forked from huawei/mindspore2022
!6783 Fix some bug in API.
Merge pull request !6783 from liuxiao93/r1.0-fix-PSRN-api
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commit
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@ -349,7 +349,7 @@ class PSNR(Cell):
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Args:
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max_val (Union[int, float]): The dynamic range of the pixel values (255 for 8-bit grayscale images).
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Default: 1.0.
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The value must be greater than 0. Default: 1.0.
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Inputs:
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- **img1** (Tensor) - The first image batch with format 'NCHW'. It must be the same shape and dtype as img2.
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@ -247,12 +247,11 @@ def multinomial(inputs, num_sample, replacement=True, seed=0):
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Args:
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inputs (Tensor): The input tensor containing probabilities, must be 1 or 2 dimensions, with
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float32 data type.
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float32 data type.
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num_sample (int): Number of samples to draw.
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replacement (bool, optional): Whether to draw with replacement or not, default True.
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seed (int, optional): Seed is used as entropy source for the random number engines to generate
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pseudo-random numbers,
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must be non-negative. Default: 0.
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pseudo-random numbers, must be non-negative. Default: 0.
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Outputs:
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Tensor, has the same rows with input. The number of sampled indices of each row is `num_samples`.
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@ -2488,7 +2488,7 @@ class ResizeBilinear(PrimitiveWithInfer):
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Inputs:
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- **input** (Tensor) - Image to be resized. Input images must be a 4-D tensor with shape
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[batch, channels, height, width], with data type of float32 or float16.
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:math:`(batch, channels, height, width)`, with data type of float32 or float16.
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Outputs:
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Tensor, resized image. 4-D with shape [batch, channels, new_height, new_width] in `float32`.
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