline:
# - AZURE_DEVOPS_CLI_PAT: Secret var for authenticating to Azure DevOps
# - AZURE_STORAGE_KEY: Secret var for authenticating to Azure Storage
# - _TS_CLONE_P, _TS_P, _TS_SM_P: Secret vars for specific unit tests
parameters:
name: ''
pool: ''
container_endpoint: ''
customMatrixes: ''
jobs:
- job: ${{parameters.name}}
timeoutInMinutes: 600
strategy:
matrix:
${{ insert }}: ${{parameters.customMatrixes}}
pool:
name: ${{ parameters.pool}}
variables:
DECODE_PERCENTS: false
steps:
# Don't checkout repo contents to save time and CPU compute. Environment variables
# related to checkout branch such as $(BUILD_SOURCEBRANCH) are still available.
- checkout: none
# Delete pytorch_tests repo from previous builds if exists
- bash: rm -rf pytorch_tests/
displayName: Delete pytorch_tests repo from previous builds if exists
# Clone PyTorch Tests repository
- bash: |
B64_PAT=$(echo -n ":$_ADOTOKEN" | base64)
git -c http.extraHeader="Authorization: Basic ${B64_PAT}" clone $(AZURE_DEVOPS_PYTORCH_TESTS_REPO_URL)
cd pytorch_tests
git checkout $(PYTORCH_TESTS_CHECKOUT_BRANCH)
env:
_ADOTOKEN: $(AZURE_DEVOPS_CLI_PAT)
displayName: Clone PyTorch Tests repo
# Run PyTorch Unit Tests
- bash: bash $(Build.SourcesDirectory)/pytorch_tests/scripts/linux/run.sh
env:
_AZURE_STORAGE_KEY: $(AZURE_STORAGE_KEY)
_TS_CLONE_P: $(TS_CLONE_PASSWORD)
_TS_P: $(TS_PAT)
_TS_SM_P: $(TS_SM_PAT)
_AZUREML_CLONE_PASSWORD: $(AZUREML_CLONE_PASSWORD)
_SPPASSWORD: $(SPPASSWORD)
displayName: Run PyTorch Unit Tests
# Tests results are available outside the docker container since
# the current directory is mounted as a volume of the container.
- task: PublishTestResults@2
condition: always()
inputs:
testResultsFiles: '**/test-*.xml'
testRunTitle: 'Publish test results for Python'

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# PyTorch build steps template with Windows images Azure DevOps Instances
#
# This build depends on 5 parameters set as an environment variables in the pipeline:
# - AZURE_DEVOPS_CLI_PAT: Secret var for authenticating to Azure DevOps
# - AZURE_STORAGE_KEY: Secret var for authenticating to Azure Storage
# - _TS_CLONE_P, _TS_P, _TS_SM_P: Secret vars for specific unit tests
parameters:
name: ''
pool: ''
customMatrixes: ''
jobs:
- job: ${{parameters.name}}
timeoutInMinutes: 600
strategy:
matrix:
${{ insert }}: ${{parameters.customMatrixes}}
pool:
name: ${{ parameters.pool}}
steps:
# Don't checkout repo contents to save time and CPU compute. Environment variables
# related to checkout branch such as $(BUILD_SOURCEBRANCH) are still available.
- checkout: none
# Delete pytorch_tests repo from previous builds if exists
- script: if exist "pytorch_tests/" rmdir "pytorch_tests/" /q /s
displayName: Delete pytorch_tests repo from previous builds if exists
# Clone PyTorch Tests repository
- powershell: |
$env:B64Pat = [Convert]::ToBase64String([System.Text.Encoding]::UTF8.GetBytes(":$env:_ADOTOKEN"))
git -c http.extraHeader="Authorization: Basic $env:B64Pat" clone $env:AZURE_DEVOPS_pytorch_tests_REPO_URL
cd pytorch_tests
git checkout $(PYTORCH_TESTS_CHECKOUT_BRANCH)
env:
_ADOTOKEN: $(AZURE_DEVOPS_CLI_PAT)
displayName: Clone PyTorch Tests repo
# Run PyTorch Unit Tests
- script: call $(Build.SourcesDirectory)\pytorch_tests\scripts\windows\run.bat
env:
_ADOTOKEN: $(AZURE_DEVOPS_CLI_PAT)
_AZURE_STORAGE_KEY: $(AZURE_STORAGE_KEY)
_TS_CLONE_P: $(TS_CLONE_PASSWORD)
_TS_P: $(TS_PAT)
_TS_SM_P: $(TS_SM_PAT)
displayName: Run PyTorch Unit Tests
# Tests results are available outside the docker container since
# the current directory is mounted as a volume of the container.
- task: PublishTestResults@2
condition: always()
inputs:
testResultsFiles: '**\test-*.xml'
testRunTitle: 'Publish test results for Python'

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# Set environment variables for specific configurations
parameters:
is_official_build: False
os: ''
cuda: ''
steps:
# Environment configuration steps for Ubuntu builds
- ${{ if contains(parameters.os, 'ubuntu') }}:
# Set configuration specific build flags
- ${{ if eq(parameters.is_official_build, True) }}:
- bash: |
echo "##vso[task.setvariable variable=INSTALL_TEST;]0"
echo "##vso[task.setvariable variable=PYTORCH_BUILD_NUMBER;]1"
export PYTORCH_VERSION=$(head -c 5 ./version.txt)
echo "##vso[task.setvariable variable=PYTORCH_BUILD_VERSION;]$PYTORCH_VERSION.dev"
displayName: Set configuration-specific build flags
# Set PyTorch CPU/GPU build flags.
- ${{ if contains(parameters.cuda, 'cpu') }}:
- bash: |
echo "##vso[task.setvariable variable=USE_CUDA;]0"
echo "##vso[task.setvariable variable=PYTORCH_BUILD_VERSION;]$(PYTORCH_BUILD_VERSION).cpu"
displayName: Set CUDA-specific build flag for CPU builds
- ${{ if contains(parameters.cuda, 'gpu') }}:
- bash: |
echo "##vso[task.setvariable variable=USE_CUDA;]1"
echo "##vso[task.setvariable variable=PYTORCH_BUILD_VERSION;]$(PYTORCH_BUILD_VERSION).cu$(CUDA_VERSION)"
displayName: Set CUDA-specific build flag for GPU builds
# Set MKL environment variables
- bash: |
echo "##vso[task.setvariable variable=CMAKE_LIBRARY_PATH;]/opt/intel/lib:$CMAKE_LIBRARY_PATH"
echo "##vso[task.setvariable variable=CMAKE_INCLUDE_PATH;]/opt/intel/include:$CMAKE_INCLUDE_PATH"
displayName: Set MKL paths
# View current environment variables
- bash:
printenv
displayName: Show environment variables
# Environment configuration steps for Windows builds
- ${{ if contains(parameters.os, 'windows') }}:
# Set Conda Lib Path
- powershell: Write-Host "##vso[task.setvariable variable=CONDA_LIB_PATH;]C:\Miniconda\envs\$(configuration)\Library\bin"
displayName: Set Conda Lib Path
# Set configuration specific build flags
- ${{ if eq(parameters.is_official_build, True) }}:
- powershell: |
Write-Host "##vso[task.setvariable variable=INSTALL_TEST;]0"
Write-Host "##vso[task.setvariable variable=PYTORCH_BUILD_NUMBER;]1"
Set-Variable -Name PYTORCH_VERSION -Value (Get-Content .\version.txt).Substring(0,5)
Write-Host "##vso[task.setvariable variable=PYTORCH_BUILD_VERSION;]$PYTORCH_VERSION.dev"
displayName: Set configuration-specific build flags
# Set PyTorch CPU/GPU build flags..
- ${{ if contains(parameters.cuda, 'cpu') }}:
- powershell: |
Write-Host "##vso[task.setvariable variable=USE_CUDA;]0"
Write-Host "##vso[task.setvariable variable=PYTORCH_BUILD_VERSION;]$(PYTORCH_BUILD_VERSION).cpu"
displayName: Set CUDA-specific build flag for CPU build
- ${{ if contains(parameters.cuda, 'gpu') }}:
- powershell: |
Write-Host "##vso[task.setvariable variable=USE_CUDA;]1"
Write-Host "##vso[task.setvariable variable=PYTORCH_BUILD_VERSION;]$(PYTORCH_BUILD_VERSION).cu$(CUDA_VERSION)"
displayName: Set CUDA-specific build flag for GPU build
# Set CUDA 11.2, 10.2 or 10.1 specific build flags
- ${{ if eq(parameters.cuda, 'gpu') }}:
- powershell: |
Write-Host "##vso[task.setvariable variable=TORCH_CUDA_ARCH_LIST;]3.7+PTX;5.0;6.0;6.1;7.0;7.5;8.0;8.6"
Write-Host "##vso[task.setvariable variable=CUDA_PATH;]C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.2\"
displayName: Set CUDA 11.2 specific build flags
condition: eq(variables.CUDA_VERSION, '112')
- powershell: |
Write-Host "##vso[task.setvariable variable=TORCH_CUDA_ARCH_LIST;]3.7+PTX;5.0;6.0;6.1;7.0;7.5"
Write-Host "##vso[task.setvariable variable=CUDA_PATH;]C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v10.2\"
displayName: Set CUDA 10.2 specific build flags
condition: eq(variables.CUDA_VERSION, '102')
- powershell: |
Write-Host "##vso[task.setvariable variable=TORCH_CUDA_ARCH_LIST;]3.7+PTX;5.0;6.0;6.1;7.0;7.5"
Write-Host "##vso[task.setvariable variable=CUDA_PATH;]C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v10.1\"
displayName: Set CUDA 10.1 specific build flags
condition: eq(variables.CUDA_VERSION, '101')
- powershell: |
Write-Host "##vso[task.setvariable variable=CUDA_BIN_PATH;]$env:CUDA_PATH\bin\"
Write-Host "##vso[task.setvariable variable=CUDNN_ROOT;]$env:CUDA_PATH"
Write-Host "##vso[task.setvariable variable=CUDNN_INCLUDE_DIR;]$env:CUDA_PATH\include\"
Write-Host "##vso[task.setvariable variable=CUDNN_LIBRARY;]$env:CUDA_PATH\lib\x64\"
Write-Host "##vso[task.prependpath]$env:CUDA_PATH\bin"
Write-Host "##vso[task.setvariable variable=TORCH_NVCC_FLAGS;]-Xfatbin -compress-all --no-host-device-move-forward"
Write-Host "##vso[task.setvariable variable=THRUST_IGNORE_CUB_VERSION_CHECK;]1"
Write-Host "##vso[task.setvariable variable=NVTOOLSEXT_PATH;]C:\Program Files\NVIDIA Corporation\NvToolsExt\"
displayName: Set CUDA environment variables
- powershell: |
copy "$(CUDA_BIN_PATH)\cusparse*64_*.dll*" $(Build.SourcesDirectory)\torch\lib
copy "$(CUDA_BIN_PATH)\cublas*64_*.dll*" $(Build.SourcesDirectory)\torch\lib
copy "$(CUDA_BIN_PATH)\cudart*64_*.dll*" $(Build.SourcesDirectory)\torch\lib
copy "$(CUDA_BIN_PATH)\curand*64_*.dll*" $(Build.SourcesDirectory)\torch\lib
copy "$(CUDA_BIN_PATH)\cufft*64_*.dll*" $(Build.SourcesDirectory)\torch\lib
copy "$(CUDA_BIN_PATH)\cusolver*64_*.dll*" $(Build.SourcesDirectory)\torch\lib
copy "$(CUDA_BIN_PATH)\cudnn*64_*.dll*" $(Build.SourcesDirectory)\torch\lib
copy "$(CUDA_BIN_PATH)\nvrtc*64_*.dll*" $(Build.SourcesDirectory)\torch\lib
copy "C:\Program Files\NVIDIA Corporation\NvToolsExt\bin\x64\nvToolsExt64_1.dll*" $(Build.SourcesDirectory)\torch\lib
copy "$(CONDA_LIB_PATH)\libiomp*5md.dll" $(Build.SourcesDirectory)\torch\lib
copy "$(CONDA_LIB_PATH)\uv.dll" $(Build.SourcesDirectory)\torch\lib
displayName: Copy CUDA/cuDNN/libomp/libuv dlls to torch\lib
# Set MKL, sccache and randomtemp environment variables
- powershell: |
Write-Host "##vso[task.setvariable variable=CMAKE_INCLUDE_PATH;]$(Build.SourcesDirectory)\mkl\include"
Write-Host "##vso[task.setvariable variable=CMAKE_LIBRARY_PATH;]$(Build.SourcesDirectory)\mkl\lib;$env:CMAKE_LIBRARY_PATH"
Write-Host "##vso[task.setvariable variable=ADDITIONAL_PATH;]$(Build.SourcesDirectory)\tmp_bin"
Write-Host "##vso[task.setvariable variable=SCCACHE_IDLE_TIMEOUT;]1500"
Write-Host "##vso[task.setvariable variable=CMAKE_CUDA_COMPILER_LAUNCHER;]$(Build.SourcesDirectory)/tmp_bin/randomtemp.exe;$(Build.SourcesDirectory)/tmp_bin/sccache.exe"
displayName: Set MKL, sccache and randomtemp environment variables
# View current environment variables
- script:
set
displayName: Show environment variables

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# Main logic to initiate wait for PR artifact to be ready
steps:
- task: InvokeRESTAPI@1
displayName: 'Wait for job success and wheel ready'
timeoutInMinutes: 60
inputs:
connectionType: 'connectedServiceName'
serviceConnection: circleciconn
method: 'POST'
headers: '{"Content-Type":"application/json", "BranchName":"$(_TARGET_BRANCH_TO_CHECK)", "JobName":"$(TARGET_CIRCLECI_BUILD_PR)", "PRNumber":"$(_TARGET_PR_NUMBER)", "TargetCommit":"$(_TARGET_COMMIT)", "PlanUrl":"$(System.CollectionUri)", "ProjectId":"$(System.TeamProjectId)", "HubName":"$(System.HostType)", "PlanId":"$(System.PlanId)", "JobId":"$(System.JobId)", "TimelineId":"$(System.TimelineId)", "TaskInstanceId":"$(System.TaskInstanceId)", "AuthToken":"$(System.AccessToken)"}'
body: ''
urlSuffix: 'api/JobStatus'
waitForCompletion: true

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# Initiate 5 agentless-server waiting jobs to check on the
# status of PR artifact builds, for a maximum wait time of
# 11*60 min=660 mins. These jobs will pass immediately
# once targeted CircleCI build is ready.
jobs:
- job: checkjob1
pool: server
timeoutInMinutes: 60
continueOnError: true
steps:
- template: wheel-wait-job-template.yml
- job: checkjob2
pool: server
timeoutInMinutes: 60
dependsOn: checkjob1
continueOnError: true
steps:
- template: wheel-wait-job-template.yml
- job: checkjob3
pool: server
timeoutInMinutes: 60
dependsOn: checkjob2
continueOnError: true
steps:
- template: wheel-wait-job-template.yml
- job: checkjob4
pool: server
timeoutInMinutes: 60
dependsOn: checkjob3
continueOnError: true
steps:
- template: wheel-wait-job-template.yml
- job: checkjob5
pool: server
timeoutInMinutes: 60
dependsOn: checkjob4
continueOnError: true
steps:
- template: wheel-wait-job-template.yml
- job: checkjob6
pool: server
timeoutInMinutes: 60
dependsOn: checkjob5
continueOnError: true
steps:
- template: wheel-wait-job-template.yml
- job: checkjob7
pool: server
timeoutInMinutes: 60
dependsOn: checkjob6
continueOnError: true
steps:
- template: wheel-wait-job-template.yml
- job: checkjob8
pool: server
timeoutInMinutes: 60
dependsOn: checkjob7
continueOnError: true
steps:
- template: wheel-wait-job-template.yml
- job: checkjob9
pool: server
timeoutInMinutes: 60
dependsOn: checkjob8
continueOnError: true
steps:
- template: wheel-wait-job-template.yml
- job: checkjob10
pool: server
timeoutInMinutes: 60
dependsOn: checkjob9
continueOnError: true
steps:
- template: wheel-wait-job-template.yml
- job: checkjob11
pool: server
timeoutInMinutes: 60
dependsOn: checkjob10
continueOnError: true
steps:
- template: wheel-wait-job-template.yml

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# PyTorch Nightly PyTorch Tests Builds Pipeline on Azure DevOps
#
# This pipeline runs custom PyTorch unit-tests on nightly
# PyTorch wheels.
stages:
- stage: 'NightlyCustomTests'
displayName: 'Run custom unit tests on PyTorch wheels'
jobs:
- template: job_templates/pytorch-template-unix.yml
parameters:
name: ubuntu_1804_CPU_docker
pool: $(BUILD_POOL_LIN_1)
customMatrixes:
Nightly_Custom_Tests:
_DOCKER_IMAGE: $(DOCKER_IMAGE_LIN_1)
_PYTHON_VERSION: $(PYTHON_VERSION_LIN_1)
_CUDA_BUILD_VERSION: $(CUDA_BUILD_VERSION_LIN_1)
_RUN_TESTS: $(RUN_TESTS_LIN)
- template: job_templates/pytorch-template-unix.yml
parameters:
name: ubuntu_1804_GPU_docker
pool: $(BUILD_POOL_LIN_2)
customMatrixes:
Nightly_Custom_Tests:
_DOCKER_IMAGE: $(DOCKER_IMAGE_LIN_2)
_PYTHON_VERSION: $(PYTHON_VERSION_LIN_2)
_CUDA_BUILD_VERSION: $(CUDA_BUILD_VERSION_LIN_2)
_RUN_TESTS: $(RUN_TESTS_LIN)
- template: job_templates/pytorch-template-win.yml
parameters:
name: windows_2019_CPU
pool: $(BUILD_POOL_WIN_1)
customMatrixes:
Nightly_Custom_Tests:
_PYTHON_VERSION: $(PYTHON_VERSION_WIN_1)
_CUDA_BUILD_VERSION: $(CUDA_BUILD_VERSION_WIN_1)
_RUN_TESTS: $(RUN_TESTS_WIN)
- template: job_templates/pytorch-template-win.yml
parameters:
name: windows_2019_GPU
pool: $(BUILD_POOL_WIN_2)
customMatrixes:
Nightly_Custom_Tests:
_PYTHON_VERSION: $(PYTHON_VERSION_WIN_2)
_CUDA_BUILD_VERSION: $(CUDA_BUILD_VERSION_WIN_2)
_RUN_TESTS: $(RUN_TESTS_WIN)
- stage: 'NotifyWebapp'
displayName: 'Notify Webapp that pipeline is finished'
dependsOn: NightlyCustomTests
condition: succeededOrFailed()
jobs:
- template: job_templates/notify-webapp-template.yml
parameters:
name: ubuntu_1804_CPU
pool: $(BUILD_POOL_LIN_1)

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# PyTorch PR PyTorch Tests Builds Pipeline on Azure DevOps
#
# This pipeline:
# 1) ensures that CircleCI builds for a given PR
# have finished, and that its artifacts are
# ready for download
# 2) runs custom PyTorch unit-tests on PyTorch
# wheels generated during PR builds.
resources:
webhooks:
- webhook: GitHubPyTorchPRTrigger
connection: GitHubPyTorchPRTriggerConnection
filters:
- path: repositoryName
value: pytorch_tests
stages:
- stage: 'EnsureArtifactsReady'
displayName: 'Ensure PyTorch PR Artifacts are ready'
jobs:
- template: job_templates/wheel-wait-template.yml
variables:
_TARGET_BRANCH_TO_CHECK: ${{parameters.GitHubPyTorchPRTrigger.TARGET_BRANCH_TO_CHECK_AZ_DEVOPS_PR}}
_TARGET_PR_NUMBER: ${{parameters.GitHubPyTorchPRTrigger.PR_NUMBER}}
_TARGET_COMMIT: ${{parameters.GitHubPyTorchPRTrigger.TARGET_COMMIT}}
- stage: 'PRCustomTests'
displayName: 'Run custom unit tests on PyTorch wheels'
dependsOn: EnsureArtifactsReady
condition: succeeded()
jobs:
- template: job_templates/pytorch-template-unix.yml
parameters:
name: ubuntu_1804_GPU_docker
pool: $(BUILD_POOL_PR)
customMatrixes:
PR_Custom_Tests:
_PYTHON_VERSION: $(PYTHON_VERSION_PR)
_CUDA_BUILD_VERSION: $(CUDA_BUILD_VERSION_PR)
_TARGET_CIRCLECI_BUILD: $(TARGET_CIRCLECI_BUILD_PR)
_TARGET_BRANCH_TO_CHECK: ${{parameters.GitHubPyTorchPRTrigger.TARGET_BRANCH_TO_CHECK_AZ_DEVOPS_PR}}
_TARGET_PR_NUMBER: ${{parameters.GitHubPyTorchPRTrigger.PR_NUMBER}}
_TARGET_COMMIT: ${{parameters.GitHubPyTorchPRTrigger.TARGET_COMMIT}}
_DOCKER_IMAGE: $(DOCKER_IMAGE_PR)
_RUN_TESTS: $(RUN_TESTS_PR)
- stage: 'NotifyWebapp'
displayName: 'Notify Webapp that pipeline is finished'
dependsOn: PRCustomTests
condition: succeededOrFailed()
jobs:
- template: job_templates/notify-webapp-template.yml
parameters:
name: ubuntu_1804_CPU
pool: $(BUILD_POOL_LIN_1)
customMatrixes:
PR_Notify_WebApp:
_TARGET_CIRCLECI_BUILD: $(TARGET_CIRCLECI_BUILD_PR)
_TARGET_BRANCH_TO_CHECK: ${{parameters.GitHubPyTorchPRTrigger.TARGET_BRANCH_TO_CHECK_AZ_DEVOPS_PR}}
_TARGET_PR_NUMBER: ${{parameters.GitHubPyTorchPRTrigger.PR_NUMBER}}
_TARGET_COMMIT: ${{parameters.GitHubPyTorchPRTrigger.TARGET_COMMIT}}

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# PyTorch Official Builds Pipeline on Azure DevOps
#
# This pipeline:
# 1) builds PyTorch on all available configurations
# 2) verifies PyTorch artifacts by installing them in a clean environment
# and checking torch.__version_
# 3) publishes official PyTorch artifacts to Azure DevOps Artifacts for consumption
stages:
- stage: 'Build'
displayName: 'Build PyTorch'
jobs:
- template: job_templates/build-verify-publish-template-unix.yml
parameters:
name: ubuntu_1804_CPU_docker
pool: 'PyTorch-Linux-CPU'
container_endpoint: pytorchms.azurecr.io
build_stage: True
is_official_build: True
os: ubuntu
cuda: cpu
customMatrixes:
Py_38:
configuration: ubuntu_1804_py_38_cpu
container_image: pytorchms.azurecr.io/ubuntu_1804_py_38_cpu_dev
Py_37:
configuration: ubuntu_1804_py_37_cpu
container_image: pytorchms.azurecr.io/ubuntu_1804_py_37_cpu_dev
- template: job_templates/build-verify-publish-template-unix.yml
parameters:
name: ubuntu_1804_GPU_docker
pool: 'PyTorch-Linux-GPU'
container_endpoint: pytorchms.azurecr.io
build_stage: True
is_official_build: True
os: ubuntu
cuda: gpu
customMatrixes:
Py_39_CUDA_112_cuDNN_810:
configuration: ubuntu_1804_py_39_cuda_112_cudnn_810
container_image: pytorchms.azurecr.io/ubuntu_1804_py_39_cuda_112_cudnn_8_dev
CUDA_VERSION: 112
Py_38_CUDA_102_cuDNN_810:
configuration: ubuntu_1804_py_38_cuda_102_cudnn_810
container_image: pytorchms.azurecr.io/ubuntu_1804_py_38_cuda_102_cudnn_8_dev
CUDA_VERSION: 102
Py_37_CUDA_101_cuDNN_765:
configuration: ubuntu_1804_py_37_cuda_101_cudnn_765
container_image: pytorchms.azurecr.io/ubuntu_1804_py_37_cuda_101_cudnn_7_dev
CUDA_VERSION: 101
- template: job_templates/build-verify-publish-template-win.yml
parameters:
name: windows_2019_CPU
pool: 'PyTorch-Win-CPU'
build_stage: True
is_official_build: True
os: windows
cuda: cpu
customMatrixes:
Py_38:
configuration: windows_2019_py_38_cpu
Py_37:
configuration: windows_2019_py_37_cpu
- template: job_templates/build-verify-publish-template-win.yml
parameters:
name: windows_2019_GPU
pool: 'PyTorch-Win-GPU'
build_stage: True
is_official_build: True
os: windows
cuda: gpu
customMatrixes:
Py_39_CUDA_112_cuDNN_810:
configuration: windows_2019_py_39_cuda_112_cudnn_810
CUDA_VERSION: 112
Py_38_CUDA_102_cuDNN_765:
configuration: windows_2019_py_38_cuda_102_cudnn_765
CUDA_VERSION: 102
Py_37_CUDA_101_cuDNN_764:
configuration: windows_2019_py_37_cuda_101_cudnn_764
CUDA_VERSION: 101
- stage: 'Verify'
displayName: 'Verify PyTorch wheels'
dependsOn: Build
condition: succeeded()
jobs:
- template: job_templates/build-verify-publish-template-unix.yml
parameters:
name: ubuntu_1804_CPU_docker
pool: 'PyTorch-Linux-CPU'
container_endpoint: pytorchms.azurecr.io
verify_stage: True
is_official_build: True
customMatrixes:
Py_38:
configuration: ubuntu_1804_py_38_cpu
container_image: pytorchms.azurecr.io/ubuntu_1804_py_38_cpu_dev
Py_37:
configuration: ubuntu_1804_py_37_cpu
container_image: pytorchms.azurecr.io/ubuntu_1804_py_37_cpu_dev
- template: job_templates/build-verify-publish-template-unix.yml
parameters:
name: ubuntu_1804_GPU_docker
pool: 'PyTorch-Linux-GPU'
container_endpoint: pytorchms.azurecr.io
verify_stage: True
is_official_build: True
customMatrixes:
Py_39_CUDA_112_cuDNN_810:
configuration: ubuntu_1804_py_39_cuda_112_cudnn_810
container_image: pytorchms.azurecr.io/ubuntu_1804_py_39_cuda_112_cudnn_8_dev
CUDA_VERSION: 112
Py_38_CUDA_102_cuDNN_810:
configuration: ubuntu_1804_py_38_cuda_102_cudnn_810
container_image: pytorchms.azurecr.io/ubuntu_1804_py_38_cuda_102_cudnn_8_dev
CUDA_VERSION: 102
Py_37_CUDA_101_cuDNN_765:
configuration: ubuntu_1804_py_37_cuda_101_cudnn_765
container_image: pytorchms.azurecr.io/ubuntu_1804_py_37_cuda_101_cudnn_7_dev
CUDA_VERSION: 101
- template: job_templates/build-verify-publish-template-win.yml
parameters:
name: windows_2019_CPU
pool: 'PyTorch-Win-CPU'
verify_stage: True
is_official_build: True
customMatrixes:
Py_38:
configuration: windows_2019_py_38_cpu
Py_37:
configuration: windows_2019_py_37_cpu
- template: job_templates/build-verify-publish-template-win.yml
parameters:
name: windows_2019_GPU
pool: 'PyTorch-Win-GPU'
verify_stage: True
is_official_build: True
customMatrixes:
Py_39_CUDA_112_cuDNN_810:
configuration: windows_2019_py_39_cuda_112_cudnn_810
CUDA_VERSION: 112
Py_38_CUDA_102_cuDNN_765:
configuration: windows_2019_py_38_cuda_102_cudnn_765
CUDA_VERSION: 102
Py_37_CUDA_101_cuDNN_764:
configuration: windows_2019_py_37_cuda_101_cudnn_764
CUDA_VERSION: 101
- stage: 'Publish'
displayName: 'Publish PyTorch wheels'
dependsOn: Verify
condition: succeeded()
jobs:
- template: job_templates/build-verify-publish-template-unix.yml
parameters:
name: ubuntu_1804_CPU_docker
pool: 'PyTorch-Linux-CPU'
container_endpoint: pytorchms.azurecr.io
publish_stage: True
is_official_build: True
customMatrixes:
Py_38:
configuration: ubuntu_1804_py_38_cpu
container_image: pytorchms.azurecr.io/ubuntu_1804_py_38_cpu_dev
Py_37:
configuration: ubuntu_1804_py_37_cpu
container_image: pytorchms.azurecr.io/ubuntu_1804_py_37_cpu_dev
- template: job_templates/build-verify-publish-template-unix.yml
parameters:
name: ubuntu_1804_GPU_docker
pool: 'PyTorch-Linux-GPU'
container_endpoint: pytorchms.azurecr.io
publish_stage: True
is_official_build: True
customMatrixes:
Py_39_CUDA_112_cuDNN_810:
configuration: ubuntu_1804_py_39_cuda_112_cudnn_810
container_image: pytorchms.azurecr.io/ubuntu_1804_py_39_cuda_112_cudnn_8_dev
CUDA_VERSION: 112
Py_38_CUDA_102_cuDNN_810:
configuration: ubuntu_1804_py_38_cuda_102_cudnn_810
container_image: pytorchms.azurecr.io/ubuntu_1804_py_38_cuda_102_cudnn_8_dev
CUDA_VERSION: 102
Py_37_CUDA_101_cuDNN_765:
configuration: ubuntu_1804_py_37_cuda_101_cudnn_765
container_image: pytorchms.azurecr.io/ubuntu_1804_py_37_cuda_101_cudnn_7_dev
CUDA_VERSION: 101
- template: job_templates/build-verify-publish-template-win.yml
parameters:
name: windows_2019_CPU
pool: 'PyTorch-Win-CPU'
publish_stage: True
is_official_build: True
customMatrixes:
Py_38:
configuration: windows_2019_py_38_cpu
Py_37:
configuration: windows_2019_py_37_cpu
- template: job_templates/build-verify-publish-template-win.yml
parameters:
name: windows_2019_GPU
pool: 'PyTorch-Win-GPU'
publish_stage: True
is_official_build: True
customMatrixes:
Py_39_CUDA_112_cuDNN_810:
configuration: windows_2019_py_39_cuda_112_cudnn_810
CUDA_VERSION: 112
Py_38_CUDA_102_cuDNN_765:
configuration: windows_2019_py_38_cuda_102_cudnn_765
CUDA_VERSION: 102
Py_37_CUDA_101_cuDNN_764:
configuration: windows_2019_py_37_cuda_101_cudnn_764
CUDA_VERSION: 101

View File

@ -1,4 +0,0 @@
# We do not use this library in our Bazel build. It contains an
# infinitely recursing symlink that makes Bazel very unhappy.
third_party/ittapi/
third_party/opentelemetry-cpp

108
.bazelrc
View File

@ -1,11 +1,10 @@
build --cxxopt=--std=c++17
build --copt=--std=c++14
build --copt=-I.
# Bazel does not support including its cc_library targets as system
# headers. We work around this for generated code
# (e.g. c10/macros/cmake_macros.h) by making the generated directory a
# system include path.
build --copt=-isystem --copt bazel-out/k8-fastbuild/bin
build --copt=-isystem --copt bazel-out/darwin-fastbuild/bin
build --experimental_ui_max_stdouterr_bytes=2048576
# Configuration to disable tty features for environments like CI
@ -13,102 +12,15 @@ build:no-tty --curses no
build:no-tty --progress_report_interval 10
build:no-tty --show_progress_rate_limit 10
# Build with GPU support by default.
build --define=cuda=true
# rules_cuda configuration
build --@rules_cuda//cuda:enable_cuda
build --@rules_cuda//cuda:cuda_targets=sm_52
build --@rules_cuda//cuda:compiler=nvcc
build --repo_env=CUDA_PATH=/usr/local/cuda
# Configuration to build without GPU support
build:cpu-only --define=cuda=false
# Configuration to build with GPU support
build:gpu --define=cuda=true
# define a separate build folder for faster switching between configs
build:cpu-only --platform_suffix=-cpu-only
build:gpu --platform_suffix=-gpu
# See the note on the config-less build for details about why we are
# doing this. We must also do it for the "-cpu-only" platform suffix.
build --copt=-isystem --copt=bazel-out/k8-fastbuild-cpu-only/bin
# doing this. We must also do it for the "-gpu" platform suffix.
build --copt=-isystem --copt=bazel-out/k8-fastbuild-gpu/bin
# rules_cuda configuration
build:cpu-only --@rules_cuda//cuda:enable_cuda=False
# Definition of --config=shell
# interactive shell immediately before execution
build:shell --run_under="//tools/bazel_tools:shellwrap"
# Disable all warnings for external repositories. We don't care about
# their warnings.
build --per_file_copt=^external/@-w
# Set additional warnings to error level.
#
# Implementation notes:
# * we use file extensions to determine if we are using the C++
# compiler or the cuda compiler
# * we use ^// at the start of the regex to only permit matching
# PyTorch files. This excludes external repos.
#
# Note that because this is logically a command-line flag, it is
# considered the word on what warnings are enabled. This has the
# unfortunate consequence of preventing us from disabling an error at
# the target level because those flags will come before these flags in
# the action invocation. Instead we provide per-file exceptions after
# this.
#
# On the bright side, this means we don't have to more broadly apply
# the exceptions to an entire target.
#
# Looking for CUDA flags? We have a cu_library macro that we can edit
# directly. Look in //tools/rules:cu.bzl for details. Editing the
# macro over this has the following advantages:
# * making changes does not require discarding the Bazel analysis
# cache
# * it allows for selective overrides on individual targets since the
# macro-level opts will come earlier than target level overrides
build --per_file_copt='^//.*\.(cpp|cc)$'@-Werror=all
# The following warnings come from -Wall. We downgrade them from error
# to warnings here.
#
# We intentionally use #pragma unroll, which is compiler specific.
build --per_file_copt='^//.*\.(cpp|cc)$'@-Wno-error=unknown-pragmas
build --per_file_copt='^//.*\.(cpp|cc)$'@-Werror=extra
# The following warnings come from -Wextra. We downgrade them from error
# to warnings here.
#
# unused-parameter-compare has a tremendous amount of violations in the
# codebase. It will be a lot of work to fix them, just disable it for
# now.
build --per_file_copt='^//.*\.(cpp|cc)$'@-Wno-unused-parameter
# missing-field-parameters has both a large number of violations in
# the codebase, but it also is used pervasively in the Python C
# API. There are a couple of catches though:
# * we use multiple versions of the Python API and hence have
# potentially multiple different versions of each relevant
# struct. They may have different numbers of fields. It will be
# unwieldy to support multiple versions in the same source file.
# * Python itself for many of these structs recommends only
# initializing a subset of the fields. We should respect the API
# usage conventions of our dependencies.
#
# Hence, we just disable this warning altogether. We may want to clean
# up some of the clear-cut cases that could be risky, but we still
# likely want to have this disabled for the most part.
build --per_file_copt='^//.*\.(cpp|cc)$'@-Wno-missing-field-initializers
build --per_file_copt='^//.*\.(cpp|cc)$'@-Wno-unused-function
build --per_file_copt='^//.*\.(cpp|cc)$'@-Wno-unused-variable
build --per_file_copt='//:aten/src/ATen/RegisterCompositeExplicitAutograd\.cpp$'@-Wno-error=unused-function
build --per_file_copt='//:aten/src/ATen/RegisterCompositeImplicitAutograd\.cpp$'@-Wno-error=unused-function
build --per_file_copt='//:aten/src/ATen/RegisterMkldnnCPU\.cpp$'@-Wno-error=unused-function
build --per_file_copt='//:aten/src/ATen/RegisterNestedTensorCPU\.cpp$'@-Wno-error=unused-function
build --per_file_copt='//:aten/src/ATen/RegisterQuantizedCPU\.cpp$'@-Wno-error=unused-function
build --per_file_copt='//:aten/src/ATen/RegisterSparseCPU\.cpp$'@-Wno-error=unused-function
build --per_file_copt='//:aten/src/ATen/RegisterSparseCsrCPU\.cpp$'@-Wno-error=unused-function
build --per_file_copt='//:aten/src/ATen/RegisterNestedTensorMeta\.cpp$'@-Wno-error=unused-function
build --per_file_copt='//:aten/src/ATen/RegisterSparseMeta\.cpp$'@-Wno-error=unused-function
build --per_file_copt='//:aten/src/ATen/RegisterQuantizedMeta\.cpp$'@-Wno-error=unused-function
build --per_file_copt='//:aten/src/ATen/RegisterZeroTensor\.cpp$'@-Wno-error=unused-function
build --per_file_copt='//:torch/csrc/lazy/generated/RegisterAutogradLazy\.cpp$'@-Wno-error=unused-function
build --per_file_copt='//:torch/csrc/lazy/generated/RegisterLazy\.cpp$'@-Wno-error=unused-function
build:gpu --@rules_cuda//cuda:enable_cuda
build:gpu --@rules_cuda//cuda:cuda_targets=sm_52
build:gpu --@rules_cuda//cuda:compiler=nvcc
build:gpu --repo_env=CUDA_PATH=/usr/local/cuda

