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[ci] don't run sana layerwise casting tests in CI. - #12551
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dg845
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Oct 28, 2025
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Thanks, LGTM! I've observed that some other test_layerwise_casting_inference tests seem to fail in the CI as well. For example, on the CI job when PRX was merged, both Qwen Image (https://github.com/huggingface/diffusers/actions/runs/18701189489/job/53330184168):
FAILED tests/pipelines/qwenimage/test_qwenimage_edit.py::QwenImageEditPipelineFastTests::test_layerwise_casting_inference - torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 16.00 GiB. GPU 0 has a total capacity of 14.74 GiB of which 14.03 GiB is free. Process 19357 has 724.00 MiB memory in use. Of the allocated memory 465.60 MiB is allocated by PyTorch, and 132.40 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)
FAILED tests/pipelines/qwenimage/test_qwenimage_edit_plus.py::QwenImageEditPlusPipelineFastTests::test_layerwise_casting_inference - torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 16.00 GiB. GPU 0 has a total capacity of 14.74 GiB of which 14.05 GiB is free. Process 19357 has 708.00 MiB memory in use. Of the allocated memory 484.53 MiB is allocated by PyTorch, and 97.47 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)
and Sana (https://github.com/huggingface/diffusers/actions/runs/18701189489/job/53330184161):
FAILED tests/pipelines/sana/test_sana.py::SanaPipelineFastTests::test_layerwise_casting_inference - RuntimeError: GET was unable to find an engine to execute this computation
FAILED tests/pipelines/sana/test_sana_controlnet.py::SanaControlNetPipelineFastTests::test_layerwise_casting_inference - RuntimeError: GET was unable to find an engine to execute this computation
FAILED tests/pipelines/sana/test_sana_sprint.py::SanaSprintPipelineFastTests::test_layerwise_casting_inference - RuntimeError: GET was unable to find an engine to execute this computation
FAILED tests/pipelines/sana/test_sana_sprint_img2img.py::SanaSprintImg2ImgPipelineFastTests::test_layerwise_casting_inference - RuntimeError: GET was unable to find an engine to execute this computation
test_layerwise_casting_inference tests failed.
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What does this PR do?
Tests pass locally perfectly fine on different GPUs (RT 4090, A100, H100).
Example failures: