* server : Smart selection of available slot using Longest Common Substring
* add usage
* remove trailing whitespaces
* Use Longest Common Prefix (LCP) instead of LCS
* Rename argument
* vulkan : reuse parent extra for views
* Fix validation error when multiple compute contexts are used in a graph
---------
Co-authored-by: 0cc4m <picard12@live.de>
* avoid to get prompt in infill mode and embedding mode
* remove embedding mode
* refactor format
---------
Co-authored-by: wudexiang <wudexiang@bytedance.com>
* feat: add changes to handle jina v2 base code
* fix: do not complicate things
* fix: fix the usage of the code model
* fix: fix comments
* fix: fix linting issues
* fix: remove ollama patches
* style : minor
---------
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
Previously the code would have failed to cope in the case that the
number of nodes changes in an existing CUDA graph. This fixes the
issue by removing an unnecessary conditional.
* common : gpt_params_parse do not print usage
* common : rework usage print (wip)
* common : valign
* common : rework print_usage
* infill : remove cfg support
* common : reorder args
* server : deduplicate parameters
ggml-ci
* common : add missing header
ggml-ci
* common : remote --random-prompt usages
ggml-ci
* examples : migrate to gpt_params
ggml-ci
* batched-bench : migrate to gpt_params
* retrieval : migrate to gpt_params
* common : change defaults for escape and n_ctx
* common : remove chatml and instruct params
ggml-ci
* common : passkey use gpt_params
* Improve hipBLAS support in CMake
This improves the detection of the correct CMAKE_PREFIX_PATH when using different distributions or a self-built ROCm SDK.
* Set ROCM_PATH correctly
* Add per token attributes enum
* Using phi-3 for testing 'rstrip'
* Using jina-v2 for testing 'lstrip'
* Brute force test for 'lstrip' and 'rstrip'
* Implement 'rstrip' and 'lstrip'
* Update phi-3 GGUF file (obsolete since 917dc8c)
* Replace llama_token_type with llama_token_attribs
This enforces a check that -fno-finite-math-only was set and that the operating
compiling mode is not in finite maths mode. This is because during rewriting of
silu and softmax for cpu #7154 there emerged an issue where the result that was
observed when >1 slot was nondeterministic as found by @JohannesGaessler.
@LostRuins narrowed the problem down to -ffinite-math-only which was theorised
to be due to SiLU, instead of flushing small values to 0, returns NaN or some
other garbage. @jart proposed a fix that @ggerganov then implemented in this fix
ref https://github.com/ggerganov/llama.cpp/pull/7154#issuecomment-2145661825
* ggml : allow GGML_OP_CONCAT to work on non-contiguous tensors
The implementation already supported it,
and this makes Mamba's conv step slightly faster.
* llama : offload to RPC in addition to other backends
* - fix copy_tensor being called on the src buffer instead of the dst buffer
- always initialize views in the view_src buffer
- add RPC backend to Makefile build
- add endpoint to all RPC object names
* add rpc-server to Makefile
* Update llama.cpp
Co-authored-by: slaren <slarengh@gmail.com>
---------
Co-authored-by: slaren <slarengh@gmail.com>
* ggml: Added OpenMP for multi-threads processing
* ggml : Limit the number of threads used to avoid deadlock
* update shared state n_threads in parallel region
* clear numa affinity for main thread even with openmp
* enable openmp by default
* fix msvc build
* disable openmp on macos
* ci : disable openmp with thread sanitizer
* Update ggml.c
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
---------
Co-authored-by: slaren <slarengh@gmail.com>
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
op_getrows_f32 is required since https://github.com/ggerganov/llama.cpp/pull/6122
for the Vulkan w/ Kompute backend to be functional.
As such, implement this op to make this backend functional again.
This removes the need for ggml_ssm_conv!!!
But performance seems slighly worse on my system,
especially for prompt processing.
Maybe ggml_mul_mat isn't optimized for small row sizes?
More performance testing is necessary until GGML_OP_SSM_CONV is removed.
* ggml : make ggml_ssm_scan not modify its source tensors
* llama : fix shared recurrent tail cell count for small ubatch sizes
Otherwise it was impossible to run the 'parallel' example with '-ub 1'
with a Mamba or Jamba model.
