Generative Adversarial Networks Projects

The encoder network

The encoder network is a convolutional neural network (CNN) that encodes an image (x) to a latent vector (z) or a latent vector representation. Let's start by implementing the encoder network in the Keras framework.

Perform the following steps to implement the encoder network:

1. Start by creating an input layer:

input_layer = Input(shape=(64, 64, 3))

2. Next, add the first convolution block, which contains a 2D convolution layer with an activation function with the following configurations:
   • Filters: 32
   • Kernel size: 5
   • Strides: 2
   • Padding: same
   • Activation: LeakyReLU with alpha equal to 0.2:

# 1st Convolutional Blockenc = Conv2D(filters=32, kernel_size=5, strides=2, padding='same')(input_layer)enc = LeakyReLU(alpha=0.2