
Although work is ongoing to integrate oneDNN Graph with TorchDynamo as well, its integration with the PyTorch JIT Fuser attained beta status in PyTorch 2.0 for Float32 & BFloat16 inference (on machines that support AVX512_BF16 ISA).

From a developer’s/researcher’s perspective, the usage is quite simple & intuitive, with the only change in code being an API invocation:
* Leverage oneDNN Graph, with JIT-tracing, a model is profiled with an example input. 
* The context manager with torch.jit.fuser(“fuser3”): can also be used instead of invoking torch.jit.enable_onednn_fusion(True).