mirror of
https://github.com/ggerganov/llama.cpp.git
synced 2025-01-11 21:10:24 +01:00
6381d4e110
* gguf : first API pass * gguf : read header + meta data * gguf : read tensor info * gguf : initial model loading - not tested * gguf : add gguf_get_tensor_name() * gguf : do not support passing existing ggml_context to gguf_init * gguf : simplify gguf_get_val * gguf : gguf.c is now part of ggml.c * gguf : read / write sample models * gguf : add comments * refactor : reduce code duplication and better API (#2415) * gguf : expose the gguf_type enum through the API for now * gguf : add array support * gguf.py : some code style changes * convert.py : start a new simplified implementation by removing old stuff * convert.py : remove GGML vocab + other obsolete stuff * GGUF : write tensor (#2426) * WIP: Write tensor * GGUF : Support writing tensors in Python * refactor : rm unused import and upd todos * fix : fix errors upd writing example * rm example.gguf * gitignore *.gguf * undo formatting * gguf : add gguf_find_key (#2438) * gguf.cpp : find key example * ggml.h : add gguf_find_key * ggml.c : add gguf_find_key * gguf : fix writing tensors * gguf : do not hardcode tensor names to read * gguf : write sample tensors to read * gguf : add tokenization constants * quick and dirty conversion example * gguf : fix writing gguf arrays * gguf : write tensors one by one and code reuse * gguf : fix writing gguf arrays * gguf : write tensors one by one * gguf : write tensors one by one * gguf : write tokenizer data * gguf : upd gguf conversion script * Update convert-llama-h5-to-gguf.py * gguf : handle already encoded string * ggml.h : get array str and f32 * ggml.c : get arr str and f32 * gguf.py : support any type * Update convert-llama-h5-to-gguf.py * gguf : fix set is not subscriptable * gguf : update convert-llama-h5-to-gguf.py * constants.py : add layer norm eps * gguf.py : add layer norm eps and merges * ggml.h : increase GGML_MAX_NAME to 64 * ggml.c : add gguf_get_arr_n * Update convert-llama-h5-to-gguf.py * add gptneox gguf example * Makefile : add gptneox gguf example * Update convert-llama-h5-to-gguf.py * add gptneox gguf example * Update convert-llama-h5-to-gguf.py * Update convert-gptneox-h5-to-gguf.py * Update convert-gptneox-h5-to-gguf.py * Update convert-llama-h5-to-gguf.py * gguf : support custom alignment value * gguf : fix typo in function call * gguf : mmap tensor data example * fix : update convert-llama-h5-to-gguf.py * Update convert-llama-h5-to-gguf.py * convert-gptneox-h5-to-gguf.py : Special tokens * gptneox-main.cpp : special tokens * Update gptneox-main.cpp * constants.py : special tokens * gguf.py : accumulate kv and tensor info data + special tokens * convert-gptneox-h5-to-gguf.py : accumulate kv and ti + special tokens * gguf : gguf counterpart of llama-util.h * gguf-util.h : update note * convert-llama-h5-to-gguf.py : accumulate kv / ti + special tokens * convert-llama-h5-to-gguf.py : special tokens * Delete gptneox-common.cpp * Delete gptneox-common.h * convert-gptneox-h5-to-gguf.py : gpt2bpe tokenizer * gptneox-main.cpp : gpt2 bpe tokenizer * gpt2 bpe tokenizer (handles merges and unicode) * Makefile : remove gptneox-common * gguf.py : bytesarray for gpt2bpe tokenizer * cmpnct_gpt2bpe.hpp : comments * gguf.py : use custom alignment if present * gguf : minor stuff * Update gptneox-main.cpp * map tensor names * convert-gptneox-h5-to-gguf.py : map tensor names * convert-llama-h5-to-gguf.py : map tensor names * gptneox-main.cpp : map tensor names * gguf : start implementing libllama in GGUF (WIP) * gguf : start implementing libllama in GGUF (WIP) * rm binary commited by mistake * upd .gitignore * gguf : calculate n_mult * gguf : inference with 7B model working (WIP) * gguf : rm deprecated function * gguf : start implementing gguf_file_saver (WIP) * gguf : start implementing gguf_file_saver (WIP) * gguf : start implementing gguf_file_saver (WIP) * gguf : add gguf_get_kv_type * gguf : add gguf_get_kv_type * gguf : write metadata in gguf_file_saver (WIP) * gguf : write metadata in gguf_file_saver (WIP) * gguf : write metadata in gguf_file_saver * gguf : rm references to old file formats * gguf : shorter name for member variable * gguf : rm redundant method * gguf : get rid of n_mult, read n_ff from file * Update gguf_tensor_map.py * Update gptneox-main.cpp * gguf : rm references to old file magics * gguf : start implementing quantization (WIP) * gguf : start implementing quantization (WIP) * gguf : start implementing quantization (WIP) * gguf : start implementing quantization (WIP) * gguf : start implementing quantization (WIP) * gguf : start implementing quantization (WIP) * gguf : quantization is working * gguf : roper closing of file * gguf.py : no need to convert tensors twice * convert-gptneox-h5-to-gguf.py : no need to convert tensors twice * convert-llama-h5-to-gguf.py : no need to convert tensors twice * convert-gptneox-h5-to-gguf.py : simplify nbytes * convert-llama-h5-to-gguf.py : simplify nbytes * gptneox-main.cpp : n_layer --> n_block * constants.py : n_layer --> n_block * gguf.py : n_layer --> n_block * convert-gptneox-h5-to-gguf.py : n_layer --> n_block * convert-llama-h5-to-gguf.py : n_layer --> n_block * gptneox-main.cpp : n_layer --> n_block * Update gguf_tensor_map.py * convert-gptneox-h5-to-gguf.py : load model in parts to save memory * convert-llama-h5-to-gguf.py : load model in parts to save memory * convert : write more metadata for LLaMA * convert : rm quantization version * convert-gptneox-h5-to-gguf.py : add file_type key * gptneox-main.cpp : add file_type key * fix conflicts * gguf : add todos and comments * convert-gptneox-h5-to-gguf.py : tensor name map changes * Create gguf_namemap.py : tensor name map changes * Delete gguf_tensor_map.py * gptneox-main.cpp : tensor name map changes * convert-llama-h5-to-gguf.py : fixes * gguf.py : dont add empty strings * simple : minor style changes * gguf : use UNIX line ending * Create convert-llama-7b-pth-to-gguf.py * llama : sync gguf-llama.cpp with latest llama.cpp (#2608) * llama : sync gguf-llama.cpp with latest llama.cpp * minor : indentation + assert * llama : refactor gguf_buffer and gguf_ctx_buffer * llama : minor * gitignore : add gptneox-main * llama : tokenizer fixes (#2549) * Merge