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775 changed files with 68767 additions and 210540 deletions

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@ -12,7 +12,7 @@ FROM ${BASE_CUDA_DEV_CONTAINER} as build
ARG CUDA_DOCKER_ARCH=all
RUN apt-get update && \
apt-get install -y build-essential git cmake libsdl2-dev wget
apt-get install -y build-essential git cmake
WORKDIR /app
@ -21,8 +21,8 @@ COPY . .
# Set nvcc architecture
ENV CUDA_DOCKER_ARCH=${CUDA_DOCKER_ARCH}
# Enable cuBLAS
ENV GGML_CUDA=1
ENV WHISPER_CUBLAS=1
RUN make base.en
RUN make
ENTRYPOINT ["/app/main"]

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@ -1,40 +0,0 @@
ARG UBUNTU_VERSION=22.04
# This needs to generally match the container host's environment.
ARG CUDA_VERSION=12.3.1
# 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 ${BASE_CUDA_DEV_CONTAINER} AS build
WORKDIR /app
# Unless otherwise specified, we make a fat build.
ARG CUDA_DOCKER_ARCH=all
# Set nvcc architecture
ENV CUDA_DOCKER_ARCH=${CUDA_DOCKER_ARCH}
# Enable cuBLAS
ENV GGML_CUDA=1
RUN apt-get update && \
apt-get install -y build-essential libsdl2-dev wget cmake \
&& rm -rf /var/lib/apt/lists/* /var/cache/apt/archives/*
# Ref: https://stackoverflow.com/a/53464012
ENV CUDA_MAIN_VERSION=12.3
ENV LD_LIBRARY_PATH /usr/local/cuda-${CUDA_MAIN_VERSION}/compat:$LD_LIBRARY_PATH
COPY .. .
RUN make base.en
FROM ${BASE_CUDA_RUN_CONTAINER} AS runtime
ENV CUDA_MAIN_VERSION=12.3
ENV LD_LIBRARY_PATH /usr/local/cuda-${CUDA_MAIN_VERSION}/compat:$LD_LIBRARY_PATH
WORKDIR /app
RUN apt-get update && \
apt-get install -y curl ffmpeg wget cmake \
&& rm -rf /var/lib/apt/lists/* /var/cache/apt/archives/*
COPY --from=build /app /app
ENTRYPOINT [ "bash", "-c" ]

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@ -1,19 +0,0 @@
FROM ubuntu:22.04 AS build
WORKDIR /app
RUN apt-get update && \
apt-get install -y build-essential wget cmake \
&& rm -rf /var/lib/apt/lists/* /var/cache/apt/archives/*
COPY .. .
RUN make base.en
FROM ubuntu:22.04 AS runtime
WORKDIR /app
RUN apt-get update && \
apt-get install -y curl ffmpeg libsdl2-dev wget cmake \
&& rm -rf /var/lib/apt/lists/* /var/cache/apt/archives/*
COPY --from=build /app /app
ENTRYPOINT [ "bash", "-c" ]

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@ -13,10 +13,10 @@ jobs:
ubuntu-latest:
runs-on: ubuntu-latest
steps:
- uses: actions/setup-go@v5
- uses: actions/setup-go@v3
with:
go-version: '^1.23'
- uses: actions/checkout@v4
go-version: '^1.19'
- uses: actions/checkout@v1
- run: |
cd bindings/go
make test

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@ -3,53 +3,20 @@ on:
push:
paths:
- bindings/ruby/**
- src/**/*.c
- src/**/*.cpp
- src/**/*.h
- src/**/*.m
- src/**/*.metal
- include/**/*.c
- include/**/*.cpp
- include/**/*.h
- include/**/*.m
- include/**/*.metal
- ggml/**/*.c
- ggml/**/*.cpp
- ggml/**/*.h
- ggml/**/*.m
- ggml/**/*.metal
- scripts/get-flags.mk
- examples/dr_wav.h
- whisper.h
pull_request:
paths:
- bindings/ruby/**
- src/**/*.c
- src/**/*.cpp
- src/**/*.h
- src/**/*.m
- src/**/*.metal
- include/**/*.c
- include/**/*.cpp
- include/**/*.h
- include/**/*.m
- include/**/*.metal
- ggml/**/*.c
- ggml/**/*.cpp
- ggml/**/*.h
- ggml/**/*.m
- ggml/**/*.metal
- scripts/get-flags.mk
- examples/dr_wav.h
- whisper.h
jobs:
ubuntu-latest:
runs-on: ubuntu-latest
defaults:
run:
working-directory: bindings/ruby
steps:
- uses: ruby/setup-ruby@v1
with:
ruby-version: '3.1'
- uses: actions/checkout@v4
- run: rake test
ruby-version: '3.0'
- uses: actions/checkout@v1
- run: |
cd bindings/ruby/ext
ruby extconf.rb && make

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@ -3,7 +3,6 @@ on: [push, pull_request]
env:
ubuntu_image: "ubuntu:22.04"
VCPKG_BINARY_SOURCES: "clear;x-gha,readwrite"
jobs:
ubuntu-latest:
@ -16,56 +15,55 @@ jobs:
steps:
- name: Clone
uses: actions/checkout@v4
uses: actions/checkout@v3
- name: Set up QEMU
uses: docker/setup-qemu-action@v3
uses: docker/setup-qemu-action@v2
- name: Build ${{ matrix.arch }}
run: |
docker run --platform ${{ matrix.arch }} --rm \
-v ${{ github.workspace }}:/workspace \
-w /workspace ${{ env.ubuntu_image }} /bin/sh -c '
set -e
apt update
apt install -y build-essential libsdl2-dev cmake
cmake -B build
cmake --build build --config Release -j $(nproc)'
apt install -y build-essential libsdl2-dev
make
make stream'
macOS-latest:
runs-on: macOS-latest
steps:
- name: Clone
uses: actions/checkout@v4
uses: actions/checkout@v3
- name: Dependencies
run: |
brew update
brew install sdl2 cmake
brew install sdl2
- name: Build
run: |
cmake -B build
cmake --build build --config Release
make
make stream
# freeBSD-latest:
# runs-on: macos-12
#
# steps:
# - name: Clone
# uses: actions/checkout@v4
#
# - name: Build
# uses: cross-platform-actions/action@v0.24.0
# with:
# operating_system: freebsd
# version: '13.3'
# run: |
# sudo pkg update
# sudo pkg install -y gmake sdl2 cmake
# cmake -B build
# cmake --build build --config Release
freeBSD-latest:
runs-on: macos-12
steps:
- name: Clone
uses: actions/checkout@v3
- name: Build
uses: cross-platform-actions/action@v0.15.0
with:
operating_system: freebsd
version: '13.2'
run: |
sudo pkg update
sudo pkg install -y gmake sdl2
gmake
gmake stream
ubuntu-latest-gcc:
runs-on: ubuntu-latest
@ -78,17 +76,16 @@ jobs:
steps:
- name: Clone
uses: actions/checkout@v4
uses: actions/checkout@v3
- name: Set up QEMU
uses: docker/setup-qemu-action@v3
uses: docker/setup-qemu-action@v2
- name: Build ${{ matrix.arch }}
run: |
docker run --platform ${{ matrix.arch }} --rm \
-v ${{ github.workspace }}:/workspace \
-w /workspace ${{ env.ubuntu_image }} /bin/sh -c '
set -e
apt update
apt install -y build-essential cmake libsdl2-dev
cmake . -DWHISPER_SDL2=ON -DCMAKE_BUILD_TYPE=${{ matrix.build }}
@ -102,26 +99,22 @@ jobs:
fail-fast: false
matrix:
build: [Debug, Release]
#arch: [linux/amd64, linux/arm64, linux/arm/v7, linux/ppc64le]
# TODO: arm/v7 disabled due to clang bug
# https://github.com/ggerganov/whisper.cpp/actions/runs/9657764109/job/26637633042?pr=2256#step:4:1990
arch: [linux/amd64, linux/arm64, linux/ppc64le]
arch: [linux/amd64, linux/arm64, linux/arm/v7, linux/ppc64le]
steps:
- name: Clone
uses: actions/checkout@v4
uses: actions/checkout@v3
- name: Set up QEMU
uses: docker/setup-qemu-action@v3
uses: docker/setup-qemu-action@v2
- name: Build ${{ matrix.arch }}
run: |
docker run --platform ${{ matrix.arch }} --rm \
-v ${{ github.workspace }}:/workspace \
-w /workspace ${{ env.ubuntu_image }} /bin/sh -c '
set -e
apt update
apt install -y clang build-essential cmake libsdl2-dev
apt install -y build-essential cmake libsdl2-dev
cmake . -DWHISPER_SDL2=ON -DCMAKE_BUILD_TYPE=${{ matrix.build }} -DCMAKE_CXX_COMPILER=clang++ -DCMAKE_C_COMPILER=clang
make
ctest -L gh --output-on-failure'
@ -137,166 +130,22 @@ jobs:
steps:
- name: Clone
uses: actions/checkout@v4
uses: actions/checkout@v3
- name: Set up QEMU
uses: docker/setup-qemu-action@v3
uses: docker/setup-qemu-action@v2
- name: Build ${{ matrix.arch }}
run: |
docker run --platform ${{ matrix.arch }} --rm \
-v ${{ github.workspace }}:/workspace \
-w /workspace ${{ env.ubuntu_image }} /bin/sh -c '
set -e
apt update
apt install -y build-essential cmake
cmake . -DCMAKE_BUILD_TYPE=Debug -DWHISPER_SANITIZE_${{ matrix.sanitizer }}=ON
make
ctest -L gh --output-on-failure'
ubuntu-22-cmake-sycl:
runs-on: ubuntu-22.04
strategy:
fail-fast: false
matrix:
dwhisper_sycl: [ON]
dcmake_c_compiler: [icx]
dcmake_cxx_compiler: [icpx]
arch: [linux/amd64, linux/arm64, linux/arm/v7, linux/ppc64le]
continue-on-error: true
steps:
- name: Clone
uses: actions/checkout@v4
- name: add oneAPI to apt
shell: bash
run: |
cd /tmp
wget https://apt.repos.intel.com/intel-gpg-keys/GPG-PUB-KEY-INTEL-SW-PRODUCTS.PUB
sudo apt-key add GPG-PUB-KEY-INTEL-SW-PRODUCTS.PUB
rm GPG-PUB-KEY-INTEL-SW-PRODUCTS.PUB
sudo add-apt-repository "deb https://apt.repos.intel.com/oneapi all main"
- name: install oneAPI dpcpp compiler
shell: bash
run: |
sudo apt update
sudo apt install intel-oneapi-compiler-dpcpp-cpp
- name: install oneAPI MKL library
shell: bash
run: |
sudo apt install intel-oneapi-mkl-devel
- name: Clone
id: checkout
uses: actions/checkout@v4
- name: Build
id: cmake_build
run: |
source /opt/intel/oneapi/setvars.sh
mkdir build
cd build
cmake -DGGML_SYCL=ON -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx ..
cmake --build . --config Release -j $(nproc)
ubuntu-22-cmake-sycl-fp16:
runs-on: ubuntu-22.04
strategy:
fail-fast: false
matrix:
dwhisper_sycl: [ON]
dcmake_c_compiler: [icx]
dcmake_cxx_compiler: [icpx]
arch: [linux/amd64, linux/arm64, linux/arm/v7, linux/ppc64le]
continue-on-error: true
steps:
- name: Clone
uses: actions/checkout@v4
- name: add oneAPI to apt
shell: bash
run: |
cd /tmp
wget https://apt.repos.intel.com/intel-gpg-keys/GPG-PUB-KEY-INTEL-SW-PRODUCTS.PUB
sudo apt-key add GPG-PUB-KEY-INTEL-SW-PRODUCTS.PUB
rm GPG-PUB-KEY-INTEL-SW-PRODUCTS.PUB
sudo add-apt-repository "deb https://apt.repos.intel.com/oneapi all main"
- name: install oneAPI dpcpp compiler
shell: bash
run: |
sudo apt update
sudo apt install intel-oneapi-compiler-dpcpp-cpp
- name: install oneAPI MKL library
shell: bash
run: |
sudo apt install intel-oneapi-mkl-devel
- name: Clone
id: checkout
uses: actions/checkout@v4
- name: Build
id: cmake_build
run: |
source /opt/intel/oneapi/setvars.sh
mkdir build
cd build
cmake -DGGML_SYCL_F16=ON -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx ..
cmake --build . --config Release -j $(nproc)
windows-msys2:
runs-on: windows-latest
strategy:
fail-fast: false
matrix:
include:
- { sys: UCRT64, env: ucrt-x86_64, build: Release }
- { sys: CLANG64, env: clang-x86_64, build: Release }
steps:
- name: Clone
uses: actions/checkout@v4
- name: Setup ${{ matrix.sys }}
uses: msys2/setup-msys2@v2
with:
update: true
msystem: ${{matrix.sys}}
install: >-
base-devel
mingw-w64-${{matrix.env}}-toolchain
mingw-w64-${{matrix.env}}-cmake
mingw-w64-${{matrix.env}}-SDL2
mingw-w64-${{matrix.env}}-openblas
- name: Build using CMake
shell: msys2 {0}
run: |
cmake -B build -DWHISPER_SDL2=ON
cmake --build build --config ${{ matrix.build }} -j $(nproc)
- name: Clean after building using CMake
shell: msys2 {0}
run: |
rm -rf build
- name: Build using CMake w/ OpenBLAS
shell: msys2 {0}
run: |
cmake -B build -DGGML_BLAS=ON -DGGML_BLAS_VENDOR=OpenBLAS
cmake --build build --config ${{ matrix.build }} -j $(nproc)
windows:
runs-on: windows-latest
@ -313,14 +162,14 @@ jobs:
s2arc: x64
jnaPath: win32-x86-64
- sdl2: ON
s2ver: 2.28.5
s2ver: 2.26.0
steps:
- name: Clone
uses: actions/checkout@v4
uses: actions/checkout@v3
- name: Add msbuild to PATH
uses: microsoft/setup-msbuild@v2
uses: microsoft/setup-msbuild@v1
- name: Fetch SDL2 and set SDL2_DIR
if: matrix.sdl2 == 'ON'
@ -345,14 +194,14 @@ jobs:
run: copy "$env:SDL2_DIR/../lib/${{ matrix.s2arc }}/SDL2.dll" build/bin/${{ matrix.build }}
- name: Upload dll
uses: actions/upload-artifact@v4
uses: actions/upload-artifact@v3
with:
name: ${{ matrix.jnaPath }}_whisper.dll
path: build/bin/${{ matrix.build }}/whisper.dll
- name: Upload binaries
if: matrix.sdl2 == 'ON'
uses: actions/upload-artifact@v4
uses: actions/upload-artifact@v1
with:
name: whisper-bin-${{ matrix.arch }}
path: build/bin/${{ matrix.build }}
@ -368,31 +217,29 @@ jobs:
sdl2: [ON]
include:
- arch: Win32
obzip: https://github.com/OpenMathLib/OpenBLAS/releases/download/v0.3.24/OpenBLAS-0.3.24-x86.zip
s2arc: x86
- arch: x64
obzip: https://github.com/OpenMathLib/OpenBLAS/releases/download/v0.3.24/OpenBLAS-0.3.24-x64.zip
s2arc: x64
- sdl2: ON
s2ver: 2.28.5
s2ver: 2.26.0
steps:
- name: Clone
uses: actions/checkout@v4
- name: Export GitHub Actions cache environment variables
uses: actions/github-script@v7
with:
script: |
core.exportVariable('ACTIONS_CACHE_URL', process.env.ACTIONS_CACHE_URL || '');
core.exportVariable('ACTIONS_RUNTIME_TOKEN', process.env.ACTIONS_RUNTIME_TOKEN || '');
uses: actions/checkout@v3
- name: Add msbuild to PATH
uses: microsoft/setup-msbuild@v2
uses: microsoft/setup-msbuild@v1
- name: Install OpenBLAS and pkgconfiglite
- name: Fetch OpenBLAS
if: matrix.blas == 'ON'
run: |
vcpkg install --triplet=${{ matrix.s2arc }}-windows openblas
choco install pkgconfiglite
C:/msys64/usr/bin/wget.exe -qO blas.zip ${{ matrix.obzip }}
7z x blas.zip -oblas -y
copy blas/include/cblas.h .
copy blas/include/openblas_config.h .
echo "OPENBLAS_PATH=$env:GITHUB_WORKSPACE/blas" >> $env:GITHUB_ENV
- name: Fetch SDL2 and set SDL2_DIR
if: matrix.sdl2 == 'ON'
@ -404,10 +251,9 @@ jobs:
- name: Configure
run: >
cmake -S . -B ./build -A ${{ matrix.arch }}
-DCMAKE_TOOLCHAIN_FILE="$env:VCPKG_INSTALLATION_ROOT/scripts/buildsystems/vcpkg.cmake"
-DCMAKE_BUILD_TYPE=${{ matrix.build }}
-DGGML_BLAS=${{ matrix.blas }}
-DGGML_BLAS_VENDOR=OpenBLAS
-DWHISPER_OPENBLAS=${{ matrix.blas }}
-DCMAKE_LIBRARY_PATH="$env:OPENBLAS_PATH/lib"
-DWHISPER_SDL2=${{ matrix.sdl2 }}
- name: Build
@ -415,9 +261,9 @@ jobs:
cd ./build
msbuild ALL_BUILD.vcxproj -t:build -p:configuration=${{ matrix.build }} -p:platform=${{ matrix.arch }}
- name: Copy openblas.dll
- name: Copy libopenblas.dll
if: matrix.blas == 'ON'
run: copy "C:/vcpkg/packages/openblas_${{ matrix.s2arc }}-windows/bin/openblas.dll" build/bin/${{ matrix.build }}
run: copy "$env:OPENBLAS_PATH/bin/libopenblas.dll" build/bin/${{ matrix.build }}
- name: Copy SDL2.dll
if: matrix.sdl2 == 'ON'
@ -425,77 +271,65 @@ jobs:
- name: Upload binaries
if: matrix.blas == 'ON' && matrix.sdl2 == 'ON'
uses: actions/upload-artifact@v4
uses: actions/upload-artifact@v1
with:
name: whisper-blas-bin-${{ matrix.arch }}
path: build/bin/${{ matrix.build }}
# TODO: fix and re-enable
# windows-cublas:
# runs-on: windows-2019
#
# strategy:
# matrix:
# build: [Release]
# arch: [x64]
# cublas: [ON]
# sdl2: [ON]
# cuda-toolkit: [12.2.0, 11.8.0]
# include:
# - arch: x64
# s2arc: x64
# - sdl2: ON
# s2ver: 2.28.5
#
# steps:
# - name: Clone
# uses: actions/checkout@v4
#
# - name: Add msbuild to PATH
# uses: microsoft/setup-msbuild@v2
#
# - name: Install CUDA Toolkit
# id: cuda-toolkit
# uses: Jimver/cuda-toolkit@v0.2.15
# with:
# cuda: '${{ matrix.cuda-toolkit }}'
#
# - name: Fetch SDL2 and set SDL2_DIR
# if: matrix.sdl2 == 'ON'
# run: |
# C:/msys64/usr/bin/wget.exe -qO sdl2.zip https://github.com/libsdl-org/SDL/releases/download/release-${{ matrix.s2ver }}/SDL2-devel-${{ matrix.s2ver }}-VC.zip
# 7z x sdl2.zip
# echo "SDL2_DIR=$env:GITHUB_WORKSPACE/SDL2-${{ matrix.s2ver }}/cmake" >> $env:GITHUB_ENV
#
# - name: Configure
# run: >
# cmake -S . -B ./build -A ${{ matrix.arch }}
# -DCMAKE_BUILD_TYPE=${{ matrix.build }}
# -DGGML_CUDA=${{ matrix.cublas }}
# -DWHISPER_SDL2=${{ matrix.sdl2 }}
#
# - name: Build ${{ matrix.cuda-toolkit }}
# run: |
# cd ./build
# cmake --build . --config ${{ matrix.build }}
#
# - name: Copy CUDA DLLs
# run: >
# Copy-Item -PassThru
# -Path "${{ steps.cuda-toolkit.outputs.CUDA_PATH }}/bin/*.dll"
# -Include cudart64_*,cublas64_*,cublasLt64_*
# -Destination build/bin/${{ matrix.build }}
#
# - name: Copy SDL2.dll
# if: matrix.sdl2 == 'ON'
# run: copy "$env:SDL2_DIR/../lib/${{ matrix.s2arc }}/SDL2.dll" build/bin/${{ matrix.build }}
#
# - name: Upload binaries
# if: matrix.sdl2 == 'ON'
# uses: actions/upload-artifact@v4
# with:
# name: whisper-cublas-${{ matrix.cuda-toolkit }}-bin-${{ matrix.arch }}
# path: build/bin/${{ matrix.build }}
windows-cublas:
runs-on: windows-latest
strategy:
matrix:
build: [Release]
arch: [x64]
cublas: [ON]
sdl2: [ON]
include:
- arch: x64
s2arc: x64
- sdl2: ON
s2ver: 2.26.0
steps:
- name: Clone
uses: actions/checkout@v3
- name: Add msbuild to PATH
uses: microsoft/setup-msbuild@v1
- name: Install CUDA Toolkit
id: cuda-toolkit
uses: Jimver/cuda-toolkit@v0.2.10
- name: Fetch SDL2 and set SDL2_DIR
if: matrix.sdl2 == 'ON'
run: |
C:/msys64/usr/bin/wget.exe -qO sdl2.zip https://github.com/libsdl-org/SDL/releases/download/release-${{ matrix.s2ver }}/SDL2-devel-${{ matrix.s2ver }}-VC.zip
7z x sdl2.zip
echo "SDL2_DIR=$env:GITHUB_WORKSPACE/SDL2-${{ matrix.s2ver }}/cmake" >> $env:GITHUB_ENV
- name: Configure
run: >
cmake -S . -B ./build -A ${{ matrix.arch }}
-DCMAKE_BUILD_TYPE=${{ matrix.build }}
-DWHISPER_CUBLAS=1
- name: Build
run: |
cd ./build
msbuild ALL_BUILD.vcxproj -t:build -p:configuration=${{ matrix.build }} -p:platform=${{ matrix.arch }}
- name: Copy SDL2.dll
if: matrix.sdl2 == 'ON'
run: copy "$env:SDL2_DIR/../lib/${{ matrix.s2arc }}/SDL2.dll" build/bin/${{ matrix.build }}
- name: Upload binaries
if: matrix.sdl2 == 'ON'
uses: actions/upload-artifact@v1
with:
name: whisper-cublas-bin-${{ matrix.arch }}
path: build/bin/${{ matrix.build }}
emscripten:
runs-on: ubuntu-latest
@ -506,10 +340,10 @@ jobs:
steps:
- name: Clone
uses: actions/checkout@v4
uses: actions/checkout@v3
- name: Setup emsdk
uses: mymindstorm/setup-emsdk@v14
uses: mymindstorm/setup-emsdk@v12
- name: Verify
run: emcc -v
@ -519,7 +353,7 @@ jobs:
emcmake cmake . -DCMAKE_BUILD_TYPE=${{ matrix.build }}
make
ios-xcode-build:
ios:
runs-on: macos-latest
strategy:
@ -527,152 +361,92 @@ jobs:
build: [Release]
steps:
- name: Checkout code
uses: actions/checkout@v4
- name: Clone
uses: actions/checkout@v3
- name: Configure
run: |
cp models/for-tests-ggml-base.en.bin models/ggml-base.en.bin
mkdir models/ggml-base.en-encoder.mlmodelc
- name: Build
id: cmake_build
run: |
sysctl -a
mkdir build
cd build
cmake -G Xcode .. \
-DGGML_METAL_USE_BF16=ON \
-DGGML_METAL_EMBED_LIBRARY=ON \
-DWHISPER_BUILD_EXAMPLES=OFF \
-DWHISPER_BUILD_TESTS=OFF \
-DWHISPER_BUILD_SERVER=OFF \
-DCMAKE_SYSTEM_NAME=iOS \
-DCMAKE_OSX_DEPLOYMENT_TARGET=14.0 \
-DCMAKE_XCODE_ATTRIBUTE_DEVELOPMENT_TEAM=ggml
cmake --build . --config Release -j $(sysctl -n hw.logicalcpu) -- CODE_SIGNING_ALLOWED=NO
sudo cmake --install . --config Release
- name: xcodebuild for swift package
id: xcodebuild
run: |
xcodebuild -scheme whisper-Package -destination 'generic/platform=iOS'
#- name: Build objc example
# run: xcodebuild -project examples/whisper.objc/whisper.objc.xcodeproj -scheme whisper.objc -configuration ${{ matrix.build }} -sdk iphoneos build
- name: Build objc example
run: xcodebuild -project examples/whisper.objc/whisper.objc.xcodeproj -scheme whisper.objc -configuration ${{ matrix.build }} -sdk iphonesimulator build
- name: Build swiftui example
run: xcodebuild -project examples/whisper.swiftui/whisper.swiftui.xcodeproj -scheme WhisperCppDemo -configuration ${{ matrix.build }} -sdk iphoneos CODE_SIGNING_REQUIRED=NO CODE_SIGN_IDENTITY= -destination 'generic/platform=iOS' build
run: xcodebuild -project examples/whisper.swiftui/whisper.swiftui.xcodeproj -scheme WhisperCppDemo -configuration ${{ matrix.build }} -sdk iphonesimulator build
android:
runs-on: ubuntu-latest
steps:
- name: Clone
uses: actions/checkout@v4
with:
path: whisper
uses: actions/checkout@v3
- name: Install Java
uses: actions/setup-java@v4
uses: actions/setup-java@v3
with:
distribution: zulu
java-version: 21
java-version: 17
- name: Setup Android SDK
uses: android-actions/setup-android@v3
uses: android-actions/setup-android@v2
- name: Build
run: |
cd whisper/examples/whisper.android
cd examples/whisper.android
./gradlew assembleRelease --no-daemon
- name: Build with external ggml
java:
needs: [ 'windows' ]
runs-on: windows-latest
steps:
- uses: actions/checkout@v3
- name: Install Java
uses: actions/setup-java@v1
with:
java-version: 17
- name: Download Windows lib
uses: actions/download-artifact@v3
with:
name: win32-x86-64_whisper.dll
path: bindings/java/build/generated/resources/main/win32-x86-64
- name: Build
run: |
export PATH_TO_GGML=$PWD/ggml
cd whisper/examples/whisper.android
./gradlew assembleRelease --no-daemon
models\download-ggml-model.cmd tiny.en
cd bindings/java
chmod +x ./gradlew
./gradlew build
# TODO: disable because of following fail: https://github.com/ggerganov/whisper.cpp/actions/runs/11019444420/job/30627193602
# android_java:
# runs-on: ubuntu-latest
#
# steps:
# - name: Clone
# uses: actions/checkout@v4
#
# - name: set up JDK 11
# uses: actions/setup-java@v4
# with:
# java-version: '11'
# distribution: 'temurin'
# cache: gradle
#
# - name: Setup Android SDK
# uses: android-actions/setup-android@v3
# with:
# cmdline-tools-version: 9.0
#
# - name: Build
# run: |
# cd examples/whisper.android.java
# chmod +x ./gradlew
# ./gradlew assembleRelease
- name: Upload jar
uses: actions/upload-artifact@v3
with:
name: whispercpp.jar
path: bindings/java/build/libs/whispercpp-*.jar
# TODO: disabled because of following fail: https://github.com/ggerganov/whisper.cpp/actions/runs/9686220096/job/26735899598
# java:
# needs: [ 'windows' ]
# runs-on: windows-latest
# steps:
# - uses: actions/checkout@v4
#
# - name: Install Java
# uses: actions/setup-java@v4
# with:
# distribution: zulu
# java-version: 20
#
# - name: Download Windows lib
# uses: actions/download-artifact@v4
# with:
# name: win32-x86-64_whisper.dll
# path: bindings/java/build/generated/resources/main/win32-x86-64
#
# - name: Build
# run: |
# models\download-ggml-model.cmd tiny.en
# cd bindings/java
# chmod +x ./gradlew
# ./gradlew build
#
# - name: Upload jar
# uses: actions/upload-artifact@v4
# with:
# name: whispercpp.jar
# path: bindings/java/build/libs/whispercpp-*.jar
#
# - name: Publish package
# if: ${{ github.ref == 'refs/heads/master' }}
# uses: gradle/gradle-build-action@v2.4.2
# with:
# arguments: publish
# build-root-directory: bindings/java
# env:
# MAVEN_USERNAME: ${{ secrets.JIRA_USER }}
# MAVEN_PASSWORD: ${{ secrets.JIRA_PASS }}
# PGP_SECRET: ${{ secrets.GPG_PRIVATE_KEY }}
# PGP_PASSPHRASE: ${{ secrets.GPG_PASSPHRASE }}
- name: Publish package
if: ${{ github.ref == 'refs/heads/master' }}
uses: gradle/gradle-build-action@v2.4.2
with:
arguments: publish
build-root-directory: bindings/java
env:
MAVEN_USERNAME: ${{ secrets.JIRA_USER }}
MAVEN_PASSWORD: ${{ secrets.JIRA_PASS }}
PGP_SECRET: ${{ secrets.GPG_PRIVATE_KEY }}
PGP_PASSPHRASE: ${{ secrets.GPG_PASSPHRASE }}
quantize:
runs-on: ubuntu-latest
steps:
- name: Clone
uses: actions/checkout@v4
uses: actions/checkout@v3
- name: Test quantize
run: |
./models/download-ggml-model.sh tiny.en
cmake -B build
cmake --build build --config Release
./build/bin/quantize models/ggml-tiny.en.bin models/ggml-tiny.en-q4_0.bin q4_0
make quantize
./quantize models/ggml-tiny.en.bin models/ggml-tiny.en-q4_0.bin q4_0

View File

@ -1,59 +0,0 @@
name: Publish Docker image
on:
pull_request:
push:
branches:
- master
jobs:
push_to_registry:
name: Push Docker image to Docker Hub
if: github.event.pull_request.draft == false
runs-on: ubuntu-latest
env:
COMMIT_SHA: ${{ github.sha }}
strategy:
matrix:
config:
- { tag: "main", dockerfile: ".devops/main.Dockerfile", platform: "linux/amd64,linux/arm64" }
#TODO: the cuda image keeps failing - disable for now
# https://github.com/ggerganov/whisper.cpp/actions/runs/11019444428/job/30602020339
#- { tag: "main-cuda", dockerfile: ".devops/main-cuda.Dockerfile", platform: "linux/amd64" }
steps:
- name: Check out the repo
uses: actions/checkout@v3
- name: Set up QEMU
uses: docker/setup-qemu-action@v3
- name: Set up Docker Buildx
uses: docker/setup-buildx-action@v3
- name: Log in to Docker Hub
uses: docker/login-action@v3
with:
registry: ghcr.io
username: ${{ github.repository_owner }}
password: ${{ secrets.GITHUB_TOKEN }}
- name: Build and push Docker image (versioned)
if: github.event_name == 'push'
uses: docker/build-push-action@v5
with:
context: .
push: true
platforms: ${{ matrix.config.platform }}
tags: "ghcr.io/${{ github.repository }}:${{ matrix.config.tag }}-${{ 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: ${{ matrix.config.platform }}
tags: "ghcr.io/${{ github.repository }}:${{ matrix.config.tag }}"
file: ${{ matrix.config.dockerfile }}

View File

@ -37,7 +37,7 @@ jobs:
run: npm install
- name: Compile addon.node
run: npx cmake-js compile -T addon.node -B Release
run: npx cmake-js compile -T whisper-addon -B Release
- name: Download test model
run: |

23
.gitignore vendored
View File

@ -1,28 +1,28 @@
*.o
*.a
*.d
.cache/
.coreml/
.test/
.venv/
.vs/
.vscode/
.DS_Store
.vimspector.json
/CMakeSettings.json
/talk-llama.dSYM/
build/
build-*/
build-em/
build-debug/
build-release/
build-rwdi/
build-static/
build-cublas/
build-no-accel/
build-sanitize-addr/
build-sanitize-thread/
# SPM
.build/
.swiftpm
*.metallib
ggml-metal-embed.metal
ggml-metal-embed.metal.tmp
/main
/stream
/command
@ -30,7 +30,6 @@ ggml-metal-embed.metal.tmp
/talk-llama
/bench
/quantize
/server
/lsp
arm_neon.h
@ -54,7 +53,3 @@ bindings/java/.idea/
.idea/
benchmark_results.csv
cmake-build-debug/
.cxx/
.gradle/
local.properties

3
.gitmodules vendored
View File

@ -0,0 +1,3 @@
[submodule "bindings/ios"]
path = bindings/ios
url = https://github.com/ggerganov/whisper.spm

301
AUTHORS
View File

@ -1,301 +0,0 @@
# date: Tue Apr 9 20:27:03 EEST 2024
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Murilo Santana <mvrilo@gmail.com>
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ulatekh <ulatekh@yahoo.com>
undef <undefdev@gmail.com>
venkr <venkateshrameshkumar+1@gmail.com>
vicalloy <zbirder@gmail.com>
xdrudis <xavierdrudis@yahoo.es>
zhouwg <6889919+zhouwg@users.noreply.github.com>
布客飞龙 <562826179@qq.com>
Артём Земляк <azemlyak@smart-consulting.ru>

