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[Bug]: Multi GPU tests failing silently #11614

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Description

@greg-kwasniewski1

🚀 The feature, motivation and pitch

Issue

Running any multi-GPU test via spawn_multiprocess_job (e.g.
test_sharding[MLP-torch_dist_all_reduce-False-False-2]) reports 1 passed
even though both child processes crash during initialization with:

File "/usr/lib/python3.12/multiprocessing/synchronize.py", line 115, in __setstate__
    self._semlock = _multiprocessing.SemLock._rebuild(*state)
FileNotFoundError: [Errno 2] No such file or directory

The test body never executes — the processes die before reaching
init_and_run_process — yet pytest shows a green result.

Steps to reproduce:
Launch any multi-gpu test and put assert False on top. Test will still be reported as "Passed", even though the output log reports a failed assert.

$ git diff tests/unittest/_torch/auto_deploy/unit/multigpu/transformations/library/test_tp_sharding.py
@@ -417,6 +417,7 @@ def _run_sharding_execution_job(
     rank: int,
     world_size: int,
 ) -> None:
+    assert False
     # init model and input
     batch_size = 4
     sequence_len = 8
pytest tests/unittest/_torch/auto_deploy/unit/multigpu/t
ransformations/library/test_tp_sharding.py::test_sharding[MLP-torch_dist_all_reduce-False-False-2] 

Output:

============== 1 passed, 4 warnings in 19.89s =======

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Activity

  1. added
    bugSomething isn't working
    feature requestNew feature or request. This includes new model, dtype, functionality support
    AutoDeploy<NV> AutoDeploy Backend
    on Feb 21, 2026
  2. added
    Scale-out<NV>Multi-GPU and distributed inference scaling issues, tensor/pipeline/data parallelism
    Testing<NV>Continuous integration, build system, and testing infrastructure issues
    on Feb 21, 2026
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AutoDeploy<NV> AutoDeploy BackendScale-out<NV>Multi-GPU and distributed inference scaling issues, tensor/pipeline/data parallelismTesting<NV>Continuous integration, build system, and testing infrastructure issuesbugSomething isn't workingfeature requestNew feature or request. This includes new model, dtype, functionality support

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