Commit Graph

12 Commits

Author SHA1 Message Date
Mwiza Kunda
22d2e2d9a0 Set RUNPATH so installed tests can find the required shared libraries (#136627)
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
2024-10-25 09:38:08 +00:00
PaliC
a25b28a753 [Split Build] Add option to create libtorch wheel and use it to build pytorch as a separate wheel (#126328)
Creates an option to just build the libtorch portion of pytorch such that we have the necessary .so files.  Then it builds a torch package using the libtorch wheel. These options are enabled using ` BUILD_LIBTORCH_WHL` and `BUILD_PYTHON_ONLY`.

We run

```
 BUILD_LIBTORCH_WHL=1 python setup.py install
python setup.py clean
BUILD_PYTHON_ONLY=1 python setup.py install
```

to produce

```
sahanp@devgpu086 ~/pytorch (detached HEAD|REBASE-i 3/5)> ls /home/sahanp/.conda/envs/pytorch-3.10/lib/python3.10/site-packages/torch/lib/                                                                                                                (pytorch-3.10)
libshm.so*  libtorch_global_deps.so*  libtorch_python.so*
sahanp@devgpu086 ~/pytorch (detached HEAD|REBASE-i 3/5)> ldd build/lib/libtorch_python.so                                                                                                                                                                (pytorch-3.10)
        linux-vdso.so.1 (0x00007ffdc2d37000)
        libtorch.so => /home/sahanp/.conda/envs/pytorch-3.10/lib/python3.10/site-packages/libtorch/lib/libtorch.so (0x00007f539fe99000)
        libshm.so => /home/sahanp/pytorch/build/lib/libshm.so (0x00007f539fe90000)
        libcudnn.so.8 => /usr/local/cuda-12.1/targets/x86_64-linux/lib/libcudnn.so.8 (0x00007f539e800000)
        libnvToolsExt.so.1 => /usr/local/cuda/lib64/libnvToolsExt.so.1 (0x00007f539e400000)
        libstdc++.so.6 => /lib64/libstdc++.so.6 (0x00007f539e000000)
        libm.so.6 => /lib64/libm.so.6 (0x00007f539fda5000)
        libgcc_s.so.1 => /lib64/libgcc_s.so.1 (0x00007f539ebe5000)
        libc.so.6 => /lib64/libc.so.6 (0x00007f539dc00000)
        /lib64/ld-linux-x86-64.so.2 (0x00007f539fea0000)
        libtorch_cpu.so => /home/sahanp/.conda/envs/pytorch-3.10/lib/python3.10/site-packages/libtorch/lib/libtorch_cpu.so (0x00007f5392400000)
        libtorch_cuda.so => /home/sahanp/.conda/envs/pytorch-3.10/lib/python3.10/site-packages/libtorch/lib/libtorch_cuda.so (0x00007f5380000000)
        librt.so.1 => /lib64/librt.so.1 (0x00007f539fd9e000)
        libpthread.so.0 => /lib64/libpthread.so.0 (0x00007f539fd99000)
        libdl.so.2 => /lib64/libdl.so.2 (0x00007f539fd94000)
        libc10.so => /home/sahanp/.conda/envs/pytorch-3.10/lib/python3.10/site-packages/libtorch/lib/libc10.so (0x00007f539eb07000)
        libmkl_intel_lp64.so.2 => /home/sahanp/.conda/envs/pytorch-3.10/lib/libmkl_intel_lp64.so.2 (0x00007f537ec00000)
        libmkl_gnu_thread.so.2 => /home/sahanp/.conda/envs/pytorch-3.10/lib/libmkl_gnu_thread.so.2 (0x00007f537ce00000)
        libmkl_core.so.2 => /home/sahanp/.conda/envs/pytorch-3.10/lib/libmkl_core.so.2 (0x00007f5378800000)
        libomp.so => /home/sahanp/.conda/envs/pytorch-3.10/lib/libomp.so (0x00007f539e707000)
