old_contents: # Copyright 2020 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 script operations."""
  
  from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  
  from tensorflow.python.eager import def_function
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import test_util
  from tensorflow.python.framework import constant_op
  from tensorflow.python.ops import script_ops
  from tensorflow.python.ops.script_ops import numpy_function
  from tensorflow.python.ops.variables import Variable
  from tensorflow.python.platform import test
  
  
  class NumpyFunctionTest(test.TestCase):
  
    @test_util.run_in_graph_and_eager_modes
    def test_numpy_arguments(self):
  
      def plus(a, b):
        return a + b
  
      actual_result = script_ops.numpy_function(plus, [1, 2], dtypes.int32)
      expect_result = constant_op.constant(3, dtypes.int32)
      self.assertAllEqual(actual_result, expect_result)
  
    def test_stateless_flag(self):
      call_count = Variable(0, dtype=dtypes.int32)
  
      # make sure to have a significant difference to the expected number of execution, which is 1
      nruns = 10
  
      def plus(a, b):
        call_count.assign_add(1)
        return a + b
  
      @def_function.function
      def tensor_double_plus_stateless(a, b):
        sum1 = 0.
        for _ in range(nruns):
          sum1 += numpy_function(plus, [a, b], dtypes.int32, stateful=False)
        return sum1
  
      # different argument
      tensor_double_plus_stateless(
        constant_op.constant(1),
        constant_op.constant(2),
      )
      # This is not a safe test: as the docs say, using a stateful function while guaranteeing statelessness is
      # undefined. Since it is a guarantee we give without receiving anything for it, we cannot test an expected
      # behavior really. As a proxy, we can say that it will *most likely* not be called 10 times.
      self.assertNotEqual(call_count, nruns)  # If it is 10, every call was executed (most likely)
  
      @def_function.function
      def tensor_double_plus_stateful(a, b):
        sum1 = 0.
        for _ in range(nruns):
          sum1 += numpy_function(plus, [a, b], dtypes.int32, stateful=True)
        return sum1
  
      call_count.assign(0)
      tensor_double_plus_stateful(
        constant_op.constant(3),
        constant_op.constant(4),
                            )
      self.assertEqual(call_count, nruns)  # as it is stateful, func was executed every time executed
  
  
  if __name__ == "__main__":
    test.main()
  
new_contents: # Copyright 2020 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 script operations."""
  
  from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  
  from tensorflow.python.eager import def_function
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import test_util
  from tensorflow.python.framework import constant_op
  from tensorflow.python.ops import script_ops
  from tensorflow.python.ops.script_ops import numpy_function
  from tensorflow.python.platform import test
  
  
  class NumpyFunctionTest(test.TestCase):
  
    @test_util.run_in_graph_and_eager_modes
    def test_numpy_arguments(self):
  
      def plus(a, b):
        return a + b
  
      actual_result = script_ops.numpy_function(plus, [1, 2], dtypes.int32)
      expect_result = constant_op.constant(3, dtypes.int32)
      self.assertAllEqual(actual_result, expect_result)
  
    def test_stateless_flag(self):
      call_count = 0
  
      def plus(a, b):
        nonlocal call_count
        call_count += 1
        return a + b
  
      @def_function.function
      def tensor_double_plus_stateless(a, b):
        sum1 = numpy_function(plus, [a, b], dtypes.int32, stateful=False)
        sum2 = numpy_function(plus, [a, b], dtypes.int32, stateful=False)
        return sum1 + sum2
  
      # different argument
      tensor_double_plus_stateless(
        constant_op.constant(1),
        constant_op.constant(2),
      )
      self.assertEqual(call_count, 1)  # +1 as only the first encounter was executed
  
      @def_function.function
      def tensor_double_plus_stateful(a, b):
        sum1 = numpy_function(plus, [a, b], dtypes.int32, stateful=True)
        sum2 = numpy_function(plus, [a, b], dtypes.int32, stateful=True)
        return sum1 + sum2
  
      tensor_double_plus_stateful(
        constant_op.constant(3),
        constant_op.constant(4),
                            )
      self.assertEqual(call_count, 3)  # +2 as it is stateful, func was both times executed
  
  
  if __name__ == "__main__":
    test.main()
  
subject: update stateless flag test