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.grad() function is used to return the gradient of the specified function f(x) with respect to x.
Syntax:
tf.grad (f)
Parameters: This function accepts a parameter which is illustrated below:
- f: The specified function f(x) for which gradient is being calculated.
Return Value: It returns the gradient of the specified function f(x) with respect to x.
Example 1:
Javascript
// Importing the tensorflow.js library import * as tf from "@tensorflow/tfjs" // Initializing a function f(x) = x^2 const f = x => x.square(); // Calling the .grad() function which // calculates f'(x) and gives value as 2x const g = tf.grad(f); // Initializing a tensor of values for // which gradient will be returned const x = tf.tensor1d([1, 2, 3]); // Getting the values of gradient of the // function f(x) for the above specified // tensor g(x).print(); |
Output:
Tensor [2, 4, 6]
Example 2:
Javascript
// Importing the tensorflow.js library import * as tf from "@tensorflow/tfjs" // Using the function f(x) = x^3 as the // parameter for the .grad() function which // calculates f'(x) and gives value as 3x^2 const g = tf.grad(x => x.pow(tf.scalar(3, 'int32'))); // Initializing a tensor of values for // which gradient will be returned const x = tf.tensor1d([0, 1, 2]); // Getting the values of gradient of the // function f(x) for the above specified // tensor g(x).print(); |
Output:
Tensor [0, 3, 12]
Reference: https://js.tensorflow.org/api/latest/#grad
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