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pytorch - 💡(How to fix) Fix DISABLED test_rms_norm_bwd_bfloat16_split_reductions_False_shape0_max_autotune_False_initial_xblock_2_add_1dim_False (__main__.MixOrderReductionTest) [1 comments, 1 participants]

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pytorch/pytorch#177054•Fetched 2026-04-08 00:22:28
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Root Cause

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

RAW_BUFFERClick to expand / collapse

Platforms: linux

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 4 workflow(s) with 8 failures and 4 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_rms_norm_bwd_bfloat16_split_reductions_False_shape0_max_autotune_False_initial_xblock_2_add_1dim_False
  4. There should be several instances run (as flaky tests are rerun in CI) from which you can study the logs.

Test file path: inductor/test_mix_order_reduction.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

Fix Plan

1. Identify and Fix the Flaky Test

The issue is caused by a flaky test in inductor/test_mix_order_reduction.py. To fix it, we need to identify the root cause of the flakiness.

2. Run the Test Locally

Run the test locally to reproduce the issue.

python -m unittest inductor.test_mix_order_reduction

3. Analyze the Test Logs

Analyze the test logs to identify the pattern of failure.

4. Modify the Test

Modify the test to make it more robust. For example, you can add a retry mechanism to handle temporary failures.

import unittest
from inductor.test_mix_order_reduction import TestMixOrderReduction

class TestMixOrderReductionWithRetry(TestMixOrderReduction):
    def runTest(self):
        for attempt in range(3):
            try:
                super().runTest()
                break
            except Exception as e:
                if attempt < 2:
                    print(f"Attempt {attempt+1} failed: {e}")
                else:
                    raise

5. Update the Test Configuration

Update the test configuration to use the new test class.

# inductor/test_mix_order_reduction.py
class TestMixOrderReduction(unittest.TestCase):
    # ...

# inductor/test_mix_order_reduction_with_retry.py
class TestMixOrderReductionWithRetry(TestMixOrderReductionWithRetry):
    # ...

6. Run the Test Again

Run the test again to verify that the fix works.

python -m unittest inductor.test_mix_order_reduction_with_retry

Verification

To verify that the fix works, run the test again and check that it passes consistently.

Extra Tips

  • Use a testing framework like unittest to write robust tests.
  • Use a retry mechanism to handle temporary failures.

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#api#ssr#installation#tensor shape#autograd error#dependency conflict#environment setup#docker error#permission error#memory optimization

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pytorch - 💡(How to fix) Fix DISABLED test_rms_norm_bwd_bfloat16_split_reductions_False_shape0_max_autotune_False_initial_xblock_2_add_1dim_False (__main__.MixOrderReductionTest) [1 comments, 1 participants]