What is the use of tf data Options function

This recipe explains what is the use of tf data Options function

Recipe Objective

What is the use of tf.data.Options() function?

This function in tensorflow will represent the options for "tf.data.Dataset". The function "tf.data.options()" can be used for controlling the static optimizations to apply to input pipeline graph or we can say whether to use performance modeling to dynamically tune the parallelism of the operations for example, "tf.data.Dataset.map" or "tf.data.Dataset.interleave". The options which are set for entire dataset and are carried over to datasets created through "tf.data" transformations. The object which are returned by "tf.data.Dataset.options()" or by constructing an option object and using the "tf.data.Dataset.with_options(options)" transformation the options can be set by mutating by this returned object. Where the object also returns a dataset with the options set.

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Step 1 - Import library

import tensorflow as tf

Step 2 - Perform Task

My_dataset = tf.data.Dataset.range(52) data_options = tf.data.Options() data_options.experimental_deterministic = False My_dataset = My_dataset.with_options(data_options) print(My_dataset.options().experimental_deterministic)

False

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