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# Copyright 2016 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 debugger functionalities in tf.Session with grpc:// URLs.
This test focus on grpc:// debugging of distributed (gRPC) sessions.
"""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import json
import subprocess
import sys
import time
import portpicker
from six.moves import xrange # pylint: disable=redefined-builtin
from tensorflow.core.protobuf import config_pb2
from tensorflow.python.client import session
from tensorflow.python.debug.lib import debug_utils
from tensorflow.python.debug.lib import grpc_debug_test_server
from tensorflow.python.debug.wrappers import framework
from tensorflow.python.debug.wrappers import grpc_wrapper
from tensorflow.python.framework import ops
from tensorflow.python.framework import test_util
from tensorflow.python.ops import math_ops
from tensorflow.python.ops import state_ops
from tensorflow.python.ops import variables
from tensorflow.python.platform import googletest
from tensorflow.python.platform import test
from tensorflow.python.platform import tf_logging
class DistributedSessionDebugTest(test_util.TensorFlowTestCase):
"""Test the debugging of distributed sessions."""
PER_PROC_GPU_MEMORY_FRACTION = 0.1
POLLING_INTERVAL_SEC = 0.025
@classmethod
def setUpClass(cls):
gpu_memory_fraction_opt = (
"--gpu_memory_fraction=%f" % cls.PER_PROC_GPU_MEMORY_FRACTION)
worker_port = portpicker.pick_unused_port()
cluster_spec = "worker|localhost:%d" % worker_port
tf_logging.info("cluster_spec: %s", cluster_spec)
server_bin = test.test_src_dir_path(
"tools/dist_test/server/grpc_tensorflow_server")
cls.server_target = "grpc://localhost:%d" % worker_port
cls.server_procs = {}
cls.server_procs["worker"] = subprocess.Popen(
[
server_bin,
"--cluster_spec=%s" % cluster_spec,
"--job_name=worker",
"--task_id=0",
gpu_memory_fraction_opt,
],
stdout=sys.stdout,
stderr=sys.stderr)
# Start debug server in-process, on separate thread.
(cls.debug_server_port, cls.debug_server_url, _, cls.debug_server_thread,
cls.debug_server
) = grpc_debug_test_server.start_server_on_separate_thread(
dump_to_filesystem=False)
tf_logging.info("debug server url: %s", cls.debug_server_url)
cls.session_config = config_pb2.ConfigProto(
gpu_options=config_pb2.GPUOptions(
per_process_gpu_memory_fraction=cls.PER_PROC_GPU_MEMORY_FRACTION))
@classmethod
def tearDownClass(cls):
for key in cls.server_procs:
cls.server_procs[key].terminate()
cls.debug_server.stop_server().wait()
cls.debug_server_thread.join()
def setUp(self):
pass
def tearDown(self):
self.debug_server.clear_data()
def _pollingAssertDebugTensorValuesAllClose(self, expected_values,
debug_tensor_name):
"""Poll debug_server till tensor appears and matches expected values."""
while (debug_tensor_name not in self.debug_server.debug_tensor_values or
len(self.debug_server.debug_tensor_values) < len(expected_values)):
time.sleep(self.POLLING_INTERVAL_SEC)
self.assertAllClose(
expected_values,
self.debug_server.debug_tensor_values[debug_tensor_name])
def _createGraph(self):
"""Create graph for testing.
Returns:
Python Graph object.