View File

@ -1 +1 @@
6.1.1
4.2.1

View File

@ -1,26 +0,0 @@
[pt]
is_oss=1
[buildfile]
name = BUCK.oss
includes = //tools/build_defs/select.bzl
[repositories]
bazel_skylib = third_party/bazel-skylib/
ovr_config = .
[download]
in_build = true
[cxx]
cxxflags = -std=c++17
ldflags = -Wl,--no-undefined
should_remap_host_platform = true
cpp = /usr/bin/clang
cc = /usr/bin/clang
cxx = /usr/bin/clang++
cxxpp = /usr/bin/clang++
ld = /usr/bin/clang++
[project]
default_flavors_mode=all

View File

@ -1,36 +0,0 @@
set -ex
LOCAL_DIR=$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)
ROOT_DIR=$(cd "$LOCAL_DIR"/../.. && pwd)
TEST_DIR="$ROOT_DIR/test"
gtest_reports_dir="${TEST_DIR}/test-reports/cpp"
pytest_reports_dir="${TEST_DIR}/test-reports/python"
# Figure out which Python to use
PYTHON="$(which python)"
if [[ "${BUILD_ENVIRONMENT}" =~ py((2|3)\.?[0-9]?\.?[0-9]?) ]]; then
PYTHON=$(which "python${BASH_REMATCH[1]}")
fi
if [[ "${BUILD_ENVIRONMENT}" == *rocm* ]]; then
# HIP_PLATFORM is auto-detected by hipcc; unset to avoid build errors
unset HIP_PLATFORM
if which sccache > /dev/null; then
# Save sccache logs to file
sccache --stop-server || true
rm -f ~/sccache_error.log || true
SCCACHE_ERROR_LOG=~/sccache_error.log SCCACHE_IDLE_TIMEOUT=0 sccache --start-server
# Report sccache stats for easier debugging
sccache --zero-stats
fi
fi
# /usr/local/caffe2 is where the cpp bits are installed to in cmake-only
# builds. In +python builds the cpp tests are copied to /usr/local/caffe2 so
# that the test code in .ci/test.sh is the same
INSTALL_PREFIX="/usr/local/caffe2"
mkdir -p "$gtest_reports_dir" || true
mkdir -p "$pytest_reports_dir" || true
mkdir -p "$INSTALL_PREFIX" || true

View File

@ -1,172 +0,0 @@
#!/bin/bash
# shellcheck source=./common.sh
source "$(dirname "${BASH_SOURCE[0]}")/common.sh"
if [[ ${BUILD_ENVIRONMENT} == *onnx* ]]; then
pip install click mock tabulate networkx==2.0
pip -q install --user "file:///var/lib/jenkins/workspace/third_party/onnx#egg=onnx"
fi
# Skip tests in environments where they are not built/applicable
if [[ "${BUILD_ENVIRONMENT}" == *-android* ]]; then
echo 'Skipping tests'
exit 0
fi
if [[ "${BUILD_ENVIRONMENT}" == *-rocm* ]]; then
# temporary to locate some kernel issues on the CI nodes
export HSAKMT_DEBUG_LEVEL=4
fi
# These additional packages are needed for circleci ROCm builds.
if [[ $BUILD_ENVIRONMENT == *rocm* ]]; then
# Need networkx 2.0 because bellmand_ford was moved in 2.1 . Scikit-image by
# defaults installs the most recent networkx version, so we install this lower
# version explicitly before scikit-image pulls it in as a dependency
pip install networkx==2.0
# click - onnx
pip install --progress-bar off click protobuf tabulate virtualenv mock typing-extensions
fi
# Find where cpp tests and Caffe2 itself are installed
if [[ "$BUILD_ENVIRONMENT" == *cmake* ]]; then
# For cmake only build we install everything into /usr/local
cpp_test_dir="$INSTALL_PREFIX/cpp_test"
ld_library_path="$INSTALL_PREFIX/lib"
else
# For Python builds we install into python
# cd to /usr first so the python import doesn't get confused by any 'caffe2'
# directory in cwd
python_installation="$(dirname $(dirname $(cd /usr && $PYTHON -c 'import os; import caffe2; print(os.path.realpath(caffe2.__file__))')))"
caffe2_pypath="$python_installation/caffe2"
cpp_test_dir="$python_installation/torch/test"
ld_library_path="$python_installation/torch/lib"
fi
################################################################################
# C++ tests #
################################################################################
# Only run cpp tests in the first shard, don't run cpp tests a second time in the second shard
if [[ "${SHARD_NUMBER:-1}" == "1" ]]; then
echo "Running C++ tests.."
for test in $(find "$cpp_test_dir" -executable -type f); do
case "$test" in
# skip tests we know are hanging or bad
*/mkl_utils_test|*/aten/integer_divider_test)
continue
;;
*/scalar_tensor_test|*/basic|*/native_test)
if [[ "$BUILD_ENVIRONMENT" == *rocm* ]]; then
continue
else
LD_LIBRARY_PATH="$ld_library_path" "$test"
fi
;;
*/*_benchmark)
LD_LIBRARY_PATH="$ld_library_path" "$test" --benchmark_color=false
;;
*)
# Currently, we use a mixture of gtest (caffe2) and Catch2 (ATen). While
# planning to migrate to gtest as the common PyTorch c++ test suite, we
# currently do NOT use the xml test reporter, because Catch doesn't
# support multiple reporters
# c.f. https://github.com/catchorg/Catch2/blob/master/docs/release-notes.md#223
# which means that enabling XML output means you lose useful stdout
# output for Jenkins. It's more important to have useful console
# output than it is to have XML output for Jenkins.
# Note: in the future, if we want to use xml test reporter once we switch
# to all gtest, one can simply do:
LD_LIBRARY_PATH="$ld_library_path" \
"$test" --gtest_output=xml:"$gtest_reports_dir/$(basename $test).xml"
;;
esac
done
fi
################################################################################
# Python tests #
################################################################################
if [[ "$BUILD_ENVIRONMENT" == *cmake* ]]; then
exit 0
fi
# If pip is installed as root, we must use sudo.
# CircleCI docker images could install conda as jenkins user, or use the OS's python package.
PIP=$(which pip)
PIP_USER=$(stat --format '%U' $PIP)
CURRENT_USER=$(id -u -n)
if [[ "$PIP_USER" = root && "$CURRENT_USER" != root ]]; then
MAYBE_SUDO=sudo
fi
# Uninstall pre-installed hypothesis and coverage to use an older version as newer
# versions remove the timeout parameter from settings which ideep/conv_transpose_test.py uses
$MAYBE_SUDO pip -q uninstall -y hypothesis
$MAYBE_SUDO pip -q uninstall -y coverage
# "pip install hypothesis==3.44.6" from official server is unreliable on
# CircleCI, so we host a copy on S3 instead
$MAYBE_SUDO pip -q install attrs==18.1.0 -f https://s3.amazonaws.com/ossci-linux/wheels/attrs-18.1.0-py2.py3-none-any.whl
$MAYBE_SUDO pip -q install coverage==4.5.1 -f https://s3.amazonaws.com/ossci-linux/wheels/coverage-4.5.1-cp36-cp36m-macosx_10_12_x86_64.whl
$MAYBE_SUDO pip -q install hypothesis==3.44.6 -f https://s3.amazonaws.com/ossci-linux/wheels/hypothesis-3.44.6-py3-none-any.whl
# Collect additional tests to run (outside caffe2/python)
EXTRA_TESTS=()
# CUDA builds always include NCCL support
if [[ "$BUILD_ENVIRONMENT" == *-cuda* ]] || [[ "$BUILD_ENVIRONMENT" == *-rocm* ]]; then
EXTRA_TESTS+=("$caffe2_pypath/contrib/nccl")
fi
rocm_ignore_test=()
if [[ $BUILD_ENVIRONMENT == *-rocm* ]]; then
# Currently these tests are failing on ROCM platform:
# On ROCm, RCCL (distributed) development isn't complete.
# https://github.com/ROCmSoftwarePlatform/rccl
rocm_ignore_test+=("--ignore $caffe2_pypath/python/data_parallel_model_test.py")
# This test has been flaky in ROCm CI (but note the tests are
# cpu-only so should be unrelated to ROCm)
rocm_ignore_test+=("--ignore $caffe2_pypath/python/operator_test/blobs_queue_db_test.py")
# This test is skipped on Jenkins(compiled without MKL) and otherwise known flaky
rocm_ignore_test+=("--ignore $caffe2_pypath/python/ideep/convfusion_op_test.py")
# This test is skipped on Jenkins(compiled without MKL) and causing segfault on Circle
rocm_ignore_test+=("--ignore $caffe2_pypath/python/ideep/pool_op_test.py")
fi
echo "Running Python tests.."
# locale setting is required by click package
for loc in "en_US.utf8" "C.UTF-8"; do
if locale -a | grep "$loc" >/dev/null 2>&1; then
export LC_ALL="$loc"
export LANG="$loc"
break;
fi
done
# Some Caffe2 tests fail when run using AVX512 ISA, see https://github.com/pytorch/pytorch/issues/66111
export DNNL_MAX_CPU_ISA=AVX2
# Should still run even in the absence of SHARD_NUMBER
if [[ "${SHARD_NUMBER:-1}" == "1" ]]; then
# TODO(sdym@meta.com) remove this when the linked issue resolved.
# py is temporary until https://github.com/Teemu/pytest-sugar/issues/241 is fixed
pip install --user py==1.11.0
pip install --user pytest-sugar
# NB: Warnings are disabled because they make it harder to see what
# the actual erroring test is
"$PYTHON" \
-m pytest \
-x \
-v \
--disable-warnings \
--junit-xml="$pytest_reports_dir/result.xml" \
--ignore "$caffe2_pypath/python/test/executor_test.py" \
--ignore "$caffe2_pypath/python/operator_test/matmul_op_test.py" \
--ignore "$caffe2_pypath/python/operator_test/pack_ops_test.py" \
--ignore "$caffe2_pypath/python/mkl/mkl_sbn_speed_test.py" \
--ignore "$caffe2_pypath/python/trt/test_pt_onnx_trt.py" \
${rocm_ignore_test[@]} \
"$caffe2_pypath/python" \
"${EXTRA_TESTS[@]}"
fi

View File

@ -1,38 +0,0 @@
# Docker images for GitHub CI and CD
This directory contains everything needed to build the Docker images
that are used in our CI.
The Dockerfiles located in subdirectories are parameterized to
conditionally run build stages depending on build arguments passed to
`docker build`. This lets us use only a few Dockerfiles for many
images. The different configurations are identified by a freeform
string that we call a _build environment_. This string is persisted in
each image as the `BUILD_ENVIRONMENT` environment variable.
See `build.sh` for valid build environments (it's the giant switch).
## Docker CI builds
* `build.sh` -- dispatch script to launch all builds
* `common` -- scripts used to execute individual Docker build stages
* `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
### Docker CD builds
* `conda` - Dockerfile and build.sh to build Docker images used in nightly conda builds
* `manywheel` - Dockerfile and build.sh to build Docker images used in nightly manywheel builds
* `libtorch` - Dockerfile and build.sh to build Docker images used in nightly libtorch builds
## Usage
```bash
# Build a specific image
./build.sh pytorch-linux-bionic-py3.8-gcc9 -t myimage:latest
# Set flags (see build.sh) and build image
sudo bash -c 'PROTOBUF=1 ./build.sh pytorch-linux-bionic-py3.8-gcc9 -t myimage:latest
```

View File

@ -1,5 +0,0 @@
0.7b
manylinux_2_17
rocm6.2
9be04068c3c0857a4cfd17d7e39e71d0423ebac2
3e9e1959d23b93d78a08fcc5f868125dc3854dece32fd9458be9ef4467982291

View File

@ -1,583 +0,0 @@
#!/bin/bash
set -ex
image="$1"
shift
if [ -z "${image}" ]; then
echo "Usage: $0 IMAGE"
exit 1
fi
function extract_version_from_image_name() {
eval export $2=$(echo "${image}" | perl -n -e"/$1(\d+(\.\d+)?(\.\d+)?)/ && print \$1")
if [ "x${!2}" = x ]; then
echo "variable '$2' not correctly parsed from image='$image'"
exit 1
fi
}
function extract_all_from_image_name() {
# parts $image into array, splitting on '-'
keep_IFS="$IFS"
IFS="-"
declare -a parts=($image)
IFS="$keep_IFS"
unset keep_IFS
for part in "${parts[@]}"; do
name=$(echo "${part}" | perl -n -e"/([a-zA-Z]+)\d+(\.\d+)?(\.\d+)?/ && print \$1")
vername="${name^^}_VERSION"
# "py" is the odd one out, needs this special case
if [ "x${name}" = xpy ]; then
vername=ANACONDA_PYTHON_VERSION
fi
# skip non-conforming fields such as "pytorch", "linux" or "bionic" without version string
if [ -n "${name}" ]; then
extract_version_from_image_name "${name}" "${vername}"
fi
done
}
# Use the same pre-built XLA test image from PyTorch/XLA
if [[ "$image" == *xla* ]]; then
echo "Using pre-built XLA test image..."
exit 0
fi
if [[ "$image" == *-focal* ]]; then
UBUNTU_VERSION=20.04
elif [[ "$image" == *-jammy* ]]; then
UBUNTU_VERSION=22.04
elif [[ "$image" == *ubuntu* ]]; then
extract_version_from_image_name ubuntu UBUNTU_VERSION
elif [[ "$image" == *centos* ]]; then
extract_version_from_image_name centos CENTOS_VERSION
fi
if [ -n "${UBUNTU_VERSION}" ]; then
OS="ubuntu"
elif [ -n "${CENTOS_VERSION}" ]; then
OS="centos"
else
echo "Unable to derive operating system base..."
exit 1
fi
DOCKERFILE="${OS}/Dockerfile"
# When using ubuntu - 22.04, start from Ubuntu docker image, instead of nvidia/cuda docker image.
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"
elif [[ "$image" == *linter* ]]; then
# Use a separate Dockerfile for linter to keep a small image size
DOCKERFILE="linter/Dockerfile"
fi
# CMake 3.18 is needed to support CUDA17 language variant
CMAKE_VERSION=3.18.5
_UCX_COMMIT=7bb2722ff2187a0cad557ae4a6afa090569f83fb
_UCC_COMMIT=20eae37090a4ce1b32bcce6144ccad0b49943e0b
# It's annoying to rename jobs every time you want to rewrite a
# configuration, so we hardcode everything here rather than do it
# from scratch
case "$image" in
pytorch-linux-focal-cuda12.4-cudnn9-py3-gcc9)
CUDA_VERSION=12.4.1
CUDNN_VERSION=9
ANACONDA_PYTHON_VERSION=3.10
GCC_VERSION=9
PROTOBUF=yes
DB=yes
VISION=yes
KATEX=yes
UCX_COMMIT=${_UCX_COMMIT}
UCC_COMMIT=${_UCC_COMMIT}
CONDA_CMAKE=yes
TRITON=yes
;;
pytorch-linux-focal-cuda12.1-cudnn9-py3-gcc9)
CUDA_VERSION=12.1.1
CUDNN_VERSION=9
ANACONDA_PYTHON_VERSION=3.10
GCC_VERSION=9
PROTOBUF=yes
DB=yes
VISION=yes
KATEX=yes
UCX_COMMIT=${_UCX_COMMIT}
UCC_COMMIT=${_UCC_COMMIT}
CONDA_CMAKE=yes
TRITON=yes
;;
pytorch-linux-focal-cuda12.4-cudnn9-py3-gcc9-inductor-benchmarks)
CUDA_VERSION=12.4.1
CUDNN_VERSION=9
ANACONDA_PYTHON_VERSION=3.10
GCC_VERSION=9
PROTOBUF=yes
DB=yes
VISION=yes
KATEX=yes
UCX_COMMIT=${_UCX_COMMIT}
UCC_COMMIT=${_UCC_COMMIT}
CONDA_CMAKE=yes
TRITON=yes
INDUCTOR_BENCHMARKS=yes
;;
pytorch-linux-focal-cuda12.1-cudnn9-py3-gcc9-inductor-benchmarks)
CUDA_VERSION=12.1.1
CUDNN_VERSION=9
ANACONDA_PYTHON_VERSION=3.10
GCC_VERSION=9
PROTOBUF=yes
DB=yes
VISION=yes
KATEX=yes
UCX_COMMIT=${_UCX_COMMIT}
UCC_COMMIT=${_UCC_COMMIT}
CONDA_CMAKE=yes
TRITON=yes
INDUCTOR_BENCHMARKS=yes
;;
pytorch-linux-focal-cuda12.1-cudnn9-py3.12-gcc9-inductor-benchmarks)
CUDA_VERSION=12.1.1
CUDNN_VERSION=9
ANACONDA_PYTHON_VERSION=3.12
GCC_VERSION=9
PROTOBUF=yes
DB=yes
VISION=yes
KATEX=yes
UCX_COMMIT=${_UCX_COMMIT}
UCC_COMMIT=${_UCC_COMMIT}
CONDA_CMAKE=yes
TRITON=yes
INDUCTOR_BENCHMARKS=yes
;;
pytorch-linux-focal-cuda12.4-cudnn9-py3.12-gcc9-inductor-benchmarks)
CUDA_VERSION=12.4.1
CUDNN_VERSION=9
ANACONDA_PYTHON_VERSION=3.12
GCC_VERSION=9
PROTOBUF=yes
DB=yes
VISION=yes
KATEX=yes
UCX_COMMIT=${_UCX_COMMIT}
UCC_COMMIT=${_UCC_COMMIT}
CONDA_CMAKE=yes
TRITON=yes
INDUCTOR_BENCHMARKS=yes
;;
pytorch-linux-focal-cuda11.8-cudnn9-py3-gcc9)
CUDA_VERSION=11.8.0
CUDNN_VERSION=9
ANACONDA_PYTHON_VERSION=3.10
GCC_VERSION=9
PROTOBUF=yes
DB=yes
VISION=yes
KATEX=yes
UCX_COMMIT=${_UCX_COMMIT}
UCC_COMMIT=${_UCC_COMMIT}
CONDA_CMAKE=yes
TRITON=yes
;;
pytorch-linux-focal-cuda12.4-cudnn9-py3-gcc9)
CUDA_VERSION=12.4.1
CUDNN_VERSION=9
ANACONDA_PYTHON_VERSION=3.10
GCC_VERSION=9
PROTOBUF=yes
DB=yes
VISION=yes
KATEX=yes
UCX_COMMIT=${_UCX_COMMIT}
UCC_COMMIT=${_UCC_COMMIT}
CONDA_CMAKE=yes
TRITON=yes
;;
pytorch-linux-focal-cuda12.1-cudnn9-py3-gcc9)
CUDA_VERSION=12.1.1
CUDNN_VERSION=9
ANACONDA_PYTHON_VERSION=3.10
GCC_VERSION=9
PROTOBUF=yes
DB=yes
VISION=yes
KATEX=yes
UCX_COMMIT=${_UCX_COMMIT}
UCC_COMMIT=${_UCC_COMMIT}
CONDA_CMAKE=yes
TRITON=yes
;;
pytorch-linux-focal-cuda12.4-cudnn9-py3-gcc9)
CUDA_VERSION=12.4.1
CUDNN_VERSION=9
ANACONDA_PYTHON_VERSION=3.10
GCC_VERSION=9
PROTOBUF=yes
DB=yes
VISION=yes
KATEX=yes
UCX_COMMIT=${_UCX_COMMIT}
UCC_COMMIT=${_UCC_COMMIT}
CONDA_CMAKE=yes
TRITON=yes
;;
pytorch-linux-focal-py3-clang10-onnx)
ANACONDA_PYTHON_VERSION=3.9
CLANG_VERSION=10
PROTOBUF=yes
DB=yes
VISION=yes
CONDA_CMAKE=yes
ONNX=yes
;;
pytorch-linux-focal-py3-clang9-android-ndk-r21e)
ANACONDA_PYTHON_VERSION=3.9
CLANG_VERSION=9
LLVMDEV=yes
PROTOBUF=yes
ANDROID=yes
ANDROID_NDK_VERSION=r21e
GRADLE_VERSION=6.8.3
NINJA_VERSION=1.9.0
;;
pytorch-linux-focal-py3.9-clang10)
ANACONDA_PYTHON_VERSION=3.9
CLANG_VERSION=10
PROTOBUF=yes
DB=yes
VISION=yes
VULKAN_SDK_VERSION=1.2.162.1
SWIFTSHADER=yes
CONDA_CMAKE=yes
TRITON=yes
;;
pytorch-linux-focal-py3.11-clang10)
ANACONDA_PYTHON_VERSION=3.11
CLANG_VERSION=10
PROTOBUF=yes
DB=yes
VISION=yes
VULKAN_SDK_VERSION=1.2.162.1
SWIFTSHADER=yes
CONDA_CMAKE=yes
TRITON=yes
;;
pytorch-linux-focal-py3.9-gcc9)
ANACONDA_PYTHON_VERSION=3.9
GCC_VERSION=9
PROTOBUF=yes
DB=yes
VISION=yes
CONDA_CMAKE=yes
TRITON=yes
;;
pytorch-linux-focal-rocm-n-1-py3)
ANACONDA_PYTHON_VERSION=3.10
GCC_VERSION=9
PROTOBUF=yes
DB=yes
VISION=yes
ROCM_VERSION=6.1
NINJA_VERSION=1.9.0
CONDA_CMAKE=yes
TRITON=yes
;;
pytorch-linux-focal-rocm-n-py3)
ANACONDA_PYTHON_VERSION=3.10
GCC_VERSION=9
PROTOBUF=yes
DB=yes
VISION=yes
ROCM_VERSION=6.2
NINJA_VERSION=1.9.0
CONDA_CMAKE=yes
TRITON=yes
;;
pytorch-linux-jammy-xpu-2024.0-py3)
ANACONDA_PYTHON_VERSION=3.9
GCC_VERSION=11
PROTOBUF=yes
DB=yes
VISION=yes
XPU_VERSION=0.5
NINJA_VERSION=1.9.0
CONDA_CMAKE=yes
TRITON=yes
;;
pytorch-linux-jammy-py3.9-gcc11-inductor-benchmarks)
ANACONDA_PYTHON_VERSION=3.9
GCC_VERSION=11
PROTOBUF=yes
DB=yes
VISION=yes
KATEX=yes
CONDA_CMAKE=yes
TRITON=yes
DOCS=yes
INDUCTOR_BENCHMARKS=yes
;;
pytorch-linux-jammy-cuda11.8-cudnn9-py3.9-clang12)
ANACONDA_PYTHON_VERSION=3.9
CUDA_VERSION=11.8
CUDNN_VERSION=9
CLANG_VERSION=12
PROTOBUF=yes
DB=yes
VISION=yes
TRITON=yes
;;
pytorch-linux-jammy-py3-clang12-asan)
ANACONDA_PYTHON_VERSION=3.9
CLANG_VERSION=12
PROTOBUF=yes
DB=yes
VISION=yes
CONDA_CMAKE=yes
TRITON=yes
;;
pytorch-linux-jammy-py3-clang15-asan)
ANACONDA_PYTHON_VERSION=3.10
CLANG_VERSION=15
CONDA_CMAKE=yes
VISION=yes
;;
pytorch-linux-jammy-py3.9-gcc11)
ANACONDA_PYTHON_VERSION=3.9
GCC_VERSION=11
PROTOBUF=yes
DB=yes
VISION=yes
KATEX=yes
CONDA_CMAKE=yes
TRITON=yes
DOCS=yes
UNINSTALL_DILL=yes
;;
pytorch-linux-jammy-py3-clang12-executorch)
ANACONDA_PYTHON_VERSION=3.10
CLANG_VERSION=12
CONDA_CMAKE=yes
EXECUTORCH=yes
;;
pytorch-linux-jammy-py3.12-halide)
CUDA_VERSION=12.4
ANACONDA_PYTHON_VERSION=3.12
GCC_VERSION=11
CONDA_CMAKE=yes
HALIDE=yes
TRITON=yes
;;
pytorch-linux-focal-linter)
# TODO: Use 3.9 here because of this issue https://github.com/python/mypy/issues/13627.
# We will need to update mypy version eventually, but that's for another day. The task
# would be to upgrade mypy to 1.0.0 with Python 3.11
ANACONDA_PYTHON_VERSION=3.9
CONDA_CMAKE=yes
;;
pytorch-linux-jammy-cuda11.8-cudnn9-py3.9-linter)
ANACONDA_PYTHON_VERSION=3.9
CUDA_VERSION=11.8
CONDA_CMAKE=yes
;;
pytorch-linux-jammy-aarch64-py3.10-gcc11)
ANACONDA_PYTHON_VERSION=3.10
GCC_VERSION=11
ACL=yes
PROTOBUF=yes
DB=yes
VISION=yes
CONDA_CMAKE=yes
# snadampal: skipping sccache due to the following issue
# https://github.com/pytorch/pytorch/issues/121559
SKIP_SCCACHE_INSTALL=yes
# snadampal: skipping llvm src build install because the current version
# from pytorch/llvm:9.0.1 is x86 specific
SKIP_LLVM_SRC_BUILD_INSTALL=yes
;;
pytorch-linux-jammy-aarch64-py3.10-gcc11-inductor-benchmarks)
ANACONDA_PYTHON_VERSION=3.10
GCC_VERSION=11
ACL=yes
PROTOBUF=yes
DB=yes
VISION=yes
CONDA_CMAKE=yes
# snadampal: skipping sccache due to the following issue
# https://github.com/pytorch/pytorch/issues/121559
SKIP_SCCACHE_INSTALL=yes
# snadampal: skipping llvm src build install because the current version
# from pytorch/llvm:9.0.1 is x86 specific
SKIP_LLVM_SRC_BUILD_INSTALL=yes
INDUCTOR_BENCHMARKS=yes
;;
*)
# Catch-all for builds that are not hardcoded.
PROTOBUF=yes
DB=yes
VISION=yes
echo "image '$image' did not match an existing build configuration"
if [[ "$image" == *py* ]]; then
extract_version_from_image_name py ANACONDA_PYTHON_VERSION
fi
if [[ "$image" == *cuda* ]]; then
extract_version_from_image_name cuda CUDA_VERSION
extract_version_from_image_name cudnn CUDNN_VERSION
fi
if [[ "$image" == *rocm* ]]; then
extract_version_from_image_name rocm ROCM_VERSION
NINJA_VERSION=1.9.0
TRITON=yes
# To ensure that any ROCm config will build using conda cmake
# and thus have LAPACK/MKL enabled
CONDA_CMAKE=yes
fi
if [[ "$image" == *centos7* ]]; then
NINJA_VERSION=1.10.2
fi
if [[ "$image" == *gcc* ]]; then
extract_version_from_image_name gcc GCC_VERSION
fi
if [[ "$image" == *clang* ]]; then
extract_version_from_image_name clang CLANG_VERSION
fi
if [[ "$image" == *devtoolset* ]]; then
extract_version_from_image_name devtoolset DEVTOOLSET_VERSION
fi
if [[ "$image" == *glibc* ]]; then
extract_version_from_image_name glibc GLIBC_VERSION
fi
if [[ "$image" == *cmake* ]]; then
extract_version_from_image_name cmake CMAKE_VERSION
fi
;;
esac
tmp_tag=$(basename "$(mktemp -u)" | tr '[:upper:]' '[:lower:]')
#when using cudnn version 8 install it separately from cuda
if [[ "$image" == *cuda* && ${OS} == "ubuntu" ]]; then
IMAGE_NAME="nvidia/cuda:${CUDA_VERSION}-cudnn${CUDNN_VERSION}-devel-ubuntu${UBUNTU_VERSION}"
if [[ ${CUDNN_VERSION} == 9 ]]; then
IMAGE_NAME="nvidia/cuda:${CUDA_VERSION}-devel-ubuntu${UBUNTU_VERSION}"
fi
fi
# Build image
docker build \
--no-cache \
--progress=plain \
--build-arg "BUILD_ENVIRONMENT=${image}" \
--build-arg "PROTOBUF=${PROTOBUF:-}" \
--build-arg "LLVMDEV=${LLVMDEV:-}" \
--build-arg "DB=${DB:-}" \
--build-arg "VISION=${VISION:-}" \
--build-arg "UBUNTU_VERSION=${UBUNTU_VERSION}" \
--build-arg "CENTOS_VERSION=${CENTOS_VERSION}" \
--build-arg "DEVTOOLSET_VERSION=${DEVTOOLSET_VERSION}" \
--build-arg "GLIBC_VERSION=${GLIBC_VERSION}" \
--build-arg "CLANG_VERSION=${CLANG_VERSION}" \
--build-arg "ANACONDA_PYTHON_VERSION=${ANACONDA_PYTHON_VERSION}" \
--build-arg "GCC_VERSION=${GCC_VERSION}" \
--build-arg "CUDA_VERSION=${CUDA_VERSION}" \
--build-arg "CUDNN_VERSION=${CUDNN_VERSION}" \
--build-arg "TENSORRT_VERSION=${TENSORRT_VERSION}" \
--build-arg "ANDROID=${ANDROID}" \
--build-arg "ANDROID_NDK=${ANDROID_NDK_VERSION}" \
--build-arg "GRADLE_VERSION=${GRADLE_VERSION}" \
--build-arg "VULKAN_SDK_VERSION=${VULKAN_SDK_VERSION}" \
--build-arg "SWIFTSHADER=${SWIFTSHADER}" \
--build-arg "CMAKE_VERSION=${CMAKE_VERSION:-}" \
--build-arg "NINJA_VERSION=${NINJA_VERSION:-}" \
--build-arg "KATEX=${KATEX:-}" \
--build-arg "ROCM_VERSION=${ROCM_VERSION:-}" \
--build-arg "PYTORCH_ROCM_ARCH=${PYTORCH_ROCM_ARCH:-gfx906;gfx90a}" \
--build-arg "IMAGE_NAME=${IMAGE_NAME}" \
--build-arg "UCX_COMMIT=${UCX_COMMIT}" \
--build-arg "UCC_COMMIT=${UCC_COMMIT}" \
--build-arg "CONDA_CMAKE=${CONDA_CMAKE}" \
--build-arg "TRITON=${TRITON}" \
--build-arg "ONNX=${ONNX}" \
--build-arg "DOCS=${DOCS}" \
--build-arg "INDUCTOR_BENCHMARKS=${INDUCTOR_BENCHMARKS}" \
--build-arg "EXECUTORCH=${EXECUTORCH}" \
--build-arg "HALIDE=${HALIDE}" \
--build-arg "XPU_VERSION=${XPU_VERSION}" \
--build-arg "ACL=${ACL:-}" \
--build-arg "SKIP_SCCACHE_INSTALL=${SKIP_SCCACHE_INSTALL:-}" \
--build-arg "SKIP_LLVM_SRC_BUILD_INSTALL=${SKIP_LLVM_SRC_BUILD_INSTALL:-}" \
-f $(dirname ${DOCKERFILE})/Dockerfile \
-t "$tmp_tag" \
"$@" \
.
# NVIDIA dockers for RC releases use tag names like `11.0-cudnn9-devel-ubuntu18.04-rc`,
# for this case we will set UBUNTU_VERSION to `18.04-rc` so that the Dockerfile could
# find the correct image. As a result, here we have to replace the
# "$UBUNTU_VERSION" == "18.04-rc"
# with
# "$UBUNTU_VERSION" == "18.04"
UBUNTU_VERSION=$(echo ${UBUNTU_VERSION} | sed 's/-rc$//')
function drun() {
docker run --rm "$tmp_tag" $*
}
if [[ "$OS" == "ubuntu" ]]; then
if !(drun lsb_release -a 2>&1 | grep -qF Ubuntu); then
echo "OS=ubuntu, but:"
drun lsb_release -a
exit 1
fi
if !(drun lsb_release -a 2>&1 | grep -qF "$UBUNTU_VERSION"); then
echo "UBUNTU_VERSION=$UBUNTU_VERSION, but:"
drun lsb_release -a
exit 1
fi
fi
if [ -n "$ANACONDA_PYTHON_VERSION" ]; then
if !(drun python --version 2>&1 | grep -qF "Python $ANACONDA_PYTHON_VERSION"); then
echo "ANACONDA_PYTHON_VERSION=$ANACONDA_PYTHON_VERSION, but:"
drun python --version
exit 1
fi
fi
if [ -n "$GCC_VERSION" ]; then
if !(drun gcc --version 2>&1 | grep -q " $GCC_VERSION\\W"); then
echo "GCC_VERSION=$GCC_VERSION, but:"
drun gcc --version
exit 1
fi
fi
if [ -n "$CLANG_VERSION" ]; then
if !(drun clang --version 2>&1 | grep -qF "clang version $CLANG_VERSION"); then
echo "CLANG_VERSION=$CLANG_VERSION, but:"
drun clang --version
exit 1
fi
fi
if [ -n "$KATEX" ]; then
if !(drun katex --version); then
echo "KATEX=$KATEX, but:"
drun katex --version
exit 1
fi
fi

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@ -1,133 +0,0 @@
ARG CENTOS_VERSION
FROM centos:${CENTOS_VERSION}
ARG CENTOS_VERSION
# Set AMD gpu targets to build for
ARG PYTORCH_ROCM_ARCH
ENV PYTORCH_ROCM_ARCH ${PYTORCH_ROCM_ARCH}
# Install required packages to build Caffe2
# Install common dependencies (so that this step can be cached separately)
COPY ./common/install_base.sh install_base.sh
RUN bash ./install_base.sh && rm install_base.sh
# Update CentOS git version
RUN yum -y remove git
RUN yum -y remove git-*
RUN yum -y install https://packages.endpoint.com/rhel/7/os/x86_64/endpoint-repo-1.9-1.x86_64.rpm || \
(yum -y install https://packages.endpointdev.com/rhel/7/os/x86_64/endpoint-repo-1.9-1.x86_64.rpm && \
sed -i "s/packages.endpoint/packages.endpointdev/" /etc/yum.repos.d/endpoint.repo)
RUN yum install -y git
# Install devtoolset
ARG DEVTOOLSET_VERSION
COPY ./common/install_devtoolset.sh install_devtoolset.sh
RUN bash ./install_devtoolset.sh && rm install_devtoolset.sh
ENV BASH_ENV "/etc/profile"
# (optional) Install non-default glibc version
ARG GLIBC_VERSION
COPY ./common/install_glibc.sh install_glibc.sh
RUN if [ -n "${GLIBC_VERSION}" ]; then bash ./install_glibc.sh; fi
RUN rm install_glibc.sh
# Install user
COPY ./common/install_user.sh install_user.sh
RUN bash ./install_user.sh && rm install_user.sh
# Install conda and other packages (e.g., numpy, pytest)
ARG ANACONDA_PYTHON_VERSION
ARG CONDA_CMAKE
ENV ANACONDA_PYTHON_VERSION=$ANACONDA_PYTHON_VERSION
ENV PATH /opt/conda/envs/py_$ANACONDA_PYTHON_VERSION/bin:/opt/conda/bin:$PATH
COPY requirements-ci.txt /opt/conda/requirements-ci.txt
COPY ./common/install_conda.sh install_conda.sh
COPY ./common/common_utils.sh common_utils.sh
RUN bash ./install_conda.sh && rm install_conda.sh common_utils.sh /opt/conda/requirements-ci.txt
# (optional) Install protobuf for ONNX
ARG PROTOBUF
COPY ./common/install_protobuf.sh install_protobuf.sh
RUN if [ -n "${PROTOBUF}" ]; then bash ./install_protobuf.sh; fi
RUN rm install_protobuf.sh
ENV INSTALLED_PROTOBUF ${PROTOBUF}
# (optional) Install database packages like LMDB and LevelDB
ARG DB
COPY ./common/install_db.sh install_db.sh
RUN if [ -n "${DB}" ]; then bash ./install_db.sh; fi
RUN rm install_db.sh
ENV INSTALLED_DB ${DB}
# (optional) Install vision packages like OpenCV
ARG VISION
COPY ./common/install_vision.sh ./common/cache_vision_models.sh ./common/common_utils.sh ./
RUN if [ -n "${VISION}" ]; then bash ./install_vision.sh; fi
RUN rm install_vision.sh cache_vision_models.sh common_utils.sh
ENV INSTALLED_VISION ${VISION}
# Install rocm
ARG ROCM_VERSION
COPY ./common/install_rocm.sh install_rocm.sh
RUN bash ./install_rocm.sh
RUN rm install_rocm.sh
COPY ./common/install_rocm_magma.sh install_rocm_magma.sh
RUN bash ./install_rocm_magma.sh
RUN rm install_rocm_magma.sh
COPY ./common/install_amdsmi.sh install_amdsmi.sh
RUN bash ./install_amdsmi.sh
RUN rm install_amdsmi.sh
ENV PATH /opt/rocm/bin:$PATH
ENV PATH /opt/rocm/hcc/bin:$PATH
ENV PATH /opt/rocm/hip/bin:$PATH
ENV PATH /opt/rocm/opencl/bin:$PATH
ENV PATH /opt/rocm/llvm/bin:$PATH
ENV MAGMA_HOME /opt/rocm/magma
ENV LANG en_US.utf8
ENV LC_ALL en_US.utf8
# (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
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
ENV CMAKE_C_COMPILER cc
ENV CMAKE_CXX_COMPILER c++
COPY ./common/install_triton.sh install_triton.sh
COPY ./common/common_utils.sh common_utils.sh
COPY ci_commit_pins/triton.txt triton.txt
COPY triton_version.txt triton_version.txt
RUN if [ -n "${TRITON}" ]; then bash ./install_triton.sh; fi
RUN rm install_triton.sh common_utils.sh triton.txt triton_version.txt
# Install AOTriton (Early fail)
COPY ./aotriton_version.txt aotriton_version.txt
COPY ./common/common_utils.sh common_utils.sh
COPY ./common/install_aotriton.sh install_aotriton.sh
RUN ["/bin/bash", "-c", "./install_aotriton.sh /opt/rocm && rm -rf install_aotriton.sh aotriton_version.txt common_utils.sh"]
ENV AOTRITON_INSTALLED_PREFIX /opt/rocm/aotriton
# Install ccache/sccache (do this last, so we get priority in PATH)
COPY ./common/install_cache.sh install_cache.sh
ENV PATH /opt/cache/bin:$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}
USER jenkins
CMD ["bash"]