tokenizer fixes into the gguf branch. * Add test vocabularies * convert : update convert-new.py with tokenizer fixes (#2614) * Merge tokenizer fixes into the gguf branch. * Add test vocabularies * Adapt convert-new.py (and fix a clang-cl compiler error on windows) * llama : sync gguf-llama with llama (#2613) * llama : sync gguf-llama with llama * tests : fix build + warnings (test-tokenizer-1 still fails) * tests : fix wstring_convert * convert : fix layer names * llama : sync gguf-llama.cpp * convert : update HF converter to new tokenizer voodoo magics * llama : update tokenizer style * convert-llama-h5-to-gguf.py : add token types * constants.py : add token types * gguf.py : add token types * convert-llama-7b-pth-to-gguf.py : add token types * gguf-llama.cpp : fix n_head_kv * convert-llama-h5-to-gguf.py : add 70b gqa support * gguf.py : add tensor data layout * convert-llama-h5-to-gguf.py : add tensor data layout * convert-llama-7b-pth-to-gguf.py : add tensor data layout * gptneox-main.cpp : add tensor data layout * convert-llama-h5-to-gguf.py : clarify the reverse permute * llama : refactor model loading code (#2620) * llama : style formatting + remove helper methods * llama : fix quantization using gguf tool * llama : simplify gguf_file_saver * llama : fix method names * llama : simplify write_header() * llama : no need to pass full file loader to the file saver just gguf_ctx * llama : gguf_file_saver write I32 * llama : refactor tensor names (#2622) * gguf: update tensor names searched in quantization * gguf : define tensor names as constants * gguf : initial write API (not tested yet) * gguf : write to file API (not tested) * gguf : initial write API ready + example * gguf : fix header write * gguf : fixes + simplify example + add ggml_nbytes_pad() * gguf : minor * llama : replace gguf_file_saver with new gguf write API * gguf : streaming support when writing files * gguf : remove oboslete write methods * gguf : remove obosolete gguf_get_arr_xxx API * llama : simplify gguf_file_loader * llama : move hparams and vocab from gguf_file_loader to llama_model_loader * llama : merge gguf-util.h in llama.cpp * llama : reorder definitions in .cpp to match .h * llama : minor simplifications * llama : refactor llama_model_loader (WIP) wip : remove ggml_ctx from llama_model_loader wip : merge gguf_file_loader in llama_model_loader * llama : fix shape prints * llama : fix Windows build + fix norm_rms_eps key * llama : throw error on missing KV paris in model meta data * llama : improve printing + log meta data * llama : switch print order of meta data --------- Co-authored-by: M. Yusuf Sarıgöz <yusufsarigoz@gmail.com> * gguf : deduplicate (#2629) * gguf : better type names * dedup : CPU + Metal is working * ggml : fix warnings about unused results * llama.cpp : fix line feed and compiler warning * llama : fix strncpy warning + note token_to_str does not write null * llama : restore the original load/save session implementation Will migrate this to GGUF in the future * convert-llama-h5-to-gguf.py : support alt ctx param name * ggml : assert when using ggml_mul with non-F32 src1 * examples : dedup simple --------- Co-authored-by: klosax <131523366+klosax@users.noreply.github.com> * gguf.py : merge all files in gguf.py * convert-new.py : pick #2427 for HF 70B support * examples/gguf : no need to keep q option for quantization any more * llama.cpp : print actual model size * llama.cpp : use ggml_elements() * convert-new.py : output gguf (#2635) * convert-new.py : output gguf (WIP) * convert-new.py : add gguf key-value pairs * llama : add hparams.ctx_train + no longer print ftype * convert-new.py : minor fixes * convert-new.py : vocab-only option should work now * llama : fix tokenizer to use llama_char_to_byte * tests : add new ggml-vocab-llama.gguf * convert-new.py : tensor name mapping * convert-new.py : add map for skipping tensor serialization * convert-new.py : convert script now works * gguf.py : pick some of the refactoring from #2644 * convert-new.py : minor fixes * convert.py : update to support GGUF output * Revert "ci : disable CI temporary to not waste energy" This reverts commit 7e82d25f40386540c2c15226300ad998ecd871ea. * convert.py : n_head_kv optional and .gguf file extension * convert.py : better always have n_head_kv and default it to n_head * llama : sync with recent PRs on master * editorconfig : ignore models folder ggml-ci * ci : update ".bin" to ".gguf" extension ggml-ci * llama : fix llama_model_loader memory leak * gptneox : move as a WIP example * llama : fix lambda capture ggml-ci * ggml : fix bug in gguf_set_kv ggml-ci * common.h : .bin --> .gguf * quantize-stats.cpp : .bin --> .gguf * convert.py : fix HF tensor permuting / unpacking ggml-ci * llama.cpp : typo * llama : throw error if gguf fails to init from file ggml-ci * llama : fix tensor name grepping during quantization ggml-ci * gguf.py : write tensors in a single pass (#2644) * gguf : single pass for writing tensors + refactoring writer * gguf : single pass for writing tensors + refactoring writer * gguf : single pass for writing tensors + refactoring writer * gguf : style fixes in simple conversion script * gguf : refactor gptneox conversion script * gguf : rename h5 to hf (for HuggingFace) * gguf : refactor pth to gguf conversion script * gguf : rm file_type key and method * gguf.py : fix vertical alignment * gguf.py : indentation --------- Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> * convert-gptneox-hf-to-gguf.py : fixes * gguf.py : gptneox mapping * convert-llama-hf-to-gguf.py : fixes * convert-llama-7b-pth-to-gguf.py : fixes * ggml.h : reverse GGUF_MAGIC * gguf.py : reverse GGUF_MAGIC * test-tokenizer-0.cpp : fix warning * llama.cpp : print kv general.name * llama.cpp : get special token kv and linefeed token id * llama : print number of tensors per type + print arch + style * tests : update vocab file with new magic * editorconfig : fix whitespaces * llama : re-order functions * llama : remove C++ API + reorganize common source in /common dir * llama : minor API updates * llama : avoid hardcoded special tokens * llama : fix MPI build ggml-ci * llama : introduce enum llama_vocab_type + remove hardcoded string constants * convert-falcon-hf-to-gguf.py : falcon HF --> gguf conversion, not