Compare commits

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30 Commits

Author SHA1 Message Date
ParthSareen
a4265c278a wip 2025-03-24 11:02:02 -07:00
ParthSareen
ffd6428758 err handling + fixing scope issue 2025-02-11 19:29:48 -08:00
ParthSareen
aa6d5151df wip with json stuff and cleanup 2025-02-11 16:40:40 -08:00
ParthSareen
25edfa6fdb first pass so working 2025-02-04 22:09:22 -08:00
ParthSareen
cc2e44b885 Improved sampler interface 2025-02-03 16:05:15 -08:00
ParthSareen
d5f8670f0a WIP simple SO working 2025-02-03 11:40:06 -08:00
ParthSareen
524029cd6d tested with so 2025-01-31 17:12:39 -08:00
ParthSareen
b973dedb4b saved state 2025-01-30 15:17:42 -08:00
ParthSareen
c56a8b7749 wip 2025-01-30 15:05:25 -08:00
ParthSareen
198fde82aa Enable array type json 2025-01-29 14:54:39 -08:00
ParthSareen
77f709ebd5 cleanup state machine 2025-01-29 14:28:02 -08:00
ParthSareen
73098a2973 WIP working with other stuff 2025-01-29 10:28:22 -08:00
ParthSareen
e93db4d20e WIP 2025-01-27 16:33:55 -08:00
ParthSareen
a2a73ce5e0 wip! 2025-01-23 20:21:50 -08:00
ParthSareen
6ba557f25b checkpoint 2025-01-23 09:46:14 -08:00
ParthSareen
a7c8cc06da json checkpoint 2025-01-21 17:48:12 -08:00
Blake Mizerany
089bbb537d grammar: introduce new grammar package
This package provides a way to convert JSON schemas to equivalent EBNF.
It is intended to be a replacement to llama.cpp's schema_to_grammar.

This is still an early version and does not yet support all JSON schema
features. The to-do list includes:

- minumum/maximum constraints on integer types
- minLength/maxLength constraints on string types
- defs and refs
2025-01-20 14:40:50 -08:00
ParthSareen
7cd9fbbbb1 improve temperature sampler 2025-01-20 13:53:07 -08:00
ParthSareen
b91487f289 Working json sampler 2025-01-15 14:08:54 -08:00
ParthSareen
5b19d4941a addressing comments + cleanup 2025-01-14 16:23:48 -08:00
ParthSareen
5e73f24e16 sampling package 2025-01-14 16:23:38 -08:00
Michael Yang
4aac178cac update ci 2025-01-14 14:25:56 -08:00
Michael Yang
800e21d060 sort devices by type 2025-01-14 14:25:56 -08:00
Michael Yang
5827999e9e next ollama runner
implement llama and mllama model architectures in go using ggml (through
cgo)
2025-01-14 14:25:56 -08:00
Jeffrey Morgan
61676fb506 llama: move grammar tests to llama_test.go (#8411) 2025-01-14 12:55:45 -08:00
Bruce MacDonald
f6f3713001 convert: qwen2 from safetensors (#8408)
Add native support for converting Qwen2 family models (including Qwen2.5)
from safetensors to gguf format so we can run it.
2025-01-14 10:34:37 -08:00
Steve Berdy
a30f347201 readme: add LangChain for .NET to community integrations (#8352) 2025-01-14 09:37:35 -08:00
Jeffrey Morgan
74ea4fb604 remove .prettierrc.json (#8413) 2025-01-14 09:30:34 -08:00
Jeffrey Morgan
6982e9cc96 readme: remove link to missing page 2025-01-13 18:56:31 -08:00
Patrick Devine
ab39872cb4 add new create api doc (#8388) 2025-01-13 17:30:24 -08:00
619 changed files with 13031 additions and 10930 deletions

9
.gitattributes vendored
View File

@@ -7,5 +7,14 @@ llama/**/*.cuh linguist-vendored
llama/**/*.m linguist-vendored llama/**/*.m linguist-vendored
llama/**/*.metal 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 * text=auto
*.go text eol=lf *.go text eol=lf

View File

@@ -1,11 +1,5 @@
name: test 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: concurrency:
# For PRs, later CI runs preempt previous ones. e.g. a force push on a PR # 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. # cancels running CI jobs and starts all new ones.
@@ -27,7 +21,7 @@ jobs:
changes: changes:
runs-on: ubuntu-latest runs-on: ubuntu-latest
outputs: outputs:
RUNNERS: ${{ steps.changes.outputs.RUNNERS }} changed: ${{ steps.changes.outputs.changed }}
steps: steps:
- uses: actions/checkout@v4 - uses: actions/checkout@v4
with: with:
@@ -35,309 +29,61 @@ jobs:
- id: changes - id: changes
run: | run: |
changed() { changed() {
git diff-tree -r --no-commit-id --name-only \ local BASE=${{ github.event.pull_request.base.sha }}
$(git merge-base ${{ github.event.pull_request.base.sha }} ${{ github.event.pull_request.head.sha }}) \ local HEAD=${{ github.event.pull_request.head.sha }}
${{ github.event.pull_request.head.sha }} \ local MERGE_BASE=$(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(' ')))" | xargs python3 -c "import sys; from pathlib import Path; print(any(Path(x).match(glob) for x in sys.argv[1:] for glob in '$*'.split(' ')))"
} }
{ echo changed=$(changed 'llama/llama.cpp/**' 'ml/backend/ggml/ggml/**') | tee -a $GITHUB_OUTPUT
echo RUNNERS=$(changed 'llama/**')
} >>$GITHUB_OUTPUT
runners-linux-cuda: linux:
needs: [changes] needs: [changes]
if: ${{ needs.changes.outputs.RUNNERS == 'True' }} if: ${{ needs.changes.outputs.changed == 'True' }}
strategy: strategy:
matrix: matrix:
cuda-version: include:
- '11.8.0' - container: nvidia/cuda:11.8.0-devel-ubuntu22.04
runs-on: linux preset: CUDA
container: nvidia/cuda:${{ matrix.cuda-version }}-devel-ubuntu20.04 - container: rocm/dev-ubuntu-22.04:6.1.2
preset: ROCm
extra-packages: rocm-libs
runs-on: ubuntu-latest
container: ${{ matrix.container }}
steps: steps:
- uses: actions/checkout@v4
- run: | - 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: env:
DEBIAN_FRONTEND: noninteractive DEBIAN_FRONTEND: noninteractive
- uses: actions/checkout@v4
- uses: actions/setup-go@v4
with:
go-version-file: go.mod
cache: true
- run: go get ./...
- run: | - run: |
git config --global --add safe.directory /__w/ollama/ollama cmake --preset ${{ matrix.preset }}
cores=$(grep '^core id' /proc/cpuinfo |sort -u|wc -l) cmake --build --preset ${{ matrix.preset }} --parallel
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
# 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: test:
strategy: strategy:
matrix: matrix:
os: [ubuntu-latest, macos-latest, windows-2019] os: [ubuntu-latest, macos-latest, windows-latest]
arch: [amd64]
exclude:
- os: ubuntu-latest
arch: arm64
- os: windows-2019
arch: arm64
runs-on: ${{ matrix.os }} runs-on: ${{ matrix.os }}
env: env:
GOARCH: ${{ matrix.arch }}
CGO_ENABLED: '1' CGO_ENABLED: '1'
steps: steps:
- uses: actions/checkout@v4 - 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 - uses: actions/setup-go@v5
with: with:
go-version-file: go.mod go-version-file: go.mod
cache: true - uses: golangci/golangci-lint-action@v6
- run: | with:
case ${{ matrix.arch }} in args: --timeout 10m0s -v
amd64) echo ARCH=amd64 ;;
arm64) echo ARCH=arm64 ;;
esac >>$GITHUB_ENV
shell: bash
- run: go test ./... - run: go test ./...
patches: patches:
needs: [changes]
if: ${{ needs.changes.outputs.RUNNERS == 'True' }}
runs-on: ubuntu-latest runs-on: ubuntu-latest
steps: steps:
- uses: actions/checkout@v4 - uses: actions/checkout@v4
with: - name: Verify patches apply cleanly and do not change files
submodules: recursive
- name: Verify patches carry all the changes
run: | run: |
make apply-patches sync && git diff --compact-summary --exit-code llama make -f Makefile2 clean checkout sync
git diff --compact-summary --exit-code

View File

@@ -1,10 +0,0 @@
{
"trailingComma": "es5",
"tabWidth": 2,
"useTabs": false,
"semi": false,
"singleQuote": true,
"jsxSingleQuote": true,
"printWidth": 120,
"arrowParens": "avoid"
}

45
CMakeLists.txt Normal file
View File

@@ -0,0 +1,45 @@
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_CPU_ALL_VARIANTS ON)
set(GGML_CUDA_PEER_MAX_BATCH_SIZE 128)
set(GGML_LLAMAFILE ON)
set(CMAKE_RUNTIME_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)
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()

96
CMakePresets.json Normal file
View File

@@ -0,0 +1,96 @@
{
"version": 3,
"configurePresets": [
{
"name": "Default",
"binaryDir": "${sourceDir}/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"
},
{
"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"
}
]
}

