tensorplay.nn.functional.grid_sample

tensorplay.nn.functional.grid_sample(input: TensorBase, grid: TensorBase, mode: str = 'bilinear', padding_mode: str = 'zeros', align_corners=None) → TensorBase[source]

Compute grid sample.

Given an input and a flow-field grid, computes the output using input values and pixel locations from grid. Currently, only spatial (4-D) and volumetric (5-D) input are supported.

Parameters:

• input (Tensor) – input of shape $(N, C, H_\text{in}, W_\text{in})$ (4-D case) or $(N, C, D_\text{in}, H_\text{in}, W_\text{in})$ (5-D case)

• grid (Tensor) – flow-field of shape $(N, H_\text{out}, W_\text{out}, 2)$ (4-D case) or $(N, D_\text{out}, H_\text{out}, W_\text{out}, 3)$ (5-D case)

• mode (str) – 'bilinear' | 'nearest' | 'bicubic'. Default: 'bilinear'

• padding_mode (str) – 'zeros' | 'border' | 'reflection'. Default: 'zeros'

• align_corners (bool, optional) – extrema treatment, default False.

Dispatches to the native grid_sampler_2d / grid_sampler_3d kernels both input and grid.