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cd1c833b079adb324871dcbbe75b43d42ffc0ade

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461c12871f336fe6f57b55d6a297f13ef209161b

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243e186efbf7fb93328dd6b34927a4e8c8f24395

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ac3470188b914c5d7a5058a7e28b9eb685a62427

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91b14bf5593cf58a8541f3e6b9125600a867d4ef

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5fe38ffd73c2ac6ed6323b554205186696631c6f

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@ -1,18 +0,0 @@
#!/bin/bash
set -ex
source "$(dirname "${BASH_SOURCE[0]}")/common_utils.sh"
# Cache the test models at ~/.cache/torch/hub/
IMPORT_SCRIPT_FILENAME="/tmp/torchvision_import_script.py"
as_jenkins echo 'import torchvision; torchvision.models.mobilenet_v2(pretrained=True); torchvision.models.mobilenet_v3_large(pretrained=True);' > "${IMPORT_SCRIPT_FILENAME}"
pip_install --pre torch torchvision --index-url https://download.pytorch.org/whl/nightly/cpu
# Very weird quoting behavior here https://github.com/conda/conda/issues/10972,
# so echo the command to a file and run the file instead
conda_run python "${IMPORT_SCRIPT_FILENAME}"
# Cleaning up
conda_run pip uninstall -y torch torchvision
rm "${IMPORT_SCRIPT_FILENAME}" || true

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@ -1,36 +0,0 @@
#!/bin/bash
# Work around bug where devtoolset replaces sudo and breaks it.
if [ -n "$DEVTOOLSET_VERSION" ]; then
export SUDO=/bin/sudo
else
export SUDO=sudo
fi
as_jenkins() {
# NB: unsetting the environment variables works around a conda bug
# https://github.com/conda/conda/issues/6576
# NB: Pass on PATH and LD_LIBRARY_PATH to sudo invocation
# NB: This must be run from a directory that jenkins has access to,
# works around https://github.com/conda/conda-package-handling/pull/34
$SUDO -E -H -u jenkins env -u SUDO_UID -u SUDO_GID -u SUDO_COMMAND -u SUDO_USER env "PATH=$PATH" "LD_LIBRARY_PATH=$LD_LIBRARY_PATH" $*
}
conda_install() {
# Ensure that the install command don't upgrade/downgrade Python
# This should be called as
# conda_install pkg1 pkg2 ... [-c channel]
as_jenkins conda install -q -n py_$ANACONDA_PYTHON_VERSION -y python="$ANACONDA_PYTHON_VERSION" $*
}
conda_run() {
as_jenkins conda run -n py_$ANACONDA_PYTHON_VERSION --no-capture-output $*
}
pip_install() {
as_jenkins conda run -n py_$ANACONDA_PYTHON_VERSION pip install --progress-bar off $*
}
get_pinned_commit() {
cat "${1}".txt
}

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@ -1,16 +0,0 @@
set -euo pipefail
readonly version=v24.04
readonly src_host=https://review.mlplatform.org/ml
readonly src_repo=ComputeLibrary
# Clone ACL
[[ ! -d ${src_repo} ]] && git clone ${src_host}/${src_repo}.git
cd ${src_repo}
git checkout $version
# Build with scons
scons -j8 Werror=0 debug=0 neon=1 opencl=0 embed_kernels=0 \
os=linux arch=armv8a build=native multi_isa=1 \
fixed_format_kernels=1 openmp=1 cppthreads=0

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@ -1,5 +0,0 @@
#!/bin/bash
set -ex
cd /opt/rocm/share/amd_smi && pip install .

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@ -1,23 +0,0 @@
#!/bin/bash
set -ex
source "$(dirname "${BASH_SOURCE[0]}")/common_utils.sh"
TARBALL='aotriton.tar.gz'
# This read command alwasy returns with exit code 1
read -d "\n" VER MANYLINUX ROCMBASE PINNED_COMMIT SHA256 < aotriton_version.txt || true
ARCH=$(uname -m)
AOTRITON_INSTALL_PREFIX="$1"
AOTRITON_URL="https://github.com/ROCm/aotriton/releases/download/${VER}/aotriton-${VER}-${MANYLINUX}_${ARCH}-${ROCMBASE}-shared.tar.gz"
cd "${AOTRITON_INSTALL_PREFIX}"
# Must use -L to follow redirects
curl -L --retry 3 -o "${TARBALL}" "${AOTRITON_URL}"
ACTUAL_SHA256=$(sha256sum "${TARBALL}" | cut -d " " -f 1)
if [ "${SHA256}" != "${ACTUAL_SHA256}" ]; then
echo -n "Error: The SHA256 of downloaded tarball is ${ACTUAL_SHA256},"
echo " which does not match the expected value ${SHA256}."
exit
fi
tar xf "${TARBALL}" && rm -rf "${TARBALL}"

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@ -1,159 +0,0 @@
#!/bin/bash
set -ex
install_ubuntu() {
# NVIDIA dockers for RC releases use tag names like `11.0-cudnn9-devel-ubuntu18.04-rc`,
# for this case we will set UBUNTU_VERSION to `18.04-rc` so that the Dockerfile could
# find the correct image. As a result, here we have to check for
# "$UBUNTU_VERSION" == "18.04"*
# instead of
# "$UBUNTU_VERSION" == "18.04"
if [[ "$UBUNTU_VERSION" == "20.04"* ]]; then
cmake3="cmake=3.16*"
maybe_libiomp_dev=""
elif [[ "$UBUNTU_VERSION" == "22.04"* ]]; then
cmake3="cmake=3.22*"
maybe_libiomp_dev=""
else
cmake3="cmake=3.5*"
maybe_libiomp_dev="libiomp-dev"
fi
if [[ "$CLANG_VERSION" == 15 ]]; then
maybe_libomp_dev="libomp-15-dev"
elif [[ "$CLANG_VERSION" == 12 ]]; then
maybe_libomp_dev="libomp-12-dev"
elif [[ "$CLANG_VERSION" == 10 ]]; then
maybe_libomp_dev="libomp-10-dev"
else
maybe_libomp_dev=""
fi
# HACK: UCC testing relies on libnccl library from NVIDIA repo, and version 2.16 crashes
# See https://github.com/pytorch/pytorch/pull/105260#issuecomment-1673399729
if [[ "$UBUNTU_VERSION" == "20.04"* && "$CUDA_VERSION" == "11.8"* ]]; then
maybe_libnccl_dev="libnccl2=2.15.5-1+cuda11.8 libnccl-dev=2.15.5-1+cuda11.8 --allow-downgrades --allow-change-held-packages"
else
maybe_libnccl_dev=""
fi
# Install common dependencies
apt-get update
# TODO: Some of these may not be necessary
ccache_deps="asciidoc docbook-xml docbook-xsl xsltproc"
deploy_deps="libffi-dev libbz2-dev libreadline-dev libncurses5-dev libncursesw5-dev libgdbm-dev libsqlite3-dev uuid-dev tk-dev"
numpy_deps="gfortran"
apt-get install -y --no-install-recommends \
$ccache_deps \
$numpy_deps \
${deploy_deps} \
${cmake3} \
apt-transport-https \
autoconf \
automake \
build-essential \
ca-certificates \
curl \
git \
libatlas-base-dev \
libc6-dbg \
${maybe_libiomp_dev} \
libyaml-dev \
libz-dev \
libjemalloc2 \
libjpeg-dev \
libasound2-dev \
libsndfile-dev \
${maybe_libomp_dev} \
${maybe_libnccl_dev} \
software-properties-common \
wget \
sudo \
vim \
jq \
libtool \
vim \
unzip \
gpg-agent \
gdb
# Should resolve issues related to various apt package repository cert issues
# see: https://github.com/pytorch/pytorch/issues/65931
apt-get install -y libgnutls30
# Cleanup package manager
apt-get autoclean && apt-get clean
rm -rf /var/lib/apt/lists/* /tmp/* /var/tmp/*
}
install_centos() {
# Need EPEL for many packages we depend on.
# See http://fedoraproject.org/wiki/EPEL
yum --enablerepo=extras install -y epel-release
ccache_deps="asciidoc docbook-dtds docbook-style-xsl libxslt"
numpy_deps="gcc-gfortran"
# Note: protobuf-c-{compiler,devel} on CentOS are too old to be used
# for Caffe2. That said, we still install them to make sure the build
# system opts to build/use protoc and libprotobuf from third-party.
yum install -y \
$ccache_deps \
$numpy_deps \
autoconf \
automake \
bzip2 \
cmake \
cmake3 \
curl \
gcc \
gcc-c++ \
gflags-devel \
git \
glibc-devel \
glibc-headers \
glog-devel \
libstdc++-devel \
libsndfile-devel \
make \
opencv-devel \
sudo \
wget \
vim \
unzip \
gdb
# Cleanup
yum clean all
rm -rf /var/cache/yum
rm -rf /var/lib/yum/yumdb
rm -rf /var/lib/yum/history
}
# Install base packages depending on the base OS
ID=$(grep -oP '(?<=^ID=).+' /etc/os-release | tr -d '"')
case "$ID" in
ubuntu)
install_ubuntu
;;
centos)
install_centos
;;
*)
echo "Unable to determine OS..."
exit 1
;;
esac
# Install Valgrind separately since the apt-get version is too old.
mkdir valgrind_build && cd valgrind_build
VALGRIND_VERSION=3.20.0
wget https://ossci-linux.s3.amazonaws.com/valgrind-${VALGRIND_VERSION}.tar.bz2
tar -xjf valgrind-${VALGRIND_VERSION}.tar.bz2
cd valgrind-${VALGRIND_VERSION}
./configure --prefix=/usr/local
make -j$[$(nproc) - 2]
sudo make install
cd ../../
rm -rf valgrind_build
alias valgrind="/usr/local/bin/valgrind"

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@ -1,44 +0,0 @@
#!/bin/bash
set -ex
if [ -n "$CLANG_VERSION" ]; then
if [[ $CLANG_VERSION == 9 && $UBUNTU_VERSION == 18.04 ]]; then
sudo apt-get update
# gpg-agent is not available by default on 18.04
sudo apt-get install -y --no-install-recommends gpg-agent
wget --no-check-certificate -O - https://apt.llvm.org/llvm-snapshot.gpg.key | sudo apt-key add -
apt-add-repository "deb http://apt.llvm.org/bionic/ llvm-toolchain-bionic-${CLANG_VERSION} main"
elif [[ $UBUNTU_VERSION == 22.04 ]]; then
# work around ubuntu apt-get conflicts
sudo apt-get -y -f install
fi
sudo apt-get update
apt-get install -y --no-install-recommends clang-"$CLANG_VERSION"
apt-get install -y --no-install-recommends llvm-"$CLANG_VERSION"
# Install dev version of LLVM.
if [ -n "$LLVMDEV" ]; then
sudo apt-get install -y --no-install-recommends llvm-"$CLANG_VERSION"-dev
fi
# Use update-alternatives to make this version the default
update-alternatives --install /usr/bin/clang clang /usr/bin/clang-"$CLANG_VERSION" 50
update-alternatives --install /usr/bin/clang++ clang++ /usr/bin/clang++-"$CLANG_VERSION" 50
# Override cc/c++ to clang as well
update-alternatives --install /usr/bin/cc cc /usr/bin/clang 50
update-alternatives --install /usr/bin/c++ c++ /usr/bin/clang++ 50
# clang's packaging is a little messed up (the runtime libs aren't
# added into the linker path), so give it a little help
clang_lib=("/usr/lib/llvm-$CLANG_VERSION/lib/clang/"*"/lib/linux")
echo "$clang_lib" > /etc/ld.so.conf.d/clang.conf
ldconfig
# Cleanup package manager
apt-get autoclean && apt-get clean
rm -rf /var/lib/apt/lists/* /tmp/* /var/tmp/*
fi

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@ -1,31 +0,0 @@
#!/bin/bash
set -ex
[ -n "$CMAKE_VERSION" ]
# Remove system cmake install so it won't get used instead
ID=$(grep -oP '(?<=^ID=).+' /etc/os-release | tr -d '"')
case "$ID" in
ubuntu)
apt-get remove cmake -y
;;
centos)
yum remove cmake -y
;;
*)
echo "Unable to determine OS..."
exit 1
;;
esac
# Turn 3.6.3 into v3.6
path=$(echo "${CMAKE_VERSION}" | sed -e 's/\([0-9].[0-9]\+\).*/v\1/')
file="cmake-${CMAKE_VERSION}-Linux-x86_64.tar.gz"
# Download and install specific CMake version in /usr/local
pushd /tmp
curl -Os --retry 3 "https://cmake.org/files/${path}/${file}"
tar -C /usr/local --strip-components 1 --no-same-owner -zxf cmake-*.tar.gz
rm -f cmake-*.tar.gz
popd

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@ -1,118 +0,0 @@
#!/bin/bash
set -ex
# Optionally install conda
if [ -n "$ANACONDA_PYTHON_VERSION" ]; then
BASE_URL="https://repo.anaconda.com/miniconda"
CONDA_FILE="Miniconda3-latest-Linux-x86_64.sh"
if [[ $(uname -m) == "aarch64" ]] || [[ "$BUILD_ENVIRONMENT" == *xpu* ]]; then
BASE_URL="https://github.com/conda-forge/miniforge/releases/latest/download"
CONDA_FILE="Miniforge3-Linux-$(uname -m).sh"
fi
MAJOR_PYTHON_VERSION=$(echo "$ANACONDA_PYTHON_VERSION" | cut -d . -f 1)
MINOR_PYTHON_VERSION=$(echo "$ANACONDA_PYTHON_VERSION" | cut -d . -f 2)
case "$MAJOR_PYTHON_VERSION" in
3);;
*)
echo "Unsupported ANACONDA_PYTHON_VERSION: $ANACONDA_PYTHON_VERSION"
exit 1
;;
esac
mkdir -p /opt/conda
chown jenkins:jenkins /opt/conda
source "$(dirname "${BASH_SOURCE[0]}")/common_utils.sh"
pushd /tmp
wget -q "${BASE_URL}/${CONDA_FILE}"
# NB: Manually invoke bash per https://github.com/conda/conda/issues/10431
as_jenkins bash "${CONDA_FILE}" -b -f -p "/opt/conda"
popd
# NB: Don't do this, rely on the rpath to get it right
#echo "/opt/conda/lib" > /etc/ld.so.conf.d/conda-python.conf
#ldconfig
sed -e 's|PATH="\(.*\)"|PATH="/opt/conda/bin:\1"|g' -i /etc/environment
export PATH="/opt/conda/bin:$PATH"
# Ensure we run conda in a directory that jenkins has write access to
pushd /opt/conda
# Prevent conda from updating to 4.14.0, which causes docker build failures
# See https://hud.pytorch.org/pytorch/pytorch/commit/754d7f05b6841e555cea5a4b2c505dd9e0baec1d
# Uncomment the below when resolved to track the latest conda update
# as_jenkins conda update -y -n base conda
if [[ $(uname -m) == "aarch64" ]]; then
export SYSROOT_DEP="sysroot_linux-aarch64=2.17"
else
export SYSROOT_DEP="sysroot_linux-64=2.17"
fi
# Install correct Python version
# Also ensure sysroot is using a modern GLIBC to match system compilers
as_jenkins conda create -n py_$ANACONDA_PYTHON_VERSION -y\
python="$ANACONDA_PYTHON_VERSION" \
${SYSROOT_DEP}
# libstdcxx from conda default channels are too old, we need GLIBCXX_3.4.30
# which is provided in libstdcxx 12 and up.
conda_install libstdcxx-ng=12.3.0 -c conda-forge
# Install PyTorch conda deps, as per https://github.com/pytorch/pytorch README
if [[ $(uname -m) == "aarch64" ]]; then
CONDA_COMMON_DEPS="astunparse pyyaml setuptools openblas==0.3.25=*openmp* ninja==1.11.1 scons==4.5.2"
if [ "$ANACONDA_PYTHON_VERSION" = "3.8" ]; then
NUMPY_VERSION=1.24.4
else
NUMPY_VERSION=1.26.2
fi
else
CONDA_COMMON_DEPS="astunparse pyyaml mkl=2021.4.0 mkl-include=2021.4.0 setuptools"
if [ "$ANACONDA_PYTHON_VERSION" = "3.11" ] || [ "$ANACONDA_PYTHON_VERSION" = "3.12" ] || [ "$ANACONDA_PYTHON_VERSION" = "3.13" ]; then
NUMPY_VERSION=1.26.0
else
NUMPY_VERSION=1.21.2
fi
fi
conda_install ${CONDA_COMMON_DEPS}
# Install llvm-8 as it is required to compile llvmlite-0.30.0 from source
# and libpython-static for torch deploy
conda_install llvmdev=8.0.0 "libpython-static=${ANACONDA_PYTHON_VERSION}"
# Use conda cmake in some cases. Conda cmake will be newer than our supported
# min version (3.5 for xenial and 3.10 for bionic), so we only do it in those
# following builds that we know should use conda. Specifically, Ubuntu bionic
# and focal cannot find conda mkl with stock cmake, so we need a cmake from conda
if [ -n "${CONDA_CMAKE}" ]; then
conda_install cmake
fi
# Magma package names are concatenation of CUDA major and minor ignoring revision
# I.e. magma-cuda102 package corresponds to CUDA_VERSION=10.2 and CUDA_VERSION=10.2.89
if [ -n "$CUDA_VERSION" ]; then
conda_install magma-cuda$(TMP=${CUDA_VERSION/./};echo ${TMP%.*[0-9]}) -c pytorch
fi
# Install some other packages, including those needed for Python test reporting
pip_install -r /opt/conda/requirements-ci.txt
pip_install numpy=="$NUMPY_VERSION"
pip_install -U scikit-learn
if [ -n "$DOCS" ]; then
apt-get update
apt-get -y install expect-dev
# We are currently building docs with python 3.8 (min support version)
pip_install -r /opt/conda/requirements-docs.txt
fi
popd
fi

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@ -1,20 +0,0 @@
#!/bin/bash
# Script used only in CD pipeline
set -ex
# Anaconda
# Latest anaconda is using openssl-3 which is incompatible with all currently published versions of git
# Which are using openssl-1.1.1, see https://anaconda.org/anaconda/git/files?version=2.40.1 for example
MINICONDA_URL=https://repo.anaconda.com/miniconda/Miniconda3-py311_23.5.2-0-Linux-x86_64.sh
wget -q $MINICONDA_URL
# NB: Manually invoke bash per https://github.com/conda/conda/issues/10431
bash $(basename "$MINICONDA_URL") -b -p /opt/conda
rm $(basename "$MINICONDA_URL")
export PATH=/opt/conda/bin:$PATH
# See https://github.com/pytorch/builder/issues/1473
# Pin conda to 23.5.2 as it's the last one compatible with openssl-1.1.1
conda install -y conda=23.5.2 conda-build anaconda-client git ninja
# The cmake version here needs to match with the minimum version of cmake
# supported by PyTorch (3.18). There is only 3.18.2 on anaconda
/opt/conda/bin/pip3 install cmake==3.18.2
conda remove -y --force patchelf

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@ -1,112 +0,0 @@
#!/bin/bash
# Script used only in CD pipeline
set -uex -o pipefail
PYTHON_DOWNLOAD_URL=https://www.python.org/ftp/python
PYTHON_DOWNLOAD_GITHUB_BRANCH=https://github.com/python/cpython/archive/refs/heads
GET_PIP_URL=https://bootstrap.pypa.io/get-pip.py
# Python versions to be installed in /opt/$VERSION_NO
CPYTHON_VERSIONS=${CPYTHON_VERSIONS:-"3.8.1 3.9.0 3.10.1 3.11.0 3.12.0 3.13.0 3.13.0t"}
function check_var {
if [ -z "$1" ]; then
echo "required variable not defined"
exit 1
fi
}
function do_cpython_build {
local py_ver=$1
local py_folder=$2
check_var $py_ver
check_var $py_folder
tar -xzf Python-$py_ver.tgz
local additional_flags=""
if [ "$py_ver" == "3.13.0t" ]; then
additional_flags=" --disable-gil"
mv cpython-3.13/ cpython-3.13t/
fi
pushd $py_folder
local prefix="/opt/_internal/cpython-${py_ver}"
mkdir -p ${prefix}/lib
if [[ -n $(which patchelf) ]]; then
local shared_flags="--enable-shared"
else
local shared_flags="--disable-shared"
fi
if [[ -z "${WITH_OPENSSL+x}" ]]; then
local openssl_flags=""
else
local openssl_flags="--with-openssl=${WITH_OPENSSL} --with-openssl-rpath=auto"
fi
# -Wformat added for https://bugs.python.org/issue17547 on Python 2.6
CFLAGS="-Wformat" ./configure --prefix=${prefix} ${openssl_flags} ${shared_flags} ${additional_flags} > /dev/null
make -j40 > /dev/null
make install > /dev/null
if [[ "${shared_flags}" == "--enable-shared" ]]; then
patchelf --set-rpath '$ORIGIN/../lib' ${prefix}/bin/python3
fi
popd
rm -rf $py_folder
# Some python's install as bin/python3. Make them available as
# bin/python.
if [ -e ${prefix}/bin/python3 ]; then
ln -s python3 ${prefix}/bin/python
fi
${prefix}/bin/python get-pip.py
if [ -e ${prefix}/bin/pip3 ] && [ ! -e ${prefix}/bin/pip ]; then
ln -s pip3 ${prefix}/bin/pip
fi
# install setuptools since python 3.12 is required to use distutils
${prefix}/bin/pip install wheel==0.34.2 setuptools==68.2.2
local abi_tag=$(${prefix}/bin/python -c "from wheel.pep425tags import get_abbr_impl, get_impl_ver, get_abi_tag; print('{0}{1}-{2}'.format(get_abbr_impl(), get_impl_ver(), get_abi_tag()))")
ln -s ${prefix} /opt/python/${abi_tag}
}
function build_cpython {
local py_ver=$1
check_var $py_ver
check_var $PYTHON_DOWNLOAD_URL
local py_ver_folder=$py_ver
if [ "$py_ver" = "3.13.0t" ]; then
PY_VER_SHORT="3.13"
PYT_VER_SHORT="3.13t"
check_var $PYTHON_DOWNLOAD_GITHUB_BRANCH
wget $PYTHON_DOWNLOAD_GITHUB_BRANCH/$PY_VER_SHORT.tar.gz -O Python-$py_ver.tgz
do_cpython_build $py_ver cpython-$PYT_VER_SHORT
elif [ "$py_ver" = "3.13.0" ]; then
PY_VER_SHORT="3.13"
check_var $PYTHON_DOWNLOAD_GITHUB_BRANCH
wget $PYTHON_DOWNLOAD_GITHUB_BRANCH/$PY_VER_SHORT.tar.gz -O Python-$py_ver.tgz
do_cpython_build $py_ver cpython-$PY_VER_SHORT
else
wget -q $PYTHON_DOWNLOAD_URL/$py_ver_folder/Python-$py_ver.tgz
do_cpython_build $py_ver Python-$py_ver
fi
rm -f Python-$py_ver.tgz
}
function build_cpythons {
check_var $GET_PIP_URL
curl -sLO $GET_PIP_URL
for py_ver in $@; do
build_cpython $py_ver
done
rm -f get-pip.py
}
mkdir -p /opt/python
mkdir -p /opt/_internal
build_cpythons $CPYTHON_VERSIONS

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@ -1,250 +0,0 @@
#!/bin/bash
set -ex
NCCL_VERSION=v2.21.5-1
CUDNN_VERSION=9.1.0.70
function install_cusparselt_040 {
# cuSparseLt license: https://docs.nvidia.com/cuda/cusparselt/license.html
mkdir tmp_cusparselt && pushd tmp_cusparselt
wget -q https://developer.download.nvidia.com/compute/cusparselt/redist/libcusparse_lt/linux-x86_64/libcusparse_lt-linux-x86_64-0.4.0.7-archive.tar.xz
tar xf libcusparse_lt-linux-x86_64-0.4.0.7-archive.tar.xz
cp -a libcusparse_lt-linux-x86_64-0.4.0.7-archive/include/* /usr/local/cuda/include/
cp -a libcusparse_lt-linux-x86_64-0.4.0.7-archive/lib/* /usr/local/cuda/lib64/
popd
rm -rf tmp_cusparselt
}
function install_cusparselt_052 {
# cuSparseLt license: https://docs.nvidia.com/cuda/cusparselt/license.html
mkdir tmp_cusparselt && pushd tmp_cusparselt
wget -q https://developer.download.nvidia.com/compute/cusparselt/redist/libcusparse_lt/linux-x86_64/libcusparse_lt-linux-x86_64-0.5.2.1-archive.tar.xz
tar xf libcusparse_lt-linux-x86_64-0.5.2.1-archive.tar.xz
cp -a libcusparse_lt-linux-x86_64-0.5.2.1-archive/include/* /usr/local/cuda/include/
cp -a libcusparse_lt-linux-x86_64-0.5.2.1-archive/lib/* /usr/local/cuda/lib64/
popd
rm -rf tmp_cusparselt
}
function install_cusparselt_062 {
# cuSparseLt license: https://docs.nvidia.com/cuda/cusparselt/license.html
mkdir tmp_cusparselt && pushd tmp_cusparselt
wget -q https://developer.download.nvidia.com/compute/cusparselt/redist/libcusparse_lt/linux-x86_64/libcusparse_lt-linux-x86_64-0.6.2.3-archive.tar.xz
tar xf libcusparse_lt-linux-x86_64-0.6.2.3-archive.tar.xz
cp -a libcusparse_lt-linux-x86_64-0.6.2.3-archive/include/* /usr/local/cuda/include/
cp -a libcusparse_lt-linux-x86_64-0.6.2.3-archive/lib/* /usr/local/cuda/lib64/
popd
rm -rf tmp_cusparselt
}
function install_118 {
echo "Installing CUDA 11.8 and cuDNN ${CUDNN_VERSION} and NCCL ${NCCL_VERSION} and cuSparseLt-0.4.0"
rm -rf /usr/local/cuda-11.8 /usr/local/cuda
# install CUDA 11.8.0 in the same container
wget -q https://developer.download.nvidia.com/compute/cuda/11.8.0/local_installers/cuda_11.8.0_520.61.05_linux.run
chmod +x cuda_11.8.0_520.61.05_linux.run
./cuda_11.8.0_520.61.05_linux.run --toolkit --silent
rm -f cuda_11.8.0_520.61.05_linux.run
rm -f /usr/local/cuda && ln -s /usr/local/cuda-11.8 /usr/local/cuda
# cuDNN license: https://developer.nvidia.com/cudnn/license_agreement
mkdir tmp_cudnn && cd tmp_cudnn
wget -q https://developer.download.nvidia.com/compute/cudnn/redist/cudnn/linux-x86_64/cudnn-linux-x86_64-${CUDNN_VERSION}_cuda11-archive.tar.xz -O cudnn-linux-x86_64-${CUDNN_VERSION}_cuda11-archive.tar.xz
tar xf cudnn-linux-x86_64-${CUDNN_VERSION}_cuda11-archive.tar.xz
cp -a cudnn-linux-x86_64-${CUDNN_VERSION}_cuda11-archive/include/* /usr/local/cuda/include/
cp -a cudnn-linux-x86_64-${CUDNN_VERSION}_cuda11-archive/lib/* /usr/local/cuda/lib64/
cd ..
rm -rf tmp_cudnn
# NCCL license: https://docs.nvidia.com/deeplearning/nccl/#licenses
# Follow build: https://github.com/NVIDIA/nccl/tree/master?tab=readme-ov-file#build
git clone -b $NCCL_VERSION --depth 1 https://github.com/NVIDIA/nccl.git
cd nccl && make -j src.build
cp -a build/include/* /usr/local/cuda/include/
cp -a build/lib/* /usr/local/cuda/lib64/
cd ..
rm -rf nccl
install_cusparselt_040
ldconfig
}
function install_121 {
echo "Installing CUDA 12.1 and cuDNN ${CUDNN_VERSION} and NCCL ${NCCL_VERSION} and cuSparseLt-0.5.2"
rm -rf /usr/local/cuda-12.1 /usr/local/cuda
# install CUDA 12.1.0 in the same container
wget -q https://developer.download.nvidia.com/compute/cuda/12.1.1/local_installers/cuda_12.1.1_530.30.02_linux.run
chmod +x cuda_12.1.1_530.30.02_linux.run
./cuda_12.1.1_530.30.02_linux.run --toolkit --silent
rm -f cuda_12.1.1_530.30.02_linux.run
rm -f /usr/local/cuda && ln -s /usr/local/cuda-12.1 /usr/local/cuda
# cuDNN license: https://developer.nvidia.com/cudnn/license_agreement
mkdir tmp_cudnn && cd tmp_cudnn
wget -q https://developer.download.nvidia.com/compute/cudnn/redist/cudnn/linux-x86_64/cudnn-linux-x86_64-${CUDNN_VERSION}_cuda12-archive.tar.xz -O cudnn-linux-x86_64-${CUDNN_VERSION}_cuda12-archive.tar.xz
tar xf cudnn-linux-x86_64-${CUDNN_VERSION}_cuda12-archive.tar.xz
cp -a cudnn-linux-x86_64-${CUDNN_VERSION}_cuda12-archive/include/* /usr/local/cuda/include/
cp -a cudnn-linux-x86_64-${CUDNN_VERSION}_cuda12-archive/lib/* /usr/local/cuda/lib64/
cd ..
rm -rf tmp_cudnn
# NCCL license: https://docs.nvidia.com/deeplearning/nccl/#licenses
# Follow build: https://github.com/NVIDIA/nccl/tree/master?tab=readme-ov-file#build
git clone -b $NCCL_VERSION --depth 1 https://github.com/NVIDIA/nccl.git
cd nccl && make -j src.build
cp -a build/include/* /usr/local/cuda/include/
cp -a build/lib/* /usr/local/cuda/lib64/
cd ..
rm -rf nccl
install_cusparselt_052
ldconfig
}
function install_124 {
echo "Installing CUDA 12.4.1 and cuDNN ${CUDNN_VERSION} and NCCL ${NCCL_VERSION} and cuSparseLt-0.5.2"
rm -rf /usr/local/cuda-12.4 /usr/local/cuda
# install CUDA 12.4.1 in the same container
wget -q https://developer.download.nvidia.com/compute/cuda/12.4.1/local_installers/cuda_12.4.1_550.54.15_linux.run
chmod +x cuda_12.4.1_550.54.15_linux.run
./cuda_12.4.1_550.54.15_linux.run --toolkit --silent
rm -f cuda_12.4.1_550.54.15_linux.run
rm -f /usr/local/cuda && ln -s /usr/local/cuda-12.4 /usr/local/cuda
# cuDNN license: https://developer.nvidia.com/cudnn/license_agreement
mkdir tmp_cudnn && cd tmp_cudnn
wget -q https://developer.download.nvidia.com/compute/cudnn/redist/cudnn/linux-x86_64/cudnn-linux-x86_64-${CUDNN_VERSION}_cuda12-archive.tar.xz -O cudnn-linux-x86_64-${CUDNN_VERSION}_cuda12-archive.tar.xz
tar xf cudnn-linux-x86_64-${CUDNN_VERSION}_cuda12-archive.tar.xz
cp -a cudnn-linux-x86_64-${CUDNN_VERSION}_cuda12-archive/include/* /usr/local/cuda/include/
cp -a cudnn-linux-x86_64-${CUDNN_VERSION}_cuda12-archive/lib/* /usr/local/cuda/lib64/
cd ..
rm -rf tmp_cudnn
# NCCL license: https://docs.nvidia.com/deeplearning/nccl/#licenses
# Follow build: https://github.com/NVIDIA/nccl/tree/master?tab=readme-ov-file#build
git clone -b $NCCL_VERSION --depth 1 https://github.com/NVIDIA/nccl.git
cd nccl && make -j src.build
cp -a build/include/* /usr/local/cuda/include/
cp -a build/lib/* /usr/local/cuda/lib64/
cd ..
rm -rf nccl
install_cusparselt_062
ldconfig
}
function prune_118 {
echo "Pruning CUDA 11.8 and cuDNN"
#####################################################################################
# CUDA 11.8 prune static libs
#####################################################################################
export NVPRUNE="/usr/local/cuda-11.8/bin/nvprune"
export CUDA_LIB_DIR="/usr/local/cuda-11.8/lib64"
export GENCODE="-gencode arch=compute_35,code=sm_35 -gencode arch=compute_50,code=sm_50 -gencode arch=compute_60,code=sm_60 -gencode arch=compute_70,code=sm_70 -gencode arch=compute_75,code=sm_75 -gencode arch=compute_80,code=sm_80 -gencode arch=compute_86,code=sm_86 -gencode arch=compute_90,code=sm_90"
export GENCODE_CUDNN="-gencode arch=compute_35,code=sm_35 -gencode arch=compute_37,code=sm_37 -gencode arch=compute_50,code=sm_50 -gencode arch=compute_60,code=sm_60 -gencode arch=compute_61,code=sm_61 -gencode arch=compute_70,code=sm_70 -gencode arch=compute_75,code=sm_75 -gencode arch=compute_80,code=sm_80 -gencode arch=compute_86,code=sm_86 -gencode arch=compute_90,code=sm_90"
if [[ -n "$OVERRIDE_GENCODE" ]]; then
export GENCODE=$OVERRIDE_GENCODE
fi
# all CUDA libs except CuDNN and CuBLAS (cudnn and cublas need arch 3.7 included)
ls $CUDA_LIB_DIR/ | grep "\.a" | grep -v "culibos" | grep -v "cudart" | grep -v "cudnn" | grep -v "cublas" | grep -v "metis" \
| xargs -I {} bash -c \
"echo {} && $NVPRUNE $GENCODE $CUDA_LIB_DIR/{} -o $CUDA_LIB_DIR/{}"
# prune CuDNN and CuBLAS
$NVPRUNE $GENCODE_CUDNN $CUDA_LIB_DIR/libcublas_static.a -o $CUDA_LIB_DIR/libcublas_static.a
$NVPRUNE $GENCODE_CUDNN $CUDA_LIB_DIR/libcublasLt_static.a -o $CUDA_LIB_DIR/libcublasLt_static.a
#####################################################################################
# CUDA 11.8 prune visual tools
#####################################################################################
export CUDA_BASE="/usr/local/cuda-11.8/"
rm -rf $CUDA_BASE/libnvvp $CUDA_BASE/nsightee_plugins $CUDA_BASE/nsight-compute-2022.3.0 $CUDA_BASE/nsight-systems-2022.4.2/
}
function prune_121 {
echo "Pruning CUDA 12.1"
#####################################################################################
# CUDA 12.1 prune static libs
#####################################################################################
export NVPRUNE="/usr/local/cuda-12.1/bin/nvprune"
export CUDA_LIB_DIR="/usr/local/cuda-12.1/lib64"
export GENCODE="-gencode arch=compute_50,code=sm_50 -gencode arch=compute_60,code=sm_60 -gencode arch=compute_70,code=sm_70 -gencode arch=compute_75,code=sm_75 -gencode arch=compute_80,code=sm_80 -gencode arch=compute_86,code=sm_86 -gencode arch=compute_90,code=sm_90"
export GENCODE_CUDNN="-gencode arch=compute_50,code=sm_50 -gencode arch=compute_60,code=sm_60 -gencode arch=compute_61,code=sm_61 -gencode arch=compute_70,code=sm_70 -gencode arch=compute_75,code=sm_75 -gencode arch=compute_80,code=sm_80 -gencode arch=compute_86,code=sm_86 -gencode arch=compute_90,code=sm_90"
if [[ -n "$OVERRIDE_GENCODE" ]]; then
export GENCODE=$OVERRIDE_GENCODE
fi
# all CUDA libs except CuDNN and CuBLAS
ls $CUDA_LIB_DIR/ | grep "\.a" | grep -v "culibos" | grep -v "cudart" | grep -v "cudnn" | grep -v "cublas" | grep -v "metis" \
| xargs -I {} bash -c \
"echo {} && $NVPRUNE $GENCODE $CUDA_LIB_DIR/{} -o $CUDA_LIB_DIR/{}"
# prune CuDNN and CuBLAS
$NVPRUNE $GENCODE_CUDNN $CUDA_LIB_DIR/libcublas_static.a -o $CUDA_LIB_DIR/libcublas_static.a
$NVPRUNE $GENCODE_CUDNN $CUDA_LIB_DIR/libcublasLt_static.a -o $CUDA_LIB_DIR/libcublasLt_static.a
#####################################################################################
# CUDA 12.1 prune visual tools
#####################################################################################
export CUDA_BASE="/usr/local/cuda-12.1/"
rm -rf $CUDA_BASE/libnvvp $CUDA_BASE/nsightee_plugins $CUDA_BASE/nsight-compute-2023.1.0 $CUDA_BASE/nsight-systems-2023.1.2/
}
function prune_124 {
echo "Pruning CUDA 12.4"
#####################################################################################
# CUDA 12.4 prune static libs
#####################################################################################
export NVPRUNE="/usr/local/cuda-12.4/bin/nvprune"
export CUDA_LIB_DIR="/usr/local/cuda-12.4/lib64"
export GENCODE="-gencode arch=compute_50,code=sm_50 -gencode arch=compute_60,code=sm_60 -gencode arch=compute_70,code=sm_70 -gencode arch=compute_75,code=sm_75 -gencode arch=compute_80,code=sm_80 -gencode arch=compute_86,code=sm_86 -gencode arch=compute_90,code=sm_90"
export GENCODE_CUDNN="-gencode arch=compute_50,code=sm_50 -gencode arch=compute_60,code=sm_60 -gencode arch=compute_61,code=sm_61 -gencode arch=compute_70,code=sm_70 -gencode arch=compute_75,code=sm_75 -gencode arch=compute_80,code=sm_80 -gencode arch=compute_86,code=sm_86 -gencode arch=compute_90,code=sm_90"
if [[ -n "$OVERRIDE_GENCODE" ]]; then
export GENCODE=$OVERRIDE_GENCODE
fi
if [[ -n "$OVERRIDE_GENCODE_CUDNN" ]]; then
export GENCODE_CUDNN=$OVERRIDE_GENCODE_CUDNN
fi
# all CUDA libs except CuDNN and CuBLAS
ls $CUDA_LIB_DIR/ | grep "\.a" | grep -v "culibos" | grep -v "cudart" | grep -v "cudnn" | grep -v "cublas" | grep -v "metis" \
| xargs -I {} bash -c \
"echo {} && $NVPRUNE $GENCODE $CUDA_LIB_DIR/{} -o $CUDA_LIB_DIR/{}"
# prune CuDNN and CuBLAS
$NVPRUNE $GENCODE_CUDNN $CUDA_LIB_DIR/libcublas_static.a -o $CUDA_LIB_DIR/libcublas_static.a
$NVPRUNE $GENCODE_CUDNN $CUDA_LIB_DIR/libcublasLt_static.a -o $CUDA_LIB_DIR/libcublasLt_static.a
#####################################################################################
# CUDA 12.1 prune visual tools
#####################################################################################
export CUDA_BASE="/usr/local/cuda-12.4/"
rm -rf $CUDA_BASE/libnvvp $CUDA_BASE/nsightee_plugins $CUDA_BASE/nsight-compute-2024.1.0 $CUDA_BASE/nsight-systems-2023.4.4/
}
# idiomatic parameter and option handling in sh
while test $# -gt 0
do
case "$1" in
11.8) install_118; prune_118
;;
12.1) install_121; prune_121
;;
12.4) install_124; prune_124
;;
*) echo "bad argument $1"; exit 1
;;
esac
shift
done

