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9 Commits

Author SHA1 Message Date
Bruce MacDonald
60f0b7db76 working 2025-01-24 16:51:19 -08:00
Jesse Gross
0d22c0ec1a new runner 2025-01-21 10:54:22 -08:00
Jesse Gross
a34960a516 tensor loading iface 2025-01-21 10:54:16 -08:00
Michael Yang
9722d96db2 docker 2025-01-20 17:06:45 -08:00
Michael Yang
fd868e5a88 default native cuda architecture when possible 2025-01-20 16:19:52 -08:00
Michael Yang
a48bd5bbe7 cpu all 2025-01-20 15:40:05 -08:00
Michael Yang
ffd9914d0a update ci 2025-01-20 09:39:43 -08:00
Michael Yang
9d249bfcab sort devices by type 2025-01-20 09:39:43 -08:00
Michael Yang
8cb7b94c40 next ollama runner
implement llama and mllama model architectures in go using ggml (through
cgo)
2025-01-20 09:39:43 -08:00
603 changed files with 11950 additions and 11141 deletions

9
.gitattributes vendored
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@ -7,5 +7,14 @@ llama/**/*.cuh linguist-vendored
llama/**/*.m linguist-vendored
llama/**/*.metal linguist-vendored
ml/backend/**/*.c linguist-vendored
ml/backend/**/*.h linguist-vendored
ml/backend/**/*.cpp linguist-vendored
ml/backend/**/*.hpp linguist-vendored
ml/backend/**/*.cu linguist-vendored
ml/backend/**/*.cuh linguist-vendored
ml/backend/**/*.m linguist-vendored
ml/backend/**/*.metal linguist-vendored
* text=auto
*.go text eol=lf

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@ -478,243 +478,77 @@ jobs:
dist/OllamaSetup.exe
dist/ollama-windows-*.zip
# Linux x86 assets built using the container based build
build-linux-amd64:
build-linux:
environment: release
runs-on: linux
env:
PLATFORM: linux/amd64
steps:
- uses: actions/checkout@v4
with:
submodules: recursive
- name: Set Version
shell: bash
run: echo "VERSION=${GITHUB_REF_NAME#v}" >> $GITHUB_ENV
- run: |
./scripts/build_linux.sh
- uses: actions/upload-artifact@v4
with:
name: dist-linux-amd64
path: |
dist/*linux*
!dist/*-cov
# Linux ARM assets built using the container based build
# (at present, docker isn't pre-installed on arm ubunutu images)
build-linux-arm64:
environment: release
runs-on: linux-arm64
env:
PLATFORM: linux/arm64
steps:
- uses: actions/checkout@v4
with:
submodules: recursive
- name: Set Version
shell: bash
run: echo "VERSION=${GITHUB_REF_NAME#v}" >> $GITHUB_ENV
- name: 'Install Docker'
run: |
# Add Docker's official GPG key:
env
uname -a
sudo apt-get update
sudo apt-get install -y ca-certificates curl
sudo install -m 0755 -d /etc/apt/keyrings
sudo curl -fsSL https://download.docker.com/linux/ubuntu/gpg -o /etc/apt/keyrings/docker.asc
sudo chmod a+r /etc/apt/keyrings/docker.asc
# Add the repository to Apt sources:
echo \
"deb [arch=$(dpkg --print-architecture) signed-by=/etc/apt/keyrings/docker.asc] https://download.docker.com/linux/ubuntu \
$(. /etc/os-release && echo "$VERSION_CODENAME") stable" | \
sudo tee /etc/apt/sources.list.d/docker.list > /dev/null
sudo apt-get update
sudo apt-get install -y docker-ce docker-ce-cli containerd.io
sudo usermod -aG docker $USER
sudo apt-get install acl
sudo setfacl --modify user:$USER:rw /var/run/docker.sock
- run: |
./scripts/build_linux.sh
- uses: actions/upload-artifact@v4
with:
name: dist-linux-arm64
path: |
dist/*linux*
!dist/*-cov
# Container image build
build-container-image:
environment: release
strategy:
matrix:
runner:
- linux
- linux-arm64
runs-on: ${{ matrix.runner }}
env:
FINAL_IMAGE_REPO: ollama/ollama
include:
- os: linux
arch: amd64
targets: [archive, rocm]
- os: linux
arch: arm64
targets: [archive]
steps:
- uses: actions/checkout@v4
- uses: docker/setup-qemu-action@v3
- uses: docker/setup-buildx-action@v3
- run: |
apt-get update && apt-get install pigz
for TARGET in ${{ matrix.targets }}; do docker buildx build --platform $PLATFORM --target $TARGET --output type=local,dest=dist/$PLATFORM .; done
tar c -C dist/$PLATFORM . | pigz -9cv >dist/ollama-${PLATFORM//\//-}.tar.gz
env:
PLATFORM: ${{ matrix.os }}/${{ matrix.arch }}
- uses: actions/upload-artifact@v4
with:
submodules: recursive
- name: 'Install Docker'
if: ${{ startsWith(matrix.runner, 'linux-arm64') }}
run: |
sudo apt-get update
sudo apt-get install -y ca-certificates curl
sudo install -m 0755 -d /etc/apt/keyrings
sudo curl -fsSL https://download.docker.com/linux/ubuntu/gpg -o /etc/apt/keyrings/docker.asc
sudo chmod a+r /etc/apt/keyrings/docker.asc
echo "deb [arch=$(dpkg --print-architecture) signed-by=/etc/apt/keyrings/docker.asc] https://download.docker.com/linux/ubuntu \
$(. /etc/os-release && echo "$VERSION_CODENAME") stable" | \
sudo tee /etc/apt/sources.list.d/docker.list > /dev/null
sudo apt-get update
sudo apt-get install -y docker-ce docker-ce-cli containerd.io
sudo usermod -aG docker $USER
sudo apt-get install acl
sudo setfacl --modify user:$USER:rw /var/run/docker.sock
- name: Docker meta
id: meta
uses: docker/metadata-action@v5
with:
images: ${{ env.FINAL_IMAGE_REPO }}
flavor: |
latest=false
tags: |
type=ref,enable=true,priority=600,prefix=0.0.0-pr,suffix=,event=pr
type=semver,pattern={{version}}
- name: Set Version
shell: bash
run: |
machine=$(uname -m)
case ${machine} in
x86_64) echo ARCH=amd64; echo PLATFORM_PAIR=linux-amd64 ;;
aarch64) echo ARCH=arm64; echo PLATFORM_PAIR=linux-arm64 ;;
esac >>$GITHUB_ENV
echo GOFLAGS="'-ldflags=-w -s \"-X=github.com/ollama/ollama/version.Version=${{ env.DOCKER_METADATA_OUTPUT_VERSION }}\" \"-X=github.com/ollama/ollama/server.mode=release\"'" >>$GITHUB_ENV
- name: Set up Docker Buildx
uses: docker/setup-buildx-action@v3
- name: Login to Docker Hub
uses: docker/login-action@v3
with:
username: ${{ vars.DOCKER_USER }}
password: ${{ secrets.DOCKER_ACCESS_TOKEN }}
- name: Build and push by digest
id: build
uses: docker/build-push-action@v6
with:
context: "."
platforms: linux/${{ env.ARCH }}
build-args: |
GOFLAGS
outputs: type=image,name=${{ env.FINAL_IMAGE_REPO }},push-by-digest=true,name-canonical=true,push=true
- name: Export digest
run: |
mkdir -p /tmp/digests
digest="${{ steps.build.outputs.digest }}"
touch "/tmp/digests/${digest#sha256:}"
- name: Upload digest
uses: actions/upload-artifact@v4
with:
name: digests-${{ env.PLATFORM_PAIR }}
path: /tmp/digests/*
if-no-files-found: error
retention-days: 1
merge:
name: dist-${{ matrix.os }}-${{ matrix.arch }}
path: |
dist/ollama-${{ matrix.os }}-${{ matrix.arch }}.tar.gz
build-docker:
environment: release
runs-on: linux
needs:
- build-container-image
env:
FINAL_IMAGE_REPO: ollama/ollama
runs-on: ubuntu-latest
strategy:
matrix:
include:
- flavor: |
latest=auto
platforms: linux/amd64,linux/arm64
build-args: [GOFLAGS]
- flavor: |
suffix=-rocm,onlatest=false
platforms: linux/amd64
build-args: [GOFLAGS, FLAVOR=rocm]
steps:
- uses: actions/checkout@v4
with:
submodules: recursive
- name: Download digests
uses: actions/download-artifact@v4
with:
path: /tmp/digests
pattern: digests-*
merge-multiple: true
- name: Set up Docker Buildx
uses: docker/setup-buildx-action@v3
- name: Docker meta
id: meta
uses: docker/metadata-action@v5
with:
images: ${{ env.FINAL_IMAGE_REPO }}
flavor: |
latest=false
tags: |
type=ref,enable=true,priority=600,prefix=0.0.0-pr,suffix=,event=pr
type=semver,pattern={{version}}
- name: Set Version
shell: bash
run: |
machine=$(uname -m)
case ${machine} in
x86_64) echo ARCH=amd64; echo PLATFORM_PAIR=linux-amd64 ;;
aarch64) echo ARCH=arm64; echo PLATFORM_PAIR=linux-arm64 ;;
esac >>$GITHUB_ENV
echo GOFLAGS="'-ldflags=-w -s \"-X=github.com/ollama/ollama/version.Version=${{ env.DOCKER_METADATA_OUTPUT_VERSION }}\" \"-X=github.com/ollama/ollama/server.mode=release\"'" >>$GITHUB_ENV
- name: Login to Docker Hub
uses: docker/login-action@v3
- uses: docker/setup-qemu-action@v2
- uses: docker/setup-buildx-action@v2
- uses: docker/login-action@v3
with:
username: ${{ vars.DOCKER_USER }}
password: ${{ secrets.DOCKER_ACCESS_TOKEN }}
- name: Create manifest list and push
working-directory: /tmp/digests
run: |
docker buildx imagetools create $(jq -cr '.tags | map("-t " + .) | join(" ")' <<< "$DOCKER_METADATA_OUTPUT_JSON") \
$(printf '${{ env.FINAL_IMAGE_REPO }}@sha256:%s ' *)
- name: Inspect image
run: |
docker buildx imagetools inspect ${{ env.FINAL_IMAGE_REPO }}:${{ steps.meta.outputs.version }}
build-container-image-rocm:
environment: release
runs-on: linux
env:
FINAL_IMAGE_REPO: ollama/ollama
ARCH: amd64
PLATFORM_PAIR: linux-amd64
steps:
- uses: actions/checkout@v4
- id: metadata
uses: docker/metadata-action@v4
with:
submodules: recursive
- name: Docker meta
id: meta
uses: docker/metadata-action@v5
with:
images: ${{ env.FINAL_IMAGE_REPO }}
flavor: |
latest=false
flavor: ${{ matrix.flavor }}
images: |
ollama/ollama
tags: |
type=ref,enable=true,priority=600,prefix=0.0.0-pr,suffix=,event=pr
type=semver,pattern={{version}}
- name: Set Version
shell: bash
run: |
echo GOFLAGS="'-ldflags=-w -s \"-X=github.com/ollama/ollama/version.Version=${{ env.DOCKER_METADATA_OUTPUT_VERSION }}\" \"-X=github.com/ollama/ollama/server.mode=release\"'" >>$GITHUB_ENV
- name: Set up Docker Buildx
uses: docker/setup-buildx-action@v3
- name: Login to Docker Hub
uses: docker/login-action@v3
- uses: docker/build-push-action@v6
with:
username: ${{ vars.DOCKER_USER }}
password: ${{ secrets.DOCKER_ACCESS_TOKEN }}
- name: Build and push by digest
id: build
uses: docker/build-push-action@v6
with:
context: "."
target: runtime-rocm
build-args: |
GOFLAGS
tags: ${{ env.FINAL_IMAGE_REPO }}:${{ env.DOCKER_METADATA_OUTPUT_VERSION}}-rocm
context: .
push: true
platforms: ${{ matrix.platforms }}
build-args: ${{ matrix.build-args }}
tags: ${{ steps.metadata.outputs.tags }}
labels: ${{ steps.metadata.outputs.labels }}
cache-from: type=registry,ref=ollama/ollama:latest
cache-to: type=inline
provenance: false
env:
GOFLAGS="'-ldflags=-w -s \"-X=github.com/ollama/ollama/version.Version=${{ steps.metadata.outputs.version }}\" \"-X=github.com/ollama/ollama/server.mode=release\"'"
# Aggregate all the assets and ship a release
release:

