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@@ -10,12 +10,14 @@ WORKDIR /app
|
||||
|
||||
COPY . .
|
||||
|
||||
RUN if [ "${LLAMA_SYCL_F16}" = "ON" ]; then \
|
||||
RUN mkdir build && \
|
||||
cd build && \
|
||||
if [ "${LLAMA_SYCL_F16}" = "ON" ]; then \
|
||||
echo "LLAMA_SYCL_F16 is set" && \
|
||||
export OPT_SYCL_F16="-DLLAMA_SYCL_F16=ON"; \
|
||||
fi && \
|
||||
cmake -B build -DLLAMA_SYCL=ON -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx ${OPT_SYCL_F16} && \
|
||||
cmake --build build --config Release --target main
|
||||
cmake .. -DLLAMA_SYCL=ON -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx ${OPT_SYCL_F16} && \
|
||||
cmake --build . --config Release --target main
|
||||
|
||||
FROM intel/oneapi-basekit:$ONEAPI_VERSION as runtime
|
||||
|
||||
|
||||
@@ -14,8 +14,10 @@ RUN wget -qO - https://packages.lunarg.com/lunarg-signing-key-pub.asc | apt-key
|
||||
# Build it
|
||||
WORKDIR /app
|
||||
COPY . .
|
||||
RUN cmake -B build -DLLAMA_VULKAN=1 && \
|
||||
cmake --build build --config Release --target main
|
||||
RUN mkdir build && \
|
||||
cd build && \
|
||||
cmake .. -DLLAMA_VULKAN=1 && \
|
||||
cmake --build . --config Release --target main
|
||||
|
||||
# Clean up
|
||||
WORKDIR /
|
||||
|
||||
@@ -10,12 +10,14 @@ WORKDIR /app
|
||||
|
||||
COPY . .
|
||||
|
||||
RUN if [ "${LLAMA_SYCL_F16}" = "ON" ]; then \
|
||||
RUN mkdir build && \
|
||||
cd build && \
|
||||
if [ "${LLAMA_SYCL_F16}" = "ON" ]; then \
|
||||
echo "LLAMA_SYCL_F16 is set" && \
|
||||
export OPT_SYCL_F16="-DLLAMA_SYCL_F16=ON"; \
|
||||
fi && \
|
||||
cmake -B build -DLLAMA_SYCL=ON -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx -DLLAMA_CURL=ON ${OPT_SYCL_F16} && \
|
||||
cmake --build build --config Release --target server
|
||||
cmake .. -DLLAMA_SYCL=ON -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx -DLLAMA_CURL=ON ${OPT_SYCL_F16} && \
|
||||
cmake --build . --config Release --target server
|
||||
|
||||
FROM intel/oneapi-basekit:$ONEAPI_VERSION as runtime
|
||||
|
||||
|
||||
@@ -18,8 +18,10 @@ RUN apt-get update && \
|
||||
# Build it
|
||||
WORKDIR /app
|
||||
COPY . .
|
||||
RUN cmake -B build -DLLAMA_VULKAN=1 -DLLAMA_CURL=1 && \
|
||||
cmake --build build --config Release --target server
|
||||
RUN mkdir build && \
|
||||
cd build && \
|
||||
cmake .. -DLLAMA_VULKAN=1 -DLLAMA_CURL=1 && \
|
||||
cmake --build . --config Release --target server
|
||||
|
||||
# Clean up
|
||||
WORKDIR /
|
||||
|
||||
@@ -96,7 +96,9 @@ jobs:
|
||||
id: cmake_build
|
||||
run: |
|
||||
set -eux
|
||||
cmake -B build \
|
||||
mkdir build
|
||||
cd build
|
||||
cmake .. \
|
||||
-DLLAMA_NATIVE=OFF \
|
||||
-DLLAMA_BUILD_SERVER=ON \
|
||||
-DLLAMA_CURL=ON \
|
||||
@@ -107,7 +109,7 @@ jobs:
|
||||
-DLLAMA_FATAL_WARNINGS=OFF \
|
||||
-DLLAMA_ALL_WARNINGS=OFF \
|
||||
-DCMAKE_BUILD_TYPE=Release;
|
||||
cmake --build build --config Release -j $(nproc) --target server
|
||||
cmake --build . --config Release -j $(nproc) --target server
|
||||
|
||||
- name: Download the dataset
|
||||
id: download_dataset
|
||||
|
||||
@@ -94,13 +94,15 @@ jobs:
|
||||
- name: Build
|
||||
id: cmake_build
|
||||
run: |
|
||||
cmake -B build \
|
||||
mkdir build
|
||||
cd build
|
||||
cmake .. \
|
||||
-DLLAMA_NATIVE=OFF \
|
||||
-DLLAMA_BUILD_SERVER=ON \
|
||||
-DLLAMA_CURL=ON \
|
||||
-DCMAKE_BUILD_TYPE=${{ matrix.build_type }} \
|
||||
-DLLAMA_SANITIZE_${{ matrix.sanitizer }}=ON ;
|
||||
cmake --build build --config ${{ matrix.build_type }} -j $(nproc) --target server
|
||||
cmake --build . --config ${{ matrix.build_type }} -j $(nproc) --target server
|
||||
|
||||
|
||||
- name: Tests
|
||||
@@ -141,8 +143,10 @@ jobs:
|
||||
- name: Build
|
||||
id: cmake_build
|
||||
run: |
|
||||
cmake -B build -DLLAMA_CURL=ON -DCURL_LIBRARY="$env:RUNNER_TEMP/libcurl/lib/libcurl.dll.a" -DCURL_INCLUDE_DIR="$env:RUNNER_TEMP/libcurl/include"
|
||||
cmake --build build --config Release -j ${env:NUMBER_OF_PROCESSORS} --target server
|
||||
mkdir build
|
||||
cd build
|
||||
cmake .. -DLLAMA_CURL=ON -DCURL_LIBRARY="$env:RUNNER_TEMP/libcurl/lib/libcurl.dll.a" -DCURL_INCLUDE_DIR="$env:RUNNER_TEMP/libcurl/include"
|
||||
cmake --build . --config Release -j ${env:NUMBER_OF_PROCESSORS} --target server
|
||||
|
||||
- name: Python setup
|
||||
id: setup_python
|
||||
|
||||
@@ -2,7 +2,6 @@
|
||||
*.a
|
||||
*.so
|
||||
*.gguf
|
||||
*.gguf.json
|
||||
*.bin
|
||||
*.exe
|
||||
*.dll
|
||||
|
||||
+18
-13
@@ -185,8 +185,9 @@ Upon a successful installation, SYCL is enabled for the available intel devices,
|
||||
```sh
|
||||
git clone https://github.com/oneapi-src/oneMKL
|
||||
cd oneMKL
|
||||
cmake -B buildWithCublas -DCMAKE_CXX_COMPILER=icpx -DCMAKE_C_COMPILER=icx -DENABLE_MKLGPU_BACKEND=OFF -DENABLE_MKLCPU_BACKEND=OFF -DENABLE_CUBLAS_BACKEND=ON -DTARGET_DOMAINS=blas
|
||||
cmake --build buildWithCublas --config Release
|
||||
mkdir -p buildWithCublas && cd buildWithCublas
|
||||
cmake ../ -DCMAKE_CXX_COMPILER=icpx -DCMAKE_C_COMPILER=icx -DENABLE_MKLGPU_BACKEND=OFF -DENABLE_MKLCPU_BACKEND=OFF -DENABLE_CUBLAS_BACKEND=ON -DTARGET_DOMAINS=blas
|
||||
make
|
||||
```
|
||||
|
||||
|
||||
@@ -226,15 +227,16 @@ Similarly, user targeting Nvidia GPUs should expect at least one SYCL-CUDA devic
|
||||
source /opt/intel/oneapi/setvars.sh
|
||||
|
||||
# Build LLAMA with MKL BLAS acceleration for intel GPU
|
||||
mkdir -p build && cd build
|
||||
|
||||
# Option 1: Use FP32 (recommended for better performance in most cases)
|
||||
cmake -B build -DLLAMA_SYCL=ON -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx
|
||||
cmake .. -DLLAMA_SYCL=ON -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx
|
||||
|
||||
# Option 2: Use FP16
|
||||
cmake -B build -DLLAMA_SYCL=ON -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx -DLLAMA_SYCL_F16=ON
|
||||
cmake .. -DLLAMA_SYCL=ON -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx -DLLAMA_SYCL_F16=ON
|
||||
|
||||
# build all binary
|
||||
cmake --build build --config Release -j -v
|
||||
#build all binary
|
||||
cmake --build . --config Release -j -v
|
||||
```
|
||||
|
||||
#### Nvidia GPU
|
||||
@@ -246,15 +248,16 @@ export CPLUS_INCLUDE_DIR=/path/to/oneMKL/buildWithCublas/include:$CPLUS_INCLUDE_
|
||||
export CPLUS_INCLUDE_DIR=/path/to/oneMKL/include:$CPLUS_INCLUDE_DIR
|
||||
|
||||
# Build LLAMA with Nvidia BLAS acceleration through SYCL
|
||||
mkdir -p build && cd build
|
||||
|
||||
# Option 1: Use FP32 (recommended for better performance in most cases)
|
||||
cmake -B build -DLLAMA_SYCL=ON -DLLAMA_SYCL_TARGET=NVIDIA -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx
|
||||
cmake .. -DLLAMA_SYCL=ON -DLLAMA_SYCL_TARGET=NVIDIA -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx
|
||||
|
||||
# Option 2: Use FP16
|
||||
cmake -B build -DLLAMA_SYCL=ON -DLLAMA_SYCL_TARGET=NVIDIA -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx -DLLAMA_SYCL_F16=ON
|
||||
cmake .. -DLLAMA_SYCL=ON -DLLAMA_SYCL_TARGET=NVIDIA -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx -DLLAMA_SYCL_F16=ON
|
||||
|
||||
# build all binary
|
||||
cmake --build build --config Release -j -v
|
||||
#build all binary
|
||||
cmake --build . --config Release -j -v
|
||||
|
||||
```
|
||||
|
||||
@@ -409,15 +412,17 @@ b. Download & install mingw-w64 make for Windows provided by w64devkit
|
||||
On the oneAPI command line window, step into the llama.cpp main directory and run the following:
|
||||
|
||||
```
|
||||
mkdir -p build
|
||||
cd build
|
||||
@call "C:\Program Files (x86)\Intel\oneAPI\setvars.bat" intel64 --force
|
||||
|
||||
# Option 1: Use FP32 (recommended for better performance in most cases)
|
||||
cmake -B build -G "MinGW Makefiles" -DLLAMA_SYCL=ON -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icx -DCMAKE_BUILD_TYPE=Release
|
||||
cmake -G "MinGW Makefiles" .. -DLLAMA_SYCL=ON -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icx -DCMAKE_BUILD_TYPE=Release
|
||||
|
||||
# Option 2: Or FP16
|
||||
cmake -B build -G "MinGW Makefiles" -DLLAMA_SYCL=ON -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icx -DCMAKE_BUILD_TYPE=Release -DLLAMA_SYCL_F16=ON
|
||||
cmake -G "MinGW Makefiles" .. -DLLAMA_SYCL=ON -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icx -DCMAKE_BUILD_TYPE=Release -DLLAMA_SYCL_F16=ON
|
||||
|
||||
cmake --build build --config Release -j
|
||||
make -j
|
||||
```
|
||||
|
||||
Otherwise, run the `win-build-sycl.bat` wrapper which encapsulates the former instructions:
|
||||
|
||||
@@ -308,8 +308,6 @@ In order to build llama.cpp you have three different options.
