Compare commits

..

9 Commits

Author SHA1 Message Date
3c50be2217 whisper : remove comment 2023-09-10 13:27:06 +03:00
37de5dcf2b command : enable beam-search, add "no_timestamps", add "context", add p 2023-09-10 12:22:57 +03:00
7a2abb311d grammars : add assistant + update comments 2023-09-09 20:24:58 +03:00
54d168db67 command : grammar-related improvements
- option to read grammar from file
- add sample grammars for colors and chess moves
- fine-tune the performance further
2023-09-09 20:05:57 +03:00
b8f34d1ed7 whisper : fine-tuning grammar functionality 2023-09-06 17:05:05 +03:00
97ebb48b99 command : fix exception when recognizing the command 2023-09-06 15:05:17 +03:00
b0306cd5cf build : fix after master merge 2023-09-06 14:28:25 +03:00
afc84b35b0 Merge branch 'master' into HEAD 2023-09-06 13:33:34 +03:00
31476ccc0e whisper : add grammar-based sampling 2023-08-30 20:00:31 -04:00
363 changed files with 20713 additions and 145635 deletions

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@ -1,28 +0,0 @@
ARG UBUNTU_VERSION=22.04
# This needs to generally match the container host's environment.
ARG CUDA_VERSION=11.7.1
# Target the CUDA build image
ARG BASE_CUDA_DEV_CONTAINER=nvidia/cuda:${CUDA_VERSION}-devel-ubuntu${UBUNTU_VERSION}
FROM ${BASE_CUDA_DEV_CONTAINER} as build
# Unless otherwise specified, we make a fat build.
ARG CUDA_DOCKER_ARCH=all
RUN apt-get update && \
apt-get install -y build-essential git cmake
WORKDIR /app
COPY . .
# Set nvcc architecture
ENV CUDA_DOCKER_ARCH=${CUDA_DOCKER_ARCH}
# Enable cuBLAS
ENV WHISPER_CUBLAS=1
RUN make
ENTRYPOINT ["/app/main"]

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@ -1,40 +0,0 @@
ARG UBUNTU_VERSION=22.04
# This needs to generally match the container host's environment.
ARG CUDA_VERSION=12.3.1
# Target the CUDA build image
ARG BASE_CUDA_DEV_CONTAINER=nvidia/cuda:${CUDA_VERSION}-devel-ubuntu${UBUNTU_VERSION}
# Target the CUDA runtime image
ARG BASE_CUDA_RUN_CONTAINER=nvidia/cuda:${CUDA_VERSION}-runtime-ubuntu${UBUNTU_VERSION}
FROM ${BASE_CUDA_DEV_CONTAINER} AS build
WORKDIR /app
# Unless otherwise specified, we make a fat build.
ARG CUDA_DOCKER_ARCH=all
# Set nvcc architecture
ENV CUDA_DOCKER_ARCH=${CUDA_DOCKER_ARCH}
# Enable cuBLAS
ENV WHISPER_CUBLAS=1
RUN apt-get update && \
apt-get install -y build-essential \
&& 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 \
&& rm -rf /var/lib/apt/lists/* /var/cache/apt/archives/*
COPY --from=build /app /app
ENTRYPOINT [ "bash", "-c" ]

View File

@ -15,17 +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
@ -36,7 +35,7 @@ jobs:
steps:
- name: Clone
uses: actions/checkout@v4
uses: actions/checkout@v3
- name: Dependencies
run: |
@ -53,10 +52,10 @@ 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: '13.2'
@ -77,20 +76,19 @@ 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 }}
cmake . -DWHISPER_SUPPORT_SDL2=ON -DCMAKE_BUILD_TYPE=${{ matrix.build }}
make
ctest -L gh --output-on-failure'
@ -105,20 +103,19 @@ 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 ${{ env.ubuntu_image }} /bin/sh -c '
set -e
apt update
apt install -y clang build-essential cmake libsdl2-dev
cmake . -DWHISPER_SDL2=ON -DCMAKE_BUILD_TYPE=${{ matrix.build }} -DCMAKE_CXX_COMPILER=clang++ -DCMAKE_C_COMPILER=clang
apt install -y build-essential cmake libsdl2-dev
cmake . -DWHISPER_SUPPORT_SDL2=ON -DCMAKE_BUILD_TYPE=${{ matrix.build }} -DCMAKE_CXX_COMPILER=clang++ -DCMAKE_C_COMPILER=clang
make
ctest -L gh --output-on-failure'
@ -133,181 +130,22 @@ jobs:
steps:
- name: Clone
uses: actions/checkout@v4
uses: actions/checkout@v3
- name: Set up QEMU
uses: docker/setup-qemu-action@v3
uses: docker/setup-qemu-action@v2
- name: Build ${{ matrix.arch }}
run: |
docker run --platform ${{ matrix.arch }} --rm \
-v ${{ github.workspace }}:/workspace \
-w /workspace ${{ env.ubuntu_image }} /bin/sh -c '
set -e
apt update
apt install -y build-essential cmake
cmake . -DCMAKE_BUILD_TYPE=Debug -DWHISPER_SANITIZE_${{ matrix.sanitizer }}=ON
make
ctest -L gh --output-on-failure'
ubuntu-22-cmake-sycl:
runs-on: ubuntu-22.04
strategy:
fail-fast: false
matrix:
dwhisper_sycl: [ON]
dcmake_c_compiler: [icx]
dcmake_cxx_compiler: [icpx]
arch: [linux/amd64, linux/arm64, linux/arm/v7, linux/ppc64le]
continue-on-error: true
steps:
- name: Clone
uses: actions/checkout@v4
- name: add oneAPI to apt
shell: bash
run: |
cd /tmp
wget https://apt.repos.intel.com/intel-gpg-keys/GPG-PUB-KEY-INTEL-SW-PRODUCTS.PUB
sudo apt-key add GPG-PUB-KEY-INTEL-SW-PRODUCTS.PUB
rm GPG-PUB-KEY-INTEL-SW-PRODUCTS.PUB
sudo add-apt-repository "deb https://apt.repos.intel.com/oneapi all main"
- name: install oneAPI dpcpp compiler
shell: bash
run: |
sudo apt update
sudo apt install intel-oneapi-compiler-dpcpp-cpp
- name: install oneAPI MKL library
shell: bash
run: |
sudo apt install intel-oneapi-mkl-devel
- name: Clone
id: checkout
uses: actions/checkout@v4
- name: Build
id: cmake_build
run: |
source /opt/intel/oneapi/setvars.sh
mkdir build
cd build
cmake -DWHISPER_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 -DWHISPER_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 WHISPER_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 -DWHISPER_OPENBLAS=ON
cmake --build build --config ${{ matrix.build }} -j $(nproc)
windows:
runs-on: windows-latest
@ -324,14 +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'
@ -344,7 +182,7 @@ jobs:
run: >
cmake -S . -B ./build -A ${{ matrix.arch }}
-DCMAKE_BUILD_TYPE=${{ matrix.build }}
-DWHISPER_SDL2=${{ matrix.sdl2 }}
-DWHISPER_SUPPORT_SDL2=${{ matrix.sdl2 }}
- name: Build
run: |
@ -356,14 +194,14 @@ jobs:
run: copy "$env:SDL2_DIR/../lib/${{ matrix.s2arc }}/SDL2.dll" build/bin/${{ matrix.build }}
- name: Upload dll
uses: actions/upload-artifact@v4
uses: actions/upload-artifact@v3
with:
name: ${{ matrix.jnaPath }}_whisper.dll
path: build/bin/${{ matrix.build }}/whisper.dll
- name: Upload binaries
if: matrix.sdl2 == 'ON'
uses: actions/upload-artifact@v4
uses: actions/upload-artifact@v1
with:
name: whisper-bin-${{ matrix.arch }}
path: build/bin/${{ matrix.build }}
@ -379,23 +217,20 @@ jobs:
sdl2: [ON]
include:
- arch: Win32
obzip: https://github.com/OpenMathLib/OpenBLAS/releases/download/v0.3.25/OpenBLAS-0.3.25-x86.zip
obzip: https://github.com/xianyi/OpenBLAS/releases/download/v0.3.21/OpenBLAS-0.3.21-x86.zip
s2arc: x86
clblast: OFF
- arch: x64
obzip: https://github.com/OpenMathLib/OpenBLAS/releases/download/v0.3.25/OpenBLAS-0.3.25-x64.zip
obzip: https://github.com/xianyi/OpenBLAS/releases/download/v0.3.21/OpenBLAS-0.3.21-x64.zip
s2arc: x64
clblast: ON
clver: 1.6.1
- 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 OpenBLAS
if: matrix.blas == 'ON'
@ -404,7 +239,7 @@ jobs:
7z x blas.zip -oblas -y
copy blas/include/cblas.h .
copy blas/include/openblas_config.h .
echo "OPENBLAS_PATH=$env:GITHUB_WORKSPACE/blas" >> $env:GITHUB_ENV
echo "blasdir=$env:GITHUB_WORKSPACE/blas" >> $env:GITHUB_ENV
- name: Fetch SDL2 and set SDL2_DIR
if: matrix.sdl2 == 'ON'
@ -413,26 +248,13 @@ jobs:
7z x sdl2.zip
echo "SDL2_DIR=$env:GITHUB_WORKSPACE/SDL2-${{ matrix.s2ver }}/cmake" >> $env:GITHUB_ENV
- name: Install OpenCL
if: matrix.clblast == 'ON'
run: vcpkg.exe --triplet=${{ matrix.arch }}-windows install opencl
- name: Fetch CLBlast and set CLBlast_DIR
if: matrix.clblast == 'ON'
run: |
C:/msys64/usr/bin/wget.exe -qO clblast.zip https://github.com/CNugteren/CLBlast/releases/download/${{ matrix.clver }}/CLBlast-${{ matrix.clver }}-windows-x64.zip
7z x clblast.zip
7z x CLBlast-${{ matrix.clver }}-windows-x64.7z
echo "CLBlast_DIR=$env:GITHUB_WORKSPACE/CLBlast-${{ matrix.clver }}-windows-x64/lib/cmake/CLBlast" >> $env:GITHUB_ENV
- name: Configure
run: >
cmake -S . -B ./build -A ${{ matrix.arch }}
-DCMAKE_BUILD_TYPE=${{ matrix.build }}
-DWHISPER_OPENBLAS=${{ matrix.blas }}
-DCMAKE_LIBRARY_PATH="$env:OPENBLAS_PATH/lib"
-DWHISPER_SDL2=${{ matrix.sdl2 }}
-DWHISPER_CLBLAST=${{ matrix.clblast }}
-DWHISPER_SUPPORT_OPENBLAS=${{ matrix.blas }}
-DCMAKE_LIBRARY_PATH="$env:blasdir/lib"
-DWHISPER_SUPPORT_SDL2=${{ matrix.sdl2 }}
- name: Build
run: |
@ -441,25 +263,21 @@ jobs:
- name: Copy libopenblas.dll
if: matrix.blas == 'ON'
run: copy "$env:OPENBLAS_PATH/bin/libopenblas.dll" build/bin/${{ matrix.build }}
run: copy "$env:blasdir/bin/libopenblas.dll" build/bin/${{ matrix.build }}
- name: Copy SDL2.dll
if: matrix.sdl2 == 'ON'
run: copy "$env:SDL2_DIR/../lib/${{ matrix.s2arc }}/SDL2.dll" build/bin/${{ matrix.build }}
- name: Copy clblast.dll
if: matrix.clblast == 'ON'
run: copy "$env:CLBlast_DIR/../../clblast.dll" build/bin/${{ matrix.build }}
- name: Upload binaries
if: matrix.blas == 'ON' && matrix.sdl2 == 'ON'
uses: actions/upload-artifact@v4
uses: actions/upload-artifact@v1
with:
name: whisper-blas${{ matrix.clblast == 'ON' && '-clblast' || ''}}-bin-${{ matrix.arch }}
name: whisper-blas-bin-${{ matrix.arch }}
path: build/bin/${{ matrix.build }}
windows-cublas:
runs-on: windows-2019
runs-on: windows-latest
strategy:
matrix:
@ -467,25 +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'
@ -498,20 +313,12 @@ jobs:
run: >
cmake -S . -B ./build -A ${{ matrix.arch }}
-DCMAKE_BUILD_TYPE=${{ matrix.build }}
-DWHISPER_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=${{ matrix.arch }}
- name: Copy SDL2.dll
if: matrix.sdl2 == 'ON'
@ -519,9 +326,9 @@ jobs:
- name: Upload binaries
if: matrix.sdl2 == 'ON'
uses: actions/upload-artifact@v4
uses: actions/upload-artifact@v1
with:
name: whisper-cublas-${{ matrix.cuda-toolkit }}-bin-${{ matrix.arch }}
name: whisper-cublas-bin-${{ matrix.arch }}
path: build/bin/${{ matrix.build }}
emscripten:
@ -533,10 +340,10 @@ jobs:
steps:
- name: Clone
uses: actions/checkout@v4
uses: actions/checkout@v3
- name: Setup emsdk
uses: mymindstorm/setup-emsdk@v14
uses: mymindstorm/setup-emsdk@v12
- name: Verify
run: emcc -v
@ -555,7 +362,7 @@ jobs:
steps:
- name: Clone
uses: actions/checkout@v4
uses: actions/checkout@v3
- name: Configure
run: |
@ -573,75 +380,35 @@ jobs:
steps:
- name: Clone
uses: actions/checkout@v4
with:
path: whisper
- name: Clone
uses: actions/checkout@v4
with:
repository: ggerganov/ggml
path: ggml
uses: actions/checkout@v3
- name: Install Java
uses: actions/setup-java@v4
uses: actions/setup-java@v3
with:
distribution: zulu
java-version: 21
java-version: 17
- name: Setup Android SDK
uses: android-actions/setup-android@v3
uses: android-actions/setup-android@v2
- name: Build
run: |
cd whisper/examples/whisper.android
cd examples/whisper.android
./gradlew assembleRelease --no-daemon
- name: Build with external ggml
run: |
export PATH_TO_GGML=$PWD/ggml
cd whisper/examples/whisper.android
./gradlew assembleRelease --no-daemon -PGGML_HOME=$PATH_TO_GGML
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
java:
needs: [ 'windows' ]
runs-on: windows-latest
steps:
- uses: actions/checkout@v4
- uses: actions/checkout@v3
- name: Install Java
uses: actions/setup-java@v4
uses: actions/setup-java@v1
with:
distribution: zulu
java-version: 20
java-version: 17
- name: Download Windows lib
uses: actions/download-artifact@v4
uses: actions/download-artifact@v3
with:
name: win32-x86-64_whisper.dll
path: bindings/java/build/generated/resources/main/win32-x86-64
@ -654,29 +421,29 @@ jobs:
./gradlew build
- name: Upload jar
uses: actions/upload-artifact@v4
uses: actions/upload-artifact@v3
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
uses: gradle/gradle-build-action@v2
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 }}
# MAVEN_USERNAME: ${{ secrets.OSSRH_USERNAME }}
# MAVEN_PASSWORD: ${{ secrets.OSSRH_TOKEN }}
quantize:
runs-on: ubuntu-latest
steps:
- name: Clone
uses: actions/checkout@v4
uses: actions/checkout@v3
- name: Test quantize
run: |

View File

@ -1,57 +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" }
- { 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: ${{ matrix.config.platforms }}
tags: "ghcr.io/${{ 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: ${{ matrix.config.platforms }}
tags: "ghcr.io/${{ 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: |

15
.gitignore vendored
View File

@ -6,11 +6,8 @@
.vs/
.vscode/
.DS_Store
.vimspector.json
/CMakeSettings.json
build/
build-coreml/
build-em/
build-debug/
build-release/
@ -21,11 +18,6 @@ build-no-accel/
build-sanitize-addr/
build-sanitize-thread/
# SPM
.build/
.swiftpm
*.metallib
/main
/stream
/command
@ -33,7 +25,6 @@ build-sanitize-thread/
/talk-llama
/bench
/quantize
/server
/lsp
arm_neon.h
@ -55,9 +46,3 @@ models/*.mlpackage
bindings/java/.gradle/
bindings/java/.idea/
.idea/
benchmark_results.csv
cmake-build-debug/
.cxx/
.gradle/
local.properties

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>
InconsolableCellist <23345188+InconsolableCellist@users.noreply.github.com>
Ismatulla Mansurov <47342870+sapoepsilon@users.noreply.github.com>
Ivan Gorin <ivangorin21@gmail.com>
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>
jwijffels <jwijffels@bnosac.be>
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>
sandrohanea <40202887+sandrohanea@users.noreply.github.com>
semiformal-net <84111142+semiformal-net@users.noreply.github.com>
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

