code refactoring and add CI (#11)
This commit is contained in:
85
.github/workflows/test-linux.yaml
vendored
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85
.github/workflows/test-linux.yaml
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@@ -0,0 +1,85 @@
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name: test-linux
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on:
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push:
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branches:
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- master
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paths:
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- '.github/workflows/test-linux.yaml'
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- 'CMakeLists.txt'
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- 'cmake/**'
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- 'sherpa-onnx/csrc/*'
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pull_request:
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branches:
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- master
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paths:
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- '.github/workflows/test-linux.yaml'
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- 'CMakeLists.txt'
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- 'cmake/**'
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- 'sherpa-onnx/csrc/*'
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concurrency:
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group: test-linux-${{ github.ref }}
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cancel-in-progress: true
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permissions:
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contents: read
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jobs:
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test-linux:
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runs-on: ${{ matrix.os }}
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strategy:
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fail-fast: false
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matrix:
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os: [ubuntu-latest]
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steps:
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- uses: actions/checkout@v2
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with:
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fetch-depth: 0
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- name: Download pretrained model and test-data (English)
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shell: bash
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run: |
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git lfs install
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git clone https://huggingface.co/csukuangfj/icefall-asr-librispeech-pruned-transducer-stateless3-2022-05-13
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- name: Configure Cmake
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shell: bash
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run: |
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mkdir build
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cd build
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cmake -D CMAKE_BUILD_TYPE=Release ..
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- name: Build sherpa-onnx for ubuntu
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run: |
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cd build
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make VERBOSE=1 -j3
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- name: Run tests for ubuntu (English)
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run: |
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time ./build/bin/sherpa-onnx \
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./icefall-asr-librispeech-pruned-transducer-stateless3-2022-05-13/exp/onnx/encoder.onnx \
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./icefall-asr-librispeech-pruned-transducer-stateless3-2022-05-13/exp/onnx/decoder.onnx \
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./icefall-asr-librispeech-pruned-transducer-stateless3-2022-05-13/exp/onnx/joiner.onnx \
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./icefall-asr-librispeech-pruned-transducer-stateless3-2022-05-13/exp/onnx/joiner_encoder_proj.onnx \
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./icefall-asr-librispeech-pruned-transducer-stateless3-2022-05-13/exp/onnx/joiner_decoder_proj.onnx \
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./icefall-asr-librispeech-pruned-transducer-stateless3-2022-05-13/data/lang_bpe_500/tokens.txt \
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./icefall-asr-librispeech-pruned-transducer-stateless3-2022-05-13/test_wavs/1089-134686-0001.wav
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time ./build/bin/sherpa-onnx \
