minor code cleanup

Author: Unni

src/encoder_decoder_1.py

@@ -35,40 +35,3 @@ def forward(self, x):
         out = self.conv3(out)
         return out
 
-
-class encoder2(nn.Module):
-    def __init__(self, vgg):
-        super(encoder2, self).__init__()
-        self.conv1 = nn.Conv2d(3, 3, 1, 1, 0)
-        self.conv1.weight = torch.nn.Parameter(vgg.get(0).weight.float())
-        self.conv1.bias = torch.nn.Parameter(vgg.get(0).bias.float())
-        self.rp1 = nn.ReflectionPad2d((1, 1, 1, 1))
-        self.conv2 = nn.Conv2d(3, 64, 3, 1, 0)
-        self.conv2.weight = torch.nn.Parameter(vgg.get(2).weight.float())
-        self.conv2.bias = torch.nn.Parameter(vgg.get(2).bias.float())
-        self.relu2 = nn.ReLU(inplace=True)
-        self.rp3 = nn.ReflectionPad2d((1, 1, 1, 1))
-        self.conv3 = nn.Conv2d(64, 64, 3, 1, 0)
-        self.conv3.weight = torch.nn.Parameter(vgg.get(5).weight.float())
-        self.conv3.bias = torch.nn.Parameter(vgg.get(5).bias.float())
-        self.relu3 = nn.ReLU(inplace=True)
-        self.mp = nn.MaxPool2d(kernel_size=2, stride=2, return_indices=True)
-        self.rp4 = nn.ReflectionPad2d((1, 1, 1, 1))
-        self.conv4 = nn.Conv2d(64, 128, 3, 1, 0)
-        self.conv4.weight = torch.nn.Parameter(vgg.get(9).weight.float())
-        self.conv4.bias = torch.nn.Parameter(vgg.get(9).bias.float())
-        self.relu4 = nn.ReLU(inplace=True)
-
-    def forward(self, x):
-        out = self.conv1(x)
-        out = self.rp1(out)
-        out = self.conv2(out)
-        out = self.relu2(out)
-        out = self.rp3(out)
-        out = self.conv3(out)
-        pool = self.relu3(out)
-        out, pool_idx = self.mp(pool)
-        out = self.rp4(out)
-        out = self.conv4(out)
-        out = self.relu4(out)
-        return out