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38
.devops/main-cuda.Dockerfile
Normal file
@ -0,0 +1,38 @@
|
||||
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
|
||||
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" ]
|
19
.devops/main.Dockerfile
Normal file
@ -0,0 +1,19 @@
|
||||
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" ]
|
52
.github/workflows/build.yml
vendored
@ -25,6 +25,7 @@ jobs:
|
||||
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
|
||||
@ -86,6 +87,7 @@ jobs:
|
||||
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 }}
|
||||
@ -113,8 +115,9 @@ jobs:
|
||||
docker run --platform ${{ matrix.arch }} --rm \
|
||||
-v ${{ github.workspace }}:/workspace \
|
||||
-w /workspace ${{ env.ubuntu_image }} /bin/sh -c '
|
||||
set -e
|
||||
apt update
|
||||
apt install -y build-essential cmake libsdl2-dev
|
||||
apt install -y clang build-essential cmake libsdl2-dev
|
||||
cmake . -DWHISPER_SDL2=ON -DCMAKE_BUILD_TYPE=${{ matrix.build }} -DCMAKE_CXX_COMPILER=clang++ -DCMAKE_C_COMPILER=clang
|
||||
make
|
||||
ctest -L gh --output-on-failure'
|
||||
@ -140,6 +143,7 @@ jobs:
|
||||
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
|
||||
@ -162,7 +166,7 @@ jobs:
|
||||
s2arc: x64
|
||||
jnaPath: win32-x86-64
|
||||
- sdl2: ON
|
||||
s2ver: 2.26.0
|
||||
s2ver: 2.28.5
|
||||
|
||||
steps:
|
||||
- name: Clone
|
||||
@ -217,13 +221,16 @@ jobs:
|
||||
sdl2: [ON]
|
||||
include:
|
||||
- arch: Win32
|
||||
obzip: https://github.com/OpenMathLib/OpenBLAS/releases/download/v0.3.24/OpenBLAS-0.3.24-x86.zip
|
||||
obzip: https://github.com/OpenMathLib/OpenBLAS/releases/download/v0.3.25/OpenBLAS-0.3.25-x86.zip
|
||||
s2arc: x86
|
||||
clblast: OFF
|
||||
- arch: x64
|
||||
obzip: https://github.com/OpenMathLib/OpenBLAS/releases/download/v0.3.24/OpenBLAS-0.3.24-x64.zip
|
||||
obzip: https://github.com/OpenMathLib/OpenBLAS/releases/download/v0.3.25/OpenBLAS-0.3.25-x64.zip
|
||||
s2arc: x64
|
||||
clblast: ON
|
||||
clver: 1.6.1
|
||||
- sdl2: ON
|
||||
s2ver: 2.26.0
|
||||
s2ver: 2.28.5
|
||||
|
||||
steps:
|
||||
- name: Clone
|
||||
@ -248,6 +255,18 @@ 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 ${{ matrix.arch }}
|
||||
@ -255,6 +274,7 @@ jobs:
|
||||
-DWHISPER_OPENBLAS=${{ matrix.blas }}
|
||||
-DCMAKE_LIBRARY_PATH="$env:OPENBLAS_PATH/lib"
|
||||
-DWHISPER_SDL2=${{ matrix.sdl2 }}
|
||||
-DWHISPER_CLBLAST=${{ matrix.clblast }}
|
||||
|
||||
- name: Build
|
||||
run: |
|
||||
@ -269,11 +289,15 @@ jobs:
|
||||
if: matrix.sdl2 == 'ON'
|
||||
run: copy "$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@v1
|
||||
with:
|
||||
name: whisper-blas-bin-${{ matrix.arch }}
|
||||
name: whisper-blas${{ matrix.clblast == 'ON' && '-clblast' || ''}}-bin-${{ matrix.arch }}
|
||||
path: build/bin/${{ matrix.build }}
|
||||
|
||||
windows-cublas:
|
||||
@ -285,11 +309,12 @@ jobs:
|
||||
arch: [x64]
|
||||
cublas: [ON]
|
||||
sdl2: [ON]
|
||||
cuda-toolkit: [12.2.0, 11.8.0]
|
||||
include:
|
||||
- arch: x64
|
||||
s2arc: x64
|
||||
- sdl2: ON
|
||||
s2ver: 2.26.0
|
||||
s2ver: 2.28.5
|
||||
|
||||
steps:
|
||||
- name: Clone
|
||||
@ -300,7 +325,9 @@ jobs:
|
||||
|
||||
- name: Install CUDA Toolkit
|
||||
id: cuda-toolkit
|
||||
uses: Jimver/cuda-toolkit@v0.2.10
|
||||
uses: Jimver/cuda-toolkit@v0.2.11
|
||||
with:
|
||||
cuda: '${{ matrix.cuda-toolkit }}'
|
||||
|
||||
- name: Fetch SDL2 and set SDL2_DIR
|
||||
if: matrix.sdl2 == 'ON'
|
||||
@ -313,12 +340,13 @@ jobs:
|
||||
run: >
|
||||
cmake -S . -B ./build -A ${{ matrix.arch }}
|
||||
-DCMAKE_BUILD_TYPE=${{ matrix.build }}
|
||||
-DWHISPER_CUBLAS=1
|
||||
-DWHISPER_CUBLAS=${{ matrix.cublas }}
|
||||
-DWHISPER_SDL2=${{ matrix.sdl2 }}
|
||||
|
||||
- name: Build
|
||||
- name: Build ${{ matrix.cuda-toolkit }}
|
||||
run: |
|
||||
cd ./build
|
||||
msbuild ALL_BUILD.vcxproj -t:build -p:configuration=${{ matrix.build }} -p:platform=${{ matrix.arch }}
|
||||
cmake --build . --config ${{ matrix.build }}
|
||||
|
||||
- name: Copy CUDA DLLs
|
||||
run: >
|
||||
@ -335,7 +363,7 @@ jobs:
|
||||
if: matrix.sdl2 == 'ON'
|
||||
uses: actions/upload-artifact@v1
|
||||
with:
|
||||
name: whisper-cublas-bin-${{ matrix.arch }}
|
||||
name: whisper-cublas-${{ matrix.cuda-toolkit }}-bin-${{ matrix.arch }}
|
||||
path: build/bin/${{ matrix.build }}
|
||||
|
||||
emscripten:
|
||||
|
57
.github/workflows/docker.yml
vendored
Normal file
@ -0,0 +1,57 @@
|
||||
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: ${{ matrix.config.dockerfile }}
|
@ -1,6 +1,6 @@
|
||||
cmake_minimum_required (VERSION 3.5)
|
||||
|
||||
project(whisper.cpp VERSION 1.5.1)
|
||||
project(whisper.cpp VERSION 1.5.4)
|
||||
|
||||
# Add path to modules
|
||||
list(APPEND CMAKE_MODULE_PATH "${CMAKE_CURRENT_SOURCE_DIR}/cmake/")
|
||||
@ -218,11 +218,17 @@ if (WHISPER_CUBLAS)
|
||||
add_compile_definitions(GGML_USE_CUBLAS)
|
||||
|
||||
if (WHISPER_STATIC)
|
||||
set(WHISPER_EXTRA_LIBS ${WHISPER_EXTRA_LIBS} CUDA::cudart_static CUDA::cublas_static CUDA::cublasLt_static)
|
||||
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)
|
||||
else ()
|
||||
set(WHISPER_EXTRA_LIBS ${WHISPER_EXTRA_LIBS} CUDA::cudart_static CUDA::cublas_static CUDA::cublasLt_static)
|
||||
endif()
|
||||
else()
|
||||
set(WHISPER_EXTRA_LIBS ${WHISPER_EXTRA_LIBS} CUDA::cudart CUDA::cublas CUDA::cublasLt)
|
||||
endif()
|
||||
|
||||
set(WHISPER_EXTRA_LIBS ${WHISPER_EXTRA_LIBS} CUDA::cuda_driver)
|
||||
else()
|
||||
message(FATAL_ERROR "cuBLAS not found")
|
||||
endif()
|
||||
@ -338,8 +344,8 @@ else()
|
||||
endif()
|
||||
else()
|
||||
if (EMSCRIPTEN)
|
||||
set(CMAKE_C_FLAGS "${CMAKE_C_FLAGS} -pthread")
|
||||
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -pthread")
|
||||
set(CMAKE_C_FLAGS "${CMAKE_C_FLAGS} -pthread -s TOTAL_STACK=5242880")
|
||||
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -pthread -s TOTAL_STACK=5242880")
|
||||
else()
|
||||
if(NOT WHISPER_NO_AVX)
|
||||
set(CMAKE_C_FLAGS "${CMAKE_C_FLAGS} -mavx")
|
||||
@ -521,7 +527,13 @@ endif()
|
||||
|
||||
if (GGML_SOURCES_CUDA)
|
||||
message(STATUS "GGML CUDA sources found, configuring CUDA architecture")
|
||||
set_property(TARGET whisper PROPERTY CUDA_ARCHITECTURES OFF)
|
||||
# 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 ${GGML_CUDA_ARCHITECTURES})
|
||||
set_property(TARGET whisper PROPERTY CUDA_SELECT_NVCC_ARCH_FLAGS "Auto")
|
||||
endif()
|
||||
|
||||
@ -533,7 +545,7 @@ target_compile_definitions(${TARGET} PUBLIC
|
||||
${WHISPER_EXTRA_FLAGS}
|
||||
)
|
||||
|
||||
set_target_properties(${TARGET} PROPERTIES PUBLIC_HEADER "whisper.h")
|
||||
set_target_properties(${TARGET} PROPERTIES PUBLIC_HEADER "ggml.h;whisper.h")
|
||||
|
||||
include(GNUInstallDirs)
|
||||
|
||||
|
2
Makefile
@ -206,7 +206,7 @@ ifdef WHISPER_CUBLAS
|
||||
|
||||
CFLAGS += -DGGML_USE_CUBLAS -I/usr/local/cuda/include -I/opt/cuda/include -I$(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/$(UNAME_M)-linux/lib
|
||||
LDFLAGS += -lcuda -lcublas -lculibos -lcudart -lcublasLt -lpthread -ldl -lrt -L/usr/local/cuda/lib64 -L/opt/cuda/lib64 -L$(CUDA_PATH)/targets/$(UNAME_M)-linux/lib
|
||||
WHISPER_OBJ += ggml-cuda.o
|
||||
NVCC = nvcc
|
||||
NVCCFLAGS = --forward-unknown-to-host-compiler -arch=$(CUDA_ARCH_FLAG)
|
||||
|
@ -2,41 +2,26 @@
|
||||
|
||||
import PackageDescription
|
||||
|
||||
#if arch(arm) || arch(arm64)
|
||||
let platforms: [SupportedPlatform]? = [
|
||||
.macOS(.v12),
|
||||
.iOS(.v14),
|
||||
.watchOS(.v4),
|
||||
.tvOS(.v14)
|
||||
]
|
||||
let exclude: [String] = []
|
||||
let resources: [Resource] = [
|
||||
.process("ggml-metal.metal")
|
||||
]
|
||||
let additionalSources: [String] = ["ggml-metal.m"]
|
||||
let additionalSettings: [CSetting] = [
|
||||
.unsafeFlags(["-fno-objc-arc"]),
|
||||
.define("GGML_USE_METAL")
|
||||
]
|
||||
#else
|
||||
let platforms: [SupportedPlatform]? = nil
|
||||
let exclude: [String] = ["ggml-metal.metal"]
|
||||
let resources: [Resource] = []
|
||||
let additionalSources: [String] = []
|
||||
let additionalSettings: [CSetting] = []
|
||||
#endif
|
||||
|
||||
let package = Package(
|
||||
name: "whisper",
|
||||
platforms: platforms,
|
||||
platforms: [
|
||||
.macOS(.v12),
|
||||
.iOS(.v14),
|
||||
.watchOS(.v4),
|
||||
.tvOS(.v14)
|
||||
],
|
||||
products: [
|
||||
.library(name: "whisper", targets: ["whisper"]),
|
||||
],
|
||||
dependencies: [
|
||||
.package(url: "https://github.com/ggerganov/ggml.git", .branch("master"))
|
||||
],
|
||||
targets: [
|
||||
.target(
|
||||
name: "whisper",
|
||||
dependencies: ["ggml"],
|
||||
path: ".",
|
||||
exclude: exclude + [
|
||||
exclude: [
|
||||
"bindings",
|
||||
"cmake",
|
||||
"coreml",
|
||||
@ -51,23 +36,20 @@ let package = Package(
|
||||
"Makefile"
|
||||
],
|
||||
sources: [
|
||||
"ggml.c",
|
||||
"whisper.cpp",
|
||||
"ggml-alloc.c",
|
||||
"ggml-backend.c",
|
||||
"ggml-quants.c"
|
||||
] + additionalSources,
|
||||
resources: resources,
|
||||
],
|
||||
publicHeadersPath: "spm-headers",
|
||||
cSettings: [
|
||||
.unsafeFlags(["-Wno-shorten-64-to-32", "-O3", "-DNDEBUG"]),
|
||||
.define("GGML_USE_ACCELERATE")
|
||||
.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")
|
||||
] + additionalSettings,
|
||||
],
|
||||
linkerSettings: [
|
||||
.linkedFramework("Accelerate")
|
||||
]
|
||||
|
42
README.md
@ -6,7 +6,7 @@
|
||||
[](https://opensource.org/licenses/MIT)
|
||||
[](https://www.npmjs.com/package/whisper.cpp/)
|
||||
|
||||
Stable: [v1.5.1](https://github.com/ggerganov/whisper.cpp/releases/tag/v1.5.1) / [Roadmap | F.A.Q.](https://github.com/ggerganov/whisper.cpp/discussions/126)
|
||||
Stable: [v1.5.4](https://github.com/ggerganov/whisper.cpp/releases/tag/v1.5.4) / [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:
|
||||
|
||||
@ -33,6 +33,7 @@ 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.
|
||||
@ -110,8 +111,8 @@ options:
|
||||
-mc N, --max-context N [-1 ] maximum number of text context tokens to store
|
||||
-ml N, --max-len N [0 ] maximum segment length in characters
|
||||
-sow, --split-on-word [false ] split on word rather than on token
|
||||
-bo N, --best-of N [2 ] number of best candidates to keep
|
||||
-bs N, --beam-size N [-1 ] beam size for beam search
|
||||
-bo N, --best-of N [5 ] number of best candidates to keep
|
||||
-bs N, --beam-size N [5 ] 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
|
||||
@ -128,6 +129,7 @@ options:
|
||||
-fp, --font-path [/System/Library/Fonts/Supplemental/Courier New Bold.ttf] path to a monospace font for karaoke video
|
||||
-ocsv, --output-csv [false ] output result in a CSV file
|
||||
-oj, --output-json [false ] output result in a JSON file
|
||||
-ojf, --output-json-full [false ] include more information in the JSON file
|
||||
-of FNAME, --output-file FNAME [ ] output file path (without file extension)
|
||||
-ps, --print-special [false ] print special tokens
|
||||
-pc, --print-colors [false ] print colors
|
||||
@ -139,7 +141,8 @@ options:
|
||||
-m FNAME, --model FNAME [models/ggml-base.en.bin] model path
|
||||
-f FNAME, --file FNAME [ ] input WAV file path
|
||||
-oved D, --ov-e-device DNAME [CPU ] the OpenVINO device used for encode inference
|
||||
-ls, --log-score [false ] log best decoder scores of token
|
||||
-ls, --log-score [false ] log best decoder scores of tokens
|
||||
-ng, --no-gpu [false ] disable GPU
|
||||
|
||||
|
||||
bash ./models/download-ggml-model.sh base.en
|
||||
@ -446,6 +449,36 @@ make clean
|
||||
WHISPER_OPENBLAS=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"
|
||||
```
|
||||
|
||||
## Limitations
|
||||
|
||||
- Inference only
|
||||
@ -768,6 +801,7 @@ Some of the examples are even ported to run in the browser using WebAssembly. Ch
|
||||
| [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 |
|
||||
|
@ -1,6 +1,6 @@
|
||||
{
|
||||
"name": "whisper.cpp",
|
||||
"version": "1.5.1",
|
||||
"version": "1.5.4",
|
||||
"description": "Whisper speech recognition",
|
||||
"main": "whisper.js",
|
||||
"scripts": {
|
||||
|
@ -70,7 +70,7 @@ extern "C" {
|
||||
void (*graph_plan_compute)(ggml_backend_t backend, ggml_backend_graph_plan_t plan);
|
||||
|
||||
// compute graph without a plan
|
||||
void (*graph_compute)(ggml_backend_t backend, struct ggml_cgraph * cgraph);
|
||||
bool (*graph_compute)(ggml_backend_t backend, struct ggml_cgraph * cgraph);
|
||||
|
||||
// check if the backend supports an operation
|
||||
bool (*supports_op)(ggml_backend_t backend, const struct ggml_tensor * op);
|
||||
|
@ -156,8 +156,8 @@ void ggml_backend_graph_plan_compute(ggml_backend_t backend, ggml_backend_graph_
|
||||
backend->iface.graph_plan_compute(backend, plan);
|
||||
}
|
||||
|
||||
void ggml_backend_graph_compute(ggml_backend_t backend, struct ggml_cgraph * cgraph) {
|
||||
backend->iface.graph_compute(backend, cgraph);
|
||||
bool ggml_backend_graph_compute(ggml_backend_t backend, struct ggml_cgraph * cgraph) {
|
||||
return backend->iface.graph_compute(backend, cgraph);
|
||||
}
|
||||
|
||||
bool ggml_backend_supports_op(ggml_backend_t backend, const struct ggml_tensor * op) {
|
||||
|
@ -52,7 +52,7 @@ extern "C" {
|
||||
|
||||
GGML_API void ggml_backend_graph_plan_free (ggml_backend_t backend, ggml_backend_graph_plan_t plan);
|
||||
GGML_API void ggml_backend_graph_plan_compute(ggml_backend_t backend, ggml_backend_graph_plan_t plan);
|
||||
GGML_API void ggml_backend_graph_compute (ggml_backend_t backend, struct ggml_cgraph * cgraph);
|
||||
GGML_API bool ggml_backend_graph_compute (ggml_backend_t backend, struct ggml_cgraph * cgraph);
|
||||
GGML_API bool ggml_backend_supports_op (ggml_backend_t backend, const struct ggml_tensor * op);
|
||||
|
||||
// tensor copy between different backends
|
||||
|
@ -24,9 +24,9 @@ struct whisper_coreml_context * whisper_coreml_init(const char * path_model) {
|
||||
|
||||
// select which device to run the Core ML model on
|
||||
MLModelConfiguration *config = [[MLModelConfiguration alloc] init];
|
||||
config.computeUnits = MLComputeUnitsCPUAndGPU;
|
||||
// config.computeUnits = MLComputeUnitsCPUAndGPU;
|
||||
//config.computeUnits = MLComputeUnitsCPUAndNeuralEngine;
|
||||
//config.computeUnits = MLComputeUnitsAll;
|
||||
config.computeUnits = MLComputeUnitsAll;
|
||||
|
||||
const void * data = CFBridgingRetain([[whisper_encoder_impl alloc] initWithContentsOfURL:url_model configuration:config error:nil]);
|
||||
|
||||
|
@ -14,6 +14,10 @@ if (WHISPER_SDL2)
|
||||
message(STATUS "SDL2_LIBRARIES = ${SDL2_LIBRARIES}")
|
||||
endif()
|
||||
|
||||
if (WHISPER_CLBLAST)
|
||||
find_package(CLBlast REQUIRED)
|
||||
endif()
|
||||
|
||||
# common
|
||||
|
||||
set(TARGET common)
|
||||
@ -73,3 +77,5 @@ else()
|
||||
add_subdirectory(talk-llama)
|
||||
add_subdirectory(lsp)
|
||||
endif()
|
||||
|
||||
add_subdirectory(wchess)
|
||||
|
@ -22,6 +22,7 @@ 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();
|
||||
}
|
||||
}
|
||||
|
||||
|
@ -17,28 +17,37 @@ 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 [-1 ] beam size for beam search
|
||||
-bs N, --beam-size N [5 ] 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
|
||||
-su, --speed-up [false ] speed up audio by x2 (reduced accuracy)
|
||||
-debug, --debug-mode [false ] enable debug mode (eg. dump log_mel)
|
||||
-tr, --translate [false ] translate from source language to english
|
||||
-di, --diarize [false ] stereo audio diarization
|
||||
-tdrz, --tinydiarize [false ] enable tinydiarize (requires a tdrz model)
|
||||
-nf, --no-fallback [false ] do not use temperature fallback while decoding
|
||||
-otxt, --output-txt [false ] output result in a text file
|
||||
-ovtt, --output-vtt [false ] output result in a vtt file
|
||||
-osrt, --output-srt [false ] output result in a srt file
|
||||
-olrc, --output-lrc [false ] output result in a lrc file
|
||||
-owts, --output-words [false ] output script for generating karaoke video
|
||||
-fp, --font-path [/System/Library/Fonts/Supplemental/Courier New Bold.ttf] path to a monospace font for karaoke video
|
||||
-ocsv, --output-csv [false ] output result in a CSV file
|
||||
-oj, --output-json [false ] output result in a JSON file
|
||||
-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 [true ] do not print timestamps
|
||||
-nt, --no-timestamps [false ] do not print timestamps
|
||||
-l LANG, --language LANG [en ] spoken language ('auto' for auto-detect)
|
||||
-dl, --detect-language [false ] exit after automatically detecting language
|
||||
--prompt PROMPT [ ] initial prompt
|
||||
-m FNAME, --model FNAME [models/ggml-base.en.bin] model path
|
||||
-f FNAME, --file FNAME [ ] input WAV file path
|
||||
-oved D, --ov-e-device DNAME [CPU ] the OpenVINO device used for encode inference
|
||||
-ls, --log-score [false ] log best decoder scores of tokens
|
||||
-ng, --no-gpu [false ] disable GPU
|
||||
```
|
||||
|
@ -4,3 +4,9 @@ add_executable(${TARGET} server.cpp httplib.h json.hpp)
|
||||
include(DefaultTargetOptions)
|
||||
|
||||
target_link_libraries(${TARGET} PRIVATE common whisper ${CMAKE_THREAD_LIBS_INIT})
|
||||
|
||||
# Check if the compiler is MinGW
|
||||
if(MINGW)
|
||||
# Link the necessary libraries for SSL and Winsock
|
||||
target_link_libraries(${TARGET} PRIVATE -lcrypt32 -lssl -lcrypto -lws2_32)
|
||||
endif()
|
||||
|
@ -43,8 +43,12 @@ options:
|
||||
-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**
|
||||
|
@ -11,6 +11,7 @@
|
||||
#include <thread>
|
||||
#include <vector>
|
||||
#include <cstring>
|
||||
#include <sstream>
|
||||
|
||||
#if defined(_MSC_VER)
|
||||
#pragma warning(disable: 4244 4267) // possible loss of data
|
||||
@ -43,6 +44,8 @@ struct server_params
|
||||
int32_t port = 8080;
|
||||
int32_t read_timeout = 600;
|
||||
int32_t write_timeout = 600;
|
||||
|
||||
bool ffmpeg_converter = false;
|
||||
};
|
||||
|
||||
struct whisper_params {
|
||||
@ -157,6 +160,7 @@ void whisper_print_usage(int /*argc*/, char ** argv, const whisper_params & para
|
||||
fprintf(stderr, " --host HOST, [%-7s] Hostname/ip-adress for the server\n", sparams.hostname.c_str());
|
||||
fprintf(stderr, " --port PORT, [%-7d] Port number for the server\n", sparams.port);
|
||||
fprintf(stderr, " --public PATH, [%-7s] Path to the public folder\n", sparams.public_path.c_str());
|
||||
fprintf(stderr, " --convert, [%-7s] Convert audio to WAV, requires ffmpeg on the server", sparams.ffmpeg_converter ? "true" : "false");
|
||||
fprintf(stderr, "\n");
|
||||
}
|
||||
|
||||
@ -203,6 +207,7 @@ bool whisper_params_parse(int argc, char ** argv, whisper_params & params, serve
|
||||
else if ( arg == "--port") { sparams.port = std::stoi(argv[++i]); }
|
||||
else if ( arg == "--host") { sparams.hostname = argv[++i]; }
|
||||
else if ( arg == "--public") { sparams.public_path = argv[++i]; }
|
||||
else if ( arg == "--convert") { sparams.ffmpeg_converter = true; }
|
||||
else {
|
||||
fprintf(stderr, "error: unknown argument: %s\n", arg.c_str());
|
||||
whisper_print_usage(argc, argv, params, sparams);
|
||||
@ -220,6 +225,45 @@ struct whisper_print_user_data {
|
||||
int progress_prev;
|
||||
};
|
||||
|
||||
void check_ffmpeg_availibility() {
|
||||
int result = system("ffmpeg -version");
|
||||
|
||||
if (result == 0) {
|
||||
std::cout << "ffmpeg is available." << std::endl;
|
||||
} else {
|
||||
// ffmpeg is not available
|
||||
std::cout << "ffmpeg is not found. Please ensure that ffmpeg is installed ";
|
||||
std::cout << "and that its executable is included in your system's PATH. ";
|
||||
exit(0);
|
||||
}
|
||||
}
|
||||
|
||||
bool convert_to_wav(const std::string & temp_filename, std::string & error_resp) {
|
||||
std::ostringstream cmd_stream;
|
||||
std::string converted_filename_temp = temp_filename + "_temp.wav";
|
||||
cmd_stream << "ffmpeg -i \"" << temp_filename << "\" -ar 16000 -ac 1 -c:a pcm_s16le \"" << converted_filename_temp << "\" 2>&1";
|
||||
std::string cmd = cmd_stream.str();
|
||||
|
||||
int status = std::system(cmd.c_str());
|
||||
if (status != 0) {
|
||||
error_resp = "{\"error\":\"FFmpeg conversion failed.\"}";
|
||||
return false;
|
||||
}
|
||||
|
||||
// Remove the original file
|
||||
if (remove(temp_filename.c_str()) != 0) {
|
||||
error_resp = "{\"error\":\"Failed to remove the original file.\"}";
|
||||
return false;
|
||||
}
|
||||
|
||||
// Rename the temporary file to match the original filename
|
||||
if (rename(converted_filename_temp.c_str(), temp_filename.c_str()) != 0) {
|
||||
error_resp = "{\"error\":\"Failed to rename the temporary file.\"}";
|
||||
return false;
|
||||
}
|
||||
return true;
|
||||
}
|
||||
|
||||
std::string estimate_diarization_speaker(std::vector<std::vector<float>> pcmf32s, int64_t t0, int64_t t1, bool id_only = false) {
|
||||
std::string speaker = "";
|
||||
const int64_t n_samples = pcmf32s[0].size();
|
||||
@ -407,6 +451,9 @@ int main(int argc, char ** argv) {
|
||||
exit(0);
|
||||
}
|
||||
|
||||
if (sparams.ffmpeg_converter) {
|
||||
check_ffmpeg_availibility();
|
||||
}
|
||||
// whisper init
|
||||
struct whisper_context_params cparams;
|
||||
cparams.use_gpu = params.use_gpu;
|
||||
@ -422,6 +469,9 @@ int main(int argc, char ** argv) {
|
||||
whisper_ctx_init_openvino_encoder(ctx, nullptr, params.openvino_encode_device.c_str(), nullptr);
|
||||
|
||||
Server svr;
|
||||
svr.set_default_headers({{"Server", "whisper.cpp"},
|
||||
{"Access-Control-Allow-Origin", "*"},
|
||||
{"Access-Control-Allow-Headers", "content-type"}});
|
||||
|
||||
std::string const default_content = "<html>hello</html>";
|
||||
|
||||
@ -462,6 +512,18 @@ int main(int argc, char ** argv) {
|
||||
temp_file << audio_file.content;
|
||||
temp_file.close();
|
||||
|
||||
// if file is not wav, convert to wav
|
||||
|
||||
if (sparams.ffmpeg_converter) {
|
||||
std::string error_resp = "{\"error\":\"Failed to execute ffmpeg command.\"}";
|
||||
const bool is_converted = convert_to_wav(temp_filename, error_resp);
|
||||
if (!is_converted) {
|
||||
res.set_content(error_resp, "application/json");
|
||||
whisper_mutex.unlock();
|
||||
return;
|
||||
}
|
||||
}
|
||||
|
||||
// read wav content into pcmf32
|
||||
if (!::read_wav(temp_filename, pcmf32, pcmf32s, params.diarize)) {
|
||||
fprintf(stderr, "error: failed to read WAV file '%s'\n", temp_filename.c_str());
|
||||
@ -509,7 +571,6 @@ int main(int argc, char ** argv) {
|
||||
|
||||
// run the inference
|
||||
{
|
||||
|
||||
printf("Running whisper.cpp inference on %s\n", filename.c_str());
|
||||
whisper_full_params wparams = whisper_full_default_params(WHISPER_SAMPLING_GREEDY);
|
||||
|
||||
@ -528,6 +589,7 @@ int main(int argc, char ** argv) {
|
||||
wparams.duration_ms = params.duration_ms;
|
||||
|
||||
wparams.thold_pt = params.word_thold;
|
||||
wparams.max_len = params.max_len == 0 ? 60 : params.max_len;
|
||||
wparams.split_on_word = params.split_on_word;
|
||||
|
||||
wparams.speed_up = params.speed_up;
|
||||
@ -597,6 +659,50 @@ int main(int argc, char ** argv) {
|
||||
std::string results = output_str(ctx, params, pcmf32s);
|
||||
res.set_content(results.c_str(), "text/html");
|
||||
}
|
||||
else if (params.response_format == srt_format)
|
||||
{
|
||||
std::stringstream ss;
|
||||
const int n_segments = whisper_full_n_segments(ctx);
|
||||
for (int i = 0; i < n_segments; ++i) {
|
||||
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);
|
||||
std::string speaker = "";
|
||||
|
||||
if (params.diarize && pcmf32s.size() == 2)
|
||||
{
|
||||
speaker = estimate_diarization_speaker(pcmf32s, t0, t1);
|
||||
}
|
||||
|
||||
ss << i + 1 + params.offset_n << "\n";
|
||||
ss << to_timestamp(t0, true) << " --> " << to_timestamp(t1, true) << "\n";
|
||||
ss << speaker << text << "\n\n";
|
||||
}
|
||||
res.set_content(ss.str(), "application/x-subrip");
|
||||
} else if (params.response_format == vtt_format) {
|
||||
std::stringstream ss;
|
||||
|
||||
ss << "WEBVTT\n\n";
|
||||
|
||||
const int n_segments = whisper_full_n_segments(ctx);
|
||||
for (int i = 0; i < n_segments; ++i) {
|
||||
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);
|
||||
std::string speaker = "";
|
||||
|
||||
if (params.diarize && pcmf32s.size() == 2)
|
||||
{
|
||||
speaker = estimate_diarization_speaker(pcmf32s, t0, t1, true);
|
||||
speaker.insert(0, "<v Speaker");
|
||||
speaker.append(">");
|
||||
}
|
||||
|
||||
ss << to_timestamp(t0) << " --> " << to_timestamp(t1) << "\n";
|
||||
ss << speaker << text << "\n\n";
|
||||
}
|
||||
res.set_content(ss.str(), "text/vtt");
|
||||
}
|
||||
// TODO add more output formats
|
||||
else
|
||||
{
|
||||
|
@ -1,25 +1,18 @@
|
||||
if (WHISPER_SDL2)
|
||||
# talk-llama
|
||||
set(TARGET talk-llama)
|
||||
#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} ${CMAKE_THREAD_LIBS_INIT})
|
||||
add_executable(${TARGET} talk-llama.cpp llama.cpp)
|
||||
target_include_directories(${TARGET} PRIVATE ${SDL2_INCLUDE_DIRS})
|
||||
|
||||
# TODO: this is temporary
|
||||
# need to export ggml symbols for MSVC, but too lazy ..
|
||||
add_executable(${TARGET}
|
||||
talk-llama.cpp
|
||||
llama.cpp
|
||||
../common.cpp
|
||||
../common-sdl.cpp
|
||||
../../ggml.c
|
||||
../../ggml-alloc.c
|
||||
../../ggml-backend.c
|
||||
../../ggml-quants.c
|
||||
../../whisper.cpp)
|
||||
if (WHISPER_CLBLAST)
|
||||
set(CLBLAST_LIBNAME clblast)
|
||||
endif ()
|
||||
target_link_libraries(${TARGET} PRIVATE common common-sdl whisper ${SDL2_LIBRARIES} ${CLBLAST_LIBNAME} ${CMAKE_THREAD_LIBS_INIT})
|
||||
|
||||
target_include_directories(${TARGET} PRIVATE ${SDL2_INCLUDE_DIRS} ../../)
|
||||
target_link_libraries(${TARGET} PRIVATE ${SDL2_LIBRARIES} ${CMAKE_THREAD_LIBS_INIT})
|
||||
if(WIN32)
|
||||
# It requires Windows 8.1 or later for PrefetchVirtualMemory
|
||||
target_compile_definitions(${TARGET} PRIVATE -D_WIN32_WINNT=0x0602)
|
||||
endif()
|
||||
|
||||
include(DefaultTargetOptions)
|
||||
endif ()
|
||||
|
@ -39,10 +39,11 @@
|
||||
|
||||
#define LLAMA_MAX_RNG_STATE (64*1024)
|
||||
|
||||
#define LLAMA_FILE_MAGIC_GGLA 0x67676c61u // 'ggla'
|
||||
#define LLAMA_FILE_MAGIC_GGSN 0x6767736eu // 'ggsn'
|
||||
|
||||
#define LLAMA_SESSION_MAGIC LLAMA_FILE_MAGIC_GGSN
|
||||
#define LLAMA_SESSION_VERSION 2
|
||||
#define LLAMA_SESSION_VERSION 3
|
||||
|
||||
#if defined(GGML_USE_CUBLAS) || defined(GGML_USE_CLBLAST) || defined(GGML_USE_METAL)
|
||||
// Defined when llama.cpp is compiled with support for offloading model layers to GPU.
|
||||
@ -126,7 +127,7 @@ extern "C" {
|
||||
bool sorted;
|
||||
} llama_token_data_array;
|
||||
|
||||
typedef void (*llama_progress_callback)(float progress, void *ctx);
|
||||
typedef bool (*llama_progress_callback)(float progress, void *ctx);
|
||||
|
||||
// Input data for llama_decode
|
||||
// A llama_batch object can contain input about one or many sequences
|
||||
@ -158,16 +159,38 @@ extern "C" {
|
||||
llama_seq_id all_seq_id; // used if seq_id == NULL
|
||||
} llama_batch;
|
||||
|
||||
enum llama_model_kv_override_type {
|
||||
LLAMA_KV_OVERRIDE_INT,
|
||||
LLAMA_KV_OVERRIDE_FLOAT,
|
||||
LLAMA_KV_OVERRIDE_BOOL,
|
||||
};
|
||||
|
||||
struct llama_model_kv_override {
|
||||
char key[128];
|
||||
enum llama_model_kv_override_type tag;
|
||||
union {
|
||||
int64_t int_value;
|
||||
double float_value;
|
||||
bool bool_value;
|
||||
};
|
||||
};
|
||||
|
||||
struct llama_model_params {
|
||||
int32_t n_gpu_layers; // number of layers to store in VRAM
|
||||
int32_t main_gpu; // the GPU that is used for scratch and small tensors
|
||||
const float * tensor_split; // how to split layers across multiple GPUs (size: LLAMA_MAX_DEVICES)
|
||||
|
||||
// called with a progress value between 0 and 1, pass NULL to disable
|
||||
// Called with a progress value between 0.0 and 1.0. Pass NULL to disable.
|
||||
// If the provided progress_callback returns true, model loading continues.
|
||||
// If it returns false, model loading is immediately aborted.
|
||||
llama_progress_callback progress_callback;
|
||||
|
||||
// context pointer passed to the progress callback
|
||||
void * progress_callback_user_data;
|
||||
|
||||
// override key-value pairs of the model meta data
|
||||
const struct llama_model_kv_override * kv_overrides;
|
||||
|
||||
// Keep the booleans together to avoid misalignment during copy-by-value.
|
||||
bool vocab_only; // only load the vocabulary, no weights
|
||||
bool use_mmap; // use mmap if possible
|
||||
@ -185,17 +208,20 @@ extern "C" {
|
||||
// ref: https://github.com/ggerganov/llama.cpp/pull/2054
|
||||
float rope_freq_base; // RoPE base frequency, 0 = from model
|
||||
float rope_freq_scale; // RoPE frequency scaling factor, 0 = from model
|
||||
float yarn_ext_factor; // YaRN extrapolation mix factor, NaN = from model
|
||||
float yarn_ext_factor; // YaRN extrapolation mix factor, negative = from model
|
||||
float yarn_attn_factor; // YaRN magnitude scaling factor
|
||||
float yarn_beta_fast; // YaRN low correction dim
|
||||
float yarn_beta_slow; // YaRN high correction dim
|
||||
uint32_t yarn_orig_ctx; // YaRN original context size
|
||||
|
||||
enum ggml_type type_k; // data type for K cache
|
||||
enum ggml_type type_v; // data type for V cache
|
||||
|
||||
// Keep the booleans together to avoid misalignment during copy-by-value.
|
||||
bool mul_mat_q; // if true, use experimental mul_mat_q kernels (DEPRECATED - always true)
|
||||
bool f16_kv; // use fp16 for KV cache, fp32 otherwise
|
||||
bool logits_all; // the llama_eval() call computes all logits, not just the last one
|
||||
bool embedding; // embedding mode only
|
||||
bool mul_mat_q; // if true, use experimental mul_mat_q kernels (DEPRECATED - always true)
|
||||
bool logits_all; // the llama_eval() call computes all logits, not just the last one (DEPRECATED - set llama_batch.logits instead)
|
||||
bool embedding; // embedding mode only
|
||||
bool offload_kqv; // whether to offload the KQV ops (including the KV cache) to GPU
|
||||
};
|
||||
|
||||
// model quantization parameters
|
||||
@ -290,7 +316,9 @@ extern "C" {
|
||||
|
||||
LLAMA_API const struct llama_model * llama_get_model(const struct llama_context * ctx);
|
||||
|
||||
LLAMA_API int llama_n_ctx (const struct llama_context * ctx);
|
||||
// TODO: become more consistent with returned int types across the API
|
||||
LLAMA_API uint32_t llama_n_ctx (const struct llama_context * ctx);
|
||||
LLAMA_API uint32_t llama_n_batch (const struct llama_context * ctx);
|
||||
|
||||
LLAMA_API enum llama_vocab_type llama_vocab_type(const struct llama_model * model);
|
||||
|
||||
@ -301,6 +329,23 @@ extern "C" {
|
||||
// Get the model's RoPE frequency scaling factor
|
||||
LLAMA_API float llama_rope_freq_scale_train(const struct llama_model * model);
|
||||
|
||||
// Functions to access the model's GGUF metadata scalar values
|
||||
// - The functions return the length of the string on success, or -1 on failure
|
||||
// - The output string is always null-terminated and cleared on failure
|
||||
// - GGUF array values are not supported by these functions
|
||||
|
||||
// Get metadata value as a string by key name
|
||||
LLAMA_API int llama_model_meta_val_str(const struct llama_model * model, const char * key, char * buf, size_t buf_size);
|
||||
|
||||
// Get the number of metadata key/value pairs
|
||||
LLAMA_API int llama_model_meta_count(const struct llama_model * model);
|
||||
|
||||
// Get metadata key name by index
|
||||
LLAMA_API int llama_model_meta_key_by_index(const struct llama_model * model, int i, char * buf, size_t buf_size);
|
||||
|
||||
// Get metadata value as a string by index
|
||||
LLAMA_API int llama_model_meta_val_str_by_index(const struct llama_model * model, int i, char * buf, size_t buf_size);
|
||||
|
||||
// Get a string describing the model type
|
||||
LLAMA_API int llama_model_desc(const struct llama_model * model, char * buf, size_t buf_size);
|
||||
|
||||
@ -344,9 +389,60 @@ extern "C" {
|
||||
// KV cache
|
||||
//
|
||||
|
||||
// Returns the number of tokens in the KV cache
|
||||
LLAMA_API DEPRECATED(int llama_get_kv_cache_token_count(const struct llama_context * ctx),
|
||||
"avoid using this, it will be removed in the future, instead - count the tokens in user code");
|
||||
// Information associated with an individual cell in the KV cache view.
|
||||
struct llama_kv_cache_view_cell {
|
||||
// The position for this cell. Takes KV cache shifts into account.
|
||||
// May be negative if the cell is not populated.
|
||||
llama_pos pos;
|
||||
};
|
||||
|
||||
// An updateable view of the KV cache.
|
||||
struct llama_kv_cache_view {
|
||||
// Number of KV cache cells. This will be the same as the context size.
|
||||
int32_t n_cells;
|
||||
|
||||
// Maximum number of sequences that can exist in a cell. It's not an error
|
||||
// if there are more sequences in a cell than this value, however they will
|
||||
// not be visible in the view cells_sequences.
|
||||
int32_t n_max_seq;
|
||||
|
||||
// Number of tokens in the cache. For example, if there are two populated
|
||||
// cells, the first with 1 sequence id in it and the second with 2 sequence
|
||||
// ids then you'll have 3 tokens.
|
||||
int32_t token_count;
|
||||
|
||||
// Number of populated cache cells.
|
||||
int32_t used_cells;
|
||||
|
||||
// Maximum contiguous empty slots in the cache.
|
||||
int32_t max_contiguous;
|
||||
|
||||
// Index to the start of the max_contiguous slot range. Can be negative
|
||||
// when cache is full.
|
||||
int32_t max_contiguous_idx;
|
||||
|
||||
// Information for an individual cell.
|
||||
struct llama_kv_cache_view_cell * cells;
|
||||
|
||||
// The sequences for each cell. There will be n_max_seq items per cell.
