Georgi Gerganov
e16b9fa4ba
metal : multi-simd softmax ( #3710 )
...
ggml-ci
2023-11-01 21:25:00 +02:00
Georgi Gerganov
71e3718abd
llama : refactor graph build code ( #3837 )
...
* llama : factor out ggml-alloc from graph graph build functions
ggml-ci
* metal : disable kernel load log
* llama : factor out tensor offloading outside the build call (wip)
ggml-ci
* llama : offload rest of the models
ggml-ci
* llama : update offload log messages to print node index
* llama : comments
* llama : support offloading result_norm + comments
* llama : factor graph input into a function
* llama : do tensor offload only with CUDA
* llama : fix res_norm offloading
* llama : try to optimize offloading code
* llama : fix non-CUDA build
* llama : try to fix build
* llama : move refact in correct place + optimize graph input
* llama : refactor tensor offloading as callback
* llama : add layer index to all tensor names
* llama : add functional header
* llama : comment
ggml-ci
* llama : remove obsolete map for layer counting
* llama : add llm_build helper functions (#3848 )
* llama : add llm_build_norm helper function
ggml-ci
* llama : add llm_build_ffn helper function (#3849 )
ggml-ci
* llama : add llm_build_k_shift helper
ggml-ci
* llama : fix offloading after recent changes
* llama : add llm_build_kv_store helper
ggml-ci
* llama : remove obsolete offload names
* llama : fix llm_build_k_shift to use n_head_kv instead of n_head
* llama : simplify falcon Q, K, V computation
* llama : remove obsolete comments in build graphs
* llama : add llm_build_kqv helper
ggml-ci
* llama : minor
* llama : add LLAMA_OFFLOAD_DEBUG + fix starcoder offloading
* llama : fix input allocation logic
* llama : update offload functions for KQ tensors
* llama : normalize tensor names
ggml-ci
* llama : enable warning about not offloaded tensors
* llama : remove extra ; + deduplicate gate_b logic
* llama : add llm_build_inp_embd helper
2023-11-01 08:04:02 +02:00
Aarni Koskela
82a6646e02
metal : try cwd for ggml-metal.metal if bundle lookup fails ( #3793 )
...
* Try cwd for ggml-metal if bundle lookup fails
When building with `-DBUILD_SHARED_LIBS=ON -DLLAMA_METAL=ON -DLLAMA_BUILD_SERVER=ON`,
`server` would fail to load `ggml-metal.metal` because `[bundle pathForResource:...]`
returns `nil`. In that case, fall back to `ggml-metal.metal` in the cwd instead of
passing `null` as a path.
Follows up on #1782
* Update ggml-metal.m
---------
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2023-10-28 15:43:01 +03:00
Georgi Gerganov
469c9addef
metal : handle ggml_scale for n%4 != 0 ( close #3754 )
...
ggml-ci
2023-10-24 09:47:22 +03:00
Jhen-Jie Hong
c67fe68e41
metal : implement q5_0 and q5_1 kernels ( #3648 )
...
* metal : implement dequantize_q5_0
* metal : block_q_n_dot_y for block_q5_0 (broken)
* metal : revert unnecessary change
* metal : implement dequantize_q5_1
* metal : block_q_n_dot_y for q5_1 (broken)
* metal : fix block_q_n_dot_y
* minor : spaces / formatting
---------
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2023-10-18 15:21:48 +03:00
Jan Ploski
f5f9121de1
llm : add MPT support ( #3417 )
...
* CUDA: added support for ggml_clamp (see also: https://github.com/ggerganov/ggml/issues/545 )
* mpt : added an implementation based (mostly) on falcon integration, modified with deltas from ggml/examples/mpt
* mpt : protect against "clip_qkv": null in mpt-7b
* mpt : quick fix to avoid "Strange model" warning when quantizing MPT models
* mpt : addendum to changeset:84e30e8 - leave parameter clamp_kqv out from metadata rather than use 0.0 to indicate "no clamping" (more compliant with the current GGUF spec?)
* mpt : standardized all tensor names to follow GGUF spec
* mpt : addendum to changeset:1be89c40 - use "req" parameter of GGUF_GET_KEY macro instead of duplicate code
* mpt : fixed comment s/gptneox/mpt/
* mpt : remove tabs, trailing whitespace
* mpt : removed ne01 + n_past == ne00 assertion from alibi (cuda/f32) and rope_shift from build_mpt
* mpt : updated convert-mpt-hf-to-gguf.py to reflect changes made to convert-gptneox-hf-to-gguf.py in pr:3252
* comment out n_past instead of marking it unused
* mpt : removed hardcoded +178 from convert script in favor of utilizing hparams["vocab_size"]
* mpt : remove unused tokenizer_json in convert script
* ggml : remove obsolete n_past assert in ggml_alibi
* llama : print clam_kqv and max_alibi_bias hparams
---------
Co-authored-by: Cebtenzzre <cebtenzzre@gmail.com>
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2023-10-10 10:50:23 +03:00
Georgi Gerganov
fcca0a7004
refact : fix convert script + zero out KV cache to avoid nans ( #3523 )
...
* refact : fix convert script + zero out KV cache to avoid nans
* ggml : silu(-inf) should never happen
* metal : assert various kernel requirements
2023-10-09 14:32:17 +03:00
Georgi Gerganov
dcc09d2596
metal : do not use mul_mm kernels when ne00 < 64 ( #3542 )
2023-10-09 14:28:27 +03:00
Georgi Gerganov
db3abcc114
sync : ggml (ggml-backend) ( #3548 )
...