66
Dockerfile2 Normal file
View File

@@ -0,0 +1,66 @@
ARG CUDA_11_VERSION=11.3
ARG CUDA_12_VERSION=12.4
ARG ROCM_VERSION=6.1.2
ARG JETPACK_5_VERSION=r35.4.1
ARG JETPACK_6_VERSION=r36.2.0
ARG CMAKE_VERSION=3.31.2
FROM --platform=linux/amd64 rocm/dev-centos-7:${ROCM_VERSION}-complete AS base
ARG CMAKE_VERSION
RUN curl -fsSL https://github.com/Kitware/CMake/releases/download/v${CMAKE_VERSION}/cmake-${CMAKE_VERSION}-linux-x86_64.tar.gz | tar xz -C /usr --strip-components 1
RUN sed -i -e 's/mirror.centos.org/vault.centos.org/g' -e 's/^#.*baseurl=http/baseurl=http/g' -e 's/^mirrorlist=http/#mirrorlist=http/g' /etc/yum.repos.d/*.repo \
&& yum-config-manager --add-repo https://developer.download.nvidia.com/compute/cuda/repos/rhel7/x86_64/cuda-rhel7.repo
# FROM --platform=linux/arm64 rockylinux:8 AS base
# ARG CMAKE_VERSION
# RUN curl -fsSL https://github.com/Kitware/CMake/releases/download/v${CMAKE_VERSION}/cmake-${CMAKE_VERSION}-linux-aarch64.tar.gz | tar xz -C /usr --strip-components 1
# RUN yum-config-manager --add-repo https://developer.download.nvidia.com/compute/cuda/repos/rhel8/sbsa/cuda-rhel8.repo
FROM base AS amd64
ARG CUDA_11_VERSION
ARG CUDA_12_VERSION
RUN yum install -y cuda-toolkit-${CUDA_11_VERSION//./-} \
&& yum install -y cuda-toolkit-${CUDA_12_VERSION//./-}
COPY CMakeLists.txt CMakeLists.txt
COPY ml/backend/ggml/ggml ml/backend/ggml/ggml
FROM --platform=linux/amd64 amd64 AS cuda_11
ENV PATH=/usr/local/cuda-${CUDA_11_VERSION}/bin:$PATH
RUN cmake -S . -B build -DCMAKE_CUDA_ARCHITECTURES="50;52;53;60;61;62;70;72;75;80;86"
RUN cmake --build build --target ggml-cuda -j
FROM --platform=linux/amd64 amd64 AS cuda_12
ENV PATH=/usr/local/cuda-${CUDA_12_VERSION}/bin:$PATH
RUN cmake -S . -B build -DCMAKE_CUDA_ARCHITECTURES="60;61;62;70;72;75;80;86;87;89;90;90a"
RUN cmake --build build --target ggml-cuda -j
FROM --platform=linux/amd64 amd64 AS rocm
RUN cmake -S . -B build -DCMAKE_HIP_ARCHITECTURES="gfx900;gfx940;gfx941;gfx942;gfx1010;gfx1012;gfx1030;gfx1100;gfx1101;gfx1102"
RUN cmake --build build --target ggml-hip -j
FROM --platform=linux/arm64 nvcr.io/nvidia/l4t-jetpack:${JETPACK_5_VERSION} AS jetpack_5
ARG CMAKE_VERSION
RUN curl -fsSL https://github.com/Kitware/CMake/releases/download/v${CMAKE_VERSION}/cmake-${CMAKE_VERSION}-linux-aarch64.tar.gz | tar xz -C /usr --strip-components 1
COPY CMakeLists.txt .
COPY ml/backend/ggml/ggml .
RUN cmake -S . -B build \
-DCMAKE_CUDA_ARCHITECTURES="72;87"
RUN cmake --build build --target ggml-cuda
FROM --platform=linux/arm64 nvcr.io/nvidia/l4t-jetpack:${JETPACK_6_VERSION} AS jetpack_6
ARG CMAKE_VERSION
RUN curl -fsSL https://github.com/Kitware/CMake/releases/download/v${CMAKE_VERSION}/cmake-${CMAKE_VERSION}-linux-aarch64.tar.gz | tar xz -C /usr --strip-components 1
COPY CMakeLists.txt .
COPY ml/backend/ggml/ggml .
RUN cmake -S . -B build \
-DCMAKE_CUDA_ARCHITECTURES="87"
RUN cmake --build build --target ggml-cuda
FROM --platform=linux/amd64 golang:1.23
COPY --from=cuda_11 build/ml/backend/ggml/ggml/src/ggml-cuda/libggml-cuda.so libggml-cuda-11.so
COPY --from=cuda_12 build/ml/backend/ggml/ggml/src/ggml-cuda/libggml-cuda.so libggml-cuda-12.so
COPY --from=rocm build/ml/backend/ggml/ggml/src/ggml-hip/libggml-hip.so libggml-hip.so
# FROM --platform=linux/arm64 golang:1.23
# COPY --from=jetpack_5 build/ml/backend/ggml/ggml/src/ggml-cuda/libggml-cuda.so libggml-cuda-jetpack-5.so
# COPY --from=jetpack_6 build/ml/backend/ggml/ggml/src/ggml-cuda/libggml-cuda.so libggml-cuda-jetpack-6.so

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))

