code: def forward(self, x):
      o = self.conv1(x)
      o = o.transpose(1, 2)
      o = self.norm(o)
      o = o.transpose(1, 2)
      o = self.relu(o)
      o = self.dropout(o)
      mu_sigma = self.conv2(o)
      # TODO: check this sigmoid
      # mu = torch.sigmoid(mu_sigma[:, :self.out_channels//2, :])
      mu = mu_sigma[:, : self.out_channels // 2, :]
      log_sigma = mu_sigma[:, self.out_channels // 2 :, :]
      return mu, log_sigma
  
imports: from torch import nn
label_desc: Use image node_id 2 for calling the MDNBlock obj's underlying member method code with example usage: obj.forward(x) and returns: mu,  log_sigma