Track a list of nodes that need synchronization, and only sync if the new node
depends on them (or overwrites them). This allows some overlap which can
improve performance, and centralizes a big chunk of the synchronization logic.
The remaining synchronization logic involves writes to memory other than the
nodes, e.g. for dequantization or split_k. Each of these allocations has a bool
indicating whether they were in use and need to be synced. This should be
checked before they are written to, and set to true after they are done being
consumed.
* vulkan : support ggml_mean
* vulkan : support sum, sum_rows and mean with non-contiguous tensors
* vulkan : fix subbuffer size not accounting for misalign offset
* tests : add backend-op tests for non-contiguous sum_rows
* cuda : require contiguous src for SUM_ROWS, MEAN support
* sycl : require contiguous src for SUM, SUM_ROWS, ARGSORT support
* require ggml_contiguous_rows in supports_op and expect nb00=1 in the shader
- Spread the work across the whole workgroup. Using more threads seems to
far outweigh the synchronization overhead.
- Specialize the code for when the division is by a power of two.
* Begin work on set_rows
* Work on set rows
* Add error buffers for reporting unsupported SET_ROWS indices
* Remove extra comments
* Work on templating for different types in shaders
* Work on shader type generation
* Working q4_0 mul_mat and some templating for different types
* Add q4_0_f16 matmul and fix device init
* Add matmul support for basic quantization types
* Add q2_k and q3_k quantization
* Add rest of k-quants
* Get firt i-quant working
* Closer to supporting all i-quants
* Support rest of i-quants
* Cleanup code
* Fix python formatting
* debug
* Bugfix for memset
* Add padding to end of buffers on creation
* Simplify bit-shifting
* Update usage of StringView
* Support q8_0 quantization for image model loading
q4_0 may degrade quality significantly, especially for smaller
models like SD 1.5 and SDXL. q8_0 provides a middle-ground,
giving half the memory savings of q4_0 but loading faster and
with less quality loss.
* Accept --sdquant with no parameters
* Use numerical values for the sdquant option
* Add Pad Reflect 1D CUDA support
* Update ggml/src/ggml-cuda/pad_reflect_1d.cu
Co-authored-by: Johannes Gäßler <johannesg@5d6.de>
---------
Co-authored-by: Johannes Gäßler <johannesg@5d6.de>
- Use server_tokens in more places in server and util.cpp
- Convert most functions that used llama_tokens to server_tokens
- Modify input tokenizer to handle JSON objects as subprompts
- Break out MTMD prompt parsing into utility function
- Support JSON objects with multimodal_data arrays for MTMD prompts along with other existing types
- Add capability to model endpoint to indicate if client can send multimodal data
- Add tests.
* vulkan: Reuse conversion results in prealloc_y
Cache the pipeline and tensor that were most recently used to fill prealloc_y,
and skip the conversion if the current pipeline/tensor match.
* don't use shared pointer for prealloc_y_last_pipeline_used
* Changed the CI file to hw
* Changed the CI file to hw
* Added to sudoers for apt
* Removed the clone command and used checkout
* Added libcurl
* Added gcc-14
* Checking gcc --version
* added gcc-14 symlink
* added CC and C++ variables
* Added the gguf weight
* Changed the weights path
* Added system specification
* Removed white spaces
* ci: Replace Jenkins riscv native build Cloud-V pipeline with GitHub Actions workflow
Removed the legacy .devops/cloud-v-pipeline Jenkins CI configuration and introduced .github/workflows/build-riscv-native.yml for native RISC-V builds using GitHub Actions.
* removed trailing whitespaces
* Added the trigger at PR creation
* Corrected OS name
* Added ccache as setup package
* Added ccache for self-hosted runner
* Added directory for ccache size storage
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* Changed the build command and added ccache debug log
* Added the base dir for the ccache
* Re-trigger CI
* Cleanup and refactored ccache steps
* Cleanup and refactored ccache steps
---------
Co-authored-by: Akif Ejaz <akifejaz40@gmail.com>
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* examples : add model conversion tool/example
This commit adds an "example/tool" that is intended to help in the
process of converting models to GGUF. Currently it supports normal
causal models and embedding models. The readme contains instructions and
command to guide through the process.
The motivation for this to have a structured and repeatable process for
model conversions and hopefully with time improve upon it to make the
process easier and more reliable. We have started to use this for new
model conversions internally and will continue doing so and improve it
as we go along. Perhaps with time this should be placed in a different
directory than the examples directory, but for now it seems like a good
place to keep it while we are still developing it.
* squash! examples : add model conversion tool/example
Remove dependency on scikit-learn in model conversion example.
* squash! examples : add model conversion tool/example
Update transformer dep to use non-dev version. And also import
`AutoModelForCausalLM` instead of `AutoModel` to ensure compatibility
with the latest version.
* squash! examples : add model conversion tool/example
Remove the logits requirements file from the all requirements file.
* Fix -Werror=return-type so ci/run.sh can run
* Update tools/mtmd/clip.cpp
Co-authored-by: Diego Devesa <slarengh@gmail.com>
* Remove false now that we have abort
---------
Co-authored-by: Diego Devesa <slarengh@gmail.com>
* Initial plan
* Initialize copilot instructions exploration
* Add comprehensive .github/copilot-instructions.md file
* Update Python environment and tools directory documentation
- Add instructions for using .venv Python environment
- Include flake8 and pyright linting tools from virtual environment
- Add tools/ as core directory in project layout
- Reference existing configuration files (.flake8, pyrightconfig.json)
* add more python dependencies to .venv
* Update copilot instructions: add backend hardware note and server testing
* Apply suggestions from code review
* Apply suggestions from code review
* Replace clang-format with git clang-format to format only changed code
* Minor formatting improvements: remove extra blank line and add trailing newline
* try installing git-clang-format
* try just clang-format
* Remove --binary flag from git clang-format and add git-clang-format installation to CI
* download 18.x release
* typo--
* remove --binary flag
---------
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* Make Mistral community chat templates optional
* Change the flag arg to disable instead of enable community chat templates
* Improve error message
* Improve help message
* Tone down the logger messages