|
||||
llama_seq_id * cells_sequences;
|
||||
};
|
||||
|
||||
// Create an empty KV cache view. (use only for debugging purposes)
|
||||
LLAMA_API struct llama_kv_cache_view llama_kv_cache_view_init(const struct llama_context * ctx, int32_t n_max_seq);
|
||||
|
||||
// Free a KV cache view. (use only for debugging purposes)
|
||||
LLAMA_API void llama_kv_cache_view_free(struct llama_kv_cache_view * view);
|
||||
|
||||
// Update the KV cache view structure with the current state of the KV cache. (use only for debugging purposes)
|
||||
LLAMA_API void llama_kv_cache_view_update(const struct llama_context * ctx, struct llama_kv_cache_view * view);
|
||||
|
||||
// Returns the number of tokens in the KV cache (slow, use only for debug)
|
||||
// If a KV cell has multiple sequences assigned to it, it will be counted multiple times
|
||||
LLAMA_API int llama_get_kv_cache_token_count(const struct llama_context * ctx);
|
||||
|
||||
// Returns the number of used KV cells (i.e. have at least one sequence assigned to them)
|
||||
LLAMA_API int llama_get_kv_cache_used_cells(const struct llama_context * ctx);
|
||||
|
||||
// Clear the KV cache
|
||||
LLAMA_API void llama_kv_cache_clear(
|
||||
@ -517,6 +613,12 @@ extern "C" {
|
||||
LLAMA_API llama_token llama_token_eos(const struct llama_model * model); // end-of-sentence
|
||||
LLAMA_API llama_token llama_token_nl (const struct llama_model * model); // next-line
|
||||
|
||||
// Returns -1 if unknown, 1 for true or 0 for false.
|
||||
LLAMA_API int llama_add_bos_token(const struct llama_model * model);
|
||||
|
||||
// Returns -1 if unknown, 1 for true or 0 for false.
|
||||
LLAMA_API int llama_add_eos_token(const struct llama_model * model);
|
||||
|
||||
// codellama infill tokens
|
||||
LLAMA_API llama_token llama_token_prefix(const struct llama_model * model); // Beginning of infill prefix
|
||||
LLAMA_API llama_token llama_token_middle(const struct llama_model * model); // Beginning of infill middle
|
||||
|
@ -282,7 +282,6 @@ int main(int argc, char ** argv) {
|
||||
// tune these to your liking
|
||||
lcparams.n_ctx = 2048;
|
||||
lcparams.seed = 1;
|
||||
lcparams.f16_kv = true;
|
||||
lcparams.n_threads = params.n_threads;
|
||||
|
||||
struct llama_context * ctx_llama = llama_new_context_with_model(model_llama, lcparams);
|
||||
|
@ -155,33 +155,33 @@ bool gpt2_model_load(const std::string & fname, gpt2_model & model, gpt_vocab &
|
||||
const int n_ctx = hparams.n_ctx;
|
||||
const int n_vocab = hparams.n_vocab;
|
||||
|
||||
ctx_size += n_embd*ggml_type_sizef(GGML_TYPE_F32); // ln_f_g
|
||||
ctx_size += n_embd*ggml_type_sizef(GGML_TYPE_F32); // ln_f_b
|
||||
ctx_size += ggml_row_size(GGML_TYPE_F32, n_embd); // ln_f_g
|
||||
ctx_size += ggml_row_size(GGML_TYPE_F32, n_embd); // ln_f_b
|
||||
|
||||
ctx_size += n_vocab*n_embd*ggml_type_sizef(wtype); // wte
|
||||
ctx_size += n_ctx*n_embd*ggml_type_sizef(GGML_TYPE_F32); // wpe
|
||||
ctx_size += n_vocab*n_embd*ggml_type_sizef(wtype); // lm_head
|
||||
ctx_size += n_vocab*ggml_row_size(wtype, n_embd); // wte
|
||||
ctx_size += n_ctx*ggml_row_size(GGML_TYPE_F32, n_embd); // wpe
|
||||
ctx_size += n_vocab*ggml_row_size(wtype, n_embd); // lm_head
|
||||
|
||||
ctx_size += n_layer*(n_embd*ggml_type_sizef(GGML_TYPE_F32)); // ln_1_g
|
||||
ctx_size += n_layer*(n_embd*ggml_type_sizef(GGML_TYPE_F32)); // ln_1_b
|
||||
ctx_size += n_layer*(ggml_row_size(GGML_TYPE_F32, n_embd)); // ln_1_g
|
||||
ctx_size += n_layer*(ggml_row_size(GGML_TYPE_F32, n_embd)); // ln_1_b
|
||||
|
||||
ctx_size += n_layer*(n_embd*ggml_type_sizef(GGML_TYPE_F32)); // ln_2_g
|
||||
ctx_size += n_layer*(n_embd*ggml_type_sizef(GGML_TYPE_F32)); // ln_2_b
|
||||
ctx_size += n_layer*(ggml_row_size(GGML_TYPE_F32, n_embd)); // ln_2_g
|
||||
ctx_size += n_layer*(ggml_row_size(GGML_TYPE_F32, n_embd)); // ln_2_b
|
||||
|
||||
ctx_size += n_layer*(3*n_embd*n_embd*ggml_type_sizef(wtype)); // c_attn_attn_w
|
||||
ctx_size += n_layer*( 3*n_embd*ggml_type_sizef(GGML_TYPE_F32)); // c_attn_attn_b
|
||||
ctx_size += n_layer*(ggml_row_size(wtype, 3*n_embd*n_embd)); // c_attn_attn_w
|
||||
ctx_size += n_layer*(ggml_row_size(GGML_TYPE_F32, 3*n_embd)); // c_attn_attn_b
|
||||
|
||||
ctx_size += n_layer*(n_embd*n_embd*ggml_type_sizef(wtype)); // c_attn_proj_w
|
||||
ctx_size += n_layer*( n_embd*ggml_type_sizef(GGML_TYPE_F32)); // c_attn_proj_b
|
||||
ctx_size += n_layer*(ggml_row_size(wtype, n_embd*n_embd)); // c_attn_proj_w
|
||||
ctx_size += n_layer*(ggml_row_size(GGML_TYPE_F32, n_embd)); // c_attn_proj_b
|
||||
|
||||
ctx_size += n_layer*(4*n_embd*n_embd*ggml_type_sizef(wtype)); // c_mlp_fc_w
|
||||
ctx_size += n_layer*( 4*n_embd*ggml_type_sizef(GGML_TYPE_F32)); // c_mlp_fc_b
|
||||
ctx_size += n_layer*(ggml_row_size(wtype, 4*n_embd*n_embd)); // c_mlp_fc_w
|
||||
ctx_size += n_layer*(ggml_row_size(GGML_TYPE_F32, 4*n_embd)); // c_mlp_fc_b
|
||||
|
||||
ctx_size += n_layer*(4*n_embd*n_embd*ggml_type_sizef(wtype)); // c_mlp_proj_w
|
||||
ctx_size += n_layer*( n_embd*ggml_type_sizef(GGML_TYPE_F32)); // c_mlp_proj_b
|
||||
ctx_size += n_layer*(ggml_row_size(wtype, 4*n_embd*n_embd)); // c_mlp_proj_w
|
||||
ctx_size += n_layer*(ggml_row_size(GGML_TYPE_F32, n_embd)); // c_mlp_proj_b
|
||||
|
||||
ctx_size += n_ctx*n_layer*n_embd*ggml_type_sizef(GGML_TYPE_F32); // memory_k
|
||||
ctx_size += n_ctx*n_layer*n_embd*ggml_type_sizef(GGML_TYPE_F32); // memory_v
|
||||
ctx_size += n_ctx*n_layer*ggml_row_size(GGML_TYPE_F32, n_embd); // memory_k
|
||||
ctx_size += n_ctx*n_layer*ggml_row_size(GGML_TYPE_F32, n_embd); // memory_v
|
||||
|
||||
ctx_size += (6 + 12*n_layer)*256; // object overhead
|
||||
|
||||
@ -524,8 +524,7 @@ bool gpt2_eval(
|
||||
struct ggml_tensor * KQ_scaled =
|
||||
ggml_scale(ctx0,
|
||||
KQ,
|
||||
ggml_new_f32(ctx0, 1.0f/sqrt(float(n_embd)/n_head))
|
||||
);
|
||||
1.0f/sqrt(float(n_embd)/n_head));
|
||||
|
||||
// KQ_masked = mask_past(KQ_scaled)
|
||||
// [n_past + N, N, 12]
|
||||
|
@ -155,33 +155,33 @@ bool gpt2_model_load(const std::string & fname, gpt2_model & model, gpt_vocab &
|
||||
const int n_ctx = hparams.n_ctx;
|
||||
const int n_vocab = hparams.n_vocab;
|
||||
|
||||
ctx_size += n_embd*ggml_type_sizef(GGML_TYPE_F32); // ln_f_g
|
||||
ctx_size += n_embd*ggml_type_sizef(GGML_TYPE_F32); // ln_f_b
|
||||
ctx_size += ggml_row_size(GGML_TYPE_F32, n_embd); // ln_f_g
|
||||
ctx_size += ggml_row_size(GGML_TYPE_F32, n_embd); // ln_f_b
|
||||
|
||||
ctx_size += n_vocab*n_embd*ggml_type_sizef(wtype); // wte
|
||||
ctx_size += n_ctx*n_embd*ggml_type_sizef(GGML_TYPE_F32); // wpe
|
||||
ctx_size += n_vocab*n_embd*ggml_type_sizef(wtype); // lm_head
|
||||
ctx_size += n_vocab*ggml_row_size(wtype, n_embd); // wte
|
||||
ctx_size += n_ctx*ggml_row_size(GGML_TYPE_F32, n_embd); // wpe
|
||||
ctx_size += n_vocab*ggml_row_size(wtype, n_embd); // lm_head
|
||||
|
||||
ctx_size += n_layer*(n_embd*ggml_type_sizef(GGML_TYPE_F32)); // ln_1_g
|
||||
ctx_size += n_layer*(n_embd*ggml_type_sizef(GGML_TYPE_F32)); // ln_1_b
|
||||
ctx_size += n_layer*(ggml_row_size(GGML_TYPE_F32, n_embd)); // ln_1_g
|
||||
ctx_size += n_layer*(ggml_row_size(GGML_TYPE_F32, n_embd)); // ln_1_b
|
||||
|
||||
ctx_size += n_layer*(n_embd*ggml_type_sizef(GGML_TYPE_F32)); // ln_2_g
|
||||
ctx_size += n_layer*(n_embd*ggml_type_sizef(GGML_TYPE_F32)); // ln_2_b
|
||||
ctx_size += n_layer*(ggml_row_size(GGML_TYPE_F32, n_embd)); // ln_2_g
|
||||
ctx_size += n_layer*(ggml_row_size(GGML_TYPE_F32, n_embd)); // ln_2_b
|
||||
|
||||
ctx_size += n_layer*(3*n_embd*n_embd*ggml_type_sizef(wtype)); // c_attn_attn_w
|
||||
ctx_size += n_layer*( 3*n_embd*ggml_type_sizef(GGML_TYPE_F32)); // c_attn_attn_b
|
||||
ctx_size += n_layer*(ggml_row_size(wtype, 3*n_embd*n_embd)); // c_attn_attn_w
|
||||
ctx_size += n_layer*(ggml_row_size(GGML_TYPE_F32, 3*n_embd)); // c_attn_attn_b
|
||||
|
||||
ctx_size += n_layer*(n_embd*n_embd*ggml_type_sizef(wtype)); // c_attn_proj_w
|
||||
ctx_size += n_layer*( n_embd*ggml_type_sizef(GGML_TYPE_F32)); // c_attn_proj_b
|
||||
ctx_size += n_layer*(ggml_row_size(wtype, n_embd*n_embd)); // c_attn_proj_w
|
||||
ctx_size += n_layer*(ggml_row_size(GGML_TYPE_F32, n_embd)); // c_attn_proj_b
|
||||
|
||||
ctx_size += n_layer*(4*n_embd*n_embd*ggml_type_sizef(wtype)); // c_mlp_fc_w
|
||||
ctx_size += n_layer*( 4*n_embd*ggml_type_sizef(GGML_TYPE_F32)); // c_mlp_fc_b
|
||||
ctx_size += n_layer*(ggml_row_size(wtype, 4*n_embd*n_embd)); // c_mlp_fc_w
|
||||
ctx_size += n_layer*(ggml_row_size(GGML_TYPE_F32, 4*n_embd)); // c_mlp_fc_b
|
||||
|
||||
ctx_size += n_layer*(4*n_embd*n_embd*ggml_type_sizef(wtype)); // c_mlp_proj_w
|
||||
ctx_size += n_layer*( n_embd*ggml_type_sizef(GGML_TYPE_F32)); // c_mlp_proj_b
|
||||
ctx_size += n_layer*(ggml_row_size(wtype, 4*n_embd*n_embd)); // c_mlp_proj_w
|
||||
ctx_size += n_layer*(ggml_row_size(GGML_TYPE_F32, n_embd)); // c_mlp_proj_b
|
||||
|
||||
ctx_size += n_ctx*n_layer*n_embd*ggml_type_sizef(GGML_TYPE_F32); // memory_k
|
||||
ctx_size += n_ctx*n_layer*n_embd*ggml_type_sizef(GGML_TYPE_F32); // memory_v
|
||||
ctx_size += n_ctx*n_layer*ggml_row_size(GGML_TYPE_F32, n_embd); // memory_k
|
||||
ctx_size += n_ctx*n_layer*ggml_row_size(GGML_TYPE_F32, n_embd); // memory_v
|
||||
|
||||
ctx_size += (6 + 12*n_layer)*256; // object overhead
|
||||
|
||||
@ -525,8 +525,7 @@ bool gpt2_eval(
|
||||
struct ggml_tensor * KQ_scaled =
|
||||
ggml_scale(ctx0,
|
||||
KQ,
|
||||
ggml_new_f32(ctx0, 1.0f/sqrt(float(n_embd)/n_head))
|
||||
);
|
||||
1.0f/sqrt(float(n_embd)/n_head));
|
||||
|
||||
// KQ_masked = mask_past(KQ_scaled)
|
||||
// [n_past + N, N, 12]
|
||||
|
9
examples/wchess/CMakeLists.txt
Normal file
@ -0,0 +1,9 @@
|
||||
set(CMAKE_CXX_STANDARD 11)
|
||||
|
||||
add_subdirectory(libwchess)
|
||||
|
||||
if (EMSCRIPTEN)
|
||||
add_subdirectory(wchess.wasm)
|
||||
else()
|
||||
add_subdirectory(wchess.cmd)
|
||||
endif()
|
45
examples/wchess/README.md
Normal file
@ -0,0 +1,45 @@
|
||||
# wchess
|
||||
|
||||
Voice-controlled chess using Whisper
|
||||
|
||||
Online demo: https://whisper.ggerganov.com/wchess/
|
||||
|
||||
https://github.com/ggerganov/whisper.cpp/assets/1991296/c2b2f03c-9684-49f3-8106-357d2d4e67fa
|
||||
|
||||
## Command-line tool
|
||||
|
||||
```bash
|
||||
mkdir build && cd build
|
||||
cmake -DWHISPER_SDL2=1 ..
|
||||
make -j
|
||||
|
||||
./bin/wchess -m ../models/ggml-base.en.bin
|
||||
|
||||
Move: start
|
||||
|
||||
a b c d e f g h
|
||||
r n b q k b n r 8
|
||||
p p p p p p p p 7
|
||||
. * . * . * . * 6
|
||||
* . * . * . * . 5
|
||||
. * . * . * . * 4
|
||||
* . * . * . * . 3
|
||||
P P P P P P P P 2
|
||||
R N B Q K B N R 1
|
||||
|
||||
White's turn
|
||||
[(l)isten/(p)ause/(q)uit]:
|
||||
```
|
||||
|
||||
## TODO
|
||||
|
||||
- Fix bugs in the chess moves logic
|
||||
- Improve web-browser audio capture - sometimes it does not record the voice properly
|
||||
- Add support for more languages by making the generated grammar string multilingual
|
||||
- Explore ways to improve the dynamic grammar to be narrower
|
||||
|
||||
PRs welcome!
|
||||
|
||||
## Thanks
|
||||
|
||||
- [chessboardjs](https://chessboardjs.com) for the neat chessboard JS library used in this demo
|
19
examples/wchess/libwchess/CMakeLists.txt
Normal file
@ -0,0 +1,19 @@
|
||||
add_library(wchess-core STATIC
|
||||
WChess.cpp
|
||||
WChess.h
|
||||
Chessboard.cpp
|
||||
Chessboard.h
|
||||
)
|
||||
|
||||
target_link_libraries(wchess-core
|
||||
PUBLIC
|
||||
whisper
|
||||
common
|
||||
)
|
||||
|
||||
target_include_directories(wchess-core
|
||||
PUBLIC
|
||||
"$<BUILD_INTERFACE:${CMAKE_CURRENT_SOURCE_DIR}>"
|
||||
)
|
||||
|
||||
# add_executable(test-chessboard test-chessboard.cpp Chessboard.cpp)
|
803
examples/wchess/libwchess/Chessboard.cpp
Normal file
@ -0,0 +1,803 @@
|
||||
#include "Chessboard.h"
|
||||
|
||||
#include <array>
|
||||
#include <vector>
|
||||
#include <algorithm>
|
||||
#include <cstring>
|
||||
#include <set>
|
||||
#include <list>
|
||||
#include <chrono>
|
||||
|
||||
namespace {
|
||||
constexpr std::array<const char*, 64> positions = {
|
||||
"a1", "b1", "c1", "d1", "e1", "f1", "g1", "h1",
|
||||
"a2", "b2", "c2", "d2", "e2", "f2", "g2", "h2",
|
||||
"a3", "b3", "c3", "d3", "e3", "f3", "g3", "h3",
|
||||
"a4", "b4", "c4", "d4", "e4", "f4", "g4", "h4",
|
||||
"a5", "b5", "c5", "d5", "e5", "f5", "g5", "h5",
|
||||
"a6", "b6", "c6", "d6", "e6", "f6", "g6", "h6",
|
||||
"a7", "b7", "c7", "d7", "e7", "f7", "g7", "h7",
|
||||
"a8", "b8", "c8", "d8", "e8", "f8", "g8", "h8",
|
||||
};
|
||||
constexpr char INVALID_POS = positions.size();
|
||||
constexpr int R = 0; // rank index
|
||||
constexpr int F = 1; // file index
|
||||
#define FILE (c[F] - '1')
|
||||
#define RANK (c[R] - 'a')
|
||||
constexpr char operator ""_P(const char * c, size_t size) {
|
||||
return size < 2 || RANK < 0 || RANK > 7 ||
|
||||
FILE < 0 || FILE > 7 ? INVALID_POS : FILE * 8 + RANK;
|
||||
}
|
||||
#undef FILE
|
||||
#undef RANK
|
||||
|
||||
struct sview {
|
||||
const char * ptr = nullptr;
|
||||
size_t size = 0;
|
||||
|
||||
sview() = default;
|
||||
sview(const char * p, size_t s) : ptr(p), size(s) {}
|
||||
sview(const std::string& s) : ptr(s.data()), size(s.size()) {}
|
||||
|
||||
size_t find(char del, size_t pos) {
|
||||
while (pos < size && ptr[pos] != del) ++pos;
|
||||
return pos < size ? pos : std::string::npos;
|
||||
}
|
||||
};
|
||||
|
||||
std::vector<sview> split(sview str, char del) {
|
||||
std::vector<sview> res;
|
||||
size_t cur = 0;
|
||||
size_t last = 0;
|
||||
while (cur != std::string::npos) {
|
||||
if (str.ptr[last] == ' ') {
|
||||
++last;
|
||||
continue;
|
||||
}
|
||||
cur = str.find(del, last);
|
||||
size_t len = cur == std::string::npos ? str.size - last : cur - last;
|
||||
res.emplace_back(str.ptr + last, len);
|
||||
last = cur + 1;
|
||||
}
|
||||
return res;
|
||||
}
|
||||
|
||||
char strToPos(sview str) {
|
||||
return operator ""_P(str.ptr, str.size);
|
||||
}
|
||||
|
||||
constexpr std::array<const char*, 6> pieceNames = {
|
||||
"pawn", "knight", "bishop", "rook", "queen", "king",
|
||||
};
|
||||
|
||||
static constexpr std::array<char, 6> blackShort = {
|
||||
'p', 'n', 'b', 'r', 'q', 'k',
|
||||
};
|
||||
static constexpr std::array<char, 6> whiteShort = {
|
||||
'P', 'N', 'B', 'R', 'Q', 'K',
|
||||
};
|
||||
|
||||
char strToType(sview str) {
|
||||
auto it = std::find_if(pieceNames.begin(), pieceNames.end(), [str] (const char* name) { return strncmp(name, str.ptr, str.size) == 0; });
|
||||
return it != pieceNames.end() ? it - pieceNames.begin() : pieceNames.size();
|
||||
}
|
||||
|
||||
// directions
|
||||
using Direction = std::array<char, 2>;
|
||||
|
||||
constexpr Direction N = {(char) 0, (char) 1};
|
||||
constexpr Direction NNE = {(char) 1, (char) 2};
|
||||
constexpr Direction NE = {(char) 1, (char) 1};
|
||||
constexpr Direction ENE = {(char) 2, (char) 1};
|
||||
constexpr Direction E = {(char) 1, (char) 0};
|
||||
constexpr Direction ESE = {(char) 2, (char) -1};
|
||||
constexpr Direction SE = {(char) 1, (char) -1};
|
||||
constexpr Direction SSE = {(char) 1, (char) -2};
|
||||
constexpr Direction S = {(char) 0, (char) -1};
|
||||
constexpr Direction SSW = {(char) -1, (char) -2};
|
||||
constexpr Direction SW = {(char) -1, (char) -1};
|
||||
constexpr Direction WSW = {(char) -2, (char) -1};
|
||||
constexpr Direction W = {(char) -1, (char) 0};
|
||||
constexpr Direction WNW = {(char) -2, (char) 1};
|
||||
constexpr Direction NW = {(char) -1, (char) 1};
|
||||
constexpr Direction NNW = {(char) -1, (char) 2};
|
||||
|
||||
char makeStep(char pos, const Direction& d) {
|
||||
char next[2] = { char(positions[pos][R] + d[R]) , char(positions[pos][F] + d[F]) };
|
||||
return strToPos(sview{next, sizeof(next)});
|
||||
}
|
||||
|
||||
template<class Modifier>
|
||||
char traverse(char pos, const Direction& d, const Modifier& m, int count = 8) {
|
||||
while (--count >= 0) {
|
||||
pos = makeStep(pos, d);
|
||||
if (pos == INVALID_POS || m(pos)) break;
|
||||
}
|
||||
return pos;
|
||||
}
|
||||
|
||||
Direction normalize(const Direction& distance) {
|
||||
//return {char((distance[R] > 0) - (distance[R] < 0)), char((distance[F] > 0) - (distance[F] < 0))};
|
||||
const int drp = distance[R] > 0 ? 1 : 0;
|
||||
const int drn = distance[R] < 0 ? 1 : 0;
|
||||
const int dfp = distance[F] > 0 ? 1 : 0;
|
||||
const int dfn = distance[F] < 0 ? 1 : 0;
|
||||
return {char(drp - drn), char(dfp - dfn)};
|
||||
}
|
||||
|
||||
struct Pin {
|
||||
Direction d;
|
||||
Piece* pinner;
|
||||
Piece* pinned;
|
||||
};
|
||||
using Pins = std::list<Pin>;
|
||||
using Board = std::array<Piece*, 64>;
|
||||
|
||||
std::vector<Direction> filter(const Direction& pin, std::initializer_list<Direction> directions) {
|
||||
if (pin[R] == 0 && pin[F] == 0) return directions;
|
||||
std::vector<Direction> result;
|
||||
for (auto& d : directions) {
|
||||
if ((d[R] == pin[R] || d[R] == -pin[R]) && (d[F] == pin[F] || d[F] == -pin[F])) result.push_back(d);
|
||||
}
|
||||
return result;
|
||||
}
|
||||
}
|
||||
|
||||
class Piece {
|
||||
public:
|
||||
enum Types : char {
|
||||
Pawn,
|
||||
Knight,
|
||||
Bishop,
|
||||
Rook,
|
||||
Queen,
|
||||
King,
|
||||
//
|
||||
NUM_PIECES
|
||||
};
|
||||
|
||||
enum Colors : char {
|
||||
White,
|
||||
Black,
|
||||
};
|
||||
|
||||
const char* name() const;
|
||||
char initial() const;
|
||||
Types type() const { return m_type; }
|
||||
Colors color() const { return m_color; }
|
||||
char pos() const { return m_pos; }
|
||||
void setPos(char pos) {
|
||||
m_pos = pos;
|
||||
invalidate();
|
||||
}
|
||||
const char* coord() const;
|
||||
const std::set<char>& allowed() const { return m_allowed; }
|
||||
bool canReach(char pos) const;
|
||||
virtual bool movePattern(char pos) const = 0;
|
||||
void take();
|
||||
virtual void reinit(const State& state) = 0;
|
||||
void invalidate();
|
||||
protected:
|
||||
Piece(Types type, Colors color, char pos, std::set<char> allowed)
|
||||
: m_type(type), m_color(color), m_pos(pos), m_allowed(std::move(allowed)) {}
|
||||
Piece(const Piece&) = delete;
|
||||
~Piece() = default;
|
||||
|
||||
const Types m_type;
|
||||
const Colors m_color;
|
||||
char m_pos;
|
||||
std::set<char> m_allowed;
|
||||
bool m_update = false;
|
||||
};
|
||||
|
||||
struct Pawn : public Piece {
|
||||
Pawn(Colors color, char pos, std::set<char> next) : Piece(Types::Pawn, color, pos, std::move(next)) {}
|
||||
|
||||
bool is_first_move() const {
|
||||
return m_color ? coord()[F] == '7' : coord()[F] == '2';
|
||||
}
|
||||
|
||||
virtual bool movePattern(char pos) const override {
|
||||
if (m_pos == INVALID_POS) return false;
|
||||
auto cur = coord();
|
||||
auto next = positions[pos];
|
||||
Direction distance = {char(next[R] - cur[R]), char(next[F] - cur[F])};
|
||||
char forward = m_color ? -1 : 1;
|
||||
return (forward == distance[F] && distance[R] * distance[R] <= 1)
|
||||
|| (is_first_move() && 2 * forward == distance[F] && distance[R] == 0);
|
||||
}
|
||||
|
||||
virtual void reinit(const State& state) override;
|
||||
};
|
||||
|
||||
struct Knight : public Piece {
|
||||
Knight(Colors color, char pos, std::set<char> next) : Piece(Types::Knight, color, pos, std::move(next)) {}
|
||||
|
||||
virtual bool movePattern(char pos) const override {
|
||||
if (m_pos == INVALID_POS) return false;
|
||||
auto cur = coord();
|
||||
auto next = positions[pos];
|
||||
Direction diff = {char(next[R] - cur[R]), char(next[F] - cur[F])};
|
||||
return diff[R]*diff[R] + diff[F]*diff[F] == 5;
|
||||
}
|
||||
|
||||
virtual void reinit(const State& state) override;
|
||||
};
|
||||
|
||||
struct Bishop : public Piece {
|
||||
Bishop(Colors color, char pos) : Piece(Types::Bishop, color, pos, {}) {}
|
||||
|
||||
virtual bool movePattern(char pos) const override {
|
||||
if (m_pos == INVALID_POS) return false;
|
||||
auto cur = coord();
|
||||
auto next = positions[pos];
|
||||
return cur[R] - cur[F] == next[R] - next[F] || cur[R] + cur[F] == next[R] + next[F];
|
||||
}
|
||||
|
||||
virtual void reinit(const State& state) override;
|
||||
};
|
||||
|
||||
struct Rook : public Piece {
|
||||
Rook(Colors color, char pos) : Piece(Types::Rook, color, pos, {}) {}
|
||||
|
||||
virtual bool movePattern(char pos) const override {
|
||||
if (m_pos == INVALID_POS) return false;
|
||||
auto cur = coord();
|
||||
auto next = positions[pos];
|
||||
return cur[R] == next[R] || cur[F] == next[F];
|
||||
}
|
||||
|
||||
virtual void reinit(const State& state) override;
|
||||
};
|
||||
|
||||
struct Queen : public Piece {
|
||||
Queen(Colors color, char pos) : Piece(Types::Queen, color, pos, {}) {}
|
||||
|
||||
virtual bool movePattern(char pos) const override {
|
||||
if (m_pos == INVALID_POS) return false;
|
||||
auto cur = coord();
|
||||
auto next = positions[pos];
|
||||
return cur[R] == next[R] || cur[F] == next[F] || cur[R] - cur[F] == next[R] - next[F] || cur[R] + cur[F] == next[R] + next[F];
|
||||
}
|
||||
|
||||
virtual void reinit(const State& state) override;
|
||||
};
|
||||
|
||||
struct King : public Piece {
|
||||
King(Colors color, char pos) : Piece(Types::King, color, pos, {}) {}
|
||||
|
||||
virtual bool movePattern(char pos) const override {
|
||||
if (m_pos == INVALID_POS) return false;
|
||||
auto cur = coord();
|
||||
auto next = positions[pos];
|
||||
Direction diff = {char(next[R] - cur[R]), char(next[F] - cur[F])};
|
||||
return diff[R]*diff[R] + diff[F]*diff[F] <= 2;
|
||||
}
|
||||
|
||||
virtual void reinit(const State& state) override;
|
||||
};
|
||||
|
||||
struct PieceSet {
|
||||
Piece* begin() { return &p1; }
|
||||
Piece* end() { return &r2 + 1; }
|
||||
const Piece* begin() const { return &p1; }
|
||||
const Piece* end() const { return &r2 + 1; }
|
||||
Piece& operator[](int i) { return *(begin() + i); }
|
||||
const Piece& operator[](int i) const { return *(begin() + i); }
|
||||
|
||||
Pawn p1;
|
||||
Pawn p2;
|
||||
Pawn p3;
|
||||
Pawn p4;
|
||||
Pawn p5;
|
||||
Pawn p6;
|
||||
Pawn p7;
|
||||
Pawn p8;
|
||||
Rook r1;
|
||||
Knight n1;
|
||||
Bishop b1;
|
||||
Queen q;
|
||||
King k;
|
||||
Bishop b2;
|
||||
Knight n2;
|
||||
Rook r2;
|
||||
};
|
||||
|
||||
struct State {
|
||||
State();
|
||||
PieceSet blacks;
|
||||
PieceSet whites;
|
||||
Board board;
|
||||
Pins blackPins;
|
||||
Pins whitePins;
|
||||
};
|
||||
|
||||
Direction findPin(const Piece& piece, const State& state) {
|
||||
auto& pins = piece.color() ? state.blackPins : state.whitePins;
|
||||
auto it = std::find_if(pins.begin(), pins.end(), [&] (const Pin& pin) { return pin.pinned == &piece; });
|
||||
if (it != pins.end()) return it->d;
|
||||
return {0, 0};
|
||||
}
|
||||
|
||||
struct Find {
|
||||
Find(const Board& board) : m_board(board) {}
|
||||
bool operator() (char pos) const { return m_board[pos]; }
|
||||
const Board& m_board;
|
||||
};
|
||||
|
||||
struct Add {
|
||||
Add(const Board& board, std::set<char>& moves, Piece::Colors color) : m_board(board), m_moves(moves), m_color(color) {}
|
||||
bool operator() (char pos) const {
|
||||
if (!m_board[pos] || m_board[pos]->color() != m_color) m_moves.insert(pos);
|
||||
return m_board[pos];
|
||||
}
|
||||
const Board& m_board;
|
||||
std::set<char>& m_moves;
|
||||
Piece::Colors m_color;
|
||||
};
|
||||
|
||||
void Pawn::reinit(const State& state) {
|
||||
if (m_pos == INVALID_POS) return;
|
||||
if (!m_update) return;
|
||||
m_update = false;
|
||||
m_allowed.clear();
|
||||
|
||||
auto pin = findPin(*this, state);
|
||||
|
||||
auto & left = m_color ? SW : NW;
|
||||
auto & right = m_color ? SE : NE;
|
||||
|
||||
for (auto& direction : filter(pin, { left, right })) {
|
||||
auto pos = makeStep(m_pos, direction);
|
||||
if (pos != INVALID_POS && state.board[pos] && state.board[pos]->color() != m_color) m_allowed.insert(pos);
|
||||
}
|
||||
|
||||
auto & forward = m_color ? S : N;
|
||||
if (!filter(pin, {forward}).empty()) {
|
||||
traverse(m_pos, forward, [&] (char pos) {
|
||||
if (!state.board[pos]) m_allowed.insert(pos);
|
||||
return state.board[pos] || !is_first_move();
|
||||
}, 2);
|
||||
}
|
||||
}
|
||||
|
||||
void Knight::reinit(const State& state) {
|
||||
if (m_pos == INVALID_POS) return;
|
||||
if (!m_update) return;
|
||||
m_update = false;
|
||||
m_allowed.clear();
|
||||
auto pin = findPin(*this, state);
|
||||
if (pin[R] != 0 || pin[F] != 0) return;
|
||||
for (auto& direction : { NNE, ENE, ESE, SSE, SSW, WSW, WNW, NNW }) {
|
||||
auto pos = makeStep(m_pos, direction);
|
||||
if (pos != INVALID_POS && (!state.board[pos] || state.board[pos]->color() != m_color)) m_allowed.insert(pos);
|
||||
}
|
||||
}
|
||||
|
||||
void Bishop::reinit(const State& state) {
|
||||
if (m_pos == INVALID_POS) return;
|
||||
if (!m_update) return;
|
||||
m_update = false;
|
||||
m_allowed.clear();
|
||||
auto pin = findPin(*this, state);
|
||||
for (auto& direction : filter(pin, { NE, SE, SW, NW })) {
|
||||
traverse(m_pos, direction, Add(state.board, m_allowed, m_color));
|
||||
}
|
||||
}
|
||||
|
||||
void Rook::reinit(const State& state) {
|
||||
if (m_pos == INVALID_POS) return;
|
||||
if (!m_update) return;
|
||||
m_update = false;
|
||||
m_allowed.clear();
|
||||
auto pin = findPin(*this, state);
|
||||
for (auto& direction : filter(pin, { N, E, S, W })) {
|
||||
traverse(m_pos, direction, Add(state.board, m_allowed, m_color));
|
||||
}
|
||||
}
|
||||
|
||||
void Queen::reinit(const State& state) {
|
||||
if (m_pos == INVALID_POS) return;
|
||||
if (!m_update) return;
|
||||
m_update = false;
|
||||
m_allowed.clear();
|
||||
auto pin = findPin(*this, state);
|
||||
for (auto& direction : filter(pin, { N, NE, E, SE, S, SW, W, NW })) {
|
||||
traverse(m_pos, direction, Add(state.board, m_allowed, m_color));
|
||||
}
|
||||
}
|
||||
|
||||
void King::reinit(const State& state) {
|
||||
if (m_pos == INVALID_POS) return;
|
||||
if (!m_update) return;
|
||||
m_update = false;
|
||||
m_allowed.clear();
|
||||
auto& enemyPieces = m_color ? state.whites : state.blacks;
|
||||
auto& pawnAttackLeft = m_color ? SW : NW;
|
||||
auto& pawnAttackRight = m_color ? SE : NE;
|
||||
for (auto& direction : { N, NE, E, SE, S, SW, W, NW }) {
|
||||
auto pos = makeStep(m_pos, direction);
|
||||
bool accept = pos != INVALID_POS && !(state.board[pos] && state.board[pos]->color() == m_color);
|
||||
if (accept) {
|
||||
for (auto& p : enemyPieces) {
|
||||
if (!p.movePattern(pos)) continue;
|
||||
if (p.type() == Piece::Knight || p.type() == Piece::King) {
|
||||
accept = false;
|
||||
break;
|
||||
}
|
||||
else if (p.type() == Piece::Pawn) {
|
||||
auto from = positions[pos];
|
||||
auto to = p.coord();
|
||||
Direction d {char(to[R] - from[R]), char(to[F] - from[F])};
|
||||
if (d == pawnAttackLeft || d == pawnAttackRight) {
|
||||
accept = false;
|
||||
break;
|
||||
}
|
||||
}
|
||||
else {
|
||||
auto from = positions[pos];
|
||||
auto to = p.coord();
|
||||
Direction d = normalize({char(to[R] - from[R]), char(to[F] - from[F])});
|
||||
auto reached = traverse(pos, d, Find(state.board));
|
||||
if (p.pos() == reached) {
|
||||
accept = false;
|
||||
break;
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
if (accept) m_allowed.insert(pos);
|
||||
}
|
||||
}
|
||||
|
||||
const char* Piece::name() const {
|
||||
static_assert(pieceNames.size() == Piece::NUM_PIECES, "Mismatch between piece names and types");
|
||||
return pieceNames[m_type];
|
||||
}
|
||||
|
||||
char Piece::initial() const {
|
||||
static_assert(blackShort.size() == Piece::NUM_PIECES, "Mismatch between piece names and types");
|
||||
static_assert(whiteShort.size() == Piece::NUM_PIECES, "Mismatch between piece names and types");
|
||||
return m_color ? blackShort[m_type] : whiteShort[m_type];
|
||||
}
|
||||
|
||||
void Piece::invalidate() {
|
||||
m_update = true;
|
||||
}
|
||||
|
||||
|
||||
const char* Piece::coord() const {
|
||||
if (m_pos == INVALID_POS) return "";
|
||||
return positions[m_pos];
|
||||
}
|
||||
|
||||
bool Piece::canReach(char pos) const {
|
||||
return movePattern(pos) && m_allowed.count(pos);
|
||||
}
|
||||
|
||||
void Piece::take() {
|
||||
m_pos = INVALID_POS;
|
||||
m_allowed = {};
|
||||
}
|
||||
|
||||
State::State()
|
||||
: blacks {
|
||||
{Piece::Black, "a7"_P, {"a5"_P, "a6"_P} },
|
||||
{Piece::Black, "b7"_P, {"b5"_P, "b6"_P} },
|
||||
{Piece::Black, "c7"_P, {"c5"_P, "c6"_P} },
|
||||
{Piece::Black, "d7"_P, {"d5"_P, "d6"_P} },
|
||||
{Piece::Black, "e7"_P, {"e5"_P, "e6"_P} },
|
||||
{Piece::Black, "f7"_P, {"f5"_P, "f6"_P} },
|
||||
{Piece::Black, "g7"_P, {"g5"_P, "g6"_P} },
|
||||
{Piece::Black, "h7"_P, {"h5"_P, "h6"_P} },
|
||||
{Piece::Black, "a8"_P},
|
||||
{Piece::Black, "b8"_P, {"a6"_P, "c6"_P} },
|
||||
{Piece::Black, "c8"_P},
|
||||
{Piece::Black, "d8"_P},
|
||||
{Piece::Black, "e8"_P},
|
||||
{Piece::Black, "f8"_P},
|
||||
{Piece::Black, "g8"_P, {"f6"_P, "h6"_P} },
|
||||
{Piece::Black, "h8"_P},
|
||||
}
|
||||
, whites {
|
||||
{Piece::White, "a2"_P, {"a3"_P, "a4"_P} },
|
||||
{Piece::White, "b2"_P, {"b3"_P, "b4"_P} },
|
||||
{Piece::White, "c2"_P, {"c3"_P, "c4"_P} },
|
||||
{Piece::White, "d2"_P, {"d3"_P, "d4"_P} },
|
||||
{Piece::White, "e2"_P, {"e3"_P, "e4"_P} },
|
||||
{Piece::White, "f2"_P, {"f3"_P, "f4"_P} },
|
||||
{Piece::White, "g2"_P, {"g3"_P, "g4"_P} },
|
||||
{Piece::White, "h2"_P, {"h3"_P, "h4"_P} },
|
||||
{Piece::White, "a1"_P},
|
||||
{Piece::White, "b1"_P, {"a3"_P, "c3"_P} },
|
||||
{Piece::White, "c1"_P},
|
||||
{Piece::White, "d1"_P},
|
||||
{Piece::White, "e1"_P},
|
||||
{Piece::White, "f1"_P},
|
||||
{Piece::White, "g1"_P, {"f3"_P, "h3"_P} },
|
||||
{Piece::White, "h1"_P},
|
||||
}
|
||||
, board {{
|
||||
&whites[ 8], &whites[ 9], &whites[10], &whites[11], &whites[12], &whites[13], &whites[14], &whites[15],
|
||||
&whites[ 0], &whites[ 1], &whites[ 2], &whites[ 3], &whites[ 4], &whites[ 5], &whites[ 6], &whites[ 7],
|
||||
nullptr, nullptr, nullptr, nullptr, nullptr, nullptr, nullptr, nullptr,
|
||||
nullptr, nullptr, nullptr, nullptr, nullptr, nullptr, nullptr, nullptr,
|
||||
nullptr, nullptr, nullptr, nullptr, nullptr, nullptr, nullptr, nullptr,
|
||||
nullptr, nullptr, nullptr, nullptr, nullptr, nullptr, nullptr, nullptr,
|
||||
&blacks[ 0], &blacks[ 1], &blacks[ 2], &blacks[ 3], &blacks[ 4], &blacks[ 5], &blacks[ 6], &blacks[ 7],
|
||||
&blacks[ 8], &blacks[ 9], &blacks[10], &blacks[11], &blacks[12], &blacks[13], &blacks[14], &blacks[15],
|
||||
}}
|
||||
{}
|
||||
|
||||
Chessboard::Chessboard()
|
||||
: m_state(new State())
|
||||
{
|
||||
setGrammar();
|
||||
}
|
||||
|
||||
Chessboard::~Chessboard() = default;
|
||||
|
||||
void Chessboard::setPrompt(const std::string& prompt) {
|
||||
m_prompt = prompt;
|
||||
setGrammar();
|
||||
}
|
||||
|
||||
void Chessboard::setGrammar() {
|
||||
m_grammar.clear();
|
||||
|
||||
std::string result;
|
||||
if (m_prompt.empty()) {
|
||||
result += "move ::= \" \" ((piece | frompos) \" \" \"to \"?)? topos\n";
|
||||
//result += "move ::= \" \" frompos \" \" \"to \"? topos\n";
|
||||
}
|
||||
else {
|
||||
// result += "move ::= prompt \" \" ((piece | frompos) \" \" \"to \"?)? topos\n"
|
||||
result += "move ::= prompt \" \" frompos \" \" \"to \"? topos\n"
|
||||
"prompt ::= \" " + m_prompt + "\"\n";
|
||||
}
|
||||
|
||||
std::set<Piece::Types> pieceTypes;
|
||||
std::set<char> from_pos;
|
||||
std::set<char> to_pos;
|
||||
auto& pieces = m_moveCounter % 2 ? m_state->blacks : m_state->whites;
|
||||
std::set<size_t> flags;
|
||||
for (auto& p : pieces) {
|
||||
if (p.allowed().empty()) continue;
|
||||
bool addPiece = false;
|
||||
if (!m_inCheck || p.type() == Piece::King) {
|
||||
to_pos.insert(p.allowed().begin(), p.allowed().end());
|
||||
addPiece = !p.allowed().empty();
|
||||
}
|
||||
else {
|
||||
for (auto move : p.allowed()) {
|
||||
if (m_allowedInCheck.count(move)) {
|
||||
to_pos.insert(move);
|
||||
addPiece = true;
|
||||
}
|
||||
}
|
||||
}
|
||||
if (addPiece) {
|
||||
pieceTypes.insert(p.type());
|
||||
from_pos.insert(p.pos());
|
||||
}
|
||||
}
|
||||
if (pieceTypes.empty()) return;
|
||||
|
||||
result += "piece ::= (";
|
||||
for (auto& p : pieceTypes) result += " \"" + std::string(pieceNames[p]) + "\" |";
|
||||
result.pop_back();
|
||||
result += ")\n\n";
|
||||
|
||||
result += "frompos ::= (";
|
||||
for (auto& p : from_pos) result += " \"" + std::string(positions[p]) + "\" |";
|
||||
result.pop_back();
|
||||
result += ")\n";
|
||||
|
||||
result += "topos ::= (";
|
||||
for (auto& p : to_pos) result += " \"" + std::string(positions[p]) + "\" |";
|
||||
result.pop_back();
|
||||
result += ")\n";
|
||||
|
||||
m_grammar = std::move(result);
|
||||
}
|
||||
|
||||
std::string Chessboard::stringifyBoard() {
|
||||
std::string result;
|
||||
result.reserve(16 + 2 * 64 + 16);
|
||||
for (char rank = 'a'; rank <= 'h'; ++rank) {
|
||||
result.push_back(rank);
|
||||
result.push_back(' ');
|
||||
}
|
||||
result.back() = '\n';
|
||||
for (int i = 7; i >= 0; --i) {
|
||||
for (int j = 0; j < 8; ++j) {
|
||||
auto p = m_state->board[i * 8 + j];
|
||||
if (p) result.push_back(p->initial());
|
||||
else result.push_back((i + j) % 2 ? '.' : '*');
|
||||
result.push_back(' ');
|
||||
}
|
||||
result.push_back('0' + i + 1);
|
||||
result.push_back('\n');
|
||||
}
|
||||
return result;
|
||||
}
|
||||
|
||||
std::string Chessboard::process(const std::string& command) {
|
||||
const auto t_start = std::chrono::high_resolution_clock::now();
|
||||
auto color = Piece::Colors(m_moveCounter % 2);
|
||||
Piece* piece = nullptr;
|
||||
auto pos_to = INVALID_POS;
|
||||
if (!parseCommand(command, piece, pos_to)) return "";
|
||||
|
||||
auto pos_from = piece->pos();
|
||||
|
||||
if (!move(*piece, pos_to)) return "";
|
||||
|
||||
flagUpdates(pos_from, pos_to);
|
||||
|
||||
detectChecks();
|
||||
|
||||
auto& enemyPieces = color ? m_state->whites : m_state->blacks;
|
||||
for (auto& p : enemyPieces) p.reinit(*m_state); // only enemy moves needed next
|
||||
|
||||
std::string result = {positions[pos_from][R], positions[pos_from][F], '-', positions[pos_to][R], positions[pos_to][F]};
|
||||
++m_moveCounter;
|
||||
setGrammar();
|
||||
const auto t_end = std::chrono::high_resolution_clock::now();
|
||||
auto t_ms = std::chrono::duration_cast<std::chrono::milliseconds>(t_end - t_start).count();
|
||||
fprintf(stdout, "%s: Move '%s%s%s', (t = %d ms)\n", __func__, "\033[1m", result.data(), "\033[0m", (int) t_ms);
|
||||
if (m_grammar.empty()) result.push_back('#');
|
||||
return result;
|
||||
}
|
||||
|
||||
bool Chessboard::parseCommand(const std::string& command, Piece*& piece, char& pos_to) {
|
||||
auto color = Piece::Colors(m_moveCounter % 2);
|
||||
fprintf(stdout, "%s: Command to %s: '%s%.*s%s'\n", __func__, (color ? "Black" : "White"), "\033[1m", int(command.size()), command.data(), "\033[0m");
|
||||
|
||||
if (command.empty()) return false;
|
||||
auto tokens = split(command, ' ');
|
||||
auto pos_from = INVALID_POS;
|
||||
auto type = Piece::Types::NUM_PIECES;
|
||||
if (tokens.size() == 1) {
|
||||
type = Piece::Types::Pawn;
|
||||
pos_to = strToPos(tokens.front());
|
||||
}
|
||||
else {
|
||||
pos_from = strToPos(tokens.front());
|
||||
if (pos_from == INVALID_POS) type = Piece::Types(strToType(tokens.front()));
|
||||
pos_to = strToPos(tokens.back());
|
||||
}
|
||||
if (pos_to == INVALID_POS) return false;
|
||||
if (pos_from == INVALID_POS) {
|
||||
if (type == Piece::Types::NUM_PIECES) return false;
|
||||
auto& pieces = color ? m_state->blacks : m_state->whites;
|
||||
for (auto& p : pieces) {
|
||||
if (p.type() == type && p.canReach(pos_to)) {
|
||||
pos_from = p.pos();
|
||||
break;
|
||||
}
|
||||
}
|
||||
}
|
||||
if (pos_from == INVALID_POS) return false;
|
||||
if (m_state->board[pos_from] == nullptr) return false;
|
||||
piece = m_state->board[pos_from];
|
||||
if (piece->color() != color) return false;
|
||||
return true;
|
||||
}
|
||||
|
||||
void Chessboard::flagUpdates(char pos_from, char pos_to) {
|
||||
auto color = Piece::Colors(m_moveCounter % 2);
|
||||
auto& enemyPieces = color ? m_state->whites : m_state->blacks;
|
||||
auto& ownPieces = color ? m_state->blacks : m_state->whites;
|
||||
for (auto& p : enemyPieces) {
|
||||
if (p.movePattern(pos_to) || p.movePattern(pos_from)) {
|
||||
updatePins(p);
|
||||
p.invalidate();
|
||||
}
|
||||
}
|
||||
|
||||
for (auto& p : ownPieces) {
|
||||
if (p.movePattern(pos_to) || p.movePattern(pos_from)) {
|
||||
updatePins(p);
|
||||
p.invalidate();
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
void Chessboard::updatePins(Piece& piece) {
|
||||
if (piece.type() == Piece::Pawn || piece.type() == Piece::Knight || piece.type() == Piece::King) return;
|
||||
auto& enemyPieces = piece.color() ? m_state->whites : m_state->blacks;
|
||||
auto& enemyPins = piece.color() ? m_state->whitePins : m_state->blackPins;
|
||||
auto& king = enemyPieces.k;
|
||||
auto it = std::find_if(enemyPins.begin(), enemyPins.end(), [&] (const Pin& pin) { return pin.pinner == &piece; });
|
||||
if (it != enemyPins.end()) {
|
||||
it->pinned->invalidate();
|
||||
enemyPins.erase(it);
|
||||
}
|
||||
if (piece.movePattern(king.pos())) {
|
||||
auto to = positions[king.pos()];
|
||||
auto from = piece.coord();
|
||||
Direction d = normalize({char(to[R] - from[R]), char(to[F] - from[F])});
|
||||
|
||||
auto reached = traverse(piece.pos(), d, Find(m_state->board));
|
||||
auto foundPiece = m_state->board[reached];
|
||||
if (&king == foundPiece) {
|
||||
// check
|
||||
king.invalidate();
|
||||
}
|
||||
else if (foundPiece && foundPiece->color() != piece.color()) {
|
||||
reached = traverse(reached, d, Find(m_state->board));
|
||||
if (&king == m_state->board[reached]) {
|
||||
enemyPins.push_back({d, &piece, foundPiece});
|
||||
foundPiece->invalidate();
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
void Chessboard::detectChecks() {
|
||||
auto color = Piece::Colors(m_moveCounter % 2);
|
||||
auto& enemyPieces = color ? m_state->whites : m_state->blacks;
|
||||
auto& ownPieces = color ? m_state->blacks : m_state->whites;
|
||||
auto& king = enemyPieces.k;
|
||||
auto& pawnAttackLeft = color ? SW : NW;
|
||||
auto& pawnAttackRight = color ? SE : NE;
|
||||
for (auto& p : ownPieces) {
|
||||
if (!p.movePattern(king.pos())) continue;
|
||||
auto to = positions[king.pos()];
|
||||
auto from = p.coord();
|
||||
|
||||
if (p.type() == Piece::Knight) {
|
||||
if (!m_inCheck) {
|
||||
m_allowedInCheck = { p.pos() };
|
||||
}
|
||||
else {
|
||||
m_allowedInCheck.clear();
|
||||
}
|
||||
m_inCheck = true;
|
||||
}
|
||||
else if (p.type() == Piece::Pawn) {
|
||||
Direction d {char(to[R] - from[R]), char(to[F] - from[F])};
|
||||
if (d == pawnAttackLeft || d == pawnAttackRight) {
|
||||
if (!m_inCheck) {
|
||||
m_allowedInCheck = { p.pos() };
|
||||
}
|
||||
else {
|
||||
m_allowedInCheck.clear();
|
||||
}
|
||||
m_inCheck = true;
|
||||
}
|
||||
}
|
||||
else {
|
||||
Direction d = normalize({char(to[R] - from[R]), char(to[F] - from[F])});
|
||||
std::set<char> tmp;
|
||||
auto pos = traverse(p.pos(), d, Add(m_state->board, tmp, king.color()));
|
||||
if (pos == king.pos()) {
|
||||
tmp.insert(p.pos());
|
||||
if (!m_inCheck) {
|
||||
m_allowedInCheck = std::move(tmp);
|
||||
}
|
||||
else {
|
||||
m_allowedInCheck.clear();
|
||||
}
|
||||
m_inCheck = true;
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
bool Chessboard::move(Piece& piece, char pos_to) {
|
||||
auto& allowed = piece.allowed();
|
||||
|
||||
if (allowed.count(pos_to) == 0 || (m_inCheck && piece.type() != Piece::King && m_allowedInCheck.count(pos_to) == 0)) return false;
|
||||
if (m_state->board[pos_to] && m_state->board[pos_to]->color() == piece.color()) return false;
|
||||
if (m_state->board[pos_to]) m_state->board[pos_to]->take();
|
||||
m_state->board[piece.pos()] = nullptr;
|
||||
m_state->board[pos_to] = &piece;
|
||||
piece.setPos(pos_to);
|
||||
|
||||
m_inCheck = false;
|
||||
m_allowedInCheck.clear();
|
||||
|
||||
return true;
|
||||
}
|
33
examples/wchess/libwchess/Chessboard.h
Normal file
@ -0,0 +1,33 @@
|
||||
#pragma once
|
||||
#include <string>
|
||||
#include <set>
|
||||
#include <memory>
|
||||
|
||||
// just basic validation
|
||||
// fixme: missing en passant, castling, promotion, etc.
