How to address the issue of gradient vanishing and exploding in PyTorch?

1. Vanishing gradient problem:

1. Utilize non-linear activation functions such as ReLU, Leaky ReLU, etc.
2. Normalize the input of the network using Batch Normalization.
3. Use a smaller learning rate.
4. Limiting the size of gradients using gradient clipping.

1. Gradient explosion issue:

1. Limit the size of the gradient by using gradient clipping.
2. Utilizing weight regularization, such as L1 regularization or L2 regularization.
3. Use a smaller learning rate.
4. You can use Xavier initialization or He initialization when starting the weights.

The above methods can effectively alleviate the issues of gradient vanishing and exploding, improving the stability and effectiveness of training.