xref: /external/tensorflow/tensorflow/python/training/server_lib_sparse_job_test.py

# Copyright 2017 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 tf.GrpcServer."""

from __future__ import absolute_import
from __future__ import division
from __future__ import print_function

from tensorflow.python.client import session
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import ops
from tensorflow.python.platform import test
from tensorflow.python.training import server_lib


class SparseJobTest(test.TestCase):

  # TODO(b/34465411): Starting multiple servers with different configurations
  # in the same test is flaky. Move this test case back into
  # "server_lib_test.py" when this is no longer the case.
  def testSparseJob(self):
    server = server_lib.Server({"local": {37: "localhost:0"}})
    with ops.device("/job:local/task:37"):
      a = constant_op.constant(1.0)

    with session.Session(server.target) as sess:
      self.assertEqual(1.0, sess.run(a))


if __name__ == "__main__":
  test.main()