quantized_model = convert_fx(prepared_model)
```
Find more information: https://github.com/pytorch/pytorch/issues/83888 and https://www.intel.com/content/www/us/en/developer/articles/technical/accelerate-pytorch-int8-inf-with-new-x86-backend.html.
[Beta] GNN inference and training optimization on CPU
PyTorch 2.0 includes several critical optimizations to improve GNN inference and training performance on CPU. Before 2.0, GNN models of PyG suffers from low efficiency on CPU due to lack of performance tuning for several critical kernels (scatter/gather, etc) and the lack of GNN-related sparse matrix multiplication ops. To be specific, optimizations include:
* scatter_reduce: performance hotspot in Message Passing when the edge index is stored in Coordinate format (COO).