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Fangjun Kuang
Committed by GitHub
4d79e6a0 1 parent bafd1103

Add C++ API for streaming zipformer ASR on RK NPU (#1908)

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正在显示 73 个修改的文件 包含 1906 行增加 和 117 行删除
... ... @@ -199,6 +199,7 @@ jobs:
timeout_seconds: 200
shell: bash
command: |
SHERPA_ONNX_VERSION=$(grep "SHERPA_ONNX_VERSION" ./CMakeLists.txt | cut -d " " -f 2 | cut -d '"' -f 2)
git config --global user.email "csukuangfj@gmail.com"
git config --global user.name "Fangjun Kuang"
... ... @@ -207,9 +208,10 @@ jobs:
GIT_LFS_SKIP_SMUDGE=1 git clone https://csukuangfj:$HF_TOKEN@huggingface.co/csukuangfj/sherpa-onnx-libs huggingface
cd huggingface
mkdir -p aarch64
dst=aarch64/$SHERPA_ONNX_VERSION
mkdir -p $dst
cp -v ../sherpa-onnx-*-shared*.tar.bz2 ./aarch64
cp -v ../sherpa-onnx-*-shared*.tar.bz2 $dst/
git status
git lfs track "*.bz2"
... ...
... ... @@ -124,6 +124,7 @@ jobs:
timeout_seconds: 200
shell: bash
command: |
SHERPA_ONNX_VERSION=$(grep "SHERPA_ONNX_VERSION" ./CMakeLists.txt | cut -d " " -f 2 | cut -d '"' -f 2)
git config --global user.email "csukuangfj@gmail.com"
git config --global user.name "Fangjun Kuang"
... ... @@ -132,9 +133,10 @@ jobs:
GIT_LFS_SKIP_SMUDGE=1 git clone https://csukuangfj:$HF_TOKEN@huggingface.co/csukuangfj/sherpa-onnx-libs huggingface
cd huggingface
mkdir -p aarch64
dst=aarch64/$SHERPA_ONNX_VERSION
mkdir -p $dst
cp -v ../sherpa-onnx-*-static.tar.bz2 ./aarch64
cp -v ../sherpa-onnx-*-static.tar.bz2 $dst/
git status
git lfs track "*.bz2"
... ...
... ... @@ -140,6 +140,7 @@ jobs:
timeout_seconds: 200
shell: bash
command: |
SHERPA_ONNX_VERSION=$(grep "SHERPA_ONNX_VERSION" ./CMakeLists.txt | cut -d " " -f 2 | cut -d '"' -f 2)
git config --global user.email "csukuangfj@gmail.com"
git config --global user.name "Fangjun Kuang"
du -h -d1 .
... ... @@ -150,8 +151,10 @@ jobs:
GIT_LFS_SKIP_SMUDGE=1 git clone https://csukuangfj:$HF_TOKEN@huggingface.co/csukuangfj/sherpa-onnx-libs huggingface
cd huggingface
dst=$SHERPA_ONNX_VERSION
mkdir -p $dst
cp -v ../sherpa-onnx-*-android*.tar.bz2 ./
cp -v ../sherpa-onnx-*-android*.tar.bz2 $dst/
git status
git lfs track "*.bz2"
... ... @@ -263,6 +266,7 @@ jobs:
timeout_seconds: 200
shell: bash
command: |
SHERPA_ONNX_VERSION=$(grep "SHERPA_ONNX_VERSION" ./CMakeLists.txt | cut -d " " -f 2 | cut -d '"' -f 2)
git config --global user.email "csukuangfj@gmail.com"
git config --global user.name "Fangjun Kuang"
du -h -d1 .
... ... @@ -273,7 +277,7 @@ jobs:
GIT_LFS_SKIP_SMUDGE=1 git clone https://csukuangfj:$HF_TOKEN@huggingface.co/csukuangfj/sherpa-onnx-libs huggingface
cd huggingface
dst=android/aar
dst=android/aar/$SHERPA_ONNX_VERSION
mkdir -p $dst
cp -v ../*.aar $dst
... ...
... ... @@ -199,6 +199,7 @@ jobs:
timeout_seconds: 200
shell: bash
command: |
SHERPA_ONNX_VERSION=$(grep "SHERPA_ONNX_VERSION" ./CMakeLists.txt | cut -d " " -f 2 | cut -d '"' -f 2)
git config --global user.email "csukuangfj@gmail.com"
git config --global user.name "Fangjun Kuang"
... ... @@ -206,9 +207,10 @@ jobs:
GIT_LFS_SKIP_SMUDGE=1 git clone https://csukuangfj:$HF_TOKEN@huggingface.co/csukuangfj/sherpa-onnx-libs huggingface
cd huggingface
mkdir -p arm32
dst=arm32/$SHERPA_ONNX_VERSION
mkdir -p $dst
cp -v ../sherpa-onnx-*.tar.bz2 ./arm32
cp -v ../sherpa-onnx-*.tar.bz2 $dst/
git status
git lfs track "*.bz2"
... ...
... ... @@ -83,6 +83,7 @@ jobs:
timeout_seconds: 200
shell: bash
command: |
SHERPA_ONNX_VERSION=$(grep "SHERPA_ONNX_VERSION" ./CMakeLists.txt | cut -d " " -f 2 | cut -d '"' -f 2)
git config --global user.email "csukuangfj@gmail.com"
git config --global user.name "Fangjun Kuang"
... ... @@ -95,9 +96,10 @@ jobs:
cd huggingface
git fetch
git pull
mkdir -p windows-for-dotnet
dst=windows-for-dotnet/$SHERPA_ONNX_VERSION
mkdir -p $dst
cp -v ../sherpa-onnx-*.tar.bz2 ./windows-for-dotnet
cp -v ../sherpa-onnx-*.tar.bz2 $dst/
git status
git lfs track "*.bz2"
... ...
... ... @@ -138,6 +138,7 @@ jobs:
timeout_seconds: 200
shell: bash
command: |
SHERPA_ONNX_VERSION=$(grep "SHERPA_ONNX_VERSION" ./CMakeLists.txt | cut -d " " -f 2 | cut -d '"' -f 2)
git config --global user.email "csukuangfj@gmail.com"
git config --global user.name "Fangjun Kuang"
... ... @@ -146,10 +147,11 @@ jobs:
GIT_LFS_SKIP_SMUDGE=1 git clone https://huggingface.co/csukuangfj/sherpa-onnx-libs huggingface
cd huggingface
mkdir -p jni
dst=jni/$SHERPA_ONNX_VERSION
mkdir -p $dst
cp -v ../sherpa-onnx-*.tar.bz2 ./jni
cp -v ../*.jar ./jni
cp -v ../sherpa-onnx-*.tar.bz2 $dst/
cp -v ../*.jar $dst/
git status
git lfs track "*.bz2"
... ...
... ... @@ -197,6 +197,7 @@ jobs:
timeout_seconds: 200
shell: bash
command: |
SHERPA_ONNX_VERSION=$(grep "SHERPA_ONNX_VERSION" ./CMakeLists.txt | cut -d " " -f 2 | cut -d '"' -f 2)
git config --global user.email "csukuangfj@gmail.com"
git config --global user.name "Fangjun Kuang"
... ... @@ -205,10 +206,11 @@ jobs:
GIT_LFS_SKIP_SMUDGE=1 git clone https://huggingface.co/csukuangfj/sherpa-onnx-libs huggingface
cd huggingface
mkdir -p jni
dst=jni/$SHERPA_ONNX_VERSION
mkdir -p $dst
cp -v ../sherpa-onnx-*.tar.bz2 ./jni
cp -v ../*.jar ./jni
cp -v ../sherpa-onnx-*.tar.bz2 $dst/
cp -v ../*.jar $dst/
git status
git lfs track "*.bz2"
... ...
... ... @@ -113,6 +113,7 @@ jobs:
timeout_seconds: 200
shell: bash
command: |
SHERPA_ONNX_VERSION=$(grep "SHERPA_ONNX_VERSION" ./CMakeLists.txt | cut -d " " -f 2 | cut -d '"' -f 2)
git config --global user.email "csukuangfj@gmail.com"
git config --global user.name "Fangjun Kuang"
... ... @@ -121,9 +122,10 @@ jobs:
GIT_LFS_SKIP_SMUDGE=1 git clone https://huggingface.co/csukuangfj/sherpa-onnx-libs huggingface
cd huggingface
mkdir -p jni
dst=jni/$SHERPA_ONNX_VERSION
mkdir -p $dst
cp -v ../sherpa-onnx-*.tar.bz2 ./jni
cp -v ../sherpa-onnx-*.tar.bz2 $dst
git status
git lfs track "*.bz2"
... ...
... ... @@ -239,6 +239,7 @@ jobs:
timeout_seconds: 200
shell: bash
command: |
SHERPA_ONNX_VERSION=$(grep "SHERPA_ONNX_VERSION" ./CMakeLists.txt | cut -d " " -f 2 | cut -d '"' -f 2)
git config --global user.email "csukuangfj@gmail.com"
git config --global user.name "Fangjun Kuang"
... ... @@ -248,9 +249,10 @@ jobs:
GIT_LFS_SKIP_SMUDGE=1 git clone https://huggingface.co/csukuangfj/sherpa-onnx-libs huggingface
cd huggingface
mkdir -p riscv64
dst=riscv64/$SHERPA_ONNX_VERSION
mkdir -p $dst
cp -v ../sherpa-onnx-*-shared.tar.bz2 ./riscv64
cp -v ../sherpa-onnx-*-shared.tar.bz2 $dst/
git status
git lfs track "*.bz2"
... ...
name: rknn-linux-aarch64
on:
push:
branches:
- master
- rknn-c-api-2
tags:
- 'v[0-9]+.[0-9]+.[0-9]+*'
paths:
- '.github/workflows/rknn-linux-aarch64.yaml'
- 'cmake/**'
- 'sherpa-onnx/csrc/*'
- 'sherpa-onnx/csrc/rknn/*'
- 'sherpa-onnx/c-api/*'
- 'toolchains/aarch64-linux-gnu.toolchain.cmake'
pull_request:
branches:
- master
paths:
- '.github/workflows/rknn-linux-aarch64.yaml'
- 'cmake/**'
- 'sherpa-onnx/csrc/*'
- 'sherpa-onnx/csrc/rknn/*'
- 'sherpa-onnx/c-api/*'
- 'toolchains/aarch64-linux-gnu.toolchain.cmake'
workflow_dispatch:
concurrency:
group: aarch64-linux-gnu-shared-${{ github.ref }}
cancel-in-progress: true
jobs:
rknn_linux_aarch64:
runs-on: ${{ matrix.os }}
name: rknn shared ${{ matrix.shared }}
strategy:
fail-fast: false
matrix:
include:
- os: ubuntu-22.04-arm
shared: ON
- os: ubuntu-22.04-arm
shared: OFF
steps:
- uses: actions/checkout@v4
with:
fetch-depth: 0
- name: ccache
uses: hendrikmuhs/ccache-action@v1.2
with:
key: ${{ matrix.os }}-${{ matrix.shared }}-rknn-linux-aarch64
- name: Download rknn-toolkit2
shell: bash
run: |
git clone --depth 1 https://github.com/airockchip/rknn-toolkit2
- name: Build sherpa-onnx
shell: bash
run: |
export CMAKE_CXX_COMPILER_LAUNCHER=ccache
export PATH="/usr/lib/ccache:/usr/local/opt/ccache/libexec:$PATH"
cmake --version
echo "config: ${{ matrix.config }}"
uname -a
which gcc
gcc --version
g++ --version
echo "pwd"
ls -lh
git clone --depth 1 --branch v1.2.12 https://github.com/alsa-project/alsa-lib
pushd alsa-lib
./gitcompile
popd
export SHERPA_ONNX_RKNN_TOOLKIT2_PATH=$PWD/rknn-toolkit2
export SHERPA_ONNX_RKNN_TOOLKIT2_LIB_DIR=$SHERPA_ONNX_RKNN_TOOLKIT2_PATH/rknpu2/runtime/Linux/librknn_api/aarch64
export CPLUS_INCLUDE_PATH=$SHERPA_ONNX_RKNN_TOOLKIT2_PATH/rknpu2/runtime/Linux/librknn_api/include:$CPLUS_INCLUDE_PATH
export CPLUS_INCLUDE_PATH=$PWD/alsa-lib/include:$CPLUS_INCLUDE_PATH
export SHERPA_ONNX_ALSA_LIB_DIR=$PWD/alsa-lib/src/.libs
mkdir build
cd build
BUILD_SHARED_LIBS=${{ matrix.shared }}
cmake \
-DBUILD_SHARED_LIBS=ON \
-DCMAKE_INSTALL_PREFIX=./install \
-DSHERPA_ONNX_ENABLE_RKNN=ON \
-DBUILD_SHARED_LIBS=$BUILD_SHARED_LIBS \
..
