code: def forward(self, x):
      fmap = []
      for l in self.convs:
          x = l(x)
          x = F.leaky_relu(x, LRELU_SLOPE)
          fmap.append(x)
      x = self.conv_post(x)
      fmap.append(x)
      x = torch.flatten(x, 1, -1)
  
      return x, fmap
  
imports: import torch
  import torch.nn
  import torch.nn.functional
  from torch.nn import AvgPool1d, Conv1d, Conv2d, ConvTranspose1d
  from torch.nn.utils import remove_weight_norm, spectral_norm, weight_norm
label_desc: Use image node_id 2 for calling the DiscriminatorS obj's underlying member method code with example usage: obj.forward(x) and returns: x,  fmap