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@ -1,93 +0,0 @@
#!/bin/bash
# Script used only in CD pipeline
set -ex
NCCL_VERSION=v2.21.5-1
function install_cusparselt_052 {
# cuSparseLt license: https://docs.nvidia.com/cuda/cusparselt/license.html
mkdir tmp_cusparselt && pushd tmp_cusparselt
wget -q https://developer.download.nvidia.com/compute/cusparselt/redist/libcusparse_lt/linux-sbsa/libcusparse_lt-linux-sbsa-0.5.2.1-archive.tar.xz
tar xf libcusparse_lt-linux-sbsa-0.5.2.1-archive.tar.xz
cp -a libcusparse_lt-linux-sbsa-0.5.2.1-archive/include/* /usr/local/cuda/include/
cp -a libcusparse_lt-linux-sbsa-0.5.2.1-archive/lib/* /usr/local/cuda/lib64/
popd
rm -rf tmp_cusparselt
}
function install_124 {
echo "Installing CUDA 12.4.1 and cuDNN 9.1 and NCCL ${NCCL_VERSION} and cuSparseLt-0.5.2"
rm -rf /usr/local/cuda-12.4 /usr/local/cuda
# install CUDA 12.4.1 in the same container
wget -q https://developer.download.nvidia.com/compute/cuda/12.4.1/local_installers/cuda_12.4.1_550.54.15_linux_sbsa.run
chmod +x cuda_12.4.1_550.54.15_linux_sbsa.run
./cuda_12.4.1_550.54.15_linux_sbsa.run --toolkit --silent
rm -f cuda_12.4.1_550.54.15_linux_sbsa.run
rm -f /usr/local/cuda && ln -s /usr/local/cuda-12.4 /usr/local/cuda
# cuDNN license: https://developer.nvidia.com/cudnn/license_agreement
mkdir tmp_cudnn && cd tmp_cudnn
wget -q https://developer.download.nvidia.com/compute/cudnn/redist/cudnn/linux-sbsa/cudnn-linux-sbsa-9.1.0.70_cuda12-archive.tar.xz -O cudnn-linux-sbsa-9.1.0.70_cuda12-archive.tar.xz
tar xf cudnn-linux-sbsa-9.1.0.70_cuda12-archive.tar.xz
cp -a cudnn-linux-sbsa-9.1.0.70_cuda12-archive/include/* /usr/local/cuda/include/
cp -a cudnn-linux-sbsa-9.1.0.70_cuda12-archive/lib/* /usr/local/cuda/lib64/
cd ..
rm -rf tmp_cudnn
# NCCL license: https://docs.nvidia.com/deeplearning/nccl/#licenses
# Follow build: https://github.com/NVIDIA/nccl/tree/master?tab=readme-ov-file#build
git clone -b ${NCCL_VERSION} --depth 1 https://github.com/NVIDIA/nccl.git
cd nccl && make -j src.build
cp -a build/include/* /usr/local/cuda/include/
cp -a build/lib/* /usr/local/cuda/lib64/
cd ..
rm -rf nccl
install_cusparselt_052
ldconfig
}
function prune_124 {
echo "Pruning CUDA 12.4"
#####################################################################################
# CUDA 12.4 prune static libs
#####################################################################################
export NVPRUNE="/usr/local/cuda-12.4/bin/nvprune"
export CUDA_LIB_DIR="/usr/local/cuda-12.4/lib64"
export GENCODE="-gencode arch=compute_50,code=sm_50 -gencode arch=compute_60,code=sm_60 -gencode arch=compute_70,code=sm_70 -gencode arch=compute_75,code=sm_75 -gencode arch=compute_80,code=sm_80 -gencode arch=compute_86,code=sm_86 -gencode arch=compute_90,code=sm_90"
export GENCODE_CUDNN="-gencode arch=compute_50,code=sm_50 -gencode arch=compute_60,code=sm_60 -gencode arch=compute_61,code=sm_61 -gencode arch=compute_70,code=sm_70 -gencode arch=compute_75,code=sm_75 -gencode arch=compute_80,code=sm_80 -gencode arch=compute_86,code=sm_86 -gencode arch=compute_90,code=sm_90"
if [[ -n "$OVERRIDE_GENCODE" ]]; then
export GENCODE=$OVERRIDE_GENCODE
fi
# all CUDA libs except CuDNN and CuBLAS
ls $CUDA_LIB_DIR/ | grep "\.a" | grep -v "culibos" | grep -v "cudart" | grep -v "cudnn" | grep -v "cublas" | grep -v "metis" \
| xargs -I {} bash -c \
"echo {} && $NVPRUNE $GENCODE $CUDA_LIB_DIR/{} -o $CUDA_LIB_DIR/{}"
# prune CuDNN and CuBLAS
$NVPRUNE $GENCODE_CUDNN $CUDA_LIB_DIR/libcublas_static.a -o $CUDA_LIB_DIR/libcublas_static.a
$NVPRUNE $GENCODE_CUDNN $CUDA_LIB_DIR/libcublasLt_static.a -o $CUDA_LIB_DIR/libcublasLt_static.a
#####################################################################################
# CUDA 12.1 prune visual tools
#####################################################################################
export CUDA_BASE="/usr/local/cuda-12.4/"
rm -rf $CUDA_BASE/libnvvp $CUDA_BASE/nsightee_plugins $CUDA_BASE/nsight-compute-2024.1.0 $CUDA_BASE/nsight-systems-2023.4.4/
}
# idiomatic parameter and option handling in sh
while test $# -gt 0
do
case "$1" in
12.4) install_124; prune_124
;;
*) echo "bad argument $1"; exit 1
;;
esac
shift
done

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@ -1,22 +0,0 @@
#!/bin/bash
if [[ -n "${CUDNN_VERSION}" ]]; then
# cuDNN license: https://developer.nvidia.com/cudnn/license_agreement
mkdir tmp_cudnn
pushd tmp_cudnn
if [[ ${CUDA_VERSION:0:2} == "12" ]]; then
CUDNN_NAME="cudnn-linux-x86_64-9.1.0.70_cuda12-archive"
elif [[ ${CUDA_VERSION:0:2} == "11" ]]; then
CUDNN_NAME="cudnn-linux-x86_64-9.1.0.70_cuda11-archive"
else
print "Unsupported CUDA version ${CUDA_VERSION}"
exit 1
fi
curl --retry 3 -OLs https://developer.download.nvidia.com/compute/cudnn/redist/cudnn/linux-x86_64/${CUDNN_NAME}.tar.xz
tar xf ${CUDNN_NAME}.tar.xz
cp -a ${CUDNN_NAME}/include/* /usr/local/cuda/include/
cp -a ${CUDNN_NAME}/lib/* /usr/local/cuda/lib64/
popd
rm -rf tmp_cudnn
ldconfig
fi

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@ -1,25 +0,0 @@
#!/bin/bash
set -ex
# cudss license: https://docs.nvidia.com/cuda/cudss/license.html
mkdir tmp_cudss && cd tmp_cudss
if [[ ${CUDA_VERSION:0:4} =~ ^12\.[1-4]$ ]]; then
arch_path='sbsa'
export TARGETARCH=${TARGETARCH:-$(uname -m)}
if [ ${TARGETARCH} = 'amd64' ] || [ "${TARGETARCH}" = 'x86_64' ]; then
arch_path='x86_64'
fi
CUDSS_NAME="libcudss-linux-${arch_path}-0.3.0.9_cuda12-archive"
curl --retry 3 -OLs https://developer.download.nvidia.com/compute/cudss/redist/libcudss/linux-${arch_path}/${CUDSS_NAME}.tar.xz
# only for cuda 12
tar xf ${CUDSS_NAME}.tar.xz
cp -a ${CUDSS_NAME}/include/* /usr/local/cuda/include/
cp -a ${CUDSS_NAME}/lib/* /usr/local/cuda/lib64/
fi
cd ..
rm -rf tmp_cudss
ldconfig

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@ -1,34 +0,0 @@
#!/bin/bash
set -ex
# cuSPARSELt license: https://docs.nvidia.com/cuda/cusparselt/license.html
mkdir tmp_cusparselt && cd tmp_cusparselt
if [[ ${CUDA_VERSION:0:4} =~ ^12\.[2-6]$ ]]; then
arch_path='sbsa'
export TARGETARCH=${TARGETARCH:-$(uname -m)}
if [ ${TARGETARCH} = 'amd64' ] || [ "${TARGETARCH}" = 'x86_64' ]; then
arch_path='x86_64'
fi
CUSPARSELT_NAME="libcusparse_lt-linux-${arch_path}-0.6.2.3-archive"
curl --retry 3 -OLs https://developer.download.nvidia.com/compute/cusparselt/redist/libcusparse_lt/linux-${arch_path}/${CUSPARSELT_NAME}.tar.xz
elif [[ ${CUDA_VERSION:0:4} == "12.1" ]]; then
arch_path='sbsa'
export TARGETARCH=${TARGETARCH:-$(uname -m)}
if [ ${TARGETARCH} = 'amd64' ] || [ "${TARGETARCH}" = 'x86_64' ]; then
arch_path='x86_64'
fi
CUSPARSELT_NAME="libcusparse_lt-linux-${arch_path}-0.5.2.1-archive"
curl --retry 3 -OLs https://developer.download.nvidia.com/compute/cusparselt/redist/libcusparse_lt/linux-${arch_path}/${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

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@ -1,38 +0,0 @@
#!/bin/bash
set -ex
install_ubuntu() {
apt-get update
# Cleanup
apt-get autoclean && apt-get clean
rm -rf /var/lib/apt/lists/* /tmp/* /var/tmp/*
}
install_centos() {
# Need EPEL for many packages we depend on.
# See http://fedoraproject.org/wiki/EPEL
yum --enablerepo=extras install -y epel-release
# Cleanup
yum clean all
rm -rf /var/cache/yum
rm -rf /var/lib/yum/yumdb
rm -rf /var/lib/yum/history
}
# Install base packages depending 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

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@ -1,25 +0,0 @@
#!/bin/bash
set -ex
if [ -n "$KATEX" ]; then
apt-get update
# Ignore error if gpg-agent doesn't exist (for Ubuntu 16.04)
apt-get install -y gpg-agent || :
curl --retry 3 -sL https://deb.nodesource.com/setup_16.x | sudo -E bash -
sudo apt-get install -y nodejs
curl --retry 3 -sS https://dl.yarnpkg.com/debian/pubkey.gpg | sudo apt-key add -
echo "deb https://dl.yarnpkg.com/debian/ stable main" | sudo tee /etc/apt/sources.list.d/yarn.list
apt-get update
apt-get install -y --no-install-recommends yarn
yarn global add katex --prefix /usr/local
sudo apt-get -y install doxygen
apt-get autoclean && apt-get clean
rm -rf /var/lib/apt/lists/* /tmp/* /var/tmp/*
fi

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@ -1,65 +0,0 @@
#!/bin/bash
set -ex
source "$(dirname "${BASH_SOURCE[0]}")/common_utils.sh"
clone_executorch() {
EXECUTORCH_PINNED_COMMIT=$(get_pinned_commit executorch)
# Clone the Executorch
git clone https://github.com/pytorch/executorch.git
# and fetch the target commit
pushd executorch
git checkout "${EXECUTORCH_PINNED_COMMIT}"
git submodule update --init
popd
chown -R jenkins executorch
}
install_buck2() {
pushd executorch/.ci/docker
BUCK2_VERSION=$(cat ci_commit_pins/buck2.txt)
source common/install_buck.sh
popd
}
install_conda_dependencies() {
pushd executorch/.ci/docker
# Install conda dependencies like flatbuffer
conda_install --file conda-env-ci.txt
popd
}
install_pip_dependencies() {
pushd executorch/.ci/docker
# Install PyTorch CPU build beforehand to avoid installing the much bigger CUDA
# binaries later, ExecuTorch only needs CPU
pip_install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cpu
# Install all Python dependencies
pip_install -r requirements-ci.txt
popd
}
setup_executorch() {
pushd executorch
# Setup swiftshader and Vulkan SDK which are required to build the Vulkan delegate
as_jenkins bash .ci/scripts/setup-vulkan-linux-deps.sh
export PYTHON_EXECUTABLE=python
export EXECUTORCH_BUILD_PYBIND=ON
export CMAKE_ARGS="-DEXECUTORCH_BUILD_XNNPACK=ON -DEXECUTORCH_BUILD_KERNELS_QUANTIZED=ON"
as_jenkins .ci/scripts/setup-linux.sh cmake
popd
}
clone_executorch
install_buck2
install_conda_dependencies
install_pip_dependencies
setup_executorch

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@ -1,20 +0,0 @@
#!/bin/bash
set -ex
if [ -n "$GCC_VERSION" ]; then
# Need the official toolchain repo to get alternate packages
add-apt-repository ppa:ubuntu-toolchain-r/test
apt-get update
apt-get install -y g++-$GCC_VERSION
update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-"$GCC_VERSION" 50
update-alternatives --install /usr/bin/g++ g++ /usr/bin/g++-"$GCC_VERSION" 50
update-alternatives --install /usr/bin/gcov gcov /usr/bin/gcov-"$GCC_VERSION" 50
# Cleanup package manager
apt-get autoclean && apt-get clean
rm -rf /var/lib/apt/lists/* /tmp/* /var/tmp/*
fi

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@ -1,46 +0,0 @@
#!/bin/bash
set -ex
source "$(dirname "${BASH_SOURCE[0]}")/common_utils.sh"
COMMIT=$(get_pinned_commit halide)
test -n "$COMMIT"
# activate conda to populate CONDA_PREFIX
test -n "$ANACONDA_PYTHON_VERSION"
eval "$(conda shell.bash hook)"
conda activate py_$ANACONDA_PYTHON_VERSION
if [ -n "${UBUNTU_VERSION}" ];then
apt update
apt-get install -y lld liblld-15-dev libpng-dev libjpeg-dev libgl-dev \
libopenblas-dev libeigen3-dev libatlas-base-dev libzstd-dev
fi
conda_install numpy scipy imageio cmake ninja
git clone --depth 1 --branch release/16.x --recursive https://github.com/llvm/llvm-project.git
cmake -DCMAKE_BUILD_TYPE=Release \
-DLLVM_ENABLE_PROJECTS="clang" \
-DLLVM_TARGETS_TO_BUILD="X86;NVPTX" \
-DLLVM_ENABLE_TERMINFO=OFF -DLLVM_ENABLE_ASSERTIONS=ON \
-DLLVM_ENABLE_EH=ON -DLLVM_ENABLE_RTTI=ON -DLLVM_BUILD_32_BITS=OFF \
-S llvm-project/llvm -B llvm-build -G Ninja
cmake --build llvm-build
cmake --install llvm-build --prefix llvm-install
export LLVM_ROOT=`pwd`/llvm-install
export LLVM_CONFIG=$LLVM_ROOT/bin/llvm-config
git clone https://github.com/halide/Halide.git
pushd Halide
git checkout ${COMMIT} && git submodule update --init --recursive
pip_install -r requirements.txt
cmake -G Ninja -DCMAKE_BUILD_TYPE=Release -S . -B build
cmake --build build
test -e ${CONDA_PREFIX}/lib/python3 || ln -s python${ANACONDA_PYTHON_VERSION} ${CONDA_PREFIX}/lib/python3
cmake --install build --prefix ${CONDA_PREFIX}
chown -R jenkins ${CONDA_PREFIX}
popd
rm -rf Halide llvm-build llvm-project llvm-install
python -c "import halide" # check for errors

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@ -1,26 +0,0 @@
#!/bin/bash
set -ex
source "$(dirname "${BASH_SOURCE[0]}")/common_utils.sh"
function install_huggingface() {
local version
commit=$(get_pinned_commit huggingface)
pip_install pandas==2.0.3
pip_install "git+https://github.com/huggingface/transformers@${commit}"
}
function install_timm() {
local commit
commit=$(get_pinned_commit timm)
pip_install pandas==2.0.3
pip_install "git+https://github.com/huggingface/pytorch-image-models@${commit}"
# Clean up
conda_run pip uninstall -y cmake torch torchvision triton
}
# Pango is needed for weasyprint which is needed for doctr
conda_install pango
install_huggingface
install_timm

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@ -1,23 +0,0 @@
#!/bin/bash
# Script used only in CD pipeline
set -ex
LIBPNG_VERSION=1.6.37
mkdir -p libpng
pushd libpng
wget http://download.sourceforge.net/libpng/libpng-$LIBPNG_VERSION.tar.gz
tar -xvzf libpng-$LIBPNG_VERSION.tar.gz
pushd libpng-$LIBPNG_VERSION
./configure
make
make install
popd
popd
rm -rf libpng

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@ -1,29 +0,0 @@
#!/bin/bash
set -ex
source "$(dirname "${BASH_SOURCE[0]}")/common_utils.sh"
if [ -n "${UBUNTU_VERSION}" ]; then
apt update
apt-get install -y clang doxygen git graphviz nodejs npm libtinfo5
fi
# Do shallow clone of PyTorch so that we can init lintrunner in Docker build context
git clone https://github.com/pytorch/pytorch.git --depth 1
chown -R jenkins pytorch
pushd pytorch
# Install all linter dependencies
pip_install -r requirements.txt
conda_run lintrunner init
# Cache .lintbin directory as part of the Docker image
cp -r .lintbin /tmp
popd
# Node dependencies required by toc linter job
npm install -g markdown-toc
# Cleaning up
rm -rf pytorch

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@ -1,29 +0,0 @@
#!/usr/bin/env bash
# Script used only in CD pipeline
set -eou pipefail
MAGMA_VERSION="2.5.2"
function do_install() {
cuda_version=$1
cuda_version_nodot=${1/./}
MAGMA_VERSION="2.6.1"
magma_archive="magma-cuda${cuda_version_nodot}-${MAGMA_VERSION}-1.tar.bz2"
cuda_dir="/usr/local/cuda-${cuda_version}"
(
set -x
tmp_dir=$(mktemp -d)
pushd ${tmp_dir}
curl -OLs https://anaconda.org/pytorch/magma-cuda${cuda_version_nodot}/${MAGMA_VERSION}/download/linux-64/${magma_archive}
tar -xvf "${magma_archive}"
mkdir -p "${cuda_dir}/magma"
mv include "${cuda_dir}/magma/include"
mv lib "${cuda_dir}/magma/lib"
popd
)
}
do_install $1

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@ -1,172 +0,0 @@
#!/bin/bash
# Script used only in CD pipeline
set -ex
ROCM_VERSION=$1
if [[ -z $ROCM_VERSION ]]; then
echo "missing ROCM_VERSION"
exit 1;
fi
IS_UBUNTU=0
ID=$(grep -oP '(?<=^ID=).+' /etc/os-release | tr -d '"')
case "$ID" in
ubuntu)
IS_UBUNTU=1
;;
centos)
IS_UBUNTU=0
;;
*)
echo "Unable to determine OS..."
exit 1
;;
esac
# To make version comparison easier, create an integer representation.
save_IFS="$IFS"
IFS=. ROCM_VERSION_ARRAY=(${ROCM_VERSION})
IFS="$save_IFS"
if [[ ${#ROCM_VERSION_ARRAY[@]} == 2 ]]; then
ROCM_VERSION_MAJOR=${ROCM_VERSION_ARRAY[0]}
ROCM_VERSION_MINOR=${ROCM_VERSION_ARRAY[1]}
ROCM_VERSION_PATCH=0
elif [[ ${#ROCM_VERSION_ARRAY[@]} == 3 ]]; then
ROCM_VERSION_MAJOR=${ROCM_VERSION_ARRAY[0]}
ROCM_VERSION_MINOR=${ROCM_VERSION_ARRAY[1]}
ROCM_VERSION_PATCH=${ROCM_VERSION_ARRAY[2]}
else
echo "Unhandled ROCM_VERSION ${ROCM_VERSION}"
exit 1
fi
ROCM_INT=$(($ROCM_VERSION_MAJOR * 10000 + $ROCM_VERSION_MINOR * 100 + $ROCM_VERSION_PATCH))
# Install custom MIOpen + COMgr for ROCm >= 4.0.1
if [[ $ROCM_INT -lt 40001 ]]; then
echo "ROCm version < 4.0.1; will not install custom MIOpen"
exit 0
fi
# Function to retry functions that sometimes timeout or have flaky failures
retry () {
$* || (sleep 1 && $*) || (sleep 2 && $*) || (sleep 4 && $*) || (sleep 8 && $*)
}
# Build custom MIOpen to use comgr for offline compilation.
## Need a sanitized ROCM_VERSION without patchlevel; patchlevel version 0 must be added to paths.
ROCM_DOTS=$(echo ${ROCM_VERSION} | tr -d -c '.' | wc -c)
if [[ ${ROCM_DOTS} == 1 ]]; then
ROCM_VERSION_NOPATCH="${ROCM_VERSION}"
ROCM_INSTALL_PATH="/opt/rocm-${ROCM_VERSION}.0"
else
ROCM_VERSION_NOPATCH="${ROCM_VERSION%.*}"
ROCM_INSTALL_PATH="/opt/rocm-${ROCM_VERSION}"
fi
# MIOPEN_USE_HIP_KERNELS is a Workaround for COMgr issues
MIOPEN_CMAKE_COMMON_FLAGS="
-DMIOPEN_USE_COMGR=ON
-DMIOPEN_BUILD_DRIVER=OFF
"
# Pull MIOpen repo and set DMIOPEN_EMBED_DB based on ROCm version
if [[ $ROCM_INT -ge 60300 ]]; then
echo "ROCm 6.3+ MIOpen does not need any patches, do not build from source"
exit 0
elif [[ $ROCM_INT -ge 60200 ]] && [[ $ROCM_INT -lt 60300 ]]; then
MIOPEN_BRANCH="release/rocm-rel-6.2-staging"
elif [[ $ROCM_INT -ge 60100 ]] && [[ $ROCM_INT -lt 60200 ]]; then
echo "ROCm 6.1 MIOpen does not need any patches, do not build from source"
exit 0
elif [[ $ROCM_INT -ge 60000 ]] && [[ $ROCM_INT -lt 60100 ]]; then
echo "ROCm 6.0 MIOpen does not need any patches, do not build from source"
exit 0
elif [[ $ROCM_INT -ge 50700 ]] && [[ $ROCM_INT -lt 60000 ]]; then
echo "ROCm 5.7 MIOpen does not need any patches, do not build from source"
exit 0
elif [[ $ROCM_INT -ge 50600 ]] && [[ $ROCM_INT -lt 50700 ]]; then
MIOPEN_BRANCH="release/rocm-rel-5.6-staging"
elif [[ $ROCM_INT -ge 50500 ]] && [[ $ROCM_INT -lt 50600 ]]; then
MIOPEN_BRANCH="release/rocm-rel-5.5-gfx11"
elif [[ $ROCM_INT -ge 50400 ]] && [[ $ROCM_INT -lt 50500 ]]; then
MIOPEN_CMAKE_DB_FLAGS="-DMIOPEN_EMBED_DB=gfx900_56;gfx906_60;gfx90878;gfx90a6e;gfx1030_36 -DMIOPEN_USE_MLIR=Off"
MIOPEN_BRANCH="release/rocm-rel-5.4-staging"
elif [[ $ROCM_INT -ge 50300 ]] && [[ $ROCM_INT -lt 50400 ]]; then
MIOPEN_CMAKE_DB_FLAGS="-DMIOPEN_EMBED_DB=gfx900_56;gfx906_60;gfx90878;gfx90a6e;gfx1030_36 -DMIOPEN_USE_MLIR=Off"
MIOPEN_BRANCH="release/rocm-rel-5.3-staging"
elif [[ $ROCM_INT -ge 50200 ]] && [[ $ROCM_INT -lt 50300 ]]; then
MIOPEN_CMAKE_DB_FLAGS="-DMIOPEN_EMBED_DB=gfx900_56;gfx906_60;gfx90878;gfx90a6e;gfx1030_36 -DMIOPEN_USE_MLIR=Off"
MIOPEN_BRANCH="release/rocm-rel-5.2-staging"
elif [[ $ROCM_INT -ge 50100 ]] && [[ $ROCM_INT -lt 50200 ]]; then
MIOPEN_CMAKE_DB_FLAGS="-DMIOPEN_EMBED_DB=gfx900_56;gfx906_60;gfx90878;gfx90a6e;gfx1030_36"
MIOPEN_BRANCH="release/rocm-rel-5.1-staging"
elif [[ $ROCM_INT -ge 50000 ]] && [[ $ROCM_INT -lt 50100 ]]; then
MIOPEN_CMAKE_DB_FLAGS="-DMIOPEN_EMBED_DB=gfx900_56;gfx906_60;gfx90878;gfx90a6e;gfx1030_36"
MIOPEN_BRANCH="release/rocm-rel-5.0-staging"
else
echo "Unhandled ROCM_VERSION ${ROCM_VERSION}"
exit 1
fi
if [[ ${IS_UBUNTU} == 1 ]]; then
apt-get remove -y miopen-hip
else
yum remove -y miopen-hip
fi
git clone https://github.com/ROCm/MIOpen -b ${MIOPEN_BRANCH}
pushd MIOpen
# remove .git to save disk space since CI runner was running out
rm -rf .git
# Don't build CK to save docker build time
if [[ $ROCM_INT -ge 60200 ]]; then
sed -i '/composable_kernel/d' requirements.txt
fi
# Don't build MLIR to save docker build time
# since we are disabling MLIR backend for MIOpen anyway
if [[ $ROCM_INT -ge 50400 ]] && [[ $ROCM_INT -lt 50500 ]]; then
sed -i '/rocMLIR/d' requirements.txt
elif [[ $ROCM_INT -ge 50200 ]] && [[ $ROCM_INT -lt 50400 ]]; then
sed -i '/llvm-project-mlir/d' requirements.txt
fi
## MIOpen minimum requirements
cmake -P install_deps.cmake --minimum
# clean up since CI runner was running out of disk space
rm -rf /tmp/*
if [[ ${IS_UBUNTU} == 1 ]]; then
apt-get autoclean && apt-get clean
rm -rf /var/lib/apt/lists/* /tmp/* /var/tmp/*
else
yum clean all
rm -rf /var/cache/yum
rm -rf /var/lib/yum/yumdb
rm -rf /var/lib/yum/history
fi
## Build MIOpen
mkdir -p build
cd build
PKG_CONFIG_PATH=/usr/local/lib/pkgconfig CXX=${ROCM_INSTALL_PATH}/llvm/bin/clang++ cmake .. \
${MIOPEN_CMAKE_COMMON_FLAGS} \
${MIOPEN_CMAKE_DB_FLAGS} \
-DCMAKE_PREFIX_PATH="${ROCM_INSTALL_PATH}/hip;${ROCM_INSTALL_PATH}"
make MIOpen -j $(nproc)
# Build MIOpen package
make -j $(nproc) package
# clean up since CI runner was running out of disk space
rm -rf /usr/local/cget
if [[ ${IS_UBUNTU} == 1 ]]; then
sudo dpkg -i miopen-hip*.deb
else
yum install -y miopen-*.rpm
fi
popd
rm -rf MIOpen

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@ -1,16 +0,0 @@
#!/bin/bash
set -ex
# MKL
MKL_VERSION=2024.2.0
MKLROOT=/opt/intel
mkdir -p ${MKLROOT}
pushd /tmp
python3 -mpip install wheel
python3 -mpip download -d . mkl-static==${MKL_VERSION}
python3 -m wheel unpack mkl_static-${MKL_VERSION}-py2.py3-none-manylinux1_x86_64.whl
python3 -m wheel unpack mkl_include-${MKL_VERSION}-py2.py3-none-manylinux1_x86_64.whl
mv mkl_static-${MKL_VERSION}/mkl_static-${MKL_VERSION}.data/data/lib ${MKLROOT}
mv mkl_include-${MKL_VERSION}/mkl_include-${MKL_VERSION}.data/data/include ${MKLROOT}

View File

@ -1,13 +0,0 @@
#!/bin/bash
# Script used only in CD pipeline
set -ex
mkdir -p /usr/local/mnist/
cd /usr/local/mnist
for img in train-images-idx3-ubyte.gz train-labels-idx1-ubyte.gz t10k-images-idx3-ubyte.gz t10k-labels-idx1-ubyte.gz; do
wget -q https://ossci-datasets.s3.amazonaws.com/mnist/$img
gzip -d $img
done

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@ -1,20 +0,0 @@
#!/bin/bash
set -ex
function install_nvpl {
mkdir -p /opt/nvpl/lib /opt/nvpl/include
wget https://developer.download.nvidia.com/compute/nvpl/redist/nvpl_blas/linux-sbsa/nvpl_blas-linux-sbsa-0.3.0-archive.tar.xz
tar xf nvpl_blas-linux-sbsa-0.3.0-archive.tar.xz
cp -r nvpl_blas-linux-sbsa-0.3.0-archive/lib/* /opt/nvpl/lib/
cp -r nvpl_blas-linux-sbsa-0.3.0-archive/include/* /opt/nvpl/include/
wget https://developer.download.nvidia.com/compute/nvpl/redist/nvpl_lapack/linux-sbsa/nvpl_lapack-linux-sbsa-0.2.3.1-archive.tar.xz
tar xf nvpl_lapack-linux-sbsa-0.2.3.1-archive.tar.xz
cp -r nvpl_lapack-linux-sbsa-0.2.3.1-archive/lib/* /opt/nvpl/lib/
cp -r nvpl_lapack-linux-sbsa-0.2.3.1-archive/include/* /opt/nvpl/include/
}
install_nvpl

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@ -1,52 +0,0 @@
#!/bin/bash
set -ex
source "$(dirname "${BASH_SOURCE[0]}")/common_utils.sh"
retry () {
"$@" || (sleep 10 && "$@") || (sleep 20 && "$@") || (sleep 40 && "$@")
}
# A bunch of custom pip dependencies for ONNX
pip_install \
beartype==0.15.0 \
filelock==3.9.0 \
flatbuffers==2.0 \
mock==5.0.1 \
ninja==1.10.2 \
networkx==2.5 \
numpy==1.24.2
# ONNXRuntime should be installed before installing
# onnx-weekly. Otherwise, onnx-weekly could be
# overwritten by onnx.
pip_install \
parameterized==0.8.1 \
pytest-cov==4.0.0 \
pytest-subtests==0.10.0 \
tabulate==0.9.0 \
transformers==4.36.2
pip_install coloredlogs packaging
pip_install onnxruntime==1.18.1
pip_install onnx==1.16.2
pip_install onnxscript==0.1.0.dev20240831 --no-deps
# required by onnxscript
pip_install ml_dtypes
# Cache the transformers model to be used later by ONNX tests. We need to run the transformers
# package to download the model. By default, the model is cached at ~/.cache/huggingface/hub/
IMPORT_SCRIPT_FILENAME="/tmp/onnx_import_script.py"
as_jenkins echo 'import transformers; transformers.AutoModel.from_pretrained("sshleifer/tiny-gpt2"); transformers.AutoTokenizer.from_pretrained("sshleifer/tiny-gpt2"); transformers.AutoModelForSpeechSeq2Seq.from_pretrained("openai/whisper-large-v3");' > "${IMPORT_SCRIPT_FILENAME}"
# Need a PyTorch version for transformers to work
pip_install --pre torch --index-url https://download.pytorch.org/whl/nightly/cpu
# Very weird quoting behavior here https://github.com/conda/conda/issues/10972,
# so echo the command to a file and run the file instead
conda_run python "${IMPORT_SCRIPT_FILENAME}"
# Cleaning up
conda_run pip uninstall -y torch
rm "${IMPORT_SCRIPT_FILENAME}" || true

