tf.compat.v1.profiler.Profiler
TensorFlow multi-step profiler.
tf.compat.v1.profiler.Profiler(
graph=None, op_log=None
)
https://github.com/tensorflow/tensorflow/tree/master/tensorflow/core/profiler/README.md
Typical use case:
# Currently we are only allowed to create 1 profiler per process.
profiler = Profiler(sess.graph)
for i in xrange(total_steps):
if i % 10000 == 0:
run_meta = tf.compat.v1.RunMetadata()
_ = sess.run(...,
options=tf.compat.v1.RunOptions(
trace_level=tf.RunOptions.FULL_TRACE),
run_metadata=run_meta)
profiler.add_step(i, run_meta)
# Profile the parameters of your model.
profiler.profile_name_scope(options=(option_builder.ProfileOptionBuilder
.trainable_variables_parameter()))
# Or profile the timing of your model operations.
opts = option_builder.ProfileOptionBuilder.time_and_memory()
profiler.profile_operations(options=opts)
# Or you can generate a timeline:
opts = (option_builder.ProfileOptionBuilder(
option_builder.ProfileOptionBuilder.time_and_memory())
.with_step(i)
.with_timeline_output(filename).build())
profiler.profile_graph(options=opts)
else:
_ = sess.run(...)
# Auto detect problems and generate advice.
profiler.advise()
| Args |
graph |
tf.Graph. If None and eager execution is not enabled, use default graph. |
op_log |
optional. tensorflow::tfprof::OpLogProto proto. Used to define extra op types. |
Methods
add_step
View source
add_step(
step, run_meta
)
Add statistics of a step.
| Args |
step |
int, An id used to group one or more different run_meta together. When profiling with the profile_xxx APIs, user can use the step id in the options to profile these run_meta together. |
run_meta |
RunMetadata proto that contains statistics of a session run. |
advise
View source
advise(
options
)
Automatically detect problems and generate reports.
| Args |
options |
A dict of options. See ALL_ADVICE example above. |
| Returns |
| An Advise proto that contains the reports from all checkers. |
profile_graph
View source
profile_graph(
options
)
Profile the statistics of graph nodes, organized by dataflow graph.
| Args |
options |
A dict of options. See core/profiler/g3doc/options.md. |
| Returns |
| a GraphNodeProto that records the results. |
profile_name_scope
View source
profile_name_scope(
options
)
Profile the statistics of graph nodes, organized by name scope.
| Args |
options |
A dict of options. See core/profiler/g3doc/options.md. |
| Returns |
| a GraphNodeProto that records the results. |
profile_operations
View source
profile_operations(
options
)
Profile the statistics of the Operation types (e.g. MatMul, Conv2D).
| Args |
options |
A dict of options. See core/profiler/g3doc/options.md. |
| Returns |
| a MultiGraphNodeProto that records the results. |
profile_python
View source
profile_python(
options
)
Profile the statistics of the Python codes.
By default, it shows the call stack from root. To avoid redundant output, you may use options to filter as below options['show_name_regexes'] = ['.my_code.py.']
| Args |
options |
A dict of options. See core/profiler/g3doc/options.md. |
| Returns |
| a MultiGraphNodeProto that records the results. |
serialize_to_string
View source
serialize_to_string()
Serialize the ProfileProto to a binary string.
Users can write it to file for offline analysis by tfprof commandline or graphical interface.
| Returns |
| ProfileProto binary string. |