DirectMLを使用する

.github/workflows/build.yml

@@ -24,32 +24,37 @@ jobs:
             device: gpu
             python_architecture: 'x64'
             onnxruntime_url: https://github.com/microsoft/onnxruntime/releases/download/v1.10.0/onnxruntime-win-x64-gpu-1.10.0.zip
-            artifact_name: windows-x64-gpu
+            artifact_name: windows-x64-cuda
 
           - os: windows-2019
-            device: cpu-x64
+            device: directml-x64
             python_architecture: 'x64'
-            onnxruntime_url: https://github.com/microsoft/onnxruntime/releases/download/v1.10.0/onnxruntime-win-x64-1.10.0.zip
-            artifact_name: windows-x64-cpu
+            onnxruntime_url: https://github.com/microsoft/onnxruntime/releases/download/v1.10.0/Microsoft.ML.OnnxRuntime.DirectML.1.10.0.zip
+            directml_url: https://www.nuget.org/api/v2/package/Microsoft.AI.DirectML/1.8.0
+            artifact_name: windows-x64-directml
+            cmake_additional_options: -DDIRECTML=ON -DDIRECTML_DIR=download/directml
 
           - os: windows-2019
-            device: cpu-x86
+            device: directml-x86
             python_architecture: 'x86'
-            onnxruntime_url: https://github.com/microsoft/onnxruntime/releases/download/v1.10.0/onnxruntime-win-x86-1.10.0.zip
-            cmake_additional_options: -DCMAKE_GENERATOR_PLATFORM=Win32
-            artifact_name: windows-x86-cpu
+            onnxruntime_url: https://github.com/microsoft/onnxruntime/releases/download/v1.10.0/Microsoft.ML.OnnxRuntime.DirectML.1.10.0.zip
+            directml_url: https://www.nuget.org/api/v2/package/Microsoft.AI.DirectML/1.8.0
+            cmake_additional_options: -DCMAKE_GENERATOR_PLATFORM=Win32 -DDIRECTML=ON -DDIRECTML_DIR=download/directml
+            artifact_name: windows-x86-directml
 
           - os: windows-2019
-            device: cpu-arm64
-            onnxruntime_url: https://github.com/microsoft/onnxruntime/releases/download/v1.10.0/onnxruntime-win-arm64-1.10.0.zip
-            cmake_additional_options: -DCMAKE_GENERATOR_PLATFORM=arm64
-            artifact_name: windows-arm64-cpu
+            device: directml-arm64
+            onnxruntime_url: https://github.com/microsoft/onnxruntime/releases/download/v1.10.0/Microsoft.ML.OnnxRuntime.DirectML.1.10.0.zip
+            directml_url: https://www.nuget.org/api/v2/package/Microsoft.AI.DirectML/1.8.0
+            cmake_additional_options: -DCMAKE_GENERATOR_PLATFORM=arm64 -DDIRECTML=ON -DDIRECTML_DIR=download/directml
+            artifact_name: windows-arm64-directml
 
           - os: windows-2019
-            device: cpu-arm
-            onnxruntime_url: https://github.com/microsoft/onnxruntime/releases/download/v1.10.0/onnxruntime-win-arm-1.10.0.zip
-            cmake_additional_options: -DCMAKE_GENERATOR_PLATFORM=arm
-            artifact_name: windows-arm-cpu
+            device: directml-arm
+            onnxruntime_url: https://github.com/microsoft/onnxruntime/releases/download/v1.10.0/Microsoft.ML.OnnxRuntime.DirectML.1.10.0.zip
+            directml_url: https://www.nuget.org/api/v2/package/Microsoft.AI.DirectML/1.8.0
+            cmake_additional_options: -DCMAKE_GENERATOR_PLATFORM=arm -DDIRECTML=ON -DDIRECTML_DIR=download/directml
+            artifact_name: windows-arm-directml
 
