xref: /aosp_15_r20/external/tensorflow/tensorflow/python/distribute/ps_values_test.py (revision b6fb3261f9314811a0f4371741dbb8839866f948) 
1# Copyright 2020 The TensorFlow Authors. All Rights Reserved.
2#
3# Licensed under the Apache License, Version 2.0 (the "License");
4# you may not use this file except in compliance with the License.
5# You may obtain a copy of the License at
6#
7#     http://www.apache.org/licenses/LICENSE-2.0
8#
9# Unless required by applicable law or agreed to in writing, software
10# distributed under the License is distributed on an "AS IS" BASIS,
11# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
12# See the License for the specific language governing permissions and
13# limitations under the License.
14# ==============================================================================
15"""Tests for the distributed values library."""
16
17from absl.testing import parameterized
18
19from tensorflow.python.distribute import combinations
20from tensorflow.python.distribute import ps_values
21from tensorflow.python.distribute import strategy_combinations
22from tensorflow.python.eager import def_function
23from tensorflow.python.eager import test
24from tensorflow.python.ops import variable_scope
25from tensorflow.python.ops import variables as variables_lib
26
27
28@combinations.generate(
29    combinations.combine(
30        distribution=[
31            strategy_combinations.central_storage_strategy_with_two_gpus
32        ],
33        mode=["graph", "eager"]))
34class AggregatingVariableTest(test.TestCase, parameterized.TestCase):
35
36  def testAssignOutOfScope(self, distribution):
37    with distribution.scope():
38      aggregating = variables_lib.Variable(1.)
39    self.assertIsInstance(aggregating, ps_values.AggregatingVariable)
40    self.evaluate(aggregating.assign(3.))
41    self.assertEqual(self.evaluate(aggregating.read_value()), 3.)
42    self.assertEqual(self.evaluate(aggregating._v.read_value()), 3.)
43
44  def testAssignAdd(self, distribution):
45    with distribution.scope():
46      v = variable_scope.variable(
47          1, aggregation=variables_lib.VariableAggregation.MEAN)
48    self.evaluate(variables_lib.global_variables_initializer())
49
50    @def_function.function
51    def assign():
52      return v.assign_add(2)
53
54    per_replica_results = self.evaluate(
55        distribution.experimental_local_results(
56            distribution.run(assign)))
57    self.assertAllEqual([3], per_replica_results)
58
59
60if __name__ == "__main__":
61  test.main()
62