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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 and benchmarks for creating RPC clusters on localhost."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import time
import numpy as np
from tensorflow.python.client import session as session_lib
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import ops
from tensorflow.python.ops import partitioned_variables
from tensorflow.python.ops import variable_scope
from tensorflow.python.ops import variables
from tensorflow.python.platform import test
from tensorflow.python.training import device_setter
class CreateLocalClusterTest(test.TestCase):
def testCreateLocalCluster(self):
workers, _ = test.create_local_cluster(num_workers=2, num_ps=2)
worker_sessions = [session_lib.Session(w.target) for w in workers]
with ops.device("/job:ps/task:0"):
var0 = variables.Variable(0.0)
with ops.device("/job:ps/task:1"):
var1 = variables.Variable(1.0)
worker_sessions[0].run([var0.initializer, var1.initializer])
with ops.device("/job:ps/task:0"):
var2 = variables.Variable(2.0)
with ops.device("/job:ps/task:1"):
var3 = variables.Variable(3.0)
worker_sessions[1].run([var2.initializer, var3.initializer])
# Read values back in the opposite session
self.assertAllEqual(0.0, var0.eval(session=worker_sessions[1]))
self.assertAllEqual(1.0, var1.eval(session=worker_sessions[1]))
self.assertAllEqual(2.0, var2.eval(session=worker_sessions[0]))
self.assertAllEqual(3.0, var3.eval(session=worker_sessions[0]))
class CreateLocalClusterBenchmark(test.Benchmark):
def benchmarkCreateLocalCluster(self):
deltas = []
iters = 5
for _ in range(iters):
start_time = time.time()
test.create_local_cluster(num_workers=1, num_ps=10)
end_time = time.time()
deltas.append(end_time - start_time)
median_deltas = np.median(deltas)
print("\n\nbenchmark_create_local_cluster_1_worker_10_ps. "
"iterations: %d, median wall time: %g\n\n" % (iters, median_deltas))
self.report_benchmark(
iters=iters,
wall_time=median_deltas,
name="benchmark_create_local_cluster_1_worker_10_ps")
class PartitionedVariablesBenchmark(test.Benchmark):
def benchmark_create_1000_partitions_with_100_parameter_servers(self):
workers, _ = test.create_local_cluster(num_workers=1, num_ps=100)
worker_sessions = [session_lib.Session(w.target) for w in workers]
worker = worker_sessions[0]
partition_sizes = (1, 512, 1024 * 32, 1024 * 128)
partitioned = []
for partition_size in partition_sizes:
# max_shard_bytes is 4, shape is 1000*partition_size float32s which should
# partition into 1000 shards, each containing partition_size float32s.
print("Building partitioned variable with %d floats per partition" %
partition_size)
with ops.device(device_setter.replica_device_setter(ps_tasks=100)):
partitioned_ix = variable_scope.get_variable(
"partitioned_%d" % partition_size,
shape=[1000 * partition_size],
dtype=dtypes.float32,
# Each partition to have exactly N float32s
partitioner=partitioned_variables.variable_axis_size_partitioner(
max_shard_bytes=4 * partition_size))
# Concatenates along axis 0
partitioned.append(ops.convert_to_tensor(partitioned_ix))
variables.global_variables_initializer().run(session=worker)
for ix, partition_size in enumerate(partition_sizes):
print("Running benchmark having partitions with %d floats" %
partition_size)
self.run_op_benchmark(
worker,
partitioned[ix],
name=("read_concat_1000_partitions_from_"
"100_parameter_servers_partsize_%d_floats" % partition_size))
if __name__ == "__main__":
test.main()
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