whisper : reduce delta_min from 1000ms to 100ms

ggml-ci

.github/workflows/build.yml

@@ -6,17 +6,81 @@ on:
       - master
   pull_request:
     types: [opened, synchronize, reopened]
+  workflow_dispatch:
+    inputs:
+      create_release:
+        description: 'Create new release'
+        required: true
+        type: boolean
+      pre_release_tag:
+        description: 'Pre-release tag name'
+        required: false
+        type: string
+      run_type:
+        description: 'Workflow type to run'
+        required: true
+        type: choice
+        options:
+          - full-ci
+          - release-only
 
 concurrency:
   group: ${{ github.workflow }}-${{ github.head_ref && github.ref || github.run_id }}
   cancel-in-progress: true
 
+permissions:
+  contents: write  # for creating release
+
 env:
+  BRANCH_NAME: ${{ github.head_ref || github.ref_name }}
   ubuntu_image: "ubuntu:22.04"
   VCPKG_BINARY_SOURCES: "clear;x-gha,readwrite"
 
 jobs:
+  determine-tag:
+    runs-on: ubuntu-latest
+    outputs:
+      tag_name: ${{ steps.tag.outputs.name }}
+
+    steps:
+      - name: Checkout with full history
+        uses: actions/checkout@v4
+        with:
+          fetch-depth: 0
+
+      - name: Determine tag name
+        id: tag
+        shell: bash
+        run: |
+          BUILD_NUMBER=$(git rev-list --count HEAD)
+          SHORT_HASH=$(git rev-parse --short=7 HEAD)
+          CUSTOM_TAG="${{ github.event.inputs.pre_release_tag }}"
+
+          echo "Raw values:"
+          echo "BUILD_NUMBER: $BUILD_NUMBER"
+          echo "SHORT_HASH: $SHORT_HASH"
+          echo "BRANCH_NAME: ${{ env.BRANCH_NAME }}"
+          echo "CUSTOM_TAG: $CUSTOM_TAG"
+
+          # Use custom tag if provided
+          if [[ -n "$CUSTOM_TAG" ]]; then
+            echo "Using custom tag"
+            TAG_NAME="${CUSTOM_TAG}"
+          elif [[ "${{ env.BRANCH_NAME }}" == "master" ]]; then
+            echo "Using master branch format"
+            TAG_NAME="b${BUILD_NUMBER}"
+          else
+            echo "Using non-master branch format"
+            SAFE_NAME=$(echo "${{ env.BRANCH_NAME }}" | tr '/' '-')
+            TAG_NAME="${SAFE_NAME}-b${BUILD_NUMBER}-${SHORT_HASH}"
+          fi
+
+          echo "Final tag name: $TAG_NAME"
+          echo "name=$TAG_NAME" >> $GITHUB_OUTPUT
+
   ubuntu-22:
+    if: ${{ github.event_name == 'push' || github.event_name == 'pull_request' ||
+            github.event.inputs.run_type == 'full-ci' }}
     runs-on: ubuntu-22.04
 
     strategy:
@@ -43,6 +107,8 @@ jobs:
             cmake --build build --config Release -j $(nproc)'
 
   ubuntu-22-arm64:
+    if: ${{ github.event_name == 'push' || github.event_name == 'pull_request' ||
+            github.event.inputs.run_type == 'full-ci' }}
     runs-on: ubuntu-22.04
 
     strategy:
@@ -69,6 +135,8 @@ jobs:
             cmake --build build --config Release -j $(nproc)'
 
   ubuntu-22-arm-v7:
+    if: ${{ github.event_name == 'push' || github.event_name == 'pull_request' ||
+            github.event.inputs.run_type == 'full-ci' }}
     runs-on: ubuntu-22.04
 
     strategy:
@@ -95,6 +163,8 @@ jobs:
             cmake --build build --config Release -j $(nproc)'
 
   macOS-latest:
+    if: ${{ github.event_name == 'push' || github.event_name == 'pull_request' ||
+            github.event.inputs.run_type == 'full-ci' }}
     runs-on: macOS-latest
 
     strategy:
@@ -129,31 +199,28 @@ jobs:
             -DCMAKE_OSX_ARCHITECTURES="arm64;x86_64"
           cmake --build build --config Release -j $(sysctl -n hw.logicalcpu)
 
-      - name: xcodebuild for swift package
-        id: xcodebuild
-        run: |
-          ./build-xcframework.sh
 
+  freeBSD-latest:
+    runs-on: macos-13
 
-#  freeBSD-latest:
-#    runs-on: macos-12
-#
-#    steps:
-#      - name: Clone
-#        uses: actions/checkout@v4
-#
-#      - name: Build
-#        uses: cross-platform-actions/action@v0.24.0
-#        with:
-#          operating_system: freebsd
-#          version: '13.3'
-#          run: |
-#            sudo pkg update
-#            sudo pkg install -y gmake sdl2 cmake
-#            cmake -B build
-#            cmake --build build --config Release
+    steps:
+      - name: Clone
+        uses: actions/checkout@v4
+
+      - name: Build
+        uses: cross-platform-actions/action@v0.27.0
+        with:
+          operating_system: freebsd
+          version: '14.2'
+          run: |
+            sudo pkg update
+            sudo pkg install -y gmake sdl2 cmake git
+            cmake -B build
+            cmake --build build --config Release
 
   ubuntu-22-gcc:
+    if: ${{ github.event_name == 'push' || github.event_name == 'pull_request' ||
+            github.event.inputs.run_type == 'full-ci' }}
     runs-on: ubuntu-22.04
 
     strategy:
@@ -182,6 +249,8 @@ jobs:
             ctest -L gh --output-on-failure'
 
   ubuntu-22-gcc-arm64:
+    if: ${{ github.event_name == 'push' || github.event_name == 'pull_request' ||
+            github.event.inputs.run_type == 'full-ci' }}
     runs-on: ubuntu-22.04
 
     strategy:
@@ -210,6 +279,8 @@ jobs:
             ctest -L gh --output-on-failure'
 
   ubuntu-22-gcc-arm-v7:
+    if: ${{ github.event_name == 'push' || github.event_name == 'pull_request' ||
+            github.event.inputs.run_type == 'full-ci' }}
     runs-on: ubuntu-22.04
 
     strategy:
@@ -238,6 +309,8 @@ jobs:
             ctest -L gh --output-on-failure'
 
   ubuntu-22-clang:
+    if: ${{ github.event_name == 'push' || github.event_name == 'pull_request' ||
+            github.event.inputs.run_type == 'full-ci' }}
     runs-on: ubuntu-22.04
 
     strategy:
@@ -269,6 +342,8 @@ jobs:
             ctest -L gh --output-on-failure'
 
   ubuntu-22-gcc-sanitized:
+    if: ${{ github.event_name == 'push' || github.event_name == 'pull_request' ||
+            github.event.inputs.run_type == 'full-ci' }}
     runs-on: ubuntu-22.04
 
     strategy:
@@ -292,11 +367,15 @@ jobs:
             set -e
             apt update
             apt install -y build-essential cmake git
-            cmake . -DCMAKE_BUILD_TYPE=Debug -DWHISPER_SANITIZE_${{ matrix.sanitizer }}=ON
+            cmake . -DCMAKE_BUILD_TYPE=Debug \
+              -DWHISPER_SANITIZE_${{ matrix.sanitizer }}=ON \
+              -DGGML_OPENMP=OFF
             make
             ctest -L gh --output-on-failure'
 
   ubuntu-22-cmake-sycl:
+    if: ${{ github.event_name == 'push' || github.event_name == 'pull_request' ||
+            github.event.inputs.run_type == 'full-ci' }}
     runs-on: ubuntu-22.04
 
     strategy:
@@ -347,6 +426,8 @@ jobs:
           cmake --build . --config Release -j $(nproc)
 
   ubuntu-22-cmake-sycl-fp16:
+    if: ${{ github.event_name == 'push' || github.event_name == 'pull_request' ||
+            github.event.inputs.run_type == 'full-ci' }}
     runs-on: ubuntu-22.04
 
     strategy:
@@ -397,6 +478,8 @@ jobs:
           cmake --build . --config Release -j $(nproc)
 
   windows-msys2:
+    if: ${{ github.event_name == 'push' || github.event_name == 'pull_request' ||
+            github.event.inputs.run_type == 'full-ci' }}
     runs-on: windows-latest
 
     strategy:
@@ -441,6 +524,8 @@ jobs:
             cmake --build build --config ${{ matrix.build }} -j $(nproc)
 
   windows:
+    if: ${{ github.event_name == 'push' || github.event_name == 'pull_request' ||
+            github.event.inputs.run_type == 'full-ci' }}
     runs-on: windows-latest
 
     strategy:
@@ -501,6 +586,8 @@ jobs:
           path: build/bin/${{ matrix.build }}
 
   windows-blas:
+    if: ${{ github.event_name == 'push' || github.event_name == 'pull_request' ||
+            github.event.inputs.run_type == 'full-ci' }}
     runs-on: windows-latest
 
     strategy:
@@ -574,6 +661,8 @@ jobs:
           path: build/bin/${{ matrix.build }}
 
   windows-cublas:
+    if: ${{ github.event_name == 'push' || github.event_name == 'pull_request' ||
+            github.event.inputs.run_type == 'full-ci' }}
     runs-on: windows-2019
     strategy:
       matrix:
@@ -590,15 +679,134 @@ jobs:
       - name: Clone repository
         uses: actions/checkout@v4
 
+      - name: Install Ninja
+        id: install_ninja
+        run: |
+          choco install ninja
+
+      - name: Install ccache
+        uses: hendrikmuhs/ccache-action@v1.2.16
+        with:
+          key: ${{ github.job }}-${{ matrix.cuda-toolkit }}-${{ matrix.build }}
+          variant: sccache
+          evict-old-files: 5d
+
+      - name: Install Cuda Toolkit 11.8.0
+        if: ${{ matrix.cuda-toolkit == '11.8.0' }}
+        run: |
+          $CUDA_VERSION = ${{ matrix.cuda-toolkit }}
+          $CUDA_TOOLKIT_DIR = "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v$CUDA_VERSION"
+          $CUDA_DOWNLOAD = "https://developer.download.nvidia.com/compute/cuda/redist"
+
+          # Components versions
+          $CUDART_VER = "11.8.89"
+          $NVCC_VER   = "11.8.89"
+          $NVRTC_VER  = "11.8.89"
+          $CUBLAS_VER = "11.8.1.74"
+          $NVTX_VER   = "11.8.86"
+          $VS_VER     = "11.8.86"
+          $NVPROF_VER = "11.8.87"
+          $CCCL_VER   = "11.8.89"
+
+          # Create the directory where the CUDA Toolkit will be installed
+          mkdir -p $CUDA_TOOLKIT_DIR
+
+          # Install unzip to extract the downloaded files
+          choco install unzip -y
+
+          # Download all the required components
+          curl -O "$CUDA_DOWNLOAD/cuda_cudart/windows-x86_64/cuda_cudart-windows-x86_64-${CUDART_VER}-archive.zip"
+          curl -O "$CUDA_DOWNLOAD/cuda_nvcc/windows-x86_64/cuda_nvcc-windows-x86_64-${NVCC_VER}-archive.zip"
+          curl -O "$CUDA_DOWNLOAD/cuda_nvrtc/windows-x86_64/cuda_nvrtc-windows-x86_64-${NVRTC_VER}-archive.zip"
+          curl -O "$CUDA_DOWNLOAD/libcublas/windows-x86_64/libcublas-windows-x86_64-${CUBLAS_VER}-archive.zip"
+          curl -O "$CUDA_DOWNLOAD/cuda_nvtx/windows-x86_64/cuda_nvtx-windows-x86_64-${NVTX_VER}-archive.zip"
+          curl -O "$CUDA_DOWNLOAD/visual_studio_integration/windows-x86_64/visual_studio_integration-windows-x86_64-${VS_VER}-archive.zip"
+          curl -O "$CUDA_DOWNLOAD/cuda_nvprof/windows-x86_64/cuda_nvprof-windows-x86_64-${NVPROF_VER}-archive.zip"
+          curl -O "$CUDA_DOWNLOAD/cuda_cccl/windows-x86_64/cuda_cccl-windows-x86_64-${CCCL_VER}-archive.zip"
+
+          # Extract all the downloaded files to the CUDA Toolkit directory
+          unzip '*.zip' -d $CUDA_TOOLKIT_DIR
+
+          # Copy all the extracted files to the main CUDA Toolkit directory
+          xcopy "$CUDA_TOOLKIT_DIR\cuda_cudart-windows-x86_64-${CUDART_VER}-archive\*" "$CUDA_TOOLKIT_DIR" /E /I /H /Y
+          xcopy "$CUDA_TOOLKIT_DIR\cuda_nvcc-windows-x86_64-${NVCC_VER}-archive\*" "$CUDA_TOOLKIT_DIR" /E /I /H /Y
+          xcopy "$CUDA_TOOLKIT_DIR\cuda_nvrtc-windows-x86_64-${NVRTC_VER}-archive\*" "$CUDA_TOOLKIT_DIR" /E /I /H /Y
+          xcopy "$CUDA_TOOLKIT_DIR\libcublas-windows-x86_64-${CUBLAS_VER}-archive\*" "$CUDA_TOOLKIT_DIR" /E /I /H /Y
+          xcopy "$CUDA_TOOLKIT_DIR\cuda_nvtx-windows-x86_64-${NVTX_VER}-archive\*" "$CUDA_TOOLKIT_DIR" /E /I /H /Y
+          xcopy "$CUDA_TOOLKIT_DIR\cuda_nvprof-windows-x86_64-${NVPROF_VER}-archive\*" "$CUDA_TOOLKIT_DIR" /E /I /H /Y
+          xcopy "$CUDA_TOOLKIT_DIR\cuda_cccl-windows-x86_64-${CCCL_VER}-archive\*" "$CUDA_TOOLKIT_DIR" /E /I /H /Y
+          xcopy "$CUDA_TOOLKIT_DIR\visual_studio_integration-windows-x86_64-${VS_VER}-archive\*" "$CUDA_TOOLKIT_DIR" /E /I /H /Y
+
+          # Visual Studio integration
+          xcopy "$CUDA_TOOLKIT_DIR\visual_studio_integration-windows-x86_64-${VS_VER}-archive\visual_studio_integration\MSBuildExtensions\*" "C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\MSBuild\Microsoft\VC\v160\BuildCustomizations" /E /I /H /Y
+
+          # Set environment variables
+          echo "$CUDA_TOOLKIT_DIR\bin" | Out-File -FilePath $env:GITHUB_PATH -Encoding utf8 -Append
+          echo "$CUDA_TOOLKIT_DIR\libnvvp" | Out-File -FilePath $env:GITHUB_PATH -Encoding utf8 -Append
+          echo "CUDA_PATH=$CUDA_TOOLKIT_DIR" | Out-File -FilePath $env:GITHUB_ENV -Append -Encoding utf8
+          echo "CUDA_PATH_V11_8=$CUDA_TOOLKIT_DIR" | Out-File -FilePath $env:GITHUB_ENV -Append -Encoding utf8
+        
+      - name: Install Cuda Toolkit 12.2.0
+        if: ${{ matrix.cuda-toolkit == '12.2.0' }}
+        run: |
+          $CUDA_VERSION = ${{ matrix.cuda-toolkit }}
+          $CUDA_TOOLKIT_DIR = "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v$CUDA_VERSION"
+          $CUDA_DOWNLOAD = "https://developer.download.nvidia.com/compute/cuda/redist"
+
+          # Components versions
+          $CUDART_VER   = "12.2.140"
+          $NVCC_VER     = "12.2.140"
+          $NVRTC_VER    = "12.2.140"
+          $CUBLAS_VER   = "12.2.5.6"
+          $NVTX_VER     = "12.2.140"
+          $PROFILER_VER = "12.2.140"
+          $VS_VER       = "12.2.140"
+          $NVPROF_VER   = "12.2.142"
+          $CCCL_VER     = "12.2.140"
+
+          # Create the directory where the CUDA Toolkit will be installed
+          mkdir -p $CUDA_TOOLKIT_DIR
+
+          # Install unzip to extract the downloaded files
+          choco install unzip -y
+
+          # Download all the required components
+          curl -O "$CUDA_DOWNLOAD/cuda_cudart/windows-x86_64/cuda_cudart-windows-x86_64-${CUDART_VER}-archive.zip"
+          curl -O "$CUDA_DOWNLOAD/cuda_nvcc/windows-x86_64/cuda_nvcc-windows-x86_64-${NVCC_VER}-archive.zip"
+          curl -O "$CUDA_DOWNLOAD/cuda_nvrtc/windows-x86_64/cuda_nvrtc-windows-x86_64-${NVRTC_VER}-archive.zip"
+          curl -O "$CUDA_DOWNLOAD/libcublas/windows-x86_64/libcublas-windows-x86_64-${CUBLAS_VER}-archive.zip"
+          curl -O "$CUDA_DOWNLOAD/cuda_nvtx/windows-x86_64/cuda_nvtx-windows-x86_64-${NVTX_VER}-archive.zip"
+          curl -O "$CUDA_DOWNLOAD/cuda_profiler_api/windows-x86_64/cuda_profiler_api-windows-x86_64-${PROFILER_VER}-archive.zip"
+          curl -O "$CUDA_DOWNLOAD/visual_studio_integration/windows-x86_64/visual_studio_integration-windows-x86_64-${VS_VER}-archive.zip"
+          curl -O "$CUDA_DOWNLOAD/cuda_nvprof/windows-x86_64/cuda_nvprof-windows-x86_64-${NVPROF_VER}-archive.zip"
+          curl -O "$CUDA_DOWNLOAD/cuda_cccl/windows-x86_64/cuda_cccl-windows-x86_64-${CCCL_VER}-archive.zip"
+
+          # Extract all the downloaded files to the CUDA Toolkit directory
+          unzip -q '*.zip' -d $CUDA_TOOLKIT_DIR
+
+          # Copy all the extracted files to the main CUDA Toolkit directory
+          xcopy "$CUDA_TOOLKIT_DIR\cuda_cudart-windows-x86_64-${CUDART_VER}-archive\*" "$CUDA_TOOLKIT_DIR" /E /I /H /Y
+          xcopy "$CUDA_TOOLKIT_DIR\cuda_nvcc-windows-x86_64-${NVCC_VER}-archive\*"     "$CUDA_TOOLKIT_DIR" /E /I /H /Y
+          xcopy "$CUDA_TOOLKIT_DIR\cuda_nvrtc-windows-x86_64-${NVRTC_VER}-archive\*"   "$CUDA_TOOLKIT_DIR" /E /I /H /Y
+          xcopy "$CUDA_TOOLKIT_DIR\libcublas-windows-x86_64-${CUBLAS_VER}-archive\*"   "$CUDA_TOOLKIT_DIR" /E /I /H /Y
+          xcopy "$CUDA_TOOLKIT_DIR\cuda_nvtx-windows-x86_64-${NVTX_VER}-archive\*"     "$CUDA_TOOLKIT_DIR" /E /I /H /Y
+          xcopy "$CUDA_TOOLKIT_DIR\cuda_nvprof-windows-x86_64-${NVPROF_VER}-archive\*" "$CUDA_TOOLKIT_DIR" /E /I /H /Y
+          xcopy "$CUDA_TOOLKIT_DIR\cuda_cccl-windows-x86_64-${CCCL_VER}-archive\*" "$CUDA_TOOLKIT_DIR" /E /I /H /Y
+          xcopy "$CUDA_TOOLKIT_DIR\cuda_profiler_api-windows-x86_64-${PROFILER_VER}-archive\*" "$CUDA_TOOLKIT_DIR" /E /I /H /Y
+          xcopy "$CUDA_TOOLKIT_DIR\visual_studio_integration-windows-x86_64-${VS_VER}-archive\*" "$CUDA_TOOLKIT_DIR" /E /I /H /Y
+
+          # Visual Studio integration
+          xcopy "$CUDA_TOOLKIT_DIR\visual_studio_integration-windows-x86_64-${VS_VER}-archive\visual_studio_integration\MSBuildExtensions\*" "C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\MSBuild\Microsoft\VC\v160\BuildCustomizations" /E /I /H /Y
+
+          # Set environment variables
+          echo "$CUDA_TOOLKIT_DIR\bin" | Out-File -FilePath $env:GITHUB_PATH -Encoding utf8 -Append
+          echo "$CUDA_TOOLKIT_DIR\libnvvp" | Out-File -FilePath $env:GITHUB_PATH -Encoding utf8 -Append
+          echo "CUDA_PATH=$CUDA_TOOLKIT_DIR" | Out-File -FilePath $env:GITHUB_ENV -Append -Encoding utf8
+          echo "CUDA_PATH_V12_2=$CUDA_TOOLKIT_DIR" | Out-File -FilePath $env:GITHUB_ENV -Append -Encoding utf8
+
       - name: Add msbuild to PATH
         uses: microsoft/setup-msbuild@v2
 
-      - name: Install CUDA Toolkit
-        id: cuda-toolkit
-        uses: Jimver/cuda-toolkit@v0.2.15
-        with:
-          cuda: '${{ matrix.cuda-toolkit }}'
-
       - name: Install 7-Zip
         run: choco install 7zip -y
 
@@ -610,25 +818,30 @@ jobs:
           echo "SDL2_DIR=${{ github.workspace }}\SDL2-${{ matrix.sdl2_ver }}\cmake" | Out-File -FilePath $env:GITHUB_ENV -Append
           echo "${{ github.workspace }}\SDL2-${{ matrix.sdl2_ver }}\cmake" > SDL2_PATH.txt
 
-      - name: Configure CMake
-        shell: cmd
-        run: |
-          cmake -S . -B ./build -A ${{ matrix.arch }} ^
-            -DCMAKE_BUILD_TYPE=${{ matrix.build }} ^
-            -DGGML_CUDA=${{ matrix.cublas }} ^
-            -DCMAKE_CUDA_ARCHITECTURES=all  ^
-            -DWHISPER_SDL2=${{ matrix.sdl2 }} ^
-            -DSDL2_DIR="%SDL2_DIR%"
+      - name: Install cmake
+        run: choco install cmake
 
       - name: Build Project
         shell: cmd
         run: |
-          cd ./build
-          cmake --build . --config ${{ matrix.build }}
+          call "C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Auxiliary\Build\vcvars64.bat"
+          cmake --version
+          where cmake
+          cmake -S . -B build -G "Ninja Multi-Config" ^
+            -DCMAKE_BUILD_TYPE=${{ matrix.build }} ^
+            -DGGML_CUDA=${{ matrix.cublas }} ^
+            -DWHISPER_SDL2=${{ matrix.sdl2 }} ^
+            -DSDL2_DIR="%SDL2_DIR%"
+          set /A NINJA_JOBS=%NUMBER_OF_PROCESSORS%-1
+          cmake --build build --config ${{ matrix.build }} -j %NUMBER_OF_PROCESSORS%
+
+      - name: Check sccache status after build
+        run: |
+          sccache --show-stats
 
       - name: Copy CUDA DLLs
         run: |
-          Get-ChildItem "${{ steps.cuda-toolkit.outputs.CUDA_PATH }}/bin/" -Filter "*.dll" |
+          Get-ChildItem "$env:CUDA_PATH\bin\" -Filter "*.dll" |
           Copy-Item -Destination "build/bin/${{ matrix.build }}"
 
       - name: Copy SDL2.dll
@@ -642,6 +855,8 @@ jobs:
           path: build/bin/${{ matrix.build }}
 
   emscripten:
+    if: ${{ github.event_name == 'push' || github.event_name == 'pull_request' ||
+            github.event.inputs.run_type == 'full-ci' }}
     runs-on: ubuntu-22.04
 
     strategy:
@@ -665,6 +880,7 @@ jobs:
 
   ios-xcode-build:
     runs-on: macos-latest
+    needs: determine-tag
 
     strategy:
       matrix:
@@ -707,7 +923,26 @@ jobs:
       - name: Build swiftui example
         run: xcodebuild -project examples/whisper.swiftui/whisper.swiftui.xcodeproj -scheme WhisperCppDemo -configuration ${{ matrix.build }} -sdk iphoneos CODE_SIGNING_REQUIRED=NO CODE_SIGN_IDENTITY= -destination 'generic/platform=iOS' FRAMEWORK_FOLDER_PATH=./build-ios build
 
+      - name: Pack artifacts
+        id: pack_artifacts
+        if: ${{ (github.event_name == 'push' && github.ref == 'refs/heads/master') ||
+                github.event.inputs.create_release == 'true' ||
+                github.event.inputs.pre_release_tag != '' }}
+        run: |
+          zip --symlinks -r whisper-${{ needs.determine-tag.outputs.tag_name }}-xcframework.zip build-apple/whisper.xcframework
+
+      - name: Upload artifacts
+        if: ${{ (github.event_name == 'push' && github.ref == 'refs/heads/master') ||
+                github.event.inputs.create_release == 'true' ||
+                github.event.inputs.pre_release_tag != '' }}
+        uses: actions/upload-artifact@v4
+        with:
+          path: whisper-${{ needs.determine-tag.outputs.tag_name }}-xcframework.zip
+          name: whisper-${{ needs.determine-tag.outputs.tag_name }}-xcframework
+
   android:
+    if: ${{ github.event_name == 'push' || github.event_name == 'pull_request' ||
+            github.event.inputs.run_type == 'full-ci' }}
     runs-on: ubuntu-22.04
 
     steps:
@@ -736,31 +971,30 @@ jobs:
           cd whisper/examples/whisper.android
           ./gradlew assembleRelease --no-daemon
 
-# TODO: disable because of following fail: https://github.com/ggerganov/whisper.cpp/actions/runs/11019444420/job/30627193602
-#  android_java:
-#    runs-on: ubuntu-22.04
-#
-#    steps:
-#      - name: Clone
-#        uses: actions/checkout@v4
-#
-#      - name: set up JDK 11
-#        uses: actions/setup-java@v4
-#        with:
-#          java-version: '11'
-#          distribution: 'temurin'
-#          cache: gradle
-#
-#      - name: Setup Android SDK
-#        uses: android-actions/setup-android@v3
-#        with:
-#          cmdline-tools-version: 9.0
-#
-#      - name: Build
-#        run: |
-#          cd examples/whisper.android.java
-#          chmod +x ./gradlew
-#          ./gradlew assembleRelease
+  android_java:
+    runs-on: ubuntu-22.04
+
+    steps:
+      - name: Clone
+        uses: actions/checkout@v4
+
+      - name: set up JDK 11
+        uses: actions/setup-java@v4
+        with:
+          java-version: '11'
+          distribution: 'temurin'
+          cache: gradle
+
+      - name: Setup Android SDK
+        uses: android-actions/setup-android@v3
+        with:
+          cmdline-tools-version: 9.0
+
+      - name: Build
+        run: |
+          cd examples/whisper.android.java
+          chmod +x ./gradlew
+          ./gradlew assembleRelease
 
 # TODO: disabled because of following fail: https://github.com/ggerganov/whisper.cpp/actions/runs/9686220096/job/26735899598
 #  java:
@@ -807,6 +1041,8 @@ jobs:
 #          PGP_PASSPHRASE: ${{ secrets.GPG_PASSPHRASE }}
 
   quantize:
+    if: ${{ github.event_name == 'push' || github.event_name == 'pull_request' ||
+            github.event.inputs.run_type == 'full-ci' }}
     runs-on: ubuntu-22.04
 
     steps:
@@ -819,3 +1055,95 @@ jobs:
           cmake -B build
           cmake --build build --config Release
           ./build/bin/quantize models/ggml-tiny.en.bin models/ggml-tiny.en-q4_0.bin q4_0
+
+  release:
+    if: ${{ github.event.inputs.create_release == 'true' || github.event.inputs.pre_release_tag != '' }}
+
+    runs-on: ubuntu-latest
+
+    needs:
+      - determine-tag
+      - ios-xcode-build
+
+    steps:
+      - name: Clone
+        id: checkout
+        uses: actions/checkout@v4
+        with:
+          fetch-depth: 0
+
+      - name: ccache
+        uses: hendrikmuhs/ccache-action@v1.2.16
+        with:
+          key: release
+          evict-old-files: 1d
+
+      # Downloads all the artifacts from the previous jobs
+      - name: Download artifacts
+        id: download-artifact
+        uses: actions/download-artifact@v4
+        with:
+          path: ./artifact
+
+      - name: Move artifacts
+        id: move_artifacts
+        run: mkdir -p ./artifact/release && mv ./artifact/*/*.zip ./artifact/release
+
+      - name: Create release
+        id: create_release
+        uses: ggml-org/action-create-release@v1
+        env:
+          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+        with:
+          tag_name: ${{ needs.determine-tag.outputs.tag_name }}
+          prerelease: ${{ github.event.inputs.pre_release_tag != '' }}
+
+      - name: Upload release
+        id: upload_release
+        uses: actions/github-script@v3
+        with:
+          github-token: ${{secrets.GITHUB_TOKEN}}
+          script: |
+            const path = require('path');
+            const fs = require('fs');
+            const release_id = '${{ steps.create_release.outputs.id }}';
+            for (let file of await fs.readdirSync('./artifact/release')) {
+              if (path.extname(file) === '.zip') {
+                console.log('uploadReleaseAsset', file);
+                await github.repos.uploadReleaseAsset({
+                  owner: context.repo.owner,
+                  repo: context.repo.repo,
+                  release_id: release_id,
+                  name: file,
+                  data: await fs.readFileSync(`./artifact/release/${file}`)
+                });
+              }
+            }
+
+  coreml-base-en:
+    if: ${{ (github.event_name == 'push' && github.ref == 'refs/heads/master') ||
+            github.event.inputs.create_release == 'true' ||
+            github.event.inputs.pre_release_tag != '' }}
+    runs-on: macos-latest
+    needs: determine-tag
+
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v4
+
+      - name: Set environment variables
+        id: set_vars
+        run: |
+          echo "MODEL_NAME=base.en" >> $GITHUB_ENV
+          echo "GEN_MODEL_NAME=whisper-${{ needs.determine-tag.outputs.tag_name }}-ggml-base.en-encoder.mlmodelc" >> $GITHUB_ENV
+
+      - name: Download model
+        run: |
+          ./models/download-ggml-model.sh ${{ env.MODEL_NAME }}
+
+      - name: Generate CoreML model
+        run: |
+          python3.11 -m venv venv
+          source venv/bin/activate
+          pip install ane_transformers openai-whisper coremltools
+          ./models/generate-coreml-model.sh ${{ env.MODEL_NAME }}

.github/workflows/examples-wasm.yml

@@ -0,0 +1,91 @@
+name: Examples WASM
+on:
+  push:
+    branches: ["master"]
+
+  workflow_dispatch:
+
+permissions:
+  contents: read
+  pages: write
+  id-token: write
+
+concurrency:
+  group: "pages"
+  cancel-in-progress: false
+
+jobs:
+  deploy-wasm-github-pages:
+    environment:
+      name: github-pages
+      url: ${{ steps.deployment.outputs.page_url }}
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout
+        uses: actions/checkout@v4
+
+      - name: Setup Pages
+        uses: actions/configure-pages@v4
+
+      - name: Setup emsdk
+        uses: mymindstorm/setup-emsdk@v14
+
+      - name: Build WASM Examples
+        # Enable for real build later in whisper.cpp
+        run: |
+          mkdir -p build-em && cd build-em
+          emcmake cmake .. -DCMAKE_BUILD_TYPE=Release
+          make -j
+
+      - name: Create staging directory
+        run: mkdir -p staging
+
+      - name: Create .nojekyll file in staging directory
+        run: touch staging/.nojekyll
+
+      - name: Copy application files
+        run: |
+          build_dir=build-em/bin
+
+          ls ${build_dir}
+
+          # command.wasm
+          target_dir=staging/command.wasm
+          mkdir -p ${target_dir}
+          cp ${build_dir}/command.wasm/{index.html,command.js,helpers.js} ${target_dir}
+          cp ${build_dir}/libcommand.js ${target_dir}
+
+          # bench.wasm
+          target_dir=staging/bench.wasm
+          mkdir -p ${target_dir}
+          cp ${build_dir}/bench.wasm/{index.html,bench.js,helpers.js} ${target_dir}
+          cp ${build_dir}/libbench.js ${target_dir}
+
+          # stream.wasm
+          target_dir=staging/stream.wasm
+          mkdir -p ${target_dir}
+          cp ${build_dir}/stream.wasm/{index.html,stream.js,helpers.js} ${target_dir}
+          cp ${build_dir}/libstream.js ${target_dir}
+
+          # whisper.wasm (this will be the main example page)
+          target_dir=staging
+          mkdir -p ${target_dir}
+          cp ${build_dir}/whisper.wasm/{index.html,main.js,helpers.js} ${target_dir}
+          cp ${build_dir}/libmain.js ${target_dir}
+
+          # Copy Cross-Origin Isolation service worker
+          cp -v examples/coi-serviceworker.js staging/
+
+      - name: List files in staging directory (for debugging)
+        run: |
+          echo "Files in staging directory:"
+          find staging -type f | sort
+
+      - name: Upload artifact
+        uses: actions/upload-pages-artifact@v3
+        with:
+          path: ./staging
+
+      - name: Deploy to GitHub Pages
+        id: deployment
+        uses: actions/deploy-pages@v4

CMakeLists.txt

@@ -1,6 +1,6 @@
 cmake_minimum_required(VERSION 3.5) # for add_link_options and implicit target directories.
 project("whisper.cpp" C CXX)
-project("whisper.cpp" VERSION 1.7.4)
+project("whisper.cpp" VERSION 1.7.5)
 include(CheckIncludeFileCXX)
 
 set(SOVERSION 1)
@@ -38,8 +38,13 @@ if (EMSCRIPTEN)
 
     # TODO: without these, we get the following error:
     #       wasm-ld: error: --shared-memory is disallowed by whisper.cpp.o because it was not compiled with 'atomics' or 'bulk-memory' features.
-    set(CMAKE_C_FLAGS   "${CMAKE_C_FLAGS}   -pthread -s TOTAL_STACK=5242880")
-    set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -pthread -s TOTAL_STACK=5242880")
+    set(CMAKE_C_FLAGS   "${CMAKE_C_FLAGS}   -pthread")
+    set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -pthread")
+
+    set(CMAKE_EXE_LINKER_FLAGS "${CMAKE_EXE_LINKER_FLAGS} -s TOTAL_STACK=5242880")
+    set(CMAKE_SHARED_LINKER_FLAGS "${CMAKE_SHARED_LINKER_FLAGS} -s TOTAL_STACK=5242880")
+
+    set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -Wno-deprecated")
 else()
     if (MINGW)
         set(BUILD_SHARED_LIBS_DEFAULT OFF)
@@ -62,7 +67,8 @@ option(WHISPER_ALL_WARNINGS           "whisper: enable all compiler warnings"
 option(WHISPER_ALL_WARNINGS_3RD_PARTY "whisper: enable all compiler warnings in 3rd party libs" OFF)
 
 # build
-option(WHISPER_FATAL_WARNINGS "whisper: enable -Werror flag" OFF)
+option(WHISPER_FATAL_WARNINGS  "whisper: enable -Werror flag"               OFF)
+option(WHISPER_USE_SYSTEM_GGML "whisper: use system-installed GGML library" OFF)
 
 # sanitizers
 option(WHISPER_SANITIZE_THREAD    "whisper: enable thread sanitizer"    OFF)
@@ -121,7 +127,15 @@ whisper_option_depr(WARNING     WHISPER_SYCL_F16            GGML_SYCL_F16)
 #
 
 if (NOT TARGET ggml)
-    add_subdirectory(ggml)
+    if (WHISPER_USE_SYSTEM_GGML)
+        find_package(ggml REQUIRED)
+        if (NOT ggml_FOUND)
+            message(FATAL_ERROR "System-installed GGML library not found.")
+        endif()
+        add_library(ggml ALIAS ggml::ggml)
+    else()
+        add_subdirectory(ggml)
+    endif()
     # ... otherwise assume ggml is added by a parent CMakeLists.txt
 endif()
 add_subdirectory(src)
@@ -176,8 +190,8 @@ install(FILES "${CMAKE_CURRENT_BINARY_DIR}/whisper.pc"
 #
 
 if (WHISPER_BUILD_TESTS AND NOT CMAKE_JS_VERSION)
-    #include(CTest)
-    #add_subdirectory(tests)
+    include(CTest)
+    add_subdirectory(tests)
 endif ()
 
 if (WHISPER_BUILD_EXAMPLES)

README.md

@@ -2,15 +2,12 @@
 
 ![whisper.cpp](https://user-images.githubusercontent.com/1991296/235238348-05d0f6a4-da44-4900-a1de-d0707e75b763.jpeg)
 
-[![Actions Status](https://github.com/ggerganov/whisper.cpp/workflows/CI/badge.svg)](https://github.com/ggerganov/whisper.cpp/actions)
+[![Actions Status](https://github.com/ggml-org/whisper.cpp/workflows/CI/badge.svg)](https://github.com/ggml-org/whisper.cpp/actions)
 [![License: MIT](https://img.shields.io/badge/license-MIT-blue.svg)](https://opensource.org/licenses/MIT)
 [![Conan Center](https://shields.io/conan/v/whisper-cpp)](https://conan.io/center/whisper-cpp)
 [![npm](https://img.shields.io/npm/v/whisper.cpp.svg)](https://www.npmjs.com/package/whisper.cpp/)
 
-> [!NOTE]
-> New maintenance roadmap: https://github.com/ggerganov/whisper.cpp/discussions/2788
-
-Stable: [v1.7.4](https://github.com/ggerganov/whisper.cpp/releases/tag/v1.7.4) / [Roadmap | F.A.Q.](https://github.com/ggerganov/whisper.cpp/discussions/126)
+Stable: [v1.7.5](https://github.com/ggml-org/whisper.cpp/releases/tag/v1.7.5) / [Roadmap](https://github.com/orgs/ggml-org/projects/4/)
 
 High-performance inference of [OpenAI's Whisper](https://github.com/openai/whisper) automatic speech recognition (ASR) model:
 
@@ -26,7 +23,7 @@ High-performance inference of [OpenAI's Whisper](https://github.com/openai/whisp
 - [Efficient GPU support for NVIDIA](#nvidia-gpu-support)
 - [OpenVINO Support](#openvino-support)
 - [Ascend NPU Support](#ascend-npu-support)
-- [C-style API](https://github.com/ggerganov/whisper.cpp/blob/master/include/whisper.h)
+- [C-style API](https://github.com/ggml-org/whisper.cpp/blob/master/include/whisper.h)
 
 Supported platforms:
 
@@ -34,14 +31,14 @@ Supported platforms:
 - [x] [iOS](examples/whisper.objc)
 - [x] [Android](examples/whisper.android)
 - [x] [Java](bindings/java/README.md)
-- [x] Linux / [FreeBSD](https://github.com/ggerganov/whisper.cpp/issues/56#issuecomment-1350920264)
+- [x] Linux / [FreeBSD](https://github.com/ggml-org/whisper.cpp/issues/56#issuecomment-1350920264)
 - [x] [WebAssembly](examples/whisper.wasm)
-- [x] Windows ([MSVC](https://github.com/ggerganov/whisper.cpp/blob/master/.github/workflows/build.yml#L117-L144) and [MinGW](https://github.com/ggerganov/whisper.cpp/issues/168)]
-- [x] [Raspberry Pi](https://github.com/ggerganov/whisper.cpp/discussions/166)
-- [x] [Docker](https://github.com/ggerganov/whisper.cpp/pkgs/container/whisper.cpp)
+- [x] Windows ([MSVC](https://github.com/ggml-org/whisper.cpp/blob/master/.github/workflows/build.yml#L117-L144) and [MinGW](https://github.com/ggml-org/whisper.cpp/issues/168)]
+- [x] [Raspberry Pi](https://github.com/ggml-org/whisper.cpp/discussions/166)
+- [x] [Docker](https://github.com/ggml-org/whisper.cpp/pkgs/container/whisper.cpp)
 
 The entire high-level implementation of the model is contained in [whisper.h](include/whisper.h) and [whisper.cpp](src/whisper.cpp).
-The rest of the code is part of the [`ggml`](https://github.com/ggerganov/ggml) machine learning library.
+The rest of the code is part of the [`ggml`](https://github.com/ggml-org/ggml) machine learning library.
 
 Having such a lightweight implementation of the model allows to easily integrate it in different platforms and applications.
 As an example, here is a video of running the model on an iPhone 13 device - fully offline, on-device: [whisper.objc](examples/whisper.objc)
@@ -54,14 +51,14 @@ https://user-images.githubusercontent.com/1991296/204038393-2f846eae-c255-4099-a
 
 On Apple Silicon, the inference runs fully on the GPU via Metal:
 
-https://github.com/ggerganov/whisper.cpp/assets/1991296/c82e8f86-60dc-49f2-b048-d2fdbd6b5225
+https://github.com/ggml-org/whisper.cpp/assets/1991296/c82e8f86-60dc-49f2-b048-d2fdbd6b5225
 
 ## Quick start
 
 First clone the repository:
 
 ```bash
-git clone https://github.com/ggerganov/whisper.cpp.git
+git clone https://github.com/ggml-org/whisper.cpp.git
 ```
 
 Navigate into the directory:
@@ -152,6 +149,7 @@ standard cmake setup with:
 cmake -B build -DGGML_BLAS=1
 cmake --build build --config Release
 ./build/bin/whisper-cli [ .. etc .. ]
+```
 
 ## Quantization
 
@@ -184,11 +182,11 @@ speed-up - more than x3 faster compared with CPU-only execution. Here are the in
   ```
 
   - To ensure `coremltools` operates correctly, please confirm that [Xcode](https://developer.apple.com/xcode/) is installed and execute `xcode-select --install` to install the command-line tools.
-  - Python 3.10 is recommended.
+  - Python 3.11 is recommended.
   - MacOS Sonoma (version 14) or newer is recommended, as older versions of MacOS might experience issues with transcription hallucination.
   - [OPTIONAL] It is recommended to utilize a Python version management system, such as [Miniconda](https://docs.conda.io/en/latest/miniconda.html) for this step:
-    - To create an environment, use: `conda create -n py310-whisper python=3.10 -y`
-    - To activate the environment, use: `conda activate py310-whisper`
+    - To create an environment, use: `conda create -n py311-whisper python=3.11 -y`
+    - To activate the environment, use: `conda activate py311-whisper`
 
 - Generate a Core ML model. For example, to generate a `base.en` model, use:
 
@@ -225,7 +223,7 @@ speed-up - more than x3 faster compared with CPU-only execution. Here are the in
   The first run on a device is slow, since the ANE service compiles the Core ML model to some device-specific format.
   Next runs are faster.
 
-For more information about the Core ML implementation please refer to PR [#566](https://github.com/ggerganov/whisper.cpp/pull/566).
+For more information about the Core ML implementation please refer to PR [#566](https://github.com/ggml-org/whisper.cpp/pull/566).
 
 ## OpenVINO support
 
@@ -310,7 +308,7 @@ This can result in significant speedup in encoder performance. Here are the inst
   The first time run on an OpenVINO device is slow, since the OpenVINO framework will compile the IR (Intermediate Representation) model to a device-specific 'blob'. This device-specific blob will get
   cached for the next run.
 
-For more information about the OpenVINO implementation please refer to PR [#1037](https://github.com/ggerganov/whisper.cpp/pull/1037).
+For more information about the OpenVINO implementation please refer to PR [#1037](https://github.com/ggml-org/whisper.cpp/pull/1037).
 
 ## NVIDIA GPU support
 
@@ -388,8 +386,8 @@ Run the inference examples as usual, for example:
 
 We have two Docker images available for this project:
 
-1. `ghcr.io/ggerganov/whisper.cpp:main`: This image includes the main executable file as well as `curl` and `ffmpeg`. (platforms: `linux/amd64`, `linux/arm64`)
-2. `ghcr.io/ggerganov/whisper.cpp:main-cuda`: Same as `main` but compiled with CUDA support. (platforms: `linux/amd64`)
+1. `ghcr.io/ggml-org/whisper.cpp:main`: This image includes the main executable file as well as `curl` and `ffmpeg`. (platforms: `linux/amd64`, `linux/arm64`)
+2. `ghcr.io/ggml-org/whisper.cpp:main-cuda`: Same as `main` but compiled with CUDA support. (platforms: `linux/amd64`)
 
 ### Usage
 
@@ -427,7 +425,8 @@ For detailed instructions on how to use Conan, please refer to the [Conan docume
 
 This is a naive example of performing real-time inference on audio from your microphone.
 The [stream](examples/stream) tool samples the audio every half a second and runs the transcription continuously.
-More info is available in [issue #10](https://github.com/ggerganov/whisper.cpp/issues/10).
+More info is available in [issue #10](https://github.com/ggml-org/whisper.cpp/issues/10).
+You will need to have [sdl2](https://wiki.libsdl.org/SDL2/Installation) installed for it to work properly.
 
