mirror of
https://github.com/zebrajr/pytorch.git
synced 2025-12-07 00:21:07 +01:00
Fixes the following issue:
```C++
In file included from /home/gaoxiang/pytorch-ucc/c10/test/util/ConstexprCrc_test.cpp:1:
In file included from /home/gaoxiang/pytorch-ucc/c10/util/ConstexprCrc.h:3:
/home/gaoxiang/pytorch-ucc/c10/util/IdWrapper.h:42:10: error: unknown type name 'size_t'; did you mean 'std::size_t'?
friend size_t hash_value(const concrete_type& v) {
^~~~~~
std::size_t
/usr/bin/../lib64/gcc/x86_64-pc-linux-gnu/12.2.0/../../../../include/c++/12.2.0/x86_64-pc-linux-gnu/bits/c++config.h:298:26: note: 'std::size_t' declared here
typedef __SIZE_TYPE__ size_t;
^
1 error generated.
[111/2069] Generating /home/gaoxiang/pytorch-ucc/torch/csrc/a...ch-ucc/torch/testing/_internal/generated/annotated_fn_args.py
ninja: build stopped: subcommand failed.
```
This error happens with my GCC 12.2.0 + Clang 14.0.6.
Full environment:
```
Collecting environment information...
PyTorch version: 1.13.0a0+git14a53e6
Is debug build: True
CUDA used to build PyTorch: 11.7
ROCM used to build PyTorch: N/A
OS: Arch Linux (x86_64)
GCC version: (GCC) 12.2.0
Clang version: 14.0.6
CMake version: version 3.24.1
Libc version: glibc-2.36
Python version: 3.10.6 (main, Aug 3 2022, 17:39:45) [GCC 12.1.1 20220730] (64-bit runtime)
Python platform: Linux-5.19.3-arch1-1-x86_64-with-glibc2.36
Is CUDA available: True
CUDA runtime version: 11.7.99
GPU models and configuration:
GPU 0: NVIDIA GeForce RTX 3090
GPU 1: NVIDIA GeForce RTX 2080 Ti
Nvidia driver version: 515.65.01
cuDNN version: Probably one of the following:
/usr/lib/libcudnn.so.8.4.1
/usr/lib/libcudnn_adv_infer.so.8.4.1
/usr/lib/libcudnn_adv_train.so.8.4.1
/usr/lib/libcudnn_cnn_infer.so.8.4.1
/usr/lib/libcudnn_cnn_train.so.8.4.1
/usr/lib/libcudnn_ops_infer.so.8.4.1
/usr/lib/libcudnn_ops_train.so.8.4.1
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True
Versions of relevant libraries:
[pip3] numpy==1.23.1
[pip3] torch==1.13.0a0+gitbcc6f6c
[pip3] torch-ucc==1.0.0
[pip3] torchani==2.2
[pip3] torchvision==0.2.2.post3
[conda] Could not collect
```
Pull Request resolved: https://github.com/pytorch/pytorch/pull/84088
Approved by: https://github.com/ezyang
79 lines
2.3 KiB
C++
79 lines
2.3 KiB
C++
#pragma once
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#include <c10/macros/Macros.h>
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#include <cstddef>
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#include <functional>
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#include <utility>
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namespace c10 {
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/**
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* This template simplifies generation of simple classes that wrap an id
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* in a typesafe way. Namely, you can use it to create a very lightweight
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* type that only offers equality comparators and hashing. Example:
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*
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* struct MyIdType final : IdWrapper<MyIdType, uint32_t> {
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* constexpr explicit MyIdType(uint32_t id): IdWrapper(id) {}
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* };
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*
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* Then in the global top level namespace:
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*
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* C10_DEFINE_HASH_FOR_IDWRAPPER(MyIdType);
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*
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* That's it - equality operators and hash functions are automatically defined
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* for you, given the underlying type supports it.
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*/
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template <class ConcreteType, class UnderlyingType>
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class IdWrapper {
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public:
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using underlying_type = UnderlyingType;
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using concrete_type = ConcreteType;
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protected:
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constexpr explicit IdWrapper(underlying_type id) noexcept(
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noexcept(underlying_type(std::declval<underlying_type>())))
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: id_(id) {}
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constexpr underlying_type underlyingId() const
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noexcept(noexcept(underlying_type(std::declval<underlying_type>()))) {
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return id_;
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}
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private:
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friend size_t hash_value(const concrete_type& v) {
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return std::hash<underlying_type>()(v.id_);
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}
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// TODO Making operator== noexcept if underlying type is noexcept equality
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// comparable doesn't work with GCC 4.8.
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// Fix this once we don't need GCC 4.8 anymore.
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friend constexpr bool operator==(
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const concrete_type& lhs,
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const concrete_type& rhs) noexcept {
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return lhs.id_ == rhs.id_;
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}
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// TODO Making operator!= noexcept if operator== is noexcept doesn't work with
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// GCC 4.8.
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// Fix this once we don't need GCC 4.8 anymore.
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friend constexpr bool operator!=(
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const concrete_type& lhs,
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const concrete_type& rhs) noexcept {
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return !(lhs == rhs);
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}
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underlying_type id_;
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};
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} // namespace c10
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#define C10_DEFINE_HASH_FOR_IDWRAPPER(ClassName) \
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namespace std { \
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template <> \
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struct hash<ClassName> { \
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size_t operator()(ClassName x) const { \
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return hash_value(x); \
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} \
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}; \
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}
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