@ -1,10 +1,6 @@
cmake_minimum_required (VERSION 3.5)
cmake_minimum_required (VERSION 3.0)
# Allow for the creation of solution folders.
set_property(GLOBAL PROPERTY USE_FOLDERS ON)
project(whisper.cpp VERSION 1.6.2)
set(SOVERSION 1)
project(whisper.cpp VERSION 1.4.2)
# Add path to modules
list(APPEND CMAKE_MODULE_PATH "${CMAKE_CURRENT_SOURCE_DIR}/cmake/")
@ -39,12 +35,6 @@ endif()
# options
if (APPLE)
set(WHISPER_METAL_DEFAULT ON)
else()
set(WHISPER_METAL_DEFAULT OFF)
endif()
option(BUILD_SHARED_LIBS "whisper: build shared libs" ${BUILD_SHARED_LIBS_DEFAULT})
option(WHISPER_ALL_WARNINGS "whisper: enable all compiler warnings" ON)
@ -59,39 +49,24 @@ option(WHISPER_BUILD_EXAMPLES "whisper: build examples" ${WHISPER_STANDA
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_NO_AVX "whisper: disable AVX" OFF)
option(WHISPER_NO_AVX2 "whisper: disable AVX2" OFF)
option(WHISPER_NO_AVX512 "whisper: disable AVX512" ON)
option(WHISPER_NO_AVX512_VBMI "whisper: disable AVX512-VBMI" ON)
option(WHISPER_NO_AVX512_VNNI "whisper: disable AVX512-VNNI" ON)
option(WHISPER_NO_FMA "whisper: disable FMA" OFF)
option(WHISPER_NO_F16C "whisper: disable F16c" 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)
option(WHISPER_METAL_EMBED_LIBRARY "whisper: embed Metal library" 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_OPENBLAS_INTERFACE64 "whisper: use OpenBLAS w/ 64-bit interface" OFF)
option(WHISPER_CUDA "whisper: support for CUDA" OFF)
option(WHISPER_CUBLAS "whisper: support for CUDA (deprecated)" OFF)
option(WHISPER_HIPBLAS "whisper: support for hipBLAS" OFF)
option(WHISPER_CLBLAST "whisper: use CLBlast" OFF)
option(WHISPER_MKL "whisper: use Intel Math Kernel Library (MKL)" OFF)
option(WHISPER_SYCL "whisper: use SYCL" OFF)
option(WHISPER_SYCL_F16 "whisper: use 16 bit floats for sycl calculations" OFF)
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)
@ -122,33 +97,6 @@ endif()
find_package(Threads REQUIRED)
#compile flag sycl
if (WHISPER_SYCL)
set(CMAKE_CXX_STANDARD 17)
else()
set(CMAKE_CXX_STANDARD 11)
endif()
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)
set(WHISPER_EXTRA_LIBS ${WHISPER_EXTRA_LIBS} ${FFMPEG_LIBRARIES})
endif()
# on APPLE
if (APPLE)
# include Accelerate framework
@ -159,71 +107,9 @@ if (APPLE)
message(STATUS "Accelerate framework found")
set(WHISPER_EXTRA_LIBS ${WHISPER_EXTRA_LIBS} ${ACCELERATE_FRAMEWORK})
set(WHISPER_EXTRA_FLAGS ${WHISPER_EXTRA_FLAGS} -DGGML_USE_ACCELERATE -DACCELERATE_NEW_LAPACK -DACCELERATE_LAPACK_ILP64)
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-common.h and ggml-metal.metal to bin directory
configure_file(ggml-common.h bin/ggml-common.h COPYONLY)
configure_file(ggml-metal.metal bin/ggml-metal.metal COPYONLY)
if (WHISPER_METAL_EMBED_LIBRARY)
enable_language(ASM)
set(WHISPER_EXTRA_FLAGS ${WHISPER_EXTRA_FLAGS} -DGGML_METAL_EMBED_LIBRARY)
set(METALLIB_SOURCE "${CMAKE_CURRENT_SOURCE_DIR}/ggml-metal.metal")
set(COMMON_HEADER "${CMAKE_CURRENT_SOURCE_DIR}/ggml-common.h")
file(MAKE_DIRECTORY "${CMAKE_BINARY_DIR}/autogenerated")
set(EMBED_METALLIB_ASSEMBLY "${CMAKE_BINARY_DIR}/autogenerated/ggml-embed-metallib.s")
set(EMBED_METALLIB_SOURCE "${CMAKE_BINARY_DIR}/autogenerated/ggml-metal-combined.metal")
add_custom_command(
OUTPUT ${EMBED_METALLIB_SOURCE}
COMMAND sed -e "/^#include \\\"ggml-common.h\\\"/r ${COMMON_HEADER}" -e "/^#include \\\"ggml-common.h\\\"/d" ${METALLIB_SOURCE} > ${EMBED_METALLIB_SOURCE}
DEPENDS ${METALLIB_SOURCE} ${COMMON_HEADER}
COMMENT "Generating combined Metal library for embedding"
)
add_custom_command(
OUTPUT ${EMBED_METALLIB_ASSEMBLY}
COMMAND echo ".section __DATA,__ggml_metallib" > ${EMBED_METALLIB_ASSEMBLY}
COMMAND echo ".globl _ggml_metallib_start" >> ${EMBED_METALLIB_ASSEMBLY}
COMMAND echo "_ggml_metallib_start:" >> ${EMBED_METALLIB_ASSEMBLY}
COMMAND echo ".incbin \\\"${EMBED_METALLIB_SOURCE}\\\"" >> ${EMBED_METALLIB_ASSEMBLY}
COMMAND echo ".globl _ggml_metallib_end" >> ${EMBED_METALLIB_ASSEMBLY}
COMMAND echo "_ggml_metallib_end:" >> ${EMBED_METALLIB_ASSEMBLY}
DEPENDS ${EMBED_METALLIB_SOURCE}
COMMENT "Generate assembly for embedded Metal library"
)
set(GGML_SOURCES_METAL ${GGML_SOURCES_METAL} ${EMBED_METALLIB_ASSEMBLY})
message(WARNING "Accelerate framework not found")
endif()
endif()
@ -236,7 +122,7 @@ if (APPLE)
set(WHISPER_EXTRA_FLAGS ${WHISPER_EXTRA_FLAGS} -DWHISPER_USE_COREML)
else()
message(FATAL_ERROR "CoreML framework not found")
message(WARNING "CoreML framework not found")
endif()
if (WHISPER_COREML_ALLOW_FALLBACK)
@ -248,104 +134,40 @@ endif()
if (WHISPER_OPENBLAS)
set(WHISPER_BLAS_VENDOR "OpenBLAS")
set(WHISPER_BLAS ON)
# BLA_PKGCONFIG_BLAS is supported since CMake 3.25.
# FindBLAS.cmake pkg-config logic seems incomplete, because when
# BLA_SIZEOF_INTEGER is 8, then it should search for blas64 instead of blas.
# blas.pc/blas64.pc are not always provided, so let's be more specific
# and go with openblas.pc/openblas64.pc if WHISPER_OPENBLAS is on.
if (WHISPER_OPENBLAS_INTERFACE64)
set(WHISPER_BLAS_LIB "openblas64")
else ()
set(WHISPER_BLAS_LIB "openblas")
endif ()
set(BLA_PKGCONFIG_BLAS ${WHISPER_BLAS_LIB})
# OpenBLAS prebuilt libraries for Windows do not have "64" suffix in filename.
# (But .pc file has "64" suffix in filename for USE_64BITINT=1 Windows build.)
if (MSVC)
set(WHISPER_BLAS_LIB "openblas")
endif ()
endif()
if (WHISPER_BLAS)
if (NOT "$ENV{OPENBLAS_PATH}" STREQUAL "")
if (WHISPER_STATIC)
set(WHISPER_BLAS_LIB_PREFIX ${CMAKE_STATIC_LIBRARY_PREFIX})
set(WHISPER_BLAS_LIB_SUFFIX ${CMAKE_STATIC_LIBRARY_SUFFIX})
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 ()
if (CMAKE_IMPORT_LIBRARY_SUFFIX)
set(WHISPER_BLAS_LIB_PREFIX ${CMAKE_IMPORT_LIBRARY_PREFIX})
set(WHISPER_BLAS_LIB_SUFFIX ${CMAKE_IMPORT_LIBRARY_SUFFIX})
else ()
set(WHISPER_BLAS_LIB_PREFIX ${CMAKE_SHARED_LIBRARY_PREFIX})
set(WHISPER_BLAS_LIB_SUFFIX ${CMAKE_SHARED_LIBRARY_SUFFIX})
endif ()
message(WARNING "BLAS library was not found. Environment variable OPENBLAS_PATH not defined.")
endif ()
# OpenBLAS prebuilt libraries hardcode "lib" prefix in filename even on Windows
if (WHISPER_OPENBLAS)
set(WHISPER_BLAS_LIB_PREFIX "lib")
endif ()
message(STATUS "BLAS compatible library path provided")
set(BLAS_LIBRARIES "$ENV{OPENBLAS_PATH}/lib/${WHISPER_BLAS_LIB_PREFIX}${WHISPER_BLAS_LIB}${WHISPER_BLAS_LIB_SUFFIX}")
message(STATUS "Libraries ${BLAS_LIBRARIES}")
set(BLAS_INCLUDE_DIRS "$ENV{OPENBLAS_PATH}/include")
message(STATUS "Include dirs ${BLAS_INCLUDE_DIRS}")
if (NOT EXISTS "${BLAS_LIBRARIES}")
message(FATAL_ERROR "BLAS library was not found. Environment variable OPENBLAS_PATH misdefined.")
endif ()
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 ()
if (WHISPER_STATIC)
# FindBLAS.cmake pkg-config logic seems incomplete, because when
# BLA_STATIC is on, then it should use pkg_check_modules_static
# instead of pkg_check_modules.
# Some manual variable overriding may be necessary if you don't
# achieve desired results.
set(BLA_STATIC 1)
endif ()
set(BLA_STATIC 1)
set(BLA_VENDOR ${WHISPER_BLAS_VENDOR})
if (WHISPER_OPENBLAS_INTERFACE64)
set(BLA_SIZEOF_INTEGER 8)
else ()
set(BLA_SIZEOF_INTEGER 4)
endif()
set(BLA_PREFER_PKGCONFIG 1)
# set(BLA_PREFER_PKGCONFIG 1)
set(BLA_SIZEOF_INTEGER 8)
find_package(BLAS)
if(BLAS_FOUND)
message(STATUS "BLAS compatible library found")
message(STATUS "Libraries ${BLAS_LIBRARIES}")
if (NOT DEFINED BLAS_INCLUDE_DIRS)
if (PKGC_BLAS_FOUND)
set(BLAS_INCLUDE_DIRS "${PKGC_BLAS_INCLUDE_DIRS}")
else ()
find_path(BLAS_INCLUDE_DIRS cblas.h /usr/include/openblas)
endif()
endif()
message(STATUS "Include dirs ${BLAS_INCLUDE_DIRS}")
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")
message(WARNING "BLAS library was not found")
endif()
endif ()
endif ()
if (WHISPER_MKL)
find_package(MKL CONFIG REQUIRED PATHS $ENV{MKLROOT})
message(STATUS "Imported oneMKL targets: ${MKL_IMPORTED_TARGETS}")
set(WHISPER_EXTRA_FLAGS ${WHISPER_EXTRA_FLAGS} -DGGML_USE_OPENBLAS)
set(WHISPER_EXTRA_FLAGS ${WHISPER_EXTRA_FLAGS} -DGGML_BLAS_USE_MKL)
endif()
if (WHISPER_CUBLAS)
message(WARNING "WHISPER_CUBLAS is deprecated and will be removed in the future.\nUse WHISPER_CUDA instead")
set(WHISPER_CUDA ON)
endif()
if (WHISPER_CUDA)
cmake_minimum_required(VERSION 3.17)
find_package(CUDAToolkit)
@ -355,26 +177,18 @@ if (WHISPER_CUDA)
enable_language(CUDA)
file(GLOB GGML_SOURCES_CUDA "ggml-cuda/*.cu")
list(APPEND GGML_SOURCES_CUDA ggml-cuda.h)
list(APPEND GGML_SOURCES_CUDA ggml-cuda.cu)
set(GGML_CUDA_SOURCES ggml-cuda.cu ggml-cuda.h)
add_compile_definitions(GGML_USE_CUDA)
add_compile_definitions(GGML_USE_CUBLAS)
if (WHISPER_STATIC)
if (WIN32)
# As of 12.3.1 CUDA Tookit for Windows does not offer a static cublas library
set(WHISPER_EXTRA_LIBS ${WHISPER_EXTRA_LIBS} CUDA::cudart_static CUDA::cublas CUDA::cublasLt CUDA::cufft)
else ()
set(WHISPER_EXTRA_LIBS ${WHISPER_EXTRA_LIBS} CUDA::cudart_static CUDA::cublas_static CUDA::cublasLt_static CUDA::cufft_static)
endif()
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 CUDA::cufft)
set(WHISPER_EXTRA_LIBS ${WHISPER_EXTRA_LIBS} CUDA::cudart CUDA::cublas CUDA::cublasLt)
endif()
set(WHISPER_EXTRA_LIBS ${WHISPER_EXTRA_LIBS} CUDA::cuda_driver)
else()
message(FATAL_ERROR "cuBLAS not found")
message(WARNING "cuBLAS not found")
endif()
endif()
@ -394,20 +208,18 @@ if (WHISPER_HIPBLAS)
if (${hipblas_FOUND} AND ${hip_FOUND})
message(STATUS "HIP and hipBLAS found")
set(GGML_HEADERS_ROCM "ggml-cuda.h")
add_compile_definitions(GGML_USE_HIPBLAS GGML_USE_CUBLAS)
add_library(ggml-rocm OBJECT ggml-cuda.cu ggml-cuda.h)
set_property(TARGET ggml-rocm PROPERTY POSITION_INDEPENDENT_CODE ON)
set_source_files_properties(ggml-cuda.cu PROPERTIES LANGUAGE CXX)
target_link_libraries(ggml-rocm PRIVATE hip::device PUBLIC hip::host roc::rocblas roc::hipblas)
file(GLOB GGML_SOURCES_ROCM "ggml-cuda/*.cu")
list(APPEND GGML_SOURCES_ROCM "ggml-cuda.cu")
add_compile_definitions(GGML_USE_HIPBLAS GGML_USE_CUDA)
set_source_files_properties(${GGML_SOURCES_ROCM} PROPERTIES LANGUAGE CXX)
if (WHISPER_STATIC)
message(FATAL_ERROR "Static linking not supported for HIP/ROCm")
endif()
set(WHISPER_EXTRA_LIBS ${WHISPER_EXTRA_LIBS} hip::device PUBLIC hip::host roc::rocblas roc::hipblas)
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")
message(WARNING "hipBLAS or HIP not found. Try setting CMAKE_PREFIX_PATH=/opt/rocm")
endif()
endif()
@ -416,13 +228,13 @@ if (WHISPER_CLBLAST)
if (CLBlast_FOUND)
message(STATUS "CLBlast found")
set(GGML_SOURCES_OPENCL ggml-opencl.cpp ggml-opencl.h)
set(GGML_OPENCL_SOURCES ggml-opencl.cpp ggml-opencl.h)
add_compile_definitions(GGML_USE_CLBLAST)
set(WHISPER_EXTRA_LIBS ${WHISPER_EXTRA_LIBS} clblast)
else()
message(FATAL_ERROR "CLBlast not found")
message(WARNING "CLBlast not found")
endif()
endif()
@ -430,30 +242,6 @@ if( WHISPER_OPENVINO )
find_package(OpenVINO REQUIRED COMPONENTS Runtime)
endif()
if (WHISPER_SYCL)
if ( NOT DEFINED ENV{ONEAPI_ROOT})
message(FATAL_ERROR "Not detect ENV {ONEAPI_ROOT}, please install oneAPI & source it, like: source /opt/intel/oneapi/setvars.sh")
endif()
#todo: AOT
find_package(IntelSYCL REQUIRED)
if (WHISPER_SYCL_F16)
add_compile_definitions(GGML_SYCL_F16)
endif()
add_compile_definitions(GGML_USE_SYCL)
add_compile_options(-I./) #include DPCT
add_compile_options(-I/${SYCL_INCLUDE_DIR})
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -Wno-narrowing")
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -O3")
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -fsycl -L${MKLROOT}/lib")
set(GGML_HEADERS_SYCL ggml-sycl.h)
set(GGML_SOURCES_SYCL ggml-sycl.cpp)
set(WHISPER_EXTRA_LIBS ${WHISPER_EXTRA_LIBS} sycl OpenCL mkl_core pthread m dl mkl_sycl_blas mkl_intel_ilp64 mkl_tbb_thread)
endif()
# compiler flags
if (NOT CMAKE_BUILD_TYPE AND NOT CMAKE_CONFIGURATION_TYPES)
@ -485,8 +273,7 @@ if (WHISPER_ALL_WARNINGS)
endif()
if (NOT MSVC)
# TODO: temporary disabled until we figure out ggml-metal.m
#set(CMAKE_C_FLAGS "${CMAKE_C_FLAGS} -Werror=vla")
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()
@ -502,35 +289,21 @@ else()
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} /utf-8")
set(CMAKE_CXX_FLAGS_RELEASE "${CMAKE_CXX_FLAGS_RELEASE} /utf-8")
set(CMAKE_C_FLAGS "${CMAKE_C_FLAGS} /utf-8")
if(NOT WHISPER_NO_AVX512)
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} /arch:AVX512")
set(CMAKE_CXX_FLAGS_RELEASE "${CMAKE_CXX_FLAGS_RELEASE} /arch:AVX512")
set(CMAKE_C_FLAGS "${CMAKE_C_FLAGS} /arch:AVX512")
# MSVC has no compile-time flags enabling specific
# AVX512 extensions, neither it defines the
# macros corresponding to the extensions.
# Do it manually.
if (NOT WHISPER_NO_AVX512_VBMI)
add_compile_definitions($<$<COMPILE_LANGUAGE:C>:__AVX512VBMI__>)
add_compile_definitions($<$<COMPILE_LANGUAGE:CXX>:__AVX512VBMI__>)
endif()
if (NOT WHISPER_NO_AVX512_VNNI)
add_compile_definitions($<$<COMPILE_LANGUAGE:C>:__AVX512VNNI__>)
add_compile_definitions($<$<COMPILE_LANGUAGE:CXX>:__AVX512VNNI__>)
endif()
elseif(NOT WHISPER_NO_AVX2)
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 "${CMAKE_C_FLAGS} /arch:AVX2")
elseif(NOT WHISPER_NO_AVX)
set(CMAKE_CXX_FLAGS "${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")
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 -s TOTAL_STACK=5242880")
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -pthread -s TOTAL_STACK=5242880")
set(CMAKE_C_FLAGS "${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")
@ -538,15 +311,6 @@ else()
if(NOT WHISPER_NO_AVX2)
set(CMAKE_C_FLAGS "${CMAKE_C_FLAGS} -mavx2")
endif()
if(NOT WHISPER_NO_AVX512)
set(CMAKE_C_FLAGS "${CMAKE_C_FLAGS} -mavx512f -mavx512cd -mavx512vl -mavx512dq -mavx512bw")
if(NOT WHISPER_NO_AVX512_VBMI)
set(CMAKE_C_FLAGS "${CMAKE_C_FLAGS} -mavx512vbmi")
endif()
if(NOT WHISPER_NO_AVX512_VNNI)
set(CMAKE_C_FLAGS "${CMAKE_C_FLAGS} -mavx512vnni")
endif()
endif()
if(NOT WHISPER_NO_FMA)
set(CMAKE_C_FLAGS "${CMAKE_C_FLAGS} -mfma")
endif()
@ -557,53 +321,6 @@ else()
endif()
endif()
#
# 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 ${WHISPER_EXTRA_FLAGS} -DGGML_PERF)
endif()
@ -633,7 +350,6 @@ if (WHISPER_COREML)
set_target_properties(${TARGET} PROPERTIES
COMPILE_FLAGS "-fobjc-arc"
)
set_target_properties(${TARGET} PROPERTIES FOLDER "libs")
endif()
if (WHISPER_OPENVINO)
@ -652,7 +368,6 @@ if (WHISPER_OPENVINO)
set(WHISPER_EXTRA_FLAGS ${WHISPER_EXTRA_FLAGS} -DWHISPER_USE_OPENVINO)
target_link_libraries(${TARGET} PRIVATE openvino::runtime)
set_target_properties(${TARGET} PROPERTIES FOLDER "libs")
endif()
#
@ -664,34 +379,12 @@ set(TARGET whisper)
add_library(${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}
${GGML_SOURCES_SYCL} ${GGML_HEADERS_SYCL}
${GGML_SOURCES_ROCM} ${GGML_HEADERS_ROCM}
${GGML_CUDA_SOURCES}
${GGML_OPENCL_SOURCES}
whisper.h
whisper.cpp
)
if (WHISPER_CUDA)
target_sources(${TARGET} PRIVATE whisper-mel-cuda.cu)
endif()
include_directories (
.
)
# Set the version numbers
set_target_properties(whisper PROPERTIES
VERSION ${PROJECT_VERSION}
SOVERSION ${SOVERSION}
)
include(DefaultTargetOptions)
target_include_directories(${TARGET} PUBLIC
@ -706,10 +399,6 @@ if (WHISPER_OPENVINO)
target_link_libraries(${TARGET} PRIVATE whisper.openvino)
endif()
if (WHISPER_MKL)
target_link_libraries(${TARGET} PUBLIC MKL::MKL)
endif()
if (MSVC)
target_link_libraries(${TARGET} PRIVATE ${WHISPER_EXTRA_LIBS} ${CMAKE_THREAD_LIBS_INIT})
@ -719,7 +408,6 @@ else()
endif()
if (BUILD_SHARED_LIBS)
set_target_properties(${TARGET} PROPERTIES POSITION_INDEPENDENT_CODE ON)
target_link_libraries(${TARGET} PUBLIC
${CMAKE_DL_LIBS}
)
@ -733,23 +421,11 @@ if (BUILD_SHARED_LIBS)
WHISPER_BUILD
GGML_BUILD
)
if (WHISPER_METAL)
# TODO: I think this should make ggml-metal.m "see" the ggml-metal.metal file from the "bin" directory
# but for some reason it does not work here like it does in llama.cpp
set_target_properties(${TARGET} PROPERTIES RESOURCE "${CMAKE_CURRENT_SOURCE_DIR}/ggml-metal.metal")
endif()
endif()
if (GGML_SOURCES_CUDA)
if (GGML_CUDA_SOURCES)
message(STATUS "GGML CUDA sources found, configuring CUDA architecture")
# Only configure gmml CUDA architectures is not globally set
if (NOT DEFINED GGML_CUDA_ARCHITECTURES)
# Not overriden by user, so set defaults
set(GGML_CUDA_ARCHITECTURES 52 61 70)
endif()
message(STATUS "GGML Configuring CUDA architectures ${GGML_CUDA_ARCHITECTURES}")
set_property(TARGET whisper PROPERTY CUDA_ARCHITECTURES ${GGML_CUDA_ARCHITECTURES})
set_property(TARGET whisper PROPERTY CUDA_ARCHITECTURES OFF)
set_property(TARGET whisper PROPERTY CUDA_SELECT_NVCC_ARCH_FLAGS "Auto")
endif()
@ -761,16 +437,12 @@ target_compile_definitions(${TARGET} PUBLIC
${WHISPER_EXTRA_FLAGS}
)
set_target_properties(${TARGET} PROPERTIES PUBLIC_HEADER "ggml.h;whisper.h")
set_target_properties(${TARGET} PROPERTIES FOLDER "libs")
include(GNUInstallDirs)
set_target_properties(${TARGET} PROPERTIES PUBLIC_HEADER "whisper.h")
install(TARGETS ${TARGET}
LIBRARY DESTINATION lib
ARCHIVE DESTINATION lib/static
RUNTIME DESTINATION bin
RESOURCE DESTINATION bin
LIBRARY DESTINATION lib
ARCHIVE DESTINATION lib/static
RUNTIME DESTINATION bin
PUBLIC_HEADER DESTINATION include
)

