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. It also helps the developers to develop ML models in JavaScript language and can use ML directly in the browser or in Node.js.
The tf.grads() function takes a function f(x) and return a function gx
Syntax:
tf.grads (f)
Parameters:
- f: This is the given function for which gradients are calculated.
Return Value: It returns an array.
Example 1:
Javascript
// Importing the @tensorflow/tjs library const tf=require("@tensorflow/tfjs") const f = (a, b) => b.add(a); // Grad function is used const g = tf.grads(f); // Tensor is declared const a = tf.tensor1d([5, 6]); const b = tf.tensor1d([-10, -20]); // Variables are defined const [gfg1] = g([b, a]); // Variable is printed gfg1.print(); |
Output:
Tensor
[1, 1]
Example 2:
Javascript
// Importing the @tensorflow/tfjs library const tf=require("@tensorflow/tfjs") const f = (a) => a.mul(8); // Grad function is used const g = tf.grads(f); // Tensor is declared const a = tf.tensor1d([50, 60]); // Variables are defined const [gfg1] = g([a]); // Variable is printed gfg1.print(); |
Output:
Tensor
[8, 8]
Reference: https://js.tensorflow.org/api/latest/#grads
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