code: def forward(self, inputs, hidden_state):
      x = F.relu(self.fc1(inputs))
      h_in = hidden_state.reshape(shape=(-1, self.rnn_hidden_dim))
  
      _, h = self.rnn(x, h_in)
      q = self.fc2(h)  # (batch_size, n_actions)
      return q, h
  
file_path: PARL/examples/QMIX/rnn_model.py
imports: import paddle
  import paddle.nn
  import paddle.nn.functional
  import parl
label_desc: Use image node_id 3 for calling the RNNModel obj's underlying member method code with example usage: obj.forward(inputs, hidden_state) and returns: q,  h