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

317
Makefile
View File

@ -1,4 +1,4 @@
default: main bench quantize server
default: main bench quantize
ifndef UNAME_S
UNAME_S := $(shell uname -s)
@ -18,18 +18,7 @@ ifndef NVCC_VERSION
endif
endif
# In GNU make default CXX is g++ instead of c++. Let's fix that so that users
# of non-gcc compilers don't have to provide g++ alias or wrapper.
DEFCC := cc
DEFCXX := c++
ifeq ($(origin CC),default)
CC := $(DEFCC)
endif
ifeq ($(origin CXX),default)
CXX := $(DEFCXX)
endif
CCV := $(shell $(CC) --version | head -n 1)
CCV := $(shell $(CC) --version | head -n 1)
CXXV := $(shell $(CXX) --version | head -n 1)
# Mac OS + Arm can report x86_64
@ -53,61 +42,18 @@ CFLAGS = -I. -O3 -DNDEBUG -std=c11 -fPIC
CXXFLAGS = -I. -I./examples -O3 -DNDEBUG -std=c++11 -fPIC
LDFLAGS =
ifdef MACOSX_DEPLOYMENT_TARGET
CFLAGS += -mmacosx-version-min=$(MACOSX_DEPLOYMENT_TARGET)
CXXFLAGS += -mmacosx-version-min=$(MACOSX_DEPLOYMENT_TARGET)
LDFLAGS += -mmacosx-version-min=$(MACOSX_DEPLOYMENT_TARGET)
endif
# clock_gettime came in POSIX.1b (1993)
# CLOCK_MONOTONIC came in POSIX.1-2001 / SUSv3 as optional
# posix_memalign came in POSIX.1-2001 / SUSv3
# M_PI is an XSI extension since POSIX.1-2001 / SUSv3, came in XPG1 (1985)
CFLAGS += -D_XOPEN_SOURCE=600
CXXFLAGS += -D_XOPEN_SOURCE=600
# Somehow in OpenBSD whenever POSIX conformance is specified
# some string functions rely on locale_t availability,
# which was introduced in POSIX.1-2008, forcing us to go higher
ifeq ($(UNAME_S),OpenBSD)
CFLAGS += -U_XOPEN_SOURCE -D_XOPEN_SOURCE=700
CXXFLAGS += -U_XOPEN_SOURCE -D_XOPEN_SOURCE=700
endif
# Data types, macros and functions related to controlling CPU affinity
# are available on Linux through GNU extensions in libc
ifeq ($(UNAME_S),Linux)
CFLAGS += -D_GNU_SOURCE
CXXFLAGS += -D_GNU_SOURCE
# ref: https://github.com/ggerganov/whisper.cpp/issues/37
ifneq ($(wildcard /usr/include/musl/*),)
CFLAGS += -D_POSIX_SOURCE -D_GNU_SOURCE
CXXFLAGS += -D_POSIX_SOURCE -D_GNU_SOURCE
endif
# RLIMIT_MEMLOCK came in BSD, is not specified in POSIX.1,
# and on macOS its availability depends on enabling Darwin extensions
# similarly on DragonFly, enabling BSD extensions is necessary
ifeq ($(UNAME_S),Darwin)
CFLAGS += -D_DARWIN_C_SOURCE
CXXFLAGS += -D_DARWIN_C_SOURCE
endif
ifeq ($(UNAME_S),DragonFly)
CFLAGS += -D__BSD_VISIBLE
CXXFLAGS += -D__BSD_VISIBLE
endif
# alloca is a non-standard interface that is not visible on BSDs when
# POSIX conformance is specified, but not all of them provide a clean way
# to enable it in such cases
ifeq ($(UNAME_S),FreeBSD)
CFLAGS += -D__BSD_VISIBLE
CXXFLAGS += -D__BSD_VISIBLE
endif
ifeq ($(UNAME_S),NetBSD)
CFLAGS += -D_NETBSD_SOURCE
CXXFLAGS += -D_NETBSD_SOURCE
endif
ifeq ($(UNAME_S),OpenBSD)
CFLAGS += -D_BSD_SOURCE
CXXFLAGS += -D_BSD_SOURCE
endif
# OS specific
# TODO: support Windows
@ -116,25 +62,15 @@ ifeq ($(filter $(UNAME_S),Linux Darwin DragonFly FreeBSD NetBSD OpenBSD Haiku),$
CXXFLAGS += -pthread
endif
# detect Windows
ifneq ($(findstring _NT,$(UNAME_S)),)
_WIN32 := 1
endif
# Windows Sockets 2 (Winsock) for network-capable apps
ifeq ($(_WIN32),1)
LWINSOCK2 := -lws2_32
endif
# Architecture specific
# TODO: probably these flags need to be tweaked on some architectures
# feel free to update the Makefile for your architecture and send a pull request or issue
ifeq ($(UNAME_M),$(filter $(UNAME_M),x86_64 i686 amd64))
ifeq ($(UNAME_S),Darwin)
CPUINFO_CMD := sysctl machdep.cpu.features machdep.cpu.leaf7_features
CPUINFO_CMD := sysctl machdep.cpu.features
else ifeq ($(UNAME_S),Linux)
CPUINFO_CMD := cat /proc/cpuinfo
else ifneq (,$(filter MINGW32_NT% MINGW64_NT% MSYS_NT%,$(UNAME_S)))
else ifneq (,$(filter MINGW32_NT% MINGW64_NT%,$(UNAME_S)))
CPUINFO_CMD := cat /proc/cpuinfo
else ifneq (,$(filter DragonFly FreeBSD,$(UNAME_S)))
CPUINFO_CMD := grep Features /var/run/dmesg.boot
@ -142,68 +78,41 @@ ifeq ($(UNAME_M),$(filter $(UNAME_M),x86_64 i686 amd64))
CPUINFO_CMD := sysinfo -cpu
endif
# x86 ISA extensions (chronological order)
ifdef CPUINFO_CMD
SSE3_M := $(shell $(CPUINFO_CMD) | grep -iwE 'PNI|SSE3')
SSSE3_M := $(shell $(CPUINFO_CMD) | grep -iw 'SSSE3')
AVX_M := $(shell $(CPUINFO_CMD) | grep -iwE 'AVX|AVX1.0')
F16C_M := $(shell $(CPUINFO_CMD) | grep -iw 'F16C')
FMA_M := $(shell $(CPUINFO_CMD) | grep -iw 'FMA')
AVX2_M := $(shell $(CPUINFO_CMD) | grep -iw 'AVX2')
AVX512F_M := $(shell $(CPUINFO_CMD) | grep -iw 'AVX512F')
AVX512VBMI_M := $(shell $(CPUINFO_CMD) | grep -iw 'AVX512VBMI')
AVX512VNNI_M := $(shell $(CPUINFO_CMD) | grep -iwE 'AVX512_VNNI|AVX512VNNI')
# AVX-512 has many subsets, so let's make it easy to disable them all
ifneq ($(filter-out 0,$(WHISPER_NO_AVX512)),)
AVX512F_M :=
AVX512VBMI_M :=
AVX512VNNI_M :=
endif
ifneq (,$(SSE3_M))
CFLAGS += -msse3
CXXFLAGS += -msse3
endif
ifneq (,$(SSSE3_M))
CFLAGS += -mssse3
CXXFLAGS += -mssse3
endif
ifneq (,$(AVX_M))
CFLAGS += -mavx
CXXFLAGS += -mavx
endif
ifneq (,$(F16C_M))
CFLAGS += -mf16c
CXXFLAGS += -mf16c
endif
ifneq (,$(FMA_M))
CFLAGS += -mfma
CXXFLAGS += -mfma
endif
AVX2_M := $(shell $(CPUINFO_CMD) | grep -iw 'AVX2')
ifneq (,$(AVX2_M))
CFLAGS += -mavx2
CXXFLAGS += -mavx2
endif
ifneq (,$(AVX512F_M))
CFLAGS += -mavx512f -mavx512cd -mavx512vl -mavx512dq -mavx512bw
CXXFLAGS += -mavx512f -mavx512cd -mavx512vl -mavx512dq -mavx512bw
FMA_M := $(shell $(CPUINFO_CMD) | grep -iw 'FMA')
ifneq (,$(FMA_M))
CFLAGS += -mfma
CXXFLAGS += -mfma
endif
ifneq (,$(AVX512VBMI_M))
CFLAGS += -mavx512vbmi
CXXFLAGS += -mavx512vbmi
F16C_M := $(shell $(CPUINFO_CMD) | grep -iw 'F16C')
ifneq (,$(F16C_M))
CFLAGS += -mf16c
CXXFLAGS += -mf16c
endif
ifneq (,$(AVX512VNNI_M))
CFLAGS += -mavx512vnni
CXXFLAGS += -mavx512vnni
SSE3_M := $(shell $(CPUINFO_CMD) | grep -iwE 'PNI|SSE3')
ifneq (,$(SSE3_M))
CFLAGS += -msse3
CXXFLAGS += -msse3
endif
SSSE3_M := $(shell $(CPUINFO_CMD) | grep -iw 'SSSE3')
ifneq (,$(SSSE3_M))
CFLAGS += -mssse3
CXXFLAGS += -mssse3
endif
endif
endif
@ -223,8 +132,6 @@ ifndef WHISPER_NO_ACCELERATE
# Mac M1 - include Accelerate framework
ifeq ($(UNAME_S),Darwin)
CFLAGS += -DGGML_USE_ACCELERATE
CFLAGS += -DACCELERATE_NEW_LAPACK
CFLAGS += -DACCELERATE_LAPACK_ILP64
LDFLAGS += -framework Accelerate
endif
endif
@ -238,67 +145,26 @@ ifdef WHISPER_COREML_ALLOW_FALLBACK
endif
endif
ifndef WHISPER_NO_METAL
ifeq ($(UNAME_S),Darwin)
WHISPER_METAL := 1
CFLAGS += -DGGML_USE_METAL
CXXFLAGS += -DGGML_USE_METAL
LDFLAGS += -framework Foundation -framework Metal -framework MetalKit
endif
endif
ifneq ($(filter-out 0,$(WHISPER_OPENBLAS)),) # OpenBLAS
WHISPER_OPENBLAS_INTERFACE64 ?= 0 # use 32-bit interface by default
ifneq ($(filter-out 0,$(WHISPER_OPENBLAS_INTERFACE64)),)
WHISPER_BLAS_LIB := openblas64
else
WHISPER_BLAS_LIB := openblas
endif
ifneq ($(OPENBLAS_PATH),)
WHISPER_BLAS_CFLAGS := -I$(OPENBLAS_PATH)/include
WHISPER_BLAS_LDFLAGS := -L$(OPENBLAS_PATH)/lib -l$(WHISPER_BLAS_LIB)
else
WHISPER_BLAS_LIB_PC_EXISTS := $(shell pkg-config --exists $(WHISPER_BLAS_LIB) && echo 1)
ifneq ($(filter-out 0,$(WHISPER_BLAS_LIB_PC_EXISTS)),)
WHISPER_BLAS_CFLAGS := $(shell pkg-config --cflags $(WHISPER_BLAS_LIB))
WHISPER_BLAS_LDFLAGS := $(shell pkg-config --libs $(WHISPER_BLAS_LIB))
else
WHISPER_BLAS_CFLAGS := -I/usr/include/openblas
WHISPER_BLAS_LDFLAGS := -l$(WHISPER_BLAS_LIB)
endif
endif
CFLAGS += $(WHISPER_BLAS_CFLAGS) -DGGML_USE_OPENBLAS
LDFLAGS += $(WHISPER_BLAS_LDFLAGS)
ifdef WHISPER_OPENBLAS
CFLAGS += -DGGML_USE_OPENBLAS -I/usr/local/include/openblas -I/usr/include/openblas
LDFLAGS += -lopenblas
endif
ifdef WHISPER_CUBLAS
# WHISPER_CUBLAS is deprecated and will be removed in the future
WHISPER_CUDA := 1
endif
ifdef WHISPER_CUDA
ifeq ($(shell expr $(NVCC_VERSION) \>= 11.6), 1)
CUDA_ARCH_FLAG ?= native
CUDA_ARCH_FLAG=native
else
CUDA_ARCH_FLAG ?= all
CUDA_ARCH_FLAG=all
endif
CFLAGS += -DGGML_USE_CUDA -I/usr/local/cuda/include -I/opt/cuda/include -I$(CUDA_PATH)/targets/$(UNAME_M)-linux/include
CXXFLAGS += -DGGML_USE_CUDA -I/usr/local/cuda/include -I/opt/cuda/include -I$(CUDA_PATH)/targets/$(UNAME_M)-linux/include
LDFLAGS += -lcuda -lcublas -lculibos -lcudart -lcublasLt -lcufft -lpthread -ldl -lrt -L/usr/local/cuda/lib64 -L/opt/cuda/lib64 -L$(CUDA_PATH)/targets/$(UNAME_M)-linux/lib -L/usr/lib/wsl/lib
WHISPER_OBJ += ggml-cuda.o whisper-mel-cuda.o
WHISPER_OBJ += $(patsubst %.cu,%.o,$(wildcard ggml-cuda/*.cu))
CFLAGS += -DGGML_USE_CUBLAS -I/usr/local/cuda/include -I/opt/cuda/include -I$(CUDA_PATH)/targets/$(UNAME_M)-linux/include
CXXFLAGS += -DGGML_USE_CUBLAS -I/usr/local/cuda/include -I/opt/cuda/include -I$(CUDA_PATH)/targets/$(UNAME_M)-linux/include
LDFLAGS += -lcublas -lculibos -lcudart -lcublasLt -lpthread -ldl -lrt -L/usr/local/cuda/lib64 -L/opt/cuda/lib64 -L$(CUDA_PATH)/targets/$(UNAME_M)-linux/lib
WHISPER_OBJ += ggml-cuda.o
NVCC = nvcc
NVCCFLAGS = --forward-unknown-to-host-compiler -arch=$(CUDA_ARCH_FLAG)
ggml-cuda/%.o: ggml-cuda/%.cu ggml-cuda/%.cuh ggml.h ggml-common.h ggml-cuda/common.cuh
$(NVCC) $(NVCCFLAGS) $(CXXFLAGS) -c $< -o $@
ggml-cuda.o: ggml-cuda.cu ggml-cuda.h ggml.h ggml-backend.h ggml-backend-impl.h ggml-common.h $(wildcard ggml-cuda/*.cuh)
$(NVCC) $(NVCCFLAGS) $(CXXFLAGS) -Wno-pedantic -c $< -o $@
whisper-mel-cuda.o: whisper-mel-cuda.cu whisper.h ggml.h ggml-backend.h whisper-mel.hpp whisper-mel-cuda.hpp
ggml-cuda.o: ggml-cuda.cu ggml-cuda.h
$(NVCC) $(NVCCFLAGS) $(CXXFLAGS) -Wno-pedantic -c $< -o $@
endif
@ -306,18 +172,14 @@ ifdef WHISPER_HIPBLAS
ROCM_PATH ?= /opt/rocm
HIPCC ?= $(ROCM_PATH)/bin/hipcc
GPU_TARGETS ?= $(shell $(ROCM_PATH)/llvm/bin/amdgpu-arch)
CFLAGS += -DGGML_USE_HIPBLAS -DGGML_USE_CUDA
CXXFLAGS += -DGGML_USE_HIPBLAS -DGGML_USE_CUDA
CFLAGS += -DGGML_USE_HIPBLAS -DGGML_USE_CUBLAS
CXXFLAGS += -DGGML_USE_HIPBLAS -DGGML_USE_CUBLAS
LDFLAGS += -L$(ROCM_PATH)/lib -Wl,-rpath=$(ROCM_PATH)/lib
LDFLAGS += -lhipblas -lamdhip64 -lrocblas
HIPFLAGS += $(addprefix --offload-arch=,$(GPU_TARGETS))
WHISPER_OBJ += ggml-cuda.o
WHISPER_OBJ += $(patsubst %.cu,%.o,$(wildcard ggml-cuda/*.cu))
ggml-cuda/%.o: ggml-cuda/%.cu ggml-cuda/%.cuh ggml.h ggml-common.h ggml-cuda/common.cuh
$(HIPCC) $(CXXFLAGS) $(HIPFLAGS) -x hip -c -o $@ $<
ggml-cuda.o: ggml-cuda.cu ggml-cuda.h ggml.h ggml-backend.h ggml-backend-impl.h ggml-common.h $(wildcard ggml-cuda/*.cuh)
ggml-cuda.o: ggml-cuda.cu ggml-cuda.h
$(HIPCC) $(CXXFLAGS) $(HIPFLAGS) -x hip -c -o $@ $<
endif
@ -382,13 +244,6 @@ $(info I CC: $(CCV))
$(info I CXX: $(CXXV))
$(info )
ifdef WHISPER_CUBLAS
$(info !!!!)
$(info WHISPER_CUBLAS is deprecated and will be removed in the future. Use WHISPER_CUDA instead.)
$(info !!!!)
$(info )
endif
#
# Build library
#
@ -396,18 +251,7 @@ endif
ggml.o: ggml.c ggml.h ggml-cuda.h
$(CC) $(CFLAGS) -c $< -o $@
ggml-alloc.o: ggml-alloc.c ggml.h ggml-alloc.h
$(CC) $(CFLAGS) -c $< -o $@
ggml-backend.o: ggml-backend.c ggml.h ggml-backend.h
$(CC) $(CFLAGS) -c $< -o $@
ggml-quants.o: ggml-quants.c ggml.h ggml-quants.h
$(CC) $(CFLAGS) -c $< -o $@
WHISPER_OBJ += ggml.o ggml-alloc.o ggml-backend.o ggml-quants.o
whisper.o: whisper.cpp whisper.h whisper-mel.hpp ggml.h ggml-cuda.h
whisper.o: whisper.cpp whisper.h ggml.h ggml-cuda.h
$(CXX) $(CXXFLAGS) -c $< -o $@
ifndef WHISPER_COREML
@ -422,41 +266,14 @@ whisper-encoder-impl.o: coreml/whisper-encoder-impl.m coreml/whisper-encoder-imp
WHISPER_OBJ += whisper.o whisper-encoder.o whisper-encoder-impl.o
endif
ifdef WHISPER_METAL
ggml-metal.o: ggml-metal.m ggml-metal.h
$(CC) $(CFLAGS) -c $< -o $@
libwhisper.a: ggml.o $(WHISPER_OBJ)
$(AR) rcs libwhisper.a ggml.o $(WHISPER_OBJ)
WHISPER_OBJ += ggml-metal.o
ifdef WHISPER_METAL_EMBED_LIBRARY
CFLAGS += -DGGML_METAL_EMBED_LIBRARY
ggml-metal-embed.o: ggml-metal.metal ggml-common.h
@echo "Embedding Metal library"
$(eval TEMP_ASSEMBLY=$(shell mktemp))
$(eval TEMP_METALLIB=$(shell mktemp))
@sed "/^#include \"ggml-common.h\"/{r ggml-common.h"$$'\n'"d;}" ggml-metal.metal > $(TEMP_METALLIB)
@echo ".section __DATA, __ggml_metallib" > $(TEMP_ASSEMBLY)
@echo ".globl _ggml_metallib_start" >> $(TEMP_ASSEMBLY)
@echo "_ggml_metallib_start:" >> $(TEMP_ASSEMBLY)
@echo ".incbin \"$(TEMP_METALLIB)\"" >> $(TEMP_ASSEMBLY)
@echo ".globl _ggml_metallib_end" >> $(TEMP_ASSEMBLY)
@echo "_ggml_metallib_end:" >> $(TEMP_ASSEMBLY)
@$(AS) $(TEMP_ASSEMBLY) -o $@
@rm -f $(TEMP_ASSEMBLY) $(TEMP_METALLIB)
WHISPER_OBJ += ggml-metal-embed.o
endif
endif
libwhisper.a: $(WHISPER_OBJ)
$(AR) rcs libwhisper.a $(WHISPER_OBJ)
libwhisper.so: $(WHISPER_OBJ)
$(CXX) $(CXXFLAGS) -shared -o libwhisper.so $(WHISPER_OBJ) $(LDFLAGS)
libwhisper.so: ggml.o $(WHISPER_OBJ)
$(CXX) $(CXXFLAGS) -shared -o libwhisper.so ggml.o $(WHISPER_OBJ) $(LDFLAGS)
clean:
rm -f *.o main stream command talk talk-llama bench quantize server lsp libwhisper.a libwhisper.so
rm -f *.o main stream command talk talk-llama bench quantize lsp libwhisper.a libwhisper.so
#
# Examples
@ -464,36 +281,33 @@ clean:
CC_SDL=`sdl2-config --cflags --libs`
SRC_COMMON = examples/common.cpp examples/common-ggml.cpp examples/grammar-parser.cpp
SRC_COMMON = examples/common.cpp examples/common-ggml.cpp
SRC_COMMON_SDL = examples/common-sdl.cpp
main: examples/main/main.cpp $(SRC_COMMON) $(WHISPER_OBJ)
$(CXX) $(CXXFLAGS) examples/main/main.cpp $(SRC_COMMON) $(WHISPER_OBJ) -o main $(LDFLAGS)
main: examples/main/main.cpp $(SRC_COMMON) ggml.o $(WHISPER_OBJ)
$(CXX) $(CXXFLAGS) examples/main/main.cpp $(SRC_COMMON) ggml.o $(WHISPER_OBJ) -o main $(LDFLAGS)
./main -h
bench: examples/bench/bench.cpp $(WHISPER_OBJ)
$(CXX) $(CXXFLAGS) examples/bench/bench.cpp $(WHISPER_OBJ) -o bench $(LDFLAGS)
bench: examples/bench/bench.cpp ggml.o $(WHISPER_OBJ)
$(CXX) $(CXXFLAGS) examples/bench/bench.cpp ggml.o $(WHISPER_OBJ) -o bench $(LDFLAGS)
quantize: examples/quantize/quantize.cpp $(WHISPER_OBJ) $(SRC_COMMON)
$(CXX) $(CXXFLAGS) examples/quantize/quantize.cpp $(SRC_COMMON) $(WHISPER_OBJ) -o quantize $(LDFLAGS)
quantize: examples/quantize/quantize.cpp ggml.o $(WHISPER_OBJ) $(SRC_COMMON)
$(CXX) $(CXXFLAGS) examples/quantize/quantize.cpp $(SRC_COMMON) ggml.o $(WHISPER_OBJ) -o quantize $(LDFLAGS)
server: examples/server/server.cpp $(SRC_COMMON) $(WHISPER_OBJ)
$(CXX) $(CXXFLAGS) examples/server/server.cpp $(SRC_COMMON) $(WHISPER_OBJ) -o server $(LDFLAGS) $(LWINSOCK2)
stream: examples/stream/stream.cpp $(SRC_COMMON) $(SRC_COMMON_SDL) ggml.o $(WHISPER_OBJ)
$(CXX) $(CXXFLAGS) examples/stream/stream.cpp $(SRC_COMMON) $(SRC_COMMON_SDL) ggml.o $(WHISPER_OBJ) -o stream $(CC_SDL) $(LDFLAGS)
stream: examples/stream/stream.cpp $(SRC_COMMON) $(SRC_COMMON_SDL) $(WHISPER_OBJ)
$(CXX) $(CXXFLAGS) examples/stream/stream.cpp $(SRC_COMMON) $(SRC_COMMON_SDL) $(WHISPER_OBJ) -o stream $(CC_SDL) $(LDFLAGS)
command: examples/command/command.cpp examples/grammar-parser.cpp $(SRC_COMMON) $(SRC_COMMON_SDL) ggml.o $(WHISPER_OBJ)
$(CXX) $(CXXFLAGS) examples/command/command.cpp examples/grammar-parser.cpp $(SRC_COMMON) $(SRC_COMMON_SDL) ggml.o $(WHISPER_OBJ) -o command $(CC_SDL) $(LDFLAGS)
command: examples/command/command.cpp $(SRC_COMMON) $(SRC_COMMON_SDL) $(WHISPER_OBJ)
$(CXX) $(CXXFLAGS) examples/command/command.cpp $(SRC_COMMON) $(SRC_COMMON_SDL) $(WHISPER_OBJ) -o command $(CC_SDL) $(LDFLAGS)
lsp: examples/lsp/lsp.cpp $(SRC_COMMON) $(SRC_COMMON_SDL) ggml.o $(WHISPER_OBJ)
$(CXX) $(CXXFLAGS) examples/lsp/lsp.cpp $(SRC_COMMON) $(SRC_COMMON_SDL) ggml.o $(WHISPER_OBJ) -o lsp $(CC_SDL) $(LDFLAGS)
lsp: examples/lsp/lsp.cpp $(SRC_COMMON) $(SRC_COMMON_SDL) $(WHISPER_OBJ)
$(CXX) $(CXXFLAGS) examples/lsp/lsp.cpp $(SRC_COMMON) $(SRC_COMMON_SDL) $(WHISPER_OBJ) -o lsp $(CC_SDL) $(LDFLAGS)
talk: examples/talk/talk.cpp examples/talk/gpt-2.cpp $(SRC_COMMON) $(SRC_COMMON_SDL) ggml.o $(WHISPER_OBJ)
$(CXX) $(CXXFLAGS) examples/talk/talk.cpp examples/talk/gpt-2.cpp $(SRC_COMMON) $(SRC_COMMON_SDL) ggml.o $(WHISPER_OBJ) -o talk $(CC_SDL) $(LDFLAGS)
talk: examples/talk/talk.cpp examples/talk/gpt-2.cpp $(SRC_COMMON) $(SRC_COMMON_SDL) $(WHISPER_OBJ)
$(CXX) $(CXXFLAGS) examples/talk/talk.cpp examples/talk/gpt-2.cpp $(SRC_COMMON) $(SRC_COMMON_SDL) $(WHISPER_OBJ) -o talk $(CC_SDL) $(LDFLAGS)
talk-llama: examples/talk-llama/talk-llama.cpp examples/talk-llama/llama.cpp examples/talk-llama/unicode.cpp examples/talk-llama/unicode-data.cpp $(SRC_COMMON) $(SRC_COMMON_SDL) $(WHISPER_OBJ)
$(CXX) $(CXXFLAGS) examples/talk-llama/talk-llama.cpp examples/talk-llama/llama.cpp examples/talk-llama/unicode.cpp examples/talk-llama/unicode-data.cpp $(SRC_COMMON) $(SRC_COMMON_SDL) $(WHISPER_OBJ) -o talk-llama $(CC_SDL) $(LDFLAGS)
talk-llama: examples/talk-llama/talk-llama.cpp examples/talk-llama/llama.cpp $(SRC_COMMON) $(SRC_COMMON_SDL) ggml.o $(WHISPER_OBJ)
$(CXX) $(CXXFLAGS) examples/talk-llama/talk-llama.cpp examples/talk-llama/llama.cpp $(SRC_COMMON) $(SRC_COMMON_SDL) ggml.o $(WHISPER_OBJ) -o talk-llama $(CC_SDL) $(LDFLAGS)
#
# Audio samples
@ -538,10 +352,9 @@ samples:
.PHONY: medium.en
.PHONY: medium
.PHONY: large-v1
.PHONY: large-v2
.PHONY: large-v3
.PHONY: large
tiny.en tiny base.en base small.en small medium.en medium large-v1 large-v2 large-v3: main
tiny.en tiny base.en base small.en small medium.en medium large-v1 large: main
bash ./models/download-ggml-model.sh $@
@echo ""
@echo "==============================================="

View File

@ -1,61 +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: [
"bindings",
"cmake",
"coreml",
"examples",
"extra",
"models",
"samples",
"tests",
"CMakeLists.txt",
"ggml-cuda.cu",
"ggml-cuda.h",
"Makefile"
],
sources: [
"ggml.c",
"whisper.cpp",
"ggml-alloc.c",
"ggml-backend.c",
"ggml-quants.c",
"ggml-metal.m"
],
resources: [.process("ggml-metal.metal")],
publicHeadersPath: "spm-headers",
cSettings: [
.unsafeFlags(["-Wno-shorten-64-to-32", "-O3", "-DNDEBUG"]),
.define("GGML_USE_ACCELERATE"),
.unsafeFlags(["-fno-objc-arc"]),
.define("GGML_USE_METAL")
// NOTE: NEW_LAPACK will required iOS version 16.4+
// We should consider add this in the future when we drop support for iOS 14
// (ref: ref: https://developer.apple.com/documentation/accelerate/1513264-cblas_sgemm?language=objc)
// .define("ACCELERATE_NEW_LAPACK"),
// .define("ACCELERATE_LAPACK_ILP64")
],
linkerSettings: [
.linkedFramework("Accelerate")
]
)
],
cxxLanguageStandard: .cxx11
)

270
README.md
View File

@ -4,23 +4,24 @@
[![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: [v1.6.2](https://github.com/ggerganov/whisper.cpp/releases/tag/v1.6.0) / [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](https://github.com/ggerganov/whisper.cpp#core-ml-support)
- Apple silicon first-class citizen - optimized via ARM NEON, Accelerate framework 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
- [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
- Support for CPU-only inference
- [Efficient GPU support for NVIDIA](https://github.com/ggerganov/whisper.cpp#nvidia-gpu-support-via-cublas)
- Runs on the CPU
- [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)
@ -34,10 +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](whisper.h) and [whisper.cpp](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)
@ -48,10 +50,6 @@ You can also easily make your own offline voice assistant application: [command]
https://user-images.githubusercontent.com/1991296/204038393-2f846eae-c255-4099-a76d-5735c25c49da.mp4
On Apple Silicon, the inference runs fully on the GPU via Metal:
https://github.com/ggerganov/whisper.cpp/assets/1991296/c82e8f86-60dc-49f2-b048-d2fdbd6b5225
Or you can even run it straight in the browser: [talk.wasm](examples/talk.wasm)
## Implementation details
@ -62,22 +60,22 @@ Or you can even run it straight in the browser: [talk.wasm](examples/talk.wasm)
- 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.
```bash
git clone https://github.com/ggerganov/whisper.cpp.git
```
Then, download one of the Whisper [models](models/README.md) converted in [`ggml` format](#ggml-format). For example:
Then, download one of the Whisper models converted in [ggml format](models). For example:
```bash
bash ./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
@ -92,7 +90,7 @@ make
For a quick demo, simply run `make base.en`:
```text
```java
$ make base.en
cc -I. -O3 -std=c11 -pthread -DGGML_USE_ACCELERATE -c ggml.c -o ggml.o
@ -111,39 +109,30 @@ options:
-d N, --duration N [0 ] duration of audio to process in milliseconds
-mc N, --max-context N [-1 ] maximum number of text context tokens to store
-ml N, --max-len N [0 ] maximum segment length in characters
-sow, --split-on-word [false ] split on word rather than on token
-bo N, --best-of N [5 ] number of best candidates to keep
-bs N, --beam-size N [5 ] beam size for beam search
-bs N, --beam-size N [-1 ] beam size for beam search
-wt N, --word-thold N [0.01 ] word timestamp probability threshold
-et N, --entropy-thold N [2.40 ] entropy threshold for decoder fail
-lpt N, --logprob-thold N [-1.00 ] log probability threshold for decoder fail
-debug, --debug-mode [false ] enable debug mode (eg. dump log_mel)
-su, --speed-up [false ] speed up audio by x2 (reduced accuracy)
-tr, --translate [false ] translate from source language to english
-di, --diarize [false ] stereo audio diarization
-tdrz, --tinydiarize [false ] enable tinydiarize (requires a tdrz model)
-di, --diarize [false ] stereo audio diarization
-nf, --no-fallback [false ] do not use temperature fallback while decoding
-otxt, --output-txt [false ] output result in a text file
-ovtt, --output-vtt [false ] output result in a vtt file
-osrt, --output-srt [false ] output result in a srt file
-olrc, --output-lrc [false ] output result in a lrc file
-owts, --output-words [false ] output script for generating karaoke video
-fp, --font-path [/System/Library/Fonts/Supplemental/Courier New Bold.ttf] path to a monospace font for karaoke video
-ocsv, --output-csv [false ] output result in a CSV file
-oj, --output-json [false ] output result in a JSON file
-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
-pp, --print-progress [false ] print progress
-nt, --no-timestamps [false ] do not print timestamps
-nt, --no-timestamps [true ] do not print timestamps
-l LANG, --language LANG [en ] spoken language ('auto' for auto-detect)
-dl, --detect-language [false ] exit after automatically detecting language
--prompt PROMPT [ ] initial prompt
-m FNAME, --model FNAME [models/ggml-base.en.bin] model path
-f FNAME, --file FNAME [ ] input WAV file path
-oved D, --ov-e-device DNAME [CPU ] the OpenVINO device used for encode inference
-ls, --log-score [false ] log best decoder scores of tokens
-ng, --no-gpu [false ] disable GPU
bash ./models/download-ggml-model.sh base.en
@ -208,7 +197,7 @@ 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
```
@ -234,19 +223,18 @@ make small
make medium.en
make medium
make large-v1
make large-v2
make large-v3
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 | `0f4c8e34f21cf1a914c59d8b3ce882345ad349d6` |
## Quantization
@ -279,8 +267,7 @@ 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`
@ -306,8 +293,8 @@ 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
...
@ -335,23 +322,21 @@ 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:
@ -360,7 +345,7 @@ 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:
@ -370,28 +355,24 @@ 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
...
@ -407,19 +388,19 @@ 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
WHISPER_CUDA=1 make -j
WHISPER_CUBLAS=1 make -j
```
## OpenCL GPU support via CLBlast
@ -442,6 +423,7 @@ cmake -B build -DWHISPER_CLBLAST=ON
cmake --build build -j --config Release
```
Run all the examples as usual.
## BLAS CPU support via OpenBLAS
@ -456,63 +438,6 @@ make clean
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
```
## 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
@ -525,7 +450,7 @@ 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'
@ -597,7 +522,6 @@ 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
@ -606,7 +530,7 @@ 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
```java
make stream
./stream -m ./models/ggml-base.en.bin -t 8 --step 500 --length 5000
```
@ -618,7 +542,7 @@ 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
```
@ -628,8 +552,8 @@ 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'
...
@ -652,8 +576,8 @@ 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'
...
@ -721,9 +645,9 @@ 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
@ -733,7 +657,7 @@ 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
@ -743,7 +667,7 @@ 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
@ -755,10 +679,10 @@ 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
```
@ -774,19 +698,7 @@ 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](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
```
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:
@ -801,51 +713,49 @@ 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)
- [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

@ -1,26 +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 ../..)
LIBRARY_PATH := $(abspath ../..)
ifeq ($(UNAME_S),Darwin)
EXT_LDFLAGS := -framework Foundation -framework Metal -framework MetalKit
endif
all: clean whisper examples
whisper: mkdir
@ -28,13 +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)
@ -43,11 +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

@ -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"}
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"}
)
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

