Method conv_block

light_classifier.py:36–43

(self, c_in, c_out, dropout=0.1, kernel_size=3, stride=1, **kwargs)

      # self.prefc1 = nn.Linear(self.bigN, )

   def conv_block(self, c_in, c_out, dropout=0.1, kernel_size=3, stride=1, **kwargs):
      seq_block = nn.Sequential(
         nn.Conv2d(in_channels=c_in, out_channels=c_out, kernel_size=kernel_size, **kwargs),
         nn.BatchNorm2d(num_features=c_out),
         nn.ReLU(),
         # nn.Dropout2d(p=dropout)
      )
      return seq_block

   def forward(self, x):
      x = self.conv1(x)