Example of using stats summarizer

stats_summarizer_example.py

# export LD_LIBRARY_PATH="/usr/local/cuda/lib64:/usr/local/cuda/extras/CUPTI/lib64:$LD_LIBRARY_PATH"

import tensorflow as tf
a = tf.ones((10, 10))
b = tf.ones((10, 10))
c = tf.matmul(a, b)
ss = tf.contrib.stat_summarizer.NewStatSummarizer(tf.get_default_graph().as_graph_def().SerializeToString())

sess = tf.Session()
for i in range(10):
  run_metadata = tf.RunMetadata()
  run_options = tf.RunOptions(trace_level=tf.RunOptions.FULL_TRACE)
  sess.run(c, options=run_options, run_metadata=run_metadata)
  ss.ProcessStepStatsStr(run_metadata.step_stats.SerializeToString())

print(ss.GetOutputString())