torch.nn.functional.affine_grid
torch.nn.functional.affine_grid(theta, size, align_corners=None)
Generates a 2D or 3D flow field (sampling grid), given a batch of
   affine matrices "theta".
Note:
 This function is often used in conjunction with "grid_sample()"
 to build Spatial Transformer Networks .

Parameters:
      * 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 "grid_sample()"
    for a more complete description. A grid generated by
