Commit Graph

217 Commits

Author SHA1 Message Date
slaren
280345968d
cuda : rename build flag to LLAMA_CUDA (#6299) 2024-03-26 01:16:01 +01:00
Neo Zhang Jianyu
95ad616cdd
[SYCL] fix SYCL backend build on windows is break by LOG() error (#6290)
* fix LOG() error for SYCL, enhance erro check by CI

* rollback to bash

* add newline at end of file
2024-03-25 15:52:41 +08:00
Minsoo Cheong
64e7b47c69
examples : add "retrieval" (#6193)
* add `retrieval` example

* add README

* minor fixes

* cast filepos on print

* remove use of variable sized array

* store similarities in separate vector

* print error on insufficient batch size

* fix error message printing

* assign n_batch value to n_ubatch

* fix param definitions

* define retrieval-only parameters in retrieval.cpp

* fix `--context-file` option to be provided multiple times for multiple files

* use vector for `query_emb`

* add usage description in README

* fix merge conflict

* fix usage printing

* remove seed setting

* fix lint

* increase file read buffer size

* retrieval : minor

---------

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2024-03-25 09:38:22 +02:00
Johannes Gäßler
7aed0ffe68
Fixed lookup compilation issues on Windows (#6273) 2024-03-24 14:21:17 +01:00
Minsoo Cheong
586e7bc561
sampling : deduplicated code for probability distribution access (#6240)
* sampling: remove duplicated code for probability distribution access

* free original_logits

* fix original_logits allocation

* fixes based on review @cebtenzzre

* change function name to `llama_sampling_prepare`
2024-03-24 10:54:07 +02:00
Pierrick Hymbert
f482bb2e49
common: llama_load_model_from_url split support (#6192)
* llama: llama_split_prefix fix strncpy does not include string termination
common: llama_load_model_from_url:
 - fix header name case sensitive
 - support downloading additional split in parallel
 - hide password in url

* common: EOL EOF

* common: remove redundant LLAMA_CURL_MAX_PATH_LENGTH definition

* common: change max url max length

* common: minor comment

* server: support HF URL options

* llama: llama_model_loader fix log

* common: use a constant for max url length

* common: clean up curl if file cannot be loaded in gguf

* server: tests: add split tests, and HF options params

* common: move llama_download_hide_password_in_url inside llama_download_file as a lambda

* server: tests: enable back Release test on PR

* spacing

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

* spacing

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

* spacing

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

---------

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2024-03-23 18:07:00 +01:00
Johannes Gäßler
50ccaf5eac
lookup: complement data from context with general text statistics (#5479)
* lookup: evaluation tools, use corpus/previous gens

* fixup! lookup: evaluation tools, use corpus/previous gens

* fixup! lookup: evaluation tools, use corpus/previous gens

* fixup! lookup: evaluation tools, use corpus/previous gens

* fixup! lookup: evaluation tools, use corpus/previous gens
2024-03-23 01:24:36 +01:00
Georgi Gerganov
56a00f0a2f
common : default --hf-file to --model (#6234) 2024-03-22 21:10:39 +02:00
Georgi Gerganov
80bd33bc2c
common : add HF arg helpers (#6234)
* common : add HF arg helpers

* common : remove defaults
2024-03-22 15:33:38 +02:00
Olivier Chafik
72114edf06
json-schema-to-grammar : fix order of props + non-str const/enum (#6232)
* json: ordered json in server/schema converter to respect orig order

* json: ws nits

* json: support non-string const / enums
2024-03-22 15:07:44 +02:00
Georgi Gerganov
68e210b354
server : enable continuous batching by default (#6231) 2024-03-22 13:08:28 +02:00
Georgi Gerganov
95d576b48e
metal : pad n_ctx by 32 (#6177)
* metal : require ne00 >= 128 for mat-mat kernels

ggml-ci

* llama : pad n_ctx by 32

ggml-ci
2024-03-22 09:36:03 +02:00
DAN™
fa046eafbc
Fix params underscore convert to dash. (#6203)
* Fix params underscore convert to dash.

* Update common/common.cpp

---------

Co-authored-by: slaren <slarengh@gmail.com>
2024-03-22 02:32:42 +01:00
Olivier Chafik
5b7b0ac8df
json-schema-to-grammar improvements (+ added to server) (#5978)
* json: fix arrays (disallow `[,1]`)

* json: support tuple types (`[number, string]`)

* json: support additionalProperties (`{[k: string]: [string,number][]}`)

* json: support required / optional properties

* json: add support for pattern

* json: resolve $ref (and support https schema urls)

* json: fix $ref resolution

* join: support union types (mostly for nullable types I think)

* json: support allOf + nested anyOf

* json: support any (`{}` or `{type: object}`)

* json: fix merge

* json: temp fix for escapes

* json: spaces in output and unrestricted output spaces

* json: add typings

* json:fix typo

* Create ts-type-to-grammar.sh

* json: fix _format_literal (json.dumps already escapes quotes)

* json: merge lit sequences and handle negatives

{"type": "string", "pattern": "^({\"question\": \"[^\"]+\", \"response\": \"[^\"]+\"}\\n)+$"}

* json: handle pattern repetitions

* Update json-schema-to-grammar.mjs

* Create regex-to-grammar.py

* json: extract repeated regexp patterns to subrule

* Update json-schema-to-grammar.py

* Update json-schema-to-grammar.py

* Update json-schema-to-grammar.py

* json: handle schema from pydantic Optional fields

* Update json-schema-to-grammar.py

* Update json-schema-to-grammar.py

* Update ts-type-to-grammar.sh

* Update ts-type-to-grammar.sh

* json: simplify nullable fields handling

* json: accept duplicate identical rules

* json: revert space to 1 at most

* json: reuse regexp pattern subrules

* json: handle uuid string format

* json: fix literal escapes

* json: add --allow-fetch

* json: simplify range escapes

* json: support negative ranges in patterns

* Delete commit.txt

* json: custom regex parser, adds dot support & JS-portable

* json: rm trailing spaces

* Update json-schema-to-grammar.mjs

* json: updated server & chat `( cd examples/server && ./deps.sh )`

* json: port fixes from mjs to python

* Update ts-type-to-grammar.sh

* json: support prefixItems alongside array items

* json: add date format + fix uuid

* json: add date, time, date-time formats

* json: preserve order of props from TS defs

* json: port schema converter to C++, wire in ./server

* json: nits

* Update json-schema-to-grammar.cpp

* Update json-schema-to-grammar.cpp

* Update json-schema-to-grammar.cpp

* json: fix mjs implementation + align outputs

* Update json-schema-to-grammar.mjs.hpp

* json: test C++, JS & Python versions

* json: nits + regen deps

* json: cleanup test

* json: revert from c++17 to 11

* json: nit fixes

* json: dirty include for test

* json: fix zig build

* json: pass static command to std::system in tests (fixed temp files)

