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4 Commits

Author SHA1 Message Date
40be74271f models : update readme 2023-11-07 13:53:01 +02:00
a0c0d08d0f bench : fix n_mels 2023-11-07 13:45:56 +02:00
8fb0a1cd1c bench : fix build + fix go bindings 2023-11-07 13:20:02 +02:00
185d3fd6d9 whisper : add support for large v3 2023-11-07 11:58:39 +02:00
744 changed files with 65583 additions and 201577 deletions

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

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

View File

@ -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

View File

@ -3,73 +3,20 @@ on:
push:
paths:
- bindings/ruby/**
- src/whisper.cpp
- include/whisper.h
- ggml/src/ggml.c
- ggml/src/ggml-impl.h
- ggml/src/ggml-aarch64.h
- ggml/src/ggml-aarch64.c
- ggml/src/ggml-alloc.c
- ggml/src/ggml-backend-impl.h
- ggml/src/ggml-backend.cpp
- ggml/src/ggml-common.h
- ggml/src/ggml-quants.h
- ggml/src/ggml-quants.c
- ggml/src/ggml-cpu-impl.h
- ggml/src/ggml-metal.m
- ggml/src/ggml-metal.metal
- ggml/src/ggml-blas.cpp
- ggml/include/ggml.h
- ggml/include/ggml-alloc.h
- ggml/include/ggml-backend.h
- ggml/include/ggml-cuda.h
- ggml/include/ggml-kompute.h
- ggml/include/ggml-metal.h
- ggml/include/ggml-sycl.h
- ggml/include/ggml-vulkan.h
- ggml/include/ggml-blas.h
- scripts/get-flags.mk
- examples/dr_wav.h
- whisper.h
pull_request:
paths:
- bindings/ruby/**
- src/whisper.cpp
- include/whisper.h
- ggml/src/ggml.c
- ggml/src/ggml-impl.h
- ggml/src/ggml-aarch64.h
- ggml/src/ggml-aarch64.c
- ggml/src/ggml-alloc.c
- ggml/src/ggml-backend-impl.h
- ggml/src/ggml-backend.cpp
- ggml/src/ggml-common.h
- ggml/src/ggml-quants.h
- ggml/src/ggml-quants.c
- ggml/src/ggml-cpu-impl.h
- ggml/src/ggml-metal.m
- ggml/src/ggml-metal.metal
- ggml/src/ggml-blas.cpp
- ggml/include/ggml.h
- ggml/include/ggml-alloc.h
- ggml/include/ggml-backend.h
- ggml/include/ggml-cuda.h
- ggml/include/ggml-kompute.h
- ggml/include/ggml-metal.h
- ggml/include/ggml-sycl.h
- ggml/include/ggml-vulkan.h
- ggml/include/ggml-blas.h
- 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: '3.0'
- uses: actions/checkout@v4
- run: rake test
- uses: actions/checkout@v1
- run: |
cd bindings/ruby/ext
ruby extconf.rb && make

View File

@ -3,7 +3,6 @@ on: [push, pull_request]
env:
ubuntu_image: "ubuntu:22.04"
VCPKG_BINARY_SOURCES: "clear;x-gha,readwrite"
jobs:
ubuntu-latest:
@ -16,17 +15,16 @@ 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 libsdl2-dev
make
@ -37,7 +35,7 @@ jobs:
steps:
- name: Clone
uses: actions/checkout@v4
uses: actions/checkout@v3
- name: Dependencies
run: |
@ -54,13 +52,13 @@ jobs:
steps:
- name: Clone
uses: actions/checkout@v4
uses: actions/checkout@v3
- name: Build
uses: cross-platform-actions/action@v0.24.0
uses: cross-platform-actions/action@v0.15.0
with:
operating_system: freebsd
version: '13.3'
version: '13.2'
run: |
sudo pkg update
sudo pkg install -y gmake sdl2
@ -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'
@ -137,183 +130,24 @@ 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 make
shell: msys2 {0}
run: |
make -j $(nproc)
- name: Clean after building using make
shell: msys2 {0}
run: |
make clean
- name: Build using make w/ OpenBLAS
shell: msys2 {0}
run: |
make GGML_OPENBLAS=1 -j $(nproc)
- name: Build using CMake
shell: msys2 {0}
run: |
cmake -B build
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 $(nproc)
windows:
runs-on: windows-2019
runs-on: windows-latest
strategy:
matrix:
@ -328,14 +162,14 @@ jobs:
s2arc: x64
jnaPath: win32-x86-64
- sdl2: ON
s2ver: 2.28.5
s2ver: 2.26.0
steps:
- name: Clone
uses: actions/checkout@v4
uses: actions/checkout@v3
- name: Add msbuild to PATH
uses: microsoft/setup-msbuild@v2
uses: microsoft/setup-msbuild@v1
- name: Fetch SDL2 and set SDL2_DIR
if: matrix.sdl2 == 'ON'
@ -360,20 +194,20 @@ jobs:
run: copy "$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 }}
windows-blas:
runs-on: windows-2019
runs-on: windows-latest
strategy:
matrix:
@ -383,31 +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'
@ -419,10 +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=${{ matrix.sdl2 }}
- name: Build
@ -430,9 +261,9 @@ jobs:
cd ./build
msbuild ALL_BUILD.vcxproj -t:build -p:configuration=${{ 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/${{ matrix.build }}
- name: Copy SDL2.dll
if: matrix.sdl2 == 'ON'
@ -440,13 +271,13 @@ jobs:
- name: Upload binaries
if: matrix.blas == 'ON' && matrix.sdl2 == 'ON'
uses: actions/upload-artifact@v4
uses: actions/upload-artifact@v1
with:
name: whisper-blas-bin-${{ matrix.arch }}
path: build/bin/${{ matrix.build }}
windows-cublas:
runs-on: windows-2019
runs-on: windows-latest
strategy:
matrix:
@ -454,25 +285,22 @@ jobs:
arch: [x64]
cublas: [ON]
sdl2: [ON]
cuda-toolkit: [12.2.0, 11.8.0]
include:
- arch: x64
s2arc: x64
- sdl2: ON
s2ver: 2.28.5
s2ver: 2.26.0
steps:
- name: Clone
uses: actions/checkout@v4
uses: actions/checkout@v3
- name: Add msbuild to PATH
uses: microsoft/setup-msbuild@v2
uses: microsoft/setup-msbuild@v1
- name: Install CUDA Toolkit
id: cuda-toolkit
uses: Jimver/cuda-toolkit@v0.2.15
with:
cuda: '${{ matrix.cuda-toolkit }}'
uses: Jimver/cuda-toolkit@v0.2.10
- name: Fetch SDL2 and set SDL2_DIR
if: matrix.sdl2 == 'ON'
@ -485,20 +313,12 @@ jobs:
run: >
cmake -S . -B ./build -A ${{ matrix.arch }}
-DCMAKE_BUILD_TYPE=${{ matrix.build }}
-DGGML_CUDA=${{ matrix.cublas }}
-DWHISPER_SDL2=${{ matrix.sdl2 }}
-DWHISPER_CUBLAS=1
- name: Build ${{ matrix.cuda-toolkit }}
- name: Build
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/${{ matrix.build }}
msbuild ALL_BUILD.vcxproj -t:build -p:configuration=${{ matrix.build }} -p:platform=${{ matrix.arch }}
- name: Copy SDL2.dll
if: matrix.sdl2 == 'ON'
@ -506,9 +326,9 @@ jobs:
- name: Upload binaries
if: matrix.sdl2 == 'ON'
uses: actions/upload-artifact@v4
uses: actions/upload-artifact@v1
with:
name: whisper-cublas-${{ matrix.cuda-toolkit }}-bin-${{ matrix.arch }}
name: whisper-cublas-bin-${{ matrix.arch }}
path: build/bin/${{ matrix.build }}
emscripten:
@ -520,10 +340,10 @@ jobs:
steps:
- name: Clone
uses: actions/checkout@v4
uses: actions/checkout@v3
- name: Setup emsdk
uses: mymindstorm/setup-emsdk@v14
uses: mymindstorm/setup-emsdk@v12
- name: Verify
run: emcc -v
@ -542,7 +362,7 @@ jobs:
steps:
- name: Clone
uses: actions/checkout@v4
uses: actions/checkout@v3
- name: Configure
run: |
@ -560,106 +380,70 @@ jobs:
steps:
- name: Clone
uses: actions/checkout@v4
with:
path: whisper
uses: actions/checkout@v3
- name: Install Java
uses: actions/setup-java@v4
uses: actions/setup-java@v3
with:
distribution: zulu
java-version: 21
java-version: 17
- name: Setup Android SDK
uses: android-actions/setup-android@v3
uses: android-actions/setup-android@v2
- name: Build
run: |
cd whisper/examples/whisper.android
cd examples/whisper.android
./gradlew assembleRelease --no-daemon
- name: Build with external ggml
java:
needs: [ 'windows' ]
runs-on: windows-latest
steps:
- uses: actions/checkout@v3
- name: Install Java
uses: actions/setup-java@v1
with:
java-version: 17
- name: Download Windows lib
uses: actions/download-artifact@v3
with:
name: win32-x86-64_whisper.dll
path: bindings/java/build/generated/resources/main/win32-x86-64
- name: Build
run: |
export PATH_TO_GGML=$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: |

