Tensorflow.js is an open-source library for creating machine learning models in Javascript that allows users to run the models directly in the browser.
The tf.fill() is a function defined in the class tf.Tensor. It is used to create a tensor that is filled with a scalar value.
Syntax:
tf.fill( shape, value, dtype )
Parameters:
- shape: It’s an array of integers defining the shape of the output tensor.
- value: It’s a scalar value with which the output tensor is to be filled.
- dtype: It defines the data type of elements in the output tensor. It can be ‘float32’|’int32’|’bool’|’complex64’|’string’. It’s optional to include and default value is ‘float32’.
Return value: It returns the tensor of a specified shape filled with a scalar value.
Example 1: Filling the tensor with a scalar number
- Creating a tensor of shape [4, 2] filled with scalar value 2.
- It takes the default datatype of elements in the output tensor as float.
Javascript
// Dynamic loading the "@tensorflow/tfjs" module const tf = require('@tensorflow/tfjs'); require('@tensorflow/tfjs-node'); // Creating a tensor of of shape [4,2] filled with // scalar value 2 var matrix = tf.fill(shape = [4,2],value = 2) // Printing the tensor matrix.print() |
Output:
Tensor
[[2, 2],
[2, 2],
[2, 2],
[2, 2]]
Example 2: Explicitly defining the data type of elements
- Create a tensor of shape [3, 4] filled with string ‘Gfg’.
Javascript
// Dynamic loading the "@tensorflow/tfjs" module const tf = require('@tensorflow/tfjs'); require('@tensorflow/tfjs-node'); // Creating a tensor of shape [3,4] filled // with string value 'Gfg' var matrix = tf.fill(shape = [3, 4], value = 'Gfg', dtype = 'string') // Printing the tensor matrix.print() |
Output:
Tensor
[['Gfg', 'Gfg', 'Gfg', 'Gfg'],
['Gfg', 'Gfg', 'Gfg', 'Gfg'],
['Gfg', 'Gfg', 'Gfg', 'Gfg']]
Reference: https://js.tensorflow.org/api/latest/#fill
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