make -j4 install
rm -rf install/lib/pkgconfig
rm -fv install/lib/cargs.h
rm -fv install/lib/libcargs.so
- name: Display system info
shell: bash
run: |
uname -a
gcc --version
g++ --version
- name: Display generated files
shell: bash
run: |
export SHERPA_ONNX_RKNN_TOOLKIT2_PATH=$PWD/rknn-toolkit2
export LD_LIBRARY_PATH=$SHERPA_ONNX_RKNN_TOOLKIT2_PATH/rknpu2/runtime/Linux/librknn_api/aarch64:$LD_LIBRARY_PATH
cd build/install
ls -lh bin
echo "---"
ls -lh lib
file bin/sherpa-onnx
readelf -d bin/sherpa-onnx
ldd bin/sherpa-onnx
./bin/sherpa-onnx --help
- name: Copy files
shell: bash
run: |
SHERPA_ONNX_VERSION=v$(grep "SHERPA_ONNX_VERSION" ./CMakeLists.txt | cut -d " " -f 2 | cut -d '"' -f 2)
if [[ ${{ matrix.shared }} == ON ]]; then
suffix=shared
else
suffix=static
fi
dst=sherpa-onnx-${SHERPA_ONNX_VERSION}-rknn-linux-aarch64-$suffix
mkdir $dst
cp -a build/install/bin $dst/
if [[ ${{ matrix.shared }} == ON ]]; then
cp -v build/install/lib/lib*.so $dst/
fi
ls -lh build/install/lib
ls -lh build/install/bin
ls -lh $dst/bin/
echo "strip"
strip $dst/bin/*
echo "after strip"
ls -lh $dst/bin/
tree $dst
tar cjvf ${dst}.tar.bz2 $dst
- uses: actions/upload-artifact@v4
with:
name: sherpa-onnx-linux-linux-aarch64-shared-${{ matrix.shared }}
path: sherpa-onnx-*linux-aarch64*.tar.bz2
# https://huggingface.co/docs/hub/spaces-github-actions
- name: Publish to huggingface
if: (github.repository_owner == 'csukuangfj' || github.repository_owner == 'k2-fsa') && (github.event_name == 'push' || github.event_name == 'workflow_dispatch')
env:
HF_TOKEN: ${{ secrets.HF_TOKEN }}
uses: nick-fields/retry@v3
with:
max_attempts: 20
timeout_seconds: 200
shell: bash
command: |
SHERPA_ONNX_VERSION=$(grep "SHERPA_ONNX_VERSION" ./CMakeLists.txt | cut -d " " -f 2 | cut -d '"' -f 2)
git config --global user.email "csukuangfj@gmail.com"
git config --global user.name "Fangjun Kuang"
rm -rf huggingface
export GIT_CLONE_PROTECTION_ACTIVE=false
GIT_LFS_SKIP_SMUDGE=1 git clone https://csukuangfj:$HF_TOKEN@huggingface.co/csukuangfj/sherpa-onnx-libs huggingface
cd huggingface
dst=rknn-linux-aarch64/$SHERPA_ONNX_VERSION
mkdir -p $dst
cp -v ../sherpa-onnx-*rknn*-*.tar.bz2 $dst
git status
git lfs track "*.bz2"
git add .
git commit -m "upload sherpa-onnx-${SHERPA_ONNX_VERSION}-rknn-linux-aarch64.tar.bz2"
git push https://csukuangfj:$HF_TOKEN@huggingface.co/csukuangfj/sherpa-onnx-libs main
- name: Release pre-compiled binaries and libs for rknn linux aarch64
if: github.repository_owner == 'k2-fsa' && github.event_name == 'push' && contains(github.ref, 'refs/tags/')
uses: svenstaro/upload-release-action@v2
with:
file_glob: true
overwrite: true
file: sherpa-onnx-*linux-aarch64*.tar.bz2
- name: Release pre-compiled binaries and libs for rknn linux aarch64
# if: github.repository_owner == 'csukuangfj' && github.event_name == 'push' && contains(github.ref, 'refs/tags/')
uses: svenstaro/upload-release-action@v2
with:
file_glob: true
overwrite: true
file: sherpa-onnx-*linux-aarch64*.tar.bz2
repo_name: k2-fsa/sherpa-onnx
repo_token: ${{ secrets.UPLOAD_GH_SHERPA_ONNX_TOKEN }}
tag: v1.10.45
- name: Test offline Moonshine
if: matrix.build_type != 'Debug'
shell: bash
run: |
du -h -d1 .
export PATH=$PWD/build/install/bin:$PATH
export EXE=sherpa-onnx-offline
readelf -d build/bin/sherpa-onnx-offline
.github/scripts/test-offline-moonshine.sh
... ...
... ... @@ -92,6 +92,7 @@ jobs:
timeout_seconds: 200
shell: bash
command: |
SHERPA_ONNX_VERSION=$(grep "SHERPA_ONNX_VERSION" ./CMakeLists.txt | cut -d " " -f 2 | cut -d '"' -f 2)
git config --global user.email "csukuangfj@gmail.com"
git config --global user.name "Fangjun Kuang"
... ... @@ -100,9 +101,10 @@ jobs:
GIT_LFS_SKIP_SMUDGE=1 git clone https://huggingface.co/csukuangfj/sherpa-onnx-libs huggingface
cd huggingface
mkdir -p jni
dst=jni/$SHERPA_ONNX_VERSION
mkdir -p $dst
cp -v ../sherpa-onnx-*.tar.bz2 ./jni
cp -v ../sherpa-onnx-*.tar.bz2 $dst
git status
git lfs track "*.bz2"
... ...
... ... @@ -128,6 +128,7 @@ jobs:
timeout_seconds: 200
shell: bash
command: |
SHERPA_ONNX_VERSION=$(grep "SHERPA_ONNX_VERSION" ./CMakeLists.txt | cut -d " " -f 2 | cut -d '"' -f 2)
git config --global user.email "csukuangfj@gmail.com"
git config --global user.name "Fangjun Kuang"
... ... @@ -136,9 +137,10 @@ jobs:
GIT_LFS_SKIP_SMUDGE=1 git clone https://huggingface.co/csukuangfj/sherpa-onnx-libs huggingface
cd huggingface
mkdir -p win64
dst=win64/$SHERPA_ONNX_VERSION
mkdir -p $dst
cp -v ../sherpa-onnx-*.tar.bz2 ./win64
cp -v ../sherpa-onnx-*.tar.bz2 $dst
git status
git lfs track "*.bz2"
... ...
... ... @@ -131,6 +131,7 @@ jobs:
timeout_seconds: 200
shell: bash
command: |
SHERPA_ONNX_VERSION=$(grep "SHERPA_ONNX_VERSION" ./CMakeLists.txt | cut -d " " -f 2 | cut -d '"' -f 2)
git config --global user.email "csukuangfj@gmail.com"
git config --global user.name "Fangjun Kuang"
... ... @@ -139,7 +140,8 @@ jobs:
GIT_LFS_SKIP_SMUDGE=1 git clone https://huggingface.co/csukuangfj/sherpa-onnx-libs huggingface
cd huggingface
mkdir -p win32
dst=win32/$SHERPA_ONNX_VERSION
mkdir -p $dst
cp -v ../sherpa-onnx-*.tar.bz2 ./win32
... ...
... ... @@ -45,6 +45,7 @@ option(SHERPA_ONNX_LINK_LIBSTDCPP_STATICALLY "True to link libstdc++ statically.
option(SHERPA_ONNX_USE_PRE_INSTALLED_ONNXRUNTIME_IF_AVAILABLE "True to use pre-installed onnxruntime if available" ON)
option(SHERPA_ONNX_ENABLE_SANITIZER "Whether to enable ubsan and asan" OFF)
option(SHERPA_ONNX_BUILD_C_API_EXAMPLES "Whether to enable C API examples" ON)
option(SHERPA_ONNX_ENABLE_RKNN "Whether to build for RKNN NPU " OFF)
set(SHERPA_ONNX_LINUX_ARM64_GPU_ONNXRUNTIME_VERSION "1.11.0" CACHE STRING "Used only for Linux ARM64 GPU. If you use Jetson nano b01, then please set it to 1.11.0. If you use Jetson Orin NX, then set it to 1.16.0.If you use NVIDIA Jetson Orin Nano Engineering Reference Developer Kit
Super - Jetpack 6.2 [L4T 36.4.3], then set it to 1.18.1")
... ... @@ -155,6 +156,7 @@ message(STATUS "SHERPA_ONNX_LINK_LIBSTDCPP_STATICALLY ${SHERPA_ONNX_LINK_LIBSTDC
message(STATUS "SHERPA_ONNX_USE_PRE_INSTALLED_ONNXRUNTIME_IF_AVAILABLE ${SHERPA_ONNX_USE_PRE_INSTALLED_ONNXRUNTIME_IF_AVAILABLE}")
message(STATUS "SHERPA_ONNX_ENABLE_SANITIZER: ${SHERPA_ONNX_ENABLE_SANITIZER}")
message(STATUS "SHERPA_ONNX_BUILD_C_API_EXAMPLES: ${SHERPA_ONNX_BUILD_C_API_EXAMPLES}")
message(STATUS "SHERPA_ONNX_ENABLE_RKNN: ${SHERPA_ONNX_ENABLE_RKNN}")
if(BUILD_SHARED_LIBS OR SHERPA_ONNX_ENABLE_JNI)
set(CMAKE_CXX_VISIBILITY_PRESET hidden)
... ... @@ -199,7 +201,7 @@ if(SHERPA_ONNX_ENABLE_DIRECTML)
message(STATUS "DirectML is enabled")
add_definitions(-DSHERPA_ONNX_ENABLE_DIRECTML=1)
else()
message(WARNING "DirectML is disabled")
message(STATUS "DirectML is disabled")
add_definitions(-DSHERPA_ONNX_ENABLE_DIRECTML=0)
endif()
... ... @@ -267,6 +269,10 @@ message(STATUS "C++ Standard version: ${CMAKE_CXX_STANDARD}")
include(CheckIncludeFileCXX)
if(SHERPA_ONNX_ENABLE_RKNN)
add_definitions(-DSHERPA_ONNX_ENABLE_RKNN=1)
endif()
if(UNIX AND NOT APPLE AND NOT SHERPA_ONNX_ENABLE_WASM AND NOT CMAKE_SYSTEM_NAME STREQUAL Android AND NOT CMAKE_SYSTEM_NAME STREQUAL OHOS)
check_include_file_cxx(alsa/asoundlib.h SHERPA_ONNX_HAS_ALSA)
if(SHERPA_ONNX_HAS_ALSA)
... ...
... ... @@ -74,7 +74,7 @@ if [[ x"$BUILD_SHARED_LIBS" == x"" ]]; then
fi
if [[ x"$SHERPA_ONNX_ENABLE_GPU" == x"" ]]; then
# By default, use CPU
# By default, don't use CPU
SHERPA_ONNX_ENABLE_GPU=OFF
fi
... ...
#!/usr/bin/env bash
set -ex
# Before you run this file, make sure you have first cloned
# https://github.com/airockchip/rknn-toolkit2
# and set the environment variable SHERPA_ONNX_RKNN_TOOLKIT2_PATH
if [ -z $SHERPA_ONNX_RKNN_TOOLKIT2_PATH ]; then
SHERPA_ONNX_RKNN_TOOLKIT2_PATH=/star-fj/fangjun/open-source/rknn-toolkit2
fi
if [ ! -d $SHERPA_ONNX_RKNN_TOOLKIT2_PATH ]; then
echo "Please first clone https://github.com/airockchip/rknn-toolkit2"
echo "You can use"
echo " git clone --depth 1 https://github.com/airockchip/rknn-toolkit2"
echo " export SHERPA_ONNX_RKNN_TOOLKIT2_PATH=$PWD/rknn-toolkit2"
exit 1
fi
if [ ! -f $SHERPA_ONNX_RKNN_TOOLKIT2_PATH/rknpu2/runtime/Linux/librknn_api/include/rknn_api.h ]; then
echo "$SHERPA_ONNX_RKNN_TOOLKIT2_PATH/rknpu2/runtime/Linux/librknn_api/include/rknn_api.h does not exist"
exit 1
fi
if [ ! -f $SHERPA_ONNX_RKNN_TOOLKIT2_PATH/rknpu2/runtime/Linux/librknn_api/aarch64/librknnrt.so ]; then
echo "$SHERPA_ONNX_RKNN_TOOLKIT2_PATH/rknpu2/runtime/Linux/librknn_api/aarch64/librknnrt.so does not exist"
exit 1
fi
export SHERPA_ONNX_RKNN_TOOLKIT2_LIB_DIR=$SHERPA_ONNX_RKNN_TOOLKIT2_PATH/rknpu2/runtime/Linux/librknn_api/aarch64
export CPLUS_INCLUDE_PATH=$SHERPA_ONNX_RKNN_TOOLKIT2_PATH/rknpu2/runtime/Linux/librknn_api/include:$CPLUS_INCLUDE_PATH
if ! command -v aarch64-linux-gnu-gcc &> /dev/null; then
echo "Please install a toolchain for cross-compiling."
