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# Copyright 2018 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 remote eager execution."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import functools
import os
import numpy as np
from tensorflow.contrib.eager.python import parameter_server
from tensorflow.contrib.eager.python import remote
from tensorflow.core.protobuf import cluster_pb2
from tensorflow.core.protobuf import tensorflow_server_pb2
from tensorflow.python.eager import backprop
from tensorflow.python.eager import context
from tensorflow.python.eager import function
from tensorflow.python.framework import ops
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import math_ops
from tensorflow.python.ops import resource_variable_ops
from tensorflow.python.ops import variables
from tensorflow.python.platform import test
from tensorflow.python.training import server_lib
JOB_NAME = "remote_device"
ALT_JOB_NAME = "alt_remote_device"
def run_sync_and_async(f):
"""Execute all test methods in the given class in sync and async modes."""
@functools.wraps(f)
def decorator(self, *args, **kwargs):
# TODO(b/117110239): Re-enable.
# with context.execution_mode(context.ASYNC):
# f(self, *args, **kwargs)
with context.execution_mode(context.SYNC):
f(self, *args, **kwargs)
return decorator
def get_server_def(job_name, local_server_port, remote_server_addresses,
task_index):
"""Returns a server def with a single job + multiple tasks."""
cluster_def = cluster_pb2.ClusterDef()
job_def = cluster_def.job.add()
job_def.name = job_name
job_def.tasks[0] = "localhost:%d" % local_server_port
for i, remote_server_address in enumerate(remote_server_addresses, start=1):
job_def.tasks[i] = remote_server_address
server_def = tensorflow_server_pb2.ServerDef(
cluster=cluster_def,
job_name=job_name,
task_index=task_index,
protocol="grpc")
return server_def
class RemoteExecutionTest(test.TestCase):
def __init__(self, methodName="runTest"): # pylint: disable=invalid-name
super(RemoteExecutionTest, self).__init__(methodName)
self._cached_server1 = server_lib.Server.create_local_server()
self._cached_server2 = server_lib.Server.create_local_server()
os.environ["TF_EAGER_REMOTE_USE_SEND_TENSOR_RPC"] = "1"
self._cached_server1_target = self._cached_server1.target[len("grpc://"):]
self._cached_server2_target = self._cached_server2.target[len("grpc://"):]
def setUp(self):
# Start the local server.
context.set_server_def(
server_def=get_server_def(
JOB_NAME,
local_server_port=0,
remote_server_addresses=[
self._cached_server1_target, self._cached_server2_target
],
task_index=0))
@run_sync_and_async
def testDefunMatmul(self):
"""Basic remote eager execution with defun."""
mm_defun = function.defun(math_ops.matmul)
with ops.device("job:%s/replica:0/task:1/device:CPU:0" % JOB_NAME):
x1 = array_ops.ones([2, 2])
with ops.device("job:%s/replica:0/task:2/device:CPU:0" % JOB_NAME):
x2 = array_ops.ones([2, 2])
y = mm_defun(x1, x2)
np.testing.assert_array_equal([[2, 2], [2, 2]], y.numpy())
@run_sync_and_async
def testSimpleMatmul(self):
"""Basic remote eager execution."""
with ops.device("job:%s/replica:0/task:1/device:CPU:0" % JOB_NAME):
x1 = array_ops.ones([2, 2])
with ops.device("job:%s/replica:0/task:2/device:CPU:0" % JOB_NAME):
x2 = array_ops.ones([2, 2])
y = math_ops.matmul(x1, x2)
np.testing.assert_array_equal([[2, 2], [2, 2]], y.numpy())
def testParameterServer(self):
with parameter_server.parameter_server_scope(
is_chief=True, ps_job_name=JOB_NAME, num_ps_tasks=3):
v0 = variables.Variable([1.0], name="v0")
v1 = variables.Variable([2.0], name="v1")
v0.assign(v0 * v1)
self.assertAllEqual(v0.read_value(), [2.0])
self.assertAllEqual(v0.device,
"/job:%s/replica:0/task:0/device:CPU:0" % JOB_NAME)
self.assertAllEqual(v1.device,
"/job:%s/replica:0/task:1/device:CPU:0" % JOB_NAME)
v1.assign_add(v1)
# Simulate aliasing another variable of the same name as v1
with ops.device("/job:%s/replica:0/task:1/device:CPU:0" % JOB_NAME):
v1_replica = parameter_server.SharedVariable(
[1.0], name="v1", initialize=False)
self.assertAllEqual(v1_replica.read_value(), [4.0])
@run_sync_and_async
def testSimpleWeightRead(self):
"""Basic remote eager weight read."""
with ops.device("job:%s/replica:0/task:1/device:CPU:0" % JOB_NAME):
w = resource_variable_ops.ResourceVariable([[2.0]])
loss = w * w
np.testing.assert_array_equal([[4.0]], loss.numpy())
@run_sync_and_async
def testTapeWeightRead(self):
"""Remote eager weight read in a tape."""
with ops.device("job:%s/replica:0/task:1/device:CPU:0" % JOB_NAME):
w = resource_variable_ops.ResourceVariable([[3.0]])
with backprop.GradientTape() as tape:
loss = w * w
grad = tape.gradient(loss, w)
np.testing.assert_array_equal([[9.0]], loss.numpy())
np.testing.assert_array_equal([[6.0]], grad.numpy())
@run_sync_and_async
def testServerDefChanged(self):
"""Update server def, and run ops on new cluster."""
context.set_server_def(
server_def=get_server_def(
ALT_JOB_NAME,
local_server_port=0,
remote_server_addresses=[
self._cached_server1_target, self._cached_server2_target
],
task_index=0))
with ops.device("job:%s/replica:0/task:1/device:CPU:0" % ALT_JOB_NAME):
x1 = array_ops.ones([2, 2])
y = math_ops.matmul(x1, x1)
np.testing.assert_array_equal([[2, 2], [2, 2]], y.numpy())
# Set the server def back to JOB_NAME
context.set_server_def(
server_def=get_server_def(
JOB_NAME,
local_server_port=0,
remote_server_addresses=[
self._cached_server1_target, self._cached_server2_target
],
task_index=0))
with ops.device("job:%s/replica:0/task:1/device:CPU:0" % JOB_NAME):
x1 = array_ops.ones([2, 2])
y = math_ops.matmul(x1, x1)
np.testing.assert_array_equal([[2, 2], [2, 2]], y.numpy())
@run_sync_and_async
def testConnectToRemoteServer(self):
"""Basic server connection."""
remote.connect_to_remote_host(self._cached_server1_target)
with ops.device("job:worker/replica:0/task:1/device:CPU:0"):
x1 = array_ops.ones([2, 2])
x2 = array_ops.ones([2, 2])
y = math_ops.matmul(x1, x2)
np.testing.assert_array_equal([[2, 2], [2, 2]], y.numpy())
if __name__ == "__main__":
ops.enable_eager_execution()
test.main()
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