A high-throughput and memory-efficient inference and serving engine for LLMs
Mirrored from https://github.com/tduncan-lum/Nvidia-Optimization-Stack---VLLM.git
Synced Nov 14, 05:30 UTC
Add more test scenario for tensor schema (#22733)
Signed-off-by: teekenl <teekenlau@gmail.com>
TeeKen Lau committed
Aug 13, 2025 at 02:34 UTC
c42fe0b63a29d3ec157089c9784643000dde4aec
1 file changed
+25
tests/utils_/test_tensor_schema.py
+25
@@ -33,6 +33,31 @@ def test_tensor_schema_constant_dim_failure():
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)
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+def test_tensor_schema_invalid_types_in_list():
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+ with pytest.raises(ValueError, match="is not a torch.Tensor"):
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+ Phi3VImagePixelInputs(
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+ data=[
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+ torch.randn(64, 3, 32, 32),
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+ "not_a_tensor",
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+ torch.randn(64, 3, 32, 32),
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+ ],
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+ image_sizes=torch.randint(0, 256, (3, 2)),
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+ )
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+
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+
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+def test_tensor_schema_rank_mismatch():
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+ with pytest.raises(ValueError, match="has rank 3 but expected 5"):
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+ Phi3VImagePixelInputs(
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+ data=torch.randn(16, 64, 3),
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+ image_sizes=torch.randint(0, 256, (16, 2)),
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+ )
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+
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+
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+def test_tensor_schema_missing_required_field():
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+ with pytest.raises(ValueError, match="Required field 'data' is missing"):
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+ Phi3VImagePixelInputs(image_sizes=torch.randint(0, 256, (16, 2)), )
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+
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+
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def test_tensor_schema_symbolic_dim_mismatch():
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with pytest.raises(ValueError, match="expected 'bn'=12, got 16"):
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Phi3VImagePixelInputs(