How would you implement federated learning for training GANs across distributed devices

Question

With the help of code, can I know How you would implement federated learning for training GANs across distributed devices?

Answer 1

You can implement federated learning for training GANs across distributed devices.

Here is an example of implementing federated learning for GANs:

In the above code we are using the following key points:

• Local Training: Each device trains the GAN locally on its own data (via train_on_client).
• Global Model Aggregation: After each local training, model updates (weights) are aggregated by averaging using aggregate_updates.
• Federated Iterations: The process repeats across multiple clients, improving the global model without sharing raw data.

Hence, this enables GAN training across distributed devices, maintaining data privacy.