        libcupti.so.12 => /usr/local/cuda/lib64/libcupti.so.12 (0x00007f5377e00000)
        libcudart.so.12 => /usr/local/cuda/lib64/libcudart.so.12 (0x00007f5377a00000)
        libc10_cuda.so => /home/sahanp/.conda/envs/pytorch-3.10/lib/python3.10/site-packages/libtorch/lib/libc10_cuda.so (0x00007f539ea6a000)
        libcusparse.so.12 => /usr/local/cuda/lib64/libcusparse.so.12 (0x00007f5368400000)
        libcufft.so.11 => /usr/local/cuda/lib64/libcufft.so.11 (0x00007f535ee00000)
        libcusolver.so.11 => /usr/local/cuda/lib64/libcusolver.so.11 (0x00007f534c800000)
        libcurand.so.10 => /usr/local/cuda/lib64/libcurand.so.10 (0x00007f5346200000)
        libcublas.so.12 => /usr/local/cuda/lib64/libcublas.so.12 (0x00007f533f800000)
        libcublasLt.so.12 => /usr/local/cuda/lib64/libcublasLt.so.12 (0x00007f531e800000)
        libutil.so.1 => /lib64/libutil.so.1 (0x00007f539ea63000)
        libnvJitLink.so.12 => /usr/local/cuda/lib64/libnvJitLink.so.12 (0x00007f531b800000)
sahanp@devgpu086 ~/pytorch (detached HEAD|REBASE-i 3/5)> ldd build/lib/libtorch_global_deps.so                                                                                                                                                           (pytorch-3.10)
        linux-vdso.so.1 (0x00007ffc265df000)
        libmkl_intel_lp64.so.2 => /home/sahanp/.conda/envs/pytorch-3.10/lib/libmkl_intel_lp64.so.2 (0x00007fa93fc00000)
        libmkl_gnu_thread.so.2 => /home/sahanp/.conda/envs/pytorch-3.10/lib/libmkl_gnu_thread.so.2 (0x00007fa93de00000)
        libmkl_core.so.2 => /home/sahanp/.conda/envs/pytorch-3.10/lib/libmkl_core.so.2 (0x00007fa939800000)
        libm.so.6 => /lib64/libm.so.6 (0x00007fa940f05000)
        libcudart.so.12 => /usr/local/cuda/lib64/libcudart.so.12 (0x00007fa939400000)
        libnvToolsExt.so.1 => /usr/local/cuda/lib64/libnvToolsExt.so.1 (0x00007fa939000000)
        libgomp.so.1 => /home/sahanp/.conda/envs/pytorch-3.10/lib/libgomp.so.1 (0x00007fa93fb07000)
        libc.so.6 => /lib64/libc.so.6 (0x00007fa938c00000)
        libdl.so.2 => /lib64/libdl.so.2 (0x00007fa940efe000)
        libpthread.so.0 => /lib64/libpthread.so.0 (0x00007fa940ef9000)
        /lib64/ld-linux-x86-64.so.2 (0x00007fa940ff5000)
        librt.so.1 => /lib64/librt.so.1 (0x00007fa940ef2000)
        libstdc++.so.6 => /home/sahanp/.conda/envs/pytorch-3.10/lib/libstdc++.so.6 (0x00007fa93921d000)
        libgcc_s.so.1 => /home/sahanp/.conda/envs/pytorch-3.10/lib/libgcc_s.so.1 (0x00007fa93faec000)
        ```
Pull Request resolved: https://github.com/pytorch/pytorch/pull/126328
Approved by: https://github.com/atalman
2024-05-29 04:33:56 +00:00
cyy
87cbfe957a increase clang-tidy coverage to more c10 source files (#102902)
Pull Request resolved: https://github.com/pytorch/pytorch/pull/102902
Approved by: https://github.com/Skylion007
2023-06-04 06:33:01 +00:00
Scott Wolchok
cfd697c979 [PyTorch] add intrusive_ptr exclusive ownership benchmark
Pull Request resolved: https://github.com/pytorch/pytorch/pull/76766

None of the existing benchmarks captured the cost of the final destruction of an intrusive_ptr.

