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Author SHA1 Message Date
c04134cdb1 [ROCM] Restrict pytorch rocm to only use triton 2.0.x (#95793) (#95834)
To align with upstream, we are requiring triton dependency to be between 2.0.0 and 2.1.  This will allow PyTorch 2.0 on ROCM to stay flexible enough to pick up any performance/stability improvements from Triton, without needing to cut a separate PyTorch version.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/95793
Approved by: https://github.com/huydhn
2023-03-01 19:10:00 -05:00
72d0863ab2 [BE] Fix TORCH_WARN_ONCE (#95559) (#95822)
It does not take a condition as first argument, unlike `TORCH_CHECK`
Test plan, run: ` python3 -c "import torch;print(torch.arange(1., 10.,device='mps').view(3, 3).trace())"` and observe no warning

Pull Request resolved: https://github.com/pytorch/pytorch/pull/95559
Approved by: https://github.com/Skylion007

(cherry picked from commit 9bca9df42b5898e45e2a80e03a4a4ba9a6fe654a)
2023-03-01 19:03:41 -05:00
1bd334dc25 Update copyright (#95652) (#95700)
Updating the copyright to reflect on the website.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/95652
Approved by: https://github.com/atalman

Co-authored-by: Svetlana Karslioglu <svekars@fb.com>
2023-02-28 11:00:18 -05:00
93e13cd429 [MPS] Remove FFT from the fallback as its causing crashes in test_ops and TestConsistency tests. (#95625) 2023-02-27 17:26:32 -08:00
4e4d4b0afe [MPS] Add TORCH_CHECK for Convolution (#95495)
* Raise errors for Conv and remove FFTs from Fallback list.

* Move the FFT to a separate commit.
2023-02-27 17:25:14 -08:00
Wei
c4fa850827 Reserve the tensorrt backend name for torch-tensorrt (#95627) 2023-02-27 17:17:47 -08:00
36ead09873 Add float to list of allowed ops (#94910) (#95661)
By adding `BINFLOAT` op support

Fixes https://github.com/pytorch/pytorch/issues/94670
Pull Request resolved: https://github.com/pytorch/pytorch/pull/94910
Approved by: https://github.com/albanD

Co-authored-by: Nikita Shulga <nshulga@meta.com>
2023-02-27 15:09:00 -08:00
66d23dbad7 fix spurious aot autograd warning (#95521) (#95614)
The _make_boxed logic probably needs a cleanup, but this fixes a spurious warning that we should get in before the release.

Confirmed that this used to emit a warning and no longer does:
```
import torch

lin = torch.nn.Linear(100, 10)
def f(x):
    return lin(x)

opt_f = torch.compile(f)
opt_f(torch.randn(10, 100, requires_grad=False))
```

Pull Request resolved: https://github.com/pytorch/pytorch/pull/95521
Approved by: https://github.com/ngimel
2023-02-27 14:31:02 -05:00
e2fff58844 [CUDA][CUBLAS] Explicitly link against cuBLASLt (#95094) (#95615)
An issue surfaced recently that revealed that we were never explicitly linking against `cuBLASLt`, this fixes it by linking explicitly rather than depending on linker magic.

CC @ptrblck @ngimel
Pull Request resolved: https://github.com/pytorch/pytorch/pull/95094
Approved by: https://github.com/malfet, https://github.com/ngimel, https://github.com/atalman

Co-authored-by: eqy <eddiey@nvidia.com>
2023-02-27 14:27:06 -05:00
735333a7ff Update triton hash (#95540) (#95577)
Fixes #95523

Pull Request resolved: https://github.com/pytorch/pytorch/pull/95540
Approved by: https://github.com/ngimel
2023-02-27 09:03:50 -08:00
6017488801 [MPS] LSTM fixes (#95388)
* [MPS] Fix LSTM backward and forward pass (#95137)

Fixes #91694
Fixes #92615

Several transpositions were missing for backward graph in case of `batch_first=True`. The #91694 is not reproduced with `batch_first=False`.

After fixing transpose issue, I finally thought that now I can use LSTM freely in my project. And then I got horrific results on train. Seems related to #92615.

After that I decided to fix LSTM's backward step completely. I collected all my findings in this thread — seems like I succeeded

Funny enough, backward tests were completely disabled before and were not passing:
```python
    @unittest.skipIf(True, "Backward of lstm returns wrong result")
    def test_lstm_2(self, device="mps", dtype=torch.float32):
```

UPD: forward pass of multi-layer version also was wrong due to the incorrect `initState, initCell` slices. Tests were passing because states were inited with zeros. *Accidentally* fixed this too

Pull Request resolved: https://github.com/pytorch/pytorch/pull/95137
Approved by: https://github.com/jhavukainen, https://github.com/kulinseth, https://github.com/soulitzer

* Update the allowlist for lstm_mps_backward

* More update to the BC allowlist

---------

Co-authored-by: alexdremov <dremov.me@gmail.com>
Co-authored-by: albanD <desmaison.alban@gmail.com>
2023-02-25 14:04:15 -05:00
e51e5e721c [optim] Add general documentation on our algorithm defaults (#95391) (#95516)
I added a section + table under Algorithms
https://docs-preview.pytorch.org/95391/optim.html?highlight=optim#module-torch.optim
<img width="725" alt="image" src="https://user-images.githubusercontent.com/31798555/221246256-99325a27-9016-407b-a9fe-404d61e41a82.png">

Pull Request resolved: https://github.com/pytorch/pytorch/pull/95391
Approved by: https://github.com/albanD
2023-02-25 14:02:57 -05:00
91739a0279 hotfix for memory leak in aot autograd induced by saving tensors for backward (#95101) (#95477)
Workaround fix in AOTAutograd for https://github.com/pytorch/pytorch/issues/94990 (see the comments for more details / discussion)

Pull Request resolved: https://github.com/pytorch/pytorch/pull/95101
Approved by: https://github.com/albanD
2023-02-24 16:40:30 -05:00
531f097b6f inductor: fix complier error when trying to vectorize logit_and and logit_or (#95361) (#95439)
Currently, `operator&& `  and `operator|| ` don't have vectorization implementation, disable them now for a quick fix for 2.0 release.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/95361
Approved by: https://github.com/ngimel, https://github.com/EikanWang
2023-02-24 09:23:29 -05:00
00eb7b0d78 [optim] Set defaults to foreach, NOT fused (#95241) (#95415)
Rolling back the default change for Adam and rectifying the docs to reflect that AdamW never defaulted to fused.

Since our fused implementations are relatively newer, let's give them a longer bake-in time before flipping the switch for every user.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/95241
Approved by: https://github.com/ngimel
2023-02-24 09:19:40 -05:00
2180f342c4 [SDPA] Fix bug in parsing scaled_dot_product_attention arguments (#95311) (#95397)
Fixes #95266

Pull Request resolved: https://github.com/pytorch/pytorch/pull/95311
Approved by: https://github.com/cpuhrsch
2023-02-24 09:18:19 -05:00
a90b4f09ac use 4 warps for small block config in mm (#95383)
* use 4 warps for small block config in mm

* Update test/inductor/test_select_algorithm.py

* Update test/inductor/test_select_algorithm.py
2023-02-24 09:12:36 -05:00
1211ceeaa4 [MPS] Fix issues with max_pool2d (#95325)
* [MPS] Fix upsample for NHWC output  (#94963)

Fixes https://github.com/huggingface/diffusers/issues/941

**Before**:
<img width="1144" alt="Screenshot 2023-02-15 at 8 11 53 PM" src="https://user-images.githubusercontent.com/104024078/219266709-6a77636a-2fc0-4802-b130-85069b95953f.png">

**After**:
<img width="1144" alt="Screenshot 2023-02-15 at 8 12 02 PM" src="https://user-images.githubusercontent.com/104024078/219266694-ea743c02-fb55-44f1-b7d6-5946106527c3.png">

Pull Request resolved: https://github.com/pytorch/pytorch/pull/94963
Approved by: https://github.com/razarmehr

* [MPS] Move max_pool2d to mps dispatch key (#90772)

Related issue: #77394

This PR also modifies some assertions in the codegen, an explanatory comment for it has been added.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/90772
Approved by: https://github.com/albanD

* [MPS] Convert output back to ChannelsLast for MaxPool2D (#94877)

Since we re-stride the indices and output in MPS pooling from ChannelsLast to Contiguous, we need to convert the results back to ChannelsLast.
This will fix the failure with test_memory_format with MaxPool2D in test_modules.py.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/94877
Approved by: https://github.com/kulinseth, https://github.com/DenisVieriu97

---------

Co-authored-by: Denis Vieriu <104024078+DenisVieriu97@users.noreply.github.com>
Co-authored-by: Li-Huai (Allan) Lin <qqaatw@gmail.com>
Co-authored-by: Ramin Azarmehr <razarmehr@apple.com>
2023-02-24 09:10:49 -05:00
beaa5c5908 [MPS] View fixes (#95323)
* [MPS] Fix the uint8 type issue with View ops kernels (#95145)

This should fix the problem in Resnet model with image artifacts due to saturation on int8 type and also the incorrect class recognition reported in #86954.

Fixes #86954

Pull Request resolved: https://github.com/pytorch/pytorch/pull/95145
Approved by: https://github.com/kulinseth, https://github.com/DenisVieriu97

* [MPS] Fix tensor with non-zero storage offset graph gathering (#91071)

Previously, the "can slice" flag in Placeholder constructor in `OperationUtils.mm` is conditioned on whether the numbers of dimensions of base shape and view shape are the same. This doesn't consider the situation that a view tensor could be the base tensor's sliced and then unsqueezed version, resulting in different num of dims.

For example, if we want to stack `y_mps` and `x_mps` on the last dim:
```
t_mps = torch.tensor([1, 2, 3, 4], device="mps")
x_mps = t_mps[2:]  # [3, 4]
y_mps = t_mps[:2]  # [1, 2]

res_mps = torch.stack((y_mps, x_mps), dim=-1)
```

the kernel will unsqueeze both of them on the last dim and then concatenate them, which is equivalent to:

```
res_mps = torch.cat((y_mps.unsqueeze(-1), x_mps.unsqueeze(-1)), dim=-1)
```

`x_mps.unsqueeze(-1)` is an unsqueezed and contiguous tensor with a storage offset, this kind of tensors should be sliceable without cloning its storage.

Fixes #87856
Fixes #91065

Pull Request resolved: https://github.com/pytorch/pytorch/pull/91071
Approved by: https://github.com/kulinseth

* [MPS] Fix fill_ where input tensor has a storage offset (#95113)

Fixes #94390

Apart from fixing the issue above, this PR also fixes a bug that when an input tensor can be sliced, a sliced array view is created. This array view seems to be not writable or have a different storage from the original tensor, causing incorrect results with the in-place `fill`.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/95113
Approved by: https://github.com/kulinseth

* [MPS] Fix view op slicing for 2nd dim in case of 0 offset (#95381)

* Fix view op slicing for 2nd dim in case of 0 offset

Pull Request resolved: https://github.com/pytorch/pytorch/pull/95381
Approved by: https://github.com/razarmehr

---------

Co-authored-by: Ramin Azarmehr <razarmehr@apple.com>
Co-authored-by: Li-Huai (Allan) Lin <qqaatw@gmail.com>
Co-authored-by: Denis Vieriu <104024078+DenisVieriu97@users.noreply.github.com>
2023-02-24 09:09:49 -05:00
4bd5c1e4f4 Fix warning if backend registers timer (#91702) (#95363)
currently logger timer is registered default for
cpu/cuda. for other backends, it may or may not
registers this timer. It reports warning for other backends and return which is not expected.
The above may fail, if the backends has have registered this timer. For example, HPU(habana) backend registers this timer. so, in this case it reports a warning and return which is incorrect.

Other case is where lazy backend timer is never registered. so, this returns a warning, and this is the reason the check was added, but it fails for other cases.

Add a generic check if the timer is registered, then don’t report warning.

Signed-off-by: Jeeja <jeejakp@habana.ai>

Fixes #ISSUE_NUMBER

Pull Request resolved: https://github.com/pytorch/pytorch/pull/91702
Approved by: https://github.com/kit1980
2023-02-23 18:57:09 -05:00
f3c97a4e43 Raise error on 3.11 dynamo export (#95088) (#95396)
For https://github.com/pytorch/pytorch/issues/94914. Realized that `dynamo.export` doesn't immediately raise an error when dynamo is trying to run on 3.11/windows.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/95088
Approved by: https://github.com/weiwangmeta
2023-02-23 18:55:32 -05:00
30cf0e70f7 [MPS] Copy fixes for MPS backend (#95321)
* [MPS] Handle broadcasting by expanding src tensor in Copy.mm (#95272)

Fixes #ISSUE_NUMBER

Pull Request resolved: https://github.com/pytorch/pytorch/pull/95272
Approved by: https://github.com/DenisVieriu97

* [MPS] Fix copy_cast_mps() on tensors with storage offset (#95093)

- The copy_cast path requires storage_offset to be applied before casting
- This should fix some correctness issues in transformer models

Fixes #94980

Pull Request resolved: https://github.com/pytorch/pytorch/pull/95093
Approved by: https://github.com/kulinseth

---------

Co-authored-by: Ramin Azarmehr <razarmehr@apple.com>
2023-02-23 18:17:20 -05:00
96f627dcde [MPS] Fixes in backward functions of the MPS ops (#95327)
* [MPS] Fix bilinear backward pass (#94892)

Fixes backward pass for bilinear.

Summary of changes:
- bilinear op is able to produce **contiguous, non-view** tensors with a storage offset, such as: shape=`[1, 1, 1, 1]`, `storage_offset=12`. This seems a weird case, but it is valid, and for these type of tensors we wouldn't be able to gather/scatter since we look at the view flag (which is not set here). This change looks into `storage_offset` only rather than the is_view flag which is not being set
- **reduction sum** must return a zeroed out output if passing an input with 0 elements (e.g a shape of (0, 5)).
Pull Request resolved: https://github.com/pytorch/pytorch/pull/94892
Approved by: https://github.com/kulinseth

* [MPS] Fix the crash in elu_backward() (#94923)

Fixes a crash where the inputTensor could go null and cause a crash.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/94923
Approved by: https://github.com/DenisVieriu97, https://github.com/kulinseth

* [MPS] Fix prelu backward pass (#94933)

Allocate the correct shape for the weights gradient
Pull Request resolved: https://github.com/pytorch/pytorch/pull/94933
Approved by: https://github.com/razarmehr

* [MPS] Fix embedding_backward() issue with Float16 (#94950)

- Casting the float16 input tensor to float32 and cast back the output tensor

Pull Request resolved: https://github.com/pytorch/pytorch/pull/94950
Approved by: https://github.com/DenisVieriu97

---------

Co-authored-by: Denis Vieriu <dvieriu@apple.com>
Co-authored-by: Ramin Azarmehr <razarmehr@apple.com>
2023-02-23 16:28:33 -05:00
6f11e6d6a1 [MPS] Convolution fixes (#95318)
* [MPS] Convolution cleanup; remove unnecessary contiguous calls (#95078)

- Fixes convolution crashes in backward with weights
- Removes unnecessary contiguous calls
Pull Request resolved: https://github.com/pytorch/pytorch/pull/95078
Approved by: https://github.com/kulinseth

* [MPS] Fix nn.functional.conv_transpose2d grad (#94871)

- add _mps_convolution_impl that takes optional shape
- for conv_tranpose2d grad, use the shape from forward pass directly
- for conv, calculate the shape from input
- remove nn.functional.conv_transpose2d grad from blocklist

Pull Request resolved: https://github.com/pytorch/pytorch/pull/94871
Approved by: https://github.com/kulinseth

---------

Co-authored-by: Denis Vieriu <104024078+DenisVieriu97@users.noreply.github.com>
Co-authored-by: Denis Vieriu <dvieriu@apple.com>
2023-02-23 12:31:30 -05:00
fcec27f7d5 [MPS] Numerical stability and reduction fixes (#95317)
* [MPS] Fixes for LSTM. (#94889)

- Backward pass has to give explicit bias tensor of zeros if none is passed to the op or the bias gradient will not be calculated.
- Fixed bias tensor mistakenly getting overwritten to zeros
- Fixes crash when lstm op called with has_biases set to false. Change takes into account the changed shape of the input params TensorList depending on the bias flag.

