pytorch

4a2d2e5e - Change API type `Tensor[]` for structured kernels. (#73350)

Change API type `Tensor[]` for structured kernels. (#73350) Partially fixes: #66328 This PR: - adds support for `ITensorList` to the dispatcher for: - computing the dispatch key - boxing and unboxing `ITensorList` - modified the codegen for structured kernels: - codegen APIs use `ITensorList` instead of `ArrayRef<Tensor>` **Changes summary:** - Signature changes due to the different APIs: - dispatcher API (e.g. `BatchingRegistrations.cpp`) - C++ API (e.g. `TensorShape.cpp`) - Miscelaneous functions used by codegen'd functions (e.g. `FunctionalTensorWrapper.*`) - Dispatcher changes for handling `ITensorList` correctly (e.g. `DispatchKeyExtractor.h`) - Signature changes of `at::cat` due to the need of `const` inside `TensorBody.h` - Forward declarations of `ITensorList` (e.g. `MethodOperators.h`) - Codegen changes, special casing structured kernels (e.g. `gen.py`) **Short description of structured kernels special casing:** I introduced, mainly, 5 types of changes to the codegen for generating code depending on whether the kernel is structured or not: 1. Added a `structured_type_override` flag to the `argument_type` function definition of the affected APIs (mainly the dispatcher and C++ APIs). - `api/cpp.py`, `api/dispatcher.py`, `api/native.py` 2. Added a `structured_type_override` member to the signature classes (e.g. `CppSignature`), since `FunctionSchema` doesn't really know whether the function is structured or not - `api/types.py` 3. Added a `part_of_structured_group` to `NativeFunction` class, which is just a convenient function to forward to `structured_type_override` wherever needed - `model.py` 4. Appropriately changed the rest of the codegen, whenever it used either the signature classes or the `arguments` function directly 5. Added a check for `const ITensorList&` type wherever there was a check for `TensorList` Pull Request resolved: https://github.com/pytorch/pytorch/pull/73350 Approved by: https://github.com/bdhirsh