def setUp(self):
super(FaultToleranceTest, self).setUp()
# Set the environment variable to prevent hanging upon job failure and
# restart. Note that it defaults to 'use_caller' at Google, but defaults
# to False in OSS.
os.environ["GRPC_FAIL_FAST"] = "use_caller"
self._cluster = multi_worker_test_base.create_multi_process_cluster(
num_workers=FaultToleranceTest.NUM_WORKERS,
num_ps=FaultToleranceTest.NUM_PS,
rpc_layer="grpc")
self._cluster_def = self._cluster.cluster_resolver.cluster_spec().as_dict()
self._cluster_def["chief"] = [
"localhost:%d" % multi_worker_test_base.pick_unused_port()
]
cluster_resolver = SimpleClusterResolver(
server_lib.ClusterSpec(self._cluster_def), rpc_layer="grpc")
# The strategy's constructor would connect to the cluster.
self.strategy = parameter_server_strategy_v2.ParameterServerStrategyV2(
cluster_resolver)
self.cluster_coord = cluster_coordinator.ClusterCoordinator(self.strategy)
self.thread_coord = thread_coordinator.Coordinator(
clean_stop_exception_types=[])
def setUp(self):
super(MultiProcessClusterTest, self).setUp()
self._cluster = multi_worker_test_base.create_multi_process_cluster(
num_workers=2, num_ps=1, has_chief=True, rpc_layer="grpc")
remote.connect_to_cluster(
self._cluster.cluster_resolver.cluster_spec(), protocol="grpc")
context.ensure_initialized()
def setUpClass(cls):
super(EvaluationTest, cls).setUpClass()
cls._cluster = multi_worker_test_base.create_multi_process_cluster(
num_workers=3, num_ps=2, rpc_layer="grpc")
cls._cluster_def = cls._cluster.cluster_resolver.cluster_spec().as_dict()
cluster_resolver = SimpleClusterResolver(
tf.train.ClusterSpec(cls._cluster_def), rpc_layer="grpc")
cls.strategy = tf.distribute.experimental.ParameterServerStrategy(
cluster_resolver)
cls.cluster_coord = tf.distribute.experimental.coordinator.ClusterCoordinator(cls.strategy)
def setUpClass(cls):
super(EvaluationTest, cls).setUpClass()
cls._cluster = multi_worker_test_base.create_multi_process_cluster(
num_workers=3, num_ps=2, rpc_layer="grpc")
cls._cluster_def = cls._cluster.cluster_resolver.cluster_spec(
).as_dict()
cluster_resolver = SimpleClusterResolver(server_lib.ClusterSpec(
cls._cluster_def),
rpc_layer="grpc")
cls.strategy = parameter_server_strategy_v2.ParameterServerStrategyV2(
cluster_resolver)
cls.cluster_coord = coordinator_lib.ClusterCoordinator(cls.strategy)
def setUp(self, num_workers, num_ps):
super(BaseFaultToleranceTest, self).setUp()
self._cluster = multi_worker_test_base.create_multi_process_cluster(
num_workers=num_workers, num_ps=num_ps, rpc_layer="grpc")
self._cluster_def = self._cluster.cluster_resolver.cluster_spec().as_dict()
self._cluster_def["chief"] = [
"localhost:%d" % multi_worker_test_base.pick_unused_port()
]
cluster_resolver = SimpleClusterResolver(
server_lib.ClusterSpec(self._cluster_def), rpc_layer="grpc")
# The strategy's constructor would connect to the cluster.
self.strategy = parameter_server_strategy_v2.ParameterServerStrategyV2(
cluster_resolver)
self.cluster_coord = cluster_coordinator.ClusterCoordinator(self.strategy)
self.thread_coord = thread_coordinator.Coordinator(
clean_stop_exception_types=[])
self.num_workers = num_workers
self.num_ps = num_ps
def setUpClass(cls):
super(ParameterServerStrategyV2Test, cls).setUpClass()
cls.cluster = multi_worker_test_base.create_multi_process_cluster(
num_workers=2, num_ps=3, rpc_layer="grpc")
cls.cluster_resolver = cls.cluster.cluster_resolver
def setUpClass(cls):
super(VariablePartitioningTest, cls).setUpClass()
cls.cluster = multi_worker_test_base.create_multi_process_cluster(
num_workers=2, num_ps=2, rpc_layer="grpc")
cls.cluster_resolver = cls.cluster.cluster_resolver
def setUpClass(cls):
super(DistributedTableTest, cls).setUpClass()
cls.cluster = multi_worker_test_base.create_multi_process_cluster(
num_workers=2, num_ps=3, rpc_layer="grpc")
cls.cluster_resolver = cls.cluster.cluster_resolver
