diff options
author | V3n3RiX <venerix@koprulu.sector> | 2024-08-07 12:37:21 +0100 |
---|---|---|
committer | V3n3RiX <venerix@koprulu.sector> | 2024-08-07 12:37:21 +0100 |
commit | b8c7370a682e4e29cda623222d17a790c01c3642 (patch) | |
tree | f6caa14689bd00a5760eadaa381ff41e50ef3c1b /sci-libs/caffe2/files | |
parent | 8a4997a7e2d1e36c089d4d76935b5a902d98d3d0 (diff) |
gentoo auto-resync : 07:08:2024 - 12:37:20
Diffstat (limited to 'sci-libs/caffe2/files')
5 files changed, 329 insertions, 0 deletions
diff --git a/sci-libs/caffe2/files/caffe2-2.3.0-exclude-aotriton.patch b/sci-libs/caffe2/files/caffe2-2.3.0-exclude-aotriton.patch new file mode 100644 index 000000000000..2c65987acd85 --- /dev/null +++ b/sci-libs/caffe2/files/caffe2-2.3.0-exclude-aotriton.patch @@ -0,0 +1,35 @@ +Disables aotriton download when both USE_FLASH_ATTENTION and USE_MEM_EFF_ATTENTION cmake flags are OFF +Backports upstream PR to 2.3.0: https://github.com/pytorch/pytorch/pull/130197 +--- a/cmake/Dependencies.cmake ++++ b/cmake/Dependencies.cmake +@@ -1334,7 +1334,9 @@ if(USE_ROCM) + message(STATUS "Disabling Kernel Assert for ROCm") + endif() + +- include(${CMAKE_CURRENT_LIST_DIR}/External/aotriton.cmake) ++ if(USE_FLASH_ATTENTION) ++ include(${CMAKE_CURRENT_LIST_DIR}/External/aotriton.cmake) ++ endif() + if(USE_CUDA) + caffe2_update_option(USE_MEM_EFF_ATTENTION OFF) + endif() +--- a/aten/src/ATen/native/transformers/cuda/sdp_utils.cpp ++++ b/aten/src/ATen/native/transformers/cuda/sdp_utils.cpp +@@ -21,7 +21,7 @@ + #include <cmath> + #include <functional> + +-#if USE_ROCM ++#if defined(USE_ROCM) && defined(USE_FLASH_ATTENTION) + #include <aotriton/flash.h> + #endif + +@@ -186,7 +186,7 @@ bool check_flash_attention_hardware_support(sdp_params const& params, bool debug + // Check that the gpu is capable of running flash attention + using sm80 = SMVersion<8, 0>; + using sm90 = SMVersion<9, 0>; +-#if USE_ROCM ++#if defined(USE_ROCM) && defined(USE_FLASH_ATTENTION) + auto stream = at::cuda::getCurrentCUDAStream().stream(); + if (hipSuccess != aotriton::v2::flash::check_gpu(stream)) { + auto dprops = at::cuda::getCurrentDeviceProperties(); diff --git a/sci-libs/caffe2/files/caffe2-2.3.0-fix-gcc-clang-abi-compat.patch b/sci-libs/caffe2/files/caffe2-2.3.0-fix-gcc-clang-abi-compat.patch new file mode 100644 index 000000000000..a6f981b7e054 --- /dev/null +++ b/sci-libs/caffe2/files/caffe2-2.3.0-fix-gcc-clang-abi-compat.patch @@ -0,0 +1,17 @@ + +When gcc builds libtorch_cpu.so and hipcc (clang-18) build libtorch_hip.so, +resulting binary fails in runtime due to different mangling. +Related issue in LLVM: https://github.com/llvm/llvm-project/issues/85656 +Fixed in pytorch-2.4.0 in https://github.com/pytorch/pytorch/commit/a89f442f0b103fa6f38103784a2dfedbd147f863 +--- a/cmake/Dependencies.cmake ++++ b/cmake/Dependencies.cmake +@@ -1314,6 +1314,9 @@ if(USE_ROCM) + list(APPEND HIP_HIPCC_FLAGS -fdebug-info-for-profiling) + endif(CMAKE_BUILD_TYPE MATCHES Debug) + ++ # needed for compat with newer versions of hip-clang that introduced C++20 mangling rules ++ list(APPEND HIP_HIPCC_FLAGS -fclang-abi-compat=17) ++ + set(HIP_CLANG_FLAGS ${HIP_CXX_FLAGS}) + # Ask hcc to generate device code during compilation so we can use + # host linker to link. diff --git a/sci-libs/caffe2/files/caffe2-2.3.0-fix-libcpp.patch b/sci-libs/caffe2/files/caffe2-2.3.0-fix-libcpp.patch new file mode 100644 index 000000000000..75808fd7ec50 --- /dev/null +++ b/sci-libs/caffe2/files/caffe2-2.3.0-fix-libcpp.patch @@ -0,0 +1,24 @@ +Workaround for libc++ issue https://github.com/llvm/llvm-project/issues/100802 +"reference to __host__ function 'memcpy' in __device__ function" +--- a/c10/util/Half.h ++++ b/c10/util/Half.h +@@ -227,7 +227,7 @@ C10_HOST_DEVICE inline float fp16_ieee_to_fp32_value(uint16_t h) { + // const float exp_scale = 0x1.0p-112f; + constexpr uint32_t scale_bits = (uint32_t)15 << 23; + float exp_scale_val = 0; +- std::memcpy(&exp_scale_val, &scale_bits, sizeof(exp_scale_val)); ++ memcpy(&exp_scale_val, &scale_bits, sizeof(exp_scale_val)); + const float exp_scale = exp_scale_val; + const float normalized_value = + fp32_from_bits((two_w >> 4) + exp_offset) * exp_scale; +@@ -298,8 +298,8 @@ inline uint16_t fp16_ieee_from_fp32_value(float f) { + constexpr uint32_t scale_to_inf_bits = (uint32_t)239 << 23; + constexpr uint32_t scale_to_zero_bits = (uint32_t)17 << 23; + float scale_to_inf_val = 0, scale_to_zero_val = 0; +- std::memcpy(&scale_to_inf_val, &scale_to_inf_bits, sizeof(scale_to_inf_val)); +- std::memcpy( ++ memcpy(&scale_to_inf_val, &scale_to_inf_bits, sizeof(scale_to_inf_val)); ++ memcpy( + &scale_to_zero_val, &scale_to_zero_bits, sizeof(scale_to_zero_val)); + const float scale_to_inf = scale_to_inf_val; + const float scale_to_zero = scale_to_zero_val; diff --git a/sci-libs/caffe2/files/caffe2-2.3.0-fix-rocm-gcc14-clamp.patch b/sci-libs/caffe2/files/caffe2-2.3.0-fix-rocm-gcc14-clamp.patch new file mode 100644 index 000000000000..81ae075c67cc --- /dev/null +++ b/sci-libs/caffe2/files/caffe2-2.3.0-fix-rocm-gcc14-clamp.patch @@ -0,0 +1,18 @@ +Fix hip compilation with gcc-14 +Upstream commit: https://github.com/pytorch/pytorch/commit/8c2c3a03fb87c3568a22362d83b00d82b9fb3db2 +--- a/aten/src/ATen/native/cuda/IndexKernel.cu ++++ b/aten/src/ATen/native/cuda/IndexKernel.cu +@@ -259,7 +259,13 @@ void index_put_kernel_quantized_cuda(TensorIterator& iter, const IntArrayRef ind + + gpu_index_kernel(iter, index_size, index_stride, [inv_scale, zero_point, qmin, qmax]C10_DEVICE(char* const out_data, const char* const in_data, const int64_t offset) { + int64_t qvalue = static_cast<int64_t>(zero_point + nearbyintf(*(float*)in_data * inv_scale)); ++ // See https://github.com/pytorch/pytorch/issues/127666 ++ // hip-clang std::clamp __glibcxx_assert_fail host function when building on Fedora40/gcc14 ++#ifndef USE_ROCM + qvalue = std::clamp(qvalue, qmin, qmax); ++#else ++ qvalue = (qvalue < qmin) ? qmin : (qmax < qvalue) ? qmax : qvalue; ++#endif + *(scalar_t*)(out_data + offset) = static_cast<scalar_t>(qvalue); + }); + }); diff --git a/sci-libs/caffe2/files/caffe2-2.3.0-optional-hipblaslt.patch b/sci-libs/caffe2/files/caffe2-2.3.0-optional-hipblaslt.patch new file mode 100644 index 000000000000..dc544255c2bd --- /dev/null +++ b/sci-libs/caffe2/files/caffe2-2.3.0-optional-hipblaslt.patch @@ -0,0 +1,235 @@ +Makes hipblaslt optional to simplify build for non-datacenter GPUs. +Based on https://github.com/pytorch/pytorch/pull/120551 with added USE_HIPBLASLT cmake option. +--- a/CMakeLists.txt ++++ b/CMakeLists.txt +@@ -225,6 +225,9 @@ option(USE_FAKELOWP "Use FakeLowp operators" OFF) + option(USE_FFMPEG "Use ffmpeg" OFF) + option(USE_GFLAGS "Use GFLAGS" OFF) + option(USE_GLOG "Use GLOG" OFF) ++cmake_dependent_option( ++ USE_HIPBLASLT "Use hipBLASLt" ON ++ "USE_ROCM" OFF) + option(USE_LEVELDB "Use LEVELDB" OFF) + option(USE_LITE_PROTO "Use lite protobuf instead of full." OFF) + option(USE_LMDB "Use LMDB" OFF) +--- a/aten/src/ATen/cuda/CUDABlas.cpp ++++ b/aten/src/ATen/cuda/CUDABlas.cpp +@@ -14,7 +14,7 @@ + #include <c10/util/irange.h> + + #ifdef USE_ROCM +-#if ROCM_VERSION >= 60000 ++#ifdef USE_HIPBLASLT + #include <hipblaslt/hipblaslt-ext.hpp> + #endif + // until hipblas has an API to accept flags, we must use rocblas here +@@ -781,7 +781,7 @@ void gemm<at::BFloat16>(CUDABLAS_GEMM_ARGTYPES(at::BFloat16)) { + } + } + +-#if (!defined(USE_ROCM) && !defined(_MSC_VER)) || (defined(USE_ROCM) && ROCM_VERSION >= 50700) ++#if (!defined(USE_ROCM) && !defined(_MSC_VER)) || (defined(USE_ROCM) && defined(USE_HIPBLASLT)) + + #if defined(USE_ROCM) && ROCM_VERSION >= 50700 && ROCM_VERSION < 60000 + // only for rocm 5.7 where we first supported hipblaslt, it was difficult +@@ -912,6 +912,7 @@ class CuBlasLtMatmulPreference : public CuBlasLtDescriptor< + }; + } // namespace + ++#if (!defined(USE_ROCM) && !defined(_MSC_VER)) || (defined(USE_ROCM) && defined(USE_HIPBLASLT)) + template <typename Dtype> + void gemm_and_bias( + bool transpose_mat1, +@@ -1124,7 +1125,7 @@ template void gemm_and_bias( + at::BFloat16* result_ptr, + int64_t result_ld, + GEMMAndBiasActivationEpilogue activation); +- ++#endif + void scaled_gemm( + char transa, + char transb, +--- a/aten/src/ATen/cuda/CUDABlas.h ++++ b/aten/src/ATen/cuda/CUDABlas.h +@@ -82,7 +82,7 @@ void gemm_internal<at::Half>(CUDABLAS_GEMM_ARGTYPES(at::Half)); + template <> + void gemm_internal<at::BFloat16>(CUDABLAS_GEMM_ARGTYPES(at::BFloat16)); + +-#if (!defined(USE_ROCM) && !defined(_MSC_VER)) || (defined(USE_ROCM) && ROCM_VERSION >= 50700) ++#if (!defined(USE_ROCM) && !defined(_MSC_VER)) || (defined(USE_ROCM) && defined(USE_HIPBLASLT)) + enum GEMMAndBiasActivationEpilogue { + None, + RELU, +--- a/aten/src/ATen/cuda/CUDAContextLight.h ++++ b/aten/src/ATen/cuda/CUDAContextLight.h +@@ -9,7 +9,7 @@ + + // cublasLT was introduced in CUDA 10.1 but we enable only for 11.1 that also + // added bf16 support +-#if (!defined(USE_ROCM) && !defined(_MSC_VER)) || (defined(USE_ROCM) && ROCM_VERSION >= 50700) ++#if (!defined(USE_ROCM) && !defined(_MSC_VER)) || (defined(USE_ROCM) && defined(USE_HIPBLASLT)) + #include <cublasLt.h> + #endif + +@@ -82,7 +82,7 @@ TORCH_CUDA_CPP_API c10::Allocator* getCUDADeviceAllocator(); + /* Handles */ + TORCH_CUDA_CPP_API cusparseHandle_t getCurrentCUDASparseHandle(); + TORCH_CUDA_CPP_API cublasHandle_t getCurrentCUDABlasHandle(); +-#if (!defined(USE_ROCM) && !defined(_MSC_VER)) || (defined(USE_ROCM) && ROCM_VERSION >= 50700) ++#if (!defined(USE_ROCM) && !defined(_MSC_VER)) || (defined(USE_ROCM) && defined(USE_HIPBLASLT)) + TORCH_CUDA_CPP_API cublasLtHandle_t getCurrentCUDABlasLtHandle(); + #endif + +--- a/aten/src/ATen/cuda/CublasHandlePool.cpp ++++ b/aten/src/ATen/cuda/CublasHandlePool.cpp +@@ -29,7 +29,7 @@ namespace at::cuda { + + namespace { + +-#if defined(USE_ROCM) && ROCM_VERSION >= 50700 ++#if defined(USE_ROCM) && defined(USE_HIPBLASLT) + void createCublasLtHandle(cublasLtHandle_t *handle) { + TORCH_CUDABLAS_CHECK(cublasLtCreate(handle)); + } +@@ -190,7 +190,7 @@ cublasHandle_t getCurrentCUDABlasHandle() { + return handle; + } + +-#if (!defined(USE_ROCM) && !defined(_MSC_VER)) || (defined(USE_ROCM) && ROCM_VERSION >= 50700) ++#if (!defined(USE_ROCM) && !defined(_MSC_VER)) || (defined(USE_ROCM) && defined(USE_HIPBLASLT)) + cublasLtHandle_t getCurrentCUDABlasLtHandle() { + #ifdef USE_ROCM + c10::DeviceIndex device = 0; +--- a/aten/src/ATen/cuda/tunable/TunableGemm.h ++++ b/aten/src/ATen/cuda/tunable/TunableGemm.h +@@ -11,7 +11,7 @@ + + #include <ATen/cuda/tunable/GemmCommon.h> + #ifdef USE_ROCM +-#if ROCM_VERSION >= 50700 ++#ifdef USE_HIPBLASLT + #include <ATen/cuda/tunable/GemmHipblaslt.h> + #endif + #include <ATen/cuda/tunable/GemmRocblas.h> +@@ -166,7 +166,7 @@ class GemmTunableOp : public TunableOp<GemmParams<T>, StreamTimer> { + } + #endif + +-#if defined(USE_ROCM) && ROCM_VERSION >= 50700 ++#if defined(USE_ROCM) && defined(USE_HIPBLASLT) + static const char *env = std::getenv("PYTORCH_TUNABLEOP_HIPBLASLT_ENABLED"); + if (env == nullptr || strcmp(env, "1") == 0) { + // disallow tuning of hipblaslt with c10::complex +@@ -240,7 +240,7 @@ class GemmStridedBatchedTunableOp : public TunableOp<GemmStridedBatchedParams<T> + } + #endif + +-#if defined(USE_ROCM) && ROCM_VERSION >= 50700 ++#if defined(USE_ROCM) && defined(USE_HIPBLASLT) + static const char *env = std::getenv("PYTORCH_TUNABLEOP_HIPBLASLT_ENABLED"); + if (env == nullptr || strcmp(env, "1") == 0) { + // disallow tuning of hipblaslt with c10::complex +--- a/aten/src/ATen/native/cuda/Blas.cpp ++++ b/aten/src/ATen/native/cuda/Blas.cpp +@@ -155,7 +155,7 @@ enum class Activation { + GELU, + }; + +-#if (!defined(USE_ROCM) && !defined(_MSC_VER)) || (defined(USE_ROCM) && ROCM_VERSION >= 50700) ++#if (!defined(USE_ROCM) && !defined(_MSC_VER)) || (defined(USE_ROCM) && defined(USE_HIPBLASLT)) + cuda::blas::GEMMAndBiasActivationEpilogue activation_to_gemm_and_blas_arg(Activation a) { + switch (a) { + case Activation::None: +@@ -193,6 +193,7 @@ static bool getDisableAddmmCudaLt() { + + #ifdef USE_ROCM + static bool isSupportedHipLtROCmArch(int index) { ++#if defined(USE_HIPBLASLT) + hipDeviceProp_t* prop = at::cuda::getDeviceProperties(index); + std::string device_arch = prop->gcnArchName; + static const std::vector<std::string> archs = {"gfx90a", "gfx940", "gfx941", "gfx942"}; +@@ -203,6 +204,7 @@ static bool isSupportedHipLtROCmArch(int index) { + } + } + TORCH_CHECK(false, "Attempting to use hipBLASLt on a unsupported architecture!"); ++#endif + return false; + } + #endif +@@ -228,7 +230,7 @@ Tensor& addmm_out_cuda_impl(Tensor& result, const Tensor& self, const Tensor& ma + at::ScalarType scalar_type = self.scalar_type(); + c10::MaybeOwned<Tensor> self_; + if (&result != &self) { +-#if (defined(CUDA_VERSION) && CUDA_VERSION >= 11040 && !defined(_MSC_VER)) || defined(USE_ROCM) && ROCM_VERSION >= 50700 ++#if (defined(CUDA_VERSION) && CUDA_VERSION >= 11040 && !defined(_MSC_VER)) || defined(USE_ROCM) && defined(USE_HIPBLASLT) + // Strangely, if mat2 has only 1 row or column, we get + // CUBLAS_STATUS_INVALID_VALUE error from cublasLtMatmulAlgoGetHeuristic. + // self.dim() == 1 && result.dim() == 2 && self.sizes()[0] == mat2_sizes[1] +@@ -271,7 +273,7 @@ Tensor& addmm_out_cuda_impl(Tensor& result, const Tensor& self, const Tensor& ma + } + self__sizes = self_->sizes(); + } else { +-#if defined(USE_ROCM) && ROCM_VERSION >= 50700 ++#if defined(USE_ROCM) && defined(USE_HIPBLASLT) + useLtInterface = !disable_addmm_cuda_lt && + result.dim() == 2 && result.is_contiguous() && + isSupportedHipLtROCmArch(self.device().index()) && +@@ -322,7 +324,7 @@ Tensor& addmm_out_cuda_impl(Tensor& result, const Tensor& self, const Tensor& ma + + TORCH_INTERNAL_ASSERT_DEBUG_ONLY(!args.result->is_conj()); + +-#if (!defined(USE_ROCM) && !defined(_MSC_VER)) || (defined(USE_ROCM) && ROCM_VERSION >= 50700) ++#if (!defined(USE_ROCM) && !defined(_MSC_VER)) || (defined(USE_ROCM) && defined(USE_HIPBLASLT)) + if (useLtInterface) { + AT_DISPATCH_FLOATING_TYPES_AND2( + at::ScalarType::Half, +@@ -876,7 +878,7 @@ _scaled_mm_out_cuda(const Tensor& mat1, const Tensor& mat2, + at::native::resize_output(out, {mat1_sizes[0], mat2_sizes[1]}); + at::native::resize_output(amax, {}); + +-#if !defined(USE_ROCM) && !defined(_MSC_VER) || (defined(USE_ROCM) && ROCM_VERSION >= 60000) ++#if !defined(USE_ROCM) && !defined(_MSC_VER) || (defined(USE_ROCM) && defined(USE_HIPBLASLT)) + cublasCommonArgs args(mat1, mat2, out); + const auto out_dtype_ = args.result->scalar_type(); + TORCH_CHECK(args.transa == 't' && args.transb == 'n', "Only multiplication of row-major and column-major matrices is supported by cuBLASLt"); +@@ -906,7 +908,7 @@ _scaled_mm_out_cuda(const Tensor& mat1, const Tensor& mat2, + TORCH_CHECK(false, "_scaled_mm_out_cuda is not compiled for this platform."); + #endif + +-#if defined(USE_ROCM) && ROCM_VERSION >= 60000 ++#if defined(USE_ROCM) && defined(USE_HIPBLASLT) + // rocm's hipblaslt does not yet support amax, so calculate separately + auto out_float32 = out.to(kFloat); + out_float32.abs_(); +--- a/cmake/Dependencies.cmake ++++ b/cmake/Dependencies.cmake +@@ -1282,6 +1282,9 @@ if(USE_ROCM) + if(ROCM_VERSION_DEV VERSION_GREATER_EQUAL "6.0.0") + list(APPEND HIP_CXX_FLAGS -DHIPBLAS_V2) + endif() ++ if(hipblast_FOUND) ++ list(APPEND HIP_CXX_FLAGS -DHIPBLASLT) ++ endif() + if(HIPBLASLT_CUSTOM_DATA_TYPE) + list(APPEND HIP_CXX_FLAGS -DHIPBLASLT_CUSTOM_DATA_TYPE) + endif() +--- a/cmake/public/LoadHIP.cmake ++++ b/cmake/public/LoadHIP.cmake +@@ -155,7 +155,7 @@ if(HIP_FOUND) + find_package_and_print_version(hiprand REQUIRED) + find_package_and_print_version(rocblas REQUIRED) + find_package_and_print_version(hipblas REQUIRED) +- if(ROCM_VERSION_DEV VERSION_GREATER_EQUAL "5.7.0") ++ if(ROCM_VERSION_DEV VERSION_GREATER_EQUAL "5.7.0" AND USE_HIPBLASLT) + find_package_and_print_version(hipblaslt REQUIRED) + endif() + find_package_and_print_version(miopen REQUIRED) +@@ -191,7 +191,7 @@ if(HIP_FOUND) + # roctx is part of roctracer + find_library(ROCM_ROCTX_LIB roctx64 HINTS ${ROCM_PATH}/lib) + +- if(ROCM_VERSION_DEV VERSION_GREATER_EQUAL "5.7.0") ++ if(hipblastlt_FOUND) + # check whether hipblaslt is using its own datatype + set(file "${PROJECT_BINARY_DIR}/hipblaslt_test_data_type.cc") + file(WRITE ${file} "" |