Tensorflow.js tf.TensorBuffer Class .set() Method

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.TensorBuffer class .set() function is used to set a given value in the buffer at a specified location.

Syntax:

set (value, ...locations)

Parameters: This function accepts two parameters which are illustrated below:

• value: The specified value to set.
• locations: The specified location indices.

Return Value: It does not return any value.

Example 1:

Javascript

// Importing the tensorflow.js library
import * as tf from "@tensorflow/tfjs"

// Creating a buffer of 2*2 dimensions
const buffer = tf.buffer([2, 2]);

// Setting values at particular indices.
buffer.set(5, 0, 0);
buffer.set(10, 1, 0);

// Converting the above buffer
// back to a tensor value to print
buffer.toTensor().print();

Output:

Tensor
   [[5 , 0],
    [10, 0]]

Example 2:

Javascript

// Importing the tensorflow.js library
import * as tf from "@tensorflow/tfjs"

// Creating a buffer of 3*3 dimensions
const buffer = tf.buffer([3, 3]);

// Setting values at particular indices.
buffer.set(5, 0, 0);
buffer.set(10, 0, 1);
buffer.set(15, 1, 0);
buffer.set(20, 1, 1);
buffer.set(25, 2, 0);
buffer.set(30, 2, 1);
buffer.set(35, 2, 2);

// Converting the above buffer
// back to a tensor value to print
buffer.toTensor().print()

Output:

Tensor
   [[5 , 10, 0 ],
    [15, 20, 0 ],
    [25, 30, 35]]

Reference: https://js.tensorflow.org/api/latest/#tf.TensorBuffer.set