* json: fix top-level $refs

* json: don't use c++20 designated initializers

* nit

* json: basic support for reserved names `{number:{number:{root:number}}}`

* Revamp test cmake to allow args (WORKING_DIRECTORY needed for JSON test)

* json: re-ran server deps.sh

* json: simplify test

* json: support mix of additional props & required/optional

* json: add tests for some expected failures

* json: fix type=const in c++, add failure expectations for non-str const&enum

* json: test (& simplify output of) empty schema

* json: check parsing in test + fix value & string refs

* json: add server tests for OAI JSON response_format

* json: test/fix top-level anyOf

* json: improve grammar parsing failures

* json: test/fix additional props corner cases

* json: fix string patterns (was missing quotes)

* json: ws nit

* json: fix json handling in server when there's no response_format

* json: catch schema conversion errors in server

* json: don't complain about unknown format type in server if unset

* json: cleaner build of test

* json: create examples/json-schema-pydantic-example.py

* json: fix date pattern

* json: move json.hpp & json-schema-to-grammar.{cpp,h} to common

* json: indent 4 spaces

* json: fix naming of top-level c++ function (+ drop unused one)

* json: avoid using namespace std

* json: fix zig build

* Update server.feature

* json: iostream -> fprintf

* json: space before & refs for consistency

* json: nits
2024-03-21 11:50:43 +00:00
Kawrakow
76aa30a263
Add ability to use Q5_0, Q5_1, and IQ4_NL for quantized K cache (#6183)
* k_cache: be able to use Q5_0

* k_cache: be able to use Q5_1 on CODA

* k_cache: be able to use Q5_0 on Metal

* k_cache: be able to use Q5_1 on Metal

* k_cache: be able to use IQ4_NL - just CUDA for now

* k_cache: be able to use IQ4_NL on Metal

* k_cache: add newly added supported types to llama-bench and CUDA supports_op

---------

Co-authored-by: Iwan Kawrakow <iwan.kawrakow@gmail.com>
2024-03-21 08:27:57 +01:00
Georgi Gerganov
b80cf3b2d1
common : disable repeat penalties by default (#6127) 2024-03-19 10:21:54 +02:00
DAN™
4c28b82529
common : print usage on '-h' and '--help' (#6145) 2024-03-19 07:59:36 +02:00
DAN™
496bc79bc2
common : tidy-up argument parsing (#6105)
* Tidy-up argument parsing.

* Missing ref.

* common : minor

* common : add static classifier

---------

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2024-03-18 10:27:44 +02:00
Pierrick Hymbert
d01b3c4c32
common: llama_load_model_from_url using --model-url (#6098)
* common: llama_load_model_from_url with libcurl dependency

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2024-03-17 19:12:37 +01:00
DAN™
15961ec04d
common : refactor nested if causing error C1061 on MSVC (#6101)
* Refactor nested if causing error C1061 on MSVC.

* Revert back and remove else's.

* Add flag to track found arguments.
2024-03-16 17:39:15 +02:00
Theia Vogel
877b4d0c62
llama : add support for control vectors (#5970)
* control vector api and implementation

* control-vectors : minor code style updates

* disable control vector when data == nullptr

use -1 for disabled range (also on init) in case we ever support controlling layer 0 (embeddings)

---------

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2024-03-15 22:43:02 +02:00
Georgi Gerganov
0fd6c1f015
embedding : print cosine similarity (#899) 2024-03-14 10:12:29 +02:00
Clint Herron
463628372d
grammar : handle missing "root" node (#6004) 2024-03-13 20:10:40 +02:00
slaren
f30ea47a87
llama : add pipeline parallelism support (#6017)
* llama : add pipeline parallelism support for batch processing with multiple CUDA GPUs

ggml-ci

* server : add -ub, --ubatch-size parameter

* fix server embedding test

* llama : fix Mamba inference for pipeline parallelism

Tested to work correctly with both `main` and `parallel` examples.

* llama : limit max batch size to n_batch

* add LLAMA_SCHED_MAX_COPIES to configure the number of input copies for pipeline parallelism
default increase to 4 (from 2)

changing this value may improve performance for some systems, but increases memory usage

* fix hip build

* fix sycl build (disable cpy_tensor_async)

* fix hip build

* llama : limit n_batch and n_ubatch to n_ctx during context creation

* llama : fix norm backend

* batched-bench : sync after decode

* swiftui : sync after decode

* ggml : allow ggml_get_rows to use multiple threads if they are available

* check n_ubatch >= n_tokens with non-casual attention

* llama : do not limit n_batch to n_ctx with non-casual attn

* server : construct batch with size of llama_n_batch

* ggml_backend_cpu_graph_compute : fix return value when alloc fails

* llama : better n_batch and n_ubatch comment

* fix merge

* small fix

* reduce default n_batch to 2048

---------

Co-authored-by: Francis Couture-Harpin <git@compilade.net>
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2024-03-13 18:54:21 +01:00
Georgi Gerganov
05b06210c9
llama : more consistent names of count variables (#5994)
* llama : more consistent names of count variables

ggml-ci

* llama : n_parallel -> n_seq_max

* common : fix param name

* examples : fix param name
2024-03-11 17:49:47 +02:00
Clint Herron
2960eae847
grammar : verify parsed state (#5950) 2024-03-10 17:17:43 +02:00
SeungWon Jeong
fb215c3832
server : normalize embeddings (#5956)
* output normalize embedding in '/v1/embeddings'

* common : reuse llama_embd_normalize

* common : better normalize impl

---------

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2024-03-09 14:27:58 +02:00
compilade
c2101a2e90
llama : support Mamba Selective State Space Models (#5328)
* mamba : begin working on support for Mamba SSM

* mamba : begin figuring out how to (ab)use the kv cache for Mamba

* mamba : recurrent inference almost works, but incoherent

* mamba : recurrent inference WORKS!!!

* convert : optionally use d_conv and d_state from config.json for Mamba

* mamba : refactor recurrent conv, resulting in 20% perf increase

It's still slower than I'd like, but I did not really optimize `ggml_exp` yet.

I also refactored `ggml_exp` to work with tensors with more than 2 dimensions.

* ggml : parallelize ggml_exp

This results in 8% faster token generation for Mamba-130M.

* mamba : simplify the conv step with a self-overlapping view

Turns out the conv_state can be made smaller by one column.
Note that this breaks existing GGUFs of Mamba,
because the key_value_length field is tied to the conv_state size.

Convolution with a self-overlapping view is cool!
And it's much simpler than what I initially thought would be necessary
to make the convolution step work with more than 1 token at a time.

Next step is to make the SSM step work on batches of tokens too,
and thus I need to figure out a way to make a parallel selective scan
which will keep the ssm_state small and won't make it bigger
by a factor of (n_layer * batch_size).

* llama : fix Mamba KV self size wrongly displaying as f16 instead of f32

Relatedly, I also tried to see if other types than f32 worked for the states,
but they don't, because of the operators used.
It's probably better anyway to keep lots of precision there,
since the states are small anyway.

* mamba : fix self-overlapping view depth stride

* mamba : handle batches of more than 1 token

This means running Mamba no longer crashes when using the default settings!
And probably also slightly faster prompt processing.
Both batched and non-batched processing yield the same output.

Previously, the state was not cleared when starting a sequence.
Next step is to make the KV cache API work as expected for Mamba models.

* ggml: add ggml_ssm_scan to help with parallel selective scan

If the selective scan was implemented without a custom operator,
there would be waaay too many nodes in the graph. For example,
for Mamba-130M, with a batch size of 512 (the default),
a naive selective scan could add at least 24*512=12288 nodes,
which is more than LLAMA_MAX_NODES (8192),
and that's only for the smallest Mamba model.
So it's much cleaner with a custom operator.
Not sure about the name, though.

* ggml : in ggml_ssm_scan, merge multiple rows in the same vec operation

This will help with performance on CPU if ggml_vec_mul_f32
and ggml_vec_add_f32 are ever optimized with SIMD.

* mamba : very basic quantization support

Mostly works, but there is currently no difference
between the variants of a k-quant (e.g. Q4_K_S and Q4_K_M are the same).
Most of the SSM-specific weights can be kept in f32 without affecting
the size that much, since they are relatively small.
(the linear projection weights are responsible for most of Mamba's size)

Too much quantization seems to make the state degrade quite fast, and
the model begins to output gibberish.
It seems to affect bigger models to a lesser extent than small models,
but I'm not sure by how much.

Experimentation will be needed to figure out which weights are more important
for the _M (and _L?) variants of k-quants for Mamba.

* convert : fix wrong name for layer norm weight of offical Mamba models

I was using Q-bert/Mamba-* models before, which have a slighlty different
naming scheme for the weights.
(they start with "model.layers" instead of "backbone.layers")

* mamba : fuse more steps of the SSM scan in the ggml_ssm_scan operator

This increases performance on CPU by around 30% for prompt processing,
and by around 20% for text generation.

However, it also makes the ggml_exp and ggml_soft_plus operators unused.
Whether or not they should be kept will be decided later.

* convert : for Mamba, also consider the "MambaLMHeadModel" arch name

It's the name of the class of the official implementation,
though they don't use it (yet) in the "architectures" field of config.json

* mamba : fix vocab size problems with official models

The perplexity was waaaay to high for models with a non-round vocab size.
Not sure why, but it needed to be fixed in the metadata.

Note that this breaks existing GGUF-converted Mamba models,
but **only if** the vocab size was not already rounded.

* ggml : remove ggml_exp and ggml_soft_plus

They did not exist anyway outside of this branch,
and since ggml_ssm_scan fused operations together, they are unused.
It's always possible to bring them back if needed.

* mamba : remove some useless comments

No code change.

* convert : fix flake8 linter errors

* mamba : apply suggestions from code review

* mamba : remove unecessary branch for row-wise ssm_state and C multiplication

It was previously done to avoid permuting when only one token is processed
at a time (like when generating text), but permuting is cheap,
and dynamically changing the compute graph is not future-proof.

* ggml : in ggml_ssm_scan, use more appropriate asserts

* ggml : rename the destination pointer in ggml_compute_forward_ssm_scan_f32

* mamba : multiple sequences, but one at a time

This is a step towards making this Mamba implementation usable
with the server example (the way the system prompt is kept when clearing
the client slots will need to be changed before this can work, though).

The KV cache size for this kind of model is tied to the maximum number
of sequences kept at any single time.
For now, this number is obtained from n_parallel (plus one,
to have an extra sequence to dedicate to the system prompt),
but there might be a better way to do this which won't also
make the main example use 2 cells even if only 1 is really used.
(for this specific case, --parallel 0 helps)

Simultaneous sequence processing will probably require changes to
ggml_ssm_scan, and possibly a new operator for the conv step.

* mamba : support llama_kv_cache_seq_cp

This (mis)uses the logic around K shifts, because tokens in a state
can't be shifted anyway, and because inp_K_shift has the right shape and type.
Using ggml_get_rows is a nice way to do copies, but copy chains can't work.
Fortunately, copy chains don't really seem to be used in the examples.

Each KV cell is dedicated to the sequence ID corresponding to its own index.

* mamba : use a state mask

It's cleaner than the previous heuristic of
checking for the pos of the first token in the batch.

inp_KQ_mask could not be re-used for this, because it has the wrong shape
and because it seems more suited to the next step of
simultaneous sequence processing (helping with the problem of
remembering which token belongs to which sequence(s)/state(s)).

* llama : replace the usage of n_ctx with kv_self.size in many places

* mamba : use n_tokens directly instead of n_tok

* mamba : in comments, properly refer to KV cells instead of slots

* mamba : reduce memory usage of ggml_ssm_scan

From 290.37 MiB to 140.68 MiB of CPU compute buffer size
with Mamba 3B with a batch size of 512.

The result tensor of ggml_ssm_scan was previously a big part
of the CPU compute buffer size. To make it smaller,
it does not contain the intermediate ssm states anymore.
Both y and the last ssm state are combined in the result tensor,
because it seems only a single tensor can be returned by an operator
with the way the graph is built.

* mamba : simultaneous sequence processing

A batch can now contain tokens from multiple sequences.