Fixes #ISSUE_NUMBER

Pull Request resolved: https://github.com/pytorch/pytorch/pull/94889
Approved by: https://github.com/DenisVieriu97

* [MPS] LogSoftmax numerical stability (#95091)

Fixes #94043

Calculations are now consistent with numericaly stable formula and CPU:

$LogSoftmax(X, \dim) = X - \max(X, \dim) - \log(sum(X - \max(X, \dim), \dim))$

@malfet

Pull Request resolved: https://github.com/pytorch/pytorch/pull/95091
Approved by: https://github.com/malfet, https://github.com/kulinseth

* [MPS] Cast int64 to int32 for reduction ops (#95231)

- give warnings of converting int64 for reduction ops
- use cast tensor for reduction sum on trace
- unblock trace from running
Pull Request resolved: https://github.com/pytorch/pytorch/pull/95231
Approved by: https://github.com/razarmehr

* [MPS] Fix Float16 issue with Reduction ops for macOS 12 (#94952)

This would fix the issue with `__rdiv__` with float16
Pull Request resolved: https://github.com/pytorch/pytorch/pull/94952
Approved by: https://github.com/kulinseth

---------

Co-authored-by: alexdremov <dremov.me@gmail.com>
Co-authored-by: Denis Vieriu <dvieriu@apple.com>
Co-authored-by: Ramin Azarmehr <razarmehr@apple.com>
2023-02-23 12:27:40 -05:00
cddcb1e526 Raise error if torch.compile is called from windows or py 3.11 (#94940) (#95329)
For https://github.com/pytorch/pytorch/issues/94914

Pull Request resolved: https://github.com/pytorch/pytorch/pull/94940
Approved by: https://github.com/albanD

Co-authored-by: William Wen <williamwen@fb.com>
2023-02-23 07:56:44 -05:00
0553b46df1 [profiler] update docs with repeat=1 (#95085) (#95242)
Specifying number of times to repeat is now required when defining the schedule.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/95085
Approved by: https://github.com/aaronenyeshi
2023-02-22 16:15:37 -08:00
b45d7697a5 fix numpy1.24 deprecations in unittests (#93997) (#95150)
Fixes https://github.com/pytorch/pytorch/issues/91329

Pull Request resolved: https://github.com/pytorch/pytorch/pull/93997
Approved by: https://github.com/ngimel, https://github.com/jerryzh168
2023-02-22 17:48:57 -05:00
7ebb309457 Revert "[CI] Use prebuilt triton from nightly repo (#94732)" (#95310)
This reverts commit 18d93cdc5dba50633a72363625601f9cf7253162.

Reverted https://github.com/pytorch/pytorch/pull/94732 on behalf of https://github.com/kit1980 due to Reverting per offline discussion to try to fix dynamo test failures after triton update

Co-authored-by: PyTorch MergeBot <pytorchmergebot@users.noreply.github.com>
2023-02-22 15:52:19 -05:00
cedfcdab46 Upgrade setuptools before building wheels (#95288)
* [BE] Cleanup triton builds (#95026)

Remove Python-3.7 clause
Do not install llvm-11, as llvm-14 is installed by triton/python/setup.py script

Pull Request resolved: https://github.com/pytorch/pytorch/pull/95026
Approved by: https://github.com/osalpekar, https://github.com/weiwangmeta

* Upgrade setuptools before building wheels (#95265)

Should fix https://github.com/pytorch/builder/issues/1318

Pull Request resolved: https://github.com/pytorch/pytorch/pull/95265
Approved by: https://github.com/ngimel

---------

Co-authored-by: Nikita Shulga <nshulga@fb.com>
Co-authored-by: Wei Wang <weiwangmeta@meta.com>
2023-02-22 12:23:21 -08:00
0b21e62406 Update triton hash (#95247) (#95285)
Should fix #95082
This hash commit is supposed to fix sm_89 issue.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/95247
Approved by: https://github.com/ngimel, https://github.com/seemethere

Co-authored-by: Wei Wang <weiwangmeta@meta.com>
2023-02-22 12:19:13 -08:00
91994c999f Deprecate Caffe2 ONNX exporter (#95071) 2023-02-21 11:01:34 -08:00
0b82f58866 inductor(cpu): fix C++ compile error when sigmoid's post ops is a reduction op (#94890) (#95054)
For timm **nfnet_l0** model. CPU path has the following error: `torch._dynamo.exc.BackendCompilerFailed: inductor raised CppCompileError: C++ compile error`.

There has a simple test case:

```
def fn(x):
    x = torch.ops.aten.sigmoid.default(x)
    return torch.ops.aten.mean.dim(x, [-1, -2], True)

x = torch.randn((1, 8, 8, 8))
opt_fn = torch._dynamo.optimize("inductor")(fn)
opt_fn(x)

real_out = fn(x)
compiled_out = opt_fn(x)
tol = 0.0001
print(torch.allclose(real_out, compiled_out, atol=tol, rtol=tol))

```

before:

```
extern "C" void kernel(float* __restrict__ in_out_ptr0,
                       const float* __restrict__ in_ptr0)
{
    auto out_ptr0 = in_out_ptr0;
    {
        #pragma GCC ivdep
        for(long i0=0; i0<8; i0+=1)
        {
            {
                #pragma omp declare reduction(+:at::vec::Vectorized<float>:omp_out += omp_in) initializer(omp_priv={{0}})
                float tmp2 = 0;
                auto tmp2_vec = at::vec::Vectorized<float>(tmp2);
                for(long i1=0; i1<4; i1+=1)
                {
                    auto tmp0 = at::vec::Vectorized<float>::loadu(in_ptr0 + (16*i1) + (64*i0));
                    auto tmp1 = decltype(tmp0)(1)/(decltype(tmp0)(1) + tmp0.neg().exp());
                    tmp2_vec += tmp1;
                }
                #pragma omp simd simdlen(8)  reduction(+:tmp3)
                for(long i1=64; i1<64; i1+=1)
                {
                    auto tmp0 = in_ptr0[i1 + (64*i0)];
                    auto tmp1 = std::exp(-tmp0);
                    auto tmp2 = 1 / (1 + tmp1);
                    tmp3 += tmp2;
                }
                tmp2 += at::vec::vec_reduce_all<float>([](at::vec::Vectorized<float>& x, at::vec::Vectorized<float>&y) {return x + y;}, tmp2_vec);
                out_ptr0[i0] = tmp3;
            }
        }
    }
    {
        for(long i0=0; i0<0; i0+=1)
        {
            auto tmp0 = at::vec::Vectorized<float>::loadu(out_ptr0 + 16*i0);
            auto tmp1 = at::vec::Vectorized<float>(static_cast<float>(64));
            auto tmp2 = tmp0 / tmp1;
            tmp2.store(in_out_ptr0 + 16*i0);
        }
        #pragma omp simd simdlen(8)
        for(long i0=0; i0<8; i0+=1)
        {
            auto tmp0 = out_ptr0[i0];
            auto tmp1 = static_cast<float>(64);
            auto tmp2 = tmp0 / tmp1;
            in_out_ptr0[i0] = tmp2;
        }
    }
}
```

after:
```
extern "C" void kernel(float* __restrict__ in_out_ptr0,
                       const float* __restrict__ in_ptr0)
{
    auto out_ptr0 = in_out_ptr0;
    #pragma omp parallel num_threads(40)
    {
        {
            #pragma omp for
            for(long i0=0; i0<8; i0+=1)
            {
                {
                    #pragma omp declare reduction(+:at::vec::Vectorized<float>:omp_out += omp_in) initializer(omp_priv={{0}})
                    float tmp2 = 0;
                    auto tmp2_vec = at::vec::Vectorized<float>(tmp2);
                    for(long i1=0; i1<4; i1+=1)
                    {
                        auto tmp0 = at::vec::Vectorized<float>::loadu(in_ptr0 + (16*i1) + (64*i0));
                        auto tmp1 = decltype(tmp0)(1)/(decltype(tmp0)(1) + tmp0.neg().exp());
                        tmp2_vec += tmp1;
                    }
                    #pragma omp simd simdlen(8)  reduction(+:tmp2)
                    for(long i1=64; i1<64; i1+=1)
                    {
                        auto tmp0 = in_ptr0[i1 + (64*i0)];
                        auto tmp1 = decltype(tmp0)(1) / (decltype(tmp0)(1) + std::exp(-tmp0));
                        tmp2 += tmp1;
                    }
                    tmp2 += at::vec::vec_reduce_all<float>([](at::vec::Vectorized<float>& x, at::vec::Vectorized<float>&y) {return x + y;}, tmp2_vec);
                    out_ptr0[i0] = tmp2;
                }
            }
        }
        #pragma omp single
        {
            {
                for(long i0=0; i0<0; i0+=1)
                {
                    auto tmp0 = at::vec::Vectorized<float>::loadu(out_ptr0 + 16*i0);
                    auto tmp1 = at::vec::Vectorized<float>(static_cast<float>(64));
                    auto tmp2 = tmp0 / tmp1;
                    tmp2.store(in_out_ptr0 + 16*i0);
                }
                #pragma omp simd simdlen(8)
                for(long i0=0; i0<8; i0+=1)
                {
                    auto tmp0 = out_ptr0[i0];
                    auto tmp1 = static_cast<float>(64);
                    auto tmp2 = tmp0 / tmp1;
                    in_out_ptr0[i0] = tmp2;
                }
            }
        }
    }
}
''')
```

Pull Request resolved: https://github.com/pytorch/pytorch/pull/94890
Approved by: https://github.com/EikanWang, https://github.com/jgong5, https://github.com/lezcano
2023-02-20 14:35:40 -05:00
1f7ab1c823 fix performance issue in torch.sparse.mm reduce mode (#94969) (#95018)
Fix performance bug for `torch.sparse.mm()` with reduce flag.

Found this bug within internal benchmarking.
Made a mistake when updating previous patch which causes load imbalance between threads:

Test on ogbn-products datasets on Xeon CLX with 24 cores:

#### before
```
sparse.mm: mean: 1156.148 ms
sparse.mm: sum: 1163.754 ms
sparse.mm: (using mkl): 703.227 ms
```

#### after
```
sparse.mm: mean: 662.578 ms
sparse.mm: sum: 662.301 ms
sparse.mm: (using mkl): 700.178 ms
```

The result also indicates that the current spmm kernel is no worse than MKL's sparse_mm .

Also update results on `pyg benchmark` with:
```
python gnn.py --use_sage --epochs=3 --runs=1 --inference
```

* Out of box: `13.32s`
* Without the fix in this PR: `5.87s`
* With the fix in this PR: `3.19s`

Pull Request resolved: https://github.com/pytorch/pytorch/pull/94969
Approved by: https://github.com/jgong5
2023-02-20 14:30:52 -05:00
52a27dd0ee [release only change] Add change to template - fix lint (#94981) 2023-02-16 09:53:48 -05:00
e0c728c545 Changes for release 2.0 only (#94934)
* Changes for release 2.0 only

* Delete the refs during pytorch checkout

* Bug fix and add xla r2.0 hash
2023-02-15 18:08:38 -05:00
dbcd11f3a7 try to fix OSS CI error (#94785) (#94936)
Differential Revision: D43259005

Pull Request resolved: https://github.com/pytorch/pytorch/pull/94785
Approved by: https://github.com/weiwangmeta, https://github.com/digantdesai

Co-authored-by: Cuiqing Li <cuiqingli123@meta.com>
2023-02-15 17:47:26 -05:00
16935 changed files with 1100420 additions and 1203582 deletions

View File

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

View File

@ -69,6 +69,10 @@ build --per_file_copt='^//.*\.(cpp|cc)$'@-Werror=all
# The following warnings come from -Wall. We downgrade them from error
# to warnings here.
#
# sign-compare has a tremendous amount of violations in the
# codebase. It will be a lot of work to fix them, just disable it for
# now.
build --per_file_copt='^//.*\.(cpp|cc)$'@-Wno-sign-compare
# We intentionally use #pragma unroll, which is compiler specific.
build --per_file_copt='^//.*\.(cpp|cc)$'@-Wno-error=unknown-pragmas
@ -96,9 +100,6 @@ build --per_file_copt='^//.*\.(cpp|cc)$'@-Wno-unused-parameter
# likely want to have this disabled for the most part.
build --per_file_copt='^//.*\.(cpp|cc)$'@-Wno-missing-field-initializers
build --per_file_copt='^//.*\.(cpp|cc)$'@-Wno-unused-function
build --per_file_copt='^//.*\.(cpp|cc)$'@-Wno-unused-variable
build --per_file_copt='//:aten/src/ATen/RegisterCompositeExplicitAutograd\.cpp$'@-Wno-error=unused-function
build --per_file_copt='//:aten/src/ATen/RegisterCompositeImplicitAutograd\.cpp$'@-Wno-error=unused-function
build --per_file_copt='//:aten/src/ATen/RegisterMkldnnCPU\.cpp$'@-Wno-error=unused-function

View File

@ -1 +1 @@
6.1.1
4.2.1

View File

@ -14,7 +14,6 @@
[cxx]
cxxflags = -std=c++17
ldflags = -Wl,--no-undefined
should_remap_host_platform = true
cpp = /usr/bin/clang
cc = /usr/bin/clang

View File

@ -1,7 +1,7 @@
# Docker images for GitHub CI and CD
# Docker images for Jenkins
This directory contains everything needed to build the Docker images
that are used in our CI.
that are used in our CI
The Dockerfiles located in subdirectories are parameterized to
conditionally run build stages depending on build arguments passed to
@ -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
Docker builds are now defined with `.circleci/cimodel/data/simple/docker_definitions.py`
## 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

@ -53,7 +53,7 @@ dependencies {
implementation 'androidx.appcompat:appcompat:1.0.0'
implementation 'com.facebook.fbjni:fbjni-java-only:0.2.2'
implementation 'com.google.code.findbugs:jsr305:3.0.1'
implementation 'com.facebook.soloader:nativeloader:0.10.5'
implementation 'com.facebook.soloader:nativeloader:0.10.4'
implementation 'junit:junit:' + rootProject.junitVersion
implementation 'androidx.test:core:' + rootProject.coreVersion

