* refactor: replace ggml_hexagon_mul_mat with template-based binary operation for improved flexibility
* refactor: replace ggml_hexagon_mul_mat_id with template-based binary operation for improved flexibility
* refactor: initialize buffer types and streamline dspqueue_buffers_init calls for clarity
* add comment
* refactor: remove redundant buffer checks in hexagon supported operations
* wip
* add missing include to fix weak symbol warning
* add ggml_hexagon_op_generic
* refactor: simplify tensor operation initialization and buffer management in hexagon implementation
* refactor: streamline hexagon operation initialization and buffer management
* refactor: update function signatures and streamline request handling in hexagon operations
* wip
* ggml-hexagon: clean up code formatting and improve unary operation handling
* wip
* rename
* fix: add support for permuted F16 tensors and enhance quantization checks in matrix operations
* refactor: replace ggml_hexagon_mul_mat with template-based binary operation for improved flexibility
refactor: replace ggml_hexagon_mul_mat_id with template-based binary operation for improved flexibility
refactor: initialize buffer types and streamline dspqueue_buffers_init calls for clarity
refactor: remove redundant buffer checks in hexagon supported operations
add missing include to fix weak symbol warning
add ggml_hexagon_op_generic
refactor: simplify tensor operation initialization and buffer management in hexagon implementation
refactor: streamline hexagon operation initialization and buffer management
refactor: update function signatures and streamline request handling in hexagon operations
ggml-hexagon: clean up code formatting and improve unary operation handling
fix: add support for permuted F16 tensors and enhance quantization checks in matrix operations
# Conflicts:
# ggml/src/ggml-hexagon/ggml-hexagon.cpp
* hexagon: fix merge conflicts
* hexagon: minor cleanup for buffer support checks
* hexagon: factor out op_desc and the overal op logging
* hexagon: further simplify and cleanup op dispatch logic
* snapdragon: update adb scripts to use llama-cli and llama-completion
* fix pipeline failure
---------
Co-authored-by: Max Krasnyansky <maxk@qti.qualcomm.com>
This commit adds the trust_remote_code=True parameter when loading
models and configurations in the embedding model conversion scripts.
It also adds a cast to float for models that might use a data type that
is not supported by python, for example bfloat16.
The motivation for this is that some models may require custom code to
be executed during loading, and setting trust_remote_code to True avoids
getting prompted for confirmation.
Future work will consolidate the embedding conversion scripts with the
causal conversion scripts to avoid code duplication. But in the mean
time it would be nice to have this fix in place.
ModernBERT but without `head.norm` so will currently fail to convert and run any other ModernBERT models, PRs with `head.norm` support welcome!
* constants and tensor mappings for modern bert support, model not supported yet but working on getting conversion to work for encoder only
* conversion now working, hf -> gguf
* working on support, now working on building graph
* some cleanup
* cleanup
* continuing
* correct tensor shape for qkv
* fixed tensor mappings and working on buildin graph
* tensor debugging now works -> (llama-eval-callback), instead of simulated gate split with views, GEGLU is now used which does exactly this
* cleanup
* cleanup
* cleanup
* more cleanup
* ubatch issues, the assert for checking equal seqs in llama-graph.cpp when building attention keeps failing, setting ubatch size to 1 when running llama-embedding with --ubatch-size 1 makes it work, but needs to be looked into more
* added cls token per previous modern bert attempt, still working on checking out the rest
* fixed pre tokenizer and still working through previous pr
* working through previous attemp, implimented more accurate conversion per previous attempt, added local sliding window attention that alternates every third layer
* fixed pre tokenizer
* working on swa with local and global alternating attention
* some cleanup and now fails on build attn
* starting to work, and some cleanup, currently failing on last layer construction in graph build
* alternating rope implemented and modern bert graph build succeeds
* fixed asser for equal ubatch seq
* cleanup
* added mask check in vocab
* fixed alternating rope, the hparams.rope_freq_base_train and hparams.rope_freq_base_train_swa were the same and i set them to correct values
* reuse variable
* removed repeat
* standard swa method can be used instead of a new enum being LLAMA_SWA_TYPE_LOCAL
* correct swa layer indexing, is supposed to be 0, 3, 6 ... instead of 1, 4, 7 ...
