The Graph Mode Post Training Quantization in Pytorch is awesome because it doesn’t need the model to be defined in certain way only using Modules. (https://pytorch.org/tutorials/prototype/graph_mode_static_quantization_tutorial.html)
Wondering if there is a plan for Graph Mode Quantization Aware Training as well in Pytorch?
Yes. It’s very much work in progress and the code is at https://github.com/pytorch/pytorch/tree/master/torch/quantization/fx Tutorials and docs will be released once it’s ready.
What would be the rough timeline for graph mode QAT to be available - will it be included in PyTorch 1.7 release?
Also wondering what would be the difference between quantize_jit and quantize_fx
It’s not a part of 1.7. quantize_jit is the current api that you used for graph-mode post-training quantization and it will be deprecated once quantize_fx is available (i.e., new graph mode).