* sync : ggml (ggml-backend)
ggml-ci
* zig : add ggml-backend to the build
2023-10-08 20:19:14 +03:00
Georgi Gerganov
94e502dfb7
ci : enable on obj-c changes + fix metal build ( #3540 )
2023-10-08 11:24:50 +03:00
Georgi Gerganov
b0ec5218c3
metal : support MTLGPUFamily < Apple7, formatting, style ( #3524 )
...
* metal : improve decoding speed for batches of 2-16
* metal : rename kernels mul_mat_ to mul_mv_
* metal : indentations
* minor
* metal : print more GPU info + disable mul_mm for MTLGPUFamiliy < Apple7
2023-10-08 10:01:53 +03:00
Jhen-Jie Hong
c26765a0a1
metal : support default.metallib load & reuse code for swift package ( #3522 )
...
* metal : support load default.metallib & reuse code for swift package
* metal : use SWIFT_PACKAGE def instead of define GGML_SWIFT
2023-10-07 11:40:27 +03:00
Phillip Kravtsov
0e797c2fc5
llm : support Adept Persimmon 8B ( #3410 )
...
* Produces garbage output
* wip: correct tensors up to RoPE
* correct tensors thru RoPE
* Correct outputs through masked & softmax'd KQ
* fp32 works
* Rename adept->persimmon
* Produces correct outputs
* clean up convert scripts
* remove printing logic from ggml.c
* remove prints from llama.cpp & fix merge
* trivial cleanups
* Add offload funcs
* update conversion script to directly take adept artifacts rather than .saftensors file
* Fix norm eps bug
* Support sqr and concat on metal, persimmon-8b-q4 runs correctly
* Small changes from review
* Formatting changes
* Minor changes to conversion script
* Remove old script
* Fix editorconfig formatting
* Fix build
* add overlooked offload code ggml-ci
2023-10-07 10:12:43 +03:00
Jiahao Li
f56e1baec3
metal : alibi for arbitrary number of heads ( #3426 )
2023-10-03 19:55:21 +03:00
Georgi Gerganov
ec893798b7
llama : custom attention mask + parallel decoding + no context swaps ( #3228 )
...
* tests : verify that RoPE is "additive"
* llama : replace ggml_diag_mask_inf with ggml_add (custom -inf mask)
* ggml : ggml_rope now takes a vector with positions instead of n_past
* metal : add rope_f16 kernel + optimize cpy kernels
* llama : unified KV cache + batch inference API
* llama : add new llama_decode() API that works with llama_batch
* llama : add cell_max heuristic for more efficient kv_cache
* llama : extend llama_kv_cache API
* llama : more robust cell_max heuristic + wip shift
* metal : disable concurrency optimization
* llama : add llama_kv_cache_shift_seq + no more context swaps
* llama : apply K-cache roping for Falcon and Baichuan
* speculative : fix KV cache management
* parallel : example for serving multiple users in parallel
* parallel : disable hot-plug to avoid cache fragmentation
* fixes : speculative KV cache + llama worst-case graph
* llama : extend batch API to select which logits to output
* llama : fix worst case graph build
* ggml-cuda : update rope implementation for parallel decoding (#3254 )
* ggml-cuda : update rope implementation for parallel decoding
* better solution for p0 computation
* fix rope
* simpler rope implementation
---------
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* make : add parallel to build + fix static functions in llama.cpp
* simple : fix token counting
* parallel : various improvements
* llama : fix cell_max logic + rename functions
* parallel : try smaller batches when the KV cache is fragmented
* parallel : fix sequence termination criteria
* llama : silence errors KV cache errors
* parallel : remove new line from prompt
* parallel : process system prompt once + configurable paramters + llama API
* parallel : remove question with short answers
* parallel : count cache misses
* parallel : print misses on each request
* parallel : minor
* llama : fix n_kv to never become 0
* parallel : rename hot-plug to continuous-batching
* llama : improve llama_batch API + simplify parallel example
* simple : add parallel decoding support
* simple : improve comments + free batch
* ggml-cuda : add rope f16, restore performance with parallel decoding (#3272 )
* ggml-cuda : add rope f16, restore performance
* offload KQ_mask with all models
* fix rope shift
---------
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* llama : disable MPI for now
ggml-ci
* train : make KQ_pos memory buffer permanent via dummy scale op
* ggml : revert change to ggml_cpy, add ggml_cont_Nd instead (#3275 )
ggml-ci
* parallel : fix bug (extra BOS) + smaller token_prev array
* parallel : fix cases where the input prompts can overflow the batch
* parallel : add disabled experimental batch chunking in powers of two
* llama : llama.h formatting + comments
* simple : add README.md
* llama : fix kv cache heuristic when context is less than 32
* parallel : fix crash when `-n -1`
* llama : simplify returns if/else branches
* metal : use mm kernels for batch size > 2
* examples : utilize new llama_get_logits_ith()
* examples : add example for batched decoding
* examples : do not eval prompt 2 times (close #3348 )
* server : clear the KV cache beyond n_past before llama_decode
* server : avoid context swaps by shifting the KV cache
---------
Co-authored-by: slaren <slarengh@gmail.com>
2023-09-28 19:04:36 +03:00
Rickard Hallerbäck
dc6897404e
metal : reusing llama.cpp logging ( #3152 )
...
