cmake_minimum_required(VERSION 3.26) # When building directly using CMake, make sure you run the install step # (it places the .so files in the correct location). # # Example: # mkdir build && cd build # cmake -G Ninja -DVLLM_PYTHON_EXECUTABLE=`which python3` -DCMAKE_INSTALL_PREFIX=.. .. # cmake --build . --target install # # If you want to only build one target, make sure to install it manually: # cmake --build . --target _C # cmake --install . --component _C project(vllm_extensions LANGUAGES CXX) # CUDA by default, can be overridden by using -DVLLM_TARGET_DEVICE=... (used by setup.py) set(VLLM_TARGET_DEVICE "cuda" CACHE STRING "Target device backend for vLLM") message(STATUS "Build type: ${CMAKE_BUILD_TYPE}") message(STATUS "Target device: ${VLLM_TARGET_DEVICE}") include(${CMAKE_CURRENT_LIST_DIR}/cmake/utils.cmake) # Suppress potential warnings about unused manually-specified variables set(ignoreMe "${VLLM_PYTHON_PATH}") # Prevent installation of dependencies (cutlass) by default. install(CODE "set(CMAKE_INSTALL_LOCAL_ONLY TRUE)" ALL_COMPONENTS) # # Supported python versions. These versions will be searched in order, the # first match will be selected. These should be kept in sync with setup.py. # set(PYTHON_SUPPORTED_VERSIONS "3.9" "3.10" "3.11" "3.12") # Supported NVIDIA architectures. set(CUDA_SUPPORTED_ARCHS "7.0;7.2;7.5;8.0;8.6;8.7;8.9;9.0") # Supported AMD GPU architectures. set(HIP_SUPPORTED_ARCHS "gfx906;gfx908;gfx90a;gfx940;gfx941;gfx942;gfx1030;gfx1100;gfx1101") # # Supported/expected torch versions for CUDA/ROCm. # # Currently, having an incorrect pytorch version results in a warning # rather than an error. # # Note: the CUDA torch version is derived from pyproject.toml and various # requirements.txt files and should be kept consistent. The ROCm torch # versions are derived from Dockerfile.rocm # set(TORCH_SUPPORTED_VERSION_CUDA "2.5.1") set(TORCH_SUPPORTED_VERSION_ROCM "2.5.1") # # Try to find python package with an executable that exactly matches # `VLLM_PYTHON_EXECUTABLE` and is one of the supported versions. # if (VLLM_PYTHON_EXECUTABLE) find_python_from_executable(${VLLM_PYTHON_EXECUTABLE} "${PYTHON_SUPPORTED_VERSIONS}") else() message(FATAL_ERROR "Please set VLLM_PYTHON_EXECUTABLE to the path of the desired python version" " before running cmake configure.") endif() # # Update cmake's `CMAKE_PREFIX_PATH` with torch location. # append_cmake_prefix_path("torch" "torch.utils.cmake_prefix_path") # Ensure the 'nvcc' command is in the PATH find_program(NVCC_EXECUTABLE nvcc) if (CUDA_FOUND AND NOT NVCC_EXECUTABLE) message(FATAL_ERROR "nvcc not found") endif() # # Import torch cmake configuration. # Torch also imports CUDA (and partially HIP) languages with some customizations, # so there is no need to do this explicitly with check_language/enable_language, # etc. # find_package(Torch REQUIRED) # # Forward the non-CUDA device extensions to external CMake scripts. # if (NOT VLLM_TARGET_DEVICE STREQUAL "cuda" AND NOT VLLM_TARGET_DEVICE