code: def generate_l_m_permutations(
      max_band: int,
      name: str = "spherical_harmonics_generate_l_m_permutations",
  ) -> Tuple[TensorLike, TensorLike]:  # pylint: disable=line-too-long
      """Generates permutations of degree l and order m for spherical harmonics.
  
      Args:
        max_band: An integer scalar storing the highest band.
        name: A name for this op. Defaults to
          "spherical_harmonics_generate_l_m_permutations".
  
      Returns:
        Two tensors of shape `[max_band*max_band]`.
      """
      with tf.name_scope(name):
          degree_l = []
          order_m = []
          for degree in range(0, max_band + 1):
              for order in range(-degree, degree + 1):
                  degree_l.append(degree)
                  order_m.append(order)
          return (
              tf.convert_to_tensor(value=degree_l),
              tf.convert_to_tensor(value=order_m),
          )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from typing import Tuple
  import numpy
  from six.moves import range
  import tensorflow
  from tensorflow_graphics.math import math_helpers
  from tensorflow_graphics.math import vector
  from tensorflow_graphics.util import asserts
  from tensorflow_graphics.util import export_api
  from tensorflow_graphics.util import shape
  from tensorflow_graphics.util.type_alias import TensorLike
label_desc: Use image node_id 2 for calling a global function with example usage: generate_l_m_permutations(max_band, name) and returns: tf,  tf