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chore: minor linting
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  • py/torch_tensorrt/dynamo/conversion/impl/normalization

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py/torch_tensorrt/dynamo/conversion/impl/normalization/ops.py

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@@ -551,8 +551,9 @@ def cdist_forward(
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- For x1.shape = [10, 5] (10 vectors, each of 5 features) and x2.shape = [20, 5] (20 vectors, each of 5 features),
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since there are no batch dimensions to match, the output shape is simply [10, 20], comparing all vectors from x1 against all vectors from x2.
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Note: The `compute_mode` parameter is designed to optimize the performance of the Euclidean distance calculation, especially useful when working with large datasets.
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This parameter allows you to control how the distances are computed, with different modes available to leverage matrix multiplication for speed improvements.
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Note: The `compute_mode` parameter is designed to optimize the performance of the Euclidean distance calculation,
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especially useful when working with large datasets. This parameter allows you to control how the distances are computed,
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with different modes available to leverage matrix multiplication for speed improvements.
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"""
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if compute_mode is None:
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compute_mode = 0

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