@ -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 {
@ -114,16 +118,6 @@ func (p *Params) SetMaxTokensPerSegment(n int) {
p.max_tokens = C.int(n)
}
// Set audio encoder context
func (p *Params) SetAudioCtx(n int) {
p.audio_ctx = C.int(n)
}
// Set initial prompt
func (p *Params) SetInitialPrompt(prompt string) {
p.initial_prompt = C.CString(prompt)
}
///////////////////////////////////////////////////////////////////////////////
// PRIVATE METHODS
@ -147,8 +141,6 @@ func (p *Params) String() string {
str += fmt.Sprintf(" n_max_text_ctx=%d", p.n_max_text_ctx)
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))
if p.translate {
str += " translate"
}
@ -173,6 +165,9 @@ func (p *Params) String() string {
if p.token_timestamps {
str += " token_timestamps"
}
if p.speed_up {
str += " speed_up"
}
return str + ">"
}

View File

@ -76,8 +76,13 @@ 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)
context.params.SetSplitOnWord(v)
}
// Set number of threads to use
@ -120,16 +125,6 @@ func (context *context) SetMaxTokensPerSegment(n uint) {
context.params.SetMaxTokensPerSegment(int(n))
}
// Set audio encoder context
func (context *context) SetAudioCtx(n uint) {
context.params.SetAudioCtx(int(n))
}
// 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

@ -38,17 +38,16 @@ 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
SetInitialPrompt(prompt string) // Set initial prompt
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)
// Process mono audio data and return any errors.
// If defined, newly generated segments are passed to the

View File

@ -10,7 +10,7 @@ import (
/*
#cgo LDFLAGS: -lwhisper -lm -lstdc++
#cgo darwin LDFLAGS: -framework Accelerate -framework Metal -framework Foundation -framework CoreGraphics
#cgo darwin LDFLAGS: -framework Accelerate
#include <whisper.h>
#include <stdlib.h>
@ -83,6 +83,7 @@ const (
SampleRate = C.WHISPER_SAMPLE_RATE // Expected sample rate, samples per second
SampleBits = uint16(unsafe.Sizeof(C.float(0))) * 8 // Sample size in bits
NumFFT = C.WHISPER_N_FFT
NumMEL = C.WHISPER_N_MEL
HopLength = C.WHISPER_HOP_LENGTH
ChunkSize = C.WHISPER_CHUNK_SIZE
)
@ -102,7 +103,7 @@ var (
func Whisper_init(path string) *Context {
cPath := C.CString(path)
defer C.free(unsafe.Pointer(cPath))
if ctx := C.whisper_init_from_file_with_params(cPath, C.whisper_context_default_params()); ctx != nil {
if ctx := C.whisper_init_from_file(cPath); ctx != nil {
return (*Context)(ctx)
} else {
return nil

View File

@ -2,14 +2,12 @@ plugins {
id 'java'
id 'java-library'
id 'maven-publish'
id 'signing'
}
archivesBaseName = 'whispercpp'
group = 'io.github.ggerganov'
version = '1.4.0'
sourceCompatibility = 1.8
targetCompatibility = 1.8
@ -111,23 +109,4 @@ publishing {
}
}
}
repositories {
maven {
def releasesRepoUrl = 'https://s01.oss.sonatype.org/service/local/staging/deploy/maven2/'
def snapshotsRepoUrl = 'https://s01.oss.sonatype.org/content/repositories/snapshots/'
url = version.endsWith('-SNAPSHOT') ? snapshotsRepoUrl : releasesRepoUrl
credentials {
username = System.getenv("MAVEN_USERNAME")
password = System.getenv("MAVEN_PASSWORD")
}
}
}
}
signing {
def signingKey = System.getenv("PGP_SECRET")
def signingPassword = System.getenv("PGP_PASSPHRASE")
useInMemoryPgpKeys(signingKey, signingPassword)
sign publishing.publications.mavenJava
}

View File

@ -4,7 +4,6 @@ import com.sun.jna.Structure;
import com.sun.jna.ptr.PointerByReference;
import io.github.ggerganov.whispercpp.ggml.GgmlType;
import io.github.ggerganov.whispercpp.WhisperModel;
import io.github.ggerganov.whispercpp.params.WhisperContextParams;
import java.util.List;
@ -24,9 +23,8 @@ public class WhisperContext extends Structure {
public PointerByReference vocab;
public PointerByReference state;
/** populated by whisper_init_from_file_with_params() */
/** populated by whisper_init_from_file() */
String path_model;
WhisperContextParams params;
// public static class ByReference extends WhisperContext implements Structure.ByReference {
// }

View File

@ -2,16 +2,12 @@ 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;
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.
@ -19,9 +15,8 @@ import java.util.List;
public class WhisperCpp implements AutoCloseable {
private WhisperCppJnaLibrary lib = WhisperCppJnaLibrary.instance;
private Pointer ctx = null;
private Pointer paramsPointer = null;
private Pointer greedyParamsPointer = null;
private Pointer beamParamsPointer = null;
private Pointer greedyPointer = null;
private Pointer beamPointer = null;
public File modelDir() {
String modelDirPath = System.getenv("XDG_CACHE_HOME");
@ -36,18 +31,6 @@ public class WhisperCpp implements AutoCloseable {
* @param modelPath - absolute path, or just the name (eg: "base", "base-en" or "base.en")
*/
public void initContext(String modelPath) throws FileNotFoundException {
initContextImpl(modelPath, getContextDefaultParams());
}
/**
* @param modelPath - absolute path, or just the name (eg: "base", "base-en" or "base.en")
* @param params - params to use when initialising the context
*/
public void initContext(String modelPath, WhisperContextParams params) throws FileNotFoundException {
initContextImpl(modelPath, params);
}
private void initContextImpl(String modelPath, WhisperContextParams params) throws FileNotFoundException {
if (ctx != null) {
lib.whisper_free(ctx);
}
@ -60,26 +43,13 @@ public class WhisperCpp implements AutoCloseable {
modelPath = new File(modelDir(), modelPath).getAbsolutePath();
}
ctx = lib.whisper_init_from_file_with_params(modelPath, params);
ctx = lib.whisper_init_from_file(modelPath);
if (ctx == null) {
throw new FileNotFoundException(modelPath);
}
}
/**
* 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:
* - call `whisper_free_context_params()`
* - `Native.free(Pointer.nativeValue(pointer));`
*/
public WhisperContextParams getContextDefaultParams() {
paramsPointer = lib.whisper_context_default_params_by_ref();
WhisperContextParams params = new WhisperContextParams(paramsPointer);
params.read();
return params;
}
/**
* Provides default params which can be used with `whisper_full()` etc.
* Because this function allocates memory for the params, the caller must call either:
@ -93,15 +63,15 @@ public class WhisperCpp implements AutoCloseable {
// whisper_full_default_params_by_ref allocates memory which we need to delete, so only create max 1 pointer for each strategy.
if (strategy == WhisperSamplingStrategy.WHISPER_SAMPLING_GREEDY) {
if (greedyParamsPointer == null) {
greedyParamsPointer = lib.whisper_full_default_params_by_ref(strategy.ordinal());
if (greedyPointer == null) {
greedyPointer = lib.whisper_full_default_params_by_ref(strategy.ordinal());
}
pointer = greedyParamsPointer;
pointer = greedyPointer;
} else {
if (beamParamsPointer == null) {
beamParamsPointer = lib.whisper_full_default_params_by_ref(strategy.ordinal());
if (beamPointer == null) {
beamPointer = lib.whisper_full_default_params_by_ref(strategy.ordinal());
}
pointer = beamParamsPointer;
pointer = beamPointer;
}
WhisperFullParams params = new WhisperFullParams(pointer);
@ -123,17 +93,13 @@ public class WhisperCpp implements AutoCloseable {
}
private void freeParams() {
if (paramsPointer != null) {
Native.free(Pointer.nativeValue(paramsPointer));
paramsPointer = null;
if (greedyPointer != null) {
Native.free(Pointer.nativeValue(greedyPointer));
greedyPointer = null;
}
if (greedyParamsPointer != null) {
Native.free(Pointer.nativeValue(greedyParamsPointer));
greedyParamsPointer = null;
}
if (beamParamsPointer != null) {
Native.free(Pointer.nativeValue(beamParamsPointer));
beamParamsPointer = null;
if (beamPointer != null) {
Native.free(Pointer.nativeValue(beamPointer));
beamPointer = null;
}
}
@ -163,28 +129,6 @@ 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);

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@ -5,7 +5,6 @@ import com.sun.jna.Native;
import com.sun.jna.Pointer;
import io.github.ggerganov.whispercpp.model.WhisperModelLoader;
import io.github.ggerganov.whispercpp.model.WhisperTokenData;
import io.github.ggerganov.whispercpp.params.WhisperContextParams;
import io.github.ggerganov.whispercpp.params.WhisperFullParams;
public interface WhisperCppJnaLibrary extends Library {
@ -14,32 +13,13 @@ public interface WhisperCppJnaLibrary extends Library {
String whisper_print_system_info();
/**
* DEPRECATED. Allocate (almost) all memory needed for the model by loading from a file.
* Allocate (almost) all memory needed for the model by loading from a file.
*
* @param path_model Path to the model file
* @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:
* - call `whisper_free_context_params()`
* - `Native.free(Pointer.nativeValue(pointer));`
*/
Pointer whisper_context_default_params_by_ref();
void whisper_free_context_params(Pointer params);
/**
* Allocate (almost) all memory needed for the model by loading from a file.
*
* @param path_model Path to the model file
* @param params Pointer to whisper_context_params
* @return Whisper context on success, null on failure
*/
Pointer whisper_init_from_file_with_params(String path_model, WhisperContextParams params);
/**
* Allocate (almost) all memory needed for the model by loading from a buffer.
*
@ -304,6 +284,14 @@ 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);

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@ -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;
}
}

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@ -1,31 +0,0 @@
package io.github.ggerganov.whispercpp.params;
import com.sun.jna.*;
import java.util.Arrays;
import java.util.List;
/**
* Parameters for the whisper_init_from_file_with_params() function.
* If you change the order or add new parameters, make sure to update the default values in whisper.cpp:
* whisper_context_default_params()
*/
public class WhisperContextParams extends Structure {
public WhisperContextParams(Pointer p) {
super(p);
}
/** Use GPU for inference Number (default = true) */
public CBool use_gpu;
/** Use GPU for inference Number (default = true) */
public void useGpu(boolean enable) {
use_gpu = enable ? CBool.TRUE : CBool.FALSE;
}
@Override
protected List<String> getFieldOrder() {
return Arrays.asList("use_gpu");
}
}

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");
}
}

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@ -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();
}
}
}

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@ -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 ...

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@ -20,7 +20,7 @@ struct whisper_context * g_context;
EMSCRIPTEN_BINDINGS(whisper) {
emscripten::function("init", emscripten::optional_override([](const std::string & path_model) {
if (g_context == nullptr) {
g_context = whisper_init_from_file_with_params(path_model.c_str(), whisper_context_default_params());
g_context = whisper_init_from_file(path_model.c_str());
if (g_context != nullptr) {
return true;
} else {

View File

@ -1,6 +1,6 @@
{
"name": "whisper.cpp",
"version": "1.6.2",
"version": "1.4.2",
"description": "Whisper speech recognition",
"main": "whisper.js",
"scripts": {

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@ -1,12 +0,0 @@
require 'rake/clean'
require 'rubygems/package'
desc 'Build gem'
task :package do
spec_source = File.read File.join(File.dirname(__FILE__),'whispercpp.gemspec')
spec = nil
# see: http://gist.github.com/16215
Thread.new { spec = eval("#{spec_source}") }.join
spec.validate
Gem::Package.build(spec)
end

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@ -1,8 +1,6 @@
Makefile
ggml.c
ggml.h
ggml-alloc.c
ggml-alloc.h
whisper.bundle
whisper.cpp
whisper.h

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@ -1,18 +1,8 @@
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__),'..','..','..','whisper-mel.hpp')} .")
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-common.h')} .")
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')} .")

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@ -1,141 +0,0 @@
#pragma once
// ggml-backend internal header
#include "ggml-backend.h"
#ifdef __cplusplus
extern "C" {
#endif
//
// Backend buffer
//
// buffer type
typedef void * ggml_backend_buffer_type_context_t;
struct ggml_backend_buffer_type_i {
const char * (*GGML_CALL get_name) (ggml_backend_buffer_type_t buft);
ggml_backend_buffer_t (*GGML_CALL alloc_buffer) (ggml_backend_buffer_type_t buft, size_t size);
size_t (*GGML_CALL get_alignment) (ggml_backend_buffer_type_t buft); // tensor alignment
size_t (*GGML_CALL get_max_size) (ggml_backend_buffer_type_t buft); // allocation max size
size_t (*GGML_CALL get_alloc_size) (ggml_backend_buffer_type_t buft, const struct ggml_tensor * tensor); // data size needed to allocate the tensor, including padding
bool (*GGML_CALL supports_backend)(ggml_backend_buffer_type_t buft, ggml_backend_t backend); // check if the buffer type is usable by the backend
// check if tensor data is in host memory
// should be equivalent to supports_backend(buft, ggml_backend_cpu_init())
bool (*GGML_CALL is_host) (ggml_backend_buffer_type_t buft);
};
struct ggml_backend_buffer_type {
struct ggml_backend_buffer_type_i iface;
ggml_backend_buffer_type_context_t context;
};
// buffer
typedef void * ggml_backend_buffer_context_t;
struct ggml_backend_buffer_i {
const char * (*GGML_CALL get_name) (ggml_backend_buffer_t buffer);
void (*GGML_CALL free_buffer)(ggml_backend_buffer_t buffer);
void * (*GGML_CALL get_base) (ggml_backend_buffer_t buffer);
void (*GGML_CALL init_tensor)(ggml_backend_buffer_t buffer, struct ggml_tensor * tensor);
void (*GGML_CALL set_tensor) (ggml_backend_buffer_t buffer, struct ggml_tensor * tensor, const void * data, size_t offset, size_t size);
void (*GGML_CALL get_tensor) (ggml_backend_buffer_t buffer, const struct ggml_tensor * tensor, void * data, size_t offset, size_t size);
bool (*GGML_CALL cpy_tensor) (ggml_backend_buffer_t buffer, const struct ggml_tensor * src, struct ggml_tensor * dst); // dst is in the buffer, src may be in any buffer
void (*GGML_CALL clear) (ggml_backend_buffer_t buffer, uint8_t value);
void (*GGML_CALL reset) (ggml_backend_buffer_t buffer); // reset any internal state due to tensor initialization, such as tensor extras
};
struct ggml_backend_buffer {
struct ggml_backend_buffer_i iface;
ggml_backend_buffer_type_t buft;
ggml_backend_buffer_context_t context;
size_t size;
enum ggml_backend_buffer_usage usage;
};
GGML_CALL ggml_backend_buffer_t ggml_backend_buffer_init(
ggml_backend_buffer_type_t buft,
struct ggml_backend_buffer_i iface,
ggml_backend_buffer_context_t context,
size_t size);
// do not use directly, use ggml_backend_tensor_copy instead
bool ggml_backend_buffer_copy_tensor(const struct ggml_tensor * src, struct ggml_tensor * dst);
// buffer that contains a collection of buffers
GGML_CALL ggml_backend_buffer_t ggml_backend_multi_buffer_alloc_buffer(ggml_backend_buffer_t * buffers, size_t n_buffers);
GGML_CALL bool ggml_backend_buffer_is_multi_buffer(ggml_backend_buffer_t buffer);
GGML_CALL void ggml_backend_multi_buffer_set_usage(ggml_backend_buffer_t buffer, enum ggml_backend_buffer_usage usage);
//
// Backend
//
typedef void * ggml_backend_context_t;
struct ggml_backend_i {
const char * (*GGML_CALL get_name)(ggml_backend_t backend);
void (*GGML_CALL free)(ggml_backend_t backend);
// buffer allocation
ggml_backend_buffer_type_t (*GGML_CALL get_default_buffer_type)(ggml_backend_t backend);
// (optional) asynchronous tensor data access
void (*GGML_CALL set_tensor_async)(ggml_backend_t backend, struct ggml_tensor * tensor, const void * data, size_t offset, size_t size);
void (*GGML_CALL get_tensor_async)(ggml_backend_t backend, const struct ggml_tensor * tensor, void * data, size_t offset, size_t size);
bool (*GGML_CALL cpy_tensor_async)(ggml_backend_t backend_src, ggml_backend_t backend_dst, const struct ggml_tensor * src, struct ggml_tensor * dst);
// (optional) complete all pending operations
void (*GGML_CALL synchronize)(ggml_backend_t backend);
// compute graph with a plan (not used currently)
ggml_backend_graph_plan_t (*GGML_CALL graph_plan_create) (ggml_backend_t backend, const struct ggml_cgraph * cgraph);
void (*GGML_CALL graph_plan_free) (ggml_backend_t backend, ggml_backend_graph_plan_t plan);
// compute graph with a plan
enum ggml_status (*GGML_CALL graph_plan_compute)(ggml_backend_t backend, ggml_backend_graph_plan_t plan);
// compute graph without a plan (async)
enum ggml_status (*GGML_CALL graph_compute) (ggml_backend_t backend, struct ggml_cgraph * cgraph);
// check if the backend supports an operation
bool (*GGML_CALL supports_op)(ggml_backend_t backend, const struct ggml_tensor * op);
// check if the backend wants to run an operation, even if the weights are allocated in a CPU buffer
// these should be expensive operations with large batch sizes that may benefit from running on this backend
// even if the weight has to be copied from the CPU temporarily
bool (*GGML_CALL offload_op)(ggml_backend_t backend, const struct ggml_tensor * op);
// (optional) event synchronization
ggml_backend_event_t (*GGML_CALL event_new) (ggml_backend_t backend);
void (*GGML_CALL event_free) (ggml_backend_event_t event);
void (*GGML_CALL event_record) (ggml_backend_event_t event);
void (*GGML_CALL event_wait) (ggml_backend_t backend, ggml_backend_event_t event);
void (*GGML_CALL event_synchronize) (ggml_backend_event_t event);
};
struct ggml_backend {
ggml_guid_t guid;
struct ggml_backend_i iface;
ggml_backend_context_t context;
};
struct ggml_backend_event {
ggml_backend_t backend;
void * context;
};
//
// Backend registry
//
typedef ggml_backend_t (*GGML_CALL ggml_backend_init_fn)(const char * params, void * user_data);
GGML_CALL void ggml_backend_register(const char * name, ggml_backend_init_fn init_fn, ggml_backend_buffer_type_t default_buffer_type, void * user_data);
#ifdef __cplusplus
}
#endif

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@ -1,233 +0,0 @@
#pragma once
#include "ggml.h"
#include "ggml-alloc.h"
#ifdef __cplusplus
extern "C" {
#endif
typedef struct ggml_backend_buffer_type * ggml_backend_buffer_type_t;
typedef struct ggml_backend_buffer * ggml_backend_buffer_t;
typedef struct ggml_backend_event * ggml_backend_event_t;
typedef struct ggml_backend * ggml_backend_t;
typedef void * ggml_backend_graph_plan_t;
//
// Backend buffer
//
// buffer type
GGML_API const char * ggml_backend_buft_name (ggml_backend_buffer_type_t buft);
GGML_API GGML_CALL ggml_backend_buffer_t ggml_backend_buft_alloc_buffer (ggml_backend_buffer_type_t buft, size_t size);
GGML_API size_t ggml_backend_buft_get_alignment (ggml_backend_buffer_type_t buft);
GGML_API size_t ggml_backend_buft_get_max_size (ggml_backend_buffer_type_t buft);
GGML_API GGML_CALL size_t ggml_backend_buft_get_alloc_size (ggml_backend_buffer_type_t buft, struct ggml_tensor * tensor);
GGML_API bool ggml_backend_buft_supports_backend(ggml_backend_buffer_type_t buft, ggml_backend_t backend);
GGML_API bool ggml_backend_buft_is_host (ggml_backend_buffer_type_t buft);
// buffer
enum ggml_backend_buffer_usage {
GGML_BACKEND_BUFFER_USAGE_ANY = 0,
GGML_BACKEND_BUFFER_USAGE_WEIGHTS = 1,
};
GGML_API const char * ggml_backend_buffer_name (ggml_backend_buffer_t buffer);
GGML_API void ggml_backend_buffer_free (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 GGML_CALL void ggml_backend_buffer_init_tensor (ggml_backend_buffer_t buffer, struct ggml_tensor * tensor);
GGML_API size_t ggml_backend_buffer_get_alignment (ggml_backend_buffer_t buffer);
GGML_API size_t ggml_backend_buffer_get_max_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_clear (ggml_backend_buffer_t buffer, uint8_t value);
GGML_API bool ggml_backend_buffer_is_host (ggml_backend_buffer_t buffer);
GGML_API void ggml_backend_buffer_set_usage (ggml_backend_buffer_t buffer, enum ggml_backend_buffer_usage usage);
GGML_API ggml_backend_buffer_type_t ggml_backend_buffer_get_type (ggml_backend_buffer_t buffer);
GGML_API void ggml_backend_buffer_reset (ggml_backend_buffer_t buffer);
//
// Backend
//
GGML_API ggml_guid_t ggml_backend_guid(ggml_backend_t backend);
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_type_t ggml_backend_get_default_buffer_type(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 size_t ggml_backend_get_max_size(ggml_backend_t backend);
GGML_API void ggml_backend_tensor_set_async(ggml_backend_t backend, struct ggml_tensor * tensor, const void * data, size_t offset, size_t size);
GGML_API void ggml_backend_tensor_get_async(ggml_backend_t backend, const struct ggml_tensor * tensor, void * data, size_t offset, size_t size);
GGML_API GGML_CALL void ggml_backend_tensor_set( struct ggml_tensor * tensor, const void * data, size_t offset, size_t size);
GGML_API GGML_CALL 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 enum ggml_status ggml_backend_graph_plan_compute (ggml_backend_t backend, ggml_backend_graph_plan_t plan);
GGML_API enum ggml_status ggml_backend_graph_compute (ggml_backend_t backend, struct ggml_cgraph * cgraph);
GGML_API enum ggml_status ggml_backend_graph_compute_async(ggml_backend_t backend, struct ggml_cgraph * cgraph);
GGML_API bool ggml_backend_supports_op(ggml_backend_t backend, const struct ggml_tensor * op);
GGML_API bool ggml_backend_offload_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);
// asynchronous copy
// the copy is performed after all the currently queued operations in backend_src
// backend_dst will wait for the copy to complete before performing other operations
// automatic fallback to sync copy if async is not supported
GGML_API void ggml_backend_tensor_copy_async(ggml_backend_t backend_src, ggml_backend_t backend_dst, struct ggml_tensor * src, struct ggml_tensor * dst);
// events
GGML_API ggml_backend_event_t ggml_backend_event_new (ggml_backend_t backend);
GGML_API void ggml_backend_event_free (ggml_backend_event_t event);
GGML_API void ggml_backend_event_record (ggml_backend_event_t event);
GGML_API void ggml_backend_event_synchronize(ggml_backend_event_t event);
GGML_API void ggml_backend_event_wait (ggml_backend_t backend, ggml_backend_event_t event); // wait async on event
//
// CPU backend
//
GGML_API ggml_backend_t ggml_backend_cpu_init(void);
GGML_API GGML_CALL 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);
GGML_API void ggml_backend_cpu_set_abort_callback(ggml_backend_t backend_cpu, ggml_abort_callback abort_callback, void * abort_callback_data);
// Create a backend buffer from an existing pointer
GGML_API GGML_CALL ggml_backend_buffer_t ggml_backend_cpu_buffer_from_ptr(void * ptr, size_t size);
GGML_API GGML_CALL ggml_backend_buffer_type_t ggml_backend_cpu_buffer_type(void);
#ifdef GGML_USE_CPU_HBM
GGML_API ggml_backend_buffer_type_t ggml_backend_cpu_hbm_buffer_type(void);
#endif
//
// Backend registry
//
// The backend registry is a registry of all the available backends, and allows initializing backends in a generic way
GGML_API size_t ggml_backend_reg_get_count(void);
GGML_API size_t ggml_backend_reg_find_by_name(const char * name);
GGML_API ggml_backend_t ggml_backend_reg_init_backend_from_str(const char * backend_str); // str is name[:params]
GGML_API const char * ggml_backend_reg_get_name(size_t i);
GGML_API ggml_backend_t ggml_backend_reg_init_backend(size_t i, const char * params); // params is backend-specific
GGML_API ggml_backend_buffer_type_t ggml_backend_reg_get_default_buffer_type(size_t i);
GGML_API ggml_backend_buffer_t ggml_backend_reg_alloc_buffer(size_t i, 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:
// operations that use tensors allocated in a buffer with USAGE_WEIGHTS will be assigned
// preferrably to run on the same backend as the buffer
ggml_backend_buffer_set_usage(buf_weights, GGML_BACKEND_BUFFER_USAGE_WEIGHTS);
sched = ggml_backend_sched_new({backend_gpu, backend_gpu2, backend_cpu}, NULL, num_backends, GGML_DEFAULT_GRAPH_SIZE, false);
// initialize buffers from a max size graph (optional)
reserve_graph = build_graph(sched, max_batch_size);
// manually assign nodes to a backend (optional, should not be needed in most cases)
struct ggml_tensor * node = ggml_mul_mat(ctx, ...);
ggml_backend_sched_set_tensor_backend(sched, node, backend_gpu);
ggml_backend_sched_reserve(sched, reserve_graph);
// compute
graph = build_graph(sched);
ggml_backend_sched_graph_compute(sched, graph);
// if there are graph inputs:
ggml_backend_sched_reset(sched);
ggml_backend_sched_alloc_graph(sched, graph);
ggml_backend_tensor_set(input_tensor, ...);
ggml_backend_sched_graph_compute(sched, graph);
}
*/
struct ggml_backend_sched;
typedef struct ggml_backend_sched * ggml_backend_sched_t;
// when ask == true, the scheduler wants to know if the user wants to observe this node
// this allows the scheduler to batch nodes together in order to evaluate them in a single call
//
// when ask == false, the scheduler is passing the node tensor to the user for observation
// if the user returns false, the scheduler will cancel the graph compute
//
typedef bool (*ggml_backend_sched_eval_callback)(struct ggml_tensor * t, bool ask, void * user_data);
// Initialize a backend scheduler
GGML_API ggml_backend_sched_t ggml_backend_sched_new(ggml_backend_t * backends, ggml_backend_buffer_type_t * bufts, int n_backends, size_t graph_size, bool parallel);
GGML_API void ggml_backend_sched_free(ggml_backend_sched_t sched);
// Initialize backend buffers from a measure graph
GGML_API bool ggml_backend_sched_reserve(ggml_backend_sched_t sched, struct ggml_cgraph * measure_graph);
// Get the number of splits of the last graph
GGML_API int ggml_backend_sched_get_n_splits(ggml_backend_sched_t sched);
GGML_API int ggml_backend_sched_get_n_copies(ggml_backend_sched_t sched);
GGML_API size_t ggml_backend_sched_get_buffer_size(ggml_backend_sched_t sched, ggml_backend_t backend);
GGML_API void ggml_backend_sched_set_tensor_backend(ggml_backend_sched_t sched, struct ggml_tensor * node, ggml_backend_t backend);
GGML_API ggml_backend_t ggml_backend_sched_get_tensor_backend(ggml_backend_sched_t sched, struct ggml_tensor * node);
// Allocate and compute graph on the backend scheduler
GGML_API bool ggml_backend_sched_alloc_graph(ggml_backend_sched_t sched, struct ggml_cgraph * graph);
GGML_API enum ggml_status ggml_backend_sched_graph_compute(ggml_backend_sched_t sched, struct ggml_cgraph * graph);
GGML_API enum ggml_status ggml_backend_sched_graph_compute_async(ggml_backend_sched_t sched, struct ggml_cgraph * graph);
GGML_API void ggml_backend_sched_synchronize(ggml_backend_sched_t sched);
// Reset all assignments and allocators - must be called before changing the node backends
GGML_API void ggml_backend_sched_reset(ggml_backend_sched_t sched);
// Set a callback to be called for each resulting node during graph compute
GGML_API void ggml_backend_sched_set_eval_callback(ggml_backend_sched_t sched, ggml_backend_sched_eval_callback callback, void * user_data);
//
// Utils
//
struct ggml_backend_graph_copy {
ggml_backend_buffer_t buffer;
struct ggml_context * ctx_allocated;
struct ggml_context * ctx_unallocated;
struct ggml_cgraph * graph;
};
// Copy a graph to a different backend
GGML_API struct ggml_backend_graph_copy ggml_backend_graph_copy(ggml_backend_t backend, struct ggml_cgraph * graph);
GGML_API void ggml_backend_graph_copy_free(struct ggml_backend_graph_copy copy);
typedef bool (*GGML_CALL ggml_backend_eval_callback)(int node_index, struct ggml_tensor * t1, struct ggml_tensor * t2, void * user_data);
// Compare the output of two backends
GGML_API bool ggml_backend_compare_graph_backend(ggml_backend_t backend1, ggml_backend_t backend2, struct ggml_cgraph * graph, ggml_backend_eval_callback callback, void * user_data);
// Tensor initialization
GGML_API void ggml_backend_tensor_alloc(ggml_backend_buffer_t buffer, struct ggml_tensor * tensor, void * addr);
GGML_API void ggml_backend_view_init(ggml_backend_buffer_t buffer, struct ggml_tensor * tensor);
#ifdef __cplusplus
}
#endif

