tf.test.Benchmark

Abstract class that provides helpers for TensorFlow benchmarks.

View aliases

Compat aliases for migration

tf.compat.v1.test.Benchmark

tf.test.Benchmark()

Methods

`evaluate`

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evaluate(
    tensors
)

Evaluates tensors and returns numpy values.

Args
`tensors`	A Tensor or a nested list/tuple of Tensors.

Returns
tensors numpy values.

`is_abstract`

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@classmethod
is_abstract()

`report_benchmark`

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report_benchmark(
    iters=None, cpu_time=None, wall_time=None, throughput=None, extras=None,
    name=None, metrics=None
)

Report a benchmark.

Args
`iters`	(optional) How many iterations were run
`cpu_time`	(optional) Median or mean cpu time in seconds.
`wall_time`	(optional) Median or mean wall time in seconds.
`throughput`	(optional) Throughput (in MB/s)
`extras`	(optional) Dict mapping string keys to additional benchmark info. Values may be either floats or values that are convertible to strings.
`name`	(optional) Override the BenchmarkEntry name with `name`. Otherwise it is inferred from the top-level method name.
`metrics`	(optional) A list of dict, where each dict has the keys below name (required), string, metric name value (required), double, metric value min_value (optional), double, minimum acceptable metric value max_value (optional), double, maximum acceptable metric value

`run_op_benchmark`

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run_op_benchmark(
    sess, op_or_tensor, feed_dict=None, burn_iters=2, min_iters=10,
    store_trace=False, store_memory_usage=True, name=None, extras=None, mbs=0
)

Run an op or tensor in the given session. Report the results.

Args
`sess`	`Session` object to use for timing.
`op_or_tensor`	`Operation` or `Tensor` to benchmark.
`feed_dict`	A `dict` of values to feed for each op iteration (see the `feed_dict` parameter of `Session.run`).
`burn_iters`	Number of burn-in iterations to run.
`min_iters`	Minimum number of iterations to use for timing.
`store_trace`	Boolean, whether to run an extra untimed iteration and store the trace of iteration in returned extras. The trace will be stored as a string in Google Chrome trace format in the extras field "full_trace_chrome_format". Note that trace will not be stored in test_log_pb2.TestResults proto.
`store_memory_usage`	Boolean, whether to run an extra untimed iteration, calculate memory usage, and store that in extras fields.
`name`	(optional) Override the BenchmarkEntry name with `name`. Otherwise it is inferred from the top-level method name.
`extras`	(optional) Dict mapping string keys to additional benchmark info. Values may be either floats or values that are convertible to strings.
`mbs`	(optional) The number of megabytes moved by this op, used to calculate the ops throughput.

Returns
A `dict` containing the key-value pairs that were passed to `report_benchmark`. If `store_trace` option is used, then `full_chrome_trace_format` will be included in return dictionary even though it is not passed to `report_benchmark` with `extras`.

© 2020 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r2.4/api_docs/python/tf/test/Benchmark