Differential Revision: [D36109756](https://our.internmc.facebook.com/intern/diff/D36109756/)

Approved by: https://github.com/ezyang
2022-06-10 19:26:28 +00:00
mikey dagitses
026c0af479 move intrusive_ptr benchmark to shared build structure (#71413)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/71413

ghstack-source-id: 150235101

Test Plan: Verified manually. Rely on CI to validate.

Reviewed By: malfet

Differential Revision: D33635740

fbshipit-source-id: 82c6798a20c01c16fb17547d4a0ba30e6ffc272d
(cherry picked from commit d7a0b39f510f59fe16f138a712d380e0091b230a)
2022-03-02 11:33:22 +00:00
mikey dagitses
4bf8a9b259 add benchmark to Bazel build (#71412)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/71412

This is only in CMake and internal builds right now. Add to Bazel for
parity.
ghstack-source-id: 150235094

Test Plan: Built and ran locally. Rely on CI to verify.

Reviewed By: malfet

Differential Revision: D33635743

fbshipit-source-id: b9e5abbef5feabd52c53a9c2b95713b87ce81681
(cherry picked from commit 11700dbc80200093fdd74b1be066b4e740cee516)
2022-03-02 11:33:22 +00:00
Nikita Shulga
a9b0a921d5 Disable avoid-non-const-global-variables lint check (#62008)
Summary:
As GoogleTest `TEST` macro is non-compliant with it as well as `DEFINE_DISPATCH`

All changes but the ones to `.clang-tidy` are generated using following script:
```
for i in `find . -type f -iname "*.c*" -or -iname "*.h"|xargs grep cppcoreguidelines-avoid-non-const-global-variables|cut -f1 -d:|sort|uniq`;  do sed -i "/\/\/ NOLINTNEXTLINE(cppcoreguidelines-avoid-non-const-global-variables)/d" $i; done
```

Pull Request resolved: https://github.com/pytorch/pytorch/pull/62008

Reviewed By: driazati, r-barnes

Differential Revision: D29838584

Pulled By: malfet

fbshipit-source-id: 1b2f8602c945bd4ce50a9bfdd204755556e31d13
2021-07-22 18:04:40 -07:00
Scott Wolchok
44cc873fba [PyTorch] Autoformat c10 (#56830)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/56830

Opt into formatting on GitHub and format everything. This is a trial run before turning on formatting for more and eventually all of the codebase.

Test Plan: CI

Reviewed By: zertosh

Differential Revision: D27979080

fbshipit-source-id: a80f0c48691c08ae8ca0af06377b87e6a2351151
2021-04-30 21:23:28 -07:00
Nikita Shulga
087049000b Make c10 clang-tidy clean (#55870)
Summary:
This change was autogenerated by running:
```
% find c10 -iname "*.cpp" -exec python3 tools/clang_tidy.py -c build -x {} -s \;
```

Pull Request resolved: https://github.com/pytorch/pytorch/pull/55870

Reviewed By: janeyx99

Differential Revision: D27728617

Pulled By: malfet

fbshipit-source-id: bede4d7f0c106d51394d1e9efddf01bf894421c5
2021-04-14 11:23:28 -07:00
frdong
92770d25cd fix comparison of narrow type with wide type in loop condition (#53951)
Summary:
fix Semmle warning: Comparison of narrow type with wide type in loop condition

For example there is below piece of code:
for (int i=0; i<array.size(); ++i) {}