echo "You can refer to: "
echo " https://k2-fsa.github.io/sherpa/onnx/install/rknn-linux-aarch64.html"
echo "for help."
exit 1
fi
dir=$PWD/build-rknn-linux-aarch64
mkdir -p $dir
cd $dir
if [ ! -f alsa-lib/src/.libs/libasound.so ]; then
echo "Start to cross-compile alsa-lib"
if [ ! -d alsa-lib ]; then
git clone --depth 1 --branch v1.2.12 https://github.com/alsa-project/alsa-lib
fi
# If it shows:
# ./gitcompile: line 79: libtoolize: command not found
# Please use:
# sudo apt-get install libtool m4 automake
#
pushd alsa-lib
CC=aarch64-linux-gnu-gcc ./gitcompile --host=aarch64-linux-gnu
popd
echo "Finish cross-compiling alsa-lib"
fi
export CPLUS_INCLUDE_PATH=$PWD/alsa-lib/include:$CPLUS_INCLUDE_PATH
export SHERPA_ONNX_ALSA_LIB_DIR=$PWD/alsa-lib/src/.libs
if [[ x"$BUILD_SHARED_LIBS" == x"" ]]; then
# By default, use shared link
BUILD_SHARED_LIBS=ON
fi
cmake \
-DBUILD_PIPER_PHONMIZE_EXE=OFF \
-DBUILD_PIPER_PHONMIZE_TESTS=OFF \
-DBUILD_ESPEAK_NG_EXE=OFF \
-DBUILD_ESPEAK_NG_TESTS=OFF \
-DCMAKE_INSTALL_PREFIX=./install \
-DCMAKE_BUILD_TYPE=Release \
-DSHERPA_ONNX_ENABLE_GPU=OFF \
-DBUILD_SHARED_LIBS=$BUILD_SHARED_LIBS \
-DSHERPA_ONNX_ENABLE_TESTS=OFF \
-DSHERPA_ONNX_ENABLE_PYTHON=OFF \
-DSHERPA_ONNX_ENABLE_CHECK=OFF \
-DSHERPA_ONNX_ENABLE_PORTAUDIO=OFF \
-DSHERPA_ONNX_ENABLE_JNI=OFF \
-DSHERPA_ONNX_ENABLE_C_API=ON \
-DSHERPA_ONNX_ENABLE_WEBSOCKET=ON \
-DSHERPA_ONNX_ENABLE_RKNN=ON \
-DCMAKE_TOOLCHAIN_FILE=../toolchains/aarch64-linux-gnu.toolchain.cmake \
..
make VERBOSE=1 -j4
make install/strip
# Enable it if only needed
# cp -v $SHERPA_ONNX_ALSA_LIB_DIR/libasound.so* ./install/lib/
# See also
# https://github.com/airockchip/rknn-toolkit2/blob/master/rknpu2/examples/rknn_api_demo/build-linux.sh
... ...
... ... @@ -150,7 +150,7 @@ if [ ! -f $src_dir/windows-x86/sherpa-onnx-c-api.dll ]; then
if [ -f $windows_x86_wheel ]; then
cp -v $windows_x86_wheel .
else
curl -OL https://$HF_MIRROR/csukuangfj/sherpa-onnx-libs/resolve/main/windows-for-dotnet/$windows_x86_wheel_filename
curl -OL https://$HF_MIRROR/csukuangfj/sherpa-onnx-libs/resolve/main/windows-for-dotnet/$SHERPA_ONNX_VERSION/$windows_x86_wheel_filename
fi
tar xvf $windows_x86_wheel_filename
cp -v sherpa-onnx-${SHERPA_ONNX_VERSION}-win-x86/*dll ../
... ... @@ -169,7 +169,7 @@ if [ ! -f $src_dir/windows-arm64/sherpa-onnx-c-api.dll ]; then
if [ -f $windows_arm64_wheel ]; then
cp -v $windows_arm64_wheel .
else
curl -OL https://$HF_MIRROR/csukuangfj/sherpa-onnx-libs/resolve/main/windows-for-dotnet/$windows_arm64_wheel_filename
curl -OL https://$HF_MIRROR/csukuangfj/sherpa-onnx-libs/resolve/main/windows-for-dotnet/$SHERPA_ONNX_VERSION/$windows_arm64_wheel_filename
fi
tar xvf $windows_arm64_wheel_filename
cp -v sherpa-onnx-${SHERPA_ONNX_VERSION}-win-arm64/*dll ../
... ...
... ... @@ -151,6 +151,14 @@ list(APPEND sources
online-punctuation-model-config.cc
online-punctuation.cc
)
if(SHERPA_ONNX_ENABLE_RKNN)
list(APPEND sources
./rknn/online-stream-rknn.cc
./rknn/online-transducer-greedy-search-decoder-rknn.cc
./rknn/online-zipformer-transducer-model-rknn.cc
)
endif()
if(SHERPA_ONNX_ENABLE_TTS)
list(APPEND sources
... ... @@ -230,6 +238,14 @@ if(SHERPA_ONNX_ENABLE_GPU)
)
endif()
if(SHERPA_ONNX_ENABLE_RKNN)
if(DEFINED ENV{SHERPA_ONNX_RKNN_TOOLKIT2_LIB_DIR})
target_link_libraries(sherpa-onnx-core -L$ENV{SHERPA_ONNX_RKNN_TOOLKIT2_LIB_DIR} -lrknnrt)
else()
target_link_libraries(sherpa-onnx-core rknnrt)
endif()
endif()
if(BUILD_SHARED_LIBS AND NOT DEFINED onnxruntime_lib_files)
target_link_libraries(sherpa-onnx-core onnxruntime)
else()
... ...
... ... @@ -5,6 +5,7 @@
#include "sherpa-onnx/csrc/file-utils.h"
#include <fstream>
#include <memory>
#include <string>
#include "sherpa-onnx/csrc/macros.h"
... ... @@ -22,4 +23,61 @@ void AssertFileExists(const std::string &filename) {
}
}
std::vector<char> ReadFile(const std::string &filename) {
std::ifstream input(filename, std::ios::binary);
std::vector<char> buffer(std::istreambuf_iterator<char>(input), {});
return buffer;
}
#if __ANDROID_API__ >= 9
std::vector<char> ReadFile(AAssetManager *mgr, const std::string &filename) {
AAsset *asset = AAssetManager_open(mgr, filename.c_str(), AASSET_MODE_BUFFER);
if (!asset) {
__android_log_print(ANDROID_LOG_FATAL, "sherpa-onnx",
"Read binary file: Load %s failed", filename.c_str());
exit(-1);
}
auto p = reinterpret_cast<const char *>(AAsset_getBuffer(asset));
size_t asset_length = AAsset_getLength(asset);
std::vector<char> buffer(p, p + asset_length);
AAsset_close(asset);
return buffer;
}
#endif
#if __OHOS__
std::vector<char> ReadFile(NativeResourceManager *mgr,
const std::string &filename) {
std::unique_ptr<RawFile, decltype(&OH_ResourceManager_CloseRawFile)> fp(
OH_ResourceManager_OpenRawFile(mgr, filename.c_str()),
OH_ResourceManager_CloseRawFile);
if (!fp) {
std::ostringstream os;
os << "Read file '" << filename << "' failed.";
SHERPA_ONNX_LOGE("%s", os.str().c_str());
return {};
}
auto len = static_cast<int32_t>(OH_ResourceManager_GetRawFileSize(fp.get()));
std::vector<char> buffer(len);
int32_t n = OH_ResourceManager_ReadRawFile(fp.get(), buffer.data(), len);
if (n != len) {
std::ostringstream os;
os << "Read file '" << filename << "' failed. Number of bytes read: " << n
<< ". Expected bytes to read: " << len;
SHERPA_ONNX_LOGE("%s", os.str().c_str());
return {};
}
return buffer;
}
#endif
} // namespace sherpa_onnx
... ...
... ... @@ -7,6 +7,16 @@
#include <fstream>
#include <string>
#include <vector>
#if __ANDROID_API__ >= 9
#include "android/asset_manager.h"
#include "android/asset_manager_jni.h"
#endif
#if __OHOS__
#include "rawfile/raw_file_manager.h"
#endif
namespace sherpa_onnx {
... ... @@ -23,6 +33,17 @@ bool FileExists(const std::string &filename);
*/
void AssertFileExists(const std::string &filename);
std::vector<char> ReadFile(const std::string &filename);
#if __ANDROID_API__ >= 9
std::vector<char> ReadFile(AAssetManager *mgr, const std::string &filename);
#endif
#if __OHOS__
std::vector<char> ReadFile(NativeResourceManager *mgr,
const std::string &filename);
#endif
} // namespace sherpa_onnx
#endif // SHERPA_ONNX_CSRC_FILE_UTILS_H_
... ...
... ... @@ -17,6 +17,7 @@
#include "rawfile/raw_file_manager.h"
#endif
#include "sherpa-onnx/csrc/file-utils.h"
#include "sherpa-onnx/csrc/macros.h"
#include "sherpa-onnx/csrc/onnx-utils.h"
#include "sherpa-onnx/csrc/session.h"
... ...
... ... @@ -7,6 +7,7 @@
#include <string>
#include <vector>
#include "sherpa-onnx/csrc/file-utils.h"
#include "sherpa-onnx/csrc/onnx-utils.h"
#include "sherpa-onnx/csrc/session.h"
#include "sherpa-onnx/csrc/text-utils.h"
... ...
... ... @@ -7,6 +7,7 @@
#include <string>
#include <vector>
#include "sherpa-onnx/csrc/file-utils.h"
#include "sherpa-onnx/csrc/onnx-utils.h"
#include "sherpa-onnx/csrc/session.h"
#include "sherpa-onnx/csrc/text-utils.h"
... ...
... ... @@ -18,6 +18,7 @@
#include "rawfile/raw_file_manager.h"
#endif
#include "sherpa-onnx/csrc/file-utils.h"
#include "sherpa-onnx/csrc/macros.h"
#include "sherpa-onnx/csrc/offline-nemo-enc-dec-ctc-model.h"
#include "sherpa-onnx/csrc/offline-tdnn-ctc-model.h"
... ...
... ... @@ -20,6 +20,7 @@
#include "rawfile/raw_file_manager.h"
#endif
#include "sherpa-onnx/csrc/file-utils.h"
#include "sherpa-onnx/csrc/macros.h"
#include "sherpa-onnx/csrc/onnx-utils.h"
#include "sherpa-onnx/csrc/session.h"
... ...
... ... @@ -17,6 +17,7 @@
#include "rawfile/raw_file_manager.h"
#endif
#include "sherpa-onnx/csrc/file-utils.h"
#include "sherpa-onnx/csrc/macros.h"
#include "sherpa-onnx/csrc/onnx-utils.h"
#include "sherpa-onnx/csrc/session.h"
... ...
... ... @@ -13,6 +13,7 @@
#include "rawfile/raw_file_manager.h"
#endif
#include "sherpa-onnx/csrc/file-utils.h"
#include "sherpa-onnx/csrc/macros.h"
#include "sherpa-onnx/csrc/onnx-utils.h"
#include "sherpa-onnx/csrc/session.h"
... ...
... ... @@ -17,6 +17,7 @@
#include "rawfile/raw_file_manager.h"
#endif
#include "sherpa-onnx/csrc/file-utils.h"
#include "sherpa-onnx/csrc/macros.h"
#include "sherpa-onnx/csrc/onnx-utils.h"
#include "sherpa-onnx/csrc/session.h"
... ...
... ... @@ -22,6 +22,7 @@
#include "fst/extensions/far/far.h"
#include "kaldifst/csrc/kaldi-fst-io.h"
#include "onnxruntime_cxx_api.h" // NOLINT
#include "sherpa-onnx/csrc/file-utils.h"
#include "sherpa-onnx/csrc/macros.h"
#include "sherpa-onnx/csrc/offline-recognizer-ctc-impl.h"
#include "sherpa-onnx/csrc/offline-recognizer-fire-red-asr-impl.h"
... ... @@ -31,7 +32,6 @@
#include "sherpa-onnx/csrc/offline-recognizer-transducer-impl.h"
#include "sherpa-onnx/csrc/offline-recognizer-transducer-nemo-impl.h"
#include "sherpa-onnx/csrc/offline-recognizer-whisper-impl.h"
#include "sherpa-onnx/csrc/onnx-utils.h"
#include "sherpa-onnx/csrc/text-utils.h"
namespace sherpa_onnx {
... ...
... ... @@ -18,6 +18,7 @@
#endif
#include "onnxruntime_cxx_api.h" // NOLINT
#include "sherpa-onnx/csrc/file-utils.h"
#include "sherpa-onnx/csrc/macros.h"
#include "sherpa-onnx/csrc/onnx-utils.h"
#include "sherpa-onnx/csrc/session.h"
... ...