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#pragma once
#include "ggml.h"
#include "ggml-backend.h"
#ifdef GGML_USE_HIPBLAS
#define GGML_CUDA_NAME "ROCm"
#define GGML_CUBLAS_NAME "hipBLAS"
#else
#define GGML_CUDA_NAME "CUDA"
#define GGML_CUBLAS_NAME "cuBLAS"
#endif
#ifdef __cplusplus
extern "C" {
#endif
#define GGML_CUDA_MAX_DEVICES 16
// backend API
GGML_API GGML_CALL ggml_backend_t ggml_backend_cuda_init(int device);
GGML_API GGML_CALL bool ggml_backend_is_cuda(ggml_backend_t backend);
// device buffer
GGML_API GGML_CALL ggml_backend_buffer_type_t ggml_backend_cuda_buffer_type(int device);
// split tensor buffer that splits matrices by rows across multiple devices
GGML_API GGML_CALL ggml_backend_buffer_type_t ggml_backend_cuda_split_buffer_type(const float * tensor_split);
// pinned host buffer for use with the CPU backend for faster copies between CPU and GPU
GGML_API GGML_CALL ggml_backend_buffer_type_t ggml_backend_cuda_host_buffer_type(void);
GGML_API GGML_CALL int ggml_backend_cuda_get_device_count(void);
GGML_API GGML_CALL void ggml_backend_cuda_get_device_description(int device, char * description, size_t description_size);
GGML_API GGML_CALL void ggml_backend_cuda_get_device_memory(int device, size_t * free, size_t * total);
GGML_API GGML_CALL bool ggml_backend_cuda_register_host_buffer(void * buffer, size_t size);
GGML_API GGML_CALL void ggml_backend_cuda_unregister_host_buffer(void * buffer);
#ifdef __cplusplus
}
#endif

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#pragma once
#include "ggml.h"
// GGML internal header
#include <assert.h>
#include <stdlib.h> // load `stdlib.h` before other headers to work around MinGW bug: https://sourceforge.net/p/mingw-w64/bugs/192/
#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 __cplusplus
#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
#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
#endif
// __SSE3__ and __SSSE3__ are not defined in MSVC, but SSE3/SSSE3 are present when AVX/AVX2/AVX512 are available
#if defined(_MSC_VER) && (defined(__AVX__) || defined(__AVX2__) || defined(__AVX512F__))
#ifndef __SSE3__
#define __SSE3__
#endif
#ifndef __SSSE3__
#define __SSSE3__
#endif
#endif
// 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>
typedef __fp16 ggml_fp16_internal_t;
#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)
#define GGML_FP16_TO_FP32(x) ggml_compute_fp16_to_fp32(x)
static inline float ggml_compute_fp16_to_fp32(ggml_fp16_t h) {
ggml_fp16_internal_t tmp;
memcpy(&tmp, &h, sizeof(ggml_fp16_t));
return (float)tmp;
}
static inline ggml_fp16_t ggml_compute_fp32_to_fp16(float f) {
ggml_fp16_t res;
ggml_fp16_internal_t tmp = f;
memcpy(&res, &tmp, sizeof(ggml_fp16_t));
return res;
}
#else
typedef uint16_t ggml_fp16_internal_t;
#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)
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)
#endif
#if !defined(GGML_FP32_TO_FP16)
#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)
struct ggml_hash_set ggml_hash_set_new(size_t size);
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_HASHTABLE_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.h"
#include "ggml-backend.h"
#include <stdbool.h>
#include <stddef.h>
#include <stdint.h>
#ifdef __cplusplus
extern "C" {
#endif
struct ggml_vk_device {
int index;
int type; // same as VkPhysicalDeviceType
size_t heapSize;
const char * name;
const char * vendor;
int subgroupSize;
uint64_t bufferAlignment;
uint64_t maxAlloc;
};
struct ggml_vk_device * ggml_vk_available_devices(size_t memoryRequired, size_t * count);
bool ggml_vk_get_device(struct ggml_vk_device * device, size_t memoryRequired, const char * name);
bool ggml_vk_has_vulkan(void);
bool ggml_vk_has_device(void);
struct ggml_vk_device ggml_vk_current_device(void);
//
// backend API
//
// forward declaration
typedef struct ggml_backend * ggml_backend_t;
GGML_API ggml_backend_t ggml_backend_kompute_init(int device);
GGML_API bool ggml_backend_is_kompute(ggml_backend_t backend);
GGML_API ggml_backend_buffer_type_t ggml_backend_kompute_buffer_type(int device);
#ifdef __cplusplus
}
#endif

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// An interface allowing to compute ggml_cgraph with Metal
//
// This is a fully functional interface that extends ggml with GPU support for Apple devices.
// A similar interface can be created for other GPU backends (e.g. Vulkan, CUDA, OpenCL, etc.)
//
// How it works?
//
// As long as your program can create and evaluate a ggml_cgraph on the CPU, you can use this
// interface to evaluate the same graph on the GPU. Instead of using ggml_graph_compute(), you
// use ggml_metal_graph_compute() (or ggml_vulkan_graph_compute(), etc.)
//
// You only need to make sure that all memory buffers that you used during the graph creation
// are mapped to the device memory with the ggml_metal_add_buffer() function. This mapping is
// used during the graph evaluation to determine the arguments of the compute kernels.
//
// Synchronization between device and host memory (for example for input and output tensors)
// is done with the ggml_metal_set_tensor() and ggml_metal_get_tensor() functions.
//
#pragma once
#include "ggml.h"
#include "ggml-backend.h"
#include <stddef.h>
#include <stdbool.h>
// max memory buffers that can be mapped to the device
#define GGML_METAL_MAX_BUFFERS 64
struct ggml_tensor;
struct ggml_cgraph;
#ifdef __cplusplus
extern "C" {
#endif
//
// backend API
// user-code should use only these functions
//
GGML_API void ggml_backend_metal_log_set_callback(ggml_log_callback log_callback, void * user_data);
GGML_API ggml_backend_t ggml_backend_metal_init(void);
GGML_API bool ggml_backend_is_metal(ggml_backend_t backend);
GGML_API GGML_CALL ggml_backend_buffer_t ggml_backend_metal_buffer_from_ptr(void * data, size_t size, size_t max_size);
GGML_API void ggml_backend_metal_set_n_cb(ggml_backend_t backend, int n_cb);
GGML_API GGML_CALL ggml_backend_buffer_type_t ggml_backend_metal_buffer_type(void);
// helper to check if the device supports a specific family
// ideally, the user code should be doing these checks
// ref: https://developer.apple.com/metal/Metal-Feature-Set-Tables.pdf
GGML_API bool ggml_backend_metal_supports_family(ggml_backend_t backend, int family);
// capture all command buffers committed the next time `ggml_backend_graph_compute` is called
GGML_API void ggml_backend_metal_capture_next_compute(ggml_backend_t backend);
#ifdef __cplusplus
}
#endif

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@ -1,36 +0,0 @@
#pragma once
#include "ggml.h"
#include "ggml-backend.h"
#ifdef __cplusplus
extern "C" {
#endif
GGML_API void ggml_cl_init(void);
GGML_API void ggml_cl_mul(const struct ggml_tensor * src0, const struct ggml_tensor * src1, struct ggml_tensor * dst);
GGML_API void ggml_cl_add(const struct ggml_tensor * src0, const struct ggml_tensor * src1, struct ggml_tensor * dst);
GGML_API bool ggml_cl_can_mul_mat(const struct ggml_tensor * src0, const struct ggml_tensor * src1, const struct ggml_tensor * dst);
GGML_API size_t ggml_cl_mul_mat_get_wsize(const struct ggml_tensor * src0, const struct ggml_tensor * src1, struct ggml_tensor * dst);
GGML_API void ggml_cl_mul_mat(const struct ggml_tensor * src0, const struct ggml_tensor * src1, struct ggml_tensor * dst, void * wdata, size_t wsize);
// GGML_API void * ggml_cl_host_malloc(size_t size);
// GGML_API void ggml_cl_host_free(void * ptr);
GGML_API void ggml_cl_free_data(const struct ggml_tensor* tensor);
GGML_API void ggml_cl_transform_tensor(void * data, struct ggml_tensor * tensor);
// backend API
// GGML_API ggml_backend_t ggml_backend_opencl_init(void);
// GGML_API bool ggml_backend_is_opencl(ggml_backend_t backend);
GGML_API ggml_backend_buffer_type_t ggml_backend_opencl_buffer_type(void);
// GGML_API ggml_backend_buffer_type_t ggml_backend_opencl_host_buffer_type(void);
#ifdef __cplusplus
}
#endif

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#pragma once
#define GGML_COMMON_DECL_C
#include "ggml-common.h"
#include "ggml.h"
// GGML internal header
#ifdef __cplusplus
extern "C" {
#endif
// Quantization
void quantize_row_q4_0_reference(const float * GGML_RESTRICT x, block_q4_0 * GGML_RESTRICT y, int64_t k);
void quantize_row_q4_1_reference(const float * GGML_RESTRICT x, block_q4_1 * GGML_RESTRICT y, int64_t k);
void quantize_row_q5_0_reference(const float * GGML_RESTRICT x, block_q5_0 * GGML_RESTRICT y, int64_t k);
void quantize_row_q5_1_reference(const float * GGML_RESTRICT x, block_q5_1 * GGML_RESTRICT y, int64_t k);
void quantize_row_q8_0_reference(const float * GGML_RESTRICT x, block_q8_0 * GGML_RESTRICT y, int64_t k);
void quantize_row_q8_1_reference(const float * GGML_RESTRICT x, block_q8_1 * GGML_RESTRICT y, int64_t k);
void quantize_row_q2_K_reference(const float * GGML_RESTRICT x, block_q2_K * GGML_RESTRICT y, int64_t k);
void quantize_row_q3_K_reference(const float * GGML_RESTRICT x, block_q3_K * GGML_RESTRICT y, int64_t k);
void quantize_row_q4_K_reference(const float * GGML_RESTRICT x, block_q4_K * GGML_RESTRICT y, int64_t k);
void quantize_row_q5_K_reference(const float * GGML_RESTRICT x, block_q5_K * GGML_RESTRICT y, int64_t k);
void quantize_row_q6_K_reference(const float * GGML_RESTRICT x, block_q6_K * GGML_RESTRICT y, int64_t k);
void quantize_row_q8_K_reference(const float * GGML_RESTRICT x, block_q8_K * GGML_RESTRICT y, int64_t k);
void quantize_row_iq3_xxs_reference(const float * GGML_RESTRICT x, block_iq3_xxs * GGML_RESTRICT y, int64_t k);
void quantize_row_iq4_nl_reference (const float * GGML_RESTRICT x, block_iq4_nl * GGML_RESTRICT y, int64_t k);
void quantize_row_iq4_xs_reference (const float * GGML_RESTRICT x, block_iq4_xs * GGML_RESTRICT y, int64_t k);
void quantize_row_iq3_s_reference (const float * GGML_RESTRICT x, block_iq3_s * GGML_RESTRICT y, int64_t k);
void quantize_row_iq2_s_reference (const float * GGML_RESTRICT x, block_iq2_s * GGML_RESTRICT y, int64_t k);
void quantize_row_q4_0(const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int64_t k);
void quantize_row_q4_1(const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int64_t k);
void quantize_row_q5_0(const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int64_t k);
void quantize_row_q5_1(const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int64_t k);
void quantize_row_q8_0(const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int64_t k);
void quantize_row_q8_1(const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int64_t k);
void quantize_row_q2_K(const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int64_t k);
void quantize_row_q3_K(const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int64_t k);
void quantize_row_q4_K(const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int64_t k);
void quantize_row_q5_K(const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int64_t k);
void quantize_row_q6_K(const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int64_t k);
void quantize_row_q8_K(const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int64_t k);
void quantize_row_iq3_xxs(const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int64_t k);
void quantize_row_iq4_nl (const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int64_t k);
void quantize_row_iq4_xs (const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int64_t k);
void quantize_row_iq3_s (const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int64_t k);
void quantize_row_iq2_s (const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int64_t k);
// Dequantization
void dequantize_row_q4_0(const block_q4_0 * GGML_RESTRICT x, float * GGML_RESTRICT y, int64_t k);
void dequantize_row_q4_1(const block_q4_1 * GGML_RESTRICT x, float * GGML_RESTRICT y, int64_t k);
void dequantize_row_q5_0(const block_q5_0 * GGML_RESTRICT x, float * GGML_RESTRICT y, int64_t k);
void dequantize_row_q5_1(const block_q5_1 * GGML_RESTRICT x, float * GGML_RESTRICT y, int64_t k);
void dequantize_row_q8_0(const block_q8_0 * GGML_RESTRICT x, float * GGML_RESTRICT y, int64_t k);
//void dequantize_row_q8_1(const block_q8_1 * GGML_RESTRICT x, float * GGML_RESTRICT y, int64_t k);
void dequantize_row_q2_K(const block_q2_K * GGML_RESTRICT x, float * GGML_RESTRICT y, int64_t k);
void dequantize_row_q3_K(const block_q3_K * GGML_RESTRICT x, float * GGML_RESTRICT y, int64_t k);
void dequantize_row_q4_K(const block_q4_K * GGML_RESTRICT x, float * GGML_RESTRICT y, int64_t k);
void dequantize_row_q5_K(const block_q5_K * GGML_RESTRICT x, float * GGML_RESTRICT y, int64_t k);
void dequantize_row_q6_K(const block_q6_K * GGML_RESTRICT x, float * GGML_RESTRICT y, int64_t k);
void dequantize_row_q8_K(const block_q8_K * GGML_RESTRICT x, float * GGML_RESTRICT y, int64_t k);
void dequantize_row_iq2_xxs(const block_iq2_xxs * GGML_RESTRICT x, float * GGML_RESTRICT y, int64_t k);
void dequantize_row_iq2_xs (const block_iq2_xs * GGML_RESTRICT x, float * GGML_RESTRICT y, int64_t k);
void dequantize_row_iq2_s (const block_iq2_s * GGML_RESTRICT x, float * GGML_RESTRICT y, int64_t k);
void dequantize_row_iq3_xxs(const block_iq3_xxs * GGML_RESTRICT x, float * GGML_RESTRICT y, int64_t k);
void dequantize_row_iq1_s (const block_iq1_s * GGML_RESTRICT x, float * GGML_RESTRICT y, int64_t k);
void dequantize_row_iq1_m (const block_iq1_m * GGML_RESTRICT x, float * GGML_RESTRICT y, int64_t k);
void dequantize_row_iq4_nl (const block_iq4_nl * GGML_RESTRICT x, float * GGML_RESTRICT y, int64_t k);
void dequantize_row_iq4_xs (const block_iq4_xs * GGML_RESTRICT x, float * GGML_RESTRICT y, int64_t k);
void dequantize_row_iq3_s (const block_iq3_s * GGML_RESTRICT x, float * GGML_RESTRICT y, int64_t k);
// Dot product
void ggml_vec_dot_q4_0_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, size_t bx, const void * GGML_RESTRICT vy, size_t by, int nrc);
void ggml_vec_dot_q4_1_q8_1(int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, size_t bx, const void * GGML_RESTRICT vy, size_t by, int nrc);
void ggml_vec_dot_q5_0_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, size_t bx, const void * GGML_RESTRICT vy, size_t by, int nrc);
void ggml_vec_dot_q5_1_q8_1(int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, size_t bx, const void * GGML_RESTRICT vy, size_t by, int nrc);
void ggml_vec_dot_q8_0_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, size_t bx, const void * GGML_RESTRICT vy, size_t by, int nrc);
void ggml_vec_dot_q2_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, size_t bx, const void * GGML_RESTRICT vy, size_t by, int nrc);
void ggml_vec_dot_q3_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, size_t bx, const void * GGML_RESTRICT vy, size_t by, int nrc);
void ggml_vec_dot_q4_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, size_t bx, const void * GGML_RESTRICT vy, size_t by, int nrc);
void ggml_vec_dot_q5_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, size_t bx, const void * GGML_RESTRICT vy, size_t by, int nrc);
void ggml_vec_dot_q6_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, size_t bx, const void * GGML_RESTRICT vy, size_t by, int nrc);
void ggml_vec_dot_iq2_xxs_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, size_t bx, const void * GGML_RESTRICT vy, size_t by, int nrc);
void ggml_vec_dot_iq2_xs_q8_K (int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, size_t bx, const void * GGML_RESTRICT vy, size_t by, int nrc);
void ggml_vec_dot_iq2_s_q8_K (int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, size_t bx, const void * GGML_RESTRICT vy, size_t by, int nrc);
void ggml_vec_dot_iq3_xxs_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, size_t bx, const void * GGML_RESTRICT vy, size_t by, int nrc);
void ggml_vec_dot_iq1_s_q8_K (int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, size_t bx, const void * GGML_RESTRICT vy, size_t by, int nrc);
void ggml_vec_dot_iq1_m_q8_K (int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, size_t bx, const void * GGML_RESTRICT vy, size_t by, int nrc);
void ggml_vec_dot_iq4_nl_q8_0 (int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, size_t bx, const void * GGML_RESTRICT vy, size_t by, int nrc);
void ggml_vec_dot_iq4_xs_q8_K (int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, size_t bx, const void * GGML_RESTRICT vy, size_t by, int nrc);
void ggml_vec_dot_iq3_s_q8_K (int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, size_t bx, const void * GGML_RESTRICT vy, size_t by, int nrc);
// Quantization utilizing an importance matrix (a.k.a. "Activation aWare Quantization")
size_t quantize_iq2_xxs(const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int64_t nrows, int64_t n_per_row, const float * imatrix);
size_t quantize_iq2_xs (const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int64_t nrows, int64_t n_per_row, const float * imatrix);
size_t quantize_iq2_s (const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int64_t nrows, int64_t n_per_row, const float * imatrix);
size_t quantize_iq3_xxs(const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int64_t nrows, int64_t n_per_row, const float * imatrix);
size_t quantize_iq1_s (const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int64_t nrows, int64_t n_per_row, const float * imatrix);
size_t quantize_iq1_m (const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int64_t nrows, int64_t n_per_row, const float * imatrix);
size_t quantize_iq4_nl (const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int64_t nrows, int64_t n_per_row, const float * imatrix);
size_t quantize_iq4_xs (const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int64_t nrows, int64_t n_per_row, const float * imatrix);
size_t quantize_iq3_s (const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int64_t nrows, int64_t n_per_row, const float * imatrix);
size_t quantize_q2_K(const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int64_t nrows, int64_t n_per_row, const float * imatrix);
size_t quantize_q3_K(const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int64_t nrows, int64_t n_per_row, const float * imatrix);
size_t quantize_q4_K(const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int64_t nrows, int64_t n_per_row, const float * imatrix);
size_t quantize_q5_K(const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int64_t nrows, int64_t n_per_row, const float * imatrix);
size_t quantize_q6_K(const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int64_t nrows, int64_t n_per_row, const float * imatrix);
size_t quantize_q4_0(const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int64_t nrows, int64_t n_per_row, const float * imatrix);
size_t quantize_q4_1(const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int64_t nrows, int64_t n_per_row, const float * imatrix);
size_t quantize_q5_0(const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int64_t nrows, int64_t n_per_row, const float * imatrix);
size_t quantize_q5_1(const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int64_t nrows, int64_t n_per_row, const float * imatrix);
size_t quantize_q8_0(const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int64_t nrows, int64_t n_per_row, const float * imatrix);
void iq2xs_init_impl(enum ggml_type type);
void iq2xs_free_impl(enum ggml_type type);
void iq3xs_init_impl(int grid_size);
void iq3xs_free_impl(int grid_size);
#ifdef __cplusplus
}
#endif

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@ -1,49 +0,0 @@
//
// MIT license
// Copyright (C) 2024 Intel Corporation
// SPDX-License-Identifier: MIT
//
#pragma once
#include "ggml.h"
#include "ggml-backend.h"
#ifdef __cplusplus
extern "C" {
#endif
#define GGML_SYCL_MAX_DEVICES 48
#define GGML_SYCL_NAME "SYCL"
// backend API
GGML_API ggml_backend_t ggml_backend_sycl_init(int device);
// devide buffer
GGML_API ggml_backend_buffer_type_t ggml_backend_sycl_buffer_type(int device);
// split tensor buffer that splits matrices by rows across multiple devices
GGML_API GGML_CALL ggml_backend_buffer_type_t ggml_backend_sycl_split_buffer_type(const float * tensor_split);
// pinned host buffer for use with the CPU backend for faster copies between CPU and GPU
GGML_API ggml_backend_buffer_type_t ggml_backend_sycl_host_buffer_type(void);
GGML_API void ggml_backend_sycl_print_sycl_devices(void);
GGML_API GGML_CALL void ggml_sycl_get_gpu_list(int *id_list, int max_len);
GGML_API GGML_CALL void ggml_sycl_get_device_description(int device, char *description, size_t description_size);
GGML_API GGML_CALL int ggml_backend_sycl_get_device_count();
GGML_API GGML_CALL void ggml_backend_sycl_get_device_memory(int device, size_t *free, size_t *total);
GGML_API GGML_CALL int ggml_backend_sycl_get_device_index(int device_id);
// TODO: these are temporary
// ref: https://github.com/ggerganov/llama.cpp/pull/6022#issuecomment-1992615670
GGML_API GGML_CALL int ggml_backend_sycl_get_device_id(int device_index);
GGML_API GGML_CALL void ggml_backend_sycl_set_single_device_mode(int main_gpu_id);
GGML_API GGML_CALL void ggml_backend_sycl_set_mul_device_mode();
// SYCL doesn't support registering host memory, keep here for reference
// GGML_API GGML_CALL bool ggml_backend_sycl_register_host_buffer(void * buffer, size_t size);
// GGML_API GGML_CALL void ggml_backend_sycl_unregister_host_buffer(void * buffer);
#ifdef __cplusplus
}
#endif

