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. It also helps the developers to develop ML models in JavaScript language and can use ML directly in the browser or in Node.js.
The tf.initializers.heUniform() function draws samples from a uniform distribution within [-cap, cap] where cap is sqrt(6 / fan_in). Note that the fanIn is the number of inputs in the tensor weight.
Syntax:
tf.initializers.heUniform(arguments)
Parameters:
- arguments: It is an object that contains seed (a number) which is the random number generator seed/number.
Returns value: It returns tf.initializers.Initializer
Example 1:
Javascript
// Importing the tensorflow.js libraryimport * as tf from "@tensorflow/tfjs"// Initializing the .initializers.heUniform() functionconst geek = tf.initializers.heUniform(7)// Printing gainconsole.log(geek);console.log('\nIndividual values:\n');console.log(geek.scale);console.log(geek.mode);console.log(geek.distribution); |
Output:
{
"scale": 2,
"mode": "fanIn",
"distribution": "uniform"
}
Individual values:
2
fanIn
uniform
Example 2:
Javascript
// Importing the tensorflow.Js libraryimport * as tf from "@tensorflow/tfjs// Defining the input valueconst inputValue = tf.input({shape:[4]});// Initializing tf.initializers.heUniform() functionconst funcValue = tf.initializers.heUniform(4)// Creating dense layer 1const dense_layer_1 = tf.layers.dense({ units: 6, activation: 'relu', kernelInitialize: funcValue});// Creating dense layer 2const dense_layer_2 = tf.layers.dense({ units: 8, activation: 'softmax'});// Output const outputValue = dense_layer_2.apply( dense_layer_1.apply(inputValue));// Creation the model.const model = tf.model({ inputs: inputValue, outputs: outputValue});// Predicting the output.model.predict(tf.ones([2, 4])).print(); |
Output:
Tensor
[[0.2727611, 0.1405532, 0.0409708, 0.1262356,
0.1215546, 0.134949, 0.0845761, 0.0783997],
[0.2727611, 0.1405532, 0.0409708, 0.1262356,
0.1215546, 0.134949, 0.0845761, 0.0783997]]
Reference: https://js.tensorflow.org/api/latest/#initializers.heUniform
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