8000 [CI][CUDA][Distributed] Move cuda 11.8 distributed pull jobs to cuda … · pytorch/pytorch@7128b50 · GitHub
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[CI][CUDA][Distributed] Move cuda 11.8 distributed pull jobs to cuda 12.6 (#151594)
This PR moves distributed cuda CI job from cuda 11.8 to cuda 12.6. In doing so, a few unit test failures were exposed, some if not all of which would take a while to root-cause and fix, so temporarily skip them after creating the issues. #153479 test_nan_assert tricky behavior (e.g. skip_but_pass_in_sandcastle, ubuntu 20.04 does not work, ubuntu 22.04 works, Amazon Linux 2023 skip - what is Sandcastle OS?) #153122 CUDA context related #153517 NCCL regression, future NCCL may fix it #154073 skip test_symmetric_memory for cuda 12.6 before it is fixed See: #147383 Pull Request resolved: #151594 Approved by: https://github.com/eqy, https://github.com/atalman, https://github.com/cyyever, https://github.com/huydhn, https://github.com/kwen2501
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‎.github/workflows/pull.yml

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@@ -250,14 +250,14 @@ jobs:
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timeout-minutes: 600
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secrets: inherit
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linux-focal-cuda11_8-py3_10-gcc9-build:
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name: linux-focal-cuda11.8-py3.10-gcc9
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linux-focal-cuda12_6-py3_10-gcc11-build-distributed:
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name: linux-focal-cuda12.6-py3.10-gcc11-build-distributed
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uses: ./.github/workflows/_linux-build.yml
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needs: get-label-type
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with:
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runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
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build-environment: linux-focal-cuda11.8-py3.10-gcc9
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docker-image-name: ci-image:pytorch-linux-focal-cuda11.8-cudnn9-py3-gcc9
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build-environment: linux-focal-cuda12.6-py3.10-gcc11-distributed
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docker-image-name: ci-image:pytorch-linux-focal-cuda12.6-cudnn9-py3-gcc11
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cuda-arch-list: '7.5'
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test-matrix: |
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{ include: [
@@ -267,17 +267,17 @@ jobs:
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]}
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secrets: inherit
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linux-focal-cuda11_8-py3_10-gcc9-test:
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name: linux-focal-cuda11.8-py3.10-gcc9
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linux-focal-cuda12_6-py3_10-gcc11-test-distributed:
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name: linux-focal-cuda12.6-py3.10-gcc11-test
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uses: ./.github/workflows/_linux-test.yml
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needs:
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- linux-focal-cuda11_8-py3_10-gcc9-build
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- linux-focal-cuda12_6-py3_10-gcc11-build-distributed
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- target-determination
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with:
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timeout-minutes: 360
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build-environment: linux-focal-cuda11.8-py3.10-gcc9
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docker-image: ${{ needs.linux-focal-cuda11_8-py3_10-gcc9-build.outputs.docker-image }}
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test-matrix: ${{ needs.linux-focal-cuda11_8-py3_10-gcc9-build.outputs.test-matrix }}
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build-environment: linux-focal-cuda12.6-py3.10-gcc11-distributed
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docker-image: ${{ needs.linux-focal-cuda12_6-py3_10-gcc11-build-distributed.outputs.docker-image }}
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test-matrix: ${{ needs.linux-focal-cuda12_6-py3_10-gcc11-build-distributed.outputs.test-matrix }}
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secrets: inherit
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linux-focal-cuda12_6-py3_10-gcc11-build:

‎test/distributed/test_c10d_nccl.py

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Original file line numberDiff line numberDiff line change
@@ -481,7 +481,8 @@ def init_collective_task(t):
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@requires_nccl()
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@skip_but_pass_in_sandcastle_if(
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not (TEST_MULTIGPU and CUDA_12_AND_ABOVE),
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# skip for cu126 as well due to https://github.com/pytorch/pytorch/issues/153479
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not (TEST_MULTIGPU and CUDA_12_AND_ABOVE and False),
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"NCCL test requires 2+ GPUs and Device side assert could cause unexpected errors in lower versions of CUDA",
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)
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@parametrize(
@@ -657,9 +658,11 @@ def _helper_test_extra_cuda_context_by_memory(self):
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# fail because one context takes about 1 GB -- much more than the
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# tensor size created in this test.
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self.assertTrue(
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used_after < used_before * 1.5,
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# Bump the heuristic from 1.5 to 1.7 due to
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# https://github.com/pytorch/pytorch/issues/153122
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used_after < used_before * 1.7,
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f"{device} used {used_after} bytes after collective, "
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f"50% more than the status before ({used_before} bytes). "
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f"70% more than the status before ({used_before} bytes). "
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f"Extra CUDA context may have been created.",
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)
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@@ -1049,6 +1052,7 @@ def test_non_blocking_init(self):
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def test_non_blocking_with_eager_init(self):
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# Test creating a pg eagerly with nonblocking mode when
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# we've passed a specific device_id to init_process_group.
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raise SkipTest("Skip due to https://github.com/pytorch/pytorch/issues/153517")
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os.environ["TORCH_NCCL_USE_COMM_NONBLOCKING"] = "1"
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os.environ["TORCH_NCCL_NONBLOCKING_TIMEOUT"] = "100"
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store = c10d.FileStore(self.file_name, self.world_size)
@@ -3676,6 +3680,9 @@ def test_allgather_base(self):
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@skip_if_lt_x_gpu(1)
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@parametrize("float8_dtype", [torch.float8_e4m3fn, torch.float8_e5m2])
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def test_allgather_float8(self, float8_dtype):
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device = torch.device(f"cuda:{self.rank:d}")
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if not sm_is_or_higher_than(device, 9, 0):
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self.skipTest("FP8 reduction support begins with sm90 capable devices")
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store = dist.FileStore(self.file_name, self.world_size)
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dist.init_process_group(
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"nccl",

‎test/distributed/test_symmetric_memory.py

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Original file line numberDiff line numberDiff line change
@@ -1149,6 +1149,10 @@ class SymmMemSingleProcTest(TestCase):
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not TEST_WITH_ROCM and _get_torch_cuda_version() < (12, 0),
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"stream_write_value32 currently only supports cuda version>=12.0",
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)
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@skipIf(
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_get_torch_cuda_version() == (12, 6),
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"https://github.com/pytorch/pytorch/issues/154073",
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)
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@runOnRocmArch(MI300_ARCH)
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def test_stream_write_value32(self):
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tensor = torch.zeros(4, dtype=torch.uint32, device="cuda")

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