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./icefall-asr-librispeech-pruned-transducer-stateless3-2022-05-13/exp/onnx/encoder.onnx \
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./icefall-asr-librispeech-pruned-transducer-stateless3-2022-05-13/exp/onnx/decoder.onnx \
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./icefall-asr-librispeech-pruned-transducer-stateless3-2022-05-13/exp/onnx/joiner.onnx \
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./icefall-asr-librispeech-pruned-transducer-stateless3-2022-05-13/exp/onnx/joiner_encoder_proj.onnx \
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./icefall-asr-librispeech-pruned-transducer-stateless3-2022-05-13/exp/onnx/joiner_decoder_proj.onnx \
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./icefall-asr-librispeech-pruned-transducer-stateless3-2022-05-13/data/lang_bpe_500/tokens.txt \
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./icefall-asr-librispeech-pruned-transducer-stateless3-2022-05-13/test_wavs/1221-135766-0001.wav
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./icefall-asr-librispeech-pruned-transducer-stateless3-2022-05-13/exp/onnx/encoder.onnx \
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./icefall-asr-librispeech-pruned-transducer-stateless3-2022-05-13/exp/onnx/decoder.onnx \
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./icefall-asr-librispeech-pruned-transducer-stateless3-2022-05-13/exp/onnx/joiner.onnx \
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./icefall-asr-librispeech-pruned-transducer-stateless3-2022-05-13/exp/onnx/joiner_encoder_proj.onnx \
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./icefall-asr-librispeech-pruned-transducer-stateless3-2022-05-13/exp/onnx/joiner_decoder_proj.onnx \
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./icefall-asr-librispeech-pruned-transducer-stateless3-2022-05-13/data/lang_bpe_500/tokens.txt \
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./icefall-asr-librispeech-pruned-transducer-stateless3-2022-05-13/test_wavs/1221-135766-0002.wav
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1
.gitignore
vendored
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1
.gitignore
vendored
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@@ -0,0 +1 @@
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build
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@@ -38,7 +38,8 @@ set(CMAKE_CXX_EXTENSIONS OFF)
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list(APPEND CMAKE_MODULE_PATH ${CMAKE_SOURCE_DIR}/cmake/Modules)
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list(APPEND CMAKE_MODULE_PATH ${CMAKE_SOURCE_DIR}/cmake)
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include(cmake/kaldi_native_io.cmake)
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include(cmake/kaldi-native-fbank.cmake)
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include(kaldi_native_io)
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include(kaldi-native-fbank)
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include(onnxruntime)
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add_subdirectory(sherpa-onnx)
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@@ -1,27 +1,39 @@
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if(DEFINED ENV{KALDI_NATIVE_IO_INSTALL_PREFIX})
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message(STATUS "Using environment variable KALDI_NATIVE_IO_INSTALL_PREFIX: $ENV{KALDI_NATIVE_IO_INSTALL_PREFIX}")
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set(KALDI_NATIVE_IO_CMAKE_PREFIX_PATH $ENV{KALDI_NATIVE_IO_INSTALL_PREFIX})
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else()
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# PYTHON_EXECUTABLE is set by cmake/pybind11.cmake
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message(STATUS "Python executable: ${PYTHON_EXECUTABLE}")
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function(download_kaldi_native_io)
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if(CMAKE_VERSION VERSION_LESS 3.11)
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# FetchContent is available since 3.11,
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# we've copied it to ${CMAKE_SOURCE_DIR}/cmake/Modules
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# so that it can be used in lower CMake versions.
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message(STATUS "Use FetchContent provided by sherpa-onnx")
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list(APPEND CMAKE_MODULE_PATH ${CMAKE_SOURCE_DIR}/cmake/Modules)
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endif()
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execute_process(
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COMMAND "${PYTHON_EXECUTABLE}" -c "import kaldi_native_io; print(kaldi_native_io.cmake_prefix_path)"
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OUTPUT_STRIP_TRAILING_WHITESPACE
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OUTPUT_VARIABLE KALDI_NATIVE_IO_CMAKE_PREFIX_PATH
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include(FetchContent)
