def test_input_specs(self):
@eager_def_function.function(input_signature=[{
"a": tensor_spec.TensorSpec([], dtypes.int32),
"b": tensor_spec.TensorSpec([], dtypes.int32)
}])
def test_input_dict(value):
return math_ops.add(value["a"], value["b"])
port = portpicker.pick_unused_port()
address = "localhost:{}".format(port)
server_resource = rpc_ops.Server(address)
server_resource.register("test_input_dict", test_input_dict)
server_resource.start()
client = rpc_ops.Client(
address=address, name="test_client", list_registered_methods=True)
a = variables.Variable(2, dtype=dtypes.int32)
b = variables.Variable(3, dtype=dtypes.int32)
result_or = client.test_input_dict({"a": a, "b": b})
self.assertAllEqual(result_or.is_ok(), True)
self.assertAllEqual(result_or.get_value(), 5)
with self.assertRaises(TypeError):
client.test_input_dict([a, b])
def test_captured_inputs(self):
v = variables.Variable(initial_value=0, dtype=dtypes.int64)
@eager_def_function.function(
input_signature=[tensor_spec.TensorSpec([], dtypes.int64)])
def assign_add(a):
v.assign_add(a)
@eager_def_function.function(input_signature=[])
def read_var():
return v.value()
port = portpicker.pick_unused_port()
address = "localhost:{}".format(port)
server = rpc_ops.Server(address)
server.register("assign_add", assign_add)
server.register("read_var", read_var)
server.start()
client = rpc_ops.Client(address)
result_or = client.call("assign_add",
[variables.Variable(2, dtype=dtypes.int64)])
self.assertAllEqual(result_or.is_ok(), True)
result_or = client.call("assign_add",
[variables.Variable(2, dtype=dtypes.int64)])
self.assertAllEqual(result_or.is_ok(), True)
result_or = client.call(
"read_var", output_specs=[tensor_spec.TensorSpec([], dtypes.int64)])
self.assertAllEqual(result_or.is_ok(), True)
self.assertAllEqual(result_or.get_value(), [4])
def test_rpc_ops_wrapper(self):
@eager_def_function.function(input_signature=[
tensor_spec.TensorSpec([], dtypes.int32),
tensor_spec.TensorSpec([], dtypes.int32)
])
def _remote_fn(a, b):
return math_ops.multiply(a, b)
port = portpicker.pick_unused_port()
address = "localhost:{}".format(port)
server_resource = rpc_ops.Server(address)
server_resource.register("multiply", _remote_fn)
server_resource.start()
client = rpc_ops.Client(address=address, name="test_client")
a = variables.Variable(2, dtype=dtypes.int32)
b = variables.Variable(3, dtype=dtypes.int32)
mul_or = client.call(
args=[a, b],
method_name="multiply",
output_specs=tensor_spec.TensorSpec((), dtypes.int32))
self.assertAllEqual(mul_or.is_ok(), True)
self.assertAllEqual(mul_or.get_value(), 6)
# Test empty client name
client1 = rpc_ops.Client(address, list_registered_methods=True)
mul_or = client1.call(
args=[a, b],
method_name="multiply",
output_specs=tensor_spec.TensorSpec((), dtypes.int32))
self.assertAllEqual(mul_or.is_ok(), True)
self.assertAllEqual(mul_or.get_value(), 6)
# Test without output_spec
mul_or = client1.multiply(a, b)
self.assertAllEqual(mul_or.is_ok(), True)
self.assertAllEqual(mul_or.get_value(), 6)
self.assertEqual(client1.multiply.__doc__,
"RPC Call for multiply method to server " + address)
def test_output_specs(self):
@eager_def_function.function(
input_signature=[tensor_spec.TensorSpec([], dtypes.int32)])
def test_dict(val):
return {"key": val}
@eager_def_function.function(
input_signature=[tensor_spec.TensorSpec([], dtypes.int32)])
def is_positive(a):
if a > 0:
return True
return False
@eager_def_function.function(input_signature=[])
def do_nothing():
return []
@eager_def_function.function(
input_signature=[tensor_spec.TensorSpec([], dtypes.int32)])
def test_nested_structure(v):
return {"test": (v, [v, v]), "test1": (v,)}
port = portpicker.pick_unused_port()
address = "localhost:{}".format(port)
server_resource = rpc_ops.Server(address)
server_resource.register("test_dict", test_dict)
server_resource.register("is_positive", is_positive)
server_resource.register("test_nested_structure", test_nested_structure)
server_resource.register("do_nothing", do_nothing)
server_resource.start()
client = rpc_ops.Client(
address=address, name="test_client", list_registered_methods=True)