 ```bash
 cmake -B build -DWHISPER_SDL2=ON
@@ -515,7 +514,7 @@ main: processing './samples/jfk.wav' (176000 samples, 11.0 sec), 4 threads, 1 pr
 
 ## Speaker segmentation via tinydiarize (experimental)
 
-More information about this approach is available here: https://github.com/ggerganov/whisper.cpp/pull/1058
+More information about this approach is available here: https://github.com/ggml-org/whisper.cpp/pull/1058
 
 Sample usage:
 
@@ -579,7 +578,7 @@ https://user-images.githubusercontent.com/1991296/199337538-b7b0c7a3-2753-4a88-a
 
 ## Video comparison of different models
 
-Use the [scripts/bench-wts.sh](https://github.com/ggerganov/whisper.cpp/blob/master/scripts/bench-wts.sh) script to generate a video in the following format:
+Use the [scripts/bench-wts.sh](https://github.com/ggml-org/whisper.cpp/blob/master/scripts/bench-wts.sh) script to generate a video in the following format:
 
 ```bash
 ./scripts/bench-wts.sh samples/jfk.wav
@@ -596,7 +595,7 @@ In order to have an objective comparison of the performance of the inference acr
 use the [whisper-bench](examples/bench) tool. The tool simply runs the Encoder part of the model and prints how much time it
 took to execute it. The results are summarized in the following Github issue:
 
-[Benchmark results](https://github.com/ggerganov/whisper.cpp/issues/89)
+[Benchmark results](https://github.com/ggml-org/whisper.cpp/issues/89)
 
 Additionally a script to run whisper.cpp with different models and audio files is provided [bench.py](scripts/bench.py).
 
@@ -623,25 +622,24 @@ You can download the converted models using the [models/download-ggml-model.sh](
 or manually from here:
 
 - https://huggingface.co/ggerganov/whisper.cpp
-- https://ggml.ggerganov.com
 
 For more details, see the conversion script [models/convert-pt-to-ggml.py](models/convert-pt-to-ggml.py) or [models/README.md](models/README.md).
 
-## [Bindings](https://github.com/ggerganov/whisper.cpp/discussions/categories/bindings)
+## [Bindings](https://github.com/ggml-org/whisper.cpp/discussions/categories/bindings)
 
-- [x] Rust: [tazz4843/whisper-rs](https://github.com/tazz4843/whisper-rs) | [#310](https://github.com/ggerganov/whisper.cpp/discussions/310)
-- [x] JavaScript: [bindings/javascript](bindings/javascript) | [#309](https://github.com/ggerganov/whisper.cpp/discussions/309)
+- [x] Rust: [tazz4843/whisper-rs](https://github.com/tazz4843/whisper-rs) | [#310](https://github.com/ggml-org/whisper.cpp/discussions/310)
+- [x] JavaScript: [bindings/javascript](bindings/javascript) | [#309](https://github.com/ggml-org/whisper.cpp/discussions/309)
   - React Native (iOS / Android): [whisper.rn](https://github.com/mybigday/whisper.rn)
-- [x] Go: [bindings/go](bindings/go) | [#312](https://github.com/ggerganov/whisper.cpp/discussions/312)
+- [x] Go: [bindings/go](bindings/go) | [#312](https://github.com/ggml-org/whisper.cpp/discussions/312)
 - [x] Java:
   - [GiviMAD/whisper-jni](https://github.com/GiviMAD/whisper-jni)
-- [x] Ruby: [bindings/ruby](bindings/ruby) | [#507](https://github.com/ggerganov/whisper.cpp/discussions/507)
-- [x] Objective-C / Swift: [ggerganov/whisper.spm](https://github.com/ggerganov/whisper.spm) | [#313](https://github.com/ggerganov/whisper.cpp/discussions/313)
+- [x] Ruby: [bindings/ruby](bindings/ruby) | [#507](https://github.com/ggml-org/whisper.cpp/discussions/507)
+- [x] Objective-C / Swift: [ggml-org/whisper.spm](https://github.com/ggml-org/whisper.spm) | [#313](https://github.com/ggml-org/whisper.cpp/discussions/313)
   - [exPHAT/SwiftWhisper](https://github.com/exPHAT/SwiftWhisper)
-- [x] .NET: | [#422](https://github.com/ggerganov/whisper.cpp/discussions/422)
+- [x] .NET: | [#422](https://github.com/ggml-org/whisper.cpp/discussions/422)
   - [sandrohanea/whisper.net](https://github.com/sandrohanea/whisper.net)
   - [NickDarvey/whisper](https://github.com/NickDarvey/whisper)
-- [x] Python: | [#9](https://github.com/ggerganov/whisper.cpp/issues/9)
+- [x] Python: | [#9](https://github.com/ggml-org/whisper.cpp/issues/9)
   - [stlukey/whispercpp.py](https://github.com/stlukey/whispercpp.py) (Cython)
   - [AIWintermuteAI/whispercpp](https://github.com/AIWintermuteAI/whispercpp) (Updated fork of aarnphm/whispercpp)
   - [aarnphm/whispercpp](https://github.com/aarnphm/whispercpp) (Pybind11)
@@ -649,6 +647,33 @@ For more details, see the conversion script [models/convert-pt-to-ggml.py](model
 - [x] R: [bnosac/audio.whisper](https://github.com/bnosac/audio.whisper)
 - [x] Unity: [macoron/whisper.unity](https://github.com/Macoron/whisper.unity)
 
+## XCFramework
+The XCFramework is a precompiled version of the library for iOS, visionOS, tvOS,
+and macOS. It can be used in Swift projects without the need to compile the
+library from source. For examples:
+```swift
+// swift-tools-version: 5.10
+// The swift-tools-version declares the minimum version of Swift required to build this package.
+
+import PackageDescription
+
+let package = Package(
+    name: "Whisper",
+    targets: [
+        .executableTarget(
+            name: "Whisper",
+            dependencies: [
+                "WhisperFramework"
+            ]),
+        .binaryTarget(
+            name: "WhisperFramework",
+            url: "https://github.com/ggml-org/whisper.cpp/releases/download/v1.7.5/whisper-v1.7.5-xcframework.zip",
+            checksum: "c7faeb328620d6012e130f3d705c51a6ea6c995605f2df50f6e1ad68c59c6c4a"
+        )
+    ]
+)
+```
+
 ## Examples
 
 There are various examples of using the library for different projects in the [examples](examples) folder.
@@ -667,13 +692,13 @@ Some of the examples are even ported to run in the browser using WebAssembly. Ch
 | [whisper.android](examples/whisper.android)         |                                       | Android mobile application using whisper.cpp                                                                                    |
 | [whisper.nvim](examples/whisper.nvim)               |                                       | Speech-to-text plugin for Neovim                                                                                                |
 | [generate-karaoke.sh](examples/generate-karaoke.sh) |                                       | Helper script to easily [generate a karaoke video](https://youtu.be/uj7hVta4blM) of raw audio capture                           |
-| [livestream.sh](examples/livestream.sh)             |                                       | [Livestream audio transcription](https://github.com/ggerganov/whisper.cpp/issues/185)                                           |
+| [livestream.sh](examples/livestream.sh)             |                                       | [Livestream audio transcription](https://github.com/ggml-org/whisper.cpp/issues/185)                                            |
 | [yt-wsp.sh](examples/yt-wsp.sh)                     |                                       | Download + transcribe and/or translate any VOD [(original)](https://gist.github.com/DaniruKun/96f763ec1a037cc92fe1a059b643b818) |
 | [wchess](examples/wchess)                           | [wchess.wasm](examples/wchess)        | Voice-controlled chess                                                                                                          |
 
-## [Discussions](https://github.com/ggerganov/whisper.cpp/discussions)
+## [Discussions](https://github.com/ggml-org/whisper.cpp/discussions)
 
 If you have any kind of feedback about this project feel free to use the Discussions section and open a new topic.
-You can use the [Show and tell](https://github.com/ggerganov/whisper.cpp/discussions/categories/show-and-tell) category
+You can use the [Show and tell](https://github.com/ggml-org/whisper.cpp/discussions/categories/show-and-tell) category
 to share your own projects that use `whisper.cpp`. If you have a question, make sure to check the
-[Frequently asked questions (#126)](https://github.com/ggerganov/whisper.cpp/discussions/126) discussion.
+[Frequently asked questions (#126)](https://github.com/ggml-org/whisper.cpp/discussions/126) discussion.

bindings/go/Makefile

@@ -11,11 +11,11 @@ UNAME_M := $(shell uname -m)
 endif
 
 GGML_METAL_PATH_RESOURCES := $(abspath ../..)
-BUILD_DIR := build
+BUILD_DIR := build_go
 MODELS_DIR := models
 EXAMPLES_DIR := $(wildcard examples/*)
 INCLUDE_PATH := $(abspath ../../include):$(abspath ../../ggml/include)
-LIBRARY_PATH := $(abspath ../..)
+LIBRARY_PATH := $(abspath ../../${BUILD_DIR}/src:$(abspath ../../${BUILD_DIR}/ggml/src))
 
 ifeq ($(GGML_CUDA),1)
 	LIBRARY_PATH := $(LIBRARY_PATH):$(CUDA_PATH)/targets/$(UNAME_M)-linux/lib/
@@ -29,8 +29,10 @@ endif
 all: clean whisper examples
 
 whisper: mkdir
-	@echo Build whisper
-	@${MAKE} -C ../.. libwhisper.a
+	cmake -S ../.. -B ../../${BUILD_DIR} \
+		-DCMAKE_BUILD_TYPE=Release \
+		-DBUILD_SHARED_LIBS=OFF
+	cmake --build ../../${BUILD_DIR} --target whisper
 
 test: model-small whisper modtidy
 ifeq ($(UNAME_S),Darwin)

bindings/go/README.md

@@ -31,7 +31,7 @@ func main() {
 	if err != nil {
 		panic(err)
 	}
-	if err := context.Process(samples, nil, nil); err != nil {
+	if err := context.Process(samples, nil, nil, nil); err != nil {
 		return err
 	}
 
@@ -51,7 +51,7 @@ func main() {
 In order to build, you need to have the Go compiler installed. You can get it from [here](https://golang.org/dl/). Run the tests with:
 
 ```bash
-git clone https://github.com/ggerganov/whisper.cpp.git
+git clone https://github.com/ggml-org/whisper.cpp.git
 cd whisper.cpp/bindings/go
 make test
 ```
@@ -98,7 +98,7 @@ The API Documentation:
 
 Getting help:
 
-  * Follow the discussion for the go bindings [here](https://github.com/ggerganov/whisper.cpp/discussions/312)
+  * Follow the discussion for the go bindings [here](https://github.com/ggml-org/whisper.cpp/discussions/312)
 
 ## License
 

bindings/go/doc.go

@@ -1,5 +1,5 @@
 /*
-github.com/ggerganov/whisper.cpp/bindings/go
+github.com/ggml-org/whisper.cpp/bindings/go
 provides a speech-to-text service bindings for the Go programming language.
 */
 package whisper

bindings/go/examples/go-whisper/process.go

@@ -67,7 +67,7 @@ func Process(model whisper.Model, path string, flags *Flags) error {
 	// Process the data
 	fmt.Fprintf(flags.Output(), "  ...processing %q\n", path)
 	context.ResetTimings()
-	if err := context.Process(data, cb, nil); err != nil {
+	if err := context.Process(data, nil, cb, nil); err != nil {
 		return err
 	}
 

bindings/go/pkg/whisper/context.go

@@ -71,6 +71,10 @@ func (context *context) Language() string {
 	return whisper.Whisper_lang_str(context.params.Language())
 }
 
+func (context *context) DetectedLanguage() string {
+	return whisper.Whisper_lang_str(context.model.ctx.Whisper_full_lang_id())
+}
+
 // Set translate flag
 func (context *context) SetTranslate(v bool) {
 	context.params.SetTranslate(v)
@@ -189,6 +193,7 @@ func (context *context) WhisperLangAutoDetect(offset_ms int, n_threads int) ([]f
 // Process new sample data and return any errors
 func (context *context) Process(
 	data []float32,
+	callEncoderBegin EncoderBeginCallback,
 	callNewSegment SegmentCallback,
 	callProgress ProgressCallback,
 ) error {
@@ -203,7 +208,20 @@ func (context *context) Process(
 	// We don't do parallel processing at the moment
 	processors := 0
 	if processors > 1 {
-		if err := context.model.ctx.Whisper_full_parallel(context.params, data, processors, nil, func(new int) {
+		if err := context.model.ctx.Whisper_full_parallel(context.params, data, processors, callEncoderBegin,
+			func(new int) {
+				if callNewSegment != nil {
+					num_segments := context.model.ctx.Whisper_full_n_segments()
+					s0 := num_segments - new
+					for i := s0; i < num_segments; i++ {
+						callNewSegment(toSegment(context.model.ctx, i))
+					}
+				}
+			}); err != nil {
+			return err
+		}
+	} else if err := context.model.ctx.Whisper_full(context.params, data, callEncoderBegin,
+		func(new int) {
 			if callNewSegment != nil {
 				num_segments := context.model.ctx.Whisper_full_n_segments()
 				s0 := num_segments - new
@@ -211,22 +229,11 @@ func (context *context) Process(
 					callNewSegment(toSegment(context.model.ctx, i))
 				}
 			}
-		}); err != nil {
-			return err
-		}
-	} else if err := context.model.ctx.Whisper_full(context.params, data, nil, func(new int) {
-		if callNewSegment != nil {
-			num_segments := context.model.ctx.Whisper_full_n_segments()
-			s0 := num_segments - new
-			for i := s0; i < num_segments; i++ {
-				callNewSegment(toSegment(context.model.ctx, i))
+		}, func(progress int) {
+			if callProgress != nil {
+				callProgress(progress)
 			}
-		}
-	}, func(progress int) {
-		if callProgress != nil {
-			callProgress(progress)
-		}
-	}); err != nil {
+		}); err != nil {
 		return err
 	}
 

bindings/go/pkg/whisper/context_test.go

@@ -88,6 +88,37 @@ func TestProcess(t *testing.T) {
 	context, err := model.NewContext()
 	assert.NoError(err)
 
-	err = context.Process(data, nil, nil)
+	err = context.Process(data, nil, nil, nil)
 	assert.NoError(err)
 }
+
+func TestDetectedLanguage(t *testing.T) {
+	assert := assert.New(t)
+
+	fh, err := os.Open(SamplePath)
+	assert.NoError(err)
+	defer fh.Close()
+
+	// Decode the WAV file - load the full buffer
+	dec := wav.NewDecoder(fh)
+	buf, err := dec.FullPCMBuffer()
+	assert.NoError(err)
+	assert.Equal(uint16(1), dec.NumChans)
+
+	data := buf.AsFloat32Buffer().Data
+
+	model, err := whisper.New(ModelPath)
+	assert.NoError(err)
+	assert.NotNil(model)
+	defer model.Close()
+
+	context, err := model.NewContext()
+	assert.NoError(err)
+
+	err = context.Process(data, nil, nil, nil)
+	assert.NoError(err)
+
+	expectedLanguage := "en"
+	actualLanguage := context.DetectedLanguage()
+	assert.Equal(expectedLanguage, actualLanguage)
+}

bindings/go/pkg/whisper/interface.go

@@ -16,6 +16,10 @@ type SegmentCallback func(Segment)
 // processing. It is called during the Process function
 type ProgressCallback func(int)
 
+// EncoderBeginCallback is the callback function for checking if we want to
+// continue processing. It is called during the Process function
+type EncoderBeginCallback func() bool
+
 // Model is the interface to a whisper model. Create a new model with the
 // function whisper.New(string)
 type Model interface {
@@ -31,12 +35,13 @@ type Model interface {
 	Languages() []string
 }
 
-// Context is the speach recognition context.
+// Context is the speech recognition context.
 type Context interface {
 	SetLanguage(string) error // Set the language to use for speech recognition, use "auto" for auto detect language.
 	SetTranslate(bool)        // Set translate flag
 	IsMultilingual() bool     // Return true if the model is multilingual.
 	Language() string         // Get language
+	DetectedLanguage() string // Get detected language
 
 	SetOffset(time.Duration)          // Set offset
 	SetDuration(time.Duration)        // Set duration
@@ -58,7 +63,7 @@ type Context interface {
 	// Process mono audio data and return any errors.
 	// If defined, newly generated segments are passed to the
 	// callback function during processing.
-	Process([]float32, SegmentCallback, ProgressCallback) error
+	Process([]float32, EncoderBeginCallback, SegmentCallback, ProgressCallback) error
 
 	// After process is called, return segments until the end of the stream
 	// is reached, when io.EOF is returned.

bindings/go/whisper.go

@@ -9,7 +9,7 @@ import (
 // CGO
 
 /*
-#cgo LDFLAGS: -lwhisper -lm -lstdc++ -fopenmp
+#cgo LDFLAGS: -lwhisper -lggml -lggml-base -lggml-cpu  -lm -lstdc++ -fopenmp
 #cgo darwin LDFLAGS: -framework Accelerate -framework Metal -framework Foundation -framework CoreGraphics
 #include <whisper.h>
 #include <stdlib.h>

bindings/java/README.md

@@ -31,10 +31,10 @@ public class Example {
             var whisperParams = whisper.getFullDefaultParams(WhisperSamplingStrategy.WHISPER_SAMPLING_GREEDY);
             // custom configuration if required
             whisperParams.temperature_inc = 0f;
-            
+
             var samples = readAudio(); // divide each value by 32767.0f
             whisper.fullTranscribe(whisperParams, samples);
-            
+
             int segmentCount = whisper.getTextSegmentCount(context);
             for (int i = 0; i < segmentCount; i++) {
                 String text = whisper.getTextSegment(context, i);
@@ -52,7 +52,7 @@ public class Example {
 In order to build, you need to have the JDK 8 or higher installed. Run the tests with:
 
 ```bash
-git clone https://github.com/ggerganov/whisper.cpp.git
+git clone https://github.com/ggml-org/whisper.cpp.git
 cd whisper.cpp/bindings/java
 
 ./gradlew build

bindings/java/build.gradle

@@ -25,13 +25,13 @@ sourceSets {
 }
 
 tasks.register('copyLibwhisperDynlib', Copy) {
-    from '../../build'
-    include 'libwhisper.dynlib'
+    from '../../build/src'
+    include 'libwhisper.dylib'
     into 'build/generated/resources/main/darwin'
 }
 
 tasks.register('copyLibwhisperSo', Copy) {
-    from '../../build'
+    from '../../build/src'
     include 'libwhisper.so'
     into 'build/generated/resources/main/linux-x86-64'
 }
@@ -55,7 +55,12 @@ java {
     withJavadocJar()
 }
 
+sourcesJar() {
+    dependsOn copyLibs
+}
+
 jar {
+    dependsOn copyLibs
     exclude '**/whisper_java.exp', '**/whisper_java.lib'
 }
 
@@ -67,6 +72,9 @@ tasks.withType(Test) {
     useJUnitPlatform()
 }
 
+test.dependsOn copyLibs
+processResources.dependsOn copyLibs
+
 dependencies {
     implementation "net.java.dev.jna:jna:5.13.0"
     testImplementation "org.junit.jupiter:junit-jupiter:5.9.2"

bindings/java/src/main/java/io/github/ggerganov/whispercpp/WhisperConstants.java

@@ -0,0 +1,24 @@
+package io.github.ggerganov.whispercpp;
+
+/**
+ * Presets for alignment heads in DTW token timestamps
+ */
+public class WhisperConstants {
+    // Alignment heads presets
+    public static final int WHISPER_AHEADS_NONE = 0;
+    public static final int WHISPER_AHEADS_TINY_EN = 1;
+    public static final int WHISPER_AHEADS_TINY = 2;
+    public static final int WHISPER_AHEADS_BASE_EN = 3;
+    public static final int WHISPER_AHEADS_BASE = 4;
+    public static final int WHISPER_AHEADS_SMALL_EN = 5;
+    public static final int WHISPER_AHEADS_SMALL = 6;
+    public static final int WHISPER_AHEADS_MEDIUM_EN = 7;
+    public static final int WHISPER_AHEADS_MEDIUM = 8;
+    public static final int WHISPER_AHEADS_LARGE_V1 = 9;
+    public static final int WHISPER_AHEADS_LARGE_V2 = 10;
+    public static final int WHISPER_AHEADS_LARGE_V3 = 11;
+    public static final int WHISPER_AHEADS_LARGE_V3_TURBO = 12;
+    public static final int WHISPER_AHEADS_CUSTOM = 13;
+    public static final int WHISPER_AHEADS_N_TOP_MOST = 14;
+    public static final int WHISPER_AHEADS_COUNT = 15;
+}

bindings/java/src/main/java/io/github/ggerganov/whispercpp/WhisperContext.java

@@ -1,7 +1,9 @@
 package io.github.ggerganov.whispercpp;
 
+import com.sun.jna.NativeLong;
 import com.sun.jna.Structure;
 import com.sun.jna.ptr.PointerByReference;
+import com.sun.jna.Pointer;
 import io.github.ggerganov.whispercpp.ggml.GgmlType;
 import io.github.ggerganov.whispercpp.WhisperModel;
 import io.github.ggerganov.whispercpp.params.WhisperContextParams;
@@ -9,33 +11,26 @@ import io.github.ggerganov.whispercpp.params.WhisperContextParams;
 import java.util.List;
 
 public class WhisperContext extends Structure {
-    int t_load_us = 0;
-    int t_start_us = 0;
+    public NativeLong t_load_us;
+    public NativeLong t_start_us;
 
     /** weight type (FP32 / FP16 / QX) */
-    GgmlType wtype = GgmlType.GGML_TYPE_F16;
+    public GgmlType wtype = GgmlType.GGML_TYPE_F16;
     /** intermediate type (FP32 or FP16) */
-    GgmlType itype = GgmlType.GGML_TYPE_F16;
+    public GgmlType itype = GgmlType.GGML_TYPE_F16;
 
-//    WhisperModel model;
-    public PointerByReference model;
-//    whisper_vocab vocab;
-//    whisper_state * state = nullptr;
-    public PointerByReference vocab;
-    public PointerByReference state;
+    public WhisperContextParams.ByValue params;
+
+    public Pointer model;
+    public Pointer vocab;
+    public Pointer state;
 
     /** populated by whisper_init_from_file_with_params() */
-    String path_model;
-    WhisperContextParams params;
+    public Pointer path_model;
 
-//    public static class ByReference extends WhisperContext implements Structure.ByReference {
-//    }
-//
-//    public static class ByValue extends WhisperContext implements Structure.ByValue {
-//    }
-//
-//    @Override
-//    protected List<String> getFieldOrder() {
-//        return List.of("t_load_us", "t_start_us", "wtype", "itype", "model", "vocab", "state", "path_model");
-//    }
+    @Override
+    protected List<String> getFieldOrder() {
+        return List.of("t_load_us", "t_start_us", "wtype", "itype",
+                "params", "model", "vocab", "state", "path_model");
+    }
 }

bindings/java/src/main/java/io/github/ggerganov/whispercpp/WhisperCpp.java

@@ -43,11 +43,11 @@ public class WhisperCpp implements AutoCloseable {
      * @param modelPath - absolute path, or just the name (eg: "base", "base-en" or "base.en")
      * @param params - params to use when initialising the context
      */
-    public void initContext(String modelPath, WhisperContextParams params) throws FileNotFoundException {
+    public void initContext(String modelPath, WhisperContextParams.ByValue params) throws FileNotFoundException {
         initContextImpl(modelPath, params);
     }
 
-    private void initContextImpl(String modelPath, WhisperContextParams params) throws FileNotFoundException {
+    private void initContextImpl(String modelPath, WhisperContextParams.ByValue params) throws FileNotFoundException {
         if (ctx != null) {
             lib.whisper_free(ctx);
         }
@@ -69,15 +69,13 @@ public class WhisperCpp implements AutoCloseable {
 
     /**
      * Provides default params which can be used with `whisper_init_from_file_with_params()` etc.
-     * Because this function allocates memory for the params, the caller must call either:
-     * - call `whisper_free_context_params()`
-     * - `Native.free(Pointer.nativeValue(pointer));`
+     * Returns a ByValue instance to ensure proper parameter passing to native code.
      */
-    public WhisperContextParams getContextDefaultParams() {
-        paramsPointer = lib.whisper_context_default_params_by_ref();
-        WhisperContextParams params = new WhisperContextParams(paramsPointer);
-        params.read();
-        return params;
+    public WhisperContextParams.ByValue getContextDefaultParams() {
+        WhisperContextParams.ByValue valueParams = new WhisperContextParams.ByValue(
+            lib.whisper_context_default_params_by_ref());
+        valueParams.read();
+        return valueParams;
     }
     
     /**
@@ -88,7 +86,7 @@ public class WhisperCpp implements AutoCloseable {
      *
      * @param strategy - GREEDY
      */
-    public WhisperFullParams getFullDefaultParams(WhisperSamplingStrategy strategy) {
+    public WhisperFullParams.ByValue getFullDefaultParams(WhisperSamplingStrategy strategy) {
         Pointer pointer;
 
         // whisper_full_default_params_by_ref allocates memory which we need to delete, so only create max 1 pointer for each strategy.
@@ -104,7 +102,7 @@ public class WhisperCpp implements AutoCloseable {
             pointer = beamParamsPointer;
         }
 
-        WhisperFullParams params = new WhisperFullParams(pointer);
+        WhisperFullParams.ByValue params = new WhisperFullParams.ByValue(pointer);
         params.read();
         return params;
     }
@@ -138,15 +136,21 @@ public class WhisperCpp implements AutoCloseable {
     }
 
     /**
-     * Run the entire model: PCM -> log mel spectrogram -> encoder -> decoder -> text.
+     * Run the entire model: PCM -> log mel spectrogram -> encoder -> decoder -> text.
      * Not thread safe for same context
      * Uses the specified decoding strategy to obtain the text.
      */
-    public String fullTranscribe(WhisperFullParams whisperParams, float[] audioData) throws IOException {
+    public String fullTranscribe(WhisperFullParams.ByValue whisperParams, float[] audioData) throws IOException {
         if (ctx == null) {
             throw new IllegalStateException("Model not initialised");
         }
 
+        /*
+        WhisperFullParams.ByValue valueParams = new WhisperFullParams.ByValue(
+            lib.whisper_full_default_params_by_ref(WhisperSamplingStrategy.WHISPER_SAMPLING_BEAM_SEARCH.ordinal()));
+        valueParams.read();
+        */
+
         if (lib.whisper_full(ctx, whisperParams, audioData, audioData.length) != 0) {
             throw new IOException("Failed to process audio");
         }
@@ -163,12 +167,17 @@ public class WhisperCpp implements AutoCloseable {
 
         return str.toString().trim();
     }
+
     public List<WhisperSegment> fullTranscribeWithTime(WhisperFullParams whisperParams, float[] audioData) throws IOException {
         if (ctx == null) {
             throw new IllegalStateException("Model not initialised");
         }
 
-        if (lib.whisper_full(ctx, whisperParams, audioData, audioData.length) != 0) {
+        WhisperFullParams.ByValue valueParams = new WhisperFullParams.ByValue(
+            lib.whisper_full_default_params_by_ref(WhisperSamplingStrategy.WHISPER_SAMPLING_BEAM_SEARCH.ordinal()));
+        valueParams.read();
+
+        if (lib.whisper_full(ctx, valueParams, audioData, audioData.length) != 0) {
             throw new IOException("Failed to process audio");
         }
 

bindings/java/src/main/java/io/github/ggerganov/whispercpp/WhisperCppJnaLibrary.java

@@ -38,7 +38,7 @@ public interface WhisperCppJnaLibrary extends Library {
      * @param params     Pointer to whisper_context_params
      * @return Whisper context on success, null on failure
      */
-    Pointer whisper_init_from_file_with_params(String path_model, WhisperContextParams params);
+    Pointer whisper_init_from_file_with_params(String path_model, WhisperContextParams.ByValue params);
 
     /**
      * Allocate (almost) all memory needed for the model by loading from a buffer.
@@ -180,12 +180,12 @@ public interface WhisperCppJnaLibrary extends Library {
     /**
      * @return the id of the specified language, returns -1 if not found.
      * Examples:
-     *   "de" -> 2
-     *   "german" -> 2
+     *   "de" -> 2
+     *   "german" -> 2
      */
     int whisper_lang_id(String lang);
 
-    /** @return the short string of the specified language id (e.g. 2 -> "de"), returns nullptr if not found */
+    /** @return the short string of the specified language id (e.g. 2 -> "de"), returns nullptr if not found */
     String whisper_lang_str(int id);
 
     /**
@@ -268,20 +268,21 @@ public interface WhisperCppJnaLibrary extends Library {
     void whisper_free_params(Pointer params);
 
     /**
-     * Run the entire model: PCM -> log mel spectrogram -> encoder -> decoder -> text
+     * Run the entire model: PCM -> log mel spectrogram -> encoder -> decoder -> text
      * Not thread safe for same context
      * Uses the specified decoding strategy to obtain the text.
      */
-    int whisper_full(Pointer ctx, WhisperFullParams params, final float[] samples, int n_samples);
+    int whisper_full(Pointer ctx, WhisperFullParams.ByValue params, final float[] samples, int n_samples);
 
-    int whisper_full_with_state(Pointer ctx, Pointer state, WhisperFullParams params, final float[] samples, int n_samples);
+    public int whisper_full_with_state(Pointer ctx, Pointer state, WhisperFullParams.ByValue params, float[] samples, int n_samples);
+    //int whisper_full_with_state(Pointer ctx, Pointer state, WhisperFullParams params, final float[] samples, int n_samples);
 
     // Split the input audio in chunks and process each chunk separately using whisper_full_with_state()
     // Result is stored in the default state of the context
     // Not thread safe if executed in parallel on the same context.
     // It seems this approach can offer some speedup in some cases.
     // However, the transcription accuracy can be worse at the beginning and end of each chunk.
-    int whisper_full_parallel(Pointer ctx, WhisperFullParams params, final float[] samples, int n_samples, int n_processors);
+    int whisper_full_parallel(Pointer ctx, WhisperFullParams.ByValue params, final float[] samples, int n_samples, int n_processors);
 
     /**
      * Number of generated text segments.

bindings/java/src/main/java/io/github/ggerganov/whispercpp/callbacks/GgmlAbortCallback.java

@@ -0,0 +1,17 @@
+package io.github.ggerganov.whispercpp.callbacks;
+
+import com.sun.jna.Callback;
+
+/**
+ * Callback for aborting GGML computation
+ * Maps to the C typedef: bool (*ggml_abort_callback)(void * data)
+ */
+public interface GgmlAbortCallback extends Callback {
+    /**
+     * Return true to abort the computation, false to continue
+     *
+     * @param data User data passed to the callback
+     * @return true to abort, false to continue
+     */
+    boolean invoke(com.sun.jna.Pointer data);
+}

bindings/java/src/main/java/io/github/ggerganov/whispercpp/params/WhisperAhead.java

@@ -0,0 +1,30 @@
+package io.github.ggerganov.whispercpp.params;
+import com.sun.jna.*;
+import java.util.Arrays;
+import java.util.List;
+
+public class WhisperAhead extends Structure {
+
+    public int n_text_layer;
+
+    public int n_head;
+
+    public WhisperAhead() {
+        super();
+    }
+
+    public WhisperAhead(int textLayer, int head) {
+        super();
+        this.n_text_layer = textLayer;
+        this.n_head = head;
+    }
+
+    @Override
+    protected List<String> getFieldOrder() {
+        return Arrays.asList("n_text_layer", "n_head");
+    }
+
+    public static class ByReference extends WhisperAhead implements Structure.ByReference {}
+
+    public static class ByValue extends WhisperAhead implements Structure.ByValue {}
+}

bindings/java/src/main/java/io/github/ggerganov/whispercpp/params/WhisperAheads.java

@@ -0,0 +1,41 @@
+package io.github.ggerganov.whispercpp.params;
+import com.sun.jna.*;
+import java.util.Arrays;
+import java.util.List;
+
+public class WhisperAheads extends Structure {
+    public NativeLong n_heads;
+
+    public Pointer heads;
+
+    public WhisperAheads() {
+        super();
+    }
+
+    /**
+     * Create alignment heads from an array of WhisperAhead objects
+     */
+    public void setHeads(WhisperAhead[] aheadsArray) {
+        this.n_heads = new NativeLong(aheadsArray.length);
+
+        int structSize = aheadsArray[0].size();
+        Memory mem = new Memory(structSize * aheadsArray.length);
+
+        for (int i = 0; i < aheadsArray.length; i++) {
+            aheadsArray[i].write();
+            byte[] buffer = aheadsArray[i].getPointer().getByteArray(0, structSize);
+            mem.write(i * structSize, buffer, 0, buffer.length);
+        }
+
+        this.heads = mem;
+    }
+
+    @Override
+    protected List<String> getFieldOrder() {
+        return Arrays.asList("n_heads", "heads");
+    }
+
+    public static class ByReference extends WhisperAheads implements Structure.ByReference {}
+
+    public static class ByValue extends WhisperAheads implements Structure.ByValue {}
+}

bindings/java/src/main/java/io/github/ggerganov/whispercpp/params/WhisperContextParams.java

@@ -1,7 +1,5 @@
 package io.github.ggerganov.whispercpp.params;
-
 import com.sun.jna.*;
-
 import java.util.Arrays;
 import java.util.List;
 
@@ -11,21 +9,73 @@ import java.util.List;
  * whisper_context_default_params()
  */
 public class WhisperContextParams extends Structure {
-
     public WhisperContextParams(Pointer p) {
         super(p);
     }
 
-    /** Use GPU for inference Number (default = true) */
+    public WhisperContextParams() {
+        super();
+    }
+
+    /** Use GPU for inference (default = true) */
     public CBool use_gpu;
 
-    /** Use GPU for inference Number (default = true) */
+    /** Use flash attention (default = false) */
+    public CBool flash_attn;
+
+    /** CUDA device to use (default = 0) */
+    public int gpu_device;
+
+    /** [EXPERIMENTAL] Enable token-level timestamps with DTW (default = false) */
+    public CBool dtw_token_timestamps;
+
+    /** [EXPERIMENTAL] Alignment heads preset for DTW */
+    public int dtw_aheads_preset;
+
+    /** Number of top layers to use for DTW when using WHISPER_AHEADS_N_TOP_MOST preset */
+    public int dtw_n_top;
+
+    public WhisperAheads.ByValue dtw_aheads;
+
+    /** DTW memory size (internal use) */
+    public NativeLong dtw_mem_size;
+
+    /** Use GPU for inference */
     public void useGpu(boolean enable) {
         use_gpu = enable ? CBool.TRUE : CBool.FALSE;
     }
 
+    /** Use flash attention */
+    public void useFlashAttn(boolean enable) {
+        flash_attn = enable ? CBool.TRUE : CBool.FALSE;
+    }
+
+    /** Enable DTW token-level timestamps */
+    public void enableDtwTokenTimestamps(boolean enable) {
+        dtw_token_timestamps = enable ? CBool.TRUE : CBool.FALSE;
+    }
+
+    /** Set DTW alignment heads preset */
+    public void setDtwAheadsPreset(int preset) {
+        dtw_aheads_preset = preset;
+    }
+
     @Override
     protected List<String> getFieldOrder() {
-        return Arrays.asList("use_gpu");
+        return Arrays.asList(
+            "use_gpu",
+            "flash_attn",
+            "gpu_device",
+            "dtw_token_timestamps",
+            "dtw_aheads_preset",
+            "dtw_n_top",
+            "dtw_aheads",
+            "dtw_mem_size"
+        );
+    }
+
+    public static class ByValue extends WhisperContextParams implements Structure.ByValue {
+        public ByValue() { super(); }
+        public ByValue(Pointer p) { super(p); }
     }
 }

bindings/java/src/main/java/io/github/ggerganov/whispercpp/params/WhisperFullParams.java

@@ -5,6 +5,7 @@ import io.github.ggerganov.whispercpp.callbacks.WhisperEncoderBeginCallback;
 import io.github.ggerganov.whispercpp.callbacks.WhisperLogitsFilterCallback;
 import io.github.ggerganov.whispercpp.callbacks.WhisperNewSegmentCallback;
 import io.github.ggerganov.whispercpp.callbacks.WhisperProgressCallback;
+import io.github.ggerganov.whispercpp.callbacks.GgmlAbortCallback;
 
 import java.util.Arrays;
 import java.util.List;
@@ -16,10 +17,12 @@ import java.util.List;
  */
 public class WhisperFullParams extends Structure {
 
+    public WhisperFullParams() {
+        super();
+    }
+
     public WhisperFullParams(Pointer p) {
         super(p);
-//        super(p, ALIGN_MSVC);
-//        super(p, ALIGN_GNUC);
     }
 
     /** Sampling strategy for whisper_full() function. */
@@ -69,10 +72,10 @@ public class WhisperFullParams extends Structure {
         single_segment = single ? CBool.TRUE : CBool.FALSE;
     }
 
-    /** Flag to print special tokens (e.g., <SOT>, <EOT>, <BEG>, etc.). (default = false) */
+    /** Flag to print special tokens (e.g., <SOT>, <EOT>, <BEG>, etc.). (default = false) */
     public CBool print_special;
 
-    /** Flag to print special tokens (e.g., <SOT>, <EOT>, <BEG>, etc.). (default = false) */
+    /** Flag to print special tokens (e.g., <SOT>, <EOT>, <BEG>, etc.). (default = false) */
     public void printSpecial(boolean enable) {
         print_special = enable ? CBool.TRUE : CBool.FALSE;
     }
@@ -129,6 +132,14 @@ public class WhisperFullParams extends Structure {
     /** Maximum tokens per segment (0, default = no limit) */
     public int max_tokens;
 
+    /** [EXPERIMENTAL] Enable debug mode for extra info */
+    public CBool debug_mode;
+
+    /** Enable debug mode */
+    public void enableDebugMode(boolean enable) {
+        debug_mode = enable ? CBool.TRUE : CBool.FALSE;
+    }
+
     /** Overwrite the audio context size (0 = use default). */
     public int audio_ctx;
 
@@ -274,6 +285,16 @@ public class WhisperFullParams extends Structure {
      */
     public Pointer encoder_begin_callback_user_data;
 
+    /** Callback used to abort GGML computation */
+    public Pointer abort_callback;
+
+    /** User data for the abort_callback */
+    public Pointer abort_callback_user_data;
+
+    public void setAbortCallback(GgmlAbortCallback callback) {
+        abort_callback = CallbackReference.getFunctionPointer(callback);
+    }
+
     /**
      * Callback by each decoder to filter obtained logits.
      * WhisperLogitsFilterCallback
@@ -310,17 +331,28 @@ public class WhisperFullParams extends Structure {
 
     @Override
     protected List<String> getFieldOrder() {
-        return Arrays.asList("strategy", "n_threads", "n_max_text_ctx", "offset_ms", "duration_ms", "translate",
-                "no_context", "single_segment", "no_timestamps",
-                "print_special", "print_progress", "print_realtime", "print_timestamps",  "token_timestamps",
-                "thold_pt", "thold_ptsum", "max_len", "split_on_word", "max_tokens", "audio_ctx",
-                "tdrz_enable", "suppress_regex", "initial_prompt", "prompt_tokens", "prompt_n_tokens", "language", "detect_language",
-                "suppress_blank", "suppress_nst", "temperature", "max_initial_ts", "length_penalty",
-                "temperature_inc", "entropy_thold", "logprob_thold", "no_speech_thold", "greedy", "beam_search",
-                "new_segment_callback", "new_segment_callback_user_data",
+        return Arrays.asList("strategy", "n_threads", "n_max_text_ctx",
+                "offset_ms", "duration_ms", "translate", "no_context",
+                "no_timestamps", "single_segment", "print_special",
+                "print_progress", "print_realtime", "print_timestamps",
+                "token_timestamps", "thold_pt", "thold_ptsum", "max_len",
+                "split_on_word", "max_tokens", "debug_mode", "audio_ctx", 
+                "tdrz_enable", "suppress_regex", "initial_prompt",
+                "prompt_tokens", "prompt_n_tokens", "language", "detect_language",
+                "suppress_blank", "suppress_nst", "temperature",
+                "max_initial_ts", "length_penalty", "temperature_inc",
+                "entropy_thold", "logprob_thold", "no_speech_thold", "greedy",
+                "beam_search", "new_segment_callback", "new_segment_callback_user_data",
                 "progress_callback", "progress_callback_user_data",
                 "encoder_begin_callback", "encoder_begin_callback_user_data",
+                "abort_callback", "abort_callback_user_data",
                 "logits_filter_callback", "logits_filter_callback_user_data",
                 "grammar_rules", "n_grammar_rules", "i_start_rule", "grammar_penalty");
     }
+
+    public static class ByValue extends WhisperFullParams implements Structure.ByValue {
+        public ByValue() { super(); }
+        public ByValue(Pointer p) { super(p); }
+    }
+
 }

bindings/java/src/test/java/io/github/ggerganov/whispercpp/WhisperCppTest.java

@@ -76,7 +76,7 @@ class WhisperCppTest {
         float[] floats = new float[b.length / 2];
 
         //WhisperFullParams params = whisper.getFullDefaultParams(WhisperSamplingStrategy.WHISPER_SAMPLING_GREEDY);
-        WhisperFullParams params = whisper.getFullDefaultParams(WhisperSamplingStrategy.WHISPER_SAMPLING_BEAM_SEARCH);
+        WhisperFullParams.ByValue params = whisper.getFullDefaultParams(WhisperSamplingStrategy.WHISPER_SAMPLING_BEAM_SEARCH);
         params.setProgressCallback((ctx, state, progress, user_data) -> System.out.println("progress: " + progress));
         params.print_progress = CBool.FALSE;
         //params.initial_prompt = "and so my fellow Americans um, like";

bindings/javascript/README.md

@@ -33,6 +33,9 @@ mkdir build-em && cd build-em
 emcmake cmake .. && make -j
 
 # run test
+node ../tests/test-whisper.js
+
+# For Node.js versions prior to v16.4.0, experimental features need to be enabled:
 node --experimental-wasm-threads --experimental-wasm-simd ../tests/test-whisper.js
 
 # publish npm package

bindings/javascript/package.json

@@ -1,6 +1,6 @@
 {
   "name": "whisper.cpp",
-  "version": "1.7.4",
+  "version": "1.7.5",
   "description": "Whisper speech recognition",
   "main": "whisper.js",
   "scripts": {

bindings/ruby/README.md

@@ -228,7 +228,7 @@ The second argument `samples` may be an array, an object with `length` and `each
 Development
 -----------
 
-    % git clone https://github.com/ggerganov/whisper.cpp.git
+    % git clone https://github.com/ggml-org/whisper.cpp.git
     % cd whisper.cpp/bindings/ruby
     % rake test
 
@@ -241,5 +241,5 @@ License
 
 The same to [whisper.cpp][].
 
