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.squaredDifference() function is used to return (a – b) * (a – b) element-wise, where “a” is the first specified tensor and “b” is the second tensor. It Supports broadcasting.
Syntax:
tf.squaredDifference(a, b)
Parameters: This function accepts two parameters which are illustrated below:
- a: The first specified tensor.
- b: The second specified tensor. It must have same data type as “a”.
Return Value: It returns (a – b) * (a – b) element-wise, where “a” is the first specified 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([1, 3, 5, 7]); const b = tf.tensor1d([1, 2, 9, 4]); // Calling the .squaredDifference() function // over the above tensor as its parameters a.squaredDifference(b).print(); |
Output:
Tensor [0, 1, 16, 9]
Example 2:
Javascript
// Importing the tensorflow.js library import * as tf from "@tensorflow/tfjs" // Broadcasting squared difference a with b. const a = tf.tensor1d([1, 3, 6, 7]); const b = tf.scalar(4); // Calling the .squaredDifference() function a.squaredDifference(b).print(); |
Output:
Tensor [9, 1, 4, 9]
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