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pytorch - 💡(How to fix) Fix DISABLED test_cudagraph_indexing_ops_diagonal_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_diagonal_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_diagonal_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_diagonal_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_diagonal_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_diagonal_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_diagonal_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_diagonal_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 test_cudagraph_indexing_ops_diagonal_scatter_cuda_float32 is to investigate and address the reported CUDA memory leak.

Guidance

  • Investigate the CUDA memory leak by analyzing the workflow logs and grep for test_cudagraph_indexing_ops_diagonal_scatter_cuda_float32 to identify patterns or clues.
  • Run the test with PYTORCH_TEST_CUDA_MEM_LEAK_CHECK=1 and PYTORCH_TEST_WITH_SLOW_GRADCHECK=1 to reproduce the issue and gather more information.
  • Review the test code in inductor/test_cudagraph_trees.py to ensure proper memory management and CUDA resource handling.
  • 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, which requires further investigation.

Notes

The issue is specific to the Linux platform and is related to a flaky test. The provided error message indicates a CUDA memory leak, which needs to be addressed.

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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