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set(kaldi_native_io_URL "https://github.com/csukuangfj/kaldi_native_io/archive/refs/tags/v1.15.1.tar.gz")
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set(kaldi_native_io_HASH "SHA256=97377e1d61e99d8fc1d6037a418d3037522dfa46337e06162e24b1d97f3d70a6")
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set(KALDI_NATIVE_IO_BUILD_TESTS OFF CACHE BOOL "" FORCE)
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set(KALDI_NATIVE_IO_BUILD_PYTHON OFF CACHE BOOL "" FORCE)
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FetchContent_Declare(kaldi_native_io
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URL ${kaldi_native_io_URL}
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URL_HASH ${kaldi_native_io_HASH}
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)
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endif()
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message(STATUS "KALDI_NATIVE_IO_CMAKE_PREFIX_PATH: ${KALDI_NATIVE_IO_CMAKE_PREFIX_PATH}")
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list(APPEND CMAKE_PREFIX_PATH "${KALDI_NATIVE_IO_CMAKE_PREFIX_PATH}")
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FetchContent_GetProperties(kaldi_native_io)
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if(NOT kaldi_native_io_POPULATED)
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message(STATUS "Downloading kaldi_native_io ${kaldi_native_io_URL}")
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FetchContent_Populate(kaldi_native_io)
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endif()
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message(STATUS "kaldi_native_io is downloaded to ${kaldi_native_io_SOURCE_DIR}")
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message(STATUS "kaldi_native_io's binary dir is ${kaldi_native_io_BINARY_DIR}")
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find_package(kaldi_native_io REQUIRED)
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add_subdirectory(${kaldi_native_io_SOURCE_DIR} ${kaldi_native_io_BINARY_DIR} EXCLUDE_FROM_ALL)
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message(STATUS "KALDI_NATIVE_IO_FOUND: ${KALDI_NATIVE_IO_FOUND}")
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message(STATUS "KALDI_NATIVE_IO_VERSION: ${KALDI_NATIVE_IO_VERSION}")
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message(STATUS "KALDI_NATIVE_IO_INCLUDE_DIRS: ${KALDI_NATIVE_IO_INCLUDE_DIRS}")
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message(STATUS "KALDI_NATIVE_IO_CXX_FLAGS: ${KALDI_NATIVE_IO_CXX_FLAGS}")
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message(STATUS "KALDI_NATIVE_IO_LIBRARIES: ${KALDI_NATIVE_IO_LIBRARIES}")
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target_include_directories(kaldi_native_io_core
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PUBLIC
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${kaldi_native_io_SOURCE_DIR}/
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)
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endfunction()
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set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} ${KALDI_NATIVE_IO_CXX_FLAGS}")
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message(STATUS "CMAKE_CXX_FLAGS: ${CMAKE_CXX_FLAGS}")
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download_kaldi_native_io()
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55
cmake/onnxruntime.cmake
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55
cmake/onnxruntime.cmake
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@@ -0,0 +1,55 @@
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function(download_onnxruntime)
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if(CMAKE_VERSION VERSION_LESS 3.11)
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# FetchContent is available since 3.11,
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# we've copied it to ${CMAKE_SOURCE_DIR}/cmake/Modules
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# so that it can be used in lower CMake versions.
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message(STATUS "Use FetchContent provided by sherpa-onnx")
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list(APPEND CMAKE_MODULE_PATH ${CMAKE_SOURCE_DIR}/cmake/Modules)
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endif()
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include(FetchContent)
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if(UNIX AND NOT APPLE)
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# set(onnxruntime_URL "http://github.com/microsoft/onnxruntime/releases/download/v1.12.1/onnxruntime-linux-x64-1.12.1.tgz")
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# If you don't have access to the internet, you can first download onnxruntime to some directory, and the use
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# set(onnxruntime_URL "file:///ceph-fj/fangjun/open-source/sherpa-onnx/onnxruntime-linux-x64-1.12.1.tgz")