|
||||
struct State;
|
||||
class Piece;
|
||||
class Chessboard {
|
||||
public:
|
||||
Chessboard();
|
||||
~Chessboard();
|
||||
std::string process(const std::string& command);
|
||||
std::string stringifyBoard();
|
||||
const std::string& grammar() { return m_grammar; }
|
||||
const std::string& prompt() { return m_prompt; }
|
||||
void setPrompt(const std::string& prompt);
|
||||
private:
|
||||
bool parseCommand(const std::string& command, Piece*& piece, char& pos_to);
|
||||
bool move(Piece& piece, char pos);
|
||||
void flagUpdates(char pos_from, char pos_to);
|
||||
void updatePins(Piece& piece);
|
||||
void detectChecks();
|
||||
void setGrammar();
|
||||
|
||||
std::unique_ptr<State> m_state;
|
||||
std::set<char> m_allowedInCheck;
|
||||
bool m_inCheck = false;
|
||||
int m_moveCounter = 0;
|
||||
std::string m_grammar;
|
||||
std::string m_prompt;
|
||||
};
|
193
examples/wchess/libwchess/WChess.cpp
Normal file
@ -0,0 +1,193 @@
|
||||
#include "WChess.h"
|
||||
#include "Chessboard.h"
|
||||
#include "grammar-parser.h"
|
||||
#include "common.h"
|
||||
#include <thread>
|
||||
|
||||
WChess::WChess(whisper_context * ctx,
|
||||
const whisper_full_params & wparams,
|
||||
callbacks cb,
|
||||
settings s)
|
||||
: m_ctx(ctx)
|
||||
, m_wparams(wparams)
|
||||
, m_cb(cb)
|
||||
, m_settings(s)
|
||||
, m_board(new Chessboard())
|
||||
{}
|
||||
|
||||
WChess::~WChess() = default;
|
||||
|
||||
void WChess::set_move(const std::string& moves, float prob) const {
|
||||
if (m_cb.set_move) (*m_cb.set_move)(moves, prob);
|
||||
}
|
||||
|
||||
void WChess::set_grammar(const std::string& grammar) const {
|
||||
if (m_cb.set_grammar) (*m_cb.set_grammar)(grammar);
|
||||
}
|
||||
|
||||
bool WChess::get_audio(std::vector<float>& pcmf32) const {
|
||||
if (m_cb.get_audio) return (*m_cb.get_audio)(pcmf32);
|
||||
return false;
|
||||
}
|
||||
|
||||
std::string WChess::stringify_board() const {
|
||||
return m_board->stringifyBoard();
|
||||
}
|
||||
|
||||
std::string WChess::get_grammar() const {
|
||||
return m_board->grammar();
|
||||
}
|
||||
|
||||
void WChess::run() {
|
||||
bool have_prompt = true;
|
||||
bool ask_prompt = !have_prompt;
|
||||
|
||||
float logprob_min = 0.0f;
|
||||
|
||||
float logprob_sum = 0.0f;
|
||||
|
||||
int n_tokens = 0;
|
||||
|
||||
std::vector<float> pcmf32_cur;
|
||||
std::vector<float> pcmf32_prompt;
|
||||
|
||||
const std::string k_prompt = have_prompt ? "" : "rook to d4, f3";
|
||||
int64_t t_ms = 0;
|
||||
|
||||
if (ask_prompt) {
|
||||
fprintf(stdout, "\n");
|
||||
fprintf(stdout, "%s: Say the following phrase: '%s%s%s'\n", __func__, "\033[1m", k_prompt.c_str(), "\033[0m");
|
||||
fprintf(stdout, "\n");
|
||||
|
||||
ask_prompt = false;
|
||||
}
|
||||
|
||||
while (get_audio(pcmf32_cur)) {
|
||||
if (!pcmf32_cur.empty()) {
|
||||
// fprintf(stdout, "%s: Processing ...\n", __func__);
|
||||
|
||||
if (!have_prompt) {
|
||||
const auto txt = ::trim(transcribe(pcmf32_cur, logprob_min, logprob_sum, n_tokens, t_ms));
|
||||
|
||||
fprintf(stdout, "%s: Heard '%s%s%s', (t = %d ms)\n", __func__, "\033[1m", txt.c_str(), "\033[0m", (int) t_ms);
|
||||
|
||||
const float sim = similarity(txt, k_prompt);
|
||||
|
||||
if (txt.length() < 0.8*k_prompt.length() || txt.length() > 1.2*k_prompt.length() || sim < 0.8f) {
|
||||
fprintf(stdout, "%s: WARNING: prompt not recognized, try again\n", __func__);
|
||||
ask_prompt = true;
|
||||
} else {
|
||||
fprintf(stdout, "\n");
|
||||
fprintf(stdout, "%s: The prompt has been recognized!\n", __func__);
|
||||
fprintf(stdout, "%s: Waiting for voice commands ...\n", __func__);
|
||||
fprintf(stdout, "\n");
|
||||
|
||||
// save the audio for the prompt
|
||||
pcmf32_prompt = pcmf32_cur;
|
||||
have_prompt = true;
|
||||
m_board->setPrompt(k_prompt);
|
||||
}
|
||||
} else {
|
||||
if (!pcmf32_prompt.empty()) pcmf32_cur.insert(pcmf32_cur.begin(), pcmf32_prompt.begin(), pcmf32_prompt.end());
|
||||
constexpr size_t MIN_SIZE = 1.2 * WHISPER_SAMPLE_RATE;
|
||||
if (MIN_SIZE > pcmf32_cur.size()) pcmf32_cur.insert(pcmf32_cur.begin(), MIN_SIZE - pcmf32_cur.size(), 0.0f);
|
||||
|
||||
// fprintf(stdout, "%s: grammar rules:\n'%s'\n", __func__, m_board->grammar().c_str());
|
||||
|
||||
auto grammar_parsed = grammar_parser::parse(m_board->grammar().c_str());
|
||||
auto grammar_rules = grammar_parsed.c_rules();
|
||||
|
||||
m_wparams.grammar_rules = grammar_rules.data();
|
||||
m_wparams.n_grammar_rules = grammar_rules.size();
|
||||
|
||||
m_wparams.i_start_rule = grammar_parsed.symbol_ids.at("move");
|
||||
auto txt = ::trim(transcribe(pcmf32_cur, logprob_min, logprob_sum, n_tokens, t_ms));
|
||||
|
||||
const float p = 100.0f * std::exp(logprob_min);
|
||||
|
||||
fprintf(stdout, "%s: heard '%s'\n", __func__, txt.c_str());
|
||||
|
||||
// find the prompt in the text
|
||||
float best_sim = 0.0f;
|
||||
size_t best_len = 0;
|
||||
for (int n = 0.8*k_prompt.size(); n <= 1.2*k_prompt.size(); ++n) {
|
||||
const auto prompt = txt.substr(0, n);
|
||||
|
||||
const float sim = similarity(prompt, k_prompt);
|
||||
|
||||
//fprintf(stderr, "%s: prompt = '%s', sim = %f\n", __func__, prompt.c_str(), sim);
|
||||
|
||||
if (sim > best_sim) {
|
||||
best_sim = sim;
|
||||
best_len = n;
|
||||
}
|
||||
}
|
||||
|
||||
fprintf(stdout, "%s: DEBUG: txt = '%s', prob = %.2f%%\n", __func__, txt.c_str(), p);
|
||||
std::string command = ::trim(txt.substr(best_len));
|
||||
|
||||
fprintf(stdout, "%s: Command '%s%s%s', (t = %d ms)\n", __func__, "\033[1m", command.c_str(), "\033[0m", (int) t_ms);
|
||||
fprintf(stdout, "\n");
|
||||
|
||||
if (!command.empty()) {
|
||||
set_move(m_board->process(command), p);
|
||||
set_grammar(m_board->grammar());
|
||||
}
|
||||
if (m_board->grammar().empty()) {
|
||||
fprintf(stdout, "%s: No more moves possible\n", __func__);
|
||||
break;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
if (ask_prompt) {
|
||||
fprintf(stdout, "\n");
|
||||
fprintf(stdout, "%s: Say the following phrase: '%s%s%s'\n", __func__, "\033[1m", k_prompt.c_str(), "\033[0m");
|
||||
fprintf(stdout, "\n");
|
||||
|
||||
ask_prompt = false;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
std::string WChess::transcribe(
|
||||
const std::vector<float> & pcmf32,
|
||||
float & logprob_min,
|
||||
float & logprob_sum,
|
||||
int & n_tokens,
|
||||
int64_t & t_ms) {
|
||||
const auto t_start = std::chrono::high_resolution_clock::now();
|
||||
|
||||
logprob_min = 0.0f;
|
||||
logprob_sum = 0.0f;
|
||||
n_tokens = 0;
|
||||
t_ms = 0;
|
||||
|
||||
if (whisper_full(m_ctx, m_wparams, pcmf32.data(), pcmf32.size()) != 0) {
|
||||
return {};
|
||||
}
|
||||
|
||||
std::string result;
|
||||
|
||||
const int n_segments = whisper_full_n_segments(m_ctx);
|
||||
for (int i = 0; i < n_segments; ++i) {
|
||||
const char * text = whisper_full_get_segment_text(m_ctx, i);
|
||||
|
||||
result += text;
|
||||
|
||||
const int n = whisper_full_n_tokens(m_ctx, i);
|
||||
for (int j = 0; j < n; ++j) {
|
||||
const auto token = whisper_full_get_token_data(m_ctx, i, j);
|
||||
|
||||
if(token.plog > 0.0f) return {};
|
||||
logprob_min = std::min(logprob_min, token.plog);
|
||||
logprob_sum += token.plog;
|
||||
++n_tokens;
|
||||
}
|
||||
}
|
||||
|
||||
const auto t_end = std::chrono::high_resolution_clock::now();
|
||||
t_ms = std::chrono::duration_cast<std::chrono::milliseconds>(t_end - t_start).count();
|
||||
|
||||
return result;
|
||||
}
|
63
examples/wchess/libwchess/WChess.h
Normal file
@ -0,0 +1,63 @@
|
||||
#pragma once
|
||||
#include "whisper.h"
|
||||
#include <string>
|
||||
#include <vector>
|
||||
#include <memory>
|
||||
|
||||
class Chessboard;
|
||||
|
||||
class WChess {
|
||||
public:
|
||||
using CheckRunningCb = bool (*)();
|
||||
using GetAudioCb = bool (*)(std::vector<float> &);
|
||||
using SetMovesCb = void (*)(const std::string &, float);
|
||||
using SetGrammarCb = void (*)(const std::string &);
|
||||
using ClearAudioCb = void (*)();
|
||||
|
||||
struct callbacks {
|
||||
GetAudioCb get_audio = nullptr;
|
||||
SetMovesCb set_move = nullptr;
|
||||
SetGrammarCb set_grammar = nullptr;
|
||||
};
|
||||
|
||||
struct settings {
|
||||
int32_t vad_ms = 2000;
|
||||
int32_t prompt_ms = 5000;
|
||||
int32_t command_ms = 4000;
|
||||
float vad_thold = 0.2f;
|
||||
float freq_thold = 100.0f;
|
||||
bool print_energy = false;
|
||||
};
|
||||
|
||||
WChess(
|
||||
whisper_context * ctx,
|
||||
const whisper_full_params & wparams,
|
||||
callbacks cb,
|
||||
settings s
|
||||
);
|
||||
~WChess();
|
||||
|
||||
void run();
|
||||
|
||||
std::string stringify_board() const;
|
||||
|
||||
std::string get_grammar() const;
|
||||
|
||||
private:
|
||||
bool get_audio(std::vector<float>& pcmf32) const;
|
||||
void set_move(const std::string& moves, float prob) const;
|
||||
void set_grammar(const std::string& grammar) const;
|
||||
|
||||
std::string transcribe(
|
||||
const std::vector<float> & pcmf32,
|
||||
float & logprob_min,
|
||||
float & logprob_sum,
|
||||
int & n_tokens,
|
||||
int64_t & t_ms);
|
||||
|
||||
whisper_context * m_ctx;
|
||||
whisper_full_params m_wparams;
|
||||
const callbacks m_cb;
|
||||
const settings m_settings;
|
||||
std::unique_ptr<Chessboard> m_board;
|
||||
};
|
117
examples/wchess/libwchess/test-chessboard.cpp
Normal file
@ -0,0 +1,117 @@
|
||||
#include "Chessboard.h"
|
||||
|
||||
#define ASSERT(x) \
|
||||
do { \
|
||||
if (!(x)) { \
|
||||
fprintf(stderr, "ASSERT: %s:%d: %s\n", __FILE__, __LINE__, #x); \
|
||||
fflush(stderr); \
|
||||
exit(1); \
|
||||
} \
|
||||
} while (0)
|
||||
|
||||
|
||||
int main() {
|
||||
{
|
||||
Chessboard chess;
|
||||
|
||||
ASSERT(chess.process("pawn to d4") == "d2-d4");
|
||||
ASSERT(chess.process("e5") == "e7-e5");
|
||||
ASSERT(chess.process("c1 h6") == "c1-h6");
|
||||
ASSERT(chess.process("queen h4") == "d8-h4");
|
||||
ASSERT(chess.process("bishop to g5") == "h6-g5");
|
||||
ASSERT(chess.process("bishop to b4") == "f8-b4");
|
||||
ASSERT(chess.process("c4") == "");
|
||||
ASSERT(chess.process("knight c3") == "b1-c3");
|
||||
ASSERT(chess.process("knight c6") == "b8-c6");
|
||||
ASSERT(chess.process("f3") == "");
|
||||
}
|
||||
|
||||
{
|
||||
Chessboard chess;
|
||||
|
||||
ASSERT(chess.process("d4") == "d2-d4");
|
||||
ASSERT(chess.process("e5") == "e7-e5");
|
||||
ASSERT(chess.process("e4") == "e2-e4");
|
||||
ASSERT(chess.process("queen h4") == "d8-h4");
|
||||
ASSERT(chess.process("queen h5") == "d1-h5");
|
||||
ASSERT(chess.process("f5") == "");
|
||||
ASSERT(chess.process("g6") == "g7-g6");
|
||||
ASSERT(chess.process("knight e2") == "g1-e2");
|
||||
ASSERT(chess.process("f5") == "f7-f5");
|
||||
ASSERT(chess.process("knight g3") == "e2-g3");
|
||||
ASSERT(chess.process("g5") == "");
|
||||
ASSERT(chess.process("king e7") == "e8-e7");
|
||||
ASSERT(chess.process("f4") == "f2-f4");
|
||||
ASSERT(chess.process("g5") == "g6-g5");
|
||||
}
|
||||
|
||||
{
|
||||
Chessboard chess;
|
||||
|
||||
ASSERT(chess.process("e4") == "e2-e4");
|
||||
ASSERT(chess.process("c5") == "c7-c5");
|
||||
ASSERT(chess.process("e5") == "e4-e5");
|
||||
ASSERT(chess.process("c4") == "c5-c4");
|
||||
ASSERT(chess.process("e6") == "e5-e6");
|
||||
ASSERT(chess.process("c3") == "c4-c3");
|
||||
ASSERT(chess.process("e7") == "");
|
||||
ASSERT(chess.process("f7") == "e6-f7");
|
||||
ASSERT(chess.process("d2") == "");
|
||||
ASSERT(chess.process("king to f7") == "e8-f7");
|
||||
ASSERT(chess.process("f4") == "f2-f4");
|
||||
ASSERT(chess.process("d2") == "c3-d2");
|
||||
ASSERT(chess.process("f5") == "");
|
||||
ASSERT(chess.process("king to e2") == "e1-e2");
|
||||
ASSERT(chess.process("king to g6") == "f7-g6");
|
||||
ASSERT(chess.process("f5") == "f4-f5");
|
||||
ASSERT(chess.process("e6") == "");
|
||||
ASSERT(chess.process("king to h5") == "g6-h5");
|
||||
ASSERT(chess.process("g4") == "g2-g4");
|
||||
ASSERT(chess.process("king to g5") == "h5-g5");
|
||||
ASSERT(chess.process("h4") == "h2-h4");
|
||||
ASSERT(chess.process("king to h5") == "");
|
||||
ASSERT(chess.process("king to g6") == "");
|
||||
ASSERT(chess.process("king to h6") == "g5-h6");
|
||||
ASSERT(chess.process("bishop to d2") == "c1-d2");
|
||||
ASSERT(chess.process("king to g5") == "");
|
||||
ASSERT(chess.process("g5") == "g7-g5");
|
||||
}
|
||||
|
||||
{
|
||||
Chessboard chess;
|
||||
ASSERT(chess.process("f4") == "f2-f4");
|
||||
ASSERT(chess.process("e5") == "e7-e5");
|
||||
ASSERT(chess.process("g4") == "g2-g4");
|
||||
ASSERT(chess.process("queen to h4") == "d8-h4#");
|
||||
ASSERT(chess.process("knight f3") == "");
|
||||
ASSERT(chess.grammar().empty());
|
||||
}
|
||||
|
||||
{
|
||||
Chessboard chess;
|
||||
ASSERT(chess.process("f4") == "f2-f4");
|
||||
ASSERT(chess.process("e5") == "e7-e5");
|
||||
ASSERT(chess.process("g4") == "g2-g4");
|
||||
ASSERT(chess.process("d5") == "d7-d5");
|
||||
ASSERT(chess.process("g1 f3") == "g1-f3");
|
||||
ASSERT(chess.process("queen to h4") == "d8-h4");
|
||||
ASSERT(!chess.grammar().empty());
|
||||
}
|
||||
|
||||
{
|
||||
Chessboard chess;
|
||||
ASSERT(chess.process("knight c3") == "b1-c3");
|
||||
ASSERT(chess.process("knight c6") == "b8-c6");
|
||||
ASSERT(chess.process("knight b5") == "c3-b5");
|
||||
ASSERT(chess.process("knight f6") == "g8-f6");
|
||||
ASSERT(chess.process("knight d6") == "b5-d6");
|
||||
ASSERT(chess.process("knight d4") == "");
|
||||
ASSERT(chess.process("d6") == "c7-d6");
|
||||
ASSERT(chess.process("e4") == "e2-e4");
|
||||
ASSERT(chess.process("knight d4") == "c6-d4");
|
||||
ASSERT(chess.process("d3") == "d2-d3");
|
||||
ASSERT(chess.process("knight e4") == "f6-e4");
|
||||
ASSERT(chess.process("king to e2") == "");
|
||||
ASSERT(chess.process("king to d2") == "");
|
||||
}
|
||||
}
|
8
examples/wchess/wchess.cmd/CMakeLists.txt
Normal file
@ -0,0 +1,8 @@
|
||||
if (WHISPER_SDL2)
|
||||
set(TARGET wchess)
|
||||
add_executable(${TARGET} wchess.cmd.cpp)
|
||||
|
||||
include(DefaultTargetOptions)
|
||||
|
||||
target_link_libraries(${TARGET} PRIVATE wchess-core common-sdl ${CMAKE_THREAD_LIBS_INIT})
|
||||
endif ()
|
247
examples/wchess/wchess.cmd/wchess.cmd.cpp
Normal file
@ -0,0 +1,247 @@
|
||||
// Command line voice assisted chess
|
||||
//
|
||||
// Speak chess move commands to the microphone.
|
||||
// The moves will translated to chessboard positions.
|
||||
//
|
||||
//
|
||||
|
||||
#include "WChess.h"
|
||||
#include "common-sdl.h"
|
||||
#include <iostream>
|
||||
|
||||
#include <memory>
|
||||
#include <thread>
|
||||
|
||||
// command-line parameters
|
||||
struct whisper_params {
|
||||
int32_t n_threads = std::min(4, (int32_t) std::thread::hardware_concurrency());
|
||||
int32_t prompt_ms = 5000;
|
||||
int32_t command_ms = 8000;
|
||||
int32_t capture_id = -1;
|
||||
int32_t max_tokens = 32;
|
||||
int32_t audio_ctx = 0;
|
||||
|
||||
float vad_thold = 0.6f;
|
||||
float freq_thold = 100.0f;
|
||||
|
||||
float grammar_penalty = 100.0f;
|
||||
|
||||
bool speed_up = false;
|
||||
bool translate = false;
|
||||
bool print_special = false;
|
||||
bool print_energy = false;
|
||||
bool no_timestamps = true;
|
||||
bool use_gpu = true;
|
||||
|
||||
std::string language = "en";
|
||||
std::string model = "models/ggml-base.en.bin";
|
||||
std::string fname_out;
|
||||
std::string commands;
|
||||
std::string prompt;
|
||||
std::string context;
|
||||
std::string grammar;
|
||||
};
|
||||
|
||||
void whisper_print_usage(int /*argc*/, char ** argv, const whisper_params & params) {
|
||||
fprintf(stderr, "\n");
|
||||
fprintf(stderr, "usage: %s [options]\n", argv[0]);
|
||||
fprintf(stderr, "\n");
|
||||
fprintf(stderr, "options:\n");
|
||||
fprintf(stderr, " -h, --help [default] show this help message and exit\n");
|
||||
fprintf(stderr, " -t N, --threads N [%-7d] number of threads to use during computation\n", params.n_threads);
|
||||
fprintf(stderr, " -pms N, --prompt-ms N [%-7d] prompt duration in milliseconds\n", params.prompt_ms);
|
||||
fprintf(stderr, " -cms N, --command-ms N [%-7d] command duration in milliseconds\n", params.command_ms);
|
||||
fprintf(stderr, " -c ID, --capture ID [%-7d] capture device ID\n", params.capture_id);
|
||||
fprintf(stderr, " -mt N, --max-tokens N [%-7d] maximum number of tokens per audio chunk\n", params.max_tokens);
|
||||
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, " -l LANG, --language LANG [%-7s] spoken language\n", params.language.c_str());
|
||||
fprintf(stderr, " -m FNAME, --model FNAME [%-7s] model path\n", params.model.c_str());
|
||||
fprintf(stderr, " -f FNAME, --file FNAME [%-7s] text output file name\n", params.fname_out.c_str());
|
||||
fprintf(stderr, " -cmd FNAME, --commands FNAME [%-7s] text file with allowed commands\n", params.commands.c_str());
|
||||
fprintf(stderr, " -p, --prompt [%-7s] the required activation prompt\n", params.prompt.c_str());
|
||||
fprintf(stderr, " -ctx, --context [%-7s] sample text to help the transcription\n", params.context.c_str());
|
||||
fprintf(stderr, " --grammar-penalty N [%-7.1f] scales down logits of nongrammar tokens\n", params.grammar_penalty);
|
||||
fprintf(stderr, "\n");
|
||||
}
|
||||
|
||||
bool whisper_params_parse(int argc, char ** argv, whisper_params & params) {
|
||||
for (int i = 1; i < argc; i++) {
|
||||
std::string arg = argv[i];
|
||||
|
||||
if (arg == "-h" || arg == "--help") {
|
||||
whisper_print_usage(argc, argv, params);
|
||||
exit(0);
|
||||
}
|
||||
else if (arg == "-t" || arg == "--threads") { params.n_threads = std::stoi(argv[++i]); }
|
||||
else if (arg == "-pms" || arg == "--prompt-ms") { params.prompt_ms = std::stoi(argv[++i]); }
|
||||
else if (arg == "-cms" || arg == "--command-ms") { params.command_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 == "-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 == "-l" || arg == "--language") { params.language = argv[++i]; }
|
||||
else if (arg == "-m" || arg == "--model") { params.model = argv[++i]; }
|
||||
else if (arg == "-f" || arg == "--file") { params.fname_out = argv[++i]; }
|
||||
else if (arg == "-cmd" || arg == "--commands") { params.commands = argv[++i]; }
|
||||
else if (arg == "-p" || arg == "--prompt") { params.prompt = argv[++i]; }
|
||||
else if (arg == "-ctx" || arg == "--context") { params.context = argv[++i]; }
|
||||
else if ( arg == "--grammar-penalty") { params.grammar_penalty = std::stof(argv[++i]); }
|
||||
else {
|
||||
fprintf(stderr, "error: unknown argument: %s\n", arg.c_str());
|
||||
whisper_print_usage(argc, argv, params);
|
||||
exit(0);
|
||||
}
|
||||
}
|
||||
|
||||
return true;
|
||||
}
|
||||
|
||||
std::unique_ptr<WChess> g_wchess;
|
||||
int g_moveCount = 0;
|
||||
void set_move(const std::string & move, float) {
|
||||
if (!move.empty()) {
|
||||
g_moveCount++;
|
||||
fprintf(stdout, "Move: %s\n\n", move.c_str());
|
||||
}
|
||||
else fprintf(stdout, "Move rejected\n\n");
|
||||
fprintf(stdout, "%s\n", g_wchess->stringify_board().c_str());
|
||||
fprintf(stdout, "%s\n", g_moveCount ? "White's turn" : "Black's turn");
|
||||
}
|
||||
|
||||
audio_async g_audio(30*1000);
|
||||
bool g_listening = false;
|
||||
std::vector<float> g_pcmf32;
|
||||
|
||||
bool read_input() {
|
||||
std::string input;
|
||||
while (true) {
|
||||
fprintf(stdout, "[(l)isten/(p)ause/(q)uit]: ");
|
||||
std::cin >> input;
|
||||
fprintf(stdout, "\n");
|
||||
if (input[0] == 'q') {
|
||||
fprintf(stdout, "Quitting\n");
|
||||
return false;
|
||||
}
|
||||
if (input[0] == 'l') {
|
||||
if (!g_listening) {
|
||||
fprintf(stdout, "Listening\n");
|
||||
g_listening = true;
|
||||
g_pcmf32.clear();
|
||||
g_audio.resume();
|
||||
g_audio.clear();
|
||||
}
|
||||
else fprintf(stdout, "Still listening\n");
|
||||
return true;
|
||||
}
|
||||
else {
|
||||
if (g_listening) {
|
||||
g_listening = false;
|
||||
g_audio.get(0, g_pcmf32);
|
||||
g_audio.pause();
|
||||
fprintf(stdout, "Processing\n");
|
||||
}
|
||||
else fprintf(stdout, "Not listening\n");
|
||||
return true;
|
||||
}
|
||||
}
|
||||
return true;
|
||||
}
|
||||
|
||||
bool get_audio(std::vector<float> & pcmf32_cur) {
|
||||
if (!read_input()) return false;
|
||||
if (!g_pcmf32.empty()) pcmf32_cur = std::move(g_pcmf32);
|
||||
else pcmf32_cur.clear();
|
||||
return true;
|
||||
}
|
||||
|
||||
int main(int argc, char ** argv) {
|
||||
whisper_params params;
|
||||
|
||||
if (whisper_params_parse(argc, argv, params) == false) {
|
||||
return 1;
|
||||
}
|
||||
|
||||
if (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);
|
||||
}
|
||||
|
||||
// whisper init
|
||||
|
||||
struct whisper_context_params cparams;
|
||||
cparams.use_gpu = params.use_gpu;
|
||||
|
||||
struct whisper_context * ctx = whisper_init_from_file_with_params(params.model.c_str(), cparams);
|
||||
if (!ctx) {
|
||||
fprintf(stderr, "%s: whisper_init_from_file_with_params() failed!\n", __func__);
|
||||
return 1;
|
||||
}
|
||||
|
||||
// init audio
|
||||
|
||||
if (!g_audio.init(params.capture_id, WHISPER_SAMPLE_RATE)) {
|
||||
fprintf(stderr, "%s: audio.init() failed!\n", __func__);
|
||||
return 1;
|
||||
}
|
||||
|
||||
struct whisper_full_params wparams = whisper_full_default_params(whisper_sampling_strategy::WHISPER_SAMPLING_GREEDY);
|
||||
wparams.offset_ms = 0;
|
||||
wparams.translate = false;
|
||||
wparams.no_context = true;
|
||||
wparams.single_segment = true;
|
||||
wparams.print_realtime = false;
|
||||
wparams.print_progress = false;
|
||||
wparams.print_timestamps = true;
|
||||
wparams.print_special = false;
|
||||
wparams.no_timestamps = true;
|
||||
|
||||
wparams.max_tokens = 32;
|
||||
wparams.audio_ctx = 768; // partial encoder context for better performance
|
||||
|
||||
wparams.temperature = 0.0f;
|
||||
wparams.temperature_inc = 2.0f;
|
||||
wparams.greedy.best_of = 1;
|
||||
|
||||
wparams.beam_search.beam_size = 1;
|
||||
|
||||
wparams.language = "en";
|
||||
|
||||
wparams.grammar_penalty = 100.0;
|
||||
|
||||
wparams.initial_prompt = params.context.data();
|
||||
|
||||
WChess::callbacks cb;
|
||||
cb.get_audio = get_audio;
|
||||
cb.set_move = set_move;
|
||||
|
||||
WChess::settings s;
|
||||
s.vad_ms = 2000;
|
||||
s.prompt_ms = params.prompt_ms;
|
||||
s.command_ms = params.command_ms;
|
||||
s.vad_thold = params.vad_thold;
|
||||
s.freq_thold = params.freq_thold;
|
||||
s.print_energy = params.print_energy;
|
||||
|
||||
g_wchess.reset(new WChess(ctx, wparams, cb, s));
|
||||
set_move("start", 0);
|
||||
g_wchess->run();
|
||||
|
||||
whisper_print_timings(ctx);
|
||||
whisper_free(ctx);
|
||||
|
||||
return 0;
|
||||
}
|
51
examples/wchess/wchess.wasm/CMakeLists.txt
Normal file
@ -0,0 +1,51 @@
|
||||
set(TARGET wchess.wasm)
|
||||
|
||||
add_executable(${TARGET}
|
||||
wchess.wasm.cpp
|
||||
)
|
||||
|
||||
include(DefaultTargetOptions)
|
||||
|
||||
target_link_libraries(${TARGET} PRIVATE
|
||||
common
|
||||
wchess-core
|
||||
)
|
||||
|
||||
unset(EXTRA_FLAGS)
|
||||
|
||||
if (WHISPER_WASM_SINGLE_FILE)
|
||||
set(EXTRA_FLAGS "-s SINGLE_FILE=1")
|
||||
message(STATUS "Embedding WASM inside chess.js")
|
||||
|
||||
add_custom_command(
|
||||
TARGET ${TARGET} POST_BUILD
|
||||
COMMAND ${CMAKE_COMMAND} -E copy
|
||||
${CMAKE_BINARY_DIR}/bin/${TARGET}.js
|
||||
${CMAKE_RUNTIME_OUTPUT_DIRECTORY}/${TARGET}/js/chess.js
|
||||
)
|
||||
endif()
|
||||
|
||||
set_target_properties(${TARGET} PROPERTIES LINK_FLAGS " \
|
||||
--bind \
|
||||
-s USE_PTHREADS=1 \
|
||||
-s PTHREAD_POOL_SIZE=8 \
|
||||
-s INITIAL_MEMORY=1024MB \
|
||||
-s TOTAL_MEMORY=1024MB \
|
||||
-s FORCE_FILESYSTEM=1 \
|
||||
-s EXPORTED_RUNTIME_METHODS=\"['print', 'printErr', 'ccall', 'cwrap']\" \
|
||||
${EXTRA_FLAGS} \
|
||||
")
|
||||
|
||||
|
||||
add_custom_command(
|
||||
TARGET ${TARGET} POST_BUILD
|
||||
COMMAND ${CMAKE_COMMAND} -E copy_directory
|
||||
${CMAKE_CURRENT_SOURCE_DIR}/chessboardjs-1.0.0
|
||||
${CMAKE_RUNTIME_OUTPUT_DIRECTORY}/${TARGET}/
|
||||
COMMAND ${CMAKE_COMMAND} -E copy
|
||||
${CMAKE_CURRENT_SOURCE_DIR}/jquery-3.7.1.min.js
|
||||
${CMAKE_RUNTIME_OUTPUT_DIRECTORY}/${TARGET}/js/
|
||||
)
|
||||
|
||||
configure_file(${CMAKE_CURRENT_SOURCE_DIR}/index-tmpl.html ${CMAKE_RUNTIME_OUTPUT_DIRECTORY}/${TARGET}/index.html @ONLY)
|
||||
configure_file(${CMAKE_SOURCE_DIR}/examples/helpers.js ${CMAKE_RUNTIME_OUTPUT_DIRECTORY}/${TARGET}/js/helpers.js @ONLY)
|
@ -0,0 +1,54 @@
|
||||
/*! chessboard.js v1.0.0 | (c) 2019 Chris Oakman | MIT License chessboardjs.com/license */
|
||||
|
||||
.clearfix-7da63 {
|
||||
clear: both;
|
||||
}
|
||||
|
||||
.board-b72b1 {
|
||||
border: 2px solid #404040;
|
||||
box-sizing: content-box;
|
||||
}
|
||||
|
||||
.square-55d63 {
|
||||
float: left;
|
||||
position: relative;
|
||||
|
||||
/* disable any native browser highlighting */
|
||||
-webkit-touch-callout: none;
|
||||
-webkit-user-select: none;
|
||||
-khtml-user-select: none;
|
||||
-moz-user-select: none;
|
||||
-ms-user-select: none;
|
||||
user-select: none;
|
||||
}
|
||||
|
||||
.white-1e1d7 {
|
||||
background-color: #f0d9b5;
|
||||
color: #b58863;
|
||||
}
|
||||
|
||||
.black-3c85d {
|
||||
background-color: #b58863;
|
||||
color: #f0d9b5;
|
||||
}
|
||||
|
||||
.highlight1-32417, .highlight2-9c5d2 {
|
||||
box-shadow: inset 0 0 3px 3px yellow;
|
||||
}
|
||||
|
||||
.notation-322f9 {
|
||||
cursor: default;
|
||||
font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
|
||||
font-size: 14px;
|
||||
position: absolute;
|
||||
}
|
||||
|
||||
.alpha-d2270 {
|
||||
bottom: 1px;
|
||||
right: 3px;
|
||||
}
|
||||
|
||||
.numeric-fc462 {
|
||||
top: 2px;
|
||||
left: 2px;
|
||||
}
|
2
examples/wchess/wchess.wasm/chessboardjs-1.0.0/css/chessboard-1.0.0.min.css
vendored
Normal file
@ -0,0 +1,2 @@
|
||||
/*! chessboard.js v1.0.0 | (c) 2019 Chris Oakman | MIT License chessboardjs.com/license */
|
||||
.clearfix-7da63{clear:both}.board-b72b1{border:2px solid #404040;box-sizing:content-box}.square-55d63{float:left;position:relative;-webkit-touch-callout:none;-webkit-user-select:none;-khtml-user-select:none;-moz-user-select:none;-ms-user-select:none;user-select:none}.white-1e1d7{background-color:#f0d9b5;color:#b58863}.black-3c85d{background-color:#b58863;color:#f0d9b5}.highlight1-32417,.highlight2-9c5d2{box-shadow:inset 0 0 3px 3px #ff0}.notation-322f9{cursor:default;font-family:"Helvetica Neue",Helvetica,Arial,sans-serif;font-size:14px;position:absolute}.alpha-d2270{bottom:1px;right:3px}.numeric-fc462{top:2px;left:2px}
|
After Width: | Height: | Size: 1.4 KiB |
After Width: | Height: | Size: 2.9 KiB |
After Width: | Height: | Size: 1.8 KiB |
After Width: | Height: | Size: 777 B |
After Width: | Height: | Size: 2.6 KiB |
After Width: | Height: | Size: 748 B |
After Width: | Height: | Size: 2.3 KiB |
After Width: | Height: | Size: 2.8 KiB |
After Width: | Height: | Size: 2.3 KiB |
After Width: | Height: | Size: 1.5 KiB |
After Width: | Height: | Size: 3.7 KiB |
After Width: | Height: | Size: 1.1 KiB |
2
examples/wchess/wchess.wasm/chessboardjs-1.0.0/js/chessboard-1.0.0.min.js
vendored
Normal file
@ -0,0 +1,32 @@
|
||||
# chessboard.js Change Log
|
||||
|
||||
All notable changes to this project will be documented in this file.
