Tensorflow.js is an open-source library that is developed by Google for running machine learning models as well as deep learning neural networks in the browser or node environment.
The .build() function is used to create the weights of the layer stated. This method should be applied on every layers that hold weights. Moreover, its invoked when the apply() method is invoked in order to build the weights.
Syntax:
build(inputShape)
Parameters:
- inputShape: It is the stated shape or an array of shape that is untouched.
Return Value: It returns void.
Example 1:
Javascript
// Importing the tensorflow.js library import * as tf from "@tensorflow/tfjs"  // Creating a model const model = tf.sequential();   // Adding a layer model.add(tf.layers.dense({units: 1, inputShape: [3]}));   // Defining input const input = tf.input({shape: [6, 2, 6]});   // Calling build method with its // parameter model.layers[0].build([input.Shape]);   // Printing output console.log(JSON.stringify(input.shape)); model.layers[0].getWeights()[0].print(); |
Output:
[null,6,2,6]
Tensor
[[-0.3726568],
[0.7343086 ],
[-0.2459907]]
Here, getWeights() method is used to print the weights.
Example 2:
Javascript
// Importing the tensorflow.js library //import * as tf from "@tensorflow/tfjs"   // Creating a model const model = tf.sequential();   // Adding layers model.add(tf.layers.dense({units: 1, inputShape: [2]})); model.add(tf.layers.dense({units: 2}));     // Defining inputs const input1 = tf.input({shape: [1, 2]}); const input2 = tf.input({shape: [1.7, 2.7, 6.5]});   // Calling build method with its // parameter model.layers[0].build([input1.Shape]); model.layers[1].build([input2.Shape]);   // Printing outputs console.log(JSON.stringify(input1.shape)); console.log(JSON.stringify(input2.shape)); model.layers[0].getWeights()[0].print(); model.layers[1].getWeights()[0].print(); |
Output:
[null,1,2]
[null,1.7,2.7,6.5]
Tensor
[[0.6224715],
[1.2144204]]
Tensor
[[0.8342852, 0.4770206],]
Reference: https://js.tensorflow.org/api/latest/#tf.layers.Layer.build
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