STREQUAL "rocm") if (VLLM_TARGET_DEVICE STREQUAL "cpu") include(${CMAKE_CURRENT_LIST_DIR}/cmake/cpu_extension.cmake) else() return() endif() return() endif() # # Set up GPU language and check the torch version and warn if it isn't # what is expected. # if (NOT HIP_FOUND AND CUDA_FOUND) set(VLLM_GPU_LANG "CUDA") if (NOT Torch_VERSION VERSION_EQUAL ${TORCH_SUPPORTED_VERSION_CUDA}) message(WARNING "Pytorch version ${TORCH_SUPPORTED_VERSION_CUDA} " "expected for CUDA build, saw ${Torch_VERSION} instead.") endif() elseif(HIP_FOUND) set(VLLM_GPU_LANG "HIP") # Importing torch recognizes and sets up some HIP/ROCm configuration but does # not let cmake recognize .hip files. In order to get cmake to understand the # .hip extension automatically, HIP must be enabled explicitly. enable_language(HIP) # ROCm 5.X and 6.X if (ROCM_VERSION_DEV_MAJOR GREATER_EQUAL 5 AND NOT Torch_VERSION VERSION_EQUAL ${TORCH_SUPPORTED_VERSION_ROCM}) message(WARNING "Pytorch version >= ${TORCH_SUPPORTED_VERSION_ROCM} " "expected for ROCm build, saw ${Torch_VERSION} instead.") endif() else() message(FATAL_ERROR "Can't find CUDA or HIP installation.") endif() if(VLLM_GPU_LANG STREQUAL "CUDA") # # For cuda we want to be able to control which architectures we compile for on # a per-file basis in order to cut down on compile time. So here we extract # the set of architectures we want to compile for and remove the from the # CMAKE_CUDA_FLAGS so that they are not applied globally. # clear_cuda_arches(CUDA_ARCH_FLAGS) extract_unique_cuda_archs_ascending(CUDA_ARCHS "${CUDA_ARCH_FLAGS}") message(STATUS "CUDA target architectures: ${CUDA_ARCHS}") # Filter the target architectures by the supported supported archs # since for some files we will build for all CUDA_ARCHS. cuda_archs_loose_intersection(CUDA_ARCHS "${CUDA_SUPPORTED_ARCHS}" "${CUDA_ARCHS}") message(STATUS "CUDA supported target architectures: ${CUDA_ARCHS}") else() # # For other GPU targets override the GPU architectures detected by cmake/torch # and filter them by the supported versions for the current language. # The final set of arches is stored in `VLLM_GPU_ARCHES`. # override_gpu_arches(VLLM_GPU_ARCHES ${VLLM_GPU_LANG} "${${VLLM_GPU_LANG}_SUPPORTED_ARCHS}") endif() # # Query torch for additional GPU compilation flags for the given # `VLLM_GPU_LANG`. # The final set of arches is stored in `VLLM_GPU_FLAGS`. # get_torch_gpu_compiler_flags(VLLM_GPU_FLAGS ${VLLM_GPU_LANG}) # # Set nvcc parallelism. # if(NVCC_THREADS AND VLLM_GPU_LANG STREQUAL "CUDA") list(APPEND VLLM_GPU_FLAGS "--threads=${NVCC_THREADS}") endif() # # Use FetchContent for C++ dependencies that are compiled as part of vLLM's build process. # setup.py will override FETCHCONTENT_BASE_DIR to play nicely with sccache. # Each dependency that produces build artifacts should override its BINARY_DIR to avoid # conflicts between build types. It should instead be set to ${CMAKE_BINARY_DIR}/. # include(FetchContent) file(MAKE_DIRECTORY ${FETCHCONTENT_BASE_DIR}) # Ensure