| def contextual_loss(x, y, h=0.5): | |
| """Computes contextual loss between x and y. | |
| Args: | |
| x: features of shape (N, C, H, W). | |
| y: features of shape (N, C, H, W). | |
| Returns: | |
| cx_loss = contextual loss between x and y (Eq (1) in the paper) | |
| """ |
| class DepthToSpace(nn.Module): | |
| def __init__(self, block_size): | |
| super(DepthToSpace, self).__init__() | |
| self.block_size = block_size | |
| self.block_size_sq = block_size*block_size | |
| def forward(self, input): | |
| output = input.permute(0, 2, 3, 1) | |
| (batch_size, d_height, d_width, d_depth) = output.size() | |
| s_depth = int(d_depth / self.block_size_sq) |
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