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Tensorflow.js tf.isInf() Function

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  • Last Updated : 12 May, 2021
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Tensorflow.js is an open-source library which is being developed by Google for running machine learning models as well as deep learning neural networks in the browser or node environment.

The .isInf() function is used to find the Infinity or -Infinity elements of the stated tensor input.

Syntax:  

tf.isInf(x)

Parameters:  

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

Return Value: It returns the tf.Tensor object. However, it returns true for infinite elements and false for finite ones.

Example 1: In this example, we are defining an input tensor and then printing true for the infinite values and false for the finite ones. 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([3, .5, -38.8, NaN]);
  
// Calling isInf() method and
// printing output
y.isInf().print();


Output:

Tensor
    [false, false, false, false]

Example 2: In this example, the parameter is passed directly to the isInf function.

Javascript




// Importing the tensorflow.js library 
import * as tf from "@tensorflow/tfjs"
  
// Defining tensor input
var val = [Infinity, -Infinity, 5.78799797];
  
// Calling tensor1d method
const y = tf.tensor1d(val);
  
// Calling isInf() method
var res = tf.isInf(y)
  
// printing output
res.print();


Output:

Tensor
    [true, true, false]

Reference: https://js.tensorflow.org/api/latest/#isInf

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