This is necessary for at least the parallel example, the server example,
and the HellaSwag test in the perplexity example.

However, for this to be useful, uses of llama_kv_cache_seq_rm/cp
will need to be changed to work on whole sequences.

* ggml : add ggml_ssm_conv as a new operator for the conv step of Mamba

This operator makes it possible to use and update the correct states
for each token of the batch in the same way as ggml_ssm_scan.
Other solutions which use existing operators would need loops which would
add too many nodes to the graph (at least the ones I thought of).

Using this operator further reduces the size of the CPU compute buffer
from 140.68 MiB to 103.20 MiB with Mamba 3B with a batch size of 512.
And (at least on CPU), it's a bit faster than before.

Note that "ggml_ssm_conv" is probably not the most appropriate name,
and it could be changed if a better one is found.

* llama : add inp_s_seq as a new input tensor

The most convenient implementation to select the correct state (for Mamba)
for each token is to directly get the correct index from a tensor.
This is why inp_s_seq is storing int32_t and not floats.

The other, less convenient way to select the correct state would be
to have inp_KQ_mask contain 1.0f for each state used by a token
and 0.0f otherwise. This complicates quickly fetching the first used
state of a token, and is also less efficient because a whole row
of the mask would always need to be read for each token.

Using indexes makes it easy to stop searching when there are
no more sequences for a token, and the first sequence assigned
is always very quickly available (it's the first element of each row).

* mamba : support llama_kv_cache_seq_cp copy chains

* mamba : support shifting and dividing the kv cache pos

* mamba : make the server and parallel examples work with whole sequences

A seq_id is dedicated to the system prompt in both cases.

* llama : make llama_kv_cache_seq_rm return whether it succeeded or not

* mamba : dedicate an input tensor for state copy indices

This is cleaner and makes it easier to adapt when/if token positions
(and by extension, inp_K_shift) are no longer integers.

* mamba : adapt perplexity, batched, and batched-bench examples

* perplexity : limit the max number of sequences

This adapts to what the loaded model can provide.

* llama : add llama_n_max_seq to get the upper limit for seq_ids

Used by the perplexity example.

* batched : pass n_parallel to the model's context params

This should have been there already, but it wasn't.

* batched-bench : reserve sequences to support Mamba

* batched-bench : fix tokens being put in wrong sequences

Generation quality isn't what's measured in there anyway,
but at least using the correct sequences avoids using non-consecutive
token positions.

* mamba : stop abusing attention metadata

This breaks existing converted-to-GGUF Mamba models,
but will allow supporting mixed architectures like MambaFormer
without needing to break Mamba models.

This will also allow changing the size of Mamba's states
without having to reconvert models in the future.
(e.g. using something else than d_conv - 1 columns for the conv_states
 will not require breaking existing converted Mamba models again)

* gguf-py : add new KV metadata key-value pairs for Mamba

* llama : add new metadata key-value pairs for Mamba

* llama : guard against divisions by zero when n_head is 0

* mamba : rename "unlimited" KV cache property to "recurrent"

* mamba : more correctly update the "used" field of the KV cache

* ggml : in ggml_ssm_scan, use a threshold for soft_plus

This is how the official Mamba implementation does it,
and it's also what torch.nn.Softplus does.

* convert : for Mamba, fallback to internal NeoX tokenizer

The resulting models are exactly the same
as if the tokenizer.json and tokenizer_config.json of GPT-NeoX were there.

* mamba : support state saving and restoring

* ggml : implicitly pass src tensors through dst for Mamba-related ops

* mamba : clarify some comments

* server : fix cache_tokens not getting correctly resized

Otherwise, when the "we have to evaluate at least 1 token" special case
was triggered, an extra token was kept in cache_tokens even if it was
removed from the KV cache.

For Mamba, this caused useless prompt reprocessing when the previous
request triggered the above case.

* convert-hf : support new metadata keys for Mamba

For the models available at
https://huggingface.co/collections/state-spaces/transformers-compatible-mamba-65e7b40ab87e5297e45ae406

* mamba : rename metadata to be more similar to transformers library

This breaks existing converted-to-GGUF models,
but the metadata names are more "standard".

* mamba : support mamba-*-hf models

These models share their token_embd.weight with their output.weight

* mamba : add missing spaces

This is purely a formatting change.

* convert-hf : omit output.weight when identical with token_embd.weight

Only for Mamba for now, but it might be relevant for other models eventually.
Most Mamba models actually share these two tensors, albeit implicitly.

* readme : add Mamba to supported models, and add recent API changes

* mamba : move state_seq and state_mask views outside layer loop

A few tensors were also missing `struct` in front of `ggml_tensor`.
2024-03-08 17:31:00 -05:00
UEXTM.com
581ed5c4fe
log : fix MSVC compile errors (#5643)
MSVC gives the following error with the existing macros:
`Error C2059 : syntax error: ','`

This patch adds `##` as a prefix to `__VA_ARGS__` to address this error.
2024-03-08 11:35:04 +02:00
Georgi Gerganov
29ae62d2ae
llama : fix embeddings (#5796)
* llama : fix embeddings

ggml-ci

* llama : do not use KV cache for non-causal models

ggml-ci

* embeddings : fix llama_batch_init arg

* llama : add pooling switch

* llama : distinguish token vs sequence embeddings

ggml-ci

* llama : assert pooling tensor

* llama : simplify causal mask condition

ggml-ci

* llama : assert input batch with pooling enabled

* readme : update API changes list
2024-03-04 22:31:20 +02:00
Dane Madsen
fe52be11e3
cmake : handle cases where git index is not found in .git (#5844)
* Update CMakeLists.txt

* Update CMakeLists.txt
2024-03-04 20:26:55 +02:00
Minsoo Cheong
6d341ab6c5
speculative : implement stochastic speculative sampling (#5625)
* (WIP) Implement stochastic speculative decoding

* sample from residual distribution on draft accept failure

* fix #5657: force greedy sampling with probs when temp is 0

* remove p_accept parameter

* fix style

* remove unused variables

* add srand() in speculative.cpp

* replace use of rand() with mt19937 sampling

* fixes based on review (@JohannesGaessler)

