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

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  • Last Updated : 22 Apr, 2022

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


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