Commit Graph

3923 Commits

Author SHA1 Message Date
Gabe Goodhart
3d6bf6919f
llama : add IBM Granite MoE architecture (#9438)
* feat(gguf-py): Add granitemoe architecture

This includes the addition of new tensor names for the new moe layers.
These may not be correct at this point due to the need for the hack in
gguf_writer.py to double-check the length of the shape for these layers.

Branch: GraniteMoE

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat(convert_hf_to_gguf): Add GraniteMoeModel

GraniteMoe has the same configuration deltas as Granite

Branch: GraniteMoE

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix(granitemoe convert): Split the double-sized input layer into gate and up

After a lot of staring and squinting, it's clear that the standard mixtral
expert implementation is equivalent to the vectorized parallel experts in
granite. The difference is that in granite, the w1 and w3 are concatenated
into a single tensor "input_linear." Rather than reimplementing all of the
math on the llama.cpp side, the much simpler route is to just split this
tensor during conversion and follow the standard mixtral route.

Branch: GraniteMoE

Co-Authored-By: alex.brooks@ibm.com

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat(granitemoe): Implement granitemoe

GraniteMoE follows the mixtral architecture (once the input_linear layers
are split into gate_exps/up_exps). The main delta is the addition of the
same four multipliers used in Granite.

Branch: GraniteMoE

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* Typo fix in docstring

Co-Authored-By: ggerganov@gmail.com

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix(conversion): Simplify tensor name mapping in conversion

Branch: GraniteMoE

Co-Authored-By: git@compilade.net
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix(convert): Remove unused tensor name mappings

Branch: GraniteMoE

Co-Authored-By: git@compilade.net
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix(convert): Sanity check on merged FFN tensor sizes

Branch: GraniteMoE

Co-Authored-By: git@compilade.net
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Allow "output" layer in granite moe architecture (convert and cpp)

Branch: GraniteMoE

Co-Authored-By: git@compilade.net
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix(granite): Add missing 'output' tensor for Granite

This is a fix for the previous `granite` architecture PR. Recent snapshots
have included this (`lm_head.weights`) as part of the architecture

Branch: GraniteMoE

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

---------

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2024-09-25 10:06:52 +03:00
Dou Xinpeng
904837e0cb
cann: fix crash when llama-bench is running on multiple cann devices (#9627)
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2024-09-25 11:30:38 +08:00
Eric Zhang
70392f1f81
ggml : add AVX512DQ requirement for AVX512 builds (#9622)
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2024-09-24 11:03:21 +03:00
Georgi Gerganov
bb5f819975
sync : ggml 2024-09-24 11:01:18 +03:00
Georgi Gerganov
c038931615
examples : adapt to ggml.h changes (ggml/0)
ggml-ci
2024-09-24 11:00:52 +03:00
Georgi Gerganov
31ac5834fe
llama : keep track of all EOG tokens in the vocab (#9609)
ggml-ci
2024-09-24 10:16:06 +03:00
Georgi Gerganov
cea1486ecf
log : add CONT level for continuing previous log entry (#9610) 2024-09-24 10:15:35 +03:00
StrangeBytesDev
0aa15011e3
server : add newline after chat example (#9616) 2024-09-24 09:04:39 +03:00
Georgi Gerganov
b0f27361f3
sampling : avoid expensive softmax during greedy sampling (#9605)
* sampling : avoid expensive softmax during greedy sampling

ggml-ci

* speculative : fix default RNG seed + set sparams.n_probs

* Update tests/test-sampling.cpp

Co-authored-by: slaren <slarengh@gmail.com>

* sampling : add clarifying comment [no ci]

---------

Co-authored-by: slaren <slarengh@gmail.com>
2024-09-24 09:03:17 +03:00
Max Krasnyansky
c087b6f11d
threads: fix msvc build without openmp (#9615)
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We're missing atomic_thread_fence() in MSVC builds when openmp is disabled.
2024-09-23 21:18:48 -07:00
Ivan
116efee0ee
cuda: add q8_0->f32 cpy operation (#9571)
llama: enable K-shift for quantized KV cache
It will fail on unsupported backends or quant types.
2024-09-24 02:14:24 +02:00
Xuan Son Nguyen
0b3bf966f4
server : add --no-context-shift option (#9607)
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* server : add --no-context-shift option

* small fix

* Update examples/server/tests/features/embeddings.feature

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>

* tests : minor fix

* revert usage of GGML_ASSERT

* update server documentation

---------

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2024-09-23 22:23:54 +02:00
Max Krasnyansky
f0c7b5edf8
threads: improve ggml_barrier scaling with large number of threads (#9598)
Make sure n_barrier and n_barrier_passed do not share the cache line to avoid cache line bouncing.
This optimization shows performance improvements even for n_threads <= 8 cases.

