This change fixes the RUNPATH of installed c++ tests so that the linker can find the shared libraries they depend on.
For example, currently:
```bash
venv/lib/python3.10/site-packages/torch $ ./bin/test_lazy
./bin/test_lazy: error while loading shared libraries: libtorch.so: cannot open shared object file: No such file or directory
```
Pull Request resolved: https://github.com/pytorch/pytorch/pull/136627
Approved by: https://github.com/malfet
Summary:
X-link: https://github.com/pytorch/executorch/pull/5720
For smaller models the overhead of profiling ops might be prohibitively large (distorting the inference execution time significantly) so we provide users an option to disable op profiling and essentially only profile the important events such as inference execution time.
To disable operator profiling users need to do:
```
etdump_gen.set_event_tracer_profiling_level(executorch::runtime::EventTracerProfilingLevel::kNoOperatorProfiling);
```
Test Plan: Added test case.
Differential Revision: D61883224
Pull Request resolved: https://github.com/pytorch/pytorch/pull/136838
Approved by: https://github.com/dbort
As FindPythonInterp and FindPythonLibs has been deprecated since cmake-3.12
Replace `PYTHON_EXECUTABLE` with `Python_EXECUTABLE` everywhere (CMake variable names are case-sensitive)
This makes PyTorch buildable with python3 binary shipped with XCode on MacOS
TODO: Get rid of `FindNumpy` as its part of Python package
Pull Request resolved: https://github.com/pytorch/pytorch/pull/124613
Approved by: https://github.com/cyyever, https://github.com/Skylion007
Summary:
This diff adds support in the ExecuTorch codegen layer to log the outputs of kernels to event_tracer. It does this by calling the `event_tracer_log_evalue` API.
When the `ET_EVENT_TRACER_ENABLED` flag is disabled this is essentially a no-op and will add no overhead.
Test Plan: CI
Reviewed By: larryliu0820
Differential Revision: D51534590
Pull Request resolved: https://github.com/pytorch/pytorch/pull/114584
Approved by: https://github.com/larryliu0820
Summary:
Exposing a codegen mode for generating a hook for user to register their kernels.
If we pass `--manual-registration` flag to `gen_executorch.py`, we will generate the following files:
1. RegisterKernels.h which declares a `register_all_kernels()` API inside `torch::executor` namespace.
2. RegisterKernelsEverything.cpp which implements `register_all_kernels()` by defining an array of generated kernels.
This way user can depend on the library declared by `executorch_generated_lib` macro (with `manual_registration=True`) and be able to include `RegisterKernels.h`. Then they can manually call `register_all_kernels()` instead of relying on C++ static initialization mechanism which is not available in some embedded systems.
Test Plan:
Rely on the unit test:
```
buck2 test fbcode//executorch/runtime/kernel/test:test_kernel_manual_registration
```
Reviewed By: cccclai
Differential Revision: D49439673
Pull Request resolved: https://github.com/pytorch/pytorch/pull/110086
Approved by: https://github.com/cccclai
Summary: Split out from D48975975, this handles the pytorch specific changes to add support for event_tracer in codegen layer.
Test Plan: CI
Reviewed By: dbort
Differential Revision: D49487710
Pull Request resolved: https://github.com/pytorch/pytorch/pull/109990
Approved by: https://github.com/Jack-Khuu
Based on this [code search](https://fburl.com/code/gjcnw8ly) (*.yaml with `dispatch: CPU:`), update all files found to use
```
kernels:
- arg_meta: None
kernel_name:
```
instead of
```
dispatch:
CPU:
```
---
## Code changes:
- `fbcode/executorch/codegen/tools/gen_oplist.py`
- Strip ET specific fields prior to calling parse_native_yaml_struct
---
## Files edited that are not `*functions.yaml` or `custom_ops.yaml`
- fbcode/executorch/kernels/optimized/optimized.yaml
- fbcode/executorch/kernels/quantized/quantized.yaml
- fbcode/executorch/kernels/test/custom_kernel_example/my_functions.yaml
---
## Found Files that were not edited
**Dispatched to more than just CPU**
- fbcode/caffe2/aten/src/ATen/native/native_functions.yaml
- xplat/caffe2/aten/src/ATen/native/native_functions.yaml
- xros/third-party/caffe2/caffe2/aten/src/ATen/native/native_functions.yaml
**Grouped ops.yaml path**
- fbcode/on_device_ai/Assistant/Jarvis/min_runtime/operators/ops.yaml
---
**Design Doc:** https://docs.google.com/document/d/1gq4Wz2R6verKJ2EFseLyPdAF0wqomnCrVDDJpRkYsRw/edit?kh_source=GDOCS#heading=h.8raqyft9y50
Differential Revision: [D46952067](https://our.internmc.facebook.com/intern/diff/D46952067/)
**NOTE FOR REVIEWERS**: This PR has internal Meta-specific changes or comments, please review them on [Phabricator](https://our.internmc.facebook.com/intern/diff/D46952067/)!
Pull Request resolved: https://github.com/pytorch/pytorch/pull/104070
Approved by: https://github.com/larryliu0820
Summary: Currently we rely on root operator, but we also need to check for et_kernel_metadata for used specialized kernels.
Test Plan: contbuild & OSS CI
Reviewed By: Jack-Khuu
Differential Revision: D46882119
Pull Request resolved: https://github.com/pytorch/pytorch/pull/104005
Approved by: https://github.com/Jack-Khuu
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
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
--whole-archive is a linker option(notice, that flag is passed as -Wl,--whole-archive), and -force_load is indeed available on MacOS platform (below is the quote from man ld):
-force_load path_to_archive
Loads all members of the specified static archive library. Note:
-all_load forces all members of all archives to be loaded. This
option allows you to target a specific archive.
Quote from malfet
Pull Request resolved: https://github.com/pytorch/pytorch/pull/91736
Approved by: https://github.com/larryliu0820
## Job
Test running on most CI jobs.
## Test binary
* `test_main.cpp`: entry for gtest
* `test_operator_registration.cpp`: test cases for gtest
## Helper sources
* `operator_registry.h/cpp`: simple operator registry for testing purpose.
* `Evalue.h`: a boxed data type that wraps ATen types, for testing purpose.
* `selected_operators.yaml`: operators Executorch care about so far, we should cover all of them.
## Templates
* `NativeFunctions.h`: for generating headers for native functions. (not compiled in the test, since we will be using `libtorch`)
* `RegisterCodegenUnboxedKernels.cpp`: for registering boxed operators.
* `Functions.h`: for declaring operator C++ APIs. Generated `Functions.h` merely wraps `ATen/Functions.h`.
## Build files
* `CMakeLists.txt`: generate code to register ops.
* `build.sh`: driver file, to be called by CI job.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/89596
Approved by: https://github.com/ezyang
