A toy example to check if we can force dependencies between completely unrelated operations

toy_matmul.py

import tensorflow as tf

dim = 32

X1 = tf.random_uniform([dim, dim], 0, 10)
_X1 = tf.placeholder(dtype=tf.float32, shape=[dim, dim])

X2 = tf.random_uniform([dim, dim], 0, 10)
_X2 = tf.placeholder(dtype=tf.float32, shape=[dim, dim])

mul1 = tf.matmul(_X1, _X1)
mul2 = tf.matmul(_X2, _X2)

config_proto = tf.ConfigProto(graph_options=tf.GraphOptions(build_cost_model=1))

sess = tf.Session(config=config_proto)
sess.run(tf.global_variables_initializer())

X1_, X2_ = sess.run([X1, X2])
X_ = [X1_, X2_]
_X = [_X1, _X2]

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

W_ = sess.run([mul1, mul2], {_i: i_ for _i, i_ in zip(_X, X_)}, options=run_options, run_metadata=run_metadata)

trace = timeline.Timeline(step_stats=run_metadata.step_stats)
trace_file = open('timeline.ctf.json', 'w')
trace_file.write(trace.generate_chrome_trace_format())