Commit Graph

72 Commits

Author SHA1 Message Date
Georgi Gerganov
5946d98fc8
metal : disable kernel load log 2023-10-28 21:22:01 +03:00
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.

* convert.py : n_head_kv optional and .gguf file extension

* convert.py : better always have n_head_kv and default it to n_head

* llama : sync with recent PRs on master

* editorconfig : ignore models folder

ggml-ci

* ci : update ".bin" to ".gguf" extension

ggml-ci

* llama : fix llama_model_loader memory leak

* gptneox : move as a WIP example

* llama : fix lambda capture

ggml-ci

* ggml : fix bug in gguf_set_kv

ggml-ci

* common.h : .bin --> .gguf

* quantize-stats.cpp : .bin --> .gguf

* convert.py : fix HF tensor permuting / unpacking

ggml-ci

* llama.cpp : typo

* llama : throw error if gguf fails to init from file

ggml-ci

* llama : fix tensor name grepping during quantization

ggml-ci

* gguf.py : write tensors in a single pass (#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
Shouzheng Liu
1cbf561466
metal : new q4_0 matrix-vector kernel (#2188)
Prefetch data to improve GPU utilization. ~48% faster for 33B model.
2023-07-12 23:10:55 +03:00