code: def _dummy_variables(in_channels, out_channels, num_weight_matrices):
      """Create variable substitutes for feature_steered_convolution."""
      var_u = tf.zeros(shape=(in_channels, num_weight_matrices))
      var_v = tf.zeros(shape=(in_channels, num_weight_matrices))
      var_c = tf.zeros(shape=(num_weight_matrices))
      var_w = tf.zeros(
          shape=(num_weight_matrices, in_channels, out_channels)
      )
      var_b = tf.zeros(shape=(out_channels))
      return var_u, var_v, var_c, var_w, var_b
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import itertools
  from absl.testing import parameterized
  import numpy
  from six.moves import range
  import tensorflow
  import tensorflow_graphics.geometry.convolution.graph_convolution
  from tensorflow_graphics.util import test_case
label_desc: Use image node_id 3 for calling a global function with example usage: _dummy_variables(in_channels, out_channels, num_weight_matrices) and returns: var_u,  var_v,  var_c,  var_w,  var_b