tested * falcon-main.cpp : falcon inference example * convert-falcon-hf-to-gguf.py : remove extra kv * convert-gptneox-hf-to-gguf.py : remove extra kv * convert-llama-7b-pth-to-gguf.py : remove extra kv * convert-llama-hf-to-gguf.py : remove extra kv * gguf.py : fix for falcon 40b * falcon-main.cpp : fix for falcon 40b * convert-falcon-hf-to-gguf.py : update ref * convert-falcon-hf-to-gguf.py : add tensor data layout * cmpnct_gpt2bpe.hpp : fixes * falcon-main.cpp : fixes * gptneox-main.cpp : fixes * cmpnct_gpt2bpe.hpp : remove non-general stuff * Update examples/server/README.md Co-authored-by: slaren <slarengh@gmail.com> * cmpnct_gpt2bpe.hpp : cleanup * convert-llama-hf-to-gguf.py : special tokens * convert-llama-7b-pth-to-gguf.py : special tokens * convert-permute-debug.py : permute debug print * convert-permute-debug-master.py : permute debug for master * convert-permute-debug.py : change permute type of attn_q * convert.py : 70b model working (change attn_q permute) * Delete convert-permute-debug-master.py * Delete convert-permute-debug.py * convert-llama-hf-to-gguf.py : fix attn_q permute * gguf.py : fix rope scale kv * convert-llama-hf-to-gguf.py : rope scale and added tokens * convert-llama-7b-pth-to-gguf.py : rope scale and added tokens * llama.cpp : use rope scale kv * convert-llama-7b-pth-to-gguf.py : rope scale fix * convert-llama-hf-to-gguf.py : rope scale fix * py : fix whitespace * gguf : add Python script to convert GGMLv3 LLaMA models to GGUF (#2682) * First pass at converting GGMLv3 LLaMA models to GGUF * Cleanups, better output during conversion * Fix vocab space conversion logic * More vocab conversion fixes * Add description to converted GGUF files * Improve help text, expand warning * Allow specifying name and description for output GGUF * Allow overriding vocab and hyperparams from original model metadata * Use correct params override var name * Fix wrong type size for Q8_K Better handling of original style metadata * Set default value for gguf add_tensor raw_shape KW arg * llama : improve token type support (#2668) * Merge tokenizer fixes into the gguf branch. * Add test vocabularies * Adapt convert-new.py (and fix a clang-cl compiler error on windows) * Improved tokenizer test But does it work on MacOS? * Improve token type support - Added @klosax code to convert.py - Improved token type support in vocabulary * Exclude platform dependent tests * More sentencepiece compatibility by eliminating magic numbers * Restored accidentally removed comment * llama : add API for token type ggml-ci * tests : use new tokenizer type API (#2692) * Merge tokenizer fixes into the gguf branch. * Add test vocabularies * Adapt convert-new.py (and fix a clang-cl compiler error on windows) * Improved tokenizer test But does it work on MacOS? * Improve token type support - Added @klosax code to convert.py - Improved token type support in vocabulary * Exclude platform dependent tests * More sentencepiece compatibility by eliminating magic numbers * Restored accidentally removed comment * Improve commentary * Use token type API in test-tokenizer-1.cpp * py : cosmetics * readme : add notice about new file format ggml-ci --------- Co-authored-by: M. Yusuf Sarıgöz <yusufsarigoz@gmail.com> Co-authored-by: klosax <131523366+klosax@users.noreply.github.com> Co-authored-by: goerch <jhr.walter@t-online.de> Co-authored-by: slaren <slarengh@gmail.com> Co-authored-by: Kerfuffle <44031344+KerfuffleV2@users.noreply.github.com>
605 lines
21 KiB
CMake
605 lines
21 KiB
CMake
cmake_minimum_required(VERSION 3.12) # Don't bump this version for no reason
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project("llama.cpp" C CXX)
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set(CMAKE_EXPORT_COMPILE_COMMANDS ON)
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if (NOT XCODE AND NOT MSVC AND NOT CMAKE_BUILD_TYPE)
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set(CMAKE_BUILD_TYPE Release CACHE STRING "Build type" FORCE)
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set_property(CACHE CMAKE_BUILD_TYPE PROPERTY STRINGS "Debug" "Release" "MinSizeRel" "RelWithDebInfo")
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endif()
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set(CMAKE_RUNTIME_OUTPUT_DIRECTORY ${CMAKE_BINARY_DIR}/bin)
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if(CMAKE_SOURCE_DIR STREQUAL CMAKE_CURRENT_SOURCE_DIR)
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set(LLAMA_STANDALONE ON)
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# configure project version
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# TODO
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else()
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set(LLAMA_STANDALONE OFF)
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endif()
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if (EMSCRIPTEN)
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set(BUILD_SHARED_LIBS_DEFAULT OFF)
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option(LLAMA_WASM_SINGLE_FILE "llama: embed WASM inside the generated llama.js" ON)
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else()
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if (MINGW)
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set(BUILD_SHARED_LIBS_DEFAULT OFF)
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else()
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set(BUILD_SHARED_LIBS_DEFAULT ON)
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endif()
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endif()
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#
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# Option list
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#
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# general
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option(LLAMA_STATIC "llama: static link libraries" OFF)
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option(LLAMA_NATIVE "llama: enable -march=native flag" OFF)
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option(LLAMA_LTO "llama: enable link time optimization" OFF)
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# debug
