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Remove redundant condition checks in get_image_size method #45461

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Merged
Rocketknight1 merged 2 commits into from
Apr 17, 2026
+0 −16
Merged

Remove redundant condition checks in get_image_size method #45461

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19975d3
remove redundant condition checks in get_image_size method
JiauZhang Apr 15, 2026
482c117
update modular file
JiauZhang Apr 17, 2026
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8 changes: 0 additions & 8 deletions src/transformers/models/pp_ocrv5_server_det/image_processing_pp_ocrv5_server_det.py
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Original file line number Diff line number Diff line change
Expand Up @@ -358,14 +358,6 @@ def get_image_size(
resize_height = max(int(round(resize_height / 32) * 32), 32)
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@afurm afurm Apr 15, 2026

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The removed early-return optimization (if resize_height == height and resize_width == width) avoided tensor allocation when no resize was needed. Its removal means every call now allocates a torch.tensor even when input dimensions are already valid — this could add measurable overhead in high-throughput inference pipelines. Consider restoring the check or benchmarking the impact.

resize_width = max(int(round(resize_width / 32) * 32), 32)

if resize_height == height and resize_width == width:
return SizeDict(height=resize_height, width=resize_width), torch.tensor(
[height, width], dtype=torch.float32, device=image.device
)

if resize_width <= 0 or resize_height <= 0:
return None, (None, None)

return SizeDict(height=resize_height, width=resize_width), torch.tensor(
[height, width], dtype=torch.float32, device=image.device
)
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8 changes: 0 additions & 8 deletions src/transformers/models/pp_ocrv5_server_det/modular_pp_ocrv5_server_det.py
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Original file line number Diff line number Diff line change
Expand Up @@ -429,14 +429,6 @@ def get_image_size(
resize_height = max(int(round(resize_height / 32) * 32), 32)
resize_width = max(int(round(resize_width / 32) * 32), 32)

if resize_height == height and resize_width == width:
return SizeDict(height=resize_height, width=resize_width), torch.tensor(
[height, width], dtype=torch.float32, device=image.device
)

if resize_width <= 0 or resize_height <= 0:
return None, (None, None)

return SizeDict(height=resize_height, width=resize_width), torch.tensor(
[height, width], dtype=torch.float32, device=image.device
)
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