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pytorch - 💡(How to fix) Fix DISABLED test_cudagraph_indexing_ops_select_scatter_cuda_float32 (__main__.TestCudagraphIndexingOpsCUDA)

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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 3444, in wrapper method(*args, **kwargs) File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/testing/_internal/common_utils.py", line 3444, in wrapper method(*args, **kwargs) File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/testing/_internal/common_utils.py", line 3443, in wrapper with policy(): File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/testing/_internal/common_utils.py", line 2820, in exit raise RuntimeError(msg) RuntimeError: CUDA driver API confirmed a leak in main.TestCudagraphIndexingOpsCUDA.test_cudagraph_indexing_ops_select_scatter_cuda_float32! Caching allocator allocated memory was 2048 and is now reported as 4096 on device 0. CUDA driver allocated memory was 373489664 and is now 375586816.

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/inductor/test_cudagraph_trees.py TestCudagraphIndexingOpsCUDA.test_cudagraph_indexing_ops_select_scatter_cuda_float32

This message can be suppressed by setting PYTORCH_PRINT_REPRO_ON_FAILURE=0

Root Cause

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

Code Example

Traceback (most recent call last):
  File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/testing/_internal/common_utils.py", line 3444, in wrapper
    method(*args, **kwargs)
  File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/testing/_internal/common_utils.py", line 3444, in wrapper
    method(*args, **kwargs)
  File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/testing/_internal/common_utils.py", line 3443, in wrapper
    with policy():
  File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/testing/_internal/common_utils.py", line 2820, in __exit__
    raise RuntimeError(msg)
RuntimeError: CUDA driver API confirmed a leak in __main__.TestCudagraphIndexingOpsCUDA.test_cudagraph_indexing_ops_select_scatter_cuda_float32! Caching allocator allocated memory was 2048 and is now reported as 4096 on device 0. CUDA driver allocated memory was 373489664 and is now 375586816.

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/inductor/test_cudagraph_trees.py TestCudagraphIndexingOpsCUDA.test_cudagraph_indexing_ops_select_scatter_cuda_float32

This message can be suppressed by setting PYTORCH_PRINT_REPRO_ON_FAILURE=0
RAW_BUFFERClick to expand / collapse

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 6 hours, it has been determined flaky in 5 workflow(s) with 5 failures and 5 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_cudagraph_indexing_ops_select_scatter_cuda_float32
  4. There should be several instances run (as flaky tests are rerun in CI) from which you can study the logs.
<details><summary>Sample error message</summary> 
Traceback (most recent call last):
  File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/testing/_internal/common_utils.py", line 3444, in wrapper
    method(*args, **kwargs)
  File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/testing/_internal/common_utils.py", line 3444, in wrapper
    method(*args, **kwargs)
  File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/testing/_internal/common_utils.py", line 3443, in wrapper
    with policy():
  File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/testing/_internal/common_utils.py", line 2820, in __exit__
    raise RuntimeError(msg)
RuntimeError: CUDA driver API confirmed a leak in __main__.TestCudagraphIndexingOpsCUDA.test_cudagraph_indexing_ops_select_scatter_cuda_float32! Caching allocator allocated memory was 2048 and is now reported as 4096 on device 0. CUDA driver allocated memory was 373489664 and is now 375586816.

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/inductor/test_cudagraph_trees.py TestCudagraphIndexingOpsCUDA.test_cudagraph_indexing_ops_select_scatter_cuda_float32

This message can be suppressed by setting PYTORCH_PRINT_REPRO_ON_FAILURE=0
</details>

Test file path: inductor/test_cudagraph_trees.py

For all disabled tests (by GitHub issue), see https://hud.pytorch.org/disabled.

cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @kadeng @muchulee8 @amjames @chauhang @aakhundov @coconutruben @jataylo

extent analysis

TL;DR

The most likely fix for the flaky test is to investigate and address the reported CUDA memory leak in the test_cudagraph_indexing_ops_select_scatter_cuda_float32 test.

Guidance

  • Review the workflow logs and grep for test_cudagraph_indexing_ops_select_scatter_cuda_float32 to study the logs and identify patterns or clues that may indicate the cause of the memory leak.
  • Run the test with the provided command PYTORCH_TEST_CUDA_MEM_LEAK_CHECK=1 PYTORCH_TEST_WITH_SLOW_GRADCHECK=1 python test/inductor/test_cudagraph_trees.py TestCudagraphIndexingOpsCUDA.test_cudagraph_indexing_ops_select_scatter_cuda_float32 to reproduce the issue and gather more information.
  • Investigate the CUDA driver API and caching allocator to understand why the allocated memory is increasing and not being released.
  • Consider setting PYTORCH_PRINT_REPRO_ON_FAILURE=0 to suppress the error message and focus on debugging the underlying issue.

Example

No code snippet is provided as the issue is related to a specific test and CUDA memory leak, and modifying the code without understanding the root cause may not be effective.

Notes

The issue is specific to the test_cudagraph_indexing_ops_select_scatter_cuda_float32 test and the CUDA memory leak, so the guidance is focused on debugging and investigating this particular issue. The provided command and workflow logs should help identify the cause of the problem.

Recommendation

Apply workaround: Investigate and address the CUDA memory leak to stabilize the test. This approach is recommended as it targets the root cause of the issue, rather than just suppressing the error message.

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#api#ssr#memory leak#API versioning#request timeout

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