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Merge branch 'master' into llg

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This commit is contained in:
Michal Moskal 2025-01-31 11:23:33 -08:00
commit 6b2de55137
102 changed files with 6972 additions and 888 deletions
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10
.devops/tools.sh
View file

@ -13,9 +13,13 @@ elif [[ "$arg1" == '--quantize' || "$arg1" == '-q' ]]; then
exec ./llama-quantize "$@"
elif [[ "$arg1" == '--run' || "$arg1" == '-r' ]]; then
exec ./llama-cli "$@"
elif [[ "$arg1" == '--bench' || "$arg1" == '-b' ]]; then
exec ./llama-bench "$@"
elif [[ "$arg1" == '--perplexity' || "$arg1" == '-p' ]]; then
exec ./llama-perplexity "$@"
elif [[ "$arg1" == '--all-in-one' || "$arg1" == '-a' ]]; then
echo "Converting PTH to GGML..."
for i in `ls $1/$2/ggml-model-f16.bin*`; do
for i in $(ls $1/$2/ggml-model-f16.bin*); do
if [ -f "${i/f16/q4_0}" ]; then
echo "Skip model quantization, it already exists: ${i/f16/q4_0}"
else
@ -30,6 +34,10 @@ else
echo "Available commands: "
echo " --run (-r): Run a model previously converted into ggml"
echo " ex: -m /models/7B/ggml-model-q4_0.bin -p \"Building a website can be done in 10 simple steps:\" -n 512"
echo " --bench (-b): Benchmark the performance of the inference for various parameters."
echo " ex: -m model.gguf"
echo " --perplexity (-p): Measure the perplexity of a model over a given text."
echo " ex: -m model.gguf -f file.txt"
echo " --convert (-c): Convert a llama model into ggml"
echo " ex: --outtype f16 \"/models/7B/\" "
echo " --quantize (-q): Optimize with quantization process ggml"

11
.devops/vulkan.Dockerfile
View file

@ -1,4 +1,4 @@
ARG UBUNTU_VERSION=jammy
ARG UBUNTU_VERSION=24.04
FROM ubuntu:$UBUNTU_VERSION AS build
@ -7,7 +7,7 @@ RUN apt update && apt install -y git build-essential cmake wget
# Install Vulkan SDK and cURL
RUN wget -qO - https://packages.lunarg.com/lunarg-signing-key-pub.asc | apt-key add - && \
wget -qO /etc/apt/sources.list.d/lunarg-vulkan-jammy.list https://packages.lunarg.com/vulkan/lunarg-vulkan-jammy.list && \
wget -qO /etc/apt/sources.list.d/lunarg-vulkan-noble.list https://packages.lunarg.com/vulkan/lunarg-vulkan-noble.list && \
apt update -y && \
apt-get install -y vulkan-sdk libcurl4-openssl-dev curl
@ -34,7 +34,7 @@ RUN mkdir -p /app/full \
FROM ubuntu:$UBUNTU_VERSION AS base
RUN apt-get update \
&& apt-get install -y libgomp1 curl\
&& apt-get install -y libgomp1 curl libvulkan-dev \
&& apt autoremove -y \
&& apt clean -y \
&& rm -rf /tmp/* /var/tmp/* \
@ -55,8 +55,9 @@ RUN apt-get update \
git \
python3 \
python3-pip \
&& pip install --upgrade pip setuptools wheel \
&& pip install -r requirements.txt \
python3-wheel \
&& pip install --break-system-packages --upgrade setuptools \
&& pip install --break-system-packages -r requirements.txt \
&& apt autoremove -y \
&& apt clean -y \
&& rm -rf /tmp/* /var/tmp/* \

8
.editorconfig
View file

@ -40,3 +40,11 @@ indent_style = tab
[examples/cvector-generator/*.txt]
trim_trailing_whitespace = unset
insert_final_newline = unset
[models/templates/*.jinja]
indent_style = unset
indent_size = unset
end_of_line = unset
charset = unset
trim_trailing_whitespace = unset
insert_final_newline = unset

146
.github/workflows/build.yml vendored
View file

@ -43,6 +43,12 @@ jobs:
with:
fetch-depth: 0
- name: ccache
uses: hendrikmuhs/ccache-action@v1.2.16
with:
key: macOS-latest-cmake-arm64
evict-old-files: 1d
- name: Dependencies
id: depends
continue-on-error: true
@ -108,6 +114,12 @@ jobs:
with:
fetch-depth: 0
- name: ccache
uses: hendrikmuhs/ccache-action@v1.2.16
with:
key: macOS-latest-cmake-x64
evict-old-files: 1d
- name: Dependencies
id: depends
continue-on-error: true
@ -172,6 +184,12 @@ jobs:
with:
fetch-depth: 0
- name: ccache
uses: hendrikmuhs/ccache-action@v1.2.16
with:
key: ubuntu-cpu-cmake
evict-old-files: 1d
- name: Dependencies
id: depends
run: |
@ -249,6 +267,12 @@ jobs:
id: checkout
uses: actions/checkout@v4
- name: ccache
uses: hendrikmuhs/ccache-action@v1.2.16
with:
key: ubuntu-latest-cmake-sanitizer-${{ matrix.sanitizer }}
evict-old-files: 1d
- name: Dependencies
id: depends
run: |
@ -326,6 +350,12 @@ jobs:
id: checkout
uses: actions/checkout@v4
- name: ccache
uses: hendrikmuhs/ccache-action@v1.2.16
with:
key: ubuntu-latest-cmake-rpc
evict-old-files: 1d
- name: Dependencies
id: depends
run: |
@ -355,6 +385,12 @@ jobs:
id: checkout
uses: actions/checkout@v4
- name: ccache
uses: hendrikmuhs/ccache-action@v1.2.16
with:
key: ubuntu-22-cmake-vulkan
evict-old-files: 1d
- name: Dependencies
id: depends
run: |
@ -376,7 +412,8 @@ jobs:
id: cmake_test
run: |
cd build
ctest -L main --verbose --timeout 900
# This is using llvmpipe and runs slower than other backends
ctest -L main --verbose --timeout 1800
ubuntu-22-cmake-hip:
runs-on: ubuntu-22.04
@ -393,6 +430,12 @@ jobs:
sudo apt-get update
sudo apt-get install -y build-essential git cmake rocblas-dev hipblas-dev
- name: ccache
uses: hendrikmuhs/ccache-action@v1.2.16
with:
key: ubuntu-22-cmake-hip
evict-old-files: 1d
- name: Build with native CMake HIP support
id: cmake_build
run: |
@ -425,6 +468,12 @@ jobs:
apt-get update
apt-get install -y build-essential git cmake libcurl4-openssl-dev
- name: ccache
uses: hendrikmuhs/ccache-action@v1.2.16
with:
key: ubuntu-22-cmake-musa
evict-old-files: 1d
- name: Build with native CMake MUSA support
id: cmake_build
run: |
@ -464,6 +513,12 @@ jobs:
id: checkout
uses: actions/checkout@v4
- name: ccache
uses: hendrikmuhs/ccache-action@v1.2.16
with:
key: ubuntu-22-cmake-sycl
evict-old-files: 1d
- name: Build
id: cmake_build
run: |
@ -508,6 +563,12 @@ jobs:
id: checkout
uses: actions/checkout@v4
- name: ccache
uses: hendrikmuhs/ccache-action@v1.2.16
with:
key: ubuntu-22-cmake-sycl-fp16
evict-old-files: 1d
- name: Build
id: cmake_build
run: |
@ -529,6 +590,12 @@ jobs:
id: checkout
uses: actions/checkout@v4
- name: ccache
uses: hendrikmuhs/ccache-action@v1.2.16
with:
key: macOS-latest-cmake-ios
evict-old-files: 1d
- name: Dependencies
id: depends
continue-on-error: true
@ -560,6 +627,12 @@ jobs:
id: checkout
uses: actions/checkout@v4
- name: ccache
uses: hendrikmuhs/ccache-action@v1.2.16
with:
key: macOS-latest-cmake-tvos
evict-old-files: 1d
- name: Dependencies
id: depends
continue-on-error: true
@ -595,6 +668,12 @@ jobs:
id: checkout
uses: actions/checkout@v4
- name: ccache
uses: hendrikmuhs/ccache-action@v1.2.16
with:
key: macOS-latest-swift
evict-old-files: 1d
- name: Dependencies
id: depends
continue-on-error: true
@ -636,6 +715,13 @@ jobs:
- name: Clone
uses: actions/checkout@v4
- name: ccache
uses: hendrikmuhs/ccache-action@v1.2.16
with:
key: windows-msys2
variant: sccache
evict-old-files: 1d
- name: Setup ${{ matrix.sys }}
uses: msys2/setup-msys2@v2
with:
@ -643,6 +729,7 @@ jobs:
msystem: ${{matrix.sys}}
install: >-
base-devel
git
mingw-w64-${{matrix.env}}-toolchain
mingw-w64-${{matrix.env}}-cmake
mingw-w64-${{matrix.env}}-openblas
@ -703,6 +790,13 @@ jobs:
with:
fetch-depth: 0
- name: ccache
uses: hendrikmuhs/ccache-action@v1.2.16
with:
key: windows-latest-cmake-${{ matrix.build }}
variant: sccache
evict-old-files: 1d
- name: Clone Kompute submodule
id: clone_kompute
if: ${{ matrix.build == 'kompute-x64' }}
@ -841,6 +935,8 @@ jobs:
- name: Clone
id: checkout
uses: actions/checkout@v4
with:
fetch-depth: 0
- name: Install dependencies
env:
@ -849,6 +945,12 @@ jobs:
apt update
apt install -y cmake build-essential ninja-build libgomp1 git
- name: ccache
uses: hendrikmuhs/ccache-action@v1.2.16
with:
key: ubuntu-latest-cmake-cuda
evict-old-files: 1d
- name: Build with CMake
run: |
cmake -S . -B build -G Ninja \
@ -875,6 +977,13 @@ jobs:
with:
fetch-depth: 0
- name: Install ccache
uses: hendrikmuhs/ccache-action@v1.2.16
with:
key: ${{ github.job }}-${{ matrix.cuda }}-${{ matrix.build }}
variant: sccache
evict-old-files: 1d
- name: Install Cuda Toolkit 11.7
if: ${{ matrix.cuda == '11.7' }}
run: |
@ -931,11 +1040,6 @@ jobs:
echo "CUDA_PATH=C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.4" | Out-File -FilePath $env:GITHUB_ENV -Append -Encoding utf8
echo "CUDA_PATH_V12_4=C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.4" | Out-File -FilePath $env:GITHUB_ENV -Append -Encoding utf8
- name: Install ccache
uses: hendrikmuhs/ccache-action@v1.2
with:
key: ${{ github.job }}-${{ matrix.cuda }}-${{ matrix.build }}
- name: Install Ninja
id: install_ninja
run: |
@ -1015,6 +1119,13 @@ jobs:
with:
fetch-depth: 0
- name: ccache
uses: hendrikmuhs/ccache-action@v1.2.16
with:
key: windows-latest-cmake-sycl
variant: sccache
evict-old-files: 1d
- name: Install
run: |
scripts/install-oneapi.bat $WINDOWS_BASEKIT_URL $WINDOWS_DPCPP_MKL
@ -1094,9 +1205,11 @@ jobs:
& 'C:\Program Files\AMD\ROCm\*\bin\clang.exe' --version
- name: Install ccache
uses: hendrikmuhs/ccache-action@v1.2
uses: hendrikmuhs/ccache-action@v1.2.16
with:
key: ${{ github.job }}
variant: sccache
evict-old-files: 1d
- name: Build
id: cmake_build
@ -1126,6 +1239,13 @@ jobs:
with:
fetch-depth: 0
- name: ccache
uses: hendrikmuhs/ccache-action@v1.2.16
with:
key: windows-latest-cmake-hip-release
variant: sccache
evict-old-files: 1d
- name: Install
id: depends
run: |
@ -1223,6 +1343,12 @@ jobs:
- name: Clone
uses: actions/checkout@v4
- name: ccache
uses: hendrikmuhs/ccache-action@v1.2.16
with:
key: android-build
evict-old-files: 1d
- name: Set up JDK
uses: actions/setup-java@v3
with:
@ -1260,6 +1386,12 @@ jobs:
with:
fetch-depth: 0
- name: ccache
uses: hendrikmuhs/ccache-action@v1.2.16
with:
key: release
evict-old-files: 1d
- name: Determine tag name
id: tag
shell: bash

3
.github/workflows/docker.yml vendored
View file

@ -28,10 +28,11 @@ jobs:
push_to_registry:
name: Push Docker image to Docker Hub
runs-on: ubuntu-latest
runs-on: ubuntu-22.04
env:
COMMIT_SHA: ${{ github.sha }}
strategy:
fail-fast: false
matrix:
config:
# Multi-stage build

2
.github/workflows/server.yml vendored
View file

@ -205,7 +205,7 @@ jobs:
run: |
cd examples/server/tests
$env:PYTHONIOENCODING = ":replace"
pytest -v -x
pytest -v -x -m "not slow"
- name: Slow tests
id: server_integration_tests_slow

26
CMakeLists.txt
View file

@ -50,7 +50,8 @@ endif()
if (MSVC)
add_compile_options("$<$<COMPILE_LANGUAGE:C>:/utf-8>")
add_compile_options("$<$<COMPILE_LANGUAGE:CXX>:/utf-8>")
add_compile_options(/bigobj)
add_compile_options("$<$<COMPILE_LANGUAGE:C>:/bigobj>")
add_compile_options("$<$<COMPILE_LANGUAGE:CXX>:/bigobj>")
endif()
#
@ -188,27 +189,14 @@ set(LLAMA_INCLUDE_INSTALL_DIR ${CMAKE_INSTALL_INCLUDEDIR} CACHE PATH "Location o
set(LLAMA_LIB_INSTALL_DIR ${CMAKE_INSTALL_LIBDIR} CACHE PATH "Location of library files")
set(LLAMA_BIN_INSTALL_DIR ${CMAKE_INSTALL_BINDIR} CACHE PATH "Location of binary files")
# At the moment some compile definitions are placed within the ggml/src
# directory but not exported on the `ggml` target. This could be improved by
# determining _precisely_ which defines are necessary for the llama-config
# package.
#
set(GGML_TRANSIENT_DEFINES)
get_target_property(GGML_DIRECTORY ggml SOURCE_DIR)
get_directory_property(GGML_DIR_DEFINES DIRECTORY ${GGML_DIRECTORY} COMPILE_DEFINITIONS)
if (GGML_DIR_DEFINES)
list(APPEND GGML_TRANSIENT_DEFINES ${GGML_DIR_DEFINES})
endif()
get_target_property(GGML_TARGET_DEFINES ggml COMPILE_DEFINITIONS)
if (GGML_TARGET_DEFINES)
list(APPEND GGML_TRANSIENT_DEFINES ${GGML_TARGET_DEFINES})
endif()
get_target_property(GGML_LINK_LIBRARIES ggml LINK_LIBRARIES)
# all public headers
set(LLAMA_PUBLIC_HEADERS
${CMAKE_CURRENT_SOURCE_DIR}/include/llama.h
${CMAKE_CURRENT_SOURCE_DIR}/include/llama-cpp.h)
set_target_properties(llama PROPERTIES PUBLIC_HEADER "${LLAMA_PUBLIC_HEADERS}")
set_target_properties(llama
PROPERTIES
PUBLIC_HEADER "${LLAMA_PUBLIC_HEADERS}")
install(TARGETS llama LIBRARY PUBLIC_HEADER)
configure_package_config_file(

9
Makefile
View file

@ -52,6 +52,7 @@ TEST_TARGETS = \
tests/test-arg-parser \
tests/test-autorelease \
tests/test-backend-ops \
tests/test-chat \
tests/test-chat-template \
tests/test-double-float \
tests/test-grammar-integration \
@ -983,6 +984,7 @@ OBJ_COMMON = \
$(DIR_COMMON)/ngram-cache.o \
$(DIR_COMMON)/sampling.o \
$(DIR_COMMON)/speculative.o \
$(DIR_COMMON)/chat.o \
$(DIR_COMMON)/build-info.o \
$(DIR_COMMON)/json-schema-to-grammar.o
@ -1361,6 +1363,8 @@ llama-server: \
examples/server/httplib.h \
examples/server/index.html.hpp \
examples/server/loading.html.hpp \
common/chat.cpp \
common/chat.hpp \
common/chat-template.hpp \
common/json.hpp \
common/minja.hpp \
@ -1471,6 +1475,11 @@ tests/test-json-schema-to-grammar: tests/test-json-schema-to-grammar.cpp \
$(CXX) $(CXXFLAGS) -Iexamples/server -c $< -o $(call GET_OBJ_FILE, $<)
$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
tests/test-chat: tests/test-chat.cpp \
$(OBJ_ALL)
$(CXX) $(CXXFLAGS) -Iexamples/server -c $< -o $(call GET_OBJ_FILE, $<)
$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
tests/test-opt: tests/test-opt.cpp \
$(OBJ_GGML)
$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)

4
README.md
View file

@ -16,7 +16,9 @@ Inference of Meta's [LLaMA](https://arxiv.org/abs/2302.13971) model (and others)
## Hot topics
- **How to use [MTLResidencySet](https://developer.apple.com/documentation/metal/mtlresidencyset?language=objc) to keep the GPU memory active?** https://github.com/ggerganov/llama.cpp/pull/11427
- **VS Code extension for FIM completions:** https://github.com/ggml-org/llama.vscode
- Universal tool call support in `llama-server`: https://github.com/ggerganov/llama.cpp/pull/9639
- Vim/Neovim plugin for FIM completions: https://github.com/ggml-org/llama.vim
- Introducing GGUF-my-LoRA https://github.com/ggerganov/llama.cpp/discussions/10123
- Hugging Face Inference Endpoints now support GGUF out of the box! https://github.com/ggerganov/llama.cpp/discussions/9669
@ -421,7 +423,7 @@ To learn more about model quantization, [read this documentation](examples/quant
</details>
[^1]: [examples/perplexity/README.md](examples/perplexity/README.md)
[^1]: [examples/perplexity/README.md](./examples/perplexity/README.md)
[^2]: [https://huggingface.co/docs/transformers/perplexity](https://huggingface.co/docs/transformers/perplexity)
## [`llama-bench`](examples/llama-bench)

156
cmake/llama-config.cmake.in
View file

@ -3,159 +3,13 @@ set(LLAMA_BUILD_COMMIT @LLAMA_BUILD_COMMIT@)
set(LLAMA_BUILD_NUMBER @LLAMA_BUILD_NUMBER@)
set(LLAMA_SHARED_LIB @BUILD_SHARED_LIBS@)
set(GGML_STATIC @GGML_STATIC@)
set(GGML_NATIVE @GGML_NATIVE@)
set(GGML_LTO @GGML_LTO@)
set(GGML_CCACHE @GGML_CCACHE@)
set(GGML_AVX @GGML_AVX@)
set(GGML_AVX2 @GGML_AVX2@)
set(GGML_AVX512 @GGML_AVX512@)
set(GGML_AVX512_VBMI @GGML_AVX512_VBMI@)
set(GGML_AVX512_VNNI @GGML_AVX512_VNNI@)
set(GGML_AVX512_BF16 @GGML_AVX512_BF16@)
set(GGML_AMX_TILE @GGML_AMX_TILE@)
set(GGML_AMX_INT8 @GGML_AMX_INT8@)
set(GGML_AMX_BF16 @GGML_AMX_BF16@)
set(GGML_FMA @GGML_FMA@)
set(GGML_LASX @GGML_LASX@)
set(GGML_LSX @GGML_LSX@)
set(GGML_RVV @GGML_RVV@)
set(GGML_SVE @GGML_SVE@)
set(GGML_ACCELERATE @GGML_ACCELERATE@)
set(GGML_OPENMP @GGML_OPENMP@)
set(GGML_CPU_HBM @GGML_CPU_HBM@)
set(GGML_BLAS_VENDOR @GGML_BLAS_VENDOR@)
set(GGML_CUDA_FORCE_MMQ @GGML_CUDA_FORCE_MMQ@)
set(GGML_CUDA_FORCE_CUBLAS @GGML_CUDA_FORCE_CUBLAS@)
set(GGML_CUDA_F16 @GGML_CUDA_F16@)
set(GGML_CUDA_PEER_MAX_BATCH_SIZE @GGML_CUDA_PEER_MAX_BATCH_SIZE@)
set(GGML_CUDA_NO_PEER_COPY @GGML_CUDA_NO_PEER_COPY@)
set(GGML_CUDA_NO_VMM @GGML_CUDA_NO_VMM@)
set(GGML_CUDA_FA_ALL_QUANTS @GGML_CUDA_FA_ALL_QUANTS@)
set(GGML_CUDA_GRAPHS @GGML_CUDA_GRAPHS@)
set(GGML_HIP_UMA @GGML_HIP_UMA@)
set(GGML_VULKAN_CHECK_RESULTS @GGML_VULKAN_CHECK_RESULTS@)
set(GGML_VULKAN_DEBUG @GGML_VULKAN_DEBUG@)
set(GGML_VULKAN_MEMORY_DEBUG @GGML_VULKAN_MEMORY_DEBUG@)
set(GGML_VULKAN_SHADER_DEBUG_INFO @GGML_VULKAN_SHADER_DEBUG_INFO@)
set(GGML_VULKAN_PERF @GGML_VULKAN_PERF@)
set(GGML_VULKAN_VALIDATE @GGML_VULKAN_VALIDATE@)
set(GGML_VULKAN_RUN_TESTS @GGML_VULKAN_RUN_TESTS@)
set(GGML_METAL_USE_BF16 @GGML_METAL_USE_BF16@)
set(GGML_METAL_NDEBUG @GGML_METAL_NDEBUG@)
set(GGML_METAL_SHADER_DEBUG @GGML_METAL_SHADER_DEBUG@)
set(GGML_METAL_EMBED_LIBRARY @GGML_METAL_EMBED_LIBRARY@)
set(GGML_METAL_MACOSX_VERSION_MIN @GGML_METAL_MACOSX_VERSION_MIN@)
set(GGML_METAL_STD @GGML_METAL_STD@)
set(GGML_SYCL_F16 @GGML_SYCL_F16@)
set(GGML_SYCL_TARGET @GGML_SYCL_TARGET@)
set(GGML_SYCL_DEVICE_ARCH @GGML_SYCL_DEVICE_ARCH@)
@PACKAGE_INIT@
set_and_check(LLAMA_INCLUDE_DIR "@PACKAGE_LLAMA_INCLUDE_INSTALL_DIR@")
set_and_check(LLAMA_LIB_DIR "@PACKAGE_LLAMA_LIB_INSTALL_DIR@")
set_and_check(LLAMA_BIN_DIR "@PACKAGE_LLAMA_BIN_INSTALL_DIR@")
find_package(Threads REQUIRED)
set(_llama_transient_defines "@GGML_TRANSIENT_DEFINES@")
set(_llama_link_deps "")
set(_llama_link_opts "")
foreach(_ggml_lib ggml ggml-base)
string(REPLACE "-" "_" _ggml_lib_var "${_ggml_lib}_LIBRARY")
find_library(${_ggml_lib_var} ${_ggml_lib}
REQUIRED
HINTS ${LLAMA_LIB_DIR}
NO_CMAKE_FIND_ROOT_PATH
)
list(APPEND _llama_link_deps "${${_ggml_lib_var}}")
message(STATUS "Found ${${_ggml_lib_var}}")
endforeach()
foreach(backend amx blas cann cpu cuda hip kompute metal musa rpc sycl vulkan)
string(TOUPPER "GGML_${backend}" backend_id)
set(_ggml_lib "ggml-${backend}")
string(REPLACE "-" "_" _ggml_lib_var "${_ggml_lib}_LIBRARY")
find_library(${_ggml_lib_var} ${_ggml_lib}
HINTS ${LLAMA_LIB_DIR}
NO_CMAKE_FIND_ROOT_PATH
)
if(${_ggml_lib_var})
list(APPEND _llama_link_deps "${${_ggml_lib_var}}")
set(${backend_id} ON)
message(STATUS "Found backend ${${_ggml_lib_var}}")
else()
set(${backend_id} OFF)
endif()
endforeach()
if (NOT LLAMA_SHARED_LIB)
if (APPLE AND GGML_ACCELERATE)
find_library(ACCELERATE_FRAMEWORK Accelerate REQUIRED)
list(APPEND _llama_link_deps ${ACCELERATE_FRAMEWORK})
endif()
if (GGML_OPENMP)
find_package(OpenMP REQUIRED)
list(APPEND _llama_link_deps OpenMP::OpenMP_C OpenMP::OpenMP_CXX)
endif()
if (GGML_CPU_HBM)
find_library(memkind memkind REQUIRED)
list(APPEND _llama_link_deps memkind)
endif()
if (GGML_BLAS)
find_package(BLAS REQUIRED)
list(APPEND _llama_link_deps ${BLAS_LIBRARIES})
list(APPEND _llama_link_opts ${BLAS_LINKER_FLAGS})
endif()
if (GGML_CUDA)
find_package(CUDAToolkit REQUIRED)
endif()
if (GGML_METAL)
find_library(FOUNDATION_LIBRARY Foundation REQUIRED)
find_library(METAL_FRAMEWORK Metal REQUIRED)
find_library(METALKIT_FRAMEWORK MetalKit REQUIRED)
list(APPEND _llama_link_deps ${FOUNDATION_LIBRARY}
${METAL_FRAMEWORK} ${METALKIT_FRAMEWORK})
endif()
if (GGML_VULKAN)
find_package(Vulkan REQUIRED)
list(APPEND _llama_link_deps Vulkan::Vulkan)
endif()
if (GGML_HIP)
find_package(hip REQUIRED)
find_package(hipblas REQUIRED)
find_package(rocblas REQUIRED)
list(APPEND _llama_link_deps hip::host roc::rocblas roc::hipblas)
endif()
if (GGML_SYCL)
find_package(DNNL)
if (${DNNL_FOUND} AND GGML_SYCL_TARGET STREQUAL "INTEL")
list(APPEND _llama_link_deps DNNL::dnnl)
endif()
if (WIN32)
find_package(IntelSYCL REQUIRED)
find_package(MKL REQUIRED)
list(APPEND _llama_link_deps IntelSYCL::SYCL_CXX MKL::MKL MKL::MKL_SYCL)
endif()
endif()
endif()
find_package(ggml REQUIRED HINTS ${LLAMA_LIB_DIR}/cmake)
find_library(llama_LIBRARY llama
REQUIRED
@ -167,12 +21,10 @@ add_library(llama UNKNOWN IMPORTED)
set_target_properties(llama
PROPERTIES
INTERFACE_INCLUDE_DIRECTORIES "${LLAMA_INCLUDE_DIR}"
INTERFACE_LINK_LIBRARIES "${_llama_link_deps}"
INTERFACE_LINK_OPTIONS "${_llama_link_opts}"
INTERFACE_COMPILE_DEFINITIONS "${_llama_transient_defines}"
INTERFACE_LINK_LIBRARIES "ggml::ggml;ggml::ggml-base;"
IMPORTED_LINK_INTERFACE_LANGUAGES "CXX"
IMPORTED_LOCATION "${llama_LIBRARY}"
INTERFACE_COMPILE_FEATURES cxx_std_11
POSITION_INDEPENDENT_CODE ON )
INTERFACE_COMPILE_FEATURES c_std_90
POSITION_INDEPENDENT_CODE ON)
check_required_components(Llama)

2
common/CMakeLists.txt
View file

@ -56,6 +56,8 @@ add_library(${TARGET} STATIC
arg.cpp
arg.h
base64.hpp
chat.cpp
chat.hpp
chat-template.hpp
common.cpp
common.h

2
common/arg.cpp
View file

@ -877,7 +877,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
[](common_params & params) {
params.warmup = false;
}
).set_examples({LLAMA_EXAMPLE_MAIN, LLAMA_EXAMPLE_SERVER}));
).set_examples({LLAMA_EXAMPLE_MAIN, LLAMA_EXAMPLE_SERVER, LLAMA_EXAMPLE_EMBEDDING}));
add_opt(common_arg(
{"--spm-infill"},
string_format(

256
common/chat-template.hpp
View file

@ -17,17 +17,26 @@ using json = nlohmann::ordered_json;
namespace minja {
struct chat_template_caps {
bool supports_tools = false;
bool supports_tool_calls = false;
bool supports_tool_responses = false;
bool supports_system_role = false;
bool supports_parallel_tool_calls = false;
bool supports_tool_call_id = false;
// meta-llama/Llama-3.1-8B-Instruct expects arguments to be an object.
// Most other templates (and OpenAI's API) expect the arguments object to be stringified.
bool requires_object_arguments = false;
// CohereForAI/c4ai-command-r-plus simple variant
bool requires_non_null_content = false;
// MiniMaxAI/MiniMax-Text-01 special
bool requires_typed_content = false;
};
class chat_template {
public:
private:
bool supports_tools_ = true;
// Meta-Llama-3.1-8B-Instruct's template expects arguments to be an object.
// Most other templates (and OpenAI's API) expect the arguments object to be stringified.
bool requires_object_arguments_ = false;
bool requires_typed_content_ = false;
bool supports_system_role_ = true;
bool supports_parallel_tool_calls_ = false;
chat_template_caps caps_;
std::string source_;
std::string bos_token_;
std::string eos_token_;
@ -41,15 +50,16 @@ class chat_template {
{
try {
auto prompt = apply(messages, tools, add_generation_prompt, extra_context, /* adjust_inputs= */ false);
// fprintf(stderr, "Prompt: %s\n", prompt.c_str());
// fprintf(stderr, "try_raw_render: %s\n", prompt.c_str());
return prompt;
} catch (const std::exception & e) {
// fprintf(stderr, "Error: %s\n", e.what());
// fprintf(stderr, "try_raw_render error: %s\n", e.what());
return "";
}
}
public:
chat_template(const std::string & source, const std::string & bos_token, const std::string & eos_token)
: source_(source), bos_token_(bos_token), eos_token_(eos_token)
{
@ -58,69 +68,120 @@ class chat_template {
/* .lstrip_blocks = */ true,
/* .keep_trailing_newline = */ false,
});
supports_tools_ = source.find("tools") != std::string::npos;
auto renders_string_arguments =
try_raw_render({
{
{"role", "user"},
{"content", "Hey"}
},
{
{"role", "assistant"},
{"tool_calls", json::array({
{
{"id", "call_1___"},
{"type", "function"},
{"function", {
{"arguments", "{\"code\": \"print('Hello, World!')\"}"},
{"name", "ipython"},
auto contains = [](const std::string & haystack, const std::string & needle) {
return haystack.find(needle) != std::string::npos;
};
const std::string user_needle = "<User Needle>";
const std::string sys_needle = "<System Needle>";
const json dummy_str_user_msg = {{"role", "user"}, {"content", user_needle}};
const json dummy_typed_user_msg = {{"role", "user"}, {"content", json::array({{{"type", "text"}, {"text", user_needle}}})}};
caps_.requires_typed_content =
!contains(try_raw_render(json::array({dummy_str_user_msg}), {}, false), user_needle)
&& contains(try_raw_render(json::array({dummy_typed_user_msg}), {}, false), user_needle);
const auto dummy_user_msg = caps_.requires_typed_content
? dummy_typed_user_msg
: dummy_str_user_msg;
const json needle_system_msg = {
{"role", "system"},
{"content", caps_.requires_typed_content ? json::array({{{"type", "text"}, {"text", sys_needle}}}) : json(sys_needle)},
};
caps_.supports_system_role = contains(try_raw_render({needle_system_msg, dummy_user_msg,}, {}, false), sys_needle);
auto out = try_raw_render(json::array({
dummy_user_msg
}), json::array({
{
{"name", "some_tool"},
{"type", "function"},
{"function", {
{"name", "some_tool"},
{"description", "Some tool."},
{"parameters", {
{"type", "object"},
{"properties", {
{"arg", {
{"type", "string"},
{"description", "Some argument."},
}},
},
})},
}},
{"required", json::array({ "arg" })},
}},
}},
},
}), false);
caps_.supports_tools = contains(out, "some_tool");
auto make_tool_calls_msg = [&](const json & tool_calls) {
return json {
{"role", "assistant"},
{"content", nullptr},
{"tool_calls", tool_calls},
};
};
auto make_tool_call = [](const std::string & tool_name, const json & arguments) {
return json {
{"id", "call_1___"},
{"type", "function"},
{"function", {
{"arguments", arguments},
{"name", tool_name},
}},
};
};
const json dummy_args_obj {{"argument_needle", "print('Hello, World!')"}};
// Note: the arguments are rendered in both cases, but may be double-escaped, which we don't want.
out = try_raw_render(json::array({
dummy_user_msg,
make_tool_calls_msg(json::array({make_tool_call("ipython", dummy_args_obj.dump())})),
}), {}, false);
auto tool_call_renders_str_arguments = contains(out, "\"argument_needle\":") || contains(out, "'argument_needle':");
out = try_raw_render(json::array({
dummy_user_msg,
make_tool_calls_msg(json::array({make_tool_call("ipython", dummy_args_obj)})),
}), {}, false);
auto tool_call_renders_obj_arguments = contains(out, "\"argument_needle\":") || contains(out, "'argument_needle':");
caps_.supports_tool_calls = tool_call_renders_str_arguments || tool_call_renders_obj_arguments;
caps_.requires_object_arguments = !tool_call_renders_str_arguments && tool_call_renders_obj_arguments;
auto out_empty = try_raw_render(json::array({dummy_user_msg, {{"role", "assistant"}, {"content", ""}}}), {}, false);
auto out_null = try_raw_render(json::array({dummy_user_msg, {{"role", "assistant"}, {"content", nullptr}}}), {}, false);
caps_.requires_non_null_content = contains(out_empty, user_needle) && !contains(out_null, user_needle);
if (caps_.supports_tool_calls) {
auto dummy_args = caps_.requires_object_arguments ? dummy_args_obj : json(dummy_args_obj.dump());
auto tc1 = make_tool_call("test_tool1", dummy_args);
auto tc2 = make_tool_call("test_tool2", dummy_args);
auto out = try_raw_render(json::array({
dummy_user_msg,
make_tool_calls_msg(json::array({tc1, tc2})),
}), {}, false);
caps_.supports_parallel_tool_calls = contains(out, "test_tool1") && contains(out, "test_tool2");
out = try_raw_render(json::array({
dummy_user_msg,
make_tool_calls_msg(json::array({tc1})),
{
{"role", "tool"},
{"name", "test_tool1"},
{"content", "Some response!"},
{"tool_call_id", "call_911_"},
}
}, {}, false).find("{\"code\": \"print") != std::string::npos;
if (!renders_string_arguments) {
auto renders_object_arguments =
try_raw_render({
{
{"role", "user"},
{"content", "Hey"}
},
{
{"role", "assistant"},
{"tool_calls", json::array({
{
{"id", "call_1___"},
{"type", "function"},
{"function", {
{"arguments", {
{"code", "print('Hello, World!')"},
}},
{"name", "ipython"},
}},
},
})},
}
}, {}, false).find("{\"code\": \"print") != std::string::npos;
requires_object_arguments_ = renders_object_arguments;
}), {}, false);
caps_.supports_tool_responses = contains(out, "Some response!");
caps_.supports_tool_call_id = contains(out, "call_911_");
}
supports_parallel_tool_calls_ = source.find("tool_call_id") != std::string::npos;
supports_system_role_ = try_raw_render({
{{"role", "system"}, {"content", "<System Needle>"}},
{{"role", "user"}, {"content", "Hey"}}
}, {}, false).find("<System Needle>") != std::string::npos;
requires_typed_content_ = try_raw_render({{{"role", "user"}, {"content", "Hey"}}}, {}, false).find("Hey") == std::string::npos
&& try_raw_render({{{"role", "user"}, {"content", {{{"type", "text"}, {"text", "Hey"}}}}}}, {}, false).find("Hey") != std::string::npos;
}
const std::string & source() const { return source_; }
const std::string & bos_token() const { return bos_token_; }
const std::string & eos_token() const { return eos_token_; }
bool supports_tools() const { return supports_tools_; }
bool supports_parallel_tool_calls() const { return supports_parallel_tool_calls_; }
const chat_template_caps & original_caps() const { return caps_; }
std::string apply(
const nlohmann::ordered_json & messages,
@ -131,13 +192,19 @@ class chat_template {
{
json actual_messages;
// First, "fix" messages so they have a chance to be rendered correctly by the template
if (adjust_inputs && (requires_object_arguments_ || !supports_system_role_ || !supports_tools_ || requires_typed_content_)) {
auto needs_adjustments = adjust_inputs && (false
|| !caps_.supports_system_role
|| !caps_.supports_tools
|| !caps_.supports_tool_responses
|| !caps_.supports_tool_calls
|| caps_.requires_object_arguments
|| caps_.requires_typed_content
);
if (needs_adjustments) {
actual_messages = json::array();
auto add_message = [&](const json & msg) {
if (requires_typed_content_ && msg.contains("content") && !msg.at("content").is_null() && msg.at("content").is_string()) {
if (caps_.requires_typed_content && msg.contains("content") && !msg.at("content").is_null() && msg.at("content").is_string()) {
actual_messages.push_back({
{"role", msg.at("role")},
{"content", {{
@ -160,7 +227,9 @@ class chat_template {
pending_system.clear();
}
};
for (const auto & message_ : messages) {
auto needs_tools_in_system = !tools.is_null() && tools.size() > 0 && !caps_.supports_tools;
for (const auto & message_ : needs_tools_in_system ? add_system(messages, "Available tools: " + tools.dump(2)) : messages) {
auto message = message_;
if (!message.contains("role") || !message.contains("content")) {
throw std::runtime_error("message must have 'role' and 'content' fields: " + message.dump());
@ -168,16 +237,22 @@ class chat_template {
std::string role = message.at("role");
if (message.contains("tool_calls")) {
if (requires_object_arguments_ || !supports_tools_) {
if (caps_.requires_object_arguments || !caps_.supports_tool_calls) {
for (auto & tool_call : message.at("tool_calls")) {
if (tool_call["type"] == "function") {
auto & function = tool_call.at("function");
std::string arguments = function.at("arguments");
function["arguments"] = json::parse(arguments);
auto & arguments = function.at("arguments");
if (arguments.is_string()) {
try {
arguments = json::parse(arguments.get<std::string>());
} catch (const std::exception & ecvt) {
fprintf(stderr, "Failed to parse arguments: %s\n", ecvt.what());
}
}
}
}
}
if (!supports_tools_) {
if (!caps_.supports_tool_calls) {
auto content = message.at("content");
auto tool_calls = json::array();
for (const auto & tool_call : message.at("tool_calls")) {
@ -204,14 +279,16 @@ class chat_template {
message.erase("tool_calls");
}
}
if (!supports_tools_ && role == "tool") {
if (!caps_.supports_tool_responses && role == "tool") {
message["role"] = "user";
auto obj = json {
{"tool_response", {
{"tool", message.at("name")},
{"content", message.at("content")},
}},
};
if (message.contains("name")) {
obj["tool_response"]["name"] = message.at("name");
}
if (message.contains("tool_call_id")) {
obj["tool_response"]["tool_call_id"] = message.at("tool_call_id");
}
@ -219,7 +296,7 @@ class chat_template {
message.erase("name");
}
if (!message["content"].is_null() && !supports_system_role_) {
if (!message["content"].is_null() && !caps_.supports_system_role) {
std::string content = message.at("content");
if (role == "system") {
if (!pending_system.empty()) pending_system += "\n";
@ -238,7 +315,9 @@ class chat_template {
}
add_message(message);
}
flush_sys();
if (!caps_.supports_system_role) {
flush_sys();
}
} else {
actual_messages = messages;
}
@ -261,7 +340,28 @@ class chat_template {
}
}
return template_root_->render(context);
auto ret = template_root_->render(context);
// fprintf(stderr, "actual_messages: %s\n", actual_messages.dump(2).c_str());
// fprintf(stderr, "apply: %s\n\n", ret.c_str());
return ret;
}
static nlohmann::ordered_json add_system(const nlohmann::ordered_json & messages, const std::string & system_prompt) {
json messages_with_system = messages;
if (messages_with_system.size() > 0 && messages_with_system[0].at("role") == "system") {
std::string existing_system = messages_with_system.at(0).at("content");
messages_with_system[0] = json {
{"role", "system"},
{"content", existing_system + "\n" + system_prompt},
};
} else {
messages_with_system.insert(messages_with_system.begin(), json {
{"role", "system"},
{"content", system_prompt},
});
}
return messages_with_system;
}
};

861
common/chat.cpp Normal file
View file

@ -0,0 +1,861 @@
#include "chat.hpp"
#include "chat-template.hpp"
#include "json-schema-to-grammar.h"
#include "log.h"
#include "minja.hpp"
std::string common_chat_format_name(common_chat_format format) {
switch (format) {
case COMMON_CHAT_FORMAT_CONTENT_ONLY: return "Content-only";
case COMMON_CHAT_FORMAT_GENERIC: return "Generic";
case COMMON_CHAT_FORMAT_MISTRAL_NEMO: return "Mistral Nemo";
case COMMON_CHAT_FORMAT_LLAMA_3_X: return "Llama 3.x";
case COMMON_CHAT_FORMAT_LLAMA_3_X_WITH_BUILTIN_TOOLS: return "Llama 3.x with builtin tools";
case COMMON_CHAT_FORMAT_DEEPSEEK_R1: return "DeepSeek R1";
case COMMON_CHAT_FORMAT_FIREFUNCTION_V2: return "FireFunction v2";
case COMMON_CHAT_FORMAT_FUNCTIONARY_V3_2: return "Functionary v3.2";
case COMMON_CHAT_FORMAT_FUNCTIONARY_V3_1_LLAMA_3_1: return "Functionary v3.1 Llama 3.1";
case COMMON_CHAT_FORMAT_HERMES_2_PRO: return "Hermes 2 Pro";
default:
throw std::runtime_error("Unknown chat format");
}
}
const common_grammar_options grammar_options {
/* .dotall = */ false,
/* .compact_spaces = */ false,
// /* .compact_spaces = */ true,
};
static bool parse_json(std::string::const_iterator & it, const std::string::const_iterator & end, json & out) {
// // https://json.nlohmann.me/features/parsing/sax_interface/
struct json_error_locator : public nlohmann::json_sax<json> {
std::size_t position;
bool found_error;
json_error_locator() : position(0), found_error(false) {}
bool parse_error(std::size_t position, const std::string &, const json::exception &) override {
this->position = position - 1;
this->found_error = true;
return false;
}
bool null() override { return true; }
bool boolean(bool) override { return true; }
bool number_integer(number_integer_t) override { return true; }
bool number_unsigned(number_unsigned_t) override { return true; }
bool number_float(number_float_t, const string_t &) override { return true; }
bool string(string_t &) override { return true; }
bool binary(binary_t &) override { return true; }
bool start_object(std::size_t) override { return true; }
bool key(string_t &) override { return true; }
bool end_object() override { return true; }
bool start_array(std::size_t) override { return true; }
bool end_array() override { return true; }
};
json_error_locator err_loc;
json::sax_parse(it, end, &err_loc);
std::string::const_iterator temptative_end;
if (err_loc.found_error) {
temptative_end = it + err_loc.position;
} else {
temptative_end = end;
}
std::string json_sub {it, temptative_end};
try {
out = json::parse(json_sub);
it = temptative_end;
return true;
} catch (const std::exception &) {
return false;
}
}
/**
* Takes a prefix regex that must have 1 group to capture the function name, a closing suffix, and expects json parameters in between.
* Aggregates the prefix, suffix and in-between text into the content.
*/
static common_chat_msg parse_json_tool_calls(
const std::string& input,
const std::optional<std::regex> & trigger_opt,
const std::regex & function_regex,
const std::regex & close_regex) {
std::smatch match;
common_chat_msg result;
result.role = "assistant";
auto end = input.end();
auto it = input.begin();
if (trigger_opt) {
if (!std::regex_search(it, end, match, *trigger_opt)) {
result.content = input;
return result;
}
result.content = match.prefix().str();
it = match.suffix().first;
}
while (it != end) {
std::sregex_iterator rend;
std::sregex_iterator rit(it, end, function_regex);
if (rit == rend) {
fprintf(stderr, "No more tool calls found\n");
result.content += std::string(it, end);
break;
}
auto name = rit->str(1);
result.content += std::string(it, rit->prefix().second);
it = rit->suffix().first;
json arguments;
if (!parse_json(it, end, arguments)) {
throw std::runtime_error("Failed to parse json tool call arguments");
}
if (!std::regex_search(it, end, match, close_regex)) {
throw std::runtime_error("Malformed input, missing closing pattern");
}
it = match.suffix().first;
result.tool_calls.push_back({name, arguments.is_string() ? arguments.get<std::string>() : arguments.dump(), /* id= */ ""});
}
return result;
}
static common_chat_msg parse_prefixed_json_tool_call_array(const std::string& input, const std::string & prefix, size_t rstrip_prefix = 0) {
auto content_end = input.find(prefix);
size_t tc_start = std::string::npos;
common_chat_msg result;
result.role = "assistant";
const auto process_tool_calls = [&](const json & tool_calls) {
for (const auto & tool_call : tool_calls) {
const auto & arguments = tool_call["arguments"];
result.tool_calls.push_back({
tool_call["name"],
arguments.is_string() ? arguments.get<std::string>() : arguments.dump(),
tool_call.contains("id") ? tool_call["id"] : "",
});
}
};
if (content_end == std::string::npos) {
result.content = input;
} else {
tc_start = content_end + prefix.size() - rstrip_prefix;
result.content = input.substr(0, content_end);
auto tool_calls = json::parse(input.substr(tc_start));
process_tool_calls(tool_calls);
}
return result;
}
static void foreach_function(const json & tools, const std::function<void(const json &)> & fn) {
for (const auto & tool : tools) {
if (!tool.contains("type") || tool["type"] != "function" || !tool.contains("function")) {
LOG_INF("Skipping tool without function: %s", tool.dump(2).c_str());
continue;
}
fn(tool);
}
}
static common_chat_params common_chat_params_init_generic(const common_chat_template & tmpl, const struct common_chat_inputs & inputs) {
common_chat_params data;
auto tool_call_schemas = json::array();
foreach_function(inputs.tools, [&](const json & tool) {
const auto & function = tool["function"];
auto tool_schema = json {
{"type", "object"},
{"properties", {
{"name", {
{"type", "string"},
{"const", function["name"]},
}},
{"arguments", function["parameters"]},
}},
{"required", json::array({"name", "arguments"})},
};
if (function.contains("description")) {
tool_schema["description"] = function["description"];
}
if (inputs.parallel_tool_calls) {
tool_schema["properties"]["id"] = {
{"type", "string"},
{"minLength", 4},
};
tool_schema["required"].push_back("id");
}
tool_call_schemas.emplace_back(tool_schema);
});
const auto tool_call =
inputs.parallel_tool_calls
? json {
{"type", "object"},
{"properties", {
{"tool_calls", {
{"type", "array"},
{"items", tool_call_schemas.size() == 1 ? tool_call_schemas[0] : json {
{"anyOf", tool_call_schemas},
}},
{"minItems", 1},
}},
}},
{"required", json::array({"tool_calls"})},
}
: json {
{"type", "object"},
{"properties", {
{"tool_call", tool_call_schemas.size() == 1 ? tool_call_schemas[0] : json {
{"anyOf", tool_call_schemas},
}},
}},
{"required", json::array({"tool_call"})},
};
const auto schema =
inputs.tool_choice != "required"
? json {
{"anyOf", json::array({
tool_call,
{
{"type", "object"},
{"properties", {
{"response", inputs.json_schema.is_null()
? json {{"type", "string"}}
: inputs.json_schema
},
}},
{"required", json::array({"response"})},
},
})}
}
: tool_call;
data.grammar_lazy = false;
data.grammar = build_grammar([&](const common_grammar_builder & builder) {
builder.add_schema("root", schema);
}, grammar_options);
auto tweaked_messages = common_chat_template::add_system(
inputs.messages,
"Respond in JSON format, either with `tool_call` (a request to call tools) or with `response` reply to the user's request");
data.prompt = tmpl.apply(tweaked_messages, inputs.tools.empty() ? json() : inputs.tools, inputs.add_generation_prompt);
data.format = COMMON_CHAT_FORMAT_GENERIC;
return data;
}
static common_chat_msg common_chat_parse_generic(const std::string & input) {
json data = json::parse(input);
common_chat_msg result;
result.role = "assistant";
if (data.contains("tool_calls")) {
for (const auto & tool_call : data["tool_calls"]) {
result.tool_calls.push_back({
tool_call["name"],
tool_call["arguments"].dump(),
tool_call.contains("id") ? tool_call["id"] : "",
});
}
} else if (data.contains("tool_call")) {
result.tool_calls.push_back({
data["tool_call"]["name"],
data["tool_call"]["arguments"].dump(),
/* id= */ "",
});
} else if (data.contains("response")) {
const auto & response = data["response"];
result.content = response.is_string() ? response.get<std::string>() : response.dump(2);
}
return result;
}
static common_chat_params common_chat_params_init_mistral_nemo(const common_chat_template & tmpl, const struct common_chat_inputs & inputs) {
common_chat_params data;
data.grammar_lazy = inputs.tool_choice != "required";
data.grammar = build_grammar([&](const common_grammar_builder & builder) {
auto schemas = json::array();
foreach_function(inputs.tools, [&](const json & tool) {
const auto & function = tool["function"];
schemas.push_back({
{"type", "object"},
{"properties", {
// Important note: the model is probably trained to take a JSON stringified arguments value.
// It's hard to constrain that for now (while reusing the JSON schema conversion), so we're just expecting a plain object.
{"name", {
{"type", "string"},
{"const", function["name"]},
}},
{"arguments", function["parameters"]},
{"id", {
{"type", "string"},
// Nemo's template expects a 9-character alphanumeric ID.
{"pattern", "^[a-zA-Z0-9]{9}$"},
}},
}},
{"required", json::array({"name", "arguments", "id"})},
});
});
auto schema = json {
{"type", "array"},
{"items", schemas.size() == 1 ? schemas[0] : json {{"anyOf", schemas}}},
{"minItems", 1},
};
if (!inputs.parallel_tool_calls) {
schema["maxItems"] = 1;
}
builder.add_rule("root", "\"[TOOL_CALLS]\" " + builder.add_schema("tool_calls", schema));
}, grammar_options);
data.grammar_triggers.push_back({"[TOOL_CALLS]", /* .at_start = */ true});
data.prompt = tmpl.apply(inputs.messages, inputs.tools.empty() ? json() : inputs.tools, inputs.add_generation_prompt);
data.format = COMMON_CHAT_FORMAT_MISTRAL_NEMO;
return data;
}
static common_chat_msg common_chat_parse_mistral_nemo(const std::string & input) {
return parse_prefixed_json_tool_call_array(input, "[TOOL_CALLS]");
}
static void expect_tool_parameters(const std::string & name, const json & parameters, const std::vector<std::string> & expected_properties) {
if (!parameters.is_object() || !parameters.contains("type") || parameters["type"] != "object" || !parameters.contains("properties") || !parameters.contains("required")) {
throw std::runtime_error("Parameters of tool " + name + " must be an object w/ required properties");
}
const auto & parameters_properties = parameters.at("properties");
const auto & parameters_required = parameters.at("required");
for (const auto & prop : expected_properties) {
if (!parameters_properties.contains(prop)) {
throw std::runtime_error("Parameters of tool " + name + " is missing property: " + prop);
}
if (std::find(parameters_required.begin(), parameters_required.end(), json(prop)) == parameters_required.end()) {
throw std::runtime_error("Parameters of tool " + name + " must have property marked as required: " + prop);
}
}
if (parameters_properties.size() != expected_properties.size()) {
throw std::runtime_error("Parameters of tool " + name + " must only have these properties:" + string_join(expected_properties, ", "));
}
}
static common_chat_params common_chat_params_init_llama_3_1_tool_calls(const common_chat_template & tmpl, const struct common_chat_inputs & inputs, bool allow_python_tag_builtin_tools) {
auto builtin_tools = json::array();
common_chat_params data;
data.grammar_lazy = inputs.tool_choice != "required";
data.grammar = build_grammar([&](const common_grammar_builder & builder) {
std::vector<std::string> tool_rules;
auto handle_builtin_tool = [&](const std::string & name, const json & parameters) {
if (name == "wolfram_alpha") {
// https://github.com/meta-llama/llama-stack/blob/main/llama_stack/providers/remote/tool_runtime/wolfram_alpha/wolfram_alpha.py
expect_tool_parameters(name, parameters, {"query"});
} else if (name == "web_search" || name == "brave_search") {
// https://github.com/meta-llama/llama-stack/blob/main/llama_stack/providers/remote/tool_runtime/brave_search/brave_search.py
expect_tool_parameters(name, parameters, {"query"});
} else if (name == "python" || name == "code_interpreter") {
// https://github.com/meta-llama/llama-stack/blob/main/llama_stack/providers/inline/tool_runtime/code_interpreter/code_interpreter.py
expect_tool_parameters(name, parameters, {"code"});
} else {
return false;
}
std::vector<std::string> kvs;
for (const auto & [key, value] : parameters.at("properties").items()) {
kvs.push_back("\"" + key + "=\" " + builder.add_schema(name + "-args-" + key, value));
}
tool_rules.push_back(
builder.add_rule(
name + "-call",
"\"<|python_tag|>" + name + ".call(\" " + string_join(kvs, " \", \" ") + " \")\""));
builtin_tools.push_back(name);
return true;
};
foreach_function(inputs.tools, [&](const json & tool) {
const auto & function = tool["function"];
std::string name = function["name"];
auto parameters = function["parameters"];
builder.resolve_refs(parameters);
// https://github.com/meta-llama/llama-stack/tree/main/llama_stack/providers/remote/tool_runtime
if (allow_python_tag_builtin_tools) {
handle_builtin_tool(name, parameters);
}
tool_rules.push_back(
builder.add_rule(
name + "-call",
"\"{\" space "
"( \"\\\"type\\\":\" space \"\\\"function\\\",\" space )? "
"\"\\\"name\\\": \\\"" + name + "\\\", \\\"parameters\\\": \" " +
builder.add_schema(name + "-args", parameters) +
" \"}\""));
data.grammar_triggers.push_back({"{\"name\": \"" + name + "\"", /* .at_start = */ true});
});
data.grammar_triggers.push_back({"{\"name\":", /* .at_start = */ true});
data.grammar_triggers.push_back({"{\n \"name\":", /* .at_start = */ true});
data.grammar_triggers.push_back({"{\n \"name\":", /* .at_start = */ true});
data.grammar_triggers.push_back({"{\"type\": \"function\"", /* .at_start = */ true});
data.grammar_triggers.push_back({"{\n \"type\": \"function\"", /* .at_start = */ true});
data.grammar_triggers.push_back({"{\n \"type\": \"function\"", /* .at_start = */ true});
if (!builtin_tools.empty()) {
data.grammar_triggers.push_back({"<|python_tag|>", /* .at_start = */ false});
}
builder.add_rule("root", string_join(tool_rules, " | "));
}, grammar_options);
data.additional_stops.push_back("<|eom_id|>");
data.prompt = tmpl.apply(inputs.messages, inputs.tools.empty() ? json() : inputs.tools, inputs.add_generation_prompt, {
{"tools_in_user_message", false},
{"builtin_tools", builtin_tools.empty() ? json() : builtin_tools},
});
data.format = allow_python_tag_builtin_tools && !builtin_tools.empty()
? COMMON_CHAT_FORMAT_LLAMA_3_X_WITH_BUILTIN_TOOLS
: COMMON_CHAT_FORMAT_LLAMA_3_X;
return data;
}
static common_chat_msg common_chat_parse_llama_3_1(const std::string & input, bool with_builtin_tools = false) {
// TODO: tighten & simplify the parser, don't accept leading text context.
static std::regex function_regex("\\{[\\s\\n\\r]*(?:\"type\"[\\s\\n\\r]*:[\\s\\n\\r]*\"function\"[\\s\\n\\r]*,[\\s\\n\\r]*|[\\s\\n\\r]*)\"name\"[\\s\\n\\r]*:[\\s\\n\\r]*\"([^\"]+)\"[\\s\\n\\r]*,[\\s\\n\\r]*\"parameters\": ");
static std::regex close_regex("\\}");
static std::regex builtin_call_regex("<\\|python_tag\\|>([^.(]+)\\.call\\((.*)\\)");
if (with_builtin_tools) {
std::smatch match;
if (std::regex_match(input, match, builtin_call_regex)) {
auto name = match[1].str();
auto raw_args = match[2].str();
// TODO: if/when builtin tools start accepting more than 1 argument, use parse_json for real parsing.
auto it_eq = raw_args.find('=');
auto arg_name = raw_args.substr(0, it_eq);
auto arg_value_str = raw_args.substr(it_eq + 1);
auto arg_value = json::parse(arg_value_str);
return {
/* .role = */ "assistant",
/* .content = */ match.prefix().str(),
/* .tool_calls = */ {
{
/* .name = */ match[1],
/* .arguments = */ (json {
{arg_name, arg_value},
}).dump(),
/* .id = */ "",
},
},
};
}
}
return parse_json_tool_calls(input, std::nullopt, function_regex, close_regex);
}
static common_chat_params common_chat_params_init_deepseek_r1(const common_chat_template & tmpl, const struct common_chat_inputs & inputs) {
common_chat_params data;
data.grammar_lazy = inputs.tool_choice != "required";
data.grammar = build_grammar([&](const common_grammar_builder & builder) {
std::vector<std::string> tool_rules;
foreach_function(inputs.tools, [&](const json & tool) {
const auto & function = tool["function"];
std::string name = function["name"];
auto parameters = function["parameters"];
auto args_rule = builder.add_schema(name + "-args", parameters);
tool_rules.push_back(builder.add_rule(name + "-call",
"\"<｜tool▁call▁begin｜>function<｜tool▁sep｜>" + name + "\\n```json\\n\" " + args_rule + " \"```<｜tool▁call▁end｜>\""));
});
data.grammar_triggers.push_back({"<｜tool▁calls▁begin｜>", /* .at_start = */ false});
builder.add_rule("root", "\"<｜tool▁calls▁begin｜>\" (" + string_join(tool_rules, " | ") + ")" + (inputs.parallel_tool_calls ? "*" : "") + " space");
}, grammar_options);
data.prompt = tmpl.apply(inputs.messages, inputs.tools.empty() ? json() : inputs.tools, inputs.add_generation_prompt);
data.format = COMMON_CHAT_FORMAT_DEEPSEEK_R1;
return data;
}
static common_chat_msg common_chat_parse_deepseek_r1(const std::string & input) {
static std::regex trigger_regex("<｜tool▁calls▁begin｜>");
static std::regex function_regex("<｜tool▁call▁begin｜>function<｜tool▁sep｜>([^\n]+)\n```json\n");
static std::regex close_regex("```<｜tool▁call▁end｜>");
return parse_json_tool_calls(input, trigger_regex, function_regex, close_regex);
}
static common_chat_params common_chat_params_init_firefunction_v2(const common_chat_template & tmpl, const struct common_chat_inputs & inputs) {
fprintf(stderr, "%s\n", __func__);
common_chat_params data;
data.prompt = tmpl.apply(inputs.messages, /* tools= */ nullptr, inputs.add_generation_prompt, {
{"datetime", "Jan 29 2025 13:00:00 GMT"},
{"functions", json(inputs.tools.empty() ? "" : inputs.tools.dump(2))},
}, /* adjust_inputs= */ false);
if (!inputs.tools.is_null() && !inputs.tools.empty()) {
data.grammar_lazy = inputs.tool_choice != "required";
data.grammar = build_grammar([&](const common_grammar_builder & builder) {
auto schemas = json::array();
foreach_function(inputs.tools, [&](const json & tool) {
const auto & function = tool["function"];
schemas.push_back({
{"type", "object"},
{"properties", {
{"name", {
{"type", "string"},
{"const", function["name"]},
}},
{"arguments", function["parameters"]},
}},
{"required", json::array({"name", "arguments", "id"})},
});
});
auto schema = json {
{"type", "array"},
{"items", schemas.size() == 1 ? schemas[0] : json {{"anyOf", schemas}}},
{"minItems", 1},
};
if (!inputs.parallel_tool_calls) {
schema["maxItems"] = 1;
}
builder.add_rule("root", "\" functools\"? " + builder.add_schema("tool_calls", schema));
}, grammar_options);
data.grammar_triggers.push_back({" functools[", /* .at_start = */ false});
data.format = COMMON_CHAT_FORMAT_FIREFUNCTION_V2;
} else {
data.format = COMMON_CHAT_FORMAT_CONTENT_ONLY;
}
return data;
}
static common_chat_msg common_chat_parse_firefunction_v2(const std::string & input) {
return parse_prefixed_json_tool_call_array(input, " functools[", /* rstrip_prefix= */ 1);
}
static common_chat_params common_chat_params_init_functionary_v3_2(const common_chat_template & tmpl, const struct common_chat_inputs & inputs) {
// >>>all\nlet's call functions>>>fn1\n{"arg1": 1...}\n>>>fn2\n{"arg1": 1...}...
// Using ">>>f1\n", ">>>f2\n"... as trigger words for the grammar
common_chat_params data;
data.prompt = tmpl.apply(inputs.messages, inputs.tools.empty() ? json() : inputs.tools, inputs.add_generation_prompt);
data.format = COMMON_CHAT_FORMAT_FUNCTIONARY_V3_2;
if (!inputs.tools.is_null() && !inputs.tools.empty()) {
data.grammar_lazy = inputs.tool_choice != "required";
data.grammar = build_grammar([&](const common_grammar_builder & builder) {
std::vector<std::string> first_tool_rules;
std::vector<std::string> subsequent_tool_rules;
foreach_function(inputs.tools, [&](const json & tool) {
const auto & function = tool["function"];
std::string name = function["name"];
auto parameters = function["parameters"];
auto args_rule = builder.add_schema(name + "-args", parameters);
first_tool_rules.push_back(builder.add_rule(name + "-call", "\"" + name + "\\n\" " + args_rule));
subsequent_tool_rules.push_back(builder.add_rule(name + "-call2", "\">>>" + name + "\\n\" " + args_rule));
data.grammar_triggers.push_back({name, /* .at_start = */ true});
data.grammar_triggers.push_back({">>>" + name, /* .at_start = */ false});
});
auto first_rule = first_tool_rules.empty() ? "" : builder.add_rule("first_tool_call", string_join(first_tool_rules, " | ")) + " space";
if (inputs.parallel_tool_calls) {
auto subsequent_rule = builder.add_rule("subsequent_tool_call", string_join(subsequent_tool_rules, " | ")) + " space";
builder.add_rule("root", first_rule + " (" + subsequent_rule + ")*");
} else {
builder.add_rule("root", first_rule);
}
}, grammar_options);
}
return data;
}
static bool consume(std::string::const_iterator & it, const std::string::const_iterator & end, const std::string & expected) {
auto expected_it = expected.begin();
auto tmp_it = it;
while (tmp_it != end && expected_it != expected.end() && *tmp_it == *expected_it) {
++tmp_it;
++expected_it;
}
if (expected_it == expected.end()) {
it = tmp_it;
return true;
}
return false;
}
static common_chat_msg common_chat_parse_functionary_v3_2(const std::string & input) {
static std::regex function_regex(R"((?:>>>)?(\w+)\n)");
static std::regex close_regex(R"($|(?=>>>))");
std::string content;
auto it = input.begin();
const auto end = input.end();
if (consume(it, end, "all\n")) {
std::smatch match;
if (std::regex_search(it, end, match, function_regex)) {
auto fun_it = match.prefix().second;
content = std::string(it, fun_it);
it = fun_it;
} else {
common_chat_msg res;
res.role = "assistant";
res.content = std::string(it, end);
return res;
}
}
// TODO: tighten & simplify.
try {
auto res = parse_json_tool_calls(std::string(it, end), std::nullopt, function_regex, close_regex);
res.content = content + res.content;
return res;
} catch (const std::exception & e) {
LOG_ERR("Failed to parse functionary v3.2 input: %s\n", e.what());
common_chat_msg res;
res.role = "assistant";
res.content = input;
return res;
}
}
static common_chat_params common_chat_params_init_functionary_v3_1_llama_3_1(const common_chat_template & tmpl, const struct common_chat_inputs & inputs) {
// https://github.com/MeetKai/functionary/blob/main/tests/prompt_test_v3-llama3.1.txt
common_chat_params data;
json tools = inputs.tools.is_null() ? inputs.tools : json::array();
std::string python_code_argument_name;
auto has_raw_python = false;
data.grammar_lazy = inputs.tool_choice != "required";
data.grammar = build_grammar([&](const common_grammar_builder & builder) {
std::vector<std::string> tool_rules;
foreach_function(inputs.tools, [&](const json & tool) {
const auto & function = tool["function"];
const auto & parameters = function["parameters"];
std::string name = function["name"];
if (name == "python" || name == "ipython") {
if (!parameters.contains("type")) {
throw std::runtime_error("Missing type in python tool");
}
has_raw_python = true;
auto type = parameters.at("type");
if (type == "object") {
auto properties = parameters.at("properties");
for (auto it = properties.begin(); it != properties.end(); ++it) {
if (it.value().at("type") == "string") {
if (!python_code_argument_name.empty()) {
throw std::runtime_error("Multiple string arguments found in python tool");
}
python_code_argument_name = it.key();
}
}
if (python_code_argument_name.empty()) {
throw std::runtime_error("No string argument found in python tool");
}
} else if (type != "string") {
throw std::runtime_error("Invalid type in python tool: " + type.dump());
}
}
tool_rules.push_back(builder.add_rule(name + "-call", "\"<function=" + name + ">\" " + builder.add_schema(name + "-args", parameters) + " \"</function>\" space"));
});
if (has_raw_python) {
tool_rules.push_back(builder.add_rule("python-call", "\"<|python_tag|>\" .*"));
data.grammar_triggers.push_back({"<|python_tag|>", /* .at_start = */ false});
}
auto tool_call = builder.add_rule("tool_call", string_join(tool_rules, " | ")) + " space";
builder.add_rule("root", inputs.parallel_tool_calls ? "(" + tool_call + ")+" : tool_call);
data.grammar_triggers.push_back({"<function=", /* .at_start = */ false});
}, grammar_options);
data.prompt = tmpl.apply(inputs.messages, inputs.tools.empty() ? json() : inputs.tools, inputs.add_generation_prompt);
// TODO: if (has_raw_python)
data.format = COMMON_CHAT_FORMAT_FUNCTIONARY_V3_1_LLAMA_3_1;
return data;
}
static common_chat_msg common_chat_parse_functionary_v3_1_llama_3_1(const std::string & input) {
// This version of Functionary still supports the llama 3.1 tool call format for the python tool.
static std::regex python_tag_regex(R"(<\|python_tag\|>([\s\S\n]*)$)");
std::smatch match;
if (std::regex_search(input, match, python_tag_regex)) {
auto code = match[1].str();
return {
/* .role = */ "assistant",
/* .content = */ match.prefix().str(),
/* .tool_calls = */ {
{
/* .name = */ "python",
/* .arguments = */ (json {{"code", code}}).dump(),
/* .id = */ "",
},
}
};
}
static std::regex function_regex(R"(<function=(\w+)>)");
static std::regex close_regex(R"(</function>)");
// TODO: tighten & simplify.
return parse_json_tool_calls(input, std::nullopt, function_regex, close_regex);
}
static common_chat_params common_chat_params_init_hermes_2_pro(const common_chat_template & tmpl, const struct common_chat_inputs & inputs) {
common_chat_params data;
// (content)?(<tool_call>{"name": "foo", "arguments": {"a": 1}}</tool_call>)*
data.grammar_lazy = inputs.tool_choice != "required";
data.grammar = build_grammar([&](const common_grammar_builder & builder) {
std::vector<std::string> tool_rules;
foreach_function(inputs.tools, [&](const json & tool) {
const auto & function = tool["function"];
std::string name = function["name"];
auto parameters = function["parameters"];
builder.resolve_refs(parameters);
tool_rules.push_back(builder.add_schema(name + "-call", {
{"type", "object"},
{"properties", json {
{"name", json {{"const", name}}},
{"arguments", parameters},
}},
{"required", json::array({"name", "arguments"})},
}));
});
auto tool_call = "\"<tool_call>\" space " + builder.add_rule("tool_call", string_join(tool_rules, " | ")) + " \"</tool_call>\" space";
builder.add_rule("root", inputs.parallel_tool_calls ? "(" + tool_call + ")+" : tool_call);
data.grammar_triggers.push_back({"<tool_call>", /* .at_start = */ false});
// Not really a trigger but need to print this special token to get a successful parse.
data.grammar_triggers.push_back({"</tool_call>", /* .at_start = */ false});
}, grammar_options);
data.prompt = tmpl.apply(inputs.messages, inputs.tools.empty() ? json() : inputs.tools, inputs.add_generation_prompt);
data.format = COMMON_CHAT_FORMAT_HERMES_2_PRO;
return data;
}
static common_chat_msg common_chat_parse_hermes_2_pro(const std::string & input) {
try {
std::regex start_pattern(R"([\n\s]*<tool_call>)");
std::regex middle_pattern(R"([\n\s]*</tool_call>[\n\s]*<tool_call>)");
std::regex end_pattern(R"([\n\s]*</tool_call>[\n\s]*$)");
auto end = input.end();
std::sregex_iterator rend;
std::sregex_iterator rit(input.begin(), end, start_pattern);
if (rit == rend) {
return {
/* .role = */ "assistant",
/* .content = */ input,
/* .tool_calls = */ {},
};
}
common_chat_msg result;
result.role = "assistant";
result.content = rit->prefix();
auto it = rit->suffix().first;
while (it != end) {
json call;
if (!parse_json(it, end, call)) {
throw std::runtime_error("Failed to parse json tool call");
}
const auto & arguments = call["arguments"];
result.tool_calls.push_back({
call["name"],
arguments.dump(),
// arguments.is_string() ? arguments.get<std::string>() : arguments.dump(),
/* id= */ "",
});
rit = {it, end, middle_pattern};
if (rit != rend) {
it = rit->suffix().first;
} else {
rit = {it, end, end_pattern};
if (rit == rend) {
throw std::runtime_error("Malformed input, missing </tool_call>");
}
break;
}
}
return result;
} catch (const std::exception & e) {
return {
/* .role = */ "assistant",
/* .content = */ input,
/* .tool_calls = */ {},
};
}
}
static common_chat_params common_chat_params_init_without_tools(const common_chat_template & tmpl, const struct common_chat_inputs & inputs) {
common_chat_params data;
data.prompt = tmpl.apply(inputs.messages, inputs.tools.empty() ? json() : inputs.tools, inputs.add_generation_prompt);
data.format = COMMON_CHAT_FORMAT_CONTENT_ONLY;
data.grammar_lazy = false;
if (!inputs.json_schema.is_null()) {
if (!inputs.grammar.empty()) {
throw std::runtime_error("Either \"json_schema\" or \"grammar\" can be specified, but not both");
}
data.grammar = json_schema_to_grammar(inputs.json_schema);
} else {
data.grammar = inputs.grammar.empty();
}
return data;
}
common_chat_params common_chat_params_init(const common_chat_template & tmpl, const struct common_chat_inputs & inputs) {
auto has_tools = !inputs.tools.is_null() && inputs.tool_choice != "none";
LOG_DBG("[%s] has_tools=%s\n", __func__, has_tools ? "true" : "false");
if (has_tools && !inputs.grammar.empty()) {
throw std::runtime_error("Cannot specify grammar with tools");
}
const auto & src = tmpl.source();
if (src.find(">>>all") != std::string::npos) {
// Functionary prepends "all\n" to plain content outputs, so we use the parser no matter when
return common_chat_params_init_functionary_v3_2(tmpl, inputs);
}
if (src.find(" functools[") != std::string::npos) {
// Firefunction v2 requires datetime and functions in the context, even w/o tools.
return common_chat_params_init_firefunction_v2(tmpl, inputs);
}
if (!has_tools) {
return common_chat_params_init_without_tools(tmpl, inputs);
}
if (src.find("<tool_call>") != std::string::npos) {
return common_chat_params_init_hermes_2_pro(tmpl, inputs);
}
if (src.find("<|start_header_id|>") != std::string::npos
&& src.find("<function=") != std::string::npos) {
return common_chat_params_init_functionary_v3_1_llama_3_1(tmpl, inputs);
}
if (src.find("<|start_header_id|>ipython<|end_header_id|>") != std::string::npos) {
auto allow_python_tag_builtin_tools = src.find("<|python_tag|>") != std::string::npos;
return common_chat_params_init_llama_3_1_tool_calls(tmpl, inputs, allow_python_tag_builtin_tools);
}
if (src.find("<｜tool▁calls▁begin｜>") != std::string::npos) {
return common_chat_params_init_deepseek_r1(tmpl, inputs);
}
if (src.find("[TOOL_CALLS]") != std::string::npos) {
return common_chat_params_init_mistral_nemo(tmpl, inputs);
}
return common_chat_params_init_generic(tmpl, inputs);
}
static common_chat_msg common_chat_parse_content_only(const std::string & input) {
return {
/* .role = */ "assistant",
/* .content = */ input,
/* .tool_calls = */ {},
};
}
common_chat_msg common_chat_parse(const std::string & input, common_chat_format format) {
switch (format) {
case COMMON_CHAT_FORMAT_CONTENT_ONLY:
return common_chat_parse_content_only(input);
case COMMON_CHAT_FORMAT_GENERIC:
return common_chat_parse_generic(input);
case COMMON_CHAT_FORMAT_MISTRAL_NEMO:
return common_chat_parse_mistral_nemo(input);
case COMMON_CHAT_FORMAT_LLAMA_3_X:
return common_chat_parse_llama_3_1(input);
case COMMON_CHAT_FORMAT_LLAMA_3_X_WITH_BUILTIN_TOOLS:
return common_chat_parse_llama_3_1(input, /* with_builtin_tools= */ true);
case COMMON_CHAT_FORMAT_DEEPSEEK_R1:
return common_chat_parse_deepseek_r1(input);
case COMMON_CHAT_FORMAT_FUNCTIONARY_V3_2:
return common_chat_parse_functionary_v3_2(input);
case COMMON_CHAT_FORMAT_FUNCTIONARY_V3_1_LLAMA_3_1:
return common_chat_parse_functionary_v3_1_llama_3_1(input);
case COMMON_CHAT_FORMAT_HERMES_2_PRO:
return common_chat_parse_hermes_2_pro(input);
case COMMON_CHAT_FORMAT_FIREFUNCTION_V2:
return common_chat_parse_firefunction_v2(input);
default:
throw std::runtime_error("Unsupported format: " + common_chat_format_name(format));
}
}

50
common/chat.hpp Normal file
View file

@ -0,0 +1,50 @@
// Chat support (incl. tool call grammar constraining & output parsing) w/ generic & custom template handlers.
#pragma once
#include "common.h"
#include <json.hpp>
#include <optional>
#include <string>
#include <vector>
using json = nlohmann::ordered_json;
struct common_chat_inputs {
json messages;
json tools;
json tool_choice;
json json_schema;
bool parallel_tool_calls;
bool stream;
std::string grammar;
bool add_generation_prompt = true;
};
enum common_chat_format {
COMMON_CHAT_FORMAT_CONTENT_ONLY,
COMMON_CHAT_FORMAT_GENERIC,
COMMON_CHAT_FORMAT_MISTRAL_NEMO,
COMMON_CHAT_FORMAT_LLAMA_3_X,
COMMON_CHAT_FORMAT_LLAMA_3_X_WITH_BUILTIN_TOOLS,
COMMON_CHAT_FORMAT_DEEPSEEK_R1,
COMMON_CHAT_FORMAT_FIREFUNCTION_V2,
COMMON_CHAT_FORMAT_FUNCTIONARY_V3_2,
COMMON_CHAT_FORMAT_FUNCTIONARY_V3_1_LLAMA_3_1,
COMMON_CHAT_FORMAT_HERMES_2_PRO,
COMMON_CHAT_FORMAT_COUNT, // Not a format, just the # formats
};
struct common_chat_params {
common_chat_format format = COMMON_CHAT_FORMAT_CONTENT_ONLY;
json prompt;
std::string grammar;
bool grammar_lazy = false;
std::vector<common_grammar_trigger> grammar_triggers;
std::vector<std::string> additional_stops;
};
struct common_chat_params common_chat_params_init(const common_chat_template & tmpl, const struct common_chat_inputs & params);
std::string common_chat_format_name(common_chat_format format);
common_chat_msg common_chat_parse( const std::string & input, common_chat_format format);

22
common/common.cpp
View file

@ -12,6 +12,7 @@
#include "json.hpp"
#include "json-schema-to-grammar.h"
#include "llama.h"
#include "chat.hpp"
#include "chat-template.hpp"
#include <algorithm>
@ -1774,11 +1775,13 @@ std::string common_detokenize(const struct llama_vocab * vocab, const std::vecto
bool common_chat_verify_template(const std::string & tmpl, bool use_jinja) {
if (use_jinja) {
try {
auto chat_template = minja::chat_template(tmpl, "<s>", "</s>");
chat_template.apply({{
auto chat_template = common_chat_template(tmpl, "<s>", "</s>");
common_chat_inputs inputs;
inputs.messages = json::array({{
{"role", "user"},
{"content", "test"},
}}, json(), true);
}});
common_chat_params_init(chat_template, inputs);
return true;
} catch (const std::exception & e) {
LOG_ERR("%s: failed to apply template: %s\n", __func__, e.what());
@ -1800,7 +1803,10 @@ std::string common_chat_apply_template(
for (const auto & msg : msgs) {
messages.push_back({{"role", msg.role}, {"content", msg.content}});
}
return tmpl.apply(messages, /* tools= */ json(), add_ass);
common_chat_inputs inputs;
inputs.messages = messages;
inputs.add_generation_prompt = add_ass;
return common_chat_params_init(tmpl, inputs).prompt;
}
int alloc_size = 0;
@ -1855,10 +1861,10 @@ std::string common_chat_format_single(
std::string common_chat_format_example(const common_chat_template & tmpl, bool use_jinja) {
std::vector<common_chat_msg> msgs = {
{"system", "You are a helpful assistant"},
{"user", "Hello"},
{"assistant", "Hi there"},
{"user", "How are you?"},
{"system", "You are a helpful assistant", {}},
{"user", "Hello", {}},
{"assistant", "Hi there", {}},
{"user", "How are you?", {}},
};
return common_chat_apply_template(tmpl, msgs, true, use_jinja);
}

17
common/common.h
View file

@ -109,6 +109,11 @@ enum common_conversation_mode {
COMMON_CONVERSATION_MODE_AUTO = 2,
};
struct common_grammar_trigger {
std::string word;
bool at_start;
};
// sampling parameters
struct common_params_sampling {
uint32_t seed = LLAMA_DEFAULT_SEED; // the seed used to initialize llama_sampler
@ -154,7 +159,10 @@ struct common_params_sampling {
COMMON_SAMPLER_TYPE_TEMPERATURE,
};
std::string grammar; // optional BNF-like grammar to constrain sampling
std::string grammar; // optional BNF-like grammar to constrain sampling
bool grammar_lazy = false;
std::vector<common_grammar_trigger> grammar_trigger_words; // optional trigger words to trigger lazy grammar
std::vector<llama_token> grammar_trigger_tokens; // optional trigger tokens to trigger lazy grammar and print trigger special tokens.
std::vector<llama_logit_bias> logit_bias; // logit biases to apply
@ -602,10 +610,17 @@ std::string common_detokenize(
// Chat template utils
//
struct common_tool_call {
std::string name;
std::string arguments;
std::string id;
};
// same with llama_chat_message, but uses std::string
struct common_chat_msg {
std::string role;
std::string content;
std::vector<common_tool_call> tool_calls;
};
// Check if the template supplied via "--chat-template" is supported or not. Returns true if it's valid

15
common/json-schema-to-grammar.cpp
View file

@ -343,7 +343,7 @@ static std::string format_literal(const std::string & literal) {
class SchemaConverter {
private:
friend std::string build_grammar(const std::function<void(const llama_grammar_builder &)> & cb);
friend std::string build_grammar(const std::function<void(const common_grammar_builder &)> & cb, const common_grammar_options & options);
std::function<json(const std::string &)> _fetch_json;
bool _dotall;
std::map<std::string, std::string> _rules;
@ -764,10 +764,11 @@ private:
public:
SchemaConverter(
const std::function<json(const std::string &)> & fetch_json,
bool dotall)
bool dotall,
bool compact_spaces)
: _fetch_json(fetch_json), _dotall(dotall)
{
_rules["space"] = SPACE_RULE;
_rules["space"] = compact_spaces ? "\" \"?" : SPACE_RULE;
}
void resolve_refs(json & schema, const std::string & url) {
@ -998,16 +999,16 @@ std::string json_schema_to_grammar(const json & schema, bool force_gbnf) {
#else
(void)force_gbnf;
#endif // LLAMA_USE_LLGUIDANCE
return build_grammar([&](const llama_grammar_builder & callbacks) {
return build_grammar([&](const common_grammar_builder & callbacks) {
auto copy = schema;
callbacks.resolve_refs(copy);
callbacks.add_schema("", copy);
});
}
std::string build_grammar(const std::function<void(const llama_grammar_builder &)> & cb) {
SchemaConverter converter([&](const std::string &) { return json(); }, /* dotall= */ false);
llama_grammar_builder builder {
std::string build_grammar(const std::function<void(const common_grammar_builder &)> & cb, const common_grammar_options & options) {
SchemaConverter converter([&](const std::string &) { return json(); }, options.dotall, options.compact_spaces);
common_grammar_builder builder {
/* .add_rule = */ [&](const std::string & name, const std::string & rule) {
return converter._add_rule(name, rule);
},

9
common/json-schema-to-grammar.h
View file

@ -8,10 +8,15 @@
std::string json_schema_to_grammar(const nlohmann::ordered_json & schema,
bool force_gbnf = false);
struct llama_grammar_builder {
struct common_grammar_builder {
std::function<std::string(const std::string &, const std::string &)> add_rule;
std::function<std::string(const std::string &, const nlohmann::ordered_json &)> add_schema;
std::function<void(nlohmann::ordered_json &)> resolve_refs;
};
std::string build_grammar(const std::function<void(const llama_grammar_builder &)> & cb);
struct common_grammar_options {
bool dotall = false;
bool compact_spaces = false;
};
std::string build_grammar(const std::function<void(const common_grammar_builder &)> & cb, const common_grammar_options & options = {});

1
common/log.cpp
View file

@ -206,6 +206,7 @@ public:
vsnprintf(entry.msg.data(), entry.msg.size(), ss.str().c_str(), args_copy);
}
#endif
va_end(args_copy);
}
entry.level = level;

119
common/minja.hpp
View file

@ -628,7 +628,7 @@ class Context : public std::enable_shared_from_this<Context> {
if (parent_) return parent_->contains(key);
return false;
}
virtual void set(const Value & key, Value & value) {
virtual void set(const Value & key, const Value & value) {
values_.set(key, value);
}
};
@ -2648,31 +2648,34 @@ inline std::shared_ptr<Context> Context::builtins() {
return filter.call(context, actual_args);
});
};
// https://jinja.palletsprojects.com/en/3.0.x/templates/#jinja-filters.reject
globals.set("reject", Value::callable([=](const std::shared_ptr<Context> & context, ArgumentsValue & args) {
args.expectArgs("reject", {2, (std::numeric_limits<size_t>::max)()}, {0, 0});
auto & items = args.args[0];
auto filter_fn = context->get(args.args[1]);
if (filter_fn.is_null()) throw std::runtime_error("Undefined filter: " + args.args[1].dump());
auto select_or_reject = [make_filter](bool is_select) {
return Value::callable([=](const std::shared_ptr<Context> & context, ArgumentsValue & args) {
args.expectArgs(is_select ? "select" : "reject", {2, (std::numeric_limits<size_t>::max)()}, {0, 0});
auto & items = args.args[0];
auto filter_fn = context->get(args.args[1]);
if (filter_fn.is_null()) throw std::runtime_error("Undefined filter: " + args.args[1].dump());
auto filter_args = Value::array();
for (size_t i = 2, n = args.args.size(); i < n; i++) {
filter_args.push_back(args.args[i]);
}
auto filter = make_filter(filter_fn, filter_args);
auto res = Value::array();
for (size_t i = 0, n = items.size(); i < n; i++) {
auto & item = items.at(i);
ArgumentsValue filter_args;
filter_args.args.emplace_back(item);
auto pred_res = filter.call(context, filter_args);
if (!pred_res.to_bool()) {
res.push_back(item);
auto filter_args = Value::array();
for (size_t i = 2, n = args.args.size(); i < n; i++) {
filter_args.push_back(args.args[i]);
}
}
return res;
}));
auto filter = make_filter(filter_fn, filter_args);
auto res = Value::array();
for (size_t i = 0, n = items.size(); i < n; i++) {
auto & item = items.at(i);
ArgumentsValue filter_args;
filter_args.args.emplace_back(item);
auto pred_res = filter.call(context, filter_args);
if (pred_res.to_bool() == (is_select ? true : false)) {
res.push_back(item);
}
}
return res;
});
};
globals.set("select", select_or_reject(/* is_select= */ true));
globals.set("reject", select_or_reject(/* is_select= */ false));
globals.set("map", Value::callable([=](const std::shared_ptr<Context> & context, ArgumentsValue & args) {
auto res = Value::array();
if (args.args.size() == 1 &&
@ -2720,41 +2723,45 @@ inline std::shared_ptr<Context> Context::builtins() {
if (!text.empty() && text.back() == '\n') out += "\n";
return out;
}));
globals.set("selectattr", Value::callable([=](const std::shared_ptr<Context> & context, ArgumentsValue & args) {
args.expectArgs("selectattr", {2, (std::numeric_limits<size_t>::max)()}, {0, 0});
auto & items = args.args[0];
if (items.is_null())
return Value::array();
auto attr_name = args.args[1].get<std::string>();
auto select_or_reject_attr = [](bool is_select) {
return Value::callable([=](const std::shared_ptr<Context> & context, ArgumentsValue & args) {
args.expectArgs(is_select ? "selectattr" : "rejectattr", {2, (std::numeric_limits<size_t>::max)()}, {0, 0});
auto & items = args.args[0];
if (items.is_null())
return Value::array();
auto attr_name = args.args[1].get<std::string>();
bool has_test = false;
Value test_fn;
ArgumentsValue test_args {{Value()}, {}};
if (args.args.size() >= 3) {
has_test = true;
test_fn = context->get(args.args[2]);
if (test_fn.is_null()) throw std::runtime_error("Undefined test: " + args.args[2].dump());
for (size_t i = 3, n = args.args.size(); i < n; i++) {
test_args.args.emplace_back(args.args[i]);
}
test_args.kwargs = args.kwargs;
}
auto res = Value::array();
for (size_t i = 0, n = items.size(); i < n; i++) {
auto & item = items.at(i);
auto attr = item.get(attr_name);
if (has_test) {
test_args.args[0] = attr;
if (test_fn.call(context, test_args).to_bool()) {
res.push_back(item);
bool has_test = false;
Value test_fn;
ArgumentsValue test_args {{Value()}, {}};
if (args.args.size() >= 3) {
has_test = true;
test_fn = context->get(args.args[2]);
if (test_fn.is_null()) throw std::runtime_error("Undefined test: " + args.args[2].dump());
for (size_t i = 3, n = args.args.size(); i < n; i++) {
test_args.args.emplace_back(args.args[i]);
}
} else {
res.push_back(attr);
test_args.kwargs = args.kwargs;
}
}
return res;
}));
auto res = Value::array();
for (size_t i = 0, n = items.size(); i < n; i++) {
auto & item = items.at(i);
auto attr = item.get(attr_name);
if (has_test) {
test_args.args[0] = attr;
if (test_fn.call(context, test_args).to_bool() == (is_select ? true : false)) {
res.push_back(item);
}
} else {
res.push_back(attr);
}
}
return res;
});
};
globals.set("selectattr", select_or_reject_attr(/* is_select= */ true));
globals.set("rejectattr", select_or_reject_attr(/* is_select= */ false));
globals.set("range", Value::callable([=](const std::shared_ptr<Context> &, ArgumentsValue & args) {
std::vector<int64_t> startEndStep(3);
std::vector<bool> param_set(3);

12
common/sampling.cpp
View file

@ -151,6 +151,12 @@ struct common_sampler * common_sampler_init(const struct llama_model * model, co
lparams.no_perf = params.no_perf;
std::vector<const char *> trigger_words;
trigger_words.reserve(params.grammar_trigger_words.size());
for (const auto & str : params.grammar_trigger_words) {
trigger_words.push_back(str.word.c_str());
}
struct llama_sampler * grmr;
if (params.grammar.compare(0, 11, "%llguidance") == 0) {
#ifdef LLAMA_USE_LLGUIDANCE
@ -159,7 +165,11 @@ struct common_sampler * common_sampler_init(const struct llama_model * model, co
GGML_ABORT("llguidance (cmake -DLLAMA_LLGUIDANCE=ON) is not enabled");
#endif // LLAMA_USE_LLGUIDANCE
} else {
grmr = llama_sampler_init_grammar(vocab, params.grammar.c_str(), "root");
grmr = params.grammar_lazy
? llama_sampler_init_grammar_lazy(vocab, params.grammar.c_str(), "root",
trigger_words.data(), trigger_words.size(),
params.grammar_trigger_tokens.data(), params.grammar_trigger_tokens.size())
: llama_sampler_init_grammar(vocab, params.grammar.c_str(), "root")
}
auto * result = new common_sampler {

2
examples/gbnf-validator/gbnf-validator.cpp
View file

@ -76,7 +76,7 @@ int main(int argc, char** argv) {
grammar_str = buffer.str();
}
llama_grammar * grammar = llama_grammar_init_impl(nullptr, grammar_str.c_str(), "root");
llama_grammar * grammar = llama_grammar_init_impl(nullptr, grammar_str.c_str(), "root", false, nullptr, 0, nullptr, 0);
if (grammar == nullptr) {
fprintf(stdout, "Failed to initialize llama_grammar\n");
return 1;

32
examples/main-cmake-pkg/CMakeLists.txt
View file

@ -1,32 +0,0 @@
cmake_minimum_required(VERSION 3.12)
project("llama-cli-cmake-pkg" C CXX)
set(TARGET llama-cli-cmake-pkg)
find_package(Llama 0.0.1 REQUIRED)
# Bake common functionality in with target. Because applications
# using the relocatable Llama package should be outside of the
# source tree, llama-cli-cmake-pkg pretends the dependencies are built-in.
set(_common_path "${CMAKE_CURRENT_LIST_DIR}/../../common")
add_library(common OBJECT)
file(GLOB _common_files
"${_common_path}/*.h"
"${_common_path}/*.cpp"
)
target_sources(common PRIVATE ${_common_files})
# If the common project was part of "llama-cli-cmake-pkg" the transient
# defines would automatically be attached. Because the common func-
# tionality is separate, but dependent upon the defines, it must be
# explicitly extracted from the "llama" target.
#
get_target_property(_llama_transient_defines llama
INTERFACE_COMPILE_DEFINITIONS)
target_compile_definitions(common PRIVATE "${_llama_transient_defines}")
add_executable(${TARGET} ${CMAKE_CURRENT_LIST_DIR}/../main/main.cpp)
target_include_directories(${TARGET} PRIVATE ${_common_path})
install(TARGETS ${TARGET} RUNTIME)
target_link_libraries(${TARGET} PRIVATE common llama ${CMAKE_THREAD_LIBS_INIT})
target_compile_features(${TARGET} PRIVATE cxx_std_17)

31
examples/main-cmake-pkg/README.md
View file

@ -1,31 +0,0 @@
# llama.cpp/example/main-cmake-pkg
This program builds [llama-cli](../main) using a relocatable CMake package. It serves as an example of using the `find_package()` CMake command to conveniently include [llama.cpp](https://github.com/ggerganov/llama.cpp) in projects which live outside of the source tree.
## Building
Because this example is "outside of the source tree", it is important to first build/install llama.cpp using CMake. An example is provided here, but please see the [llama.cpp build instructions](../..) for more detailed build instructions.
### Considerations
When hardware acceleration libraries are used (e.g. CUDA, Metal, etc.), CMake must be able to locate the associated CMake package.
### Build llama.cpp and install to C:\LlamaCPP directory
```cmd
git clone https://github.com/ggerganov/llama.cpp
cd llama.cpp
cmake -B build -DBUILD_SHARED_LIBS=OFF -G "Visual Studio 17 2022" -A x64
cmake --build build --config Release
cmake --install build --prefix C:/LlamaCPP
```
### Build llama-cli-cmake-pkg
```cmd
cd ..\examples\main-cmake-pkg
cmake -B build -DBUILD_SHARED_LIBS=OFF -DCMAKE_PREFIX_PATH="C:/LlamaCPP/lib/cmake/Llama" -G "Visual Studio 17 2022" -A x64
cmake --build build --config Release
cmake --install build --prefix C:/MyLlamaApp
```

27
examples/main/main.cpp
View file

@ -254,7 +254,7 @@ int main(int argc, char ** argv) {
}
}
const bool add_bos = llama_vocab_get_add_bos(vocab);
const bool add_bos = llama_vocab_get_add_bos(vocab) && !params.use_jinja;
if (!llama_model_has_encoder(model)) {
GGML_ASSERT(!llama_vocab_get_add_eos(vocab));
}
@ -264,9 +264,9 @@ int main(int argc, char ** argv) {
std::vector<llama_token> embd_inp;
auto chat_add_and_format = [&chat_msgs, &chat_templates](const std::string & role, const std::string & content) {
common_chat_msg new_msg{role, content};
common_chat_msg new_msg{role, content, {}};
auto formatted = common_chat_format_single(*chat_templates.template_default, chat_msgs, new_msg, role == "user", g_params->use_jinja);
chat_msgs.push_back({role, content});
chat_msgs.push_back({role, content, {}});
LOG_DBG("formatted: '%s'\n", formatted.c_str());
return formatted;
};
@ -503,12 +503,14 @@ int main(int argc, char ** argv) {
std::vector<llama_token> embd;
// tokenized antiprompts
std::vector<std::vector<llama_token>> antiprompt_ids;
// single-token antiprompts
std::vector<llama_token> antiprompt_token;
antiprompt_ids.reserve(params.antiprompt.size());
for (const std::string & antiprompt : params.antiprompt) {
antiprompt_ids.emplace_back(::common_tokenize(ctx, antiprompt, false, true));
auto ids = ::common_tokenize(ctx, antiprompt, false, true);
if (ids.size() == 1) {
antiprompt_token.push_back(ids[0]);
}
}
if (llama_model_has_encoder(model)) {
@ -753,14 +755,11 @@ int main(int argc, char ** argv) {
// check for reverse prompt using special tokens
llama_token last_token = common_sampler_last(smpl);
for (std::vector<llama_token> ids : antiprompt_ids) {
if (ids.size() == 1 && last_token == ids[0]) {
if (params.interactive) {
is_interacting = true;
}
is_antiprompt = true;
break;
if (std::find(antiprompt_token.begin(), antiprompt_token.end(), last_token) != antiprompt_token.end()) {
if (params.interactive) {
is_interacting = true;
}
is_antiprompt = true;
}
if (is_antiprompt) {

175
examples/run/run.cpp
View file

@ -181,6 +181,10 @@ class Opt {
}
}
if (model_.empty()){
return 1;
}
return 0;
}
@ -319,6 +323,10 @@ class HttpClient {
public:
int init(const std::string & url, const std::vector<std::string> & headers, const std::string & output_file,
const bool progress, std::string * response_str = nullptr) {
if (std::filesystem::exists(output_file)) {
return 0;
}
std::string output_file_partial;
curl = curl_easy_init();
if (!curl) {
@ -346,7 +354,11 @@ class HttpClient {
data.file_size = set_resume_point(output_file_partial);
set_progress_options(progress, data);
set_headers(headers);
perform(url);
CURLcode res = perform(url);
if (res != CURLE_OK){
printe("Fetching resource '%s' failed: %s\n", url.c_str(), curl_easy_strerror(res));
return 1;
}
if (!output_file.empty()) {
std::filesystem::rename(output_file_partial, output_file);
}
@ -411,16 +423,12 @@ class HttpClient {
}
}
void perform(const std::string & url) {
CURLcode res;
CURLcode perform(const std::string & url) {
curl_easy_setopt(curl, CURLOPT_URL, url.c_str());
curl_easy_setopt(curl, CURLOPT_FOLLOWLOCATION, 1L);
curl_easy_setopt(curl, CURLOPT_DEFAULT_PROTOCOL, "https");
curl_easy_setopt(curl, CURLOPT_FAILONERROR, 1L);
res = curl_easy_perform(curl);
if (res != CURLE_OK) {
printe("curl_easy_perform() failed: %s\n", curl_easy_strerror(res));
}
return curl_easy_perform(curl);
}
static std::string human_readable_time(double seconds) {
@ -558,13 +566,14 @@ class LlamaData {
}
sampler = initialize_sampler(opt);
return 0;
}
private:
#ifdef LLAMA_USE_CURL
int download(const std::string & url, const std::vector<std::string> & headers, const std::string & output_file,
const bool progress, std::string * response_str = nullptr) {
int download(const std::string & url, const std::string & output_file, const bool progress,
const std::vector<std::string> & headers = {}, std::string * response_str = nullptr) {
HttpClient http;
if (http.init(url, headers, output_file, progress, response_str)) {
return 1;
@ -573,48 +582,85 @@ class LlamaData {
return 0;
}
#else
int download(const std::string &, const std::vector<std::string> &, const std::string &, const bool,
int download(const std::string &, const std::string &, const bool, const std::vector<std::string> & = {},
std::string * = nullptr) {
printe("%s: llama.cpp built without libcurl, downloading from an url not supported.\n", __func__);
return 1;
}
#endif
int huggingface_dl(const std::string & model, const std::vector<std::string> headers, const std::string & bn) {
// Find the second occurrence of '/' after protocol string
size_t pos = model.find('/');
pos = model.find('/', pos + 1);
if (pos == std::string::npos) {
return 1;
}
const std::string hfr = model.substr(0, pos);
const std::string hff = model.substr(pos + 1);
const std::string url = "https://huggingface.co/" + hfr + "/resolve/main/" + hff;
return download(url, headers, bn, true);
}
int ollama_dl(std::string & model, const std::vector<std::string> headers, const std::string & bn) {
if (model.find('/') == std::string::npos) {
model = "library/" + model;
}
std::string model_tag = "latest";
size_t colon_pos = model.find(':');
// Helper function to handle model tag extraction and URL construction
std::pair<std::string, std::string> extract_model_and_tag(std::string & model, const std::string & base_url) {
std::string model_tag = "latest";
const size_t colon_pos = model.find(':');
if (colon_pos != std::string::npos) {
model_tag = model.substr(colon_pos + 1);
model = model.substr(0, colon_pos);
}
std::string manifest_url = "https://registry.ollama.ai/v2/" + model + "/manifests/" + model_tag;
std::string url = base_url + model + "/manifests/" + model_tag;
return { model, url };
}
// Helper function to download and parse the manifest
int download_and_parse_manifest(const std::string & url, const std::vector<std::string> & headers,
nlohmann::json & manifest) {
std::string manifest_str;
const int ret = download(manifest_url, headers, "", false, &manifest_str);
int ret = download(url, "", false, headers, &manifest_str);
if (ret) {
return ret;
}
nlohmann::json manifest = nlohmann::json::parse(manifest_str);
std::string layer;
manifest = nlohmann::json::parse(manifest_str);
return 0;
}
int huggingface_dl(std::string & model, const std::string & bn) {
// Find the second occurrence of '/' after protocol string
size_t pos = model.find('/');
pos = model.find('/', pos + 1);
std::string hfr, hff;
std::vector<std::string> headers = { "User-Agent: llama-cpp", "Accept: application/json" };
std::string url;
if (pos == std::string::npos) {
auto [model_name, manifest_url] = extract_model_and_tag(model, "https://huggingface.co/v2/");
hfr = model_name;
nlohmann::json manifest;
int ret = download_and_parse_manifest(manifest_url, headers, manifest);
if (ret) {
return ret;
}
hff = manifest["ggufFile"]["rfilename"];
} else {
hfr = model.substr(0, pos);
hff = model.substr(pos + 1);
}
url = "https://huggingface.co/" + hfr + "/resolve/main/" + hff;
return download(url, bn, true, headers);
}
int ollama_dl(std::string & model, const std::string & bn) {
const std::vector<std::string> headers = { "Accept: application/vnd.docker.distribution.manifest.v2+json" };
if (model.find('/') == std::string::npos) {
model = "library/" + model;
}
auto [model_name, manifest_url] = extract_model_and_tag(model, "https://registry.ollama.ai/v2/");
nlohmann::json manifest;
int ret = download_and_parse_manifest(manifest_url, {}, manifest);
if (ret) {
return ret;
}
std::string layer;
for (const auto & l : manifest["layers"]) {
if (l["mediaType"] == "application/vnd.ollama.image.model") {
layer = l["digest"];
@ -622,8 +668,34 @@ class LlamaData {
}
}
std::string blob_url = "https://registry.ollama.ai/v2/" + model + "/blobs/" + layer;
return download(blob_url, headers, bn, true);
std::string blob_url = "https://registry.ollama.ai/v2/" + model_name + "/blobs/" + layer;
return download(blob_url, bn, true, headers);
}
int github_dl(const std::string & model, const std::string & bn) {
std::string repository = model;
std::string branch = "main";
const size_t at_pos = model.find('@');
if (at_pos != std::string::npos) {
repository = model.substr(0, at_pos);
branch = model.substr(at_pos + 1);
}
const std::vector<std::string> repo_parts = string_split(repository, "/");
if (repo_parts.size() < 3) {
printe("Invalid GitHub repository format\n");
return 1;
}
const std::string & org = repo_parts[0];
const std::string & project = repo_parts[1];
std::string url = "https://raw.githubusercontent.com/" + org + "/" + project + "/" + branch;
for (size_t i = 2; i < repo_parts.size(); ++i) {
url += "/" + repo_parts[i];
}
return download(url, bn, true);
}
std::string basename(const std::string & path) {
@ -653,22 +725,23 @@ class LlamaData {
return ret;
}
const std::string bn = basename(model_);
const std::vector<std::string> headers = { "--header",
"Accept: application/vnd.docker.distribution.manifest.v2+json" };
if (string_starts_with(model_, "hf://") || string_starts_with(model_, "huggingface://")) {
rm_until_substring(model_, "://");
ret = huggingface_dl(model_, headers, bn);
} else if (string_starts_with(model_, "hf.co/")) {
const std::string bn = basename(model_);
if (string_starts_with(model_, "hf://") || string_starts_with(model_, "huggingface://") ||
string_starts_with(model_, "hf.co/")) {
rm_until_substring(model_, "hf.co/");
ret = huggingface_dl(model_, headers, bn);
} else if (string_starts_with(model_, "ollama://")) {
rm_until_substring(model_, "://");
ret = ollama_dl(model_, headers, bn);
} else if (string_starts_with(model_, "https://")) {
ret = download(model_, headers, bn, true);
} else {
ret = ollama_dl(model_, headers, bn);
ret = huggingface_dl(model_, bn);
} else if ((string_starts_with(model_, "https://") || string_starts_with(model_, "http://")) &&
!string_starts_with(model_, "https://ollama.com/library/")) {
ret = download(model_, bn, true);
} else if (string_starts_with(model_, "github:") || string_starts_with(model_, "github://")) {
rm_until_substring(model_, "github:");
rm_until_substring(model_, "://");
ret = github_dl(model_, bn);
} else { // ollama:// or nothing
rm_until_substring(model_, "ollama.com/library/");
rm_until_substring(model_, "://");
ret = ollama_dl(model_, bn);
}
model_ = bn;

198
examples/server/README.md
View file

@ -126,7 +126,7 @@ The project is under active development, and we are [looking for feedback and co
| `--grammar GRAMMAR` | BNF-like grammar to constrain generations (see samples in grammars/ dir) (default: '') |
| `--grammar-file FNAME` | file to read grammar from |
| `-j, --json-schema SCHEMA` | JSON schema to constrain generations (https://json-schema.org/), e.g. `{}` for any JSON object<br/>For schemas w/ external $refs, use --grammar + example/json_schema_to_grammar.py instead |
| `--jinja` | Enable experimental Jinja templating engine (needed for tool use) |
| `--jinja` | Enable experimental Jinja templating engine (required for tool use) |
**Example-specific params**
@ -236,9 +236,13 @@ npm i
# to run the dev server
npm run dev
# to build the public/index.html
# to build the public/index.html.gz
npm run build
```
After `public/index.html.gz` has been generated we need to generate the c++
headers (like build/examples/server/index.html.gz.hpp) that will be included
by server.cpp. This is done by building `llama-server` as described in the
[build](#build) section above.
NOTE: if you are using the vite dev server, you can change the API base URL to llama.cpp. To do that, run this code snippet in browser's console:
@ -456,7 +460,7 @@ These words will not be included in the completion, so make sure to add them to
- Note: In streaming mode (`stream`), only `content`, `tokens` and `stop` will be returned until end of completion. Responses are sent using the [Server-sent events](https://html.spec.whatwg.org/multipage/server-sent-events.html) standard. Note: the browser's `EventSource` interface cannot be used due to its lack of `POST` request support.
- `completion_probabilities`: An array of token probabilities for each completion. The array's length is `n_predict`. Each item in the array has a nested array `top_logprobs`. It contains at **maximum** `n_probs` elements:
```json
```
{
"content": "<the generated completion text>",
"tokens": [ generated token ids if requested ],
@ -557,7 +561,7 @@ If `with_pieces` is `true`:
```
With input 'á' (utf8 hex: C3 A1) on tinyllama/stories260k
```json
```
{
"tokens": [
{"id": 198, "piece": [195]}, // hex C3
@ -572,6 +576,18 @@ With input 'á' (utf8 hex: C3 A1) on tinyllama/stories260k
`tokens`: Set the tokens to detokenize.
### POST `/apply-template`: Apply chat template to a conversation
Uses the server's prompt template formatting functionality to convert chat messages to a single string expected by a chat model as input, but does not perform inference. Instead, the prompt string is returned in the `prompt` field of the JSON response. The prompt can then be modified as desired (for example, to insert "Sure!" at the beginning of the model's response) before sending to `/completion` to generate the chat response.
*Options:*
`messages`: (Required) Chat turns in the same format as `/v1/chat/completions`.
**Response format**
Returns a JSON object with a field `prompt` containing a string of the input messages formatted according to the model's chat template format.
### POST `/embedding`: Generate embedding of a given text
> [!IMPORTANT]
@ -764,7 +780,7 @@ Same as the `/v1/embeddings` endpoint.
**Response format**
```json
```
[
{
"index": 0,
@ -1053,7 +1069,7 @@ Given a ChatML-formatted json description in `messages`, it returns the predicte
*Options:*
See [OpenAI Chat Completions API documentation](https://platform.openai.com/docs/api-reference/chat). While some OpenAI-specific features such as function calling aren't supported, llama.cpp `/completion`-specific features such as `mirostat` are supported.
See [OpenAI Chat Completions API documentation](https://platform.openai.com/docs/api-reference/chat). llama.cpp `/completion`-specific features such as `mirostat` are also supported.
The `response_format` parameter supports both plain JSON output (e.g. `{"type": "json_object"}`) and schema-constrained JSON (e.g. `{"type": "json_object", "schema": {"type": "string", "minLength": 10, "maxLength": 100}}` or `{"type": "json_schema", "schema": {"properties": { "name": { "title": "Name", "type": "string" }, "date": { "title": "Date", "type": "string" }, "participants": { "items": {"type: "string" }, "title": "Participants", "type": "string" } } } }`), similar to other OpenAI-inspired API providers.
@ -1101,6 +1117,176 @@ curl http://localhost:8080/v1/chat/completions \
}'
```
*Tool call support*
[Function calling](https://platform.openai.com/docs/guides/function-calling) is supported for all models (see https://github.com/ggerganov/llama.cpp/pull/9639):
- Requires `--jinja` flag
- Native tool call formats supported:
- Llama 3.1 / 3.3 (including builtin tools support - tool names for `wolfram_alpha`, `web_search` / `brave_search`, `code_interpreter`), Llama 3.2
- Functionary v3.1 / v3.2
- Hermes 2/3, Qwen 2.5
- Mistral Nemo
- Firefunction v2
- DeepSeek R1 (WIP / seems reluctant to call any tools?)
<details>
<summary>Show some common templates and which format handler they use</summary>
| Template | Format |
|----------|--------|
| CohereForAI-c4ai-command-r-plus-default.jinja | generic tool calls |
| CohereForAI-c4ai-command-r-plus-rag.jinja | generic tool calls |
| CohereForAI-c4ai-command-r-plus-tool_use.jinja | generic tool calls |
| MiniMaxAI-MiniMax-Text-01.jinja | generic tool calls |
| NexaAIDev-Octopus-v2.jinja | generic tool calls |
| NousResearch-Hermes-2-Pro-Llama-3-8B-default.jinja | generic tool calls |
| NousResearch-Hermes-2-Pro-Llama-3-8B-tool_use.jinja | hermes 2 pro tool calls |
| NousResearch-Hermes-2-Pro-Mistral-7B-default.jinja | generic tool calls |
| NousResearch-Hermes-2-Pro-Mistral-7B-tool_use.jinja | hermes 2 pro tool calls |
| NousResearch-Hermes-3-Llama-3.1-70B-default.jinja | generic tool calls |
| NousResearch-Hermes-3-Llama-3.1-70B-tool_use.jinja | hermes 2 pro tool calls |
| OrionStarAI-Orion-14B-Chat.jinja | generic tool calls |
| Qwen-QwQ-32B-Preview.jinja | hermes 2 pro tool calls |
| Qwen-Qwen2-7B-Instruct.jinja | generic tool calls |
| Qwen-Qwen2-VL-7B-Instruct.jinja | generic tool calls |
| Qwen-Qwen2.5-7B-Instruct.jinja | hermes 2 pro tool calls |
| Qwen-Qwen2.5-Math-7B-Instruct.jinja | hermes 2 pro tool calls |
| TheBloke-FusionNet_34Bx2_MoE-AWQ.jinja | generic tool calls |
| abacusai-Fewshot-Metamath-OrcaVicuna-Mistral.jinja | generic tool calls |
| bofenghuang-vigogne-2-70b-chat.jinja | generic tool calls |
| databricks-dbrx-instruct.jinja | generic tool calls |
| deepseek-ai-DeepSeek-Coder-V2-Instruct.jinja | generic tool calls |
| deepseek-ai-DeepSeek-R1-Distill-Llama-8B.jinja | deepseek r1 tool calls |
| deepseek-ai-DeepSeek-R1-Distill-Qwen-32B.jinja | deepseek r1 tool calls |
| deepseek-ai-DeepSeek-R1-Distill-Qwen-7B.jinja | deepseek r1 tool calls |
| deepseek-ai-DeepSeek-V2.5.jinja | deepseek r1 tool calls |
| deepseek-ai-deepseek-coder-33b-instruct.jinja | generic tool calls |
| google-gemma-2-2b-it.jinja | generic tool calls |
| google-gemma-7b-it.jinja | generic tool calls |
| indischepartij-MiniCPM-3B-OpenHermes-2.5-v2.jinja | generic tool calls |
| mattshumer-Reflection-Llama-3.1-70B.jinja | generic tool calls |
| meetkai-functionary-medium-v3.2.jinja | functionary v3.2 tool calls |
| meta-llama-Llama-3.1-8B-Instruct.jinja | llama 3.x tool calls (w/ builtin tools) |
| meta-llama-Llama-3.2-3B-Instruct.jinja | llama 3.x tool calls |
| meta-llama-Llama-3.3-70B-Instruct.jinja | llama 3.x tool calls (w/ builtin tools) |
| meta-llama-Meta-Llama-3.1-8B-Instruct.jinja | llama 3.x tool calls (w/ builtin tools) |
| microsoft-Phi-3-medium-4k-instruct.jinja | generic tool calls |
| microsoft-Phi-3-mini-4k-instruct.jinja | generic tool calls |
| microsoft-Phi-3-small-8k-instruct.jinja | generic tool calls |
| microsoft-Phi-3.5-mini-instruct.jinja | generic tool calls |
| microsoft-Phi-3.5-vision-instruct.jinja | generic tool calls |
| mistralai-Mistral-7B-Instruct-v0.2.jinja | generic tool calls |
| mistralai-Mistral-Large-Instruct-2407.jinja | mistral nemo tool calls |
| mistralai-Mistral-Large-Instruct-2411.jinja | generic tool calls |
| mistralai-Mistral-Nemo-Instruct-2407.jinja | mistral nemo tool calls |
| mistralai-Mixtral-8x7B-Instruct-v0.1.jinja | generic tool calls |
| mlabonne-AlphaMonarch-7B.jinja | generic tool calls |
| nvidia-Llama-3.1-Nemotron-70B-Instruct-HF.jinja | llama 3.x tool calls (w/ builtin tools) |
| openchat-openchat-3.5-0106.jinja | generic tool calls |
| teknium-OpenHermes-2.5-Mistral-7B.jinja | generic tool calls |
This table can be generated with:
```bash
./build/bin/test-chat ../minja/build/tests/*.jinja 2>/dev/null
</details>
- Generic tool call is supported when the template isn't recognized by native format handlers (you'll see `Chat format: Generic` in the logs).
- Use `--chat-template-file` to override the template when appropriate (see examples below)
- Generic support may consume more tokens and be less efficient than a model's native format.
- Run with:
```shell
# Native support:
llama-server --jinja -fa -hf bartowski/Qwen2.5-7B-Instruct-GGUF:Q4_K_M
llama-server --jinja -fa -hf bartowski/Mistral-Nemo-Instruct-2407-GGUF:Q4_K_M
llama-server --jinja -fa -hf bartowski/Llama-3.2-3B-Instruct-GGUF:Q6_K
llama-server --jinja -fa -hf bartowski/functionary-small-v3.2-GGUF:Q4_K_M
llama-server --jinja -fa -hf bartowski/Hermes-2-Pro-Llama-3-8B-GGUF:Q4_K_M \
--chat-template-file <( python scripts/get_chat_template.py NousResearch/Hermes-2-Pro-Llama-3-8B )
# Native support requires the right template for these GGUFs:
llama-server --jinja -fa -hf bartowski/Hermes-3-Llama-3.1-8B-GGUF:Q4_K_M \
--chat-template-file <( python scripts/get_chat_template.py NousResearch/Hermes-3-Llama-3.1-8B tool_use )
llama-server --jinja -fa -hf bartowski/firefunction-v2-GGUF -hff firefunction-v2-IQ1_M.gguf \
--chat-template-file <( python scripts/get_chat_template.py fireworks-ai/firellama-3-firefunction-v2 )
# Generic format support
llama-server --jinja -fa -hf bartowski/Phi-3.5-mini-instruct-GGUF:Q4_K_M
llama-server --jinja -fa -hf bartowski/gemma-2-2b-it-GGUF:Q4_K_M
```
- Test in CLI:
```bash
curl http://localhost:8080/v1/chat/completions -d '{
"model": "gpt-3.5-turbo",
"tools": [
{
"type":"function",
"function":{
"name":"get_current_weather",
"description":"Get the current weather in a given location",
"parameters":{
"type":"object",
"properties":{
"location":{
"type":"string",
"description":"The city and state, e.g. San Francisco, CA"
}
},
"required":["location"]
}
}
}
],
"messages": [
{
"role": "user",
"content": "What is the weather like in Istanbul?."
}
]
}'
```
<details>
<summary>Show output</summary>
```json
{
"choices": [
{
"finish_reason": "tool",
"index": 0,
"message": {
"content": null,
"tool_calls": [
{
"name": "python",
"arguments": "{\"code\":\" \\nprint(\\\"Hello, World!\\\")\"}"
}
],
"role": "assistant"
}
}
],
"created": 1727287211,
"model": "gpt-3.5-turbo",
"object": "chat.completion",
"usage": {
"completion_tokens": 16,
"prompt_tokens": 44,
"total_tokens": 60
},
"id": "chatcmpl-Htbgh9feMmGM0LEH2hmQvwsCxq3c6Ni8"
}
```
</details>
### POST `/v1/embeddings`: OpenAI-compatible embeddings API
This endpoint requires that the model uses a pooling different than type `none`. The embeddings are normalized using the Eucledian norm.

212
examples/server/server.cpp
View file

@ -14,7 +14,7 @@
// mime type for sending response
#define MIMETYPE_JSON "application/json; charset=utf-8"
// auto generated files (update with ./deps.sh)
// auto generated files (see README.md for details)
#include "index.html.gz.hpp"
#include "loading.html.hpp"
@ -113,10 +113,11 @@ struct slot_params {
struct common_params_speculative speculative;
// OAI-compat fields
bool verbose = false;
oaicompat_type oaicompat = OAICOMPAT_TYPE_NONE;
std::string oaicompat_model;
std::string oaicompat_cmpl_id;
bool verbose = false;
oaicompat_type oaicompat = OAICOMPAT_TYPE_NONE;
std::string oaicompat_model;
std::string oaicompat_cmpl_id;
common_chat_format oaicompat_chat_format = COMMON_CHAT_FORMAT_CONTENT_ONLY;
json to_json() const {
std::vector<std::string> samplers;
@ -164,6 +165,8 @@ struct slot_params {
{"n_probs", sampling.n_probs},
{"min_keep", sampling.min_keep},
{"grammar", sampling.grammar},
// {"grammar_trigger_words", sampling.grammar_trigger_words},
{"grammar_trigger_tokens", sampling.grammar_trigger_tokens},
{"samplers", samplers},
{"speculative.n_max", speculative.n_max},
{"speculative.n_min", speculative.n_min},
@ -325,12 +328,50 @@ struct server_task {
if (data.contains("json_schema") && !data.contains("grammar")) {
try {
auto schema = json_value(data, "json_schema", json::object());
params.sampling.grammar = json_schema_to_grammar(schema);
LOG_DBG("JSON schema: %s\n", schema.dump(2).c_str());
params.sampling.grammar = json_schema_to_grammar(schema);
LOG_DBG("Converted grammar: %s\n", params.sampling.grammar.c_str());
} catch (const std::exception & e) {
throw std::runtime_error(std::string("\"json_schema\": ") + e.what());
}
} else {
params.sampling.grammar = json_value(data, "grammar", defaults.sampling.grammar);
params.sampling.grammar = json_value(data, "grammar", defaults.sampling.grammar);
LOG_DBG("Grammar: %s\n", params.sampling.grammar.c_str());
params.sampling.grammar_lazy = json_value(data, "grammar_lazy", defaults.sampling.grammar_lazy);
LOG_DBG("Grammar lazy: %s\n", params.sampling.grammar_lazy ? "true" : "false");
}
{
auto it = data.find("chat_format");
if (it != data.end()) {
params.oaicompat_chat_format = static_cast<common_chat_format>(it->get<int>());
LOG_INF("Chat format: %s\n", common_chat_format_name(params.oaicompat_chat_format).c_str());
} else {
params.oaicompat_chat_format = defaults.oaicompat_chat_format;
}
}
{
const auto grammar_triggers = data.find("grammar_triggers");
if (grammar_triggers != data.end()) {
for (const auto & t : *grammar_triggers) {
common_grammar_trigger trigger;
trigger.word = t.at("word");
trigger.at_start = t.at("at_start");
auto ids = common_tokenize(vocab, trigger.word, /* add_special= */ false, /* parse_special= */ true);
if (ids.size() == 1) {
LOG_DBG("Grammar trigger token: %d (`%s`)\n", ids[0], trigger.word.c_str());
params.sampling.grammar_trigger_tokens.push_back(ids[0]);
continue;
}
LOG_DBG("Grammar trigger word: `%s`\n", trigger.word.c_str());
params.sampling.grammar_trigger_words.push_back(trigger);
}
}
if (params.sampling.grammar_lazy) {
GGML_ASSERT(params.sampling.grammar_trigger_tokens.size() > 0 || params.sampling.grammar_trigger_words.size() > 0);
}
}
{
@ -382,22 +423,12 @@ struct server_task {
}
{
const auto & samplers = data.find("samplers");
const auto samplers = data.find("samplers");
if (samplers != data.end()) {
if (samplers->is_array()) {
std::vector<std::string> sampler_names;
for (const auto & name : *samplers) {
if (name.is_string()) {
sampler_names.emplace_back(name);
}
}
params.sampling.samplers = common_sampler_types_from_names(sampler_names, false);
params.sampling.samplers = common_sampler_types_from_names(*samplers, false);
} else if (samplers->is_string()){
std::string sampler_string;
for (const auto & name : *samplers) {
sampler_string += name;
}
params.sampling.samplers = common_sampler_types_from_chars(sampler_string);
params.sampling.samplers = common_sampler_types_from_chars(samplers->get<std::string>());
}
} else {
params.sampling.samplers = defaults.sampling.samplers;
@ -544,7 +575,7 @@ struct completion_token_output {
struct server_task_result_cmpl_final : server_task_result {
int index = 0;
std::string content;
std::string content;
llama_tokens tokens;
bool stream;
@ -566,10 +597,11 @@ struct server_task_result_cmpl_final : server_task_result {
slot_params generation_params;
// OAI-compat fields
bool verbose = false;
oaicompat_type oaicompat = OAICOMPAT_TYPE_NONE;
std::string oaicompat_model;
std::string oaicompat_cmpl_id;
bool verbose = false;
oaicompat_type oaicompat = OAICOMPAT_TYPE_NONE;
std::string oaicompat_model;
std::string oaicompat_cmpl_id;
common_chat_format oaicompat_chat_format = COMMON_CHAT_FORMAT_CONTENT_ONLY;
virtual int get_index() override {
return index;
@ -663,18 +695,39 @@ struct server_task_result_cmpl_final : server_task_result {
json to_json_oaicompat_chat() {
std::string finish_reason = "length";
common_chat_msg message;
if (stop == STOP_TYPE_WORD || stop == STOP_TYPE_EOS) {
finish_reason = "stop";
LOG_DBG("Parsing chat message: %s\n", content.c_str());
message = common_chat_parse(content, oaicompat_chat_format);
finish_reason = message.tool_calls.empty() ? "stop" : "tool_calls";
} else {
message.content = content;
}
json choice = json{
json tool_calls;
if (!message.tool_calls.empty()) {
tool_calls = json::array();
for (const auto & tc : message.tool_calls) {
tool_calls.push_back({
{"type", "function"},
{"function", {
{"name", tc.name},
{"arguments", tc.arguments},
}},
{"id", tc.id},
});
}
}
json choice {
{"finish_reason", finish_reason},
{"index", 0},
{"message", json {
{"content", content},
{"role", "assistant"}
}
}};
{"content", message.content},
{"tool_calls", tool_calls},
{"role", "assistant"},
}},
};
if (!stream && probs_output.size() > 0) {
choice["logprobs"] = json{
@ -716,7 +769,7 @@ struct server_task_result_cmpl_final : server_task_result {
finish_reason = "stop";
}
json choice = json{
json choice = json {
{"finish_reason", finish_reason},
{"index", 0},
{"delta", json::object()}
@ -1191,6 +1244,8 @@ struct server_slot {
llama_token sampled;
common_chat_format chat_format = COMMON_CHAT_FORMAT_CONTENT_ONLY;
// stats
size_t n_sent_text = 0; // number of sent text character
@ -1804,7 +1859,12 @@ struct server_context {
llama_init_dft.context.reset();
}
chat_templates = common_chat_templates_from_model(model, params_base.chat_template);
if (params_base.chat_template.empty() && !validate_builtin_chat_template(params.use_jinja)) {
LOG_WRN("%s: The chat template that comes with this model is not yet supported, falling back to chatml. This may cause the model to output suboptimal responses\n", __func__);
chat_templates = common_chat_templates_from_model(model, "chatml");
} else {
chat_templates = common_chat_templates_from_model(model, params_base.chat_template);
}
GGML_ASSERT(chat_templates.template_default.get() != nullptr);
return true;
@ -1815,17 +1875,16 @@ struct server_context {
if (use_jinja) {
auto templates = common_chat_templates_from_model(model, "");
common_chat_inputs inputs;
inputs.messages = json::array({{
{"role", "user"},
{"content", "test"},
}});
GGML_ASSERT(templates.template_default);
try {
templates.template_default->apply({{
{"role", "user"},
{"content", "test"},
}}, json(), true);
common_chat_params_init(*templates.template_default, inputs);
if (templates.template_tool_use) {
templates.template_tool_use->apply({{
{"role", "user"},
{"content", "test"},
}}, json(), true);
common_chat_params_init(*templates.template_tool_use, inputs);
}
return true;
} catch (const std::exception & e) {
@ -2275,11 +2334,11 @@ struct server_context {
res->id_slot = slot.id;
res->index = slot.index;
res->content = slot.generated_text;
res->tokens = slot.generated_tokens;
res->content = std::move(slot.generated_text);
res->tokens = std::move(slot.generated_tokens);
res->timings = slot.get_timings();
res->prompt = common_detokenize(ctx, slot.prompt_tokens, true);
res->response_fields = slot.params.response_fields;
res->response_fields = std::move(slot.params.response_fields);
res->truncated = slot.truncated;
res->n_decoded = slot.n_decoded;
@ -2290,12 +2349,12 @@ struct server_context {
res->stop = slot.stop;
res->post_sampling_probs = slot.params.post_sampling_probs;
res->verbose = slot.params.verbose;
res->stream = slot.params.stream;
res->oaicompat = slot.params.oaicompat;
res->oaicompat_model = slot.params.oaicompat_model;
res->oaicompat_cmpl_id = slot.params.oaicompat_cmpl_id;
res->verbose = slot.params.verbose;
res->stream = slot.params.stream;
res->oaicompat = slot.params.oaicompat;
res->oaicompat_model = slot.params.oaicompat_model;
res->oaicompat_cmpl_id = slot.params.oaicompat_cmpl_id;
res->oaicompat_chat_format = slot.params.oaicompat_chat_format;
// populate res.probs_output
if (slot.params.sampling.n_probs > 0) {
if (!slot.params.stream && slot.stop == STOP_TYPE_WORD) {
@ -2773,6 +2832,11 @@ struct server_context {
// track if given slot can be batched with slots already in the batch
server_slot * slot_batched = nullptr;
auto accept_special_token = [&](server_slot & slot, llama_token token) {
const auto & trigger_tokens = slot.params.sampling.grammar_trigger_tokens;
return params_base.special || std::find(trigger_tokens.begin(), trigger_tokens.end(), token) != trigger_tokens.end();
};
// frist, add sampled tokens from any ongoing sequences
for (auto & slot : slots) {
if (slot.state != SLOT_STATE_GENERATING) {
@ -3136,7 +3200,7 @@ struct server_context {
completion_token_output result;
result.tok = id;
result.text_to_send = common_token_to_piece(ctx, result.tok, params_base.special);
result.text_to_send = common_token_to_piece(ctx, result.tok, accept_special_token(slot, result.tok));
result.prob = 1.0f; // TODO: set it here instead of doing inside populate_token_probs
if (slot.params.sampling.n_probs > 0) {
@ -3225,7 +3289,7 @@ struct server_context {
completion_token_output result;
result.tok = ids[i];
result.text_to_send = common_token_to_piece(ctx, result.tok, params_base.special);
result.text_to_send = common_token_to_piece(ctx, result.tok, accept_special_token(slot, result.tok));
result.prob = 1.0f; // set later
// TODO: set result.probs
@ -3575,11 +3639,11 @@ int main(int argc, char ** argv) {
{"value", (uint64_t) res_metrics->kv_cache_tokens_count}
},{
{"name", "requests_processing"},
{"help", "Number of request processing."},
{"help", "Number of requests processing."},
{"value", (uint64_t) res_metrics->n_processing_slots}
},{
{"name", "requests_deferred"},
{"help", "Number of request deferred."},
{"help", "Number of requests deferred."},
{"value", (uint64_t) res_metrics->n_tasks_deferred}
}}}
};
@ -3722,6 +3786,8 @@ int main(int argc, char ** argv) {
{ "total_slots", ctx_server.params_base.n_parallel },
{ "model_path", ctx_server.params_base.model },
{ "chat_template", ctx_server.chat_templates.template_default->source() },
{ "bos_token", ctx_server.chat_templates.template_default->bos_token() },
{ "eos_token", ctx_server.chat_templates.template_default->eos_token() },
{ "build_info", build_info },
};
if (ctx_server.params_base.use_jinja && ctx_server.chat_templates.template_tool_use) {
@ -3763,7 +3829,9 @@ int main(int argc, char ** argv) {
std::vector<server_task> tasks;
try {
std::vector<llama_tokens> tokenized_prompts = tokenize_input_prompts(ctx_server.vocab, data.at("prompt"), true, true);
const auto & prompt = data.at("prompt");
LOG_DBG("Prompt: %s\n", prompt.is_string() ? prompt.get<std::string>().c_str() : prompt.dump(2).c_str());
std::vector<llama_tokens> tokenized_prompts = tokenize_input_prompts(ctx_server.vocab, prompt, true, true);
tasks.reserve(tokenized_prompts.size());
for (size_t i = 0; i < tokenized_prompts.size(); i++) {
server_task task = server_task(type);
@ -3779,8 +3847,8 @@ int main(int argc, char ** argv) {
task.id_selected_slot = json_value(data, "id_slot", -1);
// OAI-compat
task.params.oaicompat = oaicompat;
task.params.oaicompat_cmpl_id = completion_id;
task.params.oaicompat = oaicompat;
task.params.oaicompat_cmpl_id = completion_id;
// oaicompat_model is already populated by params_from_json_cmpl
tasks.push_back(task);
@ -3949,14 +4017,14 @@ int main(int argc, char ** argv) {
};
const auto handle_chat_completions = [&ctx_server, &params, &res_error, &handle_completions_impl](const httplib::Request & req, httplib::Response & res) {
LOG_DBG("request: %s\n", req.body.c_str());
if (ctx_server.params_base.embedding) {
res_error(res, format_error_response("This server does not support completions. Start it without `--embeddings`", ERROR_TYPE_NOT_SUPPORTED));
return;
}
auto body = json::parse(req.body);
const auto & chat_template = body.contains("tools") && ctx_server.chat_templates.template_tool_use ? *ctx_server.chat_templates.template_tool_use : *ctx_server.chat_templates.template_default;
json data = oaicompat_completion_params_parse(body, chat_template, params.use_jinja);
json data = oaicompat_completion_params_parse(body, params.use_jinja, ctx_server.chat_templates);
return handle_completions_impl(
SERVER_TASK_TYPE_COMPLETION,
@ -3966,6 +4034,13 @@ int main(int argc, char ** argv) {
OAICOMPAT_TYPE_CHAT);
};
// same with handle_chat_completions, but without inference part
const auto handle_apply_template = [&ctx_server, &params, &res_ok](const httplib::Request & req, httplib::Response & res) {
auto body = json::parse(req.body);
json data = oaicompat_completion_params_parse(body, params.use_jinja, ctx_server.chat_templates);
res_ok(res, {{ "prompt", std::move(data.at("prompt")) }});
};
const auto handle_models = [&params, &ctx_server, &res_ok](const httplib::Request &, httplib::Response & res) {
json models = {
{"object", "list"},
@ -4300,6 +4375,7 @@ int main(int argc, char ** argv) {
svr->Post("/v1/reranking", handle_rerank);
svr->Post("/tokenize", handle_tokenize);
svr->Post("/detokenize", handle_detokenize);
svr->Post("/apply-template", handle_apply_template);
// LoRA adapters hotswap
svr->Get ("/lora-adapters", handle_lora_adapters_list);
svr->Post("/lora-adapters", handle_lora_adapters_apply);
@ -4365,24 +4441,18 @@ int main(int argc, char ** argv) {
LOG_INF("%s: model loaded\n", __func__);
// if a custom chat template is not supplied, we will use the one that comes with the model (if any)
if (params.chat_template.empty()) {
if (!ctx_server.validate_builtin_chat_template(params.use_jinja)) {
LOG_WRN("%s: The chat template that comes with this model is not yet supported, falling back to chatml. This may cause the model to output suboptimal responses\n", __func__);
params.chat_template = "chatml";
}
}
// print sample chat example to make it clear which template is used
LOG_INF("%s: chat template, chat_template: %s, example_format: '%s'\n", __func__,
ctx_server.chat_templates.template_default->source().c_str(),
common_chat_format_example(*ctx_server.chat_templates.template_default, ctx_server.params_base.use_jinja).c_str());
ctx_server.queue_tasks.on_new_task(std::bind(
&server_context::process_single_task, &ctx_server, std::placeholders::_1));
ctx_server.queue_tasks.on_new_task([&ctx_server](const server_task & task) {
ctx_server.process_single_task(task);
});
ctx_server.queue_tasks.on_update_slots(std::bind(
&server_context::update_slots, &ctx_server));
ctx_server.queue_tasks.on_update_slots([&ctx_server]() {
ctx_server.update_slots();
});
shutdown_handler = [&](int) {
ctx_server.queue_tasks.terminate();

13
examples/server/tests/README.md
View file

@ -31,8 +31,9 @@ It's possible to override some scenario steps values with environment variables:
| `LLAMA_SERVER_BIN_PATH` | to change the server binary path, default: `../../../build/bin/llama-server` |
| `DEBUG` | to enable steps and server verbose mode `--verbose` |
| `N_GPU_LAYERS` | number of model layers to offload to VRAM `-ngl --n-gpu-layers` |
| `LLAMA_CACHE` | by default server tests re-download models to the `tmp` subfolder. Set this to your cache (e.g. `$HOME/Library/Caches/llama.cpp` on Mac or `$HOME/.cache/llama.cpp` on Unix) to avoid this |
To run slow tests:
To run slow tests (will download many models, make sure to set `LLAMA_CACHE` if needed):
```shell
SLOW_TESTS=1 ./tests.sh
@ -44,10 +45,16 @@ To run with stdout/stderr display in real time (verbose output, but useful for d
DEBUG=1 ./tests.sh -s -v -x
```
To run single test unit:
To run all the tests in a file:
```shell
./tests.sh unit/test_{name of test case here}.py -v -x
./tests.sh unit/test_chat_completion.py.py -v -x
```
To run a single test:
```shell
./tests.sh unit/test_chat_completion.py::test_invalid_chat_completion_req
```
Hint: You can compile and run test in single command, useful for local developement:

4
examples/server/tests/pytest.ini Normal file
View file

@ -0,0 +1,4 @@
[pytest]
markers =
slow: marks tests as slow (deselect with '-m "not slow"')
serial

11
examples/server/tests/tests.sh
View file

@ -6,9 +6,18 @@ cd $SCRIPT_DIR
set -eu
if [[ "${SLOW_TESTS:-0}" == 1 ]]; then
# Slow tests for tool calls need quite a few models ahead of time to avoid timing out.
python $SCRIPT_DIR/../../../scripts/fetch_server_test_models.py
fi
if [ $# -lt 1 ]
then
pytest -v -x
if [[ "${SLOW_TESTS:-0}" == 1 ]]; then
pytest -v -x
else
pytest -v -x -m "not slow"
fi
else
pytest "$@"
fi

21
examples/server/tests/unit/test_chat_completion.py
View file

@ -2,7 +2,7 @@ import pytest
from openai import OpenAI
from utils import *
server = ServerPreset.tinyllama2()
server: ServerProcess
@pytest.fixture(autouse=True)
def create_server():
@ -13,8 +13,8 @@ def create_server():
@pytest.mark.parametrize(
"model,system_prompt,user_prompt,max_tokens,re_content,n_prompt,n_predicted,finish_reason,jinja,chat_template",
[
(None, "Book", "What is the best book", 8, "(Suddenly)+", 77, 8, "length", False, None),
(None, "Book", "What is the best book", 8, "(Suddenly)+", 77, 8, "length", True, None),
(None, "Book", "What is the best book", 8, "(Suddenly)+|\\{ \" Sarax.", 77, 8, "length", False, None),
(None, "Book", "What is the best book", 8, "(Suddenly)+|\\{ \" Sarax.", 77, 8, "length", True, None),
(None, "Book", "What is the best book", 8, "^ blue", 23, 8, "length", True, "This is not a chat template, it is"),
("codellama70b", "You are a coding assistant.", "Write the fibonacci function in c++.", 128, "(Aside|she|felter|alonger)+", 104, 64, "length", False, None),
("codellama70b", "You are a coding assistant.", "Write the fibonacci function in c++.", 128, "(Aside|she|felter|alonger)+", 104, 64, "length", True, None),
@ -121,6 +121,21 @@ def test_chat_template():
assert res.body["__verbose"]["prompt"] == "<s> <|start_header_id|>system<|end_header_id|>\n\nBook<|eot_id|><|start_header_id|>user<|end_header_id|>\n\nWhat is the best book<|eot_id|><|start_header_id|>assistant<|end_header_id|>\n\n"
def test_apply_chat_template():
global server
server.chat_template = "command-r"
server.start()
res = server.make_request("POST", "/apply-template", data={
"messages": [
{"role": "system", "content": "You are a test."},
{"role": "user", "content":"Hi there"},
]
})
assert res.status_code == 200
assert "prompt" in res.body
assert res.body["prompt"] == "<|START_OF_TURN_TOKEN|><|SYSTEM_TOKEN|>You are a test.<|END_OF_TURN_TOKEN|><|START_OF_TURN_TOKEN|><|USER_TOKEN|>Hi there<|END_OF_TURN_TOKEN|><|START_OF_TURN_TOKEN|><|CHATBOT_TOKEN|>"
@pytest.mark.parametrize("response_format,n_predicted,re_content", [
({"type": "json_object", "schema": {"const": "42"}}, 6, "\"42\""),
({"type": "json_object", "schema": {"items": [{"type": "integer"}]}}, 10, "[ -3000 ]"),

4
examples/server/tests/unit/test_completion.py
View file

@ -87,7 +87,7 @@ def test_completion_stream_vs_non_stream():
assert content_stream == res_non_stream.body["content"]
def test_completion_stream_with_openai_library():
def test_completion_with_openai_library():
global server
server.start()
client = OpenAI(api_key="dummy", base_url=f"http://{server.server_host}:{server.server_port}/v1")
@ -102,7 +102,7 @@ def test_completion_stream_with_openai_library():
assert match_regex("(going|bed)+", res.choices[0].text)
def test_completion_with_openai_library():
def test_completion_stream_with_openai_library():
global server
server.start()
client = OpenAI(api_key="dummy", base_url=f"http://{server.server_host}:{server.server_port}/v1")

352
examples/server/tests/unit/test_tool_call.py Normal file
View file

@ -0,0 +1,352 @@
import pytest
from utils import *
server: ServerProcess
TIMEOUT_SERVER_START = 15*60
TIMEOUT_HTTP_REQUEST = 60
@pytest.fixture(autouse=True)
def create_server():
global server
server = ServerPreset.tinyllama2()
server.model_alias = "tinyllama-2-tool-call"
server.server_port = 8081
TEST_TOOL = {
"type":"function",
"function": {
"name": "test",
"description": "",
"parameters": {
"type": "object",
"properties": {
"success": {"type": "boolean", "const": True},
},
"required": ["success"]
}
}
}
PYTHON_TOOL = {
"type": "function",
"function": {
"name": "python",
"description": "Runs code in an ipython interpreter and returns the result of the execution after 60 seconds.",
"parameters": {
"type": "object",
"properties": {
"code": {
"type": "string",
"description": "The code to run in the ipython interpreter."
}
},
"required": ["code"]
}
}
}
WEATHER_TOOL = {
"type":"function",
"function":{
"name":"get_current_weather",
"description":"Get the current weather in a given location",
"parameters":{
"type":"object",
"properties":{
"location":{
"type":"string",
"description":"The city and country/state, e.g. 'San Francisco, CA', or 'Paris, France'"
}
},
"required":["location"]
}
}
}
def do_test_completion_with_required_tool_tiny(template_name: str, tool: dict, argument_key: str | None):
n_predict = 512
global server
# server = ServerPreset.stories15m_moe()
server.jinja = True
server.n_predict = n_predict
server.chat_template_file = f'../../../models/templates/{template_name}.jinja'
server.start(timeout_seconds=TIMEOUT_SERVER_START)
res = server.make_request("POST", "/chat/completions", data={
"max_tokens": n_predict,
"messages": [
{"role": "system", "content": "You are a coding assistant."},
{"role": "user", "content": "Write an example"},
],
"tool_choice": "required",
"tools": [tool],
"parallel_tool_calls": False,
"temperature": 0.0,
"top_k": 1,
"top_p": 1.0,
})
assert res.status_code == 200, f"Expected status code 200, got {res.status_code}"
choice = res.body["choices"][0]
tool_calls = choice["message"].get("tool_calls")
assert tool_calls and len(tool_calls) == 1, f'Expected 1 tool call in {choice["message"]}'
tool_call = tool_calls[0]
expected_function_name = "python" if tool["type"] == "code_interpreter" else tool["function"]["name"]
assert expected_function_name == tool_call["function"]["name"]
actual_arguments = tool_call["function"]["arguments"]
assert isinstance(actual_arguments, str)
if argument_key is not None:
actual_arguments = json.loads(actual_arguments)
assert argument_key in actual_arguments, f"tool arguments: {json.dumps(actual_arguments)}, expected: {argument_key}"
@pytest.mark.parametrize("template_name,tool,argument_key", [
("google-gemma-2-2b-it", TEST_TOOL, "success"),
("meta-llama-Llama-3.3-70B-Instruct", TEST_TOOL, "success"),
("meta-llama-Llama-3.3-70B-Instruct", PYTHON_TOOL, "code"),
])
def test_completion_with_required_tool_tiny_fast(template_name: str, tool: dict, argument_key: str | None):
do_test_completion_with_required_tool_tiny(template_name, tool, argument_key)
@pytest.mark.slow
@pytest.mark.parametrize("template_name,tool,argument_key", [
("meta-llama-Llama-3.1-8B-Instruct", TEST_TOOL, "success"),
("meta-llama-Llama-3.1-8B-Instruct", PYTHON_TOOL, "code"),
("meetkai-functionary-medium-v3.1", TEST_TOOL, "success"),
("meetkai-functionary-medium-v3.1", PYTHON_TOOL, "code"),
("meetkai-functionary-medium-v3.2", TEST_TOOL, "success"),
("meetkai-functionary-medium-v3.2", PYTHON_TOOL, "code"),
("NousResearch-Hermes-2-Pro-Llama-3-8B-tool_use", TEST_TOOL, "success"),
("NousResearch-Hermes-2-Pro-Llama-3-8B-tool_use", PYTHON_TOOL, "code"),
("meta-llama-Llama-3.2-3B-Instruct", TEST_TOOL, "success"),
("meta-llama-Llama-3.2-3B-Instruct", PYTHON_TOOL, "code"),
("mistralai-Mistral-Nemo-Instruct-2407", TEST_TOOL, "success"),
("mistralai-Mistral-Nemo-Instruct-2407", PYTHON_TOOL, "code"),
("NousResearch-Hermes-3-Llama-3.1-8B-tool_use", TEST_TOOL, "success"),
("NousResearch-Hermes-3-Llama-3.1-8B-tool_use", PYTHON_TOOL, "code"),
("deepseek-ai-DeepSeek-R1-Distill-Llama-8B", TEST_TOOL, "success"),
("deepseek-ai-DeepSeek-R1-Distill-Llama-8B", PYTHON_TOOL, "code"),
("fireworks-ai-llama-3-firefunction-v2", TEST_TOOL, "success"),
("fireworks-ai-llama-3-firefunction-v2", PYTHON_TOOL, "code"),
])
def test_completion_with_required_tool_tiny_slow(template_name: str, tool: dict, argument_key: str | None):
do_test_completion_with_required_tool_tiny(template_name, tool, argument_key)
@pytest.mark.slow
@pytest.mark.parametrize("tool,argument_key,hf_repo,template_override", [
(TEST_TOOL, "success", "bartowski/Meta-Llama-3.1-8B-Instruct-GGUF:Q4_K_M", None),
(PYTHON_TOOL, "code", "bartowski/Meta-Llama-3.1-8B-Instruct-GGUF:Q4_K_M", None),
(TEST_TOOL, "success", "bartowski/gemma-2-2b-it-GGUF:Q4_K_M", None),
(PYTHON_TOOL, "code", "bartowski/gemma-2-2b-it-GGUF:Q4_K_M", None),
(TEST_TOOL, "success", "bartowski/Phi-3.5-mini-instruct-GGUF:Q4_K_M", None),
(PYTHON_TOOL, "code", "bartowski/Phi-3.5-mini-instruct-GGUF:Q4_K_M", None),
(TEST_TOOL, "success", "bartowski/Qwen2.5-7B-Instruct-GGUF:Q4_K_M", None),
(PYTHON_TOOL, "code", "bartowski/Qwen2.5-7B-Instruct-GGUF:Q4_K_M", None),
(TEST_TOOL, "success", "bartowski/Hermes-2-Pro-Llama-3-8B-GGUF:Q4_K_M", ("NousResearch/Hermes-2-Pro-Llama-3-8B", "tool_use")),
(PYTHON_TOOL, "code", "bartowski/Hermes-2-Pro-Llama-3-8B-GGUF:Q4_K_M", ("NousResearch/Hermes-2-Pro-Llama-3-8B", "tool_use")),
(TEST_TOOL, "success", "bartowski/Hermes-3-Llama-3.1-8B-GGUF:Q4_K_M", ("NousResearch/Hermes-3-Llama-3.1-8B", "tool_use")),
(PYTHON_TOOL, "code", "bartowski/Hermes-3-Llama-3.1-8B-GGUF:Q4_K_M", ("NousResearch/Hermes-3-Llama-3.1-8B", "tool_use")),
(TEST_TOOL, "success", "bartowski/Mistral-Nemo-Instruct-2407-GGUF:Q4_K_M", None),
(PYTHON_TOOL, "code", "bartowski/Mistral-Nemo-Instruct-2407-GGUF:Q4_K_M", None),
(TEST_TOOL, "success", "bartowski/functionary-small-v3.2-GGUF:Q8_0", ("meetkai/functionary-medium-v3.2", None)),
(PYTHON_TOOL, "code", "bartowski/functionary-small-v3.2-GGUF:Q8_0", ("meetkai/functionary-medium-v3.2", None)),
(TEST_TOOL, "success", "bartowski/Llama-3.2-3B-Instruct-GGUF:Q4_K_M", ("meta-llama/Llama-3.2-3B-Instruct", None)),
(PYTHON_TOOL, "code", "bartowski/Llama-3.2-3B-Instruct-GGUF:Q4_K_M", ("meta-llama/Llama-3.2-3B-Instruct", None)),
(TEST_TOOL, "success", "bartowski/Llama-3.2-1B-Instruct-GGUF:Q4_K_M", ("meta-llama/Llama-3.2-3B-Instruct", None)),
(PYTHON_TOOL, "code", "bartowski/Llama-3.2-1B-Instruct-GGUF:Q4_K_M", ("meta-llama/Llama-3.2-3B-Instruct", None)),
# TODO: fix these
# (TEST_TOOL, "success", "bartowski/DeepSeek-R1-Distill-Qwen-7B-GGUF:Q4_K_M", None),
# (PYTHON_TOOL, "code", "bartowski/DeepSeek-R1-Distill-Qwen-7B-GGUF:Q4_K_M", None),
])
def test_completion_with_required_tool_real_model(tool: dict, argument_key: str | None, hf_repo: str, template_override: Tuple[str, str | None] | None):
n_predict = 512
server.n_slots = 1
server.jinja = True
server.n_ctx = 8192
server.n_predict = n_predict
server.model_hf_repo = hf_repo
server.model_hf_file = None
if template_override:
(template_hf_repo, template_variant) = template_override
server.chat_template_file = f"../../../models/templates/{template_hf_repo.replace('/', '-') + ('-' + template_variant if template_variant else '')}.jinja"
assert os.path.exists(server.chat_template_file), f"Template file {server.chat_template_file} does not exist. Run `python scripts/get_chat_template.py {template_hf_repo} {template_variant} > {server.chat_template_file}` to download the template."
server.start(timeout_seconds=TIMEOUT_SERVER_START)
res = server.make_request("POST", "/chat/completions", data={
"max_tokens": n_predict,
"messages": [
{"role": "system", "content": "You are a coding assistant."},
{"role": "user", "content": "Write an example"},
],
"tool_choice": "required",
"tools": [tool],
"parallel_tool_calls": False,
"temperature": 0.0,
"top_k": 1,
"top_p": 1.0,
}, timeout=TIMEOUT_HTTP_REQUEST)
assert res.status_code == 200, f"Expected status code 200, got {res.status_code}"
choice = res.body["choices"][0]
tool_calls = choice["message"].get("tool_calls")
assert tool_calls and len(tool_calls) == 1, f'Expected 1 tool call in {choice["message"]}'
tool_call = tool_calls[0]
expected_function_name = "python" if tool["type"] == "code_interpreter" else tool["function"]["name"]
assert expected_function_name == tool_call["function"]["name"]
actual_arguments = tool_call["function"]["arguments"]
assert isinstance(actual_arguments, str)
if argument_key is not None:
actual_arguments = json.loads(actual_arguments)
assert argument_key in actual_arguments, f"tool arguments: {json.dumps(actual_arguments)}, expected: {argument_key}"
def do_test_completion_without_tool_call(template_name: str, n_predict: int, tools: list[dict], tool_choice: str | None):
global server
server.jinja = True
server.n_predict = n_predict
server.chat_template_file = f'../../../models/templates/{template_name}.jinja'
server.start(timeout_seconds=TIMEOUT_SERVER_START)
res = server.make_request("POST", "/chat/completions", data={
"max_tokens": n_predict,
"messages": [
{"role": "system", "content": "You are a coding assistant."},
{"role": "user", "content": "say hello world with python"},
],
"tools": tools if tools else None,
"tool_choice": tool_choice,
"temperature": 0.0,
"top_k": 1,
"top_p": 1.0,
}, timeout=TIMEOUT_HTTP_REQUEST)
assert res.status_code == 200, f"Expected status code 200, got {res.status_code}"
choice = res.body["choices"][0]
assert choice["message"].get("tool_calls") is None, f'Expected no tool call in {choice["message"]}'
@pytest.mark.parametrize("template_name,n_predict,tools,tool_choice", [
("meta-llama-Llama-3.3-70B-Instruct", 128, [], None),
("meta-llama-Llama-3.3-70B-Instruct", 128, [TEST_TOOL], None),
("meta-llama-Llama-3.3-70B-Instruct", 128, [PYTHON_TOOL], 'none'),
])
def test_completion_without_tool_call_fast(template_name: str, n_predict: int, tools: list[dict], tool_choice: str | None):
do_test_completion_without_tool_call(template_name, n_predict, tools, tool_choice)
@pytest.mark.slow
@pytest.mark.parametrize("template_name,n_predict,tools,tool_choice", [
("meetkai-functionary-medium-v3.2", 256, [], None),
("meetkai-functionary-medium-v3.2", 256, [TEST_TOOL], None),
("meetkai-functionary-medium-v3.2", 256, [PYTHON_TOOL], 'none'),
("meetkai-functionary-medium-v3.1", 256, [], None),
("meetkai-functionary-medium-v3.1", 256, [TEST_TOOL], None),
("meetkai-functionary-medium-v3.1", 256, [PYTHON_TOOL], 'none'),
("meta-llama-Llama-3.2-3B-Instruct", 256, [], None),
("meta-llama-Llama-3.2-3B-Instruct", 256, [TEST_TOOL], None),
("meta-llama-Llama-3.2-3B-Instruct", 256, [PYTHON_TOOL], 'none'),
])
def test_completion_without_tool_call_slow(template_name: str, n_predict: int, tools: list[dict], tool_choice: str | None):
do_test_completion_without_tool_call(template_name, n_predict, tools, tool_choice)
@pytest.mark.slow
@pytest.mark.parametrize("hf_repo,template_override", [
("bartowski/Meta-Llama-3.1-8B-Instruct-GGUF:Q4_K_M", None),
("bartowski/gemma-2-2b-it-GGUF:Q4_K_M", None),
("bartowski/Phi-3.5-mini-instruct-GGUF:Q4_K_M", None),
("bartowski/Qwen2.5-7B-Instruct-GGUF:Q4_K_M", None),
("bartowski/Hermes-2-Pro-Llama-3-8B-GGUF:Q4_K_M", ("NousResearch/Hermes-2-Pro-Llama-3-8B", "tool_use")),
("bartowski/Hermes-3-Llama-3.1-8B-GGUF:Q4_K_M", ("NousResearch/Hermes-3-Llama-3.1-8B", "tool_use")),
("bartowski/Mistral-Nemo-Instruct-2407-GGUF:Q4_K_M", None),
("bartowski/functionary-small-v3.2-GGUF:Q8_0", ("meetkai/functionary-medium-v3.2", None)),
("bartowski/Llama-3.2-3B-Instruct-GGUF:Q4_K_M", ("meta-llama/Llama-3.2-3B-Instruct", None)),
# ("bartowski/Llama-3.2-1B-Instruct-GGUF:Q4_K_M", ("meta-llama/Llama-3.2-3B-Instruct", None)),
# ("bartowski/DeepSeek-R1-Distill-Qwen-7B-GGUF:Q4_K_M", None),
])
def test_weather_tool_call(hf_repo: str, template_override: Tuple[str, str | None] | None):
global server
server.n_slots = 1
server.jinja = True
server.n_ctx = 8192
server.n_predict = 512
server.model_hf_repo = hf_repo
server.model_hf_file = None
if template_override:
(template_hf_repo, template_variant) = template_override
server.chat_template_file = f"../../../models/templates/{template_hf_repo.replace('/', '-') + ('-' + template_variant if template_variant else '')}.jinja"
assert os.path.exists(server.chat_template_file), f"Template file {server.chat_template_file} does not exist. Run `python scripts/get_chat_template.py {template_hf_repo} {template_variant} > {server.chat_template_file}` to download the template."
server.start(timeout_seconds=TIMEOUT_SERVER_START)
res = server.make_request("POST", "/chat/completions", data={
"max_tokens": 256,
"messages": [
{"role": "user", "content": "What is the weather in Istanbul?"},
],
"tools": [WEATHER_TOOL],
}, timeout=TIMEOUT_HTTP_REQUEST)
assert res.status_code == 200, f"Expected status code 200, got {res.status_code}"
choice = res.body["choices"][0]
tool_calls = choice["message"].get("tool_calls")
assert tool_calls and len(tool_calls) == 1, f'Expected 1 tool call in {choice["message"]}'
tool_call = tool_calls[0]
assert tool_call["function"]["name"] == WEATHER_TOOL["function"]["name"]
actual_arguments = json.loads(tool_call["function"]["arguments"])
assert 'location' in actual_arguments, f"location not found in {json.dumps(actual_arguments)}"
location = actual_arguments["location"]
assert isinstance(location, str), f"Expected location to be a string, got {type(location)}: {json.dumps(location)}"
assert re.match('^Istanbul(, (TR|Turkey|Türkiye))?$', location), f'Expected Istanbul for location, got {location}'
@pytest.mark.slow
@pytest.mark.parametrize("expected_arguments_override,hf_repo,template_override", [
(None, "bartowski/gemma-2-2b-it-GGUF:Q4_K_M", None),
(None, "bartowski/Phi-3.5-mini-instruct-GGUF:Q4_K_M", None),
(None, "bartowski/functionary-small-v3.2-GGUF:Q8_0", ("meetkai-functionary-medium-v3.2", None)),
('{"code":"print("}', "bartowski/Meta-Llama-3.1-8B-Instruct-GGUF:Q4_K_M", None),
(None, "bartowski/Llama-3.2-1B-Instruct-GGUF:Q4_K_M", ("meta-llama-Llama-3.2-3B-Instruct", None)),
('{"code":"print("}', "bartowski/Llama-3.2-3B-Instruct-GGUF:Q4_K_M", ("meta-llama-Llama-3.2-3B-Instruct", None)),
(None, "bartowski/Qwen2.5-7B-Instruct-GGUF:Q4_K_M", None),
(None, "bartowski/Hermes-2-Pro-Llama-3-8B-GGUF:Q4_K_M", ("NousResearch/Hermes-2-Pro-Llama-3-8B", "tool_use")),
(None, "bartowski/Hermes-3-Llama-3.1-8B-GGUF:Q4_K_M", ("NousResearch-Hermes-3-Llama-3.1-8B", "tool_use")),
(None, "bartowski/Mistral-Nemo-Instruct-2407-GGUF:Q4_K_M", None),
# (None, "bartowski/DeepSeek-R1-Distill-Qwen-7B-GGUF:Q4_K_M", None),
])
def test_hello_world_tool_call(expected_arguments_override: str | None, hf_repo: str, template_override: Tuple[str, str | None] | None):
global server
server.n_slots = 1
server.jinja = True
server.n_ctx = 8192
server.n_predict = 128
server.model_hf_repo = hf_repo
server.model_hf_file = None
if template_override:
(template_hf_repo, template_variant) = template_override
server.chat_template_file = f"../../../models/templates/{template_hf_repo.replace('/', '-') + ('-' + template_variant if template_variant else '')}.jinja"
assert os.path.exists(server.chat_template_file), f"Template file {server.chat_template_file} does not exist. Run `python scripts/get_chat_template.py {template_hf_repo} {template_variant} > {server.chat_template_file}` to download the template."
server.start(timeout_seconds=TIMEOUT_SERVER_START)
res = server.make_request("POST", "/chat/completions", data={
"max_tokens": 256,
"messages": [
{"role": "system", "content": "You are a coding assistant."},
{"role": "user", "content": "say hello world with python"},
],
"tools": [PYTHON_TOOL],
# Note: without these greedy params, Functionary v3.2 writes `def hello_world():\n print("Hello, World!")\nhello_world()` which is correct but a pain to test.
"temperature": 0.0,
"top_k": 1,
"top_p": 1.0,
}, timeout=TIMEOUT_HTTP_REQUEST)
assert res.status_code == 200, f"Expected status code 200, got {res.status_code}"
choice = res.body["choices"][0]
tool_calls = choice["message"].get("tool_calls")
assert tool_calls and len(tool_calls) == 1, f'Expected 1 tool call in {choice["message"]}'
tool_call = tool_calls[0]
assert tool_call["function"]["name"] == PYTHON_TOOL["function"]["name"]
actual_arguments = tool_call["function"]["arguments"]
if expected_arguments_override is not None:
assert actual_arguments == expected_arguments_override
else:
actual_arguments = json.loads(actual_arguments)
assert 'code' in actual_arguments, f"code not found in {json.dumps(actual_arguments)}"
code = actual_arguments["code"]
assert isinstance(code, str), f"Expected code to be a string, got {type(code)}: {json.dumps(code)}"
assert re.match(r'''print\(("[Hh]ello,? [Ww]orld!?"|'[Hh]ello,? [Ww]orld!?')\)''', code), f'Expected hello world, got {code}'

6
examples/server/tests/utils.py
View file

@ -26,7 +26,7 @@ from re import RegexFlag
import wget
DEFAULT_HTTP_TIMEOUT = 10 if "LLAMA_SANITIZE" not in os.environ else 30
DEFAULT_HTTP_TIMEOUT = 12 if "LLAMA_SANITIZE" not in os.environ else 30
class ServerResponse:
@ -41,7 +41,7 @@ class ServerProcess:
server_port: int = 8080
server_host: str = "127.0.0.1"
model_hf_repo: str = "ggml-org/models"
model_hf_file: str = "tinyllamas/stories260K.gguf"
model_hf_file: str | None = "tinyllamas/stories260K.gguf"
model_alias: str = "tinyllama-2"
temperature: float = 0.8
seed: int = 42
@ -191,7 +191,7 @@ class ServerProcess:
creationflags=flags,
stdout=sys.stdout,
stderr=sys.stdout,
env={**os.environ, "LLAMA_CACHE": "tmp"},
env={**os.environ, "LLAMA_CACHE": "tmp"} if "LLAMA_CACHE" not in os.environ else None,
)
server_instances.add(self)

71
examples/server/utils.hpp
View file

@ -17,6 +17,7 @@
#define JSON_ASSERT GGML_ASSERT
#include "json.hpp"
#include "minja.hpp"
#include "chat.hpp"
#include "chat-template.hpp"
#include <random>
@ -376,7 +377,7 @@ inline std::string format_chat(const common_chat_template & tmpl, const std::vec
throw std::runtime_error("Missing 'content' (ref: https://github.com/ggerganov/llama.cpp/issues/8367)");
}
chat.push_back({role, content});
chat.push_back({role, content, /* tool_calls= */ {}});
}
const auto formatted_chat = common_chat_apply_template(tmpl, chat, true, /* use_jinja= */ false);
@ -580,21 +581,30 @@ static json oaicompat_completion_params_parse(const json & body) {
static json oaicompat_completion_params_parse(
const json & body, /* openai api json semantics */
const common_chat_template & tmpl,
bool use_jinja)
bool use_jinja,
const common_chat_templates & chat_templates)
{
json llama_params;
const auto & tmpl = body.contains("tools") && chat_templates.template_tool_use
? *chat_templates.template_tool_use
: *chat_templates.template_default;
auto tools = json_value(body, "tools", json());
auto has_tools = tools.is_array() && !tools.empty();
auto stream = json_value(body, "stream", false);
if (has_tools) {
if (use_jinja) {
LOG_WRN("tools param is not fully supported yet\n");
} else {
if (tools.is_array() && !tools.empty()) {
if (stream) {
throw std::runtime_error("Cannot use tools with stream");
}
if (!use_jinja) {
throw std::runtime_error("tools param requires --jinja flag");
}
}
if (!use_jinja) {
if (body.contains("tool_choice") && !body.at("tool_choice").is_null()) {
throw std::runtime_error("Unsupported param: tool_choice");
}
}
// Handle "stop" field
if (body.contains("stop") && body.at("stop").is_string()) {
@ -619,7 +629,42 @@ static json oaicompat_completion_params_parse(
// Apply chat template to the list of messages
if (use_jinja) {
llama_params["prompt"] = tmpl.apply(body.at("messages"), tools, /* add_generation_prompt= */ true);
auto tool_choice = json_value(body, "tool_choice", std::string("auto"));
if (tool_choice != "none" && tool_choice != "auto" && tool_choice != "required") {
throw std::runtime_error("Invalid tool_choice: " + tool_choice);
}
if (tool_choice != "none" && llama_params.contains("grammar")) {
throw std::runtime_error("Cannot use custom grammar constraints with tools.");
}
common_chat_inputs inputs;
inputs.messages = body.at("messages");
inputs.tools = tools;
inputs.tool_choice = tool_choice;
inputs.parallel_tool_calls = json_value(body, "parallel_tool_calls", false);
if (inputs.parallel_tool_calls && !tmpl.original_caps().supports_parallel_tool_calls) {
LOG_DBG("Disabling parallel_tool_calls because the template does not support it\n");
inputs.parallel_tool_calls = false;
}
inputs.stream = stream;
// TODO: support mixing schema w/ tools beyond generic format.
inputs.json_schema = json_value(llama_params, "json_schema", json());
auto chat_params = common_chat_params_init(tmpl, inputs);
llama_params["chat_format"] = static_cast<int>(chat_params.format);
llama_params["prompt"] = chat_params.prompt;
llama_params["grammar"] = chat_params.grammar;
llama_params["grammar_lazy"] = chat_params.grammar_lazy;
auto grammar_triggers = json::array();
for (const auto & trigger : chat_params.grammar_triggers) {
grammar_triggers.push_back({
{"word", trigger.word},
{"at_start", trigger.at_start},
});
}
llama_params["grammar_triggers"] = grammar_triggers;
for (const auto & stop : chat_params.additional_stops) {
llama_params["stop"].push_back(stop);
}
} else {
llama_params["prompt"] = format_chat(tmpl, body.at("messages"));
}
@ -638,14 +683,6 @@ static json oaicompat_completion_params_parse(
throw std::runtime_error("top_logprobs requires logprobs to be set to true");
}
// Params supported by OAI but unsupported by llama.cpp
static const std::vector<std::string> unsupported_params { "tool_choice" };
for (const auto & param : unsupported_params) {
if (body.contains(param)) {
throw std::runtime_error("Unsupported param: " + param);
}
}
// Copy remaining properties to llama_params
// This allows user to use llama.cpp-specific params like "mirostat", ... via OAI endpoint.
// See "launch_slot_with_task()" for a complete list of params supported by llama.cpp

0
examples/main-cmake-pkg/.gitignore → examples/simple-cmake-pkg/.gitignore vendored
View file

11
examples/simple-cmake-pkg/CMakeLists.txt Normal file
View file

@ -0,0 +1,11 @@
cmake_minimum_required(VERSION 3.12)
project(llama-simple-cmake-pkg)
set(TARGET llama-simple-cmake-pkg)
find_package(Llama REQUIRED)
add_executable(${TARGET} ${CMAKE_CURRENT_LIST_DIR}/../simple/simple.cpp)
install(TARGETS ${TARGET} RUNTIME)
target_link_libraries(${TARGET} PRIVATE llama ggml::all ${CMAKE_THREAD_LIBS_INIT})
target_compile_features(${TARGET} PRIVATE cxx_std_17)

34
examples/simple-cmake-pkg/README.md Normal file
View file

@ -0,0 +1,34 @@
# llama.cpp/example/simple-cmake-pkg
This program builds [simple](../simple) using a relocatable CMake package. It serves as an example of using the `find_package()` CMake command to conveniently include [llama.cpp](https://github.com/ggerganov/llama.cpp) in projects which live outside of the source tree.
## Building
Because this example is "outside of the source tree", it is important to first build/install llama.cpp using CMake. An example is provided here, but please see the [llama.cpp build instructions](../..) for more detailed build instructions.
### Considerations
When hardware acceleration libraries are used (e.g. CUDA, Metal, Vulkan, etc.), the appropriate dependencies will be searched for automatically. So, for example, when finding a package
### Build llama.cpp and install to llama.cpp/inst
```sh
git clone https://github.com/ggerganov/llama.cpp
cd llama.cpp
cmake -S . -B build
cmake --build build
cmake --install build --prefix inst
### Build simple-cmake-pkg
```sh
cd examples/simple-cmake-pkg
cmake -S . -B build -DCMAKE_PREFIX_PATH=../../inst/lib/cmake
cmake --build build
```
### Run simple-cmake-pkg
```sh
./build/llama-simple-cmake-pkg -m ./models/llama-7b-v2/ggml-model-f16.gguf "Hello my name is"
```

71
ggml/CMakeLists.txt
View file

@ -267,3 +267,74 @@ if (GGML_STANDALONE)
install(FILES ${CMAKE_CURRENT_BINARY_DIR}/ggml.pc
DESTINATION share/pkgconfig)
endif()
#
# Create CMake package
#
# Generate version info based on git commit.
find_program(GIT_EXE NAMES git git.exe REQUIRED NO_CMAKE_FIND_ROOT_PATH)
execute_process(COMMAND ${GIT_EXE} rev-list --count HEAD
WORKING_DIRECTORY ${CMAKE_CURRENT_SOURCE_DIR}
OUTPUT_VARIABLE GGML_BUILD_NUMBER
OUTPUT_STRIP_TRAILING_WHITESPACE
)
if(GGML_BUILD_NUMBER EQUAL 1)
message(WARNING "GGML build version fixed at 1 likely due to a shallow clone.")
endif()
execute_process(COMMAND ${GIT_EXE} rev-parse --short HEAD
WORKING_DIRECTORY ${CMAKE_CURRENT_SOURCE_DIR}
OUTPUT_VARIABLE GGML_BUILD_COMMIT
OUTPUT_STRIP_TRAILING_WHITESPACE
)
# Capture variables prefixed with GGML_.
set(variable_set_statements
"
####### Expanded from @GGML_VARIABLES_EXPANED@ by configure_package_config_file() #######
####### Any changes to this file will be overwritten by the next CMake run #######
")
set(GGML_SHARED_LIB ${BUILD_SHARED_LIBS})
get_cmake_property(all_variables VARIABLES)
foreach(variable_name IN LISTS all_variables)
if(variable_name MATCHES "^GGML_")
string(REPLACE ";" "\\;"
variable_value "${${variable_name}}")
set(variable_set_statements
"${variable_set_statements}set(${variable_name} \"${variable_value}\")\n")
endif()
endforeach()
set(GGML_VARIABLES_EXPANDED ${variable_set_statements})
# Create the CMake package and set install location.
set(GGML_INSTALL_VERSION 0.0.${GGML_BUILD_NUMBER})
set(GGML_INCLUDE_INSTALL_DIR ${CMAKE_INSTALL_INCLUDEDIR} CACHE PATH "Location of header files")
set(GGML_LIB_INSTALL_DIR ${CMAKE_INSTALL_LIBDIR} CACHE PATH "Location of library files")
set(GGML_BIN_INSTALL_DIR ${CMAKE_INSTALL_BINDIR} CACHE PATH "Location of binary files")
configure_package_config_file(
${CMAKE_CURRENT_SOURCE_DIR}/cmake/ggml-config.cmake.in
${CMAKE_CURRENT_BINARY_DIR}/ggml-config.cmake
INSTALL_DESTINATION ${CMAKE_INSTALL_LIBDIR}/cmake/ggml
PATH_VARS GGML_INCLUDE_INSTALL_DIR
GGML_LIB_INSTALL_DIR
GGML_BIN_INSTALL_DIR)
write_basic_package_version_file(
${CMAKE_CURRENT_BINARY_DIR}/ggml-version.cmake
VERSION ${GGML_INSTALL_VERSION}
COMPATIBILITY SameMajorVersion)
install(FILES ${CMAKE_CURRENT_BINARY_DIR}/ggml-config.cmake
${CMAKE_CURRENT_BINARY_DIR}/ggml-version.cmake
DESTINATION ${CMAKE_INSTALL_LIBDIR}/cmake/ggml)

147
ggml/cmake/ggml-config.cmake.in Normal file
View file

@ -0,0 +1,147 @@
@GGML_VARIABLES_EXPANDED@
@PACKAGE_INIT@
set_and_check(GGML_INCLUDE_DIR "@PACKAGE_GGML_INCLUDE_INSTALL_DIR@")
set_and_check(GGML_LIB_DIR "@PACKAGE_GGML_LIB_INSTALL_DIR@")
set_and_check(GGML_BIN_DIR "@PACKAGE_GGML_BIN_INSTALL_DIR@")
find_package(Threads REQUIRED)
find_library(GGML_LIBRARY ggml
REQUIRED
HINTS ${GGML_LIB_DIR}
NO_CMAKE_FIND_ROOT_PATH)
add_library(ggml::ggml UNKNOWN IMPORTED)
set_target_properties(ggml::ggml
PROPERTIES
IMPORTED_LOCATION "${GGML_LIBRARY}")
find_library(GGML_BASE_LIBRARY ggml-base
REQUIRED
HINTS ${GGML_LIB_DIR}
NO_CMAKE_FIND_ROOT_PATH)
add_library(ggml::ggml-base UNKNOWN IMPORTED)
set_target_properties(ggml::ggml-base
PROPERTIES
IMPORTED_LOCATION "${GGML_BASE_LIBRARY}")
if (NOT GGML_SHARED_LIB)
if (APPLE AND GGML_ACCELERATE)
find_library(ACCELERATE_FRAMEWORK Accelerate REQUIRED)
list(APPEND GGML_CPU_INTERFACE_LINK_LIBRARIES ${ACCELERATE_FRAMEWORK})
endif()
if (GGML_OPENMP)
find_package(OpenMP REQUIRED)
list(APPEND GGML_CPU_INTERFACE_LINK_LIBRARIES OpenMP::OpenMP_C OpenMP::OpenMP_CXX)
endif()
if (GGML_CPU_HBM)
find_library(memkind memkind REQUIRED)
list(APPEND GGML_CPU_INTERFACE_LINK_LIBRARIES memkind)
endif()
if (GGML_BLAS)
find_package(BLAS REQUIRED)
list(APPEND GGML_CPU_INTERFACE_LINK_LIBRARIES ${BLAS_LIBRARIES})
list(APPEND GGML_CPU_INTERFACE_LINK_OPTIONS ${BLAS_LINKER_FLAGS})
endif()
if (GGML_CUDA)
find_package(CUDAToolkit REQUIRED)
endif()
if (GGML_METAL)
find_library(FOUNDATION_LIBRARY Foundation REQUIRED)
find_library(METAL_FRAMEWORK Metal REQUIRED)
find_library(METALKIT_FRAMEWORK MetalKit REQUIRED)
list(APPEND GGML_METAL_INTERFACE_LINK_LIBRARIES
${FOUNDATION_LIBRARY} ${METAL_FRAMEWORK} ${METALKIT_FRAMEWORK})
endif()
if (GGML_VULKAN)
find_package(Vulkan REQUIRED)
list(APPEND GGML_VULKAN_INTERFACE_LINK_LIBRARIES Vulkan::Vulkan)
endif()
if (GGML_HIP)
find_package(hip REQUIRED)
find_package(hipblas REQUIRED)
find_package(rocblas REQUIRED)
list(APPEND GGML_HIP_INTERFACE_LINK_LIBRARIES hip::host roc::rocblas roc::hipblas)
endif()
if (GGML_SYCL)
find_package(DNNL)
if (${DNNL_FOUND} AND GGML_SYCL_TARGET STREQUAL "INTEL")
list(APPEND GGML_SYCL_INTERFACE_LINK_LIBRARIES DNNL::dnnl)
endif()
if (WIN32)
find_package(IntelSYCL REQUIRED)
find_package(MKL REQUIRED)
list(APPEND GGML_SYCL_INTERFACE_LINK_LIBRARIES IntelSYCL::SYCL_CXX MKL::MKL MKL::MKL_SYCL)
endif()
endif()
endif()
set(_ggml_all_targets "")
foreach(_ggml_backend ${GGML_AVAILABLE_BACKENDS})
string(REPLACE "-" "_" _ggml_backend_pfx "${_ggml_backend}")
string(TOUPPER "${_ggml_backend_pfx}" _ggml_backend_pfx)
find_library(${_ggml_backend_pfx}_LIBRARY ${_ggml_backend}
REQUIRED
HINTS ${GGML_LIB_DIR}
NO_CMAKE_FIND_ROOT_PATH)
message(STATUS "Found ${${_ggml_backend_pfx}_LIBRARY}")
add_library(ggml::${_ggml_backend} UNKNOWN IMPORTED)
set_target_properties(ggml::${_ggml_backend}
PROPERTIES
INTERFACE_INCLUDE_DIRECTORIES "${GGML_INCLUDE_DIR}"
IMPORTED_LINK_INTERFACE_LANGUAGES "CXX"
IMPORTED_LOCATION "${${_ggml_backend_pfx}_LIBRARY}"
INTERFACE_COMPILE_FEATURES c_std_90
POSITION_INDEPENDENT_CODE ON)
string(REGEX MATCH "^ggml-cpu" is_cpu_variant "${_ggml_backend}")
if(is_cpu_variant)
list(APPEND GGML_CPU_INTERFACE_LINK_LIBRARIES "ggml::ggml" "ggml::ggml-base")
set_target_properties(ggml::${_ggml_backend}
PROPERTIES
INTERFACE_LINK_LIBRARIES "${GGML_CPU_INTERFACE_LINK_LIBRARIES}")
if(GGML_CPU_INTERFACE_LINK_OPTIONS)
set_target_properties(ggml::${_ggml_backend}
PROPERTIES
INTERFACE_LINK_OPTIONS "${GGML_CPU_INTERFACE_LINK_OPTIONS}")
endif()
else()
list(APPEND ${_ggml_backend_pfx}_INTERFACE_LINK_LIBRARIES "ggml::ggml" "ggml::ggml-base")
set_target_properties(ggml::${_ggml_backend}
PROPERTIES
INTERFACE_LINK_LIBRARIES "${${_ggml_backend_pfx}_INTERFACE_LINK_LIBRARIES}")
if(${_ggml_backend_pfx}_INTERFACE_LINK_OPTIONS)
set_target_properties(ggml::${_ggml_backend}
PROPERTIES
INTERFACE_LINK_OPTIONS "${${_ggml_backend_pfx}_INTERFACE_LINK_OPTIONS}")
endif()
endif()
list(APPEND _ggml_all_targets ggml::${_ggml_backend})
endforeach()
add_library(ggml::all INTERFACE IMPORTED)
set_target_properties(ggml::all
PROPERTIES
INTERFACE_LINK_LIBRARIES "${_ggml_all_targets}")
check_required_components(ggml)

25
ggml/src/CMakeLists.txt
View file

@ -93,12 +93,18 @@ endif()
if (GGML_CCACHE)
find_program(GGML_CCACHE_FOUND ccache)
find_program(GGML_SCCACHE_FOUND sccache)
if (GGML_CCACHE_FOUND)
if (GGML_CCACHE_FOUND OR GGML_SCCACHE_FOUND)
if(GGML_CCACHE_FOUND)
set(GGML_CCACHE_VARIANT ccache)
else()
set(GGML_CCACHE_VARIANT sccache)
endif()
# TODO: should not be set globally
set_property(GLOBAL PROPERTY RULE_LAUNCH_COMPILE ccache)
set_property(GLOBAL PROPERTY RULE_LAUNCH_COMPILE "${GGML_CCACHE_VARIANT}")
set(ENV{CCACHE_SLOPPINESS} time_macros)
message(STATUS "ccache found, compilation results will be cached. Disable with GGML_CCACHE=OFF.")
message(STATUS "${GGML_CCACHE_VARIANT} found, compilation results will be cached. Disable with GGML_CCACHE=OFF.")
else()
message(STATUS "Warning: ccache not found - consider installing it for faster compilation or disable this warning with GGML_CCACHE=OFF")
endif ()
@ -250,6 +256,17 @@ function(ggml_add_backend_library backend)
target_compile_definitions(${backend} PRIVATE GGML_BACKEND_BUILD)
target_compile_definitions(${backend} PUBLIC GGML_BACKEND_SHARED)
endif()
if(NOT GGML_AVAILABLE_BACKENDS)
set(GGML_AVAILABLE_BACKENDS "${backend}"
CACHE INTERNAL "List of backends for cmake package")
else()
list(FIND GGML_AVAILABLE_BACKENDS "${backend}" has_backend)
if(has_backend EQUAL -1)
set(GGML_AVAILABLE_BACKENDS "${GGML_AVAILABLE_BACKENDS};${backend}"
CACHE INTERNAL "List of backends for cmake package")
endif()
endif()
endfunction()
function(ggml_add_backend backend)
@ -297,7 +314,7 @@ if (GGML_CPU_ALL_VARIANTS)
# MSVC doesn't support AMX
ggml_add_cpu_backend_variant(sapphirerapids AVX F16C AVX2 FMA AVX512 AVX512_VBMI AVX512_VNNI AVX512_BF16 AMX_TILE AMX_INT8)
endif()
else ()
elseif (GGML_CPU)
ggml_add_cpu_backend_variant_impl("")
endif()

10
ggml/src/ggml-cpu/ggml-cpu.c
View file

@ -1302,7 +1302,7 @@ struct ggml_threadpool {
// these are atomic as an annotation for thread-sanitizer
atomic_bool stop; // Used for stopping the threadpool altogether
atomic_bool pause; // Used for pausing the threadpool or individual threads
atomic_bool abort; // Used for aborting processing of a graph
atomic_int abort; // Used for aborting processing of a graph
struct ggml_compute_state * workers; // per thread state
int n_threads_max; // number of threads in the pool
@ -13851,14 +13851,14 @@ static thread_ret_t ggml_graph_compute_thread(void * data) {
/*.threadpool=*/ tp,
};
for (int node_n = 0; node_n < cgraph->n_nodes && !tp->abort; node_n++) {
for (int node_n = 0; node_n < cgraph->n_nodes && atomic_load_explicit(&tp->abort, memory_order_relaxed) != node_n; node_n++) {
struct ggml_tensor * node = cgraph->nodes[node_n];
ggml_compute_forward(&params, node);
if (state->ith == 0 && cplan->abort_callback &&
cplan->abort_callback(cplan->abort_callback_data)) {
tp->abort = true;
atomic_store_explicit(&tp->abort, node_n + 1, memory_order_relaxed);
tp->ec = GGML_STATUS_ABORTED;
}
@ -14031,7 +14031,7 @@ static struct ggml_threadpool * ggml_threadpool_new_impl(
threadpool->current_chunk = 0;
threadpool->stop = false;
threadpool->pause = tpp->paused;
threadpool->abort = false;
threadpool->abort = -1;
threadpool->workers = NULL;
threadpool->n_threads_max = tpp->n_threads;
threadpool->n_threads_cur = tpp->n_threads;
@ -14110,7 +14110,7 @@ enum ggml_status ggml_graph_compute(struct ggml_cgraph * cgraph, struct ggml_cpl
threadpool->cgraph = cgraph;
threadpool->cplan = cplan;
threadpool->current_chunk = 0;
threadpool->abort = false;
threadpool->abort = -1;
threadpool->ec = GGML_STATUS_SUCCESS;
}

80
ggml/src/ggml-cuda/common.cuh
View file

@ -46,20 +46,20 @@
#define GGML_CUDA_CC_VOLTA 700
#define GGML_CUDA_CC_TURING 750
#define GGML_CUDA_CC_AMPERE 800
#define GGML_CUDA_CC_OFFSET_AMD 1000000
#define GGML_CUDA_CC_OFFSET_AMD 0x1000000
// GCN/CNDA, wave size is 64
#define GGML_CUDA_CC_GCN4 (GGML_CUDA_CC_OFFSET_AMD + 803) // Tonga, Fiji, Polaris, minimum for fast fp16
#define GGML_CUDA_CC_VEGA (GGML_CUDA_CC_OFFSET_AMD + 900) // Vega56/64, minimum for fp16 dual issue
#define GGML_CUDA_CC_VEGA20 (GGML_CUDA_CC_OFFSET_AMD + 906) // MI50/Radeon VII, minimum for dp4a
#define GGML_CUDA_CC_CDNA (GGML_CUDA_CC_OFFSET_AMD + 908) // MI100, minimum for MFMA, acc registers
#define GGML_CUDA_CC_CDNA2 (GGML_CUDA_CC_OFFSET_AMD + 910) // MI210, minimum acc register renameing
#define GGML_CUDA_CC_CDNA3 (GGML_CUDA_CC_OFFSET_AMD + 942) // MI300
#define GGML_CUDA_CC_GCN4 (GGML_CUDA_CC_OFFSET_AMD + 0x803) // Tonga, Fiji, Polaris, minimum for fast fp16
#define GGML_CUDA_CC_VEGA (GGML_CUDA_CC_OFFSET_AMD + 0x900) // Vega56/64, minimum for fp16 dual issue
#define GGML_CUDA_CC_VEGA20 (GGML_CUDA_CC_OFFSET_AMD + 0x906) // MI50/Radeon VII, minimum for dp4a
#define GGML_CUDA_CC_CDNA (GGML_CUDA_CC_OFFSET_AMD + 0x908) // MI100, minimum for MFMA, acc registers
#define GGML_CUDA_CC_CDNA2 (GGML_CUDA_CC_OFFSET_AMD + 0x910) // MI210, minimum acc register renameing
#define GGML_CUDA_CC_CDNA3 (GGML_CUDA_CC_OFFSET_AMD + 0x942) // MI300
// RNDA removes MFMA, dp4a, xnack, acc registers, wave size is 32
#define GGML_CUDA_CC_RDNA1 (GGML_CUDA_CC_OFFSET_AMD + 1010) // RX 5000
#define GGML_CUDA_CC_RDNA2 (GGML_CUDA_CC_OFFSET_AMD + 1030) // RX 6000, minimum for dp4a
#define GGML_CUDA_CC_RDNA3 (GGML_CUDA_CC_OFFSET_AMD + 1100) // RX 7000, minimum for WMMA
#define GGML_CUDA_CC_RDNA1 (GGML_CUDA_CC_OFFSET_AMD + 0x1010) // RX 5000
#define GGML_CUDA_CC_RDNA2 (GGML_CUDA_CC_OFFSET_AMD + 0x1030) // RX 6000, minimum for dp4a
#define GGML_CUDA_CC_RDNA3 (GGML_CUDA_CC_OFFSET_AMD + 0x1100) // RX 7000, minimum for WMMA
#define GGML_CUDA_CC_QY1 210
#define GGML_CUDA_CC_QY2 220
@ -190,53 +190,46 @@ static __device__ void no_device_code(
#define NO_DEVICE_CODE //GGML_ABORT("NO_DEVICE_CODE not valid in host code.")
#endif // __CUDA_ARCH__
template<int width = WARP_SIZE>
static __device__ __forceinline__ int warp_reduce_sum(int x) {
#if !(defined(GGML_USE_HIP) && defined(__HIP_PLATFORM_AMD__)) && __CUDA_ARCH__ >= GGML_CUDA_CC_AMPERE
return __reduce_add_sync(0xffffffff, x);
#else
#pragma unroll
for (int offset = 16; offset > 0; offset >>= 1) {
x += __shfl_xor_sync(0xffffffff, x, offset, 32);
for (int offset = width/2; offset > 0; offset >>= 1) {
x += __shfl_xor_sync(0xffffffff, x, offset, width);
}
return x;
#endif // !(defined(GGML_USE_HIP) && defined(__HIP_PLATFORM_AMD__)) && __CUDA_ARCH__ >= GGML_CUDA_CC_AMPERE
}
template<int width = WARP_SIZE>
static __device__ __forceinline__ float warp_reduce_sum(float x) {
#pragma unroll
for (int offset = 16; offset > 0; offset >>= 1) {
x += __shfl_xor_sync(0xffffffff, x, offset, 32);
for (int offset = width/2; offset > 0; offset >>= 1) {
x += __shfl_xor_sync(0xffffffff, x, offset, width);
}
return x;
}
template<int width = WARP_SIZE>
static __device__ __forceinline__ float2 warp_reduce_sum(float2 a) {
#pragma unroll
for (int offset = 16; offset > 0; offset >>= 1) {
a.x += __shfl_xor_sync(0xffffffff, a.x, offset, 32);
a.y += __shfl_xor_sync(0xffffffff, a.y, offset, 32);
for (int offset = width/2; offset > 0; offset >>= 1) {
a.x += __shfl_xor_sync(0xffffffff, a.x, offset, width);
a.y += __shfl_xor_sync(0xffffffff, a.y, offset, width);
}
return a;
}
template<int width = WARP_SIZE>
static __device__ __forceinline__ half2 warp_reduce_sum(half2 a) {
#ifdef FP16_AVAILABLE
#if defined(GGML_USE_HIP) && defined(__HIP_PLATFORM_AMD__)
#pragma unroll
for (int offset = 16; offset > 0; offset >>= 1) {
const half2 a_other = __shfl_xor_sync(0xffffffff, a, offset, 32);
reinterpret_cast<half&>(a.x) += __low2half(a_other);
reinterpret_cast<half&>(a.y) += __high2half(a_other);
for (int offset = width/2; offset > 0; offset >>= 1) {
a = __hadd2(a, __shfl_xor_sync(0xffffffff, a, offset, width));
}
return a;
#else
#pragma unroll
for (int offset = 16; offset > 0; offset >>= 1) {
a = __hadd2(a, __shfl_xor_sync(0xffffffff, a, offset, 32));
}
return a;
#endif // defined(GGML_USE_HIP) && defined(__HIP_PLATFORM_AMD__)
#else
NO_DEVICE_CODE;
@ -244,10 +237,11 @@ static __device__ __forceinline__ half2 warp_reduce_sum(half2 a) {
#endif // FP16_AVAILABLE
}
template<int width = WARP_SIZE>
static __device__ __forceinline__ float warp_reduce_max(float x) {
#pragma unroll
for (int offset = 16; offset > 0; offset >>= 1) {
x = fmaxf(x, __shfl_xor_sync(0xffffffff, x, offset, 32));
for (int offset = width/2; offset > 0; offset >>= 1) {
x = fmaxf(x, __shfl_xor_sync(0xffffffff, x, offset, width));
}
return x;
}
@ -269,35 +263,34 @@ static __device__ __forceinline__ half ggml_cuda_hmax(const half a, const half b
}
static __device__ __forceinline__ half2 ggml_cuda_hmax2(const half2 a, const half2 b) {
#if !(defined(GGML_USE_HIP) && defined(__HIP_PLATFORM_AMD__))
#if CUDART_VERSION >= CUDART_HMAX
#if defined(GGML_USE_HIP) && HIP_VERSION >= 50700000
return half2(__hmax(a.x, b.x), __hmax(a.y, b.y));
#elif !defined(GGML_USE_HIP) && CUDART_VERSION >= CUDART_HMAX
return __hmax2(a, b);
#else
#elif !defined(GGML_USE_HIP)
half2 ret;
reinterpret_cast<half&>(ret.x) = __float2half(fmaxf( __low2float(a), __low2float(b)));
reinterpret_cast<half&>(ret.y) = __float2half(fmaxf(__high2float(a), __high2float(b)));
return ret;
#endif // CUDART_VERSION >= CUDART_HMAX
#else
GGML_UNUSED(a);
GGML_UNUSED(b);
NO_DEVICE_CODE;
#endif // !(defined(GGML_USE_HIP) && defined(__HIP_PLATFORM_AMD__))
#endif
}
template<int width = WARP_SIZE>
static __device__ __forceinline__ half2 warp_reduce_max(half2 x) {
#if !(defined(GGML_USE_HIP) && defined(__HIP_PLATFORM_AMD__)) && __CUDA_ARCH__ >= GGML_CUDA_CC_PASCAL
#if !(defined(GGML_USE_HIP) && defined(__HIP_PLATFORM_AMD__)) && __CUDA_ARCH__ >= GGML_CUDA_CC_PASCAL || (defined(GGML_USE_HIP) && HIP_VERSION >= 50700000)
#pragma unroll
for (int offset = 16; offset > 0; offset >>= 1) {
x = ggml_cuda_hmax2(x, __shfl_xor_sync(0xffffffff, x, offset, 32));
for (int offset = width/2; offset > 0; offset >>= 1) {
x = ggml_cuda_hmax2(x, __shfl_xor_sync(0xffffffff, x, offset, width));
}
return x;
#else
GGML_UNUSED(x);
NO_DEVICE_CODE;
#endif // !(defined(GGML_USE_HIP) && defined(__HIP_PLATFORM_AMD__)) && __CUDA_ARCH__ >= GGML_CUDA_CC_PASCAL
#endif // !(defined(GGML_USE_HIP) && defined(__HIP_PLATFORM_AMD__)) && __CUDA_ARCH__ >= GGML_CUDA_CC_PASCAL || (defined(GGML_USE_HIP) && HIP_VERSION >= 50700000)
}
#if CUDART_VERSION < CUDART_HMASK
@ -520,6 +513,7 @@ struct ggml_cuda_device_info {
bool vmm; // virtual memory support
size_t vmm_granularity; // granularity of virtual memory
size_t total_vram;
int warp_size; // Number of threads in a dispatch
};
cuda_device_info devices[GGML_CUDA_MAX_DEVICES] = {};

95
ggml/src/ggml-cuda/ggml-cuda.cu
View file

@ -42,6 +42,7 @@
#include <algorithm>
#include <array>
#include <atomic>
#include <charconv>
#include <cinttypes>
#include <cstddef>
#include <cstdint>
@ -119,12 +120,78 @@ static cudaError_t ggml_cuda_device_malloc(void ** ptr, size_t size, int device)
#endif
}
#if defined(GGML_USE_HIP) && defined(__HIP_PLATFORM_AMD__)
static int ggml_cuda_parse_id(char devName[]) {
// A list of possible Target IDs can be found under the rocclr/clr repo in device.cpp
// these values are not stable so this is susceptible to breakage
// https://github.com/ROCm/clr/blob/amd-staging/rocclr/device/device.cpp
int archMajor = 0x0;
int archMinor = 0x0;
int archNum = GGML_CUDA_CC_OFFSET_AMD;
int archLen = strlen(devName);
char archName[archLen + 1];
// strip leading 'gfx' while copying into our buffer
if (archLen > 3) {
strcpy(archName, &devName[3]);
archLen -= 3;
}
// trim trailing :xnack- or :sramecc- statuses
archLen = strcspn(archName, ":");
archName[archLen] = '\0';
// tease out the version information
if (archLen > 8) {
// versions labeled generic use '-' as delimiter
// strip the trailing "-generic" then iterate through what remains
if ((strstr(archName, "-generic"))) {
archName[archLen - 8] = '\0';
char * pch;
if ((pch = strtok(archName, "-"))) {
archMajor = (int)strtoul(pch, 0, 16);
if ((pch = strtok(NULL, "-"))) {
archMinor = 0x10 * (int)strtoul(pch, 0, 16);
}
}
}
} else if (archLen >= 3) {
// last two digits should be the minor * 0x10 + stepping
archMinor = (int)strtoul(&archName[archLen - 2], 0, 16);
archName[archLen - 2] = '\0';
// only the major version remains
archMajor = (int)strtoul(archName, 0, 16);
}
archNum += archMajor * 0x100;
archNum += archMinor;
return archNum;
}
#endif // defined(GGML_USE_HIP) && defined(__HIP_PLATFORM_AMD__)
static ggml_cuda_device_info ggml_cuda_init() {
#ifdef __HIP_PLATFORM_AMD__
// Workaround for a rocBLAS bug when using multiple graphics cards:
// https://github.com/ROCmSoftwarePlatform/rocBLAS/issues/1346
rocblas_initialize();
CUDA_CHECK(cudaDeviceSynchronize());
{
int major_version = 0;
size_t version_length = 0;
if (rocblas_get_version_string_size(&version_length) == rocblas_status_success) {
std::string version(version_length, '\0');
if (rocblas_get_version_string(version.data(), version.size()) == rocblas_status_success) {
version.resize(::strlen(version.c_str()));
int parsed_value = 0;
if (std::from_chars(version.c_str(), version.c_str() + version.length(), parsed_value).ec == std::errc()) {
major_version = parsed_value;
}
}
}
if (major_version < 4) {
GGML_LOG_DEBUG(GGML_CUDA_NAME " calling rocblas_initialize as a workaround for a rocBLAS bug\n");
rocblas_initialize();
CUDA_CHECK(cudaDeviceSynchronize());
}
}
#endif
ggml_cuda_device_info info = {};
@ -169,19 +236,35 @@ static ggml_cuda_device_info ggml_cuda_init() {
cudaDeviceProp prop;
CUDA_CHECK(cudaGetDeviceProperties(&prop, id));
GGML_LOG_INFO(" Device %d: %s, compute capability %d.%d, VMM: %s\n", id, prop.name, prop.major, prop.minor, device_vmm ? "yes" : "no");
info.default_tensor_split[id] = total_vram;
total_vram += prop.totalGlobalMem;
info.devices[id].nsm = prop.multiProcessorCount;
info.devices[id].smpb = prop.sharedMemPerBlock;
info.devices[id].nsm = prop.multiProcessorCount;
info.devices[id].smpb = prop.sharedMemPerBlock;
info.devices[id].warp_size = prop.warpSize;
#if defined(GGML_USE_HIP) && defined(__HIP_PLATFORM_AMD__)
info.devices[id].smpbo = prop.sharedMemPerBlock;
info.devices[id].cc = 100*prop.major + 10*prop.minor + GGML_CUDA_CC_OFFSET_AMD;
info.devices[id].cc = ggml_cuda_parse_id(prop.gcnArchName);
if ((info.devices[id].cc & 0xff00) == 0x0) {
GGML_LOG_WARN("invalid architecture ID received for device %d %s: %s cc %d.%d\n",
id, prop.name, prop.gcnArchName, prop.major, prop.minor);
// Fallback to prop.major and prop.minor
if (prop.major > 0) {
info.devices[id].cc = GGML_CUDA_CC_OFFSET_AMD + prop.major * 0x100;
info.devices[id].cc += prop.minor * 0x10;
}
}
GGML_LOG_INFO(" Device %d: %s, %s (0x%x), VMM: %s, Wave Size: %d\n",
id, prop.name, prop.gcnArchName, info.devices[id].cc & 0xffff,
device_vmm ? "yes" : "no", prop.warpSize);
#else
info.devices[id].smpbo = prop.sharedMemPerBlockOptin;
info.devices[id].cc = 100*prop.major + 10*prop.minor;
GGML_LOG_INFO(" Device %d: %s, compute capability %d.%d, VMM: %s\n",
id, prop.name, prop.major, prop.minor, device_vmm ? "yes" : "no");
#endif // defined(GGML_USE_HIP) && defined(__HIP_PLATFORM_AMD__)
}

9
ggml/src/ggml-cuda/softmax.cu
View file

@ -13,6 +13,12 @@ __device__ float __forceinline__ t2f32<half>(half val) {
return __half2float(val);
}
// When ncols_template == 0 the bounds for the loops in this function are not known and can't be unrolled.
// As we want to keep pragma unroll for all other cases we supress the clang transformation warning here.
#ifdef __clang__
#pragma clang diagnostic push
#pragma clang diagnostic ignored "-Wpass-failed"
#endif
template <bool use_shared, int ncols_template, int block_size_template, typename T>
static __global__ void soft_max_f32(
const float * x, const T * mask, float * dst, const int ncols_par, const int nrows_y,
@ -118,6 +124,9 @@ static __global__ void soft_max_f32(
dst[col] = vals[col] * inv_sum;
}
}
#ifdef __clang__
#pragma clang diagnostic pop
#endif
static __global__ void soft_max_back_f32(
const float * grad, const float * dstf, float * dst, const int ncols, const float scale) {

4
ggml/src/ggml-hip/CMakeLists.txt
View file

@ -40,6 +40,10 @@ find_package(hip REQUIRED)
find_package(hipblas REQUIRED)
find_package(rocblas REQUIRED)
if (${hip_VERSION} VERSION_LESS 5.5)
message(FATAL_ERROR "At least ROCM/HIP V5.5 is required")
endif()
message(STATUS "HIP and hipBLAS found")
file(GLOB GGML_HEADERS_ROCM "../ggml-cuda/*.cuh")

144
ggml/src/ggml-metal/ggml-metal.m
View file

@ -19,7 +19,10 @@
// max number of MTLCommandBuffer used to submit a graph for processing
#define GGML_METAL_MAX_COMMAND_BUFFERS 8
#define UNUSED(x) (void)(x)
// create residency sets only on macOS >= 15.0
#if TARGET_OS_OSX && __MAC_OS_X_VERSION_MAX_ALLOWED >= 150000
#define GGML_METAL_HAS_RESIDENCY_SETS 1
#endif
// globals
@ -39,6 +42,7 @@ static struct ggml_backend_metal_device_context {
bool has_simdgroup_reduction;
bool has_simdgroup_mm;
bool has_residency_sets;
bool has_bfloat;
bool use_bfloat;
@ -48,6 +52,7 @@ static struct ggml_backend_metal_device_context {
/*.mtl_device_ref_count =*/ 0,
/*.has_simdgroup_reduction =*/ false,
/*.has_simdgroup_mm =*/ false,
/*.has_residency_sets =*/ false,
/*.has_bfloat =*/ false,
/*.use_bfloat =*/ false,
/*.name =*/ "",
@ -59,12 +64,18 @@ static id<MTLDevice> ggml_backend_metal_device_acq(struct ggml_backend_metal_dev
if (ctx->mtl_device == nil) {
ctx->mtl_device = MTLCreateSystemDefaultDevice();
}
if (ctx->mtl_device) {
ctx->has_simdgroup_reduction = [ctx->mtl_device supportsFamily:MTLGPUFamilyApple7];
ctx->has_simdgroup_reduction |= [ctx->mtl_device supportsFamily:MTLGPUFamilyMetal3_GGML];
ctx->has_simdgroup_mm = [ctx->mtl_device supportsFamily:MTLGPUFamilyApple7];
#if defined(GGML_METAL_HAS_RESIDENCY_SETS)
ctx->has_residency_sets = getenv("GGML_METAL_NO_RESIDENCY") == NULL;
#endif
ctx->has_bfloat = [ctx->mtl_device supportsFamily:MTLGPUFamilyMetal3_GGML];
ctx->has_bfloat |= [ctx->mtl_device supportsFamily:MTLGPUFamilyApple6];
@ -90,8 +101,10 @@ static void ggml_backend_metal_device_rel(struct ggml_backend_metal_device_conte
ctx->mtl_device_ref_count--;
if (ctx->mtl_device_ref_count == 0) {
[ctx->mtl_device release];
ctx->mtl_device = nil;
if (ctx->mtl_device) {
[ctx->mtl_device release];
ctx->mtl_device = nil;
}
}
}
@ -483,6 +496,11 @@ static struct ggml_backend_metal_context * ggml_metal_init(ggml_backend_dev_t de
GGML_LOG_INFO("%s: picking default device: %s\n", __func__, [[device name] UTF8String]);
ctx->queue = [device newCommandQueue];
if (ctx->queue == nil) {
GGML_LOG_ERROR("%s: error: failed to create command queue\n", __func__);
return NULL;
}
ctx->d_queue = dispatch_queue_create("ggml-metal", DISPATCH_QUEUE_CONCURRENT);
id<MTLLibrary> metal_library;
@ -649,6 +667,7 @@ static struct ggml_backend_metal_context * ggml_metal_init(ggml_backend_dev_t de
GGML_LOG_INFO("%s: simdgroup reduction = %s\n", __func__, ctx_dev->has_simdgroup_reduction ? "true" : "false");
GGML_LOG_INFO("%s: simdgroup matrix mul. = %s\n", __func__, ctx_dev->has_simdgroup_mm ? "true" : "false");
GGML_LOG_INFO("%s: has residency sets = %s\n", __func__, ctx_dev->has_residency_sets ? "true" : "false");
GGML_LOG_INFO("%s: has bfloat = %s\n", __func__, ctx_dev->has_bfloat ? "true" : "false");
GGML_LOG_INFO("%s: use bfloat = %s\n", __func__, ctx_dev->use_bfloat ? "true" : "false");
GGML_LOG_INFO("%s: hasUnifiedMemory = %s\n", __func__, ctx_dev->mtl_device.hasUnifiedMemory ? "true" : "false");
@ -1035,8 +1054,70 @@ struct ggml_backend_metal_buffer_context {
// multiple buffers are used only to avoid the maximum buffer size limitation when using mmap
int n_buffers;
struct ggml_backend_metal_buffer buffers[GGML_METAL_MAX_BUFFERS];
// optional MTLResidencySet
id rset;
};
// rset init
static bool ggml_backend_metal_buffer_rset_init(
struct ggml_backend_metal_buffer_context * ctx,
struct ggml_backend_metal_device_context * ctx_dev,
id<MTLDevice> device) {
ctx->rset = nil;
if (!ctx_dev->has_residency_sets) {
return true;
}
#if defined(GGML_METAL_HAS_RESIDENCY_SETS)
if (@available(macOS 15.0, *)) {
MTLResidencySetDescriptor * desc = [[MTLResidencySetDescriptor alloc] init];
desc.label = @"ggml_backend_metal";
desc.initialCapacity = ctx->n_buffers;
NSError * error;
ctx->rset = [device newResidencySetWithDescriptor:desc error:&error];
if (error) {
GGML_LOG_ERROR("%s: error: %s\n", __func__, [[error description] UTF8String]);
[desc release];
return false;
}
[desc release];
for (int i = 0; i < ctx->n_buffers; i++) {
[ctx->rset addAllocation:ctx->buffers[i].metal];
}
[ctx->rset commit];
[ctx->rset requestResidency];
return true;
}
#else
GGML_UNUSED(ctx_dev);
GGML_UNUSED(device);
#endif
return true;
}
// rset free
static void ggml_backend_metal_buffer_rset_free(struct ggml_backend_metal_buffer_context * ctx) {
#if defined(GGML_METAL_HAS_RESIDENCY_SETS)
if (@available(macOS 15.0, *)) {
if (ctx->rset) {
[ctx->rset endResidency];
[ctx->rset removeAllAllocations];
[ctx->rset release];
}
}
#else
GGML_UNUSED(ctx);
#endif
}
// finds the Metal buffer that contains the tensor data on the GPU device
// the assumption is that there is 1-to-1 mapping between the host and device memory buffers, so we can find the
// Metal buffer based on the host memory pointer
@ -4176,6 +4257,8 @@ static void ggml_backend_metal_buffer_free_buffer(ggml_backend_buffer_t buffer)
for (int i = 0; i < ctx->n_buffers; i++) {
[ctx->buffers[i].metal release];
}
ggml_backend_metal_buffer_rset_free(ctx);
ggml_backend_metal_device_rel(buffer->buft->device->context);
if (ctx->owned) {
@ -4198,19 +4281,19 @@ static void * ggml_backend_metal_buffer_get_base(ggml_backend_buffer_t buffer) {
static void ggml_backend_metal_buffer_memset_tensor(ggml_backend_buffer_t buffer, struct ggml_tensor * tensor, uint8_t value, size_t offset, size_t size) {
memset((char *)tensor->data + offset, value, size);
UNUSED(buffer);
GGML_UNUSED(buffer);
}
static void ggml_backend_metal_buffer_set_tensor(ggml_backend_buffer_t buffer, struct ggml_tensor * tensor, const void * data, size_t offset, size_t size) {
memcpy((char *)tensor->data + offset, data, size);
UNUSED(buffer);
GGML_UNUSED(buffer);
}
static void ggml_backend_metal_buffer_get_tensor(ggml_backend_buffer_t buffer, const struct ggml_tensor * tensor, void * data, size_t offset, size_t size) {
memcpy(data, (const char *)tensor->data + offset, size);
UNUSED(buffer);
GGML_UNUSED(buffer);
}
static bool ggml_backend_metal_buffer_cpy_tensor(ggml_backend_buffer_t buffer, const struct ggml_tensor * src, struct ggml_tensor * dst) {
@ -4220,7 +4303,7 @@ static bool ggml_backend_metal_buffer_cpy_tensor(ggml_backend_buffer_t buffer, c
}
return false;
UNUSED(buffer);
GGML_UNUSED(buffer);
}
static void ggml_backend_metal_buffer_clear(ggml_backend_buffer_t buffer, uint8_t value) {
@ -4246,7 +4329,7 @@ static struct ggml_backend_buffer_i ggml_backend_metal_buffer_i = {
static const char * ggml_backend_metal_buffer_type_get_name(ggml_backend_buffer_type_t buft) {
return "Metal";
UNUSED(buft);
GGML_UNUSED(buft);
}
static void ggml_backend_metal_log_allocated_size(id<MTLDevice> device, size_t size_aligned) {
@ -4270,8 +4353,8 @@ static void ggml_backend_metal_log_allocated_size(id<MTLDevice> device, size_t s
}
#endif
#endif
UNUSED(device);
UNUSED(size_aligned);
GGML_UNUSED(device);
GGML_UNUSED(size_aligned);
}
static ggml_backend_buffer_t ggml_backend_metal_buffer_type_alloc_buffer(ggml_backend_buffer_type_t buft, size_t size) {
@ -4284,7 +4367,8 @@ static ggml_backend_buffer_t ggml_backend_metal_buffer_type_alloc_buffer(ggml_ba
size_aligned += (size_page - (size_aligned % size_page));
}
id<MTLDevice> device = ggml_backend_metal_device_acq(buft->device->context);
struct ggml_backend_metal_device_context * ctx_dev = (struct ggml_backend_metal_device_context *)buft->device->context;
id<MTLDevice> device = ggml_backend_metal_device_acq(ctx_dev);
ctx->all_data = ggml_metal_host_malloc(size_aligned);
ctx->all_size = size_aligned;
@ -4307,7 +4391,14 @@ static ggml_backend_buffer_t ggml_backend_metal_buffer_type_alloc_buffer(ggml_ba
if (size_aligned > 0 && (ctx->all_data == NULL || ctx->buffers[0].metal == nil)) {
GGML_LOG_ERROR("%s: error: failed to allocate buffer, size = %8.2f MiB\n", __func__, size_aligned / 1024.0 / 1024.0);
free(ctx);
ggml_backend_metal_device_rel(buft->device->context);
ggml_backend_metal_device_rel(ctx_dev);
return NULL;
}
if (!ggml_backend_metal_buffer_rset_init(ctx, ctx_dev, device)) {
GGML_LOG_ERROR("%s: error: failed to initialize residency set\n", __func__);
free(ctx);
ggml_backend_metal_device_rel(ctx_dev);
return NULL;
}
@ -4318,7 +4409,7 @@ static ggml_backend_buffer_t ggml_backend_metal_buffer_type_alloc_buffer(ggml_ba
static size_t ggml_backend_metal_buffer_type_get_alignment(ggml_backend_buffer_type_t buft) {
return 32;
UNUSED(buft);
GGML_UNUSED(buft);
}
static size_t ggml_backend_metal_buffer_type_get_max_size(ggml_backend_buffer_type_t buft) {
@ -4328,13 +4419,13 @@ static size_t ggml_backend_metal_buffer_type_get_max_size(ggml_backend_buffer_ty
return max_size;
UNUSED(buft);
GGML_UNUSED(buft);
}
static bool ggml_backend_metal_buffer_type_is_host(ggml_backend_buffer_type_t buft) {
return true;
UNUSED(buft);
GGML_UNUSED(buft);
}
ggml_backend_buffer_type_t ggml_backend_metal_buffer_type(void) {
@ -4357,7 +4448,7 @@ ggml_backend_buffer_type_t ggml_backend_metal_buffer_type(void) {
static const char * ggml_backend_metal_buffer_from_ptr_type_get_name(ggml_backend_buffer_type_t buft) {
return "Metal_Mapped";
UNUSED(buft);
GGML_UNUSED(buft);
}
static ggml_backend_buffer_type_t ggml_backend_metal_buffer_from_ptr_type(void) {
@ -4400,7 +4491,8 @@ ggml_backend_buffer_t ggml_backend_metal_buffer_from_ptr(void * data, size_t siz
size_aligned += (size_page - (size_aligned % size_page));
}
id<MTLDevice> device = ggml_backend_metal_device_acq(&g_ggml_ctx_dev_main);
struct ggml_backend_metal_device_context * ctx_dev = &g_ggml_ctx_dev_main;
id<MTLDevice> device = ggml_backend_metal_device_acq(ctx_dev);
// the buffer fits into the max buffer size allowed by the device
if (size_aligned <= device.maxBufferLength) {
@ -4453,6 +4545,13 @@ ggml_backend_buffer_t ggml_backend_metal_buffer_from_ptr(void * data, size_t siz
}
}
if (!ggml_backend_metal_buffer_rset_init(ctx, ctx_dev, device)) {
GGML_LOG_ERROR("%s: error: failed to initialize residency set\n", __func__);
free(ctx);
ggml_backend_metal_device_rel(ctx_dev);
return NULL;
}
return ggml_backend_buffer_init(ggml_backend_metal_buffer_from_ptr_type(), ggml_backend_metal_buffer_i, ctx, size);
}
@ -4461,7 +4560,7 @@ ggml_backend_buffer_t ggml_backend_metal_buffer_from_ptr(void * data, size_t siz
static const char * ggml_backend_metal_name(ggml_backend_t backend) {
return "Metal";
UNUSED(backend);
GGML_UNUSED(backend);
}
static void ggml_backend_metal_free(ggml_backend_t backend) {
@ -4766,6 +4865,13 @@ static ggml_backend_buffer_t ggml_backend_metal_device_buffer_from_ptr(ggml_back
}
}
if (!ggml_backend_metal_buffer_rset_init(ctx, ctx_dev, device)) {
GGML_LOG_ERROR("%s: error: failed to initialize residency set\n", __func__);
free(ctx);
ggml_backend_metal_device_rel(ctx_dev);
return NULL;
}
return ggml_backend_buffer_init(ggml_backend_metal_buffer_from_ptr_type(), ggml_backend_metal_buffer_i, ctx, size);
}
@ -4779,7 +4885,7 @@ static bool ggml_backend_metal_device_supports_buft(ggml_backend_dev_t dev, ggml
return buft->iface.get_name == ggml_backend_metal_buffer_type_get_name ||
buft->iface.get_name == ggml_backend_metal_buffer_from_ptr_type_get_name;
UNUSED(dev);
GGML_UNUSED(dev);
}
static bool ggml_backend_metal_device_offload_op(ggml_backend_dev_t dev, const struct ggml_tensor * op) {

6
ggml/src/ggml-sycl/ggml-sycl.cpp
View file

@ -3878,10 +3878,6 @@ static void ggml_sycl_diag_mask_inf(ggml_backend_sycl_context & ctx, ggml_tensor
ggml_sycl_op_flatten(ctx, dst->src[0], dst->src[1], dst, ggml_sycl_op_diag_mask_inf);
}
static void ggml_sycl_soft_max(ggml_backend_sycl_context & ctx, ggml_tensor * dst) {
ggml_sycl_op_flatten(ctx, dst->src[0], dst->src[1], dst, ggml_sycl_op_soft_max);
}
static void ggml_sycl_rope(ggml_backend_sycl_context & ctx, ggml_tensor * dst) {
GGML_ASSERT(ggml_is_contiguous(dst->src[0])); // TODO: this restriction is temporary until non-cont support is implemented
ggml_sycl_op_flatten(ctx, dst->src[0], dst->src[1], dst, ggml_sycl_op_rope);
@ -4090,7 +4086,7 @@ bool ggml_sycl_compute_forward(ggml_backend_sycl_context & ctx, struct ggml_tens
ggml_sycl_diag_mask_inf(ctx, dst);
break;
case GGML_OP_SOFT_MAX:
ggml_sycl_soft_max(ctx, dst);
ggml_sycl_op_soft_max(ctx, dst);
break;
case GGML_OP_ROPE:
ggml_sycl_rope(ctx, dst);

56
ggml/src/ggml-sycl/softmax.cpp
View file

@ -1,7 +1,7 @@
#include "norm.hpp"
#include "softmax.hpp"
template <bool vals_smem, int ncols_template, int block_size_template>
static void soft_max_f32(const float * x, const float * mask, float * dst, const int ncols_par,
template <bool vals_smem, int ncols_template, int block_size_template, typename T>
static void soft_max_f32(const float * x, const T * mask, float * dst, const int ncols_par,
const int nrows_y, const float scale, const float max_bias, const float m0,
const float m1, uint32_t n_head_log2, const sycl::nd_item<3> &item_ct1, float *buf) {
const int ncols = ncols_template == 0 ? ncols_par : ncols_template;
@ -29,7 +29,7 @@ static void soft_max_f32(const float * x, const float * mask, float * dst, const
slope = sycl::pow(base, float(exp));
}
float *vals = vals_smem ? buf + std::max(nwarps, WARP_SIZE) : dst + rowx * ncols;
float *vals = vals_smem ? buf + sycl::max(nwarps, WARP_SIZE) : dst + rowx * ncols;
float max_val = -INFINITY;
for (int col0 = 0; col0 < ncols; col0 += block_size) {
@ -42,7 +42,7 @@ static void soft_max_f32(const float * x, const float * mask, float * dst, const
const int ix = rowx*ncols + col;
const int iy = rowy*ncols + col;
const float val = x[ix]*scale + (mask ? slope*mask[iy] : 0.0f);
const float val = x[ix]*scale + (mask ? slope*static_cast<float>(mask[iy]) : 0.0f);
vals[col] = val;
max_val = sycl::max(max_val, val);
@ -65,7 +65,7 @@ static void soft_max_f32(const float * x, const float * mask, float * dst, const
item_ct1.barrier(sycl::access::fence_space::local_space);
max_val = buf[lane_id];
for (size_t i = 1; i < nreduce; i += 1) {
max_val = std::max(max_val, buf[lane_id + i * WARP_SIZE]);
max_val = sycl::max(max_val, buf[lane_id + i * WARP_SIZE]);
}
max_val = warp_reduce_max(max_val, item_ct1);
}
@ -122,8 +122,8 @@ static void soft_max_f32(const float * x, const float * mask, float * dst, const
}
}
template <bool vals_smem, int ncols_template, int block_size_template>
static void soft_max_f32_submitter(const float * x, const float * mask, float * dst, const int ncols_par,
template <bool vals_smem, int ncols_template, int block_size_template, typename T>
static void soft_max_f32_submitter(const float * x, const T * mask, float * dst, const int ncols_par,
const int nrows_y, const float scale, const float max_bias, const float m0,
const float m1, uint32_t n_head_log2, sycl::range<3> block_nums, sycl::range<3> block_dims,
const size_t n_local_scratch, queue_ptr stream) {
@ -141,7 +141,8 @@ static void soft_max_f32_submitter(const float * x, const float * mask, float *
});
}
static void soft_max_f32_sycl(const float * x, const float * mask,
template<typename T>
static void soft_max_f32_sycl(const float * x, const T * mask,
float * dst, const int ncols_x, const int nrows_x,
const int nrows_y, const float scale, const float max_bias,
queue_ptr stream, int device) {
@ -223,22 +224,16 @@ static void soft_max_f32_sycl(const float * x, const float * mask,
}
}
void ggml_sycl_op_soft_max(ggml_backend_sycl_context & ctx, const ggml_tensor *src0,
const ggml_tensor *src1, ggml_tensor *dst,
const float *src0_dd, const float *src1_dd,
float *dst_dd,
const queue_ptr &main_stream) {
void ggml_sycl_op_soft_max(ggml_backend_sycl_context & ctx, ggml_tensor * dst) {
GGML_ASSERT(src0->type == GGML_TYPE_F32);
GGML_ASSERT(dst->src[0]->type == GGML_TYPE_F32);
GGML_ASSERT( dst->type == GGML_TYPE_F32);
#pragma message("TODO: add ggml_sycl_op_soft_max() F16 src1 support")
#pragma message("ref: https://github.com/ggerganov/llama.cpp/pull/5021")
GGML_ASSERT(!src1 || src1->type == GGML_TYPE_F32); // src1 contains mask and it is optional
GGML_ASSERT(!dst->src[1] || dst->src[1]->type == GGML_TYPE_F16 || dst->src[1]->type == GGML_TYPE_F32); // src1 contains mask and it is optional
const int64_t ne00 = src0->ne[0];
const int64_t nrows_x = ggml_nrows(src0);
const int64_t nrows_y = src0->ne[1];
const int64_t ne00 = dst->src[0]->ne[0];
const int64_t nrows_x = ggml_nrows(dst->src[0]);
const int64_t nrows_y = dst->src[0]->ne[1];
float scale = 1.0f;
float max_bias = 0.0f;
@ -246,6 +241,21 @@ void ggml_sycl_op_soft_max(ggml_backend_sycl_context & ctx, const ggml_tensor *s
memcpy(&scale, dst->op_params + 0, sizeof(float));
memcpy(&max_bias, dst->op_params + 1, sizeof(float));
soft_max_f32_sycl(src0_dd, src1 ? src1_dd : nullptr, dst_dd, ne00,
nrows_x, nrows_y, scale, max_bias, main_stream, ctx.device);
const float * src0_dd = static_cast<const float *>(dst->src[0]->data);
float * dst_dd = static_cast<float *>(dst->data);
ggml_sycl_set_device(ctx.device);
dpct::queue_ptr main_stream = ctx.stream();
if (dst->src[1] && dst->src[1]->type == GGML_TYPE_F16) {
const sycl::half * src1_dd = static_cast<sycl::half *>(dst->src[1]->data);
soft_max_f32_sycl<sycl::half>(src0_dd, src1_dd, dst_dd, ne00, nrows_x, nrows_y, scale, max_bias,
main_stream, ctx.device);
} else if (dst->src[1] && dst->src[1]->type == GGML_TYPE_F32) {
const float * src1_dd = static_cast<const float *>(dst->src[1]->data);
soft_max_f32_sycl<float>(src0_dd, src1_dd, dst_dd, ne00, nrows_x, nrows_y, scale, max_bias, main_stream, ctx.device);
} else {
/* mask unavailable */
soft_max_f32_sycl<float>(src0_dd, nullptr, dst_dd, ne00, nrows_x, nrows_y, scale, max_bias, main_stream, ctx.device);
}
}

6
ggml/src/ggml-sycl/softmax.hpp
View file

@ -15,10 +15,6 @@
#include "common.hpp"
void ggml_sycl_op_soft_max(ggml_backend_sycl_context &ctx, const ggml_tensor *src0,
const ggml_tensor *src1, ggml_tensor *dst,
const float *src0_dd, const float *src1_dd,
float *dst_dd,
const queue_ptr &main_stream);
void ggml_sycl_op_soft_max(ggml_backend_sycl_context &ctx, ggml_tensor *dst);
#endif // GGML_SYCL_SOFTMAX_HPP

181
ggml/src/ggml-vulkan/ggml-vulkan.cpp
View file

@ -774,12 +774,12 @@ static uint32_t compile_count = 0;
static std::mutex compile_count_mutex;
static std::condition_variable compile_count_cond;
static void ggml_vk_create_pipeline_func(vk_device& device, vk_pipeline& pipeline, const std::string name, size_t spv_size, const void* spv_data, const std::string entrypoint,
uint32_t parameter_count, uint32_t push_constant_size, std::array<uint32_t, 3> wg_denoms, std::vector<uint32_t> specialization_constants,
uint32_t align, bool disable_robustness, bool require_full_subgroups, uint32_t required_subgroup_size) {
VK_LOG_DEBUG("ggml_vk_create_pipeline(" << device->name << ", " << name << ", " << entrypoint << ", " << parameter_count << ", " << push_constant_size <<
", (" << wg_denoms[0] << "," << wg_denoms[1] << "," << wg_denoms[2] << "), specialization_constants, " << align <<
", " << disable_robustness << ", " << require_full_subgroups << ", " << required_subgroup_size << ")");
static void ggml_vk_create_pipeline_func(vk_device& device, vk_pipeline& pipeline, size_t spv_size, const void* spv_data, const std::string entrypoint,
uint32_t parameter_count, std::array<uint32_t, 3> wg_denoms, std::vector<uint32_t> specialization_constants,
bool disable_robustness, bool require_full_subgroups, uint32_t required_subgroup_size) {
VK_LOG_DEBUG("ggml_vk_create_pipeline(" << device->name << ", " << pipeline->name << ", " << entrypoint << ", " << parameter_count <<
", (" << wg_denoms[0] << "," << wg_denoms[1] << "," << wg_denoms[2] << "), specialization_constants, " <<
disable_robustness << ", " << require_full_subgroups << ", " << required_subgroup_size << ")");
GGML_ASSERT(parameter_count > 0);
GGML_ASSERT(wg_denoms[0] > 0 && wg_denoms[1] > 0 && wg_denoms[2] > 0); // NOLINT
@ -864,7 +864,13 @@ static void ggml_vk_create_pipeline_func(vk_device& device, vk_pipeline& pipelin
compute_pipeline_create_info.setPNext(&rci);
}
pipeline->pipeline = device->device.createComputePipeline(VK_NULL_HANDLE, compute_pipeline_create_info).value;
try {
pipeline->pipeline = device->device.createComputePipeline(VK_NULL_HANDLE, compute_pipeline_create_info).value;
} catch (const vk::SystemError& e) {
std::cerr << "ggml_vulkan: Compute pipeline creation failed for " << pipeline->name << std::endl;
std::cerr << "ggml_vulkan: " << e.what() << std::endl;
throw e;
}
pipeline->compiled = true;
{
@ -1560,8 +1566,8 @@ static void ggml_vk_load_shaders(vk_device& device) {
}
compile_count++;
}
compiles.push_back(std::async(ggml_vk_create_pipeline_func, std::ref(device), std::ref(pipeline), name, spv_size, spv_data, entrypoint,
parameter_count, push_constant_size, wg_denoms, specialization_constants, align, disable_robustness, require_full_subgroups, required_subgroup_size));
compiles.push_back(std::async(ggml_vk_create_pipeline_func, std::ref(device), std::ref(pipeline), spv_size, spv_data, entrypoint,
parameter_count, wg_denoms, specialization_constants, disable_robustness, require_full_subgroups, required_subgroup_size));
};
#if defined(VK_NV_cooperative_matrix2) && defined(GGML_VULKAN_COOPMAT2_GLSLC_SUPPORT)
@ -1610,6 +1616,11 @@ static void ggml_vk_load_shaders(vk_device& device) {
//CREATE_FA(GGML_TYPE_Q4_K, q4_k)
//CREATE_FA(GGML_TYPE_Q5_K, q5_k)
//CREATE_FA(GGML_TYPE_Q6_K, q6_k)
//CREATE_FA(GGML_TYPE_IQ2_XXS, iq2_xxs)
//CREATE_FA(GGML_TYPE_IQ2_XS, iq2_xs)
//CREATE_FA(GGML_TYPE_IQ2_S, iq2_s)
//CREATE_FA(GGML_TYPE_IQ3_XXS, iq3_xxs)
//CREATE_FA(GGML_TYPE_IQ3_S, iq3_s)
CREATE_FA(GGML_TYPE_IQ4_NL, iq4_nl)
#undef CREATE_FA
@ -1638,7 +1649,12 @@ static void ggml_vk_load_shaders(vk_device& device) {
CREATE_MM(pipeline_dequant_mul_mat_mat_f16[GGML_TYPE_Q4_K].f16acc, matmul_q4_k_f16, _f16acc, mmq_wg_denoms_k, warptile_mmq_k, vk_mat_mat_push_constants, 3)
CREATE_MM(pipeline_dequant_mul_mat_mat_f16[GGML_TYPE_Q5_K].f16acc, matmul_q5_k_f16, _f16acc, mmq_wg_denoms_k, warptile_mmq_k, vk_mat_mat_push_constants, 3)
CREATE_MM(pipeline_dequant_mul_mat_mat_f16[GGML_TYPE_Q6_K].f16acc, matmul_q6_k_f16, _f16acc, mmq_wg_denoms_k, warptile_mmq_k, vk_mat_mat_push_constants, 3)
CREATE_MM(pipeline_dequant_mul_mat_mat_f16[GGML_TYPE_IQ4_NL].f16acc, matmul_iq4_nl_f16, _f16acc, mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3)
CREATE_MM(pipeline_dequant_mul_mat_mat_f16[GGML_TYPE_IQ2_XXS].f16acc, matmul_iq2_xxs_f16, _f16acc, mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3)
CREATE_MM(pipeline_dequant_mul_mat_mat_f16[GGML_TYPE_IQ2_XS].f16acc, matmul_iq2_xs_f16, _f16acc, mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3)
CREATE_MM(pipeline_dequant_mul_mat_mat_f16[GGML_TYPE_IQ2_S].f16acc, matmul_iq2_s_f16, _f16acc, mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3)
CREATE_MM(pipeline_dequant_mul_mat_mat_f16[GGML_TYPE_IQ3_XXS].f16acc, matmul_iq3_xxs_f16, _f16acc, mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3)
CREATE_MM(pipeline_dequant_mul_mat_mat_f16[GGML_TYPE_IQ3_S].f16acc, matmul_iq3_s_f16, _f16acc, mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3)
CREATE_MM(pipeline_dequant_mul_mat_mat_f16[GGML_TYPE_IQ4_NL].f16acc, matmul_iq4_nl_f16, _f16acc, mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3)
CREATE_MM2(pipeline_matmul_id_f16, matmul_id_f16, wg_denoms, warptile, vk_mat_mat_id_push_constants, 4)
CREATE_MM(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_0].f16acc, matmul_id_q4_0_f16, , mmqid_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4)
@ -1651,7 +1667,12 @@ static void ggml_vk_load_shaders(vk_device& device) {
CREATE_MM(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_K].f16acc, matmul_id_q4_k_f16, , mmqid_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4)
CREATE_MM(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_K].f16acc, matmul_id_q5_k_f16, , mmqid_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4)
CREATE_MM(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q6_K].f16acc, matmul_id_q6_k_f16, , mmqid_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4)
CREATE_MM(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ4_NL].f16acc, matmul_id_iq4_nl_f16, , mmqid_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4)
CREATE_MM(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ2_XXS].f16acc, matmul_id_iq2_xxs_f16, , mmqid_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4)
CREATE_MM(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ2_XS].f16acc, matmul_id_iq2_xs_f16, , mmqid_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4)
CREATE_MM(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ2_S].f16acc, matmul_id_iq2_s_f16, , mmqid_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4)
CREATE_MM(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ3_XXS].f16acc, matmul_id_iq3_xxs_f16, , mmqid_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4)
CREATE_MM(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ3_S].f16acc, matmul_id_iq3_s_f16, , mmqid_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4)
CREATE_MM(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ4_NL].f16acc, matmul_id_iq4_nl_f16, , mmqid_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4)
#undef CREATE_MM
#undef CREATE_MM2
} else
@ -1699,7 +1720,12 @@ static void ggml_vk_load_shaders(vk_device& device) {
CREATE_MM(pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_K].f16acc, matmul_q4_k_f32, _f16acc, mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
CREATE_MM(pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_K].f16acc, matmul_q5_k_f32, _f16acc, mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
CREATE_MM(pipeline_dequant_mul_mat_mat[GGML_TYPE_Q6_K].f16acc, matmul_q6_k_f32, _f16acc, mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
CREATE_MM(pipeline_dequant_mul_mat_mat[GGML_TYPE_IQ4_NL].f16acc, matmul_iq4_nl_f32, _f16acc, mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
CREATE_MM(pipeline_dequant_mul_mat_mat[GGML_TYPE_IQ2_XXS].f16acc, matmul_iq2_xxs_f32, _f16acc, mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
CREATE_MM(pipeline_dequant_mul_mat_mat[GGML_TYPE_IQ2_XS].f16acc, matmul_iq2_xs_f32, _f16acc, mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
CREATE_MM(pipeline_dequant_mul_mat_mat[GGML_TYPE_IQ2_S].f16acc, matmul_iq2_s_f32, _f16acc, mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
CREATE_MM(pipeline_dequant_mul_mat_mat[GGML_TYPE_IQ3_XXS].f16acc, matmul_iq3_xxs_f32, _f16acc, mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
CREATE_MM(pipeline_dequant_mul_mat_mat[GGML_TYPE_IQ3_S].f16acc, matmul_iq3_s_f32, _f16acc, mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
CREATE_MM(pipeline_dequant_mul_mat_mat[GGML_TYPE_IQ4_NL].f16acc, matmul_iq4_nl_f32, _f16acc, mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
} else {
CREATE_MM(pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_0].f16acc, matmul_q4_0_f32, , mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
CREATE_MM(pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_1].f16acc, matmul_q4_1_f32, , mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
@ -1712,7 +1738,12 @@ static void ggml_vk_load_shaders(vk_device& device) {
CREATE_MM(pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_K].f16acc, matmul_q4_k_f32, , mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
CREATE_MM(pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_K].f16acc, matmul_q5_k_f32, , mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
CREATE_MM(pipeline_dequant_mul_mat_mat[GGML_TYPE_Q6_K].f16acc, matmul_q6_k_f32, , mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
CREATE_MM(pipeline_dequant_mul_mat_mat[GGML_TYPE_IQ4_NL].f16acc, matmul_iq4_nl_f32, , mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
CREATE_MM(pipeline_dequant_mul_mat_mat[GGML_TYPE_IQ2_XXS].f16acc, matmul_iq2_xxs_f32, , mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
CREATE_MM(pipeline_dequant_mul_mat_mat[GGML_TYPE_IQ2_XS].f16acc, matmul_iq2_xs_f32, , mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
CREATE_MM(pipeline_dequant_mul_mat_mat[GGML_TYPE_IQ2_S].f16acc, matmul_iq2_s_f32, , mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
CREATE_MM(pipeline_dequant_mul_mat_mat[GGML_TYPE_IQ3_XXS].f16acc, matmul_iq3_xxs_f32, , mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
CREATE_MM(pipeline_dequant_mul_mat_mat[GGML_TYPE_IQ3_S].f16acc, matmul_iq3_s_f32, , mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
CREATE_MM(pipeline_dequant_mul_mat_mat[GGML_TYPE_IQ4_NL].f16acc, matmul_iq4_nl_f32, , mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
}
// If there's not enough shared memory for row_ids and the result tile, don't create these pipelines.
@ -1733,7 +1764,12 @@ static void ggml_vk_load_shaders(vk_device& device) {
CREATE_MM(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_K].f16acc, matmul_id_q4_k_f32, _f16acc, mmq_wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
CREATE_MM(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_K].f16acc, matmul_id_q5_k_f32, _f16acc, mmq_wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
CREATE_MM(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q6_K].f16acc, matmul_id_q6_k_f32, _f16acc, mmq_wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
CREATE_MM(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ4_NL].f16acc, matmul_id_iq4_nl_f32, _f16acc, mmq_wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
CREATE_MM(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ2_XXS].f16acc, matmul_id_iq2_xxs_f32, _f16acc, mmq_wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
CREATE_MM(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ2_XS].f16acc, matmul_id_iq2_xs_f32, _f16acc, mmq_wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
CREATE_MM(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ2_S].f16acc, matmul_id_iq2_s_f32, _f16acc, mmq_wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
CREATE_MM(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ3_XXS].f16acc, matmul_id_iq3_xxs_f32, _f16acc, mmq_wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
CREATE_MM(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ3_S].f16acc, matmul_id_iq3_s_f32, _f16acc, mmq_wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
CREATE_MM(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ4_NL].f16acc, matmul_id_iq4_nl_f32, _f16acc, mmq_wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
} else {
CREATE_MM(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_0].f16acc, matmul_id_q4_0_f32, , mmq_wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
CREATE_MM(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_1].f16acc, matmul_id_q4_1_f32, , mmq_wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
@ -1746,7 +1782,12 @@ static void ggml_vk_load_shaders(vk_device& device) {
CREATE_MM(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_K].f16acc, matmul_id_q4_k_f32, , mmq_wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
CREATE_MM(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_K].f16acc, matmul_id_q5_k_f32, , mmq_wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
CREATE_MM(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q6_K].f16acc, matmul_id_q6_k_f32, , mmq_wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
CREATE_MM(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ4_NL].f16acc, matmul_id_iq4_nl_f32, , mmq_wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
CREATE_MM(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ2_XXS].f16acc, matmul_id_iq2_xxs_f32, , mmq_wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
CREATE_MM(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ2_XS].f16acc, matmul_id_iq2_xs_f32, , mmq_wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
CREATE_MM(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ2_S].f16acc, matmul_id_iq2_s_f32, , mmq_wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
CREATE_MM(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ3_XXS].f16acc, matmul_id_iq3_xxs_f32, , mmq_wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
CREATE_MM(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ3_S].f16acc, matmul_id_iq3_s_f32, , mmq_wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
CREATE_MM(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ4_NL].f16acc, matmul_id_iq4_nl_f32, , mmq_wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
}
}
#undef CREATE_MM2
@ -1790,7 +1831,12 @@ static void ggml_vk_load_shaders(vk_device& device) {
CREATE_MM(pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_K].f16acc, matmul_q4_k_f32, _f16acc, mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
CREATE_MM(pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_K].f16acc, matmul_q5_k_f32, _f16acc, mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
CREATE_MM(pipeline_dequant_mul_mat_mat[GGML_TYPE_Q6_K].f16acc, matmul_q6_k_f32, _f16acc, mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
CREATE_MM(pipeline_dequant_mul_mat_mat[GGML_TYPE_IQ4_NL].f16acc, matmul_iq4_nl_f32, _f16acc, mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
CREATE_MM(pipeline_dequant_mul_mat_mat[GGML_TYPE_IQ2_XXS].f16acc, matmul_iq2_xxs_f32, _f16acc, mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
CREATE_MM(pipeline_dequant_mul_mat_mat[GGML_TYPE_IQ2_XS].f16acc, matmul_iq2_xs_f32, _f16acc, mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
CREATE_MM(pipeline_dequant_mul_mat_mat[GGML_TYPE_IQ2_S].f16acc, matmul_iq2_s_f32, _f16acc, mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
CREATE_MM(pipeline_dequant_mul_mat_mat[GGML_TYPE_IQ3_XXS].f16acc, matmul_iq3_xxs_f32, _f16acc, mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
CREATE_MM(pipeline_dequant_mul_mat_mat[GGML_TYPE_IQ3_S].f16acc, matmul_iq3_s_f32, _f16acc, mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
CREATE_MM(pipeline_dequant_mul_mat_mat[GGML_TYPE_IQ4_NL].f16acc, matmul_iq4_nl_f32, _f16acc, mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
// If there's not enough shared memory for row_ids and the result tile, don't create these pipelines.
if (device->mul_mat_id_s || device->mul_mat_id_m || device->mul_mat_id_l) {
@ -1809,7 +1855,12 @@ static void ggml_vk_load_shaders(vk_device& device) {
CREATE_MM(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_K].f16acc, matmul_id_q4_k_f32, _f16acc, mmq_wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
CREATE_MM(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_K].f16acc, matmul_id_q5_k_f32, _f16acc, mmq_wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
CREATE_MM(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q6_K].f16acc, matmul_id_q6_k_f32, _f16acc, mmq_wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
CREATE_MM(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ4_NL].f16acc, matmul_id_iq4_nl_f32, _f16acc, mmq_wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
CREATE_MM(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ2_XXS].f16acc, matmul_id_iq2_xxs_f32, _f16acc, mmq_wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
CREATE_MM(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ2_XS].f16acc, matmul_id_iq2_xs_f32, _f16acc, mmq_wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
CREATE_MM(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ2_S].f16acc, matmul_id_iq2_s_f32, _f16acc, mmq_wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
CREATE_MM(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ3_XXS].f16acc, matmul_id_iq3_xxs_f32, _f16acc, mmq_wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
CREATE_MM(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ3_S].f16acc, matmul_id_iq3_s_f32, _f16acc, mmq_wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
CREATE_MM(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ4_NL].f16acc, matmul_id_iq4_nl_f32, _f16acc, mmq_wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
}
#undef CREATE_MM2
#undef CREATE_MM
@ -1845,7 +1896,12 @@ static void ggml_vk_load_shaders(vk_device& device) {
CREATE_MM(pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_K].f32acc, matmul_q4_k_f32, , mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
CREATE_MM(pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_K].f32acc, matmul_q5_k_f32, , mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
CREATE_MM(pipeline_dequant_mul_mat_mat[GGML_TYPE_Q6_K].f32acc, matmul_q6_k_f32, , mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
CREATE_MM(pipeline_dequant_mul_mat_mat[GGML_TYPE_IQ4_NL].f32acc, matmul_iq4_nl_f32, , mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
CREATE_MM(pipeline_dequant_mul_mat_mat[GGML_TYPE_IQ2_XXS].f32acc, matmul_iq2_xxs_f32, , mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
CREATE_MM(pipeline_dequant_mul_mat_mat[GGML_TYPE_IQ2_XS].f32acc, matmul_iq2_xs_f32, , mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
CREATE_MM(pipeline_dequant_mul_mat_mat[GGML_TYPE_IQ2_S].f32acc, matmul_iq2_s_f32, , mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
CREATE_MM(pipeline_dequant_mul_mat_mat[GGML_TYPE_IQ3_XXS].f32acc, matmul_iq3_xxs_f32, , mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
CREATE_MM(pipeline_dequant_mul_mat_mat[GGML_TYPE_IQ3_S].f32acc, matmul_iq3_s_f32, , mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
CREATE_MM(pipeline_dequant_mul_mat_mat[GGML_TYPE_IQ4_NL].f32acc, matmul_iq4_nl_f32, , mmq_wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
// If there's not enough shared memory for row_ids and the result tile, don't create these pipelines.
if (device->mul_mat_id_s || device->mul_mat_id_m || device->mul_mat_id_l) {
@ -1864,7 +1920,12 @@ static void ggml_vk_load_shaders(vk_device& device) {
CREATE_MM(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_K].f32acc, matmul_id_q4_k_f32, , mmq_wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
CREATE_MM(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_K].f32acc, matmul_id_q5_k_f32, , mmq_wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
CREATE_MM(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q6_K].f32acc, matmul_id_q6_k_f32, , mmq_wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
CREATE_MM(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ4_NL].f32acc, matmul_id_iq4_nl_f32, , mmq_wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
CREATE_MM(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ2_XXS].f32acc, matmul_id_iq2_xxs_f32, , mmq_wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
CREATE_MM(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ2_XS].f32acc, matmul_id_iq2_xs_f32, , mmq_wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
CREATE_MM(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ2_S].f32acc, matmul_id_iq2_s_f32, , mmq_wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
CREATE_MM(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ3_XXS].f32acc, matmul_id_iq3_xxs_f32, , mmq_wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
CREATE_MM(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ3_S].f32acc, matmul_id_iq3_s_f32, , mmq_wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
CREATE_MM(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ4_NL].f32acc, matmul_id_iq4_nl_f32, , mmq_wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
}
#undef CREATE_MM
}
@ -1895,7 +1956,12 @@ static void ggml_vk_load_shaders(vk_device& device) {
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f32_f32[GGML_TYPE_Q4_K][i], "mul_mat_vec_q4_k_f32_f32_"+std::to_string(i+1), mul_mat_vec_q4_k_f32_f32_len, mul_mat_vec_q4_k_f32_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {rm_kq, 1, 1}, {subgroup_size_16, rm_kq, i+1}, 1, true);
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f32_f32[GGML_TYPE_Q5_K][i], "mul_mat_vec_q5_k_f32_f32_"+std::to_string(i+1), mul_mat_vec_q5_k_f32_f32_len, mul_mat_vec_q5_k_f32_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {rm_kq, 1, 1}, {subgroup_size_16, rm_kq, i+1}, 1, true);
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f32_f32[GGML_TYPE_Q6_K][i], "mul_mat_vec_q6_k_f32_f32_"+std::to_string(i+1), mul_mat_vec_q6_k_f32_f32_len, mul_mat_vec_q6_k_f32_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {rm_kq, 1, 1}, {subgroup_size_16, rm_kq, i+1}, 1, true);
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f32_f32[GGML_TYPE_IQ4_NL][i], "mul_mat_vec_iq4_nl_f32_f32_"+std::to_string(i+1), mul_mat_vec_iq4_nl_f32_f32_len, mul_mat_vec_iq4_nl_f32_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {2*rm_stdq, 1, 1}, {subgroup_size_16, 2*rm_stdq, i+1}, 1, true);
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f32_f32[GGML_TYPE_IQ2_XXS][i], "mul_mat_vec_iq2_xxs_f32_f32_"+std::to_string(i+1), mul_mat_vec_iq2_xxs_f32_f32_len, mul_mat_vec_iq2_xxs_f32_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {rm_kq, 1, 1}, {subgroup_size_16, rm_kq, i+1}, 1, true);
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f32_f32[GGML_TYPE_IQ2_XS][i], "mul_mat_vec_iq2_xs_f32_f32_"+std::to_string(i+1), mul_mat_vec_iq2_xs_f32_f32_len, mul_mat_vec_iq2_xs_f32_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {rm_kq, 1, 1}, {subgroup_size_16, rm_kq, i+1}, 1, true);
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f32_f32[GGML_TYPE_IQ2_S][i], "mul_mat_vec_iq2_s_f32_f32_"+std::to_string(i+1), mul_mat_vec_iq2_s_f32_f32_len, mul_mat_vec_iq2_s_f32_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {rm_kq, 1, 1}, {subgroup_size_16, rm_kq, i+1}, 1, true);
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f32_f32[GGML_TYPE_IQ3_XXS][i], "mul_mat_vec_iq3_xxs_f32_f32_"+std::to_string(i+1), mul_mat_vec_iq3_xxs_f32_f32_len, mul_mat_vec_iq3_xxs_f32_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {rm_kq, 1, 1}, {subgroup_size_16, rm_kq, i+1}, 1, true);
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f32_f32[GGML_TYPE_IQ3_S][i], "mul_mat_vec_iq3_s_f32_f32_"+std::to_string(i+1), mul_mat_vec_iq3_s_f32_f32_len, mul_mat_vec_iq3_s_f32_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {rm_kq, 1, 1}, {subgroup_size_16, rm_kq, i+1}, 1, true);
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f32_f32[GGML_TYPE_IQ4_NL][i], "mul_mat_vec_iq4_nl_f32_f32_"+std::to_string(i+1), mul_mat_vec_iq4_nl_f32_f32_len, mul_mat_vec_iq4_nl_f32_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {2*rm_stdq, 1, 1}, {subgroup_size_16, 2*rm_stdq, i+1}, 1, true);
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f16_f32[GGML_TYPE_F32 ][i], "mul_mat_vec_f32_f16_f32_"+std::to_string(i+1), mul_mat_vec_f32_f16_f32_len, mul_mat_vec_f32_f16_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {2, 1, 1}, {device->subgroup_size, 2, i+1}, 1);
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f16_f32[GGML_TYPE_F16 ][i], "mul_mat_vec_f16_f16_f32_"+std::to_string(i+1), mul_mat_vec_f16_f16_f32_len, mul_mat_vec_f16_f16_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {2, 1, 1}, {device->subgroup_size, 2, i+1}, 1);
@ -1909,7 +1975,12 @@ static void ggml_vk_load_shaders(vk_device& device) {
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f16_f32[GGML_TYPE_Q4_K][i], "mul_mat_vec_q4_k_f16_f32_"+std::to_string(i+1), mul_mat_vec_q4_k_f16_f32_len, mul_mat_vec_q4_k_f16_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {rm_kq, 1, 1}, {subgroup_size_16, rm_kq, i+1}, 1, true);
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f16_f32[GGML_TYPE_Q5_K][i], "mul_mat_vec_q5_k_f16_f32_"+std::to_string(i+1), mul_mat_vec_q5_k_f16_f32_len, mul_mat_vec_q5_k_f16_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {rm_kq, 1, 1}, {subgroup_size_16, rm_kq, i+1}, 1, true);
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f16_f32[GGML_TYPE_Q6_K][i], "mul_mat_vec_q6_k_f16_f32_"+std::to_string(i+1), mul_mat_vec_q6_k_f16_f32_len, mul_mat_vec_q6_k_f16_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {rm_kq, 1, 1}, {subgroup_size_16, rm_kq, i+1}, 1, true);
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f16_f32[GGML_TYPE_IQ4_NL][i], "mul_mat_vec_iq4_nl_f16_f32_"+std::to_string(i+1), mul_mat_vec_iq4_nl_f16_f32_len, mul_mat_vec_iq4_nl_f16_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {2*rm_stdq, 1, 1}, {subgroup_size_16, 2*rm_stdq, i+1}, 1, true);
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f16_f32[GGML_TYPE_IQ2_XXS][i], "mul_mat_vec_iq2_xxs_f16_f32_"+std::to_string(i+1), mul_mat_vec_iq2_xxs_f16_f32_len, mul_mat_vec_iq2_xxs_f16_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {rm_kq, 1, 1}, {subgroup_size_16, rm_kq, i+1}, 1, true);
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f16_f32[GGML_TYPE_IQ2_XS][i], "mul_mat_vec_iq2_xs_f16_f32_"+std::to_string(i+1), mul_mat_vec_iq2_xs_f16_f32_len, mul_mat_vec_iq2_xs_f16_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {rm_kq, 1, 1}, {subgroup_size_16, rm_kq, i+1}, 1, true);
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f16_f32[GGML_TYPE_IQ2_S][i], "mul_mat_vec_iq2_s_f16_f32_"+std::to_string(i+1), mul_mat_vec_iq2_s_f16_f32_len, mul_mat_vec_iq2_s_f16_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {rm_kq, 1, 1}, {subgroup_size_16, rm_kq, i+1}, 1, true);
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f16_f32[GGML_TYPE_IQ3_XXS][i], "mul_mat_vec_iq3_xxs_f16_f32_"+std::to_string(i+1), mul_mat_vec_iq3_xxs_f16_f32_len, mul_mat_vec_iq3_xxs_f16_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {rm_kq, 1, 1}, {subgroup_size_16, rm_kq, i+1}, 1, true);
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f16_f32[GGML_TYPE_IQ3_S][i], "mul_mat_vec_iq3_s_f16_f32_"+std::to_string(i+1), mul_mat_vec_iq3_s_f16_f32_len, mul_mat_vec_iq3_s_f16_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {rm_kq, 1, 1}, {subgroup_size_16, rm_kq, i+1}, 1, true);
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_f16_f32[GGML_TYPE_IQ4_NL][i], "mul_mat_vec_iq4_nl_f16_f32_"+std::to_string(i+1), mul_mat_vec_iq4_nl_f16_f32_len, mul_mat_vec_iq4_nl_f16_f32_data, "main", 3, sizeof(vk_mat_vec_push_constants), {2*rm_stdq, 1, 1}, {subgroup_size_16, 2*rm_stdq, i+1}, 1, true);
}
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_id_f32[GGML_TYPE_F32 ], "mul_mat_vec_id_f32_f32", mul_mat_vec_id_f32_f32_len, mul_mat_vec_id_f32_f32_data, "main", 4, sizeof(vk_mat_vec_id_push_constants), {2, 1, 1}, {device->subgroup_size, 2}, 1);
@ -1924,7 +1995,12 @@ static void ggml_vk_load_shaders(vk_device& device) {
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_id_f32[GGML_TYPE_Q4_K], "mul_mat_vec_id_q4_k_f32", mul_mat_vec_id_q4_k_f32_len, mul_mat_vec_id_q4_k_f32_data, "main", 4, sizeof(vk_mat_vec_id_push_constants), {rm_kq, 1, 1}, {subgroup_size_16, rm_kq}, 1, true);
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_id_f32[GGML_TYPE_Q5_K], "mul_mat_vec_id_q5_k_f32", mul_mat_vec_id_q5_k_f32_len, mul_mat_vec_id_q5_k_f32_data, "main", 4, sizeof(vk_mat_vec_id_push_constants), {rm_kq, 1, 1}, {subgroup_size_16, rm_kq}, 1, true);
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_id_f32[GGML_TYPE_Q6_K], "mul_mat_vec_id_q6_k_f32", mul_mat_vec_id_q6_k_f32_len, mul_mat_vec_id_q6_k_f32_data, "main", 4, sizeof(vk_mat_vec_id_push_constants), {rm_kq, 1, 1}, {subgroup_size_16, rm_kq}, 1, true);
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_id_f32[GGML_TYPE_IQ4_NL], "mul_mat_vec_id_iq4_nl_f32", mul_mat_vec_id_iq4_nl_f32_len, mul_mat_vec_id_iq4_nl_f32_data, "main", 4, sizeof(vk_mat_vec_id_push_constants), {2*rm_stdq, 1, 1}, {subgroup_size_16, 2*rm_stdq}, 1, true);
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_id_f32[GGML_TYPE_IQ2_XXS], "mul_mat_vec_id_iq2_xxs_f32", mul_mat_vec_id_iq2_xxs_f32_len, mul_mat_vec_id_iq2_xxs_f32_data, "main", 4, sizeof(vk_mat_vec_id_push_constants), {rm_kq, 1, 1}, {subgroup_size_16, rm_kq}, 1, true);
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_id_f32[GGML_TYPE_IQ2_XS], "mul_mat_vec_id_iq2_xs_f32", mul_mat_vec_id_iq2_xs_f32_len, mul_mat_vec_id_iq2_xs_f32_data, "main", 4, sizeof(vk_mat_vec_id_push_constants), {rm_kq, 1, 1}, {subgroup_size_16, rm_kq}, 1, true);
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_id_f32[GGML_TYPE_IQ2_S], "mul_mat_vec_id_iq2_s_f32", mul_mat_vec_id_iq2_s_f32_len, mul_mat_vec_id_iq2_s_f32_data, "main", 4, sizeof(vk_mat_vec_id_push_constants), {rm_kq, 1, 1}, {subgroup_size_16, rm_kq}, 1, true);
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_id_f32[GGML_TYPE_IQ3_XXS], "mul_mat_vec_id_iq3_xxs_f32", mul_mat_vec_id_iq3_xxs_f32_len, mul_mat_vec_id_iq3_xxs_f32_data, "main", 4, sizeof(vk_mat_vec_id_push_constants), {rm_kq, 1, 1}, {subgroup_size_16, rm_kq}, 1, true);
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_id_f32[GGML_TYPE_IQ3_S], "mul_mat_vec_id_iq3_s_f32", mul_mat_vec_id_iq3_s_f32_len, mul_mat_vec_id_iq3_s_f32_data, "main", 4, sizeof(vk_mat_vec_id_push_constants), {rm_kq, 1, 1}, {subgroup_size_16, rm_kq}, 1, true);
ggml_vk_create_pipeline(device, device->pipeline_dequant_mul_mat_vec_id_f32[GGML_TYPE_IQ4_NL], "mul_mat_vec_id_iq4_nl_f32", mul_mat_vec_id_iq4_nl_f32_len, mul_mat_vec_id_iq4_nl_f32_data, "main", 4, sizeof(vk_mat_vec_id_push_constants), {2*rm_stdq, 1, 1}, {subgroup_size_16, 2*rm_stdq}, 1, true);
// dequant shaders
ggml_vk_create_pipeline(device, device->pipeline_dequant[GGML_TYPE_F32 ], "f32_to_f16", dequant_f32_len, dequant_f32_data, "main", 2, 5 * sizeof(uint32_t), {256 * 16, 1, 1}, {}, 1);
@ -1938,7 +2014,12 @@ static void ggml_vk_load_shaders(vk_device& device) {
ggml_vk_create_pipeline(device, device->pipeline_dequant[GGML_TYPE_Q4_K], "dequant_q4_k", dequant_q4_k_len, dequant_q4_k_data, "main", 2, 5 * sizeof(uint32_t), {256 * 32, 1, 1}, {}, 1);
ggml_vk_create_pipeline(device, device->pipeline_dequant[GGML_TYPE_Q5_K], "dequant_q5_k", dequant_q5_k_len, dequant_q5_k_data, "main", 2, 5 * sizeof(uint32_t), {256 * 64, 1, 1}, {}, 1);
ggml_vk_create_pipeline(device, device->pipeline_dequant[GGML_TYPE_Q6_K], "dequant_q6_k", dequant_q6_k_len, dequant_q6_k_data, "main", 2, 5 * sizeof(uint32_t), {256 * 64, 1, 1}, {}, 1);
ggml_vk_create_pipeline(device, device->pipeline_dequant[GGML_TYPE_IQ4_NL], "dequant_iq4_nl", dequant_iq4_nl_len, dequant_iq4_nl_data, "main", 2, 5 * sizeof(uint32_t), {256 * 16, 1, 1}, {}, 1);
ggml_vk_create_pipeline(device, device->pipeline_dequant[GGML_TYPE_IQ2_XXS], "dequant_iq2_xxs", dequant_iq2_xxs_len, dequant_iq2_xxs_data, "main", 2, 5 * sizeof(uint32_t), {256 * 32, 1, 1}, {}, 1);
ggml_vk_create_pipeline(device, device->pipeline_dequant[GGML_TYPE_IQ2_XS], "dequant_iq2_xs", dequant_iq2_xs_len, dequant_iq2_xs_data, "main", 2, 5 * sizeof(uint32_t), {256 * 32, 1, 1}, {}, 1);
ggml_vk_create_pipeline(device, device->pipeline_dequant[GGML_TYPE_IQ2_S], "dequant_iq2_s", dequant_iq2_s_len, dequant_iq2_s_data, "main", 2, 5 * sizeof(uint32_t), {256 * 32, 1, 1}, {}, 1);
ggml_vk_create_pipeline(device, device->pipeline_dequant[GGML_TYPE_IQ3_XXS], "dequant_iq3_xxs", dequant_iq3_xxs_len, dequant_iq3_xxs_data, "main", 2, 5 * sizeof(uint32_t), {256 * 32, 1, 1}, {}, 1);
ggml_vk_create_pipeline(device, device->pipeline_dequant[GGML_TYPE_IQ3_S], "dequant_iq3_s", dequant_iq3_s_len, dequant_iq3_s_data, "main", 2, 5 * sizeof(uint32_t), {256 * 32, 1, 1}, {}, 1);
ggml_vk_create_pipeline(device, device->pipeline_dequant[GGML_TYPE_IQ4_NL], "dequant_iq4_nl", dequant_iq4_nl_len, dequant_iq4_nl_data, "main", 2, 5 * sizeof(uint32_t), {256 * 16, 1, 1}, {}, 1);
// get_rows
ggml_vk_create_pipeline(device, device->pipeline_get_rows[GGML_TYPE_F32 ], "get_rows_f32", get_rows_f32_len, get_rows_f32_data, "main", 3, sizeof(vk_op_binary_push_constants), { 512, 1, 1}, {}, 1);
@ -1948,7 +2029,12 @@ static void ggml_vk_load_shaders(vk_device& device) {
ggml_vk_create_pipeline(device, device->pipeline_get_rows[GGML_TYPE_Q5_0], "get_rows_q5_0", get_rows_q5_0_len, get_rows_q5_0_data, "main", 3, sizeof(vk_op_binary_push_constants), {1024, 1, 1}, {}, 1);
ggml_vk_create_pipeline(device, device->pipeline_get_rows[GGML_TYPE_Q5_1], "get_rows_q5_1", get_rows_q5_1_len, get_rows_q5_1_data, "main", 3, sizeof(vk_op_binary_push_constants), {1024, 1, 1}, {}, 1);
ggml_vk_create_pipeline(device, device->pipeline_get_rows[GGML_TYPE_Q8_0], "get_rows_q8_0", get_rows_q8_0_len, get_rows_q8_0_data, "main", 3, sizeof(vk_op_binary_push_constants), {1024, 1, 1}, {}, 1);
ggml_vk_create_pipeline(device, device->pipeline_get_rows[GGML_TYPE_IQ4_NL], "get_rows_iq4_nl", get_rows_iq4_nl_len, get_rows_iq4_nl_data, "main", 3, sizeof(vk_op_binary_push_constants), {1024, 1, 1}, {}, 1);
ggml_vk_create_pipeline(device, device->pipeline_get_rows[GGML_TYPE_IQ2_XXS], "get_rows_iq2_xxs", get_rows_iq2_xxs_len, get_rows_iq2_xxs_data, "main", 3, sizeof(vk_op_binary_push_constants), {1024, 1, 1}, {}, 1);
ggml_vk_create_pipeline(device, device->pipeline_get_rows[GGML_TYPE_IQ2_XS], "get_rows_iq2_xs", get_rows_iq2_xs_len, get_rows_iq2_xs_data, "main", 3, sizeof(vk_op_binary_push_constants), {1024, 1, 1}, {}, 1);
ggml_vk_create_pipeline(device, device->pipeline_get_rows[GGML_TYPE_IQ2_S], "get_rows_iq2_s", get_rows_iq2_s_len, get_rows_iq2_s_data, "main", 3, sizeof(vk_op_binary_push_constants), {1024, 1, 1}, {}, 1);
ggml_vk_create_pipeline(device, device->pipeline_get_rows[GGML_TYPE_IQ3_XXS], "get_rows_iq3_xxs", get_rows_iq3_xxs_len, get_rows_iq3_xxs_data, "main", 3, sizeof(vk_op_binary_push_constants), {1024, 1, 1}, {}, 1);
ggml_vk_create_pipeline(device, device->pipeline_get_rows[GGML_TYPE_IQ3_S], "get_rows_iq3_s", get_rows_iq3_s_len, get_rows_iq3_s_data, "main", 3, sizeof(vk_op_binary_push_constants), {1024, 1, 1}, {}, 1);
ggml_vk_create_pipeline(device, device->pipeline_get_rows[GGML_TYPE_IQ4_NL], "get_rows_iq4_nl", get_rows_iq4_nl_len, get_rows_iq4_nl_data, "main", 3, sizeof(vk_op_binary_push_constants), {1024, 1, 1}, {}, 1);
ggml_vk_create_pipeline(device, device->pipeline_get_rows_f32[GGML_TYPE_F32 ], "get_rows_f32_f32", get_rows_f32_f32_len, get_rows_f32_f32_data, "main", 3, sizeof(vk_op_binary_push_constants), { 512, 1, 1}, {}, 1);
ggml_vk_create_pipeline(device, device->pipeline_get_rows_f32[GGML_TYPE_F16 ], "get_rows_f16_f32", get_rows_f16_f32_len, get_rows_f16_f32_data, "main", 3, sizeof(vk_op_binary_push_constants), { 512, 1, 1}, {}, 1);
@ -1957,7 +2043,12 @@ static void ggml_vk_load_shaders(vk_device& device) {
ggml_vk_create_pipeline(device, device->pipeline_get_rows_f32[GGML_TYPE_Q5_0], "get_rows_q5_0_f32", get_rows_q5_0_f32_len, get_rows_q5_0_f32_data, "main", 3, sizeof(vk_op_binary_push_constants), {1024, 1, 1}, {}, 1);
ggml_vk_create_pipeline(device, device->pipeline_get_rows_f32[GGML_TYPE_Q5_1], "get_rows_q5_1_f32", get_rows_q5_1_f32_len, get_rows_q5_1_f32_data, "main", 3, sizeof(vk_op_binary_push_constants), {1024, 1, 1}, {}, 1);
ggml_vk_create_pipeline(device, device->pipeline_get_rows_f32[GGML_TYPE_Q8_0], "get_rows_q8_0_f32", get_rows_q8_0_f32_len, get_rows_q8_0_f32_data, "main", 3, sizeof(vk_op_binary_push_constants), {1024, 1, 1}, {}, 1);
ggml_vk_create_pipeline(device, device->pipeline_get_rows_f32[GGML_TYPE_IQ4_NL], "get_rows_iq4_nl_f32", get_rows_iq4_nl_f32_len, get_rows_iq4_nl_f32_data, "main", 3, sizeof(vk_op_binary_push_constants), {1024, 1, 1}, {}, 1);
ggml_vk_create_pipeline(device, device->pipeline_get_rows_f32[GGML_TYPE_IQ2_XXS], "get_rows_iq2_xxs_f32", get_rows_iq2_xxs_f32_len, get_rows_iq2_xxs_f32_data, "main", 3, sizeof(vk_op_binary_push_constants), {1024, 1, 1}, {}, 1);
ggml_vk_create_pipeline(device, device->pipeline_get_rows_f32[GGML_TYPE_IQ2_XS], "get_rows_iq2_xs_f32", get_rows_iq2_xs_f32_len, get_rows_iq2_xs_f32_data, "main", 3, sizeof(vk_op_binary_push_constants), {1024, 1, 1}, {}, 1);
ggml_vk_create_pipeline(device, device->pipeline_get_rows_f32[GGML_TYPE_IQ2_S], "get_rows_iq2_s_f32", get_rows_iq2_s_f32_len, get_rows_iq2_s_f32_data, "main", 3, sizeof(vk_op_binary_push_constants), {1024, 1, 1}, {}, 1);
ggml_vk_create_pipeline(device, device->pipeline_get_rows_f32[GGML_TYPE_IQ3_XXS], "get_rows_iq3_xxs_f32", get_rows_iq3_xxs_f32_len, get_rows_iq3_xxs_f32_data, "main", 3, sizeof(vk_op_binary_push_constants), {1024, 1, 1}, {}, 1);
ggml_vk_create_pipeline(device, device->pipeline_get_rows_f32[GGML_TYPE_IQ3_S], "get_rows_iq3_s_f32", get_rows_iq3_s_f32_len, get_rows_iq3_s_f32_data, "main", 3, sizeof(vk_op_binary_push_constants), {1024, 1, 1}, {}, 1);
ggml_vk_create_pipeline(device, device->pipeline_get_rows_f32[GGML_TYPE_IQ4_NL], "get_rows_iq4_nl_f32", get_rows_iq4_nl_f32_len, get_rows_iq4_nl_f32_data, "main", 3, sizeof(vk_op_binary_push_constants), {1024, 1, 1}, {}, 1);
ggml_vk_create_pipeline(device, device->pipeline_matmul_split_k_reduce, "split_k_reduce", split_k_reduce_len, split_k_reduce_data, "main", 2, 2 * sizeof(uint32_t), {256 * 4, 1, 1}, {}, 1);
@ -2884,6 +2975,11 @@ static vk_pipeline ggml_vk_get_to_fp16(ggml_backend_vk_context * ctx, ggml_type
case GGML_TYPE_Q4_K:
case GGML_TYPE_Q5_K:
case GGML_TYPE_Q6_K:
case GGML_TYPE_IQ2_XXS:
case GGML_TYPE_IQ2_XS:
case GGML_TYPE_IQ2_S:
case GGML_TYPE_IQ3_XXS:
case GGML_TYPE_IQ3_S:
case GGML_TYPE_IQ4_NL:
break;
default:
@ -2932,6 +3028,11 @@ static vk_matmul_pipeline ggml_vk_get_mul_mat_mat_pipeline(ggml_backend_vk_conte
case GGML_TYPE_Q4_K:
case GGML_TYPE_Q5_K:
case GGML_TYPE_Q6_K:
case GGML_TYPE_IQ2_XXS:
case GGML_TYPE_IQ2_XS:
case GGML_TYPE_IQ2_S:
case GGML_TYPE_IQ3_XXS:
case GGML_TYPE_IQ3_S:
case GGML_TYPE_IQ4_NL:
break;
default:
@ -2963,6 +3064,11 @@ static vk_pipeline ggml_vk_get_dequantize_mul_mat_vec(ggml_backend_vk_context *
case GGML_TYPE_Q4_K:
case GGML_TYPE_Q5_K:
case GGML_TYPE_Q6_K:
case GGML_TYPE_IQ2_XXS:
case GGML_TYPE_IQ2_XS:
case GGML_TYPE_IQ2_S:
case GGML_TYPE_IQ3_XXS:
case GGML_TYPE_IQ3_S:
case GGML_TYPE_IQ4_NL:
break;
default:
@ -3006,6 +3112,11 @@ static vk_matmul_pipeline ggml_vk_get_mul_mat_mat_id_pipeline(ggml_backend_vk_co
case GGML_TYPE_Q4_K:
case GGML_TYPE_Q5_K:
case GGML_TYPE_Q6_K:
case GGML_TYPE_IQ2_XXS:
case GGML_TYPE_IQ2_XS:
case GGML_TYPE_IQ2_S:
case GGML_TYPE_IQ3_XXS:
case GGML_TYPE_IQ3_S:
case GGML_TYPE_IQ4_NL:
break;
default:
@ -3032,6 +3143,11 @@ static vk_pipeline ggml_vk_get_dequantize_mul_mat_vec_id(ggml_backend_vk_context
case GGML_TYPE_Q4_K:
case GGML_TYPE_Q5_K:
case GGML_TYPE_Q6_K:
case GGML_TYPE_IQ2_XXS:
case GGML_TYPE_IQ2_XS:
case GGML_TYPE_IQ2_S:
case GGML_TYPE_IQ3_XXS:
case GGML_TYPE_IQ3_S:
case GGML_TYPE_IQ4_NL:
break;
default:
@ -7901,6 +8017,11 @@ static bool ggml_backend_vk_device_supports_op(ggml_backend_dev_t dev, const ggm
case GGML_TYPE_Q4_K:
case GGML_TYPE_Q5_K:
case GGML_TYPE_Q6_K:
case GGML_TYPE_IQ2_XXS:
case GGML_TYPE_IQ2_XS:
case GGML_TYPE_IQ2_S:
case GGML_TYPE_IQ3_XXS:
case GGML_TYPE_IQ3_S:
case GGML_TYPE_IQ4_NL:
break;
default:
@ -7969,6 +8090,11 @@ static bool ggml_backend_vk_device_supports_op(ggml_backend_dev_t dev, const ggm
//case GGML_TYPE_Q4_K:
//case GGML_TYPE_Q5_K:
//case GGML_TYPE_Q6_K:
//case GGML_TYPE_IQ2_XXS:
//case GGML_TYPE_IQ2_XS:
//case GGML_TYPE_IQ2_S:
//case GGML_TYPE_IQ3_XXS:
//case GGML_TYPE_IQ3_S:
case GGML_TYPE_IQ4_NL:
break;
default:
@ -7986,6 +8112,11 @@ static bool ggml_backend_vk_device_supports_op(ggml_backend_dev_t dev, const ggm
case GGML_TYPE_Q5_0:
case GGML_TYPE_Q5_1:
case GGML_TYPE_Q8_0:
case GGML_TYPE_IQ2_XXS:
case GGML_TYPE_IQ2_XS:
case GGML_TYPE_IQ2_S:
case GGML_TYPE_IQ3_XXS:
case GGML_TYPE_IQ3_S:
case GGML_TYPE_IQ4_NL:
return true;
default:

4
ggml/src/ggml-vulkan/vulkan-shaders/copy_from_quant.comp
View file

@ -12,8 +12,8 @@ layout(local_size_x = 1, local_size_y = 1, local_size_z = 1) in;
#endif
void main() {
#if defined(DATA_A_IQ4_NL)
init_iq4nl_shmem();
#if defined(DATA_A_IQ2_XXS) || defined(DATA_A_IQ2_XS) || defined(DATA_A_IQ2_S) || defined(DATA_A_IQ3_XXS) || defined(DATA_A_IQ3_S) || defined(DATA_A_IQ4_NL)
init_iq_shmem(gl_WorkGroupSize);
if (gl_LocalInvocationIndex.x != 0) {
return;
}

4
ggml/src/ggml-vulkan/vulkan-shaders/copy_to_quant.comp
View file

@ -217,8 +217,8 @@ void quantize(uint dst_idx, uint src_idx)
#endif
void main() {
#if defined(DATA_A_IQ4_NL)
init_iq4nl_shmem();
#if defined(DATA_A_IQ2_XXS) || defined(DATA_A_IQ2_XS) || defined(DATA_A_IQ2_S) || defined(DATA_A_IQ3_XXS) || defined(DATA_A_IQ3_S) || defined(DATA_A_IQ4_NL)
init_iq_shmem(gl_WorkGroupSize);
if (gl_LocalInvocationIndex.x != 0) {
return;
}

218
ggml/src/ggml-vulkan/vulkan-shaders/dequant_funcs.comp
View file

@ -88,6 +88,222 @@ vec4 dequantize4(uint ib, uint iqs, uint a_offset) {
}
#endif
#if defined(DATA_A_IQ2_XXS)
vec2 dequantize(uint ib, uint iqs, uint a_offset) {
const uint ib32 = iqs / 32;
const uint ib8 = (iqs / 8) % 4;
const uint qs = data_a[a_offset + ib].qs[8 * ib32 + ib8];
// Scales are stored as packed 7+7+7+7+4 bits (4 sign tuples and 1 int4 scale)
const uint signs = pack32(u16vec2(data_a_packed16[a_offset + ib].qs[4 * ib32 + 2],
data_a_packed16[a_offset + ib].qs[4 * ib32 + 3]));
const float db = 0.25 * (0.5 + (signs >> 28));
const uint sign7 = bitfieldExtract(signs, 7 * int(ib8), 7);
// Add parity bit
const uint sign8 = sign7 | (bitCount(sign7) << 7);
const uint sign = sign8 >> (iqs % 8);
const u8vec4 grid = unpack8(iq2xxs_grid[qs][(iqs % 8) / 4] >> (8 * (iqs % 4)));
bool sign0 = (sign & 1) != 0;
bool sign1 = (sign & 2) != 0;
return db * vec2(
grid.x * (sign0 ? -1.0 : 1.0),
grid.y * (sign1 ? -1.0 : 1.0)
);
}
vec4 dequantize4(uint ib, uint iqs, uint a_offset) {
const uint ib32 = iqs / 32;
const uint ib8 = (iqs / 8) % 4;
const uint qs = data_a[a_offset + ib].qs[8 * ib32 + ib8];
// Scales are stored as packed 7+7+7+7+4 bits (4 sign tuples and 1 int4 scale)
const uint signs = pack32(u16vec2(data_a_packed16[a_offset + ib].qs[4 * ib32 + 2],
data_a_packed16[a_offset + ib].qs[4 * ib32 + 3]));
const float db = 0.25 * (0.5 + (signs >> 28));
const uint sign7 = bitfieldExtract(signs, 7 * int(ib8), 7);
// Add parity bit
const uint sign8 = sign7 | (bitCount(sign7) << 7);
const uint sign = sign8 >> (iqs % 8);
const u8vec4 grid = unpack8(iq2xxs_grid[qs][(iqs % 8) / 4] >> (8 * (iqs % 4)));
bool sign0 = (sign & 1) != 0;
bool sign1 = (sign & 2) != 0;
bool sign2 = (sign & 4) != 0;
bool sign3 = (sign & 8) != 0;
return db * vec4(
grid.x * (sign0 ? -1.0 : 1.0),
grid.y * (sign1 ? -1.0 : 1.0),
grid.z * (sign2 ? -1.0 : 1.0),
grid.w * (sign3 ? -1.0 : 1.0)
);
}
#endif
#if defined(DATA_A_IQ2_XS)
vec2 dequantize(uint ib, uint iqs, uint a_offset) {
const uint scale = (data_a[a_offset + ib].scales[iqs / 32] >> (4 * ((iqs / 16) & 1))) & 0xf;
const uint qs = data_a[a_offset + ib].qs[iqs / 8];
const float db = 0.25 * (0.5 + scale);
const uint sign7 = qs >> 9;
// Add parity bit
const uint sign8 = sign7 | (bitCount(sign7) << 7);
const uint sign = sign8 >> (iqs % 8);
const u8vec4 grid = unpack8(iq2xs_grid[qs & 511][(iqs % 8) / 4] >> (8 * (iqs % 4)));
bool sign0 = (sign & 1) != 0;
bool sign1 = (sign & 2) != 0;
return db * vec2(
grid.x * (sign0 ? -1.0 : 1.0),
grid.y * (sign1 ? -1.0 : 1.0)
);
}
vec4 dequantize4(uint ib, uint iqs, uint a_offset) {
const uint scale = (data_a[a_offset + ib].scales[iqs / 32] >> (4 * ((iqs / 16) & 1))) & 0xf;
const uint qs = data_a[a_offset + ib].qs[iqs / 8];
const float db = 0.25 * (0.5 + scale);
const uint sign7 = qs >> 9;
// Add parity bit
const uint sign8 = sign7 | (bitCount(sign7) << 7);
const uint sign = sign8 >> (iqs % 8);
const u8vec4 grid = unpack8(iq2xs_grid[qs & 511][(iqs % 8) / 4] >> (8 * (iqs % 4)));
bool sign0 = (sign & 1) != 0;
bool sign1 = (sign & 2) != 0;
bool sign2 = (sign & 4) != 0;
bool sign3 = (sign & 8) != 0;
return db * vec4(
grid.x * (sign0 ? -1.0 : 1.0),
grid.y * (sign1 ? -1.0 : 1.0),
grid.z * (sign2 ? -1.0 : 1.0),
grid.w * (sign3 ? -1.0 : 1.0)
);
}
#endif
#if defined(DATA_A_IQ2_S)
vec2 dequantize(uint ib, uint iqs, uint a_offset) {
const uint ib32 = iqs / 32;
const uint ib8 = iqs / 8;
const uint scale = (data_a[a_offset + ib].scales[ib32] >> (4 * ((iqs / 16) & 1))) & 0xf;
const uint qs = data_a[a_offset + ib].qs[ib8];
const uint qh = data_a[a_offset + ib].qh[ib32];
const uint qhshift = 2 * (ib8 % 4);
const uint sign = data_a[a_offset + ib].qs[QUANT_K / 8 + ib8] >> (iqs % 8);
const float db = 0.25 * (0.5 + scale);
const u8vec4 grid = unpack8(iq2s_grid[qs | ((qh << (8 - qhshift)) & 0x300)][(iqs % 8) / 4]);
bool sign0 = (sign & 1) != 0;
bool sign1 = (sign & 2) != 0;
return db * vec2(
grid[iqs % 4] * (sign0 ? -1.0 : 1.0),
grid[(iqs % 4) + 1] * (sign1 ? -1.0 : 1.0)
);
}
vec4 dequantize4(uint ib, uint iqs, uint a_offset) {
const uint ib32 = iqs / 32;
const uint ib8 = iqs / 8;
const uint scale = (data_a[a_offset + ib].scales[ib32] >> (4 * ((iqs / 16) & 1))) & 0xf;
const uint qs = data_a[a_offset + ib].qs[ib8];
const uint qh = data_a[a_offset + ib].qh[ib32];
const uint qhshift = 2 * (ib8 % 4);
const uint sign = data_a[a_offset + ib].qs[QUANT_K / 8 + ib8] >> (iqs % 8);
const float db = 0.25 * (0.5 + scale);
const u8vec4 grid = unpack8(iq2s_grid[qs | ((qh << (8 - qhshift)) & 0x300)][(iqs % 8) / 4]);
bool sign0 = (sign & 1) != 0;
bool sign1 = (sign & 2) != 0;
bool sign2 = (sign & 4) != 0;
bool sign3 = (sign & 8) != 0;
return db * vec4(
grid.x * (sign0 ? -1.0 : 1.0),
grid.y * (sign1 ? -1.0 : 1.0),
grid.z * (sign2 ? -1.0 : 1.0),
grid.w * (sign3 ? -1.0 : 1.0)
);
}
#endif
#if defined(DATA_A_IQ3_XXS)
vec2 dequantize(uint ib, uint iqs, uint a_offset) {
const uint ib4 = iqs / 4;
const uint ib32 = iqs / 32;
const uint is = QUANT_K / 4 + 4 * ib32;
const uint qs = data_a[a_offset + ib].qs[ib4];
// Scales are stored as packed 7+7+7+7+4 bits (4 sign tuples and 1 int4 scale)
const uint signs = pack32(u16vec2(data_a_packed16[a_offset + ib].qs[is / 2],
data_a_packed16[a_offset + ib].qs[is / 2 + 1]));
const float db = 0.5 * (0.5 + (signs >> 28));
const uint sign7 = bitfieldExtract(signs, 7 * (int(ib4 / 2) % 4), 7);
// Add parity bit
const uint sign8 = sign7 | (bitCount(sign7) << 7);
const uint sign = sign8 >> (iqs % 8);
const u8vec4 grid = unpack8(iq3xxs_grid[qs] >> (8 * (iqs % 4)));
bool sign0 = (sign & 1) != 0;
bool sign1 = (sign & 2) != 0;
return db * vec2(
grid.x * (sign0 ? -1.0 : 1.0),
grid.y * (sign1 ? -1.0 : 1.0)
);
}
vec4 dequantize4(uint ib, uint iqs, uint a_offset) {
const uint ib4 = iqs / 4;
const uint ib32 = iqs / 32;
const uint is = QUANT_K / 4 + 4 * ib32;
const uint qs = data_a[a_offset + ib].qs[ib4];
const uint signs = pack32(u16vec2(data_a_packed16[a_offset + ib].qs[is / 2],
data_a_packed16[a_offset + ib].qs[is / 2 + 1]));
const float db = 0.5 * (0.5 + (signs >> 28));
const uint sign7 = bitfieldExtract(signs, 7 * (int(ib4 / 2) % 4), 7);
// Add parity bit
const uint sign8 = sign7 | (bitCount(sign7) << 7);
const uint sign = sign8 >> (iqs % 8);
const u8vec4 grid = unpack8(iq3xxs_grid[qs]);
bool sign0 = (sign & 1) != 0;
bool sign1 = (sign & 2) != 0;
bool sign2 = (sign & 4) != 0;
bool sign3 = (sign & 8) != 0;
return db * vec4(
grid.x * (sign0 ? -1.0 : 1.0),
grid.y * (sign1 ? -1.0 : 1.0),
grid.z * (sign2 ? -1.0 : 1.0),
grid.w * (sign3 ? -1.0 : 1.0)
);
}
#endif
#if defined(DATA_A_IQ3_S)
vec2 dequantize(uint ib, uint iqs, uint a_offset) {
const uint qs = data_a[a_offset + ib].qs[iqs / 4];
const uint qh = data_a[a_offset + ib].qh[iqs / 32];
const uint sign = data_a[a_offset + ib].signs[iqs / 8] >> (iqs % 8);
const uint scale = data_a[a_offset + ib].scales[iqs / 64];
bool sign0 = (sign & 1) != 0;
bool sign1 = (sign & 2) != 0;
const float db = 1 + 2 * ((scale >> (4 * ((iqs / 32) & 1))) & 0xf);
const uint32_t grid = iq3s_grid[qs | ((qh << (8 - ((iqs / 4) % 8))) & 256)] >> (8 * (iqs % 4));
return db * vec2(
int(grid & 0xFF) * (sign0 ? -1.0 : 1.0),
int((grid >> 8) & 0xFF) * (sign1 ? -1.0 : 1.0)
);
}
vec4 dequantize4(uint ib, uint iqs, uint a_offset) {
const uint ib4 = iqs / 4;
const uint ib32 = iqs / 32;
const uint qs = data_a[a_offset + ib].qs[ib4];
const uint qh = data_a[a_offset + ib].qh[ib32];
const uint sign = data_a[a_offset + ib].signs[iqs / 8] >> (iqs % 8);
const uint scale = data_a[a_offset + ib].scales[ib32 / 2];
bool sign0 = (sign & 1) != 0;
bool sign1 = (sign & 2) != 0;
bool sign2 = (sign & 4) != 0;
bool sign3 = (sign & 8) != 0;
const float db = 1 + 2 * ((scale >> (4 * (ib32 & 1))) & 0xf);
const uint32_t grid = iq3s_grid[qs | ((qh << (8 - ib4 % 8)) & 256)] >> (8 * (iqs % 4));
return db * vec4(
int(grid & 0xFF) * (sign0 ? -1.0 : 1.0),
int((grid >> 8) & 0xFF) * (sign1 ? -1.0 : 1.0),
int((grid >> 16) & 0xFF) * (sign2 ? -1.0 : 1.0),
int((grid >> 24) & 0xFF) * (sign3 ? -1.0 : 1.0)
);
}
#endif
#if defined(DATA_A_IQ4_NL)
vec2 dequantize(uint ib, uint iqs, uint a_offset) {
const uint vui = uint(data_a[a_offset + ib].qs[iqs]);
@ -105,7 +321,7 @@ vec2 get_dm(uint ib, uint a_offset) {
}
#endif
#if defined(DATA_A_Q4_0) || defined(DATA_A_Q5_0) || defined(DATA_A_Q8_0) || defined(DATA_A_IQ4_NL)
#if defined(DATA_A_Q4_0) || defined(DATA_A_Q5_0) || defined(DATA_A_Q8_0) || defined(DATA_A_IQ2_XXS) || defined(DATA_A_IQ2_XS) || defined(DATA_A_IQ2_S) || defined(DATA_A_IQ3_XXS) || defined(DATA_A_IQ3_S) || defined(DATA_A_IQ4_NL)
vec2 get_dm(uint ib, uint a_offset) {
return vec2(float(data_a[a_offset + ib].d), 0);
}

164
ggml/src/ggml-vulkan/vulkan-shaders/dequant_funcs_cm2.comp
View file

@ -301,6 +301,160 @@ float16_t dequantFuncQ6_K(const in decodeBufQ6_K bl, const in uint blockCoords[2
return ret;
}
#if defined(DATA_A_IQ2_XXS)
layout(buffer_reference, std430, buffer_reference_align = 2) buffer decodeBufIQ2_XXS {
block_iq2_xxs block;
};
layout(buffer_reference, std430, buffer_reference_align = 2) buffer decodeBufIQ2_XXS_packed16 {
block_iq2_xxs_packed16 block;
};
float16_t dequantFuncIQ2_XXS(const in decodeBufIQ2_XXS bl, const in uint blockCoords[2], const in uint coordInBlock[2])
{
decodeBufIQ2_XXS_packed16 bl16 = decodeBufIQ2_XXS_packed16(bl);
const float16_t d = bl.block.d;
const uint idx = coordInBlock[1];
const uint ib32 = (idx & 0xE0) >> 5; // 0..7
const uint ib8 = (idx & 0x18) >> 3; // 0..3
const uint iqs = 8 * ib32 + ib8;
const uint8_t qs = bl.block.qs[iqs];
const uint signscale = pack32(u16vec2(bl16.block.qs[4*ib32+2], bl16.block.qs[4*ib32+3]));
const float16_t dscale = bl.block.d * 0.25hf * (0.5hf + float16_t(signscale >> 28));
uint sign = bitfieldExtract(signscale, 7 * int(ib8), 7);
sign |= bitCount(sign) << 7;
const uint8_t g = unpack8(iq2xxs_grid[qs][(idx & 4) >> 2])[idx & 3];
float16_t ret = dscale * float16_t(g) * ((sign & (1 << (idx & 7))) != 0 ? -1.0hf : 1.0hf);
return ret;
}
#endif
#if defined(DATA_A_IQ2_XS)
layout(buffer_reference, std430, buffer_reference_align = 2) buffer decodeBufIQ2_XS {
block_iq2_xs block;
};
float16_t dequantFuncIQ2_XS(const in decodeBufIQ2_XS bl, const in uint blockCoords[2], const in uint coordInBlock[2])
{
const float16_t d = bl.block.d;
const uint idx = coordInBlock[1];
const uint is = (idx & 0xE0) >> 5; // 0..8
const uint sshift = (idx & 0x10) >> 2; // 0,4
const uint iqs = (idx & 0xF8) >> 3; // 0..63
const uint16_t qs = bl.block.qs[iqs];
const float16_t dscale = bl.block.d * 0.25hf * (0.5hf + float16_t((bl.block.scales[is] >> sshift) & 0xF));
uint sign = uint(qs >> 9);
sign |= bitCount(sign) << 7;
const uint8_t g = unpack8(iq2xs_grid[qs & 0x1FF][(idx & 4) >> 2])[idx & 3];
float16_t ret = dscale * float16_t(g) * ((sign & (1 << (idx & 7))) != 0 ? -1.0hf : 1.0hf);
return ret;
}
#endif
#if defined(DATA_A_IQ2_S)
layout(buffer_reference, std430, buffer_reference_align = 2) buffer decodeBufIQ2_S {
block_iq2_s block;
};
float16_t dequantFuncIQ2_S(const in decodeBufIQ2_S bl, const in uint blockCoords[2], const in uint coordInBlock[2])
{
uint idx = coordInBlock[1];
uint lsb = idx & 1;
idx /= 2;
const uint ib8 = (idx % 128) / 4; // 0..31
const uint ib32 = ib8 / 4; // 0..7
const uint scale = (bl.block.scales[ib32] >> (2 * (ib8 & 2))) & 0xf;
const uint qs = bl.block.qs[ib8];
const uint qh = bl.block.qh[ib32];
const uint qhshift = 2 * (ib8 % 4);
const uint sign = bl.block.qs[QUANT_K / 8 + ib8] >> (2 * (idx % 4));
const float d = float(bl.block.d);
const float db = d * 0.25 * (0.5 + scale);
const i8vec2 sign01 = i8vec2(1 - (2 & i8vec2(int8_t(sign << 1), int8_t(sign))));
const uint16_t grid = unpack16(iq2s_grid[qs | ((qh << (8 - qhshift)) & 0x300)][(idx & 2) >> 1])[idx & 1];
const vec2 v = db * vec2(sign01) * vec2(unpack8(grid));
return float16_t(v[lsb]);
}
#endif
#if defined(DATA_A_IQ3_XXS)
layout(buffer_reference, std430, buffer_reference_align = 2) buffer decodeBufIQ3_XXS {
block_iq3_xxs block;
};
layout(buffer_reference, std430, buffer_reference_align = 2) buffer decodeBufIQ3_XXS_packed16 {
block_iq3_xxs_packed16 block;
};
float16_t dequantFuncIQ3_XXS(const in decodeBufIQ3_XXS bl, const in uint blockCoords[2], const in uint coordInBlock[2])
{
uint idx = coordInBlock[1];
uint lsb = idx & 1;
idx /= 2;
const uint iqs = (idx % 128) / 2; // 0..63
const uint is = QUANT_K / 4 + 4 * (iqs / 8); // 8 values
const float d = float(bl.block.d);
const uint qs = bl.block.qs[iqs];
const uint signs = pack32(u8vec4(
bl.block.qs[is+0],
bl.block.qs[is+1],
bl.block.qs[is+2],
bl.block.qs[is+3]
));
const float db = d * 0.5 * (0.5 + (signs >> 28));
const uint32_t sign7 = bitfieldExtract(signs, 7 * (int(iqs / 2) % 4), 7);
const uint sign = (sign7 | (bitCount(sign7) << 7)) >> (2 * (idx % 4));
const i8vec2 sign01 = i8vec2(1 - (2 & i8vec2(int8_t(sign << 1), int8_t(sign))));
const uint grid = iq3xxs_grid[qs] >> (16 * (idx & 1));
const vec2 v = db * vec2(sign01) * vec2(unpack8(grid).xy);
return float16_t(v[lsb]);
}
#endif
#if defined(DATA_A_IQ3_S)
layout(buffer_reference, std430, buffer_reference_align = 2) buffer decodeBufIQ3_S {
block_iq3_s block;
};
float16_t dequantFuncIQ3_S(const in decodeBufIQ3_S bl, const in uint blockCoords[2], const in uint coordInBlock[2])
{
uint idx = coordInBlock[1];
uint lsb = idx & 1;
idx /= 2;
const uint iqs = (idx % 128) / 2; // 0..63
const uint iqh = iqs / 8;
const float d = float(bl.block.d);
const uint qs = bl.block.qs[iqs];
const uint qh = bl.block.qh[iqh];
const int8_t sign = int8_t(bl.block.signs[iqs / 2] >> (2 * (idx % 4)));
const uint scale = bl.block.scales[iqs / 16];
const i8vec2 sign01 = i8vec2(1 - (2 & i8vec2(sign << 1, sign)));
const float db = d * (1 + 2 * ((scale >> (4 * (iqh & 1))) & 0xf));
const uint32_t grid = iq3s_grid[qs | ((qh << (8 - (iqs % 8))) & 256)] >> (16 * (idx % 2));
const vec2 v = db * vec2(sign01) * vec2(unpack8(grid).xy);
return float16_t(v[lsb]);
}
#endif
#if defined(DATA_A_IQ4_NL)
layout(buffer_reference, std430, buffer_reference_align = 2) buffer decodeBufIQ4_NL {
block_iq4_nl block;
@ -340,6 +494,16 @@ float16_t dequantFuncIQ4_NL(const in decodeBufIQ4_NL bl, const in uint blockCoor
#define dequantFuncA dequantFuncQ5_K
#elif defined(DATA_A_Q6_K)
#define dequantFuncA dequantFuncQ6_K
#elif defined(DATA_A_IQ2_XXS)
#define dequantFuncA dequantFuncIQ2_XXS
#elif defined(DATA_A_IQ2_XS)
#define dequantFuncA dequantFuncIQ2_XS
#elif defined(DATA_A_IQ2_S)
#define dequantFuncA dequantFuncIQ2_S
#elif defined(DATA_A_IQ3_XXS)
#define dequantFuncA dequantFuncIQ3_XXS
#elif defined(DATA_A_IQ3_S)
#define dequantFuncA dequantFuncIQ3_S
#elif defined(DATA_A_IQ4_NL)
#define dequantFuncA dequantFuncIQ4_NL
#endif

44
ggml/src/ggml-vulkan/vulkan-shaders/dequant_iq2_s.comp Normal file
View file

@ -0,0 +1,44 @@
#version 450
#include "dequant_head.comp"
layout(local_size_x = 256, local_size_y = 1, local_size_z = 1) in;
layout (binding = 0) readonly buffer A {block_iq2_s data_a[];};
layout (binding = 1) writeonly buffer D {D_TYPE data_b[];};
void main() {
// Each thread handles 1 subblock (32 values with 2 scales)
const uint ib = gl_WorkGroupID.x * 32 + gl_LocalInvocationID.x / 8;
init_iq_shmem(gl_WorkGroupSize);
if (ib >= p.nel / 256) {
return;
}
const uint ib32 = gl_LocalInvocationID.x % 8;
const uint b_idx = 256 * ib + 32 * ib32;
const float d = float(data_a[ib].d);
const vec2 scale = vec2(data_a[ib].scales[ib32] & 0xf, data_a[ib].scales[ib32] >> 4);
const vec2 db = d * (0.5 + scale) * 0.25;
uint qh = data_a[ib].qh[ib32];
[[unroll]] for (uint l = 0; l < 4; ++l) {
uint qs = data_a[ib].qs[4 * ib32 + l];
const uint8_t sign = data_a[ib].qs[QUANT_K / 8 + 4 * ib32 + l];
qs |= (qh << (8 - 2 * l)) & 0x300;
const uvec2 grid = iq2s_grid[qs & 511];
const u8vec4 grid0 = unpack8(grid.x);
const u8vec4 grid1 = unpack8(grid.y);
data_b[b_idx + 8 * l + 0] = D_TYPE(db[l/2] * grid0.x * ((sign & 1) != 0 ? -1.0 : 1.0));
data_b[b_idx + 8 * l + 1] = D_TYPE(db[l/2] * grid0.y * ((sign & 2) != 0 ? -1.0 : 1.0));
data_b[b_idx + 8 * l + 2] = D_TYPE(db[l/2] * grid0.z * ((sign & 4) != 0 ? -1.0 : 1.0));
data_b[b_idx + 8 * l + 3] = D_TYPE(db[l/2] * grid0.w * ((sign & 8) != 0 ? -1.0 : 1.0));
data_b[b_idx + 8 * l + 4] = D_TYPE(db[l/2] * grid1.x * ((sign & 16) != 0 ? -1.0 : 1.0));
data_b[b_idx + 8 * l + 5] = D_TYPE(db[l/2] * grid1.y * ((sign & 32) != 0 ? -1.0 : 1.0));
data_b[b_idx + 8 * l + 6] = D_TYPE(db[l/2] * grid1.z * ((sign & 64) != 0 ? -1.0 : 1.0));
data_b[b_idx + 8 * l + 7] = D_TYPE(db[l/2] * grid1.w * ((sign & 128) != 0 ? -1.0 : 1.0));
}
}

43
ggml/src/ggml-vulkan/vulkan-shaders/dequant_iq2_xs.comp Normal file
View file

@ -0,0 +1,43 @@
#version 450
#include "dequant_head.comp"
layout(local_size_x = 256, local_size_y = 1, local_size_z = 1) in;
layout (binding = 0) readonly buffer A {block_iq2_xs data_a[];};
layout (binding = 1) writeonly buffer D {D_TYPE data_b[];};
void main() {
// Each thread handles 1 subblock (32 values with 2 scales)
const uint ib = gl_WorkGroupID.x * 32 + gl_LocalInvocationID.x / 8;
init_iq_shmem(gl_WorkGroupSize);
if (ib >= p.nel / 256) {
return;
}
const uint ib32 = gl_LocalInvocationID.x % 8;
const uint b_idx = 256 * ib + 32 * ib32;
const float d = float(data_a[ib].d);
const vec2 scale = vec2(data_a[ib].scales[ib32] & 0xf, data_a[ib].scales[ib32] >> 4);
const vec2 db = d * (0.5 + scale) * 0.25;
[[unroll]] for (uint l = 0; l < 4; ++l) {
uint16_t qs = data_a[ib].qs[4 * ib32 + l];
const uint sign7 = qs >> 9;
const uint sign8 = sign7 | (bitCount(sign7) << 7); // parity bit
const uvec2 grid = iq2xs_grid[qs & 511];
const u8vec4 grid0 = unpack8(grid.x);
const u8vec4 grid1 = unpack8(grid.y);
data_b[b_idx + 8 * l + 0] = D_TYPE(db[l/2] * grid0.x * ((sign8 & 1) != 0 ? -1.0 : 1.0));
data_b[b_idx + 8 * l + 1] = D_TYPE(db[l/2] * grid0.y * ((sign8 & 2) != 0 ? -1.0 : 1.0));
data_b[b_idx + 8 * l + 2] = D_TYPE(db[l/2] * grid0.z * ((sign8 & 4) != 0 ? -1.0 : 1.0));
data_b[b_idx + 8 * l + 3] = D_TYPE(db[l/2] * grid0.w * ((sign8 & 8) != 0 ? -1.0 : 1.0));
data_b[b_idx + 8 * l + 4] = D_TYPE(db[l/2] * grid1.x * ((sign8 & 16) != 0 ? -1.0 : 1.0));
data_b[b_idx + 8 * l + 5] = D_TYPE(db[l/2] * grid1.y * ((sign8 & 32) != 0 ? -1.0 : 1.0));
data_b[b_idx + 8 * l + 6] = D_TYPE(db[l/2] * grid1.z * ((sign8 & 64) != 0 ? -1.0 : 1.0));
data_b[b_idx + 8 * l + 7] = D_TYPE(db[l/2] * grid1.w * ((sign8 & 128) != 0 ? -1.0 : 1.0));
}
}

48
ggml/src/ggml-vulkan/vulkan-shaders/dequant_iq2_xxs.comp Normal file
View file

@ -0,0 +1,48 @@
#version 450
#include "dequant_head.comp"
layout(local_size_x = 256, local_size_y = 1, local_size_z = 1) in;
layout (binding = 0) readonly buffer A {block_iq2_xxs data_a[];};
layout (binding = 1) writeonly buffer D {D_TYPE data_b[];};
void main() {
// Each thread handles 1 scale block (32 values)
// Each block is described by 4 lattice indices, 4x7 sign bits and 4 scale bits
const uint ib = gl_WorkGroupID.x * 32 + gl_LocalInvocationID.x / 8;
init_iq_shmem(gl_WorkGroupSize);
if (ib >= p.nel / 256) {
return;
}
const uint is = gl_LocalInvocationID.x % 8;
const uint b_idx = 256 * ib + 32 * is;
const float d = float(data_a[ib].d);
uint signscale = pack32(u8vec4(
data_a[ib].qs[8*is + 4],
data_a[ib].qs[8*is + 5],
data_a[ib].qs[8*is + 6],
data_a[ib].qs[8*is + 7]
));
const float db = d * (0.5 + (signscale >> 28)) * 0.25;
[[unroll]] for (uint l = 0; l < 4; ++l) {
const uint sign7 = bitfieldExtract(signscale, 7 * int(l), 7);
const uint sign8 = sign7 | (bitCount(sign7) << 7); // parity bit
const uvec2 grid = iq2xxs_grid[data_a[ib].qs[8 * is + l]];
const u8vec4 grid0 = unpack8(grid.x);
const u8vec4 grid1 = unpack8(grid.y);
data_b[b_idx + 8 * l + 0] = D_TYPE(db * grid0.x * ((sign8 & 1) != 0 ? -1.0 : 1.0));
data_b[b_idx + 8 * l + 1] = D_TYPE(db * grid0.y * ((sign8 & 2) != 0 ? -1.0 : 1.0));
data_b[b_idx + 8 * l + 2] = D_TYPE(db * grid0.z * ((sign8 & 4) != 0 ? -1.0 : 1.0));
data_b[b_idx + 8 * l + 3] = D_TYPE(db * grid0.w * ((sign8 & 8) != 0 ? -1.0 : 1.0));
data_b[b_idx + 8 * l + 4] = D_TYPE(db * grid1.x * ((sign8 & 16) != 0 ? -1.0 : 1.0));
data_b[b_idx + 8 * l + 5] = D_TYPE(db * grid1.y * ((sign8 & 32) != 0 ? -1.0 : 1.0));
data_b[b_idx + 8 * l + 6] = D_TYPE(db * grid1.z * ((sign8 & 64) != 0 ? -1.0 : 1.0));
data_b[b_idx + 8 * l + 7] = D_TYPE(db * grid1.w * ((sign8 & 128) != 0 ? -1.0 : 1.0));
}
}

39
ggml/src/ggml-vulkan/vulkan-shaders/dequant_iq3_s.comp Normal file
View file

@ -0,0 +1,39 @@
#version 450
#include "dequant_head.comp"
layout(local_size_x = 256, local_size_y = 1, local_size_z = 1) in;
layout (binding = 0) readonly buffer A {block_iq3_s data_a[];};
layout (binding = 1) writeonly buffer D {D_TYPE data_b[];};
void main() {
// Each thread handles 1 scale nibble.
// Each block contains 4 scale bytes (8 scales) for 256 output values.
const uint ib = gl_WorkGroupID.x * 32 + gl_LocalInvocationID.x / 8;
init_iq_shmem(gl_WorkGroupSize);
if (ib >= p.nel / 256) {
return;
}
const uint is = gl_LocalInvocationID.x % 8;
const uint b_idx = 256 * ib + 32 * is;
const float d = float(data_a[ib].d);
const float db = d * (1 + 2 * ((data_a[ib].scales[is] >> (4 * (is % 2))) & 0xf));
// We must produce 32 values using 4 sign bytes, 1 qh byte, 8 qs bytes.
uint qh = data_a[ib].qh[is];
[[unroll]] for (uint l = 0; l < 8; ++l) {
uint qs = data_a[ib].qs[8 * is + l];
uint gidx = qs | ((qh << (8 - l)) & 256);
uint8_t signs = data_a[ib].signs[8 * is + l / 2] >> (4 * (l & 1));
u8vec4 grid = unpack8(iq3s_grid[gidx]);
data_b[b_idx + 4 * l + 0] = D_TYPE(db * grid.x * ((signs & 1) != 0 ? -1.0 : 1.0));
data_b[b_idx + 4 * l + 1] = D_TYPE(db * grid.y * ((signs & 2) != 0 ? -1.0 : 1.0));
data_b[b_idx + 4 * l + 2] = D_TYPE(db * grid.z * ((signs & 4) != 0 ? -1.0 : 1.0));
data_b[b_idx + 4 * l + 3] = D_TYPE(db * grid.w * ((signs & 8) != 0 ? -1.0 : 1.0));
}
}

49
ggml/src/ggml-vulkan/vulkan-shaders/dequant_iq3_xxs.comp Normal file
View file

@ -0,0 +1,49 @@
#version 450
#include "dequant_head.comp"
layout(local_size_x = 256, local_size_y = 1, local_size_z = 1) in;
layout (binding = 0) readonly buffer A {block_iq3_xxs data_a[];};
layout (binding = 1) writeonly buffer D {D_TYPE data_b[];};
void main() {
// Each thread handles 1 scale block (32 values)
// 8 threads handle 1 superblock
const uint ib = gl_WorkGroupID.x * 32 + gl_LocalInvocationID.x / 8;
init_iq_shmem(gl_WorkGroupSize);
if (ib >= p.nel / 256) {
return;
}
const uint is = gl_LocalInvocationID.x % 8;
const uint b_idx = 256 * ib + 32 * is;
const uint s_idx = QUANT_K / 4 + 4 * is;
const float d = float(data_a[ib].d);
uint signscale = pack32(u8vec4(
data_a[ib].qs[s_idx + 0],
data_a[ib].qs[s_idx + 1],
data_a[ib].qs[s_idx + 2],
data_a[ib].qs[s_idx + 3]
));
const float db = d * (0.5 + (signscale >> 28)) * 0.5;
[[unroll]] for (uint l = 0; l < 4; ++l) {
const uint sign7 = bitfieldExtract(signscale, 7 * int(l), 7);
// Restore parity bit.
const uint sign8 = sign7 | (bitCount(sign7) << 7);
const u8vec4 grid0 = unpack8(iq3xxs_grid[data_a[ib].qs[8 * is + 2 * l]]);
const u8vec4 grid1 = unpack8(iq3xxs_grid[data_a[ib].qs[8 * is + 2 * l + 1]]);
data_b[b_idx + 8 * l + 0] = D_TYPE(db * grid0.x * ((sign8 & 1) != 0 ? -1.0 : 1.0));
data_b[b_idx + 8 * l + 1] = D_TYPE(db * grid0.y * ((sign8 & 2) != 0 ? -1.0 : 1.0));
data_b[b_idx + 8 * l + 2] = D_TYPE(db * grid0.z * ((sign8 & 4) != 0 ? -1.0 : 1.0));
data_b[b_idx + 8 * l + 3] = D_TYPE(db * grid0.w * ((sign8 & 8) != 0 ? -1.0 : 1.0));
data_b[b_idx + 8 * l + 4] = D_TYPE(db * grid1.x * ((sign8 & 16) != 0 ? -1.0 : 1.0));
data_b[b_idx + 8 * l + 5] = D_TYPE(db * grid1.y * ((sign8 & 32) != 0 ? -1.0 : 1.0));
data_b[b_idx + 8 * l + 6] = D_TYPE(db * grid1.z * ((sign8 & 64) != 0 ? -1.0 : 1.0));
data_b[b_idx + 8 * l + 7] = D_TYPE(db * grid1.w * ((sign8 & 128) != 0 ? -1.0 : 1.0));
}
}

2
ggml/src/ggml-vulkan/vulkan-shaders/dequant_iq4_nl.comp
View file

@ -10,7 +10,7 @@ layout (binding = 1) writeonly buffer D {D_TYPE data_b[];};
void main() {
const uint i = gl_WorkGroupID.x * 4 + gl_LocalInvocationID.x / 64;
init_iq4nl_shmem();
init_iq_shmem(gl_WorkGroupSize);
const uint tid = gl_LocalInvocationID.x % 64;
const uint il = tid/32;

4
ggml/src/ggml-vulkan/vulkan-shaders/flash_attn_cm2.comp
View file

@ -104,8 +104,8 @@ ACC_TYPE Max(const in uint32_t row, const in uint32_t col, const in ACC_TYPE ele
#endif
void main() {
#if defined(DATA_A_IQ4_NL)
init_iq4nl_shmem();
#if defined(DATA_A_IQ2_XXS) || defined(DATA_A_IQ2_XS) || defined(DATA_A_IQ2_S) || defined(DATA_A_IQ3_XXS) || defined(DATA_A_IQ3_S) || defined(DATA_A_IQ4_NL)
init_iq_shmem(gl_WorkGroupSize);
#endif
const uint32_t N = p.N;

4
ggml/src/ggml-vulkan/vulkan-shaders/get_rows_quant.comp
View file

@ -12,8 +12,8 @@ void main() {
const uint i11 = (gl_GlobalInvocationID.z)/p.ne12;
const uint i12 = (gl_GlobalInvocationID.z)%p.ne12;
#if defined(DATA_A_IQ4_NL)
init_iq4nl_shmem();
#if defined(DATA_A_IQ2_XXS) || defined(DATA_A_IQ2_XS) || defined(DATA_A_IQ2_S) || defined(DATA_A_IQ3_XXS) || defined(DATA_A_IQ3_S) || defined(DATA_A_IQ4_NL)
init_iq_shmem(gl_WorkGroupSize);
#endif
if (i00 >= p.ne00) {

4
ggml/src/ggml-vulkan/vulkan-shaders/mul_mat_vec.comp
View file

@ -133,8 +133,8 @@ void compute_outputs(const uint32_t first_row, const uint32_t num_rows) {
void main() {
const uint first_row = NUM_ROWS * (gl_WorkGroupID.x + gl_NumWorkGroups.x * gl_WorkGroupID.z);
#if defined(DATA_A_IQ4_NL)
init_iq4nl_shmem();
#if defined(DATA_A_IQ2_XXS) || defined(DATA_A_IQ2_XS) || defined(DATA_A_IQ2_S) || defined(DATA_A_IQ3_XXS) || defined(DATA_A_IQ3_S) || defined(DATA_A_IQ4_NL)
init_iq_shmem(gl_WorkGroupSize);
#endif
// do NUM_ROWS at a time, unless there aren't enough remaining rows

122
ggml/src/ggml-vulkan/vulkan-shaders/mul_mm.comp
View file

@ -95,8 +95,8 @@ shared ACC_TYPE coopmat_stage[TM * TN * NUM_WARPS];
#endif
void main() {
#if defined(DATA_A_IQ4_NL)
init_iq4nl_shmem();
#if defined(DATA_A_IQ2_XXS) || defined(DATA_A_IQ2_XS) || defined(DATA_A_IQ2_S) || defined(DATA_A_IQ3_XXS) || defined(DATA_A_IQ3_S) || defined(DATA_A_IQ4_NL)
init_iq_shmem(gl_WorkGroupSize);
#endif
#ifdef MUL_MAT_ID
@ -343,10 +343,8 @@ void main() {
const uint qsshift = halfsplit * 2; // 0,2,4,6
const uint m = 1 << (4 * n + halfsplit); // 1,2,4,8,16,32,64,128
const int8_t us = int8_t(is < 4 ? (data_a[ib].scales[is-0] & 0xF) | (((data_a[ib].scales[is+8] >> 0) & 3) << 4) :
is < 8 ? (data_a[ib].scales[is-0] & 0xF) | (((data_a[ib].scales[is+4] >> 2) & 3) << 4) :
is < 12 ? (data_a[ib].scales[is-8] >> 4) | (((data_a[ib].scales[is+0] >> 4) & 3) << 4) :
(data_a[ib].scales[is-8] >> 4) | (((data_a[ib].scales[is-4] >> 6) & 3) << 4));
const int8_t us = int8_t(((data_a[ib].scales[is % 8] >> (4 * int(is / 8))) & 0xF)
| (((data_a[ib].scales[8 + (is % 4)] >> (2 * int(is / 4))) & 3) << 4));
const float dl = float(data_a[ib].d) * float(us - 32);
buf_a[buf_idx ] = FLOAT_TYPE(dl * float(int8_t((data_a[ib].qs[qsi ] >> qsshift) & 3) - (((data_a[ib].hmask[hmi ] & m) != 0) ? 0 : 4)));
@ -439,6 +437,118 @@ void main() {
buf_a[buf_idx ] = FLOAT_TYPE(dscale * float(int8_t(((data_a[ib].ql[qsi ] >> (b * 4)) & 0xF) | (((data_a[ib].qh[qhi ] >> qhshift) & 3) << 4)) - 32));
buf_a[buf_idx + 1] = FLOAT_TYPE(dscale * float(int8_t(((data_a[ib].ql[qsi + 1] >> (b * 4)) & 0xF) | (((data_a[ib].qh[qhi + 1] >> qhshift) & 3) << 4)) - 32));
#elif defined(DATA_A_IQ2_XXS)
const uint idx = pos_a + (loadc_a + l) * p.stride_a / LOAD_VEC_A + loadr_a;
const uint buf_idx = (loadc_a + l) * SHMEM_STRIDE + loadr_a * LOAD_VEC_A;
const uint ib = idx / 128; // 2 values per idx
const uint ib32 = (idx % 128) / 16; // 0..7
const uint ib8 = (idx / 4) % 4;
const float d = float(data_a[ib].d);
const uint qs = data_a[ib].qs[8 * ib32 + ib8];
const uint signs = pack32(u8vec4(
data_a[ib].qs[8*ib32 + 4],
data_a[ib].qs[8*ib32 + 5],
data_a[ib].qs[8*ib32 + 6],
data_a[ib].qs[8*ib32 + 7]
));
const float db = d * 0.25 * (0.5 + (signs >> 28));
const uint32_t sign7 = bitfieldExtract(signs, 7 * int(ib8), 7);
const uint sign = (sign7 | (bitCount(sign7) << 7)) >> (2 * (idx % 4));
const i8vec2 sign01 = i8vec2(1 - (2 & i8vec2(int8_t(sign << 1), int8_t(sign))));
const uint grid = iq2xxs_grid[qs][(idx % 4) / 2] >> (16 * (idx & 1));
const vec2 v = db * vec2(sign01) * vec2(unpack8(grid).xy);
buf_a[buf_idx ] = FLOAT_TYPE(v.x);
buf_a[buf_idx + 1] = FLOAT_TYPE(v.y);
#elif defined(DATA_A_IQ2_XS)
const uint idx = pos_a + (loadc_a + l) * p.stride_a / LOAD_VEC_A + loadr_a;
const uint buf_idx = (loadc_a + l) * SHMEM_STRIDE + loadr_a * LOAD_VEC_A;
const uint ib = idx / 128; // 2 values per idx
const uint ib32 = (idx % 128) / 16; // 0..7
const uint ib8 = (idx / 4) % 4; // 0..3
const float d = float(data_a[ib].d);
const uint scale = (data_a[ib].scales[ib32] >> (2 * (ib8 & 2))) & 0xf;
const float db = d * 0.25 * (0.5 + scale);
const uint qs = data_a[ib].qs[4 * ib32 + ib8];
const uint sign7 = qs >> 9;
const uint sign = (sign7 | (bitCount(sign7) << 7)) >> (2 * (idx % 4));
const i8vec2 sign01 = i8vec2(1 - (2 & i8vec2(int8_t(sign << 1), int8_t(sign))));
const uint grid = iq2xs_grid[qs & 511][(idx % 4) / 2] >> (16 * (idx & 1));
const vec2 v = db * vec2(sign01) * vec2(unpack8(grid).xy);
buf_a[buf_idx ] = FLOAT_TYPE(v.x);
buf_a[buf_idx + 1] = FLOAT_TYPE(v.y);
#elif defined(DATA_A_IQ2_S)
const uint idx = pos_a + (loadc_a + l) * p.stride_a / LOAD_VEC_A + loadr_a;
const uint buf_idx = (loadc_a + l) * SHMEM_STRIDE + loadr_a * LOAD_VEC_A;
const uint ib = idx / 128; // 2 values per idx
const uint ib8 = (idx % 128) / 4; // 0..31
const uint ib32 = ib8 / 4; // 0..7
const uint scale = (data_a[ib].scales[ib32] >> (2 * (ib8 & 2))) & 0xf;
const uint qs = data_a[ib].qs[ib8];
const uint qh = data_a[ib].qh[ib32];
const uint qhshift = 2 * (ib8 % 4);
const uint sign = data_a[ib].qs[QUANT_K / 8 + ib8] >> (2 * (idx % 4));
const float d = float(data_a[ib].d);
const float db = d * 0.25 * (0.5 + scale);
const i8vec2 sign01 = i8vec2(1 - (2 & i8vec2(int8_t(sign << 1), int8_t(sign))));
const uint16_t grid = unpack16(iq2s_grid[qs | ((qh << (8 - qhshift)) & 0x300)][(idx & 2) >> 1])[idx & 1];
const vec2 v = db * vec2(sign01) * vec2(unpack8(grid));
buf_a[buf_idx ] = FLOAT_TYPE(v.x);
buf_a[buf_idx + 1] = FLOAT_TYPE(v.y);
#elif defined(DATA_A_IQ3_XXS)
const uint idx = pos_a + (loadc_a + l) * p.stride_a / LOAD_VEC_A + loadr_a;
const uint buf_idx = (loadc_a + l) * SHMEM_STRIDE + loadr_a * LOAD_VEC_A;
const uint ib = idx / 128; // 2 values per idx
const uint iqs = (idx % 128) / 2; // 0..63
const uint is = QUANT_K / 4 + 4 * (iqs / 8); // 8 values
const float d = float(data_a[ib].d);
const uint qs = data_a[ib].qs[iqs];
const uint signs = pack32(u8vec4(
data_a[ib].qs[is+0],
data_a[ib].qs[is+1],
data_a[ib].qs[is+2],
data_a[ib].qs[is+3]
));
const float db = d * 0.5 * (0.5 + (signs >> 28));
const uint32_t sign7 = bitfieldExtract(signs, 7 * (int(iqs / 2) % 4), 7);
const uint sign = (sign7 | (bitCount(sign7) << 7)) >> (2 * (idx % 4));
const i8vec2 sign01 = i8vec2(1 - (2 & i8vec2(int8_t(sign << 1), int8_t(sign))));
const uint grid = iq3xxs_grid[qs] >> (16 * (idx & 1));
const vec2 v = db * vec2(sign01) * vec2(unpack8(grid).xy);
buf_a[buf_idx ] = FLOAT_TYPE(v.x);
buf_a[buf_idx + 1] = FLOAT_TYPE(v.y);
#elif defined(DATA_A_IQ3_S)
const uint idx = pos_a + (loadc_a + l) * p.stride_a / LOAD_VEC_A + loadr_a;
const uint buf_idx = (loadc_a + l) * SHMEM_STRIDE + loadr_a * LOAD_VEC_A;
const uint ib = idx / 128; // 2 values per idx
const uint iqs = (idx % 128) / 2; // 0..63
const uint iqh = iqs / 8;
const float d = float(data_a[ib].d);
const uint qs = data_a[ib].qs[iqs];
const uint qh = data_a[ib].qh[iqh];
const int8_t sign = int8_t(data_a[ib].signs[iqs / 2] >> (2 * (idx % 4)));
const uint scale = data_a[ib].scales[iqs / 16];
const i8vec2 sign01 = i8vec2(1 - (2 & i8vec2(sign << 1, sign)));
const float db = d * (1 + 2 * ((scale >> (4 * (iqh & 1))) & 0xf));
const uint32_t grid = iq3s_grid[qs | ((qh << (8 - (iqs % 8))) & 256)] >> (16 * (idx % 2));
const vec2 v = db * vec2(sign01) * vec2(unpack8(grid).xy);
buf_a[buf_idx ] = FLOAT_TYPE(v.x);
buf_a[buf_idx + 1] = FLOAT_TYPE(v.y);
#elif defined(DATA_A_IQ4_NL)
const uint idx = pos_a + (loadc_a + l) * p.stride_a / LOAD_VEC_A + loadr_a;
const uint buf_idx = (loadc_a + l) * SHMEM_STRIDE + loadr_a;

4
ggml/src/ggml-vulkan/vulkan-shaders/mul_mm_cm2.comp
View file

@ -106,8 +106,8 @@ D_TYPE perElemOpD(const in uint32_t r, const in uint32_t c, const in D_TYPE elem
#endif
void main() {
#if defined(DATA_A_IQ4_NL)
init_iq4nl_shmem();
#if defined(DATA_A_IQ2_XXS) || defined(DATA_A_IQ2_XS) || defined(DATA_A_IQ2_S) || defined(DATA_A_IQ3_XXS) || defined(DATA_A_IQ3_S) || defined(DATA_A_IQ4_NL)
init_iq_shmem(gl_WorkGroupSize);
#endif
#ifdef MUL_MAT_ID

738
ggml/src/ggml-vulkan/vulkan-shaders/types.comp
View file

@ -294,6 +294,738 @@ struct block_q6_K_packed16
// IQuants
#define QUANT_K_IQ2_XXS 256
#define QUANT_R_IQ2_XXS 1
struct block_iq2_xxs
{
float16_t d;
uint8_t qs[QUANT_K_IQ2_XXS/4];
};
struct block_iq2_xxs_packed16
{
float16_t d;
uint16_t qs[QUANT_K_IQ2_XXS/8];
};
#if defined(DATA_A_IQ2_XXS)
const uvec2[256] iq2xxs_grid_const = {
uvec2(0x08080808, 0x08080808), uvec2(0x0808082b, 0x08080808), uvec2(0x08081919, 0x08080808), uvec2(0x08082b08, 0x08080808),
uvec2(0x08082b2b, 0x08080808), uvec2(0x08190819, 0x08080808), uvec2(0x08191908, 0x08080808), uvec2(0x082b0808, 0x08080808),
uvec2(0x082b082b, 0x08080808), uvec2(0x082b2b08, 0x08080808), uvec2(0x082b2b2b, 0x08080808), uvec2(0x19080819, 0x08080808),
uvec2(0x19081908, 0x08080808), uvec2(0x19190808, 0x08080808), uvec2(0x19192b08, 0x08080808), uvec2(0x192b0819, 0x08080808),
uvec2(0x192b1908, 0x08080808), uvec2(0x2b080808, 0x08080808), uvec2(0x2b08082b, 0x08080808), uvec2(0x2b082b2b, 0x08080808),
uvec2(0x2b2b082b, 0x08080808), uvec2(0x08080819, 0x08080819), uvec2(0x08081908, 0x08080819), uvec2(0x08190808, 0x08080819),
uvec2(0x08191919, 0x08080819), uvec2(0x19080808, 0x08080819), uvec2(0x2b081908, 0x08080819), uvec2(0x2b192b08, 0x08080819),
uvec2(0x08080808, 0x0808082b), uvec2(0x0808082b, 0x0808082b), uvec2(0x082b082b, 0x0808082b), uvec2(0x2b08082b, 0x0808082b),
uvec2(0x08080819, 0x08081908), uvec2(0x08081908, 0x08081908), uvec2(0x08190808, 0x08081908), uvec2(0x082b0819, 0x08081908),
uvec2(0x082b1908, 0x08081908), uvec2(0x19080808, 0x08081908), uvec2(0x1908082b, 0x08081908), uvec2(0x19082b08, 0x08081908),
uvec2(0x192b0808, 0x08081908), uvec2(0x2b080819, 0x08081908), uvec2(0x2b081908, 0x08081908), uvec2(0x2b190808, 0x08081908),
uvec2(0x2b2b1908, 0x08081908), uvec2(0x08080808, 0x08081919), uvec2(0x0808082b, 0x08081919), uvec2(0x08082b08, 0x08081919),
uvec2(0x082b0808, 0x08081919), uvec2(0x1908192b, 0x08081919), uvec2(0x192b2b19, 0x08081919), uvec2(0x2b080808, 0x08081919),
uvec2(0x2b190819, 0x08081919), uvec2(0x08082b19, 0x0808192b), uvec2(0x08190808, 0x0808192b), uvec2(0x19080808, 0x0808192b),
uvec2(0x2b081908, 0x0808192b), uvec2(0x2b2b1908, 0x0808192b), uvec2(0x08080808, 0x08082b08), uvec2(0x08081919, 0x08082b08),
uvec2(0x08082b08, 0x08082b08), uvec2(0x08191908, 0x08082b08), uvec2(0x082b2b08, 0x08082b08), uvec2(0x19080819, 0x08082b08),
uvec2(0x19081908, 0x08082b08), uvec2(0x19190808, 0x08082b08), uvec2(0x1919082b, 0x08082b08), uvec2(0x2b082b08, 0x08082b08),
uvec2(0x08081908, 0x08082b19), uvec2(0x19080808, 0x08082b19), uvec2(0x0808082b, 0x08082b2b), uvec2(0x08191908, 0x08082b2b),
uvec2(0x08080819, 0x08190808), uvec2(0x08081908, 0x08190808), uvec2(0x08190808, 0x08190808), uvec2(0x082b0819, 0x08190808),
uvec2(0x19080808, 0x08190808), uvec2(0x192b0808, 0x08190808), uvec2(0x2b081908, 0x08190808), uvec2(0x2b190808, 0x08190808),
uvec2(0x2b191919, 0x08190808), uvec2(0x08080808, 0x08190819), uvec2(0x08082b08, 0x08190819), uvec2(0x082b0808, 0x08190819),
uvec2(0x19190808, 0x08190819), uvec2(0x19192b2b, 0x08190819), uvec2(0x2b080808, 0x08190819), uvec2(0x082b1908, 0x0819082b),
uvec2(0x19081919, 0x0819082b), uvec2(0x08080808, 0x08191908), uvec2(0x08082b08, 0x08191908), uvec2(0x082b0808, 0x08191908),
uvec2(0x082b1919, 0x08191908), uvec2(0x19082b19, 0x08191908), uvec2(0x2b080808, 0x08191908), uvec2(0x08192b08, 0x08191919),
uvec2(0x192b082b, 0x08191919), uvec2(0x08080808, 0x0819192b), uvec2(0x0819192b, 0x0819192b), uvec2(0x08080819, 0x08192b08),
uvec2(0x08081908, 0x08192b08), uvec2(0x08190808, 0x08192b08), uvec2(0x19080808, 0x08192b08), uvec2(0x2b080819, 0x08192b08),
uvec2(0x08080808, 0x08192b19), uvec2(0x08081919, 0x08192b19), uvec2(0x2b2b0808, 0x08192b19), uvec2(0x19190819, 0x08192b2b),
uvec2(0x08080808, 0x082b0808), uvec2(0x0808082b, 0x082b0808), uvec2(0x08082b2b, 0x082b0808), uvec2(0x19081908, 0x082b0808),
uvec2(0x192b0819, 0x082b0808), uvec2(0x2b080808, 0x082b0808), uvec2(0x2b08082b, 0x082b0808), uvec2(0x082b2b19, 0x082b0819),
uvec2(0x19082b08, 0x082b0819), uvec2(0x08080808, 0x082b082b), uvec2(0x0808082b, 0x082b082b), uvec2(0x08080819, 0x082b1908),
uvec2(0x08081908, 0x082b1908), uvec2(0x08190808, 0x082b1908), uvec2(0x19080808, 0x082b1908), uvec2(0x1919192b, 0x082b1908),
uvec2(0x08080808, 0x082b1919), uvec2(0x19080819, 0x082b1919), uvec2(0x192b1908, 0x082b1919), uvec2(0x2b190808, 0x082b192b),
uvec2(0x08082b08, 0x082b2b08), uvec2(0x082b0808, 0x082b2b08), uvec2(0x2b191908, 0x082b2b08), uvec2(0x19081908, 0x082b2b2b),
uvec2(0x08080819, 0x19080808), uvec2(0x08081908, 0x19080808), uvec2(0x08190808, 0x19080808), uvec2(0x08192b08, 0x19080808),
uvec2(0x082b0819, 0x19080808), uvec2(0x082b1908, 0x19080808), uvec2(0x19080808, 0x19080808), uvec2(0x19082b08, 0x19080808),
uvec2(0x1919192b, 0x19080808), uvec2(0x192b0808, 0x19080808), uvec2(0x2b080819, 0x19080808), uvec2(0x2b081908, 0x19080808),
uvec2(0x2b190808, 0x19080808), uvec2(0x08080808, 0x19080819), uvec2(0x082b0808, 0x19080819), uvec2(0x192b0819, 0x19080819),
uvec2(0x2b080808, 0x19080819), uvec2(0x2b081919, 0x19080819), uvec2(0x08080819, 0x1908082b), uvec2(0x08190808, 0x1908082b),
uvec2(0x19082b08, 0x1908082b), uvec2(0x1919192b, 0x1908082b), uvec2(0x192b2b08, 0x1908082b), uvec2(0x08080808, 0x19081908),
uvec2(0x08082b08, 0x19081908), uvec2(0x082b0808, 0x19081908), uvec2(0x2b080808, 0x19081908), uvec2(0x2b192b19, 0x19081908),
uvec2(0x0819082b, 0x19081919), uvec2(0x082b1908, 0x19081919), uvec2(0x08080808, 0x1908192b), uvec2(0x08080819, 0x19082b08),
uvec2(0x08081908, 0x19082b08), uvec2(0x08190808, 0x19082b08), uvec2(0x19080808, 0x19082b08), uvec2(0x19081919, 0x19082b08),
uvec2(0x08080808, 0x19082b19), uvec2(0x19192b08, 0x19082b19), uvec2(0x192b0819, 0x19082b19), uvec2(0x2b08082b, 0x19082b19),
uvec2(0x19081919, 0x19082b2b), uvec2(0x2b190808, 0x19082b2b), uvec2(0x08080808, 0x19190808), uvec2(0x08082b08, 0x19190808),
uvec2(0x08190819, 0x19190808), uvec2(0x08192b19, 0x19190808), uvec2(0x082b0808, 0x19190808), uvec2(0x2b080808, 0x19190808),
uvec2(0x2b082b08, 0x19190808), uvec2(0x08081908, 0x19190819), uvec2(0x1908082b, 0x19190819), uvec2(0x2b2b1908, 0x19190819),
uvec2(0x2b190819, 0x1919082b), uvec2(0x2b190808, 0x19191908), uvec2(0x2b19082b, 0x19191908), uvec2(0x08082b2b, 0x19191919),
uvec2(0x08080819, 0x1919192b), uvec2(0x19191908, 0x1919192b), uvec2(0x08080808, 0x19192b08), uvec2(0x08190819, 0x19192b08),
uvec2(0x08192b19, 0x19192b08), uvec2(0x192b1908, 0x19192b08), uvec2(0x19080808, 0x19192b19), uvec2(0x08082b08, 0x19192b2b),
uvec2(0x08081908, 0x192b0808), uvec2(0x08190808, 0x192b0808), uvec2(0x19080808, 0x192b0808), uvec2(0x192b2b08, 0x192b0808),
uvec2(0x08080808, 0x192b0819), uvec2(0x19191919, 0x192b0819), uvec2(0x08192b08, 0x192b082b), uvec2(0x192b0808, 0x192b082b),
uvec2(0x08080808, 0x192b1908), uvec2(0x08081919, 0x192b1908), uvec2(0x08190808, 0x192b1919), uvec2(0x0819082b, 0x192b1919),
uvec2(0x2b081908, 0x192b1919), uvec2(0x1908082b, 0x192b2b08), uvec2(0x08080808, 0x2b080808), uvec2(0x0808082b, 0x2b080808),
uvec2(0x08082b2b, 0x2b080808), uvec2(0x19080819, 0x2b080808), uvec2(0x2b08082b, 0x2b080808), uvec2(0x08081908, 0x2b080819),
uvec2(0x08192b08, 0x2b080819), uvec2(0x19080808, 0x2b080819), uvec2(0x08190819, 0x2b08082b), uvec2(0x08080819, 0x2b081908),
uvec2(0x08081908, 0x2b081908), uvec2(0x08190808, 0x2b081908), uvec2(0x08191919, 0x2b081908), uvec2(0x19080808, 0x2b081908),
uvec2(0x192b0808, 0x2b081908), uvec2(0x08080808, 0x2b081919), uvec2(0x1908192b, 0x2b081919), uvec2(0x2b191908, 0x2b081919),
uvec2(0x08082b19, 0x2b08192b), uvec2(0x19080808, 0x2b08192b), uvec2(0x192b0808, 0x2b08192b), uvec2(0x0808082b, 0x2b082b08),
uvec2(0x08081908, 0x2b082b19), uvec2(0x08190819, 0x2b082b2b), uvec2(0x08081908, 0x2b190808), uvec2(0x08190808, 0x2b190808),
uvec2(0x082b1908, 0x2b190808), uvec2(0x19080808, 0x2b190808), uvec2(0x2b2b0819, 0x2b190808), uvec2(0x0819192b, 0x2b190819),
uvec2(0x2b080808, 0x2b190819), uvec2(0x19081919, 0x2b19082b), uvec2(0x08080808, 0x2b191908), uvec2(0x082b082b, 0x2b191908),
uvec2(0x19081908, 0x2b191908), uvec2(0x19190819, 0x2b191919), uvec2(0x2b080819, 0x2b192b08), uvec2(0x082b0808, 0x2b192b19),
uvec2(0x0808082b, 0x2b2b0808), uvec2(0x19190808, 0x2b2b0808), uvec2(0x2b081919, 0x2b2b0808), uvec2(0x08082b19, 0x2b2b0819),
uvec2(0x08080808, 0x2b2b082b), uvec2(0x08192b08, 0x2b2b1908), uvec2(0x19190808, 0x2b2b2b08), uvec2(0x08081908, 0x2b2b2b19)
};
shared uvec2 iq2xxs_grid[256];
void init_iq_shmem(uvec3 wgsize)
{
// copy the table into shared memory and sync
for (uint i = gl_LocalInvocationIndex.x; i < iq2xxs_grid.length(); i += wgsize.x) {
iq2xxs_grid[i] = iq2xxs_grid_const[i];
}
barrier();
}
#define QUANT_K QUANT_K_IQ2_XXS
#define QUANT_R QUANT_R_IQ2_XXS
#define A_TYPE block_iq2_xxs
#define A_TYPE_PACKED16 block_iq2_xxs_packed16
#endif
#define QUANT_K_IQ2_XS 256
#define QUANT_R_IQ2_XS 1
struct block_iq2_xs
{
float16_t d;
uint16_t qs[QUANT_K_IQ2_XS/8];
uint8_t scales[QUANT_K_IQ2_XS/32];
};
struct block_iq2_xs_packed16
{
float16_t d;
uint16_t qs[QUANT_K_IQ2_XS/8];
uint16_t scales[QUANT_K_IQ2_XS/64];
};
#if defined(DATA_A_IQ2_XS)
const uvec2 iq2xs_grid_const[512] = {
uvec2(0x08080808, 0x08080808), uvec2(0x0808082b, 0x08080808), uvec2(0x08081919, 0x08080808), uvec2(0x08082b08, 0x08080808),
uvec2(0x08082b2b, 0x08080808), uvec2(0x08190819, 0x08080808), uvec2(0x08191908, 0x08080808), uvec2(0x0819192b, 0x08080808),
uvec2(0x08192b19, 0x08080808), uvec2(0x082b0808, 0x08080808), uvec2(0x082b082b, 0x08080808), uvec2(0x082b1919, 0x08080808),
uvec2(0x082b2b08, 0x08080808), uvec2(0x19080819, 0x08080808), uvec2(0x19081908, 0x08080808), uvec2(0x1908192b, 0x08080808),
uvec2(0x19082b19, 0x08080808), uvec2(0x19190808, 0x08080808), uvec2(0x1919082b, 0x08080808), uvec2(0x19191919, 0x08080808),
uvec2(0x19192b08, 0x08080808), uvec2(0x192b0819, 0x08080808), uvec2(0x192b1908, 0x08080808), uvec2(0x2b080808, 0x08080808),
uvec2(0x2b08082b, 0x08080808), uvec2(0x2b081919, 0x08080808), uvec2(0x2b082b08, 0x08080808), uvec2(0x2b190819, 0x08080808),
uvec2(0x2b191908, 0x08080808), uvec2(0x2b192b19, 0x08080808), uvec2(0x2b2b0808, 0x08080808), uvec2(0x08080819, 0x08080819),
uvec2(0x08081908, 0x08080819), uvec2(0x0808192b, 0x08080819), uvec2(0x08082b19, 0x08080819), uvec2(0x08190808, 0x08080819),
uvec2(0x0819082b, 0x08080819), uvec2(0x08191919, 0x08080819), uvec2(0x08192b08, 0x08080819), uvec2(0x08192b2b, 0x08080819),
uvec2(0x082b0819, 0x08080819), uvec2(0x082b1908, 0x08080819), uvec2(0x19080808, 0x08080819), uvec2(0x1908082b, 0x08080819),
uvec2(0x19081919, 0x08080819), uvec2(0x19082b08, 0x08080819), uvec2(0x19190819, 0x08080819), uvec2(0x19191908, 0x08080819),
uvec2(0x192b0808, 0x08080819), uvec2(0x192b2b08, 0x08080819), uvec2(0x2b080819, 0x08080819), uvec2(0x2b081908, 0x08080819),
uvec2(0x2b190808, 0x08080819), uvec2(0x08080808, 0x0808082b), uvec2(0x0808082b, 0x0808082b), uvec2(0x08081919, 0x0808082b),
uvec2(0x08082b08, 0x0808082b), uvec2(0x08190819, 0x0808082b), uvec2(0x08191908, 0x0808082b), uvec2(0x082b0808, 0x0808082b),
uvec2(0x19080819, 0x0808082b), uvec2(0x19081908, 0x0808082b), uvec2(0x19190808, 0x0808082b), uvec2(0x19191919, 0x0808082b),
uvec2(0x2b080808, 0x0808082b), uvec2(0x2b082b2b, 0x0808082b), uvec2(0x08080819, 0x08081908), uvec2(0x08081908, 0x08081908),
uvec2(0x0808192b, 0x08081908), uvec2(0x08082b19, 0x08081908), uvec2(0x08190808, 0x08081908), uvec2(0x0819082b, 0x08081908),
uvec2(0x08191919, 0x08081908), uvec2(0x08192b08, 0x08081908), uvec2(0x082b0819, 0x08081908), uvec2(0x082b1908, 0x08081908),
uvec2(0x19080808, 0x08081908), uvec2(0x1908082b, 0x08081908), uvec2(0x19081919, 0x08081908), uvec2(0x19082b08, 0x08081908),
uvec2(0x19190819, 0x08081908), uvec2(0x19191908, 0x08081908), uvec2(0x1919192b, 0x08081908), uvec2(0x192b0808, 0x08081908),
uvec2(0x2b080819, 0x08081908), uvec2(0x2b081908, 0x08081908), uvec2(0x2b190808, 0x08081908), uvec2(0x08080808, 0x08081919),
uvec2(0x0808082b, 0x08081919), uvec2(0x08081919, 0x08081919), uvec2(0x08082b08, 0x08081919), uvec2(0x08190819, 0x08081919),
uvec2(0x08191908, 0x08081919), uvec2(0x082b0808, 0x08081919), uvec2(0x19080819, 0x08081919), uvec2(0x19081908, 0x08081919),
uvec2(0x19190808, 0x08081919), uvec2(0x192b0819, 0x08081919), uvec2(0x2b080808, 0x08081919), uvec2(0x08080819, 0x0808192b),
uvec2(0x08081908, 0x0808192b), uvec2(0x08190808, 0x0808192b), uvec2(0x082b192b, 0x0808192b), uvec2(0x19080808, 0x0808192b),
uvec2(0x1908082b, 0x0808192b), uvec2(0x2b081908, 0x0808192b), uvec2(0x08080808, 0x08082b08), uvec2(0x0808082b, 0x08082b08),
uvec2(0x08081919, 0x08082b08), uvec2(0x08082b08, 0x08082b08), uvec2(0x08082b2b, 0x08082b08), uvec2(0x08190819, 0x08082b08),
uvec2(0x08191908, 0x08082b08), uvec2(0x082b0808, 0x08082b08), uvec2(0x082b1919, 0x08082b08), uvec2(0x19080819, 0x08082b08),
uvec2(0x19081908, 0x08082b08), uvec2(0x19190808, 0x08082b08), uvec2(0x19192b08, 0x08082b08), uvec2(0x2b080808, 0x08082b08),
uvec2(0x2b2b0808, 0x08082b08), uvec2(0x2b2b2b2b, 0x08082b08), uvec2(0x08080819, 0x08082b19), uvec2(0x08081908, 0x08082b19),
uvec2(0x08190808, 0x08082b19), uvec2(0x19080808, 0x08082b19), uvec2(0x2b080819, 0x08082b19), uvec2(0x2b082b19, 0x08082b19),
uvec2(0x08080808, 0x08082b2b), uvec2(0x082b0808, 0x08082b2b), uvec2(0x082b2b08, 0x08082b2b), uvec2(0x2b19192b, 0x08082b2b),
uvec2(0x2b2b0808, 0x08082b2b), uvec2(0x08080819, 0x08190808), uvec2(0x08081908, 0x08190808), uvec2(0x0808192b, 0x08190808),
uvec2(0x08082b19, 0x08190808), uvec2(0x08190808, 0x08190808), uvec2(0x0819082b, 0x08190808), uvec2(0x08191919, 0x08190808),
uvec2(0x08192b08, 0x08190808), uvec2(0x082b0819, 0x08190808), uvec2(0x082b1908, 0x08190808), uvec2(0x19080808, 0x08190808),
uvec2(0x1908082b, 0x08190808), uvec2(0x19081919, 0x08190808), uvec2(0x19082b08, 0x08190808), uvec2(0x19190819, 0x08190808),
uvec2(0x19191908, 0x08190808), uvec2(0x192b0808, 0x08190808), uvec2(0x192b2b2b, 0x08190808), uvec2(0x2b080819, 0x08190808),
uvec2(0x2b081908, 0x08190808), uvec2(0x2b190808, 0x08190808), uvec2(0x08080808, 0x08190819), uvec2(0x0808082b, 0x08190819),
uvec2(0x08081919, 0x08190819), uvec2(0x08082b08, 0x08190819), uvec2(0x08190819, 0x08190819), uvec2(0x08191908, 0x08190819),
uvec2(0x082b0808, 0x08190819), uvec2(0x19080819, 0x08190819), uvec2(0x19081908, 0x08190819), uvec2(0x19190808, 0x08190819),
uvec2(0x2b080808, 0x08190819), uvec2(0x2b191908, 0x08190819), uvec2(0x2b19192b, 0x08190819), uvec2(0x08080819, 0x0819082b),
uvec2(0x08081908, 0x0819082b), uvec2(0x0808192b, 0x0819082b), uvec2(0x08190808, 0x0819082b), uvec2(0x19080808, 0x0819082b),
uvec2(0x192b0808, 0x0819082b), uvec2(0x08080808, 0x08191908), uvec2(0x0808082b, 0x08191908), uvec2(0x08081919, 0x08191908),
uvec2(0x08082b08, 0x08191908), uvec2(0x08190819, 0x08191908), uvec2(0x08191908, 0x08191908), uvec2(0x082b0808, 0x08191908),
uvec2(0x19080819, 0x08191908), uvec2(0x19081908, 0x08191908), uvec2(0x19082b19, 0x08191908), uvec2(0x19190808, 0x08191908),
uvec2(0x192b1908, 0x08191908), uvec2(0x2b080808, 0x08191908), uvec2(0x08080819, 0x08191919), uvec2(0x08081908, 0x08191919),
uvec2(0x08190808, 0x08191919), uvec2(0x19080808, 0x08191919), uvec2(0x08080808, 0x0819192b), uvec2(0x08191908, 0x0819192b),
uvec2(0x19082b19, 0x0819192b), uvec2(0x08080819, 0x08192b08), uvec2(0x08081908, 0x08192b08), uvec2(0x08190808, 0x08192b08),
uvec2(0x0819082b, 0x08192b08), uvec2(0x19080808, 0x08192b08), uvec2(0x19191908, 0x08192b08), uvec2(0x2b08192b, 0x08192b08),
uvec2(0x08080808, 0x08192b19), uvec2(0x08081919, 0x08192b19), uvec2(0x192b192b, 0x08192b19), uvec2(0x19190819, 0x08192b2b),
uvec2(0x2b2b2b19, 0x08192b2b), uvec2(0x08080808, 0x082b0808), uvec2(0x0808082b, 0x082b0808), uvec2(0x08081919, 0x082b0808),
uvec2(0x08082b08, 0x082b0808), uvec2(0x08082b2b, 0x082b0808), uvec2(0x08190819, 0x082b0808), uvec2(0x08191908, 0x082b0808),
uvec2(0x082b0808, 0x082b0808), uvec2(0x19080819, 0x082b0808), uvec2(0x19081908, 0x082b0808), uvec2(0x19190808, 0x082b0808),
uvec2(0x2b080808, 0x082b0808), uvec2(0x2b2b0808, 0x082b0808), uvec2(0x08080819, 0x082b0819), uvec2(0x08081908, 0x082b0819),
uvec2(0x08190808, 0x082b0819), uvec2(0x19080808, 0x082b0819), uvec2(0x19082b08, 0x082b0819), uvec2(0x192b1919, 0x082b0819),
uvec2(0x08080808, 0x082b082b), uvec2(0x082b082b, 0x082b082b), uvec2(0x2b080808, 0x082b082b), uvec2(0x2b2b2b08, 0x082b082b),
uvec2(0x08080819, 0x082b1908), uvec2(0x08081908, 0x082b1908), uvec2(0x08190808, 0x082b1908), uvec2(0x082b2b19, 0x082b1908),
uvec2(0x19080808, 0x082b1908), uvec2(0x08080808, 0x082b1919), uvec2(0x19080819, 0x082b1919), uvec2(0x1919082b, 0x082b1919),
uvec2(0x2b192b19, 0x082b1919), uvec2(0x08080819, 0x082b192b), uvec2(0x08192b2b, 0x082b192b), uvec2(0x2b2b192b, 0x082b192b),
uvec2(0x08080808, 0x082b2b08), uvec2(0x08082b08, 0x082b2b08), uvec2(0x08082b2b, 0x082b2b08), uvec2(0x082b0808, 0x082b2b08),
uvec2(0x19191919, 0x082b2b08), uvec2(0x2b082b08, 0x082b2b08), uvec2(0x2b2b082b, 0x082b2b08), uvec2(0x192b2b08, 0x082b2b19),
uvec2(0x2b190808, 0x082b2b19), uvec2(0x08082b08, 0x082b2b2b), uvec2(0x082b0808, 0x082b2b2b), uvec2(0x2b08082b, 0x082b2b2b),
uvec2(0x2b082b08, 0x082b2b2b), uvec2(0x2b082b2b, 0x082b2b2b), uvec2(0x08080819, 0x19080808), uvec2(0x08081908, 0x19080808),
uvec2(0x0808192b, 0x19080808), uvec2(0x08082b19, 0x19080808), uvec2(0x08190808, 0x19080808), uvec2(0x0819082b, 0x19080808),
uvec2(0x08191919, 0x19080808), uvec2(0x08192b08, 0x19080808), uvec2(0x082b0819, 0x19080808), uvec2(0x082b1908, 0x19080808),
uvec2(0x19080808, 0x19080808), uvec2(0x1908082b, 0x19080808), uvec2(0x19081919, 0x19080808), uvec2(0x19082b08, 0x19080808),
uvec2(0x19082b2b, 0x19080808), uvec2(0x19190819, 0x19080808), uvec2(0x19191908, 0x19080808), uvec2(0x192b0808, 0x19080808),
uvec2(0x192b1919, 0x19080808), uvec2(0x2b080819, 0x19080808), uvec2(0x2b081908, 0x19080808), uvec2(0x2b190808, 0x19080808),
uvec2(0x08080808, 0x19080819), uvec2(0x0808082b, 0x19080819), uvec2(0x08081919, 0x19080819), uvec2(0x08082b08, 0x19080819),
uvec2(0x08190819, 0x19080819), uvec2(0x08191908, 0x19080819), uvec2(0x082b0808, 0x19080819), uvec2(0x19080819, 0x19080819),
uvec2(0x19081908, 0x19080819), uvec2(0x19190808, 0x19080819), uvec2(0x2b080808, 0x19080819), uvec2(0x2b081919, 0x19080819),
uvec2(0x2b2b082b, 0x19080819), uvec2(0x08080819, 0x1908082b), uvec2(0x08081908, 0x1908082b), uvec2(0x08190808, 0x1908082b),
uvec2(0x0819082b, 0x1908082b), uvec2(0x082b2b19, 0x1908082b), uvec2(0x19080808, 0x1908082b), uvec2(0x08080808, 0x19081908),
uvec2(0x0808082b, 0x19081908), uvec2(0x08081919, 0x19081908), uvec2(0x08082b08, 0x19081908), uvec2(0x08190819, 0x19081908),
uvec2(0x08191908, 0x19081908), uvec2(0x08192b19, 0x19081908), uvec2(0x082b0808, 0x19081908), uvec2(0x19080819, 0x19081908),
uvec2(0x19081908, 0x19081908), uvec2(0x19190808, 0x19081908), uvec2(0x2b080808, 0x19081908), uvec2(0x2b191908, 0x19081908),
uvec2(0x08080819, 0x19081919), uvec2(0x08081908, 0x19081919), uvec2(0x08190808, 0x19081919), uvec2(0x082b1908, 0x19081919),
uvec2(0x19080808, 0x19081919), uvec2(0x2b192b2b, 0x19081919), uvec2(0x08080808, 0x1908192b), uvec2(0x08082b2b, 0x1908192b),
uvec2(0x19081908, 0x1908192b), uvec2(0x19190808, 0x1908192b), uvec2(0x08080819, 0x19082b08), uvec2(0x08081908, 0x19082b08),
uvec2(0x08190808, 0x19082b08), uvec2(0x19080808, 0x19082b08), uvec2(0x19081919, 0x19082b08), uvec2(0x19191908, 0x19082b08),
uvec2(0x192b082b, 0x19082b08), uvec2(0x08080808, 0x19082b19), uvec2(0x08190819, 0x19082b19), uvec2(0x19081908, 0x19082b19),
uvec2(0x19190808, 0x19082b19), uvec2(0x192b2b19, 0x19082b19), uvec2(0x08081908, 0x19082b2b), uvec2(0x08080808, 0x19190808),
uvec2(0x0808082b, 0x19190808), uvec2(0x08081919, 0x19190808), uvec2(0x08082b08, 0x19190808), uvec2(0x08190819, 0x19190808),
uvec2(0x08191908, 0x19190808), uvec2(0x082b0808, 0x19190808), uvec2(0x082b2b08, 0x19190808), uvec2(0x19080819, 0x19190808),
uvec2(0x19081908, 0x19190808), uvec2(0x19190808, 0x19190808), uvec2(0x2b080808, 0x19190808), uvec2(0x08080819, 0x19190819),
uvec2(0x08081908, 0x19190819), uvec2(0x08190808, 0x19190819), uvec2(0x08191919, 0x19190819), uvec2(0x19080808, 0x19190819),
uvec2(0x1908082b, 0x19190819), uvec2(0x08080808, 0x1919082b), uvec2(0x19081908, 0x1919082b), uvec2(0x2b2b2b2b, 0x1919082b),
uvec2(0x08080819, 0x19191908), uvec2(0x08081908, 0x19191908), uvec2(0x08190808, 0x19191908), uvec2(0x082b0819, 0x19191908),
uvec2(0x19080808, 0x19191908), uvec2(0x192b0808, 0x19191908), uvec2(0x2b080819, 0x19191908), uvec2(0x2b2b0819, 0x19191908),
uvec2(0x08080808, 0x19191919), uvec2(0x08082b08, 0x19191919), uvec2(0x2b080808, 0x19191919), uvec2(0x2b082b08, 0x19191919),
uvec2(0x082b0819, 0x1919192b), uvec2(0x192b2b08, 0x1919192b), uvec2(0x2b2b0819, 0x1919192b), uvec2(0x08080808, 0x19192b08),
uvec2(0x08191908, 0x19192b08), uvec2(0x19080819, 0x19192b08), uvec2(0x19190808, 0x19192b08), uvec2(0x2b192b19, 0x19192b08),
uvec2(0x08192b2b, 0x19192b19), uvec2(0x19080808, 0x19192b19), uvec2(0x1908082b, 0x19192b19), uvec2(0x2b081919, 0x19192b2b),
uvec2(0x08080819, 0x192b0808), uvec2(0x08081908, 0x192b0808), uvec2(0x08190808, 0x192b0808), uvec2(0x19080808, 0x192b0808),
uvec2(0x19191908, 0x192b0808), uvec2(0x192b082b, 0x192b0808), uvec2(0x2b08192b, 0x192b0808), uvec2(0x2b2b2b19, 0x192b0808),
uvec2(0x08080808, 0x192b0819), uvec2(0x082b1908, 0x192b082b), uvec2(0x19082b2b, 0x192b082b), uvec2(0x2b19082b, 0x192b082b),
uvec2(0x08080808, 0x192b1908), uvec2(0x0819192b, 0x192b1908), uvec2(0x08190808, 0x192b1919), uvec2(0x19080808, 0x192b1919),
uvec2(0x19081919, 0x192b1919), uvec2(0x2b2b1908, 0x192b1919), uvec2(0x08080819, 0x192b2b08), uvec2(0x192b2b2b, 0x192b2b08),
uvec2(0x082b1919, 0x192b2b19), uvec2(0x0808192b, 0x192b2b2b), uvec2(0x19191908, 0x192b2b2b), uvec2(0x192b082b, 0x192b2b2b),
uvec2(0x08080808, 0x2b080808), uvec2(0x0808082b, 0x2b080808), uvec2(0x08081919, 0x2b080808), uvec2(0x08082b08, 0x2b080808),
uvec2(0x08190819, 0x2b080808), uvec2(0x08191908, 0x2b080808), uvec2(0x082b0808, 0x2b080808), uvec2(0x082b2b2b, 0x2b080808),
uvec2(0x19080819, 0x2b080808), uvec2(0x19081908, 0x2b080808), uvec2(0x19190808, 0x2b080808), uvec2(0x2b080808, 0x2b080808),
uvec2(0x2b08082b, 0x2b080808), uvec2(0x2b2b2b08, 0x2b080808), uvec2(0x2b2b2b2b, 0x2b080808), uvec2(0x08080819, 0x2b080819),
uvec2(0x08081908, 0x2b080819), uvec2(0x0808192b, 0x2b080819), uvec2(0x08190808, 0x2b080819), uvec2(0x19080808, 0x2b080819),
uvec2(0x19190819, 0x2b080819), uvec2(0x19192b19, 0x2b080819), uvec2(0x08080808, 0x2b08082b), uvec2(0x082b0808, 0x2b08082b),
uvec2(0x2b080808, 0x2b08082b), uvec2(0x2b08082b, 0x2b08082b), uvec2(0x2b2b0808, 0x2b08082b), uvec2(0x2b2b2b08, 0x2b08082b),
uvec2(0x08080819, 0x2b081908), uvec2(0x08081908, 0x2b081908), uvec2(0x08190808, 0x2b081908), uvec2(0x0819082b, 0x2b081908),
uvec2(0x08191919, 0x2b081908), uvec2(0x19080808, 0x2b081908), uvec2(0x192b0808, 0x2b081908), uvec2(0x2b082b19, 0x2b081908),
uvec2(0x08080808, 0x2b081919), uvec2(0x19081908, 0x2b081919), uvec2(0x2b2b1919, 0x2b081919), uvec2(0x08192b08, 0x2b08192b),
uvec2(0x192b2b2b, 0x2b08192b), uvec2(0x08080808, 0x2b082b08), uvec2(0x08082b08, 0x2b082b08), uvec2(0x082b1919, 0x2b082b08),
uvec2(0x19192b2b, 0x2b082b08), uvec2(0x2b080808, 0x2b082b08), uvec2(0x2b08082b, 0x2b082b08), uvec2(0x2b2b2b08, 0x2b082b08),
uvec2(0x0808192b, 0x2b082b19), uvec2(0x082b082b, 0x2b082b2b), uvec2(0x2b080808, 0x2b082b2b), uvec2(0x2b082b08, 0x2b082b2b),
uvec2(0x2b19192b, 0x2b082b2b), uvec2(0x2b2b2b08, 0x2b082b2b), uvec2(0x08080819, 0x2b190808), uvec2(0x08081908, 0x2b190808),
uvec2(0x08190808, 0x2b190808), uvec2(0x19080808, 0x2b190808), uvec2(0x1919192b, 0x2b190808), uvec2(0x2b081908, 0x2b190808),
uvec2(0x08080808, 0x2b190819), uvec2(0x082b082b, 0x2b190819), uvec2(0x192b1908, 0x2b190819), uvec2(0x1919192b, 0x2b19082b),
uvec2(0x2b082b19, 0x2b19082b), uvec2(0x08080808, 0x2b191908), uvec2(0x08081919, 0x2b191908), uvec2(0x19081908, 0x2b191908),
uvec2(0x19190808, 0x2b191908), uvec2(0x19192b08, 0x2b191908), uvec2(0x082b2b19, 0x2b191919), uvec2(0x2b190808, 0x2b191919),
uvec2(0x2b19082b, 0x2b191919), uvec2(0x19080819, 0x2b19192b), uvec2(0x19190819, 0x2b192b08), uvec2(0x2b2b192b, 0x2b192b08),
uvec2(0x19082b19, 0x2b192b19), uvec2(0x08191919, 0x2b192b2b), uvec2(0x192b0808, 0x2b192b2b), uvec2(0x08080808, 0x2b2b0808),
uvec2(0x0808082b, 0x2b2b0808), uvec2(0x08082b08, 0x2b2b0808), uvec2(0x08082b2b, 0x2b2b0808), uvec2(0x082b0808, 0x2b2b0808),
uvec2(0x082b2b2b, 0x2b2b0808), uvec2(0x2b2b0808, 0x2b2b0808), uvec2(0x19190819, 0x2b2b0819), uvec2(0x19192b19, 0x2b2b0819),
uvec2(0x2b2b192b, 0x2b2b0819), uvec2(0x08080808, 0x2b2b082b), uvec2(0x0808082b, 0x2b2b082b), uvec2(0x08082b08, 0x2b2b082b),
uvec2(0x082b2b2b, 0x2b2b082b), uvec2(0x2b080808, 0x2b2b082b), uvec2(0x2b2b0808, 0x2b2b082b), uvec2(0x19080808, 0x2b2b1908),
uvec2(0x2b191919, 0x2b2b1908), uvec2(0x192b1919, 0x2b2b192b), uvec2(0x2b192b08, 0x2b2b192b), uvec2(0x08082b2b, 0x2b2b2b08),
uvec2(0x082b0808, 0x2b2b2b08), uvec2(0x082b082b, 0x2b2b2b08), uvec2(0x082b2b08, 0x2b2b2b08), uvec2(0x2b2b0808, 0x2b2b2b08),
uvec2(0x2b2b2b08, 0x2b2b2b08), uvec2(0x08081908, 0x2b2b2b19), uvec2(0x2b081908, 0x2b2b2b19), uvec2(0x2b08192b, 0x2b2b2b19),
uvec2(0x082b2b08, 0x2b2b2b2b), uvec2(0x082b2b2b, 0x2b2b2b2b), uvec2(0x2b190819, 0x2b2b2b2b), uvec2(0x2b2b2b2b, 0x2b2b2b2b),
};
shared uvec2 iq2xs_grid[512];
void init_iq_shmem(uvec3 wgsize)
{
// copy the table into shared memory and sync
for (uint i = gl_LocalInvocationIndex.x; i < iq2xs_grid.length(); i += wgsize.x) {
iq2xs_grid[i] = iq2xs_grid_const[i];
}
barrier();
}
#define QUANT_K QUANT_K_IQ2_XS
#define QUANT_R QUANT_R_IQ2_XS
#define A_TYPE block_iq2_xs
#define A_TYPE_PACKED16 block_iq2_xs_packed16
#endif
#define QUANT_K_IQ2_S 256
#define QUANT_R_IQ2_S 1
struct block_iq2_s
{
float16_t d;
uint8_t qs[QUANT_K_IQ2_S/4];
uint8_t qh[QUANT_K_IQ2_S/32];
uint8_t scales[QUANT_K_IQ2_S/32];
};
#if defined(DATA_A_IQ2_S)
const uvec2 iq2s_grid_const[1024] = {
uvec2(0x08080808, 0x08080808), uvec2(0x0808082b, 0x08080808), uvec2(0x08081919, 0x08080808), uvec2(0x08082b08, 0x08080808),
uvec2(0x08082b2b, 0x08080808), uvec2(0x08190819, 0x08080808), uvec2(0x08191908, 0x08080808), uvec2(0x0819192b, 0x08080808),
uvec2(0x08192b19, 0x08080808), uvec2(0x082b0808, 0x08080808), uvec2(0x082b082b, 0x08080808), uvec2(0x082b1919, 0x08080808),
uvec2(0x082b2b08, 0x08080808), uvec2(0x19080819, 0x08080808), uvec2(0x19081908, 0x08080808), uvec2(0x1908192b, 0x08080808),
uvec2(0x19082b19, 0x08080808), uvec2(0x19190808, 0x08080808), uvec2(0x1919082b, 0x08080808), uvec2(0x19191919, 0x08080808),
uvec2(0x19192b08, 0x08080808), uvec2(0x192b0819, 0x08080808), uvec2(0x192b1908, 0x08080808), uvec2(0x192b192b, 0x08080808),
uvec2(0x192b2b19, 0x08080808), uvec2(0x2b080808, 0x08080808), uvec2(0x2b08082b, 0x08080808), uvec2(0x2b081919, 0x08080808),
uvec2(0x2b082b08, 0x08080808), uvec2(0x2b190819, 0x08080808), uvec2(0x2b191908, 0x08080808), uvec2(0x2b2b0808, 0x08080808),
uvec2(0x2b2b1919, 0x08080808), uvec2(0x2b2b2b2b, 0x08080808), uvec2(0x08080819, 0x08080819), uvec2(0x08081908, 0x08080819),
uvec2(0x0808192b, 0x08080819), uvec2(0x08082b19, 0x08080819), uvec2(0x08190808, 0x08080819), uvec2(0x0819082b, 0x08080819),
uvec2(0x08191919, 0x08080819), uvec2(0x08192b08, 0x08080819), uvec2(0x082b0819, 0x08080819), uvec2(0x082b1908, 0x08080819),
uvec2(0x19080808, 0x08080819), uvec2(0x1908082b, 0x08080819), uvec2(0x19081919, 0x08080819), uvec2(0x19082b08, 0x08080819),
uvec2(0x19190819, 0x08080819), uvec2(0x19191908, 0x08080819), uvec2(0x1919192b, 0x08080819), uvec2(0x19192b19, 0x08080819),
uvec2(0x192b0808, 0x08080819), uvec2(0x192b1919, 0x08080819), uvec2(0x192b2b08, 0x08080819), uvec2(0x2b080819, 0x08080819),
uvec2(0x2b081908, 0x08080819), uvec2(0x2b190808, 0x08080819), uvec2(0x2b19082b, 0x08080819), uvec2(0x2b191919, 0x08080819),
uvec2(0x2b2b0819, 0x08080819), uvec2(0x2b2b1908, 0x08080819), uvec2(0x08080808, 0x0808082b), uvec2(0x0808082b, 0x0808082b),
uvec2(0x08081919, 0x0808082b), uvec2(0x08082b08, 0x0808082b), uvec2(0x08190819, 0x0808082b), uvec2(0x08191908, 0x0808082b),
uvec2(0x082b0808, 0x0808082b), uvec2(0x082b2b2b, 0x0808082b), uvec2(0x19080819, 0x0808082b), uvec2(0x19081908, 0x0808082b),
uvec2(0x1908192b, 0x0808082b), uvec2(0x19082b19, 0x0808082b), uvec2(0x19190808, 0x0808082b), uvec2(0x19191919, 0x0808082b),
uvec2(0x2b080808, 0x0808082b), uvec2(0x2b081919, 0x0808082b), uvec2(0x2b082b2b, 0x0808082b), uvec2(0x2b191908, 0x0808082b),
uvec2(0x2b2b082b, 0x0808082b), uvec2(0x08080819, 0x08081908), uvec2(0x08081908, 0x08081908), uvec2(0x0808192b, 0x08081908),
uvec2(0x08082b19, 0x08081908), uvec2(0x08190808, 0x08081908), uvec2(0x0819082b, 0x08081908), uvec2(0x08191919, 0x08081908),
uvec2(0x08192b08, 0x08081908), uvec2(0x082b0819, 0x08081908), uvec2(0x082b1908, 0x08081908), uvec2(0x082b192b, 0x08081908),
uvec2(0x082b2b19, 0x08081908), uvec2(0x19080808, 0x08081908), uvec2(0x1908082b, 0x08081908), uvec2(0x19081919, 0x08081908),
uvec2(0x19082b08, 0x08081908), uvec2(0x19082b2b, 0x08081908), uvec2(0x19190819, 0x08081908), uvec2(0x19191908, 0x08081908),
uvec2(0x1919192b, 0x08081908), uvec2(0x19192b19, 0x08081908), uvec2(0x192b0808, 0x08081908), uvec2(0x192b082b, 0x08081908),
uvec2(0x192b1919, 0x08081908), uvec2(0x2b080819, 0x08081908), uvec2(0x2b081908, 0x08081908), uvec2(0x2b08192b, 0x08081908),
uvec2(0x2b082b19, 0x08081908), uvec2(0x2b190808, 0x08081908), uvec2(0x2b191919, 0x08081908), uvec2(0x2b192b08, 0x08081908),
uvec2(0x2b2b0819, 0x08081908), uvec2(0x2b2b1908, 0x08081908), uvec2(0x08080808, 0x08081919), uvec2(0x0808082b, 0x08081919),
uvec2(0x08081919, 0x08081919), uvec2(0x08082b08, 0x08081919), uvec2(0x08082b2b, 0x08081919), uvec2(0x08190819, 0x08081919),
uvec2(0x08191908, 0x08081919), uvec2(0x0819192b, 0x08081919), uvec2(0x08192b19, 0x08081919), uvec2(0x082b0808, 0x08081919),
uvec2(0x082b1919, 0x08081919), uvec2(0x082b2b08, 0x08081919), uvec2(0x19080819, 0x08081919), uvec2(0x19081908, 0x08081919),
uvec2(0x1908192b, 0x08081919), uvec2(0x19082b19, 0x08081919), uvec2(0x19190808, 0x08081919), uvec2(0x1919082b, 0x08081919),
uvec2(0x19191919, 0x08081919), uvec2(0x19192b08, 0x08081919), uvec2(0x192b0819, 0x08081919), uvec2(0x192b1908, 0x08081919),
uvec2(0x2b080808, 0x08081919), uvec2(0x2b08082b, 0x08081919), uvec2(0x2b081919, 0x08081919), uvec2(0x2b082b08, 0x08081919),
uvec2(0x2b190819, 0x08081919), uvec2(0x2b191908, 0x08081919), uvec2(0x2b2b0808, 0x08081919), uvec2(0x08080819, 0x0808192b),
uvec2(0x08081908, 0x0808192b), uvec2(0x0808192b, 0x0808192b), uvec2(0x08082b19, 0x0808192b), uvec2(0x08190808, 0x0808192b),
uvec2(0x08191919, 0x0808192b), uvec2(0x19080808, 0x0808192b), uvec2(0x19081919, 0x0808192b), uvec2(0x19082b08, 0x0808192b),
uvec2(0x19190819, 0x0808192b), uvec2(0x19191908, 0x0808192b), uvec2(0x192b0808, 0x0808192b), uvec2(0x2b080819, 0x0808192b),
uvec2(0x2b081908, 0x0808192b), uvec2(0x2b190808, 0x0808192b), uvec2(0x08080808, 0x08082b08), uvec2(0x0808082b, 0x08082b08),
uvec2(0x08081919, 0x08082b08), uvec2(0x08082b08, 0x08082b08), uvec2(0x08190819, 0x08082b08), uvec2(0x08191908, 0x08082b08),
uvec2(0x0819192b, 0x08082b08), uvec2(0x08192b19, 0x08082b08), uvec2(0x082b0808, 0x08082b08), uvec2(0x082b1919, 0x08082b08),
uvec2(0x082b2b2b, 0x08082b08), uvec2(0x19080819, 0x08082b08), uvec2(0x19081908, 0x08082b08), uvec2(0x1908192b, 0x08082b08),
uvec2(0x19082b19, 0x08082b08), uvec2(0x19190808, 0x08082b08), uvec2(0x1919082b, 0x08082b08), uvec2(0x19191919, 0x08082b08),
uvec2(0x19192b08, 0x08082b08), uvec2(0x192b0819, 0x08082b08), uvec2(0x192b1908, 0x08082b08), uvec2(0x2b080808, 0x08082b08),
uvec2(0x2b081919, 0x08082b08), uvec2(0x2b191908, 0x08082b08), uvec2(0x2b2b2b2b, 0x08082b08), uvec2(0x08080819, 0x08082b19),
uvec2(0x08081908, 0x08082b19), uvec2(0x08190808, 0x08082b19), uvec2(0x0819082b, 0x08082b19), uvec2(0x08191919, 0x08082b19),
uvec2(0x08192b08, 0x08082b19), uvec2(0x082b0819, 0x08082b19), uvec2(0x19080808, 0x08082b19), uvec2(0x19081919, 0x08082b19),
uvec2(0x19082b08, 0x08082b19), uvec2(0x19190819, 0x08082b19), uvec2(0x19191908, 0x08082b19), uvec2(0x192b0808, 0x08082b19),
uvec2(0x2b080819, 0x08082b19), uvec2(0x2b190808, 0x08082b19), uvec2(0x08080808, 0x08082b2b), uvec2(0x08190819, 0x08082b2b),
uvec2(0x08191908, 0x08082b2b), uvec2(0x082b082b, 0x08082b2b), uvec2(0x082b2b08, 0x08082b2b), uvec2(0x082b2b2b, 0x08082b2b),
uvec2(0x19190808, 0x08082b2b), uvec2(0x2b192b19, 0x08082b2b), uvec2(0x08080819, 0x08190808), uvec2(0x08081908, 0x08190808),
uvec2(0x0808192b, 0x08190808), uvec2(0x08082b19, 0x08190808), uvec2(0x08190808, 0x08190808), uvec2(0x0819082b, 0x08190808),
uvec2(0x08191919, 0x08190808), uvec2(0x08192b08, 0x08190808), uvec2(0x082b0819, 0x08190808), uvec2(0x082b1908, 0x08190808),
uvec2(0x082b192b, 0x08190808), uvec2(0x19080808, 0x08190808), uvec2(0x1908082b, 0x08190808), uvec2(0x19081919, 0x08190808),
uvec2(0x19082b08, 0x08190808), uvec2(0x19190819, 0x08190808), uvec2(0x19191908, 0x08190808), uvec2(0x1919192b, 0x08190808),
uvec2(0x19192b19, 0x08190808), uvec2(0x192b0808, 0x08190808), uvec2(0x192b082b, 0x08190808), uvec2(0x192b1919, 0x08190808),
uvec2(0x192b2b08, 0x08190808), uvec2(0x2b080819, 0x08190808), uvec2(0x2b081908, 0x08190808), uvec2(0x2b08192b, 0x08190808),
uvec2(0x2b190808, 0x08190808), uvec2(0x2b191919, 0x08190808), uvec2(0x2b192b08, 0x08190808), uvec2(0x2b2b0819, 0x08190808),
uvec2(0x2b2b1908, 0x08190808), uvec2(0x08080808, 0x08190819), uvec2(0x0808082b, 0x08190819), uvec2(0x08081919, 0x08190819),
uvec2(0x08082b08, 0x08190819), uvec2(0x08082b2b, 0x08190819), uvec2(0x08190819, 0x08190819), uvec2(0x08191908, 0x08190819),
uvec2(0x0819192b, 0x08190819), uvec2(0x08192b19, 0x08190819), uvec2(0x082b0808, 0x08190819), uvec2(0x082b082b, 0x08190819),
uvec2(0x082b1919, 0x08190819), uvec2(0x082b2b08, 0x08190819), uvec2(0x19080819, 0x08190819), uvec2(0x19081908, 0x08190819),
uvec2(0x1908192b, 0x08190819), uvec2(0x19082b19, 0x08190819), uvec2(0x19190808, 0x08190819), uvec2(0x1919082b, 0x08190819),
uvec2(0x19191919, 0x08190819), uvec2(0x19192b08, 0x08190819), uvec2(0x192b0819, 0x08190819), uvec2(0x192b1908, 0x08190819),
uvec2(0x2b080808, 0x08190819), uvec2(0x2b08082b, 0x08190819), uvec2(0x2b081919, 0x08190819), uvec2(0x2b082b08, 0x08190819),
uvec2(0x2b190819, 0x08190819), uvec2(0x2b191908, 0x08190819), uvec2(0x08080819, 0x0819082b), uvec2(0x08081908, 0x0819082b),
uvec2(0x08082b19, 0x0819082b), uvec2(0x08190808, 0x0819082b), uvec2(0x08191919, 0x0819082b), uvec2(0x082b0819, 0x0819082b),
uvec2(0x082b1908, 0x0819082b), uvec2(0x19080808, 0x0819082b), uvec2(0x19081919, 0x0819082b), uvec2(0x19190819, 0x0819082b),
uvec2(0x19191908, 0x0819082b), uvec2(0x2b080819, 0x0819082b), uvec2(0x2b081908, 0x0819082b), uvec2(0x2b190808, 0x0819082b),
uvec2(0x08080808, 0x08191908), uvec2(0x0808082b, 0x08191908), uvec2(0x08081919, 0x08191908), uvec2(0x08082b08, 0x08191908),
uvec2(0x08190819, 0x08191908), uvec2(0x08191908, 0x08191908), uvec2(0x0819192b, 0x08191908), uvec2(0x08192b19, 0x08191908),
uvec2(0x082b0808, 0x08191908), uvec2(0x082b1919, 0x08191908), uvec2(0x082b2b08, 0x08191908), uvec2(0x19080819, 0x08191908),
uvec2(0x19081908, 0x08191908), uvec2(0x1908192b, 0x08191908), uvec2(0x19082b19, 0x08191908), uvec2(0x19190808, 0x08191908),
uvec2(0x1919082b, 0x08191908), uvec2(0x19191919, 0x08191908), uvec2(0x19192b08, 0x08191908), uvec2(0x192b0819, 0x08191908),
uvec2(0x192b1908, 0x08191908), uvec2(0x2b080808, 0x08191908), uvec2(0x2b08082b, 0x08191908), uvec2(0x2b081919, 0x08191908),
uvec2(0x2b082b08, 0x08191908), uvec2(0x2b190819, 0x08191908), uvec2(0x2b191908, 0x08191908), uvec2(0x2b2b0808, 0x08191908),
uvec2(0x08080819, 0x08191919), uvec2(0x08081908, 0x08191919), uvec2(0x0808192b, 0x08191919), uvec2(0x08082b19, 0x08191919),
uvec2(0x08190808, 0x08191919), uvec2(0x0819082b, 0x08191919), uvec2(0x08191919, 0x08191919), uvec2(0x08192b08, 0x08191919),
uvec2(0x082b0819, 0x08191919), uvec2(0x082b1908, 0x08191919), uvec2(0x19080808, 0x08191919), uvec2(0x1908082b, 0x08191919),
uvec2(0x19081919, 0x08191919), uvec2(0x19082b08, 0x08191919), uvec2(0x19190819, 0x08191919), uvec2(0x19191908, 0x08191919),
uvec2(0x192b0808, 0x08191919), uvec2(0x2b080819, 0x08191919), uvec2(0x2b081908, 0x08191919), uvec2(0x2b190808, 0x08191919),
uvec2(0x08080808, 0x0819192b), uvec2(0x08081919, 0x0819192b), uvec2(0x08082b08, 0x0819192b), uvec2(0x08190819, 0x0819192b),
uvec2(0x08191908, 0x0819192b), uvec2(0x082b0808, 0x0819192b), uvec2(0x19080819, 0x0819192b), uvec2(0x19081908, 0x0819192b),
uvec2(0x19190808, 0x0819192b), uvec2(0x2b080808, 0x0819192b), uvec2(0x2b2b2b2b, 0x0819192b), uvec2(0x08080819, 0x08192b08),
uvec2(0x08081908, 0x08192b08), uvec2(0x0808192b, 0x08192b08), uvec2(0x08082b19, 0x08192b08), uvec2(0x08190808, 0x08192b08),
uvec2(0x08191919, 0x08192b08), uvec2(0x08192b08, 0x08192b08), uvec2(0x082b0819, 0x08192b08), uvec2(0x19080808, 0x08192b08),
uvec2(0x1908082b, 0x08192b08), uvec2(0x19081919, 0x08192b08), uvec2(0x19082b08, 0x08192b08), uvec2(0x19190819, 0x08192b08),
uvec2(0x19191908, 0x08192b08), uvec2(0x192b0808, 0x08192b08), uvec2(0x2b080819, 0x08192b08), uvec2(0x2b081908, 0x08192b08),
uvec2(0x08080808, 0x08192b19), uvec2(0x0808082b, 0x08192b19), uvec2(0x08081919, 0x08192b19), uvec2(0x08082b08, 0x08192b19),
uvec2(0x08190819, 0x08192b19), uvec2(0x08191908, 0x08192b19), uvec2(0x082b0808, 0x08192b19), uvec2(0x19080819, 0x08192b19),
uvec2(0x19081908, 0x08192b19), uvec2(0x19190808, 0x08192b19), uvec2(0x192b2b19, 0x08192b19), uvec2(0x2b2b082b, 0x08192b19),
uvec2(0x08081908, 0x08192b2b), uvec2(0x08190808, 0x08192b2b), uvec2(0x19080808, 0x08192b2b), uvec2(0x1919192b, 0x08192b2b),
uvec2(0x08080808, 0x082b0808), uvec2(0x0808082b, 0x082b0808), uvec2(0x08081919, 0x082b0808), uvec2(0x08082b08, 0x082b0808),
uvec2(0x08190819, 0x082b0808), uvec2(0x08191908, 0x082b0808), uvec2(0x0819192b, 0x082b0808), uvec2(0x08192b19, 0x082b0808),
uvec2(0x082b0808, 0x082b0808), uvec2(0x082b1919, 0x082b0808), uvec2(0x082b2b2b, 0x082b0808), uvec2(0x19080819, 0x082b0808),
uvec2(0x19081908, 0x082b0808), uvec2(0x19190808, 0x082b0808), uvec2(0x1919082b, 0x082b0808), uvec2(0x19191919, 0x082b0808),
uvec2(0x192b1908, 0x082b0808), uvec2(0x2b080808, 0x082b0808), uvec2(0x2b082b2b, 0x082b0808), uvec2(0x2b191908, 0x082b0808),
uvec2(0x2b2b2b2b, 0x082b0808), uvec2(0x08080819, 0x082b0819), uvec2(0x08081908, 0x082b0819), uvec2(0x08190808, 0x082b0819),
uvec2(0x0819082b, 0x082b0819), uvec2(0x08191919, 0x082b0819), uvec2(0x082b0819, 0x082b0819), uvec2(0x19080808, 0x082b0819),
uvec2(0x1908082b, 0x082b0819), uvec2(0x19081919, 0x082b0819), uvec2(0x19190819, 0x082b0819), uvec2(0x19191908, 0x082b0819),
uvec2(0x192b0808, 0x082b0819), uvec2(0x2b080819, 0x082b0819), uvec2(0x2b081908, 0x082b0819), uvec2(0x2b190808, 0x082b0819),
uvec2(0x08080808, 0x082b082b), uvec2(0x08082b2b, 0x082b082b), uvec2(0x082b082b, 0x082b082b), uvec2(0x082b2b08, 0x082b082b),
uvec2(0x082b2b2b, 0x082b082b), uvec2(0x19081908, 0x082b082b), uvec2(0x19190808, 0x082b082b), uvec2(0x2b082b08, 0x082b082b),
uvec2(0x2b082b2b, 0x082b082b), uvec2(0x2b2b2b08, 0x082b082b), uvec2(0x08080819, 0x082b1908), uvec2(0x08081908, 0x082b1908),
uvec2(0x0808192b, 0x082b1908), uvec2(0x08082b19, 0x082b1908), uvec2(0x08190808, 0x082b1908), uvec2(0x08191919, 0x082b1908),
uvec2(0x08192b08, 0x082b1908), uvec2(0x082b0819, 0x082b1908), uvec2(0x082b1908, 0x082b1908), uvec2(0x19080808, 0x082b1908),
uvec2(0x1908082b, 0x082b1908), uvec2(0x19081919, 0x082b1908), uvec2(0x19082b08, 0x082b1908), uvec2(0x19190819, 0x082b1908),
uvec2(0x19191908, 0x082b1908), uvec2(0x192b0808, 0x082b1908), uvec2(0x2b080819, 0x082b1908), uvec2(0x2b081908, 0x082b1908),
uvec2(0x2b190808, 0x082b1908), uvec2(0x08080808, 0x082b1919), uvec2(0x08081919, 0x082b1919), uvec2(0x08082b08, 0x082b1919),
uvec2(0x08190819, 0x082b1919), uvec2(0x08191908, 0x082b1919), uvec2(0x082b0808, 0x082b1919), uvec2(0x19080819, 0x082b1919),
uvec2(0x19081908, 0x082b1919), uvec2(0x19190808, 0x082b1919), uvec2(0x192b192b, 0x082b1919), uvec2(0x2b080808, 0x082b1919),
uvec2(0x08080819, 0x082b192b), uvec2(0x08081908, 0x082b192b), uvec2(0x08190808, 0x082b192b), uvec2(0x19080808, 0x082b192b),
uvec2(0x19192b19, 0x082b192b), uvec2(0x08080808, 0x082b2b08), uvec2(0x08081919, 0x082b2b08), uvec2(0x08190819, 0x082b2b08),
uvec2(0x08191908, 0x082b2b08), uvec2(0x19080819, 0x082b2b08), uvec2(0x19081908, 0x082b2b08), uvec2(0x19190808, 0x082b2b08),
uvec2(0x2b082b2b, 0x082b2b08), uvec2(0x2b2b2b2b, 0x082b2b08), uvec2(0x08080819, 0x082b2b19), uvec2(0x08081908, 0x082b2b19),
uvec2(0x08190808, 0x082b2b19), uvec2(0x2b191919, 0x082b2b19), uvec2(0x08082b2b, 0x082b2b2b), uvec2(0x082b082b, 0x082b2b2b),
uvec2(0x192b1908, 0x082b2b2b), uvec2(0x2b082b08, 0x082b2b2b), uvec2(0x2b082b2b, 0x082b2b2b), uvec2(0x08080819, 0x19080808),
uvec2(0x08081908, 0x19080808), uvec2(0x0808192b, 0x19080808), uvec2(0x08082b19, 0x19080808), uvec2(0x08190808, 0x19080808),
uvec2(0x0819082b, 0x19080808), uvec2(0x08191919, 0x19080808), uvec2(0x08192b08, 0x19080808), uvec2(0x08192b2b, 0x19080808),
uvec2(0x082b0819, 0x19080808), uvec2(0x082b1908, 0x19080808), uvec2(0x082b192b, 0x19080808), uvec2(0x19080808, 0x19080808),
uvec2(0x1908082b, 0x19080808), uvec2(0x19081919, 0x19080808), uvec2(0x19082b08, 0x19080808), uvec2(0x19082b2b, 0x19080808),
uvec2(0x19190819, 0x19080808), uvec2(0x19191908, 0x19080808), uvec2(0x1919192b, 0x19080808), uvec2(0x19192b19, 0x19080808),
uvec2(0x192b0808, 0x19080808), uvec2(0x192b082b, 0x19080808), uvec2(0x192b1919, 0x19080808), uvec2(0x2b080819, 0x19080808),
uvec2(0x2b081908, 0x19080808), uvec2(0x2b190808, 0x19080808), uvec2(0x2b191919, 0x19080808), uvec2(0x2b192b08, 0x19080808),
uvec2(0x2b2b0819, 0x19080808), uvec2(0x2b2b1908, 0x19080808), uvec2(0x08080808, 0x19080819), uvec2(0x0808082b, 0x19080819),
uvec2(0x08081919, 0x19080819), uvec2(0x08082b08, 0x19080819), uvec2(0x08190819, 0x19080819), uvec2(0x08191908, 0x19080819),
uvec2(0x0819192b, 0x19080819), uvec2(0x08192b19, 0x19080819), uvec2(0x082b0808, 0x19080819), uvec2(0x082b082b, 0x19080819),
uvec2(0x082b1919, 0x19080819), uvec2(0x19080819, 0x19080819), uvec2(0x19081908, 0x19080819), uvec2(0x1908192b, 0x19080819),
uvec2(0x19082b19, 0x19080819), uvec2(0x19190808, 0x19080819), uvec2(0x1919082b, 0x19080819), uvec2(0x19191919, 0x19080819),
uvec2(0x19192b08, 0x19080819), uvec2(0x192b0819, 0x19080819), uvec2(0x192b1908, 0x19080819), uvec2(0x2b080808, 0x19080819),
uvec2(0x2b08082b, 0x19080819), uvec2(0x2b081919, 0x19080819), uvec2(0x2b082b08, 0x19080819), uvec2(0x2b190819, 0x19080819),
uvec2(0x2b191908, 0x19080819), uvec2(0x2b2b0808, 0x19080819), uvec2(0x08080819, 0x1908082b), uvec2(0x08081908, 0x1908082b),
uvec2(0x08190808, 0x1908082b), uvec2(0x0819082b, 0x1908082b), uvec2(0x08191919, 0x1908082b), uvec2(0x08192b08, 0x1908082b),
uvec2(0x082b1908, 0x1908082b), uvec2(0x19080808, 0x1908082b), uvec2(0x19081919, 0x1908082b), uvec2(0x19082b08, 0x1908082b),
uvec2(0x19190819, 0x1908082b), uvec2(0x19191908, 0x1908082b), uvec2(0x192b0808, 0x1908082b), uvec2(0x2b080819, 0x1908082b),
uvec2(0x2b081908, 0x1908082b), uvec2(0x08080808, 0x19081908), uvec2(0x0808082b, 0x19081908), uvec2(0x08081919, 0x19081908),
uvec2(0x08082b08, 0x19081908), uvec2(0x08082b2b, 0x19081908), uvec2(0x08190819, 0x19081908), uvec2(0x08191908, 0x19081908),
uvec2(0x0819192b, 0x19081908), uvec2(0x08192b19, 0x19081908), uvec2(0x082b0808, 0x19081908), uvec2(0x082b082b, 0x19081908),
uvec2(0x082b1919, 0x19081908), uvec2(0x082b2b08, 0x19081908), uvec2(0x19080819, 0x19081908), uvec2(0x19081908, 0x19081908),
uvec2(0x1908192b, 0x19081908), uvec2(0x19082b19, 0x19081908), uvec2(0x19190808, 0x19081908), uvec2(0x1919082b, 0x19081908),
uvec2(0x19191919, 0x19081908), uvec2(0x19192b08, 0x19081908), uvec2(0x192b0819, 0x19081908), uvec2(0x192b1908, 0x19081908),
uvec2(0x2b080808, 0x19081908), uvec2(0x2b08082b, 0x19081908), uvec2(0x2b081919, 0x19081908), uvec2(0x2b082b08, 0x19081908),
uvec2(0x2b190819, 0x19081908), uvec2(0x2b191908, 0x19081908), uvec2(0x2b2b0808, 0x19081908), uvec2(0x08080819, 0x19081919),
uvec2(0x08081908, 0x19081919), uvec2(0x0808192b, 0x19081919), uvec2(0x08082b19, 0x19081919), uvec2(0x08190808, 0x19081919),
uvec2(0x0819082b, 0x19081919), uvec2(0x08191919, 0x19081919), uvec2(0x08192b08, 0x19081919), uvec2(0x082b0819, 0x19081919),
uvec2(0x082b1908, 0x19081919), uvec2(0x19080808, 0x19081919), uvec2(0x1908082b, 0x19081919), uvec2(0x19081919, 0x19081919),
uvec2(0x19082b08, 0x19081919), uvec2(0x19190819, 0x19081919), uvec2(0x19191908, 0x19081919), uvec2(0x192b0808, 0x19081919),
uvec2(0x192b2b2b, 0x19081919), uvec2(0x2b080819, 0x19081919), uvec2(0x2b081908, 0x19081919), uvec2(0x2b190808, 0x19081919),
uvec2(0x08080808, 0x1908192b), uvec2(0x0808082b, 0x1908192b), uvec2(0x08081919, 0x1908192b), uvec2(0x08082b08, 0x1908192b),
uvec2(0x08190819, 0x1908192b), uvec2(0x08191908, 0x1908192b), uvec2(0x082b0808, 0x1908192b), uvec2(0x19080819, 0x1908192b),
uvec2(0x19081908, 0x1908192b), uvec2(0x19190808, 0x1908192b), uvec2(0x2b080808, 0x1908192b), uvec2(0x2b2b1919, 0x1908192b),
uvec2(0x08080819, 0x19082b08), uvec2(0x08081908, 0x19082b08), uvec2(0x08082b19, 0x19082b08), uvec2(0x08190808, 0x19082b08),
uvec2(0x0819082b, 0x19082b08), uvec2(0x08191919, 0x19082b08), uvec2(0x08192b08, 0x19082b08), uvec2(0x082b0819, 0x19082b08),
uvec2(0x082b1908, 0x19082b08), uvec2(0x19080808, 0x19082b08), uvec2(0x1908082b, 0x19082b08), uvec2(0x19081919, 0x19082b08),
uvec2(0x19082b08, 0x19082b08), uvec2(0x19190819, 0x19082b08), uvec2(0x19191908, 0x19082b08), uvec2(0x192b0808, 0x19082b08),
uvec2(0x2b081908, 0x19082b08), uvec2(0x2b190808, 0x19082b08), uvec2(0x08080808, 0x19082b19), uvec2(0x0808082b, 0x19082b19),
uvec2(0x08081919, 0x19082b19), uvec2(0x08082b08, 0x19082b19), uvec2(0x08190819, 0x19082b19), uvec2(0x08191908, 0x19082b19),
uvec2(0x082b0808, 0x19082b19), uvec2(0x19080819, 0x19082b19), uvec2(0x19081908, 0x19082b19), uvec2(0x19190808, 0x19082b19),
uvec2(0x2b080808, 0x19082b19), uvec2(0x2b19192b, 0x19082b19), uvec2(0x08080819, 0x19082b2b), uvec2(0x08081908, 0x19082b2b),
uvec2(0x08190808, 0x19082b2b), uvec2(0x19080808, 0x19082b2b), uvec2(0x08080808, 0x19190808), uvec2(0x0808082b, 0x19190808),
uvec2(0x08081919, 0x19190808), uvec2(0x08082b08, 0x19190808), uvec2(0x08190819, 0x19190808), uvec2(0x08191908, 0x19190808),
uvec2(0x0819192b, 0x19190808), uvec2(0x08192b19, 0x19190808), uvec2(0x082b0808, 0x19190808), uvec2(0x082b082b, 0x19190808),
uvec2(0x082b1919, 0x19190808), uvec2(0x082b2b08, 0x19190808), uvec2(0x19080819, 0x19190808), uvec2(0x19081908, 0x19190808),
uvec2(0x1908192b, 0x19190808), uvec2(0x19082b19, 0x19190808), uvec2(0x19190808, 0x19190808), uvec2(0x1919082b, 0x19190808),
uvec2(0x19191919, 0x19190808), uvec2(0x19192b08, 0x19190808), uvec2(0x192b0819, 0x19190808), uvec2(0x192b1908, 0x19190808),
uvec2(0x2b080808, 0x19190808), uvec2(0x2b08082b, 0x19190808), uvec2(0x2b081919, 0x19190808), uvec2(0x2b082b08, 0x19190808),
uvec2(0x2b190819, 0x19190808), uvec2(0x2b191908, 0x19190808), uvec2(0x08080819, 0x19190819), uvec2(0x08081908, 0x19190819),
uvec2(0x0808192b, 0x19190819), uvec2(0x08082b19, 0x19190819), uvec2(0x08190808, 0x19190819), uvec2(0x0819082b, 0x19190819),
uvec2(0x08191919, 0x19190819), uvec2(0x08192b08, 0x19190819), uvec2(0x082b0819, 0x19190819), uvec2(0x082b1908, 0x19190819),
uvec2(0x19080808, 0x19190819), uvec2(0x1908082b, 0x19190819), uvec2(0x19081919, 0x19190819), uvec2(0x19082b08, 0x19190819),
uvec2(0x19190819, 0x19190819), uvec2(0x19191908, 0x19190819), uvec2(0x192b0808, 0x19190819), uvec2(0x2b080819, 0x19190819),
uvec2(0x2b081908, 0x19190819), uvec2(0x2b190808, 0x19190819), uvec2(0x08080808, 0x1919082b), uvec2(0x08081919, 0x1919082b),
uvec2(0x08082b08, 0x1919082b), uvec2(0x08190819, 0x1919082b), uvec2(0x08191908, 0x1919082b), uvec2(0x082b0808, 0x1919082b),
uvec2(0x19080819, 0x1919082b), uvec2(0x19081908, 0x1919082b), uvec2(0x19190808, 0x1919082b), uvec2(0x192b2b19, 0x1919082b),
uvec2(0x2b080808, 0x1919082b), uvec2(0x08080819, 0x19191908), uvec2(0x08081908, 0x19191908), uvec2(0x0808192b, 0x19191908),
uvec2(0x08082b19, 0x19191908), uvec2(0x08190808, 0x19191908), uvec2(0x0819082b, 0x19191908), uvec2(0x08191919, 0x19191908),
uvec2(0x08192b08, 0x19191908), uvec2(0x082b0819, 0x19191908), uvec2(0x082b1908, 0x19191908), uvec2(0x19080808, 0x19191908),
uvec2(0x1908082b, 0x19191908), uvec2(0x19081919, 0x19191908), uvec2(0x19082b08, 0x19191908), uvec2(0x19190819, 0x19191908),
uvec2(0x19191908, 0x19191908), uvec2(0x192b0808, 0x19191908), uvec2(0x2b080819, 0x19191908), uvec2(0x2b081908, 0x19191908),
uvec2(0x2b190808, 0x19191908), uvec2(0x08080808, 0x19191919), uvec2(0x0808082b, 0x19191919), uvec2(0x08081919, 0x19191919),
uvec2(0x08082b08, 0x19191919), uvec2(0x08190819, 0x19191919), uvec2(0x08191908, 0x19191919), uvec2(0x082b0808, 0x19191919),
uvec2(0x19080819, 0x19191919), uvec2(0x19081908, 0x19191919), uvec2(0x19190808, 0x19191919), uvec2(0x2b080808, 0x19191919),
uvec2(0x08080819, 0x1919192b), uvec2(0x08081908, 0x1919192b), uvec2(0x08190808, 0x1919192b), uvec2(0x082b192b, 0x1919192b),
uvec2(0x19080808, 0x1919192b), uvec2(0x08080808, 0x19192b08), uvec2(0x0808082b, 0x19192b08), uvec2(0x08081919, 0x19192b08),
uvec2(0x08082b08, 0x19192b08), uvec2(0x08190819, 0x19192b08), uvec2(0x08191908, 0x19192b08), uvec2(0x082b0808, 0x19192b08),
uvec2(0x19080819, 0x19192b08), uvec2(0x19081908, 0x19192b08), uvec2(0x19190808, 0x19192b08), uvec2(0x19192b2b, 0x19192b08),
uvec2(0x2b080808, 0x19192b08), uvec2(0x08080819, 0x19192b19), uvec2(0x08081908, 0x19192b19), uvec2(0x08190808, 0x19192b19),
uvec2(0x19080808, 0x19192b19), uvec2(0x08080808, 0x19192b2b), uvec2(0x08192b19, 0x19192b2b), uvec2(0x2b081919, 0x19192b2b),
uvec2(0x2b2b2b08, 0x19192b2b), uvec2(0x08080819, 0x192b0808), uvec2(0x08081908, 0x192b0808), uvec2(0x0808192b, 0x192b0808),
uvec2(0x08190808, 0x192b0808), uvec2(0x0819082b, 0x192b0808), uvec2(0x08191919, 0x192b0808), uvec2(0x08192b08, 0x192b0808),
uvec2(0x082b0819, 0x192b0808), uvec2(0x082b1908, 0x192b0808), uvec2(0x19080808, 0x192b0808), uvec2(0x19081919, 0x192b0808),
uvec2(0x19082b08, 0x192b0808), uvec2(0x19190819, 0x192b0808), uvec2(0x19191908, 0x192b0808), uvec2(0x192b0808, 0x192b0808),
uvec2(0x2b081908, 0x192b0808), uvec2(0x2b190808, 0x192b0808), uvec2(0x08080808, 0x192b0819), uvec2(0x0808082b, 0x192b0819),
uvec2(0x08081919, 0x192b0819), uvec2(0x08082b08, 0x192b0819), uvec2(0x08190819, 0x192b0819), uvec2(0x08191908, 0x192b0819),
uvec2(0x082b0808, 0x192b0819), uvec2(0x19080819, 0x192b0819), uvec2(0x19081908, 0x192b0819), uvec2(0x19190808, 0x192b0819),
uvec2(0x2b080808, 0x192b0819), uvec2(0x2b192b19, 0x192b0819), uvec2(0x08081908, 0x192b082b), uvec2(0x08190808, 0x192b082b),
uvec2(0x19080808, 0x192b082b), uvec2(0x1919192b, 0x192b082b), uvec2(0x2b2b0819, 0x192b082b), uvec2(0x08080808, 0x192b1908),
uvec2(0x08081919, 0x192b1908), uvec2(0x08082b08, 0x192b1908), uvec2(0x08190819, 0x192b1908), uvec2(0x08191908, 0x192b1908),
uvec2(0x082b0808, 0x192b1908), uvec2(0x19080819, 0x192b1908), uvec2(0x19081908, 0x192b1908), uvec2(0x19190808, 0x192b1908),
uvec2(0x2b080808, 0x192b1908), uvec2(0x08080819, 0x192b1919), uvec2(0x08081908, 0x192b1919), uvec2(0x08190808, 0x192b1919),
uvec2(0x19080808, 0x192b1919), uvec2(0x19082b2b, 0x192b1919), uvec2(0x192b2b08, 0x192b1919), uvec2(0x2b19082b, 0x192b1919),
uvec2(0x08080808, 0x192b192b), uvec2(0x2b191908, 0x192b192b), uvec2(0x08080819, 0x192b2b08), uvec2(0x08081908, 0x192b2b08),
uvec2(0x08190808, 0x192b2b08), uvec2(0x192b1919, 0x192b2b08), uvec2(0x2b192b08, 0x192b2b08), uvec2(0x08080808, 0x192b2b19),
uvec2(0x082b2b2b, 0x192b2b19), uvec2(0x1908082b, 0x192b2b2b), uvec2(0x2b2b0819, 0x192b2b2b), uvec2(0x08080808, 0x2b080808),
uvec2(0x0808082b, 0x2b080808), uvec2(0x08081919, 0x2b080808), uvec2(0x08082b08, 0x2b080808), uvec2(0x08190819, 0x2b080808),
uvec2(0x08191908, 0x2b080808), uvec2(0x08192b19, 0x2b080808), uvec2(0x082b0808, 0x2b080808), uvec2(0x082b1919, 0x2b080808),
uvec2(0x19080819, 0x2b080808), uvec2(0x19081908, 0x2b080808), uvec2(0x19190808, 0x2b080808), uvec2(0x1919082b, 0x2b080808),
uvec2(0x19191919, 0x2b080808), uvec2(0x19192b08, 0x2b080808), uvec2(0x192b0819, 0x2b080808), uvec2(0x2b080808, 0x2b080808),
uvec2(0x2b081919, 0x2b080808), uvec2(0x2b190819, 0x2b080808), uvec2(0x2b191908, 0x2b080808), uvec2(0x08080819, 0x2b080819),
uvec2(0x08081908, 0x2b080819), uvec2(0x08082b19, 0x2b080819), uvec2(0x08190808, 0x2b080819), uvec2(0x0819082b, 0x2b080819),
uvec2(0x08191919, 0x2b080819), uvec2(0x08192b08, 0x2b080819), uvec2(0x082b0819, 0x2b080819), uvec2(0x082b1908, 0x2b080819),
uvec2(0x19080808, 0x2b080819), uvec2(0x1908082b, 0x2b080819), uvec2(0x19081919, 0x2b080819), uvec2(0x19082b08, 0x2b080819),
uvec2(0x19190819, 0x2b080819), uvec2(0x19191908, 0x2b080819), uvec2(0x2b080819, 0x2b080819), uvec2(0x2b081908, 0x2b080819),
uvec2(0x2b190808, 0x2b080819), uvec2(0x2b2b2b19, 0x2b080819), uvec2(0x08080808, 0x2b08082b), uvec2(0x08081919, 0x2b08082b),
uvec2(0x08082b2b, 0x2b08082b), uvec2(0x08190819, 0x2b08082b), uvec2(0x08191908, 0x2b08082b), uvec2(0x19080819, 0x2b08082b),
uvec2(0x19081908, 0x2b08082b), uvec2(0x19190808, 0x2b08082b), uvec2(0x08080819, 0x2b081908), uvec2(0x08081908, 0x2b081908),
uvec2(0x0808192b, 0x2b081908), uvec2(0x08082b19, 0x2b081908), uvec2(0x08190808, 0x2b081908), uvec2(0x0819082b, 0x2b081908),
uvec2(0x08191919, 0x2b081908), uvec2(0x08192b08, 0x2b081908), uvec2(0x082b0819, 0x2b081908), uvec2(0x19080808, 0x2b081908),
uvec2(0x1908082b, 0x2b081908), uvec2(0x19081919, 0x2b081908), uvec2(0x19082b08, 0x2b081908), uvec2(0x19190819, 0x2b081908),
uvec2(0x19191908, 0x2b081908), uvec2(0x192b0808, 0x2b081908), uvec2(0x2b080819, 0x2b081908), uvec2(0x2b081908, 0x2b081908),
uvec2(0x2b190808, 0x2b081908), uvec2(0x08080808, 0x2b081919), uvec2(0x0808082b, 0x2b081919), uvec2(0x08081919, 0x2b081919),
uvec2(0x08082b08, 0x2b081919), uvec2(0x08190819, 0x2b081919), uvec2(0x08191908, 0x2b081919), uvec2(0x082b0808, 0x2b081919),
uvec2(0x19080819, 0x2b081919), uvec2(0x19081908, 0x2b081919), uvec2(0x19190808, 0x2b081919), uvec2(0x2b080808, 0x2b081919),
uvec2(0x2b082b2b, 0x2b081919), uvec2(0x08080819, 0x2b08192b), uvec2(0x08081908, 0x2b08192b), uvec2(0x08190808, 0x2b08192b),
uvec2(0x082b2b19, 0x2b08192b), uvec2(0x19080808, 0x2b08192b), uvec2(0x08080808, 0x2b082b08), uvec2(0x08081919, 0x2b082b08),
uvec2(0x08190819, 0x2b082b08), uvec2(0x08191908, 0x2b082b08), uvec2(0x19080819, 0x2b082b08), uvec2(0x19081908, 0x2b082b08),
uvec2(0x19190808, 0x2b082b08), uvec2(0x2b2b082b, 0x2b082b08), uvec2(0x08080819, 0x2b082b19), uvec2(0x08081908, 0x2b082b19),
uvec2(0x19080808, 0x2b082b19), uvec2(0x192b1919, 0x2b082b19), uvec2(0x082b082b, 0x2b082b2b), uvec2(0x19192b08, 0x2b082b2b),
uvec2(0x19192b2b, 0x2b082b2b), uvec2(0x2b08082b, 0x2b082b2b), uvec2(0x2b2b082b, 0x2b082b2b), uvec2(0x08080819, 0x2b190808),
uvec2(0x08081908, 0x2b190808), uvec2(0x08082b19, 0x2b190808), uvec2(0x08190808, 0x2b190808), uvec2(0x0819082b, 0x2b190808),
uvec2(0x08191919, 0x2b190808), uvec2(0x08192b08, 0x2b190808), uvec2(0x082b1908, 0x2b190808), uvec2(0x19080808, 0x2b190808),
uvec2(0x1908082b, 0x2b190808), uvec2(0x19081919, 0x2b190808), uvec2(0x19082b08, 0x2b190808), uvec2(0x19190819, 0x2b190808),
uvec2(0x19191908, 0x2b190808), uvec2(0x192b0808, 0x2b190808), uvec2(0x2b080819, 0x2b190808), uvec2(0x2b081908, 0x2b190808),
uvec2(0x2b190808, 0x2b190808), uvec2(0x08080808, 0x2b190819), uvec2(0x08081919, 0x2b190819), uvec2(0x08190819, 0x2b190819),
uvec2(0x08191908, 0x2b190819), uvec2(0x19080819, 0x2b190819), uvec2(0x19081908, 0x2b190819), uvec2(0x19190808, 0x2b190819),
uvec2(0x19192b2b, 0x2b190819), uvec2(0x08080819, 0x2b19082b), uvec2(0x08081908, 0x2b19082b), uvec2(0x08190808, 0x2b19082b),
uvec2(0x19080808, 0x2b19082b), uvec2(0x2b2b192b, 0x2b19082b), uvec2(0x08080808, 0x2b191908), uvec2(0x0808082b, 0x2b191908),
uvec2(0x08081919, 0x2b191908), uvec2(0x08082b08, 0x2b191908), uvec2(0x08190819, 0x2b191908), uvec2(0x08191908, 0x2b191908),
uvec2(0x082b0808, 0x2b191908), uvec2(0x19080819, 0x2b191908), uvec2(0x19081908, 0x2b191908), uvec2(0x19190808, 0x2b191908),
uvec2(0x2b080808, 0x2b191908), uvec2(0x2b19192b, 0x2b191908), uvec2(0x08080819, 0x2b191919), uvec2(0x08081908, 0x2b191919),
uvec2(0x08190808, 0x2b191919), uvec2(0x19080808, 0x2b191919), uvec2(0x2b192b08, 0x2b191919), uvec2(0x2b2b0819, 0x2b191919),
uvec2(0x08080808, 0x2b19192b), uvec2(0x1908192b, 0x2b19192b), uvec2(0x192b1908, 0x2b19192b), uvec2(0x08080819, 0x2b192b08),
uvec2(0x08081908, 0x2b192b08), uvec2(0x08190808, 0x2b192b08), uvec2(0x082b192b, 0x2b192b08), uvec2(0x19080808, 0x2b192b08),
uvec2(0x2b2b2b19, 0x2b192b08), uvec2(0x08080808, 0x2b192b19), uvec2(0x19082b19, 0x2b192b19), uvec2(0x1919082b, 0x2b192b19),
uvec2(0x2b190808, 0x2b192b2b), uvec2(0x08080808, 0x2b2b0808), uvec2(0x08081919, 0x2b2b0808), uvec2(0x08082b2b, 0x2b2b0808),
uvec2(0x08191908, 0x2b2b0808), uvec2(0x082b082b, 0x2b2b0808), uvec2(0x082b2b2b, 0x2b2b0808), uvec2(0x19080819, 0x2b2b0808),
uvec2(0x19081908, 0x2b2b0808), uvec2(0x19190808, 0x2b2b0808), uvec2(0x2b2b082b, 0x2b2b0808), uvec2(0x2b2b2b2b, 0x2b2b0808),
uvec2(0x19080808, 0x2b2b0819), uvec2(0x192b1919, 0x2b2b0819), uvec2(0x0808082b, 0x2b2b082b), uvec2(0x08082b2b, 0x2b2b082b),
uvec2(0x082b082b, 0x2b2b082b), uvec2(0x082b2b08, 0x2b2b082b), uvec2(0x082b2b2b, 0x2b2b082b), uvec2(0x2b08082b, 0x2b2b082b),
uvec2(0x2b082b08, 0x2b2b082b), uvec2(0x2b082b2b, 0x2b2b082b), uvec2(0x2b2b2b08, 0x2b2b082b), uvec2(0x08080819, 0x2b2b1908),
uvec2(0x08081908, 0x2b2b1908), uvec2(0x08190808, 0x2b2b1908), uvec2(0x19080808, 0x2b2b1908), uvec2(0x2b082b19, 0x2b2b1908),
uvec2(0x2b2b1908, 0x2b2b1908), uvec2(0x08080808, 0x2b2b1919), uvec2(0x08192b19, 0x2b2b1919), uvec2(0x19190819, 0x2b2b192b),
uvec2(0x08082b2b, 0x2b2b2b08), uvec2(0x082b2b08, 0x2b2b2b08), uvec2(0x2b2b082b, 0x2b2b2b08), uvec2(0x19191908, 0x2b2b2b19),
uvec2(0x2b08192b, 0x2b2b2b19), uvec2(0x08082b08, 0x2b2b2b2b), uvec2(0x08082b2b, 0x2b2b2b2b), uvec2(0x082b0808, 0x2b2b2b2b),
uvec2(0x082b082b, 0x2b2b2b2b), uvec2(0x082b2b08, 0x2b2b2b2b), uvec2(0x2b082b08, 0x2b2b2b2b), uvec2(0x2b2b2b2b, 0x2b2b2b2b)
};
shared uvec2 iq2s_grid[1024];
void init_iq_shmem(uvec3 wgsize)
{
// copy the table into shared memory and sync
for (uint i = gl_LocalInvocationIndex.x; i < iq2s_grid.length(); i += wgsize.x) {
iq2s_grid[i] = iq2s_grid_const[i];
}
barrier();
}
#define QUANT_K QUANT_K_IQ2_S
#define QUANT_R QUANT_R_IQ2_S
#define A_TYPE block_iq2_s
#endif
#define QUANT_K_IQ3_XXS 256
#define QUANT_R_IQ3_XXS 1
struct block_iq3_xxs
{
float16_t d;
uint8_t qs[QUANT_K_IQ3_XXS/4 + QUANT_K_IQ3_XXS/8];
};
struct block_iq3_xxs_packed16
{
float16_t d;
uint16_t qs[QUANT_K_IQ3_XXS/8 + QUANT_K_IQ3_XXS/16];
};
#if defined(DATA_A_IQ3_XXS)
const uint32_t iq3xxs_grid_const[256] = {
0x04040404, 0x04040414, 0x04040424, 0x04040c0c, 0x04040c1c, 0x04040c3e, 0x04041404, 0x04041414,
0x04041c0c, 0x04042414, 0x04043e1c, 0x04043e2c, 0x040c040c, 0x040c041c, 0x040c0c04, 0x040c0c14,
0x040c140c, 0x040c142c, 0x040c1c04, 0x040c1c14, 0x040c240c, 0x040c2c24, 0x040c3e04, 0x04140404,
0x04140414, 0x04140424, 0x04140c0c, 0x04141404, 0x04141414, 0x04141c0c, 0x04141c1c, 0x04141c3e,
0x04142c0c, 0x04142c3e, 0x04143e2c, 0x041c040c, 0x041c043e, 0x041c0c04, 0x041c0c14, 0x041c142c,
0x041c3e04, 0x04240c1c, 0x04241c3e, 0x04242424, 0x04242c3e, 0x04243e1c, 0x04243e2c, 0x042c040c,
0x042c043e, 0x042c1c14, 0x042c2c14, 0x04341c2c, 0x04343424, 0x043e0c04, 0x043e0c24, 0x043e0c34,
0x043e241c, 0x043e340c, 0x0c04040c, 0x0c04041c, 0x0c040c04, 0x0c040c14, 0x0c04140c, 0x0c04141c,
0x0c041c04, 0x0c041c14, 0x0c041c24, 0x0c04243e, 0x0c042c04, 0x0c0c0404, 0x0c0c0414, 0x0c0c0c0c,
0x0c0c1404, 0x0c0c1414, 0x0c14040c, 0x0c14041c, 0x0c140c04, 0x0c140c14, 0x0c14140c, 0x0c141c04,
0x0c143e14, 0x0c1c0404, 0x0c1c0414, 0x0c1c1404, 0x0c1c1c0c, 0x0c1c2434, 0x0c1c3434, 0x0c24040c,
0x0c24042c, 0x0c242c04, 0x0c2c1404, 0x0c2c1424, 0x0c2c2434, 0x0c2c3e0c, 0x0c34042c, 0x0c3e1414,
0x0c3e2404, 0x14040404, 0x14040414, 0x14040c0c, 0x14040c1c, 0x14041404, 0x14041414, 0x14041434,
0x14041c0c, 0x14042414, 0x140c040c, 0x140c041c, 0x140c042c, 0x140c0c04, 0x140c0c14, 0x140c140c,
0x140c1c04, 0x140c341c, 0x140c343e, 0x140c3e04, 0x14140404, 0x14140414, 0x14140c0c, 0x14140c3e,
0x14141404, 0x14141414, 0x14141c3e, 0x14142404, 0x14142c2c, 0x141c040c, 0x141c0c04, 0x141c0c24,
0x141c3e04, 0x141c3e24, 0x14241c2c, 0x14242c1c, 0x142c041c, 0x142c143e, 0x142c240c, 0x142c3e24,
0x143e040c, 0x143e041c, 0x143e0c34, 0x143e242c, 0x1c04040c, 0x1c040c04, 0x1c040c14, 0x1c04140c,
0x1c04141c, 0x1c042c04, 0x1c04342c, 0x1c043e14, 0x1c0c0404, 0x1c0c0414, 0x1c0c1404, 0x1c0c1c0c,
0x1c0c2424, 0x1c0c2434, 0x1c14040c, 0x1c14041c, 0x1c140c04, 0x1c14142c, 0x1c142c14, 0x1c143e14,
0x1c1c0c0c, 0x1c1c1c1c, 0x1c241c04, 0x1c24243e, 0x1c243e14, 0x1c2c0404, 0x1c2c0434, 0x1c2c1414,
0x1c2c2c2c, 0x1c340c24, 0x1c341c34, 0x1c34341c, 0x1c3e1c1c, 0x1c3e3404, 0x24040424, 0x24040c3e,
0x24041c2c, 0x24041c3e, 0x24042c1c, 0x24042c3e, 0x240c3e24, 0x24141404, 0x24141c3e, 0x24142404,
0x24143404, 0x24143434, 0x241c043e, 0x241c242c, 0x24240424, 0x24242c0c, 0x24243424, 0x242c142c,
0x242c241c, 0x242c3e04, 0x243e042c, 0x243e0c04, 0x243e0c14, 0x243e1c04, 0x2c040c14, 0x2c04240c,
0x2c043e04, 0x2c0c0404, 0x2c0c0434, 0x2c0c1434, 0x2c0c2c2c, 0x2c140c24, 0x2c141c14, 0x2c143e14,
0x2c1c0414, 0x2c1c2c1c, 0x2c240c04, 0x2c24141c, 0x2c24143e, 0x2c243e14, 0x2c2c0414, 0x2c2c1c0c,
0x2c342c04, 0x2c3e1424, 0x2c3e2414, 0x34041424, 0x34042424, 0x34042434, 0x34043424, 0x340c140c,
0x340c340c, 0x34140c3e, 0x34143424, 0x341c1c04, 0x341c1c34, 0x34242424, 0x342c042c, 0x342c2c14,
0x34341c1c, 0x343e041c, 0x343e140c, 0x3e04041c, 0x3e04042c, 0x3e04043e, 0x3e040c04, 0x3e041c14,
0x3e042c14, 0x3e0c1434, 0x3e0c2404, 0x3e140c14, 0x3e14242c, 0x3e142c14, 0x3e1c0404, 0x3e1c0c2c,
0x3e1c1c1c, 0x3e1c3404, 0x3e24140c, 0x3e24240c, 0x3e2c0404, 0x3e2c0414, 0x3e2c1424, 0x3e341c04,
};
shared uint32_t iq3xxs_grid[256];
void init_iq_shmem(uvec3 wgsize)
{
// copy the table into shared memory and sync
for (uint i = gl_LocalInvocationIndex.x; i < iq3xxs_grid.length(); i += wgsize.x) {
iq3xxs_grid[i] = iq3xxs_grid_const[i];
}
barrier();
}
#define QUANT_K QUANT_K_IQ3_XXS
#define QUANT_R QUANT_R_IQ3_XXS
#define A_TYPE block_iq3_xxs
#define A_TYPE_PACKED16 block_iq3_xxs_packed16
#endif
#define QUANT_K_IQ3_S 256
#define QUANT_R_IQ3_S 1
struct block_iq3_s
{
float16_t d;
uint8_t qs[QUANT_K_IQ3_S/4];
uint8_t qh[QUANT_K_IQ3_S/32];
uint8_t signs[QUANT_K_IQ3_S/8];
uint8_t scales[QUANT_K_IQ3_S/64];
};
struct block_iq3_s_packed16
{
float16_t d;
uint16_t qs[QUANT_K_IQ3_S/4/2];
uint16_t qh[QUANT_K_IQ3_S/32/2];
uint16_t signs[QUANT_K_IQ3_S/8/2];
uint16_t scales[QUANT_K_IQ3_S/64/2];
};
#if defined(DATA_A_IQ3_S)
const uint32_t iq3s_grid_const[512] = {
0x01010101, 0x01010103, 0x01010105, 0x0101010b, 0x0101010f, 0x01010301, 0x01010303, 0x01010305,
0x01010309, 0x0101030d, 0x01010501, 0x01010503, 0x0101050b, 0x01010707, 0x01010901, 0x01010905,
0x0101090b, 0x0101090f, 0x01010b03, 0x01010b07, 0x01010d01, 0x01010d05, 0x01010f03, 0x01010f09,
0x01010f0f, 0x01030101, 0x01030103, 0x01030105, 0x01030109, 0x01030301, 0x01030303, 0x0103030b,
0x01030501, 0x01030507, 0x0103050f, 0x01030703, 0x0103070b, 0x01030909, 0x01030d03, 0x01030d0b,
0x01030f05, 0x01050101, 0x01050103, 0x0105010b, 0x0105010f, 0x01050301, 0x01050307, 0x0105030d,
0x01050503, 0x0105050b, 0x01050701, 0x01050709, 0x01050905, 0x0105090b, 0x0105090f, 0x01050b03,
0x01050b07, 0x01050f01, 0x01050f07, 0x01070107, 0x01070303, 0x0107030b, 0x01070501, 0x01070505,
0x01070703, 0x01070707, 0x0107070d, 0x01070909, 0x01070b01, 0x01070b05, 0x01070d0f, 0x01070f03,
0x01070f0b, 0x01090101, 0x01090307, 0x0109030f, 0x01090503, 0x01090509, 0x01090705, 0x01090901,
0x01090907, 0x01090b03, 0x01090f01, 0x010b0105, 0x010b0109, 0x010b0501, 0x010b0505, 0x010b050d,
0x010b0707, 0x010b0903, 0x010b090b, 0x010b090f, 0x010b0d0d, 0x010b0f07, 0x010d010d, 0x010d0303,
0x010d0307, 0x010d0703, 0x010d0b05, 0x010d0f03, 0x010f0101, 0x010f0105, 0x010f0109, 0x010f0501,
0x010f0505, 0x010f050d, 0x010f0707, 0x010f0b01, 0x010f0b09, 0x03010101, 0x03010103, 0x03010105,
0x03010109, 0x03010301, 0x03010303, 0x03010307, 0x0301030b, 0x0301030f, 0x03010501, 0x03010505,
0x03010703, 0x03010709, 0x0301070d, 0x03010b09, 0x03010b0d, 0x03010d03, 0x03010f05, 0x03030101,
0x03030103, 0x03030107, 0x0303010d, 0x03030301, 0x03030309, 0x03030503, 0x03030701, 0x03030707,
0x03030903, 0x03030b01, 0x03030b05, 0x03030f01, 0x03030f0d, 0x03050101, 0x03050305, 0x0305030b,
0x0305030f, 0x03050501, 0x03050509, 0x03050705, 0x03050901, 0x03050907, 0x03050b0b, 0x03050d01,
0x03050f05, 0x03070103, 0x03070109, 0x0307010f, 0x03070301, 0x03070307, 0x03070503, 0x0307050f,
0x03070701, 0x03070709, 0x03070903, 0x03070d05, 0x03070f01, 0x03090107, 0x0309010b, 0x03090305,
0x03090309, 0x03090703, 0x03090707, 0x03090905, 0x0309090d, 0x03090b01, 0x03090b09, 0x030b0103,
0x030b0301, 0x030b0307, 0x030b0503, 0x030b0701, 0x030b0705, 0x030b0b03, 0x030d0501, 0x030d0509,
0x030d050f, 0x030d0909, 0x030d090d, 0x030f0103, 0x030f0107, 0x030f0301, 0x030f0305, 0x030f0503,
0x030f070b, 0x030f0903, 0x030f0d05, 0x030f0f01, 0x05010101, 0x05010103, 0x05010107, 0x0501010b,
0x0501010f, 0x05010301, 0x05010305, 0x05010309, 0x0501030d, 0x05010503, 0x05010507, 0x0501050f,
0x05010701, 0x05010705, 0x05010903, 0x05010907, 0x0501090b, 0x05010b01, 0x05010b05, 0x05010d0f,
0x05010f01, 0x05010f07, 0x05010f0b, 0x05030101, 0x05030105, 0x05030301, 0x05030307, 0x0503030f,
0x05030505, 0x0503050b, 0x05030703, 0x05030709, 0x05030905, 0x05030b03, 0x05050103, 0x05050109,
0x0505010f, 0x05050503, 0x05050507, 0x05050701, 0x0505070f, 0x05050903, 0x05050b07, 0x05050b0f,
0x05050f03, 0x05050f09, 0x05070101, 0x05070105, 0x0507010b, 0x05070303, 0x05070505, 0x05070509,
0x05070703, 0x05070707, 0x05070905, 0x05070b01, 0x05070d0d, 0x05090103, 0x0509010f, 0x05090501,
0x05090507, 0x05090705, 0x0509070b, 0x05090903, 0x05090f05, 0x05090f0b, 0x050b0109, 0x050b0303,
0x050b0505, 0x050b070f, 0x050b0901, 0x050b0b07, 0x050b0f01, 0x050d0101, 0x050d0105, 0x050d010f,
0x050d0503, 0x050d0b0b, 0x050d0d03, 0x050f010b, 0x050f0303, 0x050f050d, 0x050f0701, 0x050f0907,
0x050f0b01, 0x07010105, 0x07010303, 0x07010307, 0x0701030b, 0x0701030f, 0x07010505, 0x07010703,
0x07010707, 0x0701070b, 0x07010905, 0x07010909, 0x0701090f, 0x07010b03, 0x07010d07, 0x07010f03,
0x07030103, 0x07030107, 0x0703010b, 0x07030309, 0x07030503, 0x07030507, 0x07030901, 0x07030d01,
0x07030f05, 0x07030f0d, 0x07050101, 0x07050305, 0x07050501, 0x07050705, 0x07050709, 0x07050b01,
0x07070103, 0x07070301, 0x07070309, 0x07070503, 0x07070507, 0x0707050f, 0x07070701, 0x07070903,
0x07070907, 0x0707090f, 0x07070b0b, 0x07070f07, 0x07090107, 0x07090303, 0x0709030d, 0x07090505,
0x07090703, 0x07090b05, 0x07090d01, 0x07090d09, 0x070b0103, 0x070b0301, 0x070b0305, 0x070b050b,
0x070b0705, 0x070b0909, 0x070b0b0d, 0x070b0f07, 0x070d030d, 0x070d0903, 0x070f0103, 0x070f0107,
0x070f0501, 0x070f0505, 0x070f070b, 0x09010101, 0x09010109, 0x09010305, 0x09010501, 0x09010509,
0x0901050f, 0x09010705, 0x09010903, 0x09010b01, 0x09010f01, 0x09030105, 0x0903010f, 0x09030303,
0x09030307, 0x09030505, 0x09030701, 0x0903070b, 0x09030907, 0x09030b03, 0x09030b0b, 0x09050103,
0x09050107, 0x09050301, 0x0905030b, 0x09050503, 0x09050707, 0x09050901, 0x09050b0f, 0x09050d05,
0x09050f01, 0x09070109, 0x09070303, 0x09070307, 0x09070501, 0x09070505, 0x09070703, 0x0907070b,
0x09090101, 0x09090105, 0x09090509, 0x0909070f, 0x09090901, 0x09090f03, 0x090b010b, 0x090b010f,
0x090b0503, 0x090b0d05, 0x090d0307, 0x090d0709, 0x090d0d01, 0x090f0301, 0x090f030b, 0x090f0701,
0x090f0907, 0x090f0b03, 0x0b010105, 0x0b010301, 0x0b010309, 0x0b010505, 0x0b010901, 0x0b010909,
0x0b01090f, 0x0b010b05, 0x0b010d0d, 0x0b010f09, 0x0b030103, 0x0b030107, 0x0b03010b, 0x0b030305,
0x0b030503, 0x0b030705, 0x0b030f05, 0x0b050101, 0x0b050303, 0x0b050507, 0x0b050701, 0x0b05070d,
0x0b050b07, 0x0b070105, 0x0b07010f, 0x0b070301, 0x0b07050f, 0x0b070909, 0x0b070b03, 0x0b070d0b,
0x0b070f07, 0x0b090103, 0x0b090109, 0x0b090501, 0x0b090705, 0x0b09090d, 0x0b0b0305, 0x0b0b050d,
0x0b0b0b03, 0x0b0b0b07, 0x0b0d0905, 0x0b0f0105, 0x0b0f0109, 0x0b0f0505, 0x0d010303, 0x0d010307,
0x0d01030b, 0x0d010703, 0x0d010707, 0x0d010d01, 0x0d030101, 0x0d030501, 0x0d03050f, 0x0d030d09,
0x0d050305, 0x0d050709, 0x0d050905, 0x0d050b0b, 0x0d050d05, 0x0d050f01, 0x0d070101, 0x0d070309,
0x0d070503, 0x0d070901, 0x0d09050b, 0x0d090907, 0x0d090d05, 0x0d0b0101, 0x0d0b0107, 0x0d0b0709,
0x0d0b0d01, 0x0d0d010b, 0x0d0d0901, 0x0d0f0303, 0x0d0f0307, 0x0f010101, 0x0f010109, 0x0f01010f,
0x0f010501, 0x0f010505, 0x0f01070d, 0x0f010901, 0x0f010b09, 0x0f010d05, 0x0f030105, 0x0f030303,
0x0f030509, 0x0f030907, 0x0f03090b, 0x0f050103, 0x0f050109, 0x0f050301, 0x0f05030d, 0x0f050503,
0x0f050701, 0x0f050b03, 0x0f070105, 0x0f070705, 0x0f07070b, 0x0f070b07, 0x0f090103, 0x0f09010b,
0x0f090307, 0x0f090501, 0x0f090b01, 0x0f0b0505, 0x0f0b0905, 0x0f0d0105, 0x0f0d0703, 0x0f0f0101,
};
shared uint32_t iq3s_grid[512];
void init_iq_shmem(uvec3 wgsize)
{
// copy the table into shared memory and sync
for (uint i = gl_LocalInvocationIndex.x; i < iq3s_grid.length(); i += wgsize.x) {
iq3s_grid[i] = iq3s_grid_const[i];
}
barrier();
}
#define QUANT_K QUANT_K_IQ3_S
#define QUANT_R QUANT_R_IQ3_S
#define A_TYPE block_iq3_s
#define A_TYPE_PACKED16 block_iq3_s_packed16
#endif
#define QUANT_K_IQ4_NL 32
#define QUANT_R_IQ4_NL 2
@ -318,11 +1050,11 @@ const int8_t kvalues_iq4nl_const[16] = {
shared FLOAT_TYPE kvalues_iq4nl[16];
void init_iq4nl_shmem()
void init_iq_shmem(uvec3 wgsize)
{
// copy the table into shared memory and sync
if (gl_LocalInvocationIndex.x < 16) {
kvalues_iq4nl[gl_LocalInvocationIndex.x] = FLOAT_TYPE(kvalues_iq4nl_const[gl_LocalInvocationIndex.x]);
for (uint i = gl_LocalInvocationIndex.x; i < kvalues_iq4nl.length(); i += wgsize.x) {
kvalues_iq4nl[i] = FLOAT_TYPE(kvalues_iq4nl_const[i]);
}
barrier();
}

5
ggml/src/ggml-vulkan/vulkan-shaders/vulkan-shaders-gen.cpp
View file

@ -55,6 +55,11 @@ const std::vector<std::string> type_names = {
"q4_k",
"q5_k",
"q6_k",
"iq2_xxs",
"iq2_xs",
"iq2_s",
"iq3_xxs",
"iq3_s",
"iq4_nl"
};

4
ggml/src/ggml.c
View file

@ -128,6 +128,10 @@ static void ggml_print_backtrace_symbols(void) {
#endif
static void ggml_print_backtrace(void) {
const char * GGML_NO_BACKTRACE = getenv("GGML_NO_BACKTRACE");
if (GGML_NO_BACKTRACE) {
return;
}
char attach[32];
snprintf(attach, sizeof(attach), "attach %d", getpid());
int pid = fork();

12
include/llama.h
View file

@ -1199,6 +1199,18 @@ extern "C" {
const char * grammar_str,
const char * grammar_root);
/// @details Lazy grammar sampler, introduced in https://github.com/ggerganov/llama.cpp/pull/9639
/// @param trigger_words A list of words that will trigger the grammar sampler. This may be updated to a loose regex syntax (w/ ^) in a near future.
/// @param trigger_tokens A list of tokens that will trigger the grammar sampler.
LLAMA_API struct llama_sampler * llama_sampler_init_grammar_lazy(
const struct llama_vocab * vocab,
const char * grammar_str,
const char * grammar_root,
const char ** trigger_words,
size_t num_trigger_words,
const llama_token * trigger_tokens,
size_t num_trigger_tokens);
/// NOTE: Avoid using on the full vocabulary as searching for repeated tokens can become slow. For example, apply top-k or top-p sampling first.
LLAMA_API struct llama_sampler * llama_sampler_init_penalties(
int32_t penalty_last_n, // last n tokens to penalize (0 = disable penalty, -1 = context size)

202
models/templates/CohereForAI-c4ai-command-r-plus-tool_use.jinja Normal file
View file

@ -0,0 +1,202 @@
{%- macro json_to_python_type(json_spec) %}
{%- set basic_type_map = {
"string": "str",
"number": "float",
"integer": "int",
"boolean": "bool"
} %}
{%- if basic_type_map[json_spec.type] is defined %}
{{- basic_type_map[json_spec.type] }}
{%- elif json_spec.type == "array" %}
{{- "List[" + json_to_python_type(json_spec.items) + "]"}}
{%- elif json_spec.type == "object" %}
{{- "Dict[str, " + json_to_python_type(json_spec.additionalProperties) + ']'}}
{%- elif json_spec.type is iterable %}
{{- "Union[" }}
{%- for t in json_spec.type %}
{{- json_to_python_type({"type": t}) }}
{%- if not loop.last %}
{{- "," }}
{%- endif %}
{%- endfor %}
{{- "]" }}
{%- else %}
{{- "Any" }}
{%- endif %}
{%- endmacro %}
{%- macro old_tool_parser(tools) %}
{%- for tool in tools %}
{%- if loop.index0 != 0 %}
{{- '\n\n' }}
{%- endif %}
{{- '```python\ndef ' + tool.name + '(' }}
{%- for param_name, param_fields in tool.parameter_definitions|items %}
{%- if loop.index0 != 0 %}
{{- ', '}}
{%- endif %}
{{- param_name + ': ' }}
{%- if not param_fields.required %}
{{- 'Optional[' + param_fields.type + '] = None'}}
{%- else %}
{{- param_fields.type }}
{%- endif %}
{%- endfor %}
{{- ') -> List[Dict]:\n """'}}
{{- tool.description }}
{%- if tool.parameter_definitions|length != 0 %}
{{- '\n\n Args:\n '}}
{%- for param_name, param_fields in tool.parameter_definitions|items %}
{%- if loop.index0 != 0 %}
{{- '\n ' }}
{%- endif %}
{{- param_name + ' ('}}
{%- if not param_fields.required %}
{{- 'Optional[' + param_fields.type + ']'}}
{%- else %}
{{- param_fields.type }}
{%- endif %}
{{- '): ' + param_fields.description }}
{%- endfor %}
{%- endif %}
{{- '\n """\n pass\n```' }}
{%- endfor %}
{%- endmacro %}
{%- macro new_tool_parser(tools) %}
{%- for tool in tools %}
{%- if loop.index0 != 0 %}
{{- '\n\n'}}
{%- endif %}
{%- if tool.function is defined %}
{%- set tool = tool.function %}
{%- endif %}
{{-'```python
def ' + tool.name + '('}}
{%- for param_name, param_fields in tool.parameters.properties|items %}
{%- if loop.index0 != 0 %}
{{- ', '}}
{%- endif %}
{{-param_name + ": "}}
{%- if not param_name in tool.parameters.required %}
{{-'Optional[' + json_to_python_type(param_fields) + '] = None'}}
{%- else %}
{{- json_to_python_type(param_fields) }}
{%- endif %}
{%- endfor %}
{{- ') -> List[Dict]:
"""'}}
{{- tool.description }}
{%- if tool.parameters.properties|length != 0 %}
{{- '\n\n Args:\n '}}
{%- for param_name, param_fields in tool.parameters.properties|items %}
{%- if loop.index0 != 0 %}
{{- '\n ' }}
{%- endif %}
{{- param_name + ' ('}}
{%- if not param_name in tool.parameters.required %}
{{-'Optional[' + json_to_python_type(param_fields) + ']'}}
{%- else %}
{{- json_to_python_type(param_fields) }}
{%- endif %}
{{- '): ' + param_fields.description }}
{%- endfor %}
{%- endif %}
{{- '\n """\n pass\n```' }}
{%- endfor %}
{%- endmacro %}
{{- bos_token }}
{%- if messages[0]['role'] == 'system' %}
{%- set loop_messages = messages[1:] %}
{%- set system_message = messages[0]['content'] %}
{%- else %}
{%- set loop_messages = messages %}
{%- set system_message = '## Task and Context\nYou help people answer their questions and other requests interactively. You will be asked a very wide array of requests on all kinds of topics. You will be equipped with a wide range of search engines or similar tools to help you, which you use to research your answer. You should focus on serving the user\'s needs as best you can, which will be wide-ranging.\n\n## Style Guide\nUnless the user asks for a different style of answer, you should answer in full sentences, using proper grammar and spelling.' %}
{%- endif %}
{{- '<|START_OF_TURN_TOKEN|><|SYSTEM_TOKEN|>' }}
{{- '# Safety Preamble' }}
{{- '
The instructions in this section override those in the task description and style guide sections. Don\'t answer questions that are harmful or immoral.' }}
{{- '
# System Preamble' }}
{{- '
## Basic Rules' }}
{{- '
You are a powerful conversational AI trained by Cohere to help people. You are augmented by a number of tools, and your job is to use and consume the output of these tools to best help the user. You will see a conversation history between yourself and a user, ending with an utterance from the user. You will then see a specific instruction instructing you what kind of response to generate. When you answer the user\'s requests, you cite your sources in your answers, according to those instructions.' }}
{{- '
# User Preamble' }}
{{- '
' + system_message }}
{{-'
## Available Tools
Here is a list of tools that you have available to you:
'}}
{%- set ns = namespace(new_tools=true) %}
{%- for tool in tools %}
{%- if tool.parameter_definitions is defined %}
{%- set ns.new_tools = false %}
{%- endif %}
{%- endfor %}
{%- if ns.new_tools %}
{{- new_tool_parser(tools) }}
{%- else %}
{{- old_tool_parser(tools) }}
{%- endif %}
{{- '<|END_OF_TURN_TOKEN|>'}}
{%- for message in loop_messages %}
{%- set content = message['content'] %}
{%- if message.role == 'user' %}
{{- '<|START_OF_TURN_TOKEN|><|USER_TOKEN|>' + content|trim + '<|END_OF_TURN_TOKEN|>' }}
{%- elif message.role == 'system' %}
{{- '<|START_OF_TURN_TOKEN|><|SYSTEM_TOKEN|>' + content|trim + '<|END_OF_TURN_TOKEN|>' }}
{%- elif message.role == 'assistant' and message.tool_calls is defined %}
{{- '<|START_OF_TURN_TOKEN|><|CHATBOT_TOKEN|>' }}
{%- if message.content is defined %}
{{- message.content|trim }}
{%- endif %}
{{- '\nAction:\n```json\n[\n' }}
{%- for tool_call in message.tool_calls %}
{%- if tool_call.function is defined %}
{%- set tool_call = tool_call.function %}
{%- endif %}
{{- '{\n'|indent(4, first=true) }}
{{- '"tool_name": "'|indent(8, first=true) + tool_call.name + '",\n' }}
{{- '"parameters": '|indent(8, first=true) }}
{%- if tool_call.arguments is defined and tool_call.arguments|length > 0 %}
{{- tool_call.arguments|tojson(indent=4)|indent(8) }}
{{- '\n' }}
{%- else %}
{{- '{}\n' }}
{%- endif %}
{{- '}'|indent(4, first=true) }}
{%- if not loop.last %}
{{- ',\n' }}
{%- endif %}
{%- endfor %}
{{- "\n]```\n" }}
{%- elif message.role == 'assistant' %}
{{- '<|START_OF_TURN_TOKEN|><|CHATBOT_TOKEN|>' + content|trim + '<|END_OF_TURN_TOKEN|>' }}
{%- elif message.role == 'tool' %}
{{- '<|START_OF_TURN_TOKEN|><|SYSTEM_TOKEN|><results>\n' }}
{{- message.content|trim }}
{{- '</results><|END_OF_TURN_TOKEN|>' }}
{%- endif %}
{%- endfor %}
{{-'<|START_OF_TURN_TOKEN|><|SYSTEM_TOKEN|>Write \'Action:\' followed by a json-formatted list of actions that you want to perform in order to produce a good response to the user\'s last input. You can use any of the supplied tools any number of times, but you should aim to execute the minimum number of necessary actions for the input. You should use the `directly-answer` tool if calling the other tools is unnecessary. The list of actions you want to call should be formatted as a list of json objects, for example:
```json
[
{
"tool_name": title of the tool in the specification,
"parameters": a dict of parameters to input into the tool as they are defined in the specs, or {} if it takes no parameters
}
]```<|END_OF_TURN_TOKEN|>'}}
{%- if add_generation_prompt %}
{{- '<|START_OF_TURN_TOKEN|><|CHATBOT_TOKEN|>' }}
{%- endif %}

152
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{%- macro json_to_python_type(json_spec) %}
{%- set basic_type_map = {
"string": "str",
"number": "float",
"integer": "int",
"boolean": "bool"
} %}
{%- if basic_type_map[json_spec.type] is defined %}
{{- basic_type_map[json_spec.type] }}
{%- elif json_spec.type == "array" %}
{{- "list[" + json_to_python_type(json_spec|items) + "]"}}
{%- elif json_spec.type == "object" %}
{%- if json_spec.additionalProperties is defined %}
{{- "dict[str, " + json_to_python_type(json_spec.additionalProperties) + ']'}}
{%- else %}
{{- "dict" }}
{%- endif %}
{%- elif json_spec.type is iterable %}
{{- "Union[" }}
{%- for t in json_spec.type %}
{{- json_to_python_type({"type": t}) }}
{%- if not loop.last %}
{{- "," }}
{%- endif %}
{%- endfor %}
{{- "]" }}
{%- else %}
{{- "Any" }}
{%- endif %}
{%- endmacro %}
{{- bos_token }}
{{- '<|im_start|>system
' }}
{{- "You are a function calling AI model. You are provided with function signatures within <tools></tools> XML tags. You may call one or more functions to assist with the user query. Don't make assumptions about what values to plug into functions. Here are the available tools: <tools> " }}
{%- for tool in tools %}
{%- if tool.function is defined %}
{%- set tool = tool.function %}
{%- endif %}
{{- '{"type": "function", "function": ' }}
{{- '{"name": "' + tool.name + '", ' }}
{{- '"description": "' + tool.name + '(' }}
{%- for param_name, param_fields in tool.parameters.properties|items %}
{{- param_name + ": " + json_to_python_type(param_fields) }}
{%- if not loop.last %}
{{- ", " }}
{%- endif %}
{%- endfor %}
{{- ")" }}
{%- if tool.return is defined %}
{{- " -> " + json_to_python_type(tool.return) }}
{%- endif %}
{{- " - " + tool.description + "
" }}
{%- for param_name, param_fields in tool.parameters.properties|items %}
{%- if loop.first %}
{{- " Args:
" }}
{%- endif %}
{{- " " + param_name + "(" + json_to_python_type(param_fields) + "): " + param_fields.description|trim }}
{%- endfor %}
{%- if tool.return is defined and tool.return.description is defined %}
{{- "
Returns:
" + tool.return.description }}
{%- endif %}
{{- '"' }}
{{- ', "parameters": ' }}
{%- if tool.parameters.properties | length == 0 %}
{{- "{}" }}
{%- else %}
{{- tool.parameters|tojson }}
{%- endif %}
{{- "}" }}
{%- if not loop.last %}
{{- "
" }}
{%- endif %}
{%- endfor %}
{{- " </tools>" }}
{{- 'Use the following pydantic model json schema for each tool call you will make: {"properties": {"name": {"title": "Name", "type": "string"}, "arguments": {"title": "Arguments", "type": "object"}}, "required": ["name", "arguments"], "title": "FunctionCall", "type": "object"}}
' }}
{{- "For each function call return a json object with function name and arguments within <tool_call></tool_call> XML tags as follows:
" }}
{{- "<tool_call>
" }}
{{- '{"name": <function-name>, "arguments": <args-dict>}
' }}
{{- '</tool_call><|im_end|>
' }}
{%- for message in messages %}
{%- if message.role == "user" or message.role == "system" or (message.role == "assistant" and message.tool_calls is not defined) %}
{{- '<|im_start|>' + message.role + '
' + message.content + '<|im_end|>' + '
' }}
{%- elif message.role == "assistant" %}
{{- '<|im_start|>' + message.role }}
{%- for tool_call in message.tool_calls %}
{{- '
<tool_call>
' }} {%- if tool_call.function is defined %}
{%- set tool_call = tool_call.function %}
{%- endif %}
{{- '{' }}
{{- '"name": "' }}
{{- tool_call.name }}
{{- '"' }}
{{- ', '}}
{%- if tool_call.arguments is defined %}
{{- '"arguments": ' }}
{%- if tool_call.arguments is string %}
{{- tool_call.arguments }}
{%- else %}
{{- tool_call.arguments|tojson }}
{%- endif %}
{%- endif %}
{{- '}' }}
{{- '
</tool_call>' }}
{%- endfor %}
{{- '<|im_end|>
' }}
{%- elif message.role == "tool" %}
{%- if loop.previtem and loop.previtem.role != "tool" %}
{{- '<|im_start|>tool
' }}
{%- endif %}
{{- '<tool_response>
' }}
{{- message.content }}
{%- if not loop.last %}
{{- '
</tool_response>
' }}
{%- else %}
{{- '
</tool_response>' }}
{%- endif %}
{%- if not loop.last and loop.nextitem.role != "tool" %}
{{- '<|im_end|>' }}
{%- elif loop.last %}
{{- '<|im_end|>' }}
{%- endif %}
{%- endif %}
{%- endfor %}
{%- if add_generation_prompt %}
{{- '<|im_start|>assistant
' }}
{%- endif %}

152
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{%- macro json_to_python_type(json_spec) %}
{%- set basic_type_map = {
"string": "str",
"number": "float",
"integer": "int",
"boolean": "bool"
} %}
{%- if basic_type_map[json_spec.type] is defined %}
{{- basic_type_map[json_spec.type] }}
{%- elif json_spec.type == "array" %}
{{- "list[" + json_to_python_type(json_spec|items) + "]"}}
{%- elif json_spec.type == "object" %}
{%- if json_spec.additionalProperties is defined %}
{{- "dict[str, " + json_to_python_type(json_spec.additionalProperties) + ']'}}
{%- else %}
{{- "dict" }}
{%- endif %}
{%- elif json_spec.type is iterable %}
{{- "Union[" }}
{%- for t in json_spec.type %}
{{- json_to_python_type({"type": t}) }}
{%- if not loop.last %}
{{- "," }}
{%- endif %}
{%- endfor %}
{{- "]" }}
{%- else %}
{{- "Any" }}
{%- endif %}
{%- endmacro %}
{{- bos_token }}
{{- '<|im_start|>system
' }}
{{- "You are a function calling AI model. You are provided with function signatures within <tools></tools> XML tags. You may call one or more functions to assist with the user query. Don't make assumptions about what values to plug into functions. Here are the available tools: <tools> " }}
{%- for tool in tools %}
{%- if tool.function is defined %}
{%- set tool = tool.function %}
{%- endif %}
{{- '{"type": "function", "function": ' }}
{{- '{"name": "' + tool.name + '", ' }}
{{- '"description": "' + tool.name + '(' }}
{%- for param_name, param_fields in tool.parameters.properties|items %}
{{- param_name + ": " + json_to_python_type(param_fields) }}
{%- if not loop.last %}
{{- ", " }}
{%- endif %}
{%- endfor %}
{{- ")" }}
{%- if tool.return is defined %}
{{- " -> " + json_to_python_type(tool.return) }}
{%- endif %}
{{- " - " + tool.description + "
" }}
{%- for param_name, param_fields in tool.parameters.properties|items %}
{%- if loop.first %}
{{- " Args:
" }}
{%- endif %}
{{- " " + param_name + "(" + json_to_python_type(param_fields) + "): " + param_fields.description|trim }}
{%- endfor %}
{%- if tool.return is defined and tool.return.description is defined %}
{{- "
Returns:
" + tool.return.description }}
{%- endif %}
{{- '"' }}
{{- ', "parameters": ' }}
{%- if tool.parameters.properties | length == 0 %}
{{- "{}" }}
{%- else %}
{{- tool.parameters|tojson }}
{%- endif %}
{{- "}" }}
{%- if not loop.last %}
{{- "
" }}
{%- endif %}
{%- endfor %}
{{- " </tools>" }}
{{- 'Use the following pydantic model json schema for each tool call you will make: {"properties": {"name": {"title": "Name", "type": "string"}, "arguments": {"title": "Arguments", "type": "object"}}, "required": ["name", "arguments"], "title": "FunctionCall", "type": "object"}}
' }}
{{- "For each function call return a json object with function name and arguments within <tool_call></tool_call> XML tags as follows:
" }}
{{- "<tool_call>
" }}
{{- '{"name": <function-name>, "arguments": <args-dict>}
' }}
{{- '</tool_call><|im_end|>
' }}
{%- for message in messages %}
{%- if message.role == "user" or message.role == "system" or (message.role == "assistant" and message.tool_calls is not defined) %}
{{- '<|im_start|>' + message.role + '
' + message.content + '<|im_end|>' + '
' }}
{%- elif message.role == "assistant" %}
{{- '<|im_start|>' + message.role }}
{%- for tool_call in message.tool_calls %}
{{- '
<tool_call>
' }} {%- if tool_call.function is defined %}
{%- set tool_call = tool_call.function %}
{%- endif %}
{{- '{' }}
{{- '"name": "' }}
{{- tool_call.name }}
{{- '"' }}
{{- ', '}}
{%- if tool_call.arguments is defined %}
{{- '"arguments": ' }}
{%- if tool_call.arguments is string %}
{{- tool_call.arguments }}
{%- else %}
{{- tool_call.arguments|tojson }}
{%- endif %}
{%- endif %}
{{- '}' }}
{{- '
</tool_call>' }}
{%- endfor %}
{{- '<|im_end|>
' }}
{%- elif message.role == "tool" %}
{%- if loop.previtem and loop.previtem.role != "tool" %}
{{- '<|im_start|>tool
' }}
{%- endif %}
{{- '<tool_response>
' }}
{{- message.content }}
{%- if not loop.last %}
{{- '
</tool_response>
' }}
{%- else %}
{{- '
</tool_response>' }}
{%- endif %}
{%- if not loop.last and loop.nextitem.role != "tool" %}
{{- '<|im_end|>' }}
{%- elif loop.last %}
{{- '<|im_end|>' }}
{%- endif %}
{%- endif %}
{%- endfor %}
{%- if add_generation_prompt %}
{{- '<|im_start|>assistant
' }}
{%- endif %}

54
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{%- if tools %}
{{- '<|im_start|>system\n' }}
{%- if messages[0]['role'] == 'system' %}
{{- messages[0]['content'] }}
{%- else %}
{{- 'You are Qwen, created by Alibaba Cloud. You are a helpful assistant.' }}
{%- endif %}
{{- "\n\n# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within <tools></tools> XML tags:\n<tools>" }}
{%- for tool in tools %}
{{- "\n" }}
{{- tool | tojson }}
{%- endfor %}
{{- "\n</tools>\n\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{\"name\": <function-name>, \"arguments\": <args-json-object>}\n</tool_call><|im_end|>\n" }}
{%- else %}
{%- if messages[0]['role'] == 'system' %}
{{- '<|im_start|>system\n' + messages[0]['content'] + '<|im_end|>\n' }}
{%- else %}
{{- '<|im_start|>system\nYou are Qwen, created by Alibaba Cloud. You are a helpful assistant.<|im_end|>\n' }}
{%- endif %}
{%- endif %}
{%- for message in messages %}
{%- if (message.role == "user") or (message.role == "system" and not loop.first) or (message.role == "assistant" and not message.tool_calls) %}
{{- '<|im_start|>' + message.role + '\n' + message.content + '<|im_end|>' + '\n' }}
{%- elif message.role == "assistant" %}
{{- '<|im_start|>' + message.role }}
{%- if message.content %}
{{- '\n' + message.content }}
{%- endif %}
{%- for tool_call in message.tool_calls %}
{%- if tool_call.function is defined %}
{%- set tool_call = tool_call.function %}
{%- endif %}
{{- '\n<tool_call>\n{"name": "' }}
{{- tool_call.name }}
{{- '", "arguments": ' }}
{{- tool_call.arguments | tojson }}
{{- '}\n</tool_call>' }}
{%- endfor %}
{{- '<|im_end|>\n' }}
{%- elif message.role == "tool" %}
{%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != "tool") %}
{{- '<|im_start|>user' }}
{%- endif %}
{{- '\n<tool_response>\n' }}
{{- message.content }}
{{- '\n</tool_response>' }}
{%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
{{- '<|im_end|>\n' }}
{%- endif %}
{%- endif %}
{%- endfor %}
{%- if add_generation_prompt %}
{{- '<|im_start|>assistant\n' }}
{%- endif %}

1
models/templates/deepseek-ai-DeepSeek-R1-Distill-Llama-8B.jinja Normal file
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{% if not add_generation_prompt is defined %}{% set add_generation_prompt = false %}{% endif %}{% set ns = namespace(is_first=false, is_tool=false, is_output_first=true, system_prompt='') %}{%- for message in messages %}{%- if message['role'] == 'system' %}{% set ns.system_prompt = message['content'] %}{%- endif %}{%- endfor %}{{bos_token}}{{ns.system_prompt}}{%- for message in messages %}{%- if message['role'] == 'user' %}{%- set ns.is_tool = false -%}{{'<｜User｜>' + message['content']}}{%- endif %}{%- if message['role'] == 'assistant' and message['content'] is none %}{%- set ns.is_tool = false -%}{%- for tool in message['tool_calls']%}{%- if not ns.is_first %}{{'<｜Assistant｜><｜tool▁calls▁begin｜><｜tool▁call▁begin｜>' + tool['type'] + '<｜tool▁sep｜>' + tool['function']['name'] + '\n' + '```json' + '\n' + tool['function']['arguments'] + '\n' + '```' + '<｜tool▁call▁end｜>'}}{%- set ns.is_first = true -%}{%- else %}{{'\n' + '<｜tool▁call▁begin｜>' + tool['type'] + '<｜tool▁sep｜>' + tool['function']['name'] + '\n' + '```json' + '\n' + tool['function']['arguments'] + '\n' + '```' + '<｜tool▁call▁end｜>'}}{{'<｜tool▁calls▁end｜><｜end▁of▁sentence｜>'}}{%- endif %}{%- endfor %}{%- endif %}{%- if message['role'] == 'assistant' and message['content'] is not none %}{%- if ns.is_tool %}{{'<｜tool▁outputs▁end｜>' + message['content'] + '<｜end▁of▁sentence｜>'}}{%- set ns.is_tool = false -%}{%- else %}{% set content = message['content'] %}{% if '</think>' in content %}{% set content = content.split('</think>')[-1] %}{% endif %}{{'<｜Assistant｜>' + content + '<｜end▁of▁sentence｜>'}}{%- endif %}{%- endif %}{%- if message['role'] == 'tool' %}{%- set ns.is_tool = true -%}{%- if ns.is_output_first %}{{'<｜tool▁outputs▁begin｜><｜tool▁output▁begin｜>' + message['content'] + '<｜tool▁output▁end｜>'}}{%- set ns.is_output_first = false %}{%- else %}{{'\n<｜tool▁output▁begin｜>' + message['content'] + '<｜tool▁output▁end｜>'}}{%- endif %}{%- endif %}{%- endfor -%}{% if ns.is_tool %}{{'<｜tool▁outputs▁end｜>'}}{% endif %}{% if add_generation_prompt and not ns.is_tool %}{{'<｜Assistant｜>'}}{% endif %}

56
models/templates/deepseek-ai-DeepSeek-R1-Distill-Qwen-32B.jinja Normal file
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{% if not add_generation_prompt is defined %}
{% set add_generation_prompt = false %}
{% endif %}
{% set ns = namespace(is_first=false, is_tool=false, is_output_first=true, system_prompt='') %}
{%- for message in messages %}
{%- if message['role'] == 'system' %}
{% set ns.system_prompt = message['content'] %}
{%- endif %}
{%- endfor %}
{{bos_token}}
{{ns.system_prompt}}
{%- for message in messages %}
{%- if message['role'] == 'user' %}
{%- set ns.is_tool = false -%}
{{'<｜User｜>' + message['content']}}
{%- endif %}
{%- if message['role'] == 'assistant' and message['content'] is none %}
{%- set ns.is_tool = false -%}
{%- for tool in message['tool_calls']%}
{%- if not ns.is_first %}
{{'<｜Assistant｜><｜tool▁calls▁begin｜><｜tool▁call▁begin｜>' + tool['type'] + '<｜tool▁sep｜>' + tool['function']['name'] + '\n' + '```json' + '\n' + tool['function']['arguments'] + '\n' + '```' + '<｜tool▁call▁end｜>'}}
{%- set ns.is_first = true -%}
{%- else %}
{{'\n' + '<｜tool▁call▁begin｜>' + tool['type'] + '<｜tool▁sep｜>' + tool['function']['name'] + '\n' + '```json' + '\n' + tool['function']['arguments'] + '\n' + '```' + '<｜tool▁call▁end｜>'}}
{{'<｜tool▁calls▁end｜><｜end▁of▁sentence｜>'}}
{%- endif %}
{%- endfor %}
{%- endif %}
{%- if message['role'] == 'assistant' and message['content'] is not none %}
{%- if ns.is_tool %}
{{'<｜tool▁outputs▁end｜>' + message['content'] + '<｜end▁of▁sentence｜>'}}
{%- set ns.is_tool = false -%}
{%- else %}
{% set content = message['content'] %}
{% if '</think>' in content %}
{% set content = content.split('</think>')[-1] %}
{% endif %}
{{'<｜Assistant｜>' + content + '<｜end▁of▁sentence｜>'}}
{%- endif %}
{%- endif %}
{%- if message['role'] == 'tool' %}
{%- set ns.is_tool = true -%}
{%- if ns.is_output_first %}
{{'<｜tool▁outputs▁begin｜><｜tool▁output▁begin｜>' + message['content'] + '<｜tool▁output▁end｜>'}}
{%- set ns.is_output_first = false %}
{%- else %}
{{'\n<｜tool▁output▁begin｜>' + message['content'] + '<｜tool▁output▁end｜>'}}
{%- endif %}
{%- endif %}
{%- endfor -%}
{% if ns.is_tool %}
{{'<｜tool▁outputs▁end｜>'}}
{% endif %}
{% if add_generation_prompt and not ns.is_tool %}
{{'<｜Assistant｜>'}}
{% endif %}

57
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{%- set loop_messages = messages -%}
{%- set message_roles = ['system', 'user', 'assistant', 'tool'] -%}
{%- set system_prompt_suffix -%}
{%- filter trim -%}
In addition to plain text responses, you can chose to call one or more of the provided functions.
Use the following rule to decide when to call a function:
* if the response can be generated from your internal knowledge (e.g., as in the case of queries like "What is the capital of Poland?"), do so
* if you need external information that can be obtained by calling one or more of the provided functions, generate a function calls
If you decide to call functions:
* prefix function calls with functools marker (no closing marker required)
* all function calls should be generated in a single JSON list formatted as functools[{"name": [function name], "arguments": [function arguments as JSON]}, ...]
* follow the provided JSON schema. Do not hallucinate arguments or values. Do to blindly copy values from the provided samples
* respect the argument type formatting. E.g., if the type if number and format is float, write value 7 as 7.0
* make sure you pick the right functions that match the user intent
Available functions as JSON spec:
{%- endfilter -%}
{%- endset -%}
{%- set system_prompt_suffix = system_prompt_suffix + "\n" + functions -%}
{%- set system_prompt_suffix = system_prompt_suffix + '\nToday is ' + datetime + '.' -%}
{%- set ns = namespace(role='', content='') -%}
{#- Basic consistency checks -#}
{%- if not loop_messages -%}
{{ raise_exception('Expected non-empty messages') }}
{%- endif -%}
{%- for message in loop_messages -%}
{%- set ns.role = message['role'] | lower -%}
{%- if ns.role not in message_roles -%}
{%- set message_roles_string = message_roles | join(', ') -%}
{{ raise_exception('Invalid role ' + message['role'] + '. Only ' + message_roles_string + ' are supported.') }}
{%- endif -%}
{%- set msg_content = message['content'] | default('', true) | trim -%}
{%- if loop.index0 == 0 -%}
{%- if ns.role == 'system' -%}
{%- set system_prompt = '<|start_header_id|>' + 'system' + '<|end_header_id|>\n\n' + message['content'] | trim + '\n' + system_prompt_suffix + '<|eot_id|>' -%}
{%- else -%}
{%- set system_prompt = '<|start_header_id|>' + 'system' + '<|end_header_id|>\n\nYou are a helpful assistant with access to functions.\n' + system_prompt_suffix + '<|eot_id|>' -%}
{%- endif -%}
{%- set ns.content = bos_token + system_prompt -%}
{{- ns.content -}}
{%- endif -%}
{%- if loop.index0 > 0 or ns.role != 'system' -%}
{%- set ns.content = '<|start_header_id|>' + ns.role + '<|end_header_id|>\n\n' + msg_content -%}
{%- if 'tool_calls' in message and message['tool_calls'] -%}
{%- set tool = namespace(calls=[]) -%}
{%- for call in message['tool_calls'] -%}
{%- set tool.calls = tool.calls + ['{"name": "' + call['function']['name'] + '", "arguments": ' + call['function']['arguments'] + '}'] -%}
{%- endfor -%}
{%- set ns.content = ns.content + ' functools[' + tool.calls | join(', ') + ']' -%}
{%- endif -%}
{%- set ns.content = ns.content + '<|eot_id|>' -%}
{{- ns.content -}}
{%- endif -%}
{%- endfor -%}
{{- '<|start_header_id|>assistant<|end_header_id|>\n\n' -}}

4
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{{ bos_token }}{% if messages[0]['role'] == 'system' %}{{ raise_exception('System role not supported') }}{% endif %}{% for message in messages %}{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}{{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }}{% endif %}{% if (message['role'] == 'assistant') %}{% set role = 'model' %}{% else %}{% set role = message['role'] %}{% endif %}{{ '<start_of_turn>' + role + '
' + message['content'] | trim + '<end_of_turn>
' }}{% endfor %}{% if add_generation_prompt %}{{'<start_of_turn>model
'}}{% endif %}

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{# version=v3-llama3.1 #}{%- if not tools is defined -%}
{%- set tools = none -%}
{%- endif -%}
{%- set has_code_interpreter = tools | selectattr("type", "equalto", "code_interpreter") | list | length > 0 -%}
{%- if has_code_interpreter -%}
{%- set tools = tools | rejectattr("type", "equalto", "code_interpreter") | list -%}
{%- endif -%}
{#- System message + builtin tools #}
{{- bos_token + "<|start_header_id|>system<|end_header_id|>\n\n" }}
{%- if has_code_interpreter %}
{{- "Environment: ipython\n\n" }}
{%- else -%}
{{ "\n"}}
{%- endif %}
{{- "Cutting Knowledge Date: December 2023\n\n" }}
{%- if tools %}
{{- "\nYou have access to the following functions:\n\n" }}
{%- for t in tools %}
{%- if "type" in t -%}
{{ "Use the function '"|safe + t["function"]["name"] + "' to '"|safe + t["function"]["description"] + "'\n"|safe + t["function"] | tojson() }}
{%- else -%}
{{ "Use the function '"|safe + t["name"] + "' to '"|safe + t["description"] + "'\n"|safe + t | tojson() }}
{%- endif -%}
{{- "\n\n" }}
{%- endfor %}
{{- '\nThink very carefully before calling functions.\nIf a you choose to call a function ONLY reply in the following format:\n<{start_tag}={function_name}>{parameters}{end_tag}\nwhere\n\nstart_tag => `<function`\nparameters => a JSON dict with the function argument name as key and function argument value as value.\nend_tag => `</function>`\n\nHere is an example,\n<function=example_function_name>{"example_name": "example_value"}</function>\n\nReminder:\n- If looking for real time information use relevant functions before falling back to brave_search\n- Function calls MUST follow the specified format, start with <function= and end with </function>\n- Required parameters MUST be specified\n- Only call one function at a time\n- Put the entire function call reply on one line\n\n' -}}
{%- endif %}
{{- "<|eot_id|>" -}}
{%- for message in messages -%}
{%- if message['role'] == 'user' or message['role'] == 'system' -%}
{{ '<|start_header_id|>' + message['role'] + '<|end_header_id|>\n\n' + message['content'] + '<|eot_id|>' }}
{%- elif message['role'] == 'tool' -%}
{{ '<|start_header_id|>ipython<|end_header_id|>\n\n' + message['content'] + '<|eot_id|>' }}
{%- else -%}
{{ '<|start_header_id|>' + message['role'] + '<|end_header_id|>\n\n'}}
{%- if message['content'] -%}
{{ message['content'] }}
{%- endif -%}
{%- if 'tool_calls' in message and message['tool_calls'] -%}
{%- for tool_call in message['tool_calls'] -%}
{%- if tool_call["function"]["name"] == "python" -%}
{{ '<|python_tag|>' + tool_call['function']['arguments'] }}
{%- else -%}
{{ '<function=' + tool_call['function']['name'] + '>' + tool_call['function']['arguments'] + '</function>' }}
{%- endif -%}
{%- endfor -%}
{{ '<|eom_id|>' }}
{%- else -%}
{{ '<|eot_id|>' }}
{%- endif -%}
{%- endif -%}
{%- endfor -%}
{%- if add_generation_prompt -%}
{{ '<|start_header_id|>assistant<|end_header_id|>\n\n' }}
{%- endif -%}

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{# version=v3.llama3 #}{%- macro append_new_param_info(param_declaration, comment_info, examples_info, depth) -%}
{%- set offset = "" -%}
{%- if depth >= 1 -%}
{%- set offset = " " * depth -%}
{%- endif -%}
{%- if comment_info != "<|NONE|>" -%}
{{ "\n" + offset + comment_info }}
{%- if examples_info | length > 0 -%}
{# Append each example info #}
{%- for example in examples_info -%}
{{ "\n" + offset + "// " + example|string|replace("'", '"') }}
{%- endfor -%}
{%- endif -%}
{%- endif -%}
{{ "\n" + offset + param_declaration }}
{%- endmacro -%}
{%- macro convert_data_type(param_type) -%}
{%- if param_type == "integer" or param_type == "float" -%}
{{ "number" }}
{%- else -%}
{{ param_type }}
{%- endif -%}
{%- endmacro -%}
{%- macro get_param_type(param) -%}
{%- set param_type = "any" -%}
{%- if "type" in param -%}
{%- set raw_param_type = param["type"] -%}
{%- if raw_param_type is iterable and raw_param_type is not string -%}
{%- set param_type = raw_param_type | join(" | ") -%}
{%- else -%}
{%- set param_type = raw_param_type -%}
{%- endif -%}
{{ convert_data_type(param_type) }}
{%- elif "oneOf" in param -%}
{%- set one_of_types = param["oneOf"]|selectattr("type", "defined")|list -%}
{%- set one_of_types = one_of_types|map(attribute="type")|unique|list -%}
{{ convert_data_type(one_of_types | join(" | ")) }}
{%- endif -%}
{%- endmacro -%}
{%- macro get_format_param(param) -%}
{%- if "format" in param -%}
{{ param["format"] }}
{%- elif "oneOf" in param -%}
{%- set formats = [] -%}
{%- for item in param["oneOf"] -%}
{%- if "format" in item -%}
{%- if item["format"] == param["oneOf"][-1]["format"] -%}
{{ item["format"] }}
{%- else -%}
{{ item["format"] + " or "}}
{%- endif -%}
{%- endif -%}
{%- endfor -%}
{%- else -%}
{{ "<|NONE|>" }}
{%- endif -%}
{%- endmacro -%}
{%- macro get_param_info(param) -%}
{%- set param_type = param.get("type", "any") -%}
{%- set format_param = get_format_param(param) -%}
{%- if "description" in param or "default" in param or format_param != "<|NONE|>" or param["maximum"] or param["minimum"] or param["maxLength"] or param["minLength"] -%}
{{ "//" }}
{%- if "description" in param -%}
{%- set desc = param["description"] -%}
{%- if not desc.endswith(".") -%}
{%- set desc = desc + "." -%}
{%- endif -%}
{{ " " + desc }}
{%- endif -%}
{%- if "default" in param -%}
{%- set default_value = param["default"] -%}
{%- if param_type == "string" -%}
{%- set default_value = '"' ~ default_value ~ '"' -%}
{%- endif -%}
{{ " Default=" ~ default_value ~ "." }}
{%- endif -%}
{%- set format_param = get_format_param(param) -%}
{%- if format_param != "<|NONE|>" -%}
{{ " Format=" ~ format_param }}
{%- endif -%}
{%- for field, field_name in [("maximum", "Maximum"), ("minimum", "Minimum"), ("maxLength", "Maximum length"), ("minLength", "Minimum length")] -%}
{%- if field in param -%}
{{ " " + field_name ~ "=" ~ param[field] }}
{%- endif -%}
{%- endfor -%}
{%- else -%}
{{ "<|NONE|>"}}
{%- endif -%}
{%- endmacro -%}
{%- macro get_enum_option_str(enum_options) -%}
{%- for v in enum_options -%}
{%- if v is string -%}
{{ '"' + v + '"' }}
{%- else -%}
{{ v }}
{%- endif -%}
{%- if enum_options|length > 0 and v != enum_options[-1] -%}
{{ " | " }}
{%- endif -%}
{%- endfor -%}
{%- endmacro -%}
{%- macro get_array_typescript(param_name, param_dic, depth) -%}
{%- set offset = '' -%}
{%- if depth >= 1 -%}
{%- set offset = " " * depth -%}
{%- endif -%}
{%- set items_info = param_dic.get('items', {}) -%}
{%- if items_info|length == 0 -%}
{%- if param_name -%}
{{ "\n" + offset + param_name + ": []" }}
{%- else -%}
{{ "\n" + offset + "[]" }}
{%- endif -%}
{%- else -%}
{%- set array_type = get_param_type(items_info) -%}
{%- if array_type == 'object' -%}
{%- if param_name -%}
{{ "\n" + offset + param_name + ": {" }}
{%- else -%}
{{ "\n" + offset + "{" }}
{%- endif -%}
{{ get_parameter_typescript(items_info.get('properties', {}), items_info.get('required', []), depth + 1) -}}
{{- "\n" + offset + "}[]" }}
{%- elif array_type == 'array' -%}
{%- set item_info = get_array_typescript(None, items_info, depth + 1) -%}
{%- if not param_name -%}
{{ "\n" + item_info + "[]" }}
{%- else -%}
{{ "\n" + offset + param_name + ": " + item_info|trim + "[]" }}
{%- endif -%}
{%- else -%}
{%- if 'enum' in items_info -%}
{%- set item_type = get_enum_option_str(items_info['enum']) -%}
{%- if param_name is none -%}
{{ "(" + item_type + ")[]"}}
{%- else -%}
{{ "\n" + offset + param_name + ": (" + item_type + ")[]" }}
{%- endif -%}
{%- else -%}
{%- if param_name is none -%}
{{ "\n" + array_type + "[]" }}
{%- else -%}
{{ "\n" + offset + param_name + ": " + array_type + "[]," }}
{%- endif -%}
{%- endif -%}
{%- endif -%}
{%- endif -%}
{%- endmacro -%}
{%- macro get_parameter_typescript(properties, required_params, depth=0) -%}
{%- set res = "" -%}
{%- for param_name, param in properties.items() -%}
{%- if param is mapping -%}
{%- set comment_info = get_param_info(param) -%}
{# Param Examples #}
{%- set examples_info = [] -%}
{%- if "examples" in param -%}
{%- set examples_info = ["Example " + param_name + ":"] -%}
{%- set examples_info = examples_info + param["examples"] -%}
{%- endif -%}
{# Param Name declaration #}
{%- set param_declaration = param_name -%}
{%- if required_params is iterable and param_name not in required_params -%}
{%- set param_declaration = param_declaration + "?" -%}
{%- endif -%}
{%- set param_type = get_param_type(param) -%}
{# Handle indentation based on depth #}
{%- set offset = "" -%}
{%- if depth >= 1 -%}
{%- set offset = " " * depth -%}
{%- endif -%}
{%- if param_type == "object" -%}
{%- if comment_info != "<|NONE|>" -%}
{{ "\n" + offset + comment_info }}
{%- endif -%}
{%- if examples_info|length > 0 -%}
{%- for example in examples_info -%}
{{ "\n" + offset + "// " + example|string|replace("'", '"') }}
{%- endfor -%}
{%- endif -%}
{%- set param_declaration = param_declaration + ": {" -%}
{{ "\n" + offset + param_declaration -}}
{{- get_parameter_typescript(param.get("properties", {}), param.get("required", []), depth + 1) -}}
{{- "\n" + offset + "}," }}
{%- elif param_type == "array" -%}
{%- set item_info = param.get("items", {}) -%}
{%- if "type" not in item_info -%}
{%- set param_declaration = param_declaration + ": []," -%}
{{ append_new_param_info(param_declaration, comment_info, examples_info, depth) }}
{%- else -%}
{%- if comment_info != "<|NONE|>" -%}
{{ "\n" + offset + comment_info }}
{%- endif -%}
{%- if examples_info|length > 0 -%}
{%- for example in examples_info -%}
{{ "\n" + offset + "// " + example|string|replace("'", '"') }}
{%- endfor -%}
{%- endif -%}
{%- set array_declaration = get_array_typescript(param_declaration, param, depth) -%}
{%- if not array_declaration.endswith(",") -%}
{%- set array_declaration = array_declaration + "," -%}
{%- endif -%}
{{ array_declaration}}
{%- endif -%}
{%- else -%}
{%- if "enum" in param -%}
{%- set param_type = get_enum_option_str(param["enum"]) -%}
{%- endif -%}
{%- if "nullable" in param and param["nullable"] -%}
{%- set param_type = param_type + " | null" -%}
{%- endif -%}
{%- set param_declaration = param_declaration + ": " + param_type + "," -%}
{{ append_new_param_info(param_declaration, comment_info, examples_info, depth) }}
{%- endif -%}
{%- endif -%}
{%- endfor -%}
{%- endmacro -%}
{%- macro generate_schema_from_functions(functions, namespace='functions') -%}
{{ "// Supported function definitions that should be called when necessary.\n" -}}
{{- "namespace " + namespace + " {\n\n" -}}
{%- for function in functions -%}
{%- if function.get("function") -%}
{%- set function = function.get("function") -%}
{%- endif -%}
{%- set function_name = function.get("name") -%}
{%- if function_name -%}
{%- set description = function.get('description', '') -%}
{%- set parameters = function.get('parameters', {}) -%}
{{- "// " + description + "\n" -}}
{{- "type " + function_name -}}
{%- if parameters and parameters.get("properties") -%}
{{- " = (_: {" -}}
{%- set required_params = parameters.get("required", []) -%}
{{ get_parameter_typescript(parameters.get("properties"), required_params, 0) -}}
{{- "\n}) => any;\n\n" }}
{%- else -%}
{{ " = () => any;\n\n" }}
{%- endif -%}
{%- endif -%}
{%- endfor -%}
{{ "} // namespace " + namespace }}
{%- endmacro -%}
{%- if not tools -%}
{%- set tools = [] -%}
{%- endif -%}
{{ bos_token + '<|start_header_id|>system<|end_header_id|>\n\nYou are capable of executing available function(s) if required.\nOnly execute function(s) when absolutely necessary.\nAsk for the required input to:recipient==all\nUse JSON for function arguments.\nRespond in this format:\n>>>${recipient}\n${content}\nAvailable functions:\n' + generate_schema_from_functions(tools) + '<|eot_id|>' -}}
{%- if tools|length > 0 and tools|selectattr("type", "equalto", "code_interpreter")|list|length > 0 -%}
{{ '<|start_header_id|>system<|end_header_id|>\n\nWhen you send a message containing Python code to python, it will be executed in a stateful Jupyter notebook environment. python will respond with the output of the execution or time out after 60.0 seconds. The drive at \'/mnt/data\' can be used to save and persist user files.<|eot_id|>' }}
{%- endif -%}
{%- for message in messages -%}
{%- if message['role'] == 'user' or message['role'] == 'system' -%}
{{ '<|start_header_id|>' + message['role'] + '<|end_header_id|>\n\n' + message['content'] + '<|eot_id|>' }}
{%- elif message['role'] == 'tool' -%}
{{ '<|start_header_id|>' + message['role'] + '<|end_header_id|>\n\n' + message['content'] + '<|eot_id|>' }}
{%- else -%}
{{ '<|start_header_id|>' + message['role'] + '<|end_header_id|>\n\n'}}
{%- if message['content'] -%}
{{ '>>>all\n' + message['content'] }}
{%- endif -%}
{%- if 'tool_calls' in message and message['tool_calls'] -%}
{%- for tool_call in message['tool_calls'] -%}
{{ '>>>' + tool_call['function']['name'] + '\n' + tool_call['function']['arguments'] }}
{%- endfor -%}
{%- endif -%}
{{ '<|eot_id|>' }}
{%- endif -%}
{%- endfor -%}
{% if add_generation_prompt %}{{ '<|start_header_id|>assistant<|end_header_id|>\n\n>>>' }}{% endif %}

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{{- bos_token }}
{%- if custom_tools is defined %}
{%- set tools = custom_tools %}
{%- endif %}
{%- if not tools_in_user_message is defined %}
{%- set tools_in_user_message = true %}
{%- endif %}
{%- if not date_string is defined %}
{%- set date_string = "26 Jul 2024" %}
{%- endif %}
{%- if not tools is defined %}
{%- set tools = none %}
{%- endif %}
{#- This block extracts the system message, so we can slot it into the right place. #}
{%- if messages[0]['role'] == 'system' %}
{%- set system_message = messages[0]['content']|trim %}
{%- set messages = messages[1:] %}
{%- else %}
{%- set system_message = "" %}
{%- endif %}
{#- System message + builtin tools #}
{{- "<|start_header_id|>system<|end_header_id|>\n\n" }}
{%- if builtin_tools is defined or tools is not none %}
{{- "Environment: ipython\n" }}
{%- endif %}
{%- if builtin_tools is defined %}
{{- "Tools: " + builtin_tools | reject('equalto', 'code_interpreter') | join(", ") + "\n\n"}}
{%- endif %}
{{- "Cutting Knowledge Date: December 2023\n" }}
{{- "Today Date: " + date_string + "\n\n" }}
{%- if tools is not none and not tools_in_user_message %}
{{- "You have access to the following functions. To call a function, please respond with JSON for a function call." }}
{{- 'Respond in the format {"name": function name, "parameters": dictionary of argument name and its value}.' }}
{{- "Do not use variables.\n\n" }}
{%- for t in tools %}
{{- t | tojson(indent=4) }}
{{- "\n\n" }}
{%- endfor %}
{%- endif %}
{{- system_message }}
{{- "<|eot_id|>" }}
{#- Custom tools are passed in a user message with some extra guidance #}
{%- if tools_in_user_message and not tools is none %}
{#- Extract the first user message so we can plug it in here #}
{%- if messages | length != 0 %}
{%- set first_user_message = messages[0]['content']|trim %}
{%- set messages = messages[1:] %}
{%- else %}
{{- raise_exception("Cannot put tools in the first user message when there's no first user message!") }}
{%- endif %}
{{- '<|start_header_id|>user<|end_header_id|>\n\n' -}}
{{- "Given the following functions, please respond with a JSON for a function call " }}
{{- "with its proper arguments that best answers the given prompt.\n\n" }}
{{- 'Respond in the format {"name": function name, "parameters": dictionary of argument name and its value}.' }}
{{- "Do not use variables.\n\n" }}
{%- for t in tools %}
{{- t | tojson(indent=4) }}
{{- "\n\n" }}
{%- endfor %}
{{- first_user_message + "<|eot_id|>"}}
{%- endif %}
{%- for message in messages %}
{%- if not (message.role == 'ipython' or message.role == 'tool' or 'tool_calls' in message) %}
{{- '<|start_header_id|>' + message['role'] + '<|end_header_id|>\n\n'+ message['content'] | trim + '<|eot_id|>' }}
{%- elif 'tool_calls' in message %}
{%- if not message.tool_calls|length == 1 %}
{{- raise_exception("This model only supports single tool-calls at once!") }}
{%- endif %}
{%- set tool_call = message.tool_calls[0].function %}
{%- if builtin_tools is defined and tool_call.name in builtin_tools %}
{{- '<|start_header_id|>assistant<|end_header_id|>\n\n' -}}
{{- "<|python_tag|>" + tool_call.name + ".call(" }}
{%- for arg_name, arg_val in tool_call.arguments | items %}
{{- arg_name + '="' + arg_val + '"' }}
{%- if not loop.last %}
{{- ", " }}
{%- endif %}
{%- endfor %}
{{- ")" }}
{%- else %}
{{- '<|start_header_id|>assistant<|end_header_id|>\n\n' -}}
{{- '{"name": "' + tool_call.name + '", ' }}
{{- '"parameters": ' }}
{{- tool_call.arguments | tojson }}
{{- "}" }}
{%- endif %}
{%- if builtin_tools is defined %}
{#- This means we're in ipython mode #}
{{- "<|eom_id|>" }}
{%- else %}
{{- "<|eot_id|>" }}
{%- endif %}
{%- elif message.role == "tool" or message.role == "ipython" %}
{{- "<|start_header_id|>ipython<|end_header_id|>\n\n" }}
{%- if message.content is mapping or message.content is iterable %}
{{- message.content | tojson }}
{%- else %}
{{- message.content }}
{%- endif %}
{{- "<|eot_id|>" }}
{%- endif %}
{%- endfor %}
{%- if add_generation_prompt %}
{{- '<|start_header_id|>assistant<|end_header_id|>\n\n' }}
{%- endif %}

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{{- bos_token }}
{%- if custom_tools is defined %}
{%- set tools = custom_tools %}
{%- endif %}
{%- if not tools_in_user_message is defined %}
{%- set tools_in_user_message = true %}
{%- endif %}
{%- if not date_string is defined %}
{%- if strftime_now is defined %}
{%- set date_string = strftime_now("%d %b %Y") %}
{%- else %}
{%- set date_string = "26 Jul 2024" %}
{%- endif %}
{%- endif %}
{%- if not tools is defined %}
{%- set tools = none %}
{%- endif %}
{#- This block extracts the system message, so we can slot it into the right place. #}
{%- if messages[0]['role'] == 'system' %}
{%- set system_message = messages[0]['content']|trim %}
{%- set messages = messages[1:] %}
{%- else %}
{%- set system_message = "" %}
{%- endif %}
{#- System message #}
{{- "<|start_header_id|>system<|end_header_id|>\n\n" }}
{%- if tools is not none %}
{{- "Environment: ipython\n" }}
{%- endif %}
{{- "Cutting Knowledge Date: December 2023\n" }}
{{- "Today Date: " + date_string + "\n\n" }}
{%- if tools is not none and not tools_in_user_message %}
{{- "You have access to the following functions. To call a function, please respond with JSON for a function call." }}
{{- 'Respond in the format {"name": function name, "parameters": dictionary of argument name and its value}.' }}
{{- "Do not use variables.\n\n" }}
{%- for t in tools %}
{{- t | tojson(indent=4) }}
{{- "\n\n" }}
{%- endfor %}
{%- endif %}
{{- system_message }}
{{- "<|eot_id|>" }}
{#- Custom tools are passed in a user message with some extra guidance #}
{%- if tools_in_user_message and not tools is none %}
{#- Extract the first user message so we can plug it in here #}
{%- if messages | length != 0 %}
{%- set first_user_message = messages[0]['content']|trim %}
{%- set messages = messages[1:] %}
{%- else %}
{{- raise_exception("Cannot put tools in the first user message when there's no first user message!") }}
{%- endif %}
{{- '<|start_header_id|>user<|end_header_id|>\n\n' -}}
{{- "Given the following functions, please respond with a JSON for a function call " }}
{{- "with its proper arguments that best answers the given prompt.\n\n" }}
{{- 'Respond in the format {"name": function name, "parameters": dictionary of argument name and its value}.' }}
{{- "Do not use variables.\n\n" }}
{%- for t in tools %}
{{- t | tojson(indent=4) }}
{{- "\n\n" }}
{%- endfor %}
{{- first_user_message + "<|eot_id|>"}}
{%- endif %}
{%- for message in messages %}
{%- if not (message.role == 'ipython' or message.role == 'tool' or 'tool_calls' in message) %}
{{- '<|start_header_id|>' + message['role'] + '<|end_header_id|>\n\n'+ message['content'] | trim + '<|eot_id|>' }}
{%- elif 'tool_calls' in message %}
{%- if not message.tool_calls|length == 1 %}
{{- raise_exception("This model only supports single tool-calls at once!") }}
{%- endif %}
{%- set tool_call = message.tool_calls[0].function %}
{{- '<|start_header_id|>assistant<|end_header_id|>\n\n' -}}
{{- '{"name": "' + tool_call.name + '", ' }}
{{- '"parameters": ' }}
{{- tool_call.arguments | tojson }}
{{- "}" }}
{{- "<|eot_id|>" }}
{%- elif message.role == "tool" or message.role == "ipython" %}
{{- "<|start_header_id|>ipython<|end_header_id|>\n\n" }}
{%- if message.content is mapping or message.content is iterable %}
{{- message.content | tojson }}
{%- else %}
{{- message.content }}
{%- endif %}
{{- "<|eot_id|>" }}
{%- endif %}
{%- endfor %}
{%- if add_generation_prompt %}
{{- '<|start_header_id|>assistant<|end_header_id|>\n\n' }}
{%- endif %}

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{{- bos_token }}
{%- if custom_tools is defined %}
{%- set tools = custom_tools %}
{%- endif %}
{%- if not tools_in_user_message is defined %}
{%- set tools_in_user_message = true %}
{%- endif %}
{%- if not date_string is defined %}
{%- set date_string = "26 Jul 2024" %}
{%- endif %}
{%- if not tools is defined %}
{%- set tools = none %}
{%- endif %}
{#- This block extracts the system message, so we can slot it into the right place. #}
{%- if messages[0]['role'] == 'system' %}
{%- set system_message = messages[0]['content']|trim %}
{%- set messages = messages[1:] %}
{%- else %}
{%- set system_message = "" %}
{%- endif %}
{#- System message + builtin tools #}
{{- "<|start_header_id|>system<|end_header_id|>\n\n" }}
{%- if builtin_tools is defined or tools is not none %}
{{- "Environment: ipython\n" }}
{%- endif %}
{%- if builtin_tools is defined %}
{{- "Tools: " + builtin_tools | reject('equalto', 'code_interpreter') | join(", ") + "\n\n"}}
{%- endif %}
{{- "Cutting Knowledge Date: December 2023\n" }}
{{- "Today Date: " + date_string + "\n\n" }}
{%- if tools is not none and not tools_in_user_message %}
{{- "You have access to the following functions. To call a function, please respond with JSON for a function call." }}
{{- 'Respond in the format {"name": function name, "parameters": dictionary of argument name and its value}.' }}
{{- "Do not use variables.\n\n" }}
{%- for t in tools %}
{{- t | tojson(indent=4) }}
{{- "\n\n" }}
{%- endfor %}
{%- endif %}
{{- system_message }}
{{- "<|eot_id|>" }}
{#- Custom tools are passed in a user message with some extra guidance #}
{%- if tools_in_user_message and not tools is none %}
{#- Extract the first user message so we can plug it in here #}
{%- if messages | length != 0 %}
{%- set first_user_message = messages[0]['content']|trim %}
{%- set messages = messages[1:] %}
{%- else %}
{{- raise_exception("Cannot put tools in the first user message when there's no first user message!") }}
{%- endif %}
{{- '<|start_header_id|>user<|end_header_id|>\n\n' -}}
{{- "Given the following functions, please respond with a JSON for a function call " }}
{{- "with its proper arguments that best answers the given prompt.\n\n" }}
{{- 'Respond in the format {"name": function name, "parameters": dictionary of argument name and its value}.' }}
{{- "Do not use variables.\n\n" }}
{%- for t in tools %}
{{- t | tojson(indent=4) }}
{{- "\n\n" }}
{%- endfor %}
{{- first_user_message + "<|eot_id|>"}}
{%- endif %}
{%- for message in messages %}
{%- if not (message.role == 'ipython' or message.role == 'tool' or 'tool_calls' in message) %}
{{- '<|start_header_id|>' + message['role'] + '<|end_header_id|>\n\n'+ message['content'] | trim + '<|eot_id|>' }}
{%- elif 'tool_calls' in message %}
{%- if not message.tool_calls|length == 1 %}
{{- raise_exception("This model only supports single tool-calls at once!") }}
{%- endif %}
{%- set tool_call = message.tool_calls[0].function %}
{%- if builtin_tools is defined and tool_call.name in builtin_tools %}
{{- '<|start_header_id|>assistant<|end_header_id|>\n\n' -}}
{{- "<|python_tag|>" + tool_call.name + ".call(" }}
{%- for arg_name, arg_val in tool_call.arguments | items %}
{{- arg_name + '="' + arg_val + '"' }}
{%- if not loop.last %}
{{- ", " }}
{%- endif %}
{%- endfor %}
{{- ")" }}
{%- else %}
{{- '<|start_header_id|>assistant<|end_header_id|>\n\n' -}}
{{- '{"name": "' + tool_call.name + '", ' }}
{{- '"parameters": ' }}
{{- tool_call.arguments | tojson }}
{{- "}" }}
{%- endif %}
{%- if builtin_tools is defined %}
{#- This means we're in ipython mode #}
{{- "<|eom_id|>" }}
{%- else %}
{{- "<|eot_id|>" }}
{%- endif %}
{%- elif message.role == "tool" or message.role == "ipython" %}
{{- "<|start_header_id|>ipython<|end_header_id|>\n\n" }}
{%- if message.content is mapping or message.content is iterable %}
{{- message.content | tojson }}
{%- else %}
{{- message.content }}
{%- endif %}
{{- "<|eot_id|>" }}
{%- endif %}
{%- endfor %}
{%- if add_generation_prompt %}
{{- '<|start_header_id|>assistant<|end_header_id|>\n\n' }}
{%- endif %}

8
models/templates/microsoft-Phi-3.5-mini-instruct.jinja Normal file
View file

@ -0,0 +1,8 @@
{% for message in messages %}{% if message['role'] == 'system' and message['content'] %}{{'<|system|>
' + message['content'] + '<|end|>
'}}{% elif message['role'] == 'user' %}{{'<|user|>
' + message['content'] + '<|end|>
'}}{% elif message['role'] == 'assistant' %}{{'<|assistant|>
' + message['content'] + '<|end|>
'}}{% endif %}{% endfor %}{% if add_generation_prompt %}{{ '<|assistant|>
' }}{% else %}{{ eos_token }}{% endif %}

87
models/templates/mistralai-Mistral-Nemo-Instruct-2407.jinja Normal file
View file

@ -0,0 +1,87 @@
{%- if messages[0]["role"] == "system" %}
{%- set system_message = messages[0]["content"] %}
{%- set loop_messages = messages[1:] %}
{%- else %}
{%- set loop_messages = messages %}
{%- endif %}
{%- if not tools is defined %}
{%- set tools = none %}
{%- endif %}
{%- set user_messages = loop_messages | selectattr("role", "equalto", "user") | list %}
{#- This block checks for alternating user/assistant messages, skipping tool calling messages #}
{%- set ns = namespace() %}
{%- set ns.index = 0 %}
{%- for message in loop_messages %}
{%- if not (message.role == "tool" or message.role == "tool_results" or (message.tool_calls is defined and message.tool_calls is not none)) %}
{%- if (message["role"] == "user") != (ns.index % 2 == 0) %}
{{- raise_exception("After the optional system message, conversation roles must alternate user/assistant/user/assistant/...") }}
{%- endif %}
{%- set ns.index = ns.index + 1 %}
{%- endif %}
{%- endfor %}
{{- bos_token }}
{%- for message in loop_messages %}
{%- if message["role"] == "user" %}
{%- if tools is not none and (message == user_messages[-1]) %}
{{- "[AVAILABLE_TOOLS][" }}
{%- for tool in tools %}
{%- set tool = tool.function %}
{{- '{"type": "function", "function": {' }}
{%- for key, val in tool.items() if key != "return" %}
{%- if val is string %}
{{- '"' + key + '": "' + val + '"' }}
{%- else %}
{{- '"' + key + '": ' + val|tojson }}
{%- endif %}
{%- if not loop.last %}
{{- ", " }}
{%- endif %}
{%- endfor %}
{{- "}}" }}
{%- if not loop.last %}
{{- ", " }}
{%- else %}
{{- "]" }}
{%- endif %}
{%- endfor %}
{{- "[/AVAILABLE_TOOLS]" }}
{%- endif %}
{%- if loop.last and system_message is defined %}
{{- "[INST]" + system_message + "\n\n" + message["content"] + "[/INST]" }}
{%- else %}
{{- "[INST]" + message["content"] + "[/INST]" }}
{%- endif %}
{%- elif (message.tool_calls is defined and message.tool_calls is not none) %}
{{- "[TOOL_CALLS][" }}
{%- for tool_call in message.tool_calls %}
{%- set out = tool_call.function|tojson %}
{{- out[:-1] }}
{%- if not tool_call.id is defined or tool_call.id|length != 9 %}
{{- raise_exception("Tool call IDs should be alphanumeric strings with length 9!") }}
{%- endif %}
{{- ', "id": "' + tool_call.id + '"}' }}
{%- if not loop.last %}
{{- ", " }}
{%- else %}
{{- "]" + eos_token }}
{%- endif %}
{%- endfor %}
{%- elif message["role"] == "assistant" %}
{{- message["content"] + eos_token}}
{%- elif message["role"] == "tool_results" or message["role"] == "tool" %}
{%- if message.content is defined and message.content.content is defined %}
{%- set content = message.content.content %}
{%- else %}
{%- set content = message.content %}
{%- endif %}
{{- '[TOOL_RESULTS]{"content": ' + content|string + ", " }}
{%- if not message.tool_call_id is defined or message.tool_call_id|length != 9 %}
{{- raise_exception("Tool call IDs should be alphanumeric strings with length 9!") }}
{%- endif %}
{{- '"call_id": "' + message.tool_call_id + '"}[/TOOL_RESULTS]' }}
{%- else %}
{{- raise_exception("Only user and assistant roles are supported, with the exception of an initial optional system message!") }}
{%- endif %}
{%- endfor %}

105
scripts/fetch_server_test_models.py Executable file
View file

@ -0,0 +1,105 @@
#!/usr/bin/env python
'''
This script fetches all the models used in the server tests.
This is useful for slow tests that use larger models, to avoid them timing out on the model downloads.
It is meant to be run from the root of the repository.
Example:
python scripts/fetch_server_test_models.py
( cd examples/server/tests && ./tests.sh -v -x -m slow )
'''
import ast
import glob
import logging
import os
from typing import Generator
from pydantic import BaseModel
from typing import Optional
import subprocess
class HuggingFaceModel(BaseModel):
hf_repo: str
hf_file: Optional[str] = None
class Config:
frozen = True
def collect_hf_model_test_parameters(test_file) -> Generator[HuggingFaceModel, None, None]:
try:
with open(test_file) as f:
tree = ast.parse(f.read())
except Exception as e:
logging.error(f'collect_hf_model_test_parameters failed on {test_file}: {e}')
return
for node in ast.walk(tree):
if isinstance(node, ast.FunctionDef):
for dec in node.decorator_list:
if isinstance(dec, ast.Call) and isinstance(dec.func, ast.Attribute) and dec.func.attr == 'parametrize':
param_names = ast.literal_eval(dec.args[0]).split(",")
if "hf_repo" not in param_names:
continue
raw_param_values = dec.args[1]
if not isinstance(raw_param_values, ast.List):
logging.warning(f'Skipping non-list parametrize entry at {test_file}:{node.lineno}')
continue
hf_repo_idx = param_names.index("hf_repo")
hf_file_idx = param_names.index("hf_file") if "hf_file" in param_names else None
for t in raw_param_values.elts:
if not isinstance(t, ast.Tuple):
logging.warning(f'Skipping non-tuple parametrize entry at {test_file}:{node.lineno}')
continue
yield HuggingFaceModel(
hf_repo=ast.literal_eval(t.elts[hf_repo_idx]),
hf_file=ast.literal_eval(t.elts[hf_file_idx]) if hf_file_idx is not None else None)
if __name__ == '__main__':
logging.basicConfig(level=logging.INFO, format='%(levelname)s: %(message)s')
models = sorted(list(set([
model
for test_file in glob.glob('examples/server/tests/unit/test_*.py')
for model in collect_hf_model_test_parameters(test_file)
])), key=lambda m: (m.hf_repo, m.hf_file))
logging.info(f'Found {len(models)} models in parameterized tests:')
for m in models:
logging.info(f' - {m.hf_repo} / {m.hf_file}')
cli_path = os.environ.get(
'LLAMA_SERVER_BIN_PATH',
os.path.join(
os.path.dirname(__file__),
'../build/bin/Release/llama-cli.exe' if os.name == 'nt' else '../build/bin/llama-cli'))
for m in models:
if '<' in m.hf_repo or (m.hf_file is not None and '<' in m.hf_file):
continue
if m.hf_file is not None and '-of-' in m.hf_file:
logging.warning(f'Skipping model at {m.hf_repo} / {m.hf_file} because it is a split file')
continue
logging.info(f'Using llama-cli to ensure model {m.hf_repo}/{m.hf_file} was fetched')
cmd = [
cli_path,
'-hfr', m.hf_repo,
*([] if m.hf_file is None else ['-hff', m.hf_file]),
'-n', '1',
'-p', 'Hey',
'--no-warmup',
'--log-disable',
'-no-cnv']
if m.hf_file != 'tinyllamas/stories260K.gguf' and 'Mistral-Nemo' not in m.hf_repo:
cmd.append('-fa')
try:
subprocess.check_call(cmd)
except subprocess.CalledProcessError:
logging.error(f'Failed to fetch model at {m.hf_repo} / {m.hf_file} with command:\n {" ".join(cmd)}')
exit(1)

12
scripts/get_hf_chat_template.py → scripts/get_chat_template.py Executable file → Normal file
View file

@ -4,12 +4,12 @@
If a model has multiple chat templates, you can specify the variant name.
Syntax:
./scripts/get_hf_chat_template.py model_id [variant]
./scripts/get_chat_template.py model_id [variant]
Examples:
./scripts/get_hf_chat_template.py NousResearch/Meta-Llama-3-8B-Instruct
./scripts/get_hf_chat_template.py NousResearch/Hermes-3-Llama-3.1-8B tool_use
./scripts/get_hf_chat_template.py meta-llama/Llama-3.2-3B-Instruct
./scripts/get_chat_template.py NousResearch/Meta-Llama-3-8B-Instruct
./scripts/get_chat_template.py NousResearch/Hermes-3-Llama-3.1-8B tool_use
./scripts/get_chat_template.py meta-llama/Llama-3.2-3B-Instruct
'''
import json
@ -17,7 +17,7 @@ import re
import sys
def get_hf_chat_template(model_id, variant=None):
def get_chat_template(model_id, variant=None):
try:
# Use huggingface_hub library if available.
# Allows access to gated models if the user has access and ran `huggingface-cli login`.
@ -69,7 +69,7 @@ def main(args):
model_id = args[0]
variant = None if len(args) < 2 else args[1]
template = get_hf_chat_template(model_id, variant)
template = get_chat_template(model_id, variant)
sys.stdout.write(template)

2
scripts/sync-ggml.last
View file

@ -1 +1 @@
d92321c0d151fe73a47d89738c7c3091ac904297
32f0b85987396945afea2291d5f4c5862434292b

88
src/llama-grammar.cpp
View file

@ -560,7 +560,7 @@ bool llama_grammar_parser::parse(const char * src) {
}
}
} catch (const std::exception & err) {
fprintf(stderr, "%s: error parsing grammar: %s\n", __func__, err.what());
fprintf(stderr, "%s: error parsing grammar: %s\n\n%s\n", __func__, err.what(), src);
rules.clear();
return false;
}
@ -960,10 +960,28 @@ struct llama_grammar * llama_grammar_init_impl(
// Important: vec_rules has to be moved here, not copied, because stacks contains
// pointers to elements of vec_rules. If vec_rules were copied into llama_grammar
// then the pointers would be invalidated when the local vec_rules goes out of scope.
return new llama_grammar { vocab, std::move(vec_rules), std::move(stacks), {}, };
return new llama_grammar {
vocab,
std::move(vec_rules),
std::move(stacks),
/* .partial_utf8 = */ {},
/* .lazy =*/ false,
/* .awaiting_trigger = */ false,
/* .trigger_buffer = */ "",
/* .trigger_tokens = */ {},
/* .trigger_words = */ {},
};
}
struct llama_grammar * llama_grammar_init_impl(const struct llama_vocab * vocab, const char * grammar_str, const char * grammar_root) {
struct llama_grammar * llama_grammar_init_impl(
const struct llama_vocab * vocab,
const char * grammar_str,
const char * grammar_root,
bool lazy,
const char ** trigger_words,
size_t num_trigger_words,
const llama_token * trigger_tokens,
size_t num_trigger_tokens) {
llama_grammar_parser parser;
// if there is a grammar, parse it
@ -1035,10 +1053,31 @@ struct llama_grammar * llama_grammar_init_impl(const struct llama_vocab * vocab,
}
} while (true);
std::vector<llama_token> vec_trigger_tokens;
std::vector<std::string> vec_trigger_words;
for (size_t i = 0; i < num_trigger_tokens; i++) {
GGML_ASSERT(trigger_tokens != nullptr);
vec_trigger_tokens.push_back(trigger_tokens[i]);
}
for (size_t i = 0; i < num_trigger_words; i++) {
GGML_ASSERT(trigger_words != nullptr);
vec_trigger_words.push_back(trigger_words[i]);
}
// Important: vec_rules has to be moved here, not copied, because stacks contains
// pointers to elements of vec_rules. If vec_rules were copied into llama_grammar
// then the pointers would be invalidated when the local vec_rules goes out of scope.
return new llama_grammar { vocab, std::move(vec_rules), std::move(stacks), {}, };
return new llama_grammar {
vocab,
std::move(vec_rules),
std::move(stacks),
/* .partial_utf8 = */ {},
/* .lazy = */ lazy,
/* .awaiting_trigger = */ lazy,
/* .trigger_buffer = */ "",
std::move(vec_trigger_tokens),
std::move(vec_trigger_words),
};
}
void llama_grammar_free_impl(struct llama_grammar * grammar) {
@ -1055,6 +1094,11 @@ struct llama_grammar * llama_grammar_clone_impl(const struct llama_grammar & gra
grammar.rules,
grammar.stacks,
grammar.partial_utf8,
grammar.lazy,
grammar.awaiting_trigger,
grammar.trigger_buffer,
grammar.trigger_tokens,
grammar.trigger_words,
};
// redirect elements in stacks to point to new rules
@ -1076,6 +1120,10 @@ struct llama_grammar * llama_grammar_clone_impl(const struct llama_grammar & gra
void llama_grammar_apply_impl(const struct llama_grammar & grammar, llama_token_data_array * cur_p) {
GGML_ASSERT(grammar.vocab != nullptr);
if (grammar.awaiting_trigger) {
return;
}
bool allow_eog = false;
for (const auto & stack : grammar.stacks) {
if (stack.empty()) {
@ -1115,6 +1163,34 @@ void llama_grammar_apply_impl(const struct llama_grammar & grammar, llama_token_
void llama_grammar_accept_impl(struct llama_grammar & grammar, llama_token token) {
GGML_ASSERT(grammar.vocab != nullptr);
const auto & piece = grammar.vocab->token_to_piece(token);
if (grammar.awaiting_trigger) {
if (std::find(grammar.trigger_tokens.begin(), grammar.trigger_tokens.end(), token) != grammar.trigger_tokens.end()) {
grammar.awaiting_trigger = false;
grammar.trigger_buffer.clear();
llama_grammar_accept_str(grammar, piece);
LLAMA_LOG_DEBUG("Grammar triggered on token %u (`%s`)", token, piece.c_str());
return;
} else {
// TODO: consider a smarter incremental substring search algorithm (store last position to search from).
grammar.trigger_buffer += piece;
for (const auto & word : grammar.trigger_words) {
auto pos = grammar.trigger_buffer.find(word);
if (pos != std::string::npos) {
grammar.awaiting_trigger = false;
auto constrained_str = grammar.trigger_buffer.substr(pos);
grammar.trigger_buffer.clear();
llama_grammar_accept_str(grammar, constrained_str);
LLAMA_LOG_DEBUG("Grammar triggered on word `%s`", word.c_str());
return;
}
}
LLAMA_LOG_DEBUG("Grammar still awaiting trigger after token %d (`%s`) (buffer: `%s`)\n", token, piece.c_str(), grammar.trigger_buffer.c_str());
return;
}
}
if (grammar.vocab->is_eog(token)) {
for (const auto & stack : grammar.stacks) {
if (stack.empty()) {
@ -1124,8 +1200,10 @@ void llama_grammar_accept_impl(struct llama_grammar & grammar, llama_token token
GGML_ABORT("fatal error");
}
const std::string & piece = grammar.vocab->token_to_piece(token);
llama_grammar_accept_str(grammar, piece);
}
void llama_grammar_accept_str(struct llama_grammar & grammar, const std::string & piece) {
// Note terminating 0 in decoded string
const auto decoded = decode_utf8(piece, grammar.partial_utf8);
const auto & code_points = decoded.first;

23
src/llama-grammar.h
View file

@ -114,6 +114,15 @@ struct llama_grammar {
// buffer for partially generated UTF-8 sequence from accepted tokens
llama_partial_utf8 partial_utf8;
// lazy grammars wait for trigger words or tokens before constraining the sampling.
// we still ahve trigger_tokens for non-lazy grammars to force printing of special trigger tokens.
// (useful e.g. for tool_choice=required)
bool lazy = false;
bool awaiting_trigger = false; // Initialized to true for lazy grammars only
std::string trigger_buffer; // Output buffered by lazy grammar. Will be cleared once trigger is found.
std::vector<llama_token> trigger_tokens; // Tokens that trigger a lazy grammar, or tokens to force printing of (even if special).
std::vector<std::string> trigger_words;
};
//
@ -127,7 +136,15 @@ struct llama_grammar * llama_grammar_init_impl(
size_t n_rules,
size_t start_rule_index);
struct llama_grammar * llama_grammar_init_impl(const struct llama_vocab * vocab, const char * grammar_str, const char * grammar_root);
struct llama_grammar * llama_grammar_init_impl(
const struct llama_vocab * vocab,
const char * grammar_str,
const char * grammar_root,
bool lazy,
const char ** trigger_words,
size_t num_trigger_words,
const llama_token * trigger_tokens,
size_t num_trigger_tokens);
void llama_grammar_free_impl(struct llama_grammar * grammar);
@ -141,3 +158,7 @@ void llama_grammar_apply_impl(
void llama_grammar_accept_impl(
struct llama_grammar & grammar,
llama_token token);
void llama_grammar_accept_str(
struct llama_grammar & grammar,
const std::string & piece);

2
src/llama-model-loader.cpp
View file

@ -819,7 +819,7 @@ void llama_model_loader::init_mappings(bool prefetch, llama_mlocks * mlock_mmaps
for (const auto & file : files) {
auto * reg = ggml_backend_dev_backend_reg(ggml_backend_dev_by_type(GGML_BACKEND_DEVICE_TYPE_CPU));
auto * is_numa_fn = (decltype(ggml_is_numa) *) ggml_backend_reg_get_proc_address(reg, "ggml_backend_cpu_is_numa");
std::unique_ptr<llama_mmap> mapping(new llama_mmap(file.get(), prefetch ? -1 : 0, is_numa_fn()));
std::unique_ptr<llama_mmap> mapping = std::make_unique<llama_mmap>(file.get(), prefetch ? -1 : 0, is_numa_fn());
mmaps_used.emplace_back(mapping->size(), 0);
if (mlock_mmaps) {
std::unique_ptr<llama_mlock> mlock_mmap(new llama_mlock());

2
src/llama-model.cpp
View file

@ -1303,10 +1303,12 @@ bool llama_model::load_tensors(llama_model_loader & ml) {
const int act_gpu_layers = devices.empty() ? 0 : std::min(n_gpu_layers, (int)n_layer + 1);
auto get_layer_buft_list = [&](int il) -> llama_model::impl::layer_dev {
if (il < i_gpu_start || (il - i_gpu_start) >= act_gpu_layers) {
LLAMA_LOG_DEBUG("load_tensors: layer %3d assigned to device %s\n", il, ggml_backend_dev_name(cpu_dev));
return {cpu_dev, &pimpl->cpu_buft_list};
}
const int layer_gpu = std::upper_bound(splits.begin(), splits.begin() + n_devices(), float(il - i_gpu_start)/act_gpu_layers) - splits.begin();
auto * dev = devices.at(layer_gpu);
LLAMA_LOG_DEBUG("load_tensors: layer %3d assigned to device %s\n", il, ggml_backend_dev_name(dev));
return {dev, &pimpl->gpu_buft_list.at(dev)};
};

51
src/llama-sampling.cpp
View file

@ -1433,13 +1433,30 @@ static void llama_sampler_grammar_apply(struct llama_sampler * smpl, llama_token
}
}
// Fwd declare to break reset --> init_impl --> llama_sampler_grammar_i --> reset cycle.
static struct llama_sampler * llama_sampler_init_grammar_impl(
const struct llama_vocab * vocab,
const char * grammar_str,
const char * grammar_root,
bool lazy,
const char ** trigger_words,
size_t num_trigger_words,
const llama_token * trigger_tokens,
size_t num_trigger_tokens);
static void llama_sampler_grammar_reset(struct llama_sampler * smpl) {
auto * ctx = (llama_sampler_grammar *) smpl->ctx;
if (!ctx->grammar) {
return;
}
auto * grammar_new = llama_grammar_init_impl(ctx->grammar->vocab, ctx->grammar_str.c_str(), ctx->grammar_root.c_str());
std::vector<const char *> trigger_words;
for (auto & word : ctx->grammar->trigger_words) {
trigger_words.push_back(word.c_str());
}
auto * grammar_new = llama_grammar_init_impl(ctx->grammar->vocab, ctx->grammar_str.c_str(), ctx->grammar_root.c_str(),
ctx->grammar->lazy, trigger_words.data(), trigger_words.size(),
ctx->grammar->trigger_tokens.data(), ctx->grammar->trigger_tokens.size());
llama_grammar_free_impl(ctx->grammar);
ctx->grammar = grammar_new;
@ -1448,7 +1465,7 @@ static void llama_sampler_grammar_reset(struct llama_sampler * smpl) {
static struct llama_sampler * llama_sampler_grammar_clone(const struct llama_sampler * smpl) {
const auto * ctx = (const llama_sampler_grammar *) smpl->ctx;
auto * result = llama_sampler_init_grammar(ctx->vocab, nullptr, nullptr);
auto * result = llama_sampler_init_grammar_impl(ctx->vocab, nullptr, nullptr, false, nullptr, 0, nullptr, 0);
// copy the state
{
@ -1484,7 +1501,15 @@ static struct llama_sampler_i llama_sampler_grammar_i = {
/* .free = */ llama_sampler_grammar_free,
};
struct llama_sampler * llama_sampler_init_grammar(const struct llama_vocab * vocab, const char * grammar_str, const char * grammar_root) {
static struct llama_sampler * llama_sampler_init_grammar_impl(
const struct llama_vocab * vocab,
const char * grammar_str,
const char * grammar_root,
bool lazy,
const char ** trigger_words,
size_t num_trigger_words,
const llama_token * trigger_tokens,
size_t num_trigger_tokens) {
auto * ctx = new llama_sampler_grammar;
if (grammar_str != nullptr && grammar_str[0] != '\0') {
@ -1492,7 +1517,7 @@ struct llama_sampler * llama_sampler_init_grammar(const struct llama_vocab * voc
/* .vocab = */ vocab,
/* .grammar_str = */ grammar_str,
/* .grammar_root = */ grammar_root,
/* .grammar = */ llama_grammar_init_impl(vocab, grammar_str, grammar_root),
/* .grammar = */ llama_grammar_init_impl(vocab, grammar_str, grammar_root, lazy, trigger_words, num_trigger_words, trigger_tokens, num_trigger_tokens),
};
} else {
*ctx = {
@ -1509,6 +1534,24 @@ struct llama_sampler * llama_sampler_init_grammar(const struct llama_vocab * voc
};
}
struct llama_sampler * llama_sampler_init_grammar(
const struct llama_vocab * vocab,
const char * grammar_str,
const char * grammar_root) {
return llama_sampler_init_grammar_impl(vocab, grammar_str, grammar_root, /* lazy= */ false, nullptr, 0, nullptr, 0);
}
struct llama_sampler * llama_sampler_init_grammar_lazy(
const struct llama_vocab * vocab,
const char * grammar_str,
const char * grammar_root,
const char ** trigger_words,
size_t num_trigger_words,
const llama_token * trigger_tokens,
size_t num_trigger_tokens) {
return llama_sampler_init_grammar_impl(vocab, grammar_str, grammar_root, /* lazy= */ true, trigger_words, num_trigger_words, trigger_tokens, num_trigger_tokens);
}
// penalties
struct llama_sampler_penalties {

11
src/llama-vocab.cpp
View file

@ -1245,8 +1245,13 @@ struct llama_vocab::impl {
std::vector<llama_token> cache_special_tokens;
std::vector<std::string> cache_token_to_piece; // llama_token_to_piece(special = true);
std::map<std::pair<std::string, std::string>, int> bpe_ranks;
struct pair_hash {
size_t operator()(const std::pair<std::string, std::string> & p) const {
return std::hash<std::string>{}(p.first) ^ //create some hash for pair
(std::hash<std::string>{}(p.second) << 1);
}
};
std::unordered_map<std::pair<std::string, std::string>, int, pair_hash> bpe_ranks;
// set of all tokens that cause "end of generation"
std::set<llama_token> special_eog_ids;
@ -1687,7 +1692,7 @@ void llama_vocab::impl::load(llama_model_loader & ml, const LLM_KV & kv) {
GGML_ASSERT(!ids.empty() && "model vocab missing newline token");
linefeed_id = ids[0];
} else {
const std::vector<int> ids = tokenize("\xC4\x8A", false); // U+010A
const std::vector<int> ids = tokenize("\n", false);
//GGML_ASSERT(!ids.empty() && "model vocab missing newline token");
if (ids.empty()) {

265
src/llama.cpp
View file

@ -7700,17 +7700,13 @@ struct llm_build_context {
1
);
struct ggml_tensor * last_norm_att = ggml_view_3d(ctx0, x_norm_att, n_embd, 1, n_seqs, x_norm_att->nb[1], x_norm_att->nb[2], (n_seq_tokens-1)*n_embd*ggml_element_size(x_norm_att));
ggml_build_forward_expand(
gf,
ggml_cpy(
ctx0,
wkv_states,
ggml_view_1d(
ctx0,
kv_self.v_l[il],
hparams.n_embd_v_s() * n_seqs,
hparams.n_embd_v_s() * kv_head * ggml_element_size(kv_self.v_l[il])
)
ggml_view_1d(ctx0, last_norm_att, n_embd * n_seqs, 0),
ggml_view_1d(ctx0, kv_self.k_l[il], hparams.n_embd_k_s() * n_seqs, hparams.n_embd_k_s() * kv_head * ggml_element_size(kv_self.k_l[il]))
)
);
@ -8432,13 +8428,141 @@ static enum ggml_status llama_graph_compute(
return status;
}
static int llama_prepare_sbatch(
llama_context & lctx,
const llama_batch & batch,
uint32_t & n_outputs) {
const auto & model = lctx.model;
const auto & hparams = model.hparams;
const auto & cparams = lctx.cparams;
const uint32_t n_tokens_all = batch.n_tokens;
const int64_t n_embd = hparams.n_embd;
// this indicates we are doing pooled embedding, so we ignore batch.logits and output all tokens
const bool embd_pooled = cparams.embeddings && cparams.pooling_type != LLAMA_POOLING_TYPE_NONE;
GGML_ASSERT((!batch.token && batch.embd) || (batch.token && !batch.embd)); // NOLINT
if (batch.token) {
for (uint32_t i = 0; i < n_tokens_all; ++i) {
if (batch.token[i] < 0 || uint32_t(batch.token[i]) >= model.vocab.n_tokens()) {
LLAMA_LOG_ERROR("%s: invalid token[%d] = %d\n", __func__, i, batch.token[i]);
return -1;
}
}
}
GGML_ASSERT(n_tokens_all <= cparams.n_batch);
GGML_ASSERT((cparams.causal_attn || cparams.n_ubatch >= n_tokens_all) && "non-causal attention requires n_ubatch >= n_tokens");
lctx.n_queued_tokens += n_tokens_all;
lctx.embd_seq.clear();
// count outputs
if (batch.logits && !embd_pooled) {
for (uint32_t i = 0; i < n_tokens_all; ++i) {
n_outputs += batch.logits[i] != 0;
}
} else if (lctx.logits_all || embd_pooled) {
n_outputs = n_tokens_all;
} else {
// keep last output only
n_outputs = 1;
}
lctx.sbatch.from_batch(batch, n_embd,
/* simple_split */ !lctx.kv_self.recurrent,
/* logits_all */ n_outputs == n_tokens_all);
// reserve output buffer
if (llama_output_reserve(lctx, n_outputs) < n_outputs) {
LLAMA_LOG_ERROR("%s: could not reserve space for batch with %u outputs\n", __func__, n_outputs);
return -2;
};
return 0;
}
static int llama_prepare_ubatch(
llama_context & lctx,
llama_kv_slot_restorer & kv_slot_restorer,
llama_ubatch & ubatch,
const uint32_t n_outputs,
const uint32_t n_tokens_all) {
GGML_ASSERT(lctx.sbatch.n_tokens > 0);
auto & kv_self = lctx.kv_self;
const auto & cparams = lctx.cparams;
const auto & hparams = lctx.model.hparams;
// this indicates we are doing pooled embedding, so we ignore batch.logits and output all tokens
const bool embd_pooled = cparams.embeddings && cparams.pooling_type != LLAMA_POOLING_TYPE_NONE;
if (lctx.kv_self.recurrent) {
if (embd_pooled) {
// Pooled embeddings cannot be split across ubatches (yet)
ubatch = lctx.sbatch.split_seq(cparams.n_ubatch);
} else {
// recurrent model architectures are easier to implement
// with equal-length sequences
ubatch = lctx.sbatch.split_equal(cparams.n_ubatch);
}
} else {
ubatch = lctx.sbatch.split_simple(cparams.n_ubatch);
}
// count the outputs in this u_batch
{
int32_t n_outputs_new = 0;
if (n_outputs == n_tokens_all) {
n_outputs_new = ubatch.n_tokens;
} else {
GGML_ASSERT(ubatch.output);
for (uint32_t i = 0; i < ubatch.n_tokens; i++) {
n_outputs_new += int32_t(ubatch.output[i] != 0);
}
}
// needs to happen before the graph is built
lctx.n_outputs = n_outputs_new;
}
// non-causal masks do not use the KV cache
if (hparams.causal_attn) {
llama_kv_cache_update(&lctx);
// if we have enough unused cells before the current head ->
// better to start searching from the beginning of the cache, hoping to fill it
if (kv_self.head > kv_self.used + 2*ubatch.n_tokens) {
kv_self.head = 0;
}
const auto slot = llama_kv_cache_find_slot(kv_self, ubatch);
if (!slot) {
return 1;
}
kv_slot_restorer.save(slot);
if (!kv_self.recurrent) {
// a heuristic, to avoid attending the full cache if it is not yet utilized
// after enough generations, the benefit from this heuristic disappears
// if we start defragmenting the cache, the benefit from this will be more important
const uint32_t pad = llama_kv_cache_get_padding(cparams);
kv_self.n = std::min(kv_self.size, std::max(pad, GGML_PAD(llama_kv_cache_cell_max(kv_self), pad)));
//kv_self.n = llama_kv_cache_cell_max(kv_self);
}
}
return 0;
}
// decode a batch of tokens by evaluating the transformer
// in case of unsuccessful decoding (error or warning),
// the kv_cache state will be returned to its original state
// (for non-recurrent models) or cleaned (for recurrent models)
//
// - lctx: llama context
// - batch: batch to evaluate
// - inp_batch: batch to evaluate
//
// return 0 on success
// return positive int on warning
@ -8455,37 +8579,18 @@ static int llama_decode_impl(
return -1;
}
// temporary allocate memory for the input batch if needed
// temporarily allocate memory for the input batch if needed
llama_batch_allocr batch_allocr(inp_batch, inp_batch.pos ? -1 : lctx.kv_self.max_pos() + 1);
const llama_batch & batch = batch_allocr.batch;
const uint32_t n_tokens_all = batch.n_tokens;
const auto & model = lctx.model;
const auto & vocab = model.vocab;
const auto & hparams = model.hparams;
const auto & cparams = lctx.cparams;
GGML_ASSERT((!batch.token && batch.embd) || (batch.token && !batch.embd)); // NOLINT
if (batch.token) {
for (uint32_t i = 0; i < n_tokens_all; ++i) {
if (batch.token[i] < 0 || (uint32_t) batch.token[i] >= model.vocab.n_tokens()) {
LLAMA_LOG_ERROR("%s: invalid token[%d] = %d\n", __func__, i, batch.token[i]);
return -1;
}
}
}
GGML_ASSERT(n_tokens_all <= cparams.n_batch);
GGML_ASSERT((cparams.causal_attn || cparams.n_ubatch >= n_tokens_all) && "non-causal attention requires n_ubatch >= n_tokens");
if (lctx.t_compute_start_us == 0) {
lctx.t_compute_start_us = ggml_time_us();
}
lctx.n_queued_tokens += n_tokens_all;
auto & kv_self = lctx.kv_self;
llama_kv_slot_restorer kv_slot_restorer(kv_self);
@ -8495,99 +8600,27 @@ static int llama_decode_impl(
uint32_t n_outputs = 0;
uint32_t n_outputs_prev = 0;
const auto n_ubatch = cparams.n_ubatch;
// this indicates we are doing pooled embedding, so we ignore batch.logits and output all tokens
const bool embd_pooled = cparams.embeddings && cparams.pooling_type != LLAMA_POOLING_TYPE_NONE;
lctx.embd_seq.clear();
// count outputs
if (batch.logits && !embd_pooled) {
for (uint32_t i = 0; i < n_tokens_all; ++i) {
n_outputs += batch.logits[i] != 0;
{
const int ret = llama_prepare_sbatch(lctx, batch, n_outputs);
if (ret != 0) {
return ret;
}
} else if (lctx.logits_all || embd_pooled) {
n_outputs = n_tokens_all;
} else {
// keep last output only
n_outputs = 1;
}
lctx.sbatch.from_batch(batch, n_embd,
/* simple_split */ !kv_self.recurrent,
/* logits_all */ n_outputs == n_tokens_all);
// reserve output buffer
if (llama_output_reserve(lctx, n_outputs) < n_outputs) {
LLAMA_LOG_ERROR("%s: could not reserve space for batch with %u outputs\n", __func__, n_outputs);
return -2;
};
while (lctx.sbatch.n_tokens > 0) {
llama_ubatch ubatch;
if (kv_self.recurrent) {
if (embd_pooled) {
// Pooled embeddings cannot be split across ubatches (yet)
ubatch = lctx.sbatch.split_seq(n_ubatch);
} else {
// recurrent model architectures are easier to implement
// with equal-length sequences
ubatch = lctx.sbatch.split_equal(n_ubatch);
}
} else {
ubatch = lctx.sbatch.split_simple(n_ubatch);
}
const uint32_t n_tokens = ubatch.n_tokens;
// count the outputs in this u_batch
{
int32_t n_outputs_new = 0;
if (n_outputs == n_tokens_all) {
n_outputs_new = n_tokens;
} else {
GGML_ASSERT(ubatch.output);
for (uint32_t i = 0; i < n_tokens; i++) {
n_outputs_new += (int32_t) (ubatch.output[i] != 0);
}
const int ret = llama_prepare_ubatch(lctx, kv_slot_restorer, ubatch, n_outputs, batch.n_tokens);
if (ret != 0) {
return ret;
}
// needs to happen before the graph is built
lctx.n_outputs = n_outputs_new;
}
int n_threads = n_tokens == 1 ? cparams.n_threads : cparams.n_threads_batch;
ggml_threadpool_t threadpool = n_tokens == 1 ? lctx.threadpool : lctx.threadpool_batch;
const int n_threads = ubatch.n_tokens == 1 ? cparams.n_threads : cparams.n_threads_batch;
ggml_threadpool_t threadpool = ubatch.n_tokens == 1 ? lctx.threadpool : lctx.threadpool_batch;
GGML_ASSERT(n_threads > 0);
// non-causal masks do not use the KV cache
if (hparams.causal_attn) {
llama_kv_cache_update(&lctx);
// if we have enough unused cells before the current head ->
// better to start searching from the beginning of the cache, hoping to fill it
if (kv_self.head > kv_self.used + 2*n_tokens) {
kv_self.head = 0;
}
const auto slot = llama_kv_cache_find_slot(kv_self, ubatch);
if (!slot) {
return 1;
}
kv_slot_restorer.save(slot);
if (!kv_self.recurrent) {
// a heuristic, to avoid attending the full cache if it is not yet utilized
// after enough generations, the benefit from this heuristic disappears
// if we start defragmenting the cache, the benefit from this will be more important
const uint32_t pad = llama_kv_cache_get_padding(cparams);
kv_self.n = std::min(kv_self.size, std::max(pad, GGML_PAD(llama_kv_cache_cell_max(kv_self), pad)));
//kv_self.n = llama_kv_cache_cell_max(kv_self);
}
}
//printf("kv_self.n = %5d, kv_self.used = %5d, kv_self.head = %5d\n", kv_self.n, kv_self.used, kv_self.head);
ggml_backend_sched_reset(lctx.sched.get());
@ -8640,7 +8673,7 @@ static int llama_decode_impl(
// update the kv ring buffer
{
kv_self.head += n_tokens;
kv_self.head += ubatch.n_tokens;
// Ensure kv cache head points to a valid index.
if (kv_self.head >= kv_self.size) {
@ -9405,6 +9438,7 @@ static struct llama_model * llama_model_load_from_file_impl(
model->devices.push_back(*dev);
}
} else {
std::vector<ggml_backend_dev_t> rpc_servers;
// use all available devices
for (size_t i = 0; i < ggml_backend_dev_count(); ++i) {
ggml_backend_dev_t dev = ggml_backend_dev_get(i);
@ -9415,10 +9449,19 @@ static struct llama_model * llama_model_load_from_file_impl(
break;
case GGML_BACKEND_DEVICE_TYPE_GPU:
model->devices.push_back(dev);
ggml_backend_reg_t reg = ggml_backend_dev_backend_reg(dev);
if (ggml_backend_reg_name(reg) == std::string("RPC")) {
rpc_servers.push_back(dev);
} else {
model->devices.push_back(dev);
}
break;
}
}
// add RPC servers at the front of the list
if (!rpc_servers.empty()) {
model->devices.insert(model->devices.begin(), rpc_servers.begin(), rpc_servers.end());
}
}
// if using single GPU mode, remove all except the main GPU

1
tests/CMakeLists.txt
View file

@ -96,6 +96,7 @@ if (NOT WIN32)
llama_target_and_test(test-grammar-parser.cpp)
llama_target_and_test(test-grammar-integration.cpp)
llama_target_and_test(test-llama-grammar.cpp)
llama_target_and_test(test-chat.cpp)
# TODO: disabled on loongarch64 because the ggml-ci node lacks Python 3.8
if (NOT ${CMAKE_SYSTEM_PROCESSOR} MATCHES "loongarch64")
llama_target_and_test(test-json-schema-to-grammar.cpp WORKING_DIRECTORY ${CMAKE_CURRENT_SOURCE_DIR}/..)

45
tests/test-backend-ops.cpp
View file

@ -2347,11 +2347,12 @@ struct test_soft_max : public test_case {
const ggml_type type;
const std::array<int64_t, 4> ne;
const bool mask;
const ggml_type m_prec;
const float scale;
const float max_bias;
std::string vars() override {
return VARS_TO_STR5(type, ne, mask, scale, max_bias);
return VARS_TO_STR6(type, ne, mask, m_prec, scale, max_bias);
}
// the 1024 test with bias occasionally fails:
@ -2363,9 +2364,10 @@ struct test_soft_max : public test_case {
test_soft_max(ggml_type type = GGML_TYPE_F32,
std::array<int64_t, 4> ne = {10, 5, 4, 3},
bool mask = false,
ggml_type m_prec = GGML_TYPE_F32,
float scale = 1.0f,
float max_bias = 0.0f)
: type(type), ne(ne), mask(mask), scale(scale), max_bias(max_bias) {}
: type(type), ne(ne), mask(mask), m_prec(m_prec), scale(scale), max_bias(max_bias) {}
ggml_tensor * build_graph(ggml_context * ctx) override {
ggml_tensor * a = ggml_new_tensor(ctx, type, 4, ne.data());
@ -2374,7 +2376,7 @@ struct test_soft_max : public test_case {
ggml_tensor * mask = nullptr;
if (this->mask) {
mask = ggml_new_tensor_2d(ctx, GGML_TYPE_F32, ne[0], ne[1]);
mask = ggml_new_tensor_2d(ctx, m_prec, ne[0], ne[1]);
ggml_set_name(mask, "mask");
}
@ -4150,17 +4152,28 @@ static std::vector<std::unique_ptr<test_case>> make_test_cases_eval() {
for (float scale : {1.0f, 0.1f}) {
for (int64_t ne0 : {16, 1024}) {
for (int64_t ne1 : {16, 1024}) {
test_cases.emplace_back(new test_soft_max(GGML_TYPE_F32, {ne0, ne1, 1, 1}, mask, scale, max_bias));
test_cases.emplace_back(new test_soft_max(GGML_TYPE_F32, {ne0-1, ne1-1, 1, 1}, mask, scale, max_bias));
if (mask) {
for (ggml_type m_prec : {GGML_TYPE_F32, GGML_TYPE_F16}) {
test_cases.emplace_back(new test_soft_max(GGML_TYPE_F32, {ne0, ne1, 1, 1}, mask, m_prec, scale, max_bias));
test_cases.emplace_back(new test_soft_max(GGML_TYPE_F32, {ne0-1, ne1-1, 1, 1}, mask, m_prec, scale, max_bias));
}
} else {
/* The precision of mask here doesn't matter as boolean mask is false */
test_cases.emplace_back(new test_soft_max(GGML_TYPE_F32, {ne0, ne1, 1, 1}, mask, GGML_TYPE_F32, scale, max_bias));
test_cases.emplace_back(new test_soft_max(GGML_TYPE_F32, {ne0-1, ne1-1, 1, 1}, mask, GGML_TYPE_F32, scale, max_bias));
}
}
}
}
}
}
test_cases.emplace_back(new test_soft_max(GGML_TYPE_F32, {16, 2, 32, 1}, true, 0.1f, 0.0f));
test_cases.emplace_back(new test_soft_max(GGML_TYPE_F32, {16, 2, 32, 1}, false, 0.1f, 0.0f));
test_cases.emplace_back(new test_soft_max(GGML_TYPE_F32, {32, 2, 32, 1}, true, 0.1f, 0.0f));
test_cases.emplace_back(new test_soft_max(GGML_TYPE_F32, {32, 2, 32, 1}, true, 0.1f, 8.0f));
test_cases.emplace_back(new test_soft_max(GGML_TYPE_F32, {16, 2, 32, 1}, true, GGML_TYPE_F32, 0.1f, 0.0f));
test_cases.emplace_back(new test_soft_max(GGML_TYPE_F32, {16, 2, 32, 1}, true, GGML_TYPE_F16, 0.1f, 0.0f));
test_cases.emplace_back(new test_soft_max(GGML_TYPE_F32, {16, 2, 32, 1}, false, GGML_TYPE_F32, 0.1f, 0.0f));
test_cases.emplace_back(new test_soft_max(GGML_TYPE_F32, {32, 2, 32, 1}, true, GGML_TYPE_F32, 0.1f, 0.0f));
test_cases.emplace_back(new test_soft_max(GGML_TYPE_F32, {32, 2, 32, 1}, true, GGML_TYPE_F16, 0.1f, 0.0f));
test_cases.emplace_back(new test_soft_max(GGML_TYPE_F32, {32, 2, 32, 1}, true, GGML_TYPE_F32, 0.1f, 8.0f));
test_cases.emplace_back(new test_soft_max(GGML_TYPE_F32, {32, 2, 32, 1}, true, GGML_TYPE_F16, 0.1f, 8.0f));
for (float max_bias : {0.0f, 8.0f}) {
for (float scale : {1.0f, 0.1f}) {
@ -4296,13 +4309,13 @@ static std::vector<std::unique_ptr<test_case>> make_test_cases_perf() {
test_cases.emplace_back(new test_cpy(GGML_TYPE_F32, GGML_TYPE_F32, {8192, 512, 2, 1}, {0, 2, 1, 3}));
test_cases.emplace_back(new test_cpy(GGML_TYPE_F32, GGML_TYPE_F32, {3072, 512, 2, 1}, {0, 2, 1, 3}));
test_cases.emplace_back(new test_soft_max(GGML_TYPE_F32, {4096, 4096, 5, 1}, false, 1.0f, 0.0f));
test_cases.emplace_back(new test_soft_max(GGML_TYPE_F32, {77, 4096, 5, 1}, false, 1.0f, 0.0f));
test_cases.emplace_back(new test_soft_max(GGML_TYPE_F32, {1024, 1024, 10, 1}, false, 1.0f, 0.0f));
test_cases.emplace_back(new test_soft_max(GGML_TYPE_F32, {77, 1024, 10, 1}, false, 1.0f, 0.0f));
test_cases.emplace_back(new test_soft_max(GGML_TYPE_F32, {256, 256, 20, 1}, false, 1.0f, 0.0f));
test_cases.emplace_back(new test_soft_max(GGML_TYPE_F32, {64, 64, 20, 1}, false, 1.0f, 0.0f));
test_cases.emplace_back(new test_soft_max(GGML_TYPE_F32, {77, 64, 20, 1}, false, 1.0f, 0.0f));
test_cases.emplace_back(new test_soft_max(GGML_TYPE_F32, {4096, 4096, 5, 1}, false, GGML_TYPE_F32, 1.0f, 0.0f));
test_cases.emplace_back(new test_soft_max(GGML_TYPE_F32, {77, 4096, 5, 1}, false, GGML_TYPE_F32, 1.0f, 0.0f));
test_cases.emplace_back(new test_soft_max(GGML_TYPE_F32, {1024, 1024, 10, 1}, false, GGML_TYPE_F32, 1.0f, 0.0f));
test_cases.emplace_back(new test_soft_max(GGML_TYPE_F32, {77, 1024, 10, 1}, false, GGML_TYPE_F32, 1.0f, 0.0f));
test_cases.emplace_back(new test_soft_max(GGML_TYPE_F32, {256, 256, 20, 1}, false, GGML_TYPE_F32, 1.0f, 0.0f));
test_cases.emplace_back(new test_soft_max(GGML_TYPE_F32, {64, 64, 20, 1}, false, GGML_TYPE_F32, 1.0f, 0.0f));
test_cases.emplace_back(new test_soft_max(GGML_TYPE_F32, {77, 64, 20, 1}, false, GGML_TYPE_F32, 1.0f, 0.0f));
test_cases.emplace_back(new test_argmax(GGML_TYPE_F32, {32, 10, 1, 1}));
test_cases.emplace_back(new test_argmax(GGML_TYPE_F32, {1024, 10, 1, 1}));

10
tests/test-chat-template.cpp
View file

@ -328,7 +328,7 @@ int main(void) {
// test llama_chat_format_single for system message
printf("\n\n=== llama_chat_format_single (system message) ===\n\n");
std::vector<common_chat_msg> chat2;
common_chat_msg sys_msg{"system", "You are a helpful assistant"};
common_chat_msg sys_msg{"system", "You are a helpful assistant", {}};
auto fmt_sys = [&](std::string tmpl_str) {
minja::chat_template tmpl(tmpl_str, "", "");
@ -352,10 +352,10 @@ int main(void) {
// test llama_chat_format_single for user message
printf("\n\n=== llama_chat_format_single (user message) ===\n\n");
chat2.push_back({"system", "You are a helpful assistant"});
chat2.push_back({"user", "Hello"});
chat2.push_back({"assistant", "I am assistant"});
common_chat_msg new_msg{"user", "How are you"};
chat2.push_back({"system", "You are a helpful assistant", {}});
chat2.push_back({"user", "Hello", {}});
chat2.push_back({"assistant", "I am assistant", {}});
common_chat_msg new_msg{"user", "How are you", {}};
auto fmt_single = [&](std::string tmpl_str) {
minja::chat_template tmpl(tmpl_str, "", "");

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