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option(LLAMA_ALL_WARNINGS "llama: enable all compiler warnings" ON)
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option(LLAMA_ALL_WARNINGS_3RD_PARTY "llama: enable all compiler warnings in 3rd party libs" OFF)
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option(LLAMA_GPROF "llama: enable gprof" OFF)
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# sanitizers
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option(LLAMA_SANITIZE_THREAD "llama: enable thread sanitizer" OFF)
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option(LLAMA_SANITIZE_ADDRESS "llama: enable address sanitizer" OFF)
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option(LLAMA_SANITIZE_UNDEFINED "llama: enable undefined sanitizer" OFF)
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# instruction set specific
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option(LLAMA_AVX "llama: enable AVX" ON)
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option(LLAMA_AVX2 "llama: enable AVX2" ON)
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option(LLAMA_AVX512 "llama: enable AVX512" OFF)
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option(LLAMA_AVX512_VBMI "llama: enable AVX512-VBMI" OFF)
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option(LLAMA_AVX512_VNNI "llama: enable AVX512-VNNI" OFF)
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option(LLAMA_FMA "llama: enable FMA" ON)
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# in MSVC F16C is implied with AVX2/AVX512
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if (NOT MSVC)
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option(LLAMA_F16C "llama: enable F16C" ON)
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endif()
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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_BLAS "llama: use BLAS" OFF)
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set(LLAMA_BLAS_VENDOR "Generic" CACHE STRING "llama: BLAS library vendor")
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option(LLAMA_CUBLAS "llama: use CUDA" OFF)
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#option(LLAMA_CUDA_CUBLAS "llama: use cuBLAS for prompt processing" OFF)
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option(LLAMA_CUDA_FORCE_DMMV "llama: use dmmv instead of mmvq CUDA kernels" OFF)
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set(LLAMA_CUDA_DMMV_X "32" CACHE STRING "llama: x stride for dmmv CUDA kernels")
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set(LLAMA_CUDA_MMV_Y "1" CACHE STRING "llama: y block size for mmv CUDA kernels")
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option(LLAMA_CUDA_F16 "llama: use 16 bit floats for some calculations" OFF)
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set(LLAMA_CUDA_KQUANTS_ITER "2" CACHE STRING "llama: iters./thread per block for Q2_K/Q6_K")
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option(LLAMA_CLBLAST "llama: use CLBlast" OFF)
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option(LLAMA_METAL "llama: use Metal" OFF)
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option(LLAMA_MPI "llama: use MPI" OFF)
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option(LLAMA_K_QUANTS "llama: use k-quants" ON)
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option(LLAMA_QKK_64 "llama: use super-block size of 64 for k-quants" OFF)
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option(LLAMA_BUILD_TESTS "llama: build tests" ${LLAMA_STANDALONE})
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option(LLAMA_BUILD_EXAMPLES "llama: build examples" ${LLAMA_STANDALONE})
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option(LLAMA_BUILD_SERVER "llama: build server example" ON)
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#
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# Build info header
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#
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# Generate initial build-info.h
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include(${CMAKE_CURRENT_SOURCE_DIR}/scripts/build-info.cmake)
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if(EXISTS "${CMAKE_CURRENT_SOURCE_DIR}/.git")
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set(GIT_DIR "${CMAKE_CURRENT_SOURCE_DIR}/.git")
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# Is git submodule
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if(NOT IS_DIRECTORY "${GIT_DIR}")
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file(READ ${GIT_DIR} REAL_GIT_DIR_LINK)
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string(REGEX REPLACE "gitdir: (.*)\n$" "\\1" REAL_GIT_DIR ${REAL_GIT_DIR_LINK})
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set(GIT_DIR "${CMAKE_CURRENT_SOURCE_DIR}/${REAL_GIT_DIR}")
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endif()
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# Add a custom target for build-info.h
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add_custom_target(BUILD_INFO ALL DEPENDS "${CMAKE_CURRENT_SOURCE_DIR}/build-info.h")
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# Add a custom command to rebuild build-info.h when .git/index changes
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add_custom_command(
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OUTPUT "${CMAKE_CURRENT_SOURCE_DIR}/build-info.h"
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COMMENT "Generating build details from Git"
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COMMAND ${CMAKE_COMMAND} -P "${CMAKE_CURRENT_SOURCE_DIR}/scripts/build-info.cmake"
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WORKING_DIRECTORY ${CMAKE_CURRENT_SOURCE_DIR}
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DEPENDS "${GIT_DIR}/index"
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VERBATIM
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)
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else()
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message(WARNING "Git repository not found; to enable automatic generation of build info, make sure Git is installed and the project is a Git repository.")