... ... @@ -17,6 +17,7 @@
#include "rawfile/raw_file_manager.h"
#endif
#include "sherpa-onnx/csrc/file-utils.h"
#include "sherpa-onnx/csrc/macros.h"
#include "sherpa-onnx/csrc/onnx-utils.h"
#include "sherpa-onnx/csrc/session.h"
... ...
... ... @@ -17,6 +17,7 @@
#include "rawfile/raw_file_manager.h"
#endif
#include "sherpa-onnx/csrc/file-utils.h"
#include "sherpa-onnx/csrc/onnx-utils.h"
#include "sherpa-onnx/csrc/session.h"
... ...
... ... @@ -15,6 +15,7 @@
#include "rawfile/raw_file_manager.h"
#endif
#include "sherpa-onnx/csrc/file-utils.h"
#include "sherpa-onnx/csrc/macros.h"
#include "sherpa-onnx/csrc/onnx-utils.h"
#include "sherpa-onnx/csrc/session.h"
... ...
... ... @@ -13,6 +13,7 @@
#include "rawfile/raw_file_manager.h"
#endif
#include "sherpa-onnx/csrc/file-utils.h"
#include "sherpa-onnx/csrc/macros.h"
#include "sherpa-onnx/csrc/onnx-utils.h"
#include "sherpa-onnx/csrc/session.h"
... ...
... ... @@ -17,6 +17,7 @@
#include "rawfile/raw_file_manager.h"
#endif
#include "sherpa-onnx/csrc/file-utils.h"
#include "sherpa-onnx/csrc/macros.h"
#include "sherpa-onnx/csrc/offline-transducer-decoder.h"
#include "sherpa-onnx/csrc/onnx-utils.h"
... ...
... ... @@ -18,6 +18,7 @@
#include "rawfile/raw_file_manager.h"
#endif
#include "sherpa-onnx/csrc/file-utils.h"
#include "sherpa-onnx/csrc/macros.h"
#include "sherpa-onnx/csrc/offline-transducer-decoder.h"
#include "sherpa-onnx/csrc/onnx-utils.h"
... ...
... ... @@ -18,6 +18,7 @@
#include "rawfile/raw_file_manager.h"
#endif
#include "sherpa-onnx/csrc/file-utils.h"
#include "sherpa-onnx/csrc/macros.h"
#include "sherpa-onnx/csrc/onnx-utils.h"
#include "sherpa-onnx/csrc/session.h"
... ...
... ... @@ -18,6 +18,7 @@
#include "rawfile/raw_file_manager.h"
#endif
#include "sherpa-onnx/csrc/file-utils.h"
#include "sherpa-onnx/csrc/macros.h"
#include "sherpa-onnx/csrc/onnx-utils.h"
#include "sherpa-onnx/csrc/session.h"
... ...
... ... @@ -18,6 +18,7 @@
#include "rawfile/raw_file_manager.h"
#endif
#include "sherpa-onnx/csrc/file-utils.h"
#include "sherpa-onnx/csrc/macros.h"
#include "sherpa-onnx/csrc/onnx-utils.h"
#include "sherpa-onnx/csrc/session.h"
... ...
... ... @@ -13,6 +13,7 @@
#include "rawfile/raw_file_manager.h"
#endif
#include "sherpa-onnx/csrc/file-utils.h"
#include "sherpa-onnx/csrc/macros.h"
#include "sherpa-onnx/csrc/onnx-utils.h"
#include "sherpa-onnx/csrc/session.h"
... ...
... ... @@ -20,6 +20,7 @@
#include "rawfile/raw_file_manager.h"
#endif
#include "sherpa-onnx/csrc/file-utils.h"
#include "sherpa-onnx/csrc/macros.h"
#include "sherpa-onnx/csrc/onnx-utils.h"
#include "sherpa-onnx/csrc/session.h"
... ...
... ... @@ -7,6 +7,7 @@
#include <string>
#include <vector>
#include "sherpa-onnx/csrc/file-utils.h"
#include "sherpa-onnx/csrc/onnx-utils.h"
#include "sherpa-onnx/csrc/session.h"
#include "sherpa-onnx/csrc/text-utils.h"
... ...
... ... @@ -15,6 +15,7 @@
#include "rawfile/raw_file_manager.h"
#endif
#include "sherpa-onnx/csrc/file-utils.h"
#include "sherpa-onnx/csrc/macros.h"
#include "sherpa-onnx/csrc/onnx-utils.h"
#include "sherpa-onnx/csrc/session.h"
... ...
... ... @@ -7,6 +7,7 @@
#include <string>
#include <vector>
#include "sherpa-onnx/csrc/file-utils.h"
#include "sherpa-onnx/csrc/onnx-utils.h"
#include "sherpa-onnx/csrc/session.h"
#include "sherpa-onnx/csrc/text-utils.h"
... ...
... ... @@ -23,6 +23,7 @@
#include "onnxruntime_cxx_api.h" // NOLINT
#include "sherpa-onnx/csrc/cat.h"
#include "sherpa-onnx/csrc/file-utils.h"
#include "sherpa-onnx/csrc/macros.h"
#include "sherpa-onnx/csrc/online-transducer-decoder.h"
#include "sherpa-onnx/csrc/onnx-utils.h"
... ...
... ... @@ -22,6 +22,7 @@
#include "onnxruntime_cxx_api.h" // NOLINT
#include "sherpa-onnx/csrc/cat.h"
#include "sherpa-onnx/csrc/file-utils.h"
#include "sherpa-onnx/csrc/macros.h"
#include "sherpa-onnx/csrc/online-transducer-decoder.h"
#include "sherpa-onnx/csrc/onnx-utils.h"
... ...
... ... @@ -51,10 +51,21 @@ void OnlineModelConfig::Register(ParseOptions *po) {
}
bool OnlineModelConfig::Validate() const {
// For RK NPU, we reinterpret num_threads:
//
// For RK3588 only
// num_threads == 1 -> Select a core randomly
// num_threads == 0 -> Use NPU core 0
// num_threads == -1 -> Use NPU core 1
// num_threads == -2 -> Use NPU core 2
// num_threads == -3 -> Use NPU core 0 and core 1
// num_threads == -4 -> Use NPU core 0, core 1, and core 2
if (provider_config.provider != "rknn") {
if (num_threads < 1) {
SHERPA_ONNX_LOGE("num_threads should be > 0. Given %d", num_threads);
return false;
}
}
if (!tokens_buf.empty() && FileExists(tokens)) {
SHERPA_ONNX_LOGE(
... ...
... ... @@ -18,6 +18,7 @@
#endif
#include "sherpa-onnx/csrc/cat.h"
#include "sherpa-onnx/csrc/file-utils.h"
#include "sherpa-onnx/csrc/macros.h"
#include "sherpa-onnx/csrc/onnx-utils.h"
#include "sherpa-onnx/csrc/session.h"
... ...
... ... @@ -17,6 +17,7 @@
#include "rawfile/raw_file_manager.h"
#endif
#include "sherpa-onnx/csrc/file-utils.h"
#include "sherpa-onnx/csrc/macros.h"
#include "sherpa-onnx/csrc/onnx-utils.h"
#include "sherpa-onnx/csrc/session.h"
... ...
// sherpa-onnx/csrc/online-recognizer-impl.cc
//
// Copyright (c) 2023 Xiaomi Corporation
// Copyright (c) 2023-2025 Xiaomi Corporation
#include "sherpa-onnx/csrc/online-recognizer-impl.h"
... ... @@ -26,10 +26,31 @@
#include "sherpa-onnx/csrc/onnx-utils.h"
#include "sherpa-onnx/csrc/text-utils.h"
#if SHERPA_ONNX_ENABLE_RKNN
#include "sherpa-onnx/csrc/rknn/online-recognizer-transducer-rknn-impl.h"
#endif
namespace sherpa_onnx {
std::unique_ptr<OnlineRecognizerImpl> OnlineRecognizerImpl::Create(
const OnlineRecognizerConfig &config) {
if (config.model_config.provider_config.provider == "rknn") {
#if SHERPA_ONNX_ENABLE_RKNN
// Currently, only zipformer v1 is suported for rknn
if (config.model_config.transducer.encoder.empty()) {
SHERPA_ONNX_LOGE(
"Only Zipformer transducers are currently supported by rknn. "
"Fallback to CPU");
} else {
return std::make_unique<OnlineRecognizerTransducerRknnImpl>(config);
}
#else
SHERPA_ONNX_LOGE(
"Please rebuild sherpa-onnx with -DSHERPA_ONNX_ENABLE_RKNN=ON if you "
"want to use rknn. Fallback to CPU");
#endif
}
if (!config.model_config.transducer.encoder.empty()) {
Ort::Env env(ORT_LOGGING_LEVEL_ERROR);
... ...
... ... @@ -11,6 +11,7 @@
#include <vector>
#include "onnxruntime_cxx_api.h" // NOLINT
#include "sherpa-onnx/csrc/file-utils.h"
#include "sherpa-onnx/csrc/macros.h"
#include "sherpa-onnx/csrc/onnx-utils.h"
#include "sherpa-onnx/csrc/session.h"
... ...
... ... @@ -23,7 +23,8 @@ class OnlineStream {
public:
explicit OnlineStream(const FeatureExtractorConfig &config = {},
ContextGraphPtr context_graph = nullptr);
~OnlineStream();
virtual ~OnlineStream();
/**
@param sampling_rate The sampling_rate of the input waveform. If it does
... ...
... ... @@ -18,6 +18,7 @@
#include <sstream>
#include <string>
#include "sherpa-onnx/csrc/file-utils.h"
#include "sherpa-onnx/csrc/macros.h"
#include "sherpa-onnx/csrc/online-conformer-transducer-model.h"
#include "sherpa-onnx/csrc/online-lstm-transducer-model.h"
... ...
... ... @@ -25,6 +25,7 @@
#endif
#include "sherpa-onnx/csrc/cat.h"
#include "sherpa-onnx/csrc/file-utils.h"
#include "sherpa-onnx/csrc/macros.h"
#include "sherpa-onnx/csrc/online-transducer-decoder.h"
#include "sherpa-onnx/csrc/onnx-utils.h"
... ...
... ... @@ -17,6 +17,7 @@
#include "rawfile/raw_file_manager.h"
#endif
#include "sherpa-onnx/csrc/file-utils.h"
#include "sherpa-onnx/csrc/macros.h"
#include "sherpa-onnx/csrc/onnx-utils.h"
#include "sherpa-onnx/csrc/session.h"
... ...
... ... @@ -23,6 +23,7 @@
#include "onnxruntime_cxx_api.h" // NOLINT
#include "sherpa-onnx/csrc/cat.h"
#include "sherpa-onnx/csrc/file-utils.h"
#include "sherpa-onnx/csrc/macros.h"
#include "sherpa-onnx/csrc/online-transducer-decoder.h"
#include "sherpa-onnx/csrc/onnx-utils.h"
... ...
... ... @@ -20,6 +20,7 @@
#endif
#include "sherpa-onnx/csrc/cat.h"
#include "sherpa-onnx/csrc/file-utils.h"
#include "sherpa-onnx/csrc/macros.h"
#include "sherpa-onnx/csrc/onnx-utils.h"
#include "sherpa-onnx/csrc/session.h"
... ...
... ... @@ -25,6 +25,7 @@
#include "onnxruntime_cxx_api.h" // NOLINT
#include "sherpa-onnx/csrc/cat.h"
#include "sherpa-onnx/csrc/file-utils.h"
#include "sherpa-onnx/csrc/macros.h"
#include "sherpa-onnx/csrc/online-transducer-decoder.h"
#include "sherpa-onnx/csrc/onnx-utils.h"
... ...
... ... @@ -13,15 +13,8 @@
#include <string>
#include <vector>
#include "sherpa-onnx/csrc/macros.h"
#if __ANDROID_API__ >= 9
#include "android/asset_manager.h"
#include "android/asset_manager_jni.h"
#include "android/log.h"
#endif
#include "onnxruntime_cxx_api.h" // NOLINT
#include "sherpa-onnx/csrc/macros.h"
namespace sherpa_onnx {
... ... @@ -305,63 +298,6 @@ void Print4D(const Ort::Value *v) {
fprintf(stderr, "\n");
}
std::vector<char> ReadFile(const std::string &filename) {
std::ifstream input(filename, std::ios::binary);
std::vector<char> buffer(std::istreambuf_iterator<char>(input), {});
return buffer;
}
#if __ANDROID_API__ >= 9
std::vector<char> ReadFile(AAssetManager *mgr, const std::string &filename) {
AAsset *asset = AAssetManager_open(mgr, filename.c_str(), AASSET_MODE_BUFFER);
if (!asset) {
__android_log_print(ANDROID_LOG_FATAL, "sherpa-onnx",
"Read binary file: Load %s failed", filename.c_str());
exit(-1);
}
auto p = reinterpret_cast<const char *>(AAsset_getBuffer(asset));
size_t asset_length = AAsset_getLength(asset);
std::vector<char> buffer(p, p + asset_length);
AAsset_close(asset);
return buffer;
}
#endif
#if __OHOS__
std::vector<char> ReadFile(NativeResourceManager *mgr,
const std::string &filename) {
std::unique_ptr<RawFile, decltype(&OH_ResourceManager_CloseRawFile)> fp(
OH_ResourceManager_OpenRawFile(mgr, filename.c_str()),
OH_ResourceManager_CloseRawFile);
if (!fp) {
std::ostringstream os;
os << "Read file '" << filename << "' failed.";
SHERPA_ONNX_LOGE("%s", os.str().c_str());
return {};
}
auto len = static_cast<int32_t>(OH_ResourceManager_GetRawFileSize(fp.get()));
std::vector<char> buffer(len);
int32_t n = OH_ResourceManager_ReadRawFile(fp.get(), buffer.data(), len);
if (n != len) {
std::ostringstream os;
os << "Read file '" << filename << "' failed. Number of bytes read: " << n
<< ". Expected bytes to read: " << len;
SHERPA_ONNX_LOGE("%s", os.str().c_str());
return {};
}
return buffer;
}
#endif
Ort::Value Repeat(OrtAllocator *allocator, Ort::Value *cur_encoder_out,
const std::vector<int32_t> &hyps_num_split) {
std::vector<int64_t> cur_encoder_out_shape =
... ...