|
||||
|
||||
## [1.0.0] - 2019-06-11
|
||||
- Orientation methods now return current orientation. [Issue #64]
|
||||
- Drop support for IE8
|
||||
- Do not check for `window.JSON` (Error #1004)
|
||||
- Rename `ChessBoard` to `Chessboard` (`ChessBoard` is still supported, however)
|
||||
- id query selectors are now supported as the first argument to `Chessboard()`
|
||||
- Remove Error #1002
|
||||
- Format code according to [StandardJS]
|
||||
- Bump minimum jQuery version to 1.8.3
|
||||
- Throttle piece drag functions
|
||||
|
||||
## [0.3.0] - 2013-08-10
|
||||
- Added `appearSpeed` animation config property
|
||||
- Added `onSnapbackEnd` event
|
||||
- Added `onMoveEnd` event
|
||||
|
||||
## [0.2.0] - 2013-08-05
|
||||
- Added `onMouseoverSquare` and `onMouseoutSquare` events
|
||||
- Added `onSnapEnd` event
|
||||
- Added square code as CSS class on the squares
|
||||
- Added [chess.js] integration examples
|
||||
|
||||
## [0.1.0] - 2013-05-21
|
||||
- Initial release
|
||||
|
||||
[chess.js]:https://github.com/jhlywa/chess.js
|
||||
[Issue #64]:https://github.com/oakmac/chessboardjs/issues/64
|
||||
[StandardJS]:https://standardjs.com/
|
@ -0,0 +1,20 @@
|
||||
Copyright 2019 Chris Oakman
|
||||
|
||||
Permission is hereby granted, free of charge, to any person obtaining
|
||||
a copy of this software and associated documentation files (the
|
||||
"Software"), to deal in the Software without restriction, including
|
||||
without limitation the rights to use, copy, modify, merge, publish,
|
||||
distribute, sublicense, and/or sell copies of the Software, and to
|
||||
permit persons to whom the Software is furnished to do so, subject to
|
||||
the following conditions:
|
||||
|
||||
The above copyright notice and this permission notice shall be
|
||||
included in all copies or substantial portions of the Software.
|
||||
|
||||
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
|
||||
EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
|
||||
MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
|
||||
NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE
|
||||
LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION
|
||||
OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION
|
||||
WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
|
@ -0,0 +1,82 @@
|
||||
# chessboard.js
|
||||
|
||||
chessboard.js is a JavaScript chessboard component. It depends on [jQuery].
|
||||
|
||||
Please see [chessboardjs.com] for documentation and examples.
|
||||
|
||||
## What is chessboard.js?
|
||||
|
||||
chessboard.js is a JavaScript chessboard component with a flexible "just a
|
||||
board" API that
|
||||
|
||||
chessboard.js is a standalone JavaScript Chess Board. It is designed to be "just
|
||||
a board" and expose a powerful API so that it can be used in different ways.
|
||||
Here's a non-exhaustive list of things you can do with chessboard.js:
|
||||
|
||||
- Use chessboard.js to show game positions alongside your expert commentary.
|
||||
- Use chessboard.js to have a tactics website where users have to guess the best
|
||||
move.
|
||||
- Integrate chessboard.js and [chess.js] with a PGN database and allow people to
|
||||
search and playback games (see [Example 5000])
|
||||
- Build a chess server and have users play their games out using the
|
||||
chessboard.js board.
|
||||
|
||||
chessboard.js is flexible enough to handle any of these situations with relative
|
||||
ease.
|
||||
|
||||
## What can chessboard.js **not** do?
|
||||
|
||||
The scope of chessboard.js is limited to "just a board." This is intentional and
|
||||
makes chessboard.js flexible for handling a multitude of chess-related problems.
|
||||
|
||||
This is a common source of confusion for new users. [remove?]
|
||||
|
||||
Specifically, chessboard.js does not understand anything about how the game of
|
||||
chess is played: how a knight moves, who's turn is it, is White in check?, etc.
|
||||
|
||||
Fortunately, the powerful [chess.js] library deals with exactly this sort of
|
||||
problem domain and plays nicely with chessboard.js's flexible API. Some examples
|
||||
of chessboard.js combined with chess.js: 5000, 5001, 5002
|
||||
|
||||
Please see the powerful [chess.js] library for an API to deal with these sorts
|
||||
of questions.
|
||||
|
||||
|
||||
This logic is distinct from the logic of the board. Please see the powerful
|
||||
[chess.js] library for this aspect of your application.
|
||||
|
||||
|
||||
|
||||
Here is a list of things that chessboard.js is **not**:
|
||||
|
||||
- A chess engine
|
||||
- A legal move validator
|
||||
- A PGN parser
|
||||
|
||||
chessboard.js is designed to work well with any of those things, but the idea
|
||||
behind chessboard.js is that the logic that controls the board should be
|
||||
independent of those other problems.
|
||||
|
||||
## Docs and Examples
|
||||
|
||||
- Docs - <http://chessboardjs.com/docs>
|
||||
- Examples - <http://chessboardjs.com/examples>
|
||||
|
||||
## Developer Tools
|
||||
|
||||
```sh
|
||||
# create a build in the build/ directory
|
||||
npm run build
|
||||
|
||||
# re-build the website
|
||||
npm run website
|
||||
```
|
||||
|
||||
## License
|
||||
|
||||
[MIT License](LICENSE.md)
|
||||
|
||||
[jQuery]:https://jquery.com/
|
||||
[chessboardjs.com]:http://chessboardjs.com
|
||||
[chess.js]:https://github.com/jhlywa/chess.js
|
||||
[Example 5000]:http://chessboardjs.com/examples#5000
|
@ -0,0 +1,29 @@
|
||||
{
|
||||
"author": "Chris Oakman <chris@oakmac.com> (http://chrisoakman.com/)",
|
||||
"name": "@chrisoakman/chessboardjs",
|
||||
"description": "JavaScript chessboard widget",
|
||||
"homepage": "https://chessboardjs.com",
|
||||
"license": "MIT",
|
||||
"version": "1.0.0",
|
||||
"repository": {
|
||||
"type": "git",
|
||||
"url": "git://github.com/oakmac/chessboardjs.git"
|
||||
},
|
||||
"files": ["dist/"],
|
||||
"dependencies": {
|
||||
"jquery": ">=3.4.1"
|
||||
},
|
||||
"devDependencies": {
|
||||
"csso": "3.5.1",
|
||||
"fs-plus": "3.1.1",
|
||||
"kidif": "1.1.0",
|
||||
"mustache": "2.3.0",
|
||||
"standard": "10.0.2",
|
||||
"uglify-js": "3.6.0"
|
||||
},
|
||||
"scripts": {
|
||||
"build": "standard lib/chessboard.js && node scripts/build.js",
|
||||
"standard": "standard --fix lib/*.js website/js/*.js",
|
||||
"website": "node scripts/website.js"
|
||||
}
|
||||
}
|
499
examples/wchess/wchess.wasm/index-tmpl.html
Normal file
@ -0,0 +1,499 @@
|
||||
<!doctype html>
|
||||
<html lang="en-us">
|
||||
<head>
|
||||
<title>wchess : voice-controlled chess using Whisper + WebAssembly</title>
|
||||
<script src="https://cdnjs.cloudflare.com/ajax/libs/iframe-resizer/4.3.1/iframeResizer.contentWindow.min.js"></script>
|
||||
|
||||
<meta name="viewport" content="width=device-width, initial-scale=0.7, maximum-scale=1, minimum-scale=0.7, user-scalable=no"/>
|
||||
<meta name="apple-mobile-web-app-capable" content="yes" />
|
||||
|
||||
<style>
|
||||
#output {
|
||||
width: 100%;
|
||||
height: 100%;
|
||||
margin: 0 auto;
|
||||
margin-top: 10px;
|
||||
border-left: 0px;
|
||||
border-right: 0px;
|
||||
padding-left: 0px;
|
||||
padding-right: 0px;
|
||||
display: block;
|
||||
background-color: black;
|
||||
color: white;
|
||||
font-size: 10px;
|
||||
font-family: 'Lucida Console', Monaco, monospace;
|
||||
outline: none;
|
||||
white-space: pre;
|
||||
overflow-wrap: normal;
|
||||
overflow-x: scroll;
|
||||
}
|
||||
.button {
|
||||
background-color: #000000;
|
||||
color: #FFFFFF;
|
||||
padding: 20px;
|
||||
border-radius: 10px;
|
||||
-moz-border-radius: 10px;
|
||||
-webkit-border-radius: 10px;
|
||||
margin:10px;
|
||||
width: 100px;
|
||||
height: 50px;
|
||||
-webkit-touch-callout: none; /* Safari */
|
||||
-webkit-user-select: none; /* Chrome */
|
||||
-moz-user-select: none; /* Firefox */
|
||||
-ms-user-select: none; /* Internet Explorer/Edge */
|
||||
user-select: none;
|
||||
}
|
||||
button[disabled]{
|
||||
background-color: #cccccc;
|
||||
color: #666666;
|
||||
padding: 20px;
|
||||
border-radius: 10px;
|
||||
-moz-border-radius: 10px;
|
||||
-webkit-border-radius: 10px;
|
||||
margin:10px;
|
||||
width: 100px;
|
||||
}
|
||||
.center {
|
||||
display: flex;
|
||||
justify-content: center;
|
||||
align-items: center;
|
||||
width: 500px;
|
||||
}
|
||||
#description {
|
||||
width: 500px;
|
||||
}
|
||||
</style>
|
||||
<link rel="stylesheet" href="css/chessboard-1.0.0.min.css" integrity="sha384-q94+BZtLrkL1/ohfjR8c6L+A6qzNH9R2hBLwyoAfu3i/WCvQjzL2RQJ3uNHDISdU" crossorigin="anonymous">
|
||||
</head>
|
||||
<body>
|
||||
<div id="main-container">
|
||||
<div id="description">
|
||||
<b>wchess : voice-controlled chess using Whisper + WebAssembly</b>
|
||||
|
||||
<br><br>
|
||||
|
||||
This is a demonstration of using Whisper to recognize voice commands in the browser.
|
||||
|
||||
<br><br>
|
||||
|
||||
Usage:<br>
|
||||
|
||||
<ul>
|
||||
<li>Select a Whisper model</li>
|
||||
<li>Accept the microphone permission request if prompted</li>
|
||||
<li>Hold the button and say a chess move (e.g. "Knight to c3")</li>
|
||||
<li>Release the button and wait for the move to be recognized</li>
|
||||
<li>Repeat</li>
|
||||
</ul>
|
||||
|
||||
Examples:<br>
|
||||
|
||||
<ul>
|
||||
<li><b>"d4"</b></li>
|
||||
<li><b>"e2 e4"</b></li>
|
||||
<li><b>"Knight f3"</b></li>
|
||||
<li><b>"Bishop to b5"</b></li>
|
||||
</ul>
|
||||
|
||||
Features:<br>
|
||||
|
||||
<ul>
|
||||
<li>Model quantization for reduced memory footprint (~42MB)</li>
|
||||
<li><a href="https://github.com/ggerganov/whisper.cpp/pull/1229">Grammar-based sampling</a> for improved recognition accuracy</li>
|
||||
</ul>
|
||||
|
||||
<b>
|
||||
Note that not all chess moves are supported. For example, castling and pawn promotion
|
||||
currently do not work, but can be easily implemented. There could also be some bugs in
|
||||
the move handling logic in general. The main reason for that is to keep the implementation
|
||||
simple. The assumption is that a real application would already have a proper move
|
||||
validation logic in place.<br><br>
|
||||
|
||||
The main purpose of this example is to demonstrate the capabilities of whisper.cpp and
|
||||
its application in the browser for voice recognition locally on your device.
|
||||
</b>
|
||||
|
||||
<br><br>
|
||||
|
||||
You can find more about this project on <a href="https://github.com/ggerganov/whisper.cpp/tree/master/examples/wchess">GitHub</a>.
|
||||
|
||||
<br><br>
|
||||
|
||||
<b>More examples:</b>
|
||||
<a href="https://whisper.ggerganov.com/">main</a> |
|
||||
<a href="https://whisper.ggerganov.com/bench">bench</a> |
|
||||
<a href="https://whisper.ggerganov.com/stream">stream</a> |
|
||||
<a href="https://whisper.ggerganov.com/command">command</a> |
|
||||
<a href="https://whisper.ggerganov.com/talk">talk</a> |
|
||||
|
||||
<br><br>
|
||||
|
||||
</div>
|
||||
|
||||
<hr>
|
||||
|
||||
<div id="model-whisper">
|
||||
Whisper model: <span id="model-whisper-status"></span>
|
||||
<button id="fetch-whisper-tiny-en" onclick="loadWhisper()">tiny.en (Q8_0, 42 MB)</button>
|
||||
<span id="fetch-whisper-progress"></span>
|
||||
<br><br>
|
||||
<button id="clear" onclick="clearCache()">Clear browser cache</button>
|
||||
<!--
|
||||
<input type="file" id="file" name="file" onchange="loadFile(event, 'whisper.bin')" />
|
||||
-->
|
||||
</div>
|
||||
|
||||
<div id="game">
|
||||
<br>
|
||||
<div id="chessboard" style="width: 500px"></div>
|
||||
<script src="js/jquery-3.7.1.min.js"></script>
|
||||
<script src="js/chessboard-1.0.0.min.js"></script>
|
||||
<script>
|
||||
var board = Chessboard('chessboard', 'start')
|
||||
var move_count = 0;
|
||||
</script>
|
||||
|
||||
<br>
|
||||
|
||||
<div id="state">
|
||||
Status: <b><span id="state-status">select model</span></b>
|
||||
|
||||
<div id="input" class="center">
|
||||
<button id="toggler" class="button" onselectstart="return false" style="display: none">Hold</button>
|
||||
</div>
|
||||
|
||||
<pre id="state-grammar">[The grammar will be displayed here]</pre>
|
||||
|
||||
<pre id="state-moves">[The moves will be displayed here]</pre>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<hr>
|
||||
|
||||
Debug output:
|
||||
<textarea id="output" rows="20"></textarea>
|
||||
|
||||
<br>
|
||||
|
||||
<b>Troubleshooting</b>
|
||||
|
||||
<br><br>
|
||||
|
||||
The page does some heavy computations, so make sure:
|
||||
|
||||
<ul>
|
||||
<li>To use a modern web browser (e.g. Chrome, Firefox)</li>
|
||||
<li>Your browser supports WASM <a href="https://webassembly.org/roadmap/">Fixed-width SIMD</a></li>
|
||||
</ul>
|
||||
|
||||
<div class="cell-version">
|
||||
<span>
|
||||
|
|
||||
Build time: <span class="nav-link">@GIT_DATE@</span> |
|
||||
Commit hash: <a class="nav-link" href="https://github.com/ggerganov/whisper.cpp/commit/@GIT_SHA1@">@GIT_SHA1@</a> |
|
||||
Commit subject: <span class="nav-link">@GIT_COMMIT_SUBJECT@</span> |
|
||||
<a class="nav-link" href="https://github.com/ggerganov/whisper.cpp/tree/master/examples/command.wasm">Source Code</a> |
|
||||
</span>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<script type="text/javascript" src="js/helpers.js"></script>
|
||||
<script type='text/javascript'>
|
||||
// web audio context
|
||||
var context = null;
|
||||
|
||||
// the command instance
|
||||
var instance = null;
|
||||
|
||||
// model name
|
||||
var model_whisper = null;
|
||||
var model_file = null;
|
||||
|
||||
var module_ready = null;
|
||||
|
||||
var Module = {
|
||||
print: printTextarea,
|
||||
printErr: printTextarea,
|
||||
setStatus: function(text) {
|
||||
printTextarea('js: ' + text);
|
||||
},
|
||||
monitorRunDependencies: function(left) {
|
||||
},
|
||||
preRun: function() {
|
||||
printTextarea('js: Preparing ...');
|
||||
},
|
||||
postRun: function() {
|
||||
printTextarea('js: Module initialized successfully!');
|
||||
module_ready = true;
|
||||
initInstance();
|
||||
}
|
||||
};
|
||||
|
||||
function initInstance() {
|
||||
if (!module_ready || !model_file || instance) return
|
||||
|
||||
instance = Module.init(model_file);
|
||||
|
||||
if (instance) {
|
||||
setStatus('Ready');
|
||||
printTextarea("js: whisper initialized, instance: " + instance);
|
||||
}
|
||||
else {
|
||||
printTextarea("js: failed to initialize whisper");
|
||||
}
|
||||
}
|
||||
|
||||
function setStatus(text) {
|
||||
document.getElementById('state-status').innerHTML = text;
|
||||
}
|
||||
|
||||
//
|
||||
// fetch models
|
||||
//
|
||||
|
||||
let dbVersion = 1
|
||||
let dbName = 'whisper.ggerganov.com';
|
||||
let indexedDB = window.indexedDB || window.mozIndexedDB || window.webkitIndexedDB || window.msIndexedDB
|
||||
|
||||
function storeFS(fname, buf) {
|
||||
// write to WASM file using FS_createDataFile
|
||||
// if the file exists, delete it
|
||||
try {
|
||||
Module.FS_unlink(fname);
|
||||
} catch (e) {
|
||||
// ignore
|
||||
}
|
||||
|
||||
Module.FS_createDataFile("/", fname, buf, true, true);
|
||||
|
||||
printTextarea('storeFS: stored model: ' + fname + ' size: ' + buf.length);
|
||||
|
||||
document.getElementById('model-whisper-status').innerHTML = 'loaded "' + model_whisper + '"!';
|
||||
|
||||
model_file = fname;
|
||||
initInstance();
|
||||
}
|
||||
|
||||
function loadWhisper() {
|
||||
setStatus('Loading')
|
||||
//let url = 'https://whisper.ggerganov.com/ggml-model-whisper-tiny.en-q8_0.bin';
|
||||
let url = 'https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-tiny.en-q8_0.bin';
|
||||
let dst = 'whisper.bin';
|
||||
let size_mb = 42;
|
||||
|
||||
model_whisper = 'tiny.en-q8_0';
|
||||
|
||||
document.getElementById('model-whisper-status').innerHTML = 'loading "' + model_whisper + '" ... ';
|
||||
document.getElementById('fetch-whisper-tiny-en').style.display = 'none';
|
||||
|
||||
cbProgress = function(p) {
|
||||
let el = document.getElementById('fetch-whisper-progress');
|
||||
el.innerHTML = Math.round(100*p) + '%';
|
||||
};
|
||||
|
||||
cbCancel = function() {
|
||||
var el;
|
||||
el = document.getElementById('model-whisper-status'); if (el) el.innerHTML = '';
|
||||
};
|
||||
|
||||
loadRemote(url, dst, size_mb, cbProgress, storeFS, cbCancel, printTextarea);
|
||||
|
||||
// init audio capture so that the user receives a permission request
|
||||
{
|
||||
let context = new AudioContext({
|
||||
sampleRate: 16000,
|
||||
channelCount: 1,
|
||||
echoCancellation: false,
|
||||
autoGainControl: true,
|
||||
noiseSuppression: true,
|
||||
});
|
||||
navigator.mediaDevices.getUserMedia({audio: true, video: false})
|
||||
.then(function(s) {
|
||||
stream = s;
|
||||
stream.getTracks().forEach(function(track) {
|
||||
track.stop();
|
||||
});
|
||||
})
|
||||
.catch(function(err) {
|
||||
printTextarea('js: error getting audio stream: ' + err);
|
||||
});
|
||||
context.close();
|
||||
}
|
||||
|
||||
document.getElementById('toggler').style.display = 'block';
|
||||
}
|
||||
|
||||
//
|
||||
// microphone
|
||||
//
|
||||
|
||||
const kSampleRate = 16000;
|
||||
const kRestartRecording_s = 120;
|
||||
const kIntervalAudio_ms = 250; // pass the recorded audio to the C++ instance at this rate
|
||||
|
||||
var mediaRecorder = null;
|
||||
var doRecording = false;
|
||||
var startTime = 0;
|
||||
|
||||
window.AudioContext = window.AudioContext || window.webkitAudioContext;
|
||||
window.OfflineAudioContext = window.OfflineAudioContext || window.webkitOfflineAudioContext;
|
||||
|
||||
function stopRecording() {
|
||||
if (mediaRecorder) {
|
||||
mediaRecorder.stop();
|
||||
}
|
||||
}
|
||||
|
||||
function startRecording() {
|
||||
if (!context) {
|
||||
context = new AudioContext({
|
||||
sampleRate: kSampleRate,
|
||||
channelCount: 1,
|
||||
echoCancellation: false,
|
||||
autoGainControl: true,
|
||||
noiseSuppression: true,
|
||||
});
|
||||
}
|
||||
|
||||
startTime = Date.now();
|
||||
|
||||
var chunks = [];
|
||||
var stream = null;
|
||||
|
||||
navigator.mediaDevices.getUserMedia({audio: true, video: false})
|
||||
.then(function(s) {
|
||||
stream = s;
|
||||
mediaRecorder = new MediaRecorder(stream);
|
||||
mediaRecorder.ondataavailable = function(e) {
|
||||
chunks.push(e.data);
|
||||
|
||||
var blob = new Blob(chunks, { 'type' : 'audio/ogg; codecs=opus' });
|
||||
var reader = new FileReader();
|
||||
|
||||
reader.onload = function(event) {
|
||||
var buf = new Uint8Array(reader.result);
|
||||
context.decodeAudioData(buf.buffer, function(audioBuffer) {
|
||||
var offlineContext = new OfflineAudioContext(audioBuffer.numberOfChannels, audioBuffer.length, audioBuffer.sampleRate);
|
||||
var source = offlineContext.createBufferSource();
|
||||
source.buffer = audioBuffer;
|
||||
source.connect(offlineContext.destination);
|
||||
source.start(0);
|
||||
|
||||
offlineContext.startRendering().then(function(renderedBuffer) {
|
||||
let audio = renderedBuffer.getChannelData(0);
|
||||
printTextarea('js: number of samples: ' + audio.length);
|
||||
Module.set_audio(instance, audio);
|
||||
});
|
||||
|
||||
mediaRecorder = null;
|
||||
context = null;
|
||||
});
|
||||
}
|
||||
|
||||
reader.readAsArrayBuffer(blob);
|
||||
};
|
||||
|
||||
mediaRecorder.onstop = function(e) {
|
||||
stream.getTracks().forEach(function(track) {
|
||||
track.stop();
|
||||
});
|
||||
};
|
||||
|
||||
mediaRecorder.start();
|
||||
})
|
||||
.catch(function(err) {
|
||||
printTextarea('js: error getting audio stream: ' + err);
|
||||
});
|
||||
}
|
||||
|
||||
//
|
||||
// main
|
||||
//
|
||||
|
||||
var nLines = 0;
|
||||
var movesAll = '';
|
||||
|
||||
// document.body.addEventListener('keydown', function(event) {
|
||||
// if (event.keyCode === 32) {
|
||||
// document.getElementById('toggler').innerText = "";
|
||||
// onStart();
|
||||
// }
|
||||
// }, true);
|
||||
|
||||
// document.body.addEventListener('keyup', function(event) {
|
||||
// if (event.keyCode === 32) {
|
||||
// document.getElementById('toggler').innerText = "Hold";
|
||||
// onStop();
|
||||
// }
|
||||
// }, true);
|
||||
|
||||
document.getElementById('toggler').addEventListener("touchstart", function(event){
|
||||
this.innerText = "";
|
||||
onStart();
|
||||
}, true);
|
||||
|
||||
document.getElementById('toggler').addEventListener("touchend", function(event){
|
||||
this.innerText = "Hold";
|
||||
onStop();
|
||||
}, true)
|
||||
|
||||
document.getElementById('toggler').addEventListener('mousedown', function(event) {
|
||||
this.innerText = "";
|
||||
onStart();
|
||||
}, true);
|
||||
|
||||
document.getElementById('toggler').addEventListener('mouseup', function(event) {
|
||||
this.innerText = "Hold";
|
||||
onStop();
|
||||
}, true);
|
||||
|
||||
function onStart() {
|
||||
if (!instance) return;
|
||||
setStatus('Listening');
|
||||
|
||||
startRecording();
|
||||
}
|
||||
|
||||
function onStop() {
|
||||
setStatus('Processing');
|
||||
printTextarea('js: stopping recording ...');
|
||||
stopRecording();
|
||||
}
|
||||
|
||||
function setMove(move, prob) {
|
||||
if (move != null && move.length > 1) {
|
||||
let gameOver = move[move.length - 1] === '#';
|
||||
if (gameOver) {
|
||||
move = move.substring(0, move.length - 1);
|
||||
document.getElementById('toggler').disabled = true;
|
||||
}
|
||||
board.move(move);
|
||||
|
||||
movesAll += move + ', prob = ' + prob.toFixed(2) + '% <br>';
|
||||
nLines++;
|
||||
|
||||
// if more than 10 lines, remove the first line
|
||||
if (nLines > 10) {
|
||||
var i = movesAll.indexOf('<br>');
|
||||
if (i > 0) {
|
||||
movesAll = movesAll.substring(i + 4);
|
||||
nLines--;
|
||||
}
|
||||
}
|
||||
++move_count;
|
||||
setStatus(gameOver ? 'Done' : move_count % 2 ? 'Black\'s turn' : 'White\'s turn');
|
||||
document.getElementById('state-moves').innerHTML = movesAll;
|
||||
}
|
||||
else {
|
||||
setStatus('Failed. ' + (move_count % 2 ? 'Black\'s turn' : 'White\'s turn'));
|
||||
}
|
||||
}
|
||||
|
||||
function setGrammar(grammar) {
|
||||
document.getElementById('state-grammar').innerHTML = grammar;
|
||||
}
|
||||
|
||||
</script>
|
||||
<script type="text/javascript" src="js/chess.js"></script>
|
||||
</body>
|
||||
</html>
|
2
examples/wchess/wchess.wasm/jquery-3.7.1.min.js
vendored
Normal file
141
examples/wchess/wchess.wasm/wchess.wasm.cpp
Normal file
@ -0,0 +1,141 @@
|
||||
#include <WChess.h>
|
||||
#include <emscripten.h>
|
||||
#include <emscripten/bind.h>
|
||||
|
||||
#include <thread>
|
||||
|
||||
constexpr int N_THREAD = 8;
|
||||
|
||||
std::vector<struct whisper_context *> g_contexts(4, nullptr);
|
||||
|
||||
std::mutex g_mutex;
|
||||
std::thread g_worker;
|
||||
|
||||
std::condition_variable g_cv;
|
||||
|
||||
bool g_running(false);
|
||||
std::vector<float> g_pcmf32;
|
||||
|
||||
void set_move(const std::string & move, float prob) {
|
||||
MAIN_THREAD_EM_ASM({
|
||||
setMove(UTF8ToString($0), $1)
|
||||
}, move.c_str(), prob);
|
||||
}
|
||||
|
||||
void set_grammar(const std::string & grammar) {
|
||||
MAIN_THREAD_EM_ASM({
|
||||
setGrammar(UTF8ToString($0))
|
||||
}, grammar.c_str());
|
||||
}
|
||||
|
||||
bool get_audio(std::vector<float> & audio) {
|
||||
std::unique_lock<std::mutex> lock(g_mutex);
|
||||
g_cv.wait(lock, [] { return !g_running || !g_pcmf32.empty(); });
|
||||
if (!g_running) return false;
|
||||
audio = std::move(g_pcmf32);
|
||||
return true;
|
||||
}
|
||||
|
||||
void wchess_main(size_t i) {
|
||||
struct whisper_full_params wparams = whisper_full_default_params(whisper_sampling_strategy::WHISPER_SAMPLING_GREEDY);
|
||||
|
||||
wparams.n_threads = std::min(N_THREAD, (int) std::thread::hardware_concurrency());
|
||||
wparams.offset_ms = 0;
|
||||
wparams.translate = false;
|
||||
wparams.no_context = true;
|
||||
wparams.single_segment = true;
|
||||
wparams.print_realtime = false;
|
||||
wparams.print_progress = false;
|
||||
wparams.print_timestamps = true;
|
||||
wparams.print_special = false;
|
||||
wparams.no_timestamps = true;
|
||||
|
||||
wparams.max_tokens = 32;
|
||||
wparams.audio_ctx = 1280; // partial encoder context for better performance
|
||||
|
||||
wparams.temperature = 0.0f;
|
||||
wparams.temperature_inc = 2.0f;
|
||||
wparams.greedy.best_of = 1;
|
||||
|
||||
wparams.beam_search.beam_size = 1;
|
||||
|
||||
wparams.language = "en";
|
||||
|
||||
wparams.grammar_penalty = 100.0;
|
||||
wparams.initial_prompt = "bishop to c3, rook to d4, knight to e5, d4 d5, knight to c3, c3, queen to d4, king b1, pawn to a1, bishop to b2, knight to c3,";
|
||||
|
||||
printf("command: using %d threads\n", wparams.n_threads);
|
||||
|
||||
WChess::callbacks cb;
|
||||
cb.get_audio = get_audio;
|
||||
cb.set_move = set_move;
|
||||
cb.set_grammar = set_grammar;
|
||||
|
||||
WChess(g_contexts[i], wparams, cb, {}).run();
|
||||
|
||||
if (i < g_contexts.size()) {
|
||||
whisper_free(g_contexts[i]);
|
||||
g_contexts[i] = nullptr;
|
||||
}
|
||||
}
|
||||
|
||||
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());
|
||||
if (g_contexts[i] != nullptr) {
|
||||
g_running = true;
|
||||
if (g_worker.joinable()) {
|
||||
g_worker.join();
|
||||
}
|
||||
g_worker = std::thread([i]() {
|
||||
wchess_main(i);
|
||||
});
|
||||
|
||||
return i + 1;
|
||||
} else {
|
||||
return (size_t) 0;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
return (size_t) 0;
|
||||
}));
|
||||
|
||||
emscripten::function("free", emscripten::optional_override([](size_t /* index */) {
|
||||
{
|
||||
std::unique_lock<std::mutex> lock(g_mutex);
|
||||
g_running = false;
|
||||
}
|
||||
g_cv.notify_one();
|
||||
}));
|
||||
|
||||
emscripten::function("set_audio", emscripten::optional_override([](size_t index, const emscripten::val & audio) {
|
||||
--index;
|
||||
|
||||
if (index >= g_contexts.size()) {
|
||||
return -1;
|
||||
}
|
||||
|
||||
if (g_contexts[index] == nullptr) {
|
||||
return -2;
|
||||
}
|
||||
|
||||
{
|
||||
std::lock_guard<std::mutex> lock(g_mutex);
|
||||
const int n = audio["length"].as<int>();
|
||||
|
||||
emscripten::val heap = emscripten::val::module_property("HEAPU8");
|
||||
emscripten::val memory = heap["buffer"];
|
||||
|
||||
g_pcmf32.resize(n);
|
||||
|
||||
emscripten::val memoryView = audio["constructor"].new_(memory, reinterpret_cast<uintptr_t>(g_pcmf32.data()), n);
|
||||
memoryView.call<void>("set", audio);
|
||||
}
|
||||
g_cv.notify_one();
|
||||
|
||||
return 0;
|
||||
}));
|
||||
}
|
@ -206,6 +206,7 @@ void AudioInputCallback(void * inUserData,
|
||||
params.offset_ms = 0;
|
||||
params.no_context = true;
|
||||
params.single_segment = self->stateInp.isRealtime;
|
||||
params.no_timestamps = params.single_segment;
|
||||
|
||||
CFTimeInterval startTime = CACurrentMediaTime();
|
||||
|
||||
|
2
examples/whisper.swiftui/.gitignore
vendored
Normal file
@ -0,0 +1,2 @@
|
||||
xcuserdata
|
||||
xcshareddata
|
@ -8,15 +8,15 @@ enum WhisperError: Error {
|
||||
// Meet Whisper C++ constraint: Don't access from more than one thread at a time.
|
||||
actor WhisperContext {
|
||||
private var context: OpaquePointer
|
||||
|
||||
|
||||
init(context: OpaquePointer) {
|
||||
self.context = context
|
||||
}
|
||||
|
||||
|
||||
deinit {
|
||||
whisper_free(context)
|
||||
}
|
||||
|
||||
|
||||
func fullTranscribe(samples: [Float]) {
|
||||
// Leave 2 processors free (i.e. the high-efficiency cores).
