tf.profiler.write_op_log( graph, log_dir, op_log=None, run_meta=None, add_trace=True )
Log provided 'op_log', and add additional model information below.
The API also assigns ops in tf.trainable_variables() an op type called '_trainable_variables'. The API also logs 'flops' statistics for ops with op.RegisterStatistics() defined. flops calculation depends on Tensor shapes defined in 'graph', which might not be complete. 'run_meta', if provided, completes the shape information with best effort.
graph: tf.Graph. If None and eager execution is not enabled, use default graph.
log_dir: directory to write the log file.
op_log: (Optional) OpLogProto proto to be written. If not provided, an new one is created.
run_meta: (Optional) RunMetadata proto that helps flops computation using run time shape information.
add_trace: Whether to add python code trace information. Used to support "code" view.