           - os: macos-10.15
             device: cpu-x64
@@ -122,6 +127,19 @@ jobs:
           key: onnxruntime-cache-v1-${{ hashFiles('download/onnxruntime_url.txt') }}
           path: download/onnxruntime
 
+      - name: Export DirectML url to calc hash
+        if: endswith(matrix.artifact_name, '-directml')
+        shell: bash
+        run: echo "${{matrix.directml_url}}" >> download/directml_url.txt
+
+      - name: Cache DirectML
+        if: endswith(matrix.artifact_name, '-directml')
+        uses: actions/cache@v2
+        id: directml-cache
+        with:
+          key: directml-cache-v1-${{ hashFiles('download/directml_url.txt') }}
+          path: download/directml
+
       # download/onnxruntime/lib/onnxruntime.dll
       - name: Download ONNX Runtime (zip)
         if: steps.onnxruntime-cache.outputs.cache-hit != 'true' && endsWith(matrix.onnxruntime_url, '.zip')
@@ -133,11 +151,14 @@ jobs:
           # strip-components
           TEMPDIR=$(mktemp -d)
           unzip download/onnxruntime.zip -d "${TEMPDIR}"
-          mv "${TEMPDIR}"/*/* download/onnxruntime/
+          mv "${TEMPDIR}"/* download/onnxruntime/.
           rm -rf "${TEMPDIR}"
 
           rm download/onnxruntime.zip
 
+      - run: ls download
+      - run: ls download/onnxruntime
+
       # download/onnxruntime/lib/libonnxruntime.so
       # download/onnxruntime/lib/libonnxruntime.dylib
       - name: Download ONNX Runtime (tgz)
@@ -149,6 +170,24 @@ jobs:
           tar xf download/onnxruntime.tgz -C download/onnxruntime --strip-components 1
           rm download/onnxruntime.tgz
 
+      # download directml
+      - name: Download DirectML
+        if: steps.directml-cache.outputs.cache-hit != 'true' && endswith(matrix.artifact_name, '-directml')
+        shell: bash
+        run: |
+          curl -L "${{matrix.directml_url}}" -o download/directml.zip
+          mkdir -p download/directml
+
+          # strip-components
+          TEMPDIR=$(mktemp -d)
+          unzip download/directml.zip -d "${TEMPDIR}"
+          mv "${TEMPDIR}"/* download/directml/.
+          rm -rf "${TEMPDIR}"
+
+          rm download/directml.zip
+
+          ls download/directml
+
       # Build
       - if: startsWith(matrix.os, 'windows')
         uses: ilammy/msvc-dev-cmd@v1
@@ -255,16 +294,16 @@ jobs:
           mkdir release
 
           readarray -t MAPPINGS <<EOF
-          windows-x64-gpu     core.dll      core_gpu_x64_nvidia.dll
-          windows-x64-cpu     core.dll      core_cpu_x64.dll
-          windows-x86-cpu     core.dll      core_cpu_x86.dll
-          windows-arm64-cpu   core.dll      core_cpu_arm64.dll
-          windows-arm-cpu     core.dll      core_cpu_arm.dll
-          osx-universal2-cpu  libcore.dylib libcore_cpu_universal2.dylib
-          linux-x64-gpu       libcore.so    libcore_gpu_x64_nvidia.so
-          linux-x64-cpu       libcore.so    libcore_cpu_x64.so
-          linux-armhf-cpu     libcore.so    libcore_cpu_armhf.so
-          linux-arm64-cpu     libcore.so    libcore_cpu_arm64.so
+          windows-x64-cuda       core.dll      core_gpu_x64_nvidia.dll
+          windows-x64-directml   core.dll      core_gpu_x64_directml.dll
+          windows-x86-directml   core.dll      core_gpu_x86_directml.dll
+          windows-arm64-directml core.dll      core_gpu_arm64_directml.dll
+          windows-arm-directml   core.dll      core_gpu_arm_directml.dll
+          osx-universal2-cpu     libcore.dylib libcore_cpu_universal2.dylib
+          linux-x64-gpu          libcore.so    libcore_gpu_x64_nvidia.so
+          linux-x64-cpu          libcore.so    libcore_cpu_x64.so
+          linux-armhf-cpu        libcore.so    libcore_cpu_armhf.so
+          linux-arm64-cpu        libcore.so    libcore_cpu_arm64.so
           EOF
 