View File

@ -1,31 +1,21 @@
cmake_minimum_required(VERSION 3.5) # for add_link_options and implicit target directories.
project("whisper.cpp" C CXX)
project("whisper.cpp" VERSION 1.7.3)
include(CheckIncludeFileCXX)
cmake_minimum_required (VERSION 3.5)
set(SOVERSION 1)
#set(CMAKE_WARN_DEPRECATED YES)
set(CMAKE_WARN_UNUSED_CLI YES)
set(CMAKE_EXPORT_COMPILE_COMMANDS ON)
if (NOT XCODE AND NOT MSVC AND NOT CMAKE_BUILD_TYPE)
set(CMAKE_BUILD_TYPE Release CACHE STRING "Build type" FORCE)
set_property(CACHE CMAKE_BUILD_TYPE PROPERTY STRINGS "Debug" "Release" "MinSizeRel" "RelWithDebInfo")
endif()
project(whisper.cpp VERSION 1.4.3)
# Add path to modules
list(APPEND CMAKE_MODULE_PATH "${CMAKE_CURRENT_SOURCE_DIR}/cmake/")
set(CMAKE_RUNTIME_OUTPUT_DIRECTORY ${CMAKE_BINARY_DIR}/bin)
if (CMAKE_SOURCE_DIR STREQUAL CMAKE_CURRENT_SOURCE_DIR)
if(CMAKE_SOURCE_DIR STREQUAL CMAKE_CURRENT_SOURCE_DIR)
set(WHISPER_STANDALONE ON)
include(git-vars)
include(GitVars)
include(BuildTypes)
# configure project version
if (EXISTS "${CMAKE_SOURCE_DIR}/bindings/ios/Makefile-tmpl")
configure_file(${CMAKE_SOURCE_DIR}/bindings/ios/Makefile-tmpl ${CMAKE_SOURCE_DIR}/bindings/ios/Makefile @ONLY)
endif()
configure_file(${CMAKE_SOURCE_DIR}/bindings/javascript/package-tmpl.json ${CMAKE_SOURCE_DIR}/bindings/javascript/package.json @ONLY)
else()
set(WHISPER_STANDALONE OFF)
@ -35,11 +25,6 @@ if (EMSCRIPTEN)
set(BUILD_SHARED_LIBS_DEFAULT OFF)
option(WHISPER_WASM_SINGLE_FILE "whisper: embed WASM inside the generated whisper.js" ON)
# TODO: without these, we get the following error:
# wasm-ld: error: --shared-memory is disallowed by whisper.cpp.o because it was not compiled with 'atomics' or 'bulk-memory' features.
set(CMAKE_C_FLAGS "${CMAKE_C_FLAGS} -pthread -s TOTAL_STACK=5242880")
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -pthread -s TOTAL_STACK=5242880")
else()
if (MINGW)
set(BUILD_SHARED_LIBS_DEFAULT OFF)
@ -48,136 +33,531 @@ else()
endif()
endif()
option(BUILD_SHARED_LIBS "build shared libraries" ${BUILD_SHARED_LIBS_DEFAULT})
# options
#
# option list
#
if (APPLE)
set(WHISPER_METAL_DEFAULT ON)
else()
set(WHISPER_METAL_DEFAULT OFF)
endif()
# general
option(WHISPER_CCACHE "whisper: use ccache if available" ON)
option(BUILD_SHARED_LIBS "whisper: build shared libs" ${BUILD_SHARED_LIBS_DEFAULT})
# debug
option(WHISPER_ALL_WARNINGS "whisper: enable all compiler warnings" ON)
option(WHISPER_ALL_WARNINGS_3RD_PARTY "whisper: enable all compiler warnings in 3rd party libs" OFF)
# build
option(WHISPER_FATAL_WARNINGS "whisper: enable -Werror flag" OFF)
option(WHISPER_SANITIZE_THREAD "whisper: enable thread sanitizer" OFF)
option(WHISPER_SANITIZE_ADDRESS "whisper: enable address sanitizer" OFF)
option(WHISPER_SANITIZE_UNDEFINED "whisper: enable undefined sanitizer" OFF)
option(WHISPER_BUILD_TESTS "whisper: build tests" ${WHISPER_STANDALONE})
option(WHISPER_BUILD_EXAMPLES "whisper: build examples" ${WHISPER_STANDALONE})
option(WHISPER_SDL2 "whisper: support for libSDL2" OFF)
option(WHISPER_NO_AVX "whisper: disable AVX" OFF)
option(WHISPER_NO_AVX2 "whisper: disable AVX2" OFF)
option(WHISPER_NO_FMA "whisper: disable FMA" OFF)
option(WHISPER_NO_F16C "whisper: disable F16c" OFF)
option(WHISPER_OPENVINO "whisper: support for OpenVINO" OFF)
if (APPLE)
option(WHISPER_NO_ACCELERATE "whisper: disable Accelerate framework" OFF)
option(WHISPER_METAL "whisper: use Metal" ${WHISPER_METAL_DEFAULT})
option(WHISPER_METAL_NDEBUG "whisper: disable Metal debugging" OFF)
option(WHISPER_COREML "whisper: enable Core ML framework" OFF)
option(WHISPER_COREML_ALLOW_FALLBACK "whisper: allow non-CoreML fallback" OFF)
else()
option(WHISPER_BLAS "whisper: use BLAS libraries" OFF)
option(WHISPER_BLAS_VENDOR "whisper: BLAS library vendor" Generic)
option(WHISPER_OPENBLAS "whisper: prefer OpenBLAS" OFF)
option(WHISPER_CUBLAS "whisper: support for cuBLAS" OFF)
option(WHISPER_HIPBLAS "whisper: support for hipBLAS" OFF)
option(WHISPER_CLBLAST "whisper: use CLBlast" OFF)
endif()
option(WHISPER_PERF "whisper: enable perf timings" OFF)
# sanitizers
option(WHISPER_SANITIZE_THREAD "whisper: enable thread sanitizer" OFF)
option(WHISPER_SANITIZE_ADDRESS "whisper: enable address sanitizer" OFF)
option(WHISPER_SANITIZE_UNDEFINED "whisper: enable undefined sanitizer" OFF)
# extra artifacts
option(WHISPER_BUILD_TESTS "whisper: build tests" ${WHISPER_STANDALONE})
option(WHISPER_BUILD_EXAMPLES "whisper: build examples" ${WHISPER_STANDALONE})
option(WHISPER_BUILD_SERVER "whisper: build server example" ${WHISPER_STANDALONE})
# 3rd party libs
option(WHISPER_CURL "whisper: use libcurl to download model from an URL" OFF)
option(WHISPER_SDL2 "whisper: support for libSDL2" OFF)
if (CMAKE_SYSTEM_NAME MATCHES "Linux")
option(WHISPER_FFMPEG "whisper: support building and linking with ffmpeg libs (avcodec, swresample, ...)" OFF)
endif()
option(WHISPER_COREML "whisper: enable Core ML framework" OFF)
option(WHISPER_COREML_ALLOW_FALLBACK "whisper: allow non-CoreML fallback" OFF)
option(WHISPER_OPENVINO "whisper: support for OpenVINO" OFF)
# Required for relocatable CMake package
include(${CMAKE_CURRENT_SOURCE_DIR}/cmake/build-info.cmake)
# override ggml options
set(GGML_CCACHE ${WHISPER_CCACHE})
set(GGML_SANITIZE_THREAD ${WHISPER_SANITIZE_THREAD})
set(GGML_SANITIZE_ADDRESS ${WHISPER_SANITIZE_ADDRESS})
set(GGML_SANITIZE_UNDEFINED ${WHISPER_SANITIZE_UNDEFINED})
set(GGML_ALL_WARNINGS ${WHISPER_ALL_WARNINGS})
set(GGML_FATAL_WARNINGS ${WHISPER_FATAL_WARNINGS})
# transition helpers
function (whisper_option_depr TYPE OLD NEW)
if (${OLD})
message(${TYPE} "${OLD} is deprecated and will be removed in the future.\nUse ${NEW} instead\n")
set(${NEW} ON)
if (NOT MSVC)
if (WHISPER_SANITIZE_THREAD)
set(CMAKE_C_FLAGS "${CMAKE_C_FLAGS} -fsanitize=thread")
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -fsanitize=thread")
endif()
endfunction()
whisper_option_depr(FATAL_ERROR WHISPER_CUBLAS GGML_CUDA)
whisper_option_depr(WARNING WHISPER_CUDA GGML_CUDA)
whisper_option_depr(WARNING WHISPER_KOMPUTE GGML_KOMPUTE)
whisper_option_depr(WARNING WHISPER_METAL GGML_METAL)
whisper_option_depr(WARNING WHISPER_METAL_EMBED_LIBRARY GGML_METAL_EMBED_LIBRARY)
whisper_option_depr(WARNING WHISPER_NATIVE GGML_NATIVE)
whisper_option_depr(WARNING WHISPER_OPENMP GGML_OPENMP)
whisper_option_depr(WARNING WHISPER_RPC GGML_RPC)
whisper_option_depr(WARNING WHISPER_SYCL GGML_SYCL)
whisper_option_depr(WARNING WHISPER_SYCL_F16 GGML_SYCL_F16)
if (WHISPER_SANITIZE_ADDRESS)
set(CMAKE_C_FLAGS "${CMAKE_C_FLAGS} -fsanitize=address -fno-omit-frame-pointer")
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -fsanitize=address -fno-omit-frame-pointer")
endif()
#
# build the library
#
if (NOT TARGET ggml)
add_subdirectory(ggml)
# ... otherwise assume ggml is added by a parent CMakeLists.txt
if (WHISPER_SANITIZE_UNDEFINED)
set(CMAKE_C_FLAGS "${CMAKE_C_FLAGS} -fsanitize=undefined")
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -fsanitize=undefined")
endif()
endif()
#set(CMAKE_C_FLAGS "${CMAKE_C_FLAGS} -ffast-math")
#set(CMAKE_C_FLAGS "${CMAKE_C_FLAGS} -march=native")
# dependencies
find_package(Threads REQUIRED)
# on APPLE
if (APPLE)
# include Accelerate framework
if (NOT WHISPER_NO_ACCELERATE)
find_library(ACCELERATE_FRAMEWORK Accelerate)
if (ACCELERATE_FRAMEWORK)
message(STATUS "Accelerate framework found")
set(WHISPER_EXTRA_LIBS ${WHISPER_EXTRA_LIBS} ${ACCELERATE_FRAMEWORK})
set(WHISPER_EXTRA_FLAGS ${WHISPER_EXTRA_FLAGS} -DGGML_USE_ACCELERATE)
else()
message(FATAL_ERROR "Accelerate framework not found")
endif()
endif()
if (WHISPER_METAL)
find_library(FOUNDATION_LIBRARY Foundation REQUIRED)
find_library(METAL_FRAMEWORK Metal REQUIRED)
find_library(METALKIT_FRAMEWORK MetalKit REQUIRED)
if (METAL_FRAMEWORK)
message(STATUS "Metal framework found")
set(WHISPER_EXTRA_LIBS ${WHISPER_EXTRA_LIBS}
${FOUNDATION_LIBRARY}
${METAL_FRAMEWORK}
${METALKIT_FRAMEWORK}
)
set(WHISPER_EXTRA_FLAGS ${WHISPER_EXTRA_FLAGS} -DGGML_USE_METAL)
if (WHISPER_METAL_NDEBUG)
set(WHISPER_EXTRA_FLAGS ${WHISPER_EXTRA_FLAGS} -DGGML_METAL_NDEBUG)
endif()
else()
message(FATAL_ERROR "Metal framework not found")
endif()
set(GGML_SOURCES_METAL ggml-metal.m ggml-metal.h)
# copy ggml-metal.metal to bin directory
configure_file(ggml-metal.metal bin/ggml-metal.metal COPYONLY)
endif()
if (WHISPER_COREML)
find_library(FOUNDATION_FRAMEWORK Foundation)
find_library(COREML_FRAMEWORK CoreML)
if (COREML_FRAMEWORK)
message(STATUS "CoreML framework found")
set(WHISPER_EXTRA_FLAGS ${WHISPER_EXTRA_FLAGS} -DWHISPER_USE_COREML)
else()
message(FATAL_ERROR "CoreML framework not found")
endif()
if (WHISPER_COREML_ALLOW_FALLBACK)
set(WHISPER_EXTRA_FLAGS ${WHISPER_EXTRA_FLAGS} -DWHISPER_COREML_ALLOW_FALLBACK)
endif()
endif()
endif()
if (WHISPER_OPENBLAS)
set(WHISPER_BLAS_VENDOR "OpenBLAS")
set(WHISPER_BLAS ON)
endif()
if (WHISPER_BLAS)
if (WIN32)
if(DEFINED ENV{OPENBLAS_PATH})
set(BLAS_LIBRARIES $ENV{OPENBLAS_PATH}/lib/libopenblas.dll.a)
message(STATUS "Libraries ${BLAS_LIBRARIES}")
set(WHISPER_EXTRA_FLAGS ${WHISPER_EXTRA_FLAGS} -DGGML_USE_OPENBLAS)
include_directories($ENV{OPENBLAS_PATH}/include)
set(WHISPER_EXTRA_LIBS ${WHISPER_EXTRA_LIBS} ${BLAS_LIBRARIES})
else ()
message(FATAL_ERROR "BLAS library was not found. Environment variable OPENBLAS_PATH not defined.")
endif ()
else ()
set(BLA_STATIC 1)
set(BLA_VENDOR ${WHISPER_BLAS_VENDOR})
set(BLA_SIZEOF_INTEGER 8)
set(BLA_PREFER_PKGCONFIG 1)
find_package(BLAS)
if(BLAS_FOUND)
message(STATUS "BLAS compatible library found")
message(STATUS "Libraries ${BLAS_LIBRARIES}")
find_path(BLAS_INCLUDE_DIRS cblas.h /usr/include/openblas /usr/local/include/openblas $ENV{BLAS_HOME}/include)
set(WHISPER_EXTRA_FLAGS ${WHISPER_EXTRA_FLAGS} -DGGML_USE_OPENBLAS)
include_directories(${BLAS_INCLUDE_DIRS})
set(WHISPER_EXTRA_LIBS ${WHISPER_EXTRA_LIBS} ${BLAS_LIBRARIES})
else()
message(FATAL_ERROR "BLAS library was not found")
endif()
endif ()
endif ()
if (WHISPER_CUBLAS)
cmake_minimum_required(VERSION 3.17)
find_package(CUDAToolkit)
if (CUDAToolkit_FOUND)
message(STATUS "cuBLAS found")
enable_language(CUDA)
set(GGML_SOURCES_CUDA ggml-cuda.cu ggml-cuda.h)
add_compile_definitions(GGML_USE_CUBLAS)
if (WHISPER_STATIC)
set(WHISPER_EXTRA_LIBS ${WHISPER_EXTRA_LIBS} CUDA::cudart_static CUDA::cublas_static CUDA::cublasLt_static)
else()
set(WHISPER_EXTRA_LIBS ${WHISPER_EXTRA_LIBS} CUDA::cudart CUDA::cublas CUDA::cublasLt)
endif()
else()
message(FATAL_ERROR "cuBLAS not found")
endif()
endif()
if (WHISPER_HIPBLAS)
list(APPEND CMAKE_PREFIX_PATH /opt/rocm)
if (NOT ${CMAKE_C_COMPILER_ID} MATCHES "Clang")
message(WARNING "Only LLVM is supported for HIP, hint: CC=/opt/rocm/llvm/bin/clang")
endif()
if (NOT ${CMAKE_CXX_COMPILER_ID} MATCHES "Clang")
message(WARNING "Only LLVM is supported for HIP, hint: CXX=/opt/rocm/llvm/bin/clang++")
endif()
find_package(hip)
find_package(hipblas)
find_package(rocblas)
if (${hipblas_FOUND} AND ${hip_FOUND})
message(STATUS "HIP and hipBLAS found")
add_compile_definitions(GGML_USE_HIPBLAS GGML_USE_CUBLAS)
add_library(ggml-rocm OBJECT ggml-cuda.cu ggml-cuda.h)
set_property(TARGET ggml-rocm PROPERTY POSITION_INDEPENDENT_CODE ON)
set_source_files_properties(ggml-cuda.cu PROPERTIES LANGUAGE CXX)
target_link_libraries(ggml-rocm PRIVATE hip::device PUBLIC hip::host roc::rocblas roc::hipblas)
if (WHISPER_STATIC)
message(FATAL_ERROR "Static linking not supported for HIP/ROCm")
endif()
set(WHISPER_EXTRA_LIBS ${WHISPER_EXTRA_LIBS} ggml-rocm)
else()
message(FATAL_ERROR "hipBLAS or HIP not found. Try setting CMAKE_PREFIX_PATH=/opt/rocm")
endif()
endif()
if (WHISPER_CLBLAST)
find_package(CLBlast)
if (CLBlast_FOUND)
message(STATUS "CLBlast found")
set(GGML_SOURCES_OPENCL ggml-opencl.cpp ggml-opencl.h)
add_compile_definitions(GGML_USE_CLBLAST)
set(WHISPER_EXTRA_LIBS ${WHISPER_EXTRA_LIBS} clblast)
else()
message(FATAL_ERROR "CLBlast not found")
endif()
endif()
if( WHISPER_OPENVINO )
find_package(OpenVINO REQUIRED COMPONENTS Runtime)
endif()
# compiler flags
if (NOT CMAKE_BUILD_TYPE AND NOT CMAKE_CONFIGURATION_TYPES)
set(CMAKE_BUILD_TYPE Release CACHE STRING "Build type" FORCE)
set_property(CACHE CMAKE_BUILD_TYPE PROPERTY STRINGS "Debug" "Release" "RelWithDebInfo")
endif ()
if (WHISPER_ALL_WARNINGS)
if (NOT MSVC)
set(CMAKE_C_FLAGS "${CMAKE_C_FLAGS} \
-Wall \
-Wextra \
-Wpedantic \
-Wshadow \
-Wcast-qual \
-Wstrict-prototypes \
-Wpointer-arith \
-Wno-unused-function \
")
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} \
-Wall \
-Wextra \
-Wpedantic \
-Wcast-qual \
")
else()
# todo : msvc
endif()
endif()
if (NOT MSVC)
set(CMAKE_C_FLAGS "${CMAKE_C_FLAGS} -Werror=vla")
#set(CMAKE_C_FLAGS "${CMAKE_C_FLAGS} -fno-math-errno -ffinite-math-only -funsafe-math-optimizations")
endif()
message(STATUS "CMAKE_SYSTEM_PROCESSOR: ${CMAKE_SYSTEM_PROCESSOR}")
if (${CMAKE_SYSTEM_PROCESSOR} MATCHES "arm" OR ${CMAKE_SYSTEM_PROCESSOR} MATCHES "aarch64")
message(STATUS "ARM detected")
elseif(${CMAKE_SYSTEM_PROCESSOR} MATCHES "ppc64le")
message(STATUS "PowerPC detected")
else()
message(STATUS "x86 detected")
if (MSVC)
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} /utf-8")
set(CMAKE_CXX_FLAGS_RELEASE "${CMAKE_CXX_FLAGS_RELEASE} /utf-8")
set(CMAKE_C_FLAGS "${CMAKE_C_FLAGS} /utf-8")
if(NOT WHISPER_NO_AVX2)
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} /arch:AVX2")
set(CMAKE_CXX_FLAGS_RELEASE "${CMAKE_CXX_FLAGS_RELEASE} /arch:AVX2")
set(CMAKE_C_FLAGS "${CMAKE_C_FLAGS} /arch:AVX2")
else()
if(NOT WHISPER_NO_AVX)
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} /arch:AVX")
set(CMAKE_CXX_FLAGS_RELEASE "${CMAKE_CXX_FLAGS_RELEASE} /arch:AVX")
set(CMAKE_C_FLAGS "${CMAKE_C_FLAGS} /arch:AVX")
endif()
endif()
else()
if (EMSCRIPTEN)
set(CMAKE_C_FLAGS "${CMAKE_C_FLAGS} -pthread")
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -pthread")
else()
if(NOT WHISPER_NO_AVX)
set(CMAKE_C_FLAGS "${CMAKE_C_FLAGS} -mavx")
endif()
if(NOT WHISPER_NO_AVX2)
set(CMAKE_C_FLAGS "${CMAKE_C_FLAGS} -mavx2")
endif()
if(NOT WHISPER_NO_FMA)
set(CMAKE_C_FLAGS "${CMAKE_C_FLAGS} -mfma")
endif()
if(NOT WHISPER_NO_F16C)
set(CMAKE_C_FLAGS "${CMAKE_C_FLAGS} -mf16c")
endif()
endif()
endif()
endif()
add_subdirectory(src)
#
# install
# POSIX conformance
#
# clock_gettime came in POSIX.1b (1993)
# CLOCK_MONOTONIC came in POSIX.1-2001 / SUSv3 as optional
# posix_memalign came in POSIX.1-2001 / SUSv3
# M_PI is an XSI extension since POSIX.1-2001 / SUSv3, came in XPG1 (1985)
add_compile_definitions(_XOPEN_SOURCE=600)
# Somehow in OpenBSD whenever POSIX conformance is specified
# some string functions rely on locale_t availability,
# which was introduced in POSIX.1-2008, forcing us to go higher
if (CMAKE_SYSTEM_NAME MATCHES "OpenBSD")
remove_definitions(-D_XOPEN_SOURCE=600)
add_compile_definitions(_XOPEN_SOURCE=700)
endif()
# Data types, macros and functions related to controlling CPU affinity
# are available on Linux through GNU extensions in libc
if (CMAKE_SYSTEM_NAME MATCHES "Linux")
add_compile_definitions(_GNU_SOURCE)
endif()
# RLIMIT_MEMLOCK came in BSD, is not specified in POSIX.1,
# and on macOS its availability depends on enabling Darwin extensions
# similarly on DragonFly, enabling BSD extensions is necessary
if (CMAKE_SYSTEM_NAME MATCHES "Darwin")
add_compile_definitions(_DARWIN_C_SOURCE)
endif()
if (CMAKE_SYSTEM_NAME MATCHES "DragonFly")
add_compile_definitions(_DARWIN_C_SOURCE)
endif()
# alloca is a non-standard interface that is not visible on BSDs when
# POSIX conformance is specified, but not all of them provide a clean way
# to enable it in such cases
if (CMAKE_SYSTEM_NAME MATCHES "FreeBSD")
add_compile_definitions(__BSD_VISIBLE)
endif()
if (CMAKE_SYSTEM_NAME MATCHES "NetBSD")
add_compile_definitions(_NETBSD_SOURCE)
endif()
if (CMAKE_SYSTEM_NAME MATCHES "OpenBSD")
add_compile_definitions(_BSD_SOURCE)
endif()
if (WHISPER_PERF)
set(WHISPER_EXTRA_FLAGS ${WHISPER_EXTRA_FLAGS} -DGGML_PERF)
endif()
#
# whisper.coreml - Core ML support
#
if (WHISPER_COREML)
set(TARGET whisper.coreml)
add_library(${TARGET}
coreml/whisper-encoder.h
coreml/whisper-encoder.mm
coreml/whisper-encoder-impl.h
coreml/whisper-encoder-impl.m
)
include(DefaultTargetOptions)
target_include_directories(${TARGET} PUBLIC
.
)
target_link_libraries(${TARGET} PRIVATE ${FOUNDATION_FRAMEWORK} ${COREML_FRAMEWORK})
set_target_properties(${TARGET} PROPERTIES
COMPILE_FLAGS "-fobjc-arc"
)
endif()
if (WHISPER_OPENVINO)
set(TARGET whisper.openvino)
add_library(${TARGET} OBJECT
openvino/whisper-openvino-encoder.h
openvino/whisper-openvino-encoder.cpp
)
target_include_directories(${TARGET} PUBLIC
.
)
set_property(TARGET ${TARGET} PROPERTY POSITION_INDEPENDENT_CODE ON)
set(WHISPER_EXTRA_FLAGS ${WHISPER_EXTRA_FLAGS} -DWHISPER_USE_OPENVINO)
target_link_libraries(${TARGET} PRIVATE openvino::runtime)
endif()
#
# whisper - this is the main library of the project
#
set(TARGET whisper)
add_library(${TARGET}
ggml.h
ggml.c
ggml-alloc.h
ggml-alloc.c
ggml-backend.h
ggml-backend.c
ggml-quants.h
ggml-quants.c
${GGML_SOURCES_METAL}
${GGML_SOURCES_CUDA}
${GGML_SOURCES_OPENCL}
whisper.h
whisper.cpp
)
include(DefaultTargetOptions)
target_include_directories(${TARGET} PUBLIC
.
)
if (WHISPER_COREML)
target_link_libraries(${TARGET} PRIVATE whisper.coreml)
endif()
if (WHISPER_OPENVINO)
target_link_libraries(${TARGET} PRIVATE whisper.openvino)
endif()
if (MSVC)
target_link_libraries(${TARGET} PRIVATE ${WHISPER_EXTRA_LIBS} ${CMAKE_THREAD_LIBS_INIT})
set(WHISPER_EXTRA_FLAGS ${WHISPER_EXTRA_FLAGS} -D_CRT_SECURE_NO_WARNINGS)
else()
target_link_libraries(${TARGET} PRIVATE m ${WHISPER_EXTRA_LIBS} ${CMAKE_THREAD_LIBS_INIT})
endif()
if (BUILD_SHARED_LIBS)
target_link_libraries(${TARGET} PUBLIC
${CMAKE_DL_LIBS}
)
target_compile_definitions(${TARGET} PUBLIC
WHISPER_SHARED
GGML_SHARED
)
target_compile_definitions(${TARGET} PRIVATE
WHISPER_BUILD
GGML_BUILD
)
if (WHISPER_METAL)
# TODO: I think this should make ggml-metal.m "see" the ggml-metal.metal file from the "bin" directory
# but for some reason it does not work here like it does in llama.cpp
set_target_properties(${TARGET} PROPERTIES RESOURCE "${CMAKE_CURRENT_SOURCE_DIR}/ggml-metal.metal")
endif()
endif()
if (GGML_SOURCES_CUDA)
message(STATUS "GGML CUDA sources found, configuring CUDA architecture")
set_property(TARGET whisper PROPERTY CUDA_ARCHITECTURES OFF)
set_property(TARGET whisper PROPERTY CUDA_SELECT_NVCC_ARCH_FLAGS "Auto")
endif()
if (EMSCRIPTEN)
set_target_properties(${TARGET} PROPERTIES COMPILE_FLAGS "-msimd128")
endif()
target_compile_definitions(${TARGET} PUBLIC
${WHISPER_EXTRA_FLAGS}
)
set_target_properties(${TARGET} PROPERTIES PUBLIC_HEADER "whisper.h")
include(GNUInstallDirs)
include(CMakePackageConfigHelpers)
set(WHISPER_BUILD_NUMBER ${BUILD_NUMBER})
set(WHISPER_BUILD_COMMIT ${BUILD_COMMIT})
set(WHISPER_INSTALL_VERSION ${CMAKE_PROJECT_VERSION})
install(TARGETS ${TARGET}
LIBRARY DESTINATION lib
ARCHIVE DESTINATION lib/static
RUNTIME DESTINATION bin
RESOURCE DESTINATION bin
PUBLIC_HEADER DESTINATION include
)
set(WHISPER_INCLUDE_INSTALL_DIR ${CMAKE_INSTALL_INCLUDEDIR} CACHE PATH "Location of header files")
set(WHISPER_LIB_INSTALL_DIR ${CMAKE_INSTALL_LIBDIR} CACHE PATH "Location of library files")
set(WHISPER_BIN_INSTALL_DIR ${CMAKE_INSTALL_BINDIR} CACHE PATH "Location of binary files")
#
# bindings
#
get_directory_property(WHISPER_TRANSIENT_DEFINES COMPILE_DEFINITIONS)
set_target_properties(whisper PROPERTIES PUBLIC_HEADER ${CMAKE_CURRENT_SOURCE_DIR}/include/whisper.h)
install(TARGETS whisper LIBRARY PUBLIC_HEADER)
configure_package_config_file(
${CMAKE_CURRENT_SOURCE_DIR}/cmake/whisper-config.cmake.in
${CMAKE_CURRENT_BINARY_DIR}/whisper-config.cmake
INSTALL_DESTINATION ${CMAKE_INSTALL_LIBDIR}/cmake/whisper
PATH_VARS
WHISPER_INCLUDE_INSTALL_DIR
WHISPER_LIB_INSTALL_DIR
WHISPER_BIN_INSTALL_DIR )
write_basic_package_version_file(
${CMAKE_CURRENT_BINARY_DIR}/whisper-version.cmake
VERSION ${WHISPER_INSTALL_VERSION}
COMPATIBILITY SameMajorVersion)
install(FILES ${CMAKE_CURRENT_BINARY_DIR}/whisper-config.cmake
${CMAKE_CURRENT_BINARY_DIR}/whisper-version.cmake
DESTINATION ${CMAKE_INSTALL_LIBDIR}/cmake/whisper)
configure_file(cmake/whisper.pc.in
"${CMAKE_CURRENT_BINARY_DIR}/whisper.pc"
@ONLY)
install(FILES "${CMAKE_CURRENT_BINARY_DIR}/whisper.pc"
DESTINATION lib/pkgconfig)
add_subdirectory(bindings)
#
# programs, examples and tests
#
if (WHISPER_BUILD_TESTS AND NOT CMAKE_JS_VERSION)
#include(CTest)
#add_subdirectory(tests)
enable_testing()
add_subdirectory(tests)
endif ()
if (WHISPER_BUILD_EXAMPLES)

View File

@ -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

398
Makefile
View File

@ -1,12 +1,383 @@
default: main bench quantize
ifndef UNAME_S
UNAME_S := $(shell uname -s)
endif
ifndef UNAME_P
UNAME_P := $(shell uname -p)
endif
ifndef UNAME_M
UNAME_M := $(shell uname -m)
endif
ifndef NVCC_VERSION
ifeq ($(call,$(shell which nvcc))$(.SHELLSTATUS),0)
NVCC_VERSION := $(shell nvcc --version | egrep -o "V[0-9]+.[0-9]+.[0-9]+" | cut -c2-)
endif
endif
CCV := $(shell $(CC) --version | head -n 1)
CXXV := $(shell $(CXX) --version | head -n 1)
# Mac OS + Arm can report x86_64
# ref: https://github.com/ggerganov/whisper.cpp/issues/66#issuecomment-1282546789
ifeq ($(UNAME_S),Darwin)
ifneq ($(UNAME_P),arm)
SYSCTL_M := $(shell sysctl -n hw.optional.arm64)
ifeq ($(SYSCTL_M),1)
# UNAME_P := arm
# UNAME_M := arm64
warn := $(warning Your arch is announced as x86_64, but it seems to actually be ARM64. Not fixing that can lead to bad performance. For more info see: https://github.com/ggerganov/whisper.cpp/issues/66\#issuecomment-1282546789)
endif
endif
endif
#
# Compile flags
#
CFLAGS = -I. -O3 -DNDEBUG -std=c11 -fPIC
CXXFLAGS = -I. -I./examples -O3 -DNDEBUG -std=c++11 -fPIC
LDFLAGS =
# clock_gettime came in POSIX.1b (1993)
# CLOCK_MONOTONIC came in POSIX.1-2001 / SUSv3 as optional
# posix_memalign came in POSIX.1-2001 / SUSv3
# M_PI is an XSI extension since POSIX.1-2001 / SUSv3, came in XPG1 (1985)
CFLAGS += -D_XOPEN_SOURCE=600
CXXFLAGS += -D_XOPEN_SOURCE=600
# Somehow in OpenBSD whenever POSIX conformance is specified
# some string functions rely on locale_t availability,
# which was introduced in POSIX.1-2008, forcing us to go higher
ifeq ($(UNAME_S),OpenBSD)
CFLAGS += -U_XOPEN_SOURCE -D_XOPEN_SOURCE=700
CXXFLAGS += -U_XOPEN_SOURCE -D_XOPEN_SOURCE=700
endif
# Data types, macros and functions related to controlling CPU affinity
# are available on Linux through GNU extensions in libc
ifeq ($(UNAME_S),Linux)
CFLAGS += -D_GNU_SOURCE
CXXFLAGS += -D_GNU_SOURCE
endif
# RLIMIT_MEMLOCK came in BSD, is not specified in POSIX.1,
# and on macOS its availability depends on enabling Darwin extensions
# similarly on DragonFly, enabling BSD extensions is necessary
ifeq ($(UNAME_S),Darwin)
CFLAGS += -D_DARWIN_C_SOURCE
CXXFLAGS += -D_DARWIN_C_SOURCE
endif
ifeq ($(UNAME_S),DragonFly)
CFLAGS += -D__BSD_VISIBLE
CXXFLAGS += -D__BSD_VISIBLE
endif
# alloca is a non-standard interface that is not visible on BSDs when
# POSIX conformance is specified, but not all of them provide a clean way
# to enable it in such cases
ifeq ($(UNAME_S),FreeBSD)
CFLAGS += -D__BSD_VISIBLE
CXXFLAGS += -D__BSD_VISIBLE
endif
ifeq ($(UNAME_S),NetBSD)
CFLAGS += -D_NETBSD_SOURCE
CXXFLAGS += -D_NETBSD_SOURCE
endif
ifeq ($(UNAME_S),OpenBSD)
CFLAGS += -D_BSD_SOURCE
CXXFLAGS += -D_BSD_SOURCE
endif
# OS specific
# TODO: support Windows
ifeq ($(filter $(UNAME_S),Linux Darwin DragonFly FreeBSD NetBSD OpenBSD Haiku),$(UNAME_S))
CFLAGS += -pthread
CXXFLAGS += -pthread
endif
# Architecture specific
# TODO: probably these flags need to be tweaked on some architectures
# feel free to update the Makefile for your architecture and send a pull request or issue
ifeq ($(UNAME_M),$(filter $(UNAME_M),x86_64 i686 amd64))
ifeq ($(UNAME_S),Darwin)
CPUINFO_CMD := sysctl machdep.cpu.features machdep.cpu.leaf7_features
else ifeq ($(UNAME_S),Linux)
CPUINFO_CMD := cat /proc/cpuinfo
else ifneq (,$(filter MINGW32_NT% MINGW64_NT%,$(UNAME_S)))
CPUINFO_CMD := cat /proc/cpuinfo
else ifneq (,$(filter DragonFly FreeBSD,$(UNAME_S)))
CPUINFO_CMD := grep Features /var/run/dmesg.boot
else ifeq ($(UNAME_S),Haiku)
CPUINFO_CMD := sysinfo -cpu
endif
ifdef CPUINFO_CMD
AVX_M := $(shell $(CPUINFO_CMD) | grep -iwE 'AVX|AVX1.0')
ifneq (,$(AVX_M))
CFLAGS += -mavx
CXXFLAGS += -mavx
endif
AVX2_M := $(shell $(CPUINFO_CMD) | grep -iw 'AVX2')
ifneq (,$(AVX2_M))
CFLAGS += -mavx2
CXXFLAGS += -mavx2
endif
FMA_M := $(shell $(CPUINFO_CMD) | grep -iw 'FMA')
ifneq (,$(FMA_M))
CFLAGS += -mfma
CXXFLAGS += -mfma
endif
F16C_M := $(shell $(CPUINFO_CMD) | grep -iw 'F16C')
ifneq (,$(F16C_M))
CFLAGS += -mf16c
CXXFLAGS += -mf16c
endif
SSE3_M := $(shell $(CPUINFO_CMD) | grep -iwE 'PNI|SSE3')
ifneq (,$(SSE3_M))
CFLAGS += -msse3
CXXFLAGS += -msse3
endif
SSSE3_M := $(shell $(CPUINFO_CMD) | grep -iw 'SSSE3')
ifneq (,$(SSSE3_M))
CFLAGS += -mssse3
CXXFLAGS += -mssse3
endif
endif
endif
ifneq ($(filter ppc64%,$(UNAME_M)),)
POWER9_M := $(shell grep "POWER9" /proc/cpuinfo)
ifneq (,$(findstring POWER9,$(POWER9_M)))
CFLAGS += -mpower9-vector
endif
# Require c++23's std::byteswap for big-endian support.
ifeq ($(UNAME_M),ppc64)
CXXFLAGS += -std=c++23 -DGGML_BIG_ENDIAN
endif
endif
ifndef WHISPER_NO_ACCELERATE
# Mac M1 - include Accelerate framework
ifeq ($(UNAME_S),Darwin)
CFLAGS += -DGGML_USE_ACCELERATE
LDFLAGS += -framework Accelerate
endif
endif
ifdef WHISPER_COREML
CXXFLAGS += -DWHISPER_USE_COREML
LDFLAGS += -framework Foundation -framework CoreML
ifdef WHISPER_COREML_ALLOW_FALLBACK
CXXFLAGS += -DWHISPER_COREML_ALLOW_FALLBACK
endif
endif
ifndef WHISPER_NO_METAL
ifeq ($(UNAME_S),Darwin)
WHISPER_METAL := 1
CFLAGS += -DGGML_USE_METAL
CXXFLAGS += -DGGML_USE_METAL
LDFLAGS += -framework Foundation -framework Metal -framework MetalKit
endif
endif
ifdef WHISPER_OPENBLAS
CFLAGS += -DGGML_USE_OPENBLAS -I/usr/local/include/openblas -I/usr/include/openblas
LDFLAGS += -lopenblas
endif
ifdef WHISPER_CUBLAS
ifeq ($(shell expr $(NVCC_VERSION) \>= 11.6), 1)
CUDA_ARCH_FLAG=native
else
CUDA_ARCH_FLAG=all
endif
CFLAGS += -DGGML_USE_CUBLAS -I/usr/local/cuda/include -I/opt/cuda/include -I$(CUDA_PATH)/targets/$(UNAME_M)-linux/include
CXXFLAGS += -DGGML_USE_CUBLAS -I/usr/local/cuda/include -I/opt/cuda/include -I$(CUDA_PATH)/targets/$(UNAME_M)-linux/include
LDFLAGS += -lcublas -lculibos -lcudart -lcublasLt -lpthread -ldl -lrt -L/usr/local/cuda/lib64 -L/opt/cuda/lib64 -L$(CUDA_PATH)/targets/$(UNAME_M)-linux/lib
WHISPER_OBJ += ggml-cuda.o
NVCC = nvcc
NVCCFLAGS = --forward-unknown-to-host-compiler -arch=$(CUDA_ARCH_FLAG)
ggml-cuda.o: ggml-cuda.cu ggml-cuda.h
$(NVCC) $(NVCCFLAGS) $(CXXFLAGS) -Wno-pedantic -c $< -o $@
endif
ifdef WHISPER_HIPBLAS
ROCM_PATH ?= /opt/rocm
HIPCC ?= $(ROCM_PATH)/bin/hipcc
GPU_TARGETS ?= $(shell $(ROCM_PATH)/llvm/bin/amdgpu-arch)
CFLAGS += -DGGML_USE_HIPBLAS -DGGML_USE_CUBLAS
CXXFLAGS += -DGGML_USE_HIPBLAS -DGGML_USE_CUBLAS
LDFLAGS += -L$(ROCM_PATH)/lib -Wl,-rpath=$(ROCM_PATH)/lib
LDFLAGS += -lhipblas -lamdhip64 -lrocblas
HIPFLAGS += $(addprefix --offload-arch=,$(GPU_TARGETS))
WHISPER_OBJ += ggml-cuda.o
ggml-cuda.o: ggml-cuda.cu ggml-cuda.h
$(HIPCC) $(CXXFLAGS) $(HIPFLAGS) -x hip -c -o $@ $<
endif
ifdef WHISPER_CLBLAST
CFLAGS += -DGGML_USE_CLBLAST
CXXFLAGS += -DGGML_USE_CLBLAST
LDFLAGS += -lclblast
ifeq ($(UNAME_S),Darwin)
LDFLAGS += -framework OpenCL
else
LDFLAGS += -lOpenCL
endif
WHISPER_OBJ += ggml-opencl.o
ggml-opencl.o: ggml-opencl.cpp ggml-opencl.h
$(CXX) $(CXXFLAGS) -c $< -o $@
endif
ifdef WHISPER_GPROF
CFLAGS += -pg
CXXFLAGS += -pg
endif
ifneq ($(filter aarch64%,$(UNAME_M)),)
CFLAGS += -mcpu=native
CXXFLAGS += -mcpu=native
endif
ifneq ($(filter armv6%,$(UNAME_M)),)
# 32-bit Raspberry Pi 1, 2, 3
CFLAGS += -mfpu=neon -mfp16-format=ieee -mno-unaligned-access
endif
ifneq ($(filter armv7%,$(UNAME_M)),)
# 32-bit ARM, for example on Armbian or possibly raspbian
#CFLAGS += -mfpu=neon -mfp16-format=ieee -funsafe-math-optimizations -mno-unaligned-access
#CXXFLAGS += -mfpu=neon -mfp16-format=ieee -funsafe-math-optimizations -mno-unaligned-access
# 64-bit ARM on 32-bit OS, use these (TODO: auto-detect 64-bit)
CFLAGS += -mfpu=neon-fp-armv8 -mfp16-format=ieee -funsafe-math-optimizations -mno-unaligned-access
CXXFLAGS += -mfpu=neon-fp-armv8 -mfp16-format=ieee -funsafe-math-optimizations -mno-unaligned-access
endif
ifneq ($(filter armv8%,$(UNAME_M)),)
# Raspberry Pi 4
CFLAGS += -mfpu=neon-fp-armv8 -mfp16-format=ieee -funsafe-math-optimizations -mno-unaligned-access
CXXFLAGS += -mfpu=neon-fp-armv8 -mfp16-format=ieee -funsafe-math-optimizations -mno-unaligned-access
endif
#
# Print build information
#
$(info I whisper.cpp build info: )
$(info I UNAME_S: $(UNAME_S))
$(info I UNAME_P: $(UNAME_P))
$(info I UNAME_M: $(UNAME_M))
$(info I CFLAGS: $(CFLAGS))
$(info I CXXFLAGS: $(CXXFLAGS))
$(info I LDFLAGS: $(LDFLAGS))
$(info I CC: $(CCV))
$(info I CXX: $(CXXV))
$(info )
#
# Build library
#
ggml.o: ggml.c ggml.h ggml-cuda.h
$(CC) $(CFLAGS) -c $< -o $@
ggml-alloc.o: ggml-alloc.c ggml.h ggml-alloc.h
$(CC) $(CFLAGS) -c $< -o $@
ggml-backend.o: ggml-backend.c ggml.h ggml-backend.h
$(CC) $(CFLAGS) -c $< -o $@
ggml-quants.o: ggml-quants.c ggml.h ggml-quants.h
$(CC) $(CFLAGS) -c $< -o $@
WHISPER_OBJ += ggml.o ggml-alloc.o ggml-backend.o ggml-quants.o
whisper.o: whisper.cpp whisper.h ggml.h ggml-cuda.h
$(CXX) $(CXXFLAGS) -c $< -o $@
ifndef WHISPER_COREML
WHISPER_OBJ += whisper.o
else
whisper-encoder.o: coreml/whisper-encoder.mm coreml/whisper-encoder.h
$(CXX) -O3 -I . -fobjc-arc -c coreml/whisper-encoder.mm -o whisper-encoder.o
whisper-encoder-impl.o: coreml/whisper-encoder-impl.m coreml/whisper-encoder-impl.h
$(CXX) -O3 -I . -fobjc-arc -c coreml/whisper-encoder-impl.m -o whisper-encoder-impl.o
WHISPER_OBJ += whisper.o whisper-encoder.o whisper-encoder-impl.o
endif
ifdef WHISPER_METAL
ggml-metal.o: ggml-metal.m ggml-metal.h
$(CC) $(CFLAGS) -c $< -o $@
WHISPER_OBJ += ggml-metal.o
endif
libwhisper.a: $(WHISPER_OBJ)
$(AR) rcs libwhisper.a $(WHISPER_OBJ)
libwhisper.so: $(WHISPER_OBJ)
$(CXX) $(CXXFLAGS) -shared -o libwhisper.so $(WHISPER_OBJ) $(LDFLAGS)
clean:
rm -f *.o main stream command talk talk-llama bench quantize lsp libwhisper.a libwhisper.so
#
# Examples
#
CC_SDL=`sdl2-config --cflags --libs`
SRC_COMMON = examples/common.cpp examples/common-ggml.cpp
SRC_COMMON_SDL = examples/common-sdl.cpp
main: examples/main/main.cpp $(SRC_COMMON) $(WHISPER_OBJ)
$(CXX) $(CXXFLAGS) examples/main/main.cpp $(SRC_COMMON) $(WHISPER_OBJ) -o main $(LDFLAGS)
./main -h
bench: examples/bench/bench.cpp $(WHISPER_OBJ)
$(CXX) $(CXXFLAGS) examples/bench/bench.cpp $(WHISPER_OBJ) -o bench $(LDFLAGS)
quantize: examples/quantize/quantize.cpp $(WHISPER_OBJ) $(SRC_COMMON)
$(CXX) $(CXXFLAGS) examples/quantize/quantize.cpp $(SRC_COMMON) $(WHISPER_OBJ) -o quantize $(LDFLAGS)
stream: examples/stream/stream.cpp $(SRC_COMMON) $(SRC_COMMON_SDL) $(WHISPER_OBJ)
$(CXX) $(CXXFLAGS) examples/stream/stream.cpp $(SRC_COMMON) $(SRC_COMMON_SDL) $(WHISPER_OBJ) -o stream $(CC_SDL) $(LDFLAGS)
command: examples/command/command.cpp $(SRC_COMMON) $(SRC_COMMON_SDL) $(WHISPER_OBJ)
$(CXX) $(CXXFLAGS) examples/command/command.cpp $(SRC_COMMON) $(SRC_COMMON_SDL) $(WHISPER_OBJ) -o command $(CC_SDL) $(LDFLAGS)
lsp: examples/lsp/lsp.cpp $(SRC_COMMON) $(SRC_COMMON_SDL) $(WHISPER_OBJ)
$(CXX) $(CXXFLAGS) examples/lsp/lsp.cpp $(SRC_COMMON) $(SRC_COMMON_SDL) $(WHISPER_OBJ) -o lsp $(CC_SDL) $(LDFLAGS)
talk: examples/talk/talk.cpp examples/talk/gpt-2.cpp $(SRC_COMMON) $(SRC_COMMON_SDL) $(WHISPER_OBJ)
$(CXX) $(CXXFLAGS) examples/talk/talk.cpp examples/talk/gpt-2.cpp $(SRC_COMMON) $(SRC_COMMON_SDL) $(WHISPER_OBJ) -o talk $(CC_SDL) $(LDFLAGS)
talk-llama: examples/talk-llama/talk-llama.cpp examples/talk-llama/llama.cpp $(SRC_COMMON) $(SRC_COMMON_SDL) $(WHISPER_OBJ)
$(CXX) $(CXXFLAGS) examples/talk-llama/talk-llama.cpp examples/talk-llama/llama.cpp $(SRC_COMMON) $(SRC_COMMON_SDL) $(WHISPER_OBJ) -o talk-llama $(CC_SDL) $(LDFLAGS)
#
# Audio samples
#
.PHONY: build
build:
cmake -B build
cmake --build build --config Release
# download a few audio samples into folder "./samples":
.PHONY: samples
samples:
@ -47,13 +418,10 @@ samples:
.PHONY: medium
.PHONY: large-v1
.PHONY: large-v2
.PHONY: large-v3
.PHONY: large-v3-turbo
.PHONY: large
tiny.en tiny base.en base small.en small medium.en medium large-v1 large-v2 large-v3 large-v3-turbo:
tiny.en tiny base.en base small.en small medium.en medium large-v1 large-v2 large: main
bash ./models/download-ggml-model.sh $@
cmake -B build
cmake --build build --config Release
@echo ""
@echo "==============================================="
@echo "Running $@ on all samples in ./samples ..."
@ -64,6 +432,14 @@ tiny.en tiny base.en base small.en small medium.en medium large-v1 large-v2 larg
echo "[+] Running $@ on $$f ... (run 'ffplay $$f' to listen)" ; \
echo "----------------------------------------------" ; \
echo "" ; \
./build/bin/main -m models/ggml-$@.bin -f $$f ; \
./main -m models/ggml-$@.bin -f $$f ; \
echo "" ; \
done
#
# Tests
#
.PHONY: tests
tests:
bash ./tests/run-tests.sh $(word 2, $(MAKECMDGOALS))

View File

@ -2,18 +2,76 @@
import PackageDescription
#if arch(arm) || arch(arm64)
let platforms: [SupportedPlatform]? = [
.macOS(.v12),
.iOS(.v14),
.watchOS(.v4),
.tvOS(.v14)
]
let exclude: [String] = []
let resources: [Resource] = [
.process("ggml-metal.metal")
]
let additionalSources: [String] = ["ggml-metal.m"]
let additionalSettings: [CSetting] = [
.unsafeFlags(["-fno-objc-arc"]),
.define("GGML_USE_METAL")
]
#else
let platforms: [SupportedPlatform]? = nil
let exclude: [String] = ["ggml-metal.metal"]
let resources: [Resource] = []
let additionalSources: [String] = []
let additionalSettings: [CSetting] = []
#endif
let package = Package(
name: "whisper",
platforms: [
.macOS(.v12),
.iOS(.v14),
.watchOS(.v4),
.tvOS(.v14)
],
platforms: platforms,
products: [
.library(name: "whisper", targets: ["whisper"]),
],
targets: [
.systemLibrary(name: "whisper", pkgConfig: "whisper"),
]
.target(
name: "whisper",
path: ".",
exclude: exclude + [
"bindings",
"cmake",
"coreml",
"examples",
"extra",
"models",
"samples",
"tests",
"CMakeLists.txt",
"ggml-cuda.cu",
"ggml-cuda.h",
"Makefile"
],
sources: [
"ggml.c",
"whisper.cpp",
"ggml-alloc.c",
"ggml-backend.c",
"ggml-quants.c"
] + additionalSources,
resources: resources,
publicHeadersPath: "spm-headers",
cSettings: [
.unsafeFlags(["-Wno-shorten-64-to-32", "-O3", "-DNDEBUG"]),
.define("GGML_USE_ACCELERATE")
// 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")
] + additionalSettings,
linkerSettings: [
.linkedFramework("Accelerate")
]
)
],
cxxLanguageStandard: .cxx11
)

534
README.md
View File

@ -4,26 +4,26 @@
[![Actions Status](https://github.com/ggerganov/whisper.cpp/workflows/CI/badge.svg)](https://github.com/ggerganov/whisper.cpp/actions)
[![License: MIT](https://img.shields.io/badge/license-MIT-blue.svg)](https://opensource.org/licenses/MIT)
[![Conan Center](https://shields.io/conan/v/whisper-cpp)](https://conan.io/center/whisper-cpp)
[![npm](https://img.shields.io/npm/v/whisper.cpp.svg)](https://www.npmjs.com/package/whisper.cpp/)
Stable: [v1.7.3](https://github.com/ggerganov/whisper.cpp/releases/tag/v1.7.3) / [Roadmap | F.A.Q.](https://github.com/ggerganov/whisper.cpp/discussions/126)
Beta: [v1.4.3](https://github.com/ggerganov/whisper.cpp/releases/tag/v1.4.3) / Stable: [v1.2.1](https://github.com/ggerganov/whisper.cpp/releases/tag/v1.2.1) / [Roadmap | F.A.Q.](https://github.com/ggerganov/whisper.cpp/discussions/126)
High-performance inference of [OpenAI's Whisper](https://github.com/openai/whisper) automatic speech recognition (ASR) model:
- Plain C/C++ implementation without dependencies
- Apple Silicon first-class citizen - optimized via ARM NEON, Accelerate framework, Metal and [Core ML](#core-ml-support)
- Apple Silicon first-class citizen - optimized via ARM NEON, Accelerate framework, Metal and [Core ML](https://github.com/ggerganov/whisper.cpp#core-ml-support)
- AVX intrinsics support for x86 architectures
- VSX intrinsics support for POWER architectures
- Mixed F16 / F32 precision
- [Integer quantization support](#quantization)
- [4-bit and 5-bit integer quantization support](https://github.com/ggerganov/whisper.cpp#quantization)
- Low memory usage (Flash Attention)
- Zero memory allocations at runtime
- [Vulkan support](#vulkan-gpu-support)
- Support for CPU-only inference
- [Efficient GPU support for NVIDIA](#nvidia-gpu-support)
- [OpenVINO Support](#openvino-support)
- [Ascend NPU Support](#ascend-npu-support)
- [C-style API](https://github.com/ggerganov/whisper.cpp/blob/master/include/whisper.h)
- [Partial GPU support for NVIDIA via cuBLAS](https://github.com/ggerganov/whisper.cpp#nvidia-gpu-support-via-cublas)
- [Partial OpenCL GPU support via CLBlast](https://github.com/ggerganov/whisper.cpp#opencl-gpu-support-via-clblast)
- [BLAS CPU support via OpenBLAS](https://github.com/ggerganov/whisper.cpp#blas-cpu-support-via-openblas)
- [OpenVINO Support](https://github.com/ggerganov/whisper.cpp#openvino-support)
- [C-style API](https://github.com/ggerganov/whisper.cpp/blob/master/whisper.h)
Supported platforms:
@ -35,10 +35,11 @@ Supported platforms:
- [x] [WebAssembly](examples/whisper.wasm)
- [x] Windows ([MSVC](https://github.com/ggerganov/whisper.cpp/blob/master/.github/workflows/build.yml#L117-L144) and [MinGW](https://github.com/ggerganov/whisper.cpp/issues/168)]
- [x] [Raspberry Pi](https://github.com/ggerganov/whisper.cpp/discussions/166)
- [x] [Docker](https://github.com/ggerganov/whisper.cpp/pkgs/container/whisper.cpp)
The entire high-level implementation of the model is contained in [whisper.h](include/whisper.h) and [whisper.cpp](src/whisper.cpp).
The rest of the code is part of the [`ggml`](https://github.com/ggerganov/ggml) machine learning library.
The entire implementation of the model is contained in 2 source files:
- Tensor operations: [ggml.h](ggml.h) / [ggml.c](ggml.c)
- Transformer inference: [whisper.h](whisper.h) / [whisper.cpp](whisper.cpp)
Having such a lightweight implementation of the model allows to easily integrate it in different platforms and applications.
As an example, here is a video of running the model on an iPhone 13 device - fully offline, on-device: [whisper.objc](examples/whisper.objc)
@ -53,49 +54,161 @@ On Apple Silicon, the inference runs fully on the GPU via Metal:
https://github.com/ggerganov/whisper.cpp/assets/1991296/c82e8f86-60dc-49f2-b048-d2fdbd6b5225
Or you can even run it straight in the browser: [talk.wasm](examples/talk.wasm)
## Implementation details
- The core tensor operations are implemented in C ([ggml.h](ggml.h) / [ggml.c](ggml.c))
- The transformer model and the high-level C-style API are implemented in C++ ([whisper.h](whisper.h) / [whisper.cpp](whisper.cpp))
- Sample usage is demonstrated in [main.cpp](examples/main)
- Sample real-time audio transcription from the microphone is demonstrated in [stream.cpp](examples/stream)
- Various other examples are available in the [examples](examples) folder
The tensor operators are optimized heavily for Apple silicon CPUs. Depending on the computation size, Arm Neon SIMD
intrinsics or CBLAS Accelerate framework routines are used. The latter are especially effective for bigger sizes since
the Accelerate framework utilizes the special-purpose AMX coprocessor available in modern Apple products.
## Quick start
First clone the repository:
First clone the repository.
Then, download one of the Whisper models converted in [ggml format](models). For example:
```bash
git clone https://github.com/ggerganov/whisper.cpp.git
bash ./models/download-ggml-model.sh base.en
```
Navigate into the directory:
If you wish to convert the Whisper models to ggml format yourself, instructions are in [models/README.md](models/README.md).
```
cd whisper.cpp
```
Then, download one of the Whisper [models](models/README.md) converted in [`ggml` format](#ggml-format). For example:
Now build the [main](examples/main) example and transcribe an audio file like this:
```bash
sh ./models/download-ggml-model.sh base.en
```
Now build the [whisper-cli](examples/cli) example and transcribe an audio file like this:
```bash
# build the project
cmake -B build
cmake --build build --config Release
# build the main example
make
# transcribe an audio file
./build/bin/whisper-cli -f samples/jfk.wav
./main -f samples/jfk.wav
```
---
For a quick demo, simply run `make base.en`.
For a quick demo, simply run `make base.en`:
```java
$ make base.en
cc -I. -O3 -std=c11 -pthread -DGGML_USE_ACCELERATE -c ggml.c -o ggml.o
c++ -I. -I./examples -O3 -std=c++11 -pthread -c whisper.cpp -o whisper.o
c++ -I. -I./examples -O3 -std=c++11 -pthread examples/main/main.cpp whisper.o ggml.o -o main -framework Accelerate
./main -h
usage: ./main [options] file0.wav file1.wav ...
options:
-h, --help [default] show this help message and exit
-t N, --threads N [4 ] number of threads to use during computation
-p N, --processors N [1 ] number of processors to use during computation
-ot N, --offset-t N [0 ] time offset in milliseconds
-on N, --offset-n N [0 ] segment index offset
-d N, --duration N [0 ] duration of audio to process in milliseconds
-mc N, --max-context N [-1 ] maximum number of text context tokens to store
-ml N, --max-len N [0 ] maximum segment length in characters
-sow, --split-on-word [false ] split on word rather than on token
-bo N, --best-of N [2 ] number of best candidates to keep
-bs N, --beam-size N [-1 ] beam size for beam search
-wt N, --word-thold N [0.01 ] word timestamp probability threshold
-et N, --entropy-thold N [2.40 ] entropy threshold for decoder fail
-lpt N, --logprob-thold N [-1.00 ] log probability threshold for decoder fail
-debug, --debug-mode [false ] enable debug mode (eg. dump log_mel)
-tr, --translate [false ] translate from source language to english
-di, --diarize [false ] stereo audio diarization
-tdrz, --tinydiarize [false ] enable tinydiarize (requires a tdrz model)
-nf, --no-fallback [false ] do not use temperature fallback while decoding
-otxt, --output-txt [false ] output result in a text file
-ovtt, --output-vtt [false ] output result in a vtt file
-osrt, --output-srt [false ] output result in a srt file
-olrc, --output-lrc [false ] output result in a lrc file
-owts, --output-words [false ] output script for generating karaoke video
-fp, --font-path [/System/Library/Fonts/Supplemental/Courier New Bold.ttf] path to a monospace font for karaoke video
-ocsv, --output-csv [false ] output result in a CSV file
-oj, --output-json [false ] output result in a JSON file
-of FNAME, --output-file FNAME [ ] output file path (without file extension)
-ps, --print-special [false ] print special tokens
-pc, --print-colors [false ] print colors
-pp, --print-progress [false ] print progress
-nt, --no-timestamps [false ] do not print timestamps
-l LANG, --language LANG [en ] spoken language ('auto' for auto-detect)
-dl, --detect-language [false ] exit after automatically detecting language
--prompt PROMPT [ ] initial prompt
-m FNAME, --model FNAME [models/ggml-base.en.bin] model path
-f FNAME, --file FNAME [ ] input WAV file path
-oved D, --ov-e-device DNAME [CPU ] the OpenVINO device used for encode inference
-ls, --log-score [false ] log best decoder scores of token
bash ./models/download-ggml-model.sh base.en
Downloading ggml model base.en ...
ggml-base.en.bin 100%[========================>] 141.11M 6.34MB/s in 24s
Done! Model 'base.en' saved in 'models/ggml-base.en.bin'
You can now use it like this:
$ ./main -m models/ggml-base.en.bin -f samples/jfk.wav
===============================================
Running base.en on all samples in ./samples ...
===============================================
----------------------------------------------
[+] Running base.en on samples/jfk.wav ... (run 'ffplay samples/jfk.wav' to listen)
----------------------------------------------
whisper_init_from_file: loading model from 'models/ggml-base.en.bin'
whisper_model_load: loading model
whisper_model_load: n_vocab = 51864
whisper_model_load: n_audio_ctx = 1500
whisper_model_load: n_audio_state = 512
whisper_model_load: n_audio_head = 8
whisper_model_load: n_audio_layer = 6
whisper_model_load: n_text_ctx = 448
whisper_model_load: n_text_state = 512
whisper_model_load: n_text_head = 8
whisper_model_load: n_text_layer = 6
whisper_model_load: n_mels = 80
whisper_model_load: f16 = 1
whisper_model_load: type = 2
whisper_model_load: mem required = 215.00 MB (+ 6.00 MB per decoder)
whisper_model_load: kv self size = 5.25 MB
whisper_model_load: kv cross size = 17.58 MB
whisper_model_load: adding 1607 extra tokens
whisper_model_load: model ctx = 140.60 MB
whisper_model_load: model size = 140.54 MB
system_info: n_threads = 4 / 10 | AVX = 0 | AVX2 = 0 | AVX512 = 0 | FMA = 0 | NEON = 1 | ARM_FMA = 1 | F16C = 0 | FP16_VA = 1 | WASM_SIMD = 0 | BLAS = 1 | SSE3 = 0 | VSX = 0 |
main: processing 'samples/jfk.wav' (176000 samples, 11.0 sec), 4 threads, 1 processors, lang = en, task = transcribe, timestamps = 1 ...
[00:00:00.000 --> 00:00:11.000] And so my fellow Americans, ask not what your country can do for you, ask what you can do for your country.
whisper_print_timings: fallbacks = 0 p / 0 h
whisper_print_timings: load time = 113.81 ms
whisper_print_timings: mel time = 15.40 ms
whisper_print_timings: sample time = 11.58 ms / 27 runs ( 0.43 ms per run)
whisper_print_timings: encode time = 266.60 ms / 1 runs ( 266.60 ms per run)
whisper_print_timings: decode time = 66.11 ms / 27 runs ( 2.45 ms per run)
whisper_print_timings: total time = 476.31 ms
```
The command downloads the `base.en` model converted to custom `ggml` format and runs the inference on all `.wav` samples in the folder `samples`.
For detailed usage instructions, run: `./build/bin/whisper-cli -h`
For detailed usage instructions, run: `./main -h`
Note that the [whisper-cli](examples/cli) example currently runs only with 16-bit WAV files, so make sure to convert your input before running the tool.
Note that the [main](examples/main) example currently runs only with 16-bit WAV files, so make sure to convert your input before running the tool.
For example, you can use `ffmpeg` like this:
```bash
```java
ffmpeg -i input.mp3 -ar 16000 -ac 1 -c:a pcm_s16le output.wav
```
@ -104,7 +217,7 @@ ffmpeg -i input.mp3 -ar 16000 -ac 1 -c:a pcm_s16le output.wav
If you want some extra audio samples to play with, simply run:
```
make -j samples
make samples
```
This will download a few more audio files from Wikipedia and convert them to 16-bit WAV format via `ffmpeg`.
@ -112,29 +225,28 @@ This will download a few more audio files from Wikipedia and convert them to 16-
You can download and run the other models as follows:
```
make -j tiny.en
make -j tiny
make -j base.en
make -j base
make -j small.en
make -j small
make -j medium.en
make -j medium
make -j large-v1
make -j large-v2
make -j large-v3
make -j large-v3-turbo
make tiny.en
make tiny
make base.en
make base
make small.en
make small
make medium.en
make medium
make large-v1
make large-v2
make large
```
## Memory usage
| Model | Disk | Mem |
| ------ | ------- | ------- |
| tiny | 75 MiB | ~273 MB |
| base | 142 MiB | ~388 MB |
| small | 466 MiB | ~852 MB |
| medium | 1.5 GiB | ~2.1 GB |
| large | 2.9 GiB | ~3.9 GB |
| Model | Disk | Mem | SHA |
| --- | --- | --- | --- |
| tiny | 75 MB | ~125 MB | `bd577a113a864445d4c299885e0cb97d4ba92b5f` |
| base | 142 MB | ~210 MB | `465707469ff3a37a2b9b8d8f89f2f99de7299dac` |
| small | 466 MB | ~600 MB | `55356645c2b361a969dfd0ef2c5a50d530afd8d5` |
| medium | 1.5 GB | ~1.7 GB | `fd9727b6e1217c2f614f9b698455c4ffd82463b4` |
| large | 2.9 GB | ~3.3 GB | `ad82bf6a9043ceed055076d0fd39f5f186ff8062` |
## Quantization
@ -145,12 +257,11 @@ Here are the steps for creating and using a quantized model:
```bash
# quantize a model with Q5_0 method
cmake -B build
cmake --build build --config Release
./build/bin/quantize models/ggml-base.en.bin models/ggml-base.en-q5_0.bin q5_0
make quantize
./quantize models/ggml-base.en.bin models/ggml-base.en-q5_0.bin q5_0
# run the examples as usual, specifying the quantized model file
./build/bin/whisper-cli -m models/ggml-base.en-q5_0.bin ./samples/gb0.wav
./main -m models/ggml-base.en-q5_0.bin ./samples/gb0.wav
```
## Core ML support
@ -168,8 +279,7 @@ speed-up - more than x3 faster compared with CPU-only execution. Here are the in
- To ensure `coremltools` operates correctly, please confirm that [Xcode](https://developer.apple.com/xcode/) is installed and execute `xcode-select --install` to install the command-line tools.
- Python 3.10 is recommended.
- MacOS Sonoma (version 14) or newer is recommended, as older versions of MacOS might experience issues with transcription hallucination.
- [OPTIONAL] It is recommended to utilize a Python version management system, such as [Miniconda](https://docs.conda.io/en/latest/miniconda.html) for this step:
- [OPTIONAL] It is recommended to utilize a Python version management system, such as [Miniconda](https://docs.conda.io/en/latest/miniconda.html) for this step:
- To create an environment, use: `conda create -n py310-whisper python=3.10 -y`
- To activate the environment, use: `conda activate py310-whisper`
@ -184,6 +294,10 @@ speed-up - more than x3 faster compared with CPU-only execution. Here are the in
- Build `whisper.cpp` with Core ML support:
```bash
# using Makefile
make clean
WHISPER_COREML=1 make -j
# using CMake
cmake -B build -DWHISPER_COREML=1
cmake --build build -j --config Release
@ -191,8 +305,8 @@ speed-up - more than x3 faster compared with CPU-only execution. Here are the in
- Run the examples as usual. For example:
```text
$ ./build/bin/whisper-cli -m models/ggml-base.en.bin -f samples/jfk.wav
```bash
./main -m models/ggml-base.en.bin -f samples/jfk.wav
...
@ -220,23 +334,21 @@ This can result in significant speedup in encoder performance. Here are the inst
- First, setup python virtual env. and install python dependencies. Python 3.10 is recommended.
Windows:
```powershell
```
cd models
python -m venv openvino_conv_env
openvino_conv_env\Scripts\activate
python -m pip install --upgrade pip
pip install -r requirements-openvino.txt
pip install -r openvino-conversion-requirements.txt
```
Linux and macOS:
```bash
```
cd models
python3 -m venv openvino_conv_env
source openvino_conv_env/bin/activate
python -m pip install --upgrade pip
pip install -r requirements-openvino.txt
pip install -r openvino-conversion-requirements.txt
```
- Generate an OpenVINO encoder model. For example, to generate a `base.en` model, use:
@ -245,7 +357,7 @@ This can result in significant speedup in encoder performance. Here are the inst
python convert-whisper-to-openvino.py --model base.en
```
This will produce ggml-base.en-encoder-openvino.xml/.bin IR model files. It's recommended to relocate these to the same folder as `ggml` models, as that
This will produce ggml-base.en-encoder-openvino.xml/.bin IR model files. It's recommended to relocate these to the same folder as ggml models, as that
is the default location that the OpenVINO extension will search at runtime.
- Build `whisper.cpp` with OpenVINO support:
@ -255,28 +367,24 @@ This can result in significant speedup in encoder performance. Here are the inst
After downloading & extracting package onto your development system, set up required environment by sourcing setupvars script. For example:
Linux:
```bash
source /path/to/l_openvino_toolkit_ubuntu22_2023.0.0.10926.b4452d56304_x86_64/setupvars.sh
```
Windows (cmd):
```powershell
```
C:\Path\To\w_openvino_toolkit_windows_2023.0.0.10926.b4452d56304_x86_64\setupvars.bat
```
And then build the project using cmake:
```bash
cmake -B build -DWHISPER_OPENVINO=1
cmake --build build -j --config Release
```
- Run the examples as usual. For example:
```text
$ ./build/bin/whisper-cli -m models/ggml-base.en.bin -f samples/jfk.wav
```bash
./main -m models/ggml-base.en.bin -f samples/jfk.wav
...
@ -292,30 +400,43 @@ This can result in significant speedup in encoder performance. Here are the inst
The first time run on an OpenVINO device is slow, since the OpenVINO framework will compile the IR (Intermediate Representation) model to a device-specific 'blob'. This device-specific blob will get
cached for the next run.
For more information about the Core ML implementation please refer to PR [#1037](https://github.com/ggerganov/whisper.cpp/pull/1037).
## NVIDIA GPU support
## NVIDIA GPU support via cuBLAS
With NVIDIA cards the processing of the models is done efficiently on the GPU via cuBLAS and custom CUDA kernels.
With NVIDIA cards the Encoder processing can to a large extent be offloaded to the GPU through cuBLAS.
First, make sure you have installed `cuda`: https://developer.nvidia.com/cuda-downloads
Now build `whisper.cpp` with CUDA support:
Now build `whisper.cpp` with cuBLAS support:
```
cmake -B build -DGGML_CUDA=1
make clean
WHISPER_CUBLAS=1 make -j
```
## OpenCL GPU support via CLBlast
For cards and integrated GPUs that support OpenCL, the Encoder processing can be largely offloaded to the GPU through CLBlast. This is especially useful for users with AMD APUs or low end devices for up to ~2x speedup.
First, make sure you have installed `CLBlast` for your OS or Distribution: https://github.com/CNugteren/CLBlast
Now build `whisper.cpp` with CLBlast support:
```
Makefile:
cd whisper.cpp
make clean
WHISPER_CLBLAST=1 make -j
CMake:
cd whisper.cpp
cmake -B build -DWHISPER_CLBLAST=ON
cmake --build build -j --config Release
```
## Vulkan GPU support
Cross-vendor solution which allows you to accelerate workload on your GPU.
First, make sure your graphics card driver provides support for Vulkan API.
Now build `whisper.cpp` with Vulkan support:
```
cmake -B build -DGGML_VULKAN=1
cmake --build build -j --config Release
```
Run all the examples as usual.
## BLAS CPU support via OpenBLAS
@ -325,65 +446,105 @@ First, make sure you have installed `openblas`: https://www.openblas.net/
Now build `whisper.cpp` with OpenBLAS support:
```
cmake -B build -DGGML_BLAS=1
cmake --build build -j --config Release
make clean
WHISPER_OPENBLAS=1 make -j
```
## Ascend NPU support
Ascend NPU provides inference acceleration via [`CANN`](https://www.hiascend.com/en/software/cann) and AI cores.
First, check if your Ascend NPU device is supported:
**Verified devices**
| Ascend NPU | Status |
|:-----------------------------:|:-------:|
| Atlas 300T A2 | Support |
Then, make sure you have installed [`CANN toolkit`](https://www.hiascend.com/en/software/cann/community) . The lasted version of CANN is recommanded.
Now build `whisper.cpp` with CANN support:
```
cmake -B build -DGGML_CANN=1
cmake --build build -j --config Release
```
Run the inference examples as usual, for example:
```
./build/bin/whisper-cli -f samples/jfk.wav -m models/ggml-base.en.bin -t 8
```
*Notes:*
- If you have trouble with Ascend NPU device, please create a issue with **[CANN]** prefix/tag.
- If you run successfully with your Ascend NPU device, please help update the table `Verified devices`.
## Installing with Conan
You can install pre-built binaries for whisper.cpp or build it from source using [Conan](https://conan.io/). Use the following command:
```
conan install --requires="whisper-cpp/[*]" --build=missing
```
For detailed instructions on how to use Conan, please refer to the [Conan documentation](https://docs.conan.io/2/).
## Limitations
- Inference only
## Another example
Here is another example of transcribing a [3:24 min speech](https://upload.wikimedia.org/wikipedia/commons/1/1f/George_W_Bush_Columbia_FINAL.ogg)
in about half a minute on a MacBook M1 Pro, using `medium.en` model:
<details>
<summary>Expand to see the result</summary>
```java
$ ./main -m models/ggml-medium.en.bin -f samples/gb1.wav -t 8
whisper_init_from_file: loading model from 'models/ggml-medium.en.bin'
whisper_model_load: loading model
whisper_model_load: n_vocab = 51864
whisper_model_load: n_audio_ctx = 1500
whisper_model_load: n_audio_state = 1024
whisper_model_load: n_audio_head = 16
whisper_model_load: n_audio_layer = 24
whisper_model_load: n_text_ctx = 448
whisper_model_load: n_text_state = 1024
whisper_model_load: n_text_head = 16
whisper_model_load: n_text_layer = 24
whisper_model_load: n_mels = 80
whisper_model_load: f16 = 1
whisper_model_load: type = 4
whisper_model_load: mem required = 1720.00 MB (+ 43.00 MB per decoder)
whisper_model_load: kv self size = 42.00 MB
whisper_model_load: kv cross size = 140.62 MB
whisper_model_load: adding 1607 extra tokens
whisper_model_load: model ctx = 1462.35 MB
whisper_model_load: model size = 1462.12 MB
system_info: n_threads = 8 / 10 | AVX = 0 | AVX2 = 0 | AVX512 = 0 | FMA = 0 | NEON = 1 | ARM_FMA = 1 | F16C = 0 | FP16_VA = 1 | WASM_SIMD = 0 | BLAS = 1 | SSE3 = 0 | VSX = 0 |
main: processing 'samples/gb1.wav' (3179750 samples, 198.7 sec), 8 threads, 1 processors, lang = en, task = transcribe, timestamps = 1 ...
[00:00:00.000 --> 00:00:08.000] My fellow Americans, this day has brought terrible news and great sadness to our country.
[00:00:08.000 --> 00:00:17.000] At nine o'clock this morning, Mission Control in Houston lost contact with our Space Shuttle Columbia.
[00:00:17.000 --> 00:00:23.000] A short time later, debris was seen falling from the skies above Texas.
[00:00:23.000 --> 00:00:29.000] The Columbia's lost. There are no survivors.
[00:00:29.000 --> 00:00:32.000] On board was a crew of seven.
[00:00:32.000 --> 00:00:39.000] Colonel Rick Husband, Lieutenant Colonel Michael Anderson, Commander Laurel Clark,
[00:00:39.000 --> 00:00:48.000] Captain David Brown, Commander William McCool, Dr. Kultna Shavla, and Ilan Ramon,
[00:00:48.000 --> 00:00:52.000] a colonel in the Israeli Air Force.
[00:00:52.000 --> 00:00:58.000] These men and women assumed great risk in the service to all humanity.
[00:00:58.000 --> 00:01:03.000] In an age when space flight has come to seem almost routine,
[00:01:03.000 --> 00:01:07.000] it is easy to overlook the dangers of travel by rocket
[00:01:07.000 --> 00:01:12.000] and the difficulties of navigating the fierce outer atmosphere of the Earth.
[00:01:12.000 --> 00:01:18.000] These astronauts knew the dangers, and they faced them willingly,
[00:01:18.000 --> 00:01:23.000] knowing they had a high and noble purpose in life.
[00:01:23.000 --> 00:01:31.000] Because of their courage and daring and idealism, we will miss them all the more.
[00:01:31.000 --> 00:01:36.000] All Americans today are thinking as well of the families of these men and women
[00:01:36.000 --> 00:01:40.000] who have been given this sudden shock and grief.
[00:01:40.000 --> 00:01:45.000] You're not alone. Our entire nation grieves with you,
[00:01:45.000 --> 00:01:52.000] and those you love will always have the respect and gratitude of this country.
[00:01:52.000 --> 00:01:56.000] The cause in which they died will continue.
[00:01:56.000 --> 00:02:04.000] Mankind is led into the darkness beyond our world by the inspiration of discovery
[00:02:04.000 --> 00:02:11.000] and the longing to understand. Our journey into space will go on.
[00:02:11.000 --> 00:02:16.000] In the skies today, we saw destruction and tragedy.
[00:02:16.000 --> 00:02:22.000] Yet farther than we can see, there is comfort and hope.
[00:02:22.000 --> 00:02:29.000] In the words of the prophet Isaiah, "Lift your eyes and look to the heavens
[00:02:29.000 --> 00:02:35.000] who created all these. He who brings out the starry hosts one by one
[00:02:35.000 --> 00:02:39.000] and calls them each by name."
[00:02:39.000 --> 00:02:46.000] Because of His great power and mighty strength, not one of them is missing.
[00:02:46.000 --> 00:02:55.000] The same Creator who names the stars also knows the names of the seven souls we mourn today.
[00:02:55.000 --> 00:03:01.000] The crew of the shuttle Columbia did not return safely to earth,
[00:03:01.000 --> 00:03:05.000] yet we can pray that all are safely home.
[00:03:05.000 --> 00:03:13.000] May God bless the grieving families, and may God continue to bless America.
[00:03:13.000 --> 00:03:19.000] [Silence]
whisper_print_timings: fallbacks = 1 p / 0 h
whisper_print_timings: load time = 569.03 ms
whisper_print_timings: mel time = 146.85 ms
whisper_print_timings: sample time = 238.66 ms / 553 runs ( 0.43 ms per run)
whisper_print_timings: encode time = 18665.10 ms / 9 runs ( 2073.90 ms per run)
whisper_print_timings: decode time = 13090.93 ms / 549 runs ( 23.85 ms per run)
whisper_print_timings: total time = 32733.52 ms
```
</details>
## Real-time audio input example
This is a naive example of performing real-time inference on audio from your microphone.
The [stream](examples/stream) tool samples the audio every half a second and runs the transcription continuously.
More info is available in [issue #10](https://github.com/ggerganov/whisper.cpp/issues/10).
```bash
cmake -B build
cmake --build build --config Release
./build/bin/stream -m ./models/ggml-base.en.bin -t 8 --step 500 --length 5000
```java
make stream
./stream -m ./models/ggml-base.en.bin -t 8 --step 500 --length 5000
```
https://user-images.githubusercontent.com/1991296/194935793-76afede7-cfa8-48d8-a80f-28ba83be7d09.mp4
@ -393,8 +554,8 @@ https://user-images.githubusercontent.com/1991296/194935793-76afede7-cfa8-48d8-a
Adding the `--print-colors` argument will print the transcribed text using an experimental color coding strategy
to highlight words with high or low confidence:
```bash
./build/bin/whisper-cli -m models/ggml-base.en.bin -f samples/gb0.wav --print-colors
```java
./main -m models/ggml-base.en.bin -f samples/gb0.wav --print-colors
```
<img width="965" alt="image" src="https://user-images.githubusercontent.com/1991296/197356445-311c8643-9397-4e5e-b46e-0b4b4daa2530.png">
@ -403,8 +564,8 @@ to highlight words with high or low confidence:
For example, to limit the line length to a maximum of 16 characters, simply add `-ml 16`:
```text
$ ./build/bin/whisper-cli -m ./models/ggml-base.en.bin -f ./samples/jfk.wav -ml 16
```java
./main -m ./models/ggml-base.en.bin -f ./samples/jfk.wav -ml 16
whisper_model_load: loading model from './models/ggml-base.en.bin'
...
@ -427,8 +588,8 @@ main: processing './samples/jfk.wav' (176000 samples, 11.0 sec), 4 threads, 1 pr
The `--max-len` argument can be used to obtain word-level timestamps. Simply use `-ml 1`:
```text
$ ./build/bin/whisper-cli -m ./models/ggml-base.en.bin -f ./samples/jfk.wav -ml 1
```java
./main -m ./models/ggml-base.en.bin -f ./samples/jfk.wav -ml 1
whisper_model_load: loading model from './models/ggml-base.en.bin'
...
@ -475,7 +636,7 @@ Sample usage:
./models/download-ggml-model.sh small.en-tdrz
# run as usual, adding the "-tdrz" command-line argument
./build/bin/whisper-cli -f ./samples/a13.wav -m ./models/ggml-small.en-tdrz.bin -tdrz
./main -f ./samples/a13.wav -m ./models/ggml-small.en-tdrz.bin -tdrz
...
main: processing './samples/a13.wav' (480000 samples, 30.0 sec), 4 threads, 1 processors, lang = en, task = transcribe, tdrz = 1, timestamps = 1 ...
...
@ -492,14 +653,14 @@ main: processing './samples/a13.wav' (480000 samples, 30.0 sec), 4 threads, 1 pr
## Karaoke-style movie generation (experimental)
The [whisper-cli](examples/cli) example provides support for output of karaoke-style movies, where the
The [main](examples/main) example provides support for output of karaoke-style movies, where the
currently pronounced word is highlighted. Use the `-wts` argument and run the generated bash script.
This requires to have `ffmpeg` installed.
Here are a few _"typical"_ examples:
Here are a few *"typical"* examples:
```bash
./build/bin/whisper-cli -m ./models/ggml-base.en.bin -f ./samples/jfk.wav -owts
```java
./main -m ./models/ggml-base.en.bin -f ./samples/jfk.wav -owts
source ./samples/jfk.wav.wts
ffplay ./samples/jfk.wav.mp4
```
@ -508,8 +669,8 @@ https://user-images.githubusercontent.com/1991296/199337465-dbee4b5e-9aeb-48a3-b
---
```bash
./build/bin/whisper-cli -m ./models/ggml-base.en.bin -f ./samples/mm0.wav -owts
```java
./main -m ./models/ggml-base.en.bin -f ./samples/mm0.wav -owts
source ./samples/mm0.wav.wts
ffplay ./samples/mm0.wav.mp4
```
@ -518,8 +679,8 @@ https://user-images.githubusercontent.com/1991296/199337504-cc8fd233-0cb7-4920-9
---
```bash
./build/bin/whisper-cli -m ./models/ggml-base.en.bin -f ./samples/gb0.wav -owts
```java
./main -m ./models/ggml-base.en.bin -f ./samples/gb0.wav -owts
source ./samples/gb0.wav.wts
ffplay ./samples/gb0.wav.mp4
```
@ -530,10 +691,10 @@ https://user-images.githubusercontent.com/1991296/199337538-b7b0c7a3-2753-4a88-a
## Video comparison of different models
Use the [scripts/bench-wts.sh](https://github.com/ggerganov/whisper.cpp/blob/master/scripts/bench-wts.sh) script to generate a video in the following format:
Use the [extra/bench-wts.sh](https://github.com/ggerganov/whisper.cpp/blob/master/extra/bench-wts.sh) script to generate a video in the following format:
```bash
./scripts/bench-wts.sh samples/jfk.wav
```java
./extra/bench-wts.sh samples/jfk.wav
ffplay ./samples/jfk.wav.all.mp4
```
@ -544,24 +705,25 @@ https://user-images.githubusercontent.com/1991296/223206245-2d36d903-cf8e-4f09-8
## Benchmarks
In order to have an objective comparison of the performance of the inference across different system configurations,
use the [whisper-bench](examples/bench) tool. The tool simply runs the Encoder part of the model and prints how much time it
use the [bench](examples/bench) tool. The tool simply runs the Encoder part of the model and prints how much time it
took to execute it. The results are summarized in the following Github issue:
[Benchmark results](https://github.com/ggerganov/whisper.cpp/issues/89)
Additionally a script to run whisper.cpp with different models and audio files is provided [bench.py](scripts/bench.py).
Additionally a script to run whisper.cpp with different models and audio files is provided [bench.py](bench.py).
You can run it with the following command, by default it will run against any standard model in the models folder.
```bash
python3 scripts/bench.py -f samples/jfk.wav -t 2,4,8 -p 1,2
python3 extra/bench.py -f samples/jfk.wav -t 2,4,8 -p 1,2
```
It is written in python with the intention of being easy to modify and extend for your benchmarking use case.
It outputs a csv file with the results of the benchmarking.
## `ggml` format
## ggml format
The original models are converted to a custom binary format. This allows to pack everything needed into a single file:
@ -576,51 +738,49 @@ or manually from here:
- https://huggingface.co/ggerganov/whisper.cpp
- https://ggml.ggerganov.com
For more details, see the conversion script [models/convert-pt-to-ggml.py](models/convert-pt-to-ggml.py) or [models/README.md](models/README.md).
For more details, see the conversion script [models/convert-pt-to-ggml.py](models/convert-pt-to-ggml.py) or the README
in [models](models).
## [Bindings](https://github.com/ggerganov/whisper.cpp/discussions/categories/bindings)
- [x] Rust: [tazz4843/whisper-rs](https://github.com/tazz4843/whisper-rs) | [#310](https://github.com/ggerganov/whisper.cpp/discussions/310)
- [x] JavaScript: [bindings/javascript](bindings/javascript) | [#309](https://github.com/ggerganov/whisper.cpp/discussions/309)
- [X] Rust: [tazz4843/whisper-rs](https://github.com/tazz4843/whisper-rs) | [#310](https://github.com/ggerganov/whisper.cpp/discussions/310)
- [X] JavaScript: [bindings/javascript](bindings/javascript) | [#309](https://github.com/ggerganov/whisper.cpp/discussions/309)
- React Native (iOS / Android): [whisper.rn](https://github.com/mybigday/whisper.rn)
- [x] Go: [bindings/go](bindings/go) | [#312](https://github.com/ggerganov/whisper.cpp/discussions/312)
- [x] Java:
- [X] Go: [bindings/go](bindings/go) | [#312](https://github.com/ggerganov/whisper.cpp/discussions/312)
- [X] Java:
- [GiviMAD/whisper-jni](https://github.com/GiviMAD/whisper-jni)
- [x] Ruby: [bindings/ruby](bindings/ruby) | [#507](https://github.com/ggerganov/whisper.cpp/discussions/507)
- [x] Objective-C / Swift: [ggerganov/whisper.spm](https://github.com/ggerganov/whisper.spm) | [#313](https://github.com/ggerganov/whisper.cpp/discussions/313)
- [X] Ruby: [bindings/ruby](bindings/ruby) | [#507](https://github.com/ggerganov/whisper.cpp/discussions/507)
- [X] Objective-C / Swift: [ggerganov/whisper.spm](https://github.com/ggerganov/whisper.spm) | [#313](https://github.com/ggerganov/whisper.cpp/discussions/313)
- [exPHAT/SwiftWhisper](https://github.com/exPHAT/SwiftWhisper)
- [x] .NET: | [#422](https://github.com/ggerganov/whisper.cpp/discussions/422)
- [X] .NET: | [#422](https://github.com/ggerganov/whisper.cpp/discussions/422)
- [sandrohanea/whisper.net](https://github.com/sandrohanea/whisper.net)
- [NickDarvey/whisper](https://github.com/NickDarvey/whisper)
- [x] Python: | [#9](https://github.com/ggerganov/whisper.cpp/issues/9)
- [X] Python: | [#9](https://github.com/ggerganov/whisper.cpp/issues/9)
- [stlukey/whispercpp.py](https://github.com/stlukey/whispercpp.py) (Cython)
- [AIWintermuteAI/whispercpp](https://github.com/AIWintermuteAI/whispercpp) (Updated fork of aarnphm/whispercpp)
- [aarnphm/whispercpp](https://github.com/aarnphm/whispercpp) (Pybind11)
- [abdeladim-s/pywhispercpp](https://github.com/abdeladim-s/pywhispercpp) (Pybind11)
- [x] R: [bnosac/audio.whisper](https://github.com/bnosac/audio.whisper)
- [x] Unity: [macoron/whisper.unity](https://github.com/Macoron/whisper.unity)
- [X] R: [bnosac/audio.whisper](https://github.com/bnosac/audio.whisper)
- [X] Unity: [macoron/whisper.unity](https://github.com/Macoron/whisper.unity)
## Examples
There are various examples of using the library for different projects in the [examples](examples) folder.
Some of the examples are even ported to run in the browser using WebAssembly. Check them out!
| Example | Web | Description |
| --------------------------------------------------- | ------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------- |
| [whisper-cli](examples/cli) | [whisper.wasm](examples/whisper.wasm) | Tool for translating and transcribing audio using Whisper |
| [whisper-bench](examples/bench) | [bench.wasm](examples/bench.wasm) | Benchmark the performance of Whisper on your machine |
| [whisper-stream](examples/stream) | [stream.wasm](examples/stream.wasm) | Real-time transcription of raw microphone capture |
| [whisper-command](examples/command) | [command.wasm](examples/command.wasm) | Basic voice assistant example for receiving voice commands from the mic |
| [whisper-server](examples/server) | | HTTP transcription server with OAI-like API |
| [whisper-talk-llama](examples/talk-llama) | | Talk with a LLaMA bot |
| [whisper.objc](examples/whisper.objc) | | iOS mobile application using whisper.cpp |
| [whisper.swiftui](examples/whisper.swiftui) | | SwiftUI iOS / macOS application using whisper.cpp |
| [whisper.android](examples/whisper.android) | | Android mobile application using whisper.cpp |
| [whisper.nvim](examples/whisper.nvim) | | Speech-to-text plugin for Neovim |
| [generate-karaoke.sh](examples/generate-karaoke.sh) | | Helper script to easily [generate a karaoke video](https://youtu.be/uj7hVta4blM) of raw audio capture |
| [livestream.sh](examples/livestream.sh) | | [Livestream audio transcription](https://github.com/ggerganov/whisper.cpp/issues/185) |
| [yt-wsp.sh](examples/yt-wsp.sh) | | Download + transcribe and/or translate any VOD [(original)](https://gist.github.com/DaniruKun/96f763ec1a037cc92fe1a059b643b818) |
| [wchess](examples/wchess) | [wchess.wasm](examples/wchess) | Voice-controlled chess |
| Example | Web | Description |
| --- | --- | --- |
| [main](examples/main) | [whisper.wasm](examples/whisper.wasm) | Tool for translating and transcribing audio using Whisper |
| [bench](examples/bench) | [bench.wasm](examples/bench.wasm) | Benchmark the performance of Whisper on your machine |
| [stream](examples/stream) | [stream.wasm](examples/stream.wasm) | Real-time transcription of raw microphone capture |
| [command](examples/command) | [command.wasm](examples/command.wasm) | Basic voice assistant example for receiving voice commands from the mic |
| [talk](examples/talk) | [talk.wasm](examples/talk.wasm) | Talk with a GPT-2 bot |
| [talk-llama](examples/talk-llama) | | Talk with a LLaMA bot |
| [whisper.objc](examples/whisper.objc) | | iOS mobile application using whisper.cpp |
| [whisper.swiftui](examples/whisper.swiftui) | | SwiftUI iOS / macOS application using whisper.cpp |
| [whisper.android](examples/whisper.android) | | Android mobile application using whisper.cpp |
| [whisper.nvim](examples/whisper.nvim) | | Speech-to-text plugin for Neovim |
| [generate-karaoke.sh](examples/generate-karaoke.sh) | | Helper script to easily [generate a karaoke video](https://youtu.be/uj7hVta4blM) of raw audio capture |
| [livestream.sh](examples/livestream.sh) | | [Livestream audio transcription](https://github.com/ggerganov/whisper.cpp/issues/185) |
| [yt-wsp.sh](examples/yt-wsp.sh) | | Download + transcribe and/or translate any VOD [(original)](https://gist.github.com/DaniruKun/96f763ec1a037cc92fe1a059b643b818) |
## [Discussions](https://github.com/ggerganov/whisper.cpp/discussions)

