code: def forward(self, x: Tensor):
      for layer in range(self.n_layer):
          x = F.linear(x, self.weights[layer], self.biases[layer])
          x = F.gelu(x)
      x = F.linear(x, self.class_weight, self.class_bias)
      x = pt.sigmoid(x)
      x = x.add(1e-10).log()
      return x
  
imports: import torch
  from torch import Tensor, nn
  from torch.nn import init, functional
label_desc: Use image node_id 3 for calling the SimpleDiscriminator obj's underlying member method code with example usage: obj.forward(x) and returns: x