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doc comment fix: Args was in wrong place (#20164)

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Matthijs Hollemans 2022-11-10 16:02:24 +01:00 committed by GitHub
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2 changed files with 6 additions and 2 deletions
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4
src/transformers/models/dpt/image_processing_dpt.py
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@ -345,13 +345,15 @@ class DPTImageProcessor(BaseImageProcessor):
def post_process_semantic_segmentation(self, outputs, target_sizes: List[Tuple] = None): def post_process_semantic_segmentation(self, outputs, target_sizes: List[Tuple] = None):
""" """
Args:
Converts the output of [`DPTForSemanticSegmentation`] into semantic segmentation maps. Only supports PyTorch. Converts the output of [`DPTForSemanticSegmentation`] into semantic segmentation maps. Only supports PyTorch.
Args:
outputs ([`DPTForSemanticSegmentation`]): outputs ([`DPTForSemanticSegmentation`]):
Raw outputs of the model. Raw outputs of the model.
target_sizes (`List[Tuple]` of length `batch_size`, *optional*): target_sizes (`List[Tuple]` of length `batch_size`, *optional*):
List of tuples corresponding to the requested final size (height, width) of each prediction. If unset, List of tuples corresponding to the requested final size (height, width) of each prediction. If unset,
predictions will not be resized. predictions will not be resized.
Returns: Returns:
semantic_segmentation: `List[torch.Tensor]` of length `batch_size`, where each item is a semantic semantic_segmentation: `List[torch.Tensor]` of length `batch_size`, where each item is a semantic
segmentation map of shape (height, width) corresponding to the target_sizes entry (if `target_sizes` is segmentation map of shape (height, width) corresponding to the target_sizes entry (if `target_sizes` is

4
src/transformers/models/mobilevit/image_processing_mobilevit.py
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@ -323,14 +323,16 @@ class MobileViTImageProcessor(BaseImageProcessor):
def post_process_semantic_segmentation(self, outputs, target_sizes: List[Tuple] = None): def post_process_semantic_segmentation(self, outputs, target_sizes: List[Tuple] = None):
""" """
Args:
Converts the output of [`MobileViTForSemanticSegmentation`] into semantic segmentation maps. Only supports Converts the output of [`MobileViTForSemanticSegmentation`] into semantic segmentation maps. Only supports
PyTorch. PyTorch.
Args:
outputs ([`MobileViTForSemanticSegmentation`]): outputs ([`MobileViTForSemanticSegmentation`]):
Raw outputs of the model. Raw outputs of the model.
target_sizes (`List[Tuple]`, *optional*): target_sizes (`List[Tuple]`, *optional*):
A list of length `batch_size`, where each item is a `Tuple[int, int]` corresponding to the requested A list of length `batch_size`, where each item is a `Tuple[int, int]` corresponding to the requested
final size (height, width) of each prediction. If left to None, predictions will not be resized. final size (height, width) of each prediction. If left to None, predictions will not be resized.
Returns: Returns:
`List[torch.Tensor]`: `List[torch.Tensor]`:
A list of length `batch_size`, where each item is a semantic segmentation map of shape (height, width) A list of length `batch_size`, where each item is a semantic segmentation map of shape (height, width)