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: |

28
.gitignore vendored
View File

@ -1,27 +1,22 @@
*.o
*.a
*.d
.cache/
.coreml/
.test/
.venv/
.vs/
.vscode/
.DS_Store
.vimspector.json
/CMakeSettings.json
/talk-llama.dSYM/
build/
build-*/
# SPM
.build/
.swiftpm
*.metallib
ggml-metal-embed.metal
ggml-metal-embed.metal.tmp
build-em/
build-debug/
build-release/
build-rwdi/
build-static/
build-cublas/
build-no-accel/
build-sanitize-addr/
build-sanitize-thread/
/main
/stream
@ -30,7 +25,6 @@ ggml-metal-embed.metal.tmp
/talk-llama
/bench
/quantize
/server
/lsp
arm_neon.h
@ -54,7 +48,3 @@ 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
# this file is auto-generated by scripts/gen-authors.sh
0/0 <zero@imaskeleton.me>
0cc4m <picard12@live.de>
0xsourcecode <134374803+0xsourcecode@users.noreply.github.com>
AT <manyoso@users.noreply.github.com>
Aarni Koskela <akx@iki.fi>
Aaron Pham <29749331+aarnphm@users.noreply.github.com>
Aaron Taylor <aaron@exphat.com>
Abhilash Majumder <30946547+abhilash1910@users.noreply.github.com>
Abitofevrything <54505189+abitofevrything@users.noreply.github.com>
AfryMask <AfryMask@163.com>
Ahmad Bilal <ahmad.bilal@empglabs.com>
AidanBeltonS <87009434+AidanBeltonS@users.noreply.github.com>
Akash Mahajan <akash7190@gmail.com>
Akash Mahajan <akashmjn@stanford.edu>
Al Hoang <3811822-hoanga@users.noreply.gitlab.com>
Alan <unknown>
Aleksander Andrzejewski <18704749+aleksanderandrzejewski@users.noreply.github.com>
Alex Azarov <alex@azarov.by>
Alex Bacart <13940752+alex-bacart@users.noreply.github.com>
Alex Evgrashin <aevgrashin@yandex.ru>
Alexandr Graschenkov <alexandr.graschenkov91@gmail.com>
Alexandru Mariuti <alex@mariuti.com>
Alexey Kharlamov <alexey@kharlamov.biz>
Alfredo Montesinos <alfredo.montesinos@g.austincc.edu>
Ali Alameh <ali.alameh@isae.edu.lb>
Ananta Bastola <anantarajbastola@gmail.com>
Andreu Huguet <andreuhuguet@gmail.com>
Andrew Huynh <a5thuynh@gmail.com>
Andrew S <andrews54757@gmail.com>
Andy Maloney <asmaloney@gmail.com>
Anton Kostin <masguit42@users.noreply.github.com>
Artyom Mezin <psycho.fading@gmail.com>
Asad Memon <asad.lionpk@gmail.com>
Ashraful Islam <ashraful.meche@gmail.com>
AsukaMinato <asukaminato@nyan.eu.org>
AustinMroz <austinmroz@utexas.edu>
Avik Sengupta <avik@sengupta.net>
Bader-eddine Ouaich <49657842+baderouaich@users.noreply.github.com>
Baffin Lee <baffinlee@gmail.com>
Ben Nortier <bjnortier@gmail.com>
Benjamin Heiniger <benjamin.heiniger@bluewin.ch>
Bo-Yi Wu <appleboy.tw@gmail.com>
Boris Bliznioukov <blib@mail.com>
Borislav Stanimirov <b.stanimirov@abv.bg>
Brad Murray <59848399+bradmurray-dt@users.noreply.github.com>
Brian Murray <brian@bmurray.ca>
CRD716 <crd716@gmail.com>
Canis Lupus <Canis-UK@users.noreply.github.com>
Carolinabanana <140120812+Carolinabanana@users.noreply.github.com>
ChangSeok Oh <shivamidow@users.noreply.github.com>
Chaoqun <27287694+OpenWaygate@users.noreply.github.com>
Chia-Hsiang Cheng <88014292+garychia@users.noreply.github.com>
Chidi Williams <williamschidi1@gmail.com>
Christian <12550267+iceychris@users.noreply.github.com>
Clifford Heath <clifford.heath@gmail.com>
Colin <github@whoisc.cc>
DGdev91 <DGdev91@users.noreply.github.com>
Damian Czaja <trojan295@protonmail.com>
Daniel Bevenius <daniel.bevenius@gmail.com>
David <dnhkng@gmail.com>
David Thorpe <djt@mutablelogic.com>
Davidson Francis <davidsondfgl@gmail.com>
Dener Stassun <denerstassun@gmail.com>
Didzis Gosko <didzis@users.noreply.github.com>
Digipom <admin@digipom.com>
Dimo <dimo@ieee.org>
Dody Suria Wijaya <dodysw@gmail.com>
Dr. Tom Murphy VII Ph.D <499244+tom7@users.noreply.github.com>
Duncan McConnell <ddmcconnell4@gmail.com>
Egor Egorov <me@egorfine.com>
Elkana Bardugo <ttv200@gmail.com>
Emmanuel Schmidbauer <eschmidbauer@gmail.com>
Engininja2 <139037756+Engininja2@users.noreply.github.com>
Eric Swanson <eswanson@alloscomp.com>
Eric Tendian <erictendian@gmail.com>
Erik Scholz <Green-Sky@users.noreply.github.com>
Evan Jones <evan.q.jones@gmail.com>
Evan Martin <evan.martin@gmail.com>
Eve <139727413+netrunnereve@users.noreply.github.com>
Evgeny Kuznetsov <evgeny@kuznetsov.md>
F1L1P <78918286+F1L1Pv2@users.noreply.github.com>
Fangjun Kuang <csukuangfj@gmail.com>
Felix <stenbackfelix@gmail.com>
Finn Voorhees <finnvoorhees@gmail.com>
FlippFuzz <41221030+FlippFuzz@users.noreply.github.com>
Gang Chen <goncha@gmail.com>
Gavin Cai <gavin1818@hotmail.com>
George Hindle <george@georgehindle.com>
Georgi Gerganov <ggerganov@gmail.com>
GitAritron <103900385+GitAritron@users.noreply.github.com>
GiviMAD <GiviMAD@users.noreply.github.com>
Gleicon Moraes <gleicon@gmail.com>
Gregor Jasny <gjasny@googlemail.com>
Guillaume Wenzek <gwenzek@users.noreply.github.com>
HY. Kelvin Lee <34256578+hykelvinlee42@users.noreply.github.com>
Halalaluyafail3 <55773281+Halalaluyafail3@users.noreply.github.com>
Hang <bebound@gmail.com>
Herman Semenov <GermanAizek@yandex.ru>
Hrishikesh Barman <geekodour@users.noreply.github.com>
Ian Bicking <ian@ianbicking.org>
Ian Bull <irbull@eclipsesource.com>
Ikko Ashimine <eltociear@gmail.com>
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Ismatulla Mansurov <47342870+sapoepsilon@users.noreply.github.com>
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JJ <103335846+computerscienceiscool@users.noreply.github.com>
Jack Mousseau <jmousseau@users.noreply.github.com>
JacobLinCool <jacoblincool@gmail.com>
Jakub Ráček <blizzcz@gmail.com>
Jared Van Bortel <jared@nomic.ai>
Jay Binks <jaybinks@gmail.com>
Jhen-Jie Hong <developer@jhen.me>
Jhen-Jie Hong <iainst0409@gmail.com>
JidongZhang-THU <1119708529@qq.com>
Jo Liss <joliss42@gmail.com>
Johan <jr.raffin@gmail.com>
Johannes Gäßler <johannesg@5d6.de>
John Balis <phobossystems@gmail.com>
Jonathan Soo <jcsoo@agora.com>
Jonno <1160532+razodactyl@users.noreply.github.com>
Joonas Pihlajamaa <joonas.pihlajamaa@iki.fi>
Jose <34888496+Jerry-Master@users.noreply.github.com>
Josh Bleecher Snyder <josharian@gmail.com>
Judd <foldl@users.noreply.github.com>
Jumper775 <78500318+jumpers775@users.noreply.github.com>
Justine Tunney <jtunney@gmail.com>
KP Kaiser <kirk@zothcorp.com>
Kamilake <exjang0@gmail.com>
Kartik Saranathan <278928+Kartiku@users.noreply.github.com>
Kasumi <90275229+kasumi-1@users.noreply.github.com>
Kawrakow <48489457+ikawrakow@users.noreply.github.com>
Kevin Brothaler <admin@digipom.com>
Konstantin Zhuravlyov <konstantin.zhuravlyov@amd.com>
Kreijstal <rainb@tfwno.gf>
Kylin <56434533+KyL0N@users.noreply.github.com>
LBlue <153975653+lbluep@users.noreply.github.com>
Larry Battle <larry.battle.tech@gmail.com>
Laytan Laats <laytanlaats@hotmail.com>
Leo Moll <leo.moll@yeasoft.com>
Lexevolution <31176843+Lexevolution@users.noreply.github.com>
LittleLoli <26589867+WhichWho@users.noreply.github.com>
Lucas Zanek <57494138+LucasZNK@users.noreply.github.com>
Luis Herrera <herrera-luis@users.noreply.github.com>
Lukas Rist <glaslos@gmail.com>
M. A. Ali <73258591+MightyStud@users.noreply.github.com>
M. Eren Akbiyik <erenakbiyik@gmail.com>
Maciek <maciek.mab122@gmail.com>
Marcin Mielniczuk <marmistrz.dev@zoho.eu>
Martin Warnaar <martinwarnaar@gmail.com>
Matheus de Sousa <23645013+keyehzy@users.noreply.github.com>
Mathijs de Bruin <mathijs@mathijsfietst.nl>
Matija Pevec <mightymatth@users.noreply.github.com>
Maximiliano Levi <8160966+maxilevi@users.noreply.github.com>
Meng, Hengyu <hengyu.meng@intel.com>
Michael Podvitskiy <podvitskiymichael@gmail.com>
Michael Rienstra <mrienstra@gmail.com>
Mikhail Grigorev <sleuthhound@gmail.com>
Mohammadreza Hendiani <hendiani.mohammadreza@gmail.com>
Mohit Agarwal <mohit@sdf.org>
Murilo Santana <mvrilo@gmail.com>
Neil Chudleigh <nchudleigh@users.noreply.github.com>
Neo Zhang Jianyu <jianyu.zhang@intel.com>
Neuman Vong <neuman.vong@gmail.com>
Nicholas Albion <nalbion@yahoo.com>
Niels Mayer <Niels.Mayer@gmail.com>
Okabintaro <103938900+Okabintaro@users.noreply.github.com>
Oleg Sidorov <me@whitebox.io>
Oleg Sidorov <oleg@sidorov.nl>
Ondrej Kokes <ondrej.kokes@gmail.com>
Ouadie EL FAROUKI <ouadie.elfarouki@codeplay.com>
Paul Tsochantaris <ptsochantaris@icloud.com>
Philipp Zabel <philipp.zabel@gmail.com>
Philippe Normand <phil@base-art.net>
Przemysław Pawełczyk <przemoc@gmail.com>
Qianhe Chen <54462604+chenqianhe@users.noreply.github.com>
Radosław Gryta <radek.gryta@gmail.com>
Reinforce-II <fate@eastal.com>
Reinis Muiznieks <muiznieks.reinis@gmail.com>
RelatedTitle <r3latedtitle@gmail.com>
RhinoDevel <RhinoDevel@users.noreply.github.com>
Rich Jones <miserlou@gmail.com>
Robin <robin.xw@hotmail.com>
Roddur Dasgupta <roddurd@gmail.com>
Roland Rabien <figbug@gmail.com>
Rotem Dan <rotemdan@gmail.com>
Ryan Hitchman <hitchmanr@gmail.com>
Ryan Metcalfe <107415876+RyanMetcalfeInt8@users.noreply.github.com>
RyanChang <ftes90015@gmail.com>
Sam <49637763+Onlyartist9@users.noreply.github.com>
Sam Pullara <spullara@gmail.com>
Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com>
Sergio López <slp@sinrega.org>
Siddharth Ramakrishnan <srr2141@columbia.edu>
Simon Moisselin <simon.moisstoll@gmail.com>
Sindre Sorhus <sindresorhus@gmail.com>
Slava Primenko <primenko.s@gmail.com>
Syahmi Azhar <prsyahmi@gmail.com>
Syed Jafri <syedjafri97@gmail.com>
Sơn Phan Trung <phantrungson17@gmail.com>
Taisei Mima <bhbstar.me@gmail.com>
Takeshi Inoue <inoue.takeshi@gmail.com>
Tamotsu Takahashi <ttakah+github@gmail.com>
Taras Glek <taras@thegp.com>
Tauseef Mohiuddin <35351464+tauseefmohammed2@users.noreply.github.com>
Thijs Raymakers <thijs@raymakers.nl>
Thomas Fitzsimmons <fitzsim@fitzsim.org>
Tiago Fassoni <tiagofassoni@users.noreply.github.com>
Tienshiao Ma <tienshiao@tienshiao.org>
Timothy Cronin <40186632+4imothy@users.noreply.github.com>
Tobrun <tobrun.van.nuland@gmail.com>
Todd <taf2@users.noreply.github.com>
Tong Li <31761981+litongjava@users.noreply.github.com>
Topping1 <78745143+Topping1@users.noreply.github.com>
Travis Cline <travis.cline@gmail.com>
UEXTM.com <84163508+uextm@users.noreply.github.com>
Vadim Peretokin <vperetokin@hey.com>
Valentin Gosu <1454649+valenting@users.noreply.github.com>
Vulcan <93451215+trholding@users.noreply.github.com>
WhiteOlivierus <36532695+WhiteOlivierus@users.noreply.github.com>
Xiang (Kevin) Li <kevinli020508@gmail.com>
Xiao-Yong Jin <jinxiaoyong@gmail.com>
XiaotaoChen <chenxiaotao1234@gmail.com>
Yajing Tang <phillis@google.com>
Yang Shen <aplshenyang@gmail.com>
Yunès <jean.baptiste.yunes@free.fr>
ZaBlazzingZephyrus <119159668+blazingzephyr@users.noreply.github.com>
Zigfrid Zvezdin <ziggerZZ@gmail.com>
Zollner <24618122+Zolliner@users.noreply.github.com>
ai-at-home <149282006+ai-at-home@users.noreply.github.com>
alonfaraj <alonfaraj@gmail.com>
andypayne <apayne@gmail.com>
ardfork <134447697+ardfork@users.noreply.github.com>
automaticcat <daogiatuank54@gmail.com>
be-next <jerome.ramette@gmail.com>
bert hubert <bert@hubertnet.nl>
bmwl <brian.marshall@tolko.com>
bobqianic <129547291+bobqianic@users.noreply.github.com>
bocytko <bocytko+github@gmail.com>
boolemancer <48014766+boolemancer@users.noreply.github.com>
boolemancer <boolemancer@gmail.com>
bradmit <151883577+bradmit@users.noreply.github.com>
brunofaustino <b.fa.amorim@gmail.com>
bssrdf <merlintiger@hotmail.com>
byte-6174 <88070277+byte-6174@users.noreply.github.com>
cdosoftei <ciprian.dosoftei@gmail.com>
clach04 <Chris.Clark@actian.com>
compilade <113953597+compilade@users.noreply.github.com>
conradg <conradjgodfrey@gmail.com>
ddpasa <112642920+ddpasa@users.noreply.github.com>
denersc <denerstassun@gmail.com>
dscripka <dscripka@users.noreply.github.com>
duthils <duthils@duthils.net>
ecneladis <ecneladis@users.noreply.github.com>
faker <nspyia2002@gmail.com>
fitzsim <fitzsim@fitzsim.org>
fraxy-v <65565042+fraxy-v@users.noreply.github.com>
genevera (she/her) <genevera@users.noreply.github.com>
geniusnut <geniusnut@gmail.com>
greeshmay <greeshmay@gmail.com>
hydai <z54981220@gmail.com>
iamthad <thadeus.j.fleming@gmail.com>
james wolf <contractorwolf@hotmail.com>
joecryptotoo <80373433+joecryptotoo@users.noreply.github.com>
jorismertz <35079666+jorismertz@users.noreply.github.com>
junkfood <69683722+JunkFood02@users.noreply.github.com>
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kamranjon <kamranjon@gmail.com>
katsu560 <katsu560oo-@docomo.ne.jp>
kennethge <57784063+kenneth-ge@users.noreply.github.com>
keyehzy <msamuel@aluno.puc-rio.br>
leejet <leejet714@gmail.com>
litong <31761981+litongjava@users.noreply.github.com>
lnyan <lkwq007@gmail.com>
m.bell <m.bell@techsmith.com>
mkiol <mkiol@users.noreply.github.com>
novag <7754358+novag@users.noreply.github.com>
pajowu <pajowu@pajowu.de>
polarmoon <90010972+polarmoon@users.noreply.github.com>
rlapray <lapray.romain@gmail.com>
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shibukazu <61775791+shibukazu@users.noreply.github.com>
shikokuchuo <53399081+shikokuchuo@users.noreply.github.com>
slaren <slarengh@gmail.com>
slashlib <slashlib@users.noreply.github.com>
snadampal <87143774+snadampal@users.noreply.github.com>
st-gr <38470677+st-gr@users.noreply.github.com>
texmex76 <40733439+texmex76@users.noreply.github.com>
thefinaldegree <thefinaldegree@gmail.com>
trixirt <trix@redhat.com>
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 1.7.2)
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 1.4.2)
# 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

1167
Makefile

File diff suppressed because it is too large Load Diff

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@ -1,68 +0,0 @@
// swift-tools-version:5.5
import PackageDescription
let package = Package(
name: "whisper",
platforms: [
.macOS(.v12),
.iOS(.v14),
.watchOS(.v4),
.tvOS(.v14)
],
products: [
.library(name: "whisper", targets: ["whisper"]),
],
targets: [
.target(
name: "whisper",
path: ".",
exclude: [
"build",
"bindings",
"cmake",
"examples",
"scripts",
"models",
"samples",
"tests",
"CMakeLists.txt",
"Makefile",
"ggml/src/ggml-metal/ggml-metal-embed.metal"
],
sources: [
"ggml/src/ggml.c",
"src/whisper.cpp",
"ggml/src/ggml-aarch64.c",
"ggml/src/ggml-alloc.c",
"ggml/src/ggml-backend.cpp",
"ggml/src/ggml-backend-reg.cpp",
"ggml/src/ggml-cpu/ggml-cpu.c",
"ggml/src/ggml-cpu/ggml-cpu.cpp",
"ggml/src/ggml-cpu/ggml-cpu-aarch64.c",
"ggml/src/ggml-cpu/ggml-cpu-quants.c",
"ggml/src/ggml-quants.c",
"ggml/src/ggml-threading.cpp",
"ggml/src/ggml-metal/ggml-metal.m"
],
resources: [.process("ggml/src/ggml-metal/ggml-metal.metal")],
publicHeadersPath: "spm-headers",
cSettings: [
.unsafeFlags(["-Wno-shorten-64-to-32", "-O3", "-DNDEBUG"]),
.unsafeFlags(["-fno-objc-arc"]),
.headerSearchPath("ggml/src"),
.define("GGML_USE_ACCELERATE"),
.define("GGML_USE_METAL")
// NOTE: NEW_LAPACK will required iOS version 16.4+
// We should consider add this in the future when we drop support for iOS 14
// (ref: ref: https://developer.apple.com/documentation/accelerate/1513264-cblas_sgemm?language=objc)
// .define("ACCELERATE_NEW_LAPACK"),
// .define("ACCELERATE_LAPACK_ILP64")
],
linkerSettings: [
.linkedFramework("Accelerate")
]
)
],
cxxLanguageStandard: .cxx11
)

