Generates a 2D or 3D flow field (sampling grid), given a batch of
affine matrices `theta`

.

## Arguments

- theta
(Tensor) input batch of affine matrices with shape (\(N \times 2 \times 3\)) for 2D or (\(N \times 3 \times 4\)) for 3D

- size
(torch.Size) the target output image size. (\(N \times C \times H \times W\) for 2D or \(N \times C \times D \times H \times W\) for 3D) Example: torch.Size((32, 3, 24, 24))

- align_corners
(bool, optional) if

`True`

, consider`-1`

and`1`

to refer to the centers of the corner pixels rather than the image corners. Refer to`nnf_grid_sample()`

for a more complete description. A grid generated by`nnf_affine_grid()`

should be passed to`nnf_grid_sample()`

with the same setting for this option. Default:`False`

## Note

This function is often used in conjunction with `nnf_grid_sample()`

to build `Spatial Transformer Networks`

_ .