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@ -1,22 +0,0 @@
#!/bin/bash
# Script used only in CD pipeline
set -ex
cd /
git clone https://github.com/OpenMathLib/OpenBLAS.git -b v0.3.25 --depth 1 --shallow-submodules
OPENBLAS_BUILD_FLAGS="
NUM_THREADS=128
USE_OPENMP=1
NO_SHARED=0
DYNAMIC_ARCH=1
TARGET=ARMV8
CFLAGS=-O3
"
OPENBLAS_CHECKOUT_DIR="OpenBLAS"
make -j8 ${OPENBLAS_BUILD_FLAGS} -C ${OPENBLAS_CHECKOUT_DIR}
make -j8 ${OPENBLAS_BUILD_FLAGS} install -C ${OPENBLAS_CHECKOUT_DIR}

View File

@ -1,17 +0,0 @@
#!/bin/bash
set -ex
OPENSSL=openssl-1.1.1k
wget -q -O "${OPENSSL}.tar.gz" "https://ossci-linux.s3.amazonaws.com/${OPENSSL}.tar.gz"
tar xf "${OPENSSL}.tar.gz"
cd "${OPENSSL}"
./config --prefix=/opt/openssl -d '-Wl,--enable-new-dtags,-rpath,$(LIBRPATH)'
# NOTE: openssl install errors out when built with the -j option
NPROC=$[$(nproc) - 2]
make -j${NPROC}; make install_sw
# Link the ssl libraries to the /usr/lib folder.
sudo ln -s /opt/openssl/lib/lib* /usr/lib
cd ..
rm -rf "${OPENSSL}"

View File

@ -1,16 +0,0 @@
#!/bin/bash
# Script used only in CD pipeline
set -ex
# Pin the version to latest release 0.17.2, building newer commit starts
# to fail on the current image
git clone -b 0.17.2 --single-branch https://github.com/NixOS/patchelf
cd patchelf
sed -i 's/serial/parallel/g' configure.ac
./bootstrap.sh
./configure
make
make install
cd ..
rm -rf patchelf

View File

@ -1,19 +0,0 @@
#!/bin/bash
set -ex
pb_dir="/usr/temp_pb_install_dir"
mkdir -p $pb_dir
# On the nvidia/cuda:9-cudnn7-devel-centos7 image we need this symlink or
# else it will fail with
# g++: error: ./../lib64/crti.o: No such file or directory
ln -s /usr/lib64 "$pb_dir/lib64"
curl -LO "https://github.com/protocolbuffers/protobuf/releases/download/v3.17.3/protobuf-all-3.17.3.tar.gz" --retry 3
tar -xvz --no-same-owner -C "$pb_dir" --strip-components 1 -f protobuf-all-3.17.3.tar.gz
NPROC=$[$(nproc) - 2]
pushd "$pb_dir" && ./configure && make -j${NPROC} && make -j${NPROC} check && sudo make -j${NRPOC} install && sudo ldconfig
popd
rm -rf $pb_dir

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@ -1,148 +0,0 @@
#!/bin/bash
set -ex
ver() {
printf "%3d%03d%03d%03d" $(echo "$1" | tr '.' ' ');
}
install_ubuntu() {
apt-get update
if [[ $UBUNTU_VERSION == 18.04 ]]; then
# gpg-agent is not available by default on 18.04
apt-get install -y --no-install-recommends gpg-agent
fi
if [[ $UBUNTU_VERSION == 20.04 ]]; then
# gpg-agent is not available by default on 20.04
apt-get install -y --no-install-recommends gpg-agent
fi
apt-get install -y kmod
apt-get install -y wget
# Need the libc++1 and libc++abi1 libraries to allow torch._C to load at runtime
apt-get install -y libc++1
apt-get install -y libc++abi1
# Add amdgpu repository
UBUNTU_VERSION_NAME=`cat /etc/os-release | grep UBUNTU_CODENAME | awk -F= '{print $2}'`
echo "deb [arch=amd64] https://repo.radeon.com/amdgpu/${ROCM_VERSION}/ubuntu ${UBUNTU_VERSION_NAME} main" > /etc/apt/sources.list.d/amdgpu.list
# Add rocm repository
wget -qO - http://repo.radeon.com/rocm/rocm.gpg.key | apt-key add -
local rocm_baseurl="http://repo.radeon.com/rocm/apt/${ROCM_VERSION}"
echo "deb [arch=amd64] ${rocm_baseurl} ${UBUNTU_VERSION_NAME} main" > /etc/apt/sources.list.d/rocm.list
apt-get update --allow-insecure-repositories
DEBIAN_FRONTEND=noninteractive apt-get install -y --allow-unauthenticated \
rocm-dev \
rocm-utils \
rocm-libs \
rccl \
rocprofiler-dev \
roctracer-dev \
amd-smi-lib
if [[ $(ver $ROCM_VERSION) -ge $(ver 6.1) ]]; then
DEBIAN_FRONTEND=noninteractive apt-get install -y --allow-unauthenticated rocm-llvm-dev
fi
# precompiled miopen kernels added in ROCm 3.5, renamed in ROCm 5.5
# search for all unversioned packages
# if search fails it will abort this script; use true to avoid case where search fails
MIOPENHIPGFX=$(apt-cache search --names-only miopen-hip-gfx | awk '{print $1}' | grep -F -v . || true)
if [[ "x${MIOPENHIPGFX}" = x ]]; then
echo "miopen-hip-gfx package not available" && exit 1
else
DEBIAN_FRONTEND=noninteractive apt-get install -y --allow-unauthenticated ${MIOPENHIPGFX}
fi
# ROCm 6.0 had a regression where journal_mode was enabled on the kdb files resulting in permission errors at runtime
for kdb in /opt/rocm/share/miopen/db/*.kdb
do
sqlite3 $kdb "PRAGMA journal_mode=off; PRAGMA VACUUM;"
done
# Cleanup
apt-get autoclean && apt-get clean
rm -rf /var/lib/apt/lists/* /tmp/* /var/tmp/*
}
install_centos() {
yum update -y
yum install -y kmod
yum install -y wget
yum install -y openblas-devel
yum install -y epel-release
yum install -y dkms kernel-headers-`uname -r` kernel-devel-`uname -r`
# Add amdgpu repository
local amdgpu_baseurl
if [[ $OS_VERSION == 9 ]]; then
amdgpu_baseurl="https://repo.radeon.com/amdgpu/${ROCM_VERSION}/rhel/9.0/main/x86_64"
else
amdgpu_baseurl="https://repo.radeon.com/amdgpu/${ROCM_VERSION}/rhel/7.9/main/x86_64"
fi
echo "[AMDGPU]" > /etc/yum.repos.d/amdgpu.repo
echo "name=AMDGPU" >> /etc/yum.repos.d/amdgpu.repo
echo "baseurl=${amdgpu_baseurl}" >> /etc/yum.repos.d/amdgpu.repo
echo "enabled=1" >> /etc/yum.repos.d/amdgpu.repo
echo "gpgcheck=1" >> /etc/yum.repos.d/amdgpu.repo
echo "gpgkey=http://repo.radeon.com/rocm/rocm.gpg.key" >> /etc/yum.repos.d/amdgpu.repo
local rocm_baseurl="http://repo.radeon.com/rocm/yum/${ROCM_VERSION}"
echo "[ROCm]" > /etc/yum.repos.d/rocm.repo
echo "name=ROCm" >> /etc/yum.repos.d/rocm.repo
echo "baseurl=${rocm_baseurl}" >> /etc/yum.repos.d/rocm.repo
echo "enabled=1" >> /etc/yum.repos.d/rocm.repo
echo "gpgcheck=1" >> /etc/yum.repos.d/rocm.repo
echo "gpgkey=http://repo.radeon.com/rocm/rocm.gpg.key" >> /etc/yum.repos.d/rocm.repo
yum update -y
yum install -y \
rocm-dev \
rocm-utils \
rocm-libs \
rccl \
rocprofiler-dev \
roctracer-dev \
amd-smi-lib
# precompiled miopen kernels; search for all unversioned packages
# if search fails it will abort this script; use true to avoid case where search fails
MIOPENHIPGFX=$(yum -q search miopen-hip-gfx | grep miopen-hip-gfx | awk '{print $1}'| grep -F kdb. || true)
if [[ "x${MIOPENHIPGFX}" = x ]]; then
echo "miopen-hip-gfx package not available" && exit 1
else
yum install -y ${MIOPENHIPGFX}
fi
# ROCm 6.0 had a regression where journal_mode was enabled on the kdb files resulting in permission errors at runtime
for kdb in /opt/rocm/share/miopen/db/*.kdb
do
sqlite3 $kdb "PRAGMA journal_mode=off; PRAGMA VACUUM;"
done
# Cleanup
yum clean all
rm -rf /var/cache/yum
rm -rf /var/lib/yum/yumdb
rm -rf /var/lib/yum/history
}
# Install Python packages depending on the base OS
ID=$(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

@ -1,150 +0,0 @@
#!/bin/bash
# Script used only in CD pipeline
###########################
### prereqs
###########################
# Install Python packages depending on the base OS
ID=$(grep -oP '(?<=^ID=).+' /etc/os-release | tr -d '"')
case "$ID" in
ubuntu)
apt-get update -y
apt-get install -y libpciaccess-dev pkg-config
apt-get clean
;;
centos)
yum install -y libpciaccess-devel pkgconfig
;;
*)
echo "Unable to determine OS..."
exit 1
;;
esac
python3 -m pip install meson ninja
###########################
### clone repo
###########################
GIT_SSL_NO_VERIFY=true git clone https://gitlab.freedesktop.org/mesa/drm.git
pushd drm
###########################
### patch
###########################
patch -p1 <<'EOF'
diff --git a/amdgpu/amdgpu_asic_id.c b/amdgpu/amdgpu_asic_id.c
index a5007ffc..13fa07fc 100644
--- a/amdgpu/amdgpu_asic_id.c
+++ b/amdgpu/amdgpu_asic_id.c
@@ -22,6 +22,13 @@
*
*/
+#define _XOPEN_SOURCE 700
+#define _LARGEFILE64_SOURCE
+#define _FILE_OFFSET_BITS 64
+#include <ftw.h>
+#include <link.h>
+#include <limits.h>
+
#include <ctype.h>
#include <stdio.h>
#include <stdlib.h>
@@ -34,6 +41,19 @@
#include "amdgpu_drm.h"
#include "amdgpu_internal.h"
+static char *amdgpuids_path = NULL;
+static const char* amdgpuids_path_msg = NULL;
+
+static int check_for_location_of_amdgpuids(const char *filepath, const struct stat *info, const int typeflag, struct FTW *pathinfo)
+{
+ if (typeflag == FTW_F && strstr(filepath, "amdgpu.ids")) {
+ amdgpuids_path = strdup(filepath);
+ return 1;
+ }
+
+ return 0;
+}
+
static int parse_one_line(struct amdgpu_device *dev, const char *line)
{
char *buf, *saveptr;
@@ -113,10 +133,46 @@ void amdgpu_parse_asic_ids(struct amdgpu_device *dev)
int line_num = 1;
int r = 0;
+ // attempt to find typical location for amdgpu.ids file
fp = fopen(AMDGPU_ASIC_ID_TABLE, "r");
+
+ // if it doesn't exist, search
+ if (!fp) {
+
+ char self_path[ PATH_MAX ];
+ ssize_t count;
+ ssize_t i;
+
+ count = readlink( "/proc/self/exe", self_path, PATH_MAX );
+ if (count > 0) {
+ self_path[count] = '\0';
+
+ // remove '/bin/python' from self_path
+ for (i=count; i>0; --i) {
+ if (self_path[i] == '/') break;
+ self_path[i] = '\0';
+ }
+ self_path[i] = '\0';
+ for (; i>0; --i) {
+ if (self_path[i] == '/') break;
+ self_path[i] = '\0';
+ }
+ self_path[i] = '\0';
+
+ if (1 == nftw(self_path, check_for_location_of_amdgpuids, 5, FTW_PHYS)) {
+ fp = fopen(amdgpuids_path, "r");
+ amdgpuids_path_msg = amdgpuids_path;
+ }
+ }
+
+ }
+ else {
+ amdgpuids_path_msg = AMDGPU_ASIC_ID_TABLE;
+ }
+
+ // both hard-coded location and search have failed
if (!fp) {
- fprintf(stderr, "%s: %s\n", AMDGPU_ASIC_ID_TABLE,
- strerror(errno));
+ fprintf(stderr, "amdgpu.ids: No such file or directory\n");
return;
}
@@ -132,7 +188,7 @@ void amdgpu_parse_asic_ids(struct amdgpu_device *dev)
continue;
}
- drmMsg("%s version: %s\n", AMDGPU_ASIC_ID_TABLE, line);
+ drmMsg("%s version: %s\n", amdgpuids_path_msg, line);
break;
}
@@ -150,7 +206,7 @@ void amdgpu_parse_asic_ids(struct amdgpu_device *dev)
if (r == -EINVAL) {
fprintf(stderr, "Invalid format: %s: line %d: %s\n",
- AMDGPU_ASIC_ID_TABLE, line_num, line);
+ amdgpuids_path_msg, line_num, line);
} else if (r && r != -EAGAIN) {
fprintf(stderr, "%s: Cannot parse ASIC IDs: %s\n",
__func__, strerror(-r));
EOF
###########################
### build
###########################
meson builddir --prefix=/opt/amdgpu
pushd builddir
ninja install
popd
popd

View File

@ -1,38 +0,0 @@
#!/bin/bash
# Script used in CI and CD pipeline
set -ex
MKLROOT=${MKLROOT:-/opt/conda/envs/py_$ANACONDA_PYTHON_VERSION}
# "install" hipMAGMA into /opt/rocm/magma by copying after build
git clone https://bitbucket.org/icl/magma.git
pushd magma
# Version 2.7.2 + ROCm related updates
git checkout a1625ff4d9bc362906bd01f805dbbe12612953f6
cp make.inc-examples/make.inc.hip-gcc-mkl make.inc
echo 'LIBDIR += -L$(MKLROOT)/lib' >> make.inc
if [[ -f "${MKLROOT}/lib/libmkl_core.a" ]]; then
echo 'LIB = -Wl,--start-group -lmkl_gf_lp64 -lmkl_gnu_thread -lmkl_core -Wl,--end-group -lpthread -lstdc++ -lm -lgomp -lhipblas -lhipsparse' >> make.inc
fi
echo 'LIB += -Wl,--enable-new-dtags -Wl,--rpath,/opt/rocm/lib -Wl,--rpath,$(MKLROOT)/lib -Wl,--rpath,/opt/rocm/magma/lib -ldl' >> make.inc
echo 'DEVCCFLAGS += --gpu-max-threads-per-block=256' >> make.inc
export PATH="${PATH}:/opt/rocm/bin"
if [[ -n "$PYTORCH_ROCM_ARCH" ]]; then
amdgpu_targets=`echo $PYTORCH_ROCM_ARCH | sed 's/;/ /g'`
else
amdgpu_targets=`rocm_agent_enumerator | grep -v gfx000 | sort -u | xargs`
fi
for arch in $amdgpu_targets; do
echo "DEVCCFLAGS += --offload-arch=$arch" >> make.inc
done
# hipcc with openmp flag may cause isnan() on __device__ not to be found; depending on context, compiler may attempt to match with host definition
sed -i 's/^FOPENMP/#FOPENMP/g' make.inc
make -f make.gen.hipMAGMA -j $(nproc)
LANG=C.UTF-8 make lib/libmagma.so -j $(nproc) MKLROOT="${MKLROOT}"
make testing/testing_dgemm -j $(nproc) MKLROOT="${MKLROOT}"
popd
mv magma /opt/rocm

View File

@ -1,83 +0,0 @@
#!/bin/bash
set -ex
source "$(dirname "${BASH_SOURCE[0]}")/common_utils.sh"
get_conda_version() {
as_jenkins conda list -n py_$ANACONDA_PYTHON_VERSION | grep -w $* | head -n 1 | awk '{print $2}'
}
conda_reinstall() {
as_jenkins conda install -q -n py_$ANACONDA_PYTHON_VERSION -y --force-reinstall $*
}
if [ -n "${XPU_VERSION}" ]; then
TRITON_REPO="https://github.com/intel/intel-xpu-backend-for-triton"
TRITON_TEXT_FILE="triton-xpu"
else
TRITON_REPO="https://github.com/openai/triton"
TRITON_TEXT_FILE="triton"
fi
# The logic here is copied from .ci/pytorch/common_utils.sh
TRITON_PINNED_COMMIT=$(get_pinned_commit ${TRITON_TEXT_FILE})
if [ -n "${UBUNTU_VERSION}" ];then
apt update
apt-get install -y gpg-agent
fi
if [ -n "${CONDA_CMAKE}" ]; then
# Keep the current cmake and numpy version here, so we can reinstall them later
CMAKE_VERSION=$(get_conda_version cmake)
NUMPY_VERSION=$(get_conda_version numpy)
fi
if [ -z "${MAX_JOBS}" ]; then
export MAX_JOBS=$(nproc)
fi
# Git checkout triton
mkdir /var/lib/jenkins/triton
chown -R jenkins /var/lib/jenkins/triton
chgrp -R jenkins /var/lib/jenkins/triton
pushd /var/lib/jenkins/
as_jenkins git clone ${TRITON_REPO} triton
cd triton
as_jenkins git checkout ${TRITON_PINNED_COMMIT}
cd python
# TODO: remove patch setup.py once we have a proper fix for https://github.com/triton-lang/triton/issues/4527
as_jenkins sed -i -e 's/https:\/\/tritonlang.blob.core.windows.net\/llvm-builds/https:\/\/oaitriton.blob.core.windows.net\/public\/llvm-builds/g' setup.py
if [ -n "${UBUNTU_VERSION}" ] && [ -n "${GCC_VERSION}" ] && [[ "${GCC_VERSION}" == "7" ]]; then
# Triton needs at least gcc-9 to build
apt-get install -y g++-9
CXX=g++-9 pip_install -e .
elif [ -n "${UBUNTU_VERSION}" ] && [ -n "${CLANG_VERSION}" ]; then
# Triton needs <filesystem> which surprisingly is not available with clang-9 toolchain
add-apt-repository -y ppa:ubuntu-toolchain-r/test
apt-get install -y g++-9
CXX=g++-9 pip_install -e .
else
pip_install -e .
fi
if [ -n "${CONDA_CMAKE}" ]; then
# TODO: This is to make sure that the same cmake and numpy version from install conda
# script is used. Without this step, the newer cmake version (3.25.2) downloaded by
# triton build step via pip will fail to detect conda MKL. Once that issue is fixed,
# this can be removed.
#
# The correct numpy version also needs to be set here because conda claims that it
# causes inconsistent environment. Without this, conda will attempt to install the
# latest numpy version, which fails ASAN tests with the following import error: Numba
# needs NumPy 1.20 or less.
conda_reinstall cmake="${CMAKE_VERSION}"
# Note that we install numpy with pip as conda might not have the version we want
pip_install --force-reinstall numpy=="${NUMPY_VERSION}"
fi

View File

@ -1,53 +0,0 @@
#!/bin/bash
set -ex
if [[ -d "/usr/local/cuda/" ]]; then
with_cuda=/usr/local/cuda/
else
with_cuda=no
fi
function install_ucx() {
set -ex
git clone --recursive https://github.com/openucx/ucx.git
pushd ucx
git checkout ${UCX_COMMIT}
git submodule update --init --recursive
./autogen.sh
./configure --prefix=$UCX_HOME \
--enable-mt \
--with-cuda=$with_cuda \
--enable-profiling \
--enable-stats
time make -j
sudo make install
popd
rm -rf ucx
}
function install_ucc() {
set -ex
git clone --recursive https://github.com/openucx/ucc.git
pushd ucc
git checkout ${UCC_COMMIT}
git submodule update --init --recursive
./autogen.sh
# We only run distributed tests on Tesla M60 and A10G
NVCC_GENCODE="-gencode=arch=compute_52,code=sm_52 -gencode=arch=compute_86,code=compute_86"
./configure --prefix=$UCC_HOME \
--with-ucx=$UCX_HOME \
--with-cuda=$with_cuda \
--with-nvcc-gencode="${NVCC_GENCODE}"
time make -j
sudo make install
popd
rm -rf ucc
}
install_ucx
install_ucc

View File

@ -1,33 +0,0 @@
#!/bin/bash
set -ex
# Mirror jenkins user in container
# jenkins user as ec2-user should have the same user-id
echo "jenkins:x:1000:1000::/var/lib/jenkins:" >> /etc/passwd
echo "jenkins:x:1000:" >> /etc/group
# Needed on focal or newer
echo "jenkins:*:19110:0:99999:7:::" >>/etc/shadow
# Create $HOME
mkdir -p /var/lib/jenkins
chown jenkins:jenkins /var/lib/jenkins
mkdir -p /var/lib/jenkins/.ccache
chown jenkins:jenkins /var/lib/jenkins/.ccache
# Allow writing to /usr/local (for make install)
chown jenkins:jenkins /usr/local
# Allow sudo
# TODO: Maybe we shouldn't
echo 'jenkins ALL=(ALL) NOPASSWD:ALL' > /etc/sudoers.d/jenkins
# Work around bug where devtoolset replaces sudo and breaks it.
if [ -n "$DEVTOOLSET_VERSION" ]; then
SUDO=/bin/sudo
else
SUDO=sudo
fi
# Test that sudo works
$SUDO -u jenkins $SUDO -v

View File

@ -1,161 +0,0 @@
#!/bin/bash
set -xe
# Script used in CI and CD pipeline
# Intel® software for general purpose GPU capabilities.
# Refer to https://www.intel.com/content/www/us/en/developer/articles/tool/pytorch-prerequisites-for-intel-gpus.html
# Users should update to the latest version as it becomes available
function install_ubuntu() {
. /etc/os-release
if [[ ! " jammy " =~ " ${VERSION_CODENAME} " ]]; then
echo "Ubuntu version ${VERSION_CODENAME} not supported"
exit
fi
apt-get update -y
apt-get install -y gpg-agent wget
# To add the online network package repository for the GPU Driver
wget -qO - https://repositories.intel.com/gpu/intel-graphics.key \
| gpg --yes --dearmor --output /usr/share/keyrings/intel-graphics.gpg
echo "deb [arch=amd64 signed-by=/usr/share/keyrings/intel-graphics.gpg] \
https://repositories.intel.com/gpu/ubuntu ${VERSION_CODENAME}${XPU_DRIVER_VERSION} unified" \
| tee /etc/apt/sources.list.d/intel-gpu-${VERSION_CODENAME}.list
# To add the online network network package repository for the Intel Support Packages
wget -O- https://apt.repos.intel.com/intel-gpg-keys/GPG-PUB-KEY-INTEL-SW-PRODUCTS.PUB \
| gpg --dearmor > /usr/share/keyrings/intel-for-pytorch-gpu-dev-keyring.gpg
echo "deb [signed-by=/usr/share/keyrings/intel-for-pytorch-gpu-dev-keyring.gpg] \
https://apt.repos.intel.com/intel-for-pytorch-gpu-dev all main" \
| tee /etc/apt/sources.list.d/intel-for-pytorch-gpu-dev.list
# Update the packages list and repository index
apt-get update
# The xpu-smi packages
apt-get install -y flex bison xpu-smi
# Compute and Media Runtimes
apt-get install -y \
intel-opencl-icd intel-level-zero-gpu level-zero \
intel-media-va-driver-non-free libmfx1 libmfxgen1 libvpl2 \
libegl-mesa0 libegl1-mesa libegl1-mesa-dev libgbm1 libgl1-mesa-dev libgl1-mesa-dri \
libglapi-mesa libgles2-mesa-dev libglx-mesa0 libigdgmm12 libxatracker2 mesa-va-drivers \
mesa-vdpau-drivers mesa-vulkan-drivers va-driver-all vainfo hwinfo clinfo
# Development Packages
apt-get install -y libigc-dev intel-igc-cm libigdfcl-dev libigfxcmrt-dev level-zero-dev
# Install Intel Support Packages
if [ -n "$XPU_VERSION" ]; then
apt-get install -y intel-for-pytorch-gpu-dev-${XPU_VERSION} intel-pti-dev
else
apt-get install -y intel-for-pytorch-gpu-dev intel-pti-dev
fi
# Cleanup
apt-get autoclean && apt-get clean
rm -rf /var/lib/apt/lists/* /tmp/* /var/tmp/*
}
function install_rhel() {
. /etc/os-release
if [[ "${ID}" == "rhel" ]]; then
if [[ ! " 8.6 8.8 8.9 9.0 9.2 9.3 " =~ " ${VERSION_ID} " ]]; then
echo "RHEL version ${VERSION_ID} not supported"
exit
fi
elif [[ "${ID}" == "almalinux" ]]; then
# Workaround for almalinux8 which used by quay.io/pypa/manylinux_2_28_x86_64
VERSION_ID="8.6"
fi
dnf install -y 'dnf-command(config-manager)'
# To add the online network package repository for the GPU Driver
dnf config-manager --add-repo \
https://repositories.intel.com/gpu/rhel/${VERSION_ID}${XPU_DRIVER_VERSION}/unified/intel-gpu-${VERSION_ID}.repo
# To add the online network network package repository for the Intel Support Packages
tee > /etc/yum.repos.d/intel-for-pytorch-gpu-dev.repo << EOF
[intel-for-pytorch-gpu-dev]
name=Intel for Pytorch GPU dev repository
baseurl=https://yum.repos.intel.com/intel-for-pytorch-gpu-dev
enabled=1
gpgcheck=1
repo_gpgcheck=1
gpgkey=https://yum.repos.intel.com/intel-gpg-keys/GPG-PUB-KEY-INTEL-SW-PRODUCTS.PUB
EOF
# The xpu-smi packages
dnf install -y xpu-smi
# Compute and Media Runtimes
dnf install --skip-broken -y \
intel-opencl intel-media intel-mediasdk libmfxgen1 libvpl2\
level-zero intel-level-zero-gpu mesa-dri-drivers mesa-vulkan-drivers \
mesa-vdpau-drivers libdrm mesa-libEGL mesa-libgbm mesa-libGL \
mesa-libxatracker libvpl-tools intel-metrics-discovery \
intel-metrics-library intel-igc-core intel-igc-cm \
libva libva-utils intel-gmmlib libmetee intel-gsc intel-ocloc
# Development packages
dnf install -y --refresh \
intel-igc-opencl-devel level-zero-devel intel-gsc-devel libmetee-devel \
level-zero-devel
# Install Intel Support Packages
yum install -y intel-for-pytorch-gpu-dev intel-pti-dev
# Cleanup
dnf clean all
rm -rf /var/cache/yum
rm -rf /var/lib/yum/yumdb
rm -rf /var/lib/yum/history
}
function install_sles() {
. /etc/os-release
VERSION_SP=${VERSION_ID//./sp}
if [[ ! " 15sp4 15sp5 " =~ " ${VERSION_SP} " ]]; then
echo "SLES version ${VERSION_ID} not supported"
exit
fi
# To add the online network package repository for the GPU Driver
zypper addrepo -f -r \
https://repositories.intel.com/gpu/sles/${VERSION_SP}${XPU_DRIVER_VERSION}/unified/intel-gpu-${VERSION_SP}.repo
rpm --import https://repositories.intel.com/gpu/intel-graphics.key
# To add the online network network package repository for the Intel Support Packages
zypper addrepo https://yum.repos.intel.com/intel-for-pytorch-gpu-dev intel-for-pytorch-gpu-dev
rpm --import https://yum.repos.intel.com/intel-gpg-keys/GPG-PUB-KEY-INTEL-SW-PRODUCTS.PUB
# The xpu-smi packages
zypper install -y lsb-release flex bison xpu-smi
# Compute and Media Runtimes
zypper install -y intel-level-zero-gpu level-zero intel-gsc intel-opencl intel-ocloc \
intel-media-driver libigfxcmrt7 libvpl2 libvpl-tools libmfxgen1 libmfx1
# Development packages
zypper install -y libigdfcl-devel intel-igc-cm libigfxcmrt-devel level-zero-devel
# Install Intel Support Packages
zypper install -y intel-for-pytorch-gpu-dev intel-pti-dev
}
# Default use GPU driver LTS releases
XPU_DRIVER_VERSION="/lts/2350"
if [[ "${XPU_DRIVER_TYPE,,}" == "rolling" ]]; then
# Use GPU driver rolling releases
XPU_DRIVER_VERSION=""
fi
# The installation depends on the base OS
ID=$(grep -oP '(?<=^ID=).+' /etc/os-release | tr -d '"')
case "$ID" in
ubuntu)
install_ubuntu
;;
rhel|almalinux)
install_rhel
;;
sles)
install_sles
;;
*)
echo "Unable to determine OS..."
exit 1
;;
esac

View File

@ -1,100 +0,0 @@
ARG CUDA_VERSION=10.2
ARG BASE_TARGET=cuda${CUDA_VERSION}
FROM centos:7 as base
ENV LC_ALL en_US.UTF-8
ENV LANG en_US.UTF-8
ENV LANGUAGE en_US.UTF-8
ARG DEVTOOLSET_VERSION=9
RUN sed -i s/mirror.centos.org/vault.centos.org/g /etc/yum.repos.d/*.repo
RUN sed -i s/^#.*baseurl=http/baseurl=http/g /etc/yum.repos.d/*.repo
RUN sed -i s/^mirrorlist=http/#mirrorlist=http/g /etc/yum.repos.d/*.repo
RUN yum update -y
RUN yum install -y wget curl perl util-linux xz bzip2 git patch which unzip
# Just add everything as a safe.directory for git since these will be used in multiple places with git
RUN git config --global --add safe.directory '*'
RUN yum install -y yum-utils centos-release-scl
RUN yum-config-manager --enable rhel-server-rhscl-7-rpms
RUN sed -i s/mirror.centos.org/vault.centos.org/g /etc/yum.repos.d/*.repo
RUN sed -i s/^#.*baseurl=http/baseurl=http/g /etc/yum.repos.d/*.repo
RUN sed -i s/^mirrorlist=http/#mirrorlist=http/g /etc/yum.repos.d/*.repo
RUN yum install -y devtoolset-${DEVTOOLSET_VERSION}-gcc devtoolset-${DEVTOOLSET_VERSION}-gcc-c++ devtoolset-${DEVTOOLSET_VERSION}-gcc-gfortran devtoolset-${DEVTOOLSET_VERSION}-binutils
# EPEL for cmake
RUN yum --enablerepo=extras install -y epel-release
# cmake
RUN yum install -y cmake3 && \
ln -s /usr/bin/cmake3 /usr/bin/cmake
ENV PATH=/opt/rh/devtoolset-${DEVTOOLSET_VERSION}/root/usr/bin:$PATH
ENV LD_LIBRARY_PATH=/opt/rh/devtoolset-${DEVTOOLSET_VERSION}/root/usr/lib64:/opt/rh/devtoolset-${DEVTOOLSET_VERSION}/root/usr/lib:$LD_LIBRARY_PATH
RUN yum install -y autoconf aclocal automake make sudo
RUN rm -rf /usr/local/cuda-*
FROM base as patchelf
# Install patchelf
ADD ./common/install_patchelf.sh install_patchelf.sh
RUN bash ./install_patchelf.sh && rm install_patchelf.sh && cp $(which patchelf) /patchelf
FROM base as openssl
# Install openssl
ADD ./common/install_openssl.sh install_openssl.sh
RUN bash ./install_openssl.sh && rm install_openssl.sh
FROM base as conda
# Install Anaconda
ADD ./common/install_conda_docker.sh install_conda.sh
RUN bash ./install_conda.sh && rm install_conda.sh
# Install CUDA
FROM base as cuda
ARG CUDA_VERSION=10.2
RUN rm -rf /usr/local/cuda-*
ADD ./common/install_cuda.sh install_cuda.sh
ENV CUDA_HOME=/usr/local/cuda-${CUDA_VERSION}
# Preserve CUDA_VERSION for the builds
ENV CUDA_VERSION=${CUDA_VERSION}
# Make things in our path by default
ENV PATH=/usr/local/cuda-${CUDA_VERSION}/bin:$PATH
FROM cuda as cuda11.8
RUN bash ./install_cuda.sh 11.8
ENV DESIRED_CUDA=11.8
FROM cuda as cuda12.1
RUN bash ./install_cuda.sh 12.1
ENV DESIRED_CUDA=12.1
FROM cuda as cuda12.4
RUN bash ./install_cuda.sh 12.4
ENV DESIRED_CUDA=12.4
# Install MNIST test data
FROM base as mnist
ADD ./common/install_mnist.sh install_mnist.sh
RUN bash ./install_mnist.sh
FROM base as all_cuda
COPY --from=cuda11.8 /usr/local/cuda-11.8 /usr/local/cuda-11.8
COPY --from=cuda12.1 /usr/local/cuda-12.1 /usr/local/cuda-12.1
COPY --from=cuda12.4 /usr/local/cuda-12.4 /usr/local/cuda-12.4
# Final step
FROM ${BASE_TARGET} as final
COPY --from=openssl /opt/openssl /opt/openssl
COPY --from=patchelf /patchelf /usr/local/bin/patchelf
COPY --from=conda /opt/conda /opt/conda
# Add jni.h for java host build.
COPY ./common/install_jni.sh install_jni.sh
COPY ./java/jni.h jni.h
RUN bash ./install_jni.sh && rm install_jni.sh
ENV PATH /opt/conda/bin:$PATH
COPY --from=mnist /usr/local/mnist /usr/local/mnist
RUN rm -rf /usr/local/cuda
RUN chmod o+rw /usr/local
RUN touch /.condarc && \
chmod o+rw /.condarc && \
chmod -R o+rw /opt/conda

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@ -1,82 +0,0 @@
#!/usr/bin/env bash
# Script used only in CD pipeline
set -eou pipefail
image="$1"
shift
if [ -z "${image}" ]; then
echo "Usage: $0 IMAGE"
exit 1
fi
DOCKER_IMAGE_NAME="pytorch/${image}"
export DOCKER_BUILDKIT=1
TOPDIR=$(git rev-parse --show-toplevel)
CUDA_VERSION=${CUDA_VERSION:-12.1}
case ${CUDA_VERSION} in
cpu)
BASE_TARGET=base
DOCKER_TAG=cpu
;;
all)
BASE_TARGET=all_cuda
DOCKER_TAG=latest
;;
*)
BASE_TARGET=cuda${CUDA_VERSION}
DOCKER_TAG=cuda${CUDA_VERSION}
;;
esac
(
set -x
# TODO: Remove LimitNOFILE=1048576 patch once https://github.com/pytorch/test-infra/issues/5712
# is resolved. This patch is required in order to fix timing out of Docker build on Amazon Linux 2023.
sudo sed -i s/LimitNOFILE=infinity/LimitNOFILE=1048576/ /usr/lib/systemd/system/docker.service
sudo systemctl daemon-reload
sudo systemctl restart docker
docker build \
--target final \
--progress plain \
--build-arg "BASE_TARGET=${BASE_TARGET}" \
--build-arg "CUDA_VERSION=${CUDA_VERSION}" \
--build-arg "DEVTOOLSET_VERSION=9" \
-t ${DOCKER_IMAGE_NAME} \
$@ \
-f "${TOPDIR}/.ci/docker/conda/Dockerfile" \
${TOPDIR}/.ci/docker/
)
if [[ "${DOCKER_TAG}" =~ ^cuda* ]]; then
# Test that we're using the right CUDA compiler
(
set -x
docker run --rm "${DOCKER_IMAGE_NAME}" nvcc --version | grep "cuda_${CUDA_VERSION}"
)
fi
GITHUB_REF=${GITHUB_REF:-$(git symbolic-ref -q HEAD || git describe --tags --exact-match)}
GIT_BRANCH_NAME=${GITHUB_REF##*/}
GIT_COMMIT_SHA=${GITHUB_SHA:-$(git rev-parse HEAD)}
DOCKER_IMAGE_BRANCH_TAG=${DOCKER_IMAGE_NAME}-${GIT_BRANCH_NAME}
DOCKER_IMAGE_SHA_TAG=${DOCKER_IMAGE_NAME}-${GIT_COMMIT_SHA}
if [[ "${WITH_PUSH:-}" == true ]]; then
(
set -x
docker push "${DOCKER_IMAGE_NAME}"
if [[ -n ${GITHUB_REF} ]]; then
docker tag ${DOCKER_IMAGE_NAME} ${DOCKER_IMAGE_BRANCH_TAG}
docker tag ${DOCKER_IMAGE_NAME} ${DOCKER_IMAGE_SHA_TAG}
docker push "${DOCKER_IMAGE_BRANCH_TAG}"
docker push "${DOCKER_IMAGE_SHA_TAG}"
fi
)
fi

