Update vq_vae.py

vq_vae.py

@@ -1,7 +1,7 @@
 import matplotlib.pyplot as plt
 import numpy as np
 import os, cv2
-import imageio, glob
+import glob
 import torch
 import torch.nn as nn
 import torch.nn.functional as F
@@ -365,30 +365,6 @@ class Pix2PixGenerator(nn.Module):
             nn.Tanh(),
         )
 
-        # self.down1 = UNetDown(in_channels, 16, normalize=False)
-        # self.down2 = UNetDown(16, 32)
-        # self.down3 = UNetDown(32, 64)
-        # self.down4 = UNetDown(64, 128, dropout=0.5)
-        # self.down5 = UNetDown(128, 256, dropout=0.5)
-        # self.down6 = UNetDown(256, 512, dropout=0.5)
-        # self.down7 = UNetDown(512, 512, dropout=0.5)
-        # self.down8 = UNetDown(512, 512, normalize=False, dropout=0.5)
-        #
-        # self.up1 = UNetUp(512, 512, dropout=0.5)
-        # self.up2 = UNetUp(1024, 512, dropout=0.5)
-        # self.up3 = UNetUp(1024, 256, dropout=0.5)
-        # self.up4 = UNetUp(512, 128, dropout=0.5)
-        # self.up5 = UNetUp(256, 64)
-        # self.up6 = UNetUp(128, 32)
-        # self.up7 = UNetUp(64, 16)
-        #
-        # self.final = nn.Sequential(
-        #     nn.Upsample(scale_factor=2),
-        #     nn.ZeroPad2d((1, 0, 1, 0)),
-        #     nn.Conv2d(32, out_channels, 4, padding=1),
-        #     nn.Tanh(),
-        # )
-
 
     def forward(self, x):
         # U-Net generator with skip connections from encoder to decoder