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
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