qsdy
/
mindspore2022
forked from huawei/mindspore2022
0
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

!24139 update docs about the operator 'ResizeBillinear' 

Merge pull request !24139 from dinglinhe/code_docs_dlh_r1.5_I4BQF1
This commit is contained in:
i-robot 2021-09-27 11:16:19 +00:00 committed by Gitee
parent dab18254ad 7cdd39439e
commit 90331788f3
1 changed files with 12 additions and 10 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

22
mindspore/nn/layer/basic.py
View File

@ -852,21 +852,23 @@ class ResizeBilinear(Cell):
Samples the input tensor to the given size or scale_factor by using bilinear interpolate.
Inputs:
- **x** (Tensor) - Tensor to be resized. Input tensor must be a 4-D tensor with shape:
math:`(batch, channels, height, width)`, with data type of float16 or float32.
- **size** (Union[tuple[int], list[int]]): A tuple or list of 2 int elements '(new_height, new_width)',
the new size of the tensor. One and only one of size and scale_factor can be set to None. Default: None.
- **x** (Tensor) - Tensor to be resized. Input tensor must be a 4-D tensor with shape
:math:`(batch, channels, height, width)`, with data type of float16 or float32.
- **size** (Union[tuple[int], list[int]]): A tuple or list of 2 int elements
:math:`(new_{height}, new_{width})`,the new size of the tensor.
One and only one of size and scale_factor can be set to None. Default: None.
- **scale_factor** (int): The scale factor of new size of the tensor. The value should be positive integer.
One and only one of size and scale_factor can be set to None. Default: None.
- **align_corners** (bool): If true, rescale input by '(new_height - 1) / (height - 1)', which exactly aligns
the 4 corners of images and resized images. If false, rescale by 'new_height / height'. Default: False.
- **align_corners** (bool): If true, rescale input by :math:`(new_{height} - 1) / (height - 1)`, which exactly
aligns the 4 corners of images and resized images. If false, rescale by :math:`new_{height} / height`.
Default: False.
Outputs:
Resized tensor.
If size is set, the result is 4-D tensor with shape:math:`(batch, channels, new_height, new_width)`
in float32.
If scale is set, the result is 4-D tensor with shape:math:`(batch, channels, scale_factor * height,
scale_factor * width)` in float32
If size is set, the result is 4-D tensor with shape :math:`(batch, channels, new_{height}, new_{width})`,
and the data type is the same as `x`.
If scale is set, the result is 4-D tensor with shape
:math:`(batch, channels, scale_{factor} * height, scale_{factor} * width)` and the data type is the same as `x`.
Raises:
TypeError: If `size` is not one of tuple, list, None.