* fix r random generation

* randomly select next sequence to verify + fix bug in memory freeing

* fix bug in active_seqs sync

* fix uniform int distribution initialization

* remove warnings from comparison between int and size_t

* check grammar in `llama_sample_probability_distribution_impl`

* remove malloc code by utilizing vectors

* add PR link to README
2024-03-04 20:24:00 +02:00
DAN™
82f3e668ad
common : use LLAMA_DEFAULT_SEED (#5855) 2024-03-04 10:08:19 +02:00
Douglas Hanley
475df1d6cf
llama : allow for user specified embedding pooling type (#5849)
* allow for user specified pooling type

* llama : use enum types over int

---------

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2024-03-03 12:40:27 +02:00
Neo Zhang Jianyu
715641391d
Support multiple GPUs (split mode) on SYCL backend (#5806)
* suport multiple cards: split-mode - layer|row

* rm warning

* rebase with master, support tow new OPs, close feature for -sm=row, fix for unit test

* update news

* fix merge error

* update according to review comments
2024-03-02 19:49:30 +08:00
Miwa / Ensan
f49a535686
common : fix flag --logits-all to --all-logits (#5805) 2024-03-01 15:48:56 +02:00
Pierrick Hymbert
3ab8b3a92e
llama : cleanup unused mmq flags (#5772)
* cleanup unused --no-mul-mat-q,-nommq, -mmq, --mul-mat-q, mul_mat_q

* remove: mul_mat_q in compare llama bench and usage

* update llama-bench

---------

Co-authored-by: slaren <slarengh@gmail.com>
2024-03-01 13:39:06 +02:00
Georgi Gerganov
9d533a77d0
llama : fix defrag bugs + add parameter (#5735)
* llama : fix defrag bugs + enable by default

ggml-ci

* llama : add defrag_thold parameter

ggml-ci

* llama : cont

* llama : disable log message

ggml-ci

* llama : fix graph size check during defrag
2024-02-27 14:35:51 +02:00
Pierrick Hymbert
e3965cf35a
server: tests - slow inference causes timeout on the CI (#5715)
* server: tests - longer inference timeout for CI
2024-02-25 22:48:33 +01:00
Georgi Gerganov
ab336a9d5e
code : normalize enum names (#5697)
* coda : normalize enum names

ggml-ci

* code : cont

* code : cont
2024-02-25 12:09:09 +02:00
Robey Holderith
5ee99c32f5
common, server : surface min_keep as its own parameter (#5567)
* Feature - surface min_keep as its own parameter

* Updated README with min_keep param
2024-02-18 21:11:16 +02:00
Georgi Gerganov
689a091bbe
sampling : do not set min_keep to n_probs (#5564) 2024-02-18 19:38:06 +02:00
Georgi Gerganov
1dcc3fde00
common : fix ub (#5530) 2024-02-18 18:21:52 +02:00
Herman Semenov
5d3de51f97
ggml, common, examples, tests : fixed type arguments in printf (#5528) 2024-02-18 18:20:12 +02:00
Alexey Parfenov
6dcc02d244
server : add "samplers" param to control the samplers order (#5494) 2024-02-16 13:33:25 +02:00
bmwl
f486f6e1e5
ggml : add numa options (#5377)
* Added numa options to allow finer grained control as well as plumbing for a new mirror mode that will require numa.h

* Reverted Makefile

* Fixed include

* Removed sched.h from ggml.h, moved ggml_get_numa_affinity into ggml.c, removed trailing whitespace and fixed up a few inconsistent variables

* removed trailing whitespace

* Added numa options to allow finer grained control as well as plumbing for a new mirror mode that will require numa.h

* Reverting Makefile

* Fixed a number of issues with the move from BOOL to ggml_numa_strategies. Added a note about mirror mode note being implemented yet

* Removing MIRROR_MODE code for this PR

* Removing last bit of MIRROR_MODE code for this PR

* Removing unneeded branch in server.cpp example and moving get_numa_affinity and making it static

* Fixed lingering init_llama_backend() bool calls in tests and examples

* Remote enum llama_numa_strategies

* Revert bad merge with dynatemp flags

* add missing enum ggml_numa_strategies declaration and revert sync problem with master

* add missing enum ggml_numa_strategies declaration

* fixed ggml_init_numa variable

* Update ggml.h

Co-authored-by: Jared Van Bortel <cebtenzzre@gmail.com>

* Update READMEs with info about numa flags, change INTERLEAVE strategy name to DISTRIBUTE everywhere, implement the improved distribution strategy from @rankaiyx, fix a spelling mistake and un-merge some bad merges

* split numa init out from llama_backend_init and created llama_numa_init. Updated all code paths and samples

* Fix up some boolean vs enum comparisons

* Added #ifdefs for non-Linux OS that don't have cpu_set_t datatype

* Update ggml.h

Align enum values

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

* Update ggml.c

Remove whitespace

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

* Update ggml.c

align paremeters

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

* Update examples/server/server.cpp

remove whitespace and align brace

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

* Update common/common.cpp

Remove whitespace and align brace

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

* unified ggml_numa_strategy enum and fixed text alignment in server.cpp example

* Update ggml.c

simplified return for platforms without NUMA support

Co-authored-by: Jared Van Bortel <cebtenzzre@gmail.com>

* removed redundant else from cli argument processing of --numa

* whitespace

---------

Co-authored-by: root <root@nenya.lothlorien.ca>
Co-authored-by: Jared Van Bortel <cebtenzzre@gmail.com>
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
Co-authored-by: Jared Van Bortel <jared@nomic.ai>
2024-02-16 11:31:07 +02:00
Alexey Parfenov
a803333a4e
common : use enums for sampler types (#5418)
* common: use enums for sampler types

* Apply suggestions from code review

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

* minor : spaces

---------

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2024-02-11 15:43:31 +02:00
Georgi Gerganov
139b62a839
common : fix compile warning 2024-02-11 15:33:43 +02:00
snadampal
a07d0fee1f
ggml : add mmla kernels for quantized GEMM (#4966)
* ggml: aarch64: implement smmla kernel for q8_0_q8_0 quantized gemm

armv8.2-a and above supports MMLA instructions that have higher
throughput than DOT. this commit adds mmla kernel for
q8_0_q8_0 gemm. The feature is enabled if the platform supports
"__ARM_FEATURE_MATMUL_INT8"

On AWS Graviton3 processors this kernel resulted up to 1.5x
improvement for prompt evaluation throughput compared to the
default sdot kernel.