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ARG BASE_TARGET=base
ARG GPU_IMAGE=ubuntu:20.04
FROM ${GPU_IMAGE} as base
ENV DEBIAN_FRONTEND=noninteractive
RUN apt-get clean && apt-get update
RUN apt-get install -y curl locales g++ git-all autoconf automake make cmake wget unzip sudo
# Just add everything as a safe.directory for git since these will be used in multiple places with git
RUN git config --global --add safe.directory '*'
RUN locale-gen en_US.UTF-8
ENV LC_ALL en_US.UTF-8
ENV LANG en_US.UTF-8
ENV LANGUAGE en_US.UTF-8
# Install openssl
FROM base as openssl
ADD ./common/install_openssl.sh install_openssl.sh
RUN bash ./install_openssl.sh && rm install_openssl.sh
# Install python
FROM base as python
ADD common/install_cpython.sh install_cpython.sh
RUN apt-get update -y && \
apt-get install build-essential gdb lcov libbz2-dev libffi-dev \
libgdbm-dev liblzma-dev libncurses5-dev libreadline6-dev \
libsqlite3-dev libssl-dev lzma lzma-dev tk-dev uuid-dev zlib1g-dev -y && \
bash ./install_cpython.sh && \
rm install_cpython.sh && \
apt-get clean
FROM base as conda
ADD ./common/install_conda_docker.sh install_conda.sh
RUN bash ./install_conda.sh && rm install_conda.sh
FROM base as cpu
# Install Anaconda
COPY --from=conda /opt/conda /opt/conda
# Install python
COPY --from=python /opt/python /opt/python
COPY --from=python /opt/_internal /opt/_internal
ENV PATH=/opt/conda/bin:/usr/local/cuda/bin:$PATH
# Install MKL
ADD ./common/install_mkl.sh install_mkl.sh
RUN bash ./install_mkl.sh && rm install_mkl.sh
FROM cpu as cuda
ADD ./common/install_cuda.sh install_cuda.sh
ADD ./common/install_magma.sh install_magma.sh
ENV CUDA_HOME /usr/local/cuda
FROM cuda as cuda11.8
RUN bash ./install_cuda.sh 11.8
RUN bash ./install_magma.sh 11.8
RUN ln -sf /usr/local/cuda-11.8 /usr/local/cuda
FROM cuda as cuda12.1
RUN bash ./install_cuda.sh 12.1
RUN bash ./install_magma.sh 12.1
RUN ln -sf /usr/local/cuda-12.1 /usr/local/cuda
FROM cuda as cuda12.4
RUN bash ./install_cuda.sh 12.4
RUN bash ./install_magma.sh 12.4
RUN ln -sf /usr/local/cuda-12.4 /usr/local/cuda
FROM cpu as rocm
ARG PYTORCH_ROCM_ARCH
ENV PYTORCH_ROCM_ARCH ${PYTORCH_ROCM_ARCH}
ENV MKLROOT /opt/intel
# Adding ROCM_PATH env var so that LoadHip.cmake (even with logic updated for ROCm6.0)
# find HIP works for ROCm5.7. Not needed for ROCm6.0 and above.
# Remove below when ROCm5.7 is not in support matrix anymore.
ENV ROCM_PATH /opt/rocm
# No need to install ROCm as base docker image should have full ROCm install
#ADD ./common/install_rocm.sh install_rocm.sh
ADD ./common/install_rocm_drm.sh install_rocm_drm.sh
ADD ./common/install_rocm_magma.sh install_rocm_magma.sh
# gfortran and python needed for building magma from source for ROCm
RUN apt-get update -y && \
apt-get install gfortran -y && \
apt-get install python -y && \
apt-get clean
RUN bash ./install_rocm_drm.sh && rm install_rocm_drm.sh
RUN bash ./install_rocm_magma.sh && rm install_rocm_magma.sh
# Install AOTriton
COPY ./common/common_utils.sh common_utils.sh
COPY ./aotriton_version.txt aotriton_version.txt
COPY ./common/install_aotriton.sh install_aotriton.sh
RUN bash ./install_aotriton.sh /opt/rocm && rm install_aotriton.sh aotriton_version.txt
ENV AOTRITON_INSTALLED_PREFIX /opt/rocm/aotriton
FROM ${BASE_TARGET} as final
COPY --from=openssl /opt/openssl /opt/openssl
# Install patchelf
ADD ./common/install_patchelf.sh install_patchelf.sh
RUN bash ./install_patchelf.sh && rm install_patchelf.sh
# Install Anaconda
COPY --from=conda /opt/conda /opt/conda
# Install python
COPY --from=python /opt/python /opt/python
COPY --from=python /opt/_internal /opt/_internal
ENV PATH=/opt/conda/bin:/usr/local/cuda/bin:$PATH

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@ -1,93 +0,0 @@
#!/usr/bin/env bash
# Script used only in CD pipeline
set -eou pipefail
image="$1"
shift
if [ -z "${image}" ]; then
echo "Usage: $0 IMAGE"
exit 1
fi
DOCKER_IMAGE="pytorch/${image}"
TOPDIR=$(git rev-parse --show-toplevel)
GPU_ARCH_TYPE=${GPU_ARCH_TYPE:-cpu}
GPU_ARCH_VERSION=${GPU_ARCH_VERSION:-}
WITH_PUSH=${WITH_PUSH:-}
DOCKER=${DOCKER:-docker}
case ${GPU_ARCH_TYPE} in
cpu)
BASE_TARGET=cpu
DOCKER_TAG=cpu
GPU_IMAGE=ubuntu:20.04
DOCKER_GPU_BUILD_ARG=""
;;
cuda)
BASE_TARGET=cuda${GPU_ARCH_VERSION}
DOCKER_TAG=cuda${GPU_ARCH_VERSION}
GPU_IMAGE=ubuntu:20.04
DOCKER_GPU_BUILD_ARG=""
;;
rocm)
BASE_TARGET=rocm
DOCKER_TAG=rocm${GPU_ARCH_VERSION}
GPU_IMAGE=rocm/dev-ubuntu-20.04:${GPU_ARCH_VERSION}-complete
PYTORCH_ROCM_ARCH="gfx900;gfx906;gfx908;gfx90a;gfx1030;gfx1100"
ROCM_REGEX="([0-9]+)\.([0-9]+)[\.]?([0-9]*)"
if [[ $GPU_ARCH_VERSION =~ $ROCM_REGEX ]]; then
ROCM_VERSION_INT=$((${BASH_REMATCH[1]}*10000 + ${BASH_REMATCH[2]}*100 + ${BASH_REMATCH[3]:-0}))
else
echo "ERROR: rocm regex failed"
exit 1
fi
if [[ $ROCM_VERSION_INT -ge 60000 ]]; then
PYTORCH_ROCM_ARCH+=";gfx942"
fi
DOCKER_GPU_BUILD_ARG="--build-arg PYTORCH_ROCM_ARCH=${PYTORCH_ROCM_ARCH}"
;;
*)
echo "ERROR: Unrecognized GPU_ARCH_TYPE: ${GPU_ARCH_TYPE}"
exit 1
;;
esac
(
set -x
DOCKER_BUILDKIT=1 ${DOCKER} build \
--target final \
${DOCKER_GPU_BUILD_ARG} \
--build-arg "GPU_IMAGE=${GPU_IMAGE}" \
--build-arg "BASE_TARGET=${BASE_TARGET}" \
-t "${DOCKER_IMAGE}" \
$@ \
-f "${TOPDIR}/.ci/docker/libtorch/Dockerfile" \
"${TOPDIR}/.ci/docker/"
)
GITHUB_REF=${GITHUB_REF:-$(git symbolic-ref -q HEAD || git describe --tags --exact-match)}
GIT_BRANCH_NAME=${GITHUB_REF##*/}
GIT_COMMIT_SHA=${GITHUB_SHA:-$(git rev-parse HEAD)}
DOCKER_IMAGE_BRANCH_TAG=${DOCKER_IMAGE}-${GIT_BRANCH_NAME}
DOCKER_IMAGE_SHA_TAG=${DOCKER_IMAGE}-${GIT_COMMIT_SHA}
if [[ "${WITH_PUSH}" == true ]]; then
(
set -x
${DOCKER} push "${DOCKER_IMAGE}"
if [[ -n ${GITHUB_REF} ]]; then
${DOCKER} tag ${DOCKER_IMAGE} ${DOCKER_IMAGE_BRANCH_TAG}
${DOCKER} tag ${DOCKER_IMAGE} ${DOCKER_IMAGE_SHA_TAG}
${DOCKER} push "${DOCKER_IMAGE_BRANCH_TAG}"
${DOCKER} push "${DOCKER_IMAGE_SHA_TAG}"
fi
)
fi

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@ -1,44 +0,0 @@
ARG UBUNTU_VERSION
FROM ubuntu:${UBUNTU_VERSION}
ARG UBUNTU_VERSION
ENV DEBIAN_FRONTEND noninteractive
# Install common dependencies (so that this step can be cached separately)
COPY ./common/install_base.sh install_base.sh
RUN bash ./install_base.sh && rm install_base.sh
# Install missing libomp-dev
RUN apt-get update && apt-get install -y --no-install-recommends libomp-dev && apt-get autoclean && apt-get clean && rm -rf /var/lib/apt/lists/* /tmp/* /var/tmp/*
# Install user
COPY ./common/install_user.sh install_user.sh
RUN bash ./install_user.sh && rm install_user.sh
# Install conda and other packages (e.g., numpy, pytest)
ARG ANACONDA_PYTHON_VERSION
ARG CONDA_CMAKE
ENV ANACONDA_PYTHON_VERSION=$ANACONDA_PYTHON_VERSION
ENV PATH /opt/conda/envs/py_$ANACONDA_PYTHON_VERSION/bin:/opt/conda/bin:$PATH
COPY requirements-ci.txt /opt/conda/requirements-ci.txt
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
# Install cuda and cudnn
ARG CUDA_VERSION
COPY ./common/install_cuda.sh install_cuda.sh
RUN bash ./install_cuda.sh ${CUDA_VERSION} && rm install_cuda.sh
ENV DESIRED_CUDA ${CUDA_VERSION}
ENV PATH /usr/local/nvidia/bin:/usr/local/cuda/bin:$PATH
# Note that Docker build forbids copying file outside the build context
COPY ./common/install_linter.sh install_linter.sh
COPY ./common/common_utils.sh common_utils.sh
RUN bash ./install_linter.sh
RUN rm install_linter.sh common_utils.sh
USER jenkins
CMD ["bash"]

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@ -1,34 +0,0 @@
ARG UBUNTU_VERSION
FROM ubuntu:${UBUNTU_VERSION}
ARG UBUNTU_VERSION
ENV DEBIAN_FRONTEND noninteractive
# Install common dependencies (so that this step can be cached separately)
COPY ./common/install_base.sh install_base.sh
RUN bash ./install_base.sh && rm install_base.sh
# Install user
COPY ./common/install_user.sh install_user.sh
RUN bash ./install_user.sh && rm install_user.sh
# Install conda and other packages (e.g., numpy, pytest)
ARG ANACONDA_PYTHON_VERSION
ARG CONDA_CMAKE
ENV ANACONDA_PYTHON_VERSION=$ANACONDA_PYTHON_VERSION
ENV PATH /opt/conda/envs/py_$ANACONDA_PYTHON_VERSION/bin:/opt/conda/bin:$PATH
COPY requirements-ci.txt /opt/conda/requirements-ci.txt
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
# Note that Docker build forbids copying file outside the build context
COPY ./common/install_linter.sh install_linter.sh
COPY ./common/common_utils.sh common_utils.sh
RUN bash ./install_linter.sh
RUN rm install_linter.sh common_utils.sh
USER jenkins
CMD ["bash"]

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@ -1,203 +0,0 @@
# syntax = docker/dockerfile:experimental
ARG ROCM_VERSION=3.7
ARG BASE_CUDA_VERSION=11.8
ARG GPU_IMAGE=centos:7
FROM centos:7 as base
ENV LC_ALL en_US.UTF-8
ENV LANG en_US.UTF-8
ENV LANGUAGE en_US.UTF-8
ARG DEVTOOLSET_VERSION=9
# Note: This is required patch since CentOS have reached EOL
# otherwise any yum install setp will fail
RUN sed -i s/mirror.centos.org/vault.centos.org/g /etc/yum.repos.d/*.repo
RUN sed -i s/^#.*baseurl=http/baseurl=http/g /etc/yum.repos.d/*.repo
RUN sed -i s/^mirrorlist=http/#mirrorlist=http/g /etc/yum.repos.d/*.repo
RUN yum install -y wget curl perl util-linux xz bzip2 git patch which perl zlib-devel
# Just add everything as a safe.directory for git since these will be used in multiple places with git
RUN git config --global --add safe.directory '*'
RUN yum install -y yum-utils centos-release-scl
RUN yum-config-manager --enable rhel-server-rhscl-7-rpms
# Note: After running yum-config-manager --enable rhel-server-rhscl-7-rpms
# patch is required once again. Somehow this steps adds mirror.centos.org
RUN sed -i s/mirror.centos.org/vault.centos.org/g /etc/yum.repos.d/*.repo
RUN sed -i s/^#.*baseurl=http/baseurl=http/g /etc/yum.repos.d/*.repo
RUN sed -i s/^mirrorlist=http/#mirrorlist=http/g /etc/yum.repos.d/*.repo
RUN yum install -y devtoolset-${DEVTOOLSET_VERSION}-gcc devtoolset-${DEVTOOLSET_VERSION}-gcc-c++ devtoolset-${DEVTOOLSET_VERSION}-gcc-gfortran devtoolset-${DEVTOOLSET_VERSION}-binutils
ENV PATH=/opt/rh/devtoolset-${DEVTOOLSET_VERSION}/root/usr/bin:$PATH
ENV LD_LIBRARY_PATH=/opt/rh/devtoolset-${DEVTOOLSET_VERSION}/root/usr/lib64:/opt/rh/devtoolset-${DEVTOOLSET_VERSION}/root/usr/lib:$LD_LIBRARY_PATH
RUN yum --enablerepo=extras install -y epel-release
# cmake-3.18.4 from pip
RUN yum install -y python3-pip && \
python3 -mpip install cmake==3.18.4 && \
ln -s /usr/local/bin/cmake /usr/bin/cmake
RUN yum install -y autoconf aclocal automake make sudo
FROM base as openssl
# Install openssl (this must precede `build python` step)
# (In order to have a proper SSL module, Python is compiled
# against a recent openssl [see env vars above], which is linked
# statically. We delete openssl afterwards.)
ADD ./common/install_openssl.sh install_openssl.sh
RUN bash ./install_openssl.sh && rm install_openssl.sh
# EPEL for cmake
FROM base as patchelf
# Install patchelf
ADD ./common/install_patchelf.sh install_patchelf.sh
RUN bash ./install_patchelf.sh && rm install_patchelf.sh
RUN cp $(which patchelf) /patchelf
FROM patchelf as python
# build python
COPY manywheel/build_scripts /build_scripts
ADD ./common/install_cpython.sh /build_scripts/install_cpython.sh
RUN bash build_scripts/build.sh && rm -r build_scripts
FROM base as cuda
ARG BASE_CUDA_VERSION=10.2
# Install CUDA
ADD ./common/install_cuda.sh install_cuda.sh
RUN bash ./install_cuda.sh ${BASE_CUDA_VERSION} && rm install_cuda.sh
FROM base as intel
# MKL
ADD ./common/install_mkl.sh install_mkl.sh
RUN bash ./install_mkl.sh && rm install_mkl.sh
FROM base as magma
ARG BASE_CUDA_VERSION=10.2
# Install magma
ADD ./common/install_magma.sh install_magma.sh
RUN bash ./install_magma.sh ${BASE_CUDA_VERSION} && rm install_magma.sh
FROM base as jni
# Install java jni header
ADD ./common/install_jni.sh install_jni.sh
ADD ./java/jni.h jni.h
RUN bash ./install_jni.sh && rm install_jni.sh
FROM base as libpng
# Install libpng
ADD ./common/install_libpng.sh install_libpng.sh
RUN bash ./install_libpng.sh && rm install_libpng.sh
FROM ${GPU_IMAGE} as common
RUN sed -i s/mirror.centos.org/vault.centos.org/g /etc/yum.repos.d/*.repo
RUN sed -i s/^#.*baseurl=http/baseurl=http/g /etc/yum.repos.d/*.repo
RUN sed -i s/^mirrorlist=http/#mirrorlist=http/g /etc/yum.repos.d/*.repo
ENV LC_ALL en_US.UTF-8
ENV LANG en_US.UTF-8
ENV LANGUAGE en_US.UTF-8
RUN yum install -y \
aclocal \
autoconf \
automake \
bison \
bzip2 \
curl \
diffutils \
file \
git \
make \
patch \
perl \
unzip \
util-linux \
wget \
which \
xz \
yasm
RUN yum install -y \
https://repo.ius.io/ius-release-el7.rpm \
https://ossci-linux.s3.amazonaws.com/epel-release-7-14.noarch.rpm
RUN yum swap -y git git236-core
# git236+ would refuse to run git commands in repos owned by other users
# Which causes version check to fail, as pytorch repo is bind-mounted into the image
# Override this behaviour by treating every folder as safe
# For more details see https://github.com/pytorch/pytorch/issues/78659#issuecomment-1144107327
RUN git config --global --add safe.directory "*"
ENV SSL_CERT_FILE=/opt/_internal/certs.pem
# Install LLVM version
COPY --from=openssl /opt/openssl /opt/openssl
COPY --from=python /opt/python /opt/python
COPY --from=python /opt/_internal /opt/_internal
COPY --from=python /opt/python/cp39-cp39/bin/auditwheel /usr/local/bin/auditwheel
COPY --from=intel /opt/intel /opt/intel
COPY --from=patchelf /usr/local/bin/patchelf /usr/local/bin/patchelf
COPY --from=jni /usr/local/include/jni.h /usr/local/include/jni.h
COPY --from=libpng /usr/local/bin/png* /usr/local/bin/
COPY --from=libpng /usr/local/bin/libpng* /usr/local/bin/
COPY --from=libpng /usr/local/include/png* /usr/local/include/
COPY --from=libpng /usr/local/include/libpng* /usr/local/include/
COPY --from=libpng /usr/local/lib/libpng* /usr/local/lib/
COPY --from=libpng /usr/local/lib/pkgconfig /usr/local/lib/pkgconfig
FROM common as cpu_final
ARG BASE_CUDA_VERSION=10.1
ARG DEVTOOLSET_VERSION=9
RUN sed -i s/mirror.centos.org/vault.centos.org/g /etc/yum.repos.d/*.repo
RUN sed -i s/^#.*baseurl=http/baseurl=http/g /etc/yum.repos.d/*.repo
RUN sed -i s/^mirrorlist=http/#mirrorlist=http/g /etc/yum.repos.d/*.repo
RUN yum install -y yum-utils centos-release-scl
RUN yum-config-manager --enable rhel-server-rhscl-7-rpms
RUN sed -i s/mirror.centos.org/vault.centos.org/g /etc/yum.repos.d/*.repo
RUN sed -i s/^#.*baseurl=http/baseurl=http/g /etc/yum.repos.d/*.repo
RUN sed -i s/^mirrorlist=http/#mirrorlist=http/g /etc/yum.repos.d/*.repo
RUN yum install -y devtoolset-${DEVTOOLSET_VERSION}-gcc devtoolset-${DEVTOOLSET_VERSION}-gcc-c++ devtoolset-${DEVTOOLSET_VERSION}-gcc-gfortran devtoolset-${DEVTOOLSET_VERSION}-binutils
ENV PATH=/opt/rh/devtoolset-${DEVTOOLSET_VERSION}/root/usr/bin:$PATH
ENV LD_LIBRARY_PATH=/opt/rh/devtoolset-${DEVTOOLSET_VERSION}/root/usr/lib64:/opt/rh/devtoolset-${DEVTOOLSET_VERSION}/root/usr/lib:$LD_LIBRARY_PATH
# cmake is already installed inside the rocm base image, so remove if present
RUN rpm -e cmake || true
# cmake-3.18.4 from pip
RUN yum install -y python3-pip && \
python3 -mpip install cmake==3.18.4 && \
ln -s /usr/local/bin/cmake /usr/bin/cmake
# ninja
RUN yum install -y ninja-build
FROM cpu_final as cuda_final
RUN rm -rf /usr/local/cuda-${BASE_CUDA_VERSION}
COPY --from=cuda /usr/local/cuda-${BASE_CUDA_VERSION} /usr/local/cuda-${BASE_CUDA_VERSION}
COPY --from=magma /usr/local/cuda-${BASE_CUDA_VERSION} /usr/local/cuda-${BASE_CUDA_VERSION}
RUN ln -sf /usr/local/cuda-${BASE_CUDA_VERSION} /usr/local/cuda
ENV PATH=/usr/local/cuda/bin:$PATH
FROM cpu_final as rocm_final
ARG ROCM_VERSION=3.7
ARG PYTORCH_ROCM_ARCH
ENV PYTORCH_ROCM_ARCH ${PYTORCH_ROCM_ARCH}
# Adding ROCM_PATH env var so that LoadHip.cmake (even with logic updated for ROCm6.0)
# find HIP works for ROCm5.7. Not needed for ROCm6.0 and above.
# Remove below when ROCm5.7 is not in support matrix anymore.
ENV ROCM_PATH /opt/rocm
ENV MKLROOT /opt/intel
# No need to install ROCm as base docker image should have full ROCm install
#ADD ./common/install_rocm.sh install_rocm.sh
#RUN ROCM_VERSION=${ROCM_VERSION} bash ./install_rocm.sh && rm install_rocm.sh
ADD ./common/install_rocm_drm.sh install_rocm_drm.sh
RUN bash ./install_rocm_drm.sh && rm install_rocm_drm.sh
# cmake3 is needed for the MIOpen build
RUN ln -sf /usr/local/bin/cmake /usr/bin/cmake3
ADD ./common/install_rocm_magma.sh install_rocm_magma.sh
RUN bash ./install_rocm_magma.sh && rm install_rocm_magma.sh
ADD ./common/install_miopen.sh install_miopen.sh
RUN bash ./install_miopen.sh ${ROCM_VERSION} && rm install_miopen.sh
# Install AOTriton
COPY ./common/common_utils.sh common_utils.sh
COPY ./aotriton_version.txt aotriton_version.txt
COPY ./common/install_aotriton.sh install_aotriton.sh
RUN bash ./install_aotriton.sh /opt/rocm && rm install_aotriton.sh aotriton_version.txt
ENV AOTRITON_INSTALLED_PREFIX /opt/rocm/aotriton

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@ -1,153 +0,0 @@
# syntax = docker/dockerfile:experimental
ARG ROCM_VERSION=3.7
ARG BASE_CUDA_VERSION=10.2
ARG GPU_IMAGE=nvidia/cuda:${BASE_CUDA_VERSION}-devel-centos7
FROM quay.io/pypa/manylinux2014_x86_64 as base
ENV LC_ALL en_US.UTF-8
ENV LANG en_US.UTF-8
ENV LANGUAGE en_US.UTF-8
RUN sed -i s/mirror.centos.org/vault.centos.org/g /etc/yum.repos.d/*.repo
RUN sed -i s/^#.*baseurl=http/baseurl=http/g /etc/yum.repos.d/*.repo
RUN sed -i s/^mirrorlist=http/#mirrorlist=http/g /etc/yum.repos.d/*.repo
RUN yum install -y wget curl perl util-linux xz bzip2 git patch which perl zlib-devel
RUN yum install -y yum-utils centos-release-scl sudo
RUN yum-config-manager --enable rhel-server-rhscl-7-rpms
RUN yum install -y devtoolset-7-gcc devtoolset-7-gcc-c++ devtoolset-7-gcc-gfortran devtoolset-7-binutils
ENV PATH=/opt/rh/devtoolset-7/root/usr/bin:$PATH
ENV LD_LIBRARY_PATH=/opt/rh/devtoolset-7/root/usr/lib64:/opt/rh/devtoolset-7/root/usr/lib:$LD_LIBRARY_PATH
# cmake
RUN yum install -y cmake3 && \
ln -s /usr/bin/cmake3 /usr/bin/cmake
FROM base as openssl
# Install openssl (this must precede `build python` step)
# (In order to have a proper SSL module, Python is compiled
# against a recent openssl [see env vars above], which is linked
# statically. We delete openssl afterwards.)
ADD ./common/install_openssl.sh install_openssl.sh
RUN bash ./install_openssl.sh && rm install_openssl.sh
# remove unncessary python versions
RUN rm -rf /opt/python/cp26-cp26m /opt/_internal/cpython-2.6.9-ucs2
RUN rm -rf /opt/python/cp26-cp26mu /opt/_internal/cpython-2.6.9-ucs4
RUN rm -rf /opt/python/cp33-cp33m /opt/_internal/cpython-3.3.6
RUN rm -rf /opt/python/cp34-cp34m /opt/_internal/cpython-3.4.6
FROM base as cuda
ARG BASE_CUDA_VERSION=10.2
# Install CUDA
ADD ./common/install_cuda.sh install_cuda.sh
RUN bash ./install_cuda.sh ${BASE_CUDA_VERSION} && rm install_cuda.sh
FROM base as intel
# MKL
ADD ./common/install_mkl.sh install_mkl.sh
RUN bash ./install_mkl.sh && rm install_mkl.sh
FROM base as magma
ARG BASE_CUDA_VERSION=10.2
# Install magma
ADD ./common/install_magma.sh install_magma.sh
RUN bash ./install_magma.sh ${BASE_CUDA_VERSION} && rm install_magma.sh
FROM base as jni
# Install java jni header
ADD ./common/install_jni.sh install_jni.sh
ADD ./java/jni.h jni.h
RUN bash ./install_jni.sh && rm install_jni.sh
FROM base as libpng
# Install libpng
ADD ./common/install_libpng.sh install_libpng.sh
RUN bash ./install_libpng.sh && rm install_libpng.sh
FROM ${GPU_IMAGE} as common
RUN sed -i s/mirror.centos.org/vault.centos.org/g /etc/yum.repos.d/*.repo
RUN sed -i s/^#.*baseurl=http/baseurl=http/g /etc/yum.repos.d/*.repo
RUN sed -i s/^mirrorlist=http/#mirrorlist=http/g /etc/yum.repos.d/*.repo
ENV LC_ALL en_US.UTF-8
ENV LANG en_US.UTF-8
ENV LANGUAGE en_US.UTF-8
RUN yum install -y \
aclocal \
autoconf \
automake \
bison \
bzip2 \
curl \
diffutils \
file \
git \
make \
patch \
perl \
unzip \
util-linux \
wget \
which \
xz \
yasm
RUN yum install -y \
https://repo.ius.io/ius-release-el7.rpm \
https://ossci-linux.s3.amazonaws.com/epel-release-7-14.noarch.rpm
RUN yum swap -y git git236-core
# git236+ would refuse to run git commands in repos owned by other users
# Which causes version check to fail, as pytorch repo is bind-mounted into the image
# Override this behaviour by treating every folder as safe
# For more details see https://github.com/pytorch/pytorch/issues/78659#issuecomment-1144107327
RUN git config --global --add safe.directory "*"
ENV SSL_CERT_FILE=/opt/_internal/certs.pem
# Install LLVM version
COPY --from=openssl /opt/openssl /opt/openssl
COPY --from=base /opt/python /opt/python
COPY --from=base /opt/_internal /opt/_internal
COPY --from=base /usr/local/bin/auditwheel /usr/local/bin/auditwheel
COPY --from=intel /opt/intel /opt/intel
COPY --from=base /usr/local/bin/patchelf /usr/local/bin/patchelf
COPY --from=libpng /usr/local/bin/png* /usr/local/bin/
COPY --from=libpng /usr/local/bin/libpng* /usr/local/bin/
COPY --from=libpng /usr/local/include/png* /usr/local/include/
COPY --from=libpng /usr/local/include/libpng* /usr/local/include/
COPY --from=libpng /usr/local/lib/libpng* /usr/local/lib/
COPY --from=libpng /usr/local/lib/pkgconfig /usr/local/lib/pkgconfig
COPY --from=jni /usr/local/include/jni.h /usr/local/include/jni.h
FROM common as cpu_final
ARG BASE_CUDA_VERSION=10.2
RUN yum install -y yum-utils centos-release-scl
RUN yum-config-manager --enable rhel-server-rhscl-7-rpms
RUN yum install -y devtoolset-7-gcc devtoolset-7-gcc-c++ devtoolset-7-gcc-gfortran devtoolset-7-binutils
ENV PATH=/opt/rh/devtoolset-7/root/usr/bin:$PATH
ENV LD_LIBRARY_PATH=/opt/rh/devtoolset-7/root/usr/lib64:/opt/rh/devtoolset-7/root/usr/lib:$LD_LIBRARY_PATH
# cmake
RUN yum install -y cmake3 && \
ln -s /usr/bin/cmake3 /usr/bin/cmake
# ninja
RUN yum install -y http://repo.okay.com.mx/centos/7/x86_64/release/okay-release-1-1.noarch.rpm
RUN yum install -y ninja-build
FROM cpu_final as cuda_final
RUN rm -rf /usr/local/cuda-${BASE_CUDA_VERSION}
COPY --from=cuda /usr/local/cuda-${BASE_CUDA_VERSION} /usr/local/cuda-${BASE_CUDA_VERSION}
COPY --from=magma /usr/local/cuda-${BASE_CUDA_VERSION} /usr/local/cuda-${BASE_CUDA_VERSION}
FROM common as rocm_final
ARG ROCM_VERSION=3.7
# Install ROCm
ADD ./common/install_rocm.sh install_rocm.sh
RUN bash ./install_rocm.sh ${ROCM_VERSION} && rm install_rocm.sh
# cmake is already installed inside the rocm base image, but both 2 and 3 exist
# cmake3 is needed for the later MIOpen custom build, so that step is last.
RUN yum install -y cmake3 && \
rm -f /usr/bin/cmake && \
ln -s /usr/bin/cmake3 /usr/bin/cmake
ADD ./common/install_miopen.sh install_miopen.sh
RUN bash ./install_miopen.sh ${ROCM_VERSION} && rm install_miopen.sh

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# syntax = docker/dockerfile:experimental
ARG ROCM_VERSION=3.7
ARG BASE_CUDA_VERSION=11.8
ARG GPU_IMAGE=amd64/almalinux:8
FROM quay.io/pypa/manylinux_2_28_x86_64 as base
ENV LC_ALL en_US.UTF-8
ENV LANG en_US.UTF-8
ENV LANGUAGE en_US.UTF-8
ARG DEVTOOLSET_VERSION=11
RUN yum install -y sudo wget curl perl util-linux xz bzip2 git patch which perl zlib-devel yum-utils gcc-toolset-${DEVTOOLSET_VERSION}-toolchain
ENV PATH=/opt/rh/gcc-toolset-${DEVTOOLSET_VERSION}/root/usr/bin:$PATH
ENV LD_LIBRARY_PATH=/opt/rh/gcc-toolset-${DEVTOOLSET_VERSION}/root/usr/lib64:/opt/rh/gcc-toolset-${DEVTOOLSET_VERSION}/root/usr/lib:$LD_LIBRARY_PATH
# cmake-3.18.4 from pip
RUN yum install -y python3-pip && \
python3 -mpip install cmake==3.18.4 && \
ln -s /usr/local/bin/cmake /usr/bin/cmake3
FROM base as openssl
# Install openssl (this must precede `build python` step)
# (In order to have a proper SSL module, Python is compiled
# against a recent openssl [see env vars above], which is linked
# statically. We delete openssl afterwards.)
ADD ./common/install_openssl.sh install_openssl.sh
RUN bash ./install_openssl.sh && rm install_openssl.sh
# remove unncessary python versions
RUN rm -rf /opt/python/cp26-cp26m /opt/_internal/cpython-2.6.9-ucs2
RUN rm -rf /opt/python/cp26-cp26mu /opt/_internal/cpython-2.6.9-ucs4
RUN rm -rf /opt/python/cp33-cp33m /opt/_internal/cpython-3.3.6
RUN rm -rf /opt/python/cp34-cp34m /opt/_internal/cpython-3.4.6
FROM base as cuda
ARG BASE_CUDA_VERSION=11.8
# Install CUDA
ADD ./common/install_cuda.sh install_cuda.sh
RUN bash ./install_cuda.sh ${BASE_CUDA_VERSION} && rm install_cuda.sh
FROM base as intel
# MKL
ADD ./common/install_mkl.sh install_mkl.sh
RUN bash ./install_mkl.sh && rm install_mkl.sh
FROM base as magma
ARG BASE_CUDA_VERSION=10.2
# Install magma
ADD ./common/install_magma.sh install_magma.sh
RUN bash ./install_magma.sh ${BASE_CUDA_VERSION} && rm install_magma.sh
FROM base as jni
# Install java jni header
ADD ./common/install_jni.sh install_jni.sh
ADD ./java/jni.h jni.h
RUN bash ./install_jni.sh && rm install_jni.sh
FROM base as libpng
# Install libpng
ADD ./common/install_libpng.sh install_libpng.sh
RUN bash ./install_libpng.sh && rm install_libpng.sh
FROM ${GPU_IMAGE} as common
ARG DEVTOOLSET_VERSION=11
ENV LC_ALL en_US.UTF-8
ENV LANG en_US.UTF-8
ENV LANGUAGE en_US.UTF-8
RUN yum -y install epel-release
RUN yum -y update
RUN yum install -y \
autoconf \
automake \
bison \
bzip2 \
curl \
diffutils \
file \
git \
make \
patch \
perl \
unzip \
util-linux \
wget \
which \
xz \
gcc-toolset-${DEVTOOLSET_VERSION}-toolchain \
glibc-langpack-en
RUN yum install -y \
https://repo.ius.io/ius-release-el7.rpm \
https://ossci-linux.s3.amazonaws.com/epel-release-7-14.noarch.rpm
RUN yum swap -y git git236-core
# git236+ would refuse to run git commands in repos owned by other users
# Which causes version check to fail, as pytorch repo is bind-mounted into the image
# Override this behaviour by treating every folder as safe
# For more details see https://github.com/pytorch/pytorch/issues/78659#issuecomment-1144107327
RUN git config --global --add safe.directory "*"
ENV SSL_CERT_FILE=/opt/_internal/certs.pem
# Install LLVM version
COPY --from=openssl /opt/openssl /opt/openssl
COPY --from=base /opt/python /opt/python
COPY --from=base /opt/_internal /opt/_internal
COPY --from=base /usr/local/bin/auditwheel /usr/local/bin/auditwheel
COPY --from=intel /opt/intel /opt/intel
COPY --from=base /usr/local/bin/patchelf /usr/local/bin/patchelf
COPY --from=libpng /usr/local/bin/png* /usr/local/bin/
COPY --from=libpng /usr/local/bin/libpng* /usr/local/bin/
COPY --from=libpng /usr/local/include/png* /usr/local/include/
COPY --from=libpng /usr/local/include/libpng* /usr/local/include/
COPY --from=libpng /usr/local/lib/libpng* /usr/local/lib/
COPY --from=libpng /usr/local/lib/pkgconfig /usr/local/lib/pkgconfig
COPY --from=jni /usr/local/include/jni.h /usr/local/include/jni.h
FROM common as cpu_final
ARG BASE_CUDA_VERSION=11.8
ARG DEVTOOLSET_VERSION=11
# Ensure the expected devtoolset is used
ENV PATH=/opt/rh/gcc-toolset-${DEVTOOLSET_VERSION}/root/usr/bin:$PATH
ENV LD_LIBRARY_PATH=/opt/rh/gcc-toolset-${DEVTOOLSET_VERSION}/root/usr/lib64:/opt/rh/gcc-toolset-${DEVTOOLSET_VERSION}/root/usr/lib:$LD_LIBRARY_PATH
# cmake-3.18.4 from pip
RUN yum install -y python3-pip && \
python3 -mpip install cmake==3.18.4 && \
ln -s /usr/local/bin/cmake /usr/bin/cmake3
FROM cpu_final as cuda_final
RUN rm -rf /usr/local/cuda-${BASE_CUDA_VERSION}
COPY --from=cuda /usr/local/cuda-${BASE_CUDA_VERSION} /usr/local/cuda-${BASE_CUDA_VERSION}
COPY --from=magma /usr/local/cuda-${BASE_CUDA_VERSION} /usr/local/cuda-${BASE_CUDA_VERSION}
FROM common as rocm_final
ARG ROCM_VERSION=3.7
# Install ROCm
ADD ./common/install_rocm.sh install_rocm.sh
RUN bash ./install_rocm.sh ${ROCM_VERSION} && rm install_rocm.sh
# cmake is already installed inside the rocm base image, but both 2 and 3 exist
# cmake3 is needed for the later MIOpen custom build, so that step is last.
RUN yum install -y cmake3 && \
rm -f /usr/bin/cmake && \
ln -s /usr/bin/cmake3 /usr/bin/cmake
ADD ./common/install_miopen.sh install_miopen.sh
RUN bash ./install_miopen.sh ${ROCM_VERSION} && rm install_miopen.sh
FROM cpu_final as xpu_final
# XPU CD use rolling driver
ENV XPU_DRIVER_TYPE ROLLING
# cmake-3.28.4 from pip
RUN python3 -m pip install --upgrade pip && \
python3 -mpip install cmake==3.28.4
# Install setuptools and wheel for python 3.13
RUN /opt/python/cp313-cp313/bin/python -m pip install setuptools wheel
ADD ./common/install_xpu.sh install_xpu.sh
RUN bash ./install_xpu.sh && rm install_xpu.sh
RUN pushd /opt/_internal && tar -xJf static-libs-for-embedding-only.tar.xz && popd

