mirror of
https://github.com/ggml-org/llama.cpp.git
synced 2026-06-21 21:27:37 +02:00
Compare commits
40 Commits
| Author | SHA1 | Date | |
|---|---|---|---|
| 7c082bc417 | |||
| bddfd2b113 | |||
| 0d135df48c | |||
| bf533823cd | |||
| 2f89acc2bc | |||
| bfa3219177 | |||
| d6d899580d | |||
| 8a118ee86c | |||
| d789527482 | |||
| 063d9c156e | |||
| c57607016a | |||
| 4a80943174 | |||
| 84de01a1f1 | |||
| 75f460ac28 | |||
| 8452824611 | |||
| e27f308597 | |||
| 67e9fd3b74 | |||
| 796f41bedc | |||
| 37a77fb057 | |||
| f4043fec01 | |||
| f449e05537 | |||
| 2b686a9120 | |||
| 4b48a53b6c | |||
| e475fa2b5f | |||
| 175147e8f6 | |||
| fabde3bf51 | |||
| 0d2d9ccbf6 | |||
| 8c2d6f6475 | |||
| 38724ab593 | |||
| e2e7a9b2d0 | |||
| b14e3fb90c | |||
| 159d093a43 | |||
| 5fd2dc2c41 | |||
| 1868af13ac | |||
| 5bd21b8555 | |||
| 80452d65b9 | |||
| 8141e730f1 | |||
| db52540f73 | |||
| 3a3edc9ac6 | |||
| 40f3aafc45 |
@@ -13,6 +13,20 @@ ARG APP_REVISION=N/A
|
||||
# BUILD STAGE
|
||||
# Compile all binary files and libraries
|
||||
# ==============================================================================
|
||||
ARG NODE_VERSION=24
|
||||
|
||||
FROM docker.io/node:$NODE_VERSION AS web
|
||||
|
||||
ARG APP_VERSION
|
||||
|
||||
WORKDIR /app/tools/ui
|
||||
|
||||
COPY tools/ui/package.json tools/ui/package-lock.json ./
|
||||
RUN npm ci
|
||||
|
||||
COPY tools/ui/ ./
|
||||
RUN LLAMA_BUILD_NUMBER="$APP_VERSION" npm run build
|
||||
|
||||
FROM ${CANN_BASE_IMAGE} AS build
|
||||
|
||||
# -- Install build dependencies --
|
||||
@@ -26,6 +40,8 @@ WORKDIR /app
|
||||
# -- Copy project files --
|
||||
COPY . .
|
||||
|
||||
COPY --from=web /app/tools/ui/dist tools/ui/dist
|
||||
|
||||
# -- Set CANN environment variables (required for compilation) --
|
||||
# Using ENV instead of `source` allows environment variables to persist across the entire image layer
|
||||
ENV ASCEND_TOOLKIT_HOME=/usr/local/Ascend/ascend-toolkit/latest
|
||||
|
||||
@@ -3,6 +3,20 @@ ARG BUILD_DATE=N/A
|
||||
ARG APP_VERSION=N/A
|
||||
ARG APP_REVISION=N/A
|
||||
|
||||
ARG NODE_VERSION=24
|
||||
|
||||
FROM docker.io/node:$NODE_VERSION AS web
|
||||
|
||||
ARG APP_VERSION
|
||||
|
||||
WORKDIR /app/tools/ui
|
||||
|
||||
COPY tools/ui/package.json tools/ui/package-lock.json ./
|
||||
RUN npm ci
|
||||
|
||||
COPY tools/ui/ ./
|
||||
RUN LLAMA_BUILD_NUMBER="$APP_VERSION" npm run build
|
||||
|
||||
FROM docker.io/ubuntu:$UBUNTU_VERSION AS build
|
||||
|
||||
ARG TARGETARCH
|
||||
@@ -16,6 +30,8 @@ WORKDIR /app
|
||||
|
||||
COPY . .
|
||||
|
||||
COPY --from=web /app/tools/ui/dist tools/ui/dist
|
||||
|
||||
RUN if [ "$TARGETARCH" = "amd64" ] || [ "$TARGETARCH" = "arm64" ]; then \
|
||||
cmake -S . -B build -DCMAKE_BUILD_TYPE=Release -DGGML_NATIVE=OFF -DLLAMA_BUILD_TESTS=OFF -DGGML_BACKEND_DL=ON -DGGML_CPU_ALL_VARIANTS=ON; \
|
||||
else \
|
||||
|
||||
@@ -11,6 +11,20 @@ ARG BUILD_DATE=N/A
|
||||
ARG APP_VERSION=N/A
|
||||
ARG APP_REVISION=N/A
|
||||
|
||||
ARG NODE_VERSION=24
|
||||
|
||||
FROM docker.io/node:$NODE_VERSION AS web
|
||||
|
||||
ARG APP_VERSION
|
||||
|
||||
WORKDIR /app/tools/ui
|
||||
|
||||
COPY tools/ui/package.json tools/ui/package-lock.json ./
|
||||
RUN npm ci
|
||||
|
||||
COPY tools/ui/ ./
|
||||
RUN LLAMA_BUILD_NUMBER="$APP_VERSION" npm run build
|
||||
|
||||
FROM ${BASE_CUDA_DEV_CONTAINER} AS build
|
||||
|
||||
ARG GCC_VERSION
|
||||
@@ -26,6 +40,8 @@ WORKDIR /app
|
||||
|
||||
COPY . .
|
||||
|
||||
COPY --from=web /app/tools/ui/dist tools/ui/dist
|
||||
|
||||
RUN if [ "${CUDA_DOCKER_ARCH}" != "default" ]; then \
|
||||
export CMAKE_ARGS="-DCMAKE_CUDA_ARCHITECTURES=${CUDA_DOCKER_ARCH}"; \
|
||||
fi && \
|
||||
|
||||
@@ -5,6 +5,20 @@ ARG APP_REVISION=N/A
|
||||
|
||||
## Build Image
|
||||
|
||||
ARG NODE_VERSION=24
|
||||
|
||||
FROM docker.io/node:$NODE_VERSION AS web
|
||||
|
||||
ARG APP_VERSION
|
||||
|
||||
WORKDIR /app/tools/ui
|
||||
|
||||
COPY tools/ui/package.json tools/ui/package-lock.json ./
|
||||
RUN npm ci
|
||||
|
||||
COPY tools/ui/ ./
|
||||
RUN LLAMA_BUILD_NUMBER="$APP_VERSION" npm run build
|
||||
|
||||
FROM docker.io/intel/deep-learning-essentials:$ONEAPI_VERSION AS build
|
||||
|
||||
ARG GGML_SYCL_F16=ON
|
||||
@@ -22,6 +36,8 @@ WORKDIR /app
|
||||
|
||||
COPY . .
|
||||
|
||||
COPY --from=web /app/tools/ui/dist tools/ui/dist
|
||||
|
||||
RUN if [ "${GGML_SYCL_F16}" = "ON" ]; then \
|
||||
echo "GGML_SYCL_F16 is set" \
|
||||
&& export OPT_SYCL_F16="-DGGML_SYCL_F16=ON" \
|
||||
|
||||
@@ -10,6 +10,20 @@ ARG BUILD_DATE=N/A
|
||||
ARG APP_VERSION=N/A
|
||||
ARG APP_REVISION=N/A
|
||||
|
||||
ARG NODE_VERSION=24
|
||||
|
||||
FROM docker.io/node:$NODE_VERSION AS web
|
||||
|
||||
ARG APP_VERSION
|
||||
|
||||
WORKDIR /app/tools/ui
|
||||
|
||||
COPY tools/ui/package.json tools/ui/package-lock.json ./
|
||||
RUN npm ci
|
||||
|
||||
COPY tools/ui/ ./
|
||||
RUN LLAMA_BUILD_NUMBER="$APP_VERSION" npm run build
|
||||
|
||||
FROM ${BASE_MUSA_DEV_CONTAINER} AS build
|
||||
|
||||
# MUSA architecture to build for (defaults to all supported archs)
|
||||
@@ -29,6 +43,8 @@ WORKDIR /app
|
||||
|
||||
COPY . .
|
||||
|
||||
COPY --from=web /app/tools/ui/dist tools/ui/dist
|
||||
|
||||
RUN if [ "${MUSA_DOCKER_ARCH}" != "default" ]; then \
|
||||
export CMAKE_ARGS="-DMUSA_ARCHITECTURES=${MUSA_DOCKER_ARCH}"; \
|
||||
fi && \
|
||||
|
||||
@@ -22,6 +22,20 @@ ARG BUILD_DATE=N/A
|
||||
ARG APP_VERSION=N/A
|
||||
ARG APP_REVISION=N/A
|
||||
|
||||
ARG NODE_VERSION=24
|
||||
|
||||
FROM docker.io/node:$NODE_VERSION AS web
|
||||
|
||||
ARG APP_VERSION
|
||||
|
||||
WORKDIR /app/tools/ui
|
||||
|
||||
COPY tools/ui/package.json tools/ui/package-lock.json ./
|
||||
RUN npm ci
|
||||
|
||||
COPY tools/ui/ ./
|
||||
RUN LLAMA_BUILD_NUMBER="$APP_VERSION" npm run build
|
||||
|
||||
## Build Image
|
||||
FROM docker.io/ubuntu:${UBUNTU_VERSION} AS build
|
||||
|
||||
@@ -69,6 +83,8 @@ WORKDIR /app
|
||||
|
||||
COPY . .
|
||||
|
||||
COPY --from=web /app/tools/ui/dist tools/ui/dist
|
||||
|
||||
# Build Stage
|
||||
RUN bash -c "source ${OpenVINO_DIR}/setupvars.sh && \
|
||||
cmake -B build/ReleaseOV -G Ninja \
|
||||
|
||||
@@ -11,6 +11,20 @@ ARG BUILD_DATE=N/A
|
||||
ARG APP_VERSION=N/A
|
||||
ARG APP_REVISION=N/A
|
||||
|
||||
ARG NODE_VERSION=24
|
||||
|
||||
FROM docker.io/node:$NODE_VERSION AS web
|
||||
|
||||
ARG APP_VERSION
|
||||
|
||||
WORKDIR /app/tools/ui
|
||||
|
||||
COPY tools/ui/package.json tools/ui/package-lock.json ./
|
||||
RUN npm ci
|
||||
|
||||
COPY tools/ui/ ./
|
||||
RUN LLAMA_BUILD_NUMBER="$APP_VERSION" npm run build
|
||||
|
||||
### Build image
|
||||
FROM ${BASE_ROCM_DEV_CONTAINER} AS build
|
||||
|
||||
@@ -38,6 +52,8 @@ WORKDIR /app
|
||||
|
||||
COPY . .
|
||||
|
||||
COPY --from=web /app/tools/ui/dist tools/ui/dist
|
||||
|
||||
RUN HIPCXX="$(hipconfig -l)/clang" HIP_PATH="$(hipconfig -R)" \
|
||||
cmake -S . -B build \
|
||||
-DGGML_HIP=ON \
|
||||
|
||||
@@ -3,6 +3,20 @@ ARG BUILD_DATE=N/A
|
||||
ARG APP_VERSION=N/A
|
||||
ARG APP_REVISION=N/A
|
||||
|
||||
ARG NODE_VERSION=24
|
||||
|
||||
FROM docker.io/node:$NODE_VERSION AS web
|
||||
|
||||
ARG APP_VERSION
|
||||
|
||||
WORKDIR /app/tools/ui
|
||||
|
||||
COPY tools/ui/package.json tools/ui/package-lock.json ./
|
||||
RUN npm ci
|
||||
|
||||
COPY tools/ui/ ./
|
||||
RUN LLAMA_BUILD_NUMBER="$APP_VERSION" npm run build
|
||||
|
||||
FROM docker.io/ubuntu:$UBUNTU_VERSION AS build
|
||||
|
||||
# Install build tools
|
||||
@@ -17,6 +31,8 @@ WORKDIR /app
|
||||
|
||||
COPY . .
|
||||
|
||||
COPY --from=web /app/tools/ui/dist tools/ui/dist
|
||||
|
||||
RUN cmake -B build -DGGML_NATIVE=OFF -DGGML_VULKAN=ON -DLLAMA_BUILD_TESTS=OFF -DGGML_BACKEND_DL=ON -DGGML_CPU_ALL_VARIANTS=ON && \
|
||||
cmake --build build --config Release -j$(nproc)
|
||||
|
||||
|
||||
@@ -3,6 +3,20 @@ ARG BUILD_DATE=N/A
|
||||
ARG APP_VERSION=N/A
|
||||
ARG APP_REVISION=N/A
|
||||
|
||||
ARG NODE_VERSION=24
|
||||
|
||||
FROM docker.io/node:$NODE_VERSION AS web
|
||||
|
||||
ARG APP_VERSION
|
||||
|
||||
WORKDIR /app/tools/ui
|
||||
|
||||
COPY tools/ui/package.json tools/ui/package-lock.json ./
|
||||
RUN npm ci
|
||||
|
||||
COPY tools/ui/ ./
|
||||
RUN LLAMA_BUILD_NUMBER="$APP_VERSION" npm run build
|
||||
|
||||
FROM docker.io/ubuntu:$UBUNTU_VERSION AS build
|
||||
|
||||
RUN apt-get update && \
|
||||
@@ -14,6 +28,8 @@ WORKDIR /app
|
||||
|
||||
COPY . .
|
||||
|
||||
COPY --from=web /app/tools/ui/dist tools/ui/dist
|
||||
|
||||
RUN cmake -S . -B build -DCMAKE_BUILD_TYPE=Release -DGGML_NATIVE=OFF -DLLAMA_BUILD_TESTS=OFF -DGGML_BACKEND_DL=ON -DGGML_CPU_ALL_VARIANTS=ON -DGGML_ZENDNN=ON && \
|
||||
cmake --build build -j $(nproc)
|
||||
|
||||
|
||||
@@ -10,6 +10,8 @@
|
||||
|
||||
build*/
|
||||
|
||||
tools/ui/node_modules/
|
||||
|
||||
models/*
|
||||
|
||||
/llama-cli
|
||||
|
||||
@@ -58,6 +58,13 @@ jobs:
|
||||
git tag ${{ steps.srctag.outputs.name }} || exit 0
|
||||
git push origin ${{ steps.srctag.outputs.name }} || exit 0
|
||||
|
||||
build_ui:
|
||||
name: Build UI
|
||||
needs: create_tag
|
||||
uses: ./.github/workflows/ui-build.yml
|
||||
with:
|
||||
hf_ui_version: ${{ needs.create_tag.outputs.source_tag }}
|
||||
|
||||
prepare_matrices:
|
||||
name: Prepare Docker matrices
|
||||
runs-on: ubuntu-24.04
|
||||
@@ -79,7 +86,7 @@ jobs:
|
||||
[
|
||||
{ "tag": "cpu", "dockerfile": ".devops/cpu.Dockerfile", "platforms": "linux/amd64", "full": true, "light": true, "server": true, "free_disk_space": false, "runs_on": "ubuntu-24.04" },
|
||||
{ "tag": "cpu", "dockerfile": ".devops/cpu.Dockerfile", "platforms": "linux/arm64", "full": true, "light": true, "server": true, "free_disk_space": false, "runs_on": "ubuntu-24.04-arm" },
|
||||
{ "tag": "cpu", "dockerfile": ".devops/s390x.Dockerfile", "platforms": "linux/s390x", "full": true, "light": true, "server": true, "free_disk_space": false, "runs_on": "ubuntu-24.04-s390x" },
|
||||
{ "tag": "cpu", "dockerfile": ".devops/s390x.Dockerfile", "platforms": "linux/s390x", "full": true, "light": true, "server": true, "free_disk_space": false, "runs_on": "ubuntu-24.04-s390x", "prebuilt_ui": true },
|
||||
{ "tag": "cuda cuda12", "dockerfile": ".devops/cuda.Dockerfile", "cuda_version": "12.8.1", "platforms": "linux/amd64", "full": true, "light": true, "server": true, "free_disk_space": true, "runs_on": "ubuntu-24.04" },
|
||||
{ "tag": "cuda cuda12", "dockerfile": ".devops/cuda.Dockerfile", "cuda_version": "12.8.1", "platforms": "linux/arm64", "full": true, "light": true, "server": true, "free_disk_space": true, "runs_on": "ubuntu-24.04-arm" },
|
||||
{ "tag": "cuda13", "dockerfile": ".devops/cuda.Dockerfile", "cuda_version": "13.3.0", "platforms": "linux/amd64", "full": true, "light": true, "server": true, "free_disk_space": true, "runs_on": "ubuntu-24.04" },
|
||||
@@ -135,7 +142,7 @@ jobs:
|
||||
|
||||
push_to_registry:
|
||||
name: Push Docker image to Docker Registry
|
||||
needs: [prepare_matrices, create_tag]
|
||||
needs: [prepare_matrices, create_tag, build_ui]
|
||||
|
||||
runs-on: ${{ matrix.config.runs_on }}
|
||||
strategy:
|
||||
@@ -150,6 +157,13 @@ jobs:
|
||||
fetch-depth: 0
|
||||
ref: ${{ needs.create_tag.outputs.source_tag }}
|
||||
|
||||
- name: Download prebuilt UI
|
||||
if: ${{ matrix.config.prebuilt_ui == true }}
|
||||
uses: actions/download-artifact@3e5f45b2cfb9172054b4087a40e8e0b5a5461e7c # v8
|
||||
with:
|
||||
name: ui-build
|
||||
path: tools/ui/dist
|
||||
|
||||
- name: Set up QEMU
|
||||
if: ${{ contains(matrix.config.platforms, 'linux/amd64') }}
|
||||
uses: docker/setup-qemu-action@ce360397dd3f832beb865e1373c09c0e9f86d70a # v4
|
||||
|
||||
@@ -1627,6 +1627,7 @@ jobs:
|
||||
**Windows:**
|
||||
- [Windows x64 (CPU)](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-bin-win-cpu-x64.zip)
|
||||
- [Windows arm64 (CPU)](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-bin-win-cpu-arm64.zip)
|
||||
- [Windows arm64 (OpenCL Adreno)](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-bin-win-opencl-adreno-arm64.zip)
|
||||
- [Windows x64 (CUDA 12)](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-bin-win-cuda-12.4-x64.zip) - [CUDA 12.4 DLLs](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/cudart-llama-bin-win-cuda-12.4-x64.zip)
|
||||
- [Windows x64 (CUDA 13)](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-bin-win-cuda-13.3-x64.zip) - [CUDA 13.3 DLLs](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/cudart-llama-bin-win-cuda-13.3-x64.zip)
|
||||
- [Windows x64 (Vulkan)](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-bin-win-vulkan-x64.zip)
|
||||
|
||||
@@ -25,13 +25,3 @@ Commits:
|
||||
- Do not explicitly set the git author in commits - rely on the default git config
|
||||
- Always use `--no-gpg-sign` when committing
|
||||
- Never `git push` without explicit confirmation from the user
|
||||
|
||||
Resources (read on demand):
|
||||
- [CONTRIBUTING.md](CONTRIBUTING.md)
|
||||
- [Build documentation](docs/build.md)
|
||||
- [Server usage documentation](tools/server/README.md)
|
||||
- [Server development documentation](tools/server/README-dev.md)
|
||||
- [PEG parser](docs/development/parsing.md)
|
||||
- [Auto parser](docs/autoparser.md)
|
||||
- [Jinja engine](common/jinja/README.md)
|
||||
- [PR template](.github/pull_request_template.md)
|
||||
|
||||
+57
-55
@@ -17,6 +17,7 @@
|
||||
# define NOMINMAX
|
||||
#endif
|
||||
#include <windows.h>
|
||||
#include <shellapi.h>
|
||||
#endif
|
||||
|
||||
#define JSON_ASSERT GGML_ASSERT
|
||||
@@ -302,7 +303,6 @@ static handle_model_result common_params_handle_model(struct common_params_model
|
||||
|
||||
if (!model.docker_repo.empty()) {
|
||||
model.path = common_docker_resolve_model(model.docker_repo);
|
||||
model.name = model.docker_repo;
|
||||
} else if (!model.hf_repo.empty()) {
|
||||
// If -m was used with -hf, treat the model "path" as the hf_file to download
|
||||
if (model.hf_file.empty() && !model.path.empty()) {
|
||||
@@ -322,7 +322,6 @@ static handle_model_result common_params_handle_model(struct common_params_model
|
||||
throw std::runtime_error("failed to download model from Hugging Face");
|
||||
}
|
||||
|
||||
model.name = model.hf_repo;
|
||||
model.path = download_result.model_path;
|
||||
|
||||
if (!download_result.mmproj_path.empty()) {
|
||||
@@ -893,7 +892,44 @@ bool common_params_to_map(int argc, char ** argv, llama_example ex, std::map<com
|
||||
return true;
|
||||
}
|
||||
|
||||
#ifdef _WIN32
|
||||
struct utf8_argv {
|
||||
std::vector<std::string> buf;
|
||||
std::vector<char*> ptrs;
|
||||
};
|
||||
|
||||
static utf8_argv make_utf8_argv() {
|
||||
utf8_argv out;
|
||||
int wargc = 0;
|
||||
LPWSTR* wargv = CommandLineToArgvW(GetCommandLineW(), &wargc);
|
||||
if (!wargv) return out;
|
||||
|
||||
out.buf.reserve(wargc);
|
||||
for (int i = 0; i < wargc; ++i) {
|
||||
int n = WideCharToMultiByte(CP_UTF8, WC_ERR_INVALID_CHARS, wargv[i], -1, nullptr, 0, nullptr, nullptr);
|
||||
if (n <= 0) { out.buf.emplace_back(); continue; }
|
||||
auto& s = out.buf.emplace_back();
|
||||
s.resize(static_cast<size_t>(n - 1));
|
||||
(void)WideCharToMultiByte(CP_UTF8, 0, wargv[i], -1, s.data(), n, nullptr, nullptr);
|
||||
}
|
||||
LocalFree(wargv);
|
||||
|
||||
out.ptrs.reserve(out.buf.size() + 1);
|
||||
for (auto& s : out.buf) out.ptrs.push_back(s.data());
|
||||
out.ptrs.push_back(nullptr);
|
||||
return out;
|
||||
}
|
||||
#endif
|
||||
|
||||
bool common_params_parse(int argc, char ** argv, common_params & params, llama_example ex, void(*print_usage)(int, char **)) {
|
||||
#ifdef _WIN32
|
||||
auto utf8 = make_utf8_argv();
|
||||
// repair argv only when it matches the process command line
|
||||
if (static_cast<int>(utf8.buf.size()) == argc) {
|
||||
argv = utf8.ptrs.data();
|
||||
}
|
||||
#endif
|
||||
|
||||
auto ctx_arg = common_params_parser_init(params, ex, print_usage);
|
||||
const common_params params_org = ctx_arg.params; // the example can modify the default params
|
||||
|
||||
@@ -2830,62 +2866,26 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
|
||||
params.api_prefix = value;
|
||||
}
|
||||
).set_examples({LLAMA_EXAMPLE_SERVER}).set_env("LLAMA_ARG_API_PREFIX"));
|
||||
// Deprecated: use --ui-config instead (kept for backward compat)
|
||||
add_opt(common_arg(
|
||||
{"--webui-config"}, "JSON",
|
||||
"[DEPRECATED: use --ui-config] JSON that provides default WebUI settings (overrides WebUI defaults)",
|
||||
[](common_params & params, const std::string & value) {
|
||||
params.ui_config_json = value;
|
||||
params.webui_config_json = value;
|
||||
}
|
||||
).set_examples({LLAMA_EXAMPLE_SERVER}).set_env("LLAMA_ARG_WEBUI_CONFIG"));
|
||||
|
||||
add_opt(common_arg(
|
||||
{"--ui-config"}, "JSON",
|
||||
{"--ui-config", "--webui-config"}, "JSON",
|
||||
"JSON that provides default UI settings (overrides UI defaults)",
|
||||
[](common_params & params, const std::string & value) {
|
||||
params.ui_config_json = value;
|
||||
params.webui_config_json = value;
|
||||
}
|
||||
).set_examples({LLAMA_EXAMPLE_SERVER}).set_env("LLAMA_ARG_UI_CONFIG"));
|
||||
|
||||
// Deprecated: use --ui-config-file instead (kept for backward compat)
|
||||
add_opt(common_arg(
|
||||
{"--webui-config-file"}, "PATH",
|
||||
"[DEPRECATED: use --ui-config-file] JSON file that provides default WebUI settings (overrides WebUI defaults)",
|
||||
[](common_params & params, const std::string & value) {
|
||||
params.ui_config_json = read_file(value);
|
||||
params.webui_config_json = params.ui_config_json;
|
||||
}
|
||||
).set_examples({LLAMA_EXAMPLE_SERVER}).set_env("LLAMA_ARG_WEBUI_CONFIG_FILE"));
|
||||
|
||||
add_opt(common_arg(
|
||||
{"--ui-config-file"}, "PATH",
|
||||
{"--ui-config-file", "--webui-config-file"}, "PATH",
|
||||
"JSON file that provides default UI settings (overrides UI defaults)",
|
||||
[](common_params & params, const std::string & value) {
|
||||
params.ui_config_json = read_file(value);
|
||||
params.webui_config_json = params.ui_config_json;
|
||||
}
|
||||
).set_examples({LLAMA_EXAMPLE_SERVER}).set_env("LLAMA_ARG_UI_CONFIG_FILE"));
|
||||
|
||||
// Deprecated: use --ui-mcp-proxy instead (kept for backward compat)
|
||||
add_opt(common_arg(
|
||||
{"--webui-mcp-proxy"},
|
||||
{"--no-webui-mcp-proxy"},
|
||||
"[DEPRECATED: use --ui-mcp-proxy/--no-ui-mcp-proxy] experimental: whether to enable MCP CORS proxy",
|
||||
[](common_params & params, bool value) {
|
||||
params.ui_mcp_proxy = value;
|
||||
params.webui_mcp_proxy = value;
|
||||
}
|
||||
).set_examples({LLAMA_EXAMPLE_SERVER}).set_env("LLAMA_ARG_WEBUI_MCP_PROXY"));
|
||||
|
||||
add_opt(common_arg(
|
||||
{"--ui-mcp-proxy"},
|
||||
{"--no-ui-mcp-proxy"},
|
||||
{"--ui-mcp-proxy", "--webui-mcp-proxy"},
|
||||
{"--no-ui-mcp-proxy", "--no-webui-mcp-proxy"},
|
||||
"experimental: whether to enable MCP CORS proxy - do not enable in untrusted environments (default: disabled)",
|
||||
[](common_params & params, bool value) {
|
||||
params.ui_mcp_proxy = value;
|
||||
params.webui_mcp_proxy = value;
|
||||
}
|
||||
).set_examples({LLAMA_EXAMPLE_SERVER}).set_env("LLAMA_ARG_UI_MCP_PROXY"));
|
||||
add_opt(common_arg(
|
||||
@@ -2897,24 +2897,26 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
|
||||
params.server_tools = parse_csv_row(value);
|
||||
}
|
||||
).set_examples({LLAMA_EXAMPLE_SERVER}).set_env("LLAMA_ARG_TOOLS"));
|
||||
// Deprecated: use --ui/--no-ui instead (kept for backward compat)
|
||||
add_opt(common_arg(
|
||||
{"--webui"},
|
||||
{"--no-webui"},
|
||||
"[DEPRECATED: use --ui/--no-ui] whether to enable the Web UI",
|
||||
{"-ag", "--agent"},
|
||||
{"-no-ag", "--no-agent"},
|
||||
"whether to enable CORS proxy and all built-in tools - do not enable in untrusted environments (default: disabled)",
|
||||
[](common_params & params, bool value) {
|
||||
params.ui = value;
|
||||
params.webui = value;
|
||||
if (value) {
|
||||
params.server_tools = {"all"};
|
||||
params.ui_mcp_proxy = true;
|
||||
} else {
|
||||
params.server_tools.clear();
|
||||
params.ui_mcp_proxy = false;
|
||||
}
|
||||
}
|
||||
).set_examples({LLAMA_EXAMPLE_SERVER}).set_env("LLAMA_ARG_WEBUI"));
|
||||
|
||||
).set_examples({LLAMA_EXAMPLE_SERVER}).set_env("LLAMA_ARG_AGENT"));
|
||||
add_opt(common_arg(
|
||||
{"--ui"},
|
||||
{"--no-ui"},
|
||||
{"--ui", "--webui"},
|
||||
{"--no-ui", "--no-webui"},
|
||||
string_format("whether to enable the Web UI (default: %s)", params.ui ? "enabled" : "disabled"),
|
||||
[](common_params & params, bool value) {
|
||||
params.ui = value;
|
||||
params.webui = value;
|
||||
}
|
||||
).set_examples({LLAMA_EXAMPLE_SERVER}).set_env("LLAMA_ARG_UI"));
|
||||
add_opt(common_arg(
|
||||
@@ -2945,7 +2947,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
|
||||
).set_examples({LLAMA_EXAMPLE_SERVER}).set_env("LLAMA_API_KEY"));
|
||||
add_opt(common_arg(
|
||||
{"--api-key-file"}, "FNAME",
|
||||
"path to file containing API keys (default: none)",
|
||||
"path to file containing API keys, one per line; lines starting with a hash are treated as comments (default: none)",
|
||||
[](common_params & params, const std::string & value) {
|
||||
std::ifstream key_file(value);
|
||||
if (!key_file) {
|
||||
@@ -2953,7 +2955,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
|
||||
}
|
||||
std::string key;
|
||||
while (std::getline(key_file, key)) {
|
||||
if (!key.empty()) {
|
||||
if (!key.empty() && key[0] != '#') {
|
||||
params.api_keys.push_back(key);
|
||||
}
|
||||
}
|
||||
|
||||
+15
-1
@@ -1074,6 +1074,18 @@ std::vector<common_file_info> fs_list(const std::string & path, bool include_dir
|
||||
return files;
|
||||
}
|
||||
|
||||
std::ifstream fs_open_ifstream(const std::string & fname, std::ios_base::openmode mode) {
|
||||
#ifdef _WIN32
|
||||
int wlen = MultiByteToWideChar(CP_UTF8, 0, fname.c_str(), -1, NULL, 0);
|
||||
if (!wlen) { return std::ifstream(); }
|
||||
std::vector<wchar_t> wfname(wlen);
|
||||
(void)MultiByteToWideChar(CP_UTF8, 0, fname.c_str(), -1, wfname.data(), wlen);
|
||||
return std::ifstream(wfname.data(), mode);
|
||||
#else
|
||||
return std::ifstream(fname, mode);
|
||||
#endif
|
||||
}
|
||||
|
||||
//
|
||||
// TTY utils
|
||||
//
|
||||
@@ -2034,7 +2046,7 @@ bool common_prompt_batch_decode(
|
||||
}
|
||||
|
||||
size_t common_prompt_checkpoint::size() const {
|
||||
return data_tgt.size() + data_dft.size();
|
||||
return data_tgt.size() + data_dft.size() + data_spec.size();
|
||||
}
|
||||
|
||||
bool common_prompt_checkpoint::empty() const {
|
||||
@@ -2049,6 +2061,7 @@ void common_prompt_checkpoint::clear() {
|
||||
|
||||
data_tgt.clear();
|
||||
data_dft.clear();
|
||||
data_spec.clear();
|
||||
}
|
||||
|
||||
void common_prompt_checkpoint::update_pos(
|
||||
@@ -2138,4 +2151,5 @@ void common_prompt_checkpoint::clear_tgt() {
|
||||
|
||||
void common_prompt_checkpoint::clear_dft() {
|
||||
data_dft.clear();
|
||||
data_spec.clear();
|
||||
}
|
||||
|
||||
+18
-8
@@ -295,7 +295,16 @@ struct common_params_model {
|
||||
std::string hf_repo = ""; // HF repo // NOLINT
|
||||
std::string hf_file = ""; // HF file // NOLINT
|
||||
std::string docker_repo = ""; // Docker repo // NOLINT
|
||||
std::string name = ""; // in format <user>/<model>[:<tag>] (tag is optional) // NOLINT
|
||||
|
||||
std::string get_name() {
|
||||
if (!hf_repo.empty()) {
|
||||
return hf_repo;
|
||||
}
|
||||
if (!docker_repo.empty()) {
|
||||
return docker_repo;
|
||||
}
|
||||
return path;
|
||||
}
|
||||
};
|
||||
|
||||
// draft-model-based speculative decoding parameters
|
||||
@@ -363,7 +372,7 @@ struct common_params_speculative {
|
||||
|
||||
uint32_t need_n_rs_seq() const {
|
||||
bool needs_rs_seq = std::any_of(types.begin(), types.end(), [&](auto t) {
|
||||
return t == COMMON_SPECULATIVE_TYPE_DRAFT_MTP;
|
||||
return t == COMMON_SPECULATIVE_TYPE_DRAFT_MTP || t == COMMON_SPECULATIVE_TYPE_DRAFT_EAGLE3;
|
||||
});
|
||||
|
||||
return needs_rs_seq ? draft.n_max : 0u;
|
||||
@@ -624,12 +633,6 @@ struct common_params {
|
||||
|
||||
// UI configs
|
||||
bool ui = true;
|
||||
|
||||
// Deprecated: use ui, ui_mcp_proxy, ui_config_json instead
|
||||
bool webui = ui;
|
||||
bool webui_mcp_proxy = false;
|
||||
std::string webui_config_json;
|
||||
|
||||
bool ui_mcp_proxy = false;
|
||||
std::string ui_config_json;
|
||||
|
||||
@@ -848,6 +851,9 @@ struct common_file_info {
|
||||
};
|
||||
std::vector<common_file_info> fs_list(const std::string & path, bool include_directories);
|
||||
|
||||
// fs open, also handle UTF8 on Windows
|
||||
std::ifstream fs_open_ifstream(const std::string & fname, std::ios_base::openmode mode);
|
||||
|
||||
//
|
||||
// TTY utils
|
||||
//
|
||||
@@ -1065,6 +1071,10 @@ struct common_prompt_checkpoint {
|
||||
std::vector<uint8_t> data_tgt;
|
||||
std::vector<uint8_t> data_dft;
|
||||
|
||||
// (optional) speculative-decoding implementation state stashed with the checkpoint
|
||||
// (e.g. eagle3's deferred-boundary g_embd row)
|
||||
std::vector<uint8_t> data_spec;
|
||||
|
||||
size_t size() const;
|
||||
|
||||
bool empty() const;
|
||||
|
||||
+89
-46
@@ -686,59 +686,62 @@ value set_statement::execute_impl(context & ctx) {
|
||||
return mk_val<value_undefined>();
|
||||
}
|
||||
|
||||
static inline void bind_parameters(const std::string & name, const statements & this_args, const func_args & args, context & ctx) {
|
||||
const size_t expected_count = this_args.size();
|
||||
const size_t input_count = args.count();
|
||||
|
||||
JJ_DEBUG("Invoking '%s' with %zu input arguments (expected %zu)", name.c_str(), input_count, expected_count);
|
||||
for (size_t i = 0; i < expected_count; ++i) {
|
||||
if (i < input_count) {
|
||||
if (is_stmt<identifier>(this_args[i])) {
|
||||
// normal parameter
|
||||
std::string param_name = cast_stmt<identifier>(this_args[i])->val;
|
||||
value param_value = args.get_kwarg_or_pos(param_name, i);
|
||||
JJ_DEBUG(" Binding parameter '%s' to argument of type %s", param_name.c_str(), param_value->type().c_str());
|
||||
ctx.set_val(param_name, param_value);
|
||||
} else if (is_stmt<keyword_argument_expression>(this_args[i])) {
|
||||
// default argument used as normal parameter
|
||||
auto kwarg = cast_stmt<keyword_argument_expression>(this_args[i]);
|
||||
if (!is_stmt<identifier>(kwarg->key)) {
|
||||
throw std::runtime_error("Keyword argument key must be an identifier in '" + name + "'");
|
||||
}
|
||||
std::string param_name = cast_stmt<identifier>(kwarg->key)->val;
|
||||
value param_value = args.get_kwarg_or_pos(param_name, i);
|
||||
JJ_DEBUG(" Binding parameter '%s' to argument of type %s", param_name.c_str(), param_value->type().c_str());
|
||||
ctx.set_val(param_name, param_value);
|
||||
} else {
|
||||
throw std::runtime_error("Invalid parameter type in '" + name + "'");
|
||||
}
|
||||
} else {
|
||||
auto & default_arg = this_args[i];
|
||||
if (is_stmt<keyword_argument_expression>(default_arg)) {
|
||||
auto kwarg = cast_stmt<keyword_argument_expression>(default_arg);
|
||||
if (!is_stmt<identifier>(kwarg->key)) {
|
||||
throw std::runtime_error("Keyword argument key must be an identifier in '" + name + "'");
|
||||
}
|
||||
std::string param_name = cast_stmt<identifier>(kwarg->key)->val;
|
||||
JJ_DEBUG(" Binding parameter '%s' to default argument of type %s", param_name.c_str(), kwarg->val->type().c_str());
|
||||
ctx.set_val(param_name, kwarg->val->execute(args.ctx));
|
||||
} else {
|
||||
throw std::runtime_error("Not enough arguments provided to '" + name + "'");
|
||||
}
|
||||
//std::string param_name = cast_stmt<identifier>(default_args[i])->val;
|
||||
//JJ_DEBUG(" Binding parameter '%s' to default", param_name.c_str());
|
||||
//ctx.var[param_name] = default_args[i]->execute(ctx);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
value macro_statement::execute_impl(context & ctx) {
|
||||
if (!is_stmt<identifier>(this->name)) {
|
||||
throw std::runtime_error("Macro name must be an identifier");
|
||||
}
|
||||
std::string name = cast_stmt<identifier>(this->name)->val;
|
||||
|
||||
const func_handler func = [this, name, &ctx](const func_args & args) -> value {
|
||||
size_t expected_count = this->args.size();
|
||||
size_t input_count = args.count();
|
||||
const func_handler func = [this, name](const func_args & args) -> value {
|
||||
context macro_ctx(args.ctx); // new scope for macro execution
|
||||
|
||||
JJ_DEBUG("Invoking macro '%s' with %zu input arguments (expected %zu)", name.c_str(), input_count, expected_count);
|
||||
context macro_ctx(ctx); // new scope for macro execution
|
||||
|
||||
// bind parameters
|
||||
for (size_t i = 0; i < expected_count; ++i) {
|
||||
if (i < input_count) {
|
||||
if (is_stmt<identifier>(this->args[i])) {
|
||||
// normal parameter
|
||||
std::string param_name = cast_stmt<identifier>(this->args[i])->val;
|
||||
value param_value = args.get_kwarg_or_pos(param_name, i);
|
||||
JJ_DEBUG(" Binding parameter '%s' to argument of type %s", param_name.c_str(), param_value->type().c_str());
|
||||
macro_ctx.set_val(param_name, param_value);
|
||||
} else if (is_stmt<keyword_argument_expression>(this->args[i])) {
|
||||
// default argument used as normal parameter
|
||||
auto kwarg = cast_stmt<keyword_argument_expression>(this->args[i]);
|
||||
if (!is_stmt<identifier>(kwarg->key)) {
|
||||
throw std::runtime_error("Keyword argument key must be an identifier in macro '" + name + "'");
|
||||
}
|
||||
std::string param_name = cast_stmt<identifier>(kwarg->key)->val;
|
||||
value param_value = args.get_kwarg_or_pos(param_name, i);
|
||||
JJ_DEBUG(" Binding parameter '%s' to argument of type %s", param_name.c_str(), param_value->type().c_str());
|
||||
macro_ctx.set_val(param_name, param_value);
|
||||
} else {
|
||||
throw std::runtime_error("Invalid parameter type in macro '" + name + "'");
|
||||
}
|
||||
} else {
|
||||
auto & default_arg = this->args[i];
|
||||
if (is_stmt<keyword_argument_expression>(default_arg)) {
|
||||
auto kwarg = cast_stmt<keyword_argument_expression>(default_arg);
|
||||
if (!is_stmt<identifier>(kwarg->key)) {
|
||||
throw std::runtime_error("Keyword argument key must be an identifier in macro '" + name + "'");
|
||||
}
|
||||
std::string param_name = cast_stmt<identifier>(kwarg->key)->val;
|
||||
JJ_DEBUG(" Binding parameter '%s' to default argument of type %s", param_name.c_str(), kwarg->val->type().c_str());
|
||||
macro_ctx.set_val(param_name, kwarg->val->execute(ctx));
|
||||
} else {
|
||||
throw std::runtime_error("Not enough arguments provided to macro '" + name + "'");
|
||||
}
|
||||
//std::string param_name = cast_stmt<identifier>(default_args[i])->val;
|
||||
//JJ_DEBUG(" Binding parameter '%s' to default", param_name.c_str());
|
||||
//macro_ctx.var[param_name] = default_args[i]->execute(ctx);
|
||||
}
|
||||
}
|
||||
bind_parameters(name, this->args, args, macro_ctx);
|
||||
|
||||
// execute macro body
|
||||
JJ_DEBUG("Executing macro '%s' body with %zu statements", name.c_str(), this->body.size());
