Improved speed of frobenous norm for non-complex dtype (#30871)
Summary:
In-tree changes to pytorch to support complex numbers are being submitted here.
Out-of-tree support for CUDA complex numbers is here: [pytorch-cuda-strided-complex extension](https://gitlab.com/pytorch-complex/pytorch-cuda-strided-complex)
Changes:
[x] Fixed performance issue raise in https://github.com/pytorch/pytorch/issues/30704 so that non-complex numbers do not call `conj()` and `real()`.
[x] Fixed tensor_to_numpy() conversion likely broken by a `checkBackend()` in https://github.com/pytorch/pytorch/issues/27064.
[x] Fixed some ReduceOps and TensorCompare Ops that recently added a `checkBackend()`.
- `checkBackend()` is replaced with a device type check and a layout check.
- This ensures the ComplexCPU Type ID is supported.
[x] Added AVX support for complex `exp()`, as requested in https://github.com/pytorch/pytorch/issues/755
Pull Request resolved: https://github.com/pytorch/pytorch/pull/30871
Differential Revision: D19200726
Pulled By: ezyang
fbshipit-source-id: d7e1be0b0a89c5d6e5f4a68ce5fcd2adc5b88277