|
||||
make
|
||||
```
|
||||
|
||||
**Note**: for `Debug` builds, run `make LLAMA_DEBUG=1`
|
||||
|
||||
- On Windows:
|
||||
|
||||
1. Download the latest fortran version of [w64devkit](https://github.com/skeeto/w64devkit/releases).
|
||||
@@ -324,26 +322,12 @@ In order to build llama.cpp you have three different options.
|
||||
- Using `CMake`:
|
||||
|
||||
```bash
|
||||
cmake -B build
|
||||
cmake --build build --config Release
|
||||
mkdir build
|
||||
cd build
|
||||
cmake ..
|
||||
cmake --build . --config Release
|
||||
```
|
||||
|
||||
**Note**: for `Debug` builds, there are two cases:
|
||||
|
||||
- Single-config generators (e.g. default = `Unix Makefiles`; note that they just ignore the `--config` flag):
|
||||
|
||||
```bash
|
||||
cmake -B build -DCMAKE_BUILD_TYPE=Debug
|
||||
cmake --build build
|
||||
```
|
||||
|
||||
- Multi-config generators (`-G` param set to Visual Studio, XCode...):
|
||||
|
||||
```bash
|
||||
cmake -B build -G "Xcode"
|
||||
cmake --build build --config Debug
|
||||
```
|
||||
|
||||
- Using `Zig` (version 0.11 or later):
|
||||
|
||||
Building for optimization levels and CPU features can be accomplished using standard build arguments, for example AVX2, FMA, F16C,
|
||||
@@ -455,8 +439,10 @@ Building the program with BLAS support may lead to some performance improvements
|
||||
- Using `CMake` on Linux:
|
||||
|
||||
```bash
|
||||
cmake -B build -DLLAMA_BLAS=ON -DLLAMA_BLAS_VENDOR=OpenBLAS
|
||||
cmake --build build --config Release
|
||||
mkdir build
|
||||
cd build
|
||||
cmake .. -DLLAMA_BLAS=ON -DLLAMA_BLAS_VENDOR=OpenBLAS
|
||||
cmake --build . --config Release
|
||||
```
|
||||
|
||||
- #### BLIS
|
||||
@@ -476,9 +462,11 @@ Building the program with BLAS support may lead to some performance improvements
|
||||
- Using manual oneAPI installation:
|
||||
By default, `LLAMA_BLAS_VENDOR` is set to `Generic`, so if you already sourced intel environment script and assign `-DLLAMA_BLAS=ON` in cmake, the mkl version of Blas will automatically been selected. Otherwise please install oneAPI and follow the below steps:
|
||||
```bash
|
||||
mkdir build
|
||||
cd build
|
||||
source /opt/intel/oneapi/setvars.sh # You can skip this step if in oneapi-basekit docker image, only required for manual installation
|
||||
cmake -B build -DLLAMA_BLAS=ON -DLLAMA_BLAS_VENDOR=Intel10_64lp -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx -DLLAMA_NATIVE=ON
|
||||
cmake --build build --config Release
|
||||
cmake .. -DLLAMA_BLAS=ON -DLLAMA_BLAS_VENDOR=Intel10_64lp -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx -DLLAMA_NATIVE=ON
|
||||
cmake --build . --config Release
|
||||
```
|
||||
|
||||
- Using oneAPI docker image:
|
||||
@@ -499,8 +487,10 @@ Building the program with BLAS support may lead to some performance improvements
|
||||
- Using `CMake`:
|
||||
|
||||
```bash
|
||||
cmake -B build -DLLAMA_CUDA=ON
|
||||
cmake --build build --config Release
|
||||
mkdir build
|
||||
cd build
|
||||
cmake .. -DLLAMA_CUDA=ON
|
||||
cmake --build . --config Release
|
||||
```
|
||||
|
||||
The environment variable [`CUDA_VISIBLE_DEVICES`](https://docs.nvidia.com/cuda/cuda-c-programming-guide/index.html#env-vars) can be used to specify which GPU(s) will be used. The following compilation options are also available to tweak performance:
|
||||
@@ -527,8 +517,8 @@ Building the program with BLAS support may lead to some performance improvements
|
||||
- Using `CMake` for Linux (assuming a gfx1030-compatible AMD GPU):
|
||||
```bash
|
||||
CC=/opt/rocm/llvm/bin/clang CXX=/opt/rocm/llvm/bin/clang++ \
|
||||
cmake -B build -DLLAMA_HIPBLAS=ON -DAMDGPU_TARGETS=gfx1030 -DCMAKE_BUILD_TYPE=Release \
|
||||
&& cmake --build build --config Release -- -j 16
|
||||
cmake -H. -Bbuild -DLLAMA_HIPBLAS=ON -DAMDGPU_TARGETS=gfx1030 -DCMAKE_BUILD_TYPE=Release \
|
||||
&& cmake --build build -- -j 16
|
||||
```
|
||||
On Linux it is also possible to use unified memory architecture (UMA) to share main memory between the CPU and integrated GPU by setting `-DLLAMA_HIP_UMA=ON"`.
|
||||
However, this hurts performance for non-integrated GPUs (but enables working with integrated GPUs).
|
||||
@@ -574,14 +564,15 @@ Building the program with BLAS support may lead to some performance improvements
|
||||
|
||||
```sh
|
||||
git clone --recurse-submodules https://github.com/KhronosGroup/OpenCL-SDK.git
|
||||
cd OpenCL-SDK
|
||||
cmake -B build -DBUILD_DOCS=OFF \
|
||||
mkdir OpenCL-SDK/build
|
||||
cd OpenCL-SDK/build
|
||||
cmake .. -DBUILD_DOCS=OFF \
|
||||
-DBUILD_EXAMPLES=OFF \
|
||||
-DBUILD_TESTING=OFF \
|
||||
-DOPENCL_SDK_BUILD_SAMPLES=OFF \
|
||||
-DOPENCL_SDK_TEST_SAMPLES=OFF
|
||||
cmake --build build
|
||||
cmake --install build --prefix /some/path
|
||||
cmake --build . --config Release
|
||||
cmake --install . --prefix /some/path
|
||||
```
|
||||
</details>
|
||||
|
||||
@@ -603,23 +594,23 @@ Building the program with BLAS support may lead to some performance improvements
|
||||
```cmd
|
||||
set OPENCL_SDK_ROOT="C:/OpenCL-SDK-v2023.04.17-Win-x64"
|
||||
git clone https://github.com/CNugteren/CLBlast.git
|
||||
cd CLBlast
|
||||
cmake -B build -DBUILD_SHARED_LIBS=OFF -DOVERRIDE_MSVC_FLAGS_TO_MT=OFF -DTUNERS=OFF -DOPENCL_ROOT=%OPENCL_SDK_ROOT% -G "Visual Studio 17 2022" -A x64
|
||||
cmake --build build --config Release
|
||||
cmake --install build --prefix C:/CLBlast
|
||||
mkdir CLBlast\build
|
||||
cd CLBlast\build
|
||||
cmake .. -DBUILD_SHARED_LIBS=OFF -DOVERRIDE_MSVC_FLAGS_TO_MT=OFF -DTUNERS=OFF -DOPENCL_ROOT=%OPENCL_SDK_ROOT% -G "Visual Studio 17 2022" -A x64
|
||||
cmake --build . --config Release
|
||||
cmake --install . --prefix C:/CLBlast
|
||||
```
|
||||
|
||||
(note: `--config Release` at build time is the default and only relevant for Visual Studio builds - or multi-config Ninja builds)
|
||||
|
||||
- <details>
|
||||
<summary>Unix:</summary>
|
||||
|
||||
```sh
|
||||
git clone https://github.com/CNugteren/CLBlast.git
|
||||
cd CLBlast
|
||||
cmake -B build -DBUILD_SHARED_LIBS=OFF -DTUNERS=OFF
|
||||
cmake --build build --config Release
|
||||
cmake --install build --prefix /some/path
|
||||
mkdir CLBlast/build
|
||||
cd CLBlast/build
|
||||
cmake .. -DBUILD_SHARED_LIBS=OFF -DTUNERS=OFF
|
||||
cmake --build . --config Release
|
||||
cmake --install . --prefix /some/path
|
||||
```
|
||||
|
||||
Where `/some/path` is where the built library will be installed (default is `/usr/local`).
