Aug 21, 2020 · from pytorch_msssim import ssim, ms_ssim, SSIM, MS_SSIM # X: (N,3,H,W) a batch of non-negative RGB images (0~255) # Y: (N,3,H,W) # calculate ssim & ms-ssim for each image ssim_val = ssim (X, Y, data_range = 255, size_average = False) # return (N,) ms_ssim_val = ms_ssim (X, Y, data_range = 255, size_average = False) #(N,) # set 'size_average ...

Pick 4 results for today jamaicaLinear (hidden_dim, output_dim) def forward (self, x): # Initialize hidden state with zeros # (layer_dim, batch_size, hidden_dim) h0 = torch. zeros (self. layer_dim, x. size (0), self. hidden_dim). requires_grad_ # We need to detach the hidden state to prevent exploding/vanishing gradients # This is part of truncated backpropagation through ...

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