diff --git a/.github/workflows/build.yml b/.github/workflows/build.yml index b6e21b4ec..84faad37a 100644 --- a/.github/workflows/build.yml +++ b/.github/workflows/build.yml @@ -197,6 +197,8 @@ jobs: strategy: matrix: include: + - build: 'noavx' + defines: '-DLLAMA_BUILD_SERVER=ON -DLLAMA_AVX=OFF -DLLAMA_AVX2=OFF -DLLAMA_FMA=OFF' - build: 'avx2' defines: '-DLLAMA_BUILD_SERVER=ON' - build: 'avx' diff --git a/CMakeLists.txt b/CMakeLists.txt index abc96814d..d085bc835 100644 --- a/CMakeLists.txt +++ b/CMakeLists.txt @@ -67,11 +67,13 @@ endif() option(LLAMA_ACCELERATE "llama: enable Accelerate framework" ON) option(LLAMA_BLAS "llama: use BLAS" OFF) set(LLAMA_BLAS_VENDOR "Generic" CACHE STRING "llama: BLAS library vendor") -option(LLAMA_CUBLAS "llama: use cuBLAS" OFF) +option(LLAMA_CUBLAS "llama: use CUDA" OFF) +#option(LLAMA_CUDA_CUBLAS "llama: use cuBLAS for prompt processing" OFF) +set(LLAMA_CUDA_MMQ_Y "64" CACHE STRING "llama: y tile size for mmq CUDA kernels") option(LLAMA_CUDA_FORCE_DMMV "llama: use dmmv instead of mmvq CUDA kernels" OFF) set(LLAMA_CUDA_DMMV_X "32" CACHE STRING "llama: x stride for dmmv CUDA kernels") set(LLAMA_CUDA_MMV_Y "1" CACHE STRING "llama: y block size for mmv CUDA kernels") -option(LLAMA_CUDA_DMMV_F16 "llama: use 16 bit floats for dmmv CUDA kernels" OFF) +option(LLAMA_CUDA_F16 "llama: use 16 bit floats for some calculations" OFF) set(LLAMA_CUDA_KQUANTS_ITER "2" CACHE STRING "llama: iters./thread per block for Q2_K/Q6_K") option(LLAMA_CLBLAST "llama: use CLBlast" OFF) option(LLAMA_METAL "llama: use Metal" OFF) @@ -251,6 +253,10 @@ if (LLAMA_CUBLAS) 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() + add_compile_definitions(GGML_CUDA_MMQ_Y=${LLAMA_CUDA_MMQ_Y}) if (LLAMA_CUDA_FORCE_DMMV) add_compile_definitions(GGML_CUDA_FORCE_DMMV) endif() @@ -259,8 +265,8 @@ if (LLAMA_CUBLAS) if (DEFINED LLAMA_CUDA_DMMV_Y) add_compile_definitions(GGML_CUDA_MMV_Y=${LLAMA_CUDA_DMMV_Y}) # for backwards compatibility endif() - if (LLAMA_CUDA_DMMV_F16) - add_compile_definitions(GGML_CUDA_DMMV_F16) + 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}) @@ -271,10 +277,14 @@ if (LLAMA_CUBLAS) endif() if (NOT DEFINED CMAKE_CUDA_ARCHITECTURES) - if (LLAMA_CUDA_DMMV_F16) - set(CMAKE_CUDA_ARCHITECTURES "60;61") # needed for f16 CUDA intrinsics + # 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") # lowest CUDA 12 standard + lowest for integer intrinsics + 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}") @@ -357,6 +367,7 @@ if (LLAMA_ALL_WARNINGS) -Wshadow -Wstrict-prototypes -Wpointer-arith + -Wmissing-prototypes ) set(cxx_flags -Wall @@ -496,6 +507,8 @@ endif() add_library(ggml OBJECT ggml.c ggml.h + ggml-alloc.c + ggml-alloc.h ${GGML_SOURCES_CUDA} ${GGML_SOURCES_OPENCL} ${GGML_SOURCES_METAL} diff --git a/Makefile b/Makefile index 5f8a0ae21..54a838223 100644 --- a/Makefile +++ b/Makefile @@ -63,7 +63,8 @@ ifdef LLAMA_SERVER_VERBOSE endif # warnings -CFLAGS += -Wall -Wextra -Wpedantic -Wcast-qual -Wdouble-promotion -Wshadow -Wstrict-prototypes -Wpointer-arith +CFLAGS += -Wall -Wextra -Wpedantic -Wcast-qual -Wdouble-promotion -Wshadow -Wstrict-prototypes -Wpointer-arith \ + -Wmissing-prototypes CXXFLAGS += -Wall -Wextra -Wpedantic -Wcast-qual -Wno-unused-function -Wno-multichar # OS specific @@ -141,6 +142,28 @@ ifeq ($(UNAME_M),$(filter $(UNAME_M),x86_64 i686 amd64)) #CXXFLAGS += -mssse3 endif +ifneq ($(filter aarch64%,$(UNAME_M)),) + # Apple M1, M2, etc. + # Raspberry Pi 3, 4, Zero 2 (64-bit) + CFLAGS += -mcpu=native + CXXFLAGS += -mcpu=native +endif + +ifneq ($(filter armv6%,$(UNAME_M)),) + # Raspberry Pi 1, Zero + CFLAGS += -mfpu=neon-fp-armv8 -mfp16-format=ieee -mno-unaligned-access +endif + +ifneq ($(filter armv7%,$(UNAME_M)),) + # Raspberry Pi 2 + CFLAGS += -mfpu=neon-fp-armv8 -mfp16-format=ieee -mno-unaligned-access -funsafe-math-optimizations +endif + +ifneq ($(filter armv8%,$(UNAME_M)),) + # Raspberry Pi 3, 4, Zero 2 (32-bit) + CFLAGS += -mfp16-format=ieee -mno-unaligned-access +endif + ifneq ($(filter ppc64%,$(UNAME_M)),) POWER9_M := $(shell grep "POWER9" /proc/cpuinfo) ifneq (,$(findstring POWER9,$(POWER9_M))) @@ -193,7 +216,7 @@ ifdef LLAMA_CUBLAS CXXFLAGS += -DGGML_USE_CUBLAS -I/usr/local/cuda/include -I/opt/cuda/include -I$(CUDA_PATH)/targets/x86_64-linux/include LDFLAGS += -lcublas -lculibos -lcudart -lcublasLt -lpthread -ldl -lrt -L/usr/local/cuda/lib64 -L/opt/cuda/lib64 -L$(CUDA_PATH)/targets/x86_64-linux/lib OBJS += ggml-cuda.o - NVCCFLAGS = --forward-unknown-to-host-compiler + NVCCFLAGS = --forward-unknown-to-host-compiler -use_fast_math ifdef LLAMA_CUDA_NVCC NVCC = $(LLAMA_CUDA_NVCC) else @@ -219,19 +242,30 @@ else ifdef LLAMA_CUDA_DMMV_Y else NVCCFLAGS += -DGGML_CUDA_MMV_Y=1 endif # LLAMA_CUDA_MMV_Y +ifdef LLAMA_CUDA_F16 + NVCCFLAGS += -DGGML_CUDA_F16 +endif # LLAMA_CUDA_F16 ifdef LLAMA_CUDA_DMMV_F16 - NVCCFLAGS += -DGGML_CUDA_DMMV_F16 + NVCCFLAGS += -DGGML_CUDA_F16 endif # LLAMA_CUDA_DMMV_F16 ifdef LLAMA_CUDA_KQUANTS_ITER NVCCFLAGS += -DK_QUANTS_PER_ITERATION=$(LLAMA_CUDA_KQUANTS_ITER) else NVCCFLAGS += -DK_QUANTS_PER_ITERATION=2 endif +ifdef LLAMA_CUDA_MMQ_Y + NVCCFLAGS += -DGGML_CUDA_MMQ_Y=$(LLAMA_CUDA_MMQ_Y) +else + NVCCFLAGS += -DGGML_CUDA_MMQ_Y=64 +endif # LLAMA_CUDA_MMQ_Y +#ifdef LLAMA_CUDA_CUBLAS +# NVCCFLAGS += -DGGML_CUDA_CUBLAS +#endif # LLAMA_CUDA_CUBLAS ifdef LLAMA_CUDA_CCBIN NVCCFLAGS += -ccbin $(LLAMA_CUDA_CCBIN) endif ggml-cuda.o: ggml-cuda.cu ggml-cuda.h - $(NVCC) $(NVCCFLAGS) $(CXXFLAGS) -Wno-pedantic -c $< -o $@ + $(NVCC) $(NVCCFLAGS) $(subst -Ofast,-O3,$(CXXFLAGS)) -Wno-pedantic -c $< -o $@ endif # LLAMA_CUBLAS ifdef LLAMA_CLBLAST @@ -258,28 +292,6 @@ ifdef LLAMA_METAL OBJS += ggml-metal.o endif # LLAMA_METAL -ifneq ($(filter aarch64%,$(UNAME_M)),) - # Apple M1, M2, etc. - # Raspberry Pi 3, 4, Zero 2 (64-bit) - CFLAGS += -mcpu=native - CXXFLAGS += -mcpu=native -endif - -ifneq ($(filter armv6%,$(UNAME_M)),) - # Raspberry Pi 1, Zero - CFLAGS += -mfpu=neon-fp-armv8 -mfp16-format=ieee -mno-unaligned-access -endif - -ifneq ($(filter armv7%,$(UNAME_M)),) - # Raspberry Pi 2 - CFLAGS += -mfpu=neon-fp-armv8 -mfp16-format=ieee -mno-unaligned-access -funsafe-math-optimizations -endif - -ifneq ($(filter armv8%,$(UNAME_M)),) - # Raspberry Pi 3, 4, Zero 2 (32-bit) - CFLAGS += -mfp16-format=ieee -mno-unaligned-access -endif - ifdef LLAMA_METAL ggml-metal.o: ggml-metal.m ggml-metal.h $(CC) $(CFLAGS) -c $< -o $@ @@ -317,12 +329,20 @@ $(info ) ggml.o: ggml.c ggml.h ggml-cuda.h $(CC) $(CFLAGS) -c $< -o $@ -llama.o: llama.cpp ggml.h ggml-cuda.h ggml-metal.h llama.h llama-util.h +ggml-alloc.o: ggml-alloc.c ggml.h ggml-alloc.h + $(CC) $(CFLAGS) -c $< -o $@ + +OBJS += ggml-alloc.o + +llama.o: llama.cpp ggml.h ggml-alloc.h ggml-cuda.h ggml-metal.h llama.h llama-util.h $(CXX) $(CXXFLAGS) -c $< -o $@ common.o: examples/common.cpp examples/common.h $(CXX) $(CXXFLAGS) -c $< -o $@ +console.o: examples/console.cpp examples/console.h + $(CXX) $(CXXFLAGS) -c $< -o $@ + grammar-parser.o: examples/grammar-parser.cpp examples/grammar-parser.h $(CXX) $(CXXFLAGS) -c $< -o $@ @@ -336,7 +356,7 @@ clean: # Examples # -main: examples/main/main.cpp build-info.h ggml.o llama.o common.o grammar-parser.o $(OBJS) +main: examples/main/main.cpp build-info.h ggml.o llama.o common.o console.o grammar-parser.o $(OBJS) $(CXX) $(CXXFLAGS) $(filter-out %.h,$^) -o $@ $(LDFLAGS) @echo @echo '==== Run ./main -h for help. ====' @@ -360,7 +380,7 @@ embedding: examples/embedding/embedding.cpp build-info.h ggml. save-load-state: examples/save-load-state/save-load-state.cpp build-info.h ggml.o llama.o common.o $(OBJS) $(CXX) $(CXXFLAGS) $(filter-out %.h,$^) -o $@ $(LDFLAGS) -server: examples/server/server.cpp examples/server/httplib.h examples/server/json.hpp examples/server/index.html.hpp examples/server/index.js.hpp examples/server/completion.js.hpp build-info.h ggml.o llama.o common.o $(OBJS) +server: examples/server/server.cpp examples/server/httplib.h examples/server/json.hpp examples/server/index.html.hpp examples/server/index.js.hpp examples/server/completion.js.hpp build-info.h ggml.o llama.o common.o grammar-parser.o $(OBJS) $(CXX) $(CXXFLAGS) -Iexamples/server $(filter-out %.h,$(filter-out %.hpp,$^)) -o $@ $(LDFLAGS) $(LWINSOCK2) $(LIB_PRE)embdinput$(DSO_EXT): examples/embd-input/embd-input.h examples/embd-input/embd-input-lib.cpp build-info.h ggml.o llama.o common.o $(OBJS) @@ -401,13 +421,13 @@ benchmark-matmult: examples/benchmark/benchmark-matmult.cpp build-info.h ggml.o vdot: pocs/vdot/vdot.cpp ggml.o $(OBJS) $(CXX) $(CXXFLAGS) $^ -o $@ $(LDFLAGS) -tests/test-double-float: tests/test-double-float.c build-info.h ggml.o llama.o common.o $(OBJS) +tests/test-double-float: tests/test-double-float.cpp build-info.h ggml.o llama.o common.o $(OBJS) $(CXX) $(CXXFLAGS) $(filter-out %.txt,$^) -o $@ $(LDFLAGS) -tests/test-grad0: tests/test-grad0.c build-info.h ggml.o llama.o common.o $(OBJS) +tests/test-grad0: tests/test-grad0.cpp build-info.h ggml.o llama.o common.o $(OBJS) $(CXX) $(CXXFLAGS) $(filter-out %.txt,$^) -o $@ $(LDFLAGS) -tests/test-opt: tests/test-opt.c build-info.h ggml.o llama.o common.o $(OBJS) +tests/test-opt: tests/test-opt.cpp build-info.h ggml.o llama.o common.o $(OBJS) $(CXX) $(CXXFLAGS) $(filter-out %.txt,$^) -o $@ $(LDFLAGS) tests/test-quantize-fns: tests/test-quantize-fns.cpp build-info.h ggml.o llama.o common.o $(OBJS) diff --git a/README.md b/README.md index a0e0ea2e0..2ece294b7 100644 --- a/README.md +++ b/README.md @@ -77,9 +77,10 @@ as the main playground for developing new features for the [ggml](https://github **Supported models:** - [X] LLaMA 🦙 +- [x] LLaMA 2 🦙🦙 - [X] [Alpaca](https://github.com/ggerganov/llama.cpp#instruction-mode-with-alpaca) - [X] [GPT4All](https://github.com/ggerganov/llama.cpp#using-gpt4all) -- [X] [Chinese LLaMA / Alpaca](https://github.com/ymcui/Chinese-LLaMA-Alpaca) +- [X] [Chinese LLaMA / Alpaca](https://github.com/ymcui/Chinese-LLaMA-Alpaca) and [Chinese LLaMA-2 / Alpaca-2](https://github.com/ymcui/Chinese-LLaMA-Alpaca-2) - [X] [Vigogne (French)](https://github.com/bofenghuang/vigogne) - [X] [Vicuna](https://github.com/ggerganov/llama.cpp/discussions/643#discussioncomment-5533894) - [X] [Koala](https://bair.berkeley.edu/blog/2023/04/03/koala/) @@ -87,6 +88,7 @@ as the main playground for developing new features for the [ggml](https://github - [X] [Pygmalion 7B / Metharme 7B](#using-pygmalion-7b--metharme-7b) - [X] [WizardLM](https://github.com/nlpxucan/WizardLM) - [X] [Baichuan-7B](https://huggingface.co/baichuan-inc/baichuan-7B) and its derivations (such as [baichuan-7b-sft](https://huggingface.co/hiyouga/baichuan-7b-sft)) +- [X] [Aquila-7B](https://huggingface.co/BAAI/Aquila-7B) / [AquilaChat-7B](https://huggingface.co/BAAI/AquilaChat-7B) **Bindings:** @@ -399,12 +401,16 @@ Building the program with BLAS support may lead to some performance improvements The environment variable [`CUDA_VISIBLE_DEVICES`](https://docs.nvidia.com/cuda/cuda-c-programming-guide/index.html#env-vars) can be used to specify which GPU(s) will be used. The following compilation options are also available to tweak performance: + | Option | Legal values | Default | Description | |-------------------------|------------------------|---------|-------------| + | LLAMA_CUDA_MMQ_Y | Positive integer >= 32 | 64 | Tile size in y direction when using the custom CUDA kernels for prompt processing. Higher values can be faster depending on the amount of shared memory available. Power of 2 heavily recommended. | | LLAMA_CUDA_FORCE_DMMV | Boolean | false | Force the use of dequantization + matrix vector multiplication kernels instead of using kernels that do matrix vector multiplication on quantized data. By default the decision is made based on compute capability (MMVQ for 6.1/Pascal/GTX 1000 or higher). Does not affect k-quants. | | LLAMA_CUDA_DMMV_X | Positive integer >= 32 | 32 | Number of values in x direction processed by the CUDA dequantization + matrix vector multiplication kernel per iteration. Increasing this value can improve performance on fast GPUs. Power of 2 heavily recommended. Does not affect k-quants. | - | LLAMA_CUDA_MMV_Y | Positive integer | 1 | Block size in y direction for the CUDA mul mat vec kernels. Increasing this value can improve performance on fast GPUs. Power of 2 recommended. Does not affect k-quants. | - | LLAMA_CUDA_DMMV_F16 | Boolean | false | If enabled, use half-precision floating point arithmetic for the CUDA dequantization + mul mat vec kernels. Can improve performance on relatively recent GPUs. | + | LLAMA_CUDA_MMV_Y | Positive integer | 1 | Block size in y direction for the CUDA mul mat vec kernels. Increasing this value can improve performance on fast GPUs. Power of 2 recommended. Does not affect k-quants. | + | LLAMA_CUDA_F16 | Boolean | false | If enabled, use half-precision floating point arithmetic for the CUDA dequantization + mul mat vec kernels and for the q4_1 and q5_1 matrix matrix multiplication kernels. Can improve performance on relatively recent GPUs. | | LLAMA_CUDA_KQUANTS_ITER | 1 or 2 | 2 | Number of values processed per iteration and per CUDA thread for Q2_K and Q6_K quantization formats. Setting this value to 1 can improve performance for slow