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Tensorflow.js tf.data.Dataset class .shuffle() Method

  • Last Updated : 01 Jul, 2021

Tensorflow.js is an open-source library developed by Google for running machine learning models and deep learning neural networks in the browser or node environment.

The tf.data.Dataset.shuffle() method randomly shuffles a tensor along its first dimension.

Syntax:

tf.data.Dataset.shuffle(
    buffer_size, seed=None, 
    reshuffle_each_iteration=None
)

Parameters:

  • buffer_size: This is the number of elements from which the new dataset will be sampled.
  • seed[optional]: It is an optional parameter used to create a random seed for the distribution, to see the same results use same seed.
  • reshuffle_each_iteration: A Boolean, which is true indicates that the dataset should be pseudo randomly reshuffled each time it is iterated over. Default value is true. It is Optional parameter.

Return Value: A tensor with same shape and data type as value, but shuffled along its first dimension.



Example 1: In this example first we will create a tensor and then shuffle it, In this example reshuffle_each_iteration is True

Javascript




async function shuffle() {
 
    // Creating a Tensor
    const a = tf.data.array([1, 2, 3, 4, 5, 6]).shuffle(3);
    await a.forEachAsync(e => console.log(e)); //print 1
    await a.forEachAsync(e => console.log(e)); //print 2
}
 
shuffle();

Output:

3 4 1 2 5 6
3 4 2 5 6 1

Example 2: In this example, seed is set to an Integer, whenever a specific integer is used it will generate that specific output

Javascript




async function shuffleseed() {
    const a = tf.data.array([1, 2, 3]).shuffle(3, seed = 42);
    await a.forEachAsync(e => console.log(e));
 
    const b = tf.data.array([1, 2, 3]).shuffle(3, seed = 42);
    await b.forEachAsync(e => console.log(e));
}
 
shuffleseed();

Output:

2 1 3
2 1 3

Reference: https://js.tensorflow.org/api/3.6.0/#tf.data.Dataset.shuffle

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