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@ -1,249 +0,0 @@
# whisper.cpp for SYCL
[Background](#background)
[OS](#os)
[Intel GPU](#intel-gpu)
[Linux](#linux)
[Environment Variable](#environment-variable)
[Known Issue](#known-issue)
[Todo](#todo)
## Background
SYCL is a higher-level programming model to improve programming productivity on various hardware accelerators<72>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 re-inventing the wheel, this code refers 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<EFBFBD> DPC++ Compatibility Tool](https://www.intel.com/content/www/us/en/developer/tools/oneapi/dpc-compatibility-tool.html)) migrate to SYCL.
The whisper.cpp for SYCL is used to support Intel GPUs.
For Intel CPU, recommend to use whisper.cpp for X86 (Intel MKL build).
## OS
|OS|Status|Verified|
|-|-|-|
|Linux|Support|Ubuntu 22.04|
|Windows|Ongoing| |
## Intel GPU
|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|
|Intel built-in Arc GPU| Support| built-in Arc GPU in Meteor Lake|
|Intel iGPU| Support| iGPU in i5-1250P, i7-1165G7|
## 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.
```
sudo usermod -aG render username
sudo usermod -aG video username
```
Note: re-login to enable it.
c. Check
```
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<65> oneAPI Base toolkit.
a. Please follow the procedure in [Get the Intel<65> 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
```
source /opt/intel/oneapi/setvars.sh
sycl-ls
```
There should be one or more level-zero devices. 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:
```
mkdir -p build
cd build
source /opt/intel/oneapi/setvars.sh
#for FP16
#cmake .. -DWHISPER_SYCL=ON -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx -DWHISPER_SYCL_F16=ON
#for FP32
cmake .. -DWHISPER_SYCL=ON -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx
#build example/main only
#cmake --build . --config Release --target main
#build all binary
cmake --build . --config Release -v
```
or
```
./examples/sycl/build.sh
```
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**
2. Enable oneAPI running environment
```
source /opt/intel/oneapi/setvars.sh
```
3. List device ID
Run without parameter:
```
./build/bin/ls-sycl-device
or
./build/bin/main
```
Check the ID in startup log, like:
```
found 4 SYCL devices:
Device 0: Intel(R) Arc(TM) A770 Graphics, compute capability 1.3,
max compute_units 512, max work group size 1024, max sub group size 32, global mem size 16225243136
Device 1: Intel(R) FPGA Emulation Device, compute capability 1.2,
max compute_units 24, max work group size 67108864, max sub group size 64, global mem size 67065057280
Device 2: 13th Gen Intel(R) Core(TM) i7-13700K, compute capability 3.0,
max compute_units 24, max work group size 8192, max sub group size 64, global mem size 67065057280
Device 3: Intel(R) Arc(TM) A770 Graphics, compute capability 3.0,
max compute_units 512, max work group size 1024, max sub group size 32, global mem size 16225243136
```
|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. Set device ID and execute whisper.cpp
Set device ID = 0 by **GGML_SYCL_DEVICE=0**
```
GGML_SYCL_DEVICE=0 ./build/bin/main -m models/ggml-base.en.bin -f samples/jfk.wav
```
or run by script:
```
./examples/sycl/run_whisper.sh
```
5. Check the device ID in output
Like:
```
Using device **0** (Intel(R) Arc(TM) A770 Graphics) as main device
```
## Environment Variable
#### Build
|Name|Value|Function|
|-|-|-|
|WHISPER_SYCL|ON (mandatory)|Enable build with SYCL code path. <br>For FP32/FP16, WHISPER_SYCL=ON is mandatory.|
|WHISPER_SYCL_F16|ON (optional)|Enable FP16 build with SYCL code path.For FP32, do not set it.|
|CMAKE_C_COMPILER|icx|Use icx compiler for SYCL code path|
|CMAKE_CXX_COMPILER|icpx|use icpx for SYCL code path|
#### Running
|Name|Value|Function|
|-|-|-|
|GGML_SYCL_DEVICE|0 (default) or 1|Set the device id used. Check the device ids by default running output|
|GGML_SYCL_DEBUG|0 (default) or 1|Enable log function by macro: GGML_SYCL_DEBUG|
## Known Issue
- 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`.
- 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**.
## Todo
- Support to build in Windows.
- Support multiple cards.

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@ -1,5 +0,0 @@
module whisper [system] {
header "whisper.h"
link "whisper"
export *
}

View File

@ -1,4 +0,0 @@
#pragma once
#include <whisper.h>

View File

@ -1,31 +1,9 @@
ifndef UNAME_S
UNAME_S := $(shell uname -s)
endif
ifndef UNAME_P
UNAME_P := $(shell uname -p)
endif
ifndef UNAME_M
UNAME_M := $(shell uname -m)
endif
GGML_METAL_PATH_RESOURCES := $(abspath ../..)
BUILD_DIR := build
MODELS_DIR := models
EXAMPLES_DIR := $(wildcard examples/*)
INCLUDE_PATH := $(abspath ../../include):$(abspath ../../ggml/include)
INCLUDE_PATH := $(abspath ../..)
LIBRARY_PATH := $(abspath ../..)
ifeq ($(GGML_CUDA),1)
LIBRARY_PATH := $(LIBRARY_PATH):$(CUDA_PATH)/targets/$(UNAME_M)-linux/lib/
BUILD_FLAGS := -ldflags "-extldflags '-lcudart -lcuda -lcublas'"
endif
ifeq ($(UNAME_S),Darwin)
EXT_LDFLAGS := -framework Foundation -framework Metal -framework MetalKit
endif
all: clean whisper examples
whisper: mkdir
@ -33,13 +11,8 @@ whisper: mkdir
@${MAKE} -C ../.. libwhisper.a
test: model-small whisper modtidy
ifeq ($(UNAME_S),Darwin)
@C_INCLUDE_PATH=${INCLUDE_PATH} LIBRARY_PATH=${LIBRARY_PATH} GGML_METAL_PATH_RESOURCES=${GGML_METAL_PATH_RESOURCES} go test -ldflags "-extldflags '$(EXT_LDFLAGS)'" -v .
@C_INCLUDE_PATH=${INCLUDE_PATH} LIBRARY_PATH=${LIBRARY_PATH} GGML_METAL_PATH_RESOURCES=${GGML_METAL_PATH_RESOURCES} go test -ldflags "-extldflags '$(EXT_LDFLAGS)'" -v ./pkg/whisper/...
else
@C_INCLUDE_PATH=${INCLUDE_PATH} LIBRARY_PATH=${LIBRARY_PATH} go test -v .
@C_INCLUDE_PATH=${INCLUDE_PATH} LIBRARY_PATH=${LIBRARY_PATH} go test -v ./pkg/whisper/...
endif
examples: $(EXAMPLES_DIR)
@ -48,11 +21,7 @@ model-small: mkdir examples/go-model-download
$(EXAMPLES_DIR): mkdir whisper modtidy
@echo Build example $(notdir $@)
ifeq ($(UNAME_S),Darwin)
@C_INCLUDE_PATH=${INCLUDE_PATH} LIBRARY_PATH=${LIBRARY_PATH} GGML_METAL_PATH_RESOURCES=${GGML_METAL_PATH_RESOURCES} go build ${BUILD_FLAGS} -ldflags "-extldflags '$(EXT_LDFLAGS)'" -o ${BUILD_DIR}/$(notdir $@) ./$@
else
@C_INCLUDE_PATH=${INCLUDE_PATH} LIBRARY_PATH=${LIBRARY_PATH} go build ${BUILD_FLAGS} -o ${BUILD_DIR}/$(notdir $@) ./$@
endif
mkdir:
@echo Mkdir ${BUILD_DIR}

View File

@ -62,12 +62,6 @@ This will compile a static `libwhisper.a` in a `build` folder, download a model
make examples
```
To build using cuda support add `GGML_CUDA=1`:
```bash
GGML_CUDA=1 make examples
```
The examples are placed in the `build` directory. Once built, you can download all the models with the following command:
```bash

View File

@ -24,7 +24,7 @@ const (
var (
// The models which will be downloaded, if no model is specified as an argument
modelNames = []string{"ggml-tiny.en", "ggml-tiny", "ggml-base.en", "ggml-base", "ggml-small.en", "ggml-small", "ggml-medium.en", "ggml-medium", "ggml-large-v1", "ggml-large-v2", "ggml-large-v3", "large-v3-turbo"}
modelNames = []string{"ggml-tiny.en", "ggml-tiny", "ggml-base.en", "ggml-base", "ggml-small.en", "ggml-small", "ggml-medium.en", "ggml-medium", "ggml-large-v1", "ggml-large-v2", "ggml-large"}
)
var (

View File

@ -68,6 +68,10 @@ func (flags *Flags) GetOut() string {
return strings.ToLower(flags.Lookup("out").Value.String())
}
func (flags *Flags) IsSpeedup() bool {
return flags.Lookup("speedup").Value.String() == "true"
}
func (flags *Flags) IsTokens() bool {
return flags.Lookup("tokens").Value.String() == "true"
}
@ -107,6 +111,10 @@ func (flags *Flags) SetParams(context whisper.Context) error {
fmt.Fprintf(flags.Output(), "Setting duration to %v\n", duration)
context.SetDuration(duration)
}
if flags.IsSpeedup() {
fmt.Fprintf(flags.Output(), "Setting speedup to true\n")
context.SetSpeedup(true)
}
if threads := flags.GetThreads(); threads != 0 {
fmt.Fprintf(flags.Output(), "Setting threads to %d\n", threads)
context.SetThreads(threads)
@ -138,6 +146,7 @@ func registerFlags(flag *Flags) {
flag.Duration("offset", 0, "Time offset")
flag.Duration("duration", 0, "Duration of audio to process")
flag.Uint("threads", 0, "Number of threads to use")
flag.Bool("speedup", false, "Enable speedup")
flag.Uint("max-len", 0, "Maximum segment length in characters")
flag.Uint("max-tokens", 0, "Maximum tokens per segment")
flag.Float64("word-thold", 0, "Maximum segment score")

View File

@ -1,10 +1,10 @@
module github.com/ggerganov/whisper.cpp/bindings/go
go 1.23
go 1.19
require (
github.com/go-audio/wav v1.1.0
github.com/stretchr/testify v1.9.0
github.com/stretchr/testify v1.8.1
)
require (

View File

@ -1,3 +1,4 @@
github.com/davecgh/go-spew v1.1.0/go.mod h1:J7Y8YcW2NihsgmVo/mv3lAwl/skON4iLHjSsI+c5H38=
github.com/davecgh/go-spew v1.1.1 h1:vj9j/u1bqnvCEfJOwUhtlOARqs3+rkHYY13jYWTU97c=
github.com/davecgh/go-spew v1.1.1/go.mod h1:J7Y8YcW2NihsgmVo/mv3lAwl/skON4iLHjSsI+c5H38=
github.com/go-audio/audio v1.0.0 h1:zS9vebldgbQqktK4H0lUqWrG8P0NxCJVqcj7ZpNnwd4=
@ -8,9 +9,15 @@ github.com/go-audio/wav v1.1.0 h1:jQgLtbqBzY7G+BM8fXF7AHUk1uHUviWS4X39d5rsL2g=
github.com/go-audio/wav v1.1.0/go.mod h1:mpe9qfwbScEbkd8uybLuIpTgHyrISw/OTuvjUW2iGtE=
github.com/pmezard/go-difflib v1.0.0 h1:4DBwDE0NGyQoBHbLQYPwSUPoCMWR5BEzIk/f1lZbAQM=
github.com/pmezard/go-difflib v1.0.0/go.mod h1:iKH77koFhYxTK1pcRnkKkqfTogsbg7gZNVY4sRDYZ/4=
github.com/stretchr/testify v1.9.0 h1:HtqpIVDClZ4nwg75+f6Lvsy/wHu+3BoSGCbBAcpTsTg=
github.com/stretchr/testify v1.9.0/go.mod h1:r2ic/lqez/lEtzL7wO/rwa5dbSLXVDPFyf8C91i36aY=
github.com/stretchr/objx v0.1.0/go.mod h1:HFkY916IF+rwdDfMAkV7OtwuqBVzrE8GR6GFx+wExME=
github.com/stretchr/objx v0.4.0/go.mod h1:YvHI0jy2hoMjB+UWwv71VJQ9isScKT/TqJzVSSt89Yw=
github.com/stretchr/objx v0.5.0/go.mod h1:Yh+to48EsGEfYuaHDzXPcE3xhTkx73EhmCGUpEOglKo=
github.com/stretchr/testify v1.7.1/go.mod h1:6Fq8oRcR53rry900zMqJjRRixrwX3KX962/h/Wwjteg=
github.com/stretchr/testify v1.8.0/go.mod h1:yNjHg4UonilssWZ8iaSj1OCr/vHnekPRkoO+kdMU+MU=
github.com/stretchr/testify v1.8.1 h1:w7B6lhMri9wdJUVmEZPGGhZzrYTPvgJArz7wNPgYKsk=
github.com/stretchr/testify v1.8.1/go.mod h1:w2LPCIKwWwSfY2zedu0+kehJoqGctiVI29o6fzry7u4=
gopkg.in/check.v1 v0.0.0-20161208181325-20d25e280405 h1:yhCVgyC4o1eVCa2tZl7eS0r+SDo693bJlVdllGtEeKM=
gopkg.in/check.v1 v0.0.0-20161208181325-20d25e280405/go.mod h1:Co6ibVJAznAaIkqp8huTwlJQCZ016jof/cbN4VW5Yz0=
gopkg.in/yaml.v3 v3.0.0-20200313102051-9f266ea9e77c/go.mod h1:K4uyk7z7BCEPqu6E+C64Yfv1cQ7kz7rIZviUmN+EgEM=
gopkg.in/yaml.v3 v3.0.1 h1:fxVm/GzAzEWqLHuvctI91KS9hhNmmWOoWu0XTYJS7CA=
gopkg.in/yaml.v3 v3.0.1/go.mod h1:K4uyk7z7BCEPqu6E+C64Yfv1cQ7kz7rIZviUmN+EgEM=

View File

@ -47,6 +47,10 @@ func (p *Params) SetPrintTimestamps(v bool) {
p.print_timestamps = toBool(v)
}
func (p *Params) SetSpeedup(v bool) {
p.speed_up = toBool(v)
}
// Set language id
func (p *Params) SetLanguage(lang int) error {
if lang == -1 {
@ -119,33 +123,6 @@ func (p *Params) SetAudioCtx(n int) {
p.audio_ctx = C.int(n)
}
func (p *Params) SetMaxContext(n int) {
p.n_max_text_ctx = C.int(n)
}
func (p *Params) SetBeamSize(n int) {
p.beam_search.beam_size = C.int(n)
}
func (p *Params) SetEntropyThold(t float32) {
p.entropy_thold = C.float(t)
}
func (p *Params) SetTemperature(t float32) {
p.temperature = C.float(t)
}
// Sets the fallback temperature incrementation
// Pass -1.0 to disable this feature
func (p *Params) SetTemperatureFallback(t float32) {
p.temperature_inc = C.float(t)
}
// Set initial prompt
func (p *Params) SetInitialPrompt(prompt string) {
p.initial_prompt = C.CString(prompt)
}
///////////////////////////////////////////////////////////////////////////////
// PRIVATE METHODS
@ -170,11 +147,6 @@ func (p *Params) String() string {
str += fmt.Sprintf(" offset_ms=%d", p.offset_ms)
str += fmt.Sprintf(" duration_ms=%d", p.duration_ms)
str += fmt.Sprintf(" audio_ctx=%d", p.audio_ctx)
str += fmt.Sprintf(" initial_prompt=%s", C.GoString(p.initial_prompt))
str += fmt.Sprintf(" entropy_thold=%f", p.entropy_thold)
str += fmt.Sprintf(" temperature=%f", p.temperature)
str += fmt.Sprintf(" temperature_inc=%f", p.temperature_inc)
str += fmt.Sprintf(" beam_size=%d", p.beam_search.beam_size)
if p.translate {
str += " translate"
}
@ -199,6 +171,9 @@ func (p *Params) String() string {
if p.token_timestamps {
str += " token_timestamps"
}
if p.speed_up {
str += " speed_up"
}
return str + ">"
}

View File

@ -76,6 +76,11 @@ func (context *context) SetTranslate(v bool) {
context.params.SetTranslate(v)
}
// Set speedup flag
func (context *context) SetSpeedup(v bool) {
context.params.SetSpeedup(v)
}
func (context *context) SetSplitOnWord(v bool) {
context.params.SetSplitOnWord(v)
}
@ -125,37 +130,6 @@ func (context *context) SetAudioCtx(n uint) {
context.params.SetAudioCtx(int(n))
}
// Set maximum number of text context tokens to store
func (context *context) SetMaxContext(n int) {
context.params.SetMaxContext(n)
}
// Set Beam Size
func (context *context) SetBeamSize(n int) {
context.params.SetBeamSize(n)
}
// Set Entropy threshold
func (context *context) SetEntropyThold(t float32) {
context.params.SetEntropyThold(t)
}
// Set Temperature
func (context *context) SetTemperature(t float32) {
context.params.SetTemperature(t)
}
// Set the fallback temperature incrementation
// Pass -1.0 to disable this feature
func (context *context) SetTemperatureFallback(t float32) {
context.params.SetTemperatureFallback(t)
}
// Set initial prompt
func (context *context) SetInitialPrompt(prompt string) {
context.params.SetInitialPrompt(prompt)
}
// ResetTimings resets the mode timings. Should be called before processing
func (context *context) ResetTimings() {
context.model.ctx.Whisper_reset_timings()

View File

@ -4,90 +4,52 @@ import (
"os"
"testing"
"github.com/ggerganov/whisper.cpp/bindings/go/pkg/whisper"
"github.com/go-audio/wav"
// Packages
whisper "github.com/ggerganov/whisper.cpp/bindings/go/pkg/whisper"
assert "github.com/stretchr/testify/assert"
)
func TestSetLanguage(t *testing.T) {
assert := assert.New(t)
const (
ModelPath = "../../models/ggml-tiny.bin"
SamplePath = "../../samples/jfk.wav"
)
func Test_Whisper_000(t *testing.T) {
assert := assert.New(t)
if _, err := os.Stat(ModelPath); os.IsNotExist(err) {
t.Skip("Skipping test, model not found:", ModelPath)
}
if _, err := os.Stat(SamplePath); os.IsNotExist(err) {
t.Skip("Skipping test, sample not found:", SamplePath)
}
// Load model
model, err := whisper.New(ModelPath)
assert.NoError(err)
assert.NotNil(model)
assert.NoError(model.Close())
t.Log("languages=", model.Languages())
}
func Test_Whisper_001(t *testing.T) {
assert := assert.New(t)
if _, err := os.Stat(ModelPath); os.IsNotExist(err) {
t.Skip("Skipping test, model not found:", ModelPath)
}
if _, err := os.Stat(SamplePath); os.IsNotExist(err) {
t.Skip("Skipping test, sample not found:", SamplePath)
}
// Load model
model, err := whisper.New(ModelPath)
assert.NoError(err)
assert.NotNil(model)
defer model.Close()
context, err := model.NewContext()
// Get context for decoding
ctx, err := model.NewContext()
assert.NoError(err)
assert.NotNil(ctx)
// This returns an error since
// the model 'models/ggml-small.en.bin'
// that is loaded is not multilingual
err = context.SetLanguage("en")
assert.Error(err)
}
func TestContextModelIsMultilingual(t *testing.T) {
assert := assert.New(t)
model, err := whisper.New(ModelPath)
assert.NoError(err)
assert.NotNil(model)
defer model.Close()
context, err := model.NewContext()
assert.NoError(err)
isMultilingual := context.IsMultilingual()
// This returns false since
// the model 'models/ggml-small.en.bin'
// that is loaded is not multilingual
assert.False(isMultilingual)
}
func TestLanguage(t *testing.T) {
assert := assert.New(t)
model, err := whisper.New(ModelPath)
assert.NoError(err)
assert.NotNil(model)
defer model.Close()
context, err := model.NewContext()
assert.NoError(err)
// This always returns en since
// the model 'models/ggml-small.en.bin'
// that is loaded is not multilingual
expectedLanguage := "en"
actualLanguage := context.Language()
assert.Equal(expectedLanguage, actualLanguage)
}
func TestProcess(t *testing.T) {
assert := assert.New(t)
fh, err := os.Open(SamplePath)
assert.NoError(err)
defer fh.Close()
// Decode the WAV file - load the full buffer
dec := wav.NewDecoder(fh)
buf, err := dec.FullPCMBuffer()
assert.NoError(err)
assert.Equal(uint16(1), dec.NumChans)
data := buf.AsFloat32Buffer().Data
model, err := whisper.New(ModelPath)
assert.NoError(err)
assert.NotNil(model)
defer model.Close()
context, err := model.NewContext()
assert.NoError(err)
err = context.Process(data, nil, nil)
assert.NoError(err)
}

View File

@ -38,22 +38,17 @@ type Context interface {
IsMultilingual() bool // Return true if the model is multilingual.
Language() string // Get language
SetOffset(time.Duration) // Set offset
SetDuration(time.Duration) // Set duration
SetThreads(uint) // Set number of threads to use
SetSplitOnWord(bool) // Set split on word flag
SetTokenThreshold(float32) // Set timestamp token probability threshold
SetTokenSumThreshold(float32) // Set timestamp token sum probability threshold
SetMaxSegmentLength(uint) // Set max segment length in characters
SetTokenTimestamps(bool) // Set token timestamps flag
SetMaxTokensPerSegment(uint) // Set max tokens per segment (0 = no limit)
SetAudioCtx(uint) // Set audio encoder context
SetMaxContext(n int) // Set maximum number of text context tokens to store
SetBeamSize(n int) // Set Beam Size
SetEntropyThold(t float32) // Set Entropy threshold
SetInitialPrompt(prompt string) // Set initial prompt
SetTemperature(t float32) // Set temperature
SetTemperatureFallback(t float32) // Set temperature incrementation
SetOffset(time.Duration) // Set offset
SetDuration(time.Duration) // Set duration
SetThreads(uint) // Set number of threads to use
SetSpeedup(bool) // Set speedup flag
SetSplitOnWord(bool) // Set split on word flag
SetTokenThreshold(float32) // Set timestamp token probability threshold
SetTokenSumThreshold(float32) // Set timestamp token sum probability threshold
SetMaxSegmentLength(uint) // Set max segment length in characters
SetTokenTimestamps(bool) // Set token timestamps flag
SetMaxTokensPerSegment(uint) // Set max tokens per segment (0 = no limit)
SetAudioCtx(uint) // Set audio encoder context
// Process mono audio data and return any errors.
// If defined, newly generated segments are passed to the

View File

@ -1,91 +0,0 @@
package whisper_test
import (
"testing"
"github.com/ggerganov/whisper.cpp/bindings/go/pkg/whisper"
assert "github.com/stretchr/testify/assert"
)
func TestNew(t *testing.T) {
assert := assert.New(t)
t.Run("valid model path", func(t *testing.T) {
model, err := whisper.New(ModelPath)
assert.NoError(err)
assert.NotNil(model)
defer model.Close()
})
t.Run("invalid model path", func(t *testing.T) {
invalidModelPath := "invalid-model-path.bin"
model, err := whisper.New(invalidModelPath)
assert.Error(err)
assert.Nil(model)
})
}
func TestClose(t *testing.T) {
assert := assert.New(t)
model, err := whisper.New(ModelPath)
assert.NoError(err)
assert.NotNil(model)
err = model.Close()
assert.NoError(err)
}
func TestNewContext(t *testing.T) {
assert := assert.New(t)
model, err := whisper.New(ModelPath)
assert.NoError(err)
assert.NotNil(model)
defer model.Close()
context, err := model.NewContext()
assert.NoError(err)
assert.NotNil(context)
}
func TestIsMultilingual(t *testing.T) {
assert := assert.New(t)
model, err := whisper.New(ModelPath)
assert.NoError(err)
assert.NotNil(model)
defer model.Close()
isMultilingual := model.IsMultilingual()
// This returns false since
// the model 'models/ggml-small.en.bin'
// that is loaded is not multilingual
assert.False(isMultilingual)
}
func TestLanguages(t *testing.T) {
assert := assert.New(t)
model, err := whisper.New(ModelPath)
assert.NoError(err)
assert.NotNil(model)
defer model.Close()
expectedLanguages := []string{
"en", "zh", "de", "es", "ru", "ko", "fr", "ja", "pt", "tr", "pl",
"ca", "nl", "ar", "sv", "it", "id", "hi", "fi", "vi", "he", "uk",
"el", "ms", "cs", "ro", "da", "hu", "ta", "no", "th", "ur", "hr",
"bg", "lt", "la", "mi", "ml", "cy", "sk", "te", "fa", "lv", "bn",
"sr", "az", "sl", "kn", "et", "mk", "br", "eu", "is", "hy", "ne",
"mn", "bs", "kk", "sq", "sw", "gl", "mr", "pa", "si", "km", "sn",
"yo", "so", "af", "oc", "ka", "be", "tg", "sd", "gu", "am", "yi",
"lo", "uz", "fo", "ht", "ps", "tk", "nn", "mt", "sa", "lb", "my",
"bo", "tl", "mg", "as", "tt", "haw", "ln", "ha", "ba", "jw", "su",
}
actualLanguages := model.Languages()
assert.Equal(expectedLanguages, actualLanguages)
}

View File

@ -1,6 +0,0 @@
package whisper_test
const (
ModelPath = "../../models/ggml-small.en.bin"
SamplePath = "../../samples/jfk.wav"
)

View File

@ -9,8 +9,8 @@ import (
// CGO
/*
#cgo LDFLAGS: -lwhisper -lm -lstdc++ -fopenmp
#cgo darwin LDFLAGS: -framework Accelerate -framework Metal -framework Foundation -framework CoreGraphics
#cgo LDFLAGS: -lwhisper -lm -lstdc++
#cgo darwin LDFLAGS: -framework Accelerate
#include <whisper.h>
#include <stdlib.h>

1
bindings/ios Submodule

Submodule bindings/ios added at 9752de4100

View File

@ -67,5 +67,5 @@ copy /y ..\..\build\bin\Release\whisper.dll build\generated\resources\main\win32
## License
The license for the Java bindings is the same as the license for the rest of the whisper.cpp project, which is the MIT License. See the `LICENSE` file for more details.
The license for the Go bindings is the same as the license for the rest of the whisper.cpp project, which is the MIT License. See the `LICENSE` file for more details.

View File

@ -9,7 +9,6 @@ archivesBaseName = 'whispercpp'
group = 'io.github.ggerganov'
version = '1.4.0'
sourceCompatibility = 1.8
targetCompatibility = 1.8

View File

@ -2,7 +2,6 @@ package io.github.ggerganov.whispercpp;
import com.sun.jna.Native;
import com.sun.jna.Pointer;
import io.github.ggerganov.whispercpp.bean.WhisperSegment;
import io.github.ggerganov.whispercpp.params.WhisperContextParams;
import io.github.ggerganov.whispercpp.params.WhisperFullParams;
import io.github.ggerganov.whispercpp.params.WhisperSamplingStrategy;
@ -10,8 +9,6 @@ import io.github.ggerganov.whispercpp.params.WhisperSamplingStrategy;
import java.io.File;
import java.io.FileNotFoundException;
import java.io.IOException;
import java.util.ArrayList;
import java.util.List;
/**
* Before calling most methods, you must call `initContext(modelPath)` to initialise the `ctx` Pointer.
@ -163,28 +160,6 @@ public class WhisperCpp implements AutoCloseable {
return str.toString().trim();
}
public List<WhisperSegment> fullTranscribeWithTime(WhisperFullParams whisperParams, float[] audioData) throws IOException {
if (ctx == null) {
throw new IllegalStateException("Model not initialised");
}
if (lib.whisper_full(ctx, whisperParams, audioData, audioData.length) != 0) {
throw new IOException("Failed to process audio");
}
int nSegments = lib.whisper_full_n_segments(ctx);
List<WhisperSegment> segments= new ArrayList<>(nSegments);
for (int i = 0; i < nSegments; i++) {
long t0 = lib.whisper_full_get_segment_t0(ctx, i);
String text = lib.whisper_full_get_segment_text(ctx, i);
long t1 = lib.whisper_full_get_segment_t1(ctx, i);
segments.add(new WhisperSegment(t0,t1,text));
}
return segments;
}
// public int getTextSegmentCount(Pointer ctx) {
// return lib.whisper_full_n_segments(ctx);

View File

@ -20,7 +20,7 @@ public interface WhisperCppJnaLibrary extends Library {
* @return Whisper context on success, null on failure
*/
Pointer whisper_init_from_file(String path_model);
/**
* Provides default params which can be used with `whisper_init_from_file_with_params()` etc.
* Because this function allocates memory for the params, the caller must call either:
@ -304,6 +304,14 @@ public interface WhisperCppJnaLibrary extends Library {
/** Language id associated with the provided state */
int whisper_full_lang_id_from_state(Pointer state);
/**
* Convert RAW PCM audio to log mel spectrogram but applies a Phase Vocoder to speed up the audio x2.
* The resulting spectrogram is stored inside the default state of the provided whisper context.
* @return 0 on success
*/
int whisper_pcm_to_mel_phase_vocoder(Pointer ctx, final float[] samples, int n_samples, int n_threads);
int whisper_pcm_to_mel_phase_vocoder_with_state(Pointer ctx, Pointer state, final float[] samples, int n_samples, int n_threads);
/** Get the start time of the specified segment. */
long whisper_full_get_segment_t0(Pointer ctx, int i_segment);

View File

@ -1,47 +0,0 @@
package io.github.ggerganov.whispercpp.bean;
/**
* Created by litonglinux@qq.com on 10/21/2023_7:48 AM
*/
public class WhisperSegment {
private long start, end;
private String sentence;
public WhisperSegment() {
}
public WhisperSegment(long start, long end, String sentence) {
this.start = start;
this.end = end;
this.sentence = sentence;
}
public long getStart() {
return start;
}
public long getEnd() {
return end;
}
public String getSentence() {
return sentence;
}
public void setStart(long start) {
this.start = start;
}
public void setEnd(long end) {
this.end = end;
}
public void setSentence(String sentence) {
this.sentence = sentence;
}
@Override
public String toString() {
return "[" + start + " --> " + end + "]:" + sentence;
}
}

View File

@ -58,9 +58,6 @@ public class WhisperFullParams extends Structure {
no_context = enable ? CBool.FALSE : CBool.TRUE;
}
/** Generate timestamps or not? */
public CBool no_timestamps;
/** Flag to force single segment output (useful for streaming). (default = false) */
public CBool single_segment;
@ -129,6 +126,14 @@ public class WhisperFullParams extends Structure {
/** Maximum tokens per segment (0, default = no limit) */
public int max_tokens;
/** Flag to speed up the audio by 2x using Phase Vocoder. (default = false) */
public CBool speed_up;
/** Flag to speed up the audio by 2x using Phase Vocoder. (default = false) */
public void speedUp(boolean enable) {
speed_up = enable ? CBool.TRUE : CBool.FALSE;
}
/** Overwrite the audio context size (0 = use default). */
public int audio_ctx;
@ -140,9 +145,6 @@ public class WhisperFullParams extends Structure {
tdrz_enable = enable ? CBool.TRUE : CBool.FALSE;
}
/** Regular expression matching tokens to suppress. */
public String suppress_regex;
/** Tokens to provide to the whisper decoder as an initial prompt.
* These are prepended to any existing text context from a previous call. */
public String initial_prompt;
@ -181,11 +183,11 @@ public class WhisperFullParams extends Structure {
}
/** Flag to suppress non-speech tokens. */
public CBool suppress_nst;
public CBool suppress_non_speech_tokens;
/** Flag to suppress non-speech tokens. */
public void suppressNonSpeechTokens(boolean enable) {
suppress_nst = enable ? CBool.TRUE : CBool.FALSE;
suppress_non_speech_tokens = enable ? CBool.TRUE : CBool.FALSE;
}
/** Initial decoding temperature. */
@ -302,25 +304,18 @@ public class WhisperFullParams extends Structure {
logits_filter_callback = CallbackReference.getFunctionPointer(callback);
}
/** Grammar stuff */
public Pointer grammar_rules;
public long n_grammar_rules;
public long i_start_rule;
public float grammar_penalty;
@Override
protected List<String> getFieldOrder() {
return Arrays.asList("strategy", "n_threads", "n_max_text_ctx", "offset_ms", "duration_ms", "translate",
"no_context", "single_segment", "no_timestamps",
"no_context", "single_segment",
"print_special", "print_progress", "print_realtime", "print_timestamps", "token_timestamps",
"thold_pt", "thold_ptsum", "max_len", "split_on_word", "max_tokens", "audio_ctx",
"tdrz_enable", "suppress_regex", "initial_prompt", "prompt_tokens", "prompt_n_tokens", "language", "detect_language",
"suppress_blank", "suppress_nst", "temperature", "max_initial_ts", "length_penalty",
"thold_pt", "thold_ptsum", "max_len", "split_on_word", "max_tokens", "speed_up", "audio_ctx",
"tdrz_enable", "initial_prompt", "prompt_tokens", "prompt_n_tokens", "language", "detect_language",
"suppress_blank", "suppress_non_speech_tokens", "temperature", "max_initial_ts", "length_penalty",
"temperature_inc", "entropy_thold", "logprob_thold", "no_speech_thold", "greedy", "beam_search",
"new_segment_callback", "new_segment_callback_user_data",
"progress_callback", "progress_callback_user_data",
"encoder_begin_callback", "encoder_begin_callback_user_data",
"logits_filter_callback", "logits_filter_callback_user_data",
"grammar_rules", "n_grammar_rules", "i_start_rule", "grammar_penalty");
"logits_filter_callback", "logits_filter_callback_user_data");
}
}

View File

@ -2,7 +2,6 @@ package io.github.ggerganov.whispercpp;
import static org.junit.jupiter.api.Assertions.*;
import io.github.ggerganov.whispercpp.bean.WhisperSegment;
import io.github.ggerganov.whispercpp.params.CBool;
import io.github.ggerganov.whispercpp.params.WhisperFullParams;
import io.github.ggerganov.whispercpp.params.WhisperSamplingStrategy;
@ -12,7 +11,6 @@ import javax.sound.sampled.AudioInputStream;
import javax.sound.sampled.AudioSystem;
import java.io.File;
import java.io.FileNotFoundException;
import java.util.List;
class WhisperCppTest {
private static WhisperCpp whisper = new WhisperCpp();
@ -22,12 +20,11 @@ class WhisperCppTest {
static void init() throws FileNotFoundException {
// By default, models are loaded from ~/.cache/whisper/ and are usually named "ggml-${name}.bin"
// or you can provide the absolute path to the model file.
//String modelName = "../../models/ggml-tiny.bin";
String modelName = "../../models/ggml-tiny.en.bin";
try {
whisper.initContext(modelName);
//whisper.getFullDefaultParams(WhisperSamplingStrategy.WHISPER_SAMPLING_GREEDY);
//whisper.getJavaDefaultParams(WhisperSamplingStrategy.WHISPER_SAMPLING_BEAM_SEARCH);
// whisper.getFullDefaultParams(WhisperSamplingStrategy.WHISPER_SAMPLING_GREEDY);
// whisper.getJavaDefaultParams(WhisperSamplingStrategy.WHISPER_SAMPLING_BEAM_SEARCH);
modelInitialised = true;
} catch (FileNotFoundException ex) {
System.out.println("Model " + modelName + " not found");
@ -45,7 +42,7 @@ class WhisperCppTest {
assertEquals(16384, params.n_max_text_ctx);
assertFalse(params.translate);
assertEquals(0.01f, params.thold_pt);
assertEquals(5, params.beam_search.beam_size);
assertEquals(2, params.beam_search.beam_size);
assertEquals(-1.0f, params.beam_search.patience);
}
@ -58,7 +55,7 @@ class WhisperCppTest {
assertEquals(WhisperSamplingStrategy.WHISPER_SAMPLING_GREEDY.ordinal(), params.strategy);
assertNotEquals(0, params.n_threads);
assertEquals(16384, params.n_max_text_ctx);
assertEquals(5, params.greedy.best_of);
assertEquals(2, params.greedy.best_of);
}
@Test
@ -75,11 +72,11 @@ class WhisperCppTest {
byte[] b = new byte[audioInputStream.available()];
float[] floats = new float[b.length / 2];
//WhisperFullParams params = whisper.getFullDefaultParams(WhisperSamplingStrategy.WHISPER_SAMPLING_GREEDY);
// WhisperFullParams params = whisper.getFullDefaultParams(WhisperSamplingStrategy.WHISPER_SAMPLING_GREEDY);
WhisperFullParams params = whisper.getFullDefaultParams(WhisperSamplingStrategy.WHISPER_SAMPLING_BEAM_SEARCH);
params.setProgressCallback((ctx, state, progress, user_data) -> System.out.println("progress: " + progress));
params.print_progress = CBool.FALSE;
//params.initial_prompt = "and so my fellow Americans um, like";
// params.initial_prompt = "and so my fellow Americans um, like";
try {
@ -102,43 +99,4 @@ class WhisperCppTest {
audioInputStream.close();
}
}
@Test
void testFullTranscribeWithTime() throws Exception {
if (!modelInitialised) {
System.out.println("Model not initialised, skipping test");
return;
}
// Given
File file = new File(System.getProperty("user.dir"), "../../samples/jfk.wav");
AudioInputStream audioInputStream = AudioSystem.getAudioInputStream(file);
byte[] b = new byte[audioInputStream.available()];
float[] floats = new float[b.length / 2];
//WhisperFullParams params = whisper.getFullDefaultParams(WhisperSamplingStrategy.WHISPER_SAMPLING_GREEDY);
WhisperFullParams params = whisper.getFullDefaultParams(WhisperSamplingStrategy.WHISPER_SAMPLING_BEAM_SEARCH);
params.setProgressCallback((ctx, state, progress, user_data) -> System.out.println("progress: " + progress));
params.print_progress = CBool.FALSE;
//params.initial_prompt = "and so my fellow Americans um, like";
try {
audioInputStream.read(b);
for (int i = 0, j = 0; i < b.length; i += 2, j++) {
int intSample = (int) (b[i + 1]) << 8 | (int) (b[i]) & 0xFF;
floats[j] = intSample / 32767.0f;
}
List<WhisperSegment> segments = whisper.fullTranscribeWithTime(params, floats);
assertTrue(segments.size() > 0, "The size of segments should be greater than 0");
for (WhisperSegment segment : segments) {
System.out.println(segment);
}
} finally {
audioInputStream.close();
}
}
}

View File

@ -41,7 +41,7 @@ make publish-npm
## Sample run
```text
```java
$ node --experimental-wasm-threads --experimental-wasm-simd ../tests/test-whisper.js
whisper_model_load: loading model from 'whisper.bin'
@ -63,7 +63,7 @@ whisper_model_load: ggml ctx size = 140.60 MB
whisper_model_load: memory size = 22.83 MB
whisper_model_load: model size = 140.54 MB
system_info: n_threads = 8 / 10 | AVX = 0 | AVX2 = 0 | AVX512 = 0 | NEON = 0 | F16C = 0 | FP16_VA = 0 | WASM_SIMD = 1 | BLAS = 0 |
system_info: n_threads = 8 / 10 | AVX = 0 | AVX2 = 0 | AVX512 = 0 | NEON = 0 | F16C = 0 | FP16_VA = 0 | WASM_SIMD = 1 | BLAS = 0 |
operator(): processing 176000 samples, 11.0 sec, 8 threads, 1 processors, lang = en, task = transcribe ...

View File

@ -1,6 +1,6 @@
{
"name": "whisper.cpp",
"version": "1.7.3",
"version": "1.4.3",
"description": "Whisper speech recognition",
"main": "whisper.js",
"scripts": {

File diff suppressed because one or more lines are too long

View File

@ -1,5 +0,0 @@
LICENSE
pkg/
lib/whisper.so
lib/whisper.bundle
lib/whisper.dll

View File

@ -1,231 +0,0 @@
whispercpp
==========
![whisper.cpp](https://user-images.githubusercontent.com/1991296/235238348-05d0f6a4-da44-4900-a1de-d0707e75b763.jpeg)
Ruby bindings for [whisper.cpp][], an interface of automatic speech recognition model.
Installation
------------
Install the gem and add to the application's Gemfile by executing:
$ bundle add whispercpp
If bundler is not being used to manage dependencies, install the gem by executing:
$ gem install whispercpp
Usage
-----
```ruby
require "whisper"
whisper = Whisper::Context.new("base")
params = Whisper::Params.new
params.language = "en"
params.offset = 10_000
params.duration = 60_000
params.max_text_tokens = 300
params.translate = true
params.print_timestamps = false
params.initial_prompt = "Initial prompt here."
whisper.transcribe("path/to/audio.wav", params) do |whole_text|
puts whole_text
end
```
### Preparing model ###
Some models are prepared up-front:
```ruby
base_en = Whisper::Model.pre_converted_models["base.en"]
whisper = Whisper::Context.new(base_en)
```
At first time you use a model, it is downloaded automatically. After that, downloaded cached file is used. To clear cache, call `#clear_cache`:
```ruby
Whisper::Model.pre_converted_models["base"].clear_cache
```
You also can use shorthand for pre-converted models:
```ruby
whisper = Whisper::Context.new("base.en")
```
You can see the list of prepared model names by `Whisper::Model.preconverted_models.keys`:
```ruby
puts Whisper::Model.preconverted_models.keys
# tiny
# tiny.en
# tiny-q5_1
# tiny.en-q5_1
# tiny-q8_0
# base
# base.en
# base-q5_1
# base.en-q5_1
# base-q8_0
# :
# :
```
You can also use local model files you prepared:
```ruby
whisper = Whisper::Context.new("path/to/your/model.bin")
```
Or, you can download model files:
```ruby
model_uri = Whisper::Model::URI.new("http://example.net/uri/of/your/model.bin")
whisper = Whisper::Context.new(model_uri)
```
See [models][] page for details.
### Preparing audio file ###
Currently, whisper.cpp accepts only 16-bit WAV files.
API
---
### Segments ###
Once `Whisper::Context#transcribe` called, you can retrieve segments by `#each_segment`:
```ruby
def format_time(time_ms)
sec, decimal_part = time_ms.divmod(1000)
min, sec = sec.divmod(60)
hour, min = min.divmod(60)
"%02d:%02d:%02d.%03d" % [hour, min, sec, decimal_part]
end
whisper.transcribe("path/to/audio.wav", params)
whisper.each_segment.with_index do |segment, index|
line = "[%{nth}: %{st} --> %{ed}] %{text}" % {
nth: index + 1,
st: format_time(segment.start_time),
ed: format_time(segment.end_time),
text: segment.text
}
line << " (speaker turned)" if segment.speaker_next_turn?
puts line
end
```
You can also add hook to params called on new segment:
```ruby
# Add hook before calling #transcribe
params.on_new_segment do |segment|
line = "[%{st} --> %{ed}] %{text}" % {
st: format_time(segment.start_time),
ed: format_time(segment.end_time),
text: segment.text
}
line << " (speaker turned)" if segment.speaker_next_turn?
puts line
end
whisper.transcribe("path/to/audio.wav", params)
```
### Models ###
You can see model information:
```ruby
whisper = Whisper::Context.new("base")
model = whisper.model
model.n_vocab # => 51864
model.n_audio_ctx # => 1500
model.n_audio_state # => 512
model.n_audio_head # => 8
model.n_audio_layer # => 6
model.n_text_ctx # => 448
model.n_text_state # => 512
model.n_text_head # => 8
model.n_text_layer # => 6
model.n_mels # => 80
model.ftype # => 1
model.type # => "base"
```
### Logging ###
You can set log callback:
```ruby
prefix = "[MyApp] "
log_callback = ->(level, buffer, user_data) {
case level
when Whisper::LOG_LEVEL_NONE
puts "#{user_data}none: #{buffer}"
when Whisper::LOG_LEVEL_INFO
puts "#{user_data}info: #{buffer}"
when Whisper::LOG_LEVEL_WARN
puts "#{user_data}warn: #{buffer}"
when Whisper::LOG_LEVEL_ERROR
puts "#{user_data}error: #{buffer}"
when Whisper::LOG_LEVEL_DEBUG
puts "#{user_data}debug: #{buffer}"
when Whisper::LOG_LEVEL_CONT
puts "#{user_data}same to previous: #{buffer}"
end
}
Whisper.log_set log_callback, prefix
```
Using this feature, you are also able to suppress log:
```ruby
Whisper.log_set ->(level, buffer, user_data) {
# do nothing
}, nil
Whisper::Context.new("base")
```
### Low-level API to transcribe ###
You can also call `Whisper::Context#full` and `#full_parallel` with a Ruby array as samples. Although `#transcribe` with audio file path is recommended because it extracts PCM samples in C++ and is fast, `#full` and `#full_parallel` give you flexibility.
```ruby
require "whisper"
require "wavefile"
reader = WaveFile::Reader.new("path/to/audio.wav", WaveFile::Format.new(:mono, :float, 16000))
samples = reader.enum_for(:each_buffer).map(&:samples).flatten
whisper = Whisper::Context.new("base")
whisper.full(Whisper::Params.new, samples)
whisper.each_segment do |segment|
puts segment.text
end
```
The second argument `samples` may be an array, an object with `length` and `each` method, or a MemoryView. If you can prepare audio data as C array and export it as a MemoryView, whispercpp accepts and works with it with zero copy.
License
-------
The same to [whisper.cpp][].
[whisper.cpp]: https://github.com/ggerganov/whisper.cpp
[models]: https://github.com/ggerganov/whisper.cpp/tree/master/models

View File

@ -1,64 +0,0 @@
require 'rake/clean'
require "bundler/gem_tasks"
require "rake/testtask"
require_relative "extsources"
SOURCES = FileList[]
EXTSOURCES.each do |src|
basename = src.pathmap("%f")
dest = basename == "LICENSE" ? basename : src.pathmap("%{../..,ext}p")
dir = dest.pathmap("%d")
file src
directory dir
file dest => [src, dir] do |t|
cp t.source, t.name
end
SOURCES.include dest
end
CLEAN.include SOURCES
CLEAN.include FileList["ext/*.o", "ext/*.metal", "ext/whisper.{so,bundle,dll}"]
task build: ["ext/Makefile", "ext/ruby_whisper.h", "ext/ruby_whisper.cpp", "whispercpp.gemspec"]
directory "pkg"
CLOBBER.include "pkg"
LIB_NAME = "whisper".ext(RbConfig::CONFIG["DLEXT"])
SO_FILE = File.join("ext", LIB_NAME)
LIB_FILE = File.join("lib", LIB_NAME)
file "ext/Makefile" => ["ext/extconf.rb", "ext/ruby_whisper.h", "ext/ruby_whisper.cpp"] + SOURCES do |t|
Dir.chdir "ext" do
ruby "extconf.rb"
end
end
file SO_FILE => "ext/Makefile" do |t|
Dir.chdir "ext" do
sh "make"
end
end
CLEAN.include SO_FILE
directory "lib"
file LIB_FILE => [SO_FILE, "lib"] do |t|
copy t.source, t.name
end
CLEAN.include LIB_FILE
Rake::TestTask.new do |t|
