The tf.mul() function returns the multiplication of two tf.Tensor objects element wise. The tf.Tensor object represents the multidimensional array of numbers.
Syntax:
tf.mul( a, b )
Parameters:
- a: It contains the first tf.Tensor object that multiplied by second tf.Tensor object element-wise. The value of this parameter can be tf.TensorTypedArray|Array.
- b: It contains the second tf.Tensor object that multiplied by first tf.Tensor object. The value of this parameter can be (tf.Tensor|TypedArray|Array). The type of this parameter is same as type of a.
Return Value: This function returns the tf.Tensor object.
Example 1:
// Importing the tensorflow.js library
import * as tf from "@tensorflow/tfjs"
// Declare the Tensor array
const arr1 = tf.tensor1d([10, 20, 30, 40, 50]);
const arr2 = tf.tensor1d([5, 10, 15, 20, 25]);
// Use mul() function to multiply
// two Tensor objects
arr1.mul(arr2).print();
Output:
Tensor
[50, 200, 450, 800, 1250]
Example 2:
// Importing the tensorflow.js library
import * as tf from "@tensorflow/tfjs"
// Declare the Tensor array
const arr1 = tf.tensor1d([30, 40, 50]);
const arr2 = tf.tensor1d([5, 10, 15, 20, 25]);
// Use mul() function to multiply
// two Tensor objects
arr1.mul(arr2).print();
Output:
An error occurred on line: 7 Operands could not be broadcast together with shapes 3 and 5.
Example 3:
// Importing the tensorflow.js library
import * as tf from "@tensorflow/tfjs"
// Declare the Tensor array
const arr = tf.tensor1d([5, 10, 15, 20, 25]);
// Declare a number
const num = tf.scalar(30);
// Use mul() function to multiply
// Tensor object and a number
arr.mul(num).print();