* ggml: aarch64: implement smmla kernel for q4_0_q8_0 quantized gemm

armv8.2-a and above supports MMLA instructions that have higher
throughput than DOT. this commit adds mmla kernel for
q4_0_q8_0 gemm. The feature is enabled if the platform supports
"__ARM_FEATURE_MATMUL_INT8"

On AWS Graviton3 processors this kernel resulted up to 1.5x
improvement for prompt evaluation throughput compared to the
default sdot kernel.

* ggml: aarch64: implement smmla kernel for q4_1_q8_1 quantized gemm

armv8.2-a and above supports MMLA instructions that have higher
throughput than DOT. this commit adds mmla kernel for
q4_1_q8_1 gemm. The feature is enabled if the platform supports
"__ARM_FEATURE_MATMUL_INT8"

On AWS Graviton3 processors this kernel resulted up to 1.5x
improvement for prompt evaluation throughput compared to the
default sdot kernel.

* ggml: update unit tests for the new vec_dot interface

* llama.cpp: add MATMUL_INT8 capability to system_info
2024-02-11 15:22:33 +02:00
Johannes Gäßler
26d4efd11e
sampling: fix top_k <= 0 (#5388)
* sampling: fix top_k <= 0

* Update llama.cpp

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

---------

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2024-02-08 09:46:30 +01:00
0cc4m
ee1628bdfe
Basic Vulkan Multi-GPU implementation (#5321)
* Initial Vulkan multi-gpu implementation

Move most global variables into backend context

* Add names to backend device functions

* Add further missing cleanup code

* Reduce code duplication in tensor split layer assignment

* generalize LLAMA_SPLIT_LAYER for all backends, do not expose device count and memory in llama.h

* Only do device info print in the beginning and initialize one backend for cpu assist

Add missing cleanup code

* Rework backend memory management to make sure devices and buffers get properly allocated and freed

* Rename cpu assist free function

---------

Co-authored-by: slaren <slarengh@gmail.com>
2024-02-07 07:54:50 +01:00
l3utterfly
e6f8177532
common : add dynamic temperature parameters to main example cli (#5295)
* added dynamic temp params in main

* added help text
2024-02-05 10:00:47 +02:00
Michael Klimenko
52bb63c708
refactor : switch to emplace_back to avoid extra object (#5291) 2024-02-03 13:23:37 +02:00
Jared Van Bortel
1ec3332ade
YaRN : store rope scaling type as int32_t in memory (#5285)
* YaRN : store rope scaling type as int32_t in memory

* llama : store mapped names as const char *
2024-02-03 13:22:06 +02:00
Georgi Gerganov
5cb04dbc16
llama : remove LLAMA_MAX_DEVICES and LLAMA_SUPPORTS_GPU_OFFLOAD (#5240)
* llama : remove LLAMA_MAX_DEVICES from llama.h

ggml-ci

* Update llama.cpp

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

* server : remove LLAMA_MAX_DEVICES

ggml-ci

* llama : remove LLAMA_SUPPORTS_GPU_OFFLOAD

ggml-ci

* train : remove LLAMA_SUPPORTS_GPU_OFFLOAD

* readme : add deprecation notice

* readme : change deprecation notice to "remove" and fix url

* llama : remove gpu includes from llama.h

ggml-ci

---------

Co-authored-by: slaren <slarengh@gmail.com>
2024-01-31 17:30:17 +02:00
0cc4m
f8e9140cb4
Vulkan Fixes (#5223)
* Fix Vulkan F16 models

* Fix Vulkan context shift crash

* Add Vulkan to common.cpp dump_non_result_info_yaml function

* Fix bug in Vulkan CPY op

* Fix small matrix multiplication errors in AMD GPUs on Windows or with amdvlk

Co-authored-by: Engininja2 <139037756+Engininja2@users.noreply.github.com>

---------

Co-authored-by: Engininja2 <139037756+Engininja2@users.noreply.github.com>
2024-01-31 11:44:19 +01:00
Jared Van Bortel
e8dc55d006
kompute : llama-bench support and ggml_cpu_has_kompute() (#5226) 2024-01-30 19:04:37 -05:00
Abhilash Majumder
0f648573dd
ggml : add unified SYCL backend for Intel GPUs (#2690)
* first update for migration

* update init_cublas

* add debug functio, commit all help code

* step 1

* step 2

* step3 add fp16, slower 31->28

* add GGML_LIST_DEVICE function

* step 5 format device and print

* step6, enhance error check, remove CUDA macro, enhance device id to fix none-zero id issue

* support main device is non-zero

* step7 add debug for code path, rm log

* step 8, rename all macro & func from cuda by sycl

* fix error of select non-zero device, format device list

* ren ggml-sycl.hpp -> ggml-sycl.h

* clear CMAKE to rm unused lib and options

* correct queue: rm dtct:get_queue

* add print tensor function to debug

* fix error: wrong result in 658746bb26702e50f2c59c0e4ada8e9da6010481

* summary dpct definition in one header file to replace folder:dpct

* refactor device log

* mv dpct definition from folder dpct to ggml-sycl.h

* update readme, refactor build script

* fix build with sycl

* set nthread=1 when sycl, increase performance

* add run script, comment debug code

* add ls-sycl-device tool

* add ls-sycl-device, rm unused files

* rm rear space

* dos2unix

* Update README_sycl.md

* fix return type

* remove sycl version from include path

* restore rm code to fix hang issue

* add syc and link for sycl readme

* rm original sycl code before refactor

* fix code err

* add know issue for pvc hang issue

* enable SYCL_F16 support

* align pr4766

* check for sycl blas, better performance

* cleanup 1

* remove extra endif

* add build&run script, clean CMakefile, update guide by review comments

* rename macro to intel hardware

* editor config format

* format fixes

* format fixes

* editor format fix

* Remove unused headers

* skip build sycl tool for other code path

* replace tab by space

* fix blas matmul function

* fix mac build

* restore hip dependency

* fix conflict

* ren as review comments

* mv internal function to .cpp file

* export funciton print_sycl_devices(), mv class dpct definition to source file

* update CI/action for sycl code, fix CI error of repeat/dup

* fix action ID format issue

* rm unused strategy

* enable llama_f16 in ci

* fix conflict

* fix build break on MacOS, due to CI of MacOS depend on external ggml, instead of internal ggml

* fix ci cases for unsupported data type

* revert unrelated changed in cuda cmake
remove useless nommq
fix typo of GGML_USE_CLBLAS_SYCL

* revert hip cmake changes

* fix indent

* add prefix in func name

* revert no mmq

* rm cpu blas duplicate

* fix no_new_line

* fix src1->type==F16 bug.