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FROM quay.io/pypa/manylinux_2_28_aarch64 as base
# Graviton needs GCC 10 or above for the build. GCC12 is the default version in almalinux-8.
ARG GCCTOOLSET_VERSION=11
# Language variabes
ENV LC_ALL=en_US.UTF-8
ENV LANG=en_US.UTF-8
ENV LANGUAGE=en_US.UTF-8
# Installed needed OS packages. This is to support all
# the binary builds (torch, vision, audio, text, data)
RUN yum -y install epel-release
RUN yum -y update
RUN yum install -y \
autoconf \
automake \
bison \
bzip2 \
curl \
diffutils \
file \
git \
less \
libffi-devel \
libgomp \
make \
openssl-devel \
patch \
perl \
unzip \
util-linux \
wget \
which \
xz \
yasm \
zstd \
sudo \
gcc-toolset-${GCCTOOLSET_VERSION}-toolchain
# Ensure the expected devtoolset is used
ENV PATH=/opt/rh/gcc-toolset-${GCCTOOLSET_VERSION}/root/usr/bin:$PATH
ENV LD_LIBRARY_PATH=/opt/rh/gcc-toolset-${GCCTOOLSET_VERSION}/root/usr/lib64:/opt/rh/gcc-toolset-${GCCTOOLSET_VERSION}/root/usr/lib:$LD_LIBRARY_PATH
# git236+ would refuse to run git commands in repos owned by other users
# Which causes version check to fail, as pytorch repo is bind-mounted into the image
# Override this behaviour by treating every folder as safe
# For more details see https://github.com/pytorch/pytorch/issues/78659#issuecomment-1144107327
RUN git config --global --add safe.directory "*"
FROM base as final
# remove unncessary python versions
RUN rm -rf /opt/python/cp26-cp26m /opt/_internal/cpython-2.6.9-ucs2
RUN rm -rf /opt/python/cp26-cp26mu /opt/_internal/cpython-2.6.9-ucs4
RUN rm -rf /opt/python/cp33-cp33m /opt/_internal/cpython-3.3.6
RUN rm -rf /opt/python/cp34-cp34m /opt/_internal/cpython-3.4.6

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FROM quay.io/pypa/manylinux2014_aarch64 as base
# Graviton needs GCC 10 for the build
ARG DEVTOOLSET_VERSION=10
# Language variabes
ENV LC_ALL=en_US.UTF-8
ENV LANG=en_US.UTF-8
ENV LANGUAGE=en_US.UTF-8
# Installed needed OS packages. This is to support all
# the binary builds (torch, vision, audio, text, data)
RUN yum -y install epel-release
RUN yum -y update
RUN yum install -y \
autoconf \
automake \
bison \
bzip2 \
curl \
diffutils \
file \
git \
make \
patch \
perl \
unzip \
util-linux \
wget \
which \
xz \
yasm \
less \
zstd \
libgomp \
sudo \
devtoolset-${DEVTOOLSET_VERSION}-gcc \
devtoolset-${DEVTOOLSET_VERSION}-gcc-c++ \
devtoolset-${DEVTOOLSET_VERSION}-gcc-gfortran \
devtoolset-${DEVTOOLSET_VERSION}-binutils
# Ensure the expected devtoolset is used
ENV PATH=/opt/rh/devtoolset-${DEVTOOLSET_VERSION}/root/usr/bin:$PATH
ENV LD_LIBRARY_PATH=/opt/rh/devtoolset-${DEVTOOLSET_VERSION}/root/usr/lib64:/opt/rh/devtoolset-${DEVTOOLSET_VERSION}/root/usr/lib:$LD_LIBRARY_PATH
# git236+ would refuse to run git commands in repos owned by other users
# Which causes version check to fail, as pytorch repo is bind-mounted into the image
# Override this behaviour by treating every folder as safe
# For more details see https://github.com/pytorch/pytorch/issues/78659#issuecomment-1144107327
RUN git config --global --add safe.directory "*"
###############################################################################
# libglfortran.a hack
#
# libgfortran.a from quay.io/pypa/manylinux2014_aarch64 is not compiled with -fPIC.
# This causes __stack_chk_guard@@GLIBC_2.17 on pytorch build. To solve, get
# ubuntu's libgfortran.a which is compiled with -fPIC
# NOTE: Need a better way to get this library as Ubuntu's package can be removed by the vender, or changed
###############################################################################
RUN cd ~/ \
&& curl -L -o ~/libgfortran-10-dev.deb http://ports.ubuntu.com/ubuntu-ports/pool/universe/g/gcc-10/libgfortran-10-dev_10.5.0-1ubuntu1_arm64.deb \
&& ar x ~/libgfortran-10-dev.deb \
&& tar --use-compress-program=unzstd -xvf data.tar.zst -C ~/ \
&& cp -f ~/usr/lib/gcc/aarch64-linux-gnu/10/libgfortran.a /opt/rh/devtoolset-10/root/usr/lib/gcc/aarch64-redhat-linux/10/
# install cmake
RUN yum install -y cmake3 && \
ln -s /usr/bin/cmake3 /usr/bin/cmake
FROM base as openssl
# Install openssl (this must precede `build python` step)
# (In order to have a proper SSL module, Python is compiled
# against a recent openssl [see env vars above], which is linked
# statically. We delete openssl afterwards.)
ADD ./common/install_openssl.sh install_openssl.sh
RUN bash ./install_openssl.sh && rm install_openssl.sh
ENV SSL_CERT_FILE=/opt/_internal/certs.pem
FROM base as openblas
# Install openblas
ADD ./common/install_openblas.sh install_openblas.sh
RUN bash ./install_openblas.sh && rm install_openblas.sh
FROM openssl as final
# remove unncessary python versions
RUN rm -rf /opt/python/cp26-cp26m /opt/_internal/cpython-2.6.9-ucs2
RUN rm -rf /opt/python/cp26-cp26mu /opt/_internal/cpython-2.6.9-ucs4
RUN rm -rf /opt/python/cp33-cp33m /opt/_internal/cpython-3.3.6
RUN rm -rf /opt/python/cp34-cp34m /opt/_internal/cpython-3.4.6
COPY --from=openblas /opt/OpenBLAS/ /opt/OpenBLAS/
ENV LD_LIBRARY_PATH=/opt/OpenBLAS/lib:$LD_LIBRARY_PATH

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FROM quay.io/pypa/manylinux_2_28_aarch64 as base
# Cuda ARM build needs gcc 11
ARG DEVTOOLSET_VERSION=11
# Language variables
ENV LC_ALL=en_US.UTF-8
ENV LANG=en_US.UTF-8
ENV LANGUAGE=en_US.UTF-8
# Installed needed OS packages. This is to support all
# the binary builds (torch, vision, audio, text, data)
RUN yum -y install epel-release
RUN yum -y update
RUN yum install -y \
autoconf \
automake \
bison \
bzip2 \
curl \
diffutils \
file \
git \
make \
patch \
perl \
unzip \
util-linux \
wget \
which \
xz \
yasm \
less \
zstd \
libgomp \
sudo \
gcc-toolset-${DEVTOOLSET_VERSION}-toolchain
# Ensure the expected devtoolset is used
ENV PATH=/opt/rh/gcc-toolset-${DEVTOOLSET_VERSION}/root/usr/bin:$PATH
ENV LD_LIBRARY_PATH=/opt/rh/gcc-toolset-${DEVTOOLSET_VERSION}/root/usr/lib64:/opt/rh/gcc-toolset-${DEVTOOLSET_VERSION}/root/usr/lib:$LD_LIBRARY_PATH
# git236+ would refuse to run git commands in repos owned by other users
# Which causes version check to fail, as pytorch repo is bind-mounted into the image
# Override this behaviour by treating every folder as safe
# For more details see https://github.com/pytorch/pytorch/issues/78659#issuecomment-1144107327
RUN git config --global --add safe.directory "*"
FROM base as openssl
# Install openssl (this must precede `build python` step)
# (In order to have a proper SSL module, Python is compiled
# against a recent openssl [see env vars above], which is linked
# statically. We delete openssl afterwards.)
ADD ./common/install_openssl.sh install_openssl.sh
RUN bash ./install_openssl.sh && rm install_openssl.sh
ENV SSL_CERT_FILE=/opt/_internal/certs.pem
FROM openssl as final
# remove unncessary python versions
RUN rm -rf /opt/python/cp26-cp26m /opt/_internal/cpython-2.6.9-ucs2
RUN rm -rf /opt/python/cp26-cp26mu /opt/_internal/cpython-2.6.9-ucs4
RUN rm -rf /opt/python/cp33-cp33m /opt/_internal/cpython-3.3.6
RUN rm -rf /opt/python/cp34-cp34m /opt/_internal/cpython-3.4.6
FROM base as cuda
ARG BASE_CUDA_VERSION
# Install CUDA
ADD ./common/install_cuda_aarch64.sh install_cuda_aarch64.sh
RUN bash ./install_cuda_aarch64.sh ${BASE_CUDA_VERSION} && rm install_cuda_aarch64.sh
FROM base as magma
ARG BASE_CUDA_VERSION
# Install magma
ADD ./common/install_magma.sh install_magma.sh
RUN bash ./install_magma.sh ${BASE_CUDA_VERSION} && rm install_magma.sh
FROM base as nvpl
# Install nvpl
ADD ./common/install_nvpl.sh install_nvpl.sh
RUN bash ./install_nvpl.sh && rm install_nvpl.sh
FROM final as cuda_final
ARG BASE_CUDA_VERSION
RUN rm -rf /usr/local/cuda-${BASE_CUDA_VERSION}
COPY --from=cuda /usr/local/cuda-${BASE_CUDA_VERSION} /usr/local/cuda-${BASE_CUDA_VERSION}
COPY --from=magma /usr/local/cuda-${BASE_CUDA_VERSION} /usr/local/cuda-${BASE_CUDA_VERSION}
COPY --from=nvpl /opt/nvpl/lib/ /usr/local/lib/
COPY --from=nvpl /opt/nvpl/include/ /usr/local/include/
RUN ln -sf /usr/local/cuda-${BASE_CUDA_VERSION} /usr/local/cuda
ENV PATH=/usr/local/cuda/bin:$PATH

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FROM centos:8 as base
ENV LC_ALL en_US.UTF-8
ENV LANG en_US.UTF-8
ENV LANGUAGE en_US.UTF-8
ENV PATH /opt/rh/gcc-toolset-11/root/bin/:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin
# change to a valid repo
RUN sed -i 's|#baseurl=http://mirror.centos.org|baseurl=http://vault.centos.org|g' /etc/yum.repos.d/CentOS-Linux-*.repo
# enable to install ninja-build
RUN sed -i 's|enabled=0|enabled=1|g' /etc/yum.repos.d/CentOS-Linux-PowerTools.repo
RUN yum -y update
RUN yum install -y wget curl perl util-linux xz bzip2 git patch which zlib-devel sudo
RUN yum install -y autoconf automake make cmake gdb gcc-toolset-11-gcc-c++
FROM base as openssl
ADD ./common/install_openssl.sh install_openssl.sh
RUN bash ./install_openssl.sh && rm install_openssl.sh
# Install python
FROM base as python
RUN yum install -y openssl-devel zlib-devel bzip2-devel ncurses-devel sqlite-devel readline-devel tk-devel gdbm-devel libpcap-devel xz-devel libffi-devel
ADD common/install_cpython.sh install_cpython.sh
RUN bash ./install_cpython.sh && rm install_cpython.sh
FROM base as conda
ADD ./common/install_conda_docker.sh install_conda.sh
RUN bash ./install_conda.sh && rm install_conda.sh
RUN /opt/conda/bin/conda install -y cmake
FROM base as intel
# Install MKL
COPY --from=python /opt/python /opt/python
COPY --from=python /opt/_internal /opt/_internal
COPY --from=conda /opt/conda /opt/conda
ENV PATH=/opt/conda/bin:$PATH
ADD ./common/install_mkl.sh install_mkl.sh
RUN bash ./install_mkl.sh && rm install_mkl.sh
FROM base as patchelf
ADD ./common/install_patchelf.sh install_patchelf.sh
RUN bash ./install_patchelf.sh && rm install_patchelf.sh
RUN cp $(which patchelf) /patchelf
FROM base as jni
ADD ./common/install_jni.sh install_jni.sh
ADD ./java/jni.h jni.h
RUN bash ./install_jni.sh && rm install_jni.sh
FROM base as libpng
ADD ./common/install_libpng.sh install_libpng.sh
RUN bash ./install_libpng.sh && rm install_libpng.sh
FROM base as final
COPY --from=openssl /opt/openssl /opt/openssl
COPY --from=python /opt/python /opt/python
COPY --from=python /opt/_internal /opt/_internal
COPY --from=intel /opt/intel /opt/intel
COPY --from=conda /opt/conda /opt/conda
COPY --from=patchelf /usr/local/bin/patchelf /usr/local/bin/patchelf
COPY --from=jni /usr/local/include/jni.h /usr/local/include/jni.h
COPY --from=libpng /usr/local/bin/png* /usr/local/bin/
COPY --from=libpng /usr/local/bin/libpng* /usr/local/bin/
COPY --from=libpng /usr/local/include/png* /usr/local/include/
COPY --from=libpng /usr/local/include/libpng* /usr/local/include/
COPY --from=libpng /usr/local/lib/libpng* /usr/local/lib/
COPY --from=libpng /usr/local/lib/pkgconfig /usr/local/lib/pkgconfig
RUN yum install -y ninja-build

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FROM --platform=linux/s390x docker.io/ubuntu:24.04 as base
# Language variables
ENV LC_ALL=C.UTF-8
ENV LANG=C.UTF-8
ENV LANGUAGE=C.UTF-8
# Installed needed OS packages. This is to support all
# the binary builds (torch, vision, audio, text, data)
RUN apt update ; apt upgrade -y
RUN apt install -y \
build-essential \
autoconf \
automake \
bzip2 \
curl \
diffutils \
file \
git \
make \
patch \
perl \
unzip \
util-linux \
wget \
which \
xz-utils \
less \
zstd \
cmake \
python3 \
python3-dev \
python3-setuptools \
python3-yaml \
python3-typing-extensions \
libblas-dev \
libopenblas-dev \
liblapack-dev \
libatlas-base-dev
# git236+ would refuse to run git commands in repos owned by other users
# Which causes version check to fail, as pytorch repo is bind-mounted into the image
# Override this behaviour by treating every folder as safe
# For more details see https://github.com/pytorch/pytorch/issues/78659#issuecomment-1144107327
RUN git config --global --add safe.directory "*"
FROM base as openssl
# Install openssl (this must precede `build python` step)
# (In order to have a proper SSL module, Python is compiled
# against a recent openssl [see env vars above], which is linked
# statically. We delete openssl afterwards.)
ADD ./common/install_openssl.sh install_openssl.sh
RUN bash ./install_openssl.sh && rm install_openssl.sh
ENV SSL_CERT_FILE=/opt/_internal/certs.pem
# EPEL for cmake
FROM base as patchelf
# Install patchelf
ADD ./common/install_patchelf.sh install_patchelf.sh
RUN bash ./install_patchelf.sh && rm install_patchelf.sh
RUN cp $(which patchelf) /patchelf
FROM patchelf as python
# build python
COPY manywheel/build_scripts /build_scripts
ADD ./common/install_cpython.sh /build_scripts/install_cpython.sh
RUN bash build_scripts/build.sh && rm -r build_scripts
FROM openssl as final
COPY --from=python /opt/python /opt/python
COPY --from=python /opt/_internal /opt/_internal
COPY --from=python /opt/python/cp39-cp39/bin/auditwheel /usr/local/bin/auditwheel
COPY --from=patchelf /usr/local/bin/patchelf /usr/local/bin/patchelf

View File

@ -1,161 +0,0 @@
#!/usr/bin/env bash
# Script used only in CD pipeline
set -eou pipefail
TOPDIR=$(git rev-parse --show-toplevel)
image="$1"
shift
if [ -z "${image}" ]; then
echo "Usage: $0 IMAGE"
exit 1
fi
DOCKER_IMAGE="pytorch/${image}"
DOCKER_REGISTRY="${DOCKER_REGISTRY:-docker.io}"
GPU_ARCH_TYPE=${GPU_ARCH_TYPE:-cpu}
GPU_ARCH_VERSION=${GPU_ARCH_VERSION:-}
MANY_LINUX_VERSION=${MANY_LINUX_VERSION:-}
DOCKERFILE_SUFFIX=${DOCKERFILE_SUFFIX:-}
WITH_PUSH=${WITH_PUSH:-}
case ${GPU_ARCH_TYPE} in
cpu)
TARGET=cpu_final
DOCKER_TAG=cpu
GPU_IMAGE=centos:7
DOCKER_GPU_BUILD_ARG=" --build-arg DEVTOOLSET_VERSION=9"
;;
cpu-manylinux_2_28)
TARGET=cpu_final
DOCKER_TAG=cpu
GPU_IMAGE=amd64/almalinux:8
DOCKER_GPU_BUILD_ARG=" --build-arg DEVTOOLSET_VERSION=11"
MANY_LINUX_VERSION="2_28"
;;
cpu-aarch64)
TARGET=final
DOCKER_TAG=cpu-aarch64
GPU_IMAGE=arm64v8/centos:7
DOCKER_GPU_BUILD_ARG=" --build-arg DEVTOOLSET_VERSION=10"
MANY_LINUX_VERSION="aarch64"
;;
cpu-aarch64-2_28)
TARGET=final
DOCKER_TAG=cpu-aarch64
GPU_IMAGE=arm64v8/almalinux:8
DOCKER_GPU_BUILD_ARG=" --build-arg DEVTOOLSET_VERSION=11"
MANY_LINUX_VERSION="2_28_aarch64"
;;
cpu-cxx11-abi)
TARGET=final
DOCKER_TAG=cpu-cxx11-abi
GPU_IMAGE=""
DOCKER_GPU_BUILD_ARG=" --build-arg DEVTOOLSET_VERSION=9"
MANY_LINUX_VERSION="cxx11-abi"
;;
cpu-s390x)
TARGET=final
DOCKER_TAG=cpu-s390x
GPU_IMAGE=redhat/ubi9
DOCKER_GPU_BUILD_ARG=""
MANY_LINUX_VERSION="s390x"
;;
cuda)
TARGET=cuda_final
DOCKER_TAG=cuda${GPU_ARCH_VERSION}
# Keep this up to date with the minimum version of CUDA we currently support
GPU_IMAGE=centos:7
DOCKER_GPU_BUILD_ARG="--build-arg BASE_CUDA_VERSION=${GPU_ARCH_VERSION} --build-arg DEVTOOLSET_VERSION=9"
;;
cuda-manylinux_2_28)
TARGET=cuda_final
DOCKER_TAG=cuda${GPU_ARCH_VERSION}
GPU_IMAGE=amd64/almalinux:8
DOCKER_GPU_BUILD_ARG="--build-arg BASE_CUDA_VERSION=${GPU_ARCH_VERSION} --build-arg DEVTOOLSET_VERSION=11"
MANY_LINUX_VERSION="2_28"
;;
cuda-aarch64)
TARGET=cuda_final
DOCKER_TAG=cuda${GPU_ARCH_VERSION}
GPU_IMAGE=arm64v8/centos:7
DOCKER_GPU_BUILD_ARG="--build-arg BASE_CUDA_VERSION=${GPU_ARCH_VERSION} --build-arg DEVTOOLSET_VERSION=11"
MANY_LINUX_VERSION="aarch64"
DOCKERFILE_SUFFIX="_cuda_aarch64"
;;
rocm)
TARGET=rocm_final
DOCKER_TAG=rocm${GPU_ARCH_VERSION}
GPU_IMAGE=rocm/dev-centos-7:${GPU_ARCH_VERSION}-complete
PYTORCH_ROCM_ARCH="gfx900;gfx906;gfx908;gfx90a;gfx1030;gfx1100"
ROCM_REGEX="([0-9]+)\.([0-9]+)[\.]?([0-9]*)"
if [[ $GPU_ARCH_VERSION =~ $ROCM_REGEX ]]; then
ROCM_VERSION_INT=$((${BASH_REMATCH[1]}*10000 + ${BASH_REMATCH[2]}*100 + ${BASH_REMATCH[3]:-0}))
else
echo "ERROR: rocm regex failed"
exit 1
fi
if [[ $ROCM_VERSION_INT -ge 60000 ]]; then
PYTORCH_ROCM_ARCH+=";gfx942"
fi
DOCKER_GPU_BUILD_ARG="--build-arg ROCM_VERSION=${GPU_ARCH_VERSION} --build-arg PYTORCH_ROCM_ARCH=${PYTORCH_ROCM_ARCH} --build-arg DEVTOOLSET_VERSION=9"
;;
xpu)
TARGET=xpu_final
DOCKER_TAG=xpu
GPU_IMAGE=amd64/almalinux:8
DOCKER_GPU_BUILD_ARG=" --build-arg DEVTOOLSET_VERSION=11"
MANY_LINUX_VERSION="2_28"
;;
*)
echo "ERROR: Unrecognized GPU_ARCH_TYPE: ${GPU_ARCH_TYPE}"
exit 1
;;
esac
IMAGES=''
if [[ -n ${MANY_LINUX_VERSION} && -z ${DOCKERFILE_SUFFIX} ]]; then
DOCKERFILE_SUFFIX=_${MANY_LINUX_VERSION}
fi
(
set -x
# TODO: Remove LimitNOFILE=1048576 patch once https://github.com/pytorch/test-infra/issues/5712
# is resolved. This patch is required in order to fix timing out of Docker build on Amazon Linux 2023.
sudo sed -i s/LimitNOFILE=infinity/LimitNOFILE=1048576/ /usr/lib/systemd/system/docker.service
sudo systemctl daemon-reload
sudo systemctl restart docker
DOCKER_BUILDKIT=1 docker build \
${DOCKER_GPU_BUILD_ARG} \
--build-arg "GPU_IMAGE=${GPU_IMAGE}" \
--target "${TARGET}" \
-t "${DOCKER_IMAGE}" \
$@ \
-f "${TOPDIR}/.ci/docker/manywheel/Dockerfile${DOCKERFILE_SUFFIX}" \
"${TOPDIR}/.ci/docker/"
)
GITHUB_REF=${GITHUB_REF:-$(git symbolic-ref -q HEAD || git describe --tags --exact-match)}
GIT_BRANCH_NAME=${GITHUB_REF##*/}
GIT_COMMIT_SHA=${GITHUB_SHA:-$(git rev-parse HEAD)}
DOCKER_IMAGE_BRANCH_TAG=${DOCKER_IMAGE}-${GIT_BRANCH_NAME}
DOCKER_IMAGE_SHA_TAG=${DOCKER_IMAGE}-${GIT_COMMIT_SHA}
if [[ "${WITH_PUSH}" == true ]]; then
(
set -x
docker push "${DOCKER_IMAGE}"
if [[ -n ${GITHUB_REF} ]]; then
docker tag ${DOCKER_IMAGE} ${DOCKER_IMAGE_BRANCH_TAG}
docker tag ${DOCKER_IMAGE} ${DOCKER_IMAGE_SHA_TAG}
docker push "${DOCKER_IMAGE_BRANCH_TAG}"
docker push "${DOCKER_IMAGE_SHA_TAG}"
fi
)
fi

View File

@ -1,131 +0,0 @@
#!/bin/bash
# Top-level build script called from Dockerfile
# Script used only in CD pipeline
# Stop at any error, show all commands
set -ex
# openssl version to build, with expected sha256 hash of .tar.gz
# archive
OPENSSL_ROOT=openssl-1.1.1l
OPENSSL_HASH=0b7a3e5e59c34827fe0c3a74b7ec8baef302b98fa80088d7f9153aa16fa76bd1
DEVTOOLS_HASH=a8ebeb4bed624700f727179e6ef771dafe47651131a00a78b342251415646acc
PATCHELF_HASH=d9afdff4baeacfbc64861454f368b7f2c15c44d245293f7587bbf726bfe722fb
CURL_ROOT=curl-7.73.0
CURL_HASH=cf34fe0b07b800f1c01a499a6e8b2af548f6d0e044dca4a29d88a4bee146d131
AUTOCONF_ROOT=autoconf-2.69
AUTOCONF_HASH=954bd69b391edc12d6a4a51a2dd1476543da5c6bbf05a95b59dc0dd6fd4c2969
# Get build utilities
MY_DIR=$(dirname "${BASH_SOURCE[0]}")
source $MY_DIR/build_utils.sh
if [ "$(uname -m)" != "s390x" ] ; then
# Dependencies for compiling Python that we want to remove from
# the final image after compiling Python
PYTHON_COMPILE_DEPS="zlib-devel bzip2-devel ncurses-devel sqlite-devel readline-devel tk-devel gdbm-devel db4-devel libpcap-devel xz-devel libffi-devel"
# Libraries that are allowed as part of the manylinux1 profile
MANYLINUX1_DEPS="glibc-devel libstdc++-devel glib2-devel libX11-devel libXext-devel libXrender-devel mesa-libGL-devel libICE-devel libSM-devel ncurses-devel"
# Development tools and libraries
yum -y install bzip2 make git patch unzip bison yasm diffutils \
automake which file cmake28 \
kernel-devel-`uname -r` \
${PYTHON_COMPILE_DEPS}
else
# Dependencies for compiling Python that we want to remove from
# the final image after compiling Python
PYTHON_COMPILE_DEPS="zlib1g-dev libbz2-dev libncurses-dev libsqlite3-dev libdb-dev libpcap-dev liblzma-dev libffi-dev"
# Libraries that are allowed as part of the manylinux1 profile
MANYLINUX1_DEPS="libglib2.0-dev libX11-dev libncurses-dev"
# Development tools and libraries
apt install -y bzip2 make git patch unzip diffutils \
automake which file cmake \
linux-headers-virtual \
${PYTHON_COMPILE_DEPS}
fi
# Install newest autoconf
build_autoconf $AUTOCONF_ROOT $AUTOCONF_HASH
autoconf --version
# Compile the latest Python releases.
# (In order to have a proper SSL module, Python is compiled
# against a recent openssl [see env vars above], which is linked
# statically. We delete openssl afterwards.)
build_openssl $OPENSSL_ROOT $OPENSSL_HASH
/build_scripts/install_cpython.sh
PY39_BIN=/opt/python/cp39-cp39/bin
# Our openssl doesn't know how to find the system CA trust store
# (https://github.com/pypa/manylinux/issues/53)
# And it's not clear how up-to-date that is anyway
# So let's just use the same one pip and everyone uses
$PY39_BIN/pip install certifi
ln -s $($PY39_BIN/python -c 'import certifi; print(certifi.where())') \
/opt/_internal/certs.pem
# If you modify this line you also have to modify the versions in the
# Dockerfiles:
export SSL_CERT_FILE=/opt/_internal/certs.pem
# Install newest curl
build_curl $CURL_ROOT $CURL_HASH
rm -rf /usr/local/include/curl /usr/local/lib/libcurl* /usr/local/lib/pkgconfig/libcurl.pc
hash -r
curl --version
curl-config --features
# Install patchelf (latest with unreleased bug fixes)
curl -sLOk https://nixos.org/releases/patchelf/patchelf-0.10/patchelf-0.10.tar.gz
# check_sha256sum patchelf-0.9njs2.tar.gz $PATCHELF_HASH
tar -xzf patchelf-0.10.tar.gz
(cd patchelf-0.10 && ./configure && make && make install)
rm -rf patchelf-0.10.tar.gz patchelf-0.10
# Install latest pypi release of auditwheel
$PY39_BIN/pip install auditwheel
ln -s $PY39_BIN/auditwheel /usr/local/bin/auditwheel
# Clean up development headers and other unnecessary stuff for
# final image
if [ "$(uname -m)" != "s390x" ] ; then
yum -y erase wireless-tools gtk2 libX11 hicolor-icon-theme \
avahi freetype bitstream-vera-fonts \
${PYTHON_COMPILE_DEPS} || true > /dev/null 2>&1
yum -y install ${MANYLINUX1_DEPS}
yum -y clean all > /dev/null 2>&1
yum list installed
else
apt purge -y ${PYTHON_COMPILE_DEPS} || true > /dev/null 2>&1
fi
# we don't need libpython*.a, and they're many megabytes
find /opt/_internal -name '*.a' -print0 | xargs -0 rm -f
# Strip what we can -- and ignore errors, because this just attempts to strip
# *everything*, including non-ELF files:
find /opt/_internal -type f -print0 \
| xargs -0 -n1 strip --strip-unneeded 2>/dev/null || true
# We do not need the Python test suites, or indeed the precompiled .pyc and
# .pyo files. Partially cribbed from:
# https://github.com/docker-library/python/blob/master/3.4/slim/Dockerfile
find /opt/_internal \
\( -type d -a -name test -o -name tests \) \
-o \( -type f -a -name '*.pyc' -o -name '*.pyo' \) \
-print0 | xargs -0 rm -f
for PYTHON in /opt/python/*/bin/python; do
# Smoke test to make sure that our Pythons work, and do indeed detect as
# being manylinux compatible:
$PYTHON $MY_DIR/manylinux1-check.py
# Make sure that SSL cert checking works
$PYTHON $MY_DIR/ssl-check.py
done
# Fix libc headers to remain compatible with C99 compilers.
find /usr/include/ -type f -exec sed -i 's/\bextern _*inline_*\b/extern __inline __attribute__ ((__gnu_inline__))/g' {} +
# Now we can delete our built SSL
rm -rf /usr/local/ssl

View File

@ -1,91 +0,0 @@
#!/bin/bash
# Helper utilities for build
# Script used only in CD pipeline
OPENSSL_DOWNLOAD_URL=https://www.openssl.org/source/old/1.1.1/
CURL_DOWNLOAD_URL=https://curl.askapache.com/download
AUTOCONF_DOWNLOAD_URL=https://ftp.gnu.org/gnu/autoconf
function check_var {
if [ -z "$1" ]; then
echo "required variable not defined"
exit 1
fi
}
function do_openssl_build {
./config no-ssl2 no-shared -fPIC --prefix=/usr/local/ssl > /dev/null
make > /dev/null
make install > /dev/null
}
function check_sha256sum {
local fname=$1
check_var ${fname}
local sha256=$2
check_var ${sha256}
echo "${sha256} ${fname}" > ${fname}.sha256
sha256sum -c ${fname}.sha256
rm -f ${fname}.sha256
}
function build_openssl {
local openssl_fname=$1
check_var ${openssl_fname}
local openssl_sha256=$2
check_var ${openssl_sha256}
check_var ${OPENSSL_DOWNLOAD_URL}
curl -sLO ${OPENSSL_DOWNLOAD_URL}/${openssl_fname}.tar.gz
check_sha256sum ${openssl_fname}.tar.gz ${openssl_sha256}
tar -xzf ${openssl_fname}.tar.gz
(cd ${openssl_fname} && do_openssl_build)
rm -rf ${openssl_fname} ${openssl_fname}.tar.gz
}
function do_curl_build {
LIBS=-ldl ./configure --with-ssl --disable-shared > /dev/null
make > /dev/null
make install > /dev/null
}
function build_curl {
local curl_fname=$1
check_var ${curl_fname}
local curl_sha256=$2
check_var ${curl_sha256}
check_var ${CURL_DOWNLOAD_URL}
curl -sLO ${CURL_DOWNLOAD_URL}/${curl_fname}.tar.bz2
check_sha256sum ${curl_fname}.tar.bz2 ${curl_sha256}
tar -jxf ${curl_fname}.tar.bz2
(cd ${curl_fname} && do_curl_build)
rm -rf ${curl_fname} ${curl_fname}.tar.bz2
}
function do_standard_install {
./configure > /dev/null
make > /dev/null
make install > /dev/null
}
function build_autoconf {
local autoconf_fname=$1
check_var ${autoconf_fname}
local autoconf_sha256=$2
check_var ${autoconf_sha256}
check_var ${AUTOCONF_DOWNLOAD_URL}
curl -sLO ${AUTOCONF_DOWNLOAD_URL}/${autoconf_fname}.tar.gz
check_sha256sum ${autoconf_fname}.tar.gz ${autoconf_sha256}
tar -zxf ${autoconf_fname}.tar.gz
(cd ${autoconf_fname} && do_standard_install)
rm -rf ${autoconf_fname} ${autoconf_fname}.tar.gz
}

View File

@ -1,60 +0,0 @@
# Logic copied from PEP 513
def is_manylinux1_compatible():
# Only Linux, and only x86-64 / i686
from distutils.util import get_platform
if get_platform() not in ["linux-x86_64", "linux-i686", "linux-s390x"]:
return False
# Check for presence of _manylinux module
try:
import _manylinux
return bool(_manylinux.manylinux1_compatible)
except (ImportError, AttributeError):
# Fall through to heuristic check below
pass
# Check glibc version. CentOS 5 uses glibc 2.5.
return have_compatible_glibc(2, 5)
def have_compatible_glibc(major, minimum_minor):
import ctypes
process_namespace = ctypes.CDLL(None)
try:
gnu_get_libc_version = process_namespace.gnu_get_libc_version
except AttributeError:
# Symbol doesn't exist -> therefore, we are not linked to
# glibc.
return False
# Call gnu_get_libc_version, which returns a string like "2.5".
gnu_get_libc_version.restype = ctypes.c_char_p
version_str = gnu_get_libc_version()
# py2 / py3 compatibility:
if not isinstance(version_str, str):
version_str = version_str.decode("ascii")
# Parse string and check against requested version.
version = [int(piece) for piece in version_str.split(".")]
assert len(version) == 2
if major != version[0]:
return False
if minimum_minor > version[1]:
return False
return True
import sys
if is_manylinux1_compatible():
print(f"{sys.executable} is manylinux1 compatible")
sys.exit(0)
else:
print(f"{sys.executable} is NOT manylinux1 compatible")
sys.exit(1)

View File

@ -1,35 +0,0 @@
# cf. https://github.com/pypa/manylinux/issues/53
GOOD_SSL = "https://google.com"
BAD_SSL = "https://self-signed.badssl.com"
import sys
print("Testing SSL certificate checking for Python:", sys.version)
if sys.version_info[:2] < (2, 7) or sys.version_info[:2] < (3, 4):
print("This version never checks SSL certs; skipping tests")
sys.exit(0)
if sys.version_info[0] >= 3:
from urllib.request import urlopen
EXC = OSError
else:
from urllib import urlopen
EXC = IOError
print(f"Connecting to {GOOD_SSL} should work")
urlopen(GOOD_SSL)
print("...it did, yay.")
print(f"Connecting to {BAD_SSL} should fail")
try:
urlopen(BAD_SSL)
# If we get here then we failed:
print("...it DIDN'T!!!!!11!!1one!")
sys.exit(1)
except EXC:
print("...it did, yay.")