GPUs. | - #### CLBlast @@ -487,6 +493,9 @@ Building the program with BLAS support may lead to some performance improvements # obtain the original LLaMA model weights and place them in ./models ls ./models 65B 30B 13B 7B tokenizer_checklist.chk tokenizer.model + # [Optional] for models using BPE tokenizers + ls ./models + 65B 30B 13B 7B vocab.json # install Python dependencies python3 -m pip install -r requirements.txt @@ -494,6 +503,9 @@ python3 -m pip install -r requirements.txt # convert the 7B model to ggml FP16 format python3 convert.py models/7B/ + # [Optional] for models using BPE tokenizers + python convert.py models/7B/ --vocabtype bpe + # quantize the model to 4-bits (using q4_0 method) ./quantize ./models/7B/ggml-model-f16.bin ./models/7B/ggml-model-q4_0.bin q4_0 @@ -650,6 +662,19 @@ python3 convert.py pygmalion-7b/ --outtype q4_1 - The LLaMA models are officially distributed by Facebook and will **never** be provided through this repository. - Refer to [Facebook's LLaMA repository](https://github.com/facebookresearch/llama/pull/73/files) if you need to request access to the model data. +### Obtaining and using the Facebook LLaMA 2 model + +- Refer to [Facebook's LLaMA download page](https://ai.meta.com/resources/models-and-libraries/llama-downloads/) if you want to access the model data. +- Alternatively, if you want to save time and space, you can download already converted and quantized models from [TheBloke](https://huggingface.co/TheBloke), including: + - [LLaMA 2 7B base](https://huggingface.co/TheBloke/Llama-2-7B-GGML) + - [LLaMA 2 13B base](https://huggingface.co/TheBloke/Llama-2-13B-GGML) + - [LLaMA 2 70B base](https://huggingface.co/TheBloke/Llama-2-70B-GGML) + - [LLaMA 2 7B chat](https://huggingface.co/TheBloke/Llama-2-7B-chat-GGML) + - [LLaMA 2 13B chat](https://huggingface.co/TheBloke/Llama-2-13B-chat-GGML) + - [LLaMA 2 70B chat](https://huggingface.co/TheBloke/Llama-2-70B-chat-GGML) +- Specify `-eps 1e-5` for best generation quality +- Specify `-gqa 8` for 70B models to work + ### Verifying the model files Please verify the [sha256 checksums](SHA256SUMS) of all downloaded model files to confirm that you have the correct model data files before creating an issue relating to your model files. diff --git a/build.zig b/build.zig index 2287d2a2c..04c88d8a2 100644 --- a/build.zig +++ b/build.zig @@ -1,68 +1,87 @@ +// Compatible with Zig Version 0.11.0 const std = @import("std"); -const commit_hash = @embedFile(".git/refs/heads/master"); +const Compile = std.Build.Step.Compile; +const ConfigHeader = std.Build.Step.ConfigHeader; +const Mode = std.builtin.Mode; +const CrossTarget = std.zig.CrossTarget; + +const Maker = struct { + builder: *std.build.Builder, + target: CrossTarget, + optimize: Mode, + config_header: *ConfigHeader, + + const cflags = .{"-std=c11"}; + const cxxflags = .{"-std=c++11"}; + + fn init(builder: *std.build.Builder) Maker { + const commit_hash = @embedFile(".git/refs/heads/master"); + const config_header = builder.addConfigHeader( + .{ .style = .blank, .include_path = "build-info.h" }, + .{ + .BUILD_NUMBER = 0, + .BUILD_COMMIT = commit_hash[0 .. commit_hash.len - 1], // omit newline + }, + ); + return Maker{ + .builder = builder, + .target = builder.standardTargetOptions(.{}), + .optimize = builder.standardOptimizeOption(.{}), + .config_header = config_header, + }; + } + + fn obj(m: *const Maker, name: []const u8, src: []const u8) *Compile { + const o = m.builder.addObject(.{ .name = name, .target = m.target, .optimize = m.optimize }); + if (std.mem.endsWith(u8, src, ".c")) { + o.addCSourceFiles(&.{src}, &cflags); + o.linkLibC(); + } else { + o.addCSourceFiles(&.{src}, &cxxflags); + o.linkLibCpp(); + } + o.addIncludePath(.{ .path = "." }); + o.addIncludePath(.{ .path = "./examples" }); + return o; + } + + fn exe(m: *const Maker, name: []const u8, src: []const u8, deps: []const *Compile) *Compile { + const e = m.builder.addExecutable(.{ .name = name, .target = m.target, .optimize = m.optimize }); + e.addIncludePath(.{ .path = "." }); + e.addIncludePath(.{ .path = "./examples" }); + e.addCSourceFiles(&.{src}, &cxxflags); + for (deps) |d| e.addObject(d); + e.linkLibC(); + e.linkLibCpp(); + e.addConfigHeader(m.config_header); + m.builder.installArtifact(e); + + // Currently a bug is preventing correct linking for optimized builds for Windows: + // https://github.com/ziglang/zig/issues/15958 + if (e.target.isWindows()) { + e.want_lto = false; + } + return e; + } +}; -// Zig Version: 0.11.0-dev.3986+e05c242cd pub fn build(b: *std.build.Builder) void { - const target = b.standardTargetOptions(.{}); - const optimize = b.standardOptimizeOption(.{}); + const make = Maker.init(b); - const config_header = b.addConfigHeader( - .{ .style = .blank, .include_path = "build-info.h" }, - .{ - .BUILD_NUMBER = 0, - .BUILD_COMMIT = commit_hash[0 .. commit_hash.len - 1], // omit newline - }, - ); + const ggml = make.obj("ggml", "ggml.c"); + const ggml_alloc = make.obj("ggml-alloc", "ggml-alloc.c"); + const llama = make.obj("llama", "llama.cpp"); + const common = make.obj("common", "examples/common.cpp"); + const grammar_parser = make.obj("grammar-parser", "examples/grammar-parser.cpp"); - const lib = b.addStaticLibrary(.{ - .name = "llama", - .target = target, - .optimize = optimize, - }); - lib.linkLibC(); - lib.linkLibCpp(); - lib.addIncludePath("."); - lib.addIncludePath("./examples"); - lib.addConfigHeader(config_header); - lib.addCSourceFiles(&.{"ggml.c"}, &.{"-std=c11"}); - lib.addCSourceFiles(&.{"llama.cpp"}, &.{"-std=c++11"}); - b.installArtifact(lib); + _ = make.exe("main", "examples/main/main.cpp", &.{ ggml, ggml_alloc, llama, common, grammar_parser }); + _ = make.exe("quantize", "examples/quantize/quantize.cpp", &.{ ggml, ggml_alloc, llama }); + _ = make.exe("perplexity", "examples/perplexity/perplexity.cpp", &.{ ggml, ggml_alloc, llama, common }); + _ = make.exe("embedding", "examples/embedding/embedding.cpp", &.{ ggml, ggml_alloc, llama, common }); + _ = make.exe("train-text-from-scratch", "examples/train-text-from-scratch/train-text-from-scratch.cpp", &.{ ggml, ggml_alloc, llama }); - const examples = .{ - "main", - "baby-llama", - "embedding", - "metal", - "perplexity", - "quantize", - "quantize-stats", - "save-load-state", - "server", - "simple", - "train-text-from-scratch", - }; - - inline for (examples) |example_name| { - const exe = b.addExecutable(.{ - .name = example_name, - .target = target, - .optimize = optimize, - }); - exe.addIncludePath("."); - exe.addIncludePath("./examples"); - exe.addConfigHeader(config_header); - exe.addCSourceFiles(&.{ - std.fmt.comptimePrint("examples/{s}/{s}.cpp", .{ example_name, example_name }), - "examples/common.cpp", - }, &.{"-std=c++11"}); - exe.linkLibrary(lib); - b.installArtifact(exe); - - const run_cmd = b.addRunArtifact(exe); - run_cmd.step.dependOn(b.getInstallStep()); - if (b.args) |args| run_cmd.addArgs(args); - - const run_step = b.step("run-" ++ example_name, "Run the app"); - run_step.dependOn(&run_cmd.step); + const server = make.exe("server", "examples/server/server.cpp", &.{ ggml, ggml_alloc, llama, common, grammar_parser }); + if (server.target.isWindows()) { + server.linkSystemLibrary("ws2_32"); } } diff --git a/convert.py b/convert.py old mode 100755 new mode 100644 index 8d7af06d1..f3bf17980 --- a/convert.py +++ b/convert.py @@ -133,7 +133,7 @@ TENSORS_SET = set(TENSORS_LIST) def find_n_mult(n_ff: int, n_embd: int) -> int: # hardcoded magic range - for n_mult in range(256, 1, -1): + for n_mult in range(8192, 1, -1): calc_ff = (((8*n_embd) // 3 + n_mult - 1) // n_mult)*n_mult if calc_ff == n_ff: return n_mult @@ -141,11 +141,12 @@ def find_n_mult(n_ff: int, n_embd: int) -> int: @dataclass class Params: - n_vocab: int - n_embd: int - n_mult: int - n_head: int - n_layer: int + n_vocab: int + n_embd: int + n_mult: int + n_head: int + n_layer: int + n_kv_head: Optional[int] # This parameter is only used for Llama 2 @staticmethod def guessed(model: 'LazyModel') -> 'Params': @@ -167,11 +168,12 @@ class Params: n_head=n_embd // 128 # guessed return Params( - n_vocab = n_vocab, - n_embd = n_embd, - n_mult = 256, - n_head = n_head, - n_layer = n_layer, + n_vocab = n_vocab, + n_embd = n_embd, + n_mult = 256, + n_head = n_head, + n_layer = n_layer, + n_kv_head = None, ) @staticmethod @@ -183,15 +185,17 @@ class Params: n_head = config["num_attention_heads"]; n_layer = config["num_hidden_layers"]; n_ff = config["intermediate_size"]; + n_kv_head = config.get("num_key_value_heads") n_mult = find_n_mult(n_ff, n_embd); return Params( - n_vocab = n_vocab, - n_embd = n_embd, - n_mult = n_mult, - n_head = n_head, - n_layer = n_layer, + n_vocab = n_vocab, + n_embd = n_embd, + n_mult = n_mult, + n_head = n_head, + n_layer = n_layer, + n_kv_head = n_kv_head, ) # LLaMA v2 70B params.json @@ -200,21 +204,22 @@ class Params: def loadOriginalParamsJson(model: 'LazyModel', config_path: 'Path') -> 'Params': config = json.load(open(config_path)) - n_vocab = config["vocab_size"]; - n_embd = config["dim"]; - n_head = config["n_heads"]; - n_layer = config["n_layers"]; - n_mult = config["multiple_of"]; + n_vocab = config["vocab_size"]; + n_embd = config["dim"]; + n_head = config["n_heads"]; + n_layer = config["n_layers"]; + n_mult = config["multiple_of"]; if n_vocab == -1: n_vocab = model["tok_embeddings.weight"].shape[0] return Params( - n_vocab = n_vocab, - n_embd = n_embd, - n_mult = n_mult, - n_head = n_head, - n_layer = n_layer, + n_vocab = n_vocab, + n_embd = n_embd, + n_mult = n_mult, + n_head = n_head, + n_layer = n_layer, + n_kv_head = None, ) @staticmethod @@ -234,14 +239,21 @@ class Params: class SentencePieceVocab: - def __init__(self, fname_tokenizer: Path, fname_added_tokens: Optional[Path]) -> None: - self.sentencepiece_tokenizer = SentencePieceProcessor(str(fname_tokenizer)) + def __init__(self, fname_tokenizer: Path, fname_added_tokens: Optional[Path], vocabtype: Optional[str]) -> None: + self.vocabtype = vocabtype + if self.vocabtype == "bpe": + self.sentencepiece_tokenizer = json.loads(open(str(fname_tokenizer)).read()) + else: + self.sentencepiece_tokenizer = SentencePieceProcessor(str(fname_tokenizer)) added_tokens: Dict[str, int] if fname_added_tokens is not None: added_tokens = json.load(open(fname_added_tokens)) else: added_tokens = {} - vocab_size: int = self.sentencepiece_tokenizer.vocab_size() + if self.vocabtype == "bpe": + vocab_size: int = len(self.sentencepiece_tokenizer) + else: + vocab_size: int = self.sentencepiece_tokenizer.vocab_size() expected_ids = list(range(vocab_size, vocab_size + len(added_tokens))) actual_ids = sorted(added_tokens.values()) if expected_ids != actual_ids: @@ -255,22 +267,32 @@ class SentencePieceVocab: def sentencepiece_tokens(self) -> Iterable[Tuple[bytes, float]]: tokenizer = self.sentencepiece_tokenizer - for i in range(tokenizer.vocab_size()): + if self.vocabtype == "bpe": + from transformers.models.gpt2 import tokenization_gpt2 + byte_encoder = tokenization_gpt2.bytes_to_unicode() + byte_decoder = {v: k for k, v in byte_encoder.items()} + for i, item in enumerate(tokenizer): text: bytes - if tokenizer.is_unknown(i): - text = " \u2047 ".encode("utf-8") - elif tokenizer.is_control(i): - text = b"" - elif tokenizer.is_byte(i): - piece = tokenizer.id_to_piece(i) - if len(piece) != 6: - raise Exception(f"Invalid token: {piece}") - byte_value = int(piece[3:-1], 16) - text = struct.pack("B", byte_value) - else: - text = tokenizer.id_to_piece(i).replace("\u2581", " ").encode("utf-8") - score: float = tokenizer.get_score(i) + text = b''.join([x.to_bytes(1, byteorder='big') for x in [byte_decoder[y] for y in item]]) + score: float = -i yield text, score + else: + for i in range(tokenizer.vocab_size()): + text: bytes + if tokenizer.is_unknown(i): + text = " \u2047 ".encode("utf-8") + elif tokenizer.is_control(i): + text = b"" + elif tokenizer.is_byte(i): + piece = tokenizer.id_to_piece(i) + if len(piece) != 6: + raise Exception(f"Invalid token: {piece}") + byte_value = int(piece[3:-1], 16) + text = struct.pack("B", byte_value) + else: + text = tokenizer.id_to_piece(i).replace("\u2581", " ").encode("utf-8") + score: float = tokenizer.get_score(i) + yield text, score def added_tokens(self) -> Iterable[Tuple[bytes, float]]: for text in self.added_tokens_list: @@ -300,10 +322,12 @@ class GGMLVocab: Vocab = Union[SentencePieceVocab, GGMLVocab] -def permute(weights: NDArray, n_head: int) -> NDArray: +def permute(weights: NDArray, n_head: int, n_kv_head: Optional[int] = None) -> NDArray: + if n_kv_head is not None and n_head != n_kv_head: + n_head //= n_kv_head return (weights.reshape(n_head, 2, weights.shape[0] // n_head // 2, *weights.shape[1:]) - .swapaxes(1, 2) - .reshape(weights.shape)) + .swapaxes(1, 2) + .reshape(weights.shape)) def dequantize_q4(qvalues_pack32: NDArray, scales: NDArray, addends: Optional[NDArray], g_idx: Optional[NDArray]) -> NDArray: @@ -351,7 +375,7 @@ class Tensor(metaclass=ABCMeta): @abstractmethod def astype(self, data_type: DataType) -> 'Tensor': ... @abstractmethod - def permute(self, n_head: int) -> 'Tensor': ... + def permute(self, n_head: int, n_kv_head: Optional[int] = None) -> 'Tensor': ... @abstractmethod