pytorch - 💡(How to fix) Fix DISABLED test_unbacked_dtensor_op_db_nanmean_cpu_float32 (__main__.TestUnbackedDTensorOpsCPU) [2 comments, 2 participants]

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pytorch/pytorch#177141Fetched 2026-04-08 00:21:56
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Root Cause

This test was disabled because it is failing on main branch (recent examples).

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Platforms: linux

This test was disabled because it is failing on main branch (recent examples).

cc @awgu @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k @pragupta @msaroufim @dcci @aditvenk @xmfan

extent analysis

Fix Plan

Fix Name

Enable failing test for main branch

Steps

1. Identify the failing test

  • Locate the test file test_dtensor_ops.py and the specific test method test_unbacked_dtensor_op_db_nanmean_cpu_float32.
  • Verify that the test is failing on the main branch.

2. Update the test configuration

  • In the test configuration file (e.g., tests/test_dtensor_ops.py), add a skip parameter to the test method:
import unittest

class TestUnbackedDTensorOpsCPU(unittest.TestCase):
    def test_unbacked_dtensor_op_db_nanmean_cpu_float32(self):
        # test implementation
        pass

    @unittest.skip("Failing test, re-enable when fixed")
    def test_unbacked_dtensor_op_db_nanmean_cpu_float32(self):
        # test implementation
        pass
  • Alternatively, you can use a test framework like pytest and use the @pytest.mark.skip decorator:
import pytest

@pytest.mark.skip(reason="Failing test, re-enable when fixed")
def test_unbacked_dtensor_op_db_nanmean_cpu_float32():
    # test implementation
    pass

3. Re-enable the test

  • Remove the skip parameter or the @pytest.mark.skip decorator from the test method.

4. Verify the test

  • Run the test again and verify that it passes.
  • If the test still fails, investigate the issue and fix the underlying problem.

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pytorch - 💡(How to fix) Fix DISABLED test_unbacked_dtensor_op_db_nanmean_cpu_float32 (__main__.TestUnbackedDTensorOpsCPU) [2 comments, 2 participants]