Summary:
keys and change codegen to take ETKernelIndex
We are adding support for dtype and dim order specialized kernel registration. This requires us to reorganize `BackendIndex` (which is a `Dict[DispatchKey, Dict[OperatorName, BackendMetadata]]`) to be `Dict[OperatorName, Dict[ETKernelKey, BackendMetadata]]`. This PR adds new data structures in order to support this change:
* `ETKernelKey` to retrieve a certain kernel from the registry.
* `ETKernelIndex`, the dictionary from operator name to kernel key to kernel mapping.
Note that the codegen logic is not changed yet, we need subsequent diffs to actually generate code for different kernel keys.
Test Plan: Added tests
Reviewed By: Jack-Khuu
Differential Revision: D46407096
Pull Request resolved: https://github.com/pytorch/pytorch/pull/102874
Approved by: https://github.com/Jack-Khuu, https://github.com/kirklandsign
keys and change codegen to take ETKernelIndex
We are adding support for dtype and dim order specialized kernel registration. This requires us to reorganize `BackendIndex` (which is a `Dict[DispatchKey, Dict[OperatorName, BackendMetadata]]`) to be `Dict[OperatorName, Dict[ETKernelKey, BackendMetadata]]`. This PR adds new data structures in order to support this change:
* `ETKernelKey` to retrieve a certain kernel from the registry.
* `ETKernelIndex`, the dictionary from operator name to kernel key to kernel mapping.
Note that the codegen logic is not changed yet, we need subsequent diffs to actually generate code for different kernel keys.
Differential Revision: [D46206339](https://our.internmc.facebook.com/intern/diff/D46206339/)
Pull Request resolved: https://github.com/pytorch/pytorch/pull/102565
Approved by: https://github.com/Jack-Khuu
As titled. To register a custom op into Executorch, we need:
* `custom_ops.yaml`, defines the operator schema and the corresponding native function.
* `custom_ops.cpp`, defines the kernel.
* `RegisterDispatchKeyCustomOps.cpp`, a template to register operator into PyTorch.
Added a new test for custom ops. The custom op `custom::add_3.out` takes 3 tensors and add them together. The test makes sure it is registered correctly and then verifies the outcome is correct.
Differential Revision: [D42204263](https://our.internmc.facebook.com/intern/diff/D42204263/)
Pull Request resolved: https://github.com/pytorch/pytorch/pull/91291
Approved by: https://github.com/ezyang
## Logic to handle custom ops
We generate files for custom ops, so that they can be registered into PyTorch.
Generated files:
* `Register{dispatch_key}CustomOps.cpp` (dispatch_key = CPU), it's basically the same as vanilla PyTorch `RegisterCPU.cpp`. The only difference is that we bind to native functions directly.
* `Register{dispatch_key}Stub.cpp` (dispatch_key = CPU), register placeholder kernels for custom ops. Only used when there's no custom op kernel available.
As an example:
```cpp
namespace {
at::Tensor & wrapper_out_unsqueeze_out(const at::Tensor & self, int64_t dim, at::Tensor & out) {
// No device check
// DeviceGuard omitted
return torch::executor::native::unsqueeze_out(self, dim, out);
}
} // anonymous namespace
TORCH_LIBRARY_IMPL(aten, CPU, m) {
m.impl("unsqueeze.out",
TORCH_FN(wrapper_out_unsqueeze_out));
}
```
Pull Request resolved: https://github.com/pytorch/pytorch/pull/90099
Approved by: https://github.com/ezyang
This PR adds `unboxing.py` which converts a `EValue` (similar to `IValue`) to its corresponding C++ type, based on the `ExecutorchCppSignature`.
Added unit tests to it in `test_executorch_unboxing.py`. Notice that this unboxing logic should work for both ATen types and Executorch types, hence the unit tests are parametrized.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/90098
Approved by: https://github.com/ezyang
Retry of #90591, which is a retry of #89595. Reverted due to dependency PR breaking internal fbcode.
## Forked BaseCppType
Created a module for Executorch: `torchgen.executorch`.
## In `torchgen.executorch.api.types.types`:
* Define `BaseCppType` with `torch::executor` namespace.
## In `torchgen.executorch.api.et_cpp`:
* Help generate `NamedCType` for `ExecutorchCppSignature` arguments.
## In `torchgen.executorch.api.types.signatures`:
* Define the signature using these types. (`ExecutorchCppSignature`)
## In `torchgen.executorch.api.types.__init__`:
* Suppress flake8 error for `import *`.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/90781
Approved by: https://github.com/ezyang
Retry of #89595. Accidentally closed.
## Forked `BaseCppType`
Created a module for Executorch: `torchgen.executorch`.
In `torchgen.executorch.api.types.types`:
* Define `BaseCppType` with `torch::executor` namespace.
In `torchgen.executorch.api.et_cpp`:
* Help generate `NamedCType` for `ExecutorchCppSignature` arguments.
In `torchgen.executorch.api.types.signatures`:
* Define the signature using these types. (`ExecutorchCppSignature`)
In `torchgen.executorch.api.types.__init__`:
* Suppress flake8 error for `import *`.
Differential Revision: [D41501836](https://our.internmc.facebook.com/intern/diff/D41501836/)
Pull Request resolved: https://github.com/pytorch/pytorch/pull/90591
Approved by: https://github.com/iseeyuan
