Testing CI

[winskuo-quic]

Summary

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Test plan

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[pytorch-bot]

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❌ 8 New Failures, 1 Cancelled Job

As of commit 43cfbcb with merge base 2c706f1 ():

NEW FAILURES - The following jobs have failed:

• pull / test-qnn-wheel-packages-linux (3.10) / linux-job (gh)
  RuntimeError: Command docker exec -t 842697c348bcf305cf8281b5f1aaa5624082bd451a9909d7ae6e91a9da44027e /exec failed with exit code 1
• pull / test-samsung-models-linux / linux-job (gh)
  RuntimeError: Command docker exec -t 5b645ec04e0b47994e10848077448c29239906b491b4cd104b4f6ce34def99cd /exec failed with exit code 1
• Test CUDA Builds / export-gemma3-cuda-non-quantized / linux-job (gh)
  RuntimeError: Command docker exec -t cf1d331085a29ad4bc7bb67bc5551b247a600215d43490ca2d2907557fa721a2 /exec failed with exit code 2
• Test CUDA Builds / export-voxtral-cuda-non-quantized / linux-job (gh)
  RuntimeError: Command docker exec -t 111a0bb28a39c38cad4c3549615f8ae47efdce0c5b77839ae1ddb3043e2569ce /exec failed with exit code 2
• Test CUDA Builds / export-voxtral-cuda-quantized-int4-tile-packed / linux-job (gh)
  RuntimeError: Command docker exec -t 0d9a007bc094d597bcd694f62446d0a6f1a4315b53c51ec42d0ff76425a4e9cb /exec failed with exit code 2
• Test CUDA Builds / export-voxtral-cuda-quantized-int4-weight-only / linux-job (gh)
  RuntimeError: Command docker exec -t 6127f300d6a4dae35f6b91eba08a3d0d9b0d609ea139da2b697a073225aa48b7 /exec failed with exit code 2
• Test Metal Backend / export-voxtral-metal-artifact / macos-job (gh)
  RuntimeError: Command bash /Users/ec2-user/runner/_work/_temp/exec_script failed with exit code 2
• trunk / test-arm-backend (test_model_smollm2-135M) / linux-job (gh)
  RuntimeError: Command docker exec -t 4d371a8cab201bbe9ed3f79eb93a5dd803b2ccea703bff6db9c9d83cb14af2b8 /exec failed with exit code 127

CANCELLED JOB - The following job was cancelled. Please retry:

• trunk / test-models-macos-coreml (efficient_sam) / macos-job (gh)
  ##[error]The operation was canceled.

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[github-actions]

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[winskuo-quic]

Hi @cccclai,
This is the PR to enable LLM Decoder CI, please notice that we are using x86 emulator for QNN execution. Therefore, I am guessing it will take at least 8-10 hours to finish, so I think it will be better to place it under nightly.
This PR is still WIP and I will let you know when it is ready.
Thanks

[winskuo-quic]

Hi @cccclai,
This PR is to support community CI to eval PPL scores for static HF decoder models.
I have chosen the smallest HF decoder model for ppl evaluation.
The total time to taken to finish execution is about 5.5 hours.
I would like to confirm on the following:

1. Is this taking too long and we should move it to nightly.yml.
2. Is using linux.24xlarge to run CI a concern?

[cccclai]

Hi @cccclai, This is the PR to enable LLM Decoder CI, please notice that we are using x86 emulator for QNN execution. Therefore, I am guessing it will take at least 8-10 hours to finish, so I think it will be better to place it under nightly. This PR is still WIP and I will let you know when it is ready. Thanks

Thanks for adding CI, this is definately helpful and can help prevent regression early. Yeah nightly will be better, 8-10 hours are quite long. Will need to read which task you're trying.