|
||||
@@ -752,6 +755,46 @@ value macro_statement::execute_impl(context & ctx) {
|
||||
return mk_val<value_undefined>();
|
||||
}
|
||||
|
||||
value call_statement::execute_impl(context & ctx) {
|
||||
auto call_expr = cast_stmt<call_expression>(this->call);
|
||||
if (!call_expr) {
|
||||
throw std::runtime_error("Call statement requires a valid call expression");
|
||||
}
|
||||
|
||||
value callee_val = call_expr->callee->execute(ctx);
|
||||
if (!is_val<value_func>(callee_val)) {
|
||||
throw std::runtime_error("Callee is not a function: got " + callee_val->type());
|
||||
}
|
||||
auto * callee_func = cast_val<value_func>(callee_val);
|
||||
|
||||
context caller_ctx(ctx); // new scope for caller execution
|
||||
|
||||
const func_handler func = [this, caller_ctx = std::move(caller_ctx)](const func_args & args) -> value {
|
||||
context block_ctx(caller_ctx); // new scope for block execution
|
||||
|
||||
bind_parameters("caller", this->caller_args, args, block_ctx);
|
||||
|
||||
JJ_DEBUG("Executing call body with %zu statements", this->body.size());
|
||||
auto res = exec_statements(this->body, block_ctx);
|
||||
JJ_DEBUG("Call body execution complete, result: %s", res->val_str.str().c_str());
|
||||
return res;
|
||||
};
|
||||
|
||||
context call_ctx(ctx);
|
||||
call_ctx.set_val("caller", mk_val<value_func>("caller", func));
|
||||
|
||||
func_args args(call_ctx);
|
||||
|
||||
for (const auto & arg_expr : call_expr->args) {
|
||||
auto arg_val = arg_expr->execute(ctx);
|
||||
JJ_DEBUG(" Argument type: %s", arg_val->type().c_str());
|
||||
args.push_back(arg_val);
|
||||
}
|
||||
|
||||
JJ_DEBUG("Calling macro '%s' with %zu arguments", callee_func->name.c_str(), args.count());
|
||||
return callee_func->invoke(args);
|
||||
}
|
||||
|
||||
value member_expression::execute_impl(context & ctx) {
|
||||
value object = this->object->execute(ctx);
|
||||
|
||||
|
||||
@@ -552,6 +552,7 @@ struct call_statement : public statement {
|
||||
for (const auto & arg : this->caller_args) chk_type<expression>(arg);
|
||||
}
|
||||
std::string type() const override { return "CallStatement"; }
|
||||
value execute_impl(context & ctx) override;
|
||||
};
|
||||
|
||||
struct ternary_expression : public expression {
|
||||
|
||||
@@ -233,27 +233,27 @@ struct BuiltinRule {
|
||||
};
|
||||
|
||||
static std::unordered_map<std::string, BuiltinRule> PRIMITIVE_RULES = {
|
||||
{"boolean", {"(\"true\" | \"false\") space", {}}},
|
||||
{"boolean", {"(\"true\" | \"false\")", {}}},
|
||||
{"decimal-part", {"[0-9]{1,16}", {}}},
|
||||
{"integral-part", {"[0] | [1-9] [0-9]{0,15}", {}}},
|
||||
{"number", {"(\"-\"? integral-part) (\".\" decimal-part)? ([eE] [-+]? integral-part)? space", {"integral-part", "decimal-part"}}},
|
||||
{"integer", {"(\"-\"? integral-part) space", {"integral-part"}}},
|
||||
{"number", {"(\"-\"? integral-part) (\".\" decimal-part)? ([eE] [-+]? integral-part)?", {"integral-part", "decimal-part"}}},
|
||||
{"integer", {"(\"-\"? integral-part)", {"integral-part"}}},
|
||||
{"value", {"object | array | string | number | boolean | null", {"object", "array", "string", "number", "boolean", "null"}}},
|
||||
{"object", {"\"{\" space ( string \":\" space value (\",\" space string \":\" space value)* )? \"}\" space", {"string", "value"}}},
|
||||
{"array", {"\"[\" space ( value (\",\" space value)* )? \"]\" space", {"value"}}},
|
||||
{"uuid", {"\"\\\"\" [0-9a-fA-F]{8} \"-\" [0-9a-fA-F]{4} \"-\" [0-9a-fA-F]{4} \"-\" [0-9a-fA-F]{4} \"-\" [0-9a-fA-F]{12} \"\\\"\" space", {}}},
|
||||
{"object", {"\"{\" space ( string \":\" space value (\",\" space string \":\" space value)* )? space \"}\"", {"string", "value"}}},
|
||||
{"array", {"\"[\" space ( value (\",\" space value)* )? space \"]\"", {"value"}}},
|
||||
{"uuid", {"\"\\\"\" [0-9a-fA-F]{8} \"-\" [0-9a-fA-F]{4} \"-\" [0-9a-fA-F]{4} \"-\" [0-9a-fA-F]{4} \"-\" [0-9a-fA-F]{12} \"\\\"\"", {}}},
|
||||
{"char", {"[^\"\\\\\\x7F\\x00-\\x1F] | [\\\\] ([\"\\\\bfnrt] | \"u\" [0-9a-fA-F]{4})", {}}},
|
||||
{"string", {"\"\\\"\" char* \"\\\"\" space", {"char"}}},
|
||||
{"null", {"\"null\" space", {}}},
|
||||
{"string", {"\"\\\"\" char* \"\\\"\"", {"char"}}},
|
||||
{"null", {"\"null\"", {}}},
|
||||
};
|
||||
|
||||
static std::unordered_map<std::string, BuiltinRule> STRING_FORMAT_RULES = {
|
||||
{"date", {"[0-9]{4} \"-\" ( \"0\" [1-9] | \"1\" [0-2] ) \"-\" ( \"0\" [1-9] | [1-2] [0-9] | \"3\" [0-1] )", {}}},
|
||||
{"time", {"([01] [0-9] | \"2\" [0-3]) \":\" [0-5] [0-9] \":\" [0-5] [0-9] ( \".\" [0-9]{3} )? ( \"Z\" | ( \"+\" | \"-\" ) ( [01] [0-9] | \"2\" [0-3] ) \":\" [0-5] [0-9] )", {}}},
|
||||
{"date-time", {"date \"T\" time", {"date", "time"}}},
|
||||
{"date-string", {"\"\\\"\" date \"\\\"\" space", {"date"}}},
|
||||
{"time-string", {"\"\\\"\" time \"\\\"\" space", {"time"}}},
|
||||
{"date-time-string", {"\"\\\"\" date-time \"\\\"\" space", {"date-time"}}}
|
||||
{"date-string", {"\"\\\"\" date \"\\\"\"", {"date"}}},
|
||||
{"time-string", {"\"\\\"\" time \"\\\"\"", {"time"}}},
|
||||
{"date-time-string", {"\"\\\"\" date-time \"\\\"\"", {"date-time"}}}
|
||||
};
|
||||
|
||||
static bool is_reserved_name(const std::string & name) {
|
||||
@@ -551,16 +551,16 @@ private:
|
||||
}
|
||||
return join_seq();
|
||||
};
|
||||
return _add_rule(name, "\"\\\"\" (" + to_rule(transform()) + ") \"\\\"\" space");
|
||||
return _add_rule(name, "\"\\\"\" (" + to_rule(transform()) + ") \"\\\"\"");
|
||||
}
|
||||
|
||||
/*
|
||||
Returns a rule that matches a JSON string that is none of the provided strings
|
||||
|
||||
not_strings({"a"})
|
||||
-> ["] ( [a] char+ | [^"a] char* )? ["] space
|
||||
-> ["] ( [a] char+ | [^"a] char* )? ["]
|
||||
not_strings({"and", "also"})
|
||||
-> ["] ( [a] ([l] ([s] ([o] char+ | [^"o] char*) | [^"s] char*) | [n] ([d] char+ | [^"d] char*) | [^"ln] char*) | [^"a] char* )? ["] space
|
||||
-> ["] ( [a] ([l] ([s] ([o] char+ | [^"o] char*) | [^"s] char*) | [n] ([d] char+ | [^"d] char*) | [^"ln] char*) | [^"a] char* )? ["]
|
||||
*/
|
||||
std::string _not_strings(const std::vector<std::string> & strings) {
|
||||
|
||||
@@ -619,7 +619,7 @@ private:
|
||||
if (!trie.is_end_of_string) {
|
||||
out << "?";
|
||||
}
|
||||
out << " [\"] space";
|
||||
out << " [\"]";
|
||||
return out.str();
|
||||
}
|
||||
|
||||
@@ -725,7 +725,7 @@ private:
|
||||
rule += " )?";
|
||||
}
|
||||
|
||||
rule += " \"}\" space";
|
||||
rule += " space \"}\"";
|
||||
|
||||
return rule;
|
||||
}
|
||||
@@ -858,14 +858,14 @@ public:
|
||||
return _add_rule(rule_name, _generate_union_rule(name, schema_types));
|
||||
}
|
||||
if (schema.contains("const")) {
|
||||
return _add_rule(rule_name, _generate_constant_rule(schema["const"]) + " space");
|
||||
return _add_rule(rule_name, _generate_constant_rule(schema["const"]));
|
||||
}
|
||||
if (schema.contains("enum")) {
|
||||
std::vector<std::string> enum_values;
|
||||
for (const auto & v : schema["enum"]) {
|
||||
enum_values.push_back(_generate_constant_rule(v));
|
||||
}
|
||||
return _add_rule(rule_name, "(" + string_join(enum_values, " | ") + ") space");
|
||||
return _add_rule(rule_name, "(" + string_join(enum_values, " | ") + ")");
|
||||
}
|
||||
if ((schema_type.is_null() || schema_type == "object")
|
||||
&& (schema.contains("properties") ||
|
||||
@@ -933,7 +933,7 @@ public:
|
||||
}
|
||||
}
|
||||
if (!enum_intersection.empty()) {
|
||||
return _add_rule(rule_name, "(" + string_join(enum_intersection, " | ") + ") space");
|
||||
return _add_rule(rule_name, "(" + string_join(enum_intersection, " | ") + ")");
|
||||
}
|
||||
}
|
||||
return _add_rule(rule_name, _build_object_rule(properties, required, hybrid_name, json()));
|
||||
@@ -948,7 +948,7 @@ public:
|
||||
}
|
||||
rule += visit(items[i], name + (name.empty() ? "" : "-") + "tuple-" + std::to_string(i));
|
||||
}
|
||||
rule += " \"]\" space";
|
||||
rule += " space \"]\"";
|
||||
return _add_rule(rule_name, rule);
|
||||
}
|
||||
std::string item_rule_name = visit(items, name + (name.empty() ? "" : "-") + "item");
|
||||
@@ -956,7 +956,7 @@ public:
|
||||
json max_items_json = schema.contains("maxItems") ? schema["maxItems"] : json();
|
||||
int max_items = max_items_json.is_number_integer() ? max_items_json.get<int>() : std::numeric_limits<int>::max();
|
||||
|
||||
return _add_rule(rule_name, "\"[\" space " + build_repetition(item_rule_name, min_items, max_items, "\",\" space") + " \"]\" space");
|
||||
return _add_rule(rule_name, "\"[\" space " + build_repetition(item_rule_name, min_items, max_items, "\",\" space") + " space \"]\"");
|
||||
}
|
||||
if ((schema_type.is_null() || schema_type == "string") && schema.contains("pattern")) {
|
||||
return _visit_pattern(schema["pattern"], rule_name);
|
||||
@@ -972,7 +972,7 @@ public:
|
||||
std::string char_rule = _add_primitive("char", PRIMITIVE_RULES.at("char"));
|
||||
int min_len = schema.contains("minLength") ? schema["minLength"].get<int>() : 0;
|
||||
int max_len = schema.contains("maxLength") ? schema["maxLength"].get<int>() : std::numeric_limits<int>::max();
|
||||
return _add_rule(rule_name, "\"\\\"\" " + build_repetition(char_rule, min_len, max_len) + " \"\\\"\" space");
|
||||
return _add_rule(rule_name, "\"\\\"\" " + build_repetition(char_rule, min_len, max_len) + " \"\\\"\"");
|
||||
}
|
||||
if (schema_type == "integer" && (schema.contains("minimum") || schema.contains("exclusiveMinimum") || schema.contains("maximum") || schema.contains("exclusiveMaximum"))) {
|
||||
int64_t min_value = std::numeric_limits<int64_t>::min();
|
||||
@@ -990,7 +990,7 @@ public:
|
||||
std::stringstream out;
|
||||
out << "(";
|
||||
build_min_max_int(min_value, max_value, out);
|
||||
out << ") space";
|
||||
out << ")";
|
||||
return _add_rule(rule_name, out.str());
|
||||
}
|
||||
if (schema.empty() || schema_type == "object") {
|
||||
|
||||
+118
-78
@@ -6,13 +6,14 @@
|
||||
#include "unicode.h"
|
||||
|
||||
#include <algorithm>
|
||||
#include <deque>
|
||||
#include <initializer_list>
|
||||
#include <map>
|
||||
#include <memory>
|
||||
#include <nlohmann/json.hpp>
|
||||
#include <regex>
|
||||
#include <set>
|
||||
#include <stdexcept>
|
||||
#include <unordered_set>
|
||||
|
||||
// Trick to catch missing branches
|
||||
template <typename T>
|
||||
@@ -88,40 +89,7 @@ struct trie {
|
||||
return match_result{match_result::NO_MATCH};
|
||||
}
|
||||
|
||||
struct prefix_and_next {
|
||||
std::vector<uint32_t> prefix;
|
||||
std::vector<uint32_t> next_chars;
|
||||
};
|
||||
|
||||
std::vector<prefix_and_next> collect_prefix_and_next() {
|
||||
std::vector<uint32_t> prefix;
|
||||
std::vector<prefix_and_next> result;
|
||||
collect_prefix_and_next(0, prefix, result);
|
||||
return result;
|
||||
}
|
||||
|
||||
private:
|
||||
void collect_prefix_and_next(size_t index, std::vector<uint32_t> & prefix, std::vector<prefix_and_next> & out) {
|
||||
if (!nodes[index].is_word) {
|
||||
if (!nodes[index].children.empty()) {
|
||||
std::vector<uint32_t> chars;
|
||||
chars.reserve(nodes[index].children.size());
|
||||
for (const auto & p : nodes[index].children) {
|
||||
chars.push_back(p.first);
|
||||
}
|
||||
out.emplace_back(prefix_and_next{prefix, chars});
|
||||
}
|
||||
}
|
||||
|
||||
for (const auto & p : nodes[index].children) {
|
||||
uint32_t ch = p.first;
|
||||
auto child = p.second;
|
||||
prefix.push_back(ch);
|
||||
collect_prefix_and_next(child, prefix, out);
|
||||
prefix.pop_back();
|
||||
}
|
||||
}
|
||||
|
||||
size_t create_node() {
|
||||
size_t index = nodes.size();
|
||||
nodes.emplace_back();
|
||||
@@ -153,6 +121,65 @@ struct trie {
|
||||
}
|
||||
};
|
||||
|
||||
// Aho-Corasick automaton
|
||||
struct aho_corasick {
|
||||
trie t;
|
||||
std::vector<size_t> fail; // failure links
|
||||
std::vector<size_t> order; // states in BFS order
|
||||
std::vector<bool> terminal; // match states (directly or via a suffix link)
|
||||
std::set<uint32_t> alphabet; // every character with a transition
|
||||
|
||||
aho_corasick(const std::vector<std::string> & strings) : t(strings) {
|
||||
const auto & nodes = t.nodes;
|
||||
const size_t n = nodes.size();
|
||||
|
||||
fail.assign(n, 0);
|
||||
order.reserve(n);
|
||||
|
||||
std::deque<size_t> queue{ 0 };
|
||||
while (!queue.empty()) {
|
||||
size_t u = queue.front();
|
||||
queue.pop_front();
|
||||
order.push_back(u);
|
||||
for (const auto & [ch, v] : nodes[u].children) {
|
||||
if (u != 0) {
|
||||
size_t f = fail[u];
|
||||
while (f && nodes[f].children.find(ch) == nodes[f].children.end()) {
|
||||
f = fail[f];
|
||||
}
|
||||
auto it = nodes[f].children.find(ch);
|
||||
fail[v] = (it != nodes[f].children.end() && it->second != v) ? it->second : 0;
|
||||
}
|
||||
queue.push_back(v);
|
||||
}
|
||||
}
|
||||
|
||||
terminal.assign(n, false);
|
||||
for (size_t u : order) {
|
||||
terminal[u] = nodes[u].is_word || (u != 0 && terminal[fail[u]]);
|
||||
}
|
||||
|
||||
for (const auto & node : nodes) {
|
||||
for (const auto & [ch, v] : node.children) {
|
||||
alphabet.insert(ch);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
size_t num_states() const { return t.nodes.size(); }
|
||||
bool is_terminal(size_t s) const { return terminal[s]; }
|
||||
|
||||
// follow failure links until a transition on `ch` exists.
|
||||
size_t next(size_t state, uint32_t ch) const {
|
||||
const auto & nodes = t.nodes;
|
||||
while (state && nodes[state].children.find(ch) == nodes[state].children.end()) {
|
||||
state = fail[state];
|
||||
}
|
||||
auto it = nodes[state].children.find(ch);
|
||||
return it != nodes[state].children.end() ? it->second : 0;
|
||||
}
|
||||
};
|
||||
|
||||
static std::pair<uint32_t, size_t> parse_hex_escape(const std::string & str, size_t pos, int hex_count) {
|
||||
if (pos + hex_count > str.length()) {
|
||||
return {0, 0};
|
||||
@@ -992,12 +1019,12 @@ void common_peg_arena::resolve_refs() {
|
||||
}
|
||||
|
||||
std::string common_peg_arena::dump(common_peg_parser_id id) const {
|
||||
std::unordered_set<common_peg_parser_id> visited;
|
||||
std::set<common_peg_parser_id> visited;
|
||||
return dump_impl(id, visited);
|
||||
}
|
||||
|
||||
std::string common_peg_arena::dump_impl(common_peg_parser_id id,
|
||||
std::unordered_set<common_peg_parser_id> & visited) const {
|
||||
std::set<common_peg_parser_id> & visited) const {
|
||||
// Check for cycles
|
||||
if (visited.count(id)) {
|
||||
return "[cycle]";
|
||||
@@ -1342,7 +1369,7 @@ common_peg_parser common_peg_parser_builder::json_object() {
|
||||
common_peg_parser common_peg_parser_builder::json_array() {
|
||||
return rule("json-array", [this]() {
|
||||
auto ws = space();
|
||||
auto elements = sequence({json(), zero_or_more(sequence({literal(","), ws, json()}))});
|
||||
auto elements = sequence({json(), zero_or_more(sequence({ws, literal(","), ws, json()}))});
|
||||
return sequence({
|
||||
literal("["),
|
||||
ws,
|
||||
@@ -1502,61 +1529,74 @@ static std::string gbnf_escape_char_class(uint32_t c) {
|
||||
return std::string(buf);
|
||||
}
|
||||
|
||||
static std::string gbnf_excluding_pattern(const std::vector<std::string> & strings) {
|
||||
trie matcher(strings);
|
||||
auto pieces = matcher.collect_prefix_and_next();
|
||||
// GBNF grammar matching strings that contain no string in `strings` as a
|
||||
// substring. Emits the complement of an Aho-Corasick automaton DFA and returns
|
||||
// the start state rule name.
|
||||
//
|
||||
// ref: https://github.com/ggml-org/llama.cpp/pull/24839
|
||||
static std::string gbnf_excluding_grammar(const common_grammar_builder & builder,
|
||||
const std::string & prefix,
|
||||
const std::vector<std::string> & strings) {
|
||||
aho_corasick ac(strings);
|
||||
|
||||
std::string pattern;
|
||||
std::string trailing; // optional proper-prefix of a delimiter, allowed only at the very end
|
||||
for (size_t i = 0; i < pieces.size(); ++i) {
|
||||
if (i > 0) {
|
||||
pattern += " | ";
|
||||
auto state_name = [&](size_t s) -> std::string {
|
||||
if (s == 0) {
|
||||
return prefix;
|
||||
}
|
||||
std::string num = std::to_string(s);
|
||||
num = num.size() == 1 ? ("0" + num) : num;
|
||||
return prefix + "-" + num;
|
||||
};
|
||||
|
||||
const auto & pre = pieces[i].prefix;
|
||||
const auto & chars = pieces[i].next_chars;
|
||||
|
||||
std::string cls;
|
||||
cls.reserve(chars.size());
|
||||
auto char_class = [](const std::vector<uint32_t> & chars, bool negate) {
|
||||
std::string s = negate ? "[^" : "[";
|
||||
for (uint32_t ch : chars) {
|
||||
cls += gbnf_escape_char_class(ch);
|
||||
s += gbnf_escape_char_class(ch);
|
||||
}
|
||||
return s + "]";
|
||||
};
|
||||
|
||||
for (size_t q = 0; q < ac.num_states(); q++) {
|
||||
if (ac.is_terminal(q)) {
|
||||
continue; // match states are dropped
|
||||
}
|
||||
|
||||
if (!pre.empty()) {
|
||||
std::string pre_literal = gbnf_format_literal(common_unicode_cpts_to_utf8(pre));
|
||||
pattern += pre_literal + " [^" + cls + "]";
|
||||
// Each interior alternative consumes a delimiter-prefix plus a disambiguating
|
||||
// char, so the repetition alone cannot match a value that *ends* on a proper
|
||||
// prefix of a delimiter (e.g. a trailing "\n" when the delimiter is
|
||||
// "\n</parameter>\n"). The runtime until() (greedy first-match) accepts such
|
||||
// values, so without this the grammar would reject input the parser accepts.
|
||||
// Allow the value to terminate on any proper prefix as an optional tail.
|
||||
// This makes the grammar a slight superset of the runtime language (a value
|
||||
// may end on the longest prefix, which greedy first-match would not itself
|
||||
// produce); harmless for constrained generation, which only needs to admit
|
||||
// every runtime-valid string.
|
||||
if (!trailing.empty()) {
|
||||
trailing += " | ";
|
||||
std::map<size_t, std::vector<uint32_t>> buckets;
|
||||
std::vector<uint32_t> excluded;
|
||||
for (uint32_t c : ac.alphabet) {
|
||||
size_t d = ac.next(q, c);
|
||||
if (ac.is_terminal(d)) {
|
||||
excluded.push_back(c); // completes a forbidden string -> omit
|
||||
} else if (d != 0) {
|
||||
buckets[d].push_back(c); // specific non-root destination
|
||||
excluded.push_back(c);
|
||||
}
|
||||
trailing += pre_literal;
|
||||
} else {
|
||||
pattern += "[^" + cls + "]";
|
||||
}
|
||||
|
||||
std::string rhs = "|"; // every state is accepting
|
||||
for (const auto & [d, chars] : buckets) {
|
||||
rhs += " " + char_class(chars, false) + " " + state_name(d) + " |";
|
||||
}
|
||||
rhs += " " + char_class(excluded, true) + " " + state_name(0);
|
||||
|
||||
builder.add_rule(state_name(q), rhs);
|
||||
}
|
||||
|
||||
std::string result = "(" + pattern + ")*";
|
||||
if (!trailing.empty()) {
|
||||
result += " (" + trailing + ")?";
|
||||
// An empty delimiter makes the start state terminal. Emit an entry rule
|
||||
// that matches nothing so the returned reference stays valid.
|
||||
if (ac.is_terminal(0)) {
|
||||
builder.add_rule(prefix, "|");
|
||||
}
|
||||
return result;
|
||||
|
||||
return state_name(0);
|
||||
}
|
||||
|
||||
static std::unordered_set<std::string> collect_reachable_rules(
|
||||
static std::set<std::string> collect_reachable_rules(
|
||||
const common_peg_arena & arena,
|
||||
const common_peg_parser_id & rule
|
||||
) {
|
||||
std::unordered_set<std::string> reachable;
|
||||
std::unordered_set<std::string> visited;
|
||||
std::set<std::string> reachable;
|
||||
std::set<std::string> visited;
|
||||
|
||||
std::function<void(common_peg_parser_id)> visit = [&](common_peg_parser_id id) {
|
||||
const auto & parser = arena.get(id);
|
||||
@@ -1765,7 +1805,7 @@ void common_peg_arena::build_grammar(const common_grammar_builder & builder, boo
|
||||
if (p.delimiters.empty()) {
|
||||
return ".*";
|
||||
}
|
||||
return gbnf_excluding_pattern(p.delimiters);
|
||||
return gbnf_excluding_grammar(builder, "until-" + std::to_string(id), p.delimiters);
|
||||
} else if constexpr (std::is_same_v<T, common_peg_schema_parser>) {
|
||||
if (schema_delegates(p)) {
|
||||
return to_gbnf(p.child);
|
||||
@@ -1789,7 +1829,7 @@ void common_peg_arena::build_grammar(const common_grammar_builder & builder, boo
|
||||
};
|
||||
|
||||
// Collect reachable rules
|
||||
std::unordered_set<std::string> reachable_rules;
|
||||
std::set<std::string> reachable_rules;
|
||||
|
||||
if (lazy) {
|
||||
// Collect rules reachable from trigger rules
|
||||
|
||||
+2
-2
@@ -3,8 +3,8 @@
|
||||
#include <nlohmann/json_fwd.hpp>
|
||||
|
||||
#include <memory>
|
||||
#include <set>
|
||||
#include <unordered_map>
|
||||
#include <unordered_set>
|
||||
#include <string>
|
||||
#include <string_view>
|
||||
#include <functional>
|
||||
@@ -335,7 +335,7 @@ class common_peg_arena {
|
||||
friend class common_peg_parser_builder;
|
||||
|
||||
private:
|
||||
std::string dump_impl(common_peg_parser_id id, std::unordered_set<common_peg_parser_id> & visited) const;
|
||||
std::string dump_impl(common_peg_parser_id id, std::set<common_peg_parser_id> & visited) const;
|
||||
|
||||
common_peg_parser_id add_parser(common_peg_parser_variant parser);
|
||||
void add_rule(const std::string & name, common_peg_parser_id id);
|
||||
|
||||
+174
-35
@@ -161,6 +161,10 @@ struct common_speculative_impl {
|
||||
|
||||
virtual void accept(llama_seq_id seq_id, uint16_t n_accepted, bool is_other) = 0;
|
||||
|
||||
// (optional) serialize/restore per-seq internal state (e.g. eagle3's deferred boundary).
|
||||
virtual bool get_state(llama_seq_id /*seq_id*/, std::vector<uint8_t> & /*data*/) const { return false; }
|
||||
virtual void set_state(llama_seq_id /*seq_id*/, const std::vector<uint8_t> & /*data*/) {}
|
||||
|
||||
// true if this implementation requires the target context to extract post-norm embeddings
|
||||
virtual bool need_embd() const = 0;
|
||||
|
||||
@@ -841,6 +845,49 @@ struct common_speculative_impl_draft_eagle3 : public common_speculative_impl {
|
||||
(size_t) n_embd_dec * sizeof(float));
|
||||
}
|
||||
|
||||
// we only need to stash the deferred boundary's g_embd row for recurrent/hybrid targets:
|
||||
// their single-position checkpoints drop it on restore
|
||||
bool need_boundary_stash() const {
|
||||
const llama_model * model_tgt = llama_get_model(params.ctx_tgt);
|
||||
return llama_model_is_recurrent(model_tgt) || llama_model_is_hybrid(model_tgt);
|
||||
}
|
||||
|
||||
bool get_state(llama_seq_id seq_id, std::vector<uint8_t> & data) const override {
|
||||
if (!need_boundary_stash()) {
|
||||
return false;
|
||||
}
|
||||
if (seq_id < 0 || seq_id >= (llama_seq_id) n_seq || pending_pos_last[seq_id] < 0) {
|
||||
return false;
|
||||
}
|
||||
|
||||
const llama_pos pos = pending_pos_last[seq_id];
|
||||
const std::vector<float> & g = pending_g_last[seq_id];
|
||||
|
||||
data.resize(sizeof(llama_pos) + g.size() * sizeof(float));
|
||||
std::memcpy(data.data(), &pos, sizeof(llama_pos));
|
||||
std::memcpy(data.data() + sizeof(llama_pos), g.data(), g.size() * sizeof(float));
|
||||
return true;
|
||||
}
|
||||
|
||||
void set_state(llama_seq_id seq_id, const std::vector<uint8_t> & data) override {
|
||||
if (!need_boundary_stash()) {
|
||||
return;
|
||||
}
|
||||
if (seq_id < 0 || seq_id >= (llama_seq_id) n_seq) {
|
||||
return;
|
||||
}
|
||||
if (data.size() != sizeof(llama_pos) + (size_t) n_embd_dec * sizeof(float)) {
|
||||
return;
|
||||
}
|
||||
|
||||
llama_pos pos = -1;
|
||||
std::memcpy(&pos, data.data(), sizeof(llama_pos));
|
||||
|
||||
pending_pos_last[seq_id] = pos;
|
||||
pending_g_last[seq_id].resize(n_embd_dec);
|
||||
std::memcpy(pending_g_last[seq_id].data(), data.data() + sizeof(llama_pos), (size_t) n_embd_dec * sizeof(float));
|
||||
}
|
||||
|
||||
bool need_embd() const override {
|
||||
return false;
|
||||
}
|
||||
@@ -858,7 +905,13 @@ struct common_speculative_impl_draft_mtp : public common_speculative_impl {
|
||||
|
||||
int32_t n_embd = 0;
|
||||
|
||||
bool is_mem_shared = false;
|
||||
// One MTP draft driver, three modes (set once in the ctor):
|
||||
// is_mem_shared (gemma4): shares the target KV, runs all heads in one graph.
|
||||
// chain_heads (step35): n_mtp_layers trained heads, one per draft step.
|
||||
// neither (qwen35 / qwen35moe): a single trained MTP head.
|
||||
int32_t n_mtp_layers = 1;
|
||||
bool is_mem_shared = false; // gemma4
|
||||
bool chain_heads = false; // derived in the ctor: n_mtp_layers > 1 && !is_mem_shared
|
||||
|
||||
// Per-sequence cross-batch carryover: pair (h_p, x_{p+1}) at MTP pos p+1.
|
||||
// The last h-row of one process() call needs the first token of the NEXT
|
||||
@@ -873,10 +926,8 @@ struct common_speculative_impl_draft_mtp : public common_speculative_impl {
|
||||
std::vector<std::vector<float>> verify_h;
|
||||
std::vector<int32_t> verify_h_rows;
|
||||
|
||||
// Per-seq draft length from the last draft() call, used in accept() to
|
||||
// roll back ctx_dft's recurrent state past the AR draft's redundant
|
||||
// pre-advancement before process() mirrored the verify batch.
|
||||
std::vector<uint16_t> last_n_drafted;
|
||||
std::vector<int> i_last;
|
||||
std::vector<std::vector<float>> chain_h;
|
||||
|
||||
common_speculative_impl_draft_mtp(const common_params_speculative & params, uint32_t n_seq)
|
||||
: common_speculative_impl(COMMON_SPECULATIVE_TYPE_DRAFT_MTP, n_seq)
|
||||
@@ -889,6 +940,7 @@ struct common_speculative_impl_draft_mtp : public common_speculative_impl {
|
||||
n_embd = llama_model_n_embd_out(llama_get_model(ctx_dft));
|
||||
GGML_ASSERT(n_embd == llama_model_n_embd(llama_get_model(ctx_tgt)) &&
|
||||
"MTP input row width must match the target h_nextn width");
|
||||
n_mtp_layers = std::max(1, (int) llama_model_n_layer_nextn(llama_get_model(ctx_dft)));
|
||||
|
||||
LOG_INF("%s: adding speculative implementation 'draft-mtp'\n", __func__);
|
||||
LOG_INF("%s: - n_max=%d, n_min=%d, p_min=%.2f, n_embd=%d, backend_sampling=%d\n", __func__, this->params.n_max, this->params.n_min, this->params.p_min, n_embd, (int) this->params.backend_sampling);
|
||||
@@ -935,16 +987,25 @@ struct common_speculative_impl_draft_mtp : public common_speculative_impl {
|
||||
llama_set_embeddings_nextn(ctx_dft, true, /*masked*/ true);
|
||||
|
||||
is_mem_shared = llama_get_ctx_other(ctx_dft) == ctx_tgt;
|
||||
chain_heads = n_mtp_layers > 1 && !is_mem_shared;
|
||||
|
||||
if (chain_heads) {
|
||||
this->params.n_max = std::min(this->params.n_max, n_mtp_layers);
|
||||
|
||||
chain_h.assign(n_seq, {});
|
||||
for (auto & c : chain_h) {
|
||||
c.reserve((size_t) (this->params.n_max + 1) * n_embd);
|
||||
}
|
||||
}
|
||||
|
||||
pending_h.assign(n_seq, std::vector<float>(n_embd, 0.0f));
|
||||
|
||||
i_last.assign(n_seq, -1);
|
||||
i_batch_beg.assign(n_seq, -1);
|
||||
i_batch_end.assign(n_seq, -1);
|
||||
|
||||
verify_h.assign(n_seq, {});
|
||||
verify_h_rows.assign(n_seq, 0);
|
||||
|
||||
last_n_drafted.assign(n_seq, 0);
|
||||
}
|
||||
|
||||
~common_speculative_impl_draft_mtp() override {
|
||||
@@ -1050,9 +1111,34 @@ struct common_speculative_impl_draft_mtp : public common_speculative_impl {
|
||||
set_h(i_batch_beg[seq_id], pending_h[seq_id].data());
|
||||
}
|
||||
|
||||
const int32_t rc = llama_decode(ctx_dft, batch);
|
||||
if (rc != 0) {
|
||||
LOG_ERR("%s: llama_decode(ctx_dft) failed rc=%d (pos=%d)\n", __func__, (int) rc, (int) batch_in.pos[0]);
|
||||
auto * mem_dft = llama_get_memory(ctx_dft);
|
||||
|
||||
bool ok = true;
|
||||
for (int head = 0; head < n_mtp_layers; ++head) {
|
||||
if (chain_heads) {
|
||||
// ref: https://github.com/ggml-org/llama.cpp/pull/24340/changes#r3413498544
|
||||
for (llama_seq_id seq_id = 0; seq_id < (llama_seq_id) n_seq; ++seq_id) {
|
||||
if (i_batch_beg[seq_id] < 0) {
|
||||
continue;
|
||||
}
|
||||
llama_memory_seq_rm(mem_dft, seq_id, batch_in.pos[i_batch_beg[seq_id]], -1);
|
||||
}
|
||||
llama_set_nextn_layer_offset(ctx_dft, head);
|
||||
}
|
||||
|
||||
const int32_t rc = llama_decode(ctx_dft, batch);
|
||||
if (rc != 0) {
|
||||
LOG_ERR("%s: llama_decode(ctx_dft) head=%d failed rc=%d (pos=%d)\n",
|
||||
__func__, head, (int) rc, (int) batch_in.pos[0]);
|
||||
ok = false;
|
||||
break;
|
||||
}
|
||||
}
|
||||
|
||||
if (chain_heads) {
|
||||
llama_set_nextn_layer_offset(ctx_dft, 0); // restore default for non-draft decodes
|
||||
}
|
||||
if (!ok) {
|
||||
return false;
|
||||
}
|
||||
}
|
||||
@@ -1087,7 +1173,6 @@ struct common_speculative_impl_draft_mtp : public common_speculative_impl {
|
||||
int n_drafting = 0;
|
||||
std::vector<bool> drafting(n_seq);
|
||||
|
||||
const float * h_row = nullptr;
|
||||
const size_t row_bytes = (size_t) n_embd * sizeof(float);
|
||||
|
||||
for (llama_seq_id seq_id = 0; seq_id < (llama_seq_id) n_seq; ++seq_id) {
|
||||
@@ -1102,22 +1187,43 @@ struct common_speculative_impl_draft_mtp : public common_speculative_impl {
|
||||
common_sampler_reset(smpls[seq_id].get());
|
||||
|
||||
common_batch_add(batch, dp.id_last, dp.n_past, { seq_id }, true);
|
||||
std::memcpy(batch.embd + (size_t) (batch.n_tokens - 1) * n_embd, pending_h[seq_id].data(), row_bytes);
|
||||
|
||||
h_row = pending_h[seq_id].data();
|
||||
std::memcpy(batch.embd + n_embd*(batch.n_tokens - 1), h_row, row_bytes);
|
||||
}
|
||||
i_last[seq_id] = batch.n_tokens - 1;
|
||||
|
||||
int ret = llama_decode(ctx_dft, batch);
|
||||
if (ret != 0) {
|
||||
LOG_WRN("%s: llama_decode returned %d\n", __func__, ret);
|
||||
return;
|
||||
if (chain_heads) {
|
||||
chain_h[seq_id].assign(pending_h[seq_id].begin(), pending_h[seq_id].end());
|
||||
}
|
||||
}
|
||||
|
||||
int i = 0;
|
||||
|
||||
while (n_drafting > 0) {
|
||||
int i_batch = 0;
|
||||
// each step decodes under a different head, i.e. a different decoder layer, and
|
||||
// KV is per layer. process() filled this layer's KV only for positions < n_past
|
||||
// (prompt + accepted prefix) — nothing in the draft region yet. so reset the
|
||||
// draft region (the seq_rm lower bound is n_past, leaving the prompt KV intact)
|
||||
// and select head i so it rebuilds its own layer's KV there; decoding just the
|
||||
// latest token would leave its attention reading cells only another head wrote.
|
||||
if (chain_heads) {
|
||||
auto * mem_dft = llama_get_memory(ctx_dft);
|
||||
for (llama_seq_id seq_id = 0; seq_id < (llama_seq_id) n_seq; ++seq_id) {
|
||||
if (drafting[seq_id]) {
|
||||
llama_memory_seq_rm(mem_dft, seq_id, dparams[seq_id].n_past, -1);
|
||||
}
|
||||
}
|
||||
llama_set_nextn_layer_offset(ctx_dft, i);
|
||||
}
|
||||
|
||||
int ret = llama_decode(ctx_dft, batch);
|
||||
if (ret != 0) {
|
||||
LOG_WRN("%s: llama_decode[%d] returned %d\n", __func__, i, ret);
|
||||
break;
|
||||
}
|
||||
|
||||
// rebuild the batch for the next step: the growing-KV paths re-add only the
|
||||
// new token (the KV already holds the prefix), while chained heads re-add the
|
||||
// whole prefix at the next head. dropped sequences are simply not re-added.