* pass batch offset for F16 src1

* fix batch error

* fix wrong code

* revert sycl checking in test-sampling

* pass void as arguments of ggml_backend_sycl_print_sycl_devices

* remove extra blank line in test-sampling

* revert setting n_threads in sycl

* implement std::isinf for icpx with fast math.

* Update ci/run.sh

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

* Update examples/sycl/run-llama2.sh

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

* Update examples/sycl/run-llama2.sh

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

* Update CMakeLists.txt

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

* Update CMakeLists.txt

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

* Update CMakeLists.txt

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

* Update CMakeLists.txt

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

* add copyright and MIT license declare

* update the cmd example

---------

Co-authored-by: jianyuzh <jianyu.zhang@intel.com>
Co-authored-by: luoyu-intel <yu.luo@intel.com>
Co-authored-by: Meng, Hengyu <hengyu.meng@intel.com>
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2024-01-28 17:56:23 +02:00
Michael Klimenko
35a2ee9143
Remove unused data and add fixes (#5154)
* Remove unused data and add fixes

* Add missing file

* Address review comments

* Replace the scope of vq allocation
2024-01-27 15:25:55 +01:00
l3utterfly
5eaf9964fc
llama : dynamic temperature sampling (#4972)
* implemented dynamic temperature sampling from koboldcpp

* removed trailing whitespace

* removed unused temp parameter in llama_sample_entropy

* exposed exponent_val in dynamic temp sampler

* added debug check for printf statements

* use nullptr in llama_sample_softmax call during llama_sample_entropy

this avoids counting the time taken stats twice

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

* return earlier if there is only 1 candiate (i.e. max_entropy == 0)

* reformat 't' case in llama_sample_queue

Co-authored-by: Jared Van Bortel <cebtenzzre@gmail.com>

* check for one or zero candidates case in llama_sample_entropy

---------

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
Co-authored-by: Jared Van Bortel <cebtenzzre@gmail.com>
2024-01-25 22:06:22 +02:00
Georgi Gerganov
89758723c7
minor : clean-up some warnings and style (#5094)
* minor : clean-up some warnings and style

ggml-ci

* ggml : add comment
2024-01-23 14:12:57 +02:00
Kawrakow
6f9939d119
KL-divergence (#5076)
* kl-divergence: be able to save all logits to a file

* Add ability to compute KL-divergence

---------

Co-authored-by: Iwan Kawrakow <iwan.kawrakow@gmail.com>
2024-01-22 16:10:14 +02:00
Kawrakow
7dcbe39d36
Add ability to evauate multiple choice tasks (#5047)
* TruthfulQA: 1st attempt, does not look like it is working

The same implementation can be used for HellaSwag as well,
so I converted a HellaSwag validation dataset to the binary
format used here and tested with that. The score is only
around 50, so something is not quite right.

* TruthfulQA: works but the result is bad

I know it works because if I convert the HellaSwag validation
data to the binary format used in the truthful_qa_score() function
I get the exact same result as from the hellaswag_score() function.
But I guess, the questions are tricky and the way I have done
the combination of question + answer is very likely not the best.
The TruthfulQA validation dataset contains 817 questions, with
random chance result around 19%. With this version I get
29.1% for Mistral-7B and 55.2% for Mistral-7B-Instruct-v0.2.
The HF leader board results for these two models are
42.2% and 68.3%, respectively.

* TruthfulQA: fix random sample

* TruthfulQA: prepare tasks in parallel for large test datasets

* Rename truthful_qa to multiple_choice

* Make MSVC happy

I had forgotten that MSVC does not make constexpr's available
inside a lambda.

---------

Co-authored-by: Iwan Kawrakow <iwan.kawrakow@gmail.com>
2024-01-21 14:42:44 +02:00
Kawrakow
682986a08e
Add Winogrande evaluation (#5015)
* winogrande: simple implementation

It doesn't look like it is working - why?
For Mistral-7B it is barely better than
random chance (score ~60% for 1267 tasks), while I see
Mistral-7B scoring 78.4% on the HF leader board.
1-sigma statistical uncertainty for 1267 tasks is ~1.4,
so no way the difference is due to statistics.

* winogrande: somewhat better

Score for Mistrali7-B is now 68.9 on the validation set of
winogrande_debiased. Still far from the reported 78.4, but
better than what I had before.

* winogrande: improving

Mistral-7B score is now 73.56.
Still not quite 78.4 but getting there.
We are also getting a lower score on HellaSwag
compared to HF leader board, so I'm not expecting
we will get up to 78.4 anyway.

It looks like it is better to skip the choice word(s)
when evaluating the average log-likelihood. This kind of
makes sense because a more common word (in Winogrande this is
often a name) will have a higher probability without knowing
about the follow up context, and this will skew the log-likelihood
towards the more common word. We can only do this if the
choice words are not last in the sentence.

It also looks like it is better to skip the punctuation at the
end of the sentence, provided the choice words are not last.

* winogrande: add dataset instructions

---------

Co-authored-by: Iwan Kawrakow <iwan.kawrakow@gmail.com>
2024-01-18 13:46:27 +02:00
David Renshaw
f46c0c1b0e
llama : fix copy/paste error in llama_sampling_params comment (#4994) 2024-01-17 09:17:50 +02:00
stduhpf
e0324285a5
speculative : threading options (#4959)
* speculative: expose draft threading

* fix usage format

* accept -td and -tbd args

* speculative: revert default behavior when -td is unspecified

* fix trailing whitespace
2024-01-16 13:04:32 +02:00
David Friehs
4483396751
llama : apply classifier-free guidance to logits directly (#4951) 2024-01-15 15:06:52 +02:00
Yann Follet
722d33f34e
main : add parameter --no-display-prompt (#4541)
* add the parameter : --no-display-prompt , combine with --log-disable it will display only the generated tokens

* remove empty line

---------

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2024-01-13 18:09:08 +02:00
slaren
e7e4df031b
llama : ggml-backend integration (#4766)
* llama : ggml-backend integration

* ggml-backend : add names to buffers

* fix unmap after loading

* batched-bench : add tensor_split param

* llama : check for null tensor_split

* ggml-backend : increase GGML_MAX_BACKENDS

* improve graph splitting, partial fix for --no-kv-offload

* cuda : add ggml-backend split buffer support

* cuda : do not create buffer types for devices that don't exist (fixes usage without CUDA devices available)