View File

@ -1,11 +1,5 @@
name: test
env:
ROCM_WINDOWS_URL: https://download.amd.com/developer/eula/rocm-hub/AMD-Software-PRO-Edition-24.Q3-WinSvr2022-For-HIP.exe
MSYS2_URL: https://github.com/msys2/msys2-installer/releases/download/2024-07-27/msys2-x86_64-20240727.exe
CUDA_12_WINDOWS_URL: https://developer.download.nvidia.com/compute/cuda/12.4.0/local_installers/cuda_12.4.0_551.61_windows.exe
CUDA_12_WINDOWS_VER: 12.4
concurrency:
# For PRs, later CI runs preempt previous ones. e.g. a force push on a PR
# cancels running CI jobs and starts all new ones.
@ -27,7 +21,7 @@ jobs:
changes:
runs-on: ubuntu-latest
outputs:
RUNNERS: ${{ steps.changes.outputs.RUNNERS }}
changed: ${{ steps.changes.outputs.changed }}
steps:
- uses: actions/checkout@v4
with:
@ -35,309 +29,61 @@ jobs:
- id: changes
run: |
changed() {
git diff-tree -r --no-commit-id --name-only \
$(git merge-base ${{ github.event.pull_request.base.sha }} ${{ github.event.pull_request.head.sha }}) \
${{ github.event.pull_request.head.sha }} \
local BASE=${{ github.event.pull_request.base.sha }}
local HEAD=${{ github.event.pull_request.head.sha }}
local MERGE_BASE=$(git merge-base $BASE $HEAD)
git diff-tree -r --no-commit-id --name-only "$MERGE_BASE" "$HEAD" \
| xargs python3 -c "import sys; from pathlib import Path; print(any(Path(x).match(glob) for x in sys.argv[1:] for glob in '$*'.split(' ')))"
}
{
echo RUNNERS=$(changed 'llama/**')
} >>$GITHUB_OUTPUT
echo changed=$(changed 'llama/llama.cpp/**' 'ml/backend/ggml/ggml/**') | tee -a $GITHUB_OUTPUT
runners-linux-cuda:
linux:
needs: [changes]
if: ${{ needs.changes.outputs.RUNNERS == 'True' }}
if: ${{ needs.changes.outputs.changed == 'True' }}
strategy:
matrix:
cuda-version:
- '11.8.0'
runs-on: linux
container: nvidia/cuda:${{ matrix.cuda-version }}-devel-ubuntu20.04
include:
- container: nvidia/cuda:11.8.0-devel-ubuntu22.04
preset: CUDA
- container: rocm/dev-ubuntu-22.04:6.1.2
preset: ROCm
extra-packages: rocm-libs
runs-on: ubuntu-latest
container: ${{ matrix.container }}
steps:
- uses: actions/checkout@v4
- run: |
apt-get update && apt-get install -y git build-essential curl
apt-get update
apt-get install -y cmake pkg-config ${{ matrix.extra-packages }}
env:
DEBIAN_FRONTEND: noninteractive
- uses: actions/checkout@v4
- uses: actions/setup-go@v4
with:
go-version-file: go.mod
cache: true
- run: go get ./...
- run: |
git config --global --add safe.directory /__w/ollama/ollama
cores=$(grep '^core id' /proc/cpuinfo |sort -u|wc -l)
make -j $cores cuda_v11
runners-linux-rocm:
needs: [changes]
if: ${{ needs.changes.outputs.RUNNERS == 'True' }}
strategy:
matrix:
rocm-version:
- '6.1.2'
runs-on: linux
container: rocm/dev-ubuntu-20.04:${{ matrix.rocm-version }}
steps:
- run: |
apt-get update && apt-get install -y git build-essential curl rocm-libs
env:
DEBIAN_FRONTEND: noninteractive
- uses: actions/checkout@v4
- uses: actions/setup-go@v4
with:
go-version-file: go.mod
cache: true
- run: go get ./...
- run: |
git config --global --add safe.directory /__w/ollama/ollama
cores=$(grep '^core id' /proc/cpuinfo |sort -u|wc -l)
make -j $cores rocm
cmake --preset ${{ matrix.preset }}
cmake --build --preset ${{ matrix.preset }} --parallel
# ROCm generation step
runners-windows-rocm:
needs: [changes]
if: ${{ needs.changes.outputs.RUNNERS == 'True' }}
runs-on: windows
steps:
- uses: actions/checkout@v4
- uses: actions/setup-go@v5
with:
go-version-file: go.mod
cache: true
- name: Set make jobs default
run: |
echo "MAKEFLAGS=--jobs=$((Get-ComputerInfo -Property CsProcessors).CsProcessors.NumberOfCores)" | Out-File -FilePath $env:GITHUB_ENV -Encoding utf8 -Append
# ROCM installation steps
- name: 'Cache ROCm installer'
id: cache-rocm
uses: actions/cache@v4
with:
path: rocm-install.exe
key: ${{ env.ROCM_WINDOWS_URL }}
- name: 'Conditionally Download ROCm'
if: steps.cache-rocm.outputs.cache-hit != 'true'
run: |
$ErrorActionPreference = "Stop"
Invoke-WebRequest -Uri "${env:ROCM_WINDOWS_URL}" -OutFile "rocm-install.exe"
- name: 'Install ROCm'
run: |
Start-Process "rocm-install.exe" -ArgumentList '-install' -NoNewWindow -Wait
- name: 'Verify ROCm'
run: |
& 'C:\Program Files\AMD\ROCm\*\bin\clang.exe' --version
echo "HIP_PATH=$(Resolve-Path 'C:\Program Files\AMD\ROCm\*\bin\clang.exe' | split-path | split-path | select -first 1)" | Out-File -FilePath $env:GITHUB_ENV -Encoding utf8 -Append
- name: Add msys paths
run: |
echo "c:\msys64\usr\bin" | Out-File -FilePath $env:GITHUB_PATH -Encoding utf8 -Append
echo "C:\msys64\clang64\bin" | Out-File -FilePath $env:GITHUB_PATH -Encoding utf8 -Append
- name: Install msys2 tools
run: |
Start-Process "c:\msys64\usr\bin\pacman.exe" -ArgumentList @("-S", "--noconfirm", "mingw-w64-clang-x86_64-gcc-compat", "mingw-w64-clang-x86_64-clang") -NoNewWindow -Wait
- name: make rocm runner
run: |
import-module 'C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\Common7\Tools\Microsoft.VisualStudio.DevShell.dll'
Enter-VsDevShell -vsinstallpath 'C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise' -skipautomaticlocation -DevCmdArguments '-arch=x64 -no_logo'
if (!(gcc --version | select-string -quiet clang)) { throw "wrong gcc compiler detected - must be clang" }
make -C llama print-HIP_PATH print-HIP_LIB_DIR
make rocm
# CUDA generation step
runners-windows-cuda:
needs: [changes]
if: ${{ needs.changes.outputs.RUNNERS == 'True' }}
runs-on: windows
steps:
- uses: actions/checkout@v4
- uses: actions/setup-go@v5
with:
go-version-file: go.mod
cache: true
- name: Set make jobs default
run: |
echo "MAKEFLAGS=--jobs=$((Get-ComputerInfo -Property CsProcessors).CsProcessors.NumberOfCores)" | Out-File -FilePath $env:GITHUB_ENV -Encoding utf8 -Append
# CUDA installation steps
- name: 'Cache CUDA installer'
id: cache-cuda
uses: actions/cache@v4
with:
path: cuda-install.exe
key: ${{ env.CUDA_12_WINDOWS_URL }}
- name: 'Conditionally Download CUDA'
if: steps.cache-cuda.outputs.cache-hit != 'true'
run: |
$ErrorActionPreference = "Stop"
Invoke-WebRequest -Uri "${env:CUDA_12_WINDOWS_URL}" -OutFile "cuda-install.exe"
- name: 'Install CUDA'
run: |
$subpackages = @("cudart", "nvcc", "cublas", "cublas_dev") | foreach-object {"${_}_${{ env.CUDA_12_WINDOWS_VER }}"}
Start-Process "cuda-install.exe" -ArgumentList (@("-s") + $subpackages) -NoNewWindow -Wait
- name: 'Verify CUDA'
run: |
& (resolve-path "c:\Program Files\NVIDIA*\CUDA\v*\bin\nvcc.exe")[0] --version
$cudaPath=((resolve-path "c:\Program Files\NVIDIA*\CUDA\v*\bin\nvcc.exe")[0].path | split-path | split-path)
$cudaVer=($cudaPath | split-path -leaf ) -replace 'v(\d+).(\d+)', '$1_$2'
echo "$cudaPath\bin" | Out-File -FilePath $env:GITHUB_PATH -Encoding utf8 -Append
echo "CUDA_PATH=$cudaPath" | Out-File -FilePath $env:GITHUB_ENV -Encoding utf8 -Append
echo "CUDA_PATH_V${cudaVer}=$cudaPath" | Out-File -FilePath $env:GITHUB_ENV -Encoding utf8 -Append
echo "CUDA_PATH_VX_Y=CUDA_PATH_V${cudaVer}" | Out-File -FilePath $env:GITHUB_ENV -Encoding utf8 -Append
- name: Add msys paths
run: |
echo "c:\msys64\usr\bin" | Out-File -FilePath $env:GITHUB_PATH -Encoding utf8 -Append
echo "C:\msys64\clang64\bin" | Out-File -FilePath $env:GITHUB_PATH -Encoding utf8 -Append
- name: Install msys2 tools
run: |
Start-Process "c:\msys64\usr\bin\pacman.exe" -ArgumentList @("-S", "--noconfirm", "mingw-w64-clang-x86_64-gcc-compat", "mingw-w64-clang-x86_64-clang") -NoNewWindow -Wait
- name: make cuda runner
run: |
import-module 'C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\Common7\Tools\Microsoft.VisualStudio.DevShell.dll'
Enter-VsDevShell -vsinstallpath 'C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise' -skipautomaticlocation -DevCmdArguments '-arch=x64 -no_logo'
if (!(gcc --version | select-string -quiet clang)) { throw "wrong gcc compiler detected - must be clang" }
make cuda_v$(($env:CUDA_PATH | split-path -leaf) -replace 'v(\d+).*', '$1')
runners-cpu:
needs: [changes]
if: ${{ needs.changes.outputs.RUNNERS == 'True' }}
strategy:
matrix:
os: [ubuntu-latest, macos-latest, windows-2019]
arch: [amd64, arm64]
exclude:
- os: ubuntu-latest
arch: arm64
- os: windows-2019
arch: arm64
runs-on: ${{ matrix.os }}
env:
GOARCH: ${{ matrix.arch }}
ARCH: ${{ matrix.arch }}
CGO_ENABLED: '1'
steps:
- uses: actions/checkout@v4
- uses: actions/setup-go@v5
with:
go-version-file: go.mod
cache: true
- name: Add msys paths
if: ${{ startsWith(matrix.os, 'windows-') }}
run: |
echo "c:\msys64\usr\bin" | Out-File -FilePath $env:GITHUB_PATH -Encoding utf8 -Append
echo "C:\msys64\clang64\bin" | Out-File -FilePath $env:GITHUB_PATH -Encoding utf8 -Append
- name: Install msys2 tools
if: ${{ startsWith(matrix.os, 'windows-') }}
run: |
Start-Process "c:\msys64\usr\bin\pacman.exe" -ArgumentList @("-S", "--noconfirm", "mingw-w64-clang-x86_64-gcc-compat", "mingw-w64-clang-x86_64-clang") -NoNewWindow -Wait
- name: 'Build Windows Go Runners'
if: ${{ startsWith(matrix.os, 'windows-') }}
run: |
$gopath=(get-command go).source | split-path -parent
$gccpath=(get-command gcc).source | split-path -parent
import-module 'C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\Common7\Tools\Microsoft.VisualStudio.DevShell.dll'
Enter-VsDevShell -vsinstallpath 'C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise' -skipautomaticlocation -DevCmdArguments '-arch=x64 -no_logo'
$env:CMAKE_SYSTEM_VERSION="10.0.22621.0"
$env:PATH="$gopath;$gccpath;$env:PATH"
echo $env:PATH
if (!(gcc --version | select-string -quiet clang)) { throw "wrong gcc compiler detected - must be clang" }
make -j 4
- name: 'Build Unix Go Runners'
if: ${{ ! startsWith(matrix.os, 'windows-') }}
run: make -j 4
- run: go build .
lint:
strategy:
matrix:
os: [ubuntu-latest, macos-latest, windows-2019]
arch: [amd64, arm64]
exclude:
- os: ubuntu-latest
arch: arm64
- os: windows-2019
arch: arm64
- os: macos-latest
arch: amd64
runs-on: ${{ matrix.os }}
env:
GOARCH: ${{ matrix.arch }}
CGO_ENABLED: '1'
steps:
- uses: actions/checkout@v4
with:
submodules: recursive
- name: Add msys paths
if: ${{ startsWith(matrix.os, 'windows-') }}
run: |
echo "c:\msys64\usr\bin" | Out-File -FilePath $env:GITHUB_PATH -Encoding utf8 -Append
echo "C:\msys64\clang64\bin" | Out-File -FilePath $env:GITHUB_PATH -Encoding utf8 -Append
- name: Install msys2 tools
if: ${{ startsWith(matrix.os, 'windows-') }}
run: |
Start-Process "c:\msys64\usr\bin\pacman.exe" -ArgumentList @("-S", "--noconfirm", "mingw-w64-clang-x86_64-gcc-compat", "mingw-w64-clang-x86_64-clang") -NoNewWindow -Wait
- uses: actions/setup-go@v5
with:
go-version-file: go.mod
cache: false
- run: |
case ${{ matrix.arch }} in
amd64) echo ARCH=x86_64 ;;
arm64) echo ARCH=arm64 ;;
esac >>$GITHUB_ENV
shell: bash
- uses: golangci/golangci-lint-action@v6
with:
args: --timeout 10m0s -v
test:
strategy:
matrix:
os: [ubuntu-latest, macos-latest, windows-2019]
arch: [amd64]
exclude:
- os: ubuntu-latest
arch: arm64
- os: windows-2019
arch: arm64
os: [ubuntu-latest, macos-latest, windows-latest]
runs-on: ${{ matrix.os }}
env:
GOARCH: ${{ matrix.arch }}
CGO_ENABLED: '1'
steps:
- uses: actions/checkout@v4
with:
submodules: recursive
- name: Add msys paths
if: ${{ startsWith(matrix.os, 'windows-') }}
run: |
echo "c:\msys64\usr\bin" | Out-File -FilePath $env:GITHUB_PATH -Encoding utf8 -Append
echo "C:\msys64\clang64\bin" | Out-File -FilePath $env:GITHUB_PATH -Encoding utf8 -Append
- name: Install msys2 tools
if: ${{ startsWith(matrix.os, 'windows-') }}
run: |
Start-Process "c:\msys64\usr\bin\pacman.exe" -ArgumentList @("-S", "--noconfirm", "mingw-w64-clang-x86_64-gcc-compat", "mingw-w64-clang-x86_64-clang") -NoNewWindow -Wait
- uses: actions/setup-go@v5
with:
go-version-file: go.mod
cache: true
- run: |
case ${{ matrix.arch }} in
amd64) echo ARCH=amd64 ;;
arm64) echo ARCH=arm64 ;;
esac >>$GITHUB_ENV
shell: bash
- uses: golangci/golangci-lint-action@v6
with:
args: --timeout 10m0s -v
- run: go test ./...
patches:
needs: [changes]
if: ${{ needs.changes.outputs.RUNNERS == 'True' }}
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
with:
submodules: recursive
- name: Verify patches carry all the changes
- name: Verify patches apply cleanly and do not change files
run: |
make apply-patches sync && git diff --compact-summary --exit-code llama
make -f Makefile2 clean checkout sync
git diff --compact-summary --exit-code

4
.gitignore vendored
View File

@ -12,4 +12,6 @@ test_data
*.crt
llama/build
__debug_bin*
llama/vendor
llama/vendor
model/model_test/testdata/*/
!model/model_test/testdata/*.*

52
CMakeLists.txt Normal file
View File

@ -0,0 +1,52 @@
cmake_minimum_required(VERSION 3.21)
project(Ollama C CXX)
include(CheckLanguage)
find_package(Threads REQUIRED)
set(CMAKE_BUILD_TYPE Release)
set(BUILD_SHARED_LIBS ON)
set(CMAKE_CXX_STANDARD 17)
set(CMAKE_CXX_STANDARD_REQUIRED ON)
set(CMAKE_CXX_EXTENSIONS OFF)
set(GGML_BUILD ON)
set(GGML_SHARED ON)
set(GGML_CCACHE ON)
set(GGML_BACKEND_DL ON)
set(GGML_BACKEND_SHARED ON)
set(GGML_SCHED_MAX_COPIES 4)
set(GGML_LLAMAFILE ON)
set(GGML_CPU_ALL_VARIANTS ON)
set(GGML_CUDA_PEER_MAX_BATCH_SIZE 128)
set(GGML_CUDA_GRAPHS ON)
set(CMAKE_RUNTIME_OUTPUT_DIRECTORY ${CMAKE_BINARY_DIR}/lib)
set(CMAKE_LIBRARY_OUTPUT_DIRECTORY ${CMAKE_BINARY_DIR}/lib)
include_directories(${CMAKE_CURRENT_SOURCE_DIR}/ml/backend/ggml/ggml/src)
include_directories(${CMAKE_CURRENT_SOURCE_DIR}/ml/backend/ggml/ggml/src/include)
include_directories(${CMAKE_CURRENT_SOURCE_DIR}/ml/backend/ggml/ggml/src/ggml-cpu)
include_directories(${CMAKE_CURRENT_SOURCE_DIR}/ml/backend/ggml/ggml/src/ggml-cpu/amx)
set(GGML_CPU ON)
add_subdirectory(${CMAKE_CURRENT_SOURCE_DIR}/ml/backend/ggml/ggml/src)
set_property(TARGET ggml PROPERTY EXCLUDE_FROM_ALL TRUE)
check_language(CUDA)
if(CMAKE_CUDA_COMPILER)
if(CMAKE_VERSION VERSION_GREATER_EQUAL "3.24" AND NOT CMAKE_CUDA_ARCHITECTURES)
set(CMAKE_CUDA_ARCHITECTURES "native")
endif()
add_subdirectory(${CMAKE_CURRENT_SOURCE_DIR}/ml/backend/ggml/ggml/src/ggml-cuda)
endif()
check_language(HIP)
if(CMAKE_HIP_COMPILER)
add_subdirectory(${CMAKE_CURRENT_SOURCE_DIR}/ml/backend/ggml/ggml/src/ggml-hip)
endif()

98
CMakePresets.json Normal file
View File

@ -0,0 +1,98 @@
{
"version": 3,
"configurePresets": [
{
"name": "Default",
"binaryDir": "${sourceDir}/dist/build",
"cacheVariables": {
"CMAKE_BUILD_TYPE": "Release"
}
},
{
"name": "CUDA",
"inherits": [ "Default" ]
},
{
"name": "CUDA 11",
"inherits": [ "CUDA" ],
"cacheVariables": {
"CMAKE_CUDA_ARCHITECTURES": "50;52;53;60;61;62;70;72;75;80;86"
}
},
{
"name": "CUDA 12",
"inherits": [ "CUDA" ],
"cacheVariables": {
"CMAKE_CUDA_ARCHITECTURES": "60;61;62;70;72;75;80;86;87;89;90;90a"
}
},
{
"name": "JetPack 5",
"inherits": [ "CUDA" ],
"cacheVariables": {
"CMAKE_CUDA_ARCHITECTURES": "72;87"
}
},
{
"name": "JetPack 6",
"inherits": [ "CUDA" ],
"cacheVariables": {
"CMAKE_CUDA_ARCHITECTURES": "87"
}
},
{
"name": "ROCm",
"inherits": [ "Default" ]
},
{
"name": "ROCm 6",
"inherits": [ "ROCm" ],
"cacheVariables": {
"CMAKE_HIP_ARCHITECTURES": "gfx900;gfx940;gfx941;gfx942;gfx1010;gfx1012;gfx1030;gfx1100;gfx1101;gfx1102"
}
}
],
"buildPresets": [
{
"name": "Default",
"configurePreset": "Default",
"configuration": "Release",
"targets": [ "ggml-cpu" ]
},
{
"name": "CUDA",
"configurePreset": "CUDA",
"targets": [ "ggml-cuda" ]
},
{
"name": "CUDA 11",
"inherits": [ "CUDA" ],
"configurePreset": "CUDA 11"
},
{
"name": "CUDA 12",
"inherits": [ "CUDA" ],
"configurePreset": "CUDA 12"
},
{
"name": "JetPack 5",
"inherits": [ "CUDA" ],
"configurePreset": "JetPack 5"
},
{
"name": "JetPack 6",
"inherits": [ "CUDA" ],
"configurePreset": "JetPack 6"
},
{
"name": "ROCm",
"configurePreset": "ROCm",
"targets": [ "ggml-hip" ]
},
{
"name": "ROCm 6",
"inherits": [ "ROCm" ],
"configurePreset": "ROCm 6"
}
]
}