|
||||
common_batch_clear(batch);
|
||||
|
||||
for (llama_seq_id seq_id = 0; seq_id < (llama_seq_id) n_seq; ++seq_id) {
|
||||
@@ -1127,9 +1233,8 @@ struct common_speculative_impl_draft_mtp : public common_speculative_impl {
|
||||
|
||||
auto * smpl = smpls[seq_id].get();
|
||||
|
||||
common_sampler_sample(smpl, ctx_dft, i_batch, true);
|
||||
h_row = llama_get_embeddings_nextn_ith(ctx_dft, i_batch);
|
||||
++i_batch;
|
||||
common_sampler_sample(smpl, ctx_dft, i_last[seq_id], true);
|
||||
const float * h_row = llama_get_embeddings_nextn_ith(ctx_dft, i_last[seq_id]);
|
||||
|
||||
const auto * cur_p = common_sampler_get_candidates(smpl, true);
|
||||
|
||||
@@ -1163,30 +1268,41 @@ struct common_speculative_impl_draft_mtp : public common_speculative_impl {
|
||||
continue;
|
||||
}
|
||||
|
||||
if (is_mem_shared) {
|
||||
if (chain_heads) {
|
||||
// ref: https://github.com/ggml-org/llama.cpp/pull/24340#discussion_r3448031546
|
||||
chain_h[seq_id].insert(chain_h[seq_id].end(), h_row, h_row + n_embd);
|
||||
|
||||
const int n_rows = (int) result.size() + 1; // id_last + tokens drafted so far
|
||||
for (int t = 0; t < n_rows; ++t) {
|
||||
const llama_token tok = (t == 0) ? dp.id_last : result[t - 1];
|
||||
common_batch_add(batch, tok, dp.n_past + t, { seq_id }, t == n_rows - 1);
|
||||
std::memcpy(batch.embd + (size_t) (batch.n_tokens - 1) * n_embd,
|
||||
chain_h[seq_id].data() + (size_t) t * n_embd, row_bytes);
|
||||
}
|
||||
} else if (is_mem_shared) {
|
||||
// note: with shared memory (e.g. Gemma4 assistants) we use the same position for all draft tokens
|
||||
// ref: https://github.com/huggingface/transformers/blob/effde20942e3f82a1b97449f60b3a48c5ff96145/docs/source/en/model_doc/gemma4_assistant.md?plain=1#L36-L37
|
||||
common_batch_add(batch, id, dp.n_past, { seq_id }, true);
|
||||
std::memcpy(batch.embd + (size_t) (batch.n_tokens - 1) * n_embd, h_row, row_bytes);
|
||||
} else {
|
||||
common_batch_add(batch, id, dp.n_past + i + 1, { seq_id }, true);
|
||||
std::memcpy(batch.embd + (size_t) (batch.n_tokens - 1) * n_embd, h_row, row_bytes);
|
||||
}
|
||||
std::memcpy(batch.embd + n_embd*(batch.n_tokens - 1), h_row, row_bytes);
|
||||
|
||||
i_last[seq_id] = batch.n_tokens - 1;
|
||||
}
|
||||
|
||||
if (batch.n_tokens == 0) {
|
||||
break;
|
||||
}
|
||||
|
||||
// evaluate the drafted tokens on the draft model
|
||||
ret = llama_decode(ctx_dft, batch);
|
||||
if (ret != 0) {
|
||||
LOG_WRN("%s: llama_decode[%d] returned %d\n", __func__, i, ret);
|
||||
break;
|
||||
}
|
||||
|
||||
++i;
|
||||
}
|
||||
|
||||
if (chain_heads) {
|
||||
llama_set_nextn_layer_offset(ctx_dft, 0); // restore default for non-draft decodes
|
||||
}
|
||||
|
||||
for (llama_seq_id seq_id = 0; seq_id < (llama_seq_id) n_seq; ++seq_id) {
|
||||
auto & dp = dparams[seq_id];
|
||||
if (!dp.drafting) {
|
||||
@@ -1196,8 +1312,6 @@ struct common_speculative_impl_draft_mtp : public common_speculative_impl {
|
||||
if (dp.result->size() < (size_t) params.n_min) {
|
||||
dp.result->clear();
|
||||
}
|
||||
|
||||
last_n_drafted[seq_id] = (uint16_t) dp.result->size();
|
||||
}
|
||||
}
|
||||
|
||||
@@ -1810,7 +1924,7 @@ common_speculative * common_speculative_init(common_params_speculative & params,
|
||||
|
||||
bool has_draft_simple = (enabled_configs & (1u << COMMON_SPECULATIVE_TYPE_DRAFT_SIMPLE));
|
||||
bool has_draft_eagle3 = (enabled_configs & (1u << COMMON_SPECULATIVE_TYPE_DRAFT_EAGLE3)) && params.draft.ctx_dft != nullptr;
|
||||
bool has_mtp = (enabled_configs & (1u << COMMON_SPECULATIVE_TYPE_DRAFT_MTP)) && params.draft.ctx_dft != nullptr;
|
||||
bool has_draft_mtp = (enabled_configs & (1u << COMMON_SPECULATIVE_TYPE_DRAFT_MTP)) && params.draft.ctx_dft != nullptr;
|
||||
|
||||
|
||||
|
||||
@@ -1848,7 +1962,7 @@ common_speculative * common_speculative_init(common_params_speculative & params,
|
||||
if (has_draft_eagle3) {
|
||||
configs.push_back(common_speculative_config(COMMON_SPECULATIVE_TYPE_DRAFT_EAGLE3, params));
|
||||
}
|
||||
if (has_mtp) {
|
||||
if (has_draft_mtp) {
|
||||
configs.push_back(common_speculative_config(COMMON_SPECULATIVE_TYPE_DRAFT_MTP, params));
|
||||
}
|
||||
}
|
||||
@@ -2118,6 +2232,31 @@ void common_speculative_accept(common_speculative * spec, llama_seq_id seq_id, u
|
||||
}
|
||||
}
|
||||
|
||||
// TODO: support the case of more than one speculative implementations having a state
|
||||
bool common_speculative_get_state(common_speculative * spec, llama_seq_id seq_id, std::vector<uint8_t> & data) {
|
||||
if (spec == nullptr) {
|
||||
return false;
|
||||
}
|
||||
|
||||
for (auto & impl : spec->impls) {
|
||||
if (impl->get_state(seq_id, data)) {
|
||||
return true;
|
||||
}
|
||||
}
|
||||
|
||||
return false;
|
||||
}
|
||||
|
||||
void common_speculative_set_state(common_speculative * spec, llama_seq_id seq_id, const std::vector<uint8_t> & data) {
|
||||
if (spec == nullptr) {
|
||||
return;
|
||||
}
|
||||
|
||||
for (auto & impl : spec->impls) {
|
||||
impl->set_state(seq_id, data);
|
||||
}
|
||||
}
|
||||
|
||||
void common_speculative_print_stats(const common_speculative * spec) {
|
||||
if (spec == nullptr) {
|
||||
return;
|
||||
|
||||
@@ -68,6 +68,10 @@ void common_speculative_draft(common_speculative * spec);
|
||||
// informs the speculative context that n_accepted tokens were accepted by the target model
|
||||
void common_speculative_accept(common_speculative * spec, llama_seq_id, uint16_t n_accepted);
|
||||
|
||||
// (optional) get/set internal state
|
||||
bool common_speculative_get_state(common_speculative * spec, llama_seq_id seq_id, std::vector<uint8_t> & data);
|
||||
void common_speculative_set_state(common_speculative * spec, llama_seq_id seq_id, const std::vector<uint8_t> & data);
|
||||
|
||||
// print statistics about the speculative decoding
|
||||
void common_speculative_print_stats(const common_speculative * spec);
|
||||
|
||||
|
||||
@@ -126,7 +126,7 @@ class BailingMoeV2Model(TextModel):
|
||||
if (rope_dim := hparams.get("head_dim")) is None:
|
||||
rope_dim = hparams["hidden_size"] // hparams["num_attention_heads"]
|
||||
|
||||
self.gguf_writer.add_rope_dimension_count(int(rope_dim * self.hparams.get("partial_rotary_factor", 0.5)))
|
||||
self.gguf_writer.add_rope_dimension_count(int(rope_dim * self.rope_parameters.get("partial_rotary_factor", 0.5)))
|
||||
self.gguf_writer.add_leading_dense_block_count(hparams["first_k_dense_replace"])
|
||||
self.gguf_writer.add_vocab_size(hparams["vocab_size"])
|
||||
self.gguf_writer.add_expert_feed_forward_length(hparams["moe_intermediate_size"])
|
||||
|
||||
+7
-1
@@ -1119,8 +1119,10 @@ class TextModel(ModelBase):
|
||||
|
||||
rope_theta = self.find_hparam(["global_rope_theta", "rope_global_theta", "rope_theta_global", "rope_theta", "rotary_emb_base"], optional=True)
|
||||
local_rope_theta = self.find_hparam(["local_rope_theta", "rope_local_theta", "rope_theta_local", "swa_rope_theta", "rope_local_base_freq"], optional=True)
|
||||
partial_rotary_factor = self.find_hparam(["partial_rotary_factor", "rope_pct", "rope_percent"], optional=True)
|
||||
original_max_position_embeddings = self.find_hparam(["original_max_position_embeddings"], optional=True)
|
||||
|
||||
# Ensure "rope_theta" and "rope_type" is mirrored in rope_parameters
|
||||
# Ensure global params are mirrored in rope_parameters
|
||||
if "full_attention" not in self.rope_parameters and "sliding_attention" not in self.rope_parameters:
|
||||
if local_rope_theta is not None:
|
||||
self.rope_parameters["sliding_attention"] = {"rope_theta": local_rope_theta}
|
||||
@@ -1128,6 +1130,10 @@ class TextModel(ModelBase):
|
||||
self.rope_parameters["rope_theta"] = rope_theta
|
||||
if "rope_type" not in self.rope_parameters and (rope_type := self.rope_parameters.get("type")) is not None:
|
||||
self.rope_parameters["rope_type"] = rope_type
|
||||
if "partial_rotary_factor" not in self.rope_parameters and partial_rotary_factor is not None:
|
||||
self.rope_parameters["partial_rotary_factor"] = partial_rotary_factor
|
||||
if "original_max_position_embeddings" not in self.rope_parameters and original_max_position_embeddings is not None:
|
||||
self.rope_parameters["original_max_position_embeddings"] = original_max_position_embeddings
|
||||
|
||||
@classmethod
|
||||
def __init_subclass__(cls):
|
||||
|
||||
@@ -148,7 +148,7 @@ class ChatGLMModel(TextModel):
|
||||
rope_dim = self.hparams["attention_dim"]
|
||||
else:
|
||||
rope_dim = self.hparams["hidden_size"] // self.hparams["num_attention_heads"]
|
||||
self.gguf_writer.add_rope_dimension_count(int(rope_dim * self.hparams.get("partial_rotary_factor", 0.5)))
|
||||
self.gguf_writer.add_rope_dimension_count(int(rope_dim * self.rope_parameters.get("partial_rotary_factor", 0.5)))
|
||||
self.gguf_writer.add_add_bos_token(False)
|
||||
rope_freq = 10000
|
||||
if "rope_ratio" in self.hparams:
|
||||
|
||||
+1
-1
@@ -161,7 +161,7 @@ class DeciModel(TextModel):
|
||||
factor = rope_params.get("factor", 8.0)
|
||||
low_freq_factor = rope_params.get("low_freq_factor", 1.0)
|
||||
high_freq_factor = rope_params.get("high_freq_factor", 4.0)
|
||||
old_context_len = self.hparams.get("original_max_position_embeddings", 8192)
|
||||
old_context_len = rope_params.get("original_max_position_embeddings", 8192)
|
||||
|
||||
low_freq_wavelen = old_context_len / low_freq_factor
|
||||
high_freq_wavelen = old_context_len / high_freq_factor
|
||||
|
||||
@@ -24,7 +24,7 @@ class ExaoneModel(TextModel):
|
||||
|
||||
assert (hparams["activation_function"] == "silu")
|
||||
|
||||
rotary_factor = self.find_hparam(["partial_rotary_factor", "rope_pct"], optional=True)
|
||||
rotary_factor = self.rope_parameters.get("partial_rotary_factor")
|
||||
rotary_factor = rotary_factor if rotary_factor is not None else 1.0
|
||||
self.gguf_writer.add_rope_dimension_count(int(rotary_factor * (hparams["hidden_size"] // hparams["num_attention_heads"])))
|
||||
|
||||
@@ -39,7 +39,7 @@ class ExaoneModel(TextModel):
|
||||
factor = rope_params.get("factor", 8.0)
|
||||
low_freq_factor = rope_params.get("low_freq_factor", 1.0)
|
||||
high_freq_factor = rope_params.get("high_freq_factor", 4.0)
|
||||
old_context_len = self.hparams.get("original_max_position_embeddings", 8192)
|
||||
old_context_len = rope_params.get("original_max_position_embeddings", 8192)
|
||||
|
||||
low_freq_wavelen = old_context_len / low_freq_factor
|
||||
high_freq_wavelen = old_context_len / high_freq_factor
|
||||
@@ -104,7 +104,7 @@ class Exaone4Model(TextModel):
|
||||
factor = rope_params.get("factor", 16.0)
|
||||
low_freq_factor = rope_params.get("low_freq_factor", 1.0)
|
||||
high_freq_factor = rope_params.get("high_freq_factor", 4.0)
|
||||
old_context_len = self.hparams.get("original_max_position_embeddings", 8192)
|
||||
old_context_len = rope_params.get("original_max_position_embeddings", 8192)
|
||||
|
||||
low_freq_wavelen = old_context_len / low_freq_factor
|
||||
high_freq_wavelen = old_context_len / high_freq_factor
|
||||
|
||||
+1
-1
@@ -693,7 +693,7 @@ class Gemma4Model(Gemma3Model):
|
||||
self.gguf_writer.add_head_count_kv(value_arr)
|
||||
|
||||
# handle n_rot differently for global vs swa layers
|
||||
partial_rotary_factor_swa = self.hparams.get("partial_rotary_factor", 1.0)
|
||||
partial_rotary_factor_swa = self.rope_parameters.get("partial_rotary_factor", 1.0)
|
||||
n_rot_full = int(head_dim_full) # "proportional" is used, see generate_extra_tensors
|
||||
n_rot_swa = int(head_dim_swa * partial_rotary_factor_swa)
|
||||
self.gguf_writer.add_rope_dimension_count(n_rot_full)
|
||||
|
||||
+2
-2
@@ -124,7 +124,7 @@ class Glm4MoeModel(TextModel):
|
||||
self.hparams["hidden_size"] // self.hparams["num_attention_heads"]
|
||||
)
|
||||
self.gguf_writer.add_rope_dimension_count(
|
||||
int(rope_dim * self.hparams.get("partial_rotary_factor", 0.5))
|
||||
int(rope_dim * self.rope_parameters.get("partial_rotary_factor", 0.5))
|
||||
)
|
||||
|
||||
# MoE parameters - Use only routed expert count (shared experts handled separately)
|
||||
@@ -226,7 +226,7 @@ class GlmMoeDsaModel(DeepseekV2Model):
|
||||
super().set_gguf_parameters()
|
||||
|
||||
rope_dim = self.hparams["qk_rope_head_dim"]
|
||||
partial_rotary_factor = self.hparams.get("partial_rotary_factor", 1.0)
|
||||
partial_rotary_factor = self.rope_parameters.get("partial_rotary_factor", 1.0)
|
||||
self.gguf_writer.add_rope_dimension_count(int(rope_dim * partial_rotary_factor))
|
||||
|
||||
# NextN/MTP prediction layers
|
||||
|
||||
+1
-1
@@ -289,7 +289,7 @@ class LlamaModel(TextModel):
|
||||
factor = rope_params.get("factor", 8.0)
|
||||
low_freq_factor = rope_params.get("low_freq_factor", 1.0)
|
||||
high_freq_factor = rope_params.get("high_freq_factor", 4.0)
|
||||
old_context_len = self.hparams.get("original_max_position_embeddings", 8192)
|
||||
old_context_len = rope_params.get("original_max_position_embeddings", 8192)
|
||||
|
||||
low_freq_wavelen = old_context_len / low_freq_factor
|
||||
high_freq_wavelen = old_context_len / high_freq_factor
|
||||
|
||||
+1
-1
@@ -154,7 +154,7 @@ class MimoV2Model(TextModel):
|
||||
self.gguf_writer.add_expert_count(self.hparams["n_routed_experts"])
|
||||
self.gguf_writer.add_expert_feed_forward_length(self.hparams["moe_intermediate_size"])
|
||||
|
||||
rope_dim = int(self.hparams["head_dim"] * self.hparams["partial_rotary_factor"])
|
||||
rope_dim = int(self.hparams["head_dim"] * self.rope_parameters["partial_rotary_factor"])
|
||||
self.gguf_writer.add_rope_dimension_count(rope_dim)
|
||||
|
||||
self.gguf_writer.add_layer_norm_rms_eps(self.hparams.get("layernorm_epsilon", 1e-5))
|
||||
|
||||
+6
-10
@@ -32,11 +32,9 @@ class MiniCPMModel(TextModel):
|
||||
def generate_extra_tensors(self) -> Iterable[tuple[str, Tensor]]:
|
||||
rope_dims = self.hparams["hidden_size"] // self.hparams["num_attention_heads"]
|
||||
|
||||
rope_scaling = self.find_hparam(['rope_scaling'], True)
|
||||
if rope_scaling is not None:
|
||||
long_factors = rope_scaling.get('long_factor', None)
|
||||
short_factors = rope_scaling.get('short_factor', None)
|
||||
|
||||
long_factors = self.rope_parameters.get('long_factor')
|
||||
short_factors = self.rope_parameters.get('short_factor')
|
||||
if long_factors or short_factors:
|
||||
if long_factors is None or short_factors is None:
|
||||
raise KeyError('Missing the required key rope_scaling.long_factor or rope_scaling_short_factor')
|
||||
|
||||
@@ -85,13 +83,11 @@ class MiniCPM3Model(TextModel):
|
||||
self.gguf_writer.add_rope_dimension_count(hparams["qk_rope_head_dim"])
|
||||
|
||||
def generate_extra_tensors(self) -> Iterable[tuple[str, Tensor]]:
|
||||
rope_scaling = self.find_hparam(['rope_scaling'], True)
|
||||
if rope_scaling is not None:
|
||||
long_factors = self.rope_parameters.get('long_factor')
|
||||
short_factors = self.rope_parameters.get('short_factor')
|
||||
if long_factors or short_factors:
|
||||
rope_dims = self.hparams["qk_rope_head_dim"]
|
||||
|
||||
long_factors = rope_scaling.get('long_factor', None)
|
||||
short_factors = rope_scaling.get('short_factor', None)
|
||||
|
||||
if long_factors is None or short_factors is None:
|
||||
raise KeyError('Missing the required key rope_scaling.long_factor or rope_scaling_short_factor')
|
||||
|
||||
|
||||
@@ -125,17 +125,18 @@ class NemotronModel(TextModel):
|
||||
self.gguf_writer.add_layer_norm_eps(f_norm_eps)
|
||||
|
||||
# * Partial RoPE
|
||||
rot_pct = self.find_hparam(["partial_rotary_factor", "rope_pct", "rope_percent"])
|
||||
rot_pct = self.rope_parameters["partial_rotary_factor"]
|
||||
n_embd = self.find_hparam(["hidden_size", "n_embd"])
|
||||
n_head = self.find_hparam(["num_attention_heads", "n_head"])
|
||||
self.gguf_writer.add_rope_dimension_count(int(rot_pct * n_embd) // n_head)
|
||||
|
||||
# * RopeScaling for Nemotron
|
||||
if "rope_scaling" not in self.hparams or self.hparams["rope_scaling"] is None:
|
||||
factor = self.hparams.get("factor") or self.rope_parameters.get("factor")
|
||||
if factor is None:
|
||||
self.gguf_writer.add_rope_scaling_type(gguf.RopeScalingType.NONE)
|
||||
else:
|
||||
self.gguf_writer.add_rope_scaling_type(gguf.RopeScalingType.LINEAR)
|
||||
self.gguf_writer.add_rope_scaling_factor(self.hparams["factor"])
|
||||
self.gguf_writer.add_rope_scaling_factor(factor)
|
||||
|
||||
def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iterable[tuple[str, Tensor]]:
|
||||
# * Adding +1 to LayerNorm's weights here to implement layernorm1p w/o changing anything on the GGML engine side
|
||||
|
||||
+9
-11
@@ -18,7 +18,7 @@ class Phi2Model(TextModel):
|
||||
model_arch = gguf.MODEL_ARCH.PHI2
|
||||
|
||||
def set_gguf_parameters(self):
|
||||
rot_pct = self.find_hparam(["partial_rotary_factor"])
|
||||
rot_pct = self.rope_parameters["partial_rotary_factor"]
|
||||
n_embd = self.find_hparam(["hidden_size", "n_embd"])
|
||||
n_head = self.find_hparam(["num_attention_heads", "n_head"])
|
||||
|
||||
@@ -149,8 +149,8 @@ class Phi3MiniModel(TextModel):
|
||||
n_head_kv = self.find_hparam(["num_key_value_heads", "n_head_kv"])
|
||||
rms_eps = self.find_hparam(["rms_norm_eps"])
|
||||
max_pos_embds = self.find_hparam(["n_positions", "max_position_embeddings"])
|
||||
orig_max_pos_embds = self.find_hparam(["original_max_position_embeddings"])
|
||||
rot_pct = self.hparams.get("partial_rotary_factor", 1.0)
|
||||
orig_max_pos_embds = self.rope_parameters["original_max_position_embeddings"]
|
||||
rot_pct = self.rope_parameters.get("partial_rotary_factor", 1.0)
|
||||
rope_dims = int(rot_pct * n_embd) // n_head
|
||||
|
||||
self.gguf_writer.add_context_length(max_pos_embds)
|
||||
@@ -174,18 +174,19 @@ class Phi3MiniModel(TextModel):
|
||||
n_embd = self.find_hparam(["hidden_size", "n_embd"])
|
||||
n_head = self.find_hparam(["num_attention_heads", "n_head"])
|
||||
max_pos_embds = self.find_hparam(["n_positions", "max_position_embeddings"])
|
||||
orig_max_pos_embds = self.find_hparam(["original_max_position_embeddings"])
|
||||
rot_pct = self.hparams.get("partial_rotary_factor", 1.0)
|
||||
orig_max_pos_embds = self.rope_parameters["original_max_position_embeddings"]
|
||||
rot_pct = self.rope_parameters.get("partial_rotary_factor", 1.0)
|
||||
rope_dims = int(rot_pct * n_embd) // n_head
|
||||
|
||||
# write rope scaling for long context (128k) model
|
||||
rope_scaling = self.find_hparam(['rope_scaling'], True)
|
||||
if rope_scaling is None:
|
||||
long_factors = self.rope_parameters.get('long_factor')
|
||||
short_factors = self.rope_parameters.get('short_factor')
|
||||
if not long_factors:
|
||||
return
|
||||
|
||||
scale = max_pos_embds / orig_max_pos_embds
|
||||
|
||||
rope_scaling_type = rope_scaling.get('rope_type', rope_scaling.get('type', '')).lower()
|
||||
rope_scaling_type = self.rope_parameters.get('rope_type', '').lower()
|
||||
if len(rope_scaling_type) == 0:
|
||||
raise KeyError('Missing the required key rope_scaling.type')
|
||||
|
||||
@@ -198,9 +199,6 @@ class Phi3MiniModel(TextModel):
|
||||
|
||||
self.gguf_writer.add_rope_scaling_attn_factors(attn_factor)
|
||||
|
||||
long_factors = rope_scaling.get('long_factor', None)
|
||||
short_factors = rope_scaling.get('short_factor', None)
|
||||
|
||||
if long_factors is None or short_factors is None:
|
||||
raise KeyError('Missing the required key rope_scaling.long_factor or rope_scaling_short_factor')
|
||||
|
||||
|
||||
+1
-1
@@ -280,7 +280,7 @@ class Qwen3NextModel(Qwen2MoeModel):
|
||||
self.gguf_writer.add_full_attention_interval(self.hparams.get("full_attention_interval", 4))
|
||||
if (rope_dim := self.hparams.get("head_dim")) is None:
|
||||
rope_dim = self.hparams["hidden_size"] // self.hparams["num_attention_heads"]
|
||||
self.gguf_writer.add_rope_dimension_count(int(rope_dim * self.hparams.get("partial_rotary_factor", 0.25)))
|
||||
self.gguf_writer.add_rope_dimension_count(int(rope_dim * self.rope_parameters.get("partial_rotary_factor", 0.25)))
|
||||
|
||||
@classmethod
|
||||
def filter_tensors(cls, item: tuple[str, Callable[[], Tensor]]) -> tuple[str, Callable[[], Tensor]] | None:
|
||||
|
||||
@@ -28,7 +28,7 @@ class StableLMModel(TextModel):
|
||||
self.gguf_writer.add_embedding_length(hparams["hidden_size"])
|
||||
self.gguf_writer.add_block_count(self.block_count)
|
||||
self.gguf_writer.add_feed_forward_length(hparams["intermediate_size"])
|
||||
rotary_factor = self.find_hparam(["partial_rotary_factor", "rope_pct"])
|
||||
rotary_factor = self.rope_parameters["partial_rotary_factor"]
|
||||
self.gguf_writer.add_rope_dimension_count(int(rotary_factor * (hparams["hidden_size"] // hparams["num_attention_heads"])))
|
||||
self.gguf_writer.add_head_count(hparams["num_attention_heads"])
|
||||
self.gguf_writer.add_head_count_kv(hparams["num_key_value_heads"])
|
||||
|
||||
+1
-1
@@ -314,7 +314,7 @@ class Step35Model(TextModel):
|
||||
factor = float(rope_params.get("factor", 8.0))
|
||||
low_freq_factor = float(rope_params.get("low_freq_factor", 1.0))
|
||||
high_freq_factor = float(rope_params.get("high_freq_factor", 4.0))
|
||||
old_context_len = int(rope_params.get("original_max_position_embeddings", self.hparams.get("original_max_position_embeddings", 8192)))
|
||||
old_context_len = int(rope_params.get("original_max_position_embeddings", 8192))
|
||||
|
||||
low_freq_wavelen = old_context_len / low_freq_factor
|
||||
high_freq_wavelen = old_context_len / high_freq_factor
|
||||
|
||||
@@ -198,18 +198,18 @@ class BuiltinRule:
|
||||
SPACE_RULE = '| " " | "\\n"{1,2} [ \\t]{0,20}'
|
||||
|
||||
PRIMITIVE_RULES = {
|
||||
'boolean' : BuiltinRule('("true" | "false") space', []),
|
||||
'boolean' : BuiltinRule('("true" | "false")', []),
|
||||
'decimal-part' : BuiltinRule('[0-9]{1,16}', []),
|
||||
'integral-part': BuiltinRule('[0] | [1-9] [0-9]{0,15}', []),
|
||||
'number' : BuiltinRule('("-"? integral-part) ("." decimal-part)? ([eE] [-+]? integral-part)? space', ['integral-part', 'decimal-part']),
|
||||
'integer' : BuiltinRule('("-"? integral-part) space', ['integral-part']),
|
||||
'number' : BuiltinRule('("-"? integral-part) ("." decimal-part)? ([eE] [-+]? integral-part)?', ['integral-part', 'decimal-part']),
|
||||
'integer' : BuiltinRule('("-"? integral-part)', ['integral-part']),
|
||||
'value' : BuiltinRule('object | array | string | number | boolean | null', ['object', 'array', 'string', 'number', 'boolean', 'null']),
|
||||
'object' : BuiltinRule('"{" space ( string ":" space value ("," space string ":" space value)* )? "}" space', ['string', 'value']),
|
||||
'array' : BuiltinRule('"[" space ( value ("," space value)* )? "]" space', ['value']),
|
||||
'uuid' : BuiltinRule(r'"\"" [0-9a-fA-F]{8} "-" [0-9a-fA-F]{4} "-" [0-9a-fA-F]{4} "-" [0-9a-fA-F]{4} "-" [0-9a-fA-F]{12} "\"" space', []),
|
||||
'object' : BuiltinRule('"{" space ( string ":" space value ("," space string ":" space value)* )? space "}"', ['string', 'value']),
|
||||
'array' : BuiltinRule('"[" space ( value ("," space value)* )? space "]"', ['value']),
|
||||
'uuid' : BuiltinRule(r'"\"" [0-9a-fA-F]{8} "-" [0-9a-fA-F]{4} "-" [0-9a-fA-F]{4} "-" [0-9a-fA-F]{4} "-" [0-9a-fA-F]{12} "\""', []),
|
||||
'char' : BuiltinRule(r'[^"\\\x7F\x00-\x1F] | [\\] (["\\bfnrt] | "u" [0-9a-fA-F]{4})', []),
|
||||
'string' : BuiltinRule(r'"\"" char* "\"" space', ['char']),
|
||||
'null' : BuiltinRule('"null" space', []),
|
||||
'string' : BuiltinRule(r'"\"" char* "\""', ['char']),
|
||||
'null' : BuiltinRule('"null"', []),
|
||||
}
|
||||
|
||||
# TODO: support "uri", "email" string formats
|
||||
@@ -217,9 +217,9 @@ STRING_FORMAT_RULES = {
|
||||
'date' : BuiltinRule('[0-9]{4} "-" ( "0" [1-9] | "1" [0-2] ) "-" ( \"0\" [1-9] | [1-2] [0-9] | "3" [0-1] )', []),
|
||||
'time' : BuiltinRule('([01] [0-9] | "2" [0-3]) ":" [0-5] [0-9] ":" [0-5] [0-9] ( "." [0-9]{3} )? ( "Z" | ( "+" | "-" ) ( [01] [0-9] | "2" [0-3] ) ":" [0-5] [0-9] )', []),
|
||||
'date-time' : BuiltinRule('date "T" time', ['date', 'time']),
|
||||
'date-string' : BuiltinRule('"\\"" date "\\"" space', ['date']),
|
||||
'time-string' : BuiltinRule('"\\"" time "\\"" space', ['time']),
|
||||
'date-time-string': BuiltinRule('"\\"" date-time "\\"" space', ['date-time']),
|
||||
'date-string' : BuiltinRule('"\\"" date "\\""', ['date']),
|
||||
'time-string' : BuiltinRule('"\\"" time "\\""', ['time']),
|
||||
'date-time-string': BuiltinRule('"\\"" date-time "\\""', ['date-time']),
|
||||
}
|
||||
|
||||
DOTALL = '[\\U00000000-\\U0010FFFF]'
|
||||
@@ -319,7 +319,7 @@ class SchemaConverter:
|
||||
out.append(f'[^"{"".join(rejects)}] {char_rule}*')
|
||||
visit(trie)
|
||||
|
||||
out.append(f' ){"" if trie.is_end_of_string else "?"} ["] space')
|
||||
out.append(f' ){"" if trie.is_end_of_string else "?"} ["]')
|
||||
return ''.join(out)
|
||||
|
||||
def _add_rule(self, name, rule):
|
||||
@@ -549,7 +549,7 @@ class SchemaConverter:
|
||||
return self._add_rule(
|
||||
name,
|
||||
to_rule(transform()) if self._raw_pattern \
|
||||
else "\"\\\"\" (" + to_rule(transform()) + ") \"\\\"\" space")
|
||||
else "\"\\\"\" (" + to_rule(transform()) + ") \"\\\"\"")
|
||||
|
||||
|
||||
def _resolve_ref(self, ref):
|
||||
@@ -580,10 +580,10 @@ class SchemaConverter:
|
||||
return self._add_rule(rule_name, self._generate_union_rule(name, [{**schema, 'type': t} for t in schema_type]))
|
||||
|
||||
elif 'const' in schema:
|
||||
return self._add_rule(rule_name, self._generate_constant_rule(schema['const']) + ' space')
|
||||
return self._add_rule(rule_name, self._generate_constant_rule(schema['const']))
|
||||
|
||||
elif 'enum' in schema:
|
||||
rule = '(' + ' | '.join((self._generate_constant_rule(v) for v in schema['enum'])) + ') space'
|
||||
rule = '(' + ' | '.join((self._generate_constant_rule(v) for v in schema['enum'])) + ')'
|
||||
return self._add_rule(rule_name, rule)
|
||||
|
||||
elif schema_type in (None, 'object') and \
|
||||
@@ -624,7 +624,7 @@ class SchemaConverter:
|
||||
enum_intersection &= s
|
||||
|
||||
if enum_intersection:
|
||||
rule = '(' + ' | '.join((self._generate_constant_rule(v) for v in sorted(enum_intersection))) + ') space'
|
||||
rule = '(' + ' | '.join((self._generate_constant_rule(v) for v in sorted(enum_intersection))) + ')'
|
||||
return self._add_rule(rule_name, rule)
|
||||
|
||||
return self._add_rule(rule_name, self._build_object_rule(properties, required, hybrid_name, additional_properties=None))
|
||||
@@ -638,12 +638,12 @@ class SchemaConverter:
|
||||
' "," space '.join(
|
||||
self.visit(item, f'{name}{"-" if name else ""}tuple-{i}')
|
||||
for i, item in enumerate(items)) +
|
||||
' "]" space')
|
||||
' space "]"')
|
||||
else:
|
||||
item_rule_name = self.visit(items, f'{name}{"-" if name else ""}item')
|
||||
min_items = schema.get("minItems", 0)
|
||||
max_items = schema.get("maxItems")
|
||||
return self._add_rule(rule_name, '"[" space ' + _build_repetition(item_rule_name, min_items, max_items, separator_rule='"," space') + ' "]" space')
|
||||
return self._add_rule(rule_name, '"[" space ' + _build_repetition(item_rule_name, min_items, max_items, separator_rule='"," space') + ' space "]"')
|
||||
|
||||
elif schema_type in (None, 'string') and 'pattern' in schema:
|
||||
return self._visit_pattern(schema['pattern'], rule_name)
|
||||
@@ -663,7 +663,7 @@ class SchemaConverter:
|
||||
min_len = schema.get('minLength', 0)
|
||||
max_len = schema.get('maxLength')
|
||||
|
||||
return self._add_rule(rule_name, r'"\"" ' + _build_repetition(char_rule, min_len, max_len) + r' "\"" space')
|
||||
return self._add_rule(rule_name, r'"\"" ' + _build_repetition(char_rule, min_len, max_len) + r' "\""')
|
||||
|
||||
elif schema_type in (None, 'integer') and \
|
||||
('minimum' in schema or 'exclusiveMinimum' in schema or 'maximum' in schema or 'exclusiveMaximum' in schema):
|
||||
@@ -680,7 +680,7 @@ class SchemaConverter:
|
||||
|
||||
out = ["("]
|
||||
_generate_min_max_int(min_value, max_value, out)
|
||||
out.append(") space")
|
||||
out.append(")")
|
||||
return self._add_rule(rule_name, ''.join(out))
|
||||
|
||||
elif (schema_type == 'object') or (len(schema) == 0):
|
||||
@@ -765,7 +765,7 @@ class SchemaConverter:
|
||||
rule += ' )'
|
||||
rule += ' )?'
|
||||
|
||||
rule += ' "}" space'
|
||||
rule += ' space "}"'
|
||||
|
||||
return rule
|
||||
|
||||
|
||||
+1
-1
@@ -5,7 +5,7 @@ project("ggml" C CXX ASM)
|
||||
### GGML Version
|
||||
set(GGML_VERSION_MAJOR 0)
|
||||
set(GGML_VERSION_MINOR 15)
|
||||
set(GGML_VERSION_PATCH 1)
|
||||
set(GGML_VERSION_PATCH 2)
|
||||
set(GGML_VERSION_BASE "${GGML_VERSION_MAJOR}.${GGML_VERSION_MINOR}.${GGML_VERSION_PATCH}")
|
||||
|
||||
list(APPEND CMAKE_MODULE_PATH "${CMAKE_CURRENT_SOURCE_DIR}/cmake/")
|
||||
|
||||
@@ -2417,15 +2417,14 @@ void ggml_backend_amx_mul_mat(const ggml_compute_params * params, struct ggml_te
|
||||
// Q4_K, Q5_K, Q6_K, IQ4_XS handles 8 TILE_K per blck_size
|
||||
GGML_ASSERT(TILE_K == blck_size || TILE_K * 8 == blck_size);
|
||||
|
||||
parallel_for_ggml(params, n_batch, [&](int begin, int end) {
|
||||
for (int batch_idx = begin; batch_idx < end; ++batch_idx) {
|
||||
parallel_for_ggml(params, n_batch * M, [&](int begin, int end) {
|
||||
for (int idx = begin; idx < end; ++idx) {
|
||||
int batch_idx = idx / M;
|
||||
int m = idx % M;
|
||||
int64_t src1_offset = ggml_batch_offset(src1, batch_idx, ne2);
|
||||
const float * A_data = (const float *)((const char *)src1->data + src1_offset);
|
||||
char * wdata_batch = (char *)wdata + batch_idx * M * row_size_A;
|
||||
|
||||
for (int m = 0; m < M; ++m) {
|
||||
from_float<vec_dot_type>(A_data + m * K, wdata_batch + m * row_size_A, K);
|
||||
}
|
||||
from_float<vec_dot_type>(A_data + m * K, wdata_batch + m * row_size_A, K);
|
||||
}
|
||||
});
|
||||
});
|
||||
|
||||
@@ -2345,7 +2345,7 @@ class tinyBLAS_Q0_PPC {
|
||||
else if (n_aligned % 16 == 0) nc = 16;
|
||||
else nc = 8;
|
||||
}
|
||||
bool can_use_tiled = n_aligned > 0 && (m % mc == 0) && (k % kc == 0);
|
||||
bool can_use_tiled = n_aligned > 0 && (m % mc == 0);
|
||||
if (can_use_tiled) {
|
||||
matmul_tiled(m, n_aligned, mc, nc, kc);
|
||||
if (n > n_aligned) {
|
||||
@@ -3063,13 +3063,14 @@ class tinyBLAS_Q0_PPC {
|
||||
int64_t ii = (job / xtiles) * mc;
|
||||
int64_t jj = (job % xtiles) * nc;
|
||||
for (int64_t kk = 0; kk < k; kk += kc) {
|
||||
int64_t k_cur = MIN(kc, k - kk);
|
||||
if constexpr(is_Ablock_q4) {
|
||||
packNormal_q4_fp16(A + ii * lda + kk, lda, mc, kc, (uint8_t *)A_pack);
|
||||
packNormal_q4_fp16(A + ii * lda + kk, lda, mc, k_cur, (uint8_t *)A_pack);
|
||||
} else {
|
||||
packNormal_q8_fp16(A + ii * lda + kk, lda, mc, kc, (uint8_t *)A_pack);
|
||||
packNormal_q8_fp16(A + ii * lda + kk, lda, mc, k_cur, (uint8_t *)A_pack);
|
||||
}
|
||||
packNormal_q8_fp16(B + jj * ldb + kk, ldb, nc, kc, (uint8_t *)B_pack);
|
||||
KERNEL_Q0(ii, jj, mc, nc, kc, kk, A_pack, B_pack);
|
||||
packNormal_q8_fp16(B + jj * ldb + kk, ldb, nc, k_cur, (uint8_t *)B_pack);
|
||||
KERNEL_Q0(ii, jj, mc, nc, k_cur, kk, A_pack, B_pack);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
@@ -0,0 +1,81 @@
|
||||
#include "col2im-1d.cuh"
|
||||
#include "convert.cuh"
|
||||
|
||||
// col2im_1d: scatter-add GEMM columns to 1D signal (gather approach)
|
||||
// columns: [K*OC, T_in] -> output: [T_out, OC]
|
||||
// Supports F32, F16, BF16 data with F32 accumulator.
|
||||
|
||||
template <typename T>
|
||||
static __global__ void col2im_1d_kernel(
|
||||
const T * __restrict__ col,
|
||||
T * __restrict__ dst,
|
||||
const int T_in, const uint3 T_out_fd,
|
||||
const int OC, const int K, const int K_OC,
|
||||
const int s0, const int p0, const int total) {
|
||||
|
||||
const int idx = threadIdx.x + blockIdx.x * blockDim.x;
|
||||
if (idx >= total) return;
|
||||
|
||||
// dst layout: [T_out, OC], ne[0]=T_out fastest
|
||||
const uint2 qr = fast_div_modulo((uint32_t)idx, T_out_fd); // qr.x = idx / T_out, qr.y = idx % T_out
|
||||
const int oc = (int)qr.x;
|
||||
const int t_out = (int)qr.y;
|
||||
const int t_abs = t_out + p0; // absolute position in uncropped signal
|
||||
|
||||
// Gather: find all (t_in, k) where t_in*s + k == t_abs, 0 <= k < K
|
||||
int t_in_min = (t_abs - K + s0) / s0; // ceil((t_abs - K + 1) / s)
|
||||
if (t_in_min < 0) t_in_min = 0;
|
||||
int t_in_max = t_abs / s0;
|
||||
if (t_in_max >= T_in) t_in_max = T_in - 1;
|
||||
|
||||
float sum = 0.0f;
|
||||
for (int t_in = t_in_min; t_in <= t_in_max; t_in++) {
|
||||
const int k = t_abs - t_in * s0;
|
||||
// col layout: [K*OC, T_in], column index = oc * K + k
|
||||
sum += ggml_cuda_cast<float>(col[(oc * K + k) + t_in * K_OC]);
|
||||
}
|
||||
|
||||
dst[idx] = ggml_cuda_cast<T>(sum);
|
||||
}
|
||||
|
||||
void ggml_cuda_op_col2im_1d(ggml_backend_cuda_context & ctx, ggml_tensor * dst) {
|
||||
const ggml_tensor * src0 = dst->src[0];
|
||||
cudaStream_t stream = ctx.stream();
|
||||
|
||||
GGML_ASSERT(ggml_is_contiguous(src0));
|
||||
|
||||
const int32_t s0 = ((const int32_t *)(dst->op_params))[0];
|
||||
const int32_t OC = ((const int32_t *)(dst->op_params))[1];
|
||||
const int32_t p0 = ((const int32_t *)(dst->op_params))[2];
|
||||
|
||||
const int K_OC = (int) src0->ne[0];
|
||||
const int T_in = (int) src0->ne[1];
|
||||
const int K = K_OC / OC;
|
||||
const int T_out = (int) dst->ne[0];
|
||||
|
||||
const uint3 T_out_fd = init_fastdiv_values((uint32_t)T_out);
|
||||
|
||||
const int total = T_out * OC;
|
||||
const int block_size = 256;
|
||||
const int num_blocks = (total + block_size - 1) / block_size;
|
||||
|
||||
switch (src0->type) {
|
||||
case GGML_TYPE_F32: {
|
||||
col2im_1d_kernel<<<num_blocks, block_size, 0, stream>>>(
|
||||
(const float *)src0->data, (float *)dst->data,
|
||||
T_in, T_out_fd, OC, K, K_OC, s0, p0, total);
|
||||
} break;
|
||||
case GGML_TYPE_F16: {
|
||||
col2im_1d_kernel<<<num_blocks, block_size, 0, stream>>>(
|
||||
(const half *)src0->data, (half *)dst->data,
|
||||
T_in, T_out_fd, OC, K, K_OC, s0, p0, total);
|
||||
} break;
|
||||
case GGML_TYPE_BF16: {
|
||||
col2im_1d_kernel<<<num_blocks, block_size, 0, stream>>>(
|
||||
(const nv_bfloat16 *)src0->data, (nv_bfloat16 *)dst->data,
|
||||
T_in, T_out_fd, OC, K, K_OC, s0, p0, total);
|
||||
} break;
|
||||
default:
|
||||
GGML_ABORT("col2im_1d: unsupported type");
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,3 @@
|
||||
#include "common.cuh"
|
||||
|
||||
void ggml_cuda_op_col2im_1d(ggml_backend_cuda_context & ctx, ggml_tensor * dst);
|
||||
@@ -11,6 +11,7 @@
|
||||
#include "ggml-cuda/argsort.cuh"
|
||||
#include "ggml-cuda/binbcast.cuh"
|
||||
#include "ggml-cuda/clamp.cuh"
|
||||
#include "ggml-cuda/col2im-1d.cuh"
|
||||
#include "ggml-cuda/concat.cuh"
|
||||
#include "ggml-cuda/conv-transpose-1d.cuh"
|
||||
#include "ggml-cuda/conv2d.cuh"
|
||||
@@ -3051,6 +3052,9 @@ static bool ggml_cuda_compute_forward(ggml_backend_cuda_context & ctx, struct gg
|
||||
case GGML_OP_CONV_TRANSPOSE_1D:
|
||||
ggml_cuda_op_conv_transpose_1d(ctx,dst);
|
||||
break;
|
||||
case GGML_OP_COL2IM_1D:
|
||||
ggml_cuda_op_col2im_1d(ctx, dst);
|
||||
break;
|
||||
case GGML_OP_POOL_2D:
|
||||
ggml_cuda_op_pool2d(ctx, dst);
|
||||
break;
|
||||
@@ -5316,6 +5320,14 @@ static bool ggml_backend_cuda_device_supports_op(ggml_backend_dev_t dev, const g
|
||||
}
|
||||
return false;
|
||||
} break;
|
||||
case GGML_OP_COL2IM_1D:
|
||||
{
|
||||
ggml_type src0_type = op->src[0]->type;
|
||||
return (src0_type == GGML_TYPE_F32 || src0_type == GGML_TYPE_F16 || src0_type == GGML_TYPE_BF16) &&
|
||||
op->type == src0_type &&
|
||||
ggml_is_contiguous(op->src[0]) &&
|
||||
ggml_is_contiguous(op);
|
||||
} break;
|
||||
case GGML_OP_SILU_BACK:
|
||||
return ggml_is_contiguous(op->src[0]) && op->src[0]->type == GGML_TYPE_F32;
|
||||
break;
|
||||
|
||||
@@ -183,24 +183,25 @@ static inline void hvx_transpose_32x32_f32(HVX_Vector m[32]) {
|
||||
// transposed into VTCM.