View File

@@ -137,7 +137,7 @@ ollama run mario
Hello! It's your friend Mario. Hello! It's your friend Mario.
``` ```
For more examples, see the [examples](examples) directory. For more information on working with a Modelfile, see the [Modelfile](docs/modelfile.md) documentation. For more information on working with a Modelfile, see the [Modelfile](docs/modelfile.md) documentation.
## CLI Reference ## CLI Reference
@@ -441,6 +441,7 @@ See the [API documentation](./docs/api.md) for all endpoints.
- [LangChainGo](https://github.com/tmc/langchaingo/) with [example](https://github.com/tmc/langchaingo/tree/main/examples/ollama-completion-example) - [LangChainGo](https://github.com/tmc/langchaingo/) with [example](https://github.com/tmc/langchaingo/tree/main/examples/ollama-completion-example)
- [LangChain4j](https://github.com/langchain4j/langchain4j) with [example](https://github.com/langchain4j/langchain4j-examples/tree/main/ollama-examples/src/main/java) - [LangChain4j](https://github.com/langchain4j/langchain4j) with [example](https://github.com/langchain4j/langchain4j-examples/tree/main/ollama-examples/src/main/java)
- [LangChainRust](https://github.com/Abraxas-365/langchain-rust) with [example](https://github.com/Abraxas-365/langchain-rust/blob/main/examples/llm_ollama.rs) - [LangChainRust](https://github.com/Abraxas-365/langchain-rust) with [example](https://github.com/Abraxas-365/langchain-rust/blob/main/examples/llm_ollama.rs)
- [LangChain for .NET](https://github.com/tryAGI/LangChain) with [example](https://github.com/tryAGI/LangChain/blob/main/examples/LangChain.Samples.OpenAI/Program.cs)
- [LLPhant](https://github.com/theodo-group/LLPhant?tab=readme-ov-file#ollama) - [LLPhant](https://github.com/theodo-group/LLPhant?tab=readme-ov-file#ollama)
- [LlamaIndex](https://docs.llamaindex.ai/en/stable/examples/llm/ollama/) and [LlamaIndexTS](https://ts.llamaindex.ai/modules/llms/available_llms/ollama) - [LlamaIndex](https://docs.llamaindex.ai/en/stable/examples/llm/ollama/) and [LlamaIndexTS](https://ts.llamaindex.ai/modules/llms/available_llms/ollama)
- [LiteLLM](https://github.com/BerriAI/litellm) - [LiteLLM](https://github.com/BerriAI/litellm)

63
cache/cache.go vendored Normal file
View File

@@ -0,0 +1,63 @@
package cache
import (
"github.com/ollama/ollama/ml"
)
type Options struct {
Position int
}
type Cache interface {
Sub(i int) Cache
Put(ctx ml.Context, key, value ml.Tensor, opts Options) (ml.Tensor, ml.Tensor)
}
type Simple struct {
DType ml.DType
Capacity int
keys, values []ml.Tensor
}
func (c *Simple) 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)...)
}
return &Simple{
keys: c.keys[i : i+1],
values: c.values[i : i+1],
Capacity: c.Capacity,
DType: c.DType,
}
}
func (c *Simple) Put(ctx ml.Context, key, value ml.Tensor, opts Options) (ml.Tensor, ml.Tensor) {
if c.keys[0] == nil || c.values[0] == nil {
c.keys[0] = ctx.Zeros(c.DType, int(key.Dim(0)*key.Dim(1))*c.Capacity)
c.values[0] = ctx.Zeros(c.DType, int(value.Dim(0)*value.Dim(1))*c.Capacity)
}
ctx.Forward(key.Copy(ctx, c.keys[0].View(ctx, int(key.Stride(2))*opts.Position, int(key.Dim(0)*key.Dim(1)*key.Dim(2)))))
ctx.Forward(value.Copy(ctx, c.values[0].View(ctx, int(value.Stride(2))*opts.Position, int(value.Dim(0)*value.Dim(1)*value.Dim(2)))))
n := min(c.Capacity, int(key.Dim(2))+opts.Position)
key = c.keys[0].View(ctx, 0,
int(key.Dim(0)), int(key.Stride(1)),
int(key.Dim(1)), int(key.Stride(2)),
n,
)
value = c.values[0].View(ctx, 0,
int(value.Dim(0)), int(value.Stride(1)),
int(value.Dim(1)), int(value.Stride(2)),
n,
)
// TODO shift context if necessary
return key, value
}

View File

@@ -9,7 +9,7 @@ import (
"log/slog" "log/slog"
"strings" "strings"
"github.com/ollama/ollama/llm" "github.com/ollama/ollama/fs/ggml"
) )
type ModelParameters struct { type ModelParameters struct {
@@ -27,8 +27,8 @@ type AdapterParameters struct {
} `json:"lora_parameters"` } `json:"lora_parameters"`
} }
func (ModelParameters) KV(t *Tokenizer) llm.KV { func (ModelParameters) KV(t *Tokenizer) ggml.KV {
kv := llm.KV{ kv := ggml.KV{
"general.file_type": uint32(1), "general.file_type": uint32(1),
"general.quantization_version": uint32(2), "general.quantization_version": uint32(2),
"tokenizer.ggml.pre": t.Pre, "tokenizer.ggml.pre": t.Pre,
@@ -54,7 +54,7 @@ func (ModelParameters) KV(t *Tokenizer) llm.KV {
return kv return kv
} }
func (p AdapterParameters) KV() llm.KV { func (p AdapterParameters) KV() ggml.KV {
var alpha float32 var alpha float32
if p.LoraParameters.Alpha == 0 { if p.LoraParameters.Alpha == 0 {
alpha = float32(p.Alpha) alpha = float32(p.Alpha)
@@ -62,7 +62,7 @@ func (p AdapterParameters) KV() llm.KV {
alpha = p.LoraParameters.Alpha alpha = p.LoraParameters.Alpha
} }
kv := llm.KV{ kv := ggml.KV{
"adapter.lora.alpha": alpha, "adapter.lora.alpha": alpha,
"adapter.type": "lora", "adapter.type": "lora",
"general.file_type": uint32(1), "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 { func (ModelParameters) writeFile(ws io.WriteSeeker, kv ggml.KV, ts []ggml.Tensor) error {
return llm.WriteGGUF(ws, kv, ts) return ggml.WriteGGUF(ws, kv, ts)
} }
func (AdapterParameters) writeFile(ws io.WriteSeeker, kv llm.KV, ts []llm.Tensor) error { func (AdapterParameters) writeFile(ws io.WriteSeeker, kv ggml.KV, ts []ggml.Tensor) error {
return llm.WriteGGUF(ws, kv, ts) return ggml.WriteGGUF(ws, kv, ts)
} }
type ModelConverter interface { type ModelConverter interface {
// KV maps parameters to LLM key-values // 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 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. // Replacements returns a list of string pairs to replace in tensor names.
// See [strings.Replacer](https://pkg.go.dev/strings#Replacer) for details // See [strings.Replacer](https://pkg.go.dev/strings#Replacer) for details
Replacements() []string Replacements() []string
@@ -99,7 +99,7 @@ type ModelConverter interface {
// specialTokenTypes returns any special token types the model uses // specialTokenTypes returns any special token types the model uses
specialTokenTypes() []string specialTokenTypes() []string
// writeFile writes the model to the provided io.WriteSeeker // 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 { type moreParser interface {
@@ -108,17 +108,17 @@ type moreParser interface {
type AdapterConverter interface { type AdapterConverter interface {
// KV maps parameters to LLM key-values // 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 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. // Replacements returns a list of string pairs to replace in tensor names.
// See [strings.Replacer](https://pkg.go.dev/strings#Replacer) for details // See [strings.Replacer](https://pkg.go.dev/strings#Replacer) for details
Replacements() []string 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") bts, err := fs.ReadFile(fsys, "adapter_config.json")
if err != nil { if err != nil {
return err return err
@@ -187,6 +187,8 @@ func ConvertModel(fsys fs.FS, ws io.WriteSeeker) error {
conv = &gemma2Model{} conv = &gemma2Model{}
case "Phi3ForCausalLM": case "Phi3ForCausalLM":
conv = &phi3Model{} conv = &phi3Model{}
case "Qwen2ForCausalLM":
conv = &qwen2Model{}
case "BertModel": case "BertModel":
conv = &bertModel{} conv = &bertModel{}
default: default:

View File

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

View File

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

View File

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

View File

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

View File

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

View File

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

View File

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

View File

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

79
convert/convert_qwen2.go Normal file
View File

@@ -0,0 +1,79 @@
package convert
import "github.com/ollama/ollama/fs/ggml"
type qwen2Model struct {
ModelParameters
MaxPositionEmbeddings uint32 `json:"max_position_embeddings"`
HiddenSize uint32 `json:"hidden_size"`
HiddenLayers uint32 `json:"num_hidden_layers"`
IntermediateSize uint32 `json:"intermediate_size"`
NumAttentionHeads uint32 `json:"num_attention_heads"`
NumKeyValueHeads uint32 `json:"num_key_value_heads"`
RopeTheta float32 `json:"rope_theta"`
RopeScaling struct {
Type string `json:"type"`
Factor ropeFactor `json:"factor"`
OriginalMaxPositionEmbeddings uint32 `json:"original_max_position_embeddings"`
} `json:"rope_scaling"`
RMSNormEPS float32 `json:"rms_norm_eps"`
}
var _ ModelConverter = (*qwen2Model)(nil)
func (q *qwen2Model) KV(t *Tokenizer) ggml.KV {
kv := q.ModelParameters.KV(t)
kv["general.architecture"] = "qwen2"
kv["qwen2.block_count"] = q.HiddenLayers
kv["qwen2.context_length"] = q.MaxPositionEmbeddings
kv["qwen2.embedding_length"] = q.HiddenSize
kv["qwen2.feed_forward_length"] = q.IntermediateSize
kv["qwen2.attention.head_count"] = q.NumAttentionHeads
kv["qwen2.attention.head_count_kv"] = q.NumKeyValueHeads
kv["qwen2.rope.freq_base"] = q.RopeTheta
kv["qwen2.attention.layer_norm_rms_epsilon"] = q.RMSNormEPS
switch q.RopeScaling.Type {
case "":
// no scaling
case "yarn":
kv["qwen2.rope.scaling.type"] = q.RopeScaling.Type
kv["qwen2.rope.scaling.factor"] = q.RopeScaling.Factor
default:
panic("unknown rope scaling type")
}
return kv
}
func (q *qwen2Model) Tensors(ts []Tensor) []ggml.Tensor {
var out []ggml.Tensor
for _, t := range ts {
out = append(out, ggml.Tensor{
Name: t.Name(),
Kind: t.Kind(),
Shape: t.Shape(),
WriterTo: t,
})
}
return out
}
func (p *qwen2Model) Replacements() []string {
return []string{
"lm_head", "output",
"model.embed_tokens", "token_embd",
"model.layers", "blk",
"input_layernorm", "attn_norm",
"self_attn.k_proj", "attn_k",
"self_attn.v_proj", "attn_v",
"self_attn.q_proj", "attn_q",
"self_attn.o_proj", "attn_output",
"mlp.down_proj", "ffn_down",
"mlp.gate_proj", "ffn_gate",
"mlp.up_proj", "ffn_up",
"post_attention_layernorm", "ffn_norm",
"model.norm", "output_norm",
}
}

View File

@@ -20,7 +20,7 @@ import (
"golang.org/x/exp/maps" "golang.org/x/exp/maps"
"github.com/ollama/ollama/llm" "github.com/ollama/ollama/fs/ggml"
) )
type tensorData struct { type tensorData struct {
@@ -29,7 +29,7 @@ type tensorData struct {
Shape []int `json:"shape"` 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() t.Helper()
f, err := os.CreateTemp(t.TempDir(), "f16") 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() }) t.Cleanup(func() { r.Close() })
m, _, err := llm.DecodeGGML(r, math.MaxInt) m, _, err := ggml.Decode(r, math.MaxInt)
if err != nil { if err != nil {
t.Fatal(err) 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() 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) actual := make(map[string]string)
for k, v := range kv { for k, v := range kv {
if s, ok := v.(json.Marshaler); !ok { 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() sha256sum := sha256.New()