Resurect TSAN (Thread Sanitizer) check so that we can avoid doing expensive read-modify-write
in the normal case and just use thread-fence as originally intended.

---
Here is the original description and suggestions from Willy Tarreau :

There's currently some false sharing between n_barrier and
n_barrier_passed that is amplified in ggml_barrier() by the fact that
all threads need to increment n_barrier when entering, while all
previous threads continue to read n_barrier_passed, waiting for the last
one to release them all. The side effect is that all these readers are
slowing down all new threads by making the cache line bounce back and
forth between readers and writers.

Just placing them in two distinct cache lines is sufficient to boost
the performance by 21% on a 80-core ARM server compared to the
no-openmp version, and by 3% compared to the openmp version.

Note that the variables could have been spread apart in the structure
as well, but it doesn't seem that the size of this threadpool struct is
critical so here we're simply aligning them.

Finally, the same issue was present when leaving the barrier since all
threads had to update the n_barrier_passed counter, though only one
would add a non-zero value. This alone is responsible for half of the
cost due to undesired serialization.

It might be possible that using a small array of n_barrier counters
could make things even faster on many-core systems, but it would likely
complicate the logic needed to detect the last thread.

Co-authored-by: Willy Tarreau <w@1wt.eu>
2024-09-23 11:42:43 -07:00
Riceball LEE
1d48e98e4f
readme : add programmable prompt engine language CLI (#9599) 2024-09-23 18:58:17 +03:00
Georgi Gerganov
f3979df762
flake.lock: Update (#9586)
Flake lock file updates:

• Updated input 'nixpkgs':
    'github:NixOS/nixpkgs/4f807e8940284ad7925ebd0a0993d2a1791acb2f?narHash=sha256-IiA3jfbR7K/B5%2B9byVi9BZGWTD4VSbWe8VLpp9B/iYk%3D' (2024-09-11)
  → 'github:NixOS/nixpkgs/c04d5652cfa9742b1d519688f65d1bbccea9eb7e?narHash=sha256-PmUr/2GQGvFTIJ6/Tvsins7Q43KTMvMFhvG6oaYK%2BWk%3D' (2024-09-19)

Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
2024-09-23 08:43:40 -07:00
Srihari-mcw
1e7b9299c6
ggml : AVX512 gemm for Q4_0_8_8 (#9532)
* AVX512 version of ggml_gemm_q4_0_8x8_q8_0

* Remove zero vector parameter passing

* Rename functions and rearrange order of macros

* Edit commments

* style : minor adjustments

* Update x to start from 0

---------

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2024-09-23 17:06:38 +03:00
Georgi Gerganov
37f8c7b4c9
perplexity : remove extra new lines after chunks (#9596)
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2024-09-23 11:28:02 +03:00
Georgi Gerganov
bf9c1013ac
metal : use F32 prec for K*Q in vec FA (#9595)
ggml-ci
2024-09-23 11:27:47 +03:00
Akarshan Biswas
e62e9789cd
Revert "[SYCL] fallback mmvq (#9088)" (#9579)
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This reverts commit 50addec9a5.
2024-09-23 11:28:06 +08:00
R0CKSTAR
c35e586ea5
musa: enable building fat binaries, enable unified memory, and disable Flash Attention on QY1 (MTT S80) (#9526)
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* mtgpu: add mp_21 support

Signed-off-by: Xiaodong Ye <xiaodong.ye@mthreads.com>

* mtgpu: disable flash attention on qy1 (MTT S80); disable q3_k and mul_mat_batched_cublas

Signed-off-by: Xiaodong Ye <xiaodong.ye@mthreads.com>

* mtgpu: enable unified memory

Signed-off-by: Xiaodong Ye <xiaodong.ye@mthreads.com>

* mtgpu: map cublasOperation_t to mublasOperation_t (sync code to latest)

Signed-off-by: Xiaodong Ye <xiaodong.ye@mthreads.com>

---------

Signed-off-by: Xiaodong Ye <xiaodong.ye@mthreads.com>
2024-09-22 16:55:49 +02:00
Molly Sophia
912c331d3d
Fix merge error in #9454 (#9589)
Signed-off-by: Molly Sophia <mollysophia379@gmail.com>
2024-09-22 15:26:50 +02:00
Johannes Gäßler
a5b57b08ce
CUDA: enable Gemma FA for HIP/Pascal (#9581)
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2024-09-22 09:34:52 +02:00
Shankar
ecd5d6b65b
llama: remove redundant loop when constructing ubatch (#9574)
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2024-09-22 04:30:34 +02:00
Molly Sophia
2a63caaa69
RWKV v6: RWKV_WKV op CUDA implementation (#9454)
* ggml: CUDA unary op EXP