359
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: [v1.7.2](https://github.com/ggerganov/whisper.cpp/releases/tag/v1.7.2) / [Roadmap | F.A.Q.](https://github.com/ggerganov/whisper.cpp/discussions/126)
Beta: [v1.4.2](https://github.com/ggerganov/whisper.cpp/releases/tag/v1.4.2) / 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)
@ -57,39 +58,33 @@ 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/include/ggml.h) / [ggml.c](ggml/src/ggml.c))
- The transformer model and the high-level C-style API are implemented in C++ ([whisper.h](include/whisper.h) / [whisper.cpp](src/whisper.cpp))
- 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.
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:
```
cd whisper.cpp
```
Then, download one of the Whisper [models](models/README.md) converted in [`ggml` format](#ggml-format). For example:
```bash
sh ./models/download-ggml-model.sh base.en
```
If you wish to convert the Whisper models to ggml format yourself, instructions are in [models/README.md](models/README.md).
Now build the [main](examples/main) example and transcribe an audio file like this:
```bash
# build the main example
make -j
make
# transcribe an audio file
./main -f samples/jfk.wav
@ -99,8 +94,8 @@ make -j
For a quick demo, simply run `make base.en`:
```text
$ make -j 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
@ -119,8 +114,8 @@ options:
-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 [5 ] number of best candidates to keep
-bs N, --beam-size N [5 ] beam size for beam search
-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
@ -137,7 +132,6 @@ options:
-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
-ojf, --output-json-full [false ] include more information in the 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
@ -149,11 +143,10 @@ options:
-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 tokens
-ng, --no-gpu [false ] disable GPU
-ls, --log-score [false ] log best decoder scores of token
sh ./models/download-ggml-model.sh base.en
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'
@ -215,7 +208,7 @@ For detailed usage instructions, run: `./main -h`
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
```
@ -224,7 +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`.
@ -232,29 +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
@ -265,7 +257,7 @@ Here are the steps for creating and using a quantized model:
```bash
# quantize a model with Q5_0 method
make -j quantize
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
@ -287,8 +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`
@ -314,8 +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
$ ./main -m models/ggml-base.en.bin -f samples/jfk.wav
```bash
./main -m models/ggml-base.en.bin -f samples/jfk.wav
...
@ -343,23 +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:
@ -368,7 +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:
@ -378,28 +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
$ ./main -m models/ggml-base.en.bin -f samples/jfk.wav
```bash
./main -m models/ggml-base.en.bin -f samples/jfk.wav
...
@ -415,31 +400,44 @@ 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:
```
make clean
GGML_CUDA=1 make -j
WHISPER_CUBLAS=1 make -j
```
## 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.
## 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:
Now build `whisper.cpp` with Vulkan support:
```
Makefile:
cd whisper.cpp
make clean
make GGML_VULKAN=1 -j
WHISPER_CLBLAST=1 make -j
CMake:
cd whisper.cpp
cmake -B build -DWHISPER_CLBLAST=ON
cmake --build build -j --config Release
```
Run all the examples as usual.
## BLAS CPU support via OpenBLAS
Encoder processing can be accelerated on the CPU via OpenBLAS.
@ -449,99 +447,9 @@ Now build `whisper.cpp` with OpenBLAS support:
```
make clean
GGML_OPENBLAS=1 make -j
WHISPER_OPENBLAS=1 make -j
```
## BLAS CPU support via Intel MKL
Encoder processing can be accelerated on the CPU via the BLAS compatible interface of Intel's Math Kernel Library.
First, make sure you have installed Intel's MKL runtime and development packages: https://www.intel.com/content/www/us/en/developer/tools/oneapi/onemkl-download.html
Now build `whisper.cpp` with Intel MKL BLAS support:
```
source /opt/intel/oneapi/setvars.sh
mkdir build
cd build
cmake -DWHISPER_MKL=ON ..
WHISPER_MKL=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:
```
mkdir build
cd build
cmake .. -D GGML_CANN=on
make -j
```
Run the inference examples as usual, for example:
```
./build/bin/main -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`.
## Docker
### Prerequisites
- Docker must be installed and running on your system.
- Create a folder to store big models & intermediate files (ex. /whisper/models)
### Images
We have two Docker images available for this project:
1. `ghcr.io/ggerganov/whisper.cpp:main`: This image includes the main executable file as well as `curl` and `ffmpeg`. (platforms: `linux/amd64`, `linux/arm64`)
2. `ghcr.io/ggerganov/whisper.cpp:main-cuda`: Same as `main` but compiled with CUDA support. (platforms: `linux/amd64`)
### Usage
```shell
# download model and persist it in a local folder
docker run -it --rm \
-v path/to/models:/models \
whisper.cpp:main "./models/download-ggml-model.sh base /models"
# transcribe an audio file
docker run -it --rm \
-v path/to/models:/models \
-v path/to/audios:/audios \
whisper.cpp:main "./main -m /models/ggml-base.bin -f /audios/jfk.wav"
# transcribe an audio file in samples folder
docker run -it --rm \
-v path/to/models:/models \
whisper.cpp:main "./main -m /models/ggml-base.bin -f ./samples/jfk.wav"
```
## 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
@ -554,7 +462,7 @@ in about half a minute on a MacBook M1 Pro, using `medium.en` model:
<details>
<summary>Expand to see the result</summary>
```text
```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'
@ -626,7 +534,6 @@ whisper_print_timings: encode time = 18665.10 ms / 9 runs ( 2073.90 ms per
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
@ -635,8 +542,8 @@ This is a naive example of performing real-time inference on audio from your mic
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
make stream -j
```java
make stream
./stream -m ./models/ggml-base.en.bin -t 8 --step 500 --length 5000
```
@ -647,7 +554,7 @@ 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
```java
./main -m models/ggml-base.en.bin -f samples/gb0.wav --print-colors
```
@ -657,8 +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
$ ./main -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'
...
@ -681,8 +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
$ ./main -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'
...
@ -750,9 +657,9 @@ The [main](examples/main) example provides support for output of karaoke-style m
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
```java
./main -m ./models/ggml-base.en.bin -f ./samples/jfk.wav -owts
source ./samples/jfk.wav.wts
ffplay ./samples/jfk.wav.mp4
@ -762,7 +669,7 @@ https://user-images.githubusercontent.com/1991296/199337465-dbee4b5e-9aeb-48a3-b
---
```bash
```java
./main -m ./models/ggml-base.en.bin -f ./samples/mm0.wav -owts
source ./samples/mm0.wav.wts
ffplay ./samples/mm0.wav.mp4
@ -772,7 +679,7 @@ https://user-images.githubusercontent.com/1991296/199337504-cc8fd233-0cb7-4920-9
---
```bash
```java
./main -m ./models/ggml-base.en.bin -f ./samples/gb0.wav -owts
source ./samples/gb0.wav.wts
ffplay ./samples/gb0.wav.mp4
@ -784,10 +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
```
@ -803,19 +710,20 @@ 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:
@ -830,52 +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 |
| --------------------------------------------------- | ------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------- |
| [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 |
| [wchess](examples/wchess) | [wchess.wasm](examples/wchess) | Voice-controlled chess |
| [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) |
| [server](examples/server) | | HTTP transcription server with OAI-like API |
| 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)

View File

@ -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.

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 44b39fd4ec

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;
@ -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",
"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": "1.7.2",
"version": "1.4.2",
"description": "Whisper speech recognition",
"main": "whisper.js",
"scripts": {

File diff suppressed because one or more lines are too long

View File

@ -1,3 +0,0 @@
LICENSE
pkg/
lib/whisper.*

View File

@ -1,169 +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("path/to/model.bin")
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 ###
Use script to download model file(s):
```bash
git clone https://github.com/ggerganov/whisper.cpp.git
cd whisper.cpp
sh ./models/download-ggml-model.sh base.en
```
There are some types of models. See [models][] page for details.
### Preparing audio file ###
Currently, whisper.cpp accepts only 16-bit WAV files.
### API ###
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
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
# 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)
```
You can see model information:
```ruby
whisper = Whisper::Context.new("path/to/model.bin")
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"
```
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(MODEL)
```
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

@ -1,68 +0,0 @@
require 'rake/clean'
require "bundler/gem_tasks"
require "pathname"
require "yaml"
require "rake/testtask"
extsources = YAML.load_file("extsources.yaml")
SOURCES = FileList[]
extsources.each do |src|
basename = src.pathmap("%f")
dest = basename == "LICENSE" ? basename : basename.pathmap("ext/%f")
file src
file dest => src 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}",
"ext/depend"
]
task build: FileList[
"ext/Makefile",
"ext/ruby_whisper.h",
"ext/ruby_whisper.cpp",
"whispercpp.gemspec",
]
directory "pkg"
CLOBBER.include "pkg"
TEST_MODEL = "../../models/ggml-base.en.bin"
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 LIB_FILE
directory "lib"
file LIB_FILE => [SO_FILE, "lib"] do |t|
copy t.source, t.name
end
Rake::TestTask.new do |t|
t.test_files = FileList["tests/test_*.rb"]
end
task test: [TEST_MODEL, LIB_FILE]
file TEST_MODEL do
Dir.chdir "../.." do
sh "./models/download-ggml-model.sh base.en"
end
end

View File

@ -3,33 +3,7 @@ ggml.c
ggml.h
ggml-alloc.c
ggml-alloc.h
ggml-aarch64.c
ggml-aarch64.h
ggml-backend.cpp
ggml-backend-impl.h
ggml-backend.c
ggml-backend.h
ggml-common.h
ggml-cpu-impl.h
ggml-metal.m
ggml-metal.metal
ggml-metal-embed.metal
ggml-blas.cpp
ggml-cuda.h
ggml-impl.h
ggml-kompute.h
ggml-metal.h
ggml-opencl.h
ggml-quants.c
ggml-quants.h
ggml-sycl.h
ggml-vulkan.h
ggml-blas.h
get-flags.mk
whisper.bundle
whisper.cpp
whisper.h
dr_wav.h
depend
whisper.bundle
whisper.so
whisper.dll

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++11'
$LDFLAGS << ' -lstdc++'
# Set to true when building binary gems
if enable_config('static-stdlib', false)
$LDFLAGS << ' -static-libgcc -static-libstdc++'
@ -15,180 +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 = ''
$MK_CFLAGS = '-std=c11 -fPIC'
$MK_CXXFLAGS = '-std=c++11 -fPIC'
$MK_NVCCFLAGS = '-std=c++11'
$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
if $UNAME_M.match? /aarch64.*/
$MK_CFLAGS << ' -mcpu=native'
$MK_CXXFLAGS << ' -mcpu=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'
$MK_CPPFLAGS << ' -DACCELERATE_NEW_LAPACK'
$MK_CPPFLAGS << ' -DACCELERATE_LAPACK_ILP64'
$MK_LDFLAGS << ' -framework Accelerate'
$OBJ_GGML << '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-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-blas.o'
end
if $GGML_METAL
$MK_CPPFLAGS << ' -DGGML_USE_METAL'
$MK_LDFLAGS << ' -framework Foundation -framework Metal -framework MetalKit'
$OBJ_GGML << '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-metal-embed.o'
end
end
$OBJ_GGML <<
'ggml.o' <<
'ggml-cpu.o' <<
'ggml-alloc.o' <<
'ggml-backend.o' <<
'ggml-quants.o' <<
'ggml-aarch64.o'
$OBJ_WHISPER <<
'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 get-flags.mk'
if $GGML_METAL
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

View File

@ -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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#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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@ -1,14 +0,0 @@
ggml-metal-embed.o: \
ggml-metal.metal \
ggml-common.h
@echo "Embedding Metal library"
@sed -e '/#include "ggml-common.h"/r ggml-common.h' -e '/#include "ggml-common.h"/d' < ggml-metal.metal > ggml-metal-embed.metal
$(eval TEMP_ASSEMBLY=$(shell mktemp))
@echo ".section __DATA, __ggml_metallib" > $(TEMP_ASSEMBLY)
@echo ".globl _ggml_metallib_start" >> $(TEMP_ASSEMBLY)
@echo "_ggml_metallib_start:" >> $(TEMP_ASSEMBLY)
@echo ".incbin \"ggml-metal-embed.metal\"" >> $(TEMP_ASSEMBLY)
@echo ".globl _ggml_metallib_end" >> $(TEMP_ASSEMBLY)
@echo "_ggml_metallib_end:" >> $(TEMP_ASSEMBLY)
@$(AS) $(TEMP_ASSEMBLY) -o $@
@rm -f ${TEMP_ASSEMBLY}

File diff suppressed because it is too large Load Diff

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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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@ -1,31 +0,0 @@
---
- ../../src/whisper.cpp
- ../../include/whisper.h
- ../../ggml/src/ggml.c
- ../../ggml/src/ggml-cpu.c
- ../../ggml/src/ggml-impl.h
- ../../ggml/src/ggml-aarch64.h
- ../../ggml/src/ggml-aarch64.c
- ../../ggml/src/ggml-alloc.c
- ../../ggml/src/ggml-backend-impl.h
- ../../ggml/src/ggml-backend.cpp
- ../../ggml/src/ggml-common.h
- ../../ggml/src/ggml-quants.h
- ../../ggml/src/ggml-quants.c
- ../../ggml/src/ggml-cpu-impl.h
- ../../ggml/src/ggml-metal.m
- ../../ggml/src/ggml-metal.metal
- ../../ggml/src/ggml-blas.cpp
- ../../ggml/include/ggml.h
- ../../ggml/include/ggml-alloc.h
- ../../ggml/include/ggml-backend.h
- ../../ggml/include/ggml-cpu.h
- ../../ggml/include/ggml-cuda.h
- ../../ggml/include/ggml-kompute.h
- ../../ggml/include/ggml-metal.h
- ../../ggml/include/ggml-sycl.h
- ../../ggml/include/ggml-vulkan.h
- ../../ggml/include/ggml-blas.h
- ../../scripts/get-flags.mk
- ../../examples/dr_wav.h
- ../../LICENSE

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@ -1,7 +0,0 @@
require "test/unit"
require "whisper"
class TestBase < Test::Unit::TestCase
MODEL = File.join(__dir__, "..", "..", "..", "models", "ggml-base.en.bin")
AUDIO = File.join(__dir__, "..", "..", "..", "samples", "jfk.wav")
end

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@ -1,163 +0,0 @@
require "test/unit"
require "whisper"
class TestCallback < Test::Unit::TestCase
TOPDIR = File.expand_path(File.join(File.dirname(__FILE__), '..'))
def setup
GC.start
@params = Whisper::Params.new
@whisper = Whisper::Context.new(File.join(TOPDIR, '..', '..', 'models', 'ggml-base.en.bin'))
@audio = File.join(TOPDIR, '..', '..', 'samples', 'jfk.wav')
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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@ -1,44 +0,0 @@
require_relative "helper"
class TestModel < TestBase
def test_model
whisper = Whisper::Context.new(MODEL)
assert_instance_of Whisper::Model, whisper.model
end
def test_attributes
whisper = Whisper::Context.new(MODEL)
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(MODEL).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
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, "pkg/#{filename.shellescape}", exception: true
assert_path_exist File.join(dir, "gems/whispercpp-#{version}/lib", basename)
end
end
end
end

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@ -1,154 +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_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_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
end

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@ -1,83 +0,0 @@
require_relative "helper"
class TestSegment < TestBase
class << self
attr_reader :whisper
def startup
@whisper = Whisper::Context.new(TestBase::MODEL)
params = Whisper::Params.new
params.print_timestamps = false
@whisper.transcribe(TestBase::AUDIO, params)
end
end
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_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
private
def whisper
self.class.whisper
end
end

View File

@ -1,127 +1,138 @@
require_relative "helper"
require "stringio"
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(MODEL)
@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
class << self
attr_reader :whisper
def startup
@whisper = Whisper::Context.new(TestBase::MODEL)
params = Whisper::Params.new
params.print_timestamps = false
@whisper.transcribe(TestBase::AUDIO, params)
end
end
def whisper
self.class.whisper
end
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
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(MODEL)
assert logs.length > 30
logs.each do |log|
assert_equal Whisper::LOG_LEVEL_INFO, 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(MODEL)
assert_empty dev.string
ensure
$stderr = stderr
end
end

View File

@ -1,36 +0,0 @@
require "yaml"
Gem::Specification.new do |s|
s.name = "whispercpp"
s.authors = ["Georgi Gerganov", "Todd A. Fisher"]
s.version = '1.3.0'
s.date = '2024-05-14'
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") +
YAML.load_file("extsources.yaml").collect {|file|
basename = File.basename(file)
if s.extra_rdoc_files.include?(basename)
basename
else
File.join("ext", basename)
end
}
s.summary = %q{Ruby whisper.cpp bindings}
s.test_files = ["tests/test_whisper.rb"]
s.extensions << 'ext/extconf.rb'
#### 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