|
||||
@@ -633,17 +624,21 @@ Building the program with BLAS support may lead to some performance improvements
|
||||
```
|
||||
- CMake (Unix):
|
||||
```sh
|
||||
cmake -B build -DLLAMA_CLBLAST=ON -DCLBlast_DIR=/some/path
|
||||
cmake --build build --config Release
|
||||
mkdir build
|
||||
cd build
|
||||
cmake .. -DLLAMA_CLBLAST=ON -DCLBlast_DIR=/some/path
|
||||
cmake --build . --config Release
|
||||
```
|
||||
- CMake (Windows):
|
||||
```cmd
|
||||
set CL_BLAST_CMAKE_PKG="C:/CLBlast/lib/cmake/CLBlast"
|
||||
git clone https://github.com/ggerganov/llama.cpp
|
||||
cd llama.cpp
|
||||
cmake -B build -DBUILD_SHARED_LIBS=OFF -DLLAMA_CLBLAST=ON -DCMAKE_PREFIX_PATH=%CL_BLAST_CMAKE_PKG% -G "Visual Studio 17 2022" -A x64
|
||||
cmake --build build --config Release
|
||||
cmake --install build --prefix C:/LlamaCPP
|
||||
mkdir build
|
||||
cd build
|
||||
cmake .. -DBUILD_SHARED_LIBS=OFF -DLLAMA_CLBLAST=ON -DCMAKE_PREFIX_PATH=%CL_BLAST_CMAKE_PKG% -G "Visual Studio 17 2022" -A x64
|
||||
cmake --build . --config Release
|
||||
cmake --install . --prefix C:/LlamaCPP
|
||||
```
|
||||
|
||||
##### Running Llama with CLBlast
|
||||
@@ -699,8 +694,10 @@ Building the program with BLAS support may lead to some performance improvements
|
||||
Then, build llama.cpp using the cmake command below:
|
||||
|
||||
```bash
|
||||
cmake -B build -DLLAMA_VULKAN=1
|
||||
cmake --build build --config Release
|
||||
mkdir -p build
|
||||
cd build
|
||||
cmake .. -DLLAMA_VULKAN=1
|
||||
cmake --build . --config Release
|
||||
# Test the output binary (with "-ngl 33" to offload all layers to GPU)
|
||||
./bin/main -m "PATH_TO_MODEL" -p "Hi you how are you" -n 50 -e -ngl 33 -t 4
|
||||
|
||||
|
||||
+127
-131
@@ -67,6 +67,7 @@
|
||||
#include <sys/syslimits.h>
|
||||
#endif
|
||||
#define LLAMA_CURL_MAX_URL_LENGTH 2084 // Maximum URL Length in Chrome: 2083
|
||||
#define LLAMA_CURL_MAX_HEADER_LENGTH 256
|
||||
#endif // LLAMA_USE_CURL
|
||||
|
||||
using json = nlohmann::ordered_json;
|
||||
@@ -1327,29 +1328,6 @@ bool gpt_params_find_arg(int argc, char ** argv, const std::string & arg, gpt_pa
|
||||
return false;
|
||||
}
|
||||
|
||||
void gpt_params_handle_model_default(gpt_params & params) {
|
||||
if (!params.hf_repo.empty()) {
|
||||
// short-hand to avoid specifying --hf-file -> default it to --model
|
||||
if (params.hf_file.empty()) {
|
||||
if (params.model.empty()) {
|
||||
throw std::invalid_argument("error: --hf-repo requires either --hf-file or --model\n");
|
||||
}
|
||||
params.hf_file = params.model;
|
||||
} else if (params.model.empty()) {
|
||||
params.model = "models/" + string_split(params.hf_file, '/').back();
|
||||
}
|
||||
} else if (!params.model_url.empty()) {
|
||||
if (params.model.empty()) {
|
||||
auto f = string_split(params.model_url, '#').front();
|
||||
f = string_split(f, '?').front();
|
||||
f = string_split(f, '/').back();
|
||||
params.model = "models/" + f;
|
||||
}
|
||||
} else if (params.model.empty()) {
|
||||
params.model = DEFAULT_MODEL_PATH;
|
||||
}
|
||||
}
|
||||
|
||||
bool gpt_params_parse_ex(int argc, char ** argv, gpt_params & params) {
|
||||
bool invalid_param = false;
|
||||
std::string arg;
|
||||
@@ -1378,7 +1356,10 @@ bool gpt_params_parse_ex(int argc, char ** argv, gpt_params & params) {
|
||||
throw std::invalid_argument("error: --prompt-cache-all not supported in interactive mode yet\n");
|
||||
}
|
||||
|
||||
gpt_params_handle_model_default(params);
|
||||
// short-hand to avoid specifying --hf-file -> default it to --model
|
||||
if (!params.hf_repo.empty() && params.hf_file.empty()) {
|
||||
params.hf_file = params.model;
|
||||
}
|
||||
|
||||
if (params.escape) {
|
||||
process_escapes(params.prompt);
|
||||
@@ -1572,7 +1553,7 @@ void gpt_print_usage(int /*argc*/, char ** argv, const gpt_params & params) {
|
||||
printf(" --control-vector-layer-range START END\n");
|
||||
printf(" layer range to apply the control vector(s) to, start and end inclusive\n");
|
||||
printf(" -m FNAME, --model FNAME\n");
|
||||
printf(" model path (default: models/$filename with filename from --hf-file or --model-url if set, otherwise %s)\n", DEFAULT_MODEL_PATH);
|
||||
printf(" model path (default: %s)\n", params.model.c_str());
|
||||
printf(" -md FNAME, --model-draft FNAME\n");
|
||||
printf(" draft model for speculative decoding (default: unused)\n");
|
||||
printf(" -mu MODEL_URL, --model-url MODEL_URL\n");
|
||||
@@ -1921,75 +1902,59 @@ void llama_batch_add(
|
||||
|
||||
#ifdef LLAMA_USE_CURL
|
||||
|
||||
static bool starts_with(const std::string & str, const std::string & prefix) {
|
||||
// While we wait for C++20's std::string::starts_with...
|
||||
return str.rfind(prefix, 0) == 0;
|
||||
}
|
||||
|
||||
static bool llama_download_file(const std::string & url, const std::string & path) {
|
||||
|
||||
// Initialize libcurl
|
||||
std::unique_ptr<CURL, decltype(&curl_easy_cleanup)> curl(curl_easy_init(), &curl_easy_cleanup);
|
||||
if (!curl) {
|
||||
fprintf(stderr, "%s: error initializing libcurl\n", __func__);
|
||||
return false;
|
||||
}
|
||||
|
||||
static bool llama_download_file(CURL * curl, const char * url, const char * path) {
|
||||
bool force_download = false;
|
||||
|
||||
// Set the URL, allow to follow http redirection
|
||||
curl_easy_setopt(curl.get(), CURLOPT_URL, url.c_str());
|
||||
curl_easy_setopt(curl.get(), CURLOPT_FOLLOWLOCATION, 1L);
|
||||
curl_easy_setopt(curl, CURLOPT_URL, url);
|
||||
curl_easy_setopt(curl, CURLOPT_FOLLOWLOCATION, 1L);
|
||||
|
||||
#if defined(_WIN32)
|
||||
// CURLSSLOPT_NATIVE_CA tells libcurl to use standard certificate store of
|
||||
// operating system. Currently implemented under MS-Windows.
|
||||
curl_easy_setopt(curl.get(), CURLOPT_SSL_OPTIONS, CURLSSLOPT_NATIVE_CA);
|
||||
curl_easy_setopt(curl, CURLOPT_SSL_OPTIONS, CURLSSLOPT_NATIVE_CA);
|
||||
#endif
|
||||
|
||||
// Check if the file already exists locally
|
||||
struct stat model_file_info;
|
||||
auto file_exists = (stat(path.c_str(), &model_file_info) == 0);
|
||||
auto file_exists = (stat(path, &model_file_info) == 0);
|
||||
|
||||
// If the file exists, check its JSON metadata companion file.
|
||||
std::string metadata_path = path + ".json";
|
||||
nlohmann::json metadata;
|
||||
std::string etag;
|
||||
std::string last_modified;
|
||||
// If the file exists, check for ${path_model}.etag or ${path_model}.lastModified files
|
||||
char etag[LLAMA_CURL_MAX_HEADER_LENGTH] = {0};
|
||||
char etag_path[PATH_MAX] = {0};
|
||||
snprintf(etag_path, sizeof(etag_path), "%s.etag", path);
|
||||
|
||||
char last_modified[LLAMA_CURL_MAX_HEADER_LENGTH] = {0};
|
||||
char last_modified_path[PATH_MAX] = {0};
|
||||
snprintf(last_modified_path, sizeof(last_modified_path), "%s.lastModified", path);
|
||||
|
||||
if (file_exists) {
|
||||
// Try and read the JSON metadata file (note: stream autoclosed upon exiting this block).
