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Fix docstring get maskformer resize output image size (#27196)

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* fix docstring in get_maskformer_resize_output_image_size

* fix  functions docstring

* fix 'copied from' functions docstring

* fix docstring

* fix return type

* fix docstring resize
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Wesley L Passos 2023-11-01 09:26:14 -03:00 committed by GitHub
parent ae093eef01
commit 71025520bc
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2 changed files with 22 additions and 18 deletions
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20
src/transformers/models/mask2former/image_processing_mask2former.py
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@ -304,21 +304,23 @@ def get_mask2former_resize_output_image_size(
size_divisor: int = 0,
default_to_square: bool = True,
input_data_format: Optional[Union[str, ChannelDimension]] = None,
) -> tuple:
) -> Tuple[int, int]:
"""
Computes the output size given the desired size.
Args:
input_image (`np.ndarray`):
image (`np.ndarray`):
The input image.
size (`int`, `Tuple[int, int]`, `List[int]`, `Tuple[int]`):
size (`int` or `Tuple[int, int]` or `List[int]` or `Tuple[int]`):
The size of the output image.
default_to_square (`bool`, *optional*, defaults to `True`):
Whether to default to square if no size is provided.
max_size (`int`, *optional*):
The maximum size of the output image.
size_divisible (`int`, *optional*, defaults to 0):
If size_divisible is given, the output image size will be divisible by the number.
size_divisor (`int`, *optional*, defaults to 0):
If `size_divisor` is given, the output image size will be divisible by the number.
default_to_square (`bool`, *optional*, defaults to `True`):
Whether to default to square if no size is provided.
input_data_format (`ChannelDimension` or `str`, *optional*):
The channel dimension format of the input image. If unset, will use the inferred format from the input.
Returns:
`Tuple[int, int]`: The output size.
@ -471,10 +473,10 @@ class Mask2FormerImageProcessor(BaseImageProcessor):
size (`Dict[str, int]`):
The size of the output image.
size_divisor (`int`, *optional*, defaults to 0):
If size_divisor is given, the output image size will be divisible by the number.
If `size_divisor` is given, the output image size will be divisible by the number.
resample (`PILImageResampling` resampling filter, *optional*, defaults to `PILImageResampling.BILINEAR`):
Resampling filter to use when resizing the image.
data_format (`str` or `ChannelDimension`, *optional*):
data_format (`ChannelDimension` or `str`, *optional*):
The channel dimension format for the output image. If unset, the channel dimension format of the input
image is used.
input_data_format (`ChannelDimension` or `str`, *optional*):

20
src/transformers/models/maskformer/image_processing_maskformer.py
View File

@ -306,21 +306,23 @@ def get_maskformer_resize_output_image_size(
size_divisor: int = 0,
default_to_square: bool = True,
input_data_format: Optional[Union[str, ChannelDimension]] = None,
) -> tuple:
) -> Tuple[int, int]:
"""
Computes the output size given the desired size.
Args:
input_image (`np.ndarray`):
image (`np.ndarray`):
The input image.
size (`int`, `Tuple[int, int]`, `List[int]`, `Tuple[int]`):
size (`int` or `Tuple[int, int]` or `List[int]` or `Tuple[int]`):
The size of the output image.
default_to_square (`bool`, *optional*, defaults to `True`):
Whether to default to square if no size is provided.
max_size (`int`, *optional*):
The maximum size of the output image.
size_divisible (`int`, *optional*, defaults to 0):
If size_divisible is given, the output image size will be divisible by the number.
size_divisor (`int`, *optional*, defaults to 0):
If `size_divisor` is given, the output image size will be divisible by the number.
default_to_square (`bool`, *optional*, defaults to `True`):
Whether to default to square if no size is provided.
input_data_format (`ChannelDimension` or `str`, *optional*):
The channel dimension format of the input image. If unset, will use the inferred format from the input.
Returns:
`Tuple[int, int]`: The output size.
@ -479,10 +481,10 @@ class MaskFormerImageProcessor(BaseImageProcessor):
size (`Dict[str, int]`):
The size of the output image.
size_divisor (`int`, *optional*, defaults to 0):
If size_divisor is given, the output image size will be divisible by the number.
If `size_divisor` is given, the output image size will be divisible by the number.
resample (`PILImageResampling` resampling filter, *optional*, defaults to `PILImageResampling.BILINEAR`):
Resampling filter to use when resizing the image.
data_format (`str` or `ChannelDimension`, *optional*):
data_format (`ChannelDimension` or `str`, *optional*):
The channel dimension format for the output image. If unset, the channel dimension format of the input
image is used.
input_data_format (`ChannelDimension` or `str`, *optional*):