* Add llama_model_quantize_params parameters
* Add new quantize parameters parsing and validation
* Update usage
* Add new parameters defaults
* Add new quantization parameters logic
* Add llama_model_quantize_params parameters
* Add new quantize parameters parsing and validation
* Update usage
* Add new parameters defaults
* Add new quantization parameters logic
* Minor refactoring as per the contributors' coding guidelines
* Update descriptions to match existing style
* Add llama_model_quantize_params parameters
* Add new quantize parameters parsing and validation
* Update usage
* Add new parameters defaults
* Add new quantization parameters logic
* Minor refactoring as per the contributors' guidelines
* Implement general --tensor-type instead of tensor-specific command option
* Fix implied type bug
* Restore missing #includes
* Add regex capability for tensor selection
* Refactor function name and update ALLOWED_TENSOR_TYPE
* Add missing #include
* Handle edge case when tensor name is cls.output
* Minor logging improvement
The current usage of the SYCL-Graph extension checks for
the `sycl_ext_oneapi_graph` device aspect. However, it is also
possible to support `sycl_ext_oneapi_limied_graph` devices that
don't support update
* SYCL: Add fp16 support to some elementwise OP kernels
* remove comment
ggml-ci
* Use static_cast directly
* remove not needed cast from tanh
* Use static cast and remove unneeded castings
* Adjust device_support_op for unary OPs
* Use cast_data and typed_data struct to deduplicate casting code
This commit adds a check for the visionos build version used with vtool
in build-xcframework.sh. The script now checks the Xcode version and
determines whether to use "xros" or "visionos" for the build version.
This commit also uses xcrun for the vtool so that the version of vtool
in xcode command line tools is used instead of the one in the system
path.
Refs: https://github.com/ggml-org/whisper.cpp/pull/2994#issuecomment-2773292223
* [CANN] Support ELU and CONV_TRANSPOSE_1D
* [CANN]Modification review comments
* [CANN]Modification review comments
* [CANN]name adjustment
* [CANN]remove lambda used in template
* [CANN]Use std::func instead of template
* [CANN]Modify the code according to the review comments
---------
Signed-off-by: noemotiovon <noemotiovon@gmail.com>
q4_k and q5_k had a lot of redundant global loads where the same 16B of
scale information is repeatedly loaded and decoded during each loop iteration.
This change restructures the loops to more explicitly iterate over whole
blocks in the outer loop (with unrolled inner loop) and to copy/decode the
scale data into shared memory once at the start of each outer loop. The copy
is pipelined so the scale load from global memory is relatively cheap.
This improves q4_k/q5_k model prompt processing performance by around 5-7%.
I briefly tried applying this to q6_k and q4_0, and it didn't help for q6_k
and hurt for q4_0.
The big "else" path in mul_mm_cm2.comp that had all the clamped/unclamped
variants isn't used as often as it originally was (e.g. due to the padded_N
change), so I trimmed it down to offset some of the new complexity of the
semi-manual loop unrolling.
* ggml : FA supports F32 V
* graph : cast KV to F16 when the KV cache is not used
ggml-ci
* server : add test that exercises embeddings with FA enabled
ggml-ci
