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Signed-off-by: Sun, Xuehao <xuehao.sun@intel.com>
…ments.txt Signed-off-by: Sun, Xuehao <xuehao.sun@intel.com>
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Pull request overview
This PR aims to fix failing CUDA and HPU unit test runs by adjusting test dependency requirements and updating the CUDA UT pipeline script’s installation steps.
Changes:
- Unpinned
compressed_tensorsin HPU test requirements. - Removed an invalid
extra-index-urlline from CUDA test requirements. - Reordered/relocated dependency and package installation in the CUDA UT pipeline script and made report artifact moves conditional on file existence.
Reviewed changes
Copilot reviewed 3 out of 3 changed files in this pull request and generated 2 comments.
| File | Description |
|---|---|
test/test_hpu/requirements.txt |
Removes the temporary <0.14 restriction for compressed_tensors. |
test/test_cuda/requirements.txt |
Removes an invalid requirements entry that can break pip -r parsing. |
.azure-pipelines/scripts/ut/run_ut_cuda.sh |
Moves torch + repo installation into per-test functions and guards artifact moves. |
| cd ${REPO_PATH}/test | ||
| rm -rf .coverage* *.xml *.html | ||
| uv pip install torch==2.9.1 torchvision | ||
| uv pip install -r test_cuda/requirements_sglang.txt |
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run_unit_test_sglang no longer installs/pins PyTorch (the previous torch==... line was removed), but the SGLang tests import torch and the repo install also depends on torch. Add an explicit uv pip install torch==... torchvision (matching the version used in the other CUDA UT functions) before uv pip install . so this job doesn’t end up with an unintended torch version or fail to import torch.
Suggested change
| uv pip install -r test_cuda/requirements_sglang.txt | |
| uv pip install -r test_cuda/requirements_sglang.txt | |
| uv pip install torch==2.1.2 torchvision |
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