"""
with ops.Graph().as_default() as graph:
with ops.device("/job:worker/task:0/cpu:0"):
self.a = variables.Variable(10.0, name="a")
self.b = variables.Variable(100.0, name="b")
self.inc_a = state_ops.assign_add(self.a, 2.0, name="inc_a")
self.dec_b = state_ops.assign_add(self.b, -5.0, name="dec_b")
self.p = math_ops.multiply(self.inc_a, self.dec_b, name="p")
self.q = math_ops.negative(self.p, name="q")
return graph
def testDistributedRunWithGatedGrpcCommunicatesWithDebugServerCorrectly(self):
graph = self._createGraph()
with session.Session(
config=self.session_config, graph=graph,
target=self.server_target) as sess:
sess.run(self.a.initializer)
sess.run(self.b.initializer)
run_options = config_pb2.RunOptions()
debug_utils.watch_graph(
run_options,
sess.graph,
node_name_regex_whitelist=r"a",
debug_ops=["DebugIdentity"],
debug_urls=[self.debug_server_url])
# Test gated_grpc for an op located on the worker, i.e., on the same
# host as where MasterSession is.
# TODO(cais): gRPC gating of debug ops does not work on partition graphs
# not located on MasterSession hosts (e.g., parameter servers) yet. Make
# it work.
debug_utils.watch_graph(
run_options,
sess.graph,
node_name_regex_whitelist=r"p",
debug_ops=["DebugIdentity(gated_grpc=True)"],
debug_urls=[self.debug_server_url])
for i in xrange(4):
# N.B.: These requests will be fulfilled not in this debugged
# Session.run() invocation, but in the next one.
if i % 2 == 0:
self.debug_server.request_watch("p", 0, "DebugIdentity")
else:
self.debug_server.request_unwatch("p", 0, "DebugIdentity")
expected_p = (10.0 + 2.0 * (i + 1)) * (100.0 - 5.0 * (i + 1))
self.assertAllClose(-expected_p, sess.run(self.q, options=run_options))
self.assertEqual(1, len(self.debug_server.core_metadata_json_strings))
core_metadata = json.loads(
self.debug_server.core_metadata_json_strings[0])
self.assertEqual([], core_metadata["input_names"])
self.assertEqual(["q:0"], core_metadata["output_names"])
self.assertEqual(i, core_metadata["executor_step_index"])
if i == 0:
self.assertEqual(1, len(self.debug_server.partition_graph_defs))
# Tensor "a" is from a PS. It may take longer to arrive due to the fact
# that the stream connection between the PS and the debug server is
# persistent and not torn down at the end of each Session.run()
self._pollingAssertDebugTensorValuesAllClose([10.0 + 2.0 * i],
"a:0:DebugIdentity")
# Due to the gRPC gating of the debug op for "p", the debug tensor
# should be available on odd-indexed runs.
if i % 2 == 0:
self.assertNotIn("p:0:DebugIdentity",
self.debug_server.debug_tensor_values)
else:
self.assertAllClose(
[expected_p],
self.debug_server.debug_tensor_values["p:0:DebugIdentity"])
self.assertNotIn("b:0:DebugIdentity",
self.debug_server.debug_tensor_values)
self.debug_server.clear_data()
def testDistributedRunWithGrpcDebugWrapperWorks(self):
graph = self._createGraph()
with session.Session(
config=self.session_config, graph=graph,
target=self.server_target) as sess:
sess.run(self.a.initializer)
sess.run(self.b.initializer)
def watch_fn(feeds, fetch_keys):
del feeds, fetch_keys
return framework.WatchOptions(
debug_ops=["DebugIdentity"],
node_name_regex_whitelist=r"p")
sess = grpc_wrapper.GrpcDebugWrapperSession(
sess, "localhost:%d" % self.debug_server_port, watch_fn=watch_fn)
for i in xrange(4):
expected_p = (10.0 + 2.0 * (i + 1)) * (100.0 - 5.0 * (i + 1))
self.assertAllClose(-expected_p, sess.run(self.q))
if i == 0:
self.assertEqual(1, len(self.debug_server.partition_graph_defs))
self.assertAllClose(
[expected_p],
self.debug_server.debug_tensor_values["p:0:DebugIdentity"])
self.assertNotIn("b:0:DebugIdentity",
self.debug_server.debug_tensor_values)
self.debug_server.clear_data()
if __name__ == "__main__":
googletest.main()
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