* common: fix coding mistakes (typos in identifiers, flags and log strings)
Fix misspelled identifiers and user-facing strings across common, server
and model loading:
- allow_ruless -> allow_rules (misspelled identifier used in the allowlist
CLI parsing and the server slot/context code)
- get_formated_timings/get_formated_generation -> get_formatted_*
- 'termionated' -> 'terminated' in the fit-margin assert message
- 'defaulr' -> 'default' in the YAML dump
- 'overriden' -> 'overridden' in tensor buffer type override logs
- 'becausee' -> 'because' in the output-tensor split log
- 'etected NaNs' -> 'detected NaNs' in the imatrix error message
* common: fix comment typos across src, common, include and examples
Fix misspelled words in code comments:
- llama.h: 'typy' -> 'type', 'transfrom' -> 'transform', 'ecoder' ->
'encoder', 'indicies' -> 'indices', 'Intializes' -> 'Initializes'
- common.h: 'embendings' -> 'embeddings', 'pr' -> 'or' in the
fused-indexer-topk comment
- chat.cpp: 'overridde' -> 'override'
- ngram-map: 'occurences' -> 'occurrences', 'stastistics' -> 'statistics'
- speculative.cpp: 'dont'/'inehit' -> 'don't'/'inherit'
- llama-mmap.cpp: 'dont't' -> 'don't'
- llama-model.h: 'hcurrently andle' -> 'currently handle'
- build_gemma3/4.cpp: 'emdeddings' -> 'embeddings'
- examples: 'quantizuation', 'logprobe', 'throught', 'retrun', 'swich',
'convinient', 'temporally' (-> 'temporary'), 'temproal', 'preceed'
* common: remove duplicate definitions and duplicate help entries
- clip-impl.h: drop the second, identical #define TN_FFN_GATE
- common.cpp: remove the duplicate '-t, --threads N' help entry that was
misplaced in the export-lora section (already listed in the general
section)
- common.cpp: merge the two 'embedding' help groups into a single group
so the embedding options are listed together
- llama.cpp: remove the redundant LLAMA_MAX_LAYERS define (llama-hparams.h
already defines the same value and is included by llama.cpp)
* common: fix remaining typos (accomodate, recommanded, occurences, occassionally)
- accomodate -> accommodate in src/llama.cpp comment
- recommanded -> recommended in quantize.cpp user-facing output
- occurences -> occurrences in test-chat.cpp JSON string
- occassionally -> occasionally in vendor/stb/stb_image_resize2.h comment
Note: tokenizer.ggml.seperator_token_id kept as-is to match GGUF spec
* common: remove duplicate help entries
- remove the duplicate '--reasoning-budget N' help entry that was repeated
in the main section (introduced in e0596bf614 'Autoparser - complete
refactoring of parser architecture (PR 1376)')
- remove the second '--parallel-tool-calls' help entry that advertised the
'-ptc' short flag, which belongs to '--print-token-count' (introduced in
e0596bf614 'Autoparser - complete refactoring of parser architecture
(PR 1376)'); the '-ptc' alias was non-functional for '--parallel-tool-calls'
because the parser only binds it to '--print-token-count'
The canonical help entries are kept:
- '--reasoning-budget N' is listed once
- '--parallel-tool-calls' is listed once (without the conflicting '-ptc' alias)
* common: remove duplicate LOG_ENABLE define
- the '#undef LOG_ENABLE / #define LOG_ENABLE() // dummy stub' pair was
repeated verbatim inside the LOG_DISABLE_LOGS section
- remove the second occurrence (introduced in a2588b53e1 'main : log
file (PR 2748)')
* llama-bench: align MLA and attention-max-batch flags with common tools
llama-bench used '--mla-attn' and '--attn-max-batch' while the common
CLI parsing (common/common.cpp) uses '--mla-use' and
'--attention-max-batch' for the same features. This made the flags
inconsistent across tools.