|
||||
//
|
||||
// VTCM layouts (per thread):
|
||||
// src1_T : {d_inner_per_thread, d_conv} — staged once per launch (small).
|
||||
// src0_T : {d_inner_tile, ncs} — staged per d_inner-tile.
|
||||
// src1_T : {d_inner_stride, d_conv} - staged once per launch (small).
|
||||
// src0_T : {d_inner_tile, ncs} - staged per d_inner-tile.
|
||||
//
|
||||
// d_inner_tile is chosen so that per-thread VTCM stays under the budget.
|
||||
// Each thread iterates ceil(d_inner_per_thread d_inner_tile) tiles serially.
|
||||
#define HTP_SSM_CONV_VTCM_BUDGET (1u << 20) // 1 MiB per thread
|
||||
|
||||
// Scalar transpose: src1 {d_conv, d_inner} (DDR) -> {d_inner_per_thread, d_conv} (VTCM)
|
||||
// Scalar transpose: src1 {d_conv, d_inner} (DDR) -> {d_inner_stride, d_conv} (VTCM)
|
||||
static inline void transpose_src1(const float * src1_data,
|
||||
uint32_t src1_stride_inner,
|
||||
uint32_t i1_off,
|
||||
uint32_t d_inner_per_thread,
|
||||
uint32_t d_inner_stride,
|
||||
uint32_t d_conv,
|
||||
float * src1_T) {
|
||||
for (uint32_t i = 0; i < d_inner_per_thread; ++i) {
|
||||
const float * src_row = src1_data + (i1_off + i) * src1_stride_inner;
|
||||
for (uint32_t j = 0; j < d_conv; ++j) {
|
||||
src1_T[j * d_inner_per_thread + i] = src_row[j];
|
||||
src1_T[j * d_inner_stride + i] = src_row[j];
|
||||
}
|
||||
}
|
||||
}
|
||||
@@ -280,6 +281,7 @@ static void ssm_conv_thread_f32_f32_hvx(unsigned int nth, unsigned int ith, void
|
||||
}
|
||||
|
||||
const uint32_t d_inner_per_thread = ir1 - ir0;
|
||||
const uint32_t d_inner_stride = scctx->nrows_per_thread;
|
||||
const uint32_t d_inner_tile = scctx->d_inner_tile;
|
||||
|
||||
const float * src0_data = (const float *) src0->data;
|
||||
@@ -290,8 +292,8 @@ static void ssm_conv_thread_f32_f32_hvx(unsigned int nth, unsigned int ith, void
|
||||
float * src0_T = (float *)(octx->src0_spad.data + ith * octx->src0_spad.size_per_thread);
|
||||
float * src1_T = (float *)(octx->src1_spad.data + ith * octx->src1_spad.size_per_thread);
|
||||
|
||||
// Stage src1 weights once into VTCM in {d_inner_per_thread, d_conv} layout.
|
||||
transpose_src1(src1_data, src1_stride_inner, ir0, d_inner_per_thread, d_conv, src1_T);
|
||||
// Stage src1 weights once into VTCM in {d_inner_stride, d_conv} layout.
|
||||
transpose_src1(src1_data, src1_stride_inner, ir0, d_inner_per_thread, d_inner_stride, d_conv, src1_T);
|
||||
|
||||
const uint32_t C_TILE = VLEN_FP32;
|
||||
|
||||
@@ -314,7 +316,7 @@ static void ssm_conv_thread_f32_f32_hvx(unsigned int nth, unsigned int ith, void
|
||||
HVX_Vector acc = hvx_vec_splat_f32(0.0f);
|
||||
for (uint32_t j = 0; j < d_conv; ++j) {
|
||||
HVX_Vector x = *(const HVX_Vector *) (src0_T + (t + j) * d_inner_tile + cb);
|
||||
HVX_Vector w = *(const HVX_Vector *) (src1_T + j * d_inner_per_thread + tile_off + cb);
|
||||
HVX_Vector w = *(const HVX_Vector *) (src1_T + j * d_inner_stride + tile_off + cb);
|
||||
acc = Q6_Vqf32_vadd_Vqf32Vqf32(acc, Q6_Vqf32_vmpy_VsfVsf(x, w));
|
||||
}
|
||||
HVX_Vector res = Q6_Vsf_equals_Vqf32(acc);
|
||||
@@ -362,8 +364,7 @@ int op_ssm_conv_f32(struct htp_ops_context * octx) {
|
||||
use_hvx = 1;
|
||||
}
|
||||
|
||||
scctx.nrows_per_thread = (d_inner + n_threads - 1) / n_threads;
|
||||
scctx.nrows_per_thread += (scctx.nrows_per_thread & 1);
|
||||
scctx.nrows_per_thread = hex_round_up((d_inner + n_threads - 1) / n_threads, VLEN_FP32);
|
||||
|
||||
const uint32_t d_inner_per_thread = scctx.nrows_per_thread;
|
||||
const uint32_t ncs = src0->ne[0];
|
||||
|
||||
@@ -3788,7 +3788,7 @@ static void ggml_webgpu_init_memset_pipeline(webgpu_global_context & ctx) {
|
||||
ctx->memset_pipeline = ggml_webgpu_create_pipeline(ctx->device, wgsl_memset, "memset", constants);
|
||||
}
|
||||
|
||||
static void create_webgpu_device(ggml_backend_webgpu_reg_context * ctx) {
|
||||
static void ggml_backend_webgpu_request_adapter(wgpu::Instance & instance, wgpu::Adapter & adapter) {
|
||||
wgpu::RequestAdapterOptions options = {};
|
||||
|
||||
#ifndef __EMSCRIPTEN__
|
||||
@@ -3800,17 +3800,20 @@ static void create_webgpu_device(ggml_backend_webgpu_reg_context * ctx) {
|
||||
options.nextInChain = &adapterTogglesDesc;
|
||||
#endif
|
||||
|
||||
ctx->webgpu_global_ctx->instance.WaitAny(
|
||||
ctx->webgpu_global_ctx->instance.RequestAdapter(
|
||||
&options, wgpu::CallbackMode::AllowSpontaneous,
|
||||
[&ctx](wgpu::RequestAdapterStatus status, wgpu::Adapter adapter, const char * message) {
|
||||
if (status != wgpu::RequestAdapterStatus::Success) {
|
||||
GGML_LOG_ERROR("ggml_webgpu: Failed to get an adapter: %s\n", message);
|
||||
return;
|
||||
}
|
||||
ctx->webgpu_global_ctx->adapter = std::move(adapter);
|
||||
}),
|
||||
UINT64_MAX);
|
||||
instance.WaitAny(instance.RequestAdapter(
|
||||
&options, wgpu::CallbackMode::AllowSpontaneous,
|
||||
[&adapter](wgpu::RequestAdapterStatus status, wgpu::Adapter _adapter, const char * message) {
|
||||
if (status != wgpu::RequestAdapterStatus::Success) {
|
||||
GGML_LOG_ERROR("ggml_webgpu: Failed to get an adapter: %s\n", message);
|
||||
return;
|
||||
}
|
||||
adapter = std::move(_adapter);
|
||||
}),
|
||||
UINT64_MAX);
|
||||
}
|
||||
|
||||
static void create_webgpu_device(ggml_backend_webgpu_reg_context * ctx) {
|
||||
ggml_backend_webgpu_request_adapter(ctx->webgpu_global_ctx->instance, ctx->webgpu_global_ctx->adapter);
|
||||
GGML_ASSERT(ctx->webgpu_global_ctx->adapter != nullptr);
|
||||
|
||||
ctx->webgpu_global_ctx->adapter.GetLimits(&ctx->webgpu_global_ctx->capabilities.limits);
|
||||
@@ -4543,20 +4546,7 @@ ggml_backend_reg_t ggml_backend_webgpu_reg() {
|
||||
// Probe for adapter support
|
||||
wgpu::Adapter adapter;
|
||||
if (ctx->webgpu_global_ctx->instance != nullptr) {
|
||||
wgpu::RequestAdapterOptions options = {};
|
||||
|
||||
// probe for adapter support
|
||||
ctx->webgpu_global_ctx->instance.WaitAny(
|
||||
ctx->webgpu_global_ctx->instance.RequestAdapter(
|
||||
&options, wgpu::CallbackMode::AllowSpontaneous,
|
||||
[&adapter](wgpu::RequestAdapterStatus status, wgpu::Adapter _adapter, const char * message) {
|
||||
if (status != wgpu::RequestAdapterStatus::Success) {
|
||||
GGML_LOG_ERROR("ggml_webgpu: Failed to get an adapter: %s\n", message);
|
||||
return;
|
||||
}
|
||||
adapter = std::move(_adapter);
|
||||
}),
|
||||
UINT64_MAX);
|
||||
ggml_backend_webgpu_request_adapter(ctx->webgpu_global_ctx->instance, adapter);
|
||||
}
|
||||
|
||||
// WebGPU backend requires f16 support and, on native, implicit device synchronization.
|
||||
|
||||
+7
-10
@@ -600,18 +600,15 @@ FILE * ggml_fopen(const char * fname, const char * mode) {
|
||||
// convert fname (UTF-8)
|
||||
wchar_t * wfname = ggml_mbstowcs(fname);
|
||||
if (wfname) {
|
||||
// convert mode (ANSI)
|
||||
wchar_t * wmode = GGML_MALLOC((strlen(mode) + 1) * sizeof(wchar_t));
|
||||
wchar_t * wmode_p = wmode;
|
||||
do {
|
||||
*wmode_p++ = (wchar_t)*mode;
|
||||
} while (*mode++);
|
||||
|
||||
// open file
|
||||
file = _wfopen(wfname, wmode);
|
||||
// convert mode (UTF-8)
|
||||
wchar_t * wmode = ggml_mbstowcs(mode);
|
||||
if (wmode) {
|
||||
// open file
|
||||
file = _wfopen(wfname, wmode);
|
||||
GGML_FREE(wmode);
|
||||
}
|
||||
|
||||
GGML_FREE(wfname);
|
||||
GGML_FREE(wmode);
|
||||
}
|
||||
|
||||
return file;
|
||||
|
||||
+9
-8
@@ -558,14 +558,15 @@ extern "C" {
|
||||
LLAMA_API const struct llama_vocab * llama_model_get_vocab(const struct llama_model * model);
|
||||
LLAMA_API enum llama_rope_type llama_model_rope_type(const struct llama_model * model);
|
||||
|
||||
LLAMA_API int32_t llama_model_n_ctx_train(const struct llama_model * model);
|
||||
LLAMA_API int32_t llama_model_n_embd (const struct llama_model * model);
|
||||
LLAMA_API int32_t llama_model_n_embd_inp (const struct llama_model * model);
|
||||
LLAMA_API int32_t llama_model_n_embd_out (const struct llama_model * model);
|
||||
LLAMA_API int32_t llama_model_n_layer (const struct llama_model * model);
|
||||
LLAMA_API int32_t llama_model_n_head (const struct llama_model * model);
|
||||
LLAMA_API int32_t llama_model_n_head_kv (const struct llama_model * model);
|
||||
LLAMA_API int32_t llama_model_n_swa (const struct llama_model * model);
|
||||
LLAMA_API int32_t llama_model_n_ctx_train (const struct llama_model * model);
|
||||
LLAMA_API int32_t llama_model_n_embd (const struct llama_model * model);
|
||||
LLAMA_API int32_t llama_model_n_embd_inp (const struct llama_model * model);
|
||||
LLAMA_API int32_t llama_model_n_embd_out (const struct llama_model * model);
|
||||
LLAMA_API int32_t llama_model_n_layer (const struct llama_model * model);
|
||||
LLAMA_API int32_t llama_model_n_layer_nextn(const struct llama_model * model);
|
||||
LLAMA_API int32_t llama_model_n_head (const struct llama_model * model);
|
||||
LLAMA_API int32_t llama_model_n_head_kv (const struct llama_model * model);
|
||||
LLAMA_API int32_t llama_model_n_swa (const struct llama_model * model);
|
||||
|
||||
// Get the model's RoPE frequency scaling factor
|
||||
LLAMA_API float llama_model_rope_freq_scale_train(const struct llama_model * model);
|
||||
|
||||
@@ -1 +1 @@
|
||||
3af5f5760e19a96427f5f7a93b79cbdf3d4b265b
|
||||
707321c4cf6d21cb4bc831aa8b687dbf01a521ce
|
||||
|
||||
@@ -5,7 +5,7 @@ import os
|
||||
import sys
|
||||
import subprocess
|
||||
|
||||
HTTPLIB_VERSION = "refs/tags/v0.47.0"
|
||||
HTTPLIB_VERSION = "refs/tags/v0.48.0"
|
||||
|
||||
vendor = {
|
||||
"https://github.com/nlohmann/json/releases/latest/download/json.hpp": "vendor/nlohmann/json.hpp",
|
||||
|
||||
@@ -1156,6 +1156,10 @@ void llama_context::set_embeddings_layer_inp(uint32_t lid, bool enable) {
|
||||
sched_need_reserve = true;
|
||||
}
|
||||
|
||||
void llama_context::set_nextn_layer_offset(int32_t offset) {
|
||||
cparams.nextn_layer_offset = offset;
|
||||
}
|
||||
|
||||
void llama_context::set_causal_attn(bool value) {
|
||||
LLAMA_LOG_DEBUG("%s: value = %d\n", __func__, value);
|
||||
|
||||
@@ -3699,6 +3703,10 @@ void llama_set_embeddings_layer_inp(llama_context * ctx, uint32_t lid, bool valu
|
||||
ctx->set_embeddings_layer_inp(lid, value);
|
||||
}
|
||||
|
||||
void llama_set_nextn_layer_offset(llama_context * ctx, int32_t offset) {
|
||||
ctx->set_nextn_layer_offset(offset);
|
||||
}
|
||||
|
||||
llama_memory_t llama_get_memory(const struct llama_context * ctx) {
|
||||
if (!ctx) {
|
||||
return nullptr;
|
||||
|
||||
@@ -115,6 +115,7 @@ struct llama_context {
|
||||
void set_embeddings (bool value);
|
||||
void set_embeddings_nextn(bool value, bool masked);
|
||||
void set_embeddings_layer_inp(uint32_t lid, bool enable);
|
||||
void set_nextn_layer_offset(int32_t offset);
|
||||
void set_causal_attn(bool value);
|
||||
void set_warmup(bool value);
|
||||
|
||||
|
||||
@@ -18,6 +18,8 @@ struct llama_cparams {
|
||||
int32_t n_threads; // number of threads to use for generation
|
||||
int32_t n_threads_batch; // number of threads to use for batch processing
|
||||
|
||||
int32_t nextn_layer_offset = 0;
|
||||
|
||||
float rope_freq_base;
|
||||
float rope_freq_scale;
|
||||
|
||||
|
||||
@@ -95,6 +95,11 @@ LLAMA_API llama_memory_breakdown llama_get_memory_breakdown(const struct llama_c
|
||||
// If masked == false, output the embeddings for all tokens in the batch regardless of batch.logits
|
||||
LLAMA_API void llama_set_embeddings_nextn(struct llama_context * ctx, bool value, bool masked);
|
||||
|
||||
// Select which appended NextN block the DECODER_MTP graph runs (offset past
|
||||
// the trunk: il = n_layer() + offset). Used by the speculative NextN driver to
|
||||
// chain multiple trained NextN heads. Default 0 (first head).
|
||||
LLAMA_API void llama_set_nextn_layer_offset(struct llama_context * ctx, int32_t offset);
|
||||
|
||||
// mirrors:
|
||||
// LLAMA_API float * llama_get_embeddings(struct llama_context * ctx);
|
||||
LLAMA_API float * llama_get_embeddings_nextn(struct llama_context * ctx);
|
||||
|
||||
+9
-2
@@ -682,9 +682,16 @@ struct llm_graph_params {
|
||||
}
|
||||
}
|
||||
|
||||
// TODO: https://github.com/ggml-org/llama.cpp/pull/24340#discussion_r3448035248
|
||||
if (cparams.nextn_layer_offset != other.cparams.nextn_layer_offset) {
|
||||
return false;
|
||||
}
|
||||
|
||||
return
|
||||
cparams.embeddings == other.cparams.embeddings &&
|
||||
cparams.causal_attn == other.cparams.causal_attn &&
|
||||
cparams.embeddings == other.cparams.embeddings &&
|
||||
cparams.embeddings_nextn == other.cparams.embeddings_nextn &&
|
||||
cparams.embeddings_nextn_masked == other.cparams.embeddings_nextn_masked &&
|
||||
cparams.causal_attn == other.cparams.causal_attn &&
|
||||
arch == other.arch &&
|
||||
gtype == other.gtype &&
|
||||
cvec == other.cvec &&
|
||||
|
||||
@@ -2312,6 +2312,10 @@ int32_t llama_model_n_layer(const llama_model * model) {
|
||||
return model->hparams.n_layer();
|
||||
}
|
||||
|
||||
int32_t llama_model_n_layer_nextn(const llama_model * model) {
|
||||
return model->hparams.n_layer_nextn;
|
||||
}
|
||||
|
||||
int32_t llama_model_n_head(const llama_model * model) {
|
||||
return model->hparams.n_head();
|
||||
}
|
||||
|
||||
+2
-2
@@ -932,8 +932,8 @@ static void llama_model_quantize_impl(const std::string & fname_inp, const std::
|
||||
|
||||
// copy the KV pairs from the input file
|
||||
gguf_set_kv (ctx_out.get(), ml.metadata);
|
||||
gguf_set_val_u32(ctx_out.get(), "general.quantization_version", GGML_QNT_VERSION); // TODO: use LLM_KV
|
||||
gguf_set_val_u32(ctx_out.get(), "general.file_type", ftype); // TODO: use LLM_KV
|
||||
gguf_set_val_u32(ctx_out.get(), ml.llm_kv(LLM_KV_GENERAL_QUANTIZATION_VERSION).c_str(), GGML_QNT_VERSION);
|
||||
gguf_set_val_u32(ctx_out.get(), ml.llm_kv(LLM_KV_GENERAL_FILE_TYPE).c_str(), ftype);
|
||||
|
||||
// Remove split metadata
|
||||
gguf_remove_key(ctx_out.get(), ml.llm_kv(LLM_KV_SPLIT_NO).c_str());
|
||||
|
||||
@@ -101,11 +101,11 @@ void llama_model_glm_dsa::load_arch_tensors(llama_model_loader &) {
|
||||
layer.ffn_norm = create_tensor(tn(LLM_TENSOR_FFN_NORM, "weight", i), {n_embd}, flags);
|
||||
|
||||
// DSA indexer
|
||||
layer.indexer_k_norm = create_tensor(tn(LLM_TENSOR_INDEXER_K_NORM, "weight", i), {hparams.indexer_head_size}, flags);
|
||||
layer.indexer_k_norm_b = create_tensor(tn(LLM_TENSOR_INDEXER_K_NORM, "bias", i), {hparams.indexer_head_size}, flags);
|
||||
layer.indexer_proj = create_tensor(tn(LLM_TENSOR_INDEXER_PROJ, "weight", i), {n_embd, hparams.indexer_n_head}, flags);
|
||||
layer.indexer_attn_k = create_tensor(tn(LLM_TENSOR_INDEXER_ATTN_K, "weight", i), {n_embd, hparams.indexer_head_size}, flags);
|
||||
layer.indexer_attn_q_b = create_tensor(tn(LLM_TENSOR_INDEXER_ATTN_Q_B, "weight", i), {q_lora_rank, hparams.indexer_n_head * hparams.indexer_head_size}, flags);
|
||||
layer.indexer_k_norm = create_tensor(tn(LLM_TENSOR_INDEXER_K_NORM, "weight", i), {hparams.indexer_head_size}, flags | TENSOR_NOT_REQUIRED);
|
||||
layer.indexer_k_norm_b = create_tensor(tn(LLM_TENSOR_INDEXER_K_NORM, "bias", i), {hparams.indexer_head_size}, flags | TENSOR_NOT_REQUIRED);
|
||||
layer.indexer_proj = create_tensor(tn(LLM_TENSOR_INDEXER_PROJ, "weight", i), {n_embd, hparams.indexer_n_head}, flags | TENSOR_NOT_REQUIRED);
|
||||
layer.indexer_attn_k = create_tensor(tn(LLM_TENSOR_INDEXER_ATTN_K, "weight", i), {n_embd, hparams.indexer_head_size}, flags | TENSOR_NOT_REQUIRED);
|
||||
layer.indexer_attn_q_b = create_tensor(tn(LLM_TENSOR_INDEXER_ATTN_Q_B, "weight", i), {q_lora_rank, hparams.indexer_n_head * hparams.indexer_head_size}, flags | TENSOR_NOT_REQUIRED);
|
||||
if (i < (int) hparams.n_layer_dense_lead) {
|
||||
layer.ffn_gate = create_tensor(tn(LLM_TENSOR_FFN_GATE, "weight", i), {n_embd, n_ff}, flags);
|
||||
layer.ffn_down = create_tensor(tn(LLM_TENSOR_FFN_DOWN, "weight", i), { n_ff, n_embd}, flags);
|
||||
|
||||
@@ -156,6 +156,8 @@ llama_model_qwen35::graph::graph(const llama_model & model, const llm_graph_para
|
||||
|
||||
// MTP/NextN layers are loaded as extra decoder blocks but not executed in the main pass.
|
||||
for (int il = 0; il < n_layer; ++il) {
|
||||
res->t_layer_inp[il] = inpL;
|
||||
|
||||
ggml_tensor * inpSA = inpL;
|
||||
|
||||
cur = build_norm(inpL, model.layers[il].attn_norm, nullptr, LLM_NORM_RMS, il);
|
||||
|
||||
@@ -179,6 +179,8 @@ llama_model_qwen35moe::graph::graph(const llama_model & model, const llm_graph_p
|
||||
|
||||
// MTP/NextN layers are loaded as extra decoder blocks but not executed in the main pass.
|
||||
for (int il = 0; il < n_layer; ++il) {
|
||||
res->t_layer_inp[il] = inpL;
|
||||
|
||||
ggml_tensor * inpSA = inpL;
|
||||
|
||||
cur = build_norm(inpL, model.layers[il].attn_norm, nullptr, LLM_NORM_RMS, il);
|
||||
|
||||
+27
-28
@@ -112,7 +112,7 @@ void llama_model_step35::load_arch_tensors(llama_model_loader & ml) {
|
||||
layer.ffn_down_shexp = create_tensor(tn(LLM_TENSOR_FFN_DOWN_SHEXP, "weight", i), {hparams.n_ff_shexp, n_embd}, TENSOR_NOT_REQUIRED);
|
||||
};
|
||||
|
||||
auto load_block_mtp = [&](int i, bool is_first_mtp) {
|
||||
auto load_block_mtp = [&](int i) {
|
||||
auto & layer = layers[i];
|
||||
|
||||
const uint32_t n_head_l = hparams.n_head(i);
|
||||
@@ -121,15 +121,12 @@ void llama_model_step35::load_arch_tensors(llama_model_loader & ml) {
|
||||
|
||||
// The MTP block is a full Step3p5 decoder layer (mtp_block) plus the
|
||||
// NextN-specific wiring (enorm/hnorm/eh_proj + optional shared head).
|
||||
// `mtp_flags` becomes NOT_REQUIRED when the GGUF is trunk-only.
|
||||
//
|
||||
// Only the FIRST MTP block (i == n_main) is required for the
|
||||
// single-block MTP runtime; trailing MTP blocks are always tolerated
|
||||
// as missing so pruned GGUFs (block 0 only) load cleanly. Override
|
||||
// mtp_flags to NOT_REQUIRED for those.
|
||||
const int eff_mtp_flags = is_first_mtp ? mtp_flags : (mtp_flags | TENSOR_NOT_REQUIRED);
|
||||
// Multi-block MTP: every declared MTP block is required (the draft chain
|
||||
// runs all n_layer_nextn heads), so each block uses the captured
|
||||
// `mtp_flags` directly — already NOT_REQUIRED for a trunk-only GGUF,
|
||||
// which keeps that path correct.
|
||||
|
||||
layer.attn_norm = create_tensor(tn(LLM_TENSOR_ATTN_NORM, "weight", i), {n_embd}, eff_mtp_flags);
|
||||
layer.attn_norm = create_tensor(tn(LLM_TENSOR_ATTN_NORM, "weight", i), {n_embd}, mtp_flags);
|
||||
layer.attn_q_norm = create_tensor(tn(LLM_TENSOR_ATTN_Q_NORM, "weight", i), {n_embd_head_k}, TENSOR_NOT_REQUIRED);
|
||||
layer.attn_k_norm = create_tensor(tn(LLM_TENSOR_ATTN_K_NORM, "weight", i), {n_embd_head_k}, TENSOR_NOT_REQUIRED);
|
||||
|
||||
@@ -140,12 +137,12 @@ void llama_model_step35::load_arch_tensors(llama_model_loader & ml) {
|
||||
layer.rope_freqs = create_tensor(tn(LLM_TENSOR_ROPE_FREQS, "weight", i), {n_rot_max/2}, TENSOR_NOT_REQUIRED | TENSOR_DUPLICATED);
|
||||
}
|
||||
|
||||
create_tensor_qkv(layer, i, n_embd, n_embd_head_k * n_head_l, n_embd_k_gqa, n_embd_v_gqa, eff_mtp_flags);
|
||||
layer.wo = create_tensor(tn(LLM_TENSOR_ATTN_OUT, "weight", i), {n_embd_head_v * n_head_l, n_embd}, eff_mtp_flags);
|
||||
create_tensor_qkv(layer, i, n_embd, n_embd_head_k * n_head_l, n_embd_k_gqa, n_embd_v_gqa, mtp_flags);
|
||||
layer.wo = create_tensor(tn(LLM_TENSOR_ATTN_OUT, "weight", i), {n_embd_head_v * n_head_l, n_embd}, mtp_flags);
|
||||
|
||||
layer.wqkv_gate = create_tensor(tn(LLM_TENSOR_ATTN_GATE, "weight", i), {n_embd, n_head_l}, TENSOR_NOT_REQUIRED);
|
||||
|
||||
layer.ffn_norm = create_tensor(tn(LLM_TENSOR_FFN_NORM, "weight", i), {n_embd}, eff_mtp_flags);
|
||||
layer.ffn_norm = create_tensor(tn(LLM_TENSOR_FFN_NORM, "weight", i), {n_embd}, mtp_flags);
|
||||
|
||||
// dense MLP (leading dense blocks) — present if the MTP block isn't MoE
|
||||
layer.ffn_gate = create_tensor(tn(LLM_TENSOR_FFN_GATE, "weight", i), {n_embd, n_ff}, TENSOR_NOT_REQUIRED);
|
||||
@@ -165,9 +162,9 @@ void llama_model_step35::load_arch_tensors(llama_model_loader & ml) {
|
||||
layer.ffn_down_shexp = create_tensor(tn(LLM_TENSOR_FFN_DOWN_SHEXP, "weight", i), {hparams.n_ff_shexp, n_embd}, TENSOR_NOT_REQUIRED);
|
||||
|
||||
// NextN-specific tensors that define the MTP block.
|
||||
layer.nextn.eh_proj = create_tensor(tn(LLM_TENSOR_NEXTN_EH_PROJ, "weight", i), { 2 * n_embd, n_embd }, eff_mtp_flags);
|
||||
layer.nextn.enorm = create_tensor(tn(LLM_TENSOR_NEXTN_ENORM, "weight", i), { n_embd }, eff_mtp_flags);
|
||||
layer.nextn.hnorm = create_tensor(tn(LLM_TENSOR_NEXTN_HNORM, "weight", i), { n_embd }, eff_mtp_flags);
|
||||
layer.nextn.eh_proj = create_tensor(tn(LLM_TENSOR_NEXTN_EH_PROJ, "weight", i), { 2 * n_embd, n_embd }, mtp_flags);
|
||||
layer.nextn.enorm = create_tensor(tn(LLM_TENSOR_NEXTN_ENORM, "weight", i), { n_embd }, mtp_flags);
|
||||
layer.nextn.hnorm = create_tensor(tn(LLM_TENSOR_NEXTN_HNORM, "weight", i), { n_embd }, mtp_flags);
|
||||
layer.nextn.embed_tokens = create_tensor(tn(LLM_TENSOR_NEXTN_EMBED_TOKENS, "weight", i), { n_embd, n_vocab }, TENSOR_NOT_REQUIRED);
|
||||
layer.nextn.shared_head_head = create_tensor(tn(LLM_TENSOR_NEXTN_SHARED_HEAD_HEAD, "weight", i), { n_embd, n_vocab }, TENSOR_NOT_REQUIRED);
|
||||
layer.nextn.shared_head_norm = create_tensor(tn(LLM_TENSOR_NEXTN_SHARED_HEAD_NORM, "weight", i), { n_embd }, TENSOR_NOT_REQUIRED);
|
||||
@@ -176,13 +173,11 @@ void llama_model_step35::load_arch_tensors(llama_model_loader & ml) {
|
||||
for (int i = 0; i < n_layer; ++i) {
|
||||
load_block_trunk(i, trunk_flags);
|
||||
}
|
||||
// Only the first MTP block (i == n_main) is required at runtime — the
|
||||
// single-block-MTP graph in build_arch_graph always uses that one.
|
||||
// Trailing MTP blocks are loaded if present (so an un-pruned GGUF with
|
||||
// all MTP layers still works) but tolerated when absent via the pruning
|
||||
// path. See scripts/prune_step35_extra_mtp.py for the pruner.
|
||||
// All n_layer_nextn MTP blocks are required — the multi-block draft chain
|
||||
// runs every head (head k at offset k). The GGUF declares the count via
|
||||
// step35.nextn_predict_layers.
|
||||
for (int i = n_layer; i < n_layer_all; ++i) {
|
||||
load_block_mtp(i, /*is_first_mtp=*/ i == n_layer);
|
||||
load_block_mtp(i);
|
||||
}
|
||||
}
|
||||
|
||||
@@ -372,13 +367,14 @@ llama_model_step35::graph_mtp::graph_mtp(const llama_model & model, const llm_gr
|
||||
: llm_graph_context(params) {
|
||||
GGML_ASSERT(hparams.n_layer_nextn > 0 && "STEP35 MTP requires n_layer_nextn > 0");
|
||||
|
||||
// Single-block MTP only: always run the first trained MTP block (Qwen
|
||||
// MTP / vLLM single-MTP-layer style). Multi-block round-robin proved to
|
||||
// be a much deeper refactor than this PR justifies; the trailing MTP
|
||||
// blocks are loaded with TENSOR_NOT_REQUIRED so pruned GGUFs (with just
|
||||
// block 0) also work — see load_arch_tensors below and
|
||||
// scripts/prune_step35_extra_mtp.py.
|
||||
const int il = hparams.n_layer();
|
||||
// Multi-block MTP: the DECODER_MTP graph runs the MTP head selected by
|
||||
// cparams.nextn_layer_offset (0 = first trained head). The speculative driver
|
||||
// bumps the offset per draft step to chain heads 45->46->47. offset 0 keeps
|
||||
// single-block behavior identical to before.
|
||||
const int il = hparams.n_layer() + cparams.nextn_layer_offset;
|
||||
GGML_ASSERT(cparams.nextn_layer_offset >= 0 &&
|
||||
cparams.nextn_layer_offset < (int) hparams.n_layer_nextn &&
|
||||
"nextn_layer_offset out of range [0, n_layer_nextn)");
|
||||
const auto & layer = model.layers[il];
|
||||
|
||||
GGML_ASSERT(layer.nextn.eh_proj && "MTP block missing nextn.eh_proj");
|
||||
@@ -536,6 +532,9 @@ llama_model_step35::graph_mtp::graph_mtp(const llama_model & model, const llm_gr
|
||||
cur = ggml_add(ctx0, cur, ffn_inp);
|
||||
cb(cur, "mtp_post_ffn", il);
|
||||
|
||||
ggml_tensor * inp_out_ids = build_inp_out_ids();
|
||||
cur = ggml_get_rows(ctx0, cur, inp_out_ids);
|
||||
|
||||
// Pre-norm hidden state: used by the AR draft loop to seed the next MTP step.
|
||||
cb(cur, "h_nextn", -1);
|
||||
res->t_h_nextn = cur;
|
||||
|
||||
@@ -129,8 +129,86 @@ void test_gbnf_generation(testing &t) {
|
||||
});
|
||||
|
||||
assert_gbnf_equal(t, R"""(
|
||||
root ::= ([^<] | "<" [^/] | "</" [^t] | "</t" [^a] | "</ta" [^g] | "</tag" [^>])* ("<" | "</" | "</t" | "</ta" | "</tag")?
|
||||
root ::= until-0
|
||||
space ::= | " " | "\n"{1,2} [ \t]{0,20}
|
||||
until-0 ::= | [<] until-0-01 | [^<] until-0
|
||||
until-0-01 ::= | [<] until-0-01 | [/] until-0-02 | [^/<] until-0
|
||||
until-0-02 ::= | [<] until-0-01 | [t] until-0-03 | [^<t] until-0
|
||||
until-0-03 ::= | [<] until-0-01 | [a] until-0-04 | [^<a] until-0
|
||||
until-0-04 ::= | [<] until-0-01 | [g] until-0-05 | [^<g] until-0
|
||||
until-0-05 ::= | [<] until-0-01 | [^<>] until-0
|
||||
)""", gbnf);
|
||||
});
|
||||
|
||||
t.test("until grammar overlapping delimiter", [](testing &t) {
|
||||
auto parser = build_peg_parser([](common_peg_parser_builder & p) {
|
||||
return p.until("\n</parameter>\n");
|
||||
});
|
||||
|
||||
auto gbnf = build_grammar([&](const common_grammar_builder & builder) {
|
||||
parser.build_grammar(builder);
|
||||
});
|
||||
|
||||
assert_gbnf_equal(t, R"""(
|
||||
root ::= until-0
|
||||
space ::= | " " | "\n"{1,2} [ \t]{0,20}
|
||||
until-0 ::= | [\n] until-0-01 | [^\n] until-0
|
||||
until-0-01 ::= | [\n] until-0-01 | [<] until-0-02 | [^\n<] until-0
|
||||
until-0-02 ::= | [\n] until-0-01 | [/] until-0-03 | [^\n/] until-0
|
||||
until-0-03 ::= | [\n] until-0-01 | [p] until-0-04 | [^\np] until-0
|
||||
until-0-04 ::= | [\n] until-0-01 | [a] until-0-05 | [^\na] until-0
|
||||
until-0-05 ::= | [\n] until-0-01 | [r] until-0-06 | [^\nr] until-0
|
||||
until-0-06 ::= | [\n] until-0-01 | [a] until-0-07 | [^\na] until-0
|
||||
until-0-07 ::= | [\n] until-0-01 | [m] until-0-08 | [^\nm] until-0
|
||||
until-0-08 ::= | [\n] until-0-01 | [e] until-0-09 | [^\ne] until-0
|
||||
until-0-09 ::= | [\n] until-0-01 | [t] until-0-10 | [^\nt] until-0
|
||||
until-0-10 ::= | [\n] until-0-01 | [e] until-0-11 | [^\ne] until-0
|
||||
until-0-11 ::= | [\n] until-0-01 | [r] until-0-12 | [^\nr] until-0
|
||||
until-0-12 ::= | [\n] until-0-01 | [>] until-0-13 | [^\n>] until-0
|
||||
until-0-13 ::= | [^\n] until-0
|
||||
)""", gbnf);
|
||||
});
|
||||
|
||||
// DeepSeek-V3.2 tag prefix. The DSML token (|DSML|) embeds U+FF5C,
|
||||
// so the delimiter mixes ASCII and multi-byte codepoints.
