Does it mean that we can convert to onnx scripted parts of network (using  torch.jit.script ) ?

I haven’t tried torch.jit.script for quantized pytorch network to onnx to Caffe2. But torch.jit.trace should work.

What if our network contains of operators that aren’t available in TorchScript but available in Caffe2 (e.g. RoIAlign)?

At this point this is only limited to operators present in both quantized Pytorch and quantized Caffe2 framework.

Optionally is it possible to use quantized layers with TorchScript backend on mobile (I mean without additional conversion to Caffe2 using ONNX)?

You can directly run quantized pytorch network on mobile using PyTorch Mobile which is highly recommended over converting to Caffe2. Check out https://pytorch.org/mobile/home/ 25.