View File

@ -1,201 +1,161 @@
ARG GOLANG_VERSION=1.22.8
ARG CUDA_VERSION_11=11.3.1
ARG CUDA_VERSION_12=12.4.0
ARG ROCM_VERSION=6.1.2
ARG JETPACK_6=r36.2.0
ARG JETPACK_5=r35.4.1
# vim: filetype=dockerfile
### To create a local image for building linux binaries on mac or windows with efficient incremental builds
#
# docker build --platform linux/amd64 -t builder-amd64 -f Dockerfile --target unified-builder-amd64 .
# docker run --platform linux/amd64 --rm -it -v $(pwd):/go/src/github.com/ollama/ollama/ builder-amd64
#
### Then incremental builds will be much faster in this container
#
# make -j 10 dist
#
FROM --platform=linux/amd64 rocm/dev-centos-7:${ROCM_VERSION}-complete AS unified-builder-amd64
ARG GOLANG_VERSION
ARG CUDA_VERSION_11
ARG CUDA_VERSION_12
COPY ./scripts/rh_linux_deps.sh /
ENV PATH /opt/rh/devtoolset-10/root/usr/bin:/usr/local/cuda/bin:$PATH
ENV LD_LIBRARY_PATH=${LD_LIBRARY_PATH}:/usr/local/cuda/lib64
RUN GOLANG_VERSION=${GOLANG_VERSION} sh /rh_linux_deps.sh
RUN yum-config-manager --add-repo https://developer.download.nvidia.com/compute/cuda/repos/rhel7/x86_64/cuda-rhel7.repo && \
dnf clean all && \
dnf install -y \
zsh \
cuda-toolkit-$(echo ${CUDA_VERSION_11} | cut -f1-2 -d. | sed -e "s/\./-/g") \
cuda-toolkit-$(echo ${CUDA_VERSION_12} | cut -f1-2 -d. | sed -e "s/\./-/g")
# TODO intel oneapi goes here...
ENV GOARCH amd64
ENV CGO_ENABLED 1
WORKDIR /go/src/github.com/ollama/ollama/
ENTRYPOINT [ "zsh" ]
ARG FLAVOR=${TARGETARCH}
### To create a local image for building linux binaries on mac or linux/arm64 with efficient incremental builds
# Note: this does not contain jetson variants
#
# docker build --platform linux/arm64 -t builder-arm64 -f Dockerfile --target unified-builder-arm64 .
# docker run --platform linux/arm64 --rm -it -v $(pwd):/go/src/github.com/ollama/ollama/ builder-arm64
#
FROM --platform=linux/arm64 rockylinux:8 AS unified-builder-arm64
ARG GOLANG_VERSION
ARG CUDA_VERSION_11
ARG CUDA_VERSION_12
COPY ./scripts/rh_linux_deps.sh /
RUN GOLANG_VERSION=${GOLANG_VERSION} sh /rh_linux_deps.sh
RUN yum-config-manager --add-repo https://developer.download.nvidia.com/compute/cuda/repos/rhel8/sbsa/cuda-rhel8.repo && \
dnf config-manager --set-enabled appstream && \
dnf clean all && \
dnf install -y \
zsh \
cuda-toolkit-$(echo ${CUDA_VERSION_11} | cut -f1-2 -d. | sed -e "s/\./-/g") \
cuda-toolkit-$(echo ${CUDA_VERSION_12} | cut -f1-2 -d. | sed -e "s/\./-/g")
ENV PATH /opt/rh/gcc-toolset-10/root/usr/bin:$PATH:/usr/local/cuda/bin
ENV LD_LIBRARY_PATH=${LD_LIBRARY_PATH}:/usr/local/cuda/lib64
ENV LIBRARY_PATH=/usr/local/cuda/lib64/stubs:/opt/amdgpu/lib64
ENV GOARCH arm64
ENV CGO_ENABLED 1
WORKDIR /go/src/github.com/ollama/ollama/
ENTRYPOINT [ "zsh" ]
ARG ROCMVERSION=6.1.2
ARG JETPACK5VERSION=r35.4.1
ARG JETPACK6VERSION=r36.2.0
ARG CMAKEVERSION=3.31.2
FROM --platform=linux/amd64 unified-builder-amd64 AS build-amd64
COPY . .
ARG OLLAMA_SKIP_CUDA_GENERATE
ARG OLLAMA_SKIP_ROCM_GENERATE
ARG OLLAMA_FAST_BUILD
ARG VERSION
ARG CUSTOM_CPU_FLAGS
FROM --platform=linux/amd64 rocm/dev-centos-7:${ROCMVERSION}-complete AS base-amd64
RUN sed -i -e 's/mirror.centos.org/vault.centos.org/g' -e 's/^#.*baseurl=http/baseurl=http/g' -e 's/^mirrorlist=http/#mirrorlist=http/g' /etc/yum.repos.d/*.repo \
&& yum install -y yum-utils devtoolset-10-gcc devtoolset-10-gcc-c++ \
&& yum-config-manager --add-repo https://developer.download.nvidia.com/compute/cuda/repos/rhel7/x86_64/cuda-rhel7.repo \
&& curl -s -L https://github.com/ccache/ccache/releases/download/v4.10.2/ccache-4.10.2-linux-x86_64.tar.xz | tar -Jx -C /usr/local/bin --strip-components 1
ENV PATH=/opt/rh/devtoolset-10/root/usr/bin:/opt/rh/devtoolset-11/root/usr/bin:$PATH
FROM --platform=linux/arm64 rockylinux:8 AS base-arm64
# install epel-release for ccache
RUN yum install -y yum-utils epel-release \
&& yum install -y clang ccache \
&& yum-config-manager --add-repo https://developer.download.nvidia.com/compute/cuda/repos/rhel8/sbsa/cuda-rhel8.repo
ENV CC=clang CXX=clang++
FROM base-${TARGETARCH} AS base
ARG CMAKEVERSION
RUN curl -fsSL https://github.com/Kitware/CMake/releases/download/v${CMAKEVERSION}/cmake-${CMAKEVERSION}-linux-$(uname -m).tar.gz | tar xz -C /usr/local --strip-components 1
COPY CMakeLists.txt CMakePresets.json .
COPY ml/backend/ggml/ggml ml/backend/ggml/ggml
ENV LDFLAGS=-s
FROM base AS cpu
# amd64 uses gcc which requires devtoolset-11 for AVX extensions while arm64 uses clang
RUN if [ "$(uname -m)" = "x86_64" ]; then yum install -y devtoolset-11-gcc devtoolset-11-gcc-c++; fi
ENV PATH=/opt/rh/devtoolset-11/root/usr/bin:$PATH
RUN --mount=type=cache,target=/root/.ccache \
if grep "^flags" /proc/cpuinfo|grep avx>/dev/null; then \
make -j $(nproc) dist ; \
else \
make -j 5 dist ; \
fi
RUN cd dist/linux-$GOARCH && \
tar -cf - . | pigz --best > ../ollama-linux-$GOARCH.tgz
RUN if [ -z ${OLLAMA_SKIP_ROCM_GENERATE} ] ; then \
cd dist/linux-$GOARCH-rocm && \
tar -cf - . | pigz --best > ../ollama-linux-$GOARCH-rocm.tgz ;\
fi
cmake --preset 'Default' && cmake --build --parallel --preset 'Default'
# Jetsons need to be built in discrete stages
FROM --platform=linux/arm64 nvcr.io/nvidia/l4t-jetpack:${JETPACK_5} AS runners-jetpack5-arm64
ARG GOLANG_VERSION
RUN apt-get update && apt-get install -y git curl ccache && \
curl -s -L https://dl.google.com/go/go${GOLANG_VERSION}.linux-arm64.tar.gz | tar xz -C /usr/local && \
ln -s /usr/local/go/bin/go /usr/local/bin/go && \
ln -s /usr/local/go/bin/gofmt /usr/local/bin/gofmt && \
apt-get clean && rm -rf /var/lib/apt/lists/*
WORKDIR /go/src/github.com/ollama/ollama/
COPY . .
ARG CGO_CFLAGS
ENV GOARCH arm64
ARG VERSION
FROM base AS cuda-11
ARG CUDA11VERSION=11.3
RUN yum install -y cuda-toolkit-${CUDA11VERSION//./-}
ENV PATH=/usr/local/cuda-11/bin:$PATH
RUN --mount=type=cache,target=/root/.ccache \
make -j 5 dist_cuda_v11 \
CUDA_ARCHITECTURES="72;87" \
GPU_RUNNER_VARIANT=_jetpack5 \
DIST_LIB_DIR=/go/src/github.com/ollama/ollama/dist/linux-arm64-jetpack5/lib/ollama \
DIST_GPU_RUNNER_DEPS_DIR=/go/src/github.com/ollama/ollama/dist/linux-arm64-jetpack5/lib/ollama/cuda_jetpack5
cmake --preset 'CUDA 11' && cmake --build --parallel --preset 'CUDA 11'
FROM --platform=linux/arm64 nvcr.io/nvidia/l4t-jetpack:${JETPACK_6} AS runners-jetpack6-arm64
ARG GOLANG_VERSION
RUN apt-get update && apt-get install -y git curl ccache && \
curl -s -L https://dl.google.com/go/go${GOLANG_VERSION}.linux-arm64.tar.gz | tar xz -C /usr/local && \
ln -s /usr/local/go/bin/go /usr/local/bin/go && \
ln -s /usr/local/go/bin/gofmt /usr/local/bin/gofmt && \
apt-get clean && rm -rf /var/lib/apt/lists/*
WORKDIR /go/src/github.com/ollama/ollama/
COPY . .
ARG CGO_CFLAGS
ENV GOARCH arm64
ARG VERSION
FROM base AS cuda-12
ARG CUDA12VERSION=12.4
RUN yum install -y cuda-toolkit-${CUDA12VERSION//./-}
ENV PATH=/usr/local/cuda-12/bin:$PATH
RUN --mount=type=cache,target=/root/.ccache \
make -j 5 dist_cuda_v12 \
CUDA_ARCHITECTURES="87" \
GPU_RUNNER_VARIANT=_jetpack6 \
DIST_LIB_DIR=/go/src/github.com/ollama/ollama/dist/linux-arm64-jetpack6/lib/ollama \
DIST_GPU_RUNNER_DEPS_DIR=/go/src/github.com/ollama/ollama/dist/linux-arm64-jetpack6/lib/ollama/cuda_jetpack6
cmake --preset 'CUDA 12' && cmake --build --parallel --preset 'CUDA 12'
FROM --platform=linux/arm64 unified-builder-arm64 AS build-arm64
COPY . .
ARG OLLAMA_SKIP_CUDA_GENERATE
ARG OLLAMA_FAST_BUILD
ARG VERSION
FROM base AS rocm-6
RUN --mount=type=cache,target=/root/.ccache \
make -j 5 dist
COPY --from=runners-jetpack5-arm64 /go/src/github.com/ollama/ollama/dist/ dist/
COPY --from=runners-jetpack6-arm64 /go/src/github.com/ollama/ollama/dist/ dist/
RUN cd dist/linux-$GOARCH && \
tar -cf - . | pigz --best > ../ollama-linux-$GOARCH.tgz
RUN cd dist/linux-$GOARCH-jetpack5 && \
tar -cf - . | pigz --best > ../ollama-linux-$GOARCH-jetpack5.tgz
RUN cd dist/linux-$GOARCH-jetpack6 && \
tar -cf - . | pigz --best > ../ollama-linux-$GOARCH-jetpack6.tgz
cmake --preset 'ROCm 6' && cmake --build --parallel --preset 'ROCm 6'
FROM --platform=linux/amd64 scratch AS dist-amd64
COPY --from=build-amd64 /go/src/github.com/ollama/ollama/dist/ollama-linux-*.tgz /
FROM --platform=linux/arm64 scratch AS dist-arm64
COPY --from=build-arm64 /go/src/github.com/ollama/ollama/dist/ollama-linux-*.tgz /
FROM dist-$TARGETARCH AS dist
FROM --platform=linux/arm64 nvcr.io/nvidia/l4t-jetpack:${JETPACK5VERSION} AS jetpack-5
ARG CMAKEVERSION
RUN apt-get update && apt-get install -y curl ccache \
&& curl -fsSL https://github.com/Kitware/CMake/releases/download/v${CMAKEVERSION}/cmake-${CMAKEVERSION}-linux-$(uname -m).tar.gz | tar xz -C /usr/local --strip-components 1
COPY CMakeLists.txt CMakePresets.json .
COPY ml/backend/ggml/ggml ml/backend/ggml/ggml
RUN --mount=type=cache,target=/root/.ccache \
cmake --preset 'JetPack 5' && cmake --build --parallel --preset 'JetPack 5'
FROM --platform=linux/arm64 nvcr.io/nvidia/l4t-jetpack:${JETPACK6VERSION} AS jetpack-6
ARG CMAKEVERSION
RUN apt-get update && apt-get install -y curl ccache \
&& curl -fsSL https://github.com/Kitware/CMake/releases/download/v${CMAKEVERSION}/cmake-${CMAKEVERSION}-linux-$(uname -m).tar.gz | tar xz -C /usr/local --strip-components 1
COPY CMakeLists.txt CMakePresets.json .
COPY ml/backend/ggml/ggml ml/backend/ggml/ggml
RUN --mount=type=cache,target=/root/.ccache \
cmake --preset 'JetPack 6' && cmake --build --parallel --preset 'JetPack 6'
# For amd64 container images, filter out cuda/rocm to minimize size
FROM build-amd64 AS runners-cuda-amd64
RUN rm -rf \
./dist/linux-amd64/lib/ollama/libggml_hipblas.so \
./dist/linux-amd64/lib/ollama/runners/rocm*
FROM base AS build
ARG GOVERSION=1.23.4
RUN curl -fsSL https://golang.org/dl/go${GOVERSION}.linux-$(case $(uname -m) in x86_64) echo amd64 ;; aarch64) echo arm64 ;; esac).tar.gz | tar xz -C /usr/local
ENV PATH=/usr/local/go/bin:$PATH
WORKDIR /go/src/github.com/ollama/ollama
COPY . .
ARG GOFLAGS="'-ldflags=-w -s'"
ENV CGO_ENABLED=1
RUN --mount=type=cache,target=/root/.cache/go-build \
go build -trimpath -buildmode=pie -o /bin/ollama .
FROM build-amd64 AS runners-rocm-amd64
RUN rm -rf \
./dist/linux-amd64/lib/ollama/libggml_cuda*.so \
./dist/linux-amd64/lib/ollama/libcu*.so* \
./dist/linux-amd64/lib/ollama/runners/cuda*
FROM --platform=linux/amd64 scratch AS amd64
COPY --from=cuda-11 --chmod=644 \
dist/build/lib/libggml-cuda.so \
/usr/local/cuda/lib64/libcublas.so.11 \
/usr/local/cuda/lib64/libcublasLt.so.11 \
/usr/local/cuda/lib64/libcudart.so.11.0 \
/lib/ollama/cuda_v11/
COPY --from=cuda-12 --chmod=644 \
dist/build/lib/libggml-cuda.so \
/usr/local/cuda/lib64/libcublas.so.12 \
/usr/local/cuda/lib64/libcublasLt.so.12 \
/usr/local/cuda/lib64/libcudart.so.12 \
/lib/ollama/cuda_v12/
FROM --platform=linux/amd64 ubuntu:22.04 AS runtime-amd64
RUN apt-get update && \
apt-get install -y ca-certificates && \
apt-get clean && rm -rf /var/lib/apt/lists/*
COPY --from=build-amd64 /go/src/github.com/ollama/ollama/dist/linux-amd64/bin/ /bin/
COPY --from=runners-cuda-amd64 /go/src/github.com/ollama/ollama/dist/linux-amd64/lib/ /lib/
FROM --platform=linux/arm64 scratch AS arm64
COPY --from=cuda-11 --chmod=644 \
dist/build/lib/libggml-cuda.so \
/usr/local/cuda/lib64/libcublas.so.11 \
/usr/local/cuda/lib64/libcublasLt.so.11 \
/usr/local/cuda/lib64/libcudart.so.11.0 \
/lib/ollama/cuda_v11/
COPY --from=cuda-12 --chmod=644 \
dist/build/lib/libggml-cuda.so \
/usr/local/cuda/lib64/libcublas.so.12 \
/usr/local/cuda/lib64/libcublasLt.so.12 \
/usr/local/cuda/lib64/libcudart.so.12 \
/lib/ollama/cuda_v12/
COPY --from=jetpack-5 --chmod=644 \
dist/build/lib/libggml-cuda.so \
/usr/local/cuda/lib64/libcublas.so.11 \
/usr/local/cuda/lib64/libcublasLt.so.11 \
/usr/local/cuda/lib64/libcudart.so.11.0 \
/lib/ollama/cuda_jetpack5/
COPY --from=jetpack-6 --chmod=644 \
dist/build/lib/libggml-cuda.so \
/usr/local/cuda/lib64/libcublas.so.12 \
/usr/local/cuda/lib64/libcublasLt.so.12 \
/usr/local/cuda/lib64/libcudart.so.12 \
/lib/ollama/cuda_jetpack6/
FROM --platform=linux/arm64 ubuntu:22.04 AS runtime-arm64
RUN apt-get update && \
apt-get install -y ca-certificates && \
apt-get clean && rm -rf /var/lib/apt/lists/*
COPY --from=build-arm64 /go/src/github.com/ollama/ollama/dist/linux-arm64/bin/ /bin/
COPY --from=build-arm64 /go/src/github.com/ollama/ollama/dist/linux-arm64/lib/ /lib/
COPY --from=runners-jetpack5-arm64 /go/src/github.com/ollama/ollama/dist/linux-arm64-jetpack5/lib/ /lib/
COPY --from=runners-jetpack6-arm64 /go/src/github.com/ollama/ollama/dist/linux-arm64-jetpack6/lib/ /lib/
FROM --platform=linux/arm64 scratch AS rocm
COPY --from=rocm-6 --chmod=644 \
dist/build/lib/libggml-hip.so \
/opt/rocm/lib/libamdhip64.so.6 \
/opt/rocm/lib/libhipblas.so.2 \
/opt/rocm/lib/librocblas.so.4 \
/opt/rocm/lib/libamd_comgr.so.2 \
/opt/rocm/lib/libhsa-runtime64.so.1 \
/opt/rocm/lib/librocprofiler-register.so.0 \
/opt/amdgpu/lib64/libdrm_amdgpu.so.1 \
/opt/amdgpu/lib64/libdrm.so.2 \
/usr/lib64/libnuma.so.1 \
/lib/ollama/rocm/
COPY --from=rocm-6 /opt/rocm/lib/rocblas/ /lib/ollama/rocm/rocblas/
FROM ${FLAVOR} AS archive
COPY --from=cpu --chmod=644 \
dist/build/lib/libggml-base.so \
dist/build/lib/libggml-cpu-*.so \
/lib/ollama/
COPY --from=build /bin/ollama /bin/ollama
# ROCm libraries larger so we keep it distinct from the CPU/CUDA image
FROM --platform=linux/amd64 ubuntu:22.04 AS runtime-rocm
# Frontload the rocm libraries which are large, and rarely change to increase chance of a common layer
# across releases
COPY --from=build-amd64 /go/src/github.com/ollama/ollama/dist/linux-amd64-rocm/lib/ /lib/
RUN apt-get update && \
apt-get install -y ca-certificates && \
apt-get clean && rm -rf /var/lib/apt/lists/*
COPY --from=build-amd64 /go/src/github.com/ollama/ollama/dist/linux-amd64/bin/ /bin/
COPY --from=runners-rocm-amd64 /go/src/github.com/ollama/ollama/dist/linux-amd64/lib/ /lib/
EXPOSE 11434
ENV OLLAMA_HOST 0.0.0.0
ENTRYPOINT ["/bin/ollama"]
CMD ["serve"]
FROM runtime-$TARGETARCH
EXPOSE 11434
ENV OLLAMA_HOST 0.0.0.0
FROM ubuntu:20.04
RUN apt-get update \
&& apt-get install -y ca-certificates \
&& apt-get clean \
&& rm -rf /var/lib/apt/lists/*
COPY --from=archive /bin/ /usr/bin/
ENV PATH=/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin
ENV LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64
COPY --from=archive /lib/ollama/ /usr/lib/ollama/
ENV LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64:/usr/lib/ollama
ENV NVIDIA_DRIVER_CAPABILITIES=compute,utility
ENV NVIDIA_VISIBLE_DEVICES=all
ENV OLLAMA_HOST=0.0.0.0:11434
EXPOSE 11434
ENTRYPOINT ["/bin/ollama"]
CMD ["serve"]

