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tf.data.experimental.StatsAggregator

TensorFlow 1 version View source on GitHub

Class StatsAggregator

A stateful resource that aggregates statistics from one or more iterators.

Aliases:

To record statistics, use one of the custom transformation functions defined in this module when defining your tf.data.Dataset. All statistics will be aggregated by the StatsAggregator that is associated with a particular iterator (see below). For example, to record the latency of producing each element by iterating over a dataset:

dataset = ...
dataset = dataset.apply(tf.data.experimental.latency_stats("total_bytes"))

To associate a StatsAggregator with a tf.data.Dataset object, use the following pattern:

aggregator = tf.data.experimental.StatsAggregator()
dataset = ...

# Apply `StatsOptions` to associate `dataset` with `aggregator`.
options = tf.data.Options()
options.experimental_stats.aggregator = aggregator
dataset = dataset.with_options(options)

__init__

View source

__init__()

Initialize self. See help(type(self)) for accurate signature.