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# Copyright 2017 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.
# ==============================================================================
"""Sample TensorFlow benchmark."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import time
import tensorflow as tf
# Define a class that extends from tf.test.Benchmark.
class SampleBenchmark(tf.test.Benchmark):
# Note: benchmark method name must start with `benchmark`.
def benchmarkSum(self):
with tf.Session() as sess:
x = tf.constant(10)
y = tf.constant(5)
result = tf.add(x, y)
iters = 100
start_time = time.time()
for _ in range(iters):
sess.run(result)
total_wall_time = time.time() - start_time
# Call report_benchmark to report a metric value.
self.report_benchmark(
name="sum_wall_time",
# This value should always be per iteration.
wall_time=total_wall_time/iters,
iters=iters)
if __name__ == "__main__":
tf.test.main()
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