103
Makefile
View File

@ -1,103 +0,0 @@
# top level makefile for Ollama
include make/common-defs.make
# Determine which if any GPU runners we should build
include make/cuda-v11-defs.make
include make/cuda-v12-defs.make
include make/rocm-defs.make
ifeq ($(CUSTOM_CPU_FLAGS),)
ifeq ($(ARCH),amd64)
RUNNER_TARGETS=cpu
endif
# Without CUSTOM_CPU_FLAGS we default to build both v11 and v12 if present
ifeq ($(OLLAMA_SKIP_CUDA_GENERATE),)
ifneq ($(CUDA_11_COMPILER),)
RUNNER_TARGETS += cuda_v11
endif
ifneq ($(CUDA_12_COMPILER),)
RUNNER_TARGETS += cuda_v12
endif
endif
else # CUSTOM_CPU_FLAGS is set, we'll build only the latest cuda version detected
ifneq ($(CUDA_12_COMPILER),)
RUNNER_TARGETS += cuda_v12
else ifneq ($(CUDA_11_COMPILER),)
RUNNER_TARGETS += cuda_v11
endif
endif
ifeq ($(OLLAMA_SKIP_ROCM_GENERATE),)
ifneq ($(HIP_COMPILER),)
RUNNER_TARGETS += rocm
endif
endif
all: runners exe
dist: $(addprefix dist_, $(RUNNER_TARGETS)) dist_exe
dist_%:
@$(MAKE) --no-print-directory -f make/Makefile.$* dist
runners: $(RUNNER_TARGETS)
$(RUNNER_TARGETS):
@$(MAKE) --no-print-directory -f make/Makefile.$@
exe dist_exe:
@$(MAKE) --no-print-directory -f make/Makefile.ollama $@
help-sync apply-patches create-patches sync sync-clean:
@$(MAKE) --no-print-directory -f make/Makefile.sync $@
test integration lint:
@$(MAKE) --no-print-directory -f make/Makefile.test $@
clean:
rm -rf $(BUILD_DIR) $(DIST_LIB_DIR) $(OLLAMA_EXE) $(DIST_OLLAMA_EXE)
go clean -cache
help:
@echo "The following make targets will help you build Ollama"
@echo ""
@echo " make all # (default target) Build Ollama llm subprocess runners, and the primary ollama executable"
@echo " make runners # Build Ollama llm subprocess runners; after you may use 'go build .' to build the primary ollama exectuable"
@echo " make <runner> # Build specific runners. Enabled: '$(RUNNER_TARGETS)'"
@echo " make dist # Build the runners and primary ollama executable for distribution"
@echo " make help-sync # Help information on vendor update targets"
@echo " make help-runners # Help information on runner targets"
@echo ""
@echo "The following make targets will help you test Ollama"
@echo ""
@echo " make test # Run unit tests"
@echo " make integration # Run integration tests. You must 'make all' first"
@echo " make lint # Run lint and style tests"
@echo ""
@echo "For more information see 'docs/development.md'"
@echo ""
help-runners:
@echo "The following runners will be built based on discovered GPU libraries: '$(RUNNER_TARGETS)'"
@echo ""
@echo "GPU Runner CPU Flags: '$(GPU_RUNNER_CPU_FLAGS)' (Override with CUSTOM_CPU_FLAGS)"
@echo ""
@echo "# CUDA_PATH sets the location where CUDA toolkits are present"
@echo "CUDA_PATH=$(CUDA_PATH)"
@echo " CUDA_11_PATH=$(CUDA_11_PATH)"
@echo " CUDA_11_COMPILER=$(CUDA_11_COMPILER)"
@echo " CUDA_12_PATH=$(CUDA_12_PATH)"
@echo " CUDA_12_COMPILER=$(CUDA_12_COMPILER)"
@echo ""
@echo "# HIP_PATH sets the location where the ROCm toolkit is present"
@echo "HIP_PATH=$(HIP_PATH)"
@echo " HIP_COMPILER=$(HIP_COMPILER)"
.PHONY: all exe dist help help-sync help-runners test integration lint runners clean $(RUNNER_TARGETS)
# Handy debugging for make variables
print-%:
@echo '$*=$($*)'

46
Makefile2 Normal file
View File

@ -0,0 +1,46 @@
UPSTREAM=https://github.com/ggerganov/llama.cpp.git
WORKDIR=llama/vendor
FETCH_HEAD=46e3556e01b824e52395fb050b29804b6cff2a7c
all: sync
.PHONY: sync
sync: llama/llama.cpp ml/backend/ggml/ggml
.PHONY: llama/llama.cpp
llama/llama.cpp: llama/vendor/ apply_patches
rsync -arvzc -f "merge $@/.rsync-filter" $< $@
.PHONY: ml/backend/ggml/ggml apply_patches
ml/backend/ggml/ggml: llama/vendor/ggml/ apply_patches
rsync -arvzc -f "merge $@/.rsync-filter" $< $@
PATCHES=$(wildcard llama/patches/*.patch)
.PHONY: apply_patches
.NOTPARALLEL:
apply_patches: $(addsuffix ed, $(PATCHES))
%.patched: %.patch
@if git -c user.name=nobody -c 'user.email=<>' -C $(WORKDIR) am -3 $(realpath $<); then touch $@; else git -C $(WORKDIR) am --abort; exit 1; fi
.PHONY: checkout
checkout: $(WORKDIR)
git -C $(WORKDIR) fetch
git -C $(WORKDIR) checkout -f $(FETCH_HEAD)
$(WORKDIR):
git clone $(UPSTREAM) $(WORKDIR)
.PHONE: format_patches
format_patches: llama/patches
git -C $(WORKDIR) format-patch \
--no-signature \
--no-numbered \
--zero-commit \
-o $(realpath $<) \
$(FETCH_HEAD)
.PHONE: clean
clean: checkout
$(RM) $(addsuffix ed, $(PATCHES))

384
cache/cache.go vendored Normal file
View File

@ -0,0 +1,384 @@
package cache
import (
"errors"
"fmt"
"log/slog"
"math"
"slices"
"github.com/ollama/ollama/ml"
)
var ErrNotSupported = errors.New("model does not support operation")
type Cache interface {
// used by model implementations
Sub(i int) Cache
Put(ctx ml.Context, key, value ml.Tensor) (ml.Tensor, ml.Tensor, ml.Tensor)
// cache management
Close()
StartForward(ctx ml.Context, seqs []int) error
CopyPrefix(srcSeq, dstSeq int, len int)
Remove(seq int, beginIndex, endIndex int) error
}
type Causal struct {
DType ml.DType
Capacity int
// current forward pass
curLayer int
curPos int
curBatchSize int
curMask ml.Tensor
curCellRange cellRange
// metadata
cells []cacheCell
seqNextPos map[int]int
cellRanges map[int]cellRange
// cache data storage
backend ml.Backend
cacheCtx ml.Context
keys, values []ml.Tensor
}
type seqCell struct {
seq int
pos int
}
type cacheCell struct {
sequences []seqCell
}
type cellRange struct {
min int
max int
}
func (cell cacheCell) findSeq(seq int) *seqCell {
for i := range cell.sequences {
if cell.sequences[i].seq == seq {
return &cell.sequences[i]
}
}
return nil
}
func NewCausalCache(backend ml.Backend, capacity int, dtype ml.DType) Cache {
return &Causal{
Capacity: capacity,
DType: dtype,
cells: make([]cacheCell, capacity),
seqNextPos: make(map[int]int),
cellRanges: make(map[int]cellRange),
backend: backend,
// TODO(jessegross): This context is not sized appropriately
cacheCtx: backend.NewContext(),
}
}
func (c *Causal) Close() {
c.cacheCtx.Close()
}
var ErrKvCacheFull = errors.New("could not find a kv cache slot")
func (c *Causal) StartForward(ctx ml.Context, seqs []int) error {
c.curBatchSize = len(seqs)
var err error
c.curPos, err = c.findStartPos()
if errors.Is(err, ErrKvCacheFull) {
c.defrag()
c.curPos, err = c.findStartPos()
}
if err != nil {
return err
}
// TODO(jessegross): There should be a better way to do this
origSeq := make(map[int]int)
for k, v := range c.seqNextPos {
origSeq[k] = v
}
c.curCellRange = newRange()
for i, seq := range seqs {
c.cells[c.curPos+i] = cacheCell{sequences: []seqCell{{seq: seq, pos: c.seqNextPos[seq]}}}
c.seqNextPos[seq]++
ranges := c.cellRanges[seq]
if c.curPos+i > ranges.max {
ranges.max = c.curPos + i
}
if ranges.max > c.curCellRange.max {
c.curCellRange.max = ranges.max
}
if c.curPos+i < ranges.min {
ranges.min = c.curPos + i
}
if ranges.min < c.curCellRange.min {
c.curCellRange.min = ranges.min
}
c.cellRanges[seq] = ranges
}
c.curMask, err = c.buildMask(ctx, origSeq, seqs)
return err
}
func newRange() cellRange {
return cellRange{
min: math.MaxInt,
max: 0,
}
}
func (c *Causal) findStartPos() (int, error) {
var start, count int
for i := range c.cells {
if len(c.cells[i].sequences) == 0 {
count++
if count >= c.curBatchSize {
return start, nil
}
} else {
start = i + 1
count = 0
}
}
return 0, fmt.Errorf("%w (length: %v)", ErrKvCacheFull, c.Capacity)
}
func (c *Causal) buildMask(ctx ml.Context, origSeq map[int]int, seqs []int) (ml.Tensor, error) {
// TODO(jessegross): This makes a number of simplifications such as no padding
len := c.curCellRange.max - c.curCellRange.min
mask := make([]float32, c.curBatchSize*len)
for i := range c.curBatchSize {
for j := c.curCellRange.min; j < c.curCellRange.max; j++ {
cellSeq := c.cells[j].findSeq(seqs[i])
if cellSeq == nil || cellSeq.pos > origSeq[seqs[i]]+i {
mask[i*len+(j-c.curCellRange.min)] = float32(math.Inf(-1))
}
}
}
return ctx.FromFloatSlice(mask, len, c.curBatchSize)
}
func moveCell(ctx ml.Context, objs []ml.Tensor, src, dst, len int) {
for _, obj := range objs {
srcView := obj.View(ctx, int(obj.Stride(2))*src, int(obj.Dim(0)*obj.Dim(1))*len)
dstView := obj.View(ctx, int(obj.Stride(2))*dst, int(obj.Dim(0)*obj.Dim(1))*len)
ctx.Forward(srcView.Copy(ctx, dstView))
}
}
func (c *Causal) defrag() {
slog.Debug("defragmenting kv cache")
// Defrag strategy:
// - Search for empty holes at the beginning of the cache,
// filling them with active data starting at the end
// - If there are contiguous elements that need to be moved,
// combine them into a single operation by holding new moves
// until we see the next one is non-contiguous
// - Fill up the context with the maximum number of operations it
// can hold then compute that and continue with a new context
// TODO(jessegross):
// - Need to size the context and compute maxMoves correctly
// - Just compacts, doesn't optimize placement
maxMoves := 8192 / (6 * len(c.keys))
ctx := c.backend.NewContext()
moves := 0
var pendingSrc, pendingDst, pendingLen int
for dst := range c.cells {
if len(c.cells[dst].sequences) == 0 {
for src := len(c.cells) - 1; src > dst; src-- {
if len(c.cells[src].sequences) != 0 {
c.cells[dst] = c.cells[src]
c.cells[src] = cacheCell{}
if pendingLen > 0 {
if src == pendingSrc-pendingLen && dst == pendingDst+pendingLen {
pendingSrc = src
pendingLen++
break
} else {
moveCell(ctx, c.keys, pendingSrc, pendingDst, pendingLen)
moveCell(ctx, c.values, pendingSrc, pendingDst, pendingLen)
moves++
}
}
pendingSrc = src
pendingDst = dst
pendingLen = 1
break
}
}
}
if moves >= maxMoves {
ctx.Compute(nil)
ctx.Close()
ctx = c.backend.NewContext()
moves = 0
}
}
if pendingLen > 0 {
moveCell(ctx, c.keys, pendingSrc, pendingDst, pendingLen)
moveCell(ctx, c.values, pendingSrc, pendingDst, pendingLen)
moves++
}
if moves > 0 {
ctx.Compute(nil)
}
ctx.Close()
for seq := range c.cellRanges {
seqRange := newRange()
for i, cell := range c.cells {
if cell.findSeq(seq) != nil {
if i < seqRange.min {
seqRange.min = i
}
if i > seqRange.max {
seqRange.max = i
}
}
}
c.cellRanges[seq] = seqRange
}
}
func (c *Causal) Sub(i int) Cache {
if i >= len(c.keys) {
c.keys = append(c.keys, make([]ml.Tensor, i-len(c.keys)+1)...)
c.values = append(c.values, make([]ml.Tensor, i-len(c.values)+1)...)
}
c.curLayer = i
return c
}
func (c *Causal) Put(ctx ml.Context, key, value ml.Tensor) (ml.Tensor, ml.Tensor, ml.Tensor) {
if c.curBatchSize != int(key.Dim(2)) {
panic(fmt.Errorf("inconsistent batch sizes (layer: %v, batch size: %v layer batch size: %v)", c.curLayer, c.curBatchSize, int(key.Dim(2))))
}
if c.keys[c.curLayer] == nil || c.values[c.curLayer] == nil {
c.keys[c.curLayer] = c.cacheCtx.Zeros(c.DType, key.Dim(0), key.Dim(1), int64(c.Capacity))
c.values[c.curLayer] = c.cacheCtx.Zeros(c.DType, value.Dim(0), value.Dim(1), int64(c.Capacity))
}
ctx.Forward(key.Copy(ctx, c.keys[c.curLayer].View(ctx, int(key.Stride(2))*c.curPos, int(key.Dim(0)*key.Dim(1)*key.Dim(2)))))
ctx.Forward(value.Copy(ctx, c.values[c.curLayer].View(ctx, int(value.Stride(2))*c.curPos, int(value.Dim(0)*value.Dim(1)*value.Dim(2)))))
len := c.curCellRange.max - c.curCellRange.min
key = c.keys[c.curLayer].View(ctx, int(key.Stride(2))*c.curCellRange.min,
int(key.Dim(0)), int(key.Stride(1)),
int(key.Dim(1)), int(key.Stride(2)),
len,
)
value = c.values[c.curLayer].View(ctx, int(key.Stride(2))*c.curCellRange.min,
int(value.Dim(0)), int(value.Stride(1)),
int(value.Dim(1)), int(value.Stride(2)),
len,
)
return key, value, c.curMask
}
func (c *Causal) CopyPrefix(srcSeq, dstSeq int, len int) {
seqRange := newRange()
for i := range c.cells {
srcCellSeq := c.cells[i].findSeq(srcSeq)
dstCellSeq := c.cells[i].findSeq(dstSeq)
if dstCellSeq != nil {
c.cells[i].sequences = slices.DeleteFunc(c.cells[i].sequences, func(s seqCell) bool { return s.seq == dstSeq })
}
if srcCellSeq != nil && srcCellSeq.pos < len {
c.cells[i].sequences = append(c.cells[i].sequences, seqCell{seq: dstSeq, pos: srcCellSeq.pos})
if i < seqRange.min {
seqRange.min = i
}
if i > seqRange.max {
seqRange.max = i
}
}
}
c.cellRanges[dstSeq] = seqRange
c.seqNextPos[dstSeq] = len
}
func (c *Causal) shift(seq int, beginIndex, endIndex, offset int) error {
panic("Shift not yet implemented")
}
func (c *Causal) Remove(seq int, beginIndex, endIndex int) error {
endIndex = min(endIndex, c.seqNextPos[seq])
offset := beginIndex - endIndex
seqRange := newRange()
for i := range c.cells {
cellSeq := c.cells[i].findSeq(seq)
if cellSeq != nil {
if cellSeq.pos >= beginIndex && cellSeq.pos < endIndex {
c.cells[i].sequences = slices.DeleteFunc(c.cells[i].sequences, func(s seqCell) bool { return s.seq == seq })
} else {
if cellSeq.pos >= endIndex {
cellSeq.pos += offset
}
if i < seqRange.min {
seqRange.min = i
}
if i > seqRange.max {
seqRange.max = i
}
}
}
}
if endIndex != c.seqNextPos[seq] {
err := c.shift(seq, endIndex, c.seqNextPos[seq], offset)
if err != nil {
return err
}
}
c.cellRanges[seq] = seqRange
c.seqNextPos[seq] += offset
return nil
}

48
cache/tensor.go vendored Normal file
View File

@ -0,0 +1,48 @@
package cache
import (
"github.com/ollama/ollama/ml"
)
type TensorCache struct {
curLayer int
cacheCtx ml.Context
keys, values []ml.Tensor
}
func NewTensorCache(backend ml.Backend) *TensorCache {
return &TensorCache{
// TODO(jessegross): This context is not sized appropriately
cacheCtx: backend.NewContext(),
}
}
func (c *TensorCache) Close() {
c.cacheCtx.Close()
}
func (c *TensorCache) Sub(i int) *TensorCache {
if i >= len(c.keys) {
c.keys = append(c.keys, make([]ml.Tensor, i-len(c.keys)+1)...)
c.values = append(c.values, make([]ml.Tensor, i-len(c.values)+1)...)
}
c.curLayer = i
return c
}
func (c *TensorCache) Get(ctx ml.Context) (ml.Tensor, ml.Tensor, ml.Tensor) {
return c.keys[c.curLayer], c.values[c.curLayer], nil
}
func (c *TensorCache) Put(ctx ml.Context, key, value ml.Tensor) {
if c.keys[c.curLayer] == nil || c.values[c.curLayer] == nil {
c.keys[c.curLayer] = c.cacheCtx.Zeros(key.DType(), key.Shape()...)
c.values[c.curLayer] = c.cacheCtx.Zeros(value.DType(), value.Shape()...)
}
ctx.Forward(key.Copy(ctx, c.keys[c.curLayer]))
ctx.Forward(value.Copy(ctx, c.values[c.curLayer]))
}

View File

@ -35,9 +35,9 @@ import (
"github.com/ollama/ollama/envconfig"
"github.com/ollama/ollama/format"
"github.com/ollama/ollama/llama"
"github.com/ollama/ollama/llama/runner"
"github.com/ollama/ollama/parser"
"github.com/ollama/ollama/progress"
"github.com/ollama/ollama/runner"
"github.com/ollama/ollama/server"
"github.com/ollama/ollama/types/model"
"github.com/ollama/ollama/version"
@ -338,7 +338,7 @@ func RunHandler(cmd *cobra.Command, args []string) error {
return err
}
opts.MultiModal = len(info.ProjectorInfo) != 0
opts.MultiModal = true //len(info.ProjectorInfo) != 0
opts.ParentModel = info.Details.ParentModel
if interactive {

View File

@ -4,7 +4,7 @@ import (
"fmt"
"os"
"github.com/ollama/ollama/llama/runner"
"github.com/ollama/ollama/runner"
)
func main() {