View File

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

View File

@ -46,7 +46,9 @@ if [[ "$image" == *xla* ]]; then
exit 0
fi
if [[ "$image" == *-focal* ]]; then
if [[ "$image" == *-bionic* ]]; then
UBUNTU_VERSION=18.04
elif [[ "$image" == *-focal* ]]; then
UBUNTU_VERSION=20.04
elif [[ "$image" == *-jammy* ]]; then
UBUNTU_VERSION=22.04
@ -71,11 +73,6 @@ if [[ "$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 [[ "$image" == *cuda*linter* ]]; then
# Use a separate Dockerfile for linter to keep a small image size
DOCKERFILE="linter-cuda/Dockerfile"
elif [[ "$image" == *linter* ]]; then
# Use a separate Dockerfile for linter to keep a small image size
DOCKERFILE="linter/Dockerfile"
@ -84,18 +81,18 @@ fi
# CMake 3.18 is needed to support CUDA17 language variant
CMAKE_VERSION=3.18.5
_UCX_COMMIT=7bb2722ff2187a0cad557ae4a6afa090569f83fb
_UCC_COMMIT=20eae37090a4ce1b32bcce6144ccad0b49943e0b
_UCX_COMMIT=31e74cac7bee0ef66bef2af72e7d86d9c282e5ab
_UCC_COMMIT=1c7a7127186e7836f73aafbd7697bbc274a77eee
# 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 "$image" in
pytorch-linux-focal-cuda12.4-cudnn9-py3-gcc9)
CUDA_VERSION=12.4.1
CUDNN_VERSION=9
pytorch-linux-bionic-cuda11.6-cudnn8-py3-gcc7)
CUDA_VERSION=11.6.2
CUDNN_VERSION=8
ANACONDA_PYTHON_VERSION=3.10
GCC_VERSION=9
GCC_VERSION=7
PROTOBUF=yes
DB=yes
VISION=yes
@ -103,13 +100,12 @@ case "$image" in
UCX_COMMIT=${_UCX_COMMIT}
UCC_COMMIT=${_UCC_COMMIT}
CONDA_CMAKE=yes
TRITON=yes
;;
pytorch-linux-focal-cuda12.1-cudnn9-py3-gcc9)
CUDA_VERSION=12.1.1
CUDNN_VERSION=9
pytorch-linux-bionic-cuda11.7-cudnn8-py3-gcc7)
CUDA_VERSION=11.7.0
CUDNN_VERSION=8
ANACONDA_PYTHON_VERSION=3.10
GCC_VERSION=9
GCC_VERSION=7
PROTOBUF=yes
DB=yes
VISION=yes
@ -117,73 +113,12 @@ case "$image" in
UCX_COMMIT=${_UCX_COMMIT}
UCC_COMMIT=${_UCC_COMMIT}
CONDA_CMAKE=yes
TRITON=yes
;;
pytorch-linux-focal-cuda12.4-cudnn9-py3-gcc9-inductor-benchmarks)
CUDA_VERSION=12.4.1
CUDNN_VERSION=9
ANACONDA_PYTHON_VERSION=3.10
GCC_VERSION=9
PROTOBUF=yes
DB=yes
VISION=yes
KATEX=yes
UCX_COMMIT=${_UCX_COMMIT}
UCC_COMMIT=${_UCC_COMMIT}
CONDA_CMAKE=yes
TRITON=yes
INDUCTOR_BENCHMARKS=yes
;;
pytorch-linux-focal-cuda12.1-cudnn9-py3-gcc9-inductor-benchmarks)
CUDA_VERSION=12.1.1
CUDNN_VERSION=9
ANACONDA_PYTHON_VERSION=3.10
GCC_VERSION=9
PROTOBUF=yes
DB=yes
VISION=yes
KATEX=yes
UCX_COMMIT=${_UCX_COMMIT}
UCC_COMMIT=${_UCC_COMMIT}
CONDA_CMAKE=yes
TRITON=yes
INDUCTOR_BENCHMARKS=yes
;;
pytorch-linux-focal-cuda12.1-cudnn9-py3.12-gcc9-inductor-benchmarks)
CUDA_VERSION=12.1.1
CUDNN_VERSION=9
ANACONDA_PYTHON_VERSION=3.12
GCC_VERSION=9
PROTOBUF=yes
DB=yes
VISION=yes
KATEX=yes
UCX_COMMIT=${_UCX_COMMIT}
UCC_COMMIT=${_UCC_COMMIT}
CONDA_CMAKE=yes
TRITON=yes
INDUCTOR_BENCHMARKS=yes
;;
pytorch-linux-focal-cuda12.4-cudnn9-py3.12-gcc9-inductor-benchmarks)
CUDA_VERSION=12.4.1
CUDNN_VERSION=9
ANACONDA_PYTHON_VERSION=3.12
GCC_VERSION=9
PROTOBUF=yes
DB=yes
VISION=yes
KATEX=yes
UCX_COMMIT=${_UCX_COMMIT}
UCC_COMMIT=${_UCC_COMMIT}
CONDA_CMAKE=yes
TRITON=yes
INDUCTOR_BENCHMARKS=yes
;;
pytorch-linux-focal-cuda11.8-cudnn9-py3-gcc9)
pytorch-linux-bionic-cuda11.8-cudnn8-py3-gcc7)
CUDA_VERSION=11.8.0
CUDNN_VERSION=9
CUDNN_VERSION=8
ANACONDA_PYTHON_VERSION=3.10
GCC_VERSION=9
GCC_VERSION=7
PROTOBUF=yes
DB=yes
VISION=yes
@ -191,195 +126,116 @@ case "$image" in
UCX_COMMIT=${_UCX_COMMIT}
UCC_COMMIT=${_UCC_COMMIT}
CONDA_CMAKE=yes
TRITON=yes
;;
pytorch-linux-focal-cuda12.4-cudnn9-py3-gcc9)
CUDA_VERSION=12.4.1
CUDNN_VERSION=9
ANACONDA_PYTHON_VERSION=3.10
GCC_VERSION=9
pytorch-linux-focal-py3-clang7-asan)
ANACONDA_PYTHON_VERSION=3.9
CLANG_VERSION=7
PROTOBUF=yes
DB=yes
VISION=yes
KATEX=yes
UCX_COMMIT=${_UCX_COMMIT}
UCC_COMMIT=${_UCC_COMMIT}
CONDA_CMAKE=yes
TRITON=yes
;;
pytorch-linux-focal-cuda12.1-cudnn9-py3-gcc9)
CUDA_VERSION=12.1.1
CUDNN_VERSION=9
ANACONDA_PYTHON_VERSION=3.10
GCC_VERSION=9
PROTOBUF=yes
DB=yes
VISION=yes
KATEX=yes
UCX_COMMIT=${_UCX_COMMIT}
UCC_COMMIT=${_UCC_COMMIT}
CONDA_CMAKE=yes
TRITON=yes
;;
pytorch-linux-focal-cuda12.4-cudnn9-py3-gcc9)
CUDA_VERSION=12.4.1
CUDNN_VERSION=9
ANACONDA_PYTHON_VERSION=3.10
GCC_VERSION=9
PROTOBUF=yes
DB=yes
VISION=yes
KATEX=yes
UCX_COMMIT=${_UCX_COMMIT}
UCC_COMMIT=${_UCC_COMMIT}
CONDA_CMAKE=yes
TRITON=yes
;;
pytorch-linux-focal-py3-clang10-onnx)
ANACONDA_PYTHON_VERSION=3.9
ANACONDA_PYTHON_VERSION=3.8
CLANG_VERSION=10
PROTOBUF=yes
DB=yes
VISION=yes
CONDA_CMAKE=yes
ONNX=yes
;;
pytorch-linux-focal-py3-clang9-android-ndk-r21e)
ANACONDA_PYTHON_VERSION=3.9
CLANG_VERSION=9
pytorch-linux-focal-py3-clang7-android-ndk-r19c)
ANACONDA_PYTHON_VERSION=3.7
CLANG_VERSION=7
LLVMDEV=yes
PROTOBUF=yes
ANDROID=yes
ANDROID_NDK_VERSION=r21e
ANDROID_NDK_VERSION=r19c
GRADLE_VERSION=6.8.3
NINJA_VERSION=1.9.0
;;
pytorch-linux-focal-py3.9-clang10)
ANACONDA_PYTHON_VERSION=3.9
CLANG_VERSION=10
pytorch-linux-bionic-py3.8-clang9)
ANACONDA_PYTHON_VERSION=3.8
CLANG_VERSION=9
PROTOBUF=yes
DB=yes
VISION=yes
VULKAN_SDK_VERSION=1.2.162.1
SWIFTSHADER=yes
CONDA_CMAKE=yes
TRITON=yes
;;
pytorch-linux-focal-py3.11-clang10)
pytorch-linux-bionic-py3.11-clang9)
ANACONDA_PYTHON_VERSION=3.11
CLANG_VERSION=10
CLANG_VERSION=9
PROTOBUF=yes
DB=yes
VISION=yes
VULKAN_SDK_VERSION=1.2.162.1
SWIFTSHADER=yes
CONDA_CMAKE=yes
TRITON=yes
;;
pytorch-linux-focal-py3.9-gcc9)
ANACONDA_PYTHON_VERSION=3.9
pytorch-linux-bionic-py3.8-gcc9)
ANACONDA_PYTHON_VERSION=3.8
GCC_VERSION=9
PROTOBUF=yes
DB=yes
VISION=yes
CONDA_CMAKE=yes
TRITON=yes
;;
pytorch-linux-focal-rocm-n-1-py3)
ANACONDA_PYTHON_VERSION=3.10
ANACONDA_PYTHON_VERSION=3.8
GCC_VERSION=9
PROTOBUF=yes
DB=yes
VISION=yes
ROCM_VERSION=6.1
ROCM_VERSION=5.3
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=5.4.2
NINJA_VERSION=1.9.0
CONDA_CMAKE=yes
TRITON=yes
;;
pytorch-linux-jammy-xpu-2024.0-py3)
ANACONDA_PYTHON_VERSION=3.9
GCC_VERSION=11
PROTOBUF=yes
DB=yes
VISION=yes
XPU_VERSION=0.5
NINJA_VERSION=1.9.0
CONDA_CMAKE=yes
TRITON=yes
;;
pytorch-linux-jammy-py3.9-gcc11-inductor-benchmarks)
ANACONDA_PYTHON_VERSION=3.9
GCC_VERSION=11
pytorch-linux-focal-py3.8-gcc7)
ANACONDA_PYTHON_VERSION=3.8
GCC_VERSION=7
PROTOBUF=yes
DB=yes
VISION=yes
KATEX=yes
CONDA_CMAKE=yes
TRITON=yes
DOCS=yes
INDUCTOR_BENCHMARKS=yes
;;
pytorch-linux-jammy-cuda11.8-cudnn9-py3.9-clang12)
ANACONDA_PYTHON_VERSION=3.9
pytorch-linux-jammy-cuda11.6-cudnn8-py3.8-clang12)
ANACONDA_PYTHON_VERSION=3.8
CUDA_VERSION=11.6
CUDNN_VERSION=8
CLANG_VERSION=12
PROTOBUF=yes
DB=yes
VISION=yes
;;
pytorch-linux-jammy-cuda11.7-cudnn8-py3.8-clang12)
ANACONDA_PYTHON_VERSION=3.8
CUDA_VERSION=11.7
CUDNN_VERSION=8
CLANG_VERSION=12
PROTOBUF=yes
DB=yes
VISION=yes
;;
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
VISION=yes
TRITON=yes
;;
pytorch-linux-jammy-py3-clang12-asan)
ANACONDA_PYTHON_VERSION=3.9
CLANG_VERSION=12
PROTOBUF=yes
DB=yes
VISION=yes
CONDA_CMAKE=yes
TRITON=yes
;;
pytorch-linux-jammy-py3-clang15-asan)
ANACONDA_PYTHON_VERSION=3.10
CLANG_VERSION=15
CONDA_CMAKE=yes
VISION=yes
;;
pytorch-linux-jammy-py3.9-gcc11)
ANACONDA_PYTHON_VERSION=3.9
GCC_VERSION=11
PROTOBUF=yes
DB=yes
VISION=yes
KATEX=yes
CONDA_CMAKE=yes
TRITON=yes
DOCS=yes
UNINSTALL_DILL=yes
;;
pytorch-linux-jammy-py3-clang12-executorch)
ANACONDA_PYTHON_VERSION=3.10
CLANG_VERSION=12
CONDA_CMAKE=yes
EXECUTORCH=yes
;;
pytorch-linux-jammy-py3.12-halide)
CUDA_VERSION=12.4
ANACONDA_PYTHON_VERSION=3.12
GCC_VERSION=11
CONDA_CMAKE=yes
HALIDE=yes
TRITON=yes
;;
pytorch-linux-focal-linter)
# TODO: Use 3.9 here because of this issue https://github.com/python/mypy/issues/13627.
@ -388,42 +244,6 @@ case "$image" in
ANACONDA_PYTHON_VERSION=3.9
CONDA_CMAKE=yes
;;
pytorch-linux-jammy-cuda11.8-cudnn9-py3.9-linter)
ANACONDA_PYTHON_VERSION=3.9
CUDA_VERSION=11.8
CONDA_CMAKE=yes
;;
pytorch-linux-jammy-aarch64-py3.10-gcc11)
ANACONDA_PYTHON_VERSION=3.10
GCC_VERSION=11
ACL=yes
PROTOBUF=yes
DB=yes
VISION=yes
CONDA_CMAKE=yes
# snadampal: skipping sccache due to the following issue
# https://github.com/pytorch/pytorch/issues/121559
SKIP_SCCACHE_INSTALL=yes
# snadampal: skipping llvm src build install because the current version
# from pytorch/llvm:9.0.1 is x86 specific
SKIP_LLVM_SRC_BUILD_INSTALL=yes
;;
pytorch-linux-jammy-aarch64-py3.10-gcc11-inductor-benchmarks)
ANACONDA_PYTHON_VERSION=3.10
GCC_VERSION=11
ACL=yes
PROTOBUF=yes
DB=yes
VISION=yes
CONDA_CMAKE=yes
# snadampal: skipping sccache due to the following issue
# https://github.com/pytorch/pytorch/issues/121559
SKIP_SCCACHE_INSTALL=yes
# snadampal: skipping llvm src build install because the current version
# from pytorch/llvm:9.0.1 is x86 specific
SKIP_LLVM_SRC_BUILD_INSTALL=yes
INDUCTOR_BENCHMARKS=yes
;;
*)
# Catch-all for builds that are not hardcoded.
PROTOBUF=yes
@ -440,10 +260,6 @@ case "$image" in
if [[ "$image" == *rocm* ]]; then
extract_version_from_image_name rocm ROCM_VERSION
NINJA_VERSION=1.9.0
TRITON=yes
# To ensure that any ROCm config will build using conda cmake
# and thus have LAPACK/MKL enabled
CONDA_CMAKE=yes
fi
if [[ "$image" == *centos7* ]]; then
NINJA_VERSION=1.10.2
@ -471,17 +287,20 @@ 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${UBUNTU_VERSION}"
fi
fi
# Build image
# TODO: build-arg THRIFT is not turned on for any image, remove it once we confirm
# it's no longer needed.
docker build \
--no-cache \
--progress=plain \
--build-arg "BUILD_ENVIRONMENT=${image}" \
--build-arg "PROTOBUF=${PROTOBUF:-}" \
--build-arg "THRIFT=${THRIFT:-}" \
--build-arg "LLVMDEV=${LLVMDEV:-}" \
--build-arg "DB=${DB:-}" \
--build-arg "VISION=${VISION:-}" \
@ -504,27 +323,17 @@ docker build \
--build-arg "NINJA_VERSION=${NINJA_VERSION:-}" \
--build-arg "KATEX=${KATEX:-}" \
--build-arg "ROCM_VERSION=${ROCM_VERSION:-}" \
--build-arg "PYTORCH_ROCM_ARCH=${PYTORCH_ROCM_ARCH:-gfx906;gfx90a}" \
--build-arg "PYTORCH_ROCM_ARCH=${PYTORCH_ROCM_ARCH:-gfx906}" \
--build-arg "IMAGE_NAME=${IMAGE_NAME}" \
--build-arg "UCX_COMMIT=${UCX_COMMIT}" \
--build-arg "UCC_COMMIT=${UCC_COMMIT}" \
--build-arg "CONDA_CMAKE=${CONDA_CMAKE}" \
--build-arg "TRITON=${TRITON}" \
--build-arg "ONNX=${ONNX}" \
--build-arg "DOCS=${DOCS}" \
--build-arg "INDUCTOR_BENCHMARKS=${INDUCTOR_BENCHMARKS}" \
--build-arg "EXECUTORCH=${EXECUTORCH}" \
--build-arg "HALIDE=${HALIDE}" \
--build-arg "XPU_VERSION=${XPU_VERSION}" \
--build-arg "ACL=${ACL:-}" \
--build-arg "SKIP_SCCACHE_INSTALL=${SKIP_SCCACHE_INSTALL:-}" \
--build-arg "SKIP_LLVM_SRC_BUILD_INSTALL=${SKIP_LLVM_SRC_BUILD_INSTALL:-}" \
-f $(dirname ${DOCKERFILE})/Dockerfile \
-t "$tmp_tag" \
"$@" \
.
# NVIDIA dockers for RC releases use tag names like `11.0-cudnn9-devel-ubuntu18.04-rc`,
# NVIDIA dockers for RC releases use tag names like `11.0-cudnn8-devel-ubuntu18.04-rc`,
# for this case we will set UBUNTU_VERSION to `18.04-rc` so that the Dockerfile could
# find the correct image. As a result, here we have to replace the
# "$UBUNTU_VERSION" == "18.04-rc"

