code: def test_distribute_weights(self):
      layout_map = distribution_lib.LayoutMap(self.device_mesh)
      layout_map[".*kernel"] = distribution_lib.TensorLayout(
          [None, "model"]
      )
      layout_map[".*bias"] = distribution_lib.TensorLayout(["model"])
  
      distribution = distribution_lib.ModelParallel(
          self.device_mesh, layout_map, batch_dim_name="data"
      )
      kernel = backend.Variable(
          initializer=np.arange(8, 4), name="kernel"
      )
      bias = backend.Variable(initializer=np.arange(4), name="bias")
      rng_seed = backend.Variable(initializer=[0, 1], name="seed")
  
      kernel_layout = distribution.get_variable_layout(kernel)
      self.assertIs(kernel_layout.device_mesh, self.device_mesh)
      self.assertEqual(kernel_layout.axes, (None, "model"))
  
      bias_layout = distribution.get_variable_layout(bias)
      self.assertIs(bias_layout.device_mesh, self.device_mesh)
      self.assertEqual(bias_layout.axes, ("model",))
  
      rng_seed_layout = distribution.get_variable_layout(rng_seed)
      self.assertIs(rng_seed_layout.device_mesh, self.device_mesh)
      self.assertEqual(rng_seed_layout.axes, (None,))
  
imports: import os
  from unittest import mock
  import numpy
  import pytest
  import tensorflow
  from keras import backend
  from keras import testing
  from keras.backend import distribution_lib
  from keras.distribution import distribution_lib
label_desc: Use image node_id 2 for calling the ModelParallelDistributionTest obj's underlying member method code with example usage: obj.test_distribute_weights() without return types