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endif()
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#
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# Compile flags
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#
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set(CMAKE_CXX_STANDARD 11)
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set(CMAKE_CXX_STANDARD_REQUIRED true)
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set(CMAKE_C_STANDARD 11)
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set(CMAKE_C_STANDARD_REQUIRED true)
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set(THREADS_PREFER_PTHREAD_FLAG ON)
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find_package(Threads REQUIRED)
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if (NOT MSVC)
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if (LLAMA_SANITIZE_THREAD)
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add_compile_options(-fsanitize=thread)
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link_libraries(-fsanitize=thread)
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endif()
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if (LLAMA_SANITIZE_ADDRESS)
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add_compile_options(-fsanitize=address -fno-omit-frame-pointer)
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link_libraries(-fsanitize=address)
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endif()
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if (LLAMA_SANITIZE_UNDEFINED)
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add_compile_options(-fsanitize=undefined)
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link_libraries(-fsanitize=undefined)
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endif()
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endif()
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if (APPLE AND LLAMA_ACCELERATE)
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find_library(ACCELERATE_FRAMEWORK Accelerate)
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if (ACCELERATE_FRAMEWORK)
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message(STATUS "Accelerate framework found")
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add_compile_definitions(GGML_USE_ACCELERATE)
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set(LLAMA_EXTRA_LIBS ${LLAMA_EXTRA_LIBS} ${ACCELERATE_FRAMEWORK})
|
|
else()
|
|
message(WARNING "Accelerate framework not found")
|
|
endif()
|
|
endif()
|
|
|
|
if (LLAMA_BLAS)
|
|
if (LLAMA_STATIC)
|
|
set(BLA_STATIC ON)
|
|
endif()
|
|
if ($(CMAKE_VERSION) VERSION_GREATER_EQUAL 3.22)
|
|
set(BLA_SIZEOF_INTEGER 8)
|
|
endif()
|
|
|
|
set(BLA_VENDOR ${LLAMA_BLAS_VENDOR})
|
|
find_package(BLAS)
|
|
|
|
if (BLAS_FOUND)
|
|
message(STATUS "BLAS found, Libraries: ${BLAS_LIBRARIES}")
|
|
|
|
if ("${BLAS_INCLUDE_DIRS}" STREQUAL "")
|
|
# BLAS_INCLUDE_DIRS is missing in FindBLAS.cmake.
|
|
# see https://gitlab.kitware.com/cmake/cmake/-/issues/20268
|
|
find_package(PkgConfig REQUIRED)
|
|
if (${LLAMA_BLAS_VENDOR} MATCHES "Generic")
|
|
pkg_check_modules(DepBLAS REQUIRED blas)
|
|
elseif (${LLAMA_BLAS_VENDOR} MATCHES "OpenBLAS")
|
|
pkg_check_modules(DepBLAS REQUIRED openblas)
|
|
elseif (${LLAMA_BLAS_VENDOR} MATCHES "FLAME")
|
|
pkg_check_modules(DepBLAS REQUIRED blis)
|
|
elseif (${LLAMA_BLAS_VENDOR} MATCHES "ATLAS")
|
|
pkg_check_modules(DepBLAS REQUIRED blas-atlas)
|
|
elseif (${LLAMA_BLAS_VENDOR} MATCHES "FlexiBLAS")
|
|
pkg_check_modules(DepBLAS REQUIRED flexiblas_api)
|
|
elseif (${LLAMA_BLAS_VENDOR} MATCHES "Intel")
|
|
# all Intel* libraries share the same include path
|
|
pkg_check_modules(DepBLAS REQUIRED mkl-sdl)
|
|
elseif (${LLAMA_BLAS_VENDOR} MATCHES "NVHPC")
|
|
# this doesn't provide pkg-config
|
|
# suggest to assign BLAS_INCLUDE_DIRS on your own
|
|
if ("${NVHPC_VERSION}" STREQUAL "")
|
|
message(WARNING "Better to set NVHPC_VERSION")
|
|
else()
|
|
set(DepBLAS_FOUND ON)
|
|
set(DepBLAS_INCLUDE_DIRS "/opt/nvidia/hpc_sdk/${CMAKE_SYSTEM_NAME}_${CMAKE_SYSTEM_PROCESSOR}/${NVHPC_VERSION}/math_libs/include")
|
|
endif()
|
|
endif()
|
|
if (DepBLAS_FOUND)
|
|
set(BLAS_INCLUDE_DIRS ${DepBLAS_INCLUDE_DIRS})
|
|
else()
|
|
message(WARNING "BLAS_INCLUDE_DIRS neither been provided nor been automatically"
|
|
" detected by pkgconfig, trying to find cblas.h from possible paths...")
