Run matmul on different CPU devices, plot timeline

cpu_device_test.py

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

n = 1024
with tf.device("cpu:0"):
    a1 = tf.ones((n, n))
    a2 = tf.ones((n, n))
with tf.device("cpu:1"):
    a3 = tf.matmul(a1, a2)
with tf.device("cpu:2"):
    a4 = tf.matmul(a1, a2)
with tf.device("cpu:3"):
    a5 = tf.matmul(a3, a4)
    

# turn off graph optimizations
no_opt = tf.OptimizerOptions(opt_level=tf.OptimizerOptions.L0,
                             do_common_subexpression_elimination=False,
                             do_function_inlining=False,
                             do_constant_folding=False)
config = tf.ConfigProto(graph_options=tf.GraphOptions(optimizer_options=no_opt),
                        log_device_placement=True, allow_soft_placement=False,
                        device_count={"CPU": 8},
                        inter_op_parallelism_threads=3,
                        intra_op_parallelism_threads=1)
sess = tf.Session(config=config)

run_metadata = tf.RunMetadata()
run_options = tf.RunOptions(trace_level=tf.RunOptions.FULL_TRACE,
                                    output_partition_graphs=True)

sess.run(a5.op, options=run_options, run_metadata=run_metadata)

trace = timeline.Timeline(step_stats=run_metadata.step_stats)
with open('/tmp/timeline.json', 'w') as out:
    out.write(trace.generate_chrome_trace_format())

print(str(run_metadata))

how do you determine the number of inter_op_parallelism_threads? or is there an automatic way for tensorflow to determine this?

would you mind answering some of my problems with respect to this post here? Thanks.