           for line in "${MAPPINGS[@]}"; do

.gitignore

@@ -8,6 +8,9 @@
 # ONNX
 onnxruntime*/
 
+# DirectML
+directml*/
+
 # Build artifacts
 build/
 lib/

CMakeLists.txt

@@ -4,4 +4,13 @@ project(VoiceVoxCore)
 # TODO: download onnxruntime
 set(ONNXRUNTIME_DIR "${CMAKE_CURRENT_SOURCE_DIR}/onnxruntime" CACHE PATH "Path to ONNX Runtime")
 
+option(DIRECTML "Enables building for DirectML" OFF)
+set(DIRECTML_DIR "${CMAKE_CURRENT_SOURCE_DIR}/directml" CACHE PATH "Path to ONNX Runtime")
+if(DIRECTML)
+  # DirectML読み込み用にCPUのアーキテクチャを求める
+  set(DML_ARCH)
+  include(${CMAKE_CURRENT_SOURCE_DIR}/DetermineTargetArchitecture.cmake)
+  determine_target_architecture(DML_ARCH)
+endif()
+
 add_subdirectory(core)

DetermineTargetArchitecture.cmake

@@ -0,0 +1,62 @@
+# https://github.com/civetweb/civetweb/blob/master/cmake/DetermineTargetArchitecture.cmake
+#
+# Copyright (c) 2013-2021 The CivetWeb developers (https://github.com/civetweb/civetweb/blob/master/CREDITS.md)
+# Copyright (c) 2004-2013 Sergey Lyubka
+# Copyright (c) 2013 No Face Press, LLC (Thomas Davis)
+# Copyright (c) 2013 F-Secure Corporation
+#
+# Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
+#
+# The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
+# 
+# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
+# 
+# - Determines the target architecture of the compilation
+#
+# This function checks the architecture that will be built by the compiler
+# and sets a variable to the architecture
+#
+#  determine_target_architecture(<OUTPUT_VAR>)
+#
+# - Example
+#
+# include(DetermineTargetArchitecture)
+# determine_target_architecture(PROJECT_NAME_ARCHITECTURE)
+
+if(__determine_target_architecture)
+  return()
+endif()
+set(__determine_target_architecture INCLUDED)
+
+function(determine_target_architecture FLAG)
+  if (MSVC)
+    if("${MSVC_C_ARCHITECTURE_ID}" STREQUAL "X86")
+      set(ARCH "x86")
+    elseif("${MSVC_C_ARCHITECTURE_ID}" STREQUAL "x64")
+      set(ARCH "x64")
+    elseif("${MSVC_C_ARCHITECTURE_ID}" STREQUAL "ARM64")
+      set(ARCH "arm64")
+    elseif("${MSVC_C_ARCHITECTURE_ID}" MATCHES  "ARM*")
+      set(ARCH "arm")
+    else()
+      message(FATAL_ERROR "Failed to determine the MSVC target architecture: ${MSVC_C_ARCHITECTURE_ID}")
+    endif()
+  else()
+    execute_process(
+      COMMAND ${CMAKE_C_COMPILER} -dumpmachine
+      RESULT_VARIABLE RESULT
+      OUTPUT_VARIABLE ARCH
+      ERROR_QUIET
+    )
+    if (RESULT)
+      message(FATAL_ERROR "Failed to determine target architecture triplet: ${RESULT}")
+    endif()
+    string(REGEX MATCH "([^-]+).*" ARCH_MATCH ${ARCH})
+    if (NOT CMAKE_MATCH_1 OR NOT ARCH_MATCH)
+      message(FATAL_ERROR "Failed to match the target architecture triplet: ${ARCH}")
+    endif()
+    set(ARCH ${CMAKE_MATCH_1})
+  endif()
+  message(STATUS "Target architecture - ${ARCH}")
+  set(${FLAG} ${ARCH} PARENT_SCOPE)
+endfunction()