... ... @@ -17,15 +17,6 @@
#include <utility>
#include <vector>
#if __ANDROID_API__ >= 9
#include "android/asset_manager.h"
#include "android/asset_manager_jni.h"
#endif
#if __OHOS__
#include "rawfile/raw_file_manager.h"
#endif
#include "onnxruntime_cxx_api.h" // NOLINT
namespace sherpa_onnx {
... ... @@ -101,17 +92,6 @@ void Fill(Ort::Value *tensor, T value) {
std::fill(p, p + n, value);
}
std::vector<char> ReadFile(const std::string &filename);
#if __ANDROID_API__ >= 9
std::vector<char> ReadFile(AAssetManager *mgr, const std::string &filename);
#endif
#if __OHOS__
std::vector<char> ReadFile(NativeResourceManager *mgr,
const std::string &filename);
#endif
// TODO(fangjun): Document it
Ort::Value Repeat(OrtAllocator *allocator, Ort::Value *cur_encoder_out,
const std::vector<int32_t> &hyps_num_split);
... ...
// sherpa-onnx/csrc/macros.h
//
// Copyright 2025 Xiaomi Corporation
#ifndef SHERPA_ONNX_CSRC_RKNN_MACROS_H_
#define SHERPA_ONNX_CSRC_RKNN_MACROS_H_
#include "sherpa-onnx/csrc/macros.h"
#define SHERPA_ONNX_RKNN_CHECK(ret, msg, ...) \
do { \
if (ret != RKNN_SUCC) { \
SHERPA_ONNX_LOGE("Return code is: %d", ret); \
SHERPA_ONNX_LOGE(msg, ##__VA_ARGS__); \
SHERPA_ONNX_EXIT(-1); \
} \
} while (0)
#endif // SHERPA_ONNX_CSRC_RKNN_MACROS_H_
... ...
// sherpa-onnx/csrc/rknn/online-recognizer-transducer-rknn-impl.h
//
// Copyright (c) 2025 Xiaomi Corporation
#ifndef SHERPA_ONNX_CSRC_RKNN_ONLINE_RECOGNIZER_TRANSDUCER_RKNN_IMPL_H_
#define SHERPA_ONNX_CSRC_RKNN_ONLINE_RECOGNIZER_TRANSDUCER_RKNN_IMPL_H_
#include <algorithm>
#include <memory>
#include <sstream>
#include <string>
#include <utility>
#include <vector>
#include "sherpa-onnx/csrc/macros.h"
#include "sherpa-onnx/csrc/online-recognizer-impl.h"
#include "sherpa-onnx/csrc/online-recognizer.h"
#include "sherpa-onnx/csrc/rknn/online-stream-rknn.h"
#include "sherpa-onnx/csrc/rknn/online-transducer-greedy-search-decoder-rknn.h"
#include "sherpa-onnx/csrc/rknn/online-zipformer-transducer-model-rknn.h"
#include "sherpa-onnx/csrc/symbol-table.h"
namespace sherpa_onnx {
OnlineRecognizerResult Convert(const OnlineTransducerDecoderResultRknn &src,
const SymbolTable &sym_table,
float frame_shift_ms, int32_t subsampling_factor,
int32_t segment, int32_t frames_since_start) {
OnlineRecognizerResult r;
r.tokens.reserve(src.tokens.size());
r.timestamps.reserve(src.tokens.size());
std::string text;
for (auto i : src.tokens) {
auto sym = sym_table[i];
text.append(sym);
if (sym.size() == 1 && (sym[0] < 0x20 || sym[0] > 0x7e)) {
// for bpe models with byte_fallback
// (but don't rewrite printable characters 0x20..0x7e,
// which collide with standard BPE units)
std::ostringstream os;
os << "<0x" << std::hex << std::uppercase
<< (static_cast<int32_t>(sym[0]) & 0xff) << ">";
sym = os.str();
}
r.tokens.push_back(std::move(sym));
}
if (sym_table.IsByteBpe()) {
text = sym_table.DecodeByteBpe(text);
}
r.text = std::move(text);
float frame_shift_s = frame_shift_ms / 1000. * subsampling_factor;
for (auto t : src.timestamps) {
float time = frame_shift_s * t;
r.timestamps.push_back(time);
}
r.segment = segment;
r.start_time = frames_since_start * frame_shift_ms / 1000.;
return r;
}
class OnlineRecognizerTransducerRknnImpl : public OnlineRecognizerImpl {
public:
explicit OnlineRecognizerTransducerRknnImpl(
const OnlineRecognizerConfig &config)
: OnlineRecognizerImpl(config),
config_(config),
endpoint_(config_.endpoint_config),
model_(std::make_unique<OnlineZipformerTransducerModelRknn>(
config.model_config)) {
if (!config.model_config.tokens_buf.empty()) {
sym_ = SymbolTable(config.model_config.tokens_buf, false);
} else {
/// assuming tokens_buf and tokens are guaranteed not being both empty
sym_ = SymbolTable(config.model_config.tokens, true);
}
if (sym_.Contains("<unk>")) {
unk_id_ = sym_["<unk>"];
}
decoder_ = std::make_unique<OnlineTransducerGreedySearchDecoderRknn>(
model_.get(), unk_id_);
}
template <typename Manager>
explicit OnlineRecognizerTransducerRknnImpl(
Manager *mgr, const OnlineRecognizerConfig &config)
: OnlineRecognizerImpl(mgr, config),
config_(config),
endpoint_(config_.endpoint_config),
model_(
std::make_unique<OnlineZipformerTransducerModelRknn>(mgr, config)) {
// TODO(fangjun): Support Android
}
std::unique_ptr<OnlineStream> CreateStream() const override {
auto stream = std::make_unique<OnlineStreamRknn>(config_.feat_config);
auto r = decoder_->GetEmptyResult();
stream->SetZipformerResult(std::move(r));
stream->SetZipformerEncoderStates(model_->GetEncoderInitStates());
return stream;
}
std::unique_ptr<OnlineStream> CreateStream(
const std::string &hotwords) const override {
SHERPA_ONNX_LOGE("Hotwords for RKNN is not supported now.");
return CreateStream();
}
bool IsReady(OnlineStream *s) const override {
return s->GetNumProcessedFrames() + model_->ChunkSize() <
s->NumFramesReady();
}
// Warmping up engine with wp: warm_up count and max-batch-size
void DecodeStreams(OnlineStream **ss, int32_t n) const override {
for (int32_t i = 0; i < n; ++i) {
DecodeStream(reinterpret_cast<OnlineStreamRknn *>(ss[i]));
}
}
OnlineRecognizerResult GetResult(OnlineStream *s) const override {
OnlineTransducerDecoderResultRknn decoder_result =
reinterpret_cast<OnlineStreamRknn *>(s)->GetZipformerResult();
decoder_->StripLeadingBlanks(&decoder_result);
// TODO(fangjun): Remember to change these constants if needed
int32_t frame_shift_ms = 10;
int32_t subsampling_factor = 4;
auto r = Convert(decoder_result, sym_, frame_shift_ms, subsampling_factor,
s->GetCurrentSegment(), s->GetNumFramesSinceStart());
r.text = ApplyInverseTextNormalization(std::move(r.text));
return r;
}
bool IsEndpoint(OnlineStream *s) const override {
if (!config_.enable_endpoint) {
return false;
}
int32_t num_processed_frames = s->GetNumProcessedFrames();
// frame shift is 10 milliseconds
float frame_shift_in_seconds = 0.01;
// subsampling factor is 4
int32_t trailing_silence_frames = reinterpret_cast<OnlineStreamRknn *>(s)
->GetZipformerResult()
.num_trailing_blanks *
4;
return endpoint_.IsEndpoint(num_processed_frames, trailing_silence_frames,
frame_shift_in_seconds);
}
void Reset(OnlineStream *s) const override {
int32_t context_size = model_->ContextSize();
{
// segment is incremented only when the last
// result is not empty, contains non-blanks and longer than context_size)
const auto &r =
reinterpret_cast<OnlineStreamRknn *>(s)->GetZipformerResult();
if (!r.tokens.empty() && r.tokens.back() != 0 &&
r.tokens.size() > context_size) {
s->GetCurrentSegment() += 1;
}
}
// reset encoder states
// reinterpret_cast<OnlineStreamRknn*>(s)->SetZipformerEncoderStates(model_->GetEncoderInitStates());
auto r = decoder_->GetEmptyResult();
auto last_result =
reinterpret_cast<OnlineStreamRknn *>(s)->GetZipformerResult();
// if last result is not empty, then
// preserve last tokens as the context for next result
if (static_cast<int32_t>(last_result.tokens.size()) > context_size) {
r.tokens = {last_result.tokens.end() - context_size,
last_result.tokens.end()};
}
reinterpret_cast<OnlineStreamRknn *>(s)->SetZipformerResult(std::move(r));
// Note: We only update counters. The underlying audio samples
// are not discarded.
s->Reset();
}
private:
void DecodeStream(OnlineStreamRknn *s) const {
int32_t chunk_size = model_->ChunkSize();
int32_t chunk_shift = model_->ChunkShift();
int32_t feature_dim = s->FeatureDim();
const auto num_processed_frames = s->GetNumProcessedFrames();
std::vector<float> features =
s->GetFrames(num_processed_frames, chunk_size);
s->GetNumProcessedFrames() += chunk_shift;
auto &states = s->GetZipformerEncoderStates();
auto p = model_->RunEncoder(features, std::move(states));
states = std::move(p.second);
auto &r = s->GetZipformerResult();
decoder_->Decode(std::move(p.first), &r);
}
private:
OnlineRecognizerConfig config_;
SymbolTable sym_;
Endpoint endpoint_;
int32_t unk_id_ = -1;
std::unique_ptr<OnlineZipformerTransducerModelRknn> model_;
std::unique_ptr<OnlineTransducerGreedySearchDecoderRknn> decoder_;
};
} // namespace sherpa_onnx
#endif // SHERPA_ONNX_CSRC_RKNN_ONLINE_RECOGNIZER_TRANSDUCER_RKNN_IMPL_H_
... ...
// sherpa-onnx/csrc/rknn/online-stream-rknn.cc
//
// Copyright (c) 2025 Xiaomi Corporation
#include "sherpa-onnx/csrc/rknn/online-stream-rknn.h"
#include <utility>
#include <vector>
namespace sherpa_onnx {
class OnlineStreamRknn::Impl {
public:
void SetZipformerEncoderStates(std::vector<std::vector<uint8_t>> states) {
states_ = std::move(states);
}
std::vector<std::vector<uint8_t>> &GetZipformerEncoderStates() {
return states_;
}
void SetZipformerResult(OnlineTransducerDecoderResultRknn r) {
result_ = std::move(r);
}
OnlineTransducerDecoderResultRknn &GetZipformerResult() { return result_; }
private:
std::vector<std::vector<uint8_t>> states_;
OnlineTransducerDecoderResultRknn result_;
};
OnlineStreamRknn::OnlineStreamRknn(
const FeatureExtractorConfig &config /*= {}*/,
ContextGraphPtr context_graph /*= nullptr*/)
: OnlineStream(config, context_graph), impl_(std::make_unique<Impl>()) {}
OnlineStreamRknn::~OnlineStreamRknn() = default;
void OnlineStreamRknn::SetZipformerEncoderStates(
std::vector<std::vector<uint8_t>> states) const {
impl_->SetZipformerEncoderStates(std::move(states));
}
std::vector<std::vector<uint8_t>> &OnlineStreamRknn::GetZipformerEncoderStates()
const {
return impl_->GetZipformerEncoderStates();
}
void OnlineStreamRknn::SetZipformerResult(
OnlineTransducerDecoderResultRknn r) const {
impl_->SetZipformerResult(std::move(r));
}
OnlineTransducerDecoderResultRknn &OnlineStreamRknn::GetZipformerResult()
const {
return impl_->GetZipformerResult();
}
} // namespace sherpa_onnx
... ...
