Beginner's GAN on FMNIST Produces Only Pants: Seeking Guidance

This Reddit post highlights a common challenge faced by beginners in GAN development: mode collapse. The user's GAN, trained on FMNIST, is only generating pants after several epochs, indicating a failure to capture the diversity of the dataset. The user's question about using one-hot encoded inputs is relevant, as it could potentially help the generator produce more varied outputs. However, other factors like network architecture, loss functions, and hyperparameter tuning also play crucial roles in GAN training and stability. The post underscores the difficulty of training GANs and the need for careful experimentation and debugging.

• •Mode collapse is a common problem in GAN training.
• •One-hot encoding might help diversify generator outputs.
• •GAN training requires careful tuning of various parameters.