tf.compat.v1.profiler.ProfileOptionBuilder

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Option Builder for Profiling API.

For tutorial on the options, see https://github.com/tensorflow/tensorflow/tree/master/tensorflow/core/profiler/g3doc/options.md

# Users can use pre-built options:
opts = (
    tf.profiler.ProfileOptionBuilder.trainable_variables_parameter())

# Or, build your own options:
opts = (tf.compat.v1.profiler.ProfileOptionBuilder()
    .with_max_depth(10)
    .with_min_micros(1000)
    .select(['accelerator_micros'])
    .with_stdout_output()
    .build()

# Or customize the pre-built options:
opts = (tf.compat.v1.profiler.ProfileOptionBuilder(
    tf.profiler.ProfileOptionBuilder.time_and_memory())
    .with_displaying_options(show_name_regexes=['.*rnn.*'])
    .build())

# Finally, profiling with the options:
_ = tf.compat.v1.profiler.profile(tf.compat.v1.get_default_graph(),
                        run_meta=run_meta,
                        cmd='scope',
                        options=opts)

options Optional initial option dict to start with.

Methods

account_displayed_op_only

View source

Whether only account the statistics of displayed profiler nodes.

Args
is_true If true, only account statistics of nodes eventually displayed by the outputs. Otherwise, a node's statistics are accounted by its parents as long as it's types match 'account_type_regexes', even if it is hidden from the output, say, by hide_name_regexes.

Returns
self

build

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Build a profiling option.

Returns
A dict of profiling options.

float_operation

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Options used to profile float operations.

Please see https://github.com/tensorflow/tensorflow/tree/master/tensorflow/core/profiler/g3doc/profile_model_architecture.md on the caveats of calculating float operations.

Returns
A dict of profiling options.

order_by

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Order the displayed profiler nodes based on a attribute.

Supported attribute includes micros, bytes, occurrence, params, etc. https://github.com/tensorflow/tensorflow/tree/master/tensorflow/core/profiler/g3doc/options.md

Args
attribute An attribute the profiler node has.

Returns
self

select

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Select the attributes to display.

See https://github.com/tensorflow/tensorflow/tree/master/tensorflow/core/profiler/g3doc/options.md for supported attributes.

Args
attributes A list of attribute the profiler node has.

Returns
self

time_and_memory

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Show operation time and memory consumptions.

Args
min_micros Only show profiler nodes with execution time no less than this. It sums accelerator and cpu times.
min_bytes Only show profiler nodes requested to allocate no less bytes than this.
min_accelerator_micros Only show profiler nodes spend no less than this time on accelerator (e.g. GPU).
min_cpu_micros Only show profiler nodes spend no less than this time on cpu.
min_peak_bytes Only show profiler nodes using no less than this bytes at peak (high watermark). For profiler nodes consist of multiple graph nodes, it sums the graph nodes' peak_bytes.
min_residual_bytes Only show profiler nodes have no less than this bytes not being de-allocated after Compute() ends. For profiler nodes consist of multiple graph nodes, it sums the graph nodes' residual_bytes.
min_output_bytes Only show profiler nodes have no less than this bytes output. The output are not necessarily allocated by this profiler nodes.

Returns
A dict of profiling options.

trainable_variables_parameter

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Options used to profile trainable variable parameters.

Normally used together with 'scope' view.

Returns
A dict of profiling options.

with_accounted_types

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