docstr: Forward pass used for teacher-forcing training. 
docstr_tok: ["Forward","pass","used","for","teacher-forcing","training","."]
code: def call(self, x: tf.Tensor) -> tf.Tensor:
      """Forward pass used for teacher-forcing training."""
      # reconstruct input via encoder-decoder
      init_state = self.encoder(x)[1]
      x_recon, z, _ = self.decoder(x, init_state=init_state)
  
      # compute outlier score
      err_recon = self.score_fn(x, x_recon)
  
      # estimate outlier threshold from hidden state of decoder
      z = self.threshold_net(z)
      threshold_est = self.threshold_est(z)
  
      # add threshold estimate loss
      threshold_loss = tf.reduce_mean((err_recon - threshold_est) ** 2)
      self.add_loss(self.beta * threshold_loss)
      return x_recon
  
imports: import numpy
  import tensorflow
  from tensorflow.keras.layers import Bidirectional, Concatenate, Dense, Flatten, Layer, LSTM
  from typing import Callable, List, Tuple
  from alibi_detect.utils.tensorflow.distance import relative_euclidean_distance
label_desc: Use image node_id 2 for calling the Seq2Seq obj's underlying member method code with example usage: obj.call(x) and returns: x_recon