sr := io.NewSectionReader(f, int64(tensors.Offset+tensor.Offset), int64(tensor.Size())) sr := io.NewSectionReader(f, int64(tensors.Offset+tensor.Offset), int64(tensor.Size()))
if _, err := io.Copy(sha256sum, sr); err != nil { if _, err := io.Copy(sha256sum, sr); err != nil {
@@ -108,6 +108,7 @@ func TestConvertModel(t *testing.T) {
"Phi-3-mini-128k-instruct", "Phi-3-mini-128k-instruct",
"all-MiniLM-L6-v2", "all-MiniLM-L6-v2",
"gemma-2-9b-it", "gemma-2-9b-it",
"Qwen2.5-0.5B-Instruct",
} }
for i := range cases { for i := range cases {
@@ -330,7 +331,7 @@ func TestConvertAdapter(t *testing.T) {
} }
defer r.Close() defer r.Close()
m, _, err := llm.DecodeGGML(r, math.MaxInt) m, _, err := ggml.Decode(r, math.MaxInt)
if err != nil { if err != nil {
t.Fatal(err) t.Fatal(err)
} }

View File

@@ -0,0 +1,314 @@
{
"general.architecture": "qwen2",
"general.file_type": "1",
"general.parameter_count": "494032768",
"general.quantization_version": "2",
"output_norm.weight": "93a01a6db3419e85320a244bbf8ae81c43033b1d10c342bea3797ff2ce348390",
"qwen2.attention.head_count": "14",
"qwen2.attention.head_count_kv": "2",
"qwen2.attention.layer_norm_rms_epsilon": "1e-06",
"qwen2.block_count": "24",
"qwen2.context_length": "32768",
"qwen2.embedding_length": "896",
"qwen2.feed_forward_length": "4864",
"qwen2.rope.freq_base": "1e+06",
"token_embd.weight": "d74257dc547b48be5ae7b93f1c9af072c0c42dbbb85503078e25c59cd09e68d0",
"tokenizer.ggml.add_eos_token": "false",
"tokenizer.ggml.add_padding_token": "false",
"tokenizer.ggml.eos_token_id": "151645",
"tokenizer.ggml.merges": "6b1b1c58f1223d74f9095929d3e6416cdd74784440221a5507b87b8197f2bfd2",
"tokenizer.ggml.model": "gpt2",
"tokenizer.ggml.padding_token_id": "151643",
"tokenizer.ggml.pre": "qwen2",
"tokenizer.ggml.scores": "94e247e531e8b0fa3d248f3de09c9beae0c87da8106208a8edfaac0b8ec4b53d",
"tokenizer.ggml.token_type": "b178dbc9d1b2e08f84d02918e00fc2de2619a250e6c188c91a6605f701860055",
"tokenizer.ggml.tokens": "1d93f6679b23a1152b725f7f473792d54d53c1040c5250d3e46b42f81e0a1a34",
"blk.0.attn_k.bias": "5ce6617845f66c34515978d23d52e729c298d8bffa28c356a0428bef17142cf1",
"blk.0.attn_k.weight": "a960832a9e0e83e4d95402e5d1a01cc74300fcca0c381237162126330e1a7af8",
"blk.0.attn_norm.weight": "32c7d51cd0958f1f1771174192db341f9770516d7595a2f0fd18a4d78bd5aba3",
"blk.0.attn_output.weight": "c67e6e7e868354a11bf9121c70ee56c140b20eec611a8955e7dfe54a21d40a98",
"blk.0.attn_q.bias": "3e9e994eb1f03bccfc82f8bb3c324c920d42d547e07de5be83be12c428645063",
"blk.0.attn_q.weight": "dc12132f789b97cfa1e3f5775ceb835247fa67aa47400fd09c8f9f3769208583",
"blk.0.attn_v.bias": "a3fd0757b31fdc78af5ec320332d239c1a79d34e8804df06c5454e86955e8cc9",
"blk.0.attn_v.weight": "f43094a2134c7ee2dcc52aac3c8b7d9d64fb0295a8adb94cabfd49213f017b84",
"blk.0.ffn_down.weight": "18c2aec92db14f21976838a8c35d5575f80d0e4b1e05ccc0d8388d5877e80147",
"blk.0.ffn_gate.weight": "a3a1c4ef38f8f750eabadfe3d83bbb0f77941eec1cc1a388e51852e99c8691f6",
"blk.0.ffn_norm.weight": "b59b779c42d44b5c4cec41e39b4eb61e0491a07c1b3e946ccb5b8d5c657eda3f",
"blk.0.ffn_up.weight": "db64f09987ea59449e90abae5a2ffcc20efd9203f0eebec77a6aacb5809d6cff",
"blk.1.attn_k.bias": "a5c8c5671703ec0aa0143ff70a20ffdd67b5d5790ca1dfa5bba4e87e4071ed9f",
"blk.1.attn_k.weight": "835c7c7cc95b3cb2e55bd9cac585aa0760a033896621d3e06421f3378c540f7d",
"blk.1.attn_norm.weight": "f4c36fb6c14fce721fab0de78cc118d6f66e3a3d3ea0017bb14aade24c3c5434",
"blk.1.attn_output.weight": "cc1e80310c97cef068e48e40b7096f32fa2138519d6209c6a1a9994985999016",
"blk.1.attn_q.bias": "bc332780e66b0aac80ec5e63ac32344919a840db2fcc8f87bcef16a43a54138e",
"blk.1.attn_q.weight": "d766f06c925cce38d4b31b2165b3448e1fb49a7d561985f95d9cd2fcba52367a",
"blk.1.attn_v.bias": "9f486626fb6ed9ac84970a71e9b9818dd2758501fd3f61bb1c08540dcc7a8631",
"blk.1.attn_v.weight": "e873d1e5bd4f4d6abfd47c0f55119c2c111105838753ee273a03c5ccea25ce5c",
"blk.1.ffn_down.weight": "b3ce82b093f187344de04284b1783a452de1b72640914609b8f830dc81580521",
"blk.1.ffn_gate.weight": "5cd44ad237edaca525a28a3ac13975d1b565f576d6a8003237a341ae0d156f2e",
"blk.1.ffn_norm.weight": "4ac774ee8afaee119610c46aa1ff89fc6c9084a29d226075bc4aa4d2f15f746c",
"blk.1.ffn_up.weight": "042d81ab5f1983d85c81213232f3bfc05a9302d9dfaa98d931ebba326b6058b8",
"blk.10.attn_k.bias": "767ecfeacd60a2c2221ac4d76c357190849dd9cdf64ced418d9d0c7949101401",
"blk.10.attn_k.weight": "a9f3df343227537636be8202303453086375091944e498bad11e0b91e45e8c71",
"blk.10.attn_norm.weight": "01acd0e7b3e363f873dbfde6f0995ffcce83f5aaa10ff91c31dbf775035f6d5a",
"blk.10.attn_output.weight": "a531fe660769604ab869f01b203eb115e025cad4c0baeacdd1bcca99cf6d0264",
"blk.10.attn_q.bias": "356a02c9163dd660c1340fbe1e049b335ac6178891e00996131bba9ab4cb3e59",
"blk.10.attn_q.weight": "81be0cfb227339d83f954cd8dcf35828441211c6e1d184060e3eb76085041e2f",
"blk.10.attn_v.bias": "ed0450653284b62f8bf2c2db19c0ff7a6cf3cda1324d0a044c5e3db7bb692bd3",
"blk.10.attn_v.weight": "c1247ff7092babd2ed979883095b9aa022b2996cab1c77fb9e6176ddc1498d16",
"blk.10.ffn_down.weight": "fda7544965dc9af874f1062c22151c6cefc8ba08cbe15dc67aa89979e77b2de4",
"blk.10.ffn_gate.weight": "9f2632b1dee7304d10c70bd38d85bb1f148a628a8468f894f57975b8a2f1d945",
"blk.10.ffn_norm.weight": "94f8cbd6b17a4d5aabd93fa32930a687db3b11f086142f1cd71c535c11adcad4",
"blk.10.ffn_up.weight": "8dc2f8db0474939a277a3d89db34c3bcc3381cfea57bd05a8426a164634d9112",
"blk.11.attn_k.bias": "3b8e5a662b19411e3f6530714b766aad2ee41eebc8161bec9db0bc82d383a6e0",
"blk.11.attn_k.weight": "2c29f1ed1ce53ce9604e9ea3663c2c373157e909a0d6064a8920005f6d15dad9",
"blk.11.attn_norm.weight": "48f68a99c3da4ab4c9e492677b606d1b8e0e3de1fdbf6a977523f97b8c21ec31",
"blk.11.attn_output.weight": "5859f3838a94898b020c23040941ed88f4fcb132db400d0849f30a01f62c0f1c",
"blk.11.attn_q.bias": "c5ad89a5628f2bd81252ef44ef6bbcbff15c33ad16fba66435509b959c2af6d3",
"blk.11.attn_q.weight": "d102104e5d61c1e3219564f1d0149fd593db6c6daa9f3872460c84403323cfef",
"blk.11.attn_v.bias": "8653f7d48c5f75a5b55630819f99ecf01c932f12d33fd1a3ee634613e70edde8",
"blk.11.attn_v.weight": "e0a7c7d89b9f2d0d781ce85330022229126e130a8600a09d4a5f920f0bbd50b2",
"blk.11.ffn_down.weight": "4a22b3361eba8bbe1d9a6fda1812618e894c49f13bcacb505defa9badb6b96a6",
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}

View File

@@ -100,6 +100,8 @@ func parseTokenizer(fsys fs.FS, specialTokenTypes []string) (*Tokenizer, error)
t.Pre = "deepseek-llm" t.Pre = "deepseek-llm"
case "21cde974d587f0d54dc8d56b183cc1e6239600172035c68fbd6d4b9f8da0576e": case "21cde974d587f0d54dc8d56b183cc1e6239600172035c68fbd6d4b9f8da0576e":
t.Pre = "deepseek-coder" t.Pre = "deepseek-coder"
case "1ff7f41064896984db5d1bb6ff64fa4bc29007d08c1b439e505b7392777a319e":
t.Pre = "qwen2"
case "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855": case "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855":
// noop, empty pretokenizer // noop, empty pretokenizer
default: default:

View File

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

View File

@@ -928,14 +928,25 @@ A single JSON object is returned:
POST /api/create POST /api/create
``` ```
Create a model from a [`Modelfile`](./modelfile.md). It is recommended to set `modelfile` to the content of the Modelfile rather than just set `path`. This is a requirement for remote create. Remote model creation must also create any file blobs, fields such as `FROM` and `ADAPTER`, explicitly with the server using [Create a Blob](#create-a-blob) and the value to the path indicated in the response. Create a model from:
* another model;
* a safetensors directory; or
* a GGUF file.
If you are creating a model from a safetensors directory or from a GGUF file, you must [create a blob](#create-a-blob) for each of the files and then use the file name and SHA256 digest associated with each blob in the `files` field.
### Parameters ### Parameters
- `model`: name of the model to create - `model`: name of the model to create
- `modelfile` (optional): contents of the Modelfile - `from`: (optional) name of an existing model to create the new model from
- `files`: (optional) a dictionary of file names to SHA256 digests of blobs to create the model from
- `adapters`: (optional) a dictionary of file names to SHA256 digests of blobs for LORA adapters
- `template`: (optional) the prompt template for the model
- `license`: (optional) a string or list of strings containing the license or licenses for the model
- `system`: (optional) a string containing the system prompt for the model
- `parameters`: (optional) a dictionary of parameters for the model (see [Modelfile](./modelfile.md#valid-parameters-and-values) for a list of parameters)
- `messages`: (optional) a list of message objects used to create a conversation
- `stream`: (optional) if `false` the response will be returned as a single response object, rather than a stream of objects - `stream`: (optional) if `false` the response will be returned as a single response object, rather than a stream of objects
- `path` (optional): path to the Modelfile
- `quantize` (optional): quantize a non-quantized (e.g. float16) model - `quantize` (optional): quantize a non-quantized (e.g. float16) model
#### Quantization types #### Quantization types
@@ -961,14 +972,15 @@ Create a model from a [`Modelfile`](./modelfile.md). It is recommended to set `m
#### Create a new model #### Create a new model
Create a new model from a `Modelfile`. Create a new model from an existing model.
##### Request ##### Request
```shell ```shell
curl http://localhost:11434/api/create -d '{ curl http://localhost:11434/api/create -d '{
"model": "mario", "model": "mario",
"modelfile": "FROM llama3\nSYSTEM You are mario from Super Mario Bros." "from": "llama3.2",
"system": "You are Mario from Super Mario Bros."
}' }'
``` ```
@@ -999,7 +1011,7 @@ Quantize a non-quantized model.
```shell ```shell
curl http://localhost:11434/api/create -d '{ curl http://localhost:11434/api/create -d '{
"model": "llama3.1:quantized", "model": "llama3.1:quantized",
"modelfile": "FROM llama3.1:8b-instruct-fp16", "from": "llama3.1:8b-instruct-fp16",
"quantize": "q4_K_M" "quantize": "q4_K_M"
}' }'
``` ```
@@ -1019,52 +1031,112 @@ A stream of JSON objects is returned:
{"status":"success"} {"status":"success"}
``` ```
#### Create a model from GGUF
### Check if a Blob Exists Create a model from a GGUF file. The `files` parameter should be filled out with the file name and SHA256 digest of the GGUF file you wish to use. Use [/api/blobs/:digest](#push-a-blob) to push the GGUF file to the server before calling this API.
##### Request
```shell
curl http://localhost:11434/api/create -d '{
"model": "my-gguf-model",
"files": {
"test.gguf": "sha256:432f310a77f4650a88d0fd59ecdd7cebed8d684bafea53cbff0473542964f0c3"
}
}'
```
##### Response
A stream of JSON objects is returned:
```
{"status":"parsing GGUF"}
{"status":"using existing layer sha256:432f310a77f4650a88d0fd59ecdd7cebed8d684bafea53cbff0473542964f0c3"}
{"status":"writing manifest"}