60
.ci/docker/build_docker.sh Executable file
View File

@ -0,0 +1,60 @@
#!/bin/bash
set -ex
retry () {
$* || (sleep 1 && $*) || (sleep 2 && $*)
}
# If UPSTREAM_BUILD_ID is set (see trigger job), then we can
# use it to tag this build with the same ID used to tag all other
# base image builds. Also, we can try and pull the previous
# image first, to avoid rebuilding layers that haven't changed.
#until we find a way to reliably reuse previous build, this last_tag is not in use
# last_tag="$(( CIRCLE_BUILD_NUM - 1 ))"
tag="${DOCKER_TAG}"
registry="308535385114.dkr.ecr.us-east-1.amazonaws.com"
image="${registry}/pytorch/${IMAGE_NAME}"
login() {
aws ecr get-authorization-token --region us-east-1 --output text --query 'authorizationData[].authorizationToken' |
base64 -d |
cut -d: -f2 |
docker login -u AWS --password-stdin "$1"
}
# Only run these steps if not on github actions
if [[ -z "${GITHUB_ACTIONS}" ]]; then
# Retry on timeouts (can happen on job stampede).
retry login "${registry}"
# Logout on exit
trap "docker logout ${registry}" EXIT
fi
# Try to pull the previous image (perhaps we can reuse some layers)
# if [ -n "${last_tag}" ]; then
# docker pull "${image}:${last_tag}" || true
# fi
# Build new image
./build.sh ${IMAGE_NAME} -t "${image}:${tag}"
# Only push if `DOCKER_SKIP_PUSH` = false
if [ "${DOCKER_SKIP_PUSH:-true}" = "false" ]; then
# Only push if docker image doesn't exist already.
# ECR image tags are immutable so this will avoid pushing if only just testing if the docker jobs work
# NOTE: The only workflow that should push these images should be the docker-builds.yml workflow
if ! docker manifest inspect "${image}:${tag}" >/dev/null 2>/dev/null; then
docker push "${image}:${tag}"
fi
fi
if [ -z "${DOCKER_SKIP_S3_UPLOAD:-}" ]; then
trap "rm -rf ${IMAGE_NAME}:${tag}.tar" EXIT
docker save -o "${IMAGE_NAME}:${tag}.tar" "${image}:${tag}"
aws s3 cp "${IMAGE_NAME}:${tag}.tar" "s3://ossci-linux-build/pytorch/base/${IMAGE_NAME}:${tag}.tar" --acl public-read
fi

View File

@ -62,11 +62,11 @@ RUN if [ -n "${DB}" ]; then bash ./install_db.sh; fi
RUN rm install_db.sh
ENV INSTALLED_DB ${DB}
# (optional) Install vision packages like OpenCV
# (optional) Install vision packages like OpenCV and ffmpeg
ARG VISION
COPY ./common/install_vision.sh ./common/cache_vision_models.sh ./common/common_utils.sh ./
COPY ./common/install_vision.sh install_vision.sh
RUN if [ -n "${VISION}" ]; then bash ./install_vision.sh; fi
RUN rm install_vision.sh cache_vision_models.sh common_utils.sh
RUN rm install_vision.sh
ENV INSTALLED_VISION ${VISION}
# Install rocm
@ -77,9 +77,6 @@ RUN rm install_rocm.sh
COPY ./common/install_rocm_magma.sh install_rocm_magma.sh
RUN bash ./install_rocm_magma.sh
RUN rm install_rocm_magma.sh
COPY ./common/install_amdsmi.sh install_amdsmi.sh
RUN bash ./install_amdsmi.sh
RUN rm install_amdsmi.sh
ENV PATH /opt/rocm/bin:$PATH
ENV PATH /opt/rocm/hcc/bin:$PATH
ENV PATH /opt/rocm/hip/bin:$PATH
@ -101,25 +98,6 @@ COPY ./common/install_ninja.sh install_ninja.sh
RUN if [ -n "${NINJA_VERSION}" ]; then bash ./install_ninja.sh; fi
RUN rm install_ninja.sh
ARG TRITON
# Install triton, this needs to be done before sccache because the latter will
# try to reach out to S3, which docker build runners don't have access
ENV CMAKE_C_COMPILER cc
ENV CMAKE_CXX_COMPILER c++
COPY ./common/install_triton.sh install_triton.sh
COPY ./common/common_utils.sh common_utils.sh
COPY ci_commit_pins/triton.txt triton.txt
COPY triton_version.txt triton_version.txt
RUN if [ -n "${TRITON}" ]; then bash ./install_triton.sh; fi
RUN rm install_triton.sh common_utils.sh triton.txt triton_version.txt
# Install AOTriton (Early fail)
COPY ./aotriton_version.txt aotriton_version.txt
COPY ./common/common_utils.sh common_utils.sh
COPY ./common/install_aotriton.sh install_aotriton.sh
RUN ["/bin/bash", "-c", "./install_aotriton.sh /opt/rocm && rm -rf install_aotriton.sh aotriton_version.txt common_utils.sh"]
ENV AOTRITON_INSTALLED_PREFIX /opt/rocm/aotriton
# Install ccache/sccache (do this last, so we get priority in PATH)
COPY ./common/install_cache.sh install_cache.sh
ENV PATH /opt/cache/bin:$PATH

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@ -1 +0,0 @@
cd1c833b079adb324871dcbbe75b43d42ffc0ade

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@ -1 +0,0 @@
461c12871f336fe6f57b55d6a297f13ef209161b

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@ -1 +0,0 @@
243e186efbf7fb93328dd6b34927a4e8c8f24395

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@ -1 +0,0 @@
ac3470188b914c5d7a5058a7e28b9eb685a62427

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@ -1 +0,0 @@
91b14bf5593cf58a8541f3e6b9125600a867d4ef

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@ -1 +0,0 @@
5fe38ffd73c2ac6ed6323b554205186696631c6f

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

View File

@ -13,7 +13,7 @@ as_jenkins() {
# NB: Pass on PATH and LD_LIBRARY_PATH to sudo invocation
# NB: This must be run from a directory that jenkins has access to,
# works around https://github.com/conda/conda-package-handling/pull/34
$SUDO -E -H -u jenkins env -u SUDO_UID -u SUDO_GID -u SUDO_COMMAND -u SUDO_USER env "PATH=$PATH" "LD_LIBRARY_PATH=$LD_LIBRARY_PATH" $*
$SUDO -H -u jenkins env -u SUDO_UID -u SUDO_GID -u SUDO_COMMAND -u SUDO_USER env "PATH=$PATH" "LD_LIBRARY_PATH=$LD_LIBRARY_PATH" $*
}
conda_install() {
@ -30,7 +30,3 @@ conda_run() {
pip_install() {
as_jenkins conda run -n py_$ANACONDA_PYTHON_VERSION pip install --progress-bar off $*
}
get_pinned_commit() {
cat "${1}".txt
}

View File

@ -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

View File

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

View File

@ -107,6 +107,3 @@ chgrp -R jenkins /var/lib/jenkins/.gradle
popd
rm -rf /var/lib/jenkins/.gradle/daemon
# Cache vision models used by the test
source "$(dirname "${BASH_SOURCE[0]}")/cache_vision_models.sh"

View File

@ -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

@ -3,13 +3,16 @@
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
# "$UBUNTU_VERSION" == "18.04"*
# instead of
# "$UBUNTU_VERSION" == "18.04"
if [[ "$UBUNTU_VERSION" == "20.04"* ]]; then
if [[ "$UBUNTU_VERSION" == "18.04"* ]]; then
cmake3="cmake=3.10*"
maybe_libiomp_dev="libiomp-dev"
elif [[ "$UBUNTU_VERSION" == "20.04"* ]]; then
cmake3="cmake=3.16*"
maybe_libiomp_dev=""
elif [[ "$UBUNTU_VERSION" == "22.04"* ]]; then
@ -20,9 +23,7 @@ install_ubuntu() {
maybe_libiomp_dev="libiomp-dev"
fi
if [[ "$CLANG_VERSION" == 15 ]]; then
maybe_libomp_dev="libomp-15-dev"
elif [[ "$CLANG_VERSION" == 12 ]]; then
if [[ "$CLANG_VERSION" == 12 ]]; then
maybe_libomp_dev="libomp-12-dev"
elif [[ "$CLANG_VERSION" == 10 ]]; then
maybe_libomp_dev="libomp-10-dev"
@ -30,13 +31,10 @@ install_ubuntu() {
maybe_libomp_dev=""
fi
# HACK: UCC testing relies on libnccl library from NVIDIA repo, and version 2.16 crashes
# See https://github.com/pytorch/pytorch/pull/105260#issuecomment-1673399729
if [[ "$UBUNTU_VERSION" == "20.04"* && "$CUDA_VERSION" == "11.8"* ]]; then
maybe_libnccl_dev="libnccl2=2.15.5-1+cuda11.8 libnccl-dev=2.15.5-1+cuda11.8 --allow-downgrades --allow-change-held-packages"
else
maybe_libnccl_dev=""
fi
# 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")
# Install common dependencies
apt-get update
@ -61,12 +59,10 @@ install_ubuntu() {
${maybe_libiomp_dev} \
libyaml-dev \
libz-dev \
libjemalloc2 \
libjpeg-dev \
libasound2-dev \
libsndfile-dev \
${maybe_libomp_dev} \
${maybe_libnccl_dev} \
software-properties-common \
wget \
sudo \
@ -75,13 +71,26 @@ install_ubuntu() {
libtool \
vim \
unzip \
gpg-agent \
gdb
# Should resolve issues related to various apt package repository cert issues
# see: https://github.com/pytorch/pytorch/issues/65931
apt-get install -y libgnutls30
# cuda-toolkit does not work with gcc-11.2.0 which is default in Ubunutu 22.04
# see: https://github.com/NVlabs/instant-ngp/issues/119
if [[ "$UBUNTU_VERSION" == "22.04"* ]]; then
apt-get install -y g++-10
update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-10 30
update-alternatives --install /usr/bin/g++ g++ /usr/bin/g++-10 30
update-alternatives --install /usr/bin/gcov gcov /usr/bin/gcov-10 30
# https://www.spinics.net/lists/libreoffice/msg07549.html
sudo rm -rf /usr/lib/gcc/x86_64-linux-gnu/11
wget https://github.com/gcc-mirror/gcc/commit/2b2d97fc545635a0f6aa9c9ee3b017394bc494bf.patch -O noexecpt.patch
sudo patch /usr/include/c++/10/bits/range_access.h noexecpt.patch
fi
# Cleanup package manager
apt-get autoclean && apt-get clean
rm -rf /var/lib/apt/lists/* /tmp/* /var/tmp/*
@ -113,6 +122,7 @@ install_centos() {
glibc-devel \
glibc-headers \
glog-devel \
hiredis-devel \
libstdc++-devel \
libsndfile-devel \
make \
@ -152,7 +162,7 @@ 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

View File

@ -36,11 +36,14 @@ if [ -n "$ROCM_VERSION" ]; then
curl --retry 3 http://repo.radeon.com/misc/.sccache_amd/sccache -o /opt/cache/bin/sccache
else
ID=$(grep -oP '(?<=^ID=).+' /etc/os-release | tr -d '"')
# TODO: Install the pre-built binary from S3 as building from source
# https://github.com/pytorch/sccache has started failing mysteriously
# in which sccache server couldn't start with the following error:
# sccache: error: Invalid argument (os error 22)
install_binary
case "$ID" in
ubuntu)
install_ubuntu
;;
*)
install_binary
;;
esac
fi
chmod a+x /opt/cache/bin/sccache

View File

@ -4,7 +4,10 @@ set -ex
if [ -n "$CLANG_VERSION" ]; then
if [[ $CLANG_VERSION == 9 && $UBUNTU_VERSION == 18.04 ]]; then
if [[ $CLANG_VERSION == 7 && $UBUNTU_VERSION == 16.04 ]]; then
wget -O - https://apt.llvm.org/llvm-snapshot.gpg.key | sudo apt-key add -
sudo apt-add-repository "deb http://apt.llvm.org/xenial/ llvm-toolchain-xenial-7 main"
elif [[ $CLANG_VERSION == 9 && $UBUNTU_VERSION == 18.04 ]]; then
sudo apt-get update
# gpg-agent is not available by default on 18.04
sudo apt-get install -y --no-install-recommends gpg-agent
@ -25,11 +28,11 @@ if [ -n "$CLANG_VERSION" ]; then
fi
# Use update-alternatives to make this version the default
# TODO: Decide if overriding gcc as well is a good idea
# update-alternatives --install /usr/bin/gcc gcc /usr/bin/clang-"$CLANG_VERSION" 50
# update-alternatives --install /usr/bin/g++ g++ /usr/bin/clang++-"$CLANG_VERSION" 50
update-alternatives --install /usr/bin/clang clang /usr/bin/clang-"$CLANG_VERSION" 50
update-alternatives --install /usr/bin/clang++ clang++ /usr/bin/clang++-"$CLANG_VERSION" 50
# Override cc/c++ to clang as well
update-alternatives --install /usr/bin/cc cc /usr/bin/clang 50
update-alternatives --install /usr/bin/c++ c++ /usr/bin/clang++ 50
# clang's packaging is a little messed up (the runtime libs aren't
# added into the linker path), so give it a little help

