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 .isNaN() function is used to find the NaN elements of the stated tensor input.
Syntax:
tf.isNaN(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 NaN elements and false for other than NaN ones.
Example 1: In this example, we are defining an input tensor and then printing true for the NaN values and false for the other 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([Infinity, .5, 4, -38.8, NaN]); // Calling isNaN() method and // printing output y.isNaN().print(); |
Output:
Tensor
[false, false, false, false, true]
Example 2: In this example, the parameter is passed directly to the isNaN function.
Javascript
// Importing the tensorflow.js library import * as tf from "@tensorflow/tfjs" // Defining tensor input var val = [NaN, -Infinity, 5.78799797, 'a']; // Calling tensor1d method const y = tf.tensor1d(val); // Calling isNaN() method var res = tf.isNaN(y) // printing output res.print(); |
Output:
Tensor
[true, false, false, true]
Reference: https://js.tensorflow.org/api/latest/#isNaN