t.test_files = FileList["tests/test_*.rb"]
end
TEST_MEMORY_VIEW = "tests/jfk_reader/jfk_reader.#{RbConfig::CONFIG['DLEXT']}"
file TEST_MEMORY_VIEW => "tests/jfk_reader/jfk_reader.c" do |t|
Dir.chdir "tests/jfk_reader" do
ruby "extconf.rb"
sh "make"
end
end
CLEAN.include "tests/jfk_reader/jfk_reader.{o,#{RbConfig::CONFIG['DLEXT']}}"
task test: [LIB_FILE, TEST_MEMORY_VIEW]

View File

@ -1,13 +1,9 @@
Makefile
whisper.so
ggml.c
ggml.h
ggml-alloc.c
ggml-alloc.h
whisper.bundle
whisper.dll
scripts/get-flags.mk
*.o
*.c
*.cpp
*.h
*.m
*.metal
!ruby_whisper.cpp
!ruby_whisper.h
whisper.cpp
whisper.h
dr_wav.h

View File

@ -1,9 +0,0 @@
ggml/src/ggml-cpu/ggml-cpu-cpp.o: \
ggml/src/ggml-cpu/ggml-cpu.cpp \
ggml/include/ggml-backend.h \
ggml/include/ggml.h \
ggml/include/ggml-alloc.h \
ggml/src/ggml-backend-impl.h \
ggml/include/ggml-cpu.h \
ggml/src/ggml-impl.h
$(CXX) $(CXXFLAGS) -c $< -o $@

View File

@ -1,10 +1,21 @@
require 'mkmf'
system("cp #{File.join(File.dirname(__FILE__),'..','..','..','whisper.cpp')} .")
system("cp #{File.join(File.dirname(__FILE__),'..','..','..','whisper.h')} .")
system("cp #{File.join(File.dirname(__FILE__),'..','..','..','ggml.h')} .")
system("cp #{File.join(File.dirname(__FILE__),'..','..','..','ggml.c')} .")
system("cp #{File.join(File.dirname(__FILE__),'..','..','..','ggml-impl.h')} .")
system("cp #{File.join(File.dirname(__FILE__),'..','..','..','ggml-alloc.h')} .")
system("cp #{File.join(File.dirname(__FILE__),'..','..','..','ggml-alloc.c')} .")
system("cp #{File.join(File.dirname(__FILE__),'..','..','..','ggml-backend-impl.h')} .")
system("cp #{File.join(File.dirname(__FILE__),'..','..','..','ggml-backend.h')} .")
system("cp #{File.join(File.dirname(__FILE__),'..','..','..','ggml-backend.c')} .")
system("cp #{File.join(File.dirname(__FILE__),'..','..','..','ggml-quants.h')} .")
system("cp #{File.join(File.dirname(__FILE__),'..','..','..','ggml-quants.c')} .")
system("cp #{File.join(File.dirname(__FILE__),'..','..','..','examples','dr_wav.h')} .")
# need to use c++ compiler flags
$CXXFLAGS << ' -std=c++17'
$LDFLAGS << ' -lstdc++'
$CXXFLAGS << ' -std=c++11'
# Set to true when building binary gems
if enable_config('static-stdlib', false)
$LDFLAGS << ' -static-libgcc -static-libstdc++'
@ -15,185 +26,4 @@ if enable_config('march-tune-native', false)
$CXXFLAGS << ' -march=native -mtune=native'
end
if ENV['WHISPER_METAL']
$GGML_METAL ||= true
$DEPRECATE_WARNING ||= true
end
$UNAME_S = `uname -s`.chomp
$UNAME_P = `uname -p`.chomp
$UNAME_M = `uname -m`.chomp
if $UNAME_S == 'Darwin'
unless ENV['GGML_NO_METAL']
$GGML_METAL ||= true
end
$GGML_NO_OPENMP ||= true
end
if $GGML_METAL
$GGML_METAL_EMBED_LIBRARY = true
end
$MK_CPPFLAGS = '-Iggml/include -Iggml/src -Iggml/src/ggml-cpu -Iinclude -Isrc -Iexamples'
$MK_CFLAGS = '-std=c11 -fPIC'
$MK_CXXFLAGS = '-std=c++17 -fPIC'
$MK_NVCCFLAGS = '-std=c++17'
$MK_LDFLAGS = ''
$OBJ_GGML = []
$OBJ_WHISPER = []
$OBJ_COMMON = []
$OBJ_SDL = []
$MK_CPPFLAGS << ' -D_XOPEN_SOURCE=600'
if $UNAME_S == 'Linux'
$MK_CPPFLAGS << ' -D_GNU_SOURCE'
end
if $UNAME_S == 'Darwin'
$MK_CPPFLAGS << ' -D_DARWIN_C_SOURCE'
end
if ENV['WHISPER_DEBUG']
$MK_CFLAGS << ' -O0 -g'
$MK_CXXFLAGS << ' -O0 -g'
$MK_LDFLAGS << ' -g'
$MK_NVCCFLAGS << ' -O0 -g'
else
$MK_CPPFLAGS << ' -DNDEBUG'
$MK_CFLAGS << ' -O3'
$MK_CXXFLAGS << ' -O3'
$MK_NVCCFLAGS << ' -O3'
end
$WARN_FLAGS =
' -Wall' <<
' -Wextra' <<
' -Wpedantic' <<
' -Wcast-qual' <<
' -Wno-unused-function'
$MK_CFLAGS <<
$WARN_FLAGS <<
' -Wshadow' <<
' -Wstrict-prototypes' <<
' -Wpointer-arith' <<
' -Wmissing-prototypes' <<
' -Werror=implicit-int' <<
' -Werror=implicit-function-declaration'
$MK_CXXFLAGS <<
$WARN_FLAGS <<
' -Wmissing-declarations' <<
' -Wmissing-noreturn'
unless `#{cc_command} #{$LDFLAGS} -Wl,-v 2>&1`.chomp.include? 'dyld-1015.7'
$MK_CPPFLAGS << ' -DHAVE_BUGGY_APPLE_LINKER'
end
if %w[Linux Darwin FreeBSD NetBSD OpenBSD Haiku].include? $UNAME_S
$MK_CFLAGS << ' -pthread'
$MK_CXXFLAGS << ' -pthread'
end
unless $_WIN32
$DSO_EXT = '.so'
else
$DSO_EXT = '.dll'
end
unless ENV['RISCV']
if %w[x86_64 i686 amd64].include? $UNAME_M
$HOST_CXXFLAGS ||= ''
$MK_CFLAGS << ' -march=native -mtune=native'
$HOST_CXXFLAGS << ' -march=native -mtune=native'
end
else
$MK_CFLAGS << ' -march=rv64gcv -mabi=lp64d'
$MK_CXXFLAGS << ' -march=rv64gcv -mabi=lp64d'
end
unless ENV['GGML_NO_ACCELERATE']
if $UNAME_S == 'Darwin'
$MK_CPPFLAGS << ' -DGGML_USE_ACCELERATE -DGGML_USE_BLAS -DGGML_BLAS_USE_ACCELERATE'
$MK_CPPFLAGS << ' -DACCELERATE_NEW_LAPACK'
$MK_CPPFLAGS << ' -DACCELERATE_LAPACK_ILP64'
$MK_LDFLAGS << ' -framework Accelerate'
$OBJ_GGML << 'ggml/src/ggml-blas/ggml-blas.o'
end
end
if ENV['GGML_OPENBLAS']
$MK_CPPFLAGS << " -DGGML_USE_BLAS #{`pkg-config --cflags-only-I openblas`.chomp}"
$MK_CFLAGS << " #{`pkg-config --cflags-only-other openblas)`.chomp}"
$MK_LDFLAGS << " #{`pkg-config --libs openblas`}"
$OBJ_GGML << 'ggml/src/ggml-blas/ggml-blas.o'
end
if ENV['GGML_OPENBLAS64']
$MK_CPPFLAGS << " -DGGML_USE_BLAS #{`pkg-config --cflags-only-I openblas64`.chomp}"
$MK_CFLAGS << " #{`pkg-config --cflags-only-other openblas64)`.chomp}"
$MK_LDFLAGS << " #{`pkg-config --libs openblas64`}"
$OBJ_GGML << 'ggml/src/ggml-blas/ggml-blas.o'
end
if $GGML_METAL
$MK_CPPFLAGS << ' -DGGML_USE_METAL'
$MK_LDFLAGS << ' -framework Foundation -framework Metal -framework MetalKit'
$OBJ_GGML << 'ggml/src/ggml-metal/ggml-metal.o'
if ENV['GGML_METAL_NDEBUG']
$MK_CPPFLAGS << ' -DGGML_METAL_NDEBUG'
end
if $GGML_METAL_EMBED_LIBRARY
$MK_CPPFLAGS << ' -DGGML_METAL_EMBED_LIBRARY'
$OBJ_GGML << 'ggml/src/ggml-metal/ggml-metal-embed.o'
end
end
$OBJ_GGML <<
'ggml/src/ggml.o' <<
'ggml/src/ggml-alloc.o' <<
'ggml/src/ggml-backend.o' <<
'ggml/src/ggml-backend-reg.o' <<
'ggml/src/ggml-opt.o' <<
'ggml/src/ggml-quants.o' <<
'ggml/src/ggml-threading.o' <<
'ggml/src/ggml-cpu/ggml-cpu.o' <<
'ggml/src/ggml-cpu/ggml-cpu-cpp.o' <<
'ggml/src/ggml-cpu/ggml-cpu-aarch64.o' <<
'ggml/src/ggml-cpu/ggml-cpu-hbm.o' <<
'ggml/src/ggml-cpu/ggml-cpu-quants.o' <<
'ggml/src/ggml-cpu/ggml-cpu-traits.o'
$OBJ_WHISPER <<
'src/whisper.o'
$objs = $OBJ_GGML + $OBJ_WHISPER + $OBJ_COMMON + $OBJ_SDL
$objs << "ruby_whisper.o"
$CPPFLAGS = "#{$MK_CPPFLAGS} #{$CPPFLAGS}"
$CFLAGS = "#{$CPPFLAGS} #{$MK_CFLAGS} #{$GF_CFLAGS} #{$CFLAGS}"
$BASE_CXXFLAGS = "#{$MK_CXXFLAGS} #{$CXXFLAGS}"
$CXXFLAGS = "#{$BASE_CXXFLAGS} #{$HOST_CXXFLAGS} #{$GF_CXXFLAGS} #{$CPPFLAGS}"
$NVCCFLAGS = "#{$MK_NVCCFLAGS} #{$NVCCFLAGS}"
$LDFLAGS = "#{$MK_LDFLAGS} #{$LDFLAGS}"
create_makefile('whisper')
File.open 'Makefile', 'a' do |file|
file.puts 'include scripts/get-flags.mk'
file.puts 'include cpu.mk'
if $GGML_METAL
file.puts 'include metal.mk'
if $GGML_METAL_EMBED_LIBRARY
file.puts 'include metal-embed.mk'
end
end
end

View File

@ -0,0 +1,87 @@
#pragma once
// ggml-backend internal header
#include "ggml-backend.h"
#ifdef __cplusplus
extern "C" {
#endif
//
// Backend buffer
//
typedef void * ggml_backend_buffer_context_t;
struct ggml_backend_buffer_i {
void (*free_buffer) (ggml_backend_buffer_t buffer);
void * (*get_base) (ggml_backend_buffer_t buffer); // get base pointer
size_t (*get_alloc_size)(ggml_backend_buffer_t buffer, struct ggml_tensor * tensor); // pre-allocation callback
void (*init_tensor) (ggml_backend_buffer_t buffer, struct ggml_tensor * tensor); // post-allocation callback
void (*free_tensor) (ggml_backend_buffer_t buffer, struct ggml_tensor * tensor); // pre-free callback
};
struct ggml_backend_buffer {
struct ggml_backend_buffer_i iface;
ggml_backend_t backend;
ggml_backend_buffer_context_t context;
size_t size;
};
GGML_API ggml_backend_buffer_t ggml_backend_buffer_init(
struct ggml_backend * backend,
struct ggml_backend_buffer_i iface,
ggml_backend_buffer_context_t context,
size_t size);
//
// Backend
//
typedef void * ggml_backend_context_t;
struct ggml_backend_i {
const char * (*get_name)(ggml_backend_t backend);
void (*free)(ggml_backend_t backend);
// buffer allocation
ggml_backend_buffer_t (*alloc_buffer)(ggml_backend_t backend, size_t size);
// get buffer alignment
size_t (*get_alignment)(ggml_backend_t backend);
// tensor data access
// these functions can be asynchronous, helper functions are provided for synchronous access that automatically call synchronize
void (*set_tensor_async)(ggml_backend_t backend, struct ggml_tensor * tensor, const void * data, size_t offset, size_t size);
void (*get_tensor_async)(ggml_backend_t backend, const struct ggml_tensor * tensor, void * data, size_t offset, size_t size);
void (*synchronize) (ggml_backend_t backend);
// (optional) copy tensor between different backends, allow for single-copy tranfers
void (*cpy_tensor_from)(ggml_backend_t backend, struct ggml_tensor * src, struct ggml_tensor * dst);
void (*cpy_tensor_to) (ggml_backend_t backend, struct ggml_tensor * src, struct ggml_tensor * dst);
// compute graph with a plan
ggml_backend_graph_plan_t (*graph_plan_create) (ggml_backend_t backend, struct ggml_cgraph * cgraph);
void (*graph_plan_free) (ggml_backend_t backend, ggml_backend_graph_plan_t plan);
void (*graph_plan_compute)(ggml_backend_t backend, ggml_backend_graph_plan_t plan);
// compute graph without a plan
void (*graph_compute)(ggml_backend_t backend, struct ggml_cgraph * cgraph);
// check if the backend supports an operation
bool (*supports_op)(ggml_backend_t backend, const struct ggml_tensor * op);
};
struct ggml_backend {
struct ggml_backend_i iface;
ggml_backend_context_t context;
};
#ifdef __cplusplus
}
#endif

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@ -0,0 +1,950 @@
#include "ggml-backend-impl.h"
#include "ggml-alloc.h"
#include "ggml-impl.h"
#include <assert.h>
#include <limits.h>
#include <stdarg.h>
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#define UNUSED GGML_UNUSED
#define MAX(a, b) ((a) > (b) ? (a) : (b))
// backend buffer
ggml_backend_buffer_t ggml_backend_buffer_init(
struct ggml_backend * backend,
struct ggml_backend_buffer_i iface,
ggml_backend_buffer_context_t context,
size_t size) {
ggml_backend_buffer_t buffer = malloc(sizeof(struct ggml_backend_buffer));
GGML_ASSERT(iface.get_base != NULL);
(*buffer) = (struct ggml_backend_buffer) {
/* .interface = */ iface,
/* .backend = */ backend,
/* .context = */ context,
/* .size = */ size,
};
return buffer;
}
void ggml_backend_buffer_free(ggml_backend_buffer_t buffer) {
if (buffer == NULL) {
return;
}
if (buffer->iface.free_buffer != NULL) {
buffer->iface.free_buffer(buffer);
}
free(buffer);
}
size_t ggml_backend_buffer_get_alignment(ggml_backend_buffer_t buffer) {
return ggml_backend_get_alignment(buffer->backend);
}
size_t ggml_backend_buffer_get_size(ggml_backend_buffer_t buffer) {
return buffer->size;
}
void * ggml_backend_buffer_get_base(ggml_backend_buffer_t buffer) {
void * base = buffer->iface.get_base(buffer);
GGML_ASSERT(base != NULL && "backend buffer base cannot be NULL");
return base;
}
size_t ggml_backend_buffer_get_alloc_size(ggml_backend_buffer_t buffer, struct ggml_tensor * tensor) {
// get_alloc_size is optional, defaults to ggml_nbytes
if (buffer->iface.get_alloc_size) {
return buffer->iface.get_alloc_size(buffer, tensor);
}
return ggml_nbytes(tensor);
}
void ggml_backend_buffer_init_tensor(ggml_backend_buffer_t buffer, struct ggml_tensor * tensor) {
// init_tensor is optional
if (buffer->iface.init_tensor) {
buffer->iface.init_tensor(buffer, tensor);
}
}
void ggml_backend_buffer_free_tensor(ggml_backend_buffer_t buffer, struct ggml_tensor * tensor) {
// free_tensor is optional
if (buffer->iface.free_tensor) {
buffer->iface.free_tensor(buffer, tensor);
}
}
// backend
ggml_backend_t ggml_get_backend(const struct ggml_tensor * tensor) {
return tensor->buffer ? tensor->buffer->backend : NULL;
}
const char * ggml_backend_name(ggml_backend_t backend) {
if (backend == NULL) {
return "NULL";
}
return backend->iface.get_name(backend);
}
void ggml_backend_free(ggml_backend_t backend) {
if (backend == NULL) {
return;
}
backend->iface.free(backend);
}
ggml_backend_buffer_t ggml_backend_alloc_buffer(ggml_backend_t backend, size_t size) {
return backend->iface.alloc_buffer(backend, size);
}
size_t ggml_backend_get_alignment(ggml_backend_t backend) {
return backend->iface.get_alignment(backend);
}
void ggml_backend_tensor_set_async(struct ggml_tensor * tensor, const void * data, size_t offset, size_t size) {
ggml_get_backend(tensor)->iface.set_tensor_async(ggml_get_backend(tensor), tensor, data, offset, size);
}
void ggml_backend_tensor_get_async(const struct ggml_tensor * tensor, void * data, size_t offset, size_t size) {
ggml_get_backend(tensor)->iface.get_tensor_async(ggml_get_backend(tensor), tensor, data, offset, size);
}
void ggml_backend_tensor_set(struct ggml_tensor * tensor, const void * data, size_t offset, size_t size) {
ggml_backend_t backend = ggml_get_backend(tensor);
GGML_ASSERT(tensor->data != NULL && "tensor not allocated");
GGML_ASSERT(backend != NULL && "tensor backend not set");
backend->iface.set_tensor_async(backend, tensor, data, offset, size);
backend->iface.synchronize(backend);
}
void ggml_backend_tensor_get(const struct ggml_tensor * tensor, void * data, size_t offset, size_t size) {
ggml_backend_t backend = ggml_get_backend(tensor);
GGML_ASSERT(tensor->data != NULL && "tensor not allocated");
GGML_ASSERT(backend != NULL && "tensor backend not set");
backend->iface.get_tensor_async(backend, tensor, data, offset, size);
backend->iface.synchronize(backend);
}
void ggml_backend_synchronize(ggml_backend_t backend) {
backend->iface.synchronize(backend);
}
ggml_backend_graph_plan_t ggml_backend_graph_plan_create(ggml_backend_t backend, struct ggml_cgraph * cgraph) {
return backend->iface.graph_plan_create(backend, cgraph);
}
void ggml_backend_graph_plan_free(ggml_backend_t backend, ggml_backend_graph_plan_t plan) {
backend->iface.graph_plan_free(backend, plan);
}
void ggml_backend_graph_plan_compute(ggml_backend_t backend, ggml_backend_graph_plan_t plan) {
backend->iface.graph_plan_compute(backend, plan);
}
void ggml_backend_graph_compute(ggml_backend_t backend, struct ggml_cgraph * cgraph) {
backend->iface.graph_compute(backend, cgraph);
}
bool ggml_backend_supports_op(ggml_backend_t backend, const struct ggml_tensor * op) {
return backend->iface.supports_op(backend, op);
}
// backend copy
static bool ggml_are_same_layout(const struct ggml_tensor * a, const struct ggml_tensor * b) {
if (a->type != b->type) {
return false;
}
for (int i = 0; i < GGML_MAX_DIMS; i++) {
if (a->ne[i] != b->ne[i]) {
return false;
}
if (a->nb[i] != b->nb[i]) {
return false;
}
}
return true;
}
void ggml_backend_tensor_copy(struct ggml_tensor * src, struct ggml_tensor * dst) {
//printf("src: %s ne: [%d %d %d %d] nb: [%d %d %d %d]\n", src->name, (int)src->ne[0], (int)src->ne[1], (int)src->ne[2], (int)src->ne[3], (int)src->nb[0], (int)src->nb[1], (int)src->nb[2], (int)src->nb[3]);
//printf("dst: %s ne: [%d %d %d %d] nb: [%d %d %d %d]\n", dst->name, (int)dst->ne[0], (int)dst->ne[1], (int)dst->ne[2], (int)dst->ne[3], (int)dst->nb[0], (int)dst->nb[1], (int)dst->nb[2], (int)dst->nb[3]);
GGML_ASSERT(ggml_are_same_layout(src, dst) && "cannot copy tensors with different layouts");
// fprintf(stderr, "cpy tensor %s from %s to %s (%lu bytes)\n", src->name, ggml_backend_name(src->backend), ggml_backend_name(dst->backend), ggml_nbytes(src));
if (src == dst) {
return;
}
// TODO: allow backends to support copy to/from same backend
if (ggml_get_backend(dst)->iface.cpy_tensor_from != NULL) {
ggml_get_backend(dst)->iface.cpy_tensor_from(ggml_get_backend(dst)->context, src, dst);
} else if (ggml_get_backend(src)->iface.cpy_tensor_to != NULL) {
ggml_get_backend(src)->iface.cpy_tensor_to(ggml_get_backend(src)->context, src, dst);
} else {
// shouldn't be hit when copying from/to CPU
#ifndef NDEBUG
fprintf(stderr, "ggml_backend_tensor_copy: neither cpy_tensor_from nor cpy_tensor_to are implemented for backends %s and %s, falling back to get/set\n", ggml_backend_name(src->buffer->backend), ggml_backend_name(dst->buffer->backend));
#endif
size_t nbytes = ggml_nbytes(src);
void * data = malloc(nbytes);
ggml_backend_tensor_get(src, data, 0, nbytes);
ggml_backend_tensor_set(dst, data, 0, nbytes);
free(data);
}
}
// backend CPU
struct ggml_backend_cpu_context {
int n_threads;
void * work_data;
size_t work_size;
};
static const char * ggml_backend_cpu_name(ggml_backend_t backend) {
return "CPU";
UNUSED(backend);
}
static void ggml_backend_cpu_free(ggml_backend_t backend) {
struct ggml_backend_cpu_context * cpu_ctx = (struct ggml_backend_cpu_context *)backend->context;
free(cpu_ctx->work_data);
free(cpu_ctx);
free(backend);
}
static void * ggml_backend_cpu_buffer_get_base(ggml_backend_buffer_t buffer) {
return (void *)buffer->context;
}
static void ggml_backend_cpu_buffer_free_buffer(ggml_backend_buffer_t buffer) {
free(buffer->context);
UNUSED(buffer);
}
static struct ggml_backend_buffer_i cpu_backend_buffer_i = {
/* .free_buffer = */ ggml_backend_cpu_buffer_free_buffer,
/* .get_base = */ ggml_backend_cpu_buffer_get_base,
/* .get_alloc_size = */ NULL, // defaults to ggml_nbytes
/* .init_tensor = */ NULL, // no initialization required
/* .free_tensor = */ NULL, // no cleanup required
};
// for buffers from ptr, free is not called
static struct ggml_backend_buffer_i cpu_backend_buffer_i_from_ptr = {
/* .free_buffer = */ NULL, // ptr is not owned by the buffer, so it does not need to be freed
/* .get_base = */ ggml_backend_cpu_buffer_get_base,
/* .get_alloc_size = */ NULL, // defaults to ggml_nbytes
/* .init_tensor = */ NULL,
/* .free_tensor = */ NULL,
};
static const size_t TENSOR_ALIGNMENT = 64; // should be enough for AVX 512
static ggml_backend_buffer_t ggml_backend_cpu_alloc_buffer(ggml_backend_t backend, size_t size) {
size += TENSOR_ALIGNMENT; // malloc may return an address that is not aligned
void * data = malloc(size); // TODO: maybe use GGML_ALIGNED_MALLOC?
GGML_ASSERT(data != NULL && "failed to allocate buffer");
return ggml_backend_buffer_init(backend, cpu_backend_buffer_i, data, size);
}
static size_t ggml_backend_cpu_get_alignment(ggml_backend_t backend) {
return TENSOR_ALIGNMENT;
UNUSED(backend);
}
static void ggml_backend_cpu_set_tensor_async(ggml_backend_t backend, struct ggml_tensor * tensor, const void * data, size_t offset, size_t size) {
GGML_ASSERT(offset + size <= ggml_nbytes(tensor) && "tensor write out of bounds");
GGML_ASSERT(tensor->data != NULL && "tensor not allocated");
memcpy((char *)tensor->data + offset, data, size);
UNUSED(backend);
}
static void ggml_backend_cpu_get_tensor_async(ggml_backend_t backend, const struct ggml_tensor * tensor, void * data, size_t offset, size_t size) {
GGML_ASSERT(offset + size <= ggml_nbytes(tensor) && "tensor read out of bounds");
GGML_ASSERT(tensor->data != NULL && "tensor not allocated");
memcpy(data, (const char *)tensor->data + offset, size);
UNUSED(backend);
}
static void ggml_backend_cpu_synchronize(ggml_backend_t backend) {
UNUSED(backend);
}
static void ggml_backend_cpu_cpy_tensor_from(ggml_backend_t backend, struct ggml_tensor * src, struct ggml_tensor * dst) {
ggml_backend_tensor_get(src, dst->data, 0, ggml_nbytes(src));
UNUSED(backend);
}
static void ggml_backend_cpu_cpy_tensor_to(ggml_backend_t backend, struct ggml_tensor * src, struct ggml_tensor * dst) {
ggml_backend_tensor_set(dst, src->data, 0, ggml_nbytes(src));
UNUSED(backend);
}
struct ggml_backend_plan_cpu {
struct ggml_cplan cplan;
struct ggml_cgraph cgraph;
};
static ggml_backend_graph_plan_t ggml_backend_cpu_graph_plan_create(ggml_backend_t backend, struct ggml_cgraph * cgraph) {
struct ggml_backend_cpu_context * cpu_ctx = (struct ggml_backend_cpu_context *)backend->context;
struct ggml_backend_plan_cpu * cpu_plan = malloc(sizeof(struct ggml_backend_plan_cpu));
cpu_plan->cplan = ggml_graph_plan(cgraph, cpu_ctx->n_threads);
cpu_plan->cgraph = *cgraph;
if (cpu_plan->cplan.work_size > 0) {
cpu_plan->cplan.work_data = malloc(cpu_plan->cplan.work_size);
}
return cpu_plan;
}
static void ggml_backend_cpu_graph_plan_free(ggml_backend_t backend, ggml_backend_graph_plan_t plan) {
struct ggml_backend_plan_cpu * cpu_plan = (struct ggml_backend_plan_cpu *)plan;
free(cpu_plan->cplan.work_data);
free(cpu_plan);
UNUSED(backend);
}
static void ggml_backend_cpu_graph_plan_compute(ggml_backend_t backend, ggml_backend_graph_plan_t plan) {
struct ggml_backend_plan_cpu * cpu_plan = (struct ggml_backend_plan_cpu *)plan;
ggml_graph_compute(&cpu_plan->cgraph, &cpu_plan->cplan);
UNUSED(backend);
}
static void ggml_backend_cpu_graph_compute(ggml_backend_t backend, struct ggml_cgraph * cgraph) {
struct ggml_backend_cpu_context * cpu_ctx = (struct ggml_backend_cpu_context *)backend->context;
struct ggml_cplan cplan = ggml_graph_plan(cgraph, cpu_ctx->n_threads);
if (cpu_ctx->work_size < cplan.work_size) {
// TODO: may be faster to free and use malloc to avoid the copy
cpu_ctx->work_data = realloc(cpu_ctx->work_data, cplan.work_size);
cpu_ctx->work_size = cplan.work_size;
}
cplan.work_data = cpu_ctx->work_data;
ggml_graph_compute(cgraph, &cplan);
}
static bool ggml_backend_cpu_supports_op(ggml_backend_t backend, const struct ggml_tensor * op) {
return true;
UNUSED(backend);
UNUSED(op);
}
static struct ggml_backend_i cpu_backend_i = {
/* .get_name = */ ggml_backend_cpu_name,
/* .free = */ ggml_backend_cpu_free,
/* .alloc_buffer = */ ggml_backend_cpu_alloc_buffer,
/* .get_alignment = */ ggml_backend_cpu_get_alignment,
/* .set_tensor_async = */ ggml_backend_cpu_set_tensor_async,
/* .get_tensor_async = */ ggml_backend_cpu_get_tensor_async,
/* .synchronize = */ ggml_backend_cpu_synchronize,
/* .cpy_tensor_from = */ ggml_backend_cpu_cpy_tensor_from,
/* .cpy_tensor_to = */ ggml_backend_cpu_cpy_tensor_to,
/* .graph_plan_create = */ ggml_backend_cpu_graph_plan_create,
/* .graph_plan_free = */ ggml_backend_cpu_graph_plan_free,
/* .graph_plan_compute = */ ggml_backend_cpu_graph_plan_compute,
/* .graph_compute = */ ggml_backend_cpu_graph_compute,
/* .supports_op = */ ggml_backend_cpu_supports_op,
};
ggml_backend_t ggml_backend_cpu_init(void) {
struct ggml_backend_cpu_context * ctx = malloc(sizeof(struct ggml_backend_cpu_context));
ctx->n_threads = GGML_DEFAULT_N_THREADS;
ctx->work_data = NULL;
ctx->work_size = 0;
ggml_backend_t cpu_backend = malloc(sizeof(struct ggml_backend));
*cpu_backend = (struct ggml_backend) {
/* .interface = */ cpu_backend_i,
/* .context = */ ctx
};
return cpu_backend;
}
bool ggml_backend_is_cpu(ggml_backend_t backend) {
return backend->iface.get_name == ggml_backend_cpu_name;
}
void ggml_backend_cpu_set_n_threads(ggml_backend_t backend_cpu, int n_threads) {
GGML_ASSERT(ggml_backend_is_cpu(backend_cpu));
struct ggml_backend_cpu_context * ctx = (struct ggml_backend_cpu_context *)backend_cpu->context;
ctx->n_threads = n_threads;
}
ggml_backend_buffer_t ggml_backend_cpu_buffer_from_ptr(ggml_backend_t backend_cpu, void * ptr, size_t size) {
return ggml_backend_buffer_init(backend_cpu, cpu_backend_buffer_i_from_ptr, ptr, size);
}
// scheduler
#define GGML_MAX_BACKENDS 4
#define GGML_MAX_SPLITS 256
#define GGML_MAX_SPLIT_INPUTS 16
struct ggml_backend_sched_split {
ggml_tallocr_t tallocr;
int i_start;
int i_end;
struct ggml_tensor * inputs[GGML_MAX_SPLIT_INPUTS];
int n_inputs;
struct ggml_cgraph * graph;
};
struct ggml_backend_sched {
int n_backends;
ggml_backend_t backends[GGML_MAX_BACKENDS];
ggml_tallocr_t tallocs[GGML_MAX_BACKENDS];
ggml_gallocr_t galloc;
struct ggml_hash_set hash_set;
ggml_tallocr_t * node_talloc; // [hash_set.size]
struct ggml_tensor * (* node_copies)[GGML_MAX_BACKENDS]; // [hash_set.size][GGML_MAX_BACKENDS]
struct ggml_cgraph * graph;
struct ggml_backend_sched_split splits[GGML_MAX_SPLITS];
int n_splits;
struct ggml_context * ctx;
// align context_buffer to GGML_MEM_ALIGN
#ifdef _MSC_VER
__declspec(align(GGML_MEM_ALIGN))
#else
__attribute__((aligned(GGML_MEM_ALIGN)))
#endif
char context_buffer[GGML_MAX_SPLITS*GGML_MAX_SPLIT_INPUTS*sizeof(struct ggml_tensor) + GGML_MAX_SPLITS*sizeof(struct ggml_cgraph)];
};
#define hash_id(node) ggml_hash_find_or_insert(sched->hash_set, node)
#define node_allocr(node) sched->node_talloc[hash_id(node)]
static bool ggml_is_view_op(enum ggml_op op) {
return op == GGML_OP_VIEW || op == GGML_OP_RESHAPE || op == GGML_OP_PERMUTE || op == GGML_OP_TRANSPOSE;
}
// returns the priority of the backend, lower is better
static int sched_backend_prio(ggml_backend_sched_t sched, ggml_backend_t backend) {
for (int i = 0; i < sched->n_backends; i++) {
if (sched->backends[i] == backend) {
return i;
}
}
return INT_MAX;
}
static int sched_allocr_prio(ggml_backend_sched_t sched, ggml_tallocr_t allocr) {
for (int i = 0; i < sched->n_backends; i++) {
if (sched->tallocs[i] == allocr) {
return i;
}
}
return INT_MAX;
}
// returns the backend that should be used for the node based on the current locations
char causes[GGML_DEFAULT_GRAPH_SIZE*4 + GGML_MAX_SPLITS*GGML_MAX_SPLIT_INPUTS][128]; // debug, remove
static ggml_backend_t sched_backend_from_cur(ggml_backend_sched_t sched, struct ggml_tensor * node) {
// if the dst tensor is already allocated in a buffer, we must assume that it is critical to keep it there
// ie. kv cache updates
// note that this doesn't allow fallback to CPU. need to add output tensors to the splits to copy the data back to the original backend.
// dst
ggml_backend_t cur_backend = ggml_get_backend(node);
if (cur_backend != NULL) {
sprintf(causes[hash_id(node)], "1.dst");
return cur_backend;
}
// view_src
if (node->view_src != NULL && ggml_get_backend(node->view_src) != NULL) {
sprintf(causes[hash_id(node)], "1.vsrc");
return ggml_get_backend(node->view_src);
}
// src
int cur_prio = INT_MAX;
size_t cur_size = 0;
for (int i = 0; i < GGML_MAX_SRC; i++) {
const struct ggml_tensor * src = node->src[i];
if (src == NULL) {
break;
}
ggml_backend_t src_backend = ggml_get_backend(src);
if (src_backend != NULL) {
int src_prio = sched_backend_prio(sched, src_backend);
size_t src_size = ggml_nbytes(src);
if (src_prio < cur_prio && src_size >= cur_size) {
cur_prio = src_prio;
cur_size = src_size;
cur_backend = src_backend;
sprintf(causes[hash_id(node)], "1.src%d", i);
}
}
}
return cur_backend;
}
static char * fmt_size(size_t size) {
static char buffer[128];
if (size >= 1024*1024) {
sprintf(buffer, "%zuM", size/1024/1024);
} else {
sprintf(buffer, "%zuK", size/1024);
}
return buffer;
}
static void sched_print_assignments(ggml_backend_sched_t sched, struct ggml_cgraph * graph) {
int cur_split = 0;
for (int i = 0; i < graph->n_nodes; i++) {
if (cur_split < sched->n_splits && i == sched->splits[cur_split].i_start) {
ggml_backend_t split_backend = ggml_tallocr_get_buffer(sched->splits[cur_split].tallocr)->backend;
fprintf(stderr, "\n## SPLIT #%d: %s # %d inputs: ", cur_split, ggml_backend_name(split_backend), sched->splits[cur_split].n_inputs);
for (int j = 0; j < sched->splits[cur_split].n_inputs; j++) {
fprintf(stderr, "[%s (%5.5s)] ", sched->splits[cur_split].inputs[j]->name, fmt_size(ggml_nbytes(sched->splits[cur_split].inputs[j])));
}
fprintf(stderr, "\n");
cur_split++;
}
struct ggml_tensor * node = graph->nodes[i];
if (ggml_is_view_op(node->op)) {
continue;
}
ggml_tallocr_t node_allocr = node_allocr(node);
ggml_backend_t node_backend = node_allocr ? ggml_tallocr_get_buffer(node_allocr)->backend : NULL;
fprintf(stderr, "node #%3d (%10.10s): %20.20s (%4.4s) [%4.4s %8.8s]:", i, ggml_op_name(node->op), node->name, fmt_size(ggml_nbytes(node)), node_allocr ? ggml_backend_name(node_backend) : "NULL", causes[hash_id(node)]);
for (int j = 0; j < GGML_MAX_SRC; j++) {
struct ggml_tensor * src = node->src[j];
if (src == NULL) {
break;
}
ggml_tallocr_t src_allocr = node_allocr(src);
ggml_backend_t src_backend = src_allocr ? ggml_tallocr_get_buffer(src_allocr)->backend : NULL;
fprintf(stderr, " %20.20s (%4.4s) [%4.4s %8.8s]", src->name, fmt_size(ggml_nbytes(src)), src_backend ? ggml_backend_name(src_backend) : "NULL", causes[hash_id(src)]);
}
fprintf(stderr, "\n");
}
}
// creates a copy of the tensor with the same memory layout
static struct ggml_tensor * ggml_dup_tensor_layout(struct ggml_context * ctx, const struct ggml_tensor * tensor) {
struct ggml_tensor * dup = ggml_dup_tensor(ctx, tensor);
for (int i = 0; i < GGML_MAX_DIMS; i++) {
dup->nb[i] = tensor->nb[i];
}
return dup;
}
// assigns backends to ops and splits the graph into subgraphs that can be computed on the same backend
// TODO: merge passes
static void sched_split_graph(ggml_backend_sched_t sched, struct ggml_cgraph * graph) {
// reset state
size_t hash_size = sched->hash_set.size;
memset(sched->hash_set.keys, 0, sizeof(sched->hash_set.keys[0]) * hash_size);
memset(sched->node_talloc, 0, sizeof(sched->node_talloc[0]) * hash_size);
memset(sched->node_copies, 0, sizeof(sched->node_copies[0]) * hash_size);
sched->n_splits = 0;
struct ggml_init_params params = {
/*.mem_size = */ sizeof(sched->context_buffer),
/*.mem_buffer = */ sched->context_buffer,
/*.no_alloc = */ true
};
if (sched->ctx != NULL) {
ggml_free(sched->ctx);
}
sched->ctx = ggml_init(params);
// pass 1: assign backends to ops with allocated inputs
for (int i = 0; i < graph->n_leafs; i++) {
struct ggml_tensor * leaf = graph->leafs[i];
if (node_allocr(leaf) != NULL) {
// do not overwrite user assignments
continue;
}
ggml_backend_t leaf_backend = ggml_get_backend(leaf);
if (leaf_backend == NULL && leaf->view_src != NULL) {
leaf_backend = ggml_get_backend(leaf->view_src);
}
if (leaf_backend != NULL) {
node_allocr(leaf) = ggml_backend_sched_get_tallocr(sched, leaf_backend);
}
}
for (int i = 0; i < graph->n_nodes; i++) {
struct ggml_tensor * node = graph->nodes[i];
if (node_allocr(node) != NULL) {
// do not overwrite user assignments
continue;
}
ggml_backend_t node_backend = sched_backend_from_cur(sched, node);
if (node_backend != NULL) {
node_allocr(node) = ggml_backend_sched_get_tallocr(sched, node_backend);
}
}
//printf("PASS 1 ASSIGNMENTS\n"); sched_print_assignments(sched, graph);
// pass 2: assign backends to ops from current assignments
// TODO:
// - reuse sched_backend_from_cur
for (int i = 0; i < graph->n_nodes; i++) {
struct ggml_tensor * node = graph->nodes[i];
ggml_tallocr_t node_allocr = node_allocr(node);
if (node_allocr == NULL) {
int cur_prio = INT_MAX;
size_t cur_size = 0;
for (int j = 0; j < GGML_MAX_SRC; j++) {
struct ggml_tensor * src = node->src[j];
if (src == NULL) {
break;
}
ggml_tallocr_t src_allocr = node_allocr(src);
if (src_allocr != NULL) {
int src_prio = sched_allocr_prio(sched, src_allocr);
size_t src_size = ggml_nbytes(src);
if (src_prio < cur_prio && src_size >= cur_size) {
cur_prio = src_prio;
cur_size = src_size;
node_allocr = src_allocr;
sprintf(causes[hash_id(node)], "2.src%d", j);
}
}
}
if (node_allocr != NULL) {
node_allocr(node) = node_allocr;
}
}
}
//printf("PASS 2 ASSIGNMENTS\n"); sched_print_assignments(sched, graph);
// pass 3: assign backends to remaining src from dst (should only be leafs)
for (int i = 0; i < graph->n_nodes; i++) {
struct ggml_tensor * node = graph->nodes[i];
ggml_tallocr_t node_allocr = node_allocr(node);
for (int j = 0; j < GGML_MAX_SRC; j++) {
struct ggml_tensor * src = node->src[j];
if (src == NULL) {
break;
}
ggml_tallocr_t src_allocr = node_allocr(src);
if (src_allocr == NULL) {
node_allocr(src) = node_allocr;
}
}
}
//printf("PASS 3 ASSIGNMENTS\n"); sched_print_assignments(sched, graph);
// pass 4: split graph, find tensors that need to be copied
// TODO:
// - when switching from a less preferred backend to a more preferred backend, check if it is possible to move the switch to an earlier point for the same cost
// find first backend
int cur_split = 0;
for (int i = 0; i < graph->n_nodes; i++) {
struct ggml_tensor * node = graph->nodes[i];
if (node->view_src == NULL) {
sched->splits[0].tallocr = node_allocr(node);
break;
}
}
sched->splits[0].i_start = 0;
sched->splits[0].n_inputs = 0;
memset(sched->splits[0].inputs, 0, sizeof(sched->splits[0].inputs)); //HACK
ggml_tallocr_t cur_allocr = sched->splits[0].tallocr;
size_t cur_backend_id = sched_allocr_prio(sched, cur_allocr);
for (int i = 0; i < graph->n_nodes; i++) {
struct ggml_tensor * node = graph->nodes[i];
if (ggml_is_view_op(node->op)) {
continue;
}
ggml_tallocr_t node_allocr = node_allocr(node);
if (node_allocr != cur_allocr) {
sched->splits[cur_split].i_end = i;
cur_split++;
GGML_ASSERT(cur_split < GGML_MAX_SPLITS);
sched->splits[cur_split].tallocr = node_allocr;
sched->splits[cur_split].i_start = i;
sched->splits[cur_split].n_inputs = 0;
memset(sched->splits[cur_split].inputs, 0, sizeof(sched->splits[cur_split].inputs)); //HACK
cur_allocr = node_allocr;
cur_backend_id = sched_allocr_prio(sched, cur_allocr);
}
// find inputs that are not on the same backend
for (int j = 0; j < GGML_MAX_SRC; j++) {
struct ggml_tensor * src = node->src[j];
if (src == NULL) {
break;
}
ggml_tallocr_t src_allocr = node_allocr(src);
if (src_allocr != node_allocr) {
int n_inputs = sched->splits[cur_split].n_inputs++;
GGML_ASSERT(n_inputs < GGML_MAX_SPLIT_INPUTS);
sched->splits[cur_split].inputs[n_inputs] = (struct ggml_tensor *)src;
// create copies
size_t id = hash_id(src);
if (sched->node_copies[id][cur_backend_id] == NULL) {
struct ggml_tensor * tensor_copy = ggml_dup_tensor_layout(sched->ctx, src);
sched->node_copies[id][cur_backend_id] = tensor_copy;
node_allocr(tensor_copy) = cur_allocr;
ggml_backend_t backend = ggml_tallocr_get_buffer(cur_allocr)->backend;
ggml_format_name(tensor_copy, "%s#%s", ggml_backend_name(backend), src->name);
}
node->src[j] = sched->node_copies[id][cur_backend_id];
}
}
}
sched->splits[cur_split].i_end = graph->n_nodes;
sched->n_splits = cur_split + 1;
//fprintf(stderr, "PASS 4 ASSIGNMENTS\n"); sched_print_assignments(sched, graph); fflush(stdout);
#if 1
// sanity check: all sources should have the same backend as the node
for (int i = 0; i < graph->n_nodes; i++) {
struct ggml_tensor * node = graph->nodes[i];
ggml_tallocr_t node_allocr = node_allocr(node);
if (node_allocr == NULL) {
fprintf(stderr, "!!!!!!! %s has no backend\n", node->name);
}
for (int j = 0; j < GGML_MAX_SRC; j++) {
struct ggml_tensor * src = node->src[j];
if (src == NULL) {
break;
}
ggml_tallocr_t src_allocr = node_allocr(src);
if (src_allocr != node_allocr /* && src_backend != NULL */) { // ignore nulls for now
fprintf(stderr, "!!!! %s has backend %s, src %d (%s) has backend %s\n",
node->name, node_allocr ? ggml_backend_name(ggml_tallocr_get_buffer(node_allocr)->backend) : "NULL",
j, src->name, src_allocr ? ggml_backend_name(ggml_tallocr_get_buffer(src_allocr)->backend) : "NULL");
}
}
}
#endif
// create copies of the graph for each split
// FIXME: avoid this copy, pass split inputs to ggml_gallocr_alloc_graph_n in some other way
struct ggml_cgraph * graph_copy = ggml_new_graph_custom(sched->ctx, graph->n_nodes + sched->n_splits*GGML_MAX_SPLIT_INPUTS, false);
for (int i = 0; i < sched->n_splits; i++) {
struct ggml_backend_sched_split * split = &sched->splits[i];
split->graph = ggml_graph_view(sched->ctx, graph, split->i_start, split->i_end);
// add inputs to the graph copy so that they are allocated by ggml-alloc at the start of the split
for (int j = 0; j < split->n_inputs; j++) {
struct ggml_tensor * input = split->inputs[j];
struct ggml_tensor * input_cpy = sched->node_copies[hash_id(input)][sched_allocr_prio(sched, split->tallocr)];
input_cpy->src[0] = input;
graph_copy->nodes[graph_copy->n_nodes++] = input_cpy;
}
for (int j = split->i_start; j < split->i_end; j++) {
graph_copy->nodes[graph_copy->n_nodes++] = graph->nodes[j];
}
}
sched->graph = graph_copy;
}
static void sched_alloc_splits(ggml_backend_sched_t sched) {
ggml_gallocr_alloc_graph_n(
sched->galloc,
sched->graph,
sched->hash_set,
sched->node_talloc);
}
static void sched_compute_splits(ggml_backend_sched_t sched) {
uint64_t copy_us[GGML_MAX_BACKENDS] = {0};
uint64_t compute_us[GGML_MAX_BACKENDS] = {0};
struct ggml_backend_sched_split * splits = sched->splits;
for (int i = 0; i < sched->n_splits; i++) {
struct ggml_backend_sched_split * split = &splits[i];
ggml_backend_t split_backend = ggml_tallocr_get_buffer(split->tallocr)->backend;
int split_backend_id = sched_backend_prio(sched, split_backend);
// copy the input tensors to the split backend
uint64_t copy_start_us = ggml_time_us();
for (int j = 0; j < split->n_inputs; j++) {
struct ggml_tensor * input_cpy = sched->node_copies[hash_id(split->inputs[j])][sched_backend_prio(sched, split_backend)];
if (split->inputs[j]->buffer == NULL) {
if (split->inputs[j]->view_src == NULL) {
fprintf(stderr, "input %s has no buffer and no view_src\n", split->inputs[j]->name);
exit(1);
}
struct ggml_tensor * view = split->inputs[j];
view->backend = view->view_src->backend;
view->buffer = view->view_src->buffer;
view->data = (char *)view->view_src->data + view->view_offs;
ggml_backend_buffer_init_tensor(ggml_backend_sched_get_buffer(sched, view->buffer->backend), view);
}
if (input_cpy->buffer == NULL) {
fprintf(stderr, "input_cpy %s has no buffer\n", input_cpy->name);
exit(1);
}
GGML_ASSERT(split->inputs[j]->buffer->backend != input_cpy->buffer->backend);
GGML_ASSERT(input_cpy->buffer->backend == split_backend);
ggml_backend_tensor_copy(split->inputs[j], input_cpy);
}
// ggml_backend_synchronize(split_backend);
int64_t copy_end_us = ggml_time_us();
copy_us[split_backend_id] += copy_end_us - copy_start_us;
#if 0
char split_filename[GGML_MAX_NAME];
snprintf(split_filename, GGML_MAX_NAME, "split_%i_%s.dot", i, ggml_backend_name(split_backend));
ggml_graph_dump_dot(split->graph, NULL, split_filename);
#endif
uint64_t compute_start_us = ggml_time_us();
ggml_backend_graph_compute(split_backend, split->graph);
// ggml_backend_synchronize(split_backend);
uint64_t compute_end_us = ggml_time_us();
compute_us[split_backend_id] += compute_end_us - compute_start_us;
}
#if 0
// per-backend timings
fprintf(stderr, "sched_compute_splits times (%d splits):\n", sched->n_splits);
for (int i = 0; i < sched->n_backends; i++) {
if (copy_us[i] > 0 || compute_us[i] > 0) {
fprintf(stderr, "\t%5.5s: %lu us copy, %lu us compute\n", ggml_backend_name(sched->backends[i]), copy_us[i], compute_us[i]);
}
}
#endif
}
static void sched_reset(ggml_backend_sched_t sched) {
for (int i = 0; i < sched->n_backends; i++) {
ggml_tallocr_reset(sched->tallocs[i]);
}
}
ggml_backend_sched_t ggml_backend_sched_new(ggml_backend_t * backends, int n_backends) {
GGML_ASSERT(n_backends <= GGML_MAX_BACKENDS);
struct ggml_backend_sched * sched = malloc(sizeof(struct ggml_backend_sched));
memset(sched, 0, sizeof(struct ggml_backend_sched));
fprintf(stderr, "ggml_backend_sched size: %lu KB\n", sizeof(struct ggml_backend_sched)/1024);
sched->n_backends = n_backends;
for (int i = 0; i < n_backends; i++) {
sched->backends[i] = backends[i];
}
sched->galloc = ggml_gallocr_new();
// init measure allocs for each backend
for (int i = 0; i < n_backends; i++) {
sched->tallocs[i] = ggml_tallocr_new_measure_from_backend(backends[i]);
}
return sched;
}
void ggml_backend_sched_free(ggml_backend_sched_t sched) {
if (sched == NULL) {
return;
}
for (int i = 0; i < sched->n_backends; i++) {
ggml_tallocr_free(sched->tallocs[i]);
}
ggml_gallocr_free(sched->galloc);
free(sched->hash_set.keys);
free(sched->node_talloc);
free(sched->node_copies);
free(sched);
}
void ggml_backend_sched_init_measure(ggml_backend_sched_t sched, struct ggml_cgraph * measure_graph) {
// initialize hash tables
size_t hash_size = measure_graph->visited_hash_table.size + GGML_MAX_SPLITS*GGML_MAX_SPLIT_INPUTS;
sched->hash_set.size = hash_size;
sched->hash_set.keys = malloc(sizeof(sched->hash_set.keys[0]) * hash_size);
sched->node_talloc = malloc(sizeof(sched->node_talloc[0]) * hash_size);
sched->node_copies = malloc(sizeof(sched->node_copies[0]) * hash_size);
sched_split_graph(sched, measure_graph);
sched_alloc_splits(sched);
// allocate buffers and reset allocators
for (int i = 0; i < sched->n_backends; i++) {
size_t size = ggml_tallocr_max_size(sched->tallocs[i]);
ggml_tallocr_free(sched->tallocs[i]);
sched->tallocs[i] = ggml_tallocr_new_from_backend(sched->backends[i], size);
}
sched_reset(sched);
}
void ggml_backend_sched_graph_compute(ggml_backend_sched_t sched, struct ggml_cgraph * graph) {
GGML_ASSERT(sched->hash_set.size >= graph->visited_hash_table.size + GGML_MAX_SPLITS*GGML_MAX_SPLIT_INPUTS);
sched_split_graph(sched, graph);
sched_alloc_splits(sched);
