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Author SHA1 Message Date
8ac9b20d4b Run docker release build on final tag (#117131) (#117182)
To be successful, the docker release workflow needs to run on final tag, after the Release to conda and pypi are complete.

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

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

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

This is very important for lots of distributed launchers

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

(cherry picked from commit 94d28161faccd6e2a2e99bdb22cfadef8a24077e)

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

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

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

The follow test would fail without this bug fix:

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

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

        print(y)
        print(y2)

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

test_erfinv()
```

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

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

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

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

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

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

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

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

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

Test Plan: CI

Differential Revision: D52339142

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

(cherry picked from commit a357a0f31519f96cff9839c1672a112539ba98ff)

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

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

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

Found using the repros mentioned in this issue: #112577

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

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

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

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

**Changes:**

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

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

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

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

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

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

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

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

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

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

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

>>> r
-6
```

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

(cherry picked from commit 66a76516bfc341b2b55bb2056d2faa9c2de46d69)

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

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

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

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

Test Plan: CI.

Differential Revision: D51861018

fbshipit-source-id: dc7b26cea7340d55498730123e82a42cef46ff55

* fix doc

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

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

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

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

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

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

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

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

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

This PR does 2 things.

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

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

Also make the parallelize_module doc example more concrete

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

Only enabled if `THP_MEM_ALLOC_ENABLE` environment variable is set.

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

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

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

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

Test Plan:
- Tests

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

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

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

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

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

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

Test Plan: CI.

Differential Revision: D51861018

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

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

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

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

* lint

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

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

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

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

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

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

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

* Release only part 2

* Pin unstable jobs

* fix

* Fix lint
2023-12-06 18:30:25 -05:00
15806 changed files with 810113 additions and 741389 deletions

View File

@ -1,4 +1,3 @@
# 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

View File

@ -21,3 +21,6 @@
cxx = /usr/bin/clang++
cxxpp = /usr/bin/clang++
ld = /usr/bin/clang++
[project]
default_flavors_mode=all

View File

@ -1,4 +1,4 @@
# Docker images for GitHub CI and CD
# Docker images for GitHub CI
This directory contains everything needed to build the Docker images
that are used in our CI.
@ -12,20 +12,13 @@ each image as the `BUILD_ENVIRONMENT` environment variable.
See `build.sh` for valid build environments (it's the giant switch).
## Docker CI builds
## Contents
* `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

View File

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

View File

@ -71,8 +71,6 @@ if [[ "$image" == *cuda* && "$UBUNTU_VERSION" != "22.04" ]]; then
DOCKERFILE="${OS}-cuda/Dockerfile"
elif [[ "$image" == *rocm* ]]; then
DOCKERFILE="${OS}-rocm/Dockerfile"
elif [[ "$image" == *xpu* ]]; then
DOCKERFILE="${OS}-xpu/Dockerfile"
elif [[ "$image" == *cuda*linter* ]]; then
# Use a separate Dockerfile for linter to keep a small image size
DOCKERFILE="linter-cuda/Dockerfile"
@ -84,30 +82,16 @@ fi
# CMake 3.18 is needed to support CUDA17 language variant
CMAKE_VERSION=3.18.5
_UCX_COMMIT=7bb2722ff2187a0cad557ae4a6afa090569f83fb
_UCC_COMMIT=20eae37090a4ce1b32bcce6144ccad0b49943e0b
_UCX_COMMIT=00bcc6bb18fc282eb160623b4c0d300147f579af
_UCC_COMMIT=7cb07a76ccedad7e56ceb136b865eb9319c258ea
# 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=${_UCC_COMMIT}
CONDA_CMAKE=yes
TRITON=yes
;;
pytorch-linux-focal-cuda12.1-cudnn9-py3-gcc9)
pytorch-linux-focal-cuda12.1-cudnn8-py3-gcc9)
CUDA_VERSION=12.1.1
CUDNN_VERSION=9
CUDNN_VERSION=8
ANACONDA_PYTHON_VERSION=3.10
GCC_VERSION=9
PROTOBUF=yes
@ -119,24 +103,9 @@ case "$image" in
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)
pytorch-linux-focal-cuda12.1-cudnn8-py3-gcc9-inductor-benchmarks)
CUDA_VERSION=12.1.1
CUDNN_VERSION=9
CUDNN_VERSION=8
ANACONDA_PYTHON_VERSION=3.10
GCC_VERSION=9
PROTOBUF=yes
@ -149,39 +118,9 @@ case "$image" in
TRITON=yes
INDUCTOR_BENCHMARKS=yes
;;
pytorch-linux-focal-cuda12.1-cudnn9-py3.12-gcc9-inductor-benchmarks)
CUDA_VERSION=12.1.1
CUDNN_VERSION=9
ANACONDA_PYTHON_VERSION=3.12
GCC_VERSION=9
PROTOBUF=yes
DB=yes
VISION=yes
KATEX=yes
UCX_COMMIT=${_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=${_UCC_COMMIT}
CONDA_CMAKE=yes
TRITON=yes
INDUCTOR_BENCHMARKS=yes
;;
pytorch-linux-focal-cuda11.8-cudnn9-py3-gcc9)
pytorch-linux-focal-cuda11.8-cudnn8-py3-gcc9)
CUDA_VERSION=11.8.0
CUDNN_VERSION=9
CUDNN_VERSION=8
ANACONDA_PYTHON_VERSION=3.10
GCC_VERSION=9
PROTOBUF=yes
@ -193,37 +132,9 @@ case "$image" in
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)
pytorch-linux-focal-cuda12.1-cudnn8-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
CUDNN_VERSION=8
ANACONDA_PYTHON_VERSION=3.10
GCC_VERSION=9
PROTOBUF=yes
@ -236,7 +147,7 @@ case "$image" in
TRITON=yes
;;
pytorch-linux-focal-py3-clang10-onnx)
ANACONDA_PYTHON_VERSION=3.9
ANACONDA_PYTHON_VERSION=3.8
CLANG_VERSION=10
PROTOBUF=yes
DB=yes
@ -245,7 +156,7 @@ case "$image" in
ONNX=yes
;;
pytorch-linux-focal-py3-clang9-android-ndk-r21e)
ANACONDA_PYTHON_VERSION=3.9
ANACONDA_PYTHON_VERSION=3.8
CLANG_VERSION=9
LLVMDEV=yes
PROTOBUF=yes
@ -254,8 +165,8 @@ case "$image" in
GRADLE_VERSION=6.8.3
NINJA_VERSION=1.9.0
;;
pytorch-linux-focal-py3.9-clang10)
ANACONDA_PYTHON_VERSION=3.9
pytorch-linux-focal-py3.8-clang10)
ANACONDA_PYTHON_VERSION=3.8
CLANG_VERSION=10
PROTOBUF=yes
DB=yes
@ -276,8 +187,8 @@ case "$image" in
CONDA_CMAKE=yes
TRITON=yes
;;
pytorch-linux-focal-py3.9-gcc9)
ANACONDA_PYTHON_VERSION=3.9
pytorch-linux-focal-py3.8-gcc9)
ANACONDA_PYTHON_VERSION=3.8
GCC_VERSION=9
PROTOBUF=yes
DB=yes
@ -286,40 +197,29 @@ case "$image" in
TRITON=yes
;;
pytorch-linux-focal-rocm-n-1-py3)
ANACONDA_PYTHON_VERSION=3.10
ANACONDA_PYTHON_VERSION=3.8
GCC_VERSION=9
PROTOBUF=yes
DB=yes
VISION=yes
ROCM_VERSION=6.1
ROCM_VERSION=5.6
NINJA_VERSION=1.9.0
CONDA_CMAKE=yes
TRITON=yes
;;
pytorch-linux-focal-rocm-n-py3)
ANACONDA_PYTHON_VERSION=3.10
ANACONDA_PYTHON_VERSION=3.8
GCC_VERSION=9
PROTOBUF=yes
DB=yes
VISION=yes
ROCM_VERSION=6.2
ROCM_VERSION=5.7
NINJA_VERSION=1.9.0
CONDA_CMAKE=yes
TRITON=yes
;;
pytorch-linux-jammy-xpu-2024.0-py3)
ANACONDA_PYTHON_VERSION=3.9
GCC_VERSION=11
PROTOBUF=yes
DB=yes
VISION=yes
XPU_VERSION=0.5
NINJA_VERSION=1.9.0
CONDA_CMAKE=yes
TRITON=yes
;;
pytorch-linux-jammy-py3.9-gcc11-inductor-benchmarks)
ANACONDA_PYTHON_VERSION=3.9
pytorch-linux-jammy-py3.8-gcc11-inductor-benchmarks)
ANACONDA_PYTHON_VERSION=3.8
GCC_VERSION=11
PROTOBUF=yes
DB=yes
@ -330,10 +230,10 @@ case "$image" in
DOCS=yes
INDUCTOR_BENCHMARKS=yes
;;
pytorch-linux-jammy-cuda11.8-cudnn9-py3.9-clang12)
ANACONDA_PYTHON_VERSION=3.9
pytorch-linux-jammy-cuda11.8-cudnn8-py3.8-clang12)
ANACONDA_PYTHON_VERSION=3.8
CUDA_VERSION=11.8
CUDNN_VERSION=9
CUDNN_VERSION=8
CLANG_VERSION=12
PROTOBUF=yes
DB=yes
@ -355,14 +255,8 @@ case "$image" in
CONDA_CMAKE=yes
VISION=yes
;;
pytorch-linux-jammy-py3-clang18-asan)
ANACONDA_PYTHON_VERSION=3.10
CLANG_VERSION=18
CONDA_CMAKE=yes
VISION=yes
;;
pytorch-linux-jammy-py3.9-gcc11)
ANACONDA_PYTHON_VERSION=3.9
pytorch-linux-jammy-py3.8-gcc11)
ANACONDA_PYTHON_VERSION=3.8
GCC_VERSION=11
PROTOBUF=yes
DB=yes
@ -371,7 +265,6 @@ case "$image" in
CONDA_CMAKE=yes
TRITON=yes
DOCS=yes
UNINSTALL_DILL=yes
;;
pytorch-linux-jammy-py3-clang12-executorch)
ANACONDA_PYTHON_VERSION=3.10
@ -379,21 +272,6 @@ case "$image" in
CONDA_CMAKE=yes
EXECUTORCH=yes
;;
pytorch-linux-jammy-py3.12-halide)
CUDA_VERSION=12.4
ANACONDA_PYTHON_VERSION=3.12
GCC_VERSION=11
CONDA_CMAKE=yes
HALIDE=yes
TRITON=yes
;;
pytorch-linux-jammy-py3.12-triton-cpu)
CUDA_VERSION=12.4
ANACONDA_PYTHON_VERSION=3.12
GCC_VERSION=11
CONDA_CMAKE=yes
TRITON_CPU=yes
;;
pytorch-linux-focal-linter)
# TODO: Use 3.9 here because of this issue https://github.com/python/mypy/issues/13627.
# We will need to update mypy version eventually, but that's for another day. The task
@ -401,42 +279,11 @@ case "$image" in
ANACONDA_PYTHON_VERSION=3.9
CONDA_CMAKE=yes
;;
pytorch-linux-jammy-cuda11.8-cudnn9-py3.9-linter)
pytorch-linux-jammy-cuda11.8-cudnn8-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
@ -484,7 +331,7 @@ 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
if [[ ${CUDNN_VERSION} == 8 ]]; then
IMAGE_NAME="nvidia/cuda:${CUDA_VERSION}-devel-ubuntu${UBUNTU_VERSION}"
fi
fi
@ -523,22 +370,16 @@ docker build \
--build-arg "UCC_COMMIT=${UCC_COMMIT}" \
--build-arg "CONDA_CMAKE=${CONDA_CMAKE}" \
--build-arg "TRITON=${TRITON}" \
--build-arg "TRITON_CPU=${TRITON_CPU}" \
--build-arg "ONNX=${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" \
"$@" \
.
# NVIDIA dockers for RC releases use tag names like `11.0-cudnn9-devel-ubuntu18.04-rc`,
# NVIDIA dockers for RC releases use tag names like `11.0-cudnn8-devel-ubuntu18.04-rc`,
# for this case we will set UBUNTU_VERSION to `18.04-rc` so that the Dockerfile could
# find the correct image. As a result, here we have to replace the
# "$UBUNTU_VERSION" == "18.04-rc"

View File

@ -62,7 +62,7 @@ RUN if [ -n "${DB}" ]; then bash ./install_db.sh; fi
RUN rm install_db.sh
ENV INSTALLED_DB ${DB}
# (optional) Install vision packages like OpenCV
# (optional) Install vision packages like OpenCV and ffmpeg
ARG VISION
COPY ./common/install_vision.sh ./common/cache_vision_models.sh ./common/common_utils.sh ./
RUN if [ -n "${VISION}" ]; then bash ./install_vision.sh; fi
@ -77,9 +77,6 @@ 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:$PATH
@ -108,17 +105,10 @@ ENV CMAKE_C_COMPILER cc
ENV CMAKE_CXX_COMPILER c++
COPY ./common/install_triton.sh install_triton.sh
COPY ./common/common_utils.sh common_utils.sh
COPY ci_commit_pins/triton.txt triton.txt
COPY ci_commit_pins/triton-rocm.txt triton-rocm.txt
COPY triton_version.txt triton_version.txt
RUN if [ -n "${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
RUN rm install_triton.sh common_utils.sh triton-rocm.txt triton_version.txt
# Install ccache/sccache (do this last, so we get priority in PATH)
COPY ./common/install_cache.sh install_cache.sh

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@ -1 +1 @@
cd1c833b079adb324871dcbbe75b43d42ffc0ade
b2f5dfe80704404298467347b8ee3ac229efed47

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@ -1 +0,0 @@
461c12871f336fe6f57b55d6a297f13ef209161b

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@ -1 +1 @@
243e186efbf7fb93328dd6b34927a4e8c8f24395
6c26faa159b79a42d7fa46cb66e2d21523351987

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@ -1 +1 @@
ac3470188b914c5d7a5058a7e28b9eb685a62427
730b907b4d45a4713cbc425cbf224c46089fd514

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@ -1 +0,0 @@
c7711371cace304afe265c1ffa906415ab82fc66

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@ -0,0 +1 @@
dafe1459823b9549417ed95e9720f1b594fab329

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@ -1 +0,0 @@
91b14bf5593cf58a8541f3e6b9125600a867d4ef

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@ -1 +1 @@
cf34004b8a67d290a962da166f5aa2fc66751326
bcad9dabe15021c53b6a88296e9d7a210044f108

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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}"

View File

@ -3,7 +3,7 @@
set -ex
install_ubuntu() {
# NVIDIA dockers for RC releases use tag names like `11.0-cudnn9-devel-ubuntu18.04-rc`,
# NVIDIA dockers for RC releases use tag names like `11.0-cudnn8-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
# "$UBUNTU_VERSION" == "18.04"*
@ -75,7 +75,6 @@ install_ubuntu() {
libtool \
vim \
unzip \
gpg-agent \
gdb
# Should resolve issues related to various apt package repository cert issues
@ -113,6 +112,7 @@ install_centos() {
glibc-devel \
glibc-headers \
glog-devel \
hiredis-devel \
libstdc++-devel \
libsndfile-devel \
make \
@ -152,7 +152,7 @@ wget https://ossci-linux.s3.amazonaws.com/valgrind-${VALGRIND_VERSION}.tar.bz2
tar -xjf valgrind-${VALGRIND_VERSION}.tar.bz2
cd valgrind-${VALGRIND_VERSION}
./configure --prefix=/usr/local
make -j$[$(nproc) - 2]
make -j6
sudo make install
cd ../../
rm -rf valgrind_build

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@ -13,18 +13,11 @@ if [ -n "$CLANG_VERSION" ]; then
elif [[ $UBUNTU_VERSION == 22.04 ]]; then
# work around ubuntu apt-get conflicts
sudo apt-get -y -f install
wget --no-check-certificate -O - https://apt.llvm.org/llvm-snapshot.gpg.key | sudo apt-key add -
if [[ $CLANG_VERSION == 18 ]]; then
apt-add-repository "deb http://apt.llvm.org/jammy/ llvm-toolchain-jammy-18 main"
fi
fi
sudo apt-get update
if [[ $CLANG_VERSION -ge 18 ]]; then
apt-get install -y libomp-${CLANG_VERSION}-dev libclang-rt-${CLANG_VERSION}-dev clang-"$CLANG_VERSION" llvm-"$CLANG_VERSION"
else
apt-get install -y --no-install-recommends clang-"$CLANG_VERSION" llvm-"$CLANG_VERSION"
fi
apt-get install -y --no-install-recommends clang-"$CLANG_VERSION"
apt-get install -y --no-install-recommends llvm-"$CLANG_VERSION"
# Install dev version of LLVM.
if [ -n "$LLVMDEV" ]; then

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@ -5,17 +5,17 @@ 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);;
2)
CONDA_FILE="Miniconda2-latest-Linux-x86_64.sh"
;;
3)
CONDA_FILE="Miniconda3-latest-Linux-x86_64.sh"
;;
*)
echo "Unsupported ANACONDA_PYTHON_VERSION: $ANACONDA_PYTHON_VERSION"
exit 1
@ -47,27 +47,15 @@ if [ -n "$ANACONDA_PYTHON_VERSION" ]; then
# 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" \
${SYSROOT_DEP}
# libstdcxx from conda default channels are too old, we need GLIBCXX_3.4.30
# which is provided in libstdcxx 12 and up.
conda_install libstdcxx-ng=12.3.0 -c conda-forge
as_jenkins conda create -n py_$ANACONDA_PYTHON_VERSION -y python="$ANACONDA_PYTHON_VERSION"
# Install PyTorch conda deps, as per https://github.com/pytorch/pytorch README
if [[ $(uname -m) == "aarch64" ]]; then
conda_install "openblas==0.3.25=*openmp*"
CONDA_COMMON_DEPS="astunparse pyyaml mkl=2021.4.0 mkl-include=2021.4.0 setuptools"
if [ "$ANACONDA_PYTHON_VERSION" = "3.11" ]; then
conda_install numpy=1.23.5 ${CONDA_COMMON_DEPS}
else
conda_install "mkl=2021.4.0 mkl-include=2021.4.0"
conda_install numpy=1.21.2 ${CONDA_COMMON_DEPS}
fi
# Install llvm-8 as it is required to compile llvmlite-0.30.0 from source
@ -91,6 +79,8 @@ if [ -n "$ANACONDA_PYTHON_VERSION" ]; then
# Install some other packages, including those needed for Python test reporting
pip_install -r /opt/conda/requirements-ci.txt
pip_install -U scikit-learn
if [ -n "$DOCS" ]; then
apt-get update
apt-get -y install expect-dev
@ -99,5 +89,14 @@ if [ -n "$ANACONDA_PYTHON_VERSION" ]; then
pip_install -r /opt/conda/requirements-docs.txt
fi
# HACK HACK HACK
# gcc-9 for ubuntu-18.04 from http://ppa.launchpad.net/ubuntu-toolchain-r/test/ubuntu
# Pulls llibstdc++6 13.1.0-8ubuntu1~18.04 which is too new for conda
# So remove libstdc++6.so.3.29 installed by https://anaconda.org/anaconda/libstdcxx-ng/files?version=11.2.0
# Same is true for gcc-12 from Ubuntu-22.04
if grep -e [12][82].04.[623] /etc/issue >/dev/null; then
rm /opt/conda/envs/py_$ANACONDA_PYTHON_VERSION/lib/libstdc++.so.6
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 ${NCCL_VERSION} and cuSparseLt-0.6.2"
rm -rf /usr/local/cuda-12.4 /usr/local/cuda
# install CUDA 12.4.1 in the same container
wget -q https://developer.download.nvidia.com/compute/cuda/12.4.1/local_installers/cuda_12.4.1_550.54.15_linux.run
chmod +x cuda_12.4.1_550.54.15_linux.run
./cuda_12.4.1_550.54.15_linux.run --toolkit --silent
rm -f cuda_12.4.1_550.54.15_linux.run
rm -f /usr/local/cuda && ln -s /usr/local/cuda-12.4 /usr/local/cuda
# cuDNN license: https://developer.nvidia.com/cudnn/license_agreement
mkdir tmp_cudnn && cd tmp_cudnn
wget -q https://developer.download.nvidia.com/compute/cudnn/redist/cudnn/linux-x86_64/cudnn-linux-x86_64-${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

View File

@ -1,93 +0,0 @@
#!/bin/bash
# Script used only in CD pipeline
set -ex
NCCL_VERSION=v2.21.5-1
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-sbsa/libcusparse_lt-linux-sbsa-0.6.2.3-archive.tar.xz
tar xf libcusparse_lt-linux-sbsa-0.6.2.3-archive.tar.xz
cp -a libcusparse_lt-linux-sbsa-0.6.2.3-archive/include/* /usr/local/cuda/include/
cp -a libcusparse_lt-linux-sbsa-0.6.2.3-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-0.6.2"
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 ${NCCL_VERSION} --depth 1 https://github.com/NVIDIA/nccl.git
cd nccl && make -j src.build
cp -a build/include/* /usr/local/cuda/include/
cp -a build/lib/* /usr/local/cuda/lib64/
cd ..
rm -rf nccl
install_cusparselt_062
ldconfig
}
function prune_124 {
echo "Pruning CUDA 12.4"
#####################################################################################
# CUDA 12.4 prune static libs
#####################################################################################
export NVPRUNE="/usr/local/cuda-12.4/bin/nvprune"
export CUDA_LIB_DIR="/usr/local/cuda-12.4/lib64"
export GENCODE="-gencode arch=compute_50,code=sm_50 -gencode arch=compute_60,code=sm_60 -gencode arch=compute_70,code=sm_70 -gencode arch=compute_75,code=sm_75 -gencode arch=compute_80,code=sm_80 -gencode arch=compute_86,code=sm_86 -gencode arch=compute_90,code=sm_90"
export GENCODE_CUDNN="-gencode arch=compute_50,code=sm_50 -gencode arch=compute_60,code=sm_60 -gencode arch=compute_61,code=sm_61 -gencode arch=compute_70,code=sm_70 -gencode arch=compute_75,code=sm_75 -gencode arch=compute_80,code=sm_80 -gencode arch=compute_86,code=sm_86 -gencode arch=compute_90,code=sm_90"
if [[ -n "$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

View File

@ -1,22 +1,27 @@
#!/bin/bash
if [[ -n "${CUDNN_VERSION}" ]]; then
if [[ ${CUDNN_VERSION} == 8 ]]; 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"
mkdir tmp_cudnn && cd tmp_cudnn
CUDNN_NAME="cudnn-linux-x86_64-8.3.2.44_cuda11.5-archive"
if [[ ${CUDA_VERSION:0:4} == "12.1" ]]; then
CUDNN_NAME="cudnn-linux-x86_64-8.9.2.26_cuda12-archive"
curl --retry 3 -OLs https://developer.download.nvidia.com/compute/cudnn/redist/cudnn/linux-x86_64/${CUDNN_NAME}.tar.xz
elif [[ ${CUDA_VERSION:0:4} == "11.8" ]]; then
CUDNN_NAME="cudnn-linux-x86_64-8.7.0.84_cuda11-archive"
curl --retry 3 -OLs https://developer.download.nvidia.com/compute/redist/cudnn/v8.7.0/local_installers/11.8/${CUDNN_NAME}.tar.xz
else
print "Unsupported CUDA version ${CUDA_VERSION}"
exit 1
curl --retry 3 -OLs https://developer.download.nvidia.com/compute/redist/cudnn/v8.3.2/local_installers/11.5/${CUDNN_NAME}.tar.xz
fi
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/include/
cp -a ${CUDNN_NAME}/include/* /usr/local/cuda/include/
cp -a ${CUDNN_NAME}/include/* /usr/include/x86_64-linux-gnu/
cp -a ${CUDNN_NAME}/lib/* /usr/local/cuda/lib64/
popd
cp -a ${CUDNN_NAME}/lib/* /usr/lib/x86_64-linux-gnu/
cd ..
rm -rf tmp_cudnn
ldconfig
fi

View File

@ -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

View File

@ -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

View File

@ -4,6 +4,11 @@ set -ex
install_ubuntu() {
apt-get update
apt-get install -y --no-install-recommends \
libhiredis-dev \
libleveldb-dev \
liblmdb-dev \
libsnappy-dev
# Cleanup
apt-get autoclean && apt-get clean
@ -15,6 +20,12 @@ install_centos() {
# See http://fedoraproject.org/wiki/EPEL
yum --enablerepo=extras install -y epel-release
yum install -y \
hiredis-devel \
leveldb-devel \
lmdb-devel \
snappy-devel
# Cleanup
yum clean all
rm -rf /var/cache/yum

View File

@ -37,9 +37,6 @@ install_conda_dependencies() {
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
@ -47,14 +44,14 @@ install_pip_dependencies() {
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
source .ci/scripts/utils.sh
export PYTHON_EXECUTABLE=python
export EXECUTORCH_BUILD_PYBIND=ON
export CMAKE_ARGS="-DEXECUTORCH_BUILD_XNNPACK=ON -DEXECUTORCH_BUILD_KERNELS_QUANTIZED=ON"
install_flatc_from_source
pip_install .
build_executorch_runner "cmake"
as_jenkins .ci/scripts/setup-linux.sh cmake
# Make sure that all the newly generate files are owned by Jenkins
chown -R jenkins .
popd
}

View File

@ -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

View File

@ -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

View File

@ -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

View File

@ -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

View File

@ -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

View File

@ -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

View File

@ -15,7 +15,7 @@ pip_install \
flatbuffers==2.0 \
mock==5.0.1 \
ninja==1.10.2 \
networkx==2.5 \
networkx==2.0 \
numpy==1.24.2
# ONNXRuntime should be installed before installing
@ -26,20 +26,18 @@ pip_install \
pytest-cov==4.0.0 \
pytest-subtests==0.10.0 \
tabulate==0.9.0 \
transformers==4.36.2
transformers==4.32.1
pip_install coloredlogs packaging
retry pip_install -i https://aiinfra.pkgs.visualstudio.com/PublicPackages/_packaging/ORT-Nightly/pypi/simple/ --no-cache-dir --no-input ort-nightly==1.17.0.dev20231005006
pip_install onnxruntime==1.18.1
pip_install onnx==1.16.2
pip_install onnxscript==0.1.0.dev20241009 --no-deps
# required by onnxscript
pip_install ml_dtypes
pip_install -i https://test.pypi.org/simple/ onnx==1.15.0rc2
pip_install onnxscript==0.1.0.dev20231128 --no-deps
# 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");' > "${IMPORT_SCRIPT_FILENAME}"
as_jenkins echo 'import transformers; transformers.AutoModel.from_pretrained("sshleifer/tiny-gpt2"); transformers.AutoTokenizer.from_pretrained("sshleifer/tiny-gpt2");' > "${IMPORT_SCRIPT_FILENAME}"
# Need a PyTorch version for transformers to work
pip_install --pre torch --index-url https://download.pytorch.org/whl/nightly/cpu

View File

@ -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

@ -9,8 +9,7 @@ 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
make -j6; make install_sw
# Link the ssl libraries to the /usr/lib folder.
sudo ln -s /opt/openssl/lib/lib* /usr/lib
cd ..