|
||||
std::ifstream metadata_in(metadata_path);
|
||||
if (metadata_in.good()) {
|
||||
try {
|
||||
metadata_in >> metadata;
|
||||
fprintf(stderr, "%s: previous metadata file found %s: %s\n", __func__, metadata_path.c_str(), metadata.dump().c_str());
|
||||
if (metadata.contains("url") && metadata["url"].is_string()) {
|
||||
auto previous_url = metadata["url"].get<std::string>();
|
||||
if (previous_url != url) {
|
||||
fprintf(stderr, "%s: Model URL mismatch: %s != %s\n", __func__, url.c_str(), previous_url.c_str());
|
||||
return false;
|
||||
}
|
||||
}
|
||||
if (metadata.contains("etag") && metadata["etag"].is_string()) {
|
||||
etag = metadata["etag"];
|
||||
}
|
||||
if (metadata.contains("lastModified") && metadata["lastModified"].is_string()) {
|
||||
last_modified = metadata["lastModified"];
|
||||
}
|
||||
} catch (const nlohmann::json::exception & e) {
|
||||
fprintf(stderr, "%s: error reading metadata file %s: %s\n", __func__, metadata_path.c_str(), e.what());
|
||||
return false;
|
||||
auto * f_etag = fopen(etag_path, "r");
|
||||
if (f_etag) {
|
||||
if (!fgets(etag, sizeof(etag), f_etag)) {
|
||||
fprintf(stderr, "%s: unable to read file %s\n", __func__, etag_path);
|
||||
} else {
|
||||
fprintf(stderr, "%s: previous file found %s: %s\n", __func__, etag_path, etag);
|
||||
}
|
||||
fclose(f_etag);
|
||||
}
|
||||
|
||||
auto * f_last_modified = fopen(last_modified_path, "r");
|
||||
if (f_last_modified) {
|
||||
if (!fgets(last_modified, sizeof(last_modified), f_last_modified)) {
|
||||
fprintf(stderr, "%s: unable to read file %s\n", __func__, last_modified_path);
|
||||
} else {
|
||||
fprintf(stderr, "%s: previous file found %s: %s\n", __func__, last_modified_path,
|
||||
last_modified);
|
||||
}
|
||||
fclose(f_last_modified);
|
||||
}
|
||||
} else {
|
||||
fprintf(stderr, "%s: no previous model file found %s\n", __func__, path.c_str());
|
||||
}
|
||||
|
||||
// Send a HEAD request to retrieve the etag and last-modified headers
|
||||
struct llama_load_model_from_url_headers {
|
||||
std::string etag;
|
||||
std::string last_modified;
|
||||
char etag[LLAMA_CURL_MAX_HEADER_LENGTH] = {0};
|
||||
char last_modified[LLAMA_CURL_MAX_HEADER_LENGTH] = {0};
|
||||
};
|
||||
llama_load_model_from_url_headers headers;
|
||||
{
|
||||
@@ -1997,37 +1962,38 @@ static bool llama_download_file(const std::string & url, const std::string & pat
|
||||
auto header_callback = [](char * buffer, size_t /*size*/, size_t n_items, void * userdata) -> size_t {
|
||||
llama_load_model_from_url_headers *headers = (llama_load_model_from_url_headers *) userdata;
|
||||
|
||||
static std::regex header_regex("([^:]+): (.*)\r\n");
|
||||
static std::regex etag_regex("ETag", std::regex_constants::icase);
|
||||
static std::regex last_modified_regex("Last-Modified", std::regex_constants::icase);
|
||||
// Convert header field name to lowercase
|
||||
for (size_t i = 0; i < n_items && buffer[i] != ':'; ++i) {
|
||||
buffer[i] = tolower(buffer[i]);
|
||||
}
|
||||
|
||||
std::string header(buffer, n_items);
|
||||
std::smatch match;
|
||||
if (std::regex_match(header, match, header_regex)) {
|
||||
const std::string & key = match[1];
|
||||
const std::string & value = match[2];
|
||||
if (std::regex_match(key, match, etag_regex)) {
|
||||
headers->etag = value;
|
||||
} else if (std::regex_match(key, match, last_modified_regex)) {
|
||||
headers->last_modified = value;
|
||||
}
|
||||
const char * etag_prefix = "etag: ";
|
||||
if (strncmp(buffer, etag_prefix, strlen(etag_prefix)) == 0) {
|
||||
strncpy(headers->etag, buffer + strlen(etag_prefix), n_items - strlen(etag_prefix) - 2); // Remove CRLF
|
||||
}
|
||||
|
||||
const char * last_modified_prefix = "last-modified: ";
|
||||
if (strncmp(buffer, last_modified_prefix, strlen(last_modified_prefix)) == 0) {
|
||||
strncpy(headers->last_modified, buffer + strlen(last_modified_prefix),
|
||||
n_items - strlen(last_modified_prefix) - 2); // Remove CRLF
|
||||
}
|
||||
return n_items;
|
||||
};
|
||||
|
||||
curl_easy_setopt(curl.get(), CURLOPT_NOBODY, 1L); // will trigger the HEAD verb
|
||||
curl_easy_setopt(curl.get(), CURLOPT_NOPROGRESS, 1L); // hide head request progress
|
||||
curl_easy_setopt(curl.get(), CURLOPT_HEADERFUNCTION, static_cast<CURLOPT_HEADERFUNCTION_PTR>(header_callback));
|
||||
curl_easy_setopt(curl.get(), CURLOPT_HEADERDATA, &headers);
|
||||
curl_easy_setopt(curl, CURLOPT_NOBODY, 1L); // will trigger the HEAD verb
|
||||
curl_easy_setopt(curl, CURLOPT_NOPROGRESS, 1L); // hide head request progress
|
||||
curl_easy_setopt(curl, CURLOPT_HEADERFUNCTION, static_cast<CURLOPT_HEADERFUNCTION_PTR>(header_callback));
|
||||
curl_easy_setopt(curl, CURLOPT_HEADERDATA, &headers);
|
||||
|
||||
CURLcode res = curl_easy_perform(curl.get());
|
||||
CURLcode res = curl_easy_perform(curl);
|
||||
if (res != CURLE_OK) {
|
||||
curl_easy_cleanup(curl);
|
||||
fprintf(stderr, "%s: curl_easy_perform() failed: %s\n", __func__, curl_easy_strerror(res));
|
||||
return false;
|
||||
}
|
||||
|
||||
long http_code = 0;
|
||||
curl_easy_getinfo(curl.get(), CURLINFO_RESPONSE_CODE, &http_code);
|
||||
curl_easy_getinfo(curl, CURLINFO_RESPONSE_CODE, &http_code);
|
||||
if (http_code != 200) {
|
||||
// HEAD not supported, we don't know if the file has changed
|
||||
// force trigger downloading
|
||||
@@ -2036,30 +2002,28 @@ static bool llama_download_file(const std::string & url, const std::string & pat
|
||||
}
|
||||
}
|
||||
|
||||
bool should_download = !file_exists || force_download;
|
||||
if (!should_download) {
|
||||
if (!etag.empty() && etag != headers.etag) {
|
||||
fprintf(stderr, "%s: ETag header is different (%s != %s): triggering a new download\n", __func__, etag.c_str(), headers.etag.c_str());
|
||||
should_download = true;
|
||||
} else if (!last_modified.empty() && last_modified != headers.last_modified) {
|
||||
fprintf(stderr, "%s: Last-Modified header is different (%s != %s): triggering a new download\n", __func__, last_modified.c_str(), headers.last_modified.c_str());
|
||||
should_download = true;
|
||||
}
|
||||
}
|
||||
// If the ETag or the Last-Modified headers are different: trigger a new download
|
||||
bool should_download = !file_exists
|
||||
|| force_download
|
||||
|| (strlen(headers.etag) > 0 && strcmp(etag, headers.etag) != 0)
|
||||
|| (strlen(headers.last_modified) > 0 && strcmp(last_modified, headers.last_modified) != 0);
|
||||
if (should_download) {
|
||||
std::string path_temporary = path + ".downloadInProgress";
|
||||
char path_temporary[PATH_MAX] = {0};
|
||||
snprintf(path_temporary, sizeof(path_temporary), "%s.downloadInProgress", path);
|
||||
if (file_exists) {
|
||||
fprintf(stderr, "%s: deleting previous downloaded file: %s\n", __func__, path.c_str());
|
||||
if (remove(path.c_str()) != 0) {
|
||||
fprintf(stderr, "%s: unable to delete file: %s\n", __func__, path.c_str());
|
||||
fprintf(stderr, "%s: deleting previous downloaded file: %s\n", __func__, path);
|
||||
if (remove(path) != 0) {
|
||||
curl_easy_cleanup(curl);
|
||||
fprintf(stderr, "%s: unable to delete file: %s\n", __func__, path);
|
||||
return false;
|
||||
}
|
||||
}
|
||||
|
||||
// Set the output file
|
||||
std::unique_ptr<FILE, decltype(&fclose)> outfile(fopen(path_temporary.c_str(), "wb"), fclose);
|
||||
auto * outfile = fopen(path_temporary, "wb");
|
||||
if (!outfile) {
|
||||
fprintf(stderr, "%s: error opening local file for writing: %s\n", __func__, path.c_str());
|
||||
curl_easy_cleanup(curl);
|
||||
fprintf(stderr, "%s: error opening local file for writing: %s\n", __func__, path);
|
||||
return false;
|
||||
}
|
||||
|
||||
@@ -2067,12 +2031,12 @@ static bool llama_download_file(const std::string & url, const std::string & pat
|
||||
auto write_callback = [](void * data, size_t size, size_t nmemb, void * fd) -> size_t {
|
||||
return fwrite(data, size, nmemb, (FILE *)fd);
|
||||
};
|
||||
curl_easy_setopt(curl.get(), CURLOPT_NOBODY, 0L);
|
||||
curl_easy_setopt(curl.get(), CURLOPT_WRITEFUNCTION, static_cast<CURLOPT_WRITEFUNCTION_PTR>(write_callback));
|
||||
curl_easy_setopt(curl.get(), CURLOPT_WRITEDATA, outfile.get());
|
||||
curl_easy_setopt(curl, CURLOPT_NOBODY, 0L);
|
||||
curl_easy_setopt(curl, CURLOPT_WRITEFUNCTION, static_cast<CURLOPT_WRITEFUNCTION_PTR>(write_callback));
|
||||
curl_easy_setopt(curl, CURLOPT_WRITEDATA, outfile);
|
||||
|
||||
// display download progress
|
||||
curl_easy_setopt(curl.get(), CURLOPT_NOPROGRESS, 0L);
|
||||
curl_easy_setopt(curl, CURLOPT_NOPROGRESS, 0L);
|
||||
|
||||
// helper function to hide password in URL
|
||||
auto llama_download_hide_password_in_url = [](const std::string & url) -> std::string {
|
||||
@@ -2091,34 +2055,51 @@ static bool llama_download_file(const std::string & url, const std::string & pat
|
||||
|
||||
// start the download
|
||||
fprintf(stderr, "%s: downloading from %s to %s (server_etag:%s, server_last_modified:%s)...\n", __func__,
|
||||
llama_download_hide_password_in_url(url).c_str(), path.c_str(), headers.etag.c_str(), headers.last_modified.c_str());
|
||||
auto res = curl_easy_perform(curl.get());
|
||||
llama_download_hide_password_in_url(url).c_str(), path, headers.etag, headers.last_modified);
|
||||
auto res = curl_easy_perform(curl);
|
||||
if (res != CURLE_OK) {
|
||||
fclose(outfile);
|
||||
curl_easy_cleanup(curl);
|
||||
fprintf(stderr, "%s: curl_easy_perform() failed: %s\n", __func__, curl_easy_strerror(res));
|
||||
return false;
|
||||
}
|
||||
|
||||
long http_code = 0;
|
||||
curl_easy_getinfo (curl.get(), CURLINFO_RESPONSE_CODE, &http_code);
|
||||
curl_easy_getinfo (curl, CURLINFO_RESPONSE_CODE, &http_code);
|
||||
if (http_code < 200 || http_code >= 400) {
|
||||
fclose(outfile);
|
||||
curl_easy_cleanup(curl);
|
||||
fprintf(stderr, "%s: invalid http status code received: %ld\n", __func__, http_code);
|
||||
return false;
|
||||
}
|
||||
|
||||
// Causes file to be closed explicitly here before we rename it.