|
||||
t.test("until grammar unicode delimiter", [](testing &t) {
|
||||
auto parser = build_peg_parser([](common_peg_parser_builder & p) {
|
||||
return p.until("<|DSML|");
|
||||
});
|
||||
|
||||
auto gbnf = build_grammar([&](const common_grammar_builder & builder) {
|
||||
parser.build_grammar(builder);
|
||||
});
|
||||
|
||||
assert_gbnf_equal(t, R"""(
|
||||
root ::= until-0
|
||||
space ::= | " " | "\n"{1,2} [ \t]{0,20}
|
||||
until-0 ::= | [<] until-0-01 | [^<] until-0
|
||||
until-0-01 ::= | [<] until-0-01 | [\uFF5C] until-0-02 | [^<\uFF5C] until-0
|
||||
until-0-02 ::= | [<] until-0-01 | [D] until-0-03 | [^<D] until-0
|
||||
until-0-03 ::= | [<] until-0-01 | [S] until-0-04 | [^<S] until-0
|
||||
until-0-04 ::= | [<] until-0-01 | [M] until-0-05 | [^<M] until-0
|
||||
until-0-05 ::= | [<] until-0-01 | [L] until-0-06 | [^<L] until-0
|
||||
until-0-06 ::= | [<] until-0-01 | [^<\uFF5C] until-0
|
||||
)""", gbnf);
|
||||
});
|
||||
|
||||
t.test("until grammar multiple delimiters", [](testing &t) {
|
||||
auto parser = build_peg_parser([](common_peg_parser_builder & p) {
|
||||
return p.until_one_of({"ab", "cd", "ef"});
|
||||
});
|
||||
|
||||
auto gbnf = build_grammar([&](const common_grammar_builder & builder) {
|
||||
parser.build_grammar(builder);
|
||||
});
|
||||
|
||||
assert_gbnf_equal(t, R"""(
|
||||
root ::= until-0
|
||||
space ::= | " " | "\n"{1,2} [ \t]{0,20}
|
||||
until-0 ::= | [a] until-0-01 | [c] until-0-03 | [e] until-0-05 | [^ace] until-0
|
||||
until-0-01 ::= | [a] until-0-01 | [c] until-0-03 | [e] until-0-05 | [^abce] until-0
|
||||
until-0-03 ::= | [a] until-0-01 | [c] until-0-03 | [e] until-0-05 | [^acde] until-0
|
||||
until-0-05 ::= | [a] until-0-01 | [c] until-0-03 | [e] until-0-05 | [^acef] until-0
|
||||
)""", gbnf);
|
||||
});
|
||||
|
||||
|
||||
@@ -10,7 +10,7 @@
|
||||
#undef NDEBUG
|
||||
#include <cassert>
|
||||
|
||||
int main(void) {
|
||||
static void test(void) {
|
||||
common_params params;
|
||||
|
||||
printf("test-arg-parser: make sure there is no duplicated arguments in any examples\n\n");
|
||||
@@ -210,3 +210,13 @@ int main(void) {
|
||||
|
||||
printf("test-arg-parser: all tests OK\n\n");
|
||||
}
|
||||
|
||||
int main(void) {
|
||||
try {
|
||||
test();
|
||||
} catch (std::exception & e) {
|
||||
fprintf(stderr, "test-arg-parser: exception: %s\n", e.what());
|
||||
return 1;
|
||||
}
|
||||
return 0;
|
||||
}
|
||||
|
||||
+2
-2
@@ -5022,14 +5022,14 @@ static void test_template_output_peg_parsers(bool detailed_debug) {
|
||||
tst.test("Hello, world!\nWhat's up?").tools({ special_function_tool }).expect(message_assist).expect_reconstruction().run();
|
||||
|
||||
tst.test(
|
||||
"```json\n\"42\" \n```")
|
||||
"```json\n\"42\"\n```")
|
||||
.reasoning_format(COMMON_REASONING_FORMAT_AUTO)
|
||||
.json_schema(const_schema)
|
||||
.expect_content(R"("42")")
|
||||
.run();
|
||||
|
||||
tst.test(
|
||||
"\"42\" \n")
|
||||
"\"42\"\n")
|
||||
.reasoning_format(COMMON_REASONING_FORMAT_AUTO)
|
||||
.json_schema(const_schema)
|
||||
.expect_content(R"("42")")
|
||||
|
||||
@@ -995,6 +995,32 @@ static void test_macros(testing & t) {
|
||||
json::object(),
|
||||
"Hello, John Smith,Hi, Jane Doe"
|
||||
);
|
||||
|
||||
test_template(t, "macro with caller",
|
||||
"\
|
||||
{%- macro nest_dict(o, i, ff='') %}\n\
|
||||
{{- caller(ff) }}\n\
|
||||
{%- for k, v in o|items %}\n\
|
||||
{{- i + k + ': ' }}\n\
|
||||
{%- if v is mapping %}\n\
|
||||
{{- '{' }}\n\
|
||||
{% call(f) nest_dict(v, i + ' ') %}\n\
|
||||
{{- 'fail' if ff is undefined }}\n\
|
||||
{%- endcall %}\n\
|
||||
{{- i + '}' }}\n\
|
||||
{% else %}\n\
|
||||
{{- v|string }}\n\
|
||||
{% endif %}\n\
|
||||
{%- endfor %}\n\
|
||||
{%- endmacro %}\n\
|
||||
{%- call(f) nest_dict({'root1': 1, 'root2': {'nest1': 1, 'nest2': {'nest3': 2}}}, ' ', 'Dict') %}\n\
|
||||
{{- 'fail' if ff is defined }}\n\
|
||||
{{- f + ' {' }}\n\
|
||||
{% endcall %}\n\
|
||||
{{- '}' }}",
|
||||
json::object(),
|
||||
"Dict {\n root1: 1\n root2: {\n nest1: 1\n nest2: {\n nest3: 2\n }\n }\n}"
|
||||
);
|
||||
}
|
||||
|
||||
static void test_namespace(testing & t) {
|
||||
|
||||
@@ -92,7 +92,7 @@ static void test_all(const std::string & lang, std::function<void(const TestCase
|
||||
"minimum": 0
|
||||
})""",
|
||||
R"""(
|
||||
root ::= ([0] | [1-9] [0-9]{0,15}) space
|
||||
root ::= ([0] | [1-9] [0-9]{0,15})
|
||||
space ::= | " " | "\n"{1,2} [ \t]{0,20}
|
||||
)"""
|
||||
});
|
||||
@@ -105,7 +105,7 @@ static void test_all(const std::string & lang, std::function<void(const TestCase
|
||||
"minimum": 1
|
||||
})""",
|
||||
R"""(
|
||||
root ::= ([1-9] [0-9]{0,15}) space
|
||||
root ::= ([1-9] [0-9]{0,15})
|
||||
space ::= | " " | "\n"{1,2} [ \t]{0,20}
|
||||
)"""
|
||||
});
|
||||
@@ -118,7 +118,7 @@ static void test_all(const std::string & lang, std::function<void(const TestCase
|
||||
"minimum": 3
|
||||
})""",
|
||||
R"""(
|
||||
root ::= ([1-2] [0-9]{1,15} | [3-9] [0-9]{0,15}) space
|
||||
root ::= ([1-2] [0-9]{1,15} | [3-9] [0-9]{0,15})
|
||||
space ::= | " " | "\n"{1,2} [ \t]{0,20}
|
||||
)"""
|
||||
});
|
||||
@@ -131,7 +131,7 @@ static void test_all(const std::string & lang, std::function<void(const TestCase
|
||||
"minimum": 9
|
||||
})""",
|
||||
R"""(
|
||||
root ::= ([1-8] [0-9]{1,15} | [9] [0-9]{0,15}) space
|
||||
root ::= ([1-8] [0-9]{1,15} | [9] [0-9]{0,15})
|
||||
space ::= | " " | "\n"{1,2} [ \t]{0,20}
|
||||
)"""
|
||||
});
|
||||
@@ -144,7 +144,7 @@ static void test_all(const std::string & lang, std::function<void(const TestCase
|
||||
"minimum": 10
|
||||
})""",
|
||||
R"""(
|
||||
root ::= ([1] ([0-9]{1,15}) | [2-9] [0-9]{1,15}) space
|
||||
root ::= ([1] ([0-9]{1,15}) | [2-9] [0-9]{1,15})
|
||||
space ::= | " " | "\n"{1,2} [ \t]{0,20}
|
||||
)"""
|
||||
});
|
||||
@@ -157,7 +157,7 @@ static void test_all(const std::string & lang, std::function<void(const TestCase
|
||||
"minimum": 25
|
||||
})""",
|
||||
R"""(
|
||||
root ::= ([1] [0-9]{2,15} | [2] ([0-4] [0-9]{1,14} | [5-9] [0-9]{0,14}) | [3-9] [0-9]{1,15}) space
|
||||
root ::= ([1] [0-9]{2,15} | [2] ([0-4] [0-9]{1,14} | [5-9] [0-9]{0,14}) | [3-9] [0-9]{1,15})
|
||||
space ::= | " " | "\n"{1,2} [ \t]{0,20}
|
||||
)"""
|
||||
});
|
||||
@@ -170,7 +170,7 @@ static void test_all(const std::string & lang, std::function<void(const TestCase
|
||||
"maximum": 30
|
||||
})""",
|
||||
R"""(
|
||||
root ::= ("-" [1-9] [0-9]{0,15} | [0-9] | ([1-2] [0-9] | [3] "0")) space
|
||||
root ::= ("-" [1-9] [0-9]{0,15} | [0-9] | ([1-2] [0-9] | [3] "0"))
|
||||
space ::= | " " | "\n"{1,2} [ \t]{0,20}
|
||||
)"""
|
||||
});
|
||||
@@ -183,7 +183,7 @@ static void test_all(const std::string & lang, std::function<void(const TestCase
|
||||
"minimum": -5
|
||||
})""",
|
||||
R"""(
|
||||
root ::= ("-" ([0-5]) | [0] | [1-9] [0-9]{0,15}) space
|
||||
root ::= ("-" ([0-5]) | [0] | [1-9] [0-9]{0,15})
|
||||
space ::= | " " | "\n"{1,2} [ \t]{0,20}
|
||||
)"""
|
||||
});
|
||||
@@ -196,7 +196,7 @@ static void test_all(const std::string & lang, std::function<void(const TestCase
|
||||
"minimum": -123
|
||||
})""",
|
||||
R"""(
|
||||
root ::= ("-" ([0-9] | ([1-8] [0-9] | [9] [0-9]) | "1" ([0-1] [0-9] | [2] [0-3])) | [0] | [1-9] [0-9]{0,15}) space
|
||||
root ::= ("-" ([0-9] | ([1-8] [0-9] | [9] [0-9]) | "1" ([0-1] [0-9] | [2] [0-3])) | [0] | [1-9] [0-9]{0,15})
|
||||
space ::= | " " | "\n"{1,2} [ \t]{0,20}
|
||||
)"""
|
||||
});
|
||||
@@ -209,7 +209,7 @@ static void test_all(const std::string & lang, std::function<void(const TestCase
|
||||
"maximum": -5
|
||||
})""",
|
||||
R"""(
|
||||
root ::= ("-" ([0-4] [0-9]{1,15} | [5-9] [0-9]{0,15})) space
|
||||
root ::= ("-" ([0-4] [0-9]{1,15} | [5-9] [0-9]{0,15}))
|
||||
space ::= | " " | "\n"{1,2} [ \t]{0,20}
|
||||
)"""
|
||||
});
|
||||
@@ -222,7 +222,7 @@ static void test_all(const std::string & lang, std::function<void(const TestCase
|
||||
"maximum": 1
|
||||
})""",
|
||||
R"""(
|
||||
root ::= ("-" [1-9] [0-9]{0,15} | [0-1]) space
|
||||
root ::= ("-" [1-9] [0-9]{0,15} | [0-1])
|
||||
space ::= | " " | "\n"{1,2} [ \t]{0,20}
|
||||
)"""
|
||||
});
|
||||
@@ -235,7 +235,7 @@ static void test_all(const std::string & lang, std::function<void(const TestCase
|
||||
"maximum": 100
|
||||
})""",
|
||||
R"""(
|
||||
root ::= ("-" [1-9] [0-9]{0,15} | [0-9] | ([1-8] [0-9] | [9] [0-9]) | "100") space
|
||||
root ::= ("-" [1-9] [0-9]{0,15} | [0-9] | ([1-8] [0-9] | [9] [0-9]) | "100")
|
||||
space ::= | " " | "\n"{1,2} [ \t]{0,20}
|
||||
)"""
|
||||
});
|
||||
@@ -249,7 +249,7 @@ static void test_all(const std::string & lang, std::function<void(const TestCase
|
||||
"maximum": 23
|
||||
})""",
|
||||
R"""(
|
||||
root ::= ([0-9] | ([1] [0-9] | [2] [0-3])) space
|
||||
root ::= ([0-9] | ([1] [0-9] | [2] [0-3]))
|
||||
space ::= | " " | "\n"{1,2} [ \t]{0,20}
|
||||
)"""
|
||||
});
|
||||
@@ -263,7 +263,7 @@ static void test_all(const std::string & lang, std::function<void(const TestCase
|
||||
"maximum": 300
|
||||
})""",
|
||||
R"""(
|
||||
root ::= (([1] ([5-9]) | [2-9] [0-9]) | ([1-2] [0-9]{2} | [3] "00")) space
|
||||
root ::= (([1] ([5-9]) | [2-9] [0-9]) | ([1-2] [0-9]{2} | [3] "00"))
|
||||
space ::= | " " | "\n"{1,2} [ \t]{0,20}
|
||||
)"""
|
||||
});
|
||||
@@ -277,7 +277,7 @@ static void test_all(const std::string & lang, std::function<void(const TestCase
|
||||
"maximum": 30
|
||||
})""",
|
||||
R"""(
|
||||
root ::= ([5-9] | ([1-2] [0-9] | [3] "0")) space
|
||||
root ::= ([5-9] | ([1-2] [0-9] | [3] "0"))
|
||||
space ::= | " " | "\n"{1,2} [ \t]{0,20}
|
||||
)"""
|
||||
});
|
||||
@@ -291,7 +291,7 @@ static void test_all(const std::string & lang, std::function<void(const TestCase
|
||||
"maximum": 42
|
||||
})""",
|
||||
R"""(
|
||||
root ::= ("-" ([0-9] | ([1-8] [0-9] | [9] [0-9]) | "1" ([0-1] [0-9] | [2] [0-3])) | [0-9] | ([1-3] [0-9] | [4] [0-2])) space
|
||||
root ::= ("-" ([0-9] | ([1-8] [0-9] | [9] [0-9]) | "1" ([0-1] [0-9] | [2] [0-3])) | [0-9] | ([1-3] [0-9] | [4] [0-2]))
|
||||
space ::= | " " | "\n"{1,2} [ \t]{0,20}
|
||||
)"""
|
||||
});
|
||||
@@ -305,7 +305,7 @@ static void test_all(const std::string & lang, std::function<void(const TestCase
|
||||
"maximum": 10
|
||||
})""",
|
||||
R"""(
|
||||
root ::= ("-" ([0-9] | "10") | [0-9] | "10") space
|
||||
root ::= ("-" ([0-9] | "10") | [0-9] | "10")
|
||||
space ::= | " " | "\n"{1,2} [ \t]{0,20}
|
||||
)"""
|
||||
});
|
||||
@@ -333,17 +333,17 @@ static void test_all(const std::string & lang, std::function<void(const TestCase
|
||||
"empty schema (object)",
|
||||
"{}",
|
||||
R"""(
|
||||
array ::= "[" space ( value ("," space value)* )? "]" space
|
||||
boolean ::= ("true" | "false") space
|
||||
array ::= "[" space ( value ("," space value)* )? space "]"
|
||||
boolean ::= ("true" | "false")
|
||||
char ::= [^"\\\x7F\x00-\x1F] | [\\] (["\\bfnrt] | "u" [0-9a-fA-F]{4})
|
||||
decimal-part ::= [0-9]{1,16}
|
||||
integral-part ::= [0] | [1-9] [0-9]{0,15}
|
||||
null ::= "null" space
|
||||
number ::= ("-"? integral-part) ("." decimal-part)? ([eE] [-+]? integral-part)? space
|
||||
object ::= "{" space ( string ":" space value ("," space string ":" space value)* )? "}" space
|
||||
null ::= "null"
|
||||
number ::= ("-"? integral-part) ("." decimal-part)? ([eE] [-+]? integral-part)?
|
||||
object ::= "{" space ( string ":" space value ("," space string ":" space value)* )? space "}"
|
||||
root ::= object
|
||||
space ::= | " " | "\n"{1,2} [ \t]{0,20}
|
||||
string ::= "\"" char* "\"" space
|
||||
string ::= "\"" char* "\""
|
||||
value ::= object | array | string | number | boolean | null
|
||||
)"""
|
||||
});
|
||||
@@ -361,17 +361,17 @@ static void test_all(const std::string & lang, std::function<void(const TestCase
|
||||
})""",
|
||||
R"""(
|
||||
date ::= [0-9]{4} "-" ( "0" [1-9] | "1" [0-2] ) "-" ( "0" [1-9] | [1-2] [0-9] | "3" [0-1] )
|
||||
date-string ::= "\"" date "\"" space
|
||||
date-string ::= "\"" date "\""
|
||||
date-time ::= date "T" time
|
||||
date-time-string ::= "\"" date-time "\"" space
|
||||
root ::= "[" space tuple-0 "," space uuid "," space tuple-2 "," space tuple-3 "]" space
|
||||
date-time-string ::= "\"" date-time "\""
|
||||
root ::= "[" space tuple-0 "," space uuid "," space tuple-2 "," space tuple-3 space "]"
|
||||
space ::= | " " | "\n"{1,2} [ \t]{0,20}
|
||||
time ::= ([01] [0-9] | "2" [0-3]) ":" [0-5] [0-9] ":" [0-5] [0-9] ( "." [0-9]{3} )? ( "Z" | ( "+" | "-" ) ( [01] [0-9] | "2" [0-3] ) ":" [0-5] [0-9] )
|
||||
time-string ::= "\"" time "\"" space
|
||||
time-string ::= "\"" time "\""
|
||||
tuple-0 ::= date-string
|
||||
tuple-2 ::= time-string
|
||||
tuple-3 ::= date-time-string
|
||||
uuid ::= "\"" [0-9a-fA-F]{8} "-" [0-9a-fA-F]{4} "-" [0-9a-fA-F]{4} "-" [0-9a-fA-F]{4} "-" [0-9a-fA-F]{12} "\"" space
|
||||
uuid ::= "\"" [0-9a-fA-F]{8} "-" [0-9a-fA-F]{4} "-" [0-9a-fA-F]{4} "-" [0-9a-fA-F]{4} "-" [0-9a-fA-F]{12} "\""
|
||||
)"""
|
||||
});
|
||||
|
||||
@@ -383,7 +383,7 @@ static void test_all(const std::string & lang, std::function<void(const TestCase
|
||||
})""",
|
||||
R"""(
|
||||
char ::= [^"\\\x7F\x00-\x1F] | [\\] (["\\bfnrt] | "u" [0-9a-fA-F]{4})
|
||||
root ::= "\"" char* "\"" space
|
||||
root ::= "\"" char* "\""
|
||||
space ::= | " " | "\n"{1,2} [ \t]{0,20}
|
||||
)"""
|
||||
});
|
||||
@@ -397,7 +397,7 @@ static void test_all(const std::string & lang, std::function<void(const TestCase
|
||||
})""",
|
||||
R"""(
|
||||
char ::= [^"\\\x7F\x00-\x1F] | [\\] (["\\bfnrt] | "u" [0-9a-fA-F]{4})
|
||||
root ::= "\"" char+ "\"" space
|
||||
root ::= "\"" char+ "\""
|
||||
space ::= | " " | "\n"{1,2} [ \t]{0,20}
|
||||
)"""
|
||||
});
|
||||
@@ -411,7 +411,7 @@ static void test_all(const std::string & lang, std::function<void(const TestCase
|
||||
})""",
|
||||
R"""(
|
||||
char ::= [^"\\\x7F\x00-\x1F] | [\\] (["\\bfnrt] | "u" [0-9a-fA-F]{4})
|
||||
root ::= "\"" char{3,} "\"" space
|
||||
root ::= "\"" char{3,} "\""
|
||||
space ::= | " " | "\n"{1,2} [ \t]{0,20}
|
||||
)"""
|
||||
});
|
||||
@@ -425,7 +425,7 @@ static void test_all(const std::string & lang, std::function<void(const TestCase
|
||||
})""",
|
||||
R"""(
|
||||
char ::= [^"\\\x7F\x00-\x1F] | [\\] (["\\bfnrt] | "u" [0-9a-fA-F]{4})
|
||||
root ::= "\"" char{0,3} "\"" space
|
||||
root ::= "\"" char{0,3} "\""
|
||||
space ::= | " " | "\n"{1,2} [ \t]{0,20}
|
||||
)"""
|
||||
});
|
||||
@@ -440,7 +440,7 @@ static void test_all(const std::string & lang, std::function<void(const TestCase
|
||||
})""",
|
||||
R"""(
|
||||
char ::= [^"\\\x7F\x00-\x1F] | [\\] (["\\bfnrt] | "u" [0-9a-fA-F]{4})
|
||||
root ::= "\"" char{1,4} "\"" space
|
||||
root ::= "\"" char{1,4} "\""
|
||||
space ::= | " " | "\n"{1,2} [ \t]{0,20}
|
||||
)"""
|
||||
});
|
||||
@@ -452,7 +452,7 @@ static void test_all(const std::string & lang, std::function<void(const TestCase
|
||||
"type": "boolean"
|
||||
})""",
|
||||
R"""(
|
||||
root ::= ("true" | "false") space
|
||||
root ::= ("true" | "false")
|
||||
space ::= | " " | "\n"{1,2} [ \t]{0,20}
|
||||
)"""
|
||||
});
|
||||
@@ -465,7 +465,7 @@ static void test_all(const std::string & lang, std::function<void(const TestCase
|
||||
})""",
|
||||
R"""(
|
||||
integral-part ::= [0] | [1-9] [0-9]{0,15}
|
||||
root ::= ("-"? integral-part) space
|
||||
root ::= ("-"? integral-part)
|
||||
space ::= | " " | "\n"{1,2} [ \t]{0,20}
|
||||
)"""
|
||||
});
|
||||
@@ -477,7 +477,7 @@ static void test_all(const std::string & lang, std::function<void(const TestCase
|
||||
"const": "foo"
|
||||
})""",
|
||||
R"""(
|
||||
root ::= "\"foo\"" space
|
||||
root ::= "\"foo\""
|
||||
space ::= | " " | "\n"{1,2} [ \t]{0,20}
|
||||
)"""
|
||||
});
|
||||
@@ -489,7 +489,7 @@ static void test_all(const std::string & lang, std::function<void(const TestCase
|
||||
"const": 123
|
||||
})""",
|
||||
R"""(
|
||||
root ::= "123" space
|
||||
root ::= "123"
|
||||
space ::= | " " | "\n"{1,2} [ \t]{0,20}
|
||||
)"""
|
||||
});
|
||||
@@ -501,7 +501,7 @@ static void test_all(const std::string & lang, std::function<void(const TestCase
|
||||
"enum": ["red", "amber", "green", null, 42, ["foo"]]
|
||||
})""",
|
||||
R"""(
|
||||
root ::= ("\"red\"" | "\"amber\"" | "\"green\"" | "null" | "42" | "[\"foo\"]") space
|
||||
root ::= ("\"red\"" | "\"amber\"" | "\"green\"" | "null" | "42" | "[\"foo\"]")
|
||||
space ::= | " " | "\n"{1,2} [ \t]{0,20}
|
||||
)"""
|
||||
});
|
||||
@@ -515,9 +515,9 @@ static void test_all(const std::string & lang, std::function<void(const TestCase
|
||||
})""",
|
||||
R"""(
|
||||
char ::= [^"\\\x7F\x00-\x1F] | [\\] (["\\bfnrt] | "u" [0-9a-fA-F]{4})
|
||||
root ::= "[" space (string ("," space string)*)? "]" space
|
||||
root ::= "[" space (string ("," space string)*)? space "]"
|
||||
space ::= | " " | "\n"{1,2} [ \t]{0,20}
|
||||
string ::= "\"" char* "\"" space
|
||||
string ::= "\"" char* "\""
|
||||
)"""
|
||||
});
|
||||
|
||||
@@ -529,12 +529,12 @@ static void test_all(const std::string & lang, std::function<void(const TestCase
|
||||
"prefixItems": { "type": "string" }
|
||||
})""",
|
||||
R"""(
|
||||
alternative-0 ::= "[" space (string ("," space string)*)? "]" space
|
||||
alternative-0 ::= "[" space (string ("," space string)*)? space "]"
|
||||
char ::= [^"\\\x7F\x00-\x1F] | [\\] (["\\bfnrt] | "u" [0-9a-fA-F]{4})
|
||||
null ::= "null" space
|
||||
null ::= "null"
|
||||
root ::= alternative-0 | null
|
||||
space ::= | " " | "\n"{1,2} [ \t]{0,20}
|
||||
string ::= "\"" char* "\"" space
|
||||
string ::= "\"" char* "\""
|
||||
)"""
|
||||
});
|
||||
|
||||
@@ -546,9 +546,9 @@ static void test_all(const std::string & lang, std::function<void(const TestCase
|
||||
})""",
|
||||
R"""(
|
||||
char ::= [^"\\\x7F\x00-\x1F] | [\\] (["\\bfnrt] | "u" [0-9a-fA-F]{4})
|
||||
root ::= "[" space string "]" space
|
||||
root ::= "[" space string space "]"
|
||||
space ::= | " " | "\n"{1,2} [ \t]{0,20}
|
||||
string ::= "\"" char* "\"" space
|
||||
string ::= "\"" char* "\""
|
||||
)"""
|
||||
});
|
||||
|
||||
@@ -562,10 +562,10 @@ static void test_all(const std::string & lang, std::function<void(const TestCase
|
||||
char ::= [^"\\\x7F\x00-\x1F] | [\\] (["\\bfnrt] | "u" [0-9a-fA-F]{4})
|
||||
decimal-part ::= [0-9]{1,16}
|
||||
integral-part ::= [0] | [1-9] [0-9]{0,15}
|
||||
number ::= ("-"? integral-part) ("." decimal-part)? ([eE] [-+]? integral-part)? space
|
||||
root ::= "[" space string "," space number "]" space
|
||||
number ::= ("-"? integral-part) ("." decimal-part)? ([eE] [-+]? integral-part)?
|
||||
root ::= "[" space string "," space number space "]"
|
||||
space ::= | " " | "\n"{1,2} [ \t]{0,20}
|
||||
string ::= "\"" char* "\"" space
|
||||
string ::= "\"" char* "\""
|
||||
)"""
|
||||
});
|
||||
|
||||
@@ -577,18 +577,18 @@ static void test_all(const std::string & lang, std::function<void(const TestCase
|
||||
"items": {}
|
||||
})""",
|
||||
R"""(
|
||||
array ::= "[" space ( value ("," space value)* )? "]" space
|
||||
boolean ::= ("true" | "false") space
|
||||
array ::= "[" space ( value ("," space value)* )? space "]"
|
||||
boolean ::= ("true" | "false")
|
||||
char ::= [^"\\\x7F\x00-\x1F] | [\\] (["\\bfnrt] | "u" [0-9a-fA-F]{4})
|
||||
decimal-part ::= [0-9]{1,16}
|
||||
integral-part ::= [0] | [1-9] [0-9]{0,15}
|
||||
item ::= object
|
||||
null ::= "null" space
|
||||
number ::= ("-"? integral-part) ("." decimal-part)? ([eE] [-+]? integral-part)? space
|
||||
object ::= "{" space ( string ":" space value ("," space string ":" space value)* )? "}" space
|
||||
root ::= "[" space (item ("," space item)*)? "]" space
|
||||
null ::= "null"
|
||||
number ::= ("-"? integral-part) ("." decimal-part)? ([eE] [-+]? integral-part)?
|
||||
object ::= "{" space ( string ":" space value ("," space string ":" space value)* )? space "}"
|
||||
root ::= "[" space (item ("," space item)*)? space "]"
|
||||
space ::= | " " | "\n"{1,2} [ \t]{0,20}
|
||||
string ::= "\"" char* "\"" space
|
||||
string ::= "\"" char* "\""
|
||||
value ::= object | array | string | number | boolean | null
|
||||
)"""
|
||||
});
|
||||
@@ -602,18 +602,18 @@ static void test_all(const std::string & lang, std::function<void(const TestCase
|
||||
"prefixItems": { "type": "string" }
|
||||
})""",
|
||||
R"""(
|
||||
array ::= "[" space ( value ("," space value)* )? "]" space
|
||||
boolean ::= ("true" | "false") space
|
||||
array ::= "[" space ( value ("," space value)* )? space "]"
|
||||
boolean ::= ("true" | "false")
|
||||
char ::= [^"\\\x7F\x00-\x1F] | [\\] (["\\bfnrt] | "u" [0-9a-fA-F]{4})
|
||||
decimal-part ::= [0-9]{1,16}
|
||||
integral-part ::= [0] | [1-9] [0-9]{0,15}
|
||||
item ::= object
|
||||
null ::= "null" space
|
||||
number ::= ("-"? integral-part) ("." decimal-part)? ([eE] [-+]? integral-part)? space
|
||||
object ::= "{" space ( string ":" space value ("," space string ":" space value)* )? "}" space
|
||||
root ::= "[" space (item ("," space item)*)? "]" space
|
||||
null ::= "null"
|
||||
number ::= ("-"? integral-part) ("." decimal-part)? ([eE] [-+]? integral-part)?
|
||||
object ::= "{" space ( string ":" space value ("," space string ":" space value)* )? space "}"
|
||||
root ::= "[" space (item ("," space item)*)? space "]"
|
||||
space ::= | " " | "\n"{1,2} [ \t]{0,20}
|
||||
string ::= "\"" char* "\"" space
|
||||
string ::= "\"" char* "\""
|
||||
value ::= object | array | string | number | boolean | null
|
||||
)"""
|
||||
});
|
||||
@@ -627,7 +627,7 @@ static void test_all(const std::string & lang, std::function<void(const TestCase
|
||||
R"""(
|
||||
decimal-part ::= [0-9]{1,16}
|
||||
integral-part ::= [0] | [1-9] [0-9]{0,15}
|
||||
root ::= ("-"? integral-part) ("." decimal-part)? ([eE] [-+]? integral-part)? space
|
||||
root ::= ("-"? integral-part) ("." decimal-part)? ([eE] [-+]? integral-part)?
|
||||
space ::= | " " | "\n"{1,2} [ \t]{0,20}
|
||||
)"""
|
||||
});
|
||||
@@ -642,8 +642,8 @@ static void test_all(const std::string & lang, std::function<void(const TestCase
|
||||
"minItems": 2
|
||||
})""",
|
||||
R"""(
|
||||
boolean ::= ("true" | "false") space
|
||||
root ::= "[" space boolean ("," space boolean)+ "]" space
|
||||
boolean ::= ("true" | "false")
|
||||
root ::= "[" space boolean ("," space boolean)+ space "]"
|
||||
space ::= | " " | "\n"{1,2} [ \t]{0,20}
|
||||
)"""
|
||||
});
|
||||
@@ -658,8 +658,8 @@ static void test_all(const std::string & lang, std::function<void(const TestCase
|
||||
"maxItems": 0
|
||||
})""",
|
||||
R"""(
|
||||
boolean ::= ("true" | "false") space
|
||||
root ::= "[" space "]" space
|
||||
boolean ::= ("true" | "false")
|
||||
root ::= "[" space space "]"
|
||||
space ::= | " " | "\n"{1,2} [ \t]{0,20}
|
||||
)"""
|
||||
});
|
||||
@@ -674,8 +674,8 @@ static void test_all(const std::string & lang, std::function<void(const TestCase
|
||||
"maxItems": 1
|
||||
})""",
|
||||
R"""(
|
||||
boolean ::= ("true" | "false") space
|
||||
root ::= "[" space boolean? "]" space
|
||||
boolean ::= ("true" | "false")
|
||||
root ::= "[" space boolean? space "]"
|
||||
space ::= | " " | "\n"{1,2} [ \t]{0,20}
|
||||
)"""
|
||||
});
|
||||
@@ -690,8 +690,8 @@ static void test_all(const std::string & lang, std::function<void(const TestCase
|
||||
"maxItems": 2
|
||||
})""",
|
||||
R"""(
|
||||
boolean ::= ("true" | "false") space
|
||||
root ::= "[" space (boolean ("," space boolean)?)? "]" space
|
||||
boolean ::= ("true" | "false")
|
||||
root ::= "[" space (boolean ("," space boolean)?)? space "]"
|
||||
space ::= | " " | "\n"{1,2} [ \t]{0,20}
|
||||
)"""
|
||||
});
|
||||
@@ -708,11 +708,11 @@ static void test_all(const std::string & lang, std::function<void(const TestCase
|
||||
})""",
|
||||
R"""(
|
||||
decimal-part ::= [0-9]{1,16}
|
||||
integer ::= ("-"? integral-part) space
|
||||
integer ::= ("-"? integral-part)
|
||||
integral-part ::= [0] | [1-9] [0-9]{0,15}
|
||||
item ::= number | integer
|
||||
number ::= ("-"? integral-part) ("." decimal-part)? ([eE] [-+]? integral-part)? space
|
||||
root ::= "[" space item ("," space item){2,4} "]" space
|
||||
number ::= ("-"? integral-part) ("." decimal-part)? ([eE] [-+]? integral-part)?
|
||||
root ::= "[" space item ("," space item){2,4} space "]"
|
||||
space ::= | " " | "\n"{1,2} [ \t]{0,20}
|
||||
)"""
|
||||
});
|
||||
@@ -730,8 +730,8 @@ static void test_all(const std::string & lang, std::function<void(const TestCase
|
||||
"maxItems": 5
|
||||
})""",
|
||||
R"""(
|
||||
item ::= ("-" ([0-9] | "1" [0-2]) | [0-9] | ([1-8] [0-9] | [9] [0-9]) | ([1] [0-9]{2} | [2] "0" [0-7])) space
|
||||
root ::= "[" space item ("," space item){2,4} "]" space
|
||||
item ::= ("-" ([0-9] | "1" [0-2]) | [0-9] | ([1-8] [0-9] | [9] [0-9]) | ([1] [0-9]{2} | [2] "0" [0-7]))
|
||||
root ::= "[" space item ("," space item){2,4} space "]"
|
||||
space ::= | " " | "\n"{1,2} [ \t]{0,20}
|
||||
)"""
|
||||
});
|
||||
@@ -749,8 +749,8 @@ static void test_all(const std::string & lang, std::function<void(const TestCase
|
||||
"maxItems": 5
|
||||
})""",
|
||||
R"""(
|
||||
item ::= (([1] ([2-9]) | [2-9] [0-9]) | ([1] [0-9]{2} | [2] "0" [0-7])) space
|
||||
root ::= "[" space item ("," space item){2,4} "]" space
|
||||
item ::= (([1] ([2-9]) | [2-9] [0-9]) | ([1] [0-9]{2} | [2] "0" [0-7]))
|
||||
root ::= "[" space item ("," space item){2,4} space "]"
|
||||
space ::= | " " | "\n"{1,2} [ \t]{0,20}
|
||||
)"""
|
||||
});
|
||||
@@ -763,7 +763,7 @@ static void test_all(const std::string & lang, std::function<void(const TestCase
|
||||
"pattern": "^abc?d*efg+(hij)?kl$"
|
||||
})""",
|
||||
R"""(
|
||||
root ::= "\"" ("ab" "c"? "d"* "ef" "g"+ ("hij")? "kl") "\"" space
|
||||
root ::= "\"" ("ab" "c"? "d"* "ef" "g"+ ("hij")? "kl") "\""
|
||||
space ::= | " " | "\n"{1,2} [ \t]{0,20}
|
||||
)"""
|
||||
});
|
||||
@@ -776,7 +776,7 @@ static void test_all(const std::string & lang, std::function<void(const TestCase
|
||||
"pattern": "^\\[\\]\\{\\}\\(\\)\\|\\+\\*\\?$"
|
||||
})""",
|
||||
R"""(
|
||||
root ::= "\"" ("[]{}()|+*?") "\"" space
|
||||
root ::= "\"" ("[]{}()|+*?") "\""
|
||||
space ::= | " " | "\n"{1,2} [ \t]{0,20}
|
||||
)"""
|
||||
});
|
||||
@@ -789,7 +789,7 @@ static void test_all(const std::string & lang, std::function<void(const TestCase
|
||||
"pattern": "^\"$"
|
||||
})""",
|
||||
R"""(
|
||||
root ::= "\"" ("\"") "\"" space
|
||||
root ::= "\"" ("\"") "\""
|
||||
space ::= | " " | "\n"{1,2} [ \t]{0,20}
|
||||
)"""
|
||||
});
|
||||
@@ -802,7 +802,7 @@ static void test_all(const std::string & lang, std::function<void(const TestCase
|
||||
"pattern": "^A|B|C|D$"
|
||||
})""",
|
||||
R"""(
|
||||
root ::= "\"" ("A" | "B" | "C" | "D") "\"" space
|
||||
root ::= "\"" ("A" | "B" | "C" | "D") "\""
|
||||
space ::= | " " | "\n"{1,2} [ \t]{0,20}
|
||||
)"""
|
||||
});
|
||||
@@ -816,7 +816,7 @@ static void test_all(const std::string & lang, std::function<void(const TestCase
|
||||
})""",
|
||||
R"""(
|
||||
dot ::= [^\x0A\x0D]
|
||||
root ::= "\"" (("(" root-1{1,3} ")")? root-1{3,3} "-" root-1{4,4} " " "a"{3,5} "nd" dot dot dot) "\"" space
|
||||
root ::= "\"" (("(" root-1{1,3} ")")? root-1{3,3} "-" root-1{4,4} " " "a"{3,5} "nd" dot dot dot) "\""
|
||||
root-1 ::= [0-9]
|
||||
space ::= | " " | "\n"{1,2} [ \t]{0,20}
|
||||
)"""
|
||||
@@ -845,9 +845,9 @@ static void test_all(const std::string & lang, std::function<void(const TestCase
|
||||
b-kv ::= "\"b\"" space ":" space string
|
||||
c-kv ::= "\"c\"" space ":" space string
|
||||
char ::= [^"\\\x7F\x00-\x1F] | [\\] (["\\bfnrt] | "u" [0-9a-fA-F]{4})
|
||||
root ::= "{" space b-kv "," space c-kv "," space a-kv "}" space
|
||||
root ::= "{" space b-kv "," space c-kv "," space a-kv space "}"
|
||||
space ::= | " " | "\n"{1,2} [ \t]{0,20}
|
||||
string ::= "\"" char* "\"" space
|
||||
string ::= "\"" char* "\""
|
||||
)"""
|
||||
});
|
||||
|
||||
@@ -865,9 +865,9 @@ static void test_all(const std::string & lang, std::function<void(const TestCase
|
||||
R"""(
|
||||
a-kv ::= "\"a\"" space ":" space string
|
||||
char ::= [^"\\\x7F\x00-\x1F] | [\\] (["\\bfnrt] | "u" [0-9a-fA-F]{4})
|
||||
root ::= "{" space (a-kv )? "}" space
|
||||
root ::= "{" space (a-kv )? space "}"
|
||||
space ::= | " " | "\n"{1,2} [ \t]{0,20}
|
||||
string ::= "\"" char* "\"" space
|
||||
string ::= "\"" char* "\""
|
||||
)"""
|
||||
});
|
||||
|
||||
@@ -889,9 +889,9 @@ static void test_all(const std::string & lang, std::function<void(const TestCase
|
||||
b-rest ::= ( "," space c-kv )?
|
||||
c-kv ::= "\"c\"" space ":" space string
|
||||
char ::= [^"\\\x7F\x00-\x1F] | [\\] (["\\bfnrt] | "u" [0-9a-fA-F]{4})
|
||||
root ::= "{" space (a-kv a-rest | b-kv b-rest | c-kv )? "}" space
|
||||
root ::= "{" space (a-kv a-rest | b-kv b-rest | c-kv )? space "}"
|
||||
space ::= | " " | "\n"{1,2} [ \t]{0,20}
|
||||
string ::= "\"" char* "\"" space
|
||||
string ::= "\"" char* "\""
|
||||
)"""
|
||||
});
|
||||
|
||||
@@ -915,9 +915,9 @@ static void test_all(const std::string & lang, std::function<void(const TestCase
|
||||
char ::= [^"\\\x7F\x00-\x1F] | [\\] (["\\bfnrt] | "u" [0-9a-fA-F]{4})
|
||||
d-kv ::= "\"d\"" space ":" space string
|
||||
d-rest ::= ( "," space c-kv )?
|
||||
root ::= "{" space b-kv "," space a-kv ( "," space ( d-kv d-rest | c-kv ) )? "}" space
|
||||
root ::= "{" space b-kv "," space a-kv ( "," space ( d-kv d-rest | c-kv ) )? space "}"
|
||||
space ::= | " " | "\n"{1,2} [ \t]{0,20}
|
||||
string ::= "\"" char* "\"" space
|
||||
string ::= "\"" char* "\""
|
||||
)"""
|
||||
});
|
||||
|
||||
@@ -930,14 +930,14 @@ static void test_all(const std::string & lang, std::function<void(const TestCase
|
||||
})""",
|
||||
R"""(
|
||||
additional-kv ::= string ":" space additional-value
|
||||
additional-value ::= "[" space (number ("," space number)*)? "]" space
|
||||
additional-value ::= "[" space (number ("," space number)*)? space "]"
|
||||
char ::= [^"\\\x7F\x00-\x1F] | [\\] (["\\bfnrt] | "u" [0-9a-fA-F]{4})
|
||||
decimal-part ::= [0-9]{1,16}
|
||||
integral-part ::= [0] | [1-9] [0-9]{0,15}
|
||||
number ::= ("-"? integral-part) ("." decimal-part)? ([eE] [-+]? integral-part)? space
|
||||
root ::= "{" space (additional-kv ( "," space additional-kv )* )? "}" space
|
||||
number ::= ("-"? integral-part) ("." decimal-part)? ([eE] [-+]? integral-part)?
|
||||
root ::= "{" space (additional-kv ( "," space additional-kv )* )? space "}"
|
||||
space ::= | " " | "\n"{1,2} [ \t]{0,20}
|
||||
string ::= "\"" char* "\"" space
|
||||
string ::= "\"" char* "\""
|
||||
)"""
|
||||
});
|
||||
|
||||
@@ -949,17 +949,17 @@ static void test_all(const std::string & lang, std::function<void(const TestCase
|
||||
"additionalProperties": true
|
||||
})""",
|
||||
R"""(
|
||||
array ::= "[" space ( value ("," space value)* )? "]" space
|
||||
boolean ::= ("true" | "false") space
|
||||
array ::= "[" space ( value ("," space value)* )? space "]"
|
||||
boolean ::= ("true" | "false")
|
||||
char ::= [^"\\\x7F\x00-\x1F] | [\\] (["\\bfnrt] | "u" [0-9a-fA-F]{4})
|
||||
decimal-part ::= [0-9]{1,16}
|
||||
integral-part ::= [0] | [1-9] [0-9]{0,15}
|
||||
null ::= "null" space
|
||||
number ::= ("-"? integral-part) ("." decimal-part)? ([eE] [-+]? integral-part)? space
|
||||
object ::= "{" space ( string ":" space value ("," space string ":" space value)* )? "}" space
|
||||
null ::= "null"
|
||||
number ::= ("-"? integral-part) ("." decimal-part)? ([eE] [-+]? integral-part)?
