How can you utilize model checkpoints in PyTorch to save and resume GAN training

Question

With the help of Python programming, can you tell me how you can utilize model checkpoints in PyTorch to save and resume GAN training?

Answer 1

To save and resume GAN training in PyTorch, you can use model checkpoints to store the generator, discriminator, and optimizer states. 

Here are the steps given below which you can follow:

• Saving Checkpoints
• Loading Checkpoints

In the above steps, we are using the following steps:

• Save States: Use state_dict() for models and optimizers.
• Resume Training: Load states into models and optimizers and resume from the saved epoch.
• Ensure Device Compatibility: Use .to(device) if loading models on a different device.

Hence, by referring to the above, you can utilize model checkpoints in PyTorch to save and resume GAN training.