@ -13,5 +13,5 @@ set_target_properties(${TARGET}
PROPERTIES
EXPORT_COMPILE_COMMANDS ON
RUNTIME_OUTPUT_DIRECTORY "${CMAKE_BINARY_DIR}/bin"
INSTALL_RPATH "${CMAKE_INSTALL_PREFIX}/lib"
INSTALL_RPATH "${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=${prefix}
libdir=@CMAKE_INSTALL_FULL_LIBDIR@
includedir=${prefix}/include
Name: whisper
Description: Port of OpenAI's Whisper model in C/C++
Version: @PROJECT_VERSION@
Libs: -L${libdir} -lwhisper
Cflags: -I${includedir}

View File

@ -123,7 +123,7 @@ API_AVAILABLE(macos(12.0), ios(15.0), watchos(8.0), tvos(15.0)) __attribute__((v
/**
Make a prediction using the convenience interface
@param logmel_data as 1 × n_mel × 3000 3-dimensional array of floats:
@param logmel_data as 1 × 80 × 3000 3-dimensional array of floats:
@param error If an error occurs, upon return contains an NSError object that describes the problem. If you are not interested in possible errors, pass in NULL.
@return the prediction as whisper_encoder_implOutput
*/

View File

@ -3,8 +3,6 @@
// Code is derived from the work of Github user @wangchou
// ref: https://github.com/wangchou/callCoreMLFromCpp
#include <stdint.h>
#if __cplusplus
extern "C" {
#endif
@ -16,8 +14,6 @@ void whisper_coreml_free(struct whisper_coreml_context * ctx);
void whisper_coreml_encode(
const whisper_coreml_context * ctx,
int64_t n_ctx,
int64_t n_mel,
float * mel,
float * out);

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]);
@ -48,15 +48,13 @@ void whisper_coreml_free(struct whisper_coreml_context * ctx) {
void whisper_coreml_encode(
const whisper_coreml_context * ctx,
int64_t n_ctx,
int64_t n_mel,
float * mel,
float * out) {
MLMultiArray * inMultiArray = [
[MLMultiArray alloc] initWithDataPointer: mel
shape: @[@1, @(n_mel), @(n_ctx)]
shape: @[@1, @80, @3000]
dataType: MLMultiArrayDataTypeFloat32
strides: @[@(n_ctx*n_mel), @(n_ctx), @1]
strides: @[@(240000), @(3000), @1]
deallocator: nil
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
@ -80,69 +43,31 @@ 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})
if (EMSCRIPTEN)
add_subdirectory(whisper.wasm)
set_target_properties(libmain PROPERTIES FOLDER "libs")
add_subdirectory(stream.wasm)
set_target_properties(libstream PROPERTIES FOLDER "libs")
add_subdirectory(command.wasm)
set_target_properties(libcommand PROPERTIES FOLDER "libs")
#add_subdirectory(talk.wasm)
#set_target_properties(libtalk PROPERTIES FOLDER "libs")
add_subdirectory(talk.wasm)
add_subdirectory(bench.wasm)
set_target_properties(libbench PROPERTIES FOLDER "libs")
elseif(CMAKE_JS_VERSION)
add_subdirectory(addon.node)
set_target_properties(addon.node PROPERTIES FOLDER "examples")
else()
add_subdirectory(main)
set_target_properties(main PROPERTIES FOLDER "examples")
if (WHISPER_SDL2)
add_subdirectory(stream)
set_target_properties(stream PROPERTIES FOLDER "examples")
endif (WHISPER_SDL2)
add_subdirectory(server)
set_target_properties(server PROPERTIES FOLDER "examples")
if (WHISPER_SDL2)
add_subdirectory(command)
set_target_properties(command PROPERTIES FOLDER "examples")
endif (WHISPER_SDL2)
add_subdirectory(bench)
set_target_properties(bench PROPERTIES FOLDER "examples")
add_subdirectory(quantize)
set_target_properties(quantize PROPERTIES FOLDER "examples")
if (WHISPER_SDL2)
# TODO: disabled until update
# https://github.com/ggerganov/whisper.cpp/issues/1818
#add_subdirectory(talk)
#set_target_properties(talk PROPERTIES FOLDER "examples")
add_subdirectory(talk)
add_subdirectory(talk-llama)
set_target_properties(talk-llama PROPERTIES FOLDER "examples")
add_subdirectory(lsp)
set_target_properties(lsp PROPERTIES FOLDER "examples")
if (GGML_SYCL)
add_subdirectory(sycl)
set_target_properties(ls-sycl-device PROPERTIES FOLDER "examples")
endif()
endif (WHISPER_SDL2)
endif()
if (WHISPER_SDL2)
add_subdirectory(wchess)
set_target_properties(wchess PROPERTIES FOLDER "examples")
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

@ -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

@ -37,13 +37,9 @@ https://user-images.githubusercontent.com/1991296/207435352-8fc4ed3f-bde5-4555-9
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

View File

@ -9,7 +9,6 @@
#include "common-sdl.h"
#include "common.h"
#include "whisper.h"
#include "grammar-parser.h"
#include <sstream>
#include <cassert>
@ -31,35 +30,26 @@ struct whisper_params {
int32_t max_tokens = 32;
int32_t audio_ctx = 0;
float vad_thold = 0.6f;
float freq_thold = 100.0f;
float grammar_penalty = 100.0f;
grammar_parser::parse_state grammar_parsed;
float vad_thold = 0.6f;
float freq_thold = 100.0f;
bool speed_up = false;
bool translate = false;
bool print_special = false;
bool print_energy = false;
bool no_timestamps = true;
bool use_gpu = true;
bool flash_attn = false;
std::string language = "en";
std::string model = "models/ggml-base.en.bin";
std::string fname_out;
std::string commands;
std::string prompt;
std::string context;
std::string grammar;
// A regular expression that matches tokens to suppress
std::string suppress_regex;
};
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];
@ -75,20 +65,16 @@ static bool whisper_params_parse(int argc, char ** argv, whisper_params & params
else if (arg == "-ac" || arg == "--audio-ctx") { params.audio_ctx = std::stoi(argv[++i]); }
else if (arg == "-vth" || arg == "--vad-thold") { params.vad_thold = std::stof(argv[++i]); }
else if (arg == "-fth" || arg == "--freq-thold") { params.freq_thold = std::stof(argv[++i]); }
else if (arg == "-su" || arg == "--speed-up") { params.speed_up = true; }
else if (arg == "-tr" || arg == "--translate") { params.translate = true; }
else if (arg == "-ps" || arg == "--print-special") { params.print_special = true; }
else if (arg == "-pe" || arg == "--print-energy") { params.print_energy = true; }
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 == "-l" || arg == "--language") { params.language = argv[++i]; }
else if (arg == "-m" || arg == "--model") { params.model = argv[++i]; }
else if (arg == "-f" || arg == "--file") { params.fname_out = argv[++i]; }
else if (arg == "-cmd" || arg == "--commands") { params.commands = argv[++i]; }
else if (arg == "-p" || arg == "--prompt") { params.prompt = argv[++i]; }
else if (arg == "-ctx" || arg == "--context") { params.context = argv[++i]; }
else if ( arg == "--grammar") { params.grammar = argv[++i]; }
else if ( arg == "--grammar-penalty") { params.grammar_penalty = std::stof(argv[++i]); }
else if ( arg == "--suppress-regex") { params.suppress_regex = argv[++i]; }
else {
fprintf(stderr, "error: unknown argument: %s\n", arg.c_str());
whisper_print_usage(argc, argv, params);
@ -113,41 +99,26 @@ void whisper_print_usage(int /*argc*/, char ** argv, const whisper_params & para
fprintf(stderr, " -ac N, --audio-ctx N [%-7d] audio context size (0 - all)\n", params.audio_ctx);
fprintf(stderr, " -vth N, --vad-thold N [%-7.2f] voice activity detection threshold\n", params.vad_thold);
fprintf(stderr, " -fth N, --freq-thold N [%-7.2f] high-pass frequency cutoff\n", params.freq_thold);
fprintf(stderr, " -su, --speed-up [%-7s] speed up audio by x2 (reduced accuracy)\n", params.speed_up ? "true" : "false");
fprintf(stderr, " -tr, --translate [%-7s] translate from source language to english\n", params.translate ? "true" : "false");
fprintf(stderr, " -ps, --print-special [%-7s] print special tokens\n", params.print_special ? "true" : "false");
fprintf(stderr, " -pe, --print-energy [%-7s] print sound energy (for debugging)\n", params.print_energy ? "true" : "false");
fprintf(stderr, " -ng, --no-gpu [%-7s] disable GPU\n", params.use_gpu ? "false" : "true");
fprintf(stderr, " -fa, --flash-attn [%-7s] flash attention\n", params.flash_attn ? "true" : "false");
fprintf(stderr, " -l LANG, --language LANG [%-7s] spoken language\n", params.language.c_str());
fprintf(stderr, " -m FNAME, --model FNAME [%-7s] model path\n", params.model.c_str());
fprintf(stderr, " -f FNAME, --file FNAME [%-7s] text output file name\n", params.fname_out.c_str());
fprintf(stderr, " -cmd FNAME, --commands FNAME [%-7s] text file with allowed commands\n", params.commands.c_str());
fprintf(stderr, " -p, --prompt [%-7s] the required activation prompt\n", params.prompt.c_str());
fprintf(stderr, " -ctx, --context [%-7s] sample text to help the transcription\n", params.context.c_str());
fprintf(stderr, " --grammar GRAMMAR [%-7s] GBNF grammar to guide decoding\n", params.grammar.c_str());
fprintf(stderr, " --grammar-penalty N [%-7.1f] scales down logits of nongrammar tokens\n", params.grammar_penalty);
fprintf(stderr, " --suppress-regex REGEX [%-7s] regular expression matching tokens to suppress\n", params.suppress_regex.c_str());
fprintf(stderr, "\n");
}
static std::string transcribe(
whisper_context * ctx,
const whisper_params & params,
const std::vector<float> & pcmf32,
const std::string & grammar_rule,
float & logprob_min,
float & logprob_sum,
int & n_tokens,
int64_t & t_ms) {
std::string transcribe(whisper_context * ctx, const whisper_params & params, const std::vector<float> & pcmf32, float & prob, int64_t & t_ms) {
const auto t_start = std::chrono::high_resolution_clock::now();
logprob_min = 0.0f;
logprob_sum = 0.0f;
n_tokens = 0;
prob = 0.0f;
t_ms = 0;
//whisper_full_params wparams = whisper_full_default_params(WHISPER_SAMPLING_GREEDY);
whisper_full_params wparams = whisper_full_default_params(WHISPER_SAMPLING_BEAM_SEARCH);
whisper_full_params wparams = whisper_full_default_params(WHISPER_SAMPLING_GREEDY);
wparams.print_progress = false;
wparams.print_special = params.print_special;
@ -155,42 +126,19 @@ static std::string transcribe(
wparams.print_timestamps = !params.no_timestamps;
wparams.translate = params.translate;
wparams.no_context = true;
wparams.no_timestamps = params.no_timestamps;
wparams.single_segment = true;
wparams.max_tokens = params.max_tokens;
wparams.language = params.language.c_str();
wparams.n_threads = params.n_threads;
wparams.audio_ctx = params.audio_ctx;
wparams.temperature = 0.4f;
wparams.temperature_inc = 1.0f;
wparams.greedy.best_of = 5;
wparams.beam_search.beam_size = 5;
wparams.initial_prompt = params.context.data();
wparams.suppress_regex = params.suppress_regex.c_str();
const auto & grammar_parsed = params.grammar_parsed;
auto grammar_rules = grammar_parsed.c_rules();
if (!params.grammar_parsed.rules.empty() && !grammar_rule.empty()) {
if (grammar_parsed.symbol_ids.find(grammar_rule) == grammar_parsed.symbol_ids.end()) {
fprintf(stderr, "%s: warning: grammar rule '%s' not found - skipping grammar sampling\n", __func__, grammar_rule.c_str());
} else {
wparams.grammar_rules = grammar_rules.data();
wparams.n_grammar_rules = grammar_rules.size();
wparams.i_start_rule = grammar_parsed.symbol_ids.at(grammar_rule);
wparams.grammar_penalty = params.grammar_penalty;
}
}
wparams.audio_ctx = params.audio_ctx;
wparams.speed_up = params.speed_up;
if (whisper_full(ctx, wparams, pcmf32.data(), pcmf32.size()) != 0) {
return "";
}
int prob_n = 0;
std::string result;
const int n_segments = whisper_full_n_segments(ctx);
@ -199,24 +147,26 @@ static std::string transcribe(
result += text;
const int n = whisper_full_n_tokens(ctx, i);
for (int j = 0; j < n; ++j) {
const int n_tokens = whisper_full_n_tokens(ctx, i);
for (int j = 0; j < n_tokens; ++j) {
const auto token = whisper_full_get_token_data(ctx, i, j);
if(token.plog > 0.0f) exit(0);
logprob_min = std::min(logprob_min, token.plog);
logprob_sum += token.plog;
++n_tokens;
prob += token.p;
++prob_n;
}
}
if (prob_n > 0) {
prob /= prob_n;
}
const auto t_end = std::chrono::high_resolution_clock::now();
t_ms = std::chrono::duration_cast<std::chrono::milliseconds>(t_end - t_start).count();
return result;
}
static std::vector<std::string> read_allowed_commands(const std::string & fname) {
std::vector<std::string> read_allowed_commands(const std::string & fname) {
std::vector<std::string> allowed_commands;
std::ifstream ifs(fname);
@ -238,7 +188,7 @@ static std::vector<std::string> read_allowed_commands(const std::string & fname)
return allowed_commands;
}
static std::vector<std::string> get_words(const std::string &txt) {
std::vector<std::string> get_words(const std::string &txt) {
std::vector<std::string> words;
std::istringstream iss(txt);
@ -252,7 +202,7 @@ static std::vector<std::string> get_words(const std::string &txt) {
// command-list mode
// guide the transcription to match the most likely command from a provided list
static int process_command_list(struct whisper_context * ctx, audio_async &audio, const whisper_params &params) {
int process_command_list(struct whisper_context * ctx, audio_async &audio, const whisper_params &params) {
fprintf(stderr, "\n");
fprintf(stderr, "%s: guided mode\n", __func__);
@ -300,7 +250,7 @@ static int process_command_list(struct whisper_context * ctx, audio_async &audio
fprintf(stderr, " ]\n");
}
std::string k_prompt = "select one from the available words: ";
std::string k_prompt = "select one from the available words: ";
for (int i = 0; i < (int) allowed_commands.size(); ++i) {
if (i > 0) {
k_prompt += ", ";
@ -367,6 +317,7 @@ static int process_command_list(struct whisper_context * ctx, audio_async &audio
wparams.n_threads = params.n_threads;
wparams.audio_ctx = params.audio_ctx;
wparams.speed_up = params.speed_up;
wparams.prompt_tokens = k_tokens.data();
wparams.prompt_n_tokens = k_tokens.size();
@ -463,13 +414,11 @@ static int process_command_list(struct whisper_context * ctx, audio_async &audio
// always-prompt mode
// transcribe the voice into text after valid prompt
static int always_prompt_transcription(struct whisper_context * ctx, audio_async & audio, const whisper_params & params) {
int always_prompt_transcription(struct whisper_context * ctx, audio_async & audio, const whisper_params & params) {
bool is_running = true;
bool ask_prompt = true;
float logprob_min = 0.0f;
float logprob_sum = 0.0f;
int n_tokens = 0;
float prob = 0.0f;
std::vector<float> pcmf32_cur;
@ -507,7 +456,7 @@ static int always_prompt_transcription(struct whisper_context * ctx, audio_async
// detect the commands
audio.get(params.command_ms, pcmf32_cur);
const auto txt = ::trim(::transcribe(ctx, params, pcmf32_cur, "", logprob_min, logprob_sum, n_tokens, t_ms));
const auto txt = ::trim(::transcribe(ctx, params, pcmf32_cur, prob, t_ms));
const auto words = get_words(txt);
@ -543,27 +492,18 @@ static int always_prompt_transcription(struct whisper_context * ctx, audio_async
// general-purpose mode
// freely transcribe the voice into text
static int process_general_transcription(struct whisper_context * ctx, audio_async & audio, const whisper_params & params) {
int process_general_transcription(struct whisper_context * ctx, audio_async &audio, const whisper_params &params) {
bool is_running = true;
bool have_prompt = false;
bool ask_prompt = true;
float logprob_min0 = 0.0f;
float logprob_min = 0.0f;
float logprob_sum0 = 0.0f;
float logprob_sum = 0.0f;
int n_tokens0 = 0;
int n_tokens = 0;
float prob0 = 0.0f;
float prob = 0.0f;
std::vector<float> pcmf32_cur;
std::vector<float> pcmf32_prompt;
std::string k_prompt = "Ok Whisper, start listening for commands.";
if (!params.prompt.empty()) {
k_prompt = params.prompt;
}
const std::string k_prompt = "Ok Whisper, start listening for commands.";
fprintf(stderr, "\n");
fprintf(stderr, "%s: general-purpose mode\n", __func__);
@ -596,11 +536,9 @@ static int process_general_transcription(struct whisper_context * ctx, audio_asy
// wait for activation phrase
audio.get(params.prompt_ms, pcmf32_cur);
const auto txt = ::trim(::transcribe(ctx, params, pcmf32_cur, "prompt", logprob_min0, logprob_sum0, n_tokens0, t_ms));
const auto txt = ::trim(::transcribe(ctx, params, pcmf32_cur, prob0, t_ms));
const float p = 100.0f * std::exp(logprob_min0);
fprintf(stdout, "%s: Heard '%s%s%s', (t = %d ms, p = %.2f%%)\n", __func__, "\033[1m", txt.c_str(), "\033[0m", (int) t_ms, p);
fprintf(stdout, "%s: Heard '%s%s%s', (t = %d ms)\n", __func__, "\033[1m", txt.c_str(), "\033[0m", (int) t_ms);
const float sim = similarity(txt, k_prompt);
@ -621,30 +559,19 @@ static int process_general_transcription(struct whisper_context * ctx, audio_asy
// we have heard the activation phrase, now detect the commands
audio.get(params.command_ms, pcmf32_cur);
//printf("len prompt: %.4f\n", pcmf32_prompt.size() / (float) WHISPER_SAMPLE_RATE);
//printf("len command: %.4f\n", pcmf32_cur.size() / (float) WHISPER_SAMPLE_RATE);
// prepend 3 second of silence
pcmf32_cur.insert(pcmf32_cur.begin(), 3.0f*WHISPER_SAMPLE_RATE, 0.0f);
// prepend the prompt audio
pcmf32_cur.insert(pcmf32_cur.begin(), pcmf32_prompt.begin(), pcmf32_prompt.end());
const auto txt = ::trim(::transcribe(ctx, params, pcmf32_cur, "root", logprob_min, logprob_sum, n_tokens, t_ms));
const auto txt = ::trim(::transcribe(ctx, params, pcmf32_cur, prob, t_ms));
//const float p = 100.0f * std::exp((logprob - logprob0) / (n_tokens - n_tokens0));
const float p = 100.0f * std::exp(logprob_min);
prob = 100.0f*(prob - prob0);
//fprintf(stdout, "%s: heard '%s'\n", __func__, txt.c_str());
// find the prompt in the text
float best_sim = 0.0f;
size_t best_len = 0;
for (size_t n = 0.8*k_prompt.size(); n <= 1.2*k_prompt.size(); ++n) {
if (n >= txt.size()) {
break;
}
for (int n = 0.8*k_prompt.size(); n <= 1.2*k_prompt.size(); ++n) {
const auto prompt = txt.substr(0, n);
const float sim = similarity(prompt, k_prompt);
@ -657,16 +584,9 @@ static int process_general_transcription(struct whisper_context * ctx, audio_asy
}
}
fprintf(stdout, "%s: DEBUG: txt = '%s', prob = %.2f%%\n", __func__, txt.c_str(), p);
if (best_len == 0) {
fprintf(stdout, "%s: WARNING: command not recognized, try again\n", __func__);
} else {
// cut the prompt from the decoded text
const std::string command = ::trim(txt.substr(best_len));
fprintf(stdout, "%s: Command '%s%s%s', (t = %d ms)\n", __func__, "\033[1m", command.c_str(), "\033[0m", (int) t_ms);
}
const std::string command = ::trim(txt.substr(best_len));
fprintf(stdout, "%s: Command '%s%s%s', (t = %d ms)\n", __func__, "\033[1m", command.c_str(), "\033[0m", (int) t_ms);
fprintf(stdout, "\n");
}
@ -693,10 +613,8 @@ int main(int argc, char ** argv) {
// 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);
@ -736,36 +654,12 @@ int main(int argc, char ** argv) {
int ret_val = 0;
if (!params.grammar.empty()) {
auto & grammar = params.grammar_parsed;
if (is_file_exist(params.grammar.c_str())) {
// read grammar from file
std::ifstream ifs(params.grammar.c_str());
const std::string txt = std::string((std::istreambuf_iterator<char>(ifs)), std::istreambuf_iterator<char>());
grammar = grammar_parser::parse(txt.c_str());
} else {
// read grammar from string
grammar = grammar_parser::parse(params.grammar.c_str());
}
// will be empty (default) if there are parse errors
if (grammar.rules.empty()) {
ret_val = 1;
} else {
fprintf(stderr, "%s: grammar:\n", __func__);
grammar_parser::print_grammar(stderr, grammar);
fprintf(stderr, "\n");
}
}
if (ret_val == 0) {
if (!params.commands.empty()) {
ret_val = process_command_list(ctx, audio, params);
} else if (!params.prompt.empty() && params.grammar_parsed.rules.empty()) {
ret_val = always_prompt_transcription(ctx, audio, params);
} else {
ret_val = process_general_transcription(ctx, audio, params);
}
if (!params.commands.empty()) {
ret_val = process_command_list(ctx, audio, params);
} else if (!params.prompt.empty()) {
ret_val = always_prompt_transcription(ctx, audio, params);
} else {
ret_val = process_general_transcription(ctx, audio, params);
}
audio.pause();