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

@ -2,18 +2,55 @@
set -ex
pb_dir="/usr/temp_pb_install_dir"
mkdir -p $pb_dir
# This function installs protobuf 3.17
install_protobuf_317() {
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"
# 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 "$pb_dir/lib64"
curl -LO "https://github.com/protocolbuffers/protobuf/releases/download/v3.17.3/protobuf-all-3.17.3.tar.gz" --retry 3
curl -LO "https://github.com/protocolbuffers/protobuf/releases/download/v3.17.3/protobuf-all-3.17.3.tar.gz" --retry 3
tar -xvz -C "$pb_dir" --strip-components 1 -f protobuf-all-3.17.3.tar.gz
# -j6 to balance memory usage and speed.
# naked `-j` seems to use too much memory.
pushd "$pb_dir" && ./configure && make -j6 && make -j6 check && sudo make -j6 install && sudo ldconfig
popd
rm -rf $pb_dir
}
tar -xvz --no-same-owner -C "$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 $pb_dir
install_ubuntu() {
# Ubuntu 14.04 has cmake 2.8.12 as the default option, so we will
# install cmake3 here and use cmake3.
apt-get update
if [[ "$UBUNTU_VERSION" == 14.04 ]]; then
apt-get install -y --no-install-recommends cmake3
fi
# Cleanup
apt-get autoclean && apt-get clean
rm -rf /var/lib/apt/lists/* /tmp/* /var/tmp/*
install_protobuf_317
}
install_centos() {
install_protobuf_317
}
# 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

View File

@ -6,6 +6,9 @@ ver() {
printf "%3d%03d%03d%03d" $(echo "$1" | tr '.' ' ');
}
# Map ROCm version to AMDGPU version
declare -A AMDGPU_VERSIONS=( ["5.0"]="21.50" ["5.1.1"]="22.10.1" ["5.2"]="22.20" )
install_ubuntu() {
apt-get update
if [[ $UBUNTU_VERSION == 18.04 ]]; then
@ -23,14 +26,31 @@ install_ubuntu() {
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
if [[ $(ver $ROCM_VERSION) -ge $(ver 4.5) ]]; then
# Add amdgpu repository
UBUNTU_VERSION_NAME=`cat /etc/os-release | grep UBUNTU_CODENAME | awk -F= '{print $2}'`
local amdgpu_baseurl
if [[ $(ver $ROCM_VERSION) -ge $(ver 5.3) ]]; then
amdgpu_baseurl="https://repo.radeon.com/amdgpu/${ROCM_VERSION}/ubuntu"
else
amdgpu_baseurl="https://repo.radeon.com/amdgpu/${AMDGPU_VERSIONS[$ROCM_VERSION]}/ubuntu"
fi
echo "deb [arch=amd64] ${amdgpu_baseurl} ${UBUNTU_VERSION_NAME} main" > /etc/apt/sources.list.d/amdgpu.list
fi
ROCM_REPO="ubuntu"
if [[ $(ver $ROCM_VERSION) -lt $(ver 4.2) ]]; then
ROCM_REPO="xenial"
fi
if [[ $(ver $ROCM_VERSION) -ge $(ver 5.3) ]]; then
ROCM_REPO="${UBUNTU_VERSION_NAME}"
fi
# 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
echo "deb [arch=amd64] ${rocm_baseurl} ${ROCM_REPO} main" > /etc/apt/sources.list.d/rocm.list
apt-get update --allow-insecure-repositories
DEBIAN_FRONTEND=noninteractive apt-get install -y --allow-unauthenticated \
@ -39,29 +59,27 @@ install_ubuntu() {
rocm-libs \
rccl \
rocprofiler-dev \
roctracer-dev \
amd-smi-lib
if [[ $(ver $ROCM_VERSION) -ge $(ver 6.1) ]]; then
DEBIAN_FRONTEND=noninteractive apt-get install -y --allow-unauthenticated rocm-llvm-dev
fi
roctracer-dev
# precompiled miopen kernels added in ROCm 3.5, renamed in ROCm 5.5
# search for all unversioned packages
# if search fails it will abort this script; use true to avoid case where search fails
MIOPENHIPGFX=$(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
if [[ $(ver $ROCM_VERSION) -ge $(ver 5.5) ]]; then
MIOPENHIPGFX=$(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
else
DEBIAN_FRONTEND=noninteractive apt-get install -y --allow-unauthenticated ${MIOPENHIPGFX}
MIOPENKERNELS=$(apt-cache search --names-only miopenkernels | awk '{print $1}' | grep -F -v . || true)
if [[ "x${MIOPENKERNELS}" = x ]]; then
echo "miopenkernels package not available" && exit 1
else
DEBIAN_FRONTEND=noninteractive apt-get install -y --allow-unauthenticated ${MIOPENKERNELS}
fi
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/*
@ -77,19 +95,25 @@ install_centos() {
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"
if [[ $(ver $ROCM_VERSION) -ge $(ver 4.5) ]]; then
# Add amdgpu repository
local amdgpu_baseurl
if [[ $OS_VERSION == 9 ]]; then
amdgpu_baseurl="https://repo.radeon.com/amdgpu/${AMDGPU_VERSIONS[$ROCM_VERSION]}/rhel/9.0/main/x86_64"
else
if [[ $(ver $ROCM_VERSION) -ge $(ver 5.3) ]]; then
amdgpu_baseurl="https://repo.radeon.com/amdgpu/${ROCM_VERSION}/rhel/7.9/main/x86_64"
else
amdgpu_baseurl="https://repo.radeon.com/amdgpu/${AMDGPU_VERSIONS[$ROCM_VERSION]}/rhel/7.9/main/x86_64"
fi
fi
echo "[AMDGPU]" > /etc/yum.repos.d/amdgpu.repo
echo "name=AMDGPU" >> /etc/yum.repos.d/amdgpu.repo
echo "baseurl=${amdgpu_baseurl}" >> /etc/yum.repos.d/amdgpu.repo
echo "enabled=1" >> /etc/yum.repos.d/amdgpu.repo
echo "gpgcheck=1" >> /etc/yum.repos.d/amdgpu.repo
echo "gpgkey=http://repo.radeon.com/rocm/rocm.gpg.key" >> /etc/yum.repos.d/amdgpu.repo
fi
echo "[AMDGPU]" > /etc/yum.repos.d/amdgpu.repo
echo "name=AMDGPU" >> /etc/yum.repos.d/amdgpu.repo
echo "baseurl=${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/${ROCM_VERSION}"
echo "[ROCm]" > /etc/yum.repos.d/rocm.repo
@ -107,24 +131,26 @@ install_centos() {
rocm-libs \
rccl \
rocprofiler-dev \
roctracer-dev \
amd-smi-lib
roctracer-dev
# precompiled miopen kernels; search for all unversioned packages
# if search fails it will abort this script; use true to avoid case where search fails
MIOPENHIPGFX=$(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
if [[ $(ver $ROCM_VERSION) -ge $(ver 5.5) ]]; then
MIOPENHIPGFX=$(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
else
yum install -y ${MIOPENHIPGFX}
MIOPENKERNELS=$(yum -q search miopenkernels | grep miopenkernels- | awk '{print $1}'| grep -F kdb. || true)
if [[ "x${MIOPENKERNELS}" = x ]]; then
echo "miopenkernels package not available" && exit 1
else
yum install -y ${MIOPENKERNELS}
fi
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

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

@ -1,24 +1,17 @@
#!/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
git checkout 823531632140d0edcb7e77c3edc0e837421471c5
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,$(MKLROOT)/lib -Wl,--rpath,/opt/rocm/magma/lib -ldl' >> make.inc
echo 'LIB += -Wl,--enable-new-dtags -Wl,--rpath,/opt/rocm/lib -Wl,--rpath,$(MKLROOT)/lib -Wl,--rpath,/opt/rocm/magma/lib' >> make.inc
echo 'DEVCCFLAGS += --gpu-max-threads-per-block=256' >> make.inc
export PATH="${PATH}:/opt/rocm/bin"
if [[ -n "$PYTORCH_ROCM_ARCH" ]]; then
@ -32,7 +25,7 @@ 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}"
LANG=C.UTF-8 make lib/libmagma.so -j $(nproc) MKLROOT=/opt/conda/envs/py_$ANACONDA_PYTHON_VERSION
make testing/testing_dgemm -j $(nproc) MKLROOT=/opt/conda/envs/py_$ANACONDA_PYTHON_VERSION
popd
mv magma /opt/rocm

View File

@ -12,14 +12,11 @@ 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"
elif [ -n "${TRITON_CPU}" ]; then
TRITON_REPO="https://github.com/triton-lang/triton-cpu"
TRITON_TEXT_FILE="triton-cpu"
if [ -n "${ROCM_VERSION}" ]; then
TRITON_REPO="https://github.com/ROCmSoftwarePlatform/triton"
TRITON_TEXT_FILE="triton-rocm"
else
TRITON_REPO="https://github.com/triton-lang/triton"
TRITON_REPO="https://github.com/openai/triton"
TRITON_TEXT_FILE="triton"
fi
@ -41,34 +38,19 @@ 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 --recursive ${TRITON_REPO} triton
cd triton
as_jenkins git checkout ${TRITON_PINNED_COMMIT}
as_jenkins git submodule update --init --recursive
cd python
# TODO: remove patch setup.py once we have a proper fix for https://github.com/triton-lang/triton/issues/4527
as_jenkins sed -i -e 's/https:\/\/tritonlang.blob.core.windows.net\/llvm-builds/https:\/\/oaitriton.blob.core.windows.net\/public\/llvm-builds/g' setup.py
if [ -n "${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 .
CXX=g++-9 pip_install "git+${TRITON_REPO}@${TRITON_PINNED_COMMIT}#subdirectory=python"
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 .
CXX=g++-9 pip_install "git+${TRITON_REPO}@${TRITON_PINNED_COMMIT}#subdirectory=python"
else
pip_install -e .
pip_install "git+${TRITON_REPO}@${TRITON_PINNED_COMMIT}#subdirectory=python"
fi
if [ -n "${CONDA_CMAKE}" ]; then
@ -82,6 +64,5 @@ if [ -n "${CONDA_CMAKE}" ]; then
# 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}"
conda_reinstall numpy="${NUMPY_VERSION}"
fi

View File

@ -36,12 +36,7 @@ function install_ucc() {
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}"
./configure --prefix=$UCC_HOME --with-ucx=$UCX_HOME --with-cuda=$with_cuda
time make -j
sudo make install

View File

@ -5,7 +5,8 @@ set -ex
install_ubuntu() {
apt-get update
apt-get install -y --no-install-recommends \
libopencv-dev
libopencv-dev \
libavcodec-dev
# Cleanup
apt-get autoclean && apt-get clean
@ -18,7 +19,8 @@ install_centos() {
yum --enablerepo=extras install -y epel-release
yum install -y \
opencv-devel
opencv-devel \
ffmpeg-devel
# Cleanup
yum clean all

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

View File

@ -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

View File

@ -1,107 +0,0 @@
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

View File

@ -29,7 +29,7 @@ RUN bash ./install_conda.sh && rm install_conda.sh common_utils.sh /opt/conda/re
# Install cuda and cudnn
ARG CUDA_VERSION
COPY ./common/install_cuda.sh install_cuda.sh
RUN wget -q https://raw.githubusercontent.com/pytorch/builder/main/common/install_cuda.sh -O 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

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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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@ -1,157 +0,0 @@
# 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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@ -1,57 +0,0 @@
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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@ -1,94 +0,0 @@
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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@ -1,91 +0,0 @@
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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@ -1,71 +0,0 @@
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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@ -1,73 +0,0 @@
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

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@ -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

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@ -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

@ -15,7 +15,7 @@ click
#Pinned versions:
#test that import:
coremltools==5.0b5 ; python_version < "3.12"
coremltools==5.0b5
#Description: Apple framework for ML integration
#Pinned versions: 5.0b5
#test that import:
@ -25,19 +25,9 @@ coremltools==5.0b5 ; python_version < "3.12"
#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
expecttest==0.1.6
#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:
@ -57,11 +47,6 @@ junitparser==2.1.1
#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
@ -81,7 +66,7 @@ librosa>=0.6.2 ; python_version < "3.11"
#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 that import: test_module_init.py, test_modules.py, test_nn.py,
#test_testing.py
#MonkeyType # breaks pytorch-xla-linux-bionic-py3.7-clang8
@ -90,10 +75,10 @@ librosa>=0.6.2 ; python_version < "3.11"
#Pinned versions:
#test that import:
mypy==1.11.2
mypy==1.7.0
# Pin MyPy version because new errors are likely to appear with each release
#Description: linter
#Pinned versions: 1.10.0
#Pinned versions: 1.7.0
#test that import: test_typing.py, test_type_hints.py
networkx==2.8.8
@ -109,7 +94,7 @@ networkx==2.8.8
#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==0.54.1 ; 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
@ -118,7 +103,7 @@ numba==0.55.2 ; python_version == "3.10"
#numpy
#Description: Provides N-dimensional arrays and linear algebra
#Pinned versions: 1.26.2
#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,
@ -128,10 +113,6 @@ numba==0.55.2 ; python_version == "3.10"
#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
numpy==1.21.2; python_version == "3.9"
numpy==1.22.4; python_version == "3.10"
numpy==1.26.2; python_version == "3.11" or python_version == "3.12"
numpy==2.1.2; python_version >= "3.13"
#onnxruntime
#Description: scoring engine for Open Neural Network Exchange (ONNX) models
@ -143,9 +124,9 @@ opt-einsum==3.3
#Pinned versions: 3.3
#test that import: test_linalg.py
optree==0.13.0
optree==0.9.1
#Description: A library for tree manipulation
#Pinned versions: 0.13.0
#Pinned versions: 0.9.1
#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,
@ -156,9 +137,9 @@ optree==0.13.0
#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
pillow==10.0.1
#Description: Python Imaging Library fork
#Pinned versions: 10.3.0
#Pinned versions: 10.0.1
#test that import:
protobuf==3.20.2
@ -181,6 +162,11 @@ pytest-xdist==3.3.1
#Pinned versions:
#test that import:
pytest-shard==0.1.2
#Description: plugin spliting up tests in pytest
#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
@ -227,7 +213,7 @@ pygments==2.15.0
#test that import:
scikit-image==0.19.3 ; python_version < "3.10"
scikit-image==0.22.0 ; python_version >= "3.10"
scikit-image==0.20.0 ; python_version >= "3.10"
#Description: image processing routines
#Pinned versions:
#test that import: test_nn.py
@ -237,11 +223,12 @@ scikit-image==0.22.0 ; python_version >= "3.10"
#Pinned versions: 0.20.3
#test that import:
scipy==1.10.1 ; python_version <= "3.11"
scipy==1.12.0 ; python_version == "3.12"
scipy==1.6.3 ; python_version < "3.10"
scipy==1.8.1 ; python_version == "3.10"
scipy==1.10.1 ; python_version == "3.11"
# Pin SciPy because of failing distribution tests (see #60347)
#Description: scientific python
#Pinned versions: 1.10.1
#Pinned versions: 1.6.3
#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
@ -256,8 +243,7 @@ tb-nightly==2.13.0a20230426
#Pinned versions:
#test that import:
# needed by torchgen utils
typing-extensions
#typing-extensions
#Description: type hints for python
#Pinned versions:
#test that import:
@ -272,29 +258,24 @@ unittest-xml-reporting<=3.2.0,>=2.0.0
#Pinned versions:
#test that import:
#lintrunner is supported on aarch64-linux only from 0.12.4 version
lintrunner==0.12.5
lintrunner==0.10.7
#Description: all about linters!
#Pinned versions: 0.12.5
#Pinned versions: 0.10.7
#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
ghstack==0.7.1
#Description: ghstack tool
#Pinned versions: 0.8.0
#Pinned versions: 0.7.1
#test that import:
jinja2==3.1.4
jinja2==3.1.2
#Description: jinja2 template engine
#Pinned versions: 3.1.4
#Pinned versions: 3.1.2
#test that import:
pytest-cpp==2.3.0
@ -312,59 +293,13 @@ tensorboard==2.13.0
#Pinned versions:
#test that import: test_tensorboard
pywavelets==1.4.1 ; python_version < "3.12"
pywavelets==1.5.0 ; python_version >= "3.12"
pywavelets==1.4.1
#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
lxml==4.9.4
#Description: This is a requirement of unittest-xml-reporting
# have to pin to 4.9.4 because 5.0.0 release on Dec 29th missing
# Python-3.9 binaries
PyGithub==2.3.0
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:
#Description: required for testing torch/distributed/_tools/sac_estimator.py
#Pinned versions: 1.24.0
#test that import: test_sac_estimator.py
pwlf==2.2.1 ; python_version >= "3.8"
#Description: required for testing torch/distributed/_tools/sac_estimator.py
#Pinned versions: 2.2.1
#test that import: test_sac_estimator.py
# To build PyTorch itself
astunparse
PyYAML
setuptools
ninja==1.11.1 ; platform_machine == "aarch64"
scons==4.5.2 ; platform_machine == "aarch64"
pulp==2.9.0 ; python_version >= "3.8"
#Description: required for testing ilp formulaiton under torch/distributed/_tools
#Pinned versions: 2.9.0
#test that import: test_sac_ilp.py

View File

@ -1 +1 @@
3.1.0
2.2.0

View File

@ -56,7 +56,7 @@ RUN if [ -n "${DB}" ]; then bash ./install_db.sh; fi
RUN rm install_db.sh
ENV INSTALLED_DB ${DB}
# (optional) Install vision packages like OpenCV
# (optional) Install vision packages like OpenCV and ffmpeg
ARG VISION
COPY ./common/install_vision.sh ./common/cache_vision_models.sh ./common/common_utils.sh ./
RUN if [ -n "${VISION}" ]; then bash ./install_vision.sh; fi
@ -103,14 +103,6 @@ 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:$PATH
@ -147,26 +139,13 @@ COPY --from=pytorch/llvm:9.0.1 /opt/llvm /opt/llvm
ARG CUDNN_VERSION
ARG CUDA_VERSION
COPY ./common/install_cudnn.sh install_cudnn.sh
RUN if [ -n "${CUDNN_VERSION}" ]; then bash install_cudnn.sh; fi
RUN if [ "${CUDNN_VERSION}" -eq 8 ]; then bash install_cudnn.sh; fi
RUN rm install_cudnn.sh
# Install CUSPARSELT
ARG CUDA_VERSION
COPY ./common/install_cusparselt.sh install_cusparselt.sh
RUN bash install_cusparselt.sh
RUN rm install_cusparselt.sh
# 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"]

View File

@ -53,7 +53,7 @@ RUN if [ -n "${DB}" ]; then bash ./install_db.sh; fi
RUN rm install_db.sh
ENV INSTALLED_DB ${DB}
# (optional) Install vision packages like OpenCV
# (optional) Install vision packages like OpenCV and ffmpeg
ARG VISION
COPY ./common/install_vision.sh ./common/cache_vision_models.sh ./common/common_utils.sh ./
RUN if [ -n "${VISION}" ]; then bash ./install_vision.sh; fi
@ -68,8 +68,6 @@ 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:$PATH
@ -80,11 +78,6 @@ ENV MAGMA_HOME /opt/rocm/magma
ENV LANG C.UTF-8
ENV LC_ALL C.UTF-8
# Install amdsmi
COPY ./common/install_amdsmi.sh install_amdsmi.sh
RUN bash ./install_amdsmi.sh
RUN rm install_amdsmi.sh
# (optional) Install non-default CMake version
ARG CMAKE_VERSION
COPY ./common/install_cmake.sh install_cmake.sh
@ -102,17 +95,10 @@ ARG TRITON
# try to reach out to S3, which docker build runners don't have access
COPY ./common/install_triton.sh install_triton.sh
COPY ./common/common_utils.sh common_utils.sh
COPY ci_commit_pins/triton.txt triton.txt
COPY ci_commit_pins/triton-rocm.txt triton-rocm.txt
COPY triton_version.txt triton_version.txt
RUN if [ -n "${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
RUN rm install_triton.sh common_utils.sh triton-rocm.txt triton_version.txt
# Install ccache/sccache (do this last, so we get priority in PATH)
COPY ./common/install_cache.sh install_cache.sh
@ -123,8 +109,5 @@ RUN bash ./install_cache.sh && rm install_cache.sh
ARG BUILD_ENVIRONMENT
ENV BUILD_ENVIRONMENT ${BUILD_ENVIRONMENT}
# Install LLVM dev version (Defined in the pytorch/builder github repository)
COPY --from=pytorch/llvm:9.0.1 /opt/llvm /opt/llvm
USER jenkins
CMD ["bash"]

View File

@ -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"]

View File

@ -37,7 +37,6 @@ 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
@ -50,7 +49,7 @@ 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 wget -q https://raw.githubusercontent.com/pytorch/builder/main/common/install_cuda.sh -O 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
@ -80,7 +79,7 @@ RUN if [ -n "${DB}" ]; then bash ./install_db.sh; fi
RUN rm install_db.sh
ENV INSTALLED_DB ${DB}
# (optional) Install vision packages like OpenCV
# (optional) Install vision packages like OpenCV and ffmpeg
ARG VISION
COPY ./common/install_vision.sh ./common/cache_vision_models.sh ./common/common_utils.sh ./
RUN if [ -n "${VISION}" ]; then bash ./install_vision.sh; fi
@ -147,13 +146,6 @@ COPY ci_commit_pins/triton.txt triton.txt
RUN if [ -n "${TRITON}" ]; then bash ./install_triton.sh; fi
RUN rm install_triton.sh common_utils.sh triton.txt
ARG TRITON_CPU
COPY ./common/install_triton.sh install_triton.sh
COPY ./common/common_utils.sh common_utils.sh
COPY ci_commit_pins/triton-cpu.txt triton-cpu.txt
RUN if [ -n "${TRITON_CPU}" ]; then bash ./install_triton.sh; fi
RUN rm install_triton.sh common_utils.sh triton-cpu.txt
ARG EXECUTORCH
# Build and install executorch
COPY ./common/install_executorch.sh install_executorch.sh
@ -162,33 +154,16 @@ 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
RUN bash ./install_cache.sh && rm install_cache.sh
# Add jni.h for java host build
COPY ./common/install_jni.sh install_jni.sh
@ -205,9 +180,7 @@ 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

View File

@ -1,10 +0,0 @@
#!/usr/bin/env bash
# This is mostly just a shim to manywheel/build.sh
# TODO: Make this a dedicated script to build just libtorch
set -ex
SCRIPTPATH="$( cd "$( dirname "${BASH_SOURCE[0]}" )" >/dev/null 2>&1 && pwd )"
USE_CUSPARSELT=0 BUILD_PYTHONLESS=1 DESIRED_PYTHON="3.9" ${SCRIPTPATH}/../manywheel/build.sh

View File

@ -1,21 +0,0 @@
The MIT License (MIT)
Copyright (c) 2016 manylinux
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.