the directory exists message(STATUS "FetchContent base directory: ${FETCHCONTENT_BASE_DIR}") # # Define other extension targets # # # _C extension # set(VLLM_EXT_SRC "csrc/cache_kernels.cu" "csrc/attention/paged_attention_v1.cu" "csrc/attention/paged_attention_v2.cu" "csrc/pos_encoding_kernels.cu" "csrc/activation_kernels.cu" "csrc/layernorm_kernels.cu" "csrc/layernorm_quant_kernels.cu" "csrc/quantization/gptq/q_gemm.cu" "csrc/quantization/compressed_tensors/int8_quant_kernels.cu" "csrc/quantization/fp8/common.cu" "csrc/quantization/fused_kernels/fused_layernorm_dynamic_per_token_quant.cu" "csrc/quantization/gguf/gguf_kernel.cu" "csrc/cuda_utils_kernels.cu" "csrc/prepare_inputs/advance_step.cu" "csrc/torch_bindings.cpp") if(VLLM_GPU_LANG STREQUAL "CUDA") SET(CUTLASS_ENABLE_HEADERS_ONLY ON CACHE BOOL "Enable only the header library") # Set CUTLASS_REVISION manually -- its revision detection doesn't work in this case. set(CUTLASS_REVISION "v3.6.0" CACHE STRING "CUTLASS revision to use") # Use the specified CUTLASS source directory for compilation if VLLM_CUTLASS_SRC_DIR is provided if (DEFINED ENV{VLLM_CUTLASS_SRC_DIR}) set(VLLM_CUTLASS_SRC_DIR $ENV{VLLM_CUTLASS_SRC_DIR}) endif() if(VLLM_CUTLASS_SRC_DIR) if(NOT IS_ABSOLUTE VLLM_CUTLASS_SRC_DIR) get_filename_component(VLLM_CUTLASS_SRC_DIR "${VLLM_CUTLASS_SRC_DIR}" ABSOLUTE) endif() message(STATUS "The VLLM_CUTLASS_SRC_DIR is set, using ${VLLM_CUTLASS_SRC_DIR} for compilation") FetchContent_Declare(cutlass SOURCE_DIR ${VLLM_CUTLASS_SRC_DIR}) else() FetchContent_Declare( cutlass GIT_REPOSITORY https://github.com/nvidia/cutlass.git GIT_TAG v3.6.0 GIT_PROGRESS TRUE # Speed up CUTLASS download by retrieving only the specified GIT_TAG instead of the history. # Important: If GIT_SHALLOW is enabled then GIT_TAG works only with branch names and tags. # So if the GIT_TAG above is updated to a commit hash, GIT_SHALLOW must be set to FALSE GIT_SHALLOW TRUE ) endif() FetchContent_MakeAvailable(cutlass) list(APPEND VLLM_EXT_SRC "csrc/mamba/mamba_ssm/selective_scan_fwd.cu" "csrc/mamba/causal_conv1d/causal_conv1d.cu" "csrc/quantization/aqlm/gemm_kernels.cu" "csrc/quantization/awq/gemm_kernels.cu" "csrc/custom_all_reduce.cu" "csrc/permute_cols.cu" "csrc/quantization/cutlass_w8a8/scaled_mm_entry.cu" "csrc/sparse/cutlass/sparse_scaled_mm_entry.cu" "csrc/sparse/cutlass/sparse_compressor_entry.cu" "csrc/cutlass_extensions/common.cpp") set_gencode_flags_for_srcs( SRCS "${VLLM_EXT_SRC}" CUDA_ARCHS "${CUDA_ARCHS}") # Only build Marlin kernels if we are building for at least some compatible archs. # Keep building Marlin for 9.0 as there are some group sizes and shapes that # are not supported by Machete yet. cuda_archs_loose_intersection(MARLIN_ARCHS "8.0;8.6;8.7;8.9;9.0" ${CUDA_ARCHS}) if (MARLIN_ARCHS) set(MARLIN_SRCS "csrc/quantization/fp8/fp8_marlin.cu" "csrc/quantization/marlin/dense/marlin_cuda_kernel.cu" "csrc/quantization/marlin/sparse/marlin_24_cuda_kernel.cu" "csrc/quantization/marlin/qqq/marlin_qqq_gemm_kernel.cu" "csrc/quantization/gptq_marlin/gptq_marlin.cu" "csrc/quantization/gptq_marlin/gptq_marlin_repack.cu" "csrc/quantization/gptq_marlin/awq_marlin_repack.cu") set_gencode_flags_for_srcs( SRCS "${MARLIN_SRCS}" CUDA_ARCHS "${MARLIN_ARCHS}") list(APPEND VLLM_EXT_SRC "${MARLIN_SRCS}") message(STATUS "Building Marlin kernels for archs: ${MARLIN_ARCHS}") else() message(STATUS "Not building Marlin kernels as no compatible archs found" " in CUDA target architectures") endif() # The cutlass_scaled_mm kernels for Hopper (c3x, i.e. CUTLASS 3.x) require # CUDA 12.0 or later (and only work on Hopper, 9.0/9.0a for now). cuda_archs_loose_intersection(SCALED_MM_3X_ARCHS "9.0;9.0a" "${CUDA_ARCHS}") if(${CMAKE_CUDA_COMPILER_VERSION} VERSION_GREATER 12.0 AND SCALED_MM_3X_ARCHS) set(SRCS "csrc/quantization/cutlass_w8a8/scaled_mm_c3x.cu") set_gencode_flags_for_srcs( SRCS "${SRCS}" CUDA_ARCHS "${SCALED_MM_3X_ARCHS}") list(APPEND VLLM_EXT_SRC "${SRCS}") list(APPEND VLLM_GPU_FLAGS "-DENABLE_SCALED_MM_C3X=1") message(STATUS "Building scaled_mm_c3x for archs: ${SCALED_MM_3X_ARCHS}") else() if (NOT ${CMAKE_CUDA_COMPILER_VERSION} VERSION_GREATER 12.0 AND SCALED_MM_3X_ARCHS) message(STATUS "Not building scaled_mm_c3x as CUDA Compiler version is " "not >= 12.0, we recommend upgrading to CUDA 12.0 or " "later if you intend on running FP8 quantized models on " "Hopper.") else() message(STATUS "Not building scaled_mm_c3x as no compatible archs found " "in CUDA target architectures") endif() # clear SCALED_MM_3X_ARCHS so the scaled_mm_c2x kernels know we didn't # build any 3x kernels set(SCALED_MM_3X_ARCHS) endif() # # For the cutlass_scaled_mm kernels we want to build the c2x (CUTLASS 2.x) # kernels for the remaining archs that are not already built for 3x. cuda_archs_loose_intersection(SCALED_MM_2X_ARCHS "7.5;8.0;8.6;8.7;8.9;9.0" "${CUDA_ARCHS}") # subtract out the archs that are already built for 3x list(REMOVE_ITEM SCALED_MM_2X_ARCHS ${SCALED_MM_3X_ARCHS}) if (SCALED_MM_2X_ARCHS) set(SRCS "csrc/quantization/cutlass_w8a8/scaled_mm_c2x.cu") set_gencode_flags_for_srcs( SRCS "${SRCS}" CUDA_ARCHS "${SCALED_MM_2X_ARCHS}") list(APPEND VLLM_EXT_SRC "${SRCS}") list(APPEND VLLM_GPU_FLAGS "-DENABLE_SCALED_MM_C2X=1") message(STATUS "Building scaled_mm_c2x for archs: ${SCALED_MM_2X_ARCHS}") else() if (SCALED_MM_3X_ARCHS) message(STATUS "Not building scaled_mm_c2x as all archs are already built" " for and covered by scaled_mm_c3x") else() message(STATUS "Not building scaled_mm_c2x as no compatible archs found " "in CUDA target architectures") endif() endif() # # 2:4 Sparse Kernels # The 2:4 sparse kernels cutlass_scaled_sparse_mm and cutlass_compressor # require CUDA 12.2 or later (and only work on Hopper, 9.0/9.0a for now). if(${CMAKE_CUDA_COMPILER_VERSION} VERSION_GREATER 12.2 AND SCALED_MM_3X_ARCHS) set(SRCS "csrc/sparse/cutlass/sparse_compressor_c3x.cu" "csrc/sparse/cutlass/sparse_scaled_mm_c3x.cu") set_gencode_flags_for_srcs( SRCS "${SRCS}" CUDA_ARCHS "${SCALED_MM_3X_ARCHS}") list(APPEND VLLM_EXT_SRC "${SRCS}") list(APPEND VLLM_GPU_FLAGS "-DENABLE_SPARSE_SCALED_MM_C3X=1") message(STATUS "Building sparse_scaled_mm_c3x for archs: ${SCALED_MM_3X_ARCHS}") else() if (NOT ${CMAKE_CUDA_COMPILER_VERSION} VERSION_GREATER 12.2 AND SCALED_MM_3X_ARCHS) message(STATUS "Not building sparse_scaled_mm_c3x kernels as CUDA Compiler version is " "not >= 12.2, we recommend upgrading to CUDA 12.2 or later " "if you intend on running FP8 sparse quantized models on Hopper.") else() message(STATUS "Not building sparse_scaled_mm_c3x as no compatible archs found " "in CUDA target architectures") endif() endif() # # Machete kernels # The machete kernels only work on hopper and require CUDA 12.0 or later. # Only build Machete kernels if we are building for something compatible with sm90a cuda_archs_loose_intersection(MACHETE_ARCHS "9.0a" "${CUDA_ARCHS}") if(${CMAKE_CUDA_COMPILER_VERSION} VERSION_GREATER 12.0 AND MACHETE_ARCHS) # # For the Machete kernels we automatically generate sources for various # preselected input type pairs and schedules. # Generate sources: set(MACHETE_GEN_SCRIPT ${CMAKE_CURRENT_SOURCE_DIR}/csrc/quantization/machete/generate.py) file(MD5 ${MACHETE_GEN_SCRIPT} MACHETE_GEN_SCRIPT_HASH) message(STATUS "Machete generation script hash: ${MACHETE_GEN_SCRIPT_HASH}") message(STATUS "Last run machete generate script hash: $CACHE{MACHETE_GEN_SCRIPT_HASH}") if (NOT DEFINED CACHE{MACHETE_GEN_SCRIPT_HASH} OR NOT $CACHE{MACHETE_GEN_SCRIPT_HASH} STREQUAL ${MACHETE_GEN_SCRIPT_HASH}) execute_process( COMMAND ${CMAKE_COMMAND} -E env PYTHONPATH=${CMAKE_CURRENT_SOURCE_DIR}/csrc/cutlass_extensions/:${CUTLASS_DIR}/python/:${VLLM_PYTHON_PATH}:$PYTHONPATH ${Python_EXECUTABLE} ${MACHETE_GEN_SCRIPT} RESULT_VARIABLE machete_generation_result OUTPUT_VARIABLE machete_generation_output OUTPUT_FILE ${CMAKE_CURRENT_BINARY_DIR}/machete_generation.log ERROR_FILE ${CMAKE_CURRENT_BINARY_DIR}/machete_generation.log ) if (NOT machete_generation_result EQUAL 0) message(FATAL_ERROR "Machete generation failed." " Result: \"${machete_generation_result}\"" "\nCheck the log for details: " "${CMAKE_CURRENT_BINARY_DIR}/machete_generation.log") else() set(MACHETE_GEN_SCRIPT_HASH ${MACHETE_GEN_SCRIPT_HASH} CACHE STRING "Last run machete generate script hash" FORCE) message(STATUS "Machete generation completed successfully.") endif() else() message(STATUS "Machete generation script has not changed, skipping generation.") endif() # Add machete generated sources file(GLOB MACHETE_GEN_SOURCES "csrc/quantization/machete/generated/*.cu") list(APPEND VLLM_EXT_SRC ${MACHETE_GEN_SOURCES}) # forward compatible set_gencode_flags_for_srcs( SRCS "${MACHETE_GEN_SOURCES}" CUDA_ARCHS "${MACHETE_ARCHS}") list(APPEND VLLM_EXT_SRC csrc/quantization/machete/machete_pytorch.cu) message(STATUS "Building Machete kernels for archs: ${MACHETE_ARCHS}") else() if (NOT ${CMAKE_CUDA_COMPILER_VERSION} VERSION_GREATER 12.0 AND MACHETE_ARCHS) message(STATUS "Not building Machete