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.logicalXor() function is used to return a tensor of Boolean values for the result of element-wise XOR operation on the two specified tensors of Boolean values.
Syntax:
tf.logicalXor(a, b)
Parameters: This function accepts two parameters which are illustrated below:
- a: The first input tensor. It should have a Boolean datatype.
- b: The second input tensor. It should have a Boolean datatype.
Return Value: It returns a tensor of Boolean values for the result of element-wise XOR operation on the two specified tensors of Boolean values.
Example 1:
Javascript
// Importing the tensorflow.js library import * as tf from "@tensorflow/tfjs" // Initializing some tensors of boolean values const a = tf.tensor1d([false, true], 'bool'); const b = tf.tensor1d([true, false], 'bool'); // Calling the .logicalXor() function a.logicalXor(b).print(); |
Output:
Tensor [true, true]
Example 2:
Javascript
// Importing the tensorflow.js library import * as tf from "@tensorflow/tfjs" // Using tensors of boolean values as // the parameters of .logicalXor() function tf.tensor1d([false, true, false, true], 'bool').logicalXor( tf.tensor1d([false, true, true, false], 'bool')).print(); |
Output:
Tensor [false, false, true, true]
Reference: https://js.tensorflow.org/api/latest/#logicalXor
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