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@ -1,29 +0,0 @@
#pragma once
#include "ggml.h"
#include "ggml-backend.h"
#ifdef __cplusplus
extern "C" {
#endif
#define GGML_VK_NAME "Vulkan"
#define GGML_VK_MAX_DEVICES 16
GGML_API void ggml_vk_instance_init(void);
// backend API
GGML_API GGML_CALL ggml_backend_t ggml_backend_vk_init(size_t dev_num);
GGML_API GGML_CALL bool ggml_backend_is_vk(ggml_backend_t backend);
GGML_API GGML_CALL int ggml_backend_vk_get_device_count(void);
GGML_API GGML_CALL void ggml_backend_vk_get_device_description(int device, char * description, size_t description_size);
GGML_API GGML_CALL void ggml_backend_vk_get_device_memory(int device, size_t * free, size_t * total);
GGML_API GGML_CALL ggml_backend_buffer_type_t ggml_backend_vk_buffer_type(size_t dev_num);
// pinned host buffer for use with the CPU backend for faster copies between CPU and GPU
GGML_API GGML_CALL ggml_backend_buffer_type_t ggml_backend_vk_host_buffer_type(void);
#ifdef __cplusplus
}
#endif

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@ -87,7 +87,7 @@ static VALUE ruby_whisper_initialize(int argc, VALUE *argv, VALUE self) {
if (!rb_respond_to(whisper_model_file_path, rb_intern("to_s"))) {
rb_raise(rb_eRuntimeError, "Expected file path to model to initialize Whisper::Context");
}
rw->context = whisper_init_from_file_with_params(StringValueCStr(whisper_model_file_path), whisper_context_default_params());
rw->context = whisper_init_from_file(StringValueCStr(whisper_model_file_path));
if (rw->context == nullptr) {
rb_raise(rb_eRuntimeError, "error: failed to initialize whisper context");
}
@ -311,6 +311,12 @@ static VALUE ruby_whisper_params_get_split_on_word(VALUE self) {
static VALUE ruby_whisper_params_set_split_on_word(VALUE self, VALUE value) {
BOOL_PARAMS_SETTER(self, split_on_word, value)
}
static VALUE ruby_whisper_params_get_speed_up(VALUE self) {
BOOL_PARAMS_GETTER(self, speed_up)
}
static VALUE ruby_whisper_params_set_speed_up(VALUE self, VALUE value) {
BOOL_PARAMS_SETTER(self, speed_up, value)
}
static VALUE ruby_whisper_params_get_diarize(VALUE self) {
ruby_whisper_params *rwp;
Data_Get_Struct(self, ruby_whisper_params, rwp);
@ -402,6 +408,8 @@ void Init_whisper() {
rb_define_method(cParams, "token_timestamps=", ruby_whisper_params_set_token_timestamps, 1);
rb_define_method(cParams, "split_on_word", ruby_whisper_params_get_split_on_word, 0);
rb_define_method(cParams, "split_on_word=", ruby_whisper_params_set_split_on_word, 1);
rb_define_method(cParams, "speed_up", ruby_whisper_params_get_speed_up, 0);
rb_define_method(cParams, "speed_up=", ruby_whisper_params_set_speed_up, 1);
rb_define_method(cParams, "diarize", ruby_whisper_params_get_diarize, 0);
rb_define_method(cParams, "diarize=", ruby_whisper_params_set_diarize, 1);

View File

@ -117,6 +117,13 @@ class TestWhisper < Test::Unit::TestCase
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(File.join(TOPDIR, '..', '..', 'models', 'ggml-base.en.bin'))
params = Whisper::Params.new

View File

@ -1,28 +0,0 @@
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 = ["LICENSE", "README.md", "Rakefile", "ext/extconf.rb", "ext/ggml.c", "ext/ruby_whisper.cpp", "ext/whisper.cpp", "ext/dr_wav.h", "ext/ggml.h", "ext/ruby_whisper.h", "ext/whisper.h"]
#### Load-time details
s.require_paths = ['lib','ext']
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

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

@ -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

@ -22,13 +22,7 @@ struct whisper_coreml_context * whisper_coreml_init(const char * path_model) {
NSURL * url_model = [NSURL fileURLWithPath: path_model_str];
// select which device to run the Core ML model on
MLModelConfiguration *config = [[MLModelConfiguration alloc] init];
// config.computeUnits = MLComputeUnitsCPUAndGPU;
//config.computeUnits = MLComputeUnitsCPUAndNeuralEngine;
config.computeUnits = MLComputeUnitsAll;
const void * data = CFBridgingRetain([[whisper_encoder_impl alloc] initWithContentsOfURL:url_model configuration:config error:nil]);
const void * data = CFBridgingRetain([[whisper_encoder_impl alloc] initWithContentsOfURL:url_model error:nil]);
if (data == NULL) {
return NULL;
@ -48,15 +42,13 @@ 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

@ -14,26 +14,16 @@ if (WHISPER_SDL2)
message(STATUS "SDL2_LIBRARIES = ${SDL2_LIBRARIES}")
endif()
if (WHISPER_CLBLAST)
find_package(CLBlast REQUIRED)
endif()
# common
set(TARGET common)
if (WHISPER_FFMPEG)
set(COMMON_SOURCES_FFMPEG ffmpeg-transcode.cpp)
endif()
add_library(${TARGET} STATIC
common.h
common.cpp
common-ggml.h
common-ggml.cpp
grammar-parser.h
grammar-parser.cpp
${COMMON_SOURCES_FFMPEG}
)
include(DefaultTargetOptions)
@ -41,7 +31,6 @@ include(DefaultTargetOptions)
target_link_libraries(${TARGET} PRIVATE whisper)
set_target_properties(${TARGET} PROPERTIES POSITION_INDEPENDENT_CODE ON)
set_target_properties(${TARGET} PROPERTIES FOLDER "libs")
if (WHISPER_SDL2)
# common-sdl
@ -59,63 +48,27 @@ if (WHISPER_SDL2)
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(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)
add_subdirectory(talk)
set_target_properties(talk PROPERTIES FOLDER "examples")
add_subdirectory(talk-llama)
set_target_properties(talk-llama PROPERTIES FOLDER "examples")
add_subdirectory(lsp)
set_target_properties(lsp PROPERTIES FOLDER "examples")
if (LLAMA_SYCL)
add_subdirectory(sycl)
set_target_properties(sycl 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");
@ -11,13 +11,6 @@ const whisperParamsMock = {
language: "en",
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 +36,6 @@ 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 +43,6 @@ 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 +51,27 @@ 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 +103,8 @@ 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 +140,9 @@ 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;
}
@ -144,24 +153,13 @@ int run(whisper_params &params, std::vector<std::vector<std::string>> &result) {
// 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 * ctx = whisper_init_from_file_with_params(params.model.c_str(), cparams);
struct whisper_context * ctx = whisper_init_from_file(params.model.c_str());
if (ctx == nullptr) {
fprintf(stderr, "error: failed to initialize whisper context\n");
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 +167,20 @@ 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 +189,12 @@ 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 +221,14 @@ 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 +264,8 @@ 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);
}
@ -324,34 +315,10 @@ Napi::Value whisper(const Napi::CallbackInfo& info) {
std::string language = whisper_params.Get("language").As<Napi::String>();
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 +10,14 @@ 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"),
use_gpu: true,
flash_attn: false,
no_prints: true,
comma_in_time: false,
translate: true,
no_timestamps: false,
audio_ctx: 0,
fname_inp: "../../samples/jfk.wav",
};
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 +32,5 @@ 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

@ -23,9 +23,7 @@ void bench_main(size_t index) {
fprintf(stderr, "%s: running benchmark with %d threads - please wait...\n", __func__, n_threads);
const int n_mels = whisper_model_n_mels(ctx);
if (int ret = whisper_set_mel(ctx, nullptr, 0, n_mels)) {
if (int ret = whisper_set_mel(ctx, nullptr, 0, WHISPER_N_MEL)) {
fprintf(stderr, "error: failed to set mel: %d\n", ret);
return;
}
@ -59,7 +57,7 @@ EMSCRIPTEN_BINDINGS(bench) {
emscripten::function("init", emscripten::optional_override([](const std::string & path_model) {
for (size_t i = 0; i < g_contexts.size(); ++i) {
if (g_contexts[i] == nullptr) {
g_contexts[i] = whisper_init_from_file_with_params(path_model.c_str(), whisper_context_default_params());
g_contexts[i] = whisper_init_from_file(path_model.c_str());
if (g_contexts[i] != nullptr) {
if (g_worker.joinable()) {
g_worker.join();

View File

@ -1,19 +1,15 @@
#include "whisper.h"
#include <cstdio>
#include <cstring>
#include <string>
#include <thread>
// 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;
};
void whisper_print_usage(int argc, char ** argv, const whisper_params & params);
@ -26,11 +22,9 @@ 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 {
fprintf(stderr, "error: unknown argument: %s\n", arg.c_str());
whisper_print_usage(argc, argv, params);
@ -50,23 +44,16 @@ void whisper_print_usage(int /*argc*/, char ** argv, const whisper_params & para
fprintf(stderr, " -t N, --threads N [%-7d] number of threads to use during computation\n", params.n_threads);
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 0 - whisper encoder\n", "");
fprintf(stderr, " %-7s 1 - memcpy\n", "");
fprintf(stderr, " %-7s 2 - ggml_mul_mat\n", "");
fprintf(stderr, "\n");
}
int whisper_bench_full(const whisper_params & params) {
int whisper_bench_encoder(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 * ctx = whisper_init_from_file_with_params(params.model.c_str(), cparams);
struct whisper_context * ctx = whisper_init_from_file(params.model.c_str());
{
fprintf(stderr, "\n");
@ -78,65 +65,16 @@ int whisper_bench_full(const whisper_params & params) {
return 2;
}
const int n_mels = whisper_model_n_mels(ctx);
if (int ret = whisper_set_mel(ctx, nullptr, 0, n_mels)) {
if (int ret = whisper_set_mel(ctx, nullptr, 0, WHISPER_N_MEL)) {
fprintf(stderr, "error: failed to set mel: %d\n", ret);
return 3;
}
// 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;
}
whisper_token tokens[512];
memset(tokens, 0, sizeof(tokens));
// prompt heat
if (int ret = whisper_decode(ctx, tokens, 256, 0, params.n_threads) != 0) {
fprintf(stderr, "error: failed to decode: %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);
return 4;
}
whisper_reset_timings(ctx);
// actual run
if (int ret = whisper_encode(ctx, 0, params.n_threads) != 0) {
fprintf(stderr, "error: failed to encode: %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);
return 4;
}
}
whisper_print_timings(ctx);
whisper_free(ctx);
@ -165,7 +103,7 @@ int main(int argc, char ** argv) {
int ret = -1;
switch (params.what) {
case 0: ret = whisper_bench_full(params); break;
case 0: ret = whisper_bench_encoder(params); break;
case 1: ret = whisper_bench_memcpy(params.n_threads); break;
case 2: ret = whisper_bench_ggml_mul_mat(params.n_threads); break;
default: fprintf(stderr, "error: unknown benchmark: %d\n", params.what); break;

View File

@ -243,7 +243,7 @@ EMSCRIPTEN_BINDINGS(command) {
emscripten::function("init", emscripten::optional_override([](const std::string & path_model) {
for (size_t i = 0; i < g_contexts.size(); ++i) {
if (g_contexts[i] == nullptr) {
g_contexts[i] = whisper_init_from_file_with_params(path_model.c_str(), whisper_context_default_params());
g_contexts[i] = whisper_init_from_file(path_model.c_str());
if (g_contexts[i] != nullptr) {
g_running = true;
if (g_worker.joinable()) {

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

@ -6,8 +6,8 @@
// ref: https://github.com/ggerganov/whisper.cpp/issues/171
//
#include "common-sdl.h"
#include "common.h"
#include "common-sdl.h"
#include "whisper.h"
#include "grammar-parser.h"
@ -22,6 +22,11 @@
#include <vector>
#include <map>
bool file_exists(const std::string & fname) {
std::ifstream f(fname.c_str());
return f.good();
}
// command-line parameters
struct whisper_params {
int32_t n_threads = std::min(4, (int32_t) std::thread::hardware_concurrency());
@ -38,12 +43,11 @@ struct whisper_params {
grammar_parser::parse_state grammar_parsed;
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";
@ -52,9 +56,6 @@ struct whisper_params {
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);
@ -75,11 +76,10 @@ 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]; }
@ -88,7 +88,6 @@ bool whisper_params_parse(int argc, char ** argv, whisper_params & params) {
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);
@ -113,11 +112,10 @@ 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());
@ -126,7 +124,6 @@ void whisper_print_usage(int /*argc*/, char ** argv, const whisper_params & para
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");
}
@ -162,6 +159,7 @@ std::string transcribe(
wparams.n_threads = params.n_threads;
wparams.audio_ctx = params.audio_ctx;
wparams.speed_up = params.speed_up;
wparams.temperature = 0.4f;
wparams.temperature_inc = 1.0f;
@ -171,20 +169,14 @@ std::string transcribe(
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.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;
}
if (whisper_full(ctx, wparams, pcmf32.data(), pcmf32.size()) != 0) {
@ -367,6 +359,7 @@ int process_command_list(struct whisper_context * ctx, audio_async &audio, const
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();
@ -693,12 +686,7 @@ 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 * ctx = whisper_init_from_file_with_params(params.model.c_str(), cparams);
struct whisper_context * ctx = whisper_init_from_file(params.model.c_str());
// print some info about the processing
{
@ -738,7 +726,7 @@ int main(int argc, char ** argv) {
if (!params.grammar.empty()) {
auto & grammar = params.grammar_parsed;
if (is_file_exist(params.grammar.c_str())) {
if (file_exists(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>());

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) {
@ -53,25 +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_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;
@ -92,6 +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;
@ -176,39 +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_COUNT:
{
fprintf(stderr, "%s: unsupported quantization type %d (%s)\n", __func__, ttype, ggml_type_name((ggml_type) ttype));
@ -219,7 +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());
@ -232,5 +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();

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

@ -19,16 +19,6 @@
#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
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] != '-') {
@ -48,12 +38,12 @@ bool gpt_params_parse(int argc, char ** argv, gpt_params & params) {
params.seed = std::stoi(get_next_arg(i, argc, argv, arg, params));
} else if (arg == "-t" || arg == "--threads") {
params.n_threads = std::stoi(get_next_arg(i, argc, argv, arg, params));
} else if (arg == "-ngl" || arg == "--gpu-layers" || arg == "--n-gpu-layers") {
params.n_gpu_layers = std::stoi(get_next_arg(i, argc, argv, arg, params));
} else if (arg == "-p" || arg == "--prompt") {
params.prompt = get_next_arg(i, argc, argv, arg, params);
} else if (arg == "-n" || arg == "--n_predict") {
params.n_predict = std::stoi(get_next_arg(i, argc, argv, arg, params));
} else if (arg == "-np" || arg == "--n_parallel") {
params.n_parallel = std::stoi(get_next_arg(i, argc, argv, arg, params));
} else if (arg == "--top_k") {
params.top_k = std::stoi(get_next_arg(i, argc, argv, arg, params));
} else if (arg == "--top_p") {
@ -66,12 +56,6 @@ bool gpt_params_parse(int argc, char ** argv, gpt_params & params) {
params.repeat_penalty = std::stof(get_next_arg(i, argc, argv, arg, params));
} else if (arg == "-b" || arg == "--batch_size") {
params.n_batch= std::stoi(get_next_arg(i, argc, argv, arg, params));
} else if (arg == "-c" || arg == "--context") {
params.n_ctx= std::stoi(get_next_arg(i, argc, argv, arg, params));
} else if (arg == "-ngl" || arg == "--gpu-layers" || arg == "--n-gpu-layers") {
params.n_gpu_layers = std::stoi(get_next_arg(i, argc, argv, arg, params));
} else if (arg == "--ignore-eos") {
params.ignore_eos = true;
} else if (arg == "-m" || arg == "--model") {
params.model = get_next_arg(i, argc, argv, arg, params);
} else if (arg == "-i" || arg == "--interactive") {
@ -113,6 +97,7 @@ void gpt_print_usage(int /*argc*/, char ** argv, const gpt_params & params) {
fprintf(stderr, " -h, --help show this help message and exit\n");
fprintf(stderr, " -s SEED, --seed SEED RNG seed (default: -1)\n");
fprintf(stderr, " -t N, --threads N number of threads to use during computation (default: %d)\n", params.n_threads);
fprintf(stderr, " -ngl N, --gpu-layers N number of layers to offload to GPU on supported models (default: %d)\n", params.n_gpu_layers);
fprintf(stderr, " -p PROMPT, --prompt PROMPT\n");
fprintf(stderr, " prompt to start generation with (default: random)\n");
fprintf(stderr, " -f FNAME, --file FNAME\n");
@ -126,9 +111,6 @@ void gpt_print_usage(int /*argc*/, char ** argv, const gpt_params & params) {
fprintf(stderr, " --repeat-last-n N last n tokens to consider for penalize (default: %d, 0 = disabled)\n", params.repeat_last_n);
fprintf(stderr, " --repeat-penalty N penalize repeat sequence of tokens (default: %.2f, 1.0 = disabled)\n", (double)params.repeat_penalty);
fprintf(stderr, " -b N, --batch_size N batch size for prompt processing (default: %d)\n", params.n_batch);
fprintf(stderr, " -c N, --context N context / KV cache size (default: %d)\n", params.n_ctx);
fprintf(stderr, " --ignore-eos ignore EOS token during generation\n");
fprintf(stderr, " -ngl N, --gpu-layers N number of layers to offload to GPU on supported models (default: %d)\n", params.n_gpu_layers);
fprintf(stderr, " -m FNAME, --model FNAME\n");
fprintf(stderr, " model path (default: %s)\n", params.model.c_str());
fprintf(stderr, "\n");
@ -625,31 +607,12 @@ 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)
{
@ -668,49 +631,28 @@ 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;
}
@ -850,7 +792,7 @@ bool sam_params_parse(int argc, char ** argv, sam_params & params) {
return true;
}
void sam_print_usage(int /*argc*/, char ** argv, const sam_params & params) {
void sam_print_usage(int argc, char ** argv, const sam_params & params) {
fprintf(stderr, "usage: %s [options]\n", argv[0]);
fprintf(stderr, "\n");
fprintf(stderr, "options:\n");
@ -865,48 +807,3 @@ 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

@ -7,8 +7,6 @@
#include <vector>
#include <random>
#include <thread>
#include <ctime>
#include <fstream>
#define COMMON_SAMPLE_RATE 16000
@ -17,15 +15,10 @@
//
struct gpt_params {
int32_t seed = -1; // RNG seed
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 = 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
bool ignore_eos = false; // ignore EOS token when generating text
int32_t seed = -1; // RNG seed
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_batch = 8; // batch size for prompt processing
// sampling parameters
int32_t top_k = 40;
@ -40,6 +33,8 @@ struct gpt_params {
bool interactive = false;
int32_t interactive_port = -1;
int32_t n_gpu_layers = 0;
};
bool gpt_params_parse(int argc, char ** argv, gpt_params & params);
@ -135,11 +130,7 @@ 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(
@ -148,104 +139,6 @@ bool read_wav(
std::vector<std::vector<float>> & pcmf32s,
bool stereo);
// Write PCM data into WAV audio file
class wav_writer {
private:
std::ofstream file;
uint32_t dataSize = 0;
std::string wav_filename;
bool write_header(const uint32_t sample_rate,
const uint16_t bits_per_sample,
const uint16_t channels) {
file.write("RIFF", 4);
file.write("\0\0\0\0", 4); // Placeholder for file size
file.write("WAVE", 4);
file.write("fmt ", 4);
const uint32_t sub_chunk_size = 16;
const uint16_t audio_format = 1; // PCM format
const uint32_t byte_rate = sample_rate * channels * bits_per_sample / 8;
const uint16_t block_align = channels * bits_per_sample / 8;
file.write(reinterpret_cast<const char *>(&sub_chunk_size), 4);
file.write(reinterpret_cast<const char *>(&audio_format), 2);
file.write(reinterpret_cast<const char *>(&channels), 2);
file.write(reinterpret_cast<const char *>(&sample_rate), 4);
file.write(reinterpret_cast<const char *>(&byte_rate), 4);
file.write(reinterpret_cast<const char *>(&block_align), 2);
file.write(reinterpret_cast<const char *>(&bits_per_sample), 2);
file.write("data", 4);
file.write("\0\0\0\0", 4); // Placeholder for data size
return true;
}
// 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);
file.write(reinterpret_cast<const char *>(&intSample), sizeof(int16_t));
dataSize += sizeof(int16_t);
}
if (file.is_open()) {
file.seekp(4, std::ios::beg);
uint32_t fileSize = 36 + dataSize;
file.write(reinterpret_cast<char *>(&fileSize), 4);
file.seekp(40, std::ios::beg);
file.write(reinterpret_cast<char *>(&dataSize), 4);
file.seekp(0, std::ios::end);
}
return true;
}
bool open_wav(const std::string & filename) {
if (filename != wav_filename) {
if (file.is_open()) {
file.close();
}
}
if (!file.is_open()) {
file.open(filename, std::ios::binary);
wav_filename = filename;
dataSize = 0;
}
return file.is_open();
}
public:
bool open(const std::string & filename,
const uint32_t sample_rate,
const uint16_t bits_per_sample,
const uint16_t channels) {
if (open_wav(filename)) {
write_header(sample_rate, bits_per_sample, channels);
} else {
return false;
}
return true;
}
bool close() {
file.close();
return true;
}
bool write(const float * data, size_t length) {
return write_audio(data, length);
}
~wav_writer() {
if (file.is_open()) {
file.close();
}
}
};
// Apply a high-pass frequency filter to PCM audio
// Suppresses frequencies below cutoff Hz
void high_pass_filter(
@ -281,31 +174,3 @@ 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
//
// Terminal color map. 10 colors grouped in ranges [0.0, 0.1, ..., 0.9]
// Lowest is red, middle is yellow, highest is green.
const std::vector<std::string> k_colors = {
"\033[38;5;196m", "\033[38;5;202m", "\033[38;5;208m", "\033[38;5;214m", "\033[38;5;220m",
"\033[38;5;226m", "\033[38;5;190m", "\033[38;5;154m", "\033[38;5;118m", "\033[38;5;82m",
};
//
// 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);

View File

@ -1,350 +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];
av_register_all(); // from avformat. Still a must-have call for ffmpeg v3! (can be skipped for later versions)
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: %x size: %d\n", ibuf, 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

@ -190,7 +190,7 @@ namespace grammar_parser {
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);
throw std::runtime_error(std::string("expecting preceeding item to */+/? at ") + pos);
}
// apply transformation to previous symbol (last_sym_start to end) according to

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" )
models=( "tiny.en" "tiny" "base.en" "base" "small.en" "small" "medium.en" "medium" "large-v1" "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 +26,10 @@ 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";
@ -69,11 +68,10 @@ 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 {
@ -100,11 +98,10 @@ 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");
@ -181,6 +178,7 @@ json unguided_transcription(struct whisper_context * ctx, audio_async &audio, js
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) {
@ -219,6 +217,7 @@ json guided_transcription(struct whisper_context * ctx, audio_async &audio, cons
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
@ -325,12 +324,12 @@ json register_commandset(struct whisper_context * ctx, json jparams, std::vector
commandset_list.push_back(cs);
return json{{"index",index}};
}
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,
// but for now, it's unsupported
throw json {
throw json{
{"code", -32601},
{"message", "Seeking is not yet supported."}
};
@ -413,7 +412,7 @@ void process_loop(struct whisper_context * ctx, audio_async &audio, const whispe
jobqueue.pop_front();
// send response
std::string data = resp.dump(-1, ' ', false, json::error_handler_t::replace);
fprintf(stdout, "Content-Length: %d\r\n\r\n%s\n", (int)data.length()+1, data.c_str());
fprintf(stdout, "Content-Length: %d\r\n\r\n%s\n", data.length()+1, data.c_str());
std::cout.flush();
}
@ -433,12 +432,7 @@ 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 * ctx = whisper_init_from_file_with_params(params.model.c_str(), cparams);
struct whisper_context * ctx = whisper_init_from_file(params.model.c_str());
// init audio
audio_async audio(30*1000);

