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
Summary:
In ATen mode, we add the RuntimeContext arg, so we have something like
```
TORCH_API inline at::Tensor & gelu_outf(torch::executor::RuntimeContext & context, const at::Tensor & self, c10::string_view approximate, at::Tensor & out) {
return at::gelu_outf(self, approximate, out);
}
```
and user can use `<namespace like aten>::gelu_outf` and we will automatically dispatch the registered function in aten kernel using `at::gelu_outf` (dispatched by ATen/Functions.h header)
In optimized kernel tests, we can now automatically handle between aten kernel and optimized kernel.
The implication is that the test must depend on the correctness of codegen; an error in codegen can break the kernel tests.
Test Plan: CI
Differential Revision: D43777848
Pull Request resolved: https://github.com/pytorch/pytorch/pull/96084
Approved by: https://github.com/larryliu0820
Applies the remaining flake8-comprehension fixes and checks. This changes replace all remaining unnecessary generator expressions with list/dict/set comprehensions which are more succinct, performant, and better supported by our torch.jit compiler. It also removes useless generators such as 'set(a for a in b)`, resolving it into just the set call.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/94676
Approved by: https://github.com/ezyang
Preferring dash over underscore in command-line options. Add `--command-arg-name` to the argument parser. The old arguments with underscores `--command_arg_name` are kept for backward compatibility.
Both dashes and underscores are used in the PyTorch codebase. Some argument parsers only have dashes or only have underscores in arguments. For example, the `torchrun` utility for distributed training only accepts underscore arguments (e.g., `--master_port`). The dashes are more common in other command-line tools. And it looks to be the default choice in the Python standard library:
`argparse.BooleanOptionalAction`: 4a9dff0e5a/Lib/argparse.py (L893-L895)
```python
class BooleanOptionalAction(Action):
def __init__(...):
if option_string.startswith('--'):
option_string = '--no-' + option_string[2:]
_option_strings.append(option_string)
```
It adds `--no-argname`, not `--no_argname`. Also typing `_` need to press the shift or the caps-lock key than `-`.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/94505
Approved by: https://github.com/ezyang, https://github.com/seemethere
Rely on CI.
Avoid issues such as:
```
Traceback (most recent call last):
File "<string>", line 38, in <module>
File "<string>", line 36, in __run
File "/usr/local/fbcode/platform010/lib/python3.8/runpy.py", line 194, in _run_module_as_main
return _run_code(code, main_globals, None,
File "/usr/local/fbcode/platform010/lib/python3.8/runpy.py", line 87, in _run_code
exec(code, run_globals)
File "/re_cwd/buck-out/v2/gen/fbcode/2841b324ed9b88dd/caffe2/torchgen/__gen_executorch__/gen_executorch#link-tree/torchgen/gen_executorch.py", line 690, in <module>
main()
File "/re_cwd/buck-out/v2/gen/fbcode/2841b324ed9b88dd/caffe2/torchgen/__gen_executorch__/gen_executorch#link-tree/torchgen/gen_executorch.py", line 626, in main
parsed_yaml, custom_ops_parsed_yaml = parse_yaml_files(
File "/re_cwd/buck-out/v2/gen/fbcode/2841b324ed9b88dd/caffe2/torchgen/__gen_executorch__/gen_executorch#link-tree/torchgen/gen_executorch.py", line 505, in parse_yaml_files
translate_native_yaml(
File "/re_cwd/buck-out/v2/gen/fbcode/2841b324ed9b88dd/caffe2/torchgen/__gen_executorch__/gen_executorch#link-tree/torchgen/gen_executorch.py", line 448, in translate_native_yaml
for e in native_es:
TypeError: 'NoneType' object is not iterable
```
Differential Revision: [D42729435](https://our.internmc.facebook.com/intern/diff/D42729435)
Pull Request resolved: https://github.com/pytorch/pytorch/pull/92938
Approved by: https://github.com/JacobSzwejbka
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
