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Profile model.

Tutorials and examples can be found in:

graph tf.Graph. If None and eager execution is not enabled, use default graph.
run_meta optional tensorflow.RunMetadata proto. It is necessary to to support run time information profiling, such as time and memory.
op_log tensorflow.tfprof.OpLogProto proto. User can assign "types" to graph nodes with op_log. "types" allow user to flexibly group and account profiles using options['accounted_type_regexes'].
cmd string. Either 'op', 'scope', 'graph' or 'code'. 'op' view organizes profile using operation type. (e.g. MatMul) 'scope' view organizes profile using graph node name scope. 'graph' view organizes profile using graph node inputs/outputs. 'code' view organizes profile using Python call stack.
options A dict of options. See core/profiler/g3doc/

If cmd is 'scope' or 'graph', returns GraphNodeProto proto. If cmd is 'op' or 'code', returns MultiGraphNodeProto proto. Side effect: stdout/file/timeline.json depending on options['output']