Summary: To fix https://github.com/pytorch/pytorch/issues/159400. Currently, test_aoti_abi_check and test_aoti_inference need to be built in two passes, first build pytorch using the regular `pythonsetup.py develop` and then build with `CMAKE_FRESH=1 BUILD_AOT_INDUCTOR_TEST=1 python setup.py devleop`. This is cumbersome. Fix by rewriting CMakeLists.txt for test_aoti_inference to one-pass build which runs AOTI to compile models at the test time. Also update CI test script to get rid of two-pass build. For test_aoti_abi_check, it is not AOTI specific, so we make it not guarded by BUILD_AOT_INDUCTOR_TEST.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/164277
Approved by: https://github.com/janeyx99
This is my suggestion for resolving #152087
This PR extends the constructor of `AOTIModelPackageLoader` with an (optional) device index. The device type is still determined by `metadata_["AOTI_DEVICE_KEY"]`, but the `device_index` argument can be used to move an AOTI model package to different devices like `cuda:0`, `cuda:1`, ... in a convenient way. AFAIK, this is not possible so far using `AOTIModelPackageLoader` alone. The default case (no device index specified) with `metadata_["AOTI_DEVICE_KEY"] == "cuda"` would lead to the current behavior, i.e., the model is loaded to device `cuda`.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/152093
Approved by: https://github.com/desertfire
Summary:
We add states in the constant folding process for AOTInductor.
Basically, there's 3 states, which is
(1) None: The state when no constants are loaded and uninitialized.
(2) Initialized: The state when constants are loaded, but not yet
folded.
(3) Folded: The state where the model is fully ready with folded
constants.
Note that even if constant folding is not enabled, we still only run
when state is FOLDED, this is okay because without constant folding, the
transition from INITIALIZED to FOLDED is just a pass-throught.
Test Plan:
python test/inductor/test_aot_inductor.py -k test_constant_folding_with_update
Reviewers:
Subscribers:
Tasks:
Tags:
Differential Revision: [D73002538](https://our.internmc.facebook.com/intern/diff/D73002538)
Pull Request resolved: https://github.com/pytorch/pytorch/pull/151273
Approved by: https://github.com/jingsh, https://github.com/desertfire
Summary:
We add the functionality to allow users to directly pass in a at::Tensor
into AOTInductor, that would be used as the constant.
This user managed buffer skips the copying step in AOTInductor, and let
users to directly manage the memory usage themselve.
Test Plan:
LD_LIBRARY_PATH=/data/users/$USER/pytorch/build/lib
/data/users/$USER/pytorch/build/bin/test_aoti_inference
Reviewers:
Subscribers:
Tasks:
Tags:
Differential Revision: [D72589514](https://our.internmc.facebook.com/intern/diff/D72589514)
Pull Request resolved: https://github.com/pytorch/pytorch/pull/150276
Approved by: https://github.com/chenyang78, https://github.com/desertfire
operations
Summary:
Fix the test for memory tracking. This PR does:
(1) Add tracking before and after for all memory-related operations.
Make sure the operation do indeed captures memory both in CUDA and
torch's CUDACachAllocator Make sure the operation do indeed captures
consumed memory both in CUDA and torch's CUDACachAllocator.
(2) Keep track of memory being reserved by CUDACacheAllocator in
torch and it's relationship with global CUDA memory consumption.
Test Plan:
This PR is adding tests.
Reviewers:
Subscribers:
Tasks:
Tags:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/150269
Approved by: https://github.com/jingsh, https://github.com/chenyang78, https://github.com/desertfire
Summary: Add extract_constant_map that allows users to inspect the constants being used by AOTInductor
Test Plan:
`python test/inductor/test_aot_inductor.py -k extract_constants_map`
`LD_LIBRARY_PATH=/data/users/$USER/pytorch/build/lib /data/users/$USER/pytorch/build/bin/test_aoti_inference`
Differential Revision: D72020400
Pull Request resolved: https://github.com/pytorch/pytorch/pull/150163
Approved by: https://github.com/chenyang78
internally.
Summary:
This diff allows freeing the usage of folded constants that's created by
AOTInductor through CUDACachingAllocator instead of the constant blob
from cudaMalloc directly.
Test Plan:
LD_LIBRARY_PATH=/data/users/$USER/pytorch/build/lib
/home/$USER/local/pytorch/build/bin/test_aoti_inference
Reviewers:
Subscribers:
Tasks:
Tags:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/149825
Approved by: https://github.com/chenyang78, https://github.com/desertfire, https://github.com/jingsh
Summary:
We might free the active buffer if we free the buffer twice.
Test Plan:
```
LD_LIBRARY_PATH=/data/users/$USER/pytorch/build/lib
/home/$USER/local/pytorch/build/bin/test_aoti_inference
```
Reviewers:
Subscribers:
Tasks:
Tags:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/149810
Approved by: https://github.com/chenyang78
The default value for `run_single_threaded` was wrongly specified in the .cpp file instead of the header, breaking C++-side instantiation of `AOTIModelPackageLoader` with no arguments. This PR fixes this and adds a test for the use case of running with `AOTIModelPackageLoader` instead of `AOTIModelContainerRunner` on the C++ side.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/149082
Approved by: https://github.com/desertfire
Summary: Tighten the AOTIModelContainerRunner::run interface to take a const vector of at::Tensor, which 1) makes it clear that the runner will not modify the input tensor vector; 2) runner will be able to take a temp vector of tensors as the input.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/139955
Approved by: https://github.com/chenyang78
Summary: In AOTInductor generated CPU model code, there can be direct references to some aten/c10 utility functions and data structures, e.g. at::vec and c10::Half. These are performance critical and thus it doesn't make sense to create C shim for them. Instead, we make sure they are implemented in a header-only way, and use this set of tests to guard future changes.
There are more header files to be updated, but we will do it in other followup PRs.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/123848
Approved by: https://github.com/jansel
ghstack dependencies: #123847