{"status":"success"}
```
#### Create a model from a Safetensors directory
The `files` parameter should include a dictionary of files for the safetensors model which includes the file names and SHA256 digest of each file. Use [/api/blobs/:digest](#push-a-blob) to first push each of the files to the server before calling this API. Files will remain in the cache until the Ollama server is restarted.
##### Request
```shell
curl http://localhost:11434/api/create -d '{
"model": "fred",
"files": {
"config.json": "sha256:dd3443e529fb2290423a0c65c2d633e67b419d273f170259e27297219828e389",
"generation_config.json": "sha256:88effbb63300dbbc7390143fbbdd9d9fa50587b37e8bfd16c8c90d4970a74a36",
"special_tokens_map.json": "sha256:b7455f0e8f00539108837bfa586c4fbf424e31f8717819a6798be74bef813d05",
"tokenizer.json": "sha256:bbc1904d35169c542dffbe1f7589a5994ec7426d9e5b609d07bab876f32e97ab",
"tokenizer_config.json": "sha256:24e8a6dc2547164b7002e3125f10b415105644fcf02bf9ad8b674c87b1eaaed6",
"model.safetensors": "sha256:1ff795ff6a07e6a68085d206fb84417da2f083f68391c2843cd2b8ac6df8538f"
}
}'
```
##### Response
A stream of JSON objects is returned:
```shell
{"status":"converting model"}
{"status":"creating new layer sha256:05ca5b813af4a53d2c2922933936e398958855c44ee534858fcfd830940618b6"}
{"status":"using autodetected template llama3-instruct"}
{"status":"using existing layer sha256:56bb8bd477a519ffa694fc449c2413c6f0e1d3b1c88fa7e3c9d88d3ae49d4dcb"}
{"status":"writing manifest"}
{"status":"success"}
```
## Check if a Blob Exists
```shell ```shell
HEAD /api/blobs/:digest HEAD /api/blobs/:digest
``` ```
Ensures that the file blob used for a FROM or ADAPTER field exists on the server. This is checking your Ollama server and not ollama.com. Ensures that the file blob (Binary Large Object) used with create a model exists on the server. This checks your Ollama server and not ollama.com.
#### Query Parameters ### Query Parameters
- `digest`: the SHA256 digest of the blob - `digest`: the SHA256 digest of the blob
#### Examples ### Examples
##### Request #### Request
```shell ```shell
curl -I http://localhost:11434/api/blobs/sha256:29fdb92e57cf0827ded04ae6461b5931d01fa595843f55d36f5b275a52087dd2 curl -I http://localhost:11434/api/blobs/sha256:29fdb92e57cf0827ded04ae6461b5931d01fa595843f55d36f5b275a52087dd2
``` ```
##### Response #### Response
Return 200 OK if the blob exists, 404 Not Found if it does not. Return 200 OK if the blob exists, 404 Not Found if it does not.
### Create a Blob ## Push a Blob
```shell ```shell
POST /api/blobs/:digest POST /api/blobs/:digest
``` ```
Create a blob from a file on the server. Returns the server file path. Push a file to the Ollama server to create a "blob" (Binary Large Object).
#### Query Parameters ### Query Parameters
- `digest`: the expected SHA256 digest of the file - `digest`: the expected SHA256 digest of the file
#### Examples ### Examples
##### Request #### Request
```shell ```shell
curl -T model.bin -X POST http://localhost:11434/api/blobs/sha256:29fdb92e57cf0827ded04ae6461b5931d01fa595843f55d36f5b275a52087dd2 curl -T model.gguf -X POST http://localhost:11434/api/blobs/sha256:29fdb92e57cf0827ded04ae6461b5931d01fa595843f55d36f5b275a52087dd2
``` ```
##### Response #### Response
Return 201 Created if the blob was successfully created, 400 Bad Request if the digest used is not expected. Return 201 Created if the blob was successfully created, 400 Bad Request if the digest used is not expected.

View File

@@ -1,15 +1,15 @@
package llm package ggml
import ( import (
"encoding/binary" "encoding/binary"
"errors" "errors"
"fmt" "fmt"
"io" "io"
"log/slog"
"slices" "slices"
"strings" "strings"
"sync"
"github.com/ollama/ollama/util/bufioutil" "github.com/ollama/ollama/fs/util/bufioutil"
) )
type GGML struct { type GGML struct {
@@ -19,145 +19,168 @@ type GGML struct {
type model interface { type model interface {
KV() KV KV() KV
Tensors() *Tensors Tensors() Tensors
} }
type KV map[string]any 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 { func (kv KV) Architecture() string {
if s, ok := kv["general.architecture"].(string); ok { return kv.String("general.architecture", "unknown")
return s
}
return "unknown"
} }
func (kv KV) Kind() string { func (kv KV) Kind() string {
if s, ok := kv["general.type"].(string); ok { return kv.String("general.type", "unknown")
return s
}
return "unknown"
} }
func (kv KV) ParameterCount() uint64 { func (kv KV) ParameterCount() uint64 {
return kv.u64("general.parameter_count") return keyValue[uint64](kv, "general.parameter_count")
} }
func (kv KV) FileType() fileType { func (kv KV) FileType() fileType {
if u64 := kv.u64("general.file_type"); u64 > 0 { if t := kv.Uint("general.file_type"); t > 0 {
return fileType(uint32(u64)) return fileType(t)
} }
return fileTypeUnknown return fileTypeUnknown
} }
func (kv KV) BlockCount() uint64 { 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 { 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 { func (kv KV) HeadCountKV() uint64 {
if headCountKV := kv.u64(fmt.Sprintf("%s.attention.head_count_kv", kv.Architecture())); headCountKV > 0 { return uint64(kv.Uint("attention.head_count_kv", 1))
return headCountKV
}
return 1
} }
func (kv KV) EmbeddingHeadCount() uint64 { func (kv KV) EmbeddingHeadCount() uint64 {
if heads := kv.HeadCount(); heads > 0 { if heads := kv.HeadCount(); heads > 0 {
return kv.EmbeddingLength() / kv.HeadCount() return kv.EmbeddingLength() / heads
} }
return 0 return 0
} }
func (kv KV) EmbeddingHeadCountK() uint64 { func (kv KV) EmbeddingHeadCountK() uint64 {
if k := kv.u64(fmt.Sprintf("%s.attention.key_length", kv.Architecture())); k > 0 { return uint64(kv.Uint("attention.key_length", uint32(kv.EmbeddingHeadCount())))
return k
}
return kv.EmbeddingHeadCount()
} }
func (kv KV) EmbeddingHeadCountV() uint64 { func (kv KV) EmbeddingHeadCountV() uint64 {
if v := kv.u64(fmt.Sprintf("%s.attention.value_length", kv.Architecture())); v > 0 { return uint64(kv.Uint("attention.value_length", uint32(kv.EmbeddingHeadCount())))
return v
}
return kv.EmbeddingHeadCount()
} }
func (kv KV) GQA() uint64 { func (kv KV) GQA() uint64 {
return kv.HeadCount() / kv.HeadCountKV() 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 { 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 { 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 return s
} }
type Tensors struct { func (kv KV) Uints(key string, defaultValue ...[]uint32) []uint32 {
Items []*Tensor r := keyValue(kv, key, &array{})
Offset uint64 s := make([]uint32, r.size)
for i := range r.size {
s[i] = uint32(r.values[i].(int32))
}
layers map[string]Layer return s
layersOnce sync.Once
} }
func (ts *Tensors) Layers() map[string]Layer { func keyValue[T string | uint32 | uint64 | float32 | *array](kv KV, key string, defaultValue ...T) T {
ts.layersOnce.Do(func() { if !strings.HasPrefix(key, "tokenizer.") && !strings.HasPrefix(key, "general.") {
ts.layers = make(map[string]Layer) key = kv.Architecture() + "." + key
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:]...)
}
}
if _, ok := ts.layers[parts[0]]; !ok { if val, ok := kv[key]; ok {
ts.layers[parts[0]] = make(Layer) 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 type Layer map[string]*Tensor
func (l Layer) size() (size uint64) { func (l Layer) Size() (size uint64) {
for _, t := range l { for _, t := range l {
size += t.Size() size += t.Size()
} }
@@ -255,8 +278,6 @@ func (t Tensor) typeSize() uint64 {
return 8 return 8
case 29: // IQ1_M case 29: // IQ1_M
return blockSize/8 + blockSize/16 + blockSize/32 return blockSize/8 + blockSize/16 + blockSize/32
case 30: // BF16
return 2
default: default:
return 0 return 0
} }
@@ -295,7 +316,7 @@ const (
var ErrUnsupportedFormat = errors.New("unsupported model format") var ErrUnsupportedFormat = errors.New("unsupported model format")
func DetectGGMLType(b []byte) string { func DetectContentType(b []byte) string {
switch binary.LittleEndian.Uint32(b[:4]) { switch binary.LittleEndian.Uint32(b[:4]) {
case FILE_MAGIC_GGML: case FILE_MAGIC_GGML:
return "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 // 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 // maxArraySize. If maxArraySize is 0, the default value of 1024 is used. If
// the maxArraySize is negative, all arrays are collected. // 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 { if maxArraySize == 0 {
maxArraySize = 1024 maxArraySize = 1024
} }
@@ -331,10 +352,6 @@ func DecodeGGML(rs io.ReadSeeker, maxArraySize int) (*GGML, int64, error) {
var c container var c container
switch magic { 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: case FILE_MAGIC_GGUF_LE:
c = &containerGGUF{ByteOrder: binary.LittleEndian, maxArraySize: maxArraySize} c = &containerGGUF{ByteOrder: binary.LittleEndian, maxArraySize: maxArraySize}
case FILE_MAGIC_GGUF_BE: 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 // SupportsKVCacheType checks if the requested cache type is supported
func (ggml GGML) SupportsKVCacheType(cacheType string) bool { func (llm GGML) SupportsKVCacheType(cacheType string) bool {
validKVCacheTypes := []string{"f16", "q8_0", "q4_0"} return slices.Contains([]string{"f16", "q8_0", "q4_0"}, cacheType)
return slices.Contains(validKVCacheTypes, cacheType)
} }
// SupportsFlashAttention checks if the model supports flash attention // SupportsFlashAttention checks if the model supports flash attention
func (ggml GGML) SupportsFlashAttention() bool { func (llm GGML) SupportsFlashAttention() bool {
_, isEmbedding := ggml.KV()[fmt.Sprintf("%s.pooling_type", ggml.KV().Architecture())] _, isEmbedding := llm.KV()[fmt.Sprintf("%s.pooling_type", llm.KV().Architecture())]
if isEmbedding { if isEmbedding {
return false return false
} }
// Check head counts match and are non-zero // Check head counts match and are non-zero
headCountK := ggml.KV().EmbeddingHeadCountK() headCountK := llm.KV().EmbeddingHeadCountK()
headCountV := ggml.KV().EmbeddingHeadCountV() headCountV := llm.KV().EmbeddingHeadCountV()
return headCountK != 0 && headCountV != 0 && headCountK == headCountV return headCountK != 0 && headCountV != 0 && headCountK == headCountV
} }

View File

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

View File

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

6
go.mod
View File

@@ -17,12 +17,15 @@ require (
require ( require (
github.com/agnivade/levenshtein v1.1.1 github.com/agnivade/levenshtein v1.1.1
github.com/d4l3k/go-bfloat16 v0.0.0-20211005043715-690c3bdd05f1 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/emirpasic/gods/v2 v2.0.0-alpha
github.com/google/go-cmp v0.6.0 github.com/google/go-cmp v0.6.0
github.com/mattn/go-runewidth v0.0.14 github.com/mattn/go-runewidth v0.0.14
github.com/nlpodyssey/gopickle v0.3.0 github.com/nlpodyssey/gopickle v0.3.0
github.com/pdevine/tensor v0.0.0-20240510204454-f88f4562727c github.com/pdevine/tensor v0.0.0-20240510204454-f88f4562727c