* more modular hparam setting
* replaced attn out norm with ffn_norm and cosine similarity between hf embds and llama.cpp embds went way up, from 0.05 to 0.24, replaced the cacheless kv with swa todo per the previous conversion
* Update gguf-py/gguf/tensor_mapping.py
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* Update convert_hf_to_gguf_update.py
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* Update src/llama-model.cpp
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* Update src/llama-vocab.cpp
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* Update src/llama-model.cpp
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* Update gguf-py/gguf/tensor_mapping.py
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* Update convert_hf_to_gguf.py
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* Update gguf-py/gguf/tensor_mapping.py
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* Update gguf-py/gguf/tensor_mapping.py
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* Update convert_hf_to_gguf.py
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* Update gguf-py/gguf/tensor_mapping.py
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* Update gguf-py/gguf/tensor_mapping.py
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* Update gguf-py/gguf/tensor_mapping.py
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* Update gguf-py/gguf/tensor_mapping.py
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* Update gguf-py/gguf/tensor_mapping.py
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* Update gguf-py/gguf/tensor_mapping.py
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* Update src/llama-graph.cpp
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* Update src/llama-arch.cpp
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* Update src/llama-model.cpp
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* Update src/llama-model.cpp
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* Update src/llama-model.cpp
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* Update src/llama-model.cpp
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* Update src/llama-model.cpp
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* removed redundant hparam set
* enums for model sizes
* conversion for modern-bert model supported rather than just granite-small
* Update src/llama-model.cpp
Co-authored-by: Gabe Goodhart <ghart@us.ibm.com>
* Update src/llama-model.cpp
Co-authored-by: Gabe Goodhart <ghart@us.ibm.com>
* fixed ordering of enum for freq_base_swa
* fixed where I added residual, now gives much much better embeddings~
* readded cacheless logic
* removing whitespace
* conversion now working for swa pattern - dense every n layers
* modern bert put into seperate src file
* removing whitespace
* fixed whitespace and newline errors in editorconfig job
* Update convert_hf_to_gguf.py
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* better naming convention, n_swa_pattern -> swa_period
* reusing sliding_window_pattern key rather than making new dense_every_n_layers key, and adding writing and reading support
* fixing pyright type-check fail
* Update convert_hf_to_gguf.py
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* Update gguf-py/gguf/gguf_writer.py
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* Update src/llama-hparams.h
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* Update src/llama-model-saver.cpp
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* Update src/models/modern-bert.cpp
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* Update src/models/modern-bert.cpp
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* Update src/models/modern-bert.cpp
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* Update gguf-py/gguf/gguf_writer.py
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* Update src/models/modern-bert.cpp
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* Update src/models/modern-bert.cpp
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* Update src/llama-model.cpp
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* Update src/llama-model-loader.cpp
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* Update src/llama-model-loader.cpp
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* Update src/llama-model-loader.cpp
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* added descriptions in llama-model
* fixed tensor mappings for conversion
* Update src/llama-model.cpp
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* Update src/llama-model.cpp
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* mapping name for size
* nits
* unused
---------
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
Co-authored-by: Gabe Goodhart <ghart@us.ibm.com>
* feat: working gelu with src0 put on vtcm
* feat: gelu ping-pong for both in and out
* fix: fixu compile error
* break: distinguish dma ddr->vtcm and vtcm->ddr operation
* fix: fix dma queue size
* break: update dma api to either pop src or dst ptr
* fix: fix activation vtcm allocation issue for src1 when swapperd
* refactor: ping-pong gelu logic to avoid unnecessary if else
* dma: improved queue interface and prefetch handling
* gelu: fix N+2 block prefetch
---------
Co-authored-by: Max Krasnyansky <maxk@qti.qualcomm.com>
* server: prevent data race from HTTP threads
* fix params
* fix default_generation_settings
* nits: make handle_completions_impl looks less strange
* stricter const
* fix GGML_ASSERT(idx < states.size())
* move index to be managed by server_response_reader
* http: make sure req & res lifecycle are tied together
* fix compile
* fix index handling buggy
* fix data race for lora endpoint
* nits: fix shadow variable
* nits: revert redundant changes
* nits: correct naming for json_webui_settings
* Update release workflow to store XCFramework as Zip file
* Add comments to document Zip file requirement for XCFramework
* Apply suggestions from code review
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
---------
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
The goal is to enable the async loading code paths in
llama_model_loader::load_all_data, originally from #7896. This works and the
loads themselves are faster, but with host visible vidmem I think the cost of
allocating/mapping vidmem moves and becomes more expensive, and I don't see a
benefit by default. But with GGML_VK_DISABLE_HOST_VISIBLE_VIDMEM=1 I do see a
significant improvement in model loading time.
