* Added a cpp loader, AOTIModelPackageLoader, which can load the .pt2, build the .so, and create a runner. The python-facing API is that users can directly call the `run` function, whereas in cpp users can directly access the `runner_` if they are more familiar with that. I couldn't figure out how to bind the `get_runner()` function to python...
* Added a new config, `aot_inductor.package_cpp_only` which will **not** package the so. This means that whenever the package is loaded, we will need to build the so. This is turned off by default so that new environments do not need to rebuild their so. The `package_cpp_only` is a feature which torchchat intends to use to provide flexibility to users.
* Added a new config, `aot_inductor.metadata` which stores user-provided metadata, serialized to the pt2 as a json file. It also stores the device used when exporting, "cuda" or "cpu", so that during load time, we can use that data to determine which AOTIModelContainerRunner to use. The metadata can be accessed through `loader.get_metadata()`. TODO is to move this metadata to the toplevel `package_aoti` function so that we can remove the metadata as a config.
* Separated out `package_aoti` as a standalone function, instead of it automatically being called in inductor. This is to prepare for the case where users will compile multiple models, and want to bundle it in one package. The specific use case is in torchchat, where we want to package the separately-exported encoder and decoder layers. An example of how to use this is in `test_multiple_methods`.
* `load_package` will load a singular model, given the model name.
* The loader doesn't support windows for now, I think I need to add some more casing to make the build commands work on windows?
Differential Revision: [D62329906](https://our.internmc.facebook.com/intern/diff/D62329906)
Pull Request resolved: https://github.com/pytorch/pytorch/pull/135374
Approved by: https://github.com/desertfire, https://github.com/malfet
Another attempt to update NVTX to NVTX3. We now avoid changing NVTX header inclusion of existing code. The advantage of NVTX3 over NVTX is that it is a header-only library so that linking with NVTX3 can greatly simplify our CMake and other building scripts for finding libraries in user environments. In addition, NVTX are indeed still present in the latest CUDA versions, but they're no longer a compiled library: It's now a header-only library. That's why there isn't a .lib file anymore.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/109843
Approved by: https://github.com/peterbell10, https://github.com/eqy
Co-authored-by: Ivan Zaitsev <108101595+izaitsevfb@users.noreply.github.com>
0.12.0 Major Updates:
- Add context manager to temporarily set the dictionary sorting mode
- Add accessor APIs
- Use `stable` tag for `pybind11` for Python 3.13 support
- Fix potential segmentation fault for pickling support
0.12.1 Updates:
- Fix warning regression during import when launch with strict warning filters
Closes#130155
Pull Request resolved: https://github.com/pytorch/pytorch/pull/130139
Approved by: https://github.com/zou3519
ghstack dependencies: #130895
------
The opposite of #130836. Pin `sympy >= 1.13.0` for Python >= 3.9 and `sympy == 1.12.1` for Python 3.8.
- #130836
See the PR description of #130836 for more details.
`sympy` 1.13.0 introduces some breaking changes which break our tests. More specifically:
- Ref [Backwards compatibility breaks and deprecations](https://github.com/sympy/sympy/wiki/release-notes-for-1.13.0#backwards-compatibility-breaks-and-deprecations)
> BREAKING CHANGE: Float and Integer/Rational no longer compare equal with a == b. From now on Float(2.0) != Integer(2). Previously expressions involving Float would compare unequal e.g. x*2.0 != x*2 but an individual Float would compare equal to an Integer. In SymPy 1.7 a Float will always compare unequal to an Integer even if they have the same "value". Use sympy.numbers.int_valued(number) to test if a number is a concrete number with no decimal part. ([#25614](https://github.com/sympy/sympy/pull/25614) by [@smichr](https://github.com/smichr))
`sympy >= 1.13.0` is required to enable Python 3.13 support. This should be part of #130689.
