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# Tensorflow.js tf.linalg.gramSchmidt() Function

• Last Updated : 02 Jun, 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.linalg.gramSchmidt() function is used to orthogonalize the vectors using the Gram-Schimdt process.

Syntax:

`tf.linalg.gramSchmidt( xs ) `

Parameters:

• xs ( a tf.Tensor1D array or tf.Tensor2D): These are the vectors that are to be orthogonalized.

Return Value: It returns a tf.Tensor1D array or tf.Tensor2D.

Example 1:

## Javascript

 `const tf = require(``"@tensorflow/tfjs"``)`` ` `// Creating a 2-D tensor``const input = tf.tensor2d([``    ``[3, 7], ``    ``[4, 6]``]);`` ` `// Getting the orthogonalized vector``let result = tf.linalg.gramSchmidt(input);`` ` `result.print();`

Output:

```Tensor
[[0.3939193, 0.919145  ],
[0.919145 , -0.3939194]]```

Example 2:

## Javascript

 `const tf = require(``"@tensorflow/tfjs"``)`` ` `// Creating a 2-D tensor``const input = tf.tensor2d([``    ``[5, 7, 2], ``    ``[7, 6, 9],``    ``[1, 2, 3]``]);`` ` `// Getting the orthogonalized vector``let result = tf.linalg.gramSchmidt(input);`` ` `result.print();`

Output:

```Tensor
[[0.5661386, 0.792594  , 0.2264554],
[0.1283516, -0.3561312, 0.925579 ],
[-0.814256, 0.4949402 , 0.3033505]]```
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