-[whisper.cpp]: https://github.com/ggerganov/whisper.cpp
-[models]: https://github.com/ggerganov/whisper.cpp/tree/master/models
+[whisper.cpp]: https://github.com/ggml-org/whisper.cpp
+[models]: https://github.com/ggml-org/whisper.cpp/tree/master/models

bindings/ruby/ext/cpu.mk

@@ -1,5 +1,9 @@
 ggml/src/ggml-cpu/ggml-cpu-cpp.o: \
 	ggml/src/ggml-cpu/ggml-cpu.cpp \
+	ggml/src/ggml-cpu/unary-ops.cpp \
+	ggml/src/ggml-cpu/binary-ops.cpp \
+	ggml/src/ggml-cpu/vec.cpp \
+	ggml/src/ggml-cpu/ops.cpp \
 	ggml/include/ggml-backend.h \
 	ggml/include/ggml.h \
 	ggml/include/ggml-alloc.h \

bindings/ruby/ext/extconf.rb

@@ -168,7 +168,11 @@ $OBJ_GGML <<
   'ggml/src/ggml-cpu/ggml-cpu-aarch64.o' <<
   'ggml/src/ggml-cpu/ggml-cpu-hbm.o' <<
   'ggml/src/ggml-cpu/ggml-cpu-quants.o' <<
-  'ggml/src/ggml-cpu/ggml-cpu-traits.o'
+  'ggml/src/ggml-cpu/ggml-cpu-traits.o' <<
+  'ggml/src/ggml-cpu/unary-ops.o' <<
+  'ggml/src/ggml-cpu/binary-ops.o' <<
+  'ggml/src/ggml-cpu/vec.o' <<
+  'ggml/src/ggml-cpu/ops.o'
 
 $OBJ_WHISPER <<
   'src/whisper.o' <<

bindings/ruby/ext/ruby_whisper_params.c

@@ -918,7 +918,7 @@ ruby_whisper_params_initialize(int argc, VALUE *argv, VALUE self)
     return self;
   }
 
-  rb_get_kwargs(kw_hash, &param_names, 0, RUBY_WHISPER_PARAMS_PARAM_NAMES_COUNT, &values);
+  rb_get_kwargs(kw_hash, param_names, 0, RUBY_WHISPER_PARAMS_PARAM_NAMES_COUNT, values);
   Data_Get_Struct(self, ruby_whisper_params, rwp);
 
   for (i = 0; i < RUBY_WHISPER_PARAMS_PARAM_NAMES_COUNT; i++) {

bindings/ruby/lib/whisper/model/uri.rb

@@ -34,7 +34,7 @@ module Whisper
                when /darwin/
                  Pathname(Dir.home)/"Library/Caches"
                else
-                 ENV.key?("XDG_CACHE_HOME") ? ENV["XDG_CACHE_HOME"] : Pathname(Dir.home)/".cache"
+                 ENV.key?("XDG_CACHE_HOME") ? Pathname(ENV["XDG_CACHE_HOME"]) : Pathname(Dir.home)/".cache"
                end
         base/"whisper.cpp"
       end

bindings/ruby/tests/test_callback.rb

@@ -25,7 +25,7 @@ class TestCallback < TestBase
         assert start_time >= 0
         assert_kind_of Integer, end_time
         assert end_time > 0
-        assert_match /ask not what your country can do for you, ask what you can do for your country/, text if i_segment == 0
+        assert_match(/ask not what your country can do for you, ask what you can do for your country/, text) if i_segment == 0
       end
     }
 
@@ -145,9 +145,9 @@ class TestCallback < TestBase
 
   def test_abort_on
     do_abort = false
-    aborted_from_callback = false
+    _aborted_from_callback = false
     @params.on_new_segment do |segment|
-      do_abort = true if segment.text.match? /ask/
+      do_abort = true if segment.text.match?(/ask/)
     end
     i = 0
     @params.abort_on do

bindings/ruby/tests/test_error.rb

@@ -4,7 +4,7 @@ class TestError < TestBase
   def test_error
     error = Whisper::Error.new(-2)
     assert_equal "failed to compute log mel spectrogram", error.message
-    assert_equal -2, error.code
+    assert_equal(-2, error.code)
   end
 
   def test_unknown_error
@@ -14,7 +14,7 @@ class TestError < TestBase
 
   def test_non_int_code
     assert_raise TypeError do
-      error = Whisper::Error.new("non int")
+      _error = Whisper::Error.new("non int")
     end
   end
 end

bindings/ruby/tests/test_params.rb

@@ -162,7 +162,7 @@ class TestParams < TestBase
   end
 
   def test_length_penalty
-    assert_equal -1.0, @params.length_penalty
+    assert_equal(-1.0, @params.length_penalty)
     @params.length_penalty = 0.5
     assert_equal 0.5, @params.length_penalty
   end
@@ -180,9 +180,9 @@ class TestParams < TestBase
   end
 
   def test_logprob_thold
-    assert_in_delta -1.0, @params.logprob_thold
+    assert_in_delta(-1.0, @params.logprob_thold)
     @params.logprob_thold = -0.5
-    assert_in_delta -0.5, @params.logprob_thold
+    assert_in_delta(-0.5, @params.logprob_thold)
   end
 
   def test_no_speech_thold

bindings/ruby/tests/test_segment.rb

@@ -49,13 +49,13 @@ class TestSegment < TestBase
       if index == 0
         seg = segment
         assert_equal 0, segment.start_time
-        assert_match /ask not what your country can do for you, ask what you can do for your country/, segment.text
+        assert_match(/ask not what your country can do for you, ask what you can do for your country/, segment.text)
       end
       index += 1
     end
     whisper.transcribe(AUDIO, params)
     assert_equal 0, seg.start_time
-    assert_match /ask not what your country can do for you, ask what you can do for your country/, seg.text
+    assert_match(/ask not what your country can do for you, ask what you can do for your country/, seg.text)
   end
 
   def test_on_new_segment_twice

bindings/ruby/tests/test_whisper.rb

@@ -16,7 +16,7 @@ class TestWhisper < TestBase
     params.print_timestamps = false
 
     @whisper.transcribe(AUDIO, params) {|text|
-      assert_match /ask not what your country can do for you, ask what you can do for your country/, text
+      assert_match(/ask not what your country can do for you, ask what you can do for your country/, text)
     }
   end
 
@@ -32,7 +32,7 @@ class TestWhisper < TestBase
     def test_full_get_segment
       segment = whisper.full_get_segment(0)
       assert_equal 0, segment.start_time
-      assert_match /ask not what your country can do for you, ask what you can do for your country/, segment.text
+      assert_match(/ask not what your country can do for you, ask what you can do for your country/, segment.text)
     end
 
     def test_full_get_segment_t0
@@ -59,7 +59,7 @@ class TestWhisper < TestBase
     end
 
     def test_full_get_segment_text
-      assert_match /ask not what your country can do for you, ask what you can do for your country/, whisper.full_get_segment_text(0)
+      assert_match(/ask not what your country can do for you, ask what you can do for your country/, whisper.full_get_segment_text(0))
     end
 
     def test_full_get_segment_no_speech_prob
@@ -134,14 +134,14 @@ class TestWhisper < TestBase
       @whisper.full(@params, @samples, @samples.length)
 
       assert_equal 1, @whisper.full_n_segments
-      assert_match /ask not what your country can do for you, ask what you can do for your country/, @whisper.each_segment.first.text
+      assert_match(/ask not what your country can do for you, ask what you can do for your country/, @whisper.each_segment.first.text)
     end
 
     def test_full_without_length
       @whisper.full(@params, @samples)
 
       assert_equal 1, @whisper.full_n_segments
-      assert_match /ask not what your country can do for you, ask what you can do for your country/, @whisper.each_segment.first.text
+      assert_match(/ask not what your country can do for you, ask what you can do for your country/, @whisper.each_segment.first.text)
     end
 
     def test_full_enumerator
@@ -149,7 +149,7 @@ class TestWhisper < TestBase
       @whisper.full(@params, samples, @samples.length)
 
       assert_equal 1, @whisper.full_n_segments
-      assert_match /ask not what your country can do for you, ask what you can do for your country/, @whisper.each_segment.first.text
+      assert_match(/ask not what your country can do for you, ask what you can do for your country/, @whisper.each_segment.first.text)
     end
 
     def test_full_enumerator_without_length
@@ -171,26 +171,28 @@ class TestWhisper < TestBase
       @whisper.full(@params, samples)
 
       assert_equal 1, @whisper.full_n_segments
-      assert_match /ask not what your country can do for you, ask what you can do for your country/, @whisper.each_segment.first.text
+      assert_match(/ask not what your country can do for you, ask what you can do for your country/, @whisper.each_segment.first.text)
     end
 
     def test_full_parallel
-      @whisper.full_parallel(@params, @samples, @samples.length, Etc.nprocessors)
+      nprocessors = 2
+      @whisper.full_parallel(@params, @samples, @samples.length, nprocessors)
 
-      assert_equal Etc.nprocessors, @whisper.full_n_segments
+      assert_equal nprocessors, @whisper.full_n_segments
       text = @whisper.each_segment.collect(&:text).join
-      assert_match /ask what you can do/i, text
-      assert_match /for your country/i, text
+      assert_match(/ask what you can do/i, text)
+      assert_match(/for your country/i, text)
     end
 
     def test_full_parallel_with_memory_view
+      nprocessors = 2
       samples = JFKReader.new(AUDIO)
-      @whisper.full_parallel(@params, samples, nil, Etc.nprocessors)
+      @whisper.full_parallel(@params, samples, nil, nprocessors)
 
-      assert_equal Etc.nprocessors, @whisper.full_n_segments
+      assert_equal nprocessors, @whisper.full_n_segments
       text = @whisper.each_segment.collect(&:text).join
-      assert_match /ask what you can do/i, text
-      assert_match /for your country/i, text
+      assert_match(/ask what you can do/i, text)
+      assert_match(/for your country/i, text)
     end
 
     def test_full_parallel_without_length_and_n_processors
@@ -198,17 +200,18 @@ class TestWhisper < TestBase
 
       assert_equal 1, @whisper.full_n_segments
       text = @whisper.each_segment.collect(&:text).join
-      assert_match /ask what you can do/i, text
-      assert_match /for your country/i, text
+      assert_match(/ask what you can do/i, text)
+      assert_match(/for your country/i, text)
     end
 
     def test_full_parallel_without_length
-      @whisper.full_parallel(@params, @samples, nil, Etc.nprocessors)
+      nprocessors = 2
+      @whisper.full_parallel(@params, @samples, nil, nprocessors)
 
-      assert_equal Etc.nprocessors, @whisper.full_n_segments
+      assert_equal nprocessors, @whisper.full_n_segments
       text = @whisper.each_segment.collect(&:text).join
-      assert_match /ask what you can do/i, text
-      assert_match /for your country/i, text
+      assert_match(/ask what you can do/i, text)
+      assert_match(/for your country/i, text)
     end
 
     def test_full_parallel_without_n_processors
@@ -216,8 +219,8 @@ class TestWhisper < TestBase
 
       assert_equal 1, @whisper.full_n_segments
       text = @whisper.each_segment.collect(&:text).join
-      assert_match /ask what you can do/i, text
-      assert_match /for your country/i, text
+      assert_match(/ask what you can do/i, text)
+      assert_match(/for your country/i, text)
     end
   end
 end

bindings/ruby/whispercpp.gemspec

@@ -26,7 +26,7 @@ Gem::Specification.new do |s|
   s.required_ruby_version = '>= 3.1.0'
 
   #### Documentation and testing.
-  s.homepage = 'https://github.com/ggerganov/whisper.cpp'
+  s.homepage = 'https://github.com/ggml-org/whisper.cpp'
   s.rdoc_options = ['--main', 'README.md']
 
 

build-xcframework.sh

@@ -41,6 +41,11 @@ COMMON_CMAKE_ARGS=(
     -DGGML_OPENMP=${GGML_OPENMP}
 )
 
+XCODE_VERSION=$(xcodebuild -version 2>/dev/null | head -n1 | awk '{ print $2 }')
+MAJOR_VERSION=$(echo $XCODE_VERSION | cut -d. -f1)
+MINOR_VERSION=$(echo $XCODE_VERSION | cut -d. -f2)
+echo "Detected Xcode version: $XCODE_VERSION"
+
 check_required_tool() {
     local tool=$1
     local install_message=$2
@@ -108,7 +113,7 @@ setup_framework_structure() {
     fi
 
     # Copy all required headers (common for all platforms)
-    cp include/whisper.h             ${header_path}
+    cp include/whisper.h           ${header_path}
     cp ggml/include/ggml.h         ${header_path}
     cp ggml/include/ggml-alloc.h   ${header_path}
     cp ggml/include/ggml-backend.h ${header_path}
@@ -245,9 +250,16 @@ combine_static_libraries() {
         "${base_dir}/${build_dir}/ggml/src/ggml-metal/${release_dir}/libggml-metal.a"
         "${base_dir}/${build_dir}/ggml/src/ggml-blas/${release_dir}/libggml-blas.a"
     )
+    if [[ "$platform" == "macos" || "$platform" == "ios" ]]; then
+        echo "Adding libwhisper.coreml library to the build."
+        libs+=(
+            "${base_dir}/${build_dir}/src/${release_dir}/libwhisper.coreml.a"
+        )
+    fi
 
     # Create temporary directory for processing
     local temp_dir="${base_dir}/${build_dir}/temp"
+    echo "Creating temporary directory: ${temp_dir}"
     mkdir -p "${temp_dir}"
 
     # Since we have multiple architectures libtool will find object files that do not
@@ -259,6 +271,7 @@ combine_static_libraries() {
     local archs=""
     local min_version_flag=""
     local install_name=""
+    local frameworks="-framework Foundation -framework Metal -framework Accelerate"
 
     case "$platform" in
         "ios")
@@ -272,12 +285,14 @@ combine_static_libraries() {
                 min_version_flag="-mios-version-min=${IOS_MIN_OS_VERSION}"
             fi
             install_name="@rpath/whisper.framework/whisper"
+            frameworks+=" -framework CoreML"
             ;;
         "macos")
             sdk="macosx"
             archs="arm64 x86_64"
             min_version_flag="-mmacosx-version-min=${MACOS_MIN_OS_VERSION}"
             install_name="@rpath/whisper.framework/Versions/Current/whisper"
+            frameworks+=" -framework CoreML"
             ;;
         "visionos")
             if [[ "$is_simulator" == "true" ]]; then
@@ -319,27 +334,34 @@ combine_static_libraries() {
         $arch_flags \
         $min_version_flag \
         -Wl,-force_load,"${temp_dir}/combined.a" \
-        -framework Foundation -framework Metal -framework Accelerate \
+        $frameworks \
         -install_name "$install_name" \
         -o "${base_dir}/${output_lib}"
 
     # Platform-specific post-processing for device builds
     if [[ "$is_simulator" == "false" ]]; then
-        if command -v vtool &>/dev/null; then
+        if command -v xcrun vtool &>/dev/null; then
             case "$platform" in
                 "ios")
                     echo "Marking binary as a framework binary for iOS..."
-                    vtool -set-build-version ios ${IOS_MIN_OS_VERSION} ${IOS_MIN_OS_VERSION} -replace \
+                    xcrun vtool -set-build-version ios ${IOS_MIN_OS_VERSION} ${IOS_MIN_OS_VERSION} -replace \
                         -output "${base_dir}/${output_lib}" "${base_dir}/${output_lib}"
                     ;;
                 "visionos")
                     echo "Marking binary as a framework binary for visionOS..."
-                    vtool -set-build-version xros ${VISIONOS_MIN_OS_VERSION} ${VISIONOS_MIN_OS_VERSION} -replace \
+                    if [[ "$MAJOR_VERSION" -gt 16 ]] || [[ "$MAJOR_VERSION" -eq 16 && "$MINOR_VERSION" -gt 2 ]]; then
+                        echo "Xcode version greater than 16.2, using visionOS."
+                        VISION_OS_BUILD_VERSION="visionos"
+                    else
+                        echo "Xcode version less than or equal to 16.2, using xros."
+                        VISION_OS_BUILD_VERSION="xros"
+                    fi
+                    xcrun vtool -set-build-version ${VISION_OS_BUILD_VERSION} ${VISIONOS_MIN_OS_VERSION} ${VISIONOS_MIN_OS_VERSION} -replace \
                         -output "${base_dir}/${output_lib}" "${base_dir}/${output_lib}"
                     ;;
                 "tvos")
                     echo "Marking binary as a framework binary for tvOS..."
-                    vtool -set-build-version tvos ${TVOS_MIN_OS_VERSION} ${TVOS_MIN_OS_VERSION} -replace \
+                    xcrun vtool -set-build-version tvos ${TVOS_MIN_OS_VERSION} ${TVOS_MIN_OS_VERSION} -replace \
                         -output "${base_dir}/${output_lib}" "${base_dir}/${output_lib}"
                     ;;
             esac
@@ -399,6 +421,8 @@ cmake -B build-ios-sim -G Xcode \
     -DCMAKE_XCODE_ATTRIBUTE_SUPPORTED_PLATFORMS=iphonesimulator \
     -DCMAKE_C_FLAGS="${COMMON_C_FLAGS}" \
     -DCMAKE_CXX_FLAGS="${COMMON_CXX_FLAGS}" \
+    -DWHISPER_COREML="ON" \
+    -DWHISPER_COREML_ALLOW_FALLBACK="ON" \
     -S .
 cmake --build build-ios-sim --config Release -- -quiet
 
@@ -411,6 +435,8 @@ cmake -B build-ios-device -G Xcode \
     -DCMAKE_XCODE_ATTRIBUTE_SUPPORTED_PLATFORMS=iphoneos \
     -DCMAKE_C_FLAGS="${COMMON_C_FLAGS}" \
     -DCMAKE_CXX_FLAGS="${COMMON_CXX_FLAGS}" \
+    -DWHISPER_COREML="ON" \
+    -DWHISPER_COREML_ALLOW_FALLBACK="ON" \
     -S .
 cmake --build build-ios-device --config Release -- -quiet
 
@@ -421,6 +447,8 @@ cmake -B build-macos -G Xcode \
     -DCMAKE_OSX_ARCHITECTURES="arm64;x86_64" \
     -DCMAKE_C_FLAGS="${COMMON_C_FLAGS}" \
     -DCMAKE_CXX_FLAGS="${COMMON_CXX_FLAGS}" \
+    -DWHISPER_COREML="ON" \
+    -DWHISPER_COREML_ALLOW_FALLBACK="ON" \
     -S .
 cmake --build build-macos --config Release -- -quiet
 
@@ -432,8 +460,8 @@ cmake -B build-visionos -G Xcode \
     -DCMAKE_SYSTEM_NAME=visionOS \
     -DCMAKE_OSX_SYSROOT=xros \
     -DCMAKE_XCODE_ATTRIBUTE_SUPPORTED_PLATFORMS=xros \
-    -DCMAKE_C_FLAGS="-D_XOPEN_SOURCE=700 -Du_int=unsigned\ int -Du_char=unsigned\ char -Du_short=unsigned\ short ${COMMON_C_FLAGS}" \
-    -DCMAKE_CXX_FLAGS="-D_XOPEN_SOURCE=700 -Du_int=unsigned\ int -Du_char=unsigned\ char -Du_short=unsigned\ short ${COMMON_CXX_FLAGS}" \
+    -DCMAKE_C_FLAGS="-D_XOPEN_SOURCE=700 ${COMMON_C_FLAGS}" \
+    -DCMAKE_CXX_FLAGS="-D_XOPEN_SOURCE=700 ${COMMON_CXX_FLAGS}" \
     -S .
 cmake --build build-visionos --config Release -- -quiet
 
@@ -445,8 +473,8 @@ cmake -B build-visionos-sim -G Xcode \
     -DCMAKE_SYSTEM_NAME=visionOS \
     -DCMAKE_OSX_SYSROOT=xrsimulator \
     -DCMAKE_XCODE_ATTRIBUTE_SUPPORTED_PLATFORMS=xrsimulator \
-    -DCMAKE_C_FLAGS="-D_XOPEN_SOURCE=700 -Du_int=unsigned\ int -Du_char=unsigned\ char -Du_short=unsigned\ short ${COMMON_C_FLAGS}" \
-    -DCMAKE_CXX_FLAGS="-D_XOPEN_SOURCE=700 -Du_int=unsigned\ int -Du_char=unsigned\ char -Du_short=unsigned\ short ${COMMON_CXX_FLAGS}" \
+    -DCMAKE_C_FLAGS="-D_XOPEN_SOURCE=700 ${COMMON_C_FLAGS}" \
+    -DCMAKE_CXX_FLAGS="-D_XOPEN_SOURCE=700 ${COMMON_CXX_FLAGS}" \
     -S .
 cmake --build build-visionos-sim --config Release -- -quiet
 

ci/README.md

@@ -21,7 +21,7 @@ mkdir tmp
 bash ./ci/run.sh ./tmp/results ./tmp/mnt
 
 # with CUDA support
-GGML_CUDA=1 bash ./ci/run.sh ./tmp/results ./tmp/mnt
+GG_BUILD_CUDA=1 bash ./ci/run.sh ./tmp/results ./tmp/mnt
 ```
 
 ## Environment Variables
@@ -30,12 +30,12 @@ The CI script supports several environment variables to control the build:
 
 | Variable | Description |
 |----------|-------------|
-| `GGML_CUDA` | Enable NVIDIA CUDA GPU acceleration |
-| `GGML_SYCL` | Enable Intel SYCL acceleration |
-| `GGML_VULKAN` | Enable Vulkan GPU acceleration |
-| `GGML_METAL` | Enable Metal acceleration on Apple Silicon |
-| `GGML_BLAS` | Enable BLAS CPU acceleration |
-| `WHISPER_OPENVINO` | Enable OpenVINO support |
-| `WHISPER_COREML` | Enable Core ML support for Apple Neural Engine |
+| `GG_BUILD_CUDA` | Enable NVIDIA CUDA GPU acceleration |
+| `GG_BUILD_SYCL` | Enable Intel SYCL acceleration |
+| `GG_BUILD_VULKAN` | Enable Vulkan GPU acceleration |
+| `GG_BUILD_METAL` | Enable Metal acceleration on Apple Silicon |
+| `GG_BUILD_BLAS` | Enable BLAS CPU acceleration |
+| `GG_BUILD_OPENVINO` | Enable OpenVINO support |
+| `GG_BUILD_COREML` | Enable Core ML support for Apple Neural Engine |
 | `GG_BUILD_LOW_PERF` | Limit tests for low-performance hardware |
-| `GGML_TEST_MODELS` | Comma-separated list of models to test (e.g. "tiny.en,tiny,base,medium", defaults to all models unless `GG_BUILD_LOW_PERF` is set) |
+| `GG_BUILD_TEST_MODELS` | Comma-separated list of models to test (e.g. "tiny.en,tiny,base,medium", defaults to all models unless `GG_BUILD_LOW_PERF` is set) |

ci/run.sh

@@ -8,8 +8,10 @@
 # bash ./ci/run.sh ./tmp/results ./tmp/mnt
 #
 # # with CUDA support
-# GGML_CUDA=1 bash ./ci/run.sh ./tmp/results ./tmp/mnt
+# GG_BUILD_CUDA=1 bash ./ci/run.sh ./tmp/results ./tmp/mnt
 #
+# # with SYCL support
+# GG_BUILD_SYCL=1 bash ./ci/run.sh ./tmp/results ./tmp/mnt
 
 if [ -z "$2" ]; then
     echo "usage: $0 <output-dir> <mnt-dir>"
@@ -36,8 +38,8 @@ BENCH_ENCODER_ONLY=0
 BENCH_FLASH_ATTN=0
 
 # check for user-specified models first. if not specified, use fast models
-if [ ! -z ${GGML_TEST_MODELS} ]; then
-    IFS=',' read -r -a MODELS <<< "${GGML_TEST_MODELS}"
+if [ ! -z ${GG_BUILD_TEST_MODELS} ]; then
+    IFS=',' read -r -a MODELS <<< "${GG_BUILD_TEST_MODELS}"
 else
     if [ ! -z ${GG_BUILD_LOW_PERF} ]; then
         MODELS=( "tiny" "base" "small" )
@@ -48,11 +50,11 @@ fi
 
 CMAKE_EXTRA="-DWHISPER_FATAL_WARNINGS=ON"
 
-if [ ! -z ${GGML_CUDA} ]; then
+if [ ! -z ${GG_BUILD_CUDA} ]; then
     CMAKE_EXTRA="${CMAKE_EXTRA} -DGGML_CUDA=ON -DCMAKE_CUDA_ARCHITECTURES=native"
 fi
 
-if [ ! -z ${GGML_SYCL} ]; then
+if [ ! -z ${GG_BUILD_SYCL} ]; then
     if [ -z ${ONEAPI_ROOT} ]; then
         echo "Not detected ONEAPI_ROOT, please install oneAPI base toolkit and enable it by:"
         echo "source /opt/intel/oneapi/setvars.sh"
@@ -62,23 +64,23 @@ if [ ! -z ${GGML_SYCL} ]; then
     CMAKE_EXTRA="${CMAKE_EXTRA} -DGGML_SYCL=ON -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx -DGGML_SYCL_F16=ON"
 fi
 
-if [ ! -z ${WHISPER_OPENVINO} ]; then
+if [ ! -z ${GG_BUILD_OPENVINO} ]; then
     CMAKE_EXTRA="${CMAKE_EXTRA} -DWHISPER_OPENVINO=ON"
 fi
 
-if [ ! -z ${GGML_METAL} ]; then
+if [ ! -z ${GG_BUILD_METAL} ]; then
     CMAKE_EXTRA="${CMAKE_EXTRA} -DGGML_METAL=ON"
 fi
 
-if [ ! -z ${GGML_VULKAN} ]; then
+if [ ! -z ${GG_BUILD_VULKAN} ]; then
     CMAKE_EXTRA="${CMAKE_EXTRA} -DGGML_VULKAN=ON"
 fi
 
-if [ ! -z ${GGML_BLAS} ]; then
+if [ ! -z ${GG_BUILD_BLAS} ]; then
     CMAKE_EXTRA="${CMAKE_EXTRA} -DGGML_BLAS=ON"
 fi
 
-if [ ! -z ${WHISPER_COREML} ]; then
+if [ ! -z ${GG_BUILD_COREML} ]; then
     CMAKE_EXTRA="${CMAKE_EXTRA} -DWHISPER_COREML=ON"
 fi
 
@@ -324,8 +326,9 @@ ret=0
 for model in "${MODELS[@]}"; do
     test $ret -eq 0 && gg_download_model ${model}
 done
-
-test $ret -eq 0 && gg_run ctest debug
+if [ -z ${GG_BUILD_SYCL}]; then
+    test $ret -eq 0 && gg_run ctest debug
+fi
 test $ret -eq 0 && gg_run ctest release
 
 test $ret -eq 0 && gg_run bench

examples/addon.node/__test__/whisper.spec.js

@@ -18,6 +18,7 @@ const whisperParamsMock = {
   translate: true,
   no_timestamps: false,
   audio_ctx: 0,
+  max_len: 0,
 };
 
 describe("Run whisper.node", () => {

examples/addon.node/addon.cpp

@@ -128,192 +128,227 @@ void whisper_print_segment_callback(struct whisper_context * ctx, struct whisper
 
 void cb_log_disable(enum ggml_log_level, const char *, void *) {}
 
-int run(whisper_params &params, std::vector<std::vector<std::string>> &result) {
-    if (params.no_prints) {
-        whisper_log_set(cb_log_disable, NULL);
-    }
-
-    if (params.fname_inp.empty() && params.pcmf32.empty()) {
-        fprintf(stderr, "error: no input files or audio buffer specified\n");
-        return 2;
-    }
-
-    if (params.language != "auto" && whisper_lang_id(params.language.c_str()) == -1) {
-        fprintf(stderr, "error: unknown language '%s'\n", params.language.c_str());
-        exit(0);
-    }
-
-    // whisper init
-
-    struct whisper_context_params cparams = whisper_context_default_params();
-    cparams.use_gpu = params.use_gpu;
-    cparams.flash_attn = params.flash_attn;
-    struct whisper_context * ctx = whisper_init_from_file_with_params(params.model.c_str(), cparams);
-
-    if (ctx == nullptr) {
-        fprintf(stderr, "error: failed to initialize whisper context\n");
-        return 3;
-    }
-
-    // if params.pcmf32 is provided, set params.fname_inp to "buffer"
-    // this is simpler than further modifications in the code
-    if (!params.pcmf32.empty()) {
-        fprintf(stderr, "info: using audio buffer as input\n");
-        params.fname_inp.clear();
-        params.fname_inp.emplace_back("buffer");
-    }
-
-    for (int f = 0; f < (int) params.fname_inp.size(); ++f) {
-        const auto fname_inp = params.fname_inp[f];
-        const auto fname_out = f < (int)params.fname_out.size() && !params.fname_out[f].empty() ? params.fname_out[f] : params.fname_inp[f];
-
-        std::vector<float> pcmf32; // mono-channel F32 PCM
-        std::vector<std::vector<float>> pcmf32s; // stereo-channel F32 PCM
-
-        // read the input audio file if params.pcmf32 is not provided
-        if (params.pcmf32.empty()) {
-            if (!::read_audio_data(fname_inp, pcmf32, pcmf32s, params.diarize)) {
-                fprintf(stderr, "error: failed to read audio file '%s'\n", fname_inp.c_str());
-                continue;
-            }
-        } else {
-            pcmf32 = params.pcmf32;
-        }
-
-        // print system information
-        if (!params.no_prints) {
-            fprintf(stderr, "\n");
-            fprintf(stderr, "system_info: n_threads = %d / %d | %s\n",
-                    params.n_threads*params.n_processors, std::thread::hardware_concurrency(), whisper_print_system_info());
-        }
-
-        // print some info about the processing
-        if (!params.no_prints) {
-            fprintf(stderr, "\n");
-            if (!whisper_is_multilingual(ctx)) {
-                if (params.language != "en" || params.translate) {
-                    params.language = "en";
-                    params.translate = false;
-                    fprintf(stderr, "%s: WARNING: model is not multilingual, ignoring language and translation options\n", __func__);
-                }
-            }
-            fprintf(stderr, "%s: processing '%s' (%d samples, %.1f sec), %d threads, %d processors, lang = %s, task = %s, timestamps = %d, audio_ctx = %d ...\n",
-                    __func__, fname_inp.c_str(), int(pcmf32.size()), float(pcmf32.size())/WHISPER_SAMPLE_RATE,
-                    params.n_threads, params.n_processors,
-                    params.language.c_str(),
-                    params.translate ? "translate" : "transcribe",
-                    params.no_timestamps ? 0 : 1,
-                    params.audio_ctx);
-
-            fprintf(stderr, "\n");
-        }
-
-        // run the inference
-        {
-            whisper_full_params wparams = whisper_full_default_params(WHISPER_SAMPLING_GREEDY);
-
-            wparams.strategy = params.beam_size > 1 ? WHISPER_SAMPLING_BEAM_SEARCH : WHISPER_SAMPLING_GREEDY;
-
-            wparams.print_realtime   = false;
-            wparams.print_progress   = params.print_progress;
-            wparams.print_timestamps = !params.no_timestamps;
-            wparams.print_special    = params.print_special;
-            wparams.translate        = params.translate;
-            wparams.language         = params.language.c_str();
-            wparams.n_threads        = params.n_threads;
-            wparams.n_max_text_ctx   = params.max_context >= 0 ? params.max_context : wparams.n_max_text_ctx;
-            wparams.offset_ms        = params.offset_t_ms;
-            wparams.duration_ms      = params.duration_ms;
-
-            wparams.token_timestamps = params.output_wts || params.max_len > 0;
-            wparams.thold_pt         = params.word_thold;
-            wparams.entropy_thold    = params.entropy_thold;
-            wparams.logprob_thold    = params.logprob_thold;
-            wparams.max_len          = params.output_wts && params.max_len == 0 ? 60 : params.max_len;
-            wparams.audio_ctx        = params.audio_ctx;
-
-            wparams.greedy.best_of        = params.best_of;
-            wparams.beam_search.beam_size = params.beam_size;
-
-            wparams.initial_prompt   = params.prompt.c_str();
-
-            wparams.no_timestamps    = params.no_timestamps;
-
-            whisper_print_user_data user_data = { &params, &pcmf32s };
-
-            // this callback is called on each new segment
-            if (!wparams.print_realtime) {
-                wparams.new_segment_callback           = whisper_print_segment_callback;
-                wparams.new_segment_callback_user_data = &user_data;
-            }
-
-            // example for abort mechanism
-            // in this example, we do not abort the processing, but we could if the flag is set to true
-            // the callback is called before every encoder run - if it returns false, the processing is aborted
-            {
-                static bool is_aborted = false; // NOTE: this should be atomic to avoid data race
-
-                wparams.encoder_begin_callback = [](struct whisper_context * /*ctx*/, struct whisper_state * /*state*/, void * user_data) {
-                    bool is_aborted = *(bool*)user_data;
-                    return !is_aborted;
-                };
-                wparams.encoder_begin_callback_user_data = &is_aborted;
-            }
-
-            if (whisper_full_parallel(ctx, wparams, pcmf32.data(), pcmf32.size(), params.n_processors) != 0) {
-                fprintf(stderr, "failed to process audio\n");
-                return 10;
-            }
-        }
-    }
-
-    const int n_segments = whisper_full_n_segments(ctx);
-    result.resize(n_segments);
-    for (int i = 0; i < n_segments; ++i) {
-        const char * text = whisper_full_get_segment_text(ctx, i);
-        const int64_t t0 = whisper_full_get_segment_t0(ctx, i);
-        const int64_t t1 = whisper_full_get_segment_t1(ctx, i);
-
-        result[i].emplace_back(to_timestamp(t0, params.comma_in_time));
-        result[i].emplace_back(to_timestamp(t1, params.comma_in_time));
-        result[i].emplace_back(text);
-    }
-
-    whisper_print_timings(ctx);
-    whisper_free(ctx);
-
-    return 0;
-}
-
-class Worker : public Napi::AsyncWorker {
+class ProgressWorker : public Napi::AsyncWorker {
  public:
-  Worker(Napi::Function& callback, whisper_params params)
-      : Napi::AsyncWorker(callback), params(params) {}
-
-  void Execute() override {
-    run(params, result);
-  }
-
-  void OnOK() override {
-    Napi::HandleScope scope(Env());
-    Napi::Object res = Napi::Array::New(Env(), result.size());
-    for (uint64_t i = 0; i < result.size(); ++i) {
-      Napi::Object tmp = Napi::Array::New(Env(), 3);
-      for (uint64_t j = 0; j < 3; ++j) {
-        tmp[j] = Napi::String::New(Env(), result[i][j]);
-      }
-      res[i] = tmp;
+    ProgressWorker(Napi::Function& callback, whisper_params params, Napi::Function progress_callback, Napi::Env env)
+        : Napi::AsyncWorker(callback), params(params), env(env) {
+        // Create thread-safe function
+        if (!progress_callback.IsEmpty()) {
+            tsfn = Napi::ThreadSafeFunction::New(
+                env,
+                progress_callback,
+                "Progress Callback",
+                0,
+                1
+            );
+        }
+    }
+
+    ~ProgressWorker() {
+        if (tsfn) {
+            // Make sure to release the thread-safe function on destruction
+            tsfn.Release();
+        }
+    }
+
+    void Execute() override {
+        // Use custom run function with progress callback support
+        run_with_progress(params, result);
+    }
+
+    void OnOK() override {
+        Napi::HandleScope scope(Env());
+        Napi::Object res = Napi::Array::New(Env(), result.size());
+        for (uint64_t i = 0; i < result.size(); ++i) {
+            Napi::Object tmp = Napi::Array::New(Env(), 3);
+            for (uint64_t j = 0; j < 3; ++j) {
+                tmp[j] = Napi::String::New(Env(), result[i][j]);
+            }
+            res[i] = tmp;
+        }
+        Callback().Call({Env().Null(), res});
+    }
+
+    // Progress callback function - using thread-safe function
+    void OnProgress(int progress) {
+        if (tsfn) {
+            // Use thread-safe function to call JavaScript callback
+            auto callback = [progress](Napi::Env env, Napi::Function jsCallback) {
+                jsCallback.Call({Napi::Number::New(env, progress)});
+            };
+            
+            tsfn.BlockingCall(callback);
+        }
     }
-    Callback().Call({Env().Null(), res});
-  }
 
  private:
-  whisper_params params;
-  std::vector<std::vector<std::string>> result;
+    whisper_params params;
+    std::vector<std::vector<std::string>> result;
+    Napi::Env env;
+    Napi::ThreadSafeFunction tsfn;
+
+    // Custom run function with progress callback support
+    int run_with_progress(whisper_params &params, std::vector<std::vector<std::string>> &result) {
+        if (params.no_prints) {
+            whisper_log_set(cb_log_disable, NULL);
+        }
+
+        if (params.fname_inp.empty() && params.pcmf32.empty()) {
+            fprintf(stderr, "error: no input files or audio buffer specified\n");
+            return 2;
+        }
+
+        if (params.language != "auto" && whisper_lang_id(params.language.c_str()) == -1) {
+            fprintf(stderr, "error: unknown language '%s'\n", params.language.c_str());
+            exit(0);
+        }
+
+        // whisper init
+        struct whisper_context_params cparams = whisper_context_default_params();
+        cparams.use_gpu = params.use_gpu;
+        cparams.flash_attn = params.flash_attn;
+        struct whisper_context * ctx = whisper_init_from_file_with_params(params.model.c_str(), cparams);
+
+        if (ctx == nullptr) {
+            fprintf(stderr, "error: failed to initialize whisper context\n");
+            return 3;
+        }
+
+        // If params.pcmf32 provides, set params.fname_inp as "buffer"
+        if (!params.pcmf32.empty()) {
+            fprintf(stderr, "info: using audio buffer as input\n");
+            params.fname_inp.clear();
+            params.fname_inp.emplace_back("buffer");
+        }
+
+        for (int f = 0; f < (int) params.fname_inp.size(); ++f) {
+            const auto fname_inp = params.fname_inp[f];
+            const auto fname_out = f < (int)params.fname_out.size() && !params.fname_out[f].empty() ? params.fname_out[f] : params.fname_inp[f];
+
+            std::vector<float> pcmf32; // mono-channel F32 PCM
+            std::vector<std::vector<float>> pcmf32s; // stereo-channel F32 PCM
+
+            // If params.pcmf32 is empty, read input audio file
+            if (params.pcmf32.empty()) {
+                if (!::read_audio_data(fname_inp, pcmf32, pcmf32s, params.diarize)) {
+                    fprintf(stderr, "error: failed to read audio file '%s'\n", fname_inp.c_str());
+                    continue;
+                }
+            } else {
+                pcmf32 = params.pcmf32;
+            }
+
+            // Print system info
+            if (!params.no_prints) {
+                fprintf(stderr, "\n");
+                fprintf(stderr, "system_info: n_threads = %d / %d | %s\n",
+                        params.n_threads*params.n_processors, std::thread::hardware_concurrency(), whisper_print_system_info());
+            }
+
+            // Print processing info
+            if (!params.no_prints) {
+                fprintf(stderr, "\n");
+                if (!whisper_is_multilingual(ctx)) {
+                    if (params.language != "en" || params.translate) {
+                        params.language = "en";
+                        params.translate = false;
+                        fprintf(stderr, "%s: WARNING: model is not multilingual, ignoring language and translation options\n", __func__);
+                    }
+                }
+                fprintf(stderr, "%s: processing '%s' (%d samples, %.1f sec), %d threads, %d processors, lang = %s, task = %s, timestamps = %d, audio_ctx = %d ...\n",
+                        __func__, fname_inp.c_str(), int(pcmf32.size()), float(pcmf32.size())/WHISPER_SAMPLE_RATE,
+                        params.n_threads, params.n_processors,
+                        params.language.c_str(),
+                        params.translate ? "translate" : "transcribe",
+                        params.no_timestamps ? 0 : 1,
+                        params.audio_ctx);
+
+                fprintf(stderr, "\n");
+            }
+
+            // Run inference
+            {
+                whisper_full_params wparams = whisper_full_default_params(WHISPER_SAMPLING_GREEDY);
+
+                wparams.strategy = params.beam_size > 1 ? WHISPER_SAMPLING_BEAM_SEARCH : WHISPER_SAMPLING_GREEDY;
+
+                wparams.print_realtime   = false;
+                wparams.print_progress   = params.print_progress;
+                wparams.print_timestamps = !params.no_timestamps;
+                wparams.print_special    = params.print_special;
+                wparams.translate        = params.translate;
+                wparams.language         = params.language.c_str();
+                wparams.n_threads        = params.n_threads;
+                wparams.n_max_text_ctx   = params.max_context >= 0 ? params.max_context : wparams.n_max_text_ctx;
+                wparams.offset_ms        = params.offset_t_ms;
+                wparams.duration_ms      = params.duration_ms;
+
+                wparams.token_timestamps = params.output_wts || params.max_len > 0;
+                wparams.thold_pt         = params.word_thold;
+                wparams.entropy_thold    = params.entropy_thold;
+                wparams.logprob_thold    = params.logprob_thold;
+                wparams.max_len          = params.output_wts && params.max_len == 0 ? 60 : params.max_len;
+                wparams.audio_ctx        = params.audio_ctx;
+
+                wparams.greedy.best_of        = params.best_of;
+                wparams.beam_search.beam_size = params.beam_size;
+
+                wparams.initial_prompt   = params.prompt.c_str();
+
+                wparams.no_timestamps    = params.no_timestamps;
+
+                whisper_print_user_data user_data = { &params, &pcmf32s };
+
+                // This callback is called for each new segment
+                if (!wparams.print_realtime) {
+                    wparams.new_segment_callback           = whisper_print_segment_callback;
+                    wparams.new_segment_callback_user_data = &user_data;
+                }
+
+                // Set progress callback
+                wparams.progress_callback = [](struct whisper_context * /*ctx*/, struct whisper_state * /*state*/, int progress, void * user_data) {
+                    ProgressWorker* worker = static_cast<ProgressWorker*>(user_data);
+                    worker->OnProgress(progress);
+                };
+                wparams.progress_callback_user_data = this;
+
+                // Abort mechanism example
+                {
+                    static bool is_aborted = false; // Note: this should be atomic to avoid data races
+
+                    wparams.encoder_begin_callback = [](struct whisper_context * /*ctx*/, struct whisper_state * /*state*/, void * user_data) {
+                        bool is_aborted = *(bool*)user_data;
+                        return !is_aborted;
+                    };
+                    wparams.encoder_begin_callback_user_data = &is_aborted;
+                }
+
+                if (whisper_full_parallel(ctx, wparams, pcmf32.data(), pcmf32.size(), params.n_processors) != 0) {
+                    fprintf(stderr, "failed to process audio\n");
+                    return 10;
+                }
+            }
+    }
+
+        const int n_segments = whisper_full_n_segments(ctx);
+        result.resize(n_segments);
+        for (int i = 0; i < n_segments; ++i) {
+            const char * text = whisper_full_get_segment_text(ctx, i);
+            const int64_t t0 = whisper_full_get_segment_t0(ctx, i);
+            const int64_t t1 = whisper_full_get_segment_t1(ctx, i);
+
+            result[i].emplace_back(to_timestamp(t0, params.comma_in_time));
+            result[i].emplace_back(to_timestamp(t1, params.comma_in_time));
+            result[i].emplace_back(text);
+        }
+
+        whisper_print_timings(ctx);
+        whisper_free(ctx);
+
+        return 0;
+    }
 };
 
-
-
 Napi::Value whisper(const Napi::CallbackInfo& info) {
   Napi::Env env = info.Env();
   if (info.Length() <= 0 || !info[0].IsObject()) {
@@ -332,6 +367,23 @@ Napi::Value whisper(const Napi::CallbackInfo& info) {
   int32_t audio_ctx = whisper_params.Get("audio_ctx").As<Napi::Number>();
   bool comma_in_time = whisper_params.Get("comma_in_time").As<Napi::Boolean>();
   int32_t max_len = whisper_params.Get("max_len").As<Napi::Number>();
+  
+  // support prompt
+  std::string prompt = "";
+  if (whisper_params.Has("prompt") && whisper_params.Get("prompt").IsString()) {
+    prompt = whisper_params.Get("prompt").As<Napi::String>();
+  }
+  
+  // Add support for print_progress
+  bool print_progress = false;
+  if (whisper_params.Has("print_progress")) {
+    print_progress = whisper_params.Get("print_progress").As<Napi::Boolean>();
+  }
+  // Add support for progress_callback
+  Napi::Function progress_callback;
+  if (whisper_params.Has("progress_callback") && whisper_params.Get("progress_callback").IsFunction()) {
+    progress_callback = whisper_params.Get("progress_callback").As<Napi::Function>();
+  }
 
   Napi::Value pcmf32Value = whisper_params.Get("pcmf32");
   std::vector<float> pcmf32_vec;
@@ -355,9 +407,12 @@ Napi::Value whisper(const Napi::CallbackInfo& info) {
   params.pcmf32 = pcmf32_vec;
   params.comma_in_time = comma_in_time;
   params.max_len = max_len;
+  params.print_progress = print_progress;
+  params.prompt = prompt;
 
   Napi::Function callback = info[1].As<Napi::Function>();
-  Worker* worker = new Worker(callback, params);
+  // Create a new Worker class with progress callback support
+  ProgressWorker* worker = new ProgressWorker(callback, params, progress_callback, env);
   worker->Queue();
   return env.Undefined();
 }

examples/addon.node/index.js

@@ -19,6 +19,9 @@ const whisperParams = {
   no_timestamps: false,
   audio_ctx: 0,
   max_len: 0,
+  progress_callback: (progress) => {
+      console.log(`progress: ${progress}%`);
+    }
 };
 
 const arguments = process.argv.slice(2);

examples/bench.wasm/README.md

@@ -2,7 +2,7 @@
 
 Benchmark the performance of whisper.cpp in the browser using WebAssembly
 
-Link: https://whisper.ggerganov.com/bench/
+Link: https://ggerganov.github.io/whisper.cpp/bench.wasm
 
 Terminal version: [examples/bench](/examples/bench)
 
@@ -15,7 +15,17 @@ cd whisper.cpp
 mkdir build-em && cd build-em
 emcmake cmake ..
 make -j
+```
+The example can then be started by running a local HTTP server:
+```console
+python3 examples/server.py
+```
+And then opening a browser to the following URL:
+http://localhost:8000/bench.wasm
 
+To run the example in a different server, you need to copy the following files
+to the server's HTTP path:
+```
 # copy the produced page to your HTTP path
 cp bin/bench.wasm/*       /path/to/html/
 cp bin/libbench.worker.js /path/to/html/

examples/bench.wasm/index-tmpl.html

@@ -24,6 +24,8 @@
                 overflow-x: scroll;
             }
         </style>
+        <script src="../coi-serviceworker.js"></script>
+        <link rel="icon" href="data:,">
     </head>
     <body>
         <div id="main-container">
@@ -36,11 +38,10 @@
             <br><br>
 
             <b>More examples:</b>
-                <a href="https://whisper.ggerganov.com/">main</a> |
-                <a href="https://whisper.ggerganov.com/bench">bench</a> |
-                <a href="https://whisper.ggerganov.com/stream">stream</a> |
-                <a href="https://whisper.ggerganov.com/command">command</a> |
-                <a href="https://whisper.ggerganov.com/talk">talk</a> |
+                <a href="../">main</a> |
+                <a href="../bench.wasm/">bench</a> |
+                <a href="../stream.wasm">stream</a> |
+                <a href="../command.wasm/">command</a> |
 
             <br><br>
 

examples/bench/README.md

@@ -4,7 +4,7 @@ A very basic tool for benchmarking the inference performance on your device. The
 the transformer on some random audio data and records the execution time. This way we can have an objective comparison
 of the performance of the model for various setups.
 
-Benchmark results are tracked in the following Github issue: https://github.com/ggerganov/whisper.cpp/issues/89
+Benchmark results are tracked in the following Github issue: https://github.com/ggml-org/whisper.cpp/issues/89
 
 ```bash
 # run the bench too on the small.en model using 4 threads
@@ -40,7 +40,7 @@ system_info: n_threads = 4 | AVX2 = 0 | AVX512 = 0 | NEON = 1 | FP16_VA = 1 | WA
 
 If you wish, you can submit these results here:
 
-  https://github.com/ggerganov/whisper.cpp/issues/89
+  https://github.com/ggml-org/whisper.cpp/issues/89
 
 Please include the following information:
 

examples/cli/cli.cpp

@@ -13,7 +13,9 @@
 #include <cstring>
 
 #if defined(_WIN32)
+#ifndef NOMINMAX
 #define NOMINMAX
+#endif
 #include <windows.h>
 #endif
 

examples/coi-serviceworker.js

@@ -0,0 +1,146 @@
+/*! coi-serviceworker v0.1.7 - Guido Zuidhof and contributors, licensed under MIT */
+let coepCredentialless = false;
+if (typeof window === 'undefined') {
+    self.addEventListener("install", () => self.skipWaiting());
+    self.addEventListener("activate", (event) => event.waitUntil(self.clients.claim()));
+
+    self.addEventListener("message", (ev) => {
+        if (!ev.data) {
+            return;
+        } else if (ev.data.type === "deregister") {
+            self.registration
+                .unregister()
+                .then(() => {
+                    return self.clients.matchAll();
+                })
+                .then(clients => {
+                    clients.forEach((client) => client.navigate(client.url));
+                });
+        } else if (ev.data.type === "coepCredentialless") {
+            coepCredentialless = ev.data.value;
+        }
+    });
+
+    self.addEventListener("fetch", function (event) {
+        const r = event.request;
+        if (r.cache === "only-if-cached" && r.mode !== "same-origin") {
+            return;
+        }
+
+        const request = (coepCredentialless && r.mode === "no-cors")
+            ? new Request(r, {
+                credentials: "omit",
+            })
+            : r;
+        event.respondWith(
+            fetch(request)
+                .then((response) => {
+                    if (response.status === 0) {
+                        return response;
+                    }
+
+                    const newHeaders = new Headers(response.headers);
+                    newHeaders.set("Cross-Origin-Embedder-Policy",
+                        coepCredentialless ? "credentialless" : "require-corp"
+                    );
+                    if (!coepCredentialless) {
+                        newHeaders.set("Cross-Origin-Resource-Policy", "cross-origin");
+                    }
+                    newHeaders.set("Cross-Origin-Opener-Policy", "same-origin");
+
+                    return new Response(response.body, {
+                        status: response.status,
+                        statusText: response.statusText,
+                        headers: newHeaders,
+                    });
+                })
+                .catch((e) => console.error(e))
+        );
+    });
+
+} else {
+    (() => {
+        const reloadedBySelf = window.sessionStorage.getItem("coiReloadedBySelf");
+        window.sessionStorage.removeItem("coiReloadedBySelf");
+        const coepDegrading = (reloadedBySelf == "coepdegrade");
+
+        // You can customize the behavior of this script through a global `coi` variable.
+        const coi = {
+            shouldRegister: () => !reloadedBySelf,
+            shouldDeregister: () => false,
+            coepCredentialless: () => true,
+            coepDegrade: () => true,
+            doReload: () => window.location.reload(),
+            quiet: false,
+            ...window.coi
+        };
+
+        const n = navigator;
+        const controlling = n.serviceWorker && n.serviceWorker.controller;
+
+        // Record the failure if the page is served by serviceWorker.
+        if (controlling && !window.crossOriginIsolated) {
+            window.sessionStorage.setItem("coiCoepHasFailed", "true");
+        }
+        const coepHasFailed = window.sessionStorage.getItem("coiCoepHasFailed");
+
+        if (controlling) {
+            // Reload only on the first failure.
+            const reloadToDegrade = coi.coepDegrade() && !(
+                coepDegrading || window.crossOriginIsolated
+            );
+            n.serviceWorker.controller.postMessage({
+                type: "coepCredentialless",
+                value: (reloadToDegrade || coepHasFailed && coi.coepDegrade())
+                    ? false
+                    : coi.coepCredentialless(),
+            });
+            if (reloadToDegrade) {
+                !coi.quiet && console.log("Reloading page to degrade COEP.");
+                window.sessionStorage.setItem("coiReloadedBySelf", "coepdegrade");
+                coi.doReload("coepdegrade");
+            }
+
+            if (coi.shouldDeregister()) {
+                n.serviceWorker.controller.postMessage({ type: "deregister" });
+            }
+        }
+
+        // If we're already coi: do nothing. Perhaps it's due to this script doing its job, or COOP/COEP are
+        // already set from the origin server. Also if the browser has no notion of crossOriginIsolated, just give up here.
+        if (window.crossOriginIsolated !== false || !coi.shouldRegister()) return;
+
+        if (!window.isSecureContext) {
+            !coi.quiet && console.log("COOP/COEP Service Worker not registered, a secure context is required.");
+            return;
+        }
+
+        // In some environments (e.g. Firefox private mode) this won't be available
+        if (!n.serviceWorker) {
+            !coi.quiet && console.error("COOP/COEP Service Worker not registered, perhaps due to private mode.");
+            return;
+        }
+
+        n.serviceWorker.register(window.document.currentScript.src).then(
+            (registration) => {
+                !coi.quiet && console.log("COOP/COEP Service Worker registered", registration.scope);
+
+                registration.addEventListener("updatefound", () => {
+                    !coi.quiet && console.log("Reloading page to make use of updated COOP/COEP Service Worker.");
+                    window.sessionStorage.setItem("coiReloadedBySelf", "updatefound");
+                    coi.doReload();
+                });
+
+                // If the registration is active, but it's not controlling the page
+                if (registration.active && !n.serviceWorker.controller) {
+                    !coi.quiet && console.log("Reloading page to make use of COOP/COEP Service Worker.");
+                    window.sessionStorage.setItem("coiReloadedBySelf", "notcontrolling");
+                    coi.doReload();
+                }
+            },
+            (err) => {
+                !coi.quiet && console.error("COOP/COEP Service Worker failed to register:", err);
+            }
+        );
+    })();
+}

examples/command.wasm/README.md

@@ -3,7 +3,7 @@
 This is a basic Voice Assistant example that accepts voice commands from the microphone.
 It runs in fully in the browser via WebAseembly.
 