kernels as CUDA Compiler version is " "not >= 12.0, we recommend upgrading to CUDA 12.0 or " "later if you intend on running w4a16 quantized models on " "Hopper.") else() message(STATUS "Not building Machete kernels as no compatible archs " "found in CUDA target architectures") endif() endif() # if CUDA endif endif() message(STATUS "Enabling C extension.") define_gpu_extension_target( _C DESTINATION vllm LANGUAGE ${VLLM_GPU_LANG} SOURCES ${VLLM_EXT_SRC} COMPILE_FLAGS ${VLLM_GPU_FLAGS} ARCHITECTURES ${VLLM_GPU_ARCHES} INCLUDE_DIRECTORIES ${CUTLASS_INCLUDE_DIR};${CUTLASS_TOOLS_UTIL_INCLUDE_DIR} USE_SABI 3 WITH_SOABI) # If CUTLASS is compiled on NVCC >= 12.5, it by default uses # cudaGetDriverEntryPointByVersion as a wrapper to avoid directly calling the # driver API. This causes problems when linking with earlier versions of CUDA. # Setting this variable sidesteps the issue by calling the driver directly. target_compile_definitions(_C PRIVATE CUTLASS_ENABLE_DIRECT_CUDA_DRIVER_CALL=1) # # _moe_C extension # set(VLLM_MOE_EXT_SRC "csrc/moe/torch_bindings.cpp" "csrc/moe/moe_align_sum_kernels.cu" "csrc/moe/topk_softmax_kernels.cu") set_gencode_flags_for_srcs( SRCS "${VLLM_MOE_EXT_SRC}" CUDA_ARCHS "${CUDA_ARCHS}") if(VLLM_GPU_LANG STREQUAL "CUDA") cuda_archs_loose_intersection(MARLIN_MOE_ARCHS "8.0;8.6;8.7;8.9;9.0" "${CUDA_ARCHS}") if (MARLIN_MOE_ARCHS) set(MARLIN_MOE_SRC "csrc/moe/marlin_kernels/marlin_moe_kernel.h" "csrc/moe/marlin_kernels/marlin_moe_kernel_ku4b8.h" "csrc/moe/marlin_kernels/marlin_moe_kernel_ku4b8.cu" "csrc/moe/marlin_kernels/marlin_moe_kernel_ku8b128.h" "csrc/moe/marlin_kernels/marlin_moe_kernel_ku8b128.cu" "csrc/moe/marlin_kernels/marlin_moe_kernel_ku4.h" "csrc/moe/marlin_kernels/marlin_moe_kernel_ku4.cu" "csrc/moe/marlin_moe_ops.cu") set_gencode_flags_for_srcs( SRCS "${MARLIN_MOE_SRC}" CUDA_ARCHS "${MARLIN_MOE_ARCHS}") list(APPEND VLLM_MOE_EXT_SRC "${MARLIN_MOE_SRC}") message(STATUS "Building Marlin MOE kernels for archs: ${MARLIN_MOE_ARCHS}") else() message(STATUS "Not building Marlin MOE kernels as no compatible archs found" " in CUDA target architectures") endif() endif() message(STATUS "Enabling moe extension.") define_gpu_extension_target( _moe_C DESTINATION vllm LANGUAGE ${VLLM_GPU_LANG} SOURCES ${VLLM_MOE_EXT_SRC} COMPILE_FLAGS ${VLLM_GPU_FLAGS} ARCHITECTURES ${VLLM_GPU_ARCHES} USE_SABI 3 WITH_SOABI) if(VLLM_GPU_LANG STREQUAL "HIP") # # _rocm_C extension # set(VLLM_ROCM_EXT_SRC "csrc/rocm/torch_bindings.cpp" "csrc/rocm/attention.cu") define_gpu_extension_target( _rocm_C DESTINATION vllm LANGUAGE ${VLLM_GPU_LANG} SOURCES ${VLLM_ROCM_EXT_SRC} COMPILE_FLAGS ${VLLM_GPU_FLAGS} ARCHITECTURES ${VLLM_GPU_ARCHES} USE_SABI 3 WITH_SOABI) endif() # vllm-flash-attn currently only supported on CUDA if (NOT VLLM_TARGET_DEVICE STREQUAL "cuda") return() endif () # vLLM flash attention requires VLLM_GPU_ARCHES to contain the set of target # arches in the CMake syntax (75-real, 89-virtual, etc), since we clear the # arches in the CUDA