|
||||
let maxThreads = max(1, min(8, cpuCount() - 2))
|
||||
@ -24,17 +24,17 @@ actor WhisperContext {
|
||||
var params = whisper_full_default_params(WHISPER_SAMPLING_GREEDY)
|
||||
"en".withCString { en in
|
||||
// Adapted from whisper.objc
|
||||
params.print_realtime = true
|
||||
params.print_progress = false
|
||||
params.print_realtime = true
|
||||
params.print_progress = false
|
||||
params.print_timestamps = true
|
||||
params.print_special = false
|
||||
params.translate = false
|
||||
params.language = en
|
||||
params.n_threads = Int32(maxThreads)
|
||||
params.offset_ms = 0
|
||||
params.no_context = true
|
||||
params.single_segment = false
|
||||
|
||||
params.print_special = false
|
||||
params.translate = false
|
||||
params.language = en
|
||||
params.n_threads = Int32(maxThreads)
|
||||
params.offset_ms = 0
|
||||
params.no_context = true
|
||||
params.single_segment = false
|
||||
|
||||
whisper_reset_timings(context)
|
||||
print("About to run whisper_full")
|
||||
samples.withUnsafeBufferPointer { samples in
|
||||
@ -46,7 +46,7 @@ actor WhisperContext {
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
func getTranscription() -> String {
|
||||
var transcription = ""
|
||||
for i in 0..<whisper_full_n_segments(context) {
|
||||
@ -54,7 +54,7 @@ actor WhisperContext {
|
||||
}
|
||||
return transcription
|
||||
}
|
||||
|
||||
|
||||
static func createContext(path: String) throws -> WhisperContext {
|
||||
var params = whisper_context_default_params()
|
||||
#if targetEnvironment(simulator)
|
||||
|
@ -61,7 +61,9 @@ models = [
|
||||
"ggml-small.bin",
|
||||
"ggml-medium.en.bin",
|
||||
"ggml-medium.bin",
|
||||
"ggml-large.bin",
|
||||
"ggml-large-v1.bin",
|
||||
"ggml-large-v2.bin",
|
||||
"ggml-large-v3.bin",
|
||||
]
|
||||
|
||||
|
||||
|
154
extra/sync-ggml-am.sh
Executable file
@ -0,0 +1,154 @@
|
||||
#!/bin/bash
|
||||
#
|
||||
# Synchronize ggml changes to whisper.cpp
|
||||
#
|
||||
# Usage:
|
||||
#
|
||||
# $ cd /path/to/whisper.cpp
|
||||
# $ ./extra/sync-ggml-am.sh
|
||||
#
|
||||
|
||||
set -e
|
||||
|
||||
sd=$(dirname $0)
|
||||
cd $sd/../
|
||||
|
||||
SRC_WHISPER=$(pwd)
|
||||
SRC_GGML=$(cd ../ggml; pwd)
|
||||
|
||||
if [ ! -d $SRC_GGML ]; then
|
||||
echo "ggml not found at $SRC_GGML"
|
||||
exit 1
|
||||
fi
|
||||
|
||||
lc=$(cat $SRC_WHISPER/extra/sync-ggml.last)
|
||||
echo "Syncing ggml changes since commit $lc"
|
||||
|
||||
cd $SRC_GGML
|
||||
|
||||
git log --oneline $lc..HEAD
|
||||
git log --oneline $lc..HEAD --reverse | grep -v "(whisper/[0-9]*)" | cut -d' ' -f1 > $SRC_WHISPER/ggml-commits
|
||||
|
||||
if [ ! -s $SRC_WHISPER/ggml-commits ]; then
|
||||
rm -v $SRC_WHISPER/ggml-commits
|
||||
echo "No new commits"
|
||||
exit 0
|
||||
fi
|
||||
|
||||
if [ -f $SRC_WHISPER/ggml-src.patch ]; then
|
||||
rm -v $SRC_WHISPER/ggml-src.patch
|
||||
fi
|
||||
|
||||
while read c; do
|
||||
git format-patch -k $c~1..$c --stdout -- \
|
||||
include/ggml/ggml*.h \
|
||||
src/ggml*.h \
|
||||
src/ggml*.c \
|
||||
src/ggml*.cpp \
|
||||
src/ggml*.m \
|
||||
src/ggml*.metal \
|
||||
src/ggml*.cu \
|
||||
examples/common.h \
|
||||
examples/common.cpp \
|
||||
examples/common-ggml.h \
|
||||
examples/common-ggml.cpp \
|
||||
examples/whisper/whisper.h \
|
||||
examples/whisper/whisper.cpp \
|
||||
examples/whisper/main.cpp \
|
||||
examples/whisper/quantize.cpp \
|
||||
>> $SRC_WHISPER/ggml-src.patch
|
||||
done < $SRC_WHISPER/ggml-commits
|
||||
|
||||
rm -v $SRC_WHISPER/ggml-commits
|
||||
|
||||
# delete files if empty
|
||||
if [ ! -s $SRC_WHISPER/ggml-src.patch ]; then
|
||||
rm -v $SRC_WHISPER/ggml-src.patch
|
||||
fi
|
||||
|
||||
cd $SRC_WHISPER
|
||||
|
||||
if [ -f $SRC_WHISPER/ggml-src.patch ]; then
|
||||
# replace PR numbers
|
||||
#
|
||||
# Subject: some text (#1234)
|
||||
# Subject: some text (ggml/1234)
|
||||
cat ggml-src.patch | sed -e 's/^Subject: \(.*\) (#\([0-9]*\))/Subject: \1 (ggml\/\2)/' > ggml-src.patch.tmp
|
||||
mv ggml-src.patch.tmp ggml-src.patch
|
||||
|
||||
cat ggml-src.patch | sed -e 's/^\(.*\) (#\([0-9]*\))$/\1 (ggml\/\2)/' > ggml-src.patch.tmp
|
||||
mv ggml-src.patch.tmp ggml-src.patch
|
||||
|
||||
# replace filenames:
|
||||
#
|
||||
# src/ggml.c -> ggml.c
|
||||
# src/ggml-alloc.c -> ggml-alloc.c
|
||||
# src/ggml-backend-impl.h -> ggml-backend-impl.h
|
||||
# src/ggml-backend.c -> ggml-backend.c
|
||||
# src/ggml-cuda.cu -> ggml-cuda.cu
|
||||
# src/ggml-cuda.h -> ggml-cuda.h
|
||||
# src/ggml-impl.h -> ggml-impl.h
|
||||
# src/ggml-metal.h -> ggml-metal.h
|
||||
# src/ggml-metal.m -> ggml-metal.m
|
||||
# src/ggml-mpi.h -> ggml-mpi.h
|
||||
# src/ggml-mpi.c -> ggml-mpi.c
|
||||
# src/ggml-opencl.cpp -> ggml-opencl.cpp
|
||||
# src/ggml-opencl.h -> ggml-opencl.h
|
||||
# src/ggml-quants.c -> ggml-quants.c
|
||||
# src/ggml-quants.h -> ggml-quants.h
|
||||
# include/ggml/ggml.h -> ggml.h
|
||||
# include/ggml/ggml-alloc.h -> ggml-alloc.h
|
||||
# include/ggml/ggml-backend.h -> ggml-backend.h
|
||||
#
|
||||
# examples/common.h -> examples/common.h
|
||||
# examples/common.cpp -> examples/common.cpp
|
||||
# examples/common-ggml.h -> examples/common-ggml.h
|
||||
# examples/common-ggml.cpp -> examples/common-ggml.cpp
|
||||
#
|
||||
# examples/whisper/whisper.h -> whisper.h
|
||||
# examples/whisper/whisper.cpp -> whisper.cpp
|
||||
# examples/whisper/main.cpp -> examples/main/main.cpp
|
||||
# examples/whisper/quantize.cpp -> examples/quantize/quantize.cpp
|
||||
|
||||
cat ggml-src.patch | sed \
|
||||
-e 's/src\/ggml\.c/ggml.c/g' \
|
||||
-e 's/src\/ggml-alloc\.c/ggml-alloc.c/g' \
|
||||
-e 's/src\/ggml-backend-impl\.h/ggml-backend-impl.h/g' \
|
||||
-e 's/src\/ggml-backend\.c/ggml-backend.c/g' \
|
||||
-e 's/src\/ggml-cuda\.cu/ggml-cuda.cu/g' \
|
||||
-e 's/src\/ggml-cuda\.h/ggml-cuda.h/g' \
|
||||
-e 's/src\/ggml-impl\.h/ggml-impl.h/g' \
|
||||
-e 's/src\/ggml-metal\.h/ggml-metal.h/g' \
|
||||
-e 's/src\/ggml-metal\.m/ggml-metal.m/g' \
|
||||
-e 's/src\/ggml-mpi\.h/ggml-mpi.h/g' \
|
||||
-e 's/src\/ggml-mpi\.c/ggml-mpi.c/g' \
|
||||
-e 's/src\/ggml-opencl\.cpp/ggml-opencl.cpp/g' \
|
||||
-e 's/src\/ggml-opencl\.h/ggml-opencl.h/g' \
|
||||
-e 's/src\/ggml-quants\.c/ggml-quants.c/g' \
|
||||
-e 's/src\/ggml-quants\.h/ggml-quants.h/g' \
|
||||
-e 's/include\/ggml\/ggml\.h/ggml.h/g' \
|
||||
-e 's/include\/ggml\/ggml-alloc\.h/ggml-alloc.h/g' \
|
||||
-e 's/include\/ggml\/ggml-backend\.h/ggml-backend.h/g' \
|
||||
-e 's/examples\/common\.h/examples\/common.h/g' \
|
||||
-e 's/examples\/common\.cpp/examples\/common.cpp/g' \
|
||||
-e 's/examples\/common-ggml\.h/examples\/common-ggml.h/g' \
|
||||
-e 's/examples\/common-ggml\.cpp/examples\/common-ggml.cpp/g' \
|
||||
-e 's/examples\/whisper\/whisper\.h/whisper.h/g' \
|
||||
-e 's/examples\/whisper\/whisper\.cpp/whisper.cpp/g' \
|
||||
-e 's/examples\/whisper\/main\.cpp/examples\/main\/main.cpp/g' \
|
||||
-e 's/examples\/whisper\/quantize\.cpp/examples\/quantize\/quantize.cpp/g' \
|
||||
> ggml-src.patch.tmp
|
||||
mv ggml-src.patch.tmp ggml-src.patch
|
||||
|
||||
git am ggml-src.patch
|
||||
|
||||
rm -v $SRC_WHISPER/ggml-src.patch
|
||||
fi
|
||||
|
||||
# update last commit
|
||||
cd $SRC_GGML
|
||||
git log -1 --format=%H > $SRC_WHISPER/extra/sync-ggml.last
|
||||
|
||||
echo "Done"
|
||||
|
||||
exit 0
|
1
extra/sync-ggml.last
Normal file
@ -0,0 +1 @@
|
||||
3eace58911ea8d2cf35defdc59848d99b91a57f5
|
5
extra/sync-llama.sh
Executable file
@ -0,0 +1,5 @@
|
||||
#!/bin/bash
|
||||
|
||||
cp -rpv ../llama.cpp/llama.h ./examples/talk-llama/llama.h
|
||||
cp -rpv ../llama.cpp/llama.cpp ./examples/talk-llama/llama.cpp
|
||||
cp -rpv ../llama.cpp/unicode.h ./examples/talk-llama/unicode.h
|
67
ggml-alloc.c
@ -72,7 +72,7 @@ static void remove_allocated_tensor(ggml_tallocr_t alloc, struct ggml_tensor * t
|
||||
|
||||
// check if a tensor is allocated by this buffer
|
||||
static bool ggml_tallocr_is_own(ggml_tallocr_t alloc, const struct ggml_tensor * tensor) {
|
||||
return tensor->buffer == alloc->buffer;
|
||||
return tensor->buffer == alloc->buffer && (!tensor->view_src || tensor->view_src->buffer == alloc->buffer);
|
||||
}
|
||||
|
||||
static bool ggml_is_view(struct ggml_tensor * t) {
|
||||
@ -137,7 +137,7 @@ void ggml_tallocr_alloc(ggml_tallocr_t alloc, struct ggml_tensor * tensor) {
|
||||
|
||||
#ifdef GGML_ALLOCATOR_DEBUG
|
||||
add_allocated_tensor(alloc, tensor);
|
||||
size_t cur_max = (char*)addr - (char*)alloc->data + size;
|
||||
size_t cur_max = (char*)addr - (char*)alloc->base + size;
|
||||
if (cur_max > alloc->max_size) {
|
||||
printf("max_size = %.2f MB: tensors: ", cur_max / 1024.0 / 1024.0);
|
||||
for (int i = 0; i < 1024; i++) {
|
||||
@ -168,10 +168,6 @@ static void ggml_tallocr_free_tensor(ggml_tallocr_t alloc, struct ggml_tensor *
|
||||
size = aligned_offset(NULL, size, alloc->alignment);
|
||||
AT_PRINTF("%s: freeing %s at %p (%zu bytes) - n_free_blocks = %d\n", __func__, tensor->name, ptr, size, alloc->n_free_blocks);
|
||||
|
||||
if (!alloc->measure) {
|
||||
ggml_backend_buffer_free_tensor(alloc->buffer, tensor);
|
||||
}
|
||||
|
||||
#ifdef GGML_ALLOCATOR_DEBUG
|
||||
remove_allocated_tensor(alloc, tensor);
|
||||
#endif
|
||||
@ -237,7 +233,7 @@ void ggml_tallocr_reset(ggml_tallocr_t alloc) {
|
||||
}
|
||||
|
||||
ggml_tallocr_t ggml_tallocr_new(void * data, size_t size, size_t alignment) {
|
||||
struct ggml_backend_buffer * buffer = ggml_backend_cpu_buffer_from_ptr(NULL, data, size);
|
||||
struct ggml_backend_buffer * buffer = ggml_backend_cpu_buffer_from_ptr(data, size);
|
||||
|
||||
ggml_tallocr_t alloc = (ggml_tallocr_t)malloc(sizeof(struct ggml_tallocr));
|
||||
|
||||
@ -449,17 +445,15 @@ static ggml_tallocr_t node_tallocr(ggml_gallocr_t galloc, struct ggml_tensor * n
|
||||
static void init_view(ggml_gallocr_t galloc, struct ggml_tensor * view, bool update_backend) {
|
||||
ggml_tallocr_t alloc = node_tallocr(galloc, view);
|
||||
|
||||
//printf("init_view: %s from src %s\n", view->name, view->view_src->name);
|
||||
GGML_ASSERT(view->view_src != NULL && view->view_src->data != NULL);
|
||||
if (update_backend) {
|
||||
view->backend = view->view_src->backend;
|
||||
}
|
||||
view->buffer = view->view_src->buffer;
|
||||
// views are initialized in the alloc buffer rather than the view_src buffer
|
||||
view->buffer = alloc->buffer;
|
||||
view->data = (char *)view->view_src->data + view->view_offs;
|
||||
|
||||
// FIXME: the view should be initialized by the owning buffer, but currently this breaks the CUDA backend
|
||||
// due to the ggml_tensor_extra_gpu ring buffer overwriting the KV cache extras
|
||||
assert(ggml_tallocr_is_measure(alloc) || !view->buffer || view->buffer->backend == alloc->buffer->backend);
|
||||
assert(ggml_tallocr_is_measure(alloc) || !view->buffer || view->buffer->buft == alloc->buffer->buft);
|
||||
|
||||
if (!alloc->measure) {
|
||||
ggml_backend_buffer_init_tensor(alloc->buffer, view);
|
||||
@ -741,6 +735,10 @@ void ggml_allocr_set_parse_seq(ggml_allocr_t alloc, const int * list, int n) {
|
||||
}
|
||||
|
||||
void ggml_allocr_free(ggml_allocr_t alloc) {
|
||||
if (alloc == NULL) {
|
||||
return;
|
||||
}
|
||||
|
||||
ggml_gallocr_free(alloc->galloc);
|
||||
ggml_tallocr_free(alloc->talloc);
|
||||
free(alloc);
|
||||
@ -765,3 +763,48 @@ size_t ggml_allocr_max_size(ggml_allocr_t alloc) {
|
||||
size_t ggml_allocr_alloc_graph(ggml_allocr_t alloc, struct ggml_cgraph * graph) {
|
||||
return ggml_gallocr_alloc_graph(alloc->galloc, alloc->talloc, graph);
|
||||
}
|
||||
|
||||
// utils
|
||||
ggml_backend_buffer_t ggml_backend_alloc_ctx_tensors_from_buft(struct ggml_context * ctx, ggml_backend_buffer_type_t buft) {
|
||||
GGML_ASSERT(ggml_get_no_alloc(ctx) == true);
|
||||
|
||||
size_t alignment = ggml_backend_buft_get_alignment(buft);
|
||||
|
||||
size_t nbytes = 0;
|
||||
for (struct ggml_tensor * t = ggml_get_first_tensor(ctx); t != NULL; t = ggml_get_next_tensor(ctx, t)) {
|
||||
if (t->data == NULL && t->view_src == NULL) {
|
||||
nbytes += GGML_PAD(ggml_backend_buft_get_alloc_size(buft, t), alignment);
|
||||
}
|
||||
}
|
||||
|
||||
if (nbytes == 0) {
|
||||
// all the tensors in the context are already allocated
|
||||
return NULL;
|
||||
}
|
||||
|
||||
ggml_backend_buffer_t buffer = ggml_backend_buft_alloc_buffer(buft, nbytes);
|
||||
ggml_tallocr_t tallocr = ggml_tallocr_new_from_buffer(buffer);
|
||||
|
||||
for (struct ggml_tensor * t = ggml_get_first_tensor(ctx); t != NULL; t = ggml_get_next_tensor(ctx, t)) {
|
||||
if (t->data == NULL) {
|
||||
if (t->view_src == NULL) {
|
||||
ggml_tallocr_alloc(tallocr, t);
|
||||
} else {
|
||||
ggml_backend_view_init(buffer, t);
|
||||
}
|
||||
} else {
|
||||
if (t->view_src != NULL) {
|
||||
// view of a pre-allocated tensor
|
||||
ggml_backend_view_init(buffer, t);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
ggml_tallocr_free(tallocr);
|
||||
|
||||
return buffer;
|
||||
}
|
||||
|
||||
ggml_backend_buffer_t ggml_backend_alloc_ctx_tensors(struct ggml_context * ctx, ggml_backend_t backend) {
|
||||
return ggml_backend_alloc_ctx_tensors_from_buft(ctx, ggml_backend_get_default_buffer_type(backend));
|
||||
}
|
||||
|
@ -8,6 +8,7 @@ extern "C" {
|
||||
|
||||
struct ggml_backend;
|
||||
struct ggml_backend_buffer;
|
||||
struct ggml_backend_buffer_type;
|
||||
|
||||
//
|
||||
// Legacy API
|
||||
@ -42,7 +43,7 @@ GGML_API size_t ggml_allocr_alloc_graph(ggml_allocr_t alloc, struct ggml_cgraph
|
||||
// ggml-backend v2 API
|
||||
//
|
||||
|
||||
// Seperate tensor and graph allocator objects
|
||||
// Separate tensor and graph allocator objects
|
||||
// This is necessary for multi-backend allocation because the graph allocator needs to use multiple tensor allocators
|
||||
// The original API is kept as a wrapper around the new API
|
||||
|
||||
@ -80,6 +81,12 @@ GGML_API void ggml_gallocr_alloc_graph_n(
|
||||
struct ggml_hash_set hash_set,
|
||||
ggml_tallocr_t * hash_node_talloc);
|
||||
|
||||
|
||||
// Utils
|
||||
// Create a buffer and allocate all the tensors in a ggml_context
|
||||
GGML_API struct ggml_backend_buffer * ggml_backend_alloc_ctx_tensors_from_buft(struct ggml_context * ctx, struct ggml_backend_buffer_type * buft);
|
||||
GGML_API struct ggml_backend_buffer * ggml_backend_alloc_ctx_tensors(struct ggml_context * ctx, struct ggml_backend * backend);
|
||||
|
||||
#ifdef __cplusplus
|
||||
}
|
||||
#endif
|
||||
|
@ -12,31 +12,54 @@ extern "C" {
|
||||
// Backend buffer
|
||||
//
|
||||
|
||||
// buffer type
|
||||
typedef void * ggml_backend_buffer_type_context_t;
|
||||
|
||||
struct ggml_backend_buffer_type_i {
|
||||
ggml_backend_buffer_t (*alloc_buffer) (ggml_backend_buffer_type_t buft, size_t size);
|
||||
size_t (*get_alignment) (ggml_backend_buffer_type_t buft); // tensor alignment
|
||||
size_t (*get_alloc_size) (ggml_backend_buffer_type_t buft, struct ggml_tensor * tensor); // data size needed to allocate the tensor, including padding
|
||||
bool (*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 (*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 {
|
||||
void (*free_buffer) (ggml_backend_buffer_t buffer);
|
||||
void * (*get_base) (ggml_backend_buffer_t buffer); // get base pointer
|
||||
size_t (*get_alloc_size)(ggml_backend_buffer_t buffer, struct ggml_tensor * tensor); // pre-allocation callback
|
||||
void (*init_tensor) (ggml_backend_buffer_t buffer, struct ggml_tensor * tensor); // post-allocation callback
|
||||
void (*free_tensor) (ggml_backend_buffer_t buffer, struct ggml_tensor * tensor); // pre-free callback
|
||||
void (*free_buffer) (ggml_backend_buffer_t buffer);
|
||||
//void (*reset) (ggml_backend_buffer_t buffer); // reset any internal state due to tensor initialization, such as tensor extras
|
||||
void * (*get_base) (ggml_backend_buffer_t buffer);
|
||||
void (*init_tensor) (ggml_backend_buffer_t buffer, struct ggml_tensor * tensor);
|
||||
void (*set_tensor) (ggml_backend_buffer_t buffer, struct ggml_tensor * tensor, const void * data, size_t offset, size_t size);
|
||||
void (*get_tensor) (ggml_backend_buffer_t buffer, const struct ggml_tensor * tensor, void * data, size_t offset, size_t size);
|
||||
// (optional) copy tensor between different buffer-type, allow for single-copy tranfers
|
||||
void (*cpy_tensor_from)(ggml_backend_buffer_t buffer, struct ggml_tensor * src, struct ggml_tensor * dst);
|
||||
void (*cpy_tensor_to) (ggml_backend_buffer_t buffer, struct ggml_tensor * src, struct ggml_tensor * dst);
|
||||
void (*clear) (ggml_backend_buffer_t buffer, uint8_t value);
|
||||
};
|
||||
|
||||
struct ggml_backend_buffer {
|
||||
struct ggml_backend_buffer_i iface;
|
||||
|
||||
ggml_backend_t backend;
|
||||
struct ggml_backend_buffer_i iface;
|
||||
ggml_backend_buffer_type_t buft;
|
||||
ggml_backend_buffer_context_t context;
|
||||
|
||||
size_t size;
|
||||
};
|
||||
|
||||
GGML_API ggml_backend_buffer_t ggml_backend_buffer_init(
|
||||
struct ggml_backend * backend,
|
||||
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);
|
||||
|
||||
|
||||
//
|
||||
// Backend
|
||||
//
|
||||
@ -49,20 +72,17 @@ extern "C" {
|
||||
void (*free)(ggml_backend_t backend);
|
||||
|
||||
// buffer allocation
|
||||
ggml_backend_buffer_t (*alloc_buffer)(ggml_backend_t backend, size_t size);
|
||||
ggml_backend_buffer_type_t (*get_default_buffer_type)(ggml_backend_t backend);
|
||||
|
||||
// get buffer alignment
|
||||
size_t (*get_alignment)(ggml_backend_t backend);
|
||||
|
||||
// tensor data access
|
||||
// these functions can be asynchronous, helper functions are provided for synchronous access that automatically call synchronize
|
||||
// (optional) asynchroneous tensor data access
|
||||
void (*set_tensor_async)(ggml_backend_t backend, struct ggml_tensor * tensor, const void * data, size_t offset, size_t size);
|
||||
void (*get_tensor_async)(ggml_backend_t backend, const struct ggml_tensor * tensor, void * data, size_t offset, size_t size);
|
||||
void (*synchronize) (ggml_backend_t backend);
|
||||
|
||||
// (optional) copy tensor between different backends, allow for single-copy tranfers
|
||||
void (*cpy_tensor_from)(ggml_backend_t backend, struct ggml_tensor * src, struct ggml_tensor * dst);
|
||||
void (*cpy_tensor_to) (ggml_backend_t backend, struct ggml_tensor * src, struct ggml_tensor * dst);
|
||||
// (optional) asynchroneous tensor copy
|
||||
void (*cpy_tensor_from_async)(ggml_backend_t backend, struct ggml_tensor * src, struct ggml_tensor * dst);
|
||||
void (*cpy_tensor_to_async) (ggml_backend_t backend, struct ggml_tensor * src, struct ggml_tensor * dst);
|
||||
|
||||
void (*synchronize)(ggml_backend_t backend);
|
||||
|
||||
// compute graph with a plan
|
||||
ggml_backend_graph_plan_t (*graph_plan_create) (ggml_backend_t backend, struct ggml_cgraph * cgraph);
|
||||
@ -70,7 +90,7 @@ extern "C" {
|
||||
void (*graph_plan_compute)(ggml_backend_t backend, ggml_backend_graph_plan_t plan);
|
||||
|
||||
// compute graph without a plan
|
||||
void (*graph_compute)(ggml_backend_t backend, struct ggml_cgraph * cgraph);
|
||||
bool (*graph_compute)(ggml_backend_t backend, struct ggml_cgraph * cgraph);
|
||||
|
||||
// check if the backend supports an operation
|
||||
bool (*supports_op)(ggml_backend_t backend, const struct ggml_tensor * op);
|
||||
@ -82,6 +102,15 @@ extern "C" {
|
||||
ggml_backend_context_t context;
|
||||
};
|
||||
|
||||
|
||||
//
|
||||
// Backend registry
|
||||
//
|
||||
|
||||
typedef ggml_backend_t (*ggml_backend_init_fn)(const char * params, void * user_data);
|
||||
|
||||
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
|
||||
|
855
ggml-backend.c
@ -7,41 +7,47 @@
|
||||
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 * ggml_backend_t;
|
||||
typedef void * ggml_backend_graph_plan_t;
|
||||
|
||||
//
|
||||
// Backend buffer
|
||||
//
|
||||
|
||||
struct ggml_backend_buffer;
|
||||
typedef struct ggml_backend_buffer * ggml_backend_buffer_t;
|
||||
// buffer type
|
||||
GGML_API 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_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);
|
||||
|
||||
// backend buffer functions
|
||||
// buffer
|
||||
GGML_API void ggml_backend_buffer_free (ggml_backend_buffer_t buffer);
|
||||
GGML_API size_t ggml_backend_buffer_get_alignment (ggml_backend_buffer_t buffer);
|
||||
GGML_API void * ggml_backend_buffer_get_base (ggml_backend_buffer_t buffer);
|
||||
GGML_API size_t ggml_backend_buffer_get_size (ggml_backend_buffer_t buffer);
|
||||
GGML_API size_t ggml_backend_buffer_get_alloc_size(ggml_backend_buffer_t buffer, struct ggml_tensor * tensor);
|
||||
GGML_API void ggml_backend_buffer_init_tensor (ggml_backend_buffer_t buffer, struct ggml_tensor * tensor);
|
||||
GGML_API void ggml_backend_buffer_free_tensor (ggml_backend_buffer_t buffer, struct ggml_tensor * tensor);
|
||||
GGML_API size_t ggml_backend_buffer_get_alignment (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 ggml_backend_buffer_type_t ggml_backend_buffer_type(ggml_backend_buffer_t buffer);
|
||||
|
||||
//
|
||||
// Backend
|
||||
//
|
||||
|
||||
struct ggml_backend;
|
||||
typedef struct ggml_backend * ggml_backend_t;
|
||||
typedef void * ggml_backend_graph_plan_t;
|
||||
|
||||
GGML_API ggml_backend_t ggml_get_backend(const struct ggml_tensor * tensor);
|
||||
|
||||
GGML_API const char * ggml_backend_name(ggml_backend_t backend);
|
||||
GGML_API void ggml_backend_free(ggml_backend_t backend);
|
||||
|
||||
GGML_API ggml_backend_buffer_t ggml_backend_alloc_buffer(ggml_backend_t backend, size_t size);
|
||||
GGML_API 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_alignment(ggml_backend_t backend);
|
||||
|
||||
GGML_API void ggml_backend_tensor_set_async( struct ggml_tensor * tensor, const void * data, size_t offset, size_t size);
|
||||
GGML_API void ggml_backend_tensor_get_async(const struct ggml_tensor * tensor, void * data, size_t offset, size_t size);
|
||||
GGML_API void ggml_backend_tensor_set_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 void ggml_backend_tensor_set( struct ggml_tensor * tensor, const void * data, size_t offset, size_t size);
|
||||
GGML_API void ggml_backend_tensor_get(const struct ggml_tensor * tensor, void * data, size_t offset, size_t size);
|
||||
@ -52,11 +58,12 @@ extern "C" {
|
||||
|
||||
GGML_API void ggml_backend_graph_plan_free (ggml_backend_t backend, ggml_backend_graph_plan_t plan);
|
||||
GGML_API void ggml_backend_graph_plan_compute(ggml_backend_t backend, ggml_backend_graph_plan_t plan);
|
||||
GGML_API void ggml_backend_graph_compute (ggml_backend_t backend, struct ggml_cgraph * cgraph);
|
||||
GGML_API bool ggml_backend_graph_compute (ggml_backend_t backend, struct ggml_cgraph * cgraph);
|
||||
GGML_API bool ggml_backend_supports_op (ggml_backend_t backend, const struct ggml_tensor * op);
|
||||
|
||||
// tensor copy between different backends
|
||||
GGML_API void ggml_backend_tensor_copy(struct ggml_tensor * src, struct ggml_tensor * dst);
|
||||
GGML_API void ggml_backend_tensor_copy_async(ggml_backend_t backend, struct ggml_tensor * src, struct ggml_tensor * dst); // automatic fallback to sync copy
|
||||
|
||||
//
|
||||
// CPU backend
|
||||
@ -68,8 +75,27 @@ extern "C" {
|
||||
GGML_API void ggml_backend_cpu_set_n_threads(ggml_backend_t backend_cpu, int n_threads);
|
||||
|
||||
// Create a backend buffer from an existing pointer
|
||||
GGML_API ggml_backend_buffer_t ggml_backend_cpu_buffer_from_ptr(ggml_backend_t backend_cpu, void * ptr, size_t size);
|
||||
GGML_API ggml_backend_buffer_t ggml_backend_cpu_buffer_from_ptr(void * ptr, size_t size);
|
||||
|
||||
GGML_API 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
|
||||
@ -131,6 +157,32 @@ extern "C" {
|
||||
ggml_backend_sched_t sched,
|
||||
struct ggml_cgraph * graph);
|
||||
|
||||
|
||||
//
|
||||
// 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_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 void 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
|
||||
|
3601
ggml-cuda.cu
10
ggml-cuda.h
@ -49,7 +49,15 @@ GGML_API int ggml_cuda_get_device_count(void);
|
||||
GGML_API void ggml_cuda_get_device_description(int device, char * description, size_t description_size);
|
||||
|
||||
// backend API
|
||||
GGML_API ggml_backend_t ggml_backend_cuda_init(void); // TODO: take a list of devices to use
|
||||
GGML_API ggml_backend_t ggml_backend_cuda_init(int device);
|
||||
|
||||
GGML_API bool ggml_backend_is_cuda(ggml_backend_t backend);
|
||||
GGML_API int ggml_backend_cuda_get_device(ggml_backend_t backend);
|
||||
|
||||
GGML_API ggml_backend_buffer_type_t ggml_backend_cuda_buffer_type(int device);
|
||||
|
||||
// pinned host buffer for use with CPU backend for faster copies between CPU and GPU
|
||||
GGML_API ggml_backend_buffer_type_t ggml_backend_cuda_host_buffer_type(void);
|
||||
|
||||
#ifdef __cplusplus
|
||||
}
|
||||
|
@ -232,7 +232,7 @@ bool ggml_hash_contains (const struct ggml_hash_set hash_set, struct ggml
|
||||
// returns GGML_HASHTABLE_FULL if table is full, otherwise the current index of the key or where it should be inserted
|
||||
size_t ggml_hash_find (const struct ggml_hash_set hash_set, struct ggml_tensor * key);
|
||||
|
||||
// returns GGML_HAHSHTABLE_ALREADY_EXISTS if key already exists, index otherwise, asserts if table is full
|
||||
// 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
|
||||
|
14
ggml-metal.h
@ -52,11 +52,6 @@ void ggml_metal_free(struct ggml_metal_context * ctx);
|
||||
void * ggml_metal_host_malloc(size_t n);
|
||||
void ggml_metal_host_free (void * data);
|
||||
|
||||
// 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
|
||||
bool ggml_metal_supports_family(struct ggml_metal_context * ctx, int family);
|
||||
|
||||
// set the number of command buffers to use
|
||||
void ggml_metal_set_n_cb(struct ggml_metal_context * ctx, int n_cb);
|
||||
|
||||
@ -92,7 +87,7 @@ int * ggml_metal_get_concur_list(struct ggml_metal_context * ctx);
|
||||
|
||||
// same as ggml_graph_compute but uses Metal
|
||||
// creates gf->n_threads command buffers in parallel
|
||||
void ggml_metal_graph_compute(struct ggml_metal_context * ctx, struct ggml_cgraph * gf);
|
||||
bool ggml_metal_graph_compute(struct ggml_metal_context * ctx, struct ggml_cgraph * gf);
|
||||
|
||||
//
|
||||
// backend API
|
||||
@ -103,8 +98,15 @@ GGML_API ggml_backend_t ggml_backend_metal_init(void);
|
||||
|
||||
GGML_API bool ggml_backend_is_metal(ggml_backend_t backend);
|
||||
|
||||
GGML_API 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_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);
|
||||
|
||||
#ifdef __cplusplus
|
||||
|
1587
ggml-metal.m
3021
ggml-metal.metal
@ -1,20 +1,18 @@
|
||||
#include "ggml.h"
|
||||
#include "ggml-opencl.h"
|
||||
|
||||
#include <array>
|
||||
#include <atomic>
|
||||
#include <cstdio>
|
||||
#include <cstdlib>
|
||||
#include <cstring>
|
||||
#include <limits>
|
||||
#include <sstream>
|
||||
#include <vector>
|
||||
#include <limits>
|
||||
|
||||
#define CL_TARGET_OPENCL_VERSION 110
|
||||
#include <clblast.h>
|
||||
|
||||
#include <stdlib.h>
|
||||
#include <stdio.h>
|
||||
#include <string.h>
|
||||
|
||||
#include "ggml.h"
|
||||
|
||||
#if defined(_MSC_VER)
|
||||
#pragma warning(disable: 4244 4267) // possible loss of data
|
||||
#endif
|
||||
|
@ -6,19 +6,19 @@
|
||||
extern "C" {
|
||||
#endif
|
||||
|
||||
void ggml_cl_init(void);
|
||||
GGML_API void ggml_cl_init(void);
|
||||
|
||||
void ggml_cl_mul(const struct ggml_tensor * src0, const struct ggml_tensor * src1, struct ggml_tensor * dst);
|
||||
bool ggml_cl_can_mul_mat(const struct ggml_tensor * src0, const struct ggml_tensor * src1, struct ggml_tensor * dst);
|
||||
size_t ggml_cl_mul_mat_get_wsize(const struct ggml_tensor * src0, const struct ggml_tensor * src1, struct ggml_tensor * dst);
|
||||
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_mul(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, 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);
|
||||
|
||||
void * ggml_cl_host_malloc(size_t size);
|
||||
void ggml_cl_host_free(void * ptr);
|
||||
GGML_API void * ggml_cl_host_malloc(size_t size);
|
||||
GGML_API void ggml_cl_host_free(void * ptr);
|
||||
|
||||
void ggml_cl_free_data(const struct ggml_tensor* tensor);
|
||||
GGML_API void ggml_cl_free_data(const struct ggml_tensor* tensor);
|
||||
|
||||
void ggml_cl_transform_tensor(void * data, struct ggml_tensor * tensor);
|
||||
GGML_API void ggml_cl_transform_tensor(void * data, struct ggml_tensor * tensor);
|
||||
|
||||
#ifdef __cplusplus
|
||||
}
|
||||
|
487
ggml-quants.c
@ -19,7 +19,7 @@
|
||||
#ifdef __wasm_simd128__
|
||||
#include <wasm_simd128.h>
|
||||
#else
|
||||
#ifdef __POWER9_VECTOR__
|
||||
#if defined(__POWER9_VECTOR__) || defined(__powerpc64__)
|
||||
#include <altivec.h>
|
||||
#undef bool
|
||||
#define bool _Bool
|
||||
@ -407,6 +407,22 @@ inline static ggml_int8x16x4_t ggml_vld1q_s8_x4(const int8_t * ptr) {
|
||||
#define ggml_vld1q_s8_x4 vld1q_s8_x4
|
||||
|
||||
#endif
|
||||
|
||||
#if !defined(__ARM_FEATURE_DOTPROD)
|
||||
|
||||
inline static int32x4_t ggml_vdotq_s32(int32x4_t acc, int8x16_t a, int8x16_t b) {
|
||||
const int16x8_t p0 = vmull_s8(vget_low_s8 (a), vget_low_s8 (b));
|
||||
const int16x8_t p1 = vmull_s8(vget_high_s8(a), vget_high_s8(b));
|
||||
|
||||
return vaddq_s32(acc, vaddq_s32(vpaddlq_s16(p0), vpaddlq_s16(p1)));
|
||||
}
|
||||
|
||||
#else
|
||||
|
||||
#define ggml_vdotq_s32(a, b, c) vdotq_s32(a, b, c)
|
||||
|
||||
#endif
|
||||
|
||||
#endif
|
||||
|
||||
#if defined(__ARM_NEON) || defined(__wasm_simd128__)
|
||||
@ -2468,32 +2484,12 @@ void ggml_vec_dot_q4_0_q8_0(int n, float * restrict s, const void * restrict vx,
|
||||
const int8x16_t v1_1l = vld1q_s8(y1->qs);
|
||||
const int8x16_t v1_1h = vld1q_s8(y1->qs + 16);