def permute_part(self, n_part: int, n_head: int) -> 'UnquantizedTensor': ... @abstractmethod @@ -389,8 +413,8 @@ class UnquantizedTensor(Tensor): r = self.ndarray.shape[0] // 3 return UnquantizedTensor(self.ndarray[r * n_part : r * n_part + r, ...]) - def permute(self, n_head: int) -> 'UnquantizedTensor': - return UnquantizedTensor(permute(self.ndarray, n_head)) + def permute(self, n_head: int, n_kv_head: Optional[int] = None) -> 'UnquantizedTensor': + return UnquantizedTensor(permute(self.ndarray, n_head, n_kv_head)) def load_unquantized(lazy_tensor: 'LazyTensor', expected_dtype: Any = None, convert: bool = False) -> NDArray: @@ -438,26 +462,34 @@ class GGMLQuantizedTensor(Tensor): def to_ggml(self) -> 'GGMLQuantizedTensor': return self - def permute(self, n_head: int) -> 'GGMLQuantizedTensor': - return GGMLQuantizedTensor(permute(self.ndarray, n_head), self.shape, self.data_type) + def permute(self, n_head: int, n_kv_head: Optional[int] = None) -> 'GGMLQuantizedTensor': + return GGMLQuantizedTensor(permute(self.ndarray, n_head, n_kv_head), self.shape, self.data_type) + def permute_part(self, n_part: int, n_head: int) -> 'UnquantizedTensor': + r = self.ndarray.shape[0] // 3 + return UnquantizedTensor(permute(self.ndarray[r * n_part : r * n_part + r, ...], n_head)) + + def part(self, n_part: int) -> 'UnquantizedTensor': + r = self.ndarray.shape[0] // 3 + return UnquantizedTensor(self.ndarray[r * n_part : r * n_part + r, ...]) GGMLCompatibleTensor = Union[UnquantizedTensor, GGMLQuantizedTensor] class DeferredPermutedTensor(Tensor): - def __init__(self, base: Tensor, n_head: int) -> None: + def __init__(self, base: Tensor, n_head: int, n_kv_head: Optional[int] = None) -> None: self.base = base self.n_head = n_head + self.n_kv_head = n_kv_head self.data_type = self.base.data_type def astype(self, data_type: DataType) -> Tensor: - return self.base.astype(data_type).permute(self.n_head) + return self.base.astype(data_type).permute(self.n_head, self.n_kv_head) def to_ggml(self) -> GGMLCompatibleTensor: - return self.base.to_ggml().permute(self.n_head) + return self.base.to_ggml().permute(self.n_head, self.n_kv_head) - def permute(self, n_head: int) -> Tensor: + def permute(self, n_head: int, n_kv_head: Optional[int] = None) -> Tensor: raise Exception("shouldn't permute twice") @@ -549,8 +581,8 @@ class GPTQForLLaMaQuantizedTensor(Tensor): ret.data_type = QuantizedDataType(groupsize=new_groupsize, have_addends=True, have_g_idx=False) return ret - def permute(self, n_head: int) -> Tensor: - return DeferredPermutedTensor(self, n_head) + def permute(self, n_head: int, n_kv_head: Optional[int] = None) -> Tensor: + return DeferredPermutedTensor(self, n_head, n_kv_head) def to_ggml(self) -> GGMLQuantizedTensor: # The output format looks like this: @@ -681,10 +713,10 @@ def merge_multifile_models(models_plus: List[ModelPlus]) -> ModelPlus: return ModelPlus(model, paths, format, vocab) -def permute_lazy(lazy_tensor: LazyTensor, n_head: int) -> LazyTensor: +def permute_lazy(lazy_tensor: LazyTensor, n_head: int, n_kv_head: Optional[int] = None) -> LazyTensor: def load() -> Tensor: - return lazy_tensor.load().permute(n_head) - return LazyTensor(load, lazy_tensor.shape, lazy_tensor.data_type, f'permute({n_head}) ' + lazy_tensor.description) + return lazy_tensor.load().permute(n_head, n_kv_head) + return LazyTensor(load, lazy_tensor.shape, lazy_tensor.data_type, f'permute({n_head}, {n_kv_head}) ' + lazy_tensor.description) def permute_part_lazy(lazy_tensor: LazyTensor, n_part: int, n_head: int) -> LazyTensor: def load() -> Tensor: @@ -709,7 +741,7 @@ def convert_transformers_to_orig(model: LazyModel, params: Params) -> LazyModel: for i in itertools.count(): if f"model.layers.{i}.self_attn.q_proj.weight" in model: out[f"layers.{i}.attention.wq.weight"] = permute_lazy(model[f"model.layers.{i}.self_attn.q_proj.weight"], params.n_head) - out[f"layers.{i}.attention.wk.weight"] = permute_lazy(model[f"model.layers.{i}.self_attn.k_proj.weight"], params.n_head) + out[f"layers.{i}.attention.wk.weight"] = permute_lazy(model[f"model.layers.{i}.self_attn.k_proj.weight"], params.n_head, params.n_kv_head) out[f"layers.{i}.attention.wv.weight"] = model[f"model.layers.{i}.self_attn.v_proj.weight"] elif f"model.layers.{i}.self_attn.W_pack.weight" in model: out[f"layers.{i}.attention.wq.weight"] = permute_part_lazy(model[f"model.layers.{i}.self_attn.W_pack.weight"], 0, params.n_head) @@ -1196,14 +1228,18 @@ def filter_and_sort_tensors(model: LazyModel) -> LazyModel: return {name: model[name] for name in TENSORS_LIST if name in model} -def load_vocab(path: Path) -> SentencePieceVocab: +def load_vocab(path: Path, vocabtype: Optional[str]) -> SentencePieceVocab: + print(f"vocabtype: {vocabtype}") # Be extra-friendly and accept either a file or a directory. Also, if it's # a directory, it might be the model directory, and tokenizer.model might # be in the parent of that. if path.is_dir(): - path2 = path / "tokenizer.model" + vocab_file = "tokenizer.model" + if vocabtype == 'bpe': + vocab_file = "vocab.json" + path2 = path / vocab_file # Use `.parent` instead of /.. to handle the symlink case better. - path3 = path.parent / "tokenizer.model" + path3 = path.parent / vocab_file if path2.exists(): path = path2 elif path3.exists(): @@ -1214,7 +1250,8 @@ def load_vocab(path: Path) -> SentencePieceVocab: "if it's in another directory, pass the directory as --vocab-dir") added_tokens_path = path.parent / "added_tokens.json" print(f"Loading vocab file {path}") - return SentencePieceVocab(path, added_tokens_path if added_tokens_path.exists() else None) + return SentencePieceVocab(path, added_tokens_path if added_tokens_path.exists() else None, + vocabtype) def default_outfile(model_paths: List[Path], file_type: GGMLFileType) -> Path: @@ -1252,6 +1289,7 @@ def main(args_in: Optional[List[str]] = None) -> None: parser.add_argument("--outfile", type=Path, help="path to write to; default: based on input") parser.add_argument("model", type=Path, help="directory containing model file, or model file itself (*.pth, *.pt, *.bin)") + parser.add_argument("--vocabtype", default='spm', choices=["spm", "bpe"], help="vocab format (default: spm)") args = parser.parse_args(args_in) vocab: Vocab @@ -1259,7 +1297,7 @@ def main(args_in: Optional[List[str]] = None) -> None: model_plus = lazy_load_file(args.model) do_dump_model(model_plus) elif args.vocab_only: - vocab = load_vocab(args.vocab_dir or args.model) + vocab = load_vocab(args.vocab_dir or args.model, args.vocabtype) assert args.outfile, "need --outfile if using --vocab-only" outfile = args.outfile OutputFile.write_vocab_only(outfile, vocab) @@ -1273,7 +1311,7 @@ def main(args_in: Optional[List[str]] = None) -> None: vocab = model_plus.vocab else: vocab_dir = args.vocab_dir if args.vocab_dir else model_plus.paths[0].parent - vocab = load_vocab(vocab_dir) + vocab = load_vocab(vocab_dir, args.vocabtype) params = Params.load(model_plus) model = model_plus.model model = do_necessary_conversions(model, params) diff --git a/examples/CMakeLists.txt b/examples/CMakeLists.txt index 4b1f1cf44..a7b26776a 100644 --- a/examples/CMakeLists.txt +++ b/examples/CMakeLists.txt @@ -13,6 +13,8 @@ set(TARGET common) add_library(${TARGET} OBJECT common.h common.cpp + console.h + console.cpp grammar-parser.h grammar-parser.cpp ) diff --git a/examples/baby-llama/baby-llama.cpp b/examples/baby-llama/baby-llama.cpp index f9dc0aaa6..6fa55b319 100644 --- a/examples/baby-llama/baby-llama.cpp +++ b/examples/baby-llama/baby-llama.cpp @@ -8,7 +8,11 @@ #pragma warning(disable: 4244 4267) // possible loss of data #endif -static const float rms_norm_eps = 1e-6f; +#ifdef LLAMA_DEFAULT_RMS_EPS +static const float rms_norm_eps = LLAMA_DEFAULT_RMS_EPS; +#else +static const float rms_norm_eps = 5e-6f; +#endif float frand() { return (float)rand()/(float)RAND_MAX; diff --git a/examples/common.cpp b/examples/common.cpp index 0e88a128a..4d3ba9bb2 100644 --- a/examples/common.cpp +++ b/examples/common.cpp @@ -25,7 +25,6 @@ #else #include #include -#include #endif #if defined(_MSC_VER) @@ -195,6 +194,12 @@ bool gpt_params_parse(int argc, char ** argv, gpt_params & params) { break; } params.rope_freq_scale = std::stof(argv[i]); + } else if (arg == "--rope-scale") { + if (++i >= argc) { + invalid_param = true; + break; + } + params.rope_freq_scale = 1.0f/std::stof(argv[i]); } else if (arg == "--memory-f32") { params.memory_f16 = false; } else if (arg == "--top-p") { @@ -329,6 +334,8 @@ bool gpt_params_parse(int argc, char ** argv, gpt_params & params) { params.instruct = true; } else if (arg == "--multiline-input") { params.multiline_input = true; + } else if (arg == "--simple-io") { + params.simple_io = true; } else if (arg == "--color") { params.use_color = true; } else if (arg == "--mlock") { @@ -352,7 +359,7 @@ bool gpt_params_parse(int argc, char ** argv, gpt_params & params) { #ifdef GGML_USE_CUBLAS params.main_gpu = std::stoi(argv[i]); #else - fprintf(stderr, "warning: llama.cpp was compiled without cuBLAS. It is not possible to set a main GPU.\n"); + fprintf(stderr, "warning: llama.cpp was compiled without cuBLAS. It is not possible to set a main GPU.\n"); #endif } else if (arg == "--tensor-split" || arg == "-ts") { if (++i >= argc) { @@ -376,13 +383,19 @@ bool gpt_params_parse(int argc, char ** argv, gpt_params & params) { } } #else - fprintf(stderr, "warning: llama.cpp was compiled without cuBLAS. It is not possible to set a tensor split.\n"); + fprintf(stderr, "warning: llama.cpp was compiled without cuBLAS. It is not possible to set a tensor split.\n"); +#endif // GGML_USE_CUBLAS + } else if (arg == "--mul-mat-q" || arg == "-mmq") { +#ifdef GGML_USE_CUBLAS + params.mul_mat_q = true; +#else + fprintf(stderr, "warning: llama.cpp was compiled without cuBLAS. It is not possible to use mul_mat_q kernels.\n"); #endif // GGML_USE_CUBLAS } else if (arg == "--low-vram" || arg == "-lv") { #ifdef GGML_USE_CUBLAS params.low_vram = true; #else - fprintf(stderr, "warning: llama.cpp was compiled without cuBLAS. It is not possible to set lower vram usage.\n"); + fprintf(stderr, "warning: llama.cpp was compiled without cuBLAS. It is not possible to set lower vram usage.\n"); #endif // GGML_USE_CUBLAS } else if (arg == "--no-mmap") { params.use_mmap = false; @@ -402,8 +415,14 @@ bool gpt_params_parse(int argc, char ** argv, gpt_params & params) { params.antiprompt.push_back(argv[i]); } else if (arg == "--perplexity") { params.perplexity = true; - } else if (arg == "--perplexity-lines") { - params.perplexity_lines = true; + } else if (arg == "--hellaswag") { + params.hellaswag = true; + } else if (arg == "--hellaswag-tasks") { + if (++i >= argc) { + invalid_param = true; + break; + } + params.hellaswag_tasks = std::stoi(argv[i]); } else if (arg == "--ignore-eos") { params.logit_bias[llama_token_eos()] = -INFINITY; } else if (arg == "--no-penalize-nl") { @@ -432,6 +451,8 @@ bool gpt_params_parse(int argc, char ** argv, gpt_params & params) { exit(0); } else if (arg == "--random-prompt") { params.random_prompt = true; + } else if (arg == "--in-prefix-bos") { + params.input_prefix_bos = true; } else if (arg == "--in-prefix") { if (++i >= argc) { invalid_param = true; @@ -517,6 +538,7 @@ void gpt_print_usage(int /*argc*/, char ** argv, const gpt_params & params) { fprintf(stdout, " not supported with --interactive or other interactive options\n"); fprintf(stdout, " --prompt-cache-ro if specified, uses the prompt cache but does not update it.\n"); fprintf(stdout, " --random-prompt start with a randomized prompt.\n"); + fprintf(stdout, " --in-prefix-bos prefix BOS to user inputs, preceding the `--in-prefix` string\n"); fprintf(stdout, " --in-prefix STRING string to prefix user inputs with (default: empty)\n"); fprintf(stdout, " --in-suffix STRING string to suffix after user inputs with (default: empty)\n"); fprintf(stdout, " -f FNAME, --file FNAME\n"); @@ -548,16 +570,18 @@ void gpt_print_usage(int /*argc*/, char ** argv, const gpt_params & params) { fprintf(stdout, " --cfg-negative-prompt PROMPT \n"); fprintf(stdout, " negative prompt to use for guidance. (default: empty)\n"); fprintf(stdout, " --cfg-scale N strength of guidance (default: %f, 1.0 = disable)\n", params.cfg_scale); - fprintf(stdout, " --rope-freq-base N RoPE base frequency (default: %.1f)\n", params.rope_freq_base); - fprintf(stdout, " --rope-freq-scale N RoPE frequency scaling factor (default: %g)\n", params.rope_freq_scale); + fprintf(stdout, " --rope-scale N RoPE context linear scaling factor, inverse of --rope-freq-scale (default: %g)\n", 1.0f/params.rope_freq_scale); + fprintf(stdout, " --rope-freq-base N RoPE base frequency, used by NTK-aware scaling (default: %.1f)\n", params.rope_freq_base); + fprintf(stdout, " --rope-freq-scale N RoPE frequency linear scaling factor, inverse of --rope-scale (default: %g)\n", params.rope_freq_scale); fprintf(stdout, " --ignore-eos ignore end of stream token and continue generating (implies --logit-bias 2-inf)\n"); fprintf(stdout, " --no-penalize-nl do not penalize newline token\n"); fprintf(stdout, " --memory-f32 use f32 instead of f16 for memory key+value (default: disabled)\n"); fprintf(stdout, " not recommended: doubles context memory required and no measurable increase in quality\n"); fprintf(stdout, " --temp N temperature (default: %.1f)\n", (double)params.temp); fprintf(stdout, " --perplexity compute perplexity over each ctx window of the prompt\n"); - fprintf(stdout, " --perplexity-lines compute perplexity over each line of the prompt\n"); - fprintf(stdout, " --keep number of tokens to keep from the initial prompt (default: %d, -1 = all)\n", params.n_keep); + fprintf(stdout, " --hellaswag compute HellaSwag score over random tasks from datafile supplied with -f\n"); + fprintf(stdout, " --hellaswag-tasks N number of tasks to use when computing the HellaSwag score (default: %zu)\n", params.hellaswag_tasks); + fprintf(stdout, " --keep N number of tokens to keep from the initial prompt (default: %d, -1 = all)\n", params.n_keep); fprintf(stdout, " --chunks N max number of chunks to process (default: %d, -1 = all)\n", params.n_chunks); if (llama_mlock_supported()) { fprintf(stdout, " --mlock force system to keep model in RAM rather than swapping or compressing\n"); @@ -575,10 +599,14 @@ void gpt_print_usage(int /*argc*/, char ** argv, const gpt_params & params) { fprintf(stdout, " how to split tensors across multiple GPUs, comma-separated list of proportions, e.g. 3,1\n"); fprintf(stdout, " -mg i, --main-gpu i the GPU to use for scratch and small tensors\n" ); fprintf(stdout, " -lv, --low-vram don't allocate VRAM scratch buffer\n" ); + fprintf(stdout, " -mmq, --mul-mat-q use experimental mul_mat_q CUDA kernels instead of cuBLAS. TEMP!!!\n" ); + fprintf(stdout, " Reduces VRAM usage by 700/970/1430 MiB for 7b/13b/33b but prompt processing speed\n" ); + fprintf(stdout, " is still suboptimal, especially q2_K, q3_K, q5_K, and q6_K.\n" ); #endif fprintf(stdout, " --mtest compute maximum memory usage\n"); fprintf(stdout, " --export export the computation graph to 'llama.ggml'\n"); fprintf(stdout, " --verbose-prompt print prompt before generation\n"); + fprintf(stderr, " --simple-io use basic IO for better compatibility in subprocesses and limited consoles\n"); fprintf(stdout, " --lora FNAME apply LoRA adapter (implies --no-mmap)\n"); fprintf(stdout, " --lora-base FNAME optional model to use as a base for the layers modified by the LoRA adapter\n"); fprintf(stdout, " -m FNAME, --model FNAME\n"); @@ -627,6 +655,7 @@ struct llama_context_params llama_context_params_from_gpt_params(const gpt_param lparams.main_gpu = params.main_gpu; lparams.tensor_split = params.tensor_split; lparams.low_vram = params.low_vram; + lparams.mul_mat_q = params.mul_mat_q; lparams.seed = params.seed; lparams.f16_kv = params.memory_f16; lparams.use_mmap = params.use_mmap; @@ -670,376 +699,3 @@ std::tuple llama_init_from_gpt_par return std::make_tuple(model, lctx); } - -void console_init(console_state & con_st) { -#if defined(_WIN32) - // Windows-specific console initialization - DWORD dwMode = 0; - con_st.hConsole = GetStdHandle(STD_OUTPUT_HANDLE); - if (con_st.hConsole == INVALID_HANDLE_VALUE || !GetConsoleMode(con_st.hConsole, &dwMode)) { - con_st.hConsole = GetStdHandle(STD_ERROR_HANDLE); - if (con_st.hConsole != INVALID_HANDLE_VALUE && (!GetConsoleMode(con_st.hConsole, &dwMode))) { - con_st.hConsole = NULL; - } - } - if (con_st.hConsole) { - // Enable ANSI colors on Windows 10+ - if (con_st.use_color && !(dwMode & ENABLE_VIRTUAL_TERMINAL_PROCESSING)) { - SetConsoleMode(con_st.hConsole, dwMode | ENABLE_VIRTUAL_TERMINAL_PROCESSING); - } - // Set console output codepage to UTF8 - SetConsoleOutputCP(CP_UTF8); - } - HANDLE hConIn = GetStdHandle(STD_INPUT_HANDLE); - if (hConIn != INVALID_HANDLE_VALUE && GetConsoleMode(hConIn, &dwMode)) { - // Set console input codepage to UTF16 - _setmode(_fileno(stdin), _O_WTEXT); - - // Turn off ICANON (ENABLE_LINE_INPUT) and ECHO (ENABLE_ECHO_INPUT) - dwMode &= ~(ENABLE_LINE_INPUT | ENABLE_ECHO_INPUT); - SetConsoleMode(hConIn, dwMode); - } -#else - // POSIX-specific console initialization - struct termios new_termios; - tcgetattr(STDIN_FILENO, &con_st.prev_state); - new_termios = con_st.prev_state; - new_termios.c_lflag &= ~(ICANON | ECHO); - new_termios.c_cc[VMIN] = 1; - new_termios.c_cc[VTIME] = 0; - tcsetattr(STDIN_FILENO, TCSANOW, &new_termios); - - con_st.tty = fopen("/dev/tty", "w+"); - if (con_st.tty != nullptr) { - con_st.out = con_st.tty; - } - - setlocale(LC_ALL, ""); -#endif -} - -void console_cleanup(console_state & con_st) { - // Reset console color - console_set_color(con_st, CONSOLE_COLOR_DEFAULT); - -#if !defined(_WIN32) - if (con_st.tty != nullptr) { - con_st.out = stdout; - fclose(con_st.tty); - con_st.tty = nullptr; - } - // Restore the terminal settings on POSIX systems - tcsetattr(STDIN_FILENO, TCSANOW, &con_st.prev_state); -#endif -} - -/* Keep track of current color of output, and emit ANSI code if it changes. */ -void console_set_color(console_state & con_st, console_color_t color) { - if (con_st.use_color && con_st.color != color) { - fflush(stdout); - switch(color) { - case CONSOLE_COLOR_DEFAULT: - fprintf(con_st.out, ANSI_COLOR_RESET); - break; - case CONSOLE_COLOR_PROMPT: - fprintf(con_st.out, ANSI_COLOR_YELLOW); - break; - case CONSOLE_COLOR_USER_INPUT: - fprintf(con_st.out, ANSI_BOLD ANSI_COLOR_GREEN); - break; - case CONSOLE_COLOR_ERROR: - fprintf(con_st.out, ANSI_BOLD ANSI_COLOR_RED); - break; - } - con_st.color = color; - fflush(con_st.out); - } -} - -char32_t getchar32() { -#if defined(_WIN32) - HANDLE hConsole = GetStdHandle(STD_INPUT_HANDLE); - wchar_t high_surrogate = 0; - - while (true) { - INPUT_RECORD record; - DWORD count; - if (!ReadConsoleInputW(hConsole, &record, 1, &count) || count == 0) { - return WEOF; - } - - if (record.EventType == KEY_EVENT && record.Event.KeyEvent.bKeyDown) { - wchar_t wc = record.Event.KeyEvent.uChar.UnicodeChar; - if (wc == 0) { - continue; - } - - if ((wc >= 0xD800) && (wc <= 0xDBFF)) { // Check if wc is a high surrogate - high_surrogate = wc; - continue; - } else if ((wc >= 0xDC00) && (wc <= 0xDFFF)) { // Check if wc is a low surrogate - if (high_surrogate != 0) { // Check if we have a high surrogate - return ((high_surrogate - 0xD800) << 10) + (wc - 0xDC00) + 0x10000; - } - } - - high_surrogate = 0; // Reset the high surrogate - return static_cast(wc); - } - } -#else - wchar_t wc = getwchar(); - if (static_cast(wc) == WEOF) { - return WEOF; - } - -#if WCHAR_MAX == 0xFFFF - if ((wc >= 0xD800) && (wc <= 0xDBFF)) { // Check if wc is a high surrogate - wchar_t low_surrogate = getwchar(); - if ((low_surrogate >= 0xDC00) && (low_surrogate <= 0xDFFF)) { // Check if the next wchar is a low surrogate - return (static_cast(wc & 0x03FF) << 10) + (low_surrogate & 0x03FF) + 0x10000; - } - } - if ((wc >= 0xD800) && (wc <= 0xDFFF)) { // Invalid surrogate pair - return 0xFFFD; // Return the replacement character U+FFFD - } -#endif - - return static_cast(wc); -#endif -} - -void pop_cursor(console_state & con_st) { -#if defined(_WIN32) - if (con_st.hConsole != NULL) { - CONSOLE_SCREEN_BUFFER_INFO bufferInfo; - GetConsoleScreenBufferInfo(con_st.hConsole, &bufferInfo); - - COORD newCursorPosition = bufferInfo.dwCursorPosition; - if (newCursorPosition.X == 0) { - newCursorPosition.X = bufferInfo.dwSize.X - 1; - newCursorPosition.Y -= 1; - } else { - newCursorPosition.X -= 1; - } - - SetConsoleCursorPosition(con_st.hConsole, newCursorPosition); - return; - } -#endif - putc('\b', con_st.out); -} - -int estimateWidth(char32_t codepoint) { -#if defined(_WIN32) - return 1; -#else - return wcwidth(codepoint); -#endif -} - -int put_codepoint(console_state & con_st, const char* utf8_codepoint, size_t length, int expectedWidth) { -#if defined(_WIN32) - CONSOLE_SCREEN_BUFFER_INFO bufferInfo; - if (!GetConsoleScreenBufferInfo(con_st.hConsole, &bufferInfo)) { - // go with the default - return expectedWidth; - } - COORD initialPosition = bufferInfo.dwCursorPosition; - DWORD nNumberOfChars = length; - WriteConsole(con_st.hConsole, utf8_codepoint, nNumberOfChars, &nNumberOfChars, NULL); - - CONSOLE_SCREEN_BUFFER_INFO newBufferInfo; - GetConsoleScreenBufferInfo(con_st.hConsole, &newBufferInfo); - - // Figure out our real position if we're in the last column - if (utf8_codepoint[0] != 0x09 && initialPosition.X == newBufferInfo.dwSize.X - 1) { - DWORD nNumberOfChars; - WriteConsole(con_st.hConsole, &" \b", 2, &nNumberOfChars, NULL); - GetConsoleScreenBufferInfo(con_st.hConsole, &newBufferInfo); - } - - int width = newBufferInfo.dwCursorPosition.X - initialPosition.X; - if (width < 0) { - width += newBufferInfo.dwSize.X; - } - return width; -#else - // we can trust expectedWidth if we've got one - if (expectedWidth >= 0 || con_st.tty == nullptr) { - fwrite(utf8_codepoint, length, 1, con_st.out); - return expectedWidth; - } - - fputs("\033[6n", con_st.tty); // Query cursor position - int x1, x2, y1, y2; - int results = 0; - results = fscanf(con_st.tty, "\033[%d;%dR", &y1, &x1); - - fwrite(utf8_codepoint, length, 1, con_st.tty); - - fputs("\033[6n", con_st.tty); // Query cursor position - results += fscanf(con_st.tty, "\033[%d;%dR", &y2, &x2); - - if (results != 4) { - return expectedWidth; - } - - int width = x2 - x1; - if (width < 0) { - // Calculate the width considering text wrapping - struct winsize w; - ioctl(STDOUT_FILENO, TIOCGWINSZ, &w); - width += w.ws_col; - } - return width; -#endif -} - -void replace_last(console_state & con_st, char ch) { -#if defined(_WIN32) - pop_cursor(con_st); - put_codepoint(con_st, &ch, 1, 1); -#else - fprintf(con_st.out, "\b%c", ch); -#endif -} - -void append_utf8(char32_t ch, std::string & out) { - if (ch <= 0x7F) { - out.push_back(static_cast(ch)); - } else if (ch <= 0x7FF) { - out.push_back(static_cast(0xC0 | ((ch >> 6) & 0x1F))); - out.push_back(static_cast(0x80 | (ch & 0x3F))); - } else if (ch <= 0xFFFF) { - out.push_back(static_cast(0xE0 | ((ch >> 12) & 0x0F))); - out.push_back(static_cast(0x80 | ((ch >> 6) & 0x3F))); - out.push_back(static_cast(0x80 | (ch & 0x3F))); - } else if (ch <= 0x10FFFF) { - out.push_back(static_cast(0xF0 | ((ch >> 18) & 0x07))); - out.push_back(static_cast(0x80 | ((ch >> 12) & 0x3F))); - out.push_back(static_cast(0x80 | ((ch >> 6) & 0x3F))); - out.push_back(static_cast(0x80 | (ch & 0x3F))); - } else { - // Invalid Unicode code point - } -} - -// Helper function to remove the last UTF-8 character from a string -void pop_back_utf8_char(std::string & line) { - if (line.empty()) { - return; - } - - size_t pos = line.length() - 1; - - // Find the start of the last UTF-8 character (checking up to 4 bytes back) - for (size_t i = 0; i < 3 && pos > 0; ++i, --pos) { - if ((line[pos] & 0xC0) != 0x80) break; // Found the start of the character - } - line.erase(pos); -} - -bool console_readline(console_state & con_st, std::string & line) { - console_set_color(con_st, CONSOLE_COLOR_USER_INPUT); - if (con_st.out != stdout) { - fflush(stdout); - } - - line.clear(); - std::vector widths; - bool is_special_char = false; - bool end_of_stream = false; - - char32_t input_char; - while (true) { - fflush(con_st.out); // Ensure all output is displayed before waiting for input - input_char = getchar32(); - - if (input_char == '\r' || input_char == '\n') { - break; - } - - if (input_char == (char32_t) WEOF || input_char == 0x04 /* Ctrl+D*/) { - end_of_stream = true; - break; - } - - if (is_special_char) { - console_set_color(con_st, CONSOLE_COLOR_USER_INPUT); - replace_last(con_st, line.back()); - is_special_char = false; - } - - if (input_char == '\033') { // Escape sequence - char32_t code = getchar32(); - if (code == '[' || code == 0x1B) { - // Discard the rest of the escape sequence - while ((code = getchar32()) != (char32_t) WEOF) { - if ((code >= 'A' && code <= 'Z') || (code >= 'a' && code <= 'z') || code == '~') { - break; - } - } - } - } else if (input_char == 0x08 || input_char == 0x7F) { // Backspace - if (!widths.empty()) { - int count; - do { - count = widths.back(); - widths.pop_back(); - // Move cursor back, print space, and move cursor back again - for (int i = 0; i < count; i++) { - replace_last(con_st, ' '); - pop_cursor(con_st); - } - pop_back_utf8_char(line); - } while (count == 0 && !widths.empty()); - } - } else { - int offset = line.length(); - append_utf8(input_char, line); - int width = put_codepoint(con_st, line.c_str() + offset, line.length() - offset, estimateWidth(input_char)); - if (width < 0) { - width = 0; - } - widths.push_back(width); - } - - if (!line.empty() && (line.back() == '\\' || line.back() == '/')) { - console_set_color(con_st, CONSOLE_COLOR_PROMPT); - replace_last(con_st, line.back()); - is_special_char = true; - } - } - - bool has_more = con_st.multiline_input; - if (is_special_char) { - replace_last(con_st, ' '); - pop_cursor(con_st); - - char last = line.back(); - line.pop_back(); - if (last == '\\') { - line += '\n'; - fputc('\n', con_st.out); - has_more = !has_more; - } else { - // llama will just eat the single space, it won't act as a space - if (line.length() == 1 && line.back() == ' ') { - line.clear(); - pop_cursor(con_st); - } - has_more = false; - } - } else { - if (end_of_stream) { - has_more = false; - } else { - line += '\n'; - fputc('\n', con_st.out); - } - } - - fflush(con_st.out); - return has_more; -} diff --git a/examples/common.h b/examples/common.h index 894a0850a..375bc0a3d 100644 --- a/examples/common.h +++ b/examples/common.h @@ -11,11 +11,6 @@ #include #include -#if !defined (_WIN32) -#include -#include -#endif - // // CLI argument parsing // @@ -34,7 +29,7 @@ struct gpt_params { int32_t main_gpu = 0; // the GPU that is used for scratch and small tensors float tensor_split[LLAMA_MAX_DEVICES] = {0}; // how split tensors should be distributed across GPUs int32_t n_probs = 0; // if greater than 0, output the probabilities of top n_probs tokens. - float rms_norm_eps = 1e-6; // rms norm epsilon + float rms_norm_eps = LLAMA_DEFAULT_RMS_EPS; // rms norm epsilon float rope_freq_base = 10000.0f; // RoPE base frequency float rope_freq_scale = 1.0f; // RoPE frequency scaling factor @@ -70,7 +65,11 @@ struct gpt_params { std::string lora_adapter = ""; // lora adapter path std::string lora_base = ""; // base model path for the lora adapter - bool low_vram = false; // if true, reduce VRAM usage at the cost of performance + bool hellaswag = false; // compute HellaSwag score over random tasks from datafile supplied in prompt + size_t hellaswag_tasks = 400; // number of tasks to use when computing the HellaSwag score + + bool low_vram = false; // if true, reduce VRAM usage at the cost of performance + bool mul_mat_q = false; // if true, use experimental mul_mat_q kernels bool memory_f16 = true; // use f16 instead of f32 for memory kv bool random_prompt = false; // do not randomize prompt if none provided bool use_color = false; // use color to distinguish generations and inputs @@ -81,11 +80,12 @@ struct gpt_params { bool embedding = false; // get only sentence embedding bool interactive_first = false; // wait for user input immediately bool multiline_input = false; // reverse the usage of `\` + bool simple_io = false; // improves compatibility with subprocesses and limited consoles + bool input_prefix_bos = false; // prefix BOS to user inputs, preceding input_prefix bool instruct = false; // instruction mode (used for Alpaca models) bool penalize_nl = true; // consider newlines as a repeatable token bool perplexity = false; // compute perplexity over the prompt - bool perplexity_lines = false; // compute perplexity over each line of the prompt bool use_mmap = true; // use mmap for faster loads bool use_mlock = false; // use mlock to keep model in memory bool mem_test = false; // compute maximum memory usage @@ -112,42 +112,3 @@ std::vector llama_tokenize(struct llama_context * ctx, const std::s std::tuple llama_init_from_gpt_params(const gpt_params & params); struct llama_context_params llama_context_params_from_gpt_params(const gpt_params & params); - -// -// Console utils -// - -#define ANSI_COLOR_RED "\x1b[31m" -#define ANSI_COLOR_GREEN "\x1b[32m" -#define ANSI_COLOR_YELLOW "\x1b[33m" -#define ANSI_COLOR_BLUE "\x1b[34m" -#define ANSI_COLOR_MAGENTA "\x1b[35m" -#define ANSI_COLOR_CYAN "\x1b[36m" -#define ANSI_COLOR_RESET "\x1b[0m" -#define ANSI_BOLD "\x1b[1m" - -enum console_color_t { - CONSOLE_COLOR_DEFAULT=0, - CONSOLE_COLOR_PROMPT, - CONSOLE_COLOR_USER_INPUT, - CONSOLE_COLOR_ERROR -}; - -struct console_state { - bool multiline_input = false; - bool use_color = false; - console_color_t color = CONSOLE_COLOR_DEFAULT; - - FILE* out = stdout; -#if defined (_WIN32) - void* hConsole; -#else - FILE* tty = nullptr; - termios prev_state; -#endif -}; - -void console_init(console_state & con_st); -void console_cleanup(console_state & con_st); -void console_set_color(console_state & con_st, console_color_t color); -bool console_readline(console_state & con_st, std::string & line); diff --git a/examples/console.cpp b/examples/console.cpp new file mode 100644 index 000000000..8966b107f --- /dev/null +++ b/examples/console.cpp @@ -0,0 +1,496 @@ +#include "console.h" +#include +#include + +#if defined(_WIN32) +#define WIN32_LEAN_AND_MEAN +#ifndef NOMINMAX +#define NOMINMAX +#endif +#include +#include +#include +#else +#include +#include +#include +#include +#include +#include +#include +#include +#endif + +#define ANSI_COLOR_RED "\x1b[31m" +#define ANSI_COLOR_GREEN "\x1b[32m" +#define ANSI_COLOR_YELLOW "\x1b[33m" +#define ANSI_COLOR_BLUE "\x1b[34m" +#define ANSI_COLOR_MAGENTA "\x1b[35m" +#define ANSI_COLOR_CYAN "\x1b[36m" +#define ANSI_COLOR_RESET "\x1b[0m" +#define ANSI_BOLD "\x1b[1m" + +namespace console { + + // + // Console state + // + + static bool advanced_display = false; + static bool simple_io = true; + static display_t current_display = reset; + + static FILE* out = stdout; + +#if defined (_WIN32) + static void* hConsole; +#else + static FILE* tty = nullptr; + static termios initial_state; +#endif + + // + // Init and cleanup + // + + void init(bool use_simple_io, bool use_advanced_display) { + advanced_display = use_advanced_display; + simple_io = use_simple_io; +#if defined(_WIN32) + // Windows-specific console initialization + DWORD dwMode = 0; + hConsole = GetStdHandle(STD_OUTPUT_HANDLE); + if (hConsole == INVALID_HANDLE_VALUE || !GetConsoleMode(hConsole, &dwMode)) { + hConsole = GetStdHandle(STD_ERROR_HANDLE); + if (hConsole != INVALID_HANDLE_VALUE && (!GetConsoleMode(hConsole, &dwMode))) { + hConsole = nullptr; + simple_io = true; + } + } + if (hConsole) { + // Enable ANSI colors on Windows 10+ + if (advanced_display && !(dwMode & ENABLE_VIRTUAL_TERMINAL_PROCESSING)) { + SetConsoleMode(hConsole, dwMode | ENABLE_VIRTUAL_TERMINAL_PROCESSING); + } + // Set console output codepage to UTF8 + SetConsoleOutputCP(CP_UTF8); + } + HANDLE hConIn = GetStdHandle(STD_INPUT_HANDLE); + if (hConIn != INVALID_HANDLE_VALUE && GetConsoleMode(hConIn, &dwMode)) { + // Set console input codepage to UTF16 + _setmode(_fileno(stdin), _O_WTEXT); + + // Set ICANON (ENABLE_LINE_INPUT) and ECHO (ENABLE_ECHO_INPUT) + if (simple_io) { + dwMode |= ENABLE_LINE_INPUT | ENABLE_ECHO_INPUT; + } else { + dwMode &= ~(ENABLE_LINE_INPUT | ENABLE_ECHO_INPUT); + } + if (!SetConsoleMode(hConIn, dwMode)) { + simple_io = true; + } + } +#else + // POSIX-specific console initialization + if (!simple_io) { + struct termios new_termios; + tcgetattr(STDIN_FILENO, &initial_state); + new_termios = initial_state; + new_termios.c_lflag &= ~(ICANON | ECHO); + new_termios.c_cc[VMIN] = 1; + new_termios.c_cc[VTIME] = 0; + tcsetattr(STDIN_FILENO, TCSANOW, &new_termios); + + tty = fopen("/dev/tty", "w+"); + if (tty != nullptr) { + out = tty; + } + } + + setlocale(LC_ALL, ""); +#endif + } + + void cleanup() { + // Reset console display + set_display(reset); + +#if !defined(_WIN32) + // Restore settings on POSIX systems + if (!simple_io) { + if (tty != nullptr) { + out = stdout; + fclose(tty); + tty = nullptr; + } + tcsetattr(STDIN_FILENO, TCSANOW, &initial_state); + } +#endif + } + + // + // Display and IO + // + + // Keep track of current display and only emit ANSI code if it changes + void set_display(display_t display) { + if (advanced_display && current_display != display) { + fflush(stdout); + switch(display) { + case reset: + fprintf(out, ANSI_COLOR_RESET); + break; + case prompt: + fprintf(out, ANSI_COLOR_YELLOW); + break; + case user_input: + fprintf(out, ANSI_BOLD ANSI_COLOR_GREEN); + break; + case error: + fprintf(out, ANSI_BOLD ANSI_COLOR_RED); + } + current_display = display; + fflush(out); + } + } + + char32_t getchar32() { +#if defined(_WIN32) + HANDLE hConsole = GetStdHandle(STD_INPUT_HANDLE); + wchar_t high_surrogate = 0; + + while (true) { + INPUT_RECORD record; + DWORD count; + if (!ReadConsoleInputW(hConsole, &record, 1, &count) || count == 0) { + return WEOF; + } + + if (record.EventType == KEY_EVENT && record.Event.KeyEvent.bKeyDown) { + wchar_t wc = record.Event.KeyEvent.uChar.UnicodeChar; + if (wc == 0) { + continue; + } + + if ((wc >= 0xD800) && (wc <= 0xDBFF)) { // Check if wc is a high surrogate + high_surrogate = wc; + continue; + } + if ((wc >= 0xDC00) && (wc <= 0xDFFF)) { // Check if wc is a low surrogate + if (high_surrogate != 0) { // Check if we have a high surrogate + return ((high_surrogate - 0xD800) << 10) + (wc - 0xDC00) + 0x10000; + } + } + + high_surrogate = 0; // Reset the high surrogate + return static_cast(wc); + } + } +#else + wchar_t wc = getwchar(); + if (static_cast(wc) == WEOF) { + return WEOF; + } + +#if WCHAR_MAX == 0xFFFF + if ((wc >= 0xD800) && (wc <= 0xDBFF)) { // Check if wc is a high surrogate + wchar_t low_surrogate = getwchar(); + if ((low_surrogate >= 0xDC00) && (low_surrogate <= 0xDFFF)) { // Check if the next wchar is a low surrogate + return (static_cast(wc & 0x03FF) << 10) + (low_surrogate & 0x03FF) + 0x10000; + } + } + if ((wc >= 0xD800) && (wc <= 0xDFFF)) { // Invalid surrogate pair + return 0xFFFD; // Return the replacement character U+FFFD + } +#endif + + return static_cast(wc); +#endif + } + + void pop_cursor() { +#if defined(_WIN32) + if (hConsole != NULL) { + CONSOLE_SCREEN_BUFFER_INFO bufferInfo; + GetConsoleScreenBufferInfo(hConsole, &bufferInfo); + + COORD newCursorPosition = bufferInfo.dwCursorPosition; + if (newCursorPosition.X == 0) { + newCursorPosition.X = bufferInfo.dwSize.X - 1; + newCursorPosition.Y -= 1; + } else { + newCursorPosition.X -= 1; + } + + SetConsoleCursorPosition(hConsole, newCursorPosition); + return; + } +#endif + putc('\b', out); + } + + int estimateWidth(char32_t codepoint) { +#if defined(_WIN32) + return 1; +#else + return wcwidth(codepoint); +#endif + } + + int put_codepoint(const char* utf8_codepoint, size_t length, int expectedWidth) { +#if defined(_WIN32) + CONSOLE_SCREEN_BUFFER_INFO bufferInfo; + if (!GetConsoleScreenBufferInfo(hConsole, &bufferInfo)) { + // go with the default + return expectedWidth; + } + COORD initialPosition = bufferInfo.dwCursorPosition; + DWORD nNumberOfChars = length; + WriteConsole(hConsole, utf8_codepoint, nNumberOfChars, &nNumberOfChars, NULL); + + CONSOLE_SCREEN_BUFFER_INFO newBufferInfo; + GetConsoleScreenBufferInfo(hConsole, &newBufferInfo); + + // Figure out our real position if we're in the last column + if (utf8_codepoint[0] != 0x09 && initialPosition.X == newBufferInfo.dwSize.X - 1) { + DWORD nNumberOfChars; + WriteConsole(hConsole, &" \b", 2, &nNumberOfChars, NULL); + GetConsoleScreenBufferInfo(hConsole, &newBufferInfo); + } + + int width = newBufferInfo.dwCursorPosition.X - initialPosition.X; + if (width < 0) { + width += newBufferInfo.dwSize.X; + } + return width; +#else + // We can trust expectedWidth if we've got one + if (expectedWidth >= 0 || tty == nullptr) { + fwrite(utf8_codepoint, length, 1, out); + return expectedWidth; + } + + fputs("\033[6n", tty); // Query cursor position + int x1; + int y1; + int x2; + int y2; + int results = 0; + results = fscanf(tty, "\033[%d;%dR", &y1, &x1); + + fwrite(utf8_codepoint, length, 1, tty); + + fputs("\033[6n", tty); // Query cursor position + results += fscanf(tty, "\033[%d;%dR", &y2, &x2); + + if (results != 4) { + return expectedWidth; + } + + int width = x2 - x1; + if (width < 0) { + // Calculate the width considering text wrapping + struct winsize w; + ioctl(STDOUT_FILENO, TIOCGWINSZ, &w); + width += w.ws_col; + } + return width; +#endif + } + + void replace_last(char ch) { +#if defined(_WIN32) + pop_cursor(); + put_codepoint(&ch, 1, 1); +#else + fprintf(out, "\b%c", ch); +#endif + } + + void append_utf8(char32_t ch, std::string & out) { + if (ch <= 0x7F) { + out.push_back(static_cast(ch)); + } else if (ch <= 0x7FF) { + out.push_back(static_cast(0xC0 | ((ch >> 6) & 0x1F))); + out.push_back(static_cast(0x80 | (ch & 0x3F))); + } else if (ch <= 0xFFFF) { + out.push_back(static_cast(0xE0 | ((ch >> 12) & 0x0F))); + out.push_back(static_cast(0x80 | ((ch >> 6) & 0x3F))); + out.push_back(static_cast(0x80 | (ch & 0x3F))); + } else if (ch <= 0x10FFFF) { + out.push_back(static_cast(0xF0 | ((ch >> 18) & 0x07))); + out.push_back(static_cast(0x80 | ((ch >> 12) & 0x3F))); + out.push_back(static_cast(0x80 | ((ch >> 6) & 0x3F))); + out.push_back(static_cast(0x80 | (ch & 0x3F))); + } else { + // Invalid Unicode code point + } + } + + // Helper function to remove the last UTF-8 character from a string + void pop_back_utf8_char(std::string & line) { + if (line.empty()) { + return; + } + + size_t pos = line.length() - 1; + + // Find the start of the last UTF-8 character (checking up to 4 bytes back) + for (size_t i = 0; i < 3 && pos > 0; ++i, --pos) { + if ((line[pos] & 0xC0) != 0x80) { + break; // Found the start of the character + } + } + line.erase(pos); + } + + bool readline_advanced(std::string & line, bool multiline_input) { + if (out != stdout) { + fflush(stdout); + } + + line.clear(); + std::vector widths; + bool is_special_char = false; + bool end_of_stream = false; + + char32_t input_char; + while (true) { + fflush(out); // Ensure all output is displayed before waiting for input + input_char = getchar32(); + + if (input_char == '\r' || input_char == '\n') { + break; + } + + if (input_char == (char32_t) WEOF || input_char == 0x04 /* Ctrl+D*/) { + end_of_stream = true; + break; + } + + if (is_special_char) { + set_display(user_input); + replace_last(line.back()); + is_special_char = false; + } + + if (input_char == '\033') { // Escape sequence + char32_t code = getchar32(); + if (code == '[' || code == 0x1B) { + // Discard the rest of the escape sequence + while ((code = getchar32()) != (char32_t) WEOF) { + if ((code >= 'A' && code <= 'Z') || (code >= 'a' && code <= 'z') || code == '~') { + break; + } + } + } + } else if (input_char == 0x08 || input_char == 0x7F) { // Backspace + if (!widths.empty()) { + int count; + do { + count = widths.back(); + widths.pop_back(); + // Move cursor back, print space, and move cursor back again + for (int i = 0; i < count; i++) { + replace_last(' '); + pop_cursor(); + } + pop_back_utf8_char(line); + } while (count == 0 && !widths.empty()); + } + } else { + int offset = line.length(); + append_utf8(input_char, line); + int width = put_codepoint(line.c_str() + offset, line.length() - offset, estimateWidth(input_char)); + if (width < 0) { + width = 0; + } + widths.push_back(width); + } + + if (!line.empty() && (line.back() == '\\' || line.back() == '/')) { + set_display(prompt); + replace_last(line.back()); + is_special_char = true; + } + } + + bool has_more = multiline_input; + if (is_special_char) { + replace_last(' '); + pop_cursor(); + + char last = line.back(); + line.pop_back(); + if (last == '\\') { + line += '\n'; + fputc('\n', out); + has_more = !has_more; + } else { + // llama will just eat the single space, it won't act as a space + if (line.length() == 1 && line.back() == ' ') { + line.clear(); + pop_cursor(); + } + has_more = false; + } + } else { + if (end_of_stream) { + has_more = false; + } else { + line += '\n'; + fputc('\n', out); + } + } + + fflush(out); + return has_more; + } + + bool readline_simple(std::string & line, bool multiline_input) { +#if defined(_WIN32) + std::wstring wline; + if (!std::getline(std::wcin, wline)) { + // Input stream is bad or EOF received + line.clear(); + GenerateConsoleCtrlEvent(CTRL_C_EVENT, 0); + return false; + } + + int size_needed = WideCharToMultiByte(CP_UTF8, 0, &wline[0], (int)wline.size(), NULL, 0, NULL, NULL); + line.resize(size_needed); + WideCharToMultiByte(CP_UTF8, 0, &wline[0], (int)wline.size(), &line[0], size_needed, NULL, NULL); +#else + if (!std::getline(std::cin, line)) { + // Input stream is bad or EOF received + line.clear(); + return false; + } +#endif + if (!line.empty()) { + char last = line.back(); + if (last == '/') { // Always return control on '/' symbol + line.pop_back(); + return false; + } + if (last == '\\') { // '\\' changes the default action + line.pop_back(); + multiline_input = !multiline_input; + } + } + line += '\n'; + + // By default, continue input if multiline_input is set + return multiline_input; + } + + bool readline(std::string & line, bool multiline_input) { + set_display(user_input); + + if (simple_io) { + return readline_simple(line, multiline_input); + } + return readline_advanced(line, multiline_input); + } + +} diff --git a/examples/console.h b/examples/console.h new file mode 100644 index 000000000..ec175269b --- /dev/null +++ b/examples/console.h @@ -0,0 +1,19 @@ +// Console functions + +#pragma once + +#include + +namespace console { + enum display_t { + reset = 0, + prompt, + user_input, + error + }; + + void init(bool use_simple_io, bool use_advanced_display); + void cleanup(); + void set_display(display_t display); + bool readline(std::string & line, bool multiline_input); +} diff --git a/examples/embd-input/embd-input-lib.cpp b/examples/embd-input/embd-input-lib.cpp index 26563821a..2185b9b0e 100644 --- a/examples/embd-input/embd-input-lib.cpp +++ b/examples/embd-input/embd-input-lib.cpp @@ -30,7 +30,7 @@ struct MyModel* create_mymodel(int argc, char ** argv) { fprintf(stderr, "%s: build = %d (%s)\n", __func__, BUILD_NUMBER, BUILD_COMMIT); if (params.seed == LLAMA_DEFAULT_SEED) { - params.seed = time(NULL); + params.seed = uint32_t(time(NULL)); } fprintf(stderr, "%s: seed = %d\n", __func__, params.seed); diff --git a/examples/grammar-parser.cpp b/examples/grammar-parser.cpp index 019d5e1bf..e76bd11c3 100644 --- a/examples/grammar-parser.cpp +++ b/examples/grammar-parser.cpp @@ -405,7 +405,7 @@ namespace grammar_parser { for (size_t i = 0, end = state.rules.size(); i < end; i++) { // fprintf(file, "%zu: ", i); // print_rule_binary(file, state.rules[i]); - print_rule(file, i, state.rules[i], symbol_id_names); + print_rule(file, uint32_t(i), state.rules[i], symbol_id_names); // fprintf(file, "\n"); } } catch (const std::exception & err) { diff --git a/examples/json-schema-to-grammar.py b/examples/json-schema-to-grammar.py new file mode 100644 index 000000000..2dccc118a --- /dev/null +++ b/examples/json-schema-to-grammar.py @@ -0,0 +1,132 @@ +import argparse +import json +import re +import sys + +# whitespace is constrained to a single space char to prevent model "running away" in +# whitespace. Also maybe improves generation quality? +SPACE_RULE = '" "?' + +PRIMITIVE_RULES = { + 'boolean': '("true" | "false") space', + 'number': '("-"? ([0-9] | [1-9] [0-9]*)) ("." [0-9]+)? ([eE] [-+]? [0-9]+)? space', + 'integer': '("-"? ([0-9] | [1-9] [0-9]*)) space', + 'string': r''' "\"" ( + [^"\\] | + "\\" (["\\/bfnrt] | "u" [0-9a-fA-F] [0-9a-fA-F] [0-9a-fA-F] [0-9a-fA-F]) + )* "\"" space ''', + 'null': '"null" space', +} + +INVALID_RULE_CHARS_RE = re.compile(r'[^a-zA-Z0-9-]+') +GRAMMAR_LITERAL_ESCAPE_RE = re.compile(r'[\r\n"]') +GRAMMAR_LITERAL_ESCAPES = {'\r': '\\r', '\n': '\\n', '"': '\\"'} + + +class SchemaConverter: + def __init__(self, prop_order): + self._prop_order = prop_order + self._rules = {'space': SPACE_RULE} + + def _format_literal(self, literal): + escaped = GRAMMAR_LITERAL_ESCAPE_RE.sub( + lambda m: GRAMMAR_LITERAL_ESCAPES.get(m.group(0)), json.dumps(literal) + ) + return f'"{escaped}"' + + def _add_rule(self, name, rule): + esc_name = INVALID_RULE_CHARS_RE.sub('-', name) + if esc_name not in self._rules or self._rules[esc_name] == rule: + key = esc_name + else: + i = 0 + while f'{esc_name}{i}' in self._rules: + i += 1 + key = f'{esc_name}{i}' + self._rules[key] = rule + return key + + def visit(self, schema, name): + schema_type = schema.get('type') + rule_name = name or 'root' + + if 'oneOf' in schema or 'anyOf' in schema: + rule = ' | '.join(( + self.visit(alt_schema, f'{name}{"-" if name else ""}{i}') + for i, alt_schema in enumerate(schema.get('oneOf') or schema['anyOf']) + )) + return self._add_rule(rule_name, rule) + + elif 'const' in schema: + return self._add_rule(rule_name, self._format_literal(schema['const'])) + + elif 'enum' in schema: + rule = ' | '.join((self._format_literal(v) for v in schema['enum'])) + return self._add_rule(rule_name, rule) + + elif schema_type == 'object' and 'properties' in schema: + # TODO: `required` keyword + prop_order = self._prop_order + prop_pairs = sorted( + schema['properties'].items(), + # sort by position in prop_order (if specified) then by key + key=lambda kv: (prop_order.get(kv[0], len(prop_order)), kv[0]), + ) + + rule = '"{" space' + for i, (prop_name, prop_schema) in enumerate(prop_pairs): + prop_rule_name = self.visit(prop_schema, f'{name}{"-" if name else ""}{prop_name}') + if i > 0: + rule += ' "," space' + rule += fr' {self._format_literal(prop_name)} space ":" space {prop_rule_name}' + rule += ' "}" space' + + return self._add_rule(rule_name, rule) + + elif schema_type == 'array' and 'items' in schema: + # TODO `prefixItems` keyword + item_rule_name = self.visit(schema['items'], f'{name}{"-" if name else ""}item') + rule = f'"[" space ({item_rule_name} ("," space {item_rule_name})*)? "]" space' + return self._add_rule(rule_name, rule) + + else: + assert schema_type in PRIMITIVE_RULES, f'Unrecognized schema: {schema}' + return self._add_rule( + 'root' if rule_name == 'root' else schema_type, + PRIMITIVE_RULES[schema_type] + ) + + def format_grammar(self): + return '\n'.join((f'{name} ::= {rule}' for name, rule in self._rules.items())) + + +def main(args_in = None): + parser = argparse.ArgumentParser( + description=''' + Generates a grammar (suitable for use in ./main) that produces JSON conforming to a + given JSON schema. Only a subset of JSON schema features are supported; more may be + added in the future. + ''', + ) + parser.add_argument( + '--prop-order', + default=[], + type=lambda s: s.split(','), + help=''' + comma-separated property names defining the order of precedence for object properties; + properties not specified here are given lower precedence than those that are, and are + sorted alphabetically + ''' + ) + parser.add_argument('schema', help='file containing JSON schema ("-" for stdin)') + args = parser.parse_args(args_in) + + schema = json.load(sys.stdin if args.schema == '-' else open(args.schema)) + prop_order = {name: idx for idx, name in enumerate(args.prop_order)} + converter = SchemaConverter(prop_order) + converter.visit(schema, '') + print(converter.format_grammar()) + + +if __name__ == '__main__': + main() diff --git a/examples/llama.vim b/examples/llama.vim new file mode 100644 index 000000000..f03fadfb7 --- /dev/null +++ b/examples/llama.vim @@ -0,0 +1,132 @@ +" Requires an already running llama.cpp server +" To install either copy or symlink to ~/.vim/autoload/llama.vim +" Then start with either :call llama#doLlamaGen(), +" or add a keybind to your vimrc such as +" nnoremap Z :call llama#doLlamaGen() +" Similarly, you could add an insert mode keybind with +" inoremap call llama#doLlamaGen() +" +" g:llama_api_url and g:llama_overrides can be configured in your .vimrc +" let g:llama_api_url = "192.168.1.10:8080" +" llama_overrides can also be set through buffer/window scopes. For instance +" autocmd filetype python let b:llama_overrides = {"temp": 0.2} +" Could be added to your .vimrc to automatically set a lower temperature when +" editing a python script +" Additionally, an override dict can be stored at the top of a file +" !*{"stop": ["User:"]} +" Could be added to the start of your chatlog.txt to set the stopping token +" These parameter dicts are merged together from lowest to highest priority: +" server default -> g:llama_overrides -> w:llama_overrides -> +" b:llama_overrides -> in file (!*) overrides +" +" Sublists (like logit_bias and stop) are overridden, not merged +" Example override: +" !*{"logit_bias": [[13, -5], [2, false]], "temperature": 1, "top_k": 5, "top_p": 0.5, "n_predict": 256, "repeat_last_n": 256, "repeat_penalty": 1.17647} +if !exists("g:llama_api_url") + let g:llama_api_url= "127.0.0.1:8080" +endif +if !exists("g:llama_overrides") + let g:llama_overrides = {} +endif +const s:querydata = {"n_predict": 256, "stop": [ "\n" ], "stream": v:true } +const s:curlcommand = ['curl','--data-raw', "{\"prompt\":\"### System:\"}", '--silent', '--no-buffer', '--request', 'POST', '--url', g:llama_api_url .. '/completion', '--header', "Content-Type: application/json"] +let s:linedict = {} + +func s:callbackHandler(bufn, channel, msg) + if len(a:msg) < 3 + return + elseif a:msg[0] == "d" + let l:msg = a:msg[6:-1] + else + let l:msg = a:msg + endif + let l:decoded_msg = json_decode(l:msg) + let l:newtext = split(l:decoded_msg['content'], "\n", 1) + if len(l:newtext) > 0 + call setbufline(a:bufn, s:linedict[a:bufn], getbufline(a:bufn, s:linedict[a:bufn])[0] .. newtext[0]) + else + echo "nothing genned" + endif + if len(newtext) > 1 + let l:failed = appendbufline(a:bufn, s:linedict[a:bufn], newtext[1:-1]) + let s:linedict[a:bufn] = s:linedict[a:bufn] + len(newtext)-1 + endif + if has_key(l:decoded_msg, "stop") && l:decoded_msg.stop + echo "Finished generation" + endif +endfunction + +func llama#doLlamaGen() + if exists("b:job") + if job_status(b:job) == "run" + call job_stop(b:job) + return + endif + endif + + let l:cbuffer = bufnr("%") + let s:linedict[l:cbuffer] = line('$') + let l:buflines = getbufline(l:cbuffer, 1, 1000) + let l:querydata = copy(s:querydata) + call extend(l:querydata, g:llama_overrides) + if exists("w:llama_overrides") + call extend(l:querydata, w:llama_overrides) + endif + if exists("b:llama_overrides") + call extend(l:querydata, b:llama_overrides) + endif + if l:buflines[0][0:1] == '!*' + let l:userdata = json_decode(l:buflines[0][2:-1]) + call extend(l:querydata, l:userdata) + let l:buflines = l:buflines[1:-1] + endif + let l:querydata.prompt = join(l:buflines, "\n") + let l:curlcommand = copy(s:curlcommand) + let l:curlcommand[2] = json_encode(l:querydata) + let b:job = job_start(l:curlcommand, {"callback": function("s:callbackHandler", [l:cbuffer])}) +endfunction + +" Echos the tokkenization of the provided string , or cursor to end of word +" Onus is placed on the user to include the preceding space +func llama#tokenizeWord(...) + if (a:0 > 0) + let l:input = a:1 + else + exe "normal \"*ye" + let l:input = @* + endif + let l:querydata = {"content": l:input} + let l:curlcommand = copy(s:curlcommand) + let l:curlcommand[2] = json_encode(l:querydata) + let l:curlcommand[8] = g:llama_api_url .. "/tokenize" + let s:token_job = job_start(l:curlcommand, {"callback": function("s:tokenizeWordCallback", [l:input])}) +endfunction + +func s:tokenizeWordCallback(plaintext, channel, msg) + echo '"' .. a:plaintext ..'" - ' .. string(json_decode(a:msg).tokens) +endfunction + + +" Echos the token count of the entire buffer (or provided string) +" Example usage :echo llama#tokenCount() +func llama#tokenCount(...) + if (a:0 > 0) + let l:buflines = a:1 + else + let l:buflines = getline(1,1000) + if l:buflines[0][0:1] == '!*' + let l:buflines = l:buflines[1:-1] + endif + let l:buflines = join(l:buflines, "\n") + endif + let l:querydata = {"content": l:buflines} + let l:curlcommand = copy(s:curlcommand) + let l:curlcommand[2] = json_encode(l:querydata) + let l:curlcommand[8] = g:llama_api_url .. "/tokenize" + let s:token_job = job_start(l:curlcommand, {"callback": "s:tokenCountCallback"}) +endfunction + +func s:tokenCountCallback(channel, msg) + let resp = json_decode(a:msg) + echo len(resp.tokens) +endfunction diff --git a/examples/llm.vim b/examples/llm.vim index efecad0cd..594a28549 100644 --- a/examples/llm.vim +++ b/examples/llm.vim @@ -1,3 +1,5 @@ +" Basic plugin example + function! Llm() let url = "http://127.0.0.1:8080/completion" @@ -16,8 +18,10 @@ function! Llm() " Extract the content field from the response let content = json_decode(response).content + let split_newlines = split(content, '\n', 1) + " Insert the content at the cursor position - call setline(line('.'), getline('.') . content) + call setline(line('.'), [ getline('.') . split_newlines[0] ] + split_newlines[1:]) endfunction command! Llm call Llm() diff --git a/examples/main/README.md b/examples/main/README.md index 375386130..55c16096f 100644 --- a/examples/main/README.md +++ b/examples/main/README.md @@ -140,6 +140,12 @@ The `--ctx-size` option allows you to set the size of the prompt context used by - `-c N, --ctx-size N`: Set the size of the prompt context (default: 512). The LLaMA models were built with a context of 2048, which will yield the best results on longer input/inference. However, increasing the context size beyond 2048 may lead to unpredictable results. +### Extended Context Size + +Some fine-tuned models have extened the context length by scaling RoPE. For example, if the original pretrained model have a context length (max sequence length) of 4096 (4k) and the fine-tuned model have 32k. That is a scaling factor of 8, and should work by setting the above `--ctx-size` to 32768 (32k) and `--rope-scale` to 8. + +- `--rope-scale N`: Where N is the linear scaling factor used by the fine-tuned model. + ### Keep Prompt The `--keep` option allows users to retain the original prompt when the model runs out of context, ensuring a connection to the initial instruction or conversation topic is maintained. @@ -202,9 +208,9 @@ Example usage: `--top-p 0.95` - `--tfs N`: Enable tail free sampling with parameter z (default: 1.0, 1.0 = disabled). -Tail free sampling (TFS) is a text generation technique that aims to reduce the impact of less likely tokens, which may be less relevant, less coherent, or nonsensical, on the output. The method adjusts the logits (token probabilities) by raising them to the power of the parameter z. A higher value of z (e.g., 2.0) will further suppress less likely tokens from the tail of the distribution, while a value of 1.0 disables the effect of TFS. By setting the parameter z, you can control how much the probabilities of less likely tokens are reduced. +Tail free sampling (TFS) is a text generation technique that aims to reduce the impact of less likely tokens, which may be less relevant, less coherent, or nonsensical, on the output. Similar to Top-P it tries to determine the bulk of the most likely tokens dynamically. But TFS filters out logits based on the second derivative of their probabilities. Adding tokens is stopped after the sum of the second derivatives reaches the parameter z. In short: TFS looks how quickly the probabilities of the tokens decrease and cuts off the tail of unlikely tokens using the parameter z. Typical values for z are in the range of 0.9 to 0.95. A value of 1.0 would include all tokens, and thus disables the effect of TFS. -Example usage: `--tfs 2.0` +Example usage: `--tfs 0.95` ### Locally Typical Sampling diff --git a/examples/main/main.cpp b/examples/main/main.cpp index 16ddc2274..56ada7e69 100644 --- a/examples/main/main.cpp +++ b/examples/main/main.cpp @@ -4,6 +4,7 @@ #endif #include "common.h" +#include "console.h" #include "llama.h" #include "build-info.h" #include "grammar-parser.h" @@ -35,9 +36,7 @@ #pragma warning(disable: 4244 4267) // possible loss of data #endif -static console_state con_st; static llama_context ** g_ctx; - static bool is_interacting = false; #if defined (__unix__) || (defined (__APPLE__) && defined (__MACH__)) || defined (_WIN32) @@ -46,7 +45,7 @@ void sigint_handler(int signo) { if (!is_interacting) { is_interacting=true; } else { - console_cleanup(con_st); + console::cleanup(); printf("\n"); llama_print_timings(*g_ctx); _exit(130); @@ -64,10 +63,8 @@ int main(int argc, char ** argv) { // save choice to use color for later // (note for later: this is a slightly awkward choice) - con_st.use_color = params.use_color; - con_st.multiline_input = params.multiline_input; - console_init(con_st); - atexit([]() { console_cleanup(con_st); }); + console::init(params.simple_io, params.use_color); + atexit([]() { console::cleanup(); }); if (params.perplexity) { printf("\n************\n"); @@ -325,6 +322,10 @@ int main(int argc, char ** argv) { } } + if (params.input_prefix_bos) { + fprintf(stderr, "Input prefix with BOS\n"); + } + if (!params.input_prefix.empty()) { fprintf(stderr, "Input prefix: '%s'\n", params.input_prefix.c_str()); } @@ -369,7 +370,7 @@ int main(int argc, char ** argv) { if (params.interactive) { const char *control_message; - if (con_st.multiline_input) { + if (params.multiline_input) { control_message = " - To return control to LLaMa, end your input with '\\'.\n" " - To return control without starting a new line, end your input with '/'.\n"; } else { @@ -397,7 +398,7 @@ int main(int argc, char ** argv) { int n_past_guidance = 0; // the first thing we will do is to output the prompt, so set color accordingly - console_set_color(con_st, CONSOLE_COLOR_PROMPT); + console::set_display(console::prompt); std::vector embd; std::vector embd_guidance; @@ -418,9 +419,9 @@ int main(int argc, char ** argv) { // Ensure the input doesn't exceed the context size by truncating embd if necessary. if ((int)embd.size() > max_embd_size) { auto skipped_tokens = embd.size() - max_embd_size; - console_set_color(con_st, CONSOLE_COLOR_ERROR); + console::set_display(console::error); printf("<>", skipped_tokens, skipped_tokens != 1 ? "s" : ""); - console_set_color(con_st, CONSOLE_COLOR_DEFAULT); + console::set_display(console::reset); fflush(stdout); embd.resize(max_embd_size); } @@ -633,16 +634,6 @@ int main(int argc, char ** argv) { last_n_tokens.push_back(id); } - // replace end of text token with newline token when in interactive mode - if (id == llama_token_eos() && params.interactive && !params.instruct) { - id = llama_token_newline.front(); - if (params.antiprompt.size() != 0) { - // tokenize and inject first reverse prompt - const auto first_antiprompt = ::llama_tokenize(ctx, params.antiprompt.front(), false); - embd_inp.insert(embd_inp.end(), first_antiprompt.begin(), first_antiprompt.end()); - } - } - // add it to the context embd.push_back(id); @@ -673,7 +664,7 @@ int main(int argc, char ** argv) { } // reset color to default if we there is no pending user input if (input_echo && (int)embd_inp.size() == n_consumed) { - console_set_color(con_st, CONSOLE_COLOR_DEFAULT); + console::set_display(console::reset); } // if not currently processing queued inputs; @@ -699,7 +690,7 @@ int main(int argc, char ** argv) { if (last_output.find(antiprompt.c_str(), search_start_pos) != std::string::npos) { if (params.interactive) { is_interacting = true; - console_set_color(con_st, CONSOLE_COLOR_USER_INPUT); + console::set_display(console::user_input); } is_antiprompt = true; fflush(stdout); @@ -708,11 +699,34 @@ int main(int argc, char ** argv) { } } + // deal with end of text token in interactive mode + if (last_n_tokens.back() == llama_token_eos()) { + if (params.interactive) { + if (params.antiprompt.size() != 0) { + // tokenize and inject first reverse prompt + const auto first_antiprompt = ::llama_tokenize(ctx, params.antiprompt.front(), false); + embd_inp.insert(embd_inp.end(), first_antiprompt.begin(), first_antiprompt.end()); + is_antiprompt = true; + } + + is_interacting = true; + printf("\n"); + console::set_display(console::user_input); + fflush(stdout); + } else if (params.instruct) { + is_interacting = true; + } + } + if (n_past > 0 && is_interacting) { if (params.instruct) { printf("\n> "); } + if (params.input_prefix_bos) { + embd_inp.push_back(llama_token_bos()); + } + std::string buffer; if (!params.input_prefix.empty()) { buffer += params.input_prefix; @@ -722,12 +736,12 @@ int main(int argc, char ** argv) { std::string line; bool another_line = true; do { - another_line = console_readline(con_st, line); + another_line = console::readline(line, params.multiline_input); buffer += line; } while (another_line); // done taking input, reset color - console_set_color(con_st, CONSOLE_COLOR_DEFAULT); + console::set_display(console::reset); // Add tokens to embd only if the input buffer is non-empty // Entering a empty line lets the user pass control back @@ -776,13 +790,9 @@ int main(int argc, char ** argv) { } // end of text token - if (!embd.empty() && embd.back() == llama_token_eos()) { - if (params.instruct) { - is_interacting = true; - } else { - fprintf(stderr, " [end of text]\n"); - break; - } + if (!embd.empty() && embd.back() == llama_token_eos() && !(params.instruct || params.interactive)) { + fprintf(stderr, " [end of text]\n"); + break; } // In interactive mode, respect the maximum number of tokens and drop back to user input when reached. diff --git a/examples/perplexity/perplexity.cpp b/examples/perplexity/perplexity.cpp index d23b7e7f0..62433e983 100644 --- a/examples/perplexity/perplexity.cpp +++ b/examples/perplexity/perplexity.cpp @@ -121,8 +121,23 @@ void perplexity(llama_context * ctx, const gpt_params & params) { printf("\n"); } -void perplexity_lines(llama_context * ctx, const gpt_params & params) { - // Calculates perplexity over each line of the prompt +void hellaswag_score(llama_context * ctx, const gpt_params & params) { + // Calculates hellaswag score (acc_norm) from prompt + // + // Data extracted from the HellaSwag validation dataset (MIT license) https://github.com/rowanz/hellaswag/blob/master/data/hellaswag_val.jsonl + // All used data fields are preprocessed as in https://github.com/EleutherAI/lm-evaluation-harness/blob/df3da98c5405deafd519c2ddca52bb7c3fe36bef/lm_eval/tasks/hellaswag.py#L62-L68 + // + // All 10042 tasks should be extracted to keep the results standardized like other implementations. + // + // Datafile layout: + // ['??'] denotes json fields + // 6 lines per task: + // ['activity_label'] + ": " +['ctx'] - The first part of the query, the context + // ['label'] - The index the best common sense ending aka gold ending + // ['endings'][0] - Endings added to the first part of the query + // ['endings'][1] + // ['endings'][2] + // ['endings'][3] std::vector prompt_lines; std::istringstream strstream(params.prompt); @@ -132,63 +147,149 @@ void perplexity_lines(llama_context * ctx, const gpt_params & params) { prompt_lines.push_back(line); } + if( prompt_lines.size() % 6 != 0) { + fprintf(stderr, "%s : number of lines in prompt not a multiple of 6.\n", __func__); + return; + } + + size_t hs_task_count = prompt_lines.size()/6; + fprintf(stderr, "%s : loaded %zu tasks from prompt.\n", __func__, hs_task_count); + + // This is needed as usual for LLaMA models + bool prepend_bos = true; + + // Number of tasks to use when computing the score + if ( params.hellaswag_tasks < hs_task_count ) { + hs_task_count = params.hellaswag_tasks; + } + + // The tasks should be randomized so the score stabilizes quickly. + bool randomize_tasks = true; + + // The random seed should not impact the final result if the computation is done over enough tasks, so kept hardcoded for now + std::mt19937 rng(1); + + // Dataholder for hellaswag tasks + struct hs_data_t { + std::string context; + size_t gold_ending_idx; + std::string ending[4]; + size_t ending_logprob_count[4]; + double ending_logprob[4]; + }; + + fprintf(stderr, "%s : selecting %zu %s tasks.\n", __func__, hs_task_count, (randomize_tasks?"randomized":"the first") ); + + // Select and read data from prompt lines + hs_data_t *hs_data = new hs_data_t[hs_task_count]; + for (size_t i=0; i < hs_task_count; i++) { + size_t idx = i; + + // Select a random example of those left in the prompt + if (randomize_tasks) { + std::uniform_int_distribution dist(0, prompt_lines.size()/6-1 ) ; + idx = dist(rng); + } + + hs_data[i].context = prompt_lines[idx*6]; + hs_data[i].gold_ending_idx = std::stoi( prompt_lines[idx*6+1] ); + for (size_t j=0; j < 4; j++) { + hs_data[i].ending[j] = " " + prompt_lines[idx*6+2+j]; + } + + // Delete the selected random example from the prompt + if (randomize_tasks) { + prompt_lines.erase( std::next(prompt_lines.begin(),idx*6) , std::next(prompt_lines.begin(),idx*6+6) ); + } + } + + fprintf(stderr, "%s : calculating hellaswag score over selected tasks.