Neural Network Programming with TensorFlow

Basic autoencoders

Let's look at a basic example of an autoencoder that also happens to be a basic autoencoder. First, we will create an AutoEncoder class and initialize it with the following parameters passed to __init__():

• num_input: Number of input samples
• num_hidden: Number of neurons in the hidden layer
• transfer_function=tf.nn.softplus: Transfer function
• optimizer = tf.train.AdamOptimizer(): Optimizer

You can either pass a custom transfer_function and optimizer or use the default one specified. In our example, we are using softplus as the default transfer_function (also called activation function): f(x)=ln(1+e^x).