How can I implement quantization in PyTorch?

How can I implement quantization in PyTorch?

To implement quantization in PyTorch, you can use the torch.quantization module. Start by preparing your model for quantization.

What are the steps to prepare my model for quantization?

First, you need to fuse layers if applicable, then specify the quantization configuration, and finally, calibrate the model with representative data.

Can you explain what layer fusion means?

Layer fusion combines multiple layers into a single layer to improve performance and reduce the model size, which is beneficial for quantization.

What types of quantization does PyTorch support?

PyTorch supports post-training quantization, quantization-aware training, and dynamic quantization, each suitable for different scenarios.