code: def forward(self, src_seq, initial_state=None):
      states = (
          initial_state
          if initial_state is not None
          else self.cell.get_initial_state(src_seq)
      )
      encoding_hidden_states = list()
      total_steps = src_seq.get_shape().as_list()[1]
      for time_step in range(total_steps):
          if not isinstance(states, list):
              states = [states]
          output, states = self.cell.call(
              src_seq[:, time_step, :], states, training=self.is_train
          )
          encoding_hidden_states.append(states[0])
      return output, encoding_hidden_states, states[0]
  
imports: import numpy
  import tensorflow
  import tensorlayer
  from tensorlayer.layers import Dense, Dropout, Input
  from tensorlayer.layers.core import Layer
  from tensorlayer.models import Model
label_desc: Use image node_id 3 for calling the Encoder obj's underlying member method code with example usage: obj.forward(src_seq, initial_state) and returns: output,  encoding_hidden_states,  states