golang.org/x/image v0.22.0 golang.org/x/image v0.22.0
golang.org/x/tools v0.28.0
gonum.org/v1/gonum v0.15.0
) )
require ( require (
@@ -42,7 +45,6 @@ require (
github.com/xtgo/set v1.0.0 // indirect github.com/xtgo/set v1.0.0 // indirect
go4.org/unsafe/assume-no-moving-gc v0.0.0-20231121144256-b99613f794b6 // indirect go4.org/unsafe/assume-no-moving-gc v0.0.0-20231121144256-b99613f794b6 // indirect
golang.org/x/xerrors v0.0.0-20200804184101-5ec99f83aff1 // 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/vecf32 v0.9.0 // indirect
gorgonia.org/vecf64 v0.9.0 // indirect gorgonia.org/vecf64 v0.9.0 // indirect
) )
@@ -70,7 +72,7 @@ require (
golang.org/x/arch v0.8.0 // indirect golang.org/x/arch v0.8.0 // indirect
golang.org/x/crypto v0.31.0 golang.org/x/crypto v0.31.0
golang.org/x/exp v0.0.0-20231110203233-9a3e6036ecaa golang.org/x/exp v0.0.0-20231110203233-9a3e6036ecaa
golang.org/x/net v0.25.0 // indirect golang.org/x/net v0.32.0 // indirect
golang.org/x/sys v0.28.0 golang.org/x/sys v0.28.0
golang.org/x/term v0.27.0 golang.org/x/term v0.27.0
golang.org/x/text v0.21.0 golang.org/x/text v0.21.0

8
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/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 h1:fRzb/w+pyskVMQ+UbP35JkH8yB7MYb4q/qhBarqZE6g=
github.com/dgryski/trifles v0.0.0-20200323201526-dd97f9abfb48/go.mod h1:if7Fbed8SFyPtHLHbg49SI7NAdJiC5WIA09pe59rfAA= 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 h1:dwFlh8pBg1VMOXWGipNMRt8v96dKAIvBehtCt6OtunU=
github.com/emirpasic/gods/v2 v2.0.0-alpha/go.mod h1:W0y4M2dtBB9U5z3YlghmpuUhiaZT2h6yoeE+C1sCp6A= 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= github.com/envoyproxy/go-control-plane v0.9.0/go.mod h1:YTl/9mNaCwkRvm6d1a2C3ymFceY/DCBVvsKhRF0iEA4=
@@ -255,8 +257,8 @@ golang.org/x/net v0.0.0-20200822124328-c89045814202/go.mod h1:/O7V0waA8r7cgGh81R
golang.org/x/net v0.0.0-20201021035429-f5854403a974/go.mod h1:sp8m0HH+o8qH0wwXwYZr8TS3Oi6o0r6Gce1SSxlDquU= golang.org/x/net v0.0.0-20201021035429-f5854403a974/go.mod h1:sp8m0HH+o8qH0wwXwYZr8TS3Oi6o0r6Gce1SSxlDquU=
golang.org/x/net v0.0.0-20210405180319-a5a99cb37ef4/go.mod h1:p54w0d4576C0XHj96bSt6lcn1PtDYWL6XObtHCRCNQM= golang.org/x/net v0.0.0-20210405180319-a5a99cb37ef4/go.mod h1:p54w0d4576C0XHj96bSt6lcn1PtDYWL6XObtHCRCNQM=
golang.org/x/net v0.0.0-20210614182718-04defd469f4e/go.mod h1:9nx3DQGgdP8bBQD5qxJ1jj9UTztislL4KSBs9R2vV5Y= golang.org/x/net v0.0.0-20210614182718-04defd469f4e/go.mod h1:9nx3DQGgdP8bBQD5qxJ1jj9UTztislL4KSBs9R2vV5Y=
golang.org/x/net v0.25.0 h1:d/OCCoBEUq33pjydKrGQhw7IlUPI2Oylr+8qLx49kac= golang.org/x/net v0.32.0 h1:ZqPmj8Kzc+Y6e0+skZsuACbx+wzMgo5MQsJh9Qd6aYI=
golang.org/x/net v0.25.0/go.mod h1:JkAGAh7GEvH74S6FOH42FLoXpXbE/aqXSrIQjXgsiwM= golang.org/x/net v0.32.0/go.mod h1:CwU0IoeOlnQQWJ6ioyFrfRuomB8GKF6KbYXZVyeXNfs=
golang.org/x/oauth2 v0.0.0-20180821212333-d2e6202438be/go.mod h1:N/0e6XlmueqKjAGxoOufVs8QHGRruUQn6yWY3a++T0U= golang.org/x/oauth2 v0.0.0-20180821212333-d2e6202438be/go.mod h1:N/0e6XlmueqKjAGxoOufVs8QHGRruUQn6yWY3a++T0U=
golang.org/x/oauth2 v0.0.0-20200107190931-bf48bf16ab8d/go.mod h1:gOpvHmFTYa4IltrdGE7lF6nIHvwfUNPOp7c8zoXwtLw= golang.org/x/oauth2 v0.0.0-20200107190931-bf48bf16ab8d/go.mod h1:gOpvHmFTYa4IltrdGE7lF6nIHvwfUNPOp7c8zoXwtLw=
golang.org/x/sync v0.0.0-20180314180146-1d60e4601c6f/go.mod h1:RxMgew5VJxzue5/jJTE5uejpjVlOe/izrB70Jof72aM= golang.org/x/sync v0.0.0-20180314180146-1d60e4601c6f/go.mod h1:RxMgew5VJxzue5/jJTE5uejpjVlOe/izrB70Jof72aM=
@@ -307,6 +309,8 @@ golang.org/x/tools v0.0.0-20200130002326-2f3ba24bd6e7/go.mod h1:TB2adYChydJhpapK
golang.org/x/tools v0.0.0-20200619180055-7c47624df98f/go.mod h1:EkVYQZoAsY45+roYkvgYkIh4xh/qjgUK9TdY2XT94GE= golang.org/x/tools v0.0.0-20200619180055-7c47624df98f/go.mod h1:EkVYQZoAsY45+roYkvgYkIh4xh/qjgUK9TdY2XT94GE=
golang.org/x/tools v0.0.0-20210106214847-113979e3529a/go.mod h1:emZCQorbCU4vsT4fOWvOPXz4eW1wZW4PmDk9uLelYpA= golang.org/x/tools v0.0.0-20210106214847-113979e3529a/go.mod h1:emZCQorbCU4vsT4fOWvOPXz4eW1wZW4PmDk9uLelYpA=
golang.org/x/tools v0.1.4/go.mod h1:o0xws9oXOQQZyjljx8fwUC0k7L1pTE6eaCbjGeHmOkk= golang.org/x/tools v0.1.4/go.mod h1:o0xws9oXOQQZyjljx8fwUC0k7L1pTE6eaCbjGeHmOkk=
golang.org/x/tools v0.28.0 h1:WuB6qZ4RPCQo5aP3WdKZS7i595EdWqWR8vqJTlwTVK8=
golang.org/x/tools v0.28.0/go.mod h1:dcIOrVd3mfQKTgrDVQHqCPMWy6lnhfhtX3hLXYVLfRw=
golang.org/x/xerrors v0.0.0-20190717185122-a985d3407aa7/go.mod h1:I/5z698sn9Ka8TeJc9MKroUUfqBBauWjQqLJ2OPfmY0= golang.org/x/xerrors v0.0.0-20190717185122-a985d3407aa7/go.mod h1:I/5z698sn9Ka8TeJc9MKroUUfqBBauWjQqLJ2OPfmY0=
golang.org/x/xerrors v0.0.0-20191011141410-1b5146add898/go.mod h1:I/5z698sn9Ka8TeJc9MKroUUfqBBauWjQqLJ2OPfmY0= golang.org/x/xerrors v0.0.0-20191011141410-1b5146add898/go.mod h1:I/5z698sn9Ka8TeJc9MKroUUfqBBauWjQqLJ2OPfmY0=
golang.org/x/xerrors v0.0.0-20191204190536-9bdfabe68543/go.mod h1:I/5z698sn9Ka8TeJc9MKroUUfqBBauWjQqLJ2OPfmY0= golang.org/x/xerrors v0.0.0-20191204190536-9bdfabe68543/go.mod h1:I/5z698sn9Ka8TeJc9MKroUUfqBBauWjQqLJ2OPfmY0=

22
grammar/bench_test.go Normal file
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@@ -0,0 +1,22 @@
//go:build go1.24
package grammar
import "testing"
func BenchmarkFromSchema(b *testing.B) {
for tt := range testCases(b) {
b.Run("", func(b *testing.B) {
s := []byte(tt.schema)
b.ReportAllocs()
for b.Loop() {
_, err := FromSchema(nil, s)
if err != nil {
b.Fatalf("GrammarFromSchema: %v", err)
}
}
})
return
}
}

227
grammar/grammar.go Normal file
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@@ -0,0 +1,227 @@
package grammar
import (
"bytes"
"encoding/json"
"fmt"
"iter"
"strconv"
"github.com/ollama/ollama/grammar/jsonschema"
)
const jsonTerms = `
# Unicode
#
# Unicode characters can be specified directly in the grammar, for example
# hiragana ::= [ぁ-ゟ], or with escapes: 8-bit (\xXX), 16-bit (\uXXXX) or 32-bit
# (\UXXXXXXXX).
unicode ::= \x{hex}{2} | \u{hex}{4} | \U{hex}{8}
# JSON grammar from RFC 7159
null ::= "null"
object ::= "{" (kv ("," kv)*)? "}"
array ::= "[" (value ("," value)*)? "]"
kv ::= string ":" value
integer ::= "0" | [1-9] [0-9]*
number ::= "-"? integer frac? exp?
frac ::= "." [0-9]+
exp ::= ("e" | "E") ("+" | "-") [0-9]+
string ::= "\"" char* "\""
escape ::= ["/" | "b" | "f" | "n" | "r" | "t" | unicode]
char ::= [^"\\] | escape
space ::= (" " | "\t" | "\n" | "\r")*
hex ::= [0-9] | [a-f] | [A-F]
boolean ::= "true" | "false"
value ::= object | array | string | number | boolean | "null"
# User-defined
`
// FromSchema generates a grammar from a JSON schema.
func FromSchema(buf []byte, jsonSchema []byte) ([]byte, error) {
var s *jsonschema.Schema
if err := json.Unmarshal(jsonSchema, &s); err != nil {
return nil, err
}
var g builder
// "root" is the only rule that is guaranteed to exist, so we start
// with its length for padding, and then adjust it as we go.
g.pad = len("root")
for id := range dependencies("root", s) {
g.pad = max(g.pad, len(id))
}
g.b.WriteString(jsonTerms)
ids := make(map[*jsonschema.Schema]string)
for id, s := range dependencies("root", s) {
ids[s] = id
g.define(id)
if err := fromSchema(&g, ids, s); err != nil {
return nil, err
}
}
g.define("root")
if err := fromSchema(&g, ids, s); err != nil {
return nil, err
}
g.define("") // finalize the last rule
return g.b.Bytes(), nil
}
func fromSchema(g *builder, ids map[*jsonschema.Schema]string, s *jsonschema.Schema) error {
switch typ := s.EffectiveType(); typ {
case "array":
if len(s.PrefixItems) == 0 && s.Items == nil {
g.u("array")
} else {
g.q("[")
for i, s := range s.PrefixItems {
if i > 0 {
g.q(",")
}
g.u(ids[s])
}
if s.Items != nil {
g.u("(")
if len(s.PrefixItems) > 0 {
g.q(",")
}
g.u(ids[s.Items])
g.u(")*")
}
g.q("]")
}
case "object":
if len(s.Properties) == 0 {
g.u("object")
} else {
g.q("{")
for i, p := range s.Properties {
name := ids[p]
if i > 0 {
g.q(",")
}
g.q(p.Name)
g.q(":")
g.u(name)
}
g.q("}")
}
case "number":
buildConstrainedNumber(g, s)
case "string":
if len(s.Enum) == 0 {
g.u("string")
} else {
g.u("(")
for i, e := range s.Enum {
if i > 0 {
g.q("|")
}
g.q(string(e))
}
g.u(")")
}
case "boolean", "value", "null", "integer":
g.u(typ)
default:
return fmt.Errorf("%s: unsupported type %q", s.Name, typ)
}
return nil
}
// dependencies returns a sequence of all child dependencies of the schema in
// post-order.
//
// The first value is the id/pointer to the dependency, and the second value
// is the schema.
func dependencies(id string, s *jsonschema.Schema) iter.Seq2[string, *jsonschema.Schema] {
return func(yield func(string, *jsonschema.Schema) bool) {
for i, p := range s.Properties {
id := fmt.Sprintf("%s_%d", id, i)
for did, d := range dependencies(id, p) {
if !yield(did, d) {
return
}
}
if !yield(id, p) {
return
}
}
for i, p := range s.PrefixItems {
id := fmt.Sprintf("tuple_%d", i)
for did, d := range dependencies(id, p) {
id := fmt.Sprintf("%s_%s", id, did)
if !yield(id, d) {
return
}
}
if !yield(id, p) {
return
}
}
if s.Items != nil {
id := fmt.Sprintf("%s_tuple_%d", id, len(s.PrefixItems))
for did, d := range dependencies(id, s.Items) {
if !yield(did, d) {
return
}
}
if !yield(id, s.Items) {
return
}
}
}
}
type builder struct {
b bytes.Buffer
pad int
rules int
items int
}
// define terminates the current rule, if any, and then either starts a new
// rule or does nothing else if the name is empty.
func (b *builder) define(name string) {
if b.rules > 0 {
b.b.WriteString(";\n")
}
if name == "" {
return
}
fmt.Fprintf(&b.b, "% -*s", b.pad, name)
b.b.WriteString(" ::=")
b.rules++
b.items = 0
}
// quote appends a terminal to the current rule.
func (b *builder) q(s string) {
if b.items > 0 {
b.b.WriteString(" ")
}
b.b.WriteString(" ")
b.b.WriteString(strconv.Quote(s))
}
// u appends a non-terminal to the current rule.
func (b *builder) u(s string) {
if b.items > 0 {
b.b.WriteString(" ")
}
b.b.WriteString(" ")
b.b.WriteString(s)
}
func buildConstrainedNumber(b *builder, s *jsonschema.Schema) {
if s.Minimum == 0 && s.Maximum == 0 {
b.u("TODO")
} else {
b.u("number")
}
}

75
grammar/grammar_test.go Normal file
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@@ -0,0 +1,75 @@
package grammar
import (
"bufio"
"cmp"
"iter"
"strings"
"testing"
_ "embed"
"github.com/ollama/ollama/grammar/internal/diff"
)
func TestFromSchema(t *testing.T) {
for tt := range testCases(t) {
t.Run(tt.name, func(t *testing.T) {
g, err := FromSchema(nil, []byte(tt.schema))
if err != nil {
t.Fatalf("FromSchema: %v", err)
}
got := string(g)
got = strings.TrimPrefix(got, jsonTerms)
if got != tt.want {
t.Logf("schema:\n%s", tt.schema)
t.Fatal(string(diff.Diff("got", []byte(got), "want", []byte(tt.want))))
}
})
}
}
type testCase struct {
name string
schema string
want string
}
//go:embed testdata/schemas.txt
var tests string
func testCases(t testing.TB) iter.Seq[testCase] {
t.Helper()
return func(yield func(testCase) bool) {
t.Helper()
sc := bufio.NewScanner(strings.NewReader(tests))
name := ""
for sc.Scan() {
line := strings.TrimSpace(sc.Text())
if line == "" {
