pytorch-bot[bot]
commented
2 weeks ago
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_gelu_dynamic_shapes_cpu (__main__.DynamicShapesCpuTests)`
* Platforms for which to skip the test: linux
* Disabled by `pytorch-bot[bot]`
Within ~15 minutes, `test_gelu_dynamic_shapes_cpu (__main__.DynamicShapesCpuTests)` will be disabled in PyTorch CI for these platforms: linux. 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.
### How to re-enable a test
To re-enable the test globally, close the issue. To re-enable a test for only a subset of platforms, remove the platforms from the list in the issue body. This may take some time to propagate. To re-enable a test only for a PR, put `Fixes #135222` in the PR body and rerun the test jobs. Note that if a test is flaky, it maybe be difficult to tell if the test is still flaky on the PR.
bdhirsh
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 3 hours, it has been determined flaky in 21 workflow(s) with 21 failures and 21 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:
test_gelu_dynamic_shapes_cpuSample error message
``` Traceback (most recent call last): File "/var/lib/jenkins/workspace/test/inductor/test_torchinductor.py", line 5206, in test_gelu self.common( File "/var/lib/jenkins/workspace/test/inductor/test_torchinductor.py", line 381, in check_model eager_result = model(*ref_inputs, **ref_kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/var/lib/jenkins/workspace/test/inductor/test_torchinductor.py", line 5204, in fn return aten.gelu(x) + 2, aten.gelu(x + 1) ^^^^^^^^^^^^ File "/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_ops.py", line 1116, in __call__ return self._op(*args, **(kwargs or {})) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ MemoryError: std::bad_alloc To execute this test, run the following from the base repo dir: python test/inductor/test_torchinductor_dynamic_shapes.py DynamicShapesCpuTests.test_gelu_dynamic_shapes_cpu This message can be suppressed by setting PYTORCH_PRINT_REPRO_ON_FAILURE=0 ```Test file path:
inductor/test_torchinductor_dynamic_shapes.pyResponseTimeoutError: Response timeout for 5000ms, GET https://raw.githubusercontent.com/pytorch/pytorch/main/test/inductor/test_torchinductor_dynamic_shapes.py -1 (connected: true, keepalive socket: false, socketHandledRequests: 1, socketHandledResponses: 0) headers: {}
cc @ezyang @gchanan @zou3519 @kadeng @msaroufim @clee2000 @chauhang @penguinwu @avikchaudhuri @gmagogsfm @zhxchen17 @tugsbayasgalan @angelayi @suo @ydwu4 @desertfire @chenyang78