tf.compat.v1.profiler.profile
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Profile model.
tf.compat.v1.profiler.profile(
graph=None,
run_meta=None,
op_log=None,
cmd='scope',
options=_DEFAULT_PROFILE_OPTIONS
)
Tutorials and examples can be found in:
https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/profiler/g3doc/python_api.md
Args |
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/options.md.
|
Returns |
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']
|
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Last updated 2022-11-04 UTC.
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