a = variables.Variable(2, dtype=dtypes.int32)
result_or = client.test_dict(a)
self.assertAllEqual(result_or.is_ok(), True)
nest.map_structure(self.assertAllEqual, result_or.get_value(), {"key": 2})
self.assertTrue(client.is_positive(a))
result_or = client.test_nested_structure(a)
self.assertAllEqual(result_or.is_ok(), True)
nest.map_structure(self.assertAllEqual, result_or.get_value(), {
"test": (2, [2, 2]),
"test1": (2,)
})
result_or = client.do_nothing()
self.assertAllEqual(result_or.is_ok(), True)
self.assertAllEqual(result_or.get_value(), [])
def test_queue_resource(self):
elements = np.random.randint(100, size=[200])
queue = data_flow_ops.FIFOQueue(200, dtypes.int64, shapes=[])
@eager_def_function.function()
def populate_queue():
queue.enqueue_many(elements)
queue.close()
port = portpicker.pick_unused_port()
address = "localhost:{}".format(port)
server = rpc_ops.Server(address)
server.register("populate_queue", populate_queue)
server.start()
client = rpc_ops.Client(address, list_registered_methods=True)
client.populate_queue()
for e in elements:
self.assertAllEqual(e, queue.dequeue())
def test_rpc_error(self):
v = variables.Variable(initial_value=0, dtype=dtypes.int64)
@eager_def_function.function(
input_signature=[tensor_spec.TensorSpec([], dtypes.int64)])
def assign_add(a):
v.assign_add(a)
@eager_def_function.function(input_signature=[])
def read_var():
return v.value()
port = portpicker.pick_unused_port()
address = "localhost:{}".format(port)
server = rpc_ops.Server(address)
server.register("assign_add", assign_add)
server.register("read_var", read_var)
server.start()
client = rpc_ops.Client(address, list_registered_methods=True)
# confirm it works as expected when arguments are passed.
result_or = client.call("assign_add",
[variables.Variable(2, dtype=dtypes.int64)])
self.assertAllEqual(result_or.is_ok(), True)
result_or = client.call(
"read_var", output_specs=[tensor_spec.TensorSpec([], dtypes.int64)])
self.assertAllEqual(result_or.is_ok(), True)
self.assertAllEqual(result_or.get_value(), [2])
result_or = client.assign_add(variables.Variable(2, dtype=dtypes.int64))
self.assertAllEqual(True, result_or.is_ok())
result_or = client.read_var()
self.assertAllEqual(True, result_or.is_ok())
self.assertAllEqual(result_or.get_value(), 4)
# Fails with invalid argument error when no arguments are passed.
result_or = client.call("assign_add")
self.assertAllEqual(result_or.is_ok(), False)
error_code, _ = result_or.get_error()
self.assertAllEqual(error_code, errors.INVALID_ARGUMENT)
def test_multi_device_resource_cpu(self):
with ops.device("/device:cpu:1"):
v = variables.Variable(initial_value=0, dtype=dtypes.int64)
@eager_def_function.function(
input_signature=[tensor_spec.TensorSpec([], dtypes.int64)])
def assign_add(a):
v.assign_add(a)
with ops.device("/device:CPU:0"):
port = portpicker.pick_unused_port()
address = "localhost:{}".format(port)
server = rpc_ops.Server(address)
server.register("assign_add", assign_add)
server.start()
client = rpc_ops.Client(address, list_registered_methods=True)
result_or = client.assign_add(variables.Variable(2, dtype=dtypes.int64))
self.assertAllEqual(result_or.is_ok(), True)
self.assertAllEqual(v, 2)
def test_rpc_call_op_in_tf_function(self):
@eager_def_function.function(input_signature=[
tensor_spec.TensorSpec([], dtypes.int32),
tensor_spec.TensorSpec([], dtypes.int32)
])
def _remote_fn(a, b):
return math_ops.multiply(a, b)
port = portpicker.pick_unused_port()
address = "localhost:{}".format(port)
server_resource = rpc_ops.Server(address)
server_resource.register("remote_fn", _remote_fn)
server_resource.start()
client = rpc_ops.Client(address=address, name="test_client")
a = variables.Variable(2, dtype=dtypes.int32)
b = variables.Variable(3, dtype=dtypes.int32)
@eager_def_function.function
def call_fn():
result_or = client.call(
args=[a, b],
method_name="remote_fn",
output_specs=[tensor_spec.TensorSpec([], dtypes.int32)])
self.assertAllEqual(True, result_or.is_ok())
result = result_or.get_value()
self.assertEqual(len(result), 1) # Call returns a list(tensors)
