text: # Copyright 2021 The TensorFlow Authors. All Rights Reserved.
  #
  # 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.ops.array_ops.repeat."""
  
  from tensorflow.compiler.tests import xla_test
  from tensorflow.python.eager import def_function
  from tensorflow.python.framework import dtypes
  from tensorflow.python.ops import array_ops
  from tensorflow.python.platform import test
  
  
  class RepeatTest(xla_test.XLATestCase):
  
    def test(self):
  
      # Verifies that bounded dynamic result generated from the Where op can be
      # Reshaped correctly.
      @def_function.function(jit_compile=True)
      def repeat(values, repeats, axis):
        return array_ops.repeat(values, repeats, axis)
  
      with self.session() as sess:
        with self.test_scope():
          values = array_ops.constant([[1, 2], [3, 4]], dtype=dtypes.int32)
          repeats = array_ops.constant([1, 2], dtype=dtypes.int32)
          y1 = repeat(values, repeats, 0)
          y2 = repeat(values, repeats, 1)
        actual1, actual2 = sess.run([y1, y2])
  
      self.assertAllEqual(actual1, [[1, 2], [3, 4], [3, 4]])
      self.assertAllEqual(actual2, [[1, 2, 2], [3, 4, 4]])
  
  
  if __name__ == "__main__":
    test.main()
  