feature: allow all BLA_VENDOR to be assigned in cmake arguments. align with whisper.cpp pr 927
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zenix
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0926278434
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4 changed files with 26 additions and 47 deletions
2
BLIS.md
2
BLIS.md
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@ -39,7 +39,7 @@ CMake:
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```bash
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```bash
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mkdir build
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mkdir build
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cd build
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cd build
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cmake -DLLAMA_BLIS=ON ..
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cmake -DLLAMA_BLAS=ON -DLLAMA_BLAS_VENDOR=FLAME ..
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make -j
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make -j
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```
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```
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@ -1,4 +1,4 @@
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cmake_minimum_required(VERSION 3.12) # Don't bump this version for no reason
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cmake_minimum_required(VERSION 3.25) # Don't bump this version for no reason
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project("llama.cpp" C CXX)
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project("llama.cpp" C CXX)
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set(CMAKE_EXPORT_COMPILE_COMMANDS ON)
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set(CMAKE_EXPORT_COMPILE_COMMANDS ON)
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@ -65,8 +65,8 @@ endif()
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# 3rd party libs
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# 3rd party libs
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option(LLAMA_ACCELERATE "llama: enable Accelerate framework" ON)
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option(LLAMA_ACCELERATE "llama: enable Accelerate framework" ON)
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option(LLAMA_OPENBLAS "llama: use OpenBLAS" OFF)
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option(LLAMA_BLAS "llama: use BLAS" OFF)
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option(LLAMA_BLIS "llama: use blis" OFF)
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option(LLAMA_BLAS_VENDOR "llama: BLA_VENDOR from https://cmake.org/cmake/help/latest/module/FindBLAS.html#blas-lapack-vendors" Generic)
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option(LLAMA_CUBLAS "llama: use cuBLAS" OFF)
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option(LLAMA_CUBLAS "llama: use cuBLAS" OFF)
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option(LLAMA_CLBLAST "llama: use CLBlast" OFF)
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option(LLAMA_CLBLAST "llama: use CLBlast" OFF)
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@ -146,57 +146,26 @@ if (APPLE AND LLAMA_ACCELERATE)
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endif()
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endif()
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endif()
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endif()
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if (LLAMA_OPENBLAS)
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if (LLAMA_BLAS)
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if (LLAMA_STATIC)
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if (LLAMA_STATIC)
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set(BLA_STATIC ON)
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set(BLA_STATIC ON)
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endif()
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endif()
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set(BLA_SIZEOF_INTEGRER 8)
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set(BLA_VENDOR OpenBLAS)
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set(BLA_VENDOR ${LLAMA_BLAS_VENDOR})
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find_package(BLAS)
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find_package(BLAS)
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if (BLAS_FOUND)
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if (BLAS_FOUND)
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message(STATUS "OpenBLAS found")
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message(STATUS "BLAS found, Libraries: ${BLAS_LIBRARIES}")
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add_compile_definitions(GGML_USE_OPENBLAS)
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add_compile_definitions(GGML_USE_OPENBLAS)
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add_link_options(${BLAS_LIBRARIES})
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set(LLAMA_EXTRA_LIBS ${LLAMA_EXTRA_LIBS} ${BLAS_LIBRARIES})
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set(LLAMA_EXTRA_LIBS ${LLAMA_EXTRA_LIBS} openblas)
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# find header file
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message("${BLAS_LIBRARIES}")
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set(OPENBLAS_INCLUDE_SEARCH_PATHS
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include_directories(${BLAS_INCLUDE_DIRS})
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/usr/include
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/usr/include/openblas
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/usr/include/openblas-base
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/usr/local/include
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/usr/local/include/openblas
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/usr/local/include/openblas-base
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/opt/OpenBLAS/include
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$ENV{OpenBLAS_HOME}
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$ENV{OpenBLAS_HOME}/include
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)
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find_path(OPENBLAS_INC NAMES cblas.h PATHS ${OPENBLAS_INCLUDE_SEARCH_PATHS})
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add_compile_options(-I${OPENBLAS_INC})
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else()
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else()
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message(WARNING "OpenBLAS not found")
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message(WARNING "BLAS not found, please refer to https://cmake.org/cmake/help/latest/module/FindBLAS.html#blas-lapack-vendors to set correct LLAMA_BLAS_VENDOR")
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endif()
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endif()
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endif()
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endif()
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if (LLAMA_BLIS)
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add_compile_definitions(GGML_USE_BLIS)
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# we don't directly call BLIS apis, use cblas wrapper instead
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add_compile_definitions(GGML_USE_OPENBLAS)