View File

@ -1,344 +0,0 @@
# Python dependencies required for unit tests
#awscli==1.6 #this breaks some platforms
#Description: AWS command line interface
#Pinned versions: 1.6
#test that import:
boto3==1.19.12
#Description: AWS SDK for python
#Pinned versions: 1.19.12, 1.16.34
#test that import:
click
#Description: Command Line Interface Creation Kit
#Pinned versions:
#test that import:
coremltools==5.0b5 ; python_version < "3.12"
#Description: Apple framework for ML integration
#Pinned versions: 5.0b5
#test that import:
#dataclasses #this breaks some platforms
#Description: Provides decorators for auto adding special methods to user classes
#Pinned versions:
#test that import:
dill==0.3.7
#Description: dill extends pickle with serializing and de-serializing for most built-ins
#Pinned versions: 0.3.7
#test that import: dynamo/test_replay_record.py test_dataloader.py test_datapipe.py test_serialization.py
expecttest==0.2.1
#Description: method for writing tests where test framework auto populates
# the expected output based on previous runs
#Pinned versions: 0.2.1
#test that import:
fbscribelogger==0.1.6
#Description: write to scribe from authenticated jobs on CI
#Pinned versions: 0.1.6
#test that import:
flatbuffers==2.0
#Description: cross platform serialization library
#Pinned versions: 2.0
#test that import:
hypothesis==5.35.1
# Pin hypothesis to avoid flakiness: https://github.com/pytorch/pytorch/issues/31136
#Description: advanced library for generating parametrized tests
#Pinned versions: 3.44.6, 4.53.2
#test that import: test_xnnpack_integration.py, test_pruning_op.py, test_nn.py
junitparser==2.1.1
#Description: unitparser handles JUnit/xUnit Result XML files
#Pinned versions: 2.1.1
#test that import:
lark==0.12.0
#Description: parser
#Pinned versions: 0.12.0
#test that import:
librosa>=0.6.2 ; python_version < "3.11"
#Description: A python package for music and audio analysis
#Pinned versions: >=0.6.2
#test that import: test_spectral_ops.py
#mkl #this breaks linux-bionic-rocm4.5-py3.7
#Description: Intel oneAPI Math Kernel Library
#Pinned versions:
#test that import: test_profiler.py, test_public_bindings.py, test_testing.py,
#test_nn.py, test_mkldnn.py, test_jit.py, test_fx_experimental.py,
#test_autograd.py
#mkl-devel
# see mkl
#mock
#Description: A testing library that allows you to replace parts of your
#system under test with mock objects
#Pinned versions:
#test that import: test_modules.py, test_nn.py,
#test_testing.py
#MonkeyType # breaks pytorch-xla-linux-bionic-py3.7-clang8
#Description: collects runtime types of function arguments and return
#values, and can automatically generate stub files
#Pinned versions:
#test that import:
mypy==1.11.2
# Pin MyPy version because new errors are likely to appear with each release
#Description: linter
#Pinned versions: 1.10.0
#test that import: test_typing.py, test_type_hints.py
networkx==2.8.8
#Description: creation, manipulation, and study of
#the structure, dynamics, and functions of complex networks
#Pinned versions: 2.8.8
#test that import: functorch
#ninja
#Description: build system. Note that it install from
#here breaks things so it is commented out
#Pinned versions: 1.10.0.post1
#test that import: run_test.py, test_cpp_extensions_aot.py,test_determination.py
numba==0.49.0 ; python_version < "3.9"
numba==0.55.2 ; python_version == "3.9"
numba==0.55.2 ; python_version == "3.10"
#Description: Just-In-Time Compiler for Numerical Functions
#Pinned versions: 0.54.1, 0.49.0, <=0.49.1
#test that import: test_numba_integration.py
#For numba issue see https://github.com/pytorch/pytorch/issues/51511
#numpy
#Description: Provides N-dimensional arrays and linear algebra
#Pinned versions: 1.20
#test that import: test_view_ops.py, test_unary_ufuncs.py, test_type_promotion.py,
#test_type_info.py, test_torch.py, test_tensorexpr_pybind.py, test_tensorexpr.py,
#test_tensorboard.py, test_tensor_creation_ops.py, test_static_runtime.py,
#test_spectral_ops.py, test_sort_and_select.py, test_shape_ops.py,
#test_segment_reductions.py, test_reductions.py, test_pruning_op.py,
#test_overrides.py, test_numpy_interop.py, test_numba_integration.py
#test_nn.py, test_namedtensor.py, test_linalg.py, test_jit_cuda_fuser.py,
#test_jit.py, test_indexing.py, test_datapipe.py, test_dataloader.py,
#test_binary_ufuncs.py
#onnxruntime
#Description: scoring engine for Open Neural Network Exchange (ONNX) models
#Pinned versions: 1.9.0
#test that import:
opt-einsum==3.3
#Description: Python library to optimize tensor contraction order, used in einsum
#Pinned versions: 3.3
#test that import: test_linalg.py
optree==0.12.1
#Description: A library for tree manipulation
#Pinned versions: 0.12.1
#test that import: test_vmap.py, test_aotdispatch.py, test_dynamic_shapes.py,
#test_pytree.py, test_ops.py, test_control_flow.py, test_modules.py,
#common_utils.py, test_eager_transforms.py, test_python_dispatch.py,
#test_expanded_weights.py, test_decomp.py, test_overrides.py, test_masked.py,
#test_ops.py, test_prims.py, test_subclass.py, test_functionalization.py,
#test_schema_check.py, test_profiler_tree.py, test_meta.py, test_torchxla_num_output.py,
#test_utils.py, test_proxy_tensor.py, test_memory_profiler.py, test_view_ops.py,
#test_pointwise_ops.py, test_dtensor_ops.py, test_torchinductor.py, test_fx.py,
#test_fake_tensor.py, test_mps.py
pillow==10.3.0
#Description: Python Imaging Library fork
#Pinned versions: 10.3.0
#test that import:
protobuf==3.20.2
#Description: Googles data interchange format
#Pinned versions: 3.20.1
#test that import: test_tensorboard.py
psutil
#Description: information on running processes and system utilization
#Pinned versions:
#test that import: test_profiler.py, test_openmp.py, test_dataloader.py
pytest==7.3.2
#Description: testing framework
#Pinned versions:
#test that import: test_typing.py, test_cpp_extensions_aot.py, run_test.py
pytest-xdist==3.3.1
#Description: plugin for running pytest in parallel
#Pinned versions:
#test that import:
pytest-flakefinder==1.1.0
#Description: plugin for rerunning tests a fixed number of times in pytest
#Pinned versions: 1.1.0
#test that import:
pytest-rerunfailures>=10.3
#Description: plugin for rerunning failure tests in pytest
#Pinned versions:
#test that import:
#pytest-benchmark
#Description: fixture for benchmarking code
#Pinned versions: 3.2.3
#test that import:
#pytest-sugar
#Description: shows failures and errors instantly
#Pinned versions:
#test that import:
xdoctest==1.1.0
#Description: runs doctests in pytest
#Pinned versions: 1.1.0
#test that import:
pygments==2.15.0
#Description: support doctest highlighting
#Pinned versions: 2.12.0
#test that import: the doctests
#PyYAML
#Description: data serialization format
#Pinned versions:
#test that import:
#requests
#Description: HTTP library
#Pinned versions:
#test that import: test_type_promotion.py
#rich
#Description: rich text and beautiful formatting in the terminal
#Pinned versions: 10.9.0
#test that import:
scikit-image==0.19.3 ; python_version < "3.10"
scikit-image==0.22.0 ; python_version >= "3.10"
#Description: image processing routines
#Pinned versions:
#test that import: test_nn.py
#scikit-learn
#Description: machine learning package
#Pinned versions: 0.20.3
#test that import:
scipy==1.10.1 ; python_version <= "3.11"
scipy==1.12.0 ; python_version == "3.12"
# Pin SciPy because of failing distribution tests (see #60347)
#Description: scientific python
#Pinned versions: 1.10.1
#test that import: test_unary_ufuncs.py, test_torch.py,test_tensor_creation_ops.py
#test_spectral_ops.py, test_sparse_csr.py, test_reductions.py,test_nn.py
#test_linalg.py, test_binary_ufuncs.py
#tabulate
#Description: Pretty-print tabular data
#Pinned versions:
#test that import:
tb-nightly==2.13.0a20230426
#Description: TensorBoard
#Pinned versions:
#test that import:
# needed by torchgen utils
typing-extensions
#Description: type hints for python
#Pinned versions:
#test that import:
#virtualenv
#Description: virtual environment for python
#Pinned versions:
#test that import:
unittest-xml-reporting<=3.2.0,>=2.0.0
#Description: saves unit test results to xml
#Pinned versions:
#test that import:
#lintrunner is supported on aarch64-linux only from 0.12.4 version
lintrunner==0.12.5
#Description: all about linters!
#Pinned versions: 0.12.5
#test that import:
redis>=4.0.0
#Description: redis database
#test that import: anything that tests OSS caching/mocking (inductor/test_codecache.py, inductor/test_max_autotune.py)
rockset==1.0.3
#Description: queries Rockset
#Pinned versions: 1.0.3
#test that import:
ghstack==0.8.0
#Description: ghstack tool
#Pinned versions: 0.8.0
#test that import:
jinja2==3.1.4
#Description: jinja2 template engine
#Pinned versions: 3.1.4
#test that import:
pytest-cpp==2.3.0
#Description: This is used by pytest to invoke C++ tests
#Pinned versions: 2.3.0
#test that import:
z3-solver==4.12.2.0
#Description: The Z3 Theorem Prover Project
#Pinned versions:
#test that import:
tensorboard==2.13.0
#Description: Also included in .ci/docker/requirements-docs.txt
#Pinned versions:
#test that import: test_tensorboard
pywavelets==1.4.1 ; python_version < "3.12"
pywavelets==1.5.0 ; python_version >= "3.12"
#Description: This is a requirement of scikit-image, we need to pin
# it here because 1.5.0 conflicts with numpy 1.21.2 used in CI
#Pinned versions: 1.4.1
#test that import:
lxml==5.0.0
#Description: This is a requirement of unittest-xml-reporting
# Python-3.9 binaries
PyGithub==2.3.0
sympy==1.12.1 ; python_version == "3.8"
sympy==1.13.1 ; python_version >= "3.9"
#Description: Required by coremltools, also pinned in .github/requirements/pip-requirements-macOS.txt
#Pinned versions:
#test that import:
onnx==1.16.1
#Description: Required by mypy and test_public_bindings.py when checking torch.onnx._internal
#Pinned versions:
#test that import:
onnxscript==0.1.0.dev20240817
#Description: Required by mypy and test_public_bindings.py when checking torch.onnx._internal
#Pinned versions:
#test that import:
parameterized==0.8.1
#Description: Parameterizes unittests, both the tests themselves and the entire testing class
#Pinned versions:
#test that import:

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@ -1,49 +0,0 @@
sphinx==5.3.0
#Description: This is used to generate PyTorch docs
#Pinned versions: 5.3.0
-e git+https://github.com/pytorch/pytorch_sphinx_theme.git#egg=pytorch_sphinx_theme
# TODO: sphinxcontrib.katex 0.9.0 adds a local KaTeX server to speed up pre-rendering
# but it doesn't seem to work and hangs around idly. The initial thought is probably
# something related to Docker setup. We can investigate this later
sphinxcontrib.katex==0.8.6
#Description: This is used to generate PyTorch docs
#Pinned versions: 0.8.6
matplotlib==3.5.3
#Description: This is used to generate PyTorch docs
#Pinned versions: 3.5.3
tensorboard==2.13.0
#Description: This is used to generate PyTorch docs
#Pinned versions: 2.13.0
breathe==4.34.0
#Description: This is used to generate PyTorch C++ docs
#Pinned versions: 4.34.0
exhale==0.2.3
#Description: This is used to generate PyTorch C++ docs
#Pinned versions: 0.2.3
docutils==0.16
#Description: This is used to generate PyTorch C++ docs
#Pinned versions: 0.16
bs4==0.0.1
#Description: This is used to generate PyTorch C++ docs
#Pinned versions: 0.0.1
IPython==8.12.0
#Description: This is used to generate PyTorch functorch docs
#Pinned versions: 8.12.0
myst-nb==0.17.2
#Description: This is used to generate PyTorch functorch docs
#Pinned versions: 0.13.2
# The following are required to build torch.distributed.elastic.rendezvous.etcd* docs
python-etcd==0.4.5
sphinx-copybutton==0.5.0
sphinx-panels==0.4.1
myst-parser==0.18.1

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@ -1 +0,0 @@
3.1.0

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@ -1,172 +0,0 @@
ARG UBUNTU_VERSION
ARG CUDA_VERSION
ARG IMAGE_NAME
FROM ${IMAGE_NAME}
ARG UBUNTU_VERSION
ARG CUDA_VERSION
ENV DEBIAN_FRONTEND noninteractive
# Install common dependencies (so that this step can be cached separately)
COPY ./common/install_base.sh install_base.sh
RUN bash ./install_base.sh && rm install_base.sh
# Install user
COPY ./common/install_user.sh install_user.sh
RUN bash ./install_user.sh && rm install_user.sh
# Install katex
ARG KATEX
COPY ./common/install_docs_reqs.sh install_docs_reqs.sh
RUN bash ./install_docs_reqs.sh && rm install_docs_reqs.sh
# Install conda and other packages (e.g., numpy, pytest)
ARG ANACONDA_PYTHON_VERSION
ENV ANACONDA_PYTHON_VERSION=$ANACONDA_PYTHON_VERSION
ENV PATH /opt/conda/envs/py_$ANACONDA_PYTHON_VERSION/bin:/opt/conda/bin:$PATH
ARG CONDA_CMAKE
COPY requirements-ci.txt /opt/conda/requirements-ci.txt
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
# Install gcc
ARG GCC_VERSION
COPY ./common/install_gcc.sh install_gcc.sh
RUN bash ./install_gcc.sh && rm install_gcc.sh
# Install clang
ARG CLANG_VERSION
COPY ./common/install_clang.sh install_clang.sh
RUN bash ./install_clang.sh && rm install_clang.sh
# (optional) Install protobuf for ONNX
ARG PROTOBUF
COPY ./common/install_protobuf.sh install_protobuf.sh
RUN if [ -n "${PROTOBUF}" ]; then bash ./install_protobuf.sh; fi
RUN rm install_protobuf.sh
ENV INSTALLED_PROTOBUF ${PROTOBUF}
# (optional) Install database packages like LMDB and LevelDB
ARG DB
COPY ./common/install_db.sh install_db.sh
RUN if [ -n "${DB}" ]; then bash ./install_db.sh; fi
RUN rm install_db.sh
ENV INSTALLED_DB ${DB}
# (optional) Install vision packages like OpenCV
ARG VISION
COPY ./common/install_vision.sh ./common/cache_vision_models.sh ./common/common_utils.sh ./
RUN if [ -n "${VISION}" ]; then bash ./install_vision.sh; fi
RUN rm install_vision.sh cache_vision_models.sh common_utils.sh
ENV INSTALLED_VISION ${VISION}
# (optional) Install UCC
ARG UCX_COMMIT
ARG UCC_COMMIT
ENV UCX_COMMIT $UCX_COMMIT
ENV UCC_COMMIT $UCC_COMMIT
ENV UCX_HOME /usr
ENV UCC_HOME /usr
ADD ./common/install_ucc.sh install_ucc.sh
RUN if [ -n "${UCX_COMMIT}" ] && [ -n "${UCC_COMMIT}" ]; then bash ./install_ucc.sh; fi
RUN rm install_ucc.sh
COPY ./common/install_openssl.sh install_openssl.sh
ENV OPENSSL_ROOT_DIR /opt/openssl
RUN bash ./install_openssl.sh
ENV OPENSSL_DIR /opt/openssl
ARG INDUCTOR_BENCHMARKS
COPY ./common/install_inductor_benchmark_deps.sh install_inductor_benchmark_deps.sh
COPY ./common/common_utils.sh common_utils.sh
COPY ci_commit_pins/huggingface.txt huggingface.txt
COPY ci_commit_pins/timm.txt timm.txt
RUN if [ -n "${INDUCTOR_BENCHMARKS}" ]; then bash ./install_inductor_benchmark_deps.sh; fi
RUN rm install_inductor_benchmark_deps.sh common_utils.sh timm.txt huggingface.txt
# (optional) Install non-default CMake version
ARG CMAKE_VERSION
COPY ./common/install_cmake.sh install_cmake.sh
RUN if [ -n "${CMAKE_VERSION}" ]; then bash ./install_cmake.sh; fi
RUN rm install_cmake.sh
ARG TRITON
# Install triton, this needs to be done before sccache because the latter will
# try to reach out to S3, which docker build runners don't have access
COPY ./common/install_triton.sh install_triton.sh
COPY ./common/common_utils.sh common_utils.sh
COPY ci_commit_pins/triton.txt triton.txt
COPY triton_version.txt triton_version.txt
RUN if [ -n "${TRITON}" ]; then bash ./install_triton.sh; fi
RUN rm install_triton.sh common_utils.sh triton.txt triton_version.txt
ARG HALIDE
# Build and install halide
COPY ./common/install_halide.sh install_halide.sh
COPY ./common/common_utils.sh common_utils.sh
COPY ci_commit_pins/halide.txt halide.txt
RUN if [ -n "${HALIDE}" ]; then bash ./install_halide.sh; fi
RUN rm install_halide.sh common_utils.sh halide.txt
# Install ccache/sccache (do this last, so we get priority in PATH)
COPY ./common/install_cache.sh install_cache.sh
ENV PATH /opt/cache/bin:$PATH
# See https://github.com/pytorch/pytorch/issues/82174
# TODO(sdym@fb.com):
# check if this is needed after full off Xenial migration
ENV CARGO_NET_GIT_FETCH_WITH_CLI true
RUN bash ./install_cache.sh && rm install_cache.sh
ENV CMAKE_CUDA_COMPILER_LAUNCHER=/opt/cache/bin/sccache
# Add jni.h for java host build
COPY ./common/install_jni.sh install_jni.sh
COPY ./java/jni.h jni.h
RUN bash ./install_jni.sh && rm install_jni.sh
# Install Open MPI for CUDA
COPY ./common/install_openmpi.sh install_openmpi.sh
RUN if [ -n "${CUDA_VERSION}" ]; then bash install_openmpi.sh; fi
RUN rm install_openmpi.sh
# Include BUILD_ENVIRONMENT environment variable in image
ARG BUILD_ENVIRONMENT
ENV BUILD_ENVIRONMENT ${BUILD_ENVIRONMENT}
# AWS specific CUDA build guidance
ENV TORCH_CUDA_ARCH_LIST Maxwell
ENV TORCH_NVCC_FLAGS "-Xfatbin -compress-all"
ENV CUDA_PATH /usr/local/cuda
# Install LLVM dev version (Defined in the pytorch/builder github repository)
COPY --from=pytorch/llvm:9.0.1 /opt/llvm /opt/llvm
# Install CUDNN
ARG CUDNN_VERSION
ARG CUDA_VERSION
COPY ./common/install_cudnn.sh install_cudnn.sh
RUN if [ -n "${CUDNN_VERSION}" ]; 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
# Install CUDSS
ARG CUDA_VERSION
COPY ./common/install_cudss.sh install_cudss.sh
RUN bash install_cudss.sh
RUN rm install_cudss.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
RUN if [ -h /usr/local/cuda-12.1/cuda-12.1 ]; then rm /usr/local/cuda-12.1/cuda-12.1; fi
RUN if [ -h /usr/local/cuda-12.4/cuda-12.4 ]; then rm /usr/local/cuda-12.4/cuda-12.4; fi
USER jenkins
CMD ["bash"]

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@ -1,130 +0,0 @@
ARG UBUNTU_VERSION
FROM ubuntu:${UBUNTU_VERSION}
ARG UBUNTU_VERSION
ENV DEBIAN_FRONTEND noninteractive
# Set AMD gpu targets to build for
ARG PYTORCH_ROCM_ARCH
ENV PYTORCH_ROCM_ARCH ${PYTORCH_ROCM_ARCH}
# Install common dependencies (so that this step can be cached separately)
COPY ./common/install_base.sh install_base.sh
RUN bash ./install_base.sh && rm install_base.sh
# Install clang
ARG LLVMDEV
ARG CLANG_VERSION
COPY ./common/install_clang.sh install_clang.sh
RUN bash ./install_clang.sh && rm install_clang.sh
# Install user
COPY ./common/install_user.sh install_user.sh
RUN bash ./install_user.sh && rm install_user.sh
# Install conda and other packages (e.g., numpy, pytest)
ARG ANACONDA_PYTHON_VERSION
ARG CONDA_CMAKE
ENV ANACONDA_PYTHON_VERSION=$ANACONDA_PYTHON_VERSION
ENV PATH /opt/conda/envs/py_$ANACONDA_PYTHON_VERSION/bin:/opt/conda/bin:$PATH
COPY requirements-ci.txt /opt/conda/requirements-ci.txt
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
# Install gcc
ARG GCC_VERSION
COPY ./common/install_gcc.sh install_gcc.sh
RUN bash ./install_gcc.sh && rm install_gcc.sh
# (optional) Install protobuf for ONNX
ARG PROTOBUF
COPY ./common/install_protobuf.sh install_protobuf.sh
RUN if [ -n "${PROTOBUF}" ]; then bash ./install_protobuf.sh; fi
RUN rm install_protobuf.sh
ENV INSTALLED_PROTOBUF ${PROTOBUF}
# (optional) Install database packages like LMDB and LevelDB
ARG DB
COPY ./common/install_db.sh install_db.sh
RUN if [ -n "${DB}" ]; then bash ./install_db.sh; fi
RUN rm install_db.sh
ENV INSTALLED_DB ${DB}
# (optional) Install vision packages like OpenCV
ARG VISION
COPY ./common/install_vision.sh ./common/cache_vision_models.sh ./common/common_utils.sh ./
RUN if [ -n "${VISION}" ]; then bash ./install_vision.sh; fi
RUN rm install_vision.sh cache_vision_models.sh common_utils.sh
ENV INSTALLED_VISION ${VISION}
# Install rocm
ARG ROCM_VERSION
COPY ./common/install_rocm.sh install_rocm.sh
RUN bash ./install_rocm.sh
RUN rm install_rocm.sh
COPY ./common/install_rocm_magma.sh install_rocm_magma.sh
RUN bash ./install_rocm_magma.sh
RUN rm install_rocm_magma.sh
ADD ./common/install_miopen.sh install_miopen.sh
RUN bash ./install_miopen.sh ${ROCM_VERSION} && rm install_miopen.sh
ENV ROCM_PATH /opt/rocm
ENV PATH /opt/rocm/bin:$PATH
ENV PATH /opt/rocm/hcc/bin:$PATH
ENV PATH /opt/rocm/hip/bin:$PATH
ENV PATH /opt/rocm/opencl/bin:$PATH
ENV PATH /opt/rocm/llvm/bin:$PATH
ENV MAGMA_HOME /opt/rocm/magma
ENV LANG C.UTF-8
ENV LC_ALL C.UTF-8
# Install amdsmi
COPY ./common/install_amdsmi.sh install_amdsmi.sh
RUN bash ./install_amdsmi.sh
RUN rm install_amdsmi.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
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
COPY ci_commit_pins/triton.txt triton.txt
COPY triton_version.txt triton_version.txt
RUN if [ -n "${TRITON}" ]; then bash ./install_triton.sh; fi
RUN rm install_triton.sh common_utils.sh triton.txt triton_version.txt
# Install AOTriton
COPY ./aotriton_version.txt aotriton_version.txt
COPY ./common/common_utils.sh common_utils.sh
COPY ./common/install_aotriton.sh install_aotriton.sh
RUN ["/bin/bash", "-c", "./install_aotriton.sh /opt/rocm && rm -rf install_aotriton.sh aotriton_version.txt common_utils.sh"]
ENV AOTRITON_INSTALLED_PREFIX /opt/rocm/aotriton
# Install ccache/sccache (do this last, so we get priority in PATH)
COPY ./common/install_cache.sh install_cache.sh
ENV PATH /opt/cache/bin:$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"]

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@ -1,119 +0,0 @@
ARG UBUNTU_VERSION
FROM ubuntu:${UBUNTU_VERSION}
ARG UBUNTU_VERSION
ENV DEBIAN_FRONTEND noninteractive
ARG CLANG_VERSION
# Install common dependencies (so that this step can be cached separately)
COPY ./common/install_base.sh install_base.sh
RUN bash ./install_base.sh && rm install_base.sh
# Install clang
ARG LLVMDEV
COPY ./common/install_clang.sh install_clang.sh
RUN bash ./install_clang.sh && rm install_clang.sh
# Install user
COPY ./common/install_user.sh install_user.sh
RUN bash ./install_user.sh && rm install_user.sh
# Install katex
ARG KATEX
COPY ./common/install_docs_reqs.sh install_docs_reqs.sh
RUN bash ./install_docs_reqs.sh && rm install_docs_reqs.sh
# Install conda and other packages (e.g., numpy, pytest)
ARG ANACONDA_PYTHON_VERSION
ARG CONDA_CMAKE
ARG DOCS
ARG BUILD_ENVIRONMENT
ENV ANACONDA_PYTHON_VERSION=$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
# Install XPU Dependencies
ARG XPU_VERSION
COPY ./common/install_xpu.sh install_xpu.sh
RUN bash ./install_xpu.sh && rm install_xpu.sh
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
COPY ci_commit_pins/triton-xpu.txt triton-xpu.txt
COPY triton_version.txt triton_version.txt
RUN if [ -n "${TRITON}" ]; then bash ./install_triton.sh; fi
RUN rm install_triton.sh common_utils.sh triton-xpu.txt triton_version.txt
# (optional) Install database packages like LMDB and LevelDB
ARG DB
COPY ./common/install_db.sh install_db.sh
RUN if [ -n "${DB}" ]; then bash ./install_db.sh; fi
RUN rm install_db.sh
ENV INSTALLED_DB ${DB}
# (optional) Install vision packages like OpenCV
ARG VISION
COPY ./common/install_vision.sh ./common/cache_vision_models.sh ./common/common_utils.sh ./
RUN if [ -n "${VISION}" ]; then bash ./install_vision.sh; fi
RUN rm install_vision.sh cache_vision_models.sh common_utils.sh
ENV INSTALLED_VISION ${VISION}
# (optional) Install non-default CMake version
ARG CMAKE_VERSION
COPY ./common/install_cmake.sh install_cmake.sh
RUN if [ -n "${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"]

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@ -1,211 +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=$DOCS
COPY requirements-ci.txt requirements-docs.txt /opt/conda/
COPY ./common/install_conda.sh install_conda.sh
COPY ./common/common_utils.sh common_utils.sh
RUN bash ./install_conda.sh && rm install_conda.sh common_utils.sh /opt/conda/requirements-ci.txt /opt/conda/requirements-docs.txt
RUN if [ -n "${UNINSTALL_DILL}" ]; then pip uninstall -y dill; fi
# 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
# Install cuda and cudnn
ARG CUDA_VERSION
COPY ./common/install_cuda.sh install_cuda.sh
RUN bash ./install_cuda.sh ${CUDA_VERSION} && rm install_cuda.sh
ENV DESIRED_CUDA ${CUDA_VERSION}
ENV PATH /usr/local/nvidia/bin:/usr/local/cuda/bin:$PATH
# (optional) Install UCC
ARG UCX_COMMIT
ARG UCC_COMMIT
ENV UCX_COMMIT $UCX_COMMIT
ENV UCC_COMMIT $UCC_COMMIT
ENV UCX_HOME /usr
ENV UCC_HOME /usr
ADD ./common/install_ucc.sh install_ucc.sh
RUN if [ -n "${UCX_COMMIT}" ] && [ -n "${UCC_COMMIT}" ]; then bash ./install_ucc.sh; fi
RUN rm install_ucc.sh
# (optional) Install protobuf for ONNX
ARG PROTOBUF
COPY ./common/install_protobuf.sh install_protobuf.sh
RUN if [ -n "${PROTOBUF}" ]; then bash ./install_protobuf.sh; fi
RUN rm install_protobuf.sh
ENV INSTALLED_PROTOBUF ${PROTOBUF}
# (optional) Install database packages like LMDB and LevelDB
ARG DB
COPY ./common/install_db.sh install_db.sh
RUN if [ -n "${DB}" ]; then bash ./install_db.sh; fi
RUN rm install_db.sh
ENV INSTALLED_DB ${DB}
# (optional) Install vision packages like OpenCV
ARG VISION
COPY ./common/install_vision.sh ./common/cache_vision_models.sh ./common/common_utils.sh ./
RUN if [ -n "${VISION}" ]; then bash ./install_vision.sh; fi
RUN rm install_vision.sh cache_vision_models.sh common_utils.sh
ENV INSTALLED_VISION ${VISION}
# (optional) Install Android NDK
ARG ANDROID
ARG ANDROID_NDK
ARG GRADLE_VERSION
COPY ./common/install_android.sh ./common/cache_vision_models.sh ./common/common_utils.sh ./
COPY ./android/AndroidManifest.xml AndroidManifest.xml
COPY ./android/build.gradle build.gradle
RUN if [ -n "${ANDROID}" ]; then bash ./install_android.sh; fi
RUN rm install_android.sh cache_vision_models.sh common_utils.sh
RUN rm AndroidManifest.xml
RUN rm build.gradle
ENV INSTALLED_ANDROID ${ANDROID}
# (optional) Install Vulkan SDK
ARG VULKAN_SDK_VERSION
COPY ./common/install_vulkan_sdk.sh install_vulkan_sdk.sh
RUN if [ -n "${VULKAN_SDK_VERSION}" ]; then bash ./install_vulkan_sdk.sh; fi
RUN rm install_vulkan_sdk.sh
# (optional) Install swiftshader
ARG SWIFTSHADER
COPY ./common/install_swiftshader.sh install_swiftshader.sh
RUN if [ -n "${SWIFTSHADER}" ]; then bash ./install_swiftshader.sh; fi
RUN rm install_swiftshader.sh
# (optional) Install non-default CMake version
ARG CMAKE_VERSION
COPY ./common/install_cmake.sh install_cmake.sh
RUN if [ -n "${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 "${NINJA_VERSION}" ]; then bash ./install_ninja.sh; fi
RUN rm install_ninja.sh
COPY ./common/install_openssl.sh install_openssl.sh
RUN bash ./install_openssl.sh
ENV OPENSSL_ROOT_DIR /opt/openssl
ENV OPENSSL_DIR /opt/openssl
RUN rm install_openssl.sh
ARG INDUCTOR_BENCHMARKS
COPY ./common/install_inductor_benchmark_deps.sh install_inductor_benchmark_deps.sh
COPY ./common/common_utils.sh common_utils.sh
COPY ci_commit_pins/huggingface.txt huggingface.txt
COPY ci_commit_pins/timm.txt timm.txt
RUN if [ -n "${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
COPY ci_commit_pins/triton.txt triton.txt
RUN if [ -n "${TRITON}" ]; then bash ./install_triton.sh; fi
RUN rm install_triton.sh common_utils.sh triton.txt
ARG EXECUTORCH
# Build and install executorch
COPY ./common/install_executorch.sh install_executorch.sh
COPY ./common/common_utils.sh common_utils.sh
COPY ci_commit_pins/executorch.txt executorch.txt
RUN if [ -n "${EXECUTORCH}" ]; then bash ./install_executorch.sh; fi
RUN rm install_executorch.sh common_utils.sh executorch.txt
ARG HALIDE
# Build and install halide
COPY ./common/install_halide.sh install_halide.sh
COPY ./common/common_utils.sh common_utils.sh
COPY ci_commit_pins/halide.txt halide.txt
RUN if [ -n "${HALIDE}" ]; then bash ./install_halide.sh; fi
RUN rm install_halide.sh common_utils.sh halide.txt
ARG ONNX
# Install ONNX dependencies
COPY ./common/install_onnx.sh ./common/common_utils.sh ./
RUN if [ -n "${ONNX}" ]; then bash ./install_onnx.sh; fi
RUN rm install_onnx.sh common_utils.sh
# (optional) Build ACL
ARG ACL
COPY ./common/install_acl.sh install_acl.sh
RUN if [ -n "${ACL}" ]; then bash ./install_acl.sh; fi
RUN rm install_acl.sh
ENV INSTALLED_ACL ${ACL}
# Install ccache/sccache (do this last, so we get priority in PATH)
ARG SKIP_SCCACHE_INSTALL
COPY ./common/install_cache.sh install_cache.sh
ENV PATH /opt/cache/bin:$PATH
RUN if [ -z "${SKIP_SCCACHE_INSTALL}" ]; then bash ./install_cache.sh; fi
RUN rm install_cache.sh
# Add jni.h for java host build
COPY ./common/install_jni.sh install_jni.sh
COPY ./java/jni.h jni.h
RUN bash ./install_jni.sh && rm install_jni.sh
# Install Open MPI for CUDA
COPY ./common/install_openmpi.sh install_openmpi.sh
RUN if [ -n "${CUDA_VERSION}" ]; then bash install_openmpi.sh; fi
RUN rm install_openmpi.sh
# Include BUILD_ENVIRONMENT environment variable in image
ARG BUILD_ENVIRONMENT
ENV BUILD_ENVIRONMENT ${BUILD_ENVIRONMENT}
# Install LLVM dev version (Defined in the pytorch/builder github repository)
ARG SKIP_LLVM_SRC_BUILD_INSTALL
COPY --from=pytorch/llvm:9.0.1 /opt/llvm /opt/llvm
RUN if [ -n "${SKIP_LLVM_SRC_BUILD_INSTALL}" ]; then set -eu; rm -rf /opt/llvm; fi
# AWS specific CUDA build guidance
ENV TORCH_CUDA_ARCH_LIST Maxwell
ENV TORCH_NVCC_FLAGS "-Xfatbin -compress-all"
ENV CUDA_PATH /usr/local/cuda
USER jenkins
CMD ["bash"]

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@ -1,14 +0,0 @@
# Jenkins
The scripts in this directory are the entrypoint for testing ONNX exporter.
The environment variable `BUILD_ENVIRONMENT` is expected to be set to
the build environment you intend to test. It is a hint for the build
and test scripts to configure Caffe2 a certain way and include/exclude
tests. Docker images, they equal the name of the image itself. For
example: `py2-cuda9.0-cudnn7-ubuntu16.04`. The Docker images that are
built on Jenkins and are used in triggered builds already have this
environment variable set in their manifest. Also see
`./docker/jenkins/*/Dockerfile` and search for `BUILD_ENVIRONMENT`.
Our Jenkins installation is located at https://ci.pytorch.org/jenkins/.

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@ -1,23 +0,0 @@
#!/bin/bash
set -ex
source "$(dirname "${BASH_SOURCE[0]}")/../pytorch/common_utils.sh"
LOCAL_DIR=$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)
ROOT_DIR=$(cd "$LOCAL_DIR"/../.. && pwd)
TEST_DIR="$ROOT_DIR/test"
pytest_reports_dir="${TEST_DIR}/test-reports/python"
# Figure out which Python to use
PYTHON="$(which python)"
if [[ "${BUILD_ENVIRONMENT}" =~ py((2|3)\.?[0-9]?\.?[0-9]?) ]]; then
PYTHON=$(which "python${BASH_REMATCH[1]}")
fi
if [[ "${BUILD_ENVIRONMENT}" == *rocm* ]]; then
# HIP_PLATFORM is auto-detected by hipcc; unset to avoid build errors
unset HIP_PLATFORM
fi
mkdir -p "$pytest_reports_dir" || true

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