View File

@ -1,25 +0,0 @@
#!/usr/bin/env bash
set -ex
SCRIPTPATH="$( cd "$( dirname "${BASH_SOURCE[0]}" )" >/dev/null 2>&1 && pwd )"
case "${GPU_ARCH_TYPE:-BLANK}" in
BLANK)
# Legacy behavior for CircleCI
bash "${SCRIPTPATH}/build_cuda.sh"
;;
cuda)
bash "${SCRIPTPATH}/build_cuda.sh"
;;
rocm)
bash "${SCRIPTPATH}/build_rocm.sh"
;;
cpu | cpu-cxx11-abi | cpu-s390x | xpu)
bash "${SCRIPTPATH}/build_cpu.sh"
;;
*)
echo "Un-recognized GPU_ARCH_TYPE '${GPU_ARCH_TYPE}', exiting..."
exit 1
;;
esac

View File

@ -1,505 +0,0 @@
#!/usr/bin/env bash
# meant to be called only from the neighboring build.sh and build_cpu.sh scripts
set -ex
SOURCE_DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" >/dev/null && pwd )"
# Require only one python installation
if [[ -z "$DESIRED_PYTHON" ]]; then
echo "Need to set DESIRED_PYTHON env variable"
exit 1
fi
if [[ -n "$BUILD_PYTHONLESS" && -z "$LIBTORCH_VARIANT" ]]; then
echo "BUILD_PYTHONLESS is set, so need LIBTORCH_VARIANT to also be set"
echo "LIBTORCH_VARIANT should be one of shared-with-deps shared-without-deps static-with-deps static-without-deps"
exit 1
fi
# Function to retry functions that sometimes timeout or have flaky failures
retry () {
$* || (sleep 1 && $*) || (sleep 2 && $*) || (sleep 4 && $*) || (sleep 8 && $*)
}
# TODO move this into the Docker images
OS_NAME=$(awk -F= '/^NAME/{print $2}' /etc/os-release)
if [[ "$OS_NAME" == *"CentOS Linux"* ]]; then
retry yum install -q -y zip openssl
elif [[ "$OS_NAME" == *"AlmaLinux"* ]]; then
retry yum install -q -y zip openssl
elif [[ "$OS_NAME" == *"Red Hat Enterprise Linux"* ]]; then
retry dnf install -q -y zip openssl
elif [[ "$OS_NAME" == *"Ubuntu"* ]]; then
# TODO: Remove this once nvidia package repos are back online
# Comment out nvidia repositories to prevent them from getting apt-get updated, see https://github.com/pytorch/pytorch/issues/74968
# shellcheck disable=SC2046
sed -i 's/.*nvidia.*/# &/' $(find /etc/apt/ -type f -name "*.list")
retry apt-get update
retry apt-get -y install zip openssl
fi
# We use the package name to test the package by passing this to 'pip install'
# This is the env variable that setup.py uses to name the package. Note that
# pip 'normalizes' the name first by changing all - to _
if [[ -z "$TORCH_PACKAGE_NAME" ]]; then
TORCH_PACKAGE_NAME='torch'
fi
if [[ -z "$TORCH_NO_PYTHON_PACKAGE_NAME" ]]; then
TORCH_NO_PYTHON_PACKAGE_NAME='torch_no_python'
fi
TORCH_PACKAGE_NAME="$(echo $TORCH_PACKAGE_NAME | tr '-' '_')"
TORCH_NO_PYTHON_PACKAGE_NAME="$(echo $TORCH_NO_PYTHON_PACKAGE_NAME | tr '-' '_')"
echo "Expecting the built wheels to all be called '$TORCH_PACKAGE_NAME' or '$TORCH_NO_PYTHON_PACKAGE_NAME'"
# Version: setup.py uses $PYTORCH_BUILD_VERSION.post$PYTORCH_BUILD_NUMBER if
# PYTORCH_BUILD_NUMBER > 1
build_version="$PYTORCH_BUILD_VERSION"
build_number="$PYTORCH_BUILD_NUMBER"
if [[ -n "$OVERRIDE_PACKAGE_VERSION" ]]; then
# This will be the *exact* version, since build_number<1
build_version="$OVERRIDE_PACKAGE_VERSION"
build_number=0
fi
if [[ -z "$build_version" ]]; then
build_version=1.0.0
fi
if [[ -z "$build_number" ]]; then
build_number=1
fi
export PYTORCH_BUILD_VERSION=$build_version
export PYTORCH_BUILD_NUMBER=$build_number
export CMAKE_LIBRARY_PATH="/opt/intel/lib:/lib:$CMAKE_LIBRARY_PATH"
export CMAKE_INCLUDE_PATH="/opt/intel/include:$CMAKE_INCLUDE_PATH"
if [[ -e /opt/openssl ]]; then
export OPENSSL_ROOT_DIR=/opt/openssl
export CMAKE_INCLUDE_PATH="/opt/openssl/include":$CMAKE_INCLUDE_PATH
fi
# If given a python version like 3.6m or 2.7mu, convert this to the format we
# expect. The binary CI jobs pass in python versions like this; they also only
# ever pass one python version, so we assume that DESIRED_PYTHON is not a list
# in this case
if [[ -n "$DESIRED_PYTHON" && $DESIRED_PYTHON =~ ([0-9].[0-9]+)t ]]; then
python_digits="$(echo $DESIRED_PYTHON | tr -cd [:digit:])"
py_majmin="${DESIRED_PYTHON}"
DESIRED_PYTHON="cp${python_digits}-cp${python_digits}t"
elif [[ -n "$DESIRED_PYTHON" && "$DESIRED_PYTHON" != cp* ]]; then
python_nodot="$(echo $DESIRED_PYTHON | tr -d m.u)"
DESIRED_PYTHON="cp${python_nodot}-cp${python_nodot}"
if [[ ${python_nodot} -ge 310 ]]; then
py_majmin="${DESIRED_PYTHON:2:1}.${DESIRED_PYTHON:3:2}"
else
py_majmin="${DESIRED_PYTHON:2:1}.${DESIRED_PYTHON:3:1}"
fi
fi
pydir="/opt/python/$DESIRED_PYTHON"
export PATH="$pydir/bin:$PATH"
echo "Will build for Python version: ${DESIRED_PYTHON} with ${python_installation}"
mkdir -p /tmp/$WHEELHOUSE_DIR
export PATCHELF_BIN=/usr/local/bin/patchelf
patchelf_version=$($PATCHELF_BIN --version)
echo "patchelf version: " $patchelf_version
if [[ "$patchelf_version" == "patchelf 0.9" ]]; then
echo "Your patchelf version is too old. Please use version >= 0.10."
exit 1
fi
########################################################
# Compile wheels as well as libtorch
#######################################################
if [[ -z "$PYTORCH_ROOT" ]]; then
echo "Need to set PYTORCH_ROOT env variable"
exit 1
fi
pushd "$PYTORCH_ROOT"
python setup.py clean
retry pip install -qr requirements.txt
case ${DESIRED_PYTHON} in
cp31*)
retry pip install -q --pre numpy==2.1.0
;;
# Should catch 3.9+
*)
retry pip install -q --pre numpy==2.0.2
;;
esac
if [[ "$DESIRED_DEVTOOLSET" == *"cxx11-abi"* ]]; then
export _GLIBCXX_USE_CXX11_ABI=1
else
export _GLIBCXX_USE_CXX11_ABI=0
fi
if [[ "$DESIRED_CUDA" == *"rocm"* ]]; then
echo "Calling build_amd.py at $(date)"
python tools/amd_build/build_amd.py
fi
# This value comes from binary_linux_build.sh (and should only be set to true
# for master / release branches)
BUILD_DEBUG_INFO=${BUILD_DEBUG_INFO:=0}
if [[ $BUILD_DEBUG_INFO == "1" ]]; then
echo "Building wheel and debug info"
else
echo "BUILD_DEBUG_INFO was not set, skipping debug info"
fi
if [[ "$DISABLE_RCCL" = 1 ]]; then
echo "Disabling NCCL/RCCL in pyTorch"
USE_RCCL=0
USE_NCCL=0
USE_KINETO=0
else
USE_RCCL=1
USE_NCCL=1
USE_KINETO=1
fi
echo "Calling setup.py bdist at $(date)"
if [[ "$USE_SPLIT_BUILD" == "true" ]]; then
echo "Calling setup.py bdist_wheel for split build (BUILD_LIBTORCH_WHL)"
time EXTRA_CAFFE2_CMAKE_FLAGS=${EXTRA_CAFFE2_CMAKE_FLAGS[@]} \
BUILD_LIBTORCH_WHL=1 BUILD_PYTHON_ONLY=0 \
BUILD_LIBTORCH_CPU_WITH_DEBUG=$BUILD_DEBUG_INFO \
USE_NCCL=${USE_NCCL} USE_RCCL=${USE_RCCL} USE_KINETO=${USE_KINETO} \
python setup.py bdist_wheel -d /tmp/$WHEELHOUSE_DIR
echo "Finished setup.py bdist_wheel for split build (BUILD_LIBTORCH_WHL)"
echo "Calling setup.py bdist_wheel for split build (BUILD_PYTHON_ONLY)"
time EXTRA_CAFFE2_CMAKE_FLAGS=${EXTRA_CAFFE2_CMAKE_FLAGS[@]} \
BUILD_LIBTORCH_WHL=0 BUILD_PYTHON_ONLY=1 \
BUILD_LIBTORCH_CPU_WITH_DEBUG=$BUILD_DEBUG_INFO \
USE_NCCL=${USE_NCCL} USE_RCCL=${USE_RCCL} USE_KINETO=${USE_KINETO} \
python setup.py bdist_wheel -d /tmp/$WHEELHOUSE_DIR --cmake
echo "Finished setup.py bdist_wheel for split build (BUILD_PYTHON_ONLY)"
else
time CMAKE_ARGS=${CMAKE_ARGS[@]} \
EXTRA_CAFFE2_CMAKE_FLAGS=${EXTRA_CAFFE2_CMAKE_FLAGS[@]} \
BUILD_LIBTORCH_CPU_WITH_DEBUG=$BUILD_DEBUG_INFO \
USE_NCCL=${USE_NCCL} USE_RCCL=${USE_RCCL} USE_KINETO=${USE_KINETO} \
python setup.py bdist_wheel -d /tmp/$WHEELHOUSE_DIR
fi
echo "Finished setup.py bdist at $(date)"
# Build libtorch packages
if [[ -n "$BUILD_PYTHONLESS" ]]; then
# Now build pythonless libtorch
# Note - just use whichever python we happen to be on
python setup.py clean
if [[ $LIBTORCH_VARIANT = *"static"* ]]; then
STATIC_CMAKE_FLAG="-DTORCH_STATIC=1"
fi
mkdir -p build
pushd build
echo "Calling tools/build_libtorch.py at $(date)"
time CMAKE_ARGS=${CMAKE_ARGS[@]} \
EXTRA_CAFFE2_CMAKE_FLAGS="${EXTRA_CAFFE2_CMAKE_FLAGS[@]} $STATIC_CMAKE_FLAG" \
python ../tools/build_libtorch.py
echo "Finished tools/build_libtorch.py at $(date)"
popd
mkdir -p libtorch/{lib,bin,include,share}
cp -r build/build/lib libtorch/
# for now, the headers for the libtorch package will just be copied in
# from one of the wheels (this is from when this script built multiple
# wheels at once)
ANY_WHEEL=$(ls /tmp/$WHEELHOUSE_DIR/torch*.whl | head -n1)
unzip -d any_wheel $ANY_WHEEL
if [[ -d any_wheel/torch/include ]]; then
cp -r any_wheel/torch/include libtorch/
else
cp -r any_wheel/torch/lib/include libtorch/
fi
cp -r any_wheel/torch/share/cmake libtorch/share/
rm -rf any_wheel
echo $PYTORCH_BUILD_VERSION > libtorch/build-version
echo "$(pushd $PYTORCH_ROOT && git rev-parse HEAD)" > libtorch/build-hash
mkdir -p /tmp/$LIBTORCH_HOUSE_DIR
if [[ "$DESIRED_DEVTOOLSET" == *"cxx11-abi"* ]]; then
LIBTORCH_ABI="cxx11-abi-"
else
LIBTORCH_ABI=
fi
zip -rq /tmp/$LIBTORCH_HOUSE_DIR/libtorch-$LIBTORCH_ABI$LIBTORCH_VARIANT-$PYTORCH_BUILD_VERSION.zip libtorch
cp /tmp/$LIBTORCH_HOUSE_DIR/libtorch-$LIBTORCH_ABI$LIBTORCH_VARIANT-$PYTORCH_BUILD_VERSION.zip \
/tmp/$LIBTORCH_HOUSE_DIR/libtorch-$LIBTORCH_ABI$LIBTORCH_VARIANT-latest.zip
fi
popd
#######################################################################
# ADD DEPENDENCIES INTO THE WHEEL
#
# auditwheel repair doesn't work correctly and is buggy
# so manually do the work of copying dependency libs and patchelfing
# and fixing RECORDS entries correctly
######################################################################
fname_with_sha256() {
HASH=$(sha256sum $1 | cut -c1-8)
DIRNAME=$(dirname $1)
BASENAME=$(basename $1)
# Do not rename nvrtc-builtins.so as they are dynamically loaded
# by libnvrtc.so
# Similarly don't mangle libcudnn and libcublas library names
if [[ $BASENAME == "libnvrtc-builtins.s"* || $BASENAME == "libcudnn"* || $BASENAME == "libcublas"* ]]; then
echo $1
else
INITNAME=$(echo $BASENAME | cut -f1 -d".")
ENDNAME=$(echo $BASENAME | cut -f 2- -d".")
echo "$DIRNAME/$INITNAME-$HASH.$ENDNAME"
fi
}
fname_without_so_number() {
LINKNAME=$(echo $1 | sed -e 's/\.so.*/.so/g')
echo "$LINKNAME"
}
make_wheel_record() {
FPATH=$1
if echo $FPATH | grep RECORD >/dev/null 2>&1; then
# if the RECORD file, then
echo "$FPATH,,"
else
HASH=$(openssl dgst -sha256 -binary $FPATH | openssl base64 | sed -e 's/+/-/g' | sed -e 's/\//_/g' | sed -e 's/=//g')
FSIZE=$(ls -nl $FPATH | awk '{print $5}')
echo "$FPATH,sha256=$HASH,$FSIZE"
fi
}
replace_needed_sofiles() {
find $1 -name '*.so*' | while read sofile; do
origname=$2
patchedname=$3
if [[ "$origname" != "$patchedname" ]] || [[ "$DESIRED_CUDA" == *"rocm"* ]]; then
set +e
origname=$($PATCHELF_BIN --print-needed $sofile | grep "$origname.*")
ERRCODE=$?
set -e
if [ "$ERRCODE" -eq "0" ]; then
echo "patching $sofile entry $origname to $patchedname"
$PATCHELF_BIN --replace-needed $origname $patchedname $sofile
fi
fi
done
}
echo 'Built this wheel:'
ls /tmp/$WHEELHOUSE_DIR
mkdir -p "/$WHEELHOUSE_DIR"
mv /tmp/$WHEELHOUSE_DIR/torch*linux*.whl /$WHEELHOUSE_DIR/
if [[ "$USE_SPLIT_BUILD" == "true" ]]; then
mv /tmp/$WHEELHOUSE_DIR/torch_no_python*.whl /$WHEELHOUSE_DIR/ || true
fi
if [[ -n "$BUILD_PYTHONLESS" ]]; then
mkdir -p /$LIBTORCH_HOUSE_DIR
mv /tmp/$LIBTORCH_HOUSE_DIR/*.zip /$LIBTORCH_HOUSE_DIR
rm -rf /tmp/$LIBTORCH_HOUSE_DIR
fi
rm -rf /tmp/$WHEELHOUSE_DIR
rm -rf /tmp_dir
mkdir /tmp_dir
pushd /tmp_dir
for pkg in /$WHEELHOUSE_DIR/torch_no_python*.whl /$WHEELHOUSE_DIR/torch*linux*.whl /$LIBTORCH_HOUSE_DIR/libtorch*.zip; do
# if the glob didn't match anything
if [[ ! -e $pkg ]]; then
continue
fi
rm -rf tmp
mkdir -p tmp
cd tmp
cp $pkg .
unzip -q $(basename $pkg)
rm -f $(basename $pkg)
if [[ -d torch ]]; then
PREFIX=torch
else
PREFIX=libtorch
fi
if [[ $pkg != *"without-deps"* ]]; then
# copy over needed dependent .so files over and tag them with their hash
patched=()
for filepath in "${DEPS_LIST[@]}"; do
filename=$(basename $filepath)
destpath=$PREFIX/lib/$filename
if [[ "$filepath" != "$destpath" ]]; then
cp $filepath $destpath
fi
# ROCm workaround for roctracer dlopens
if [[ "$DESIRED_CUDA" == *"rocm"* ]]; then
patchedpath=$(fname_without_so_number $destpath)
# Keep the so number for XPU dependencies
elif [[ "$DESIRED_CUDA" == *"xpu"* ]]; then
patchedpath=$destpath
else
patchedpath=$(fname_with_sha256 $destpath)
fi
patchedname=$(basename $patchedpath)
if [[ "$destpath" != "$patchedpath" ]]; then
mv $destpath $patchedpath
fi
patched+=("$patchedname")
echo "Copied $filepath to $patchedpath"
done
echo "patching to fix the so names to the hashed names"
for ((i=0;i<${#DEPS_LIST[@]};++i)); do
replace_needed_sofiles $PREFIX ${DEPS_SONAME[i]} ${patched[i]}
# do the same for caffe2, if it exists
if [[ -d caffe2 ]]; then
replace_needed_sofiles caffe2 ${DEPS_SONAME[i]} ${patched[i]}
fi
done
# copy over needed auxiliary files
for ((i=0;i<${#DEPS_AUX_SRCLIST[@]};++i)); do
srcpath=${DEPS_AUX_SRCLIST[i]}
dstpath=$PREFIX/${DEPS_AUX_DSTLIST[i]}
mkdir -p $(dirname $dstpath)
cp $srcpath $dstpath
done
fi
# set RPATH of _C.so and similar to $ORIGIN, $ORIGIN/lib
find $PREFIX -maxdepth 1 -type f -name "*.so*" | while read sofile; do
echo "Setting rpath of $sofile to ${C_SO_RPATH:-'$ORIGIN:$ORIGIN/lib'}"
$PATCHELF_BIN --set-rpath ${C_SO_RPATH:-'$ORIGIN:$ORIGIN/lib'} ${FORCE_RPATH:-} $sofile
$PATCHELF_BIN --print-rpath $sofile
done
# set RPATH of lib/ files to $ORIGIN
find $PREFIX/lib -maxdepth 1 -type f -name "*.so*" | while read sofile; do
echo "Setting rpath of $sofile to ${LIB_SO_RPATH:-'$ORIGIN'}"
$PATCHELF_BIN --set-rpath ${LIB_SO_RPATH:-'$ORIGIN'} ${FORCE_RPATH:-} $sofile
$PATCHELF_BIN --print-rpath $sofile
done
# regenerate the RECORD file with new hashes
record_file=$(echo $(basename $pkg) | sed -e 's/-cp.*$/.dist-info\/RECORD/g')
if [[ -e $record_file ]]; then
echo "Generating new record file $record_file"
: > "$record_file"
# generate records for folders in wheel
find * -type f | while read fname; do
make_wheel_record "$fname" >>"$record_file"
done
fi
if [[ $BUILD_DEBUG_INFO == "1" ]]; then
pushd "$PREFIX/lib"
# Duplicate library into debug lib
cp libtorch_cpu.so libtorch_cpu.so.dbg
# Keep debug symbols on debug lib
strip --only-keep-debug libtorch_cpu.so.dbg
# Remove debug info from release lib
strip --strip-debug libtorch_cpu.so
objcopy libtorch_cpu.so --add-gnu-debuglink=libtorch_cpu.so.dbg
# Zip up debug info
mkdir -p /tmp/debug
mv libtorch_cpu.so.dbg /tmp/debug/libtorch_cpu.so.dbg
CRC32=$(objcopy --dump-section .gnu_debuglink=>(tail -c4 | od -t x4 -An | xargs echo) libtorch_cpu.so)
pushd /tmp
PKG_NAME=$(basename "$pkg" | sed 's/\.whl$//g')
zip /tmp/debug-whl-libtorch-"$PKG_NAME"-"$CRC32".zip /tmp/debug/libtorch_cpu.so.dbg
cp /tmp/debug-whl-libtorch-"$PKG_NAME"-"$CRC32".zip "$PYTORCH_FINAL_PACKAGE_DIR"
popd
popd
fi
# zip up the wheel back
zip -rq $(basename $pkg) $PREIX*
# replace original wheel
rm -f $pkg
mv $(basename $pkg) $pkg
cd ..
rm -rf tmp
done
# Copy wheels to host machine for persistence before testing
if [[ -n "$PYTORCH_FINAL_PACKAGE_DIR" ]]; then
mkdir -p "$PYTORCH_FINAL_PACKAGE_DIR" || true
if [[ -n "$BUILD_PYTHONLESS" ]]; then
cp /$LIBTORCH_HOUSE_DIR/libtorch*.zip "$PYTORCH_FINAL_PACKAGE_DIR"
else
cp /$WHEELHOUSE_DIR/torch*.whl "$PYTORCH_FINAL_PACKAGE_DIR"
fi
fi
# remove stuff before testing
rm -rf /opt/rh
if ls /usr/local/cuda* >/dev/null 2>&1; then
rm -rf /usr/local/cuda*
fi
# Test that all the wheels work
if [[ -z "$BUILD_PYTHONLESS" ]]; then
export OMP_NUM_THREADS=4 # on NUMA machines this takes too long
pushd $PYTORCH_ROOT/test
# Install the wheel for this Python version
if [[ "$USE_SPLIT_BUILD" == "true" ]]; then
pip uninstall -y "$TORCH_NO_PYTHON_PACKAGE_NAME" || true
fi
pip uninstall -y "$TORCH_PACKAGE_NAME"
if [[ "$USE_SPLIT_BUILD" == "true" ]]; then
pip install "$TORCH_NO_PYTHON_PACKAGE_NAME" --no-index -f /$WHEELHOUSE_DIR --no-dependencies -v
fi
pip install "$TORCH_PACKAGE_NAME" --no-index -f /$WHEELHOUSE_DIR --no-dependencies -v
# Print info on the libraries installed in this wheel
# Rather than adjust find command to skip non-library files with an embedded *.so* in their name,
# since this is only for reporting purposes, we add the || true to the ldd command.
installed_libraries=($(find "$pydir/lib/python${py_majmin}/site-packages/torch/" -name '*.so*'))
echo "The wheel installed all of the libraries: ${installed_libraries[@]}"
for installed_lib in "${installed_libraries[@]}"; do
ldd "$installed_lib" || true
done
# Run the tests
echo "$(date) :: Running tests"
pushd "$PYTORCH_ROOT"
#TODO: run_tests.sh and check_binary.sh should be moved to pytorch/pytorch project
LD_LIBRARY_PATH=/usr/local/nvidia/lib64 \
"/builder/run_tests.sh" manywheel "${py_majmin}" "$DESIRED_CUDA"
popd
echo "$(date) :: Finished tests"
fi

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@ -1,99 +0,0 @@
#!/usr/bin/env bash
set -ex
GPU_ARCH_TYPE=${GPU_ARCH_TYPE:-cpu}
export TH_BINARY_BUILD=1
export USE_CUDA=0
# Keep an array of cmake variables to add to
if [[ -z "$CMAKE_ARGS" ]]; then
# These are passed to tools/build_pytorch_libs.sh::build()
CMAKE_ARGS=()
fi
if [[ -z "$EXTRA_CAFFE2_CMAKE_FLAGS" ]]; then
# These are passed to tools/build_pytorch_libs.sh::build_caffe2()
EXTRA_CAFFE2_CMAKE_FLAGS=()
fi
DIR_SUFFIX=cpu
if [[ "$GPU_ARCH_TYPE" == "xpu" ]]; then
DIR_SUFFIX=xpu
# Refer https://www.intel.com/content/www/us/en/developer/articles/tool/pytorch-prerequisites-for-intel-gpu/2-5.html
source /opt/intel/oneapi/pytorch-gpu-dev-0.5/oneapi-vars.sh
source /opt/intel/oneapi/pti/latest/env/vars.sh
export USE_STATIC_MKL=1
fi
WHEELHOUSE_DIR="wheelhouse$DIR_SUFFIX"
LIBTORCH_HOUSE_DIR="libtorch_house$DIR_SUFFIX"
if [[ -z "$PYTORCH_FINAL_PACKAGE_DIR" ]]; then
if [[ -z "$BUILD_PYTHONLESS" ]]; then
PYTORCH_FINAL_PACKAGE_DIR="/remote/wheelhouse$DIR_SUFFIX"
else
PYTORCH_FINAL_PACKAGE_DIR="/remote/libtorch_house$DIR_SUFFIX"
fi
fi
mkdir -p "$PYTORCH_FINAL_PACKAGE_DIR" || true
OS_NAME=$(awk -F= '/^NAME/{print $2}' /etc/os-release)
if [[ "$OS_NAME" == *"CentOS Linux"* ]]; then
LIBGOMP_PATH="/usr/lib64/libgomp.so.1"
elif [[ "$OS_NAME" == *"Red Hat Enterprise Linux"* ]]; then
LIBGOMP_PATH="/usr/lib64/libgomp.so.1"
elif [[ "$OS_NAME" == *"AlmaLinux"* ]]; then
LIBGOMP_PATH="/usr/lib64/libgomp.so.1"
elif [[ "$OS_NAME" == *"Ubuntu"* ]]; then
if [[ "$(uname -m)" == "s390x" ]]; then
LIBGOMP_PATH="/usr/lib/s390x-linux-gnu/libgomp.so.1"
else
LIBGOMP_PATH="/usr/lib/x86_64-linux-gnu/libgomp.so.1"
fi
fi
DEPS_LIST=(
"$LIBGOMP_PATH"
)
DEPS_SONAME=(
"libgomp.so.1"
)
if [[ "$GPU_ARCH_TYPE" == "xpu" ]]; then
echo "Bundling with xpu support package libs."
DEPS_LIST+=(
"/opt/intel/oneapi/compiler/latest/lib/libsycl-preview.so.7"
"/opt/intel/oneapi/compiler/latest/lib/libOpenCL.so.1"
"/opt/intel/oneapi/compiler/latest/lib/libxptifw.so"
"/opt/intel/oneapi/compiler/latest/lib/libsvml.so"
"/opt/intel/oneapi/compiler/latest/lib/libirng.so"
"/opt/intel/oneapi/compiler/latest/lib/libimf.so"
"/opt/intel/oneapi/compiler/latest/lib/libintlc.so.5"
"/opt/intel/oneapi/compiler/latest/lib/libpi_level_zero.so"
"/opt/intel/oneapi/pti/latest/lib/libpti_view.so.0.9"
"/opt/intel/oneapi/pti/latest/lib/libpti.so.0.9"
)
DEPS_SONAME+=(
"libsycl-preview.so.7"
"libOpenCL.so.1"
"libxptifw.so"
"libsvml.so"
"libirng.so"
"libimf.so"
"libintlc.so.5"
"libpi_level_zero.so"
"libpti_view.so.0.9"
"libpti.so.0.9"
)
fi
rm -rf /usr/local/cuda*
SOURCE_DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" >/dev/null && pwd )"
if [[ -z "$BUILD_PYTHONLESS" ]]; then
BUILD_SCRIPT=build_common.sh
else
BUILD_SCRIPT=build_libtorch.sh
fi
source ${SOURCE_DIR}/${BUILD_SCRIPT}