|
||||
|
||||
#if defined(__ARM_FEATURE_DOTPROD)
|
||||
// dot product into int32x4_t
|
||||
const int32x4_t p_0 = vdotq_s32(vdotq_s32(vdupq_n_s32(0), v0_0ls, v1_0l), v0_0hs, v1_0h);
|
||||
const int32x4_t p_1 = vdotq_s32(vdotq_s32(vdupq_n_s32(0), v0_1ls, v1_1l), v0_1hs, v1_1h);
|
||||
const int32x4_t p_0 = ggml_vdotq_s32(ggml_vdotq_s32(vdupq_n_s32(0), v0_0ls, v1_0l), v0_0hs, v1_0h);
|
||||
const int32x4_t p_1 = ggml_vdotq_s32(ggml_vdotq_s32(vdupq_n_s32(0), v0_1ls, v1_1l), v0_1hs, v1_1h);
|
||||
|
||||
sumv0 = vmlaq_n_f32(sumv0, vcvtq_f32_s32(p_0), GGML_FP16_TO_FP32(x0->d)*GGML_FP16_TO_FP32(y0->d));
|
||||
sumv1 = vmlaq_n_f32(sumv1, vcvtq_f32_s32(p_1), GGML_FP16_TO_FP32(x1->d)*GGML_FP16_TO_FP32(y1->d));
|
||||
#else
|
||||
const int16x8_t pl0l = vmull_s8(vget_low_s8 (v0_0ls), vget_low_s8 (v1_0l));
|
||||
const int16x8_t pl0h = vmull_s8(vget_high_s8(v0_0ls), vget_high_s8(v1_0l));
|
||||
const int16x8_t ph0l = vmull_s8(vget_low_s8 (v0_0hs), vget_low_s8 (v1_0h));
|
||||
const int16x8_t ph0h = vmull_s8(vget_high_s8(v0_0hs), vget_high_s8(v1_0h));
|
||||
|
||||
const int16x8_t pl1l = vmull_s8(vget_low_s8 (v0_1ls), vget_low_s8 (v1_1l));
|
||||
const int16x8_t pl1h = vmull_s8(vget_high_s8(v0_1ls), vget_high_s8(v1_1l));
|
||||
const int16x8_t ph1l = vmull_s8(vget_low_s8 (v0_1hs), vget_low_s8 (v1_1h));
|
||||
const int16x8_t ph1h = vmull_s8(vget_high_s8(v0_1hs), vget_high_s8(v1_1h));
|
||||
|
||||
const int32x4_t pl0 = vaddq_s32(vpaddlq_s16(pl0l), vpaddlq_s16(pl0h));
|
||||
const int32x4_t ph0 = vaddq_s32(vpaddlq_s16(ph0l), vpaddlq_s16(ph0h));
|
||||
const int32x4_t pl1 = vaddq_s32(vpaddlq_s16(pl1l), vpaddlq_s16(pl1h));
|
||||
const int32x4_t ph1 = vaddq_s32(vpaddlq_s16(ph1l), vpaddlq_s16(ph1h));
|
||||
|
||||
sumv0 = vmlaq_n_f32(sumv0, vcvtq_f32_s32(vaddq_s32(pl0, ph0)), GGML_FP16_TO_FP32(x0->d)*GGML_FP16_TO_FP32(y0->d));
|
||||
sumv1 = vmlaq_n_f32(sumv1, vcvtq_f32_s32(vaddq_s32(pl1, ph1)), GGML_FP16_TO_FP32(x1->d)*GGML_FP16_TO_FP32(y1->d));
|
||||
#endif
|
||||
}
|
||||
|
||||
*s = vaddvq_f32(sumv0) + vaddvq_f32(sumv1);
|
||||
@ -2776,32 +2772,12 @@ void ggml_vec_dot_q4_1_q8_1(const int n, float * restrict s, const void * restri
|
||||
const int8x16_t v1_1l = vld1q_s8(y1->qs);
|
||||
const int8x16_t v1_1h = vld1q_s8(y1->qs + 16);
|
||||
|
||||
#if defined(__ARM_FEATURE_DOTPROD)
|
||||
// dot product into int32x4_t
|
||||
const int32x4_t p_0 = vdotq_s32(vdotq_s32(vdupq_n_s32(0), v0_0l, v1_0l), v0_0h, v1_0h);
|
||||
const int32x4_t p_1 = vdotq_s32(vdotq_s32(vdupq_n_s32(0), v0_1l, v1_1l), v0_1h, v1_1h);
|
||||
const int32x4_t p_0 = ggml_vdotq_s32(ggml_vdotq_s32(vdupq_n_s32(0), v0_0l, v1_0l), v0_0h, v1_0h);
|
||||
const int32x4_t p_1 = ggml_vdotq_s32(ggml_vdotq_s32(vdupq_n_s32(0), v0_1l, v1_1l), v0_1h, v1_1h);
|
||||
|
||||
sumv0 = vmlaq_n_f32(sumv0, vcvtq_f32_s32(p_0), GGML_FP16_TO_FP32(x0->d)*y0->d);
|
||||
sumv1 = vmlaq_n_f32(sumv1, vcvtq_f32_s32(p_1), GGML_FP16_TO_FP32(x1->d)*y1->d);
|
||||
#else
|
||||
const int16x8_t pl0l = vmull_s8(vget_low_s8 (v0_0l), vget_low_s8 (v1_0l));
|
||||
const int16x8_t pl0h = vmull_s8(vget_high_s8(v0_0l), vget_high_s8(v1_0l));
|
||||
const int16x8_t ph0l = vmull_s8(vget_low_s8 (v0_0h), vget_low_s8 (v1_0h));
|
||||
const int16x8_t ph0h = vmull_s8(vget_high_s8(v0_0h), vget_high_s8(v1_0h));
|
||||
|
||||
const int16x8_t pl1l = vmull_s8(vget_low_s8 (v0_1l), vget_low_s8 (v1_1l));
|
||||
const int16x8_t pl1h = vmull_s8(vget_high_s8(v0_1l), vget_high_s8(v1_1l));
|
||||
const int16x8_t ph1l = vmull_s8(vget_low_s8 (v0_1h), vget_low_s8 (v1_1h));
|
||||
const int16x8_t ph1h = vmull_s8(vget_high_s8(v0_1h), vget_high_s8(v1_1h));
|
||||
|
||||
const int32x4_t pl0 = vaddq_s32(vpaddlq_s16(pl0l), vpaddlq_s16(pl0h));
|
||||
const int32x4_t ph0 = vaddq_s32(vpaddlq_s16(ph0l), vpaddlq_s16(ph0h));
|
||||
const int32x4_t pl1 = vaddq_s32(vpaddlq_s16(pl1l), vpaddlq_s16(pl1h));
|
||||
const int32x4_t ph1 = vaddq_s32(vpaddlq_s16(ph1l), vpaddlq_s16(ph1h));
|
||||
|
||||
sumv0 = vmlaq_n_f32(sumv0, vcvtq_f32_s32(vaddq_s32(pl0, ph0)), GGML_FP16_TO_FP32(x0->d)*y0->d);
|
||||
sumv1 = vmlaq_n_f32(sumv1, vcvtq_f32_s32(vaddq_s32(pl1, ph1)), GGML_FP16_TO_FP32(x1->d)*y1->d);
|
||||
#endif
|
||||
}
|
||||
|
||||
*s = vaddvq_f32(sumv0) + vaddvq_f32(sumv1) + summs;
|
||||
@ -2963,32 +2939,12 @@ void ggml_vec_dot_q5_0_q8_0(const int n, float * restrict s, const void * restri
|
||||
const int8x16_t v1_1l = vld1q_s8(y1->qs);
|
||||
const int8x16_t v1_1h = vld1q_s8(y1->qs + 16);
|
||||
|
||||
#if defined(__ARM_FEATURE_DOTPROD)
|
||||
sumv0 = vmlaq_n_f32(sumv0, vcvtq_f32_s32(vaddq_s32(
|
||||
vdotq_s32(vdupq_n_s32(0), v0_0lf, v1_0l),
|
||||
vdotq_s32(vdupq_n_s32(0), v0_0hf, v1_0h))), GGML_FP16_TO_FP32(x0->d)*GGML_FP16_TO_FP32(y0->d));
|
||||
ggml_vdotq_s32(vdupq_n_s32(0), v0_0lf, v1_0l),
|
||||
ggml_vdotq_s32(vdupq_n_s32(0), v0_0hf, v1_0h))), GGML_FP16_TO_FP32(x0->d)*GGML_FP16_TO_FP32(y0->d));
|
||||
sumv1 = vmlaq_n_f32(sumv1, vcvtq_f32_s32(vaddq_s32(
|
||||
vdotq_s32(vdupq_n_s32(0), v0_1lf, v1_1l),
|
||||
vdotq_s32(vdupq_n_s32(0), v0_1hf, v1_1h))), GGML_FP16_TO_FP32(x1->d)*GGML_FP16_TO_FP32(y1->d));
|
||||
#else
|
||||
const int16x8_t pl0l = vmull_s8(vget_low_s8 (v0_0lf), vget_low_s8 (v1_0l));
|
||||
const int16x8_t pl0h = vmull_s8(vget_high_s8(v0_0lf), vget_high_s8(v1_0l));
|
||||
const int16x8_t ph0l = vmull_s8(vget_low_s8 (v0_0hf), vget_low_s8 (v1_0h));
|
||||
const int16x8_t ph0h = vmull_s8(vget_high_s8(v0_0hf), vget_high_s8(v1_0h));
|
||||
|
||||
const int16x8_t pl1l = vmull_s8(vget_low_s8 (v0_1lf), vget_low_s8 (v1_1l));
|
||||
const int16x8_t pl1h = vmull_s8(vget_high_s8(v0_1lf), vget_high_s8(v1_1l));
|
||||
const int16x8_t ph1l = vmull_s8(vget_low_s8 (v0_1hf), vget_low_s8 (v1_1h));
|
||||
const int16x8_t ph1h = vmull_s8(vget_high_s8(v0_1hf), vget_high_s8(v1_1h));
|
||||
|
||||
const int32x4_t pl0 = vaddq_s32(vpaddlq_s16(pl0l), vpaddlq_s16(pl0h));
|
||||
const int32x4_t ph0 = vaddq_s32(vpaddlq_s16(ph0l), vpaddlq_s16(ph0h));
|
||||
const int32x4_t pl1 = vaddq_s32(vpaddlq_s16(pl1l), vpaddlq_s16(pl1h));
|
||||
const int32x4_t ph1 = vaddq_s32(vpaddlq_s16(ph1l), vpaddlq_s16(ph1h));
|
||||
|
||||
sumv0 = vmlaq_n_f32(sumv0, vcvtq_f32_s32(vaddq_s32(pl0, ph0)), GGML_FP16_TO_FP32(x0->d)*GGML_FP16_TO_FP32(y0->d));
|
||||
sumv1 = vmlaq_n_f32(sumv1, vcvtq_f32_s32(vaddq_s32(pl1, ph1)), GGML_FP16_TO_FP32(x1->d)*GGML_FP16_TO_FP32(y1->d));
|
||||
#endif
|
||||
ggml_vdotq_s32(vdupq_n_s32(0), v0_1lf, v1_1l),
|
||||
ggml_vdotq_s32(vdupq_n_s32(0), v0_1hf, v1_1h))), GGML_FP16_TO_FP32(x1->d)*GGML_FP16_TO_FP32(y1->d));
|
||||
}
|
||||
|
||||
*s = vaddvq_f32(sumv0) + vaddvq_f32(sumv1);
|
||||
@ -3114,7 +3070,7 @@ void ggml_vec_dot_q5_0_q8_0(const int n, float * restrict s, const void * restri
|
||||
|
||||
size_t vl = __riscv_vsetvl_e8m1(qk/2);
|
||||
|
||||
// These tempory registers are for masking and shift operations
|
||||
// These temporary registers are for masking and shift operations
|
||||
vuint32m2_t vt_1 = __riscv_vid_v_u32m2(vl);
|
||||
vuint32m2_t vt_2 = __riscv_vsll_vv_u32m2(__riscv_vmv_v_x_u32m2(1, vl), vt_1, vl);
|
||||
|
||||
@ -3275,32 +3231,12 @@ void ggml_vec_dot_q5_1_q8_1(const int n, float * restrict s, const void * restri
|
||||
const int8x16_t v1_1l = vld1q_s8(y1->qs);
|
||||
const int8x16_t v1_1h = vld1q_s8(y1->qs + 16);
|
||||
|
||||
#if defined(__ARM_FEATURE_DOTPROD)
|
||||
sumv0 = vmlaq_n_f32(sumv0, vcvtq_f32_s32(vaddq_s32(
|
||||
vdotq_s32(vdupq_n_s32(0), v0_0lf, v1_0l),
|
||||
vdotq_s32(vdupq_n_s32(0), v0_0hf, v1_0h))), GGML_FP16_TO_FP32(x0->d)*y0->d);
|
||||
ggml_vdotq_s32(vdupq_n_s32(0), v0_0lf, v1_0l),
|
||||
ggml_vdotq_s32(vdupq_n_s32(0), v0_0hf, v1_0h))), GGML_FP16_TO_FP32(x0->d)*y0->d);
|
||||
sumv1 = vmlaq_n_f32(sumv1, vcvtq_f32_s32(vaddq_s32(
|
||||
vdotq_s32(vdupq_n_s32(0), v0_1lf, v1_1l),
|
||||
vdotq_s32(vdupq_n_s32(0), v0_1hf, v1_1h))), GGML_FP16_TO_FP32(x1->d)*y1->d);
|
||||
#else
|
||||
const int16x8_t pl0l = vmull_s8(vget_low_s8 (v0_0lf), vget_low_s8 (v1_0l));
|
||||
const int16x8_t pl0h = vmull_s8(vget_high_s8(v0_0lf), vget_high_s8(v1_0l));
|
||||
const int16x8_t ph0l = vmull_s8(vget_low_s8 (v0_0hf), vget_low_s8 (v1_0h));
|
||||
const int16x8_t ph0h = vmull_s8(vget_high_s8(v0_0hf), vget_high_s8(v1_0h));
|
||||
|
||||
const int16x8_t pl1l = vmull_s8(vget_low_s8 (v0_1lf), vget_low_s8 (v1_1l));
|
||||
const int16x8_t pl1h = vmull_s8(vget_high_s8(v0_1lf), vget_high_s8(v1_1l));
|
||||
const int16x8_t ph1l = vmull_s8(vget_low_s8 (v0_1hf), vget_low_s8 (v1_1h));
|
||||
const int16x8_t ph1h = vmull_s8(vget_high_s8(v0_1hf), vget_high_s8(v1_1h));
|
||||
|
||||
const int32x4_t pl0 = vaddq_s32(vpaddlq_s16(pl0l), vpaddlq_s16(pl0h));
|
||||
const int32x4_t ph0 = vaddq_s32(vpaddlq_s16(ph0l), vpaddlq_s16(ph0h));
|
||||
const int32x4_t pl1 = vaddq_s32(vpaddlq_s16(pl1l), vpaddlq_s16(pl1h));
|
||||
const int32x4_t ph1 = vaddq_s32(vpaddlq_s16(ph1l), vpaddlq_s16(ph1h));
|
||||
|
||||
sumv0 = vmlaq_n_f32(sumv0, vcvtq_f32_s32(vaddq_s32(pl0, ph0)), GGML_FP16_TO_FP32(x0->d)*y0->d);
|
||||
sumv1 = vmlaq_n_f32(sumv1, vcvtq_f32_s32(vaddq_s32(pl1, ph1)), GGML_FP16_TO_FP32(x1->d)*y1->d);
|
||||
#endif
|
||||
ggml_vdotq_s32(vdupq_n_s32(0), v0_1lf, v1_1l),
|
||||
ggml_vdotq_s32(vdupq_n_s32(0), v0_1hf, v1_1h))), GGML_FP16_TO_FP32(x1->d)*y1->d);
|
||||
}
|
||||
|
||||
*s = vaddvq_f32(sumv0) + vaddvq_f32(sumv1) + summs0 + summs1;
|
||||
@ -3550,34 +3486,13 @@ void ggml_vec_dot_q8_0_q8_0(const int n, float * restrict s, const void * restri
|
||||
const int8x16_t y1_0 = vld1q_s8(y1->qs);
|
||||
const int8x16_t y1_1 = vld1q_s8(y1->qs + 16);
|
||||
|
||||
#if defined(__ARM_FEATURE_DOTPROD)
|
||||
sumv0 = vmlaq_n_f32(sumv0, vcvtq_f32_s32(vaddq_s32(
|
||||
vdotq_s32(vdupq_n_s32(0), x0_0, y0_0),
|
||||
vdotq_s32(vdupq_n_s32(0), x0_1, y0_1))), GGML_FP16_TO_FP32(x0->d)*GGML_FP16_TO_FP32(y0->d));
|
||||
ggml_vdotq_s32(vdupq_n_s32(0), x0_0, y0_0),
|
||||
ggml_vdotq_s32(vdupq_n_s32(0), x0_1, y0_1))), GGML_FP16_TO_FP32(x0->d)*GGML_FP16_TO_FP32(y0->d));
|
||||
|
||||
sumv1 = vmlaq_n_f32(sumv1, vcvtq_f32_s32(vaddq_s32(
|
||||
vdotq_s32(vdupq_n_s32(0), x1_0, y1_0),
|
||||
vdotq_s32(vdupq_n_s32(0), x1_1, y1_1))), GGML_FP16_TO_FP32(x1->d)*GGML_FP16_TO_FP32(y1->d));
|
||||
|
||||
#else
|
||||
const int16x8_t p0_0 = vmull_s8(vget_low_s8 (x0_0), vget_low_s8 (y0_0));
|
||||
const int16x8_t p0_1 = vmull_s8(vget_high_s8(x0_0), vget_high_s8(y0_0));
|
||||
const int16x8_t p0_2 = vmull_s8(vget_low_s8 (x0_1), vget_low_s8 (y0_1));
|
||||
const int16x8_t p0_3 = vmull_s8(vget_high_s8(x0_1), vget_high_s8(y0_1));
|
||||
|
||||
const int16x8_t p1_0 = vmull_s8(vget_low_s8 (x1_0), vget_low_s8 (y1_0));
|
||||
const int16x8_t p1_1 = vmull_s8(vget_high_s8(x1_0), vget_high_s8(y1_0));
|
||||
const int16x8_t p1_2 = vmull_s8(vget_low_s8 (x1_1), vget_low_s8 (y1_1));
|
||||
const int16x8_t p1_3 = vmull_s8(vget_high_s8(x1_1), vget_high_s8(y1_1));
|
||||
|
||||
const int32x4_t p0 = vaddq_s32(vpaddlq_s16(p0_0), vpaddlq_s16(p0_1));
|
||||
const int32x4_t p1 = vaddq_s32(vpaddlq_s16(p0_2), vpaddlq_s16(p0_3));
|
||||
const int32x4_t p2 = vaddq_s32(vpaddlq_s16(p1_0), vpaddlq_s16(p1_1));
|
||||
const int32x4_t p3 = vaddq_s32(vpaddlq_s16(p1_2), vpaddlq_s16(p1_3));
|
||||
|
||||
sumv0 = vmlaq_n_f32(sumv0, vcvtq_f32_s32(vaddq_s32(p0, p1)), GGML_FP16_TO_FP32(x0->d)*GGML_FP16_TO_FP32(y0->d));
|
||||
sumv1 = vmlaq_n_f32(sumv1, vcvtq_f32_s32(vaddq_s32(p2, p3)), GGML_FP16_TO_FP32(x1->d)*GGML_FP16_TO_FP32(y1->d));
|
||||
#endif
|
||||
ggml_vdotq_s32(vdupq_n_s32(0), x1_0, y1_0),
|
||||
ggml_vdotq_s32(vdupq_n_s32(0), x1_1, y1_1))), GGML_FP16_TO_FP32(x1->d)*GGML_FP16_TO_FP32(y1->d));
|
||||
}
|
||||
|
||||
*s = vaddvq_f32(sumv0) + vaddvq_f32(sumv1);
|
||||
@ -3650,12 +3565,10 @@ void ggml_vec_dot_q2_K_q8_K(const int n, float * restrict s, const void * restri
|
||||
const int nb = n / QK_K;
|
||||
|
||||
#ifdef __ARM_NEON
|
||||
|
||||
const uint8x16_t m3 = vdupq_n_u8(0x3);
|
||||
const uint8x16_t m4 = vdupq_n_u8(0xF);
|
||||
#if defined(__ARM_FEATURE_DOTPROD)
|
||||
const int32x4_t vzero = vdupq_n_s32(0);
|
||||
#endif
|
||||
|
||||
const int32x4_t vzero = vdupq_n_s32(0);
|
||||
|
||||
ggml_int8x16x2_t q2bytes;
|
||||
uint8_t aux[16];
|
||||
@ -3663,7 +3576,6 @@ void ggml_vec_dot_q2_K_q8_K(const int n, float * restrict s, const void * restri
|
||||
float sum = 0;
|
||||
|
||||
for (int i = 0; i < nb; ++i) {
|
||||
|
||||
const float d = y[i].d * GGML_FP16_TO_FP32(x[i].d);
|
||||
const float dmin = -y[i].d * GGML_FP16_TO_FP32(x[i].dmin);
|
||||
|
||||
@ -3677,7 +3589,7 @@ void ggml_vec_dot_q2_K_q8_K(const int n, float * restrict s, const void * restri
|
||||
|
||||
const uint8x16_t mins = vshrq_n_u8(mins_and_scales, 4);
|
||||
const ggml_int16x8x2_t q8sums = ggml_vld1q_s16_x2(y[i].bsums);
|
||||
const ggml_int16x8x2_t mins16 = {vreinterpretq_s16_u16(vmovl_u8(vget_low_u8(mins))), vreinterpretq_s16_u16(vmovl_u8(vget_high_u8(mins)))};
|
||||
const ggml_int16x8x2_t mins16 = {{vreinterpretq_s16_u16(vmovl_u8(vget_low_u8(mins))), vreinterpretq_s16_u16(vmovl_u8(vget_high_u8(mins)))}};
|
||||
const int32x4_t s0 = vaddq_s32(vmull_s16(vget_low_s16 (mins16.val[0]), vget_low_s16 (q8sums.val[0])),
|
||||
vmull_s16(vget_high_s16(mins16.val[0]), vget_high_s16(q8sums.val[0])));
|
||||
const int32x4_t s1 = vaddq_s32(vmull_s16(vget_low_s16 (mins16.val[1]), vget_low_s16 (q8sums.val[1])),
|
||||
@ -3689,20 +3601,9 @@ void ggml_vec_dot_q2_K_q8_K(const int n, float * restrict s, const void * restri
|
||||
|
||||
// We use this macro instead of a function call because for some reason
|
||||
// the code runs 2-3% slower, even if the function is declared inline
|
||||
#if defined(__ARM_FEATURE_DOTPROD)
|
||||
#define MULTIPLY_ACCUM_WITH_SCALE(index)\
|
||||
isum += vaddvq_s32(vdotq_s32(vzero, q2bytes.val[0], q8bytes.val[0])) * aux[is+(index)];\
|
||||
isum += vaddvq_s32(vdotq_s32(vzero, q2bytes.val[1], q8bytes.val[1])) * aux[is+1+(index)];
|
||||
#else
|
||||
#define MULTIPLY_ACCUM_WITH_SCALE(index)\
|
||||
{\
|
||||
const int16x8_t p1 = vaddq_s16(vmull_s8(vget_low_s8 (q2bytes.val[0]), vget_low_s8 (q8bytes.val[0])),\
|
||||
vmull_s8(vget_high_s8(q2bytes.val[0]), vget_high_s8(q8bytes.val[0])));\
|
||||
const int16x8_t p2 = vaddq_s16(vmull_s8(vget_low_s8 (q2bytes.val[1]), vget_low_s8 (q8bytes.val[1])),\
|
||||
vmull_s8(vget_high_s8(q2bytes.val[1]), vget_high_s8(q8bytes.val[1])));\
|
||||
isum += vaddvq_s16(p1) * aux[is+(index)] + vaddvq_s16(p2) * aux[is+1+(index)];\
|
||||
}
|
||||
#endif
|
||||
isum += vaddvq_s32(ggml_vdotq_s32(vzero, q2bytes.val[0], q8bytes.val[0])) * aux[is+(index)];\
|
||||
isum += vaddvq_s32(ggml_vdotq_s32(vzero, q2bytes.val[1], q8bytes.val[1])) * aux[is+1+(index)];
|
||||
|
||||
#define SHIFT_MULTIPLY_ACCUM_WITH_SCALE(shift, index)\
|
||||
q8bytes = ggml_vld1q_s8_x2(q8); q8 += 32;\
|
||||
@ -3710,26 +3611,23 @@ void ggml_vec_dot_q2_K_q8_K(const int n, float * restrict s, const void * restri
|
||||
q2bytes.val[1] = vreinterpretq_s8_u8(vandq_u8(vshrq_n_u8(q2bits.val[1], (shift)), m3));\
|
||||
MULTIPLY_ACCUM_WITH_SCALE((index));
|
||||
|
||||
|
||||
for (int j = 0; j < QK_K/128; ++j) {
|
||||
|
||||
const ggml_uint8x16x2_t q2bits = ggml_vld1q_u8_x2(q2); q2 += 32;
|
||||
|
||||
ggml_int8x16x2_t q8bytes = ggml_vld1q_s8_x2(q8); q8 += 32;
|
||||
q2bytes.val[0] = vreinterpretq_s8_u8(vandq_u8(q2bits.val[0], m3));
|
||||
q2bytes.val[1] = vreinterpretq_s8_u8(vandq_u8(q2bits.val[1], m3));
|
||||
|
||||
MULTIPLY_ACCUM_WITH_SCALE(0);
|
||||
|
||||
SHIFT_MULTIPLY_ACCUM_WITH_SCALE(2, 2);
|
||||
|
||||
SHIFT_MULTIPLY_ACCUM_WITH_SCALE(4, 4);
|
||||
|
||||
SHIFT_MULTIPLY_ACCUM_WITH_SCALE(6, 6);
|
||||
|
||||
is += 8;
|
||||
}
|
||||
sum += d * isum;
|
||||
|
||||
sum += d * isum;
|
||||
}
|
||||
|
||||
*s = sum;
|
||||
@ -4043,11 +3941,9 @@ void ggml_vec_dot_q2_K_q8_K(const int n, float * restrict s, const void * restri
|
||||
const int nb = n / QK_K;
|
||||
|
||||
#ifdef __ARM_NEON
|
||||
|
||||
const uint8x16_t m3 = vdupq_n_u8(0x3);
|
||||
#if defined(__ARM_FEATURE_DOTPROD)
|
||||
const int32x4_t vzero = vdupq_n_s32(0);
|
||||
#endif
|
||||
|
||||
const int32x4_t vzero = vdupq_n_s32(0);
|
||||
|
||||
ggml_int8x16x4_t q2bytes;
|
||||
|
||||
@ -4081,28 +3977,12 @@ void ggml_vec_dot_q2_K_q8_K(const int n, float * restrict s, const void * restri
|
||||
q2bytes.val[2] = vreinterpretq_s8_u8(vandq_u8(vshrq_n_u8(q2bits, 4), m3));
|
||||
q2bytes.val[3] = vreinterpretq_s8_u8(vandq_u8(vshrq_n_u8(q2bits, 6), m3));
|
||||
|
||||
#if defined(__ARM_FEATURE_DOTPROD)
|
||||
isum1 += vaddvq_s32(vdotq_s32(vzero, q2bytes.val[0], q8bytes.val[0])) * scales[0];
|
||||
isum2 += vaddvq_s32(vdotq_s32(vzero, q2bytes.val[1], q8bytes.val[1])) * scales[1];
|
||||
isum1 += vaddvq_s32(vdotq_s32(vzero, q2bytes.val[2], q8bytes.val[2])) * scales[2];
|
||||
isum2 += vaddvq_s32(vdotq_s32(vzero, q2bytes.val[3], q8bytes.val[3])) * scales[3];
|
||||
#else
|
||||
const int16x8_t p1 = vaddq_s16(vmull_s8(vget_low_s8 (q2bytes.val[0]), vget_low_s8 (q8bytes.val[0])),
|
||||
vmull_s8(vget_high_s8(q2bytes.val[0]), vget_high_s8(q8bytes.val[0])));
|
||||
const int16x8_t p2 = vaddq_s16(vmull_s8(vget_low_s8 (q2bytes.val[1]), vget_low_s8 (q8bytes.val[1])),
|
||||
vmull_s8(vget_high_s8(q2bytes.val[1]), vget_high_s8(q8bytes.val[1])));
|
||||
isum1 += vaddvq_s16(p1) * scales[0];
|
||||
isum2 += vaddvq_s16(p2) * scales[1];
|
||||
isum1 += vaddvq_s32(ggml_vdotq_s32(vzero, q2bytes.val[0], q8bytes.val[0])) * scales[0];
|
||||
isum2 += vaddvq_s32(ggml_vdotq_s32(vzero, q2bytes.val[1], q8bytes.val[1])) * scales[1];
|
||||
isum1 += vaddvq_s32(ggml_vdotq_s32(vzero, q2bytes.val[2], q8bytes.val[2])) * scales[2];
|
||||
isum2 += vaddvq_s32(ggml_vdotq_s32(vzero, q2bytes.val[3], q8bytes.val[3])) * scales[3];
|
||||
|
||||
const int16x8_t p3 = vaddq_s16(vmull_s8(vget_low_s8 (q2bytes.val[2]), vget_low_s8 (q8bytes.val[2])),
|
||||
vmull_s8(vget_high_s8(q2bytes.val[2]), vget_high_s8(q8bytes.val[2])));
|
||||
const int16x8_t p4 = vaddq_s16(vmull_s8(vget_low_s8 (q2bytes.val[3]), vget_low_s8 (q8bytes.val[3])),
|
||||
vmull_s8(vget_high_s8(q2bytes.val[3]), vget_high_s8(q8bytes.val[3])));
|
||||
isum1 += vaddvq_s16(p3) * scales[2];
|
||||
isum2 += vaddvq_s16(p4) * scales[3];
|
||||
#endif
|
||||
sum += d * (isum1 + isum2);
|
||||
|
||||
}
|
||||
|
||||
*s = sum;
|
||||
@ -4328,9 +4208,7 @@ void ggml_vec_dot_q3_K_q8_K(const int n, float * restrict s, const void * restri
|
||||
uint32_t utmp[4];
|
||||
|
||||
const uint8x16_t m3b = vdupq_n_u8(0x3);
|
||||
#ifdef __ARM_FEATURE_DOTPROD
|
||||
const int32x4_t vzero = vdupq_n_s32(0);
|
||||
#endif
|
||||
|
||||
const uint8x16_t m0 = vdupq_n_u8(1);
|
||||
const uint8x16_t m1 = vshlq_n_u8(m0, 1);
|
||||
@ -4382,22 +4260,11 @@ void ggml_vec_dot_q3_K_q8_K(const int n, float * restrict s, const void * restri
|
||||
q3bytes.val[2] = vsubq_s8(vreinterpretq_s8_u8(vandq_u8(vshrq_n_u8(q3bits.val[0], 2), m3b)), vreinterpretq_s8_u8(q3h.val[2]));
|
||||
q3bytes.val[3] = vsubq_s8(vreinterpretq_s8_u8(vandq_u8(vshrq_n_u8(q3bits.val[1], 2), m3b)), vreinterpretq_s8_u8(q3h.val[3]));
|
||||
|
||||
#if defined(__ARM_FEATURE_DOTPROD)
|
||||
isum += vaddvq_s32(vdotq_s32(vzero, q3bytes.val[0], q8bytes_1.val[0])) * scale[0];
|
||||
isum += vaddvq_s32(vdotq_s32(vzero, q3bytes.val[1], q8bytes_1.val[1])) * scale[1];
|
||||
isum += vaddvq_s32(vdotq_s32(vzero, q3bytes.val[2], q8bytes_1.val[2])) * scale[2];
|
||||
isum += vaddvq_s32(vdotq_s32(vzero, q3bytes.val[3], q8bytes_1.val[3])) * scale[3];
|
||||
#else
|
||||
int16x8_t p0 = vaddq_s16(vmull_s8(vget_low_s8 (q3bytes.val[0]), vget_low_s8 (q8bytes_1.val[0])),
|
||||
vmull_s8(vget_high_s8(q3bytes.val[0]), vget_high_s8(q8bytes_1.val[0])));
|
||||
int16x8_t p1 = vaddq_s16(vmull_s8(vget_low_s8 (q3bytes.val[1]), vget_low_s8 (q8bytes_1.val[1])),
|
||||
vmull_s8(vget_high_s8(q3bytes.val[1]), vget_high_s8(q8bytes_1.val[1])));
|
||||
int16x8_t p2 = vaddq_s16(vmull_s8(vget_low_s8 (q3bytes.val[2]), vget_low_s8 (q8bytes_1.val[2])),
|
||||
vmull_s8(vget_high_s8(q3bytes.val[2]), vget_high_s8(q8bytes_1.val[2])));
|
||||
int16x8_t p3 = vaddq_s16(vmull_s8(vget_low_s8 (q3bytes.val[3]), vget_low_s8 (q8bytes_1.val[3])),
|
||||
vmull_s8(vget_high_s8(q3bytes.val[3]), vget_high_s8(q8bytes_1.val[3])));
|
||||
isum += vaddvq_s16(p0) * scale[0] + vaddvq_s16(p1) * scale[1] + vaddvq_s16(p2) * scale[2] + vaddvq_s16(p3) * scale[3];
|
||||
#endif
|
||||
isum += vaddvq_s32(ggml_vdotq_s32(vzero, q3bytes.val[0], q8bytes_1.val[0])) * scale[0];
|
||||
isum += vaddvq_s32(ggml_vdotq_s32(vzero, q3bytes.val[1], q8bytes_1.val[1])) * scale[1];
|
||||
isum += vaddvq_s32(ggml_vdotq_s32(vzero, q3bytes.val[2], q8bytes_1.val[2])) * scale[2];
|
||||
isum += vaddvq_s32(ggml_vdotq_s32(vzero, q3bytes.val[3], q8bytes_1.val[3])) * scale[3];
|
||||
|
||||
scale += 4;
|
||||
|
||||
q3h.val[0] = vbicq_u8(m2, qhbits.val[0]);
|
||||
@ -4410,22 +4277,11 @@ void ggml_vec_dot_q3_K_q8_K(const int n, float * restrict s, const void * restri
|
||||
q3bytes.val[2] = vsubq_s8(vreinterpretq_s8_u8(vandq_u8(vshrq_n_u8(q3bits.val[0], 6), m3b)), vreinterpretq_s8_u8(q3h.val[2]));
|
||||
q3bytes.val[3] = vsubq_s8(vreinterpretq_s8_u8(vandq_u8(vshrq_n_u8(q3bits.val[1], 6), m3b)), vreinterpretq_s8_u8(q3h.val[3]));
|
||||
|
||||
#if defined(__ARM_FEATURE_DOTPROD)
|
||||
isum += vaddvq_s32(vdotq_s32(vzero, q3bytes.val[0], q8bytes_2.val[0])) * scale[0];
|
||||
isum += vaddvq_s32(vdotq_s32(vzero, q3bytes.val[1], q8bytes_2.val[1])) * scale[1];
|
||||
isum += vaddvq_s32(vdotq_s32(vzero, q3bytes.val[2], q8bytes_2.val[2])) * scale[2];
|
||||
isum += vaddvq_s32(vdotq_s32(vzero, q3bytes.val[3], q8bytes_2.val[3])) * scale[3];
|
||||
#else
|
||||
p0 = vaddq_s16(vmull_s8(vget_low_s8 (q3bytes.val[0]), vget_low_s8 (q8bytes_2.val[0])),
|
||||
vmull_s8(vget_high_s8(q3bytes.val[0]), vget_high_s8(q8bytes_2.val[0])));
|
||||
p1 = vaddq_s16(vmull_s8(vget_low_s8 (q3bytes.val[1]), vget_low_s8 (q8bytes_2.val[1])),
|
||||
vmull_s8(vget_high_s8(q3bytes.val[1]), vget_high_s8(q8bytes_2.val[1])));
|
||||
p2 = vaddq_s16(vmull_s8(vget_low_s8 (q3bytes.val[2]), vget_low_s8 (q8bytes_2.val[2])),
|
||||
vmull_s8(vget_high_s8(q3bytes.val[2]), vget_high_s8(q8bytes_2.val[2])));
|
||||
p3 = vaddq_s16(vmull_s8(vget_low_s8 (q3bytes.val[3]), vget_low_s8 (q8bytes_2.val[3])),
|
||||
vmull_s8(vget_high_s8(q3bytes.val[3]), vget_high_s8(q8bytes_2.val[3])));
|
||||
isum += vaddvq_s16(p0) * scale[0] + vaddvq_s16(p1) * scale[1] + vaddvq_s16(p2) * scale[2] + vaddvq_s16(p3) * scale[3];
|
||||
#endif
|
||||
isum += vaddvq_s32(ggml_vdotq_s32(vzero, q3bytes.val[0], q8bytes_2.val[0])) * scale[0];
|
||||
isum += vaddvq_s32(ggml_vdotq_s32(vzero, q3bytes.val[1], q8bytes_2.val[1])) * scale[1];
|
||||
isum += vaddvq_s32(ggml_vdotq_s32(vzero, q3bytes.val[2], q8bytes_2.val[2])) * scale[2];
|
||||
isum += vaddvq_s32(ggml_vdotq_s32(vzero, q3bytes.val[3], q8bytes_2.val[3])) * scale[3];
|
||||
|
||||
scale += 4;
|
||||
|
||||
if (j == 0) {
|
||||
@ -4757,7 +4613,7 @@ void ggml_vec_dot_q3_K_q8_K(const int n, float * restrict s, const void * restri
|
||||
|
||||
vl = 16;
|
||||
|
||||
// retreive lane to multiply with scale
|
||||
// retrieve lane to multiply with scale
|
||||
vint32m2_t aux0_0 = __riscv_vwmul_vx_i32m2(__riscv_vget_v_i16m2_i16m1(a0, 0), (scale[0]), vl);
|
||||
vint32m2_t aux0_1 = __riscv_vwmul_vx_i32m2(__riscv_vget_v_i16m2_i16m1(a0, 1), (scale[1]), vl);
|
||||
vint32m2_t aux1_0 = __riscv_vwmul_vx_i32m2(__riscv_vget_v_i16m2_i16m1(a1, 0), (scale[2]), vl);
|
||||
@ -4864,10 +4720,7 @@ void ggml_vec_dot_q3_K_q8_K(const int n, float * restrict s, const void * restri
|
||||
const int nb = n / QK_K;
|
||||
|
||||
#ifdef __ARM_NEON
|
||||
|
||||
#ifdef __ARM_FEATURE_DOTPROD
|
||||
const int32x4_t vzero = vdupq_n_s32(0);
|
||||
#endif
|
||||
const int32x4_t vzero = vdupq_n_s32(0);
|
||||
|
||||
const uint8x16_t m3b = vdupq_n_u8(0x3);
|
||||
const uint8x16_t mh = vdupq_n_u8(4);
|
||||
@ -4908,22 +4761,10 @@ void ggml_vec_dot_q3_K_q8_K(const int n, float * restrict s, const void * restri
|
||||
q3bytes.val[2] = vreinterpretq_s8_u8(vorrq_u8(vandq_u8(vshrq_n_u8(q3bits, 4), m3b), q3h.val[2]));
|
||||
q3bytes.val[3] = vreinterpretq_s8_u8(vorrq_u8(vshrq_n_u8(q3bits, 6), q3h.val[3]));
|
||||
|
||||
#if defined(__ARM_FEATURE_DOTPROD)
|
||||
isum += vaddvq_s32(vdotq_s32(vzero, q3bytes.val[0], q8bytes.val[0])) * scales[0];
|
||||
isum += vaddvq_s32(vdotq_s32(vzero, q3bytes.val[1], q8bytes.val[1])) * scales[2];
|
||||
isum += vaddvq_s32(vdotq_s32(vzero, q3bytes.val[2], q8bytes.val[2])) * scales[1];
|
||||
isum += vaddvq_s32(vdotq_s32(vzero, q3bytes.val[3], q8bytes.val[3])) * scales[3];
|
||||
#else
|
||||
const int16x8_t p0 = vaddq_s16(vmull_s8(vget_low_s8 (q3bytes.val[0]), vget_low_s8 (q8bytes.val[0])),
|
||||
vmull_s8(vget_high_s8(q3bytes.val[0]), vget_high_s8(q8bytes.val[0])));
|
||||
const int16x8_t p1 = vaddq_s16(vmull_s8(vget_low_s8 (q3bytes.val[1]), vget_low_s8 (q8bytes.val[1])),
|
||||
vmull_s8(vget_high_s8(q3bytes.val[1]), vget_high_s8(q8bytes.val[1])));
|
||||
const int16x8_t p2 = vaddq_s16(vmull_s8(vget_low_s8 (q3bytes.val[2]), vget_low_s8 (q8bytes.val[2])),
|
||||
vmull_s8(vget_high_s8(q3bytes.val[2]), vget_high_s8(q8bytes.val[2])));
|
||||
const int16x8_t p3 = vaddq_s16(vmull_s8(vget_low_s8 (q3bytes.val[3]), vget_low_s8 (q8bytes.val[3])),
|
||||
vmull_s8(vget_high_s8(q3bytes.val[3]), vget_high_s8(q8bytes.val[3])));
|
||||
isum += vaddvq_s16(p0) * scales[0] + vaddvq_s16(p1) * scales[2] + vaddvq_s16(p2) * scales[1] + vaddvq_s16(p3) * scales[3];
|
||||
#endif
|
||||
isum += vaddvq_s32(ggml_vdotq_s32(vzero, q3bytes.val[0], q8bytes.val[0])) * scales[0];
|
||||
isum += vaddvq_s32(ggml_vdotq_s32(vzero, q3bytes.val[1], q8bytes.val[1])) * scales[2];
|
||||
isum += vaddvq_s32(ggml_vdotq_s32(vzero, q3bytes.val[2], q8bytes.val[2])) * scales[1];
|
||||
isum += vaddvq_s32(ggml_vdotq_s32(vzero, q3bytes.val[3], q8bytes.val[3])) * scales[3];
|
||||
|
||||
sum += d * isum;
|
||||
|
||||
@ -5228,11 +5069,8 @@ void ggml_vec_dot_q4_K_q8_K(const int n, float * restrict s, const void * restri
|
||||
uint32_t utmp[4];
|
||||
|
||||
#ifdef __ARM_NEON
|
||||
|
||||
const uint8x16_t m4b = vdupq_n_u8(0xf);
|
||||
#ifdef __ARM_FEATURE_DOTPROD
|
||||
const int32x4_t mzero = vdupq_n_s32(0);
|
||||
#endif
|
||||
|
||||
ggml_int8x16x2_t q4bytes;
|
||||
ggml_int8x16x2_t q8bytes;
|
||||
@ -5269,44 +5107,22 @@ void ggml_vec_dot_q4_K_q8_K(const int n, float * restrict s, const void * restri
|
||||
int32_t sumi2 = 0;
|
||||
|
||||
for (int j = 0; j < QK_K/64; ++j) {
|
||||
|
||||
const ggml_uint8x16x2_t q4bits = ggml_vld1q_u8_x2(q4); q4 += 32;
|
||||
|
||||
#ifdef __ARM_FEATURE_DOTPROD
|
||||
q8bytes = ggml_vld1q_s8_x2(q8); q8 += 32;
|
||||
q4bytes.val[0] = vreinterpretq_s8_u8(vandq_u8 (q4bits.val[0], m4b));
|
||||
q4bytes.val[1] = vreinterpretq_s8_u8(vandq_u8 (q4bits.val[1], m4b));
|
||||
|
||||
const int32x4_t p1 = vdotq_s32(vdotq_s32(mzero, q4bytes.val[0], q8bytes.val[0]), q4bytes.val[1], q8bytes.val[1]);
|
||||
const int32x4_t p1 = ggml_vdotq_s32(ggml_vdotq_s32(mzero, q4bytes.val[0], q8bytes.val[0]), q4bytes.val[1], q8bytes.val[1]);
|
||||
sumi1 += vaddvq_s32(p1) * scales[2*j+0];
|
||||
|
||||
q8bytes = ggml_vld1q_s8_x2(q8); q8 += 32;
|
||||
q4bytes.val[0] = vreinterpretq_s8_u8(vshrq_n_u8(q4bits.val[0], 4));
|
||||
q4bytes.val[1] = vreinterpretq_s8_u8(vshrq_n_u8(q4bits.val[1], 4));
|
||||
|
||||
const int32x4_t p2 = vdotq_s32(vdotq_s32(mzero, q4bytes.val[0], q8bytes.val[0]), q4bytes.val[1], q8bytes.val[1]);
|
||||
const int32x4_t p2 = ggml_vdotq_s32(ggml_vdotq_s32(mzero, q4bytes.val[0], q8bytes.val[0]), q4bytes.val[1], q8bytes.val[1]);
|
||||
|
||||
sumi2 += vaddvq_s32(p2) * scales[2*j+1];
|
||||
#else
|
||||
q8bytes = ggml_vld1q_s8_x2(q8); q8 += 32;
|
||||
q4bytes.val[0] = vreinterpretq_s8_u8(vandq_u8 (q4bits.val[0], m4b));
|
||||
q4bytes.val[1] = vreinterpretq_s8_u8(vandq_u8 (q4bits.val[1], m4b));
|
||||
const int16x8_t p0 = vaddq_s16(vmull_s8(vget_low_s8 (q4bytes.val[0]), vget_low_s8 (q8bytes.val[0])),
|
||||
vmull_s8(vget_high_s8(q4bytes.val[0]), vget_high_s8(q8bytes.val[0])));
|
||||
const int16x8_t p1 = vaddq_s16(vmull_s8(vget_low_s8 (q4bytes.val[1]), vget_low_s8 (q8bytes.val[1])),
|
||||
vmull_s8(vget_high_s8(q4bytes.val[1]), vget_high_s8(q8bytes.val[1])));
|
||||
sumi1 += vaddvq_s16(vaddq_s16(p0, p1)) * scales[2*j+0];
|
||||
|
||||
q8bytes = ggml_vld1q_s8_x2(q8); q8 += 32;
|
||||
q4bytes.val[0] = vreinterpretq_s8_u8(vshrq_n_u8(q4bits.val[0], 4));
|
||||
q4bytes.val[1] = vreinterpretq_s8_u8(vshrq_n_u8(q4bits.val[1], 4));
|
||||
const int16x8_t p2 = vaddq_s16(vmull_s8(vget_low_s8 (q4bytes.val[0]), vget_low_s8 (q8bytes.val[0])),
|
||||
vmull_s8(vget_high_s8(q4bytes.val[0]), vget_high_s8(q8bytes.val[0])));
|
||||
const int16x8_t p3 = vaddq_s16(vmull_s8(vget_low_s8 (q4bytes.val[1]), vget_low_s8 (q8bytes.val[1])),
|
||||
vmull_s8(vget_high_s8(q4bytes.val[1]), vget_high_s8(q8bytes.val[1])));
|
||||
sumi2 += vaddvq_s16(vaddq_s16(p2, p3)) * scales[2*j+1];
|
||||
|
||||
#endif
|
||||
}
|
||||
|
||||
sumf += d * (sumi1 + sumi2);
|
||||
@ -5603,12 +5419,9 @@ void ggml_vec_dot_q4_K_q8_K(const int n, float * restrict s, const void * restri
|
||||
const int nb = n / QK_K;
|
||||
|
||||
#ifdef __ARM_NEON
|
||||
|
||||
const uint8x16_t m4b = vdupq_n_u8(0xf);
|
||||
|
||||
#ifdef __ARM_FEATURE_DOTPROD
|
||||
const int32x4_t mzero = vdupq_n_s32(0);
|
||||
#endif
|
||||
|
||||
float sumf = 0;
|
||||
|
||||
@ -5636,41 +5449,20 @@ void ggml_vec_dot_q4_K_q8_K(const int n, float * restrict s, const void * restri
|
||||
|
||||
const ggml_uint8x16x2_t q4bits = ggml_vld1q_u8_x2(q4);
|
||||
|
||||
#ifdef __ARM_FEATURE_DOTPROD
|
||||
q8bytes = ggml_vld1q_s8_x4(q8);
|
||||
q4bytes.val[0] = vreinterpretq_s8_u8(vandq_u8 (q4bits.val[0], m4b));
|
||||
q4bytes.val[1] = vreinterpretq_s8_u8(vandq_u8 (q4bits.val[1], m4b));
|
||||
|
||||
const int32x4_t p1 = vdotq_s32(vdotq_s32(mzero, q4bytes.val[0], q8bytes.val[0]), q4bytes.val[1], q8bytes.val[1]);
|
||||