- update the help text to advertise the canonical names
'--mla-use' and '--attention-max-batch'
- keep the old '--mla-attn' and '--attn-max-batch' spellings working
as aliases so existing scripts are not broken
The divergent names were introduced in 3e536b95b0 'Add optional MLA
(PR 188)'.
* fix typos in comments and user-facing strings
- ngram-map.cpp: 'Do we haven a existing' -> 'Do we have an existing'
(introduced in 1cb7e1bf39 'spec : add self speculative decoding,
ngram and refactor (PR 1261)')
- build_mamba.cpp: 'weigth' -> 'weight' (introduced in 8befd92ea5
'Refactor model compute graphs (PR 1651)')
- gguf-split.cpp: 'one of splits have 0 tensors' -> 'one of the splits
has 0 tensors' (introduced in 75b580db0a 'split: allow
--split-max-size option (PR 6343)')
- gguf-split.cpp: 'merged from %d split' -> 'merged from %d splits'
(introduced in 1b5523dc79 'gguf-split: split and merge gguf per
batch of tensors (PR 6135)')
- convert-llama2c-to-ggml.cpp: missing opening quote in the help line,
'(default %s\\')' -> '(default '%s\\')' (introduced in bb9ebb4394
'Adding support for llama2.c models (PR 2559)')
* harmonize British and American spelling to American English
The codebase uses American English (e.g. --embd-normalize, --color),
but a few strings/comments still used British spellings. Unify them:
- 'normalisation' -> 'normalization' in common.h, common.cpp help text
and code comment, and llama-build-context.cpp comment
- 'colorise' -> 'colorize' in the --color help text (common.cpp)
- 'behaviour' -> 'behavior' in a chat.cpp warning and a llama.cpp comment
- also fix 'openai' -> 'OpenAI' capitalization in the embedding help
text and common.h comment (embedding output format is OpenAI-style)
* common: fix help text formatting inconsistencies
- '-smf16'/'--split-mode-f16' and '-smf32'/'--split-mode-f32' help
entries displayed hardcoded 'true'/'false' as the default value;
show the actual state derived from params.reduce_type instead
- '-no-mmad' help entry had 'fused_mmad?' without a space before the
ternary operator
- '--reasoning-tokens' help continuation lines used tab characters for
indentation while the sibling '--reasoning-format' entry uses spaces;
convert to consistent space indentation
* common: revert smf16/smf32 help text default display change
Revert the '-smf16'/'--split-mode-f16' and '-smf32'/'--split-mode-f32'
help entries back to their original hardcoded 'true'/'false' default
display. The change to derive the default from params.reduce_type was
not desired; the split-mode options are legacy and the hardcoded
defaults reflect their intended meaning.
The other formatting fixes in the same area (fused_mmad ternary
spacing and the reasoning-tokens tab-to-space indentation) are kept.
* llama-bench: fix help text column alignment
The --mla-use and --attention-max-batch help lines introduced by the
flag alignment landed one column off from the sibling entries
((default: at column 51 instead of 50). Adjust the padding so all
help lines align.
* common: fix help text defaults for graph-reduce-type and log-format
Mismatch 1: -grt, --graph-reduce-type help shows default "f32", but actual default (common.h:463) is "f16" and llama.cpp uses GGML_TYPE_F16.
Mismatch 2: --log-format help shows default "json", but actual default (common.h:536 log_json=false) is text.
* common: add -ptcall short flag for --parallel-tool-calls
* typo
* Add --prefetch-experts to stream mmap'd MoE experts into page cache
* Drop fds, fault experts in with MADV_POPULATE_READ instead of pread
* Remove stale note about pread workers
* Move MoE prefetch behind ggml_backend_prefetch_* wrappers
* Cleanup stale comments
* Add --prefetch-experts-threads, drop GGML_MOE_PREFETCH_THREADS env var
* host-swap tensor loop
the host-swap functionality is only triggered when the certain env. variables are declared
* target_include_directories tweak
* hot-swap tensor support
two intrusions:
1.) at the model loading to collect the snapshot
2.) the modification of the `/health` HTTP endpoint to be able to trigger the hot-swap via sending the `llama-server` the HTTP-request.
