How do I resolve NaN loss values when training a generative model in Julia with Flux

Question

Can you tell me how I resolve NaN loss values when training a generative model in Julia with Flux?

Answer 1

To resolve NaN loss values when training a generative model in Julia with Flux, check for issues like learning rate, gradient explosion, and data normalization. Use gradient clipping or reduce the learning rate if necessary.

Here is the code snippet you can refer to:

In the above code, we are using the following:

• Reduce Learning Rate: A high learning rate can cause NaN values due to unstable training.
• Gradient Clipping: Prevent gradients from exploding during backpropagation by clipping them using the clamp.
• Check Data: Ensure input data is normalized and does not contain extreme values.

Hence, by referring to the above, you can resolve NaN loss values when training a generative model in Julia with Flux