View File

@ -5,17 +5,16 @@ 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: $ANACONDA_PYTHON_VERSION"
exit 1
@ -47,45 +46,28 @@ if [ -n "$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 [[ $(uname -m) == "aarch64" ]]; then
CONDA_COMMON_DEPS="astunparse pyyaml setuptools openblas==0.3.25=*openmp* ninja==1.11.1 scons==4.5.2"
if [ "$ANACONDA_PYTHON_VERSION" = "3.8" ]; then
NUMPY_VERSION=1.24.4
else
NUMPY_VERSION=1.26.2
fi
CONDA_COMMON_DEPS="astunparse pyyaml mkl=2021.4.0 mkl-include=2021.4.0 setuptools"
if [ "$ANACONDA_PYTHON_VERSION" = "3.11" ]; then
# Install llvm-8 as it is required to compile llvmlite-0.30.0 from source
# TODO: Stop using `-c malfet`
conda_install numpy=1.23.5 ${CONDA_COMMON_DEPS} llvmdev=8.0.0 -c malfet
elif [ "$ANACONDA_PYTHON_VERSION" = "3.10" ]; then
# Install llvm-8 as it is required to compile llvmlite-0.30.0 from source
conda_install numpy=1.21.2 ${CONDA_COMMON_DEPS} llvmdev=8.0.0
elif [ "$ANACONDA_PYTHON_VERSION" = "3.9" ]; then
# Install llvm-8 as it is required to compile llvmlite-0.30.0 from source
conda_install numpy=1.19.2 ${CONDA_COMMON_DEPS} llvmdev=8.0.0
elif [ "$ANACONDA_PYTHON_VERSION" = "3.8" ]; then
# Install llvm-8 as it is required to compile llvmlite-0.30.0 from source
conda_install numpy=1.18.5 ${CONDA_COMMON_DEPS} llvmdev=8.0.0
else
CONDA_COMMON_DEPS="astunparse pyyaml mkl=2021.4.0 mkl-include=2021.4.0 setuptools"
if [ "$ANACONDA_PYTHON_VERSION" = "3.11" ] || [ "$ANACONDA_PYTHON_VERSION" = "3.12" ] || [ "$ANACONDA_PYTHON_VERSION" = "3.13" ]; then
NUMPY_VERSION=1.26.0
else
NUMPY_VERSION=1.21.2
fi
# Install `typing-extensions` for 3.7
conda_install numpy=1.18.5 ${CONDA_COMMON_DEPS} typing-extensions
fi
conda_install ${CONDA_COMMON_DEPS}
# Install llvm-8 as it is required to compile llvmlite-0.30.0 from source
# and libpython-static for torch deploy
conda_install llvmdev=8.0.0 "libpython-static=${ANACONDA_PYTHON_VERSION}"
# Use conda cmake in some cases. Conda cmake will be newer than our supported
# min version (3.5 for xenial and 3.10 for bionic), so we only do it in those
@ -103,15 +85,13 @@ if [ -n "$ANACONDA_PYTHON_VERSION" ]; then
# Install some other packages, including those needed for Python test reporting
pip_install -r /opt/conda/requirements-ci.txt
pip_install numpy=="$NUMPY_VERSION"
pip_install -U scikit-learn
if [ -n "$DOCS" ]; then
apt-get update
apt-get -y install expect-dev
# We are currently building docs with python 3.8 (min support version)
pip_install -r /opt/conda/requirements-docs.txt
# Update scikit-learn to a python-3.8 compatible version
if [[ $(python -c "import sys; print(int(sys.version_info >= (3, 8)))") == "1" ]]; then
pip_install -U scikit-learn
else
# Pinned scikit-learn due to https://github.com/scikit-learn/scikit-learn/issues/14485 (affects gcc 5.5 only)
pip_install scikit-learn==0.20.3
fi
popd

View File

@ -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

View File

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

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

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

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 [[ ${CUDA_VERSION:0:4} == "11.7" ]]; then
CUDNN_NAME="cudnn-linux-x86_64-8.5.0.96_cuda11-archive"
curl --retry 3 -OLs https://ossci-linux.s3.amazonaws.com/${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

@ -7,7 +7,7 @@ if [ -n "$KATEX" ]; then
# Ignore error if gpg-agent doesn't exist (for Ubuntu 16.04)
apt-get install -y gpg-agent || :
curl --retry 3 -sL https://deb.nodesource.com/setup_16.x | sudo -E bash -
curl --retry 3 -sL https://deb.nodesource.com/setup_12.x | sudo -E bash -
sudo apt-get install -y nodejs
curl --retry 3 -sS https://dl.yarnpkg.com/debian/pubkey.gpg | sudo apt-key add -

View File

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

View File

@ -7,10 +7,17 @@ if [ -n "$GCC_VERSION" ]; then
# Need the official toolchain repo to get alternate packages
add-apt-repository ppa:ubuntu-toolchain-r/test
apt-get update
apt-get install -y g++-$GCC_VERSION
update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-"$GCC_VERSION" 50
update-alternatives --install /usr/bin/g++ g++ /usr/bin/g++-"$GCC_VERSION" 50
update-alternatives --install /usr/bin/gcov gcov /usr/bin/gcov-"$GCC_VERSION" 50
if [[ "$UBUNTU_VERSION" == "16.04" && "${GCC_VERSION:0:1}" == "5" ]]; then
apt-get install -y g++-5=5.4.0-6ubuntu1~16.04.12
update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-5 50
update-alternatives --install /usr/bin/g++ g++ /usr/bin/g++-5 50
update-alternatives --install /usr/bin/gcov gcov /usr/bin/gcov-5 50
else
apt-get install -y g++-$GCC_VERSION
update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-"$GCC_VERSION" 50
update-alternatives --install /usr/bin/g++ g++ /usr/bin/g++-"$GCC_VERSION" 50
update-alternatives --install /usr/bin/gcov gcov /usr/bin/gcov-"$GCC_VERSION" 50
fi
# Cleanup package manager

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

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

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

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

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 +59,17 @@ install_ubuntu() {
rocm-libs \
rccl \
rocprofiler-dev \
roctracer-dev \
amd-smi-lib
roctracer-dev
if [[ $(ver $ROCM_VERSION) -ge $(ver 6.1) ]]; then
DEBIAN_FRONTEND=noninteractive apt-get install -y --allow-unauthenticated rocm-llvm-dev
fi
# precompiled miopen kernels added in ROCm 3.5, renamed in ROCm 5.5
# search for all unversioned packages
# precompiled miopen kernels added in ROCm 3.5; search for all unversioned packages
# if search fails it will abort this script; use true to avoid case where search fails
MIOPENHIPGFX=$(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
MIOPENKERNELS=$(apt-cache search --names-only miopenkernels | awk '{print $1}' | grep -F -v . || true)
if [[ "x${MIOPENKERNELS}" = x ]]; then
echo "miopenkernels package not available"
else
DEBIAN_FRONTEND=noninteractive apt-get install -y --allow-unauthenticated ${MIOPENHIPGFX}
DEBIAN_FRONTEND=noninteractive apt-get install -y --allow-unauthenticated ${MIOPENKERNELS}
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 +85,25 @@ 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/${ROCM_VERSION}"
echo "[ROCm]" > /etc/yum.repos.d/rocm.repo
@ -107,23 +121,7 @@ install_centos() {
rocm-libs \
rccl \
rocprofiler-dev \
roctracer-dev \
amd-smi-lib
# precompiled miopen kernels; search for all unversioned packages
# if search fails it will abort this script; use true to avoid case where search fails
MIOPENHIPGFX=$(yum -q search miopen-hip-gfx | grep miopen-hip-gfx | awk '{print $1}'| grep -F kdb. || true)
if [[ "x${MIOPENHIPGFX}" = x ]]; then
echo "miopen-hip-gfx package not available" && exit 1
else
yum install -y ${MIOPENHIPGFX}
fi
# ROCm 6.0 had a regression where journal_mode was enabled on the kdb files resulting in permission errors at runtime
for kdb in /opt/rocm/share/miopen/db/*.kdb
do
sqlite3 $kdb "PRAGMA journal_mode=off; PRAGMA VACUUM;"
done
roctracer-dev
# Cleanup
yum clean all

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 +1,15 @@
#!/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
# Fixes memory leaks of magma found while executing linalg UTs
git checkout 5959b8783e45f1809812ed96ae762f38ee701972
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
@ -27,12 +18,12 @@ else
amdgpu_targets=`rocm_agent_enumerator | grep -v gfx000 | sort -u | xargs`
fi
for arch in $amdgpu_targets; do
echo "DEVCCFLAGS += --offload-arch=$arch" >> make.inc
echo "DEVCCFLAGS += --amdgpu-target=$arch" >> make.inc
done
# hipcc with openmp flag may cause isnan() on __device__ not to be found; depending on context, compiler may attempt to match with host definition
sed -i 's/^FOPENMP/#FOPENMP/g' make.inc
make -f make.gen.hipMAGMA -j $(nproc)
LANG=C.UTF-8 make lib/libmagma.so -j $(nproc) MKLROOT="${MKLROOT}"
make testing/testing_dgemm -j $(nproc) MKLROOT="${MKLROOT}"
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

@ -0,0 +1,14 @@
apt-get update
apt-get install -y sudo wget libboost-dev libboost-test-dev libboost-program-options-dev libboost-filesystem-dev libboost-thread-dev libevent-dev automake libtool flex bison pkg-config g++ libssl-dev
wget https://www-us.apache.org/dist/thrift/0.12.0/thrift-0.12.0.tar.gz
tar -xvf thrift-0.12.0.tar.gz
cd thrift-0.12.0
for file in ./compiler/cpp/Makefile*; do
sed -i 's/\-Werror//' $file
done
./bootstrap.sh
./configure --without-php --without-java --without-python --without-nodejs --without-go --without-ruby
sudo make
sudo make install
cd ..
rm thrift-0.12.0.tar.gz

View File

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

View File

@ -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
@ -41,6 +43,3 @@ case "$ID" in
exit 1
;;
esac
# Cache vision models used by the test
source "$(dirname "${BASH_SOURCE[0]}")/cache_vision_models.sh"

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

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

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

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

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

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@ -1,203 +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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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

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@ -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:
@ -25,20 +25,10 @@ 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==0.1.3
#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
#Pinned versions: 0.1.3
#test that import:
flatbuffers==2.0
@ -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
@ -77,11 +62,11 @@ librosa>=0.6.2 ; python_version < "3.11"
#mkl-devel
# see mkl
#mock
#mock # breaks ci/circleci: docker-pytorch-linux-xenial-py3-clang5-android-ndk-r19c
#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
@ -90,16 +75,16 @@ librosa>=0.6.2 ; python_version < "3.11"
#Pinned versions:
#test that import:
mypy==1.11.2
mypy==0.960
# Pin MyPy version because new errors are likely to appear with each release
#Description: linter
#Pinned versions: 1.10.0
#Pinned versions: 0.960
#test that import: test_typing.py, test_type_hints.py
networkx==2.8.8
networkx==2.6.3
#Description: creation, manipulation, and study of
#the structure, dynamics, and functions of complex networks
#Pinned versions: 2.8.8
#Pinned versions: 2.6.3 (latest version that works with Python 3.7+)
#test that import: functorch
#ninja
@ -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
@ -139,22 +124,9 @@ opt-einsum==3.3
#Pinned versions: 3.3
#test that import: test_linalg.py
optree==0.12.1
#Description: A library for tree manipulation
#Pinned versions: 0.12.1
#test that import: test_vmap.py, test_aotdispatch.py, test_dynamic_shapes.py,
#test_pytree.py, test_ops.py, test_control_flow.py, test_modules.py,
#common_utils.py, test_eager_transforms.py, test_python_dispatch.py,
#test_expanded_weights.py, test_decomp.py, test_overrides.py, test_masked.py,
#test_ops.py, test_prims.py, test_subclass.py, test_functionalization.py,
#test_schema_check.py, test_profiler_tree.py, test_meta.py, test_torchxla_num_output.py,
#test_utils.py, test_proxy_tensor.py, test_memory_profiler.py, test_view_ops.py,
#test_pointwise_ops.py, test_dtensor_ops.py, test_torchinductor.py, test_fx.py,
#test_fake_tensor.py, test_mps.py
pillow==10.3.0
#pillow
#Description: Python Imaging Library fork
#Pinned versions: 10.3.0
#Pinned versions:
#test that import:
protobuf==3.20.2
@ -167,22 +139,27 @@ psutil
#Pinned versions:
#test that import: test_profiler.py, test_openmp.py, test_dataloader.py
pytest==7.3.2
pytest
#Description: testing framework
#Pinned versions:
#test that import: test_typing.py, test_cpp_extensions_aot.py, run_test.py
pytest-xdist==3.3.1
pytest-xdist
#Description: plugin for running pytest in parallel
#Pinned versions:
#test that import:
pytest-shard
#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
#test that import:
pytest-rerunfailures>=10.3
pytest-rerunfailures
#Description: plugin for rerunning failure tests in pytest
#Pinned versions:
#test that import:
@ -202,7 +179,7 @@ xdoctest==1.1.0
#Pinned versions: 1.1.0
#test that import:
pygments==2.15.0
pygments==2.12.0
#Description: support doctest highlighting
#Pinned versions: 2.12.0
#test that import: the doctests
@ -222,8 +199,7 @@ pygments==2.15.0
#Pinned versions: 10.9.0
#test that import:
scikit-image==0.19.3 ; python_version < "3.10"
scikit-image==0.22.0 ; python_version >= "3.10"
scikit-image
#Description: image processing routines
#Pinned versions:
#test that import: test_nn.py
@ -233,11 +209,12 @@ 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==1.9.3 ; 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
@ -247,13 +224,12 @@ scipy==1.12.0 ; python_version == "3.12"
#Pinned versions:
#test that import:
tb-nightly==2.13.0a20230426
tb-nightly
#Description: TensorBoard
#Pinned versions:
#test that import:
# needed by torchgen utils
typing-extensions
#typing-extensions
#Description: type hints for python
#Pinned versions:
#test that import:
@ -268,77 +244,17 @@ 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
#Description: all about linters!
#Pinned versions: 0.12.5
lintrunner==0.9.2
#Description: all about linters
#Pinned versions: 0.9.2
#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
#test that import:
jinja2==3.1.4
#Description: jinja2 template engine
#Pinned versions: 3.1.4
#test that import:
pytest-cpp==2.3.0
#Description: This is used by pytest to invoke C++ tests
#Pinned versions: 2.3.0
#test that import:
z3-solver==4.12.2.0
#Description: The Z3 Theorem Prover Project
#Pinned versions:
#test that import:
tensorboard==2.13.0
#Description: Also included in .ci/docker/requirements-docs.txt
#Pinned versions:
#test that import: test_tensorboard
pywavelets==1.4.1 ; python_version < "3.12"
pywavelets==1.5.0 ; python_version >= "3.12"
#Description: This is a requirement of scikit-image, we need to pin
# it here because 1.5.0 conflicts with numpy 1.21.2 used in CI
#Pinned versions: 1.4.1
#test that import:
lxml==5.0.0
#Description: This is a requirement of unittest-xml-reporting
# Python-3.9 binaries
PyGithub==2.3.0
sympy==1.12.1 ; python_version == "3.8"
sympy==1.13.1 ; python_version >= "3.9"
#Description: Required by coremltools, also pinned in .github/requirements/pip-requirements-macOS.txt
#Pinned versions:
#test that import:
onnx==1.16.1
#Description: Required by mypy and test_public_bindings.py when checking torch.onnx._internal
#Pinned versions:
#test that import:
onnxscript==0.1.0.dev20240817
#Description: Required by mypy and test_public_bindings.py when checking torch.onnx._internal
#Pinned versions:
#test that import:
parameterized==0.8.1
#Description: Parameterizes unittests, both the tests themselves and the entire testing class
#Pinned versions:
#Pinned versions: 0.7.1
#test that import:

View File

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

View File

@ -1 +0,0 @@
3.1.0

View File

@ -56,11 +56,11 @@ RUN if [ -n "${DB}" ]; then bash ./install_db.sh; fi
RUN rm install_db.sh
ENV INSTALLED_DB ${DB}
# (optional) Install vision packages like OpenCV
# (optional) Install vision packages like OpenCV and ffmpeg
ARG VISION
COPY ./common/install_vision.sh ./common/cache_vision_models.sh ./common/common_utils.sh ./
COPY ./common/install_vision.sh install_vision.sh
RUN if [ -n "${VISION}" ]; then bash ./install_vision.sh; fi
RUN rm install_vision.sh cache_vision_models.sh common_utils.sh
RUN rm install_vision.sh
ENV INSTALLED_VISION ${VISION}
# (optional) Install UCC
@ -79,38 +79,12 @@ ENV OPENSSL_ROOT_DIR /opt/openssl
RUN bash ./install_openssl.sh
ENV OPENSSL_DIR /opt/openssl
ARG INDUCTOR_BENCHMARKS
COPY ./common/install_inductor_benchmark_deps.sh install_inductor_benchmark_deps.sh
COPY ./common/common_utils.sh common_utils.sh
COPY ci_commit_pins/huggingface.txt huggingface.txt
COPY ci_commit_pins/timm.txt timm.txt
RUN if [ -n "${INDUCTOR_BENCHMARKS}" ]; then bash ./install_inductor_benchmark_deps.sh; fi
RUN rm install_inductor_benchmark_deps.sh common_utils.sh timm.txt huggingface.txt
# (optional) Install non-default CMake version
ARG CMAKE_VERSION
COPY ./common/install_cmake.sh install_cmake.sh
RUN if [ -n "${CMAKE_VERSION}" ]; then bash ./install_cmake.sh; fi
RUN rm install_cmake.sh
ARG TRITON
# Install triton, this needs to be done before sccache because the latter will
# try to reach out to S3, which docker build runners don't have access
COPY ./common/install_triton.sh install_triton.sh
COPY ./common/common_utils.sh common_utils.sh
COPY ci_commit_pins/triton.txt triton.txt
COPY triton_version.txt triton_version.txt
RUN if [ -n "${TRITON}" ]; then bash ./install_triton.sh; fi
RUN rm install_triton.sh common_utils.sh triton.txt triton_version.txt
ARG HALIDE
# Build and install halide
COPY ./common/install_halide.sh install_halide.sh
COPY ./common/common_utils.sh common_utils.sh
COPY ci_commit_pins/halide.txt halide.txt
RUN if [ -n "${HALIDE}" ]; then bash ./install_halide.sh; fi
RUN rm install_halide.sh common_utils.sh halide.txt
# Install ccache/sccache (do this last, so we get priority in PATH)
COPY ./common/install_cache.sh install_cache.sh
ENV PATH /opt/cache/bin:$PATH
@ -147,26 +121,12 @@ 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