View File

@ -9,11 +9,6 @@ static const std::map<std::string, enum ggml_ftype> GGML_FTYPE_MAP = {
{"q5_0", GGML_FTYPE_MOSTLY_Q5_0},
{"q5_1", GGML_FTYPE_MOSTLY_Q5_1},
{"q8_0", GGML_FTYPE_MOSTLY_Q8_0},
{"q2_k", GGML_FTYPE_MOSTLY_Q2_K},
{"q3_k", GGML_FTYPE_MOSTLY_Q3_K},
{"q4_k", GGML_FTYPE_MOSTLY_Q4_K},
{"q5_k", GGML_FTYPE_MOSTLY_Q5_K},
{"q6_k", GGML_FTYPE_MOSTLY_Q6_K},
};
void ggml_print_ftypes(FILE * fp) {
@ -53,28 +48,15 @@ bool ggml_common_quantize_0(
case GGML_FTYPE_MOSTLY_Q5_0: qtype = GGML_TYPE_Q5_0; break;
case GGML_FTYPE_MOSTLY_Q5_1: qtype = GGML_TYPE_Q5_1; break;
case GGML_FTYPE_MOSTLY_Q8_0: qtype = GGML_TYPE_Q8_0; break;
case GGML_FTYPE_MOSTLY_Q2_K: qtype = GGML_TYPE_Q2_K; break;
case GGML_FTYPE_MOSTLY_Q3_K: qtype = GGML_TYPE_Q3_K; break;
case GGML_FTYPE_MOSTLY_Q4_K: qtype = GGML_TYPE_Q4_K; break;
case GGML_FTYPE_MOSTLY_Q5_K: qtype = GGML_TYPE_Q5_K; break;
case GGML_FTYPE_MOSTLY_Q6_K: qtype = GGML_TYPE_Q6_K; break;
case GGML_FTYPE_UNKNOWN:
case GGML_FTYPE_ALL_F32:
case GGML_FTYPE_MOSTLY_F16:
case GGML_FTYPE_MOSTLY_Q4_1_SOME_F16:
case GGML_FTYPE_MOSTLY_IQ2_XXS:
case GGML_FTYPE_MOSTLY_IQ2_XS:
case GGML_FTYPE_MOSTLY_IQ2_S:
case GGML_FTYPE_MOSTLY_IQ3_XXS:
case GGML_FTYPE_MOSTLY_IQ3_S:
case GGML_FTYPE_MOSTLY_IQ1_S:
case GGML_FTYPE_MOSTLY_IQ4_NL:
case GGML_FTYPE_MOSTLY_IQ4_XS:
case GGML_FTYPE_MOSTLY_IQ1_M:
case GGML_FTYPE_MOSTLY_BF16:
case GGML_FTYPE_MOSTLY_Q4_0_4_4:
case GGML_FTYPE_MOSTLY_Q4_0_4_8:
case GGML_FTYPE_MOSTLY_Q4_0_8_8:
case GGML_FTYPE_MOSTLY_Q2_K:
case GGML_FTYPE_MOSTLY_Q3_K:
case GGML_FTYPE_MOSTLY_Q4_K:
case GGML_FTYPE_MOSTLY_Q5_K:
case GGML_FTYPE_MOSTLY_Q6_K:
{
fprintf(stderr, "%s: invalid model type %d\n", __func__, ftype);
return false;
@ -95,6 +77,8 @@ bool ggml_common_quantize_0(
std::vector<ggml_fp16_t> data_f16;
std::vector<float> data_f32;
std::vector<int64_t> hist_all(1 << 4, 0);
while (true) {
int32_t n_dims;
int32_t length;
@ -179,44 +163,41 @@ bool ggml_common_quantize_0(
work.resize(nelements); // for quantization
size_t cur_size = 0;
std::vector<int64_t> hist_cur(1 << 4, 0);
switch ((ggml_type) ttype) {
case GGML_TYPE_Q4_0:
case GGML_TYPE_Q4_1:
case GGML_TYPE_Q5_0:
case GGML_TYPE_Q5_1:
case GGML_TYPE_Q8_0:
case GGML_TYPE_Q2_K:
case GGML_TYPE_Q3_K:
case GGML_TYPE_Q4_K:
case GGML_TYPE_Q5_K:
case GGML_TYPE_Q6_K:
{
cur_size = ggml_quantize_chunk((ggml_type) ttype, data_f32.data(), work.data(), 0, nelements/ne[0], ne[0], nullptr);
cur_size = ggml_quantize_q4_0(data_f32.data(), work.data(), nelements, ne[0], hist_cur.data());
} break;
case GGML_TYPE_Q4_1:
{
cur_size = ggml_quantize_q4_1(data_f32.data(), work.data(), nelements, ne[0], hist_cur.data());
} break;
case GGML_TYPE_Q5_0:
{
cur_size = ggml_quantize_q5_0(data_f32.data(), work.data(), nelements, ne[0], hist_cur.data());
} break;
case GGML_TYPE_Q5_1:
{
cur_size = ggml_quantize_q5_1(data_f32.data(), work.data(), nelements, ne[0], hist_cur.data());
} break;
case GGML_TYPE_Q8_0:
{
cur_size = ggml_quantize_q8_0(data_f32.data(), work.data(), nelements, ne[0], hist_cur.data());
} break;
case GGML_TYPE_F32:
case GGML_TYPE_F16:
case GGML_TYPE_I8:
case GGML_TYPE_I16:
case GGML_TYPE_I32:
case GGML_TYPE_I64:
case GGML_TYPE_F64:
case GGML_TYPE_Q8_1:
case GGML_TYPE_Q2_K:
case GGML_TYPE_Q3_K:
case GGML_TYPE_Q4_K:
case GGML_TYPE_Q5_K:
case GGML_TYPE_Q6_K:
case GGML_TYPE_Q8_K:
case GGML_TYPE_IQ2_XXS:
case GGML_TYPE_IQ2_XS:
case GGML_TYPE_IQ2_S:
case GGML_TYPE_IQ3_XXS:
case GGML_TYPE_IQ3_S:
case GGML_TYPE_IQ1_S:
case GGML_TYPE_IQ4_NL:
case GGML_TYPE_IQ4_XS:
case GGML_TYPE_IQ1_M:
case GGML_TYPE_BF16:
case GGML_TYPE_Q4_0_4_4:
case GGML_TYPE_Q4_0_4_8:
case GGML_TYPE_Q4_0_8_8:
case GGML_TYPE_TQ1_0:
case GGML_TYPE_TQ2_0:
case GGML_TYPE_COUNT:
{
fprintf(stderr, "%s: unsupported quantization type %d (%s)\n", __func__, ttype, ggml_type_name((ggml_type) ttype));
@ -227,7 +208,15 @@ bool ggml_common_quantize_0(
fout.write(reinterpret_cast<char *>(work.data()), cur_size);
total_size_new += cur_size;
printf("size = %8.2f MB -> %8.2f MB\n", nelements * sizeof(float)/1024.0/1024.0, cur_size/1024.0/1024.0);
printf("size = %8.2f MB -> %8.2f MB | hist: ", nelements * sizeof(float)/1024.0/1024.0, cur_size/1024.0/1024.0);
for (int i = 0; i < (int) hist_cur.size(); ++i) {
hist_all[i] += hist_cur[i];
}
for (int i = 0; i < (int) hist_cur.size(); ++i) {
printf("%5.3f ", hist_cur[i] / (float)nelements);
}
printf("\n");
} else {
printf("size = %8.3f MB\n", data_u8.size()/1024.0/1024.0);
fout.write(reinterpret_cast<char *>(data_u8.data()), data_u8.size());
@ -240,5 +229,18 @@ bool ggml_common_quantize_0(
printf("%s: model size = %8.2f MB\n", __func__, total_size_org/1024.0/1024.0);
printf("%s: quant size = %8.2f MB | ftype = %d (%s)\n", __func__, total_size_new/1024.0/1024.0, ftype, ggml_type_name(qtype));
{
int64_t sum_all = 0;
for (int i = 0; i < (int) hist_all.size(); ++i) {
sum_all += hist_all[i];
}
printf("%s: hist: ", __func__);
for (int i = 0; i < (int) hist_all.size(); ++i) {
printf("%5.3f ", hist_all[i] / (float)sum_all);
}
printf("\n");
}
return true;
}