# TODO(ishark): Shape for output tensor is unknown currently.
# Add attribute for capturing TensorSpec for output and enable
# check below:
# self.assertIsNotNone(result[0].shape.rank)
return result
self.assertAllEqual(call_fn(), [6])
def test_resource_deletion(self):
port = portpicker.pick_unused_port()
address = "localhost:{}".format(port)
server = rpc_ops.Server(address)
server_handle = server._server_handle
# Test Future resource deletion
v = variables.Variable(initial_value=0, dtype=dtypes.int64)
@eager_def_function.function(input_signature=[])
def read_var():
return v.value()
server.register("read_var", read_var)
server.start()
client = rpc_ops.Client(address)
client_handle = client._client_handle
# Check future resource deletion without calling get_value.
def _create_and_delete_rpc_future():
handle = client.call(
"read_var", output_specs=[tensor_spec.TensorSpec([], dtypes.int64)])
return handle._status_or
@eager_def_function.function
def _create_and_delete_rpc_future_fn():
handle = client.call(
"read_var", output_specs=[tensor_spec.TensorSpec([], dtypes.int64)])
return handle._status_or
for _ in range(2):
handle = _create_and_delete_rpc_future()
with self.assertRaises(errors.NotFoundError):
resource_variable_ops.destroy_resource_op(
handle, ignore_lookup_error=False)
for _ in range(2):
handle = _create_and_delete_rpc_future_fn()
with self.assertRaises(errors.NotFoundError):
resource_variable_ops.destroy_resource_op(
handle, ignore_lookup_error=False)
# Check future resource deletion with calling get_value.
def _create_and_delete_with_future():
handle = client.call(
"read_var", output_specs=[tensor_spec.TensorSpec([], dtypes.int64)])
status_or_handle = handle._status_or
handle.get_value()
return status_or_handle
# Check future resource deletion with calling get_value with tf.function.
@eager_def_function.function
def _create_and_delete_with_future_fn():
handle = client.call(
"read_var", output_specs=[tensor_spec.TensorSpec([], dtypes.int64)])
status_or_handle = handle._status_or
handle.get_value()
return status_or_handle
for _ in range(2):
resource_handle = _create_and_delete_with_future()
with self.assertRaises(errors.NotFoundError):
resource_variable_ops.destroy_resource_op(
resource_handle, ignore_lookup_error=False)
for _ in range(2):
resource_handle = _create_and_delete_with_future_fn()
with self.assertRaises(errors.NotFoundError):
resource_variable_ops.destroy_resource_op(
resource_handle, ignore_lookup_error=False)
# Test server client resource gets deleted.
del client
with self.assertRaises(errors.NotFoundError):
resource_variable_ops.destroy_resource_op(
client_handle, ignore_lookup_error=False)
# Test server server resource gets deleted.
del server
with self.assertRaises(errors.NotFoundError):
resource_variable_ops.destroy_resource_op(
server_handle, ignore_lookup_error=False)
def test_call_register_ordering(self):
port = portpicker.pick_unused_port()
address = "localhost:{}".format(port)
# Create client succeeds before server start and registration
client = rpc_ops.Client(address)
# Create client with list_registered_methods fails before server is started.
with self.assertRaises(errors.DeadlineExceededError):
rpc_ops.Client(
address,
name="client1",
list_registered_methods=True,
timeout_in_ms=1)
v = variables.Variable(initial_value=0, dtype=dtypes.int64)
@eager_def_function.function(
input_signature=[tensor_spec.TensorSpec([], dtypes.int64)])
def assign_add(a):
v.assign_add(a)
@eager_def_function.function(input_signature=[])
def read_var():
return v.value()
server = rpc_ops.Server(address)
def start_server():
# Delay server start to test whether client creation also waits
# till server is up.
time.sleep(1)
server.register("assign_add", assign_add)
server.start()
t = threading.Thread(target=start_server)
t.start()
# Create same "client1" again should succeed.
client1_with_listed_methods = rpc_ops.Client(
address, name="client1", list_registered_methods=True)
result_or = client1_with_listed_methods.assign_add(
variables.Variable(2, dtype=dtypes.int64))
self.assertAllEqual(result_or.is_ok(), True)
result_or = client.call("assign_add",
[variables.Variable(2, dtype=dtypes.int64)])
self.assertAllEqual(result_or.is_ok(), True)
# Create client with registered methods
client2_with_listed_methods = rpc_ops.Client(
address=address, name="client2", list_registered_methods=True)
result_or = client2_with_listed_methods.assign_add(
variables.Variable(2, dtype=dtypes.int64))
self.assertAllEqual(result_or.is_ok(), True)
self.assertAllEqual(v, 6)
# Register new method after server started.
with self.assertRaisesRegex(
errors.FailedPreconditionError,
"All methods must be registered before starting the server"):
server.register("read_var", read_var)