@ -53,11 +53,11 @@ RUN if [ -n "${DB}" ]; then bash ./install_db.sh; fi
RUN rm install_db.sh
ENV INSTALLED_DB ${DB}
# (optional) Install vision packages like OpenCV
# (optional) Install vision packages like OpenCV and ffmpeg
ARG VISION
COPY ./common/install_vision.sh ./common/cache_vision_models.sh ./common/common_utils.sh ./
COPY ./common/install_vision.sh install_vision.sh
RUN if [ -n "${VISION}" ]; then bash ./install_vision.sh; fi
RUN rm install_vision.sh cache_vision_models.sh common_utils.sh
RUN rm install_vision.sh
ENV INSTALLED_VISION ${VISION}
# Install rocm
@ -68,9 +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:$PATH
ENV PATH /opt/rocm/hip/bin:$PATH
@ -80,11 +77,6 @@ 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
@ -97,23 +89,6 @@ COPY ./common/install_ninja.sh install_ninja.sh
RUN if [ -n "${NINJA_VERSION}" ]; then bash ./install_ninja.sh; fi
RUN rm install_ninja.sh
ARG TRITON
# Install triton, this needs to be done before sccache because the latter will
# try to reach out to S3, which docker build runners don't have access
COPY ./common/install_triton.sh install_triton.sh
COPY ./common/common_utils.sh common_utils.sh
COPY ci_commit_pins/triton.txt triton.txt
COPY triton_version.txt triton_version.txt
RUN if [ -n "${TRITON}" ]; then bash ./install_triton.sh; fi
RUN rm install_triton.sh common_utils.sh triton.txt triton_version.txt
# Install AOTriton
COPY ./aotriton_version.txt aotriton_version.txt
COPY ./common/common_utils.sh common_utils.sh
COPY ./common/install_aotriton.sh install_aotriton.sh
RUN ["/bin/bash", "-c", "./install_aotriton.sh /opt/rocm && rm -rf install_aotriton.sh aotriton_version.txt common_utils.sh"]
ENV AOTRITON_INSTALLED_PREFIX /opt/rocm/aotriton
# Install ccache/sccache (do this last, so we get priority in PATH)
COPY ./common/install_cache.sh install_cache.sh
ENV PATH /opt/cache/bin:$PATH
@ -123,8 +98,5 @@ 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

@ -17,6 +17,13 @@ ARG LLVMDEV
COPY ./common/install_clang.sh install_clang.sh
RUN bash ./install_clang.sh && rm install_clang.sh
# (optional) Install thrift.
ARG THRIFT
COPY ./common/install_thrift.sh install_thrift.sh
RUN if [ -n "${THRIFT}" ]; then bash ./install_thrift.sh; fi
RUN rm install_thrift.sh
ENV INSTALLED_THRIFT ${THRIFT}
# Install user
COPY ./common/install_user.sh install_user.sh
RUN bash ./install_user.sh && rm install_user.sh
@ -29,15 +36,12 @@ RUN bash ./install_docs_reqs.sh && rm install_docs_reqs.sh
# Install conda and other packages (e.g., numpy, pytest)
ARG ANACONDA_PYTHON_VERSION
ARG CONDA_CMAKE
ARG DOCS
ENV ANACONDA_PYTHON_VERSION=$ANACONDA_PYTHON_VERSION
ENV PATH /opt/conda/envs/py_$ANACONDA_PYTHON_VERSION/bin:/opt/conda/bin:$PATH
ENV DOCS=$DOCS
COPY requirements-ci.txt requirements-docs.txt /opt/conda/
COPY requirements-ci.txt /opt/conda/requirements-ci.txt
COPY ./common/install_conda.sh install_conda.sh
COPY ./common/common_utils.sh common_utils.sh
RUN bash ./install_conda.sh && rm install_conda.sh common_utils.sh /opt/conda/requirements-ci.txt /opt/conda/requirements-docs.txt
RUN if [ -n "${UNINSTALL_DILL}" ]; then pip uninstall -y dill; fi
RUN bash ./install_conda.sh && rm install_conda.sh common_utils.sh /opt/conda/requirements-ci.txt
# Install gcc
ARG GCC_VERSION
@ -50,7 +54,7 @@ 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
@ -80,22 +84,22 @@ RUN if [ -n "${DB}" ]; then bash ./install_db.sh; fi
RUN rm install_db.sh
ENV INSTALLED_DB ${DB}
# (optional) Install vision packages like OpenCV
# (optional) Install vision packages like OpenCV and ffmpeg
ARG VISION
COPY ./common/install_vision.sh ./common/cache_vision_models.sh ./common/common_utils.sh ./
COPY ./common/install_vision.sh install_vision.sh
RUN if [ -n "${VISION}" ]; then bash ./install_vision.sh; fi
RUN rm install_vision.sh cache_vision_models.sh common_utils.sh
RUN rm install_vision.sh
ENV INSTALLED_VISION ${VISION}
# (optional) Install Android NDK
ARG ANDROID
ARG ANDROID_NDK
ARG GRADLE_VERSION
COPY ./common/install_android.sh ./common/cache_vision_models.sh ./common/common_utils.sh ./
COPY ./common/install_android.sh install_android.sh
COPY ./android/AndroidManifest.xml AndroidManifest.xml
COPY ./android/build.gradle build.gradle
RUN if [ -n "${ANDROID}" ]; then bash ./install_android.sh; fi
RUN rm install_android.sh cache_vision_models.sh common_utils.sh
RUN rm install_android.sh
RUN rm AndroidManifest.xml
RUN rm build.gradle
ENV INSTALLED_ANDROID ${ANDROID}
@ -130,58 +134,10 @@ ENV OPENSSL_ROOT_DIR /opt/openssl
ENV OPENSSL_DIR /opt/openssl
RUN rm install_openssl.sh
ARG INDUCTOR_BENCHMARKS
COPY ./common/install_inductor_benchmark_deps.sh install_inductor_benchmark_deps.sh
COPY ./common/common_utils.sh common_utils.sh
COPY ci_commit_pins/huggingface.txt huggingface.txt
COPY ci_commit_pins/timm.txt timm.txt
RUN if [ -n "${INDUCTOR_BENCHMARKS}" ]; then bash ./install_inductor_benchmark_deps.sh; fi
RUN rm install_inductor_benchmark_deps.sh common_utils.sh timm.txt huggingface.txt
ARG TRITON
# Install triton, this needs to be done before sccache because the latter will
# try to reach out to S3, which docker build runners don't have access
COPY ./common/install_triton.sh install_triton.sh
COPY ./common/common_utils.sh common_utils.sh
COPY ci_commit_pins/triton.txt triton.txt
RUN if [ -n "${TRITON}" ]; then bash ./install_triton.sh; fi
RUN rm install_triton.sh common_utils.sh triton.txt
ARG EXECUTORCH
# Build and install executorch
COPY ./common/install_executorch.sh install_executorch.sh
COPY ./common/common_utils.sh common_utils.sh
COPY ci_commit_pins/executorch.txt executorch.txt
RUN if [ -n "${EXECUTORCH}" ]; then bash ./install_executorch.sh; fi
RUN rm install_executorch.sh common_utils.sh executorch.txt
ARG HALIDE
# Build and install halide
COPY ./common/install_halide.sh install_halide.sh
COPY ./common/common_utils.sh common_utils.sh
COPY ci_commit_pins/halide.txt halide.txt
RUN if [ -n "${HALIDE}" ]; then bash ./install_halide.sh; fi
RUN rm install_halide.sh common_utils.sh halide.txt
ARG ONNX
# Install ONNX dependencies
COPY ./common/install_onnx.sh ./common/common_utils.sh ./
RUN if [ -n "${ONNX}" ]; then bash ./install_onnx.sh; fi
RUN rm install_onnx.sh common_utils.sh
# (optional) Build ACL
ARG ACL
COPY ./common/install_acl.sh install_acl.sh
RUN if [ -n "${ACL}" ]; then bash ./install_acl.sh; fi
RUN rm install_acl.sh
ENV INSTALLED_ACL ${ACL}
# Install ccache/sccache (do this last, so we get priority in PATH)
ARG SKIP_SCCACHE_INSTALL
COPY ./common/install_cache.sh install_cache.sh
ENV PATH /opt/cache/bin:$PATH
RUN if [ -z "${SKIP_SCCACHE_INSTALL}" ]; then bash ./install_cache.sh; fi
RUN rm install_cache.sh
RUN bash ./install_cache.sh && rm install_cache.sh
# Add jni.h for java host build
COPY ./common/install_jni.sh install_jni.sh
@ -198,9 +154,7 @@ 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

@ -1,9 +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

@ -3,27 +3,72 @@
# 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 [[ ${BUILD_ENVIRONMENT} == *onnx* ]]; then
pip install click mock tabulate networkx==2.0
pip -q install --user "file:///var/lib/jenkins/workspace/third_party/onnx#egg=onnx"
fi
# Skip tests in environments where they are not built/applicable
if [[ "${BUILD_ENVIRONMENT}" == *-android* ]]; then
echo 'Skipping tests'
exit 0
fi
if [[ "${BUILD_ENVIRONMENT}" == *-rocm* ]]; then
# temporary to locate some kernel issues on the CI nodes
export HSAKMT_DEBUG_LEVEL=4
fi
# These additional packages are needed for circleci ROCm builds.
if [[ $BUILD_ENVIRONMENT == *rocm* ]]; then
# Need networkx 2.0 because bellmand_ford was moved in 2.1 . Scikit-image by
# defaults installs the most recent networkx version, so we install this lower
# version explicitly before scikit-image pulls it in as a dependency
pip install networkx==2.0
# click - onnx
pip install --progress-bar off click protobuf tabulate virtualenv mock typing-extensions
fi
################################################################################
# Python tests #
################################################################################
if [[ "$BUILD_ENVIRONMENT" == *cmake* ]]; then
exit 0
fi
# If pip is installed as root, we must use sudo.
# CircleCI docker images could install conda as jenkins user, or use the OS's python package.
PIP=$(which pip)
PIP_USER=$(stat --format '%U' $PIP)
CURRENT_USER=$(id -u -n)
if [[ "$PIP_USER" = root && "$CURRENT_USER" != root ]]; then
MAYBE_SUDO=sudo
fi
# Uninstall pre-installed hypothesis and coverage to use an older version as newer
# versions remove the timeout parameter from settings which ideep/conv_transpose_test.py uses
$MAYBE_SUDO pip -q uninstall -y hypothesis
$MAYBE_SUDO pip -q uninstall -y coverage
# "pip install hypothesis==3.44.6" from official server is unreliable on
# CircleCI, so we host a copy on S3 instead
$MAYBE_SUDO pip -q install attrs==18.1.0 -f https://s3.amazonaws.com/ossci-linux/wheels/attrs-18.1.0-py2.py3-none-any.whl
$MAYBE_SUDO pip -q install coverage==4.5.1 -f https://s3.amazonaws.com/ossci-linux/wheels/coverage-4.5.1-cp36-cp36m-macosx_10_12_x86_64.whl
$MAYBE_SUDO pip -q install hypothesis==4.57.1
##############
# ONNX tests #
##############
if [[ "$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@$(cat .github/ci_commit_pins/vision.txt)"
pip install -q --user transformers==4.25.1
pip install -q --user ninja flatbuffers==2.0 numpy==1.22.4 onnxruntime==1.14.0 beartype==0.10.4
# TODO: change this when onnx 1.13.1 is released.
pip install --no-use-pep517 'onnx @ git+https://github.com/onnx/onnx@e192ba01e438d22ca2dedd7956e28e3551626c91'
# TODO: change this when onnx-script is on testPypi
pip install 'onnx-script @ git+https://github.com/microsoft/onnx-script@a71e35bcd72537bf7572536ee57250a0c0488bf6'
# numba requires numpy <= 1.20, onnxruntime requires numpy >= 1.21.
# We don't actually need it for our tests, but it's imported if it's present, so uninstall.
pip uninstall -q --yes numba
# JIT C++ extensions require ninja, so put it into PATH.
export PATH="/var/lib/jenkins/.local/bin:$PATH"
# NB: ONNX test is fast (~15m) so it's ok to retry it few more times to avoid any flaky issue, we
# need to bring this to the standard PyTorch run_test eventually. The issue will be tracked in
# https://github.com/pytorch/pytorch/issues/98626
"$ROOT_DIR/scripts/onnx/test.sh"
fi

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.