View File

@ -139,13 +139,10 @@ void audio_async::callback(uint8_t * stream, int len) {
return;
}
size_t n_samples = len / sizeof(float);
const size_t n_samples = len / sizeof(float);
if (n_samples > m_audio.size()) {
n_samples = m_audio.size();
stream += (len - (n_samples * sizeof(float)));
}
m_audio_new.resize(n_samples);
memcpy(m_audio_new.data(), stream, n_samples * sizeof(float));
//fprintf(stderr, "%s: %zu samples, pos %zu, len %zu\n", __func__, n_samples, m_audio_pos, m_audio_len);
@ -156,7 +153,7 @@ void audio_async::callback(uint8_t * stream, int len) {
const size_t n0 = m_audio.size() - m_audio_pos;
memcpy(&m_audio[m_audio_pos], stream, n0 * sizeof(float));
memcpy(&m_audio[0], stream + n0 * sizeof(float), (n_samples - n0) * sizeof(float));
memcpy(&m_audio[0], &stream[n0], (n_samples - n0) * sizeof(float));
m_audio_pos = (m_audio_pos + n_samples) % m_audio.size();
m_audio_len = m_audio.size();
@ -219,7 +216,7 @@ bool sdl_poll_events() {
case SDL_QUIT:
{
return false;
}
} break;
default:
break;
}

View File

@ -41,6 +41,7 @@ private:
std::mutex m_mutex;
std::vector<float> m_audio;
std::vector<float> m_audio_new;
size_t m_audio_pos = 0;
size_t m_audio_len = 0;
};

View File

@ -19,18 +19,8 @@
#pragma warning(disable: 4244 4267) // possible loss of data
#endif
#ifdef _WIN32
#include <fcntl.h>
#include <io.h>
#endif
#ifdef WHISPER_FFMPEG
// as implemented in ffmpeg_trancode.cpp only embedded in common lib if whisper built with ffmpeg support
extern bool ffmpeg_decode_audio(const std::string & ifname, std::vector<uint8_t> & wav_data);
#endif
// Function to check if the next argument exists
static std::string get_next_arg(int& i, int argc, char** argv, const std::string& flag, gpt_params& params) {
std::string get_next_arg(int& i, int argc, char** argv, const std::string& flag, gpt_params& params) {
if (i + 1 < argc && argv[i + 1][0] != '-') {
return argv[++i];
} else {
@ -147,6 +137,7 @@ std::string gpt_random_prompt(std::mt19937 & rng) {
case 7: return "He";
case 8: return "She";
case 9: return "They";
default: return "To";
}
return "The";
@ -345,7 +336,7 @@ std::vector<gpt_vocab::id> gpt_tokenize(const gpt_vocab & vocab, const std::stri
return tokens;
}
static std::vector<gpt_vocab::id> parse_tokens_from_string(const std::string& input, char delimiter) {
std::vector<gpt_vocab::id> parse_tokens_from_string(const std::string& input, char delimiter) {
std::vector<gpt_vocab::id> output;
std::stringstream ss(input);
std::string token;
@ -357,7 +348,7 @@ static std::vector<gpt_vocab::id> parse_tokens_from_string(const std::string& in
return output;
}
static std::map<std::string, std::vector<gpt_vocab::id>> extract_tests_from_file(const std::string & fpath_test){
std::map<std::string, std::vector<gpt_vocab::id>> extract_tests_from_file(const std::string & fpath_test){
if (fpath_test.empty()){
fprintf(stderr, "%s : No test file found.\n", __func__);
return std::map<std::string, std::vector<gpt_vocab::id>>();
@ -624,31 +615,12 @@ gpt_vocab::id gpt_sample_top_k_top_p_repeat(
}
bool is_wav_buffer(const std::string buf) {
// RIFF ref: https://en.wikipedia.org/wiki/Resource_Interchange_File_Format
// WAV ref: https://www.mmsp.ece.mcgill.ca/Documents/AudioFormats/WAVE/WAVE.html
if (buf.size() < 12 || buf.substr(0, 4) != "RIFF" || buf.substr(8, 4) != "WAVE") {
return false;
}
uint32_t chunk_size = *reinterpret_cast<const uint32_t*>(buf.data() + 4);
if (chunk_size + 8 != buf.size()) {
return false;
}
return true;
}
bool read_wav(const std::string & fname, std::vector<float>& pcmf32, std::vector<std::vector<float>>& pcmf32s, bool stereo) {
drwav wav;
std::vector<uint8_t> wav_data; // used for pipe input from stdin or ffmpeg decoding output
std::vector<uint8_t> wav_data; // used for pipe input from stdin
if (fname == "-") {
{
#ifdef _WIN32
_setmode(_fileno(stdin), _O_BINARY);
#endif
uint8_t buf[1024];
while (true)
{
@ -667,49 +639,28 @@ bool read_wav(const std::string & fname, std::vector<float>& pcmf32, std::vector
fprintf(stderr, "%s: read %zu bytes from stdin\n", __func__, wav_data.size());
}
else if (is_wav_buffer(fname)) {
if (drwav_init_memory(&wav, fname.c_str(), fname.size(), nullptr) == false) {
fprintf(stderr, "error: failed to open WAV file from fname buffer\n");
return false;
}
}
else if (drwav_init_file(&wav, fname.c_str(), nullptr) == false) {
#if defined(WHISPER_FFMPEG)
if (ffmpeg_decode_audio(fname, wav_data) != 0) {
fprintf(stderr, "error: failed to ffmpeg decode '%s' \n", fname.c_str());
return false;
}
if (drwav_init_memory(&wav, wav_data.data(), wav_data.size(), nullptr) == false) {
fprintf(stderr, "error: failed to read wav data as wav \n");
return false;
}
#else
fprintf(stderr, "error: failed to open '%s' as WAV file\n", fname.c_str());
return false;
#endif
}
if (wav.channels != 1 && wav.channels != 2) {
fprintf(stderr, "%s: WAV file '%s' must be mono or stereo\n", __func__, fname.c_str());
drwav_uninit(&wav);
return false;
}
if (stereo && wav.channels != 2) {
fprintf(stderr, "%s: WAV file '%s' must be stereo for diarization\n", __func__, fname.c_str());
drwav_uninit(&wav);
return false;
}
if (wav.sampleRate != COMMON_SAMPLE_RATE) {
fprintf(stderr, "%s: WAV file '%s' must be %i kHz\n", __func__, fname.c_str(), COMMON_SAMPLE_RATE/1000);
drwav_uninit(&wav);
return false;
}
if (wav.bitsPerSample != 16) {
fprintf(stderr, "%s: WAV file '%s' must be 16-bit\n", __func__, fname.c_str());
drwav_uninit(&wav);
return false;
}
@ -864,48 +815,3 @@ void sam_print_usage(int /*argc*/, char ** argv, const sam_params & params) {
fprintf(stderr, " output file (default: %s)\n", params.fname_out.c_str());
fprintf(stderr, "\n");
}
// 500 -> 00:05.000
// 6000 -> 01:00.000
std::string to_timestamp(int64_t t, bool comma) {
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, int whisper_sample_rate) {
return std::max(0, std::min((int) n_samples - 1, (int) ((t*whisper_sample_rate)/100)));
}
bool is_file_exist(const char *fileName)
{
std::ifstream infile(fileName);
return infile.good();
}
bool speak_with_file(const std::string & command, const std::string & text, const std::string & path, int voice_id)
{
std::ofstream speak_file(path.c_str());
if (speak_file.fail()) {
fprintf(stderr, "%s: failed to open speak_file\n", __func__);
return false;
} else {
speak_file.write(text.c_str(), text.size());
speak_file.close();
int ret = system((command + " " + std::to_string(voice_id) + " " + path).c_str());
if (ret != 0) {
fprintf(stderr, "%s: failed to speak\n", __func__);
return false;
}
}
return true;
}

View File

@ -9,7 +9,6 @@
#include <thread>
#include <ctime>
#include <fstream>
#include <sstream>
#define COMMON_SAMPLE_RATE 16000
@ -22,7 +21,7 @@ struct gpt_params {
int32_t n_threads = std::min(4, (int32_t) std::thread::hardware_concurrency());
int32_t n_predict = 200; // new tokens to predict
int32_t n_parallel = 1; // number of parallel streams
int32_t n_batch = 32; // batch size for prompt processing
int32_t n_batch = 8; // batch size for prompt processing
int32_t n_ctx = 2048; // context size (this is the KV cache max size)
int32_t n_gpu_layers = 0; // number of layers to offlload to the GPU
@ -136,11 +135,7 @@ gpt_vocab::id gpt_sample_top_k_top_p_repeat(
// Audio utils
//
// Check if a buffer is a WAV audio file
bool is_wav_buffer(const std::string buf);
// Read WAV audio file and store the PCM data into pcmf32
// fname can be a buffer of WAV data instead of a filename
// The sample rate of the audio must be equal to COMMON_SAMPLE_RATE
// If stereo flag is set and the audio has 2 channels, the pcmf32s will contain 2 channel PCM
bool read_wav(
@ -186,7 +181,7 @@ private:
// It is assumed that PCM data is normalized to a range from -1 to 1
bool write_audio(const float * data, size_t length) {
for (size_t i = 0; i < length; ++i) {
const int16_t intSample = int16_t(data[i] * 32767);
const auto intSample = static_cast<const int16_t>(data[i] * 32767);
file.write(reinterpret_cast<const char *>(&intSample), sizeof(int16_t));
dataSize += sizeof(int16_t);
}
@ -282,62 +277,3 @@ struct sam_params {
bool sam_params_parse(int argc, char ** argv, sam_params & params);
void sam_print_usage(int argc, char ** argv, const sam_params & params);
//
// Terminal utils
//
#define SQR(X) ((X) * (X))
#define UNCUBE(x) x < 48 ? 0 : x < 115 ? 1 : (x - 35) / 40
/**
* Quantizes 24-bit RGB to xterm256 code range [16,256).
*/
static int rgb2xterm256(int r, int g, int b) {
unsigned char cube[] = {0, 0137, 0207, 0257, 0327, 0377};
int av, ir, ig, ib, il, qr, qg, qb, ql;
av = r * .299 + g * .587 + b * .114 + .5;
ql = (il = av > 238 ? 23 : (av - 3) / 10) * 10 + 8;
qr = cube[(ir = UNCUBE(r))];
qg = cube[(ig = UNCUBE(g))];
qb = cube[(ib = UNCUBE(b))];
if (SQR(qr - r) + SQR(qg - g) + SQR(qb - b) <=
SQR(ql - r) + SQR(ql - g) + SQR(ql - b))
return ir * 36 + ig * 6 + ib + 020;
return il + 0350;
}
static std::string set_xterm256_foreground(int r, int g, int b) {
int x = rgb2xterm256(r, g, b);
std::ostringstream oss;
oss << "\033[38;5;" << x << "m";
return oss.str();
}
// Lowest is red, middle is yellow, highest is green. Color scheme from
// Paul Tol; it is colorblind friendly https://personal.sron.nl/~pault/
const std::vector<std::string> k_colors = {
set_xterm256_foreground(220, 5, 12),
set_xterm256_foreground(232, 96, 28),
set_xterm256_foreground(241, 147, 45),
set_xterm256_foreground(246, 193, 65),
set_xterm256_foreground(247, 240, 86),
set_xterm256_foreground(144, 201, 135),
set_xterm256_foreground( 78, 178, 101),
};
//
// Other utils
//
// convert timestamp to string, 6000 -> 01:00.000
std::string to_timestamp(int64_t t, bool comma = false);
// given a timestamp get the sample
int timestamp_to_sample(int64_t t, int n_samples, int whisper_sample_rate);
// check if file exists using ifstream
bool is_file_exist(const char *fileName);
// write text to file, and call system("command voice_id file")
bool speak_with_file(const std::string & command, const std::string & text, const std::string & path, int voice_id);