const int32x4_t p1 = ggml_vdotq_s32(ggml_vdotq_s32(mzero, q4bytes.val[0], q8bytes.val[0]), q4bytes.val[1], q8bytes.val[1]);
|
||||
const int32_t sumi1 = vaddvq_s32(p1) * scales[0];
|
||||
|
||||
q4bytes.val[0] = vreinterpretq_s8_u8(vshrq_n_u8(q4bits.val[0], 4));
|
||||
q4bytes.val[1] = vreinterpretq_s8_u8(vshrq_n_u8(q4bits.val[1], 4));
|
||||
|
||||
const int32x4_t p2 = vdotq_s32(vdotq_s32(mzero, q4bytes.val[0], q8bytes.val[2]), q4bytes.val[1], q8bytes.val[3]);
|
||||
const int32x4_t p2 = ggml_vdotq_s32(ggml_vdotq_s32(mzero, q4bytes.val[0], q8bytes.val[2]), q4bytes.val[1], q8bytes.val[3]);
|
||||
const int32_t sumi2 = vaddvq_s32(p2) * scales[1];
|
||||
|
||||
#else
|
||||
q8bytes = ggml_vld1q_s8_x4(q8);
|
||||
q4bytes.val[0] = vreinterpretq_s8_u8(vandq_u8 (q4bits.val[0], m4b));
|
||||
q4bytes.val[1] = vreinterpretq_s8_u8(vandq_u8 (q4bits.val[1], m4b));
|
||||
const int16x8_t p0 = vaddq_s16(vmull_s8(vget_low_s8 (q4bytes.val[0]), vget_low_s8 (q8bytes.val[0])),
|
||||
vmull_s8(vget_high_s8(q4bytes.val[0]), vget_high_s8(q8bytes.val[0])));
|
||||
const int16x8_t p1 = vaddq_s16(vmull_s8(vget_low_s8 (q4bytes.val[1]), vget_low_s8 (q8bytes.val[1])),
|
||||
vmull_s8(vget_high_s8(q4bytes.val[1]), vget_high_s8(q8bytes.val[1])));
|
||||
int32_t sumi1 = vaddvq_s16(vaddq_s16(p0, p1)) * scales[0];
|
||||
|
||||
q4bytes.val[0] = vreinterpretq_s8_u8(vshrq_n_u8(q4bits.val[0], 4));
|
||||
q4bytes.val[1] = vreinterpretq_s8_u8(vshrq_n_u8(q4bits.val[1], 4));
|
||||
const int16x8_t p2 = vaddq_s16(vmull_s8(vget_low_s8 (q4bytes.val[0]), vget_low_s8 (q8bytes.val[2])),
|
||||
vmull_s8(vget_high_s8(q4bytes.val[0]), vget_high_s8(q8bytes.val[2])));
|
||||
const int16x8_t p3 = vaddq_s16(vmull_s8(vget_low_s8 (q4bytes.val[1]), vget_low_s8 (q8bytes.val[3])),
|
||||
vmull_s8(vget_high_s8(q4bytes.val[1]), vget_high_s8(q8bytes.val[3])));
|
||||
int32_t sumi2 = vaddvq_s16(vaddq_s16(p2, p3)) * scales[1];
|
||||
|
||||
#endif
|
||||
sumf += d * (sumi1 + sumi2);
|
||||
|
||||
}
|
||||
|
||||
*s = sumf - sum_mins;
|
||||
@ -5875,15 +5667,11 @@ void ggml_vec_dot_q5_K_q8_K(const int n, float * restrict s, const void * restri
|
||||
|
||||
uint32_t utmp[4];
|
||||
|
||||
|
||||
#ifdef __ARM_NEON
|
||||
|
||||
const uint8x16_t m4b = vdupq_n_u8(0xf);
|
||||
const uint8x16_t mone = vdupq_n_u8(1);
|
||||
const uint8x16_t mtwo = vdupq_n_u8(2);
|
||||
#if defined(__ARM_FEATURE_DOTPROD)
|
||||
const int32x4_t mzero = vdupq_n_s32(0);
|
||||
#endif
|
||||
|
||||
ggml_int8x16x4_t q5bytes;
|
||||
|
||||
@ -5938,28 +5726,11 @@ void ggml_vec_dot_q5_K_q8_K(const int n, float * restrict s, const void * restri
|
||||
q5bytes.val[2] = vreinterpretq_s8_u8(vorrq_u8(vshrq_n_u8(q5bits.val[0], 4), q5h.val[2]));
|
||||
q5bytes.val[3] = vreinterpretq_s8_u8(vorrq_u8(vshrq_n_u8(q5bits.val[1], 4), q5h.val[3]));
|
||||
|
||||
#if defined(__ARM_FEATURE_DOTPROD)
|
||||
|
||||
sumi += vaddvq_s32(vdotq_s32(vdotq_s32(mzero, q5bytes.val[0], q8bytes.val[0]), q5bytes.val[1], q8bytes.val[1])) * *scales++;
|
||||
sumi += vaddvq_s32(vdotq_s32(vdotq_s32(mzero, q5bytes.val[2], q8bytes.val[2]), q5bytes.val[3], q8bytes.val[3])) * *scales++;
|
||||
#else
|
||||
|
||||
const int16x8_t p0 = vaddq_s16(vmull_s8(vget_low_s8 (q5bytes.val[0]), vget_low_s8 (q8bytes.val[0])),
|
||||
vmull_s8(vget_high_s8(q5bytes.val[0]), vget_high_s8(q8bytes.val[0])));
|
||||
const int16x8_t p1 = vaddq_s16(vmull_s8(vget_low_s8 (q5bytes.val[1]), vget_low_s8 (q8bytes.val[1])),
|
||||
vmull_s8(vget_high_s8(q5bytes.val[1]), vget_high_s8(q8bytes.val[1])));
|
||||
sumi += vaddvq_s16(vaddq_s16(p0, p1)) * *scales++;
|
||||
|
||||
const int16x8_t p2 = vaddq_s16(vmull_s8(vget_low_s8 (q5bytes.val[2]), vget_low_s8 (q8bytes.val[2])),
|
||||
vmull_s8(vget_high_s8(q5bytes.val[2]), vget_high_s8(q8bytes.val[2])));
|
||||
const int16x8_t p3 = vaddq_s16(vmull_s8(vget_low_s8 (q5bytes.val[3]), vget_low_s8 (q8bytes.val[3])),
|
||||
vmull_s8(vget_high_s8(q5bytes.val[3]), vget_high_s8(q8bytes.val[3])));
|
||||
sumi += vaddvq_s16(vaddq_s16(p2, p3)) * *scales++;
|
||||
#endif
|
||||
sumi += vaddvq_s32(ggml_vdotq_s32(ggml_vdotq_s32(mzero, q5bytes.val[0], q8bytes.val[0]), q5bytes.val[1], q8bytes.val[1])) * *scales++;
|
||||
sumi += vaddvq_s32(ggml_vdotq_s32(ggml_vdotq_s32(mzero, q5bytes.val[2], q8bytes.val[2]), q5bytes.val[3], q8bytes.val[3])) * *scales++;
|
||||
}
|
||||
|
||||
sumf += d * sumi - dmin * sumi_mins;
|
||||
|
||||
}
|
||||
|
||||
*s = sumf;
|
||||
@ -6311,12 +6082,9 @@ void ggml_vec_dot_q5_K_q8_K(const int n, float * restrict s, const void * restri
|
||||
const int nb = n / QK_K;
|
||||
|
||||
#ifdef __ARM_NEON
|
||||
|
||||
const uint8x16_t m4b = vdupq_n_u8(0xf);
|
||||
const uint8x16_t mh = vdupq_n_u8(16);
|
||||
#if defined(__ARM_FEATURE_DOTPROD)
|
||||
const int32x4_t mzero = vdupq_n_s32(0);
|
||||
#endif
|
||||
|
||||
ggml_int8x16x4_t q5bytes;
|
||||
ggml_uint8x16x4_t q5h;
|
||||
@ -6348,32 +6116,12 @@ void ggml_vec_dot_q5_K_q8_K(const int n, float * restrict s, const void * restri
|
||||
q5bytes.val[2] = vsubq_s8(vreinterpretq_s8_u8(vshrq_n_u8(q5bits.val[0], 4)), vreinterpretq_s8_u8(q5h.val[2]));
|
||||
q5bytes.val[3] = vsubq_s8(vreinterpretq_s8_u8(vshrq_n_u8(q5bits.val[1], 4)), vreinterpretq_s8_u8(q5h.val[3]));
|
||||
|
||||
#if defined(__ARM_FEATURE_DOTPROD)
|
||||
|
||||
int32_t sumi1 = sc[0] * vaddvq_s32(vdotq_s32(mzero, q5bytes.val[0], q8bytes.val[0]));
|
||||
int32_t sumi2 = sc[1] * vaddvq_s32(vdotq_s32(mzero, q5bytes.val[1], q8bytes.val[1]));
|
||||
int32_t sumi3 = sc[2] * vaddvq_s32(vdotq_s32(mzero, q5bytes.val[2], q8bytes.val[2]));
|
||||
int32_t sumi4 = sc[3] * vaddvq_s32(vdotq_s32(mzero, q5bytes.val[3], q8bytes.val[3]));
|
||||
int32_t sumi1 = sc[0] * vaddvq_s32(ggml_vdotq_s32(mzero, q5bytes.val[0], q8bytes.val[0]));
|
||||
int32_t sumi2 = sc[1] * vaddvq_s32(ggml_vdotq_s32(mzero, q5bytes.val[1], q8bytes.val[1]));
|
||||
int32_t sumi3 = sc[2] * vaddvq_s32(ggml_vdotq_s32(mzero, q5bytes.val[2], q8bytes.val[2]));
|
||||
int32_t sumi4 = sc[3] * vaddvq_s32(ggml_vdotq_s32(mzero, q5bytes.val[3], q8bytes.val[3]));
|
||||
|
||||
sumf += d * (sumi1 + sumi2 + sumi3 + sumi4);
|
||||
|
||||
#else
|
||||
|
||||
const int16x8_t p0 = vaddq_s16(vmull_s8(vget_low_s8 (q5bytes.val[0]), vget_low_s8 (q8bytes.val[0])),
|
||||
vmull_s8(vget_high_s8(q5bytes.val[0]), vget_high_s8(q8bytes.val[0])));
|
||||
const int16x8_t p1 = vaddq_s16(vmull_s8(vget_low_s8 (q5bytes.val[1]), vget_low_s8 (q8bytes.val[1])),
|
||||
vmull_s8(vget_high_s8(q5bytes.val[1]), vget_high_s8(q8bytes.val[1])));
|
||||
int32_t sumi = sc[0] * vaddvq_s16(p0) + sc[1] * vaddvq_s16(p1);
|
||||
|
||||
const int16x8_t p2 = vaddq_s16(vmull_s8(vget_low_s8 (q5bytes.val[2]), vget_low_s8 (q8bytes.val[2])),
|
||||
vmull_s8(vget_high_s8(q5bytes.val[2]), vget_high_s8(q8bytes.val[2])));
|
||||
const int16x8_t p3 = vaddq_s16(vmull_s8(vget_low_s8 (q5bytes.val[3]), vget_low_s8 (q8bytes.val[3])),
|
||||
vmull_s8(vget_high_s8(q5bytes.val[3]), vget_high_s8(q8bytes.val[3])));
|
||||
sumi += sc[2] * vaddvq_s16(p2) + sc[3] * vaddvq_s16(p3);
|
||||
|
||||
sumf += d*sumi;
|
||||
#endif
|
||||
|
||||
}
|
||||
|
||||
*s = sumf;
|
||||
@ -6600,13 +6348,10 @@ void ggml_vec_dot_q6_K_q8_K(const int n, float * restrict s, const void * restri
|
||||
const int nb = n / QK_K;
|
||||
|
||||
#ifdef __ARM_NEON
|
||||
|
||||
float sum = 0;
|
||||
|
||||
const uint8x16_t m4b = vdupq_n_u8(0xF);
|
||||
#if defined(__ARM_FEATURE_DOTPROD)
|
||||
const int32x4_t vzero = vdupq_n_s32(0);
|
||||
#endif
|
||||
//const int8x16_t m32s = vdupq_n_s8(32);
|
||||
|
||||
const uint8x16_t mone = vdupq_n_u8(3);
|
||||
@ -6626,7 +6371,7 @@ void ggml_vec_dot_q6_K_q8_K(const int n, float * restrict s, const void * restri
|
||||
|
||||
const ggml_int16x8x2_t q8sums = ggml_vld1q_s16_x2(y[i].bsums);
|
||||
const int8x16_t scales = vld1q_s8(scale);
|
||||
const ggml_int16x8x2_t q6scales = {vmovl_s8(vget_low_s8(scales)), vmovl_s8(vget_high_s8(scales))};
|
||||
const ggml_int16x8x2_t q6scales = {{vmovl_s8(vget_low_s8(scales)), vmovl_s8(vget_high_s8(scales))}};
|
||||
|
||||
const int32x4_t prod = vaddq_s32(vaddq_s32(vmull_s16(vget_low_s16 (q8sums.val[0]), vget_low_s16 (q6scales.val[0])),
|
||||
vmull_s16(vget_high_s16(q8sums.val[0]), vget_high_s16(q6scales.val[0]))),
|
||||
@ -6658,31 +6403,13 @@ void ggml_vec_dot_q6_K_q8_K(const int n, float * restrict s, const void * restri
|
||||
q6bytes.val[2] = vreinterpretq_s8_u8(vorrq_u8(vandq_u8(q6bits.val[2], m4b), q6h.val[2]));
|
||||
q6bytes.val[3] = vreinterpretq_s8_u8(vorrq_u8(vandq_u8(q6bits.val[3], m4b), q6h.val[3]));
|
||||
|
||||
#if defined(__ARM_FEATURE_DOTPROD)
|
||||
isum += vaddvq_s32(ggml_vdotq_s32(vzero, q6bytes.val[0], q8bytes.val[0])) * scale[0] +
|
||||
vaddvq_s32(ggml_vdotq_s32(vzero, q6bytes.val[1], q8bytes.val[1])) * scale[1] +
|
||||
vaddvq_s32(ggml_vdotq_s32(vzero, q6bytes.val[2], q8bytes.val[2])) * scale[2] +
|
||||
vaddvq_s32(ggml_vdotq_s32(vzero, q6bytes.val[3], q8bytes.val[3])) * scale[3];
|
||||
|
||||
isum += vaddvq_s32(vdotq_s32(vzero, q6bytes.val[0], q8bytes.val[0])) * scale[0] +
|
||||
vaddvq_s32(vdotq_s32(vzero, q6bytes.val[1], q8bytes.val[1])) * scale[1] +
|
||||
vaddvq_s32(vdotq_s32(vzero, q6bytes.val[2], q8bytes.val[2])) * scale[2] +
|
||||
vaddvq_s32(vdotq_s32(vzero, q6bytes.val[3], q8bytes.val[3])) * scale[3];
|
||||
scale += 4;
|
||||
|
||||
#else
|
||||
|
||||
int16x8_t p0 = vaddq_s16(vmull_s8(vget_low_s8 (q6bytes.val[0]), vget_low_s8 (q8bytes.val[0])),
|
||||
vmull_s8(vget_high_s8(q6bytes.val[0]), vget_high_s8(q8bytes.val[0])));
|
||||
int16x8_t p1 = vaddq_s16(vmull_s8(vget_low_s8 (q6bytes.val[1]), vget_low_s8 (q8bytes.val[1])),
|
||||
vmull_s8(vget_high_s8(q6bytes.val[1]), vget_high_s8(q8bytes.val[1])));
|
||||
isum += vaddvq_s16(p0) * scale[0] + vaddvq_s16(p1) * scale[1];
|
||||
scale += 2;
|
||||
|
||||
int16x8_t p2 = vaddq_s16(vmull_s8(vget_low_s8 (q6bytes.val[2]), vget_low_s8 (q8bytes.val[2])),
|
||||
vmull_s8(vget_high_s8(q6bytes.val[2]), vget_high_s8(q8bytes.val[2])));
|
||||
int16x8_t p3 = vaddq_s16(vmull_s8(vget_low_s8 (q6bytes.val[3]), vget_low_s8 (q8bytes.val[3])),
|
||||
vmull_s8(vget_high_s8(q6bytes.val[3]), vget_high_s8(q8bytes.val[3])));
|
||||
isum += vaddvq_s16(p2) * scale[0] + vaddvq_s16(p3) * scale[1];
|
||||
scale += 2;
|
||||
#endif
|
||||
|
||||
q8bytes = ggml_vld1q_s8_x4(q8); q8 += 64;
|
||||
|
||||
shifted = vshrq_n_u8(qhbits.val[0], 4);
|
||||
@ -6703,34 +6430,11 @@ void ggml_vec_dot_q6_K_q8_K(const int n, float * restrict s, const void * restri
|
||||
q6bytes.val[2] = vreinterpretq_s8_u8(vorrq_u8(vshrq_n_u8(q6bits.val[2], 4), q6h.val[2]));
|
||||
q6bytes.val[3] = vreinterpretq_s8_u8(vorrq_u8(vshrq_n_u8(q6bits.val[3], 4), q6h.val[3]));
|
||||
|
||||
#if defined(__ARM_FEATURE_DOTPROD)
|
||||
|
||||
isum += vaddvq_s32(vdotq_s32(vzero, q6bytes.val[0], q8bytes.val[0])) * scale[0] +
|
||||
vaddvq_s32(vdotq_s32(vzero, q6bytes.val[1], q8bytes.val[1])) * scale[1] +
|
||||
vaddvq_s32(vdotq_s32(vzero, q6bytes.val[2], q8bytes.val[2])) * scale[2] +
|
||||
vaddvq_s32(vdotq_s32(vzero, q6bytes.val[3], q8bytes.val[3])) * scale[3];
|
||||
isum += vaddvq_s32(ggml_vdotq_s32(vzero, q6bytes.val[0], q8bytes.val[0])) * scale[0] +
|
||||
vaddvq_s32(ggml_vdotq_s32(vzero, q6bytes.val[1], q8bytes.val[1])) * scale[1] +
|
||||
vaddvq_s32(ggml_vdotq_s32(vzero, q6bytes.val[2], q8bytes.val[2])) * scale[2] +
|
||||
vaddvq_s32(ggml_vdotq_s32(vzero, q6bytes.val[3], q8bytes.val[3])) * scale[3];
|
||||
scale += 4;
|
||||
|
||||
//for (int l = 0; l < 4; ++l) {
|
||||
// const int32x4_t p = vdotq_s32(vzero, q6bytes.val[l], q8bytes.val[l]);
|
||||
// isum += vaddvq_s32(p) * *scale++;
|
||||
//}
|
||||
#else
|
||||
p0 = vaddq_s16(vmull_s8(vget_low_s8 (q6bytes.val[0]), vget_low_s8 (q8bytes.val[0])),
|
||||
vmull_s8(vget_high_s8(q6bytes.val[0]), vget_high_s8(q8bytes.val[0])));
|
||||
p1 = vaddq_s16(vmull_s8(vget_low_s8 (q6bytes.val[1]), vget_low_s8 (q8bytes.val[1])),
|
||||
vmull_s8(vget_high_s8(q6bytes.val[1]), vget_high_s8(q8bytes.val[1])));
|
||||
isum += vaddvq_s16(p0) * scale[0] + vaddvq_s16(p1) * scale[1];
|
||||
scale += 2;
|
||||
|
||||
p2 = vaddq_s16(vmull_s8(vget_low_s8 (q6bytes.val[2]), vget_low_s8 (q8bytes.val[2])),
|
||||
vmull_s8(vget_high_s8(q6bytes.val[2]), vget_high_s8(q8bytes.val[2])));
|
||||
p3 = vaddq_s16(vmull_s8(vget_low_s8 (q6bytes.val[3]), vget_low_s8 (q8bytes.val[3])),
|
||||
vmull_s8(vget_high_s8(q6bytes.val[3]), vget_high_s8(q8bytes.val[3])));
|
||||
isum += vaddvq_s16(p2) * scale[0] + vaddvq_s16(p3) * scale[1];
|
||||
scale += 2;
|
||||
#endif
|
||||
|
||||
}
|
||||
//sum += isum * d_all * y[i].d;
|
||||
sum += d_all * y[i].d * (isum - 32 * isum_mins);
|
||||
@ -7076,14 +6780,11 @@ void ggml_vec_dot_q6_K_q8_K(const int n, float * restrict s, const void * restri
|
||||
const int nb = n / QK_K;
|
||||
|
||||
#ifdef __ARM_NEON
|
||||
|
||||
float sum = 0;
|
||||
|
||||
const uint8x16_t m4b = vdupq_n_u8(0xF);
|
||||
const int8x16_t m32s = vdupq_n_s8(32);
|
||||
#if defined(__ARM_FEATURE_DOTPROD)
|
||||
const int32x4_t vzero = vdupq_n_s32(0);
|
||||
#endif
|
||||
|
||||
const uint8x16_t mone = vdupq_n_u8(3);
|
||||
|
||||
@ -7119,26 +6820,10 @@ void ggml_vec_dot_q6_K_q8_K(const int n, float * restrict s, const void * restri
|
||||
q6bytes.val[2] = vsubq_s8(vreinterpretq_s8_u8(vorrq_u8(vshrq_n_u8(q6bits.val[0], 4), q6h.val[2])), m32s);
|
||||
q6bytes.val[3] = vsubq_s8(vreinterpretq_s8_u8(vorrq_u8(vshrq_n_u8(q6bits.val[1], 4), q6h.val[3])), m32s);
|
||||
|
||||
#if defined(__ARM_FEATURE_DOTPROD)
|
||||
|
||||
isum += vaddvq_s32(vdotq_s32(vzero, q6bytes.val[0], q8bytes.val[0])) * scale[0] +
|
||||
vaddvq_s32(vdotq_s32(vzero, q6bytes.val[1], q8bytes.val[1])) * scale[1] +
|
||||
vaddvq_s32(vdotq_s32(vzero, q6bytes.val[2], q8bytes.val[2])) * scale[2] +
|
||||
vaddvq_s32(vdotq_s32(vzero, q6bytes.val[3], q8bytes.val[3])) * scale[3];
|
||||
#else
|
||||
|
||||
int16x8_t p0 = vaddq_s16(vmull_s8(vget_low_s8 (q6bytes.val[0]), vget_low_s8 (q8bytes.val[0])),
|
||||
vmull_s8(vget_high_s8(q6bytes.val[0]), vget_high_s8(q8bytes.val[0])));
|
||||
int16x8_t p1 = vaddq_s16(vmull_s8(vget_low_s8 (q6bytes.val[1]), vget_low_s8 (q8bytes.val[1])),
|
||||
vmull_s8(vget_high_s8(q6bytes.val[1]), vget_high_s8(q8bytes.val[1])));
|
||||
isum += vaddvq_s16(p0) * scale[0] + vaddvq_s16(p1) * scale[1];
|
||||
|
||||
int16x8_t p2 = vaddq_s16(vmull_s8(vget_low_s8 (q6bytes.val[2]), vget_low_s8 (q8bytes.val[2])),
|
||||
vmull_s8(vget_high_s8(q6bytes.val[2]), vget_high_s8(q8bytes.val[2])));
|
||||
int16x8_t p3 = vaddq_s16(vmull_s8(vget_low_s8 (q6bytes.val[3]), vget_low_s8 (q8bytes.val[3])),
|
||||
vmull_s8(vget_high_s8(q6bytes.val[3]), vget_high_s8(q8bytes.val[3])));
|
||||
isum += vaddvq_s16(p2) * scale[2] + vaddvq_s16(p3) * scale[3];
|
||||
#endif
|
||||
isum += vaddvq_s32(ggml_vdotq_s32(vzero, q6bytes.val[0], q8bytes.val[0])) * scale[0] +
|
||||
vaddvq_s32(ggml_vdotq_s32(vzero, q6bytes.val[1], q8bytes.val[1])) * scale[1] +
|
||||
vaddvq_s32(ggml_vdotq_s32(vzero, q6bytes.val[2], q8bytes.val[2])) * scale[2] +
|
||||
vaddvq_s32(ggml_vdotq_s32(vzero, q6bytes.val[3], q8bytes.val[3])) * scale[3];
|
||||
|
||||
sum += isum * d_all * y[i].d;
|
||||
|
||||
|
@ -70,7 +70,7 @@ static_assert(sizeof(block_q8_1) == 2*sizeof(float) + QK8_1, "wrong q8_1 block s
|
||||
// 2-bit quantization
|
||||
// weight is represented as x = a * q + b
|
||||
// 16 blocks of 16 elements each
|
||||
// Effectively 2.5625 bits per weight
|
||||
// Effectively 2.625 bits per weight
|
||||
typedef struct {
|
||||
uint8_t scales[QK_K/16]; // scales and mins, quantized with 4 bits
|
||||
uint8_t qs[QK_K/4]; // quants
|
||||
|
147
ggml.h
@ -215,9 +215,9 @@
|
||||
#define GGML_QNT_VERSION_FACTOR 1000 // do not change this
|
||||
|
||||
#define GGML_MAX_DIMS 4
|
||||
#define GGML_MAX_PARAMS 1024
|
||||
#define GGML_MAX_PARAMS 2048
|
||||
#define GGML_MAX_CONTEXTS 64
|
||||
#define GGML_MAX_SRC 6
|
||||
#define GGML_MAX_SRC 10
|
||||
#define GGML_MAX_NAME 64
|
||||
#define GGML_MAX_OP_PARAMS 64
|
||||
#define GGML_DEFAULT_N_THREADS 4
|
||||
@ -244,11 +244,10 @@
|
||||
#define GGML_ASSERT(x) \
|
||||
do { \
|
||||
if (!(x)) { \
|
||||
fprintf(stderr, "GGML_ASSERT: %s:%d: %s\n", __FILE__, __LINE__, #x); \
|
||||
fflush(stderr); \
|
||||
fflush(stdout); \
|
||||
fprintf(stderr, "GGML_ASSERT: %s:%d: %s\n", __FILE__, __LINE__, #x); \
|
||||
ggml_print_backtrace(); \
|
||||
exit(1); \
|
||||
abort(); \
|
||||
} \
|
||||
} while (0)
|
||||
|
||||
@ -256,6 +255,8 @@
|
||||
#define GGML_UNREACHABLE() GGML_ASSERT(!"statement should not be reached")
|
||||
#elif defined(__GNUC__)
|
||||
#define GGML_UNREACHABLE() __builtin_unreachable()
|
||||
#elif defined(_MSC_VER)
|
||||
#define GGML_UNREACHABLE() __assume(0)
|
||||
#else
|
||||
#define GGML_UNREACHABLE() ((void) 0)
|
||||
#endif
|
||||
@ -284,13 +285,27 @@
|
||||
const type prefix##3 = (pointer)->array[3]; \
|
||||
GGML_UNUSED(prefix##3);
|
||||
|
||||
#define GGML_TENSOR_UNARY_OP_LOCALS \
|
||||
GGML_TENSOR_LOCALS(int64_t, ne0, src0, ne) \
|
||||
GGML_TENSOR_LOCALS(size_t, nb0, src0, nb) \
|
||||
GGML_TENSOR_LOCALS(int64_t, ne, dst, ne) \
|
||||
GGML_TENSOR_LOCALS(size_t, nb, dst, nb)
|
||||
|
||||
#define GGML_TENSOR_BINARY_OP_LOCALS \
|
||||
GGML_TENSOR_LOCALS(int64_t, ne0, src0, ne) \
|
||||
GGML_TENSOR_LOCALS(size_t, nb0, src0, nb) \
|
||||
GGML_TENSOR_LOCALS(int64_t, ne1, src1, ne) \
|
||||
GGML_TENSOR_LOCALS(size_t, nb1, src1, nb) \
|
||||
GGML_TENSOR_LOCALS(int64_t, ne, dst, ne) \
|
||||
GGML_TENSOR_LOCALS(size_t, nb, dst, nb)
|
||||
|
||||
#ifdef __cplusplus
|
||||
extern "C" {
|
||||
#endif
|
||||
|
||||
#if defined(__ARM_NEON) && defined(__CUDACC__)
|
||||
typedef half ggml_fp16_t;
|
||||
#elif defined(__ARM_NEON)
|
||||
#elif defined(__ARM_NEON) && !defined(_MSC_VER)
|
||||
typedef __fp16 ggml_fp16_t;
|
||||
#else
|
||||
typedef uint16_t ggml_fp16_t;
|
||||
@ -330,6 +345,12 @@ extern "C" {
|
||||
GGML_TYPE_COUNT,
|
||||
};
|
||||
|
||||
// precision
|
||||
enum ggml_prec {
|
||||
GGML_PREC_DEFAULT,
|
||||
GGML_PREC_F32,
|
||||
};
|
||||
|
||||
enum ggml_backend_type {
|
||||
GGML_BACKEND_CPU = 0,
|
||||
GGML_BACKEND_GPU = 10,
|
||||
@ -382,6 +403,7 @@ extern "C" {
|
||||
GGML_OP_GROUP_NORM,
|
||||
|
||||
GGML_OP_MUL_MAT,
|
||||
GGML_OP_MUL_MAT_ID,
|
||||
GGML_OP_OUT_PROD,
|
||||
|
||||
GGML_OP_SCALE,
|
||||
@ -408,8 +430,10 @@ extern "C" {
|
||||
GGML_OP_CONV_TRANSPOSE_2D,
|
||||
GGML_OP_POOL_1D,
|
||||
GGML_OP_POOL_2D,
|
||||
|
||||
GGML_OP_UPSCALE, // nearest interpolate
|
||||
GGML_OP_PAD,
|
||||
GGML_OP_ARGSORT,
|
||||
GGML_OP_LEAKY_RELU,
|
||||
|
||||
GGML_OP_FLASH_ATTN,
|
||||
GGML_OP_FLASH_FF,
|
||||
@ -449,7 +473,8 @@ extern "C" {
|
||||
GGML_UNARY_OP_GELU,
|
||||
GGML_UNARY_OP_GELU_QUICK,
|
||||
GGML_UNARY_OP_SILU,
|
||||
GGML_UNARY_OP_LEAKY
|
||||
|
||||
GGML_UNARY_OP_COUNT,
|
||||
};
|
||||
|
||||
enum ggml_object_type {
|
||||
@ -461,7 +486,8 @@ extern "C" {
|
||||
enum ggml_log_level {
|
||||
GGML_LOG_LEVEL_ERROR = 2,
|
||||
GGML_LOG_LEVEL_WARN = 3,
|
||||
GGML_LOG_LEVEL_INFO = 4
|
||||
GGML_LOG_LEVEL_INFO = 4,
|
||||
GGML_LOG_LEVEL_DEBUG = 5
|
||||
};
|
||||
|
||||
// ggml object
|
||||
@ -485,7 +511,6 @@ extern "C" {
|
||||
|
||||
struct ggml_backend_buffer * buffer;
|
||||
|
||||
int n_dims;
|
||||
int64_t ne[GGML_MAX_DIMS]; // number of elements
|
||||
size_t nb[GGML_MAX_DIMS]; // stride in bytes:
|
||||
// nb[0] = ggml_type_size(type)
|
||||
@ -517,7 +542,7 @@ extern "C" {
|
||||
|
||||
void * extra; // extra things e.g. for ggml-cuda.cu
|
||||
|
||||
char padding[12];
|
||||
char padding[8];
|
||||
};
|
||||
|
||||
static const size_t GGML_TENSOR_SIZE = sizeof(struct ggml_tensor);
|
||||
@ -622,16 +647,22 @@ extern "C" {
|
||||
GGML_API int64_t ggml_nrows (const struct ggml_tensor * tensor);
|
||||
GGML_API size_t ggml_nbytes (const struct ggml_tensor * tensor);
|
||||
GGML_API size_t ggml_nbytes_pad (const struct ggml_tensor * tensor); // same as ggml_nbytes() but padded to GGML_MEM_ALIGN
|
||||
GGML_API size_t ggml_nbytes_split(const struct ggml_tensor * tensor, int nrows_split);
|
||||
|
||||
GGML_API int ggml_blck_size (enum ggml_type type);
|
||||
GGML_API size_t ggml_type_size (enum ggml_type type); // size in bytes for all elements in a block
|
||||
GGML_API float ggml_type_sizef(enum ggml_type type); // ggml_type_size()/ggml_blck_size() as float
|
||||
GGML_API int ggml_blck_size(enum ggml_type type);
|
||||
GGML_API size_t ggml_type_size(enum ggml_type type); // size in bytes for all elements in a block
|
||||
GGML_API size_t ggml_row_size (enum ggml_type type, int64_t ne); // size in bytes for all elements in a row
|
||||
|
||||
GGML_DEPRECATED(
|
||||
GGML_API double ggml_type_sizef(enum ggml_type type), // ggml_type_size()/ggml_blck_size() as float
|
||||
"use ggml_row_size() instead");
|
||||
|
||||
GGML_API const char * ggml_type_name(enum ggml_type type);
|
||||
GGML_API const char * ggml_op_name (enum ggml_op op);
|
||||
GGML_API const char * ggml_op_symbol(enum ggml_op op);
|
||||
|
||||
GGML_API const char * ggml_unary_op_name(enum ggml_unary_op op);
|
||||
GGML_API const char * ggml_op_desc(const struct ggml_tensor * t); // unary or op name
|
||||
|
||||
GGML_API size_t ggml_element_size(const struct ggml_tensor * tensor);
|
||||
|
||||
GGML_API bool ggml_is_quantized(enum ggml_type type);
|
||||
@ -642,6 +673,11 @@ extern "C" {
|
||||
GGML_API bool ggml_is_transposed(const struct ggml_tensor * tensor);
|
||||
GGML_API bool ggml_is_contiguous(const struct ggml_tensor * tensor);
|
||||
GGML_API bool ggml_is_permuted (const struct ggml_tensor * tensor);
|
||||
GGML_API bool ggml_is_scalar (const struct ggml_tensor * tensor);
|
||||
GGML_API bool ggml_is_vector (const struct ggml_tensor * tensor);
|
||||
GGML_API bool ggml_is_matrix (const struct ggml_tensor * tensor);
|
||||
GGML_API bool ggml_is_3d (const struct ggml_tensor * tensor);
|
||||
GGML_API int ggml_n_dims (const struct ggml_tensor * tensor); // returns 1 for scalars
|
||||
|
||||
GGML_API bool ggml_are_same_shape(const struct ggml_tensor * t0, const struct ggml_tensor * t1);
|
||||
|
||||
@ -702,8 +738,8 @@ extern "C" {
|
||||
GGML_API struct ggml_tensor * ggml_view_tensor(struct ggml_context * ctx, struct ggml_tensor * src);
|
||||
|
||||
// Context tensor enumeration and lookup
|
||||
GGML_API struct ggml_tensor * ggml_get_first_tensor(struct ggml_context * ctx);
|
||||
GGML_API struct ggml_tensor * ggml_get_next_tensor (struct ggml_context * ctx, struct ggml_tensor * tensor);
|
||||
GGML_API struct ggml_tensor * ggml_get_first_tensor(const struct ggml_context * ctx);
|
||||
GGML_API struct ggml_tensor * ggml_get_next_tensor (const struct ggml_context * ctx, struct ggml_tensor * tensor);
|
||||
GGML_API struct ggml_tensor * ggml_get_tensor(struct ggml_context * ctx, const char * name);
|
||||
|
||||
GGML_API struct ggml_tensor * ggml_set_zero(struct ggml_tensor * tensor);
|
||||
@ -774,6 +810,9 @@ extern "C" {
|
||||
struct ggml_tensor * a,
|
||||
struct ggml_tensor * b);
|
||||
|
||||
// dst = a
|
||||
// view(dst, nb1, nb2, nb3, offset) += b
|
||||
// return dst
|
||||
GGML_API struct ggml_tensor * ggml_acc(
|
||||
struct ggml_context * ctx,
|
||||
struct ggml_tensor * a,
|
||||
@ -938,15 +977,14 @@ extern "C" {
|
||||
struct ggml_context * ctx,
|
||||
struct ggml_tensor * a);
|
||||
|
||||
GGML_API struct ggml_tensor * ggml_leaky(
|
||||
GGML_API struct ggml_tensor * ggml_leaky_relu(
|
||||
struct ggml_context * ctx,
|
||||
struct ggml_tensor * a);
|
||||
struct ggml_tensor * a, float negative_slope, bool inplace);
|
||||
|
||||
GGML_API struct ggml_tensor * ggml_relu_inplace(
|
||||
struct ggml_context * ctx,
|
||||
struct ggml_tensor * a);
|
||||
|
||||
// TODO: double-check this computation is correct
|
||||
GGML_API struct ggml_tensor * ggml_gelu(
|
||||
struct ggml_context * ctx,
|
||||
struct ggml_tensor * a);
|
||||
@ -1028,6 +1066,22 @@ extern "C" {
|
||||
struct ggml_tensor * a,
|
||||
struct ggml_tensor * b);
|
||||
|
||||
// change the precision of a matrix multiplication
|
||||
// set to GGML_PREC_F32 for higher precision (useful for phi-2)
|
||||
GGML_API void ggml_mul_mat_set_prec(
|
||||
struct ggml_tensor * a,
|
||||
enum ggml_prec prec);
|
||||
|
||||
// indirect matrix multiplication
|
||||
// ggml_mul_mat_id(ctx, as, ids, id, b) ~= ggml_mul_mat(as[ids[id]], b)
|
||||
GGML_API struct ggml_tensor * ggml_mul_mat_id(
|
||||
struct ggml_context * ctx,
|
||||
struct ggml_tensor * const as[],
|
||||
int n_as,
|
||||
struct ggml_tensor * ids,
|
||||
int id,
|
||||
struct ggml_tensor * b);
|
||||
|
||||
// A: m columns, n rows,
|
||||
// B: p columns, n rows,
|
||||
// result is m columns, p rows
|
||||
@ -1043,13 +1097,13 @@ extern "C" {
|
||||
GGML_API struct ggml_tensor * ggml_scale(
|
||||
struct ggml_context * ctx,
|
||||
struct ggml_tensor * a,
|
||||
struct ggml_tensor * b);
|
||||
float s);
|
||||
|
||||
// in-place, returns view(a)
|
||||
GGML_API struct ggml_tensor * ggml_scale_inplace(
|
||||
struct ggml_context * ctx,
|
||||
struct ggml_tensor * a,
|
||||
struct ggml_tensor * b);
|
||||
float s);
|
||||
|
||||
// b -> view(a,offset,nb1,nb2,3), return modified a
|
||||
GGML_API struct ggml_tensor * ggml_set(
|
||||
@ -1235,6 +1289,7 @@ extern "C" {
|
||||
struct ggml_context * ctx,
|
||||
struct ggml_tensor * a);
|
||||
|
||||
// supports 3D: a->ne[2] == b->ne[1]
|
||||
GGML_API struct ggml_tensor * ggml_get_rows(
|
||||
struct ggml_context * ctx,
|
||||
struct ggml_tensor * a,
|
||||
@ -1283,6 +1338,14 @@ extern "C" {
|
||||
struct ggml_context * ctx,
|
||||
struct ggml_tensor * a);
|
||||
|
||||
// fused soft_max(a*scale + mask)
|
||||
// mask is optional
|
||||
GGML_API struct ggml_tensor * ggml_soft_max_ext(
|
||||
struct ggml_context * ctx,
|
||||
struct ggml_tensor * a,
|
||||
struct ggml_tensor * mask,
|
||||
float scale);
|
||||
|
||||
GGML_API struct ggml_tensor * ggml_soft_max_back(
|
||||
struct ggml_context * ctx,
|
||||
struct ggml_tensor * a,
|
||||
@ -1513,6 +1576,32 @@ extern "C" {
|
||||
struct ggml_tensor * a,
|
||||
int scale_factor);
|
||||
|
||||
// pad each dimension with zeros: [x, ..., x] -> [x, ..., x, 0, ..., 0]
|
||||
GGML_API struct ggml_tensor * ggml_pad(
|
||||
struct ggml_context * ctx,
|
||||
struct ggml_tensor * a,
|
||||
int p0,
|
||||
int p1,
|
||||
int p2,
|
||||
int p3);
|
||||
|
||||
// sort rows
|
||||
enum ggml_sort_order {
|
||||
GGML_SORT_ASC,
|
||||
GGML_SORT_DESC,
|
||||
};
|
||||
|
||||
GGML_API struct ggml_tensor * ggml_argsort(
|
||||
struct ggml_context * ctx,
|
||||
struct ggml_tensor * a,
|
||||
enum ggml_sort_order order);
|
||||
|
||||
// top k elements per row
|
||||
GGML_API struct ggml_tensor * ggml_top_k(
|
||||
struct ggml_context * ctx,
|
||||
struct ggml_tensor * a,
|
||||
int k);
|
||||
|
||||
GGML_API struct ggml_tensor * ggml_flash_attn(
|
||||
struct ggml_context * ctx,
|
||||
struct ggml_tensor * q,
|
||||
@ -1574,7 +1663,6 @@ extern "C" {
|
||||
int kh);
|
||||
|
||||
// used in sam
|
||||
|
||||
GGML_API struct ggml_tensor * ggml_add_rel_pos(
|
||||
struct ggml_context * ctx,
|
||||
struct ggml_tensor * a,
|
||||
@ -1749,7 +1837,7 @@ extern "C" {
|
||||
GGML_API struct ggml_cgraph * ggml_new_graph (struct ggml_context * ctx); // size = GGML_DEFAULT_GRAPH_SIZE, grads = false
|
||||
GGML_API struct ggml_cgraph * ggml_new_graph_custom (struct ggml_context * ctx, size_t size, bool grads);
|
||||
GGML_API struct ggml_cgraph * ggml_graph_dup (struct ggml_context * ctx, struct ggml_cgraph * cgraph);
|
||||
GGML_API struct ggml_cgraph * ggml_graph_view (struct ggml_context * ctx, struct ggml_cgraph * cgraph, int i0, int i1);
|
||||
GGML_API struct ggml_cgraph ggml_graph_view (struct ggml_cgraph * cgraph, int i0, int i1);
|
||||
GGML_API void ggml_graph_cpy (struct ggml_cgraph * src, struct ggml_cgraph * dst);
|
||||
GGML_API void ggml_graph_reset (struct ggml_cgraph * cgraph); // zero grads
|
||||
GGML_API void ggml_graph_clear (struct ggml_cgraph * cgraph);
|
||||
@ -2045,14 +2133,16 @@ extern "C" {
|
||||
GGML_API double gguf_get_val_f64 (const struct gguf_context * ctx, int key_id);
|
||||
GGML_API bool gguf_get_val_bool(const struct gguf_context * ctx, int key_id);
|
||||
GGML_API const char * gguf_get_val_str (const struct gguf_context * ctx, int key_id);
|
||||
GGML_API const void * gguf_get_val_data(const struct gguf_context * ctx, int key_id);
|
||||
GGML_API int gguf_get_arr_n (const struct gguf_context * ctx, int key_id);
|
||||
GGML_API const void * gguf_get_arr_data(const struct gguf_context * ctx, int key_id);
|
||||
GGML_API const char * gguf_get_arr_str (const struct gguf_context * ctx, int key_id, int i);
|
||||
|
||||
GGML_API int gguf_get_n_tensors (const struct gguf_context * ctx);
|
||||
GGML_API int gguf_find_tensor (const struct gguf_context * ctx, const char * name);
|
||||
GGML_API size_t gguf_get_tensor_offset(const struct gguf_context * ctx, int i);
|
||||
GGML_API char * gguf_get_tensor_name (const struct gguf_context * ctx, int i);
|
||||
GGML_API int gguf_get_n_tensors (const struct gguf_context * ctx);
|
||||
GGML_API int gguf_find_tensor (const struct gguf_context * ctx, const char * name);
|
||||
GGML_API size_t gguf_get_tensor_offset(const struct gguf_context * ctx, int i);
|
||||
GGML_API char * gguf_get_tensor_name (const struct gguf_context * ctx, int i);
|
||||
GGML_API enum ggml_type gguf_get_tensor_type (const struct gguf_context * ctx, int i);
|
||||
|
||||
// overrides existing values or adds a new one
|
||||
GGML_API void gguf_set_val_u8 (struct gguf_context * ctx, const char * key, uint8_t val);
|
||||
@ -2108,6 +2198,7 @@ extern "C" {
|
||||
//
|
||||
|
||||
GGML_API int ggml_cpu_has_avx (void);
|
||||
GGML_API int ggml_cpu_has_avx_vnni (void);
|
||||
GGML_API int ggml_cpu_has_avx2 (void);
|
||||
GGML_API int ggml_cpu_has_avx512 (void);
|
||||
GGML_API int ggml_cpu_has_avx512_vbmi(void);
|
||||
|
@ -143,20 +143,7 @@ class AudioEncoderANE(AudioEncoder):
|
||||
x = block(x)
|
||||
|
||||
x = self.ln_post(x)