|
||||
object ::= "{" space ( string ":" space value ("," space string ":" space value)* )? space "}"
|
||||
root ::= object
|
||||
space ::= | " " | "\n"{1,2} [ \t]{0,20}
|
||||
string ::= "\"" char* "\"" space
|
||||
string ::= "\"" char* "\""
|
||||
value ::= object | array | string | number | boolean | null
|
||||
)"""
|
||||
});
|
||||
@@ -971,17 +971,17 @@ static void test_all(const std::string & lang, std::function<void(const TestCase
|
||||
"type": "object"
|
||||
})""",
|
||||
R"""(
|
||||
array ::= "[" space ( value ("," space value)* )? "]" space
|
||||
boolean ::= ("true" | "false") space
|
||||
array ::= "[" space ( value ("," space value)* )? space "]"
|
||||
boolean ::= ("true" | "false")
|
||||
char ::= [^"\\\x7F\x00-\x1F] | [\\] (["\\bfnrt] | "u" [0-9a-fA-F]{4})
|
||||
decimal-part ::= [0-9]{1,16}
|
||||
integral-part ::= [0] | [1-9] [0-9]{0,15}
|
||||
null ::= "null" space
|
||||
number ::= ("-"? integral-part) ("." decimal-part)? ([eE] [-+]? integral-part)? space
|
||||
object ::= "{" space ( string ":" space value ("," space string ":" space value)* )? "}" space
|
||||
null ::= "null"
|
||||
number ::= ("-"? integral-part) ("." decimal-part)? ([eE] [-+]? integral-part)?
|
||||
object ::= "{" space ( string ":" space value ("," space string ":" space value)* )? space "}"
|
||||
root ::= object
|
||||
space ::= | " " | "\n"{1,2} [ \t]{0,20}
|
||||
string ::= "\"" char* "\"" space
|
||||
string ::= "\"" char* "\""
|
||||
value ::= object | array | string | number | boolean | null
|
||||
)"""
|
||||
});
|
||||
@@ -994,7 +994,7 @@ static void test_all(const std::string & lang, std::function<void(const TestCase
|
||||
"additionalProperties": false
|
||||
})""",
|
||||
R"""(
|
||||
root ::= "{" space "}" space
|
||||
root ::= "{" space space "}"
|
||||
space ::= | " " | "\n"{1,2} [ \t]{0,20}
|
||||
)"""
|
||||
});
|
||||
@@ -1012,15 +1012,15 @@ static void test_all(const std::string & lang, std::function<void(const TestCase
|
||||
})""",
|
||||
R"""(
|
||||
a-kv ::= "\"a\"" space ":" space number
|
||||
additional-k ::= ["] ( [a] char+ | [^"a] char* )? ["] space
|
||||
additional-k ::= ["] ( [a] char+ | [^"a] char* )? ["]
|
||||
additional-kv ::= additional-k ":" space string
|
||||
char ::= [^"\\\x7F\x00-\x1F] | [\\] (["\\bfnrt] | "u" [0-9a-fA-F]{4})
|
||||
decimal-part ::= [0-9]{1,16}
|
||||
integral-part ::= [0] | [1-9] [0-9]{0,15}
|
||||
number ::= ("-"? integral-part) ("." decimal-part)? ([eE] [-+]? integral-part)? space
|
||||
root ::= "{" space a-kv ( "," space ( additional-kv ( "," space additional-kv )* ) )? "}" space
|
||||
number ::= ("-"? integral-part) ("." decimal-part)? ([eE] [-+]? integral-part)?
|
||||
root ::= "{" space a-kv ( "," space ( additional-kv ( "," space additional-kv )* ) )? space "}"
|
||||
space ::= | " " | "\n"{1,2} [ \t]{0,20}
|
||||
string ::= "\"" char* "\"" space
|
||||
string ::= "\"" char* "\""
|
||||
)"""
|
||||
});
|
||||
|
||||
@@ -1037,13 +1037,13 @@ static void test_all(const std::string & lang, std::function<void(const TestCase
|
||||
R"""(
|
||||
a-kv ::= "\"a\"" space ":" space number
|
||||
a-rest ::= ( "," space additional-kv )*
|
||||
additional-k ::= ["] ( [a] char+ | [^"a] char* )? ["] space
|
||||
additional-k ::= ["] ( [a] char+ | [^"a] char* )? ["]
|
||||
additional-kv ::= additional-k ":" space number
|
||||
char ::= [^"\\\x7F\x00-\x1F] | [\\] (["\\bfnrt] | "u" [0-9a-fA-F]{4})
|
||||
decimal-part ::= [0-9]{1,16}
|
||||
integral-part ::= [0] | [1-9] [0-9]{0,15}
|
||||
number ::= ("-"? integral-part) ("." decimal-part)? ([eE] [-+]? integral-part)? space
|
||||
root ::= "{" space (a-kv a-rest | additional-kv ( "," space additional-kv )* )? "}" space
|
||||
number ::= ("-"? integral-part) ("." decimal-part)? ([eE] [-+]? integral-part)?
|
||||
root ::= "{" space (a-kv a-rest | additional-kv ( "," space additional-kv )* )? space "}"
|
||||
space ::= | " " | "\n"{1,2} [ \t]{0,20}
|
||||
)"""
|
||||
});
|
||||
@@ -1061,7 +1061,7 @@ static void test_all(const std::string & lang, std::function<void(const TestCase
|
||||
"additionalProperties": {"type": "number"}
|
||||
})""",
|
||||
R"""(
|
||||
additional-k ::= ["] ( [a] ([l] ([s] ([o] char+ | [^"o] char*) | [^"s] char*) | [n] ([d] char+ | [^"d] char*) | [^"ln] char*) | [^"a] char* )? ["] space
|
||||
additional-k ::= ["] ( [a] ([l] ([s] ([o] char+ | [^"o] char*) | [^"s] char*) | [n] ([d] char+ | [^"d] char*) | [^"ln] char*) | [^"a] char* )? ["]
|
||||
additional-kv ::= additional-k ":" space number
|
||||
also-kv ::= "\"also\"" space ":" space number
|
||||
also-rest ::= ( "," space additional-kv )*
|
||||
@@ -1069,8 +1069,8 @@ static void test_all(const std::string & lang, std::function<void(const TestCase
|
||||
char ::= [^"\\\x7F\x00-\x1F] | [\\] (["\\bfnrt] | "u" [0-9a-fA-F]{4})
|
||||
decimal-part ::= [0-9]{1,16}
|
||||
integral-part ::= [0] | [1-9] [0-9]{0,15}
|
||||
number ::= ("-"? integral-part) ("." decimal-part)? ([eE] [-+]? integral-part)? space
|
||||
root ::= "{" space and-kv ( "," space ( also-kv also-rest | additional-kv ( "," space additional-kv )* ) )? "}" space
|
||||
number ::= ("-"? integral-part) ("." decimal-part)? ([eE] [-+]? integral-part)?
|
||||
root ::= "{" space and-kv ( "," space ( also-kv also-rest | additional-kv ( "," space additional-kv )* ) )? space "}"
|
||||
space ::= | " " | "\n"{1,2} [ \t]{0,20}
|
||||
)"""
|
||||
});
|
||||
@@ -1090,13 +1090,13 @@ static void test_all(const std::string & lang, std::function<void(const TestCase
|
||||
-rest ::= ( "," space a-kv )? a-rest
|
||||
a-kv ::= "\"a\"" space ":" space integer
|
||||
a-rest ::= ( "," space additional-kv )*
|
||||
additional-k ::= ["] ( [a] char+ | [^"a] char* ) ["] space
|
||||
additional-k ::= ["] ( [a] char+ | [^"a] char* ) ["]
|
||||
additional-kv ::= additional-k ":" space integer
|
||||
char ::= [^"\\\x7F\x00-\x1F] | [\\] (["\\bfnrt] | "u" [0-9a-fA-F]{4})
|
||||
integer ::= ("-"? integral-part) space
|
||||
integer ::= ("-"? integral-part)
|
||||
integral-part ::= [0] | [1-9] [0-9]{0,15}
|
||||
root ::= ("-"? integral-part) space
|
||||
root0 ::= "{" space (-kv -rest | a-kv a-rest | additional-kv ( "," space additional-kv )* )? "}" space
|
||||
root ::= ("-"? integral-part)
|
||||
root0 ::= "{" space (-kv -rest | a-kv a-rest | additional-kv ( "," space additional-kv )* )? space "}"
|
||||
space ::= | " " | "\n"{1,2} [ \t]{0,20}
|
||||
)"""
|
||||
});
|
||||
@@ -1116,12 +1116,12 @@ static void test_all(const std::string & lang, std::function<void(const TestCase
|
||||
a-rest ::= ( "," space aa-kv )? aa-rest
|
||||
aa-kv ::= "\"aa\"" space ":" space integer
|
||||
aa-rest ::= ( "," space additional-kv )*
|
||||
additional-k ::= ["] ( [a] ([a] char+ | [^"a] char*) | [^"a] char* )? ["] space
|
||||
additional-k ::= ["] ( [a] ([a] char+ | [^"a] char*) | [^"a] char* )? ["]
|
||||
additional-kv ::= additional-k ":" space integer
|
||||
char ::= [^"\\\x7F\x00-\x1F] | [\\] (["\\bfnrt] | "u" [0-9a-fA-F]{4})
|
||||
integer ::= ("-"? integral-part) space
|
||||
integer ::= ("-"? integral-part)
|
||||
integral-part ::= [0] | [1-9] [0-9]{0,15}
|
||||
root ::= "{" space (a-kv a-rest | aa-kv aa-rest | additional-kv ( "," space additional-kv )* )? "}" space
|
||||
root ::= "{" space (a-kv a-rest | aa-kv aa-rest | additional-kv ( "," space additional-kv )* )? space "}"
|
||||
space ::= | " " | "\n"{1,2} [ \t]{0,20}
|
||||
)"""
|
||||
});
|
||||
@@ -1141,12 +1141,12 @@ static void test_all(const std::string & lang, std::function<void(const TestCase
|
||||
ab-rest ::= ( "," space ac-kv )? ac-rest
|
||||
ac-kv ::= "\"ac\"" space ":" space integer
|
||||
ac-rest ::= ( "," space additional-kv )*
|
||||
additional-k ::= ["] ( [a] ([b] char+ | [c] char+ | [^"bc] char*) | [^"a] char* )? ["] space
|
||||
additional-k ::= ["] ( [a] ([b] char+ | [c] char+ | [^"bc] char*) | [^"a] char* )? ["]
|
||||
additional-kv ::= additional-k ":" space integer
|
||||
char ::= [^"\\\x7F\x00-\x1F] | [\\] (["\\bfnrt] | "u" [0-9a-fA-F]{4})
|
||||
integer ::= ("-"? integral-part) space
|
||||
integer ::= ("-"? integral-part)
|
||||
integral-part ::= [0] | [1-9] [0-9]{0,15}
|
||||
root ::= "{" space (ab-kv ab-rest | ac-kv ac-rest | additional-kv ( "," space additional-kv )* )? "}" space
|
||||
root ::= "{" space (ab-kv ab-rest | ac-kv ac-rest | additional-kv ( "," space additional-kv )* )? space "}"
|
||||
space ::= | " " | "\n"{1,2} [ \t]{0,20}
|
||||
)"""
|
||||
});
|
||||
@@ -1173,11 +1173,11 @@ static void test_all(const std::string & lang, std::function<void(const TestCase
|
||||
})""",
|
||||
R"""(
|
||||
char ::= [^"\\\x7F\x00-\x1F] | [\\] (["\\bfnrt] | "u" [0-9a-fA-F]{4})
|
||||
ref-definitions-foo ::= "{" space ref-definitions-foo-a-kv "}" space
|
||||
ref-definitions-foo ::= "{" space ref-definitions-foo-a-kv space "}"
|
||||
ref-definitions-foo-a-kv ::= "\"a\"" space ":" space string
|
||||
root ::= ref-definitions-foo
|
||||
space ::= | " " | "\n"{1,2} [ \t]{0,20}
|
||||
string ::= "\"" char* "\"" space
|
||||
string ::= "\"" char* "\""
|
||||
)"""
|
||||
});
|
||||
|
||||
@@ -1204,10 +1204,10 @@ static void test_all(const std::string & lang, std::function<void(const TestCase
|
||||
alternative-1 ::= ref-definitions-bar
|
||||
decimal-part ::= [0-9]{1,16}
|
||||
integral-part ::= [0] | [1-9] [0-9]{0,15}
|
||||
number ::= ("-"? integral-part) ("." decimal-part)? ([eE] [-+]? integral-part)? space
|
||||
ref-definitions-bar ::= "{" space (ref-definitions-bar-b-kv )? "}" space
|
||||
number ::= ("-"? integral-part) ("." decimal-part)? ([eE] [-+]? integral-part)?
|
||||
ref-definitions-bar ::= "{" space (ref-definitions-bar-b-kv )? space "}"
|
||||
ref-definitions-bar-b-kv ::= "\"b\"" space ":" space number
|
||||
ref-definitions-foo ::= "{" space (ref-definitions-foo-a-kv )? "}" space
|
||||
ref-definitions-foo ::= "{" space (ref-definitions-foo-a-kv )? space "}"
|
||||
ref-definitions-foo-a-kv ::= "\"a\"" space ":" space number
|
||||
root ::= alternative-0 | alternative-1
|
||||
space ::= | " " | "\n"{1,2} [ \t]{0,20}
|
||||
@@ -1241,14 +1241,14 @@ static void test_all(const std::string & lang, std::function<void(const TestCase
|
||||
b ::= b-0 | boolean
|
||||
b-0 ::= string
|
||||
b-kv ::= "\"b\"" space ":" space b
|
||||
boolean ::= ("true" | "false") space
|
||||
boolean ::= ("true" | "false")
|
||||
char ::= [^"\\\x7F\x00-\x1F] | [\\] (["\\bfnrt] | "u" [0-9a-fA-F]{4})
|
||||
decimal-part ::= [0-9]{1,16}
|
||||
integral-part ::= [0] | [1-9] [0-9]{0,15}
|
||||
number ::= ("-"? integral-part) ("." decimal-part)? ([eE] [-+]? integral-part)? space
|
||||
root ::= "{" space (a-kv a-rest | b-kv )? "}" space
|
||||
number ::= ("-"? integral-part) ("." decimal-part)? ([eE] [-+]? integral-part)?
|
||||
root ::= "{" space (a-kv a-rest | b-kv )? space "}"
|
||||
space ::= | " " | "\n"{1,2} [ \t]{0,20}
|
||||
string ::= "\"" char* "\"" space
|
||||
string ::= "\"" char* "\""
|
||||
)"""
|
||||
});
|
||||
|
||||
@@ -1290,8 +1290,8 @@ static void test_all(const std::string & lang, std::function<void(const TestCase
|
||||
d-rest ::= ( "," space c-kv )?
|
||||
decimal-part ::= [0-9]{1,16}
|
||||
integral-part ::= [0] | [1-9] [0-9]{0,15}
|
||||
number ::= ("-"? integral-part) ("." decimal-part)? ([eE] [-+]? integral-part)? space
|
||||
root ::= "{" space a-kv "," space b-kv ( "," space ( d-kv d-rest | c-kv ) )? "}" space
|
||||
number ::= ("-"? integral-part) ("." decimal-part)? ([eE] [-+]? integral-part)?
|
||||
root ::= "{" space a-kv "," space b-kv ( "," space ( d-kv d-rest | c-kv ) )? space "}"
|
||||
space ::= | " " | "\n"{1,2} [ \t]{0,20}
|
||||
)"""
|
||||
});
|
||||
@@ -1311,7 +1311,7 @@ static void test_all(const std::string & lang, std::function<void(const TestCase
|
||||
}
|
||||
})""",
|
||||
R"""(
|
||||
root ::= ("\"a\"" | "\"b\"") space
|
||||
root ::= ("\"a\"" | "\"b\"")
|
||||
space ::= | " " | "\n"{1,2} [ \t]{0,20}
|
||||
)"""
|
||||
});
|
||||
@@ -1336,7 +1336,7 @@ static void test_all(const std::string & lang, std::function<void(const TestCase
|
||||
}
|
||||
})""",
|
||||
R"""(
|
||||
root ::= ("\"b\"" | "\"c\"") space
|
||||
root ::= ("\"b\"" | "\"c\"")
|
||||
space ::= | " " | "\n"{1,2} [ \t]{0,20}
|
||||
)"""
|
||||
});
|
||||
@@ -1378,13 +1378,13 @@ static void test_all(const std::string & lang, std::function<void(const TestCase
|
||||
R"""(
|
||||
decimal-part ::= [0-9]{1,16}
|
||||
integral-part ::= [0] | [1-9] [0-9]{0,15}
|
||||
number ::= ("-"? integral-part) ("." decimal-part)? ([eE] [-+]? integral-part)? space
|
||||
number- ::= "{" space number-number-kv "}" space
|
||||
number ::= ("-"? integral-part) ("." decimal-part)? ([eE] [-+]? integral-part)?
|
||||
number- ::= "{" space number-number-kv space "}"
|
||||
number-kv ::= "\"number\"" space ":" space number-
|
||||
number-number ::= "{" space number-number-root-kv "}" space
|
||||
number-number ::= "{" space number-number-root-kv space "}"
|
||||
number-number-kv ::= "\"number\"" space ":" space number-number
|
||||
number-number-root-kv ::= "\"root\"" space ":" space number
|
||||
root ::= "{" space number-kv "}" space
|
||||
root ::= "{" space number-kv space "}"
|
||||
space ::= | " " | "\n"{1,2} [ \t]{0,20}
|
||||
)"""
|
||||
});
|
||||
@@ -1394,17 +1394,17 @@ static void test_all(const std::string & lang, std::function<void(const TestCase
|
||||
"description only (no type) treated as unconstrained",
|
||||
R"""({"description": "The 0-based index of the last line to be retrieved (inclusive). If None, read until the end of the file."})""",
|
||||
R"""(
|
||||
array ::= "[" space ( value ("," space value)* )? "]" space
|
||||
boolean ::= ("true" | "false") space
|
||||
array ::= "[" space ( value ("," space value)* )? space "]"
|
||||
boolean ::= ("true" | "false")
|
||||
char ::= [^"\\\x7F\x00-\x1F] | [\\] (["\\bfnrt] | "u" [0-9a-fA-F]{4})
|
||||
decimal-part ::= [0-9]{1,16}
|
||||
integral-part ::= [0] | [1-9] [0-9]{0,15}
|
||||
null ::= "null" space
|
||||
number ::= ("-"? integral-part) ("." decimal-part)? ([eE] [-+]? integral-part)? space
|
||||
object ::= "{" space ( string ":" space value ("," space string ":" space value)* )? "}" space
|
||||
null ::= "null"
|
||||
number ::= ("-"? integral-part) ("." decimal-part)? ([eE] [-+]? integral-part)?
|
||||
object ::= "{" space ( string ":" space value ("," space string ":" space value)* )? space "}"
|
||||
root ::= value
|
||||
space ::= | " " | "\n"{1,2} [ \t]{0,20}
|
||||
string ::= "\"" char* "\"" space
|
||||
string ::= "\"" char* "\""
|
||||
value ::= object | array | string | number | boolean | null
|
||||
)"""
|
||||
});
|
||||
@@ -1428,9 +1428,9 @@ static void test_all(const std::string & lang, std::function<void(const TestCase
|
||||
"type": "object"
|
||||
})""",
|
||||
R"""(
|
||||
code ::= "\" \\r \\n \\\" \\\\ \"" space
|
||||
code ::= "\" \\r \\n \\\" \\\\ \""
|
||||
code-kv ::= "\"code\"" space ":" space code
|
||||
root ::= "{" space code-kv "}" space
|
||||
root ::= "{" space code-kv space "}"
|
||||
space ::= | " " | "\n"{1,2} [ \t]{0,20}
|
||||
)"""
|
||||
});
|
||||
@@ -1547,7 +1547,7 @@ int main() {
|
||||
"pattern": "^(?:foo|bar)baz$"
|
||||
})""",
|
||||
R"""(
|
||||
root ::= "\"" (("foo" | "bar") "baz") "\"" space
|
||||
root ::= "\"" (("foo" | "bar") "baz") "\""
|
||||
space ::= | " " | "\n"{1,2} [ \t]{0,20}
|
||||
)""",
|
||||
});
|
||||
@@ -1560,7 +1560,7 @@ int main() {
|
||||
"pattern": "^(?:(?:ab)+c)?d$"
|
||||
})""",
|
||||
R"""(
|
||||
root ::= "\"" ((("ab")+ "c")? "d") "\"" space
|
||||
root ::= "\"" ((("ab")+ "c")? "d") "\""
|
||||
space ::= | " " | "\n"{1,2} [ \t]{0,20}
|
||||
)""",
|
||||
});
|
||||
|
||||
+2
-1
@@ -161,7 +161,7 @@
|
||||
| `-mmu, --mmproj-url URL` | URL to a multimodal projector file. see tools/mtmd/README.md<br/>(env: LLAMA_ARG_MMPROJ_URL) |
|
||||
| `--mmproj-auto, --no-mmproj, --no-mmproj-auto` | whether to use multimodal projector file (if available), useful when using -hf (default: enabled)<br/>(env: LLAMA_ARG_MMPROJ_AUTO) |
|
||||
| `--mmproj-offload, --no-mmproj-offload` | whether to enable GPU offloading for multimodal projector (default: enabled)<br/>(env: LLAMA_ARG_MMPROJ_OFFLOAD) |
|
||||
| `--image, --audio FILE` | path to an image or audio file. use with multimodal models, use comma-separated values for multiple files |
|
||||
| `--image, --audio, --video FILE` | path to an image, audio, or video file. use with multimodal models, use comma-separated values for multiple files |
|
||||
| `--image-min-tokens N` | minimum number of tokens each image can take, only used by vision models with dynamic resolution (default: read from model)<br/>(env: LLAMA_ARG_IMAGE_MIN_TOKENS) |
|
||||
| `--image-max-tokens N` | maximum number of tokens each image can take, only used by vision models with dynamic resolution (default: read from model)<br/>(env: LLAMA_ARG_IMAGE_MAX_TOKENS) |
|
||||
| `--chat-template-kwargs STRING` | sets additional params for the json template parser, must be a valid json object string, e.g. '{"key1":"value1","key2":"value2"}'<br/>(env: LLAMA_ARG_CHAT_TEMPLATE_KWARGS) |
|
||||
@@ -174,6 +174,7 @@
|
||||
| `--chat-template-file JINJA_TEMPLATE_FILE` | set custom jinja chat template file (default: template taken from model's metadata)<br/>if suffix/prefix are specified, template will be disabled<br/>only commonly used templates are accepted (unless --jinja is set before this flag):<br/>list of built-in templates:<br/>bailing, bailing-think, bailing2, chatglm3, chatglm4, chatml, command-r, deepseek, deepseek-ocr, deepseek2, deepseek3, exaone-moe, exaone3, exaone4, falcon3, gemma, gigachat, glmedge, gpt-oss, granite, granite-4.0, granite-4.1, grok-2, hunyuan-dense, hunyuan-moe, hunyuan-vl, kimi-k2, llama2, llama2-sys, llama2-sys-bos, llama2-sys-strip, llama3, llama4, megrez, minicpm, mistral-v1, mistral-v3, mistral-v3-tekken, mistral-v7, mistral-v7-tekken, monarch, openchat, orion, pangu-embedded, phi3, phi4, rwkv-world, seed_oss, smolvlm, solar-open, vicuna, vicuna-orca, yandex, zephyr<br/>(env: LLAMA_ARG_CHAT_TEMPLATE_FILE) |
|
||||
| `--skip-chat-parsing, --no-skip-chat-parsing` | force a pure content parser, even if a Jinja template is specified; model will output everything in the content section, including any reasoning and/or tool calls (default: disabled)<br/>(env: LLAMA_ARG_SKIP_CHAT_PARSING) |
|
||||
| `--simple-io` | use basic IO for better compatibility in subprocesses and limited consoles |
|
||||
| `--log-prompts-dir PATH` | Log prompts to directory (only used for debugging, default: disabled) |
|
||||
| `--spec-draft-hf, -hfd, -hfrd, --hf-repo-draft <user>/<model>[:quant]` | Same as --hf-repo, but for the draft model (default: unused)<br/>(env: LLAMA_ARG_SPEC_DRAFT_HF_REPO) |
|
||||
| `--spec-draft-threads, -td, --threads-draft N` | number of threads to use during generation (default: same as --threads) |
|
||||
| `--spec-draft-threads-batch, -tbd, --threads-batch-draft N` | number of threads to use during batch and prompt processing (default: same as --threads-draft) |
|
||||
|
||||
+1
-1
@@ -202,7 +202,7 @@ struct cli_context {
|
||||
|
||||
// TODO: support remote files in the future (http, https, etc)
|
||||
std::string load_input_file(const std::string & fname, bool is_media) {
|
||||
std::ifstream file(fname, std::ios::binary);
|
||||
std::ifstream file = fs_open_ifstream(fname, std::ios::binary);
|
||||
if (!file) {
|
||||
return "";
|
||||
}
|
||||
|
||||
@@ -13,6 +13,14 @@
|
||||
#include <sstream>
|
||||
#include <vector>
|
||||
#include <memory>
|
||||
#include <fstream>
|
||||
|
||||
#ifdef _WIN32
|
||||
#ifndef NOMINMAX
|
||||
#define NOMINMAX
|
||||
#endif
|
||||
#include <windows.h>
|
||||
#endif
|
||||
|
||||
// Internal header for clip.cpp
|
||||
|
||||
@@ -661,6 +669,22 @@ struct clip_image_f32_batch {
|
||||
// common utils
|
||||
//
|
||||
|
||||
#ifdef _WIN32
|
||||
static std::ifstream open_ifstream_binary(const std::string & fname) {
|
||||
int wlen = MultiByteToWideChar(CP_UTF8, 0, fname.c_str(), -1, NULL, 0);
|
||||
if (!wlen) {
|
||||
throw std::runtime_error("failed to convert filename to UTF-16: " + fname);
|
||||
}
|
||||
std::vector<wchar_t> wfname(wlen);
|
||||
(void)MultiByteToWideChar(CP_UTF8, 0, fname.c_str(), -1, wfname.data(), wlen);
|
||||
return std::ifstream(wfname.data(), std::ios::binary);
|
||||
}
|
||||
#else
|
||||
static std::ifstream open_ifstream_binary(const std::string & fname) {
|
||||
return std::ifstream(fname, std::ios::binary);
|
||||
}
|
||||
#endif
|
||||
|
||||
static std::string string_format(const char * fmt, ...) {
|
||||
va_list ap;
|
||||
va_list ap2;
|
||||
|
||||
+90
-27
@@ -534,7 +534,7 @@ ggml_tensor * clip_graph::build_vit(
|
||||
ggml_tensor * clip_graph::build_inp() {
|
||||
ggml_tensor * inp_raw = build_inp_raw();
|
||||
ggml_tensor * inp = ggml_conv_2d(ctx0, model.patch_embeddings_0, inp_raw, patch_size, patch_size, 0, 0, 1, 1);
|
||||
inp = ggml_reshape_2d(ctx0, inp, n_patches, n_embd);
|
||||
inp = ggml_reshape_3d(ctx0, inp, n_patches, n_embd, n_batch);
|
||||
inp = ggml_cont(ctx0, ggml_transpose(ctx0, inp));
|
||||
if (model.patch_bias) {
|
||||
inp = ggml_add(ctx0, inp, model.patch_bias);
|
||||
@@ -1045,8 +1045,17 @@ struct clip_model_loader {
|
||||
bool has_vision = false;
|
||||
bool has_audio = false;
|
||||
|
||||
mtmd_progress_callback progress_callback = nullptr;
|
||||
void * progress_callback_user_data = nullptr;
|
||||
|
||||
// TODO @ngxson : we should not pass clip_ctx here, it should be clip_model
|
||||
clip_model_loader(const char * fname, bool skip_tensors = false) : fname(fname) {
|
||||
clip_model_loader(const char * fname,
|
||||
bool skip_tensors = false,
|
||||
mtmd_progress_callback progress_cb = nullptr,
|
||||
void * progress_user_data = nullptr)
|
||||
: fname(fname),
|
||||
progress_callback(progress_cb),
|
||||
progress_callback_user_data(progress_user_data) {
|
||||
struct ggml_context * meta = nullptr;
|
||||
|
||||
struct gguf_init_params params = {
|
||||
@@ -1675,6 +1684,9 @@ struct clip_model_loader {
|
||||
// note: some models having hparams.image_size == 0, which means the image size is dynamic
|
||||
throw std::runtime_error(string_format("%s: image_size (%d) cannot be negative\n", __func__, hparams.image_size));
|
||||
}
|
||||
if (hparams.image_size > 65536) {
|
||||
throw std::runtime_error(string_format("%s: image_size (%d) is too large (max 65536)\n", __func__, hparams.image_size));
|
||||
}
|
||||
if (hparams.patch_size <= 0) {
|
||||
throw std::runtime_error(string_format("%s: patch_size (%d) must be greater than 0\n", __func__, hparams.patch_size));
|
||||
}
|
||||
@@ -1723,6 +1735,19 @@ struct clip_model_loader {
|
||||
LOG_INF("%s: audio_n_fft: %d\n", __func__, hparams.audio_n_fft);
|
||||
LOG_INF("%s: audio_window_len: %d\n", __func__, hparams.audio_window_len);
|
||||
LOG_INF("%s: audio_hop_len: %d\n", __func__, hparams.audio_hop_len);
|
||||
|
||||
// GEMMA4UA is encoder-free: it uses n_mel_bins as a raw-waveform frame size (640) and has no FFT/filterbank, so the mel-range and FFT
|
||||
// checks below do not apply to it.
|
||||
const bool fft_based = model.proj_type != PROJECTOR_TYPE_GEMMA4UA;
|
||||
|
||||
// Validate audio hparams loaded from GGUF metadata
|
||||
if (hparams.n_mel_bins <= 0 || (fft_based && hparams.n_mel_bins > 256)) {
|
||||
throw std::runtime_error(string_format("%s: n_mel_bins (%d) must be in range [1, 256]\n", __func__, hparams.n_mel_bins));
|
||||
}
|
||||
if (fft_based && (hparams.audio_sample_rate <= 0 || hparams.audio_n_fft <= 0 || hparams.audio_hop_len <= 0 || hparams.audio_window_len <= 0)) {
|
||||
throw std::runtime_error(string_format("%s: audio hparams invalid: sample_rate=%d n_fft=%d window_len=%d hop_len=%d\n",
|
||||
__func__, hparams.audio_sample_rate, hparams.audio_n_fft, hparams.audio_window_len, hparams.audio_hop_len));
|
||||
}
|
||||
}
|
||||
LOG_INF("\n");
|
||||
LOG_INF("%s: model size: %.2f MiB\n", __func__, model_size / 1024.0 / 1024.0);
|
||||
@@ -1736,7 +1761,7 @@ struct clip_model_loader {
|
||||
std::map<std::string, size_t> tensor_offset;
|
||||
std::vector<ggml_tensor *> tensors_to_load;
|
||||
|
||||
auto fin = std::ifstream(fname, std::ios::binary);
|
||||
auto fin = open_ifstream_binary(fname);
|
||||
if (!fin) {
|
||||
throw std::runtime_error(string_format("%s: failed to open %s\n", __func__, fname.c_str()));
|
||||
}
|
||||
@@ -2771,37 +2796,60 @@ struct clip_model_loader {
|
||||
}
|
||||
|
||||
// load data
|
||||
if (!ctx_clip.no_alloc) {
|
||||
{
|
||||
std::vector<uint8_t> read_buf;
|
||||
|
||||
// start loading event
|
||||
if (progress_callback){
|
||||
progress_callback(0.0, progress_callback_user_data);
|
||||
}
|
||||
|
||||
// compute total tensor data size for progress reporting
|
||||
size_t total_data_size = 0;
|
||||
for (auto & t : tensors_to_load) {
|
||||
total_data_size += ggml_nbytes(t);
|
||||
}
|
||||
|
||||
// alloc memory and offload data
|
||||
ggml_backend_buffer_type_t buft = ggml_backend_get_default_buffer_type(ctx_clip.backend);
|
||||
ctx_clip.buf.reset(ggml_backend_alloc_ctx_tensors_from_buft(ctx_clip.ctx_data.get(), buft));
|
||||
ggml_backend_buffer_set_usage(ctx_clip.buf.get(), GGML_BACKEND_BUFFER_USAGE_WEIGHTS);
|
||||
for (auto & t : tensors_to_load) {
|
||||
ggml_tensor * cur = ggml_get_tensor(ctx_clip.ctx_data.get(), t->name);
|
||||
GGML_ASSERT(cur && "tensor not found in ctx_data");
|
||||
auto it_off = tensor_offset.find(t->name);
|
||||
GGML_ASSERT(it_off != tensor_offset.end() && "no offset for tensor");
|
||||
const size_t offset = it_off->second;
|
||||
fin.seekg(offset, std::ios::beg);
|
||||
if (!fin) {
|
||||
throw std::runtime_error(string_format("%s: failed to seek for tensor %s\n", __func__, t->name));
|
||||
}
|
||||
size_t num_bytes = ggml_nbytes(cur);
|
||||
if (ggml_backend_buft_is_host(buft)) {
|
||||
// for the CPU and Metal backend, we can read directly into the tensor
|
||||
fin.read(reinterpret_cast<char *>(cur->data), num_bytes);
|
||||
} else {
|
||||
// read into a temporary buffer first, then copy to device memory
|
||||
read_buf.resize(num_bytes);
|
||||
fin.read(reinterpret_cast<char *>(read_buf.data()), num_bytes);
|
||||
ggml_backend_tensor_set(cur, read_buf.data(), 0, num_bytes);
|
||||
// read the weight from file
|
||||
if (!ctx_clip.no_alloc) {
|
||||
size_t data_loaded = 0;
|
||||
for (auto & t : tensors_to_load) {
|
||||
ggml_tensor * cur = ggml_get_tensor(ctx_clip.ctx_data.get(), t->name);
|
||||
GGML_ASSERT(cur && "tensor not found in ctx_data");
|
||||
auto it_off = tensor_offset.find(t->name);
|
||||
GGML_ASSERT(it_off != tensor_offset.end() && "no offset for tensor");
|
||||
const size_t offset = it_off->second;
|
||||
fin.seekg(offset, std::ios::beg);
|
||||
if (!fin) {
|
||||
throw std::runtime_error(string_format("%s: failed to seek for tensor %s\n", __func__, t->name));
|
||||
}
|
||||
size_t num_bytes = ggml_nbytes(cur);
|
||||
if (ggml_backend_buft_is_host(buft)) {
|
||||
// for the CPU and Metal backend, we can read directly into the tensor
|
||||
fin.read(reinterpret_cast<char *>(cur->data), num_bytes);
|
||||
} else {
|
||||
// read into a temporary buffer first, then copy to device memory
|
||||
read_buf.resize(num_bytes);
|
||||
fin.read(reinterpret_cast<char *>(read_buf.data()), num_bytes);
|
||||
ggml_backend_tensor_set(cur, read_buf.data(), 0, num_bytes);
|
||||
}
|
||||
data_loaded += num_bytes;
|
||||
if (progress_callback && total_data_size > 0) {
|
||||
const float progress = (float)data_loaded / (float)total_data_size;
|
||||
if (!progress_callback(progress, progress_callback_user_data)) {
|
||||
throw std::runtime_error(string_format("%s: model loading cancelled by progress_callback\n", __func__));
|
||||
}
|
||||
}
|
||||
}
|
||||
LOG_DBG("%s: loaded %zu tensors from %s\n", __func__, tensors_to_load.size(), fname.c_str());
|
||||
} else {
|
||||
LOG_DBG("%s: no_alloc is set, skipping tensor data loading (%zu tensors)\n", __func__, tensors_to_load.size());
|
||||
}
|
||||
fin.close();
|
||||
|
||||
LOG_DBG("%s: loaded %zu tensors from %s\n", __func__, tensors_to_load.size(), fname.c_str());
|
||||
}
|
||||
|
||||
}
|
||||
@@ -2831,6 +2879,12 @@ struct clip_model_loader {
|
||||
img.set_size({sz, sz}, false, false);
|
||||
LOG_INF("%s: warmup with image size = %d x %d\n", __func__, sz, sz);
|
||||
} else {
|
||||
// GEMMA4UA uses n_mel_bins as a raw-waveform frame size (640), not a mel-bin count,
|
||||
// so the [1, 256] bound only applies to FFT-based models.
