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[CI] Fix test. #2031

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Merged
Gaohan123 merged 4 commits into from
Mar 20, 2026
Merged

[CI] Fix test. #2031

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26af0a5
Fix.
congw729 Mar 20, 2026
2e79884
Fix
congw729 Mar 20, 2026
ccf45e6
Remove duplicates
congw729 Mar 20, 2026
4cff7d0
Update label name
congw729 Mar 20, 2026
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17 changes: 0 additions & 17 deletions .buildkite/test-merge.yml
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Original file line number Diff line number Diff line change
Expand Up @@ -379,20 +379,3 @@ steps:
# hostPath:
# path: /mnt/hf-cache
# type: DirectoryOrCreate

- label: "CUDA Unit Test"
timeout_in_minutes: 10
depends_on: upload-merge-pipeline
commands:
- pytest -v -s -m 'core_model and cuda'
agents:
queue: "gpu_1_queue"
plugins:
- docker#v5.2.0:
image: public.ecr.aws/q9t5s3a7/vllm-ci-test-repo:$BUILDKITE_COMMIT
always-pull: true
propagate-environment: true
environment:
- "HF_HOME=/fsx/hf_cache"
volumes:
- "/fsx/hf_cache:/fsx/hf_cache"
17 changes: 17 additions & 0 deletions .buildkite/test-ready.yml
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Expand Up @@ -16,6 +16,23 @@ steps:
volumes:
- "/fsx/hf_cache:/fsx/hf_cache"

- label: "Voxtral TTS CUDA Unit Test"
timeout_in_minutes: 10
depends_on: upload-ready-pipeline
commands:
- "timeout 10m pytest -s -v tests/model_executor/models/voxtral_tts/test_cuda_graph_acoustic_transformer.py"
agents:
queue: "gpu_1_queue"
plugins:
- docker#v5.2.0:
image: public.ecr.aws/q9t5s3a7/vllm-ci-test-repo:$BUILDKITE_COMMIT
always-pull: true
propagate-environment: true
environment:
- "HF_HOME=/fsx/hf_cache"
volumes:
- "/fsx/hf_cache:/fsx/hf_cache"

- label: "Diffusion Model Test"
depends_on: upload-ready-pipeline
commands:
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1 change: 1 addition & 0 deletions tests/model_executor/models/voxtral_tts/test_cuda_graph_acoustic_transformer.py
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Expand Up @@ -23,6 +23,7 @@
pytest.mark.skipif(not torch.cuda.is_available(), reason="CUDA required"),
pytest.mark.core_model,
pytest.mark.cuda,
pytest.mark.L4,
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@yenuo26 yenuo26 Mar 20, 2026

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Why don't you use hardware_test？

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@congw729 congw729 Mar 20, 2026

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We cannot use a custom decorator @hardware_test in the same way as pytestmark with @pytest.mark.xx. This test does not need multiple cards, so I think to stay the current style.

]

DEVICE = torch.device("cuda:0")
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