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In the WGAN_GP paper ArXiv, alpha is sampled for each example. However, it's sampled element-wise referred to WGAN_GP.
Suppose we have a tensor of the size (64, 3, 15, 15), I thought the correct way to sample is alpha = torch.rand(x_.size()[0]), which returns a (64, ) tensor.
Is there something I miss or I misunderstand the paper?
The text was updated successfully, but these errors were encountered:
In the WGAN_GP paper ArXiv, alpha is sampled for each example. However, it's sampled element-wise referred to WGAN_GP.
Suppose we have a tensor of the size
(64, 3, 15, 15)
, I thought the correct way to sample isalpha = torch.rand(x_.size()[0])
, which returns a(64, )
tensor.Is there something I miss or I misunderstand the paper?
The text was updated successfully, but these errors were encountered: