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1 Commits

Author SHA1 Message Date
Francis Couture-Harpin
64b7d85891 llama : fix command-r inference 2024-03-28 06:22:24 -04:00
950 changed files with 154271 additions and 191015 deletions

View File

@@ -15,7 +15,7 @@ node('x86_runner1'){ // Running on x86 runner containing latest vecto
stage('Running llama.cpp'){
sh'''#!/bin/bash
module load gnu-bin2/0.1 # loading latest versions of vector qemu and vector gcc
qemu-riscv64 -L /softwares/gnu-bin2/sysroot -cpu rv64,v=true,vlen=256,elen=64,vext_spec=v1.0 ./llama-cli -m /home/alitariq/codellama-7b.Q4_K_M.gguf -p "Anything" -n 9 > llama_log.txt # Running llama.cpp on vector qemu-riscv64
qemu-riscv64 -L /softwares/gnu-bin2/sysroot -cpu rv64,v=true,vlen=256,elen=64,vext_spec=v1.0 ./main -m /home/alitariq/codellama-7b.Q4_K_M.gguf -p "Anything" -n 9 > llama_log.txt # Running llama.cpp on vector qemu-riscv64
cat llama_log.txt # Printing results
'''
}

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@@ -1,16 +1,18 @@
ARG UBUNTU_VERSION=22.04
# This needs to generally match the container host's environment.
ARG CUDA_VERSION=12.6.0
ARG CUDA_VERSION=11.7.1
# Target the CUDA build image
ARG BASE_CUDA_DEV_CONTAINER=nvidia/cuda:${CUDA_VERSION}-devel-ubuntu${UBUNTU_VERSION}
FROM ${BASE_CUDA_DEV_CONTAINER} AS build
FROM ${BASE_CUDA_DEV_CONTAINER} as build
# CUDA architecture to build for (defaults to all supported archs)
ARG CUDA_DOCKER_ARCH=default
# Unless otherwise specified, we make a fat build.
ARG CUDA_DOCKER_ARCH=all
RUN apt-get update && \
apt-get install -y build-essential cmake python3 python3-pip git libcurl4-openssl-dev libgomp1
apt-get install -y build-essential python3 python3-pip git
COPY requirements.txt requirements.txt
COPY requirements requirements
@@ -22,12 +24,11 @@ WORKDIR /app
COPY . .
# Use the default CUDA archs if not specified
RUN if [ "${CUDA_DOCKER_ARCH}" != "default" ]; then \
export CMAKE_ARGS="-DCMAKE_CUDA_ARCHITECTURES=${CUDA_DOCKER_ARCH}"; \
fi && \
cmake -B build -DGGML_CUDA=ON -DLLAMA_CURL=ON ${CMAKE_ARGS} -DCMAKE_EXE_LINKER_FLAGS=-Wl,--allow-shlib-undefined . && \
cmake --build build --config Release -j$(nproc) && \
cp build/bin/* .
# Set nvcc architecture
ENV CUDA_DOCKER_ARCH=${CUDA_DOCKER_ARCH}
# Enable CUDA
ENV LLAMA_CUDA=1
RUN make
ENTRYPOINT ["/app/.devops/tools.sh"]

View File

@@ -1,26 +0,0 @@
ARG UBUNTU_VERSION=22.04
# This needs to generally match the container host's environment.
ARG MUSA_VERSION=rc3.1.0
# Target the MUSA build image
ARG BASE_MUSA_DEV_CONTAINER=mthreads/musa:${MUSA_VERSION}-devel-ubuntu${UBUNTU_VERSION}
FROM ${BASE_MUSA_DEV_CONTAINER} AS build
RUN apt-get update && \
apt-get install -y build-essential cmake python3 python3-pip git libcurl4-openssl-dev libgomp1
COPY requirements.txt requirements.txt
COPY requirements requirements
RUN pip install --upgrade pip setuptools wheel \
&& pip install -r requirements.txt
WORKDIR /app
COPY . .
RUN cmake -B build -DGGML_MUSA=ON -DLLAMA_CURL=ON ${CMAKE_ARGS} -DCMAKE_EXE_LINKER_FLAGS=-Wl,--allow-shlib-undefined . && \
cmake --build build --config Release -j$(nproc) && \
cp build/bin/* .
ENTRYPOINT ["/app/.devops/tools.sh"]

View File

@@ -6,12 +6,12 @@ ARG ROCM_VERSION=5.6
# Target the CUDA build image
ARG BASE_ROCM_DEV_CONTAINER=rocm/dev-ubuntu-${UBUNTU_VERSION}:${ROCM_VERSION}-complete
FROM ${BASE_ROCM_DEV_CONTAINER} AS build
FROM ${BASE_ROCM_DEV_CONTAINER} as build
# Unless otherwise specified, we make a fat build.
# List from https://github.com/ggerganov/llama.cpp/pull/1087#issuecomment-1682807878
# This is mostly tied to rocBLAS supported archs.
ARG ROCM_DOCKER_ARCH="\
ARG ROCM_DOCKER_ARCH=\
gfx803 \
gfx900 \
gfx906 \
@@ -21,7 +21,7 @@ ARG ROCM_DOCKER_ARCH="\
gfx1030 \
gfx1100 \
gfx1101 \
gfx1102"
gfx1102
COPY requirements.txt requirements.txt
COPY requirements requirements
@@ -34,17 +34,12 @@ WORKDIR /app
COPY . .
# Set nvcc architecture
ENV AMDGPU_TARGETS=${ROCM_DOCKER_ARCH}
ENV GPU_TARGETS=${ROCM_DOCKER_ARCH}
# Enable ROCm
ENV GGML_HIPBLAS=1
ENV LLAMA_HIPBLAS=1
ENV CC=/opt/rocm/llvm/bin/clang
ENV CXX=/opt/rocm/llvm/bin/clang++
# Enable cURL
ENV LLAMA_CURL=1
RUN apt-get update && \
apt-get install -y libcurl4-openssl-dev
RUN make -j$(nproc)
RUN make
ENTRYPOINT ["/app/.devops/tools.sh"]

View File

@@ -1,9 +1,9 @@
ARG UBUNTU_VERSION=22.04
FROM ubuntu:$UBUNTU_VERSION AS build
FROM ubuntu:$UBUNTU_VERSION as build
RUN apt-get update && \
apt-get install -y build-essential python3 python3-pip git libcurl4-openssl-dev libgomp1
apt-get install -y build-essential python3 python3-pip git
COPY requirements.txt requirements.txt
COPY requirements requirements
@@ -15,10 +15,7 @@ WORKDIR /app
COPY . .
ENV LLAMA_CURL=1
RUN make -j$(nproc)
RUN make
ENV LC_ALL=C.utf8

View File

@@ -1,44 +0,0 @@
ARG ASCEND_VERSION=8.0.rc2.alpha003-910b-openeuler22.03-py3.8
FROM cosdt/cann:$ASCEND_VERSION AS build
WORKDIR /app
COPY . .
RUN yum install -y gcc g++ cmake make
ENV ASCEND_TOOLKIT_HOME=/usr/local/Ascend/ascend-toolkit/latest
ENV LIBRARY_PATH=${ASCEND_TOOLKIT_HOME}/lib64:$LIBRARY_PATH
ENV LD_LIBRARY_PATH=${ASCEND_TOOLKIT_HOME}/lib64:${ASCEND_TOOLKIT_HOME}/lib64/plugin/opskernel:${ASCEND_TOOLKIT_HOME}/lib64/plugin/nnengine:${ASCEND_TOOLKIT_HOME}/opp/built-in/op_impl/ai_core/tbe/op_tiling:${LD_LIBRARY_PATH}
ENV PYTHONPATH=${ASCEND_TOOLKIT_HOME}/python/site-packages:${ASCEND_TOOLKIT_HOME}/opp/built-in/op_impl/ai_core/tbe:${PYTHONPATH}
ENV PATH=${ASCEND_TOOLKIT_HOME}/bin:${ASCEND_TOOLKIT_HOME}/compiler/ccec_compiler/bin:${PATH}
ENV ASCEND_AICPU_PATH=${ASCEND_TOOLKIT_HOME}
ENV ASCEND_OPP_PATH=${ASCEND_TOOLKIT_HOME}/opp
ENV TOOLCHAIN_HOME=${ASCEND_TOOLKIT_HOME}/toolkit
ENV ASCEND_HOME_PATH=${ASCEND_TOOLKIT_HOME}
# find libascend_hal.so, because the drive hasn`t been mounted.
ENV LD_LIBRARY_PATH=${ASCEND_TOOLKIT_HOME}/runtime/lib64/stub:$LD_LIBRARY_PATH
RUN echo "Building with static libs" && \
source /usr/local/Ascend/ascend-toolkit/set_env.sh --force && \
cmake -B build -DGGML_CANN=ON -DBUILD_SHARED_LIBS=OFF && \
cmake --build build --config Release --target llama-cli
# TODO: use image with NNRT
FROM cosdt/cann:$ASCEND_VERSION AS runtime
COPY --from=build /app/build/bin/llama-cli /llama-cli
ENV LC_ALL=C.utf8
ENV ASCEND_TOOLKIT_HOME=/usr/local/Ascend/ascend-toolkit/latest
ENV LIBRARY_PATH=${ASCEND_TOOLKIT_HOME}/lib64:$LIBRARY_PATH
ENV LD_LIBRARY_PATH=${ASCEND_TOOLKIT_HOME}/lib64:${ASCEND_TOOLKIT_HOME}/lib64/plugin/opskernel:${ASCEND_TOOLKIT_HOME}/lib64/plugin/nnengine:${ASCEND_TOOLKIT_HOME}/opp/built-in/op_impl/ai_core/tbe/op_tiling:${LD_LIBRARY_PATH}
ENV PYTHONPATH=${ASCEND_TOOLKIT_HOME}/python/site-packages:${ASCEND_TOOLKIT_HOME}/opp/built-in/op_impl/ai_core/tbe:${PYTHONPATH}
ENV PATH=${ASCEND_TOOLKIT_HOME}/bin:${ASCEND_TOOLKIT_HOME}/compiler/ccec_compiler/bin:${PATH}
ENV ASCEND_AICPU_PATH=${ASCEND_TOOLKIT_HOME}
ENV ASCEND_OPP_PATH=${ASCEND_TOOLKIT_HOME}/opp
ENV TOOLCHAIN_HOME=${ASCEND_TOOLKIT_HOME}/toolkit
ENV ASCEND_HOME_PATH=${ASCEND_TOOLKIT_HOME}
ENTRYPOINT ["/llama-cli" ]

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@@ -1,37 +0,0 @@
ARG UBUNTU_VERSION=22.04
# This needs to generally match the container host's environment.
ARG CUDA_VERSION=12.6.0
# Target the CUDA build image
ARG BASE_CUDA_DEV_CONTAINER=nvidia/cuda:${CUDA_VERSION}-devel-ubuntu${UBUNTU_VERSION}
# Target the CUDA runtime image
ARG BASE_CUDA_RUN_CONTAINER=nvidia/cuda:${CUDA_VERSION}-runtime-ubuntu${UBUNTU_VERSION}
FROM ${BASE_CUDA_DEV_CONTAINER} AS build
# CUDA architecture to build for (defaults to all supported archs)
ARG CUDA_DOCKER_ARCH=default
RUN apt-get update && \
apt-get install -y build-essential git cmake
WORKDIR /app
COPY . .
# Use the default CUDA archs if not specified
RUN if [ "${CUDA_DOCKER_ARCH}" != "default" ]; then \
export CMAKE_ARGS="-DCMAKE_CUDA_ARCHITECTURES=${CUDA_DOCKER_ARCH}"; \
fi && \
cmake -B build -DGGML_CUDA=ON ${CMAKE_ARGS} -DCMAKE_EXE_LINKER_FLAGS=-Wl,--allow-shlib-undefined . && \
cmake --build build --config Release --target llama-cli -j$(nproc)
FROM ${BASE_CUDA_RUN_CONTAINER} AS runtime
RUN apt-get update && \
apt-get install -y libgomp1
COPY --from=build /app/build/ggml/src/libggml.so /libggml.so
COPY --from=build /app/build/src/libllama.so /libllama.so
COPY --from=build /app/build/bin/llama-cli /llama-cli
ENTRYPOINT [ "/llama-cli" ]

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@@ -1,28 +0,0 @@
ARG ONEAPI_VERSION=2024.1.1-devel-ubuntu22.04
FROM intel/oneapi-basekit:$ONEAPI_VERSION AS build
ARG GGML_SYCL_F16=OFF
RUN apt-get update && \
apt-get install -y git
WORKDIR /app
COPY . .
RUN if [ "${GGML_SYCL_F16}" = "ON" ]; then \
echo "GGML_SYCL_F16 is set" && \
export OPT_SYCL_F16="-DGGML_SYCL_F16=ON"; \
fi && \
echo "Building with static libs" && \
cmake -B build -DGGML_SYCL=ON -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx \
${OPT_SYCL_F16} -DBUILD_SHARED_LIBS=OFF && \
cmake --build build --config Release --target llama-cli
FROM intel/oneapi-basekit:$ONEAPI_VERSION AS runtime
COPY --from=build /app/build/bin/llama-cli /llama-cli
ENV LC_ALL=C.utf8
ENTRYPOINT [ "/llama-cli" ]

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@@ -1,30 +0,0 @@
ARG UBUNTU_VERSION=22.04
# This needs to generally match the container host's environment.
ARG MUSA_VERSION=rc3.1.0
# Target the MUSA build image
ARG BASE_MUSA_DEV_CONTAINER=mthreads/musa:${MUSA_VERSION}-devel-ubuntu${UBUNTU_VERSION}
# Target the MUSA runtime image
ARG BASE_MUSA_RUN_CONTAINER=mthreads/musa:${MUSA_VERSION}-runtime-ubuntu${UBUNTU_VERSION}
FROM ${BASE_MUSA_DEV_CONTAINER} AS build
RUN apt-get update && \
apt-get install -y build-essential git cmake
WORKDIR /app
COPY . .
RUN cmake -B build -DGGML_MUSA=ON ${CMAKE_ARGS} -DCMAKE_EXE_LINKER_FLAGS=-Wl,--allow-shlib-undefined . && \
cmake --build build --config Release --target llama-cli -j$(nproc)
FROM ${BASE_MUSA_RUN_CONTAINER} AS runtime
RUN apt-get update && \
apt-get install -y libgomp1
COPY --from=build /app/build/ggml/src/libggml.so /libggml.so
COPY --from=build /app/build/src/libllama.so /libllama.so
COPY --from=build /app/build/bin/llama-cli /llama-cli
ENTRYPOINT [ "/llama-cli" ]

View File

@@ -1,23 +0,0 @@
ARG UBUNTU_VERSION=22.04
FROM ubuntu:$UBUNTU_VERSION AS build
RUN apt-get update && \
apt-get install -y build-essential git
WORKDIR /app
COPY . .
RUN make -j$(nproc) llama-cli
FROM ubuntu:$UBUNTU_VERSION AS runtime
RUN apt-get update && \
apt-get install -y libgomp1
COPY --from=build /app/llama-cli /llama-cli
ENV LC_ALL=C.utf8
ENTRYPOINT [ "/llama-cli" ]

View File

@@ -0,0 +1,84 @@
# SRPM for building from source and packaging an RPM for RPM-based distros.
# https://fedoraproject.org/wiki/How_to_create_an_RPM_package
# Built and maintained by John Boero - boeroboy@gmail.com
# In honor of Seth Vidal https://www.redhat.com/it/blog/thank-you-seth-vidal
# Notes for llama.cpp:
# 1. Tags are currently based on hash - which will not sort asciibetically.
# We need to declare standard versioning if people want to sort latest releases.
# 2. Builds for CUDA/OpenCL support are separate, with different depenedencies.
# 3. NVidia's developer repo must be enabled with nvcc, cublas, clblas, etc installed.
# Example: https://developer.download.nvidia.com/compute/cuda/repos/fedora37/x86_64/cuda-fedora37.repo
# 4. OpenCL/CLBLAST support simply requires the ICD loader and basic opencl libraries.
# It is up to the user to install the correct vendor-specific support.
Name: llama.cpp-clblast
Version: %( date "+%%Y%%m%%d" )
Release: 1%{?dist}
Summary: OpenCL Inference of LLaMA model in C/C++
License: MIT
Source0: https://github.com/ggerganov/llama.cpp/archive/refs/heads/master.tar.gz
BuildRequires: coreutils make gcc-c++ git mesa-libOpenCL-devel clblast-devel
Requires: clblast
URL: https://github.com/ggerganov/llama.cpp
%define debug_package %{nil}
%define source_date_epoch_from_changelog 0
%description
CPU inference for Meta's Lllama2 models using default options.
%prep
%setup -n llama.cpp-master
%build
make -j LLAMA_CLBLAST=1
%install
mkdir -p %{buildroot}%{_bindir}/
cp -p main %{buildroot}%{_bindir}/llamaclblast
cp -p server %{buildroot}%{_bindir}/llamaclblastserver
cp -p simple %{buildroot}%{_bindir}/llamaclblastsimple
mkdir -p %{buildroot}/usr/lib/systemd/system
%{__cat} <<EOF > %{buildroot}/usr/lib/systemd/system/llamaclblast.service
[Unit]
Description=Llama.cpp server, CPU only (no GPU support in this build).
After=syslog.target network.target local-fs.target remote-fs.target nss-lookup.target
[Service]
Type=simple
EnvironmentFile=/etc/sysconfig/llama
ExecStart=/usr/bin/llamaclblastserver $LLAMA_ARGS
ExecReload=/bin/kill -s HUP $MAINPID
Restart=never
[Install]
WantedBy=default.target
EOF
mkdir -p %{buildroot}/etc/sysconfig
%{__cat} <<EOF > %{buildroot}/etc/sysconfig/llama
LLAMA_ARGS="-m /opt/llama2/ggml-model-f32.bin"
EOF
%clean
rm -rf %{buildroot}
rm -rf %{_builddir}/*
%files
%{_bindir}/llamaclblast
%{_bindir}/llamaclblastserver
%{_bindir}/llamaclblastsimple
/usr/lib/systemd/system/llamaclblast.service
%config /etc/sysconfig/llama
%pre
%post
%preun
%postun
%changelog

View File

@@ -1,5 +1,5 @@
# SRPM for building from source and packaging an RPM for RPM-based distros.
# https://docs.fedoraproject.org/en-US/quick-docs/creating-rpm-packages
# https://fedoraproject.org/wiki/How_to_create_an_RPM_package
# Built and maintained by John Boero - boeroboy@gmail.com
# In honor of Seth Vidal https://www.redhat.com/it/blog/thank-you-seth-vidal
@@ -32,13 +32,13 @@ CPU inference for Meta's Lllama2 models using default options.
%setup -n llama.cpp-master
%build
make -j GGML_CUDA=1
make -j LLAMA_CUDA=1
%install
mkdir -p %{buildroot}%{_bindir}/
cp -p llama-cli %{buildroot}%{_bindir}/llama-cuda-cli
cp -p llama-server %{buildroot}%{_bindir}/llama-cuda-server
cp -p llama-simple %{buildroot}%{_bindir}/llama-cuda-simple
cp -p main %{buildroot}%{_bindir}/llamacppcuda
cp -p server %{buildroot}%{_bindir}/llamacppcudaserver
cp -p simple %{buildroot}%{_bindir}/llamacppcudasimple
mkdir -p %{buildroot}/usr/lib/systemd/system
%{__cat} <<EOF > %{buildroot}/usr/lib/systemd/system/llamacuda.service
@@ -49,7 +49,7 @@ After=syslog.target network.target local-fs.target remote-fs.target nss-lookup.t
[Service]
Type=simple
EnvironmentFile=/etc/sysconfig/llama
ExecStart=/usr/bin/llama-cuda-server $LLAMA_ARGS
ExecStart=/usr/bin/llamacppcudaserver $LLAMA_ARGS
ExecReload=/bin/kill -s HUP $MAINPID
Restart=never
@@ -67,9 +67,9 @@ rm -rf %{buildroot}
rm -rf %{_builddir}/*
%files
%{_bindir}/llama-cuda-cli
%{_bindir}/llama-cuda-server
%{_bindir}/llama-cuda-simple
%{_bindir}/llamacppcuda
%{_bindir}/llamacppcudaserver
%{_bindir}/llamacppcudasimple
/usr/lib/systemd/system/llamacuda.service
%config /etc/sysconfig/llama

View File

@@ -1,5 +1,5 @@
# SRPM for building from source and packaging an RPM for RPM-based distros.
# https://docs.fedoraproject.org/en-US/quick-docs/creating-rpm-packages
# https://fedoraproject.org/wiki/How_to_create_an_RPM_package
# Built and maintained by John Boero - boeroboy@gmail.com
# In honor of Seth Vidal https://www.redhat.com/it/blog/thank-you-seth-vidal
@@ -38,9 +38,9 @@ make -j
%install
mkdir -p %{buildroot}%{_bindir}/
cp -p llama-cli %{buildroot}%{_bindir}/llama-cli
cp -p llama-server %{buildroot}%{_bindir}/llama-server
cp -p llama-simple %{buildroot}%{_bindir}/llama-simple
cp -p main %{buildroot}%{_bindir}/llama
cp -p server %{buildroot}%{_bindir}/llamaserver
cp -p simple %{buildroot}%{_bindir}/llamasimple
mkdir -p %{buildroot}/usr/lib/systemd/system
%{__cat} <<EOF > %{buildroot}/usr/lib/systemd/system/llama.service
@@ -51,7 +51,7 @@ After=syslog.target network.target local-fs.target remote-fs.target nss-lookup.t
[Service]
Type=simple
EnvironmentFile=/etc/sysconfig/llama
ExecStart=/usr/bin/llama-server $LLAMA_ARGS
ExecStart=/usr/bin/llamaserver $LLAMA_ARGS
ExecReload=/bin/kill -s HUP $MAINPID
Restart=never
@@ -69,9 +69,9 @@ rm -rf %{buildroot}
rm -rf %{_builddir}/*
%files
%{_bindir}/llama-cli
%{_bindir}/llama-server
%{_bindir}/llama-simple
%{_bindir}/llama
%{_bindir}/llamaserver
%{_bindir}/llamasimple
/usr/lib/systemd/system/llama.service
%config /etc/sysconfig/llama

View File

@@ -1,42 +0,0 @@
ARG UBUNTU_VERSION=22.04
# This needs to generally match the container host's environment.
ARG CUDA_VERSION=12.6.0
# Target the CUDA build image
ARG BASE_CUDA_DEV_CONTAINER=nvidia/cuda:${CUDA_VERSION}-devel-ubuntu${UBUNTU_VERSION}
# Target the CUDA runtime image
ARG BASE_CUDA_RUN_CONTAINER=nvidia/cuda:${CUDA_VERSION}-runtime-ubuntu${UBUNTU_VERSION}
FROM ${BASE_CUDA_DEV_CONTAINER} AS build
# CUDA architecture to build for (defaults to all supported archs)
ARG CUDA_DOCKER_ARCH=default
RUN apt-get update && \
apt-get install -y build-essential git cmake libcurl4-openssl-dev
WORKDIR /app
COPY . .
# Use the default CUDA archs if not specified
RUN if [ "${CUDA_DOCKER_ARCH}" != "default" ]; then \
export CMAKE_ARGS="-DCMAKE_CUDA_ARCHITECTURES=${CUDA_DOCKER_ARCH}"; \
fi && \
cmake -B build -DGGML_CUDA=ON -DLLAMA_CURL=ON ${CMAKE_ARGS} -DCMAKE_EXE_LINKER_FLAGS=-Wl,--allow-shlib-undefined . && \
cmake --build build --config Release --target llama-server -j$(nproc)
FROM ${BASE_CUDA_RUN_CONTAINER} AS runtime
RUN apt-get update && \
apt-get install -y libcurl4-openssl-dev libgomp1 curl
COPY --from=build /app/build/ggml/src/libggml.so /libggml.so
COPY --from=build /app/build/src/libllama.so /libllama.so
COPY --from=build /app/build/bin/llama-server /llama-server
# Must be set to 0.0.0.0 so it can listen to requests from host machine
ENV LLAMA_ARG_HOST=0.0.0.0
HEALTHCHECK CMD [ "curl", "-f", "http://localhost:8080/health" ]
ENTRYPOINT [ "/llama-server" ]

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@@ -1,34 +0,0 @@
ARG ONEAPI_VERSION=2024.1.1-devel-ubuntu22.04
FROM intel/oneapi-basekit:$ONEAPI_VERSION AS build
ARG GGML_SYCL_F16=OFF
RUN apt-get update && \
apt-get install -y git libcurl4-openssl-dev
WORKDIR /app
COPY . .
RUN if [ "${GGML_SYCL_F16}" = "ON" ]; then \
echo "GGML_SYCL_F16 is set" && \
export OPT_SYCL_F16="-DGGML_SYCL_F16=ON"; \
fi && \
echo "Building with dynamic libs" && \
cmake -B build -DGGML_SYCL=ON -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx -DLLAMA_CURL=ON ${OPT_SYCL_F16} && \
cmake --build build --config Release --target llama-server
FROM intel/oneapi-basekit:$ONEAPI_VERSION AS runtime
RUN apt-get update && \
apt-get install -y libcurl4-openssl-dev curl
COPY --from=build /app/build/bin/llama-server /llama-server
ENV LC_ALL=C.utf8
# Must be set to 0.0.0.0 so it can listen to requests from host machine
ENV LLAMA_ARG_HOST=0.0.0.0
HEALTHCHECK CMD [ "curl", "-f", "http://localhost:8080/health" ]
ENTRYPOINT [ "/llama-server" ]

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@@ -1,35 +0,0 @@
ARG UBUNTU_VERSION=22.04
# This needs to generally match the container host's environment.
ARG MUSA_VERSION=rc3.1.0
# Target the MUSA build image
ARG BASE_MUSA_DEV_CONTAINER=mthreads/musa:${MUSA_VERSION}-devel-ubuntu${UBUNTU_VERSION}
# Target the MUSA runtime image
ARG BASE_MUSA_RUN_CONTAINER=mthreads/musa:${MUSA_VERSION}-runtime-ubuntu${UBUNTU_VERSION}
FROM ${BASE_MUSA_DEV_CONTAINER} AS build
RUN apt-get update && \
apt-get install -y build-essential git cmake libcurl4-openssl-dev
WORKDIR /app
COPY . .
RUN cmake -B build -DGGML_MUSA=ON -DLLAMA_CURL=ON ${CMAKE_ARGS} -DCMAKE_EXE_LINKER_FLAGS=-Wl,--allow-shlib-undefined . && \
cmake --build build --config Release --target llama-server -j$(nproc)
FROM ${BASE_MUSA_RUN_CONTAINER} AS runtime
RUN apt-get update && \
apt-get install -y libcurl4-openssl-dev libgomp1 curl
COPY --from=build /app/build/ggml/src/libggml.so /libggml.so
COPY --from=build /app/build/src/libllama.so /libllama.so
COPY --from=build /app/build/bin/llama-server /llama-server
# Must be set to 0.0.0.0 so it can listen to requests from host machine
ENV LLAMA_ARG_HOST=0.0.0.0
HEALTHCHECK CMD [ "curl", "-f", "http://localhost:8080/health" ]
ENTRYPOINT [ "/llama-server" ]

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@@ -1,31 +0,0 @@
ARG UBUNTU_VERSION=jammy
FROM ubuntu:$UBUNTU_VERSION AS build
# Install build tools
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 && \
apt update -y && \
apt-get install -y vulkan-sdk libcurl4-openssl-dev curl
# Build it
WORKDIR /app
COPY . .
RUN cmake -B build -DGGML_VULKAN=1 -DLLAMA_CURL=1 && \
cmake --build build --config Release --target llama-server
# Clean up
WORKDIR /
RUN cp /app/build/bin/llama-server /llama-server && \
rm -rf /app
ENV LC_ALL=C.utf8
# Must be set to 0.0.0.0 so it can listen to requests from host machine
ENV LLAMA_ARG_HOST=0.0.0.0
HEALTHCHECK CMD [ "curl", "-f", "http://localhost:8080/health" ]
ENTRYPOINT [ "/llama-server" ]

View File

@@ -1,29 +0,0 @@
ARG UBUNTU_VERSION=22.04
FROM ubuntu:$UBUNTU_VERSION AS build
RUN apt-get update && \
apt-get install -y build-essential git libcurl4-openssl-dev
WORKDIR /app
COPY . .
ENV LLAMA_CURL=1
RUN make -j$(nproc) llama-server
FROM ubuntu:$UBUNTU_VERSION AS runtime
RUN apt-get update && \
apt-get install -y libcurl4-openssl-dev libgomp1 curl
COPY --from=build /app/llama-server /llama-server
ENV LC_ALL=C.utf8
# Must be set to 0.0.0.0 so it can listen to requests from host machine
ENV LLAMA_ARG_HOST=0.0.0.0
HEALTHCHECK CMD [ "curl", "-f", "http://localhost:8080/health" ]
ENTRYPOINT [ "/llama-server" ]

View File

@@ -0,0 +1,32 @@
ARG UBUNTU_VERSION=22.04
# This needs to generally match the container host's environment.
ARG CUDA_VERSION=11.7.1
# Target the CUDA build image
ARG BASE_CUDA_DEV_CONTAINER=nvidia/cuda:${CUDA_VERSION}-devel-ubuntu${UBUNTU_VERSION}
# Target the CUDA runtime image
ARG BASE_CUDA_RUN_CONTAINER=nvidia/cuda:${CUDA_VERSION}-runtime-ubuntu${UBUNTU_VERSION}
FROM ${BASE_CUDA_DEV_CONTAINER} as build
# Unless otherwise specified, we make a fat build.
ARG CUDA_DOCKER_ARCH=all
RUN apt-get update && \
apt-get install -y build-essential git
WORKDIR /app
COPY . .
# Set nvcc architecture
ENV CUDA_DOCKER_ARCH=${CUDA_DOCKER_ARCH}
# Enable CUDA
ENV LLAMA_CUDA=1
RUN make
FROM ${BASE_CUDA_RUN_CONTAINER} as runtime
COPY --from=build /app/main /main
ENTRYPOINT [ "/main" ]

View File

@@ -0,0 +1,28 @@
ARG ONEAPI_VERSION=2024.0.1-devel-ubuntu22.04
FROM intel/oneapi-basekit:$ONEAPI_VERSION as build
ARG LLAMA_SYCL_F16=OFF
RUN apt-get update && \
apt-get install -y git
WORKDIR /app
COPY . .
RUN mkdir build && \
cd build && \
if [ "${LLAMA_SYCL_F16}" = "ON" ]; then \
echo "LLAMA_SYCL_F16 is set" && \
export OPT_SYCL_F16="-DLLAMA_SYCL_F16=ON"; \
fi && \
cmake .. -DLLAMA_SYCL=ON -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx ${OPT_SYCL_F16} && \
cmake --build . --config Release --target main
FROM intel/oneapi-basekit:$ONEAPI_VERSION as runtime
COPY --from=build /app/build/bin/main /main
ENV LC_ALL=C.utf8
ENTRYPOINT [ "/main" ]

View File

@@ -6,12 +6,12 @@ ARG ROCM_VERSION=5.6
# Target the CUDA build image
ARG BASE_ROCM_DEV_CONTAINER=rocm/dev-ubuntu-${UBUNTU_VERSION}:${ROCM_VERSION}-complete
FROM ${BASE_ROCM_DEV_CONTAINER} AS build
FROM ${BASE_ROCM_DEV_CONTAINER} as build
# Unless otherwise specified, we make a fat build.
# List from https://github.com/ggerganov/llama.cpp/pull/1087#issuecomment-1682807878
# This is mostly tied to rocBLAS supported archs.
ARG ROCM_DOCKER_ARCH="\
ARG ROCM_DOCKER_ARCH=\
gfx803 \
gfx900 \
gfx906 \
@@ -21,7 +21,7 @@ ARG ROCM_DOCKER_ARCH="\
gfx1030 \
gfx1100 \
gfx1101 \
gfx1102"
gfx1102
COPY requirements.txt requirements.txt
COPY requirements requirements
@@ -34,12 +34,12 @@ WORKDIR /app
COPY . .
# Set nvcc architecture
ENV AMDGPU_TARGETS=${ROCM_DOCKER_ARCH}
ENV GPU_TARGETS=${ROCM_DOCKER_ARCH}
# Enable ROCm
ENV GGML_HIPBLAS=1
ENV LLAMA_HIPBLAS=1
ENV CC=/opt/rocm/llvm/bin/clang
ENV CXX=/opt/rocm/llvm/bin/clang++
RUN make -j$(nproc) llama-cli
RUN make
ENTRYPOINT [ "/app/llama-cli" ]
ENTRYPOINT [ "/app/main" ]

View File

@@ -1,9 +1,9 @@
ARG UBUNTU_VERSION=jammy
FROM ubuntu:$UBUNTU_VERSION AS build
FROM ubuntu:$UBUNTU_VERSION as build
# Install build tools
RUN apt update && apt install -y git build-essential cmake wget libgomp1
RUN apt update && apt install -y git build-essential cmake wget
# Install Vulkan SDK
RUN wget -qO - https://packages.lunarg.com/lunarg-signing-key-pub.asc | apt-key add - && \
@@ -14,14 +14,16 @@ RUN wget -qO - https://packages.lunarg.com/lunarg-signing-key-pub.asc | apt-key
# Build it
WORKDIR /app
COPY . .
RUN cmake -B build -DGGML_VULKAN=1 && \
cmake --build build --config Release --target llama-cli
RUN mkdir build && \
cd build && \
cmake .. -DLLAMA_VULKAN=1 && \
cmake --build . --config Release --target main
# Clean up
WORKDIR /
RUN cp /app/build/bin/llama-cli /llama-cli && \
RUN cp /app/build/bin/main /main && \
rm -rf /app
ENV LC_ALL=C.utf8
ENTRYPOINT [ "/llama-cli" ]
ENTRYPOINT [ "/main" ]

20
.devops/main.Dockerfile Normal file
View File

@@ -0,0 +1,20 @@
ARG UBUNTU_VERSION=22.04
FROM ubuntu:$UBUNTU_VERSION as build
RUN apt-get update && \
apt-get install -y build-essential git
WORKDIR /app
COPY . .
RUN make
FROM ubuntu:$UBUNTU_VERSION as runtime
COPY --from=build /app/main /main
ENV LC_ALL=C.utf8
ENTRYPOINT [ "/main" ]

View File

@@ -6,10 +6,11 @@
let
inherit (config.packages) default;
binaries = [
"llama-cli"
"llama"
"llama-embedding"
"llama-server"
"llama-quantize"
"quantize"
"train-text-from-scratch"
];
mkApp = name: {
type = "app";

View File

@@ -1,52 +1,13 @@
{ inputs, ... }:
{
perSystem =
{
config,
lib,
system,
...
}:
{ config, lib, ... }:
{
devShells =
let
pkgs = import inputs.nixpkgs { inherit system; };
stdenv = pkgs.stdenv;
scripts = config.packages.python-scripts;
in
lib.pipe (config.packages) [
(lib.concatMapAttrs (
name: package: {
${name} = pkgs.mkShell {
name = "${name}";
inputsFrom = [ package ];
shellHook = ''
echo "Entering ${name} devShell"
'';
};
"${name}-extra" =
if (name == "python-scripts") then
null
else
pkgs.mkShell {
name = "${name}-extra";
inputsFrom = [
package
scripts
];
# Extra packages that *may* be used by some scripts
packages = [
pkgs.python3Packages.tiktoken
];
shellHook = ''
echo "Entering ${name} devShell"
addToSearchPath "LD_LIBRARY_PATH" "${lib.getLib stdenv.cc.cc}/lib"
'';
};
}
))
(lib.filterAttrs (name: value: value != null))
];
lib.concatMapAttrs
(name: package: {
${name} = package.passthru.shell;
${name + "-extra"} = package.passthru.shell-extra;
})
config.packages;
};
}

View File

@@ -26,14 +26,16 @@
config.cudaSupport = true;
config.allowUnfreePredicate =
p:
builtins.all (
license:
license.free
|| builtins.elem license.shortName [
"CUDA EULA"
"cuDNN EULA"
]
) (p.meta.licenses or [ p.meta.license ]);
builtins.all
(
license:
license.free
|| builtins.elem license.shortName [
"CUDA EULA"
"cuDNN EULA"
]
)
(p.meta.licenses or [ p.meta.license ]);
};
# Ensure dependencies use ROCm consistently
pkgsRocm = import inputs.nixpkgs {

View File

@@ -1,36 +0,0 @@
{
lib,
llamaVersion,
numpy,
tqdm,
sentencepiece,
pyyaml,
poetry-core,
buildPythonPackage,
pytestCheckHook,
}:
buildPythonPackage {
pname = "gguf";
version = llamaVersion;
pyproject = true;
nativeBuildInputs = [ poetry-core ];
propagatedBuildInputs = [
numpy
tqdm
sentencepiece
pyyaml
];
src = lib.cleanSource ../../gguf-py;
pythonImportsCheck = [
"numpy"
"gguf"
];
nativeCheckInputs = [ pytestCheckHook ];
doCheck = true;
meta = with lib; {
description = "Python package for writing binary files in the GGUF format";
license = licenses.mit;
maintainers = [ maintainers.ditsuke ];
};
}

View File

@@ -3,35 +3,33 @@
glibc,
config,
stdenv,
mkShell,
runCommand,
cmake,
ninja,
pkg-config,
git,
python3,
mpi,
blas,
cudaPackages,
autoAddDriverRunpath,
darwin,
rocmPackages,
vulkan-headers,
vulkan-loader,
curl,
shaderc,
useBlas ?
builtins.all (x: !x) [
useCuda
useMetalKit
useRocm
useVulkan
]
&& blas.meta.available,
clblast,
useBlas ? builtins.all (x: !x) [
useCuda
useMetalKit
useOpenCL
useRocm
useVulkan
] && blas.meta.available,
useCuda ? config.cudaSupport,
useMetalKit ? stdenv.isAarch64 && stdenv.isDarwin,
# Increases the runtime closure size by ~700M
useMpi ? false,
useMetalKit ? stdenv.isAarch64 && stdenv.isDarwin && !useOpenCL,
useMpi ? false, # Increases the runtime closure size by ~700M
useOpenCL ? false,
useRocm ? config.rocmSupport,
enableCurl ? true,
useVulkan ? false,
llamaVersion ? "0.0.0", # Arbitrary version, substituted by the flake
@@ -39,8 +37,8 @@
# otherwise we get libstdc++ errors downstream.
effectiveStdenv ? if useCuda then cudaPackages.backendStdenv else stdenv,
enableStatic ? effectiveStdenv.hostPlatform.isStatic,
precompileMetalShaders ? false,
}:
precompileMetalShaders ? false
}@inputs:
let
inherit (lib)
@@ -48,6 +46,7 @@ let
cmakeFeature
optionals
strings
versionOlder
;
stdenv = throw "Use effectiveStdenv instead";
@@ -57,17 +56,45 @@ let
++ lib.optionals useCuda [ "CUDA" ]
++ lib.optionals useMetalKit [ "MetalKit" ]
++ lib.optionals useMpi [ "MPI" ]
++ lib.optionals useOpenCL [ "OpenCL" ]
++ lib.optionals useRocm [ "ROCm" ]
++ lib.optionals useVulkan [ "Vulkan" ];
pnameSuffix =
strings.optionalString (suffices != [ ])
"-${strings.concatMapStringsSep "-" strings.toLower suffices}";
descriptionSuffix = strings.optionalString (
suffices != [ ]
) ", accelerated with ${strings.concatStringsSep ", " suffices}";
descriptionSuffix =
strings.optionalString (suffices != [ ])
", accelerated with ${strings.concatStringsSep ", " suffices}";
xcrunHost = runCommand "xcrunHost" { } ''
executableSuffix = effectiveStdenv.hostPlatform.extensions.executable;
# TODO: package the Python in this repository in a Nix-like way.
# It'd be nice to migrate to buildPythonPackage, as well as ensure this repo
# is PEP 517-compatible, and ensure the correct .dist-info is generated.
# https://peps.python.org/pep-0517/
#
# TODO: Package up each Python script or service appropriately, by making
# them into "entrypoints"
llama-python = python3.withPackages (
ps: [
ps.numpy
ps.sentencepiece
]
);
# TODO(Green-Sky): find a better way to opt-into the heavy ml python runtime
llama-python-extra = python3.withPackages (
ps: [
ps.numpy
ps.sentencepiece
ps.tiktoken
ps.torchWithoutCuda
ps.transformers
]
);
xcrunHost = runCommand "xcrunHost" {} ''
mkdir -p $out/bin
ln -s /usr/bin/xcrun $out/bin
'';
@@ -84,9 +111,16 @@ let
++ optionals useMetalKit [ MetalKit ];
cudaBuildInputs = with cudaPackages; [
cuda_cudart
cuda_cccl # <nv/target>
libcublas
cuda_cccl.dev # <nv/target>
# A temporary hack for reducing the closure size, remove once cudaPackages
# have stopped using lndir: https://github.com/NixOS/nixpkgs/issues/271792
cuda_cudart.dev
cuda_cudart.lib
cuda_cudart.static
libcublas.dev
libcublas.lib
libcublas.static
];
rocmBuildInputs = with rocmPackages; [
@@ -98,149 +132,188 @@ let
vulkanBuildInputs = [
vulkan-headers
vulkan-loader
shaderc
];
in
effectiveStdenv.mkDerivation (finalAttrs: {
pname = "llama-cpp${pnameSuffix}";
version = llamaVersion;
effectiveStdenv.mkDerivation (
finalAttrs: {
pname = "llama-cpp${pnameSuffix}";
version = llamaVersion;
# Note: none of the files discarded here are visible in the sandbox or
# affect the output hash. This also means they can be modified without
# triggering a rebuild.
src = lib.cleanSourceWith {
filter =
name: type:
let
noneOf = builtins.all (x: !x);
baseName = baseNameOf name;
in
noneOf [
(lib.hasSuffix ".nix" name) # Ignore *.nix files when computing outPaths
(lib.hasSuffix ".md" name) # Ignore *.md changes whe computing outPaths
(lib.hasPrefix "." baseName) # Skip hidden files and directories
(baseName == "flake.lock")
# Note: none of the files discarded here are visible in the sandbox or
# affect the output hash. This also means they can be modified without
# triggering a rebuild.
src = lib.cleanSourceWith {
filter =
name: type:
let
noneOf = builtins.all (x: !x);
baseName = baseNameOf name;
in
noneOf [
(lib.hasSuffix ".nix" name) # Ignore *.nix files when computing outPaths
(lib.hasSuffix ".md" name) # Ignore *.md changes whe computing outPaths
(lib.hasPrefix "." baseName) # Skip hidden files and directories
(baseName == "flake.lock")
];
src = lib.cleanSource ../../.;
};
postPatch = ''
substituteInPlace ./ggml-metal.m \
--replace '[bundle pathForResource:@"ggml-metal" ofType:@"metal"];' "@\"$out/bin/ggml-metal.metal\";"
substituteInPlace ./ggml-metal.m \
--replace '[bundle pathForResource:@"default" ofType:@"metallib"];' "@\"$out/bin/default.metallib\";"
'';
# With PR#6015 https://github.com/ggerganov/llama.cpp/pull/6015,
# `default.metallib` may be compiled with Metal compiler from XCode
# and we need to escape sandbox on MacOS to access Metal compiler.
# `xcrun` is used find the path of the Metal compiler, which is varible
# and not on $PATH
# see https://github.com/ggerganov/llama.cpp/pull/6118 for discussion
__noChroot = effectiveStdenv.isDarwin && useMetalKit && precompileMetalShaders;
nativeBuildInputs =
[
cmake
ninja
pkg-config
git
]
++ optionals useCuda [
cudaPackages.cuda_nvcc
# TODO: Replace with autoAddDriverRunpath
# once https://github.com/NixOS/nixpkgs/pull/275241 has been merged
cudaPackages.autoAddOpenGLRunpathHook
]
++ optionals (effectiveStdenv.hostPlatform.isGnu && enableStatic) [
glibc.static
] ++ optionals (effectiveStdenv.isDarwin && useMetalKit && precompileMetalShaders) [
xcrunHost
];
src = lib.cleanSource ../../.;
};
postPatch = ''
substituteInPlace ./ggml/src/ggml-metal.m \
--replace '[bundle pathForResource:@"ggml-metal" ofType:@"metal"];' "@\"$out/bin/ggml-metal.metal\";"
substituteInPlace ./ggml/src/ggml-metal.m \
--replace '[bundle pathForResource:@"default" ofType:@"metallib"];' "@\"$out/bin/default.metallib\";"
'';
buildInputs =
optionals effectiveStdenv.isDarwin darwinBuildInputs
++ optionals useCuda cudaBuildInputs
++ optionals useMpi [ mpi ]
++ optionals useOpenCL [ clblast ]
++ optionals useRocm rocmBuildInputs
++ optionals useBlas [ blas ]
++ optionals useVulkan vulkanBuildInputs;
# With PR#6015 https://github.com/ggerganov/llama.cpp/pull/6015,
# `default.metallib` may be compiled with Metal compiler from XCode
# and we need to escape sandbox on MacOS to access Metal compiler.
# `xcrun` is used find the path of the Metal compiler, which is varible
# and not on $PATH
# see https://github.com/ggerganov/llama.cpp/pull/6118 for discussion
__noChroot = effectiveStdenv.isDarwin && useMetalKit && precompileMetalShaders;
nativeBuildInputs =
[
cmake
ninja
pkg-config
git
]
++ optionals useCuda [
cudaPackages.cuda_nvcc
autoAddDriverRunpath
]
++ optionals (effectiveStdenv.hostPlatform.isGnu && enableStatic) [ glibc.static ]
++ optionals (effectiveStdenv.isDarwin && useMetalKit && precompileMetalShaders) [ xcrunHost ];
buildInputs =
optionals effectiveStdenv.isDarwin darwinBuildInputs
++ optionals useCuda cudaBuildInputs
++ optionals useMpi [ mpi ]
++ optionals useRocm rocmBuildInputs
++ optionals useBlas [ blas ]
++ optionals useVulkan vulkanBuildInputs
++ optionals enableCurl [ curl ];
cmakeFlags =
[
(cmakeBool "LLAMA_BUILD_SERVER" true)
(cmakeBool "BUILD_SHARED_LIBS" (!enableStatic))
(cmakeBool "CMAKE_SKIP_BUILD_RPATH" true)
(cmakeBool "LLAMA_CURL" enableCurl)
(cmakeBool "GGML_NATIVE" false)
(cmakeBool "GGML_BLAS" useBlas)
(cmakeBool "GGML_CUDA" useCuda)
(cmakeBool "GGML_HIPBLAS" useRocm)
(cmakeBool "GGML_METAL" useMetalKit)
(cmakeBool "GGML_VULKAN" useVulkan)
(cmakeBool "GGML_STATIC" enableStatic)
]
++ optionals useCuda [
(
with cudaPackages.flags;
cmakeFeature "CMAKE_CUDA_ARCHITECTURES" (
builtins.concatStringsSep ";" (map dropDot cudaCapabilities)
cmakeFlags =
[
(cmakeBool "LLAMA_NATIVE" false)
(cmakeBool "LLAMA_BUILD_SERVER" true)
(cmakeBool "BUILD_SHARED_LIBS" (!enableStatic))
(cmakeBool "CMAKE_SKIP_BUILD_RPATH" true)
(cmakeBool "LLAMA_BLAS" useBlas)
(cmakeBool "LLAMA_CLBLAST" useOpenCL)
(cmakeBool "LLAMA_CUDA" useCuda)
(cmakeBool "LLAMA_HIPBLAS" useRocm)
(cmakeBool "LLAMA_METAL" useMetalKit)
(cmakeBool "LLAMA_MPI" useMpi)
(cmakeBool "LLAMA_VULKAN" useVulkan)
(cmakeBool "LLAMA_STATIC" enableStatic)
]
++ optionals useCuda [
(
with cudaPackages.flags;
cmakeFeature "CMAKE_CUDA_ARCHITECTURES" (
builtins.concatStringsSep ";" (map dropDot cudaCapabilities)
)
)
)
]
++ optionals useRocm [
(cmakeFeature "CMAKE_HIP_COMPILER" "${rocmPackages.llvm.clang}/bin/clang")
(cmakeFeature "CMAKE_HIP_ARCHITECTURES" (builtins.concatStringsSep ";" rocmPackages.clr.gpuTargets))
]
++ optionals useMetalKit [
(lib.cmakeFeature "CMAKE_C_FLAGS" "-D__ARM_FEATURE_DOTPROD=1")
(cmakeBool "GGML_METAL_EMBED_LIBRARY" (!precompileMetalShaders))
];
]
++ optionals useRocm [
(cmakeFeature "CMAKE_C_COMPILER" "hipcc")
(cmakeFeature "CMAKE_CXX_COMPILER" "hipcc")
# Environment variables needed for ROCm
env = optionals useRocm {
ROCM_PATH = "${rocmPackages.clr}";
HIP_DEVICE_LIB_PATH = "${rocmPackages.rocm-device-libs}/amdgcn/bitcode";
};
# Build all targets supported by rocBLAS. When updating search for TARGET_LIST_ROCM
# in https://github.com/ROCmSoftwarePlatform/rocBLAS/blob/develop/CMakeLists.txt
# and select the line that matches the current nixpkgs version of rocBLAS.
# Should likely use `rocmPackages.clr.gpuTargets`.
"-DAMDGPU_TARGETS=gfx803;gfx900;gfx906:xnack-;gfx908:xnack-;gfx90a:xnack+;gfx90a:xnack-;gfx940;gfx941;gfx942;gfx1010;gfx1012;gfx1030;gfx1100;gfx1101;gfx1102"
]
++ optionals useMetalKit [
(lib.cmakeFeature "CMAKE_C_FLAGS" "-D__ARM_FEATURE_DOTPROD=1")
(cmakeBool "LLAMA_METAL_EMBED_LIBRARY" (!precompileMetalShaders))
];
# TODO(SomeoneSerge): It's better to add proper install targets at the CMake level,
# if they haven't been added yet.
postInstall = ''
mkdir -p $out/include
cp $src/include/llama.h $out/include/
'';
# TODO(SomeoneSerge): It's better to add proper install targets at the CMake level,
# if they haven't been added yet.
postInstall = ''
mv $out/bin/main${executableSuffix} $out/bin/llama${executableSuffix}
mv $out/bin/server${executableSuffix} $out/bin/llama-server${executableSuffix}
mkdir -p $out/include
cp $src/llama.h $out/include/
'';
meta = {
# Configurations we don't want even the CI to evaluate. Results in the
# "unsupported platform" messages. This is mostly a no-op, because
# cudaPackages would've refused to evaluate anyway.
badPlatforms = optionals useCuda lib.platforms.darwin;
# Define the shells here, but don't add in the inputsFrom to avoid recursion.
passthru = {
inherit
useBlas
useCuda
useMetalKit
useMpi
useOpenCL
useRocm
useVulkan
;
# Configurations that are known to result in build failures. Can be
# overridden by importing Nixpkgs with `allowBroken = true`.
broken = (useMetalKit && !effectiveStdenv.isDarwin);
shell = mkShell {
name = "shell-${finalAttrs.finalPackage.name}";
description = "contains numpy and sentencepiece";
buildInputs = [ llama-python ];
inputsFrom = [ finalAttrs.finalPackage ];
shellHook = ''
addToSearchPath "LD_LIBRARY_PATH" "${lib.getLib effectiveStdenv.cc.cc}/lib"
'';
};
description = "Inference of LLaMA model in pure C/C++${descriptionSuffix}";
homepage = "https://github.com/ggerganov/llama.cpp/";
license = lib.licenses.mit;
shell-extra = mkShell {
name = "shell-extra-${finalAttrs.finalPackage.name}";
description = "contains numpy, sentencepiece, torchWithoutCuda, and transformers";
buildInputs = [ llama-python-extra ];
inputsFrom = [ finalAttrs.finalPackage ];
};
};
# Accommodates `nix run` and `lib.getExe`
mainProgram = "llama-cli";
meta = {
# Configurations we don't want even the CI to evaluate. Results in the
# "unsupported platform" messages. This is mostly a no-op, because
# cudaPackages would've refused to evaluate anyway.
badPlatforms = optionals (useCuda || useOpenCL) lib.platforms.darwin;
# These people might respond, on the best effort basis, if you ping them
# in case of Nix-specific regressions or for reviewing Nix-specific PRs.
# Consider adding yourself to this list if you want to ensure this flake
# stays maintained and you're willing to invest your time. Do not add
# other people without their consent. Consider removing people after
# they've been unreachable for long periods of time.
# Configurations that are known to result in build failures. Can be
# overridden by importing Nixpkgs with `allowBroken = true`.
broken = (useMetalKit && !effectiveStdenv.isDarwin);
# Note that lib.maintainers is defined in Nixpkgs, but you may just add
# an attrset following the same format as in
# https://github.com/NixOS/nixpkgs/blob/f36a80e54da29775c78d7eff0e628c2b4e34d1d7/maintainers/maintainer-list.nix
maintainers = with lib.maintainers; [
philiptaron
SomeoneSerge
];
description = "Inference of LLaMA model in pure C/C++${descriptionSuffix}";
homepage = "https://github.com/ggerganov/llama.cpp/";
license = lib.licenses.mit;
# Extend `badPlatforms` instead
platforms = lib.platforms.all;
};
})
# Accommodates `nix run` and `lib.getExe`
mainProgram = "llama";
# These people might respond, on the best effort basis, if you ping them
# in case of Nix-specific regressions or for reviewing Nix-specific PRs.
# Consider adding yourself to this list if you want to ensure this flake
# stays maintained and you're willing to invest your time. Do not add
# other people without their consent. Consider removing people after
# they've been unreachable for long periods of time.
# Note that lib.maintainers is defined in Nixpkgs, but you may just add
# an attrset following the same format as in
# https://github.com/NixOS/nixpkgs/blob/f36a80e54da29775c78d7eff0e628c2b4e34d1d7/maintainers/maintainer-list.nix
maintainers = with lib.maintainers; [
philiptaron
SomeoneSerge
];
# Extend `badPlatforms` instead
platforms = lib.platforms.all;
};
}
)

View File

@@ -1,66 +0,0 @@
{
lib,
stdenv,
buildPythonPackage,
poetry-core,
mkShell,
python3Packages,
gguf-py,
}@inputs:
let
llama-python-deps = with python3Packages; [
numpy
sentencepiece
transformers
protobuf
torchWithoutCuda
gguf-py
tqdm
# for scripts/compare-llama-bench.py
gitpython
tabulate
# for examples/pydantic-models-to-grammar-examples.py
docstring-parser
pydantic
];
llama-python-test-deps = with python3Packages; [
# Server bench
matplotlib
# server tests
openai
behave
prometheus-client
];
in
buildPythonPackage ({
pname = "llama-scripts";
version = "0.0.0";
pyproject = true;
# NOTE: The files filtered out here are not visible in the build sandbox, neither
# do they affect the output hash. They can be modified without triggering a rebuild.
src = lib.cleanSourceWith {
filter =
name: type:
let
any = builtins.any (x: x);
baseName = builtins.baseNameOf name;
in
any [
(lib.hasSuffix ".py" name)
(baseName == "README.md")
(baseName == "pyproject.toml")
];
src = lib.cleanSource ../../.;
};
nativeBuildInputs = [ poetry-core ];
nativeCheckInputs = llama-python-test-deps;
dependencies = llama-python-deps;
})

View File

@@ -1,41 +1,19 @@
{
lib,
newScope,
python3,
llamaVersion ? "0.0.0",
}:
let
pythonPackages = python3.pkgs;
buildPythonPackage = pythonPackages.buildPythonPackage;
numpy = pythonPackages.numpy;
tqdm = pythonPackages.tqdm;
sentencepiece = pythonPackages.sentencepiece;
pyyaml = pythonPackages.pyyaml;
poetry-core = pythonPackages.poetry-core;
pytestCheckHook = pythonPackages.pytestCheckHook;
in
# We're using `makeScope` instead of just writing out an attrset
# because it allows users to apply overlays later using `overrideScope'`.
# Cf. https://noogle.dev/f/lib/makeScope
lib.makeScope newScope (self: {
inherit llamaVersion;
gguf-py = self.callPackage ./package-gguf-py.nix {
inherit
buildPythonPackage
numpy
tqdm
sentencepiece
poetry-core
pyyaml
pytestCheckHook
;
};
python-scripts = self.callPackage ./python-scripts.nix { inherit buildPythonPackage poetry-core; };
llama-cpp = self.callPackage ./package.nix { };
docker = self.callPackage ./docker.nix { };
docker-min = self.callPackage ./docker.nix { interactive = false; };
sif = self.callPackage ./sif.nix { };
})
lib.makeScope newScope (
self: {
inherit llamaVersion;
llama-cpp = self.callPackage ./package.nix { };
docker = self.callPackage ./docker.nix { };
docker-min = self.callPackage ./docker.nix { interactive = false; };
sif = self.callPackage ./sif.nix { };
}
)

View File

@@ -0,0 +1,32 @@
ARG UBUNTU_VERSION=22.04
# This needs to generally match the container host's environment.
ARG CUDA_VERSION=11.7.1
# Target the CUDA build image
ARG BASE_CUDA_DEV_CONTAINER=nvidia/cuda:${CUDA_VERSION}-devel-ubuntu${UBUNTU_VERSION}
# Target the CUDA runtime image
ARG BASE_CUDA_RUN_CONTAINER=nvidia/cuda:${CUDA_VERSION}-runtime-ubuntu${UBUNTU_VERSION}
FROM ${BASE_CUDA_DEV_CONTAINER} as build
# Unless otherwise specified, we make a fat build.
ARG CUDA_DOCKER_ARCH=all
RUN apt-get update && \
apt-get install -y build-essential git
WORKDIR /app
COPY . .
# Set nvcc architecture
ENV CUDA_DOCKER_ARCH=${CUDA_DOCKER_ARCH}
# Enable CUDA
ENV LLAMA_CUDA=1
RUN make
FROM ${BASE_CUDA_RUN_CONTAINER} as runtime
COPY --from=build /app/server /server
ENTRYPOINT [ "/server" ]

View File

@@ -0,0 +1,28 @@
ARG ONEAPI_VERSION=2024.0.1-devel-ubuntu22.04
FROM intel/oneapi-basekit:$ONEAPI_VERSION as build
ARG LLAMA_SYCL_F16=OFF
RUN apt-get update && \
apt-get install -y git
WORKDIR /app
COPY . .
RUN mkdir build && \
cd build && \
if [ "${LLAMA_SYCL_F16}" = "ON" ]; then \
echo "LLAMA_SYCL_F16 is set" && \
export OPT_SYCL_F16="-DLLAMA_SYCL_F16=ON"; \
fi && \
cmake .. -DLLAMA_SYCL=ON -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx ${OPT_SYCL_F16} && \
cmake --build . --config Release --target server
FROM intel/oneapi-basekit:$ONEAPI_VERSION as runtime
COPY --from=build /app/build/bin/server /server
ENV LC_ALL=C.utf8
ENTRYPOINT [ "/server" ]

View File

@@ -6,12 +6,12 @@ ARG ROCM_VERSION=5.6
# Target the CUDA build image
ARG BASE_ROCM_DEV_CONTAINER=rocm/dev-ubuntu-${UBUNTU_VERSION}:${ROCM_VERSION}-complete
FROM ${BASE_ROCM_DEV_CONTAINER} AS build
FROM ${BASE_ROCM_DEV_CONTAINER} as build
# Unless otherwise specified, we make a fat build.
# List from https://github.com/ggerganov/llama.cpp/pull/1087#issuecomment-1682807878
# This is mostly tied to rocBLAS supported archs.
ARG ROCM_DOCKER_ARCH="\
ARG ROCM_DOCKER_ARCH=\
gfx803 \
gfx900 \
gfx906 \
@@ -21,7 +21,7 @@ ARG ROCM_DOCKER_ARCH="\
gfx1030 \
gfx1100 \
gfx1101 \
gfx1102"
gfx1102
COPY requirements.txt requirements.txt
COPY requirements requirements
@@ -34,21 +34,12 @@ WORKDIR /app
COPY . .
# Set nvcc architecture
ENV AMDGPU_TARGETS=${ROCM_DOCKER_ARCH}
ENV GPU_TARGETS=${ROCM_DOCKER_ARCH}
# Enable ROCm
ENV GGML_HIPBLAS=1
ENV LLAMA_HIPBLAS=1
ENV CC=/opt/rocm/llvm/bin/clang
ENV CXX=/opt/rocm/llvm/bin/clang++
# Must be set to 0.0.0.0 so it can listen to requests from host machine
ENV LLAMA_ARG_HOST=0.0.0.0
# Enable cURL
ENV LLAMA_CURL=1
RUN apt-get update && \
apt-get install -y libcurl4-openssl-dev curl
RUN make
RUN make -j$(nproc) llama-server
HEALTHCHECK CMD [ "curl", "-f", "http://localhost:8080/health" ]
ENTRYPOINT [ "/app/llama-server" ]
ENTRYPOINT [ "/app/server" ]

View File

@@ -0,0 +1,29 @@
ARG UBUNTU_VERSION=jammy
FROM ubuntu:$UBUNTU_VERSION as build
# Install build tools
RUN apt update && apt install -y git build-essential cmake wget
# Install Vulkan SDK
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 && \
apt update -y && \
apt-get install -y vulkan-sdk
# Build it
WORKDIR /app
COPY . .
RUN mkdir build && \
cd build && \
cmake .. -DLLAMA_VULKAN=1 && \
cmake --build . --config Release --target server
# Clean up
WORKDIR /
RUN cp /app/build/bin/server /server && \
rm -rf /app
ENV LC_ALL=C.utf8
ENTRYPOINT [ "/server" ]

20
.devops/server.Dockerfile Normal file
View File

@@ -0,0 +1,20 @@
ARG UBUNTU_VERSION=22.04
FROM ubuntu:$UBUNTU_VERSION as build
RUN apt-get update && \
apt-get install -y build-essential git
WORKDIR /app
COPY . .
RUN make
FROM ubuntu:$UBUNTU_VERSION as runtime
COPY --from=build /app/server /server
ENV LC_ALL=C.utf8
ENTRYPOINT [ "/server" ]

View File

@@ -8,11 +8,13 @@ arg1="$1"
shift
if [[ "$arg1" == '--convert' || "$arg1" == '-c' ]]; then
python3 ./convert_hf_to_gguf.py "$@"
python3 ./convert.py "$@"
elif [[ "$arg1" == '--quantize' || "$arg1" == '-q' ]]; then
./llama-quantize "$@"
./quantize "$@"
elif [[ "$arg1" == '--run' || "$arg1" == '-r' ]]; then
./llama-cli "$@"
./main "$@"
elif [[ "$arg1" == '--finetune' || "$arg1" == '-f' ]]; then
./finetune "$@"
elif [[ "$arg1" == '--all-in-one' || "$arg1" == '-a' ]]; then
echo "Converting PTH to GGML..."
for i in `ls $1/$2/ggml-model-f16.bin*`; do
@@ -20,11 +22,11 @@ elif [[ "$arg1" == '--all-in-one' || "$arg1" == '-a' ]]; then
echo "Skip model quantization, it already exists: ${i/f16/q4_0}"
else
echo "Converting PTH to GGML: $i into ${i/f16/q4_0}..."
./llama-quantize "$i" "${i/f16/q4_0}" q4_0
./quantize "$i" "${i/f16/q4_0}" q4_0
fi
done
elif [[ "$arg1" == '--server' || "$arg1" == '-s' ]]; then
./llama-server "$@"
./server "$@"
else
echo "Unknown command: $arg1"
echo "Available commands: "
@@ -34,6 +36,8 @@ else
echo " ex: --outtype f16 \"/models/7B/\" "
echo " --quantize (-q): Optimize with quantization process ggml"
echo " ex: \"/models/7B/ggml-model-f16.bin\" \"/models/7B/ggml-model-q4_0.bin\" 2"
echo " --finetune (-f): Run finetune command to create a lora finetune of the model"
echo " See documentation for finetune for command-line parameters"
echo " --all-in-one (-a): Execute --convert & --quantize"
echo " ex: \"/models/\" 7B"
echo " --server (-s): Run a model on the server"

View File

@@ -1,7 +1,7 @@
*.o
*.a
.cache/
# Do not ignore .git directory, otherwise the reported build number will always be 0
.git/
.github/
.gitignore
.vs/
@@ -12,8 +12,8 @@ build*/
models/*
/llama-cli
/llama-quantize
/main
/quantize
arm_neon.h
compile_commands.json

2
.ecrc
View File

@@ -1,5 +1,5 @@
{
"Exclude": ["^\\.gitmodules$", "stb_image\\.h"],
"Exclude": ["^\\.gitmodules$"],
"Disable": {
"IndentSize": true
}

View File

@@ -26,7 +26,3 @@ indent_size = 2
[examples/llama.swiftui/llama.swiftui.xcodeproj/*]
indent_style = tab
[examples/cvector-generator/*.txt]
trim_trailing_whitespace = unset
insert_final_newline = unset

16
.flake8
View File

@@ -1,17 +1,3 @@
[flake8]
max-line-length = 125
ignore = E203,E211,E221,E225,E231,E241,E251,E261,E266,E501,E701,E704,W503
exclude =
# Do not traverse examples
examples,
# Do not include package initializers
__init__.py,
# No need to traverse our git directory
.git,
# There's no value in checking cache directories
__pycache__,
# No need to include the build path
build,
# This contains builds that we don't want to check
dist # This is generated with `python build .` for package releases
# max-complexity = 10
ignore = W503

View File

@@ -1,50 +0,0 @@
name: Low Severity Bugs
description: Used to report low severity bugs in llama.cpp (e.g. cosmetic issues, non critical UI glitches)
title: "Bug: "
labels: ["bug-unconfirmed", "low severity"]
body:
- type: markdown
attributes:
value: |
Thanks for taking the time to fill out this bug report!
Please include information about your system, the steps to reproduce the bug,
and the version of llama.cpp that you are using.
If possible, please provide a minimal code example that reproduces the bug.
- type: textarea
id: what-happened
attributes:
label: What happened?
description: Also tell us, what did you expect to happen?
placeholder: Tell us what you see!
validations:
required: true
- type: textarea
id: version
attributes:
label: Name and Version
description: Which executable and which version of our software are you running? (use `--version` to get a version string)
placeholder: |
$./llama-cli --version
version: 2999 (42b4109e)
built with cc (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0 for x86_64-linux-gnu
validations:
required: true
- type: dropdown
id: operating-system
attributes:
label: What operating system are you seeing the problem on?
multiple: true
options:
- Linux
- Mac
- Windows
- BSD
- Other? (Please let us know in description)
validations:
required: false
- type: textarea
id: logs
attributes:
label: Relevant log output
description: Please copy and paste any relevant log output. This will be automatically formatted into code, so no need for backticks.
render: shell

View File

@@ -1,50 +0,0 @@
name: Medium Severity Bug
description: Used to report medium severity bugs in llama.cpp (e.g. Malfunctioning Features but generally still useable)
title: "Bug: "
labels: ["bug-unconfirmed", "medium severity"]
body:
- type: markdown
attributes:
value: |
Thanks for taking the time to fill out this bug report!
Please include information about your system, the steps to reproduce the bug,
and the version of llama.cpp that you are using.
If possible, please provide a minimal code example that reproduces the bug.
- type: textarea
id: what-happened
attributes:
label: What happened?
description: Also tell us, what did you expect to happen?
placeholder: Tell us what you see!
validations:
required: true
- type: textarea
id: version
attributes:
label: Name and Version
description: Which executable and which version of our software are you running? (use `--version` to get a version string)
placeholder: |
$./llama-cli --version
version: 2999 (42b4109e)
built with cc (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0 for x86_64-linux-gnu
validations:
required: true
- type: dropdown
id: operating-system
attributes:
label: What operating system are you seeing the problem on?
multiple: true
options:
- Linux
- Mac
- Windows
- BSD
- Other? (Please let us know in description)
validations:
required: false
- type: textarea
id: logs
attributes:
label: Relevant log output
description: Please copy and paste any relevant log output. This will be automatically formatted into code, so no need for backticks.
render: shell

View File

@@ -1,50 +0,0 @@
name: High Severity Bug
description: Used to report high severity bugs in llama.cpp (e.g. Malfunctioning features hindering important common workflow)
title: "Bug: "
labels: ["bug-unconfirmed", "high severity"]
body:
- type: markdown
attributes:
value: |
Thanks for taking the time to fill out this bug report!
Please include information about your system, the steps to reproduce the bug,
and the version of llama.cpp that you are using.
If possible, please provide a minimal code example that reproduces the bug.
- type: textarea
id: what-happened
attributes:
label: What happened?
description: Also tell us, what did you expect to happen?
placeholder: Tell us what you see!
validations:
required: true
- type: textarea
id: version
attributes:
label: Name and Version
description: Which executable and which version of our software are you running? (use `--version` to get a version string)
placeholder: |
$./llama-cli --version
version: 2999 (42b4109e)
built with cc (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0 for x86_64-linux-gnu
validations:
required: true
- type: dropdown
id: operating-system
attributes:
label: What operating system are you seeing the problem on?
multiple: true
options:
- Linux
- Mac
- Windows
- BSD
- Other? (Please let us know in description)
validations:
required: false
- type: textarea
id: logs
attributes:
label: Relevant log output
description: Please copy and paste any relevant log output. This will be automatically formatted into code, so no need for backticks.
render: shell

View File

@@ -1,50 +0,0 @@
name: Critical Severity Bug
description: Used to report critical severity bugs in llama.cpp (e.g. Crashing, Corrupted, Dataloss)
title: "Bug: "
labels: ["bug-unconfirmed", "critical severity"]
body:
- type: markdown
attributes:
value: |
Thanks for taking the time to fill out this bug report!
Please include information about your system, the steps to reproduce the bug,
and the version of llama.cpp that you are using.
If possible, please provide a minimal code example that reproduces the bug.
- type: textarea
id: what-happened
attributes:
label: What happened?
description: Also tell us, what did you expect to happen?
placeholder: Tell us what you see!
validations:
required: true
- type: textarea
id: version
attributes:
label: Name and Version
description: Which executable and which version of our software are you running? (use `--version` to get a version string)
placeholder: |
$./llama-cli --version
version: 2999 (42b4109e)
built with cc (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0 for x86_64-linux-gnu
validations:
required: true
- type: dropdown
id: operating-system
attributes:
label: What operating system are you seeing the problem on?
multiple: true
options:
- Linux
- Mac
- Windows
- BSD
- Other? (Please let us know in description)
validations:
required: false
- type: textarea
id: logs
attributes:
label: Relevant log output
description: Please copy and paste any relevant log output. This will be automatically formatted into code, so no need for backticks.
render: shell

View File

@@ -1,51 +0,0 @@
name: Enhancement
description: Used to request enhancements for llama.cpp
title: "Feature Request: "
labels: ["enhancement"]
body:
- type: markdown
attributes:
value: |
[Please post your idea first in Discussion if there is not yet a consensus for this enhancement request. This will help to keep this issue tracker focused on enhancements that the community has agreed needs to be implemented.](https://github.com/ggerganov/llama.cpp/discussions/categories/ideas)
- type: checkboxes
id: prerequisites
attributes:
label: Prerequisites
description: Please confirm the following before submitting your enhancement request.
options:
- label: I am running the latest code. Mention the version if possible as well.
required: true
- label: I carefully followed the [README.md](https://github.com/ggerganov/llama.cpp/blob/master/README.md).
required: true
- label: I searched using keywords relevant to my issue to make sure that I am creating a new issue that is not already open (or closed).
required: true
- label: I reviewed the [Discussions](https://github.com/ggerganov/llama.cpp/discussions), and have a new and useful enhancement to share.
required: true
- type: textarea
id: feature-description
attributes:
label: Feature Description
description: Please provide a detailed written description of what you were trying to do, and what you expected `llama.cpp` to do as an enhancement.
placeholder: Detailed description of the enhancement
validations:
required: true
- type: textarea
id: motivation
attributes:
label: Motivation
description: Please provide a detailed written description of reasons why this feature is necessary and how it is useful to `llama.cpp` users.
placeholder: Explanation of why this feature is needed and its benefits
validations:
required: true
- type: textarea
id: possible-implementation
attributes:
label: Possible Implementation
description: If you have an idea as to how it can be implemented, please write a detailed description. Feel free to give links to external sources or share visuals that might be helpful to understand the details better.
placeholder: Detailed description of potential implementation
validations:
required: false

View File

@@ -1,52 +0,0 @@
name: Research
description: Track new technical research area
title: "Research: "
labels: ["research 🔬"]
body:
- type: markdown
attributes:
value: |
Don't forget to check for any [duplicate research issue tickets](https://github.com/ggerganov/llama.cpp/issues?q=is%3Aopen+is%3Aissue+label%3A%22research+%F0%9F%94%AC%22)
- type: checkboxes
id: research-stage
attributes:
label: Research Stage
description: Track general state of this research ticket
options:
- label: Background Research (Let's try to avoid reinventing the wheel)
- label: Hypothesis Formed (How do you think this will work and it's effect?)
- label: Strategy / Implementation Forming
- label: Analysis of results
- label: Debrief / Documentation (So people in the future can learn from us)
- type: textarea
id: background
attributes:
label: Previous existing literature and research
description: Whats the current state of the art and whats the motivation for this research?
- type: textarea
id: hypothesis
attributes:
label: Hypothesis
description: How do you think this will work and it's effect?
- type: textarea
id: implementation
attributes:
label: Implementation
description: Got an approach? e.g. a PR ready to go?
- type: textarea
id: analysis
attributes:
label: Analysis
description: How does the proposed implementation behave?
- type: textarea
id: logs
attributes:
label: Relevant log output
description: Please copy and paste any relevant log output. This will be automatically formatted into code, so no need for backticks.
render: shell

View File

@@ -1,28 +0,0 @@
name: Refactor (Maintainers)
description: Used to track refactoring opportunities
title: "Refactor: "
labels: ["refactor"]
body:
- type: markdown
attributes:
value: |
Don't forget to [check for existing refactor issue tickets](https://github.com/ggerganov/llama.cpp/issues?q=is%3Aopen+is%3Aissue+label%3Arefactoring) in case it's already covered.
Also you may want to check [Pull request refactor label as well](https://github.com/ggerganov/llama.cpp/pulls?q=is%3Aopen+is%3Apr+label%3Arefactoring) for duplicates too.
- type: textarea
id: background-description
attributes:
label: Background Description
description: Please provide a detailed written description of the pain points you are trying to solve.
placeholder: Detailed description behind your motivation to request refactor
validations:
required: true
- type: textarea
id: possible-approaches
attributes:
label: Possible Refactor Approaches
description: If you have some idea of possible approaches to solve this problem. You may want to make it a todo list.
placeholder: Your idea of possible refactoring opportunity/approaches
validations:
required: false

11
.github/ISSUE_TEMPLATE/bug.md vendored Normal file
View File

@@ -0,0 +1,11 @@
---
name: Bug template
about: Used to report bugs in llama.cpp
labels: ["bug-unconfirmed"]
assignees: ''
---
Please include information about your system, the steps to reproduce the bug, and the version of llama.cpp that you are using. If possible, please provide a minimal code example that reproduces the bug.
If the bug concerns the server, please try to reproduce it first using the [server test scenario framework](https://github.com/ggerganov/llama.cpp/tree/master/examples/server/tests).

View File

@@ -1,11 +0,0 @@
blank_issues_enabled: true
contact_links:
- name: Got an idea?
url: https://github.com/ggerganov/llama.cpp/discussions/categories/ideas
about: Pop it there. It may then become an enhancement ticket.
- name: Got a question?
url: https://github.com/ggerganov/llama.cpp/discussions/categories/q-a
about: Ask a question there!
- name: Want to contribute?
url: https://github.com/ggerganov/llama.cpp/wiki/contribute
about: Head to the contribution guide page of the wiki for areas you can help with

28
.github/ISSUE_TEMPLATE/enhancement.md vendored Normal file
View File

@@ -0,0 +1,28 @@
---
name: Enhancement template
about: Used to request enhancements for llama.cpp
labels: ["enhancement"]
assignees: ''
---
# Prerequisites
Please answer the following questions for yourself before submitting an issue.
- [ ] I am running the latest code. Development is very rapid so there are no tagged versions as of now.
- [ ] I carefully followed the [README.md](https://github.com/ggerganov/llama.cpp/blob/master/README.md).
- [ ] I [searched using keywords relevant to my issue](https://docs.github.com/en/issues/tracking-your-work-with-issues/filtering-and-searching-issues-and-pull-requests) to make sure that I am creating a new issue that is not already open (or closed).
- [ ] I reviewed the [Discussions](https://github.com/ggerganov/llama.cpp/discussions), and have a new bug or useful enhancement to share.
# Feature Description
Please provide a detailed written description of what you were trying to do, and what you expected `llama.cpp` to do as an enhancement.
# Motivation
Please provide a detailed written description of reasons why this feature is necessary and how it is useful to `llama.cpp` users.
# Possible Implementation
If you have an idea as to how it can be implemented, please write a detailed description. Feel free to give links to external sources or share visuals that might be helpful to understand the details better.

91
.github/labeler.yml vendored
View File

@@ -1,91 +0,0 @@
# https://github.com/actions/labeler
Kompute:
- changed-files:
- any-glob-to-any-file:
- ggml/include/ggml-kompute.h
- ggml/src/ggml-kompute.cpp
- README-kompute.md
Apple Metal:
- changed-files:
- any-glob-to-any-file:
- ggml/include/ggml-metal.h
- ggml/src/ggml-metal.cpp
- README-metal.md
SYCL:
- changed-files:
- any-glob-to-any-file:
- ggml/include/ggml-sycl.h
- ggml/src/ggml-sycl.cpp
- ggml/src/ggml-sycl/**
- docs/backend/SYCL.md
- examples/sycl/**
Nvidia GPU:
- changed-files:
- any-glob-to-any-file:
- ggml/include/ggml-cuda.h
- ggml/src/ggml-cuda/**
Vulkan:
- changed-files:
- any-glob-to-any-file:
- ggml/ggml_vk_generate_shaders.py
- ggml/src/ggml-vulkan*
documentation:
- changed-files:
- any-glob-to-any-file:
- docs/**
- media/**
testing:
- changed-files:
- any-glob-to-any-file:
- tests/**
build:
- changed-files:
- any-glob-to-any-file:
- cmake/**
- CMakeLists.txt
- CMakePresets.json
examples:
- changed-files:
- any-glob-to-any-file: examples/**
devops:
- changed-files:
- any-glob-to-any-file:
- .devops/**
- .github/**
- ci/**
python:
- changed-files:
- any-glob-to-any-file:
- "**/*.py"
- requirements/**
- gguf-py/**
- .flake8
script:
- changed-files:
- any-glob-to-any-file:
- scripts/**
android:
- changed-files:
- any-glob-to-any-file:
- examples/llama.android/**
server:
- changed-files:
- any-glob-to-any-file:
- examples/server/**
ggml:
- changed-files:
- any-glob-to-any-file:
- ggml/include/ggml*.h
- ggml/src/ggml*.c
- ggml/src/ggml*.cpp
- ggml/src/ggml*.h
- ggml-cuda/**
nix:
- changed-files:
- any-glob-to-any-file:
- "**/*.nix"
- .github/workflows/nix-*.yml
- .devops/nix/nixpkgs-instances.nix
embedding:
- changed-files:
- any-glob-to-any-file: examples/embedding/

View File

@@ -1,7 +0,0 @@
- [x] I have read the [contributing guidelines](https://github.com/ggerganov/llama.cpp/blob/master/CONTRIBUTING.md)
- Self-reported review complexity:
- [ ] Low
- [ ] Medium
- [ ] High

View File

@@ -1,6 +1,3 @@
# TODO: there have been some issues with the workflow, so disabling for now
# https://github.com/ggerganov/llama.cpp/issues/7893
#
# Benchmark
name: Benchmark
@@ -27,15 +24,15 @@ on:
push:
branches:
- master
paths: ['llama.cpp', 'ggml.c', 'ggml-backend.cpp', 'ggml-quants.c', '**/*.cu', 'examples/server/*.h*', 'examples/server/*.cpp']
pull_request_target:
paths: ['.github/workflows/bench.yml', '**/CMakeLists.txt', '**/Makefile', '**/*.h', '**/*.hpp', '**/*.c', '**/*.cpp', '**/*.cu', '**/*.swift', '**/*.m', 'examples/server/bench/**.*']
pull_request:
types: [opened, synchronize, reopened]
paths: ['llama.cpp', 'ggml.c', 'ggml-backend.cpp', 'ggml-quants.c', '**/*.cu', 'examples/server/*.h*', 'examples/server/*.cpp']
paths: ['.github/workflows/bench.yml', '**/CMakeLists.txt', '**/Makefile', '**/*.h', '**/*.hpp', '**/*.c', '**/*.cpp', '**/*.cu', '**/*.swift', '**/*.m', 'examples/server/bench/**.*']
schedule:
- cron: '04 2 * * *'
concurrency:
group: ${{ github.workflow }}-${{ github.ref }}-${{ github.head_ref || github.run_id }}-${{ github.event.inputs.sha }}
group: ${{ github.workflow }}-${{ github.ref }}
cancel-in-progress: true
jobs:
@@ -45,33 +42,11 @@ jobs:
RUNNER_LABEL: Standard_NC4as_T4_v3 # FIXME Do not find a way to not duplicate it
N_USERS: 8
DURATION: 10m
strategy:
matrix:
model: [phi-2]
ftype: [q4_0, q8_0, f16]
include:
- model: phi-2
ftype: q4_0
pr_comment_enabled: "true"
if: |
inputs.gpu-series == 'Standard_NC4as_T4_v3'
|| (
github.event_name == 'schedule'
&& github.ref_name == 'master'
&& github.repository_owner == 'ggerganov'
)
|| github.event_name == 'pull_request_target'
|| (
github.event_name == 'push'
&& github.event.ref == 'refs/heads/master'
&& github.repository_owner == 'ggerganov'
)
if: ${{ github.event.inputs.gpu-series == 'Standard_NC4as_T4_v3' || github.event.schedule || github.event.pull_request || github.event.push.ref == 'refs/heads/master' }}
steps:
- name: Clone
id: checkout
uses: actions/checkout@v4
uses: actions/checkout@v3
with:
fetch-depth: 0
ref: ${{ github.event.inputs.sha || github.event.pull_request.head.sha || github.sha || github.head_ref || github.ref_name }}
@@ -94,25 +69,21 @@ jobs:
sleep 0.1
done
- name: Set up Go
uses: actions/setup-go@v5
with:
go-version: '1.21'
- name: Install k6 and xk6-sse
- name: Install k6
id: k6_installation
run: |
cd examples/server/bench
go install go.k6.io/xk6/cmd/xk6@latest
xk6 build master \
--with github.com/phymbert/xk6-sse
wget --quiet https://github.com/grafana/k6/releases/download/v0.49.0/k6-v0.49.0-linux-amd64.tar.gz
tar xzf k6*.tar.gz --strip-components=1
- name: Build
id: cmake_build
run: |
set -eux
cmake -B build \
-DGGML_NATIVE=OFF \
mkdir build
cd build
cmake .. \
-DLLAMA_NATIVE=OFF \
-DLLAMA_BUILD_SERVER=ON \
-DLLAMA_CURL=ON \
-DLLAMA_CUBLAS=ON \
@@ -122,7 +93,7 @@ jobs:
-DLLAMA_FATAL_WARNINGS=OFF \
-DLLAMA_ALL_WARNINGS=OFF \
-DCMAKE_BUILD_TYPE=Release;
cmake --build build --config Release -j $(nproc) --target llama-server
cmake --build . --config Release -j $(nproc) --target server
- name: Download the dataset
id: download_dataset
@@ -132,22 +103,20 @@ jobs:
- name: Server bench
id: server_bench
env:
HEAD_REF: ${{ github.head_ref || github.ref_name }}
run: |
set -eux
cd examples/server/bench
source venv/bin/activate
python bench.py \
BENCH_K6_BIN_PATH=./k6 python bench.py \
--runner-label ${{ env.RUNNER_LABEL }} \
--name ${{ github.job }} \
--branch $HEAD_REF \
--branch ${{ github.head_ref || github.ref_name }} \
--commit ${{ github.event.inputs.sha || github.event.pull_request.head.sha || github.sha }} \
--scenario script.js \
--duration ${{ github.event.inputs.duration || env.DURATION }} \
--hf-repo ggml-org/models \
--hf-file ${{ matrix.model }}/ggml-model-${{ matrix.ftype }}.gguf \
--hf-file phi-2/ggml-model-q4_0.gguf \
--model-path-prefix /models \
--parallel ${{ env.N_USERS }} \
-ngl 33 \
@@ -165,7 +134,7 @@ jobs:
- uses: actions/upload-artifact@v4
with:
name: bench-server-${{ github.job }}-${{ env.RUNNER_LABEL }}-${{ matrix.model }}-${{ matrix.ftype }}
name: benchmark-results
compression-level: 9
path: |
examples/server/bench/*.jpg
@@ -177,7 +146,7 @@ jobs:
with:
authToken: ${{secrets.GITHUB_TOKEN}}
sha: ${{ inputs.sha || github.event.pull_request.head.sha || github.sha }}
context: bench-server-${{ github.job }}-${{ env.RUNNER_LABEL }}-${{ matrix.model }}-${{ matrix.ftype }}
context: bench-server-baseline
description: |
${{ env.BENCH_RESULTS }}
state: 'success'
@@ -234,26 +203,21 @@ jobs:
- name: Comment PR
uses: mshick/add-pr-comment@v2
id: comment_pr
if: ${{ github.event.pull_request != '' && matrix.pr_comment_enabled == 'true' }}
if: ${{ github.event.pull_request != '' }}
with:
message-id: bench-server-${{ github.job }}-${{ env.RUNNER_LABEL }}-${{ matrix.model }}-${{ matrix.ftype }}
message-id: bench-${{ github.job }}-${{ env.RUNNER_LABEL }}
message: |
<p align="center">
📈 **llama.cpp server** for _${{ github.job }}_ on _${{ env.RUNNER_LABEL }}_: **${{ env.BENCH_ITERATIONS}} iterations** 🚀
📈 **llama.cpp server** for _${{ github.job }}_ on _${{ env.RUNNER_LABEL }}_ for `${{ matrix.model }}`-`${{ matrix.ftype }}`: **${{ env.BENCH_ITERATIONS}} iterations** 🚀
</p>
- Concurrent users: ${{ env.N_USERS }}, duration: ${{ github.event.inputs.duration || env.DURATION }}
- HTTP request : avg=${{ env.HTTP_REQ_DURATION_AVG }}ms p(90)=${{ env.HTTP_REQ_DURATION_P_90_ }}ms fails=${{ env.HTTP_REQ_FAILED_PASSES }}, finish reason: stop=${{ env.LLAMACPP_COMPLETIONS_STOP_RATE_PASSES }} truncated=${{ env.LLAMACPP_COMPLETIONS_TRUNCATED_RATE_PASSES }}
- Prompt processing (pp): avg=${{ env.LLAMACPP_PROMPT_TOKENS_AVG }}tk/s p(90)=${{ env.LLAMACPP_PROMPT_TOKENS_P_90_ }}tk/s **total=${{ env.LLAMACPP_PROMPT_TOKENS_TOTAL_COUNTER_RATE }}tk/s**
- Token generation (tg): avg=${{ env.LLAMACPP_TOKENS_SECOND_AVG }}tk/s p(90)=${{ env.LLAMACPP_TOKENS_SECOND_P_90_ }}tk/s **total=${{ env.LLAMACPP_COMPLETION_TOKENS_TOTAL_COUNTER_RATE }}tk/s**
- ${{ env.BENCH_GRAPH_XLABEL }}
<details>
<summary>Expand details for performance related PR only</summary>
- Concurrent users: ${{ env.N_USERS }}, duration: ${{ github.event.inputs.duration || env.DURATION }}
- HTTP request : avg=${{ env.HTTP_REQ_DURATION_AVG }}ms p(95)=${{ env.HTTP_REQ_DURATION_P_95_ }}ms fails=${{ env.HTTP_REQ_FAILED_PASSES }}, finish reason: stop=${{ env.LLAMACPP_COMPLETIONS_STOP_RATE_PASSES }} truncated=${{ env.LLAMACPP_COMPLETIONS_TRUNCATED_RATE_PASSES }}
- Prompt processing (pp): avg=${{ env.LLAMACPP_PROMPT_PROCESSING_SECOND_AVG }}tk/s p(95)=${{ env.LLAMACPP_PROMPT_PROCESSING_SECOND_P_95_ }}tk/s
- Token generation (tg): avg=${{ env.LLAMACPP_TOKENS_SECOND_AVG }}tk/s p(95)=${{ env.LLAMACPP_TOKENS_SECOND_P_95_ }}tk/s
- ${{ env.BENCH_GRAPH_XLABEL }}
<summary>Time series</summary>
<p align="center">

File diff suppressed because it is too large Load Diff

View File

@@ -3,11 +3,6 @@ on:
schedule:
- cron: "42 0 * * *"
# Fine-grant permission
# https://docs.github.com/en/actions/security-for-github-actions/security-guides/automatic-token-authentication#modifying-the-permissions-for-the-github_token
permissions:
issues: write
jobs:
close-issues:
runs-on: ubuntu-latest
@@ -17,7 +12,7 @@ jobs:
steps:
- uses: actions/stale@v5
with:
exempt-issue-labels: "refactor,help wanted,good first issue,research,bug"
exempt-issue-labels: "refactor,help wanted,good first issue,research"
days-before-issue-stale: 30
days-before-issue-close: 14
stale-issue-label: "stale"

40
.github/workflows/code-coverage.yml vendored Normal file
View File

@@ -0,0 +1,40 @@
name: Code Coverage
on: [push, pull_request]
env:
GGML_NLOOP: 3
GGML_N_THREADS: 1
concurrency:
group: ${{ github.workflow }}-${{ github.ref }}
cancel-in-progress: true
jobs:
run:
runs-on: ubuntu-20.04
steps:
- name: Checkout
uses: actions/checkout@v3
- name: Dependencies
run: |
sudo apt-get update
sudo apt-get install build-essential gcc-8 lcov
- name: Build
run: CC=gcc-8 make -j LLAMA_CODE_COVERAGE=1 tests
- name: Run tests
run: CC=gcc-8 make test
- name: Generate coverage report
run: |
make coverage
make lcov-report
- name: Upload coverage to Codecov
uses: codecov/codecov-action@v3
env:
CODECOV_TOKEN: ${{ secrets.CODECOV_TOKEN }}
with:
files: lcov-report/coverage.info

View File

@@ -10,26 +10,19 @@
name: Publish Docker image
on:
#pull_request:
pull_request:
push:
branches:
- master
paths: ['.github/workflows/docker.yml', '.devops/*.Dockerfile', '**/CMakeLists.txt', '**/Makefile', '**/*.h', '**/*.hpp', '**/*.c', '**/*.cpp', '**/*.cu', '**/*.cuh', '**/*.swift', '**/*.m', '**/*.metal']
workflow_dispatch: # allows manual triggering, useful for debugging
concurrency:
group: ${{ github.workflow }}-${{ github.head_ref && github.ref || github.run_id }}
group: ${{ github.workflow }}-${{ github.ref }}
cancel-in-progress: true
# Fine-grant permission
# https://docs.github.com/en/actions/security-for-github-actions/security-guides/automatic-token-authentication#modifying-the-permissions-for-the-github_token
permissions:
packages: write
jobs:
push_to_registry:
name: Push Docker image to Docker Hub
#if: github.event.pull_request.draft == false
if: github.event.pull_request.draft == false
runs-on: ubuntu-latest
env:
@@ -37,26 +30,23 @@ jobs:
strategy:
matrix:
config:
- { tag: "light", dockerfile: ".devops/llama-cli.Dockerfile", platforms: "linux/amd64,linux/arm64" }
- { tag: "server", dockerfile: ".devops/llama-server.Dockerfile", platforms: "linux/amd64,linux/arm64" }
- { tag: "light", dockerfile: ".devops/main.Dockerfile", platforms: "linux/amd64,linux/arm64" }
- { tag: "full", dockerfile: ".devops/full.Dockerfile", platforms: "linux/amd64,linux/arm64" }
- { tag: "light-cuda", dockerfile: ".devops/llama-cli-cuda.Dockerfile", platforms: "linux/amd64" }
- { tag: "server-cuda", dockerfile: ".devops/llama-server-cuda.Dockerfile", platforms: "linux/amd64" }
- { tag: "server", dockerfile: ".devops/server.Dockerfile", platforms: "linux/amd64,linux/arm64" }
# NOTE(canardletter): The CUDA builds on arm64 are very slow, so I
# have disabled them for now until the reason why
# is understood.
- { tag: "light-cuda", dockerfile: ".devops/main-cuda.Dockerfile", platforms: "linux/amd64" }
- { tag: "full-cuda", dockerfile: ".devops/full-cuda.Dockerfile", platforms: "linux/amd64" }
- { tag: "light-musa", dockerfile: ".devops/llama-cli-musa.Dockerfile", platforms: "linux/amd64" }
- { tag: "server-musa", dockerfile: ".devops/llama-server-musa.Dockerfile", platforms: "linux/amd64" }
- { tag: "full-musa", dockerfile: ".devops/full-musa.Dockerfile", platforms: "linux/amd64" }
# Note: the rocm images are failing due to a compiler error and are disabled until this is fixed to allow the workflow to complete
#- { tag: "light-rocm", dockerfile: ".devops/llama-cli-rocm.Dockerfile", platforms: "linux/amd64,linux/arm64" }
#- { tag: "server-rocm", dockerfile: ".devops/llama-server-rocm.Dockerfile", platforms: "linux/amd64,linux/arm64" }
#- { tag: "full-rocm", dockerfile: ".devops/full-rocm.Dockerfile", platforms: "linux/amd64,linux/arm64" }
- { tag: "light-intel", dockerfile: ".devops/llama-cli-intel.Dockerfile", platforms: "linux/amd64" }
- { tag: "server-intel", dockerfile: ".devops/llama-server-intel.Dockerfile", platforms: "linux/amd64" }
- { tag: "server-cuda", dockerfile: ".devops/server-cuda.Dockerfile", platforms: "linux/amd64" }
- { tag: "light-rocm", dockerfile: ".devops/main-rocm.Dockerfile", platforms: "linux/amd64,linux/arm64" }
- { tag: "full-rocm", dockerfile: ".devops/full-rocm.Dockerfile", platforms: "linux/amd64,linux/arm64" }
- { tag: "server-rocm", dockerfile: ".devops/server-rocm.Dockerfile", platforms: "linux/amd64,linux/arm64" }
- { tag: "light-intel", dockerfile: ".devops/main-intel.Dockerfile", platforms: "linux/amd64" }
- { tag: "server-intel", dockerfile: ".devops/server-intel.Dockerfile", platforms: "linux/amd64" }
steps:
- name: Check out the repo
uses: actions/checkout@v4
with:
fetch-depth: 0 # preserve git history, so we can determine the build number
uses: actions/checkout@v3
- name: Set up QEMU
uses: docker/setup-qemu-action@v2
@@ -71,34 +61,6 @@ jobs:
username: ${{ github.repository_owner }}
password: ${{ secrets.GITHUB_TOKEN }}
- name: Determine tag name
id: tag
shell: bash
run: |
BUILD_NUMBER="$(git rev-list --count HEAD)"
SHORT_HASH="$(git rev-parse --short=7 HEAD)"
REPO_OWNER="${GITHUB_REPOSITORY_OWNER@L}" # to lower case
REPO_NAME="${{ github.event.repository.name }}"
# determine tag name postfix (build number, commit hash)
if [[ "${{ env.GITHUB_BRANCH_NAME }}" == "master" ]]; then
TAG_POSTFIX="b${BUILD_NUMBER}"
else
SAFE_NAME=$(echo "${{ env.GITHUB_BRANCH_NAME }}" | tr '/' '-')
TAG_POSTFIX="${SAFE_NAME}-${SHORT_HASH}"
fi
# list all tags possible
TAGS=""
TAGS="${TAGS}ghcr.io/${REPO_OWNER}/${REPO_NAME}:${{ matrix.config.tag }},"
TAGS="${TAGS}ghcr.io/${REPO_OWNER}/${REPO_NAME}:${{ matrix.config.tag }}-${TAG_POSTFIX}"
echo "output_tags=$TAGS" >> $GITHUB_OUTPUT
echo "output_tags=$TAGS" # print out for debugging
env:
GITHUB_BRANCH_NAME: ${{ github.head_ref || github.ref_name }}
GITHUB_REPOSITORY_OWNER: '${{ github.repository_owner }}'
# https://github.com/jlumbroso/free-disk-space/tree/54081f138730dfa15788a46383842cd2f914a1be#example
- name: Free Disk Space (Ubuntu)
uses: jlumbroso/free-disk-space@main
@@ -116,13 +78,34 @@ jobs:
docker-images: true
swap-storage: true
- name: Build and push Docker image (tagged + versioned)
- name: Determine tag name
id: tag
shell: bash
run: |
BUILD_NUMBER="$(git rev-list --count HEAD)"
SHORT_HASH="$(git rev-parse --short=7 HEAD)"
if [[ "${{ env.BRANCH_NAME }}" == "master" ]]; then
echo "name=b${BUILD_NUMBER}" >> $GITHUB_OUTPUT
else
SAFE_NAME=$(echo "${{ env.BRANCH_NAME }}" | tr '/' '-')
echo "name=${SAFE_NAME}-b${BUILD_NUMBER}-${SHORT_HASH}" >> $GITHUB_OUTPUT
fi
- name: Build and push Docker image (versioned)
if: github.event_name == 'push'
uses: docker/build-push-action@v6
uses: docker/build-push-action@v4
with:
context: .
push: true
platforms: ${{ matrix.config.platforms }}
# tag list is generated from step above
tags: ${{ steps.tag.outputs.output_tags }}
tags: "ghcr.io/${{ github.repository_owner }}/llama.cpp:${{ matrix.config.tag }}-${{ env.COMMIT_SHA }}"
file: ${{ matrix.config.dockerfile }}
- name: Build and push Docker image (tagged)
uses: docker/build-push-action@v4
with:
context: .
push: ${{ github.event_name == 'push' }}
platforms: ${{ matrix.config.platforms }}
tags: "ghcr.io/${{ github.repository_owner }}/llama.cpp:${{ matrix.config.tag }},ghcr.io/${{ github.repository_owner }}/llama.cpp:${{ matrix.config.tag }}-${{ steps.tag.outputs.name }}"
file: ${{ matrix.config.dockerfile }}

View File

@@ -15,13 +15,13 @@ on:
- master
concurrency:
group: ${{ github.workflow }}-${{ github.head_ref && github.ref || github.run_id }}
group: ${{ github.workflow }}-${{ github.ref }}
cancel-in-progress: true
jobs:
editorconfig:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- uses: actions/checkout@v3
- uses: editorconfig-checker/action-editorconfig-checker@main
- run: editorconfig-checker

View File

@@ -24,9 +24,9 @@ jobs:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- uses: actions/checkout@v3
- name: Set up Python
uses: actions/setup-python@v5
uses: actions/setup-python@v2
with:
python-version: '3.9.x'
- name: Install dependencies

View File

@@ -1,17 +0,0 @@
name: "Pull Request Labeler"
on:
- pull_request_target
jobs:
labeler:
permissions:
contents: read
pull-requests: write
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
with:
repository: "ggerganov/llama.cpp"
- uses: actions/labeler@v5
with:
configuration-path: '.github/labeler.yml'

View File

@@ -18,16 +18,9 @@ on:
paths: ['**/*.nix', 'flake.lock']
concurrency:
group: ${{ github.workflow }}-${{ github.head_ref && github.ref || github.run_id }}
group: ${{ github.workflow }}-${{ github.ref }}
cancel-in-progress: true
# Fine-grant permission
# https://docs.github.com/en/actions/security-for-github-actions/security-guides/automatic-token-authentication#modifying-the-permissions-for-the-github_token
permissions:
# https://github.com/DeterminateSystems/nix-installer-action?tab=readme-ov-file#with-flakehub
id-token: write
contents: read
jobs:
nix-build-aarch64:
runs-on: ubuntu-latest

View File

@@ -9,16 +9,9 @@ on:
types: [opened, synchronize, reopened]
concurrency:
group: ${{ github.workflow }}-${{ github.head_ref && github.ref || github.run_id }}
group: ${{ github.workflow }}-${{ github.ref }}
cancel-in-progress: true
# Fine-grant permission
# https://docs.github.com/en/actions/security-for-github-actions/security-guides/automatic-token-authentication#modifying-the-permissions-for-the-github_token
permissions:
# https://github.com/DeterminateSystems/nix-installer-action?tab=readme-ov-file#with-flakehub
id-token: write
contents: read
jobs:
nix-eval:
strategy:

View File

@@ -6,16 +6,18 @@ on:
- '.github/workflows/python-check-requirements.yml'
- 'scripts/check-requirements.sh'
- 'convert*.py'
- '**/requirements*.txt'
- 'requirements.txt'
- 'requirements/*.txt'
pull_request:
paths:
- '.github/workflows/python-check-requirements.yml'
- 'scripts/check-requirements.sh'
- 'convert*.py'
- '**/requirements*.txt'
- 'requirements.txt'
- 'requirements/*.txt'
concurrency:
group: ${{ github.workflow }}-${{ github.head_ref && github.ref || github.run_id }}
group: ${{ github.workflow }}-${{ github.ref }}
cancel-in-progress: true
jobs:
@@ -24,9 +26,9 @@ jobs:
name: check-requirements
steps:
- name: Check out source repository
uses: actions/checkout@v4
uses: actions/checkout@v3
- name: Set up Python environment
uses: actions/setup-python@v5
uses: actions/setup-python@v4
with:
python-version: "3.11"
- name: Run check-requirements.sh script

View File

@@ -3,7 +3,7 @@ name: flake8 Lint
on: [push, pull_request]
concurrency:
group: ${{ github.workflow }}-${{ github.head_ref && github.ref || github.run_id }}
group: ${{ github.workflow }}-${{ github.ref }}
cancel-in-progress: true
jobs:
@@ -12,12 +12,13 @@ jobs:
name: Lint
steps:
- name: Check out source repository
uses: actions/checkout@v4
uses: actions/checkout@v3
- name: Set up Python environment
uses: actions/setup-python@v5
uses: actions/setup-python@v4
with:
python-version: "3.11"
- name: flake8 Lint
uses: py-actions/flake8@v2
with:
plugins: "flake8-no-print"
ignore: "E203,E211,E221,E225,E231,E241,E251,E261,E266,E501,E701,E704,W503"
exclude: "examples/*,examples/*/**,*/**/__init__.py"

View File

@@ -1,40 +0,0 @@
name: Python Type-Check
on:
push:
paths:
- '.github/workflows/python-type-check.yml'
- 'pyrightconfig.json'
- '**.py'
- '**/requirements*.txt'
pull_request:
paths:
- '.github/workflows/python-type-check.yml'
- 'pyrightconfig.json'
- '**.py'
- '**/requirements*.txt'
concurrency:
group: ${{ github.workflow }}-${{ github.head_ref && github.ref || github.run_id }}
cancel-in-progress: true
jobs:
python-type-check:
runs-on: ubuntu-latest
name: pyright type-check
steps:
- name: Check out source repository
uses: actions/checkout@v4
- name: Set up Python environment
uses: actions/setup-python@v5
with:
python-version: "3.11"
- name: Install Python dependencies
# TODO: use a venv
run: pip install -r requirements/requirements-all.txt
- name: Type-check with Pyright
uses: jakebailey/pyright-action@v2
with:
version: 1.1.382
level: warning
warnings: true

View File

@@ -4,10 +4,6 @@ name: Server
on:
workflow_dispatch: # allows manual triggering
inputs:
sha:
description: 'Commit SHA1 to build'
required: false
type: string
slow_tests:
description: 'Run slow tests'
required: true
@@ -15,19 +11,15 @@ on:
push:
branches:
- master
paths: ['.github/workflows/server.yml', '**/CMakeLists.txt', '**/Makefile', '**/*.h', '**/*.hpp', '**/*.c', '**/*.cpp', '**/*.cu', '**/*.swift', '**/*.m', 'examples/server/**.*']
paths: ['.github/workflows/server.yml', '**/CMakeLists.txt', '**/Makefile', '**/*.h', '**/*.hpp', '**/*.c', '**/*.cpp', '**/*.cu', '**/*.swift', '**/*.m', 'examples/server/tests/**.*']
pull_request:
types: [opened, synchronize, reopened]
paths: ['.github/workflows/server.yml', '**/CMakeLists.txt', '**/Makefile', '**/*.h', '**/*.hpp', '**/*.c', '**/*.cpp', '**/*.cu', '**/*.swift', '**/*.m', 'examples/server/**.*']
env:
LLAMA_LOG_COLORS: 1
LLAMA_LOG_PREFIX: 1
LLAMA_LOG_TIMESTAMPS: 1
LLAMA_LOG_VERBOSITY: 10
paths: ['.github/workflows/server.yml', '**/CMakeLists.txt', '**/Makefile', '**/*.h', '**/*.hpp', '**/*.c', '**/*.cpp', '**/*.cu', '**/*.swift', '**/*.m', 'examples/server/tests/**.*']
schedule:
- cron: '0 0 * * *'
concurrency:
group: ${{ github.workflow }}-${{ github.ref }}-${{ github.head_ref || github.run_id }}
group: ${{ github.workflow }}-${{ github.ref }}
cancel-in-progress: true
jobs:
@@ -36,90 +28,62 @@ jobs:
strategy:
matrix:
sanitizer: [ADDRESS, UNDEFINED] # THREAD is broken
build_type: [RelWithDebInfo]
# TODO: temporary disabled due to linux kernel issues
#sanitizer: [ADDRESS, THREAD, UNDEFINED]
sanitizer: [UNDEFINED]
build_type: [Debug]
include:
- build_type: Release
sanitizer: ""
fail-fast: false # While -DLLAMA_SANITIZE_THREAD=ON is broken
container:
image: ubuntu:latest
ports:
- 8888
options: --cpus 4
steps:
- name: Clone
id: checkout
uses: actions/checkout@v3
with:
fetch-depth: 0
- name: Dependencies
id: depends
run: |
sudo apt-get update
sudo apt-get -y install \
apt-get update
apt-get -y install \
build-essential \
xxd \
git \
cmake \
curl \
python3-pip \
wget \
language-pack-en \
libcurl4-openssl-dev
- name: Clone
id: checkout
uses: actions/checkout@v4
with:
fetch-depth: 0
ref: ${{ github.event.inputs.sha || github.event.pull_request.head.sha || github.sha || github.head_ref || github.ref_name }}
- name: Python setup
id: setup_python
uses: actions/setup-python@v5
with:
python-version: '3.11'
- name: Build
id: cmake_build
run: |
mkdir build
cd build
cmake .. \
-DLLAMA_NATIVE=OFF \
-DLLAMA_BUILD_SERVER=ON \
-DLLAMA_CURL=ON \
-DCMAKE_BUILD_TYPE=${{ matrix.build_type }} \
-DLLAMA_SANITIZE_${{ matrix.sanitizer }}=ON ;
cmake --build . --config ${{ matrix.build_type }} -j $(nproc) --target server
- name: Tests dependencies
id: test_dependencies
run: |
pip install -r examples/server/tests/requirements.txt
- name: Verify server deps
id: verify_server_deps
run: |
git config --global --add safe.directory $(realpath .)
cd examples/server
git ls-files --others --modified
git status
./deps.sh
git status
not_ignored_files="$(git ls-files --others --modified)"
echo "Modified files: ${not_ignored_files}"
if [ -n "${not_ignored_files}" ]; then
echo "Repository is dirty or server deps are not built as expected"
echo "${not_ignored_files}"
exit 1
fi
- name: Build (no OpenMP)
id: cmake_build_no_openmp
if: ${{ matrix.sanitizer == 'THREAD' }}
run: |
cmake -B build \
-DGGML_NATIVE=OFF \
-DLLAMA_BUILD_SERVER=ON \
-DLLAMA_CURL=ON \
-DCMAKE_BUILD_TYPE=${{ matrix.build_type }} \
-DLLAMA_SANITIZE_${{ matrix.sanitizer }}=ON \
-DGGML_OPENMP=OFF ;
cmake --build build --config ${{ matrix.build_type }} -j $(nproc) --target llama-server
- name: Build
id: cmake_build
if: ${{ matrix.sanitizer != 'THREAD' }}
run: |
cmake -B build \
-DGGML_NATIVE=OFF \
-DLLAMA_BUILD_SERVER=ON \
-DLLAMA_CURL=ON \
-DCMAKE_BUILD_TYPE=${{ matrix.build_type }} \
-DLLAMA_SANITIZE_${{ matrix.sanitizer }}=ON ;
cmake --build build --config ${{ matrix.build_type }} -j $(nproc) --target llama-server
- name: Tests
id: server_integration_tests
if: ${{ !matrix.disabled_on_pr || !github.event.pull_request }}
run: |
cd examples/server/tests
PORT=8888 ./tests.sh
@@ -133,15 +97,14 @@ jobs:
server-windows:
runs-on: windows-2019
runs-on: windows-latest
steps:
- name: Clone
id: checkout
uses: actions/checkout@v4
uses: actions/checkout@v3
with:
fetch-depth: 0
ref: ${{ github.event.inputs.sha || github.event.pull_request.head.sha || github.sha || github.head_ref || github.ref_name }}
- name: libCURL
id: get_libcurl
@@ -155,8 +118,10 @@ jobs:
- name: Build
id: cmake_build
run: |
cmake -B build -DLLAMA_CURL=ON -DCURL_LIBRARY="$env:RUNNER_TEMP/libcurl/lib/libcurl.dll.a" -DCURL_INCLUDE_DIR="$env:RUNNER_TEMP/libcurl/include"
cmake --build build --config Release -j ${env:NUMBER_OF_PROCESSORS} --target llama-server
mkdir build
cd build
cmake .. -DLLAMA_CURL=ON -DCURL_LIBRARY="$env:RUNNER_TEMP/libcurl/lib/libcurl.dll.a" -DCURL_INCLUDE_DIR="$env:RUNNER_TEMP/libcurl/include"
cmake --build . --config Release -j ${env:NUMBER_OF_PROCESSORS} --target server
- name: Python setup
id: setup_python
@@ -179,7 +144,6 @@ jobs:
if: ${{ !matrix.disabled_on_pr || !github.event.pull_request }}
run: |
cd examples/server/tests
$env:PYTHONIOENCODING = ":replace"
behave.exe --summary --stop --no-capture --exclude 'issues|wrong_usages|passkey' --tags llama.cpp
- name: Slow tests

29
.github/workflows/zig-build.yml vendored Normal file
View File

@@ -0,0 +1,29 @@
name: Zig CI
on:
pull_request:
push:
branches:
- master
concurrency:
group: ${{ github.workflow }}-${{ github.ref }}
cancel-in-progress: true
jobs:
build:
strategy:
fail-fast: false
matrix:
runs-on: [ubuntu-latest, macos-latest, windows-latest]
runs-on: ${{ matrix.runs-on }}
steps:
- uses: actions/checkout@v3
with:
submodules: recursive
fetch-depth: 0
- uses: goto-bus-stop/setup-zig@v2
with:
version: 0.11.0
- name: Build Summary
run: zig build --summary all -freference-trace

184
.gitignore vendored
View File

@@ -1,135 +1,105 @@
# Extensions
*.a
*.bat
*.bin
*.dll
*.dot
*.etag
*.exe
*.gcda
*.gcno
*.gcov
*.gguf
*.gguf.json
*.lastModified
*.log
*.metallib
*.o
*.a
*.so
*.gguf
*.bin
*.exe
*.dll
*.log
*.gcov
*.gcno
*.gcda
*.dot
*.bat
*.tmp
# IDE / OS
*.metallib
*.etag
*.lastModified
.DS_Store
.build/
.cache/
.ccls-cache/
.direnv/
.DS_Store
.envrc
.idea/
.swiftpm
.venv
.clang-tidy
.vs/
.vscode/
nppBackup
.idea/
# Coverage
gcovr-report/
lcov-report/
# Build Artifacts
tags
.build/
build*
!build-info.cmake
!build-info.cpp.in
!build-info.sh
!build.zig
!docs/build.md
/libllama.so
/llama-*
/vulkan-shaders-gen
android-ndk-*
arm_neon.h
cmake-build-*
CMakeSettings.json
compile_commands.json
ggml-metal-embed.metal
llama-batched-swift
/rpc-server
lcov-report/
gcovr-report/
build*
cmake-build-*
out/
tmp/
autogen-*.md
# Deprecated
/main
/server
# CI
!.github/workflows/*.yml
# Models
models/*
models-mnt
!models/.editorconfig
!models/ggml-vocab-*.gguf*
# Zig
/Pipfile
/baby-llama
/beam-search
/benchmark-matmult
/convert-llama2c-to-ggml
/embd-input-test
/embedding
/gguf
/gguf-llama-simple
/gguf-split
/gritlm
/imatrix
/infill
/libllama.so
/llama-bench
/llava-cli
/lookahead
/lookup
/lookup-create
/lookup-merge
/lookup-stats
/main
/metal
/passkey
/perplexity
/q8dot
/quantize
/quantize-stats
/result
/save-load-state
/server
/simple
/batched
/batched-bench
/export-lora
/finetune
/retrieval
/speculative
/parallel
/train-text-from-scratch
/tokenize
/vdot
/common/build-info.cpp
arm_neon.h
compile_commands.json
CMakeSettings.json
__pycache__
dist
zig-out/
zig-cache/
# Logs
ppl-*.txt
qnt-*.txt
perf-*.txt
# Examples
examples/jeopardy/results.txt
examples/server/*.css.hpp
examples/server/*.html.hpp
examples/server/*.js.hpp
examples/server/*.mjs.hpp
!build_64.sh
!examples/*.bat
!examples/*/*.kts
!examples/*/*/*.kts
!examples/sycl/*.bat
!examples/sycl/*.sh
# Python
/.venv
__pycache__/
*/poetry.lock
poetry.lock
poetry.toml
# Nix
/result
# Test binaries
/tests/test-backend-ops
/tests/test-double-float
/tests/test-grad0
/tests/test-grammar-parser
/tests/test-llama-grammar
/tests/test-opt
/tests/test-quantize-fns
/tests/test-quantize-perf
/tests/test-rope
/tests/test-sampling
/tests/test-tokenizer-0
/tests/test-tokenizer-1-bpe
/tests/test-tokenizer-1-spm
# Scripts
!/scripts/install-oneapi.bat
# Test models for lora adapters
/lora-tests
nppBackup

2
.gitmodules vendored
View File

@@ -1,3 +1,3 @@
[submodule "kompute"]
path = ggml/src/kompute
path = kompute
url = https://github.com/nomic-ai/kompute.git

View File

@@ -3,14 +3,13 @@
exclude: prompts/.*.txt
repos:
- repo: https://github.com/pre-commit/pre-commit-hooks
rev: v4.6.0
rev: v3.2.0
hooks:
- id: trailing-whitespace
- id: end-of-file-fixer
- id: check-yaml
- id: check-added-large-files
- repo: https://github.com/PyCQA/flake8
rev: 7.0.0
rev: 6.0.0
hooks:
- id: flake8
additional_dependencies: [flake8-no-print]

782
AUTHORS
View File

@@ -1,782 +0,0 @@
# date: Wed Jun 26 19:36:34 EEST 2024
# this file is auto-generated by scripts/gen-authors.sh
0cc4m <picard12@live.de>
0xspringtime <110655352+0xspringtime@users.noreply.github.com>
20kdc <asdd2808@gmail.com>
2f38b454 <dxf@protonmail.com>
3ooabkhxtn <31479382+3ooabkhxtn@users.noreply.github.com>
44670 <44670@users.noreply.github.com>
AN Long <aisk@users.noreply.github.com>
AT <manyoso@users.noreply.github.com>
Aarni Koskela <akx@iki.fi>
Aaron Miller <apage43@ninjawhale.com>
Aaryaman Vasishta <aaryaman.vasishta@amd.com>
Abheek Gulati <abheekg@hotmail.com>
Abhilash Majumder <30946547+abhilash1910@users.noreply.github.com>
Abhishek Gopinath K <31348521+overtunned@users.noreply.github.com>
Adithya Balaji <adithya.b94@gmail.com>
AdithyanI <adithyan.i4internet@gmail.com>
Adrian <smith.adriane@gmail.com>
Adrian Hesketh <a-h@users.noreply.github.com>
Ahmet Zeer <ahmed.zeer@std.yildiz.edu.tr>
AidanBeltonS <87009434+AidanBeltonS@users.noreply.github.com>
Aisuko <urakiny@gmail.com>
Akarshan Biswas <akarshanbiswas@fedoraproject.org>
Albert Jin <albert.jin@gmail.com>
Alberto <57916483+albbus-stack@users.noreply.github.com>
Alex <awhill19@icloud.com>
Alex Azarov <alex@azarov.by>
Alex Azarov <alexander.azarov@mapbox.com>
Alex Klinkhamer <from.github.com.917@grencez.dev>
Alex Klinkhamer <git@grencez.dev>
Alex Nguyen <tiendung@users.noreply.github.com>
Alex Petenchea <alex.petenchea@gmail.com>
Alex Renda <alexrenda@users.noreply.github.com>
Alex von Gluck IV <kallisti5@unixzen.com>
Alexey Parfenov <zxed@alkatrazstudio.net>
Ali Chraghi <63465728+alichraghi@users.noreply.github.com>
Ali Nehzat <ali.nehzat@thanks.dev>
Ali Tariq <ali.tariq@10xengineers.ai>
Alon <alonfaraj@gmail.com>
AlpinDale <52078762+AlpinDale@users.noreply.github.com>
Amir <amir_zia@outlook.com>
AmirAli Mirian <37371367+amiralimi@users.noreply.github.com>
Ananta Bastola <anantarajbastola@gmail.com>
Anas Ahouzi <112881240+aahouzi@users.noreply.github.com>
András Salamon <ott2@users.noreply.github.com>
Andrei <abetlen@gmail.com>
Andrew Canis <andrew.canis@gmail.com>
Andrew Downing <andrew2085@gmail.com>
Andrew Duffy <a10y@users.noreply.github.com>
Andrew Godfrey <AndrewGodfrey@users.noreply.github.com>
Andy Tai <andy-tai@users.noreply.github.com>
Arik Poznanski <arikpoz@users.noreply.github.com>
Artem <guinmoon@gmail.com>
Artem Zinnatullin <ceo@abstractny.gay>
Artyom Lebedev <vagran.ast@gmail.com>
Asbjørn Olling <asbjornolling@gmail.com>
Ásgeir Bjarni Ingvarsson <asgeir@fundinn.org>
Ashish <1856117+ashishdatta@users.noreply.github.com>
Ashok Gelal <401055+ashokgelal@users.noreply.github.com>
Ashraful Islam <ashraful.meche@gmail.com>
Atsushi Tatsuma <yoshoku@outlook.com>
Austin <77757836+teleprint-me@users.noreply.github.com>
AustinMroz <austinmroz@utexas.edu>
BADR <contact@pythops.com>
Bach Le <bach@bullno1.com>
Bailey Chittle <39804642+bachittle@users.noreply.github.com>
BarfingLemurs <128182951+BarfingLemurs@users.noreply.github.com>
Bartowski <ckealty1182@gmail.com>
Behnam M <58621210+ibehnam@users.noreply.github.com>
Ben Ashbaugh <ben.ashbaugh@intel.com>
Ben Garney <bengarney@users.noreply.github.com>
Ben Siraphob <bensiraphob@gmail.com>
Ben Williams <ben@719ben.com>
Benjamin Findley <39356821+Kartoffelsaft@users.noreply.github.com>
Benjamin Lecaillon <84293038+blecaillon@users.noreply.github.com>
Bernat Vadell <hounter.caza@gmail.com>
Bingan <70050083+binganao@users.noreply.github.com>
Bodo Graumann <mail@bodograumann.de>
Bono Lv <lvscar@users.noreply.github.com>
Borislav Stanimirov <b.stanimirov@abv.bg>
Branden Butler <bwtbutler@hotmail.com>
Brian <mofosyne@gmail.com>
Bruce MacDonald <brucewmacdonald@gmail.com>
Bryan Honof <bryanhonof@gmail.com>
CJ Pais <cj@cjpais.com>
CRD716 <crd716@gmail.com>
Calvin Laurenson <calvin@laurenson.dev>
Cameron <csteele@steelecameron.com>
Cameron Kaiser <classilla@users.noreply.github.com>
Carolinabanana <140120812+Carolinabanana@users.noreply.github.com>
Casey Primozic <casey@cprimozic.net>
Casey Primozic <me@ameo.link>
CausalLM <148736309+CausalLM@users.noreply.github.com>
Cebtenzzre <cebtenzzre@gmail.com>
Chad Brewbaker <crb002@gmail.com>
Chao Jiang <jc19chaoj@zoho.com>
Cheng Shao <terrorjack@type.dance>
Chris Elrod <elrodc@gmail.com>
Chris Kuehl <ckuehl@ckuehl.me>
Christian Demsar <christian@github.email.demsar.us>
Christian Demsar <crasm@git.vczf.us>
Christian Falch <875252+chrfalch@users.noreply.github.com>
Christian Kögler <ck3d@gmx.de>
Christian Zhou-Zheng <59622928+christianazinn@users.noreply.github.com>
Clark Saben <76020733+csaben@users.noreply.github.com>
Clint Herron <hanclinto@gmail.com>
CrispStrobe <154636388+CrispStrobe@users.noreply.github.com>
Cuong Trinh Manh <nguoithichkhampha@gmail.com>
DAN™ <dranger003@gmail.com>
Damian Stewart <d@damianstewart.com>
Dane Madsen <dane_madsen@hotmail.com>
DaniAndTheWeb <57776841+DaniAndTheWeb@users.noreply.github.com>
Daniel Bevenius <daniel.bevenius@gmail.com>
Daniel Drake <drake@endlessos.org>
Daniel Hiltgen <dhiltgen@users.noreply.github.com>
Daniel Illescas Romero <illescas.daniel@protonmail.com>
Daniele <57776841+daniandtheweb@users.noreply.github.com>
DannyDaemonic <DannyDaemonic@gmail.com>
Dat Quoc Nguyen <2412555+datquocnguyen@users.noreply.github.com>
Dave <dave-fl@users.noreply.github.com>
Dave Airlie <airlied@gmail.com>
Dave Airlie <airlied@redhat.com>
Dave Della Costa <ddellacosta+github@gmail.com>
David Friehs <david@friehs.info>
David Kennedy <dakennedyd@gmail.com>
David Pflug <david@pflug.email>
David Renshaw <dwrenshaw@gmail.com>
David Sommers <12738+databyte@users.noreply.github.com>
David Yang <davidyang6us@gmail.com>
Dawid Potocki <github@dawidpotocki.com>
Dawid Wysocki <62249621+TortillaZHawaii@users.noreply.github.com>
Dean <Dean.Sinaean@gmail.com>
Deins <deinsegle@gmail.com>
Deven Mistry <31466137+deven367@users.noreply.github.com>
Didzis Gosko <didzis@users.noreply.github.com>
Djip007 <djip.perois@free.fr>
Don Mahurin <dmahurin@users.noreply.github.com>
DooWoong Lee (David) <manics99@naver.com>
Doomsdayrs <38189170+Doomsdayrs@users.noreply.github.com>
Douglas Hanley <thesecretaryofwar@gmail.com>
Dr. Tom Murphy VII Ph.D <499244+tom7@users.noreply.github.com>
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Ed Lee <edilee@mozilla.com>
Ed Lepedus <ed.lepedus@googlemail.com>
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Edward Taylor <edeetee@gmail.com>
Elaine <elaine.zosa@gmail.com>
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Engininja2 <139037756+Engininja2@users.noreply.github.com>
Equim <sayaka@ekyu.moe>
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Eve <139727413+netrunnereve@users.noreply.github.com>
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Ewout ter Hoeven <E.M.terHoeven@student.tudelft.nl>
ExtReMLapin <3909752+ExtReMLapin@users.noreply.github.com>
FK <sozforex@gmail.com>
Fabian <cmdrf@users.noreply.github.com>
Fabio R. Sluzala <Fabio3rs@users.noreply.github.com>
Faez Shakil <faez.shakil@gmail.com>
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Fattire <528174+fat-tire@users.noreply.github.com>
Felix <stenbackfelix@gmail.com>
Finn Voorhees <finnvoorhees@gmail.com>
Firat <firatkiral@gmail.com>
Folko-Ven <71110216+Folko-Ven@users.noreply.github.com>
Foul-Tarnished <107711110+Foul-Tarnished@users.noreply.github.com>
Francisco Melo <43780565+francis2tm@users.noreply.github.com>
Frank Mai <thxcode0824@gmail.com>
FrankHB <frankhb1989@gmail.com>
Fred Douglas <43351173+fredlas@users.noreply.github.com>
Frederik Vogel <Schaltfehler@users.noreply.github.com>
Gabe Goodhart <gabe.l.hart@gmail.com>
GainLee <perfecter.gen@gmail.com>
Galunid <karolek1231456@gmail.com>
Gary Linscott <glinscott@gmail.com>
Gary Mulder <gjmulder@gmail.com>
Gavin Zhao <gavinzhaojw@protonmail.com>
Genkagaku.GPT <hlhr202@163.com>
Georgi Gerganov <ggerganov@gmail.com>
Gilad S <giladgd@users.noreply.github.com>
Giuseppe Scrivano <giuseppe@scrivano.org>
GiviMAD <GiviMAD@users.noreply.github.com>
Govlzkoy <gotope@users.noreply.github.com>
Guillaume "Vermeille" Sanchez <Guillaume.V.Sanchez@gmail.com>
Guillaume Wenzek <gwenzek@users.noreply.github.com>
Guoteng <32697156+SolenoidWGT@users.noreply.github.com>
Gustavo Rocha Dias <91472747+gustrd@users.noreply.github.com>
Haggai Nuchi <h.nuchi@gmail.com>
Halalaluyafail3 <55773281+Halalaluyafail3@users.noreply.github.com>
Hamdoud Hakem <90524568+hamdoudhakem@users.noreply.github.com>
HanishKVC <hanishkvc@gmail.com>
Haohui Mai <ricetons@gmail.com>
Haoxiang Fei <tonyfettes@tonyfettes.com>
Harald Fernengel <harald.fernengel@here.com>
Hatsune Miku <129688334+at8u@users.noreply.github.com>
HatsuneMikuUwU33 <173229399+HatsuneMikuUwU33@users.noreply.github.com>
Henk Poley <HenkPoley@gmail.com>
Henri Vasserman <henv@hot.ee>
Henrik Forstén <henrik.forsten@gmail.com>
Herman Semenov <GermanAizek@yandex.ru>
Hesen Peng <hesen.peng@gmail.com>
Hoang Nguyen <hugo53@users.noreply.github.com>
Hong Bo PENG <penghb@cn.ibm.com>
Hongyu Ouyang <96765450+casavaca@users.noreply.github.com>
Howard Su <howard0su@gmail.com>
Hua Jiang <allenhjiang@outlook.com>
Huawei Lin <huaweilin.cs@gmail.com>
Hugo Roussel <hugo.rous@gmail.com>
Ian Bull <irbull@eclipsesource.com>
Ian Bull <irbull@gmail.com>
Ian Scrivener <github@zilogy.asia>
Ido S <ido.pluto@gmail.com>
IgnacioFDM <ignaciofdm@gmail.com>
Igor Okulist <okigan@gmail.com>
Ikko Eltociear Ashimine <eltociear@gmail.com>
Ilya Kurdyukov <59548320+ilyakurdyukov@users.noreply.github.com>
Ionoclast Laboratories <brigham@ionoclast.com>
Isaac McFadyen <isaac@imcf.me>
IsaacDynamo <61521674+IsaacDynamo@users.noreply.github.com>
Ivan Komarov <Ivan.Komarov@dfyz.info>
Ivan Stepanov <ivanstepanovftw@gmail.com>
JH23X <165871467+JH23X@users.noreply.github.com>
Jack Mousseau <jmousseau@users.noreply.github.com>
JackJollimore <130917767+JackJollimore@users.noreply.github.com>
Jaemin Son <woalsdnd@gmail.com>
Jag Chadha <jagtesh@gmail.com>
Jakub N <jakubniemczyk97@gmail.com>
James A Capozzoli <157492257+jac-jim@users.noreply.github.com>
James Reynolds <magnusviri@users.noreply.github.com>
Jan Boon <jan.boon@kaetemi.be>
Jan Boon <kaetemi@gmail.com>
Jan Ploski <jpl@plosquare.com>
Jannis Schönleber <joennlae@gmail.com>
Jared Van Bortel <cebtenzzre@gmail.com>
Jared Van Bortel <jared@nomic.ai>
Jason McCartney <jmac@theroot.org>
Jean-Christophe Hoelt <hoelt@fovea.cc>
Jean-Michaël Celerier <jeanmichael.celerier+github@gmail.com>
Jed Fox <git@jedfox.com>
Jeffrey Quesnelle <emozilla@nousresearch.com>
Jesse Jojo Johnson <williamsaintgeorge@gmail.com>
Jeximo <jeximo@gmail.com>
Jhen-Jie Hong <iainst0409@gmail.com>
Jiahao Li <liplus17@163.com>
Jian Liao <jianliao@users.noreply.github.com>
JidongZhang-THU <1119708529@qq.com>
Jinwoo Jeong <33892306+williamjeong2@users.noreply.github.com>
Jiří Podivín <66251151+jpodivin@users.noreply.github.com>
Jiří Sejkora <Sejseloid@gmail.com>
Joan Fontanals <jfontanalsmartinez@gmail.com>
Joan Fontanals <joan.fontanals.martinez@jina.ai>
Johan <JohanAR@users.noreply.github.com>
Johannes Gäßler <johannesg@5d6.de>
Johannes Rudolph <johannes.rudolph@gmail.com>
John <78893154+cmp-nct@users.noreply.github.com>
John Balis <phobossystems@gmail.com>
John Smith <67539080+kingsidelee@users.noreply.github.com>
JohnnyB <jboero@users.noreply.github.com>
Jonas Wunderlich <32615971+jonas-w@users.noreply.github.com>
Jorge A <161275481+jorgealias@users.noreply.github.com>
Jose Maldonado <63384398+yukiteruamano@users.noreply.github.com>
Joseph Stahl <1269177+josephst@users.noreply.github.com>
Josh Ramer <josh.ramer@icloud.com>
Joyce <joycebrum@google.com>
Juan Calderon-Perez <835733+gaby@users.noreply.github.com>
Judd <foldl@users.noreply.github.com>
Julius Arkenberg <arki05@users.noreply.github.com>
Jun Jie <71215065+junnjiee16@users.noreply.github.com>
Junyang Lin <justinlin930319@hotmail.com>
Juraj Bednar <juraj@bednar.io>
Justin Parker <jparkerweb@gmail.com>
Justin Suess <justin.suess@westpoint.edu>
Justina Cho <justcho5@gmail.com>
Justine Tunney <jtunney@gmail.com>
Justine Tunney <jtunney@mozilla.com>
Juuso Alasuutari <juuso.alasuutari@gmail.com>
KASR <karim.asrih@gmail.com>
Kamil Tomšík <info@tomsik.cz>
Karsten Weiss <knweiss@gmail.com>
Karthick <j.karthic2004@gmail.com>
Karthik Kumar Viswanathan <195178+guilt@users.noreply.github.com>
Karthik Sethuraman <k.seth1993@gmail.com>
Kasumi <90275229+kasumi-1@users.noreply.github.com>
Kawrakow <48489457+ikawrakow@users.noreply.github.com>
Keiichi Tabata <keiichi.tabata@outlook.com>
Kenvix ⭐ <kenvixzure@live.com>
Kerfuffle <44031344+KerfuffleV2@users.noreply.github.com>
Kevin Gibbons <bakkot@gmail.com>
Kevin Ji <1146876+kevinji@users.noreply.github.com>
Kevin Kwok <antimatter15@gmail.com>
Kevin Lo <kevlo@kevlo.org>
Kolen Cheung <ickc@users.noreply.github.com>
Konstantin Herud <konstantin.herud@denkbares.com>
Konstantin Zhuravlyov <konstantin.zhuravlyov@amd.com>
Kunshang Ji <kunshang.ji@intel.com>
Kyle Liang <liangmanlai@gmail.com>
Kyle Mistele <kyle@mistele.com>
Kylin <56434533+KyL0N@users.noreply.github.com>
Lars Grammel <lars.grammel@gmail.com>
Laura <Tijntje_7@msn.com>
Lee <44310445+lx200916@users.noreply.github.com>
Lee Drake <b.lee.drake@gmail.com>
Leng Yue <lengyue@lengyue.me>
Leon Knauer <git@leonknauer.com>
LeonEricsson <70749762+LeonEricsson@users.noreply.github.com>
Leonardo Neumann <leonardo@neumann.dev.br>
Li Tan <tanliboy@gmail.com>
Linwei Wang <wanix1988@gmail.com>
LoganDark <github@logandark.mozmail.com>
LostRuins <39025047+LostRuins@users.noreply.github.com>
Luciano <lucianostrika44@gmail.com>
Luo Tian <lt@basecity.com>
Lyle Dean <dean@lyle.dev>
M. Yusuf Sarıgöz <yusufsarigoz@gmail.com>
Maarten ter Huurne <maarten@treewalker.org>
Mack Straight <eiz@users.noreply.github.com>
Maël Kerbiriou <m431.kerbiriou@gmail.com>
MaggotHATE <clay1326@gmail.com>
Manuel <44313466+makuche@users.noreply.github.com>
Marc Köhlbrugge <subscriptions@marckohlbrugge.com>
Marco Matthies <71844+marcom@users.noreply.github.com>
Marcus Dunn <51931484+MarcusDunn@users.noreply.github.com>
Marian Cepok <marian.cepok@gmail.com>
Mark Fairbairn <thebaron88@gmail.com>
Marko Tasic <mtasic85@gmail.com>
Markus Tavenrath <mtavenrath@users.noreply.github.com>
Martin Delille <martin@delille.org>
Martin Krasser <krasserm@googlemail.com>
Martin Schwaighofer <mschwaig@users.noreply.github.com>
Marvin Gießing <marvin.giessing@gmail.com>
Masaya, Kato <62578291+msy-kato@users.noreply.github.com>
MasterYi1024 <39848311+MasterYi1024@users.noreply.github.com>
Mateusz Charytoniuk <mateusz.charytoniuk@protonmail.com>
Matheus C. França <matheus-catarino@hotmail.com>
Matheus Gabriel Alves Silva <matheusgasource@gmail.com>
Mathieu Nayrolles <MathieuNls@users.noreply.github.com>
Mathijs de Bruin <mathijs@mathijsfietst.nl>
Matt Clayton <156335168+mattjcly@users.noreply.github.com>
Matt Pulver <matt.pulver@heavy.ai>
Matteo Boschini <12133566+mbosc@users.noreply.github.com>
Mattheus Chediak <shammcity00@gmail.com>
Matthew Tejo <matthew.tejo@gmail.com>
Matvey Soloviev <blackhole89@gmail.com>
Max Krasnyansky <max.krasnyansky@gmail.com>
Max Krasnyansky <quic_maxk@quicinc.com>
Maxime <672982+maximegmd@users.noreply.github.com>
Maximilian Winter <maximilian.winter.91@gmail.com>
Meng Zhang <meng@tabbyml.com>
Meng, Hengyu <hengyu.meng@intel.com>
Merrick Christensen <merrick.christensen@gmail.com>
Michael Coppola <m18coppola@gmail.com>
Michael Hueschen <m@mhueschen.dev>
Michael Kesper <mkesper@schokokeks.org>
Michael Klimenko <mklimenko29@gmail.com>
Michael Podvitskiy <podvitskiymichael@gmail.com>
Michael Potter <NanoTekGuy@Gmail.com>
Michael de Gans <michael.john.degans@gmail.com>
Michaël de Vries <vriesdemichael@gmail.com>
Mihai <mihai.chirculescu@yahoo.com>
Mike <ytianhui2004@gmail.com>
Mikko Juola <mikjuo@gmail.com>
Minsoo Cheong <54794500+mscheong01@users.noreply.github.com>
Mirko185 <mirkosig@gmail.com>
Mirror Azure <54669636+MirrorAzure@users.noreply.github.com>
Miwa / Ensan <63481257+ensan-hcl@users.noreply.github.com>
Mohammadreza Hendiani <hendiani.mohammadreza@gmail.com>
Mohammadreza Hendiani <mohammad.r.hendiani@gmail.com>
Murilo Santana <mvrilo@gmail.com>
Musab Gultekin <musabgultekin@users.noreply.github.com>
Nam D. Tran <42194884+namtranase@users.noreply.github.com>
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NawafAlansari <72708095+NawafAlansari@users.noreply.github.com>
Nebula <infinitewormhole@gmail.com>
Neo Zhang <14088817+arthw@users.noreply.github.com>
Neo Zhang <zhang.jianyu@outlook.com>
Neo Zhang Jianyu <jianyu.zhang@intel.com>
Neuman Vong <neuman.vong@gmail.com>
Nexesenex <124105151+Nexesenex@users.noreply.github.com>
Niall Coates <1349685+Niall-@users.noreply.github.com>
Nicolai Weitkemper <kontakt@nicolaiweitkemper.de>
Nicolás Pérez <nicolas_perez@brown.edu>
Nigel Bosch <pnigelb@gmail.com>
Niklas Korz <niklas@niklaskorz.de>
Nikolas <127742645+nneubacher@users.noreply.github.com>
Nindaleth <Nindaleth@users.noreply.github.com>
Oleksandr Nikitin <oleksandr@tvori.info>
Oleksii Maryshchenko <oleksii.maryshchenko@gmail.com>
Olivier Chafik <ochafik@users.noreply.github.com>
Ondřej Čertík <ondrej@certik.us>
Ouadie EL FAROUKI <ouadie.elfarouki@codeplay.com>
Patrice Ferlet <metal3d@gmail.com>
Paul Tsochantaris <ptsochantaris@icloud.com>
Pavol Rusnak <pavol@rusnak.io>
Pedro Cuenca <pedro@huggingface.co>
Peter Sugihara <peter@campsh.com>
Phil H <5756783+phiharri@users.noreply.github.com>
Philip Taron <philip.taron@gmail.com>
Phillip Kravtsov <phillip@kravtsov.net>
Pierre Alexandre SCHEMBRI <pa.schembri@gmail.com>
Pierrick Hymbert <pierrick.hymbert@gmail.com>
Przemysław Pawełczyk <przemoc@gmail.com>
Qin Yue Chen <71813199+chenqiny@users.noreply.github.com>
Qingyou Meng <meng.qingyou@gmail.com>
Qu Zongfu <43257352+yancaoweidaode@users.noreply.github.com>
RJ Adriaansen <adriaansen@eshcc.eur.nl>
Radoslav Gerganov <rgerganov@gmail.com>
Radosław Gryta <radek.gryta@gmail.com>
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Ralph Soika <ralph.soika@imixs.com>
Rand Xie <randxiexyy29@gmail.com>
Randall Fitzgerald <randall@dasaku.net>
Reinforce-II <fate@eastal.com>
Ren Xuancheng <jklj077@users.noreply.github.com>
Rene Leonhardt <65483435+reneleonhardt@users.noreply.github.com>
RhinoDevel <RhinoDevel@users.noreply.github.com>
Riceball LEE <snowyu.lee@gmail.com>
Richard Kiss <him@richardkiss.com>
Richard Roberson <richardr1126@gmail.com>
Rick G <26732651+TheFlipbook@users.noreply.github.com>
Rickard Edén <rickardeden@gmail.com>
Rickard Hallerbäck <rickard.hallerback@gmail.com>
Rickey Bowers Jr <bitRAKE@gmail.com>
Riley Stewart <ristew@users.noreply.github.com>
Rinne <AsakusaRinne@gmail.com>
Rinne <liu_yaohui1998@126.com>
Robert Brisita <986796+rbrisita@users.noreply.github.com>
Robert Sung-wook Shin <edp1096@users.noreply.github.com>
Robey Holderith <robey@flaminglunchbox.net>
Robyn <robyngraf@users.noreply.github.com>
Roger Meier <r.meier@siemens.com>
Roland <14355895+rbur0425@users.noreply.github.com>
Romain D <90720+Artefact2@users.noreply.github.com>
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Ronsor <ronsor@ronsor.pw>
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Rune <43761327+Rune-AI@users.noreply.github.com>
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Sang-Kil Park <sang.park@42dot.ai>
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Sebastián A <sebastian.aedo29@gmail.com>
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Senemu <10880819+Senemu@users.noreply.github.com>
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Someone <sergei.kozlukov@aalto.fi>
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Taikono-Himazin <kazu@po.harenet.ne.jp>
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Ting Lou <ting.lou@gmail.com>
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Tom C <tom.corelis@gmail.com>
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Tomas <tom.tomas.36478119@gmail.com>
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Tungsten842 <886724vf@anonaddy.me>
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UEXTM.com <84163508+uextm@users.noreply.github.com>
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Wu Jian Ping <wujp@greatld.com>
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Yui <dev@sleepyyui.com>
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ddh0 <dylanhalladay02@icloud.com>
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eastriver <lee@eastriver.dev>
ebraminio <ebraminio@gmail.com>
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Нияз Гарифзянов <112617865+garrnizon@users.noreply.github.com>

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{
"version": 4,
"configurePresets": [
{
"name": "base",
"hidden": true,
"generator": "Ninja",
"binaryDir": "${sourceDir}/build-${presetName}",
"cacheVariables": {
"CMAKE_EXPORT_COMPILE_COMMANDS": "ON",
"CMAKE_INSTALL_RPATH": "$ORIGIN;$ORIGIN/.."
}
},
{
"name": "sycl-base",
"hidden": true,
"generator": "Ninja",
"binaryDir": "${sourceDir}/build-${presetName}",
"cacheVariables": {
"CMAKE_EXPORT_COMPILE_COMMANDS": "ON",
"CMAKE_CXX_COMPILER": "icx",
"CMAKE_C_COMPILER": "cl",
"GGML_SYCL": "ON",
"CMAKE_INSTALL_RPATH": "$ORIGIN;$ORIGIN/.."
}
},
{ "name": "debug", "hidden": true, "cacheVariables": { "CMAKE_BUILD_TYPE": "Debug" } },
{ "name": "release", "hidden": true, "cacheVariables": { "CMAKE_BUILD_TYPE": "Release" } },
{ "name": "reldbg", "hidden": true, "cacheVariables": { "CMAKE_BUILD_TYPE": "RelWithDebInfo" } },
{ "name": "static", "hidden": true, "cacheVariables": { "GGML_STATIC": "ON" } },
{ "name": "sycl_f16", "hidden": true, "cacheVariables": { "GGML_SYCL_F16": "ON" } },
{
"name": "arm64-windows-msvc", "hidden": true,
"architecture": { "value": "arm64", "strategy": "external" },
"toolset": { "value": "host=x64", "strategy": "external" },
"cacheVariables": {
"CMAKE_TOOLCHAIN_FILE": "${sourceDir}/cmake/arm64-windows-msvc.cmake"
}
},
{
"name": "arm64-windows-llvm", "hidden": true,
"architecture": { "value": "arm64", "strategy": "external" },
"toolset": { "value": "host=x64", "strategy": "external" },
"cacheVariables": {
"CMAKE_TOOLCHAIN_FILE": "${sourceDir}/cmake/arm64-windows-llvm.cmake"
}
},
{ "name": "arm64-windows-llvm-debug" , "inherits": [ "base", "arm64-windows-llvm", "debug" ] },
{ "name": "arm64-windows-llvm-release", "inherits": [ "base", "arm64-windows-llvm", "reldbg" ] },
{ "name": "arm64-windows-llvm+static-release", "inherits": [ "base", "arm64-windows-llvm", "reldbg", "static" ] },
{ "name": "arm64-windows-msvc-debug" , "inherits": [ "base", "arm64-windows-msvc", "debug" ] },
{ "name": "arm64-windows-msvc-release", "inherits": [ "base", "arm64-windows-msvc", "reldbg" ] },
{ "name": "arm64-windows-msvc+static-release", "inherits": [ "base", "arm64-windows-msvc", "reldbg", "static" ] },
{ "name": "x64-windows-msvc-debug" , "inherits": [ "base", "debug" ] },
{ "name": "x64-windows-msvc-release", "inherits": [ "base", "reldbg" ] },
{ "name": "x64-windows-msvc+static-release", "inherits": [ "base", "reldbg", "static" ] },
{ "name": "x64-windows-sycl-debug" , "inherits": [ "sycl-base", "debug" ] },
{ "name": "x64-windows-sycl-debug-f16", "inherits": [ "sycl-base", "debug", "sycl_f16" ] },
{ "name": "x64-windows-sycl-release", "inherits": [ "sycl-base", "release" ] },
{ "name": "x64-windows-sycl-release-f16", "inherits": [ "sycl-base", "release", "sycl_f16" ] }
]
}

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@@ -1,33 +0,0 @@
# Pull requests (for contributors)
- Test your changes:
- Using the commands in the [`tests`](tests) folder. For instance, running the `./tests/test-backend-ops` command tests different backend implementations of the `ggml` library
- Execute [the full CI locally on your machine](ci/README.md) before publishing
- Optionally rate the complexity of your PR (i.e. `Review Complexity : Low`, `Review Complexity : Medium`, `Review Complexity : High`). This makes it easier for maintainers to triage the PRs
- Consider allowing write access to your branch for faster reviews, as reviewers can push commits directly
- If your PR becomes stale, don't hesitate to ping the maintainers in the comments
# Pull requests (for collaborators)
- Squash-merge PRs
- Use the following format for the squashed commit title: `<module> : <commit title> (#<issue_number>)`. For example: `utils : fix typo in utils.py (#1234)`
- Optionally pick a `<module>` from here: https://github.com/ggerganov/llama.cpp/wiki/Modules
# Coding guidelines
- Avoid adding third-party dependencies, extra files, extra headers, etc.
- Always consider cross-compatibility with other operating systems and architectures
- Avoid fancy-looking modern STL constructs, use basic `for` loops, avoid templates, keep it simple
- There are no strict rules for the code style, but try to follow the patterns in the code (indentation, spaces, etc.). Vertical alignment makes things more readable and easier to batch edit
- Clean-up any trailing whitespaces, use 4 spaces for indentation, brackets on the same line, `void * ptr`, `int & a`
- Naming usually optimizes for common prefix (see https://github.com/ggerganov/ggml/pull/302#discussion_r1243240963)
- Tensors store data in row-major order. We refer to dimension 0 as columns, 1 as rows, 2 as matrices
- Matrix multiplication is unconventional: [`C = ggml_mul_mat(ctx, A, B)`](https://github.com/ggerganov/llama.cpp/blob/880e352277fc017df4d5794f0c21c44e1eae2b84/ggml.h#L1058-L1064) means $C^T = A B^T \Leftrightarrow C = B A^T.$
![matmul](media/matmul.png)
# Resources
The Github issues, PRs and discussions contain a lot of information that can be useful to get familiar with the codebase. For convenience, some of the more important information is referenced from Github projects:
https://github.com/ggerganov/llama.cpp/projects

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@@ -1,6 +1,6 @@
MIT License
Copyright (c) 2023-2024 The ggml authors
Copyright (c) 2023 Georgi Gerganov
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal

1473
Makefile

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@@ -2,48 +2,6 @@
import PackageDescription
var sources = [
"src/llama.cpp",
"src/llama-vocab.cpp",
"src/llama-grammar.cpp",
"src/llama-sampling.cpp",
"src/unicode.cpp",
"src/unicode-data.cpp",
"ggml/src/ggml.c",
"ggml/src/ggml-alloc.c",
"ggml/src/ggml-backend.cpp",
"ggml/src/ggml-quants.c",
"ggml/src/ggml-aarch64.c",
]
var resources: [Resource] = []
var linkerSettings: [LinkerSetting] = []
var cSettings: [CSetting] = [
.unsafeFlags(["-Wno-shorten-64-to-32", "-O3", "-DNDEBUG"]),
.unsafeFlags(["-fno-objc-arc"]),
// NOTE: NEW_LAPACK will required iOS version 16.4+
// We should consider add this in the future when we drop support for iOS 14
// (ref: ref: https://developer.apple.com/documentation/accelerate/1513264-cblas_sgemm?language=objc)
// .define("ACCELERATE_NEW_LAPACK"),
// .define("ACCELERATE_LAPACK_ILP64")
]
#if canImport(Darwin)
sources.append("ggml/src/ggml-metal.m")
resources.append(.process("ggml/src/ggml-metal.metal"))
linkerSettings.append(.linkedFramework("Accelerate"))
cSettings.append(
contentsOf: [
.define("GGML_USE_ACCELERATE"),
.define("GGML_USE_METAL")
]
)
#endif
#if os(Linux)
cSettings.append(.define("_GNU_SOURCE"))
#endif
let package = Package(
name: "llama",
platforms: [
@@ -66,13 +24,38 @@ let package = Package(
"models",
"tests",
"CMakeLists.txt",
"ggml-cuda.cu",
"ggml-cuda.h",
"Makefile"
],
sources: sources,
resources: resources,
sources: [
"ggml.c",
"llama.cpp",
"unicode.cpp",
"unicode-data.cpp",
"ggml-alloc.c",
"ggml-backend.c",
"ggml-quants.c",
"ggml-metal.m",
],
resources: [
.process("ggml-metal.metal")
],
publicHeadersPath: "spm-headers",
cSettings: cSettings,
linkerSettings: linkerSettings
cSettings: [
.unsafeFlags(["-Wno-shorten-64-to-32", "-O3", "-DNDEBUG"]),
.define("GGML_USE_ACCELERATE"),
.unsafeFlags(["-fno-objc-arc"]),
.define("GGML_USE_METAL"),
// NOTE: NEW_LAPACK will required iOS version 16.4+
// We should consider add this in the future when we drop support for iOS 14
// (ref: ref: https://developer.apple.com/documentation/accelerate/1513264-cblas_sgemm?language=objc)
// .define("ACCELERATE_NEW_LAPACK"),
// .define("ACCELERATE_LAPACK_ILP64")
],
linkerSettings: [
.linkedFramework("Accelerate")
]
)
],
cxxLanguageStandard: .cxx11

599
README-sycl.md Normal file
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@@ -0,0 +1,599 @@
# llama.cpp for SYCL
- [Background](#background)
- [News](#news)
- [OS](#os)
- [Intel GPU](#intel-gpu)
- [Docker](#docker)
- [Linux](#linux)
- [Windows](#windows)
- [Environment Variable](#environment-variable)
- [Known Issue](#known-issue)
- [Q&A](#q&a)
- [Todo](#todo)
## Background
SYCL is a higher-level programming model to improve programming productivity on various hardware accelerators—such as CPUs, GPUs, and FPGAs. It is a single-source embedded domain-specific language based on pure C++17.
oneAPI is a specification that is open and standards-based, supporting multiple architecture types including but not limited to GPU, CPU, and FPGA. The spec has both direct programming and API-based programming paradigms.
Intel uses the SYCL as direct programming language to support CPU, GPUs and FPGAs.
To avoid to re-invent the wheel, this code refer other code paths in llama.cpp (like OpenBLAS, cuBLAS, CLBlast). We use a open-source tool [SYCLomatic](https://github.com/oneapi-src/SYCLomatic) (Commercial release [Intel® DPC++ Compatibility Tool](https://www.intel.com/content/www/us/en/developer/tools/oneapi/dpc-compatibility-tool.html)) migrate to SYCL.
The llama.cpp for SYCL is used to support Intel GPUs.
For Intel CPU, recommend to use llama.cpp for X86 (Intel MKL building).
## News
- 2024.3
- A blog is published: **Run LLM on all Intel GPUs Using llama.cpp**: [intel.com](https://www.intel.com/content/www/us/en/developer/articles/technical/run-llm-on-all-gpus-using-llama-cpp-artical.html) or [medium.com](https://medium.com/@jianyu_neo/run-llm-on-all-intel-gpus-using-llama-cpp-fd2e2dcbd9bd).
- New base line is ready: [tag b2437](https://github.com/ggerganov/llama.cpp/tree/b2437).
- Support multiple cards: **--split-mode**: [none|layer]; not support [row], it's on developing.
- Support to assign main GPU by **--main-gpu**, replace $GGML_SYCL_DEVICE.
- Support detecting all GPUs with level-zero and same top **Max compute units**.
- Support OPs
- hardsigmoid
- hardswish
- pool2d
- 2024.1
- Create SYCL backend for Intel GPU.
- Support Windows build
## OS
|OS|Status|Verified|
|-|-|-|
|Linux|Support|Ubuntu 22.04, Fedora Silverblue 39|
|Windows|Support|Windows 11|
## Intel GPU
### Verified
|Intel GPU| Status | Verified Model|
|-|-|-|
|Intel Data Center Max Series| Support| Max 1550|
|Intel Data Center Flex Series| Support| Flex 170|
|Intel Arc Series| Support| Arc 770, 730M|
|Intel built-in Arc GPU| Support| built-in Arc GPU in Meteor Lake|
|Intel iGPU| Support| iGPU in i5-1250P, i7-1260P, i7-1165G7|
Note: If the EUs (Execution Unit) in iGPU is less than 80, the inference speed will be too slow to use.
### Memory
The memory is a limitation to run LLM on GPUs.
When run llama.cpp, there is print log to show the applied memory on GPU. You could know how much memory to be used in your case. Like `llm_load_tensors: buffer size = 3577.56 MiB`.
For iGPU, please make sure the shared memory from host memory is enough. For llama-2-7b.Q4_0, recommend the host memory is 8GB+.
For dGPU, please make sure the device memory is enough. For llama-2-7b.Q4_0, recommend the device memory is 4GB+.
## Nvidia GPU
### Verified
|Intel GPU| Status | Verified Model|
|-|-|-|
|Ampere Series| Support| A100|
### oneMKL for CUDA
The current oneMKL release does not contain the oneMKL cuBlas backend.
As a result for Nvidia GPU's oneMKL must be built from source.
```
git clone https://github.com/oneapi-src/oneMKL
cd oneMKL
mkdir build
cd build
cmake -G Ninja .. -DCMAKE_CXX_COMPILER=icpx -DCMAKE_C_COMPILER=icx -DENABLE_MKLGPU_BACKEND=OFF -DENABLE_MKLCPU_BACKEND=OFF -DENABLE_CUBLAS_BACKEND=ON
ninja
// Add paths as necessary
```
## Docker
Note:
- Only docker on Linux is tested. Docker on WSL may not work.
- You may need to install Intel GPU driver on the host machine (See the [Linux](#linux) section to know how to do that)
### Build the image
You can choose between **F16** and **F32** build. F16 is faster for long-prompt inference.
```sh
# For F16:
#docker build -t llama-cpp-sycl --build-arg="LLAMA_SYCL_F16=ON" -f .devops/main-intel.Dockerfile .
# Or, for F32:
docker build -t llama-cpp-sycl -f .devops/main-intel.Dockerfile .
# Note: you can also use the ".devops/server-intel.Dockerfile", which compiles the "server" example
```
### Run
```sh
# Firstly, find all the DRI cards:
ls -la /dev/dri
# Then, pick the card that you want to use.
# For example with "/dev/dri/card1"
docker run -it --rm -v "$(pwd):/app:Z" --device /dev/dri/renderD128:/dev/dri/renderD128 --device /dev/dri/card1:/dev/dri/card1 llama-cpp-sycl -m "/app/models/YOUR_MODEL_FILE" -p "Building a website can be done in 10 simple steps:" -n 400 -e -ngl 33
```
## Linux
### Setup Environment
1. Install Intel GPU driver.
a. Please install Intel GPU driver by official guide: [Install GPU Drivers](https://dgpu-docs.intel.com/driver/installation.html).
Note: for iGPU, please install the client GPU driver.
b. Add user to group: video, render.
```sh
sudo usermod -aG render username
sudo usermod -aG video username
```
Note: re-login to enable it.
c. Check
```sh
sudo apt install clinfo
sudo clinfo -l
```
Output (example):
```
Platform #0: Intel(R) OpenCL Graphics
`-- Device #0: Intel(R) Arc(TM) A770 Graphics
Platform #0: Intel(R) OpenCL HD Graphics
`-- Device #0: Intel(R) Iris(R) Xe Graphics [0x9a49]
```
2. Install Intel® oneAPI Base toolkit.
a. Please follow the procedure in [Get the Intel® oneAPI Base Toolkit ](https://www.intel.com/content/www/us/en/developer/tools/oneapi/base-toolkit.html).
Recommend to install to default folder: **/opt/intel/oneapi**.
Following guide use the default folder as example. If you use other folder, please modify the following guide info with your folder.
b. Check
```sh
source /opt/intel/oneapi/setvars.sh
sycl-ls
```
There should be one or more level-zero devices. Please confirm that at least one GPU is present, like **[ext_oneapi_level_zero:gpu:0]**.
Output (example):
```
[opencl:acc:0] Intel(R) FPGA Emulation Platform for OpenCL(TM), Intel(R) FPGA Emulation Device OpenCL 1.2 [2023.16.10.0.17_160000]
[opencl:cpu:1] Intel(R) OpenCL, 13th Gen Intel(R) Core(TM) i7-13700K OpenCL 3.0 (Build 0) [2023.16.10.0.17_160000]
[opencl:gpu:2] Intel(R) OpenCL Graphics, Intel(R) Arc(TM) A770 Graphics OpenCL 3.0 NEO [23.30.26918.50]
[ext_oneapi_level_zero:gpu:0] Intel(R) Level-Zero, Intel(R) Arc(TM) A770 Graphics 1.3 [1.3.26918]
```
2. Build locally:
Note:
- You can choose between **F16** and **F32** build. F16 is faster for long-prompt inference.
- By default, it will build for all binary files. It will take more time. To reduce the time, we recommend to build for **example/main** only.
```sh
mkdir -p build
cd build
source /opt/intel/oneapi/setvars.sh
# For FP16:
#cmake .. -DLLAMA_SYCL=ON -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx -DLLAMA_SYCL_F16=ON
# Or, for FP32:
cmake .. -DLLAMA_SYCL=ON -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx
# For Nvidia GPUs
cmake .. -DLLAMA_SYCL=ON -DLLAMA_SYCL_TARGET=NVIDIA -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx
# Build example/main only
#cmake --build . --config Release --target main
# Or, build all binary
cmake --build . --config Release -v
cd ..
```
or
```sh
./examples/sycl/build.sh
```
### Run
1. Put model file to folder **models**
You could download [llama-2-7b.Q4_0.gguf](https://huggingface.co/TheBloke/Llama-2-7B-GGUF/blob/main/llama-2-7b.Q4_0.gguf) as example.
2. Enable oneAPI running environment
```
source /opt/intel/oneapi/setvars.sh
```
3. List device ID
Run without parameter:
```sh
./build/bin/ls-sycl-device
# or running the "main" executable and look at the output log:
./build/bin/main
```
Check the ID in startup log, like:
```
found 6 SYCL devices:
| | | |Compute |Max compute|Max work|Max sub| |
|ID| Device Type| Name|capability|units |group |group |Global mem size|
|--|------------------|---------------------------------------------|----------|-----------|--------|-------|---------------|
| 0|[level_zero:gpu:0]| Intel(R) Arc(TM) A770 Graphics| 1.3| 512| 1024| 32| 16225243136|
| 1|[level_zero:gpu:1]| Intel(R) UHD Graphics 770| 1.3| 32| 512| 32| 53651849216|
| 2| [opencl:gpu:0]| Intel(R) Arc(TM) A770 Graphics| 3.0| 512| 1024| 32| 16225243136|
| 3| [opencl:gpu:1]| Intel(R) UHD Graphics 770| 3.0| 32| 512| 32| 53651849216|
| 4| [opencl:cpu:0]| 13th Gen Intel(R) Core(TM) i7-13700K| 3.0| 24| 8192| 64| 67064815616|
| 5| [opencl:acc:0]| Intel(R) FPGA Emulation Device| 1.2| 24|67108864| 64| 67064815616|
```
|Attribute|Note|
|-|-|
|compute capability 1.3|Level-zero running time, recommended |
|compute capability 3.0|OpenCL running time, slower than level-zero in most cases|
4. Device selection and execution of llama.cpp
There are two device selection modes:
- Single device: Use one device assigned by user.
- Multiple devices: Automatically choose the devices with the same biggest Max compute units.
|Device selection|Parameter|
|-|-|
|Single device|--split-mode none --main-gpu DEVICE_ID |
|Multiple devices|--split-mode layer (default)|
Examples:
- Use device 0:
```sh
ZES_ENABLE_SYSMAN=1 ./build/bin/main -m models/llama-2-7b.Q4_0.gguf -p "Building a website can be done in 10 simple steps:" -n 400 -e -ngl 33 -sm none -mg 0
```
or run by script:
```sh
./examples/sycl/run_llama2.sh 0
```
- Use multiple devices:
```sh
ZES_ENABLE_SYSMAN=1 ./build/bin/main -m models/llama-2-7b.Q4_0.gguf -p "Building a website can be done in 10 simple steps:" -n 400 -e -ngl 33 -sm layer
```
or run by script:
```sh
./examples/sycl/run_llama2.sh
```
Note:
- By default, mmap is used to read model file. In some cases, it leads to the hang issue. Recommend to use parameter **--no-mmap** to disable mmap() to skip this issue.
5. Verify the device ID in output
Verify to see if the selected GPU is shown in the output, like:
```
detect 1 SYCL GPUs: [0] with top Max compute units:512
```
Or
```
use 1 SYCL GPUs: [0] with Max compute units:512
```
## Windows
### Setup Environment
1. Install Intel GPU driver.
Please install Intel GPU driver by official guide: [Install GPU Drivers](https://www.intel.com/content/www/us/en/products/docs/discrete-gpus/arc/software/drivers.html).
Note: **The driver is mandatory for compute function**.
2. Install Visual Studio.
Please install [Visual Studio](https://visualstudio.microsoft.com/) which impact oneAPI environment enabling in Windows.
3. Install Intel® oneAPI Base toolkit.
a. Please follow the procedure in [Get the Intel® oneAPI Base Toolkit ](https://www.intel.com/content/www/us/en/developer/tools/oneapi/base-toolkit.html).
Recommend to install to default folder: **C:\Program Files (x86)\Intel\oneAPI**.
Following guide uses the default folder as example. If you use other folder, please modify the following guide info with your folder.
b. Enable oneAPI running environment:
- In Search, input 'oneAPI'.
Search & open "Intel oneAPI command prompt for Intel 64 for Visual Studio 2022"
- In Run:
In CMD:
```
"C:\Program Files (x86)\Intel\oneAPI\setvars.bat" intel64
```
c. Check GPU
In oneAPI command line:
```
sycl-ls
```
There should be one or more level-zero devices. Please confirm that at least one GPU is present, like **[ext_oneapi_level_zero:gpu:0]**.
Output (example):
```
[opencl:acc:0] Intel(R) FPGA Emulation Platform for OpenCL(TM), Intel(R) FPGA Emulation Device OpenCL 1.2 [2023.16.10.0.17_160000]
[opencl:cpu:1] Intel(R) OpenCL, 11th Gen Intel(R) Core(TM) i7-1185G7 @ 3.00GHz OpenCL 3.0 (Build 0) [2023.16.10.0.17_160000]
[opencl:gpu:2] Intel(R) OpenCL Graphics, Intel(R) Iris(R) Xe Graphics OpenCL 3.0 NEO [31.0.101.5186]
[ext_oneapi_level_zero:gpu:0] Intel(R) Level-Zero, Intel(R) Iris(R) Xe Graphics 1.3 [1.3.28044]
```
4. Install cmake & make
a. Download & install cmake for Windows: https://cmake.org/download/
b. Download & install mingw-w64 make for Windows provided by w64devkit
- Download the 1.19.0 version of [w64devkit](https://github.com/skeeto/w64devkit/releases/download/v1.19.0/w64devkit-1.19.0.zip).
- Extract `w64devkit` on your pc.
- Add the **bin** folder path in the Windows system PATH environment, like `C:\xxx\w64devkit\bin\`.
### Build locally:
In oneAPI command line window:
```
mkdir -p build
cd build
@call "C:\Program Files (x86)\Intel\oneAPI\setvars.bat" intel64 --force
:: for FP16
:: faster for long-prompt inference
:: cmake -G "MinGW Makefiles" .. -DLLAMA_SYCL=ON -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icx -DCMAKE_BUILD_TYPE=Release -DLLAMA_SYCL_F16=ON
:: for FP32
cmake -G "MinGW Makefiles" .. -DLLAMA_SYCL=ON -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icx -DCMAKE_BUILD_TYPE=Release
:: build example/main only
:: make main
:: build all binary
make -j
cd ..
```
or
```
.\examples\sycl\win-build-sycl.bat
```
Note:
- By default, it will build for all binary files. It will take more time. To reduce the time, we recommend to build for **example/main** only.
### Run
1. Put model file to folder **models**
You could download [llama-2-7b.Q4_0.gguf](https://huggingface.co/TheBloke/Llama-2-7B-GGUF/blob/main/llama-2-7b.Q4_0.gguf) as example.
2. Enable oneAPI running environment
- In Search, input 'oneAPI'.
Search & open "Intel oneAPI command prompt for Intel 64 for Visual Studio 2022"
- In Run:
In CMD:
```
"C:\Program Files (x86)\Intel\oneAPI\setvars.bat" intel64
```
3. List device ID
Run without parameter:
```
build\bin\ls-sycl-device.exe
or
build\bin\main.exe
```
Check the ID in startup log, like:
```
found 6 SYCL devices:
| | | |Compute |Max compute|Max work|Max sub| |
|ID| Device Type| Name|capability|units |group |group |Global mem size|
|--|------------------|---------------------------------------------|----------|-----------|--------|-------|---------------|
| 0|[level_zero:gpu:0]| Intel(R) Arc(TM) A770 Graphics| 1.3| 512| 1024| 32| 16225243136|
| 1|[level_zero:gpu:1]| Intel(R) UHD Graphics 770| 1.3| 32| 512| 32| 53651849216|
| 2| [opencl:gpu:0]| Intel(R) Arc(TM) A770 Graphics| 3.0| 512| 1024| 32| 16225243136|
| 3| [opencl:gpu:1]| Intel(R) UHD Graphics 770| 3.0| 32| 512| 32| 53651849216|
| 4| [opencl:cpu:0]| 13th Gen Intel(R) Core(TM) i7-13700K| 3.0| 24| 8192| 64| 67064815616|
| 5| [opencl:acc:0]| Intel(R) FPGA Emulation Device| 1.2| 24|67108864| 64| 67064815616|
```
|Attribute|Note|
|-|-|
|compute capability 1.3|Level-zero running time, recommended |
|compute capability 3.0|OpenCL running time, slower than level-zero in most cases|
4. Device selection and execution of llama.cpp
There are two device selection modes:
- Single device: Use one device assigned by user.
- Multiple devices: Automatically choose the devices with the same biggest Max compute units.
|Device selection|Parameter|
|-|-|
|Single device|--split-mode none --main-gpu DEVICE_ID |
|Multiple devices|--split-mode layer (default)|
Examples:
- Use device 0:
```
build\bin\main.exe -m models\llama-2-7b.Q4_0.gguf -p "Building a website can be done in 10 simple steps:\nStep 1:" -n 400 -e -ngl 33 -s 0 -sm none -mg 0
```
- Use multiple devices:
```
build\bin\main.exe -m models\llama-2-7b.Q4_0.gguf -p "Building a website can be done in 10 simple steps:\nStep 1:" -n 400 -e -ngl 33 -s 0 -sm layer
```
or run by script:
```
.\examples\sycl\win-run-llama2.bat
```
Note:
- By default, mmap is used to read model file. In some cases, it leads to the hang issue. Recommend to use parameter **--no-mmap** to disable mmap() to skip this issue.
5. Verify the device ID in output
Verify to see if the selected GPU is shown in the output, like:
```
detect 1 SYCL GPUs: [0] with top Max compute units:512
```
Or
```
use 1 SYCL GPUs: [0] with Max compute units:512
```
## Environment Variable
#### Build
|Name|Value|Function|
|-|-|-|
|LLAMA_SYCL|ON (mandatory)|Enable build with SYCL code path. <br>For FP32/FP16, LLAMA_SYCL=ON is mandatory.|
|LLAMA_SYCL_F16|ON (optional)|Enable FP16 build with SYCL code path. Faster for long-prompt inference. <br>For FP32, not set it.|
|CMAKE_C_COMPILER|icx|Use icx compiler for SYCL code path|
|CMAKE_CXX_COMPILER|icpx (Linux), icx (Windows)|use icpx/icx for SYCL code path|
#### Running
|Name|Value|Function|
|-|-|-|
|GGML_SYCL_DEBUG|0 (default) or 1|Enable log function by macro: GGML_SYCL_DEBUG|
|ZES_ENABLE_SYSMAN| 0 (default) or 1|Support to get free memory of GPU by sycl::aspect::ext_intel_free_memory.<br>Recommended to use when --split-mode = layer|
## Known Issue
- Hang during startup
llama.cpp use mmap as default way to read model file and copy to GPU. In some system, memcpy will be abnormal and block.
Solution: add **--no-mmap** or **--mmap 0**.
- Split-mode: [row] is not supported
It's on developing.
## Q&A
Note: please add prefix **[SYCL]** in issue title, so that we will check it as soon as possible.
- Error: `error while loading shared libraries: libsycl.so.7: cannot open shared object file: No such file or directory`.
Miss to enable oneAPI running environment.
Install oneAPI base toolkit and enable it by: `source /opt/intel/oneapi/setvars.sh`.
- In Windows, no result, not error.
Miss to enable oneAPI running environment.
- Meet compile error.
Remove folder **build** and try again.
- I can **not** see **[ext_oneapi_level_zero:gpu:0]** afer install GPU driver in Linux.
Please run **sudo sycl-ls**.
If you see it in result, please add video/render group to your ID:
```
sudo usermod -aG render username
sudo usermod -aG video username
```
Then **relogin**.
If you do not see it, please check the installation GPU steps again.
## Todo
- Support row layer split for multiple card runs.

1005
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@@ -1,67 +0,0 @@
# Security Policy
- [**Using llama.cpp securely**](#using-llamacpp-securely)
- [Untrusted models](#untrusted-models)
- [Untrusted inputs](#untrusted-inputs)
- [Data privacy](#data-privacy)
- [Untrusted environments or networks](#untrusted-environments-or-networks)
- [Multi-Tenant environments](#multi-tenant-environments)
- [**Reporting a vulnerability**](#reporting-a-vulnerability)
## Using llama.cpp securely
### Untrusted models
Be careful when running untrusted models. This classification includes models created by unknown developers or utilizing data obtained from unknown sources.
*Always execute untrusted models within a secure, isolated environment such as a sandbox* (e.g., containers, virtual machines). This helps protect your system from potentially malicious code.
> [!NOTE]
> The trustworthiness of a model is not binary. You must always determine the proper level of caution depending on the specific model and how it matches your use case and risk tolerance.
### Untrusted inputs
Some models accept various input formats (text, images, audio, etc.). The libraries converting these inputs have varying security levels, so it's crucial to isolate the model and carefully pre-process inputs to mitigate script injection risks.
For maximum security when handling untrusted inputs, you may need to employ the following:
* Sandboxing: Isolate the environment where the inference happens.
* Pre-analysis: Check how the model performs by default when exposed to prompt injection (e.g. using [fuzzing for prompt injection](https://github.com/FonduAI/awesome-prompt-injection?tab=readme-ov-file#tools)). This will give you leads on how hard you will have to work on the next topics.
* Updates: Keep both LLaMA C++ and your libraries updated with the latest security patches.
* Input Sanitation: Before feeding data to the model, sanitize inputs rigorously. This involves techniques such as:
* Validation: Enforce strict rules on allowed characters and data types.
* Filtering: Remove potentially malicious scripts or code fragments.
* Encoding: Convert special characters into safe representations.
* Verification: Run tooling that identifies potential script injections (e.g. [models that detect prompt injection attempts](https://python.langchain.com/docs/guides/safety/hugging_face_prompt_injection)).
### Data privacy
To protect sensitive data from potential leaks or unauthorized access, it is crucial to sandbox the model execution. This means running the model in a secure, isolated environment, which helps mitigate many attack vectors.
### Untrusted environments or networks
If you can't run your models in a secure and isolated environment or if it must be exposed to an untrusted network, make sure to take the following security precautions:
* Confirm the hash of any downloaded artifact (e.g. pre-trained model weights) matches a known-good value
* Encrypt your data if sending it over the network.
### Multi-Tenant environments
If you intend to run multiple models in parallel with shared memory, it is your responsibility to ensure the models do not interact or access each other's data. The primary areas of concern are tenant isolation, resource allocation, model sharing and hardware attacks.
1. Tenant Isolation: Models should run separately with strong isolation methods to prevent unwanted data access. Separating networks is crucial for isolation, as it prevents unauthorized access to data or models and malicious users from sending graphs to execute under another tenant's identity.
2. Resource Allocation: A denial of service caused by one model can impact the overall system health. Implement safeguards like rate limits, access controls, and health monitoring.
3. Model Sharing: In a multitenant model sharing design, tenants and users must understand the security risks of running code provided by others. Since there are no reliable methods to detect malicious models, sandboxing the model execution is the recommended approach to mitigate the risk.
4. Hardware Attacks: GPUs or TPUs can also be attacked. [Researches](https://scholar.google.com/scholar?q=gpu+side+channel) has shown that side channel attacks on GPUs are possible, which can make data leak from other models or processes running on the same system at the same time.
## Reporting a vulnerability
Beware that none of the topics under [Using llama.cpp securely](#using-llamacpp-securely) are considered vulnerabilities of LLaMA C++.
<!-- normal version -->
However, If you have discovered a security vulnerability in this project, please report it privately. **Do not disclose it as a public issue.** This gives us time to work with you to fix the issue before public exposure, reducing the chance that the exploit will be used before a patch is released.
Please disclose it as a private [security advisory](https://github.com/ggerganov/llama.cpp/security/advisories/new).
A team of volunteers on a reasonable-effort basis maintains this project. As such, please give us at least 90 days to work on a fix before public exposure.

142
build.zig Normal file
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@@ -0,0 +1,142 @@
// Compatible with Zig Version 0.11.0
const std = @import("std");
const ArrayList = std.ArrayList;
const Compile = std.Build.Step.Compile;
const ConfigHeader = std.Build.Step.ConfigHeader;
const Mode = std.builtin.Mode;
const CrossTarget = std.zig.CrossTarget;
const Maker = struct {
builder: *std.build.Builder,
target: CrossTarget,
optimize: Mode,
enable_lto: bool,
include_dirs: ArrayList([]const u8),
cflags: ArrayList([]const u8),
cxxflags: ArrayList([]const u8),
objs: ArrayList(*Compile),
fn addInclude(m: *Maker, dir: []const u8) !void {
try m.include_dirs.append(dir);
}
fn addProjectInclude(m: *Maker, path: []const []const u8) !void {
try m.addInclude(try m.builder.build_root.join(m.builder.allocator, path));
}
fn addCFlag(m: *Maker, flag: []const u8) !void {
try m.cflags.append(flag);
}
fn addCxxFlag(m: *Maker, flag: []const u8) !void {
try m.cxxflags.append(flag);
}
fn addFlag(m: *Maker, flag: []const u8) !void {
try m.addCFlag(flag);
try m.addCxxFlag(flag);
}
fn init(builder: *std.build.Builder) !Maker {
const target = builder.standardTargetOptions(.{});
const zig_version = @import("builtin").zig_version_string;
const commit_hash = try std.ChildProcess.exec(
.{ .allocator = builder.allocator, .argv = &.{ "git", "rev-parse", "HEAD" } },
);
try std.fs.cwd().writeFile("common/build-info.cpp", builder.fmt(
\\int LLAMA_BUILD_NUMBER = {};
\\char const *LLAMA_COMMIT = "{s}";
\\char const *LLAMA_COMPILER = "Zig {s}";
\\char const *LLAMA_BUILD_TARGET = "{s}";
\\
, .{ 0, commit_hash.stdout[0 .. commit_hash.stdout.len - 1], zig_version, try target.allocDescription(builder.allocator) }));
var m = Maker{
.builder = builder,
.target = target,
.optimize = builder.standardOptimizeOption(.{}),
.enable_lto = false,
.include_dirs = ArrayList([]const u8).init(builder.allocator),
.cflags = ArrayList([]const u8).init(builder.allocator),
.cxxflags = ArrayList([]const u8).init(builder.allocator),
.objs = ArrayList(*Compile).init(builder.allocator),
};
try m.addCFlag("-std=c11");
try m.addCxxFlag("-std=c++11");
try m.addProjectInclude(&.{});
try m.addProjectInclude(&.{"common"});
return m;
}
fn obj(m: *const Maker, name: []const u8, src: []const u8) *Compile {
const o = m.builder.addObject(.{ .name = name, .target = m.target, .optimize = m.optimize });
if (o.target.getAbi() != .msvc)
o.defineCMacro("_GNU_SOURCE", null);
if (std.mem.endsWith(u8, src, ".c")) {
o.addCSourceFiles(&.{src}, m.cflags.items);
o.linkLibC();
} else {
o.addCSourceFiles(&.{src}, m.cxxflags.items);
if (o.target.getAbi() == .msvc) {
o.linkLibC(); // need winsdk + crt
} else {
// linkLibCpp already add (libc++ + libunwind + libc)
o.linkLibCpp();
}
}
for (m.include_dirs.items) |i| o.addIncludePath(.{ .path = i });
o.want_lto = m.enable_lto;
return o;
}
fn exe(m: *const Maker, name: []const u8, src: []const u8, deps: []const *Compile) *Compile {
const e = m.builder.addExecutable(.{ .name = name, .target = m.target, .optimize = m.optimize });
e.addCSourceFiles(&.{src}, m.cxxflags.items);
for (deps) |d| e.addObject(d);
for (m.objs.items) |o| e.addObject(o);
for (m.include_dirs.items) |i| e.addIncludePath(.{ .path = i });
// https://github.com/ziglang/zig/issues/15448
if (e.target.getAbi() == .msvc) {
e.linkLibC(); // need winsdk + crt
} else {
// linkLibCpp already add (libc++ + libunwind + libc)
e.linkLibCpp();
}
m.builder.installArtifact(e);
e.want_lto = m.enable_lto;
return e;
}
};
pub fn build(b: *std.build.Builder) !void {
var make = try Maker.init(b);
make.enable_lto = b.option(bool, "lto", "Enable LTO optimization, (default: false)") orelse false;
const ggml = make.obj("ggml", "ggml.c");
const ggml_alloc = make.obj("ggml-alloc", "ggml-alloc.c");
const ggml_backend = make.obj("ggml-backend", "ggml-backend.c");
const ggml_quants = make.obj("ggml-quants", "ggml-quants.c");
const unicode = make.obj("unicode", "unicode.cpp");
const unicode_data = make.obj("unicode-data", "unicode-data.cpp");
const llama = make.obj("llama", "llama.cpp");
const buildinfo = make.obj("common", "common/build-info.cpp");
const common = make.obj("common", "common/common.cpp");
const console = make.obj("console", "common/console.cpp");
const sampling = make.obj("sampling", "common/sampling.cpp");
const grammar_parser = make.obj("grammar-parser", "common/grammar-parser.cpp");
const json_schema_to_grammar = make.obj("json-schema-to-grammar", "common/json-schema-to-grammar.cpp");
const train = make.obj("train", "common/train.cpp");
const clip = make.obj("clip", "examples/llava/clip.cpp");
const llava = make.obj("llava", "examples/llava/llava.cpp");
_ = make.exe("main", "examples/main/main.cpp", &.{ ggml, ggml_alloc, ggml_backend, ggml_quants, llama, unicode, unicode_data, common, buildinfo, sampling, console, grammar_parser });
_ = make.exe("quantize", "examples/quantize/quantize.cpp", &.{ ggml, ggml_alloc, ggml_backend, ggml_quants, llama, unicode, unicode_data, common, buildinfo });
_ = make.exe("perplexity", "examples/perplexity/perplexity.cpp", &.{ ggml, ggml_alloc, ggml_backend, ggml_quants, llama, unicode, unicode_data, common, buildinfo });
_ = make.exe("embedding", "examples/embedding/embedding.cpp", &.{ ggml, ggml_alloc, ggml_backend, ggml_quants, llama, unicode, unicode_data, common, buildinfo });
_ = make.exe("finetune", "examples/finetune/finetune.cpp", &.{ ggml, ggml_alloc, ggml_backend, ggml_quants, llama, unicode, unicode_data, common, buildinfo, train });
_ = make.exe("train-text-from-scratch", "examples/train-text-from-scratch/train-text-from-scratch.cpp", &.{ ggml, ggml_alloc, ggml_backend, ggml_quants, llama, unicode, unicode_data, common, buildinfo, train });
const server = make.exe("server", "examples/server/server.cpp", &.{ ggml, ggml_alloc, ggml_backend, ggml_quants, llama, unicode, unicode_data, common, buildinfo, sampling, grammar_parser, json_schema_to_grammar, clip, llava });
if (server.target.isWindows()) {
server.linkSystemLibrary("ws2_32");
}
}

611
ci/run.sh
View File

@@ -1,4 +1,4 @@
#!/bin/bash
#/bin/bash
#
# sample usage:
#
@@ -13,9 +13,6 @@
# # with SYCL support
# GG_BUILD_SYCL=1 bash ./ci/run.sh ./tmp/results ./tmp/mnt
#
# # with VULKAN support
# GG_BUILD_VULKAN=1 bash ./ci/run.sh ./tmp/results ./tmp/mnt
#
if [ -z "$2" ]; then
echo "usage: $0 <output-dir> <mnt-dir>"
@@ -39,11 +36,11 @@ SRC=`pwd`
CMAKE_EXTRA="-DLLAMA_FATAL_WARNINGS=ON"
if [ ! -z ${GG_BUILD_METAL} ]; then
CMAKE_EXTRA="${CMAKE_EXTRA} -DGGML_METAL=ON"
CMAKE_EXTRA="${CMAKE_EXTRA} -DLLAMA_METAL_SHADER_DEBUG=ON"
fi
if [ ! -z ${GG_BUILD_CUDA} ]; then
CMAKE_EXTRA="${CMAKE_EXTRA} -DGGML_CUDA=ON -DCMAKE_CUDA_ARCHITECTURES=native"
CMAKE_EXTRA="${CMAKE_EXTRA} -DLLAMA_CUDA=1"
fi
if [ ! -z ${GG_BUILD_SYCL} ]; then
@@ -53,11 +50,7 @@ if [ ! -z ${GG_BUILD_SYCL} ]; then
exit 1
fi
CMAKE_EXTRA="${CMAKE_EXTRA} -DGGML_SYCL=1 DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx -DGGML_SYCL_F16=ON"
fi
if [ ! -z ${GG_BUILD_VULKAN} ]; then
CMAKE_EXTRA="${CMAKE_EXTRA} -DGGML_VULKAN=1"
CMAKE_EXTRA="${CMAKE_EXTRA} -DLLAMA_SYCL=1 DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx -DLLAMA_SYCL_F16=ON"
fi
## helpers
@@ -110,11 +103,8 @@ function gg_run_ctest_debug {
set -e
# Check cmake, make and ctest are installed
gg_check_build_requirements
(time cmake -DCMAKE_BUILD_TYPE=Debug ${CMAKE_EXTRA} .. ) 2>&1 | tee -a $OUT/${ci}-cmake.log
(time make -j$(nproc) ) 2>&1 | tee -a $OUT/${ci}-make.log
(time make -j ) 2>&1 | tee -a $OUT/${ci}-make.log
(time ctest --output-on-failure -L main -E test-opt ) 2>&1 | tee -a $OUT/${ci}-ctest.log
@@ -141,11 +131,8 @@ function gg_run_ctest_release {
set -e
# Check cmake, make and ctest are installed
gg_check_build_requirements
(time cmake -DCMAKE_BUILD_TYPE=Release ${CMAKE_EXTRA} .. ) 2>&1 | tee -a $OUT/${ci}-cmake.log
(time make -j$(nproc) ) 2>&1 | tee -a $OUT/${ci}-make.log
(time make -j ) 2>&1 | tee -a $OUT/${ci}-make.log
if [ -z ${GG_BUILD_LOW_PERF} ]; then
(time ctest --output-on-failure -L main ) 2>&1 | tee -a $OUT/${ci}-ctest.log
@@ -166,64 +153,13 @@ function gg_sum_ctest_release {
gg_printf '```\n'
}
# test_scripts_debug
function gg_run_test_scripts_debug {
cd ${SRC}
set -e
(cd ./examples/gguf-split && time bash tests.sh "$SRC/build-ci-debug/bin" "$MNT/models") 2>&1 | tee -a $OUT/${ci}-scripts.log
(cd ./examples/quantize && time bash tests.sh "$SRC/build-ci-debug/bin" "$MNT/models") 2>&1 | tee -a $OUT/${ci}-scripts.log
set +e
}
function gg_sum_test_scripts_debug {
gg_printf '### %s\n\n' "${ci}"
gg_printf 'Runs test scripts in debug mode\n'
gg_printf '- status: %s\n' "$(cat $OUT/${ci}.exit)"
gg_printf '```\n'
gg_printf '%s\n' "$(cat $OUT/${ci}-scripts.log)"
gg_printf '```\n'
gg_printf '\n'
}
# test_scripts_release
function gg_run_test_scripts_release {
cd ${SRC}
set -e
(cd ./examples/gguf-split && time bash tests.sh "$SRC/build-ci-release/bin" "$MNT/models") 2>&1 | tee -a $OUT/${ci}-scripts.log
(cd ./examples/quantize && time bash tests.sh "$SRC/build-ci-release/bin" "$MNT/models") 2>&1 | tee -a $OUT/${ci}-scripts.log
set +e
}
function gg_sum_test_scripts_release {
gg_printf '### %s\n\n' "${ci}"
gg_printf 'Runs test scripts in release mode\n'
gg_printf '- status: %s\n' "$(cat $OUT/${ci}.exit)"
gg_printf '```\n'
gg_printf '%s\n' "$(cat $OUT/${ci}-scripts.log)"
gg_printf '```\n'
gg_printf '\n'
}
function gg_get_model {
local gguf_0="$MNT/models/pythia/1.4B/ggml-model-f16.gguf"
local gguf_1="$MNT/models/pythia/2.8B/ggml-model-f16.gguf"
local gguf_2="$MNT/models/open-llama/7B-v2/ggml-model-f16.gguf"
if [[ -s $gguf_0 ]]; then
echo -n "$gguf_0"
elif [[ -s $gguf_1 ]]; then
echo -n "$gguf_1"
elif [[ -s $gguf_2 ]]; then
echo -n "$gguf_2"
local gguf_3b="$MNT/models/open-llama/3B-v2/ggml-model-f16.gguf"
local gguf_7b="$MNT/models/open-llama/7B-v2/ggml-model-f16.gguf"
if [[ -s $gguf_3b ]]; then
echo -n "$gguf_3b"
elif [[ -s $gguf_7b ]]; then
echo -n "$gguf_7b"
else
echo >&2 "No model found. Can't run gg_run_ctest_with_model."
exit 1
@@ -272,34 +208,33 @@ function gg_sum_ctest_with_model_release {
gg_printf '```\n'
}
# open_llama_7b_v2
# open_llama_3b_v2
function gg_run_open_llama_7b_v2 {
function gg_run_open_llama_3b_v2 {
cd ${SRC}
gg_wget models-mnt/open-llama/7B-v2/ https://huggingface.co/openlm-research/open_llama_7b_v2/raw/main/config.json
gg_wget models-mnt/open-llama/7B-v2/ https://huggingface.co/openlm-research/open_llama_7b_v2/resolve/main/tokenizer.model
gg_wget models-mnt/open-llama/7B-v2/ https://huggingface.co/openlm-research/open_llama_7b_v2/raw/main/tokenizer_config.json
gg_wget models-mnt/open-llama/7B-v2/ https://huggingface.co/openlm-research/open_llama_7b_v2/raw/main/special_tokens_map.json
gg_wget models-mnt/open-llama/7B-v2/ https://huggingface.co/openlm-research/open_llama_7b_v2/raw/main/pytorch_model.bin.index.json
gg_wget models-mnt/open-llama/7B-v2/ https://huggingface.co/openlm-research/open_llama_7b_v2/resolve/main/pytorch_model-00001-of-00002.bin
gg_wget models-mnt/open-llama/7B-v2/ https://huggingface.co/openlm-research/open_llama_7b_v2/resolve/main/pytorch_model-00002-of-00002.bin
gg_wget models-mnt/open-llama/7B-v2/ https://huggingface.co/openlm-research/open_llama_7b_v2/raw/main/generation_config.json
gg_wget models-mnt/open-llama/3B-v2/ https://huggingface.co/openlm-research/open_llama_3b_v2/raw/main/config.json
gg_wget models-mnt/open-llama/3B-v2/ https://huggingface.co/openlm-research/open_llama_3b_v2/resolve/main/tokenizer.model
gg_wget models-mnt/open-llama/3B-v2/ https://huggingface.co/openlm-research/open_llama_3b_v2/raw/main/tokenizer_config.json
gg_wget models-mnt/open-llama/3B-v2/ https://huggingface.co/openlm-research/open_llama_3b_v2/raw/main/special_tokens_map.json
gg_wget models-mnt/open-llama/3B-v2/ https://huggingface.co/openlm-research/open_llama_3b_v2/resolve/main/pytorch_model.bin
gg_wget models-mnt/open-llama/3B-v2/ https://huggingface.co/openlm-research/open_llama_3b_v2/raw/main/generation_config.json
gg_wget models-mnt/wikitext/ https://huggingface.co/datasets/ggml-org/ci/resolve/main/wikitext-2-raw-v1.zip
unzip -o models-mnt/wikitext/wikitext-2-raw-v1.zip -d models-mnt/wikitext/
head -n 60 models-mnt/wikitext/wikitext-2-raw/wiki.test.raw > models-mnt/wikitext/wikitext-2-raw/wiki.test-60.raw
path_models="../models-mnt/open-llama/7B-v2"
path_models="../models-mnt/open-llama/3B-v2"
path_wiki="../models-mnt/wikitext/wikitext-2-raw"
rm -rf build-ci-release && mkdir build-ci-release && cd build-ci-release
set -e
(time cmake -DCMAKE_BUILD_TYPE=Release ${CMAKE_EXTRA} .. ) 2>&1 | tee -a $OUT/${ci}-cmake.log
(time make -j$(nproc) ) 2>&1 | tee -a $OUT/${ci}-make.log
(time cmake -DCMAKE_BUILD_TYPE=Release ${CMAKE_EXTRA} -DLLAMA_QKK_64=1 .. ) 2>&1 | tee -a $OUT/${ci}-cmake.log
(time make -j ) 2>&1 | tee -a $OUT/${ci}-make.log
python3 ../examples/convert_legacy_llama.py ${path_models} --outfile ${path_models}/ggml-model-f16.gguf
python3 ../convert.py ${path_models}
model_f16="${path_models}/ggml-model-f16.gguf"
model_q8_0="${path_models}/ggml-model-q8_0.gguf"
@@ -313,49 +248,46 @@ function gg_run_open_llama_7b_v2 {
model_q5_k="${path_models}/ggml-model-q5_k.gguf"
model_q6_k="${path_models}/ggml-model-q6_k.gguf"
wiki_test="${path_wiki}/wiki.test.raw"
wiki_test_60="${path_wiki}/wiki.test-60.raw"
./bin/llama-quantize ${model_f16} ${model_q8_0} q8_0
./bin/llama-quantize ${model_f16} ${model_q4_0} q4_0
./bin/llama-quantize ${model_f16} ${model_q4_1} q4_1
./bin/llama-quantize ${model_f16} ${model_q5_0} q5_0
./bin/llama-quantize ${model_f16} ${model_q5_1} q5_1
./bin/llama-quantize ${model_f16} ${model_q2_k} q2_k
./bin/llama-quantize ${model_f16} ${model_q3_k} q3_k
./bin/llama-quantize ${model_f16} ${model_q4_k} q4_k
./bin/llama-quantize ${model_f16} ${model_q5_k} q5_k
./bin/llama-quantize ${model_f16} ${model_q6_k} q6_k
./bin/quantize ${model_f16} ${model_q8_0} q8_0
./bin/quantize ${model_f16} ${model_q4_0} q4_0
./bin/quantize ${model_f16} ${model_q4_1} q4_1
./bin/quantize ${model_f16} ${model_q5_0} q5_0
./bin/quantize ${model_f16} ${model_q5_1} q5_1
./bin/quantize ${model_f16} ${model_q2_k} q2_k
./bin/quantize ${model_f16} ${model_q3_k} q3_k
./bin/quantize ${model_f16} ${model_q4_k} q4_k
./bin/quantize ${model_f16} ${model_q5_k} q5_k
./bin/quantize ${model_f16} ${model_q6_k} q6_k
(time ./bin/llama-cli --model ${model_f16} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-f16.log
(time ./bin/llama-cli --model ${model_q8_0} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q8_0.log
(time ./bin/llama-cli --model ${model_q4_0} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q4_0.log
(time ./bin/llama-cli --model ${model_q4_1} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q4_1.log
(time ./bin/llama-cli --model ${model_q5_0} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q5_0.log
(time ./bin/llama-cli --model ${model_q5_1} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q5_1.log
(time ./bin/llama-cli --model ${model_q2_k} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q2_k.log
(time ./bin/llama-cli --model ${model_q3_k} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q3_k.log
(time ./bin/llama-cli --model ${model_q4_k} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q4_k.log
(time ./bin/llama-cli --model ${model_q5_k} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q5_k.log
(time ./bin/llama-cli --model ${model_q6_k} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q6_k.log
(time ./bin/main --model ${model_f16} -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-f16.log
(time ./bin/main --model ${model_q8_0} -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q8_0.log
(time ./bin/main --model ${model_q4_0} -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q4_0.log
(time ./bin/main --model ${model_q4_1} -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q4_1.log
(time ./bin/main --model ${model_q5_0} -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q5_0.log
(time ./bin/main --model ${model_q5_1} -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q5_1.log
(time ./bin/main --model ${model_q2_k} -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q2_k.log
(time ./bin/main --model ${model_q3_k} -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q3_k.log
(time ./bin/main --model ${model_q4_k} -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q4_k.log
(time ./bin/main --model ${model_q5_k} -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q5_k.log
(time ./bin/main --model ${model_q6_k} -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q6_k.log
(time ./bin/llama-perplexity --model ${model_f16} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-f16.log
(time ./bin/llama-perplexity --model ${model_q8_0} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q8_0.log
(time ./bin/llama-perplexity --model ${model_q4_0} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q4_0.log
(time ./bin/llama-perplexity --model ${model_q4_1} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q4_1.log
(time ./bin/llama-perplexity --model ${model_q5_0} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q5_0.log
(time ./bin/llama-perplexity --model ${model_q5_1} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q5_1.log
(time ./bin/llama-perplexity --model ${model_q2_k} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q2_k.log
(time ./bin/llama-perplexity --model ${model_q3_k} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q3_k.log
(time ./bin/llama-perplexity --model ${model_q4_k} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q4_k.log
(time ./bin/llama-perplexity --model ${model_q5_k} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q5_k.log
(time ./bin/llama-perplexity --model ${model_q6_k} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q6_k.log
(time ./bin/perplexity --model ${model_f16} -f ${wiki_test_60} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-tg-f16.log
(time ./bin/perplexity --model ${model_q8_0} -f ${wiki_test_60} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-tg-q8_0.log
(time ./bin/perplexity --model ${model_q4_0} -f ${wiki_test_60} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-tg-q4_0.log
(time ./bin/perplexity --model ${model_q4_1} -f ${wiki_test_60} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-tg-q4_1.log
(time ./bin/perplexity --model ${model_q5_0} -f ${wiki_test_60} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-tg-q5_0.log
(time ./bin/perplexity --model ${model_q5_1} -f ${wiki_test_60} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-tg-q5_1.log
(time ./bin/perplexity --model ${model_q2_k} -f ${wiki_test_60} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-tg-q2_k.log
(time ./bin/perplexity --model ${model_q3_k} -f ${wiki_test_60} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-tg-q3_k.log
(time ./bin/perplexity --model ${model_q4_k} -f ${wiki_test_60} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-tg-q4_k.log
(time ./bin/perplexity --model ${model_q5_k} -f ${wiki_test_60} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-tg-q5_k.log
(time ./bin/perplexity --model ${model_q6_k} -f ${wiki_test_60} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-tg-q6_k.log
(time ./bin/llama-imatrix --model ${model_f16} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-imatrix.log
(time ./bin/imatrix --model ${model_f16} -f ${wiki_test_60} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-imatrix.log
(time ./bin/llama-save-load-state -ngl 10 --model ${model_q4_0} ) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
(time ./bin/llama-save-load-state -fa -ngl 10 --model ${model_q4_0} ) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
(time ./bin/llama-save-load-state -ngl 99 --model ${model_q4_0} ) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
(time ./bin/llama-save-load-state -fa -ngl 99 --model ${model_q4_0} ) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
(time ./bin/save-load-state --model ${model_q4_0} ) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
function check_ppl {
qnt="$1"
@@ -384,148 +316,58 @@ function gg_run_open_llama_7b_v2 {
cat $OUT/${ci}-imatrix.log | grep "Final" >> $OUT/${ci}-imatrix-sum.log
set +e
}
function gg_sum_open_llama_7b_v2 {
gg_printf '### %s\n\n' "${ci}"
gg_printf 'OpenLLaMA 7B-v2:\n'
gg_printf '- status: %s\n' "$(cat $OUT/${ci}.exit)"
gg_printf '- perplexity:\n%s\n' "$(cat $OUT/${ci}-ppl.log)"
gg_printf '- imatrix:\n```\n%s\n```\n' "$(cat $OUT/${ci}-imatrix-sum.log)"
gg_printf '- f16: \n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-f16.log)"
gg_printf '- q8_0:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-q8_0.log)"
gg_printf '- q4_0:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-q4_0.log)"
gg_printf '- q4_1:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-q4_1.log)"
gg_printf '- q5_0:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-q5_0.log)"
gg_printf '- q5_1:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-q5_1.log)"
gg_printf '- q2_k:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-q2_k.log)"
gg_printf '- q3_k:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-q3_k.log)"
gg_printf '- q4_k:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-q4_k.log)"
gg_printf '- q5_k:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-q5_k.log)"
gg_printf '- q6_k:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-q6_k.log)"
gg_printf '- save-load-state: \n```\n%s\n```\n' "$(cat $OUT/${ci}-save-load-state.log)"
}
# pythia_1.4b
function gg_run_pythia_1_4b {
cd ${SRC}
gg_wget models-mnt/pythia/1.4B/ https://huggingface.co/EleutherAI/pythia-1.4b/raw/main/config.json
gg_wget models-mnt/pythia/1.4B/ https://huggingface.co/EleutherAI/pythia-1.4b/raw/main/tokenizer.json
gg_wget models-mnt/pythia/1.4B/ https://huggingface.co/EleutherAI/pythia-1.4b/raw/main/tokenizer_config.json
gg_wget models-mnt/pythia/1.4B/ https://huggingface.co/EleutherAI/pythia-1.4b/raw/main/special_tokens_map.json
gg_wget models-mnt/pythia/1.4B/ https://huggingface.co/EleutherAI/pythia-1.4b/resolve/main/pytorch_model.bin
gg_wget models-mnt/wikitext/ https://huggingface.co/datasets/ggml-org/ci/resolve/main/wikitext-2-raw-v1.zip
unzip -o models-mnt/wikitext/wikitext-2-raw-v1.zip -d models-mnt/wikitext/
head -n 60 models-mnt/wikitext/wikitext-2-raw/wiki.test.raw > models-mnt/wikitext/wikitext-2-raw/wiki.test-60.raw
path_models="../models-mnt/pythia/1.4B"
path_wiki="../models-mnt/wikitext/wikitext-2-raw"
rm -rf build-ci-release && mkdir build-ci-release && cd build-ci-release
set -e
(time cmake -DCMAKE_BUILD_TYPE=Release ${CMAKE_EXTRA} .. ) 2>&1 | tee -a $OUT/${ci}-cmake.log
(time make -j$(nproc) ) 2>&1 | tee -a $OUT/${ci}-make.log
python3 ../convert_hf_to_gguf.py ${path_models} --outfile ${path_models}/ggml-model-f16.gguf
model_f16="${path_models}/ggml-model-f16.gguf"
model_q8_0="${path_models}/ggml-model-q8_0.gguf"
model_q4_0="${path_models}/ggml-model-q4_0.gguf"
model_q4_1="${path_models}/ggml-model-q4_1.gguf"
model_q5_0="${path_models}/ggml-model-q5_0.gguf"
model_q5_1="${path_models}/ggml-model-q5_1.gguf"
model_q2_k="${path_models}/ggml-model-q2_k.gguf"
model_q3_k="${path_models}/ggml-model-q3_k.gguf"
model_q4_k="${path_models}/ggml-model-q4_k.gguf"
model_q5_k="${path_models}/ggml-model-q5_k.gguf"
model_q6_k="${path_models}/ggml-model-q6_k.gguf"
wiki_test_60="${path_wiki}/wiki.test-60.raw"
./bin/llama-quantize ${model_f16} ${model_q8_0} q8_0
./bin/llama-quantize ${model_f16} ${model_q4_0} q4_0
./bin/llama-quantize ${model_f16} ${model_q4_1} q4_1
./bin/llama-quantize ${model_f16} ${model_q5_0} q5_0
./bin/llama-quantize ${model_f16} ${model_q5_1} q5_1
./bin/llama-quantize ${model_f16} ${model_q2_k} q2_k
./bin/llama-quantize ${model_f16} ${model_q3_k} q3_k
./bin/llama-quantize ${model_f16} ${model_q4_k} q4_k
./bin/llama-quantize ${model_f16} ${model_q5_k} q5_k
./bin/llama-quantize ${model_f16} ${model_q6_k} q6_k
(time ./bin/llama-cli --model ${model_f16} -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-f16.log
(time ./bin/llama-cli --model ${model_q8_0} -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q8_0.log
(time ./bin/llama-cli --model ${model_q4_0} -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q4_0.log
(time ./bin/llama-cli --model ${model_q4_1} -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q4_1.log
(time ./bin/llama-cli --model ${model_q5_0} -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q5_0.log
(time ./bin/llama-cli --model ${model_q5_1} -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q5_1.log
(time ./bin/llama-cli --model ${model_q2_k} -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q2_k.log
(time ./bin/llama-cli --model ${model_q3_k} -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q3_k.log
(time ./bin/llama-cli --model ${model_q4_k} -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q4_k.log
(time ./bin/llama-cli --model ${model_q5_k} -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q5_k.log
(time ./bin/llama-cli --model ${model_q6_k} -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q6_k.log
(time ./bin/llama-perplexity --model ${model_f16} -f ${wiki_test_60} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-tg-f16.log
(time ./bin/llama-perplexity --model ${model_q8_0} -f ${wiki_test_60} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-tg-q8_0.log
(time ./bin/llama-perplexity --model ${model_q4_0} -f ${wiki_test_60} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-tg-q4_0.log
(time ./bin/llama-perplexity --model ${model_q4_1} -f ${wiki_test_60} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-tg-q4_1.log
(time ./bin/llama-perplexity --model ${model_q5_0} -f ${wiki_test_60} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-tg-q5_0.log
(time ./bin/llama-perplexity --model ${model_q5_1} -f ${wiki_test_60} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-tg-q5_1.log
(time ./bin/llama-perplexity --model ${model_q2_k} -f ${wiki_test_60} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-tg-q2_k.log
(time ./bin/llama-perplexity --model ${model_q3_k} -f ${wiki_test_60} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-tg-q3_k.log
(time ./bin/llama-perplexity --model ${model_q4_k} -f ${wiki_test_60} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-tg-q4_k.log
(time ./bin/llama-perplexity --model ${model_q5_k} -f ${wiki_test_60} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-tg-q5_k.log
(time ./bin/llama-perplexity --model ${model_q6_k} -f ${wiki_test_60} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-tg-q6_k.log
(time ./bin/llama-imatrix --model ${model_f16} -f ${wiki_test_60} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-imatrix.log
(time ./bin/llama-save-load-state --model ${model_q4_0} ) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
(time ./bin/llama-save-load-state -fa --model ${model_q4_0} ) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
function check_ppl {
# lora
function compare_ppl {
qnt="$1"
ppl=$(echo "$2" | grep -oE "[0-9]+\.[0-9]+" | tail -n 1)
ppl1=$(echo "$2" | grep -oE "[0-9]+\.[0-9]+" | tail -n 1)
ppl2=$(echo "$3" | grep -oE "[0-9]+\.[0-9]+" | tail -n 1)
if [ $(echo "$ppl > 20.0" | bc) -eq 1 ]; then
printf ' - %s @ %s (FAIL: ppl > 20.0)\n' "$qnt" "$ppl"
if [ $(echo "$ppl1 < $ppl2" | bc) -eq 1 ]; then
printf ' - %s @ %s (FAIL: %s > %s)\n' "$qnt" "$ppl" "$ppl1" "$ppl2"
return 20
fi
printf ' - %s @ %s OK\n' "$qnt" "$ppl"
printf ' - %s @ %s %s OK\n' "$qnt" "$ppl1" "$ppl2"
return 0
}
check_ppl "f16" "$(cat $OUT/${ci}-tg-f16.log | grep "^\[1\]")" | tee -a $OUT/${ci}-ppl.log
check_ppl "q8_0" "$(cat $OUT/${ci}-tg-q8_0.log | grep "^\[1\]")" | tee -a $OUT/${ci}-ppl.log
check_ppl "q4_0" "$(cat $OUT/${ci}-tg-q4_0.log | grep "^\[1\]")" | tee -a $OUT/${ci}-ppl.log
check_ppl "q4_1" "$(cat $OUT/${ci}-tg-q4_1.log | grep "^\[1\]")" | tee -a $OUT/${ci}-ppl.log
check_ppl "q5_0" "$(cat $OUT/${ci}-tg-q5_0.log | grep "^\[1\]")" | tee -a $OUT/${ci}-ppl.log
check_ppl "q5_1" "$(cat $OUT/${ci}-tg-q5_1.log | grep "^\[1\]")" | tee -a $OUT/${ci}-ppl.log
#check_ppl "q2_k" "$(cat $OUT/${ci}-tg-q2_k.log | grep "^\[1\]")" | tee -a $OUT/${ci}-ppl.log # note: ppl > 20.0 for this quant and model
check_ppl "q3_k" "$(cat $OUT/${ci}-tg-q3_k.log | grep "^\[1\]")" | tee -a $OUT/${ci}-ppl.log
check_ppl "q4_k" "$(cat $OUT/${ci}-tg-q4_k.log | grep "^\[1\]")" | tee -a $OUT/${ci}-ppl.log
check_ppl "q5_k" "$(cat $OUT/${ci}-tg-q5_k.log | grep "^\[1\]")" | tee -a $OUT/${ci}-ppl.log
check_ppl "q6_k" "$(cat $OUT/${ci}-tg-q6_k.log | grep "^\[1\]")" | tee -a $OUT/${ci}-ppl.log
path_lora="../models-mnt/open-llama/3B-v2/lora"
path_shakespeare="../models-mnt/shakespeare"
cat $OUT/${ci}-imatrix.log | grep "Final" >> $OUT/${ci}-imatrix-sum.log
shakespeare="${path_shakespeare}/shakespeare.txt"
lora_shakespeare="${path_lora}/ggml-adapter-model.bin"
gg_wget ${path_lora} https://huggingface.co/slaren/open_llama_3b_v2_shakespeare_lora/resolve/main/adapter_config.json
gg_wget ${path_lora} https://huggingface.co/slaren/open_llama_3b_v2_shakespeare_lora/resolve/main/adapter_model.bin
gg_wget ${path_shakespeare} https://huggingface.co/slaren/open_llama_3b_v2_shakespeare_lora/resolve/main/shakespeare.txt
python3 ../convert-lora-to-ggml.py ${path_lora}
# f16
(time ./bin/perplexity --model ${model_f16} -f ${shakespeare} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-ppl-shakespeare-f16.log
(time ./bin/perplexity --model ${model_f16} -f ${shakespeare} --lora ${lora_shakespeare} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-ppl-shakespeare-lora-f16.log
compare_ppl "f16 shakespeare" "$(cat $OUT/${ci}-ppl-shakespeare-f16.log | grep "^\[1\]")" "$(cat $OUT/${ci}-ppl-shakespeare-lora-f16.log | grep "^\[1\]")" | tee -a $OUT/${ci}-lora-ppl.log
# q8_0
(time ./bin/perplexity --model ${model_q8_0} -f ${shakespeare} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-ppl-shakespeare-q8_0.log
(time ./bin/perplexity --model ${model_q8_0} -f ${shakespeare} --lora ${lora_shakespeare} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-ppl-shakespeare-lora-q8_0.log
compare_ppl "q8_0 shakespeare" "$(cat $OUT/${ci}-ppl-shakespeare-q8_0.log | grep "^\[1\]")" "$(cat $OUT/${ci}-ppl-shakespeare-lora-q8_0.log | grep "^\[1\]")" | tee -a $OUT/${ci}-lora-ppl.log
# q8_0 + f16 lora-base
(time ./bin/perplexity --model ${model_q8_0} -f ${shakespeare} --lora ${lora_shakespeare} --lora-base ${model_f16} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-ppl-shakespeare-lora-q8_0-f16.log
compare_ppl "q8_0 / f16 base shakespeare" "$(cat $OUT/${ci}-ppl-shakespeare-q8_0.log | grep "^\[1\]")" "$(cat $OUT/${ci}-ppl-shakespeare-lora-q8_0-f16.log | grep "^\[1\]")" | tee -a $OUT/${ci}-lora-ppl.log
set +e
}
function gg_sum_pythia_1_4b {
function gg_sum_open_llama_3b_v2 {
gg_printf '### %s\n\n' "${ci}"
gg_printf 'Pythia 1.4B:\n'
gg_printf 'OpenLLaMA 3B-v2:\n'
gg_printf '- status: %s\n' "$(cat $OUT/${ci}.exit)"
gg_printf '- perplexity:\n%s\n' "$(cat $OUT/${ci}-ppl.log)"
gg_printf '- imatrix:\n```\n%s\n```\n' "$(cat $OUT/${ci}-imatrix-sum.log)"
gg_printf '- lora:\n%s\n' "$(cat $OUT/${ci}-lora-ppl.log)"
gg_printf '- f16: \n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-f16.log)"
gg_printf '- q8_0:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-q8_0.log)"
gg_printf '- q4_0:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-q4_0.log)"
@@ -538,33 +380,42 @@ function gg_sum_pythia_1_4b {
gg_printf '- q5_k:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-q5_k.log)"
gg_printf '- q6_k:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-q6_k.log)"
gg_printf '- save-load-state: \n```\n%s\n```\n' "$(cat $OUT/${ci}-save-load-state.log)"
gg_printf '- shakespeare (f16):\n```\n%s\n```\n' "$(cat $OUT/${ci}-ppl-shakespeare-f16.log)"
gg_printf '- shakespeare (f16 lora):\n```\n%s\n```\n' "$(cat $OUT/${ci}-ppl-shakespeare-lora-f16.log)"
gg_printf '- shakespeare (q8_0):\n```\n%s\n```\n' "$(cat $OUT/${ci}-ppl-shakespeare-q8_0.log)"
gg_printf '- shakespeare (q8_0 lora):\n```\n%s\n```\n' "$(cat $OUT/${ci}-ppl-shakespeare-lora-q8_0.log)"
gg_printf '- shakespeare (q8_0 / f16 base lora):\n```\n%s\n```\n' "$(cat $OUT/${ci}-ppl-shakespeare-lora-q8_0-f16.log)"
}
# pythia_2_8b
# open_llama_7b_v2
# requires: GG_BUILD_CUDA
function gg_run_pythia_2_8b {
function gg_run_open_llama_7b_v2 {
cd ${SRC}
gg_wget models-mnt/pythia/2.8B/ https://huggingface.co/EleutherAI/pythia-2.8b/raw/main/config.json
gg_wget models-mnt/pythia/2.8B/ https://huggingface.co/EleutherAI/pythia-2.8b/raw/main/tokenizer.json
gg_wget models-mnt/pythia/2.8B/ https://huggingface.co/EleutherAI/pythia-2.8b/raw/main/tokenizer_config.json
gg_wget models-mnt/pythia/2.8B/ https://huggingface.co/EleutherAI/pythia-2.8b/raw/main/special_tokens_map.json
gg_wget models-mnt/pythia/2.8B/ https://huggingface.co/EleutherAI/pythia-2.8b/resolve/main/pytorch_model.bin
gg_wget models-mnt/open-llama/7B-v2/ https://huggingface.co/openlm-research/open_llama_7b_v2/raw/main/config.json
gg_wget models-mnt/open-llama/7B-v2/ https://huggingface.co/openlm-research/open_llama_7b_v2/resolve/main/tokenizer.model
gg_wget models-mnt/open-llama/7B-v2/ https://huggingface.co/openlm-research/open_llama_7b_v2/raw/main/tokenizer_config.json
gg_wget models-mnt/open-llama/7B-v2/ https://huggingface.co/openlm-research/open_llama_7b_v2/raw/main/special_tokens_map.json
gg_wget models-mnt/open-llama/7B-v2/ https://huggingface.co/openlm-research/open_llama_7b_v2/raw/main/pytorch_model.bin.index.json
gg_wget models-mnt/open-llama/7B-v2/ https://huggingface.co/openlm-research/open_llama_7b_v2/resolve/main/pytorch_model-00001-of-00002.bin
gg_wget models-mnt/open-llama/7B-v2/ https://huggingface.co/openlm-research/open_llama_7b_v2/resolve/main/pytorch_model-00002-of-00002.bin
gg_wget models-mnt/open-llama/7B-v2/ https://huggingface.co/openlm-research/open_llama_7b_v2/raw/main/generation_config.json
gg_wget models-mnt/wikitext/ https://huggingface.co/datasets/ggml-org/ci/resolve/main/wikitext-2-raw-v1.zip
unzip -o models-mnt/wikitext/wikitext-2-raw-v1.zip -d models-mnt/wikitext/
path_models="../models-mnt/pythia/2.8B"
path_models="../models-mnt/open-llama/7B-v2"
path_wiki="../models-mnt/wikitext/wikitext-2-raw"
rm -rf build-ci-release && mkdir build-ci-release && cd build-ci-release
set -e
(time cmake -DCMAKE_BUILD_TYPE=Release ${CMAKE_EXTRA} .. ) 2>&1 | tee -a $OUT/${ci}-cmake.log
(time make -j$(nproc) ) 2>&1 | tee -a $OUT/${ci}-make.log
(time cmake -DCMAKE_BUILD_TYPE=Release ${CMAKE_EXTRA} -DLLAMA_CUDA=1 .. ) 2>&1 | tee -a $OUT/${ci}-cmake.log
(time make -j ) 2>&1 | tee -a $OUT/${ci}-make.log
python3 ../convert_hf_to_gguf.py ${path_models} --outfile ${path_models}/ggml-model-f16.gguf
python3 ../convert.py ${path_models}
model_f16="${path_models}/ggml-model-f16.gguf"
model_q8_0="${path_models}/ggml-model-q8_0.gguf"
@@ -580,47 +431,44 @@ function gg_run_pythia_2_8b {
wiki_test="${path_wiki}/wiki.test.raw"
./bin/llama-quantize ${model_f16} ${model_q8_0} q8_0
./bin/llama-quantize ${model_f16} ${model_q4_0} q4_0
./bin/llama-quantize ${model_f16} ${model_q4_1} q4_1
./bin/llama-quantize ${model_f16} ${model_q5_0} q5_0
./bin/llama-quantize ${model_f16} ${model_q5_1} q5_1
./bin/llama-quantize ${model_f16} ${model_q2_k} q2_k
./bin/llama-quantize ${model_f16} ${model_q3_k} q3_k
./bin/llama-quantize ${model_f16} ${model_q4_k} q4_k
./bin/llama-quantize ${model_f16} ${model_q5_k} q5_k
./bin/llama-quantize ${model_f16} ${model_q6_k} q6_k
./bin/quantize ${model_f16} ${model_q8_0} q8_0
./bin/quantize ${model_f16} ${model_q4_0} q4_0
./bin/quantize ${model_f16} ${model_q4_1} q4_1
./bin/quantize ${model_f16} ${model_q5_0} q5_0
./bin/quantize ${model_f16} ${model_q5_1} q5_1
./bin/quantize ${model_f16} ${model_q2_k} q2_k
./bin/quantize ${model_f16} ${model_q3_k} q3_k
./bin/quantize ${model_f16} ${model_q4_k} q4_k
./bin/quantize ${model_f16} ${model_q5_k} q5_k
./bin/quantize ${model_f16} ${model_q6_k} q6_k
(time ./bin/llama-cli --model ${model_f16} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-f16.log
(time ./bin/llama-cli --model ${model_q8_0} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q8_0.log
(time ./bin/llama-cli --model ${model_q4_0} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q4_0.log
(time ./bin/llama-cli --model ${model_q4_1} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q4_1.log
(time ./bin/llama-cli --model ${model_q5_0} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q5_0.log
(time ./bin/llama-cli --model ${model_q5_1} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q5_1.log
(time ./bin/llama-cli --model ${model_q2_k} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q2_k.log
(time ./bin/llama-cli --model ${model_q3_k} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q3_k.log
(time ./bin/llama-cli --model ${model_q4_k} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q4_k.log
(time ./bin/llama-cli --model ${model_q5_k} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q5_k.log
(time ./bin/llama-cli --model ${model_q6_k} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q6_k.log
(time ./bin/main --model ${model_f16} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-f16.log
(time ./bin/main --model ${model_q8_0} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q8_0.log
(time ./bin/main --model ${model_q4_0} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q4_0.log
(time ./bin/main --model ${model_q4_1} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q4_1.log
(time ./bin/main --model ${model_q5_0} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q5_0.log
(time ./bin/main --model ${model_q5_1} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q5_1.log
(time ./bin/main --model ${model_q2_k} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q2_k.log
(time ./bin/main --model ${model_q3_k} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q3_k.log
(time ./bin/main --model ${model_q4_k} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q4_k.log
(time ./bin/main --model ${model_q5_k} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q5_k.log
(time ./bin/main --model ${model_q6_k} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q6_k.log
(time ./bin/llama-perplexity --model ${model_f16} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-f16.log
(time ./bin/llama-perplexity --model ${model_q8_0} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q8_0.log
(time ./bin/llama-perplexity --model ${model_q4_0} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q4_0.log
(time ./bin/llama-perplexity --model ${model_q4_1} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q4_1.log
(time ./bin/llama-perplexity --model ${model_q5_0} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q5_0.log
(time ./bin/llama-perplexity --model ${model_q5_1} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q5_1.log
(time ./bin/llama-perplexity --model ${model_q2_k} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q2_k.log
(time ./bin/llama-perplexity --model ${model_q3_k} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q3_k.log
(time ./bin/llama-perplexity --model ${model_q4_k} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q4_k.log
(time ./bin/llama-perplexity --model ${model_q5_k} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q5_k.log
(time ./bin/llama-perplexity --model ${model_q6_k} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q6_k.log
(time ./bin/perplexity --model ${model_f16} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-f16.log
(time ./bin/perplexity --model ${model_q8_0} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q8_0.log
(time ./bin/perplexity --model ${model_q4_0} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q4_0.log
(time ./bin/perplexity --model ${model_q4_1} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q4_1.log
(time ./bin/perplexity --model ${model_q5_0} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q5_0.log
(time ./bin/perplexity --model ${model_q5_1} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q5_1.log
(time ./bin/perplexity --model ${model_q2_k} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q2_k.log
(time ./bin/perplexity --model ${model_q3_k} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q3_k.log
(time ./bin/perplexity --model ${model_q4_k} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q4_k.log
(time ./bin/perplexity --model ${model_q5_k} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q5_k.log
(time ./bin/perplexity --model ${model_q6_k} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q6_k.log
(time ./bin/llama-imatrix --model ${model_f16} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-imatrix.log
(time ./bin/imatrix --model ${model_f16} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-imatrix.log
(time ./bin/llama-save-load-state -ngl 10 --model ${model_q4_0} ) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
(time ./bin/llama-save-load-state -fa -ngl 10 --model ${model_q4_0} ) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
(time ./bin/llama-save-load-state -ngl 99 --model ${model_q4_0} ) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
(time ./bin/llama-save-load-state -fa -ngl 99 --model ${model_q4_0} ) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
(time ./bin/save-load-state --model ${model_q4_0} ) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
function check_ppl {
qnt="$1"
@@ -641,7 +489,7 @@ function gg_run_pythia_2_8b {
check_ppl "q4_1" "$(cat $OUT/${ci}-tg-q4_1.log | grep "^\[1\]")" | tee -a $OUT/${ci}-ppl.log
check_ppl "q5_0" "$(cat $OUT/${ci}-tg-q5_0.log | grep "^\[1\]")" | tee -a $OUT/${ci}-ppl.log
check_ppl "q5_1" "$(cat $OUT/${ci}-tg-q5_1.log | grep "^\[1\]")" | tee -a $OUT/${ci}-ppl.log
#check_ppl "q2_k" "$(cat $OUT/${ci}-tg-q2_k.log | grep "^\[1\]")" | tee -a $OUT/${ci}-ppl.log # note: ppl > 20.0 for this quant and model
check_ppl "q2_k" "$(cat $OUT/${ci}-tg-q2_k.log | grep "^\[1\]")" | tee -a $OUT/${ci}-ppl.log
check_ppl "q3_k" "$(cat $OUT/${ci}-tg-q3_k.log | grep "^\[1\]")" | tee -a $OUT/${ci}-ppl.log
check_ppl "q4_k" "$(cat $OUT/${ci}-tg-q4_k.log | grep "^\[1\]")" | tee -a $OUT/${ci}-ppl.log
check_ppl "q5_k" "$(cat $OUT/${ci}-tg-q5_k.log | grep "^\[1\]")" | tee -a $OUT/${ci}-ppl.log
@@ -649,16 +497,59 @@ function gg_run_pythia_2_8b {
cat $OUT/${ci}-imatrix.log | grep "Final" >> $OUT/${ci}-imatrix-sum.log
# lora
function compare_ppl {
qnt="$1"
ppl1=$(echo "$2" | grep -oE "[0-9]+\.[0-9]+" | tail -n 1)
ppl2=$(echo "$3" | grep -oE "[0-9]+\.[0-9]+" | tail -n 1)
if [ $(echo "$ppl1 < $ppl2" | bc) -eq 1 ]; then
printf ' - %s @ %s (FAIL: %s > %s)\n' "$qnt" "$ppl" "$ppl1" "$ppl2"
return 20
fi
printf ' - %s @ %s %s OK\n' "$qnt" "$ppl1" "$ppl2"
return 0
}
path_lora="../models-mnt/open-llama/7B-v2/lora"
path_shakespeare="../models-mnt/shakespeare"
shakespeare="${path_shakespeare}/shakespeare.txt"
lora_shakespeare="${path_lora}/ggml-adapter-model.bin"
gg_wget ${path_lora} https://huggingface.co/slaren/open_llama_7b_v2_shakespeare_lora/resolve/main/adapter_config.json
gg_wget ${path_lora} https://huggingface.co/slaren/open_llama_7b_v2_shakespeare_lora/resolve/main/adapter_model.bin
gg_wget ${path_shakespeare} https://huggingface.co/slaren/open_llama_7b_v2_shakespeare_lora/resolve/main/shakespeare.txt
python3 ../convert-lora-to-ggml.py ${path_lora}
# f16
(time ./bin/perplexity --model ${model_f16} -f ${shakespeare} -t 1 -ngl 999 -c 2048 -b 512 --chunks 3 ) 2>&1 | tee -a $OUT/${ci}-ppl-shakespeare-f16.log
(time ./bin/perplexity --model ${model_f16} -f ${shakespeare} --lora ${lora_shakespeare} -t 1 -ngl 999 -c 2048 -b 512 --chunks 3 ) 2>&1 | tee -a $OUT/${ci}-ppl-shakespeare-lora-f16.log
compare_ppl "f16 shakespeare" "$(cat $OUT/${ci}-ppl-shakespeare-f16.log | grep "^\[1\]")" "$(cat $OUT/${ci}-ppl-shakespeare-lora-f16.log | grep "^\[1\]")" | tee -a $OUT/${ci}-lora-ppl.log
# currently not supported by the CUDA backend
# q8_0
#(time ./bin/perplexity --model ${model_q8_0} -f ${shakespeare} -t 1 -ngl 999 -c 2048 -b 512 --chunks 3 ) 2>&1 | tee -a $OUT/${ci}-ppl-shakespeare-q8_0.log
#(time ./bin/perplexity --model ${model_q8_0} -f ${shakespeare} --lora ${lora_shakespeare} -t 1 -ngl 999 -c 2048 -b 512 --chunks 3 ) 2>&1 | tee -a $OUT/${ci}-ppl-shakespeare-lora-q8_0.log
#compare_ppl "q8_0 shakespeare" "$(cat $OUT/${ci}-ppl-shakespeare-q8_0.log | grep "^\[1\]")" "$(cat $OUT/${ci}-ppl-shakespeare-lora-q8_0.log | grep "^\[1\]")" | tee -a $OUT/${ci}-lora-ppl.log
# q8_0 + f16 lora-base
#(time ./bin/perplexity --model ${model_q8_0} -f ${shakespeare} --lora ${lora_shakespeare} --lora-base ${model_f16} -t 1 -ngl 999 -c 2048 -b 512 --chunks 3 ) 2>&1 | tee -a $OUT/${ci}-ppl-shakespeare-lora-q8_0-f16.log
#compare_ppl "q8_0 / f16 shakespeare" "$(cat $OUT/${ci}-ppl-shakespeare-q8_0.log | grep "^\[1\]")" "$(cat $OUT/${ci}-ppl-shakespeare-lora-q8_0-f16.log | grep "^\[1\]")" | tee -a $OUT/${ci}-lora-ppl.log
set +e
}
function gg_sum_pythia_2_8b {
function gg_sum_open_llama_7b_v2 {
gg_printf '### %s\n\n' "${ci}"
gg_printf 'Pythia 2.8B:\n'
gg_printf 'OpenLLaMA 7B-v2:\n'
gg_printf '- status: %s\n' "$(cat $OUT/${ci}.exit)"
gg_printf '- perplexity:\n%s\n' "$(cat $OUT/${ci}-ppl.log)"
gg_printf '- imatrix:\n```\n%s\n```\n' "$(cat $OUT/${ci}-imatrix-sum.log)"
gg_printf '- lora:\n%s\n' "$(cat $OUT/${ci}-lora-ppl.log)"
gg_printf '- f16: \n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-f16.log)"
gg_printf '- q8_0:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-q8_0.log)"
gg_printf '- q4_0:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-q4_0.log)"
@@ -671,6 +562,11 @@ function gg_sum_pythia_2_8b {
gg_printf '- q5_k:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-q5_k.log)"
gg_printf '- q6_k:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-q6_k.log)"
gg_printf '- save-load-state: \n```\n%s\n```\n' "$(cat $OUT/${ci}-save-load-state.log)"
gg_printf '- shakespeare (f16):\n```\n%s\n```\n' "$(cat $OUT/${ci}-ppl-shakespeare-f16.log)"
gg_printf '- shakespeare (f16 lora):\n```\n%s\n```\n' "$(cat $OUT/${ci}-ppl-shakespeare-lora-f16.log)"
#gg_printf '- shakespeare (q8_0):\n```\n%s\n```\n' "$(cat $OUT/${ci}-ppl-shakespeare-q8_0.log)"
#gg_printf '- shakespeare (q8_0 lora):\n```\n%s\n```\n' "$(cat $OUT/${ci}-ppl-shakespeare-lora-q8_0.log)"
#gg_printf '- shakespeare (q8_0 / f16 base lora):\n```\n%s\n```\n' "$(cat $OUT/${ci}-ppl-shakespeare-lora-q8_0-f16.log)"
}
# bge-small
@@ -679,7 +575,7 @@ function gg_run_embd_bge_small {
cd ${SRC}
gg_wget models-mnt/bge-small/ https://huggingface.co/BAAI/bge-small-en-v1.5/raw/main/config.json
gg_wget models-mnt/bge-small/ https://huggingface.co/BAAI/bge-small-en-v1.5/raw/main/tokenizer.json
gg_wget models-mnt/bge-small/ https://huggingface.co/BAAI/bge-small-en-v1.5/resolve/main/tokenizer.model
gg_wget models-mnt/bge-small/ https://huggingface.co/BAAI/bge-small-en-v1.5/raw/main/tokenizer_config.json
gg_wget models-mnt/bge-small/ https://huggingface.co/BAAI/bge-small-en-v1.5/raw/main/special_tokens_map.json
gg_wget models-mnt/bge-small/ https://huggingface.co/BAAI/bge-small-en-v1.5/resolve/main/pytorch_model.bin
@@ -697,17 +593,17 @@ function gg_run_embd_bge_small {
set -e
(time cmake -DCMAKE_BUILD_TYPE=Release ${CMAKE_EXTRA} .. ) 2>&1 | tee -a $OUT/${ci}-cmake.log
(time make -j$(nproc) ) 2>&1 | tee -a $OUT/${ci}-make.log
(time make -j ) 2>&1 | tee -a $OUT/${ci}-make.log
python3 ../convert_hf_to_gguf.py ${path_models} --outfile ${path_models}/ggml-model-f16.gguf
python3 ../convert-hf-to-gguf.py ${path_models}
model_f16="${path_models}/ggml-model-f16.gguf"
model_q8_0="${path_models}/ggml-model-q8_0.gguf"
./bin/llama-quantize ${model_f16} ${model_q8_0} q8_0
./bin/quantize ${model_f16} ${model_q8_0} q8_0
(time ./bin/llama-embedding --model ${model_f16} -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-f16.log
(time ./bin/llama-embedding --model ${model_q8_0} -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q8_0.log
(time ./bin/embedding --model ${model_f16} -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-f16.log
(time ./bin/embedding --model ${model_q8_0} -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q8_0.log
set +e
}
@@ -721,92 +617,8 @@ function gg_sum_embd_bge_small {
gg_printf '- q8_0:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-q8_0.log)"
}
# rerank_tiny
function gg_run_rerank_tiny {
cd ${SRC}
gg_wget models-mnt/rerank-tiny/ https://huggingface.co/jinaai/jina-reranker-v1-tiny-en/raw/main/config.json
gg_wget models-mnt/rerank-tiny/ https://huggingface.co/jinaai/jina-reranker-v1-tiny-en/raw/main/tokenizer.json
gg_wget models-mnt/rerank-tiny/ https://huggingface.co/jinaai/jina-reranker-v1-tiny-en/raw/main/tokenizer_config.json
gg_wget models-mnt/rerank-tiny/ https://huggingface.co/jinaai/jina-reranker-v1-tiny-en/raw/main/special_tokens_map.json
gg_wget models-mnt/rerank-tiny/ https://huggingface.co/jinaai/jina-reranker-v1-tiny-en/resolve/main/pytorch_model.bin
gg_wget models-mnt/rerank-tiny/ https://huggingface.co/jinaai/jina-reranker-v1-tiny-en/raw/main/sentence_bert_config.json
gg_wget models-mnt/rerank-tiny/ https://huggingface.co/jinaai/jina-reranker-v1-tiny-en/raw/main/vocab.txt
gg_wget models-mnt/rerank-tiny/ https://huggingface.co/jinaai/jina-reranker-v1-tiny-en/raw/main/modules.json
gg_wget models-mnt/rerank-tiny/ https://huggingface.co/jinaai/jina-reranker-v1-tiny-en/raw/main/config.json
gg_wget models-mnt/rerank-tiny/1_Pooling https://huggingface.co/jinaai/jina-reranker-v1-tiny-en/raw/main/1_Pooling/config.json
path_models="../models-mnt/rerank-tiny"
rm -rf build-ci-release && mkdir build-ci-release && cd build-ci-release
set -e
(time cmake -DCMAKE_BUILD_TYPE=Release ${CMAKE_EXTRA} .. ) 2>&1 | tee -a $OUT/${ci}-cmake.log
(time make -j$(nproc) ) 2>&1 | tee -a $OUT/${ci}-make.log
python3 ../convert_hf_to_gguf.py ${path_models} --outfile ${path_models}/ggml-model-f16.gguf
model_f16="${path_models}/ggml-model-f16.gguf"
# for this model, the SEP token is "</s>"
(time ./bin/llama-embedding --model ${model_f16} -p "what is panda?</s></s>hi\nwhat is panda?</s></s>it's a bear\nwhat is panda?</s></s>The giant panda (Ailuropoda melanoleuca), sometimes called a panda bear or simply panda, is a bear species endemic to China." --pooling rank --embd-normalize -1 --verbose-prompt) 2>&1 | tee -a $OUT/${ci}-rk-f16.log
# sample output
# rerank score 0: 0.029
# rerank score 1: 0.029
# rerank score 2: 0.135
# check that the score is in the range [$3, $4]
function check_score {
qnt="$1"
score=$(echo "$2" | grep -oE "[0-9]+\.[0-9]+" | tail -n 1)
if [ $(echo "$score < $3" | bc) -eq 1 ] || [ $(echo "$score > $4" | bc) -eq 1 ]; then
printf ' - %s @ %s (FAIL: score not in range [%s, %s])\n' "$qnt" "$score" "$3" "$4"
return 20
fi
printf ' - %s @ %s OK\n' "$qnt" "$score"
return 0
}
check_score "rerank score 0" "$(cat $OUT/${ci}-rk-f16.log | grep "rerank score 0")" "0.00" "0.05" | tee -a $OUT/${ci}-rk-f16.log
check_score "rerank score 1" "$(cat $OUT/${ci}-rk-f16.log | grep "rerank score 1")" "0.00" "0.05" | tee -a $OUT/${ci}-rk-f16.log
check_score "rerank score 2" "$(cat $OUT/${ci}-rk-f16.log | grep "rerank score 2")" "0.10" "0.30" | tee -a $OUT/${ci}-rk-f16.log
set +e
}
function gg_sum_rerank_tiny {
gg_printf '### %s\n\n' "${ci}"
gg_printf 'Rerank Tiny (Jina):\n'
gg_printf '- status: %s\n' "$(cat $OUT/${ci}.exit)"
gg_printf '- f16: \n```\n%s\n```\n' "$(cat $OUT/${ci}-rk-f16.log)"
}
function gg_check_build_requirements {
if ! command -v cmake &> /dev/null; then
gg_printf 'cmake not found, please install'
fi
if ! command -v make &> /dev/null; then
gg_printf 'make not found, please install'
fi
if ! command -v ctest &> /dev/null; then
gg_printf 'ctest not found, please install'
fi
}
## main
export LLAMA_LOG_PREFIX=1
export LLAMA_LOG_TIMESTAMPS=1
if [ -z ${GG_BUILD_LOW_PERF} ]; then
# Create symlink: ./llama.cpp/models-mnt -> $MNT/models/models-mnt
rm -rf ${SRC}/models-mnt
@@ -829,19 +641,12 @@ test $ret -eq 0 && gg_run ctest_release
if [ -z ${GG_BUILD_LOW_PERF} ]; then
test $ret -eq 0 && gg_run embd_bge_small
test $ret -eq 0 && gg_run rerank_tiny
if [ -z ${GG_BUILD_CLOUD} ] || [ ${GG_BUILD_EXTRA_TESTS_0} ]; then
test $ret -eq 0 && gg_run test_scripts_debug
test $ret -eq 0 && gg_run test_scripts_release
fi
if [ -z ${GG_BUILD_VRAM_GB} ] || [ ${GG_BUILD_VRAM_GB} -ge 8 ]; then
if [ -z ${GG_BUILD_CUDA} ] && [ -z ${GG_BUILD_VULKAN} ]; then
test $ret -eq 0 && gg_run pythia_1_4b
if [ -z ${GG_BUILD_CUDA} ]; then
test $ret -eq 0 && gg_run open_llama_3b_v2
else
test $ret -eq 0 && gg_run pythia_2_8b
#test $ret -eq 0 && gg_run open_llama_7b_v2
test $ret -eq 0 && gg_run open_llama_7b_v2
fi
test $ret -eq 0 && gg_run ctest_with_model_debug
test $ret -eq 0 && gg_run ctest_with_model_release

View File

@@ -79,22 +79,22 @@ endmacro()
# flags are for MSVC only!
check_sse("AVX" " ;/arch:AVX")
if (NOT ${AVX_FOUND})
set(GGML_AVX OFF)
set(LLAMA_AVX OFF)
else()
set(GGML_AVX ON)
set(LLAMA_AVX ON)
endif()
check_sse("AVX2" " ;/arch:AVX2")
check_sse("FMA" " ;/arch:AVX2")
if ((NOT ${AVX2_FOUND}) OR (NOT ${FMA_FOUND}))
set(GGML_AVX2 OFF)
set(LLAMA_AVX2 OFF)
else()
set(GGML_AVX2 ON)
set(LLAMA_AVX2 ON)
endif()
check_sse("AVX512" " ;/arch:AVX512")
if (NOT ${AVX512_FOUND})
set(GGML_AVX512 OFF)
set(LLAMA_AVX512 OFF)
else()
set(GGML_AVX512 ON)
set(LLAMA_AVX512 ON)
endif()

View File

@@ -1,16 +0,0 @@
set( CMAKE_SYSTEM_NAME Windows )
set( CMAKE_SYSTEM_PROCESSOR arm64 )
set( target arm64-pc-windows-msvc )
set( CMAKE_C_COMPILER clang )
set( CMAKE_CXX_COMPILER clang++ )
set( CMAKE_C_COMPILER_TARGET ${target} )
set( CMAKE_CXX_COMPILER_TARGET ${target} )
set( arch_c_flags "-march=armv8.7-a -fvectorize -ffp-model=fast -fno-finite-math-only" )
set( warn_c_flags "-Wno-format -Wno-unused-variable -Wno-unused-function -Wno-gnu-zero-variadic-macro-arguments" )
set( CMAKE_C_FLAGS_INIT "${arch_c_flags} ${warn_c_flags}" )
set( CMAKE_CXX_FLAGS_INIT "${arch_c_flags} ${warn_c_flags}" )

View File

@@ -1,6 +0,0 @@
set( CMAKE_SYSTEM_NAME Windows )
set( CMAKE_SYSTEM_PROCESSOR arm64 )
set( target arm64-pc-windows-msvc )
set( CMAKE_C_COMPILER_TARGET ${target} )
set( CMAKE_CXX_COMPILER_TARGET ${target} )

View File

@@ -1,22 +0,0 @@
find_package(Git)
# the commit's SHA1
execute_process(COMMAND
"${GIT_EXECUTABLE}" describe --match=NeVeRmAtCh --always --abbrev=8
WORKING_DIRECTORY "${CMAKE_SOURCE_DIR}"
OUTPUT_VARIABLE GIT_SHA1
ERROR_QUIET OUTPUT_STRIP_TRAILING_WHITESPACE)
# the date of the commit
execute_process(COMMAND
"${GIT_EXECUTABLE}" log -1 --format=%ad --date=local
WORKING_DIRECTORY "${CMAKE_SOURCE_DIR}"
OUTPUT_VARIABLE GIT_DATE
ERROR_QUIET OUTPUT_STRIP_TRAILING_WHITESPACE)
# the subject of the commit
execute_process(COMMAND
"${GIT_EXECUTABLE}" log -1 --format=%s
WORKING_DIRECTORY "${CMAKE_SOURCE_DIR}"
OUTPUT_VARIABLE GIT_COMMIT_SUBJECT
ERROR_QUIET OUTPUT_STRIP_TRAILING_WHITESPACE)

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@@ -1,10 +0,0 @@
prefix=@CMAKE_INSTALL_PREFIX@
exec_prefix=${prefix}
libdir=${exec_prefix}/lib
includedir=${prefix}/include
Name: llama
Description: Port of Facebook's LLaMA model in C/C++
Version: @PROJECT_VERSION@
Libs: -L${libdir} -lllama
Cflags: -I${includedir}

14
codecov.yml Normal file
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@@ -0,0 +1,14 @@
comment: off
coverage:
status:
project:
default:
target: auto
threshold: 0
base: auto
patch:
default:
target: auto
threshold: 0
base: auto

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@@ -1,6 +1,5 @@
# common
find_package(Threads REQUIRED)
# Build info header
#
@@ -37,7 +36,7 @@ add_custom_command(
COMMENT "Generating build details from Git"
COMMAND ${CMAKE_COMMAND} -DMSVC=${MSVC} -DCMAKE_C_COMPILER_VERSION=${CMAKE_C_COMPILER_VERSION}
-DCMAKE_C_COMPILER_ID=${CMAKE_C_COMPILER_ID} -DCMAKE_VS_PLATFORM_NAME=${CMAKE_VS_PLATFORM_NAME}
-DCMAKE_C_COMPILER=${CMAKE_C_COMPILER} -P "${CMAKE_CURRENT_SOURCE_DIR}/cmake/build-info-gen-cpp.cmake"
-DCMAKE_C_COMPILER=${CMAKE_C_COMPILER} -P "${CMAKE_CURRENT_SOURCE_DIR}/../scripts/gen-build-info-cpp.cmake"
WORKING_DIRECTORY "${CMAKE_CURRENT_SOURCE_DIR}/.."
DEPENDS "${CMAKE_CURRENT_SOURCE_DIR}/build-info.cpp.in" ${GIT_INDEX}
VERBATIM
@@ -48,26 +47,26 @@ if (BUILD_SHARED_LIBS)
set_target_properties(${TARGET} PROPERTIES POSITION_INDEPENDENT_CODE ON)
endif()
set(TARGET json-schema-to-grammar)
add_library(${TARGET} OBJECT json-schema-to-grammar.cpp json-schema-to-grammar.h)
set(TARGET common)
add_library(${TARGET} STATIC
arg.cpp
arg.h
base64.hpp
common.cpp
common.h
console.cpp
console.h
json-schema-to-grammar.cpp
json.hpp
log.cpp
log.h
ngram-cache.cpp
ngram-cache.h
sampling.cpp
common.cpp
sampling.h
train.cpp
sampling.cpp
console.h
console.cpp
grammar-parser.h
grammar-parser.cpp
json.hpp
train.h
train.cpp
ngram-cache.h
ngram-cache.cpp
)
if (BUILD_SHARED_LIBS)
@@ -86,5 +85,5 @@ if (LLAMA_CURL)
endif ()
target_include_directories(${TARGET} PUBLIC .)
target_compile_features (${TARGET} PUBLIC cxx_std_11)
target_link_libraries (${TARGET} PRIVATE ${LLAMA_COMMON_EXTRA_LIBS} PUBLIC llama Threads::Threads)
target_compile_features(${TARGET} PUBLIC cxx_std_11)
target_link_libraries(${TARGET} PRIVATE ${LLAMA_COMMON_EXTRA_LIBS} PUBLIC llama)

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@@ -1,77 +0,0 @@
#pragma once
#include "common.h"
#include <set>
#include <string>
#include <vector>
//
// CLI argument parsing
//
struct common_arg {
std::set<enum llama_example> examples = {LLAMA_EXAMPLE_COMMON};
std::vector<const char *> args;
const char * value_hint = nullptr; // help text or example for arg value
const char * value_hint_2 = nullptr; // for second arg value
const char * env = nullptr;
std::string help;
bool is_sparam = false; // is current arg a sampling param?
void (*handler_void) (common_params & params) = nullptr;
void (*handler_string) (common_params & params, const std::string &) = nullptr;
void (*handler_str_str)(common_params & params, const std::string &, const std::string &) = nullptr;
void (*handler_int) (common_params & params, int) = nullptr;
common_arg(
const std::initializer_list<const char *> & args,
const char * value_hint,
const std::string & help,
void (*handler)(common_params & params, const std::string &)
) : args(args), value_hint(value_hint), help(help), handler_string(handler) {}
common_arg(
const std::initializer_list<const char *> & args,
const char * value_hint,
const std::string & help,
void (*handler)(common_params & params, int)
) : args(args), value_hint(value_hint), help(help), handler_int(handler) {}
common_arg(
const std::initializer_list<const char *> & args,
const std::string & help,
void (*handler)(common_params & params)
) : args(args), help(help), handler_void(handler) {}
// support 2 values for arg
common_arg(
const std::initializer_list<const char *> & args,
const char * value_hint,
const char * value_hint_2,
const std::string & help,
void (*handler)(common_params & params, const std::string &, const std::string &)
) : args(args), value_hint(value_hint), value_hint_2(value_hint_2), help(help), handler_str_str(handler) {}
common_arg & set_examples(std::initializer_list<enum llama_example> examples);
common_arg & set_env(const char * env);
common_arg & set_sparam();
bool in_example(enum llama_example ex);
bool get_value_from_env(std::string & output);
bool has_value_from_env();
std::string to_string();
};
struct common_params_context {
enum llama_example ex = LLAMA_EXAMPLE_COMMON;
common_params & params;
std::vector<common_arg> options;
void(*print_usage)(int, char **) = nullptr;
common_params_context(common_params & params) : params(params) {}
};
// parse input arguments from CLI
// if one argument has invalid value, it will automatically display usage of the specific argument (and not the full usage message)
bool common_params_parse(int argc, char ** argv, common_params & params, llama_example ex, void(*print_usage)(int, char **) = nullptr);
// function to be used by test-arg-parser
common_params_context common_params_parser_init(common_params & params, llama_example ex, void(*print_usage)(int, char **) = nullptr);

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@@ -4,9 +4,18 @@
#include "llama.h"
#include "sampling.h"
#define LOG_NO_FILE_LINE_FUNCTION
#include "log.h"
#include <cmath>
#include <string>
#include <vector>
#include <sstream>
#include <random>
#include <thread>
#include <unordered_map>
#include <tuple>
#ifdef _WIN32
#define DIRECTORY_SEPARATOR '\\'
@@ -18,427 +27,185 @@
#define die_fmt(fmt, ...) do { fprintf(stderr, "error: " fmt "\n", __VA_ARGS__); exit(1); } while (0)
#define print_build_info() do { \
fprintf(stderr, "%s: build = %d (%s)\n", __func__, LLAMA_BUILD_NUMBER, LLAMA_COMMIT); \
fprintf(stderr, "%s: build = %d (%s)\n", __func__, LLAMA_BUILD_NUMBER, LLAMA_COMMIT); \
fprintf(stderr, "%s: built with %s for %s\n", __func__, LLAMA_COMPILER, LLAMA_BUILD_TARGET); \
} while(0)
#define DEFAULT_MODEL_PATH "models/7B/ggml-model-f16.gguf"
struct common_lora_adapter_info {
std::string path;
float scale;
};
struct common_lora_adapter_container : common_lora_adapter_info {
struct llama_lora_adapter * adapter;
};
// build info
extern int LLAMA_BUILD_NUMBER;
extern char const * LLAMA_COMMIT;
extern char const * LLAMA_COMPILER;
extern char const * LLAMA_BUILD_TARGET;
extern char const *LLAMA_COMMIT;
extern char const *LLAMA_COMPILER;
extern char const *LLAMA_BUILD_TARGET;
struct common_control_vector_load_info;
struct llama_control_vector_load_info;
int32_t get_num_physical_cores();
//
// CPU utils
// CLI argument parsing
//
struct cpu_params {
int n_threads = -1;
bool cpumask[GGML_MAX_N_THREADS] = {false}; // CPU affinity mask.
bool mask_valid = false; // Default: any CPU
enum ggml_sched_priority priority = GGML_SCHED_PRIO_NORMAL; // Scheduling prio : (0 - normal, 1 - medium, 2 - high, 3 - realtime)
bool strict_cpu = false; // Use strict CPU placement
uint32_t poll = 50; // Polling (busywait) level (0 - no polling, 100 - mostly polling)
};
struct gpt_params {
uint32_t seed = LLAMA_DEFAULT_SEED; // RNG seed
int32_t cpu_get_num_physical_cores();
int32_t cpu_get_num_math();
//
// Common params
//
enum llama_example {
LLAMA_EXAMPLE_COMMON,
LLAMA_EXAMPLE_SPECULATIVE,
LLAMA_EXAMPLE_MAIN,
LLAMA_EXAMPLE_INFILL,
LLAMA_EXAMPLE_EMBEDDING,
LLAMA_EXAMPLE_PERPLEXITY,
LLAMA_EXAMPLE_RETRIEVAL,
LLAMA_EXAMPLE_PASSKEY,
LLAMA_EXAMPLE_IMATRIX,
LLAMA_EXAMPLE_BENCH,
LLAMA_EXAMPLE_SERVER,
LLAMA_EXAMPLE_CVECTOR_GENERATOR,
LLAMA_EXAMPLE_EXPORT_LORA,
LLAMA_EXAMPLE_LLAVA,
LLAMA_EXAMPLE_LOOKUP,
LLAMA_EXAMPLE_PARALLEL,
LLAMA_EXAMPLE_COUNT,
};
enum common_sampler_type {
COMMON_SAMPLER_TYPE_NONE = 0,
COMMON_SAMPLER_TYPE_TOP_K = 1,
COMMON_SAMPLER_TYPE_TOP_P = 2,
COMMON_SAMPLER_TYPE_MIN_P = 3,
COMMON_SAMPLER_TYPE_TFS_Z = 4,
COMMON_SAMPLER_TYPE_TYPICAL_P = 5,
COMMON_SAMPLER_TYPE_TEMPERATURE = 6,
};
// dimensionality reduction methods, used by cvector-generator
enum dimre_method {
DIMRE_METHOD_PCA,
DIMRE_METHOD_MEAN,
};
// sampler parameters
struct common_sampler_params {
uint32_t seed = LLAMA_DEFAULT_SEED; // the seed used to initialize llama_sampler
int32_t n_prev = 64; // number of previous tokens to remember
int32_t n_probs = 0; // if greater than 0, output the probabilities of top n_probs tokens.
int32_t min_keep = 0; // 0 = disabled, otherwise samplers should return at least min_keep tokens
int32_t top_k = 40; // <= 0 to use vocab size
float top_p = 0.95f; // 1.0 = disabled
float min_p = 0.05f; // 0.0 = disabled
float tfs_z = 1.00f; // 1.0 = disabled
float typ_p = 1.00f; // typical_p, 1.0 = disabled
float temp = 0.80f; // <= 0.0 to sample greedily, 0.0 to not output probabilities
float dynatemp_range = 0.00f; // 0.0 = disabled
float dynatemp_exponent = 1.00f; // controls how entropy maps to temperature in dynamic temperature sampler
int32_t penalty_last_n = 64; // last n tokens to penalize (0 = disable penalty, -1 = context size)
float penalty_repeat = 1.00f; // 1.0 = disabled
float penalty_freq = 0.00f; // 0.0 = disabled
float penalty_present = 0.00f; // 0.0 = disabled
int32_t mirostat = 0; // 0 = disabled, 1 = mirostat, 2 = mirostat 2.0
float mirostat_tau = 5.00f; // target entropy
float mirostat_eta = 0.10f; // learning rate
bool penalize_nl = false; // consider newlines as a repeatable token
bool ignore_eos = false;
bool no_perf = false; // disable performance metrics
std::vector<enum common_sampler_type> samplers = {
COMMON_SAMPLER_TYPE_TOP_K,
COMMON_SAMPLER_TYPE_TFS_Z,
COMMON_SAMPLER_TYPE_TYPICAL_P,
COMMON_SAMPLER_TYPE_TOP_P,
COMMON_SAMPLER_TYPE_MIN_P,
COMMON_SAMPLER_TYPE_TEMPERATURE
};
std::string grammar; // optional BNF-like grammar to constrain sampling
std::vector<llama_logit_bias> logit_bias; // logit biases to apply
// print the parameters into a string
std::string print() const;
};
struct common_params {
int32_t n_predict = -1; // new tokens to predict
int32_t n_ctx = 0; // context size
int32_t n_batch = 2048; // logical batch size for prompt processing (must be >=32 to use BLAS)
int32_t n_ubatch = 512; // physical batch size for prompt processing (must be >=32 to use BLAS)
int32_t n_keep = 0; // number of tokens to keep from initial prompt
int32_t n_draft = 5; // number of tokens to draft during speculative decoding
int32_t n_chunks = -1; // max number of chunks to process (-1 = unlimited)
int32_t n_parallel = 1; // number of parallel sequences to decode
int32_t n_sequences = 1; // number of sequences to decode
float p_split = 0.1f; // speculative decoding split probability
int32_t n_gpu_layers = -1; // number of layers to store in VRAM (-1 - use default)
int32_t n_gpu_layers_draft = -1; // number of layers to store in VRAM for the draft model (-1 - use default)
int32_t main_gpu = 0; // the GPU that is used for scratch and small tensors
float tensor_split[128] = {0}; // how split tensors should be distributed across GPUs
int32_t grp_attn_n = 1; // group-attention factor
int32_t grp_attn_w = 512; // group-attention width
int32_t n_print = -1; // print token count every n tokens (-1 = disabled)
float rope_freq_base = 0.0f; // RoPE base frequency
float rope_freq_scale = 0.0f; // RoPE frequency scaling factor
int32_t n_threads = get_num_physical_cores();
int32_t n_threads_draft = -1;
int32_t n_threads_batch = -1; // number of threads to use for batch processing (-1 = use n_threads)
int32_t n_threads_batch_draft = -1;
int32_t n_predict = -1; // new tokens to predict
int32_t n_ctx = 512; // context size
int32_t n_batch = 2048; // logical batch size for prompt processing (must be >=32 to use BLAS)
int32_t n_ubatch = 512; // physical batch size for prompt processing (must be >=32 to use BLAS)
int32_t n_keep = 0; // number of tokens to keep from initial prompt
int32_t n_draft = 5; // number of tokens to draft during speculative decoding
int32_t n_chunks = -1; // max number of chunks to process (-1 = unlimited)
int32_t n_parallel = 1; // number of parallel sequences to decode
int32_t n_sequences = 1; // number of sequences to decode
float p_split = 0.1f; // speculative decoding split probability
int32_t n_gpu_layers = -1; // number of layers to store in VRAM (-1 - use default)
int32_t n_gpu_layers_draft = -1; // number of layers to store in VRAM for the draft model (-1 - use default)
llama_split_mode split_mode = LLAMA_SPLIT_MODE_LAYER; // how to split the model across GPUs
int32_t main_gpu = 0; // the GPU that is used for scratch and small tensors
float tensor_split[128] = {0}; // how split tensors should be distributed across GPUs
int32_t n_beams = 0; // if non-zero then use beam search of given width.
int32_t grp_attn_n = 1; // group-attention factor
int32_t grp_attn_w = 512; // group-attention width
int32_t n_print = -1; // print token count every n tokens (-1 = disabled)
float rope_freq_base = 0.0f; // RoPE base frequency
float rope_freq_scale = 0.0f; // RoPE frequency scaling factor
float yarn_ext_factor = -1.0f; // YaRN extrapolation mix factor
float yarn_attn_factor = 1.0f; // YaRN magnitude scaling factor
float yarn_attn_factor = 1.0f; // YaRN magnitude scaling factor
float yarn_beta_fast = 32.0f; // YaRN low correction dim
float yarn_beta_slow = 1.0f; // YaRN high correction dim
int32_t yarn_orig_ctx = 0; // YaRN original context length
float yarn_beta_slow = 1.0f; // YaRN high correction dim
int32_t yarn_orig_ctx = 0; // YaRN original context length
float defrag_thold = -1.0f; // KV cache defragmentation threshold
struct cpu_params cpuparams;
struct cpu_params cpuparams_batch;
struct cpu_params draft_cpuparams;
struct cpu_params draft_cpuparams_batch;
ggml_backend_sched_eval_callback cb_eval = nullptr;
void * cb_eval_user_data = nullptr;
ggml_numa_strategy numa = GGML_NUMA_STRATEGY_DISABLED;
enum llama_split_mode split_mode = LLAMA_SPLIT_MODE_LAYER; // how to split the model across GPUs
enum llama_rope_scaling_type rope_scaling_type = LLAMA_ROPE_SCALING_TYPE_UNSPECIFIED;
enum llama_pooling_type pooling_type = LLAMA_POOLING_TYPE_UNSPECIFIED; // pooling type for embeddings
enum llama_attention_type attention_type = LLAMA_ATTENTION_TYPE_UNSPECIFIED; // attention type for embeddings
llama_rope_scaling_type rope_scaling_type = LLAMA_ROPE_SCALING_TYPE_UNSPECIFIED;
llama_pooling_type pooling_type = LLAMA_POOLING_TYPE_UNSPECIFIED; // pooling type for embeddings
struct common_sampler_params sparams;
// // sampling parameters
struct llama_sampling_params sparams;
std::string model = ""; // model path // NOLINT
std::string model_draft = ""; // draft model for speculative decoding // NOLINT
std::string model_alias = "unknown"; // model alias // NOLINT
std::string model_url = ""; // model url to download // NOLINT
std::string hf_token = ""; // HF token // NOLINT
std::string hf_repo = ""; // HF repo // NOLINT
std::string hf_file = ""; // HF file // NOLINT
std::string prompt = ""; // NOLINT
std::string prompt_file = ""; // store the external prompt file name // NOLINT
std::string path_prompt_cache = ""; // path to file for saving/loading prompt eval state // NOLINT
std::string input_prefix = ""; // string to prefix user inputs with // NOLINT
std::string input_suffix = ""; // string to suffix user inputs with // NOLINT
std::string logdir = ""; // directory in which to save YAML log files // NOLINT
std::string lookup_cache_static = ""; // path of static ngram cache file for lookup decoding // NOLINT
std::string lookup_cache_dynamic = ""; // path of dynamic ngram cache file for lookup decoding // NOLINT
std::string logits_file = ""; // file for saving *all* logits // NOLINT
std::string rpc_servers = ""; // comma separated list of RPC servers // NOLINT
std::string model = "models/7B/ggml-model-f16.gguf"; // model path
std::string model_draft = ""; // draft model for speculative decoding
std::string model_alias = "unknown"; // model alias
std::string model_url = ""; // model url to download
std::string hf_repo = ""; // HF repo
std::string hf_file = ""; // HF file
std::string prompt = "";
std::string prompt_file = ""; // store the external prompt file name
std::string path_prompt_cache = ""; // path to file for saving/loading prompt eval state
std::string input_prefix = ""; // string to prefix user inputs with
std::string input_suffix = ""; // string to suffix user inputs with
std::vector<std::string> antiprompt; // string upon seeing which more user input is prompted
std::string logdir = ""; // directory in which to save YAML log files
std::string lookup_cache_static = ""; // path of static ngram cache file for lookup decoding
std::string lookup_cache_dynamic = ""; // path of dynamic ngram cache file for lookup decoding
std::string logits_file = ""; // file for saving *all* logits
std::vector<std::string> in_files; // all input files
std::vector<std::string> antiprompt; // strings upon which more user input is prompted (a.k.a. reverse prompts)
std::vector<llama_model_kv_override> kv_overrides;
bool lora_init_without_apply = false; // only load lora to memory, but do not apply it to ctx (user can manually apply lora later using llama_lora_adapter_apply)
std::vector<common_lora_adapter_info> lora_adapters; // lora adapter path with user defined scale
// TODO: avoid tuple, use struct
std::vector<std::tuple<std::string, float>> lora_adapter; // lora adapter path with user defined scale
std::string lora_base = ""; // base model path for the lora adapter
std::vector<common_control_vector_load_info> control_vectors; // control vector with user defined scale
std::vector<llama_control_vector_load_info> control_vectors; // control vector with user defined scale
int32_t verbosity = 0;
int32_t control_vector_layer_start = -1; // layer range for control vector
int32_t control_vector_layer_end = -1; // layer range for control vector
int32_t ppl_stride = 0; // stride for perplexity calculations. If left at 0, the pre-existing approach will be used.
int32_t ppl_output_type = 0; // = 0 -> ppl output is as usual, = 1 -> ppl output is num_tokens, ppl, one per line
// (which is more convenient to use for plotting)
//
bool hellaswag = false; // compute HellaSwag score over random tasks from datafile supplied in prompt
size_t hellaswag_tasks = 400; // number of tasks to use when computing the HellaSwag score
int ppl_stride = 0; // stride for perplexity calculations. If left at 0, the pre-existing approach will be used.
int ppl_output_type = 0; // = 0 -> ppl output is as usual, = 1 -> ppl output is num_tokens, ppl, one per line
// (which is more convenient to use for plotting)
//
bool hellaswag = false; // compute HellaSwag score over random tasks from datafile supplied in prompt
size_t hellaswag_tasks = 400; // number of tasks to use when computing the HellaSwag score
bool winogrande = false; // compute Winogrande score over random tasks from datafile supplied in prompt
size_t winogrande_tasks = 0; // number of tasks to use when computing the Winogrande score. If 0, all tasks will be computed
bool winogrande = false; // compute Winogrande score over random tasks from datafile supplied in prompt
size_t winogrande_tasks= 0; // number of tasks to use when computing the Winogrande score. If 0, all tasks will be computed
bool multiple_choice = false; // compute TruthfulQA score over random tasks from datafile supplied in prompt
size_t multiple_choice_tasks = 0; // number of tasks to use when computing the TruthfulQA score. If 0, all tasks will be computed
bool multiple_choice = false; // compute TruthfulQA score over random tasks from datafile supplied in prompt
size_t multiple_choice_tasks = 0; // number of tasks to use when computing the TruthfulQA score. If 0, all tasks will be computed
bool kl_divergence = false; // compute KL divergence
bool kl_divergence = false; // compute KL-divergence
bool usage = false; // print usage
bool random_prompt = false; // do not randomize prompt if none provided
bool use_color = false; // use color to distinguish generations and inputs
bool special = false; // enable special token output
bool interactive = false; // interactive mode
bool interactive_first = false; // wait for user input immediately
bool conversation = false; // conversation mode (does not print special tokens and suffix/prefix)
bool chatml = false; // chatml mode (used for models trained on chatml syntax)
bool prompt_cache_all = false; // save user input and generations to prompt cache
bool prompt_cache_ro = false; // open the prompt cache read-only and do not update it
bool escape = true; // escape "\n", "\r", "\t", "\'", "\"", and "\\"
bool embedding = false; // get only sentence embedding
bool escape = false; // escape "\n", "\r", "\t", "\'", "\"", and "\\"
bool interactive_first = false; // wait for user input immediately
bool multiline_input = false; // reverse the usage of `\`
bool simple_io = false; // improves compatibility with subprocesses and limited consoles
bool cont_batching = true; // insert new sequences for decoding on-the-fly
bool flash_attn = false; // flash attention
bool no_perf = false; // disable performance metrics
bool ctx_shift = true; // context shift on inifinite text generation
bool input_prefix_bos = false; // prefix BOS to user inputs, preceding input_prefix
bool ignore_eos = false; // ignore generated EOS tokens
bool instruct = false; // instruction mode (used for Alpaca models)
bool logits_all = false; // return logits for all tokens in the batch
bool use_mmap = true; // use mmap for faster loads
bool use_mlock = false; // use mlock to keep model in memory
bool verbose_prompt = false; // print prompt tokens before generation
bool display_prompt = true; // print prompt before generation
bool infill = false; // use infill mode
bool dump_kv_cache = false; // dump the KV cache contents for debugging purposes
bool no_kv_offload = false; // disable KV offloading
bool warmup = true; // warmup run
bool check_tensors = false; // validate tensor data
std::string cache_type_k = "f16"; // KV cache data type for the K
std::string cache_type_v = "f16"; // KV cache data type for the V
// multimodal models (see examples/llava)
std::string mmproj = ""; // path to multimodal projector // NOLINT
std::vector<std::string> image; // path to image file(s)
// embedding
bool embedding = false; // get only sentence embedding
int32_t embd_normalize = 2; // normalisation for embendings (-1=none, 0=max absolute int16, 1=taxicab, 2=euclidean, >2=p-norm)
std::string embd_out = ""; // empty = default, "array" = [[],[]...], "json" = openai style, "json+" = same "json" + cosine similarity matrix
std::string embd_sep = "\n"; // separator of embendings
bool reranking = false; // enable reranking support on server
// server params
int32_t port = 8080; // server listens on this network port
int32_t timeout_read = 600; // http read timeout in seconds
int32_t timeout_write = timeout_read; // http write timeout in seconds
int n_threads_http = -1; // number of threads to process HTTP requests (TODO: support threadpool)
std::string hostname = "127.0.0.1";
std::string public_path = ""; // NOLINT
std::string chat_template = ""; // NOLINT
bool enable_chat_template = true;
std::vector<std::string> api_keys;
std::string ssl_file_key = ""; // NOLINT
std::string ssl_file_cert = ""; // NOLINT
// "advanced" endpoints are disabled by default for better security
bool webui = true;
bool endpoint_slots = false;
bool endpoint_props = false; // only control POST requests, not GET
bool endpoint_metrics = false;
bool log_json = false;
std::string slot_save_path;
float slot_prompt_similarity = 0.5f;
// batched-bench params
bool is_pp_shared = false;
std::vector<int32_t> n_pp;
std::vector<int32_t> n_tg;
std::vector<int32_t> n_pl;
// retrieval params
std::vector<std::string> context_files; // context files to embed
int32_t chunk_size = 64; // chunk size for context embedding
std::string chunk_separator = "\n"; // chunk separator for context embedding
// passkey params
int32_t n_junk = 250; // number of times to repeat the junk text
int32_t i_pos = -1; // position of the passkey in the junk text
// imatrix params
std::string out_file = "imatrix.dat"; // save the resulting imatrix to this file
int32_t n_out_freq = 10; // output the imatrix every n_out_freq iterations
int32_t n_save_freq = 0; // save the imatrix every n_save_freq iterations
int32_t i_chunk = 0; // start processing from this chunk
bool process_output = false; // collect data for the output tensor
bool compute_ppl = true; // whether to compute perplexity
// cvector-generator params
int n_pca_batch = 100;
int n_pca_iterations = 1000;
dimre_method cvector_dimre_method = DIMRE_METHOD_PCA;
std::string cvector_outfile = "control_vector.gguf";
std::string cvector_positive_file = "examples/cvector-generator/positive.txt";
std::string cvector_negative_file = "examples/cvector-generator/negative.txt";
bool spm_infill = false; // suffix/prefix/middle pattern for infill
std::string lora_outfile = "ggml-lora-merged-f16.gguf";
// batched-bench params
bool batched_bench_output_jsonl = false;
std::string mmproj = ""; // path to multimodal projector
std::string image = ""; // path to an image file
};
// call once at the start of a program if it uses libcommon
// initializes the logging system and prints info about the build
void common_init();
bool gpt_params_parse_ex(int argc, char ** argv, gpt_params & params);
std::string common_params_get_system_info(const common_params & params);
bool gpt_params_parse(int argc, char ** argv, gpt_params & params);
bool parse_cpu_range(const std::string & range, bool(&boolmask)[GGML_MAX_N_THREADS]);
bool parse_cpu_mask(const std::string & mask, bool(&boolmask)[GGML_MAX_N_THREADS]);
void postprocess_cpu_params(cpu_params & cpuparams, const cpu_params * role_model = nullptr);
bool set_process_priority(enum ggml_sched_priority prio);
void gpt_print_usage(int argc, char ** argv, const gpt_params & params);
bool gpt_params_find_arg(int argc, char ** argv, const std::string & arg, gpt_params & params, int & i, bool & invalid_param);
std::string get_system_info(const gpt_params & params);
std::string gpt_random_prompt(std::mt19937 & rng);
void process_escapes(std::string& input);
//
// String utils
//
#ifdef __GNUC__
#ifdef __MINGW32__
#define LLAMA_COMMON_ATTRIBUTE_FORMAT(...) __attribute__((format(gnu_printf, __VA_ARGS__)))
#else
#define LLAMA_COMMON_ATTRIBUTE_FORMAT(...) __attribute__((format(printf, __VA_ARGS__)))
#endif
#else
#define LLAMA_COMMON_ATTRIBUTE_FORMAT(...)
#endif
LLAMA_COMMON_ATTRIBUTE_FORMAT(1, 2)
std::string string_format(const char * fmt, ...);
std::vector<llama_sampler_type> sampler_types_from_names(const std::vector<std::string> & names, bool allow_alt_names);
std::vector<llama_sampler_type> sampler_types_from_chars(const std::string & names_string);
std::vector<std::string> string_split(std::string input, char separator);
std::string string_strip(const std::string & str);
std::string string_get_sortable_timestamp();
void string_replace_all(std::string & s, const std::string & search, const std::string & replace);
template<class T>
static std::vector<T> string_split(const std::string & str, char delim) {
std::vector<T> values;
std::istringstream str_stream(str);
std::string token;
while (std::getline(str_stream, token, delim)) {
T value;
std::istringstream token_stream(token);
token_stream >> value;
values.push_back(value);
}
return values;
}
bool string_parse_kv_override(const char * data, std::vector<llama_model_kv_override> & overrides);
void string_process_escapes(std::string & input);
std::string string_from(bool value);
std::string string_from(const std::vector<int> & values);
std::string string_from(const struct llama_context * ctx, const std::vector<llama_token> & tokens);
std::string string_from(const struct llama_context * ctx, const struct llama_batch & batch);
//
// Filesystem utils
//
bool fs_validate_filename(const std::string & filename);
bool fs_create_directory_with_parents(const std::string & path);
std::string fs_get_cache_directory();
std::string fs_get_cache_file(const std::string & filename);
std::string sampler_type_to_name_string(llama_sampler_type sampler_type);
//
// Model utils
//
struct common_init_result {
struct llama_model * model = nullptr;
struct llama_context * context = nullptr;
std::vector<common_lora_adapter_container> lora_adapters;
};
// TODO: avoid tuplue, use struct
std::tuple<struct llama_model *, struct llama_context *> llama_init_from_gpt_params(gpt_params & params);
struct common_init_result common_init_from_params(common_params & params);
struct llama_model_params llama_model_params_from_gpt_params (const gpt_params & params);
struct llama_context_params llama_context_params_from_gpt_params(const gpt_params & params);
struct llama_model_params common_model_params_to_llama (const common_params & params);
struct llama_context_params common_context_params_to_llama(const common_params & params);
struct ggml_threadpool_params ggml_threadpool_params_from_cpu_params(const cpu_params & params);
struct llama_model * common_load_model_from_url(const char * model_url, const char * path_model, const char * hf_token, const struct llama_model_params & params);
struct llama_model * common_load_model_from_hf(const char * repo, const char * file, const char * path_model, const char * hf_token, const struct llama_model_params & params);
// clear LoRA adapters from context, then apply new list of adapters
void common_lora_adapters_apply(struct llama_context * ctx, std::vector<common_lora_adapter_container> & lora_adapters);
struct llama_model * llama_load_model_from_url(const char * model_url, const char * path_model, const struct llama_model_params & params);
struct llama_model * llama_load_model_from_hf(const char * repo, const char * file, const char * path_model, const struct llama_model_params & params);
// Batch utils
void common_batch_clear(struct llama_batch & batch);
void llama_batch_clear(struct llama_batch & batch);
void common_batch_add(
void llama_batch_add(
struct llama_batch & batch,
llama_token id,
llama_pos pos,
@@ -451,95 +218,88 @@ void common_batch_add(
// tokenizes a string into a vector of tokens
// should work similar to Python's `tokenizer.encode`
std::vector<llama_token> common_tokenize(
std::vector<llama_token> llama_tokenize(
const struct llama_context * ctx,
const std::string & text,
bool add_special,
bool parse_special = false);
bool add_bos,
bool special = false);
std::vector<llama_token> common_tokenize(
std::vector<llama_token> llama_tokenize(
const struct llama_model * model,
const std::string & text,
bool add_special,
bool parse_special = false);
bool add_bos,
bool special = false);
// tokenizes a token into a piece, optionally renders special/control tokens
// tokenizes a token into a piece
// should work similar to Python's `tokenizer.id_to_piece`
std::string common_token_to_piece(
std::string llama_token_to_piece(
const struct llama_context * ctx,
llama_token token,
bool special = true);
llama_token token);
// TODO: these should be moved in llama.h C-style API under single `llama_detokenize` function
// that takes into account the tokenizer type and decides how to handle the leading space
//
// detokenizes a vector of tokens into a string
// should work similar to Python's `tokenizer.decode`
// removes the leading space from the first non-BOS token
std::string llama_detokenize_spm(
llama_context * ctx,
const std::vector<llama_token> & tokens);
// detokenizes a vector of tokens into a string
// should work similar to Python's `tokenizer.decode`
// optionally renders special/control tokens
std::string common_detokenize(
std::string llama_detokenize_bpe(
llama_context * ctx,
const std::vector<llama_token> & tokens,
bool special = true);
const std::vector<llama_token> & tokens);
// Uses the value from the model metadata if possible, otherwise
// defaults to true when model type is SPM, otherwise false.
bool llama_should_add_bos_token(const llama_model * model);
//
// Chat template utils
// YAML utils
//
// same with llama_chat_message, but uses std::string
struct common_chat_msg {
std::string role;
std::string content;
};
bool create_directory_with_parents(const std::string & path);
void dump_vector_float_yaml(FILE * stream, const char * prop_name, const std::vector<float> & data);
void dump_vector_int_yaml(FILE * stream, const char * prop_name, const std::vector<int> & data);
void dump_string_yaml_multiline(FILE * stream, const char * prop_name, const char * data);
std::string get_sortable_timestamp();
// Check if the template supplied via "--chat-template" is supported or not. Returns true if it's valid
bool common_chat_verify_template(const std::string & tmpl);
// CPP wrapper for llama_chat_apply_template
// If the built-in template is not supported, we default to chatml
// If the custom "tmpl" is not supported, we throw an error
std::string common_chat_apply_template(const struct llama_model * model,
const std::string & tmpl,
const std::vector<common_chat_msg> & chat,
bool add_ass);
// Format single message, while taking into account the position of that message in chat history
std::string common_chat_format_single(const struct llama_model * model,
const std::string & tmpl,
const std::vector<common_chat_msg> & past_msg,
const common_chat_msg & new_msg,
bool add_ass);
// Returns an example of formatted chat
std::string common_chat_format_example(const struct llama_model * model,
const std::string & tmpl);
void dump_non_result_info_yaml(
FILE * stream, const gpt_params & params, const llama_context * lctx,
const std::string & timestamp, const std::vector<int> & prompt_tokens, const char * model_desc);
//
// KV cache utils
//
// Dump the KV cache view with the number of sequences per cell.
void common_kv_cache_dump_view(const llama_kv_cache_view & view, int row_size = 80);
void dump_kv_cache_view(const llama_kv_cache_view & view, int row_size = 80);
// Dump the KV cache view showing individual sequences in each cell (long output).
void common_kv_cache_dump_view_seqs(const llama_kv_cache_view & view, int row_size = 40);
void dump_kv_cache_view_seqs(const llama_kv_cache_view & view, int row_size = 40);
//
// Embedding utils
//
void common_embd_normalize(const float * inp, float * out, int n, int embd_norm = 2);
void llama_embd_normalize(const float * inp, float * out, int n);
float common_embd_similarity_cos(const float * embd1, const float * embd2, int n);
float llama_embd_similarity_cos(const float * embd1, const float * embd2, int n);
//
// Control vector utils
//
struct common_control_vector_data {
struct llama_control_vector_data {
int n_embd;
// stores data for layers [1, n_layer] where n_layer = data.size() / n_embd
std::vector<float> data;
};
struct common_control_vector_load_info {
struct llama_control_vector_load_info {
float strength;
std::string fname;
@@ -547,24 +307,11 @@ struct common_control_vector_load_info {
// Load control vectors, scale each by strength, and add them together.
// On error, returns {-1, empty}
common_control_vector_data common_control_vector_load(const std::vector<common_control_vector_load_info> & load_infos);
llama_control_vector_data llama_control_vector_load(const std::vector<llama_control_vector_load_info> & load_infos);
//
// Split utils
//
static const char * const LLM_KV_SPLIT_NO = "split.no";
static const char * const LLM_KV_SPLIT_COUNT = "split.count";
static const char * const LLM_KV_SPLIT_TENSORS_COUNT = "split.tensors.count";
//
// YAML utils
//
void yaml_dump_vector_float (FILE * stream, const char * prop_name, const std::vector<float> & data);
void yaml_dump_vector_int (FILE * stream, const char * prop_name, const std::vector<int> & data);
void yaml_dump_string_multiline(FILE * stream, const char * prop_name, const char * data);
void yaml_dump_non_result_info(
FILE * stream, const common_params & params, const llama_context * lctx,
const std::string & timestamp, const std::vector<int> & prompt_tokens, const char * model_desc);

View File

@@ -94,9 +94,6 @@ namespace console {
simple_io = true;
}
}
if (simple_io) {
_setmode(_fileno(stdin), _O_U8TEXT);
}
#else
// POSIX-specific console initialization
if (!simple_io) {

440
common/grammar-parser.cpp Normal file
View File

@@ -0,0 +1,440 @@
#include "grammar-parser.h"
#include <cstdint>
#include <cwchar>
#include <string>
#include <utility>
#include <stdexcept>
#include <exception>
namespace grammar_parser {
// NOTE: assumes valid utf8 (but checks for overrun)
// copied from llama.cpp
static std::pair<uint32_t, const char *> decode_utf8(const char * src) {
static const int lookup[] = { 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 3, 4 };
uint8_t first_byte = static_cast<uint8_t>(*src);
uint8_t highbits = first_byte >> 4;
int len = lookup[highbits];
uint8_t mask = (1 << (8 - len)) - 1;
uint32_t value = first_byte & mask;
const char * end = src + len; // may overrun!
const char * pos = src + 1;
for ( ; pos < end && *pos; pos++) {
value = (value << 6) + (static_cast<uint8_t>(*pos) & 0x3F);
}
return std::make_pair(value, pos);
}
static uint32_t get_symbol_id(parse_state & state, const char * src, size_t len) {
uint32_t next_id = static_cast<uint32_t>(state.symbol_ids.size());
auto result = state.symbol_ids.insert(std::make_pair(std::string(src, len), next_id));
return result.first->second;
}
static uint32_t generate_symbol_id(parse_state & state, const std::string & base_name) {
uint32_t next_id = static_cast<uint32_t>(state.symbol_ids.size());
state.symbol_ids[base_name + '_' + std::to_string(next_id)] = next_id;
return next_id;
}
static void add_rule(
parse_state & state,
uint32_t rule_id,
const std::vector<llama_grammar_element> & rule) {
if (state.rules.size() <= rule_id) {
state.rules.resize(rule_id + 1);
}
state.rules[rule_id] = rule;
}
static bool is_word_char(char c) {
return ('a' <= c && c <= 'z') || ('A' <= c && c <= 'Z') || c == '-' || ('0' <= c && c <= '9');
}
static std::pair<uint32_t, const char *> parse_hex(const char * src, int size) {
const char * pos = src;
const char * end = src + size;
uint32_t value = 0;
for ( ; pos < end && *pos; pos++) {
value <<= 4;
char c = *pos;
if ('a' <= c && c <= 'f') {
value += c - 'a' + 10;
} else if ('A' <= c && c <= 'F') {
value += c - 'A' + 10;
} else if ('0' <= c && c <= '9') {
value += c - '0';
} else {
break;
}
}
if (pos != end) {
throw std::runtime_error("expecting " + std::to_string(size) + " hex chars at " + src);
}
return std::make_pair(value, pos);
}
static const char * parse_space(const char * src, bool newline_ok) {
const char * pos = src;
while (*pos == ' ' || *pos == '\t' || *pos == '#' ||
(newline_ok && (*pos == '\r' || *pos == '\n'))) {
if (*pos == '#') {
while (*pos && *pos != '\r' && *pos != '\n') {
pos++;
}
} else {
pos++;
}
}
return pos;
}
static const char * parse_name(const char * src) {
const char * pos = src;
while (is_word_char(*pos)) {
pos++;
}
if (pos == src) {
throw std::runtime_error(std::string("expecting name at ") + src);
}
return pos;
}
static std::pair<uint32_t, const char *> parse_char(const char * src) {
if (*src == '\\') {
switch (src[1]) {
case 'x': return parse_hex(src + 2, 2);
case 'u': return parse_hex(src + 2, 4);
case 'U': return parse_hex(src + 2, 8);
case 't': return std::make_pair('\t', src + 2);
case 'r': return std::make_pair('\r', src + 2);
case 'n': return std::make_pair('\n', src + 2);
case '\\':
case '"':
case '[':
case ']':
return std::make_pair(src[1], src + 2);
default:
throw std::runtime_error(std::string("unknown escape at ") + src);
}
} else if (*src) {
return decode_utf8(src);
}
throw std::runtime_error("unexpected end of input");
}
const char * parse_alternates(
parse_state & state,
const char * src,
const std::string & rule_name,
uint32_t rule_id,
bool is_nested);
static const char * parse_sequence(
parse_state & state,
const char * src,
const std::string & rule_name,
std::vector<llama_grammar_element> & out_elements,
bool is_nested) {
size_t last_sym_start = out_elements.size();
const char * pos = src;
while (*pos) {
if (*pos == '"') { // literal string
pos++;
last_sym_start = out_elements.size();
while (*pos != '"') {
auto char_pair = parse_char(pos);
pos = char_pair.second;
out_elements.push_back({LLAMA_GRETYPE_CHAR, char_pair.first});
}
pos = parse_space(pos + 1, is_nested);
} else if (*pos == '[') { // char range(s)
pos++;
enum llama_gretype start_type = LLAMA_GRETYPE_CHAR;
if (*pos == '^') {
pos++;
start_type = LLAMA_GRETYPE_CHAR_NOT;
}
last_sym_start = out_elements.size();
while (*pos != ']') {
auto char_pair = parse_char(pos);
pos = char_pair.second;
enum llama_gretype type = last_sym_start < out_elements.size()
? LLAMA_GRETYPE_CHAR_ALT
: start_type;
out_elements.push_back({type, char_pair.first});
if (pos[0] == '-' && pos[1] != ']') {
auto endchar_pair = parse_char(pos + 1);
pos = endchar_pair.second;
out_elements.push_back({LLAMA_GRETYPE_CHAR_RNG_UPPER, endchar_pair.first});
}
}
pos = parse_space(pos + 1, is_nested);
} else if (is_word_char(*pos)) { // rule reference
const char * name_end = parse_name(pos);
uint32_t ref_rule_id = get_symbol_id(state, pos, name_end - pos);
pos = parse_space(name_end, is_nested);
last_sym_start = out_elements.size();
out_elements.push_back({LLAMA_GRETYPE_RULE_REF, ref_rule_id});
} else if (*pos == '(') { // grouping
// parse nested alternates into synthesized rule
pos = parse_space(pos + 1, true);
uint32_t sub_rule_id = generate_symbol_id(state, rule_name);
pos = parse_alternates(state, pos, rule_name, sub_rule_id, true);
last_sym_start = out_elements.size();
// output reference to synthesized rule
out_elements.push_back({LLAMA_GRETYPE_RULE_REF, sub_rule_id});
if (*pos != ')') {
throw std::runtime_error(std::string("expecting ')' at ") + pos);
}
pos = parse_space(pos + 1, is_nested);
} else if (*pos == '*' || *pos == '+' || *pos == '?') { // repetition operator
if (last_sym_start == out_elements.size()) {
throw std::runtime_error(std::string("expecting preceding item to */+/? at ") + pos);
}
// apply transformation to previous symbol (last_sym_start to end) according to
// rewrite rules:
// S* --> S' ::= S S' |
// S+ --> S' ::= S S' | S
// S? --> S' ::= S |
uint32_t sub_rule_id = generate_symbol_id(state, rule_name);
std::vector<llama_grammar_element> sub_rule;
// add preceding symbol to generated rule
sub_rule.insert(
sub_rule.end(), out_elements.begin() + last_sym_start, out_elements.end());
if (*pos == '*' || *pos == '+') {
// cause generated rule to recurse
sub_rule.push_back({LLAMA_GRETYPE_RULE_REF, sub_rule_id});
}
// mark start of alternate def
sub_rule.push_back({LLAMA_GRETYPE_ALT, 0});
if (*pos == '+') {
// add preceding symbol as alternate only for '+' (otherwise empty)
sub_rule.insert(
sub_rule.end(), out_elements.begin() + last_sym_start, out_elements.end());
}
sub_rule.push_back({LLAMA_GRETYPE_END, 0});
add_rule(state, sub_rule_id, sub_rule);
// in original rule, replace previous symbol with reference to generated rule
out_elements.resize(last_sym_start);
out_elements.push_back({LLAMA_GRETYPE_RULE_REF, sub_rule_id});
pos = parse_space(pos + 1, is_nested);
} else {
break;
}
}
return pos;
}
const char * parse_alternates(
parse_state & state,
const char * src,
const std::string & rule_name,
uint32_t rule_id,
bool is_nested) {
std::vector<llama_grammar_element> rule;
const char * pos = parse_sequence(state, src, rule_name, rule, is_nested);
while (*pos == '|') {
rule.push_back({LLAMA_GRETYPE_ALT, 0});
pos = parse_space(pos + 1, true);
pos = parse_sequence(state, pos, rule_name, rule, is_nested);
}
rule.push_back({LLAMA_GRETYPE_END, 0});
add_rule(state, rule_id, rule);
return pos;
}
static const char * parse_rule(parse_state & state, const char * src) {
const char * name_end = parse_name(src);
const char * pos = parse_space(name_end, false);
size_t name_len = name_end - src;
uint32_t rule_id = get_symbol_id(state, src, name_len);
const std::string name(src, name_len);
if (!(pos[0] == ':' && pos[1] == ':' && pos[2] == '=')) {
throw std::runtime_error(std::string("expecting ::= at ") + pos);
}
pos = parse_space(pos + 3, true);
pos = parse_alternates(state, pos, name, rule_id, false);
if (*pos == '\r') {
pos += pos[1] == '\n' ? 2 : 1;
} else if (*pos == '\n') {
pos++;
} else if (*pos) {
throw std::runtime_error(std::string("expecting newline or end at ") + pos);
}
return parse_space(pos, true);
}
parse_state parse(const char * src) {
try {
parse_state state;
const char * pos = parse_space(src, true);
while (*pos) {
pos = parse_rule(state, pos);
}
// Validate the state to ensure that all rules are defined
for (const auto & rule : state.rules) {
for (const auto & elem : rule) {
if (elem.type == LLAMA_GRETYPE_RULE_REF) {
// Ensure that the rule at that location exists
if (elem.value >= state.rules.size() || state.rules[elem.value].empty()) {
// Get the name of the rule that is missing
for (const auto & kv : state.symbol_ids) {
if (kv.second == elem.value) {
throw std::runtime_error("Undefined rule identifier '" + kv.first + "'");
}
}
}
}
}
}
return state;
} catch (const std::exception & err) {
fprintf(stderr, "%s: error parsing grammar: %s\n", __func__, err.what());
return parse_state();
}
}
static void print_grammar_char(FILE * file, uint32_t c) {
if (0x20 <= c && c <= 0x7f) {
fprintf(file, "%c", static_cast<char>(c));
} else {
// cop out of encoding UTF-8
fprintf(file, "<U+%04X>", c);
}
}
static bool is_char_element(llama_grammar_element elem) {
switch (elem.type) {
case LLAMA_GRETYPE_CHAR: return true;
case LLAMA_GRETYPE_CHAR_NOT: return true;
case LLAMA_GRETYPE_CHAR_ALT: return true;
case LLAMA_GRETYPE_CHAR_RNG_UPPER: return true;
default: return false;
}
}
static void print_rule_binary(FILE * file, const std::vector<llama_grammar_element> & rule) {
for (auto elem : rule) {
switch (elem.type) {
case LLAMA_GRETYPE_END: fprintf(file, "END"); break;
case LLAMA_GRETYPE_ALT: fprintf(file, "ALT"); break;
case LLAMA_GRETYPE_RULE_REF: fprintf(file, "RULE_REF"); break;
case LLAMA_GRETYPE_CHAR: fprintf(file, "CHAR"); break;
case LLAMA_GRETYPE_CHAR_NOT: fprintf(file, "CHAR_NOT"); break;
case LLAMA_GRETYPE_CHAR_RNG_UPPER: fprintf(file, "CHAR_RNG_UPPER"); break;
case LLAMA_GRETYPE_CHAR_ALT: fprintf(file, "CHAR_ALT"); break;
}
switch (elem.type) {
case LLAMA_GRETYPE_END:
case LLAMA_GRETYPE_ALT:
case LLAMA_GRETYPE_RULE_REF:
fprintf(file, "(%u) ", elem.value);
break;
case LLAMA_GRETYPE_CHAR:
case LLAMA_GRETYPE_CHAR_NOT:
case LLAMA_GRETYPE_CHAR_RNG_UPPER:
case LLAMA_GRETYPE_CHAR_ALT:
fprintf(file, "(\"");
print_grammar_char(file, elem.value);
fprintf(file, "\") ");
break;
}
}
fprintf(file, "\n");
}
static void print_rule(
FILE * file,
uint32_t rule_id,
const std::vector<llama_grammar_element> & rule,
const std::map<uint32_t, std::string> & symbol_id_names) {
if (rule.empty() || rule.back().type != LLAMA_GRETYPE_END) {
throw std::runtime_error(
"malformed rule, does not end with LLAMA_GRETYPE_END: " + std::to_string(rule_id));
}
fprintf(file, "%s ::= ", symbol_id_names.at(rule_id).c_str());
for (size_t i = 0, end = rule.size() - 1; i < end; i++) {
llama_grammar_element elem = rule[i];
switch (elem.type) {
case LLAMA_GRETYPE_END:
throw std::runtime_error(
"unexpected end of rule: " + std::to_string(rule_id) + "," +
std::to_string(i));
case LLAMA_GRETYPE_ALT:
fprintf(file, "| ");
break;
case LLAMA_GRETYPE_RULE_REF:
fprintf(file, "%s ", symbol_id_names.at(elem.value).c_str());
break;
case LLAMA_GRETYPE_CHAR:
fprintf(file, "[");
print_grammar_char(file, elem.value);
break;
case LLAMA_GRETYPE_CHAR_NOT:
fprintf(file, "[^");
print_grammar_char(file, elem.value);
break;
case LLAMA_GRETYPE_CHAR_RNG_UPPER:
if (i == 0 || !is_char_element(rule[i - 1])) {
throw std::runtime_error(
"LLAMA_GRETYPE_CHAR_RNG_UPPER without preceding char: " +
std::to_string(rule_id) + "," + std::to_string(i));
}
fprintf(file, "-");
print_grammar_char(file, elem.value);
break;
case LLAMA_GRETYPE_CHAR_ALT:
if (i == 0 || !is_char_element(rule[i - 1])) {
throw std::runtime_error(
"LLAMA_GRETYPE_CHAR_ALT without preceding char: " +
std::to_string(rule_id) + "," + std::to_string(i));
}
print_grammar_char(file, elem.value);
break;
}
if (is_char_element(elem)) {
switch (rule[i + 1].type) {
case LLAMA_GRETYPE_CHAR_ALT:
case LLAMA_GRETYPE_CHAR_RNG_UPPER:
break;
default:
fprintf(file, "] ");
}
}
}
fprintf(file, "\n");
}
void print_grammar(FILE * file, const parse_state & state) {
try {
std::map<uint32_t, std::string> symbol_id_names;
for (const auto & kv : state.symbol_ids) {
symbol_id_names[kv.second] = kv.first;
}
for (size_t i = 0, end = state.rules.size(); i < end; i++) {
// fprintf(file, "%zu: ", i);
// print_rule_binary(file, state.rules[i]);
print_rule(file, uint32_t(i), state.rules[i], symbol_id_names);
// fprintf(file, "\n");
}
} catch (const std::exception & err) {
fprintf(stderr, "\n%s: error printing grammar: %s\n", __func__, err.what());
}
}
std::vector<const llama_grammar_element *> parse_state::c_rules() {
std::vector<const llama_grammar_element *> ret;
ret.reserve(rules.size());
for (const auto & rule : rules) {
ret.push_back(rule.data());
}
return ret;
}
}

29
common/grammar-parser.h Normal file
View File

@@ -0,0 +1,29 @@
// Implements a parser for an extended Backus-Naur form (BNF), producing the
// binary context-free grammar format specified by llama.h. Supports character
// ranges, grouping, and repetition operators. As an example, a grammar for
// arithmetic might look like:
//
// root ::= expr
// expr ::= term ([-+*/] term)*
// term ::= num | "(" space expr ")" space
// num ::= [0-9]+ space
// space ::= [ \t\n]*
#pragma once
#include "llama.h"
#include <vector>
#include <map>
#include <cstdint>
#include <string>
namespace grammar_parser {
struct parse_state {
std::map<std::string, uint32_t> symbol_ids;
std::vector<std::vector<llama_grammar_element>> rules;
std::vector<const llama_grammar_element *> c_rules();
};
parse_state parse(const char * src);
void print_grammar(FILE * file, const parse_state & state);
}

View File

@@ -11,291 +11,35 @@
using json = nlohmann::ordered_json;
template <typename Iterator>
static std::string join(Iterator begin, Iterator end, const std::string & separator);
const std::string SPACE_RULE = "\" \"?";
static std::string repeat(const std::string & str, size_t n);
static std::string build_repetition(const std::string & item_rule, int min_items, int max_items, const std::string & separator_rule = "") {
auto has_max = max_items != std::numeric_limits<int>::max();
if (min_items == 0 && max_items == 1) {
return item_rule + "?";
}
if (separator_rule.empty()) {
if (min_items == 1 && !has_max) {
return item_rule + "+";
} else if (min_items == 0 && !has_max) {
return item_rule + "*";
} else {
return item_rule + "{" + std::to_string(min_items) + "," + (has_max ? std::to_string(max_items) : "") + "}";
}
}
auto result = item_rule + " " + build_repetition("(" + separator_rule + " " + item_rule + ")", min_items == 0 ? 0 : min_items - 1, has_max ? max_items - 1 : max_items);
if (min_items == 0) {
result = "(" + result + ")?";
}
return result;
}
/* Minimalistic replacement for std::string_view, which is only available from C++17 onwards */
class string_view {
const std::string & _str;
const size_t _start;
const size_t _end;
public:
string_view(const std::string & str, size_t start = 0, size_t end = std::string::npos) : _str(str), _start(start), _end(end == std::string::npos ? str.length() : end) {}
size_t size() const {
return _end - _start;
}
size_t length() const {
return size();
}
operator std::string() const {
return str();
}
std::string str() const {
return _str.substr(_start, _end - _start);
}
string_view substr(size_t pos, size_t len = std::string::npos) const {
return string_view(_str, _start + pos, len == std::string::npos ? _end : _start + pos + len);
}
char operator[](size_t pos) const {
auto index = _start + pos;
if (index >= _end) {
throw std::out_of_range("string_view index out of range");
}
return _str[_start + pos];
}
bool operator==(const string_view & other) const {
std::string this_str = *this;
std::string other_str = other;
return this_str == other_str;
}
std::unordered_map<std::string, std::string> PRIMITIVE_RULES = {
{"boolean", "(\"true\" | \"false\") space"},
{"number", "(\"-\"? ([0-9] | [1-9] [0-9]*)) (\".\" [0-9]+)? ([eE] [-+]? [0-9]+)? space"},
{"integer", "(\"-\"? ([0-9] | [1-9] [0-9]*)) space"},
{"value", "object | array | string | number | boolean"},
{"object", "\"{\" space ( string \":\" space value (\",\" space string \":\" space value)* )? \"}\" space"},
{"array", "\"[\" space ( value (\",\" space value)* )? \"]\" space"},
{"uuid", "\"\\\"\" [0-9a-fA-F][0-9a-fA-F][0-9a-fA-F][0-9a-fA-F][0-9a-fA-F][0-9a-fA-F][0-9a-fA-F][0-9a-fA-F] "
"\"-\" [0-9a-fA-F][0-9a-fA-F][0-9a-fA-F][0-9a-fA-F] "
"\"-\" [0-9a-fA-F][0-9a-fA-F][0-9a-fA-F][0-9a-fA-F] "
"\"-\" [0-9a-fA-F][0-9a-fA-F][0-9a-fA-F][0-9a-fA-F] "
"\"-\" [0-9a-fA-F][0-9a-fA-F][0-9a-fA-F][0-9a-fA-F][0-9a-fA-F][0-9a-fA-F][0-9a-fA-F][0-9a-fA-F][0-9a-fA-F][0-9a-fA-F][0-9a-fA-F][0-9a-fA-F] \"\\\"\" space"},
{"string", " \"\\\"\" (\n"
" [^\"\\\\] |\n"
" \"\\\\\" ([\"\\\\/bfnrt] | \"u\" [0-9a-fA-F] [0-9a-fA-F] [0-9a-fA-F] [0-9a-fA-F])\n"
" )* \"\\\"\" space"},
{"null", "\"null\" space"}
};
std::vector<std::string> OBJECT_RULE_NAMES = {"object", "array", "string", "number", "boolean", "null", "value"};
static void _build_min_max_int(int min_value, int max_value, std::stringstream & out, int decimals_left = 16, bool top_level = true) {
auto has_min = min_value != std::numeric_limits<int>::min();
auto has_max = max_value != std::numeric_limits<int>::max();
auto digit_range = [&](char from, char to) {
out << "[";
if (from == to) {
out << from;
} else {
out << from << "-" << to;
}
out << "]";
};
auto more_digits = [&](int min_digits, int max_digits) {
out << "[0-9]";
if (min_digits == max_digits && min_digits == 1) {
return;
}
out << "{";
out << min_digits;
if (max_digits != min_digits) {
out << ",";
if (max_digits != std::numeric_limits<int>::max()) {
out << max_digits;
}
}
out << "}";
};
std::function<void(const string_view &, const string_view &)> uniform_range =
[&](const string_view & from, const string_view & to) {
size_t i = 0;
while (i < from.length() && i < to.length() && from[i] == to[i]) {
i++;
}
if (i > 0) {
out << "\"" << from.substr(0, i).str() << "\"";
}
if (i < from.length() && i < to.length()) {
if (i > 0) {
out << " ";
}
auto sub_len = from.length() - i - 1;
if (sub_len > 0) {
auto from_sub = from.substr(i + 1);
auto to_sub = to.substr(i + 1);
auto sub_zeros = repeat("0", sub_len);
auto sub_nines = repeat("9", sub_len);
auto to_reached = false;
out << "(";
if (from_sub == sub_zeros) {
digit_range(from[i], to[i] - 1);
out << " ";
more_digits(sub_len, sub_len);
} else {
out << "[" << from[i] << "] ";
out << "(";
uniform_range(from_sub, sub_nines);
out << ")";
if (from[i] < to[i] - 1) {
out << " | ";
if (to_sub == sub_nines) {
digit_range(from[i] + 1, to[i]);
to_reached = true;
} else {
digit_range(from[i] + 1, to[i] - 1);
}
out << " ";
more_digits(sub_len, sub_len);
}
}
if (!to_reached) {
out << " | ";
digit_range(to[i], to[i]);
out << " ";
uniform_range(sub_zeros, to_sub);
}
out << ")";
} else {
out << "[" << from[i] << "-" << to[i] << "]";
}
}
};
if (has_min && has_max) {
if (min_value < 0 && max_value < 0) {
out << "\"-\" (";
_build_min_max_int(-max_value, -min_value, out, decimals_left, /* top_level= */ true);
out << ")";
return;
}
if (min_value < 0) {
out << "\"-\" (";
_build_min_max_int(0, -min_value, out, decimals_left, /* top_level= */ true);
out << ") | ";
min_value = 0;
}
auto min_s = std::to_string(min_value);
auto max_s = std::to_string(max_value);
auto min_digits = min_s.length();
auto max_digits = max_s.length();
for (auto digits = min_digits; digits < max_digits; digits++) {
uniform_range(min_s, repeat("9", digits));
min_s = "1" + repeat("0", digits);
out << " | ";
}
uniform_range(min_s, max_s);
return;
}
auto less_decimals = std::max(decimals_left - 1, 1);
if (has_min) {
if (min_value < 0) {
out << "\"-\" (";
_build_min_max_int(std::numeric_limits<int>::min(), -min_value, out, decimals_left, /* top_level= */ false);
out << ") | [0] | [1-9] ";
more_digits(0, decimals_left - 1);
} else if (min_value == 0) {
if (top_level) {
out << "[0] | [1-9] ";
more_digits(0, less_decimals);
} else {
more_digits(1, decimals_left);
}
} else if (min_value <= 9) {
char c = '0' + min_value;
auto range_start = top_level ? '1' : '0';
if (c > range_start) {
digit_range(range_start, c - 1);
out << " ";
more_digits(1, less_decimals);
out << " | ";
}
digit_range(c, '9');
out << " ";
more_digits(0, less_decimals);
} else {
auto min_s = std::to_string(min_value);
auto len = min_s.length();
auto c = min_s[0];
if (c > '1') {
digit_range(top_level ? '1' : '0', c - 1);
out << " ";
more_digits(len, less_decimals);
out << " | ";
}
digit_range(c, c);
out << " (";
_build_min_max_int(std::stoi(min_s.substr(1)), std::numeric_limits<int>::max(), out, less_decimals, /* top_level= */ false);
out << ")";
if (c < '9') {
out << " | ";
digit_range(c + 1, '9');
out << " ";
more_digits(len - 1, less_decimals);
}
}
return;
}
if (has_max) {
if (max_value >= 0) {
if (top_level) {
out << "\"-\" [1-9] ";
more_digits(0, less_decimals);
out << " | ";
}
_build_min_max_int(0, max_value, out, decimals_left, /* top_level= */ true);
} else {
out << "\"-\" (";
_build_min_max_int(-max_value, std::numeric_limits<int>::max(), out, decimals_left, /* top_level= */ false);
out << ")";
}
return;
}
throw std::runtime_error("At least one of min_value or max_value must be set");
}
const std::string SPACE_RULE = "| \" \" | \"\\n\" [ \\t]{0,20}";
struct BuiltinRule {
std::string content;
std::vector<std::string> deps;
};
std::unordered_map<std::string, BuiltinRule> PRIMITIVE_RULES = {
{"boolean", {"(\"true\" | \"false\") space", {}}},
{"decimal-part", {"[0-9]{1,16}", {}}},
{"integral-part", {"[0] | [1-9] [0-9]{0,15}", {}}},
{"number", {"(\"-\"? integral-part) (\".\" decimal-part)? ([eE] [-+]? integral-part)? space", {"integral-part", "decimal-part"}}},
{"integer", {"(\"-\"? integral-part) space", {"integral-part"}}},
{"value", {"object | array | string | number | boolean | null", {"object", "array", "string", "number", "boolean", "null"}}},
{"object", {"\"{\" space ( string \":\" space value (\",\" space string \":\" space value)* )? \"}\" space", {"string", "value"}}},
{"array", {"\"[\" space ( value (\",\" space value)* )? \"]\" space", {"value"}}},
{"uuid", {"\"\\\"\" [0-9a-fA-F]{8} \"-\" [0-9a-fA-F]{4} \"-\" [0-9a-fA-F]{4} \"-\" [0-9a-fA-F]{4} \"-\" [0-9a-fA-F]{12} \"\\\"\" space", {}}},
{"char", {"[^\"\\\\\\x7F\\x00-\\x1F] | [\\\\] ([\"\\\\bfnrt] | \"u\" [0-9a-fA-F]{4})", {}}},
{"string", {"\"\\\"\" char* \"\\\"\" space", {"char"}}},
{"null", {"\"null\" space", {}}},
};
std::unordered_map<std::string, BuiltinRule> STRING_FORMAT_RULES = {
{"date", {"[0-9]{4} \"-\" ( \"0\" [1-9] | \"1\" [0-2] ) \"-\" ( \"0\" [1-9] | [1-2] [0-9] | \"3\" [0-1] )", {}}},
{"time", {"([01] [0-9] | \"2\" [0-3]) \":\" [0-5] [0-9] \":\" [0-5] [0-9] ( \".\" [0-9]{3} )? ( \"Z\" | ( \"+\" | \"-\" ) ( [01] [0-9] | \"2\" [0-3] ) \":\" [0-5] [0-9] )", {}}},
{"date-time", {"date \"T\" time", {"date", "time"}}},
{"date-string", {"\"\\\"\" date \"\\\"\" space", {"date"}}},
{"time-string", {"\"\\\"\" time \"\\\"\" space", {"time"}}},
{"date-time-string", {"\"\\\"\" date-time \"\\\"\" space", {"date-time"}}}
std::unordered_map<std::string, std::string> DATE_RULES = {
{"date", "[0-9] [0-9] [0-9] [0-9] \"-\" ( \"0\" [1-9] | \"1\" [0-2] ) \"-\" ( \"0\" [1-9] | [1-2] [0-9] | \"3\" [0-1] )"},
{"time", "([01] [0-9] | \"2\" [0-3]) \":\" [0-5] [0-9] \":\" [0-5] [0-9] ( \".\" [0-9] [0-9] [0-9] )? ( \"Z\" | ( \"+\" | \"-\" ) ( [01] [0-9] | \"2\" [0-3] ) \":\" [0-5] [0-9] )"},
{"date-time", "date \"T\" time"},
{"date-string", "\"\\\"\" date \"\\\"\" space"},
{"time-string", "\"\\\"\" time \"\\\"\" space"},
{"date-time-string", "\"\\\"\" date-time \"\\\"\" space"}
};
static bool is_reserved_name(const std::string & name) {
@@ -303,7 +47,7 @@ static bool is_reserved_name(const std::string & name) {
if (RESERVED_NAMES.empty()) {
RESERVED_NAMES.insert("root");
for (const auto &p : PRIMITIVE_RULES) RESERVED_NAMES.insert(p.first);
for (const auto &p : STRING_FORMAT_RULES) RESERVED_NAMES.insert(p.first);
for (const auto &p : DATE_RULES) RESERVED_NAMES.insert(p.first);
}
return RESERVED_NAMES.find(name) != RESERVED_NAMES.end();
}
@@ -316,7 +60,7 @@ std::unordered_map<char, std::string> GRAMMAR_LITERAL_ESCAPES = {
};
std::unordered_set<char> NON_LITERAL_SET = {'|', '.', '(', ')', '[', ']', '{', '}', '*', '+', '?'};
std::unordered_set<char> ESCAPED_IN_REGEXPS_BUT_NOT_IN_LITERALS = {'^', '$', '.', '[', ']', '(', ')', '|', '{', '}', '*', '+', '?'};
std::unordered_set<char> ESCAPED_IN_REGEXPS_BUT_NOT_IN_LITERALS = {'[', ']', '(', ')', '|', '{', '}', '*', '+', '?'};
template <typename Iterator>
std::string join(Iterator begin, Iterator end, const std::string & separator) {
@@ -387,6 +131,7 @@ static std::string format_literal(const std::string & literal) {
return "\"" + escaped + "\"";
}
class SchemaConverter {
private:
std::function<json(const std::string &)> _fetch_json;
@@ -447,7 +192,7 @@ private:
if (_dotall) {
rule = "[\\U00000000-\\U0010FFFF]";
} else {
rule = "[^\\x0A\\x0D]";
rule = "[\\U00000000-\\x09\\x0B\\x0C\\x0E-\\U0010FFFF]";
}
return _add_rule("dot", rule);
};
@@ -461,7 +206,7 @@ private:
if (literal.empty()) {
return false;
}
ret.emplace_back(literal, true);
ret.push_back(std::make_pair(literal, true));
literal.clear();
return true;
};
@@ -487,7 +232,7 @@ private:
while (i < length) {
char c = sub_pattern[i];
if (c == '.') {
seq.emplace_back(get_dot(), false);
seq.push_back(std::make_pair(get_dot(), false));
i++;
} else if (c == '(') {
i++;
@@ -496,7 +241,7 @@ private:
_warnings.push_back("Unsupported pattern syntax");
}
}
seq.emplace_back("(" + to_rule(transform()) + ")", false);
seq.push_back(std::make_pair("(" + to_rule(transform()) + ")", false));
} else if (c == ')') {
i++;
if (start > 0 && sub_pattern[start - 1] != '(') {
@@ -520,9 +265,9 @@ private:
}
square_brackets += ']';
i++;
seq.emplace_back(square_brackets, false);
seq.push_back(std::make_pair(square_brackets, false));
} else if (c == '|') {
seq.emplace_back("|", false);
seq.push_back(std::make_pair("|", false));
i++;
} else if (c == '*' || c == '+' || c == '?') {
seq.back() = std::make_pair(to_rule(seq.back()) + c, false);
@@ -563,20 +308,47 @@ private:
auto &sub = last.first;
auto sub_is_literal = last.second;
if (!sub_is_literal) {
std::string & sub_id = sub_rule_ids[sub];
if (sub_id.empty()) {
sub_id = _add_rule(name + "-" + std::to_string(sub_rule_ids.size()), sub);
if (min_times == 0 && max_times == std::numeric_limits<int>::max()) {
sub += "*";
} else if (min_times == 0 && max_times == 1) {
sub += "?";
} else if (min_times == 1 && max_times == std::numeric_limits<int>::max()) {
sub += "+";
} else {
if (!sub_is_literal) {
std::string & sub_id = sub_rule_ids[sub];
if (sub_id.empty()) {
sub_id = _add_rule(name + "-" + std::to_string(sub_rule_ids.size()), sub);
}
sub = sub_id;
}
sub = sub_id;
std::string result;
if (sub_is_literal && min_times > 0) {
result = "\"" + repeat(sub.substr(1, sub.length() - 2), min_times) + "\"";
} else {
for (int j = 0; j < min_times; j++) {
if (j > 0) {
result += " ";
}
result += sub;
}
}
if (min_times > 0 && min_times < max_times) {
result += " ";
}
if (max_times == std::numeric_limits<int>::max()) {
result += sub + "*";
} else {
for (int j = min_times; j < max_times; j++) {
if (j > min_times) {
result += " ";
}
result += sub + "?";
}
}
seq.back().first = result;
seq.back().second = false;
}
seq.back().first = build_repetition(
sub_is_literal ? "\"" + sub + "\"" : sub,
min_times,
max_times,
""
);
seq.back().second = false;
} else {
std::string literal;
auto is_non_literal = [&](char c) {
@@ -605,7 +377,7 @@ private:
}
}
if (!literal.empty()) {
seq.emplace_back(literal, true);
seq.push_back(std::make_pair(literal, true));
}
}
}
@@ -614,75 +386,6 @@ private:
return _add_rule(name, "\"\\\"\" " + to_rule(transform()) + " \"\\\"\" space");
}
/*
Returns a rule that matches a JSON string that is none of the provided strings
not_strings({"a"})
-> ["] ( [a] char+ | [^"a] char* )? ["] space
not_strings({"and", "also"})
-> ["] ( [a] ([l] ([s] ([o] char+ | [^"o] char*) | [^"s] char*) | [n] ([d] char+ | [^"d] char*) | [^"ln] char*) | [^"a] char* )? ["] space
*/
std::string _not_strings(const std::vector<std::string> & strings) {
struct TrieNode {
std::map<char, TrieNode> children;
bool is_end_of_string;
TrieNode() : is_end_of_string(false) {}
void insert(const std::string & string) {
auto node = this;
for (char c : string) {
node = &node->children[c];
}
node->is_end_of_string = true;
}
};
TrieNode trie;
for (const auto & s : strings) {
trie.insert(s);
}
std::string char_rule = _add_primitive("char", PRIMITIVE_RULES.at("char"));
std::ostringstream out;
out << "[\"] ( ";
std::function<void(const TrieNode &)> visit = [&](const TrieNode & node) {
std::ostringstream rejects;
auto first = true;
for (const auto & kv : node.children) {
rejects << kv.first;
if (first) {
first = false;
} else {
out << " | ";
}
out << "[" << kv.first << "]";
if (!kv.second.children.empty()) {
out << " (";
visit(kv.second);
out << ")";
} else if (kv.second.is_end_of_string) {
out << " " << char_rule << "+";
}
}
if (!node.children.empty()) {
if (!first) {
out << " | ";
}
out << "[^\"" << rejects.str() << "] " << char_rule << "*";
}
};
visit(trie);
out << " )";
if (!trie.is_end_of_string) {
out << "?";
}
out << " [\"] space";
return out.str();
}
std::string _resolve_ref(const std::string & ref) {
std::string ref_name = ref.substr(ref.find_last_of('/') + 1);
if (_rules.find(ref_name) == _rules.end() && _refs_being_resolved.find(ref) == _refs_being_resolved.end()) {
@@ -703,7 +406,6 @@ private:
std::vector<std::string> required_props;
std::vector<std::string> optional_props;
std::unordered_map<std::string, std::string> prop_kv_rule_names;
std::vector<std::string> prop_names;
for (const auto & kv : properties) {
const auto &prop_name = kv.first;
const auto &prop_schema = kv.second;
@@ -718,18 +420,11 @@ private:
} else {
optional_props.push_back(prop_name);
}
prop_names.push_back(prop_name);
}
if ((additional_properties.is_boolean() && additional_properties.get<bool>()) || additional_properties.is_object()) {
if (additional_properties.is_object() || (additional_properties.is_boolean() && additional_properties.get<bool>())) {
std::string sub_name = name + (name.empty() ? "" : "-") + "additional";
std::string value_rule =
additional_properties.is_object() ? visit(additional_properties, sub_name + "-value")
: _add_primitive("value", PRIMITIVE_RULES.at("value"));
auto key_rule =
prop_names.empty() ? _add_primitive("string", PRIMITIVE_RULES.at("string"))
: _add_rule(sub_name + "-k", _not_strings(prop_names));
std::string kv_rule = _add_rule(sub_name + "-kv", key_rule + " \":\" space " + value_rule);
std::string value_rule = visit(additional_properties.is_object() ? additional_properties : json::object(), sub_name + "-value");
std::string kv_rule = _add_rule(sub_name + "-kv", _add_rule("string", PRIMITIVE_RULES.at("string")) + " \":\" space " + value_rule);
prop_kv_rule_names["*"] = kv_rule;
optional_props.push_back("*");
}
@@ -755,11 +450,15 @@ private:
}
std::string k = ks[0];
std::string kv_rule_name = prop_kv_rule_names[k];
std::string comma_ref = "( \",\" space " + kv_rule_name + " )";
if (first_is_optional) {
res = comma_ref + (k == "*" ? "*" : "?");
if (k == "*") {
res = _add_rule(
name + (name.empty() ? "" : "-") + "additional-kvs",
kv_rule_name + " ( \",\" space " + kv_rule_name + " )*"
);
} else if (first_is_optional) {
res = "( \",\" space " + kv_rule_name + " )?";
} else {
res = kv_rule_name + (k == "*" ? " " + comma_ref + "*" : "");
res = kv_rule_name;
}
if (ks.size() > 1) {
res += " " + _add_rule(
@@ -787,25 +486,6 @@ private:
return rule;
}
std::string _add_primitive(const std::string & name, const BuiltinRule & rule) {
auto n = _add_rule(name, rule.content);
for (const auto & dep : rule.deps) {
BuiltinRule dep_rule;
auto it = PRIMITIVE_RULES.find(dep);
if (it == PRIMITIVE_RULES.end()) {
it = STRING_FORMAT_RULES.find(dep);
if (it == STRING_FORMAT_RULES.end()) {
_errors.push_back("Rule " + dep + " not known");
continue;
}
}
if (_rules.find(dep) == _rules.end()) {
_add_primitive(dep, it->second);
}
}
return n;
}
public:
SchemaConverter(
const std::function<json(const std::string &)> & fetch_json,
@@ -893,19 +573,17 @@ public:
} else if (schema_type.is_array()) {
std::vector<json> schema_types;
for (const auto & t : schema_type) {
json schema_copy(schema);
schema_copy["type"] = t;
schema_types.push_back(schema_copy);
schema_types.push_back({{"type", t}});
}
return _add_rule(rule_name, _generate_union_rule(name, schema_types));
} else if (schema.contains("const")) {
return _add_rule(rule_name, _generate_constant_rule(schema["const"]) + " space");
return _add_rule(rule_name, _generate_constant_rule(schema["const"]));
} else if (schema.contains("enum")) {
std::vector<std::string> enum_values;
for (const auto & v : schema["enum"]) {
enum_values.push_back(_generate_constant_rule(v));
}
return _add_rule(rule_name, "(" + join(enum_values.begin(), enum_values.end(), " | ") + ") space");
return _add_rule(rule_name, join(enum_values.begin(), enum_values.end(), " | "));
} else if ((schema_type.is_null() || schema_type == "object")
&& (schema.contains("properties") ||
(schema.contains("additionalProperties") && schema["additionalProperties"] != true))) {
@@ -969,51 +647,49 @@ public:
return _add_rule(rule_name, rule);
} else {
std::string item_rule_name = visit(items, name + (name.empty() ? "" : "-") + "item");
std::string list_item_operator = "( \",\" space " + item_rule_name + " )";
std::string successive_items;
int min_items = schema.contains("minItems") ? schema["minItems"].get<int>() : 0;
json max_items_json = schema.contains("maxItems") ? schema["maxItems"] : json();
int max_items = max_items_json.is_number_integer() ? max_items_json.get<int>() : std::numeric_limits<int>::max();
return _add_rule(rule_name, "\"[\" space " + build_repetition(item_rule_name, min_items, max_items, "\",\" space") + " \"]\" space");
int max_items = max_items_json.is_number_integer() ? max_items_json.get<int>() : -1;
if (min_items > 0) {
successive_items += repeat(list_item_operator, min_items - 1);
min_items--;
}
if (max_items >= 0 && max_items > min_items) {
successive_items += repeat(list_item_operator + "?", max_items - min_items - 1);
} else {
successive_items += list_item_operator + "*";
}
std::string rule;
if (min_items == 0) {
rule = "\"[\" space ( " + item_rule_name + " " + successive_items + " )? \"]\" space";
} else {
rule = "\"[\" space " + item_rule_name + " " + successive_items + " \"]\" space";
}
return _add_rule(rule_name, rule);
}
} else if ((schema_type.is_null() || schema_type == "string") && schema.contains("pattern")) {
return _visit_pattern(schema["pattern"], rule_name);
} else if ((schema_type.is_null() || schema_type == "string") && std::regex_match(schema_format, std::regex("^uuid[1-5]?$"))) {
return _add_primitive(rule_name == "root" ? "root" : schema_format, PRIMITIVE_RULES.at("uuid"));
} else if ((schema_type.is_null() || schema_type == "string") && STRING_FORMAT_RULES.find(schema_format + "-string") != STRING_FORMAT_RULES.end()) {
auto prim_name = schema_format + "-string";
return _add_rule(rule_name, _add_primitive(prim_name, STRING_FORMAT_RULES.at(prim_name)));
} else if (schema_type == "string" && (schema.contains("minLength") || schema.contains("maxLength"))) {
std::string char_rule = _add_primitive("char", PRIMITIVE_RULES.at("char"));
int min_len = schema.contains("minLength") ? schema["minLength"].get<int>() : 0;
int max_len = schema.contains("maxLength") ? schema["maxLength"].get<int>() : std::numeric_limits<int>::max();
return _add_rule(rule_name, "\"\\\"\" " + build_repetition(char_rule, min_len, max_len) + " \"\\\"\" space");
} else if (schema_type == "integer" && (schema.contains("minimum") || schema.contains("exclusiveMinimum") || schema.contains("maximum") || schema.contains("exclusiveMaximum"))) {
int min_value = std::numeric_limits<int>::min();
int max_value = std::numeric_limits<int>::max();
if (schema.contains("minimum")) {
min_value = schema["minimum"].get<int>();
} else if (schema.contains("exclusiveMinimum")) {
min_value = schema["exclusiveMinimum"].get<int>() + 1;
return _add_rule(rule_name == "root" ? "root" : schema_format, PRIMITIVE_RULES.at("uuid"));
} else if ((schema_type.is_null() || schema_type == "string") && DATE_RULES.find(schema_format) != DATE_RULES.end()) {
for (const auto & kv : DATE_RULES) {
_add_rule(kv.first, kv.second);
}
if (schema.contains("maximum")) {
max_value = schema["maximum"].get<int>();
} else if (schema.contains("exclusiveMaximum")) {
max_value = schema["exclusiveMaximum"].get<int>() - 1;
}
std::stringstream out;
out << "(";
_build_min_max_int(min_value, max_value, out);
out << ") space";
return _add_rule(rule_name, out.str());
return schema_format + "-string";
} else if (schema.empty() || schema_type == "object") {
return _add_rule(rule_name, _add_primitive("object", PRIMITIVE_RULES.at("object")));
for (const auto & n : OBJECT_RULE_NAMES) {
_add_rule(n, PRIMITIVE_RULES.at(n));
}
return _add_rule(rule_name, "object");
} else {
if (!schema_type.is_string() || PRIMITIVE_RULES.find(schema_type.get<std::string>()) == PRIMITIVE_RULES.end()) {
_errors.push_back("Unrecognized schema: " + schema.dump());
return "";
}
// TODO: support minimum, maximum, exclusiveMinimum, exclusiveMaximum at least for zero
return _add_primitive(rule_name == "root" ? "root" : schema_type.get<std::string>(), PRIMITIVE_RULES.at(schema_type.get<std::string>()));
return _add_rule(rule_name == "root" ? "root" : schema_type.get<std::string>(), PRIMITIVE_RULES.at(schema_type.get<std::string>()));
}
}

View File

@@ -1,8 +1,4 @@
#pragma once
#include "ggml.h"
// Change JSON_ASSERT from assert() to GGML_ASSERT:
#define JSON_ASSERT GGML_ASSERT
#include "json.hpp"
std::string json_schema_to_grammar(const nlohmann::ordered_json& schema);

View File

@@ -1,401 +0,0 @@
#include "log.h"
#include <condition_variable>
#include <cstdarg>
#include <cstdio>
#include <mutex>
#include <sstream>
#include <thread>
#include <vector>
int common_log_verbosity_thold = LOG_DEFAULT_LLAMA;
void common_log_set_verbosity_thold(int verbosity) {
common_log_verbosity_thold = verbosity;
}
#define LOG_COL_DEFAULT "\033[0m"
#define LOG_COL_BOLD "\033[1m"
#define LOG_COL_RED "\033[31m"
#define LOG_COL_GREEN "\033[32m"
#define LOG_COL_YELLOW "\033[33m"
#define LOG_COL_BLUE "\033[34m"
#define LOG_COL_MAGENTA "\033[35m"
#define LOG_COL_CYAN "\033[36m"
#define LOG_COL_WHITE "\033[37m"
static int64_t t_us() {
return std::chrono::duration_cast<std::chrono::microseconds>(std::chrono::system_clock::now().time_since_epoch()).count();
}
// colors
enum common_log_col : int {
COMMON_LOG_COL_DEFAULT = 0,
COMMON_LOG_COL_BOLD,
COMMON_LOG_COL_RED,
COMMON_LOG_COL_GREEN,
COMMON_LOG_COL_YELLOW,
COMMON_LOG_COL_BLUE,
COMMON_LOG_COL_MAGENTA,
COMMON_LOG_COL_CYAN,
COMMON_LOG_COL_WHITE,
};
// disable colors by default
static std::vector<const char *> g_col = {
"",
"",
"",
"",
"",
"",
"",
"",
"",
};
struct common_log_entry {
enum ggml_log_level level;
bool prefix;
int64_t timestamp;
std::vector<char> msg;
// signals the worker thread to stop
bool is_end;
void print(FILE * file = nullptr) const {
FILE * fcur = file;
if (!fcur) {
// stderr displays DBG messages only when their verbosity level is not higher than the threshold
// these messages will still be logged to a file
if (level == GGML_LOG_LEVEL_DEBUG && common_log_verbosity_thold < LOG_DEFAULT_DEBUG) {
return;
}
fcur = stdout;
if (level != GGML_LOG_LEVEL_NONE) {
fcur = stderr;
}
}
if (level != GGML_LOG_LEVEL_NONE && level != GGML_LOG_LEVEL_CONT && prefix) {
if (timestamp) {
// [M.s.ms.us]
fprintf(fcur, "%s%d.%02d.%03d.%03d%s ",
g_col[COMMON_LOG_COL_BLUE],
(int) (timestamp / 1000000 / 60),
(int) (timestamp / 1000000 % 60),
(int) (timestamp / 1000 % 1000),
(int) (timestamp % 1000),
g_col[COMMON_LOG_COL_DEFAULT]);
}
switch (level) {
case GGML_LOG_LEVEL_INFO: fprintf(fcur, "%sI %s", g_col[COMMON_LOG_COL_GREEN], g_col[COMMON_LOG_COL_DEFAULT]); break;
case GGML_LOG_LEVEL_WARN: fprintf(fcur, "%sW %s", g_col[COMMON_LOG_COL_MAGENTA], "" ); break;
case GGML_LOG_LEVEL_ERROR: fprintf(fcur, "%sE %s", g_col[COMMON_LOG_COL_RED], "" ); break;
case GGML_LOG_LEVEL_DEBUG: fprintf(fcur, "%sD %s", g_col[COMMON_LOG_COL_YELLOW], "" ); break;
default:
break;
}
}
fprintf(fcur, "%s", msg.data());
if (level == GGML_LOG_LEVEL_WARN || level == GGML_LOG_LEVEL_ERROR || level == GGML_LOG_LEVEL_DEBUG) {
fprintf(fcur, "%s", g_col[COMMON_LOG_COL_DEFAULT]);
}
fflush(fcur);
}
};
struct common_log {
// default capacity - will be expanded if needed
common_log() : common_log(256) {}
common_log(size_t capacity) {
file = nullptr;
prefix = false;
timestamps = false;
running = false;
t_start = t_us();
// initial message size - will be expanded if longer messages arrive
entries.resize(capacity);
for (auto & entry : entries) {
entry.msg.resize(256);
}
head = 0;
tail = 0;
resume();
}
~common_log() {
pause();
if (file) {
fclose(file);
}
}
private:
std::mutex mtx;
std::thread thrd;
std::condition_variable cv;
FILE * file;
bool prefix;
bool timestamps;
bool running;
int64_t t_start;
// ring buffer of entries
std::vector<common_log_entry> entries;
size_t head;
size_t tail;
// worker thread copies into this
common_log_entry cur;
public:
void add(enum ggml_log_level level, const char * fmt, va_list args) {
std::lock_guard<std::mutex> lock(mtx);
if (!running) {
// discard messages while the worker thread is paused
return;
}
auto & entry = entries[tail];
{
// cannot use args twice, so make a copy in case we need to expand the buffer
va_list args_copy;
va_copy(args_copy, args);
#if 1
const size_t n = vsnprintf(entry.msg.data(), entry.msg.size(), fmt, args);
if (n >= entry.msg.size()) {
entry.msg.resize(n + 1);
vsnprintf(entry.msg.data(), entry.msg.size(), fmt, args_copy);
}
#else
// hack for bolding arguments
std::stringstream ss;
for (int i = 0; fmt[i] != 0; i++) {
if (fmt[i] == '%') {
ss << LOG_COL_BOLD;
while (fmt[i] != ' ' && fmt[i] != ')' && fmt[i] != ']' && fmt[i] != 0) ss << fmt[i++];
ss << LOG_COL_DEFAULT;
if (fmt[i] == 0) break;
}
ss << fmt[i];
}
const size_t n = vsnprintf(entry.msg.data(), entry.msg.size(), ss.str().c_str(), args);
if (n >= entry.msg.size()) {
entry.msg.resize(n + 1);
vsnprintf(entry.msg.data(), entry.msg.size(), ss.str().c_str(), args_copy);
}
#endif
}
entry.level = level;
entry.prefix = prefix;
entry.timestamp = 0;
if (timestamps) {
entry.timestamp = t_us() - t_start;
}
entry.is_end = false;
tail = (tail + 1) % entries.size();
if (tail == head) {
// expand the buffer
std::vector<common_log_entry> new_entries(2*entries.size());
size_t new_tail = 0;
do {
new_entries[new_tail] = std::move(entries[head]);
head = (head + 1) % entries.size();
new_tail = (new_tail + 1);
} while (head != tail);
head = 0;
tail = new_tail;
for (size_t i = tail; i < new_entries.size(); i++) {
new_entries[i].msg.resize(256);
}
entries = std::move(new_entries);
}
cv.notify_one();
}
void resume() {
std::lock_guard<std::mutex> lock(mtx);
if (running) {
return;
}
running = true;
thrd = std::thread([this]() {
while (true) {
{
std::unique_lock<std::mutex> lock(mtx);
cv.wait(lock, [this]() { return head != tail; });
cur = entries[head];
head = (head + 1) % entries.size();
}
if (cur.is_end) {
break;
}
cur.print(); // stdout and stderr
if (file) {
cur.print(file);
}
}
});
}
void pause() {
{
std::lock_guard<std::mutex> lock(mtx);
if (!running) {
return;
}
running = false;
// push an entry to signal the worker thread to stop
{
auto & entry = entries[tail];
entry.is_end = true;
tail = (tail + 1) % entries.size();
}
cv.notify_one();
}
thrd.join();
}
void set_file(const char * path) {
pause();
if (file) {
fclose(file);
}
if (path) {
file = fopen(path, "w");
} else {
file = nullptr;
}
resume();
}
void set_colors(bool colors) {
pause();
if (colors) {
g_col[COMMON_LOG_COL_DEFAULT] = LOG_COL_DEFAULT;
g_col[COMMON_LOG_COL_BOLD] = LOG_COL_BOLD;
g_col[COMMON_LOG_COL_RED] = LOG_COL_RED;
g_col[COMMON_LOG_COL_GREEN] = LOG_COL_GREEN;
g_col[COMMON_LOG_COL_YELLOW] = LOG_COL_YELLOW;
g_col[COMMON_LOG_COL_BLUE] = LOG_COL_BLUE;
g_col[COMMON_LOG_COL_MAGENTA] = LOG_COL_MAGENTA;
g_col[COMMON_LOG_COL_CYAN] = LOG_COL_CYAN;
g_col[COMMON_LOG_COL_WHITE] = LOG_COL_WHITE;
} else {
for (size_t i = 0; i < g_col.size(); i++) {
g_col[i] = "";
}
}
resume();
}
void set_prefix(bool prefix) {
std::lock_guard<std::mutex> lock(mtx);
this->prefix = prefix;
}
void set_timestamps(bool timestamps) {
std::lock_guard<std::mutex> lock(mtx);
this->timestamps = timestamps;
}
};
//
// public API
//
struct common_log * common_log_init() {
return new common_log;
}
struct common_log * common_log_main() {
static struct common_log log;
return &log;
}
void common_log_pause(struct common_log * log) {
log->pause();
}
void common_log_resume(struct common_log * log) {
log->resume();
}
void common_log_free(struct common_log * log) {
delete log;
}
void common_log_add(struct common_log * log, enum ggml_log_level level, const char * fmt, ...) {
va_list args;
va_start(args, fmt);
log->add(level, fmt, args);
va_end(args);
}
void common_log_set_file(struct common_log * log, const char * file) {
log->set_file(file);
}
void common_log_set_colors(struct common_log * log, bool colors) {
log->set_colors(colors);
}
void common_log_set_prefix(struct common_log * log, bool prefix) {
log->set_prefix(prefix);
}
void common_log_set_timestamps(struct common_log * log, bool timestamps) {
log->set_timestamps(timestamps);
}

View File

@@ -1,92 +1,724 @@
#pragma once
#include "ggml.h" // for ggml_log_level
#include <chrono>
#include <cstring>
#include <sstream>
#include <iostream>
#include <thread>
#include <vector>
#include <algorithm>
#include <cinttypes>
#ifndef __GNUC__
# define LOG_ATTRIBUTE_FORMAT(...)
#elif defined(__MINGW32__)
# define LOG_ATTRIBUTE_FORMAT(...) __attribute__((format(gnu_printf, __VA_ARGS__)))
#else
# define LOG_ATTRIBUTE_FORMAT(...) __attribute__((format(printf, __VA_ARGS__)))
// --------------------------------
//
// Basic usage:
//
// --------
//
// The LOG() and LOG_TEE() macros are ready to go by default
// they do not require any initialization.
//
// LOGLN() and LOG_TEELN() are variants which automatically
// include \n character at the end of the log string.
//
// LOG() behaves exactly like printf, by default writing to a logfile.
// LOG_TEE() additionally, prints to the screen too ( mimics Unix tee command ).
//
// Default logfile is named
// "llama.<threadID>.log"
// Default LOG_TEE() secondary output target is
// stderr
//
// Logs can be dynamically disabled or enabled using functions:
// log_disable()
// and
// log_enable()
//
// A log target can be changed with:
// log_set_target( string )
// creating and opening, or re-opening a file by string filename
// or
// log_set_target( FILE* )
// allowing to point at stderr, stdout, or any valid FILE* file handler.
//
// --------
//
// End of Basic usage.
//
// --------------------------------
// Specifies a log target.
// default uses log_handler() with "llama.log" log file
// this can be changed, by defining LOG_TARGET
// like so:
//
// #define LOG_TARGET (a valid FILE*)
// #include "log.h"
//
// or it can be simply redirected to stdout or stderr
// like so:
//
// #define LOG_TARGET stderr
// #include "log.h"
//
// The log target can also be redirected to a different function
// like so:
//
// #define LOG_TARGET log_handler_different()
// #include "log.h"
//
// FILE* log_handler_different()
// {
// return stderr;
// }
//
// or:
//
// #define LOG_TARGET log_handler_another_one("somelog.log")
// #include "log.h"
//
// FILE* log_handler_another_one(char*filename)
// {
// static FILE* logfile = nullptr;
// (...)
// if( !logfile )
// {
// fopen(...)
// }
// (...)
// return logfile
// }
//
#ifndef LOG_TARGET
#define LOG_TARGET log_handler()
#endif
#define LOG_DEFAULT_DEBUG 1
#define LOG_DEFAULT_LLAMA 0
#ifndef LOG_TEE_TARGET
#define LOG_TEE_TARGET stderr
#endif
// needed by the LOG_TMPL macro to avoid computing log arguments if the verbosity lower
// set via common_log_set_verbosity()
extern int common_log_verbosity_thold;
// Utility for synchronizing log configuration state
// since std::optional was introduced only in c++17
enum LogTriState
{
LogTriStateSame,
LogTriStateFalse,
LogTriStateTrue
};
void common_log_set_verbosity_thold(int verbosity); // not thread-safe
// Utility to obtain "pid" like unique process id and use it when creating log files.
inline std::string log_get_pid()
{
static std::string pid;
if (pid.empty())
{
// std::this_thread::get_id() is the most portable way of obtaining a "process id"
// it's not the same as "pid" but is unique enough to solve multiple instances
// trying to write to the same log.
std::stringstream ss;
ss << std::this_thread::get_id();
pid = ss.str();
}
// the common_log uses an internal worker thread to print/write log messages
// when the worker thread is paused, incoming log messages are discarded
struct common_log;
return pid;
}
struct common_log * common_log_init();
struct common_log * common_log_main(); // singleton, automatically destroys itself on exit
void common_log_pause (struct common_log * log); // pause the worker thread, not thread-safe
void common_log_resume(struct common_log * log); // resume the worker thread, not thread-safe
void common_log_free (struct common_log * log);
// Utility function for generating log file names with unique id based on thread id.
// invocation with log_filename_generator( "llama", "log" ) creates a string "llama.<number>.log"
// where the number is a runtime id of the current thread.
LOG_ATTRIBUTE_FORMAT(3, 4)
void common_log_add(struct common_log * log, enum ggml_log_level level, const char * fmt, ...);
#define log_filename_generator(log_file_basename, log_file_extension) log_filename_generator_impl(LogTriStateSame, log_file_basename, log_file_extension)
// defaults: file = NULL, colors = false, prefix = false, timestamps = false
//
// regular log output:
//
// ggml_backend_metal_log_allocated_size: allocated buffer, size = 6695.84 MiB, ( 6695.91 / 21845.34)
// llm_load_tensors: ggml ctx size = 0.27 MiB
// llm_load_tensors: offloading 32 repeating layers to GPU
// llm_load_tensors: offloading non-repeating layers to GPU
//
// with prefix = true, timestamps = true, the log output will look like this:
//
// 0.00.035.060 D ggml_backend_metal_log_allocated_size: allocated buffer, size = 6695.84 MiB, ( 6695.91 / 21845.34)
// 0.00.035.064 I llm_load_tensors: ggml ctx size = 0.27 MiB
// 0.00.090.578 I llm_load_tensors: offloading 32 repeating layers to GPU
// 0.00.090.579 I llm_load_tensors: offloading non-repeating layers to GPU
//
// I - info (stdout, V = 0)
// W - warning (stderr, V = 0)
// E - error (stderr, V = 0)
// D - debug (stderr, V = LOG_DEFAULT_DEBUG)
//
// INTERNAL, DO NOT USE
inline std::string log_filename_generator_impl(LogTriState multilog, const std::string & log_file_basename, const std::string & log_file_extension)
{
static bool _multilog = false;
void common_log_set_file (struct common_log * log, const char * file); // not thread-safe
void common_log_set_colors (struct common_log * log, bool colors); // not thread-safe
void common_log_set_prefix (struct common_log * log, bool prefix); // whether to output prefix to each log
void common_log_set_timestamps(struct common_log * log, bool timestamps); // whether to output timestamps in the prefix
if (multilog != LogTriStateSame)
{
_multilog = multilog == LogTriStateTrue;
}
// helper macros for logging
// use these to avoid computing log arguments if the verbosity of the log is higher than the threshold
//
// for example:
//
// LOG_DBG("this is a debug message: %d\n", expensive_function());
//
// this will avoid calling expensive_function() if LOG_DEFAULT_DEBUG > common_log_verbosity_thold
//
std::stringstream buf;
#define LOG_TMPL(level, verbosity, ...) \
do { \
if ((verbosity) <= common_log_verbosity_thold) { \
common_log_add(common_log_main(), (level), __VA_ARGS__); \
} \
buf << log_file_basename;
if (_multilog)
{
buf << ".";
buf << log_get_pid();
}
buf << ".";
buf << log_file_extension;
return buf.str();
}
#ifndef LOG_DEFAULT_FILE_NAME
#define LOG_DEFAULT_FILE_NAME log_filename_generator("llama", "log")
#endif
// Utility for turning #define values into string literals
// so we can have a define for stderr and
// we can print "stderr" instead of literal stderr, etc.
#define LOG_STRINGIZE1(s) #s
#define LOG_STRINGIZE(s) LOG_STRINGIZE1(s)
#define LOG_TEE_TARGET_STRING LOG_STRINGIZE(LOG_TEE_TARGET)
// Allows disabling timestamps.
// in order to disable, define LOG_NO_TIMESTAMPS
// like so:
//
// #define LOG_NO_TIMESTAMPS
// #include "log.h"
//
#ifndef LOG_NO_TIMESTAMPS
#ifndef _MSC_VER
#define LOG_TIMESTAMP_FMT "[%" PRIu64 "] "
#define LOG_TIMESTAMP_VAL , (std::chrono::duration_cast<std::chrono::duration<std::uint64_t>>(std::chrono::system_clock::now().time_since_epoch())).count()
#else
#define LOG_TIMESTAMP_FMT "[%" PRIu64 "] "
#define LOG_TIMESTAMP_VAL , (std::chrono::duration_cast<std::chrono::duration<std::uint64_t>>(std::chrono::system_clock::now().time_since_epoch())).count()
#endif
#else
#define LOG_TIMESTAMP_FMT "%s"
#define LOG_TIMESTAMP_VAL ,""
#endif
#ifdef LOG_TEE_TIMESTAMPS
#ifndef _MSC_VER
#define LOG_TEE_TIMESTAMP_FMT "[%" PRIu64 "] "
#define LOG_TEE_TIMESTAMP_VAL , (std::chrono::duration_cast<std::chrono::duration<std::uint64_t>>(std::chrono::system_clock::now().time_since_epoch())).count()
#else
#define LOG_TEE_TIMESTAMP_FMT "[%" PRIu64 "] "
#define LOG_TEE_TIMESTAMP_VAL , (std::chrono::duration_cast<std::chrono::duration<std::uint64_t>>(std::chrono::system_clock::now().time_since_epoch())).count()
#endif
#else
#define LOG_TEE_TIMESTAMP_FMT "%s"
#define LOG_TEE_TIMESTAMP_VAL ,""
#endif
// Allows disabling file/line/function prefix
// in order to disable, define LOG_NO_FILE_LINE_FUNCTION
// like so:
//
// #define LOG_NO_FILE_LINE_FUNCTION
// #include "log.h"
//
#ifndef LOG_NO_FILE_LINE_FUNCTION
#ifndef _MSC_VER
#define LOG_FLF_FMT "[%24s:%5d][%24s] "
#define LOG_FLF_VAL , __FILE__, __LINE__, __FUNCTION__
#else
#define LOG_FLF_FMT "[%24s:%5ld][%24s] "
#define LOG_FLF_VAL , __FILE__, __LINE__, __FUNCTION__
#endif
#else
#define LOG_FLF_FMT "%s"
#define LOG_FLF_VAL ,""
#endif
#ifdef LOG_TEE_FILE_LINE_FUNCTION
#ifndef _MSC_VER
#define LOG_TEE_FLF_FMT "[%24s:%5d][%24s] "
#define LOG_TEE_FLF_VAL , __FILE__, __LINE__, __FUNCTION__
#else
#define LOG_TEE_FLF_FMT "[%24s:%5ld][%24s] "
#define LOG_TEE_FLF_VAL , __FILE__, __LINE__, __FUNCTION__
#endif
#else
#define LOG_TEE_FLF_FMT "%s"
#define LOG_TEE_FLF_VAL ,""
#endif
// INTERNAL, DO NOT USE
// USE LOG() INSTEAD
//
#if !defined(_MSC_VER) or defined(__INTEL_LLVM_COMPILER)
#define LOG_IMPL(str, ...) \
do { \
if (LOG_TARGET != nullptr) \
{ \
fprintf(LOG_TARGET, LOG_TIMESTAMP_FMT LOG_FLF_FMT str "%s" LOG_TIMESTAMP_VAL LOG_FLF_VAL, __VA_ARGS__); \
fflush(LOG_TARGET); \
} \
} while (0)
#else
#define LOG_IMPL(str, ...) \
do { \
if (LOG_TARGET != nullptr) \
{ \
fprintf(LOG_TARGET, LOG_TIMESTAMP_FMT LOG_FLF_FMT str "%s" LOG_TIMESTAMP_VAL LOG_FLF_VAL "", ##__VA_ARGS__); \
fflush(LOG_TARGET); \
} \
} while (0)
#endif
#define LOG(...) LOG_TMPL(GGML_LOG_LEVEL_NONE, 0, __VA_ARGS__)
#define LOGV(verbosity, ...) LOG_TMPL(GGML_LOG_LEVEL_NONE, verbosity, __VA_ARGS__)
// INTERNAL, DO NOT USE
// USE LOG_TEE() INSTEAD
//
#if !defined(_MSC_VER) or defined(__INTEL_LLVM_COMPILER)
#define LOG_TEE_IMPL(str, ...) \
do { \
if (LOG_TARGET != nullptr) \
{ \
fprintf(LOG_TARGET, LOG_TIMESTAMP_FMT LOG_FLF_FMT str "%s" LOG_TIMESTAMP_VAL LOG_FLF_VAL, __VA_ARGS__); \
fflush(LOG_TARGET); \
} \
if (LOG_TARGET != nullptr && LOG_TARGET != stdout && LOG_TARGET != stderr && LOG_TEE_TARGET != nullptr) \
{ \
fprintf(LOG_TEE_TARGET, LOG_TEE_TIMESTAMP_FMT LOG_TEE_FLF_FMT str "%s" LOG_TEE_TIMESTAMP_VAL LOG_TEE_FLF_VAL, __VA_ARGS__); \
fflush(LOG_TEE_TARGET); \
} \
} while (0)
#else
#define LOG_TEE_IMPL(str, ...) \
do { \
if (LOG_TARGET != nullptr) \
{ \
fprintf(LOG_TARGET, LOG_TIMESTAMP_FMT LOG_FLF_FMT str "%s" LOG_TIMESTAMP_VAL LOG_FLF_VAL "", ##__VA_ARGS__); \
fflush(LOG_TARGET); \
} \
if (LOG_TARGET != nullptr && LOG_TARGET != stdout && LOG_TARGET != stderr && LOG_TEE_TARGET != nullptr) \
{ \
fprintf(LOG_TEE_TARGET, LOG_TEE_TIMESTAMP_FMT LOG_TEE_FLF_FMT str "%s" LOG_TEE_TIMESTAMP_VAL LOG_TEE_FLF_VAL "", ##__VA_ARGS__); \
fflush(LOG_TEE_TARGET); \
} \
} while (0)
#endif
#define LOG_INF(...) LOG_TMPL(GGML_LOG_LEVEL_INFO, 0, __VA_ARGS__)
#define LOG_WRN(...) LOG_TMPL(GGML_LOG_LEVEL_WARN, 0, __VA_ARGS__)
#define LOG_ERR(...) LOG_TMPL(GGML_LOG_LEVEL_ERROR, 0, __VA_ARGS__)
#define LOG_DBG(...) LOG_TMPL(GGML_LOG_LEVEL_DEBUG, LOG_DEFAULT_DEBUG, __VA_ARGS__)
#define LOG_CNT(...) LOG_TMPL(GGML_LOG_LEVEL_CONT, 0, __VA_ARGS__)
// The '\0' as a last argument, is a trick to bypass the silly
// "warning: ISO C++11 requires at least one argument for the "..." in a variadic macro"
// so we can have a single macro which can be called just like printf.
#define LOG_INFV(verbosity, ...) LOG_TMPL(GGML_LOG_LEVEL_INFO, verbosity, __VA_ARGS__)
#define LOG_WRNV(verbosity, ...) LOG_TMPL(GGML_LOG_LEVEL_WARN, verbosity, __VA_ARGS__)
#define LOG_ERRV(verbosity, ...) LOG_TMPL(GGML_LOG_LEVEL_ERROR, verbosity, __VA_ARGS__)
#define LOG_DBGV(verbosity, ...) LOG_TMPL(GGML_LOG_LEVEL_DEBUG, verbosity, __VA_ARGS__)
#define LOG_CNTV(verbosity, ...) LOG_TMPL(GGML_LOG_LEVEL_CONT, verbosity, __VA_ARGS__)
// Main LOG macro.
// behaves like printf, and supports arguments the exact same way.
//
#ifndef _MSC_VER
#define LOG(...) LOG_IMPL(__VA_ARGS__, "")
#else
#define LOG(str, ...) LOG_IMPL("%s" str, "", ##__VA_ARGS__, "")
#endif
// Main TEE macro.
// does the same as LOG
// and
// simultaneously writes stderr.
//
// Secondary target can be changed just like LOG_TARGET
// by defining LOG_TEE_TARGET
//
#ifndef _MSC_VER
#define LOG_TEE(...) LOG_TEE_IMPL(__VA_ARGS__, "")
#else
#define LOG_TEE(str, ...) LOG_TEE_IMPL("%s" str, "", ##__VA_ARGS__, "")
#endif
// LOG macro variants with auto endline.
#ifndef _MSC_VER
#define LOGLN(...) LOG_IMPL(__VA_ARGS__, "\n")
#define LOG_TEELN(...) LOG_TEE_IMPL(__VA_ARGS__, "\n")
#else
#define LOGLN(str, ...) LOG_IMPL("%s" str, "", ##__VA_ARGS__, "\n")
#define LOG_TEELN(str, ...) LOG_TEE_IMPL("%s" str, "", ##__VA_ARGS__, "\n")
#endif
// INTERNAL, DO NOT USE
inline FILE *log_handler1_impl(bool change = false, LogTriState append = LogTriStateSame, LogTriState disable = LogTriStateSame, const std::string & filename = LOG_DEFAULT_FILE_NAME, FILE *target = nullptr)
{
static bool _initialized = false;
static bool _append = false;
static bool _disabled = filename.empty() && target == nullptr;
static std::string log_current_filename{filename};
static FILE *log_current_target{target};
static FILE *logfile = nullptr;
if (change)
{
if (append != LogTriStateSame)
{
_append = append == LogTriStateTrue;
return logfile;
}
if (disable == LogTriStateTrue)
{
// Disable primary target
_disabled = true;
}
// If previously disabled, only enable, and keep previous target
else if (disable == LogTriStateFalse)
{
_disabled = false;
}
// Otherwise, process the arguments
else if (log_current_filename != filename || log_current_target != target)
{
_initialized = false;
}
}
if (_disabled)
{
// Log is disabled
return nullptr;
}
if (_initialized)
{
// with fallback in case something went wrong
return logfile ? logfile : stderr;
}
// do the (re)initialization
if (target != nullptr)
{
if (logfile != nullptr && logfile != stdout && logfile != stderr)
{
fclose(logfile);
}
log_current_filename = LOG_DEFAULT_FILE_NAME;
log_current_target = target;
logfile = target;
}
else
{
if (log_current_filename != filename)
{
if (logfile != nullptr && logfile != stdout && logfile != stderr)
{
fclose(logfile);
}
}
logfile = fopen(filename.c_str(), _append ? "a" : "w");
}
if (!logfile)
{
// Verify whether the file was opened, otherwise fallback to stderr
logfile = stderr;
fprintf(stderr, "Failed to open logfile '%s' with error '%s'\n", filename.c_str(), std::strerror(errno));
fflush(stderr);
// At this point we let the init flag be to true below, and let the target fallback to stderr
// otherwise we would repeatedly fopen() which was already unsuccessful
}
_initialized = true;
return logfile ? logfile : stderr;
}
// INTERNAL, DO NOT USE
inline FILE *log_handler2_impl(bool change = false, LogTriState append = LogTriStateSame, LogTriState disable = LogTriStateSame, FILE *target = nullptr, const std::string & filename = LOG_DEFAULT_FILE_NAME)
{
return log_handler1_impl(change, append, disable, filename, target);
}
// Disables logs entirely at runtime.
// Makes LOG() and LOG_TEE() produce no output,
// until enabled back.
#define log_disable() log_disable_impl()
// INTERNAL, DO NOT USE
inline FILE *log_disable_impl()
{
return log_handler1_impl(true, LogTriStateSame, LogTriStateTrue);
}
// Enables logs at runtime.
#define log_enable() log_enable_impl()
// INTERNAL, DO NOT USE
inline FILE *log_enable_impl()
{
return log_handler1_impl(true, LogTriStateSame, LogTriStateFalse);
}
// Sets target fir logs, either by a file name or FILE* pointer (stdout, stderr, or any valid FILE*)
#define log_set_target(target) log_set_target_impl(target)
// INTERNAL, DO NOT USE
inline FILE *log_set_target_impl(const std::string & filename) { return log_handler1_impl(true, LogTriStateSame, LogTriStateSame, filename); }
inline FILE *log_set_target_impl(FILE *target) { return log_handler2_impl(true, LogTriStateSame, LogTriStateSame, target); }
// INTERNAL, DO NOT USE
inline FILE *log_handler() { return log_handler1_impl(); }
// Enable or disable creating separate log files for each run.
// can ONLY be invoked BEFORE first log use.
#define log_multilog(enable) log_filename_generator_impl((enable) ? LogTriStateTrue : LogTriStateFalse, "", "")
// Enable or disable append mode for log file.
// can ONLY be invoked BEFORE first log use.
#define log_append(enable) log_append_impl(enable)
// INTERNAL, DO NOT USE
inline FILE *log_append_impl(bool enable)
{
return log_handler1_impl(true, enable ? LogTriStateTrue : LogTriStateFalse, LogTriStateSame);
}
inline void log_test()
{
log_disable();
LOG("01 Hello World to nobody, because logs are disabled!\n");
log_enable();
LOG("02 Hello World to default output, which is \"%s\" ( Yaaay, arguments! )!\n", LOG_STRINGIZE(LOG_TARGET));
LOG_TEE("03 Hello World to **both** default output and " LOG_TEE_TARGET_STRING "!\n");
log_set_target(stderr);
LOG("04 Hello World to stderr!\n");
LOG_TEE("05 Hello World TEE with double printing to stderr prevented!\n");
log_set_target(LOG_DEFAULT_FILE_NAME);
LOG("06 Hello World to default log file!\n");
log_set_target(stdout);
LOG("07 Hello World to stdout!\n");
log_set_target(LOG_DEFAULT_FILE_NAME);
LOG("08 Hello World to default log file again!\n");
log_disable();
LOG("09 Hello World _1_ into the void!\n");
log_enable();
LOG("10 Hello World back from the void ( you should not see _1_ in the log or the output )!\n");
log_disable();
log_set_target("llama.anotherlog.log");
LOG("11 Hello World _2_ to nobody, new target was selected but logs are still disabled!\n");
log_enable();
LOG("12 Hello World this time in a new file ( you should not see _2_ in the log or the output )?\n");
log_set_target("llama.yetanotherlog.log");
LOG("13 Hello World this time in yet new file?\n");
log_set_target(log_filename_generator("llama_autonamed", "log"));
LOG("14 Hello World in log with generated filename!\n");
#ifdef _MSC_VER
LOG_TEE("15 Hello msvc TEE without arguments\n");
LOG_TEE("16 Hello msvc TEE with (%d)(%s) arguments\n", 1, "test");
LOG_TEELN("17 Hello msvc TEELN without arguments\n");
LOG_TEELN("18 Hello msvc TEELN with (%d)(%s) arguments\n", 1, "test");
LOG("19 Hello msvc LOG without arguments\n");
LOG("20 Hello msvc LOG with (%d)(%s) arguments\n", 1, "test");
LOGLN("21 Hello msvc LOGLN without arguments\n");
LOGLN("22 Hello msvc LOGLN with (%d)(%s) arguments\n", 1, "test");
#endif
}
inline bool log_param_single_parse(const std::string & param)
{
if ( param == "--log-test")
{
log_test();
return true;
}
if ( param == "--log-disable")
{
log_disable();
return true;
}
if ( param == "--log-enable")
{
log_enable();
return true;
}
if (param == "--log-new")
{
log_multilog(true);
return true;
}
if (param == "--log-append")
{
log_append(true);
return true;
}
return false;
}
inline bool log_param_pair_parse(bool check_but_dont_parse, const std::string & param, const std::string & next = std::string())
{
if ( param == "--log-file")
{
if (!check_but_dont_parse)
{
log_set_target(log_filename_generator(next.empty() ? "unnamed" : next, "log"));
}
return true;
}
return false;
}
inline void log_print_usage()
{
printf("log options:\n");
/* format
printf(" -h, --help show this help message and exit\n");*/
/* spacing
printf("__-param----------------Description\n");*/
printf(" --log-test Run simple logging test\n");
printf(" --log-disable Disable trace logs\n");
printf(" --log-enable Enable trace logs\n");
printf(" --log-file Specify a log filename (without extension)\n");
printf(" --log-new Create a separate new log file on start. "
"Each log file will have unique name: \"<name>.<ID>.log\"\n");
printf(" --log-append Don't truncate the old log file.\n");
printf("\n");
}
#define log_dump_cmdline(argc, argv) log_dump_cmdline_impl(argc, argv)
// INTERNAL, DO NOT USE
inline void log_dump_cmdline_impl(int argc, char **argv)
{
std::stringstream buf;
for (int i = 0; i < argc; ++i)
{
if (std::string(argv[i]).find(' ') != std::string::npos)
{
buf << " \"" << argv[i] <<"\"";
}
else
{
buf << " " << argv[i];
}
}
LOGLN("Cmd:%s", buf.str().c_str());
}
#define log_tostr(var) log_var_to_string_impl(var).c_str()
inline std::string log_var_to_string_impl(bool var)
{
return var ? "true" : "false";
}
inline std::string log_var_to_string_impl(std::string var)
{
return var;
}
inline std::string log_var_to_string_impl(const std::vector<int> & var)
{
std::stringstream buf;
buf << "[ ";
bool first = true;
for (auto e : var)
{
if (first)
{
first = false;
}
else
{
buf << ", ";
}
buf << std::to_string(e);
}
buf << " ]";
return buf.str();
}
template <typename C, typename T>
inline std::string LOG_TOKENS_TOSTR_PRETTY(const C & ctx, const T & tokens)
{
std::stringstream buf;
buf << "[ ";
bool first = true;
for (const auto &token : tokens)
{
if (!first) {
buf << ", ";
} else {
first = false;
}
auto detokenized = llama_token_to_piece(ctx, token);
detokenized.erase(
std::remove_if(
detokenized.begin(),
detokenized.end(),
[](const unsigned char c) { return !std::isprint(c); }),
detokenized.end());
buf
<< "'" << detokenized << "'"
<< ":" << std::to_string(token);
}
buf << " ]";
return buf.str();
}
template <typename C, typename B>
inline std::string LOG_BATCH_TOSTR_PRETTY(const C & ctx, const B & batch)
{
std::stringstream buf;
buf << "[ ";
bool first = true;
for (int i = 0; i < batch.n_tokens; ++i)
{
if (!first) {
buf << ", ";
} else {
first = false;
}
auto detokenized = llama_token_to_piece(ctx, batch.token[i]);
detokenized.erase(
std::remove_if(
detokenized.begin(),
detokenized.end(),
[](const unsigned char c) { return !std::isprint(c); }),
detokenized.end());
buf
<< "\n" << std::to_string(i)
<< ":token '" << detokenized << "'"
<< ":pos " << std::to_string(batch.pos[i])
<< ":n_seq_id " << std::to_string(batch.n_seq_id[i])
<< ":seq_id " << std::to_string(batch.seq_id[i][0])
<< ":logits " << std::to_string(batch.logits[i]);
}
buf << " ]";
return buf.str();
}
#ifdef LOG_DISABLE_LOGS
#undef LOG
#define LOG(...) // dummy stub
#undef LOGLN
#define LOGLN(...) // dummy stub
#undef LOG_TEE
#define LOG_TEE(...) fprintf(stderr, __VA_ARGS__) // convert to normal fprintf
#undef LOG_TEELN
#define LOG_TEELN(...) fprintf(stderr, __VA_ARGS__) // convert to normal fprintf
#undef LOG_DISABLE
#define LOG_DISABLE() // dummy stub
#undef LOG_ENABLE
#define LOG_ENABLE() // dummy stub
#undef LOG_ENABLE
#define LOG_ENABLE() // dummy stub
#undef LOG_SET_TARGET
#define LOG_SET_TARGET(...) // dummy stub
#undef LOG_DUMP_CMDLINE
#define LOG_DUMP_CMDLINE(...) // dummy stub
#endif // LOG_DISABLE_LOGS

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