class_docstr: CNN discriminator of SEGAN
  
  Arguments
  ---------
  kernel_size : int
      Size of the convolutional kernel.
docstr: forward pass through the discriminator
docstr_tok: ["forward","pass","through","the","discriminator"]
code: def forward(self, x):
      """forward pass through the discriminator"""
      x = x.permute(0, 2, 1)
      # encode
      for i in range(len(self.Norms)):
          x = self.Layers[i](x)
          x = self.Norms[i](x)
          x = F.leaky_relu(x, negative_slope=0.3)
  
      # output
      x = self.Layers[-2](x)
      x = self.Layers[-1](x)
      # x = F.sigmoid(x)
      x = x.permute(0, 2, 1)
  
      return x
  
file_path: speechbrain/speechbrain/lobes/models/segan_model.py
imports: import torch
  import torch.nn
  import torch.utils.data
  import torch.nn.functional
  from math import floor
label_desc: Use image node_id 2 for calling the Discriminator obj's underlying member method code with example usage: obj.forward(x) and returns: x