code: def _random_variables(
      in_channels, out_channels, num_weight_matrices, dtype=np.float32
  ):
      """Create random variables for feature_steered_convolution."""
  
      def _random_constant(shape, dtype):
          return tf.constant(
              np.random.uniform(size=shape).astype(dtype)
          )
  
      var_u = _random_constant(
          [in_channels, num_weight_matrices], dtype
      )
      var_v = _random_constant(
          [in_channels, num_weight_matrices], dtype
      )
      var_c = _random_constant([num_weight_matrices], dtype)
      var_w = _random_constant(
          [num_weight_matrices, in_channels, out_channels], dtype
      )
      var_b = _random_constant([out_channels], dtype)
      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 5 for calling a global function with example usage: _random_variables(in_channels, out_channels, num_weight_matrices, dtype) and returns: var_u,  var_v,  var_c,  var_w,  var_b, tf