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mindspore
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4fae2de9
编写于
8月 26, 2020
作者:
J
jonyguo
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电子邮件补丁
差异文件
fix: update api comment for optional
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dc062649
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mindspore/dataset/transforms/vision/c_transforms.py
mindspore/dataset/transforms/vision/c_transforms.py
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mindspore/dataset/transforms/vision/c_transforms.py
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4fae2de9
...
@@ -153,8 +153,8 @@ class CutMixBatch(cde.CutMixBatchOp):
...
@@ -153,8 +153,8 @@ class CutMixBatch(cde.CutMixBatchOp):
Args:
Args:
image_batch_format (Image Batch Format): The method of padding. Can be any of
image_batch_format (Image Batch Format): The method of padding. Can be any of
[ImageBatchFormat.NHWC, ImageBatchFormat.NCHW]
[ImageBatchFormat.NHWC, ImageBatchFormat.NCHW]
alpha (float): hyperparameter of beta distribution (default = 1.0).
alpha (float
, optional
): hyperparameter of beta distribution (default = 1.0).
prob (float): The probability by which CutMix is applied to each image (default = 1.0).
prob (float
, optional
): The probability by which CutMix is applied to each image (default = 1.0).
Examples:
Examples:
>>> one_hot_op = data.OneHot(num_classes=10)
>>> one_hot_op = data.OneHot(num_classes=10)
...
@@ -197,7 +197,7 @@ class MixUpBatch(cde.MixUpBatchOp):
...
@@ -197,7 +197,7 @@ class MixUpBatch(cde.MixUpBatchOp):
Note that you need to make labels into one-hot format and batch before calling this function.
Note that you need to make labels into one-hot format and batch before calling this function.
Args:
Args:
alpha (float): hyperparameter of beta distribution (default = 1.0).
alpha (float
, optional
): hyperparameter of beta distribution (default = 1.0).
Examples:
Examples:
>>> one_hot_op = data.OneHot(num_classes=10)
>>> one_hot_op = data.OneHot(num_classes=10)
...
@@ -463,7 +463,7 @@ class RandomPosterize(cde.RandomPosterizeOp):
...
@@ -463,7 +463,7 @@ class RandomPosterize(cde.RandomPosterizeOp):
Reduce the number of bits for each color channel.
Reduce the number of bits for each color channel.
Args:
Args:
bits (sequence or int): Range of random posterize to compress image.
bits (sequence or int
, optional
): Range of random posterize to compress image.
bits values should always be in range of [1,8], and include at
bits values should always be in range of [1,8], and include at
least one integer values in the given range. It should be in
least one integer values in the given range. It should be in
(min, max) or integer format. If min=max, then it is a single fixed
(min, max) or integer format. If min=max, then it is a single fixed
...
@@ -684,7 +684,7 @@ class RandomColor(cde.RandomColorOp):
...
@@ -684,7 +684,7 @@ class RandomColor(cde.RandomColorOp):
This operation works only with 3-channel color images.
This operation works only with 3-channel color images.
Args:
Args:
degrees (sequence): Range of random color adjustment degrees.
degrees (sequence
, optional
): Range of random color adjustment degrees.
It should be in (min, max) format. If min=max, then it is a
It should be in (min, max) format. If min=max, then it is a
single fixed magnitude operation (default=(0.1,1.9)).
single fixed magnitude operation (default=(0.1,1.9)).
"""
"""
...
@@ -897,7 +897,7 @@ class Pad(cde.PadOp):
...
@@ -897,7 +897,7 @@ class Pad(cde.PadOp):
fill_value (Union[int, tuple], optional): The pixel intensity of the borders if
fill_value (Union[int, tuple], optional): The pixel intensity of the borders if
the padding_mode is Border.CONSTANT (default=0). If it is a 3-tuple, it is used to
the padding_mode is Border.CONSTANT (default=0). If it is a 3-tuple, it is used to
fill R, G, B channels respectively.
fill R, G, B channels respectively.
padding_mode (Border mode): The method of padding (default=Border.CONSTANT). Can be any of
padding_mode (Border mode
, optional
): The method of padding (default=Border.CONSTANT). Can be any of
[Border.CONSTANT, Border.EDGE, Border.REFLECT, Border.SYMMETRIC].
[Border.CONSTANT, Border.EDGE, Border.REFLECT, Border.SYMMETRIC].
- Border.CONSTANT, means it fills the border with constant values.
- Border.CONSTANT, means it fills the border with constant values.
...
...
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