|
|
find_path(BLAS_INCLUDE_DIRS
|
|
NAMES cblas.h
|
|
HINTS
|
|
/usr/include
|
|
/usr/local/include
|
|
/usr/include/openblas
|
|
/opt/homebrew/opt/openblas/include
|
|
/usr/local/opt/openblas/include
|
|
/usr/include/x86_64-linux-gnu/openblas/include
|
|
)
|
|
endif()
|
|
endif()
|
|
|
|
message(STATUS "BLAS found, Includes: ${BLAS_INCLUDE_DIRS}")
|
|
add_compile_options(${BLAS_LINKER_FLAGS})
|
|
add_compile_definitions(GGML_USE_OPENBLAS)
|
|
if (${BLAS_INCLUDE_DIRS} MATCHES "mkl" AND (${LLAMA_BLAS_VENDOR} MATCHES "Generic" OR ${LLAMA_BLAS_VENDOR} MATCHES "Intel"))
|
|
add_compile_definitions(GGML_BLAS_USE_MKL)
|
|
endif()
|
|
set(LLAMA_EXTRA_LIBS ${LLAMA_EXTRA_LIBS} ${BLAS_LIBRARIES})
|
|
set(LLAMA_EXTRA_INCLUDES ${LLAMA_EXTRA_INCLUDES} ${BLAS_INCLUDE_DIRS})
|
|
|
|
else()
|
|
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")
|
|
endif()
|
|
endif()
|
|
|
|
if (LLAMA_K_QUANTS)
|
|
set(GGML_SOURCES_EXTRA ${GGML_SOURCES_EXTRA} k_quants.c k_quants.h)
|
|
add_compile_definitions(GGML_USE_K_QUANTS)
|
|
if (LLAMA_QKK_64)
|
|
add_compile_definitions(GGML_QKK_64)
|
|
endif()
|
|
endif()
|
|
|
|
if (LLAMA_CUBLAS)
|
|
cmake_minimum_required(VERSION 3.17)
|
|
|
|
find_package(CUDAToolkit)
|
|
if (CUDAToolkit_FOUND)
|
|
message(STATUS "cuBLAS found")
|
|
|
|
enable_language(CUDA)
|
|
|
|
set(GGML_SOURCES_CUDA ggml-cuda.cu ggml-cuda.h)
|
|
|
|
add_compile_definitions(GGML_USE_CUBLAS)
|
|
# if (LLAMA_CUDA_CUBLAS)
|
|
# add_compile_definitions(GGML_CUDA_CUBLAS)
|
|
# endif()
|
|
if (LLAMA_CUDA_FORCE_DMMV)
|
|
add_compile_definitions(GGML_CUDA_FORCE_DMMV)
|
|
endif()
|
|
add_compile_definitions(GGML_CUDA_DMMV_X=${LLAMA_CUDA_DMMV_X})
|
|
add_compile_definitions(GGML_CUDA_MMV_Y=${LLAMA_CUDA_MMV_Y})
|
|
if (DEFINED LLAMA_CUDA_DMMV_Y)
|
|
add_compile_definitions(GGML_CUDA_MMV_Y=${LLAMA_CUDA_DMMV_Y}) # for backwards compatibility
|
|
endif()
|
|
if (LLAMA_CUDA_F16 OR LLAMA_CUDA_DMMV_F16)
|
|
add_compile_definitions(GGML_CUDA_F16)
|
|
endif()
|
|
add_compile_definitions(K_QUANTS_PER_ITERATION=${LLAMA_CUDA_KQUANTS_ITER})
|
|
|
|
if (LLAMA_STATIC)
|
|
set(LLAMA_EXTRA_LIBS ${LLAMA_EXTRA_LIBS} CUDA::cudart_static CUDA::cublas_static CUDA::cublasLt_static)
|
|
else()
|
|
set(LLAMA_EXTRA_LIBS ${LLAMA_EXTRA_LIBS} CUDA::cudart CUDA::cublas CUDA::cublasLt)
|
|
endif()
|
|
|
|
if (NOT DEFINED CMAKE_CUDA_ARCHITECTURES)
|
|
# 52 == lowest CUDA 12 standard
|
|
# 60 == f16 CUDA intrinsics
|
|
# 61 == integer CUDA intrinsics
|
|
# 70 == compute capability at which unrolling a loop in mul_mat_q kernels is faster
|
|
if (LLAMA_CUDA_F16 OR LLAMA_CUDA_DMMV_F16)
|
|
set(CMAKE_CUDA_ARCHITECTURES "60;61;70") # needed for f16 CUDA intrinsics
|
|
else()
|
|
set(CMAKE_CUDA_ARCHITECTURES "52;61;70") # lowest CUDA 12 standard + lowest for integer intrinsics
|
|
endif()
|
|
endif()
|
|
message(STATUS "Using CUDA architectures: ${CMAKE_CUDA_ARCHITECTURES}")
|
|
|
|
else()
|
|
message(WARNING "cuBLAS not found")
|
|
endif()
|
|
endif()
|
|
|
|
if (LLAMA_METAL)
|
|
find_library(FOUNDATION_LIBRARY Foundation REQUIRED)
|
|
find_library(METAL_FRAMEWORK Metal REQUIRED)
|
|
find_library(METALKIT_FRAMEWORK MetalKit REQUIRED)
|
|
|
|
set(GGML_SOURCES_METAL ggml-metal.m ggml-metal.h)
|
|
|
|
add_compile_definitions(GGML_USE_METAL)
|
|
add_compile_definitions(GGML_METAL_NDEBUG)
|
|
|
|
# get full path to the file
|
|
#add_compile_definitions(GGML_METAL_DIR_KERNELS="${CMAKE_CURRENT_SOURCE_DIR}/")
|
|
|
|
# copy ggml-metal.metal to bin directory
|
|
configure_file(ggml-metal.metal bin/ggml-metal.metal COPYONLY)
|
|
|
|
set(LLAMA_EXTRA_LIBS ${LLAMA_EXTRA_LIBS}
|
|
${FOUNDATION_LIBRARY}
|
|
${METAL_FRAMEWORK}
|
|
${METALKIT_FRAMEWORK}
|
|
)
|
|
endif()
|
|
|
|
if (LLAMA_MPI)
|
|
