Update dcgan_64.py

dcgan_64.py

@@ -1,4 +1,5 @@
 import torch.nn as nn
+import torch.nn.functional as F
 
 
 class dcgan_conv(nn.Module):
@@ -95,10 +96,6 @@ class decoder_woSkip(nn.Module):
         return output
 
 
-"""
-# Using Convolution and up_resize as the block to up-sample
-"""
-import torch.nn.functional as F
 class upconv(nn.Module):
     def __init__(self, nc_in, nc_out):
         super().__init__()
@@ -119,15 +116,10 @@ class decoder_conv(nn.Module):
             nn.ConvTranspose2d(dim, nf * 8, 4, 1, 0),
             nn.BatchNorm2d(nf * 8),
             nn.ReLU(),
-            # state size. (nf*8) x 4 x 4
             upconv(nf * 8, nf * 4),
-            # state size. (nf*4) x 8 x 8
             upconv(nf * 4, nf * 2),
-            # state size. (nf*2) x 16 x 16
             upconv(nf * 2, nf * 2),
-            # state size. (nf*2) x 32 x 32
             upconv(nf * 2, nf),
-            # state size. (nf) x 64 x 64
             nn.Conv2d(nf, nc, 1, 1, 0),
             nn.Sigmoid()
         )
@@ -136,5 +128,4 @@ class decoder_conv(nn.Module):
     def forward(self, input):
         output = self.main(input.view(-1, self.dim, 1, 1))
         output = output.view(input.shape[0], input.shape[1], output.shape[1], output.shape[2], output.shape[3])
-
         return output