pytorch

779cae9e - port at::pow to structured (#53669)

port at::pow to structured (#53669) Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/53669 This PR does two things: * Ports `pow` to be structured * Fixes a bug with how pow handles mixed cpu and cuda tensors **bug fix** Pow is a binary op, and all binary ops that use TensorIterator are currently written to handle the case when one of the inputs is a CUDA tensor, and the other is a zero-dimensional cpu tensor. `pow` incidentally only handles one of the two cases: it fails when the CUDA tensor is passed as the exponent, e.g. `at::pow(torch.tensor(2.0, device='cpu'), torch.tensor([2, 2], device='cuda'))`. Porting `pow` to structured happened to change the error that was outputted from a `TORCH_CHECK` in TensorIterator to an `INTERNAL_ASSERT` in loop.cuh, so I ended up trying to fix the error and update the tests. I added more details in a comment on the PR. **notes on the structured port** Pow is a little weird, so I wrote down a couple of issues I noticed during the port: * Multiple independent overloads. `pow` has two overloads that have their own cpu/cuda kernels, meaning one doesn't call the other. I have to update the names of the kernel overloads to make the compiler happy, since the codegen would otherwise try to generate two classes with the same name. `pow` actually has 3 overloads that all have `out` variants, so I ported all 3 to structured- one of them just happens to redispatch one of the others in most cases. * Name propagation. Is name propagation implemented per operator? Or is expected to work for most/all ops by default. Right now it looks like it happens for TensorIterator ops by default. For ops that don't use TensorIterator, we need to explicitly pass the names through to the `set_output()` call in the meta function. This happened to matter for `pow` because it has 3 overloads, but only two of them directly use TensorIterator. I had to pass names directly to `set_output` in the 3rd overload to make tests happy. * Lack of `const Tensor &` in the C++ API. It's a goal to slowly make all `Tensor &` arguments const as part of the structured port, but in this case I needed to explicitly cast constness away because one structured kernel called back into the C++ API, which still has ordinary `Tensor &` arguments. This probably isn't something we'll fix soon, since we have boxing logic that actually relies on the `Tensor &` / `const Tensor &` distinction in some places. Test Plan: Imported from OSS Reviewed By: ezyang Differential Revision: D27029821 Pulled By: bdhirsh fbshipit-source-id: c1786e770de6e6c2474b9a48210b88057ab1018e