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@ -1,290 +0,0 @@
#!/usr/bin/env bash
set -ex
SCRIPTPATH="$( cd "$(dirname "$0")" ; pwd -P ))"
export TORCH_NVCC_FLAGS="-Xfatbin -compress-all"
export NCCL_ROOT_DIR=/usr/local/cuda
export TH_BINARY_BUILD=1
export USE_STATIC_CUDNN=1
export USE_STATIC_NCCL=1
export ATEN_STATIC_CUDA=1
export USE_CUDA_STATIC_LINK=1
export INSTALL_TEST=0 # dont install test binaries into site-packages
export USE_CUPTI_SO=0
export USE_CUSPARSELT=${USE_CUSPARSELT:-1} # Enable if not disabled by libtorch build
# Keep an array of cmake variables to add to
if [[ -z "$CMAKE_ARGS" ]]; then
# These are passed to tools/build_pytorch_libs.sh::build()
CMAKE_ARGS=()
fi
if [[ -z "$EXTRA_CAFFE2_CMAKE_FLAGS" ]]; then
# These are passed to tools/build_pytorch_libs.sh::build_caffe2()
EXTRA_CAFFE2_CMAKE_FLAGS=()
fi
# Determine CUDA version and architectures to build for
#
# NOTE: We should first check `DESIRED_CUDA` when determining `CUDA_VERSION`,
# because in some cases a single Docker image can have multiple CUDA versions
# on it, and `nvcc --version` might not show the CUDA version we want.
if [[ -n "$DESIRED_CUDA" ]]; then
# If the DESIRED_CUDA already matches the format that we expect
if [[ ${DESIRED_CUDA} =~ ^[0-9]+\.[0-9]+$ ]]; then
CUDA_VERSION=${DESIRED_CUDA}
else
# cu90, cu92, cu100, cu101
if [[ ${#DESIRED_CUDA} -eq 4 ]]; then
CUDA_VERSION="${DESIRED_CUDA:2:1}.${DESIRED_CUDA:3:1}"
elif [[ ${#DESIRED_CUDA} -eq 5 ]]; then
CUDA_VERSION="${DESIRED_CUDA:2:2}.${DESIRED_CUDA:4:1}"
fi
fi
echo "Using CUDA $CUDA_VERSION as determined by DESIRED_CUDA"
# There really has to be a better way to do this - eli
# Possibly limiting builds to specific cuda versions be delimiting images would be a choice
if [[ "$OS_NAME" == *"Ubuntu"* ]]; then
echo "Switching to CUDA version ${DESIRED_CUDA}"
/builder/conda/switch_cuda_version.sh "${DESIRED_CUDA}"
fi
else
CUDA_VERSION=$(nvcc --version|grep release|cut -f5 -d" "|cut -f1 -d",")
echo "CUDA $CUDA_VERSION Detected"
fi
cuda_version_nodot=$(echo $CUDA_VERSION | tr -d '.')
TORCH_CUDA_ARCH_LIST="5.0;6.0;7.0;7.5;8.0;8.6"
case ${CUDA_VERSION} in
12.4)
if [[ "$GPU_ARCH_TYPE" = "cuda-aarch64" ]]; then
TORCH_CUDA_ARCH_LIST="9.0"
else
TORCH_CUDA_ARCH_LIST="${TORCH_CUDA_ARCH_LIST};9.0+PTX"
fi
EXTRA_CAFFE2_CMAKE_FLAGS+=("-DATEN_NO_TEST=ON")
;;
12.1)
TORCH_CUDA_ARCH_LIST="${TORCH_CUDA_ARCH_LIST};9.0"
EXTRA_CAFFE2_CMAKE_FLAGS+=("-DATEN_NO_TEST=ON")
;;
11.8)
TORCH_CUDA_ARCH_LIST="${TORCH_CUDA_ARCH_LIST};3.7;9.0"
EXTRA_CAFFE2_CMAKE_FLAGS+=("-DATEN_NO_TEST=ON")
;;
11.[67])
TORCH_CUDA_ARCH_LIST="${TORCH_CUDA_ARCH_LIST};3.7"
EXTRA_CAFFE2_CMAKE_FLAGS+=("-DATEN_NO_TEST=ON")
;;
*)
echo "unknown cuda version $CUDA_VERSION"
exit 1
;;
esac
export TORCH_CUDA_ARCH_LIST=${TORCH_CUDA_ARCH_LIST}
echo "${TORCH_CUDA_ARCH_LIST}"
# Package directories
WHEELHOUSE_DIR="wheelhouse$cuda_version_nodot"
LIBTORCH_HOUSE_DIR="libtorch_house$cuda_version_nodot"
if [[ -z "$PYTORCH_FINAL_PACKAGE_DIR" ]]; then
if [[ -z "$BUILD_PYTHONLESS" ]]; then
PYTORCH_FINAL_PACKAGE_DIR="/remote/wheelhouse$cuda_version_nodot"
else
PYTORCH_FINAL_PACKAGE_DIR="/remote/libtorch_house$cuda_version_nodot"
fi
fi
mkdir -p "$PYTORCH_FINAL_PACKAGE_DIR" || true
OS_NAME=$(awk -F= '/^NAME/{print $2}' /etc/os-release)
if [[ "$OS_NAME" == *"CentOS Linux"* ]]; then
LIBGOMP_PATH="/usr/lib64/libgomp.so.1"
elif [[ "$OS_NAME" == *"AlmaLinux"* ]]; then
LIBGOMP_PATH="/usr/lib64/libgomp.so.1"
elif [[ "$OS_NAME" == *"Red Hat Enterprise Linux"* ]]; then
LIBGOMP_PATH="/usr/lib64/libgomp.so.1"
elif [[ "$OS_NAME" == *"Ubuntu"* ]]; then
LIBGOMP_PATH="/usr/lib/x86_64-linux-gnu/libgomp.so.1"
fi
DEPS_LIST=(
"$LIBGOMP_PATH"
)
DEPS_SONAME=(
"libgomp.so.1"
)
if [[ $USE_CUSPARSELT == "1" ]]; then
DEPS_SONAME+=(
"libcusparseLt.so.0"
)
DEPS_LIST+=(
"/usr/local/cuda/lib64/libcusparseLt.so.0"
)
fi
if [[ $CUDA_VERSION == "12.1" || $CUDA_VERSION == "12.4" ]]; then
export USE_STATIC_CUDNN=0
# Try parallelizing nvcc as well
export TORCH_NVCC_FLAGS="-Xfatbin -compress-all --threads 2"
if [[ -z "$PYTORCH_EXTRA_INSTALL_REQUIREMENTS" ]]; then
echo "Bundling with cudnn and cublas."
DEPS_LIST+=(
"/usr/local/cuda/lib64/libcudnn_adv.so.9"
"/usr/local/cuda/lib64/libcudnn_cnn.so.9"
"/usr/local/cuda/lib64/libcudnn_graph.so.9"
"/usr/local/cuda/lib64/libcudnn_ops.so.9"
"/usr/local/cuda/lib64/libcudnn_engines_runtime_compiled.so.9"
"/usr/local/cuda/lib64/libcudnn_engines_precompiled.so.9"
"/usr/local/cuda/lib64/libcudnn_heuristic.so.9"
"/usr/local/cuda/lib64/libcudnn.so.9"
"/usr/local/cuda/lib64/libcublas.so.12"
"/usr/local/cuda/lib64/libcublasLt.so.12"
"/usr/local/cuda/lib64/libcudart.so.12"
"/usr/local/cuda/lib64/libnvToolsExt.so.1"
"/usr/local/cuda/lib64/libnvrtc.so.12"
"/usr/local/cuda/lib64/libnvrtc-builtins.so"
)
DEPS_SONAME+=(
"libcudnn_adv.so.9"
"libcudnn_cnn.so.9"
"libcudnn_graph.so.9"
"libcudnn_ops.so.9"
"libcudnn_engines_runtime_compiled.so.9"
"libcudnn_engines_precompiled.so.9"
"libcudnn_heuristic.so.9"
"libcudnn.so.9"
"libcublas.so.12"
"libcublasLt.so.12"
"libcudart.so.12"
"libnvToolsExt.so.1"
"libnvrtc.so.12"
"libnvrtc-builtins.so"
)
else
echo "Using nvidia libs from pypi."
CUDA_RPATHS=(
'$ORIGIN/../../nvidia/cublas/lib'
'$ORIGIN/../../nvidia/cuda_cupti/lib'
'$ORIGIN/../../nvidia/cuda_nvrtc/lib'
'$ORIGIN/../../nvidia/cuda_runtime/lib'
'$ORIGIN/../../nvidia/cudnn/lib'
'$ORIGIN/../../nvidia/cufft/lib'
'$ORIGIN/../../nvidia/curand/lib'
'$ORIGIN/../../nvidia/cusolver/lib'
'$ORIGIN/../../nvidia/cusparse/lib'
'$ORIGIN/../../nvidia/nccl/lib'
'$ORIGIN/../../nvidia/nvtx/lib'
)
CUDA_RPATHS=$(IFS=: ; echo "${CUDA_RPATHS[*]}")
export C_SO_RPATH=$CUDA_RPATHS':$ORIGIN:$ORIGIN/lib'
export LIB_SO_RPATH=$CUDA_RPATHS':$ORIGIN'
export FORCE_RPATH="--force-rpath"
export USE_STATIC_NCCL=0
export USE_SYSTEM_NCCL=1
export ATEN_STATIC_CUDA=0
export USE_CUDA_STATIC_LINK=0
export USE_CUPTI_SO=1
export NCCL_INCLUDE_DIR="/usr/local/cuda/include/"
export NCCL_LIB_DIR="/usr/local/cuda/lib64/"
fi
elif [[ $CUDA_VERSION == "11.8" ]]; then
export USE_STATIC_CUDNN=0
# Try parallelizing nvcc as well
export TORCH_NVCC_FLAGS="-Xfatbin -compress-all --threads 2"
# Bundle ptxas into the wheel, see https://github.com/pytorch/pytorch/pull/119750
export BUILD_BUNDLE_PTXAS=1
if [[ -z "$PYTORCH_EXTRA_INSTALL_REQUIREMENTS" ]]; then
echo "Bundling with cudnn and cublas."
DEPS_LIST+=(
"/usr/local/cuda/lib64/libcudnn_adv.so.9"
"/usr/local/cuda/lib64/libcudnn_cnn.so.9"
"/usr/local/cuda/lib64/libcudnn_graph.so.9"
"/usr/local/cuda/lib64/libcudnn_ops.so.9"
"/usr/local/cuda/lib64/libcudnn_engines_runtime_compiled.so.9"
"/usr/local/cuda/lib64/libcudnn_engines_precompiled.so.9"
"/usr/local/cuda/lib64/libcudnn_heuristic.so.9"
"/usr/local/cuda/lib64/libcudnn.so.9"
"/usr/local/cuda/lib64/libcublas.so.11"
"/usr/local/cuda/lib64/libcublasLt.so.11"
"/usr/local/cuda/lib64/libcudart.so.11.0"
"/usr/local/cuda/lib64/libnvToolsExt.so.1"
"/usr/local/cuda/lib64/libnvrtc.so.11.2" # this is not a mistake, it links to more specific cuda version
"/usr/local/cuda/lib64/libnvrtc-builtins.so.11.8"
)
DEPS_SONAME+=(
"libcudnn_adv.so.9"
"libcudnn_cnn.so.9"
"libcudnn_graph.so.9"
"libcudnn_ops.so.9"
"libcudnn_engines_runtime_compiled.so.9"
"libcudnn_engines_precompiled.so.9"
"libcudnn_heuristic.so.9"
"libcudnn.so.9"
"libcublas.so.11"
"libcublasLt.so.11"
"libcudart.so.11.0"
"libnvToolsExt.so.1"
"libnvrtc.so.11.2"
"libnvrtc-builtins.so.11.8"
)
else
echo "Using nvidia libs from pypi."
CUDA_RPATHS=(
'$ORIGIN/../../nvidia/cublas/lib'
'$ORIGIN/../../nvidia/cuda_cupti/lib'
'$ORIGIN/../../nvidia/cuda_nvrtc/lib'
'$ORIGIN/../../nvidia/cuda_runtime/lib'
'$ORIGIN/../../nvidia/cudnn/lib'
'$ORIGIN/../../nvidia/cufft/lib'
'$ORIGIN/../../nvidia/curand/lib'
'$ORIGIN/../../nvidia/cusolver/lib'
'$ORIGIN/../../nvidia/cusparse/lib'
'$ORIGIN/../../nvidia/nccl/lib'
'$ORIGIN/../../nvidia/nvtx/lib'
)
CUDA_RPATHS=$(IFS=: ; echo "${CUDA_RPATHS[*]}")
export C_SO_RPATH=$CUDA_RPATHS':$ORIGIN:$ORIGIN/lib'
export LIB_SO_RPATH=$CUDA_RPATHS':$ORIGIN'
export FORCE_RPATH="--force-rpath"
export USE_STATIC_NCCL=0
export USE_SYSTEM_NCCL=1
export ATEN_STATIC_CUDA=0
export USE_CUDA_STATIC_LINK=0
export USE_CUPTI_SO=1
export NCCL_INCLUDE_DIR="/usr/local/cuda/include/"
export NCCL_LIB_DIR="/usr/local/cuda/lib64/"
fi
else
echo "Unknown cuda version $CUDA_VERSION"
exit 1
fi
# builder/test.sh requires DESIRED_CUDA to know what tests to exclude
export DESIRED_CUDA="$cuda_version_nodot"
# Switch `/usr/local/cuda` to the desired CUDA version
rm -rf /usr/local/cuda || true
ln -s "/usr/local/cuda-${CUDA_VERSION}" /usr/local/cuda
# Switch `/usr/local/magma` to the desired CUDA version
rm -rf /usr/local/magma || true
ln -s /usr/local/cuda-${CUDA_VERSION}/magma /usr/local/magma
export CUDA_VERSION=$(ls /usr/local/cuda/lib64/libcudart.so.*|sort|tac | head -1 | rev | cut -d"." -f -3 | rev) # 10.0.130
export CUDA_VERSION_SHORT=$(ls /usr/local/cuda/lib64/libcudart.so.*|sort|tac | head -1 | rev | cut -d"." -f -3 | rev | cut -f1,2 -d".") # 10.0
export CUDNN_VERSION=$(ls /usr/local/cuda/lib64/libcudnn.so.*|sort|tac | head -1 | rev | cut -d"." -f -3 | rev)
SCRIPTPATH="$( cd "$(dirname "$0")" ; pwd -P )"
if [[ -z "$BUILD_PYTHONLESS" ]]; then
BUILD_SCRIPT=build_common.sh
else
BUILD_SCRIPT=build_libtorch.sh
fi
source $SCRIPTPATH/${BUILD_SCRIPT}

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@ -1,353 +0,0 @@
#!/usr/bin/env bash
# meant to be called only from the neighboring build.sh and build_cpu.sh scripts
set -e pipefail
SOURCE_DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" >/dev/null && pwd )"
# Require only one python installation
if [[ -z "$DESIRED_PYTHON" ]]; then
echo "Need to set DESIRED_PYTHON env variable"
exit 1
fi
if [[ -n "$BUILD_PYTHONLESS" && -z "$LIBTORCH_VARIANT" ]]; then
echo "BUILD_PYTHONLESS is set, so need LIBTORCH_VARIANT to also be set"
echo "LIBTORCH_VARIANT should be one of shared-with-deps shared-without-deps static-with-deps static-without-deps"
exit 1
fi
# Function to retry functions that sometimes timeout or have flaky failures
retry () {
$* || (sleep 1 && $*) || (sleep 2 && $*) || (sleep 4 && $*) || (sleep 8 && $*)
}
# TODO move this into the Docker images
OS_NAME=`awk -F= '/^NAME/{print $2}' /etc/os-release`
if [[ "$OS_NAME" == *"CentOS Linux"* ]]; then
retry yum install -q -y zip openssl
elif [[ "$OS_NAME" == *"AlmaLinux"* ]]; then
retry yum install -q -y zip openssl
elif [[ "$OS_NAME" == *"Red Hat Enterprise Linux"* ]]; then
retry dnf install -q -y zip openssl
elif [[ "$OS_NAME" == *"Ubuntu"* ]]; then
# TODO: Remove this once nvidia package repos are back online
# Comment out nvidia repositories to prevent them from getting apt-get updated, see https://github.com/pytorch/pytorch/issues/74968
# shellcheck disable=SC2046
sed -i 's/.*nvidia.*/# &/' $(find /etc/apt/ -type f -name "*.list")
retry apt-get update
retry apt-get -y install zip openssl
fi
# Version: setup.py uses $PYTORCH_BUILD_VERSION.post$PYTORCH_BUILD_NUMBER if
# PYTORCH_BUILD_NUMBER > 1
build_version="$PYTORCH_BUILD_VERSION"
build_number="$PYTORCH_BUILD_NUMBER"
if [[ -n "$OVERRIDE_PACKAGE_VERSION" ]]; then
# This will be the *exact* version, since build_number<1
build_version="$OVERRIDE_PACKAGE_VERSION"
build_number=0
fi
if [[ -z "$build_version" ]]; then
build_version=1.0.0
fi
if [[ -z "$build_number" ]]; then
build_number=1
fi
export PYTORCH_BUILD_VERSION=$build_version
export PYTORCH_BUILD_NUMBER=$build_number
export CMAKE_LIBRARY_PATH="/opt/intel/lib:/lib:$CMAKE_LIBRARY_PATH"
export CMAKE_INCLUDE_PATH="/opt/intel/include:$CMAKE_INCLUDE_PATH"
# set OPENSSL_ROOT_DIR=/opt/openssl if it exists
if [[ -e /opt/openssl ]]; then
export OPENSSL_ROOT_DIR=/opt/openssl
export CMAKE_INCLUDE_PATH="/opt/openssl/include":$CMAKE_INCLUDE_PATH
fi
# If given a python version like 3.6m or 2.7mu, convert this to the format we
# expect. The binary CI jobs pass in python versions like this; they also only
# ever pass one python version, so we assume that DESIRED_PYTHON is not a list
# in this case
if [[ -n "$DESIRED_PYTHON" && "$DESIRED_PYTHON" != cp* ]]; then
python_nodot="$(echo $DESIRED_PYTHON | tr -d m.u)"
DESIRED_PYTHON="cp${python_nodot}-cp${python_nodot}"
fi
pydir="/opt/python/$DESIRED_PYTHON"
export PATH="$pydir/bin:$PATH"
export PATCHELF_BIN=/usr/local/bin/patchelf
patchelf_version=`$PATCHELF_BIN --version`
echo "patchelf version: " $patchelf_version
if [[ "$patchelf_version" == "patchelf 0.9" ]]; then
echo "Your patchelf version is too old. Please use version >= 0.10."
exit 1
fi
########################################################
# Compile wheels as well as libtorch
#######################################################
if [[ -z "$PYTORCH_ROOT" ]]; then
echo "Need to set PYTORCH_ROOT env variable"
exit 1
fi
pushd "$PYTORCH_ROOT"
python setup.py clean
retry pip install -qr requirements.txt
retry pip install -q numpy==2.0.1
if [[ "$DESIRED_DEVTOOLSET" == *"cxx11-abi"* ]]; then
export _GLIBCXX_USE_CXX11_ABI=1
else
export _GLIBCXX_USE_CXX11_ABI=0
fi
if [[ "$DESIRED_CUDA" == *"rocm"* ]]; then
echo "Calling build_amd.py at $(date)"
python tools/amd_build/build_amd.py
# TODO remove this work-around once pytorch sources are updated
export ROCclr_DIR=/opt/rocm/rocclr/lib/cmake/rocclr
fi
echo "Calling setup.py install at $(date)"
if [[ $LIBTORCH_VARIANT = *"static"* ]]; then
STATIC_CMAKE_FLAG="-DTORCH_STATIC=1"
fi
(
set -x
mkdir -p build
time CMAKE_ARGS=${CMAKE_ARGS[@]} \
EXTRA_CAFFE2_CMAKE_FLAGS="${EXTRA_CAFFE2_CMAKE_FLAGS[@]} $STATIC_CMAKE_FLAG" \
# TODO: Remove this flag once https://github.com/pytorch/pytorch/issues/55952 is closed
CFLAGS='-Wno-deprecated-declarations' \
BUILD_LIBTORCH_CPU_WITH_DEBUG=1 \
python setup.py install
mkdir -p libtorch/{lib,bin,include,share}
# Make debug folder separate so it doesn't get zipped up with the rest of
# libtorch
mkdir debug
# Copy over all lib files
cp -rv build/lib/* libtorch/lib/
cp -rv build/lib*/torch/lib/* libtorch/lib/
# Copy over all include files
cp -rv build/include/* libtorch/include/
cp -rv build/lib*/torch/include/* libtorch/include/
# Copy over all of the cmake files
cp -rv build/lib*/torch/share/* libtorch/share/
# Split libtorch into debug / release version
cp libtorch/lib/libtorch_cpu.so libtorch/lib/libtorch_cpu.so.dbg
# Keep debug symbols on debug lib
strip --only-keep-debug libtorch/lib/libtorch_cpu.so.dbg
# Remove debug info from release lib
strip --strip-debug libtorch/lib/libtorch_cpu.so
# Add a debug link to the release lib to the debug lib (debuggers will then
# search for symbols in a file called libtorch_cpu.so.dbg in some
# predetermined locations) and embed a CRC32 of the debug library into the .so
cd libtorch/lib
objcopy libtorch_cpu.so --add-gnu-debuglink=libtorch_cpu.so.dbg
cd ../..
# Move the debug symbols to its own directory so it doesn't get processed /
# zipped with all the other libraries
mv libtorch/lib/libtorch_cpu.so.dbg debug/libtorch_cpu.so.dbg
echo "${PYTORCH_BUILD_VERSION}" > libtorch/build-version
echo "$(pushd $PYTORCH_ROOT && git rev-parse HEAD)" > libtorch/build-hash
)
if [[ "$DESIRED_DEVTOOLSET" == *"cxx11-abi"* ]]; then
LIBTORCH_ABI="cxx11-abi-"
else
LIBTORCH_ABI=
fi
(
set -x
mkdir -p /tmp/$LIBTORCH_HOUSE_DIR
# objcopy installs a CRC32 into libtorch_cpu above so, so add that to the name here
CRC32=$(objcopy --dump-section .gnu_debuglink=>(tail -c4 | od -t x4 -An | xargs echo) libtorch/lib/libtorch_cpu.so)
# Zip debug symbols
zip /tmp/$LIBTORCH_HOUSE_DIR/debug-libtorch-$LIBTORCH_ABI$LIBTORCH_VARIANT-$PYTORCH_BUILD_VERSION-$CRC32.zip debug/libtorch_cpu.so.dbg
# Zip and copy libtorch
zip -rq /tmp/$LIBTORCH_HOUSE_DIR/libtorch-$LIBTORCH_ABI$LIBTORCH_VARIANT-$PYTORCH_BUILD_VERSION.zip libtorch
cp /tmp/$LIBTORCH_HOUSE_DIR/libtorch-$LIBTORCH_ABI$LIBTORCH_VARIANT-$PYTORCH_BUILD_VERSION.zip \
/tmp/$LIBTORCH_HOUSE_DIR/libtorch-$LIBTORCH_ABI$LIBTORCH_VARIANT-latest.zip
)
popd
#######################################################################
# ADD DEPENDENCIES INTO THE WHEEL
#
# auditwheel repair doesn't work correctly and is buggy
# so manually do the work of copying dependency libs and patchelfing
# and fixing RECORDS entries correctly
######################################################################
fname_with_sha256() {
HASH=$(sha256sum $1 | cut -c1-8)
DIRNAME=$(dirname $1)
BASENAME=$(basename $1)
if [[ $BASENAME == "libnvrtc-builtins.so" || $BASENAME == "libcudnn"* ]]; then
echo $1
else
INITNAME=$(echo $BASENAME | cut -f1 -d".")
ENDNAME=$(echo $BASENAME | cut -f 2- -d".")
echo "$DIRNAME/$INITNAME-$HASH.$ENDNAME"
fi
}
fname_without_so_number() {
LINKNAME=$(echo $1 | sed -e 's/\.so.*/.so/g')
echo "$LINKNAME"
}
make_wheel_record() {
FPATH=$1
if echo $FPATH | grep RECORD >/dev/null 2>&1; then
# if the RECORD file, then
echo "$FPATH,,"
else
HASH=$(openssl dgst -sha256 -binary $FPATH | openssl base64 | sed -e 's/+/-/g' | sed -e 's/\//_/g' | sed -e 's/=//g')
FSIZE=$(ls -nl $FPATH | awk '{print $5}')
echo "$FPATH,sha256=$HASH,$FSIZE"
fi
}
echo 'Built this package:'
(
set -x
mkdir -p /$LIBTORCH_HOUSE_DIR
mv /tmp/$LIBTORCH_HOUSE_DIR/*.zip /$LIBTORCH_HOUSE_DIR
rm -rf /tmp/$LIBTORCH_HOUSE_DIR
)
TMP_DIR=$(mktemp -d)
trap "rm -rf ${TMP_DIR}" EXIT
pushd "${TMP_DIR}"
for pkg in /$LIBTORCH_HOUSE_DIR/libtorch*.zip; do
# if the glob didn't match anything
if [[ ! -e $pkg ]]; then
continue
fi
rm -rf tmp
mkdir -p tmp
cd tmp
cp $pkg .
unzip -q $(basename $pkg)
rm -f $(basename $pkg)
PREFIX=libtorch
if [[ $pkg != *"without-deps"* ]]; then
# copy over needed dependent .so files over and tag them with their hash
patched=()
for filepath in "${DEPS_LIST[@]}"; do
filename=$(basename $filepath)
destpath=$PREFIX/lib/$filename
if [[ "$filepath" != "$destpath" ]]; then
cp $filepath $destpath
fi
if [[ "$DESIRED_CUDA" == *"rocm"* ]]; then
patchedpath=$(fname_without_so_number $destpath)
else
patchedpath=$(fname_with_sha256 $destpath)
fi
patchedname=$(basename $patchedpath)
if [[ "$destpath" != "$patchedpath" ]]; then
mv $destpath $patchedpath
fi
patched+=("$patchedname")
echo "Copied $filepath to $patchedpath"
done
echo "patching to fix the so names to the hashed names"
for ((i=0;i<${#DEPS_LIST[@]};++i)); do
find $PREFIX -name '*.so*' | while read sofile; do
origname=${DEPS_SONAME[i]}
patchedname=${patched[i]}
if [[ "$origname" != "$patchedname" ]] || [[ "$DESIRED_CUDA" == *"rocm"* ]]; then
set +e
origname=$($PATCHELF_BIN --print-needed $sofile | grep "$origname.*")
ERRCODE=$?
set -e
if [ "$ERRCODE" -eq "0" ]; then
echo "patching $sofile entry $origname to $patchedname"
$PATCHELF_BIN --replace-needed $origname $patchedname $sofile
fi
fi
done
done
# copy over needed auxiliary files
for ((i=0;i<${#DEPS_AUX_SRCLIST[@]};++i)); do
srcpath=${DEPS_AUX_SRCLIST[i]}
dstpath=$PREFIX/${DEPS_AUX_DSTLIST[i]}
mkdir -p $(dirname $dstpath)
cp $srcpath $dstpath
done
fi
# set RPATH of _C.so and similar to $ORIGIN, $ORIGIN/lib
find $PREFIX -maxdepth 1 -type f -name "*.so*" | while read sofile; do
echo "Setting rpath of $sofile to " '$ORIGIN:$ORIGIN/lib'
$PATCHELF_BIN --set-rpath '$ORIGIN:$ORIGIN/lib' $sofile
$PATCHELF_BIN --print-rpath $sofile
done
# set RPATH of lib/ files to $ORIGIN
find $PREFIX/lib -maxdepth 1 -type f -name "*.so*" | while read sofile; do
echo "Setting rpath of $sofile to " '$ORIGIN'
$PATCHELF_BIN --set-rpath '$ORIGIN' $sofile
$PATCHELF_BIN --print-rpath $sofile
done
# regenerate the RECORD file with new hashes
record_file=`echo $(basename $pkg) | sed -e 's/-cp.*$/.dist-info\/RECORD/g'`
if [[ -e $record_file ]]; then
echo "Generating new record file $record_file"
rm -f $record_file
# generate records for folders in wheel
find * -type f | while read fname; do
echo $(make_wheel_record $fname) >>$record_file
done
fi
# zip up the wheel back
zip -rq $(basename $pkg) $PREFIX*
# replace original wheel
rm -f $pkg
mv $(basename $pkg) $pkg
cd ..
rm -rf tmp
done
# Copy wheels to host machine for persistence before testing
if [[ -n "$PYTORCH_FINAL_PACKAGE_DIR" ]]; then
cp /$LIBTORCH_HOUSE_DIR/libtorch*.zip "$PYTORCH_FINAL_PACKAGE_DIR"
cp /$LIBTORCH_HOUSE_DIR/debug-libtorch*.zip "$PYTORCH_FINAL_PACKAGE_DIR"
fi