* metal : reusing llama.cpp logging
* cmake : build fix
* metal : logging callback
* metal : logging va_args memory fix
* metal : minor cleanup
* metal : setting function like logging macro to capital letters
* llama.cpp : trailing whitespace fix
* ggml : log level enum used by llama
* Makefile : cleanup ggml-metal recipe
* ggml : ggml_log_callback typedef
* ggml : minor
---------
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2023-09-27 18:48:33 +03:00
Georgi Gerganov
8c00b7a6ff
sync : ggml (Metal F32 support + reduce ggml-alloc size) ( #3192 )
...
* sync : ggml (Metal F32 support + reduce ggml-alloc size)
ggml-ci
* llama-bench : fix ggml_cpu_has_metal() duplicate function
ggml-ci
2023-09-15 19:06:03 +03:00
Georgi Gerganov
a51b687657
metal : relax conditions on fast matrix multiplication kernel ( #3168 )
...
* metal : relax conditions on fast matrix multiplication kernel
* metal : revert the concurrnecy change because it was wrong
* llama : remove experimental stuff
2023-09-15 11:09:24 +03:00
Kawrakow
f31b6f4e2d
metal : PP speedup ( #3084 )
...
* Minor speed gains for all quantization types
* metal: faster kernel_scale via float4
* Various other speedups for "small" kernels
* metal: faster soft_max vial float4
* metal: faster diagonal infinity
Although, to me it looks like one should simply
fuse scale + diagnonal infinity + soft_max on the
KQtensor.
* Another faster f16 x f32 matrix multiply kernel
* Reverting the diag infinity change
It does work for PP, but somehow it fails for TG.
Need to look more into it.
* metal: add back faster diagonal infinity
This time more carefully
* metal : minor (readibility)
---------
Co-authored-by: Iwan Kawrakow <iwan.kawrakow@gmail.com>
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2023-09-11 10:30:11 +03:00
kchro3
21ac3a1503
metal : support for Swift ( #3078 )
...
* Metal support for Swift
* update
* add a toggle for arm/arm64
* set minimum versions for all platforms
* update to use newLibraryWithURL
* bump version
Co-authored-by: Jhen-Jie Hong <iainst0409@gmail.com>
---------
Co-authored-by: Jhen-Jie Hong <iainst0409@gmail.com>
2023-09-09 17:12:10 +08:00
Jhen-Jie Hong
4fd5477955
metal : support build for iOS/tvOS ( #3089 )
2023-09-09 11:46:04 +03:00
Kawrakow
be8c9c245b
metal : parallel RoPE on Metal ( #3024 )
...
* Parallel RoPE on metal
* PR suggestion
---------
Co-authored-by: Iwan Kawrakow <iwan.kawrakow@gmail.com>
2023-09-07 16:45:01 +03:00
Przemysław Pawełczyk
fec2fb19e4
ggml : posixify madvise and pagesize ( #3037 )
...
* llama : use posix_madvise() instead of madvise() derived from BSD
sed -i 's,\<madvise\>,posix_&,g;s,\<MADV_,POSIX_&,g' llama.cpp
* ggml : use sysconf(_SC_PAGESIZE) instead of getpagesize() derived from BSD
sed -i 's,getpagesize(),sysconf(_SC_PAGESIZE),g' ggml.c
* metal : use sysconf(_SC_PAGESIZE) instead of getpagesize() derived from BSD
sed -i 's,getpagesize(),sysconf(_SC_PAGESIZE),g' ggml-metal.m
2023-09-07 11:15:06 +03:00
Kawrakow
ca82cf7bac
metal : more optimizations ( #2959 )
...
* Very minor speedup via simd-group synchronization in f16 x f32
* Another very minor speedup on metal
* Quite significant PP speedup on metal
* Another attempt
* Minor
* Massive improvement for TG for fp16
* ~4-5% improvement for Q8_0 TG on metal
---------
Co-authored-by: Iwan Kawrakow <iwan.kawrakow@gmail.com>
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2023-09-03 11:06:22 +03:00
Karsten Weiss
8b56b4f2c3
metal : show all Metal device instances in the system ( #2952 )
...
* ggml_metal_init: Show all Metal device instances in the system
Also show the default Metal device that was picked.
* Update ggml-metal.m
---------
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2023-09-02 15:29:09 +03:00
Georgi Gerganov
13268c5331
metal : slight speed-up for add and mul kernels ( #2917 )
2023-09-01 13:42:41 +03:00
Kawrakow
e8d9158925
metal: somewhat faster f16 x f32 matrix multiply kernel ( #2951 )
...
* Somewhat faster f16 x f32 matrix multiply kernel
* Better use 32 thread groups for f16 x f32
---------
Co-authored-by: Iwan Kawrakow <iwan.kawrakow@gmail.com>
2023-09-01 11:15:57 +03:00
Georgi Gerganov
3a007648f2
metal : add option to disable debug logs ( close #2764 )
2023-08-29 11:33:46 +03:00
Georgi Gerganov
f55538c3cc
metal : fix memory leak ( #2762 )
...
* metal : fix memory leak
* metal : fix encoders memory leak
* metal : clean up more memory resources
* metal : fix more leaks
* metal : reuse dispatch queue + autoreleasepool
* metal : reuse array for command buffers and encoders
* ggml : assert for odd number of blocks on ARM
15M tinyllama is an example
2023-08-28 10:59:08 +03:00
Georgi Gerganov
d67777c202
metal : add Q8_0 support ( #2763 )
...
* metal : add dequantize_q8_0 kernel
* metal : add mul_mat_q8_0_f32 kernel
* metal : add Q8_0 mul_mm kernel
2023-08-24 16:19:57 +03:00
Georgi Gerganov
cf658adc83
llm : add Falcon support ( #2717 )
...
