Image-to-Image Translation Using Conditional DCGANs

support_blocks.py

class conv_block(nn.Module):
  def __init__(self,in_channels,out_channels,kernel_size=4,stride=2,padding=1):
    super(conv_block,self).__init__()
    self.conv_block=nn.Sequential(
        nn.Conv2d(in_channels,out_channels,kernel_size,stride,padding),
        nn.LeakyReLU(0.2),
        nn.BatchNorm2d(out_channels)
    )  
  def forward(self,x):
    return self.conv_block(x)

class transconv_block(nn.Module):
  def __init__(self,in_channels,out_channels,kernel_size=4,stride=2,padding=1):
    super(transconv_block,self).__init__()
    self.transconv_block=nn.Sequential(
        nn.ConvTranspose2d(in_channels,out_channels,kernel_size,stride,padding),
        nn.ReLU(),
        nn.BatchNorm2d(out_channels)
    )
  def forward(self,x):
    return self.transconv_block(x)