42
.ci/pytorch/build-asan.sh Executable file
View File

@ -0,0 +1,42 @@
#!/bin/bash
# Required environment variable: $BUILD_ENVIRONMENT
# (This is set by default in the Docker images we build, so you don't
# need to set it yourself.
# shellcheck source=./common.sh
source "$(dirname "${BASH_SOURCE[0]}")/common.sh"
# shellcheck source=./common-build.sh
source "$(dirname "${BASH_SOURCE[0]}")/common-build.sh"
echo "Clang version:"
clang --version
python tools/stats/export_test_times.py
# detect_leaks=0: Python is very leaky, so we need suppress it
# symbolize=1: Gives us much better errors when things go wrong
export ASAN_OPTIONS=detect_leaks=0:detect_stack_use_after_return=1:symbolize=1:detect_odr_violation=0
if [ -n "$(which conda)" ]; then
export CMAKE_PREFIX_PATH=/opt/conda
fi
# TODO: Make the ASAN flags a centralized env var and unify with USE_ASAN option
CC="clang" CXX="clang++" LDSHARED="clang --shared" \
CFLAGS="-fsanitize=address -fsanitize=undefined -fno-sanitize-recover=all -fsanitize-address-use-after-scope -shared-libasan" \
USE_ASAN=1 USE_CUDA=0 USE_MKLDNN=0 \
python setup.py bdist_wheel
pip_install_whl "$(echo dist/*.whl)"
# Test building via the sdist source tarball
python setup.py sdist
mkdir -p /tmp/tmp
pushd /tmp/tmp
tar zxf "$(dirname "${BASH_SOURCE[0]}")/../../dist/"*.tar.gz
cd torch-*
python setup.py build --cmake-only
popd
print_sccache_stats
assert_git_not_dirty

29
.ci/pytorch/build-tsan.sh Executable file
View File

@ -0,0 +1,29 @@
#!/bin/bash
# Required environment variable: $BUILD_ENVIRONMENT
# (This is set by default in the Docker images we build, so you don't
# need to set it yourself.
# shellcheck source=./common.sh
source "$(dirname "${BASH_SOURCE[0]}")/common.sh"
# shellcheck source=./common-build.sh
source "$(dirname "${BASH_SOURCE[0]}")/common-build.sh"
echo "Clang version:"
clang --version
python tools/stats/export_test_times.py
if [ -n "$(which conda)" ]; then
export CMAKE_PREFIX_PATH=/opt/conda
fi
CC="clang" CXX="clang++" LDSHARED="clang --shared" \
CFLAGS="-fsanitize=thread" \
USE_TSAN=1 USE_CUDA=0 USE_MKLDNN=0 \
python setup.py bdist_wheel
pip_install_whl "$(echo dist/*.whl)"
print_sccache_stats
assert_git_not_dirty

View File

@ -11,6 +11,14 @@ source "$(dirname "${BASH_SOURCE[0]}")/common.sh"
# shellcheck source=./common-build.sh
source "$(dirname "${BASH_SOURCE[0]}")/common-build.sh"
if [[ "$BUILD_ENVIRONMENT" == *-clang7-asan* ]]; then
exec "$(dirname "${BASH_SOURCE[0]}")/build-asan.sh" "$@"
fi
if [[ "$BUILD_ENVIRONMENT" == *-clang7-tsan* ]]; then
exec "$(dirname "${BASH_SOURCE[0]}")/build-tsan.sh" "$@"
fi
if [[ "$BUILD_ENVIRONMENT" == *-mobile-*build* ]]; then
exec "$(dirname "${BASH_SOURCE[0]}")/build-mobile.sh" "$@"
fi
@ -28,8 +36,6 @@ echo "Environment variables:"
env
if [[ "$BUILD_ENVIRONMENT" == *cuda* ]]; then
# Use jemalloc during compilation to mitigate https://github.com/pytorch/pytorch/issues/116289
export LD_PRELOAD=/usr/lib/x86_64-linux-gnu/libjemalloc.so.2
echo "NVCC version:"
nvcc --version
fi
@ -38,24 +44,30 @@ if [[ "$BUILD_ENVIRONMENT" == *cuda11* ]]; then
if [[ "$BUILD_ENVIRONMENT" != *cuda11.3* && "$BUILD_ENVIRONMENT" != *clang* ]]; then
# TODO: there is a linking issue when building with UCC using clang,
# disable it for now and to be fix later.
# TODO: disable UCC temporarily to enable CUDA 12.1 in CI
export USE_UCC=1
export USE_SYSTEM_UCC=1
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" == *executorch* ]]; then
# To build test_edge_op_registration
export BUILD_EXECUTORCH=ON
export USE_CUDA=0
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 ! which conda; then
@ -68,35 +80,7 @@ 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 [[ "$BUILD_ENVIRONMENT" == *libtorch* ]]; then
@ -168,13 +152,6 @@ if [[ "$BUILD_ENVIRONMENT" == *rocm* ]]; then
python tools/amd_build/build_amd.py
fi
if [[ "$BUILD_ENVIRONMENT" == *xpu* ]]; then
# shellcheck disable=SC1091
source /opt/intel/oneapi/compiler/latest/env/vars.sh
# XPU kineto feature dependencies are not fully ready, disable kineto build as temp WA
export USE_KINETO=0
fi
# sccache will fail for CUDA builds if all cores are used for compiling
# gcc 7 with sccache seems to have intermittent OOM issue if all cores are used
if [ -z "$MAX_JOBS" ]; then
@ -189,27 +166,11 @@ if [[ "$BUILD_ENVIRONMENT" == *cuda* && -z "$TORCH_CUDA_ARCH_LIST" ]]; then
exit 1
fi
# We only build FlashAttention files for CUDA 8.0+, and they require large amounts of
# memory to build and will OOM
if [[ "$BUILD_ENVIRONMENT" == *cuda* ]] && [[ "$TORCH_CUDA_ARCH_LIST" == *"8.6"* || "$TORCH_CUDA_ARCH_LIST" == *"8.0"* ]]; then
echo "WARNING: FlashAttention files require large amounts of memory to build and will OOM"
echo "Setting MAX_JOBS=(nproc-2)/3 to reduce memory usage"
export MAX_JOBS="$(( $(nproc --ignore=2) / 3 ))"
fi
if [[ "${BUILD_ENVIRONMENT}" == *clang* ]]; then
export CC=clang
export CXX=clang++
fi
if [[ "$BUILD_ENVIRONMENT" == *-clang*-asan* ]]; then
export LDSHARED="clang --shared"
export USE_CUDA=0
export USE_ASAN=1
export UBSAN_FLAGS="-fno-sanitize-recover=all;-fno-sanitize=float-divide-by-zero;-fno-sanitize=float-cast-overflow"
unset USE_LLVM
fi
if [[ "${BUILD_ENVIRONMENT}" == *no-ops* ]]; then
export USE_PER_OPERATOR_HEADERS=0
fi
@ -226,45 +187,20 @@ if [[ "${BUILD_ENVIRONMENT}" != *android* && "${BUILD_ENVIRONMENT}" != *cuda* ]]
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
get_bazel
install_sccache_nvcc_for_bazel
# Leave 1 CPU free and use only up to 80% of memory to reduce the change of crashing
# the runner
BAZEL_MEM_LIMIT="--local_ram_resources=HOST_RAM*.8"
BAZEL_CPU_LIMIT="--local_cpu_resources=HOST_CPUS-1"
if [[ "$CUDA_VERSION" == "cpu" ]]; then
# Build torch, the Python module, and tests for CPU-only
tools/bazel build --config=no-tty "${BAZEL_MEM_LIMIT}" "${BAZEL_CPU_LIMIT}" --config=cpu-only :torch :torch/_C.so :all_tests
else
tools/bazel build --config=no-tty "${BAZEL_MEM_LIMIT}" "${BAZEL_CPU_LIMIT}" //...
fi
tools/bazel build --config=no-tty "${BAZEL_MEM_LIMIT}" "${BAZEL_CPU_LIMIT}" //...
# Build torch, the Python module, and tests for CPU-only
tools/bazel build --config=no-tty "${BAZEL_MEM_LIMIT}" "${BAZEL_CPU_LIMIT}" --config=cpu-only :torch :_C.so :all_tests
else
# check that setup.py would fail with bad arguments
echo "The next three invocations are expected to fail with invalid command error messages."
@ -273,37 +209,16 @@ else
( ! get_exit_code python setup.py clean bad_argument )
if [[ "$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)"
@ -341,11 +256,10 @@ 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
@ -355,10 +269,10 @@ 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
@ -370,7 +284,7 @@ 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
@ -401,8 +315,4 @@ 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

@ -31,7 +31,7 @@ if [[ "$BUILD_ENVIRONMENT" != *win-* ]]; then
# as though sccache still gets used even when the sscache server isn't started
# explicitly
echo "Skipping sccache server initialization, setting environment variables"
export SCCACHE_IDLE_TIMEOUT=0
export SCCACHE_IDLE_TIMEOUT=1200
export SCCACHE_ERROR_LOG=~/sccache_error.log
export RUST_LOG=sccache::server=error
elif [[ "${BUILD_ENVIRONMENT}" == *rocm* ]]; then
@ -39,12 +39,11 @@ if [[ "$BUILD_ENVIRONMENT" != *win-* ]]; then
else
# increasing SCCACHE_IDLE_TIMEOUT so that extension_backend_test.cpp can build after this PR:
# https://github.com/pytorch/pytorch/pull/16645
SCCACHE_ERROR_LOG=~/sccache_error.log SCCACHE_IDLE_TIMEOUT=0 RUST_LOG=sccache::server=error sccache --start-server
SCCACHE_ERROR_LOG=~/sccache_error.log SCCACHE_IDLE_TIMEOUT=1200 RUST_LOG=sccache::server=error sccache --start-server
fi
# Report sccache stats for easier debugging. It's ok if this commands
# timeouts and fails on MacOS
sccache --zero-stats || true
# Report sccache stats for easier debugging
sccache --zero-stats
fi
if which ccache > /dev/null; then

View File

@ -22,3 +22,7 @@ fi
# TODO: Renable libtorch testing for MacOS, see https://github.com/pytorch/pytorch/issues/62598
# shellcheck disable=SC2034
BUILD_TEST_LIBTORCH=0
retry () {
"$@" || (sleep 1 && "$@") || (sleep 2 && "$@")
}

View File

@ -43,7 +43,7 @@ function assert_git_not_dirty() {
# TODO: we should add an option to `build_amd.py` that reverts the repo to
# an unmodified state.
if [[ "$BUILD_ENVIRONMENT" != *rocm* ]] && [[ "$BUILD_ENVIRONMENT" != *xla* ]] ; then
git_status=$(git status --porcelain | grep -v '?? third_party' || true)
git_status=$(git status --porcelain)
if [[ $git_status ]]; then
echo "Build left local git repository checkout dirty"
echo "git status --porcelain:"
@ -56,29 +56,9 @@ function assert_git_not_dirty() {
function pip_install_whl() {
# This is used to install PyTorch and other build artifacts wheel locally
# without using any network connection
# Convert the input arguments into an array
local args=("$@")
# 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
@ -100,34 +80,19 @@ function get_exit_code() {
}
function get_bazel() {
# Download and use the cross-platform, dependency-free Python
# version of Bazelisk to fetch the platform specific version of
# Bazel to use from .bazelversion.
retry curl --location --output tools/bazel \
https://raw.githubusercontent.com/bazelbuild/bazelisk/v1.16.0/bazelisk.py
shasum --algorithm=1 --check \
<(echo 'd4369c3d293814d3188019c9f7527a948972d9f8 tools/bazel')
chmod u+x tools/bazel
}
if [[ $(uname) == "Darwin" ]]; then
# download bazel version
retry curl https://github.com/bazelbuild/bazel/releases/download/4.2.1/bazel-4.2.1-darwin-x86_64 -Lo tools/bazel
# verify content
echo '74d93848f0c9d592e341e48341c53c87e3cb304a54a2a1ee9cff3df422f0b23c tools/bazel' | shasum -a 256 -c >/dev/null
else
# download bazel version
retry curl https://ossci-linux.s3.amazonaws.com/bazel-4.2.1-linux-x86_64 -o tools/bazel
# verify content
echo '1a4f3a3ce292307bceeb44f459883859c793436d564b95319aacb8af1f20557c tools/bazel' | shasum -a 256 -c >/dev/null
fi
# This function is bazel specific because of the bug
# in the bazel that requires some special paths massaging
# as a workaround. See
# https://github.com/bazelbuild/bazel/issues/10167
function install_sccache_nvcc_for_bazel() {
sudo mv /usr/local/cuda/bin/nvcc /usr/local/cuda/bin/nvcc-real
# Write the `/usr/local/cuda/bin/nvcc`
cat << EOF | sudo tee /usr/local/cuda/bin/nvcc
#!/bin/sh
if [ \$(env -u LD_PRELOAD ps -p \$PPID -o comm=) != sccache ]; then
exec sccache /usr/local/cuda/bin/nvcc "\$@"
else
exec external/local_cuda/cuda/bin/nvcc-real "\$@"
fi
EOF
sudo chmod +x /usr/local/cuda/bin/nvcc
chmod +x tools/bazel
}
function install_monkeytype {
@ -140,65 +105,21 @@ function get_pinned_commit() {
cat .github/ci_commit_pins/"${1}".txt
}
function install_torchaudio() {
local commit
commit=$(get_pinned_commit audio)
if [[ "$1" == "cuda" ]]; then
# TODO: This is better to be passed as a parameter from _linux-test workflow
# so that it can be consistent with what is set in build
TORCH_CUDA_ARCH_LIST="8.0;8.6" pip_install --no-use-pep517 --user "git+https://github.com/pytorch/audio.git@${commit}"
else
pip_install --no-use-pep517 --user "git+https://github.com/pytorch/audio.git@${commit}"
fi
}
function install_torchtext() {
local data_commit
local text_commit
data_commit=$(get_pinned_commit data)
text_commit=$(get_pinned_commit text)
pip_install --no-use-pep517 --user "git+https://github.com/pytorch/data.git@${data_commit}"
pip_install --no-use-pep517 --user "git+https://github.com/pytorch/text.git@${text_commit}"
local commit
commit=$(get_pinned_commit text)
pip_install --no-use-pep517 --user "git+https://github.com/pytorch/text.git@${commit}"
}
function install_torchvision() {
local orig_preload
local commit
commit=$(get_pinned_commit vision)
orig_preload=${LD_PRELOAD}
if [ -n "${LD_PRELOAD}" ]; then
# Silence dlerror to work-around glibc ASAN bug, see https://sourceware.org/bugzilla/show_bug.cgi?id=27653#c9
echo 'char* dlerror(void) { return "";}'|gcc -fpic -shared -o "${HOME}/dlerror.so" -x c -
LD_PRELOAD=${orig_preload}:${HOME}/dlerror.so
fi
pip_install --no-use-pep517 --user "git+https://github.com/pytorch/vision.git@${commit}"
if [ -n "${LD_PRELOAD}" ]; then
LD_PRELOAD=${orig_preload}
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=$(get_pinned_commit torchrec)
local fbgemm_commit
fbgemm_commit=$(get_pinned_commit fbgemm)
pip_uninstall torchrec-nightly
pip_uninstall fbgemm-gpu-nightly
pip_install setuptools-git-versioning scikit-build pyre-extensions
# 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}"
}
function clone_pytorch_xla() {
if [[ ! -d ./xla ]]; then
git clone --recursive --quiet https://github.com/pytorch/xla.git
git clone --recursive -b r2.0 --quiet 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 "$(cat ../.github/ci_commit_pins/xla.txt)"
@ -208,12 +129,86 @@ function clone_pytorch_xla() {
fi
}
function checkout_install_torchbench() {
function install_filelock() {
pip_install filelock
}
function install_triton() {
local commit
commit=$(get_pinned_commit torchbench)
if [[ "${TEST_CONFIG}" == *rocm* ]]; then
echo "skipping triton due to rocm"
else
commit=$(get_pinned_commit triton)
if [[ "${BUILD_ENVIRONMENT}" == *gcc7* ]]; then
# Trition needs gcc-9 to build
sudo apt-get install -y g++-9
CXX=g++-9 pip_install --user "git+https://github.com/openai/triton@${commit}#subdirectory=python"
elif [[ "${BUILD_ENVIRONMENT}" == *clang* ]]; then
# Trition needs <filesystem> which surprisingly is not available with clang-9 toolchain
sudo add-apt-repository -y ppa:ubuntu-toolchain-r/test
sudo apt-get install -y g++-9
CXX=g++-9 pip_install --user "git+https://github.com/openai/triton@${commit}#subdirectory=python"
else
pip_install --user "git+https://github.com/openai/triton@${commit}#subdirectory=python"
fi
pip_install --user jinja2
fi
}
function setup_torchdeploy_deps(){
conda install -y -n "py_${ANACONDA_PYTHON_VERSION}" "libpython-static=${ANACONDA_PYTHON_VERSION}"
local CC
local CXX
CC="$(which gcc)"
CXX="$(which g++)"
export CC
export CXX
pip install --upgrade pip
}
function checkout_install_torchdeploy() {
local commit
commit=$(get_pinned_commit multipy)
setup_torchdeploy_deps
pushd ..
git clone --recurse-submodules https://github.com/pytorch/multipy.git
pushd multipy
git checkout "${commit}"
python multipy/runtime/example/generate_examples.py
pip install -e . --install-option="--cudatests"
popd
popd
}
function test_torch_deploy(){
pushd ..
pushd multipy
./multipy/runtime/build/test_deploy
./multipy/runtime/build/test_deploy_gpu
popd
popd
}
function install_huggingface() {
local commit
commit=$(get_pinned_commit huggingface)
pip_install pandas
pip_install scipy
pip_install "git+https://github.com/huggingface/transformers.git@${commit}#egg=transformers"
}
function install_timm() {
local commit
commit=$(get_pinned_commit timm)
pip_install pandas
pip_install scipy
pip_install "git+https://github.com/rwightman/pytorch-image-models@${commit}"
}
function checkout_install_torchbench() {
git clone https://github.com/pytorch/benchmark torchbench
pushd torchbench
git checkout "$commit"
git checkout no_torchaudio
if [ "$1" ]; then
python install.py --continue_on_fail models "$@"
@ -222,11 +217,13 @@ 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
}
function test_functorch() {
python test/run_test.py --functorch --verbose
}
function print_sccache_stats() {
echo 'PyTorch Build Statistics'
sccache --show-stats