I updated test_topk_moe to more closely match llm_graph_context::build_moe_ffn
and added coverage for exp_probs_b and some other missing combinations. This
exposed a bug in both CUDA and Vulkan backends where they were assuming the
input to argsort and the input to get_rows are the same. I'd like to optimize
this graph in another change, but for now just get it functional.
CUDA also had a bug where it got n_experts from the wrong place, leading to
GGML_ASSERT failures in some of the new tests.
* Some improvement on mul_mat_iq2_xs
Refactor calculations for db values and grid data to optimize performance and reduce redundancy.
* Fix trailing whitespace
* implement sleeping at queue level
* implement server-context suspend
* add test
* add docs
* optimization: add fast path
* make sure to free llama_init
* nits
* fix use-after-free
* allow /models to be accessed during sleeping, fix use-after-free
* don't allow accessing /models during sleep, it is not thread-safe
* fix data race on accessing props and model_meta
* small clean up
* trailing whitespace
* rm outdated comments
* arg: fix order to use short form before long form
* arg: update doc
* arg: update test-arg-parser
* arg: address review feedback from ngxson
simplified to check first.length() <= last.length() only
fixed: --sampler-seq, --rerank, --draft ordering
note: middle positions in 3+ arg sets are not verified
* arg: update doc
* llama-server: friendlier error msg when ctx < input
This PR adds formatted strings to the server's send_error function
* llama-server: use string_format inline
* fix test
* presets: refactor, allow cascade presets from different sources
* update docs
* fix neg arg handling
* fix empty mmproj
* also filter out server-controlled args before to_ini()
* skip loading custom_models if not specified
* fix unset_reserved_args
* fix crash on windows
This commit adds a --verbose flag to the run-org-model.py script to
enable or disable detailed debug output, such as input and output
tensors for each layer. Debug utilities (summarize, debug_hook,
setup_rope_debug) have been moved to utils/common.py.
The motivation for this is that the detailed debug output can be useful
for diagnosing issues with model conversion or execution, but it can
also produce a large amount of output that may not always be needed.
The script will also be further cleaned/refactored in follow-up commits.
This implements a variation of the perf logger where rather than timing each
operation individually with effectively a barrier in between, we put the
timing boundaries where we already synchronize and time the groups of work
that normally overlap. This can be useful to help understand whether
individual operations need to be optimized, or if the group is already running
efficiently.
GGML_VK_PERF_LOGGER_CONCURRENT=1 enables the new mode (when
GGML_VK_PERF_LOGGER is also set).
GGML_VK_SYNC_LOGGER=1 replaces the ENABLE_SYNC_LOGGING compile time switch.
Chris Rohlf
nullname
Daniel Bevenius
Neo Zhang
Alessandro98-git
Ryan Mangeno
compilade
Shouyu
Xuan-Son Nguyen
Taimur Ahmad
lhez
Jeff Bolz
Mattt
Aaron Teo
Johannes Gäßler
lovedheart
Aldehir Rojas
Aadeshveer Singh
Oleksandr Kuvshynov
Sigbjørn Skjæret
Alfred
Pascal
Julius Tischbein
Aman Gupta
Aleksander Grygier
Naco Siren