|
||||
outfile.reset();
|
||||
// Clean up
|
||||
fclose(outfile);
|
||||
|
||||
// Write the updated JSON metadata file.
|
||||
metadata.update({
|
||||
{"url", url},
|
||||
{"etag", headers.etag},
|
||||
{"lastModified", headers.last_modified}
|
||||
});
|
||||
std::ofstream(metadata_path) << metadata.dump(4);
|
||||
fprintf(stderr, "%s: file metadata saved: %s\n", __func__, metadata_path.c_str());
|
||||
// Write the new ETag to the .etag file
|
||||
if (strlen(headers.etag) > 0) {
|
||||
auto * etag_file = fopen(etag_path, "w");
|
||||
if (etag_file) {
|
||||
fputs(headers.etag, etag_file);
|
||||
fclose(etag_file);
|
||||
fprintf(stderr, "%s: file etag saved %s: %s\n", __func__, etag_path, headers.etag);
|
||||
}
|
||||
}
|
||||
|
||||
if (rename(path_temporary.c_str(), path.c_str()) != 0) {
|
||||
fprintf(stderr, "%s: unable to rename file: %s to %s\n", __func__, path_temporary.c_str(), path.c_str());
|
||||
// Write the new lastModified to the .etag file
|
||||
if (strlen(headers.last_modified) > 0) {
|
||||
auto * last_modified_file = fopen(last_modified_path, "w");
|
||||
if (last_modified_file) {
|
||||
fputs(headers.last_modified, last_modified_file);
|
||||
fclose(last_modified_file);
|
||||
fprintf(stderr, "%s: file last modified saved %s: %s\n", __func__, last_modified_path,
|
||||
headers.last_modified);
|
||||
}
|
||||
}
|
||||
|
||||
if (rename(path_temporary, path) != 0) {
|
||||
curl_easy_cleanup(curl);
|
||||
fprintf(stderr, "%s: unable to rename file: %s to %s\n", __func__, path_temporary, path);
|
||||
return false;
|
||||
}
|
||||
}
|
||||
@@ -2136,7 +2117,15 @@ struct llama_model * llama_load_model_from_url(
|
||||
return NULL;
|
||||
}
|
||||
|
||||
if (!llama_download_file(model_url, path_model)) {
|
||||
// Initialize libcurl
|
||||
auto * curl = curl_easy_init();
|
||||
|
||||
if (!curl) {
|
||||
fprintf(stderr, "%s: error initializing libcurl\n", __func__);
|
||||
return NULL;
|
||||
}
|
||||
|
||||
if (!llama_download_file(curl, model_url, path_model)) {
|
||||
return NULL;
|
||||
}
|
||||
|
||||
@@ -2150,6 +2139,7 @@ struct llama_model * llama_load_model_from_url(
|
||||
auto * ctx_gguf = gguf_init_from_file(path_model, gguf_params);
|
||||
if (!ctx_gguf) {
|
||||
fprintf(stderr, "\n%s: failed to load input GGUF from %s\n", __func__, path_model);
|
||||
curl_easy_cleanup(curl);
|
||||
return NULL;
|
||||
}
|
||||
|
||||
@@ -2161,6 +2151,8 @@ struct llama_model * llama_load_model_from_url(
|
||||
gguf_free(ctx_gguf);
|
||||
}
|
||||
|
||||
curl_easy_cleanup(curl);
|
||||
|
||||
if (n_split > 1) {
|
||||
char split_prefix[PATH_MAX] = {0};
|
||||
char split_url_prefix[LLAMA_CURL_MAX_URL_LENGTH] = {0};
|
||||
@@ -2191,7 +2183,11 @@ struct llama_model * llama_load_model_from_url(
|
||||
char split_url[LLAMA_CURL_MAX_URL_LENGTH] = {0};
|
||||
llama_split_path(split_url, sizeof(split_url), split_url_prefix, download_idx, n_split);
|
||||
|
||||
return llama_download_file(split_url, split_path);
|
||||
auto * curl = curl_easy_init();
|
||||
bool res = llama_download_file(curl, split_url, split_path);
|
||||
curl_easy_cleanup(curl);
|
||||
|
||||
return res;
|
||||
}, idx));
|
||||
}
|
||||
|
||||
@@ -2678,7 +2674,7 @@ void dump_non_result_info_yaml(FILE * stream, const gpt_params & params, const l
|
||||
fprintf(stream, "mirostat_ent: %f # default: 5.0\n", sparams.mirostat_tau);
|
||||
fprintf(stream, "mirostat_lr: %f # default: 0.1\n", sparams.mirostat_eta);
|
||||
fprintf(stream, "mlock: %s # default: false\n", params.use_mlock ? "true" : "false");
|
||||
fprintf(stream, "model: %s # default: %s\n", params.model.c_str(), DEFAULT_MODEL_PATH);
|
||||
fprintf(stream, "model: %s # default: models/7B/ggml-model.bin\n", params.model.c_str());
|
||||
fprintf(stream, "model_draft: %s # default:\n", params.model_draft.c_str());
|
||||
fprintf(stream, "multiline_input: %s # default: false\n", params.multiline_input ? "true" : "false");
|
||||
fprintf(stream, "n_gpu_layers: %d # default: -1\n", params.n_gpu_layers);
|
||||
|
||||
+1
-5
@@ -31,8 +31,6 @@
|
||||
fprintf(stderr, "%s: built with %s for %s\n", __func__, LLAMA_COMPILER, LLAMA_BUILD_TARGET); \
|
||||
} while(0)
|
||||
|
||||
#define DEFAULT_MODEL_PATH "models/7B/ggml-model-f16.gguf"
|
||||
|
||||
// build info
|
||||
extern int LLAMA_BUILD_NUMBER;
|
||||
extern char const *LLAMA_COMMIT;
|
||||
@@ -94,7 +92,7 @@ struct gpt_params {
|
||||
// // sampling parameters
|
||||
struct llama_sampling_params sparams;
|
||||
|
||||
std::string model = ""; // model path
|
||||
std::string model = "models/7B/ggml-model-f16.gguf"; // model path
|
||||
std::string model_draft = ""; // draft model for speculative decoding
|
||||
std::string model_alias = "unknown"; // model alias
|
||||
std::string model_url = ""; // model url to download
|
||||
@@ -174,8 +172,6 @@ struct gpt_params {
|
||||
std::vector<std::string> image; // path to image file(s)
|
||||
};
|
||||
|
||||
void gpt_params_handle_model_default(gpt_params & params);
|
||||
|
||||
bool parse_kv_override(const char * data, std::vector<llama_model_kv_override> & overrides);
|
||||
|
||||
bool gpt_params_parse_ex(int argc, char ** argv, gpt_params & params);
|
||||
|
||||
@@ -128,7 +128,7 @@ for model in models:
|
||||
print(f"chkhsh: {chkhsh}")
|
||||
|
||||
# print the "pre_tokenizer" content from the tokenizer.json
|
||||
with open(f"models/tokenizers/{name}/tokenizer.json", "r", encoding="utf-8") as f:
|
||||
with open(f"models/tokenizers/{name}/tokenizer.json", "r") as f:
|
||||
cfg = json.load(f)
|
||||
pre_tokenizer = cfg["pre_tokenizer"]
|
||||
print("pre_tokenizer: " + json.dumps(pre_tokenizer, indent=4))
|
||||
@@ -156,19 +156,15 @@ src_func += " print(f\"chkhsh: {chkhsh}\")\n"
|
||||
src_func += "\n"
|
||||
src_func += " res = None\n"
|
||||
src_func += "\n"
|
||||
src_func += " # NOTE: if you get an error here, you need to update the convert-hf-to-gguf-update.py script\n"
|
||||
src_func += " # or pull the latest version of the model from Huggingface\n"
|
||||
src_func += " # don't edit the hashes manually!\n"
|
||||
src_func += " # NOTE: if you get an error here, you need to add the model to the if-elif chain below\n"
|
||||
src_func += " # don't do this manually - use the convert-hf-to-gguf-update.py script!\n"
|
||||
src_func += f"{src_ifs}\n"
|
||||
src_func += " if res is None:\n"
|
||||
src_func += " print(\"\\n\")\n"
|
||||
src_func += " print(\"**************************************************************************************\")\n"
|
||||
src_func += " print(\"** WARNING: The BPE pre-tokenizer was not recognized!\")\n"
|
||||
src_func += " print(\"** There are 2 possible reasons for this:\")\n"
|
||||
src_func += " print(\"** - the model has not been added to convert-hf-to-gguf-update.py yet\")\n"
|
||||
src_func += " print(\"** - the pre-tokenization config has changed upstream\")\n"
|
||||
src_func += " print(\"** Check your model files and convert-hf-to-gguf-update.py and update them accordingly.\")\n"
|
||||
src_func += " print(\"** ref: https://github.com/ggerganov/llama.cpp/pull/6920\")\n"
|
||||
src_func += " print(\"** This means that it was not added yet or you are using an older version.\")\n"
|
||||
src_func += " print(\"** Check convert-hf-to-gguf-update.py and update it accordingly.\")\n"
|
||||
src_func += " print(\"**\")\n"
|
||||
src_func += " print(f\"** chkhsh: {chkhsh}\")\n"
|
||||
src_func += " print(\"**************************************************************************************\")\n"
|
||||
@@ -253,7 +249,7 @@ for model in models:
|
||||
from transformers import AutoTokenizer
|
||||
tokenizer = AutoTokenizer.from_pretrained(f"models/tokenizers/{name}")
|
||||
|
||||
with open(f"models/ggml-vocab-{name}.gguf.inp", "w", encoding="utf-8") as f:
|
||||
with open(f"models/ggml-vocab-{name}.gguf.inp", "w") as f:
|
||||
for text in tests:
|
||||
f.write(f"{text}")
|
||||
f.write("\n__ggml_vocab_test__\n")
|
||||
|
||||
@@ -279,9 +279,8 @@ class Model(ABC):