name = ""
continue
}
if line[0] == '#' {
name = cmp.Or(name, strings.TrimSpace(line[1:]))
continue
}
s := sc.Text()
g := ""
for sc.Scan() {
line = strings.TrimSpace(sc.Text())
if line == "" || line[0] == '#' {
break
}
g += sc.Text() + "\n"
}
if !yield(testCase{name, s, g}) {
return
}
name = strings.TrimSpace(strings.TrimPrefix(line, "#"))
}
if err := sc.Err(); err != nil {
t.Fatalf("error reading tests: %v", err)
}
}
}

View File

@@ -0,0 +1,261 @@
// Copyright 2022 The Go Authors. All rights reserved.
// Use of this source code is governed by a BSD-style
// license that can be found in the LICENSE file.
package diff
import (
"bytes"
"fmt"
"sort"
"strings"
)
// A pair is a pair of values tracked for both the x and y side of a diff.
// It is typically a pair of line indexes.
type pair struct{ x, y int }
// Diff returns an anchored diff of the two texts old and new
// in the “unified diff” format. If old and new are identical,
// Diff returns a nil slice (no output).
//
// Unix diff implementations typically look for a diff with
// the smallest number of lines inserted and removed,
// which can in the worst case take time quadratic in the
// number of lines in the texts. As a result, many implementations
// either can be made to run for a long time or cut off the search
// after a predetermined amount of work.
//
// In contrast, this implementation looks for a diff with the
// smallest number of “unique” lines inserted and removed,
// where unique means a line that appears just once in both old and new.
// We call this an “anchored diff” because the unique lines anchor
// the chosen matching regions. An anchored diff is usually clearer
// than a standard diff, because the algorithm does not try to
// reuse unrelated blank lines or closing braces.
// The algorithm also guarantees to run in O(n log n) time
// instead of the standard O(n²) time.
//
// Some systems call this approach a “patience diff,” named for
// the “patience sorting” algorithm, itself named for a solitaire card game.
// We avoid that name for two reasons. First, the name has been used
// for a few different variants of the algorithm, so it is imprecise.
// Second, the name is frequently interpreted as meaning that you have
// to wait longer (to be patient) for the diff, meaning that it is a slower algorithm,
// when in fact the algorithm is faster than the standard one.
func Diff(oldName string, old []byte, newName string, new []byte) []byte {
if bytes.Equal(old, new) {
return nil
}
x := lines(old)
y := lines(new)
// Print diff header.
var out bytes.Buffer
fmt.Fprintf(&out, "diff %s %s\n", oldName, newName)
fmt.Fprintf(&out, "--- %s\n", oldName)
fmt.Fprintf(&out, "+++ %s\n", newName)
// Loop over matches to consider,
// expanding each match to include surrounding lines,
// and then printing diff chunks.
// To avoid setup/teardown cases outside the loop,
// tgs returns a leading {0,0} and trailing {len(x), len(y)} pair
// in the sequence of matches.
var (
done pair // printed up to x[:done.x] and y[:done.y]
chunk pair // start lines of current chunk
count pair // number of lines from each side in current chunk
ctext []string // lines for current chunk
)
for _, m := range tgs(x, y) {
if m.x < done.x {
// Already handled scanning forward from earlier match.
continue
}
// Expand matching lines as far as possible,
// establishing that x[start.x:end.x] == y[start.y:end.y].
// Note that on the first (or last) iteration we may (or definitely do)
// have an empty match: start.x==end.x and start.y==end.y.
start := m
for start.x > done.x && start.y > done.y && x[start.x-1] == y[start.y-1] {
start.x--
start.y--
}
end := m
for end.x < len(x) && end.y < len(y) && x[end.x] == y[end.y] {
end.x++
end.y++
}
// Emit the mismatched lines before start into this chunk.
// (No effect on first sentinel iteration, when start = {0,0}.)
for _, s := range x[done.x:start.x] {
ctext = append(ctext, "-"+s)
count.x++
}
for _, s := range y[done.y:start.y] {
ctext = append(ctext, "+"+s)
count.y++
}
// If we're not at EOF and have too few common lines,
// the chunk includes all the common lines and continues.
const C = 3 // number of context lines
if (end.x < len(x) || end.y < len(y)) &&
(end.x-start.x < C || (len(ctext) > 0 && end.x-start.x < 2*C)) {
for _, s := range x[start.x:end.x] {
ctext = append(ctext, " "+s)
count.x++
count.y++
}
done = end
continue
}
// End chunk with common lines for context.
if len(ctext) > 0 {
n := end.x - start.x
if n > C {
n = C
}
for _, s := range x[start.x : start.x+n] {
ctext = append(ctext, " "+s)
count.x++
count.y++
}
done = pair{start.x + n, start.y + n}
// Format and emit chunk.
// Convert line numbers to 1-indexed.
// Special case: empty file shows up as 0,0 not 1,0.
if count.x > 0 {
chunk.x++
}
if count.y > 0 {
chunk.y++
}
fmt.Fprintf(&out, "@@ -%d,%d +%d,%d @@\n", chunk.x, count.x, chunk.y, count.y)
for _, s := range ctext {
out.WriteString(s)
}
count.x = 0
count.y = 0
ctext = ctext[:0]
}
// If we reached EOF, we're done.
if end.x >= len(x) && end.y >= len(y) {
break
}
// Otherwise start a new chunk.
chunk = pair{end.x - C, end.y - C}
for _, s := range x[chunk.x:end.x] {
ctext = append(ctext, " "+s)
count.x++
count.y++
}
done = end
}
return out.Bytes()
}
// lines returns the lines in the file x, including newlines.
// If the file does not end in a newline, one is supplied
// along with a warning about the missing newline.
func lines(x []byte) []string {
l := strings.SplitAfter(string(x), "\n")
if l[len(l)-1] == "" {
l = l[:len(l)-1]
} else {
// Treat last line as having a message about the missing newline attached,
// using the same text as BSD/GNU diff (including the leading backslash).
l[len(l)-1] += "\n\\ No newline at end of file\n"
}
return l
}
// tgs returns the pairs of indexes of the longest common subsequence
// of unique lines in x and y, where a unique line is one that appears
// once in x and once in y.
//
// The longest common subsequence algorithm is as described in
// Thomas G. Szymanski, “A Special Case of the Maximal Common
// Subsequence Problem,” Princeton TR #170 (January 1975),
// available at https://research.swtch.com/tgs170.pdf.
func tgs(x, y []string) []pair {
// Count the number of times each string appears in a and b.
// We only care about 0, 1, many, counted as 0, -1, -2
// for the x side and 0, -4, -8 for the y side.
// Using negative numbers now lets us distinguish positive line numbers later.
m := make(map[string]int)
for _, s := range x {
if c := m[s]; c > -2 {
m[s] = c - 1
}
}
for _, s := range y {
if c := m[s]; c > -8 {
m[s] = c - 4
}
}
// Now unique strings can be identified by m[s] = -1+-4.
//
// Gather the indexes of those strings in x and y, building:
// xi[i] = increasing indexes of unique strings in x.
// yi[i] = increasing indexes of unique strings in y.
// inv[i] = index j such that x[xi[i]] = y[yi[j]].
var xi, yi, inv []int
for i, s := range y {
if m[s] == -1+-4 {
m[s] = len(yi)
yi = append(yi, i)
}
}
for i, s := range x {
if j, ok := m[s]; ok && j >= 0 {
xi = append(xi, i)
inv = append(inv, j)
}
}
// Apply Algorithm A from Szymanski's paper.
// In those terms, A = J = inv and B = [0, n).
// We add sentinel pairs {0,0}, and {len(x),len(y)}
// to the returned sequence, to help the processing loop.
J := inv
n := len(xi)
T := make([]int, n)
L := make([]int, n)
for i := range T {
T[i] = n + 1
}
for i := range n {
k := sort.Search(n, func(k int) bool {
return T[k] >= J[i]
})
T[k] = J[i]
L[i] = k + 1
}
k := 0
for _, v := range L {
if k < v {
k = v
}
}
seq := make([]pair, 2+k)
seq[1+k] = pair{len(x), len(y)} // sentinel at end
lastj := n
for i := n - 1; i >= 0; i-- {
if L[i] == k && J[i] < lastj {
seq[k] = pair{xi[i], yi[J[i]]}
k--
}
}
seq[0] = pair{0, 0} // sentinel at start
return seq
}

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@@ -0,0 +1,44 @@
// Copyright 2022 The Go Authors. All rights reserved.
// Use of this source code is governed by a BSD-style
// license that can be found in the LICENSE file.
package diff
import (
"bytes"
"path/filepath"
"testing"
"golang.org/x/tools/txtar"
)
func clean(text []byte) []byte {
text = bytes.ReplaceAll(text, []byte("$\n"), []byte("\n"))
text = bytes.TrimSuffix(text, []byte("^D\n"))
return text
}
func Test(t *testing.T) {
files, _ := filepath.Glob("testdata/*.txt")
if len(files) == 0 {
t.Fatalf("no testdata")
}
for _, file := range files {
t.Run(filepath.Base(file), func(t *testing.T) {
a, err := txtar.ParseFile(file)
if err != nil {
t.Fatal(err)
}
if len(a.Files) != 3 || a.Files[2].Name != "diff" {
t.Fatalf("%s: want three files, third named \"diff\"", file)
}
diffs := Diff(a.Files[0].Name, clean(a.Files[0].Data), a.Files[1].Name, clean(a.Files[1].Data))
want := clean(a.Files[2].Data)
if !bytes.Equal(diffs, want) {
t.Fatalf("%s: have:\n%s\nwant:\n%s\n%s", file,
diffs, want, Diff("have", diffs, "want", want))
}
})
}
}

View File

@@ -0,0 +1,13 @@
-- old --
-- new --
a
b
c
-- diff --
diff old new
--- old
+++ new
@@ -0,0 +1,3 @@
+a
+b
+c

View File

@@ -0,0 +1,13 @@
-- old --
a
b
c
-- new --
-- diff --
diff old new
--- old
+++ new
@@ -1,3 +0,0 @@
-a
-b
-c

View File

@@ -0,0 +1,35 @@
Example from Hunt and McIlroy, “An Algorithm for Differential File Comparison.”
https://www.cs.dartmouth.edu/~doug/diff.pdf
-- old --
a
b
c
d
e
f
g
-- new --
w
a
b
x
y
z
e
-- diff --
diff old new
--- old
+++ new
@@ -1,7 +1,7 @@
+w
a
b
-c
-d
+x
+y
+z
e
-f
-g

40
grammar/internal/diff/testdata/dups.txt vendored Normal file
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@@ -0,0 +1,40 @@
-- old --
a
b
c
d
e
f
-- new --
a
B
C
d
e
f
-- diff --
diff old new
--- old
+++ new
@@ -1,8 +1,8 @@
a
$
-b
-
-c
+B
+
+C
$
d
$

38
grammar/internal/diff/testdata/end.txt vendored Normal file
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@@ -0,0 +1,38 @@
-- old --
1
2
3
4
5
6
7
eight
nine
ten
eleven
-- new --
1
2
3
4
5
6
7
8
9
10
-- diff --
diff old new
--- old
+++ new
@@ -5,7 +5,6 @@
5
6
7
-eight
-nine
-ten
-eleven
+8
+9
+10

View File

@@ -0,0 +1,9 @@
-- old --
a
b
c^D
-- new --
a
b
c^D
-- diff --

18
grammar/internal/diff/testdata/eof1.txt vendored Normal file
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@@ -0,0 +1,18 @@
-- old --
a
b
c
-- new --
a
b
c^D
-- diff --
diff old new
--- old
+++ new
@@ -1,3 +1,3 @@
a
b
-c
+c
\ No newline at end of file

18
grammar/internal/diff/testdata/eof2.txt vendored Normal file
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@@ -0,0 +1,18 @@
-- old --
a
b
c^D
-- new --
a
b
c
-- diff --
diff old new
--- old
+++ new
@@ -1,3 +1,3 @@
a
b
-c
\ No newline at end of file
+c

62
grammar/internal/diff/testdata/long.txt vendored Normal file
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@@ -0,0 +1,62 @@
-- old --
1
2
3
4
5
6
7
8
9
10
11
12
13
14
14½
15
16
17
18
19
20
-- new --
1
2
3
4
5
6
8
9
10
11
12
13
14
17
18
19
20
-- diff --
diff old new
--- old
+++ new
@@ -4,7 +4,6 @@
4
5
6
-7
8
9
10
@@ -12,9 +11,6 @@
12
13
14
-14½
-15
-16
