mindspore.ops.ResizeNearestNeighbor

class mindspore.ops.ResizeNearestNeighbor(size, align_corners=False, half_pixel_centers=False)[source]

Resizes the input tensor to a given size by using the nearest neighbor algorithm. The nearest neighbor algorithm selects the value of the nearest point and does not consider the values of neighboring points at all, yielding a piecewise-constant interpolant.

Parameters

  • size (Union[tuple, list]) – The target size. The dimension of size must be 2.

  • align_corners (bool) – Whether the centers of the 4 corner pixels of the input and output tensors are aligned. Default: False .

  • half_pixel_centers (bool, optional) – Whether half pixel center. If set to True , align_corners should be False. Default: False .

Inputs:

  • input_x (Tensor) - The input tensor. The shape of the tensor is \((N, C, H, W)\).

Outputs:

Tensor, the shape of the output tensor is \((N, C, NEW\_H, NEW\_W)\). The data type is the same as the input_x.

Raises

  • TypeError – If size is neither tuple nor list.

  • TypeError – If align_corners is not a bool.

  • ValueError – If length of size is not equal to 2.

Supported Platforms:

Ascend GPU CPU

Examples

>>> import numpy as np
>>> import mindspore
>>> from mindspore import Tensor, ops
>>> input_tensor = Tensor(np.array([[[[-0.1, 0.3, 3.6], [0.4, 0.5, -3.2]]]]), mindspore.float32)
>>> size = (2, 2)
>>> output = ops.ResizeNearestNeighbor(size=size)(input_tensor)
>>> print(output)
[[[[-0.1  0.3]
   [ 0.4  0.5]]]]