sched_compute_splits(sched);
sched_reset(sched);
}
ggml_tallocr_t ggml_backend_sched_get_tallocr(ggml_backend_sched_t sched, ggml_backend_t backend) {
int backend_index = sched_backend_prio(sched, backend);
return sched->tallocs[backend_index];
}
ggml_backend_buffer_t ggml_backend_sched_get_buffer(ggml_backend_sched_t sched, ggml_backend_t backend) {
int backend_index = sched_backend_prio(sched, backend);
return ggml_tallocr_get_buffer(sched->tallocs[backend_index]);
}
void ggml_backend_sched_set_node_backend(ggml_backend_sched_t sched, struct ggml_tensor * node, ggml_backend_t backend) {
int backend_index = sched_backend_prio(sched, backend);
GGML_ASSERT(backend_index >= 0 && backend_index < sched->n_backends);
node_allocr(node) = sched->tallocs[backend_index];
}

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#pragma once
#include "ggml.h"
#include "ggml-alloc.h"
#ifdef __cplusplus
extern "C" {
#endif
//
// Backend buffer
//
struct ggml_backend_buffer;
typedef struct ggml_backend_buffer * ggml_backend_buffer_t;
// backend buffer functions
GGML_API void ggml_backend_buffer_free (ggml_backend_buffer_t buffer);
GGML_API size_t ggml_backend_buffer_get_alignment (ggml_backend_buffer_t buffer);
GGML_API void * ggml_backend_buffer_get_base (ggml_backend_buffer_t buffer);
GGML_API size_t ggml_backend_buffer_get_size (ggml_backend_buffer_t buffer);
GGML_API size_t ggml_backend_buffer_get_alloc_size(ggml_backend_buffer_t buffer, struct ggml_tensor * tensor);
GGML_API void ggml_backend_buffer_init_tensor (ggml_backend_buffer_t buffer, struct ggml_tensor * tensor);
GGML_API void ggml_backend_buffer_free_tensor (ggml_backend_buffer_t buffer, struct ggml_tensor * tensor);
//
// Backend
//
struct ggml_backend;
typedef struct ggml_backend * ggml_backend_t;
typedef void * ggml_backend_graph_plan_t;
GGML_API ggml_backend_t ggml_get_backend(const struct ggml_tensor * tensor);
GGML_API const char * ggml_backend_name(ggml_backend_t backend);
GGML_API void ggml_backend_free(ggml_backend_t backend);
GGML_API ggml_backend_buffer_t ggml_backend_alloc_buffer(ggml_backend_t backend, size_t size);
GGML_API size_t ggml_backend_get_alignment(ggml_backend_t backend);
GGML_API void ggml_backend_tensor_set_async( struct ggml_tensor * tensor, const void * data, size_t offset, size_t size);
GGML_API void ggml_backend_tensor_get_async(const struct ggml_tensor * tensor, void * data, size_t offset, size_t size);
GGML_API void ggml_backend_tensor_set( struct ggml_tensor * tensor, const void * data, size_t offset, size_t size);
GGML_API void ggml_backend_tensor_get(const struct ggml_tensor * tensor, void * data, size_t offset, size_t size);
GGML_API void ggml_backend_synchronize(ggml_backend_t backend);
GGML_API ggml_backend_graph_plan_t ggml_backend_graph_plan_create (ggml_backend_t backend, struct ggml_cgraph * cgraph);
GGML_API void ggml_backend_graph_plan_free (ggml_backend_t backend, ggml_backend_graph_plan_t plan);
GGML_API void ggml_backend_graph_plan_compute(ggml_backend_t backend, ggml_backend_graph_plan_t plan);
GGML_API void ggml_backend_graph_compute (ggml_backend_t backend, struct ggml_cgraph * cgraph);
GGML_API bool ggml_backend_supports_op (ggml_backend_t backend, const struct ggml_tensor * op);
// tensor copy between different backends
GGML_API void ggml_backend_tensor_copy(struct ggml_tensor * src, struct ggml_tensor * dst);
//
// CPU backend
//
GGML_API ggml_backend_t ggml_backend_cpu_init(void);
GGML_API bool ggml_backend_is_cpu(ggml_backend_t backend);
GGML_API void ggml_backend_cpu_set_n_threads(ggml_backend_t backend_cpu, int n_threads);
// Create a backend buffer from an existing pointer
GGML_API ggml_backend_buffer_t ggml_backend_cpu_buffer_from_ptr(ggml_backend_t backend_cpu, void * ptr, size_t size);
//
// Backend scheduler
//
// The backend scheduler allows for multiple backends to be used together
// Handles compute buffer allocation, assignment of tensors to backends, and copying of tensors between backends
// The backends are selected based on:
// - the backend that supports the operation
// - the location of the pre-allocated tensors (e.g. the weights)
/*
Example usage:
sched = ggml_backend_sched_new({backend_gpu, backend_gpu2, backend_cpu}, num_backends);
// sched is initialized with measure allocators and cannot be used until allocated with a measure graph
// initialize buffers from a measure graph
measure_graph = build_graph(sched); // use the allocr to allocate inputs as needed
// in build_graph:
build_graph(...) {
// allocating tensors in a specific backend (optional, recommended: pre-allocate inputs in a different buffer)
alloc_cpu = ggml_backend_sched_get_allocr(sched, backend_cpu);
ggml_allocr_alloc(alloc_cpu, tensor);
// manually assigning nodes to a backend (optional, shouldn't be needed in most cases)
struct ggml_tensor * node = ggml_mul_mat(ctx, ...);
ggml_backend_sched_set_node_backend(sched, node, backend_gpu);
}
// allocate backend buffers from measure graph
ggml_backend_sched_init_measure(sched, measure_graph);
// the scheduler is now ready to compute graphs
// compute
graph = build_graph(sched);
ggml_backend_sched_graph_compute(sched, graph);
*/
struct ggml_backend_sched;
typedef struct ggml_backend_sched * ggml_backend_sched_t;
// Initialize a backend scheduler
GGML_API ggml_backend_sched_t ggml_backend_sched_new(ggml_backend_t * backends, int n_backends);
GGML_API void ggml_backend_sched_free(ggml_backend_sched_t sched);
// Initialize backend buffers from a measure graph
GGML_API void ggml_backend_sched_init_measure(ggml_backend_sched_t sched, struct ggml_cgraph * measure_graph);
GGML_API ggml_tallocr_t ggml_backend_sched_get_tallocr(ggml_backend_sched_t sched, ggml_backend_t backend);
GGML_API ggml_backend_buffer_t ggml_backend_sched_get_buffer (ggml_backend_sched_t sched, ggml_backend_t backend);
GGML_API void ggml_backend_sched_set_node_backend(ggml_backend_sched_t sched, struct ggml_tensor * node, ggml_backend_t backend);
// Allocate a graph on the backend scheduler
GGML_API void ggml_backend_sched_graph_compute(
ggml_backend_sched_t sched,
struct ggml_cgraph * graph);
#ifdef __cplusplus
}
#endif

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#pragma once
#include "ggml.h"
// GGML internal header
#include <assert.h>
#include <stddef.h>
#include <stdbool.h>
#include <string.h> // memcpy
#include <math.h> // fabsf
#ifdef __cplusplus
extern "C" {
#endif
// static_assert should be a #define, but if it's not,
// fall back to the _Static_assert C11 keyword.
// if C99 - static_assert is noop
// ref: https://stackoverflow.com/a/53923785/4039976
#ifndef static_assert
#if defined(__STDC_VERSION__) && (__STDC_VERSION__ >= 201100L)
#define static_assert(cond, msg) _Static_assert(cond, msg)
#else
#define static_assert(cond, msg) struct global_scope_noop_trick
#endif
#endif
// __FMA__ and __F16C__ are not defined in MSVC, however they are implied with AVX2/AVX512
#if defined(_MSC_VER) && (defined(__AVX2__) || defined(__AVX512F__))
#ifndef __FMA__
#define __FMA__
#endif
#ifndef __F16C__
#define __F16C__
#endif
#ifndef __SSE3__
#define __SSE3__
#endif
#endif
#undef MIN
#undef MAX
#define MIN(a, b) ((a) < (b) ? (a) : (b))
#define MAX(a, b) ((a) > (b) ? (a) : (b))
// 16-bit float
// on Arm, we use __fp16
// on x86, we use uint16_t
#if defined(__ARM_NEON) && !defined(_MSC_VER)
// if YCM cannot find <arm_neon.h>, make a symbolic link to it, for example:
//
// $ ln -sfn /Library/Developer/CommandLineTools/usr/lib/clang/13.1.6/include/arm_neon.h ./src/
//
#include <arm_neon.h>
#define GGML_COMPUTE_FP16_TO_FP32(x) ((float) (x))
#define GGML_COMPUTE_FP32_TO_FP16(x) (x)
#define GGML_FP16_TO_FP32(x) ((float) (x))
#define GGML_FP32_TO_FP16(x) (x)
#else
#ifdef __wasm_simd128__
#include <wasm_simd128.h>
#else
#ifdef __POWER9_VECTOR__
#include <altivec.h>
#undef bool
#define bool _Bool
#else
#if defined(_MSC_VER) || defined(__MINGW32__)
#include <intrin.h>
#else
#if defined(__AVX__) || defined(__AVX2__) || defined(__AVX512F__) || defined(__SSSE3__) || defined(__SSE3__)
#if !defined(__riscv)
#include <immintrin.h>
#endif
#endif
#endif
#endif
#endif
#ifdef __riscv_v_intrinsic
#include <riscv_vector.h>
#endif
#ifdef __F16C__
#ifdef _MSC_VER
#define GGML_COMPUTE_FP16_TO_FP32(x) _mm_cvtss_f32(_mm_cvtph_ps(_mm_cvtsi32_si128(x)))
#define GGML_COMPUTE_FP32_TO_FP16(x) _mm_extract_epi16(_mm_cvtps_ph(_mm_set_ss(x), 0), 0)
#else
#define GGML_COMPUTE_FP16_TO_FP32(x) _cvtsh_ss(x)
#define GGML_COMPUTE_FP32_TO_FP16(x) _cvtss_sh(x, 0)
#endif
#elif defined(__POWER9_VECTOR__)
#define GGML_COMPUTE_FP16_TO_FP32(x) ggml_compute_fp16_to_fp32(x)
#define GGML_COMPUTE_FP32_TO_FP16(x) ggml_compute_fp32_to_fp16(x)
/* the inline asm below is about 12% faster than the lookup method */
#define GGML_FP16_TO_FP32(x) GGML_COMPUTE_FP16_TO_FP32(x)
#define GGML_FP32_TO_FP16(x) GGML_COMPUTE_FP32_TO_FP16(x)
static inline float ggml_compute_fp16_to_fp32(ggml_fp16_t h) {
register float f;
register double d;
__asm__(
"mtfprd %0,%2\n"
"xscvhpdp %0,%0\n"
"frsp %1,%0\n" :
/* temp */ "=d"(d),
/* out */ "=f"(f):
/* in */ "r"(h));
return f;
}
static inline ggml_fp16_t ggml_compute_fp32_to_fp16(float f) {
register double d;
register ggml_fp16_t r;
__asm__( /* xscvdphp can work on double or single precision */
"xscvdphp %0,%2\n"
"mffprd %1,%0\n" :
/* temp */ "=d"(d),
/* out */ "=r"(r):
/* in */ "f"(f));
return r;
}
#else
// FP16 <-> FP32
// ref: https://github.com/Maratyszcza/FP16
static inline float fp32_from_bits(uint32_t w) {
union {
uint32_t as_bits;
float as_value;
} fp32;
fp32.as_bits = w;
return fp32.as_value;
}
static inline uint32_t fp32_to_bits(float f) {
union {
float as_value;
uint32_t as_bits;
} fp32;
fp32.as_value = f;
return fp32.as_bits;
}
static inline float ggml_compute_fp16_to_fp32(ggml_fp16_t h) {
const uint32_t w = (uint32_t) h << 16;
const uint32_t sign = w & UINT32_C(0x80000000);
const uint32_t two_w = w + w;
const uint32_t exp_offset = UINT32_C(0xE0) << 23;
#if defined(__STDC_VERSION__) && (__STDC_VERSION__ >= 199901L) || defined(__GNUC__) && !defined(__STRICT_ANSI__)
const float exp_scale = 0x1.0p-112f;
#else
const float exp_scale = fp32_from_bits(UINT32_C(0x7800000));
#endif
const float normalized_value = fp32_from_bits((two_w >> 4) + exp_offset) * exp_scale;
const uint32_t magic_mask = UINT32_C(126) << 23;
const float magic_bias = 0.5f;
const float denormalized_value = fp32_from_bits((two_w >> 17) | magic_mask) - magic_bias;
const uint32_t denormalized_cutoff = UINT32_C(1) << 27;
const uint32_t result = sign |
(two_w < denormalized_cutoff ? fp32_to_bits(denormalized_value) : fp32_to_bits(normalized_value));
return fp32_from_bits(result);
}
static inline ggml_fp16_t ggml_compute_fp32_to_fp16(float f) {
#if defined(__STDC_VERSION__) && (__STDC_VERSION__ >= 199901L) || defined(__GNUC__) && !defined(__STRICT_ANSI__)
const float scale_to_inf = 0x1.0p+112f;
const float scale_to_zero = 0x1.0p-110f;
#else
const float scale_to_inf = fp32_from_bits(UINT32_C(0x77800000));
const float scale_to_zero = fp32_from_bits(UINT32_C(0x08800000));
#endif
float base = (fabsf(f) * scale_to_inf) * scale_to_zero;
const uint32_t w = fp32_to_bits(f);
const uint32_t shl1_w = w + w;
const uint32_t sign = w & UINT32_C(0x80000000);
uint32_t bias = shl1_w & UINT32_C(0xFF000000);
if (bias < UINT32_C(0x71000000)) {
bias = UINT32_C(0x71000000);
}
base = fp32_from_bits((bias >> 1) + UINT32_C(0x07800000)) + base;
const uint32_t bits = fp32_to_bits(base);
const uint32_t exp_bits = (bits >> 13) & UINT32_C(0x00007C00);
const uint32_t mantissa_bits = bits & UINT32_C(0x00000FFF);
const uint32_t nonsign = exp_bits + mantissa_bits;
return (sign >> 16) | (shl1_w > UINT32_C(0xFF000000) ? UINT16_C(0x7E00) : nonsign);
}
#define GGML_COMPUTE_FP16_TO_FP32(x) ggml_compute_fp16_to_fp32(x)
#define GGML_COMPUTE_FP32_TO_FP16(x) ggml_compute_fp32_to_fp16(x)
#endif // __F16C__
#endif // __ARM_NEON
// precomputed f32 table for f16 (256 KB)
// defined in ggml.c, initialized in ggml_init()
extern float ggml_table_f32_f16[1 << 16];
// On ARM NEON, it's quicker to directly convert x -> x instead of calling into ggml_lookup_fp16_to_fp32,
// so we define GGML_FP16_TO_FP32 and GGML_FP32_TO_FP16 elsewhere for NEON.
// This is also true for POWER9.
#if !defined(GGML_FP16_TO_FP32) || !defined(GGML_FP32_TO_FP16)
inline static float ggml_lookup_fp16_to_fp32(ggml_fp16_t f) {
uint16_t s;
memcpy(&s, &f, sizeof(uint16_t));
return ggml_table_f32_f16[s];
}
#define GGML_FP16_TO_FP32(x) ggml_lookup_fp16_to_fp32(x)
#define GGML_FP32_TO_FP16(x) GGML_COMPUTE_FP32_TO_FP16(x)
#endif
#define GGML_HASHTABLE_FULL ((size_t)-1)
#define GGML_HASHTABLE_ALREADY_EXISTS ((size_t)-2)
bool ggml_hash_contains (const struct ggml_hash_set hash_set, struct ggml_tensor * key);
// returns GGML_HASHTABLE_FULL if table is full, otherwise the current index of the key or where it should be inserted
size_t ggml_hash_find (const struct ggml_hash_set hash_set, struct ggml_tensor * key);
// returns GGML_HAHSHTABLE_ALREADY_EXISTS if key already exists, index otherwise, asserts if table is full
size_t ggml_hash_insert ( struct ggml_hash_set hash_set, struct ggml_tensor * key);
// return index, asserts if table is full
size_t ggml_hash_find_or_insert( struct ggml_hash_set hash_set, struct ggml_tensor * key);
#ifdef __cplusplus
}
#endif

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@ -0,0 +1,224 @@
#pragma once
#include "ggml-impl.h"
// GGML internal header
#include <stdint.h>
#include <stddef.h>
#define QK4_0 32
typedef struct {
ggml_fp16_t d; // delta
uint8_t qs[QK4_0 / 2]; // nibbles / quants
} block_q4_0;
static_assert(sizeof(block_q4_0) == sizeof(ggml_fp16_t) + QK4_0 / 2, "wrong q4_0 block size/padding");
#define QK4_1 32
typedef struct {
ggml_fp16_t d; // delta
ggml_fp16_t m; // min
uint8_t qs[QK4_1 / 2]; // nibbles / quants
} block_q4_1;
static_assert(sizeof(block_q4_1) == 2 * sizeof(ggml_fp16_t) + QK4_1 / 2, "wrong q4_1 block size/padding");
#define QK5_0 32
typedef struct {
ggml_fp16_t d; // delta
uint8_t qh[4]; // 5-th bit of quants
uint8_t qs[QK5_0 / 2]; // nibbles / quants
} block_q5_0;
static_assert(sizeof(block_q5_0) == sizeof(ggml_fp16_t) + sizeof(uint32_t) + QK5_0 / 2, "wrong q5_0 block size/padding");
#define QK5_1 32
typedef struct {
ggml_fp16_t d; // delta
ggml_fp16_t m; // min
uint8_t qh[4]; // 5-th bit of quants
uint8_t qs[QK5_1 / 2]; // nibbles / quants
} block_q5_1;
static_assert(sizeof(block_q5_1) == 2 * sizeof(ggml_fp16_t) + sizeof(uint32_t) + QK5_1 / 2, "wrong q5_1 block size/padding");
#define QK8_0 32
typedef struct {
ggml_fp16_t d; // delta
int8_t qs[QK8_0]; // quants
} block_q8_0;
static_assert(sizeof(block_q8_0) == sizeof(ggml_fp16_t) + QK8_0, "wrong q8_0 block size/padding");
#define QK8_1 32
typedef struct {
float d; // delta
float s; // d * sum(qs[i])
int8_t qs[QK8_1]; // quants
} block_q8_1;
static_assert(sizeof(block_q8_1) == 2*sizeof(float) + QK8_1, "wrong q8_1 block size/padding");
//
// Super-block quantization structures
//
// Super-block size
#ifdef GGML_QKK_64
#define QK_K 64
#define K_SCALE_SIZE 4
#else
#define QK_K 256
#define K_SCALE_SIZE 12
#endif
// 2-bit quantization
// weight is represented as x = a * q + b
// 16 blocks of 16 elements each
// Effectively 2.5625 bits per weight
typedef struct {
uint8_t scales[QK_K/16]; // scales and mins, quantized with 4 bits
uint8_t qs[QK_K/4]; // quants
ggml_fp16_t d; // super-block scale for quantized scales
ggml_fp16_t dmin; // super-block scale for quantized mins
} block_q2_K;
static_assert(sizeof(block_q2_K) == 2*sizeof(ggml_fp16_t) + QK_K/16 + QK_K/4, "wrong q2_K block size/padding");
// 3-bit quantization
// weight is represented as x = a * q
// 16 blocks of 16 elements each
// Effectively 3.4375 bits per weight
#ifdef GGML_QKK_64
typedef struct {
uint8_t hmask[QK_K/8]; // quants - high bit
uint8_t qs[QK_K/4]; // quants - low 2 bits
uint8_t scales[2];
ggml_fp16_t d; // super-block scale
} block_q3_K;
static_assert(sizeof(block_q3_K) == sizeof(ggml_fp16_t) + QK_K / 4 + QK_K / 8 + 2, "wrong q3_K block size/padding");
#else
typedef struct {
uint8_t hmask[QK_K/8]; // quants - high bit
uint8_t qs[QK_K/4]; // quants - low 2 bits
uint8_t scales[12]; // scales, quantized with 6 bits
ggml_fp16_t d; // super-block scale
} block_q3_K;
static_assert(sizeof(block_q3_K) == sizeof(ggml_fp16_t) + QK_K / 4 + QK_K / 8 + 12, "wrong q3_K block size/padding");
#endif
// 4-bit quantization
// 8 blocks of 32 elements each
// weight is represented as x = a * q + b
// Effectively 4.5 bits per weight
#ifdef GGML_QKK_64
typedef struct {
ggml_fp16_t d[2]; // super-block scales/mins
uint8_t scales[2]; // 4-bit block scales/mins
uint8_t qs[QK_K/2]; // 4--bit quants
} block_q4_K;
static_assert(sizeof(block_q4_K) == 2*sizeof(ggml_fp16_t) + QK_K/2 + 2, "wrong q4_K block size/padding");
#else
typedef struct {
ggml_fp16_t d; // super-block scale for quantized scales
ggml_fp16_t dmin; // super-block scale for quantized mins
uint8_t scales[K_SCALE_SIZE]; // scales and mins, quantized with 6 bits
uint8_t qs[QK_K/2]; // 4--bit quants
} block_q4_K;
static_assert(sizeof(block_q4_K) == 2*sizeof(ggml_fp16_t) + K_SCALE_SIZE + QK_K/2, "wrong q4_K block size/padding");
#endif
// 5-bit quantization
// 8 blocks of 32 elements each
// weight is represented as x = a * q + b
// Effectively 5.5 bits per weight
#ifdef GGML_QKK_64
typedef struct {
ggml_fp16_t d; // super-block scale
int8_t scales[QK_K/16]; // 8-bit block scales
uint8_t qh[QK_K/8]; // quants, high bit
uint8_t qs[QK_K/2]; // quants, low 4 bits
} block_q5_K;
static_assert(sizeof(block_q5_K) == sizeof(ggml_fp16_t) + QK_K/2 + QK_K/8 + QK_K/16, "wrong q5_K block size/padding");
#else
typedef struct {
ggml_fp16_t d; // super-block scale for quantized scales
ggml_fp16_t dmin; // super-block scale for quantized mins
uint8_t scales[K_SCALE_SIZE]; // scales and mins, quantized with 6 bits
uint8_t qh[QK_K/8]; // quants, high bit
uint8_t qs[QK_K/2]; // quants, low 4 bits
} block_q5_K;
static_assert(sizeof(block_q5_K) == 2*sizeof(ggml_fp16_t) + K_SCALE_SIZE + QK_K/2 + QK_K/8, "wrong q5_K block size/padding");
#endif
// 6-bit quantization
// weight is represented as x = a * q
// 16 blocks of 16 elements each
// Effectively 6.5625 bits per weight
typedef struct {
uint8_t ql[QK_K/2]; // quants, lower 4 bits
uint8_t qh[QK_K/4]; // quants, upper 2 bits
int8_t scales[QK_K/16]; // scales, quantized with 8 bits
ggml_fp16_t d; // super-block scale
} block_q6_K;
static_assert(sizeof(block_q6_K) == sizeof(ggml_fp16_t) + QK_K / 16 + 3*QK_K/4, "wrong q6_K block size/padding");
// This is only used for intermediate quantization and dot products
typedef struct {
float d; // delta
int8_t qs[QK_K]; // quants
int16_t bsums[QK_K/16]; // sum of quants in groups of 16
} block_q8_K;
static_assert(sizeof(block_q8_K) == sizeof(float) + QK_K + QK_K/16*sizeof(int16_t), "wrong q8_K block size/padding");
// Quantization
void quantize_row_q4_0_reference(const float * restrict x, block_q4_0 * restrict y, int k);
void quantize_row_q4_1_reference(const float * restrict x, block_q4_1 * restrict y, int k);
void quantize_row_q5_0_reference(const float * restrict x, block_q5_0 * restrict y, int k);
void quantize_row_q5_1_reference(const float * restrict x, block_q5_1 * restrict y, int k);
void quantize_row_q8_0_reference(const float * restrict x, block_q8_0 * restrict y, int k);
void quantize_row_q8_1_reference(const float * restrict x, block_q8_1 * restrict y, int k);
void quantize_row_q2_K_reference(const float * restrict x, block_q2_K * restrict y, int k);
void quantize_row_q3_K_reference(const float * restrict x, block_q3_K * restrict y, int k);
void quantize_row_q4_K_reference(const float * restrict x, block_q4_K * restrict y, int k);
void quantize_row_q5_K_reference(const float * restrict x, block_q5_K * restrict y, int k);
void quantize_row_q6_K_reference(const float * restrict x, block_q6_K * restrict y, int k);
void quantize_row_q8_K_reference(const float * restrict x, block_q8_K * restrict y, int k);
void quantize_row_q4_0(const float * restrict x, void * restrict y, int k);
void quantize_row_q4_1(const float * restrict x, void * restrict y, int k);
void quantize_row_q5_0(const float * restrict x, void * restrict y, int k);
void quantize_row_q5_1(const float * restrict x, void * restrict y, int k);
void quantize_row_q8_0(const float * restrict x, void * restrict y, int k);
void quantize_row_q8_1(const float * restrict x, void * restrict y, int k);
void quantize_row_q2_K(const float * restrict x, void * restrict y, int k);
void quantize_row_q3_K(const float * restrict x, void * restrict y, int k);
void quantize_row_q4_K(const float * restrict x, void * restrict y, int k);
void quantize_row_q5_K(const float * restrict x, void * restrict y, int k);
void quantize_row_q6_K(const float * restrict x, void * restrict y, int k);
void quantize_row_q8_K(const float * restrict x, void * restrict y, int k);
// Dequantization
void dequantize_row_q4_0(const block_q4_0 * restrict x, float * restrict y, int k);
void dequantize_row_q4_1(const block_q4_1 * restrict x, float * restrict y, int k);
void dequantize_row_q5_0(const block_q5_0 * restrict x, float * restrict y, int k);
void dequantize_row_q5_1(const block_q5_1 * restrict x, float * restrict y, int k);
void dequantize_row_q8_0(const block_q8_0 * restrict x, float * restrict y, int k);
//void dequantize_row_q8_1(const block_q8_1 * restrict x, float * restrict y, int k);
void dequantize_row_q2_K(const block_q2_K * restrict x, float * restrict y, int k);
void dequantize_row_q3_K(const block_q3_K * restrict x, float * restrict y, int k);
void dequantize_row_q4_K(const block_q4_K * restrict x, float * restrict y, int k);
void dequantize_row_q5_K(const block_q5_K * restrict x, float * restrict y, int k);
void dequantize_row_q6_K(const block_q6_K * restrict x, float * restrict y, int k);
void dequantize_row_q8_K(const block_q8_K * restrict x, float * restrict y, int k);
// Dot product
void ggml_vec_dot_q4_0_q8_0(int n, float * restrict s, const void * restrict vx, const void * restrict vy);
void ggml_vec_dot_q4_1_q8_1(int n, float * restrict s, const void * restrict vx, const void * restrict vy);
void ggml_vec_dot_q5_0_q8_0(int n, float * restrict s, const void * restrict vx, const void * restrict vy);
void ggml_vec_dot_q5_1_q8_1(int n, float * restrict s, const void * restrict vx, const void * restrict vy);
void ggml_vec_dot_q8_0_q8_0(int n, float * restrict s, const void * restrict vx, const void * restrict vy);
void ggml_vec_dot_q2_K_q8_K(int n, float * restrict s, const void * restrict vx, const void * restrict vy);
void ggml_vec_dot_q3_K_q8_K(int n, float * restrict s, const void * restrict vx, const void * restrict vy);
void ggml_vec_dot_q4_K_q8_K(int n, float * restrict s, const void * restrict vx, const void * restrict vy);
void ggml_vec_dot_q5_K_q8_K(int n, float * restrict s, const void * restrict vx, const void * restrict vy);
void ggml_vec_dot_q6_K_q8_K(int n, float * restrict s, const void * restrict vx, const void * restrict vy);

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@ -1,17 +0,0 @@
ggml/src/ggml-metal/ggml-metal-embed.o: \
ggml/src/ggml-metal/ggml-metal.metal \
ggml/src/ggml-metal/ggml-metal-impl.h \
ggml/src/ggml-common.h
@echo "Embedding Metal library"
@sed -e '/__embed_ggml-common.h__/r ggml/src/ggml-common.h' -e '/__embed_ggml-common.h__/d' < ggml/src/ggml-metal/ggml-metal.metal > ggml/src/ggml-metal/ggml-metal-embed.metal.tmp
@sed -e '/#include "ggml-metal-impl.h"/r ggml/src/ggml-metal/ggml-metal-impl.h' -e '/#include "ggml-metal-impl.h"/d' < ggml/src/ggml-metal/ggml-metal-embed.metal.tmp > ggml/src/ggml-metal/ggml-metal-embed.metal
$(eval TEMP_ASSEMBLY=$(shell mktemp -d))
@echo ".section __DATA, __ggml_metallib" > $(TEMP_ASSEMBLY)/ggml-metal-embed.s
@echo ".globl _ggml_metallib_start" >> $(TEMP_ASSEMBLY)/ggml-metal-embed.s
@echo "_ggml_metallib_start:" >> $(TEMP_ASSEMBLY)/ggml-metal-embed.s
@echo ".incbin \"ggml/src/ggml-metal/ggml-metal-embed.metal\"" >> $(TEMP_ASSEMBLY)/ggml-metal-embed.s
@echo ".globl _ggml_metallib_end" >> $(TEMP_ASSEMBLY)/ggml-metal-embed.s
@echo "_ggml_metallib_end:" >> $(TEMP_ASSEMBLY)/ggml-metal-embed.s
$(CC) $(CFLAGS) -c $(TEMP_ASSEMBLY)/ggml-metal-embed.s -o $@
@rm -f ${TEMP_ASSEMBLY}/ggml-metal-embed.s
@rmdir ${TEMP_ASSEMBLY}

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@ -1,6 +0,0 @@
ggml/src/ggml-metal/ggml-metal.o: \
ggml/src/ggml-metal/ggml-metal.m \
ggml/src/ggml-metal/ggml-metal-impl.h \
ggml/include/ggml-metal.h \
ggml/include/ggml.h
$(CC) $(CFLAGS) -c $< -o $@

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@ -3,13 +3,6 @@
#include "whisper.h"
typedef struct {
VALUE *context;
VALUE user_data;
VALUE callback;
VALUE callbacks;
} ruby_whisper_callback_container;
typedef struct {
struct whisper_context *context;
} ruby_whisper;
@ -17,9 +10,6 @@ typedef struct {
typedef struct {
struct whisper_full_params params;
bool diarize;
ruby_whisper_callback_container *new_segment_callback_container;
ruby_whisper_callback_container *progress_callback_container;
ruby_whisper_callback_container *abort_callback_container;
} ruby_whisper_params;
#endif

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@ -1,6 +0,0 @@
require "yaml"
sources = `git ls-files -z ../..`.split("\x0")
paths = YAML.load_file("../../.github/workflows/bindings-ruby.yml")[true]["push"]["paths"]
paths.delete "bindings/ruby/**"
EXTSOURCES = (Dir.glob(paths, base: "../..").collect {|path| "../../#{path}"} << "../../LICENSE") & sources

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@ -1,2 +0,0 @@
require "whisper.so"
require "whisper/model/uri"

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@ -1,163 +0,0 @@
require "whisper.so"
require "uri"
require "net/http"
require "time"
require "pathname"
require "io/console/size"
class Whisper::Model
class URI
def initialize(uri)
@uri = URI(uri)
end
def to_path
cache
cache_path.to_path
end
def clear_cache
path = cache_path
path.delete if path.exist?
end
private
def cache_path
base_cache_dir/@uri.host/@uri.path[1..]
end
def base_cache_dir
base = case RUBY_PLATFORM
when /mswin|mingw/
ENV.key?("LOCALAPPDATA") ? Pathname(ENV["LOCALAPPDATA"]) : Pathname(Dir.home)/"AppData/Local"
when /darwin/
Pathname(Dir.home)/"Library/Caches"
else
ENV.key?("XDG_CACHE_HOME") ? ENV["XDG_CACHE_HOME"] : Pathname(Dir.home)/".cache"
end
base/"whisper.cpp"
end
def cache
path = cache_path
headers = {}
headers["if-modified-since"] = path.mtime.httpdate if path.exist?
request @uri, headers
path
end
def request(uri, headers)
Net::HTTP.start uri.host, uri.port, use_ssl: uri.scheme == "https" do |http|
request = Net::HTTP::Get.new(uri, headers)
http.request request do |response|
case response
when Net::HTTPNotModified
# noop
when Net::HTTPOK
download response
when Net::HTTPRedirection
request URI(response["location"]), headers
else
return if headers.key?("if-modified-since") # Use cache file
raise "#{response.code} #{response.message}\n#{response.body}"
end
end
end
end
def download(response)
path = cache_path
path.dirname.mkpath unless path.dirname.exist?
downloading_path = Pathname("#{path}.downloading")
size = response.content_length
downloading_path.open "wb" do |file|
downloaded = 0
response.read_body do |chunk|
file << chunk
downloaded += chunk.bytesize
show_progress downloaded, size
end
$stderr.puts
end
downloading_path.rename path
end
def show_progress(current, size)
progress_rate_available = size && $stderr.tty?
unless @prev
@prev = Time.now
$stderr.puts "Downloading #{@uri} to #{cache_path}"
end
now = Time.now
if progress_rate_available
return if now - @prev < 1 && current < size
progress_width = 20
progress = current.to_f / size
arrow_length = progress * progress_width
arrow = "=" * (arrow_length - 1) + ">" + " " * (progress_width - arrow_length)
line = "[#{arrow}] (#{format_bytesize(current)} / #{format_bytesize(size)})"
padding = ' ' * ($stderr.winsize[1] - line.size)
$stderr.print "\r#{line}#{padding}"
else
return if now - @prev < 1
$stderr.print "."
end
@prev = now
end
def format_bytesize(bytesize)
return "0.0 B" if bytesize.zero?
units = %w[B KiB MiB GiB TiB]
exp = (Math.log(bytesize) / Math.log(1024)).to_i
format("%.1f %s", bytesize.to_f / 1024 ** exp, units[exp])
end
end
@pre_converted_models = {}
%w[
tiny
tiny.en
tiny-q5_1
tiny.en-q5_1
tiny-q8_0
base
base.en
base-q5_1
base.en-q5_1
base-q8_0
small
small.en
small.en-tdrz
small-q5_1
small.en-q5_1
small-q8_0
medium
medium.en
medium-q5_0
medium.en-q5_0
medium-q8_0
large-v1
large-v2
large-v2-q5_0
large-v2-q8_0
large-v3
large-v3-q5_0
large-v3-turbo
large-v3-turbo-q5_0
large-v3-turbo-q8_0
].each do |name|
@pre_converted_models[name] = URI.new("https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-#{name}.bin")
end
class << self
attr_reader :pre_converted_models
end
end

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@ -1,24 +0,0 @@
require "test/unit"
require "whisper"
require_relative "jfk_reader/jfk_reader"
class TestBase < Test::Unit::TestCase
AUDIO = File.join(__dir__, "..", "..", "..", "samples", "jfk.wav")
class << self
attr_reader :whisper
def startup
@whisper = Whisper::Context.new("base.en")
params = Whisper::Params.new
params.print_timestamps = false
@whisper.transcribe(TestBase::AUDIO, params)
end
end
private
def whisper
self.class.whisper
end
end

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Makefile
jfk_reader.o
jfk_reader.so
jfk_reader.bundle
jfk_reader.dll

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@ -1,3 +0,0 @@
require "mkmf"
create_makefile("jfk_reader")

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@ -1,68 +0,0 @@
#include <ruby.h>
#include <ruby/memory_view.h>
#include <ruby/encoding.h>
static VALUE
jfk_reader_initialize(VALUE self, VALUE audio_path)
{
rb_iv_set(self, "audio_path", audio_path);
return Qnil;
}
static bool
jfk_reader_get_memory_view(const VALUE obj, rb_memory_view_t *view, int flags)
{
VALUE audio_path = rb_iv_get(obj, "audio_path");
const char *audio_path_str = StringValueCStr(audio_path);
const int n_samples = 176000;
float *data = (float *)malloc(n_samples * sizeof(float));
short *samples = (short *)malloc(n_samples * sizeof(short));
FILE *file = fopen(audio_path_str, "rb");
fseek(file, 78, SEEK_SET);
fread(samples, sizeof(short), n_samples, file);
fclose(file);
for (int i = 0; i < n_samples; i++) {
data[i] = samples[i]/32768.0;
}
view->obj = obj;
view->data = (void *)data;
view->byte_size = sizeof(float) * n_samples;
view->readonly = true;
view->format = "f";
view->item_size = sizeof(float);
view->item_desc.components = NULL;
view->item_desc.length = 0;
view->ndim = 1;
view->shape = NULL;
view->sub_offsets = NULL;
view->private_data = NULL;
return true;
}
static bool
jfk_reader_release_memory_view(const VALUE obj, rb_memory_view_t *view)
{
return true;
}
static bool
jfk_reader_memory_view_available_p(const VALUE obj)
{
return true;
}
static const rb_memory_view_entry_t jfk_reader_view_entry = {
jfk_reader_get_memory_view,
jfk_reader_release_memory_view,
jfk_reader_memory_view_available_p
};
void Init_jfk_reader(void)
{
VALUE cJFKReader = rb_define_class("JFKReader", rb_cObject);
rb_memory_view_register(cJFKReader, &jfk_reader_view_entry);
rb_define_method(cJFKReader, "initialize", jfk_reader_initialize, 1);
}

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@ -1,160 +0,0 @@
require_relative "helper"
class TestCallback < TestBase
def setup
GC.start
@params = Whisper::Params.new
@whisper = Whisper::Context.new("base.en")
@audio = File.join(AUDIO)
end
def test_new_segment_callback
@params.new_segment_callback = ->(context, state, n_new, user_data) {
assert_kind_of Integer, n_new
assert n_new > 0
assert_same @whisper, context
n_segments = context.full_n_segments
n_new.times do |i|
i_segment = n_segments - 1 + i
start_time = context.full_get_segment_t0(i_segment) * 10
end_time = context.full_get_segment_t1(i_segment) * 10
text = context.full_get_segment_text(i_segment)
assert_kind_of Integer, start_time
assert start_time >= 0
assert_kind_of Integer, end_time
assert end_time > 0
assert_match /ask not what your country can do for you, ask what you can do for your country/, text if i_segment == 0
end
}
@whisper.transcribe(@audio, @params)
end
def test_new_segment_callback_closure
search_word = "what"
@params.new_segment_callback = ->(context, state, n_new, user_data) {
n_segments = context.full_n_segments
n_new.times do |i|
i_segment = n_segments - 1 + i
text = context.full_get_segment_text(i_segment)
if text.include?(search_word)
t0 = context.full_get_segment_t0(i_segment)
t1 = context.full_get_segment_t1(i_segment)
raise "search word '#{search_word}' found at between #{t0} and #{t1}"
end
end
}
assert_raise RuntimeError do
@whisper.transcribe(@audio, @params)
end
end
def test_new_segment_callback_user_data
udata = Object.new
@params.new_segment_callback_user_data = udata
@params.new_segment_callback = ->(context, state, n_new, user_data) {
assert_same udata, user_data
}
@whisper.transcribe(@audio, @params)
end
def test_new_segment_callback_user_data_gc
@params.new_segment_callback_user_data = "My user data"
@params.new_segment_callback = ->(context, state, n_new, user_data) {
assert_equal "My user data", user_data
}
GC.start
assert_same @whisper, @whisper.transcribe(@audio, @params)
end
def test_progress_callback
first = nil
last = nil
@params.progress_callback = ->(context, state, progress, user_data) {
assert_kind_of Integer, progress
assert 0 <= progress && progress <= 100
assert_same @whisper, context
first = progress if first.nil?
last = progress
}
@whisper.transcribe(@audio, @params)
assert_equal 0, first
assert_equal 100, last
end
def test_progress_callback_user_data
udata = Object.new
@params.progress_callback_user_data = udata
@params.progress_callback = ->(context, state, n_new, user_data) {
assert_same udata, user_data
}
@whisper.transcribe(@audio, @params)
end
def test_on_progress
first = nil
last = nil
@params.on_progress do |progress|
assert_kind_of Integer, progress
assert 0 <= progress && progress <= 100
first = progress if first.nil?
last = progress
end
@whisper.transcribe(@audio, @params)
assert_equal 0, first
assert_equal 100, last
end
def test_abort_callback
i = 0
@params.abort_callback = ->(user_data) {
assert_nil user_data
i += 1
return false
}
@whisper.transcribe(@audio, @params)
assert i > 0
end
def test_abort_callback_abort
i = 0
@params.abort_callback = ->(user_data) {
i += 1
return i == 3
}
@whisper.transcribe(@audio, @params)
assert_equal 3, i
end
def test_abort_callback_user_data
udata = Object.new
@params.abort_callback_user_data = udata
yielded = nil
@params.abort_callback = ->(user_data) {
yielded = user_data
}
@whisper.transcribe(@audio, @params)
assert_same udata, yielded
end
def test_abort_on
do_abort = false
aborted_from_callback = false
@params.on_new_segment do |segment|
do_abort = true if segment.text.match? /ask/
end
i = 0
@params.abort_on do
i += 1
do_abort
end
@whisper.transcribe(@audio, @params)
assert i > 0
end
end

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@ -1,20 +0,0 @@
require_relative "helper"
class TestError < TestBase
def test_error
error = Whisper::Error.new(-2)
assert_equal "failed to compute log mel spectrogram", error.message
assert_equal -2, error.code
end
def test_unknown_error
error = Whisper::Error.new(-20)
assert_equal "unknown error", error.message
end
def test_non_int_code
assert_raise TypeError do
error = Whisper::Error.new("non int")
end
end
end

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@ -1,71 +0,0 @@
require_relative "helper"
require "pathname"
class TestModel < TestBase
def test_model
whisper = Whisper::Context.new("base.en")
assert_instance_of Whisper::Model, whisper.model
end
def test_attributes
whisper = Whisper::Context.new("base.en")
model = whisper.model
assert_equal 51864, model.n_vocab
assert_equal 1500, model.n_audio_ctx
assert_equal 512, model.n_audio_state
assert_equal 8, model.n_audio_head
assert_equal 6, model.n_audio_layer
assert_equal 448, model.n_text_ctx
assert_equal 512, model.n_text_state
assert_equal 8, model.n_text_head
assert_equal 6, model.n_text_layer
assert_equal 80, model.n_mels
assert_equal 1, model.ftype
assert_equal "base", model.type
end
def test_gc
model = Whisper::Context.new("base.en").model
GC.start
assert_equal 51864, model.n_vocab
assert_equal 1500, model.n_audio_ctx
assert_equal 512, model.n_audio_state
assert_equal 8, model.n_audio_head
assert_equal 6, model.n_audio_layer
assert_equal 448, model.n_text_ctx
assert_equal 512, model.n_text_state
assert_equal 8, model.n_text_head
assert_equal 6, model.n_text_layer
assert_equal 80, model.n_mels
assert_equal 1, model.ftype
assert_equal "base", model.type
end
def test_pathname
path = Pathname(Whisper::Model.pre_converted_models["base.en"].to_path)
whisper = Whisper::Context.new(path)
model = whisper.model
assert_equal 51864, model.n_vocab
assert_equal 1500, model.n_audio_ctx
assert_equal 512, model.n_audio_state
assert_equal 8, model.n_audio_head
assert_equal 6, model.n_audio_layer
assert_equal 448, model.n_text_ctx
assert_equal 512, model.n_text_state
assert_equal 8, model.n_text_head
assert_equal 6, model.n_text_layer
assert_equal 80, model.n_mels
assert_equal 1, model.ftype
assert_equal "base", model.type
end
def test_auto_download
path = Whisper::Model.pre_converted_models["base.en"].to_path
assert_path_exist path
assert_equal 147964211, File.size(path)
end
end

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@ -1,31 +0,0 @@
require_relative "helper"
require 'tempfile'
require 'tmpdir'
require 'shellwords'
class TestPackage < TestBase
def test_build
Tempfile.create do |file|
assert system("gem", "build", "whispercpp.gemspec", "--output", file.to_path.shellescape, exception: true)
assert file.size > 0
assert_path_exist file.to_path
end
end
sub_test_case "Building binary on installation" do
def setup
system "rake", "build", exception: true
end
def test_install
match_data = `rake -Tbuild`.match(/(whispercpp-(.+)\.gem)/)
filename = match_data[1]
version = match_data[2]
basename = "whisper.#{RbConfig::CONFIG["DLEXT"]}"
Dir.mktmpdir do |dir|
system "gem", "install", "--install-dir", dir.shellescape, "--no-document", "pkg/#{filename.shellescape}", exception: true
assert_path_exist File.join(dir, "gems/whispercpp-#{version}/lib", basename)
end
end
end
end

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@ -1,160 +0,0 @@
require_relative "helper"
class TestParams < TestBase
def setup
@params = Whisper::Params.new
end
def test_language
@params.language = "en"
assert_equal @params.language, "en"
@params.language = "auto"
assert_equal @params.language, "auto"
end
def test_offset
@params.offset = 10_000
assert_equal @params.offset, 10_000
@params.offset = 0
assert_equal @params.offset, 0
end
def test_duration
@params.duration = 60_000
assert_equal @params.duration, 60_000
@params.duration = 0
assert_equal @params.duration, 0
end
def test_max_text_tokens
@params.max_text_tokens = 300
assert_equal @params.max_text_tokens, 300
@params.max_text_tokens = 0
assert_equal @params.max_text_tokens, 0
end
def test_translate
@params.translate = true
assert @params.translate
@params.translate = false
assert !@params.translate
end
def test_no_context
@params.no_context = true
assert @params.no_context
@params.no_context = false
assert !@params.no_context
end
def test_single_segment
@params.single_segment = true
assert @params.single_segment
@params.single_segment = false
assert !@params.single_segment
end
def test_print_special
@params.print_special = true
assert @params.print_special
@params.print_special = false
assert !@params.print_special
end
def test_print_progress
@params.print_progress = true
assert @params.print_progress
@params.print_progress = false
assert !@params.print_progress
end
def test_print_realtime
@params.print_realtime = true
assert @params.print_realtime
@params.print_realtime = false
assert !@params.print_realtime
end
def test_print_timestamps
@params.print_timestamps = true
assert @params.print_timestamps
@params.print_timestamps = false
assert !@params.print_timestamps
end
def test_suppress_blank
@params.suppress_blank = true
assert @params.suppress_blank
@params.suppress_blank = false
assert !@params.suppress_blank
