code: def tf_create_dummy_inputs():
      """Create dummy inputs for TF Tacotron2 model"""
      batch_size = 4
      max_input_length = 32
      max_mel_length = 128
      pad = 1
      n_chars = 24
      input_ids = tf.random.uniform(
          [batch_size, max_input_length + pad],
          maxval=n_chars,
          dtype=tf.int32,
      )
      input_lengths = np.random.randint(
          0, high=max_input_length + 1 + pad, size=[batch_size]
      )
      input_lengths[-1] = max_input_length
      input_lengths = tf.convert_to_tensor(
          input_lengths, dtype=tf.int32
      )
      mel_outputs = tf.random.uniform(
          shape=[batch_size, max_mel_length + pad, 80]
      )
      mel_lengths = np.random.randint(
          0, high=max_mel_length + 1 + pad, size=[batch_size]
      )
      mel_lengths[-1] = max_mel_length
      mel_lengths = tf.convert_to_tensor(mel_lengths, dtype=tf.int32)
      return input_ids, input_lengths, mel_outputs, mel_lengths
  
imports: import numpy
  import tensorflow
label_desc: Use image node_id 1 for calling a global function with example usage: tf_create_dummy_inputs() and returns: input_ids,  input_lengths,  mel_outputs,  mel_lengths