cmake_minimum_required(VERSION 3.10)
|
|
find_package(MPI)
|
|
if (MPI_C_FOUND)
|
|
message(STATUS "MPI found")
|
|
set(GGML_SOURCES_MPI ggml-mpi.c ggml-mpi.h)
|
|
add_compile_definitions(GGML_USE_MPI)
|
|
add_compile_definitions(${MPI_C_COMPILE_DEFINITIONS})
|
|
set(cxx_flags ${cxx_flags} -Wno-cast-qual)
|
|
set(c_flags ${c_flags} -Wno-cast-qual)
|
|
set(LLAMA_EXTRA_LIBS ${LLAMA_EXTRA_LIBS} ${MPI_C_LIBRARIES})
|
|
set(LLAMA_EXTRA_INCLUDES ${LLAMA_EXTRA_INCLUDES} ${MPI_C_INCLUDE_DIRS})
|
|
# Even if you're only using the C header, C++ programs may bring in MPI
|
|
# C++ functions, so more linkage is needed
|
|
if (MPI_CXX_FOUND)
|
|
set(LLAMA_EXTRA_LIBS ${LLAMA_EXTRA_LIBS} ${MPI_CXX_LIBRARIES})
|
|
endif()
|
|
else()
|
|
message(WARNING "MPI not found")
|
|
endif()
|
|
endif()
|
|
|
|
if (LLAMA_CLBLAST)
|
|
find_package(CLBlast)
|
|
if (CLBlast_FOUND)
|
|
message(STATUS "CLBlast found")
|
|
|
|
set(GGML_SOURCES_OPENCL ggml-opencl.cpp ggml-opencl.h)
|
|
|
|
add_compile_definitions(GGML_USE_CLBLAST)
|
|
|
|
set(LLAMA_EXTRA_LIBS ${LLAMA_EXTRA_LIBS} clblast)
|
|
else()
|
|
message(WARNING "CLBlast not found")
|
|
endif()
|
|
endif()
|
|
|
|
if (LLAMA_ALL_WARNINGS)
|
|
if (NOT MSVC)
|
|
set(c_flags
|
|
-Wall
|
|
-Wextra
|
|
-Wpedantic
|
|
-Wcast-qual
|
|
-Wdouble-promotion
|
|
-Wshadow
|
|
-Wstrict-prototypes
|
|
-Wpointer-arith
|
|
-Wmissing-prototypes
|
|
)
|
|
set(cxx_flags
|
|
-Wall
|
|
-Wextra
|
|
-Wpedantic
|
|
-Wcast-qual
|
|
-Wno-unused-function
|
|
-Wno-multichar
|
|
)
|
|
else()
|
|
# todo : msvc
|
|
endif()
|
|
|
|
add_compile_options(
|
|
"$<$<COMPILE_LANGUAGE:C>:${c_flags}>"
|
|
"$<$<COMPILE_LANGUAGE:CXX>:${cxx_flags}>"
|
|
)
|
|
|
|
endif()
|
|
|
|
if (MSVC)
|
|
add_compile_definitions(_CRT_SECURE_NO_WARNINGS)
|
|
|
|
if (BUILD_SHARED_LIBS)
|
|
set(CMAKE_WINDOWS_EXPORT_ALL_SYMBOLS ON)
|
|
endif()
|
|
endif()
|
|
|
|
if (LLAMA_LTO)
|
|
include(CheckIPOSupported)
|
|
check_ipo_supported(RESULT result OUTPUT output)
|
|
if (result)
|
|
set(CMAKE_INTERPROCEDURAL_OPTIMIZATION TRUE)
|
|
else()
|
|
message(WARNING "IPO is not supported: ${output}")
|
|
endif()
|
|
endif()
|
|
|
|
# Architecture specific
|
|
# TODO: probably these flags need to be tweaked on some architectures
|
|
# feel free to update the Makefile for your architecture and send a pull request or issue
|
|
message(STATUS "CMAKE_SYSTEM_PROCESSOR: ${CMAKE_SYSTEM_PROCESSOR}")
|
|
if (NOT MSVC)
|
|
if (LLAMA_STATIC)
|
|
add_link_options(-static)
|
|
if (MINGW)
|
|
add_link_options(-static-libgcc -static-libstdc++)
|
|
endif()
|
|
endif()
|
|
if (LLAMA_GPROF)
|
|
add_compile_options(-pg)
|
|
endif()
|
|
if (LLAMA_NATIVE)
|
|
add_compile_options(-march=native)
|
|
endif()
|
|
endif()
|
|
|
|
if (${CMAKE_SYSTEM_PROCESSOR} MATCHES "arm" OR ${CMAKE_SYSTEM_PROCESSOR} MATCHES "aarch64")
|
|
message(STATUS "ARM detected")
|
|
if (MSVC)
|
|
# TODO: arm msvc?
|
|
else()
|
|
if (${CMAKE_SYSTEM_PROCESSOR} MATCHES "armv6")
|
|
# Raspberry Pi 1, Zero
|
|
add_compile_options(-mfpu=neon-fp-armv8 -mfp16-format=ieee -mno-unaligned-access)
|
|
endif()
|
|
if (${CMAKE_SYSTEM_PROCESSOR} MATCHES "armv7")
|
|
# Raspberry Pi 2
|
|
add_compile_options(-mfpu=neon-fp-armv8 -mfp16-format=ieee -mno-unaligned-access -funsafe-math-optimizations)
|
|
endif()
|
|
if (${CMAKE_SYSTEM_PROCESSOR} MATCHES "armv8")
|
|
# Raspberry Pi 3, 4, Zero 2 (32-bit)
|
|
add_compile_options(-mfp16-format=ieee -mno-unaligned-access)
|
|
endif()
|
|
endif()
|
|
elseif (${CMAKE_SYSTEM_PROCESSOR} MATCHES "^(x86_64|i686|AMD64)$")
|
|
message(STATUS "x86 detected")
|
|
if (MSVC)
|
|
if (LLAMA_AVX512)
|
|
add_compile_options($<$<COMPILE_LANGUAGE:C>:/arch:AVX512>)
|
|
add_compile_options($<$<COMPILE_LANGUAGE:CXX>:/arch:AVX512>)