* llama : refactor GGUF constants into static maps
* llama : check if model architecture is known
* llama : refactor llama_model_load_internal()
* gguf : add KV constant maps
* llm : read arch-specific KVs
* convert : add dummy scores + types
* falcon : load tensor data (CPU only)
* llama : fix loading progress bar
* llama : add arch member to llama_model
* falcon : CPU inference working
* falcon : support non-40B models
* falcon : minor
* llama : minor updates
ggml-ci
* convert-falcon-hf-to-gguf.py : fix special token mapping
* llama.cpp : llama default UNK token = id 0
* llama.cpp : fix bpe tokenizer
* llama.cpp : fix the fix of bpe tokenizer
* ggml : pass eps to ggml_norm
* metal : implement RoPE (mode = 2) + avoid ggml_repeat
* ggml : ggml_repeat always creates new tensor
* falcon : copy-paste self-attention from LLaMA
* metal : print extra compute pipeline info
* falcon : minor changes (still chasing the Metal problem)
* llama.cpp : fix linefeed token
* metal : fix GELU kernel numerical stability by using precise::tanh
* metal : temporary workaround for the concurrency optimization bug
* falcon : add CUDA offloading (#2739 )
* llama : better model naming and size reporting
* llama : prep new tokenizer support
* llama : advanced BPE tokenizer based on ggllm.cpp imlpementation
* llama : remove oboslete comment
ggml-ci
* common : remove obsolete BPE API + disable test-tokenizer-1
* llama : revert BPE special-case in llama_byte_to_token()
* cuda : add TODOs for RoPE NeoX implementation
* llama : default special tokens based on vocab type
* perplexity : add log for start of tokenization
---------
Co-authored-by: klosax <131523366+klosax@users.noreply.github.com>
Co-authored-by: slaren <slarengh@gmail.com>
2023-08-23 23:08:04 +03:00
Georgi Gerganov
6381d4e110
gguf : new file format with flexible meta data (beta) ( #2398 )
...
* gguf : first API pass
* gguf : read header + meta data
* gguf : read tensor info
* gguf : initial model loading - not tested
* gguf : add gguf_get_tensor_name()
* gguf : do not support passing existing ggml_context to gguf_init
* gguf : simplify gguf_get_val
* gguf : gguf.c is now part of ggml.c
* gguf : read / write sample models
* gguf : add comments
* refactor : reduce code duplication and better API (#2415 )
* gguf : expose the gguf_type enum through the API for now
* gguf : add array support
* gguf.py : some code style changes
* convert.py : start a new simplified implementation by removing old stuff
* convert.py : remove GGML vocab + other obsolete stuff
* GGUF : write tensor (#2426 )
* WIP: Write tensor
* GGUF : Support writing tensors in Python
* refactor : rm unused import and upd todos
* fix : fix errors upd writing example
* rm example.gguf
* gitignore *.gguf
* undo formatting
* gguf : add gguf_find_key (#2438 )
* gguf.cpp : find key example
* ggml.h : add gguf_find_key
* ggml.c : add gguf_find_key
* gguf : fix writing tensors
* gguf : do not hardcode tensor names to read
* gguf : write sample tensors to read
* gguf : add tokenization constants
* quick and dirty conversion example
* gguf : fix writing gguf arrays
* gguf : write tensors one by one and code reuse
* gguf : fix writing gguf arrays
* gguf : write tensors one by one
* gguf : write tensors one by one
* gguf : write tokenizer data
* gguf : upd gguf conversion script
* Update convert-llama-h5-to-gguf.py
* gguf : handle already encoded string
* ggml.h : get array str and f32
* ggml.c : get arr str and f32
* gguf.py : support any type
* Update convert-llama-h5-to-gguf.py
* gguf : fix set is not subscriptable
* gguf : update convert-llama-h5-to-gguf.py
* constants.py : add layer norm eps
* gguf.py : add layer norm eps and merges
* ggml.h : increase GGML_MAX_NAME to 64
* ggml.c : add gguf_get_arr_n
* Update convert-llama-h5-to-gguf.py
* add gptneox gguf example
* Makefile : add gptneox gguf example
* Update convert-llama-h5-to-gguf.py
* add gptneox gguf example
* Update convert-llama-h5-to-gguf.py
* Update convert-gptneox-h5-to-gguf.py
* Update convert-gptneox-h5-to-gguf.py
* Update convert-llama-h5-to-gguf.py
* gguf : support custom alignment value
* gguf : fix typo in function call
* gguf : mmap tensor data example
* fix : update convert-llama-h5-to-gguf.py
* Update convert-llama-h5-to-gguf.py
* convert-gptneox-h5-to-gguf.py : Special tokens
* gptneox-main.cpp : special tokens
* Update gptneox-main.cpp
* constants.py : special tokens
* gguf.py : accumulate kv and tensor info data + special tokens
* convert-gptneox-h5-to-gguf.py : accumulate kv and ti + special tokens
* gguf : gguf counterpart of llama-util.h
* gguf-util.h : update note
* convert-llama-h5-to-gguf.py : accumulate kv / ti + special tokens
* convert-llama-h5-to-gguf.py : special tokens
* Delete gptneox-common.cpp
* Delete gptneox-common.h
* convert-gptneox-h5-to-gguf.py : gpt2bpe tokenizer
* gptneox-main.cpp : gpt2 bpe tokenizer
* gpt2 bpe tokenizer (handles merges and unicode)
* Makefile : remove gptneox-common
* gguf.py : bytesarray for gpt2bpe tokenizer
* cmpnct_gpt2bpe.hpp : comments
* gguf.py : use custom alignment if present
* gguf : minor stuff
* Update gptneox-main.cpp
* map tensor names
* convert-gptneox-h5-to-gguf.py : map tensor names
* convert-llama-h5-to-gguf.py : map tensor names