The problem is that array.size() return type is size_t can be larger type than int depending on the implementation so there is chance that i overflows (for very large array that array size is beyond the range of integer) and this loop will never be terminated.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/53951

Reviewed By: zou3519

Differential Revision: D27181495

Pulled By: malfet

fbshipit-source-id: 0612c5cedcdc656c193085e7fbb87dd163f20688
2021-03-22 16:40:35 -07:00
peter
45c9ed825a Formatting cmake (to lowercase without space for if/elseif/else/endif) (#35521)
Summary:
Running commands:
```bash
shopt -s globstar

sed -e 's/IF (/if(/g' -e 's/IF(/if(/g' -e 's/if (/if(/g' -e 's/ELSE (/else(/g' -e 's/ELSE(/else(/g' -e 's/else (/else(/g' -e 's/ENDif(/endif(/g' -e 's/ELSEif(/elseif(/g' -i CMakeLists.txt
sed -e 's/IF (/if(/g' -e 's/IF(/if(/g' -e 's/if (/if(/g' -e 's/ELSE (/else(/g' -e 's/ELSE(/else(/g' -e 's/else (/else(/g' -e 's/ENDif(/endif(/g' -e 's/ELSEif(/elseif(/g' -i caffe2/**/CMakeLists.txt
sed -e 's/IF (/if(/g' -e 's/IF(/if(/g' -e 's/if (/if(/g' -e 's/ELSE (/else(/g' -e 's/ELSE(/else(/g' -e 's/else (/else(/g' -e 's/ENDif(/endif(/g' -e 's/ELSEif(/elseif(/g' -i torch/**/CMakeLists.txt
sed -e 's/IF (/if(/g' -e 's/IF(/if(/g' -e 's/if (/if(/g' -e 's/ELSE (/else(/g' -e 's/ELSE(/else(/g' -e 's/else (/else(/g' -e 's/ENDif(/endif(/g' -e 's/ELSEif(/elseif(/g' -i c10/**/CMakeLists.txt
sed -e 's/IF (/if(/g' -e 's/IF(/if(/g' -e 's/if (/if(/g' -e 's/ELSE (/else(/g' -e 's/ELSE(/else(/g' -e 's/else (/else(/g' -e 's/ENDif(/endif(/g' -e 's/ELSEif(/elseif(/g' -i cmake/**/*.cmake
sed -e 's/IF (/if(/g' -e 's/IF(/if(/g' -e 's/if (/if(/g' -e 's/ELSE (/else(/g' -e 's/ELSE(/else(/g' -e 's/else (/else(/g' -e 's/ENDif(/endif(/g' -e 's/ELSEif(/elseif(/g' -i cmake/**/*.cmake.in
```
We may further convert all the commands into lowercase according to the following issue: 77543bde41.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/35521

Differential Revision: D20704382

Pulled By: malfet

fbshipit-source-id: 42186b9b1660c34428ab7ceb8d3f7a0ced5d2e80
2020-03-27 14:25:17 -07:00
Yangqing Jia
1ef99cf0ab Intrusive_ptr implementation slower than shared_ptr (#30810)
Summary:
It was a random coding exercise so I wasn't putting much effort into it; but, I was like "hey is the current intrusive_ptr implementation optimized enough?" so I compared it with shared_ptr (using std::shared_from_this).

My benchmark result shows that intrusive_ptr is actually slower. On my macbook the speed is:

```
---------------------------------------------------------------
Benchmark                        Time           CPU Iterations
---------------------------------------------------------------
BM_IntrusivePtrCtorDtor         14 ns         14 ns   52541902
BM_SharedPtrCtorDtor            10 ns         10 ns   71898849
BM_IntrusivePtrArray         14285 ns      14112 ns      49775
BM_SharedPtrArray            13821 ns      13384 ns      51602
```

Wanted to share the results so someone could probably take a look if interested.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/30810

Reviewed By: yinghai

Differential Revision: D18828785

Pulled By: bddppq

fbshipit-source-id: 202e9849c9d8a3da17edbe568572a74bb70cb6c5
2019-12-13 00:25:36 -08:00