code: def lstm_seq2seq_internal_bid_encoder(
      inputs, targets, hparams, train
  ):
      """The basic LSTM seq2seq model with bidirectional encoder."""
      with tf.variable_scope("lstm_seq2seq_bid_encoder"):
          if inputs is not None:
              inputs_length = common_layers.length_from_embedding(
                  inputs
              )
              # Flatten inputs.
              inputs = common_layers.flatten4d3d(inputs)
              # LSTM encoder.
              _, final_encoder_state = lstm_bid_encoder(
                  inputs, inputs_length, hparams, train, "encoder"
              )
          else:
              inputs_length = None
              final_encoder_state = None
          # LSTM decoder.
          shifted_targets = common_layers.shift_right(targets)
          # Add 1 to account for the padding added to the left from shift_right
          targets_length = (
              common_layers.length_from_embedding(shifted_targets) + 1
          )
          hparams_decoder = copy.copy(hparams)
          hparams_decoder.hidden_size = 2 * hparams.hidden_size
          decoder_outputs, _ = lstm(
              common_layers.flatten4d3d(shifted_targets),
              targets_length,
              hparams_decoder,
              train,
              "decoder",
              initial_state=final_encoder_state,
          )
          return tf.expand_dims(decoder_outputs, axis=2)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import copy
  from tensor2tensor.layers import area_attention
  from tensor2tensor.layers import common_hparams
  from tensor2tensor.layers import common_layers
  from tensor2tensor.utils import contrib
  from tensor2tensor.utils import registry
  from tensor2tensor.utils import t2t_model
  import tensorflow.compat.v1
  from tensorflow.compat.v1 import estimator
label_desc: Use image node_id 7 for calling a global function with example usage: lstm_seq2seq_internal_bid_encoder(inputs, targets, hparams, train) and returns: tf