View File

@ -1,263 +0,0 @@
#!/usr/bin/env bash
set -ex
export ROCM_HOME=/opt/rocm
export MAGMA_HOME=$ROCM_HOME/magma
# TODO: libtorch_cpu.so is broken when building with Debug info
export BUILD_DEBUG_INFO=0
# TODO Are these all used/needed?
export TH_BINARY_BUILD=1
export USE_STATIC_CUDNN=1
export USE_STATIC_NCCL=1
export ATEN_STATIC_CUDA=1
export USE_CUDA_STATIC_LINK=1
export INSTALL_TEST=0 # dont install test binaries into site-packages
# Set RPATH instead of RUNPATH when using patchelf to avoid LD_LIBRARY_PATH override
export FORCE_RPATH="--force-rpath"
# Keep an array of cmake variables to add to
if [[ -z "$CMAKE_ARGS" ]]; then
# These are passed to tools/build_pytorch_libs.sh::build()
CMAKE_ARGS=()
fi
if [[ -z "$EXTRA_CAFFE2_CMAKE_FLAGS" ]]; then
# These are passed to tools/build_pytorch_libs.sh::build_caffe2()
EXTRA_CAFFE2_CMAKE_FLAGS=()
fi
# Determine ROCm version and architectures to build for
#
# NOTE: We should first check `DESIRED_CUDA` when determining `ROCM_VERSION`
if [[ -n "$DESIRED_CUDA" ]]; then
if ! echo "${DESIRED_CUDA}"| grep "^rocm" >/dev/null 2>/dev/null; then
export DESIRED_CUDA="rocm${DESIRED_CUDA}"
fi
# rocm3.7, rocm3.5.1
ROCM_VERSION="$DESIRED_CUDA"
echo "Using $ROCM_VERSION as determined by DESIRED_CUDA"
else
echo "Must set DESIRED_CUDA"
exit 1
fi
# Package directories
WHEELHOUSE_DIR="wheelhouse$ROCM_VERSION"
LIBTORCH_HOUSE_DIR="libtorch_house$ROCM_VERSION"
if [[ -z "$PYTORCH_FINAL_PACKAGE_DIR" ]]; then
if [[ -z "$BUILD_PYTHONLESS" ]]; then
PYTORCH_FINAL_PACKAGE_DIR="/remote/wheelhouse$ROCM_VERSION"
else
PYTORCH_FINAL_PACKAGE_DIR="/remote/libtorch_house$ROCM_VERSION"
fi
fi
mkdir -p "$PYTORCH_FINAL_PACKAGE_DIR" || true
# To make version comparison easier, create an integer representation.
ROCM_VERSION_CLEAN=$(echo ${ROCM_VERSION} | sed s/rocm//)
save_IFS="$IFS"
IFS=. ROCM_VERSION_ARRAY=(${ROCM_VERSION_CLEAN})
IFS="$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))
# Required ROCm libraries
ROCM_SO_FILES=(
"libMIOpen.so"
"libamdhip64.so"
"libhipblas.so"
"libhipfft.so"
"libhiprand.so"
"libhipsolver.so"
"libhipsparse.so"
"libhsa-runtime64.so"
"libamd_comgr.so"
"libmagma.so"
"librccl.so"
"librocblas.so"
"librocfft.so"
"librocm_smi64.so"
"librocrand.so"
"librocsolver.so"
"librocsparse.so"
"libroctracer64.so"
"libroctx64.so"
"libhipblaslt.so"
"libhiprtc.so"
)
if [[ $ROCM_INT -ge 60100 ]]; then
ROCM_SO_FILES+=("librocprofiler-register.so")
fi
if [[ $ROCM_INT -ge 60200 ]]; then
ROCM_SO_FILES+=("librocm-core.so")
fi
OS_NAME=`awk -F= '/^NAME/{print $2}' /etc/os-release`
if [[ "$OS_NAME" == *"CentOS Linux"* ]]; then
LIBGOMP_PATH="/usr/lib64/libgomp.so.1"
LIBNUMA_PATH="/usr/lib64/libnuma.so.1"
LIBELF_PATH="/usr/lib64/libelf.so.1"
LIBTINFO_PATH="/usr/lib64/libtinfo.so.5"
LIBDRM_PATH="/opt/amdgpu/lib64/libdrm.so.2"
LIBDRM_AMDGPU_PATH="/opt/amdgpu/lib64/libdrm_amdgpu.so.1"
if [[ $ROCM_INT -ge 60100 ]]; then
# Below libs are direct dependencies of libhipsolver
LIBSUITESPARSE_CONFIG_PATH="/lib64/libsuitesparseconfig.so.4"
LIBCHOLMOD_PATH="/lib64/libcholmod.so.2"
# Below libs are direct dependencies of libcholmod
LIBAMD_PATH="/lib64/libamd.so.2"
LIBCAMD_PATH="/lib64/libcamd.so.2"
LIBCCOLAMD_PATH="/lib64/libccolamd.so.2"
LIBCOLAMD_PATH="/lib64/libcolamd.so.2"
LIBSATLAS_PATH="/lib64/atlas/libsatlas.so.3"
# Below libs are direct dependencies of libsatlas
LIBGFORTRAN_PATH="/lib64/libgfortran.so.3"
LIBQUADMATH_PATH="/lib64/libquadmath.so.0"
fi
MAYBE_LIB64=lib64
elif [[ "$OS_NAME" == *"Ubuntu"* ]]; then
LIBGOMP_PATH="/usr/lib/x86_64-linux-gnu/libgomp.so.1"
LIBNUMA_PATH="/usr/lib/x86_64-linux-gnu/libnuma.so.1"
LIBELF_PATH="/usr/lib/x86_64-linux-gnu/libelf.so.1"
if [[ $ROCM_INT -ge 50300 ]]; then
LIBTINFO_PATH="/lib/x86_64-linux-gnu/libtinfo.so.6"
else
LIBTINFO_PATH="/lib/x86_64-linux-gnu/libtinfo.so.5"
fi
LIBDRM_PATH="/usr/lib/x86_64-linux-gnu/libdrm.so.2"
LIBDRM_AMDGPU_PATH="/usr/lib/x86_64-linux-gnu/libdrm_amdgpu.so.1"
if [[ $ROCM_INT -ge 60100 ]]; then
# Below libs are direct dependencies of libhipsolver
LIBCHOLMOD_PATH="/lib/x86_64-linux-gnu/libcholmod.so.3"
# Below libs are direct dependencies of libcholmod
LIBSUITESPARSE_CONFIG_PATH="/lib/x86_64-linux-gnu/libsuitesparseconfig.so.5"
LIBAMD_PATH="/lib/x86_64-linux-gnu/libamd.so.2"
LIBCAMD_PATH="/lib/x86_64-linux-gnu/libcamd.so.2"
LIBCCOLAMD_PATH="/lib/x86_64-linux-gnu/libccolamd.so.2"
LIBCOLAMD_PATH="/lib/x86_64-linux-gnu/libcolamd.so.2"
LIBMETIS_PATH="/lib/x86_64-linux-gnu/libmetis.so.5"
LIBLAPACK_PATH="/lib/x86_64-linux-gnu/liblapack.so.3"
LIBBLAS_PATH="/lib/x86_64-linux-gnu/libblas.so.3"
# Below libs are direct dependencies of libblas
LIBGFORTRAN_PATH="/lib/x86_64-linux-gnu/libgfortran.so.5"
LIBQUADMATH_PATH="/lib/x86_64-linux-gnu/libquadmath.so.0"
fi
MAYBE_LIB64=lib
fi
OS_SO_PATHS=($LIBGOMP_PATH $LIBNUMA_PATH\
$LIBELF_PATH $LIBTINFO_PATH\
$LIBDRM_PATH $LIBDRM_AMDGPU_PATH\
$LIBSUITESPARSE_CONFIG_PATH\
$LIBCHOLMOD_PATH $LIBAMD_PATH\
$LIBCAMD_PATH $LIBCCOLAMD_PATH\
$LIBCOLAMD_PATH $LIBSATLAS_PATH\
$LIBGFORTRAN_PATH $LIBQUADMATH_PATH\
$LIBMETIS_PATH $LIBLAPACK_PATH\
$LIBBLAS_PATH)
OS_SO_FILES=()
for lib in "${OS_SO_PATHS[@]}"
do
file_name="${lib##*/}" # Substring removal of path to get filename
OS_SO_FILES[${#OS_SO_FILES[@]}]=$file_name # Append lib to array
done
# PyTorch-version specific
# AOTriton dependency only for PyTorch >= 2.4
if (( $(echo "${PYTORCH_VERSION} 2.4" | awk '{print ($1 >= $2)}') )); then
ROCM_SO_FILES+=("libaotriton_v2.so")
fi
# rocBLAS library files
ROCBLAS_LIB_SRC=$ROCM_HOME/lib/rocblas/library
ROCBLAS_LIB_DST=lib/rocblas/library
ARCH=$(echo $PYTORCH_ROCM_ARCH | sed 's/;/|/g') # Replace ; seperated arch list to bar for grep
ARCH_SPECIFIC_FILES=$(ls $ROCBLAS_LIB_SRC | grep -E $ARCH)
OTHER_FILES=$(ls $ROCBLAS_LIB_SRC | grep -v gfx)
ROCBLAS_LIB_FILES=($ARCH_SPECIFIC_FILES $OTHER_FILES)
# hipblaslt library files
HIPBLASLT_LIB_SRC=$ROCM_HOME/lib/hipblaslt/library
HIPBLASLT_LIB_DST=lib/hipblaslt/library
ARCH_SPECIFIC_FILES=$(ls $HIPBLASLT_LIB_SRC | grep -E $ARCH)
OTHER_FILES=$(ls $HIPBLASLT_LIB_SRC | grep -v gfx)
HIPBLASLT_LIB_FILES=($ARCH_SPECIFIC_FILES $OTHER_FILES)
# ROCm library files
ROCM_SO_PATHS=()
for lib in "${ROCM_SO_FILES[@]}"
do
file_path=($(find $ROCM_HOME/lib/ -name "$lib")) # First search in lib
if [[ -z $file_path ]]; then
if [ -d "$ROCM_HOME/lib64/" ]; then
file_path=($(find $ROCM_HOME/lib64/ -name "$lib")) # Then search in lib64
fi
fi
if [[ -z $file_path ]]; then
file_path=($(find $ROCM_HOME/ -name "$lib")) # Then search in ROCM_HOME
fi
if [[ -z $file_path ]]; then
echo "Error: Library file $lib is not found." >&2
exit 1
fi
ROCM_SO_PATHS[${#ROCM_SO_PATHS[@]}]="$file_path" # Append lib to array
done
DEPS_LIST=(
${ROCM_SO_PATHS[*]}
${OS_SO_PATHS[*]}
)
DEPS_SONAME=(
${ROCM_SO_FILES[*]}
${OS_SO_FILES[*]}
)
DEPS_AUX_SRCLIST=(
"${ROCBLAS_LIB_FILES[@]/#/$ROCBLAS_LIB_SRC/}"
"${HIPBLASLT_LIB_FILES[@]/#/$HIPBLASLT_LIB_SRC/}"
"/opt/amdgpu/share/libdrm/amdgpu.ids"
)
DEPS_AUX_DSTLIST=(
"${ROCBLAS_LIB_FILES[@]/#/$ROCBLAS_LIB_DST/}"
"${HIPBLASLT_LIB_FILES[@]/#/$HIPBLASLT_LIB_DST/}"
"share/libdrm/amdgpu.ids"
)
# MIOpen library files
MIOPEN_SHARE_SRC=$ROCM_HOME/share/miopen/db
MIOPEN_SHARE_DST=share/miopen/db
MIOPEN_SHARE_FILES=($(ls $MIOPEN_SHARE_SRC | grep -E $ARCH))
DEPS_AUX_SRCLIST+=(${MIOPEN_SHARE_FILES[@]/#/$MIOPEN_SHARE_SRC/})
DEPS_AUX_DSTLIST+=(${MIOPEN_SHARE_FILES[@]/#/$MIOPEN_SHARE_DST/})
# RCCL library files
RCCL_SHARE_SRC=$ROCM_HOME/share/rccl/msccl-algorithms
RCCL_SHARE_DST=share/rccl/msccl-algorithms
RCCL_SHARE_FILES=($(ls $RCCL_SHARE_SRC))
DEPS_AUX_SRCLIST+=(${RCCL_SHARE_FILES[@]/#/$RCCL_SHARE_SRC/})
DEPS_AUX_DSTLIST+=(${RCCL_SHARE_FILES[@]/#/$RCCL_SHARE_DST/})
echo "PYTORCH_ROCM_ARCH: ${PYTORCH_ROCM_ARCH}"
SCRIPTPATH="$( cd "$(dirname "$0")" ; pwd -P )"
if [[ -z "$BUILD_PYTHONLESS" ]]; then
BUILD_SCRIPT=build_common.sh
else
BUILD_SCRIPT=build_libtorch.sh
fi
source $SCRIPTPATH/${BUILD_SCRIPT}

View File

@ -1,26 +0,0 @@
#!/usr/bin/env bash
set -e
yum install -y wget git
rm -rf /usr/local/cuda*
# Install Anaconda
if ! ls /py
then
echo "Miniconda needs to be installed"
wget https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh -O ~/miniconda.sh
bash ~/miniconda.sh -b -p /py
else
echo "Miniconda is already installed"
fi
export PATH="/py/bin:$PATH"
# Anaconda token
if ls /remote/token
then
source /remote/token
fi
conda install -y conda-build anaconda-client

View File

@ -1,9 +1,5 @@
#!/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"

View File

@ -3,20 +3,6 @@
# shellcheck source=./common.sh
source "$(dirname "${BASH_SOURCE[0]}")/common.sh"
# Workaround for dind-rootless userid mapping (https://github.com/pytorch/ci-infra/issues/96)
WORKSPACE_ORIGINAL_OWNER_ID=$(stat -c '%u' "/var/lib/jenkins/workspace")
cleanup_workspace() {
echo "sudo may print the following warning message that can be ignored. The chown command will still run."
echo " sudo: setrlimit(RLIMIT_STACK): Operation not permitted"
echo "For more details refer to https://github.com/sudo-project/sudo/issues/42"
sudo chown -R "$WORKSPACE_ORIGINAL_OWNER_ID" /var/lib/jenkins/workspace
}
# Disable shellcheck SC2064 as we want to parse the original owner immediately.
# shellcheck disable=SC2064
trap_add cleanup_workspace EXIT
sudo chown -R jenkins /var/lib/jenkins/workspace
git config --global --add safe.directory /var/lib/jenkins/workspace
if [[ "$BUILD_ENVIRONMENT" == *onnx* ]]; then
# TODO: This can be removed later once vision is also part of the Docker image
pip install -q --user --no-use-pep517 "git+https://github.com/pytorch/vision.git@$(cat .github/ci_commit_pins/vision.txt)"

View File

@ -1 +1,42 @@
This directory contains scripts for our continuous integration.
One important thing to keep in mind when reading the scripts here is
that they are all based off of Docker images, which we build for each of
the various system configurations we want to run on Jenkins. This means
it is very easy to run these tests yourself:
1. Figure out what Docker image you want. The general template for our
images look like:
``registry.pytorch.org/pytorch/pytorch-$BUILD_ENVIRONMENT:$DOCKER_VERSION``,
where ``$BUILD_ENVIRONMENT`` is one of the build environments
enumerated in
[pytorch-dockerfiles](https://github.com/pytorch/pytorch/blob/master/.ci/docker/build.sh). The dockerfile used by jenkins can be found under the `.ci` [directory](https://github.com/pytorch/pytorch/blob/master/.ci/docker)
2. Run ``docker run -it -u jenkins $DOCKER_IMAGE``, clone PyTorch and
run one of the scripts in this directory.
The Docker images are designed so that any "reasonable" build commands
will work; if you look in [build.sh](build.sh) you will see that it is a
very simple script. This is intentional. Idiomatic build instructions
should work inside all of our Docker images. You can tweak the commands
however you need (e.g., in case you want to rebuild with DEBUG, or rerun
the build with higher verbosity, etc.).
We have to do some work to make this so. Here is a summary of the
mechanisms we use:
- We install binaries to directories like `/usr/local/bin` which
are automatically part of your PATH.
- We add entries to the PATH using Docker ENV variables (so
they apply when you enter Docker) and `/etc/environment` (so they
continue to apply even if you sudo), instead of modifying
`PATH` in our build scripts.
- We use `/etc/ld.so.conf.d` to register directories containing
shared libraries, instead of modifying `LD_LIBRARY_PATH` in our
build scripts.
- We reroute well known paths like `/usr/bin/gcc` to alternate
implementations with `update-alternatives`, instead of setting
`CC` and `CXX` in our implementations.

View File

@ -44,13 +44,26 @@ if [[ "$BUILD_ENVIRONMENT" == *cuda11* ]]; then
fi
fi
if [[ ${BUILD_ENVIRONMENT} == *"parallelnative"* ]]; then
if [[ ${BUILD_ENVIRONMENT} == *"caffe2"* ]]; then
echo "Caffe2 build is ON"
export BUILD_CAFFE2=ON
fi
if [[ ${BUILD_ENVIRONMENT} == *"paralleltbb"* ]]; then
export ATEN_THREADING=TBB
export USE_TBB=1
elif [[ ${BUILD_ENVIRONMENT} == *"parallelnative"* ]]; then
export ATEN_THREADING=NATIVE
fi
# Enable LLVM dependency for TensorExpr testing
export USE_LLVM=/opt/llvm
export LLVM_DIR=/opt/llvm/lib/cmake/llvm
if [[ "$BUILD_ENVIRONMENT" == *rocm* ]]; then
export USE_LLVM=/opt/rocm/llvm
export LLVM_DIR=/opt/rocm/llvm/lib/cmake/llvm
else
export USE_LLVM=/opt/llvm
export LLVM_DIR=/opt/llvm/lib/cmake/llvm
fi
if [[ "$BUILD_ENVIRONMENT" == *executorch* ]]; then
# To build test_edge_op_registration
@ -68,35 +81,7 @@ if ! which conda; then
export USE_MKLDNN=0
fi
else
# CMAKE_PREFIX_PATH precedences
# 1. $CONDA_PREFIX, if defined. This follows the pytorch official build instructions.
# 2. /opt/conda/envs/py_${ANACONDA_PYTHON_VERSION}, if ANACONDA_PYTHON_VERSION defined.
# This is for CI, which defines ANACONDA_PYTHON_VERSION but not CONDA_PREFIX.
# 3. $(conda info --base). The fallback value of pytorch official build
# instructions actually refers to this.
# Commonly this is /opt/conda/
if [[ -v CONDA_PREFIX ]]; then
export CMAKE_PREFIX_PATH=${CONDA_PREFIX}
elif [[ -v ANACONDA_PYTHON_VERSION ]]; then
export CMAKE_PREFIX_PATH="/opt/conda/envs/py_${ANACONDA_PYTHON_VERSION}"
else
# already checked by `! which conda`
CMAKE_PREFIX_PATH="$(conda info --base)"
export CMAKE_PREFIX_PATH
fi
# Workaround required for MKL library linkage
# https://github.com/pytorch/pytorch/issues/119557
if [ "$ANACONDA_PYTHON_VERSION" = "3.12" ]; then
export CMAKE_LIBRARY_PATH="/opt/conda/envs/py_$ANACONDA_PYTHON_VERSION/lib/"
export CMAKE_INCLUDE_PATH="/opt/conda/envs/py_$ANACONDA_PYTHON_VERSION/include/"
fi
fi
if [[ "$BUILD_ENVIRONMENT" == *aarch64* ]]; then
export USE_MKLDNN=1
export USE_MKLDNN_ACL=1
export ACL_ROOT_DIR=/ComputeLibrary
export CMAKE_PREFIX_PATH=/opt/conda
fi
if [[ "$BUILD_ENVIRONMENT" == *libtorch* ]]; then
@ -168,17 +153,10 @@ if [[ "$BUILD_ENVIRONMENT" == *rocm* ]]; then
python tools/amd_build/build_amd.py
fi
if [[ "$BUILD_ENVIRONMENT" == *xpu* ]]; then
# shellcheck disable=SC1091
source /opt/intel/oneapi/compiler/latest/env/vars.sh
# XPU kineto feature dependencies are not fully ready, disable kineto build as temp WA
export USE_KINETO=0
fi
# sccache will fail for CUDA builds if all cores are used for compiling
# gcc 7 with sccache seems to have intermittent OOM issue if all cores are used
if [ -z "$MAX_JOBS" ]; then
if { [[ "$BUILD_ENVIRONMENT" == *cuda* ]]; } && which sccache > /dev/null; then
if { [[ "$BUILD_ENVIRONMENT" == *cuda* ]] || [[ "$BUILD_ENVIRONMENT" == *gcc7* ]]; } && which sccache > /dev/null; then
export MAX_JOBS=$(($(nproc) - 1))
fi
fi
@ -203,6 +181,7 @@ if [[ "${BUILD_ENVIRONMENT}" == *clang* ]]; then
fi
if [[ "$BUILD_ENVIRONMENT" == *-clang*-asan* ]]; then
export LDSHARED="clang --shared"
export USE_CUDA=0
export USE_ASAN=1
export UBSAN_FLAGS="-fno-sanitize-recover=all;-fno-sanitize=float-divide-by-zero;-fno-sanitize=float-cast-overflow"
@ -217,32 +196,14 @@ if [[ "${BUILD_ENVIRONMENT}" == *-pch* ]]; then
export USE_PRECOMPILED_HEADERS=1
fi
if [[ "${BUILD_ENVIRONMENT}" == *linux-focal-py3.7-gcc7-build* ]]; then
export USE_GLOO_WITH_OPENSSL=ON
fi
if [[ "${BUILD_ENVIRONMENT}" != *android* && "${BUILD_ENVIRONMENT}" != *cuda* ]]; then
export BUILD_STATIC_RUNTIME_BENCHMARK=ON
fi
if [[ "$BUILD_ENVIRONMENT" == *-debug* ]]; then
export CMAKE_BUILD_TYPE=RelWithAssert
fi
# Do not change workspace permissions for ROCm CI jobs
# as it can leave workspace with bad permissions for cancelled jobs
if [[ "$BUILD_ENVIRONMENT" != *rocm* && "$BUILD_ENVIRONMENT" != *s390x* ]]; then
# Workaround for dind-rootless userid mapping (https://github.com/pytorch/ci-infra/issues/96)
WORKSPACE_ORIGINAL_OWNER_ID=$(stat -c '%u' "/var/lib/jenkins/workspace")
cleanup_workspace() {
echo "sudo may print the following warning message that can be ignored. The chown command will still run."
echo " sudo: setrlimit(RLIMIT_STACK): Operation not permitted"
echo "For more details refer to https://github.com/sudo-project/sudo/issues/42"
sudo chown -R "$WORKSPACE_ORIGINAL_OWNER_ID" /var/lib/jenkins/workspace
}
# Disable shellcheck SC2064 as we want to parse the original owner immediately.
# shellcheck disable=SC2064
trap_add cleanup_workspace EXIT
sudo chown -R jenkins /var/lib/jenkins/workspace
git config --global --add safe.directory /var/lib/jenkins/workspace
fi
if [[ "$BUILD_ENVIRONMENT" == *-bazel-* ]]; then
set -e
@ -268,37 +229,16 @@ else
( ! get_exit_code python setup.py clean bad_argument )
if [[ "$BUILD_ENVIRONMENT" != *libtorch* ]]; then
# rocm builds fail when WERROR=1
# XLA test build fails when WERROR=1
# set only when building other architectures
# or building non-XLA tests.
if [[ "$BUILD_ENVIRONMENT" != *rocm* &&
"$BUILD_ENVIRONMENT" != *s390x* &&
"$BUILD_ENVIRONMENT" != *xla* ]]; then
if [[ "$BUILD_ENVIRONMENT" != *py3.8* ]]; then
# Install numpy-2.0.2 for builds which are backward compatible with 1.X
python -mpip install --pre numpy==2.0.2
fi
WERROR=1 python setup.py clean
if [[ "$USE_SPLIT_BUILD" == "true" ]]; then
BUILD_LIBTORCH_WHL=1 BUILD_PYTHON_ONLY=0 python setup.py bdist_wheel
BUILD_LIBTORCH_WHL=0 BUILD_PYTHON_ONLY=1 python setup.py bdist_wheel --cmake
else
WERROR=1 python setup.py bdist_wheel
fi
WERROR=1 python setup.py bdist_wheel
else
python setup.py clean
if [[ "$BUILD_ENVIRONMENT" == *xla* ]]; then
source .ci/pytorch/install_cache_xla.sh
fi
if [[ "$USE_SPLIT_BUILD" == "true" ]]; then
echo "USE_SPLIT_BUILD cannot be used with xla or rocm"
exit 1
else
python setup.py bdist_wheel
fi
python setup.py bdist_wheel
fi
pip_install_whl "$(echo dist/*.whl)"
@ -336,11 +276,10 @@ else
CUSTOM_OP_BUILD="${CUSTOM_TEST_ARTIFACT_BUILD_DIR}/custom-op-build"
CUSTOM_OP_TEST="$PWD/test/custom_operator"
python --version
SITE_PACKAGES="$(python -c 'import site; print(";".join([x for x in site.getsitepackages()] + [x + "/torch" for x in site.getsitepackages()]))')"
SITE_PACKAGES="$(python -c 'from distutils.sysconfig import get_python_lib; print(get_python_lib())')"
mkdir -p "$CUSTOM_OP_BUILD"
pushd "$CUSTOM_OP_BUILD"
cmake "$CUSTOM_OP_TEST" -DCMAKE_PREFIX_PATH="$SITE_PACKAGES" -DPython_EXECUTABLE="$(which python)" \
cmake "$CUSTOM_OP_TEST" -DCMAKE_PREFIX_PATH="$SITE_PACKAGES/torch" -DPYTHON_EXECUTABLE="$(which python)" \
-DCMAKE_MODULE_PATH="$CUSTOM_TEST_MODULE_PATH" -DUSE_ROCM="$CUSTOM_TEST_USE_ROCM"
make VERBOSE=1
popd
@ -350,10 +289,10 @@ else
JIT_HOOK_BUILD="${CUSTOM_TEST_ARTIFACT_BUILD_DIR}/jit-hook-build"
JIT_HOOK_TEST="$PWD/test/jit_hooks"
python --version
SITE_PACKAGES="$(python -c 'import site; print(";".join([x for x in site.getsitepackages()] + [x + "/torch" for x in site.getsitepackages()]))')"
SITE_PACKAGES="$(python -c 'from distutils.sysconfig import get_python_lib; print(get_python_lib())')"
mkdir -p "$JIT_HOOK_BUILD"
pushd "$JIT_HOOK_BUILD"
cmake "$JIT_HOOK_TEST" -DCMAKE_PREFIX_PATH="$SITE_PACKAGES" -DPython_EXECUTABLE="$(which python)" \
cmake "$JIT_HOOK_TEST" -DCMAKE_PREFIX_PATH="$SITE_PACKAGES/torch" -DPYTHON_EXECUTABLE="$(which python)" \
-DCMAKE_MODULE_PATH="$CUSTOM_TEST_MODULE_PATH" -DUSE_ROCM="$CUSTOM_TEST_USE_ROCM"
make VERBOSE=1
popd
@ -365,7 +304,7 @@ else
python --version
mkdir -p "$CUSTOM_BACKEND_BUILD"
pushd "$CUSTOM_BACKEND_BUILD"
cmake "$CUSTOM_BACKEND_TEST" -DCMAKE_PREFIX_PATH="$SITE_PACKAGES" -DPython_EXECUTABLE="$(which python)" \
cmake "$CUSTOM_BACKEND_TEST" -DCMAKE_PREFIX_PATH="$SITE_PACKAGES/torch" -DPYTHON_EXECUTABLE="$(which python)" \
-DCMAKE_MODULE_PATH="$CUSTOM_TEST_MODULE_PATH" -DUSE_ROCM="$CUSTOM_TEST_USE_ROCM"
make VERBOSE=1
popd
@ -396,8 +335,4 @@ if [[ "$BUILD_ENVIRONMENT" != *libtorch* && "$BUILD_ENVIRONMENT" != *bazel* ]];
python tools/stats/export_test_times.py
fi
# snadampal: skipping it till sccache support added for aarch64
# https://github.com/pytorch/pytorch/issues/121559
if [[ "$BUILD_ENVIRONMENT" != *aarch64* && "$BUILD_ENVIRONMENT" != *s390x* ]]; then
print_sccache_stats
fi
print_sccache_stats