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set(onnxruntime_HASH "SHA256=8f6eb9e2da9cf74e7905bf3fc687ef52e34cc566af7af2f92dafe5a5d106aa3d")
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# After downloading, it contains:
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# ./lib/libonnxruntime.so.1.12.1
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# ./lib/libonnxruntime.so, which is a symlink to lib/libonnxruntime.so.1.12.1
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#
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# ./include
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# It contains all the needed header files
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else()
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message(FATAL_ERROR "Only support Linux at present. Will support other OSes later")
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endif()
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FetchContent_Declare(onnxruntime
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URL ${onnxruntime_URL}
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URL_HASH ${onnxruntime_HASH}
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)
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FetchContent_GetProperties(onnxruntime)
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if(NOT onnxruntime_POPULATED)
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message(STATUS "Downloading onnxruntime ${onnxruntime_URL}")
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FetchContent_Populate(onnxruntime)
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endif()
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message(STATUS "onnxruntime is downloaded to ${onnxruntime_SOURCE_DIR}")
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find_library(location_onnxruntime onnxruntime
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PATHS
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"${onnxruntime_SOURCE_DIR}/lib"
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)
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message(STATUS "location_onnxruntime: ${location_onnxruntime}")
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add_library(onnxruntime SHARED IMPORTED)
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set_target_properties(onnxruntime PROPERTIES
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IMPORTED_LOCATION ${location_onnxruntime}
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INTERFACE_INCLUDE_DIRECTORIES "${onnxruntime_SOURCE_DIR}/include"
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)
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endfunction()
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download_onnxruntime()
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@@ -1,13 +1,8 @@
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add_executable(online-fbank-test online-fbank-test.cc)
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target_link_libraries(online-fbank-test kaldi-native-fbank-core)
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include_directories(
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${ONNXRUNTIME_ROOTDIR}/include/onnxruntime/core/session/
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${ONNXRUNTIME_ROOTDIR}/include/onnxruntime/core/providers/tensorrt/
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)
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include_directories(
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${KALDINATIVEIO}
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)
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include_directories(${CMAKE_SOURCE_DIR})
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add_executable(sherpa-onnx main.cpp)
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target_link_libraries(sherpa-onnx onnxruntime kaldi-native-fbank-core kaldi_native_io_core)
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target_link_libraries(sherpa-onnx
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onnxruntime
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kaldi-native-fbank-core
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kaldi_native_io_core
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)
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@@ -1,101 +1,99 @@
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#include <vector>
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#include <iostream>
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#include <algorithm>
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#include <time.h>
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#include <math.h>
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#include <fstream>
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||||
#include <iostream>
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#include <math.h>
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#include <time.h>
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#include <vector>
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#include "fbank_features.h"