View File

@ -3,4 +3,4 @@ add_executable(${TARGET} main.cpp)
include(DefaultTargetOptions)
target_link_libraries(${TARGET} PRIVATE common whisper ${FFMPEG_LIBRARIES} ${CMAKE_THREAD_LIBS_INIT})
target_link_libraries(${TARGET} PRIVATE common whisper ${CMAKE_THREAD_LIBS_INIT})

View File

@ -17,37 +17,28 @@ options:
-d N, --duration N [0 ] duration of audio to process in milliseconds
-mc N, --max-context N [-1 ] maximum number of text context tokens to store
-ml N, --max-len N [0 ] maximum segment length in characters
-sow, --split-on-word [false ] split on word rather than on token
-bo N, --best-of N [5 ] number of best candidates to keep
-bs N, --beam-size N [5 ] beam size for beam search
-bs N, --beam-size N [-1 ] beam size for beam search
-wt N, --word-thold N [0.01 ] word timestamp probability threshold
-et N, --entropy-thold N [2.40 ] entropy threshold for decoder fail
-lpt N, --logprob-thold N [-1.00 ] log probability threshold for decoder fail
-debug, --debug-mode [false ] enable debug mode (eg. dump log_mel)
-su, --speed-up [false ] speed up audio by x2 (reduced accuracy)
-tr, --translate [false ] translate from source language to english
-di, --diarize [false ] stereo audio diarization
-tdrz, --tinydiarize [false ] enable tinydiarize (requires a tdrz model)
-nf, --no-fallback [false ] do not use temperature fallback while decoding
-otxt, --output-txt [false ] output result in a text file
-ovtt, --output-vtt [false ] output result in a vtt file
-osrt, --output-srt [false ] output result in a srt file
-olrc, --output-lrc [false ] output result in a lrc file
-owts, --output-words [false ] output script for generating karaoke video
-fp, --font-path [/System/Library/Fonts/Supplemental/Courier New Bold.ttf] path to a monospace font for karaoke video
-ocsv, --output-csv [false ] output result in a CSV file
-oj, --output-json [false ] output result in a JSON file
-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
-pp, --print-progress [false ] print progress
-nt, --no-timestamps [false ] do not print timestamps
-nt, --no-timestamps [true ] do not print timestamps
-l LANG, --language LANG [en ] spoken language ('auto' for auto-detect)
-dl, --detect-language [false ] exit after automatically detecting language
--prompt PROMPT [ ] initial prompt
-m FNAME, --model FNAME [models/ggml-base.en.bin] model path
-f FNAME, --file FNAME [ ] input WAV file path
-oved D, --ov-e-device DNAME [CPU ] the OpenVINO device used for encode inference
-ls, --log-score [false ] log best decoder scores of tokens
-ng, --no-gpu [false ] disable GPU
```

View File

@ -1,12 +1,10 @@
#include "common.h"
#include "whisper.h"
#include "grammar-parser.h"
#include <cmath>
#include <fstream>
#include <cstdio>
#include <regex>
#include <string>
#include <thread>
#include <vector>
@ -16,6 +14,34 @@
#pragma warning(disable: 4244 4267) // possible loss of data
#endif
// Terminal color map. 10 colors grouped in ranges [0.0, 0.1, ..., 0.9]
// Lowest is red, middle is yellow, highest is green.
const std::vector<std::string> k_colors = {
"\033[38;5;196m", "\033[38;5;202m", "\033[38;5;208m", "\033[38;5;214m", "\033[38;5;220m",
"\033[38;5;226m", "\033[38;5;190m", "\033[38;5;154m", "\033[38;5;118m", "\033[38;5;82m",
};
// 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)));
}
// helper function to replace substrings
void replace_all(std::string & s, const std::string & search, const std::string & replace) {
for (size_t pos = 0; ; pos += replace.length()) {
@ -28,25 +54,22 @@ void replace_all(std::string & s, const std::string & search, const std::string
// command-line parameters
struct whisper_params {
int32_t n_threads = std::min(4, (int32_t) std::thread::hardware_concurrency());
int32_t n_processors = 1;
int32_t offset_t_ms = 0;
int32_t offset_n = 0;
int32_t duration_ms = 0;
int32_t progress_step = 5;
int32_t max_context = -1;
int32_t max_len = 0;
int32_t best_of = whisper_full_default_params(WHISPER_SAMPLING_GREEDY).greedy.best_of;
int32_t beam_size = whisper_full_default_params(WHISPER_SAMPLING_BEAM_SEARCH).beam_search.beam_size;
int32_t audio_ctx = 0;
int32_t n_threads = std::min(4, (int32_t) std::thread::hardware_concurrency());
int32_t n_processors = 1;
int32_t offset_t_ms = 0;
int32_t offset_n = 0;
int32_t duration_ms = 0;
int32_t progress_step = 5;
int32_t max_context = -1;
int32_t max_len = 0;
int32_t best_of = 2;
int32_t beam_size = -1;
float word_thold = 0.01f;
float entropy_thold = 2.40f;
float logprob_thold = -1.00f;
float grammar_penalty = 100.0f;
float temperature = 0.0f;
float temperature_inc = 0.2f;
float word_thold = 0.01f;
float entropy_thold = 2.40f;
float logprob_thold = -1.00f;
bool speed_up = false;
bool debug_mode = false;
bool translate = false;
bool detect_language = false;
@ -60,50 +83,29 @@ struct whisper_params {
bool output_wts = false;
bool output_csv = false;
bool output_jsn = false;
bool output_jsn_full = false;
bool output_lrc = false;
bool no_prints = false;
bool print_special = false;
bool print_colors = false;
bool print_progress = false;
bool no_timestamps = false;
bool log_score = false;
bool use_gpu = true;
bool flash_attn = false;
std::string language = "en";
std::string prompt;
std::string font_path = "/System/Library/Fonts/Supplemental/Courier New Bold.ttf";
std::string model = "models/ggml-base.en.bin";
std::string grammar;
std::string grammar_rule;
// [TDRZ] speaker turn string
std::string tdrz_speaker_turn = " [SPEAKER_TURN]"; // TODO: set from command line
// A regular expression that matches tokens to suppress
std::string suppress_regex;
std::string openvino_encode_device = "CPU";
std::string dtw = "";
std::vector<std::string> fname_inp = {};
std::vector<std::string> fname_out = {};
grammar_parser::parse_state grammar_parsed;
};
void whisper_print_usage(int argc, char ** argv, const whisper_params & params);
char* whisper_param_turn_lowercase(char* in){
int string_len = strlen(in);
for(int i = 0; i < string_len; i++){
*(in+i) = tolower((unsigned char)*(in+i));
}
return in;
}
bool whisper_params_parse(int argc, char ** argv, whisper_params & params) {
for (int i = 1; i < argc; i++) {
std::string arg = argv[i];
@ -131,12 +133,10 @@ bool whisper_params_parse(int argc, char ** argv, whisper_params & params) {
else if (arg == "-ml" || arg == "--max-len") { params.max_len = std::stoi(argv[++i]); }
else if (arg == "-bo" || arg == "--best-of") { params.best_of = std::stoi(argv[++i]); }
else if (arg == "-bs" || arg == "--beam-size") { params.beam_size = std::stoi(argv[++i]); }
else if (arg == "-ac" || arg == "--audio-ctx") { params.audio_ctx = std::stoi(argv[++i]); }
else if (arg == "-wt" || arg == "--word-thold") { params.word_thold = std::stof(argv[++i]); }
else if (arg == "-et" || arg == "--entropy-thold") { params.entropy_thold = std::stof(argv[++i]); }
else if (arg == "-lpt" || arg == "--logprob-thold") { params.logprob_thold = std::stof(argv[++i]); }
else if (arg == "-tp" || arg == "--temperature") { params.temperature = std::stof(argv[++i]); }
else if (arg == "-tpi" || arg == "--temperature-inc") { params.temperature_inc = std::stof(argv[++i]); }
// else if (arg == "-su" || arg == "--speed-up") { params.speed_up = true; }
else if (arg == "-debug"|| arg == "--debug-mode") { params.debug_mode = true; }
else if (arg == "-tr" || arg == "--translate") { params.translate = true; }
else if (arg == "-di" || arg == "--diarize") { params.diarize = true; }
@ -151,27 +151,18 @@ bool whisper_params_parse(int argc, char ** argv, whisper_params & params) {
else if (arg == "-fp" || arg == "--font-path") { params.font_path = argv[++i]; }
else if (arg == "-ocsv" || arg == "--output-csv") { params.output_csv = true; }
else if (arg == "-oj" || arg == "--output-json") { params.output_jsn = true; }
else if (arg == "-ojf" || arg == "--output-json-full"){ params.output_jsn_full = params.output_jsn = true; }
else if (arg == "-of" || arg == "--output-file") { params.fname_out.emplace_back(argv[++i]); }
else if (arg == "-np" || arg == "--no-prints") { params.no_prints = true; }
else if (arg == "-ps" || arg == "--print-special") { params.print_special = true; }
else if (arg == "-pc" || arg == "--print-colors") { params.print_colors = true; }
else if (arg == "-pp" || arg == "--print-progress") { params.print_progress = true; }
else if (arg == "-nt" || arg == "--no-timestamps") { params.no_timestamps = true; }
else if (arg == "-l" || arg == "--language") { params.language = whisper_param_turn_lowercase(argv[++i]); }
else if (arg == "-l" || arg == "--language") { params.language = argv[++i]; }
else if (arg == "-dl" || arg == "--detect-language") { params.detect_language = true; }
else if ( arg == "--prompt") { params.prompt = argv[++i]; }
else if (arg == "-m" || arg == "--model") { params.model = argv[++i]; }
else if (arg == "-f" || arg == "--file") { params.fname_inp.emplace_back(argv[++i]); }
else if (arg == "-oved" || arg == "--ov-e-device") { params.openvino_encode_device = argv[++i]; }
else if (arg == "-dtw" || arg == "--dtw") { params.dtw = argv[++i]; }
else if (arg == "-ls" || arg == "--log-score") { params.log_score = 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 == "--suppress-regex") { params.suppress_regex = argv[++i]; }
else if ( arg == "--grammar") { params.grammar = argv[++i]; }
else if ( arg == "--grammar-rule") { params.grammar_rule = argv[++i]; }
else if ( arg == "--grammar-penalty") { params.grammar_penalty = std::stof(argv[++i]); }
else if (arg == "-ls" || arg == "--log-score") { params.log_score = true; }
else {
fprintf(stderr, "error: unknown argument: %s\n", arg.c_str());
whisper_print_usage(argc, argv, params);
@ -198,12 +189,10 @@ void whisper_print_usage(int /*argc*/, char ** argv, const whisper_params & para
fprintf(stderr, " -sow, --split-on-word [%-7s] split on word rather than on token\n", params.split_on_word ? "true" : "false");
fprintf(stderr, " -bo N, --best-of N [%-7d] number of best candidates to keep\n", params.best_of);
fprintf(stderr, " -bs N, --beam-size N [%-7d] beam size for beam search\n", params.beam_size);
fprintf(stderr, " -ac N, --audio-ctx N [%-7d] audio context size (0 - all)\n", params.audio_ctx);
fprintf(stderr, " -wt N, --word-thold N [%-7.2f] word timestamp probability threshold\n", params.word_thold);
fprintf(stderr, " -et N, --entropy-thold N [%-7.2f] entropy threshold for decoder fail\n", params.entropy_thold);
fprintf(stderr, " -lpt N, --logprob-thold N [%-7.2f] log probability threshold for decoder fail\n", params.logprob_thold);
fprintf(stderr, " -tp, --temperature N [%-7.2f] The sampling temperature, between 0 and 1\n", params.temperature);
fprintf(stderr, " -tpi, --temperature-inc N [%-7.2f] The increment of temperature, between 0 and 1\n",params.temperature_inc);
// fprintf(stderr, " -su, --speed-up [%-7s] speed up audio by x2 (reduced accuracy)\n", params.speed_up ? "true" : "false");
fprintf(stderr, " -debug, --debug-mode [%-7s] enable debug mode (eg. dump log_mel)\n", params.debug_mode ? "true" : "false");
fprintf(stderr, " -tr, --translate [%-7s] translate from source language to english\n", params.translate ? "true" : "false");
fprintf(stderr, " -di, --diarize [%-7s] stereo audio diarization\n", params.diarize ? "true" : "false");
@ -217,27 +206,18 @@ void whisper_print_usage(int /*argc*/, char ** argv, const whisper_params & para
fprintf(stderr, " -fp, --font-path [%-7s] path to a monospace font for karaoke video\n", params.font_path.c_str());
fprintf(stderr, " -ocsv, --output-csv [%-7s] output result in a CSV file\n", params.output_csv ? "true" : "false");
fprintf(stderr, " -oj, --output-json [%-7s] output result in a JSON file\n", params.output_jsn ? "true" : "false");
fprintf(stderr, " -ojf, --output-json-full [%-7s] include more information in the JSON file\n", params.output_jsn_full ? "true" : "false");
fprintf(stderr, " -of FNAME, --output-file FNAME [%-7s] output file path (without file extension)\n", "");
fprintf(stderr, " -np, --no-prints [%-7s] do not print anything other than the results\n", params.no_prints ? "true" : "false");
fprintf(stderr, " -ps, --print-special [%-7s] print special tokens\n", params.print_special ? "true" : "false");
fprintf(stderr, " -pc, --print-colors [%-7s] print colors\n", params.print_colors ? "true" : "false");
fprintf(stderr, " -pp, --print-progress [%-7s] print progress\n", params.print_progress ? "true" : "false");
fprintf(stderr, " -nt, --no-timestamps [%-7s] do not print timestamps\n", params.no_timestamps ? "true" : "false");
fprintf(stderr, " -l LANG, --language LANG [%-7s] spoken language ('auto' for auto-detect)\n", params.language.c_str());
fprintf(stderr, " -dl, --detect-language [%-7s] exit after automatically detecting language\n", params.detect_language ? "true" : "false");
fprintf(stderr, " --prompt PROMPT [%-7s] initial prompt (max n_text_ctx/2 tokens)\n", params.prompt.c_str());
fprintf(stderr, " --prompt PROMPT [%-7s] initial prompt\n", params.prompt.c_str());
fprintf(stderr, " -m FNAME, --model FNAME [%-7s] model path\n", params.model.c_str());
fprintf(stderr, " -f FNAME, --file FNAME [%-7s] input WAV file path\n", "");
fprintf(stderr, " -oved D, --ov-e-device DNAME [%-7s] the OpenVINO device used for encode inference\n", params.openvino_encode_device.c_str());
fprintf(stderr, " -dtw MODEL --dtw MODEL [%-7s] compute token-level timestamps\n", params.dtw.c_str());
fprintf(stderr, " -ls, --log-score [%-7s] log best decoder scores of tokens\n", params.log_score?"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, " --suppress-regex REGEX [%-7s] regular expression matching tokens to suppress\n", params.suppress_regex.c_str());
fprintf(stderr, " --grammar GRAMMAR [%-7s] GBNF grammar to guide decoding\n", params.grammar.c_str());
fprintf(stderr, " --grammar-rule RULE [%-7s] top-level GBNF grammar rule name\n", params.grammar_rule.c_str());
fprintf(stderr, " --grammar-penalty N [%-7.1f] scales down logits of nongrammar tokens\n", params.grammar_penalty);
fprintf(stderr, "\n");
}
@ -252,8 +232,8 @@ std::string estimate_diarization_speaker(std::vector<std::vector<float>> pcmf32s
std::string speaker = "";
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;
@ -280,7 +260,7 @@ std::string estimate_diarization_speaker(std::vector<std::vector<float>> pcmf32s
return speaker;
}
void whisper_print_progress_callback(struct whisper_context * /*ctx*/, struct whisper_state * /*state*/, int progress, void * user_data) {
void whisper_print_progress_callback(struct whisper_context * ctx, struct whisper_state * /*state*/, int progress, void * user_data) {
int progress_step = ((whisper_print_user_data *) user_data)->params->progress_step;
int * progress_prev = &(((whisper_print_user_data *) user_data)->progress_prev);
if (progress >= *progress_prev + progress_step) {
@ -477,38 +457,6 @@ char *escape_double_quotes_and_backslashes(const char *str) {
return escaped;
}
// double quote should be escaped by another double quote. (rfc4180)
char *escape_double_quotes_in_csv(const char *str) {
if (str == NULL) {
return NULL;
}
size_t escaped_length = strlen(str) + 1;
for (size_t i = 0; str[i] != '\0'; i++) {
if (str[i] == '"') {
escaped_length++;
}
}
char *escaped = (char *)calloc(escaped_length, 1); // pre-zeroed
if (escaped == NULL) {
return NULL;
}
size_t pos = 0;
for (size_t i = 0; str[i] != '\0'; i++) {
if (str[i] == '"') {
escaped[pos++] = '"';
}
escaped[pos++] = str[i];
}
// no need to set zero due to calloc() being used prior
return escaped;
}
bool output_csv(struct whisper_context * ctx, const char * fname, const whisper_params & params, std::vector<std::vector<float>> pcmf32s) {
std::ofstream fout(fname);
if (!fout.is_open()) {
@ -530,7 +478,7 @@ bool output_csv(struct whisper_context * ctx, const char * fname, const whisper_
const char * text = whisper_full_get_segment_text(ctx, i);
const int64_t t0 = whisper_full_get_segment_t0(ctx, i);
const int64_t t1 = whisper_full_get_segment_t1(ctx, i);
char * text_escaped = escape_double_quotes_in_csv(text);
char * text_escaped = escape_double_quotes_and_backslashes(text);
//need to multiply times returned from whisper_full_get_segment_t{0,1}() by 10 to get milliseconds.
fout << 10 * t0 << "," << 10 * t1 << ",";
@ -544,7 +492,7 @@ bool output_csv(struct whisper_context * ctx, const char * fname, const whisper_
return true;
}
bool output_score(struct whisper_context * ctx, const char * fname, const whisper_params & /*params*/, std::vector<std::vector<float>> /*pcmf32s*/) {
bool output_score(struct whisper_context * ctx, const char * fname, const whisper_params & params, std::vector<std::vector<float>> pcmf32s) {
std::ofstream fout(fname);
fprintf(stderr, "%s: saving output to '%s'\n", __func__, fname);
@ -563,12 +511,7 @@ bool output_score(struct whisper_context * ctx, const char * fname, const whispe
return true;
}
bool output_json(
struct whisper_context * ctx,
const char * fname,
const whisper_params & params,
std::vector<std::vector<float>> pcmf32s,
bool full) {
bool output_json(struct whisper_context * ctx, const char * fname, const whisper_params & params, std::vector<std::vector<float>> pcmf32s) {
std::ofstream fout(fname);
int indent = 0;
@ -585,7 +528,7 @@ bool output_json(
auto end_arr = [&](bool end) {
indent--;
doindent();
fout << (end ? "]\n" : "],\n");
fout << (end ? "]\n" : "},\n");
};
auto start_obj = [&](const char *name) {
@ -626,29 +569,12 @@ bool output_json(
end_value(end);
};
auto value_f = [&](const char *name, const float val, bool end) {
start_value(name);
fout << val;
end_value(end);
};
auto value_b = [&](const char *name, const bool val, bool end) {
start_value(name);
fout << (val ? "true" : "false");
end_value(end);
};
auto times_o = [&](int64_t t0, int64_t t1, bool end) {
start_obj("timestamps");
value_s("from", to_timestamp(t0, true).c_str(), false);
value_s("to", to_timestamp(t1, true).c_str(), true);
end_obj(false);
start_obj("offsets");
value_i("from", t0 * 10, false);
value_i("to", t1 * 10, true);
end_obj(end);
};
if (!fout.is_open()) {
fprintf(stderr, "%s: failed to open '%s' for writing\n", __func__, fname);
return false;
@ -694,27 +620,15 @@ bool output_json(
const int64_t t1 = whisper_full_get_segment_t1(ctx, i);
start_obj(nullptr);
times_o(t0, t1, false);
value_s("text", text, !params.diarize && !params.tinydiarize && !full);
if (full) {
start_arr("tokens");
const int n = whisper_full_n_tokens(ctx, i);
for (int j = 0; j < n; ++j) {
auto token = whisper_full_get_token_data(ctx, i, j);
start_obj(nullptr);
value_s("text", whisper_token_to_str(ctx, token.id), false);
if(token.t0 > -1 && token.t1 > -1) {
// If we have per-token timestamps, write them out
times_o(token.t0, token.t1, false);
}
value_i("id", token.id, false);
value_f("p", token.p, false);
value_f("t_dtw", token.t_dtw, true);
end_obj(j == (n - 1));
}
end_arr(!params.diarize && !params.tinydiarize);
}
start_obj("timestamps");
value_s("from", to_timestamp(t0, true).c_str(), false);
value_s("to", to_timestamp(t1, true).c_str(), true);
end_obj(false);
start_obj("offsets");
value_i("from", t0 * 10, false);
value_i("to", t1 * 10, true);
end_obj(false);
value_s("text", text, !params.diarize && !params.tinydiarize);
if (params.diarize && pcmf32s.size() == 2) {
value_s("speaker", estimate_diarization_speaker(pcmf32s, t0, t1, true).c_str(), true);
@ -899,59 +813,14 @@ bool output_lrc(struct whisper_context * ctx, const char * fname, const whisper_
return true;
}
void cb_log_disable(enum ggml_log_level , const char * , void * ) { }
int main(int argc, char ** argv) {
whisper_params params;
// If the only argument starts with "@", read arguments line-by-line
// from the given file.
std::vector<std::string> vec_args;
if (argc == 2 && argv != nullptr && argv[1] != nullptr && argv[1][0] == '@') {
// Save the name of the executable.
vec_args.push_back(argv[0]);
// Open the response file.
char const * rspfile = argv[1] + sizeof(char);
std::ifstream fin(rspfile);
if (fin.is_open() == false) {
fprintf(stderr, "error: response file '%s' not found\n", rspfile);
return 1;
}
// Read the entire response file.
std::string line;
while (std::getline(fin, line)) {
vec_args.push_back(line);
}
// Use the contents of the response file as the command-line arguments.
argc = static_cast<int>(vec_args.size());
argv = static_cast<char **>(alloca(argc * sizeof (char *)));
for (int i = 0; i < argc; ++i) {
argv[i] = const_cast<char *>(vec_args[i].c_str());
}
}
if (whisper_params_parse(argc, argv, params) == false) {
whisper_print_usage(argc, argv, params);
return 1;
}
// remove non-existent files
for (auto it = params.fname_inp.begin(); it != params.fname_inp.end();) {
const auto fname_inp = it->c_str();
if (*it != "-" && !is_file_exist(fname_inp)) {
fprintf(stderr, "error: input file not found '%s'\n", fname_inp);
it = params.fname_inp.erase(it);
continue;
}
it++;
}
if (params.fname_inp.empty()) {
fprintf(stderr, "error: no input files specified\n");
whisper_print_usage(argc, argv, params);
@ -970,40 +839,9 @@ int main(int argc, char ** argv) {
exit(0);
}
if (params.no_prints) {
whisper_log_set(cb_log_disable, NULL);
}
// whisper init
struct whisper_context_params cparams = whisper_context_default_params();
cparams.use_gpu = params.use_gpu;
cparams.flash_attn = params.flash_attn;
if (!params.dtw.empty()) {
cparams.dtw_token_timestamps = true;
cparams.dtw_aheads_preset = WHISPER_AHEADS_NONE;
if (params.dtw == "tiny") cparams.dtw_aheads_preset = WHISPER_AHEADS_TINY;
if (params.dtw == "tiny.en") cparams.dtw_aheads_preset = WHISPER_AHEADS_TINY_EN;
if (params.dtw == "base") cparams.dtw_aheads_preset = WHISPER_AHEADS_BASE;
if (params.dtw == "base.en") cparams.dtw_aheads_preset = WHISPER_AHEADS_BASE_EN;
if (params.dtw == "small") cparams.dtw_aheads_preset = WHISPER_AHEADS_SMALL;
if (params.dtw == "small.en") cparams.dtw_aheads_preset = WHISPER_AHEADS_SMALL_EN;
if (params.dtw == "medium") cparams.dtw_aheads_preset = WHISPER_AHEADS_MEDIUM;
if (params.dtw == "medium.en") cparams.dtw_aheads_preset = WHISPER_AHEADS_MEDIUM_EN;
if (params.dtw == "large.v1") cparams.dtw_aheads_preset = WHISPER_AHEADS_LARGE_V1;
if (params.dtw == "large.v2") cparams.dtw_aheads_preset = WHISPER_AHEADS_LARGE_V2;
if (params.dtw == "large.v3") cparams.dtw_aheads_preset = WHISPER_AHEADS_LARGE_V3;
if (cparams.dtw_aheads_preset == WHISPER_AHEADS_NONE) {
fprintf(stderr, "error: unknown DTW preset '%s'\n", params.dtw.c_str());
return 3;
}
}
struct whisper_context * ctx = whisper_init_from_file_with_params(params.model.c_str(), cparams);
struct whisper_context * ctx = whisper_init_from_file(params.model.c_str());
if (ctx == nullptr) {
fprintf(stderr, "error: failed to initialize whisper context\n");
@ -1013,29 +851,6 @@ int main(int argc, char ** argv) {
// initialize openvino encoder. this has no effect on whisper.cpp builds that don't have OpenVINO configured
whisper_ctx_init_openvino_encoder(ctx, nullptr, params.openvino_encode_device.c_str(), nullptr);
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()) {
fprintf(stderr, "error: failed to parse grammar \"%s\"\n", params.grammar.c_str());
return 4;
} else {
fprintf(stderr, "%s: grammar:\n", __func__);
grammar_parser::print_grammar(stderr, grammar);
fprintf(stderr, "\n");
}
}
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];
@ -1048,28 +863,29 @@ int main(int argc, char ** argv) {
continue;
}
if (!whisper_is_multilingual(ctx)) {
if (params.language != "en" || params.translate) {
params.language = "en";
params.translate = false;
fprintf(stderr, "%s: WARNING: model is not multilingual, ignoring language and translation options\n", __func__);
}
}
if (params.detect_language) {
params.language = "auto";
}
if (!params.no_prints) {
// print system information
// print system information
{
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
// print some info about the processing
{
fprintf(stderr, "\n");
fprintf(stderr, "%s: processing '%s' (%d samples, %.1f sec), %d threads, %d processors, %d beams + best of %d, lang = %s, task = %s, %stimestamps = %d ...\n",
if (!whisper_is_multilingual(ctx)) {
if (params.language != "en" || params.translate) {
params.language = "en";
params.translate = false;
fprintf(stderr, "%s: WARNING: model is not multilingual, ignoring language and translation options\n", __func__);
}
}
if (params.detect_language) {
params.language = "auto";
}
fprintf(stderr, "%s: processing '%s' (%d samples, %.1f sec), %d threads, %d processors, lang = %s, task = %s, %stimestamps = %d ...\n",
__func__, fname_inp.c_str(), int(pcmf32.size()), float(pcmf32.size())/WHISPER_SAMPLE_RATE,
params.n_threads, params.n_processors, params.beam_size, params.best_of,
params.n_threads, params.n_processors,
params.language.c_str(),
params.translate ? "translate" : "transcribe",
params.tinydiarize ? "tdrz = 1, " : "",
@ -1082,8 +898,7 @@ int main(int argc, char ** argv) {
{
whisper_full_params wparams = whisper_full_default_params(WHISPER_SAMPLING_GREEDY);
const bool use_grammar = (!params.grammar_parsed.rules.empty() && !params.grammar_rule.empty());
wparams.strategy = (params.beam_size > 1 || use_grammar) ? WHISPER_SAMPLING_BEAM_SEARCH : WHISPER_SAMPLING_GREEDY;
wparams.strategy = params.beam_size > 1 ? WHISPER_SAMPLING_BEAM_SEARCH : WHISPER_SAMPLING_GREEDY;
wparams.print_realtime = false;
wparams.print_progress = params.print_progress;
@ -1097,47 +912,27 @@ int main(int argc, char ** argv) {
wparams.offset_ms = params.offset_t_ms;
wparams.duration_ms = params.duration_ms;
wparams.token_timestamps = params.output_wts || params.output_jsn_full || params.max_len > 0;
wparams.token_timestamps = params.output_wts || params.max_len > 0;
wparams.thold_pt = params.word_thold;
wparams.max_len = params.output_wts && params.max_len == 0 ? 60 : params.max_len;
wparams.split_on_word = params.split_on_word;
wparams.audio_ctx = params.audio_ctx;
wparams.speed_up = params.speed_up;
wparams.debug_mode = params.debug_mode;
wparams.tdrz_enable = params.tinydiarize; // [TDRZ]
wparams.suppress_regex = params.suppress_regex.empty() ? nullptr : params.suppress_regex.c_str();
wparams.initial_prompt = params.prompt.c_str();
wparams.greedy.best_of = params.best_of;
wparams.beam_search.beam_size = params.beam_size;
wparams.temperature_inc = params.no_fallback ? 0.0f : params.temperature_inc;
wparams.temperature = params.temperature;
wparams.temperature_inc = params.no_fallback ? 0.0f : wparams.temperature_inc;
wparams.entropy_thold = params.entropy_thold;
wparams.logprob_thold = params.logprob_thold;
wparams.no_timestamps = params.no_timestamps;
whisper_print_user_data user_data = { &params, &pcmf32s, 0 };
const auto & grammar_parsed = params.grammar_parsed;
auto grammar_rules = grammar_parsed.c_rules();
if (use_grammar) {
if (grammar_parsed.symbol_ids.find(params.grammar_rule) == grammar_parsed.symbol_ids.end()) {
fprintf(stderr, "%s: warning: grammar rule '%s' not found - skipping grammar sampling\n", __func__, params.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(params.grammar_rule);
wparams.grammar_penalty = params.grammar_penalty;
}
}
// this callback is called on each new segment
if (!wparams.print_realtime) {
wparams.new_segment_callback = whisper_print_segment_callback;
@ -1149,9 +944,8 @@ int main(int argc, char ** argv) {
wparams.progress_callback_user_data = &user_data;
}
// examples for abort mechanism
// in examples below, we do not abort the processing, but we could if the flag is set to true
// example for abort mechanism
// in this example, we do not abort the processing, but we could if the flag is set to true
// the callback is called before every encoder run - if it returns false, the processing is aborted
{
static bool is_aborted = false; // NOTE: this should be atomic to avoid data race
@ -1163,17 +957,6 @@ int main(int argc, char ** argv) {
wparams.encoder_begin_callback_user_data = &is_aborted;
}
// the callback is called before every computation - if it returns true, the computation is aborted
{
static bool is_aborted = false; // NOTE: this should be atomic to avoid data race
wparams.abort_callback = [](void * user_data) {
bool is_aborted = *(bool*)user_data;
return is_aborted;
};
wparams.abort_callback_user_data = &is_aborted;
}
if (whisper_full_parallel(ctx, wparams, pcmf32.data(), pcmf32.size(), params.n_processors) != 0) {
fprintf(stderr, "%s: failed to process audio\n", argv[0]);
return 10;
@ -1217,7 +1000,7 @@ int main(int argc, char ** argv) {
// output to JSON file
if (params.output_jsn) {
const auto fname_jsn = fname_out + ".json";
output_json(ctx, fname_jsn.c_str(), params, pcmf32s, params.output_jsn_full);
output_json(ctx, fname_jsn.c_str(), params, pcmf32s);
}
// output to LRC file
@ -1234,9 +1017,7 @@ int main(int argc, char ** argv) {
}
}
if (!params.no_prints) {
whisper_print_timings(ctx);
}
whisper_print_timings(ctx);
whisper_free(ctx);
return 0;

View File

@ -1,7 +0,0 @@
import whisper_processor
try:
result = whisper_processor.process_audio("./audio/wake_word_detected16k.wav", "base.en")
print(result)
except Exception as e:
print(f"Error: {e}")

View File

@ -1,54 +0,0 @@
import subprocess
import sys
import os
def process_audio(wav_file, model_name="base.en"):
"""
Processes an audio file using a specified model and returns the processed string.
:param wav_file: Path to the WAV file
:param model_name: Name of the model to use
:return: Processed string output from the audio processing
:raises: Exception if an error occurs during processing
"""
model = f"./models/ggml-{model_name}.bin"
# Check if the file exists
if not os.path.exists(model):
raise FileNotFoundError(f"Model file not found: {model} \n\nDownload a model with this command:\n\n> bash ./models/download-ggml-model.sh {model_name}\n\n")
if not os.path.exists(wav_file):
raise FileNotFoundError(f"WAV file not found: {wav_file}")
full_command = f"./main -m {model} -f {wav_file} -np -nt"
# Execute the command
process = subprocess.Popen(full_command, shell=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
# Get the output and error (if any)
output, error = process.communicate()
if error:
raise Exception(f"Error processing audio: {error.decode('utf-8')}")
# Process and return the output string
decoded_str = output.decode('utf-8').strip()
processed_str = decoded_str.replace('[BLANK_AUDIO]', '').strip()
return processed_str
def main():
if len(sys.argv) >= 2:
wav_file = sys.argv[1]
model_name = sys.argv[2] if len(sys.argv) == 3 else "base.en"
try:
result = process_audio(wav_file, model_name)
print(result)
except Exception as e:
print(f"Error: {e}")
else:
print("Usage: python whisper_processor.py <wav_file> [<model_name>]")
if __name__ == "__main__":
main()

View File

@ -1,10 +0,0 @@
set(TARGET server)
add_executable(${TARGET} server.cpp httplib.h)
include(DefaultTargetOptions)
target_link_libraries(${TARGET} PRIVATE common json_cpp whisper ${CMAKE_THREAD_LIBS_INIT})
if (WIN32)
target_link_libraries(${TARGET} PRIVATE ws2_32)
endif()

View File

@ -1,69 +0,0 @@
# whisper.cpp http server
Simple http server. WAV Files are passed to the inference model via http requests.
https://github.com/ggerganov/whisper.cpp/assets/1991296/e983ee53-8741-4eb5-9048-afe5e4594b8f
## Usage
```
./server -h
usage: ./bin/server [options]
options:
-h, --help [default] show this help message and exit
-t N, --threads N [4 ] number of threads to use during computation
-p N, --processors N [1 ] number of processors to use during computation
-ot N, --offset-t N [0 ] time offset in milliseconds
-on N, --offset-n N [0 ] segment index offset
-d N, --duration N [0 ] duration of audio to process in milliseconds
-mc N, --max-context N [-1 ] maximum number of text context tokens to store
-ml N, --max-len N [0 ] maximum segment length in characters
-sow, --split-on-word [false ] split on word rather than on token
-bo N, --best-of N [2 ] number of best candidates to keep
-bs N, --beam-size N [-1 ] beam size for beam search
-wt N, --word-thold N [0.01 ] word timestamp probability threshold
-et N, --entropy-thold N [2.40 ] entropy threshold for decoder fail
-lpt N, --logprob-thold N [-1.00 ] log probability threshold for decoder fail
-debug, --debug-mode [false ] enable debug mode (eg. dump log_mel)
-tr, --translate [false ] translate from source language to english
-di, --diarize [false ] stereo audio diarization
-tdrz, --tinydiarize [false ] enable tinydiarize (requires a tdrz model)
-nf, --no-fallback [false ] do not use temperature fallback while decoding
-ps, --print-special [false ] print special tokens
-pc, --print-colors [false ] print colors
-pr, --print-realtime [false ] print output in realtime
-pp, --print-progress [false ] print progress
-nt, --no-timestamps [false ] do not print timestamps
-l LANG, --language LANG [en ] spoken language ('auto' for auto-detect)
-dl, --detect-language [false ] exit after automatically detecting language
--prompt PROMPT [ ] initial prompt
-m FNAME, --model FNAME [models/ggml-base.en.bin] model path
-oved D, --ov-e-device DNAME [CPU ] the OpenVINO device used for encode inference
--host HOST, [127.0.0.1] Hostname/ip-adress for the server
--port PORT, [8080 ] Port number for the server
--convert, [false ] Convert audio to WAV, requires ffmpeg on the server
```
> [!WARNING]
> **Do not run the server example with administrative privileges and ensure it's operated in a sandbox environment, especially since it involves risky operations like accepting user file uploads and using ffmpeg for format conversions. Always validate and sanitize inputs to guard against potential security threats.**
## request examples
**/inference**
```
curl 127.0.0.1:8080/inference \
-H "Content-Type: multipart/form-data" \
-F file="@<file-path>" \
-F temperature="0.0" \
-F temperature_inc="0.2" \
-F response_format="json"
```
**/load**
```
curl 127.0.0.1:8080/load \
-H "Content-Type: multipart/form-data" \
-F model="<path-to-model-file>"
```

File diff suppressed because it is too large Load Diff

File diff suppressed because it is too large Load Diff

View File

@ -103,11 +103,11 @@ void stream_main(size_t index) {
{
const int n_segments = whisper_full_n_segments(ctx);
if (n_segments > 0) {
const char * text = whisper_full_get_segment_text(ctx, n_segments - 1);
for (int i = n_segments - 1; i < n_segments; ++i) {
const char * text = whisper_full_get_segment_text(ctx, i);
const int64_t t0 = whisper_full_get_segment_t0(ctx, n_segments - 1);
const int64_t t1 = whisper_full_get_segment_t1(ctx, n_segments - 1);
const int64_t t0 = whisper_full_get_segment_t0(ctx, i);
const int64_t t1 = whisper_full_get_segment_t1(ctx, i);
printf("transcribed: %s\n", text);
@ -132,7 +132,7 @@ EMSCRIPTEN_BINDINGS(stream) {
emscripten::function("init", emscripten::optional_override([](const std::string & path_model) {
for (size_t i = 0; i < g_contexts.size(); ++i) {
if (g_contexts[i] == nullptr) {
g_contexts[i] = whisper_init_from_file_with_params(path_model.c_str(), whisper_context_default_params());
g_contexts[i] = whisper_init_from_file(path_model.c_str());
if (g_contexts[i] != nullptr) {
g_running = true;
if (g_worker.joinable()) {

View File

@ -4,7 +4,7 @@ This is a naive example of performing real-time inference on audio from your mic
The `stream` tool samples the audio every half a second and runs the transcription continously.
More info is available in [issue #10](https://github.com/ggerganov/whisper.cpp/issues/10).
```bash
```java
./stream -m ./models/ggml-base.en.bin -t 8 --step 500 --length 5000
```
@ -14,7 +14,7 @@ https://user-images.githubusercontent.com/1991296/194935793-76afede7-cfa8-48d8-a
Setting the `--step` argument to `0` enables the sliding window mode:
```bash
```java
./stream -m ./models/ggml-small.en.bin -t 6 --step 0 --length 30000 -vth 0.6
```
@ -30,33 +30,15 @@ a transcription block that is suitable for parsing.
The `stream` 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
make stream
```
Ensure you are at the root of the repo when running `make stream`. Not within the `examples/stream` dir
as the libraries needed like `common-sdl.h` are located within `examples`. Attempting to compile within
`examples/steam` means your compiler cannot find them and it gives an error it cannot find the file.
```bash
whisper.cpp/examples/stream$ make stream
g++ stream.cpp -o stream
stream.cpp:6:10: fatal error: common/sdl.h: No such file or directory
6 | #include "common/sdl.h"
| ^~~~~~~~~~~~~~
compilation terminated.
make: *** [<builtin>: stream] Error 1
```
## Web version
This tool can also run in the browser: [examples/stream.wasm](/examples/stream.wasm)