-Online demo: https://whisper.ggerganov.com/command/
+Online demo: https://ggerganov.github.io/whisper.cpp/command.wasm
 
 Terminal version: [examples/command](/examples/command)
 
@@ -15,9 +15,18 @@ git clone https://github.com/ggerganov/whisper.cpp
 cd whisper.cpp
 mkdir build-em && cd build-em
 emcmake cmake ..
-make -j
+make -j libcommand
+```
+The example can then be started by running a local HTTP server:
+```console
+python3 examples/server.py
+```
+And then opening a browser to the following URL:
+http://localhost:8000/command.wasm/
 
-# copy the produced page to your HTTP path
+To run the example in a different server, you need to copy the following files
+to the server's HTTP path:
+```
 cp bin/command.wasm/*       /path/to/html/
 cp bin/libcommand.worker.js /path/to/html/
 ```

examples/command.wasm/index-tmpl.html

@@ -24,6 +24,8 @@
                 overflow-x: scroll;
             }
         </style>
+        <script src="../coi-serviceworker.js"></script>
+        <link rel="icon" href="data:,">
     </head>
     <body>
         <div id="main-container">
@@ -36,11 +38,10 @@
             <br><br>
 
             <b>More examples:</b>
-                <a href="https://whisper.ggerganov.com/">main</a> |
-                <a href="https://whisper.ggerganov.com/bench">bench</a> |
-                <a href="https://whisper.ggerganov.com/stream">stream</a> |
-                <a href="https://whisper.ggerganov.com/command">command</a> |
-                <a href="https://whisper.ggerganov.com/talk">talk</a> |
+                <a href="../">main</a> |
+                <a href="../bench.wasm/">bench</a> |
+                <a href="../stream.wasm">stream</a> |
+                <a href="../command.wasm/">command</a> |
 
             <br><br>
 

examples/command/command.cpp

@@ -3,7 +3,7 @@
 // Speak short text commands to the microphone.
 // This program will detect your voice command and convert them to text.
 //
-// ref: https://github.com/ggerganov/whisper.cpp/issues/171
+// ref: https://github.com/ggml-org/whisper.cpp/issues/171
 //
 
 #include "common-sdl.h"

examples/common.cpp

@@ -247,17 +247,6 @@ std::map<std::string, int32_t> json_parse(const std::string & fname) {
     return result;
 }
 
-std::string convert_to_utf8(const std::wstring & input) {
-    std::wstring_convert<std::codecvt_utf8<wchar_t>> converter;
-    return converter.to_bytes(input);
-}
-
-
-std::wstring convert_to_wstring(const std::string & input) {
-    std::wstring_convert<std::codecvt_utf8<wchar_t>> converter;
-    return converter.from_bytes(input);
-}
-
 void gpt_split_words(std::string str, std::vector<std::string>& words) {
     const std::string pattern = R"('s|'t|'re|'ve|'m|'ll|'d| ?[[:alpha:]]+| ?[[:digit:]]+| ?[^\s[:alpha:][:digit:]]+|\s+(?!\S)|\s+)";
     const std::regex re(pattern);

examples/deprecation-warning/CMakeLists.txt

@@ -1,4 +1,6 @@
 add_executable(main ./deprecation-warning.cpp)
 add_executable(bench ./deprecation-warning.cpp)
-add_executable(stream ./deprecation-warning.cpp)
-add_executable(command ./deprecation-warning.cpp)
+if (WHISPER_SDL2)
+    add_executable(stream ./deprecation-warning.cpp)
+    add_executable(command ./deprecation-warning.cpp)
+endif()

examples/livestream.sh

@@ -2,7 +2,7 @@
 #
 # Transcribe audio livestream by feeding ffmpeg output to whisper.cpp at regular intervals
 # Idea by @semiformal-net
-# ref: https://github.com/ggerganov/whisper.cpp/issues/185
+# ref: https://github.com/ggml-org/whisper.cpp/issues/185
 #
 
 set -eo pipefail

examples/server.py

@@ -0,0 +1,115 @@
+import http.server
+import socketserver
+import os
+import sys
+from pathlib import Path
+import urllib.parse
+
+SCRIPT_DIR = Path(__file__).parent.absolute()
+DIRECTORY = os.path.join(SCRIPT_DIR, "../build-em/bin")
+DIRECTORY = os.path.abspath(DIRECTORY)
+
+# The context root we want for all applications
+CONTEXT_ROOT = "/whisper.cpp"
+
+class CustomHTTPRequestHandler(http.server.SimpleHTTPRequestHandler):
+    def __init__(self, *args, **kwargs):
+        super().__init__(*args, directory=DIRECTORY, **kwargs)
+
+    def do_GET(self):
+        # Redirect root to the context root
+        if self.path == '/':
+            self.send_response(302)
+            self.send_header('Location', CONTEXT_ROOT + '/')
+            self.end_headers()
+            return
+
+        # Handle requests under the context root
+        if self.path.startswith(CONTEXT_ROOT):
+            # Remove the context root prefix to get the actual path
+            actual_path = self.path[len(CONTEXT_ROOT):]
+
+            if not actual_path:
+                self.send_response(302)
+                self.send_header('Location', CONTEXT_ROOT + '/')
+                self.end_headers()
+                return
+
+            if '.worker.js' in actual_path:
+                worker_file = os.path.basename(actual_path)
+                worker_path = os.path.join(DIRECTORY, worker_file)
+
+                if os.path.exists(worker_path):
+                    print(f"Found worker file: {worker_path}")
+                    self.path = '/' + worker_file
+                else:
+                    print(f"Worker file not found: {worker_path}")
+
+            elif actual_path == '/':
+                self.path = '/whisper.wasm/index.html'
+            elif actual_path.startswith('/bench.wasm/') or actual_path.startswith('/command.wasm/') or actual_path.startswith('/stream.wasm/'):
+                # Keep the path as is, just remove the context root
+                self.path = actual_path
+            # For all other paths under the context root
+            else:
+                # Check if this is a request to a file in whisper.wasm
+                potential_file = os.path.join(DIRECTORY, 'whisper.wasm', actual_path.lstrip('/'))
+                if os.path.exists(potential_file) and not os.path.isdir(potential_file):
+                    self.path = '/whisper.wasm' + actual_path
+                else:
+                    # Try to resolve the file from the base directory
+                    potential_file = os.path.join(DIRECTORY, actual_path.lstrip('/'))
+                    if os.path.exists(potential_file):
+                        self.path = actual_path
+
+        # For direct requests to worker files (without context root as these
+        # are in the build-em/bin directory
+        elif '.worker.js' in self.path:
+            worker_file = os.path.basename(self.path)
+            worker_path = os.path.join(DIRECTORY, worker_file)
+
+            if os.path.exists(worker_path):
+                self.path = '/' + worker_file
+
+        # Handle coi-serviceworker.js separately
+        if 'coi-serviceworker.js' in self.path:
+            worker_file = "coi-serviceworker.js"
+            worker_path = os.path.join(SCRIPT_DIR, worker_file)
+            if os.path.exists(worker_path):
+                self.send_response(200)
+                self.send_header('Content-type', 'application/javascript')
+                self.end_headers()
+                with open(worker_path, 'rb') as file:
+                    self.wfile.write(file.read())
+                return
+            else:
+                print(f"Warning: Could not find {worker_path}")
+
+        return super().do_GET()
+
+    def end_headers(self):
+        # Add required headers for SharedArrayBuffer
+        self.send_header("Cross-Origin-Opener-Policy", "same-origin")
+        self.send_header("Cross-Origin-Embedder-Policy", "require-corp")
+        self.send_header("Access-Control-Allow-Origin", "*")
+        super().end_headers()
+
+PORT = 8000
+
+# Enable address reuse
+class CustomServer(socketserver.TCPServer):
+    allow_reuse_address = True
+
+try:
+    with CustomServer(("", PORT), CustomHTTPRequestHandler) as httpd:
+        print(f"Serving directory '{DIRECTORY}' at http://localhost:{PORT}")
+        print(f"Application context root: http://localhost:{PORT}{CONTEXT_ROOT}/")
+        try:
+            httpd.serve_forever()
+        except KeyboardInterrupt:
+            print("\nServer stopped.")
+            # Force complete exit
+            sys.exit(0)
+except OSError as e:
+    print(f"Error: {e}")
+    sys.exit(1)

examples/server/server.cpp

@@ -1024,6 +1024,11 @@ int main(int argc, char ** argv) {
         // check if the model is in the file system
     });
 
+    svr.Get(sparams.request_path + "/health", [&](const Request &, Response &res){
+        const std::string health_response = "{\"status\":\"ok\"}";
+        res.set_content(health_response, "application/json");
+    });
+
     svr.set_exception_handler([](const Request &, Response &res, std::exception_ptr ep) {
         const char fmt[] = "500 Internal Server Error\n%s";
         char buf[BUFSIZ];

examples/stream.wasm/README.md

@@ -13,7 +13,17 @@ cd whisper.cpp
 mkdir build-em && cd build-em
 emcmake cmake ..
 make -j
+```
+The example can then be started by running a local HTTP server:
+```console
+python3 examples/server.py
+```
+And then opening a browser to the following URL:
+http://localhost:8000/stream.wasm
 
+To run the example in a different server, you need to copy the following files
+to the server's HTTP path:
+```
 # copy the produced page to your HTTP path
 cp bin/stream.wasm/*       /path/to/html/
 cp bin/libstream.worker.js /path/to/html/

examples/stream.wasm/index-tmpl.html

@@ -24,6 +24,8 @@
                 overflow-x: scroll;
             }
         </style>
+        <script src="../coi-serviceworker.js"></script>
+        <link rel="icon" href="data:,">
     </head>
     <body>
         <div id="main-container">
@@ -36,11 +38,10 @@
             <br><br>
 
             <b>More examples:</b>
-                <a href="https://whisper.ggerganov.com/">main</a> |
-                <a href="https://whisper.ggerganov.com/bench">bench</a> |
-                <a href="https://whisper.ggerganov.com/stream">stream</a> |
-                <a href="https://whisper.ggerganov.com/command">command</a> |
-                <a href="https://whisper.ggerganov.com/talk">talk</a> |
+                <a href="../">main</a> |
+                <a href="../bench.wasm/">bench</a> |
+                <a href="../stream.wasm">stream</a> |
+                <a href="../command.wasm/">command</a> |
 
             <br><br>
 

examples/twitch.sh

@@ -2,7 +2,7 @@
 #
 # Transcribe twitch.tv livestream by feeding audio input to whisper.cpp at regular intervals
 # Thanks to @keyehzy
-# ref: https://github.com/ggerganov/whisper.cpp/issues/209
+# ref: https://github.com/ggml-org/whisper.cpp/issues/209
 #
 # The script currently depends on the third-party tool "streamlink"
 # On Mac OS, you can install it via "brew install streamlink"

examples/whisper.android.java/app/src/main/jni/whisper/CMakeLists.txt

@@ -2,15 +2,25 @@ cmake_minimum_required(VERSION 3.10)
 
 project(whisper.cpp)
 
-set(CMAKE_CXX_STANDARD 11)
+set(CMAKE_CXX_STANDARD 17)
 set(WHISPER_LIB_DIR ${CMAKE_SOURCE_DIR}/../../../../../../../)
 
 set(SOURCE_FILES
     ${WHISPER_LIB_DIR}/ggml/src/ggml.c
-    ${WHISPER_LIB_DIR}/ggml/src/ggml-aarch64.c
+    ${WHISPER_LIB_DIR}/ggml/src/ggml-cpu/ggml-cpu.c
+    ${WHISPER_LIB_DIR}/ggml/src/ggml-cpu/ggml-cpu-aarch64.cpp
+    ${WHISPER_LIB_DIR}/ggml/src/ggml-cpu/ggml-cpu-traits.cpp
+    ${WHISPER_LIB_DIR}/ggml/src/ggml-cpu/ggml-cpu-quants.c
+    ${WHISPER_LIB_DIR}/ggml/src/ggml-cpu/ggml-cpu.cpp
+    ${WHISPER_LIB_DIR}/ggml/src/ggml-cpu/unary-ops.cpp
+    ${WHISPER_LIB_DIR}/ggml/src/ggml-cpu/binary-ops.cpp
+    ${WHISPER_LIB_DIR}/ggml/src/ggml-cpu/vec.cpp
+    ${WHISPER_LIB_DIR}/ggml/src/ggml-cpu/ops.cpp
     ${WHISPER_LIB_DIR}/ggml/src/ggml-alloc.c
     ${WHISPER_LIB_DIR}/ggml/src/ggml-backend.cpp
+    ${WHISPER_LIB_DIR}/ggml/src/ggml-backend-reg.cpp
     ${WHISPER_LIB_DIR}/ggml/src/ggml-quants.c
+    ${WHISPER_LIB_DIR}/ggml/src/ggml-threading.cpp
     ${WHISPER_LIB_DIR}/src/whisper.cpp
     ${CMAKE_SOURCE_DIR}/jni.c
     )
@@ -25,6 +35,7 @@ function(build_library target_name)
     )
 
     target_link_libraries(${target_name} ${LOG_LIB} android)
+    target_compile_definitions(${target_name} PUBLIC GGML_USE_CPU)
 
     if (${target_name} STREQUAL "whisper_v8fp16_va")
         target_compile_options(${target_name} PRIVATE -march=armv8.2-a+fp16)
@@ -57,3 +68,4 @@ include_directories(${WHISPER_LIB_DIR}/src)
 include_directories(${WHISPER_LIB_DIR}/include)
 include_directories(${WHISPER_LIB_DIR}/ggml/include)
 include_directories(${WHISPER_LIB_DIR}/ggml/src)
+include_directories(${WHISPER_LIB_DIR}/ggml/src/ggml-cpu)

examples/whisper.android.java/build.gradle

@@ -16,9 +16,10 @@ allprojects {
   repositories {
     google()
     jcenter()
+    maven { url "https://maven.aliyun.com/repository/gradle-plugin" }
   }
 }
 
 task clean(type: Delete) {
   delete rootProject.buildDir
-}
+}

examples/whisper.android/lib/src/main/jni/whisper/CMakeLists.txt

@@ -32,6 +32,10 @@ if (NOT GGML_HOME)
         ${WHISPER_LIB_DIR}/ggml/src/ggml-cpu/ggml-cpu-hbm.cpp
         ${WHISPER_LIB_DIR}/ggml/src/ggml-cpu/ggml-cpu-quants.c
         ${WHISPER_LIB_DIR}/ggml/src/ggml-cpu/ggml-cpu-traits.cpp
+        ${WHISPER_LIB_DIR}/ggml/src/ggml-cpu/unary-ops.cpp
+        ${WHISPER_LIB_DIR}/ggml/src/ggml-cpu/binary-ops.cpp
+        ${WHISPER_LIB_DIR}/ggml/src/ggml-cpu/vec.cpp
+        ${WHISPER_LIB_DIR}/ggml/src/ggml-cpu/ops.cpp
         )
 endif()
 
@@ -44,6 +48,8 @@ function(build_library target_name)
         ${SOURCE_FILES}
     )
 
+    target_compile_definitions(${target_name} PUBLIC GGML_USE_CPU)
+
     if (${target_name} STREQUAL "whisper_v8fp16_va")
         target_compile_options(${target_name} PRIVATE -march=armv8.2-a+fp16)
         set(GGML_COMPILE_OPTIONS                      -march=armv8.2-a+fp16)

examples/whisper.nvim/whisper.nvim

@@ -5,7 +5,7 @@
 # This simple script is called by Neovim to capture audio from the microphone and transcribe it with Whisper.
 # In order for this to work, you need to clone the whisper.cpp repo and build the 'stream' tool
 #
-#   git clone https://github.com/ggerganov/whisper.cpp
+#   git clone https://github.com/ggml-org/whisper.cpp
 #   cd whisper.cpp
 #   make stream
 #
@@ -31,7 +31,7 @@
 model="base.en"
 
 # export the path to the whisper.cpp repo in the WHISPER_CPP_HOME env variable
-# https://github.com/ggerganov/whisper.cpp
+# https://github.com/ggml-org/whisper.cpp
 cd "${WHISPER_CPP_HOME}"
 
 if [ ! -f ./stream ] ; then

examples/whisper.objc/README.md

@@ -11,39 +11,25 @@ https://user-images.githubusercontent.com/1991296/204126266-ce4177c6-6eca-4bd9-b
 
 ## Usage
 
+This example uses the whisper.xcframework which needs to be built first using the following command:
 ```bash
-git clone https://github.com/ggerganov/whisper.cpp
-open whisper.cpp/examples/whisper.objc/whisper.objc.xcodeproj/
+./build-xcframework.sh
+```
 
-# if you don't want to convert a Core ML model, you can skip this step by create dummy model
+A model is also required to be downloaded and can be done using the following command:
+```bash
+./models/download-ggml-model.sh base.en
+```
+
+If you don't want to convert a Core ML model, you can skip this step by creating dummy model:
+```bash
 mkdir models/ggml-base.en-encoder.mlmodelc
 ```
 
-Make sure to build the project in `Release`:
-
-<img width="947" alt="image" src="https://user-images.githubusercontent.com/1991296/197382607-9e1e6d1b-79fa-496f-9d16-b71dc1535701.png">
-
-Also, don't forget to add the `-DGGML_USE_ACCELERATE` compiler flag for `ggml.c` in Build Phases.
-This can significantly improve the performance of the transcription:
-
-<img width="1072" alt="image" src="https://user-images.githubusercontent.com/1991296/208511239-8d7cdbd1-aa48-41b5-becd-ca288d53cc07.png">
-
 ## Core ML
 
-If you want to enable Core ML support, you can add the `-DWHISPER_USE_COREML -DWHISPER_COREML_ALLOW_FALLBACK` compiler flag for `whisper.cpp` in Build Phases:
-
-<img width="1072" alt="image" src="https://github.com/ggerganov/whisper.cpp/assets/3001525/103e8f57-6eb6-490d-a60c-f6cf6c319324">
-
-Then follow the [`Core ML support` section of readme](../../README.md#core-ml-support) for convert the model.
-
-In this project, it also added `-O3 -DNDEBUG` to `Other C Flags`, but adding flags to app proj is not ideal in real world (applies to all C/C++ files), consider splitting xcodeproj in workspace in your own project.
-
-## Metal
-
-You can also enable Metal to make the inference run on the GPU of your device. This might or might not be more efficient
-compared to Core ML depending on the model and device that you use.
-
-To enable Metal, just add `-DGGML_USE_METAL` instead off the `-DWHISPER_USE_COREML` flag and you are ready.
-This will make both the Encoder and the Decoder run on the GPU.
-
-If you want to run the Encoder with Core ML and the Decoder with Metal then simply add both `-DWHISPER_USE_COREML -DGGML_USE_METAL` flags. That's all!
+Follow the [`Core ML support` section of readme](../../README.md#core-ml-support) to convert the model.
+That is all the needs to be done to use the Core ML model in the app. The converted model is a
+resource in the project and will be used if it is available. Note that the Core ML model is only
+used for the encoder, the decoder which is in the ggml model is still required so both need to
+be available.

examples/whisper.objc/whisper.objc.xcodeproj/project.pbxproj

@@ -7,7 +7,6 @@
 	objects = {
 
 /* Begin PBXBuildFile section */
-		1844471A2AB211A2007D6BFE /* ggml-alloc.c in Sources */ = {isa = PBXBuildFile; fileRef = 184447182AB211A2007D6BFE /* ggml-alloc.c */; };
 		18627C7B29052BDF00BD2A04 /* AppDelegate.m in Sources */ = {isa = PBXBuildFile; fileRef = 18627C7A29052BDF00BD2A04 /* AppDelegate.m */; };
 		18627C7E29052BDF00BD2A04 /* SceneDelegate.m in Sources */ = {isa = PBXBuildFile; fileRef = 18627C7D29052BDF00BD2A04 /* SceneDelegate.m */; };
 		18627C8129052BDF00BD2A04 /* ViewController.m in Sources */ = {isa = PBXBuildFile; fileRef = 18627C8029052BDF00BD2A04 /* ViewController.m */; };
@@ -15,23 +14,12 @@
 		18627C8629052BE000BD2A04 /* Assets.xcassets in Resources */ = {isa = PBXBuildFile; fileRef = 18627C8529052BE000BD2A04 /* Assets.xcassets */; };
 		18627C8929052BE000BD2A04 /* LaunchScreen.storyboard in Resources */ = {isa = PBXBuildFile; fileRef = 18627C8729052BE000BD2A04 /* LaunchScreen.storyboard */; };
 		18627C8C29052BE000BD2A04 /* main.m in Sources */ = {isa = PBXBuildFile; fileRef = 18627C8B29052BE000BD2A04 /* main.m */; };
-		18627C9429052C4900BD2A04 /* whisper.cpp in Sources */ = {isa = PBXBuildFile; fileRef = 18627C9329052C4900BD2A04 /* whisper.cpp */; settings = {COMPILER_FLAGS = "-DWHISPER_USE_COREML -DWHISPER_COREML_ALLOW_FALLBACK -DGGML_USE_METAL"; }; };
-		18627C9629052C5800BD2A04 /* ggml.c in Sources */ = {isa = PBXBuildFile; fileRef = 18627C9529052C5800BD2A04 /* ggml.c */; settings = {COMPILER_FLAGS = "-DGGML_USE_ACCELERATE -DGGML_USE_METAL"; }; };
 		18627C9B29052CFF00BD2A04 /* ggml-base.en.bin in Resources */ = {isa = PBXBuildFile; fileRef = 18627C9A29052CFF00BD2A04 /* ggml-base.en.bin */; };
-		18ABE15A2AF556340044A204 /* ggml-backend.cpp in Sources */ = {isa = PBXBuildFile; fileRef = 18ABE1572AF556340044A204 /* ggml-backend.cpp */; };
-		18ABE15B2AF556340044A204 /* ggml-quants.c in Sources */ = {isa = PBXBuildFile; fileRef = 18ABE1592AF556340044A204 /* ggml-quants.c */; };
-		18E864A92CE73C1E0094B8B3 /* ggml-cpu.c in Sources */ = {isa = PBXBuildFile; fileRef = 18E864A82CE73C1E0094B8B3 /* ggml-cpu.c */; };
-		18F8C0BC2CEDF4DC00CAD607 /* ggml-threading.cpp in Sources */ = {isa = PBXBuildFile; fileRef = 18F8C0BB2CEDF4DC00CAD607 /* ggml-threading.cpp */; };
-		18F8C0BE2CEDF50700CAD607 /* ggml-cpu.cpp in Sources */ = {isa = PBXBuildFile; fileRef = 18F8C0BD2CEDF50700CAD607 /* ggml-cpu.cpp */; };
-		18F8C0C42CEDF52700CAD607 /* ggml-cpu-aarch64.cpp in Sources */ = {isa = PBXBuildFile; fileRef = 18F8C0C02CEDF52700CAD607 /* ggml-cpu-aarch64.cpp */; settings = {COMPILER_FLAGS = "-x c++"; }; };
-		18F8C0C52CEDF52700CAD607 /* ggml-cpu-quants.c in Sources */ = {isa = PBXBuildFile; fileRef = 18F8C0C32CEDF52700CAD607 /* ggml-cpu-quants.c */; };
-		18F8C0C72CEDF7AB00CAD607 /* ggml-backend-reg.cpp in Sources */ = {isa = PBXBuildFile; fileRef = 18F8C0C62CEDF7AB00CAD607 /* ggml-backend-reg.cpp */; };
-		433188B82D3A187C00E3FE79 /* gguf.cpp in Sources */ = {isa = PBXBuildFile; fileRef = 433188B72D3A187C00E3FE79 /* gguf.cpp */; };
-		437B63E22D36280C002A49EC /* ggml-cpu-traits.cpp in Sources */ = {isa = PBXBuildFile; fileRef = 437B63E12D36280C002A49EC /* ggml-cpu-traits.cpp */; };
 		7FE3424B2A0C3FA20015A058 /* whisper-encoder-impl.m in Sources */ = {isa = PBXBuildFile; fileRef = 7FE342452A0C3FA20015A058 /* whisper-encoder-impl.m */; };
 		7FE3424C2A0C3FA20015A058 /* whisper-encoder.mm in Sources */ = {isa = PBXBuildFile; fileRef = 7FE342472A0C3FA20015A058 /* whisper-encoder.mm */; };
-		7FE3424D2A0C3FA20015A058 /* whisper-decoder-impl.m in Sources */ = {isa = PBXBuildFile; fileRef = 7FE3424A2A0C3FA20015A058 /* whisper-decoder-impl.m */; };
 		7FE3424F2A0C418A0015A058 /* ggml-base.en-encoder.mlmodelc in Resources */ = {isa = PBXBuildFile; fileRef = 7FE3424E2A0C418A0015A058 /* ggml-base.en-encoder.mlmodelc */; };
+		DDE3609F2D87EA8C004EA223 /* whisper.xcframework in Frameworks */ = {isa = PBXBuildFile; fileRef = DDE3609E2D87EA8C004EA223 /* whisper.xcframework */; };
+		DDE360A02D87EA8C004EA223 /* whisper.xcframework in Embed Frameworks */ = {isa = PBXBuildFile; fileRef = DDE3609E2D87EA8C004EA223 /* whisper.xcframework */; settings = {ATTRIBUTES = (CodeSignOnCopy, RemoveHeadersOnCopy, ); }; };
 /* End PBXBuildFile section */
 
 /* Begin PBXCopyFilesBuildPhase section */
@@ -45,11 +33,20 @@
 			name = "Copy Files";
 			runOnlyForDeploymentPostprocessing = 0;
 		};
+		DDE360A12D87EA8C004EA223 /* Embed Frameworks */ = {
+			isa = PBXCopyFilesBuildPhase;
+			buildActionMask = 2147483647;
+			dstPath = "";
+			dstSubfolderSpec = 10;
+			files = (
+				DDE360A02D87EA8C004EA223 /* whisper.xcframework in Embed Frameworks */,
+			);
+			name = "Embed Frameworks";
+			runOnlyForDeploymentPostprocessing = 0;
+		};
 /* End PBXCopyFilesBuildPhase section */
 
 /* Begin PBXFileReference section */
-		184447182AB211A2007D6BFE /* ggml-alloc.c */ = {isa = PBXFileReference; fileEncoding = 4; lastKnownFileType = sourcecode.c.c; name = "ggml-alloc.c"; path = "../../../ggml/src/ggml-alloc.c"; sourceTree = "<group>"; };
-		184447192AB211A2007D6BFE /* ggml-alloc.h */ = {isa = PBXFileReference; fileEncoding = 4; lastKnownFileType = sourcecode.c.h; name = "ggml-alloc.h"; path = "../../../ggml/include/ggml-alloc.h"; sourceTree = "<group>"; };
 		18627C7629052BDF00BD2A04 /* whisper.objc.app */ = {isa = PBXFileReference; explicitFileType = wrapper.application; includeInIndex = 0; path = whisper.objc.app; sourceTree = BUILT_PRODUCTS_DIR; };
 		18627C7929052BDF00BD2A04 /* AppDelegate.h */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.c.h; path = AppDelegate.h; sourceTree = "<group>"; };
 		18627C7A29052BDF00BD2A04 /* AppDelegate.m */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.c.objc; path = AppDelegate.m; sourceTree = "<group>"; };
@@ -62,34 +59,7 @@
 		18627C8829052BE000BD2A04 /* Base */ = {isa = PBXFileReference; lastKnownFileType = file.storyboard; name = Base; path = Base.lproj/LaunchScreen.storyboard; sourceTree = "<group>"; };
 		18627C8A29052BE000BD2A04 /* Info.plist */ = {isa = PBXFileReference; lastKnownFileType = text.plist.xml; path = Info.plist; sourceTree = "<group>"; };
 		18627C8B29052BE000BD2A04 /* main.m */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.c.objc; path = main.m; sourceTree = "<group>"; };
-		18627C9229052C2B00BD2A04 /* whisper.h */ = {isa = PBXFileReference; fileEncoding = 4; lastKnownFileType = sourcecode.c.h; name = whisper.h; path = ../../../include/whisper.h; sourceTree = "<group>"; };
-		18627C9329052C4900BD2A04 /* whisper.cpp */ = {isa = PBXFileReference; fileEncoding = 4; lastKnownFileType = sourcecode.cpp.cpp; name = whisper.cpp; path = ../../../src/whisper.cpp; sourceTree = "<group>"; };
-		18627C9529052C5800BD2A04 /* ggml.c */ = {isa = PBXFileReference; fileEncoding = 4; lastKnownFileType = sourcecode.c.c; name = ggml.c; path = ../../../ggml/src/ggml.c; sourceTree = "<group>"; };
-		18627C9729052C6600BD2A04 /* ggml.h */ = {isa = PBXFileReference; fileEncoding = 4; lastKnownFileType = sourcecode.c.h; name = ggml.h; path = ../../../ggml/include/ggml.h; sourceTree = "<group>"; };
 		18627C9A29052CFF00BD2A04 /* ggml-base.en.bin */ = {isa = PBXFileReference; lastKnownFileType = archive.macbinary; name = "ggml-base.en.bin"; path = "../../../models/ggml-base.en.bin"; sourceTree = "<group>"; };
-		18A275FF2C2A9563001C8D37 /* ggml-common.h */ = {isa = PBXFileReference; fileEncoding = 4; lastKnownFileType = sourcecode.c.h; name = "ggml-common.h"; path = "../../../ggml/src/ggml-common.h"; sourceTree = "<group>"; };
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-		18F8C0C12CEDF52700CAD607 /* ggml-cpu-impl.h */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.c.h; name = "ggml-cpu-impl.h"; path = "../../../ggml/src/ggml-cpu/ggml-cpu-impl.h"; sourceTree = "<group>"; };
-		18F8C0C22CEDF52700CAD607 /* ggml-cpu-quants.h */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.c.h; name = "ggml-cpu-quants.h"; path = "../../../ggml/src/ggml-cpu/ggml-cpu-quants.h"; sourceTree = "<group>"; };
-		18F8C0C32CEDF52700CAD607 /* ggml-cpu-quants.c */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.c.c; name = "ggml-cpu-quants.c"; path = "../../../ggml/src/ggml-cpu/ggml-cpu-quants.c"; sourceTree = "<group>"; };
-		18F8C0C62CEDF7AB00CAD607 /* ggml-backend-reg.cpp */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.cpp.cpp; name = "ggml-backend-reg.cpp"; path = "../../../ggml/src/ggml-backend-reg.cpp"; sourceTree = "<group>"; };
-		433188B72D3A187C00E3FE79 /* gguf.cpp */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.cpp.cpp; name = gguf.cpp; path = ../../../ggml/src/gguf.cpp; sourceTree = "<group>"; };
-		433188B92D3A18A400E3FE79 /* gguf.h */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.c.h; name = gguf.h; path = ../../../ggml/include/gguf.h; sourceTree = "<group>"; };
-		437B63E02D36280C002A49EC /* ggml-cpu-traits.h */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.c.h; name = "ggml-cpu-traits.h"; path = "../../../ggml/src/ggml-cpu/ggml-cpu-traits.h"; sourceTree = "<group>"; };
-		437B63E12D36280C002A49EC /* ggml-cpu-traits.cpp */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.cpp.cpp; name = "ggml-cpu-traits.cpp"; path = "../../../ggml/src/ggml-cpu/ggml-cpu-traits.cpp"; sourceTree = "<group>"; };
 		7FE342452A0C3FA20015A058 /* whisper-encoder-impl.m */ = {isa = PBXFileReference; fileEncoding = 4; lastKnownFileType = sourcecode.c.objc; path = "whisper-encoder-impl.m"; sourceTree = "<group>"; };
 		7FE342462A0C3FA20015A058 /* whisper-encoder.h */ = {isa = PBXFileReference; fileEncoding = 4; lastKnownFileType = sourcecode.c.h; path = "whisper-encoder.h"; sourceTree = "<group>"; };
 		7FE342472A0C3FA20015A058 /* whisper-encoder.mm */ = {isa = PBXFileReference; fileEncoding = 4; lastKnownFileType = sourcecode.cpp.objcpp; path = "whisper-encoder.mm"; sourceTree = "<group>"; };
@@ -97,6 +67,7 @@
 		7FE342492A0C3FA20015A058 /* whisper-encoder-impl.h */ = {isa = PBXFileReference; fileEncoding = 4; lastKnownFileType = sourcecode.c.h; path = "whisper-encoder-impl.h"; sourceTree = "<group>"; };
 		7FE3424A2A0C3FA20015A058 /* whisper-decoder-impl.m */ = {isa = PBXFileReference; fileEncoding = 4; lastKnownFileType = sourcecode.c.objc; path = "whisper-decoder-impl.m"; sourceTree = "<group>"; };
 		7FE3424E2A0C418A0015A058 /* ggml-base.en-encoder.mlmodelc */ = {isa = PBXFileReference; lastKnownFileType = wrapper; name = "ggml-base.en-encoder.mlmodelc"; path = "../../../models/ggml-base.en-encoder.mlmodelc"; sourceTree = "<group>"; };
+		DDE3609E2D87EA8C004EA223 /* whisper.xcframework */ = {isa = PBXFileReference; lastKnownFileType = wrapper.xcframework; name = whisper.xcframework; path = "../../build-apple/whisper.xcframework"; sourceTree = "<group>"; };
 /* End PBXFileReference section */
 
 /* Begin PBXFrameworksBuildPhase section */
@@ -104,6 +75,7 @@
 			isa = PBXFrameworksBuildPhase;
 			buildActionMask = 2147483647;
 			files = (
+				DDE3609F2D87EA8C004EA223 /* whisper.xcframework in Frameworks */,
 			);
 			runOnlyForDeploymentPostprocessing = 0;
 		};
@@ -114,6 +86,7 @@
 			isa = PBXGroup;
 			children = (
 				18627C7829052BDF00BD2A04 /* whisper.objc */,
+				DDE3609D2D87EA8C004EA223 /* Frameworks */,
 				18627C7729052BDF00BD2A04 /* Products */,
 			);
 			sourceTree = "<group>";
@@ -129,38 +102,9 @@
 		18627C7829052BDF00BD2A04 /* whisper.objc */ = {
 			isa = PBXGroup;
 			children = (
-				18B07DCB2D70411100B3B87C /* ggml-cpp.h */,
-				433188B92D3A18A400E3FE79 /* gguf.h */,
-				433188B72D3A187C00E3FE79 /* gguf.cpp */,
-				18F8C0C62CEDF7AB00CAD607 /* ggml-backend-reg.cpp */,
-				18F8C0BF2CEDF52700CAD607 /* ggml-cpu-aarch64.h */,
-				18F8C0C02CEDF52700CAD607 /* ggml-cpu-aarch64.cpp */,
-				18F8C0C12CEDF52700CAD607 /* ggml-cpu-impl.h */,
-				437B63E02D36280C002A49EC /* ggml-cpu-traits.h */,
-				437B63E12D36280C002A49EC /* ggml-cpu-traits.cpp */,
-				18F8C0C22CEDF52700CAD607 /* ggml-cpu-quants.h */,
-				18F8C0C32CEDF52700CAD607 /* ggml-cpu-quants.c */,
-				18F8C0BD2CEDF50700CAD607 /* ggml-cpu.cpp */,
-				18F8C0BA2CEDF4DC00CAD607 /* ggml-threading.h */,
-				18F8C0BB2CEDF4DC00CAD607 /* ggml-threading.cpp */,
-				18E864AA2CE73C580094B8B3 /* ggml-cpu.h */,
-				18E864A82CE73C1E0094B8B3 /* ggml-cpu.c */,
-				18A275FF2C2A9563001C8D37 /* ggml-common.h */,
-				18ABE1562AF556340044A204 /* ggml-backend-impl.h */,
-				18ABE1572AF556340044A204 /* ggml-backend.cpp */,
-				18ABE1552AF556340044A204 /* ggml-backend.h */,
-				18ABE1582AF556340044A204 /* ggml-impl.h */,
-				18ABE1592AF556340044A204 /* ggml-quants.c */,
-				18ABE1542AF556340044A204 /* ggml-quants.h */,
-				184447182AB211A2007D6BFE /* ggml-alloc.c */,
-				184447192AB211A2007D6BFE /* ggml-alloc.h */,
 				7FE3424E2A0C418A0015A058 /* ggml-base.en-encoder.mlmodelc */,
 				7FE342442A0C3FA20015A058 /* coreml */,
 				18627C9A29052CFF00BD2A04 /* ggml-base.en.bin */,
-				18627C9729052C6600BD2A04 /* ggml.h */,
-				18627C9529052C5800BD2A04 /* ggml.c */,
-				18627C9329052C4900BD2A04 /* whisper.cpp */,
-				18627C9229052C2B00BD2A04 /* whisper.h */,
 				18627C7929052BDF00BD2A04 /* AppDelegate.h */,
 				18627C7A29052BDF00BD2A04 /* AppDelegate.m */,
 				18627C7C29052BDF00BD2A04 /* SceneDelegate.h */,
@@ -190,6 +134,14 @@
 			path = ../../../src/coreml;
 			sourceTree = "<group>";
 		};
+		DDE3609D2D87EA8C004EA223 /* Frameworks */ = {
+			isa = PBXGroup;
+			children = (
+				DDE3609E2D87EA8C004EA223 /* whisper.xcframework */,
+			);
+			name = Frameworks;
+			sourceTree = "<group>";
+		};
 /* End PBXGroup section */
 
 /* Begin PBXNativeTarget section */
@@ -201,6 +153,7 @@
 				18627C7329052BDF00BD2A04 /* Frameworks */,
 				18627C7429052BDF00BD2A04 /* Resources */,
 				184447202AB21B25007D6BFE /* Copy Files */,
+				DDE360A12D87EA8C004EA223 /* Embed Frameworks */,
 			);
 			buildRules = (
 			);
@@ -264,24 +217,10 @@
 			buildActionMask = 2147483647;
 			files = (
 				18627C8129052BDF00BD2A04 /* ViewController.m in Sources */,
-				18ABE15B2AF556340044A204 /* ggml-quants.c in Sources */,
 				7FE3424C2A0C3FA20015A058 /* whisper-encoder.mm in Sources */,
-				18627C9429052C4900BD2A04 /* whisper.cpp in Sources */,
-				437B63E22D36280C002A49EC /* ggml-cpu-traits.cpp in Sources */,
-				18627C9629052C5800BD2A04 /* ggml.c in Sources */,
 				18627C7B29052BDF00BD2A04 /* AppDelegate.m in Sources */,
-				7FE3424D2A0C3FA20015A058 /* whisper-decoder-impl.m in Sources */,
-				18F8C0C72CEDF7AB00CAD607 /* ggml-backend-reg.cpp in Sources */,
-				18F8C0BE2CEDF50700CAD607 /* ggml-cpu.cpp in Sources */,
-				1844471A2AB211A2007D6BFE /* ggml-alloc.c in Sources */,
-				18F8C0C42CEDF52700CAD607 /* ggml-cpu-aarch64.cpp in Sources */,
-				18F8C0C52CEDF52700CAD607 /* ggml-cpu-quants.c in Sources */,
-				18E864A92CE73C1E0094B8B3 /* ggml-cpu.c in Sources */,
-				18ABE15A2AF556340044A204 /* ggml-backend.cpp in Sources */,
 				18627C8C29052BE000BD2A04 /* main.m in Sources */,
 				18627C7E29052BDF00BD2A04 /* SceneDelegate.m in Sources */,
-				433188B82D3A187C00E3FE79 /* gguf.cpp in Sources */,
-				18F8C0BC2CEDF4DC00CAD607 /* ggml-threading.cpp in Sources */,
 				7FE3424B2A0C3FA20015A058 /* whisper-encoder-impl.m in Sources */,
 			);
 			runOnlyForDeploymentPostprocessing = 0;
@@ -359,7 +298,7 @@
 				GCC_WARN_UNINITIALIZED_AUTOS = YES_AGGRESSIVE;
 				GCC_WARN_UNUSED_FUNCTION = YES;
 				GCC_WARN_UNUSED_VARIABLE = YES;
-				HEADER_SEARCH_PATHS = ../../../ggml/src/;
+				HEADER_SEARCH_PATHS = "";
 				IPHONEOS_DEPLOYMENT_TARGET = 16.0;
 				MTL_ENABLE_DEBUG_INFO = INCLUDE_SOURCE;
 				MTL_FAST_MATH = YES;
@@ -413,7 +352,7 @@
 				GCC_WARN_UNINITIALIZED_AUTOS = YES_AGGRESSIVE;
 				GCC_WARN_UNUSED_FUNCTION = YES;
 				GCC_WARN_UNUSED_VARIABLE = YES;
-				HEADER_SEARCH_PATHS = ../../../ggml/src/;
+				HEADER_SEARCH_PATHS = "";
 				IPHONEOS_DEPLOYMENT_TARGET = 16.0;
 				MTL_ENABLE_DEBUG_INFO = NO;
 				MTL_FAST_MATH = YES;
@@ -437,7 +376,7 @@
 				DEVELOPMENT_TEAM = P8JZH34X63;
 				GCC_WARN_64_TO_32_BIT_CONVERSION = NO;
 				GENERATE_INFOPLIST_FILE = YES;
-				HEADER_SEARCH_PATHS = ../../../ggml/src/;
+				HEADER_SEARCH_PATHS = "";
 				INFOPLIST_FILE = whisper.objc/Info.plist;
 				INFOPLIST_KEY_UIApplicationSupportsIndirectInputEvents = YES;
 				INFOPLIST_KEY_UILaunchStoryboardName = LaunchScreen;
@@ -450,10 +389,12 @@
 				);
 				MARKETING_VERSION = 1.0;
 				MTL_HEADER_SEARCH_PATHS = "";
+				OTHER_CFLAGS = "-DGGML_USE_CPU=ON";
 				PRODUCT_BUNDLE_IDENTIFIER = "com.ggerganov.whisper-objc";
 				PRODUCT_NAME = "$(TARGET_NAME)";
 				SWIFT_EMIT_LOC_STRINGS = YES;
 				TARGETED_DEVICE_FAMILY = "1,2";
+				WARNING_CFLAGS = "-Wno-quoted-include-in-framework-header";
 			};
 			name = Debug;
 		};
@@ -468,7 +409,7 @@
 				DEVELOPMENT_TEAM = P8JZH34X63;
 				GCC_WARN_64_TO_32_BIT_CONVERSION = NO;
 				GENERATE_INFOPLIST_FILE = YES;
-				HEADER_SEARCH_PATHS = ../../../ggml/src/;
+				HEADER_SEARCH_PATHS = "";
 				INFOPLIST_FILE = whisper.objc/Info.plist;
 				INFOPLIST_KEY_UIApplicationSupportsIndirectInputEvents = YES;
 				INFOPLIST_KEY_UILaunchStoryboardName = LaunchScreen;
@@ -481,10 +422,12 @@
 				);
 				MARKETING_VERSION = 1.0;
 				MTL_HEADER_SEARCH_PATHS = "";
+				OTHER_CFLAGS = "-DGGML_USE_CPU=ON";
 				PRODUCT_BUNDLE_IDENTIFIER = "com.ggerganov.whisper-objc";
 				PRODUCT_NAME = "$(TARGET_NAME)";
 				SWIFT_EMIT_LOC_STRINGS = YES;
 				TARGETED_DEVICE_FAMILY = "1,2";
+				WARNING_CFLAGS = "-Wno-quoted-include-in-framework-header";
 			};
 			name = Release;
 		};

examples/whisper.objc/whisper.objc/ViewController.m

@@ -6,8 +6,8 @@
 //
 
 #import "ViewController.h"
+#import <whisper/whisper.h>
 
-#import "whisper.h"
 
 #define NUM_BYTES_PER_BUFFER 16*1024
 
@@ -83,6 +83,19 @@ void AudioInputCallback(void * inUserData,
         stateInp.n_samples = 0;
         stateInp.audioBufferI16 = malloc(MAX_AUDIO_SEC*SAMPLE_RATE*sizeof(int16_t));
         stateInp.audioBufferF32 = malloc(MAX_AUDIO_SEC*SAMPLE_RATE*sizeof(float));
+        // Set up audio session
+        NSError *error = nil;
+
+        [[AVAudioSession sharedInstance] setCategory:AVAudioSessionCategoryRecord error:&error];
+        if (error) {
+            NSLog(@"Error setting audio session category: %@", error);
+        }
+
+        [[AVAudioSession sharedInstance] setActive:YES error:&error];
+        if (error) {
+            NSLog(@"Error activating audio session: %@", error);
+        }
+
     }
 
     stateInp.isTranscribing = false;

examples/whisper.swiftui/README.md

@@ -33,6 +33,21 @@ sudo xcode-select -switch /Applications/Xcode.app/Contents/Developer
 
 **Note:** Pay attention to the folder path: `whisper.swiftui.demo/Resources/models` is the appropriate directory to place resources whilst `whisper.swiftui.demo/Models` is related to actual code.
 
+### Core ML support
+1. Follow all the steps in the `Usage` section, including adding the ggml model file.  
+The ggml model file is required as the Core ML model is only used for the encoder. The
+decoder which is in the ggml model is still required.
+2. Follow the [`Core ML support` section of readme](../../README.md#core-ml-support) to convert the
+model.
+3. Add the Core ML model (`models/ggml-base.en-encoder.mlmodelc/`) to `whisper.swiftui.demo/Resources/models` **via Xcode**.
+
+When the example starts running you should now see that it is using the Core ML model:
+```console
+whisper_init_state: loading Core ML model from '/Library/Developer/CoreSimulator/Devices/25E8C27D-0253-4281-AF17-C3F2A4D1D8F4/data/Containers/Bundle/Application/3ADA7D59-7B9C-43B4-A7E1-A87183FC546A/whisper.swiftui.app/models/ggml-base.en-encoder.mlmodelc'
+whisper_init_state: first run on a device may take a while ...
+whisper_init_state: Core ML model loaded
+```
+
 [^1]: I recommend the tiny, base or small models for running on an iOS device.
 
 [^2]: The `Release` build can boost performance of transcription. In this project, it also added `-O3 -DNDEBUG` to `Other C Flags`, but adding flags to app proj is not ideal in real world (applies to all C/C++ files), consider splitting xcodeproj in workspace in your own project.

examples/whisper.wasm/CMakeLists.txt

@@ -32,8 +32,9 @@ set_target_properties(${TARGET} PROPERTIES LINK_FLAGS " \
     --bind \
     -s USE_PTHREADS=1 \
     -s PTHREAD_POOL_SIZE_STRICT=0 \
-    -s INITIAL_MEMORY=2000MB \
-    -s TOTAL_MEMORY=2000MB \
+    -s INITIAL_MEMORY=512MB \
+    -s MAXIMUM_MEMORY=2000MB \
+    -s ALLOW_MEMORY_GROWTH=1 \
     -s FORCE_FILESYSTEM=1 \
     -s EXPORTED_RUNTIME_METHODS=\"['print', 'printErr', 'ccall', 'cwrap']\" \
     ${EXTRA_FLAGS} \

examples/whisper.wasm/README.md

@@ -22,7 +22,7 @@ audio is limited to 120 seconds.
 
 ## Live demo
 
-Link: https://whisper.ggerganov.com
+Link: https://ggerganov.github.io/whisper.cpp/
 
 ![image](https://user-images.githubusercontent.com/1991296/197348344-1a7fead8-3dae-4922-8b06-df223a206603.png)
 
@@ -30,12 +30,22 @@ Link: https://whisper.ggerganov.com
 
 ```bash (v3.1.2)
 # build using Emscripten
-git clone https://github.com/ggerganov/whisper.cpp
+git clone https://github.com/ggml-org/whisper.cpp
 cd whisper.cpp
 mkdir build-em && cd build-em
 emcmake cmake ..
 make -j
+```
+The example can then be started by running a local HTTP server:
+```console
+python3 examples/server.py
+```
+And then opening a browser to the following URL:
+http://localhost:8000/whisper.wasm
 
+To run the example in a different server, you need to copy the following files
+to the server's HTTP path:
+```
 # copy the produced page to your HTTP path
 cp bin/whisper.wasm/*    /path/to/html/
 cp bin/libmain.worker.js /path/to/html/

examples/whisper.wasm/emscripten.cpp

@@ -65,13 +65,14 @@ EMSCRIPTEN_BINDINGS(whisper) {
         }
 
         struct whisper_full_params params = whisper_full_default_params(whisper_sampling_strategy::WHISPER_SAMPLING_GREEDY);
+        bool is_multilingual = whisper_is_multilingual(g_contexts[index]);
 
         params.print_realtime   = true;
         params.print_progress   = false;
         params.print_timestamps = true;
         params.print_special    = false;
         params.translate        = translate;
-        params.language         = whisper_is_multilingual(g_contexts[index]) ? lang.c_str() : "en";
+        params.language         = is_multilingual ? strdup(lang.c_str()) : "en";
         params.n_threads        = std::min(nthreads, std::min(16, mpow2(std::thread::hardware_concurrency())));
         params.offset_ms        = 0;
 
@@ -102,10 +103,13 @@ EMSCRIPTEN_BINDINGS(whisper) {
 
         // run the worker
         {
-            g_worker = std::thread([index, params, pcmf32 = std::move(pcmf32)]() {
+            g_worker = std::thread([index, params, pcmf32 = std::move(pcmf32), is_multilingual]() {
                 whisper_reset_timings(g_contexts[index]);
                 whisper_full(g_contexts[index], params, pcmf32.data(), pcmf32.size());
                 whisper_print_timings(g_contexts[index]);
+                if (is_multilingual) {
+                    free((void*)params.language);
+                }
             });
         }
 

examples/whisper.wasm/index-tmpl.html

@@ -24,6 +24,8 @@
                 overflow-x: scroll;
             }
         </style>
+        <script src="coi-serviceworker.js"></script>
+        <link rel="icon" href="data:,">
     </head>
     <body>
         <div id="main-container">
@@ -47,11 +49,9 @@
                 </ul>
 
             <b>More examples:</b>
-                <a href="https://whisper.ggerganov.com/">main</a> |
-                <a href="https://whisper.ggerganov.com/bench">bench</a> |
-                <a href="https://whisper.ggerganov.com/stream">stream</a> |
-                <a href="https://whisper.ggerganov.com/command">command</a> |
-                <a href="https://whisper.ggerganov.com/talk">talk</a> |
+                <a href="bench.wasm/">bench</a> |
+                <a href="stream.wasm">stream</a> |
+                <a href="command.wasm/">command</a> |
 
             <hr>
 
@@ -614,7 +614,7 @@
             var nthreads = 8;
 
             function changeThreads(value) {
-                nthreads = value;
+                nthreads = parseInt(value, 10);
                 document.getElementById('threads-value').innerHTML = nthreads;
             }
 

examples/yt-wsp.sh

@@ -25,12 +25,12 @@
 # SOFTWARE.
 