|
||||
|
||||
# """
|
||||
# TODO:
|
||||
# I think we need to transpose the result here to make it fit whisper.cpp memory order.
|
||||
# However, even doing this, the results are still wrong. Kind of less wrong compared to
|
||||
# not transposing, but still wrong.
|
||||
|
||||
# Also, I don't know why the original OpenAI implementation does not need to transpose
|
||||
|
||||
# transpose to (batch_size, n_ctx, n_state)
|
||||
# x : torch.Tensor, shape = (batch_size, n_state, 1, n_ctx)
|
||||
|
||||
# """
|
||||
# x = x.transpose(1,3)
|
||||
x = x.squeeze(2).transpose(1, 2)
|
||||
|
||||
return x
|
||||
|
||||
|
@ -19,7 +19,7 @@ function get_script_path() {
|
||||
fi
|
||||
}
|
||||
|
||||
models_path="$(get_script_path)"
|
||||
models_path="${2:-$(get_script_path)}"
|
||||
|
||||
# Whisper models
|
||||
models=(
|
||||
@ -43,7 +43,7 @@ models=(
|
||||
"large-v1"
|
||||
"large-v2"
|
||||
"large-v3"
|
||||
"large-q5_0"
|
||||
"large-v3-q5_0"
|
||||
)
|
||||
|
||||
# list available models
|
||||
@ -56,8 +56,8 @@ function list_models {
|
||||
printf "\n\n"
|
||||
}
|
||||
|
||||
if [ "$#" -ne 1 ]; then
|
||||
printf "Usage: $0 <model>\n"
|
||||
if [ "$#" -lt 1 ] || [ "$#" -gt 2 ]; then
|
||||
printf "Usage: $0 <model> [models_path]\n"
|
||||
list_models
|
||||
|
||||
exit 1
|
||||
@ -105,7 +105,7 @@ if [ $? -ne 0 ]; then
|
||||
exit 1
|
||||
fi
|
||||
|
||||
printf "Done! Model '$model' saved in 'models/ggml-$model.bin'\n"
|
||||
printf "Done! Model '$model' saved in '$models_path/ggml-$model.bin'\n"
|
||||
printf "You can now use it like this:\n\n"
|
||||
printf " $ ./main -m models/ggml-$model.bin -f samples/jfk.wav\n"
|
||||
printf " $ ./main -m $models_path/ggml-$model.bin -f samples/jfk.wav\n"
|
||||
printf "\n"
|
||||
|
@ -23,7 +23,7 @@ if [[ $mname == "-h5" ]]; then
|
||||
echo $mpath
|
||||
python3 models/convert-h5-to-coreml.py --model-name $mname --model-path $mpath --encoder-only True
|
||||
else
|
||||
python3 models/convert-whisper-to-coreml.py --model $mname --encoder-only True
|
||||
python3 models/convert-whisper-to-coreml.py --model $mname --encoder-only True --optimize-ane True
|
||||
fi
|
||||
|
||||
xcrun coremlc compile models/coreml-encoder-${mname}.mlpackage models/
|
||||
|
@ -64,15 +64,15 @@ int whisper_openvino_encode(
|
||||
return 0;
|
||||
}
|
||||
|
||||
if (mel->n_dims != 2) {
|
||||
if (ggml_n_dims(mel) != 2) {
|
||||
fprintf(stderr, "%s: Error! mel ggml_tensor expected to have n_dims=2, but it has n_dims=%d\n",
|
||||
__func__, mel->n_dims);
|
||||
__func__, ggml_n_dims(mel));
|
||||
return 0;
|
||||
}
|
||||
|
||||
if (out->n_dims != 2) {
|
||||
if (ggml_n_dims(out) != 2) {
|
||||
fprintf(stderr, "%s: Error! out ggml_tensor expected to have n_dims=2, but it has n_dims=%d\n",
|
||||
__func__, out->n_dims);
|
||||
__func__, ggml_n_dims(out));
|
||||
return 0;
|
||||
}
|
||||
|
||||
@ -105,4 +105,4 @@ int whisper_openvino_encode(
|
||||
}
|
||||
|
||||
return 1;
|
||||
}
|
||||
}
|
||||
|
230
whisper.cpp
@ -122,9 +122,18 @@ WHISPER_ATTRIBUTE_FORMAT(2, 3)
|
||||
static void whisper_log_internal (ggml_log_level level, const char * format, ...);
|
||||
static void whisper_log_callback_default(ggml_log_level level, const char * text, void * user_data);
|
||||
|
||||
#define WHISPER_LOG_INFO(...) whisper_log_internal(GGML_LOG_LEVEL_INFO , __VA_ARGS__)
|
||||
#define WHISPER_LOG_WARN(...) whisper_log_internal(GGML_LOG_LEVEL_WARN , __VA_ARGS__)
|
||||
#define WHISPER_LOG_ERROR(...) whisper_log_internal(GGML_LOG_LEVEL_ERROR, __VA_ARGS__)
|
||||
#define WHISPER_LOG_WARN(...) whisper_log_internal(GGML_LOG_LEVEL_WARN , __VA_ARGS__)
|
||||
#define WHISPER_LOG_INFO(...) whisper_log_internal(GGML_LOG_LEVEL_INFO , __VA_ARGS__)
|
||||
|
||||
// define this to enable verbose trace logging - useful for debugging purposes
|
||||
// #define WHISPER_DEBUG
|
||||
|
||||
#if defined(WHISPER_DEBUG)
|
||||
#define WHISPER_LOG_DEBUG(...) whisper_log_internal(GGML_LOG_LEVEL_DEBUG, __VA_ARGS__)
|
||||
#else
|
||||
#define WHISPER_LOG_DEBUG(...)
|
||||
#endif
|
||||
|
||||
#define WHISPER_ASSERT(x) \
|
||||
do { \
|
||||
@ -134,18 +143,6 @@ static void whisper_log_callback_default(ggml_log_level level, const char * text
|
||||
} \
|
||||
} while (0)
|
||||
|
||||
// define this to enable verbose trace logging - useful for debugging purposes
|
||||
//#define WHISPER_DEBUG
|
||||
|
||||
#if defined(WHISPER_DEBUG)
|
||||
#define WHISPER_PRINT_DEBUG(...) \
|
||||
do { \
|
||||
fprintf(stderr, __VA_ARGS__); \
|
||||
} while (0)
|
||||
#else
|
||||
#define WHISPER_PRINT_DEBUG(...)
|
||||
#endif
|
||||
|
||||
//#define WHISPER_USE_FLASH_ATTN
|
||||
//#define WHISPER_USE_FLASH_FF
|
||||
#define WHISPER_MAX_DECODERS 8
|
||||
@ -155,7 +152,7 @@ static void whisper_log_callback_default(ggml_log_level level, const char * text
|
||||
// ggml helpers
|
||||
//
|
||||
|
||||
static void ggml_graph_compute_helper(
|
||||
static bool ggml_graph_compute_helper(
|
||||
struct ggml_cgraph * graph,
|
||||
std::vector<uint8_t> & buf,
|
||||
int n_threads,
|
||||
@ -171,10 +168,10 @@ static void ggml_graph_compute_helper(
|
||||
plan.work_data = buf.data();
|
||||
}
|
||||
|
||||
ggml_graph_compute(graph, &plan);
|
||||
return ggml_graph_compute(graph, &plan);
|
||||
}
|
||||
|
||||
static void ggml_graph_compute_helper(
|
||||
static bool ggml_graph_compute_helper(
|
||||
struct ggml_backend * backend,
|
||||
struct ggml_cgraph * graph,
|
||||
int n_threads) {
|
||||
@ -186,7 +183,7 @@ static void ggml_graph_compute_helper(
|
||||
ggml_backend_metal_set_n_cb(backend, n_threads);
|
||||
}
|
||||
#endif
|
||||
ggml_backend_graph_compute(backend, graph);
|
||||
return ggml_backend_graph_compute(backend, graph);
|
||||
}
|
||||
|
||||
// faster matrix multiplications for tensors that do not have dimension 0 divisible by "pad"
|
||||
@ -487,8 +484,8 @@ static size_t whisper_allocr_size(struct whisper_allocr & allocr) {
|
||||
|
||||
// measure the memory usage of a graph and prepare the allocr's internal data buffer
|
||||
static void whisper_allocr_graph_init(struct whisper_allocr & allocr, ggml_backend_t backend, std::function<struct ggml_cgraph *()> && get_graph) {
|
||||
auto & alloc = allocr.alloc;
|
||||
auto & meta = allocr.meta;
|
||||
auto & alloc = allocr.alloc;
|
||||
auto & meta = allocr.meta;
|
||||
|
||||
alloc = ggml_allocr_new_measure_from_backend(backend);
|
||||
|
||||
@ -1063,7 +1060,7 @@ static ggml_backend_t whisper_backend_init(const whisper_context_params & params
|
||||
#ifdef GGML_USE_CUBLAS
|
||||
if (params.use_gpu && ggml_cublas_loaded()) {
|
||||
WHISPER_LOG_INFO("%s: using CUDA backend\n", __func__);
|
||||
backend_gpu = ggml_backend_cuda_init();
|
||||
backend_gpu = ggml_backend_cuda_init(0);
|
||||
if (!backend_gpu) {
|
||||
WHISPER_LOG_ERROR("%s: ggml_backend_cuda_init() failed\n", __func__);
|
||||
}
|
||||
@ -1077,8 +1074,7 @@ static ggml_backend_t whisper_backend_init(const whisper_context_params & params
|
||||
backend_gpu = ggml_backend_metal_init();
|
||||
if (!backend_gpu) {
|
||||
WHISPER_LOG_ERROR("%s: ggml_backend_metal_init() failed\n", __func__);
|
||||
}
|
||||
if (!ggml_backend_metal_supports_family(backend_gpu, 7)) {
|
||||
} else if (!ggml_backend_metal_supports_family(backend_gpu, 7)) {
|
||||
WHISPER_LOG_ERROR("%s: Metal GPU does not support family 7 - falling back to CPU\n", __func__);
|
||||
ggml_backend_free(backend_gpu);
|
||||
backend_gpu = NULL;
|
||||
@ -1346,10 +1342,10 @@ static bool whisper_model_load(struct whisper_model_loader * loader, whisper_con
|
||||
model.e_pe = ggml_new_tensor_2d(ctx, GGML_TYPE_F32, n_audio_state, n_audio_ctx);
|
||||
|
||||
model.e_conv_1_w = ggml_new_tensor_3d(ctx, vtype, 3, n_mels, n_audio_state);
|
||||
model.e_conv_1_b = ggml_new_tensor_2d(ctx, GGML_TYPE_F32, 2*n_audio_ctx, n_audio_state);
|
||||
model.e_conv_1_b = ggml_new_tensor_2d(ctx, GGML_TYPE_F32, 1, n_audio_state);
|
||||
|
||||
model.e_conv_2_w = ggml_new_tensor_3d(ctx, vtype, 3, n_audio_state, n_audio_state);
|
||||
model.e_conv_2_b = ggml_new_tensor_2d(ctx, GGML_TYPE_F32, n_audio_ctx, n_audio_state);
|
||||
model.e_conv_2_b = ggml_new_tensor_2d(ctx, GGML_TYPE_F32, 1, n_audio_state);
|
||||
|
||||
model.e_ln_w = ggml_new_tensor_1d(ctx, GGML_TYPE_F32, n_audio_state);
|
||||
model.e_ln_b = ggml_new_tensor_1d(ctx, GGML_TYPE_F32, n_audio_state);
|
||||
@ -1579,29 +1575,25 @@ static bool whisper_model_load(struct whisper_model_loader * loader, whisper_con
|
||||
|
||||
auto tensor = model.tensors[name.data()];
|
||||
|
||||
const bool is_conv_bias = (name == "encoder.conv1.bias" || name == "encoder.conv2.bias");
|
||||
if (ggml_nelements(tensor) != nelements) {
|
||||
WHISPER_LOG_ERROR("%s: tensor '%s' has wrong size in model file\n", __func__, name.data());
|
||||
WHISPER_LOG_ERROR("%s: shape: [%d, %d, %d], expected: [%d, %d, %d]\n",
|
||||
__func__, ne[0], ne[1], ne[2], (int) tensor->ne[0], (int) tensor->ne[1], (int) tensor->ne[2]);
|
||||
return false;
|
||||
}
|
||||
|
||||
if (!is_conv_bias) {
|
||||
if (ggml_nelements(tensor) != nelements) {
|
||||
WHISPER_LOG_ERROR("%s: tensor '%s' has wrong size in model file\n", __func__, name.data());
|
||||
WHISPER_LOG_ERROR("%s: shape: [%d, %d, %d], expected: [%d, %d, %d]\n",
|
||||
__func__, ne[0], ne[1], ne[2], (int) tensor->ne[0], (int) tensor->ne[1], (int) tensor->ne[2]);
|
||||
return false;
|
||||
}
|
||||
if (tensor->ne[0] != ne[0] || tensor->ne[1] != ne[1] || tensor->ne[2] != ne[2]) {
|
||||
WHISPER_LOG_ERROR("%s: tensor '%s' has wrong shape in model file: got [%d, %d, %d], expected [%d, %d, %d]\n",
|
||||
__func__, name.data(), (int) tensor->ne[0], (int) tensor->ne[1], (int) tensor->ne[2], ne[0], ne[1], ne[2]);
|
||||
return false;
|
||||
}
|
||||
|
||||
if (tensor->ne[0] != ne[0] || tensor->ne[1] != ne[1] || tensor->ne[2] != ne[2]) {
|
||||
WHISPER_LOG_ERROR("%s: tensor '%s' has wrong shape in model file: got [%d, %d, %d], expected [%d, %d, %d]\n",
|
||||
__func__, name.data(), (int) tensor->ne[0], (int) tensor->ne[1], (int) tensor->ne[2], ne[0], ne[1], ne[2]);
|
||||
return false;
|
||||
}
|
||||
const size_t bpe = ggml_type_size(ggml_type(ttype));
|
||||
|
||||
const size_t bpe = ggml_type_size(ggml_type(ttype));
|
||||
|
||||
if ((nelements*bpe)/ggml_blck_size(tensor->type) != ggml_nbytes(tensor)) {
|
||||
WHISPER_LOG_ERROR("%s: tensor '%s' has wrong size in model file: got %zu, expected %zu\n",
|
||||
__func__, name.data(), ggml_nbytes(tensor), nelements*bpe);
|
||||
return false;
|
||||
}
|
||||
if ((nelements*bpe)/ggml_blck_size(tensor->type) != ggml_nbytes(tensor)) {
|
||||
WHISPER_LOG_ERROR("%s: tensor '%s' has wrong size in model file: got %zu, expected %zu\n",
|
||||
__func__, name.data(), ggml_nbytes(tensor), nelements*bpe);
|
||||
return false;
|
||||
}
|
||||
|
||||
ggml_backend_t backend = wctx.backend;
|
||||
@ -1612,7 +1604,7 @@ static bool whisper_model_load(struct whisper_model_loader * loader, whisper_con
|
||||
#ifdef GGML_USE_METAL
|
||||
|| ggml_backend_is_metal(backend)
|
||||
#endif
|
||||
) && !is_conv_bias) {
|
||||
)) {
|
||||
// for the CPU and Metal backend, we can read directly into the tensor
|
||||
loader->read(loader->context, tensor->data, ggml_nbytes(tensor));
|
||||
BYTESWAP_TENSOR(tensor);
|
||||
@ -1620,24 +1612,7 @@ static bool whisper_model_load(struct whisper_model_loader * loader, whisper_con
|
||||
// read into a temporary buffer first, then copy to device memory
|
||||
read_buf.resize(ggml_nbytes(tensor));
|
||||
|
||||
// we repeat the 2 bias tensors along dim 0:
|
||||
// [1, 512] -> [3000, 512] (conv1.bias)
|
||||
// [1, 512] -> [1500, 512] (conv2.bias)
|
||||
if (is_conv_bias) {
|
||||
loader->read(loader->context, read_buf.data(), read_buf.size() / tensor->ne[0]);
|
||||
|
||||
float * data_f32 = (float *) read_buf.data();
|
||||
for (int64_t y = 0; y < tensor->ne[1]; ++y) {
|
||||
const int64_t yy = tensor->ne[1] - y - 1;
|
||||
const float val = data_f32[yy];
|
||||
|
||||
for (int64_t x = 0; x < tensor->ne[0]; ++x) {
|
||||
data_f32[yy*tensor->ne[0] + x] = val;
|
||||
}
|
||||
}
|
||||
} else {
|
||||
loader->read(loader->context, read_buf.data(), read_buf.size());
|
||||
}
|
||||
loader->read(loader->context, read_buf.data(), read_buf.size());
|
||||
|
||||
ggml_backend_tensor_set(tensor, read_buf.data(), 0, ggml_nbytes(tensor));
|
||||
}
|
||||
@ -1737,20 +1712,12 @@ static struct ggml_cgraph * whisper_build_graph_conv(
|
||||
// convolution + gelu
|
||||
{
|
||||
cur = ggml_conv_1d_ph(ctx0, model.e_conv_1_w, mel, 1, 1);
|
||||
if (n_ctx == hparams.n_audio_ctx) {
|
||||
cur = ggml_add(ctx0, cur, model.e_conv_1_b);
|
||||
} else {
|
||||
cur = ggml_add(ctx0, cur, ggml_cont(ctx0, ggml_view_2d(ctx0, model.e_conv_1_b, cur->ne[0], cur->ne[1], model.e_conv_1_b->nb[1], 0)));
|
||||
}
|
||||
cur = ggml_add(ctx0, cur, model.e_conv_1_b);
|
||||
|
||||
cur = ggml_gelu(ctx0, cur);
|
||||
|
||||
cur = ggml_conv_1d_ph(ctx0, model.e_conv_2_w, cur, 2, 1);
|
||||
if (n_ctx == hparams.n_audio_ctx) {
|
||||
cur = ggml_add(ctx0, cur, model.e_conv_2_b);
|
||||
} else {
|
||||
cur = ggml_add(ctx0, cur, ggml_cont(ctx0, ggml_view_2d(ctx0, model.e_conv_2_b, cur->ne[0], cur->ne[1], model.e_conv_2_b->nb[1], 0)));
|
||||
}
|
||||
cur = ggml_add(ctx0, cur, model.e_conv_2_b);
|
||||
|
||||
cur = ggml_gelu(ctx0, cur);
|
||||
}
|
||||
@ -1807,7 +1774,7 @@ static struct ggml_cgraph * whisper_build_graph_encoder(
|
||||
|
||||
ggml_cgraph * gf = ggml_new_graph_custom(ctx0, WHISPER_MAX_NODES, false);
|
||||
|
||||
ggml_allocr * alloc = wstate.alloc_encode.alloc;
|
||||
//ggml_allocr * alloc = wstate.alloc_encode.alloc;
|
||||
|
||||
//struct ggml_tensor * cur = ggml_new_tensor_2d(ctx0, GGML_TYPE_F32, n_ctx, n_state);
|
||||
//ggml_allocr_alloc(alloc, cur);
|
||||
@ -1817,13 +1784,7 @@ static struct ggml_cgraph * whisper_build_graph_encoder(
|
||||
//}
|
||||
struct ggml_tensor * cur = ggml_view_tensor(ctx0, wstate.embd_conv);
|
||||
|
||||
struct ggml_tensor * KQscale = ggml_new_tensor_1d(ctx0, GGML_TYPE_F32, 1);
|
||||
ggml_allocr_alloc(alloc, KQscale);
|
||||
|
||||
if (!ggml_allocr_is_measure(alloc)) {
|
||||
const float val = 1.0f/sqrtf(float(n_state)/n_head);
|
||||
ggml_backend_tensor_set(KQscale, &val, 0, sizeof(float));
|
||||
}
|
||||
const float KQscale = 1.0f/sqrtf(float(n_state)/n_head);
|
||||
|
||||
// ===================================================================
|
||||
// NOTE: experimenting with partial evaluation of the encoder (ignore)
|
||||
@ -1873,14 +1834,14 @@ static struct ggml_cgraph * whisper_build_graph_encoder(
|
||||
|
||||
Qcur = ggml_add(ctx0, Qcur, layer.attn_q_b);
|
||||
|
||||
//Qcur = ggml_scale(ctx0, Qcur, ggml_new_f32(ctx0, pow(float(n_state)/n_head, -0.25)));
|
||||
//Qcur = ggml_scale(ctx0, Qcur, pow(float(n_state)/n_head, -0.25));
|
||||
|
||||
// note: no bias for Key
|
||||
struct ggml_tensor * Kcur = ggml_mul_mat(ctx0,
|
||||
layer.attn_k_w,
|
||||
cur);
|
||||
|
||||
//Kcur = ggml_scale(ctx0, Kcur, ggml_new_f32(ctx0, pow(float(n_state)/n_head, -0.25)));
|
||||
//Kcur = ggml_scale(ctx0, Kcur, pow(float(n_state)/n_head, -0.25));
|
||||
|
||||
struct ggml_tensor * Vcur = ggml_mul_mat(ctx0,
|
||||
layer.attn_v_w,
|
||||
@ -2062,7 +2023,7 @@ static struct ggml_cgraph * whisper_build_graph_cross(
|
||||
|
||||
ggml_cgraph * gf = ggml_new_graph(ctx0);
|
||||
|
||||
ggml_allocr * alloc = wstate.alloc_cross.alloc;
|
||||
//ggml_allocr * alloc = wstate.alloc_cross.alloc;
|
||||
|
||||
//struct ggml_tensor * cur = ggml_new_tensor_2d(ctx0, GGML_TYPE_F32, n_state, n_ctx);
|
||||
//ggml_allocr_alloc(alloc, cur);
|
||||
@ -2072,13 +2033,7 @@ static struct ggml_cgraph * whisper_build_graph_cross(
|
||||
//}
|
||||
struct ggml_tensor * cur = ggml_view_tensor(ctx0, wstate.embd_enc);
|
||||
|
||||
struct ggml_tensor * Kscale = ggml_new_tensor_1d(ctx0, GGML_TYPE_F32, 1);
|
||||
ggml_allocr_alloc(alloc, Kscale);
|
||||
|
||||
if (!ggml_allocr_is_measure(alloc)) {
|
||||
const float val = pow(float(n_state) / n_head, -0.25);
|
||||
ggml_backend_tensor_set(Kscale, &val, 0, sizeof(float));
|
||||
}
|
||||
const float Kscale = pow(float(n_state) / n_head, -0.25);
|
||||
|
||||
for (int il = 0; il < model.hparams.n_text_layer; ++il) {
|
||||
auto & layer = model.layers_decoder[il];
|
||||
@ -2148,7 +2103,9 @@ static bool whisper_encode_internal(
|
||||
ggml_allocr_alloc_graph(alloc, gf);
|
||||
|
||||
if (!whisper_encode_external(wstate)) {
|
||||
ggml_graph_compute_helper(wstate.backend, gf, n_threads);
|
||||
if (!ggml_graph_compute_helper(wstate.backend, gf, n_threads)) {
|
||||
return false;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
@ -2162,7 +2119,9 @@ static bool whisper_encode_internal(
|
||||
|
||||
ggml_allocr_alloc_graph(alloc, gf);
|
||||
|
||||
ggml_graph_compute_helper(wstate.backend, gf, n_threads);
|
||||
if (!ggml_graph_compute_helper(wstate.backend, gf, n_threads)) {
|
||||
return false;
|
||||
}
|
||||
}
|
||||
|
||||
// cross
|
||||
@ -2175,7 +2134,9 @@ static bool whisper_encode_internal(
|
||||
|
||||
ggml_allocr_alloc_graph(alloc, gf);
|
||||
|
||||
ggml_graph_compute_helper(wstate.backend, gf, n_threads);
|
||||
if (!ggml_graph_compute_helper(wstate.backend, gf, n_threads)) {
|
||||
return false;
|
||||
}
|
||||
}
|
||||
|
||||
wstate.t_encode_us += ggml_time_us() - t_start_us;
|
||||
@ -2208,7 +2169,7 @@ static struct ggml_cgraph * whisper_build_graph_decoder(
|
||||
const int32_t n_kv = ggml_allocr_is_measure(alloc) ? n_ctx : kv_self.n;
|
||||
const int32_t kv_head = ggml_allocr_is_measure(alloc) ? n_ctx - n_tokens : kv_self.head;
|
||||
|
||||
//WHISPER_PRINT_DEBUG("%s: n_past = %d, n_tokens = %d, n_audio_ctx = %d, n_ctx = %d\n", __func__, n_past, n_tokens, n_audio_ctx, n_ctx);
|
||||
//WHISPER_LOG_DEBUG("%s: n_past = %d, n_tokens = %d, n_audio_ctx = %d, n_ctx = %d\n", __func__, n_past, n_tokens, n_audio_ctx, n_ctx);
|
||||
|
||||
struct ggml_init_params params = {
|
||||
/*.mem_size =*/ wstate.alloc_decode.meta.size(),
|
||||
@ -2237,13 +2198,7 @@ static struct ggml_cgraph * whisper_build_graph_decoder(
|
||||
}
|
||||
}
|
||||
|
||||
struct ggml_tensor * KQscale = ggml_new_tensor_1d(ctx0, GGML_TYPE_F32, 1);
|
||||
ggml_allocr_alloc(alloc, KQscale);
|
||||
|
||||
if (!ggml_allocr_is_measure(alloc)) {
|
||||
const float val = pow(float(n_state)/n_head, -0.25);
|
||||
ggml_backend_tensor_set(KQscale, &val, 0, sizeof(float));
|
||||
}
|
||||
const float KQscale = pow(float(n_state)/n_head, -0.25);
|
||||
|
||||
struct ggml_tensor * KQ_mask = ggml_new_tensor_3d(ctx0, GGML_TYPE_F32, n_kv, n_tokens, 1);
|
||||
ggml_allocr_alloc(alloc, KQ_mask);
|
||||
@ -2603,7 +2558,9 @@ static bool whisper_decode_internal(
|
||||
|
||||
logits = gf->nodes[gf->n_nodes - 1];
|
||||
|
||||
ggml_graph_compute_helper(wstate.backend, gf, n_threads);
|
||||
if (!ggml_graph_compute_helper(wstate.backend, gf, n_threads)) {
|
||||
return false;
|
||||
}
|
||||
}
|
||||
|
||||
logits_out.resize(n_tokens*n_vocab);
|
||||
@ -3864,6 +3821,7 @@ void whisper_reset_timings(struct whisper_context * ctx) {
|
||||
ctx->state->t_sample_us = 0;
|
||||
ctx->state->t_encode_us = 0;
|
||||
ctx->state->t_decode_us = 0;
|
||||
ctx->state->t_batchd_us = 0;
|
||||
ctx->state->t_prompt_us = 0;
|
||||
ctx->state->n_sample = 0;
|
||||
ctx->state->n_encode = 0;
|
||||
@ -4992,7 +4950,7 @@ static void whisper_sequence_score(
|
||||
const auto p = kv.second/(double)cnt;
|
||||
entropy -= p*log(p);
|
||||
|
||||
//WHISPER_PRINT_DEBUG("entropy: %d %f %f, count %d\n", kv.first, p, log(p), kv.second);
|
||||
//WHISPER_LOG_DEBUG("entropy: %d %f %f, count %d\n", kv.first, p, log(p), kv.second);
|
||||
}
|
||||
|
||||
sequence.entropy = entropy;
|
||||
@ -5058,6 +5016,7 @@ int whisper_full_with_state(
|
||||
// basically don't process anything that is less than 1.0s
|
||||
// see issue #39: https://github.com/ggerganov/whisper.cpp/issues/39
|
||||
if (seek_end < seek_start + (params.speed_up ? 50 : 100)) {
|
||||
WHISPER_LOG_DEBUG("%s: input is too short - %d ms < 1000 ms\n", __func__, (seek_end - seek_start)*10);
|
||||
return 0;
|
||||
}
|
||||
|
||||
@ -5246,7 +5205,7 @@ int whisper_full_with_state(
|
||||
|
||||
n_decoders_cur = std::max(1, n_decoders_cur);
|
||||
|
||||
WHISPER_PRINT_DEBUG("\n%s: strategy = %d, decoding with %d decoders, temperature = %.2f\n", __func__, params.strategy, n_decoders_cur, t_cur);
|
||||
WHISPER_LOG_DEBUG("\n%s: strategy = %d, decoding with %d decoders, temperature = %.2f\n", __func__, params.strategy, n_decoders_cur, t_cur);
|
||||
|
||||
// TAGS: WHISPER_DECODER_INIT
|
||||
for (int j = 0; j < n_decoders_cur; ++j) {
|
||||
@ -5290,11 +5249,11 @@ int whisper_full_with_state(
|
||||
prompt.insert(prompt.end(), prompt_init.begin(), prompt_init.end());
|
||||
|
||||
// print the prompt
|
||||
WHISPER_PRINT_DEBUG("\n\n");
|
||||
WHISPER_LOG_DEBUG("\n\n");
|
||||
for (int i = 0; i < (int) prompt.size(); i++) {
|
||||
WHISPER_PRINT_DEBUG("%s: prompt[%d] = %s\n", __func__, i, ctx->vocab.id_to_token.at(prompt[i]).c_str());
|
||||
WHISPER_LOG_DEBUG("%s: prompt[%d] = %s\n", __func__, i, ctx->vocab.id_to_token.at(prompt[i]).c_str());
|
||||
}
|
||||
WHISPER_PRINT_DEBUG("\n\n");
|
||||
WHISPER_LOG_DEBUG("\n\n");
|
||||
|
||||
whisper_kv_cache_clear(state->kv_self);
|
||||
|
||||
@ -5442,7 +5401,7 @@ int whisper_full_with_state(
|
||||
|
||||
whisper_kv_cache_seq_cp(state->kv_self, cur.decoder_idx, WHISPER_MAX_DECODERS + j, -1, -1);
|
||||
|
||||
WHISPER_PRINT_DEBUG("%s: beam search: decoder %d: from decoder %d: token = %10s, plog = %8.5f, sum_logprobs = %8.5f\n",
|
||||
WHISPER_LOG_DEBUG("%s: beam search: decoder %d: from decoder %d: token = %10s, plog = %8.5f, sum_logprobs = %8.5f\n",
|
||||
__func__, j, cur.decoder_idx, ctx->vocab.id_to_token.at(decoder.sequence.tokens.back().id).c_str(), decoder.sequence.tokens.back().plog, decoder.sequence.sum_logprobs_all);
|
||||
}
|
||||
|
||||
@ -5485,6 +5444,7 @@ int whisper_full_with_state(
|
||||
|
||||
// do not allow to go back in time
|
||||
if (has_ts && seek_delta > seek_delta_new && result_len < i) {
|
||||
WHISPER_LOG_DEBUG("%s: decoder %d: failed due to seek_delta (%d > %d)\n", __func__, j, seek_delta, seek_delta_new);
|
||||
failed = true; // TODO: maybe this is not a failure ?
|
||||
continue;
|
||||
}
|
||||
@ -5499,7 +5459,7 @@ int whisper_full_with_state(
|
||||
#ifdef WHISPER_DEBUG
|
||||
{
|
||||
const auto tt = token.pt > 0.10 ? ctx->vocab.id_to_token.at(token.tid) : "[?]";
|
||||
WHISPER_PRINT_DEBUG("%s: id = %3d, decoder = %d, token = %6d, p = %6.3f, ts = %10s, %6.3f, result_len = %4d '%s'\n",
|
||||
WHISPER_LOG_DEBUG("%s: id = %3d, decoder = %d, token = %6d, p = %6.3f, ts = %10s, %6.3f, result_len = %4d '%s'\n",
|
||||
__func__, i, j, token.id, token.p, tt.c_str(), token.pt, result_len, ctx->vocab.id_to_token.at(token.id).c_str());
|
||||
}
|
||||
#endif
|
||||
@ -5513,6 +5473,7 @@ int whisper_full_with_state(
|
||||
if (seek + seek_delta + 100 >= seek_end) {
|
||||
result_len = i + 1;
|
||||
} else {
|
||||
WHISPER_LOG_DEBUG("%s: decoder %d failed (result_len = 0)\n", __func__, j);
|
||||
failed = true;
|
||||
continue;
|
||||
}
|
||||
@ -5523,6 +5484,7 @@ int whisper_full_with_state(
|
||||
seek_delta = 100*WHISPER_CHUNK_SIZE;
|
||||
}
|
||||
|
||||
WHISPER_LOG_DEBUG("%s: decoder %d completed\n", __func__, j);
|
||||
completed = true;
|
||||
continue;
|
||||
}
|
||||
@ -5538,6 +5500,7 @@ int whisper_full_with_state(
|
||||
// sometimes, the decoding can get stuck in a repetition loop
|
||||
// this is an attempt to mitigate such cases - we flag the decoding as failed and use a fallback strategy
|
||||
if (i == n_max - 1 && (result_len == 0 || seek_delta < 100*WHISPER_CHUNK_SIZE/2)) {
|
||||
WHISPER_LOG_DEBUG("%s: decoder %d: failed due to repetition loop\n", __func__, j);
|
||||
failed = true;
|
||||
continue;
|
||||
}
|
||||
@ -5579,7 +5542,7 @@ int whisper_full_with_state(
|
||||
continue;
|
||||
}
|
||||
|
||||
//WHISPER_PRINT_DEBUG("%s: decoder %d: token %d, seek_delta %d\n", __func__, j, decoder.sequence.tokens.back().id, decoder.seek_delta);
|
||||
//WHISPER_LOG_DEBUG("%s: decoder %d: token %d, seek_delta %d\n", __func__, j, decoder.sequence.tokens.back().id, decoder.seek_delta);
|
||||
|
||||
decoder.i_batch = batch.n_tokens;
|
||||
|
||||
@ -5659,11 +5622,11 @@ int whisper_full_with_state(
|
||||
decoder.sequence.tokens.resize(decoder.sequence.result_len);
|
||||
whisper_sequence_score(params, decoder.sequence);
|
||||
|
||||
WHISPER_PRINT_DEBUG("%s: decoder %2d: score = %8.5f, result_len = %3d, avg_logprobs = %8.5f, entropy = %8.5f\n",
|
||||
WHISPER_LOG_DEBUG("%s: decoder %2d: score = %8.5f, result_len = %3d, avg_logprobs = %8.5f, entropy = %8.5f\n",
|
||||
__func__, j, decoder.sequence.score, decoder.sequence.result_len, decoder.sequence.avg_logprobs, decoder.sequence.entropy);
|
||||
|
||||
if (decoder.sequence.result_len > 32 && decoder.sequence.entropy < params.entropy_thold) {
|
||||
WHISPER_PRINT_DEBUG("%s: decoder %2d: failed due to entropy %8.5f < %8.5f\n",
|
||||
WHISPER_LOG_DEBUG("%s: decoder %2d: failed due to entropy %8.5f < %8.5f\n",
|
||||
__func__, j, decoder.sequence.entropy, params.entropy_thold);
|
||||
|
||||
decoder.failed = true;
|
||||
@ -5678,34 +5641,33 @@ int whisper_full_with_state(
|
||||
}
|
||||
}
|
||||
|
||||
WHISPER_PRINT_DEBUG("%s: best decoder = %d\n", __func__, best_decoder_id);
|
||||
WHISPER_LOG_DEBUG("%s: best decoder = %d\n", __func__, best_decoder_id);
|
||||
}
|
||||
|
||||
bool success = true;
|
||||
|
||||
// was the decoding successful for the current temperature?
|
||||
// do fallback only if:
|
||||
// - we are not at the last temperature
|
||||
// - we are not at the end of the audio (3 sec)
|
||||
if (it != (int) temperatures.size() - 1 &&
|
||||
seek_end - seek > 10*WHISPER_CHUNK_SIZE) {
|
||||
bool success = true;
|
||||
|
||||
if (it != (int) temperatures.size() - 1) {
|
||||
const auto & decoder = state->decoders[best_decoder_id];
|
||||
|
||||
if (decoder.failed || decoder.sequence.avg_logprobs < params.logprob_thold) {
|
||||
WHISPER_LOG_DEBUG("%s: failed due to avg_logprobs %8.5f < %8.5f\n", __func__, decoder.sequence.avg_logprobs, params.logprob_thold);
|
||||
success = false;
|
||||
state->n_fail_p++;
|
||||
}
|
||||
|
||||
if (success) {
|
||||
//for (auto & token : ctx->decoders[best_decoder_id].sequence.tokens) {
|
||||
// WHISPER_PRINT_DEBUG("%s: token = %d, p = %6.3f, pt = %6.3f, ts = %s, str = %s\n", __func__, token.id, token.p, token.pt, ctx->vocab.id_to_token.at(token.tid).c_str(), ctx->vocab.id_to_token.at(token.id).c_str());
|
||||
//}
|
||||
|
||||
break;
|
||||
}
|
||||
}
|
||||
|
||||
WHISPER_PRINT_DEBUG("\n%s: failed to decode with temperature = %.2f\n", __func__, t_cur);
|
||||
if (success) {
|
||||
//for (auto & token : ctx->decoders[best_decoder_id].sequence.tokens) {
|
||||
// WHISPER_LOG_DEBUG("%s: token = %d, p = %6.3f, pt = %6.3f, ts = %s, str = %s\n", __func__, token.id, token.p, token.pt, ctx->vocab.id_to_token.at(token.tid).c_str(), ctx->vocab.id_to_token.at(token.id).c_str());
|
||||
//}
|
||||
|
||||
break;
|
||||
}
|
||||
|
||||
WHISPER_LOG_DEBUG("\n%s: failed to decode with temperature = %.2f\n", __func__, t_cur);
|
||||
}
|
||||
|
||||
// output results through a user-provided callback
|
||||
@ -5717,7 +5679,7 @@ int whisper_full_with_state(
|
||||
|
||||
const auto & tokens_cur = best_decoder.sequence.tokens;
|
||||
|
||||
//WHISPER_PRINT_DEBUG("prompt_init.size() = %d, prompt.size() = %d, result_len = %d, seek_delta = %d\n", prompt_init.size(), prompt.size(), result_len, seek_delta);
|
||||
//WHISPER_LOG_DEBUG("prompt_init.size() = %d, prompt.size() = %d, result_len = %d, seek_delta = %d\n", prompt_init.size(), prompt.size(), result_len, seek_delta);
|
||||
|
||||
// update prompt_past
|
||||
prompt_past.clear();
|
||||
@ -5837,7 +5799,7 @@ int whisper_full_with_state(
|
||||
// update audio window
|
||||
seek += seek_delta;
|
||||
|
||||
WHISPER_PRINT_DEBUG("seek = %d, seek_delta = %d\n", seek, seek_delta);
|
||||
WHISPER_LOG_DEBUG("seek = %d, seek_delta = %d\n", seek, seek_delta);
|
||||
}
|
||||
}
|
||||
|
||||
@ -6154,7 +6116,7 @@ WHISPER_API const char * whisper_bench_memcpy_str(int n_threads) {
|
||||
|
||||
// multi-thread
|
||||
|
||||
for (uint32_t k = 1; k <= n_threads; k++) {
|
||||
for (int32_t k = 1; k <= n_threads; k++) {
|
||||
char * src = (char *) malloc(size);
|
||||
char * dst = (char *) malloc(size);
|
||||
|
||||
@ -6178,13 +6140,13 @@ WHISPER_API const char * whisper_bench_memcpy_str(int n_threads) {
|
||||
const int64_t t0 = ggml_time_us();
|
||||
|
||||
std::vector<std::thread> threads(k - 1);
|
||||
for (uint32_t th = 0; th < k - 1; ++th) {
|
||||
for (int32_t th = 0; th < k - 1; ++th) {
|
||||
threads[th] = std::thread(helper, th);
|
||||
}
|
||||
|
||||
helper(k - 1);
|
||||
|
||||
for (uint32_t th = 0; th < k - 1; ++th) {
|
||||
for (int32_t th = 0; th < k - 1; ++th) {
|
||||
threads[th].join();
|
||||
}
|
||||
|
||||
|
@ -51,7 +51,7 @@ extern "C" {
|
||||
// ...
|
||||
//
|
||||
// whisper_context_params cparams = whisper_context_default_params();
|
||||
//
|
||||
//
|
||||
// struct whisper_context * ctx = whisper_init_from_file_with_params("/path/to/ggml-base.en.bin", cparams);
|
||||
//
|
||||
// if (whisper_full(ctx, wparams, pcmf32.data(), pcmf32.size()) != 0) {
|
||||
@ -316,7 +316,7 @@ extern "C" {
|
||||
WHISPER_API const char * whisper_lang_str(int id);
|
||||
|
||||
// Return the short string of the specified language name (e.g. 2 -> "german"), returns nullptr if not found
|
||||
WHISPER_API const char * whisper_lang_str_full(int id);
|
||||
WHISPER_API const char * whisper_lang_str_full(int id);
|
||||
|
||||
// Use mel data at offset_ms to try and auto-detect the spoken language
|
||||
// Make sure to call whisper_pcm_to_mel() or whisper_set_mel() first
|
||||
|