tf.profiler.write_op_log(
graph,
log_dir,
op_log=None,
run_meta=None,
add_trace=True
)
Defined in tensorflow/python/profiler/tfprof_logger.py
.
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.
Args:
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.