Support int32 indices and offsets in nn.EmbeddingBag (#46758)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/46758
It's in general helpful to support int32 indices and offsets, especially when such tensors are large and need to be transferred to accelerator backends. Since it may not be very useful to support the combination of int32 indices and int64 offsets, here we enforce that these two must have the same type.
Test Plan: unit tests
Reviewed By: ngimel
Differential Revision: D24470808
fbshipit-source-id: 94b8a1d0b7fc9fe3d128247aa042c04d7c227f0b