case (and instead set the gencodes on a per file basis) # we need to manually set VLLM_GPU_ARCHES here. if(VLLM_GPU_LANG STREQUAL "CUDA") foreach(_ARCH ${CUDA_ARCHS}) string(REPLACE "." "" _ARCH "${_ARCH}") list(APPEND VLLM_GPU_ARCHES "${_ARCH}-real") endforeach() endif() # # Build vLLM flash attention from source # # IMPORTANT: This has to be the last thing we do, because vllm-flash-attn uses the same macros/functions as vLLM. # Because functions all belong to the global scope, vllm-flash-attn's functions overwrite vLLMs. # They should be identical but if they aren't, this is a massive footgun. # # The vllm-flash-attn install rules are nested under vllm to make sure the library gets installed in the correct place. # To only install vllm-flash-attn, use --component vllm_flash_attn_c. # If no component is specified, vllm-flash-attn is still installed. # If VLLM_FLASH_ATTN_SRC_DIR is set, vllm-flash-attn is installed from that directory instead of downloading. # This is to enable local development of vllm-flash-attn within vLLM. # It can be set as an environment variable or passed as a cmake argument. # The environment variable takes precedence. if (DEFINED ENV{VLLM_FLASH_ATTN_SRC_DIR}) set(VLLM_FLASH_ATTN_SRC_DIR $ENV{VLLM_FLASH_ATTN_SRC_DIR}) endif() if(VLLM_FLASH_ATTN_SRC_DIR) FetchContent_Declare(vllm-flash-attn SOURCE_DIR ${VLLM_FLASH_ATTN_SRC_DIR}) else() FetchContent_Declare( vllm-flash-attn GIT_REPOSITORY https://github.com/vllm-project/flash-attention.git GIT_TAG 96266b1111111f3d11aabefaf3bacbab6a89d03c GIT_PROGRESS TRUE # Don't share the vllm-flash-attn build between build types BINARY_DIR ${CMAKE_BINARY_DIR}/vllm-flash-attn ) endif() # Set the parent build flag so that the vllm-flash-attn library does not redo compile flag and arch initialization. set(VLLM_PARENT_BUILD ON) # Ensure the vllm/vllm_flash_attn directory exists before installation install(CODE "file(MAKE_DIRECTORY \"\${CMAKE_INSTALL_PREFIX}/vllm/vllm_flash_attn\")" COMPONENT vllm_flash_attn_c) # Make sure vllm-flash-attn install rules are nested under vllm/ install(CODE "set(CMAKE_INSTALL_LOCAL_ONLY FALSE)" COMPONENT vllm_flash_attn_c) install(CODE "set(OLD_CMAKE_INSTALL_PREFIX \"\${CMAKE_INSTALL_PREFIX}\")" COMPONENT vllm_flash_attn_c) install(CODE "set(CMAKE_INSTALL_PREFIX \"\${CMAKE_INSTALL_PREFIX}/vllm/\")" COMPONENT vllm_flash_attn_c) # Fetch the vllm-flash-attn library FetchContent_MakeAvailable(vllm-flash-attn) message(STATUS "vllm-flash-attn is available at ${vllm-flash-attn_SOURCE_DIR}") # Restore the install prefix install(CODE "set(CMAKE_INSTALL_PREFIX \"\${OLD_CMAKE_INSTALL_PREFIX}\")" COMPONENT vllm_flash_attn_c) install(CODE "set(CMAKE_INSTALL_LOCAL_ONLY TRUE)" COMPONENT vllm_flash_attn_c) # Copy over the vllm-flash-attn python files install( DIRECTORY ${vllm-flash-attn_SOURCE_DIR}/vllm_flash_attn/ DESTINATION vllm/vllm_flash_attn COMPONENT vllm_flash_attn_c FILES_MATCHING PATTERN "*.py" ) # Nothing after vllm-flash-attn, see comment about macros above