code: def advanced_indexing_op(input, index):
      """Advanced Indexing for Sequences."""
      batch_size = tf.shape(input)[0]
      max_length = int(input.get_shape()[1])
      dim_size = int(input.get_shape()[2])
      index = tf.range(0, batch_size) * max_length + (index - 1)
      flat = tf.reshape(input, [-1, dim_size])
      relevant = tf.gather(flat, index)
      return relevant
  
imports: from __future__ import division, print_function, absolute_import
  import logging
  import numpy
  import tensorflow.compat.v1
  from tensorflow.python.ops import array_ops
  from tensorflow.python.util.nest import is_sequence
  from ..None import config
  from ..None import utils
  from ..None import activations
  from ..None import initializations
  from ..None import variables
  from .normalization import batch_normalization
label_desc: Use image node_id 8 for calling a global function with example usage: advanced_indexing_op(input, index) and returns: relevant