// sherpa-onnx/csrc/rknn/online-stream-rknn.h
//
// Copyright (c) 2025 Xiaomi Corporation
#ifndef SHERPA_ONNX_CSRC_RKNN_ONLINE_STREAM_RKNN_H_
#define SHERPA_ONNX_CSRC_RKNN_ONLINE_STREAM_RKNN_H_
#include <memory>
#include <vector>
#include "rknn_api.h" // NOLINT
#include "sherpa-onnx/csrc/online-stream.h"
#include "sherpa-onnx/csrc/rknn/online-transducer-greedy-search-decoder-rknn.h"
namespace sherpa_onnx {
class OnlineStreamRknn : public OnlineStream {
public:
explicit OnlineStreamRknn(const FeatureExtractorConfig &config = {},
ContextGraphPtr context_graph = nullptr);
~OnlineStreamRknn();
void SetZipformerEncoderStates(
std::vector<std::vector<uint8_t>> states) const;
std::vector<std::vector<uint8_t>> &GetZipformerEncoderStates() const;
void SetZipformerResult(OnlineTransducerDecoderResultRknn r) const;
OnlineTransducerDecoderResultRknn &GetZipformerResult() const;
private:
class Impl;
std::unique_ptr<Impl> impl_;
};
} // namespace sherpa_onnx
#endif // SHERPA_ONNX_CSRC_RKNN_ONLINE_STREAM_RKNN_H_
... ...
// sherpa-onnx/csrc/rknn/online-transducer-greedy-search-decoder-rknn.cc
//
// Copyright (c) 2025 Xiaomi Corporation
#include "sherpa-onnx/csrc/rknn/online-transducer-greedy-search-decoder-rknn.h"
#include <algorithm>
#include <utility>
#include <vector>
#include "sherpa-onnx/csrc/macros.h"
namespace sherpa_onnx {
OnlineTransducerDecoderResultRknn
OnlineTransducerGreedySearchDecoderRknn::GetEmptyResult() const {
int32_t context_size = model_->ContextSize();
int32_t blank_id = 0; // always 0
OnlineTransducerDecoderResultRknn r;
r.tokens.resize(context_size, -1);
r.tokens.back() = blank_id;
return r;
}
void OnlineTransducerGreedySearchDecoderRknn::StripLeadingBlanks(
OnlineTransducerDecoderResultRknn *r) const {
int32_t context_size = model_->ContextSize();
auto start = r->tokens.begin() + context_size;
auto end = r->tokens.end();
r->tokens = std::vector<int64_t>(start, end);
}
void OnlineTransducerGreedySearchDecoderRknn::Decode(
std::vector<float> encoder_out,
OnlineTransducerDecoderResultRknn *result) const {
auto &r = result[0];
auto attr = model_->GetEncoderOutAttr();
int32_t num_frames = attr.dims[1];
int32_t encoder_out_dim = attr.dims[2];
int32_t vocab_size = model_->VocabSize();
int32_t context_size = model_->ContextSize();
std::vector<int64_t> decoder_input;
std::vector<float> decoder_out;
if (r.previous_decoder_out.empty()) {
decoder_input = {r.tokens.begin() + (r.tokens.size() - context_size),
r.tokens.end()};
decoder_out = model_->RunDecoder(std::move(decoder_input));
} else {
decoder_out = std::move(r.previous_decoder_out);
}
const float *p_encoder_out = encoder_out.data();
for (int32_t t = 0; t != num_frames; ++t) {
auto logit = model_->RunJoiner(p_encoder_out, decoder_out.data());
p_encoder_out += encoder_out_dim;
bool emitted = false;
if (blank_penalty_ > 0.0) {
logit[0] -= blank_penalty_; // assuming blank id is 0
}
auto y = static_cast<int32_t>(std::distance(
logit.data(),
std::max_element(logit.data(), logit.data() + vocab_size)));
// blank id is hardcoded to 0
// also, it treats unk as blank
if (y != 0 && y != unk_id_) {
emitted = true;
r.tokens.push_back(y);
r.timestamps.push_back(t + r.frame_offset);
r.num_trailing_blanks = 0;
} else {
++r.num_trailing_blanks;
}
if (emitted) {
decoder_input = {r.tokens.begin() + (r.tokens.size() - context_size),
r.tokens.end()};
decoder_out = model_->RunDecoder(std::move(decoder_input));
}
}
r.frame_offset += num_frames;
r.previous_decoder_out = std::move(decoder_out);
}
} // namespace sherpa_onnx
... ...
// sherpa-onnx/csrc/rknn/online-transducer-greedy-search-decoder-rknn.h
//
// Copyright (c) 2025 Xiaomi Corporation
#ifndef SHERPA_ONNX_CSRC_RKNN_ONLINE_TRANSDUCER_GREEDY_SEARCH_DECODER_RKNN_H_
#define SHERPA_ONNX_CSRC_RKNN_ONLINE_TRANSDUCER_GREEDY_SEARCH_DECODER_RKNN_H_
#include <vector>
#include "sherpa-onnx/csrc/rknn/online-zipformer-transducer-model-rknn.h"
namespace sherpa_onnx {
struct OnlineTransducerDecoderResultRknn {
/// Number of frames after subsampling we have decoded so far
int32_t frame_offset = 0;
/// The decoded token IDs so far
std::vector<int64_t> tokens;
/// number of trailing blank frames decoded so far
int32_t num_trailing_blanks = 0;
/// timestamps[i] contains the output frame index where tokens[i] is decoded.
std::vector<int32_t> timestamps;
std::vector<float> previous_decoder_out;
};
class OnlineTransducerGreedySearchDecoderRknn {
public:
explicit OnlineTransducerGreedySearchDecoderRknn(
OnlineZipformerTransducerModelRknn *model, int32_t unk_id = 2,
float blank_penalty = 0.0)
: model_(model), unk_id_(unk_id), blank_penalty_(blank_penalty) {}
OnlineTransducerDecoderResultRknn GetEmptyResult() const;
void StripLeadingBlanks(OnlineTransducerDecoderResultRknn *r) const;
void Decode(std::vector<float> encoder_out,
OnlineTransducerDecoderResultRknn *result) const;
private:
OnlineZipformerTransducerModelRknn *model_; // Not owned
int32_t unk_id_;
float blank_penalty_;
};
} // namespace sherpa_onnx
#endif // SHERPA_ONNX_CSRC_RKNN_ONLINE_TRANSDUCER_GREEDY_SEARCH_DECODER_RKNN_H_
... ...
// sherpa-onnx/csrc/rknn/online-zipformer-transducer-model-rknn.cc
//
// Copyright (c) 2023 Xiaomi Corporation
#include "sherpa-onnx/csrc/rknn/online-zipformer-transducer-model-rknn.h"
#include <memory>
#include <sstream>
#include <string>
#include <unordered_map>
#include <utility>
#include <vector>
#if __ANDROID_API__ >= 9
#include "android/asset_manager.h"
#include "android/asset_manager_jni.h"
#endif
#if __OHOS__
#include "rawfile/raw_file_manager.h"
#endif
#include "sherpa-onnx/csrc/file-utils.h"
#include "sherpa-onnx/csrc/rknn/macros.h"
#include "sherpa-onnx/csrc/text-utils.h"
namespace sherpa_onnx {
// chw -> hwc
static void Transpose(const float *src, int32_t n, int32_t channel,
int32_t height, int32_t width, float *dst) {
for (int32_t i = 0; i < n; ++i) {
for (int32_t h = 0; h < height; ++h) {
for (int32_t w = 0; w < width; ++w) {
for (int32_t c = 0; c < channel; ++c) {
// dst[h, w, c] = src[c, h, w]
dst[i * height * width * channel + h * width * channel + w * channel +
c] = src[i * height * width * channel + c * height * width +
h * width + w];
}
}
}
}
}
static std::string ToString(const rknn_tensor_attr &attr) {
std::ostringstream os;
os << "{";
os << attr.index;
os << ", name: " << attr.name;
os << ", shape: (";
std::string sep;
for (int32_t i = 0; i < static_cast<int32_t>(attr.n_dims); ++i) {
os << sep << attr.dims[i];
sep = ",";
}
os << ")";
os << ", n_elems: " << attr.n_elems;
os << ", size: " << attr.size;
os << ", fmt: " << get_format_string(attr.fmt);
os << ", type: " << get_type_string(attr.type);
os << ", pass_through: " << (attr.pass_through ? "true" : "false");
os << "}";
return os.str();
}
static std::unordered_map<std::string, std::string> Parse(
const rknn_custom_string &custom_string) {
std::unordered_map<std::string, std::string> ans;
std::vector<std::string> fields;
SplitStringToVector(custom_string.string, ";", false, &fields);
std::vector<std::string> tmp;
for (const auto &f : fields) {
SplitStringToVector(f, "=", false, &tmp);
if (tmp.size() != 2) {
SHERPA_ONNX_LOGE("Invalid custom string %s for %s", custom_string.string,
f.c_str());
SHERPA_ONNX_EXIT(-1);
}
ans[std::move(tmp[0])] = std::move(tmp[1]);
}
return ans;
}
class OnlineZipformerTransducerModelRknn::Impl {
public:
~Impl() {
auto ret = rknn_destroy(encoder_ctx_);
if (ret != RKNN_SUCC) {
SHERPA_ONNX_LOGE("Failed to destroy the encoder context");
}
ret = rknn_destroy(decoder_ctx_);
if (ret != RKNN_SUCC) {
SHERPA_ONNX_LOGE("Failed to destroy the decoder context");
}
ret = rknn_destroy(joiner_ctx_);
if (ret != RKNN_SUCC) {
SHERPA_ONNX_LOGE("Failed to destroy the joiner context");
}
}
explicit Impl(const OnlineModelConfig &config) : config_(config) {
{
auto buf = ReadFile(config.transducer.encoder);
InitEncoder(buf.data(), buf.size());
}
{
auto buf = ReadFile(config.transducer.decoder);
InitDecoder(buf.data(), buf.size());
}
{
auto buf = ReadFile(config.transducer.joiner);
InitJoiner(buf.data(), buf.size());
}
// Now select which core to run for RK3588
int32_t ret_encoder = RKNN_SUCC;
int32_t ret_decoder = RKNN_SUCC;
int32_t ret_joiner = RKNN_SUCC;
switch (config_.num_threads) {
case 1:
ret_encoder = rknn_set_core_mask(encoder_ctx_, RKNN_NPU_CORE_AUTO);
ret_decoder = rknn_set_core_mask(decoder_ctx_, RKNN_NPU_CORE_AUTO);
ret_joiner = rknn_set_core_mask(joiner_ctx_, RKNN_NPU_CORE_AUTO);
break;
case 0:
ret_encoder = rknn_set_core_mask(encoder_ctx_, RKNN_NPU_CORE_0);
ret_decoder = rknn_set_core_mask(decoder_ctx_, RKNN_NPU_CORE_0);
ret_joiner = rknn_set_core_mask(joiner_ctx_, RKNN_NPU_CORE_0);
break;
case -1:
ret_encoder = rknn_set_core_mask(encoder_ctx_, RKNN_NPU_CORE_1);
ret_decoder = rknn_set_core_mask(decoder_ctx_, RKNN_NPU_CORE_1);
ret_joiner = rknn_set_core_mask(joiner_ctx_, RKNN_NPU_CORE_1);
break;
case -2:
ret_encoder = rknn_set_core_mask(encoder_ctx_, RKNN_NPU_CORE_2);
ret_decoder = rknn_set_core_mask(decoder_ctx_, RKNN_NPU_CORE_2);
ret_joiner = rknn_set_core_mask(joiner_ctx_, RKNN_NPU_CORE_2);
break;
case -3:
ret_encoder = rknn_set_core_mask(encoder_ctx_, RKNN_NPU_CORE_0_1);
ret_decoder = rknn_set_core_mask(decoder_ctx_, RKNN_NPU_CORE_0_1);
ret_joiner = rknn_set_core_mask(joiner_ctx_, RKNN_NPU_CORE_0_1);
break;
case -4:
ret_encoder = rknn_set_core_mask(encoder_ctx_, RKNN_NPU_CORE_0_1_2);
ret_decoder = rknn_set_core_mask(decoder_ctx_, RKNN_NPU_CORE_0_1_2);
ret_joiner = rknn_set_core_mask(joiner_ctx_, RKNN_NPU_CORE_0_1_2);
break;
default:
SHERPA_ONNX_LOGE(
"Valid num_threads for rk npu is 1 (auto), 0 (core 0), -1 (core "
"1), -2 (core 2), -3 (core 0_1), -4 (core 0_1_2). Given: %d",
config_.num_threads);
break;
}
if (ret_encoder != RKNN_SUCC) {
SHERPA_ONNX_LOGE(
"Failed to select npu core to run encoder (You can ignore it if you "
"are not using RK3588.");
}
if (ret_decoder != RKNN_SUCC) {
SHERPA_ONNX_LOGE(
"Failed to select npu core to run decoder (You can ignore it if you "
"are not using RK3588.");
}
if (ret_decoder != RKNN_SUCC) {
SHERPA_ONNX_LOGE(
"Failed to select npu core to run joiner (You can ignore it if you "
"are not using RK3588.");
}
}
// TODO(fangjun): Support Android
std::vector<std::vector<uint8_t>> GetEncoderInitStates() const {
// encoder_input_attrs_[0] is for the feature
// encoder_input_attrs_[1:] is for states
// so we use -1 here
std::vector<std::vector<uint8_t>> states(encoder_input_attrs_.size() - 1);
int32_t i = -1;
for (auto &attr : encoder_input_attrs_) {
i += 1;
if (i == 0) {
// skip processing the attr for features.