View File

@ -2,8 +2,9 @@
//
// A very quick-n-dirty implementation serving mainly as a proof of concept.
//
#include "common-sdl.h"
#include "common.h"
#include "common-sdl.h"
#include "whisper.h"
#include <cassert>
@ -13,6 +14,19 @@
#include <vector>
#include <fstream>
// 500 -> 00:05.000
// 6000 -> 01:00.000
std::string to_timestamp(int64_t t) {
int64_t sec = t/100;
int64_t msec = t - sec*100;
int64_t min = sec/60;
sec = sec - min*60;
char buf[32];
snprintf(buf, sizeof(buf), "%02d:%02d.%03d", (int) min, (int) sec, (int) msec);
return std::string(buf);
}
// command-line parameters
struct whisper_params {
@ -27,15 +41,13 @@ struct whisper_params {
float vad_thold = 0.6f;
float freq_thold = 100.0f;
bool speed_up = false;
bool translate = false;
bool no_fallback = false;
bool print_special = false;
bool no_context = true;
bool no_timestamps = false;
bool tinydiarize = false;
bool save_audio = false; // save audio to wav file
bool use_gpu = true;
bool flash_attn = false;
std::string language = "en";
std::string model = "models/ggml-base.en.bin";
@ -52,26 +64,24 @@ 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 == "--step") { params.step_ms = std::stoi(argv[++i]); }
else if ( arg == "--length") { params.length_ms = std::stoi(argv[++i]); }
else if ( arg == "--keep") { params.keep_ms = std::stoi(argv[++i]); }
else if (arg == "-c" || arg == "--capture") { params.capture_id = std::stoi(argv[++i]); }
else if (arg == "-mt" || arg == "--max-tokens") { params.max_tokens = std::stoi(argv[++i]); }
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 == "-tr" || arg == "--translate") { params.translate = true; }
else if (arg == "-nf" || arg == "--no-fallback") { params.no_fallback = true; }
else if (arg == "-ps" || arg == "--print-special") { params.print_special = true; }
else if (arg == "-kc" || arg == "--keep-context") { params.no_context = false; }
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 == "-tdrz" || arg == "--tinydiarize") { params.tinydiarize = true; }
else if (arg == "-sa" || arg == "--save-audio") { params.save_audio = 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 == "-t" || arg == "--threads") { params.n_threads = std::stoi(argv[++i]); }
else if ( arg == "--step") { params.step_ms = std::stoi(argv[++i]); }
else if ( arg == "--length") { params.length_ms = std::stoi(argv[++i]); }
else if ( arg == "--keep") { params.keep_ms = std::stoi(argv[++i]); }
else if (arg == "-c" || arg == "--capture") { params.capture_id = std::stoi(argv[++i]); }
else if (arg == "-mt" || arg == "--max-tokens") { params.max_tokens = std::stoi(argv[++i]); }
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 == "-nf" || arg == "--no-fallback") { params.no_fallback = true; }
else if (arg == "-ps" || arg == "--print-special") { params.print_special = true; }
else if (arg == "-kc" || arg == "--keep-context") { params.no_context = false; }
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 == "-tdrz" || arg == "--tinydiarize") { params.tinydiarize = true; }
else {
fprintf(stderr, "error: unknown argument: %s\n", arg.c_str());
@ -98,6 +108,7 @@ 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, " -nf, --no-fallback [%-7s] do not use temperature fallback while decoding\n", params.no_fallback ? "true" : "false");
fprintf(stderr, " -ps, --print-special [%-7s] print special tokens\n", params.print_special ? "true" : "false");
@ -105,10 +116,7 @@ void whisper_print_usage(int /*argc*/, char ** argv, const whisper_params & para
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, " -tdrz, --tinydiarize [%-7s] enable tinydiarize (requires a tdrz model)\n", params.tinydiarize ? "true" : "false");
fprintf(stderr, " -sa, --save-audio [%-7s] save the recorded audio to a file\n", params.save_audio ? "true" : "false");
fprintf(stderr, " -ng, --no-gpu [%-7s] disable GPU inference\n", params.use_gpu ? "false" : "true");
fprintf(stderr, " -fa, --flash-attn [%-7s] flash attention during inference\n", params.flash_attn ? "true" : "false");
fprintf(stderr, " -tdrz, --tinydiarize [%-7s] enable tinydiarize (requires a tdrz model)\n", params.tinydiarize ? "true" : "false");
fprintf(stderr, "\n");
}
@ -146,18 +154,14 @@ int main(int argc, char ** argv) {
audio.resume();
// whisper init
if (params.language != "auto" && whisper_lang_id(params.language.c_str()) == -1){
fprintf(stderr, "error: unknown language '%s'\n", params.language.c_str());
whisper_print_usage(argc, argv, params);
exit(0);
}
struct whisper_context_params cparams = whisper_context_default_params();
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);
struct whisper_context * ctx = whisper_init_from_file(params.model.c_str());
std::vector<float> pcmf32 (n_samples_30s, 0.0f);
std::vector<float> pcmf32_old;
@ -208,28 +212,14 @@ int main(int argc, char ** argv) {
}
}
wav_writer wavWriter;
// save wav file
if (params.save_audio) {
// Get current date/time for filename
time_t now = time(0);
char buffer[80];
strftime(buffer, sizeof(buffer), "%Y%m%d%H%M%S", localtime(&now));
std::string filename = std::string(buffer) + ".wav";
wavWriter.open(filename, WHISPER_SAMPLE_RATE, 16, 1);
}
printf("[Start speaking]\n");
printf("[Start speaking]");
fflush(stdout);
auto t_last = std::chrono::high_resolution_clock::now();
auto t_last = std::chrono::high_resolution_clock::now();
const auto t_start = t_last;
// main audio loop
while (is_running) {
if (params.save_audio) {
wavWriter.write(pcmf32_new.data(), pcmf32_new.size());
}
// handle Ctrl + C
is_running = sdl_poll_events();
@ -311,6 +301,7 @@ int main(int argc, char ** argv) {
wparams.n_threads = params.n_threads;
wparams.audio_ctx = params.audio_ctx;
wparams.speed_up = params.speed_up;
wparams.tdrz_enable = params.tinydiarize; // [TDRZ]
@ -359,7 +350,7 @@ int main(int argc, char ** argv) {
const int64_t t0 = whisper_full_get_segment_t0(ctx, i);
const int64_t t1 = whisper_full_get_segment_t1(ctx, i);
std::string output = "[" + to_timestamp(t0, false) + " --> " + to_timestamp(t1, false) + "] " + text;
std::string output = "[" + to_timestamp(t0) + " --> " + to_timestamp(t1) + "] " + text;
if (whisper_full_get_segment_speaker_turn_next(ctx, i)) {
output += " [SPEAKER_TURN]";
@ -380,7 +371,7 @@ int main(int argc, char ** argv) {
fout << std::endl;
}
if (use_vad) {
if (use_vad){
printf("\n");
printf("### Transcription %d END\n", n_iter);
}

View File

@ -1,9 +0,0 @@
# MIT license
# Copyright (C) 2024 Intel Corporation
# SPDX-License-Identifier: MIT
set(TARGET ls-sycl-device)
add_executable(${TARGET} ls-sycl-device.cpp)
install(TARGETS ${TARGET} RUNTIME)
target_link_libraries(${TARGET} PRIVATE common llama ${CMAKE_THREAD_LIBS_INIT})
target_compile_features(${TARGET} PRIVATE cxx_std_17)

View File

@ -1,47 +0,0 @@
# llama.cpp/example/sycl
This example program provide the tools for llama.cpp for SYCL on Intel GPU.
## Tool
|Tool Name| Function|Status|
|-|-|-|
|ls-sycl-device| List all SYCL devices with ID, compute capability, max work group size, ect.|Support|
### ls-sycl-device
List all SYCL devices with ID, compute capability, max work group size, ect.
1. Build the llama.cpp for SYCL for all targets.
2. Enable oneAPI running environment
```
source /opt/intel/oneapi/setvars.sh
```
3. Execute
```
./build/bin/ls-sycl-device
```
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|

View File

@ -1,19 +0,0 @@
# MIT license
# Copyright (C) 2024 Intel Corporation
# SPDX-License-Identifier: MIT
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 # faster for long-prompt inference
#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

View File

@ -1,11 +0,0 @@
/*MIT license
Copyright (C) 2024 Intel Corporation
SPDX-License-Identifier: MIT
*/
#include "ggml-sycl.h"
int main(int argc, char ** argv) {
ggml_backend_sycl_print_sycl_devices();
return 0;
}

View File

@ -1,17 +0,0 @@
#!/bin/bash
# MIT license
# Copyright (C) 2024 Intel Corporation
# SPDX-License-Identifier: MIT
INPUT2="Building a website can be done in 10 simple steps:\nStep 1:"
source /opt/intel/oneapi/setvars.sh
if [ $# -gt 0 ]; then
export GGML_SYCL_DEVICE=$1
else
export GGML_SYCL_DEVICE=0
fi
echo GGML_SYCL_DEVICE=$GGML_SYCL_DEVICE
#export GGML_SYCL_DEBUG=1
./build/bin/main -m models/ggml-base.en.bin -f samples/jfk.wav

View File

@ -1,2 +1 @@
audio.mp3
to_speak.txt

View File

@ -1,18 +1,16 @@
if (WHISPER_SDL2)
# talk-llama
set(TARGET talk-llama)
add_executable(${TARGET} talk-llama.cpp llama.cpp unicode.cpp unicode-data.cpp)
target_include_directories(${TARGET} PRIVATE ${SDL2_INCLUDE_DIRS})
#add_executable(${TARGET} talk-llama.cpp llama.cpp)
#target_include_directories(${TARGET} PRIVATE ${SDL2_INCLUDE_DIRS})
#target_link_libraries(${TARGET} PRIVATE common common-sdl whisper ${SDL2_LIBRARIES} ${CMAKE_THREAD_LIBS_INIT})
if (WHISPER_CLBLAST)
set(CLBLAST_LIBNAME clblast)
endif ()
target_link_libraries(${TARGET} PRIVATE common common-sdl whisper ${SDL2_LIBRARIES} ${CLBLAST_LIBNAME} ${CMAKE_THREAD_LIBS_INIT})
# TODO: this is temporary
# need to export ggml symbols for MSVC, but too lazy ..
add_executable(${TARGET} talk-llama.cpp llama.cpp ../common.cpp ../common-sdl.cpp ../../ggml.c ../../whisper.cpp)
if(WIN32)
# It requires Windows 8.1 or later for PrefetchVirtualMemory
target_compile_definitions(${TARGET} PRIVATE -D_WIN32_WINNT=0x0602)
endif()
target_include_directories(${TARGET} PRIVATE ${SDL2_INCLUDE_DIRS} ../../)
target_link_libraries(${TARGET} PRIVATE ${SDL2_LIBRARIES} ${CMAKE_THREAD_LIBS_INIT})
include(DefaultTargetOptions)
endif ()

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