View File

@ -9,7 +9,7 @@ import (
"log/slog"
"strings"
"github.com/ollama/ollama/llm"
"github.com/ollama/ollama/fs/ggml"
)
type ModelParameters struct {
@ -27,8 +27,8 @@ type AdapterParameters struct {
} `json:"lora_parameters"`
}
func (ModelParameters) KV(t *Tokenizer) llm.KV {
kv := llm.KV{
func (ModelParameters) KV(t *Tokenizer) ggml.KV {
kv := ggml.KV{
"general.file_type": uint32(1),
"general.quantization_version": uint32(2),
"tokenizer.ggml.pre": t.Pre,
@ -54,7 +54,7 @@ func (ModelParameters) KV(t *Tokenizer) llm.KV {
return kv
}
func (p AdapterParameters) KV() llm.KV {
func (p AdapterParameters) KV() ggml.KV {
var alpha float32
if p.LoraParameters.Alpha == 0 {
alpha = float32(p.Alpha)
@ -62,7 +62,7 @@ func (p AdapterParameters) KV() llm.KV {
alpha = p.LoraParameters.Alpha
}
kv := llm.KV{
kv := ggml.KV{
"adapter.lora.alpha": alpha,
"adapter.type": "lora",
"general.file_type": uint32(1),
@ -79,19 +79,19 @@ func (ModelParameters) specialTokenTypes() []string {
}
}
func (ModelParameters) writeFile(ws io.WriteSeeker, kv llm.KV, ts []llm.Tensor) error {
return llm.WriteGGUF(ws, kv, ts)
func (ModelParameters) writeFile(ws io.WriteSeeker, kv ggml.KV, ts []ggml.Tensor) error {
return ggml.WriteGGUF(ws, kv, ts)
}
func (AdapterParameters) writeFile(ws io.WriteSeeker, kv llm.KV, ts []llm.Tensor) error {
return llm.WriteGGUF(ws, kv, ts)
func (AdapterParameters) writeFile(ws io.WriteSeeker, kv ggml.KV, ts []ggml.Tensor) error {
return ggml.WriteGGUF(ws, kv, ts)
}
type ModelConverter interface {
// KV maps parameters to LLM key-values
KV(*Tokenizer) llm.KV
KV(*Tokenizer) ggml.KV
// Tensors maps input tensors to LLM tensors. Model specific modifications can be done here.
Tensors([]Tensor) []llm.Tensor
Tensors([]Tensor) []ggml.Tensor
// Replacements returns a list of string pairs to replace in tensor names.
// See [strings.Replacer](https://pkg.go.dev/strings#Replacer) for details
Replacements() []string
@ -99,7 +99,7 @@ type ModelConverter interface {
// specialTokenTypes returns any special token types the model uses
specialTokenTypes() []string
// writeFile writes the model to the provided io.WriteSeeker
writeFile(io.WriteSeeker, llm.KV, []llm.Tensor) error
writeFile(io.WriteSeeker, ggml.KV, []ggml.Tensor) error
}
type moreParser interface {
@ -108,17 +108,17 @@ type moreParser interface {
type AdapterConverter interface {
// KV maps parameters to LLM key-values
KV(llm.KV) llm.KV
KV(ggml.KV) ggml.KV
// Tensors maps input tensors to LLM tensors. Adapter specific modifications can be done here.
Tensors([]Tensor) []llm.Tensor
Tensors([]Tensor) []ggml.Tensor
// Replacements returns a list of string pairs to replace in tensor names.
// See [strings.Replacer](https://pkg.go.dev/strings#Replacer) for details
Replacements() []string
writeFile(io.WriteSeeker, llm.KV, []llm.Tensor) error
writeFile(io.WriteSeeker, ggml.KV, []ggml.Tensor) error
}
func ConvertAdapter(fsys fs.FS, ws io.WriteSeeker, baseKV llm.KV) error {
func ConvertAdapter(fsys fs.FS, ws io.WriteSeeker, baseKV ggml.KV) error {
bts, err := fs.ReadFile(fsys, "adapter_config.json")
if err != nil {
return err

View File

@ -8,7 +8,7 @@ import (
"slices"
"strings"
"github.com/ollama/ollama/llm"
"github.com/ollama/ollama/fs/ggml"
)
type bertModel struct {
@ -85,7 +85,7 @@ func (p *bertModel) parseMore(fsys fs.FS) error {
return nil
}
func (p *bertModel) KV(t *Tokenizer) llm.KV {
func (p *bertModel) KV(t *Tokenizer) ggml.KV {
kv := p.ModelParameters.KV(t)
kv["general.architecture"] = "bert"
kv["bert.attention.causal"] = false
@ -132,8 +132,8 @@ func (p *bertModel) KV(t *Tokenizer) llm.KV {
return kv
}
func (p *bertModel) Tensors(ts []Tensor) []llm.Tensor {
var out []llm.Tensor
func (p *bertModel) Tensors(ts []Tensor) []ggml.Tensor {
var out []ggml.Tensor
for _, t := range ts {
if slices.Contains([]string{
"embeddings.position_ids",
@ -143,7 +143,7 @@ func (p *bertModel) Tensors(ts []Tensor) []llm.Tensor {
continue
}
out = append(out, llm.Tensor{
out = append(out, ggml.Tensor{
Name: t.Name(),
Kind: t.Kind(),
Shape: t.Shape(),

View File

@ -3,7 +3,7 @@ package convert
import (
"cmp"
"github.com/ollama/ollama/llm"
"github.com/ollama/ollama/fs/ggml"
)
type commandrModel struct {
@ -24,7 +24,7 @@ type commandrModel struct {
var _ ModelConverter = (*commandrModel)(nil)
func (p *commandrModel) KV(t *Tokenizer) llm.KV {
func (p *commandrModel) KV(t *Tokenizer) ggml.KV {
kv := p.ModelParameters.KV(t)
kv["general.architecture"] = "command-r"
kv["general.name"] = "command-r"
@ -43,10 +43,10 @@ func (p *commandrModel) KV(t *Tokenizer) llm.KV {
return kv
}
func (p *commandrModel) Tensors(ts []Tensor) []llm.Tensor {
var out []llm.Tensor
func (p *commandrModel) Tensors(ts []Tensor) []ggml.Tensor {
var out []ggml.Tensor
for _, t := range ts {
out = append(out, llm.Tensor{
out = append(out, ggml.Tensor{
Name: t.Name(),
Kind: t.Kind(),
Shape: t.Shape(),

View File

@ -6,7 +6,7 @@ import (
"github.com/pdevine/tensor"
"github.com/pdevine/tensor/native"
"github.com/ollama/ollama/llm"
"github.com/ollama/ollama/fs/ggml"
)
type gemmaModel struct {
@ -23,7 +23,7 @@ type gemmaModel struct {
var _ ModelConverter = (*gemmaModel)(nil)
func (p *gemmaModel) KV(t *Tokenizer) llm.KV {
func (p *gemmaModel) KV(t *Tokenizer) ggml.KV {
kv := p.ModelParameters.KV(t)
kv["general.architecture"] = "gemma"
kv["gemma.context_length"] = p.MaxPositionEmbeddings
@ -42,14 +42,14 @@ func (p *gemmaModel) KV(t *Tokenizer) llm.KV {
return kv
}
func (p *gemmaModel) Tensors(ts []Tensor) []llm.Tensor {
var out []llm.Tensor
func (p *gemmaModel) Tensors(ts []Tensor) []ggml.Tensor {
var out []ggml.Tensor
for _, t := range ts {
if strings.HasSuffix(t.Name(), "_norm.weight") {
t.SetRepacker(p.addOne)
}
out = append(out, llm.Tensor{
out = append(out, ggml.Tensor{
Name: t.Name(),
Kind: t.Kind(),
Shape: t.Shape(),

View File

@ -1,8 +1,6 @@
package convert
import (
"github.com/ollama/ollama/llm"
)
import "github.com/ollama/ollama/fs/ggml"
type gemma2Model struct {
gemmaModel
@ -11,7 +9,7 @@ type gemma2Model struct {
FinalLogitSoftcap float32 `json:"final_logit_softcapping"`
}
func (p *gemma2Model) KV(t *Tokenizer) llm.KV {
func (p *gemma2Model) KV(t *Tokenizer) ggml.KV {
kv := p.ModelParameters.KV(t)
kv["general.architecture"] = "gemma2"
kv["gemma2.context_length"] = p.MaxPositionEmbeddings

View File

@ -6,7 +6,7 @@ import (
"github.com/pdevine/tensor"
"github.com/pdevine/tensor/native"
"github.com/ollama/ollama/llm"
"github.com/ollama/ollama/fs/ggml"
)
type gemma2Adapter struct {
@ -15,14 +15,14 @@ type gemma2Adapter struct {
var _ AdapterConverter = (*gemma2Adapter)(nil)
func (p *gemma2Adapter) KV(baseKV llm.KV) llm.KV {
func (p *gemma2Adapter) KV(baseKV ggml.KV) ggml.KV {
kv := p.AdapterParameters.KV()
kv["general.architecture"] = "gemma2"
return kv
}
func (p *gemma2Adapter) Tensors(ts []Tensor) []llm.Tensor {
var out []llm.Tensor
func (p *gemma2Adapter) Tensors(ts []Tensor) []ggml.Tensor {
var out []ggml.Tensor
for _, t := range ts {
shape := t.Shape()
if (strings.HasSuffix(t.Name(), "weight.lora_a") && shape[0] > shape[1]) ||
@ -31,7 +31,7 @@ func (p *gemma2Adapter) Tensors(ts []Tensor) []llm.Tensor {
t.SetRepacker(p.repack)
}
out = append(out, llm.Tensor{
out = append(out, ggml.Tensor{
Name: t.Name(),
Kind: t.Kind(),
Shape: t.Shape(),

View File

@ -9,7 +9,7 @@ import (
"github.com/pdevine/tensor"
"github.com/pdevine/tensor/native"
"github.com/ollama/ollama/llm"
"github.com/ollama/ollama/fs/ggml"
)
type llamaModel struct {
@ -46,7 +46,7 @@ type llamaModel struct {
var _ ModelConverter = (*llamaModel)(nil)
func (p *llamaModel) KV(t *Tokenizer) llm.KV {
func (p *llamaModel) KV(t *Tokenizer) ggml.KV {
kv := p.ModelParameters.KV(t)
kv["general.architecture"] = "llama"
kv["llama.vocab_size"] = p.VocabSize
@ -120,11 +120,11 @@ func (p *llamaModel) KV(t *Tokenizer) llm.KV {
return kv
}
func (p *llamaModel) Tensors(ts []Tensor) []llm.Tensor {
var out []llm.Tensor
func (p *llamaModel) Tensors(ts []Tensor) []ggml.Tensor {
var out []ggml.Tensor
if p.RopeScaling.factors != nil {
out = append(out, llm.Tensor{
out = append(out, ggml.Tensor{
Name: "rope_freqs.weight",
Kind: 0,
Shape: []uint64{uint64(len(p.RopeScaling.factors))},
@ -138,7 +138,7 @@ func (p *llamaModel) Tensors(ts []Tensor) []llm.Tensor {
t.SetRepacker(p.repack)
}
out = append(out, llm.Tensor{
out = append(out, ggml.Tensor{
Name: t.Name(),
Kind: t.Kind(),
Shape: t.Shape(),

View File

@ -7,7 +7,7 @@ import (
"github.com/pdevine/tensor"
"github.com/pdevine/tensor/native"
"github.com/ollama/ollama/llm"
"github.com/ollama/ollama/fs/ggml"
)
type llamaAdapter struct {
@ -18,7 +18,7 @@ type llamaAdapter struct {
var _ AdapterConverter = (*llamaAdapter)(nil)
func (p *llamaAdapter) KV(baseKV llm.KV) llm.KV {
func (p *llamaAdapter) KV(baseKV ggml.KV) ggml.KV {
kv := p.AdapterParameters.KV()
kv["general.architecture"] = "llama"
kv["llama.attention.head_count"] = baseKV["llama.attention.head_count"]
@ -29,8 +29,8 @@ func (p *llamaAdapter) KV(baseKV llm.KV) llm.KV {
return kv
}
func (p *llamaAdapter) Tensors(ts []Tensor) []llm.Tensor {
var out []llm.Tensor
func (p *llamaAdapter) Tensors(ts []Tensor) []ggml.Tensor {
var out []ggml.Tensor
for _, t := range ts {
shape := t.Shape()
if (strings.HasSuffix(t.Name(), "weight.lora_a") && shape[0] > shape[1]) ||
@ -41,7 +41,7 @@ func (p *llamaAdapter) Tensors(ts []Tensor) []llm.Tensor {
t.SetRepacker(p.repack)
}
out = append(out, llm.Tensor{
out = append(out, ggml.Tensor{
Name: t.Name(),
Kind: t.Kind(),
Shape: shape,

View File

@ -6,7 +6,7 @@ import (
"slices"
"strings"
"github.com/ollama/ollama/llm"
"github.com/ollama/ollama/fs/ggml"
)
type mixtralModel struct {
@ -15,7 +15,7 @@ type mixtralModel struct {
NumExpertsPerToken uint32 `json:"num_experts_per_tok"`
}
func (p *mixtralModel) KV(t *Tokenizer) llm.KV {
func (p *mixtralModel) KV(t *Tokenizer) ggml.KV {
kv := p.llamaModel.KV(t)
if p.NumLocalExperts > 0 {
@ -29,7 +29,7 @@ func (p *mixtralModel) KV(t *Tokenizer) llm.KV {
return kv
}
func (p *mixtralModel) Tensors(ts []Tensor) []llm.Tensor {
func (p *mixtralModel) Tensors(ts []Tensor) []ggml.Tensor {
oldnew := []string{
"model.layers", "blk",
"w1", "ffn_gate_exps",
@ -56,10 +56,10 @@ func (p *mixtralModel) Tensors(ts []Tensor) []llm.Tensor {
return true
})
var out []llm.Tensor
var out []ggml.Tensor
for n, e := range experts {
// TODO(mxyng): sanity check experts
out = append(out, llm.Tensor{
out = append(out, ggml.Tensor{
Name: n,
Kind: e[0].Kind(),
Shape: append([]uint64{uint64(len(e))}, e[0].Shape()...),

View File

@ -8,7 +8,7 @@ import (
"strings"
"sync"
"github.com/ollama/ollama/llm"
"github.com/ollama/ollama/fs/ggml"
)
type phi3Model struct {
@ -37,7 +37,7 @@ type phi3Model struct {
var _ ModelConverter = (*phi3Model)(nil)
func (p *phi3Model) KV(t *Tokenizer) llm.KV {
func (p *phi3Model) KV(t *Tokenizer) ggml.KV {
kv := p.ModelParameters.KV(t)
kv["general.architecture"] = "phi3"
kv["phi3.context_length"] = p.MaxPositionEmbeddings
@ -68,19 +68,19 @@ func (p *phi3Model) KV(t *Tokenizer) llm.KV {
return kv
}
func (p *phi3Model) Tensors(ts []Tensor) []llm.Tensor {
func (p *phi3Model) Tensors(ts []Tensor) []ggml.Tensor {
var addRopeFactors sync.Once
out := make([]llm.Tensor, 0, len(ts)+2)
out := make([]ggml.Tensor, 0, len(ts)+2)
for _, t := range ts {
if strings.HasPrefix(t.Name(), "blk.0.") {
addRopeFactors.Do(func() {
out = append(out, llm.Tensor{
out = append(out, ggml.Tensor{
Name: "rope_factors_long.weight",
Kind: 0,
Shape: []uint64{uint64(len(p.RopeScaling.LongFactor))},
WriterTo: p.RopeScaling.LongFactor,
}, llm.Tensor{
}, ggml.Tensor{
Name: "rope_factors_short.weight",
Kind: 0,
Shape: []uint64{uint64(len(p.RopeScaling.ShortFactor))},
@ -89,7 +89,7 @@ func (p *phi3Model) Tensors(ts []Tensor) []llm.Tensor {
})
}
out = append(out, llm.Tensor{
out = append(out, ggml.Tensor{
Name: t.Name(),
Kind: t.Kind(),
Shape: t.Shape(),

View File

@ -1,6 +1,7 @@
package convert
import "github.com/ollama/ollama/llm"
import "github.com/ollama/ollama/fs/ggml"
type qwen2Model struct {
ModelParameters
@ -21,7 +22,7 @@ type qwen2Model struct {
var _ ModelConverter = (*qwen2Model)(nil)
func (q *qwen2Model) KV(t *Tokenizer) llm.KV {
func (q *qwen2Model) KV(t *Tokenizer) ggml.KV {
kv := q.ModelParameters.KV(t)
kv["general.architecture"] = "qwen2"
kv["qwen2.block_count"] = q.HiddenLayers
@ -45,10 +46,10 @@ func (q *qwen2Model) KV(t *Tokenizer) llm.KV {
return kv
}
func (q *qwen2Model) Tensors(ts []Tensor) []llm.Tensor {
var out []llm.Tensor
func (q *qwen2Model) Tensors(ts []Tensor) []ggml.Tensor {
var out []ggml.Tensor
for _, t := range ts {
out = append(out, llm.Tensor{
out = append(out, ggml.Tensor{
Name: t.Name(),
Kind: t.Kind(),
Shape: t.Shape(),

View File

@ -20,7 +20,7 @@ import (
"golang.org/x/exp/maps"
"github.com/ollama/ollama/llm"
"github.com/ollama/ollama/fs/ggml"
)
type tensorData struct {
@ -29,7 +29,7 @@ type tensorData struct {
Shape []int `json:"shape"`
}
func convertFull(t *testing.T, fsys fs.FS) (*os.File, llm.KV, *llm.Tensors) {
func convertFull(t *testing.T, fsys fs.FS) (*os.File, ggml.KV, ggml.Tensors) {
t.Helper()
f, err := os.CreateTemp(t.TempDir(), "f16")
@ -48,7 +48,7 @@ func convertFull(t *testing.T, fsys fs.FS) (*os.File, llm.KV, *llm.Tensors) {
}
t.Cleanup(func() { r.Close() })
m, _, err := llm.DecodeGGML(r, math.MaxInt)
m, _, err := ggml.Decode(r, math.MaxInt)
if err != nil {
t.Fatal(err)
}
@ -60,7 +60,7 @@ func convertFull(t *testing.T, fsys fs.FS) (*os.File, llm.KV, *llm.Tensors) {
return r, m.KV(), m.Tensors()
}
func generateResultsJSON(t *testing.T, f *os.File, kv llm.KV, tensors *llm.Tensors) map[string]string {
func generateResultsJSON(t *testing.T, f *os.File, kv ggml.KV, tensors ggml.Tensors) map[string]string {
actual := make(map[string]string)
for k, v := range kv {
if s, ok := v.(json.Marshaler); !ok {
@ -75,7 +75,7 @@ func generateResultsJSON(t *testing.T, f *os.File, kv llm.KV, tensors *llm.Tenso
}
}
for _, tensor := range tensors.Items {
for _, tensor := range tensors.Items() {
sha256sum := sha256.New()
sr := io.NewSectionReader(f, int64(tensors.Offset+tensor.Offset), int64(tensor.Size()))
if _, err := io.Copy(sha256sum, sr); err != nil {
@ -332,7 +332,7 @@ func TestConvertAdapter(t *testing.T) {
}
defer r.Close()
m, _, err := llm.DecodeGGML(r, math.MaxInt)
m, _, err := ggml.Decode(r, math.MaxInt)
if err != nil {
t.Fatal(err)
}

