First of all, I would like to thank you for the awesome  torch.quantization . But at the moment, the quantization of embeddings is not supported, although ususally it’s one of the biggest (in terms of size) parts of the model (in NLP).
I tried to use  nn.Embeddings  as  nn.Linear  because they have a very similar nature, but get the following error:
RuntimeError: Could not run 'aten::index_select' with arguments from the 'QuantizedCPUTensorId' backend. 'aten::index_select' is only available for these backends: [CPUTensorId, CUDATensorId, SparseCPUTensorId, SparseCUDATensorId, VariableTensorId].

So I’m interested whether it’s planned to support  nn.Embeddings  quantization?