- #130689
Pull Request resolved: https://github.com/pytorch/pytorch/pull/130895
Approved by: https://github.com/ezyang
0.12.0 Major Updates:
- Add context manager to temporarily set the dictionary sorting mode
- Add accessor APIs
- Use `stable` tag for `pybind11` for Python 3.13 support
- Fix potential segmentation fault for pickling support
0.12.1 Updates:
- Fix warning regression during import when launch with strict warning filters
Closes#130155
Pull Request resolved: https://github.com/pytorch/pytorch/pull/130139
Approved by: https://github.com/zou3519
Removes extraneous .a, .so, and .py files from the split build. From here we can also clean up the builder script which produces the binary to do this. That pr is https://github.com/pytorch/builder/pull/1912
Verification:
The built wheel with BUILD_LIBTORCH_WHL=1 has the following files only (with .a, .so, and .py extensions)
```
sahanp@devgpu086 ~/p/dist (viable/strict)> pwd (pytorch-3.10)
/home/sahanp/pytorch/dist
sahanp@devgpu086 ~/p/dist (viable/strict)> find . -type f \( -name "*.py" -o -name "*.a" -o -name "*.so" \) (pytorch-3.10)
./torch/__init__.py
./torch/lib/libbackend_with_compiler.so
./torch/lib/libc10.so
./torch/lib/libjitbackend_test.so
./torch/lib/libtorch.so
./torch/lib/libtorch_cpu.so
./torch/lib/libtorch_global_deps.so
./torch/lib/libtorchbind_test.so
sahanp@devgpu086 ~/p/dist (viable/strict)>
```
Pull Request resolved: https://github.com/pytorch/pytorch/pull/130053
Approved by: https://github.com/atalman
This PR removes the second separate package we were using for the libtorch wheel.
In terms of testing that this works we will look use the PRs above this in the stack.
As for sanity checking these are the wheels that are produced by running
```
python setup.py clean && BUILD_LIBTORCH_WHL=1 with-proxy python setup.py bdist_whee
l && BUILD_PYTHON_ONLY=1 with-proxy python setup.py bdist_wheel --cmake
```
```
sahanp@devgpu086 ~/pytorch ((5f15e171…))> ls -al dist/ (pytorch-3.10)
total 677236
drwxr-xr-x 1 sahanp users 188 Jun 4 12:19 ./
drwxr-xr-x 1 sahanp users 1696 Jun 4 12:59 ../
-rw-r--r-- 1 sahanp users 81405742 Jun 4 12:19 torch-2.4.0a0+gitca0a73c-cp310-cp310-linux_x86_64.whl
-rw-r--r-- 1 sahanp users 612076919 Jun 4 12:19 libtorch-2.4.0a0+gitca0a73c-py3-none-any.whl
```
Pull Request resolved: https://github.com/pytorch/pytorch/pull/127934
Approved by: https://github.com/atalman
Summary:
1.Package public headers of kineto if USE_KINETO so that they can be used by PrivateUse1 user.
2.Add PrivateUse1 key to ActivityType.
3. Support PrivateUse1 key in function deviceTypeFromActivity and _supported_activities.
4. Fix some bugs when processing profiler results.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/124818
Approved by: https://github.com/aaronenyeshi
Summary:
1.Package public headers of kineto if USE_KINETO so that they can be used by PrivateUse1 user.
2.Add PrivateUse1 key to ActivityType.
3. Support PrivateUse1 key in function deviceTypeFromActivity and _supported_activities.
4. Fix some bugs when processing profiler results.
Co-authored-by: albanD <desmaison.alban@gmail.com>
Co-authored-by: Aaron Shi <enye.shi@gmail.com>
Pull Request resolved: https://github.com/pytorch/pytorch/pull/120556
Approved by: https://github.com/aaronenyeshi
This PR adds a linker script optimization based on prioritized symbols that can be extracted from the profiles of popular workloads. The present linker script was generated to target ARM+CUDA and later can be extended if necessary. The reason we target ARM is shown below:
> PyTorch and other applications that access more than 24x 2MB code regions in quick succession can result in performance bottlenecks in the CPU front-end. The link-time optimization improves executable code locality and improve performance. We recommend turning on the optimization always for PyTorch and other application that behaves similarly.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/121975
Approved by: https://github.com/ptrblck, https://github.com/atalman