View File

@ -718,23 +718,18 @@ func (l GpuInfoList) GetVisibleDevicesEnv() (string, string) {
func LibraryDirs() []string {
// dependencies can exist wherever we found the runners (e.g. build tree for developers) and relative to the executable
// This can be simplified once we no longer carry runners as payloads
paths := []string{}
appExe, err := os.Executable()
exe, err := os.Executable()
if err != nil {
slog.Warn("failed to lookup executable path", "error", err)
} else {
appRelative := filepath.Join(filepath.Dir(appExe), envconfig.LibRelativeToExe(), "lib", "ollama")
if _, err := os.Stat(appRelative); err == nil {
paths = append(paths, appRelative)
}
return nil
}
rDir := runners.Locate()
if err != nil {
slog.Warn("unable to locate gpu dependency libraries", "error", err)
} else {
paths = append(paths, filepath.Dir(rDir))
lib := filepath.Join(filepath.Dir(exe), envconfig.LibRelativeToExe(), "lib", "ollama")
if _, err := os.Stat(lib); err != nil {
return nil
}
return paths
return []string{lib}
}
func GetSystemInfo() SystemInfo {

View File

@ -165,6 +165,8 @@ var (
IntelGPU = Bool("OLLAMA_INTEL_GPU")
// MultiUserCache optimizes prompt caching for multi-user scenarios
MultiUserCache = Bool("OLLAMA_MULTIUSER_CACHE")
// Enable the new Ollama engine
NewRunners = Bool("OLLAMA_NEW_RUNNERS")
)
func String(s string) func() string {
@ -250,6 +252,7 @@ func AsMap() map[string]EnvVar {
"OLLAMA_ORIGINS": {"OLLAMA_ORIGINS", Origins(), "A comma separated list of allowed origins"},
"OLLAMA_SCHED_SPREAD": {"OLLAMA_SCHED_SPREAD", SchedSpread(), "Always schedule model across all GPUs"},
"OLLAMA_MULTIUSER_CACHE": {"OLLAMA_MULTIUSER_CACHE", MultiUserCache(), "Optimize prompt caching for multi-user scenarios"},
"OLLAMA_NEW_RUNNERS": {"OLLAMA_NEW_RUNNERS", NewRunners(), "Enable the new Ollama engine"},
// Informational
"HTTP_PROXY": {"HTTP_PROXY", String("HTTP_PROXY")(), "HTTP proxy"},

View File

@ -1,15 +1,15 @@
package llm
package ggml
import (
"encoding/binary"
"errors"
"fmt"
"io"
"log/slog"
"slices"
"strings"
"sync"
"github.com/ollama/ollama/util/bufioutil"
"github.com/ollama/ollama/fs/util/bufioutil"
)
type GGML struct {
@ -19,145 +19,168 @@ type GGML struct {
type model interface {
KV() KV
Tensors() *Tensors
Tensors() Tensors
}
type KV map[string]any
func (kv KV) u64(key string) uint64 {
switch v := kv[key].(type) {
case uint64:
return v
case uint32:
return uint64(v)
case float64:
return uint64(v)
default:
return 0
}
}
func (kv KV) Architecture() string {
if s, ok := kv["general.architecture"].(string); ok {
return s
}
return "unknown"
return kv.String("general.architecture", "unknown")
}
func (kv KV) Kind() string {
if s, ok := kv["general.type"].(string); ok {
return s
}
return "unknown"
return kv.String("general.type", "unknown")
}
func (kv KV) ParameterCount() uint64 {
return kv.u64("general.parameter_count")
return keyValue[uint64](kv, "general.parameter_count")
}
func (kv KV) FileType() fileType {
if u64 := kv.u64("general.file_type"); u64 > 0 {
return fileType(uint32(u64))
if t := kv.Uint("general.file_type"); t > 0 {
return fileType(t)
}
return fileTypeUnknown
}
func (kv KV) BlockCount() uint64 {
return kv.u64(fmt.Sprintf("%s.block_count", kv.Architecture()))
return uint64(kv.Uint("block_count"))
}
func (kv KV) EmbeddingLength() uint64 {
return uint64(kv.Uint("embedding_length"))
}
func (kv KV) HeadCount() uint64 {
return kv.u64(fmt.Sprintf("%s.attention.head_count", kv.Architecture()))
return uint64(kv.Uint("attention.head_count"))
}
func (kv KV) HeadCountKV() uint64 {
if headCountKV := kv.u64(fmt.Sprintf("%s.attention.head_count_kv", kv.Architecture())); headCountKV > 0 {
return headCountKV
}
return 1
return uint64(kv.Uint("attention.head_count_kv", 1))
}
func (kv KV) EmbeddingHeadCount() uint64 {
if heads := kv.HeadCount(); heads > 0 {
return kv.EmbeddingLength() / kv.HeadCount()
return kv.EmbeddingLength() / heads
}
return 0
}
func (kv KV) EmbeddingHeadCountK() uint64 {
if k := kv.u64(fmt.Sprintf("%s.attention.key_length", kv.Architecture())); k > 0 {
return k
}
return kv.EmbeddingHeadCount()
return uint64(kv.Uint("attention.key_length", uint32(kv.EmbeddingHeadCount())))
}
func (kv KV) EmbeddingHeadCountV() uint64 {
if v := kv.u64(fmt.Sprintf("%s.attention.value_length", kv.Architecture())); v > 0 {
return v
}
return kv.EmbeddingHeadCount()
return uint64(kv.Uint("attention.value_length", uint32(kv.EmbeddingHeadCount())))
}
func (kv KV) GQA() uint64 {
return kv.HeadCount() / kv.HeadCountKV()
}
func (kv KV) EmbeddingLength() uint64 {
return kv.u64(fmt.Sprintf("%s.embedding_length", kv.Architecture()))
}
func (kv KV) ContextLength() uint64 {
return kv.u64(fmt.Sprintf("%s.context_length", kv.Architecture()))
return uint64(kv.Uint("context_length"))
}
func (kv KV) ChatTemplate() string {
s, _ := kv["tokenizer.chat_template"].(string)
return kv.String("tokenizer.chat_template")
}
func (kv KV) String(key string, defaultValue ...string) string {
return keyValue(kv, key, append(defaultValue, "")...)
}
func (kv KV) Uint(key string, defaultValue ...uint32) uint32 {
return keyValue(kv, key, append(defaultValue, 0)...)
}
func (kv KV) Float(key string, defaultValue ...float32) float32 {
return keyValue(kv, key, append(defaultValue, 0)...)
}
func (kv KV) Strings(key string, defaultValue ...[]string) []string {
r := keyValue(kv, key, &array{})
s := make([]string, r.size)
for i := range r.size {
s[i] = r.values[i].(string)
}
return s
}
type Tensors struct {
Items []*Tensor
Offset uint64
func (kv KV) Uints(key string, defaultValue ...[]uint32) []uint32 {
r := keyValue(kv, key, &array{})
s := make([]uint32, r.size)
for i := range r.size {
s[i] = uint32(r.values[i].(int32))
}
layers map[string]Layer
layersOnce sync.Once
return s
}
func (ts *Tensors) Layers() map[string]Layer {
ts.layersOnce.Do(func() {
ts.layers = make(map[string]Layer)
for _, t := range ts.Items {
parts := strings.Split(t.Name, ".")
if index := slices.IndexFunc(parts, func(s string) bool { return s == "blk" || s == "mm" }); index != -1 {
if len(parts) > index+2 {
// blk and mm should have a number after them, join it
parts = append(
[]string{strings.Join(parts[:index+2], ".")},
parts[index+2:]...)
}
}
func keyValue[T string | uint32 | uint64 | float32 | *array](kv KV, key string, defaultValue ...T) T {
if !strings.HasPrefix(key, "tokenizer.") && !strings.HasPrefix(key, "general.") {
key = kv.Architecture() + "." + key
}
if _, ok := ts.layers[parts[0]]; !ok {
ts.layers[parts[0]] = make(Layer)
}
if val, ok := kv[key]; ok {
return val.(T)
}
ts.layers[parts[0]][strings.Join(parts[1:], ".")] = t
slog.Warn("key not found", "key", key, "default", defaultValue[0])
return defaultValue[0]
}
type Tensors struct {
items []*Tensor
Offset uint64
}
func (s Tensors) Items(prefix ...string) []*Tensor {
if len(prefix) == 0 {
return s.items
}
var items []*Tensor
for _, t := range s.items {
if strings.HasPrefix(t.Name, prefix[0]) {
items = append(items, t)
}
})
}
return ts.layers
return items
}
func (ts Tensors) Layers() map[string]Layer {
layers := make(map[string]Layer)
for _, t := range ts.items {
parts := strings.Split(t.Name, ".")
if i := slices.Index(parts, "blk"); i > 0 {
parts = append([]string{
strings.Join(parts[:i], "."),
strings.Join(parts[i:i+2], "."),
}, parts[i+2:]...)
} else if i == 0 {
parts = append([]string{
strings.Join(parts[i:i+2], "."),
}, parts[i+2:]...)
}
if _, ok := layers[parts[0]]; !ok {
layers[parts[0]] = make(Layer)
}
layers[parts[0]][strings.Join(parts[1:], ".")] = t
}
return layers
}
type Layer map[string]*Tensor
func (l Layer) size() (size uint64) {
func (l Layer) Size() (size uint64) {
for _, t := range l {
size += t.Size()
}
@ -255,8 +278,6 @@ func (t Tensor) typeSize() uint64 {
return 8
case 29: // IQ1_M
return blockSize/8 + blockSize/16 + blockSize/32
case 30: // BF16
return 2
default:
return 0
}
@ -295,7 +316,7 @@ const (
var ErrUnsupportedFormat = errors.New("unsupported model format")
func DetectGGMLType(b []byte) string {
func DetectContentType(b []byte) string {
switch binary.LittleEndian.Uint32(b[:4]) {
case FILE_MAGIC_GGML:
return "ggml"
@ -312,12 +333,12 @@ func DetectGGMLType(b []byte) string {
}
}
// DecodeGGML decodes a GGML model from the given reader.
// Decode decodes a GGML model from the given reader.
//
// It collects array values for arrays with a size less than or equal to
// maxArraySize. If maxArraySize is 0, the default value of 1024 is used. If
// the maxArraySize is negative, all arrays are collected.
func DecodeGGML(rs io.ReadSeeker, maxArraySize int) (*GGML, int64, error) {
func Decode(rs io.ReadSeeker, maxArraySize int) (*GGML, int64, error) {
if maxArraySize == 0 {
maxArraySize = 1024
}
@ -331,10 +352,6 @@ func DecodeGGML(rs io.ReadSeeker, maxArraySize int) (*GGML, int64, error) {
var c container
switch magic {
case FILE_MAGIC_GGML, FILE_MAGIC_GGMF, FILE_MAGIC_GGJT:
return nil, 0, ErrUnsupportedFormat
case FILE_MAGIC_GGLA:
c = &containerGGLA{}
case FILE_MAGIC_GGUF_LE:
c = &containerGGUF{ByteOrder: binary.LittleEndian, maxArraySize: maxArraySize}
case FILE_MAGIC_GGUF_BE:
@ -530,21 +547,20 @@ func (llm GGML) GraphSize(context, batch uint64, kvCacheType string) (kv, partia
}
// SupportsKVCacheType checks if the requested cache type is supported
func (ggml GGML) SupportsKVCacheType(cacheType string) bool {
validKVCacheTypes := []string{"f16", "q8_0", "q4_0"}
return slices.Contains(validKVCacheTypes, cacheType)
func (llm GGML) SupportsKVCacheType(cacheType string) bool {
return slices.Contains([]string{"f16", "q8_0", "q4_0"}, cacheType)
}
// SupportsFlashAttention checks if the model supports flash attention
func (ggml GGML) SupportsFlashAttention() bool {
_, isEmbedding := ggml.KV()[fmt.Sprintf("%s.pooling_type", ggml.KV().Architecture())]
func (llm GGML) SupportsFlashAttention() bool {
_, isEmbedding := llm.KV()[fmt.Sprintf("%s.pooling_type", llm.KV().Architecture())]
if isEmbedding {
return false
}
// Check head counts match and are non-zero
headCountK := ggml.KV().EmbeddingHeadCountK()
headCountV := ggml.KV().EmbeddingHeadCountV()
headCountK := llm.KV().EmbeddingHeadCountK()
headCountV := llm.KV().EmbeddingHeadCountV()
return headCountK != 0 && headCountV != 0 && headCountK == headCountV
}

View File

@ -1,4 +1,4 @@
package llm
package ggml
import (
"bytes"
@ -8,10 +8,9 @@ import (
"fmt"
"io"
"log/slog"
"maps"
"slices"
"strings"
"golang.org/x/exp/maps"
)
type containerGGUF struct {
@ -110,9 +109,9 @@ func (llm *gguf) KV() KV {
return llm.kv
}
func (llm *gguf) Tensors() *Tensors {
return &Tensors{
Items: llm.tensors,
func (llm *gguf) Tensors() Tensors {
return Tensors{
items: llm.tensors,
Offset: llm.tensorOffset,
}
}
@ -523,7 +522,7 @@ func WriteGGUF(ws io.WriteSeeker, kv KV, ts []Tensor) error {
return err
}
keys := maps.Keys(kv)
keys := slices.Collect(maps.Keys(kv))
slices.Sort(keys)
for _, key := range keys {

View File

@ -1,4 +1,4 @@
package llm
package ggml
import "fmt"
@ -32,10 +32,9 @@ const (
fileTypeIQ1_S
fileTypeIQ4_NL
fileTypeIQ3_S
fileTypeIQ3_M
fileTypeIQ2_S
fileTypeIQ2_M
fileTypeIQ4_XS
fileTypeIQ2_M
fileTypeIQ1_M
fileTypeBF16
@ -94,8 +93,6 @@ func ParseFileType(s string) (fileType, error) {
return fileTypeIQ4_NL, nil
case "IQ3_S":
return fileTypeIQ3_S, nil
case "IQ3_M":
return fileTypeIQ3_M, nil
case "IQ2_S":
return fileTypeIQ2_S, nil
case "IQ4_XS":
@ -163,8 +160,6 @@ func (t fileType) String() string {
return "IQ4_NL"
case fileTypeIQ3_S:
return "IQ3_S"
case fileTypeIQ3_M:
return "IQ3_M"
case fileTypeIQ2_S:
return "IQ2_S"
case fileTypeIQ4_XS:

3
go.mod
View File

@ -17,12 +17,14 @@ require (
require (
github.com/agnivade/levenshtein v1.1.1
github.com/d4l3k/go-bfloat16 v0.0.0-20211005043715-690c3bdd05f1
github.com/dlclark/regexp2 v1.11.4
github.com/emirpasic/gods/v2 v2.0.0-alpha
github.com/google/go-cmp v0.6.0
github.com/mattn/go-runewidth v0.0.14
github.com/nlpodyssey/gopickle v0.3.0
github.com/pdevine/tensor v0.0.0-20240510204454-f88f4562727c
golang.org/x/image v0.22.0
gonum.org/v1/gonum v0.15.0
)
require (
@ -42,7 +44,6 @@ require (
github.com/xtgo/set v1.0.0 // indirect
go4.org/unsafe/assume-no-moving-gc v0.0.0-20231121144256-b99613f794b6 // indirect
golang.org/x/xerrors v0.0.0-20200804184101-5ec99f83aff1 // indirect
gonum.org/v1/gonum v0.15.0 // indirect
gorgonia.org/vecf32 v0.9.0 // indirect
gorgonia.org/vecf64 v0.9.0 // indirect
)

2
go.sum
View File

@ -42,6 +42,8 @@ github.com/davecgh/go-spew v1.1.1 h1:vj9j/u1bqnvCEfJOwUhtlOARqs3+rkHYY13jYWTU97c
github.com/davecgh/go-spew v1.1.1/go.mod h1:J7Y8YcW2NihsgmVo/mv3lAwl/skON4iLHjSsI+c5H38=
github.com/dgryski/trifles v0.0.0-20200323201526-dd97f9abfb48 h1:fRzb/w+pyskVMQ+UbP35JkH8yB7MYb4q/qhBarqZE6g=
github.com/dgryski/trifles v0.0.0-20200323201526-dd97f9abfb48/go.mod h1:if7Fbed8SFyPtHLHbg49SI7NAdJiC5WIA09pe59rfAA=
github.com/dlclark/regexp2 v1.11.4 h1:rPYF9/LECdNymJufQKmri9gV604RvvABwgOA8un7yAo=
github.com/dlclark/regexp2 v1.11.4/go.mod h1:DHkYz0B9wPfa6wondMfaivmHpzrQ3v9q8cnmRbL6yW8=
github.com/emirpasic/gods/v2 v2.0.0-alpha h1:dwFlh8pBg1VMOXWGipNMRt8v96dKAIvBehtCt6OtunU=
github.com/emirpasic/gods/v2 v2.0.0-alpha/go.mod h1:W0y4M2dtBB9U5z3YlghmpuUhiaZT2h6yoeE+C1sCp6A=
github.com/envoyproxy/go-control-plane v0.9.0/go.mod h1:YTl/9mNaCwkRvm6d1a2C3ymFceY/DCBVvsKhRF0iEA4=

View File

@ -37,8 +37,7 @@ go build -tags avx .
```shell
# go doesn't recognize `-mfma` as a valid compiler flag
# see https://github.com/golang/go/issues/17895
go env -w "CGO_CFLAGS_ALLOW=-mfma|-mf16c"
go env -w "CGO_CXXFLAGS_ALLOW=-mfma|-mf16c"
go env -w "CGO_CPPFLAGS_ALLOW=-mfma|-mf16c"
go build -tags=avx,avx2 .
```

34
llama/amx.h vendored
View File

@ -1,34 +0,0 @@
/**
* llama.cpp - commit 46e3556e01b824e52395fb050b29804b6cff2a7c - do not edit this file
*
* MIT License
*
* Copyright (c) 2023-2024 The ggml authors
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#include "ggml-backend.h"
#include "ggml-cpu-impl.h"
// GGML internal header
#if defined(__AMX_INT8__) && defined(__AVX512VNNI__)
ggml_backend_buffer_type_t ggml_backend_amx_buffer_type(void);
#endif

