Tensorflow.js tf.div() Function

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.div() function is used to divides the two specified Tensors element-wise. It supports broadcasting.

Syntax:

tf.div (a, b)

Parameters: This function accepts two parameters which are illustrated below:

• a: The first input tensor as the numerator.
• b: The second input tensor as the denominator. It should must have the same data type as “a”.

Return Value: It returns a Tensor for the result of a/b, where a is the first Tensor and b is the second Tensor.

Example 1:

Javascript

// Importing the tensorflow.js library
import * as tf from "@tensorflow/tfjs"

// Initializing two Tensors
const a = tf.tensor1d([3, 5, 10, 15]);
const b = tf.tensor1d([2, 5, 2, 7]);

// Calling the .div() function over the
// above Tensors as its parameters
a.div(b).print();

Output:

Tensor
   [1.5, 1, 5, 2.1428571]

Example 2:

Javascript

// Importing the tensorflow.js library
import * as tf from "@tensorflow/tfjs"

// Broadcasting the div a with b
const a = tf.tensor1d([1, 12, 17, 20]);
const b = tf.scalar(3);

// Calling the .div() function over the
// above Tensors as its parameters
a.div(b).print();

Output:

Tensor
   [0.3333333, 3.9999998, 5.6666665, 6.666666]

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