Building CNN (Convolutional Neural Network) with Tensorflow.JS

buildCnn

const buildCnn = function (data) {
    return new Promise(function (resolve, reject) {

        // Linear (sequential) stack of layers
        const model = tf.sequential();

        // Define input layer
        model.add(tf.layers.inputLayer({
            inputShape: [7, 1],
        }));

        // Add the first convolutional layer
        model.add(tf.layers.conv1d({
            kernelSize: 2,
            filters: 128,
            strides: 1,
            use_bias: true,
            activation: 'relu',
            kernelInitializer: 'VarianceScaling'
        }));

        // Add the Average Pooling layer
        model.add(tf.layers.averagePooling1d({
            poolSize: [2],
            strides: [1]
        }));

        // Add the second convolutional layer
        model.add(tf.layers.conv1d({
            kernelSize: 2,
            filters: 64,
            strides: 1,
            use_bias: true,
            activation: 'relu',
            kernelInitializer: 'VarianceScaling'
        }));

        // Add the Average Pooling layer
        model.add(tf.layers.averagePooling1d({
            poolSize: [2],
            strides: [1]
        }));

        // Add Flatten layer, reshape input to (number of samples, number of features)
        model.add(tf.layers.flatten({

        }));

        // Add Dense layer, 
        model.add(tf.layers.dense({
            units: 1,
            kernelInitializer: 'VarianceScaling',
            activation: 'linear'
        }));

        return resolve({
            'model': model,
            'data': data
        });
    });
}
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