end
def test_suppress_nst
@params.suppress_nst = true
assert @params.suppress_nst
@params.suppress_nst = false
assert !@params.suppress_nst
end
def test_token_timestamps
@params.token_timestamps = true
assert @params.token_timestamps
@params.token_timestamps = false
assert !@params.token_timestamps
end
def test_split_on_word
@params.split_on_word = true
assert @params.split_on_word
@params.split_on_word = false
assert !@params.split_on_word
end
def test_initial_prompt
assert_nil @params.initial_prompt
@params.initial_prompt = "You are a polite person."
assert_equal "You are a polite person.", @params.initial_prompt
end
def test_temperature
assert_equal 0.0, @params.temperature
@params.temperature = 0.5
assert_equal 0.5, @params.temperature
end
def test_max_initial_ts
assert_equal 1.0, @params.max_initial_ts
@params.max_initial_ts = 600.0
assert_equal 600.0, @params.max_initial_ts
end
def test_length_penalty
assert_equal -1.0, @params.length_penalty
@params.length_penalty = 0.5
assert_equal 0.5, @params.length_penalty
end
def test_temperature_inc
assert_in_delta 0.2, @params.temperature_inc
@params.temperature_inc = 0.5
assert_in_delta 0.5, @params.temperature_inc
end
def test_entropy_thold
assert_in_delta 2.4, @params.entropy_thold
@params.entropy_thold = 3.0
assert_in_delta 3.0, @params.entropy_thold
end
def test_logprob_thold
assert_in_delta -1.0, @params.logprob_thold
@params.logprob_thold = -0.5
assert_in_delta -0.5, @params.logprob_thold
end
def test_no_speech_thold
assert_in_delta 0.6, @params.no_speech_thold
@params.no_speech_thold = 0.2
assert_in_delta 0.2, @params.no_speech_thold
end
end

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@ -1,74 +0,0 @@
require_relative "helper"
class TestSegment < TestBase
def test_iteration
whisper.each_segment do |segment|
assert_instance_of Whisper::Segment, segment
end
end
def test_enumerator
enum = whisper.each_segment
assert_instance_of Enumerator, enum
enum.to_a.each_with_index do |segment, index|
assert_instance_of Whisper::Segment, segment
assert_kind_of Integer, index
end
end
def test_start_time
i = 0
whisper.each_segment do |segment|
assert_equal 0, segment.start_time if i == 0
i += 1
end
end
def test_end_time
i = 0
whisper.each_segment do |segment|
assert_equal whisper.full_get_segment_t1(i) * 10, segment.end_time
i += 1
end
end
def test_no_speech_prob
no_speech_prob = nil
whisper.each_segment do |segment|
no_speech_prob = segment.no_speech_prob
end
assert no_speech_prob > 0.0
end
def test_on_new_segment
params = Whisper::Params.new
seg = nil
index = 0
params.on_new_segment do |segment|
assert_instance_of Whisper::Segment, segment
if index == 0
seg = segment
assert_equal 0, segment.start_time
assert_match /ask not what your country can do for you, ask what you can do for your country/, segment.text
end
index += 1
end
whisper.transcribe(AUDIO, params)
assert_equal 0, seg.start_time
assert_match /ask not what your country can do for you, ask what you can do for your country/, seg.text
end
def test_on_new_segment_twice
params = Whisper::Params.new
seg = nil
params.on_new_segment do |segment|
seg = segment
return
end
params.on_new_segment do |segment|
assert_same seg, segment
return
end
whisper.transcribe(AUDIO, params)
end
end

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@ -1,217 +1,138 @@
require_relative "helper"
require "stringio"
require "etc"
TOPDIR = File.expand_path(File.join(File.dirname(__FILE__), '..'))
EXTDIR = File.join(TOPDIR, 'ext')
#$LIBDIR = File.join(TOPDIR, 'lib')
#$:.unshift(LIBDIR)
$:.unshift(EXTDIR)
# Exists to detect memory-related bug
Whisper.log_set ->(level, buffer, user_data) {}, nil
require 'whisper'
require 'test/unit'
class TestWhisper < TestBase
class TestWhisper < Test::Unit::TestCase
def setup
@params = Whisper::Params.new
end
def test_language
@params.language = "en"
assert_equal @params.language, "en"
@params.language = "auto"
assert_equal @params.language, "auto"
end
def test_offset
@params.offset = 10_000
assert_equal @params.offset, 10_000
@params.offset = 0
assert_equal @params.offset, 0
end
def test_duration
@params.duration = 60_000
assert_equal @params.duration, 60_000
@params.duration = 0
assert_equal @params.duration, 0
end
def test_max_text_tokens
@params.max_text_tokens = 300
assert_equal @params.max_text_tokens, 300
@params.max_text_tokens = 0
assert_equal @params.max_text_tokens, 0
end
def test_translate
@params.translate = true
assert @params.translate
@params.translate = false
assert !@params.translate
end
def test_no_context
@params.no_context = true
assert @params.no_context
@params.no_context = false
assert !@params.no_context
end
def test_single_segment
@params.single_segment = true
assert @params.single_segment
@params.single_segment = false
assert !@params.single_segment
end
def test_print_special
@params.print_special = true
assert @params.print_special
@params.print_special = false
assert !@params.print_special
end
def test_print_progress
@params.print_progress = true
assert @params.print_progress
@params.print_progress = false
assert !@params.print_progress
end
def test_print_realtime
@params.print_realtime = true
assert @params.print_realtime
@params.print_realtime = false
assert !@params.print_realtime
end
def test_print_timestamps
@params.print_timestamps = true
assert @params.print_timestamps
@params.print_timestamps = false
assert !@params.print_timestamps
end
def test_suppress_blank
@params.suppress_blank = true
assert @params.suppress_blank
@params.suppress_blank = false
assert !@params.suppress_blank
end
def test_suppress_non_speech_tokens
@params.suppress_non_speech_tokens = true
assert @params.suppress_non_speech_tokens
@params.suppress_non_speech_tokens = false
assert !@params.suppress_non_speech_tokens
end
def test_token_timestamps
@params.token_timestamps = true
assert @params.token_timestamps
@params.token_timestamps = false
assert !@params.token_timestamps
end
def test_split_on_word
@params.split_on_word = true
assert @params.split_on_word
@params.split_on_word = false
assert !@params.split_on_word
end
def test_speed_up
@params.speed_up = true
assert @params.speed_up
@params.speed_up = false
assert !@params.speed_up
end
def test_whisper
@whisper = Whisper::Context.new("base.en")
@whisper = Whisper::Context.new(File.join(TOPDIR, '..', '..', 'models', 'ggml-base.en.bin'))
params = Whisper::Params.new
params.print_timestamps = false
@whisper.transcribe(AUDIO, params) {|text|
jfk = File.join(TOPDIR, '..', '..', 'samples', 'jfk.wav')
@whisper.transcribe(jfk, params) {|text|
assert_match /ask not what your country can do for you, ask what you can do for your country/, text
}
end
sub_test_case "After transcription" do
def test_full_n_segments
assert_equal 1, whisper.full_n_segments
end
def test_full_lang_id
assert_equal 0, whisper.full_lang_id
end
def test_full_get_segment_t0
assert_equal 0, whisper.full_get_segment_t0(0)
assert_raise IndexError do
whisper.full_get_segment_t0(whisper.full_n_segments)
end
assert_raise IndexError do
whisper.full_get_segment_t0(-1)
end
end
def test_full_get_segment_t1
t1 = whisper.full_get_segment_t1(0)
assert_kind_of Integer, t1
assert t1 > 0
assert_raise IndexError do
whisper.full_get_segment_t1(whisper.full_n_segments)
end
end
def test_full_get_segment_speaker_turn_next
assert_false whisper.full_get_segment_speaker_turn_next(0)
end
def test_full_get_segment_text
assert_match /ask not what your country can do for you, ask what you can do for your country/, whisper.full_get_segment_text(0)
end
def test_full_get_segment_no_speech_prob
prob = whisper.full_get_segment_no_speech_prob(0)
assert prob > 0.0
assert prob < 1.0
end
end
def test_lang_max_id
assert_kind_of Integer, Whisper.lang_max_id
end
def test_lang_id
assert_equal 0, Whisper.lang_id("en")
assert_raise ArgumentError do
Whisper.lang_id("non existing language")
end
end
def test_lang_str
assert_equal "en", Whisper.lang_str(0)
assert_raise IndexError do
Whisper.lang_str(Whisper.lang_max_id + 1)
end
end
def test_lang_str_full
assert_equal "english", Whisper.lang_str_full(0)
assert_raise IndexError do
Whisper.lang_str_full(Whisper.lang_max_id + 1)
end
end
def test_log_set
user_data = Object.new
logs = []
log_callback = ->(level, buffer, udata) {
logs << [level, buffer, udata]
}
Whisper.log_set log_callback, user_data
Whisper::Context.new("base.en")
assert logs.length > 30
logs.each do |log|
assert_include [Whisper::LOG_LEVEL_DEBUG, Whisper::LOG_LEVEL_INFO, Whisper::LOG_LEVEL_WARN], log[0]
assert_same user_data, log[2]
end
end
def test_log_suppress
stderr = $stderr
Whisper.log_set ->(level, buffer, user_data) {
# do nothing
}, nil
dev = StringIO.new("")
$stderr = dev
Whisper::Context.new("base.en")
assert_empty dev.string
ensure
$stderr = stderr
end
sub_test_case "full" do
def setup
super
@whisper = Whisper::Context.new("base.en")
@samples = File.read(AUDIO, nil, 78).unpack("s<*").collect {|i| i.to_f / 2**15}
end
def test_full
@whisper.full(@params, @samples, @samples.length)
assert_equal 1, @whisper.full_n_segments
assert_match /ask not what your country can do for you, ask what you can do for your country/, @whisper.each_segment.first.text
end
def test_full_without_length
@whisper.full(@params, @samples)
assert_equal 1, @whisper.full_n_segments
assert_match /ask not what your country can do for you, ask what you can do for your country/, @whisper.each_segment.first.text
end
def test_full_enumerator
samples = @samples.each
@whisper.full(@params, samples, @samples.length)
assert_equal 1, @whisper.full_n_segments
assert_match /ask not what your country can do for you, ask what you can do for your country/, @whisper.each_segment.first.text
end
def test_full_enumerator_without_length
samples = @samples.each
assert_raise ArgumentError do
@whisper.full(@params, samples)
end
end
def test_full_enumerator_with_too_large_length
samples = @samples.each.take(10).to_enum
assert_raise StopIteration do
@whisper.full(@params, samples, 11)
end
end
def test_full_with_memory_view
samples = JFKReader.new(AUDIO)
@whisper.full(@params, samples)
assert_equal 1, @whisper.full_n_segments
assert_match /ask not what your country can do for you, ask what you can do for your country/, @whisper.each_segment.first.text
end
def test_full_parallel
@whisper.full_parallel(@params, @samples, @samples.length, Etc.nprocessors)
assert_equal Etc.nprocessors, @whisper.full_n_segments
text = @whisper.each_segment.collect(&:text).join
assert_match /ask what you can do/i, text
assert_match /for your country/i, text
end
def test_full_parallel_with_memory_view
samples = JFKReader.new(AUDIO)
@whisper.full_parallel(@params, samples, nil, Etc.nprocessors)
assert_equal Etc.nprocessors, @whisper.full_n_segments
text = @whisper.each_segment.collect(&:text).join
assert_match /ask what you can do/i, text
assert_match /for your country/i, text
end
def test_full_parallel_without_length_and_n_processors
@whisper.full_parallel(@params, @samples)
assert_equal 1, @whisper.full_n_segments
text = @whisper.each_segment.collect(&:text).join
assert_match /ask what you can do/i, text
assert_match /for your country/i, text
end
def test_full_parallel_without_length
@whisper.full_parallel(@params, @samples, nil, Etc.nprocessors)
assert_equal Etc.nprocessors, @whisper.full_n_segments
text = @whisper.each_segment.collect(&:text).join
assert_match /ask what you can do/i, text
assert_match /for your country/i, text
end
def test_full_parallel_without_n_processors
@whisper.full_parallel(@params, @samples, @samples.length)
assert_equal 1, @whisper.full_n_segments
text = @whisper.each_segment.collect(&:text).join
assert_match /ask what you can do/i, text
assert_match /for your country/i, text
end
end
end

View File

@ -1,36 +0,0 @@
require_relative "extsources"
Gem::Specification.new do |s|
s.name = "whispercpp"
s.authors = ["Georgi Gerganov", "Todd A. Fisher"]
s.version = '1.3.1'
s.date = '2024-12-19'
s.description = %q{High-performance inference of OpenAI's Whisper automatic speech recognition (ASR) model via Ruby}
s.email = 'todd.fisher@gmail.com'
s.extra_rdoc_files = ['LICENSE', 'README.md']
s.files = `git ls-files . -z`.split("\x0") +
EXTSOURCES.collect {|file|
basename = File.basename(file)
if s.extra_rdoc_files.include?(basename)
basename
else
file.sub("../..", "ext")
end
}
s.summary = %q{Ruby whisper.cpp bindings}
s.test_files = s.files.select {|file| file.start_with? "tests/"}
s.extensions << 'ext/extconf.rb'
s.required_ruby_version = '>= 3.1.0'
#### Documentation and testing.
s.homepage = 'https://github.com/ggerganov/whisper.cpp'
s.rdoc_options = ['--main', 'README.md']
s.platform = Gem::Platform::RUBY
s.licenses = ['MIT']
end

54
cmake/BuildTypes.cmake Normal file
View File

@ -0,0 +1,54 @@
# Add new build types
# ReleaseGG - Release with enabled asserts
SET(CMAKE_CXX_FLAGS_RELEASEGG
"-O3"
CACHE STRING "Flags used by the c++ compiler during release builds with enabled asserts."
FORCE )
SET(CMAKE_C_FLAGS_RELEASEGG
"-O3"
CACHE STRING "Flags used by the compiler during release builds with enabled asserts."
FORCE )
SET(CMAKE_EXE_LINKER_FLAGS_RELEASEGG
""
CACHE STRING "Flags used for linking binaries during release builds with enabled asserts."
FORCE )
SET(CMAKE_SHARED_LINKER_FLAGS_RELEASEGG
""
CACHE STRING "Flags used by the shared libraries linker during release builds with enabled asserts."
FORCE )
MARK_AS_ADVANCED(
CMAKE_CXX_FLAGS_RELEASEGG
CMAKE_C_FLAGS_RELEASEGG
CMAKE_EXE_LINKER_FLAGS_RELEASEGG
CMAKE_SHARED_LINKER_FLAGS_RELEASEGG )
# RelWithDebInfoGG - RelWithDebInfo with enabled asserts
SET(CMAKE_CXX_FLAGS_RELWITHDEBINFOGG
"-O2 -g"
CACHE STRING "Flags used by the c++ compiler during release builds with debug symbols and enabled asserts."
FORCE )
SET(CMAKE_C_FLAGS_RELWITHDEBINFOGG
"-O2 -g"
CACHE STRING "Flags used by the compiler during release builds with debug symbols and enabled asserts."
FORCE )
SET(CMAKE_EXE_LINKER_FLAGS_RELWITHDEBINFOGG
""
CACHE STRING "Flags used for linking binaries during release builds with debug symbols and enabled asserts."
FORCE )
SET(CMAKE_SHARED_LINKER_FLAGS_RELWITHDEBINFOGG
""
CACHE STRING "Flags used by the shared libraries linker during release builds with debug symbols and enabled asserts."
FORCE )
MARK_AS_ADVANCED(
CMAKE_CXX_FLAGS_RELWITHDEBINFOGG
CMAKE_C_FLAGS_RELWITHDEBINFOGG
CMAKE_EXE_LINKER_FLAGS_RELWITHDEBINFOGG
CMAKE_SHARED_LINKER_FLAGS_RELWITHDEBINFOGG )
if (NOT XCODE AND NOT MSVC AND NOT CMAKE_BUILD_TYPE)
set(CMAKE_BUILD_TYPE Release CACHE STRING "Build type" FORCE)
set_property(CACHE CMAKE_BUILD_TYPE PROPERTY STRINGS "Debug" "Release" "MinSizeRel" "RelWithDebInfo" "ReleaseGG" "RelWithDebInfoGG")
endif()

View File

@ -13,4 +13,5 @@ set_target_properties(${TARGET}
PROPERTIES
EXPORT_COMPILE_COMMANDS ON
RUNTIME_OUTPUT_DIRECTORY "${CMAKE_BINARY_DIR}/bin"
INSTALL_RPATH "${CMAKE_INSTALL_PREFIX}/lib"
)

View File

@ -1,163 +0,0 @@
# From
# https://github.com/snikulov/cmake-modules/blob/master/FindFFmpeg.cmake
#
# vim: ts=2 sw=2
# - Try to find the required ffmpeg components(default: AVFORMAT, AVUTIL, AVCODEC)
#
# Once done this will define
# FFMPEG_FOUND - System has the all required components.
# FFMPEG_INCLUDE_DIRS - Include directory necessary for using the required components headers.
# FFMPEG_LIBRARIES - Link these to use the required ffmpeg components.
# FFMPEG_DEFINITIONS - Compiler switches required for using the required ffmpeg components.
#
# For each of the components it will additionally set.
# - AVCODEC
# - AVDEVICE
# - AVFORMAT
# - AVFILTER
# - AVUTIL
# - POSTPROC
# - SWSCALE
# the following variables will be defined
# <component>_FOUND - System has <component>
# <component>_INCLUDE_DIRS - Include directory necessary for using the <component> headers
# <component>_LIBRARIES - Link these to use <component>
# <component>_DEFINITIONS - Compiler switches required for using <component>
# <component>_VERSION - The components version
#
# Copyright (c) 2006, Matthias Kretz, <kretz@kde.org>
# Copyright (c) 2008, Alexander Neundorf, <neundorf@kde.org>
# Copyright (c) 2011, Michael Jansen, <kde@michael-jansen.biz>
#
# Redistribution and use is allowed according to the terms of the BSD license.
# For details see the accompanying COPYING-CMAKE-SCRIPTS file.
include(FindPackageHandleStandardArgs)
# The default components were taken from a survey over other FindFFMPEG.cmake files
if (NOT FFmpeg_FIND_COMPONENTS)
set(FFmpeg_FIND_COMPONENTS AVFORMAT AVCODEC AVUTIL SWRESAMPLE)
endif()
#
### Macro: set_component_found
#
# Marks the given component as found if both *_LIBRARIES AND *_INCLUDE_DIRS is present.
#
macro(set_component_found _component )
if (${_component}_LIBRARIES AND ${_component}_INCLUDE_DIRS)
message(DEBUG " - ${_component} found.")
set(${_component}_FOUND TRUE)
else ()
message(DEBUG " - ${_component} not found.")
endif ()
endmacro()
#
### Macro: find_component
#
# Checks for the given component by invoking pkgconfig and then looking up the libraries and
# include directories.
#
macro(find_component _component _pkgconfig _library _header)
if (NOT WIN32)
# use pkg-config to get the directories and then use these values
# in the FIND_PATH() and FIND_LIBRARY() calls
find_package(PkgConfig)
if (PKG_CONFIG_FOUND)
pkg_check_modules(PC_${_component} ${_pkgconfig})
message(STATUS "Pkgconfig found: ${PC_${_component}_INCLUDEDIR}")
message(STATUS "Pkgconfig found: ${PC_${_component}_INCLUDE_DIRS}")
message(STATUS "${PC_${_component}_CFLAGS}")
endif ()
endif (NOT WIN32)
find_path(${_component}_INCLUDE_DIRS ${_header}
HINTS
${PC_${_component}_INCLUDEDIR}
${PC_${_component}_INCLUDE_DIRS}
PATH_SUFFIXES
ffmpeg
)
# CMake's default is to search first for shared libraries and then for static libraries.
# Todo later: add option to prefer static libs over dynamic:
find_library(${_component}_LIBRARIES NAMES ${_library} lib${_library}.a
HINTS
${PC_${_component}_LIBDIR}
${PC_${_component}_LIBRARY_DIRS}
)
set(${_component}_DEFINITIONS ${PC_${_component}_CFLAGS_OTHER} CACHE STRING "The ${_component} CFLAGS.")
set(${_component}_VERSION ${PC_${_component}_VERSION} CACHE STRING "The ${_component} version number.")
set_component_found(${_component})
mark_as_advanced(
${_component}_INCLUDE_DIRS
${_component}_LIBRARIES
${_component}_DEFINITIONS
${_component}_VERSION)
endmacro()
# Check for cached results. If there are skip the costly part.
if (NOT FFMPEG_LIBRARIES)
# Check for all possible component.
find_component(AVCODEC libavcodec avcodec libavcodec/avcodec.h)
find_component(AVFORMAT libavformat avformat libavformat/avformat.h)
find_component(AVDEVICE libavdevice avdevice libavdevice/avdevice.h)
#find_component(AVRESAMPLE libavresample avresample libavresample/avresample.h) # old name for swresample
find_component(AVUTIL libavutil avutil libavutil/avutil.h)
find_component(AVFILTER libavfilter avfilter libavfilter/avfilter.h)
find_component(SWSCALE libswscale swscale libswscale/swscale.h)
find_component(POSTPROC libpostproc postproc libpostproc/postprocess.h)
find_component(SWRESAMPLE libswresample swresample libswresample/swresample.h)
# Check if the required components were found and add their stuff to the FFMPEG_* vars.
foreach (_component ${FFmpeg_FIND_COMPONENTS})
if (${_component}_FOUND)
# message(STATUS "Required component ${_component} present.")
set(FFMPEG_LIBRARIES ${FFMPEG_LIBRARIES} ${${_component}_LIBRARIES})
set(FFMPEG_DEFINITIONS ${FFMPEG_DEFINITIONS} ${${_component}_DEFINITIONS})
list(APPEND FFMPEG_INCLUDE_DIRS ${${_component}_INCLUDE_DIRS})
else ()
# message(STATUS "Required component ${_component} missing.")
endif ()
endforeach ()
# Build the include path with duplicates removed.
if (FFMPEG_INCLUDE_DIRS)
list(REMOVE_DUPLICATES FFMPEG_INCLUDE_DIRS)
endif ()
# cache the vars.
set(FFMPEG_INCLUDE_DIRS ${FFMPEG_INCLUDE_DIRS} CACHE STRING "The FFmpeg include directories." FORCE)
set(FFMPEG_LIBRARIES ${FFMPEG_LIBRARIES} CACHE STRING "The FFmpeg libraries." FORCE)
set(FFMPEG_DEFINITIONS ${FFMPEG_DEFINITIONS} CACHE STRING "The FFmpeg cflags." FORCE)
mark_as_advanced(FFMPEG_INCLUDE_DIRS
FFMPEG_LIBRARIES
FFMPEG_DEFINITIONS)
endif ()
# Now set the noncached _FOUND vars for the components.
# whisper.cpp does not need SWSCALE
foreach (_component AVCODEC AVDEVICE AVFORMAT AVRESAMPLE AVUTIL POSTPROCESS)
set_component_found(${_component})
endforeach ()
# Compile the list of required vars
set(_FFmpeg_REQUIRED_VARS FFMPEG_LIBRARIES FFMPEG_INCLUDE_DIRS)
foreach (_component ${FFmpeg_FIND_COMPONENTS})
list(APPEND _FFmpeg_REQUIRED_VARS ${_component}_LIBRARIES ${_component}_INCLUDE_DIRS)
endforeach ()
# Give a nice error message if some of the required vars are missing.
find_package_handle_standard_args(FFmpeg DEFAULT_MSG ${_FFmpeg_REQUIRED_VARS})

View File

@ -1,58 +0,0 @@
set(BUILD_NUMBER 0)
set(BUILD_COMMIT "unknown")
set(BUILD_COMPILER "unknown")
set(BUILD_TARGET "unknown")
# Look for git
find_package(Git)
if(NOT Git_FOUND)
find_program(GIT_EXECUTABLE NAMES git git.exe)
if(GIT_EXECUTABLE)
set(Git_FOUND TRUE)
message(STATUS "Found Git: ${GIT_EXECUTABLE}")
else()
message(WARNING "Git not found. Build info will not be accurate.")
endif()
endif()
# Get the commit count and hash
if(Git_FOUND)
execute_process(
COMMAND ${GIT_EXECUTABLE} rev-parse --short HEAD
WORKING_DIRECTORY ${CMAKE_CURRENT_SOURCE_DIR}
OUTPUT_VARIABLE HEAD
OUTPUT_STRIP_TRAILING_WHITESPACE
RESULT_VARIABLE RES
)
if (RES EQUAL 0)
set(BUILD_COMMIT ${HEAD})
endif()
execute_process(
COMMAND ${GIT_EXECUTABLE} rev-list --count HEAD
WORKING_DIRECTORY ${CMAKE_CURRENT_SOURCE_DIR}
OUTPUT_VARIABLE COUNT
OUTPUT_STRIP_TRAILING_WHITESPACE
RESULT_VARIABLE RES
)
if (RES EQUAL 0)
set(BUILD_NUMBER ${COUNT})
endif()
endif()
if(MSVC)
set(BUILD_COMPILER "${CMAKE_C_COMPILER_ID} ${CMAKE_C_COMPILER_VERSION}")
set(BUILD_TARGET ${CMAKE_VS_PLATFORM_NAME})
else()
execute_process(
COMMAND sh -c "$@ --version | head -1" _ ${CMAKE_C_COMPILER}
OUTPUT_VARIABLE OUT
OUTPUT_STRIP_TRAILING_WHITESPACE
)
set(BUILD_COMPILER ${OUT})
execute_process(
COMMAND ${CMAKE_C_COMPILER} -dumpmachine
OUTPUT_VARIABLE OUT
OUTPUT_STRIP_TRAILING_WHITESPACE
)
set(BUILD_TARGET ${OUT})
endif()

View File

@ -1,65 +0,0 @@
set(WHISPER_VERSION @WHISPER_INSTALL_VERSION@)
set(WHISPER_BUILD_COMMIT @WHISPER_BUILD_COMMIT@)
set(WHISPER_BUILD_NUMBER @WHISPER_BUILD_NUMBER@)
set(WHISPER_SHARED_LIB @BUILD_SHARED_LIBS@)
set(GGML_BLAS @GGML_BLAS@)
set(GGML_CUDA @GGML_CUDA@)
set(GGML_METAL @GGML_METAL@)
set(GGML_HIPBLAS @GGML_HIPBLAS@)
set(GGML_ACCELERATE @GGML_ACCELERATE@)
@PACKAGE_INIT@
set_and_check(WHISPER_INCLUDE_DIR "@PACKAGE_WHISPER_INCLUDE_INSTALL_DIR@")
set_and_check(WHISPER_LIB_DIR "@PACKAGE_WHISPER_LIB_INSTALL_DIR@")
set_and_check(WHISPER_BIN_DIR "@PACKAGE_WHISPER_BIN_INSTALL_DIR@")
# Ensure transient dependencies satisfied
find_package(Threads REQUIRED)
if (APPLE AND GGML_ACCELERATE)
find_library(ACCELERATE_FRAMEWORK Accelerate REQUIRED)
endif()
if (GGML_BLAS)
find_package(BLAS REQUIRED)
endif()
if (GGML_CUDA)
find_package(CUDAToolkit REQUIRED)
endif()
if (GGML_METAL)
find_library(FOUNDATION_LIBRARY Foundation REQUIRED)
find_library(METAL_FRAMEWORK Metal REQUIRED)
find_library(METALKIT_FRAMEWORK MetalKit REQUIRED)
endif()
if (GGML_HIPBLAS)
find_package(hip REQUIRED)
find_package(hipblas REQUIRED)
find_package(rocblas REQUIRED)
endif()
find_library(whisper_LIBRARY whisper
REQUIRED
HINTS ${WHISPER_LIB_DIR})
set(_whisper_link_deps "Threads::Threads" "@WHISPER_EXTRA_LIBS@")
set(_whisper_transient_defines "@WHISPER_TRANSIENT_DEFINES@")
add_library(whisper UNKNOWN IMPORTED)
set_target_properties(whisper
PROPERTIES
INTERFACE_INCLUDE_DIRECTORIES "${WHISPER_INCLUDE_DIR}"
INTERFACE_LINK_LIBRARIES "${_whisper_link_deps}"
INTERFACE_COMPILE_DEFINITIONS "${_whisper_transient_defines}"
IMPORTED_LINK_INTERFACE_LANGUAGES "CXX"
IMPORTED_LOCATION "${whisper_LIBRARY}"
INTERFACE_COMPILE_FEATURES cxx_std_11
POSITION_INDEPENDENT_CODE ON )
check_required_components(whisper)

View File

@ -1,10 +0,0 @@
prefix=@CMAKE_INSTALL_PREFIX@
exec_prefix=${prefix}
libdir=${exec_prefix}/lib
includedir=${prefix}/include
Name: whisper
Description: Port of OpenAI's Whisper model in C/C++
Version: @PROJECT_VERSION@
Libs: -L${libdir} -lggml -lggml-base -lwhisper
Cflags: -I${includedir}

View File

@ -24,9 +24,9 @@ struct whisper_coreml_context * whisper_coreml_init(const char * path_model) {
// select which device to run the Core ML model on
MLModelConfiguration *config = [[MLModelConfiguration alloc] init];
// config.computeUnits = MLComputeUnitsCPUAndGPU;
config.computeUnits = MLComputeUnitsCPUAndGPU;
//config.computeUnits = MLComputeUnitsCPUAndNeuralEngine;
config.computeUnits = MLComputeUnitsAll;
//config.computeUnits = MLComputeUnitsAll;
const void * data = CFBridgingRetain([[whisper_encoder_impl alloc] initWithContentsOfURL:url_model configuration:config error:nil]);

View File

@ -11,62 +11,25 @@ if (WHISPER_SDL2)
string(STRIP "${SDL2_LIBRARIES}" SDL2_LIBRARIES)
message(STATUS "SDL2_INCLUDE_DIRS = ${SDL2_INCLUDE_DIRS}")
message(STATUS "SDL2_LIBRARIES = ${SDL2_LIBRARIES}")
endif()
if (WHISPER_CLBLAST)
find_package(CLBlast REQUIRED)
message(STATUS "SDL2_LIBRARIES = ${SDL2_LIBRARIES}")
endif()
# common
set(TARGET common)
unset(COMMON_EXTRA_LIBS)
if (WHISPER_FFMPEG)
# As of cmake 3.27, there is no official cmake support for FindFFmpeg.
# Consequnelty we added a FindFFmpeg.cmake script the cmake subfolder:
# whisper.cpp does not need the full ffmpeg libs, just AVFORMAT AVCODEC AVUTIL SWRESAMPLE
# libswresample performs highly optimized audio resampling, rematrixing and sample format conversion operations
# libavcodec provides a generic encoding/decoding framework and contains multiple decoders and encoders for audio, video and subtitle streams, and several bitstream filters.
# libavformat provides a generic framework for multiplexing and demultiplexing (muxing and demuxing) audio, video and subtitle streams.
find_package(FFmpeg REQUIRED)
if (NOT ${FFMPEG_FOUND})
message(FATAL_ERROR "Cannot find ffmpeg libs/headers")
endif()
message(STATUS "Found ffmpeg libs: ${FFMPEG_LIBRARIES}")
message(STATUS "Found ffmpeg headers in: ${FFMPEG_INCLUDE_DIRS}")
message(STATUS "ffmpeg definitions: ${FFMPEG_DEFINITIONS}")
message(STATUS "Found avformat ${AVFORMAT_VERSION}")
include_directories(${FFMPEG_INCLUDE_DIRS})
add_compile_definitions(WHISPER_FFMPEG)
list(APPEND COMMON_EXTRA_LIBS ${FFMPEG_LIBRARIES})
set(COMMON_SOURCES_FFMPEG ffmpeg-transcode.cpp)
endif()
add_library(${TARGET} STATIC
common.h
common.cpp
common-ggml.h
common-ggml.cpp
grammar-parser.h
grammar-parser.cpp
${COMMON_SOURCES_FFMPEG}
)
include(DefaultTargetOptions)
target_link_libraries(${TARGET} PRIVATE whisper ${COMMON_EXTRA_LIBS})
target_link_libraries(${TARGET} PRIVATE whisper)
set_target_properties(${TARGET} PROPERTIES POSITION_INDEPENDENT_CODE ON)
set_target_properties(${TARGET} PROPERTIES FOLDER "libs")
if (WHISPER_SDL2)
# common-sdl
@ -80,17 +43,12 @@ if (WHISPER_SDL2)
include(DefaultTargetOptions)
target_include_directories(${TARGET} PUBLIC ${SDL2_INCLUDE_DIRS})
target_link_libraries (${TARGET} PRIVATE ${SDL2_LIBRARIES})
target_include_directories(${TARGET} PUBLIC ${SDL2_INCLUDE_DIRS})
target_link_libraries(${TARGET} PRIVATE ${SDL2_LIBRARIES})
set_target_properties(${TARGET} PROPERTIES POSITION_INDEPENDENT_CODE ON)
set_target_properties(${TARGET} PROPERTIES FOLDER "libs")
endif()
# add json lib
add_library(json_cpp INTERFACE)
target_include_directories(json_cpp INTERFACE ${CMAKE_CURRENT_SOURCE_DIR})
# examples
include_directories(${CMAKE_CURRENT_SOURCE_DIR})
@ -99,27 +57,17 @@ if (EMSCRIPTEN)
add_subdirectory(whisper.wasm)
add_subdirectory(stream.wasm)
add_subdirectory(command.wasm)
add_subdirectory(talk.wasm)
add_subdirectory(bench.wasm)
elseif(CMAKE_JS_VERSION)
add_subdirectory(addon.node)
else()
add_subdirectory(cli)
add_subdirectory(main)
add_subdirectory(stream)
add_subdirectory(command)
add_subdirectory(bench)
add_subdirectory(server)
add_subdirectory(quantize)
if (WHISPER_SDL2)
add_subdirectory(stream)
add_subdirectory(command)
add_subdirectory(talk-llama)
add_subdirectory(lsp)
if (GGML_SYCL)
add_subdirectory(sycl)
endif()
endif (WHISPER_SDL2)
add_subdirectory(deprecation-warning)
add_subdirectory(talk)
add_subdirectory(talk-llama)
add_subdirectory(lsp)
endif()
if (WHISPER_SDL2)
add_subdirectory(wchess)
endif (WHISPER_SDL2)

View File

@ -1,4 +1,4 @@
set(TARGET addon.node)
set(TARGET whisper-addon)
# Base settings
#==================================================================

View File

@ -14,14 +14,14 @@ npm install
Make sure it is in the project root directory and compiled with make-js.
```shell
npx cmake-js compile -T addon.node -B Release
npx cmake-js compile -T whisper-addon -B Release
```
For Electron addon and cmake-js options, you can see [cmake-js](https://github.com/cmake-js/cmake-js) and make very few configuration changes.
> Such as appointing special cmake path:
> ```shell
> npx cmake-js compile -c 'xxx/cmake' -T addon.node -B Release
> npx cmake-js compile -c 'xxx/cmake' -T whisper-addon -B Release
> ```
## Run

View File

@ -1,7 +1,7 @@
const path = require("path");
const { whisper } = require(path.join(
__dirname,
"../../../build/Release/addon.node"
"../../../build/Release/whisper-addon"
));
const { promisify } = require("util");
@ -12,12 +12,6 @@ const whisperParamsMock = {
model: path.join(__dirname, "../../../models/ggml-base.en.bin"),
fname_inp: path.join(__dirname, "../../../samples/jfk.wav"),
use_gpu: true,
flash_attn: false,
no_prints: true,
comma_in_time: false,
translate: true,
no_timestamps: false,
audio_ctx: 0,
};
describe("Run whisper.node", () => {

View File

@ -19,12 +19,12 @@ struct whisper_params {
int32_t max_len = 0;
int32_t best_of = 5;
int32_t beam_size = -1;
int32_t audio_ctx = 0;
float word_thold = 0.01f;
float entropy_thold = 2.4f;
float logprob_thold = -1.0f;
bool speed_up = false;
bool translate = false;
bool diarize = false;
bool output_txt = false;
@ -36,10 +36,7 @@ struct whisper_params {
bool print_colors = false;
bool print_progress = false;
bool no_timestamps = false;
bool no_prints = false;
bool use_gpu = true;
bool flash_attn = false;
bool comma_in_time = true;
std::string language = "en";
std::string prompt;
@ -47,8 +44,6 @@ struct whisper_params {
std::vector<std::string> fname_inp = {};
std::vector<std::string> fname_out = {};
std::vector<float> pcmf32 = {}; // mono-channel F32 PCM
};
struct whisper_print_user_data {
@ -57,6 +52,27 @@ struct whisper_print_user_data {
const std::vector<std::vector<float>> * pcmf32s;
};
// 500 -> 00:05.000
// 6000 -> 01:00.000
std::string to_timestamp(int64_t t, bool comma = false) {
int64_t msec = t * 10;
int64_t hr = msec / (1000 * 60 * 60);
msec = msec - hr * (1000 * 60 * 60);
int64_t min = msec / (1000 * 60);
msec = msec - min * (1000 * 60);
int64_t sec = msec / 1000;
msec = msec - sec * 1000;
char buf[32];
snprintf(buf, sizeof(buf), "%02d:%02d:%02d%s%03d", (int) hr, (int) min, (int) sec, comma ? "," : ".", (int) msec);
return std::string(buf);
}
int timestamp_to_sample(int64_t t, int n_samples) {
return std::max(0, std::min((int) n_samples - 1, (int) ((t*WHISPER_SAMPLE_RATE)/100)));
}
void whisper_print_segment_callback(struct whisper_context * ctx, struct whisper_state * state, int n_new, void * user_data) {
const auto & params = *((whisper_print_user_data *) user_data)->params;
const auto & pcmf32s = *((whisper_print_user_data *) user_data)->pcmf32s;
@ -88,8 +104,8 @@ void whisper_print_segment_callback(struct whisper_context * ctx, struct whisper
if (params.diarize && pcmf32s.size() == 2) {
const int64_t n_samples = pcmf32s[0].size();
const int64_t is0 = timestamp_to_sample(t0, n_samples, WHISPER_SAMPLE_RATE);
const int64_t is1 = timestamp_to_sample(t1, n_samples, WHISPER_SAMPLE_RATE);
const int64_t is0 = timestamp_to_sample(t0, n_samples);
const int64_t is1 = timestamp_to_sample(t1, n_samples);
double energy0 = 0.0f;
double energy1 = 0.0f;
@ -125,15 +141,9 @@ void whisper_print_segment_callback(struct whisper_context * ctx, struct whisper
}
}
void cb_log_disable(enum ggml_log_level, const char *, void *) {}
int run(whisper_params &params, std::vector<std::vector<std::string>> &result) {
if (params.no_prints) {
whisper_log_set(cb_log_disable, NULL);
}
if (params.fname_inp.empty() && params.pcmf32.empty()) {
fprintf(stderr, "error: no input files or audio buffer specified\n");
if (params.fname_inp.empty()) {
fprintf(stderr, "error: no input files specified\n");
return 2;
}
@ -144,9 +154,8 @@ int run(whisper_params &params, std::vector<std::vector<std::string>> &result) {
// whisper init
struct whisper_context_params cparams = whisper_context_default_params();
struct whisper_context_params cparams;
cparams.use_gpu = params.use_gpu;
cparams.flash_attn = params.flash_attn;
struct whisper_context * ctx = whisper_init_from_file_with_params(params.model.c_str(), cparams);
if (ctx == nullptr) {
@ -154,14 +163,6 @@ int run(whisper_params &params, std::vector<std::vector<std::string>> &result) {
return 3;
}
// if params.pcmf32 is provided, set params.fname_inp to "buffer"
// this is simpler than further modifications in the code
if (!params.pcmf32.empty()) {
fprintf(stderr, "info: using audio buffer as input\n");
params.fname_inp.clear();
params.fname_inp.emplace_back("buffer");
}
for (int f = 0; f < (int) params.fname_inp.size(); ++f) {
const auto fname_inp = params.fname_inp[f];
const auto fname_out = f < (int)params.fname_out.size() && !params.fname_out[f].empty() ? params.fname_out[f] : params.fname_inp[f];
@ -169,25 +170,20 @@ int run(whisper_params &params, std::vector<std::vector<std::string>> &result) {
std::vector<float> pcmf32; // mono-channel F32 PCM
std::vector<std::vector<float>> pcmf32s; // stereo-channel F32 PCM
// read the input audio file if params.pcmf32 is not provided
if (params.pcmf32.empty()) {
if (!::read_wav(fname_inp, pcmf32, pcmf32s, params.diarize)) {
fprintf(stderr, "error: failed to read WAV file '%s'\n", fname_inp.c_str());
continue;
}
} else {
pcmf32 = params.pcmf32;
if (!::read_wav(fname_inp, pcmf32, pcmf32s, params.diarize)) {
fprintf(stderr, "error: failed to read WAV file '%s'\n", fname_inp.c_str());
continue;
}
// print system information
if (!params.no_prints) {
{
fprintf(stderr, "\n");
fprintf(stderr, "system_info: n_threads = %d / %d | %s\n",
params.n_threads*params.n_processors, std::thread::hardware_concurrency(), whisper_print_system_info());
}
// print some info about the processing
if (!params.no_prints) {
{
fprintf(stderr, "\n");
if (!whisper_is_multilingual(ctx)) {
if (params.language != "en" || params.translate) {
@ -196,13 +192,12 @@ int run(whisper_params &params, std::vector<std::vector<std::string>> &result) {
fprintf(stderr, "%s: WARNING: model is not multilingual, ignoring language and translation options\n", __func__);
}
}
fprintf(stderr, "%s: processing '%s' (%d samples, %.1f sec), %d threads, %d processors, lang = %s, task = %s, timestamps = %d, audio_ctx = %d ...\n",
fprintf(stderr, "%s: processing '%s' (%d samples, %.1f sec), %d threads, %d processors, lang = %s, task = %s, timestamps = %d ...\n",
__func__, fname_inp.c_str(), int(pcmf32.size()), float(pcmf32.size())/WHISPER_SAMPLE_RATE,
params.n_threads, params.n_processors,
params.language.c_str(),
params.translate ? "translate" : "transcribe",
params.no_timestamps ? 0 : 1,
params.audio_ctx);
params.no_timestamps ? 0 : 1);
fprintf(stderr, "\n");
}
@ -229,15 +224,14 @@ int run(whisper_params &params, std::vector<std::vector<std::string>> &result) {
wparams.entropy_thold = params.entropy_thold;
wparams.logprob_thold = params.logprob_thold;
wparams.max_len = params.output_wts && params.max_len == 0 ? 60 : params.max_len;
wparams.audio_ctx = params.audio_ctx;
wparams.speed_up = params.speed_up;
wparams.greedy.best_of = params.best_of;
wparams.beam_search.beam_size = params.beam_size;
wparams.initial_prompt = params.prompt.c_str();
wparams.no_timestamps = params.no_timestamps;
whisper_print_user_data user_data = { &params, &pcmf32s };
// this callback is called on each new segment
@ -273,8 +267,8 @@ int run(whisper_params &params, std::vector<std::vector<std::string>> &result) {
const int64_t t0 = whisper_full_get_segment_t0(ctx, i);
const int64_t t1 = whisper_full_get_segment_t1(ctx, i);
result[i].emplace_back(to_timestamp(t0, params.comma_in_time));
result[i].emplace_back(to_timestamp(t1, params.comma_in_time));
result[i].emplace_back(to_timestamp(t0, true));
result[i].emplace_back(to_timestamp(t1, true));
result[i].emplace_back(text);
}
@ -325,33 +319,11 @@ Napi::Value whisper(const Napi::CallbackInfo& info) {
std::string model = whisper_params.Get("model").As<Napi::String>();
std::string input = whisper_params.Get("fname_inp").As<Napi::String>();
bool use_gpu = whisper_params.Get("use_gpu").As<Napi::Boolean>();
bool flash_attn = whisper_params.Get("flash_attn").As<Napi::Boolean>();
bool no_prints = whisper_params.Get("no_prints").As<Napi::Boolean>();
bool no_timestamps = whisper_params.Get("no_timestamps").As<Napi::Boolean>();
int32_t audio_ctx = whisper_params.Get("audio_ctx").As<Napi::Number>();
bool comma_in_time = whisper_params.Get("comma_in_time").As<Napi::Boolean>();
Napi::Value pcmf32Value = whisper_params.Get("pcmf32");
std::vector<float> pcmf32_vec;
if (pcmf32Value.IsTypedArray()) {
Napi::Float32Array pcmf32 = pcmf32Value.As<Napi::Float32Array>();
size_t length = pcmf32.ElementLength();
pcmf32_vec.reserve(length);
for (size_t i = 0; i < length; i++) {
pcmf32_vec.push_back(pcmf32[i]);
}
}
params.language = language;
params.model = model;
params.fname_inp.emplace_back(input);
params.use_gpu = use_gpu;
params.flash_attn = flash_attn;
params.no_prints = no_prints;
params.no_timestamps = no_timestamps;
params.audio_ctx = audio_ctx;
params.pcmf32 = pcmf32_vec;
params.comma_in_time = comma_in_time;
Napi::Function callback = info[1].As<Napi::Function>();
Worker* worker = new Worker(callback, params);

View File

@ -1,7 +1,7 @@
const path = require("path");
const { whisper } = require(path.join(
__dirname,
"../../build/Release/addon.node"
"../../build/Release/whisper-addon"
));
const { promisify } = require("util");
@ -10,27 +10,15 @@ const whisperAsync = promisify(whisper);
const whisperParams = {
language: "en",
model: path.join(__dirname, "../../models/ggml-base.en.bin"),
fname_inp: path.join(__dirname, "../../samples/jfk.wav"),
fname_inp: "../../samples/jfk.wav",
use_gpu: true,
flash_attn: false,
no_prints: true,
comma_in_time: false,
translate: true,
no_timestamps: false,
audio_ctx: 0,
};
const arguments = process.argv.slice(2);
const params = Object.fromEntries(
arguments.reduce((pre, item) => {
if (item.startsWith("--")) {
const [key, value] = item.slice(2).split("=");
if (key === "audio_ctx") {
whisperParams[key] = parseInt(value);
} else {
whisperParams[key] = value;
}
return pre;
return [...pre, item.slice(2).split("=")];
}
return pre;
}, [])
@ -45,6 +33,5 @@ for (const key in params) {
console.log("whisperParams =", whisperParams);
whisperAsync(whisperParams).then((result) => {
console.log();
console.log(result);
console.log(`Result from whisper: ${result}`);
});

View File

@ -1,5 +1,5 @@
{
"name": "addon.node",
"name": "whisper-addon",
"version": "0.0.0",
"description": "",
"main": "index.js",

View File

@ -1,8 +1,6 @@
set(TARGET whisper-bench)
set(TARGET bench)
add_executable(${TARGET} bench.cpp)
include(DefaultTargetOptions)
target_link_libraries(${TARGET} PRIVATE whisper ${CMAKE_THREAD_LIBS_INIT})
install(TARGETS ${TARGET} RUNTIME)

View File

@ -1,4 +1,4 @@
# whisper.cpp/examples/bench
# bench
A very basic tool for benchmarking the inference performance on your device. The tool simply runs the Encoder part of
the transformer on some random audio data and records the execution time. This way we can have an objective comparison
@ -7,8 +7,11 @@ of the performance of the model for various setups.
Benchmark results are tracked in the following Github issue: https://github.com/ggerganov/whisper.cpp/issues/89
```bash
# run the bench too on the small.en model using 4 threads
$ ./build/bin/whisper-bench -m ./models/ggml-small.en.bin -t 4
# build the bench tool
$ make bench
# run it on the small.en model using 4 threads
$ ./bench -m ./models/ggml-small.en.bin -t 4
whisper_model_load: loading model from './models/ggml-small.en.bin'
whisper_model_load: n_vocab = 51864