|
||||
|
||||
res = None
|
||||
|
||||
# NOTE: if you get an error here, you need to update the convert-hf-to-gguf-update.py script
|
||||
# or pull the latest version of the model from Huggingface
|
||||
# don't edit the hashes manually!
|
||||
# NOTE: if you get an error here, you need to add the model to the if-elif chain below
|
||||
# don't do this manually - use the convert-hf-to-gguf-update.py script!
|
||||
if chkhsh == "0ef9807a4087ebef797fc749390439009c3b9eda9ad1a097abbe738f486c01e5":
|
||||
# ref: https://huggingface.co/meta-llama/Meta-Llama-3-8B
|
||||
res = "llama-bpe"
|
||||
@@ -311,11 +310,8 @@ class Model(ABC):
|
||||
print("\n")
|
||||
print("**************************************************************************************")
|
||||
print("** WARNING: The BPE pre-tokenizer was not recognized!")
|
||||
print("** There are 2 possible reasons for this:")
|
||||
print("** - the model has not been added to convert-hf-to-gguf-update.py yet")
|
||||
print("** - the pre-tokenization config has changed upstream")
|
||||
print("** Check your model files and convert-hf-to-gguf-update.py and update them accordingly.")
|
||||
print("** ref: https://github.com/ggerganov/llama.cpp/pull/6920")
|
||||
print("** This means that it was not added yet or you are using an older version.")
|
||||
print("** Check convert-hf-to-gguf-update.py and update it accordingly.")
|
||||
print("**")
|
||||
print(f"** chkhsh: {chkhsh}")
|
||||
print("**************************************************************************************")
|
||||
|
||||
@@ -17,9 +17,11 @@ In this case, CLBlast was already installed so the CMake package is referenced i
|
||||
```cmd
|
||||
git clone https://github.com/ggerganov/llama.cpp
|
||||
cd llama.cpp
|
||||
cmake -B build -DBUILD_SHARED_LIBS=OFF -DLLAMA_CLBLAST=ON -DCMAKE_PREFIX_PATH=C:/CLBlast/lib/cmake/CLBlast -G "Visual Studio 17 2022" -A x64
|
||||
cmake --build build --config Release
|
||||
cmake --install build --prefix C:/LlamaCPP
|
||||
mkdir build
|
||||
cd build
|
||||
cmake .. -DBUILD_SHARED_LIBS=OFF -DLLAMA_CLBLAST=ON -DCMAKE_PREFIX_PATH=C:/CLBlast/lib/cmake/CLBlast -G "Visual Studio 17 2022" -A x64
|
||||
cmake --build . --config Release
|
||||
cmake --install . --prefix C:/LlamaCPP
|
||||
```
|
||||
|
||||
### Build main-cmake-pkg
|
||||
@@ -27,7 +29,9 @@ cmake --install build --prefix C:/LlamaCPP
|
||||
|
||||
```cmd
|
||||
cd ..\examples\main-cmake-pkg
|
||||
cmake -B build -DBUILD_SHARED_LIBS=OFF -DCMAKE_PREFIX_PATH="C:/CLBlast/lib/cmake/CLBlast;C:/LlamaCPP/lib/cmake/Llama" -G "Visual Studio 17 2022" -A x64
|
||||
cmake --build build --config Release
|
||||
cmake --install build --prefix C:/MyLlamaApp
|
||||
mkdir build
|
||||
cd build
|
||||
cmake .. -DBUILD_SHARED_LIBS=OFF -DCMAKE_PREFIX_PATH="C:/CLBlast/lib/cmake/CLBlast;C:/LlamaCPP/lib/cmake/Llama" -G "Visual Studio 17 2022" -A x64
|
||||
cmake --build . --config Release
|
||||
cmake --install . --prefix C:/MyLlamaApp
|
||||
```
|
||||
|
||||
@@ -66,7 +66,7 @@ main.exe -m models\7B\ggml-model.bin --ignore-eos -n -1 --random-prompt
|
||||
|
||||
In this section, we cover the most commonly used options for running the `main` program with the LLaMA models:
|
||||
|
||||
- `-m FNAME, --model FNAME`: Specify the path to the LLaMA model file (e.g., `models/7B/ggml-model.gguf`; inferred from `--model-url` if set).
|
||||
- `-m FNAME, --model FNAME`: Specify the path to the LLaMA model file (e.g., `models/7B/ggml-model.bin`).
|
||||
- `-mu MODEL_URL --model-url MODEL_URL`: Specify a remote http url to download the file (e.g https://huggingface.co/ggml-org/models/resolve/main/phi-2/ggml-model-q4_0.gguf).
|
||||
- `-i, --interactive`: Run the program in interactive mode, allowing you to provide input directly and receive real-time responses.
|
||||
- `-ins, --instruct`: Run the program in instruction mode, which is particularly useful when working with Alpaca models.
|
||||
|
||||
@@ -324,7 +324,7 @@ int main(int argc, char ** argv) {
|
||||
log_tostr(embd_inp.empty()), n_matching_session_tokens, embd_inp.size(), session_tokens.size(), embd_inp.size());
|
||||
|
||||
// if we will use the cache for the full prompt without reaching the end of the cache, force
|
||||
// reevaluation of the last token to recalculate the cached logits
|
||||
// reevaluation of the last token token to recalculate the cached logits
|
||||
if (!embd_inp.empty() && n_matching_session_tokens == embd_inp.size() && session_tokens.size() > embd_inp.size()) {
|
||||
LOGLN("recalculate the cached logits (do): session_tokens.resize( %zu )", embd_inp.size() - 1);
|
||||
|
||||
|
||||
@@ -23,7 +23,7 @@
|
||||
#endif
|
||||
|
||||
struct quantize_stats_params {
|
||||
std::string model = DEFAULT_MODEL_PATH;
|
||||
std::string model = "models/7B/ggml-model-f16.gguf";
|
||||
bool verbose = false;
|
||||
bool per_layer_stats = false;
|
||||
bool print_histogram = false;
|
||||
|
||||
@@ -74,18 +74,15 @@ page cache before using this. See https://github.com/ggerganov/llama.cpp/issues/
|
||||
- Using `make`:
|
||||
|
||||
```bash
|
||||
make server
|
||||
make
|
||||
```
|
||||
|
||||
- Using `CMake`:
|
||||
|
||||
```bash
|
||||
cmake -B build
|
||||
cmake --build build --config Release -t server
|
||||
cmake --build . --config Release
|
||||
```
|
||||
|
||||
Binary is at `./build/bin/server`
|
||||
|
||||
## Build with SSL
|
||||
|
||||
`server` can also be built with SSL support using OpenSSL 3
|
||||
@@ -102,8 +99,10 @@ page cache before using this. See https://github.com/ggerganov/llama.cpp/issues/
|
||||
- Using `CMake`:
|
||||
|
||||
```bash
|
||||
cmake -B build -DLLAMA_SERVER_SSL=ON
|
||||
cmake --build build --config Release -t server
|
||||
mkdir build
|
||||
cd build
|
||||
cmake .. -DLLAMA_SERVER_SSL=ON
|
||||
make server
|
||||
```
|
||||
|
||||
## Quick Start
|
||||
|
||||
@@ -2353,7 +2353,7 @@ static void server_print_usage(const char * argv0, const gpt_params & params, co
|
||||
printf(" disable KV offload\n");
|
||||
}
|
||||
printf(" -m FNAME, --model FNAME\n");
|
||||
printf(" model path (default: models/$filename with filename from --hf-file or --model-url if set, otherwise %s)\n", DEFAULT_MODEL_PATH);
|
||||
printf(" model path (default: %s)\n", params.model.c_str());
|
||||
printf(" -mu MODEL_URL, --model-url MODEL_URL\n");
|
||||
printf(" model download url (default: unused)\n");
|
||||
printf(" -hfr REPO, --hf-repo REPO\n");
|
||||
@@ -2838,8 +2838,6 @@ static void server_params_parse(int argc, char ** argv, server_params & sparams,
|
||||
}
|
||||
}
|
||||
|
||||
gpt_params_handle_model_default(params);
|
||||
|
||||
if (!params.kv_overrides.empty()) {
|
||||
params.kv_overrides.emplace_back();
|
||||
params.kv_overrides.back().key[0] = 0;
|
||||
|
||||
@@ -5,7 +5,7 @@ Feature: llama.cpp server
|
||||
Background: Server startup
|
||||
Given a server listening on localhost:8080
|
||||
And a model url https://huggingface.co/ggml-org/models/resolve/main/bert-bge-small/ggml-model-f16.gguf
|
||||
And a model file bert-bge-small.gguf
|
||||
And a model file ggml-model-f16.gguf
|
||||
And a model alias bert-bge-small
|
||||
And 42 as server seed