51
llama/ggml-blas.h vendored
View File

@ -1,51 +0,0 @@
/**
* llama.cpp - commit 46e3556e01b824e52395fb050b29804b6cff2a7c - do not edit this file
*
* MIT License
*
* Copyright (c) 2023-2024 The ggml authors
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#pragma once
#include "ggml.h"
#include "ggml-backend.h"
#ifdef __cplusplus
extern "C" {
#endif
// backend API
GGML_BACKEND_API ggml_backend_t ggml_backend_blas_init(void);
GGML_BACKEND_API bool ggml_backend_is_blas(ggml_backend_t backend);
// number of threads used for conversion to float
// for openblas and blis, this will also set the number of threads used for blas operations
GGML_BACKEND_API void ggml_backend_blas_set_n_threads(ggml_backend_t backend_blas, int n_threads);
GGML_BACKEND_API ggml_backend_reg_t ggml_backend_blas_reg(void);
#ifdef __cplusplus
}
#endif

View File

@ -1,34 +0,0 @@
/**
* llama.cpp - commit 46e3556e01b824e52395fb050b29804b6cff2a7c - do not edit this file
*
* MIT License
*
* Copyright (c) 2023-2024 The ggml authors
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#pragma once
#include "ggml-cpu-traits.h"
#include "ggml.h"
// GGML internal header
ggml_backend_buffer_type_t ggml_backend_cpu_aarch64_buffer_type(void);

View File

@ -1,64 +0,0 @@
/**
* llama.cpp - commit 46e3556e01b824e52395fb050b29804b6cff2a7c - do not edit this file
*
* MIT License
*
* Copyright (c) 2023-2024 The ggml authors
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#pragma once
#include "ggml-backend-impl.h"
#include "ggml-cpu-impl.h"
#include "ggml.h"
#ifdef __cplusplus
# include <vector>
extern "C" {
#endif
// return true if op part of extra "accelerator"
bool ggml_cpu_extra_compute_forward(struct ggml_compute_params * params, struct ggml_tensor * op);
bool ggml_cpu_extra_work_size(int n_threads, const struct ggml_tensor * op, size_t * size);
#ifdef __cplusplus
}
namespace ggml::cpu {
// register in tensor->extra
class tensor_traits {
public:
virtual ~tensor_traits();
virtual bool work_size(int n_threads, const struct ggml_tensor * op, size_t & size) = 0;
virtual bool compute_forward(struct ggml_compute_params * params, struct ggml_tensor * op) = 0;
};
class extra_buffer_type {
public:
virtual ~extra_buffer_type();
virtual bool supports_op(ggml_backend_dev_t dev, const struct ggml_tensor * op) = 0;
virtual tensor_traits * get_tensor_traits(const struct ggml_tensor * op) = 0;
};
} // namespace ggml::cpu
// implemented in ggml-cpu.cpp.
std::vector<ggml_backend_buffer_type_t> & ggml_backend_cpu_get_extra_buffers_type();
#endif

View File

@ -1,31 +0,0 @@
/**
* llama.cpp - commit 46e3556e01b824e52395fb050b29804b6cff2a7c - do not edit this file
*
* MIT License
*
* Copyright (c) 2023-2024 The ggml authors
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#include "common.cuh"
#define CUDA_ACC_BLOCK_SIZE 256
void ggml_cuda_op_acc(ggml_backend_cuda_context & ctx, ggml_tensor * dst);

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@ -1,60 +0,0 @@
/**
* llama.cpp - commit 46e3556e01b824e52395fb050b29804b6cff2a7c - do not edit this file
*
* MIT License
*
* Copyright (c) 2023-2024 The ggml authors
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#include "arange.cuh"
static __global__ void arange_f32(float * dst, const int ne0, const float start, const float step) {
// blockIDx.x: idx of ne0 / BLOCK_SIZE
int nidx = threadIdx.x + blockIdx.x * blockDim.x;
if (nidx >= ne0) {
return;
}
dst[nidx] = start + step * nidx;
}
static void arange_f32_cuda(float * dst, const int ne0, const float start, const float step, cudaStream_t stream) {
int num_blocks = (ne0 + CUDA_ARANGE_BLOCK_SIZE - 1) / CUDA_ARANGE_BLOCK_SIZE;
arange_f32<<<num_blocks, CUDA_ARANGE_BLOCK_SIZE, 0, stream>>>(dst, ne0, start, step);
}
void ggml_cuda_op_arange(ggml_backend_cuda_context & ctx, ggml_tensor * dst) {
float * dst_d = (float *)dst->data;
cudaStream_t stream = ctx.stream();
GGML_ASSERT(dst->type == GGML_TYPE_F32);
float start;
float stop;
float step;
memcpy(&start, (float *)dst->op_params + 0, sizeof(float));
memcpy(&stop, (float *)dst->op_params + 1, sizeof(float));
memcpy(&step, (float *)dst->op_params + 2, sizeof(float));
int64_t steps = (int64_t)ceil((stop - start) / step);
GGML_ASSERT(ggml_nelements(dst) == steps);
arange_f32_cuda(dst_d, dst->ne[0], start, step, stream);
}

View File

@ -1,31 +0,0 @@
/**
* llama.cpp - commit 46e3556e01b824e52395fb050b29804b6cff2a7c - do not edit this file
*
* MIT License
*
* Copyright (c) 2023-2024 The ggml authors
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#include "common.cuh"
#define CUDA_ARANGE_BLOCK_SIZE 256
void ggml_cuda_op_arange(ggml_backend_cuda_context & ctx, ggml_tensor * dst);

View File

@ -1,29 +0,0 @@
/**
* llama.cpp - commit 46e3556e01b824e52395fb050b29804b6cff2a7c - do not edit this file
*
* MIT License
*
* Copyright (c) 2023-2024 The ggml authors
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#include "common.cuh"
void ggml_cuda_argmax(ggml_backend_cuda_context & ctx, ggml_tensor * dst);

View File

@ -1,29 +0,0 @@
/**
* llama.cpp - commit 46e3556e01b824e52395fb050b29804b6cff2a7c - do not edit this file
*
* MIT License
*
* Copyright (c) 2023-2024 The ggml authors
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#include "common.cuh"
void ggml_cuda_op_argsort(ggml_backend_cuda_context & ctx, ggml_tensor * dst);

View File

@ -1,35 +0,0 @@
/**
* llama.cpp - commit 46e3556e01b824e52395fb050b29804b6cff2a7c - do not edit this file
*
* MIT License
*
* Copyright (c) 2023-2024 The ggml authors
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#include "common.cuh"
void ggml_cuda_op_repeat(ggml_backend_cuda_context & ctx, ggml_tensor * dst);
void ggml_cuda_op_add(ggml_backend_cuda_context & ctx, ggml_tensor * dst);
void ggml_cuda_op_sub(ggml_backend_cuda_context & ctx, ggml_tensor * dst);
void ggml_cuda_op_mul(ggml_backend_cuda_context & ctx, ggml_tensor * dst);
void ggml_cuda_op_div(ggml_backend_cuda_context & ctx, ggml_tensor * dst);
void ggml_cuda_op_repeat_back(ggml_backend_cuda_context & ctx, ggml_tensor * dst);

View File

@ -1,60 +0,0 @@
/**
* llama.cpp - commit 46e3556e01b824e52395fb050b29804b6cff2a7c - do not edit this file
*
* MIT License
*
* Copyright (c) 2023-2024 The ggml authors
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#include "clamp.cuh"
static __global__ void clamp_f32(const float * x, float * dst, const float min, const float max, const int k) {
const int i = blockDim.x*blockIdx.x + threadIdx.x;
if (i >= k) {
return;
}
dst[i] = x[i] < min ? min : (x[i] > max ? max : x[i]);
}
static void clamp_f32_cuda(const float * x, float * dst, const float min, const float max, const int k, cudaStream_t stream) {
const int num_blocks = (k + CUDA_CLAMP_BLOCK_SIZE - 1) / CUDA_CLAMP_BLOCK_SIZE;
clamp_f32<<<num_blocks, CUDA_CLAMP_BLOCK_SIZE, 0, stream>>>(x, dst, min, max, k);
}
void ggml_cuda_op_clamp(ggml_backend_cuda_context & ctx, ggml_tensor * dst) {
const ggml_tensor * src0 = dst->src[0];
const float * src0_d = (const float *)src0->data;
float * dst_d = (float *)dst->data;
cudaStream_t stream = ctx.stream();
GGML_ASSERT(src0->type == GGML_TYPE_F32);
GGML_ASSERT( dst->type == GGML_TYPE_F32);
float min;
float max;
memcpy(&min, dst->op_params, sizeof(float));
memcpy(&max, (float *) dst->op_params + 1, sizeof(float));
clamp_f32_cuda(src0_d, dst_d, min, max, ggml_nelements(src0), stream);
}

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/**
* llama.cpp - commit 46e3556e01b824e52395fb050b29804b6cff2a7c - do not edit this file
*
* MIT License
*
* Copyright (c) 2023-2024 The ggml authors
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#include "common.cuh"
#define CUDA_CLAMP_BLOCK_SIZE 256
void ggml_cuda_op_clamp(ggml_backend_cuda_context & ctx, ggml_tensor * dst);

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/**
* llama.cpp - commit 46e3556e01b824e52395fb050b29804b6cff2a7c - do not edit this file
*
* MIT License
*
* Copyright (c) 2023-2024 The ggml authors
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#include "common.cuh"
#define CUDA_CONCAT_BLOCK_SIZE 256
void ggml_cuda_op_concat(ggml_backend_cuda_context & ctx, ggml_tensor * dst);

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/**
* llama.cpp - commit 46e3556e01b824e52395fb050b29804b6cff2a7c - do not edit this file
*
* MIT License
*
* Copyright (c) 2023-2024 The ggml authors
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#include "common.cuh"
#define CUDA_CONV_TRANPOSE_1D_BLOCK_SIZE 256
void ggml_cuda_op_conv_transpose_1d(ggml_backend_cuda_context & ctx, ggml_tensor * dst);

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/**
* llama.cpp - commit 46e3556e01b824e52395fb050b29804b6cff2a7c - do not edit this file
*
* MIT License
*
* Copyright (c) 2023-2024 The ggml authors
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#include "common.cuh"
#define CUDA_DEQUANTIZE_BLOCK_SIZE 256
template<typename T>
using to_t_cuda_t = void (*)(const void * __restrict__ x, T * __restrict__ y, int64_t k, cudaStream_t stream);
typedef to_t_cuda_t<float> to_fp32_cuda_t;
typedef to_t_cuda_t<half> to_fp16_cuda_t;
to_fp16_cuda_t ggml_get_to_fp16_cuda(ggml_type type);
to_fp32_cuda_t ggml_get_to_fp32_cuda(ggml_type type);

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/**
* llama.cpp - commit 46e3556e01b824e52395fb050b29804b6cff2a7c - do not edit this file
*
* MIT License
*
* Copyright (c) 2023-2024 The ggml authors
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#include "common.cuh"
#define CUDA_COUNT_EQUAL_CHUNK_SIZE 128
void ggml_cuda_count_equal(ggml_backend_cuda_context & ctx, ggml_tensor * dst);

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/**
* llama.cpp - commit 46e3556e01b824e52395fb050b29804b6cff2a7c - do not edit this file
*
* MIT License
*
* Copyright (c) 2023-2024 The ggml authors
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#include "common.cuh"
#define CUDA_CPY_BLOCK_SIZE 64
void ggml_cuda_cpy(ggml_backend_cuda_context & ctx, const ggml_tensor * src0, ggml_tensor * src1);
void ggml_cuda_dup(ggml_backend_cuda_context & ctx, ggml_tensor * dst);
void* ggml_cuda_cpy_fn(const ggml_tensor * src0, ggml_tensor * src1);

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/**
* llama.cpp - commit 46e3556e01b824e52395fb050b29804b6cff2a7c - do not edit this file
*
* MIT License
*
* Copyright (c) 2023-2024 The ggml authors
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#include "common.cuh"
#define CUDA_CROSS_ENTROPY_LOSS_BLOCK_SIZE 256
void ggml_cuda_cross_entropy_loss(ggml_backend_cuda_context & ctx, ggml_tensor * dst);
void ggml_cuda_cross_entropy_loss_back(ggml_backend_cuda_context & ctx, ggml_tensor * dst);

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/**
* llama.cpp - commit 46e3556e01b824e52395fb050b29804b6cff2a7c - do not edit this file
*
* MIT License
*
* Copyright (c) 2023-2024 The ggml authors
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#include "common.cuh"
#define CUDA_DIAG_MASK_INF_BLOCK_SIZE 32
void ggml_cuda_op_diag_mask_inf(ggml_backend_cuda_context & ctx, ggml_tensor * dst);

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/**
* llama.cpp - commit 46e3556e01b824e52395fb050b29804b6cff2a7c - do not edit this file
*
* MIT License
*
* Copyright (c) 2023-2024 The ggml authors
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#include "common.cuh"
void ggml_cuda_flash_attn_ext_tile_f16(ggml_backend_cuda_context & ctx, ggml_tensor * dst);

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/**
* llama.cpp - commit 46e3556e01b824e52395fb050b29804b6cff2a7c - do not edit this file
*
* MIT License
*
* Copyright (c) 2023-2024 The ggml authors
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#include "common.cuh"
void ggml_cuda_flash_attn_ext_tile_f32(ggml_backend_cuda_context & ctx, ggml_tensor * dst);

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/**
* llama.cpp - commit 46e3556e01b824e52395fb050b29804b6cff2a7c - do not edit this file
*
* MIT License
*
* Copyright (c) 2023-2024 The ggml authors
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#include "common.cuh"
void ggml_cuda_flash_attn_ext(ggml_backend_cuda_context & ctx, ggml_tensor * dst);

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/**
* llama.cpp - commit 46e3556e01b824e52395fb050b29804b6cff2a7c - do not edit this file
*
* MIT License
*
* Copyright (c) 2023-2024 The ggml authors
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#include "common.cuh"
#define CUDA_GET_ROWS_BLOCK_SIZE 256
void ggml_cuda_op_get_rows(ggml_backend_cuda_context & ctx, ggml_tensor * dst);

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/**
* llama.cpp - commit 46e3556e01b824e52395fb050b29804b6cff2a7c - do not edit this file
*
* MIT License
*
* Copyright (c) 2023-2024 The ggml authors
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#include "common.cuh"
#define CUDA_IM2COL_BLOCK_SIZE 256
void ggml_cuda_op_im2col(ggml_backend_cuda_context & ctx, ggml_tensor * dst);

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/**
* llama.cpp - commit 46e3556e01b824e52395fb050b29804b6cff2a7c - do not edit this file
*
* MIT License
*
* Copyright (c) 2023-2024 The ggml authors
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#include "common.cuh"
// maximum number of src0 rows with which to use mul_mat_vec over cuBLAS if FP16 tensor cores are available
#define MMV_MAX_ROWS 512
void ggml_cuda_mul_mat_vec(ggml_backend_cuda_context & ctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst);
void ggml_cuda_op_mul_mat_vec(
ggml_backend_cuda_context & ctx,
const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst, const char * src0_dd_i, const float * src1_ddf_i,
const char * src1_ddq_i, float * dst_dd_i, const int64_t row_low, const int64_t row_high, const int64_t src1_ncols,
const int64_t src1_padded_row_size, cudaStream_t stream);

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/**
* llama.cpp - commit 46e3556e01b824e52395fb050b29804b6cff2a7c - do not edit this file
*
* MIT License
*
* Copyright (c) 2023-2024 The ggml authors
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#include "common.cuh"
#define MMVQ_MAX_BATCH_SIZE 8 // Max. batch size for which to use MMVQ kernels.
void ggml_cuda_op_mul_mat_vec_q(
ggml_backend_cuda_context & ctx,
const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst, const char * src0_dd_i, const float * src1_ddf_i,
const char * src1_ddq_i, float * dst_dd_i, const int64_t row_low, const int64_t row_high, const int64_t src1_ncols,
const int64_t src1_padded_row_size, cudaStream_t stream);

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/**
* llama.cpp - commit 46e3556e01b824e52395fb050b29804b6cff2a7c - do not edit this file
*
* MIT License
*
* Copyright (c) 2023-2024 The ggml authors
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#include "common.cuh"
void ggml_cuda_op_norm(ggml_backend_cuda_context & ctx, ggml_tensor * dst);
void ggml_cuda_op_group_norm(ggml_backend_cuda_context & ctx, ggml_tensor * dst);
void ggml_cuda_op_rms_norm(ggml_backend_cuda_context & ctx, ggml_tensor * dst);

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/**
* llama.cpp - commit 46e3556e01b824e52395fb050b29804b6cff2a7c - do not edit this file
*
* MIT License
*
* Copyright (c) 2023-2024 The ggml authors
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#include "common.cuh"
#define CUDA_OPT_STEP_ADAMW_BLOCK_SIZE 256
void ggml_cuda_opt_step_adamw(ggml_backend_cuda_context & ctx, ggml_tensor * dst);

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/**
* llama.cpp - commit 46e3556e01b824e52395fb050b29804b6cff2a7c - do not edit this file
*
* MIT License
*
* Copyright (c) 2023-2024 The ggml authors
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#include "common.cuh"
void ggml_cuda_out_prod(ggml_backend_cuda_context & ctx, ggml_tensor * dst);

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/**
* llama.cpp - commit 46e3556e01b824e52395fb050b29804b6cff2a7c - do not edit this file
*
* MIT License
*
* Copyright (c) 2023-2024 The ggml authors
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#include "common.cuh"
#define CUDA_PAD_BLOCK_SIZE 256
void ggml_cuda_op_pad(ggml_backend_cuda_context & ctx, ggml_tensor * dst);
void ggml_cuda_op_unpad(ggml_backend_cuda_context & ctx, ggml_tensor * dst);

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/**
* llama.cpp - commit 46e3556e01b824e52395fb050b29804b6cff2a7c - do not edit this file
*
* MIT License
*
* Copyright (c) 2023-2024 The ggml authors
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#include "common.cuh"
#define CUDA_POOL2D_BLOCK_SIZE 256
void ggml_cuda_op_pool2d(ggml_backend_cuda_context & ctx, ggml_tensor * dst);

