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Tensorflow.js is an open-source library that is being developed by Google for running machine learning models as well as deep learning neural networks in the browser or node environment.

The .asin() function is used to find the asin of the stated tensor elementwise.

Syntax:

`tf.asin(x) `

Parameters:

• x: It is the tensor input whose asin value is to be computed, and it can be of type tf.Tensor, or TypedArray, or Array.

Return Value: It returns the tf.Tensor object.

Example 1: In this example, we are defining an input tensor of integer type and then printing the asin value of it. For creating an input tensor we are utilizing the .tensor1d() method and in order to print the output we are using the .print() method.

## Javascript

 `// Importing the tensorflow.js library``import * as tf from ``"@tensorflow/tfjs"`` ` `// Defining tensor input elements``const y = tf.tensor1d([5, 1, 8, 0]);`` ` `// Calling asin() method and``// printing output``y.asin().print();`

Output:

```Tensor
[NaN, 1.5707964, NaN, 0.0000676]```

Example 2: In this example, float type values are considered as tensor input and the parameter is passed directly to the asin function.

## Javascript

 `// Importing the tensorflow.js library ``import * as tf from ``"@tensorflow/tfjs"`` ` `// Defining float values``var` `val = [1.6, .5, .34];`` ` `// Calling tensor1d method``const y = tf.tensor1d(val);`` ` `// Calling asin() method``var` `res = tf.asin(y)`` ` `// printing output``res.print();`

Output:

```Tensor
[NaN, 0.523645, 0.346944]```
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