distribute_utils_test.py

# 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 distribution util functions."""

import tensorflow as tf

from official.common import distribute_utils


class DistributeUtilsTest(tf.test.TestCase):
  """Tests for distribute util functions."""

  def test_invalid_args(self):
    with self.assertRaisesRegex(ValueError, '`num_gpus` can not be negative.'):
      _ = distribute_utils.get_distribution_strategy(num_gpus=-1)

    with self.assertRaisesRegex(ValueError,
                                '.*If you meant to pass the string .*'):
      _ = distribute_utils.get_distribution_strategy(
          distribution_strategy=False, num_gpus=0)
    with self.assertRaisesRegex(ValueError, 'When 2 GPUs are specified.*'):
      _ = distribute_utils.get_distribution_strategy(
          distribution_strategy='off', num_gpus=2)
    with self.assertRaisesRegex(ValueError,
                                '`OneDeviceStrategy` can not be used.*'):
      _ = distribute_utils.get_distribution_strategy(
          distribution_strategy='one_device', num_gpus=2)

  def test_one_device_strategy_cpu(self):
    ds = distribute_utils.get_distribution_strategy('one_device', num_gpus=0)
    self.assertEquals(ds.num_replicas_in_sync, 1)
    self.assertEquals(len(ds.extended.worker_devices), 1)
    self.assertIn('CPU', ds.extended.worker_devices[0])

  def test_one_device_strategy_gpu(self):
    ds = distribute_utils.get_distribution_strategy('one_device', num_gpus=1)
    self.assertEquals(ds.num_replicas_in_sync, 1)
    self.assertEquals(len(ds.extended.worker_devices), 1)
    self.assertIn('GPU', ds.extended.worker_devices[0])

  def test_mirrored_strategy(self):
    ds = distribute_utils.get_distribution_strategy(num_gpus=5)
    self.assertEquals(ds.num_replicas_in_sync, 5)
    self.assertEquals(len(ds.extended.worker_devices), 5)
    for device in ds.extended.worker_devices:
      self.assertIn('GPU', device)

    _ = distribute_utils.get_distribution_strategy(
        distribution_strategy='mirrored',
        num_gpus=2,
        all_reduce_alg='nccl',
        num_packs=2)
    with self.assertRaisesRegex(
        ValueError,
        'When used with `mirrored`, valid values for all_reduce_alg are.*'):
      _ = distribute_utils.get_distribution_strategy(
          distribution_strategy='mirrored',
          num_gpus=2,
          all_reduce_alg='dummy',
          num_packs=2)

  def test_mwms(self):
    distribute_utils.configure_cluster(worker_hosts=None, task_index=-1)
    ds = distribute_utils.get_distribution_strategy(
        'multi_worker_mirrored', all_reduce_alg='nccl')
    self.assertIsInstance(
        ds, tf.distribute.experimental.MultiWorkerMirroredStrategy)

  def test_no_strategy(self):
    ds = distribute_utils.get_distribution_strategy('off')
    self.assertIs(ds, tf.distribute.get_strategy())

  def test_invalid_strategy(self):
    with self.assertRaisesRegexp(
        ValueError,
        'distribution_strategy must be a string but got: False. If'):
      distribute_utils.get_distribution_strategy(False)
    with self.assertRaisesRegexp(
        ValueError, 'distribution_strategy must be a string but got: 1'):
      distribute_utils.get_distribution_strategy(1)

  def test_get_strategy_scope(self):
    ds = distribute_utils.get_distribution_strategy('one_device', num_gpus=0)
    with distribute_utils.get_strategy_scope(ds):
      self.assertIs(tf.distribute.get_strategy(), ds)
    with distribute_utils.get_strategy_scope(None):
      self.assertIsNot(tf.distribute.get_strategy(), ds)

if __name__ == '__main__':
  tf.test.main()