# Tensorflow.js tf.squaredDifference() Function

• Last Updated : 12 May, 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.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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