Commit b0a4699 changed the name of this script from convert-hf-to-gguf.py to
convert_hf_to_gguf.py breaking how convert is called from within a Docker
container.
* py : type-check all Python scripts with Pyright
* server-tests : use trailing slash in openai base_url
* server-tests : add more type annotations
* server-tests : strip "chat" from base_url in oai_chat_completions
* server-tests : model metadata is a dict
* ci : disable pip cache in type-check workflow
The cache is not shared between branches, and it's 250MB in size,
so it would become quite a big part of the 10GB cache limit of the repo.
* py : fix new type errors from master branch
* tests : fix test-tokenizer-random.py
Apparently, gcc applies optimisations even when pre-processing,
which confuses pycparser.
* ci : only show warnings and errors in python type-check
The "information" level otherwise has entries
from 'examples/pydantic_models_to_grammar.py',
which could be confusing for someone trying to figure out what failed,
considering that these messages can safely be ignored
even though they look like errors.
Supercedes #4024 and #4813.
CMake's native HIP support has become the
recommended way to add HIP code into a project (see
[here](https://rocm.docs.amd.com/en/docs-6.0.0/conceptual/cmake-packages.html#using-hip-in-cmake)).
This PR makes the following changes:
1. The environment variable `HIPCXX` or CMake option
`CMAKE_HIP_COMPILER` should be used to specify the HIP
compiler. Notably this shouldn't be `hipcc`, but ROCm's clang,
which usually resides in `$ROCM_PATH/llvm/bin/clang`. Previously
this was control by `CMAKE_C_COMPILER` and `CMAKE_CXX_COMPILER`.
Note that since native CMake HIP support is not yet available on
Windows, on Windows we fall back to the old behavior.
2. CMake option `CMAKE_HIP_ARCHITECTURES` is used to control the
GPU architectures to build for. Previously this was controled by
`GPU_TARGETS`.
3. Updated the Nix recipe to account for these new changes.
4. The GPU targets to build against in the Nix recipe is now
consistent with the supported GPU targets in nixpkgs.
5. Added CI checks for HIP on both Linux and Windows. On Linux, we test
both the new and old behavior.
The most important part about this PR is the separation of the
HIP compiler and the C/C++ compiler. This allows users to choose
a different C/C++ compiler if desired, compared to the current
situation where when building for ROCm support, everything must be
compiled with ROCm's clang.
~~Makefile is unchanged. Please let me know if we want to be
consistent on variables' naming because Makefile still uses
`GPU_TARGETS` to control architectures to build for, but I feel
like setting `CMAKE_HIP_ARCHITECTURES` is a bit awkward when you're
calling `make`.~~ Makefile used `GPU_TARGETS` but the README says
to use `AMDGPU_TARGETS`. For consistency with CMake, all usage of
`GPU_TARGETS` in Makefile has been updated to `AMDGPU_TARGETS`.
Thanks to the suggestion of @jin-eld, to maintain backwards
compatibility (and not break too many downstream users' builds), if
`CMAKE_CXX_COMPILER` ends with `hipcc`, then we still compile using
the original behavior and emit a warning that recommends switching
to the new HIP support. Similarly, if `AMDGPU_TARGETS` is set but
`CMAKE_HIP_ARCHITECTURES` is not, then we forward `AMDGPU_TARGETS`
to `CMAKE_HIP_ARCHITECTURES` to ease the transition to the new
HIP support.