 # Small shell script to more easily automatically download and transcribe live stream VODs.
-# This uses YT-DLP, ffmpeg and the CPP version of Whisper: https://github.com/ggerganov/whisper.cpp
+# This uses YT-DLP, ffmpeg and the CPP version of Whisper: https://github.com/ggml-org/whisper.cpp
 # Use `./examples/yt-wsp.sh help` to print help info.
 #
 # Sample usage:
 #
-#   git clone https://github.com/ggerganov/whisper.cpp
+#   git clone https://github.com/ggml-org/whisper.cpp
 #   cd whisper.cpp
 #   make
 #   ./examples/yt-wsp.sh https://www.youtube.com/watch?v=1234567890
@@ -44,7 +44,7 @@ SCRIPT_DIR="${SCRIPT_PATH%/*}"
 
 ################################################################################
 # Documentation on downloading models can be found in the whisper.cpp repo:
-# https://github.com/ggerganov/whisper.cpp/#usage
+# https://github.com/ggml-org/whisper.cpp/#usage
 #
 # note: unless a multilingual model is specified, WHISPER_LANG will be ignored
 # and the video will be transcribed as if the audio were in the English language
@@ -103,10 +103,10 @@ check_requirements() {
     fi;
 
     if ! command -v "${WHISPER_EXECUTABLE}" &>/dev/null; then
-        echo "The C++ implementation of Whisper is required: https://github.com/ggerganov/whisper.cpp"
+        echo "The C++ implementation of Whisper is required: https://github.com/ggml-org/whisper.cpp"
         echo "Sample usage:";
         echo "";
-        echo "  git clone https://github.com/ggerganov/whisper.cpp";
+        echo "  git clone https://github.com/ggml-org/whisper.cpp";
         echo "  cd whisper.cpp";
         echo "  make";
         echo "  ./examples/yt-wsp.sh https://www.youtube.com/watch?v=1234567890";

ggml/CMakeLists.txt

@@ -100,6 +100,10 @@ else()
     set(INS_ENB ON)
 endif()
 
+message(DEBUG "GGML_NATIVE         : ${GGML_NATIVE}")
+message(DEBUG "GGML_NATIVE_DEFAULT : ${GGML_NATIVE_DEFAULT}")
+message(DEBUG "INS_ENB             : ${INS_ENB}")
+
 option(GGML_CPU_HBM          "ggml: use memkind for CPU HBM" OFF)
 option(GGML_CPU_AARCH64      "ggml: use runtime weight conversion of Q4_0 to Q4_X_X" ON)
 option(GGML_CPU_KLEIDIAI     "ggml: use KleidiAI optimized kernels if applicable" OFF)
@@ -123,10 +127,12 @@ endif()
 option(GGML_LASX             "ggml: enable lasx"             ON)
 option(GGML_LSX              "ggml: enable lsx"              ON)
 option(GGML_RVV              "ggml: enable rvv"              ON)
+option(GGML_RV_ZFH           "ggml: enable riscv zfh"        OFF)
 option(GGML_VXE              "ggml: enable vxe"              ON)
 
 option(GGML_CPU_ALL_VARIANTS "ggml: build all variants of the CPU backend (requires GGML_BACKEND_DL)" OFF)
-set(GGML_CPU_ARM_ARCH "" CACHE STRING "ggml: CPU architecture for ARM")
+set(GGML_CPU_ARM_ARCH        "" CACHE STRING "ggml: CPU architecture for ARM")
+set(GGML_CPU_POWERPC_CPUTYPE "" CACHE STRING "ggml: CPU type for PowerPC")
 
 
 if (WIN32)
@@ -186,6 +192,7 @@ option(GGML_OPENMP                          "ggml: use OpenMP"
 option(GGML_RPC                             "ggml: use RPC"                                   OFF)
 option(GGML_SYCL                            "ggml: use SYCL"                                  OFF)
 option(GGML_SYCL_F16                        "ggml: use 16 bit floats for sycl calculations"   OFF)
+option(GGML_SYCL_GRAPH                      "ggml: enable graphs in the SYCL backend"         ON)
 set   (GGML_SYCL_TARGET "INTEL" CACHE STRING
                                             "ggml: sycl target device")
 set   (GGML_SYCL_DEVICE_ARCH "" CACHE STRING
@@ -195,6 +202,8 @@ option(GGML_OPENCL                          "ggml: use OpenCL"
 option(GGML_OPENCL_PROFILING                "ggml: use OpenCL profiling (increases overhead)" OFF)
 option(GGML_OPENCL_EMBED_KERNELS            "ggml: embed kernels"                             ON)
 option(GGML_OPENCL_USE_ADRENO_KERNELS       "ggml: use optimized kernels for Adreno"          ON)
+set   (GGML_OPENCL_TARGET_VERSION "300" CACHE STRING
+                                            "gmml: OpenCL API version to target")
 
 # toolchain for vulkan-shaders-gen
 set   (GGML_VULKAN_SHADERS_GEN_TOOLCHAIN "" CACHE FILEPATH "ggml: toolchain file for vulkan-shaders-gen")

ggml/cmake/common.cmake

@@ -0,0 +1,26 @@
+function(ggml_get_flags CCID CCVER)
+    set(C_FLAGS "")
+    set(CXX_FLAGS "")
+
+    if (CCID MATCHES "Clang")
+        set(C_FLAGS   -Wunreachable-code-break -Wunreachable-code-return)
+        set(CXX_FLAGS -Wunreachable-code-break -Wunreachable-code-return -Wmissing-prototypes -Wextra-semi)
+
+        if (
+            (CCID STREQUAL "Clang"      AND CCVER VERSION_GREATER_EQUAL 3.8.0) OR
+            (CCID STREQUAL "AppleClang" AND CCVER VERSION_GREATER_EQUAL 7.3.0)
+        )
+            list(APPEND C_FLAGS -Wdouble-promotion)
+        endif()
+    elseif (CCID STREQUAL "GNU")
+        set(C_FLAGS   -Wdouble-promotion)
+        set(CXX_FLAGS -Wno-array-bounds)
+
+        if (CCVER VERSION_GREATER_EQUAL 8.1.0)
+            list(APPEND CXX_FLAGS -Wextra-semi)
+        endif()
+    endif()
+
+    set(GF_C_FLAGS   ${C_FLAGS}   PARENT_SCOPE)
+    set(GF_CXX_FLAGS ${CXX_FLAGS} PARENT_SCOPE)
+endfunction()

ggml/cmake/ggml-config.cmake.in

@@ -5,7 +5,7 @@
 
 set_and_check(GGML_INCLUDE_DIR "@PACKAGE_GGML_INCLUDE_INSTALL_DIR@")
 set_and_check(GGML_LIB_DIR "@PACKAGE_GGML_LIB_INSTALL_DIR@")
-set_and_check(GGML_BIN_DIR "@PACKAGE_GGML_BIN_INSTALL_DIR@")
+#set_and_check(GGML_BIN_DIR "@PACKAGE_GGML_BIN_INSTALL_DIR@")
 
 find_package(Threads REQUIRED)
 

ggml/include/ggml-rpc.h

@@ -17,7 +17,9 @@ GGML_BACKEND_API ggml_backend_buffer_type_t ggml_backend_rpc_buffer_type(const c
 
 GGML_BACKEND_API void ggml_backend_rpc_get_device_memory(const char * endpoint, size_t * free, size_t * total);
 
-GGML_BACKEND_API void ggml_backend_rpc_start_server(ggml_backend_t backend, const char * endpoint, size_t free_mem, size_t total_mem);
+GGML_BACKEND_API void ggml_backend_rpc_start_server(ggml_backend_t backend, const char * endpoint,
+                                                    const char * cache_dir,
+                                                    size_t free_mem, size_t total_mem);
 
 GGML_BACKEND_API ggml_backend_reg_t ggml_backend_rpc_reg(void);
 

ggml/include/ggml.h

@@ -454,6 +454,7 @@ extern "C" {
         GGML_OP_RMS_NORM,
         GGML_OP_RMS_NORM_BACK,
         GGML_OP_GROUP_NORM,
+        GGML_OP_L2_NORM,
 
         GGML_OP_MUL_MAT,
         GGML_OP_MUL_MAT_ID,
@@ -502,6 +503,7 @@ extern "C" {
         GGML_OP_ADD_REL_POS,
         GGML_OP_RWKV_WKV6,
         GGML_OP_GATED_LINEAR_ATTN,
+        GGML_OP_RWKV_WKV7,
 
         GGML_OP_UNARY,
 
@@ -1095,6 +1097,18 @@ extern "C" {
             int                   n_groups,
             float                 eps);
 
+    // l2 normalize along rows
+    // used in rwkv v7
+    GGML_API struct ggml_tensor * ggml_l2_norm(
+            struct ggml_context * ctx,
+            struct ggml_tensor  * a,
+            float                 eps);
+
+    GGML_API struct ggml_tensor * ggml_l2_norm_inplace(
+            struct ggml_context * ctx,
+            struct ggml_tensor  * a,
+            float                 eps);
+
     // a - x
     // b - dy
     GGML_API struct ggml_tensor * ggml_rms_norm_back(
@@ -1777,11 +1791,11 @@ extern "C" {
 
 #define GGML_KQ_MASK_PAD 64
 
-    // q:    [n_embd, n_batch,     n_head,    1]
-    // k:    [n_embd, n_kv,        n_head_kv, 1]
-    // v:    [n_embd, n_kv,        n_head_kv, 1] !! not transposed !!
-    // mask: [n_kv,   n_batch_pad, 1,         1] !! n_batch_pad = GGML_PAD(n_batch, GGML_KQ_MASK_PAD) !!
-    // res:  [n_embd, n_head,      n_batch,   1] !! permuted !!
+    // q:    [n_embd_k, n_batch,     n_head,    1]
+    // k:    [n_embd_k, n_kv,        n_head_kv, 1]
+    // v:    [n_embd_v, n_kv,        n_head_kv, 1] !! not transposed !!
+    // mask: [n_kv,     n_batch_pad, 1,         1] !! n_batch_pad = GGML_PAD(n_batch, GGML_KQ_MASK_PAD) !!
+    // res:  [n_embd_v, n_head,      n_batch,   1] !! permuted !!
     GGML_API struct ggml_tensor * ggml_flash_attn_ext(
             struct ggml_context * ctx,
             struct ggml_tensor  * q,
@@ -1890,6 +1904,16 @@ extern "C" {
             struct ggml_tensor  * state,
             float scale);
 
+    GGML_API struct ggml_tensor * ggml_rwkv_wkv7(
+            struct ggml_context * ctx,
+            struct ggml_tensor  * r,
+            struct ggml_tensor  * w,
+            struct ggml_tensor  * k,
+            struct ggml_tensor  * v,
+            struct ggml_tensor  * a,
+            struct ggml_tensor  * b,
+            struct ggml_tensor  * state);
+
     // custom operators
 
     typedef void (*ggml_unary_op_f32_t) (const int, float *, const float *);

ggml/src/CMakeLists.txt

@@ -1,4 +1,5 @@
 include(CheckCXXCompilerFlag)
+include("../cmake/common.cmake")
 
 add_compile_definitions(GGML_SCHED_MAX_COPIES=${GGML_SCHED_MAX_COPIES})
 
@@ -24,33 +25,6 @@ if (NOT MSVC)
     endif()
 endif()
 
-function(ggml_get_flags CCID CCVER)
-    set(C_FLAGS "")
-    set(CXX_FLAGS "")
-
-    if (CCID MATCHES "Clang")
-        set(C_FLAGS   -Wunreachable-code-break -Wunreachable-code-return)
-        set(CXX_FLAGS -Wunreachable-code-break -Wunreachable-code-return -Wmissing-prototypes -Wextra-semi)
-
-        if (
-            (CCID STREQUAL "Clang"      AND CCVER VERSION_GREATER_EQUAL 3.8.0) OR
-            (CCID STREQUAL "AppleClang" AND CCVER VERSION_GREATER_EQUAL 7.3.0)
-        )
-            list(APPEND C_FLAGS -Wdouble-promotion)
-        endif()
-    elseif (CCID STREQUAL "GNU")
-        set(C_FLAGS   -Wdouble-promotion)
-        set(CXX_FLAGS -Wno-array-bounds)
-
-        if (CCVER VERSION_GREATER_EQUAL 8.1.0)
-            list(APPEND CXX_FLAGS -Wextra-semi)
-        endif()
-    endif()
-
-    set(GF_C_FLAGS   ${C_FLAGS}   PARENT_SCOPE)
-    set(GF_CXX_FLAGS ${CXX_FLAGS} PARENT_SCOPE)
-endfunction()
-
 if (GGML_FATAL_WARNINGS)
     if (CMAKE_CXX_COMPILER_ID MATCHES "GNU" OR CMAKE_CXX_COMPILER_ID MATCHES "Clang")
         list(APPEND C_FLAGS   -Werror)
@@ -91,7 +65,7 @@ if (GGML_LTO)
     endif()
 endif()
 
-if (GGML_CCACHE)
+if (GGML_CCACHE AND NOT CMAKE_C_COMPILER_LAUNCHER AND NOT CMAKE_CXX_COMPILER_LAUNCHER)
     find_program(GGML_CCACHE_FOUND ccache)
     find_program(GGML_SCCACHE_FOUND sccache)
 
@@ -102,7 +76,11 @@ if (GGML_CCACHE)
             set(GGML_CCACHE_VARIANT sccache)
         endif()
         # TODO: should not be set globally
-        set_property(GLOBAL PROPERTY RULE_LAUNCH_COMPILE "${GGML_CCACHE_VARIANT}")
+        if (GGML_SYCL AND GGML_CCACHE_FOUND AND WIN32)
+            set_property(GLOBAL PROPERTY RULE_LAUNCH_COMPILE "ccache compiler_type=icl")
+        else ()
+            set_property(GLOBAL PROPERTY RULE_LAUNCH_COMPILE "${GGML_CCACHE_VARIANT}")
+        endif ()
         set(ENV{CCACHE_SLOPPINESS} time_macros)
         message(STATUS "${GGML_CCACHE_VARIANT} found, compilation results will be cached. Disable with GGML_CCACHE=OFF.")
     else()
@@ -351,6 +329,10 @@ if (CMAKE_SYSTEM_NAME MATCHES "Android")
     target_link_libraries(ggml-base PRIVATE dl)
 endif()
 
+if(CMAKE_SYSTEM_NAME MATCHES "visionOS")
+    target_compile_definitions(ggml-base PUBLIC _DARWIN_C_SOURCE)
+endif()
+
 if (BUILD_SHARED_LIBS)
     foreach (target ggml-base ggml)
         set_target_properties(${target} PROPERTIES POSITION_INDEPENDENT_CODE ON)

ggml/src/ggml-backend-reg.cpp

@@ -76,7 +76,14 @@ namespace fs = std::filesystem;
 static std::string path_str(const fs::path & path) {
     std::string u8path;
     try {
+#if defined(__cpp_lib_char8_t)
+        // C++20 and later: u8string() returns std::u8string
+        std::u8string u8str = path.u8string();
+        u8path = std::string(reinterpret_cast<const char*>(u8str.c_str()));
+#else
+        // C++17: u8string() returns std::string
         u8path = path.u8string();
+#endif
     } catch (...) {
     }
     return u8path;
@@ -490,7 +497,7 @@ static ggml_backend_reg_t ggml_backend_load_best(const char * name, bool silent,
         search_paths.push_back(get_executable_path());
         search_paths.push_back(fs::current_path());
     } else {
-        search_paths.push_back(user_search_path);
+        search_paths.push_back(fs::u8path(user_search_path));
     }
 
     int best_score = 0;
@@ -504,9 +511,9 @@ static ggml_backend_reg_t ggml_backend_load_best(const char * name, bool silent,
         fs::directory_iterator dir_it(search_path, fs::directory_options::skip_permission_denied);
         for (const auto & entry : dir_it) {
             if (entry.is_regular_file()) {
-                auto filename = entry.path().filename().native();
-                auto ext = entry.path().extension().native();
-                if (filename.find(file_prefix) == 0 && ext == file_extension) {
+                auto filename = entry.path().filename();
+                auto ext = entry.path().extension();
+                if (filename.native().find(file_prefix) == 0 && ext == file_extension) {
                     dl_handle_ptr handle { dl_load_library(entry) };
                     if (!handle && !silent) {
                         GGML_LOG_ERROR("%s: failed to load %s\n", __func__, path_str(entry.path()).c_str());
@@ -537,7 +544,7 @@ static ggml_backend_reg_t ggml_backend_load_best(const char * name, bool silent,
         // try to load the base backend
         for (const auto & search_path : search_paths) {
             fs::path filename = backend_filename_prefix().native() + name_path.native() + backend_filename_extension().native();
-            fs::path path = search_path.native() + filename.native();
+            fs::path path = search_path / filename;
             if (fs::exists(path)) {
                 return get_reg().load_backend(path, silent);
             }

ggml/src/ggml-cann/CMakeLists.txt

@@ -51,13 +51,11 @@ if (CANN_INSTALL_DIR)
         ${CANN_INSTALL_DIR}/acllib/include
     )
 
-    add_subdirectory(kernels)
     list(APPEND CANN_LIBRARIES
         ascendcl
         nnopbase
         opapi
         acl_op_compiler
-        ascendc_kernels
     )
 
     file(GLOB GGML_SOURCES_CANN "*.cpp")

ggml/src/ggml-cann/aclnn_ops.cpp

@@ -30,6 +30,7 @@
 #include <aclnnop/aclnn_copy.h>
 #include <aclnnop/aclnn_cos.h>
 #include <aclnnop/aclnn_div.h>
+#include <aclnnop/aclnn_embedding.h>
 #include <aclnnop/aclnn_exp.h>
 #include <aclnnop/aclnn_fill_scalar.h>
 #include <aclnnop/aclnn_group_norm.h>
@@ -58,7 +59,6 @@
 #include <vector>
 
 #include "ggml-impl.h"
-#include "kernels/ascendc_kernels.h"
 
 #define GGML_COMMON_DECL_C
 
@@ -99,6 +99,35 @@ static void aclnn_repeat(ggml_backend_cann_context& ctx, aclTensor* acl_src,
     ACL_CHECK(aclDestroyIntArray(repeats));
 }
 
+/**
+ * @brief Casts the elements of a tensor to a specified data type using the CANN backend.
+ *
+ * @details This function performs a type conversion on the elements of the input tensor `acl_src`
+ *          and stores the results in the destination tensor `acl_dst`. The conversion type is
+ *          determined based on the `dst` tensor's data type.
+ *
+ * @param ctx The context for the CANN backend operations.
+ * @param acl_src The source tensor whose elements will be cast.
+ * @param acl_dst The destination tensor that will store the casted elements.
+ * @param dst The ggml tensor specifying the target data type.
+ */
+static void aclnn_cast(ggml_backend_cann_context& ctx, aclTensor* acl_src,
+                    aclTensor* acl_dst, ggml_tensor* dst) {
+    uint64_t workspaceSize = 0;
+    aclOpExecutor* executor;
+    void* workspaceAddr = nullptr;
+    ACL_CHECK(aclnnCastGetWorkspaceSize(acl_src,
+                                        ggml_cann_type_mapping(dst->type),
+                                        acl_dst, &workspaceSize, &executor));
+
+    if (workspaceSize > 0) {
+        ggml_cann_pool_alloc workspace_allocator(ctx.pool(), workspaceSize);
+        workspaceAddr = workspace_allocator.get();
+    }
+
+    ACL_CHECK(aclnnCast(workspaceAddr, workspaceSize, executor, ctx.stream()));
+}
+
 void ggml_cann_repeat(ggml_backend_cann_context& ctx, ggml_tensor* dst) {
     ggml_tensor* src = dst->src[0];
     GGML_ASSERT(ggml_can_repeat(src, dst));
@@ -889,173 +918,76 @@ static void cann_copy(ggml_backend_cann_context& ctx, aclTensor* acl_src,
 }
 
 void ggml_cann_dup(ggml_backend_cann_context& ctx, ggml_tensor* dst) {
-    ggml_tensor* src = dst->src[0];
+    ggml_tensor* src0 = dst->src[0];
 
-    aclTensor* acl_src = ggml_cann_create_tensor(src);
+    aclTensor* acl_src = ggml_cann_create_tensor(src0);
     aclTensor* acl_dst = ggml_cann_create_tensor(dst);
-
-    ggml_cann_pool_alloc src_extra_allocator(ctx.pool(), sizeof(ggml_tensor));
-    ggml_cann_pool_alloc dst_extra_allocator(ctx.pool(), sizeof(ggml_tensor));
-    src->extra = src_extra_allocator.get();
-    dst->extra = dst_extra_allocator.get();
-    ACL_CHECK(aclrtMemcpyAsync(src->extra, sizeof(ggml_tensor), src,
-                               sizeof(ggml_tensor), ACL_MEMCPY_HOST_TO_DEVICE,
-                               ctx.stream()));
-    ACL_CHECK(aclrtMemcpyAsync(dst->extra, sizeof(ggml_tensor), dst,
-                               sizeof(ggml_tensor), ACL_MEMCPY_HOST_TO_DEVICE,
-                               ctx.stream()));
-
-    if ((dst->type == GGML_TYPE_F16 || dst->type == GGML_TYPE_F32) &&
-        ggml_are_same_shape(src, dst)) {
-        cann_copy(ctx, acl_src, acl_dst);
-        ACL_CHECK(aclDestroyTensor(acl_src));
-        ACL_CHECK(aclDestroyTensor(acl_dst));
-        return;
-    }
-    // TODO: simplify
-    if (src->type == GGML_TYPE_F16) {
-        if (dst->type == GGML_TYPE_Q8_0) {
-            aclrtlaunch_ascendc_quantize_f16_q8_0(
-                24, ctx.stream(), src->data, dst->data,
-                ((ggml_tensor*)src->extra)->ne, ((ggml_tensor*)src->extra)->nb,
-                ((ggml_tensor*)dst->extra)->ne);
-            return;
-        }
-        if (dst->type == GGML_TYPE_Q4_0) {
-            aclrtlaunch_ascendc_quantize_f16_to_q4_0(
-                24, ctx.stream(), src->data, dst->data,
-                ((ggml_tensor*)src->extra)->ne, ((ggml_tensor*)src->extra)->nb,
-                ((ggml_tensor*)dst->extra)->ne);
-            return;
-        }
-        if (dst->type == GGML_TYPE_F16) {
-            if (ggml_are_same_shape(src, dst)) {
-                cann_copy(ctx, acl_src, acl_dst);
-                ACL_CHECK(aclDestroyTensor(acl_src));
-                ACL_CHECK(aclDestroyTensor(acl_dst));
-                return;
-            }
-            if (ggml_is_contiguous(dst)) {
-                const size_t src_type_size = ggml_type_size(src->type);
-                if (src->nb[0] == src_type_size) {
-                    // src0 is contigous on first dimension, copy by rows
-                    int64_t rows_num = ggml_nrows(src);
-
-                    aclrtlaunch_ascendc_dup_by_rows_fp16(
-                        rows_num, ctx.stream(), src->data, dst->data,
-                        ((ggml_tensor*)src->extra)->ne,
-                        ((ggml_tensor*)src->extra)->nb,
-                        ((ggml_tensor*)dst->extra)->ne,
-                        ((ggml_tensor*)dst->extra)->nb);
-                    return;
-                }
-                GGML_ABORT("fatal error");
-            }
-            GGML_ABORT("fatal error");
-        }
-        if (dst->type == GGML_TYPE_F32) {
-            if (ggml_are_same_shape(src, dst)) {
-                cann_copy(ctx, acl_src, acl_dst);
-                ACL_CHECK(aclDestroyTensor(acl_src));
-                ACL_CHECK(aclDestroyTensor(acl_dst));
-                return;
-            }
-            if (ggml_is_contiguous(dst)) {
-                const size_t src_type_size = ggml_type_size(src->type);
-                if (src->nb[0] == src_type_size) {
-                    // src0 is contigous on first dimension, copy by rows
-                    int64_t rows_num = ggml_nrows(src);
-                    aclrtlaunch_ascendc_dup_by_rows_fp16_to_fp32(
-                        rows_num, ctx.stream(), src->data, dst->data,
-                        ((ggml_tensor*)src->extra)->ne,
-                        ((ggml_tensor*)src->extra)->nb,
-                        ((ggml_tensor*)dst->extra)->ne,
-                        ((ggml_tensor*)dst->extra)->nb);
-                    return;
-                }
-                GGML_ABORT("fatal error");
-            }
-            GGML_ABORT("fatal error");
-        }
-        // TODO
-        GGML_ABORT("fatal error");
-    } else if (src->type == GGML_TYPE_F32) {
-        // TODO: if (src0->type == dst->type && ne00 == ne0 && nb00 == type_size
-        //          && nb0 == type_size)
-        if (dst->type == GGML_TYPE_Q8_0) {
-            aclrtlaunch_ascendc_quantize_f32_q8_0(
-                24, ctx.stream(), src->data, dst->data,
-                ((ggml_tensor*)src->extra)->ne, ((ggml_tensor*)src->extra)->nb,
-                ((ggml_tensor*)dst->extra)->ne);
-            return;
-        }
-        if (dst->type == GGML_TYPE_Q4_0) {
-            aclrtlaunch_ascendc_quantize_f32_to_q4_0(
-                24, ctx.stream(), src->data, dst->data,
-                ((ggml_tensor*)src->extra)->ne, ((ggml_tensor*)src->extra)->nb,
-                ((ggml_tensor*)dst->extra)->ne);
-            return;
-        }
-        if (dst->type == GGML_TYPE_F32) {
-            if (ggml_are_same_shape(src, dst)) {
-                cann_copy(ctx, acl_src, acl_dst);
-                ACL_CHECK(aclDestroyTensor(acl_src));
-                ACL_CHECK(aclDestroyTensor(acl_dst));
-                return;
-            }
-            if (ggml_is_contiguous(dst)) {
-                const size_t src_type_size = ggml_type_size(src->type);
-                if (src->nb[0] == src_type_size) {
-                    // src0 is contigous on first dimension, copy by rows
-                    int64_t rows_num = ggml_nrows(src);
-                    aclrtlaunch_ascendc_dup_by_rows_fp32(
-                        rows_num, ctx.stream(), src->data, dst->data,
-                        ((ggml_tensor*)src->extra)->ne,
-                        ((ggml_tensor*)src->extra)->nb,
-                        ((ggml_tensor*)dst->extra)->ne,
-                        ((ggml_tensor*)dst->extra)->nb);
-                    return;
-                }
-                GGML_ABORT("fatal error");
-            } else {
-                // TODO: dst not contiguous
-                GGML_ABORT("fatal error");
-            }
-        }
-        if (dst->type == GGML_TYPE_F16) {
-            if (ggml_are_same_shape(src, dst)) {
-                cann_copy(ctx, acl_src, acl_dst);
-                ACL_CHECK(aclDestroyTensor(acl_src));
-                ACL_CHECK(aclDestroyTensor(acl_dst));
-                return;
-            }
-            if (ggml_is_contiguous(dst)) {
-                const size_t src_type_size = ggml_type_size(src->type);
-                if (src->nb[0] == src_type_size) {
-                    // src0 is contigous on first dimension, copy by rows
-                    int64_t rows_num = ggml_nrows(src);
-                    aclrtlaunch_ascendc_dup_by_rows_fp32_to_fp16(
-                        rows_num, ctx.stream(), src->data, dst->data,
-                        ((ggml_tensor*)src->extra)->ne,
-                        ((ggml_tensor*)src->extra)->nb,
-                        ((ggml_tensor*)dst->extra)->ne,
-                        ((ggml_tensor*)dst->extra)->nb);
-                    return;
-                }
-                GGML_ABORT("fatal error");
-            }
-        }
-        // TODO
-        GGML_ABORT("fatal error");
-    } else {
-        if (ggml_are_same_shape(src, dst)) {
+    if (ggml_are_same_shape(src0, dst)) {
+        if (dst->type == src0->type) {
             cann_copy(ctx, acl_src, acl_dst);
-            ACL_CHECK(aclDestroyTensor(acl_src));
-            ACL_CHECK(aclDestroyTensor(acl_dst));
-            return;
+        } else {
+            aclnn_cast(ctx, acl_src, acl_dst, dst);
+        }
+    } else {
+        if (ggml_is_contiguous(src0) && ggml_is_contiguous(dst)) {
+            if (dst->type == src0->type) {
+                size_t cpy_size = ggml_nbytes(dst);
+                ACL_CHECK(aclrtMemcpyAsync(
+                    dst->data, cpy_size, src0->data, cpy_size,
+                    ACL_MEMCPY_DEVICE_TO_DEVICE, ctx.stream()));
+                return;
+            } else {
+                ggml_cann_pool_alloc src_buffer_allocator(
+                    ctx.pool(),
+                    ggml_nelements(dst) * ggml_type_size(dst->type));
+                void* src_trans_buffer = src_buffer_allocator.get();
+                size_t src_trans_nb[GGML_MAX_DIMS];
+                src_trans_nb[0] = ggml_type_size(dst->type);
+                for (int i = 1; i < GGML_MAX_DIMS; i++) {
+                    src_trans_nb[i] = src_trans_nb[i - 1] * src0->ne[i - 1];
+                }
+                aclTensor* src_trans_tensor = ggml_cann_create_tensor(
+                    src_trans_buffer, ggml_cann_type_mapping(dst->type),
+                    ggml_type_size(dst->type), src0->ne, src_trans_nb,
+                    GGML_MAX_DIMS);
+
+                aclnn_cast(ctx, acl_src, src_trans_tensor, dst);
+                size_t cpy_size = ggml_nbytes(dst);
+                ACL_CHECK(aclrtMemcpyAsync(
+                    dst->data, cpy_size, src_trans_buffer, cpy_size,
+                    ACL_MEMCPY_DEVICE_TO_DEVICE, ctx.stream()));
+                ACL_CHECK(aclDestroyTensor(src_trans_tensor));
+                return;
+            }
+        } else if (ggml_is_contiguous(dst)) {
+            ggml_cann_pool_alloc src_buffer_allocator(
+                ctx.pool(), ggml_nelements(dst) * ggml_type_size(dst->type));
+            void* src_trans_buffer = src_buffer_allocator.get();
+            size_t src_trans_nb[GGML_MAX_DIMS];
+            src_trans_nb[0] = ggml_type_size(dst->type);
+            for (int i = 1; i < GGML_MAX_DIMS; i++) {
+                src_trans_nb[i] = src_trans_nb[i - 1] * src0->ne[i - 1];
+            }
+            aclTensor* src_trans_tensor = ggml_cann_create_tensor(
+                src_trans_buffer, ggml_cann_type_mapping(dst->type),
+                ggml_type_size(dst->type), src0->ne, src_trans_nb,
+                GGML_MAX_DIMS);
+
+            aclnn_cast(ctx, acl_src, src_trans_tensor, dst);
+
+            size_t cpy_size = ggml_nbytes(dst);
+            ACL_CHECK(aclrtMemcpyAsync(dst->data, cpy_size, src_trans_buffer,
+                                       cpy_size, ACL_MEMCPY_DEVICE_TO_DEVICE,
+                                       ctx.stream()));
+            ACL_CHECK(aclDestroyTensor(src_trans_tensor));
+            return;
+        } else {
+            GGML_ABORT("Unsupport dst is not tontiguous.");
         }
-        GGML_ABORT("fatal error");
     }
+
+    ACL_CHECK(aclDestroyTensor(acl_src));
+    ACL_CHECK(aclDestroyTensor(acl_dst));
 }
 
 #ifdef __cplusplus
@@ -2378,85 +2310,168 @@ void ggml_cann_softmax(ggml_backend_cann_context& ctx, ggml_tensor* dst) {
     ACL_CHECK(aclDestroyTensor(tmp_mask_tensor));
 }
 
-void ggml_cann_get_rows(ggml_backend_cann_context& ctx, ggml_tensor* dst) {
-    ggml_tensor* src0 = dst->src[0];
-    ggml_tensor* src1 = dst->src[1];
+/**
+ * @brief Performs embedding operation on a 4D tensor using the CANN backend.
+ *
+ * This function extracts slices from the source tensor (`src_buffer`),
+ * index tensor (`index`), and destination tensor (`dst`), and performs an
+ * embedding operation on them. The embedding operation is applied by iterating
+ * over the last two dimensions of the source tensor, creating the necessary
+ * tensors for the source, index, and output, and executing the embedding operation.
+ *
+ * @param ctx The context for CANN backend operations.
+ * @param src_buffer The source buffer holding the data for the source tensor.
+ * @param src_ne The dimensions of the source tensor.
+ * @param src_nb The strides (byte offsets) of the source tensor.
+ * @param index The index tensor used in the embedding operation.
+ * @param dst The destination tensor where the result will be stored.
+ */
+static void aclnn_embedding_4d(ggml_backend_cann_context& ctx, void* src_buffer,
+                            int64_t* src_ne, size_t* src_nb, ggml_tensor* index,
+                            ggml_tensor* dst) {
+    for (int64_t i = 0; i < src_ne[3]; i++) {
+        for (int64_t j = 0; j < src_ne[2]; j++) {
+            // src
+            int64_t acl_src_ne[2] = {src_ne[0], src_ne[1]};
+            size_t acl_src_nb[2] = {src_nb[0], src_nb[1]};
+            aclTensor* acl_src_tensor = ggml_cann_create_tensor(
+                (char*)src_buffer + i * src_nb[3] + j * src_nb[2],
+                ggml_cann_type_mapping(dst->type), ggml_element_size(dst),
+                acl_src_ne, acl_src_nb, 2);
 
-    ggml_cann_pool_alloc src0_extra_allocator(ctx.pool(), sizeof(ggml_tensor));
-    ggml_cann_pool_alloc src1_extra_allocator(ctx.pool(), sizeof(ggml_tensor));
-    ggml_cann_pool_alloc dst_extra_allocator(ctx.pool(), sizeof(ggml_tensor));
-    src0->extra = src0_extra_allocator.get();
-    src1->extra = src1_extra_allocator.get();
-    dst->extra = dst_extra_allocator.get();
-    ACL_CHECK(aclrtMemcpyAsync(src0->extra, sizeof(ggml_tensor), src0,
-                               sizeof(ggml_tensor), ACL_MEMCPY_HOST_TO_DEVICE,
-                               ctx.stream()));
-    ACL_CHECK(aclrtMemcpyAsync(src1->extra, sizeof(ggml_tensor), src1,
-                               sizeof(ggml_tensor), ACL_MEMCPY_HOST_TO_DEVICE,
-                               ctx.stream()));
-    ACL_CHECK(aclrtMemcpyAsync(dst->extra, sizeof(ggml_tensor), dst,
-                               sizeof(ggml_tensor), ACL_MEMCPY_HOST_TO_DEVICE,
-                               ctx.stream()));
+            // index
+            int64_t acl_index_ne[1] = {index->ne[0]};
+            size_t acl_index_nb[1] = {index->nb[0]};
+            aclTensor* acl_index = ggml_cann_create_tensor(
+                (char*)index->data + i * index->nb[2] + j * index->nb[1],
+                ggml_cann_type_mapping(index->type), ggml_element_size(index),
+                acl_index_ne, acl_index_nb, 1);
+
+            // out
+            int64_t acl_out_ne[2] = {dst->ne[0], dst->ne[1]};
+            size_t acl_out_nb[2] = {dst->nb[0], dst->nb[1]};
+            aclTensor* acl_out = ggml_cann_create_tensor(
+                (char*)dst->data + i * dst->nb[3] + j * dst->nb[2],
+                ggml_cann_type_mapping(dst->type), ggml_element_size(dst),
+                acl_out_ne, acl_out_nb, 2);
+
+            uint64_t workspaceSize = 0;
+            aclOpExecutor* executor;
+            void* workspaceAddr = nullptr;
+
+            ACL_CHECK(aclnnEmbeddingGetWorkspaceSize(
+                acl_src_tensor, acl_index, acl_out, &workspaceSize, &executor));
+
+            if (workspaceSize > 0) {
+                ggml_cann_pool_alloc workspace_allocator(ctx.pool(),
+                                                         workspaceSize);
+                workspaceAddr = workspace_allocator.get();
+            }
+
+            ACL_CHECK(aclnnEmbedding(workspaceAddr, workspaceSize, executor,
+                                     ctx.stream()));
+
+            ACL_CHECK(aclDestroyTensor(acl_src_tensor));
+            ACL_CHECK(aclDestroyTensor(acl_index));
+            ACL_CHECK(aclDestroyTensor(acl_out));
+        }
+    }
+}
+
+void ggml_cann_get_rows(ggml_backend_cann_context& ctx, ggml_tensor* dst) {
+    ggml_tensor* src0 = dst->src[0];  // src
+    ggml_tensor* src1 = dst->src[1];  // index
 
     switch (src0->type) {
         case GGML_TYPE_F32: {
-#ifdef ASCEND_310P
-            // Special operation for get_row_f32 kernel of 310P: clear the
-            // content of dest data buffer when row is not aligned to 32 bytes
-            if ((src0->ne[0] % 8) != 0) {
-                size_t dst_len = src1->ne[0] * src1->ne[1] * src1->ne[2] *
-                                 src0->ne[0] * ggml_type_size(GGML_TYPE_F32);
-                ACL_CHECK(aclrtMemset((char*)dst->data, dst_len, 0, dst_len));
-            }
-#endif
-            aclrtlaunch_ascendc_get_row_f32(
-                24, ctx.stream(), src0->data, src1->data, dst->data,
-                ((ggml_tensor*)src0->extra)->ne,
-                ((ggml_tensor*)src0->extra)->nb,
-                ((ggml_tensor*)src1->extra)->ne,
-                ((ggml_tensor*)src1->extra)->nb, ((ggml_tensor*)dst->extra)->ne,
-                ((ggml_tensor*)dst->extra)->nb);
+            aclnn_embedding_4d(ctx, src0->data, src0->ne, src0->nb, src1,
+                                   dst);
             break;
         }
         case GGML_TYPE_F16: {
-#ifdef ASCEND_310P
-            // Special operation for get_row_f16 kernel of 310P: clear the
-            // content of dest data buffer when row is not aligned to 32 bytes
-            if ((src0->ne[0] % 16) != 0) {
-                size_t dst_len =
-                    src1->ne[0] * src1->ne[1] * src1->ne[2] * src0->ne[0] *
-                    ggml_type_size(
-                        GGML_TYPE_F32);  // out is also f32, even input is f16
-                ACL_CHECK(aclrtMemset((char*)dst->data, dst_len, 0, dst_len));
+            aclTensor* acl_src0 = ggml_cann_create_tensor(src0);
+            ggml_cann_pool_alloc src_buffer_allocator(
+                ctx.pool(), ggml_nelements(src0) * sizeof(float_t));
+            void* src_trans_buffer = src_buffer_allocator.get();
+            size_t src_trans_nb[GGML_MAX_DIMS];
+            src_trans_nb[0] = sizeof(float_t);
+            for (int i = 1; i < GGML_MAX_DIMS; i++) {
+                src_trans_nb[i] = src_trans_nb[i - 1] * src0->ne[i - 1];
             }
-#endif
-            aclrtlaunch_ascendc_get_row_f16(
-                24, ctx.stream(), src0->data, src1->data, dst->data,
-                ((ggml_tensor*)src0->extra)->ne,
-                ((ggml_tensor*)src0->extra)->nb,
-                ((ggml_tensor*)src1->extra)->ne,
-                ((ggml_tensor*)src1->extra)->nb, ((ggml_tensor*)dst->extra)->ne,
-                ((ggml_tensor*)dst->extra)->nb);
+            aclTensor* src_trans_tensor = ggml_cann_create_tensor(
+                src_trans_buffer, ACL_FLOAT, ggml_type_size(dst->type),
+                src0->ne, src_trans_nb, GGML_MAX_DIMS);
+            aclnn_cast(ctx, acl_src0, src_trans_tensor, dst);
+            aclnn_embedding_4d(ctx, src_trans_buffer, src0->ne,
+                                   src_trans_nb, src1, dst);
+            ACL_CHECK(aclDestroyTensor(acl_src0));
+            ACL_CHECK(aclDestroyTensor(src_trans_tensor));
             break;
         }
-        case GGML_TYPE_Q4_0:
-            aclrtlaunch_ascendc_get_row_q4_0(
-                24, ctx.stream(), src0->data, src1->data, dst->data,
-                ((ggml_tensor*)src0->extra)->ne,
-                ((ggml_tensor*)src1->extra)->ne,
-                ((ggml_tensor*)src1->extra)->nb, ((ggml_tensor*)dst->extra)->ne,
-                ((ggml_tensor*)dst->extra)->nb);
-            break;
-        case GGML_TYPE_Q8_0:
-            aclrtlaunch_ascendc_get_row_q8_0(
-                24, ctx.stream(), src0->data, src1->data, dst->data,
-                ((ggml_tensor*)src0->extra)->ne,
-                ((ggml_tensor*)src1->extra)->ne,
-                ((ggml_tensor*)src1->extra)->nb, ((ggml_tensor*)dst->extra)->ne,
-                ((ggml_tensor*)dst->extra)->nb);
+        case GGML_TYPE_Q8_0: {
+            // add 1 dim for bcast mul.
+            size_t weight_nb[GGML_MAX_DIMS + 1], scale_nb[GGML_MAX_DIMS + 1],
+                dequant_nb[GGML_MAX_DIMS + 1];
+            int64_t weight_ne[GGML_MAX_DIMS + 1], scale_ne[GGML_MAX_DIMS + 1],
+                *dequant_ne;
+            int64_t scale_offset = 0;
+
+            // [3,4,5,64] -> [3,4,5,2,32]
+            weight_ne[0] = QK8_0;
+            weight_ne[1] = src0->ne[0] / QK8_0;
+            weight_nb[0] = sizeof(int8_t);
+            weight_nb[1] = weight_nb[0] * weight_ne[0];
+            for (int i = 2; i < GGML_MAX_DIMS + 1; i++) {
+                weight_ne[i] = src0->ne[i - 1];
+                weight_nb[i] = weight_nb[i - 1] * weight_ne[i - 1];
+            }
+
+            // [3,4,5,64] -> [3,4,5,2,1]
+            scale_ne[0] = 1;
+            scale_ne[1] = src0->ne[0] / QK8_0;
+            scale_nb[0] = sizeof(uint16_t);
+            scale_nb[1] = scale_nb[0] * scale_ne[0];
+            for (int i = 2; i < GGML_MAX_DIMS + 1; i++) {
+                scale_ne[i] = src0->ne[i - 1];
+                scale_nb[i] = scale_nb[i - 1] * scale_ne[i - 1];
+            }
+
+            // [3,4,5,64] -> [3,4,5,2,32]
+            dequant_ne = weight_ne;
+            dequant_nb[0] = sizeof(float_t);
+            for (int i = 1; i < GGML_MAX_DIMS + 1; i++) {
+                dequant_nb[i] = dequant_nb[i - 1] * dequant_ne[i - 1];
+            }
+
+            scale_offset = ggml_nelements(src0) * sizeof(int8_t);
+            ggml_cann_pool_alloc dequant_buffer_allocator(
+                ctx.pool(), ggml_nelements(src0) * sizeof(float_t));
+
+            aclTensor* acl_weight_tensor = ggml_cann_create_tensor(
+                src0->data, ACL_INT8, sizeof(int8_t), weight_ne, weight_nb,
+                GGML_MAX_DIMS + 1);
+            aclTensor* acl_scale_tensor = ggml_cann_create_tensor(
+                src0->data, ACL_FLOAT16, sizeof(float16_t), scale_ne, scale_nb,
+                GGML_MAX_DIMS + 1, ACL_FORMAT_ND, scale_offset);
+            aclTensor* dequant_tensor = ggml_cann_create_tensor(
+                dequant_buffer_allocator.get(), ACL_FLOAT, sizeof(float_t),
+                dequant_ne, dequant_nb, GGML_MAX_DIMS + 1);
+
+            aclnn_mul(ctx, acl_weight_tensor, acl_scale_tensor, dequant_tensor);
+            dequant_nb[0] = sizeof(float_t);
+            dequant_ne = src0->ne;
+            for (int i = 1; i < GGML_MAX_DIMS; i++) {
+                dequant_nb[i] = dequant_nb[i - 1] * src0->ne[i - 1];
+            }
+
+            aclnn_embedding_4d(ctx, dequant_buffer_allocator.get(),
+                                   dequant_ne, dequant_nb, src1, dst);
+
+            ACL_CHECK(aclDestroyTensor(dequant_tensor));
             break;
+        }
         default:
-            GGML_ABORT("fatal error");
+            GGML_ABORT("Unsupported tensor type for GGML_OP_GET_ROWS");
             break;
     }
 }
@@ -2790,11 +2805,15 @@ static void ggml_cann_mul_mat_quant(ggml_backend_cann_context& ctx,
                 (char*)output_buffer + batch1 * output_stride, ACL_FLOAT16,
                 output_elem_size, output_ne, output_nb, 2, ACL_FORMAT_ND,
                 output_ne_offset);
+            int64_t antiquantGroupSize = 0;
+            if (src0->ne[0] > QK8_0) {
+                antiquantGroupSize = QK8_0;
+            }
 