* gptneox-main.cpp : map tensor names
* gguf : start implementing libllama in GGUF (WIP)
* gguf : start implementing libllama in GGUF (WIP)
* rm binary commited by mistake
* upd .gitignore
* gguf : calculate n_mult
* gguf : inference with 7B model working (WIP)
* gguf : rm deprecated function
* gguf : start implementing gguf_file_saver (WIP)
* gguf : start implementing gguf_file_saver (WIP)
* gguf : start implementing gguf_file_saver (WIP)
* gguf : add gguf_get_kv_type
* gguf : add gguf_get_kv_type
* gguf : write metadata in gguf_file_saver (WIP)
* gguf : write metadata in gguf_file_saver (WIP)
* gguf : write metadata in gguf_file_saver
* gguf : rm references to old file formats
* gguf : shorter name for member variable
* gguf : rm redundant method
* gguf : get rid of n_mult, read n_ff from file
* Update gguf_tensor_map.py
* Update gptneox-main.cpp
* gguf : rm references to old file magics
* gguf : start implementing quantization (WIP)
* gguf : start implementing quantization (WIP)
* gguf : start implementing quantization (WIP)
* gguf : start implementing quantization (WIP)
* gguf : start implementing quantization (WIP)
* gguf : start implementing quantization (WIP)
* gguf : quantization is working
* gguf : roper closing of file
* gguf.py : no need to convert tensors twice
* convert-gptneox-h5-to-gguf.py : no need to convert tensors twice
* convert-llama-h5-to-gguf.py : no need to convert tensors twice
* convert-gptneox-h5-to-gguf.py : simplify nbytes
* convert-llama-h5-to-gguf.py : simplify nbytes
* gptneox-main.cpp : n_layer --> n_block
* constants.py : n_layer --> n_block
* gguf.py : n_layer --> n_block
* convert-gptneox-h5-to-gguf.py : n_layer --> n_block
* convert-llama-h5-to-gguf.py : n_layer --> n_block
* gptneox-main.cpp : n_layer --> n_block
* Update gguf_tensor_map.py
* convert-gptneox-h5-to-gguf.py : load model in parts to save memory
* convert-llama-h5-to-gguf.py : load model in parts to save memory
* convert : write more metadata for LLaMA
* convert : rm quantization version
* convert-gptneox-h5-to-gguf.py : add file_type key
* gptneox-main.cpp : add file_type key
* fix conflicts
* gguf : add todos and comments
* convert-gptneox-h5-to-gguf.py : tensor name map changes
* Create gguf_namemap.py : tensor name map changes
* Delete gguf_tensor_map.py
* gptneox-main.cpp : tensor name map changes
* convert-llama-h5-to-gguf.py : fixes
* gguf.py : dont add empty strings
* simple : minor style changes
* gguf : use UNIX line ending
* Create convert-llama-7b-pth-to-gguf.py
* llama : sync gguf-llama.cpp with latest llama.cpp (#2608 )
* llama : sync gguf-llama.cpp with latest llama.cpp
* minor : indentation + assert
* llama : refactor gguf_buffer and gguf_ctx_buffer
* llama : minor
* gitignore : add gptneox-main
* llama : tokenizer fixes (#2549 )
* Merge tokenizer fixes into the gguf branch.
* Add test vocabularies
* convert : update convert-new.py with tokenizer fixes (#2614 )
* Merge tokenizer fixes into the gguf branch.
* Add test vocabularies
* Adapt convert-new.py (and fix a clang-cl compiler error on windows)
* llama : sync gguf-llama with llama (#2613 )
* llama : sync gguf-llama with llama
* tests : fix build + warnings (test-tokenizer-1 still fails)
* tests : fix wstring_convert
* convert : fix layer names
* llama : sync gguf-llama.cpp
* convert : update HF converter to new tokenizer voodoo magics
* llama : update tokenizer style
* convert-llama-h5-to-gguf.py : add token types
* constants.py : add token types
* gguf.py : add token types
* convert-llama-7b-pth-to-gguf.py : add token types
* gguf-llama.cpp : fix n_head_kv
* convert-llama-h5-to-gguf.py : add 70b gqa support
* gguf.py : add tensor data layout
* convert-llama-h5-to-gguf.py : add tensor data layout
* convert-llama-7b-pth-to-gguf.py : add tensor data layout
* gptneox-main.cpp : add tensor data layout
* convert-llama-h5-to-gguf.py : clarify the reverse permute
* llama : refactor model loading code (#2620 )
* llama : style formatting + remove helper methods
* llama : fix quantization using gguf tool
* llama : simplify gguf_file_saver
* llama : fix method names
* llama : simplify write_header()
* llama : no need to pass full file loader to the file saver
just gguf_ctx
* llama : gguf_file_saver write I32
* llama : refactor tensor names (#2622 )
* gguf: update tensor names searched in quantization
* gguf : define tensor names as constants
* gguf : initial write API (not tested yet)
* gguf : write to file API (not tested)
* gguf : initial write API ready + example
* gguf : fix header write
* gguf : fixes + simplify example + add ggml_nbytes_pad()
* gguf : minor
* llama : replace gguf_file_saver with new gguf write API
* gguf : streaming support when writing files
* gguf : remove oboslete write methods
* gguf : remove obosolete gguf_get_arr_xxx API
* llama : simplify gguf_file_loader
* llama : move hparams and vocab from gguf_file_loader to llama_model_loader
* llama : merge gguf-util.h in llama.cpp
* llama : reorder definitions in .cpp to match .h
* llama : minor simplifications
* llama : refactor llama_model_loader (WIP)
wip : remove ggml_ctx from llama_model_loader
wip : merge gguf_file_loader in llama_model_loader
* llama : fix shape prints
