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DISABLED test_sdpa_backwards_cuda_bfloat16 (__main__.TestNestedTensorSubclassCUDA) #125058

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pytorch-bot bot opened this issue Apr 26, 2024 · 1 comment
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module: flaky-tests Problem is a flaky test in CI module: nestedtensor NestedTensor tag see issue #25032 skipped Denotes a (flaky) test currently skipped in CI. triaged This issue has been looked at a team member, and triaged and prioritized into an appropriate module

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pytorch-bot bot commented Apr 26, 2024

Platforms: linux, slow

This test was disabled because it is failing in CI. See recent examples and the most recent trunk workflow logs.

Over the past 3 hours, it has been determined flaky in 2 workflow(s) with 2 failures and 2 successes.

Debugging instructions (after clicking on the recent samples link):
DO NOT ASSUME THINGS ARE OKAY IF THE CI IS GREEN. We now shield flaky tests from developers so CI will thus be green but it will be harder to parse the logs.
To find relevant log snippets:

  1. Click on the workflow logs linked above
  2. Click on the Test step of the job so that it is expanded. Otherwise, the grepping will not work.
  3. Grep for test_sdpa_backwards_cuda_bfloat16
  4. There should be several instances run (as flaky tests are rerun in CI) from which you can study the logs.
Sample error message
Traceback (most recent call last):
  File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/testing/_internal/common_utils.py", line 2757, in wrapper
    method(*args, **kwargs)
  File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/testing/_internal/common_utils.py", line 2757, in wrapper
    method(*args, **kwargs)
  File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/testing/_internal/common_utils.py", line 2756, in wrapper
    with policy():
  File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/testing/_internal/common_utils.py", line 2205, in __exit__
    raise RuntimeError(msg)
RuntimeError: CUDA driver API confirmed a leak in __main__.TestNestedTensorSubclassCUDA.test_sdpa_backwards_cuda_bfloat16! Caching allocator allocated memory was 4608 and is now reported as 18944 on device 0. CUDA driver allocated memory was 380305408 and is now 382402560.

To execute this test, run the following from the base repo dir:
    PYTORCH_TEST_CUDA_MEM_LEAK_CHECK=1 PYTORCH_TEST_WITH_SLOW_GRADCHECK=1 python test/test_nestedtensor.py -k test_sdpa_backwards_cuda_bfloat16

This message can be suppressed by setting PYTORCH_PRINT_REPRO_ON_FAILURE=0

Test file path: test_nestedtensor.py

cc @clee2000 @cpuhrsch @jbschlosser @bhosmer @drisspg @soulitzer

@pytorch-bot pytorch-bot bot added module: flaky-tests Problem is a flaky test in CI module: nestedtensor NestedTensor tag see issue #25032 skipped Denotes a (flaky) test currently skipped in CI. triaged This issue has been looked at a team member, and triaged and prioritized into an appropriate module labels Apr 26, 2024
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pytorch-bot bot commented Apr 26, 2024

Hello there! From the DISABLED prefix in this issue title, it looks like you are attempting to disable a test in PyTorch CI. The information I have parsed is below:
  • Test name: test_sdpa_backwards_cuda_bfloat16 (__main__.TestNestedTensorSubclassCUDA)
  • Platforms for which to skip the test: linux, slow
  • Disabled by pytorch-bot[bot]

Within ~15 minutes, test_sdpa_backwards_cuda_bfloat16 (__main__.TestNestedTensorSubclassCUDA) will be disabled in PyTorch CI for these platforms: linux, slow. Please verify that your test name looks correct, e.g., test_cuda_assert_async (__main__.TestCuda).

To modify the platforms list, please include a line in the issue body, like below. The default action will disable the test for all platforms if no platforms list is specified.

Platforms: case-insensitive, list, of, platforms

We currently support the following platforms: asan, dynamo, inductor, linux, mac, macos, rocm, slow, win, windows.

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Labels
module: flaky-tests Problem is a flaky test in CI module: nestedtensor NestedTensor tag see issue #25032 skipped Denotes a (flaky) test currently skipped in CI. triaged This issue has been looked at a team member, and triaged and prioritized into an appropriate module
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