Signed-off-by: Molly Sophia <mollysophia379@gmail.com>

* ggml: rwkv_wkv op CUDA impl

Signed-off-by: Molly Sophia <mollysophia379@gmail.com>

---------

Signed-off-by: Molly Sophia <mollysophia379@gmail.com>
2024-09-22 04:29:12 +02:00
slaren
d09770cae7
ggml-alloc : fix list of allocated tensors with GGML_ALLOCATOR_DEBUG (#9573)
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2024-09-21 14:24:23 +02:00
agray3
41f477879f
Update CUDA graph on scale change plus clear nodes/params (#9550)
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* Avoid using saved CUDA graph if scale changes and reset nodes/params on update

Fixes https://github.com/ggerganov/llama.cpp/issues/9451

* clear before resize
2024-09-21 02:41:07 +02:00
Huang Qi
e948a7da7a
CI: Provide prebuilt windows binary for hip (#9467) 2024-09-21 02:39:41 +02:00
slaren
63351143b2
quantize : improve type name parsing (#9570)
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quantize : do not ignore invalid types in arg parsing

quantize : ignore case of type and ftype arguments
2024-09-20 20:55:36 +02:00
Georgi Gerganov
d13edb17ed ggml : fix builds (#0)
ggml-ci
2024-09-20 21:15:05 +03:00
Georgi Gerganov
27609c49b9 ggml : fix trailing whitespace (#0)
ggml-ci
2024-09-20 21:15:05 +03:00
Georgi Gerganov
4301535326 sync : ggml
ggml-ci
2024-09-20 21:15:05 +03:00
Johannes Gäßler
424c5d00a9 ggml/examples: add backend support for numerical optimization (ggml/949)
* CUDA eval works

* stochastic gradient descent op

* Adam except decay

* CUDA CROSS_ENTROPY_LOSS_BACK

* CUDA mnist-fc training works

* backend CLI arg

* refactor gguf load

* remove sched from opt_step_adam

* implement l1 regularization (weight decay)

* extra call to add optimizer

* initialize gradients with ggml_graph_reset

* gradient accumulation

* increment iter per eval instead of epoch

* adjust backend interfaces

* fix ggml_graph_reset without backend

* fix ggml graph export/import

* fixup

* rename

* revert ggml_opt changes

* more general CUDA repeat_back

* update documentation, fix CNN

* validation split

* add clarifying comment

* optimize PyTorch training

* adjust buffer size, thread count

* fix 0.0f validation split

* Update examples/mnist/mnist-common.cpp

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>

* fix gradient accumulation

* tensor flag for accumulators -> tensor hash set

* Update include/ggml.h

Co-authored-by: slaren <slarengh@gmail.com>

* Update tests/test-backend-ops.cpp

Co-authored-by: slaren <slarengh@gmail.com>

* Update tests/test-backend-ops.cpp

Co-authored-by: slaren <slarengh@gmail.com>

* fix test prints

* Update src/ggml-backend.c

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>

* better CUDA support for noncontiguous out_prod

* add comment

---------

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
Co-authored-by: slaren <slarengh@gmail.com>
2024-09-20 21:15:05 +03:00
Georgi Gerganov
a6809c6a2e examples : add null threadpool args where needed (ggml/0)
ggml-ci
2024-09-20 21:15:05 +03:00
Johannes Gäßler
5cb12f6839
CUDA: fix sum.cu compilation for CUDA < 11.7 (#9562) 2024-09-20 18:35:35 +02:00
Georgi Gerganov
d39e26741f
examples : flush log upon ctrl+c (#9559)
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2024-09-20 11:46:56 +03:00
Sigbjørn Skjæret
722ec1eb51
perplexity : do not escape input data by default (#9548) 2024-09-20 09:38:10 +03:00
Georgi Gerganov
6026da52d6
server : clean-up completed tasks from waiting list (#9531)
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2024-09-19 12:44:53 +03:00
Sigbjørn Skjæret
eca0fab44e
imatrix : disable prompt escape by default (#9543) 2024-09-19 10:58:14 +03:00
slaren
64c6af3195
ggml : fix n_threads_cur initialization with one thread (#9538)
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* ggml : fix n_threads_cur initialization with one thread

* Update ggml/src/ggml.c

---------

Co-authored-by: Max Krasnyansky <quic_maxk@quicinc.com>
2024-09-18 10:13:08 -07:00
Georgi Gerganov
0d2f22e45c
scripts : verify py deps at the start of compare (#9520) 2024-09-18 18:34:32 +03:00
Daniel Bevenius
6443ddd985
llama : use reserve/emplace_back in sampler_sample (#9534)
This commit updates the llama_sampler_sample function to use reserve and
emplace_back for the vector of llama_token_data structs.

The motivation for this change is to avoid the creation of n_vocab
default-constructed llama_token_data structs which are then
immediately overwritten.
2024-09-18 14:42:36 +03:00
Vinesh Janarthanan
8a308354f6
server : match OAI structured output response (#9527)
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2024-09-18 09:50:34 +03:00
Eric Zhang
f799155ab8
server : fix OpenSSL build (remove obsolete LOG_INFO) (#9529) 2024-09-18 09:28:20 +03:00
Neo Zhang Jianyu
faf67b3de4
[SYCL]set context default value to avoid memory issue, update guide (#9476)
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* set context default to avoid memory issue, update guide

* Update docs/backend/SYCL.md

Co-authored-by: Meng, Hengyu <hengyu.meng@intel.com>

---------

Co-authored-by: arthw <14088817+arthw@users.noreply.github.com>
Co-authored-by: Meng, Hengyu <hengyu.meng@intel.com>
2024-09-18 08:30:31 +08:00
Michael Podvitskiy
7be099fa81
llama-bench: correct argument parsing error message (#9524) 2024-09-17 22:41:38 +02:00
Bert Wagner
8b836ae731
arg : add env variable for parallel (#9513)
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* add env variable for parallel

* Update README.md with env:  LLAMA_ARG_N_PARALLEL
2024-09-17 16:35:38 +03:00
Michael Podvitskiy
8344ef58f8
llama : fix n_vocab init for 'no_vocab' case (#9511)
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* llama: fixed n_vocab for `no_vocab` models

* llama: updated error output for `llama_decode_internal` and `llama_encode_internal`

* llama: log warning if there's no vocab_size in metadata

* llama: correct vocab size for logging

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>

---------

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2024-09-17 13:18:22 +03:00
Max Krasnyansky
0226613853
threadpool : skip polling for unused threads (#9461)
* threadpool: skip polling for unused threads

Currently all threads do N polling rounds even if only 1 thread is active (n_threads_cur == 1).
This commit adds a check to skip the polling for unused threads (ith >= n_threads_cur).

n_threads_cur is now an atomic_int to explicitly tell thread sanitizer that it is written
from one thread and read from other threads (not a race conditions).

* threadpool: further simplify and improve ggml_barrier

Avoid using strict memory order while polling, yet make sure that all threads go through
full memory barrier (memory fence) on ggml_barrier entrace and exit.

* threads: add simple barrier test

This test does lots of small, parallel matmul ops where the barriers in between dominate the overhead.

* threadpool: improve thread sync for new-graphs

Using the same tricks as ggml_barrier. All the polling is done with relaxed memory order
to keep it efficient, once the new graph is detected we do full fence using read-modify-write
with strict memory order.

* threadpool: improve abort handling

Do not use threadpool->ec (exit code) to decide whether to exit the compute loop.
threadpool->ec is not atomic which makes thread-sanitizer rightfully unhappy about it.

Instead introduce atomic threadpool->abort flag used for this. This is consistent with
how we handle threadpool->stop or pause.

While at it add an explicit atomic_load for n_threads_cur for consistency.

* test-barrier: release threadpool before releasing the context

fixes use-after-free detected by gcc thread-sanitizer on x86-64
for some reason llvm sanitizer is not detecting this issue.
2024-09-17 11:19:46 +03:00
Yuri Khrustalev
503147a9f9
unicode : add <algorithm> (#9508) 2024-09-17 09:51:15 +03:00
Gabe Goodhart
0d2ec43833
llama : support IBM Granite architecture (#9412)
* feat(gguf-py): Add Granite model and params to gguf-py

Branch: GraniteLM

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat(convert_hf_to_gguf): Add registration and param setup for Granite

Branch: GraniteLM

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat(llama.cpp): Add config parsing for Granite multiplier params

Branch: GraniteLM

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat(llama.cpp): First pass at full port of granite deviations from llama

Something is still not working right since the results are mostly terrible,
but on occasion it's producing relevant results at this point, so
_something_ is working.

Branch: GraniteLM

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix(llama.cpp): Determine granite language 3b instruct by vocab size

Branch: GraniteLM

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix(convert_hf_to_gguf): Use LlamaModel as base for GraniteModel

The defaults in LlamaModel are needed for Granite as well

Branch: GraniteLM

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix(llama.cpp): Switch Granite param names to use _scale for consistency

Other scalar multipliers are called *_scale, so this provides a more
consistent naming convention.

Branch: GraniteLM

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix(convert_hf_to_gguf/gguf-py): _multiplier -> _scale

The transformers names with _multiplier will now be converted to the _scale
equivalent during conversion.

Branch: GraniteLM

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix(llama.cpp): Use separate switch clause for granite in llm_load_hparams

Branch: GraniteLM

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

---------

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
2024-09-17 09:44:58 +03:00