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set(BLIS_INCLUDE_SEARCH_PATHS
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/usr/include
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/usr/include/blis
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/usr/local/include
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/usr/local/include/blis
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$ENV{BLIS_HOME}
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$ENV{BLIS_HOME}/include
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)
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find_path(BLIS_INC NAMES blis.h PATHS ${BLIS_INCLUDE_SEARCH_PATHS})
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add_compile_definitions(BLIS_ENABLE_CBLAS)
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add_link_options(-lblis)
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add_compile_options(-I${BLIS_INC})
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endif()
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if (LLAMA_CUBLAS)
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if (LLAMA_CUBLAS)
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cmake_minimum_required(VERSION 3.17)
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cmake_minimum_required(VERSION 3.17)
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2
Makefile
2
Makefile
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@ -123,7 +123,7 @@ ifdef LLAMA_OPENBLAS
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endif
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endif
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endif
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endif
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ifdef LLAMA_BLIS
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ifdef LLAMA_BLIS
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CFLAGS += -DGGML_USE_OPENBLAS -DGGML_USE_BLIS -I/usr/local/include/blis -I/usr/include/blis
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CFLAGS += -DGGML_USE_OPENBLAS -I/usr/local/include/blis -I/usr/include/blis
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LDFLAGS += -lblis -L/usr/local/lib
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LDFLAGS += -lblis -L/usr/local/lib
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endif
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endif
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ifdef LLAMA_CUBLAS
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ifdef LLAMA_CUBLAS
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16
README.md
16
README.md
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@ -56,9 +56,8 @@ The main goal of `llama.cpp` is to run the LLaMA model using 4-bit integer quant
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- Mixed F16 / F32 precision
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- Mixed F16 / F32 precision
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- 4-bit, 5-bit and 8-bit integer quantization support
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- 4-bit, 5-bit and 8-bit integer quantization support
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- Runs on the CPU
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- Runs on the CPU
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- OpenBLAS support
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- Supports OpenBLAS/Apple BLAS/ARM Performance Lib/ATLAS/BLIS/Intel MKL/NVHPC/ACML/SCSL/SGIMATH and [more](https://cmake.org/cmake/help/latest/module/FindBLAS.html#blas-lapack-vendors) in BLAS
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- cuBLAS and CLBlast support
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- cuBLAS and CLBlast support
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- BLIS support (cblas wrapper)
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The original implementation of `llama.cpp` was [hacked in an evening](https://github.com/ggerganov/llama.cpp/issues/33#issuecomment-1465108022).
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The original implementation of `llama.cpp` was [hacked in an evening](https://github.com/ggerganov/llama.cpp/issues/33#issuecomment-1465108022).
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Since then, the project has improved significantly thanks to many contributions. This project is for educational purposes and serves
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Since then, the project has improved significantly thanks to many contributions. This project is for educational purposes and serves
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@ -275,7 +274,7 @@ Building the program with BLAS support may lead to some performance improvements
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```bash
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```bash
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mkdir build
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mkdir build
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cd build
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cd build
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cmake .. -DLLAMA_OPENBLAS=ON
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cmake .. -DLLAMA_BLAS=ON -DLLAMA_BLAS_VENDOR=OpenBLAS
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cmake --build . --config Release
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cmake --build . --config Release
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```
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```
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@ -283,6 +282,17 @@ Building the program with BLAS support may lead to some performance improvements
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Check [BLIS.md](BLIS.md) for more information.
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Check [BLIS.md](BLIS.md) for more information.
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- Intel MKL
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By default, `LLAMA_BLAS_VENDOR` is set to `Generic`, so if you already sourced intel environment script and assign `-DLLAMA_BLAS=ON` in cmake, the mkl version of Blas will automatically been selected. You may also specify it by:
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```bash
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mkdir build
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cd build
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cmake .. -DLLAMA_BLAS=ON -DLLAMA_BLAS_VENDOR=Intel10_64lp -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx
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cmake --build . -config Release
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```
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- cuBLAS
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- cuBLAS
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This provides BLAS acceleration using the CUDA cores of your Nvidia GPU. Make sure to have the CUDA toolkit installed. You can download it from your Linux distro's package manager or from here: [CUDA Toolkit](https://developer.nvidia.com/cuda-downloads).
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This provides BLAS acceleration using the CUDA cores of your Nvidia GPU. Make sure to have the CUDA toolkit installed. You can download it from your Linux distro's package manager or from here: [CUDA Toolkit](https://developer.nvidia.com/cuda-downloads).
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