text: # Copyright 2018 The TensorFlow Probability Authors.
  #
  # Licensed under the Apache License, Version 2.0 (the "License");
  # you may not use this file except in compliance with the License.
  # You may obtain a copy of the License at
  #
  #     http://www.apache.org/licenses/LICENSE-2.0
  #
  # Unless required by applicable law or agreed to in writing, software
  # distributed under the License is distributed on an "AS IS" BASIS,
  # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  # See the License for the specific language governing permissions and
  # limitations under the License.
  # ============================================================================
  """Tests for tensorflow_probability.layers Keras initializers."""
  
  # Dependency imports
  import numpy as np
  
  import tensorflow.compat.v2 as tf
  import tensorflow_probability as tfp
  from tensorflow_probability.python.internal import test_util
  
  
  @test_util.test_all_tf_execution_regimes
  class BlockwiseInitializerTest(test_util.TestCase):
  
    def test_works_correctly(self):
      init = tfp.layers.BlockwiseInitializer(['glorot_uniform', 'zeros'], [3, 4])
      x = init([2, 1, 7])
      self.assertEqual((2, 1, 7), x.shape)
      x_ = self.evaluate(x)
      self.assertAllEqual(np.zeros([2, 1, 4]), x_[..., 3:])
  
    def test_de_serialization(self):
      s = tf.initializers.serialize(
          tfp.layers.BlockwiseInitializer(['glorot_uniform', 'zeros'], [3, 4]))
      init_clone = tf.initializers.deserialize(s)
      x = init_clone([2, 1, 7])
      self.assertEqual((2, 1, 7), x.shape)
      x_ = self.evaluate(x)
      self.assertAllEqual(np.zeros([2, 1, 4]), x_[..., 3:])
  
  
  if __name__ == '__main__':
    test_util.main()
  