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/**
* llama.cpp - commit 46e3556e01b824e52395fb050b29804b6cff2a7c - do not edit this file
*
* MIT License
*
* Copyright (c) 2023-2024 The ggml authors
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#pragma once
#include "common.cuh"
#include "mmq.cuh"
#include <cstdint>
#define CUDA_QUANTIZE_BLOCK_SIZE 256
#define CUDA_QUANTIZE_BLOCK_SIZE_MMQ 128
static_assert(MATRIX_ROW_PADDING % CUDA_QUANTIZE_BLOCK_SIZE == 0, "Risk of out-of-bounds access.");
static_assert(MATRIX_ROW_PADDING % (4*CUDA_QUANTIZE_BLOCK_SIZE_MMQ) == 0, "Risk of out-of-bounds access.");
typedef void (*quantize_cuda_t)(
const float * x, void * vy, const int64_t kx0, const int64_t kx1, const int64_t channels, const int64_t kx0_padded,
const ggml_type type_x, cudaStream_t stream);
void quantize_row_q8_1_cuda(
const float * x, void * vy, const int64_t kx0, const int64_t kx1, const int64_t channels, const int64_t kx0_padded,
const ggml_type type_x, cudaStream_t stream);
void quantize_mmq_q8_1_cuda(
const float * x, void * vy, const int64_t kx0, const int64_t kx1, const int64_t channels, const int64_t kx0_padded,
const ggml_type type_x, cudaStream_t stream);

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/**
* llama.cpp - commit 46e3556e01b824e52395fb050b29804b6cff2a7c - do not edit this file
*
* MIT License
*
* Copyright (c) 2023-2024 The ggml authors
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#include "common.cuh"
#define CUDA_ROPE_BLOCK_SIZE 256
void ggml_cuda_op_rope(ggml_backend_cuda_context & ctx, ggml_tensor * dst);

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/**
* llama.cpp - commit 46e3556e01b824e52395fb050b29804b6cff2a7c - do not edit this file
*
* MIT License
*
* Copyright (c) 2023-2024 The ggml authors
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#include "scale.cuh"
static __global__ void scale_f32(const float * x, float * dst, const float scale, const int k) {
const int i = blockDim.x*blockIdx.x + threadIdx.x;
if (i >= k) {
return;
}
dst[i] = scale * x[i];
}
static void scale_f32_cuda(const float * x, float * dst, const float scale, const int k, cudaStream_t stream) {
const int num_blocks = (k + CUDA_SCALE_BLOCK_SIZE - 1) / CUDA_SCALE_BLOCK_SIZE;
scale_f32<<<num_blocks, CUDA_SCALE_BLOCK_SIZE, 0, stream>>>(x, dst, scale, k);
}
void ggml_cuda_op_scale(ggml_backend_cuda_context & ctx, ggml_tensor * dst) {
const ggml_tensor * src0 = dst->src[0];
const float * src0_d = (const float *)src0->data;
float * dst_d = (float *)dst->data;
cudaStream_t stream = ctx.stream();
GGML_ASSERT(src0->type == GGML_TYPE_F32);
GGML_ASSERT( dst->type == GGML_TYPE_F32);
float scale;
memcpy(&scale, dst->op_params, sizeof(float));
scale_f32_cuda(src0_d, dst_d, scale, ggml_nelements(src0), stream);
}

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/**
* llama.cpp - commit 46e3556e01b824e52395fb050b29804b6cff2a7c - do not edit this file
*
* MIT License
*
* Copyright (c) 2023-2024 The ggml authors
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#include "common.cuh"
#define CUDA_SCALE_BLOCK_SIZE 256
void ggml_cuda_op_scale(ggml_backend_cuda_context & ctx, ggml_tensor * dst);

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/**
* llama.cpp - commit 46e3556e01b824e52395fb050b29804b6cff2a7c - do not edit this file
*
* MIT License
*
* Copyright (c) 2023-2024 The ggml authors
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#include "common.cuh"
#define CUDA_SOFT_MAX_BLOCK_SIZE 1024
void ggml_cuda_op_soft_max(ggml_backend_cuda_context & ctx, ggml_tensor * dst);

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/**
* llama.cpp - commit 46e3556e01b824e52395fb050b29804b6cff2a7c - do not edit this file
*
* MIT License
*
* Copyright (c) 2023-2024 The ggml authors
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#include "common.cuh"
void sum_f32_cuda(ggml_cuda_pool & pool, const float * x, float * dst, const int64_t ne, cudaStream_t stream);
void ggml_cuda_op_sum(ggml_backend_cuda_context & ctx, ggml_tensor * dst);

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/**
* llama.cpp - commit 46e3556e01b824e52395fb050b29804b6cff2a7c - do not edit this file
*
* MIT License
*
* Copyright (c) 2023-2024 The ggml authors
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#include "sumrows.cuh"
static __global__ void k_sum_rows_f32(const float * x, float * dst, const int ncols) {
const int row = blockIdx.x;
const int col = threadIdx.x;
float sum = 0.0f;
for (int i = col; i < ncols; i += blockDim.x) {
sum += x[row * ncols + i];
}
sum = warp_reduce_sum(sum);
if (col == 0) {
dst[row] = sum;
}
}
void sum_rows_f32_cuda(const float * x, float * dst, const int ncols, const int nrows, cudaStream_t stream) {
const dim3 block_dims(WARP_SIZE, 1, 1);
const dim3 block_nums(nrows, 1, 1);
k_sum_rows_f32<<<block_nums, block_dims, 0, stream>>>(x, dst, ncols);
}
void ggml_cuda_op_sum_rows(ggml_backend_cuda_context & ctx, ggml_tensor * dst) {
const ggml_tensor * src0 = dst->src[0];
const float * src0_d = (const float *)src0->data;
float * dst_d = (float *)dst->data;
cudaStream_t stream = ctx.stream();
GGML_ASSERT(src0->type == GGML_TYPE_F32);
GGML_ASSERT( dst->type == GGML_TYPE_F32);
GGML_ASSERT(ggml_is_contiguous(src0));
const int64_t ncols = src0->ne[0];
const int64_t nrows = ggml_nrows(src0);
sum_rows_f32_cuda(src0_d, dst_d, ncols, nrows, stream);
}

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/**
* llama.cpp - commit 46e3556e01b824e52395fb050b29804b6cff2a7c - do not edit this file
*
* MIT License
*
* Copyright (c) 2023-2024 The ggml authors
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#include "common.cuh"
void sum_rows_f32_cuda(const float * x, float * dst, const int ncols, const int nrows, cudaStream_t stream);
void ggml_cuda_op_sum_rows(ggml_backend_cuda_context & ctx, ggml_tensor * dst);

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/**
* llama.cpp - commit 46e3556e01b824e52395fb050b29804b6cff2a7c - do not edit this file
*
* MIT License
*
* Copyright (c) 2023-2024 The ggml authors
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
// This file has been autogenerated by generate_cu_files.py, do not edit manually.
#include "../fattn-vec-f16.cuh"
DECL_FATTN_VEC_F16_CASE(128, GGML_TYPE_F16, GGML_TYPE_F16);

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/**
* llama.cpp - commit 46e3556e01b824e52395fb050b29804b6cff2a7c - do not edit this file
*
* MIT License
*
* Copyright (c) 2023-2024 The ggml authors
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
// This file has been autogenerated by generate_cu_files.py, do not edit manually.
#include "../fattn-vec-f16.cuh"
DECL_FATTN_VEC_F16_CASE(128, GGML_TYPE_F16, GGML_TYPE_Q4_0);

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@ -1,31 +0,0 @@
/**
* llama.cpp - commit 46e3556e01b824e52395fb050b29804b6cff2a7c - do not edit this file
*
* MIT License
*
* Copyright (c) 2023-2024 The ggml authors
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
// This file has been autogenerated by generate_cu_files.py, do not edit manually.
#include "../fattn-vec-f16.cuh"
DECL_FATTN_VEC_F16_CASE(128, GGML_TYPE_F16, GGML_TYPE_Q4_1);

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@ -1,31 +0,0 @@
/**
* llama.cpp - commit 46e3556e01b824e52395fb050b29804b6cff2a7c - do not edit this file
*
* MIT License
*
* Copyright (c) 2023-2024 The ggml authors
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
// This file has been autogenerated by generate_cu_files.py, do not edit manually.
#include "../fattn-vec-f16.cuh"
DECL_FATTN_VEC_F16_CASE(128, GGML_TYPE_F16, GGML_TYPE_Q5_0);

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/**
* llama.cpp - commit 46e3556e01b824e52395fb050b29804b6cff2a7c - do not edit this file
*
* MIT License
*
* Copyright (c) 2023-2024 The ggml authors
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
// This file has been autogenerated by generate_cu_files.py, do not edit manually.
#include "../fattn-vec-f16.cuh"
DECL_FATTN_VEC_F16_CASE(128, GGML_TYPE_F16, GGML_TYPE_Q5_1);

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/**
* llama.cpp - commit 46e3556e01b824e52395fb050b29804b6cff2a7c - do not edit this file
*
* MIT License
*
* Copyright (c) 2023-2024 The ggml authors
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
// This file has been autogenerated by generate_cu_files.py, do not edit manually.
#include "../fattn-vec-f16.cuh"
DECL_FATTN_VEC_F16_CASE(128, GGML_TYPE_F16, GGML_TYPE_Q8_0);

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/**
* llama.cpp - commit 46e3556e01b824e52395fb050b29804b6cff2a7c - do not edit this file
*
* MIT License
*
* Copyright (c) 2023-2024 The ggml authors
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
// This file has been autogenerated by generate_cu_files.py, do not edit manually.
#include "../fattn-vec-f16.cuh"
DECL_FATTN_VEC_F16_CASE(128, GGML_TYPE_Q4_0, GGML_TYPE_F16);

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/**
* llama.cpp - commit 46e3556e01b824e52395fb050b29804b6cff2a7c - do not edit this file
*
* MIT License
*
* Copyright (c) 2023-2024 The ggml authors
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
// This file has been autogenerated by generate_cu_files.py, do not edit manually.
#include "../fattn-vec-f16.cuh"
DECL_FATTN_VEC_F16_CASE(128, GGML_TYPE_Q4_0, GGML_TYPE_Q4_0);

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@ -1,31 +0,0 @@
/**
* llama.cpp - commit 46e3556e01b824e52395fb050b29804b6cff2a7c - do not edit this file
*
* MIT License
*
* Copyright (c) 2023-2024 The ggml authors
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
// This file has been autogenerated by generate_cu_files.py, do not edit manually.
#include "../fattn-vec-f16.cuh"
DECL_FATTN_VEC_F16_CASE(128, GGML_TYPE_Q4_0, GGML_TYPE_Q4_1);

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@ -1,31 +0,0 @@
/**
* llama.cpp - commit 46e3556e01b824e52395fb050b29804b6cff2a7c - do not edit this file
*
* MIT License
*
* Copyright (c) 2023-2024 The ggml authors
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
// This file has been autogenerated by generate_cu_files.py, do not edit manually.
#include "../fattn-vec-f16.cuh"
DECL_FATTN_VEC_F16_CASE(128, GGML_TYPE_Q4_0, GGML_TYPE_Q5_0);

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@ -1,31 +0,0 @@
/**
* llama.cpp - commit 46e3556e01b824e52395fb050b29804b6cff2a7c - do not edit this file
*
* MIT License
*
* Copyright (c) 2023-2024 The ggml authors
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
// This file has been autogenerated by generate_cu_files.py, do not edit manually.
#include "../fattn-vec-f16.cuh"
DECL_FATTN_VEC_F16_CASE(128, GGML_TYPE_Q4_0, GGML_TYPE_Q5_1);

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@ -1,31 +0,0 @@
/**
* llama.cpp - commit 46e3556e01b824e52395fb050b29804b6cff2a7c - do not edit this file
*
* MIT License
*
* Copyright (c) 2023-2024 The ggml authors
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
// This file has been autogenerated by generate_cu_files.py, do not edit manually.
#include "../fattn-vec-f16.cuh"
DECL_FATTN_VEC_F16_CASE(128, GGML_TYPE_Q4_0, GGML_TYPE_Q8_0);

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@ -1,31 +0,0 @@
/**
* llama.cpp - commit 46e3556e01b824e52395fb050b29804b6cff2a7c - do not edit this file
*
* MIT License
*
* Copyright (c) 2023-2024 The ggml authors
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
// This file has been autogenerated by generate_cu_files.py, do not edit manually.
#include "../fattn-vec-f16.cuh"
DECL_FATTN_VEC_F16_CASE(128, GGML_TYPE_Q4_1, GGML_TYPE_F16);

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@ -1,31 +0,0 @@
/**
* llama.cpp - commit 46e3556e01b824e52395fb050b29804b6cff2a7c - do not edit this file
*
* MIT License
*
* Copyright (c) 2023-2024 The ggml authors
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
// This file has been autogenerated by generate_cu_files.py, do not edit manually.
#include "../fattn-vec-f16.cuh"
DECL_FATTN_VEC_F16_CASE(128, GGML_TYPE_Q4_1, GGML_TYPE_Q4_0);

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@ -1,31 +0,0 @@
/**
* llama.cpp - commit 46e3556e01b824e52395fb050b29804b6cff2a7c - do not edit this file
*
* MIT License
*
* Copyright (c) 2023-2024 The ggml authors
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
// This file has been autogenerated by generate_cu_files.py, do not edit manually.
#include "../fattn-vec-f16.cuh"
DECL_FATTN_VEC_F16_CASE(128, GGML_TYPE_Q4_1, GGML_TYPE_Q4_1);

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@ -1,31 +0,0 @@
/**
* llama.cpp - commit 46e3556e01b824e52395fb050b29804b6cff2a7c - do not edit this file
*
* MIT License
*
* Copyright (c) 2023-2024 The ggml authors
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
// This file has been autogenerated by generate_cu_files.py, do not edit manually.
#include "../fattn-vec-f16.cuh"
DECL_FATTN_VEC_F16_CASE(128, GGML_TYPE_Q4_1, GGML_TYPE_Q5_0);

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@ -1,31 +0,0 @@
/**
* llama.cpp - commit 46e3556e01b824e52395fb050b29804b6cff2a7c - do not edit this file
*
* MIT License
*
* Copyright (c) 2023-2024 The ggml authors
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
// This file has been autogenerated by generate_cu_files.py, do not edit manually.
#include "../fattn-vec-f16.cuh"
DECL_FATTN_VEC_F16_CASE(128, GGML_TYPE_Q4_1, GGML_TYPE_Q5_1);

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@ -1,31 +0,0 @@
/**
* llama.cpp - commit 46e3556e01b824e52395fb050b29804b6cff2a7c - do not edit this file
*
* MIT License
*
* Copyright (c) 2023-2024 The ggml authors
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
// This file has been autogenerated by generate_cu_files.py, do not edit manually.
#include "../fattn-vec-f16.cuh"
DECL_FATTN_VEC_F16_CASE(128, GGML_TYPE_Q4_1, GGML_TYPE_Q8_0);

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@ -1,31 +0,0 @@
/**
* llama.cpp - commit 46e3556e01b824e52395fb050b29804b6cff2a7c - do not edit this file
*
* MIT License
*
* Copyright (c) 2023-2024 The ggml authors
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
// This file has been autogenerated by generate_cu_files.py, do not edit manually.
#include "../fattn-vec-f16.cuh"
DECL_FATTN_VEC_F16_CASE(128, GGML_TYPE_Q5_0, GGML_TYPE_F16);

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@ -1,31 +0,0 @@
/**
* llama.cpp - commit 46e3556e01b824e52395fb050b29804b6cff2a7c - do not edit this file
*
* MIT License
*
* Copyright (c) 2023-2024 The ggml authors
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
// This file has been autogenerated by generate_cu_files.py, do not edit manually.
#include "../fattn-vec-f16.cuh"
DECL_FATTN_VEC_F16_CASE(128, GGML_TYPE_Q5_0, GGML_TYPE_Q4_0);

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@ -1,31 +0,0 @@
/**
* llama.cpp - commit 46e3556e01b824e52395fb050b29804b6cff2a7c - do not edit this file
*
* MIT License
*
* Copyright (c) 2023-2024 The ggml authors
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
// This file has been autogenerated by generate_cu_files.py, do not edit manually.
#include "../fattn-vec-f16.cuh"
DECL_FATTN_VEC_F16_CASE(128, GGML_TYPE_Q5_0, GGML_TYPE_Q4_1);

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@ -1,31 +0,0 @@
/**
* llama.cpp - commit 46e3556e01b824e52395fb050b29804b6cff2a7c - do not edit this file
*
* MIT License
*
* Copyright (c) 2023-2024 The ggml authors
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
// This file has been autogenerated by generate_cu_files.py, do not edit manually.
#include "../fattn-vec-f16.cuh"
DECL_FATTN_VEC_F16_CASE(128, GGML_TYPE_Q5_0, GGML_TYPE_Q5_0);

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@ -1,31 +0,0 @@
/**
* llama.cpp - commit 46e3556e01b824e52395fb050b29804b6cff2a7c - do not edit this file
*
* MIT License
*
* Copyright (c) 2023-2024 The ggml authors
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
// This file has been autogenerated by generate_cu_files.py, do not edit manually.
#include "../fattn-vec-f16.cuh"
DECL_FATTN_VEC_F16_CASE(128, GGML_TYPE_Q5_0, GGML_TYPE_Q5_1);

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@ -1,31 +0,0 @@
/**
* llama.cpp - commit 46e3556e01b824e52395fb050b29804b6cff2a7c - do not edit this file
*
* MIT License
*
* Copyright (c) 2023-2024 The ggml authors
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
// This file has been autogenerated by generate_cu_files.py, do not edit manually.
#include "../fattn-vec-f16.cuh"
DECL_FATTN_VEC_F16_CASE(128, GGML_TYPE_Q5_0, GGML_TYPE_Q8_0);

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@ -1,31 +0,0 @@
/**
* llama.cpp - commit 46e3556e01b824e52395fb050b29804b6cff2a7c - do not edit this file
*
* MIT License
*
* Copyright (c) 2023-2024 The ggml authors
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
// This file has been autogenerated by generate_cu_files.py, do not edit manually.
#include "../fattn-vec-f16.cuh"
DECL_FATTN_VEC_F16_CASE(128, GGML_TYPE_Q5_1, GGML_TYPE_F16);

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@ -1,31 +0,0 @@
/**
* llama.cpp - commit 46e3556e01b824e52395fb050b29804b6cff2a7c - do not edit this file
*
* MIT License
*
* Copyright (c) 2023-2024 The ggml authors
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
// This file has been autogenerated by generate_cu_files.py, do not edit manually.
#include "../fattn-vec-f16.cuh"
DECL_FATTN_VEC_F16_CASE(128, GGML_TYPE_Q5_1, GGML_TYPE_Q4_0);

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