17
18
19

View File

@@ -0,0 +1,5 @@
-- old --
hello world
-- new --
hello world
-- diff --

View File

@@ -0,0 +1,34 @@
-- old --
e
pi
4
5
6
7
8
9
10
-- new --
1
2
3
4
5
6
7
8
9
10
-- diff --
diff old new
--- old
+++ new
@@ -1,5 +1,6 @@
-e
-pi
+1
+2
+3
4
5
6

40
grammar/internal/diff/testdata/triv.txt vendored Normal file
View File

@@ -0,0 +1,40 @@
Another example from Hunt and McIlroy,
“An Algorithm for Differential File Comparison.”
https://www.cs.dartmouth.edu/~doug/diff.pdf
Anchored diff gives up on finding anything,
since there are no unique lines.
-- old --
a
b
c
a
b
b
a
-- new --
c
a
b
a
b
c
-- diff --
diff old new
--- old
+++ new
@@ -1,7 +1,6 @@
-a
-b
-c
-a
-b
-b
-a
+c
+a
+b
+a
+b
+c

View File

@@ -0,0 +1,171 @@
package jsonschema
import (
"bytes"
"encoding/json"
"errors"
)
// Schema holds a JSON schema.
type Schema struct {
// Name is the name of the property. For the parent/root property, this
// is "root". For child properties, this is the name of the property.
Name string `json:"-"`
// Type is the type of the property.
//
// TODO: Union types (e.g. make this a []string).
Type string
// PrefixItems is a list of schemas for each item in a tuple. By
// default, the tuple is "closed." unless Items is set to true or a
// valid Schema.
PrefixItems []*Schema
// Items is the schema for each item in a list.
//
// If it is missing, or its JSON value is "null" or "false", it is nil.
// If the JSON value is "true", it is set to the empty Schema. If the
// JSON value is an object, it will be decoded as a Schema.
Items *Schema
// MinItems specifies the minimum number of items allowed in a list.
MinItems int
// MaxItems specifies the maximum number of items allowed in a list.
MaxItems int
// Properties is the schema for each property of an object.
Properties []*Schema
// Format is the format of the property. This is used to validate the
// property against a specific format.
//
// It is the callers responsibility to validate the property against
// the format.
Format string
// Minimum specifies the minimum value for numeric properties.
Minimum float64
// Maximum specifies the maximum value for numeric properties.
Maximum float64
// Enum is a list of valid values for the property.
Enum []json.RawMessage
}
func (s *Schema) UnmarshalJSON(data []byte) error {
type S Schema
w := struct {
Properties props
Items items
*S
}{
S: (*S)(s),
}
if err := json.Unmarshal(data, &w); err != nil {
return err
}
if w.Items.set {
s.Items = &w.Items.Schema
}
s.Properties = w.Properties
return nil
}
type items struct {
Schema
set bool
}
func (s *items) UnmarshalJSON(data []byte) error {
switch b := data[0]; b {
case 't':
*s = items{set: true}
case '{':
type I items
if err := json.Unmarshal(data, (*I)(s)); err != nil {
return err
}
s.set = true
case 'n', 'f':
default:
return errors.New("invalid Items")
}
return nil
}
// EffectiveType returns the effective type of the schema. If the Type field is
// not empty, it is returned; otherwise:
//
// - If the schema has both Properties and Items, it returns an empty string.
// - If the schema has Properties, it returns "object".
// - If the schema has Items, it returns "array".
// - If the schema has neither Properties nor Items, it returns "value".
//
// The returned string is never empty.
func (d *Schema) EffectiveType() string {
if d.Type == "" {
if len(d.Properties) > 0 {
return "object"
}
if len(d.PrefixItems) > 0 || d.Items != nil {
return "array"
}
return "value"
}
return d.Type
}
// props is an ordered list of properties. The order of the properties
// is the order in which they were defined in the schema.
type props []*Schema
var _ json.Unmarshaler = (*props)(nil)
func (v *props) UnmarshalJSON(data []byte) error {
if len(data) == 0 {
return nil
}
if data[0] != '{' {
return errors.New("expected object")
}
d := json.NewDecoder(bytes.NewReader(data))
// TODO(bmizerany): Consider DisallowUnknownFields. Currently, we, like
// llama.cpp, ignore unknown fields, which could be lead to unexpected
// behavior for clients of this package, since they may not be aware
// that "additionalFields", "itemsPrefix", etc, are being ignored.
//
// For now, just do what llama.cpp does.
t, err := d.Token()
if err != nil {
return err
}
if t != json.Delim('{') {
return errors.New("expected object")
}
for d.More() {
// Use the first token (map key) as the property name, then
// decode the rest of the object fields into a Schema and
// append.
t, err := d.Token()
if err != nil {
return err
}
if t == json.Delim('}') {
return nil
}
s := &Schema{
Name: t.(string),
}
if err := d.Decode(s); err != nil {
return err
}
*v = append(*v, s)
}
return nil
}

View File

@@ -0,0 +1,104 @@
package jsonschema
import (
"encoding/json"
"reflect"
"strings"
"testing"
"github.com/google/go-cmp/cmp"
)
const testSchemaBasic = `
{
"properties": {
"tupleClosedEmpty": { "prefixItems": [] },
"tupleClosedMissing": { "prefixItems": [{}] },
"tupleClosedNull": { "prefixItems": [{}], "items": null },
"tupleClosedFalse": { "prefixItems": [{}], "items": false },
"tupleOpenTrue": { "prefixItems": [{}], "items": true },
"tupleOpenEmpty": { "prefixItems": [{}], "items": {} },
"tupleOpenTyped": { "prefixItems": [{}], "items": {"type": "boolean"} },
"tupleOpenMax": { "prefixItems": [{}], "items": true, "maxItems": 3},
"array": { "items": {"type": "number"} },
"null": { "type": "null" },
"string": { "type": "string" },
"boolean": { "type": "boolean" }
}
}
`
func TestSchemaUnmarshal(t *testing.T) {
var got *Schema
if err := json.Unmarshal([]byte(testSchemaBasic), &got); err != nil {
t.Fatalf("Unmarshal: %v", err)
}
want := &Schema{
Properties: []*Schema{
{Name: "tupleClosedEmpty", PrefixItems: []*Schema{}, Items: nil},
{Name: "tupleClosedMissing", PrefixItems: []*Schema{{}}, Items: nil},
{Name: "tupleClosedNull", PrefixItems: []*Schema{{}}, Items: nil},
{Name: "tupleClosedFalse", PrefixItems: []*Schema{{}}, Items: nil},
{Name: "tupleOpenTrue", PrefixItems: []*Schema{{}}, Items: &Schema{}},
{Name: "tupleOpenEmpty", PrefixItems: []*Schema{{}}, Items: &Schema{}},
{Name: "tupleOpenTyped", PrefixItems: []*Schema{{}}, Items: &Schema{Type: "boolean"}},
{Name: "tupleOpenMax", PrefixItems: []*Schema{{}}, Items: &Schema{}, MaxItems: 3},
{Name: "array", Items: &Schema{Type: "number"}},
{Name: "null", Type: "null"},
{Name: "string", Type: "string"},
{Name: "boolean", Type: "boolean"},
},
}
if diff := cmp.Diff(want, got); diff != "" {
t.Errorf("(-want, +got)\n%s", diff)
}
}
func TestEffectiveType(t *testing.T) {
const schema = `
{"properties": {
"o": {"type": "object"},
"a": {"type": "array"},
"n": {"type": "number"},
"s": {"type": "string"},
"z": {"type": "null"},
"b": {"type": "boolean"},
"t0": {"prefixItems": [{}], "items": {"type": "number"}},
"t1": {"items": {"type": "number"}, "maxItems": 3},
"v": {"maxItems": 3}
}}
`
var s *Schema
if err := json.Unmarshal([]byte(schema), &s); err != nil {
t.Fatalf("json.Unmarshal: %v", err)
}
var got []string
for _, p := range s.Properties {
got = append(got, p.EffectiveType())
}
want := strings.Fields(`
object
array
number
string
null
boolean
array
array
value
`)
if !reflect.DeepEqual(want, got) {
t.Errorf("\ngot:\n\t%v\nwant:\n\t%v", got, want)
}
}

76
grammar/testdata/schemas.txt vendored Normal file
View File

@@ -0,0 +1,76 @@
# This file holds tests for JSON schema to EBNF grammar conversions.
#
# The format is a JSON schema, followed by the expected EBNF grammar. Each test
# MAY be preceded by a comment that describes the test (e.g. the test name), followed by
# the JSON schema and the expected EBNF grammar. If no comment is present, the test
# name the tests number in the file (e.g. "#0", "#1", etc.)
#
# Blank lines signify the end or start of a new test. Comments can be added
# anywhere in the file, but they must be preceded by a '#' character and start at
# the beginning of the line.
# default
{}
root ::= value;
{"properties": {}}
root ::= value;
# array
{"properties": {"a": {"type": "array", "items": {"type": "string"}}}}
root_0_tuple_0 ::= string;
root_0 ::= "[" ( root_0_tuple_0 )* "]";
root ::= "{" "a" ":" root_0 "}";
# array with nested array
{"type": "array", "items": {"type": "array", "items": {"type": "string"}}}
root_tuple_0_tuple_0 ::= string;
root_tuple_0 ::= "[" ( root_tuple_0_tuple_0 )* "]";
root ::= "[" ( root_tuple_0 )* "]";
# object
{"properties": {"e": {}}}
root_0 ::= value;
root ::= "{" "e" ":" root_0 "}";
# object with nested object
{"properties": {"o": {"type": "object", "properties": {"e": {}}}}}
root_0_0 ::= value;
root_0 ::= "{" "e" ":" root_0_0 "}";
root ::= "{" "o" ":" root_0 "}";
# boolean
{"type": "boolean"}
root ::= boolean;
# number
{"properties": {"n": {"type": "number", "minimum": 123, "maximum": 4567}}}
root_0 ::= number;
root ::= "{" "n" ":" root_0 "}";
# string
{"type": "string"}
root ::= string;
# string with enum
{"type": "string", "enum": ["a", "b", "c"]}
root ::= ( "\"a\"" "|" "\"b\"" "|" "\"c\"" );
# spaces in key
{"properties": {"a b": {}}}
root_0 ::= value;
root ::= "{" "a b" ":" root_0 "}";
# issue7978
{ "type": "object", "properties": { "steps": { "type": "array", "items": { "type": "object", "properties": { "explanation": { "type": "string" }, "output": { "type": "string" } }, "required": [ "explanation", "output" ], "additionalProperties": false } }, "final_answer": { "type": "string" } }, "required": [ "steps", "final_answer" ], "additionalProperties": false }
root_0_tuple_0_0 ::= string;
root_0_tuple_0_1 ::= string;
root_0_tuple_0 ::= "{" "explanation" ":" root_0_tuple_0_0 "," "output" ":" root_0_tuple_0_1 "}";
root_0 ::= "[" ( root_0_tuple_0 )* "]";
root_1 ::= string;
root ::= "{" "steps" ":" root_0 "," "final_answer" ":" root_1 "}";
# !! # special characters in key
# !! {"properties": {"a!b": {}}}
# !! !invalid character '!' in key
# !!

View File

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

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 "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);

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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_argsort(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_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);

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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 "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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/**
* 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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/**
* 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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@@ -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_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_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_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_Q4_0, GGML_TYPE_Q4_0);

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