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#include "rnnt_beam_search.h"
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#include "sherpa-onnx/csrc/fbank_features.h"
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#include "sherpa-onnx/csrc/rnnt_beam_search.h"
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#include "kaldi-native-fbank/csrc/online-feature.h"
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int main(int argc, char *argv[]) {
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char *encoder_path = argv[1];
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char *decoder_path = argv[2];
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char *joiner_path = argv[3];
|
||||
char *joiner_encoder_proj_path = argv[4];
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char *joiner_decoder_proj_path = argv[5];
|
||||
char *token_path = argv[6];
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std::string search_method = argv[7];
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char *filename = argv[8];
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|
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int main(int argc, char* argv[]) {
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char* encoder_path = argv[1];
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char* decoder_path = argv[2];
|
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char* joiner_path = argv[3];
|
||||
char* joiner_encoder_proj_path = argv[4];
|
||||
char* joiner_decoder_proj_path = argv[5];
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||||
char* token_path = argv[6];
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||||
std::string search_method = argv[7];
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||||
char* filename = argv[8];
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||||
// General parameters
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||||
int numberOfThreads = 16;
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||||
|
||||
// General parameters
|
||||
int numberOfThreads = 16;
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||||
// Initialize fbanks
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||||
knf::FbankOptions opts;
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||||
opts.frame_opts.dither = 0;
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||||
opts.frame_opts.samp_freq = 16000;
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||||
opts.frame_opts.frame_shift_ms = 10.0f;
|
||||
opts.frame_opts.frame_length_ms = 25.0f;
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||||
opts.mel_opts.num_bins = 80;
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opts.frame_opts.window_type = "povey";
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||||
opts.frame_opts.snip_edges = false;
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knf::OnlineFbank fbank(opts);
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||||
|
||||
// Initialize fbanks
|
||||
knf::FbankOptions opts;
|
||||
opts.frame_opts.dither = 0;
|
||||
opts.frame_opts.samp_freq = 16000;
|
||||
opts.frame_opts.frame_shift_ms = 10.0f;
|
||||
opts.frame_opts.frame_length_ms = 25.0f;
|
||||
opts.mel_opts.num_bins = 80;
|
||||
opts.frame_opts.window_type = "povey";
|
||||
opts.frame_opts.snip_edges = false;
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knf::OnlineFbank fbank(opts);
|
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// set session opts
|
||||
// https://onnxruntime.ai/docs/performance/tune-performance.html
|
||||
session_options.SetIntraOpNumThreads(numberOfThreads);
|
||||
session_options.SetInterOpNumThreads(numberOfThreads);
|
||||
session_options.SetGraphOptimizationLevel(
|
||||
GraphOptimizationLevel::ORT_ENABLE_EXTENDED);
|
||||
session_options.SetLogSeverityLevel(4);
|
||||
session_options.SetExecutionMode(ExecutionMode::ORT_SEQUENTIAL);
|
||||
|
||||
// set session opts
|
||||
// https://onnxruntime.ai/docs/performance/tune-performance.html
|
||||
session_options.SetIntraOpNumThreads(numberOfThreads);
|
||||
session_options.SetInterOpNumThreads(numberOfThreads);
|
||||
session_options.SetGraphOptimizationLevel(GraphOptimizationLevel::ORT_ENABLE_EXTENDED);
|
||||
session_options.SetLogSeverityLevel(4);
|
||||
session_options.SetExecutionMode(ExecutionMode::ORT_SEQUENTIAL);
|
||||
|
||||
api.CreateTensorRTProviderOptions(&tensorrt_options);
|
||||
std::unique_ptr<OrtTensorRTProviderOptionsV2, decltype(api.ReleaseTensorRTProviderOptions)> rel_trt_options(tensorrt_options, api.ReleaseTensorRTProviderOptions);
|
||||
api.SessionOptionsAppendExecutionProvider_TensorRT_V2(static_cast<OrtSessionOptions*>(session_options), rel_trt_options.get());
|
||||
api.CreateTensorRTProviderOptions(&tensorrt_options);
|
||||
std::unique_ptr<OrtTensorRTProviderOptionsV2,
|
||||
decltype(api.ReleaseTensorRTProviderOptions)>
|
||||
rel_trt_options(tensorrt_options, api.ReleaseTensorRTProviderOptions);
|
||||
api.SessionOptionsAppendExecutionProvider_TensorRT_V2(
|
||||
static_cast<OrtSessionOptions *>(session_options), rel_trt_options.get());