README.md

@@ -26,8 +26,13 @@ pip install .
 - ONNX Runtime v1.9.0/v1.9.1
 
 #### GPUを使用する場合
+##### CUDA
+Windows, Linux上でnvidia製GPUを使用してCUDAを用いた合成を行う場合、[CUDA 11.1](https://developer.nvidia.com/cuda-11.1.0-download-archive),[CUDNN](https://developer.nvidia.com/cudnn)のインストールに加えてGPU に対応した [ONNXRUNTIME](https://github.com/microsoft/onnxruntime) のダウンロードが必要です。
 
-Windows, Linux上でnvidia製GPUを使用する場合、CUDA11.1,CUDNNのインストールに加えてGPU に対応した [ONNXRUNTIME](https://github.com/microsoft/onnxruntime) のダウンロードが必要です。
+##### DirectML
+Windows上でDirectX12に対応したGPUを使用してDirectMLを用いた合成を行う場合、[DirectML](https://www.nuget.org/packages/Microsoft.AI.DirectML)及びDirectMLに対応した[ONNXRUNTIME](https://github.com/microsoft/onnxruntime) のダウンロードが必要です。
+
+DirectMLは.nupkgファイルで提供されますが、拡張子を.zipに変更した上で、リポジトリに`directml`というディレクトリ名で展開してください。
 
 
 #### Raspberry Pi (armhf)の場合
@@ -61,10 +66,19 @@ pip install .
 ### 注意
 #### GPUの使用について
 
+##### CUDA
 nvidia製GPUを搭載したWindows, Linux PCではCUDAを用いた合成が可能です。
 CUDAを使用する場合、[CUDA 11.1](https://developer.nvidia.com/cuda-11.1.0-download-archive) と [CUDNN](https://developer.nvidia.com/cudnn) をインストールした上で、環境構築時、上記例の代わりに
 ```bash
-python configure.py --use_gpu
+python configure.py --use_cuda
+```
+を実行する必要があります
+
+##### DirectML
+DirectX12に対応したGPUを搭載したWindows PCではDirectMLを用いた合成が可能です
+DirectMLを使用する場合、環境構築時、上記例の代わりに
+```bash 
+python configure.py --use_directml
 ```
 を実行する必要があります
 
@@ -116,14 +130,18 @@ python run.py \
 ## コアライブラリのビルド
 
 [Releases](https://github.com/Hiroshiba/voicevox_core/releases) にあるビルド済みのコアライブラリを利用せず、自分で一からビルドする場合こちらを参照してください。ビルドにはONNXRUNTIMEに加えてCMake 3.16以上が必要です。
+
 modelフォルダにあるonnxモデルはダミーのため、ノイズの混じった音声が出力されます
 
 ```bash
 # C++モジュールのビルド
 mkdir build
 cd build
-# もしダウンロードしたonnx runtimeが別のところにあるなら、以下のコマンドを
-# cmake .. -DONNXRUNTIME_DIR=(ダウンロードしたonnx runtimeのパス) に変更する。
+
+# cmake .. 時のオプション
+# -DONNXRUNTIME_DIR=(パス) ダウンロードしたonnxruntimeが別フォルダにある時指定
+# -DDIRECTML=ON             DirectMLを使用する場合指定
+# -DDIRECTML_DIR=(パス)    ダウンロードしたDirectMLが別フォルダにある時指定
 cmake ..
 cmake --build . --config Release
 cmake --install .