* llama : fix Windows build + fix norm_rms_eps key
* llama : throw error on missing KV paris in model meta data
* llama : improve printing + log meta data
* llama : switch print order of meta data
---------
Co-authored-by: M. Yusuf Sarıgöz <yusufsarigoz@gmail.com>
* gguf : deduplicate (#2629 )
* gguf : better type names
* dedup : CPU + Metal is working
* ggml : fix warnings about unused results
* llama.cpp : fix line feed and compiler warning
* llama : fix strncpy warning + note token_to_str does not write null
* llama : restore the original load/save session implementation
Will migrate this to GGUF in the future
* convert-llama-h5-to-gguf.py : support alt ctx param name
* ggml : assert when using ggml_mul with non-F32 src1
* examples : dedup simple
---------
Co-authored-by: klosax <131523366+klosax@users.noreply.github.com>
* gguf.py : merge all files in gguf.py
* convert-new.py : pick #2427 for HF 70B support
* examples/gguf : no need to keep q option for quantization any more
* llama.cpp : print actual model size
* llama.cpp : use ggml_elements()
* convert-new.py : output gguf (#2635 )
* convert-new.py : output gguf (WIP)
* convert-new.py : add gguf key-value pairs
* llama : add hparams.ctx_train + no longer print ftype
* convert-new.py : minor fixes
* convert-new.py : vocab-only option should work now
* llama : fix tokenizer to use llama_char_to_byte
* tests : add new ggml-vocab-llama.gguf
* convert-new.py : tensor name mapping
* convert-new.py : add map for skipping tensor serialization
* convert-new.py : convert script now works
* gguf.py : pick some of the refactoring from #2644
* convert-new.py : minor fixes
* convert.py : update to support GGUF output
* Revert "ci : disable CI temporary to not waste energy"
This reverts commit 7e82d25f40#2644 )
* gguf : single pass for writing tensors + refactoring writer
* gguf : single pass for writing tensors + refactoring writer
* gguf : single pass for writing tensors + refactoring writer
* gguf : style fixes in simple conversion script
* gguf : refactor gptneox conversion script
* gguf : rename h5 to hf (for HuggingFace)
* gguf : refactor pth to gguf conversion script
* gguf : rm file_type key and method
* gguf.py : fix vertical alignment
* gguf.py : indentation
---------
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* convert-gptneox-hf-to-gguf.py : fixes
* gguf.py : gptneox mapping
* convert-llama-hf-to-gguf.py : fixes
* convert-llama-7b-pth-to-gguf.py : fixes
* ggml.h : reverse GGUF_MAGIC
* gguf.py : reverse GGUF_MAGIC
* test-tokenizer-0.cpp : fix warning
* llama.cpp : print kv general.name
* llama.cpp : get special token kv and linefeed token id
* llama : print number of tensors per type + print arch + style
* tests : update vocab file with new magic
* editorconfig : fix whitespaces
* llama : re-order functions
* llama : remove C++ API + reorganize common source in /common dir
* llama : minor API updates
* llama : avoid hardcoded special tokens
* llama : fix MPI build
ggml-ci
* llama : introduce enum llama_vocab_type + remove hardcoded string constants
* convert-falcon-hf-to-gguf.py : falcon HF --> gguf conversion, not tested
* falcon-main.cpp : falcon inference example
* convert-falcon-hf-to-gguf.py : remove extra kv
* convert-gptneox-hf-to-gguf.py : remove extra kv
* convert-llama-7b-pth-to-gguf.py : remove extra kv
* convert-llama-hf-to-gguf.py : remove extra kv
* gguf.py : fix for falcon 40b
* falcon-main.cpp : fix for falcon 40b
* convert-falcon-hf-to-gguf.py : update ref
* convert-falcon-hf-to-gguf.py : add tensor data layout
* cmpnct_gpt2bpe.hpp : fixes
* falcon-main.cpp : fixes
* gptneox-main.cpp : fixes
* cmpnct_gpt2bpe.hpp : remove non-general stuff
* Update examples/server/README.md
Co-authored-by: slaren <slarengh@gmail.com>
* cmpnct_gpt2bpe.hpp : cleanup
* convert-llama-hf-to-gguf.py : special tokens
* convert-llama-7b-pth-to-gguf.py : special tokens
* convert-permute-debug.py : permute debug print
* convert-permute-debug-master.py : permute debug for master
* convert-permute-debug.py : change permute type of attn_q
* convert.py : 70b model working (change attn_q permute)
* Delete convert-permute-debug-master.py
* Delete convert-permute-debug.py
* convert-llama-hf-to-gguf.py : fix attn_q permute
* gguf.py : fix rope scale kv
* convert-llama-hf-to-gguf.py : rope scale and added tokens
* convert-llama-7b-pth-to-gguf.py : rope scale and added tokens
* llama.cpp : use rope scale kv
* convert-llama-7b-pth-to-gguf.py : rope scale fix
* convert-llama-hf-to-gguf.py : rope scale fix
* py : fix whitespace
* gguf : add Python script to convert GGMLv3 LLaMA models to GGUF (#2682 )
* First pass at converting GGMLv3 LLaMA models to GGUF
* Cleanups, better output during conversion
* Fix vocab space conversion logic
* More vocab conversion fixes
* Add description to converted GGUF files
* Improve help text, expand warning
* Allow specifying name and description for output GGUF
* Allow overriding vocab and hyperparams from original model metadata
* Use correct params override var name
* Fix wrong type size for Q8_K
Better handling of original style metadata
* Set default value for gguf add_tensor raw_shape KW arg
* llama : improve token type support (#2668 )
* Merge tokenizer fixes into the gguf branch.