|
||||
And 2 slots
|
||||
|
||||
@@ -2779,11 +2779,6 @@ static enum ggml_status ggml_metal_graph_compute(
|
||||
MTLCommandBufferStatus status = [command_buffer status];
|
||||
if (status != MTLCommandBufferStatusCompleted) {
|
||||
GGML_METAL_LOG_INFO("%s: command buffer %d failed with status %lu\n", __func__, i, status);
|
||||
if (status == MTLCommandBufferStatusError) {
|
||||
NSString * error_code = [command_buffer error].localizedDescription;
|
||||
GGML_METAL_LOG_INFO("error: %s\n", [error_code UTF8String]);
|
||||
}
|
||||
|
||||
return GGML_STATUS_FAILED;
|
||||
}
|
||||
}
|
||||
|
||||
+136
-225
@@ -10,10 +10,15 @@
|
||||
#include "unicode.h"
|
||||
#include <cassert>
|
||||
#include <string>
|
||||
#include <vector>
|
||||
|
||||
static llama_grammar* build_grammar(const std::string & grammar_str) {
|
||||
auto parsed_grammar = grammar_parser::parse(grammar_str.c_str());
|
||||
static void test_simple_grammar() {
|
||||
// Test case for a simple grammar
|
||||
const std::string grammar_str = R"""(root ::= expr
|
||||
expr ::= term ("+" term)*
|
||||
term ::= number
|
||||
number ::= [0-9]+)""";
|
||||
|
||||
grammar_parser::parse_state parsed_grammar = grammar_parser::parse(grammar_str.c_str());
|
||||
|
||||
// Ensure we parsed correctly
|
||||
assert(!parsed_grammar.rules.empty());
|
||||
@@ -25,10 +30,8 @@ static llama_grammar* build_grammar(const std::string & grammar_str) {
|
||||
llama_grammar* grammar = llama_grammar_init(
|
||||
grammar_rules.data(), grammar_rules.size(), parsed_grammar.symbol_ids.at("root"));
|
||||
|
||||
return grammar;
|
||||
}
|
||||
std::string input = "123+456";
|
||||
|
||||
static bool match_string(const std::string & input, llama_grammar* grammar) {
|
||||
auto decoded = decode_utf8(input, {});
|
||||
|
||||
const auto & code_points = decoded.first;
|
||||
@@ -36,67 +39,159 @@ static bool match_string(const std::string & input, llama_grammar* grammar) {
|
||||
for (auto it = code_points.begin(), end = code_points.end() - 1; it != end; ++it) {
|
||||
auto prev_stacks = grammar->stacks;
|
||||
llama_grammar_accept(grammar->rules, prev_stacks, *it, grammar->stacks);
|
||||
if (grammar->stacks.empty()) {
|
||||
// no stacks means that the grammar failed to match at this point
|
||||
return false;
|
||||
}
|
||||
assert(!grammar->stacks.empty());
|
||||
}
|
||||
|
||||
bool completed_grammar = false;
|
||||
|
||||
for (const auto & stack : grammar->stacks) {
|
||||
if (stack.empty()) {
|
||||
// An empty stack means that the grammar has been completed
|
||||
return true;
|
||||
completed_grammar = true;
|
||||
break;
|
||||
}
|
||||
}
|
||||
|
||||
return false;
|
||||
assert(completed_grammar);
|
||||
|
||||
// Clean up allocated memory
|
||||
llama_grammar_free(grammar);
|
||||
}
|
||||
|
||||
static void test_grammar(const std::string & test_desc, const std::string & grammar_str, const std::vector<std::string> & passing_strings, const std::vector<std::string> & failing_strings) {
|
||||
fprintf(stderr, "⚫ Testing %s. Grammar: %s\n", test_desc.c_str(), grammar_str.c_str());
|
||||
fflush(stderr);
|
||||
static void test_complex_grammar() {
|
||||
// Test case for a more complex grammar, with both failure strings and success strings
|
||||
const std::string grammar_str = R"""(root ::= expression
|
||||
expression ::= term ws (("+"|"-") ws term)*
|
||||
term ::= factor ws (("*"|"/") ws factor)*
|
||||
factor ::= number | variable | "(" expression ")" | function-call
|
||||
number ::= [0-9]+
|
||||
variable ::= [a-zA-Z_][a-zA-Z0-9_]*
|
||||
function-call ::= variable ws "(" (expression ("," ws expression)*)? ")"
|
||||
ws ::= [ \t\n\r]?)""";
|
||||
|
||||
auto grammar = build_grammar(grammar_str);
|
||||
grammar_parser::parse_state parsed_grammar = grammar_parser::parse(grammar_str.c_str());
|
||||
|
||||
// Ensure we parsed correctly
|
||||
assert(!parsed_grammar.rules.empty());
|
||||
|
||||
// Ensure we have a root node
|
||||
assert(!(parsed_grammar.symbol_ids.find("root") == parsed_grammar.symbol_ids.end()));
|
||||
|
||||
std::vector<const llama_grammar_element*> grammar_rules(parsed_grammar.c_rules());
|
||||
llama_grammar* grammar = llama_grammar_init(
|
||||
grammar_rules.data(), grammar_rules.size(), parsed_grammar.symbol_ids.at("root"));
|
||||
|
||||
// Save the original grammar stacks so that we can reset after every new string we want to test
|
||||
auto original_stacks = grammar->stacks;
|
||||
|
||||
fprintf(stderr, " 🔵 Valid strings:\n");
|
||||
// Test a few strings
|
||||
std::vector<std::string> test_strings_pass = {
|
||||
"42",
|
||||
"1*2*3*4*5",
|
||||
"x",
|
||||
"x+10",
|
||||
"x1+y2",
|
||||
"(a+b)*(c-d)",
|
||||
"func()",
|
||||
"func(x,y+2)",
|
||||
"a*(b+c)-d/e",
|
||||
"f(g(x),h(y,z))",
|
||||
"x + 10",
|
||||
"x1 + y2",
|
||||
"(a + b) * (c - d)",
|
||||
"func()",
|
||||
"func(x, y + 2)",
|
||||
"a * (b + c) - d / e",
|
||||
"f(g(x), h(y, z))",
|
||||
"123+456",
|
||||
"123*456*789-123/456+789*123",
|
||||
"123+456*789-123/456+789*123-456/789+123*456-789/123+456*789-123/456+789*123-456"
|
||||
};
|
||||
|
||||
std::vector<std::string> test_strings_fail = {
|
||||
"+",
|
||||
"/ 3x",
|
||||
"x + + y",
|
||||
"a * / b",
|
||||
"func(,)",
|
||||
"func(x y)",
|
||||
"(a + b",
|
||||
"x + y)",
|
||||
"a + b * (c - d",
|
||||
"42 +",
|
||||
"x +",
|
||||
"x + 10 +",
|
||||
"(a + b) * (c - d",
|
||||
"func(",
|
||||
"func(x, y + 2",
|
||||
"a * (b + c) - d /",
|
||||
"f(g(x), h(y, z)",
|
||||
"123+456*789-123/456+789*123-456/789+123*456-789/123+456*789-123/456+789*123-456/",
|
||||
};
|
||||
|
||||
// Passing strings
|
||||
for (const auto & test_string : passing_strings) {
|
||||
fprintf(stderr, " \"%s\" ", test_string.c_str());
|
||||
fflush(stderr);
|
||||
for (const auto & test_string : test_strings_pass) {
|
||||
auto decoded = decode_utf8(test_string, {});
|
||||
|
||||
bool matched = match_string(test_string, grammar);
|
||||
const auto & code_points = decoded.first;
|
||||
|
||||
if (!matched) {
|
||||
fprintf(stderr, "❌ (failed to match)\n");
|
||||
} else {
|
||||
fprintf(stdout, "✅︎\n");
|
||||
int pos = 0;
|
||||
for (auto it = code_points.begin(), end = code_points.end() - 1; it != end; ++it) {
|
||||
++pos;
|
||||
auto prev_stacks = grammar->stacks;
|
||||
llama_grammar_accept(grammar->rules, prev_stacks, *it, grammar->stacks);
|
||||
|
||||
// Expect that each code point will not cause the grammar to fail
|
||||
if (grammar->stacks.empty()) {
|
||||
fprintf(stdout, "Error at position %d\n", pos);
|
||||
fprintf(stderr, "Unexpected character '%s'\n", unicode_cpt_to_utf8(*it).c_str());
|
||||
fprintf(stderr, "Input string is %s:\n", test_string.c_str());
|
||||
}
|
||||
assert(!grammar->stacks.empty());
|
||||
}
|
||||
|
||||
assert(matched);
|
||||
bool completed_grammar = false;
|
||||
|
||||
for (const auto & stack : grammar->stacks) {
|
||||
if (stack.empty()) {
|
||||
completed_grammar = true;
|
||||
break;
|
||||
}
|
||||
}
|
||||
|
||||
assert(completed_grammar);
|
||||
|
||||
// Reset the grammar stacks
|
||||
grammar->stacks = original_stacks;
|
||||
}
|
||||
|
||||
fprintf(stderr, " 🟠 Invalid strings:\n");
|
||||
|
||||
