Tensorflow.js is an open-source library developed by Google for running machine learning models as well as deep learning neural networks in the browser or node environment.
The .metrics.binaryCrossentropy() function is binary crossentropy metric function which uses binary tensors and returns tf.Tensor object.
Syntax:
tf.metrics.binaryCrossentropy (yTrue, yPred)
Parameters:
- yTrue: It is the stated binary tensor input of truth, and it can be of type tf.Tensor.
- yPred: It is the stated binary tensor input of prediction, and it can be of type tf.Tensor.
Return Value: It returns the tf.Tensor object.
Example 1:
Javascript
// Importing the tensorflow.js library import * as tf from "@tensorflow/tfjs" // Defining binary tensors const y = tf.tensor2d([[4], [5], [6], [7]]); const z = tf.tensor2d([[1], [2], [0], [1.8]]); // Calling metrics.binaryCrossentropy() // method const binry_crsntropy = tf.metrics.binaryCrossentropy(y, z); // Printing output binry_crsntropy.print(); |
Output:
Tensor
[-27.6301231, -36.8401985, 55.2615433, -55.2603455]
Example 2:
Javascript
// Importing the tensorflow.js library import * as tf from "@tensorflow/tfjs" // Calling metrics.binaryCrossentropy() // method and printing output tf.metrics.binaryCrossentropy( tf.tensor2d([[-13], [-2.787]]), ([[-0.6], [-12]])).print(); |
Output:
Tensor
[-119.7330246, -25.6688404]
Reference: https://js.tensorflow.org/api/latest/#metrics.binaryCrossentropy
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