View File

@ -56,29 +56,9 @@ function assert_git_not_dirty() {
function pip_install_whl() {
# This is used to install PyTorch and other build artifacts wheel locally
# without using any network connection
# Convert the input arguments into an array
local args=("$@")
# Check if the first argument contains multiple paths separated by spaces
if [[ "${args[0]}" == *" "* ]]; then
# Split the string by spaces into an array
IFS=' ' read -r -a paths <<< "${args[0]}"
# Loop through each path and install individually
for path in "${paths[@]}"; do
echo "Installing $path"
python3 -mpip install --no-index --no-deps "$path"
done
else
# Loop through each argument and install individually
for path in "${args[@]}"; do
echo "Installing $path"
python3 -mpip install --no-index --no-deps "$path"
done
fi
python3 -mpip install --no-index --no-deps "$@"
}
function pip_install() {
# retry 3 times
# old versions of pip don't have the "--progress-bar" flag
@ -178,11 +158,6 @@ function install_torchvision() {
fi
}
function install_tlparse() {
pip_install --user "tlparse==0.3.25"
PATH="$(python -m site --user-base)/bin:$PATH"
}
function install_torchrec_and_fbgemm() {
local torchrec_commit
torchrec_commit=$(get_pinned_commit torchrec)
@ -191,27 +166,14 @@ function install_torchrec_and_fbgemm() {
pip_uninstall torchrec-nightly
pip_uninstall fbgemm-gpu-nightly
pip_install setuptools-git-versioning scikit-build pyre-extensions
# TODO (huydhn): I still have no clue on why sccache doesn't work with only fbgemm_gpu here, but it
# seems to be an sccache-related issue
if [[ "$IS_A100_RUNNER" == "1" ]]; then
unset CMAKE_CUDA_COMPILER_LAUNCHER
sudo mv /opt/cache/bin /opt/cache/bin-backup
fi
# See https://github.com/pytorch/pytorch/issues/106971
CUDA_PATH=/usr/local/cuda-12.1 pip_install --no-use-pep517 --user "git+https://github.com/pytorch/FBGEMM.git@${fbgemm_commit}#egg=fbgemm-gpu&subdirectory=fbgemm_gpu"
pip_install --no-use-pep517 --user "git+https://github.com/pytorch/torchrec.git@${torchrec_commit}"
if [[ "$IS_A100_RUNNER" == "1" ]]; then
export CMAKE_CUDA_COMPILER_LAUNCHER=/opt/cache/bin/sccache
sudo mv /opt/cache/bin-backup /opt/cache/bin
fi
}
function clone_pytorch_xla() {
if [[ ! -d ./xla ]]; then
git clone --recursive --quiet https://github.com/pytorch/xla.git
git clone --recursive -b r2.2 https://github.com/pytorch/xla.git
pushd xla
# pin the xla hash so that we don't get broken by changes to xla
git checkout "$(cat ../.github/ci_commit_pins/xla.txt)"
@ -221,6 +183,28 @@ function clone_pytorch_xla() {
fi
}
function checkout_install_torchdeploy() {
local commit
commit=$(get_pinned_commit multipy)
pushd ..
git clone --recurse-submodules https://github.com/pytorch/multipy.git
pushd multipy
git checkout "${commit}"
python multipy/runtime/example/generate_examples.py
BUILD_CUDA_TESTS=1 pip install -e .
popd
popd
}
function test_torch_deploy(){
pushd ..
pushd multipy
./multipy/runtime/build/test_deploy
./multipy/runtime/build/test_deploy_gpu
popd
popd
}
function checkout_install_torchbench() {
local commit
commit=$(get_pinned_commit torchbench)
@ -235,8 +219,6 @@ function checkout_install_torchbench() {
# to install and test other models
python install.py --continue_on_fail
fi
echo "Print all dependencies after TorchBench is installed"
python -mpip freeze
popd
}

View File

@ -1,4 +1,4 @@
from datetime import datetime, timedelta, timezone
from datetime import datetime, timedelta
from tempfile import mkdtemp
from cryptography import x509
@ -6,7 +6,6 @@ from cryptography.hazmat.primitives import hashes, serialization
from cryptography.hazmat.primitives.asymmetric import rsa
from cryptography.x509.oid import NameOID
temp_dir = mkdtemp()
print(temp_dir)
@ -42,10 +41,11 @@ def create_cert(path, C, ST, L, O, key):
.issuer_name(issuer)
.public_key(key.public_key())
.serial_number(x509.random_serial_number())
.not_valid_before(datetime.now(timezone.utc))
.not_valid_before(datetime.utcnow())
.not_valid_after(
# Our certificate will be valid for 10 days
datetime.now(timezone.utc) + timedelta(days=10)
datetime.utcnow()
+ timedelta(days=10)
)
.add_extension(
x509.BasicConstraints(ca=True, path_length=None),
@ -87,10 +87,11 @@ def sign_certificate_request(path, csr_cert, ca_cert, private_ca_key):
.issuer_name(ca_cert.subject)
.public_key(csr_cert.public_key())
.serial_number(x509.random_serial_number())
.not_valid_before(datetime.now(timezone.utc))
.not_valid_before(datetime.utcnow())
.not_valid_after(
# Our certificate will be valid for 10 days
datetime.now(timezone.utc) + timedelta(days=10)
datetime.utcnow()
+ timedelta(days=10)
# Sign our certificate with our private key
)
.sign(private_ca_key, hashes.SHA256())

View File

@ -6,4 +6,4 @@ source "$(dirname "${BASH_SOURCE[0]}")/common.sh"
echo "Testing pytorch docs"
cd docs
TERM=vt100 make doctest
make doctest

View File

@ -1,37 +0,0 @@
#!/bin/bash
# Script for installing sccache on the xla build job, which uses xla's docker
# image and doesn't have sccache installed on it. This is mostly copied from
# .ci/docker/install_cache.sh. Changes are: removing checks that will always
# return the same thing, ex checks for for rocm, CUDA, and changing the path
# where sccache is installed, and not changing /etc/environment.
set -ex
install_binary() {
echo "Downloading sccache binary from S3 repo"
curl --retry 3 https://s3.amazonaws.com/ossci-linux/sccache -o /tmp/cache/bin/sccache
}
mkdir -p /tmp/cache/bin
mkdir -p /tmp/cache/lib
export PATH="/tmp/cache/bin:$PATH"
install_binary
chmod a+x /tmp/cache/bin/sccache
function write_sccache_stub() {
# Unset LD_PRELOAD for ps because of asan + ps issues
# https://gcc.gnu.org/bugzilla/show_bug.cgi?id=90589
# shellcheck disable=SC2086
# shellcheck disable=SC2059
printf "#!/bin/sh\nif [ \$(env -u LD_PRELOAD ps -p \$PPID -o comm=) != sccache ]; then\n exec sccache $(which $1) \"\$@\"\nelse\n exec $(which $1) \"\$@\"\nfi" > "/tmp/cache/bin/$1"
chmod a+x "/tmp/cache/bin/$1"
}
write_sccache_stub cc
write_sccache_stub c++
write_sccache_stub gcc
write_sccache_stub g++
write_sccache_stub clang
write_sccache_stub clang++

View File

@ -9,7 +9,7 @@ sysctl -a | grep machdep.cpu
# These are required for both the build job and the test job.
# In the latter to test cpp extensions.
export MACOSX_DEPLOYMENT_TARGET=11.1
export MACOSX_DEPLOYMENT_TARGET=11.0
export CXX=clang++
export CC=clang

View File

@ -9,13 +9,15 @@ if [[ -n "$CONDA_ENV" ]]; then
export PATH="$CONDA_ENV/bin":$PATH
fi
# Test that OpenMP is enabled
pushd test
if [[ ! $(python -c "import torch; print(int(torch.backends.openmp.is_available()))") == "1" ]]; then
echo "Build should have OpenMP enabled, but torch.backends.openmp.is_available() is False"
exit 1
# Test that OpenMP is enabled for non-arm64 build
if [[ ${BUILD_ENVIRONMENT} != *arm64* ]]; then
pushd test
if [[ ! $(python -c "import torch; print(int(torch.backends.openmp.is_available()))") == "1" ]]; then
echo "Build should have OpenMP enabled, but torch.backends.openmp.is_available() is False"
exit 1
fi
popd
fi
popd
setup_test_python() {
# The CircleCI worker hostname doesn't resolve to an address.
@ -25,9 +27,8 @@ setup_test_python() {
echo "Ninja version: $(ninja --version)"
echo "Python version: $(which python) ($(python --version))"
# Set the limit on open file handles to 16384
# might help with intermittent compiler test failures
ulimit -n 16384
# Increase default limit on open file handles from 256 to 1024
ulimit -n 1024
}
test_python_all() {
@ -148,8 +149,6 @@ test_jit_hooks() {
assert_git_not_dirty
}
install_tlparse
if [[ $NUM_TEST_SHARDS -gt 1 ]]; then
test_python_shard "${SHARD_NUMBER}"
if [[ "${SHARD_NUMBER}" == 1 ]]; then

View File

@ -18,9 +18,7 @@ time python test/run_test.py --verbose -i distributed/test_c10d_gloo
time python test/run_test.py --verbose -i distributed/test_c10d_nccl
time python test/run_test.py --verbose -i distributed/test_c10d_spawn_gloo
time python test/run_test.py --verbose -i distributed/test_c10d_spawn_nccl
time python test/run_test.py --verbose -i distributed/test_compute_comm_reordering
time python test/run_test.py --verbose -i distributed/test_store
time python test/run_test.py --verbose -i distributed/test_symmetric_memory
time python test/run_test.py --verbose -i distributed/test_pg_wrapper
time python test/run_test.py --verbose -i distributed/rpc/cuda/test_tensorpipe_agent
# FSDP tests
@ -36,6 +34,7 @@ time python test/run_test.py --verbose -i distributed/_shard/sharded_tensor/test
# functional collective tests
time python test/run_test.py --verbose -i distributed/test_functional_api
# DTensor tests
time python test/run_test.py --verbose -i distributed/_tensor/test_random_ops
time python test/run_test.py --verbose -i distributed/_tensor/test_dtensor_compile
@ -44,19 +43,12 @@ time python test/run_test.py --verbose -i distributed/_tensor/test_dtensor_compi
time python test/run_test.py --verbose -i distributed/test_device_mesh
# DTensor/TP tests
time python test/run_test.py --verbose -i distributed/tensor/parallel/test_ddp_2d_parallel
time python test/run_test.py --verbose -i distributed/tensor/parallel/test_fsdp_2d_parallel
time python test/run_test.py --verbose -i distributed/tensor/parallel/test_tp_examples
time python test/run_test.py --verbose -i distributed/tensor/parallel/test_tp_random_state
# FSDP2 tests
time python test/run_test.py --verbose -i distributed/_composable/fsdp/test_fully_shard_training -- -k test_2d_mlp_with_nd_mesh
# ND composability tests
time python test/run_test.py --verbose -i distributed/_composable/test_composability/test_2d_composability
time python test/run_test.py --verbose -i distributed/_composable/test_composability/test_pp_composability
# Other tests
time python test/run_test.py --verbose -i test_cuda_primary_ctx
time python test/run_test.py --verbose -i test_optim -- -k test_forloop_goes_right_direction_multigpu
time python test/run_test.py --verbose -i test_optim -- -k test_mixed_device_dtype
time python test/run_test.py --verbose -i test_optim -- -k optimizers_with_varying_tensors
time python test/run_test.py --verbose -i test_foreach -- -k test_tensors_grouping
assert_git_not_dirty

View File

@ -3,7 +3,6 @@ import json
import math
import sys
parser = argparse.ArgumentParser()
parser.add_argument(
"--test-name", dest="test_name", action="store", required=True, help="test name"
@ -60,16 +59,16 @@ print("sample mean: ", sample_mean)
print("sample sigma: ", sample_sigma)
if math.isnan(sample_mean):
raise Exception("""Error: sample mean is NaN""") # noqa: TRY002
raise Exception("""Error: sample mean is NaN""")
elif math.isnan(sample_sigma):
raise Exception("""Error: sample sigma is NaN""") # noqa: TRY002
raise Exception("""Error: sample sigma is NaN""")
z_value = (sample_mean - mean) / sigma
print("z-value: ", z_value)
if z_value >= 3:
raise Exception( # noqa: TRY002
raise Exception(
f"""\n
z-value >= 3, there is high chance of perf regression.\n
To reproduce this regression, run

View File

@ -3,7 +3,6 @@ import sys
import numpy
sample_data_list = sys.argv[1:]
sample_data_list = [float(v.strip()) for v in sample_data_list]

View File

@ -1,7 +1,6 @@
import json
import sys
data_file_path = sys.argv[1]
commit_hash = sys.argv[2]

View File

@ -1,6 +1,5 @@
import sys
log_file_path = sys.argv[1]
with open(log_file_path) as f:

View File

@ -26,8 +26,8 @@ echo "error: python_doc_push_script.sh: version (arg2) not specified"
fi
# Argument 1: Where to copy the built documentation to
# (pytorch_docs/$install_path)
install_path="${1:-${DOCS_INSTALL_PATH:-${DOCS_VERSION}}}"
# (pytorch.github.io/$install_path)
install_path="${1:-${DOCS_INSTALL_PATH:-docs/${DOCS_VERSION}}}"
if [ -z "$install_path" ]; then
echo "error: python_doc_push_script.sh: install_path (arg1) not specified"
exit 1
@ -68,8 +68,8 @@ build_docs () {
}
git clone https://github.com/pytorch/docs pytorch_docs -b "$branch" --depth 1
pushd pytorch_docs
git clone https://github.com/pytorch/pytorch.github.io -b "$branch" --depth 1
pushd pytorch.github.io
export LC_ALL=C
export PATH=/opt/conda/bin:$PATH
@ -105,7 +105,6 @@ if [ "$is_main_doc" = true ]; then
echo undocumented objects found:
cat build/coverage/python.txt
echo "Make sure you've updated relevant .rsts in docs/source!"
echo "You can reproduce locally by running 'cd docs && make coverage && cat build/coverage/python.txt'"
exit 1
fi
else

