How can I avoid exploding gradients in large-scale generative models

Question

With the help of good coding examples and snippets, can you tell me how I can avoid exploding gradients in large-scale generative models?

Answer 1

To avoid exploding gradients in large-scale generative models, you can use gradient clipping, lower the learning rate, or apply batch normalization.

Here is the code snippet you can refer to:

In the code, we are using the following:

• Gradient Clipping: Flux.clamp! ensures gradients are within a specified range to prevent them from exploding.
• Lower Learning Rate: A smaller learning rate helps prevent large gradient updates that can lead to instability.
• Batch Normalization: (Optional) Can also be added to stabilize activations across layers and prevent gradient explosion.

Hence, by referring to the above, you can avoid exploding gradients in large-scale generative models.