Signed-off-by: Gavin Zhao <git@gzgz.dev>
* server: add cURL support to `full.Dockerfile`
* server: add cURL support to `full-cuda.Dockerfile` and `server-cuda.Dockerfile`
* server: add cURL support to `full-rocm.Dockerfile` and `server-rocm.Dockerfile`
* server: add cURL support to `server-intel.Dockerfile`
* server: add cURL support to `server-vulkan.Dockerfile`
* fix typo in `server-vulkan.Dockerfile`
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
---------
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
- The generic /usr/bin/env shebangs are good enough
- Python deps are provisioned in the devShells
- We need to be able to leave python out at least on windows (currently breaks eval)
initial nix build for windows using zig
mingwW64 build
removes nix zig windows build
removes nix zig windows build
removed unnessesary glibc.static
removed unnessesary import of pkgs in nix
fixed missing trailing newline on non-windows nix builds
overriding stdenv when building for crosscompiling to windows in nix
better variables when crosscompiling windows in nix
cross compile windows on macos
removed trailing whitespace
remove unnessesary overwrite of "CMAKE_SYSTEM_NAME" in nix windows build
nix: keep file extension when copying result files during cross compile for windows
nix: better checking for file extensions when using MinGW
nix: using hostPlatform instead of targetPlatform when cross compiling for Windows
using hostPlatform.extensions.executable to extract executable format
* Symlink to /usr/bin/xcrun so that `xcrun` binary
is usable during build (used for compiling Metal shaders)
Fixes https://github.com/ggerganov/llama.cpp/issues/6117
* cmake - copy default.metallib to install directory
When metal files are compiled to default.metallib, Cmake needs to add this to the install directory so that it's visible to llama-cpp
Also, update package.nix to use absolute path for default.metallib (it's not finding the bundle)
* add `precompileMetalShaders` flag (defaults to false) to disable precompilation of metal shader
Precompilation requires Xcode to be installed and requires disable sandbox on nix-darwin
Exposes a few attributes demonstrating how to build [singularity](https://docs.sylabs.io/guides/latest/user-guide/)/[apptainer](https://apptainer.org/) and Docker images re-using llama.cpp's Nix expression.
Built locally on `x86_64-linux` with `nix build github:someoneserge/llama.cpp/feat/nix/images#llamaPackages.{docker,docker-min,sif,llama-cpp}` and it's fast and effective.
* feat: add Dockerfiles for each platform that user ./server instead of ./main
* feat: update .github/workflows/docker.yml to build server-first docker containers
* doc: add information about running the server with Docker to README.md
* doc: add information about running with docker to the server README
* doc: update n-gpu-layers to show correct GPU usage
* fix(doc): update container tag from `server` to `server-cuda` for README example on running server container with CUDA
this fixes the error I encountered when trying to run the convert.py
script in a venv:
```
$ nix develop
[...]$ source .venv/bin/activate
(.venv)
[...]$ pip3 install -r requirements.txt
<... clipped ...>
[...]$ python3 ./convert.py
Traceback (most recent call last):
File "/home/mhueschen/projects-reference/llama.cpp/./convert.py", line 40, in <module>
from sentencepiece import SentencePieceProcessor
File "/home/mhueschen/projects-reference/llama.cpp/.venv/lib/python3.11/site-packages/sentencepiece/__init__.py", line 13, in <module>
from . import _sentencepiece
ImportError: libstdc++.so.6: cannot open shared object file: No such file or directory
```
however, I am not sure this is the cleanest way to address this linker
issue...
* llama : support StableLM 2 1.6B
* convert : fix Qwen's set_vocab wrongly naming all special tokens [PAD{id}]
* convert : refactor Qwen's set_vocab to use it for StableLM 2 too
* nix : add tiktoken to llama-python-extra
* convert : use presence of tokenizer.json to determine StableLM tokenizer loader
It's a less arbitrary heuristic than the vocab size.
* python: add check-requirements.sh and GitHub workflow
This script and workflow forces package versions to remain compatible
across all convert*.py scripts, while allowing secondary convert scripts
to import dependencies not wanted in convert.py.
* Move requirements into ./requirements
* Fail on "==" being used for package requirements (but can be suppressed)
* Enforce "compatible release" syntax instead of ==
* Update workflow
* Add upper version bound for transformers and protobuf
* improve check-requirements.sh
* small syntax change
* don't remove venvs if nocleanup is passed
* See if this fixes docker workflow
* Move check-requirements.sh into ./scripts/
---------
Co-authored-by: Jared Van Bortel <jared@nomic.ai>