             ACL_CHECK(aclnnWeightQuantBatchMatmulV2GetWorkspaceSize(
                 acl_input_tensor, acl_weight_tensor, acl_scale_tensor, nullptr,
-                nullptr, nullptr, nullptr, QK8_0, acl_output_tensor,
-                &workspaceSize, &executor));
+                nullptr, nullptr, nullptr, antiquantGroupSize,
+                acl_output_tensor, &workspaceSize, &executor));
             if (workspaceAddr == nullptr) {
                 workspaceAddr = workspace_allocator.alloc(workspaceSize);
             }
@@ -2833,7 +2852,7 @@ static void ggml_cann_mul_mat_quant(ggml_backend_cann_context& ctx,
 
                 ACL_CHECK(aclnnWeightQuantBatchMatmulV2GetWorkspaceSize(
                     acl_input_tensor, acl_weight_tensor, acl_scale_tensor,
-                    nullptr, nullptr, nullptr, nullptr, QK8_0,
+                    nullptr, nullptr, nullptr, nullptr, antiquantGroupSize,
                     acl_output_tensor, &workspaceSize, &executor));
                 ACL_CHECK(aclnnWeightQuantBatchMatmulV2(
                     workspaceAddr, workspaceSize, executor, ctx.stream()));

ggml/src/ggml-cann/ggml-cann.cpp

@@ -1689,11 +1689,6 @@ static bool ggml_backend_cann_supports_op(ggml_backend_dev_t dev,
         case GGML_OP_MUL_MAT: {
             switch (op->src[0]->type) {
                 case GGML_TYPE_Q8_0:
-                    // Current groupsize should not be greater than k-1 in
-                    // aclnnWeightQuantBatchMatmulV2GetWorkspaceSize
-                    if (op->src[0]->ne[0] <= QK8_0) {
-                        return false;
-                    }
                 case GGML_TYPE_F16:
                 case GGML_TYPE_F32:
                 case GGML_TYPE_Q4_0:
@@ -1709,7 +1704,6 @@ static bool ggml_backend_cann_supports_op(ggml_backend_dev_t dev,
             switch (op->src[0]->type) {
                 case GGML_TYPE_F32:
                 case GGML_TYPE_F16:
-                case GGML_TYPE_Q4_0:
                 case GGML_TYPE_Q8_0:
                     return true;
                 default:
@@ -1717,16 +1711,21 @@ static bool ggml_backend_cann_supports_op(ggml_backend_dev_t dev,
             }
         } break;
         case GGML_OP_CPY: {
-            switch (op->type) {
-                case GGML_TYPE_F32:
-                case GGML_TYPE_F16:
-                case GGML_TYPE_Q8_0:
-                case GGML_TYPE_Q4_0:
-                    return true;
-                default:
-                    return false;
+            ggml_tensor *src = op->src[0];
+            if ((op->type != GGML_TYPE_F32 && op->type != GGML_TYPE_F16) ||
+                  (src->type != GGML_TYPE_F32 &&
+                    src->type != GGML_TYPE_F16)) {
+                // only support F32 and F16.
+                return false;
             }
-        }
+
+            if (!ggml_are_same_shape(op, src) && !ggml_is_contiguous(op)) {
+                // unsupport dst is not contiguous.
+                return false;
+            }
+
+            return true;
+        } break;
         case GGML_OP_CONT: {
             // TODO: support GGML_TYPE_BF16
             switch (op->src[0]->type) {
@@ -1767,9 +1766,9 @@ static bool ggml_backend_cann_supports_op(ggml_backend_dev_t dev,
             }
             return true;
         }
+        case GGML_OP_DUP:
         case GGML_OP_IM2COL:
         case GGML_OP_CONCAT:
-        case GGML_OP_DUP:
         case GGML_OP_REPEAT:
         case GGML_OP_NONE:
         case GGML_OP_RESHAPE:

ggml/src/ggml-common.h

@@ -158,6 +158,12 @@ typedef sycl::half2 ggml_half2;
 
 #endif // GGML_COMMON_DECL_CUDA || GGML_COMMON_DECL_HIP
 
+#ifdef _MSC_VER
+#define GGML_EXTENSION
+#else // _MSC_VER
+#define GGML_EXTENSION __extension__
+#endif // _MSC_VER
+
 #define QK4_0 32
 typedef struct {
     ggml_half d;           // delta
@@ -167,7 +173,7 @@ static_assert(sizeof(block_q4_0) == sizeof(ggml_half) + QK4_0 / 2, "wrong q4_0 b
 
 #define QK4_1 32
 typedef struct {
-    union {
+    GGML_EXTENSION union {
         struct {
             ggml_half d; // delta
             ggml_half m; // min
@@ -188,7 +194,7 @@ static_assert(sizeof(block_q5_0) == sizeof(ggml_half) + sizeof(uint32_t) + QK5_0
 
 #define QK5_1 32
 typedef struct {
-    union {
+    GGML_EXTENSION union {
         struct {
             ggml_half d; // delta
             ggml_half m; // min
@@ -209,7 +215,7 @@ static_assert(sizeof(block_q8_0) == sizeof(ggml_half) + QK8_0, "wrong q8_0 block
 
 #define QK8_1 32
 typedef struct {
-    union {
+    GGML_EXTENSION union {
         struct {
             ggml_half d; // delta
             ggml_half s; // d * sum(qs[i])
@@ -250,7 +256,7 @@ static_assert(sizeof(block_tq2_0) == sizeof(ggml_half) + QK_K / 4, "wrong tq2_0
 typedef struct {
     uint8_t scales[QK_K/16]; // scales and mins, quantized with 4 bits
     uint8_t qs[QK_K/4];      // quants
-    union {
+    GGML_EXTENSION union {
         struct {
             ggml_half d;    // super-block scale for quantized scales
             ggml_half dmin; // super-block scale for quantized mins
@@ -277,7 +283,7 @@ static_assert(sizeof(block_q3_K) == sizeof(ggml_half) + QK_K / 4 + QK_K / 8 + 12
 // weight is represented as x = a * q + b
 // Effectively 4.5 bits per weight
 typedef struct {
-    union {
+    GGML_EXTENSION union {
         struct {
             ggml_half d;    // super-block scale for quantized scales
             ggml_half dmin; // super-block scale for quantized mins
@@ -294,7 +300,7 @@ static_assert(sizeof(block_q4_K) == 2*sizeof(ggml_half) + K_SCALE_SIZE + QK_K/2,
 // weight is represented as x = a * q + b
 // Effectively 5.5 bits per weight
 typedef struct {
-    union {
+    GGML_EXTENSION union {
         struct {
             ggml_half d;    // super-block scale for quantized scales
             ggml_half dmin; // super-block scale for quantized mins

ggml/src/ggml-cpu/CMakeLists.txt

@@ -23,6 +23,16 @@ function(ggml_add_cpu_backend_variant_impl tag_name)
         ggml-cpu/amx/mmq.cpp
         ggml-cpu/amx/mmq.h
         ggml-cpu/ggml-cpu-impl.h
+        ggml-cpu/common.h
+        ggml-cpu/binary-ops.h
+        ggml-cpu/binary-ops.cpp
+        ggml-cpu/unary-ops.h
+        ggml-cpu/unary-ops.cpp
+        ggml-cpu/simd-mappings.h
+        ggml-cpu/vec.h
+        ggml-cpu/vec.cpp
+        ggml-cpu/ops.h
+        ggml-cpu/ops.cpp
         )
 
     target_compile_features(${GGML_CPU_NAME} PRIVATE c_std_11 cxx_std_17)
@@ -287,17 +297,31 @@ function(ggml_add_cpu_backend_variant_impl tag_name)
                 endif()
             endif()
         endif()
-    elseif (${CMAKE_SYSTEM_PROCESSOR} MATCHES "ppc64")
+    elseif ("${CMAKE_SYSTEM_PROCESSOR} " STREQUAL "ppc64le " OR "${CMAKE_SYSTEM_PROCESSOR} " STREQUAL "powerpc ")
         message(STATUS "PowerPC detected")
-        execute_process(COMMAND bash -c "grep POWER /proc/cpuinfo | head -n 1" OUTPUT_VARIABLE POWER_M)
-        if (${POWER_M} MATCHES "POWER10")
-            list(APPEND ARCH_FLAGS -mcpu=power10)
-        elseif (${POWER_M} MATCHES "POWER9")
-            list(APPEND ARCH_FLAGS -mcpu=power9)
-        elseif (${CMAKE_SYSTEM_PROCESSOR} MATCHES "ppc64le")
-            list(APPEND ARCH_FLAGS -mcpu=powerpc64le -mtune=native)
+        if (GGML_NATIVE)
+            if (${CMAKE_SYSTEM_PROCESSOR} MATCHES "ppc64")
+                file(READ "/proc/cpuinfo" POWER10_M)
+            elseif (${CMAKE_SYSTEM_PROCESSOR} MATCHES "powerpc")
+                execute_process(COMMAND bash -c "prtconf |grep 'Implementation' | head -n 1" OUTPUT_VARIABLE POWER10_M)
+            endif()
+
+            string(REGEX MATCHALL "POWER *([0-9]+)" MATCHED_STRING "${POWER10_M}")
+            string(REGEX REPLACE "POWER *([0-9]+)" "\\1" EXTRACTED_NUMBER "${MATCHED_STRING}")
+
+            if (EXTRACTED_NUMBER GREATER_EQUAL 10)
+                list(APPEND ARCH_FLAGS -mcpu=power10 -mpowerpc64)
+            elseif (EXTRACTED_NUMBER EQUAL 9)
+                list(APPEND ARCH_FLAGS -mcpu=power9 -mpowerpc64)
+            elseif (${CMAKE_SYSTEM_PROCESSOR} MATCHES "ppc64le")
+                list(APPEND ARCH_FLAGS -mcpu=powerpc64le -mtune=native)
+            else()
+                list(APPEND ARCH_FLAGS -mcpu=native -mtune=native -mpowerpc64)
+            endif()
         else()
-            list(APPEND ARCH_FLAGS -mcpu=powerpc64 -mtune=native)
+            if (GGML_CPU_POWERPC_CPUTYPE)
+                list(APPEND ARCH_FLAGS -mcpu=${GGML_CPU_POWERPC_CPUTYPE})
+            endif()
         endif()
     elseif (${CMAKE_SYSTEM_PROCESSOR} MATCHES "loongarch64")
         message(STATUS "loongarch64 detected")
@@ -312,7 +336,11 @@ function(ggml_add_cpu_backend_variant_impl tag_name)
     elseif (${CMAKE_SYSTEM_PROCESSOR} MATCHES "riscv64")
         message(STATUS "RISC-V detected")
         if (GGML_RVV)
-            list(APPEND ARCH_FLAGS -march=rv64gcv -mabi=lp64d)
+            if (GGML_RV_ZFH)
+                list(APPEND ARCH_FLAGS -march=rv64gcv_zfhmin -DGGML_RV_ZFH -mabi=lp64d)
+            else()
+                list(APPEND ARCH_FLAGS -march=rv64gcv -mabi=lp64d)
+            endif()
         endif()
     elseif (${CMAKE_SYSTEM_PROCESSOR} MATCHES "s390x")
         message(STATUS "s390x detected")
@@ -351,9 +379,9 @@ function(ggml_add_cpu_backend_variant_impl tag_name)
 
         # Fetch KleidiAI sources:
         include(FetchContent)
-        set(KLEIDIAI_COMMIT_TAG "v1.3.0")
+        set(KLEIDIAI_COMMIT_TAG "v1.5.0")
         set(KLEIDIAI_DOWNLOAD_URL "https://github.com/ARM-software/kleidiai/archive/refs/tags/${KLEIDIAI_COMMIT_TAG}.tar.gz")
-        set(KLEIDIAI_ARCHIVE_MD5  "060bd2dc64642b091f461cc8dd7426d9")
+        set(KLEIDIAI_ARCHIVE_MD5  "ea22e1aefb800e9bc8c74d91633cc58e")
 
         if (POLICY CMP0135)
             cmake_policy(SET CMP0135 NEW)

ggml/src/ggml-cpu/binary-ops.cpp

@@ -0,0 +1,158 @@
+#include "binary-ops.h"
+
+#if defined(GGML_USE_ACCELERATE)
+#include <Accelerate/Accelerate.h>
+
+using vDSP_fn_t = void (*)(const float *, vDSP_Stride, const float *, vDSP_Stride, float *, vDSP_Stride, vDSP_Length);
+#endif
+
+static inline float op_add(float a, float b) {
+    return a + b;
+}
+
+static inline float op_sub(float a, float b) {
+    return a - b;
+}
+
+static inline float op_mul(float a, float b) {
+    return a * b;
+}
+
+static inline float op_div(float a, float b) {
+    return a / b;
+}
+
+template <float (*op)(float, float), typename src0_t, typename src1_t, typename dst_t>
+static inline void vec_binary_op_contiguous(const int64_t n, dst_t * z, const src0_t * x, const src1_t * y) {
+    constexpr auto src0_to_f32 = type_conversion_table<src0_t>::to_f32;
+    constexpr auto src1_to_f32 = type_conversion_table<src1_t>::to_f32;
+    constexpr auto f32_to_dst  = type_conversion_table<dst_t >::from_f32;
+
+    for (int i = 0; i < n; i++) {
+        z[i] = f32_to_dst(op(src0_to_f32(x[i]), src1_to_f32(y[i])));
+    }
+}
+
+template <float (*op)(float, float), typename src0_t, typename src1_t, typename dst_t>
+static inline void vec_binary_op_non_contiguous(const int64_t n, const int64_t ne10, const int64_t nb10, dst_t * z, const src0_t * x, const src1_t * y) {
+    constexpr auto src0_to_f32 = type_conversion_table<src0_t>::to_f32;
+    constexpr auto src1_to_f32 = type_conversion_table<src1_t>::to_f32;
+    constexpr auto f32_to_dst  = type_conversion_table<dst_t >::from_f32;
+
+    for (int i = 0; i < n; i++) {
+        int i10 = i % ne10;
+        const src1_t * y_ptr = (const src1_t *)((const char *)y + i10*nb10);
+        z[i] = f32_to_dst(op(src0_to_f32(x[i]), src1_to_f32(*y_ptr)));
+    }
+}
+
+template <float (*op)(float, float), typename src0_t, typename src1_t, typename dst_t>
+static void apply_binary_op(const ggml_compute_params * params, ggml_tensor * dst) {
+    const ggml_tensor * src0 = dst->src[0];
+    const ggml_tensor * src1 = dst->src[1];
+
+    GGML_ASSERT(ggml_can_repeat(src1, src0) && ggml_are_same_shape(src0, dst));
+
+    GGML_TENSOR_BINARY_OP_LOCALS
+
+    GGML_ASSERT( nb0 == sizeof(dst_t));
+    GGML_ASSERT(nb00 == sizeof(src0_t));
+
+    const auto [ir0, ir1] = get_thread_range(params, src0);
+    const bool is_src1_contiguous = (nb10 == sizeof(src1_t));
+
+    if (!is_src1_contiguous) { // broadcast not implemented yet for non-contiguous
+        GGML_ASSERT(ggml_are_same_shape(src0, src1));
+    }
+
+#ifdef GGML_USE_ACCELERATE
+    vDSP_fn_t vDSP_op = nullptr;
+    // TODO - avoid the f32-only check using type 'trait' lookup tables and row-based src-to-float conversion functions
+    if (src0->type == GGML_TYPE_F32 && src1->type == GGML_TYPE_F32 && dst->type == GGML_TYPE_F32) {
+        if (op == op_add) {
+            vDSP_op = vDSP_vadd;
+        } else if (op == op_sub) {
+            vDSP_op = vDSP_vsub;
+        } else if (op == op_mul) {
+            vDSP_op = vDSP_vmul;
+        } else if (op == op_div) {
+            vDSP_op = vDSP_vdiv;
+        }
+    }
+#endif
+
+    for (int64_t ir = ir0; ir < ir1; ++ir) {
+        const int64_t i03 = ir/(ne02*ne01);
+        const int64_t i02 = (ir - i03*ne02*ne01)/ne01;
+        const int64_t i01 = (ir - i03*ne02*ne01 - i02*ne01);
+
+        const int64_t i13 = i03 % ne13;
+        const int64_t i12 = i02 % ne12;
+        const int64_t i11 = i01 % ne11;
+
+        dst_t        * dst_ptr  = (dst_t  *)       ((char *)       dst->data  + i03*nb3  + i02*nb2  + i01*nb1 );
+        const src0_t * src0_ptr = (const src0_t *) ((const char *) src0->data + i03*nb03 + i02*nb02 + i01*nb01);
+        const src1_t * src1_ptr = (const src1_t *) ((const char *) src1->data + i13*nb13 + i12*nb12 + i11*nb11);
+
+        if (is_src1_contiguous) {
+            // src1 is broadcastable across src0 and dst in i1, i2, i3
+            const int64_t nr0 = ne00 / ne10;
+
+            for (int64_t r = 0; r < nr0; ++r) {
+#ifdef GGML_USE_ACCELERATE
+                if constexpr (std::is_same_v<src0_t, float> && std::is_same_v<src1_t, float> && std::is_same_v<dst_t, float>) {
+                    if (vDSP_op != nullptr) {
+                        vDSP_op(src1_ptr, 1, src0_ptr + r*ne10, 1, dst_ptr + r*ne10, 1, ne10);
+                        continue;
+                    }
+                }
+#endif
+                vec_binary_op_contiguous<op>(ne10, dst_ptr + r*ne10, src0_ptr + r*ne10, src1_ptr);
+            }
+        } else {
+            vec_binary_op_non_contiguous<op>(ne0, ne10, nb10, dst_ptr, src0_ptr, src1_ptr);
+        }
+    }
+}
+
+// TODO: Use the 'traits' lookup table (for type conversion fns), instead of a mass of 'if' conditions with long templates
+template <float (*op)(float, float)>
+static void binary_op(const ggml_compute_params * params, ggml_tensor * dst) {
+    const ggml_tensor * src0 = dst->src[0];
+    const ggml_tensor * src1 = dst->src[1];
+
+    /*  */ if (src0->type == GGML_TYPE_F32  && src1->type == GGML_TYPE_F32  && dst->type == GGML_TYPE_F32) { // all f32
+        apply_binary_op<op, float, float, float>(params, dst);
+    } else if (src0->type == GGML_TYPE_F16  && src1->type == GGML_TYPE_F16  && dst->type == GGML_TYPE_F16) { // all f16
+        apply_binary_op<op, ggml_fp16_t, ggml_fp16_t, ggml_fp16_t>(params, dst);
+    } else if (src0->type == GGML_TYPE_BF16 && src1->type == GGML_TYPE_BF16 && dst->type == GGML_TYPE_BF16) { // all bf16
+        apply_binary_op<op, ggml_bf16_t, ggml_bf16_t, ggml_bf16_t>(params, dst);
+    } else if (src0->type == GGML_TYPE_BF16 && src1->type == GGML_TYPE_F32  && dst->type == GGML_TYPE_BF16) {
+        apply_binary_op<op, ggml_bf16_t, float, ggml_bf16_t>(params, dst);
+    } else if (src0->type == GGML_TYPE_BF16 && src1->type == GGML_TYPE_F32  && dst->type == GGML_TYPE_F32) {
+        apply_binary_op<op, ggml_bf16_t, float, float>(params, dst);
+    } else if (src0->type == GGML_TYPE_F16  && src1->type == GGML_TYPE_F32  && dst->type == GGML_TYPE_F16) {
+        apply_binary_op<op, ggml_fp16_t, float, ggml_fp16_t>(params, dst);
+    } else if (src0->type == GGML_TYPE_F16  && src1->type == GGML_TYPE_F32  && dst->type == GGML_TYPE_F32) {
+        apply_binary_op<op, ggml_fp16_t, float, float>(params, dst);
+    } else {
+        GGML_ABORT("%s: unsupported types: dst: %s, src0: %s, src1: %s\n", __func__,
+            ggml_type_name(dst->type), ggml_type_name(src0->type), ggml_type_name(src1->type));
+    }
+}
+
+void ggml_compute_forward_add_non_quantized(const ggml_compute_params * params, ggml_tensor * dst) {
+    binary_op<op_add>(params, dst);
+}
+
+void ggml_compute_forward_sub(const ggml_compute_params * params, ggml_tensor * dst) {
+    binary_op<op_sub>(params, dst);
+}
+
+void ggml_compute_forward_mul(const ggml_compute_params * params, ggml_tensor * dst) {
+    binary_op<op_mul>(params, dst);
+}
+
+void ggml_compute_forward_div(const ggml_compute_params * params, ggml_tensor * dst) {
+    binary_op<op_div>(params, dst);
+}

ggml/src/ggml-cpu/binary-ops.h

@@ -0,0 +1,16 @@
+#pragma once
+
+#include "common.h"
+
+#ifdef __cplusplus
+extern "C" {
+#endif
+
+void ggml_compute_forward_add_non_quantized(const struct ggml_compute_params * params, struct ggml_tensor * dst);
+void ggml_compute_forward_sub(const struct ggml_compute_params * params, struct ggml_tensor * dst);
+void ggml_compute_forward_mul(const struct ggml_compute_params * params, struct ggml_tensor * dst);
+void ggml_compute_forward_div(const struct ggml_compute_params * params, struct ggml_tensor * dst);
+
+#ifdef __cplusplus
+}
+#endif

ggml/src/ggml-cpu/common.h

@@ -0,0 +1,72 @@
+#pragma once
+
+#include "ggml.h"
+#include "ggml-cpu-traits.h"
+#include "ggml-cpu-impl.h"
+#include "ggml-impl.h"
+
+#ifdef __cplusplus
+
+#include <utility>
+
+// convenience functions/macros for use in template calls
+// note: these won't be required after the 'traits' lookup table is used.
+static inline ggml_fp16_t f32_to_f16(float x) {
+    return GGML_FP32_TO_FP16(x);
+}
+
+static inline float f16_to_f32(ggml_fp16_t x) {
+    return GGML_FP16_TO_FP32(x);
+}
+
+static inline ggml_bf16_t f32_to_bf16(float x) {
+    return GGML_FP32_TO_BF16(x);
+}
+
+static inline float bf16_to_f32(ggml_bf16_t x) {
+    return GGML_BF16_TO_FP32(x);
+}
+
+static inline float f32_to_f32(float x) {
+    return x;
+}
+
+// TODO - merge this into the traits table, after using row-based conversions
+template <class T>
+struct type_conversion_table;
+
+template <>
+struct type_conversion_table<ggml_fp16_t> {
+    static constexpr float (*to_f32)(ggml_fp16_t) = f16_to_f32;
+    static constexpr ggml_fp16_t (*from_f32)(float) = f32_to_f16;
+};
+
+template <>
+struct type_conversion_table<float> {
+    static constexpr float (*to_f32)(float) = f32_to_f32;
+    static constexpr float (*from_f32)(float) = f32_to_f32;
+};
+
+template <>
+struct type_conversion_table<ggml_bf16_t> {
+    static constexpr float (*to_f32)(ggml_bf16_t) = bf16_to_f32;
+    static constexpr ggml_bf16_t (*from_f32)(float) = f32_to_bf16;
+};
+
+static std::pair<int64_t, int64_t> get_thread_range(const struct ggml_compute_params * params, const struct ggml_tensor * src0) {
+    const int64_t ith = params->ith;
+    const int64_t nth = params->nth;
+
+    const int64_t nr  = ggml_nrows(src0);
+
+    // rows per thread
+    const int64_t dr = (nr + nth - 1)/nth;
+
+    // row range for this thread
+    const int64_t ir0 = dr*ith;
+    const int64_t ir1 = MIN(ir0 + dr, nr);
+
+    return {ir0, ir1};
+}
+
+#endif

ggml/src/ggml-cpu/kleidiai/kernels.cpp

@@ -51,11 +51,10 @@ static ggml_kleidiai_kernels gemm_gemv_kernels[] = {
             /* .run_kernel            = */ kai_run_matmul_clamp_f32_qsi8d32p1x4_qsi4c32p4vlx4_1x4vl_sme2_sdot,
         },
         /* .lhs_info = */ {
-            /* .get_offset            = */ kai_get_lhs_offset_lhs_quant_pack_qsi8d32p_f32,
-            /* .get_packed_offset     = */ kai_get_lhs_packed_offset_lhs_quant_pack_qsi8d32p_f32,
+            /* .get_offset            = */ kai_get_lhs_offset_lhs_quant_pack_qsi8d32p_f32_neon,
+            /* .get_packed_offset     = */ kai_get_lhs_packed_offset_lhs_quant_pack_qsi8d32p_f32_neon,
             /* .packed_size           = */ kai_get_lhs_packed_size_lhs_quant_pack_qsi8d32p_f32_neon,
             /* .pack_func             = */ kai_run_lhs_quant_pack_qsi8d32p_f32_neon,
-            /* .require_aligned_m_idx = */ true,
         },
         /* .rhs_info = */ {
             /* .packed_size = */ kai_get_rhs_packed_size_rhs_pack_nxk_qsi4c32ps1s0scalef16_qsu4c32s16s0_neon,
@@ -100,7 +99,6 @@ static ggml_kleidiai_kernels gemm_gemv_kernels[] = {
             /* .get_packed_offset     = */ kai_get_lhs_packed_offset_lhs_quant_pack_qsi8d32p_f32,
             /* .packed_size           = */ kai_get_lhs_packed_size_lhs_quant_pack_qsi8d32p_f32,
             /* .pack_func             = */ kai_run_lhs_quant_pack_qsi8d32p_f32,
-            /* .require_aligned_m_idx = */ false,
         },
         /* .rhs_info = */ {
             /* .packed_size = */ kai_get_rhs_packed_size_rhs_pack_nxk_qsi4c32pscalef16_qsu4c32s16s0,
@@ -144,7 +142,6 @@ static ggml_kleidiai_kernels gemm_gemv_kernels[] = {
             /* .get_packed_offset     = */ kai_get_lhs_packed_offset_lhs_quant_pack_qsi8d32p_f32,
             /* .packed_size           = */ kai_get_lhs_packed_size_lhs_quant_pack_qsi8d32p_f32,
             /* .pack_func             = */ kai_run_lhs_quant_pack_qsi8d32p_f32,
-            /* .require_aligned_m_idx = */ false,
         },
         /* .rhs_info = */ {
             /* .packed_size = */ kai_get_rhs_packed_size_rhs_pack_nxk_qsi4c32pscalef16_qsu4c32s16s0,
@@ -189,7 +186,6 @@ static ggml_kleidiai_kernels gemm_gemv_kernels[] = {
             /* .get_packed_offset     = */ kai_get_lhs_packed_offset_lhs_quant_pack_qsi8d32p_f32,
             /* .packed_size           = */ kai_get_lhs_packed_size_lhs_quant_pack_qsi8d32p_f32,
             /* .pack_func             = */ kai_run_lhs_quant_pack_qsi8d32p_f32,
-            /* .require_aligned_m_idx = */ false,
         },
         /* .rhs_info = */ {
             /* .packed_size = */ kai_get_rhs_packed_size_rhs_pack_nxk_qsi4c32pscalef16_qsu4c32s16s0,
@@ -233,7 +229,6 @@ static ggml_kleidiai_kernels gemm_gemv_kernels[] = {
             /* .get_packed_offset     = */ kai_get_lhs_packed_offset_lhs_quant_pack_qsi8d32p_f32,
             /* .packed_size           = */ kai_get_lhs_packed_size_lhs_quant_pack_qsi8d32p_f32,
             /* .pack_func             = */ kai_run_lhs_quant_pack_qsi8d32p_f32,
-            /* .require_aligned_m_idx = */ false,
         },
         /* .rhs_info = */ {
             /* .packed_size = */ kai_get_rhs_packed_size_rhs_pack_nxk_qsi4c32pscalef16_qsu4c32s16s0,

ggml/src/ggml-cpu/kleidiai/kernels.h

@@ -40,7 +40,6 @@ struct lhs_packing_info {
     size_t (*packed_size)(size_t m, size_t k, size_t bl, size_t mr, size_t kr, size_t sr);
     void (*pack_func)(size_t m, size_t k, size_t bl, size_t mr, size_t kr, size_t sr, size_t m_idx_start, const float* lhs,
                       size_t lhs_stride, void* lhs_packed);
-    bool require_aligned_m_idx;
 };
 
 struct rhs_packing_info {

ggml/src/ggml-cpu/kleidiai/kleidiai.cpp

@@ -124,8 +124,7 @@ class tensor_traits : public ggml::cpu::tensor_traits {
             size_t sr = kernel->get_sr();
 
             // Calculate number of columns to be processed per thread
-            const bool use_multithread = lhs_info->require_aligned_m_idx && m <= mr ? false : true;
-            const size_t num_m_per_thread = use_multithread ? kai_roundup(m, nth) / nth : m;
+            const size_t num_m_per_thread = kai_roundup(m, mr * nth) / nth;
             const size_t m_start = ith * num_m_per_thread;
             size_t m_to_process = num_m_per_thread;
             if ((m_start + m_to_process) > m) {
@@ -135,11 +134,11 @@ class tensor_traits : public ggml::cpu::tensor_traits {
             if(m_start < m) {
                 // Transform LHS
                 const size_t src_stride        = src1->nb[1];
-                const float * src_ptr          = reinterpret_cast<const float *>(lhs + lhs_info->get_offset(0, dst->src[1]->nb[1]));
+                const float * src_ptr          = reinterpret_cast<const float *>(lhs + lhs_info->get_offset(m_start, dst->src[1]->nb[1]));
                 const size_t lhs_packed_offset = lhs_info->get_packed_offset(m_start, k, QK4_0, mr, kr, sr);
                 void * lhs_packed_ptr          = static_cast<void *>(lhs_packed + lhs_packed_offset);
 
-                lhs_info->pack_func(m_to_process, k, QK4_0, mr, kr, sr, m_start, src_ptr, src_stride, lhs_packed_ptr);
+                lhs_info->pack_func(m_to_process, k, QK4_0, mr, kr, sr, 0, src_ptr, src_stride, lhs_packed_ptr);
             }
 
             ggml_barrier(params->threadpool);

ggml/src/ggml-cpu/llamafile/sgemm.cpp

@@ -55,6 +55,7 @@
 
 #include <atomic>
 #include <array>
+#include <type_traits>
 
 #ifdef _MSC_VER
 #define NOINLINE __declspec(noinline)
@@ -1092,13 +1093,403 @@ class tinyBLAS_Q0_PPC {
        }
     }
 
-    template<typename VA, typename VB>
-    void packNormal(const TA* a, int64_t lda, int rows, int cols, VA* vec, bool flip) {
+    template<typename VA, typename VB, int size>
+    void packNormalInt4(const TA* a, int64_t lda, int rows, int cols, VA* vec, std::array<int, size>& comparray) {
         int64_t i, j;
         TA *aoffset = NULL;
         VA *vecOffset = NULL;
         TA *aoffset1 = NULL, *aoffset2 = NULL, *aoffset3 = NULL, *aoffset4 = NULL;
         TA *aoffset5 = NULL, *aoffset6 = NULL, *aoffset7 = NULL, *aoffset8 = NULL;
+        VB c1[2] = {0}, c2[2] = {0}, c3[2] = {0}, c4[2] = {0};
+        VB c5[2] = {0}, c6[2] = {0}, c7[2] = {0}, c8[2] = {0};
+        VB t1, t2, t3, t4, t5, t6, t7, t8;
+        const vector signed char lowMask = vec_splats((signed char)0xF);
+        const vector unsigned char v4 = vec_splats((unsigned char)0x4);
+        const vector signed char v8 = vec_splats((signed char)0x8);
+        aoffset = const_cast<TA*>(a);
+        vecOffset = vec;
+        vector unsigned char swiz1 = {0, 1, 2, 3, 4, 5, 6, 7, 16, 17, 18, 19, 20, 21, 22, 23};
+        vector unsigned char swiz2 = {8, 9, 10, 11, 12, 13, 14, 15, 24, 25, 26, 27, 28, 29, 30, 31};
+        vector unsigned char swiz3 = {0, 1, 2, 3, 8, 9, 10, 11, 16, 17, 18, 19, 24, 25, 26, 27};
+        vector unsigned char swiz4 = {4, 5, 6, 7, 12, 13, 14, 15, 20, 21, 22, 23, 28, 29, 30, 31};
+        vector signed int vsum = {0};
+        vector signed int vsum2 = {0};
+
+        j = (rows >> 3);
+        if (j > 0) {
+            do {
+                aoffset1 = aoffset;
+                aoffset2 = aoffset1 + lda;
+                aoffset3 = aoffset2 + lda;
+                aoffset4 = aoffset3 + lda;
+                aoffset5 = aoffset4 + lda;
+                aoffset6 = aoffset5 + lda;
+                aoffset7 = aoffset6 + lda;
+                aoffset8 = aoffset7 + lda;
+                aoffset += 8 * lda;
+
+                i = (cols >> 2);
+                if (i > 0) {
+                    do {
+                        c1[1] = reinterpret_cast<VB>(vec_xl(0, aoffset1->qs));
+                        c2[1] = reinterpret_cast<VB>(vec_xl(0, aoffset2->qs));
+                        c3[1] = reinterpret_cast<VB>(vec_xl(0, aoffset3->qs));
+                        c4[1] = reinterpret_cast<VB>(vec_xl(0, aoffset4->qs));
+                        c5[1] = reinterpret_cast<VB>(vec_xl(0, aoffset5->qs));
+                        c6[1] = reinterpret_cast<VB>(vec_xl(0, aoffset6->qs));
+                        c7[1] = reinterpret_cast<VB>(vec_xl(0, aoffset7->qs));
+                        c8[1] = reinterpret_cast<VB>(vec_xl(0, aoffset8->qs));
+
+                        c1[0] = vec_and(c1[1], lowMask);
+                        c1[1] = vec_sr(c1[1], v4);
+                        c1[0] = vec_sub(c1[0], v8);
+                        c1[1] = vec_sub(c1[1], v8);
+                        vsum = vec_sum4s(c1[0], vsum);
+                        vsum2 = vec_sum4s(c1[1], vsum2);
+                        vsum = vec_add(vsum, vsum2);
+                        comparray[0] = vsum[0] + vsum[1] + vsum[2] + vsum[3];
+                        vsum = vec_splats(0);
+                        vsum2 = vec_splats(0);
+
+                        c2[0] = vec_and(c2[1], lowMask);
+                        c2[1] = vec_sr(c2[1], v4);
+                        c2[0] = vec_sub(c2[0], v8);
+                        c2[1] = vec_sub(c2[1], v8);
+                        vsum = vec_sum4s(c2[0], vsum);
+                        vsum2 = vec_sum4s(c2[1], vsum2);
+                        vsum = vec_add(vsum, vsum2);
+                        comparray[1] = vsum[0] + vsum[1] + vsum[2] + vsum[3];
+                        vsum = vec_splats(0);
+                        vsum2 = vec_splats(0);
+
+                        c3[0] = vec_and(c3[1], lowMask);
+                        c3[1] = vec_sr(c3[1], v4);
+                        c3[0] = vec_sub(c3[0], v8);
+                        c3[1] = vec_sub(c3[1], v8);
+                        vsum = vec_sum4s(c3[0], vsum);
+                        vsum2 = vec_sum4s(c3[1], vsum2);
+                        vsum = vec_add(vsum, vsum2);
+                        comparray[2] = vsum[0] + vsum[1] + vsum[2] + vsum[3];
+                        vsum = vec_splats(0);
+                        vsum2 = vec_splats(0);
+
+                        c4[0] = vec_and(c4[1], lowMask);
+                        c4[1] = vec_sr(c4[1], v4);
+                        c4[0] = vec_sub(c4[0], v8);
+                        c4[1] = vec_sub(c4[1], v8);
+                        vsum = vec_sum4s(c4[0], vsum);
+                        vsum2 = vec_sum4s(c4[1], vsum2);
+                        vsum = vec_add(vsum, vsum2);
+                        comparray[3] = vsum[0] + vsum[1] + vsum[2] + vsum[3];
+                        vsum = vec_splats(0);
+                        vsum2 = vec_splats(0);
+
+                        c5[0] = vec_and(c5[1], lowMask);
+                        c5[1] = vec_sr(c5[1], v4);
+                        c5[0] = vec_sub(c5[0], v8);
+                        c5[1] = vec_sub(c5[1], v8);
+                        vsum = vec_sum4s(c5[0], vsum);
+                        vsum2 = vec_sum4s(c5[1], vsum2);
+                        vsum = vec_add(vsum, vsum2);
+                        comparray[4] = vsum[0] + vsum[1] + vsum[2] + vsum[3];
+                        vsum = vec_splats(0);
+                        vsum2 = vec_splats(0);
+
+                        c6[0] = vec_and(c6[1], lowMask);
+                        c6[1] = vec_sr(c6[1], v4);
+                        c6[0] = vec_sub(c6[0], v8);
+                        c6[1] = vec_sub(c6[1], v8);
+                        vsum = vec_sum4s(c6[0], vsum);
+                        vsum2 = vec_sum4s(c6[1], vsum2);
+                        vsum = vec_add(vsum, vsum2);
+                        comparray[5] = vsum[0] + vsum[1] + vsum[2] + vsum[3];
+                        vsum = vec_splats(0);
+                        vsum2 = vec_splats(0);
+
+                        c7[0] = vec_and(c7[1], lowMask);
+                        c7[1] = vec_sr(c7[1], v4);
+                        c7[0] = vec_sub(c7[0], v8);
+                        c7[1] = vec_sub(c7[1], v8);
+                        vsum = vec_sum4s(c7[0], vsum);
+                        vsum2 = vec_sum4s(c7[1], vsum2);
+                        vsum = vec_add(vsum, vsum2);
+                        comparray[6] = vsum[0] + vsum[1] + vsum[2] + vsum[3];
+                        vsum = vec_splats(0);
+                        vsum2 = vec_splats(0);
+
+                        c8[0] = vec_and(c8[1], lowMask);
+                        c8[1] = vec_sr(c8[1], v4);
+                        c8[0] = vec_sub(c8[0], v8);
+                        c8[1] = vec_sub(c8[1], v8);
+                        vsum = vec_sum4s(c8[0], vsum);
+                        vsum2 = vec_sum4s(c8[1], vsum2);
+                        vsum = vec_add(vsum, vsum2);
+                        comparray[7] = vsum[0] + vsum[1] + vsum[2] + vsum[3];
+                        vsum = vec_splats(0);
+                        vsum2 = vec_splats(0);
+
+                        t1 = vec_perm(c1[0], c2[0], swiz1);
+                        t2 = vec_perm(c1[0], c2[0], swiz2);
+                        t3 = vec_perm(c3[0], c4[0], swiz1);
+                        t4 = vec_perm(c3[0], c4[0], swiz2);
+                        t5 = vec_perm(t1, t3, swiz3);
+                        t6 = vec_perm(t1, t3, swiz4);
+                        t7 = vec_perm(t2, t4, swiz3);
+                        t8 = vec_perm(t2, t4, swiz4);
+                        vec_xst(t5, 0, vecOffset);
+                        vec_xst(t6, 0, vecOffset+16);
+                        vec_xst(t7, 0, vecOffset+32);
+                        vec_xst(t8, 0, vecOffset+48);
+
+                        t1 = vec_perm(c1[1], c2[1], swiz1);
+                        t2 = vec_perm(c1[1], c2[1], swiz2);
+                        t3 = vec_perm(c3[1], c4[1], swiz1);
+                        t4 = vec_perm(c3[1], c4[1], swiz2);
+                        t5 = vec_perm(t1, t3, swiz3);
+                        t6 = vec_perm(t1, t3, swiz4);
+                        t7 = vec_perm(t2, t4, swiz3);
+                        t8 = vec_perm(t2, t4, swiz4);
+                        vec_xst(t5, 0, vecOffset+64);
+                        vec_xst(t6, 0, vecOffset+80);
+                        vec_xst(t7, 0, vecOffset+96);
+                        vec_xst(t8, 0, vecOffset+112);
+
+                        t1 = vec_perm(c5[0], c6[0], swiz1);
+                        t2 = vec_perm(c5[0], c6[0], swiz2);
+                        t3 = vec_perm(c7[0], c8[0], swiz1);
+                        t4 = vec_perm(c7[0], c8[0], swiz2);
+                        t5 = vec_perm(t1, t3, swiz3);
+                        t6 = vec_perm(t1, t3, swiz4);
+                        t7 = vec_perm(t2, t4, swiz3);
+                        t8 = vec_perm(t2, t4, swiz4);
+                        vec_xst(t5, 0, vecOffset+128);
+                        vec_xst(t6, 0, vecOffset+144);
+                        vec_xst(t7, 0, vecOffset+160);
+                        vec_xst(t8, 0, vecOffset+176);
+
+                        t1 = vec_perm(c5[1], c6[1], swiz1);
+                        t2 = vec_perm(c5[1], c6[1], swiz2);
+                        t3 = vec_perm(c7[1], c8[1], swiz1);
+                        t4 = vec_perm(c7[1], c8[1], swiz2);
+                        t5 = vec_perm(t1, t3, swiz3);
+                        t6 = vec_perm(t1, t3, swiz4);
+                        t7 = vec_perm(t2, t4, swiz3);
+                        t8 = vec_perm(t2, t4, swiz4);
+                        vec_xst(t5, 0, vecOffset+192);
+                        vec_xst(t6, 0, vecOffset+208);
+                        vec_xst(t7, 0, vecOffset+224);
+                        vec_xst(t8, 0, vecOffset+240);
+
+                        aoffset1 += lda;
+                        aoffset2 += lda;
+                        aoffset3 += lda;
+                        aoffset4 += lda;
+                        aoffset5 += lda;
+                        aoffset6 += lda;
+                        aoffset7 += lda;
+                        aoffset8 += lda;
+                        vecOffset += 256;
+                        i--;
+                    } while (i > 0);
+                }
+                j--;
+            } while (j > 0);
+        }
+
+        if (rows & 4) {
+            aoffset1 = aoffset;
+            aoffset2 = aoffset1 + lda;
+            aoffset3 = aoffset2 + lda;
+            aoffset4 = aoffset3 + lda;
+            aoffset += 4 * lda;
+
+            i = (cols >> 2);
+            if (i > 0) {
+                do {
+                    c1[1] = reinterpret_cast<VB>(vec_xl(0, aoffset1->qs));
+                    c2[1] = reinterpret_cast<VB>(vec_xl(0, aoffset2->qs));
+                    c3[1] = reinterpret_cast<VB>(vec_xl(0, aoffset3->qs));
+                    c4[1] = reinterpret_cast<VB>(vec_xl(0, aoffset4->qs));
+
+                    c1[0] = vec_and(c1[1], lowMask);
+                    c1[1] = vec_sr(c1[1], v4);
+                    c1[0] = vec_sub(c1[0], v8);
+                    c1[1] = vec_sub(c1[1], v8);
+                    vsum = vec_sum4s(c1[0], vsum);
+                    vsum2 = vec_sum4s(c1[1], vsum2);
+                    vsum = vec_add(vsum, vsum2);
+                    comparray[0] = vsum[0] + vsum[1] + vsum[2] + vsum[3];
+                    vsum = vec_splats(0);
+                    vsum2 = vec_splats(0);
+
+                    c2[0] = vec_and(c2[1], lowMask);
+                    c2[1] = vec_sr(c2[1], v4);
+                    c2[0] = vec_sub(c2[0], v8);
+                    c2[1] = vec_sub(c2[1], v8);
+                    vsum = vec_sum4s(c2[0], vsum);
+                    vsum2 = vec_sum4s(c2[1], vsum2);
+                    vsum = vec_add(vsum, vsum2);
+                    comparray[1] = vsum[0] + vsum[1] + vsum[2] + vsum[3];
+                    vsum = vec_splats(0);
+                    vsum2 = vec_splats(0);
+
+                    c3[0] = vec_and(c3[1], lowMask);
+                    c3[1] = vec_sr(c3[1], v4);
+                    c3[0] = vec_sub(c3[0], v8);
+                    c3[1] = vec_sub(c3[1], v8);
+                    vsum = vec_sum4s(c3[0], vsum);
+                    vsum2 = vec_sum4s(c3[1], vsum2);
+                    vsum = vec_add(vsum, vsum2);
+                    comparray[2] = vsum[0] + vsum[1] + vsum[2] + vsum[3];
+                    vsum = vec_splats(0);
+                    vsum2 = vec_splats(0);
+
+                    c4[0] = vec_and(c4[1], lowMask);
+                    c4[1] = vec_sr(c4[1], v4);
+                    c4[0] = vec_sub(c4[0], v8);
+                    c4[1] = vec_sub(c4[1], v8);
+                    vsum = vec_sum4s(c4[0], vsum);
+                    vsum2 = vec_sum4s(c4[1], vsum2);
+                    vsum = vec_add(vsum, vsum2);
+                    comparray[3] = vsum[0] + vsum[1] + vsum[2] + vsum[3];
+                    vsum = vec_splats(0);
+                    vsum2 = vec_splats( 0);
+
+                    t1 = vec_perm(c1[0], c2[0], swiz1);
+                    t2 = vec_perm(c1[0], c2[0], swiz2);
+                    t3 = vec_perm(c3[0], c4[0], swiz1);
+                    t4 = vec_perm(c3[0], c4[0], swiz2);
+                    t5 = vec_perm(t1, t3, swiz3);
+                    t6 = vec_perm(t1, t3, swiz4);
+                    t7 = vec_perm(t2, t4, swiz3);
+                    t8 = vec_perm(t2, t4, swiz4);
+                    vec_xst(t5, 0, vecOffset);
+                    vec_xst(t6, 0, vecOffset+16);
+                    vec_xst(t7, 0, vecOffset+32);
+                    vec_xst(t8, 0, vecOffset+48);
+
+                    t1 = vec_perm(c1[1], c2[1], swiz1);
+                    t2 = vec_perm(c1[1], c2[1], swiz2);
+                    t3 = vec_perm(c3[1], c4[1], swiz1);
+                    t4 = vec_perm(c3[1], c4[1], swiz2);
+                    t5 = vec_perm(t1, t3, swiz3);
+                    t6 = vec_perm(t1, t3, swiz4);
+                    t7 = vec_perm(t2, t4, swiz3);
+                    t8 = vec_perm(t2, t4, swiz4);
+                    vec_xst(t5, 0, vecOffset+64);
+                    vec_xst(t6, 0, vecOffset+80);
+                    vec_xst(t7, 0, vecOffset+96);
+                    vec_xst(t8, 0, vecOffset+112);
+
+                    aoffset1 += lda;
+                    aoffset2 += lda;
+                    aoffset3 += lda;
+                    aoffset4 += lda;
+                    vecOffset += 128;
+                    i--;
+                } while (i > 0);
+            }
+        }
+
+        if (rows & 3) {
+            aoffset1 = aoffset;
+            aoffset2 = aoffset1 + lda;
+            aoffset3 = aoffset2 + lda;
+            i = (cols >> 2);
+            if (i > 0) {
+                do {
+                    switch(rows) {
+                        case 3: c3[1] = reinterpret_cast<VB>(vec_xl(0, aoffset3->qs));
+                        case 2: c2[1] = reinterpret_cast<VB>(vec_xl(0, aoffset2->qs));
+                        case 1: c1[1] = reinterpret_cast<VB>(vec_xl(0, aoffset1->qs));
+                            break;
+                    }
+                    c1[0] = vec_and(c1[1], lowMask);
+                    c1[1] = vec_sr(c1[1], v4);
+                    c1[0] = vec_sub(c1[0], v8);
+                    c1[1] = vec_sub(c1[1], v8);
+                    vsum = vec_sum4s(c1[0], vsum);
+                    vsum2 = vec_sum4s(c1[1], vsum2);
+                    vsum = vec_add(vsum, vsum2);
+                    comparray[0] = vsum[0] + vsum[1] + vsum[2] + vsum[3];
+                    vsum = vec_splats(0);
+                    vsum2 = vec_splats(0);
+
+                    c2[0] = vec_and(c2[1], lowMask);
+                    c2[1] = vec_sr(c2[1], v4);
+                    c2[0] = vec_sub(c2[0], v8);
+                    c2[1] = vec_sub(c2[1], v8);
+                    vsum = vec_sum4s(c2[0], vsum);
+                    vsum2 = vec_sum4s(c2[1], vsum2);
+                    vsum = vec_add(vsum, vsum2);
+                    comparray[1] = vsum[0] + vsum[1] + vsum[2] + vsum[3];
+                    vsum = vec_splats(0);
+                    vsum2 = vec_splats(0);
+
+                    c3[0] = vec_and(c3[1], lowMask);
+                    c3[1] = vec_sr(c3[1], v4);
+                    c3[0] = vec_sub(c3[0], v8);
+                    c3[1] = vec_sub(c3[1], v8);
+                    vsum = vec_sum4s(c3[0], vsum);
+                    vsum2 = vec_sum4s(c3[1], vsum2);
+                    vsum = vec_add(vsum, vsum2);
+                    comparray[2] = vsum[0] + vsum[1] + vsum[2] + vsum[3];
+                    vsum = vec_splats(0);
+                    vsum2 = vec_splats(0);
+
+                    c4[0] = vec_and(c4[1], lowMask);
+                    c4[1] = vec_sr(c4[1], v4);
+                    c4[0] = vec_sub(c4[0], v8);
+                    c4[1] = vec_sub(c4[1], v8);
+                    vsum = vec_sum4s(c4[0], vsum);
+                    vsum2 = vec_sum4s(c4[1], vsum2);
+                    vsum = vec_add(vsum, vsum2);
+                    comparray[3] = vsum[0] + vsum[1] + vsum[2] + vsum[3];
+                    vsum = vec_splats(0);
+                    vsum2 = vec_splats(0);
+
+                    t1 = vec_perm(c1[0], c2[0], swiz1);
+                    t2 = vec_perm(c1[0], c2[0], swiz2);
+                    t3 = vec_perm(c3[0], c4[0], swiz1);
+                    t4 = vec_perm(c3[0], c4[0], swiz2);
+                    t5 = vec_perm(t1, t3, swiz3);
+                    t6 = vec_perm(t1, t3, swiz4);
+                    t7 = vec_perm(t2, t4, swiz3);
+                    t8 = vec_perm(t2, t4, swiz4);
+                    vec_xst(t5, 0, vecOffset);
+                    vec_xst(t6, 0, vecOffset+16);
+                    vec_xst(t7, 0, vecOffset+32);
+                    vec_xst(t8, 0, vecOffset+48);
+
+                    t1 = vec_perm(c1[1], c2[1], swiz1);
+                    t2 = vec_perm(c1[1], c2[1], swiz2);
+                    t3 = vec_perm(c3[1], c4[1], swiz1);
+                    t4 = vec_perm(c3[1], c4[1], swiz2);
+                    t5 = vec_perm(t1, t3, swiz3);
+                    t6 = vec_perm(t1, t3, swiz4);
+                    t7 = vec_perm(t2, t4, swiz3);
+                    t8 = vec_perm(t2, t4, swiz4);
+                    vec_xst(t5, 0, vecOffset+64);
+                    vec_xst(t6, 0, vecOffset+80);
+                    vec_xst(t7, 0, vecOffset+96);
+                    vec_xst(t8, 0, vecOffset+112);
+                    aoffset1 += lda;
+                    aoffset2 += lda;
+                    aoffset3 += lda;
+                    vecOffset += 128;
+                    i--;
+                } while(i > 0);
+            }
+        }
+    }
+
+    template<typename VA, typename VB>
+    void packNormal(const TB* a, int64_t lda, int rows, int cols, VA* vec, bool flip) {
+        int64_t i, j;
+        TB *aoffset = NULL;
+        VA *vecOffset = NULL;
+        TB *aoffset1 = NULL, *aoffset2 = NULL, *aoffset3 = NULL, *aoffset4 = NULL;
+        TB *aoffset5 = NULL, *aoffset6 = NULL, *aoffset7 = NULL, *aoffset8 = NULL;
         __vector_pair C1, C2, C3, C4, C5, C6, C7, C8;
         VB c1[2] = {0}, c2[2] = {0}, c3[2] = {0}, c4[2]={0};
         VB c5[2] = {0}, c6[2] = {0}, c7[2] = {0}, c8[2]={0};
@@ -1111,24 +1502,24 @@ class tinyBLAS_Q0_PPC {
         vector unsigned char swiz3 = {0, 1, 2, 3, 8, 9, 10, 11, 16, 17, 18, 19, 24, 25, 26, 27};
         vector unsigned char swiz4 = {4, 5, 6, 7, 12, 13, 14, 15, 20, 21, 22, 23, 28, 29, 30, 31};
 
