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[fix]fix unit_tests func name #956

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Merged
SangChengC merged 1 commit into from
Jul 4, 2025
Merged

[fix]fix unit_tests func name #956

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2 changes: 1 addition & 1 deletion unit_tests/common/basemodel/triton_kernel/test_multimodal_emb.py
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Original file line number Diff line number Diff line change
Expand Up @@ -6,7 +6,7 @@
logger = init_logger(__name__)


def test_mark_mubltimodal_obj():
def test_mark_multimodal_obj():
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@gemini-code-assist gemini-code-assist bot Jul 4, 2025

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medium

This test allocates tensors on cuda, indicating a dependency on a CUDA-enabled GPU. While this is expected for a test targeting a Triton kernel, it's a best practice to explicitly mark such tests. This allows test runners like pytest to automatically skip them on environments without a GPU, preventing the entire test suite from failing.

Consider adding a pytest.mark.skipif decorator to make the test suite more robust across different environments.

Example:

import pytest
import torch

@pytest.mark.skipif(not torch.cuda.is_available(), reason="This test requires a CUDA-enabled GPU")
def test_mark_multimodal_obj():
    # ... test implementation

Applying this pattern to all GPU-dependent tests would be a valuable improvement for the project's CI/CD pipeline and for developers working on non-GPU machines.

obj_start_ids = torch.tensor([1, 4, 100], device="cuda", dtype=torch.int64)
obj_token_lens = torch.tensor([1, 3, 2], device="cuda", dtype=torch.int64)
input_ids = torch.tensor([1, 7, 9, 333], device="cuda", dtype=torch.int64)
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