Tensorflow.js tf.layers.dense() Function

26 May, 2021
The tf.layers.dense() is an inbuilt function of Tensorflow.js library. This function is used to create fully connected layers, in which every output depends on every input.
Syntax:
tf.layers.dense(args)
Parameters: This function takes the args object as a parameter which can have the following properties:
units: It is a positive number that defines the dimensionality of the output space.
activation: Specifies which activation function to use.
useBias: specifies whether to apply a bias or not.
kernelInitializer: Specifies which initializer to use for the dense kernel weight matrix.
biasInitializer: Specifies the bias vector for this layer.
inputDim: Defines input shape as [inputDim].
kernelConstraint: Specifies the constraint for the kernel.
biasConstraint: Specifics constraint for the bias vector.
kernelRegularizer: Specifies the regularizer function applied to the dense kernel weights matrix.
biasRegularizer: Specifies the regularizer function applied to the bias vector.
activityRegularizer: Specifies the regularizer function applied to the activation.
inputShape: If this parameter is defined, it will create another input layer to insert before this layer.
batchInputShape: If this parameter is defined, it will create another input layer to insert before this layer.
batchSize : Used to construct batchInputShape, if not already specified.
dtype: Specifies the data type for this layer. The default value of this parameter is ‘float32’.
name: Specifies name for this layer.
trainable: Specifies whether the weights of this layer are updated by fit.
weights: Specifies the initial weight values of the layer.
inputDType : It is used to denote the inputDType and its value can be ‘float32’ or ‘int32’ or ‘bool’ or ‘complex64’ or ‘string’.
Return value: It returns a Dense object.
Example 1:
Javascript
import * as tf from "@tensorflow/tfjs"  // Create a new dense layerconst denseLayer = tf.layers.dense({   units: 2,   kernelInitializer: 'heNormal',   useBias: true});    const input = tf.ones([2, 3]);const output = denseLayer.apply(input);    // Print the outputoutput.print()
Output:
Example 2:
Javascript
import * as tf from "@tensorflow/tfjs"  // Create a new dense layerconst denseLayer = tf.layers.dense({   units: 3,   kernelInitializer: 'heNormal',   useBias: false});    const input = tf.ones([2, 3, 3]);const output = denseLayer.apply(input);    // Print the outputoutput.print()
Output:
Example 3:
Javascript
import * as tf from "@tensorflow/tfjs"    // Create a new dense layerconst denseLayer = tf.layers.dense({   units: 3,   kernelInitializer: 'ones',   useBias: false});    const input = tf.ones([2, 3, 3]);const output = denseLayer.apply(input);    // Print the outputoutput.print()
Output:
Example 4:
Javascript
import * as tf from "@tensorflow/tfjs"  // Create a new dense layerconst denseLayer = tf.layers.dense({   units: 3,   kernelInitializer: 'randomUniform',   useBias: false});    const input = tf.ones([2, 3, 3]);const output = denseLayer.apply(input);    // Print the outputoutput.print()
Output:
Reference: https://js.tensorflow.org/api/latest/#layers.dense
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Tensorflow
Tensorflow.js
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