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. range() is used to create a new tf.Tensor1D filled with the numbers in the range provided with the help of start, stop, step, and dtype.
Syntax:
tf.range(start, stop, step, dtype)
Parameters:
- start: It is an integer start value that denotes the starting number of the range.
- stop: It is an integer stop value that denotes the ending number of the range, and it is not included.
- step: It is an integer increment which is 1 or -1 by default. It is an optional parameter.
- dtype: It is the data type of the output tensor. It defaults to ‘float32’. It is an optional parameter.
Return Value: It returns a new Tensor1D object.
Example 1: In this example, we try to generate a range of numbers from 1 to 9 with default step 1.
Javascript
// Importing the tensorflow.js library import * as tf from "@tensorflow/tfjs" // Creating the tensor1D array by tf.range var val = tf.range(1,10); // Printing the tensor val.print() |
Output:
Tensor
[1, 2, 3, 4, 5, 6, 7, 8, 9]
Example 2: In this example, we try to generate odd numbers between 1 and 10 using step size 2.
Javascript
// Importing the tensorflow.js library import * as tf from "@tensorflow/tfjs" // Creating the tensor1D array by tf.range var val = tf.range(1,10,2); // Printing the tensor val.print() |
Output:
Tensor
[1, 3, 5, 7, 9]
Example 3: In this example, we try to generate even numbers between 0 and 10 using step size 2.
Javascript
// Importing the tensorflow.js library import * as tf from "@tensorflow/tfjs" // Creating the tensor1D array by tf.range var val = tf.range(0,10,2); // Printing the tensor val.print() |
Output:
Tensor
[0, 2, 4, 6, 8],
Example 4: In this example, we will try to use the dtype parameter.
Javascript
// Importing the tensorflow.js library import * as tf from "@tensorflow/tfjs" // Creating the tensor1D array by tf.range var val = tf.range(-1,1,1,'bool'); // Printing the tensor val.print() |
Output:
Tensor
[true, false]
Reference:https://js.tensorflow.org/api/latest/#range
