tf.test.Benchmark

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Abstract class that provides helpers for TensorFlow benchmarks.

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.