How can you use TensorFlow Keras to create a basic convolutional generator for a GAN

Question

With the help of TensorFlow/Keras, can you create a basic convolutional generator for a GAN?

Answer 1

You can use TensorFlow Keras to create a basic convolutional generator for a GAN by referring below:

In the above code we are using Input in which a latent vector (latent_dim, e.g., 100) representing random noise, Dense Layer which  maps noise to an initial low-resolution feature map, Conv2DTranspose which upscales the feature map while applying learned filters and Output which generates an image (e.g., 64x64x3) with pixel values in [-1, 1] for use in GAN training.

Hence by referring to above you can use TensorFlow Keras to create a basic convolutional generator for a GAN.