File diff suppressed because it is too large Load Diff

View File

@ -1,348 +0,0 @@
/* SPDX-License-Identifier: GPL-2.0 */
/*
* transcode.c - convert audio file to WAVE
*
* Copyright (C) 2019 Andrew Clayton <andrew@digital-domain.net>
* Copyright (C) 2024 William Tambellini <william.tambellini@gmail.com>
*/
// Just for conveninent C++ API
#include <vector>
#include <string>
// C
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#include <stdbool.h>
#include <stdint.h>
#include <sys/types.h>
#include <sys/stat.h>
#include <fcntl.h>
#include <unistd.h>
#include <sys/mman.h>
extern "C" {
#include <libavutil/opt.h>
#include <libavcodec/avcodec.h>
#include <libavformat/avformat.h>
#include <libswresample/swresample.h>
}
typedef uint64_t u64;
typedef int64_t s64;
typedef uint32_t u32;
typedef int32_t s32;
typedef uint16_t u16;
typedef int16_t s16;
typedef uint8_t u8;
typedef int8_t s8;
#define WAVE_SAMPLE_RATE 16000
#define AVIO_CTX_BUF_SZ 4096
static const char* ffmpegLog = getenv("FFMPEG_LOG");
// Todo: add __FILE__ __LINE__
#define LOG(...) \
do { if (ffmpegLog) fprintf(stderr, __VA_ARGS__); } while(0) // C99
/*
* WAVE file header based on definition from
* https://gist.github.com/Jon-Schneider/8b7c53d27a7a13346a643dac9c19d34f
*
* We must ensure this structure doesn't have any holes or
* padding so we can just map it straight to the WAVE data.
*/
struct wave_hdr {
/* RIFF Header: "RIFF" */
char riff_header[4];
/* size of audio data + sizeof(struct wave_hdr) - 8 */
int wav_size;
/* "WAVE" */
char wav_header[4];
/* Format Header */
/* "fmt " (includes trailing space) */
char fmt_header[4];
/* Should be 16 for PCM */
int fmt_chunk_size;
/* Should be 1 for PCM. 3 for IEEE Float */
s16 audio_format;
s16 num_channels;
int sample_rate;
/*
* Number of bytes per second
* sample_rate * num_channels * bit_depth/8
*/
int byte_rate;
/* num_channels * bytes per sample */
s16 sample_alignment;
/* bits per sample */
s16 bit_depth;
/* Data Header */
/* "data" */
char data_header[4];
/*
* size of audio
* number of samples * num_channels * bit_depth/8
*/
int data_bytes;
} __attribute__((__packed__));
struct audio_buffer {
u8 *ptr;
int size; /* size left in the buffer */
};
static void set_wave_hdr(wave_hdr& wh, size_t size) {
memcpy(&wh.riff_header, "RIFF", 4);
wh.wav_size = size + sizeof(struct wave_hdr) - 8;
memcpy(&wh.wav_header, "WAVE", 4);
memcpy(&wh.fmt_header, "fmt ", 4);
wh.fmt_chunk_size = 16;
wh.audio_format = 1;
wh.num_channels = 1;
wh.sample_rate = WAVE_SAMPLE_RATE;
wh.sample_alignment = 2;
wh.bit_depth = 16;
wh.byte_rate = wh.sample_rate * wh.sample_alignment;
memcpy(&wh.data_header, "data", 4);
wh.data_bytes = size;
}
static void write_wave_hdr(int fd, size_t size) {
struct wave_hdr wh;
set_wave_hdr(wh, size);
write(fd, &wh, sizeof(struct wave_hdr));
}
static int map_file(int fd, u8 **ptr, size_t *size)
{
struct stat sb;
fstat(fd, &sb);
*size = sb.st_size;
*ptr = (u8*)mmap(NULL, *size, PROT_READ|PROT_WRITE, MAP_PRIVATE, fd, 0);
if (*ptr == MAP_FAILED) {
perror("mmap");
return -1;
}
return 0;
}
static int read_packet(void *opaque, u8 *buf, int buf_size)
{
struct audio_buffer *audio_buf = (audio_buffer*)opaque;
buf_size = FFMIN(buf_size, audio_buf->size);
/* copy internal buffer data to buf */
memcpy(buf, audio_buf->ptr, buf_size);
audio_buf->ptr += buf_size;
audio_buf->size -= buf_size;
return buf_size;
}
static void convert_frame(struct SwrContext *swr, AVCodecContext *codec,
AVFrame *frame, s16 **data, int *size, bool flush)
{
int nr_samples;
s64 delay;
u8 *buffer;
delay = swr_get_delay(swr, codec->sample_rate);
nr_samples = av_rescale_rnd(delay + frame->nb_samples,
WAVE_SAMPLE_RATE, codec->sample_rate,
AV_ROUND_UP);
av_samples_alloc(&buffer, NULL, 1, nr_samples, AV_SAMPLE_FMT_S16, 0);
/*
* !flush is used to check if we are flushing any remaining
* conversion buffers...
*/
nr_samples = swr_convert(swr, &buffer, nr_samples,
!flush ? (const u8 **)frame->data : NULL,
!flush ? frame->nb_samples : 0);
*data = (s16*)realloc(*data, (*size + nr_samples) * sizeof(s16));
memcpy(*data + *size, buffer, nr_samples * sizeof(s16));
*size += nr_samples;
av_freep(&buffer);
}
static bool is_audio_stream(const AVStream *stream)
{
if (stream->codecpar->codec_type == AVMEDIA_TYPE_AUDIO)
return true;
return false;
}
// Return non zero on error, 0 on success
// audio_buffer: input memory
// data: decoded output audio data (wav file)
// size: size of output data
static int decode_audio(struct audio_buffer *audio_buf, s16 **data, int *size)
{
LOG("decode_audio: input size: %d\n", audio_buf->size);
AVFormatContext *fmt_ctx;
AVIOContext *avio_ctx;
AVStream *stream;
AVCodecContext *codec;
AVPacket packet;
AVFrame *frame;
struct SwrContext *swr;
u8 *avio_ctx_buffer;
unsigned int i;
int stream_index = -1;
int err;
const size_t errbuffsize = 1024;
char errbuff[errbuffsize];
fmt_ctx = avformat_alloc_context();
avio_ctx_buffer = (u8*)av_malloc(AVIO_CTX_BUF_SZ);
LOG("Creating an avio context: AVIO_CTX_BUF_SZ=%d\n", AVIO_CTX_BUF_SZ);
avio_ctx = avio_alloc_context(avio_ctx_buffer, AVIO_CTX_BUF_SZ, 0, audio_buf, &read_packet, NULL, NULL);
fmt_ctx->pb = avio_ctx;
// open the input stream and read header
err = avformat_open_input(&fmt_ctx, NULL, NULL, NULL);
if (err) {
LOG("Could not read audio buffer: %d: %s\n", err, av_make_error_string(errbuff, errbuffsize, err));
return err;
}
err = avformat_find_stream_info(fmt_ctx, NULL);
if (err < 0) {
LOG("Could not retrieve stream info from audio buffer: %d\n", err);
return err;
}
for (i = 0; i < fmt_ctx->nb_streams; i++) {
if (is_audio_stream(fmt_ctx->streams[i])) {
stream_index = i;
break;
}
}
if (stream_index == -1) {
LOG("Could not retrieve audio stream from buffer\n");
return -1;
}
stream = fmt_ctx->streams[stream_index];
codec = avcodec_alloc_context3(
avcodec_find_decoder(stream->codecpar->codec_id));
avcodec_parameters_to_context(codec, stream->codecpar);
err = avcodec_open2(codec, avcodec_find_decoder(codec->codec_id),
NULL);
if (err) {
LOG("Failed to open decoder for stream #%d in audio buffer\n", stream_index);
return err;
}
/* prepare resampler */
swr = swr_alloc();
av_opt_set_int(swr, "in_channel_count", codec->channels, 0);
av_opt_set_int(swr, "out_channel_count", 1, 0);
av_opt_set_int(swr, "in_channel_layout", codec->channel_layout, 0);
av_opt_set_int(swr, "out_channel_layout", AV_CH_LAYOUT_MONO, 0);
av_opt_set_int(swr, "in_sample_rate", codec->sample_rate, 0);
av_opt_set_int(swr, "out_sample_rate", WAVE_SAMPLE_RATE, 0);
av_opt_set_sample_fmt(swr, "in_sample_fmt", codec->sample_fmt, 0);
av_opt_set_sample_fmt(swr, "out_sample_fmt", AV_SAMPLE_FMT_S16, 0);
swr_init(swr);
if (!swr_is_initialized(swr)) {
LOG("Resampler has not been properly initialized\n");
return -1;
}
av_init_packet(&packet);
frame = av_frame_alloc();
if (!frame) {
LOG("Error allocating the frame\n");
return -1;
}
/* iterate through frames */
*data = NULL;
*size = 0;
while (av_read_frame(fmt_ctx, &packet) >= 0) {
avcodec_send_packet(codec, &packet);
err = avcodec_receive_frame(codec, frame);
if (err == AVERROR(EAGAIN))
continue;
convert_frame(swr, codec, frame, data, size, false);
}
/* Flush any remaining conversion buffers... */
convert_frame(swr, codec, frame, data, size, true);
av_frame_free(&frame);
swr_free(&swr);
//avio_context_free(); // todo?
avcodec_close(codec);
avformat_close_input(&fmt_ctx);
avformat_free_context(fmt_ctx);
if (avio_ctx) {
av_freep(&avio_ctx->buffer);
av_freep(&avio_ctx);
}
return 0;
}
// in mem decoding/conversion/resampling:
// ifname: input file path
// owav_data: in mem wav file. Can be forwarded as it to whisper/drwav
// return 0 on success
int ffmpeg_decode_audio(const std::string &ifname, std::vector<uint8_t>& owav_data) {
LOG("ffmpeg_decode_audio: %s\n", ifname.c_str());
int ifd = open(ifname.c_str(), O_RDONLY);
if (ifd == -1) {
fprintf(stderr, "Couldn't open input file %s\n", ifname.c_str());
return -1;
}
u8 *ibuf = NULL;
size_t ibuf_size;
int err = map_file(ifd, &ibuf, &ibuf_size);
if (err) {
LOG("Couldn't map input file %s\n", ifname.c_str());
return err;
}
LOG("Mapped input file: %s size: %d\n", ibuf, (int) ibuf_size);
struct audio_buffer inaudio_buf;
inaudio_buf.ptr = ibuf;
inaudio_buf.size = ibuf_size;
s16 *odata=NULL;
int osize=0;
err = decode_audio(&inaudio_buf, &odata, &osize);
LOG("decode_audio returned %d \n", err);
if (err != 0) {
LOG("decode_audio failed\n");
return err;
}
LOG("decode_audio output size: %d\n", osize);
wave_hdr wh;
const size_t outdatasize = osize * sizeof(s16);
set_wave_hdr(wh, outdatasize);
owav_data.resize(sizeof(wave_hdr) + outdatasize);
// header:
memcpy(owav_data.data(), &wh, sizeof(wave_hdr));
// the data:
memcpy(owav_data.data() + sizeof(wave_hdr), odata, osize* sizeof(s16));
return 0;
}

View File

@ -1,423 +0,0 @@
#include "grammar-parser.h"
#include <cstdint>
#include <cwchar>
#include <string>
#include <utility>
#include <stdexcept>
#include <exception>
namespace grammar_parser {
// NOTE: assumes valid utf8 (but checks for overrun)
// copied from whisper.cpp
static std::pair<uint32_t, const char *> decode_utf8(const char * src) {
static const int lookup[] = { 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 3, 4 };
uint8_t first_byte = static_cast<uint8_t>(*src);
uint8_t highbits = first_byte >> 4;
int len = lookup[highbits];
uint8_t mask = (1 << (8 - len)) - 1;
uint32_t value = first_byte & mask;
const char * end = src + len; // may overrun!
const char * pos = src + 1;
for ( ; pos < end && *pos; pos++) {
value = (value << 6) + (static_cast<uint8_t>(*pos) & 0x3F);
}
return std::make_pair(value, pos);
}
static uint32_t get_symbol_id(parse_state & state, const char * src, size_t len) {
uint32_t next_id = static_cast<uint32_t>(state.symbol_ids.size());
auto result = state.symbol_ids.insert(std::make_pair(std::string(src, len), next_id));
return result.first->second;
}
static uint32_t generate_symbol_id(parse_state & state, const std::string & base_name) {
uint32_t next_id = static_cast<uint32_t>(state.symbol_ids.size());
state.symbol_ids[base_name + '_' + std::to_string(next_id)] = next_id;
return next_id;
}
static void add_rule(
parse_state & state,
uint32_t rule_id,
const std::vector<whisper_grammar_element> & rule) {
if (state.rules.size() <= rule_id) {
state.rules.resize(rule_id + 1);
}
state.rules[rule_id] = rule;
}
static bool is_word_char(char c) {
return ('a' <= c && c <= 'z') || ('A' <= c && c <= 'Z') || c == '-' || ('0' <= c && c <= '9');
}
static std::pair<uint32_t, const char *> parse_hex(const char * src, int size) {
const char * pos = src;
const char * end = src + size;
uint32_t value = 0;
for ( ; pos < end && *pos; pos++) {
value <<= 4;
char c = *pos;
if ('a' <= c && c <= 'f') {
value += c - 'a' + 10;
} else if ('A' <= c && c <= 'F') {
value += c - 'A' + 10;
} else if ('0' <= c && c <= '9') {
value += c - '0';
} else {
break;
}
}
if (pos != end) {
throw std::runtime_error("expecting " + std::to_string(size) + " hex chars at " + src);
}
return std::make_pair(value, pos);
}
static const char * parse_space(const char * src, bool newline_ok) {
const char * pos = src;
while (*pos == ' ' || *pos == '\t' || *pos == '#' ||
(newline_ok && (*pos == '\r' || *pos == '\n'))) {
if (*pos == '#') {
while (*pos && *pos != '\r' && *pos != '\n') {
pos++;
}
} else {
pos++;
}
}
return pos;
}
static const char * parse_name(const char * src) {
const char * pos = src;
while (is_word_char(*pos)) {
pos++;
}
if (pos == src) {
throw std::runtime_error(std::string("expecting name at ") + src);
}
return pos;
}
static std::pair<uint32_t, const char *> parse_char(const char * src) {
if (*src == '\\') {
switch (src[1]) {
case 'x': return parse_hex(src + 2, 2);
case 'u': return parse_hex(src + 2, 4);
case 'U': return parse_hex(src + 2, 8);
case 't': return std::make_pair('\t', src + 2);
case 'r': return std::make_pair('\r', src + 2);
case 'n': return std::make_pair('\n', src + 2);
case '\\':
case '"':
case '[':
case ']':
return std::make_pair(src[1], src + 2);
default:
throw std::runtime_error(std::string("unknown escape at ") + src);
}
} else if (*src) {
return decode_utf8(src);
}
throw std::runtime_error("unexpected end of input");
}
static const char * parse_alternates(
parse_state & state,
const char * src,
const std::string & rule_name,
uint32_t rule_id,
bool is_nested);
static const char * parse_sequence(
parse_state & state,
const char * src,
const std::string & rule_name,
std::vector<whisper_grammar_element> & out_elements,
bool is_nested) {
size_t last_sym_start = out_elements.size();
const char * pos = src;
while (*pos) {
if (*pos == '"') { // literal string
pos++;
last_sym_start = out_elements.size();
while (*pos != '"') {
auto char_pair = parse_char(pos);
pos = char_pair.second;
out_elements.push_back({WHISPER_GRETYPE_CHAR, char_pair.first});
}
pos = parse_space(pos + 1, is_nested);
} else if (*pos == '[') { // char range(s)
pos++;
enum whisper_gretype start_type = WHISPER_GRETYPE_CHAR;
if (*pos == '^') {
pos++;
start_type = WHISPER_GRETYPE_CHAR_NOT;
}
last_sym_start = out_elements.size();
while (*pos != ']') {
auto char_pair = parse_char(pos);
pos = char_pair.second;
enum whisper_gretype type = last_sym_start < out_elements.size()
? WHISPER_GRETYPE_CHAR_ALT
: start_type;
out_elements.push_back({type, char_pair.first});
if (pos[0] == '-' && pos[1] != ']') {
auto endchar_pair = parse_char(pos + 1);
pos = endchar_pair.second;
out_elements.push_back({WHISPER_GRETYPE_CHAR_RNG_UPPER, endchar_pair.first});
}
}
pos = parse_space(pos + 1, is_nested);
} else if (is_word_char(*pos)) { // rule reference
const char * name_end = parse_name(pos);
uint32_t ref_rule_id = get_symbol_id(state, pos, name_end - pos);
pos = parse_space(name_end, is_nested);
last_sym_start = out_elements.size();
out_elements.push_back({WHISPER_GRETYPE_RULE_REF, ref_rule_id});
} else if (*pos == '(') { // grouping
// parse nested alternates into synthesized rule
pos = parse_space(pos + 1, true);
uint32_t sub_rule_id = generate_symbol_id(state, rule_name);
pos = parse_alternates(state, pos, rule_name, sub_rule_id, true);
last_sym_start = out_elements.size();
// output reference to synthesized rule
out_elements.push_back({WHISPER_GRETYPE_RULE_REF, sub_rule_id});
if (*pos != ')') {
throw std::runtime_error(std::string("expecting ')' at ") + pos);
}
pos = parse_space(pos + 1, is_nested);
} else if (*pos == '*' || *pos == '+' || *pos == '?') { // repetition operator
if (last_sym_start == out_elements.size()) {
throw std::runtime_error(std::string("expecting preceding item to */+/? at ") + pos);
}
// apply transformation to previous symbol (last_sym_start to end) according to
// rewrite rules:
// S* --> S' ::= S S' |
// S+ --> S' ::= S S' | S
// S? --> S' ::= S |
uint32_t sub_rule_id = generate_symbol_id(state, rule_name);
std::vector<whisper_grammar_element> sub_rule;
// add preceding symbol to generated rule
sub_rule.insert(
sub_rule.end(), out_elements.begin() + last_sym_start, out_elements.end());
if (*pos == '*' || *pos == '+') {
// cause generated rule to recurse
sub_rule.push_back({WHISPER_GRETYPE_RULE_REF, sub_rule_id});
}
// mark start of alternate def
sub_rule.push_back({WHISPER_GRETYPE_ALT, 0});
if (*pos == '+') {
// add preceding symbol as alternate only for '+' (otherwise empty)
sub_rule.insert(
sub_rule.end(), out_elements.begin() + last_sym_start, out_elements.end());
}
sub_rule.push_back({WHISPER_GRETYPE_END, 0});
add_rule(state, sub_rule_id, sub_rule);
// in original rule, replace previous symbol with reference to generated rule
out_elements.resize(last_sym_start);
out_elements.push_back({WHISPER_GRETYPE_RULE_REF, sub_rule_id});
pos = parse_space(pos + 1, is_nested);
} else {
break;
}
}
return pos;
}
static const char * parse_alternates(
parse_state & state,
const char * src,
const std::string & rule_name,
uint32_t rule_id,
bool is_nested) {
std::vector<whisper_grammar_element> rule;
const char * pos = parse_sequence(state, src, rule_name, rule, is_nested);
while (*pos == '|') {
rule.push_back({WHISPER_GRETYPE_ALT, 0});
pos = parse_space(pos + 1, true);
pos = parse_sequence(state, pos, rule_name, rule, is_nested);
}
rule.push_back({WHISPER_GRETYPE_END, 0});
add_rule(state, rule_id, rule);
return pos;
}
static const char * parse_rule(parse_state & state, const char * src) {
const char * name_end = parse_name(src);
const char * pos = parse_space(name_end, false);
size_t name_len = name_end - src;
uint32_t rule_id = get_symbol_id(state, src, name_len);
const std::string name(src, name_len);
if (!(pos[0] == ':' && pos[1] == ':' && pos[2] == '=')) {
throw std::runtime_error(std::string("expecting ::= at ") + pos);
}
pos = parse_space(pos + 3, true);
pos = parse_alternates(state, pos, name, rule_id, false);
if (*pos == '\r') {
pos += pos[1] == '\n' ? 2 : 1;
} else if (*pos == '\n') {
pos++;
} else if (*pos) {
throw std::runtime_error(std::string("expecting newline or end at ") + pos);
}
return parse_space(pos, true);
}
parse_state parse(const char * src) {
try {
parse_state state;
const char * pos = parse_space(src, true);
while (*pos) {
pos = parse_rule(state, pos);
}
return state;
} catch (const std::exception & err) {
fprintf(stderr, "%s: error parsing grammar: %s\n", __func__, err.what());
return parse_state();
}
}
static void print_grammar_char(FILE * file, uint32_t c) {
if (0x20 <= c && c <= 0x7f) {
fprintf(file, "%c", static_cast<char>(c));
} else {
// cop out of encoding UTF-8
fprintf(file, "<U+%04X>", c);
}
}
static bool is_char_element(whisper_grammar_element elem) {
switch (elem.type) {
case WHISPER_GRETYPE_CHAR: return true;
case WHISPER_GRETYPE_CHAR_NOT: return true;
case WHISPER_GRETYPE_CHAR_ALT: return true;
case WHISPER_GRETYPE_CHAR_RNG_UPPER: return true;
default: return false;
}
}
static void print_rule_binary(FILE * file, const std::vector<whisper_grammar_element> & rule) {
for (auto elem : rule) {
switch (elem.type) {
case WHISPER_GRETYPE_END: fprintf(file, "END"); break;
case WHISPER_GRETYPE_ALT: fprintf(file, "ALT"); break;
case WHISPER_GRETYPE_RULE_REF: fprintf(file, "RULE_REF"); break;
case WHISPER_GRETYPE_CHAR: fprintf(file, "CHAR"); break;
case WHISPER_GRETYPE_CHAR_NOT: fprintf(file, "CHAR_NOT"); break;
case WHISPER_GRETYPE_CHAR_RNG_UPPER: fprintf(file, "CHAR_RNG_UPPER"); break;
case WHISPER_GRETYPE_CHAR_ALT: fprintf(file, "CHAR_ALT"); break;
}
switch (elem.type) {
case WHISPER_GRETYPE_END:
case WHISPER_GRETYPE_ALT:
case WHISPER_GRETYPE_RULE_REF:
fprintf(file, "(%u) ", elem.value);
break;
case WHISPER_GRETYPE_CHAR:
case WHISPER_GRETYPE_CHAR_NOT:
case WHISPER_GRETYPE_CHAR_RNG_UPPER:
case WHISPER_GRETYPE_CHAR_ALT:
fprintf(file, "(\"");
print_grammar_char(file, elem.value);
fprintf(file, "\") ");
break;
}
}
fprintf(file, "\n");
}
static void print_rule(
FILE * file,
uint32_t rule_id,
const std::vector<whisper_grammar_element> & rule,
const std::map<uint32_t, std::string> & symbol_id_names) {
if (rule.empty() || rule.back().type != WHISPER_GRETYPE_END) {
throw std::runtime_error(
"malformed rule, does not end with WHISPER_GRETYPE_END: " + std::to_string(rule_id));
}
fprintf(file, "%s ::= ", symbol_id_names.at(rule_id).c_str());
for (size_t i = 0, end = rule.size() - 1; i < end; i++) {
whisper_grammar_element elem = rule[i];
switch (elem.type) {
case WHISPER_GRETYPE_END:
throw std::runtime_error(
"unexpected end of rule: " + std::to_string(rule_id) + "," +
std::to_string(i));
case WHISPER_GRETYPE_ALT:
fprintf(file, "| ");
break;
case WHISPER_GRETYPE_RULE_REF:
fprintf(file, "%s ", symbol_id_names.at(elem.value).c_str());
break;
case WHISPER_GRETYPE_CHAR:
fprintf(file, "[");
print_grammar_char(file, elem.value);
break;
case WHISPER_GRETYPE_CHAR_NOT:
fprintf(file, "[^");
print_grammar_char(file, elem.value);
break;
case WHISPER_GRETYPE_CHAR_RNG_UPPER:
if (i == 0 || !is_char_element(rule[i - 1])) {
throw std::runtime_error(
"WHISPER_GRETYPE_CHAR_RNG_UPPER without preceding char: " +
std::to_string(rule_id) + "," + std::to_string(i));
}
fprintf(file, "-");
print_grammar_char(file, elem.value);
break;
case WHISPER_GRETYPE_CHAR_ALT:
if (i == 0 || !is_char_element(rule[i - 1])) {
throw std::runtime_error(
"WHISPER_GRETYPE_CHAR_ALT without preceding char: " +
std::to_string(rule_id) + "," + std::to_string(i));
}
print_grammar_char(file, elem.value);
break;
}
if (is_char_element(elem)) {
switch (rule[i + 1].type) {
case WHISPER_GRETYPE_CHAR_ALT:
case WHISPER_GRETYPE_CHAR_RNG_UPPER:
break;
default:
fprintf(file, "] ");
}
}
}
fprintf(file, "\n");
}
void print_grammar(FILE * file, const parse_state & state) {
try {
std::map<uint32_t, std::string> symbol_id_names;
for (auto kv : state.symbol_ids) {
symbol_id_names[kv.second] = kv.first;
}
for (size_t i = 0, end = state.rules.size(); i < end; i++) {
// fprintf(file, "%zu: ", i);
// print_rule_binary(file, state.rules[i]);
print_rule(file, uint32_t(i), state.rules[i], symbol_id_names);
// fprintf(file, "\n");
}
} catch (const std::exception & err) {
fprintf(stderr, "\n%s: error printing grammar: %s\n", __func__, err.what());
}
}
std::vector<const whisper_grammar_element *> parse_state::c_rules() const {
std::vector<const whisper_grammar_element *> ret;
for (const auto & rule : rules) {
ret.push_back(rule.data());
}
return ret;
}
}