|
||||
const bool fft_based = ctx_clip.model.proj_type != PROJECTOR_TYPE_GEMMA4UA;
|
||||
if (hparams.n_mel_bins <= 0 || (fft_based && hparams.n_mel_bins > 256)) {
|
||||
throw std::runtime_error(string_format("%s: invalid n_mel_bins (%d), must be in [1, 256]\n", __func__, hparams.n_mel_bins));
|
||||
}
|
||||
img.set_size({hparams.warmup_audio_size, hparams.n_mel_bins}, false, false);
|
||||
LOG_INF("%s: warmup with audio size = %d\n", __func__, hparams.warmup_audio_size);
|
||||
}
|
||||
@@ -2994,7 +3048,13 @@ struct clip_model_loader {
|
||||
}
|
||||
return;
|
||||
}
|
||||
output = gguf_get_val_u32(ctx_gguf.get(), i);
|
||||
const uint32_t val = gguf_get_val_u32(ctx_gguf.get(), i);
|
||||
// sanity check
|
||||
if (val > (uint32_t) INT32_MAX) {
|
||||
throw std::runtime_error(string_format("%s: value %u for key '%s' exceeds INT32_MAX\n",
|
||||
__func__, val, key.c_str()));
|
||||
}
|
||||
output = (int) val;
|
||||
}
|
||||
|
||||
void get_f32(const std::string & key, float & output, bool required = true) const {
|
||||
@@ -3077,7 +3137,10 @@ struct clip_init_result clip_init(const char * fname, struct clip_context_params
|
||||
clip_ctx * ctx_audio = nullptr;
|
||||
|
||||
try {
|
||||
clip_model_loader loader(fname);
|
||||
clip_model_loader loader(fname,
|
||||
/* skip_tensors */ false,
|
||||
ctx_params.progress_callback,
|
||||
ctx_params.progress_callback_user_data);
|
||||
bool skip_audio = false;
|
||||
|
||||
if (loader.has_vision) {
|
||||
|
||||
@@ -24,6 +24,9 @@ struct clip_image_size {
|
||||
return !(*this == other);
|
||||
}
|
||||
int area() const {
|
||||
// avoid overflow when computing area
|
||||
GGML_ASSERT(width >= 0 && width <= 46000);
|
||||
GGML_ASSERT(height >= 0 && height <= 46000);
|
||||
return width * height;
|
||||
}
|
||||
};
|
||||
@@ -51,6 +54,8 @@ struct clip_context_params {
|
||||
ggml_backend_sched_eval_callback cb_eval;
|
||||
void * cb_eval_user_data;
|
||||
bool no_alloc;
|
||||
mtmd_progress_callback progress_callback;
|
||||
void * progress_callback_user_data;
|
||||
};
|
||||
|
||||
struct clip_init_result {
|
||||
|
||||
@@ -8,7 +8,9 @@ ggml_cgraph * clip_graph_internvl::build() {
|
||||
ggml_tensor * inp = build_inp();
|
||||
|
||||
// add CLS token
|
||||
inp = ggml_concat(ctx0, inp, model.class_embedding, 1);
|
||||
ggml_tensor * cls_repeated = ggml_repeat_4d(ctx0, model.class_embedding,
|
||||
model.class_embedding->ne[0], 1, n_batch, 1);
|
||||
inp = ggml_concat(ctx0, inp, cls_repeated, 1);
|
||||
|
||||
// The larger models use a different ViT, which uses RMS norm instead of layer norm
|
||||
// ref: https://github.com/ggml-org/llama.cpp/pull/13443#issuecomment-2869786188
|
||||
@@ -24,14 +26,15 @@ ggml_cgraph * clip_graph_internvl::build() {
|
||||
nullptr);
|
||||
|
||||
// remove CLS token
|
||||
cur = ggml_view_2d(ctx0, cur,
|
||||
n_embd, n_patches,
|
||||
ggml_row_size(cur->type, n_embd), 0);
|
||||
cur = ggml_view_3d(ctx0, cur,
|
||||
n_embd, n_patches, n_batch,
|
||||
cur->nb[1], cur->nb[2], 0);
|
||||
cur = ggml_cont(ctx0, cur);
|
||||
|
||||
// pixel shuffle
|
||||
{
|
||||
const int scale_factor = model.hparams.n_merge;
|
||||
const int bsz = 1; // batch size, always 1 for now since we don't support batching
|
||||
const int bsz = n_batch;
|
||||
const int height = n_patches_y;
|
||||
const int width = n_patches_x;
|
||||
GGML_ASSERT(scale_factor > 0);
|
||||
@@ -44,9 +47,10 @@ ggml_cgraph * clip_graph_internvl::build() {
|
||||
bsz);
|
||||
cur = ggml_permute(ctx0, cur, 0, 2, 1, 3);
|
||||
// flatten to 2D
|
||||
cur = ggml_cont_2d(ctx0, cur,
|
||||
cur = ggml_cont_3d(ctx0, cur,
|
||||
n_embd * scale_factor * scale_factor,
|
||||
cur->ne[1] * cur->ne[2]);
|
||||
cur->ne[1] * cur->ne[2],
|
||||
cur->ne[3]);
|
||||
}
|
||||
|
||||
// projector (always using GELU activation)
|
||||
|
||||
@@ -80,6 +80,7 @@ struct clip_graph_minicpmv4_6 : clip_graph {
|
||||
struct clip_graph_internvl : clip_graph {
|
||||
clip_graph_internvl(clip_ctx * ctx, const clip_image_f32 & img) : clip_graph(ctx, img) {}
|
||||
ggml_cgraph * build() override;
|
||||
bool support_batch() const override { return true; }
|
||||
};
|
||||
|
||||
struct clip_graph_nemotron_v2_vl : clip_graph {
|
||||
|
||||
+76
-63
@@ -32,8 +32,8 @@ void mtmd_audio_cache::fill_hann_window(uint32_t length, bool periodic) {
|
||||
}
|
||||
}
|
||||
|
||||
void mtmd_audio_cache::fill_mel_filterbank_matrix(int n_mel,
|
||||
int n_fft,
|
||||
void mtmd_audio_cache::fill_mel_filterbank_matrix(int64_t n_mel,
|
||||
int64_t n_fft,
|
||||
int sample_rate,
|
||||
float fmin,
|
||||
float fmax,
|
||||
@@ -86,11 +86,16 @@ void mtmd_audio_cache::fill_mel_filterbank_matrix(int n_mel,
|
||||
hz_pts[i] = mel_to_hz(mel_pts[i]);
|
||||
}
|
||||
|
||||
const int n_fft_bins = n_fft / 2 + 1;
|
||||
const int64_t n_fft_bins = n_fft / 2 + 1;
|
||||
|
||||
// Validate allocation size
|
||||
if ((size_t)n_mel * (size_t)n_fft_bins > SIZE_MAX) {
|
||||
GGML_ASSERT(false && "mel filterbank allocation too large");
|
||||
}
|
||||
|
||||
// filterbank
|
||||
std::vector<float> out(n_mel * n_fft_bins, 0);
|
||||
for (int m = 0; m < n_mel; ++m) {
|
||||
std::vector<float> out((size_t)n_mel * (size_t)n_fft_bins, 0);
|
||||
for (int64_t m = 0; m < n_mel; ++m) {
|
||||
const double f_left = hz_pts[m];
|
||||
const double f_center = hz_pts[m + 1];
|
||||
const double f_right = hz_pts[m + 2];
|
||||
@@ -266,8 +271,8 @@ static void ifft(const mtmd_audio_cache & cache, float * in, int N, float * out)
|
||||
}
|
||||
|
||||
struct filter_params {
|
||||
int32_t n_mel;
|
||||
int32_t n_fft_bins;
|
||||
int64_t n_mel;
|
||||
int64_t n_fft_bins;
|
||||
int32_t hann_window_size;
|
||||
int32_t hop_length;
|
||||
int32_t sample_rate;
|
||||
@@ -293,8 +298,8 @@ static void log_mel_spectrogram_worker_thread(int ith,
|
||||
std::vector<float> fft_in(frame_size * 2, 0.0);
|
||||
std::vector<float> fft_out(frame_size * 2 * 2 * 2);
|
||||
|
||||
int n_fft_bins = params.n_fft_bins;
|
||||
int i = ith;
|
||||
int64_t n_fft_bins = params.n_fft_bins;
|
||||
int64_t i = ith;
|
||||
|
||||
const auto & filters = cache.filters;
|
||||
|
||||
@@ -302,17 +307,18 @@ static void log_mel_spectrogram_worker_thread(int ith,
|
||||
GGML_ASSERT(n_fft_bins == 1 + (frame_size / 2));
|
||||
GGML_ASSERT(cache.sin_vals.size() == cache.cos_vals.size());
|
||||
// calculate FFT only when fft_in are not all zero
|
||||
for (; i < std::min(n_samples / frame_step + 1, out.n_len); i += n_threads) {
|
||||
const int offset = i * frame_step;
|
||||
for (; i < std::min((int64_t)(n_samples / frame_step + 1), out.n_len); i += n_threads) {
|
||||
const int64_t offset = i * frame_step;
|
||||
|
||||
// apply Hann window (~10% faster)
|
||||
for (int j = 0; j < std::min(frame_size, n_samples - offset); j++) {
|
||||
const int valid_len = std::min(frame_size, std::max(0, n_samples - (int)offset));
|
||||
for (int j = 0; j < valid_len; j++) {
|
||||
fft_in[j] = hann[j] * samples[offset + j];
|
||||
}
|
||||
|
||||
// fill the rest with zeros
|
||||
if (n_samples - offset < frame_size) {
|
||||
std::fill(fft_in.begin() + (n_samples - offset), fft_in.end(), 0.0);
|
||||
if (valid_len < frame_size) {
|
||||
std::fill(fft_in.begin() + valid_len, fft_in.end(), 0.0);
|
||||
}
|
||||
|
||||
// FFT
|
||||
@@ -325,7 +331,7 @@ static void log_mel_spectrogram_worker_thread(int ith,
|
||||
}
|
||||
|
||||
// mel spectrogram
|
||||
for (int j = 0; j < out.n_mel; j++) {
|
||||
for (int64_t j = 0; j < out.n_mel; j++) {
|
||||
double sum = 0.0;
|
||||
// unroll loop (suggested by GH user @lunixbochs)
|
||||
int k = 0;
|
||||
@@ -339,21 +345,21 @@ static void log_mel_spectrogram_worker_thread(int ith,
|
||||
}
|
||||
// handle n_fft remainder
|
||||
for (; k < n_fft_bins; k++) {
|
||||
sum += fft_out[k] * filters.data[j * n_fft_bins + k];
|
||||
sum += fft_out[k] * filters.data[(size_t)j * n_fft_bins + k];
|
||||
}
|
||||
sum = std::max(sum, (double)params.mel_floor);
|
||||
sum = params.use_natural_log
|
||||
? log(sum)
|
||||
: log10(sum);
|
||||
out.data[j * out.n_len + i] = sum;
|
||||
out.data[(size_t)j * out.n_len + i] = sum;
|
||||
}
|
||||
}
|
||||
|
||||
// Otherwise fft_out are all zero
|
||||
double sum = params.use_natural_log ? log(1e-10) : log10(1e-10);
|
||||
for (; i < out.n_len; i += n_threads) {
|
||||
for (int j = 0; j < out.n_mel; j++) {
|
||||
out.data[j * out.n_len + i] = sum;
|
||||
for (int64_t j = 0; j < out.n_mel; j++) {
|
||||
out.data[(size_t)j * out.n_len + i] = sum;
|
||||
}
|
||||
}
|
||||
}
|
||||
@@ -437,16 +443,21 @@ static bool log_mel_spectrogram(
|
||||
GGML_ASSERT(params.hop_length > 0);
|
||||
out.n_mel = params.n_mel;
|
||||
out.n_len = (n_samples - frame_size) / frame_step + 1;
|
||||
// TODO: handle these checks better
|
||||
if (out.n_mel > 0 && (unsigned long)out.n_len > SIZE_MAX / out.n_mel) {
|
||||
LOG_ERR("%s: size overflow\n", __func__);
|
||||
// Validate dimensions before allocation to prevent integer overflow
|
||||
if (out.n_mel <= 0 || out.n_len <= 0) {
|
||||
LOG_ERR("%s: invalid mel dimensions n_mel=%lld n_len=%lld\n", __func__, (long long)out.n_mel, (long long)out.n_len);
|
||||
return false;
|
||||
}
|
||||
const size_t total_size = (size_t)out.n_mel * (size_t)out.n_len;
|
||||
if (total_size > SIZE_MAX / sizeof(float)) {
|
||||
LOG_ERR("%s: size overflow: n_mel=%lld n_len=%lld\n", __func__, (long long)out.n_mel, (long long)out.n_len);
|
||||
return false;
|
||||
}
|
||||
if (n_samples < frame_size) {
|
||||
LOG_ERR("%s: not enough samples after padding\n", __func__);
|
||||
return false;
|
||||
}
|
||||
out.data.resize(out.n_mel * out.n_len);
|
||||
out.data.resize(total_size);
|
||||
|
||||
{
|
||||
std::vector<std::thread> workers(n_threads - 1);
|
||||
@@ -464,38 +475,39 @@ static bool log_mel_spectrogram(
|
||||
}
|
||||
}
|
||||
|
||||
const int effective_n_len = n_samples_in / frame_step;
|
||||
const int64_t effective_n_len = n_samples_in / frame_step;
|
||||
if (params.norm_per_feature) {
|
||||
GGML_ASSERT(effective_n_len > 1);
|
||||
for (int i = 0; i < out.n_mel; i++) {
|
||||
for (int64_t i = 0; i < out.n_mel; i++) {
|
||||
double mean = 0;
|
||||
for (int j = 0; j < effective_n_len; ++j) {
|
||||
mean += out.data[i * out.n_len + j];
|
||||
for (int64_t j = 0; j < effective_n_len; ++j) {
|
||||
mean += out.data[(size_t)i * out.n_len + j];
|
||||
}
|
||||
mean /= effective_n_len;
|
||||
|
||||
double var = 0.0;
|
||||
for (int j = 0; j < effective_n_len; ++j) {
|
||||
const double value = out.data[i * out.n_len + j] - mean;
|
||||
for (int64_t j = 0; j < effective_n_len; ++j) {
|
||||
const double value = out.data[(size_t)i * out.n_len + j] - mean;
|
||||
var += value * value;
|
||||
}
|
||||
var /= effective_n_len - 1; // unbiased
|
||||
const double mstd = std::sqrt(var + 1e-5);
|
||||
|
||||
for (int j = 0; j < effective_n_len; ++j) {
|
||||
auto &value = out.data[i * out.n_len + j];
|
||||
for (int64_t j = 0; j < effective_n_len; ++j) {
|
||||
auto &value = out.data[(size_t)i * out.n_len + j];
|
||||
value = (value - mean) / mstd;
|
||||
}
|
||||
|
||||
// pad the rest with zeros
|
||||
for (int j = effective_n_len; j < out.n_len; ++j) {
|
||||
out.data[i * out.n_len + j] = 0.0;
|
||||
for (int64_t j = effective_n_len; j < out.n_len; ++j) {
|
||||
out.data[(size_t)i * out.n_len + j] = 0.0;
|
||||
}
|
||||
}
|
||||
} else if (!params.no_padding) {
|
||||
// Whisper-style clamping and normalization (NOT used by Gemma4)
|
||||
double mmax = -1e20;
|
||||
for (int i = 0; i < out.n_mel*out.n_len; i++) {
|
||||
const size_t mel_size = (size_t)out.n_mel * (size_t)out.n_len;
|
||||
for (size_t i = 0; i < mel_size; i++) {
|
||||
if (out.data[i] > mmax) {
|
||||
mmax = out.data[i];
|
||||
}
|
||||
@@ -503,7 +515,7 @@ static bool log_mel_spectrogram(
|
||||
|
||||
mmax -= 8.0;
|
||||
|
||||
for (int i = 0; i < out.n_mel*out.n_len; i++) {
|
||||
for (size_t i = 0; i < mel_size; i++) {
|
||||
if (out.data[i] < mmax) {
|
||||
out.data[i] = mmax;
|
||||
}
|
||||
@@ -582,13 +594,13 @@ bool mtmd_audio_preprocessor_whisper::preprocess(const float * s
|
||||
// because the cgraph in clip.cpp only accepts 3000 frames each, we need to split the mel
|
||||
// we always expect the mel to have 3000 silent frames at the end
|
||||
if (DEBUG) {
|
||||
printf("output: n_mel = %d, n_len = %d\n", out_full.n_mel, out_full.n_len);
|
||||
printf("output: n_mel = %d, n_len = %d\n", (int) out_full.n_mel, (int) out_full.n_len);
|
||||
}
|
||||
const size_t frames_per_chunk = 3000;
|
||||
GGML_ASSERT((size_t) out_full.n_len > frames_per_chunk);
|
||||
for (size_t off = 0; off < (size_t) out_full.n_len; off += frames_per_chunk) {
|
||||
int n_len = std::min(frames_per_chunk, (size_t) out_full.n_len - off);
|
||||
if ((size_t) n_len < frames_per_chunk) {
|
||||
int64_t n_len = std::min((int64_t)frames_per_chunk, out_full.n_len - (int64_t)off);
|
||||
if (n_len < (int64_t)frames_per_chunk) {
|
||||
break; // last incomplete chunk will always be a padded chunk, safe to ignore
|
||||
}
|
||||
|
||||
@@ -596,10 +608,10 @@ bool mtmd_audio_preprocessor_whisper::preprocess(const float * s
|
||||
out_chunk.n_len = n_len;
|
||||
out_chunk.n_mel = out_full.n_mel;
|
||||
out_chunk.n_len_org = out_full.n_mel; // unused
|
||||
out_chunk.data.reserve(out_chunk.n_mel * out_chunk.n_len);
|
||||
out_chunk.data.reserve((size_t)out_chunk.n_mel * (size_t)out_chunk.n_len);
|
||||
|
||||
for (int i = 0; i < out_full.n_mel; i++) {
|
||||
auto src = out_full.data.begin() + i * out_full.n_len + off;
|
||||
for (int64_t i = 0; i < out_full.n_mel; i++) {
|
||||
auto src = out_full.data.begin() + (size_t)i * out_full.n_len + off;
|
||||
out_chunk.data.insert(out_chunk.data.end(), src, src + frames_per_chunk);
|
||||
}
|
||||
|
||||
@@ -681,8 +693,8 @@ bool mtmd_audio_preprocessor_qwen3a::preprocess(const float * sa
|
||||
|
||||
// The effective frame count: center-padded STFT gives ~n_samples/hop_length frames.
|
||||
// We take min(mel_full.n_len, n_samples/hop + 1) to avoid including excess frames.
|
||||
const int n_eff = std::min(mel_full.n_len,
|
||||
(int)(n_samples / hparams.audio_hop_len) + 1);
|
||||
const int64_t n_eff = std::min(mel_full.n_len,
|
||||
(int64_t)(n_samples / hparams.audio_hop_len) + 1);
|
||||
|
||||
// Split into inference windows matching n_window_infer=800 from model config.
|
||||
// Each window is padded to the next multiple of chunk_size for the cgraph.
|
||||
@@ -690,18 +702,18 @@ bool mtmd_audio_preprocessor_qwen3a::preprocess(const float * sa
|
||||
const int chunk_size = 100; // conv sub-chunk size (n_window * 2, n_window=50)
|
||||
const int window_size = 800; // mel frames per forward pass (n_window_infer=800)
|
||||
|
||||
for (int off = 0; off < n_eff; off += window_size) {
|
||||
const int win_eff = std::min(window_size, n_eff - off);
|
||||
const int n_chunks = (win_eff + chunk_size - 1) / chunk_size;
|
||||
const int n_padded = n_chunks * chunk_size;
|
||||
for (int64_t off = 0; off < n_eff; off += window_size) {
|
||||
const int64_t win_eff = std::min((int64_t)window_size, n_eff - off);
|
||||
const int64_t n_chunks = (win_eff + chunk_size - 1) / chunk_size;
|
||||
const int64_t n_padded = n_chunks * chunk_size;
|
||||
|
||||
mtmd_audio_mel out;
|
||||
out.n_mel = mel_full.n_mel;
|
||||
out.n_len = n_padded;
|
||||
out.n_len_org = win_eff;
|
||||
out.data.assign(out.n_mel * out.n_len, 0.0f);
|
||||
for (int m = 0; m < out.n_mel; m++) {
|
||||
const int copy_len = std::min(win_eff, mel_full.n_len - off);
|
||||
out.data.assign((size_t)out.n_mel * (size_t)out.n_len, 0.0f);
|
||||
for (int64_t m = 0; m < out.n_mel; m++) {
|
||||
const int64_t copy_len = std::min((int64_t)win_eff, mel_full.n_len - off);
|
||||
if (copy_len > 0) {
|
||||
std::copy(mel_full.data.begin() + (size_t)m * mel_full.n_len + off,
|
||||
mel_full.data.begin() + (size_t)m * mel_full.n_len + off + copy_len,
|
||||
@@ -823,37 +835,38 @@ bool mtmd_audio_preprocessor_granite_speech::preprocess(const float *
|
||||
}
|
||||
|
||||
double mmax = -1e20;
|
||||
for (int i = 0; i < mel.n_mel * mel.n_len; i++) {
|
||||
const size_t mel_size = (size_t)mel.n_mel * (size_t)mel.n_len;
|
||||
for (size_t i = 0; i < mel_size; i++) {
|
||||
if (mel.data[i] > mmax) {
|
||||
mmax = mel.data[i];
|
||||
}
|
||||
}
|
||||
mmax -= 8.0;
|
||||
|
||||
for (int i = 0; i < mel.n_mel * mel.n_len; i++) {
|
||||
for (size_t i = 0; i < mel_size; i++) {
|
||||
if (mel.data[i] < mmax) {
|
||||
mel.data[i] = mmax;
|
||||
}
|
||||
mel.data[i] = (mel.data[i] + 4.0) / 4.0;
|
||||
}
|
||||
|
||||
int n_frames = mel.n_len;
|
||||
int64_t n_frames = mel.n_len;
|
||||
if (n_frames % 2 == 1) {
|
||||
n_frames--;
|
||||
}
|
||||
const int n_mel = mel.n_mel;
|
||||
const int n_stacked = n_frames / 2;
|
||||
const int64_t n_mel = mel.n_mel;
|
||||
const int64_t n_stacked = n_frames / 2;
|
||||
|
||||
mtmd_audio_mel stacked;
|
||||
stacked.n_mel = 2 * n_mel;
|
||||
stacked.n_len = n_stacked;
|
||||
stacked.n_len_org = (int)n_samples;
|
||||
stacked.data.resize(2 * n_mel * n_stacked);
|
||||
stacked.n_len_org = (int64_t)n_samples;
|
||||
stacked.data.resize((size_t)2 * (size_t)n_mel * (size_t)n_stacked);
|
||||
|
||||
for (int t = 0; t < n_stacked; t++) {
|
||||
for (int m = 0; m < n_mel; m++) {
|
||||
stacked.data[m * n_stacked + t] = mel.data[m * mel.n_len + 2 * t];
|
||||
stacked.data[(m + n_mel) * n_stacked + t] = mel.data[m * mel.n_len + 2 * t + 1];
|
||||
for (int64_t t = 0; t < n_stacked; t++) {
|
||||
for (int64_t m = 0; m < n_mel; m++) {
|
||||
stacked.data[(size_t)m * n_stacked + t] = mel.data[(size_t)m * mel.n_len + 2 * t];
|
||||
stacked.data[(size_t)(m + n_mel) * n_stacked + t] = mel.data[(size_t)m * mel.n_len + 2 * t + 1];
|
||||
}
|
||||
}
|
||||
|
||||
@@ -921,8 +934,8 @@ bool mtmd_audio_preprocessor_gemma4a::preprocess(const float * s
|
||||
const int hop = hparams.audio_hop_len;
|
||||
const int n_with_left = (int)chunk_len + pad_left;
|
||||
// PyTorch: unfold(size=frame_length+1, step=hop) on semicausal-padded waveform
|
||||
const int pt_frames = (n_with_left - (hparams.audio_window_len + 1)) / hop + 1;
|
||||
const int n_padded_needed = (pt_frames - 1) * hop + fft_size;
|
||||
const int64_t pt_frames = (n_with_left - (hparams.audio_window_len + 1)) / hop + 1;
|
||||
const int64_t n_padded_needed = (pt_frames - 1) * hop + fft_size;
|
||||
const int total_pad = std::max((int)(n_padded_needed - (int)chunk_len), pad_left);
|
||||
std::vector<float> padded_samples(total_pad + chunk_len, 0.0f);
|
||||
std::copy(chunk_ptr, chunk_ptr + chunk_len, padded_samples.data() + pad_left);
|
||||
|
||||
@@ -10,16 +10,16 @@
|
||||
#define MTMD_INTERNAL_HEADER
|
||||
|
||||
struct mtmd_audio_mel {
|
||||
int n_len;
|
||||
int n_len_org;
|
||||
int n_mel;
|
||||
int64_t n_len;
|
||||
int64_t n_len_org;
|
||||
int64_t n_mel;
|
||||
|
||||
std::vector<float> data;
|
||||
};
|
||||
|
||||
struct mtmd_audio_mel_filters {
|
||||
int32_t n_mel;
|
||||
int32_t n_fft;
|
||||
int64_t n_mel;
|
||||
int64_t n_fft;
|
||||
|
||||
std::vector<float> data;
|
||||
};
|
||||
@@ -39,8 +39,8 @@ struct mtmd_audio_cache {
|
||||
|
||||
// Build mel filterbank matrix [n_mel × n_fft_bins] at runtime.
|
||||
// n_fft_bins must be (N_fft / 2 + 1). Example: if N_fft=512 -> n_fft_bins=257.
|
||||
void fill_mel_filterbank_matrix(int n_mel,
|
||||
int n_fft,
|
||||
void fill_mel_filterbank_matrix(int64_t n_mel,
|
||||
int64_t n_fft,
|
||||
int sample_rate, // e.g. 16000
|
||||
float fmin = 0.0f, // e.g. 0.0
|
||||
float fmax = -1.0f, // e.g. sr/2; pass -1 for auto
|
||||
|
||||
@@ -396,6 +396,9 @@ int main(int argc, char ** argv) {
|
||||
|
||||
int n_predict = params.n_predict < 0 ? INT_MAX : params.n_predict;
|
||||
|
||||
console::init(params.simple_io, params.use_color);
|
||||
atexit([]() { console::cleanup(); });
|
||||
|
||||
// Ctrl+C handling
|
||||
{
|
||||
#if defined (__unix__) || (defined (__APPLE__) && defined (__MACH__))
|
||||
|
||||
@@ -582,13 +582,29 @@ mtmd_helper_bitmap_wrapper mtmd_helper_bitmap_init_from_buf(mtmd_context * ctx,
|
||||
}
|
||||
|
||||
mtmd_helper_bitmap_wrapper mtmd_helper_bitmap_init_from_file(mtmd_context * ctx, const char * fname, bool placeholder) {
|
||||
std::vector<unsigned char> buf;
|
||||
#ifdef _WIN32
|
||||
int wlen = MultiByteToWideChar(CP_UTF8, 0, fname, -1, NULL, 0);
|
||||
if (!wlen) {
|
||||
LOG_ERR("Unable to convert filename to UTF-16: %s\n", fname);
|
||||
return {nullptr, nullptr};
|
||||
}
|
||||
std::vector<wchar_t> wfname(wlen);
|
||||
wlen = MultiByteToWideChar(CP_UTF8, 0, fname, -1, wfname.data(), wlen);
|
||||
if (!wlen) {
|
||||
LOG_ERR("Unable to convert filename to UTF-16: %s\n", fname);
|
||||
return {nullptr, nullptr};
|
||||
}
|
||||
FILE * f = _wfopen(wfname.data(), L"rb");
|
||||
#else
|
||||
FILE * f = fopen(fname, "rb");
|
||||
#endif
|
||||
if (!f) {
|
||||
LOG_ERR("Unable to open file %s: %s\n", fname, strerror(errno));
|
||||
return {nullptr, nullptr};
|
||||
}
|
||||
|
||||
std::vector<unsigned char> buf;
|
||||
|
||||
fseek(f, 0, SEEK_END);
|
||||
long file_size = ftell(f);
|
||||
fseek(f, 0, SEEK_SET);
|
||||
|
||||
+12
-2
@@ -251,6 +251,8 @@ mtmd_context_params mtmd_context_params_default() {
|
||||
/* cb_eval */ nullptr,
|
||||
/* cb_eval_user_data */ nullptr,
|
||||
/* batch_max_tokens */ 1024,
|
||||
/* progress_callback */ nullptr,
|
||||
/* progress_callback_user_data */ nullptr,
|
||||
};
|
||||
return params;
|
||||
}
|
||||
@@ -345,6 +347,8 @@ struct mtmd_context {
|
||||
/* cb_eval */ ctx_params.cb_eval,
|
||||
/* cb_eval_user_data */ ctx_params.cb_eval_user_data,
|
||||
/* no_alloc */ no_alloc,
|
||||
/* progress_callback */ ctx_params.progress_callback,
|
||||
/* progress_callback_user_data */ ctx_params.progress_callback_user_data,
|
||||
};
|
||||
|
||||
auto res = clip_init(mmproj_fname, ctx_clip_params);
|
||||
@@ -1295,9 +1299,12 @@ struct mtmd_tokenizer {
|
||||
for (auto & mel_spec : mel_spec_chunks) {
|
||||
const bool is_placeholder = mel_spec.data.empty();
|
||||
|
||||
// Validate dimensions fit in clip_image_size (int)
|
||||
GGML_ASSERT(mel_spec.n_len <= INT32_MAX && mel_spec.n_len >= 0);
|
||||
GGML_ASSERT(mel_spec.n_mel <= INT32_MAX && mel_spec.n_mel >= 0);
|
||||
clip_image_f32 mel_f32;
|
||||
mel_f32.set_size(
|
||||
{mel_spec.n_len, mel_spec.n_mel},
|
||||
{(int)mel_spec.n_len, (int)mel_spec.n_mel},
|
||||
is_placeholder, /* is_audio */ true);
|
||||
mel_f32.cpy_buf(mel_spec.data);
|
||||
|
||||
@@ -2130,9 +2137,12 @@ std::map<ggml_backend_dev_t, size_t> mtmd_get_memory_usage(const char * mmproj_f
|
||||
mtmd::context_ptr ctx;
|
||||
auto saved_log_callback = g_logger_state.log_callback;
|
||||
auto saved_log_user_data = g_logger_state.log_callback_user_data;
|
||||
|
||||
ctx_params.progress_callback = nullptr;
|
||||
|
||||
try {
|
||||
mtmd_log_set(stub_log_callback, nullptr); // suppress logging
|
||||
ctx.reset(new mtmd_context(mmproj_fname, nullptr, ctx_params));
|
||||
ctx.reset(new mtmd_context(mmproj_fname, nullptr, ctx_params, true));
|
||||
mtmd_log_set(saved_log_callback, saved_log_user_data); // restore log callback
|
||||
std::map<ggml_backend_dev_t, size_t> total_mem;
|
||||
auto merge = [&](const struct clip_ctx * c) {
|
||||
|
||||
@@ -83,6 +83,8 @@ typedef struct mtmd_input_chunks mtmd_input_chunks;
|
||||
typedef struct mtmd_input_text mtmd_input_text;
|
||||
typedef struct mtmd_batch mtmd_batch;
|
||||
|
||||
typedef bool (*mtmd_progress_callback)(float progress, void * user_data);
|
||||
|
||||
struct mtmd_context_params {
|
||||
bool use_gpu;
|
||||
bool print_timings;
|
||||
@@ -104,6 +106,12 @@ struct mtmd_context_params {
|
||||
int32_t batch_max_tokens; // maximum number of output tokens in a batch
|
||||
// (note: this is not a hard-limit, the first image will always be added even if it exceeds this limit)
|
||||
// (default: 1024)
|
||||
|
||||
// Called with a progress value between 0.0 and 1.0. Pass NULL to disable.
|
||||
// If the provided progress_callback returns true, model loading continues.
|
||||
// If it returns false, model loading is immediately aborted.
|
||||
mtmd_progress_callback progress_callback;
|
||||
void * progress_callback_user_data;
|
||||
};
|
||||
|
||||
MTMD_API const char * mtmd_default_marker(void);
|
||||
|
||||
@@ -180,6 +180,17 @@ That requires `JSON.stringify` when formatted to message content:
|
||||
}
|
||||
```
|
||||
|
||||
### Router mode: how child <--> router communicates
|
||||
|
||||
Upon spawning a new child process using `subprocess`, both child and router listen to the stdout/stderr (combined)
|
||||
|
||||
For the direction from child to router:
|
||||
- Generic messages are logs, it will be forwarded to router's stdout
|
||||
- Special state update messages are prefixed by `cmd_child_to_router:state:`, followed by a JSON. See `server_models::handle_child_state` for more
|
||||
|
||||
For the direction from router to child:
|
||||
- When server sends `cmd_router_to_child:exit`, the child should exit gracefully --> if after `DEFAULT_STOP_TIMEOUT` and the child is still running, force-kill it
|
||||
|
||||
### Model management API (router mode)
|
||||
|
||||
Model management API was added via PR [#23976](https://github.com/ggml-org/llama.cpp/pull/23976)
|
||||
|
||||
+39
-13
@@ -175,13 +175,12 @@ For the full list of features, please refer to [server's changelog](https://gith
|
||||
| `-np, --parallel N` | number of server slots (default: -1, -1 = auto)<br/>(env: LLAMA_ARG_N_PARALLEL) |
|
||||
| `-cb, --cont-batching, -nocb, --no-cont-batching` | whether to enable continuous batching (a.k.a dynamic batching) (default: enabled)<br/>(env: LLAMA_ARG_CONT_BATCHING) |
|
||||
| `-mm, --mmproj FILE` | path to a multimodal projector file. see tools/mtmd/README.md<br/>note: if -hf is used, this argument can be omitted<br/>(env: LLAMA_ARG_MMPROJ) |
|
||||
| `-tk, --talker-model FILE` | path to the qwen3-omni talker gguf, enables the /v1/audio/speech endpoint<br/>(env: LLAMA_ARG_TALKER_MODEL) |
|
||||
| `-c2w, --code2wav-model FILE` | path to the qwen3-omni code2wav gguf, the talker code detokenizer<br/>(env: LLAMA_ARG_CODE2WAV_MODEL) |
|
||||
| `-mmu, --mmproj-url URL` | URL to a multimodal projector file. see tools/mtmd/README.md<br/>(env: LLAMA_ARG_MMPROJ_URL) |
|
||||
| `--mmproj-auto, --no-mmproj, --no-mmproj-auto` | whether to use multimodal projector file (if available), useful when using -hf (default: enabled)<br/>(env: LLAMA_ARG_MMPROJ_AUTO) |
|
||||
| `--mmproj-offload, --no-mmproj-offload` | whether to enable GPU offloading for multimodal projector (default: enabled)<br/>(env: LLAMA_ARG_MMPROJ_OFFLOAD) |
|
||||
| `--image-min-tokens N` | minimum number of tokens each image can take, only used by vision models with dynamic resolution (default: read from model)<br/>(env: LLAMA_ARG_IMAGE_MIN_TOKENS) |
|
||||
| `--image-max-tokens N` | maximum number of tokens each image can take, only used by vision models with dynamic resolution (default: read from model)<br/>(env: LLAMA_ARG_IMAGE_MAX_TOKENS) |
|
||||
| `--mtmd-batch-max-tokens N` | maximum number of image tokens per batch when encoding images (default: 1024)<br/>(env: LLAMA_ARG_MTMD_BATCH_MAX_TOKENS) |
|
||||
| `-a, --alias STRING` | set model name aliases, comma-separated (to be used by API)<br/>(env: LLAMA_ARG_ALIAS) |
|
||||
| `--tags STRING` | set model tags, comma-separated (informational, not used for routing)<br/>(env: LLAMA_ARG_TAGS) |
|
||||
| `--embd-normalize N` | normalisation for embeddings (default: 2) (-1=none, 0=max absolute int16, 1=taxicab, 2=euclidean, >2=p-norm) |
|
||||
@@ -190,23 +189,21 @@ For the full list of features, please refer to [server's changelog](https://gith
|
||||
| `--reuse-port` | allow multiple sockets to bind to the same port (default: disabled)<br/>(env: LLAMA_ARG_REUSE_PORT) |
|
||||
| `--path PATH` | path to serve static files from (default: )<br/>(env: LLAMA_ARG_STATIC_PATH) |
|
||||
| `--api-prefix PREFIX` | prefix path the server serves from, without the trailing slash (default: )<br/>(env: LLAMA_ARG_API_PREFIX) |
|
||||
| `--webui-config JSON` | [DEPRECATED: use --ui-config] JSON that provides default WebUI settings (overrides WebUI defaults)<br/>(env: LLAMA_ARG_WEBUI_CONFIG) |
|
||||
| `--ui-config JSON` | JSON that provides default UI settings (overrides UI defaults)<br/>(env: LLAMA_ARG_UI_CONFIG) |
|
||||
| `--webui-config-file PATH` | [DEPRECATED: use --ui-config-file] JSON file that provides default WebUI settings (overrides WebUI defaults)<br/>(env: LLAMA_ARG_WEBUI_CONFIG_FILE) |
|
||||
| `--ui-config-file PATH` | JSON file that provides default UI settings (overrides UI defaults)<br/>(env: LLAMA_ARG_UI_CONFIG_FILE) |
|
||||
| `--webui-mcp-proxy, --no-webui-mcp-proxy` | [DEPRECATED: use --ui-mcp-proxy/--no-ui-mcp-proxy] experimental: whether to enable MCP CORS proxy<br/>(env: LLAMA_ARG_WEBUI_MCP_PROXY) |
|
||||
| `--ui-mcp-proxy, --no-ui-mcp-proxy` | experimental: whether to enable MCP CORS proxy - do not enable in untrusted environments (default: disabled)<br/>(env: LLAMA_ARG_UI_MCP_PROXY) |
|
||||
| `--ui-config, --webui-config JSON` | JSON that provides default UI settings (overrides UI defaults)<br/>(env: LLAMA_ARG_UI_CONFIG) |
|
||||
| `--ui-config-file, --webui-config-file PATH` | JSON file that provides default UI settings (overrides UI defaults)<br/>(env: LLAMA_ARG_UI_CONFIG_FILE) |
|
||||
| `--ui-mcp-proxy, --webui-mcp-proxy, --no-ui-mcp-proxy, --no-webui-mcp-proxy` | experimental: whether to enable MCP CORS proxy - do not enable in untrusted environments (default: disabled)<br/>(env: LLAMA_ARG_UI_MCP_PROXY) |
|
||||
| `--tools TOOL1,TOOL2,...` | experimental: whether to enable built-in tools for AI agents - do not enable in untrusted environments (default: no tools)<br/>specify "all" to enable all tools<br/>available tools: read_file, file_glob_search, grep_search, exec_shell_command, write_file, edit_file, apply_diff, get_datetime<br/>(env: LLAMA_ARG_TOOLS) |
|
||||
| `--webui, --no-webui` | [DEPRECATED: use --ui/--no-ui] whether to enable the Web UI<br/>(env: LLAMA_ARG_WEBUI) |
|
||||
| `--ui, --no-ui` | whether to enable the Web UI (default: enabled)<br/>(env: LLAMA_ARG_UI) |
|
||||
| `-ag, --agent, -no-ag, --no-agent` | whether to enable CORS proxy and all built-in tools - do not enable in untrusted environments (default: disabled)<br/>(env: LLAMA_ARG_AGENT) |
|
||||
| `--ui, --webui, --no-ui, --no-webui` | whether to enable the Web UI (default: enabled)<br/>(env: LLAMA_ARG_UI) |
|
||||
| `--embedding, --embeddings` | restrict to only support embedding use case; use only with dedicated embedding models (default: disabled)<br/>(env: LLAMA_ARG_EMBEDDINGS) |
|
||||
| `--rerank, --reranking` | enable reranking endpoint on server (default: disabled)<br/>(env: LLAMA_ARG_RERANKING) |
|
||||
| `--api-key KEY` | API key to use for authentication, multiple keys can be provided as a comma-separated list (default: none)<br/>(env: LLAMA_API_KEY) |
|
||||
| `--api-key-file FNAME` | path to file containing API keys (default: none)<br/>(env: LLAMA_ARG_API_KEY_FILE) |
|
||||
| `--api-key-file FNAME` | path to file containing API keys, one per line; lines starting with a hash are treated as comments (default: none)<br/>(env: LLAMA_ARG_API_KEY_FILE) |
|
||||
| `--ssl-key-file FNAME` | path to file a PEM-encoded SSL private key<br/>(env: LLAMA_ARG_SSL_KEY_FILE) |
|
||||
| `--ssl-cert-file FNAME` | path to file a PEM-encoded SSL certificate<br/>(env: LLAMA_ARG_SSL_CERT_FILE) |
|
||||
| `--chat-template-kwargs STRING` | sets additional params for the json template parser, must be a valid json object string, e.g. '{"key1":"value1","key2":"value2"}'<br/>(env: LLAMA_ARG_CHAT_TEMPLATE_KWARGS) |
|
||||
| `-to, --timeout N` | server read/write timeout in seconds (default: 3600)<br/>(env: LLAMA_ARG_TIMEOUT) |
|
||||
| `--sse-ping-interval N` | server SSE ping interval in seconds (-1 = disabled, default: 30)<br/>(env: LLAMA_ARG_SSE_PING_INTERVAL) |
|
||||
| `--threads-http N` | number of threads used to process HTTP requests (default: -1)<br/>(env: LLAMA_ARG_THREADS_HTTP) |
|
||||
| `--cache-prompt, --no-cache-prompt` | whether to enable prompt caching (default: enabled)<br/>(env: LLAMA_ARG_CACHE_PROMPT) |
|
||||
| `--cache-reuse N` | min chunk size to attempt reusing from the cache via KV shifting, requires prompt caching to be enabled (default: 0)<br/>[(card)](https://ggml.ai/f0.png)<br/>(env: LLAMA_ARG_CACHE_REUSE) |
|
||||
@@ -231,6 +228,7 @@ For the full list of features, please refer to [server's changelog](https://gith
|
||||
| `-sps, --slot-prompt-similarity SIMILARITY` | how much the prompt of a request must match the prompt of a slot in order to use that slot (default: 0.10, 0.0 = disabled) |
|
||||
| `--lora-init-without-apply` | load LoRA adapters without applying them (apply later via POST /lora-adapters) (default: disabled) |
|
||||
| `--sleep-idle-seconds SECONDS` | number of seconds of idleness after which the server will sleep (default: -1; -1 = disabled) |
|
||||
| `--log-prompts-dir PATH` | Log prompts to directory (only used for debugging, default: disabled) |
|
||||
| `--spec-draft-hf, -hfd, -hfrd, --hf-repo-draft <user>/<model>[:quant]` | Same as --hf-repo, but for the draft model (default: unused)<br/>(env: LLAMA_ARG_SPEC_DRAFT_HF_REPO) |
|
||||
| `--spec-draft-threads, -td, --threads-draft N` | number of threads to use during generation (default: same as --threads) |
|
||||
| `--spec-draft-threads-batch, -tbd, --threads-batch-draft N` | number of threads to use during batch and prompt processing (default: same as --threads-draft) |
|
||||
@@ -1861,9 +1859,37 @@ Example events:
|
||||
|
||||
{
|
||||
"model": "...",
|
||||
"event": "download_finished",
|
||||
"event": "model_status",
|
||||
"data": {
|
||||
"status": "loading"
|
||||
"status": "loading",
|
||||
"progress": {
|
||||
"stages": ["text_model", "spec_model", "mmproj_model"],
|
||||
"current": "text_model",
|
||||
"value": 0.5
|
||||
}
|
||||
}
|
||||
}
|
||||
// note for "loading" status:
|
||||
// - subsequent events will follow the same order of "stages" list
|
||||
// - mmap is may report incorrect progress on some platforms; if you need exact progress, use --no-mmap
|
||||
|
||||
{
|
||||
"model": "...",
|
||||
"event": "model_status",
|
||||
"data": {
|
||||
"status": "loaded",
|
||||
"info": {
|
||||
// note: only include info on first load
|
||||
// waking up from sleep doesn't have this
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
{
|
||||
"model": "...",
|
||||
"event": "model_status",
|
||||
"data": {
|
||||
"status": "sleeping"
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
@@ -12,6 +12,7 @@
|
||||
#include <random>
|
||||
#include <sstream>
|
||||
#include <fstream>
|
||||
#include <limits>
|
||||
|
||||
json format_error_response(const std::string & message, const enum error_type type) {
|
||||
std::string type_str;
|
||||
@@ -1238,7 +1239,7 @@ json format_response_rerank(
|
||||
// other utils
|
||||
//
|
||||
|
||||
std::vector<llama_token_data> get_token_probabilities(llama_context * ctx, int idx) {
|
||||
std::vector<llama_token_data> get_token_probabilities(llama_context * ctx, int idx, size_t n_top) {
|
||||
std::vector<llama_token_data> cur;
|
||||
|
||||