* Add test vocabularies
* Adapt convert-new.py (and fix a clang-cl compiler error on windows)
* Improved tokenizer test
But does it work on MacOS?
* Improve token type support
- Added @klosax code to convert.py
- Improved token type support in vocabulary
* Exclude platform dependent tests
* More sentencepiece compatibility by eliminating magic numbers
* Restored accidentally removed comment
* llama : add API for token type
ggml-ci
* tests : use new tokenizer type API (#2692 )
* Merge tokenizer fixes into the gguf branch.
* Add test vocabularies
* Adapt convert-new.py (and fix a clang-cl compiler error on windows)
* Improved tokenizer test
But does it work on MacOS?
* Improve token type support
- Added @klosax code to convert.py
- Improved token type support in vocabulary
* Exclude platform dependent tests
* More sentencepiece compatibility by eliminating magic numbers
* Restored accidentally removed comment
* Improve commentary
* Use token type API in test-tokenizer-1.cpp
* py : cosmetics
* readme : add notice about new file format
ggml-ci
---------
Co-authored-by: M. Yusuf Sarıgöz <yusufsarigoz@gmail.com>
Co-authored-by: klosax <131523366+klosax@users.noreply.github.com>
Co-authored-by: goerch <jhr.walter@t-online.de>
Co-authored-by: slaren <slarengh@gmail.com>
Co-authored-by: Kerfuffle <44031344+KerfuffleV2@users.noreply.github.com>
2023-08-21 23:07:43 +03:00
Jhen-Jie Hong
ed53db86c3
metal : print error of load pipeline state ( #2564 )
...
* metal : print error of load pipeline state
* metal : return null if load pipeline failed
2023-08-16 23:09:03 +03:00
Shouzheng Liu
fc8ef549e5
metal : enable ggml-alloc ( #2627 )
...
* metal: enable ggml-alloc
Make ggml-alloc work with concurrently dispatch.
* style-fix
Co-authored-by: slaren <slarengh@gmail.com>
---------
Co-authored-by: slaren <slarengh@gmail.com>
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2023-08-16 23:08:28 +03:00
Shouzheng Liu
bf83bff674
metal : matrix-matrix multiplication kernel ( #2615 )
...
* metal: matrix-matrix multiplication kernel
This commit removes MPS and uses custom matrix-matrix multiplication
kernels for all quantization types. This commit also adds grouped-query
attention to support llama2 70B.
* metal: fix performance degradation from gqa
Integers are slow on the GPU, and 64-bit divides are extremely slow.
In the context of GQA, we introduce a 64-bit divide that cannot be
optimized out by the compiler, which results in a decrease of ~8% in
inference performance. This commit fixes that issue by calculating a
part of the offset with a 32-bit divide. Naturally, this limits the
size of a single matrix to ~4GB. However, this limitation should
suffice for the near future.
* metal: fix bugs for GQA and perplexity test.
I mixed up ne02 and nb02 in previous commit.
2023-08-16 23:07:04 +03:00
Jhen-Jie Hong
d783f7982e
metal : return null instead of exit(1) ( #2573 )
2023-08-14 16:37:39 +03:00
Georgi Gerganov
f6f9896ac3
metal : fix out-of-bounds access + inc concurrency nodes ( #2416 )
...
* metal : fix out-of-bounds access + style changes
* metal : increase concurrency nodes to 2*GGML_MAX_NODES
2023-08-07 10:52:57 +03:00
Matteo Boschini
1873ff586b
metal : add gqa8 kernel to allow llama-2-70B on metal ( #2459 )
...
* Added gqa8 kernel to allow llama-2-70B on metal
* Update ggml-metal.m
Co-authored-by: Cebtenzzre <cebtenzzre@gmail.com>
* Extend kernel_mul_mat_f16_f32 to handle gqa broadcast
* Added ne03==ne13 assertion
---------
Co-authored-by: Cebtenzzre <cebtenzzre@gmail.com>
2023-08-01 10:43:12 +03:00
Shouzheng Liu
1aa18ef994
metal : concurrently dispatch commands ( #2358 )
...
* metal: concurrently dispatch commands
Function `ggml_metal_graph_find_concurrency` will run and write
commands that can be issued concurrently to metal context `concur_list`
array, when `ggml_metal_graph_compute` is called for the first time.
* metal: don't call find_concurrency automatically.
* metal : code style changes
---------
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2023-07-25 15:00:19 +03:00
slaren
41c674161f
make rms_norm_eps a parameter ( #2374 )
...
* make rms_norm_eps a parameter
* add rms_norm_eps to command line
* fix baby llama, test-grad0
* use scientific notation for eps param in the help
ggml-ci
2023-07-24 17:57:12 +02:00
Georgi Gerganov
5b2b2dc6ae
ggml : sync (unary ops refactor, static-correctness) ( #2370 )
...