View File

@ -1,11 +1,10 @@
from datetime import datetime, timedelta, timezone
from datetime import datetime, timedelta
from tempfile import mkdtemp
from cryptography import x509
from cryptography.hazmat.primitives import hashes, serialization
from cryptography.hazmat.primitives import serialization
from cryptography.hazmat.primitives.asymmetric import rsa
from cryptography import x509
from cryptography.x509.oid import NameOID
from cryptography.hazmat.primitives import hashes
temp_dir = mkdtemp()
print(temp_dir)
@ -17,43 +16,37 @@ def genrsa(path):
key_size=2048,
)
with open(path, "wb") as f:
f.write(
key.private_bytes(
encoding=serialization.Encoding.PEM,
format=serialization.PrivateFormat.TraditionalOpenSSL,
encryption_algorithm=serialization.NoEncryption(),
)
)
f.write(key.private_bytes(
encoding=serialization.Encoding.PEM,
format=serialization.PrivateFormat.TraditionalOpenSSL,
encryption_algorithm=serialization.NoEncryption(),
))
return key
def create_cert(path, C, ST, L, O, key):
subject = issuer = x509.Name(
[
x509.NameAttribute(NameOID.COUNTRY_NAME, C),
x509.NameAttribute(NameOID.STATE_OR_PROVINCE_NAME, ST),
x509.NameAttribute(NameOID.LOCALITY_NAME, L),
x509.NameAttribute(NameOID.ORGANIZATION_NAME, O),
]
)
cert = (
x509.CertificateBuilder()
.subject_name(subject)
.issuer_name(issuer)
.public_key(key.public_key())
.serial_number(x509.random_serial_number())
.not_valid_before(datetime.now(timezone.utc))
.not_valid_after(
# Our certificate will be valid for 10 days
datetime.now(timezone.utc)
+ timedelta(days=10)
)
.add_extension(
x509.BasicConstraints(ca=True, path_length=None),
critical=True,
)
.sign(key, hashes.SHA256())
)
subject = issuer = x509.Name([
x509.NameAttribute(NameOID.COUNTRY_NAME, C),
x509.NameAttribute(NameOID.STATE_OR_PROVINCE_NAME, ST),
x509.NameAttribute(NameOID.LOCALITY_NAME, L),
x509.NameAttribute(NameOID.ORGANIZATION_NAME, O),
])
cert = x509.CertificateBuilder().subject_name(
subject
).issuer_name(
issuer
).public_key(
key.public_key()
).serial_number(
x509.random_serial_number()
).not_valid_before(
datetime.utcnow()
).not_valid_after(
# Our certificate will be valid for 10 days
datetime.utcnow() + timedelta(days=10)
).add_extension(
x509.BasicConstraints(ca=True, path_length=None), critical=True,
).sign(key, hashes.SHA256())
# Write our certificate out to disk.
with open(path, "wb") as f:
f.write(cert.public_bytes(serialization.Encoding.PEM))
@ -61,65 +54,43 @@ def create_cert(path, C, ST, L, O, key):
def create_req(path, C, ST, L, O, key):
csr = (
x509.CertificateSigningRequestBuilder()
.subject_name(
x509.Name(
[
# Provide various details about who we are.
x509.NameAttribute(NameOID.COUNTRY_NAME, C),
x509.NameAttribute(NameOID.STATE_OR_PROVINCE_NAME, ST),
x509.NameAttribute(NameOID.LOCALITY_NAME, L),
x509.NameAttribute(NameOID.ORGANIZATION_NAME, O),
]
)
)
.sign(key, hashes.SHA256())
)
csr = x509.CertificateSigningRequestBuilder().subject_name(x509.Name([
# Provide various details about who we are.
x509.NameAttribute(NameOID.COUNTRY_NAME, C),
x509.NameAttribute(NameOID.STATE_OR_PROVINCE_NAME, ST),
x509.NameAttribute(NameOID.LOCALITY_NAME, L),
x509.NameAttribute(NameOID.ORGANIZATION_NAME, O),
])).sign(key, hashes.SHA256())
with open(path, "wb") as f:
f.write(csr.public_bytes(serialization.Encoding.PEM))
return csr
def sign_certificate_request(path, csr_cert, ca_cert, private_ca_key):
cert = (
x509.CertificateBuilder()
.subject_name(csr_cert.subject)
.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_after(
# Our certificate will be valid for 10 days
datetime.now(timezone.utc)
+ timedelta(days=10)
# Sign our certificate with our private key
)
.sign(private_ca_key, hashes.SHA256())
)
cert = x509.CertificateBuilder().subject_name(
csr_cert.subject
).issuer_name(
ca_cert.subject
).public_key(
csr_cert.public_key()
).serial_number(
x509.random_serial_number()
).not_valid_before(
datetime.utcnow()
).not_valid_after(
# Our certificate will be valid for 10 days
datetime.utcnow() + timedelta(days=10)
# Sign our certificate with our private key
).sign(private_ca_key, hashes.SHA256())
with open(path, "wb") as f:
f.write(cert.public_bytes(serialization.Encoding.PEM))
return cert
ca_key = genrsa(temp_dir + "/ca.key")
ca_cert = create_cert(
temp_dir + "/ca.pem",
"US",
"New York",
"New York",
"Gloo Certificate Authority",
ca_key,
)
ca_cert = create_cert(temp_dir + "/ca.pem", u"US", u"New York", u"New York", u"Gloo Certificate Authority", ca_key)
pkey = genrsa(temp_dir + "/pkey.key")
csr = create_req(
temp_dir + "/csr.csr",
"US",
"California",
"San Francisco",
"Gloo Testing Company",
pkey,
)
csr = create_req(temp_dir + "/csr.csr", u"US", u"California", u"San Francisco", u"Gloo Testing Company", pkey)
cert = sign_certificate_request(temp_dir + "/cert.pem", csr, ca_cert, ca_key)

View File

@ -6,4 +6,5 @@ source "$(dirname "${BASH_SOURCE[0]}")/common.sh"
echo "Testing pytorch docs"
cd docs
TERM=vt100 make doctest
pip_install -r requirements.txt
make doctest

View File

@ -1,40 +0,0 @@
#!/bin/bash
# This is where the local pytorch install in the docker image is located
pt_checkout="/var/lib/jenkins/workspace"
source "$pt_checkout/.ci/pytorch/common_utils.sh"
echo "functorch_doc_push_script.sh: Invoked with $*"
set -ex
version=${DOCS_VERSION:-nightly}
echo "version: $version"
# Build functorch docs
pushd $pt_checkout/functorch/docs
make html
popd
git clone https://github.com/pytorch/functorch -b gh-pages --depth 1 functorch_ghpages
pushd functorch_ghpages
if [ "$version" == "main" ]; then
version=nightly
fi
git rm -rf "$version" || true
mv "$pt_checkout/functorch/docs/build/html" "$version"
git add "$version" || true
git status
git config user.email "soumith+bot@pytorch.org"
git config user.name "pytorchbot"
# If there aren't changes, don't make a commit; push is no-op
git commit -m "Generate Python docs from pytorch/pytorch@${GITHUB_SHA}" || true
git status
if [[ "${WITH_PUSH:-}" == true ]]; then
git push -u origin gh-pages
fi
popd

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

@ -40,14 +40,8 @@ cross_compile_arm64() {
USE_DISTRIBUTED=0 CMAKE_OSX_ARCHITECTURES=arm64 MACOSX_DEPLOYMENT_TARGET=11.0 USE_MKLDNN=OFF USE_QNNPACK=OFF WERROR=1 BUILD_TEST=OFF USE_PYTORCH_METAL=1 python setup.py bdist_wheel
}
compile_arm64() {
# Compilation for arm64
# TODO: Compile with OpenMP support (but this causes CI regressions as cross-compilation were done with OpenMP disabled)
USE_DISTRIBUTED=0 USE_OPENMP=1 MACOSX_DEPLOYMENT_TARGET=11.0 WERROR=1 BUILD_TEST=OFF USE_PYTORCH_METAL=1 python setup.py bdist_wheel
}
compile_x86_64() {
USE_DISTRIBUTED=0 WERROR=1 python setup.py bdist_wheel --plat-name=macosx_10_9_x86_64
USE_DISTRIBUTED=0 WERROR=1 python setup.py bdist_wheel
}
build_lite_interpreter() {
@ -68,14 +62,8 @@ build_lite_interpreter() {
"${CPP_BUILD}/caffe2/build/bin/test_lite_interpreter_runtime"
}
print_cmake_info
if [[ ${BUILD_ENVIRONMENT} = *arm64* ]]; then
if [[ $(uname -m) == "arm64" ]]; then
compile_arm64
else
cross_compile_arm64
fi
cross_compile_arm64
elif [[ ${BUILD_ENVIRONMENT} = *lite-interpreter* ]]; then
export BUILD_LITE_INTERPRETER=1
build_lite_interpreter

View File

@ -9,25 +9,6 @@ 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=10.9
export CXX=clang++
export CC=clang
print_cmake_info() {
CMAKE_EXEC=$(which cmake)
echo "$CMAKE_EXEC"
CONDA_INSTALLATION_DIR=$(dirname "$CMAKE_EXEC")
# Print all libraries under cmake rpath for debugging
ls -la "$CONDA_INSTALLATION_DIR/../lib"
export CMAKE_EXEC
# Explicitly add conda env lib folder to cmake rpath to address the flaky issue
# where cmake dependencies couldn't be found. This seems to point to how conda
# links $CMAKE_EXEC to its package cache when cloning a new environment
install_name_tool -add_rpath @executable_path/../lib "${CMAKE_EXEC}" || true
# Adding the rpath will invalidate cmake signature, so signing it again here
# to trust the executable. EXC_BAD_ACCESS (SIGKILL (Code Signature Invalid))
# with an exit code 137 otherwise
codesign -f -s - "${CMAKE_EXEC}" || true
}

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.
@ -23,11 +25,9 @@ setup_test_python() {
# using the address associated with the loopback interface.
export GLOO_SOCKET_IFNAME=lo0
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() {
@ -70,19 +70,37 @@ test_libtorch() {
VERBOSE=1 DEBUG=1 python "$BUILD_LIBTORCH_PY"
popd
MNIST_DIR="${PWD}/test/cpp/api/mnist"
python tools/download_mnist.py --quiet -d "${MNIST_DIR}"
python tools/download_mnist.py --quiet -d test/cpp/api/mnist
# Unfortunately it seems like the test can't load from miniconda3
# without these paths being set
export DYLD_LIBRARY_PATH="$DYLD_LIBRARY_PATH:$PWD/miniconda3/lib"
export LD_LIBRARY_PATH="$LD_LIBRARY_PATH:$PWD/miniconda3/lib"
TORCH_CPP_TEST_MNIST_PATH="${MNIST_DIR}" CPP_TESTS_DIR="${CPP_BUILD}/caffe2/bin" python test/run_test.py --cpp --verbose -i cpp/test_api
TORCH_CPP_TEST_MNIST_PATH="test/cpp/api/mnist" "$CPP_BUILD"/caffe2/bin/test_api
assert_git_not_dirty
fi
}
print_cmake_info() {
CMAKE_EXEC=$(which cmake)
echo "$CMAKE_EXEC"
CONDA_INSTALLATION_DIR=$(dirname "$CMAKE_EXEC")
# Print all libraries under cmake rpath for debugging
ls -la "$CONDA_INSTALLATION_DIR/../lib"
export CMAKE_EXEC
# Explicitly add conda env lib folder to cmake rpath to address the flaky issue
# where cmake dependencies couldn't be found. This seems to point to how conda
# links $CMAKE_EXEC to its package cache when cloning a new environment
install_name_tool -add_rpath @executable_path/../lib "${CMAKE_EXEC}" || true
# Adding the rpath will invalidate cmake signature, so signing it again here
# to trust the executable. EXC_BAD_ACCESS (SIGKILL (Code Signature Invalid))
# with an exit code 137 otherwise
codesign -f -s - "${CMAKE_EXEC}" || true
}
test_custom_backend() {
print_cmake_info
@ -148,9 +166,9 @@ test_jit_hooks() {
assert_git_not_dirty
}
install_tlparse
if [[ $NUM_TEST_SHARDS -gt 1 ]]; then
if [[ "${TEST_CONFIG}" == *functorch* ]]; then
test_functorch
elif [[ $NUM_TEST_SHARDS -gt 1 ]]; then
test_python_shard "${SHARD_NUMBER}"
if [[ "${SHARD_NUMBER}" == 1 ]]; then
test_libtorch

View File

@ -8,7 +8,6 @@
source "$(dirname "${BASH_SOURCE[0]}")/common.sh"
echo "Testing pytorch"
time python test/run_test.py --include test_cuda_multigpu test_cuda_primary_ctx --verbose
# Disabling tests to see if they solve timeout issues; see https://github.com/pytorch/pytorch/issues/70015
# python tools/download_mnist.py --quiet -d test/cpp/api/mnist
@ -18,9 +17,7 @@ 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
@ -30,33 +27,23 @@ time python test/run_test.py --verbose -i distributed/checkpoint/test_checkpoint
time python test/run_test.py --verbose -i distributed/checkpoint/test_file_system_checkpoint
time python test/run_test.py --verbose -i distributed/_shard/sharding_spec/test_sharding_spec
time python test/run_test.py --verbose -i distributed/_shard/sharding_plan/test_sharding_plan
time python test/run_test.py --verbose -i distributed/_shard/sharded_tensor/test_megatron_prototype
time python test/run_test.py --verbose -i distributed/_shard/sharded_tensor/test_sharded_tensor
time python test/run_test.py --verbose -i distributed/_shard/sharded_tensor/test_sharded_tensor_reshard
# 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
# DeviceMesh test
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_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
time python test/run_test.py --verbose -i distributed/_shard/sharded_tensor/ops/test_chunk
time python test/run_test.py --verbose -i distributed/_shard/sharded_tensor/ops/test_elementwise_ops
time python test/run_test.py --verbose -i distributed/_shard/sharded_tensor/ops/test_embedding
time python test/run_test.py --verbose -i distributed/_shard/sharded_tensor/ops/test_embedding_bag
time python test/run_test.py --verbose -i distributed/_shard/sharded_tensor/ops/test_binary_cmp
time python test/run_test.py --verbose -i distributed/_shard/sharded_tensor/ops/test_init
time python test/run_test.py --verbose -i distributed/_shard/sharded_tensor/ops/test_linear
time python test/run_test.py --verbose -i distributed/_shard/sharded_tensor/ops/test_math_ops
time python test/run_test.py --verbose -i distributed/_shard/sharded_tensor/ops/test_matrix_ops
time python test/run_test.py --verbose -i distributed/_shard/sharded_tensor/ops/test_softmax
time python test/run_test.py --verbose -i distributed/_shard/sharded_optim/test_sharded_optim
time python test/run_test.py --verbose -i distributed/_shard/test_partial_tensor
time python test/run_test.py --verbose -i distributed/_shard/test_replicated_tensor
# 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_foreach -- -k test_tensors_grouping
time python test/run_test.py --verbose -i test_optim -- -k optimizers_with_varying_tensors
assert_git_not_dirty

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