*both a braced by the specific env. variables
* hot-swap tensor support; graph invalidation
ggml_backend_cuda_invalidate_graphs export
* hot-swap tensor support
graph invalidation implementation; extended debug output (commented out)
* llama_reload_changed_tensors export
* tensor hot-swap on-demand reload
cpu-only/hybrid/gpu-only with split mode layer/graph full support implementation
* docs
* reuse the gguf parsing from llama.cpp
gguf_init_from_file, gguf_find_tensor, ggml_get_tensor
* remove the manual scheduling for hybrid inference
* update docs
* tensor shape validation
* update docs
* update docs
accidentally wiped the previous changes; so recovered them
* revert the GGML_CUDA_MAX_DEVICES to 16
* update llama_reload_changed_tensor
update llama_reload_changed_tensor, revert CMakeLists.txt
* update llama_reload_changed_tensor
* GGML_MAX_SRC
GGML_MAX_SRC compile-time definition support
* GGML_MAX_SRC
GGML_MAX_SRC compile-time definition support
* GGML_MAX_SRC
GGML_MAX_SRC compile-time definition support
* llama_reload_changed_tensor
update llama_reload_changed_tensor definition
* refactory
move the tensor-reloading implementation to llama-reload.cpp, llama-reload-info.h; some bugfixes and code reduction
* revert
added back the missing newline
* update docs
* reload_info constructor
* bugfix: cpu-only
TODO: improve the working environment by compiling for multiple hardware configurations; possibly make a test pipeline
* cpu-only bugfix
set the fix again after unsuccessful sync with main
* windows os compilation fix
#include <string>
* fix windows os build
error C2039: 'string': is not a member of 'std'
* remove dead file
* implement perplexity in server
* Revert "implement perplexity in server"
* gmp-oss: common
* gpt-oss: attnetion sinks, swiglu_oai
* gpt-oss: WIP llama
Model loads and runs (CPU only), but PPL is much to high
(~1500 for 1st batch vs ~200 in mainline).
Is it because of SWA, because of vocab, or did I introduce a bug somewhere?
* gpt-oss: CPU seems to be working
It was the SWA thta was missing in the previous commit.
There are issues with EOG tokens, so this still needs to be added.
* CUDA: ADD_ID
Just a copy from mainline
* gpt-oss: Seems to be working on CUDA
* gpt-oss: add sinks to the attn-vec kernels
* CUDA: add head size of 64 to new mma
Haven't turned it on yet, but observe slightly better PP and slightly
worse TG performance with that.
* gpt-oss: add ability to use -fmoe (only CUDA for now)
* Move row sums to the write place
* Add sinks to iqk flash attention
* gpt_oss: Implement -fmoe on the CPU
* Simdify swiglu_oai
Turning it off for now as performance becomes more variable,
so perhaps I'm running into thermal trottling imore often
because of making the CPU work too hard.
* llama: factor out model loader
* Builds successfully
* It runs, but mmap does not work
* Fix llama_mmap so mmap works
* Minor
* Fix CUDA after latest changes
* Attempt to use CUDA graphs with MoE models - not working
* CUDA graphs WIP - still not working
* CUDA graphs - seems to be working
Likely not all MLA variants are working.
I no longer remember why I added the q8_0 cpy that
transposes the tensor, but if really needed, this is now
missing. Also missing is q6_0.
* Make q8_0 cache work for DeepSeek models with CUDA graphs
* cuda: cpy for q6_0
* Fix llama_mmap on non-Linux platforms
* Adding forgotten file
* Iterating on Windows build failures
* cuda: re-add q8_0 -> q8_0 transpose
so mla = 2 can be used with CUDA graphs and q8_0 cache.
* Disable graphs without -fmoe
* Minor
* Turn graphs on by default
---------
Co-authored-by: Iwan Kawrakow <iwan.kawrakow@gmail.com>
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