// Failing strings
|
||||
for (const auto & test_string : failing_strings) {
|
||||
fprintf(stderr, " \"%s\" ", test_string.c_str());
|
||||
fflush(stderr);
|
||||
for (const auto & test_string : test_strings_fail) {
|
||||
auto decoded = decode_utf8(test_string, {});
|
||||
|
||||
bool matched = match_string(test_string, grammar);
|
||||
const auto & code_points = decoded.first;
|
||||
bool parse_failed = false;
|
||||
|
||||
if (matched) {
|
||||
fprintf(stderr, "❌ (incorrectly matched)\n");
|
||||
} else {
|
||||
fprintf(stdout, "✅︎\n");
|
||||
for (auto it = code_points.begin(), end = code_points.end() - 1; it != end; ++it) {
|
||||
auto prev_stacks = grammar->stacks;
|
||||
llama_grammar_accept(grammar->rules, prev_stacks, *it, grammar->stacks);
|
||||
if (grammar->stacks.empty()) {
|
||||
parse_failed = true;
|
||||
break;
|
||||
}
|
||||
assert(!grammar->stacks.empty());
|
||||
}
|
||||
assert(!matched);
|
||||
|
||||
bool completed_grammar = false;
|
||||
|
||||
for (const auto & stack : grammar->stacks) {
|
||||
if (stack.empty()) {
|
||||
completed_grammar = true;
|
||||
break;
|
||||
}
|
||||
}
|
||||
|
||||
// Ensure that the grammar is not completed, or that each string failed to match as-expected
|
||||
assert((!completed_grammar) || parse_failed);
|
||||
|
||||
// Reset the grammar stacks
|
||||
grammar->stacks = original_stacks;
|
||||
@@ -106,183 +201,7 @@ static void test_grammar(const std::string & test_desc, const std::string & gram
|
||||
llama_grammar_free(grammar);
|
||||
}
|
||||
|
||||
static void test_simple_grammar() {
|
||||
// Test case for a simple grammar
|
||||
test_grammar(
|
||||
"simple grammar",
|
||||
R"""(
|
||||
root ::= expr
|
||||
expr ::= term ("+" term)*
|
||||
term ::= number
|
||||
number ::= [0-9]+)""",
|
||||
// Passing strings
|
||||
{
|
||||
"42",
|
||||
"1+2+3+4+5",
|
||||
"123+456",
|
||||
},
|
||||
// Failing strings
|
||||
{
|
||||
"+",
|
||||
"/ 3",
|
||||
"1+2+3+4+5+",
|
||||
"12a45",
|
||||
}
|
||||
);
|
||||
}
|
||||
|
||||
static void test_complex_grammar() {
|
||||
// Test case for a more complex grammar, with both failure strings and success strings
|
||||
test_grammar(
|
||||
"medium complexity grammar",
|
||||
// Grammar
|
||||
R"""(
|
||||
root ::= expression
|
||||
expression ::= term ws (("+"|"-") ws term)*
|
||||
term ::= factor ws (("*"|"/") ws factor)*
|
||||
factor ::= number | variable | "(" expression ")" | function-call
|
||||
number ::= [0-9]+
|
||||
variable ::= [a-zA-Z_][a-zA-Z0-9_]*
|
||||
function-call ::= variable ws "(" (expression ("," ws expression)*)? ")"
|
||||
ws ::= [ \t\n\r]?)""",
|
||||
// Passing strings
|
||||
{
|
||||
"42",
|
||||
"1*2*3*4*5",
|
||||
"x",
|
||||
"x+10",
|
||||
"x1+y2",
|
||||
"(a+b)*(c-d)",
|
||||
"func()",
|
||||
"func(x,y+2)",
|
||||
"a*(b+c)-d/e",
|
||||
"f(g(x),h(y,z))",
|
||||
"x + 10",
|
||||
"x1 + y2",
|
||||
"(a + b) * (c - d)",
|
||||
"func()",
|
||||
"func(x, y + 2)",
|
||||
"a * (b + c) - d / e",
|
||||
"f(g(x), h(y, z))",
|
||||
"123+456",
|
||||
"123*456*789-123/456+789*123",
|
||||
"123+456*789-123/456+789*123-456/789+123*456-789/123+456*789-123/456+789*123-456"
|
||||
},
|
||||
// Failing strings
|
||||
{
|
||||
"+",
|
||||
"/ 3x",
|
||||
"x + + y",
|
||||
"a * / b",
|
||||
"func(,)",
|
||||
"func(x y)",
|
||||
"(a + b",
|
||||
"x + y)",
|
||||
"a + b * (c - d",
|
||||
"42 +",
|
||||
"x +",
|
||||
"x + 10 +",
|
||||
"(a + b) * (c - d",
|
||||
"func(",
|
||||
"func(x, y + 2",
|
||||
"a * (b + c) - d /",
|
||||
"f(g(x), h(y, z)",
|
||||
"123+456*789-123/456+789*123-456/789+123*456-789/123+456*789-123/456+789*123-456/",
|
||||
}
|
||||
);
|
||||
}
|
||||
|
||||
static void test_quantifiers() {
|
||||
// A collection of tests to exercise * + and ? quantifiers
|
||||
|
||||
test_grammar(
|
||||
"* quantifier",
|
||||
// Grammar
|
||||
R"""(root ::= "a"*)""",
|
||||
// Passing strings
|
||||
{
|
||||
"",
|
||||
"a",
|
||||
"aaaaa",
|
||||
"aaaaaaaaaaaaaaaaaa",
|
||||
"aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa"
|
||||
},
|
||||
// Failing strings
|
||||
{
|
||||
"b",
|
||||
"ab",
|
||||
"aab",
|
||||
"ba",
|
||||
"aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaab"
|
||||
}
|
||||
);
|
||||
test_grammar(
|
||||
"+ quantifier",
|
||||
// Grammar
|
||||
R"""(root ::= "a"+)""",
|
||||
// Passing strings
|
||||
{
|
||||
"a",
|
||||
"aaaaa",
|
||||
"aaaaaaaaaaaaaaaaaa",
|
||||
"aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa"
|
||||
},
|
||||
// Failing strings
|
||||
{
|
||||
"",
|
||||
"b",
|
||||
"ab",
|
||||
"aab",
|
||||
"ba",
|
||||
"aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaab"
|
||||
}
|
||||
);
|
||||
test_grammar(
|
||||
"? quantifier",
|
||||
// Grammar
|
||||
R"""(root ::= "a"?)""",
|
||||
// Passing strings
|
||||
{
|
||||
"",
|
||||
"a"
|
||||
},
|
||||
// Failing strings
|
||||
{
|
||||
"b",
|
||||
"ab",
|
||||
"aa",
|
||||
"ba",
|
||||
}
|
||||
);
|
||||
test_grammar(
|
||||
"mixed quantifiers",
|
||||
// Grammar
|
||||
R"""(
|
||||
root ::= cons+ vowel* cons? (vowel cons)*
|
||||
vowel ::= [aeiouy]
|
||||
cons ::= [bcdfghjklmnpqrstvwxyz]
|
||||
)""",
|
||||
// Passing strings
|
||||
{
|
||||
"yes",
|
||||
"no",
|
||||
"noyes",
|
||||
"crwth",
|
||||
"four",
|
||||
"bryyyy",
|
||||
},
|
||||
// Failing strings
|
||||
{
|
||||
"yess",
|
||||
"yesno",
|
||||
"forty",
|
||||
"catyyy",
|
||||
}
|
||||
);
|
||||
}
|
||||
|
||||
static void test_failure_missing_root() {
|
||||
fprintf(stderr, "⚫ Testing missing root node:\n");
|
||||
// Test case for a grammar that is missing a root rule
|
||||
const std::string grammar_str = R"""(rot ::= expr
|
||||
expr ::= term ("+" term)*
|
||||
@@ -296,37 +215,29 @@ number ::= [0-9]+)""";
|
||||
|
||||
// Ensure we do NOT have a root node
|
||||
assert(parsed_grammar.symbol_ids.find("root") == parsed_grammar.symbol_ids.end());
|
||||
fprintf(stderr, " ✅︎ Passed\n");
|
||||
}
|
||||
|
||||
static void test_failure_missing_reference() {
|
||||
fprintf(stderr, "⚫ Testing missing reference node:\n");
|
||||
|
||||
// Test case for a grammar that is missing a referenced rule
|
||||
const std::string grammar_str =
|
||||
R"""(root ::= expr
|
||||
const std::string grammar_str = R"""(root ::= expr
|
||||
expr ::= term ("+" term)*
|
||||
term ::= numero
|
||||
number ::= [0-9]+)""";
|
||||
|
||||
fprintf(stderr, " Expected error: ");
|
||||
fprintf(stderr, "Expected error: ");
|
||||
|
||||
grammar_parser::parse_state parsed_grammar = grammar_parser::parse(grammar_str.c_str());
|
||||
|
||||
// Ensure we did NOT parsed correctly
|
||||
assert(parsed_grammar.rules.empty());
|
||||
|
||||
fprintf(stderr, " End of expected error.\n");
|
||||
fprintf(stderr, " ✅︎ Passed\n");
|
||||
fprintf(stderr, "End of expected error. Test successful.\n");
|
||||
}
|
||||
|
||||
int main() {
|
||||
fprintf(stdout, "Running grammar integration tests...\n");
|
||||
test_simple_grammar();
|
||||
test_complex_grammar();
|
||||
test_quantifiers();
|
||||
test_failure_missing_root();
|
||||
test_failure_missing_reference();
|
||||
fprintf(stdout, "All tests passed.\n");
|
||||
return 0;
|
||||
}
|
||||
|
||||
Reference in New Issue
Block a user