const auto * logits = llama_get_logits_ith(ctx, idx);
|
||||
@@ -1257,21 +1258,34 @@ std::vector<llama_token_data> get_token_probabilities(llama_context * ctx, int i
|
||||
}
|
||||
}
|
||||
|
||||
// sort tokens by logits
|
||||
std::sort(cur.begin(), cur.end(), [](const llama_token_data & a, const llama_token_data & b) {
|
||||
return a.logit > b.logit;
|
||||
});
|
||||
// sort tokens by logits (partial: only the leading `n_top` need ordering)
|
||||
if (n_top > cur.size()) {
|
||||
n_top = cur.size();
|
||||
}
|
||||
if (n_top > 0) {
|
||||
std::partial_sort(cur.begin(), cur.begin() + n_top, cur.end(),
|
||||
[](const llama_token_data & a, const llama_token_data & b) {
|
||||
return a.logit > b.logit;
|
||||
});
|
||||
}
|
||||
|
||||
// apply softmax
|
||||
float max_l = cur[0].logit;
|
||||
float max_l = -std::numeric_limits<float>::infinity();
|
||||
if (n_top > 0) {
|
||||
max_l = cur[0].logit; // partial_sort guarantees the absolute maximum is at index 0
|
||||
} else {
|
||||
for (const auto & t : cur) {
|
||||
max_l = std::max(max_l, t.logit);
|
||||
}
|
||||
}
|
||||
float cum_sum = 0.0f;
|
||||
for (size_t i = 0; i < cur.size(); ++i) {
|
||||
float p = expf(cur[i].logit - max_l);
|
||||
cur[i].p = p;
|
||||
for (auto & t : cur) {
|
||||
float p = expf(t.logit - max_l);
|
||||
t.p = p;
|
||||
cum_sum += p;
|
||||
}
|
||||
for (size_t i = 0; i < cur.size(); ++i) {
|
||||
cur[i].p /= cum_sum;
|
||||
for (auto & t : cur) {
|
||||
t.p /= cum_sum;
|
||||
}
|
||||
|
||||
return cur;
|
||||
|
||||
@@ -326,7 +326,7 @@ json format_response_rerank(
|
||||
// other utils
|
||||
//
|
||||
|
||||
std::vector<llama_token_data> get_token_probabilities(llama_context * ctx, int idx);
|
||||
std::vector<llama_token_data> get_token_probabilities(llama_context * ctx, int idx, size_t n_top);
|
||||
|
||||
std::string safe_json_to_str(const json & data);
|
||||
|
||||
|
||||
+718
-398
File diff suppressed because it is too large
Load Diff
@@ -22,8 +22,7 @@ struct server_context_meta {
|
||||
bool has_inp_image;
|
||||
bool has_inp_audio;
|
||||
bool has_inp_video;
|
||||
json json_ui_settings; // Primary: new name
|
||||
json json_webui_settings; // Deprecated: use json_ui_settings instead (kept for backward compat)
|
||||
json json_ui_settings;
|
||||
int slot_n_ctx;
|
||||
enum llama_pooling_type pooling_type;
|
||||
|
||||
@@ -53,6 +52,31 @@ struct server_context_meta {
|
||||
uint64_t model_size;
|
||||
};
|
||||
|
||||
enum server_state {
|
||||
// SERVER_STATE_DOWNLOADING,
|
||||
SERVER_STATE_LOADING,
|
||||
SERVER_STATE_READY,
|
||||
SERVER_STATE_SLEEPING,
|
||||
};
|
||||
|
||||
static std::string server_state_to_str(server_state state) {
|
||||
switch (state) {
|
||||
case SERVER_STATE_LOADING: return "loading";
|
||||
case SERVER_STATE_READY: return "ready";
|
||||
case SERVER_STATE_SLEEPING: return "sleeping";
|
||||
default: GGML_ASSERT(false && "invalid server_state");
|
||||
}
|
||||
}
|
||||
|
||||
static server_state server_state_from_str(const std::string & str) {
|
||||
if (str == "loading") return SERVER_STATE_LOADING;
|
||||
if (str == "ready") return SERVER_STATE_READY;
|
||||
if (str == "sleeping") return SERVER_STATE_SLEEPING;
|
||||
GGML_ASSERT(false && "invalid server_state string");
|
||||
}
|
||||
|
||||
using server_state_callback_t = std::function<void(server_state, json /* payload */)>;
|
||||
|
||||
struct server_context {
|
||||
std::unique_ptr<server_context_impl> impl;
|
||||
|
||||
@@ -80,9 +104,8 @@ struct server_context {
|
||||
// not thread-safe, should only be used from the main thread
|
||||
server_context_meta get_meta() const;
|
||||
|
||||
// register a callback to be called when sleeping state changes
|
||||
// must be set before load_model() is called
|
||||
void on_sleeping_changed(std::function<void(bool)> callback);
|
||||
// note: must be set before load_model() is called
|
||||
void set_state_callback(server_state_callback_t callback);
|
||||
};
|
||||
|
||||
|
||||
|
||||
@@ -7,9 +7,18 @@
|
||||
#include <unordered_set>
|
||||
#include <list>
|
||||
#include <map>
|
||||
#include <algorithm>
|
||||
#include <cctype>
|
||||
|
||||
#include "server-http.h"
|
||||
|
||||
static std::string proxy_header_to_lower(std::string header) {
|
||||
std::transform(header.begin(), header.end(), header.begin(), [](unsigned char c) {
|
||||
return std::tolower(c);
|
||||
});
|
||||
return header;
|
||||
}
|
||||
|
||||
static server_http_res_ptr proxy_request(const server_http_req & req, std::string method) {
|
||||
std::string target_url = req.get_param("url");
|
||||
common_http_url parsed_url = common_http_parse_url(target_url);
|
||||
@@ -33,11 +42,18 @@ static server_http_res_ptr proxy_request(const server_http_req & req, std::strin
|
||||
SRV_INF("proxying %s request to %s://%s:%i%s\n", method.c_str(), parsed_url.scheme.c_str(), parsed_url.host.c_str(), parsed_url.port, parsed_url.path.c_str());
|
||||
|
||||
std::map<std::string, std::string> headers;
|
||||
const std::string proxy_header_prefix = "x-llama-server-proxy-header-";
|
||||
for (auto [key, value] : req.headers) {
|
||||
auto new_key = key;
|
||||
if (string_starts_with(new_key, "x-proxy-header-")) {
|
||||
string_replace_all(new_key, "x-proxy-header-", "");
|
||||
const std::string lowered_key = proxy_header_to_lower(key);
|
||||
if (!string_starts_with(lowered_key, proxy_header_prefix)) {
|
||||
continue;
|
||||
}
|
||||
|
||||
auto new_key = key.substr(proxy_header_prefix.size());
|
||||
if (new_key.empty()) {
|
||||
continue;
|
||||
}
|
||||
|
||||
headers[new_key] = value;
|
||||
}
|
||||
|
||||
|
||||
@@ -492,6 +492,8 @@ using server_http_req_ptr = std::unique_ptr<server_http_req>;
|
||||
static void process_handler_response(server_http_req_ptr && request, server_http_res_ptr & response, httplib::Response & res) {
|
||||
if (response->is_stream()) {
|
||||
res.status = response->status;
|
||||
// Tell Nginx to not buffer any streamed response
|
||||
response->headers["X-Accel-Buffering"] = "no";
|
||||
set_headers(res, response->headers);
|
||||
const std::string content_type = response->content_type;
|
||||
// convert to shared_ptr as both chunked_content_provider() and on_complete() need to use it
|
||||
|
||||
@@ -1,5 +1,6 @@
|
||||
#include "server-common.h"
|
||||
#include "server-models.h"
|
||||
#include "server-context.h"
|
||||
|
||||
#include "build-info.h"
|
||||
#include "preset.h"
|
||||
@@ -44,9 +45,7 @@ extern char **environ;
|
||||
#define DEFAULT_STOP_TIMEOUT 10 // seconds
|
||||
|
||||
#define CMD_ROUTER_TO_CHILD_EXIT "cmd_router_to_child:exit"
|
||||
#define CMD_CHILD_TO_ROUTER_READY "cmd_child_to_router:ready" // also sent when waking up from sleep
|
||||
#define CMD_CHILD_TO_ROUTER_SLEEP "cmd_child_to_router:sleep"
|
||||
#define CMD_CHILD_TO_ROUTER_INFO "cmd_child_to_router:info:" // followed by json string
|
||||
#define CMD_CHILD_TO_ROUTER_STATE "cmd_child_to_router:state:" // followed by json string
|
||||
|
||||
// address for child process, this is needed because router may run on 0.0.0.0
|
||||
// ref: https://github.com/ggml-org/llama.cpp/issues/17862
|
||||
@@ -443,6 +442,7 @@ void server_models::load_models() {
|
||||
/* last_used */ 0,
|
||||
/* args */ std::vector<std::string>(),
|
||||
/* loaded_info */ {},
|
||||
/* progress */ {},
|
||||
/* exit_code */ 0,
|
||||
/* stop_timeout */ DEFAULT_STOP_TIMEOUT,
|
||||
/* multimodal */ mtmd_caps{false, false},
|
||||
@@ -609,6 +609,7 @@ void server_models::load_models() {
|
||||
/* last_used */ 0,
|
||||
/* args */ std::vector<std::string>(),
|
||||
/* loaded_info */ {},
|
||||
/* progress */ {},
|
||||
/* exit_code */ 0,
|
||||
/* stop_timeout */ DEFAULT_STOP_TIMEOUT,
|
||||
/* multimodal */ mtmd_caps{false, false},
|
||||
@@ -904,12 +905,8 @@ void server_models::load(const std::string & name) {
|
||||
while (fgets(buffer, vec_buf.size(), stdout_file) != nullptr) {
|
||||
LOG("[%5d] %s", port, buffer);
|
||||
std::string str(buffer);
|
||||
if (string_starts_with(buffer, CMD_CHILD_TO_ROUTER_READY)) {
|
||||
this->update_status(name, SERVER_MODEL_STATUS_LOADED, 0);
|
||||
} else if (string_starts_with(buffer, CMD_CHILD_TO_ROUTER_INFO)) {
|
||||
this->update_loaded_info(name, str);
|
||||
} else if (string_starts_with(buffer, CMD_CHILD_TO_ROUTER_SLEEP)) {
|
||||
this->update_status(name, SERVER_MODEL_STATUS_SLEEPING, 0);
|
||||
if (string_starts_with(buffer, CMD_CHILD_TO_ROUTER_STATE)) {
|
||||
this->handle_child_state(name, str);
|
||||
}
|
||||
}
|
||||
} else {
|
||||
@@ -976,7 +973,10 @@ void server_models::load(const std::string & name) {
|
||||
subprocess_destroy(&child_proc->get());
|
||||
|
||||
// update status and exit code
|
||||
this->update_status(name, SERVER_MODEL_STATUS_UNLOADED, exit_code);
|
||||
this->update_status(name, {
|
||||
SERVER_MODEL_STATUS_UNLOADED,
|
||||
exit_code
|
||||
});
|
||||
SRV_INF("instance name=%s exited with status %d\n", name.c_str(), exit_code);
|
||||
});
|
||||
|
||||
@@ -1016,7 +1016,8 @@ struct server_models_download_res : public common_download_callback {
|
||||
common_download_model(model, opts);
|
||||
is_ok = true;
|
||||
} catch (const std::exception & e) {
|
||||
SRV_ERR("download failed for model name=%s: %s\n", model.name.c_str(), e.what());
|
||||
auto model_name = model.get_name();
|
||||
SRV_ERR("download failed for model name=%s: %s\n", model_name.c_str(), e.what());
|
||||
is_ok = false;
|
||||
}
|
||||
return is_ok;
|
||||
@@ -1036,7 +1037,7 @@ struct server_models_download_res : public common_download_callback {
|
||||
};
|
||||
|
||||
void server_models::download(common_params_model && model, common_download_opts && opts) {
|
||||
std::string name = model.name;
|
||||
std::string name = model.get_name();
|
||||
GGML_ASSERT(name == model.hf_repo);
|
||||
|
||||
std::unique_lock<std::mutex> lk(mutex);
|
||||
@@ -1064,9 +1065,10 @@ void server_models::download(common_params_model && model, common_download_opts
|
||||
inst.th = std::thread([this, dl = std::move(dl)]() {
|
||||
dl->opts.callback = dl.get();
|
||||
bool ok = dl->run();
|
||||
auto model_name = dl->model.get_name();
|
||||
SRV_INF("download finished for model name=%s with status=%s\n",
|
||||
dl->model.name.c_str(), ok ? "success" : "failure");
|
||||
update_download_progress(dl->model.name, {}, true, ok);
|
||||
model_name.c_str(), ok ? "success" : "failure");
|
||||
update_download_progress(model_name, {}, true, ok);
|
||||
// need_reload is set inside update_download_progress under the mutex;
|
||||
// the next load_models() call will clean up this instance
|
||||
});
|
||||
@@ -1130,21 +1132,33 @@ void server_models::unload_all() {
|
||||
}
|
||||
}
|
||||
|
||||
void server_models::update_status(const std::string & name, server_model_status status, int exit_code) {
|
||||
void server_models::update_status(const std::string & name, const update_status_args & args) {
|
||||
std::unique_lock<std::mutex> lk(mutex);
|
||||
auto it = mapping.find(name);
|
||||
if (it != mapping.end()) {
|
||||
auto & meta = it->second.meta;
|
||||
meta.status = status;
|
||||
meta.exit_code = exit_code;
|
||||
meta.status = args.status;
|
||||
meta.exit_code = args.exit_code;
|
||||
if (!args.loaded_info.is_null()) {
|
||||
meta.loaded_info = args.loaded_info;
|
||||
}
|
||||
if (!args.progress.is_null()) {
|
||||
meta.progress = args.progress;
|
||||
}
|
||||
}
|
||||
// broadcast status change to SSE
|
||||
{
|
||||
json data = {
|
||||
{"status", server_model_status_to_string(status)},
|
||||
{"status", server_model_status_to_string(args.status)},
|
||||
};
|
||||
if (status == SERVER_MODEL_STATUS_UNLOADED) {
|
||||
data["exit_code"] = exit_code;
|
||||
if (args.status == SERVER_MODEL_STATUS_UNLOADED) {
|
||||
data["exit_code"] = args.exit_code;
|
||||
}
|
||||
if (!args.loaded_info.is_null()) {
|
||||
data["info"] = args.loaded_info;
|
||||
}
|
||||
if (!args.progress.is_null()) {
|
||||
data["progress"] = args.progress;
|
||||
}
|
||||
// note: notify_sse doesn't acquire the lock, so no deadlock here
|
||||
notify_sse("status_change", name, data);
|
||||
@@ -1152,29 +1166,6 @@ void server_models::update_status(const std::string & name, server_model_status
|
||||
cv.notify_all();
|
||||
}
|
||||
|
||||
void server_models::update_loaded_info(const std::string & name, std::string & raw_info) {
|
||||
if (!string_starts_with(raw_info, CMD_CHILD_TO_ROUTER_INFO)) {
|
||||
SRV_WRN("invalid loaded info format from child for model name=%s: %s\n", name.c_str(), raw_info.c_str());
|
||||
return;
|
||||
}
|
||||
|
||||
json info;
|
||||
try {
|
||||
info = json::parse(raw_info.substr(strlen(CMD_CHILD_TO_ROUTER_INFO)));
|
||||
} catch (const std::exception & e) {
|
||||
SRV_WRN("failed to parse loaded info from child for model name=%s: %s\n", name.c_str(), e.what());
|
||||
return;
|
||||
}
|
||||
|
||||
std::unique_lock<std::mutex> lk(mutex);
|
||||
auto it = mapping.find(name);
|
||||
if (it != mapping.end()) {
|
||||
auto & meta = it->second.meta;
|
||||
meta.loaded_info = info;
|
||||
}
|
||||
cv.notify_all();
|
||||
}
|
||||
|
||||
void server_models::update_download_progress(const std::string & name, const common_download_progress & progress, bool done, bool ok) {
|
||||
json curr;
|
||||
{
|
||||
@@ -1323,21 +1314,59 @@ server_http_res_ptr server_models::proxy_request(const server_http_req & req, co
|
||||
return proxy;
|
||||
}
|
||||
|
||||
bool server_models::is_child_server() {
|
||||
void server_models::handle_child_state(const std::string & name, const std::string & raw_input) {
|
||||
server_state state;
|
||||
json payload;
|
||||
|
||||
try {
|
||||
json data = json::parse(raw_input.substr(strlen(CMD_CHILD_TO_ROUTER_STATE)));
|
||||
state = server_state_from_str(json_value(data, "state", std::string()));
|
||||
payload = json_value(data, "payload", json{});
|
||||
} catch (const std::exception & e) {
|
||||
SRV_ERR("failed to parse child state update for name=%s: %s\n", name.c_str(), e.what());
|
||||
return;
|
||||
}
|
||||
|
||||
switch (state) {
|
||||
case SERVER_STATE_LOADING:
|
||||
{
|
||||
update_status(name, {
|
||||
SERVER_MODEL_STATUS_LOADING,
|
||||
0,
|
||||
nullptr, // no loaded_info yet
|
||||
payload,
|
||||
});
|
||||
} break;
|
||||
case SERVER_STATE_READY:
|
||||
{
|
||||
update_status(name, {
|
||||
SERVER_MODEL_STATUS_LOADED,
|
||||
0,
|
||||
// note: payload can be empty if this is a wakeup from sleep
|
||||
payload.size() > 0 ? payload : nullptr,
|
||||
{}, // reset progress info
|
||||
});
|
||||
} break;
|
||||
case SERVER_STATE_SLEEPING:
|
||||
{
|
||||
update_status(name, { SERVER_MODEL_STATUS_SLEEPING });
|
||||
} break;
|
||||
default:
|
||||
// should never happen, but just in case
|
||||
GGML_ASSERT(false && "unexpected state from child server");
|
||||
}
|
||||
}
|
||||
|
||||
//
|
||||
// server_child
|
||||
//
|
||||
|
||||
bool server_child::is_child() {
|
||||
const char * router_port = std::getenv("LLAMA_SERVER_ROUTER_PORT");
|
||||
return router_port != nullptr;
|
||||
}
|
||||
|
||||
std::thread server_models::setup_child_server(const std::function<void(int)> & shutdown_handler, const json & model_info) {
|
||||
// send a notification to the router server that a model instance is ready
|
||||
common_log_pause(common_log_main());
|
||||
fflush(stdout);
|
||||
fprintf(stdout, "%s\n", CMD_CHILD_TO_ROUTER_READY);
|
||||
fflush(stdout);
|
||||
fprintf(stdout, "%s%s\n", CMD_CHILD_TO_ROUTER_INFO, safe_json_to_str(model_info).c_str());
|
||||
fflush(stdout);
|
||||
common_log_resume(common_log_main());
|
||||
|
||||
std::thread server_child::setup(const std::function<void(int)> & shutdown_handler) {
|
||||
// setup thread for monitoring stdin
|
||||
return std::thread([shutdown_handler]() {
|
||||
// wait for EOF on stdin
|
||||
@@ -1363,10 +1392,15 @@ std::thread server_models::setup_child_server(const std::function<void(int)> & s
|
||||
});
|
||||
}
|
||||
|
||||
void server_models::notify_router_sleeping_state(bool is_sleeping) {
|
||||
void server_child::notify_to_router(const std::string & state, const json & payload) {
|
||||
json data = {
|
||||
{"state", state},
|
||||
{"payload", payload},
|
||||
};
|
||||
std::lock_guard<std::mutex> lk(mtx_stdout);
|
||||
common_log_pause(common_log_main());
|
||||
fflush(stdout);
|
||||
fprintf(stdout, "%s\n", is_sleeping ? CMD_CHILD_TO_ROUTER_SLEEP : CMD_CHILD_TO_ROUTER_READY);
|
||||
fprintf(stdout, "%s%s\n", CMD_CHILD_TO_ROUTER_STATE, safe_json_to_str(data).c_str());
|
||||
fflush(stdout);
|
||||
common_log_resume(common_log_main());
|
||||
}
|
||||
@@ -1462,9 +1496,9 @@ void server_models_routes::init_routes() {
|
||||
auto res = std::make_unique<server_http_res>();
|
||||
res_ok(res, {
|
||||
// TODO: add support for this on web UI
|
||||
{"role", "router"},
|
||||
{"max_instances", params.models_max},
|
||||
{"models_autoload", params.models_autoload},
|
||||
{"role", "router"},
|
||||
{"max_instances", params.models_max},
|
||||
{"models_autoload", params.models_autoload},
|
||||
// this is a dummy response to make sure the UI doesn't break
|
||||
{"model_alias", "llama-server"},
|
||||
{"model_path", "none"},
|
||||
@@ -1473,11 +1507,9 @@ void server_models_routes::init_routes() {
|
||||
{"n_ctx", 0},
|
||||
}},
|
||||
// New key
|
||||
{"ui_settings", ui_settings},
|
||||
// Deprecated: use ui_settings instead (kept for backward compat)
|
||||
{"webui_settings", webui_settings},
|
||||
{"build_info", std::string(llama_build_info())},
|
||||
{"cors_proxy_enabled", params.ui_mcp_proxy || params.webui_mcp_proxy},
|
||||
{"ui_settings", ui_settings},
|
||||
{"build_info", std::string(llama_build_info())},
|
||||
{"cors_proxy_enabled", params.ui_mcp_proxy},
|
||||
});
|
||||
return res;
|
||||
}
|
||||
@@ -1646,7 +1678,6 @@ void server_models_routes::init_routes() {
|
||||
common_params_model model;
|
||||
common_download_opts opts;
|
||||
|
||||
model.name = name;
|
||||
model.hf_repo = name;
|
||||
opts.bearer_token = params.hf_token;
|
||||
opts.download_mmproj = true;
|
||||
|
||||
@@ -72,6 +72,7 @@ struct server_model_meta {
|
||||
int64_t last_used = 0; // for LRU unloading
|
||||
std::vector<std::string> args; // args passed to the model instance, will be populated by render_args()
|
||||
json loaded_info; // info to be reflected via /v1/models endpoint ; if in DOWNLOADING state, it should contain download progress info
|
||||
json progress; // reflect load or download progress info, if any
|
||||
int exit_code = 0; // exit code of the model instance process (only valid if status == FAILED)
|
||||
int stop_timeout = 0; // seconds to wait before force-killing the model instance during shutdown
|
||||
mtmd_caps multimodal; // multimodal capabilities
|
||||
@@ -170,9 +171,15 @@ public:
|
||||
// to stop the download, call unload()
|
||||
void download(common_params_model && model, common_download_opts && opts);
|
||||
|
||||
struct update_status_args {
|
||||
server_model_status status;
|
||||
int exit_code = 0; // only valid if status == UNLOADED
|
||||
json loaded_info = nullptr;
|
||||
json progress = nullptr;
|
||||
};
|
||||
// update the status of a model instance (thread-safe)
|
||||
void update_status(const std::string & name, server_model_status status, int exit_code);
|
||||
void update_loaded_info(const std::string & name, std::string & raw_info);
|
||||
// also send SSE notification to /models/sse endpoint
|
||||
void update_status(const std::string & name, const update_status_args & args);
|
||||
void update_download_progress(const std::string & name, const common_download_progress & progress, bool done, bool ok = true);
|
||||
|
||||
// remove a cache model from disk and update the list (thread-safe)
|
||||
@@ -193,34 +200,44 @@ public:
|
||||
// proxy an HTTP request to the model instance
|
||||
server_http_res_ptr proxy_request(const server_http_req & req, const std::string & method, const std::string & name, bool update_last_used);
|
||||
|
||||
// handle message sent from server_child::notify_to_router()
|
||||
// raw input must starts with CMD_CHILD_TO_ROUTER_STATE, followed by a JSON string
|
||||
// this function is not thread-safe, must be called from instance's monitoring thread
|
||||
// payload per state:
|
||||
// state = loading -> payload = {} (TODO: add progress info)
|
||||
// state = ready -> payload = model_info (json), or {} if wakeup from sleeping
|
||||
// state = sleeping -> payload = {}
|
||||
void handle_child_state(const std::string & name, const std::string & raw_input);
|
||||
};
|
||||
|
||||
struct server_child {
|
||||
// serializes the notify_to_router writes
|
||||
std::mutex mtx_stdout;
|
||||
|
||||
// return true if the current process is a child server instance
|
||||
static bool is_child_server();
|
||||
bool is_child();
|
||||
|
||||
// notify the router server that a model instance is ready
|
||||
// register the shutdown_handler to be called by the router
|
||||
// return the monitoring thread (to be joined by the caller)
|
||||
static std::thread setup_child_server(const std::function<void(int)> & shutdown_handler, const json & model_info);
|
||||
std::thread setup(const std::function<void(int)> & shutdown_handler);
|
||||
|
||||
// notify the router server that the sleeping state has changed
|
||||
static void notify_router_sleeping_state(bool sleeping);
|
||||
// notify router server for status changes (e.g. loading, downloading, sleeping, etc.)
|
||||
// message will be handled by server_models::handle_child_state() on the router side
|
||||
void notify_to_router(const std::string & state_name, const json & payload);
|
||||
};
|
||||
|
||||
struct server_models_routes {
|
||||
common_params params;
|
||||
json ui_settings = json::object(); // Primary: new name
|
||||
json webui_settings = json::object(); // Deprecated: use ui_settings (kept for compat)
|
||||
std::atomic<bool> stopping = false; // for graceful disconnecting SSE clients during shutdown
|
||||
server_models models;
|
||||
server_models_routes(const common_params & params, int argc, char ** argv)
|
||||
: params(params), models(params, argc, argv) {
|
||||
// Support both new ui_config_json and deprecated webui_config_json
|
||||
const std::string & cfg = !this->params.ui_config_json.empty()
|
||||
? this->params.ui_config_json
|
||||
: this->params.webui_config_json;
|
||||
const std::string & cfg = this->params.ui_config_json;
|
||||
if (!cfg.empty()) {
|
||||
try {
|
||||
json json_settings = json::parse(cfg);
|
||||
ui_settings = json_settings;
|
||||
webui_settings = json_settings; // Deprecated: keep in sync
|
||||
} catch (const std::exception & e) {
|
||||
LOG_ERR("%s: failed to parse UI config: %s\n", __func__, e.what());
|
||||
throw;
|
||||
|
||||
@@ -14,6 +14,9 @@ std::vector<std::unique_ptr<field>> make_llama_cmpl_schema(const common_params &
|
||||
fields.emplace_back(f);
|
||||
};
|
||||
|
||||
add((new field_bool("verbose", params.verbose))
|
||||
->set_desc("Include __verbose field in the response with additional debug information"));
|
||||
|
||||
add((new field_bool("timings_per_token", params.timings_per_token))
|
||||
->set_desc("Include prompt processing and text generation speed information in each response"));
|
||||
|
||||
|
||||
@@ -11,6 +11,7 @@
|
||||
#include <cstring>
|
||||
#include <climits>
|
||||
#include <algorithm>
|
||||
#include <unordered_set>
|
||||
|
||||
namespace fs = std::filesystem;
|
||||
|
||||
|
||||
+18
-14
@@ -90,8 +90,10 @@ int llama_server(int argc, char ** argv) {
|
||||
llama_numa_init(params.numa);
|
||||
|
||||
// router server never loads a model and must not touch the GPU
|
||||
const bool is_router_server = params.model.path.empty()
|
||||
&& params.model.hf_repo.empty();
|
||||
|
||||
// skip device enumeration so the CUDA primary context stays uncreated
|
||||
const bool is_router_server = params.model.path.empty();
|
||||
common_params_print_info(params, !is_router_server);
|
||||
|
||||
if (!is_router_server) {
|
||||
@@ -113,8 +115,9 @@ int llama_server(int argc, char ** argv) {
|
||||
}
|
||||
|
||||
// for consistency between server router mode and single-model mode, we set the same model name as alias
|
||||
if (params.model_alias.empty() && !params.model.name.empty()) {
|
||||
params.model_alias.insert(params.model.name);
|
||||
auto model_name = params.model.get_name();
|
||||
if (params.model_alias.empty() && !model_name.empty()) {
|
||||
params.model_alias.insert(model_name);
|
||||
}
|
||||
|
||||
// struct that contains llama context and inference
|
||||
@@ -227,8 +230,7 @@ int llama_server(int argc, char ** argv) {
|
||||
ctx_http.register_gcp_compat();
|
||||
|
||||
// CORS proxy (EXPERIMENTAL, only used by the Web UI for MCP)
|
||||
// Supports both new ui_mcp_proxy and deprecated webui_mcp_proxy fields
|
||||
if (params.ui_mcp_proxy || params.webui_mcp_proxy) {
|
||||
if (params.ui_mcp_proxy) {
|
||||
SRV_WRN("%s", "-----------------\n");
|
||||
SRV_WRN("%s", "CORS proxy is enabled, do not expose server to untrusted environments\n");
|
||||
SRV_WRN("%s", "This feature is EXPERIMENTAL and may be removed or changed in future versions\n");
|
||||
@@ -256,6 +258,7 @@ int llama_server(int argc, char ** argv) {
|
||||
// Start the server
|
||||
//
|
||||
|
||||
server_child child; // only used in non-router mode
|
||||
std::function<void()> clean_up;
|
||||
|
||||
if (is_router_server) {
|
||||
@@ -301,15 +304,16 @@ int llama_server(int argc, char ** argv) {
|
||||
return 1;
|
||||
}
|
||||
|
||||
// load the model
|
||||
SRV_INF("%s", "loading model\n");
|
||||
|
||||
if (server_models::is_child_server()) {
|
||||
ctx_server.on_sleeping_changed([&](bool sleeping) {
|
||||
server_models::notify_router_sleeping_state(sleeping);
|
||||
// setup communication child --> router if necessary
|
||||
if (child.is_child()) {
|
||||
ctx_server.set_state_callback([&](server_state state, json payload) {
|
||||
child.notify_to_router(server_state_to_str(state), payload);
|
||||
});
|
||||
}
|
||||
|
||||
// load the model
|
||||
SRV_INF("%s", "loading model\n");
|
||||
|
||||
if (!ctx_server.load_model(params)) {
|
||||
clean_up();
|
||||
if (ctx_http.thread.joinable()) {
|
||||
@@ -366,9 +370,9 @@ int llama_server(int argc, char ** argv) {
|
||||
|
||||
// optionally, notify router server that this instance is ready
|
||||
std::thread monitor_thread;
|
||||
if (server_models::is_child_server()) {
|
||||
json model_info = routes.get_model_info();
|
||||
monitor_thread = server_models::setup_child_server(shutdown_handler, model_info);
|
||||
if (child.is_child()) {
|
||||
monitor_thread = child.setup(shutdown_handler);
|
||||
child.notify_to_router(server_state_to_str(SERVER_STATE_READY), routes.get_model_info());
|
||||
}
|
||||
|
||||
// this call blocks the main thread until queue_tasks.terminate() is called
|
||||
|
||||
@@ -79,9 +79,9 @@ def test_load_split_model():
|
||||
assert match_regex("(little|girl)+", res.body["content"])
|
||||
|
||||
|
||||
def test_no_webui():
|
||||
def test_no_ui():
|
||||
global server
|
||||
# default: webui enabled
|
||||
# default: UI enabled
|
||||
server.start()
|
||||
url = f"http://{server.server_host}:{server.server_port}"
|
||||
res = requests.get(url)
|
||||
@@ -89,8 +89,8 @@ def test_no_webui():
|
||||
assert "<!doctype html>" in res.text
|
||||
server.stop()
|
||||
|
||||
# with --no-webui
|
||||
server.no_webui = True
|
||||
# with --no-ui, the UI should be disabled
|
||||
server.no_ui = True
|
||||
server.start()
|
||||
res = requests.get(url)
|
||||
assert res.status_code == 404
|
||||
|
||||
@@ -603,3 +603,23 @@ def test_chat_completions_token_count():
|
||||
})
|
||||
assert res.status_code == 200
|
||||
assert res.body["input_tokens"] > 5
|
||||
|
||||
|
||||
def test_verbose_debug():
|
||||
global server
|
||||
server.start()
|
||||
for verbose in [True, False]:
|
||||
res = server.make_request("POST", "/chat/completions", data={
|
||||
"max_tokens": 2,
|
||||
"messages": [
|
||||
{"role": "system", "content": "Book"},
|
||||
{"role": "user", "content": "What is the best book"},
|
||||
],
|
||||
"verbose": verbose,
|
||||
})
|
||||
assert res.status_code == 200
|
||||
if verbose:
|
||||
assert "__verbose" in res.body
|
||||
assert "Book" in res.body["__verbose"]["prompt"]
|
||||
else:
|
||||
assert "__verbose" not in res.body
|
||||
|
||||
@@ -12,7 +12,7 @@ def create_server():
|
||||
|
||||
def test_mcp_no_proxy():
|
||||
global server
|
||||
server.webui_mcp_proxy = False
|
||||
server.ui_mcp_proxy = False
|
||||
server.start()
|
||||
|
||||
res = server.make_request("GET", "/cors-proxy")
|
||||
@@ -21,7 +21,7 @@ def test_mcp_no_proxy():
|
||||
|
||||
def test_mcp_proxy():
|
||||
global server
|
||||
server.webui_mcp_proxy = True
|
||||
server.ui_mcp_proxy = True
|
||||
server.start()
|
||||
|
||||
url = f"http://{server.server_host}:{server.server_port}/cors-proxy?url=http://example.com"
|
||||
@@ -32,7 +32,7 @@ def test_mcp_proxy():
|
||||
|
||||
def test_mcp_proxy_custom_port():
|
||||
global server
|
||||
server.webui_mcp_proxy = True
|
||||
server.ui_mcp_proxy = True
|
||||
server.start()
|
||||
|
||||
# try getting the server's models API via the proxy
|
||||
|
||||
@@ -1,6 +1,8 @@
|
||||
import pytest
|
||||
from openai import OpenAI
|
||||
from utils import *
|
||||
import threading
|
||||
from http.server import BaseHTTPRequestHandler, ThreadingHTTPServer
|
||||
|
||||
server = ServerPreset.tinyllama2()
|
||||
|
||||
@@ -105,6 +107,49 @@ def test_cors_options(origin: str, cors_header: str, cors_header_value: str):
|
||||
assert res.headers[cors_header] == cors_header_value
|
||||
|
||||
|
||||
def test_cors_proxy_only_forwards_explicit_proxy_headers():
|
||||
class CaptureHeadersHandler(BaseHTTPRequestHandler):
|
||||
def do_GET(self):
|
||||
self.server.captured_headers = dict(self.headers)
|
||||
self.send_response(200)
|
||||
self.end_headers()
|
||||
self.wfile.write(b"ok")
|
||||
|
||||
def log_message(self, format, *args):
|
||||
pass
|
||||
|
||||
target = ThreadingHTTPServer(("127.0.0.1", 0), CaptureHeadersHandler)
|
||||
target.captured_headers = {}
|
||||
target_thread = threading.Thread(target=target.serve_forever, daemon=True)
|
||||
target_thread.start()
|
||||
|
||||
try:
|
||||
server = ServerPreset.tinyllama2()
|
||||
server.api_key = TEST_API_KEY
|
||||
server.ui_mcp_proxy = True
|
||||
server.start()
|
||||
|
||||
res = server.make_request("GET", f"/cors-proxy?url=http://127.0.0.1:{target.server_port}/capture", headers={
|
||||
"Authorization": f"Bearer {TEST_API_KEY}",
|
||||
"Proxy-Authorization": "Basic secret",
|
||||
"X-Api-Key": TEST_API_KEY,
|
||||
"Cookie": "session=secret",
|
||||
"x-llama-server-proxy-header-accept": "application/json",
|
||||
"x-llama-server-proxy-header-authorization": "Bearer explicit",
|
||||
})
|
||||
|
||||
assert res.status_code == 200
|
||||
captured = {key.lower(): value for key, value in target.captured_headers.items()}
|
||||
assert captured["accept"] == "application/json"
|
||||
assert captured["authorization"] == "Bearer explicit"
|
||||
assert "proxy-authorization" not in captured
|
||||
assert "x-api-key" not in captured
|
||||
assert "cookie" not in captured
|
||||
finally:
|
||||
target.shutdown()
|
||||
target.server_close()
|
||||
|
||||
|
||||
@pytest.mark.parametrize(
|
||||
"media_path, image_url, success",
|
||||
[
|
||||
|
||||
@@ -94,7 +94,7 @@ class ServerProcess:
|
||||
enable_ctx_shift: int | None = False
|
||||
spec_draft_n_min: int | None = None
|
||||
spec_draft_n_max: int | None = None
|
||||
no_webui: bool | None = None
|
||||
no_ui: bool | None = None
|
||||
jinja: bool | None = None
|
||||
reasoning_format: Literal['deepseek', 'none', 'nothink'] | None = None
|
||||
reasoning: Literal['on', 'off', 'auto'] | None = None
|
||||
@@ -107,7 +107,7 @@ class ServerProcess:
|
||||
cache_ram: int | None = None
|
||||
no_cache_idle_slots: bool = False
|
||||
log_path: str | None = None
|
||||
webui_mcp_proxy: bool = False
|
||||
ui_mcp_proxy: bool = False
|
||||
backend_sampling: bool = False
|
||||
gcp_compat: bool = False
|
||||
|
||||
@@ -225,8 +225,8 @@ class ServerProcess:
|
||||
server_args.extend(["--spec-draft-n-max", self.spec_draft_n_max])
|
||||
if self.spec_draft_n_min:
|
||||
server_args.extend(["--spec-draft-n-min", self.spec_draft_n_min])
|
||||
if self.no_webui:
|
||||
server_args.append("--no-webui")
|
||||
if self.no_ui:
|
||||
server_args.append("--no-ui")
|
||||
if self.no_models_autoload:
|
||||
server_args.append("--no-models-autoload")
|
||||
if self.jinja:
|
||||
@@ -251,8 +251,8 @@ class ServerProcess:
|
||||
server_args.extend(["--cache-ram", self.cache_ram])
|
||||
if self.no_cache_idle_slots:
|
||||
server_args.append("--no-cache-idle-slots")
|
||||
if self.webui_mcp_proxy:
|
||||
server_args.append("--webui-mcp-proxy")
|
||||
if self.ui_mcp_proxy:
|
||||
server_args.append("--ui-mcp-proxy")
|
||||
if self.backend_sampling:
|
||||
server_args.append("--backend_sampling")
|
||||
if self.gcp_compat:
|
||||
|
||||
@@ -51,6 +51,9 @@ export const EXPECTED_THEMED_ICON_PAIR_COUNT = 2;
|
||||
/** CORS proxy URL query parameter name */
|
||||
export const CORS_PROXY_URL_PARAM = 'url';
|
||||
|
||||
/** Header prefix for headers that should be forwarded by the CORS proxy */
|
||||
export const CORS_PROXY_HEADER_PREFIX = 'x-llama-server-proxy-header-';
|
||||
|
||||
/** Number of trailing characters to keep visible when partially redacting mcp-session-id */
|
||||
export const MCP_SESSION_ID_VISIBLE_CHARS = 5;
|
||||
|
||||
|
||||
@@ -16,6 +16,7 @@ import {
|
||||
DEFAULT_MCP_CONFIG,
|
||||
DEFAULT_CLIENT_VERSION,
|
||||
DEFAULT_IMAGE_MIME_TYPE,
|
||||
CORS_PROXY_HEADER_PREFIX,
|
||||
MCP_PARTIAL_REDACT_HEADERS,
|
||||
CORS_PROXY_ENDPOINT
|
||||
} from '$lib/constants';
|
||||
@@ -133,6 +134,20 @@ export class MCPService {
|
||||
return details;
|
||||
}
|
||||
|
||||
private static addRequestHeaders(
|
||||
requestHeaders: Headers,
|
||||
headers: HeadersInit,
|
||||
useProxy: boolean
|
||||
) {
|
||||
for (const [key, value] of new Headers(headers).entries()) {
|
||||
const proxiedKey =
|
||||
useProxy && !key.toLowerCase().startsWith(CORS_PROXY_HEADER_PREFIX)
|
||||
? `${CORS_PROXY_HEADER_PREFIX}${key}`
|
||||
: key;
|
||||
requestHeaders.set(proxiedKey, value);
|
||||
}
|
||||
}
|
||||
|
||||
private static summarizeError(error: unknown): Record<string, unknown> {
|
||||
if (error instanceof Error) {
|
||||
return {
|
||||
@@ -271,15 +286,11 @@ export class MCPService {
|
||||
const requestHeaders = new Headers(baseInit.headers);
|
||||
|
||||
if (typeof Request !== 'undefined' && input instanceof Request) {
|
||||
for (const [key, value] of input.headers.entries()) {
|
||||
requestHeaders.set(key, value);
|
||||
}
|
||||
this.addRequestHeaders(requestHeaders, input.headers, useProxy);
|
||||
}
|
||||
|
||||
if (init?.headers) {
|
||||
for (const [key, value] of new Headers(init.headers).entries()) {
|
||||
requestHeaders.set(key, value);
|
||||
}
|
||||
this.addRequestHeaders(requestHeaders, init.headers, useProxy);
|
||||
}
|
||||
|
||||
const request = this.createDiagnosticRequestDetails(
|
||||
|
||||
Some files were not shown because too many files have changed in this diff Show More
Reference in New Issue
Block a user