View File

@ -6,30 +6,6 @@
set -ex
# Suppress ANSI color escape sequences
export TERM=vt100
# shellcheck source=./common.sh
source "$(dirname "${BASH_SOURCE[0]}")/common.sh"
# Do not change workspace permissions for ROCm CI jobs
# as it can leave workspace with bad permissions for cancelled jobs
if [[ "$BUILD_ENVIRONMENT" != *rocm* ]]; then
# Workaround for dind-rootless userid mapping (https://github.com/pytorch/ci-infra/issues/96)
WORKSPACE_ORIGINAL_OWNER_ID=$(stat -c '%u' "/var/lib/jenkins/workspace")
cleanup_workspace() {
echo "sudo may print the following warning message that can be ignored. The chown command will still run."
echo " sudo: setrlimit(RLIMIT_STACK): Operation not permitted"
echo "For more details refer to https://github.com/sudo-project/sudo/issues/42"
sudo chown -R "$WORKSPACE_ORIGINAL_OWNER_ID" /var/lib/jenkins/workspace
}
# Disable shellcheck SC2064 as we want to parse the original owner immediately.
# shellcheck disable=SC2064
trap_add cleanup_workspace EXIT
sudo chown -R jenkins /var/lib/jenkins/workspace
git config --global --add safe.directory /var/lib/jenkins/workspace
fi
echo "Environment variables:"
env
@ -42,23 +18,19 @@ BUILD_DIR="build"
BUILD_RENAMED_DIR="build_renamed"
BUILD_BIN_DIR="$BUILD_DIR"/bin
#Set Default values for these variables in case they are not set
SHARD_NUMBER="${SHARD_NUMBER:=1}"
NUM_TEST_SHARDS="${NUM_TEST_SHARDS:=1}"
export VALGRIND=ON
# export TORCH_INDUCTOR_INSTALL_GXX=ON
if [[ "$BUILD_ENVIRONMENT" == *clang9* ]]; then
# clang9 appears to miscompile code involving std::optional<c10::SymInt>,
# clang9 appears to miscompile code involving c10::optional<c10::SymInt>,
# such that valgrind complains along these lines:
#
# Conditional jump or move depends on uninitialised value(s)
# at 0x40303A: ~optional_base (Optional.h:281)
# by 0x40303A: call (Dispatcher.h:448)
# by 0x40303A: call(at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::ArrayRef<c10::SymInt>, std::optional<c10::SymInt>) (basic.cpp:10)
# by 0x40303A: call(at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::ArrayRef<c10::SymInt>, c10::optional<c10::SymInt>) (basic.cpp:10)
# by 0x403700: main (basic.cpp:16)
# Uninitialised value was created by a stack allocation
# at 0x402AAA: call(at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::ArrayRef<c10::SymInt>, std::optional<c10::SymInt>) (basic.cpp:6)
# at 0x402AAA: call(at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::ArrayRef<c10::SymInt>, c10::optional<c10::SymInt>) (basic.cpp:6)
#
# The problem does not appear with gcc or newer versions of clang (we tested
# clang14). So we suppress valgrind testing for clang9 specifically.
@ -72,7 +44,7 @@ if [[ "$BUILD_ENVIRONMENT" == *clang9* ]]; then
#
# using namespace at;
#
# Tensor call(const at::Tensor & self, c10::SymIntArrayRef size, c10::SymIntArrayRef stride, std::optional<c10::SymInt> storage_offset) {
# Tensor call(const at::Tensor & self, c10::SymIntArrayRef size, c10::SymIntArrayRef stride, c10::optional<c10::SymInt> storage_offset) {
# auto op = c10::Dispatcher::singleton()
# .findSchemaOrThrow(at::_ops::as_strided::name, at::_ops::as_strided::overload_name)
# .typed<at::_ops::as_strided::schema>();
@ -114,6 +86,9 @@ if [[ -n $TESTS_TO_INCLUDE ]]; then
INCLUDE_CLAUSE="--include $TESTS_TO_INCLUDE"
fi
# shellcheck source=./common.sh
source "$(dirname "${BASH_SOURCE[0]}")/common.sh"
echo "Environment variables"
env
@ -149,10 +124,6 @@ if [[ "$BUILD_ENVIRONMENT" == *cuda* || "$BUILD_ENVIRONMENT" == *rocm* ]]; then
# mainly used so that we're not spending extra cycles testing cpu
# devices on expensive gpu machines
export PYTORCH_TESTING_DEVICE_ONLY_FOR="cuda"
elif [[ "$BUILD_ENVIRONMENT" == *xpu* ]]; then
export PYTORCH_TESTING_DEVICE_ONLY_FOR="xpu"
# setting PYTHON_TEST_EXTRA_OPTION
export PYTHON_TEST_EXTRA_OPTION="--xpu"
fi
if [[ "$TEST_CONFIG" == *crossref* ]]; then
@ -160,22 +131,11 @@ if [[ "$TEST_CONFIG" == *crossref* ]]; then
fi
if [[ "$BUILD_ENVIRONMENT" == *rocm* ]]; then
# regression in ROCm 6.0 on MI50 CI runners due to hipblaslt; remove in 6.1
export VALGRIND=OFF
# Print GPU info
rocminfo
rocminfo | grep -E 'Name:.*\sgfx|Marketing'
fi
if [[ "$BUILD_ENVIRONMENT" == *xpu* ]]; then
# Source Intel oneAPI envrioment script to enable xpu runtime related libraries
# refer to https://www.intel.com/content/www/us/en/developer/articles/tool/pytorch-prerequisites-for-intel-gpu/2-5.html
# shellcheck disable=SC1091
source /opt/intel/oneapi/compiler/latest/env/vars.sh
# Check XPU status before testing
xpu-smi discovery
fi
if [[ "$BUILD_ENVIRONMENT" != *-bazel-* ]] ; then
# JIT C++ extensions require ninja.
pip_install --user "ninja==1.10.2"
@ -184,13 +144,6 @@ if [[ "$BUILD_ENVIRONMENT" != *-bazel-* ]] ; then
export PATH="$HOME/.local/bin:$PATH"
fi
if [[ "$BUILD_ENVIRONMENT" == *aarch64* ]]; then
# TODO: revisit this once the CI is stabilized on aarch64 linux
export VALGRIND=OFF
fi
install_tlparse
# DANGER WILL ROBINSON. The LD_PRELOAD here could cause you problems
# if you're not careful. Check this if you made some changes and the
# ASAN test is not working
@ -233,10 +186,12 @@ if [[ "$BUILD_ENVIRONMENT" == *asan* ]]; then
# it depends on a ton of dynamic libraries that most programs aren't gonna
# have, and it applies to child processes.
LD_PRELOAD=$(clang --print-file-name=libclang_rt.asan-x86_64.so)
export LD_PRELOAD
# TODO: get rid of the hardcoded path
export LD_PRELOAD=/usr/lib/llvm-15/lib/clang/15.0.7/lib/linux/libclang_rt.asan-x86_64.so
# Disable valgrind for asan
export VALGRIND=OFF
# Increase stack size, because ASAN red zones use more stack
ulimit -s 81920
(cd test && python -c "import torch; print(torch.__version__, torch.version.git_version)")
echo "The next four invocations are expected to crash; if they don't that means ASAN/UBSAN is misconfigured"
@ -252,7 +207,9 @@ fi
# This tests that the debug asserts are working correctly.
if [[ "$BUILD_ENVIRONMENT" == *-debug* ]]; then
echo "We are in debug mode: $BUILD_ENVIRONMENT. Expect the python assertion to fail"
(cd test && ! get_exit_code python -c "import torch; torch._C._crash_if_debug_asserts_fail(424242)")
# TODO: Enable the check after we setup the build to run debug asserts without having
# to do a full (and slow) debug build
# (cd test && ! get_exit_code python -c "import torch; torch._C._crash_if_debug_asserts_fail(424242)")
elif [[ "$BUILD_ENVIRONMENT" != *-bazel-* ]]; then
# Noop when debug is disabled. Skip bazel jobs because torch isn't available there yet.
echo "We are not in debug mode: $BUILD_ENVIRONMENT. Expect the assertion to pass"
@ -278,17 +235,14 @@ test_python_shard() {
# Bare --include flag is not supported and quoting for lint ends up with flag not being interpreted correctly
# shellcheck disable=SC2086
# modify LD_LIBRARY_PATH to ensure it has the conda env.
# This set of tests has been shown to be buggy without it for the split-build
time python test/run_test.py --exclude-jit-executor --exclude-distributed-tests $INCLUDE_CLAUSE --shard "$1" "$NUM_TEST_SHARDS" --verbose $PYTHON_TEST_EXTRA_OPTION
time python test/run_test.py --exclude-jit-executor --exclude-distributed-tests $INCLUDE_CLAUSE --shard "$1" "$NUM_TEST_SHARDS" --verbose
assert_git_not_dirty
}
test_python() {
# shellcheck disable=SC2086
time python test/run_test.py --exclude-jit-executor --exclude-distributed-tests $INCLUDE_CLAUSE --verbose $PYTHON_TEST_EXTRA_OPTION
time python test/run_test.py --exclude-jit-executor --exclude-distributed-tests $INCLUDE_CLAUSE --verbose
assert_git_not_dirty
}
@ -299,13 +253,33 @@ test_dynamo_shard() {
exit 1
fi
python tools/dynamo/verify_dynamo.py
# PLEASE DO NOT ADD ADDITIONAL EXCLUDES HERE.
# Instead, use @skipIfTorchDynamo on your tests.
# Temporarily disable test_fx for dynamo pending the investigation on TTS
# regression in https://github.com/pytorch/torchdynamo/issues/784
time python test/run_test.py --dynamo \
--exclude-inductor-tests \
--exclude-jit-executor \
--exclude-distributed-tests \
--exclude-torch-export-tests \
--exclude \
test_autograd \
test_jit \
test_proxy_tensor \
test_quantization \
test_public_bindings \
test_dataloader \
test_reductions \
test_namedtensor \
test_namedtuple_return_api \
profiler/test_profiler \
profiler/test_profiler_tree \
test_overrides \
test_python_dispatch \
test_fx \
test_package \
test_legacy_vmap \
test_custom_ops \
test_content_store \
export/test_db \
functorch/test_dims \
functorch/test_aotdispatch \
--shard "$1" "$NUM_TEST_SHARDS" \
--verbose
assert_git_not_dirty
@ -314,24 +288,11 @@ test_dynamo_shard() {
test_inductor_distributed() {
# Smuggle a few multi-gpu tests here so that we don't have to request another large node
echo "Testing multi_gpu tests in test_torchinductor"
python test/run_test.py -i inductor/test_torchinductor.py -k test_multi_gpu --verbose
python test/run_test.py -i inductor/test_aot_inductor.py -k test_non_default_cuda_device --verbose
python test/run_test.py -i inductor/test_aot_inductor.py -k test_replicate_on_devices --verbose
python test/run_test.py -i distributed/test_c10d_functional_native.py --verbose
python test/run_test.py -i distributed/_tensor/test_dtensor_compile.py --verbose
python test/run_test.py -i distributed/tensor/parallel/test_micro_pipeline_tp.py --verbose
python test/run_test.py -i distributed/_composable/fsdp/test_fully_shard_comm.py --verbose
python test/run_test.py -i distributed/_composable/fsdp/test_fully_shard_training.py -k test_train_parity_multi_group --verbose
python test/run_test.py -i distributed/_composable/fsdp/test_fully_shard_training.py -k test_train_parity_with_activation_checkpointing --verbose
python test/run_test.py -i distributed/_composable/fsdp/test_fully_shard_training.py -k test_train_parity_hsdp --verbose
python test/run_test.py -i distributed/_composable/fsdp/test_fully_shard_training.py -k test_train_parity_2d_transformer_checkpoint_resume --verbose
python test/run_test.py -i distributed/_composable/fsdp/test_fully_shard_training.py -k test_gradient_accumulation --verbose
python test/run_test.py -i distributed/_composable/fsdp/test_fully_shard_state_dict.py -k test_dp_state_dict_save_load --verbose
python test/run_test.py -i distributed/_composable/fsdp/test_fully_shard_frozen.py --verbose
python test/run_test.py -i distributed/_composable/fsdp/test_fully_shard_mixed_precision.py -k test_compute_dtype --verbose
python test/run_test.py -i distributed/_composable/fsdp/test_fully_shard_mixed_precision.py -k test_reduce_dtype --verbose
python test/run_test.py -i distributed/_composable/fsdp/test_fully_shard_clip_grad_norm_.py -k test_clip_grad_norm_2d --verbose
python test/run_test.py -i distributed/fsdp/test_fsdp_tp_integration.py -k test_fsdp_tp_integration --verbose
pytest test/inductor/test_torchinductor.py -k test_multi_gpu
pytest test/inductor/test_aot_inductor.py -k test_non_default_cuda_device
pytest test/inductor/test_aot_inductor.py -k test_replicate_on_devices
pytest test/distributed/_tensor/test_dtensor_compile.py
pytest test/distributed/tensor/parallel/test_fsdp_2d_parallel.py
# this runs on both single-gpu and multi-gpu instance. It should be smart about skipping tests that aren't supported
# with if required # gpus aren't available
@ -339,57 +300,16 @@ test_inductor_distributed() {
assert_git_not_dirty
}
test_inductor_shard() {
if [[ -z "$NUM_TEST_SHARDS" ]]; then
echo "NUM_TEST_SHARDS must be defined to run a Python test shard"
exit 1
fi
test_inductor() {
python tools/dynamo/verify_dynamo.py
python test/run_test.py --inductor \
--include test_modules test_ops test_ops_gradients test_torch \
--shard "$1" "$NUM_TEST_SHARDS" \
--verbose
python test/run_test.py --inductor --include test_modules test_ops test_ops_gradients test_torch --verbose
# Do not add --inductor for the following inductor unit tests, otherwise we will fail because of nested dynamo state
python test/run_test.py \
--include inductor/test_torchinductor inductor/test_torchinductor_opinfo inductor/test_aot_inductor \
--shard "$1" "$NUM_TEST_SHARDS" \
--verbose
}
python test/run_test.py --include inductor/test_torchinductor inductor/test_torchinductor_opinfo --verbose
test_inductor_aoti() {
# docker build uses bdist_wheel which does not work with test_aot_inductor
# TODO: need a faster way to build
if [[ "$BUILD_ENVIRONMENT" == *rocm* ]]; then
# We need to hipify before building again
python3 tools/amd_build/build_amd.py
fi
BUILD_AOT_INDUCTOR_TEST=1 python setup.py develop
CPP_TESTS_DIR="${BUILD_BIN_DIR}" LD_LIBRARY_PATH="${TORCH_LIB_DIR}" python test/run_test.py --cpp --verbose -i cpp/test_aoti_abi_check cpp/test_aoti_inference
}
test_inductor_cpp_wrapper() {
export TORCHINDUCTOR_CPP_WRAPPER=1
TEST_REPORTS_DIR=$(pwd)/test/test-reports
mkdir -p "$TEST_REPORTS_DIR"
python benchmarks/dynamo/timm_models.py --device cuda --accuracy --amp \
--training --inductor --disable-cudagraphs --only vit_base_patch16_224 \
--output "$TEST_REPORTS_DIR/inductor_cpp_wrapper_training.csv"
python benchmarks/dynamo/check_accuracy.py \
--actual "$TEST_REPORTS_DIR/inductor_cpp_wrapper_training.csv" \
--expected "benchmarks/dynamo/ci_expected_accuracy/inductor_timm_training.csv"
python benchmarks/dynamo/torchbench.py --device cuda --accuracy \
--bfloat16 --inference --inductor --only hf_T5 --output "$TEST_REPORTS_DIR/inductor_cpp_wrapper_inference.csv"
python benchmarks/dynamo/torchbench.py --device cuda --accuracy \
--bfloat16 --inference --inductor --only llama --output "$TEST_REPORTS_DIR/inductor_cpp_wrapper_inference.csv"
python benchmarks/dynamo/torchbench.py --device cuda --accuracy \
--bfloat16 --inference --inductor --only moco --output "$TEST_REPORTS_DIR/inductor_cpp_wrapper_inference.csv"
python benchmarks/dynamo/check_accuracy.py \
--actual "$TEST_REPORTS_DIR/inductor_cpp_wrapper_inference.csv" \
--expected "benchmarks/dynamo/ci_expected_accuracy/inductor_torchbench_inference.csv"
CPP_TESTS_DIR="${BUILD_BIN_DIR}" LD_LIBRARY_PATH="${TORCH_LIB_DIR}" python test/run_test.py --cpp --verbose -i cpp/test_aot_inductor
}
# "Global" flags for inductor benchmarking controlled by TEST_CONFIG
@ -400,22 +320,7 @@ test_inductor_cpp_wrapper() {
# .github/workflows/inductor-perf-test-nightly.yml
DYNAMO_BENCHMARK_FLAGS=()
pr_time_benchmarks() {
pip_install --user "fbscribelogger"
TEST_REPORTS_DIR=$(pwd)/test/test-reports
mkdir -p "$TEST_REPORTS_DIR"
PYTHONPATH=$(pwd)/benchmarks/dynamo/pr_time_benchmarks source benchmarks/dynamo/pr_time_benchmarks/benchmark_runner.sh "$TEST_REPORTS_DIR/pr_time_benchmarks_results.csv" "benchmarks/dynamo/pr_time_benchmarks/benchmarks"
echo "benchmark results on current PR: "
cat "$TEST_REPORTS_DIR/pr_time_benchmarks_results.csv"
PYTHONPATH=$(pwd)/benchmarks/dynamo/pr_time_benchmarks python benchmarks/dynamo/pr_time_benchmarks/check_results.py "benchmarks/dynamo/pr_time_benchmarks/expected_results.csv" "$TEST_REPORTS_DIR/pr_time_benchmarks_results.csv" "$TEST_REPORTS_DIR/new_expected_results.csv"
}
if [[ "${TEST_CONFIG}" == *pr_time_benchmarks* ]]; then
pr_time_benchmarks
exit 0
elif [[ "${TEST_CONFIG}" == *dynamo_eager* ]]; then
if [[ "${TEST_CONFIG}" == *dynamo_eager* ]]; then
DYNAMO_BENCHMARK_FLAGS+=(--backend eager)
elif [[ "${TEST_CONFIG}" == *aot_eager* ]]; then
DYNAMO_BENCHMARK_FLAGS+=(--backend aot_eager)
@ -429,7 +334,7 @@ if [[ "${TEST_CONFIG}" == *dynamic* ]]; then
DYNAMO_BENCHMARK_FLAGS+=(--dynamic-shapes --dynamic-batch-only)
fi
if [[ "${TEST_CONFIG}" == *cpu* ]]; then
if [[ "${TEST_CONFIG}" == *cpu_inductor* ]]; then
DYNAMO_BENCHMARK_FLAGS+=(--device cpu)
else
DYNAMO_BENCHMARK_FLAGS+=(--device cuda)
@ -453,18 +358,6 @@ test_perf_for_dashboard() {
# TODO: All the accuracy tests can be skipped once the CI accuracy checking is stable enough
local targets=(accuracy performance)
local device=cuda
if [[ "${TEST_CONFIG}" == *cpu* ]]; then
if [[ "${TEST_CONFIG}" == *cpu_x86* ]]; then
device=cpu_x86
elif [[ "${TEST_CONFIG}" == *cpu_aarch64* ]]; then
device=cpu_aarch64
fi
test_inductor_set_cpu_affinity
elif [[ "${TEST_CONFIG}" == *cuda_a10g* ]]; then
device=cuda_a10g
fi
for mode in "${modes[@]}"; do
if [[ "$mode" == "inference" ]]; then
dtype=bfloat16
@ -480,62 +373,45 @@ test_perf_for_dashboard() {
fi
if [[ "$DASHBOARD_TAG" == *default-true* ]]; then
$TASKSET python "benchmarks/dynamo/$suite.py" \
python "benchmarks/dynamo/$suite.py" \
"${target_flag[@]}" --"$mode" --"$dtype" --backend "$backend" --disable-cudagraphs "$@" \
--output "$TEST_REPORTS_DIR/${backend}_no_cudagraphs_${suite}_${dtype}_${mode}_${device}_${target}.csv"
--output "$TEST_REPORTS_DIR/${backend}_no_cudagraphs_${suite}_${dtype}_${mode}_cuda_${target}.csv"
fi
if [[ "$DASHBOARD_TAG" == *cudagraphs-true* ]]; then
$TASKSET python "benchmarks/dynamo/$suite.py" \
python "benchmarks/dynamo/$suite.py" \
"${target_flag[@]}" --"$mode" --"$dtype" --backend "$backend" "$@" \
--output "$TEST_REPORTS_DIR/${backend}_with_cudagraphs_${suite}_${dtype}_${mode}_${device}_${target}.csv"
--output "$TEST_REPORTS_DIR/${backend}_with_cudagraphs_${suite}_${dtype}_${mode}_cuda_${target}.csv"
fi
if [[ "$DASHBOARD_TAG" == *dynamic-true* ]]; then
$TASKSET python "benchmarks/dynamo/$suite.py" \
python "benchmarks/dynamo/$suite.py" \
"${target_flag[@]}" --"$mode" --"$dtype" --backend "$backend" --dynamic-shapes \
--dynamic-batch-only "$@" \
--output "$TEST_REPORTS_DIR/${backend}_dynamic_${suite}_${dtype}_${mode}_${device}_${target}.csv"
--output "$TEST_REPORTS_DIR/${backend}_dynamic_${suite}_${dtype}_${mode}_cuda_${target}.csv"
fi
if [[ "$DASHBOARD_TAG" == *cppwrapper-true* ]] && [[ "$mode" == "inference" ]]; then
TORCHINDUCTOR_CPP_WRAPPER=1 $TASKSET python "benchmarks/dynamo/$suite.py" \
"${target_flag[@]}" --"$mode" --"$dtype" --backend "$backend" --disable-cudagraphs "$@" \
--output "$TEST_REPORTS_DIR/${backend}_cpp_wrapper_${suite}_${dtype}_${mode}_${device}_${target}.csv"
python "benchmarks/dynamo/$suite.py" \
"${target_flag[@]}" --"$mode" --"$dtype" --backend "$backend" --disable-cudagraphs --cpp-wrapper "$@" \
--output "$TEST_REPORTS_DIR/${backend}_cpp_wrapper_${suite}_${dtype}_${mode}_cuda_${target}.csv"
fi
if [[ "$DASHBOARD_TAG" == *freezing_cudagraphs-true* ]] && [[ "$mode" == "inference" ]]; then
$TASKSET python "benchmarks/dynamo/$suite.py" \
python "benchmarks/dynamo/$suite.py" \
"${target_flag[@]}" --"$mode" --"$dtype" --backend "$backend" "$@" --freezing \
--output "$TEST_REPORTS_DIR/${backend}_with_cudagraphs_freezing_${suite}_${dtype}_${mode}_${device}_${target}.csv"
--output "$TEST_REPORTS_DIR/${backend}_with_cudagraphs_freezing_${suite}_${dtype}_${mode}_cuda_${target}.csv"
fi
if [[ "$DASHBOARD_TAG" == *freeze_autotune_cudagraphs-true* ]] && [[ "$mode" == "inference" ]]; then
TORCHINDUCTOR_MAX_AUTOTUNE=1 $TASKSET python "benchmarks/dynamo/$suite.py" \
TORCHINDUCTOR_MAX_AUTOTUNE=1 python "benchmarks/dynamo/$suite.py" \
"${target_flag[@]}" --"$mode" --"$dtype" --backend "$backend" "$@" --freezing \
--output "$TEST_REPORTS_DIR/${backend}_with_cudagraphs_freezing_autotune_${suite}_${dtype}_${mode}_${device}_${target}.csv"
--output "$TEST_REPORTS_DIR/${backend}_with_cudagraphs_freezing_autotune_${suite}_${dtype}_${mode}_cuda_${target}.csv"
fi
if [[ "$DASHBOARD_TAG" == *aotinductor-true* ]] && [[ "$mode" == "inference" ]]; then
if [[ "$target" == "accuracy" ]]; then
# Also collect Export pass rate and display as a separate row
$TASKSET python "benchmarks/dynamo/$suite.py" \
"${target_flag[@]}" --"$mode" --"$dtype" --export --disable-cudagraphs "$@" \
--output "$TEST_REPORTS_DIR/${backend}_export_${suite}_${dtype}_${mode}_${device}_${target}.csv"
fi
$TASKSET python "benchmarks/dynamo/$suite.py" \
python "benchmarks/dynamo/$suite.py" \
"${target_flag[@]}" --"$mode" --"$dtype" --export-aot-inductor --disable-cudagraphs "$@" \
--output "$TEST_REPORTS_DIR/${backend}_aot_inductor_${suite}_${dtype}_${mode}_${device}_${target}.csv"
--output "$TEST_REPORTS_DIR/${backend}_aot_inductor_${suite}_${dtype}_${mode}_cuda_${target}.csv"
fi
if [[ "$DASHBOARD_TAG" == *maxautotune-true* ]]; then
TORCHINDUCTOR_MAX_AUTOTUNE=1 $TASKSET python "benchmarks/dynamo/$suite.py" \
TORCHINDUCTOR_MAX_AUTOTUNE=1 python "benchmarks/dynamo/$suite.py" \
"${target_flag[@]}" --"$mode" --"$dtype" --backend "$backend" "$@" \
--output "$TEST_REPORTS_DIR/${backend}_max_autotune_${suite}_${dtype}_${mode}_${device}_${target}.csv"
fi
if [[ "$DASHBOARD_TAG" == *cudagraphs_low_precision-true* ]] && [[ "$mode" == "inference" ]]; then
# TODO: This has a new dtype called quant and the benchmarks script needs to be updated to support this.
# The tentative command is as follows. It doesn't work now, but it's ok because we only need mock data
# to fill the dashboard.
$TASKSET python "benchmarks/dynamo/$suite.py" \
"${target_flag[@]}" --"$mode" --quant --backend "$backend" "$@" \
--output "$TEST_REPORTS_DIR/${backend}_cudagraphs_low_precision_${suite}_quant_${mode}_${device}_${target}.csv" || true
# Copy cudagraph results as mock data, easiest choice?
cp "$TEST_REPORTS_DIR/${backend}_with_cudagraphs_${suite}_${dtype}_${mode}_${device}_${target}.csv" \
"$TEST_REPORTS_DIR/${backend}_cudagraphs_low_precision_${suite}_quant_${mode}_${device}_${target}.csv"
--output "$TEST_REPORTS_DIR/${backend}_max_autotune_${suite}_${dtype}_${mode}_cuda_${target}.csv"
fi
done
done
@ -572,12 +448,6 @@ test_single_dynamo_benchmark() {
test_perf_for_dashboard "$suite" \
"${DYNAMO_BENCHMARK_FLAGS[@]}" "$@" "${partition_flags[@]}"
else
if [[ "${TEST_CONFIG}" == *_avx2* ]]; then
TEST_CONFIG=${TEST_CONFIG//_avx2/}
fi
if [[ "${TEST_CONFIG}" == *_avx512* ]]; then
TEST_CONFIG=${TEST_CONFIG//_avx512/}
fi
python "benchmarks/dynamo/$suite.py" \
--ci --accuracy --timing --explain \
"${DYNAMO_BENCHMARK_FLAGS[@]}" \
@ -592,24 +462,6 @@ test_single_dynamo_benchmark() {
fi
}
test_inductor_micro_benchmark() {
TEST_REPORTS_DIR=$(pwd)/test/test-reports
if [[ "${TEST_CONFIG}" == *cpu* ]]; then
test_inductor_set_cpu_affinity
fi
python benchmarks/gpt_fast/benchmark.py --output "${TEST_REPORTS_DIR}/gpt_fast_benchmark.csv"
}
test_inductor_halide() {
python test/run_test.py --include inductor/test_halide.py --verbose
assert_git_not_dirty
}
test_inductor_triton_cpu() {
python test/run_test.py --include inductor/test_triton_cpu_backend.py --verbose
assert_git_not_dirty
}
test_dynamo_benchmark() {
# Usage: test_dynamo_benchmark huggingface 0
TEST_REPORTS_DIR=$(pwd)/test/test-reports
@ -624,16 +476,8 @@ test_dynamo_benchmark() {
elif [[ "${TEST_CONFIG}" == *perf* ]]; then
test_single_dynamo_benchmark "dashboard" "$suite" "$shard_id" "$@"
else
if [[ "${TEST_CONFIG}" == *cpu* ]]; then
local dt="float32"
if [[ "${TEST_CONFIG}" == *amp* ]]; then
dt="amp"
fi
if [[ "${TEST_CONFIG}" == *freezing* ]]; then
test_single_dynamo_benchmark "inference" "$suite" "$shard_id" --inference --"$dt" --freezing "$@"
else
test_single_dynamo_benchmark "inference" "$suite" "$shard_id" --inference --"$dt" "$@"
fi
if [[ "${TEST_CONFIG}" == *cpu_inductor* ]]; then
test_single_dynamo_benchmark "inference" "$suite" "$shard_id" --inference --float32 "$@"
elif [[ "${TEST_CONFIG}" == *aot_inductor* ]]; then
test_single_dynamo_benchmark "inference" "$suite" "$shard_id" --inference --bfloat16 "$@"
else
@ -653,6 +497,11 @@ test_inductor_torchbench_smoketest_perf() {
# The threshold value needs to be actively maintained to make this check useful
python benchmarks/dynamo/check_perf_csv.py -f "$TEST_REPORTS_DIR/inductor_training_smoketest.csv" -t 1.4
python benchmarks/dynamo/torchbench.py --device cuda --performance --bfloat16 --inference \
--export-aot-inductor --only nanogpt --output "$TEST_REPORTS_DIR/inductor_inference_smoketest.csv"
# The threshold value needs to be actively maintained to make this check useful
python benchmarks/dynamo/check_perf_csv.py -f "$TEST_REPORTS_DIR/inductor_inference_smoketest.csv" -t 5.2
# Check memory compression ratio for a few models
for test in hf_Albert timm_vision_transformer; do
python benchmarks/dynamo/torchbench.py --device cuda --performance --backend inductor --amp --training \
@ -663,88 +512,6 @@ test_inductor_torchbench_smoketest_perf() {
"$TEST_REPORTS_DIR/inductor_training_smoketest_$test.csv" \
--expected benchmarks/dynamo/expected_ci_perf_inductor_torchbench.csv
done
# Perform some "warm-start" runs for a few huggingface models.
for test in AlbertForQuestionAnswering AllenaiLongformerBase DistilBertForMaskedLM DistillGPT2 GoogleFnet YituTechConvBert; do
python benchmarks/dynamo/huggingface.py --accuracy --training --amp --inductor --device cuda --warm-start-latency \
--only $test --output "$TEST_REPORTS_DIR/inductor_warm_start_smoketest_$test.csv"
python benchmarks/dynamo/check_accuracy.py \
--actual "$TEST_REPORTS_DIR/inductor_warm_start_smoketest_$test.csv" \
--expected "benchmarks/dynamo/ci_expected_accuracy/inductor_huggingface_training.csv"
done
}
test_inductor_get_core_number() {
if [[ "${TEST_CONFIG}" == *aarch64* ]]; then
echo "$(($(lscpu | grep 'Cluster(s):' | awk '{print $2}') * $(lscpu | grep 'Core(s) per cluster:' | awk '{print $4}')))"
else
echo "$(($(lscpu | grep 'Socket(s):' | awk '{print $2}') * $(lscpu | grep 'Core(s) per socket:' | awk '{print $4}')))"
fi
}
test_inductor_set_cpu_affinity(){
#set jemalloc
JEMALLOC_LIB="$(find /usr/lib -name libjemalloc.so.2)"
export LD_PRELOAD="$JEMALLOC_LIB":"$LD_PRELOAD"
export MALLOC_CONF="oversize_threshold:1,background_thread:true,metadata_thp:auto,dirty_decay_ms:-1,muzzy_decay_ms:-1"
if [[ "${TEST_CONFIG}" != *aarch64* ]]; then
# Use Intel OpenMP for x86
IOMP_LIB="$(dirname "$(which python)")/../lib/libiomp5.so"
export LD_PRELOAD="$IOMP_LIB":"$LD_PRELOAD"
export KMP_AFFINITY=granularity=fine,compact,1,0
export KMP_BLOCKTIME=1
fi
cores=$(test_inductor_get_core_number)
# Set number of cores to 16 on Aarch64 for performance runs.
if [[ "${TEST_CONFIG}" == *aarch64* && $cores -gt 16 ]]; then
cores=16
fi
export OMP_NUM_THREADS=$cores
end_core=$((cores-1))
export TASKSET="taskset -c 0-$end_core"
}
test_inductor_torchbench_cpu_smoketest_perf(){
TEST_REPORTS_DIR=$(pwd)/test/test-reports
mkdir -p "$TEST_REPORTS_DIR"
test_inductor_set_cpu_affinity
MODELS_SPEEDUP_TARGET=benchmarks/dynamo/expected_ci_speedup_inductor_torchbench_cpu.csv
grep -v '^ *#' < "$MODELS_SPEEDUP_TARGET" | while IFS=',' read -r -a model_cfg
do
local model_name=${model_cfg[0]}
local data_type=${model_cfg[2]}
local speedup_target=${model_cfg[5]}
local backend=${model_cfg[1]}
if [[ ${model_cfg[4]} == "cpp" ]]; then
export TORCHINDUCTOR_CPP_WRAPPER=1
else
unset TORCHINDUCTOR_CPP_WRAPPER
fi
local output_name="$TEST_REPORTS_DIR/inductor_inference_${model_cfg[0]}_${model_cfg[1]}_${model_cfg[2]}_${model_cfg[3]}_cpu_smoketest.csv"
if [[ ${model_cfg[3]} == "dynamic" ]]; then
$TASKSET python benchmarks/dynamo/torchbench.py \
--inference --performance --"$data_type" -dcpu -n50 --only "$model_name" --dynamic-shapes \
--dynamic-batch-only --freezing --timeout 9000 --"$backend" --output "$output_name"
else
$TASKSET python benchmarks/dynamo/torchbench.py \
--inference --performance --"$data_type" -dcpu -n50 --only "$model_name" \
--freezing --timeout 9000 --"$backend" --output "$output_name"
fi
cat "$output_name"
# The threshold value needs to be actively maintained to make this check useful.
# Allow 1% variance for CPU perf to accommodate perf fluctuation
python benchmarks/dynamo/check_perf_csv.py -f "$output_name" -t "$speedup_target" -s 0.99
done
}
test_torchbench_gcp_smoketest(){
pushd "${TORCHBENCHPATH}"
python test.py -v
popd
}
test_python_gloo_with_tls() {
@ -778,6 +545,7 @@ test_aten() {
${SUDO} ln -sf "$TORCH_LIB_DIR"/libmkldnn* "$TEST_BASE_DIR"
${SUDO} ln -sf "$TORCH_LIB_DIR"/libnccl* "$TEST_BASE_DIR"
${SUDO} ln -sf "$TORCH_LIB_DIR"/libtorch* "$TEST_BASE_DIR"
${SUDO} ln -sf "$TORCH_LIB_DIR"/libtbb* "$TEST_BASE_DIR"
ls "$TEST_BASE_DIR"
aten/tools/run_tests.sh "$TEST_BASE_DIR"
@ -802,6 +570,21 @@ test_without_numpy() {
popd
}
# pytorch extensions require including torch/extension.h which includes all.h
# which includes utils.h which includes Parallel.h.
# So you can call for instance parallel_for() from your extension,
# but the compilation will fail because of Parallel.h has only declarations
# and definitions are conditionally included Parallel.h(see last lines of Parallel.h).
# I tried to solve it #39612 and #39881 by including Config.h into Parallel.h
# But if Pytorch is built with TBB it provides Config.h
# that has AT_PARALLEL_NATIVE_TBB=1(see #3961 or #39881) and it means that if you include
# torch/extension.h which transitively includes Parallel.h
# which transitively includes tbb.h which is not available!
if [[ "${BUILD_ENVIRONMENT}" == *tbb* ]]; then
sudo mkdir -p /usr/include/tbb
sudo cp -r "$PWD"/third_party/tbb/include/tbb/* /usr/include/tbb
fi
test_libtorch() {
local SHARD="$1"
@ -815,6 +598,7 @@ test_libtorch() {
ln -sf "$TORCH_LIB_DIR"/libc10* "$TORCH_BIN_DIR"
ln -sf "$TORCH_LIB_DIR"/libshm* "$TORCH_BIN_DIR"
ln -sf "$TORCH_LIB_DIR"/libtorch* "$TORCH_BIN_DIR"
ln -sf "$TORCH_LIB_DIR"/libtbb* "$TORCH_BIN_DIR"
ln -sf "$TORCH_LIB_DIR"/libnvfuser* "$TORCH_BIN_DIR"
export CPP_TESTS_DIR="${TORCH_BIN_DIR}"
@ -876,19 +660,6 @@ test_libtorch_api() {
fi
}
test_xpu_bin(){
TEST_REPORTS_DIR=$(pwd)/test/test-reports
mkdir -p "$TEST_REPORTS_DIR"
for xpu_case in "${BUILD_BIN_DIR}"/*{xpu,sycl}*; do
if [[ "$xpu_case" != *"*"* && "$xpu_case" != *.so && "$xpu_case" != *.a ]]; then
case_name=$(basename "$xpu_case")
echo "Testing ${case_name} ..."
"$xpu_case" --gtest_output=xml:"$TEST_REPORTS_DIR"/"$case_name".xml
fi
done
}
test_aot_compilation() {
echo "Testing Ahead of Time compilation"
ln -sf "$TORCH_LIB_DIR"/libc10* "$TORCH_BIN_DIR"
@ -951,6 +722,7 @@ test_rpc() {
# test reporting process to function as expected.
ln -sf "$TORCH_LIB_DIR"/libtorch* "$TORCH_BIN_DIR"
ln -sf "$TORCH_LIB_DIR"/libc10* "$TORCH_BIN_DIR"
ln -sf "$TORCH_LIB_DIR"/libtbb* "$TORCH_BIN_DIR"
CPP_TESTS_DIR="${TORCH_BIN_DIR}" python test/run_test.py --cpp --verbose -i cpp/test_cpp_rpc
}
@ -1052,113 +824,11 @@ test_xla() {
assert_git_not_dirty
}
function check_public_api_test_fails {
test_name=$1
invalid_item_name=$2
invalid_item_desc=$3
echo "Running public API test '${test_name}'..."
test_output=$(python test/test_public_bindings.py -k "${test_name}" 2>&1) && ret=$? || ret=$?
# Ensure test fails correctly.
if [ "$ret" -eq 0 ]; then
cat << EOF
Expected the public API test '${test_name}' to fail after introducing
${invalid_item_desc}, but it succeeded! Check test/test_public_bindings.py
for any changes that may have broken the test.
EOF
return 1
fi
# Ensure invalid item is in the test output.
echo "${test_output}" | grep -q "${invalid_item_name}" && ret=$? || ret=$?
if [ $ret -ne 0 ]; then
cat << EOF
Expected the public API test '${test_name}' to identify ${invalid_item_desc}, but
it didn't! It's possible the test may not have run. Check test/test_public_bindings.py
for any changes that may have broken the test.
EOF
return 1
fi
echo "Success! '${test_name}' identified ${invalid_item_desc} ${invalid_item_name}."
return 0
}
# Do NOT run this test before any other tests, like test_python_shard, etc.
# Because this function uninstalls the torch built from branch and installs
# the torch built on its base commit.
test_forward_backward_compatibility() {
set -x
# First, validate public API tests in the torch built from branch.
# Step 1. Make sure the public API test "test_correct_module_names" fails when a new file
# introduces an invalid public API function.
new_filename=$(mktemp XXXXXXXX.py -p "${TORCH_INSTALL_DIR}")
BAD_PUBLIC_FUNC=$(
cat << 'EOF'
def new_public_func():
pass
# valid public API functions have __module__ set correctly
new_public_func.__module__ = None
EOF
)
echo "${BAD_PUBLIC_FUNC}" >> "${new_filename}"
invalid_api="torch.$(basename -s '.py' "${new_filename}").new_public_func"
echo "Created an invalid public API function ${invalid_api}..."
check_public_api_test_fails \
"test_correct_module_names" \
"${invalid_api}" \
"an invalid public API function" && ret=$? || ret=$?
rm -v "${new_filename}"
if [ "$ret" -ne 0 ]; then
exit 1
fi
# Step 2. Make sure that the public API test "test_correct_module_names" fails when an existing
# file is modified to introduce an invalid public API function.
EXISTING_FILEPATH="${TORCH_INSTALL_DIR}/nn/parameter.py"
cp -v "${EXISTING_FILEPATH}" "${EXISTING_FILEPATH}.orig"
echo "${BAD_PUBLIC_FUNC}" >> "${EXISTING_FILEPATH}"
invalid_api="torch.nn.parameter.new_public_func"
echo "Appended an invalid public API function to existing file ${EXISTING_FILEPATH}..."
check_public_api_test_fails \
"test_correct_module_names" \
"${invalid_api}" \
"an invalid public API function" && ret=$? || ret=$?
mv -v "${EXISTING_FILEPATH}.orig" "${EXISTING_FILEPATH}"
if [ "$ret" -ne 0 ]; then
exit 1
fi
# Step 3. Make sure that the public API test "test_modules_can_be_imported" fails when a module
# cannot be imported.
new_module_dir=$(mktemp XXXXXXXX -d -p "${TORCH_INSTALL_DIR}")
echo "invalid syntax garbage" > "${new_module_dir}/__init__.py"
invalid_module_name="torch.$(basename "${new_module_dir}")"
check_public_api_test_fails \
"test_modules_can_be_imported" \
"${invalid_module_name}" \
"a non-importable module" && ret=$? || ret=$?
rm -rv "${new_module_dir}"
if [ "$ret" -ne 0 ]; then
exit 1
fi
# Next, build torch from the merge base.
REPO_DIR=$(pwd)
if [[ "${BASE_SHA}" == "${SHA1}" ]]; then
echo "On trunk, we should compare schemas with torch built from the parent commit"
@ -1230,8 +900,7 @@ test_bazel() {
tools/bazel test --config=cpu-only --test_timeout=480 --test_output=all --test_tag_filters=-gpu-required --test_filter=-*CUDA :all_tests
else
# Increase the test timeout to 480 like CPU tests because modules_test frequently timeout
tools/bazel test --test_timeout=480 --test_output=errors \
tools/bazel test --test_output=errors \
//:any_test \
//:autograd_test \
//:dataloader_test \
@ -1326,27 +995,18 @@ test_docs_test() {
}
test_executorch() {
echo "Install torchvision and torchaudio"
install_torchvision
install_torchaudio
pushd /executorch
export PYTHON_EXECUTABLE=python
export EXECUTORCH_BUILD_PYBIND=ON
export CMAKE_ARGS="-DEXECUTORCH_BUILD_XNNPACK=ON -DEXECUTORCH_BUILD_KERNELS_QUANTIZED=ON"
# NB: We need to rebuild ExecuTorch runner here because it depends on PyTorch
# from the PR
# shellcheck disable=SC1091
source .ci/scripts/setup-linux.sh cmake
echo "Run ExecuTorch unit tests"
pytest -v -n auto
# shellcheck disable=SC1091
LLVM_PROFDATA=llvm-profdata-12 LLVM_COV=llvm-cov-12 bash test/run_oss_cpp_tests.sh
echo "Install torchvision and torchaudio"
# TODO(huydhn): Switch this to the pinned commits on ExecuTorch once they are
# there. These libraries need to be built here, and not part of the Docker
# image because they require the target version of torch to be installed first
pip_install --no-use-pep517 --user "git+https://github.com/pytorch/audio.git"
pip_install --no-use-pep517 --user "git+https://github.com/pytorch/vision.git"
echo "Run ExecuTorch regression tests for some models"
# NB: This is a sample model, more can be added here
export PYTHON_EXECUTABLE=python
# TODO(huydhn): Add more coverage here using ExecuTorch's gather models script
# shellcheck disable=SC1091
source .ci/scripts/test.sh mv3 cmake xnnpack-quantization-delegation ''
@ -1360,36 +1020,11 @@ test_executorch() {
assert_git_not_dirty
}
test_linux_aarch64() {
python test/run_test.py --include test_modules test_mkldnn test_mkldnn_fusion test_openmp test_torch test_dynamic_shapes \
test_transformers test_multiprocessing test_numpy_interop \
--shard "$SHARD_NUMBER" "$NUM_TEST_SHARDS" --verbose
# Dynamo tests
python test/run_test.py --include dynamo/test_compile dynamo/test_backends dynamo/test_comptime dynamo/test_config \
dynamo/test_functions dynamo/test_fx_passes_pre_grad dynamo/test_interop dynamo/test_model_output dynamo/test_modules \
dynamo/test_optimizers dynamo/test_recompile_ux dynamo/test_recompiles \
--shard "$SHARD_NUMBER" "$NUM_TEST_SHARDS" --verbose
# Inductor tests
python test/run_test.py --include inductor/test_torchinductor inductor/test_benchmark_fusion inductor/test_codecache \
inductor/test_config inductor/test_control_flow inductor/test_coordinate_descent_tuner inductor/test_fx_fusion \
inductor/test_group_batch_fusion inductor/test_inductor_freezing inductor/test_inductor_utils \
inductor/test_inplacing_pass inductor/test_kernel_benchmark inductor/test_layout_optim \
inductor/test_max_autotune inductor/test_memory_planning inductor/test_metrics inductor/test_multi_kernel inductor/test_pad_mm \
inductor/test_pattern_matcher inductor/test_perf inductor/test_profiler inductor/test_select_algorithm inductor/test_smoke \
inductor/test_split_cat_fx_passes inductor/test_standalone_compile inductor/test_torchinductor \
inductor/test_torchinductor_codegen_dynamic_shapes inductor/test_torchinductor_dynamic_shapes inductor/test_memory \
--shard "$SHARD_NUMBER" "$NUM_TEST_SHARDS" --verbose
}
if ! [[ "${BUILD_ENVIRONMENT}" == *libtorch* || "${BUILD_ENVIRONMENT}" == *-bazel-* ]]; then
(cd test && python -c "import torch; print(torch.__config__.show())")
(cd test && python -c "import torch; print(torch.__config__.parallel_info())")
fi
if [[ "${BUILD_ENVIRONMENT}" == *aarch64* && "${TEST_CONFIG}" != *perf_cpu_aarch64* ]]; then
test_linux_aarch64
elif [[ "${TEST_CONFIG}" == *backward* ]]; then
if [[ "${TEST_CONFIG}" == *backward* ]]; then
test_forward_backward_compatibility
# Do NOT add tests after bc check tests, see its comment.
elif [[ "${TEST_CONFIG}" == *xla* ]]; then
@ -1409,14 +1044,11 @@ elif [[ "$TEST_CONFIG" == distributed ]]; then
if [[ "${SHARD_NUMBER}" == 1 ]]; then
test_rpc
fi
elif [[ "$TEST_CONFIG" == deploy ]]; then
checkout_install_torchdeploy
test_torch_deploy
elif [[ "${TEST_CONFIG}" == *inductor_distributed* ]]; then
test_inductor_distributed
elif [[ "${TEST_CONFIG}" == *inductor-halide* ]]; then
test_inductor_halide
elif [[ "${TEST_CONFIG}" == *inductor-triton-cpu* ]]; then
test_inductor_triton_cpu
elif [[ "${TEST_CONFIG}" == *inductor-micro-benchmark* ]]; then
test_inductor_micro_benchmark
elif [[ "${TEST_CONFIG}" == *huggingface* ]]; then
install_torchvision
id=$((SHARD_NUMBER-1))
@ -1426,68 +1058,46 @@ elif [[ "${TEST_CONFIG}" == *timm* ]]; then
id=$((SHARD_NUMBER-1))
test_dynamo_benchmark timm_models "$id"
elif [[ "${TEST_CONFIG}" == *torchbench* ]]; then
if [[ "${TEST_CONFIG}" == *cpu* ]]; then
if [[ "${TEST_CONFIG}" == *cpu_inductor* ]]; then
install_torchaudio cpu
else
install_torchaudio cuda
fi
install_torchtext
install_torchvision
TORCH_CUDA_ARCH_LIST="8.0;8.6" pip_install git+https://github.com/pytorch/ao.git
id=$((SHARD_NUMBER-1))
# https://github.com/opencv/opencv-python/issues/885
pip_install opencv-python==4.8.0.74
if [[ "${TEST_CONFIG}" == *inductor_torchbench_smoketest_perf* ]]; then
checkout_install_torchbench hf_Bert hf_Albert timm_vision_transformer
PYTHONPATH=$(pwd)/torchbench test_inductor_torchbench_smoketest_perf
elif [[ "${TEST_CONFIG}" == *inductor_torchbench_cpu_smoketest_perf* ]]; then
checkout_install_torchbench timm_vision_transformer phlippe_densenet basic_gnn_edgecnn \
llama_v2_7b_16h resnet50 timm_efficientnet mobilenet_v3_large timm_resnest \
functorch_maml_omniglot yolov3 mobilenet_v2 resnext50_32x4d densenet121 mnasnet1_0
PYTHONPATH=$(pwd)/torchbench test_inductor_torchbench_cpu_smoketest_perf
elif [[ "${TEST_CONFIG}" == *torchbench_gcp_smoketest* ]]; then
checkout_install_torchbench
TORCHBENCHPATH=$(pwd)/torchbench test_torchbench_gcp_smoketest
else
checkout_install_torchbench
# Do this after checkout_install_torchbench to ensure we clobber any
# nightlies that torchbench may pull in
if [[ "${TEST_CONFIG}" != *cpu* ]]; then
if [[ "${TEST_CONFIG}" != *cpu_inductor* ]]; then
install_torchrec_and_fbgemm
fi
PYTHONPATH=$(pwd)/torchbench test_dynamo_benchmark torchbench "$id"
fi
elif [[ "${TEST_CONFIG}" == *inductor_cpp_wrapper* ]]; then
install_torchaudio cuda
elif [[ "${TEST_CONFIG}" == *inductor* && "${SHARD_NUMBER}" == 1 ]]; then
install_torchvision
checkout_install_torchbench hf_T5 llama moco
PYTHONPATH=$(pwd)/torchbench test_inductor_cpp_wrapper
elif [[ "${TEST_CONFIG}" == *inductor* ]]; then
test_inductor
test_inductor_distributed
elif [[ "${TEST_CONFIG}" == *dynamo* && "${SHARD_NUMBER}" == 1 && $NUM_TEST_SHARDS -gt 1 ]]; then
test_without_numpy
install_torchvision
test_inductor_shard "${SHARD_NUMBER}"
if [[ "${SHARD_NUMBER}" == 1 ]]; then
if [[ "${BUILD_ENVIRONMENT}" != linux-jammy-py3.9-gcc11-build ]]; then
test_inductor_distributed
fi
fi
elif [[ "${TEST_CONFIG}" == *dynamo* ]]; then
install_torchvision
test_dynamo_shard "${SHARD_NUMBER}"
if [[ "${SHARD_NUMBER}" == 1 ]]; then
test_aten
fi
elif [[ "${BUILD_ENVIRONMENT}" == *rocm* && -n "$TESTS_TO_INCLUDE" ]]; then
install_torchvision
test_python_shard "$SHARD_NUMBER"
test_dynamo_shard 1
test_aten
elif [[ "${TEST_CONFIG}" == *dynamo* && "${SHARD_NUMBER}" == 2 && $NUM_TEST_SHARDS -gt 1 ]]; then
install_torchvision
test_dynamo_shard 2
elif [[ "${SHARD_NUMBER}" == 1 && $NUM_TEST_SHARDS -gt 1 ]]; then
test_without_numpy
install_torchvision
test_python_shard 1
test_aten
test_libtorch 1
if [[ "${BUILD_ENVIRONMENT}" == *xpu* ]]; then
test_xpu_bin
fi
elif [[ "${SHARD_NUMBER}" == 2 && $NUM_TEST_SHARDS -gt 1 ]]; then
install_torchvision
test_python_shard 2
@ -1508,11 +1118,10 @@ elif [[ "${BUILD_ENVIRONMENT}" == *-mobile-lightweight-dispatch* ]]; then
test_libtorch
elif [[ "${TEST_CONFIG}" = docs_test ]]; then
test_docs_test
elif [[ "${BUILD_ENVIRONMENT}" == *xpu* ]]; then
elif [[ "${BUILD_ENVIRONMENT}" == *rocm* && -n "$TESTS_TO_INCLUDE" ]]; then
install_torchvision
test_python
test_aten
test_xpu_bin
else
install_torchvision
install_monkeytype