View File

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

View File

@ -22,7 +22,6 @@ var printTextarea = (function() {
async function clearCache() {
if (confirm('Are you sure you want to clear the cache?\nAll the models will be downloaded again.')) {
indexedDB.deleteDatabase(dbName);
location.reload();
}
}
@ -34,6 +33,9 @@ async function fetchRemote(url, cbProgress, cbPrint) {
url,
{
method: 'GET',
headers: {
'Content-Type': 'application/octet-stream',
},
}
);

View File

@ -48,7 +48,7 @@ if [ -n "$3" ]; then
fi
# Whisper models
models=( "tiny.en" "tiny" "base.en" "base" "small.en" "small" "medium.en" "medium" "large-v1" "large-v2" "large-v3" "large-v3-turbo" )
models=( "tiny.en" "tiny" "base.en" "base" "small.en" "small" "medium.en" "medium" "large-v1" "large-v2" "large" )
# list available models
function list_models {

View File

@ -5,5 +5,5 @@ if (WHISPER_SDL2)
include(DefaultTargetOptions)
target_link_libraries(${TARGET} PRIVATE common json_cpp common-sdl whisper ${CMAKE_THREAD_LIBS_INIT})
target_link_libraries(${TARGET} PRIVATE common common-sdl whisper ${CMAKE_THREAD_LIBS_INIT})
endif ()

View File

@ -26,11 +26,11 @@ struct whisper_params {
float vad_thold = 0.6f;
float freq_thold = 100.0f;
bool speed_up = false;
bool translate = false;
bool print_special = false;
bool print_energy = false;
bool use_gpu = true;
bool flash_attn = false;
std::string language = "en";
std::string model = "models/ggml-base.en.bin";
@ -53,7 +53,7 @@ struct commandset {
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];
@ -69,11 +69,11 @@ static bool whisper_params_parse(int argc, char ** argv, whisper_params & params
else if (arg == "-ac" || arg == "--audio-ctx") { params.audio_ctx = std::stoi(argv[++i]); }
else if (arg == "-vth" || arg == "--vad-thold") { params.vad_thold = std::stof(argv[++i]); }
else if (arg == "-fth" || arg == "--freq-thold") { params.freq_thold = std::stof(argv[++i]); }
else if (arg == "-su" || arg == "--speed-up") { params.speed_up = true; }
else if (arg == "-tr" || arg == "--translate") { params.translate = true; }
else if (arg == "-ps" || arg == "--print-special") { params.print_special = true; }
else if (arg == "-pe" || arg == "--print-energy") { params.print_energy = true; }
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 == "-l" || arg == "--language") { params.language = argv[++i]; }
else if (arg == "-m" || arg == "--model") { params.model = argv[++i]; }
else {
@ -100,16 +100,16 @@ void whisper_print_usage(int /*argc*/, char ** argv, const whisper_params & para
fprintf(stderr, " -ac N, --audio-ctx N [%-7d] audio context size (0 - all)\n", params.audio_ctx);
fprintf(stderr, " -vth N, --vad-thold N [%-7.2f] voice activity detection threshold\n", params.vad_thold);
fprintf(stderr, " -fth N, --freq-thold N [%-7.2f] high-pass frequency cutoff\n", params.freq_thold);
fprintf(stderr, " -su, --speed-up [%-7s] speed up audio by x2 (reduced accuracy)\n", params.speed_up ? "true" : "false");
fprintf(stderr, " -tr, --translate [%-7s] translate from source language to english\n", params.translate ? "true" : "false");
fprintf(stderr, " -ps, --print-special [%-7s] print special tokens\n", params.print_special ? "true" : "false");
fprintf(stderr, " -pe, --print-energy [%-7s] print sound energy (for debugging)\n", params.print_energy ? "true" : "false");
fprintf(stderr, " -ng, --no-gpu [%-7s] disable GPU\n", params.use_gpu ? "false" : "true");
fprintf(stderr, " -fa, --flash-attn [%-7s] flash attention\n", params.flash_attn ? "true" : "false");
fprintf(stderr, " -l LANG, --language LANG [%-7s] spoken language\n", params.language.c_str());
fprintf(stderr, " -m FNAME, --model FNAME [%-7s] model path\n", params.model.c_str());
fprintf(stderr, "\n");
}
static uint64_t wait_for_vad(audio_async & audio, json jparams, const whisper_params & params, uint64_t maxlength_ms, std::vector<float> & pcmf32) {
uint64_t wait_for_vad(audio_async & audio, json jparams, const whisper_params & params, uint64_t maxlength_ms, std::vector<float> & pcmf32) {
using namespace std::chrono;
uint64_t time_now = time_point_cast<milliseconds>(system_clock::now()).time_since_epoch().count();
uint64_t start_time = time_now;
@ -153,7 +153,7 @@ static uint64_t wait_for_vad(audio_async & audio, json jparams, const whisper_pa
return time_now;
}
static json unguided_transcription(struct whisper_context * ctx, audio_async &audio, json jparams, const whisper_params &params) {
json unguided_transcription(struct whisper_context * ctx, audio_async &audio, json jparams, const whisper_params &params) {
std::vector<whisper_token> prompt_tokens;
std::vector<float> pcmf32;
uint64_t unprocessed_audio_timestamp = wait_for_vad(audio, jparams, params, 10000U, pcmf32);
@ -181,6 +181,7 @@ static json unguided_transcription(struct whisper_context * ctx, audio_async &au
wparams.n_threads = params.n_threads;
wparams.audio_ctx = params.audio_ctx;
wparams.speed_up = params.speed_up;
wparams.suppress_non_speech_tokens = true;
// run the transformer and a single decoding pass
if (whisper_full(ctx, wparams, pcmf32.data(), pcmf32.size()) != 0) {
@ -199,7 +200,7 @@ static json unguided_transcription(struct whisper_context * ctx, audio_async &au
// command-list mode
// guide the transcription to match the most likely command from a provided list
static json guided_transcription(struct whisper_context * ctx, audio_async &audio, const whisper_params &params, json jparams, std::vector<struct commandset> commandset_list) {
json guided_transcription(struct whisper_context * ctx, audio_async &audio, const whisper_params &params, json jparams, std::vector<struct commandset> commandset_list) {
struct commandset cs = commandset_list[jparams.value("commandset_index", commandset_list.size()-1)];
std::vector<float> pcmf32;
uint64_t unprocessed_audio_timestamp = wait_for_vad(audio, jparams, params, 2000U, pcmf32);
@ -219,6 +220,7 @@ static json guided_transcription(struct whisper_context * ctx, audio_async &audi
wparams.n_threads = params.n_threads;
wparams.audio_ctx = params.audio_ctx;
wparams.speed_up = params.speed_up;
// TODO: Do some time testing. Does an overly long prompt slow down processing?
// Set up command sets/precompute prompts
@ -285,7 +287,7 @@ static json guided_transcription(struct whisper_context * ctx, audio_async &audi
}
}
static json register_commandset(struct whisper_context * ctx, json jparams, std::vector<struct commandset> &commandset_list) {
json register_commandset(struct whisper_context * ctx, json jparams, std::vector<struct commandset> &commandset_list) {
// TODO: check for token collision
struct commandset cs;
@ -325,8 +327,7 @@ static json register_commandset(struct whisper_context * ctx, json jparams, std:
commandset_list.push_back(cs);
return json{{"index",index}};
}
static json seek(struct whisper_context * /*ctx*/, audio_async & /*audio*/, json /*params*/) {
json seek(struct whisper_context * /*ctx*/, audio_async & /*audio*/, json /*params*/) {
// whisper_state has the pertinent offsets, but there also seem to be a large
// number of scratch buffers that would prevent rewinding context in a manner similar to llama
// I'll give this a another pass once everything else is implemented,
@ -336,8 +337,7 @@ static json seek(struct whisper_context * /*ctx*/, audio_async & /*audio*/, json
{"message", "Seeking is not yet supported."}
};
}
static json parse_job(const json &body, struct whisper_context * ctx, audio_async &audio, const whisper_params &params, std::vector<struct commandset> &commandset_list) {
json parse_job(const json &body, struct whisper_context * ctx, audio_async &audio, const whisper_params &params, std::vector<struct commandset> &commandset_list) {
// See: https://www.jsonrpc.org/specification
json id = body.at("id");
try {
@ -377,7 +377,7 @@ static json parse_job(const json &body, struct whisper_context * ctx, audio_asyn
}
}
static void process_loop(struct whisper_context * ctx, audio_async &audio, const whisper_params &params) {
void process_loop(struct whisper_context * ctx, audio_async &audio, const whisper_params &params) {
std::deque<json> jobqueue;
std::vector<struct commandset> commandset_list;
while (true) {
@ -435,11 +435,8 @@ int main(int argc, char ** argv) {
}
// 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);
// init audio

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