* ggml : sync (unary ops, tests)
ggml-ci
* tests : remove unnecessary funcs
2023-07-24 14:46:21 +03:00
slaren
95a6c595e7
ggml: move op parameters from tensors to ggml_tensor::op_params ( #2333 )
...
* ggml: move op parameters from tensors to ggml_tensor::op_params
* alibi: use memcpy for float params
* remove `src[1] = NULL` in ops
2023-07-23 14:36:02 +02:00
Jiahao Li
83a00ce69b
metal : support bcast add & dup & cont op ( #2323 )
2023-07-23 14:00:37 +03:00
Kawrakow
4d76a5f49b
Faster Q3_K implementation on Metal ( #2307 )
...
* Faster Q3_K on Metal
* Additional Q3_K speedup on Metal
* Q3_K for QK_K = 64
* Better Q3_K for QK_K = 64
21.6 ms/t -> 21.1 ms/t
---------
Co-authored-by: Iwan Kawrakow <iwan.kawrakow@gmail.com>
2023-07-21 17:05:30 +03:00
Kawrakow
e68c96f7fe
Faster Q2_K on Metal ( #2297 )
...
* Faster Q2_K on Metal
* Deleting unnoticed and dangereous trailing white space
* Fixed bug in new metal Q2_K implementation
---------
Co-authored-by: Iwan Kawrakow <iwan.kawrakow@gmail.com>
2023-07-21 10:44:40 +03:00
Kawrakow
e782c9e735
Faster Q5_K and Q6_K on Metal ( #2294 )
...
* Faster Q6_K on Metal
* Faster Q5_K on Metal
* Another Q5_K speedup
---------
Co-authored-by: Iwan Kawrakow <iwan.kawrakow@gmail.com>
2023-07-20 18:19:45 +03:00
Kawrakow
785829dfe8
Faster Q4_K on Metal ( #2290 )
...
Co-authored-by: Iwan Kawrakow <iwan.kawrakow@gmail.com>
2023-07-20 15:18:43 +03:00
Shouzheng Liu
417a85a001
metal: minor q4 optimization and reduce code size ( #2248 )
...
* metal: use uint16_t instead of uint8_t.
Apple GPU doesn't like uint8_t. For every operation on uint8_t
the gpu need to copy the uint8_t to an empty 16 bit register, then
it can issue other instructions.
For the matrix-vector multiplication kernel only, we observed a
340~350 GB/s memory read speed on M1 Max after this commit, which is
very close to the reported hardware limit.
* metal: update rms_norm kernel
This commit double the speed of rms_norm operations by using 512 threads
per threadgroup, combining with SIMD primitives to minimize the need for
thread group barriers.
* metal: use template to reduce size
Revert modifications on block_q4_0 and block_q4_1.
2023-07-20 13:32:22 +03:00
Xiao-Yong Jin
6e7cca4047
llama : add custom RoPE ( #2054 )
...
* Implement customizable RoPE
The original RoPE has pre-defined parameters
theta_i = 10000^(−2(i−1)/d), for i in [1, 2, ..., d/2]
Our customizable RoPE, ggml_rope_custom_inplace, uses
theta_i = scale * base^(−2(i−1)/d), for i in [1, 2, ..., d/2]
with the default matches the original
scale = 1.0
base = 10000
The new command line arguments
--rope-freq-base
--rope-freq-scale
set the two new RoPE parameter.
Recent researches show changing these two parameters extends the context limit with minimal loss.
1. Extending Context to 8K
kaiokendev
https://kaiokendev.github.io/til#extending-context-to-8k
2. Extending Context Window of Large Language Models via Positional Interpolation
Shouyuan Chen, Sherman Wong, Liangjian Chen, Yuandong Tian
https://arxiv.org/abs/2306.15595
3. NTK-Aware Scaled RoPE allows LLaMA models to have extended (8k+) context size without any fine-tuning and minimal perplexity degradation.
https://www.reddit.com/user/bloc97
https://www.reddit.com/r/LocalLLaMA/comments/14lz7j5/ntkaware_scaled_rope_allows_llama_models_to_have/
For the bold, try adding the following command line parameters to your favorite model:
-c 16384 --rope-freq-base 80000 --rope-freq-scale 0.5
* ggml-metal: fix custom rope
* common: fix argument names in help
* llama: increase MEM_REQ_EVAL for MODEL_3B
It avoids crashing for quantized weights on CPU.
Better ways to calculate the required buffer size would be better.
* llama: make MEM_REQ_EVAL depend on n_ctx
* server: use proper Content-Type in curl examples
Without the header Content-Type: application/json, curl will POST with
Content-Type: application/x-www-form-urlencoded
Though our simple server doesn't care, the httplib.h used has a limit
with CPPHTTPLIB_FORM_URL_ENCODED_PAYLOAD_MAX_LENGTH 8192
With Content-Type: application/json, we can send large json data.
* style : minor fixes, mostly indentations
* ggml : fix asserts
---------
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2023-07-15 13:34:16 +03:00
Kawrakow
27ad57a69b
Metal: faster Q4_0 and Q4_1 matrix x vector kernels ( #2212 )
...
* 3-5% faster Q4_0 on Metal
* 7-25% faster Q4_1 on Metal
* Oops, forgot to delete the original Q4_1 kernel
---------
Co-authored-by: Iwan Kawrakow <iwan.kawrakow@gmail.com>
2023-07-14 11:46:21 +02:00