continue;
}
if (attr.type == RKNN_TENSOR_FLOAT16) {
states[i - 1].resize(attr.n_elems * sizeof(float));
} else if (attr.type == RKNN_TENSOR_INT64) {
states[i - 1].resize(attr.n_elems * sizeof(int64_t));
} else {
SHERPA_ONNX_LOGE("Unsupported tensor type: %d, %s", attr.type,
get_type_string(attr.type));
SHERPA_ONNX_EXIT(-1);
}
}
return states;
}
std::pair<std::vector<float>, std::vector<std::vector<uint8_t>>> RunEncoder(
std::vector<float> features,
std::vector<std::vector<uint8_t>> states) const {
std::vector<rknn_input> inputs(encoder_input_attrs_.size());
for (int32_t i = 0; i < static_cast<int32_t>(inputs.size()); ++i) {
auto &input = inputs[i];
auto &attr = encoder_input_attrs_[i];
input.index = attr.index;
if (attr.type == RKNN_TENSOR_FLOAT16) {
input.type = RKNN_TENSOR_FLOAT32;
} else if (attr.type == RKNN_TENSOR_INT64) {
input.type = RKNN_TENSOR_INT64;
} else {
SHERPA_ONNX_LOGE("Unsupported tensor type %d, %s", attr.type,
get_type_string(attr.type));
SHERPA_ONNX_EXIT(-1);
}
input.fmt = attr.fmt;
if (i == 0) {
input.buf = reinterpret_cast<void *>(features.data());
input.size = features.size() * sizeof(float);
} else {
input.buf = reinterpret_cast<void *>(states[i - 1].data());
input.size = states[i - 1].size();
}
}
std::vector<float> encoder_out(encoder_output_attrs_[0].n_elems);
// Note(fangjun): We can reuse the memory from input argument `states`
// auto next_states = GetEncoderInitStates();
auto &next_states = states;
std::vector<rknn_output> outputs(encoder_output_attrs_.size());
for (int32_t i = 0; i < outputs.size(); ++i) {
auto &output = outputs[i];
auto &attr = encoder_output_attrs_[i];
output.index = attr.index;
output.is_prealloc = 1;
if (attr.type == RKNN_TENSOR_FLOAT16) {
output.want_float = 1;
} else if (attr.type == RKNN_TENSOR_INT64) {
output.want_float = 0;
} else {
SHERPA_ONNX_LOGE("Unsupported tensor type %d, %s", attr.type,
get_type_string(attr.type));
SHERPA_ONNX_EXIT(-1);
}
if (i == 0) {
output.size = encoder_out.size() * sizeof(float);
output.buf = reinterpret_cast<void *>(encoder_out.data());
} else {
output.size = next_states[i - 1].size();
output.buf = reinterpret_cast<void *>(next_states[i - 1].data());
}
}
auto ret = rknn_inputs_set(encoder_ctx_, inputs.size(), inputs.data());
SHERPA_ONNX_RKNN_CHECK(ret, "Failed to set encoder inputs");
ret = rknn_run(encoder_ctx_, nullptr);
SHERPA_ONNX_RKNN_CHECK(ret, "Failed to run encoder");
ret =
rknn_outputs_get(encoder_ctx_, outputs.size(), outputs.data(), nullptr);
SHERPA_ONNX_RKNN_CHECK(ret, "Failed to get encoder output");
for (int32_t i = 0; i < next_states.size(); ++i) {
const auto &attr = encoder_input_attrs_[i + 1];
if (attr.n_dims == 4) {
// TODO(fangjun): The transpose is copied from
// https://github.com/airockchip/rknn_model_zoo/blob/main/examples/zipformer/cpp/process.cc#L22
// I don't understand why we need to do that.
std::vector<uint8_t> dst(next_states[i].size());
int32_t n = attr.dims[0];
int32_t h = attr.dims[1];
int32_t w = attr.dims[2];
int32_t c = attr.dims[3];
Transpose(reinterpret_cast<const float *>(next_states[i].data()), n, c,
h, w, reinterpret_cast<float *>(dst.data()));
next_states[i] = std::move(dst);
}
}
return {std::move(encoder_out), std::move(next_states)};
}
std::vector<float> RunDecoder(std::vector<int64_t> decoder_input) const {
auto &attr = decoder_input_attrs_[0];
rknn_input input;
input.index = 0;
input.type = RKNN_TENSOR_INT64;
input.fmt = attr.fmt;
input.buf = decoder_input.data();
input.size = decoder_input.size() * sizeof(int64_t);
std::vector<float> decoder_out(decoder_output_attrs_[0].n_elems);
rknn_output output;
output.index = decoder_output_attrs_[0].index;
output.is_prealloc = 1;
output.want_float = 1;
output.size = decoder_out.size() * sizeof(float);
output.buf = decoder_out.data();
auto ret = rknn_inputs_set(decoder_ctx_, 1, &input);
SHERPA_ONNX_RKNN_CHECK(ret, "Failed to set decoder inputs");
ret = rknn_run(decoder_ctx_, nullptr);
SHERPA_ONNX_RKNN_CHECK(ret, "Failed to run decoder");
ret = rknn_outputs_get(decoder_ctx_, 1, &output, nullptr);
SHERPA_ONNX_RKNN_CHECK(ret, "Failed to get decoder output");
return decoder_out;
}
std::vector<float> RunJoiner(const float *encoder_out,
const float *decoder_out) const {
std::vector<rknn_input> inputs(2);
inputs[0].index = 0;
inputs[0].type = RKNN_TENSOR_FLOAT32;
inputs[0].fmt = joiner_input_attrs_[0].fmt;
inputs[0].buf = const_cast<float *>(encoder_out);
inputs[0].size = joiner_input_attrs_[0].n_elems * sizeof(float);
inputs[1].index = 1;
inputs[1].type = RKNN_TENSOR_FLOAT32;
inputs[1].fmt = joiner_input_attrs_[1].fmt;
inputs[1].buf = const_cast<float *>(decoder_out);
inputs[1].size = joiner_input_attrs_[1].n_elems * sizeof(float);
std::vector<float> joiner_out(joiner_output_attrs_[0].n_elems);
rknn_output output;
output.index = joiner_output_attrs_[0].index;
output.is_prealloc = 1;
output.want_float = 1;
output.size = joiner_out.size() * sizeof(float);
output.buf = joiner_out.data();
auto ret = rknn_inputs_set(joiner_ctx_, inputs.size(), inputs.data());
SHERPA_ONNX_RKNN_CHECK(ret, "Failed to set joiner inputs");
ret = rknn_run(joiner_ctx_, nullptr);
SHERPA_ONNX_RKNN_CHECK(ret, "Failed to run joiner");
ret = rknn_outputs_get(joiner_ctx_, 1, &output, nullptr);
SHERPA_ONNX_RKNN_CHECK(ret, "Failed to get joiner output");
return joiner_out;
}
int32_t ContextSize() const { return context_size_; }
int32_t ChunkSize() const { return T_; }
int32_t ChunkShift() const { return decode_chunk_len_; }
int32_t VocabSize() const { return vocab_size_; }
rknn_tensor_attr GetEncoderOutAttr() const {
return encoder_output_attrs_[0];
}
private:
void InitEncoder(void *model_data, size_t model_data_length) {
auto ret =
rknn_init(&encoder_ctx_, model_data, model_data_length, 0, nullptr);
SHERPA_ONNX_RKNN_CHECK(ret, "Failed to init encoder '%s'",
config_.transducer.encoder.c_str());
if (config_.debug) {
rknn_sdk_version v;
ret = rknn_query(encoder_ctx_, RKNN_QUERY_SDK_VERSION, &v, sizeof(v));
SHERPA_ONNX_RKNN_CHECK(ret, "Failed to get rknn sdk version");
SHERPA_ONNX_LOGE("sdk api version: %s, driver version: %s", v.api_version,
v.drv_version);
}
rknn_input_output_num io_num;
ret = rknn_query(encoder_ctx_, RKNN_QUERY_IN_OUT_NUM, &io_num,
sizeof(io_num));
SHERPA_ONNX_RKNN_CHECK(ret,
"Failed to get I/O information for the encoder");
if (config_.debug) {
SHERPA_ONNX_LOGE("encoder: %d inputs, %d outputs",
static_cast<int32_t>(io_num.n_input),
static_cast<int32_t>(io_num.n_output));
}
encoder_input_attrs_.resize(io_num.n_input);
encoder_output_attrs_.resize(io_num.n_output);
int32_t i = 0;
for (auto &attr : encoder_input_attrs_) {
memset(&attr, 0, sizeof(attr));
attr.index = i;
ret =
rknn_query(encoder_ctx_, RKNN_QUERY_INPUT_ATTR, &attr, sizeof(attr));
SHERPA_ONNX_RKNN_CHECK(ret, "Failed to get attr for encoder input %d", i);
i += 1;
}
if (config_.debug) {
std::ostringstream os;
std::string sep;
for (auto &attr : encoder_input_attrs_) {
os << sep << ToString(attr);
sep = "\n";
}
SHERPA_ONNX_LOGE("\n----------Encoder inputs info----------\n%s",
os.str().c_str());
}
i = 0;
for (auto &attr : encoder_output_attrs_) {
memset(&attr, 0, sizeof(attr));
attr.index = i;
ret =
rknn_query(encoder_ctx_, RKNN_QUERY_OUTPUT_ATTR, &attr, sizeof(attr));
SHERPA_ONNX_RKNN_CHECK(ret, "Failed to get attr for encoder output %d",
i);
i += 1;
}
if (config_.debug) {
std::ostringstream os;
std::string sep;
for (auto &attr : encoder_output_attrs_) {
os << sep << ToString(attr);
sep = "\n";
}
SHERPA_ONNX_LOGE("\n----------Encoder outputs info----------\n%s",
os.str().c_str());
}
rknn_custom_string custom_string;
ret = rknn_query(encoder_ctx_, RKNN_QUERY_CUSTOM_STRING, &custom_string,
sizeof(custom_string));
SHERPA_ONNX_RKNN_CHECK(
ret, "Failed to read custom string from the encoder model");
if (config_.debug) {
SHERPA_ONNX_LOGE("customs string: %s", custom_string.string);
}
auto meta = Parse(custom_string);
for (const auto &p : meta) {
SHERPA_ONNX_LOGE("%s: %s", p.first.c_str(), p.second.c_str());
}
if (meta.count("encoder_dims")) {
SplitStringToIntegers(meta.at("encoder_dims"), ",", false,
&encoder_dims_);
}
if (meta.count("attention_dims")) {
SplitStringToIntegers(meta.at("attention_dims"), ",", false,
&attention_dims_);
}
if (meta.count("num_encoder_layers")) {
SplitStringToIntegers(meta.at("num_encoder_layers"), ",", false,
&num_encoder_layers_);
}
if (meta.count("cnn_module_kernels")) {
SplitStringToIntegers(meta.at("cnn_module_kernels"), ",", false,
&cnn_module_kernels_);
}
if (meta.count("left_context_len")) {
SplitStringToIntegers(meta.at("left_context_len"), ",", false,
&left_context_len_);
}
if (meta.count("T")) {
T_ = atoi(meta.at("T").c_str());
}
if (meta.count("decode_chunk_len")) {
decode_chunk_len_ = atoi(meta.at("decode_chunk_len").c_str());
}
if (meta.count("context_size")) {
context_size_ = atoi(meta.at("context_size").c_str());
}
if (config_.debug) {
auto print = [](const std::vector<int32_t> &v, const char *name) {
std::ostringstream os;
os << name << ": ";
for (auto i : v) {
os << i << " ";
}
#if __OHOS__
SHERPA_ONNX_LOGE("%{public}s\n", os.str().c_str());
#else
SHERPA_ONNX_LOGE("%s\n", os.str().c_str());
#endif
};
print(encoder_dims_, "encoder_dims");
print(attention_dims_, "attention_dims");
print(num_encoder_layers_, "num_encoder_layers");
print(cnn_module_kernels_, "cnn_module_kernels");
print(left_context_len_, "left_context_len");
#if __OHOS__
SHERPA_ONNX_LOGE("T: %{public}d", T_);
SHERPA_ONNX_LOGE("decode_chunk_len_: %{public}d", decode_chunk_len_);
SHERPA_ONNX_LOGE("context_size: %{public}d", context_size_);
#else
SHERPA_ONNX_LOGE("T: %d", T_);
SHERPA_ONNX_LOGE("decode_chunk_len_: %d", decode_chunk_len_);