\n", __func__); + printf("\ntask\tacc_norm\n"); + + double acc = 0.0f; const int n_vocab = llama_n_vocab(ctx); - int counttotal = 0; - size_t n_lines = prompt_lines.size(); + for (size_t task_idx = 0; task_idx < hs_task_count; task_idx++) { - double nll = 0.0; + // Tokenize the context to count tokens + std::vector context_embd = ::llama_tokenize(ctx, hs_data[task_idx].context, prepend_bos); + size_t context_size = context_embd.size(); - fprintf(stderr, "%s: calculating perplexity over %lu lines\n", __func__, n_lines); + for (size_t ending_idx=0;ending_idx<4;ending_idx++) { - printf("\nLine\tPPL line\tPPL cumulative\n"); + // Tokenize the query + std::vector query_embd = ::llama_tokenize(ctx, hs_data[task_idx].context + hs_data[task_idx].ending[ending_idx], prepend_bos); + size_t query_size = query_embd.size(); - for (size_t i = 0; i < n_lines; ++i) { + // Stop if query wont fit the ctx window + if (query_size > (size_t)params.n_ctx) { + fprintf(stderr, "%s : number of tokens in query %zu > n_ctxl\n", __func__, query_size); + return; + } - // Tokenize and insert BOS at start - std::vector batch_embd = ::llama_tokenize(ctx, prompt_lines[i], true); + // Speedup small evaluations by evaluating atleast 32 tokens + if (query_size < 32) { + query_embd.resize(32); + } - size_t batch_size = batch_embd.size(); + // Evaluate the query + if (llama_eval(ctx, query_embd.data(), query_embd.size(), 0, params.n_threads)) { + fprintf(stderr, "%s : failed to eval\n", __func__); + return; + } - // Stop if line is too long - if( batch_size > (size_t)params.n_ctx ) { - fprintf(stderr, "%s : tokens in line %lu > n_ctxl\n", __func__, i); - return; + const auto query_logits = llama_get_logits(ctx); + std::vector logits; + logits.insert(logits.end(), query_logits, query_logits + query_size * n_vocab); + + hs_data[task_idx].ending_logprob_count[ending_idx] = 0; + hs_data[task_idx].ending_logprob[ending_idx] = 0.0f; + + // Calculate the logprobs over the ending + for (size_t j = context_size-1; j < query_size - 1; j++) { + // Calculate probability of next token, given the previous ones. + const std::vector tok_logits( + logits.begin() + (j + 0) * n_vocab, + logits.begin() + (j + 1) * n_vocab); + + const float prob = softmax(tok_logits)[query_embd[ j + 1]]; + + hs_data[task_idx].ending_logprob[ending_idx] += std::log(prob); + hs_data[task_idx].ending_logprob_count[ending_idx]++; + } + + // Calculate the mean token logprob for acc_norm + hs_data[task_idx].ending_logprob[ending_idx] /= hs_data[task_idx].ending_logprob_count[ending_idx]; + + +// printf("task %lu, ending %lu, whole_len %lu, context_len %lu, ending_logprob_count %lu, ending_logprob %.4f\n", +// task_idx,ending_idx,whole_size,context_size, hs_data[task_idx].ending_logprob_count[ending_idx], hs_data[task_idx].ending_logprob[ending_idx] ); } - if (llama_eval(ctx, batch_embd.data(), batch_size, 0, params.n_threads)) { - fprintf(stderr, "%s : failed to eval\n", __func__); - return; + // Find the ending with maximum logprob + size_t ending_logprob_max_idx = -1; + double ending_logprob_max_val = -INFINITY; + for (size_t j=0; j < 4; j++) { + if (hs_data[task_idx].ending_logprob[j] > ending_logprob_max_val) { + ending_logprob_max_idx = j; + ending_logprob_max_val = hs_data[task_idx].ending_logprob[j]; + } } - const auto batch_logits = llama_get_logits(ctx); - std::vector logits; - logits.insert(logits.end(), batch_logits, batch_logits + batch_size * n_vocab); +// printf("max logprob ending idx %lu, gold ending idx %lu\n", ending_logprob_max_idx, hs_data[task_idx].gold_ending_idx); - double nllline = 0.0; - int countline = 0; - - // Perplexity over second half of the line - for (size_t j = batch_size/2; j < batch_size - 1; ++j) { - // Calculate probability of next token, given the previous ones. - const std::vector tok_logits( - logits.begin() + (j + 0) * n_vocab, - logits.begin() + (j + 1) * n_vocab); - - const float prob = softmax(tok_logits)[batch_embd[ j + 1]]; - - nllline += -std::log(prob); - ++countline; + // If the gold ending got the maximum logprobe add one accuracy point + if (ending_logprob_max_idx == hs_data[task_idx].gold_ending_idx) { + acc += 1.0; } - nll += nllline; - counttotal += countline; - - // perplexity is e^(average negative log-likelihood) - printf("%lu\t%.8lf\t%.8lf\n", i + 1, std::exp(nllline/countline), std::exp(nll / counttotal) ); + // Print the accumulated accuracy mean x 100 + printf("%zu\t%.8lf\n",task_idx+1, acc/double(task_idx+1)*100.0); fflush(stdout); } + delete [] hs_data; + printf("\n"); } @@ -240,8 +341,8 @@ int main(int argc, char ** argv) { params.n_threads, std::thread::hardware_concurrency(), llama_print_system_info()); } - if (params.perplexity_lines) { - perplexity_lines(ctx, params); + if (params.hellaswag) { + hellaswag_score(ctx, params); } else { perplexity(ctx, params); } diff --git a/examples/save-load-state/save-load-state.cpp b/examples/save-load-state/save-load-state.cpp index 4c8688503..61c71c358 100644 --- a/examples/save-load-state/save-load-state.cpp +++ b/examples/save-load-state/save-load-state.cpp @@ -26,6 +26,7 @@ int main(int argc, char ** argv) { auto lparams = llama_context_default_params(); lparams.n_ctx = params.n_ctx; + lparams.n_gqa = params.n_gqa; lparams.seed = params.seed; lparams.f16_kv = params.memory_f16; lparams.use_mmap = params.use_mmap; diff --git a/examples/server-llama2-13B.sh b/examples/server-llama2-13B.sh new file mode 100644 index 000000000..17fedc2b1 --- /dev/null +++ b/examples/server-llama2-13B.sh @@ -0,0 +1,26 @@ +#!/bin/bash + +set -e + +cd "$(dirname "$0")/.." || exit + +# Specify the model you want to use here: +MODEL="${MODEL:-./models/llama-2-13b-chat.ggmlv3.q5_K_M.bin}" +PROMPT_TEMPLATE=${PROMPT_TEMPLATE:-./prompts/chat-system.txt} + +# Adjust to the number of CPU cores you want to use. +N_THREAD="${N_THREAD:-12}" + +# Note: you can also override the generation options by specifying them on the command line: +GEN_OPTIONS="${GEN_OPTIONS:---ctx_size 4096 --batch-size 1024}" + + +# shellcheck disable=SC2086 # Intended splitting of GEN_OPTIONS +./server $GEN_OPTIONS \ + --model "$MODEL" \ + --threads "$N_THREAD" \ + --rope-freq-scale 1.0 \ + "$@" + +# I used this to test the model with mps, but omitted it from the general purpose. If you want to use it, just specify it on the command line. +# -ngl 1 \ diff --git a/examples/server/README.md b/examples/server/README.md index e5ca8269b..e56ca063a 100644 --- a/examples/server/README.md +++ b/examples/server/README.md @@ -151,6 +151,8 @@ node . `mirostat_eta`: Set the Mirostat learning rate, parameter eta (default: 0.1). + `grammar`: Set grammar for grammar-based sampling (default: no grammar) + `seed`: Set the random number generator (RNG) seed (default: -1, -1 = random seed). `ignore_eos`: Ignore end of stream token and continue generating (default: false). @@ -163,7 +165,7 @@ node . `content`: Set the text to tokenize. - Note that the special `BOS` token is not added in fron of the text and also a space character is not inserted automatically as it is for `/completion`. + Note that the special `BOS` token is not added in front of the text and also a space character is not inserted automatically as it is for `/completion`. - **POST** `/embedding`: Generate embedding of a given text just as [the embedding example](../embedding) does. diff --git a/examples/server/chat-llama2.sh b/examples/server/chat-llama2.sh new file mode 100644 index 000000000..1fc79b7e1 --- /dev/null +++ b/examples/server/chat-llama2.sh @@ -0,0 +1,109 @@ +#!/bin/bash + +API_URL="${API_URL:-http://127.0.0.1:8080}" + +CHAT=( + "Hello, Assistant." + "Hello. How may I help you today?" +) + +INSTRUCTION="A chat between a curious human and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the human's questions." + +trim() { + shopt -s extglob + set -- "${1##+([[:space:]])}" + printf "%s" "${1%%+([[:space:]])}" +} + +trim_trailing() { + shopt -s extglob + printf "%s" "${1%%+([[:space:]])}" +} + +format_prompt() { + if [[ "${#CHAT[@]}" -eq 0 ]]; then + echo -n "[INST] <>\n${INSTRUCTION}\n<>" + else + LAST_INDEX=$(( ${#CHAT[@]} - 1 )) + echo -n "${CHAT[$LAST_INDEX]}\n[INST] $1 [/INST]" + fi +} + +tokenize() { + curl \ + --silent \ + --request POST \ + --url "${API_URL}/tokenize" \ + --header "Content-Type: application/json" \ + --data-raw "$(jq -ns --arg content "$1" '{content:$content}')" \ + | jq '.tokens[]' +} + +N_KEEP=$(tokenize "[INST] <>\n${INSTRUCTION}\n<>" | wc -l) + +chat_completion() { + PROMPT="$(trim_trailing "$(format_prompt "$1")")" + DATA="$(echo -n "$PROMPT" | jq -Rs --argjson n_keep $N_KEEP '{ + prompt: ., + temperature: 0.2, + top_k: 40, + top_p: 0.9, + n_keep: $n_keep, + n_predict: 1024, + stop: ["[INST]"], + stream: true + }')" + + # Create a temporary file to hold the Python output + TEMPFILE=$(mktemp) + + exec 3< <(curl \ + --silent \ + --no-buffer \ + --request POST \ + --url "${API_URL}/completion" \ + --header "Content-Type: application/json" \ + --data-raw "${DATA}") + + python -c " +import json +import sys + +answer = '' +while True: + line = sys.stdin.readline() + if not line: + break + if line.startswith('data: '): + json_content = line[6:].strip() + content = json.loads(json_content)['content'] + sys.stdout.write(content) + sys.stdout.flush() + answer += content + +answer = answer.rstrip('\n') + +# Write the answer to the temporary file +with open('$TEMPFILE', 'w') as f: + f.write(answer) + " <&3 + + exec 3<&- + + # Read the answer from the temporary file + ANSWER=$(cat $TEMPFILE) + + # Clean up the temporary file + rm $TEMPFILE + + printf "\n" + + CHAT+=("$1" "$(trim "$ANSWER")") +} + +while true; do + echo -en "\033[0;32m" # Green color + read -r -e -p "> " QUESTION + echo -en "\033[0m" # Reset color + chat_completion "${QUESTION}" +done diff --git a/examples/server/completion.js.hpp b/examples/server/completion.js.hpp index f399fb19a..f0a071a69 100644 --- a/examples/server/completion.js.hpp +++ b/examples/server/completion.js.hpp @@ -87,289 +87,342 @@ unsigned char completion_js[] = { 0x20, 0x54, 0x65, 0x78, 0x74, 0x44, 0x65, 0x63, 0x6f, 0x64, 0x65, 0x72, 0x28, 0x29, 0x3b, 0x0a, 0x0a, 0x20, 0x20, 0x6c, 0x65, 0x74, 0x20, 0x63, 0x6f, 0x6e, 0x74, 0x65, 0x6e, 0x74, 0x20, 0x3d, 0x20, 0x22, 0x22, 0x3b, - 0x0a, 0x0a, 0x20, 0x20, 0x74, 0x72, 0x79, 0x20, 0x7b, 0x0a, 0x20, 0x20, - 0x20, 0x20, 0x6c, 0x65, 0x74, 0x20, 0x63, 0x6f, 0x6e, 0x74, 0x20, 0x3d, - 0x20, 0x74, 0x72, 0x75, 0x65, 0x3b, 0x0a, 0x0a, 0x20, 0x20, 0x20, 0x20, - 0x77, 0x68, 0x69, 0x6c, 0x65, 0x20, 0x28, 0x63, 0x6f, 0x6e, 0x74, 0x29, - 0x20, 0x7b, 0x0a, 0x20, 0x20, 0x20, 0x20, 0x20, 0x20, 0x63, 0x6f, 0x6e, - 0x73, 0x74, 0x20, 0x72, 0x65, 0x73, 0x75, 0x6c, 0x74, 0x20, 0x3d, 0x20, - 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llama(prompt, params = {}, config = {}) { const decoder = new TextDecoder(); let content = ""; + let leftover = ""; // Buffer for partially read lines try { let cont = true; @@ -53,29 +54,47 @@ export async function* llama(prompt, params = {}, config = {}) { break; } - // sse answers in the form multiple lines of: value\n with data always present as a key. in our case we - // mainly care about the data: key here, which we expect as json - const text = decoder.decode(result.value); + // Add any leftover data to the current chunk of data + const text = leftover + decoder.decode(result.value); - // parse all sse events and add them to result - const regex = /^(\S+):\s(.*)$/gm; - for (const match of text.matchAll(regex)) { - result[match[1]] = match[2] + // Check if the last character is a line break + const endsWithLineBreak = text.endsWith('\n'); + + // Split the text into lines + let lines = text.split('\n'); + + // If the text doesn't end with a line break, then the last line is incomplete + // Store it in leftover to be added to the next chunk of data + if (!endsWithLineBreak) { + leftover = lines.pop(); + } else { + leftover = ""; // Reset leftover if we have a line break at the end } - // since we know this is llama.cpp, let's just decode the json in data - result.data = JSON.parse(result.data); - content += result.data.content; + // Parse all sse events and add them to result + const regex = /^(\S+):\s(.*)$/gm; + for (const line of lines) { + const match = regex.exec(line); + if (match) { + result[match[1]] = match[2] + // since we know this is llama.cpp, let's just decode the json in data + if (result.data) { + result.data = JSON.parse(result.data); + content += result.data.content; - // yield - yield result; + // yield + yield result; - // if we got a stop token from server, we will break here - if (result.data.stop) { - if (result.data.generation_settings) { - generation_settings = result.data.generation_settings; + // if we got a stop token from server, we will break here + if (result.data.stop) { + if (result.data.generation_settings) { + generation_settings = result.data.generation_settings; + } + cont = false; + break; + } + } } - break; } } } catch (e) { diff --git a/examples/server/public/index.html b/examples/server/public/index.html index f5ed2d427..de41da187 100644 --- a/examples/server/public/index.html +++ b/examples/server/public/index.html @@ -3,12 +3,11 @@ + llama.cpp - chat