merge_tf_events.py

import json

import tensorflow as tf
from tensorflow.python.client import timeline

x = tf.random_normal([1000, 1000])
y = tf.random_normal([1000, 1000])
res = tf.matmul(x, y)

# Run the graph with full trace option
total_result = None
with tf.Session() as sess:
    for i in range(2):
        run_options = tf.RunOptions(trace_level=tf.RunOptions.FULL_TRACE)
        run_metadata = tf.RunMetadata()
        sess.run(res, options=run_options, run_metadata=run_metadata)

        # Create the Timeline object, and write it to a json
        tl = timeline.Timeline(run_metadata.step_stats)
        ctf = tl.generate_chrome_trace_format()
        # convert crome trace to python dict
        ctf_dict = json.loads(ctf)
        # create one dict for all results
        if total_result is None:
            total_result = ctf_dict
        else:
            for event in ctf_dict['traceEvents']:
                # add only events running times, not definitions
                if 'ts' in event:
                    total_result['traceEvents'].append(event)

with open('timeline_total.json', 'w') as f:
    json.dump(total_result, f)