mindspore.ops.GridSampler3D
- class mindspore.ops.GridSampler3D(interpolation_mode='bilinear', padding_mode='zeros', align_corners=False)[source]
Given an input and a grid, the output is calculated using the input values and pixel positions in the grid. Only volume (5-D) input is supported.
Warning
This is an experimental API that is subject to change or deletion.
Refer to
mindspore.ops.grid_sample()
for more details.- Parameters
interpolation_mode (str, optional) –
An optional string specifying the interpolation method. The optional values are
"bilinear"
or"nearest"
. Default:"bilinear"
."nearest"
: Nearest neighbor interpolation. Each output pixel is assigned the value of the nearest input pixel. This method is simple and fast but can result in blocky or pixelated outputs."bilinear"
: Bilinear interpolation. Each output pixel is a weighted average of the four nearest input pixels, computed using bilinear interpolation. This method produces smoother results compared to nearest neighbor interpolation.
padding_mode (str, optional) –
An optional string specifying the pad method. The optional values are
"zeros"
,"border"
or"reflection"
. Default:"zeros"
. When the sampling grid is outside input’s bounds, effects of various padding modes are as follows:"zeros"
: Pads the input tensor with zeros."border"
: Pads the input tensor with the values of the pixels on the border of the tensor."reflection"
: Pads the input tensor by reflecting the values of the pixels at the boundary of the tensor.
align_corners (bool, optional) – An optional bool specifying alignment method. If set to
True
, the extrema (-1 and 1) are considered as referring to the center points of the input’s corner pixels. If set toFalse
, they are instead considered as referring to the corner points of the input’s corner pixels, making the sampling more resolution agnostic. Default:False
.
- Inputs:
input_x (Tensor) - A 5-D tensor with dtype of float16, float32 or float64 and shape of \((N, C, D_{in}, H_{in}, W_{in})\).
grid (Tensor) - A 5-D tensor whose dtype is the same as input_x and whose shape is \((N, D_{out}, H_{out}, W_{out}, 3)\).
- Outputs:
A 5-D Tensor whose dtype is the same as input_x and whose shape is \((N, C, D_{out}, H_{out}, W_{out})\).
- Supported Platforms:
Ascend
GPU
CPU
Examples
>>> import numpy as np >>> from mindspore import Tensor, ops >>> gridsampler = ops.GridSampler3D(interpolation_mode='bilinear', padding_mode='zeros', align_corners=True) >>> input_x = Tensor(np.arange(32).reshape((2, 2, 2, 2, 2)).astype(np.float32)) >>> grid = Tensor(np.arange(-0.2, 1, 0.1).reshape((2, 2, 1, 1, 3)).astype(np.float32)) >>> output = gridsampler(input_x, grid) >>> print(output) [[[[[ 3.3 ]] [[ 4.35 ]]] [[[11.300001]] [[12.349999]]]] [[[[21.4 ]] [[22.449999]]] [[[29.4 ]] [[30.449999]]]]]