View File

@ -8,17 +8,16 @@
// command-line parameters
struct whisper_params {
int32_t n_threads = std::min(4, (int32_t) std::thread::hardware_concurrency());
int32_t what = 0; // what to benchmark: 0 - whisper encoder, 1 - memcpy, 2 - ggml_mul_mat
int32_t what = 0; // what to benchmark: 0 - whisper ecoder, 1 - memcpy, 2 - ggml_mul_mat
std::string model = "models/ggml-base.en.bin";
bool use_gpu = true;
bool flash_attn = false;
bool use_gpu = true;
};
void whisper_print_usage(int argc, char ** argv, const whisper_params & params);
static bool whisper_params_parse(int argc, char ** argv, whisper_params & params) {
bool whisper_params_parse(int argc, char ** argv, whisper_params & params) {
for (int i = 1; i < argc; i++) {
std::string arg = argv[i];
@ -26,11 +25,10 @@ static bool whisper_params_parse(int argc, char ** argv, whisper_params & params
whisper_print_usage(argc, argv, params);
exit(0);
}
else if (arg == "-t" || arg == "--threads") { params.n_threads = std::stoi(argv[++i]); }
else if (arg == "-m" || arg == "--model") { params.model = argv[++i]; }
else if (arg == "-w" || arg == "--what") { params.what = atoi(argv[++i]); }
else if (arg == "-ng" || arg == "--no-gpu") { params.use_gpu = false; }
else if (arg == "-fa" || arg == "--flash-attn") { params.flash_attn = true; }
else if (arg == "-t" || arg == "--threads") { params.n_threads = std::stoi(argv[++i]); }
else if (arg == "-m" || arg == "--model") { params.model = argv[++i]; }
else if (arg == "-w" || arg == "--what") { params.what = atoi(argv[++i]); }
else if (arg == "-ng" || arg == "--no-gpu") { params.use_gpu = false; }
else {
fprintf(stderr, "error: unknown argument: %s\n", arg.c_str());
whisper_print_usage(argc, argv, params);
@ -51,20 +49,17 @@ void whisper_print_usage(int /*argc*/, char ** argv, const whisper_params & para
fprintf(stderr, " -m FNAME, --model FNAME [%-7s] model path\n", params.model.c_str());
fprintf(stderr, " -w N, --what N [%-7d] what to benchmark:\n", params.what);
fprintf(stderr, " -ng, --no-gpu [%-7s] disable GPU\n", params.use_gpu ? "false" : "true");
fprintf(stderr, " -fa, --flash-attn [%-7s] enable flash attention\n", params.flash_attn ? "true" : "false");
fprintf(stderr, " %-7s 0 - whisper\n", "");
fprintf(stderr, " %-7s 1 - memcpy\n", "");
fprintf(stderr, " %-7s 2 - ggml_mul_mat\n", "");
fprintf(stderr, "\n");
}
static int whisper_bench_full(const whisper_params & params) {
int whisper_bench_full(const whisper_params & params) {
// whisper init
struct whisper_context_params cparams = whisper_context_default_params();
cparams.use_gpu = params.use_gpu;
cparams.flash_attn = params.flash_attn;
struct whisper_context_params cparams;
cparams.use_gpu = params.use_gpu;
struct whisper_context * ctx = whisper_init_from_file_with_params(params.model.c_str(), cparams);
@ -86,7 +81,7 @@ static int whisper_bench_full(const whisper_params & params) {
}
// heat encoder
if (int ret = whisper_encode(ctx, 0, params.n_threads) != 0) {
fprintf(stderr, "error: failed to encode: %d\n", ret);
fprintf(stderr, "error: failed to encode model: %d\n", ret);
return 4;
}
@ -95,13 +90,13 @@ static int whisper_bench_full(const whisper_params & params) {
// prompt heat
if (int ret = whisper_decode(ctx, tokens, 256, 0, params.n_threads) != 0) {
fprintf(stderr, "error: failed to decode: %d\n", ret);
fprintf(stderr, "error: failed to encode model: %d\n", ret);
return 4;
}
// text-generation heat
if (int ret = whisper_decode(ctx, tokens, 1, 256, params.n_threads) != 0) {
fprintf(stderr, "error: failed to decode: %d\n", ret);
fprintf(stderr, "error: failed to encode model: %d\n", ret);
return 4;
}
@ -109,30 +104,20 @@ static int whisper_bench_full(const whisper_params & params) {
// actual run
if (int ret = whisper_encode(ctx, 0, params.n_threads) != 0) {
fprintf(stderr, "error: failed to encode: %d\n", ret);
fprintf(stderr, "error: failed to encode model: %d\n", ret);
return 4;
}
// text-generation
for (int i = 0; i < 256; i++) {
if (int ret = whisper_decode(ctx, tokens, 1, i, params.n_threads) != 0) {
fprintf(stderr, "error: failed to decode: %d\n", ret);
return 4;
}
}
// batched decoding
for (int i = 0; i < 64; i++) {
if (int ret = whisper_decode(ctx, tokens, 5, 0, params.n_threads) != 0) {
fprintf(stderr, "error: failed to decode: %d\n", ret);
return 4;
}
}
// prompt processing
for (int i = 0; i < 16; i++) {
if (int ret = whisper_decode(ctx, tokens, 256, 0, params.n_threads) != 0) {
fprintf(stderr, "error: failed to decode: %d\n", ret);
fprintf(stderr, "error: failed to encode model: %d\n", ret);
return 4;
}
}
for (int i = 0; i < 256; i++) {
if (int ret = whisper_decode(ctx, tokens, 1, i, params.n_threads) != 0) {
fprintf(stderr, "error: failed to encode model: %d\n", ret);
return 4;
}
}

View File

@ -1,8 +0,0 @@
set(TARGET whisper-cli)
add_executable(${TARGET} cli.cpp)
include(DefaultTargetOptions)
target_link_libraries(${TARGET} PRIVATE common whisper ${FFMPEG_LIBRARIES} ${CMAKE_THREAD_LIBS_INIT})
install(TARGETS ${TARGET} RUNTIME)

View File

@ -1,10 +1,9 @@
if (WHISPER_SDL2)
set(TARGET whisper-command)
# command
set(TARGET command)
add_executable(${TARGET} command.cpp)
include(DefaultTargetOptions)
target_link_libraries(${TARGET} PRIVATE common common-sdl whisper ${CMAKE_THREAD_LIBS_INIT})
install(TARGETS ${TARGET} RUNTIME)
endif ()

View File

@ -1,14 +1,14 @@
# whisper.cpp/examples/command
# command
This is a basic Voice Assistant example that accepts voice commands from the microphone.
More info is available in [issue #171](https://github.com/ggerganov/whisper.cpp/issues/171).
```bash
# Run with default arguments and small model
./whisper-command -m ./models/ggml-small.en.bin -t 8
./command -m ./models/ggml-small.en.bin -t 8
# On Raspberry Pi, use tiny or base models + "-ac 768" for better performance
./whisper-command -m ./models/ggml-tiny.en.bin -ac 768 -t 3 -c 0
./command -m ./models/ggml-tiny.en.bin -ac 768 -t 3 -c 0
```
https://user-images.githubusercontent.com/1991296/204038393-2f846eae-c255-4099-a76d-5735c25c49da.mp4
@ -23,10 +23,10 @@ Initial tests show that this approach might be extremely efficient in terms of p
```bash
# Run in guided mode, the list of allowed commands is in commands.txt
./whisper-command -m ./models/ggml-base.en.bin -cmd ./examples/command/commands.txt
./command -m ./models/ggml-base.en.bin -cmd ./examples/command/commands.txt
# On Raspberry Pi, in guided mode you can use "-ac 128" for extra performance
./whisper-command -m ./models/ggml-tiny.en.bin -cmd ./examples/command/commands.txt -ac 128 -t 3 -c 0
./command -m ./models/ggml-tiny.en.bin -cmd ./examples/command/commands.txt -ac 128 -t 3 -c 0
```
https://user-images.githubusercontent.com/1991296/207435352-8fc4ed3f-bde5-4555-9b8b-aeeb76bee969.mp4
@ -34,19 +34,14 @@ https://user-images.githubusercontent.com/1991296/207435352-8fc4ed3f-bde5-4555-9
## Building
The `whisper-command` tool depends on SDL2 library to capture audio from the microphone. You can build it like this:
The `command` tool depends on SDL2 library to capture audio from the microphone. You can build it like this:
```bash
# Install SDL2
# On Debian based linux distributions:
# Install SDL2 on Linux
sudo apt-get install libsdl2-dev
# On Fedora Linux:
sudo dnf install SDL2 SDL2-devel
# Install SDL2 on Mac OS
brew install sdl2
cmake -B build -DWHISPER_SDL2=ON
cmake --build build --config Release
make command
```

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