|
||||
|
||||
// Define model
|
||||
auto model = get_model(
|
||||
encoder_path,
|
||||
decoder_path,
|
||||
joiner_path,
|
||||
joiner_encoder_proj_path,
|
||||
joiner_decoder_proj_path,
|
||||
token_path
|
||||
);
|
||||
|
||||
std::vector<std::string> filename_list {
|
||||
filename
|
||||
};
|
||||
// Define model
|
||||
auto model =
|
||||
get_model(encoder_path, decoder_path, joiner_path,
|
||||
joiner_encoder_proj_path, joiner_decoder_proj_path, token_path);
|
||||
|
||||
for (auto filename : filename_list){
|
||||
std::cout << filename << std::endl;
|
||||
auto samples = readWav(filename, true);
|
||||
int numSamples = samples.NumCols();
|
||||
std::vector<std::string> filename_list{filename};
|
||||
|
||||
auto features = ComputeFeatures(fbank, opts, samples);
|
||||
for (auto filename : filename_list) {
|
||||
std::cout << filename << std::endl;
|
||||
auto samples = readWav(filename, true);
|
||||
int numSamples = samples.NumCols();
|
||||
|
||||
auto tic = std::chrono::high_resolution_clock::now();
|
||||
auto features = ComputeFeatures(fbank, opts, samples);
|
||||
|
||||
// # === Encoder Out === #
|
||||
int num_frames = features.size() / opts.mel_opts.num_bins;
|
||||
auto encoder_out = model.encoder_forward(features,
|
||||
std::vector<int64_t> {num_frames},
|
||||
std::vector<int64_t> {1, num_frames, 80},
|
||||
std::vector<int64_t> {1},
|
||||
memory_info);
|
||||
auto tic = std::chrono::high_resolution_clock::now();
|
||||
|
||||
// # === Search === #
|
||||
std::vector<std::vector<int32_t>> hyps;
|
||||
if (search_method == "greedy")
|
||||
hyps = GreedySearch(&model, &encoder_out);
|
||||
else{
|
||||
std::cout << "wrong search method!" << std::endl;
|
||||
exit(0);
|
||||
}
|
||||
auto results = hyps2result(model.tokens_map, hyps);
|
||||
// # === Encoder Out === #
|
||||
int num_frames = features.size() / opts.mel_opts.num_bins;
|
||||
auto encoder_out =
|
||||
model.encoder_forward(features, std::vector<int64_t>{num_frames},
|
||||
std::vector<int64_t>{1, num_frames, 80},
|
||||
std::vector<int64_t>{1}, memory_info);
|
||||
|
||||
// # === Print Elapsed Time === #
|
||||
auto elapsed = std::chrono::duration_cast<std::chrono::milliseconds>(std::chrono::high_resolution_clock::now() - tic);
|
||||
std::cout << "Elapsed: " << float(elapsed.count()) / 1000 << " seconds" << std::endl;
|
||||
std::cout << "rtf: " << float(elapsed.count()) / 1000 / (numSamples / 16000) << std::endl;
|
||||
|
||||
print_hyps(hyps);
|
||||
std::cout << results[0] << std::endl;
|
||||
// # === Search === #
|
||||
std::vector<std::vector<int32_t>> hyps;
|
||||
if (search_method == "greedy")
|
||||
hyps = GreedySearch(&model, &encoder_out);
|
||||
else {
|
||||
std::cout << "wrong search method!" << std::endl;
|
||||
exit(0);
|
||||
}
|
||||
auto results = hyps2result(model.tokens_map, hyps);
|
||||
|
||||
return 0;
|
||||
// # === Print Elapsed Time === #
|
||||
auto elapsed = std::chrono::duration_cast<std::chrono::milliseconds>(
|
||||
std::chrono::high_resolution_clock::now() - tic);
|
||||
std::cout << "Elapsed: " << float(elapsed.count()) / 1000 << " seconds"
|
||||
<< std::endl;
|
||||
std::cout << "rtf: " << float(elapsed.count()) / 1000 / (numSamples / 16000)
|
||||
<< std::endl;
|
||||
|
||||
print_hyps(hyps);
|
||||
std::cout << results[0] << std::endl;
|
||||
}
|
||||
|
||||
return 0;
|
||||
}
|
||||
|
||||
@@ -61,7 +61,6 @@ std::vector<std::vector<int32_t>> GreedySearch(
|
||||
auto projected_encoder_out = model->joiner_encoder_proj_forward(encoder_out_vector,
|
||||
std::vector<int64_t> {encoder_out_dim1, encoder_out_dim2},
|
||||
memory_info);
|
||||
|
||||
Ort::Value &projected_encoder_out_tensor = projected_encoder_out[0];
|
||||
int projected_encoder_out_dim1 = projected_encoder_out_tensor.GetTensorTypeAndShapeInfo().GetShape()[0];
|
||||
int projected_encoder_out_dim2 = projected_encoder_out_tensor.GetTensorTypeAndShapeInfo().GetShape()[1];
|
||||
@@ -78,12 +77,12 @@ std::vector<std::vector<int32_t>> GreedySearch(
|
||||
|
||||
auto logits = model->joiner_forward(cur_encoder_out,
|
||||
projected_decoder_out_vector,
|
||||
std::vector<int64_t> {1, 1, 1, projected_encoder_out_dim2},
|
||||
std::vector<int64_t> {1, 1, 1, projected_decoder_out_dim},
|
||||
std::vector<int64_t> {1, projected_encoder_out_dim2},
|
||||
std::vector<int64_t> {1, projected_decoder_out_dim},
|
||||
memory_info);
|
||||
|
||||
Ort::Value &logits_tensor = logits[0];
|
||||
int logits_dim = logits_tensor.GetTensorTypeAndShapeInfo().GetShape()[3];
|
||||
int logits_dim = logits_tensor.GetTensorTypeAndShapeInfo().GetShape()[1];
|
||||
auto logits_vector = ortVal2Vector(logits_tensor, logits_dim);
|
||||
|
||||
int max_indices = static_cast<int>(std::distance(logits_vector.begin(), std::max_element(logits_vector.begin(), logits_vector.end())));
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#include <iostream>
|
||||
#include <onnxruntime_cxx_api.h>
|
||||
#include "onnxruntime_cxx_api.h"
|
||||
|
||||
Ort::Env env(ORT_LOGGING_LEVEL_WARNING, "test");
|
||||
const auto& api = Ort::GetApi();
|
||||
|
||||
Reference in New Issue
Block a user