-        aoffset = const_cast<TA*>(a);
+        aoffset = const_cast<TB*>(a);
         vecOffset = vec;
         j = (rows >> 3);
         if (j > 0) {
             do {
-            aoffset1 = aoffset;
-            aoffset2 = aoffset1 + lda;
-            aoffset3 = aoffset2 + lda;
-            aoffset4 = aoffset3 + lda;
-            aoffset5 = aoffset4 + lda;
-            aoffset6 = aoffset5 + lda;
-            aoffset7 = aoffset6 + lda;
-            aoffset8 = aoffset7 + lda;
-            aoffset += 8 * lda;
+                aoffset1 = aoffset;
+                aoffset2 = aoffset1 + lda;
+                aoffset3 = aoffset2 + lda;
+                aoffset4 = aoffset3 + lda;
+                aoffset5 = aoffset4 + lda;
+                aoffset6 = aoffset5 + lda;
+                aoffset7 = aoffset6 + lda;
+                aoffset8 = aoffset7 + lda;
+                aoffset += 8 * lda;
 
-            i = (cols >> 3);
-            if (i > 0) {
-               do {
+                i = (cols >> 3);
+                if (i > 0) {
+                do {
                     C1 = __builtin_vsx_lxvp(0, (__vector_pair*)aoffset1->qs);
                     C2 = __builtin_vsx_lxvp(0, (__vector_pair*)aoffset2->qs);
                     C3 = __builtin_vsx_lxvp(0, (__vector_pair*)aoffset3->qs);
@@ -1156,10 +1547,10 @@ class tinyBLAS_Q0_PPC {
                     t7 = vec_perm(t2, t4, swiz3);
                     t8 = vec_perm(t2, t4, swiz4);
                     if (flip == true) {
-                       t5 = vec_xor(t5, xor_vector);
-                       t6 = vec_xor(t6, xor_vector);
-                       t7 = vec_xor(t7, xor_vector);
-                       t8 = vec_xor(t8, xor_vector);
+                        t5 = vec_xor(t5, xor_vector);
+                        t6 = vec_xor(t6, xor_vector);
+                        t7 = vec_xor(t7, xor_vector);
+                        t8 = vec_xor(t8, xor_vector);
                     }
                     vec_xst(t5, 0, vecOffset);
                     vec_xst(t6, 0, vecOffset+16);
@@ -1175,10 +1566,10 @@ class tinyBLAS_Q0_PPC {
                     t7 = vec_perm(t2, t4, swiz3);
                     t8 = vec_perm(t2, t4, swiz4);
                     if (flip == true) {
-                       t5 = vec_xor(t5, xor_vector);
-                       t6 = vec_xor(t6, xor_vector);
-                       t7 = vec_xor(t7, xor_vector);
-                       t8 = vec_xor(t8, xor_vector);
+                        t5 = vec_xor(t5, xor_vector);
+                        t6 = vec_xor(t6, xor_vector);
+                        t7 = vec_xor(t7, xor_vector);
+                        t8 = vec_xor(t8, xor_vector);
                     }
                     vec_xst(t5, 0, vecOffset+64);
                     vec_xst(t6, 0, vecOffset+80);
@@ -1194,10 +1585,10 @@ class tinyBLAS_Q0_PPC {
                     t7 = vec_perm(t2, t4, swiz3);
                     t8 = vec_perm(t2, t4, swiz4);
                     if (flip == true) {
-                       t5 = vec_xor(t5, xor_vector);
-                       t6 = vec_xor(t6, xor_vector);
-                       t7 = vec_xor(t7, xor_vector);
-                       t8 = vec_xor(t8, xor_vector);
+                        t5 = vec_xor(t5, xor_vector);
+                        t6 = vec_xor(t6, xor_vector);
+                        t7 = vec_xor(t7, xor_vector);
+                        t8 = vec_xor(t8, xor_vector);
                     }
                     vec_xst(t5, 0, vecOffset+128);
                     vec_xst(t6, 0, vecOffset+144);
@@ -1213,10 +1604,10 @@ class tinyBLAS_Q0_PPC {
                     t7 = vec_perm(t2, t4, swiz3);
                     t8 = vec_perm(t2, t4, swiz4);
                     if (flip == true) {
-                       t5 = vec_xor(t5, xor_vector);
-                       t6 = vec_xor(t6, xor_vector);
-                       t7 = vec_xor(t7, xor_vector);
-                       t8 = vec_xor(t8, xor_vector);
+                        t5 = vec_xor(t5, xor_vector);
+                        t6 = vec_xor(t6, xor_vector);
+                        t7 = vec_xor(t7, xor_vector);
+                        t8 = vec_xor(t8, xor_vector);
                     }
                     vec_xst(t5, 0, vecOffset+192);
                     vec_xst(t6, 0, vecOffset+208);
@@ -1240,11 +1631,11 @@ class tinyBLAS_Q0_PPC {
     }
 
     if (rows & 4) {
-            aoffset1 = aoffset;
-            aoffset2 = aoffset1 + lda;
-            aoffset3 = aoffset2 + lda;
-            aoffset4 = aoffset3 + lda;
-            aoffset += 4 * lda;
+        aoffset1 = aoffset;
+        aoffset2 = aoffset1 + lda;
+        aoffset3 = aoffset2 + lda;
+        aoffset4 = aoffset3 + lda;
+        aoffset += 4 * lda;
 
         i = (cols >> 3);
             if (i > 0) {
@@ -1311,7 +1702,7 @@ class tinyBLAS_Q0_PPC {
             aoffset2 = aoffset1 + lda;
             aoffset3 = aoffset2 + lda;
             i = (cols >> 3);
-        if (i > 0) {
+            if (i > 0) {
                 do {
                     switch(rows) {
                         case 3: C3 = __builtin_vsx_lxvp(0, (__vector_pair*)aoffset3->qs);
@@ -1527,13 +1918,18 @@ class tinyBLAS_Q0_PPC {
     void KERNEL_4x8(int64_t ii, int64_t jj) {
         vec_t vec_A[8], vec_B[16] = {0};
         acc_t acc_0, acc_1;
-        std::array<int, 4> comparray;
+        std::array<int, 4> comparray {};
         vector float fin_res[8] = {0};
         vector float vs[8] = {0};
+        bool isAblock_q4 = std::is_same_v<TA, block_q4_0>;
         for (int l = 0; l < k; l++) {
             __builtin_mma_xxsetaccz(&acc_0);
             __builtin_mma_xxsetaccz(&acc_1);
-            packNormal<int8_t, vector signed char>((A+(ii*lda)+l), lda, 4, 8, (int8_t*)vec_A, false);
+            if (std::is_same_v<TA, block_q4_0>) {
+               packNormalInt4<int8_t, vector signed char, 4>((A+(ii*lda)+l), lda, 4, 4, (int8_t*)vec_A, comparray);
+            } else {
+               packNormal<int8_t, vector signed char>((const TB*)(A+(ii*lda)+l), lda, 4, 8, (int8_t*)vec_A, false);
+            }
             packNormal<uint8_t, vector unsigned char>((B+(jj*ldb)+l), ldb, 8, 8, (uint8_t*)vec_B, true);
             for(int x = 0; x < 8; x++) {
                 __builtin_mma_xvi8ger4pp(&acc_0, vec_A[x], vec_B[x]);
@@ -1545,15 +1941,17 @@ class tinyBLAS_Q0_PPC {
                     *((float*)&vs[I+4]+J) = (unhalf((A+((ii+I)*lda)+l)->d) * unhalf((B+((jj+J+4)*ldb)+l)->d));
                 }
             }
-            auto aoffset = A+(ii*lda)+l;
-            for (int i = 0; i < 4; i++) {
-                comparray[i] = 0;
-                int ca = 0;
-                const int8_t *at = aoffset->qs;
-                for (int j = 0; j < 32; j++)
-                    ca += (int)*at++;
-                comparray[i] = ca;
-                aoffset += lda;
+            if (!isAblock_q4) {
+                auto aoffset = A+(ii*lda)+l;
+                for (int i = 0; i < 4; i++) {
+                    comparray[i] = 0;
+                    int ca = 0;
+                    auto *at = aoffset->qs;
+                    for (int j = 0; j < 32; j++)
+                        ca += (int)*at++;
+                    comparray[i] = ca;
+                    aoffset += lda;
+                }
             }
             compute<4>(&acc_0, 0, 0, comparray, vs, fin_res);
             compute<4>(&acc_1, 0, 4, comparray, vs, fin_res);
@@ -1565,13 +1963,18 @@ class tinyBLAS_Q0_PPC {
     void KERNEL_8x4(int64_t ii, int64_t jj) {
         vec_t vec_A[16], vec_B[8] = {0};
         acc_t acc_0, acc_1;
-        std::array<int, 8> comparray;
+        std::array<int, 8> comparray {};
         vector float fin_res[8] = {0};
         vector float vs[8] = {0};
+        bool isAblock_q4 = std::is_same_v<TA, block_q4_0>;
         for (int l = 0; l < k; l++) {
             __builtin_mma_xxsetaccz(&acc_0);
             __builtin_mma_xxsetaccz(&acc_1);
-            packNormal<int8_t, vector signed char>((A+(ii*lda)+l), lda, 8, 8, (int8_t*)vec_A, false);
+            if (std::is_same_v<TA, block_q4_0>) {
+               packNormalInt4<int8_t, vector signed char, 8>((A+(ii*lda)+l), lda, 8, 4, (int8_t*)vec_A, comparray);
+            } else {
+               packNormal<int8_t, vector signed char>((const TB*)(A+(ii*lda)+l), lda, 8, 8, (int8_t*)vec_A, false);
+            }
             packNormal<uint8_t, vector unsigned char>((B+(jj*ldb)+l), ldb, 4, 8, (uint8_t*)vec_B, true);
             for(int x = 0; x < 8; x++) {
                 __builtin_mma_xvi8ger4pp(&acc_0, vec_A[x], vec_B[x]);
@@ -1582,15 +1985,17 @@ class tinyBLAS_Q0_PPC {
                     *((float*)&vs[I]+J) = (unhalf((A+((ii+I)*lda)+l)->d) * unhalf((B+((jj+J)*ldb)+l)->d));
                 }
             }
-            auto aoffset = A+(ii*lda)+l;
-            for (int i = 0; i < 8; i++) {
-                comparray[i] = 0;
-                int ca = 0;
-                const int8_t *at = aoffset->qs;
-                for (int j = 0; j < 32; j++)
-                    ca += (int)*at++;
-                comparray[i] = ca;
-                aoffset += lda;
+            if (!isAblock_q4) {
+                auto aoffset = A+(ii*lda)+l;
+                for (int i = 0; i < 8; i++) {
+                    comparray[i] = 0;
+                    int ca = 0;
+                    auto *at = aoffset->qs;
+                    for (int j = 0; j < 32; j++)
+                        ca += (int)*at++;
+                    comparray[i] = ca;
+                    aoffset += lda;
+                }
             }
             compute<8>(&acc_0, 0, 0, comparray, vs, fin_res);
             compute<8>(&acc_1, 4, 4, comparray, vs, fin_res);
@@ -1602,15 +2007,20 @@ class tinyBLAS_Q0_PPC {
     void KERNEL_8x8(int64_t ii, int64_t jj) {
         vec_t vec_A[16], vec_B[16] = {0};
         acc_t acc_0, acc_1, acc_2, acc_3;
-        std::array<int, 8> comparray;
+        std::array<int, 8> comparray {};
         vector float fin_res[16] = {0};
         vector float vs[16] = {0};
+        bool isAblock_q4 = std::is_same_v<TA, block_q4_0>;
         for (int l = 0; l < k; l++) {
             __builtin_mma_xxsetaccz(&acc_0);
             __builtin_mma_xxsetaccz(&acc_1);
             __builtin_mma_xxsetaccz(&acc_2);
             __builtin_mma_xxsetaccz(&acc_3);
-            packNormal<int8_t, vector signed char>((A+(ii*lda)+l), lda, 8, 8, (int8_t*)vec_A, false);
+            if (std::is_same_v<TA, block_q4_0>) {
+               packNormalInt4<int8_t, vector signed char, 8>((A+(ii*lda)+l), lda, 8, 4, (int8_t*)vec_A, comparray);
+            } else {
+               packNormal<int8_t, vector signed char>((const TB*)(A+(ii*lda)+l), lda, 8, 8, (int8_t*)vec_A, false);
+            }
             packNormal<uint8_t, vector unsigned char>((B+(jj*ldb)+l), ldb, 8, 8, (uint8_t*)vec_B, true);
             for(int x = 0; x < 8; x++) {
                 __builtin_mma_xvi8ger4pp(&acc_0, vec_A[x], vec_B[x]);
@@ -1624,15 +2034,17 @@ class tinyBLAS_Q0_PPC {
                     *((float*)&vs[I+8]+J) = (unhalf((A+((ii+I)*lda)+l)->d) * unhalf((B+((jj+J+4)*ldb)+l)->d));
                 }
             }
-            auto aoffset = A+(ii*lda)+l;
-            for (int i = 0; i < 8; i++) {
-                comparray[i] = 0;
-                int ca = 0;
-                const int8_t *at = aoffset->qs;
-                for (int j = 0; j < 32; j++)
-                    ca += (int)*at++;
-                comparray[i] = ca;
-                aoffset += lda;
+            if (!isAblock_q4) {
+                auto aoffset = A+(ii*lda)+l;
+                for (int i = 0; i < 8; i++) {
+                    comparray[i] = 0;
+                    int ca = 0;
+                    auto *at = aoffset->qs;
+                    for (int j = 0; j < 32; j++)
+                        ca += (int)*at++;
+                    comparray[i] = ca;
+                    aoffset += lda;
+                }
             }
             compute<8>(&acc_0, 0, 0, comparray, vs, fin_res);
             compute<8>(&acc_1, 4, 4, comparray, vs, fin_res);
@@ -1653,16 +2065,17 @@ class tinyBLAS_Q0_PPC {
         int64_t duty = (tiles + nth - 1) / nth;
         int64_t start = duty * ith;
         int64_t end = start + duty;
-        vec_t vec_A[8], vec_B[8] = {0};
+        vec_t vec_A[8] = {0}, vec_B[8] = {0};
         vector signed int vec_C[4];
         acc_t acc_0;
+        bool isAblock_q4 = std::is_same_v<TA, block_q4_0>;
 
         if (end > tiles)
             end = tiles;
         for (int64_t job = start; job < end; ++job) {
             int64_t ii = m0 + job / xtiles * RM;
             int64_t jj = n0 + job % xtiles * RN;
-            std::array<int, RM> comparray;
+            std::array<int, 4> comparray{};
             vector float res[4] = {0};
             vector float fin_res[4] = {0};
             vector float vs[4] = {0};
@@ -1673,7 +2086,11 @@ class tinyBLAS_Q0_PPC {
                 __builtin_prefetch((A+(ii*lda)+(l+1))->qs, 0, 1); // prefetch one loop ahead
                 __builtin_prefetch((B+(jj*ldb)+(l+1))->qs, 0, 1); // prefetch one loop ahead
                 __builtin_mma_xxsetaccz(&acc_0);
-                packNormal<int8_t, vector signed char>((A+(ii*lda)+l), lda, RM, 8, (int8_t*)vec_A, false);
+                if (isAblock_q4) {
+                   packNormalInt4<int8_t, vector signed char, 4>((A+(ii*lda)+l), lda, RM, 4, (int8_t*)vec_A, comparray);
+                } else {
+                   packNormal<int8_t, vector signed char>((const TB*)(A+(ii*lda)+l), lda, RM, 8, (int8_t*)vec_A, false);
+                }
                 packNormal<uint8_t, vector unsigned char>((B+(jj*ldb)+l), ldb, RN, 8, (uint8_t*)vec_B, true);
                 for(int x = 0; x < 8; x+=4) {
                     __builtin_mma_xvi8ger4pp(&acc_0, vec_A[x], vec_B[x]);
@@ -1687,17 +2104,18 @@ class tinyBLAS_Q0_PPC {
                     }
                 }
                 __builtin_mma_disassemble_acc(vec_C, &acc_0);
-                auto aoffset = A+(ii*lda)+l;
-                for (int i = 0; i < RM; i++) {
-                    comparray[i] = 0;
-                    int ca = 0;
-                    const int8_t *at = aoffset->qs;
-                    for (int j = 0; j < 32; j++)
-                        ca += (int)*at++;
-                    comparray[i] = ca;
-                    aoffset += lda;
+                if (!isAblock_q4) {
+                    auto aoffset = A+(ii*lda)+l;
+                    for (int i = 0; i < RM; i++) {
+                        comparray[i] = 0;
+                        int ca = 0;
+                        auto *at = aoffset->qs;
+                        for (int j = 0; j < 32; j++)
+                            ca += (int)*at++;
+                        comparray[i] = ca;
+                        aoffset += lda;
+                    }
                 }
-
                 for (int i = 0; i < RM; i++) {
                     CA[i] = vec_splats((float)(((double)comparray[i]) * -128.0));
                     res[i] = vec_add(vec_ctf(vec_C[i], 0), CA[i]);
@@ -2013,6 +2431,7 @@ class tinyBLAS_PPC {
             }
         }
     }
+
     void KERNEL_4x4(int64_t ii, int64_t jj) {
         vec_t vec_A[4], vec_B[4], vec_C[4];
         acc_t acc_0;
@@ -2259,15 +2678,27 @@ class tinyBLAS_PPC {
             vec_t vec_C[4];
             acc_t acc_0;
             __builtin_mma_xxsetaccz(&acc_0);
-            vec_t vec_A[4], vec_B[4];
+            vec_t vec_A[4] {0}, vec_B[4] = {0};
             for (int l=0; l<k; l+=4) {
-                if (RN >= 4 && RM == 1) {
+                /* 'GEMV Forwarding' concept is used in first two conditional loops.
+                 * when one of the matrix has a single row/column, the elements are
+                 * broadcasted, instead of using packing routine to prepack the
+                 * matrix elements.
+                 */
+                if (RM == 1) {
                     TA* a = const_cast<TA*>(A+(ii)*lda+l);
-                    packTranspose<vector float>(B+(jj*ldb)+l, ldb, 4, 4, (TA*)vec_B);
+                    packTranspose<vector float>(B+(jj*ldb)+l, ldb, RN, 4, (TA*)vec_B);
                     vec_A[0] = (vec_t)vec_xl(0,a);
                     vec_A[1] = (vec_t)vec_splats(*((TA*)&vec_A+1));
                     vec_A[2] = (vec_t)vec_splats(*((TA*)&vec_A+2));
                     vec_A[3] = (vec_t)vec_splats(*((TA*)&vec_A+3));
+                } else if (RN == 1) {
+                    packTranspose<vector float>(A+(ii*lda)+l, lda, RM, 4, (TA*)vec_A);
+                    TB* b = const_cast<TB*>(B+(jj)*ldb+l);
+                    vec_B[0] = (vec_t)vec_xl(0,b);
+                    vec_B[1] = (vec_t)vec_splats(*((TB*)&vec_B+1));
+                    vec_B[2] = (vec_t)vec_splats(*((TB*)&vec_B+2));
+                    vec_B[3] = (vec_t)vec_splats(*((TB*)&vec_B+3));
                 } else {
                     packTranspose<vector float>(A+(ii*lda)+l, lda, RM, 4, (TA*)vec_A);
                     packTranspose<vector float>(B+(jj*ldb)+l, ldb, RN, 4, (TA*)vec_B);
@@ -2371,8 +2802,10 @@ bool llamafile_sgemm(const struct ggml_compute_params * params, int64_t m, int64
     assert(params->ith < params->nth);
 
     // only enable sgemm for prompt processing
+#if !defined(__MMA__)
     if (n < 2)
         return false;
+#endif
 
     if (Ctype != GGML_TYPE_F32)
         return false;
@@ -2503,8 +2936,8 @@ bool llamafile_sgemm(const struct ggml_compute_params * params, int64_t m, int64
             params->ith, params->nth};
         tb.matmul(m, n);
         return true;
-
 #elif defined(__MMA__)
+    //TO-DO: Remove this condition once gemv forwarding is enabled.
         if (n < 8 && n != 4)
            return false;
         if (m < 8 && m != 4)
@@ -2516,7 +2949,6 @@ bool llamafile_sgemm(const struct ggml_compute_params * params, int64_t m, int64
             params->ith, params->nth};
         tb.matmul(m, n);
         return true;
-
 #else
         return false;
 #endif
@@ -2541,6 +2973,19 @@ bool llamafile_sgemm(const struct ggml_compute_params * params, int64_t m, int64
             params->ith, params->nth};
         tb.matmul(m, n);
         return true;
+#elif defined(__MMA__)
+    //TO-DO: Remove this condition once gemv forwarding is enabled.
+        if (n < 8 && n != 4)
+           return false;
+        if (m < 8 && m != 4)
+           return false;
+        tinyBLAS_Q0_PPC<block_q4_0, block_q8_0, float> tb{
+            k, (const block_q4_0 *)A, lda,
+            (const block_q8_0 *)B, ldb,
+            (float *)C, ldc,
+            params->ith, params->nth};
+        tb.matmul(m, n);
+        return true;
 #else
         return false;
 #endif

ggml/src/ggml-cpu/ops.h

@@ -0,0 +1,128 @@
+#pragma once
+
+#include "ggml.h"
+
+//
+// cache line
+//
+
+#if defined(__cpp_lib_hardware_interference_size)
+#define CACHE_LINE_SIZE std::hardware_destructive_interference_size
+#else
+#if defined(__POWER9_VECTOR__)
+#define CACHE_LINE_SIZE 128
+#elif defined(__VXE__) || defined(__VXE2__)
+#define CACHE_LINE_SIZE 256
+#else
+#define CACHE_LINE_SIZE 64
+#endif
+#endif
+
+static const size_t CACHE_LINE_SIZE_F32 = CACHE_LINE_SIZE/sizeof(float);
+
+#ifdef __cplusplus
+extern "C" {
+#endif
+
+void ggml_compute_forward_dup(const struct ggml_compute_params * params, struct ggml_tensor * dst);
+void ggml_compute_forward_add(const struct ggml_compute_params * params, struct ggml_tensor * dst);
+void ggml_compute_forward_add1(const struct ggml_compute_params * params, struct ggml_tensor * dst);
+void ggml_compute_forward_acc(const struct ggml_compute_params * params, struct ggml_tensor * dst);
+void ggml_compute_forward_sum(const struct ggml_compute_params * params, struct ggml_tensor * dst);
+void ggml_compute_forward_sum_rows(const struct ggml_compute_params * params, struct ggml_tensor * dst);
+void ggml_compute_forward_mean(const struct ggml_compute_params * params, struct ggml_tensor * dst);
+void ggml_compute_forward_argmax(const struct ggml_compute_params * params, struct ggml_tensor * dst);
+void ggml_compute_forward_count_equal(const struct ggml_compute_params * params, struct ggml_tensor * dst);
+void ggml_compute_forward_repeat(const struct ggml_compute_params * params, struct ggml_tensor * dst);
+void ggml_compute_forward_repeat_back(const struct ggml_compute_params * params, struct ggml_tensor * dst);
+void ggml_compute_forward_concat(const struct ggml_compute_params * params, struct ggml_tensor * dst);
+void ggml_compute_forward_silu_back(const struct ggml_compute_params * params, struct ggml_tensor * dst);
+void ggml_compute_forward_norm(const struct ggml_compute_params * params, struct ggml_tensor * dst);
+void ggml_compute_forward_rms_norm(const struct ggml_compute_params * params, struct ggml_tensor * dst);
+void ggml_compute_forward_rms_norm_back(const struct ggml_compute_params * params, struct ggml_tensor * dst);
+void ggml_compute_forward_group_norm(const struct ggml_compute_params * params, struct ggml_tensor * dst);
+void ggml_compute_forward_l2_norm(const struct ggml_compute_params * params, struct ggml_tensor * dst);
+void ggml_compute_forward_out_prod(const struct ggml_compute_params * params, struct ggml_tensor * dst);
+void ggml_compute_forward_scale(const struct ggml_compute_params * params, struct ggml_tensor * dst);
+void ggml_compute_forward_set(const struct ggml_compute_params * params, struct ggml_tensor * dst);
+void ggml_compute_forward_cpy(const struct ggml_compute_params * params, struct ggml_tensor * dst);
+void ggml_compute_forward_cont(const struct ggml_compute_params * params, struct ggml_tensor * dst);
+void ggml_compute_forward_reshape(const struct ggml_compute_params * params, struct ggml_tensor * dst);
+void ggml_compute_forward_view(const struct ggml_compute_params * params, struct ggml_tensor * dst);
+void ggml_compute_forward_permute(const struct ggml_compute_params * params, struct ggml_tensor * dst);
+void ggml_compute_forward_transpose(const struct ggml_compute_params * params, struct ggml_tensor * dst);
+void ggml_compute_forward_get_rows(const struct ggml_compute_params * params, struct ggml_tensor * dst);
+void ggml_compute_forward_get_rows_back(const struct ggml_compute_params * params, struct ggml_tensor * dst);
+void ggml_compute_forward_diag(const struct ggml_compute_params * params, struct ggml_tensor * dst);
+void ggml_compute_forward_diag_mask_inf(const struct ggml_compute_params * params, struct ggml_tensor * dst);
+void ggml_compute_forward_diag_mask_zero(const struct ggml_compute_params * params, struct ggml_tensor * dst);
+void ggml_compute_forward_soft_max(const struct ggml_compute_params * params, struct ggml_tensor * dst);
+void ggml_compute_forward_soft_max_ext_back(const struct ggml_compute_params * params, struct ggml_tensor * dst);
+void ggml_compute_forward_rope(const struct ggml_compute_params * params, struct ggml_tensor * dst);
+void ggml_compute_forward_rope_back(const struct ggml_compute_params * params, struct ggml_tensor * dst);
+void ggml_compute_forward_clamp(const struct ggml_compute_params * params, struct ggml_tensor * dst);
+void ggml_compute_forward_conv_transpose_1d(const struct ggml_compute_params * params, struct ggml_tensor * dst);
+void ggml_compute_forward_im2col(const struct ggml_compute_params * params, struct ggml_tensor * dst);
+void ggml_compute_forward_im2col_back_f32(const struct ggml_compute_params * params, struct ggml_tensor * dst);
+void ggml_compute_forward_conv_transpose_2d(const struct ggml_compute_params * params, struct ggml_tensor * dst);
+void ggml_compute_forward_pool_1d(const struct ggml_compute_params * params, struct ggml_tensor * dst);
+void ggml_compute_forward_pool_2d(const struct ggml_compute_params * params, struct ggml_tensor * dst);
+void ggml_compute_forward_pool_2d_back(const struct ggml_compute_params * params, struct ggml_tensor * dst);
+void ggml_compute_forward_upscale(const struct ggml_compute_params * params, struct ggml_tensor * dst);
+void ggml_compute_forward_pad(const struct ggml_compute_params * params, struct ggml_tensor * dst);
+void ggml_compute_forward_pad_reflect_1d(const struct ggml_compute_params * params, struct ggml_tensor * dst);
+void ggml_compute_forward_arange(const struct ggml_compute_params * params, struct ggml_tensor * dst);
+void ggml_compute_forward_timestep_embedding(const struct ggml_compute_params * params, struct ggml_tensor * dst);
+void ggml_compute_forward_argsort(const struct ggml_compute_params * params, struct ggml_tensor * dst);
+void ggml_compute_forward_leaky_relu(const struct ggml_compute_params * params, struct ggml_tensor * dst);
+void ggml_compute_forward_flash_attn_ext(
+    const struct ggml_compute_params * params,
+    const struct ggml_tensor * q,
+    const struct ggml_tensor * k,
+    const struct ggml_tensor * v,
+    const struct ggml_tensor * mask,
+    struct ggml_tensor * dst);
+void ggml_compute_forward_flash_attn_back(
+        const struct ggml_compute_params * params,
+        const bool masked,
+        struct ggml_tensor * dst);
+void ggml_compute_forward_ssm_conv(const struct ggml_compute_params * params, struct ggml_tensor * dst);
+void ggml_compute_forward_ssm_scan(const struct ggml_compute_params * params, struct ggml_tensor * dst);
+void ggml_compute_forward_win_part(const struct ggml_compute_params * params, struct ggml_tensor * dst);
+void ggml_compute_forward_win_unpart(const struct ggml_compute_params * params, struct ggml_tensor * dst);
+void ggml_compute_forward_unary(const struct ggml_compute_params * params, struct ggml_tensor * dst);
+void ggml_compute_forward_get_rel_pos(const struct ggml_compute_params * params, struct ggml_tensor * dst);
+void ggml_compute_forward_add_rel_pos(const struct ggml_compute_params * params, struct ggml_tensor * dst);
+void ggml_compute_forward_rwkv_wkv6(const struct ggml_compute_params * params, struct ggml_tensor * dst);
+void ggml_compute_forward_rwkv_wkv7(const struct ggml_compute_params * params, struct ggml_tensor * dst);
+void ggml_compute_forward_gla(const struct ggml_compute_params * params, struct ggml_tensor * dst);
+void ggml_compute_forward_map_unary(
+    const struct ggml_compute_params * params,
+    struct ggml_tensor * dst,
+    const ggml_unary_op_f32_t fun);
+void ggml_compute_forward_map_binary(
+    const struct ggml_compute_params * params,
+    struct ggml_tensor * dst,
+    const ggml_binary_op_f32_t fun);
+void ggml_compute_forward_map_custom1_f32(
+    const struct ggml_compute_params * params,
+    struct ggml_tensor * dst,
+    const ggml_custom1_op_f32_t fun);
+void ggml_compute_forward_map_custom2_f32(
+    const struct ggml_compute_params * params,
+    struct ggml_tensor * dst,
+    const ggml_custom2_op_f32_t fun);
+void ggml_compute_forward_map_custom3_f32(
+    const struct ggml_compute_params * params,
+    struct ggml_tensor * dst,
+    const ggml_custom3_op_f32_t fun);
+void ggml_compute_forward_map_custom1(const struct ggml_compute_params * params, struct ggml_tensor * dst);
+void ggml_compute_forward_map_custom2(const struct ggml_compute_params * params, struct ggml_tensor * dst);
+void ggml_compute_forward_map_custom3(const struct ggml_compute_params * params, struct ggml_tensor * dst);
+void ggml_compute_forward_cross_entropy_loss(const struct ggml_compute_params * params, struct ggml_tensor * dst);
+void ggml_compute_forward_cross_entropy_loss_back(const struct ggml_compute_params * params, struct ggml_tensor * dst);
+void ggml_compute_forward_opt_step_adamw(const struct ggml_compute_params * params, struct ggml_tensor * dst);
+
+#ifdef __cplusplus
+}
+#endif

