deep-vector-quantization
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VQVAEs, GumbelSoftmaxes and friends
Hey Andrej! Cool repo :+1: This is a small change that effectually computes `model(x - 0.5)` in `visualize.ipynb`. Otherwise `model(x) - 0.5` looks like this  After the change we...
#========== ` def forward(self, z): B, C, H, W = z.size() z_e = self.proj(z) z_e = z_e.permute(0, 2, 3, 1) # make (B, H, W, C) flatten = z_e.reshape(-1, self.embedding_dim)...
From my understanding, the input of `F.gumbel_softmax` (i.e., the` logits` parameter) should be the \log of a discrete distribution. However, I didn't see any softmax or log_softmax before the gumbel_softmax....
I believe that there is at least one 1x1 conv missing. In the paper on p. 3 they mention the crucial importance of those but I could only find a...