Interpolate a tensor dimension from x to nx

2

Thanks to this post (Repeat examples along batch dimension), I used torch.repeat_interleave to do it.

import torch
torch.manual_seed(0)

shape = x, y = 2, 3
"""
or : 
  - shape = x, y, z = _, _, _, ...
  - shape = x, y, z, t, ... = _, _, _, _, ...
  ...
"""
n = 3

t = torch.rand(shape)
"""
tensor([[0.4963, 0.7682, 0.0885],
        [0.1320, 0.3074, 0.6341]])
"""

t_interpolate = torch.repeat_interleave(t, repeats=n, dim=0)
"""
tensor([[0.4963, 0.7682, 0.0885],
        [0.4963, 0.7682, 0.0885],
        [0.4963, 0.7682, 0.0885],
        [0.1320, 0.3074, 0.6341],
        [0.1320, 0.3074, 0.6341],
        [0.1320, 0.3074, 0.6341]])
"""

assert t_interpolate.size() == torch.Size([n * shape[0], *shape[1:]])
1 Like