ggml/src/ggml-cpu/simd-mappings.h

@@ -0,0 +1,884 @@
+#pragma once
+
+#include "ggml-cpu-impl.h"
+
+//
+// simd mappings
+//
+
+// we define a common set of C macros which map to specific intrinsics based on the current architecture
+// we then implement the fundamental computation operations below using only these macros
+// adding support for new architectures requires to define the corresponding SIMD macros
+//
+// GGML_F32_STEP / GGML_F16_STEP
+//   number of elements to process in a single step
+//
+// GGML_F32_EPR / GGML_F16_EPR
+//   number of elements to fit in a single register
+//
+
+#if defined(__ARM_NEON) && defined(__ARM_FEATURE_FMA)
+
+#define GGML_SIMD
+
+// F32 NEON
+
+#define GGML_F32_STEP 16
+#define GGML_F32_EPR  4
+
+#define GGML_F32x4              float32x4_t
+#define GGML_F32x4_ZERO         vdupq_n_f32(0.0f)
+#define GGML_F32x4_SET1(x)      vdupq_n_f32(x)
+#define GGML_F32x4_LOAD         vld1q_f32
+#define GGML_F32x4_STORE        vst1q_f32
+#define GGML_F32x4_FMA(a, b, c) vfmaq_f32(a, b, c)
+#define GGML_F32x4_ADD          vaddq_f32
+#define GGML_F32x4_MUL          vmulq_f32
+#define GGML_F32x4_REDUCE_ONE(x) vaddvq_f32(x)
+#define GGML_F32x4_REDUCE(res, x)                       \
+{                                                       \
+    int offset = GGML_F32_ARR >> 1;                     \
+    for (int i = 0; i < offset; ++i) {                  \
+        (x)[i] = vaddq_f32((x)[i], (x)[offset+i]);      \
+    }                                                   \
+    offset >>= 1;                                       \
+    for (int i = 0; i < offset; ++i) {                  \
+        (x)[i] = vaddq_f32((x)[i], (x)[offset+i]);      \
+    }                                                   \
+    offset >>= 1;                                       \
+    for (int i = 0; i < offset; ++i) {                  \
+        (x)[i] = vaddq_f32((x)[i], (x)[offset+i]);      \
+    }                                                   \
+    (res) = (ggml_float) GGML_F32x4_REDUCE_ONE((x)[0]); \
+}
+
+#define GGML_F32_VEC        GGML_F32x4
+#define GGML_F32_VEC_ZERO   GGML_F32x4_ZERO
+#define GGML_F32_VEC_SET1   GGML_F32x4_SET1
+#define GGML_F32_VEC_LOAD   GGML_F32x4_LOAD
+#define GGML_F32_VEC_STORE  GGML_F32x4_STORE
+#define GGML_F32_VEC_FMA    GGML_F32x4_FMA
+#define GGML_F32_VEC_ADD    GGML_F32x4_ADD
+#define GGML_F32_VEC_MUL    GGML_F32x4_MUL
+#define GGML_F32_VEC_REDUCE GGML_F32x4_REDUCE
+
+// F16 NEON
+
+#if defined(__ARM_FEATURE_FP16_VECTOR_ARITHMETIC)
+    #define GGML_F16_STEP 32
+    #define GGML_F16_EPR  8
+
+    #define GGML_F16x8              float16x8_t
+    #define GGML_F16x8_ZERO         vdupq_n_f16(0.0f)
+    #define GGML_F16x8_SET1(x)      vdupq_n_f16(x)
+    #define GGML_F16x8_LOAD(x)      vld1q_f16((const ggml_fp16_internal_t *)(x))
+    #define GGML_F16x8_STORE        vst1q_f16
+    #define GGML_F16x8_FMA(a, b, c) vfmaq_f16(a, b, c)
+    #define GGML_F16x8_ADD          vaddq_f16
+    #define GGML_F16x8_MUL          vmulq_f16
+    #define GGML_F16x8_REDUCE(res, x)                               \
+    do {                                                            \
+        int offset = GGML_F16_ARR >> 1;                             \
+        for (int i = 0; i < offset; ++i) {                          \
+            (x)[i] = vaddq_f16((x)[i], (x)[offset+i]);              \
+        }                                                           \
+        offset >>= 1;                                               \
+        for (int i = 0; i < offset; ++i) {                          \
+            (x)[i] = vaddq_f16((x)[i], (x)[offset+i]);              \
+        }                                                           \
+        offset >>= 1;                                               \
+        for (int i = 0; i < offset; ++i) {                          \
+            (x)[i] = vaddq_f16((x)[i], (x)[offset+i]);              \
+        }                                                           \
+        const float32x4_t t0 = vcvt_f32_f16(vget_low_f16 ((x)[0])); \
+        const float32x4_t t1 = vcvt_f32_f16(vget_high_f16((x)[0])); \
+        (res) = (ggml_float) vaddvq_f32(vaddq_f32(t0, t1));         \
+    } while (0)
+
+    #define GGML_F16_VEC                GGML_F16x8
+    #define GGML_F16_VEC_ZERO           GGML_F16x8_ZERO
+    #define GGML_F16_VEC_SET1           GGML_F16x8_SET1
+    #define GGML_F16_VEC_LOAD(p, i)     GGML_F16x8_LOAD(p)
+    #define GGML_F16_VEC_STORE(p, r, i) GGML_F16x8_STORE((ggml_fp16_internal_t *)(p), (r)[i])
+    #define GGML_F16_VEC_FMA            GGML_F16x8_FMA
+    #define GGML_F16_VEC_ADD            GGML_F16x8_ADD
+    #define GGML_F16_VEC_MUL            GGML_F16x8_MUL
+    #define GGML_F16_VEC_REDUCE         GGML_F16x8_REDUCE
+#else
+    // if FP16 vector arithmetic is not supported, we use FP32 instead
+    // and take advantage of the vcvt_ functions to convert to/from FP16
+
+    #define GGML_F16_STEP 16
+    #define GGML_F16_EPR  4
+
+    #define GGML_F32Cx4              float32x4_t
+    #define GGML_F32Cx4_ZERO         vdupq_n_f32(0.0f)
+    #define GGML_F32Cx4_SET1(x)      vdupq_n_f32(x)
+    #define GGML_F32Cx4_LOAD(x)      vcvt_f32_f16(vld1_f16((const ggml_fp16_internal_t *)(x)))
+    #define GGML_F32Cx4_STORE(x, y)  vst1_f16(x, vcvt_f16_f32(y))
+    #define GGML_F32Cx4_FMA(a, b, c) vfmaq_f32(a, b, c)
+    #define GGML_F32Cx4_ADD          vaddq_f32
+    #define GGML_F32Cx4_MUL          vmulq_f32
+    #define GGML_F32Cx4_REDUCE       GGML_F32x4_REDUCE
+
+    #define GGML_F16_VEC                GGML_F32Cx4
+    #define GGML_F16_VEC_ZERO           GGML_F32Cx4_ZERO
+    #define GGML_F16_VEC_SET1           GGML_F32Cx4_SET1
+    #define GGML_F16_VEC_LOAD(p, i)     GGML_F32Cx4_LOAD(p)
+    #define GGML_F16_VEC_STORE(p, r, i) GGML_F32Cx4_STORE((ggml_fp16_internal_t *)(p), r[i])
+    #define GGML_F16_VEC_FMA            GGML_F32Cx4_FMA
+    #define GGML_F16_VEC_ADD            GGML_F32Cx4_ADD
+    #define GGML_F16_VEC_MUL            GGML_F32Cx4_MUL
+    #define GGML_F16_VEC_REDUCE         GGML_F32Cx4_REDUCE
+#endif
+
+#elif defined(__AVX512F__)
+
+#define GGML_SIMD
+
+// F32 AVX512
+
+#define GGML_F32_STEP 64
+#define GGML_F32_EPR  16
+
+#define GGML_F32x16         __m512
+#define GGML_F32x16_ZERO    _mm512_setzero_ps()
+#define GGML_F32x16_SET1(x) _mm512_set1_ps(x)
+#define GGML_F32x16_LOAD    _mm512_loadu_ps
+#define GGML_F32x16_STORE   _mm512_storeu_ps
+// _mm512_fmadd_ps is defined in AVX512F so no guard is required
+#define GGML_F32x16_FMA(a, b, c) _mm512_fmadd_ps(b, c, a)
+#define GGML_F32x16_ADD     _mm512_add_ps
+#define GGML_F32x16_MUL     _mm512_mul_ps
+#define GGML_F32x16_REDUCE(res, x)                                    \
+do {                                                                  \
+    int offset = GGML_F32_ARR >> 1;                                   \
+    for (int i = 0; i < offset; ++i) {                                \
+        x[i] = _mm512_add_ps(x[i], x[offset+i]);                      \
+    }                                                                 \
+    offset >>= 1;                                                     \
+    for (int i = 0; i < offset; ++i) {                                \
+        x[i] = _mm512_add_ps(x[i], x[offset+i]);                      \
+    }                                                                 \
+    offset >>= 1;                                                     \
+    for (int i = 0; i < offset; ++i) {                                \
+        x[i] = _mm512_add_ps(x[i], x[offset+i]);                      \
+    }                                                                 \
+    res = (ggml_float) _mm512_reduce_add_ps(x[0]);                    \
+} while (0)
+
+// TODO: is this optimal ?
+
+#define GGML_F32_VEC        GGML_F32x16
+#define GGML_F32_VEC_ZERO   GGML_F32x16_ZERO
+#define GGML_F32_VEC_SET1   GGML_F32x16_SET1
+#define GGML_F32_VEC_LOAD   GGML_F32x16_LOAD
+#define GGML_F32_VEC_STORE  GGML_F32x16_STORE
+#define GGML_F32_VEC_FMA    GGML_F32x16_FMA
+#define GGML_F32_VEC_ADD    GGML_F32x16_ADD
+#define GGML_F32_VEC_MUL    GGML_F32x16_MUL
+#define GGML_F32_VEC_REDUCE GGML_F32x16_REDUCE
+
+// F16 AVX512
+
+// F16 AVX
+
+#define GGML_F16_STEP 64
+#define GGML_F16_EPR  16
+
+// AVX512 has FP16 extension (AVX512_FP16) but I don't have it on my machine so I use FP32 instead
+
+#define GGML_F32Cx16             __m512
+#define GGML_F32Cx16_ZERO        _mm512_setzero_ps()
+#define GGML_F32Cx16_SET1(x)     _mm512_set1_ps(x)
+
+// unlike  _mm256_cvt intrinsics that require F16C, _mm512_cvt is defined in AVX512F
+// so F16C guard isn't required
+#define GGML_F32Cx16_LOAD(x)     _mm512_cvtph_ps(_mm256_loadu_si256((const __m256i *)(x)))
+#define GGML_F32Cx16_STORE(x, y) _mm256_storeu_si256((__m256i *)(x), _mm512_cvtps_ph(y, 0))
+
+#define GGML_F32Cx16_FMA(a, b, c) _mm512_fmadd_ps(b, c, a)
+#define GGML_F32Cx16_ADD         _mm512_add_ps
+#define GGML_F32Cx16_MUL         _mm512_mul_ps
+#define GGML_F32Cx16_REDUCE(res, x)                               \
+do {                                                              \
+    int offset = GGML_F32_ARR >> 1;                               \
+    for (int i = 0; i < offset; ++i) {                            \
+        x[i] = _mm512_add_ps(x[i], x[offset+i]);                  \
+    }                                                             \
+    offset >>= 1;                                                 \
+    for (int i = 0; i < offset; ++i) {                            \
+        x[i] = _mm512_add_ps(x[i], x[offset+i]);                  \
+    }                                                             \
+    offset >>= 1;                                                 \
+    for (int i = 0; i < offset; ++i) {                            \
+        x[i] = _mm512_add_ps(x[i], x[offset+i]);                  \
+    }                                                             \
+    res = (ggml_float) _mm512_reduce_add_ps(x[0]);                \
+} while (0)
+
+#define GGML_F16_VEC                GGML_F32Cx16
+#define GGML_F16_VEC_ZERO           GGML_F32Cx16_ZERO
+#define GGML_F16_VEC_SET1           GGML_F32Cx16_SET1
+#define GGML_F16_VEC_LOAD(p, i)     GGML_F32Cx16_LOAD(p)
+#define GGML_F16_VEC_STORE(p, r, i) GGML_F32Cx16_STORE(p, r[i])
+#define GGML_F16_VEC_FMA            GGML_F32Cx16_FMA
+#define GGML_F16_VEC_ADD            GGML_F32Cx16_ADD
+#define GGML_F16_VEC_MUL            GGML_F32Cx16_MUL
+
+#define GGML_F16_VEC_REDUCE         GGML_F32Cx16_REDUCE
+#elif defined(__AVX__)
+
+#define GGML_SIMD
+
+// F32 AVX
+
+#define GGML_F32_STEP 32
+#define GGML_F32_EPR  8
+
+#define GGML_F32x8         __m256
+#define GGML_F32x8_ZERO    _mm256_setzero_ps()
+#define GGML_F32x8_SET1(x) _mm256_set1_ps(x)
+#define GGML_F32x8_LOAD    _mm256_loadu_ps
+#define GGML_F32x8_STORE   _mm256_storeu_ps
+#if defined(__FMA__)
+    #define GGML_F32x8_FMA(a, b, c) _mm256_fmadd_ps(b, c, a)
+#else
+    #define GGML_F32x8_FMA(a, b, c) _mm256_add_ps(_mm256_mul_ps(b, c), a)
+#endif
+#define GGML_F32x8_ADD     _mm256_add_ps
+#define GGML_F32x8_MUL     _mm256_mul_ps
+#define GGML_F32x8_REDUCE(res, x)                                 \
+do {                                                              \
+    int offset = GGML_F32_ARR >> 1;                               \
+    for (int i = 0; i < offset; ++i) {                            \
+        x[i] = _mm256_add_ps(x[i], x[offset+i]);                  \
+    }                                                             \
+    offset >>= 1;                                                 \
+    for (int i = 0; i < offset; ++i) {                            \
+        x[i] = _mm256_add_ps(x[i], x[offset+i]);                  \
+    }                                                             \
+    offset >>= 1;                                                 \
+    for (int i = 0; i < offset; ++i) {                            \
+        x[i] = _mm256_add_ps(x[i], x[offset+i]);                  \
+    }                                                             \
+    const __m128 t0 = _mm_add_ps(_mm256_castps256_ps128(x[0]),    \
+                                 _mm256_extractf128_ps(x[0], 1)); \
+    const __m128 t1 = _mm_hadd_ps(t0, t0);                        \
+    res = (ggml_float) _mm_cvtss_f32(_mm_hadd_ps(t1, t1));        \
+} while (0)
+// TODO: is this optimal ?
+
+#define GGML_F32_VEC        GGML_F32x8
+#define GGML_F32_VEC_ZERO   GGML_F32x8_ZERO
+#define GGML_F32_VEC_SET1   GGML_F32x8_SET1
+#define GGML_F32_VEC_LOAD   GGML_F32x8_LOAD
+#define GGML_F32_VEC_STORE  GGML_F32x8_STORE
+#define GGML_F32_VEC_FMA    GGML_F32x8_FMA
+#define GGML_F32_VEC_ADD    GGML_F32x8_ADD
+#define GGML_F32_VEC_MUL    GGML_F32x8_MUL
+#define GGML_F32_VEC_REDUCE GGML_F32x8_REDUCE
+
+// F16 AVX
+
+#define GGML_F16_STEP 32
+#define GGML_F16_EPR  8
+
+// F16 arithmetic is not supported by AVX, so we use F32 instead
+
+#define GGML_F32Cx8             __m256
+#define GGML_F32Cx8_ZERO        _mm256_setzero_ps()
+#define GGML_F32Cx8_SET1(x)     _mm256_set1_ps(x)
+
+#if defined(__F16C__)
+// the  _mm256_cvt intrinsics require F16C
+#define GGML_F32Cx8_LOAD(x)     _mm256_cvtph_ps(_mm_loadu_si128((const __m128i *)(x)))
+#define GGML_F32Cx8_STORE(x, y) _mm_storeu_si128((__m128i *)(x), _mm256_cvtps_ph(y, 0))
+#else
+static inline __m256 __avx_f32cx8_load(const ggml_fp16_t * x) {
+    float tmp[8];
+
+    for (int i = 0; i < 8; i++) {
+        tmp[i] = GGML_FP16_TO_FP32(x[i]);
+    }
+
+    return _mm256_loadu_ps(tmp);
+}
+static inline void __avx_f32cx8_store(ggml_fp16_t *x, __m256 y) {
+    float arr[8];
+
+    _mm256_storeu_ps(arr, y);
+
+    for (int i = 0; i < 8; i++)
+        x[i] = GGML_FP32_TO_FP16(arr[i]);
+}
+#define GGML_F32Cx8_LOAD(x)     __avx_f32cx8_load(x)
+#define GGML_F32Cx8_STORE(x, y) __avx_f32cx8_store(x, y)
+#endif
+
+#define GGML_F32Cx8_FMA         GGML_F32x8_FMA
+#define GGML_F32Cx8_ADD         _mm256_add_ps
+#define GGML_F32Cx8_MUL         _mm256_mul_ps
+#define GGML_F32Cx8_REDUCE      GGML_F32x8_REDUCE
+
+#define GGML_F16_VEC                GGML_F32Cx8
+#define GGML_F16_VEC_ZERO           GGML_F32Cx8_ZERO
+#define GGML_F16_VEC_SET1           GGML_F32Cx8_SET1
+#define GGML_F16_VEC_LOAD(p, i)     GGML_F32Cx8_LOAD(p)
+#define GGML_F16_VEC_STORE(p, r, i) GGML_F32Cx8_STORE(p, r[i])
+#define GGML_F16_VEC_FMA            GGML_F32Cx8_FMA
+#define GGML_F16_VEC_ADD            GGML_F32Cx8_ADD
+#define GGML_F16_VEC_MUL            GGML_F32Cx8_MUL
+#define GGML_F16_VEC_REDUCE         GGML_F32Cx8_REDUCE
+
+#elif defined(__POWER9_VECTOR__)
+
+#define GGML_SIMD
+
+// F32 POWER9
+
+#define GGML_F32_STEP 32
+#define GGML_F32_EPR  4
+
+#define GGML_F32x4              vector float
+#define GGML_F32x4_ZERO         0.0f
+#define GGML_F32x4_SET1         vec_splats
+#define GGML_F32x4_LOAD(p)      vec_xl(0, p)
+#define GGML_F32x4_STORE(p, r)  vec_xst(r, 0, p)
+#define GGML_F32x4_FMA(a, b, c) vec_madd(b, c, a)
+#define GGML_F32x4_ADD          vec_add
+#define GGML_F32x4_MUL          vec_mul
+#define GGML_F32x4_REDUCE(res, x)              \
+{                                              \
+    int offset = GGML_F32_ARR >> 1;            \
+    for (int i = 0; i < offset; ++i) {         \
+        x[i] = vec_add(x[i], x[offset+i]);     \
+    }                                          \
+    offset >>= 1;                              \
+    for (int i = 0; i < offset; ++i) {         \
+        x[i] = vec_add(x[i], x[offset+i]);     \
+    }                                          \
+    offset >>= 1;                              \
+    for (int i = 0; i < offset; ++i) {         \
+        x[i] = vec_add(x[i], x[offset+i]);     \
+    }                                          \
+    res = vec_extract(x[0], 0) +               \
+          vec_extract(x[0], 1) +               \
+          vec_extract(x[0], 2) +               \
+          vec_extract(x[0], 3);                \
+}
+
+#define GGML_F32_VEC        GGML_F32x4
+#define GGML_F32_VEC_ZERO   GGML_F32x4_ZERO
+#define GGML_F32_VEC_SET1   GGML_F32x4_SET1
+#define GGML_F32_VEC_LOAD   GGML_F32x4_LOAD
+#define GGML_F32_VEC_STORE  GGML_F32x4_STORE
+#define GGML_F32_VEC_FMA    GGML_F32x4_FMA
+#define GGML_F32_VEC_ADD    GGML_F32x4_ADD
+#define GGML_F32_VEC_MUL    GGML_F32x4_MUL
+#define GGML_F32_VEC_REDUCE GGML_F32x4_REDUCE
+
+// F16 POWER9
+#define GGML_F16_STEP       GGML_F32_STEP
+#define GGML_F16_EPR        GGML_F32_EPR
+#define GGML_F16_VEC        GGML_F32x4
+#define GGML_F16_VEC_ZERO   GGML_F32x4_ZERO
+#define GGML_F16_VEC_SET1   GGML_F32x4_SET1
+#define GGML_F16_VEC_FMA    GGML_F32x4_FMA
+#define GGML_F16_VEC_ADD    GGML_F32x4_ADD
+#define GGML_F16_VEC_MUL    GGML_F32x4_MUL
+#define GGML_F16_VEC_REDUCE GGML_F32x4_REDUCE
+// Use vec_xl, not vec_ld, in case the load address is not aligned.
+#define GGML_F16_VEC_LOAD(p, i) (i & 0x1) ?                   \
+  vec_extract_fp32_from_shorth(vec_xl(0, p - GGML_F16_EPR)) : \
+  vec_extract_fp32_from_shortl(vec_xl(0, p))
+#define GGML_ENDIAN_BYTE(i) ((unsigned char *)&(uint16_t){1})[i]
+#define GGML_F16_VEC_STORE(p, r, i)                             \
+  if (i & 0x1)                                                  \
+    vec_xst(vec_pack_to_short_fp32(r[i - GGML_ENDIAN_BYTE(1)],  \
+                                   r[i - GGML_ENDIAN_BYTE(0)]), \
+            0, p - GGML_F16_EPR)
+
+#elif defined(__wasm_simd128__)
+
+#define GGML_SIMD
+
+// F32 WASM
+
+#define GGML_F32_STEP 16
+#define GGML_F32_EPR  4
+
+#define GGML_F32x4              v128_t
+#define GGML_F32x4_ZERO         wasm_f32x4_splat(0.0f)
+#define GGML_F32x4_SET1(x)      wasm_f32x4_splat(x)
+#define GGML_F32x4_LOAD         wasm_v128_load
+#define GGML_F32x4_STORE        wasm_v128_store
+#define GGML_F32x4_FMA(a, b, c) wasm_f32x4_add(wasm_f32x4_mul(b, c), a)
+#define GGML_F32x4_ADD          wasm_f32x4_add
+#define GGML_F32x4_MUL          wasm_f32x4_mul
+#define GGML_F32x4_REDUCE(res, x)                  \
+{                                                  \
+    int offset = GGML_F32_ARR >> 1;                \
+    for (int i = 0; i < offset; ++i) {             \
+        x[i] = wasm_f32x4_add(x[i], x[offset+i]);  \
+    }                                              \
+    offset >>= 1;                                  \
+    for (int i = 0; i < offset; ++i) {             \
+        x[i] = wasm_f32x4_add(x[i], x[offset+i]);  \
+    }                                              \
+    offset >>= 1;                                  \
+    for (int i = 0; i < offset; ++i) {             \
+        x[i] = wasm_f32x4_add(x[i], x[offset+i]);  \
+    }                                              \
+    res = wasm_f32x4_extract_lane(x[0], 0) +       \
+          wasm_f32x4_extract_lane(x[0], 1) +       \
+          wasm_f32x4_extract_lane(x[0], 2) +       \
+          wasm_f32x4_extract_lane(x[0], 3);        \
+}
+
+#define GGML_F32_VEC        GGML_F32x4
+#define GGML_F32_VEC_ZERO   GGML_F32x4_ZERO
+#define GGML_F32_VEC_SET1   GGML_F32x4_SET1
+#define GGML_F32_VEC_LOAD   GGML_F32x4_LOAD
+#define GGML_F32_VEC_STORE  GGML_F32x4_STORE
+#define GGML_F32_VEC_FMA    GGML_F32x4_FMA
+#define GGML_F32_VEC_ADD    GGML_F32x4_ADD
+#define GGML_F32_VEC_MUL    GGML_F32x4_MUL
+#define GGML_F32_VEC_REDUCE GGML_F32x4_REDUCE
+
+// F16 WASM
+
+#define GGML_F16_STEP 16
+#define GGML_F16_EPR  4
+
+inline static v128_t __wasm_f16x4_load(const ggml_fp16_t * p) {
+    float tmp[4];
+
+    tmp[0] = GGML_FP16_TO_FP32(p[0]);
+    tmp[1] = GGML_FP16_TO_FP32(p[1]);
+    tmp[2] = GGML_FP16_TO_FP32(p[2]);
+    tmp[3] = GGML_FP16_TO_FP32(p[3]);
+
+    return wasm_v128_load(tmp);
+}
+
+inline static void __wasm_f16x4_store(ggml_fp16_t * p, v128_t x) {
+    float tmp[4];
+
+    wasm_v128_store(tmp, x);
+
+    p[0] = GGML_FP32_TO_FP16(tmp[0]);
+    p[1] = GGML_FP32_TO_FP16(tmp[1]);
+    p[2] = GGML_FP32_TO_FP16(tmp[2]);
+    p[3] = GGML_FP32_TO_FP16(tmp[3]);
+}
+
+#define GGML_F16x4             v128_t
+#define GGML_F16x4_ZERO        wasm_f32x4_splat(0.0f)
+#define GGML_F16x4_SET1(x)     wasm_f32x4_splat(x)
+#define GGML_F16x4_LOAD(x)     __wasm_f16x4_load(x)
+#define GGML_F16x4_STORE(x, y) __wasm_f16x4_store(x, y)
+#define GGML_F16x4_FMA         GGML_F32x4_FMA
+#define GGML_F16x4_ADD         wasm_f32x4_add
+#define GGML_F16x4_MUL         wasm_f32x4_mul
+#define GGML_F16x4_REDUCE(res, x)                           \
+{                                                           \
+    int offset = GGML_F16_ARR >> 1;                         \
+    for (int i = 0; i < offset; ++i) {                      \
+        x[i] = wasm_f32x4_add(x[i], x[offset+i]);           \
+    }                                                       \
+    offset >>= 1;                                           \
+    for (int i = 0; i < offset; ++i) {                      \
+        x[i] = wasm_f32x4_add(x[i], x[offset+i]);           \
+    }                                                       \
+    offset >>= 1;                                           \
+    for (int i = 0; i < offset; ++i) {                      \
+        x[i] = wasm_f32x4_add(x[i], x[offset+i]);           \
+    }                                                       \
+    res = (ggml_float) (wasm_f32x4_extract_lane(x[0], 0) +  \
+          wasm_f32x4_extract_lane(x[0], 1) +                \
+          wasm_f32x4_extract_lane(x[0], 2) +                \
+          wasm_f32x4_extract_lane(x[0], 3));                \
+}
+
+#define GGML_F16_VEC                GGML_F16x4
+#define GGML_F16_VEC_ZERO           GGML_F16x4_ZERO
+#define GGML_F16_VEC_SET1           GGML_F16x4_SET1
+#define GGML_F16_VEC_LOAD(p, i)     GGML_F16x4_LOAD(p)
+#define GGML_F16_VEC_STORE(p, r, i) GGML_F16x4_STORE(p, r[i])
+#define GGML_F16_VEC_FMA            GGML_F16x4_FMA
+#define GGML_F16_VEC_ADD            GGML_F16x4_ADD
+#define GGML_F16_VEC_MUL            GGML_F16x4_MUL
+#define GGML_F16_VEC_REDUCE         GGML_F16x4_REDUCE
+
+#elif defined(__SSE3__)
+
+#define GGML_SIMD
+
+// F32 SSE
+
+#define GGML_F32_STEP 32
+#define GGML_F32_EPR  4
+
+#define GGML_F32x4         __m128
+#define GGML_F32x4_ZERO    _mm_setzero_ps()
+#define GGML_F32x4_SET1(x) _mm_set1_ps(x)
+#define GGML_F32x4_LOAD    _mm_loadu_ps
+#define GGML_F32x4_STORE   _mm_storeu_ps
+#if defined(__FMA__)
+    // TODO: Does this work?
+    #define GGML_F32x4_FMA(a, b, c) _mm_fmadd_ps(b, c, a)
+#else
+    #define GGML_F32x4_FMA(a, b, c) _mm_add_ps(_mm_mul_ps(b, c), a)
+#endif
+#define GGML_F32x4_ADD     _mm_add_ps
+#define GGML_F32x4_MUL     _mm_mul_ps
+#define GGML_F32x4_REDUCE(res, x)                                 \
+{                                                                 \
+    int offset = GGML_F32_ARR >> 1;                               \
+    for (int i = 0; i < offset; ++i) {                            \
+        x[i] = _mm_add_ps(x[i], x[offset+i]);                     \
+    }                                                             \
+    offset >>= 1;                                                 \
+    for (int i = 0; i < offset; ++i) {                            \
+        x[i] = _mm_add_ps(x[i], x[offset+i]);                     \
+    }                                                             \
+    offset >>= 1;                                                 \
+    for (int i = 0; i < offset; ++i) {                            \
+        x[i] = _mm_add_ps(x[i], x[offset+i]);                     \
+    }                                                             \
+    const __m128 t0 = _mm_hadd_ps(x[0], x[0]);                    \
+    res = (ggml_float) _mm_cvtss_f32(_mm_hadd_ps(t0, t0));        \
+}
+// TODO: is this optimal ?
+
+#define GGML_F32_VEC        GGML_F32x4
+#define GGML_F32_VEC_ZERO   GGML_F32x4_ZERO
+#define GGML_F32_VEC_SET1   GGML_F32x4_SET1
+#define GGML_F32_VEC_LOAD   GGML_F32x4_LOAD
+#define GGML_F32_VEC_STORE  GGML_F32x4_STORE
+#define GGML_F32_VEC_FMA    GGML_F32x4_FMA
+#define GGML_F32_VEC_ADD    GGML_F32x4_ADD
+#define GGML_F32_VEC_MUL    GGML_F32x4_MUL
+#define GGML_F32_VEC_REDUCE GGML_F32x4_REDUCE
+
+// F16 SSE
+
+#define GGML_F16_STEP 32
+#define GGML_F16_EPR  4
+
+static inline __m128 __sse_f16x4_load(const ggml_fp16_t * x) {
+    float tmp[4];
+
+    tmp[0] = GGML_FP16_TO_FP32(x[0]);
+    tmp[1] = GGML_FP16_TO_FP32(x[1]);
+    tmp[2] = GGML_FP16_TO_FP32(x[2]);
+    tmp[3] = GGML_FP16_TO_FP32(x[3]);
+
+    return _mm_loadu_ps(tmp);
+}
+
+static inline void __sse_f16x4_store(ggml_fp16_t * x, __m128 y) {
+    float arr[4];
+
+    _mm_storeu_ps(arr, y);
+
+    x[0] = GGML_FP32_TO_FP16(arr[0]);
+    x[1] = GGML_FP32_TO_FP16(arr[1]);
+    x[2] = GGML_FP32_TO_FP16(arr[2]);
+    x[3] = GGML_FP32_TO_FP16(arr[3]);
+}
+
+#define GGML_F32Cx4             __m128
+#define GGML_F32Cx4_ZERO        _mm_setzero_ps()
+#define GGML_F32Cx4_SET1(x)     _mm_set1_ps(x)
+#define GGML_F32Cx4_LOAD(x)     __sse_f16x4_load(x)
+#define GGML_F32Cx4_STORE(x, y) __sse_f16x4_store(x, y)
+#define GGML_F32Cx4_FMA         GGML_F32x4_FMA
+#define GGML_F32Cx4_ADD         _mm_add_ps
+#define GGML_F32Cx4_MUL         _mm_mul_ps
+#define GGML_F32Cx4_REDUCE      GGML_F32x4_REDUCE
+
+#define GGML_F16_VEC                 GGML_F32Cx4
+#define GGML_F16_VEC_ZERO            GGML_F32Cx4_ZERO
+#define GGML_F16_VEC_SET1            GGML_F32Cx4_SET1
+#define GGML_F16_VEC_LOAD(p, i)      GGML_F32Cx4_LOAD(p)
+#define GGML_F16_VEC_STORE(p, r, i)  GGML_F32Cx4_STORE(p, r[i])
+#define GGML_F16_VEC_FMA             GGML_F32Cx4_FMA
+#define GGML_F16_VEC_ADD             GGML_F32Cx4_ADD
+#define GGML_F16_VEC_MUL             GGML_F32Cx4_MUL
+#define GGML_F16_VEC_REDUCE          GGML_F32Cx4_REDUCE
+
+#elif defined(__loongarch_asx)
+
+#define GGML_SIMD
+
+// F32 LASX
+#define GGML_F32_STEP 32
+#define GGML_F32_EPR  8
+
+#define GGML_F32x8         __m256
+#define GGML_F32x8_ZERO    (__m256)__lasx_xvldi(0)
+#define GGML_F32x8_SET1(x) (__m256)__lasx_xvreplfr2vr_s((x))
+#define GGML_F32x8_LOAD(x) (__m256)__lasx_xvld((x), 0)
+#define GGML_F32x8_STORE(x,y)   __lasx_xvst((y), (x), 0)
+#define GGML_F32x8_FMA(a, b, c) __lasx_xvfmadd_s(b, c, a)
+#define GGML_F32x8_ADD     __lasx_xvfadd_s
+#define GGML_F32x8_MUL     __lasx_xvfmul_s
+#define GGML_F32x8_REDUCE(res, x)                                 \
+do {                                                              \
+    int offset = GGML_F32_ARR >> 1;                               \
+    for (int i = 0; i < offset; ++i) {                            \
+        x[i] = __lasx_xvfadd_s(x[i], x[offset+i]);                  \
+    }                                                             \
+    offset >>= 1;                                                 \
+    for (int i = 0; i < offset; ++i) {                            \
+        x[i] = __lasx_xvfadd_s(x[i], x[offset+i]);                  \
+    }                                                             \
+    offset >>= 1;                                                 \
+    for (int i = 0; i < offset; ++i) {                            \
+        x[i] = __lasx_xvfadd_s(x[i], x[offset+i]);                  \
+    }                                                             \
+    float *tmp_p = (float *)&x[0]; \
+    res = tmp_p[0] + tmp_p[1] + tmp_p[2] + tmp_p[3] + tmp_p[4] + tmp_p[5] + tmp_p[6] + tmp_p[7];  \
+} while (0)
+// TODO: is this optimal ?
+
+#define GGML_F32_VEC        GGML_F32x8
+#define GGML_F32_VEC_ZERO   GGML_F32x8_ZERO
+#define GGML_F32_VEC_SET1   GGML_F32x8_SET1
+#define GGML_F32_VEC_LOAD   GGML_F32x8_LOAD
+#define GGML_F32_VEC_STORE  GGML_F32x8_STORE
+#define GGML_F32_VEC_FMA    GGML_F32x8_FMA
+#define GGML_F32_VEC_ADD    GGML_F32x8_ADD
+#define GGML_F32_VEC_MUL    GGML_F32x8_MUL
+#define GGML_F32_VEC_REDUCE GGML_F32x8_REDUCE
+
+// F16 LASX
+
+#define GGML_F16_STEP 32
+#define GGML_F16_EPR  8
+
+// F16 arithmetic is not supported by LASX, so we use F32 instead
+
+#define GGML_F32Cx8          __m256
+#define GGML_F32Cx8_ZERO    (__m256)__lasx_xvldi(0)
+#define GGML_F32Cx8_SET1(x) (__m256)__lasx_xvreplgr2vr_w((x))
+
+static inline __m256 __lasx_f32cx8_load(const ggml_fp16_t * x) {
+    __m256i a;
+    memcpy(&a, x, sizeof(ggml_fp16_t) * 8);
+    a = __lasx_xvpermi_d(a, 0 | (1 << 4));
+    return __lasx_xvfcvtl_s_h(a);
+}
+
+static inline void __lasx_f32cx8_store(ggml_fp16_t * x, __m256 y) {
+    __m256i a = __lasx_xvfcvt_h_s(y, y);
+    a = __lasx_xvpermi_d(a, 0 | (2 << 2));
+    memcpy(x, &a, sizeof(ggml_fp16_t) * 8);
+}
+#define GGML_F32Cx8_LOAD(x)     __lasx_f32cx8_load(x)
+#define GGML_F32Cx8_STORE(x, y) __lasx_f32cx8_store(x, y)
+
+#define GGML_F32Cx8_FMA         GGML_F32x8_FMA
+#define GGML_F32Cx8_ADD         __lasx_xvfadd_s
+#define GGML_F32Cx8_MUL         __lasx_xvfmul_s
+#define GGML_F32Cx8_REDUCE      GGML_F32x8_REDUCE
+
+#define GGML_F16_VEC                GGML_F32Cx8
+#define GGML_F16_VEC_ZERO           GGML_F32Cx8_ZERO
+#define GGML_F16_VEC_SET1           GGML_F32Cx8_SET1
+#define GGML_F16_VEC_LOAD(p, i)     GGML_F32Cx8_LOAD(p)
+#define GGML_F16_VEC_STORE(p, r, i) GGML_F32Cx8_STORE(p, r[i])
+#define GGML_F16_VEC_FMA            GGML_F32Cx8_FMA
+#define GGML_F16_VEC_ADD            GGML_F32Cx8_ADD
+#define GGML_F16_VEC_MUL            GGML_F32Cx8_MUL
+#define GGML_F16_VEC_REDUCE         GGML_F32Cx8_REDUCE
+
+#elif defined(__loongarch_sx)
+
+#define GGML_SIMD
+
+// F32 LSX
+
+#define GGML_F32_STEP 32
+#define GGML_F32_EPR  4
+
+#define GGML_F32x4         __m128
+#define GGML_F32x4_ZERO    __lsx_vldi(0)
+#define GGML_F32x4_SET1(x) __lsx_vinsgr2vr_w(__lsx_vldi(0),(x), 0)
+#define GGML_F32x4_LOAD(x) __lsx_vld((x), 0)
+#define GGML_F32x4_STORE((x),(y))   __lsx_vst((y), (x), 0)
+#define GGML_F32x4_FMA(a, b, c) __lsx_vfmadd_s(b, c, a)
+#define GGML_F32x4_ADD     __lsx_vfadd_s
+#define GGML_F32x4_MUL     __lsx_vfmul_s
+#define GGML_F32x4_REDUCE(res, x)                                                     \
+{                                                                                     \
+    int offset = GGML_F32_ARR >> 1;                                                   \
+    for (int i = 0; i < offset; ++i) {                                                \
+        x[i] = __lsx_vfadd_s(x[i], x[offset + i]);                                    \
+    }                                                                                 \
+    offset >>= 1;                                                                     \
+    for (int i = 0; i < offset; ++i) {                                                \
+        x[i] = __lsx_vfadd_s(x[i], x[offset + i]);                                    \
+    }                                                                                 \
+    offset >>= 1;                                                                     \
+    for (int i = 0; i < offset; ++i) {                                                \
+        x[i] = __lsx_vfadd_s(x[i], x[offset + i]);                                    \
+    }                                                                                 \
+    __m128i tmp     = __lsx_vsrli_d((__m128i) x[0], 32);                              \
+    tmp             = (__m128i) __lsx_vfadd_s((__m128) tmp, x[0]);                    \
+    tmp             = __lsx_vpickev_w(__lsx_vldi(0), tmp);                            \
+    const __m128 t0 = __lsx_vshuf4i_w(tmp, 0x88);                                     \
+    tmp             = __lsx_vsrli_d((__m128i) t0, 32);                                \
+    tmp             = (__m128i) __lsx_vfadd_s((__m128) tmp, t0);                      \
+    tmp             = __lsx_vpickev_w(__lsx_vldi(0), tmp);                            \
+    res             = (ggml_float) __lsx_vpickve2gr_w(__lsx_vshuf4i_w(tmp, 0x88), 0); \
+}
+
+#define GGML_F32_VEC        GGML_F32x4
+#define GGML_F32_VEC_ZERO   GGML_F32x4_ZERO
+#define GGML_F32_VEC_SET1   GGML_F32x4_SET1
+#define GGML_F32_VEC_LOAD   GGML_F32x4_LOAD
+#define GGML_F32_VEC_STORE  GGML_F32x4_STORE
+#define GGML_F32_VEC_FMA    GGML_F32x4_FMA
+#define GGML_F32_VEC_ADD    GGML_F32x4_ADD
+#define GGML_F32_VEC_MUL    GGML_F32x4_MUL
+#define GGML_F32_VEC_REDUCE GGML_F32x4_REDUCE
+
+// F16 LSX
+
+#define GGML_F16_STEP 32
+#define GGML_F16_EPR  4
+
+static inline __m128 __lsx_f16x4_load(const ggml_fp16_t * x) {
+    float tmp[4];
+
+    tmp[0] = GGML_FP16_TO_FP32(x[0]);
+    tmp[1] = GGML_FP16_TO_FP32(x[1]);
+    tmp[2] = GGML_FP16_TO_FP32(x[2]);
+    tmp[3] = GGML_FP16_TO_FP32(x[3]);
+
+    return __lsx_vld(tmp, 0);
+}
+
+static inline void __lsx_f16x4_store(ggml_fp16_t * x, __m128 y) {
+    float arr[4];
+
+    __lsx_vst(y, arr, 0);
+
+    x[0] = GGML_FP32_TO_FP16(arr[0]);
+    x[1] = GGML_FP32_TO_FP16(arr[1]);
+    x[2] = GGML_FP32_TO_FP16(arr[2]);
+    x[3] = GGML_FP32_TO_FP16(arr[3]);
+}
+
+#define GGML_F32Cx4             __m128
+#define GGML_F32Cx4_ZERO        __lsx_vldi(0)
+#define GGML_F32Cx4_SET1(x)     __lsx_vinsgr2vr_w(__lsx_vldi(0),(x), 0)
+#define GGML_F32Cx4_LOAD(x)     __lsx_f16x4_load(x)
+#define GGML_F32Cx4_STORE(x, y) __lsx_f16x4_store(x, y)
+#define GGML_F32Cx4_FMA         GGML_F32x4_FMA
+#define GGML_F32Cx4_ADD         __lsx_vfadd_s
+#define GGML_F32Cx4_MUL         __lsx_vfmul_s
+#define GGML_F32Cx4_REDUCE      GGML_F32x4_REDUCE
+
+#define GGML_F16_VEC                 GGML_F32Cx4
+#define GGML_F16_VEC_ZERO            GGML_F32Cx4_ZERO
+#define GGML_F16_VEC_SET1            GGML_F32Cx4_SET1
+#define GGML_F16_VEC_LOAD(p, i)      GGML_F32Cx4_LOAD(p)
+#define GGML_F16_VEC_STORE(p, r, i)  GGML_F32Cx4_STORE(p, r[i])
+#define GGML_F16_VEC_FMA             GGML_F32Cx4_FMA
+#define GGML_F16_VEC_ADD             GGML_F32Cx4_ADD
+#define GGML_F16_VEC_MUL             GGML_F32Cx4_MUL
+#define GGML_F16_VEC_REDUCE          GGML_F32Cx4_REDUCE
+
+#elif defined(__VXE__) || defined(__VXE2__)
+
+#define GGML_SIMD
+
+// F32 s390x
+
+#define GGML_F32_STEP 32
+#define GGML_F32_EPR  4
+
+#define GGML_F32x4              __vector float
+#define GGML_F32x4_ZERO         vec_splats(0.0f)
+#define GGML_F32x4_SET1         vec_splats
+#define GGML_F32x4_LOAD(p)      vec_xl(0, p)
+#define GGML_F32x4_STORE(p, r)  vec_xst(r, 0, p)
+#define GGML_F32x4_FMA(a, b, c) vec_madd(b, c, a)
+#define GGML_F32x4_ADD          vec_add
+#define GGML_F32x4_MUL          vec_mul
+#define GGML_F32x4_REDUCE(res, x)                   \
+{                                                   \
+    int offset = GGML_F32_ARR >> 1;                 \
+    for (int i = 0; i < offset; ++i) {              \
+        x[i] = vec_add(x[i], x[offset + i]);        \
+    }                                               \
+    offset >>= 1;                                   \
+    for (int i = 0; i < offset; ++i) {              \
+        x[i] = vec_add(x[i], x[offset + i]);        \
+    }                                               \
+    offset >>= 1;                                   \
+    for (int i = 0; i < offset; ++i) {              \
+        x[i] = vec_add(x[i], x[offset + i]);        \
+    }                                               \
+    res = vec_extract(x[0], 0) +                    \
+          vec_extract(x[0], 1) +                    \
+          vec_extract(x[0], 2) +                    \
+          vec_extract(x[0], 3);                     \
+}
+
+#define GGML_F32_VEC        GGML_F32x4
+#define GGML_F32_VEC_ZERO   GGML_F32x4_ZERO
+#define GGML_F32_VEC_SET1   GGML_F32x4_SET1
+#define GGML_F32_VEC_LOAD   GGML_F32x4_LOAD
+#define GGML_F32_VEC_STORE  GGML_F32x4_STORE
+#define GGML_F32_VEC_FMA    GGML_F32x4_FMA
+#define GGML_F32_VEC_ADD    GGML_F32x4_ADD
+#define GGML_F32_VEC_MUL    GGML_F32x4_MUL
+#define GGML_F32_VEC_REDUCE GGML_F32x4_REDUCE
+
+// F16 s390x
+#define GGML_F16_STEP GGML_F32_STEP
+#define GGML_F16_EPR  GGML_F32_EPR
+
+static inline __vector float __lzs_f16cx4_load(const ggml_fp16_t * x) {
+    float tmp[4];
+
+    for (int i = 0; i < 4; i++) {
+        tmp[i] = GGML_FP16_TO_FP32(x[i]);
+    }
+
+    return vec_xl(0, tmp);
+}
+
+static inline void __lzs_f16cx4_store(ggml_fp16_t * x, __vector float y) {
+    float arr[4];
+
+    vec_xst(y, 0, arr);
+
+    for (int i = 0; i < 4; i++) {
+        x[i] = GGML_FP32_TO_FP16(arr[i]);
+    }
+}
+
+#define GGML_F16_VEC                GGML_F32x4
+#define GGML_F16_VEC_ZERO           GGML_F32x4_ZERO
+#define GGML_F16_VEC_SET1           GGML_F32x4_SET1
+#define GGML_F16_VEC_LOAD(p, i)     __lzs_f16cx4_load(p)
+#define GGML_F16_VEC_STORE(p, r, i) __lzs_f16cx4_store(p, r[i])
+#define GGML_F16_VEC_FMA            GGML_F32x4_FMA
+#define GGML_F16_VEC_ADD            GGML_F32x4_ADD
+#define GGML_F16_VEC_MUL            GGML_F32x4_MUL
+#define GGML_F16_VEC_REDUCE         GGML_F32x4_REDUCE
+
+#endif
+
+// GGML_F32_ARR / GGML_F16_ARR
+//   number of registers to use per step
+#ifdef GGML_SIMD
+#define GGML_F32_ARR (GGML_F32_STEP/GGML_F32_EPR)
+#define GGML_F16_ARR (GGML_F16_STEP/GGML_F16_EPR)
+#endif

ggml/src/ggml-cpu/unary-ops.cpp

@@ -0,0 +1,186 @@
+#include "unary-ops.h"
+
+static inline float op_abs(float x) {
+    return fabsf(x);
+}
+
+static inline float op_sgn(float x) {
+    return (x > 0.f) ? 1.f : ((x < 0.f) ? -1.f : 0.f);
+}
+
+static inline float op_neg(float x) {
+    return -x;
+}
+
+static inline float op_step(float x) {
+    return (x > 0.f) ? 1.f : 0.f;
+}
+
+static inline float op_tanh(float x) {
+    return tanhf(x);
+}
+
+static inline float op_elu(float x) {
+    return (x > 0.f) ? x : expm1f(x);
+}
+
+static inline float op_relu(float x) {
+    return (x > 0.f) ? x : 0.f;
+}
+
+static inline float op_sigmoid(float x) {
+    return 1.f / (1.f + expf(-x));
+}
+
+static inline float op_hardsigmoid(float x) {
+    return fminf(1.0f, fmaxf(0.0f, (x + 3.0f) / 6.0f));
+}
+
+static inline float op_exp(float x) {
+    return expf(x);
+}
+
+static inline float op_hardswish(float x) {
+    return x * fminf(1.0f, fmaxf(0.0f, (x + 3.0f) / 6.0f));
+}
+
+static inline float op_sqr(float x) {
+    return x * x;
+}
+
+static inline float op_sqrt(float x) {
+    return sqrtf(x);
+}
+
+static inline float op_sin(float x) {
+    return sinf(x);
+}
+
+static inline float op_cos(float x) {
+    return cosf(x);
+}
+
+static inline float op_log(float x) {
+    return logf(x);
+}
+
+template <float (*op)(float), typename src0_t, typename dst_t>
+static inline void vec_unary_op(int64_t n, dst_t * y, const src0_t * x) {
+    constexpr auto src0_to_f32 = type_conversion_table<src0_t>::to_f32;
+    constexpr auto f32_to_dst  = type_conversion_table<dst_t >::from_f32;
+
+    for (int i = 0; i < n; i++) {
+        y[i] = f32_to_dst(op(src0_to_f32(x[i])));
+    }
+}
+
+template <float (*op)(float), typename src0_t, typename dst_t>
+static void apply_unary_op(const ggml_compute_params * params, ggml_tensor * dst) {
+    const ggml_tensor * src0 = dst->src[0];
+
+    GGML_ASSERT(ggml_is_contiguous_1(src0) && ggml_is_contiguous_1(dst) && ggml_are_same_shape(src0, dst));
+
+    GGML_TENSOR_UNARY_OP_LOCALS
+
+    GGML_ASSERT( nb0 == sizeof(dst_t));
+    GGML_ASSERT(nb00 == sizeof(src0_t));
+
+    const auto [ir0, ir1] = get_thread_range(params, src0);
+
+    for (int64_t ir = ir0; ir < ir1; ++ir) {
+        const int64_t i03 = ir/(ne02*ne01);
+        const int64_t i02 = (ir - i03*ne02*ne01)/ne01;
+        const int64_t i01 = (ir - i03*ne02*ne01 - i02*ne01);
+
+        dst_t        * dst_ptr  = (dst_t  *)       ((char *)       dst->data  + i03*nb3  + i02*nb2  + i01*nb1 );
+        const src0_t * src0_ptr = (const src0_t *) ((const char *) src0->data + i03*nb03 + i02*nb02 + i01*nb01);
+
+        vec_unary_op<op>(ne0, dst_ptr, src0_ptr);
+    }
+}
+
+// TODO: Use the 'traits' lookup table (for type conversion fns), instead of a mass of 'if' conditions with long templates
+template <float (*op)(float)>
+static void unary_op(const ggml_compute_params * params, ggml_tensor * dst) {
+    const ggml_tensor * src0 = dst->src[0];
+
+    /*  */ if (src0->type == GGML_TYPE_F32  && dst->type == GGML_TYPE_F32) { // all f32
+        apply_unary_op<op, float, float>(params, dst);
+    } else if (src0->type == GGML_TYPE_F16  && dst->type == GGML_TYPE_F16) { // all f16
+        apply_unary_op<op, ggml_fp16_t, ggml_fp16_t>(params, dst);
+    } else if (src0->type == GGML_TYPE_BF16 && dst->type == GGML_TYPE_BF16) { // all bf16
+        apply_unary_op<op, ggml_bf16_t, ggml_bf16_t>(params, dst);
+    } else if (src0->type == GGML_TYPE_BF16 && dst->type == GGML_TYPE_F32) {
+        apply_unary_op<op, ggml_bf16_t, float>(params, dst);
+    } else if (src0->type == GGML_TYPE_F16  && dst->type == GGML_TYPE_F32) {
+        apply_unary_op<op, ggml_fp16_t, float>(params, dst);
+    } else {
+        fprintf(stderr, "%s: unsupported types: dst: %s, src0: %s\n", __func__,
+            ggml_type_name(dst->type), ggml_type_name(src0->type));
+        GGML_ABORT("fatal error");
+    }
+}
+
+void ggml_compute_forward_abs(const ggml_compute_params * params, ggml_tensor * dst) {
+    unary_op<op_abs>(params, dst);
+}
+
+void ggml_compute_forward_sgn(const ggml_compute_params * params, ggml_tensor * dst) {
+    unary_op<op_sgn>(params, dst);
+}
+
+void ggml_compute_forward_neg(const ggml_compute_params * params, ggml_tensor * dst) {
+    unary_op<op_neg>(params, dst);
+}
+
+void ggml_compute_forward_step(const ggml_compute_params * params, ggml_tensor * dst) {
+    unary_op<op_step>(params, dst);
+}
+
+void ggml_compute_forward_tanh(const ggml_compute_params * params, ggml_tensor * dst) {
+    unary_op<op_tanh>(params, dst);
+}
+
+void ggml_compute_forward_elu(const ggml_compute_params * params, ggml_tensor * dst) {
+    unary_op<op_elu>(params, dst);
+}
+
+void ggml_compute_forward_relu(const ggml_compute_params * params, ggml_tensor * dst) {
+    unary_op<op_relu>(params, dst);
+}
+
+void ggml_compute_forward_sigmoid(const ggml_compute_params * params, ggml_tensor * dst) {
+    unary_op<op_sigmoid>(params, dst);
+}
+
+void ggml_compute_forward_hardsigmoid(const ggml_compute_params * params, ggml_tensor * dst) {
+    unary_op<op_hardsigmoid>(params, dst);
+}
+
+void ggml_compute_forward_exp(const ggml_compute_params * params, ggml_tensor * dst) {
+    unary_op<op_exp>(params, dst);
+}
+
+void ggml_compute_forward_hardswish(const ggml_compute_params * params, ggml_tensor * dst) {
+    unary_op<op_hardswish>(params, dst);
+}
+
+void ggml_compute_forward_sqr(const ggml_compute_params * params, ggml_tensor * dst) {
+    unary_op<op_sqr>(params, dst);
+}
+
+void ggml_compute_forward_sqrt(const ggml_compute_params * params, ggml_tensor * dst) {
+    unary_op<op_sqrt>(params, dst);
+}
+
+void ggml_compute_forward_sin(const ggml_compute_params * params, ggml_tensor * dst) {
+    unary_op<op_sin>(params, dst);
+}
+
+void ggml_compute_forward_cos(const ggml_compute_params * params, ggml_tensor * dst) {
+    unary_op<op_cos>(params, dst);
+}
+
+void ggml_compute_forward_log(const ggml_compute_params * params, ggml_tensor * dst) {
+    unary_op<op_log>(params, dst);
+}