| ## UTILS | |
| import torch | |
| from torch import nn | |
| import torch.nn.functional as F | |
| class PixelDownsampleEncoder(nn.Module): | |
| def __init__( | |
| self, | |
| ): | |
| super().__init__() | |
| def encode(self, x: torch.Tensor) -> torch.Tensor: | |
| # normalize input | |
| # x : b c h w | |
| x = F.interpolate(x, size=(64, 64), mode='area') | |
| B, C, H, W = x.shape | |
| p = 4 # patch size | |
| z = x.view(B, C, H // p, p, W // p, p).permute(0, 1, 3, 5, 2, 4).reshape(B, 48, 16, 16) | |
| return z | |