|
|
# MSVC has no compile-time flags enabling specific
|
|
# AVX512 extensions, neither it defines the
|
|
# macros corresponding to the extensions.
|
|
# Do it manually.
|
|
if (LLAMA_AVX512_VBMI)
|
|
add_compile_definitions($<$<COMPILE_LANGUAGE:C>:__AVX512VBMI__>)
|
|
add_compile_definitions($<$<COMPILE_LANGUAGE:CXX>:__AVX512VBMI__>)
|
|
endif()
|
|
if (LLAMA_AVX512_VNNI)
|
|
add_compile_definitions($<$<COMPILE_LANGUAGE:C>:__AVX512VNNI__>)
|
|
add_compile_definitions($<$<COMPILE_LANGUAGE:CXX>:__AVX512VNNI__>)
|
|
endif()
|
|
elseif (LLAMA_AVX2)
|
|
add_compile_options($<$<COMPILE_LANGUAGE:C>:/arch:AVX2>)
|
|
add_compile_options($<$<COMPILE_LANGUAGE:CXX>:/arch:AVX2>)
|
|
elseif (LLAMA_AVX)
|
|
add_compile_options($<$<COMPILE_LANGUAGE:C>:/arch:AVX>)
|
|
add_compile_options($<$<COMPILE_LANGUAGE:CXX>:/arch:AVX>)
|
|
endif()
|
|
else()
|
|
if (LLAMA_F16C)
|
|
add_compile_options(-mf16c)
|
|
endif()
|
|
if (LLAMA_FMA)
|
|
add_compile_options(-mfma)
|
|
endif()
|
|
if (LLAMA_AVX)
|
|
add_compile_options(-mavx)
|
|
endif()
|
|
if (LLAMA_AVX2)
|
|
add_compile_options(-mavx2)
|
|
endif()
|
|
if (LLAMA_AVX512)
|
|
add_compile_options(-mavx512f)
|
|
add_compile_options(-mavx512bw)
|
|
endif()
|
|
if (LLAMA_AVX512_VBMI)
|
|
add_compile_options(-mavx512vbmi)
|
|
endif()
|
|
if (LLAMA_AVX512_VNNI)
|
|
add_compile_options(-mavx512vnni)
|
|
endif()
|
|
endif()
|
|
elseif (${CMAKE_SYSTEM_PROCESSOR} MATCHES "ppc64")
|
|
message(STATUS "PowerPC detected")
|
|
add_compile_options(-mcpu=native -mtune=native)
|
|
#TODO: Add targets for Power8/Power9 (Altivec/VSX) and Power10(MMA) and query for big endian systems (ppc64/le/be)
|
|
else()
|
|
message(STATUS "Unknown architecture")
|
|
endif()
|
|
|
|
#
|
|
# libraries
|
|
#
|
|
|
|
# ggml
|
|
|
|
add_library(ggml OBJECT
|
|
ggml.c
|
|
ggml.h
|
|
ggml-alloc.c
|
|
ggml-alloc.h
|
|
${GGML_SOURCES_CUDA}
|
|
${GGML_SOURCES_OPENCL}
|
|
${GGML_SOURCES_METAL}
|
|
${GGML_SOURCES_MPI}
|
|
${GGML_SOURCES_EXTRA}
|
|
)
|
|
|
|
target_include_directories(ggml PUBLIC . ${LLAMA_EXTRA_INCLUDES})
|
|
target_compile_features(ggml PUBLIC c_std_11) # don't bump
|
|
target_link_libraries(ggml PUBLIC Threads::Threads ${LLAMA_EXTRA_LIBS})
|
|
|
|
add_library(ggml_static STATIC $<TARGET_OBJECTS:ggml>)
|
|
if (BUILD_SHARED_LIBS)
|
|
set_target_properties(ggml PROPERTIES POSITION_INDEPENDENT_CODE ON)
|
|
add_library(ggml_shared SHARED $<TARGET_OBJECTS:ggml>)
|
|
target_link_libraries(ggml_shared PUBLIC Threads::Threads ${LLAMA_EXTRA_LIBS})
|
|
install(TARGETS ggml_shared LIBRARY)
|
|
endif()
|
|
|
|
# llama
|
|
|
|
add_library(llama
|
|
llama.cpp
|
|
llama.h
|
|
)
|
|
|
|
target_include_directories(llama PUBLIC .)
|
|
target_compile_features(llama PUBLIC cxx_std_11) # don't bump
|
|
target_link_libraries(llama PRIVATE
|
|
ggml
|
|
${LLAMA_EXTRA_LIBS}
|
|
)
|
|
|
|
if (BUILD_SHARED_LIBS)
|
|
set_target_properties(llama PROPERTIES POSITION_INDEPENDENT_CODE ON)
|
|
target_compile_definitions(llama PRIVATE LLAMA_SHARED LLAMA_BUILD)
|
|
if (LLAMA_METAL)
|
|
set_target_properties(llama PROPERTIES RESOURCE "${CMAKE_CURRENT_SOURCE_DIR}/ggml-metal.metal")
|
|
endif()
|
|
install(TARGETS llama LIBRARY)
|
|
endif()
|
|
|
|
#
|
|
# install
|
|
#
|
|
|
|
include(GNUInstallDirs)
|
|
install(
|
|
FILES convert.py
|
|
PERMISSIONS
|
|
OWNER_READ
|
|
OWNER_WRITE
|
|
OWNER_EXECUTE
|
|
GROUP_READ
|
|
GROUP_EXECUTE
|
|
WORLD_READ
|
|
WORLD_EXECUTE
|
|
DESTINATION ${CMAKE_INSTALL_BINDIR})
|
|
install(
|
|
FILES convert-lora-to-ggml.py
|
|
PERMISSIONS
|
|
OWNER_READ
|
|
OWNER_WRITE
|
|
OWNER_EXECUTE
|
|
GROUP_READ
|
|
GROUP_EXECUTE
|
|
WORLD_READ
|
|
WORLD_EXECUTE
|
|
DESTINATION ${CMAKE_INSTALL_BINDIR})
|
|
if (LLAMA_METAL)
|
|
install(
|
|
FILES ggml-metal.metal
|
|
PERMISSIONS
|
|
OWNER_READ
|
|
OWNER_WRITE
|
|
GROUP_READ
|
|
WORLD_READ
|
|
DESTINATION ${CMAKE_INSTALL_BINDIR})
|
|
endif()
|
|
|
|
#
|
|
# programs, examples and tests
|
|
#
|
|
|
|
add_subdirectory(common)
|
|
|
|
if (LLAMA_BUILD_TESTS AND NOT CMAKE_JS_VERSION)
|
|
include(CTest)
|
|
add_subdirectory(tests)
|
|
endif ()
|
|
|
|
if (LLAMA_BUILD_EXAMPLES)
|
|
add_subdirectory(examples)
|
|
add_subdirectory(pocs)
|
|
endif()
|