SHERPA_ONNX_LOGE("context_size: %d", context_size_);
#endif
}
}
void InitDecoder(void *model_data, size_t model_data_length) {
auto ret =
rknn_init(&decoder_ctx_, model_data, model_data_length, 0, nullptr);
SHERPA_ONNX_RKNN_CHECK(ret, "Failed to init decoder '%s'",
config_.transducer.decoder.c_str());
rknn_input_output_num io_num;
ret = rknn_query(decoder_ctx_, RKNN_QUERY_IN_OUT_NUM, &io_num,
sizeof(io_num));
SHERPA_ONNX_RKNN_CHECK(ret,
"Failed to get I/O information for the decoder");
if (io_num.n_input != 1) {
SHERPA_ONNX_LOGE("Expect only 1 decoder input. Given %d",
static_cast<int32_t>(io_num.n_input));
SHERPA_ONNX_EXIT(-1);
}
if (io_num.n_output != 1) {
SHERPA_ONNX_LOGE("Expect only 1 decoder output. Given %d",
static_cast<int32_t>(io_num.n_output));
SHERPA_ONNX_EXIT(-1);
}
if (config_.debug) {
SHERPA_ONNX_LOGE("decoder: %d inputs, %d outputs",
static_cast<int32_t>(io_num.n_input),
static_cast<int32_t>(io_num.n_output));
}
decoder_input_attrs_.resize(io_num.n_input);
decoder_output_attrs_.resize(io_num.n_output);
int32_t i = 0;
for (auto &attr : decoder_input_attrs_) {
memset(&attr, 0, sizeof(attr));
attr.index = i;
ret =
rknn_query(decoder_ctx_, RKNN_QUERY_INPUT_ATTR, &attr, sizeof(attr));
SHERPA_ONNX_RKNN_CHECK(ret, "Failed to get attr for decoder input %d", i);
i += 1;
}
if (config_.debug) {
std::ostringstream os;
std::string sep;
for (auto &attr : decoder_input_attrs_) {
os << sep << ToString(attr);
sep = "\n";
}
SHERPA_ONNX_LOGE("\n----------Decoder inputs info----------\n%s",
os.str().c_str());
}
if (decoder_input_attrs_[0].type != RKNN_TENSOR_INT64) {
SHERPA_ONNX_LOGE("Expect int64 for decoder input. Given: %d, %s",
decoder_input_attrs_[0].type,
get_type_string(decoder_input_attrs_[0].type));
SHERPA_ONNX_EXIT(-1);
}
i = 0;
for (auto &attr : decoder_output_attrs_) {
memset(&attr, 0, sizeof(attr));
attr.index = i;
ret =
rknn_query(decoder_ctx_, RKNN_QUERY_OUTPUT_ATTR, &attr, sizeof(attr));
SHERPA_ONNX_RKNN_CHECK(ret, "Failed to get attr for decoder output %d",
i);
i += 1;
}
if (config_.debug) {
std::ostringstream os;
std::string sep;
for (auto &attr : decoder_output_attrs_) {
os << sep << ToString(attr);
sep = "\n";
}
SHERPA_ONNX_LOGE("\n----------Decoder outputs info----------\n%s",
os.str().c_str());
}
}
void InitJoiner(void *model_data, size_t model_data_length) {
auto ret =
rknn_init(&joiner_ctx_, model_data, model_data_length, 0, nullptr);
SHERPA_ONNX_RKNN_CHECK(ret, "Failed to init joiner '%s'",
config_.transducer.joiner.c_str());
rknn_input_output_num io_num;
ret =
rknn_query(joiner_ctx_, RKNN_QUERY_IN_OUT_NUM, &io_num, sizeof(io_num));
SHERPA_ONNX_RKNN_CHECK(ret, "Failed to get I/O information for the joiner");
if (config_.debug) {
SHERPA_ONNX_LOGE("joiner: %d inputs, %d outputs",
static_cast<int32_t>(io_num.n_input),
static_cast<int32_t>(io_num.n_output));
}
joiner_input_attrs_.resize(io_num.n_input);
joiner_output_attrs_.resize(io_num.n_output);
int32_t i = 0;
for (auto &attr : joiner_input_attrs_) {
memset(&attr, 0, sizeof(attr));
attr.index = i;
ret = rknn_query(joiner_ctx_, RKNN_QUERY_INPUT_ATTR, &attr, sizeof(attr));
SHERPA_ONNX_RKNN_CHECK(ret, "Failed to get attr for joiner input %d", i);
i += 1;
}
if (config_.debug) {
std::ostringstream os;
std::string sep;
for (auto &attr : joiner_input_attrs_) {
os << sep << ToString(attr);
sep = "\n";
}
SHERPA_ONNX_LOGE("\n----------Joiner inputs info----------\n%s",
os.str().c_str());
}
i = 0;
for (auto &attr : joiner_output_attrs_) {
memset(&attr, 0, sizeof(attr));
attr.index = i;
ret =
rknn_query(joiner_ctx_, RKNN_QUERY_OUTPUT_ATTR, &attr, sizeof(attr));
SHERPA_ONNX_RKNN_CHECK(ret, "Failed to get attr for joiner output %d", i);
i += 1;
}
if (config_.debug) {
std::ostringstream os;
std::string sep;
for (auto &attr : joiner_output_attrs_) {
os << sep << ToString(attr);
sep = "\n";
}
SHERPA_ONNX_LOGE("\n----------Joiner outputs info----------\n%s",
os.str().c_str());
}
vocab_size_ = joiner_output_attrs_[0].dims[1];
if (config_.debug) {
SHERPA_ONNX_LOGE("vocab_size: %d", vocab_size_);
}
}
private:
OnlineModelConfig config_;
rknn_context encoder_ctx_ = 0;
rknn_context decoder_ctx_ = 0;
rknn_context joiner_ctx_ = 0;
std::vector<rknn_tensor_attr> encoder_input_attrs_;
std::vector<rknn_tensor_attr> encoder_output_attrs_;
std::vector<rknn_tensor_attr> decoder_input_attrs_;
std::vector<rknn_tensor_attr> decoder_output_attrs_;
std::vector<rknn_tensor_attr> joiner_input_attrs_;
std::vector<rknn_tensor_attr> joiner_output_attrs_;
std::vector<int32_t> encoder_dims_;
std::vector<int32_t> attention_dims_;
std::vector<int32_t> num_encoder_layers_;
std::vector<int32_t> cnn_module_kernels_;
std::vector<int32_t> left_context_len_;
int32_t T_ = 0;
int32_t decode_chunk_len_ = 0;
int32_t context_size_ = 2;
int32_t vocab_size_ = 0;
};
OnlineZipformerTransducerModelRknn::~OnlineZipformerTransducerModelRknn() =
default;
OnlineZipformerTransducerModelRknn::OnlineZipformerTransducerModelRknn(
const OnlineModelConfig &config)
: impl_(std::make_unique<Impl>(config)) {}
template <typename Manager>
OnlineZipformerTransducerModelRknn::OnlineZipformerTransducerModelRknn(
Manager *mgr, const OnlineModelConfig &config)
: impl_(std::make_unique<OnlineZipformerTransducerModelRknn>(mgr, config)) {
}
std::vector<std::vector<uint8_t>>
OnlineZipformerTransducerModelRknn::GetEncoderInitStates() const {
return impl_->GetEncoderInitStates();
}
std::pair<std::vector<float>, std::vector<std::vector<uint8_t>>>
OnlineZipformerTransducerModelRknn::RunEncoder(
std::vector<float> features,
std::vector<std::vector<uint8_t>> states) const {
return impl_->RunEncoder(std::move(features), std::move(states));
}
std::vector<float> OnlineZipformerTransducerModelRknn::RunDecoder(
std::vector<int64_t> decoder_input) const {
return impl_->RunDecoder(std::move(decoder_input));
}
std::vector<float> OnlineZipformerTransducerModelRknn::RunJoiner(
const float *encoder_out, const float *decoder_out) const {
return impl_->RunJoiner(encoder_out, decoder_out);
}
int32_t OnlineZipformerTransducerModelRknn::ContextSize() const {
return impl_->ContextSize();
}
int32_t OnlineZipformerTransducerModelRknn::ChunkSize() const {
return impl_->ChunkSize();
}
int32_t OnlineZipformerTransducerModelRknn::ChunkShift() const {
return impl_->ChunkShift();
}
int32_t OnlineZipformerTransducerModelRknn::VocabSize() const {
return impl_->VocabSize();
}
rknn_tensor_attr OnlineZipformerTransducerModelRknn::GetEncoderOutAttr() const {
return impl_->GetEncoderOutAttr();
}
#if __ANDROID_API__ >= 9
template OnlineZipformerTransducerModelRknn::OnlineZipformerTransducerModelRknn(
AAssetManager *mgr, const OnlineModelConfig &config);
#endif
#if __OHOS__
template OnlineZipformerTransducerModelRknn::OnlineZipformerTransducerModelRknn(
NativeResourceManager *mgr, const OnlineModelConfig &config);
#endif
} // namespace sherpa_onnx
... ...
// sherpa-onnx/csrc/rknn/online-zipformer-transducer-model-rknn.h
//
// Copyright (c) 2025 Xiaomi Corporation
#ifndef SHERPA_ONNX_CSRC_RKNN_ONLINE_ZIPFORMER_TRANSDUCER_MODEL_RKNN_H_
#define SHERPA_ONNX_CSRC_RKNN_ONLINE_ZIPFORMER_TRANSDUCER_MODEL_RKNN_H_
#include <memory>
#include <utility>
#include <vector>
#include "rknn_api.h" // NOLINT
#include "sherpa-onnx/csrc/online-model-config.h"
#include "sherpa-onnx/csrc/online-transducer-model.h"
namespace sherpa_onnx {
// this is for zipformer v1, i.e., the folder
// pruned_transducer_statelss7_streaming from icefall
class OnlineZipformerTransducerModelRknn {
public:
~OnlineZipformerTransducerModelRknn();
explicit OnlineZipformerTransducerModelRknn(const OnlineModelConfig &config);
template <typename Manager>
OnlineZipformerTransducerModelRknn(Manager *mgr,
const OnlineModelConfig &config);
std::vector<std::vector<uint8_t>> GetEncoderInitStates() const;
std::pair<std::vector<float>, std::vector<std::vector<uint8_t>>> RunEncoder(
std::vector<float> features,
std::vector<std::vector<uint8_t>> states) const;
std::vector<float> RunDecoder(std::vector<int64_t> decoder_input) const;
std::vector<float> RunJoiner(const float *encoder_out,
const float *decoder_out) const;
int32_t ContextSize() const;
int32_t ChunkSize() const;
int32_t ChunkShift() const;
int32_t VocabSize() const;
rknn_tensor_attr GetEncoderOutAttr() const;
private:
class Impl;
std::unique_ptr<Impl> impl_;
};
} // namespace sherpa_onnx
#endif // SHERPA_ONNX_CSRC_RKNN_ONLINE_ZIPFORMER_TRANSDUCER_MODEL_RKNN_H_
... ...
... ... @@ -17,6 +17,7 @@
#include "rawfile/raw_file_manager.h"
#endif
#include "sherpa-onnx/csrc/file-utils.h"
#include "sherpa-onnx/csrc/macros.h"
#include "sherpa-onnx/csrc/onnx-utils.h"
#include "sherpa-onnx/csrc/session.h"
... ...
... ... @@ -12,6 +12,7 @@
#include "rawfile/raw_file_manager.h"
#endif
#include "sherpa-onnx/csrc/file-utils.h"
#include "sherpa-onnx/csrc/macros.h"
#include "sherpa-onnx/csrc/onnx-utils.h"
#include "sherpa-onnx/csrc/speaker-embedding-extractor-general-impl.h"
... ...
... ... @@ -17,6 +17,7 @@
#include "rawfile/raw_file_manager.h"
#endif
#include "sherpa-onnx/csrc/file-utils.h"
#include "sherpa-onnx/csrc/macros.h"
#include "sherpa-onnx/csrc/onnx-utils.h"
#include "sherpa-onnx/csrc/session.h"
... ...
... ... @@ -17,6 +17,7 @@
#include "rawfile/raw_file_manager.h"
#endif
#include "sherpa-onnx/csrc/file-utils.h"
#include "sherpa-onnx/csrc/macros.h"
#include "sherpa-onnx/csrc/onnx-utils.h"
#include "sherpa-onnx/csrc/session.h"
... ...
... ... @@ -10,6 +10,7 @@
#include "android/asset_manager_jni.h"
#endif
#include "sherpa-onnx/csrc/file-utils.h"
#include "sherpa-onnx/csrc/macros.h"
#include "sherpa-onnx/csrc/onnx-utils.h"
#include "sherpa-onnx/csrc/spoken-language-identification-whisper-impl.h"
... ...