View File

@ -26,7 +26,7 @@ fi
export SCRIPT_HELPERS_DIR=$SCRIPT_PARENT_DIR/win-test-helpers
set +ex
grep -E -R 'PyLong_(From|As)(Unsigned|)Long\(' --exclude=python_numbers.h --exclude=pythoncapi_compat.h --exclude=eval_frame.c torch/
grep -E -R 'PyLong_(From|As)(Unsigned|)Long\(' --exclude=python_numbers.h --exclude=eval_frame.c torch/
PYLONG_API_CHECK=$?
if [[ $PYLONG_API_CHECK == 0 ]]; then
echo "Usage of PyLong_{From,As}{Unsigned}Long API may lead to overflow errors on Windows"

View File

@ -16,29 +16,24 @@ set PATH=C:\Program Files\CMake\bin;C:\Program Files\7-Zip;C:\ProgramData\chocol
set INSTALLER_DIR=%SCRIPT_HELPERS_DIR%\installation-helpers
call %INSTALLER_DIR%\install_mkl.bat
if errorlevel 1 exit /b
if not errorlevel 0 exit /b
call %INSTALLER_DIR%\install_magma.bat
if errorlevel 1 goto fail
if not errorlevel 0 goto fail
if errorlevel 1 exit /b
if not errorlevel 0 exit /b
call %INSTALLER_DIR%\install_sccache.bat
if errorlevel 1 goto fail
if not errorlevel 0 goto fail
if "%USE_XPU%"=="1" (
:: Install xpu support packages
call %INSTALLER_DIR%\install_xpu.bat
if errorlevel 1 exit /b 1
)
if errorlevel 1 exit /b
if not errorlevel 0 exit /b
:: Miniconda has been installed as part of the Windows AMI with all the dependencies.
:: We just need to activate it here
call %INSTALLER_DIR%\activate_miniconda3.bat
if errorlevel 1 goto fail
if not errorlevel 0 goto fail
call pip install mkl-include==2021.4.0 mkl-devel==2021.4.0
if errorlevel 1 goto fail
if not errorlevel 0 goto fail
if errorlevel 1 exit /b
if not errorlevel 0 exit /b
:: Override VS env here
pushd .
@ -47,18 +42,8 @@ if "%VC_VERSION%" == "" (
) else (
call "C:\Program Files (x86)\Microsoft Visual Studio\%VC_YEAR%\%VC_PRODUCT%\VC\Auxiliary\Build\vcvarsall.bat" x64 -vcvars_ver=%VC_VERSION%
)
if errorlevel 1 goto fail
if not errorlevel 0 goto fail
if "%USE_XPU%"=="1" (
:: Activate xpu environment - VS env is required for xpu
call "C:\Program Files (x86)\Intel\oneAPI\setvars.bat"
if errorlevel 1 exit /b 1
:: Reduce build time. Only have MTL self-hosted runner now
SET TORCH_XPU_ARCH_LIST=xe-lpg
SET USE_KINETO=0
)
if errorlevel 1 exit /b
if not errorlevel 0 exit /b
@echo on
popd
@ -68,12 +53,12 @@ set CUDA_PATH=C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v%CUDA_VERSION%
if x%CUDA_VERSION:.=%==x%CUDA_VERSION% (
echo CUDA version %CUDA_VERSION% format isn't correct, which doesn't contain '.'
goto fail
exit /b 1
)
rem version transformer, for example 10.1 to 10_1.
if x%CUDA_VERSION:.=%==x%CUDA_VERSION% (
echo CUDA version %CUDA_VERSION% format isn't correct, which doesn't contain '.'
goto fail
exit /b 1
)
set VERSION_SUFFIX=%CUDA_VERSION:.=_%
set CUDA_PATH_V%VERSION_SUFFIX%=%CUDA_PATH%
@ -81,6 +66,13 @@ set CUDA_PATH_V%VERSION_SUFFIX%=%CUDA_PATH%
set CUDNN_LIB_DIR=%CUDA_PATH%\lib\x64
set CUDA_TOOLKIT_ROOT_DIR=%CUDA_PATH%
set CUDNN_ROOT_DIR=%CUDA_PATH%
set NVTOOLSEXT_PATH=C:\Program Files\NVIDIA Corporation\NvToolsExt
set PATH=%CUDA_PATH%\bin;%CUDA_PATH%\libnvvp;%PATH%
set CUDNN_LIB_DIR=%CUDA_PATH%\lib\x64
set CUDA_TOOLKIT_ROOT_DIR=%CUDA_PATH%
set CUDNN_ROOT_DIR=%CUDA_PATH%
set NVTOOLSEXT_PATH=C:\Program Files\NVIDIA Corporation\NvToolsExt
set PATH=%CUDA_PATH%\bin;%CUDA_PATH%\libnvvp;%PATH%
:cuda_build_end
@ -97,8 +89,8 @@ set SCCACHE_IGNORE_SERVER_IO_ERROR=1
sccache --stop-server
sccache --start-server
sccache --zero-stats
set CMAKE_C_COMPILER_LAUNCHER=sccache
set CMAKE_CXX_COMPILER_LAUNCHER=sccache
set CC=sccache-cl
set CXX=sccache-cl
set CMAKE_GENERATOR=Ninja
@ -110,8 +102,8 @@ if "%USE_CUDA%"=="1" (
:: CMake requires a single command as CUDA_NVCC_EXECUTABLE, so we push the wrappers
:: randomtemp.exe and sccache.exe into a batch file which CMake invokes.
curl -kL https://github.com/peterjc123/randomtemp-rust/releases/download/v0.4/randomtemp.exe --output %TMP_DIR_WIN%\bin\randomtemp.exe
if errorlevel 1 goto fail
if not errorlevel 0 goto fail
if errorlevel 1 exit /b
if not errorlevel 0 exit /b
echo @"%TMP_DIR_WIN%\bin\randomtemp.exe" "%TMP_DIR_WIN%\bin\sccache.exe" "%CUDA_PATH%\bin\nvcc.exe" %%* > "%TMP_DIR%/bin/nvcc.bat"
cat %TMP_DIR%/bin/nvcc.bat
set CUDA_NVCC_EXECUTABLE=%TMP_DIR%/bin/nvcc.bat
@ -123,8 +115,8 @@ if "%USE_CUDA%"=="1" (
set
python setup.py bdist_wheel
if errorlevel 1 goto fail
if not errorlevel 0 goto fail
if errorlevel 1 exit /b
if not errorlevel 0 exit /b
sccache --show-stats
python -c "import os, glob; os.system('python -mpip install --no-index --no-deps ' + glob.glob('dist/*.whl')[0])"
(
@ -144,8 +136,3 @@ python -c "import os, glob; os.system('python -mpip install --no-index --no-deps
sccache --show-stats --stats-format json | jq .stats > sccache-stats-%BUILD_ENVIRONMENT%-%OUR_GITHUB_JOB_ID%.json
sccache --stop-server
exit /b 0
:fail
exit /b 1

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