* ggml : fix null backend dereference (#4807)

* ggml : fix null backend dereference

* ggml : also check ggml_backend_is_cpu

* test-backend-ops : check buffer allocation failures

* llama : add cparam (split_mode) and command line argument (--split-mode, -sm) to configure the split mode (none, layer or row)

* ggml : fix mul_mat_id work size

* llama : rewrite session kv load/set without graphs

* minor

* llama : only initialize used backends, free backends on context free

* llama : abort ctx if cuda backend init fails

* llama : rewrite lora with ggml-backend and compute on CPU

ggml-ci

* llama : only map to a backend buffer the region of the file mapping containing the tensors used in the buffer

* opencl : add ggml-backend buffer type

* cuda : only use batched_cublas with batched mat muls (fixes fp16 tg perf)

* llama : on Metal, by default offload the full model

ggml-ci

* metal : page align the data ptr (#4854)

* Apply suggestions from code review

Co-authored-by: Johannes Gäßler <johannesg@5d6.de>

* cuda : fix split buffer free

* address review comments

* llama-bench : add split-mode parameter

* fix whitespace

* opencl : fix double initialization

* server : add --split-mode parameter

* use async copy and compute to improve multi-gpu performance

ggml-ci

* use async memcpys to copy the graph outputs to the CPU

* fix opencl

* use a host buffer for the cpu compute buffer for faster copies to the gpu

---------

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
Co-authored-by: Johannes Gäßler <johannesg@5d6.de>
2024-01-12 20:07:38 +01:00
howlger
4315a94366
common : streamline the formatting of help (#4890)
* common : streamline the formatting of help

- Separate alternative parameters by a comma

- Do not indent `--version` differently

* Update common/common.cpp

---------

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2024-01-12 13:05:32 +02:00
Georgi Gerganov
f445c0e68c
llama : fix llm_build_k_shift to use correct n_rot (#4889)
* llama : fix llm_build_k_shift to use correct n_rot

ggml-ci

* llama : always use hparams.n_rot for ggml_rope_custom

ggml-ci

* convert : fix persimmon conversion to write correct n_rot
2024-01-12 13:01:56 +02:00
Georgi Gerganov
7edefbd79c
main : better name for variable n_print (#4874) 2024-01-11 22:46:26 +02:00
Georgi Gerganov
3ca63b4538
main : disable token count by default (#4874) 2024-01-11 22:43:05 +02:00
pudepiedj
43f76bf1c3
main : print total token count and tokens consumed so far (#4874)
* Token count changes

* Add show token count

* Updating before PR

* Two requested changes

* Move param def posn
2024-01-11 18:14:52 +02:00
howlger
1fc2f265ff
common : fix the short form of --grp-attn-w, not -gat (#4825)
See https://github.com/ggerganov/llama.cpp/blob/master/common/common.cpp#L230C53-L230C57
2024-01-08 21:05:53 +02:00
Georgi Gerganov
52531fdff8
main : add self-extend support (#4815)
* examples : add passkey test

* passkey : better prints

* passkey : select pass key pos from CLI

* passkey : simplify n_past logic

* llama : "self-extend"-like context extension

* passkey : add comment

* main : add Self-Extend support

* llama : add comment about llama_kv_cache_seq_div
2024-01-08 11:18:32 +02:00
Daniel Bevenius
cb1e2818e0
train : fix typo in overlapping-samples help msg (#4758)
This commit fixes a typo in the help message for the
--overlapping-samples option.

Signed-off-by: Daniel Bevenius <daniel.bevenius@gmail.com>
2024-01-03 19:53:40 +02:00
automaticcat
24a447e20a
ggml : add ggml_cpu_has_avx_vnni() (#4589)
* feat: add avx_vnni based on intel documents

* ggml: add avx vnni based on intel document

* llama: add avx vnni information display

* docs: add more details about using oneMKL and oneAPI for intel processors

* docs: add more details about using oneMKL and oneAPI for intel processors

* docs: add more details about using oneMKL and oneAPI for intel processors

* docs: add more details about using oneMKL and oneAPI for intel processors

* docs: add more details about using oneMKL and oneAPI for intel processors

* Update ggml.c

Fix indentation upgate

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

---------

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2023-12-30 10:07:48 +02:00
Cuong Trinh Manh
97bbca6e85
cmake : fix ld warning duplicate libraries libllama.a (#4671)
* fix "ld: warning: ignoring duplicate libraries: '../libllama.a'"

* fix warning in example.
2023-12-29 16:39:15 +02:00
Alexey Parfenov
6123979952
server : allow to specify custom prompt for penalty calculation (#3727) 2023-12-23 11:31:49 +02:00
kalomaze
b9ec82d262
grammar : check the full vocab only if necessary (opt) (#4306)
* Check the full vocab for grammar only if necessary

* Fix missing logit restoration step (?)

Does this matter, actually?

* Fix whitespace / formatting

* Adjust comment

* Didn't mean to push test gbnf

* Split sampling into the helper function (?)

And also revert the changes made to the header

* common : fix final newline

---------

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2023-12-23 11:27:07 +02:00
LeonEricsson
7082d24cec
lookup : add prompt lookup decoding example (#4484)
* initial commit, going through initializations

* main loop finished, starting to debug

* BUG: generates gibberish/repeating tokens after a while

* kv_cache management

* Added colors to distinguish drafted tokens (--color). Updated README

* lookup : fix token positions in the draft batch

* lookup : use n_draft from CLI params

* lookup : final touches

---------

Co-authored-by: Leon Ericsson <leon.ericsson@icloud.com>
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2023-12-22 18:05:56 +02:00
Jared Van Bortel
8fe03ffdda
common : remove incorrect --model-draft default (#4568) 2023-12-21 19:55:34 +02:00
slaren
cafcd4f895
ggml : remove n_dims from ggml_tensor (#4469)
ggml-ci
2023-12-14 16:52:08 +01:00
Siwen Yu
9fb13f9584
common : add --version option to show build info in CLI (#4433) 2023-12-13 14:50:14 +02:00
Richard Kiss
9494d7c477
english : use typos to fix comments and logs (#4354) 2023-12-12 11:53:36 +02:00
Georgi Gerganov
bcc0eb4591
llama : per-layer KV cache + quantum K cache (#4309)
* per-layer KV

* remove unnecessary copies

* less code duplication, offload k and v separately

* llama : offload KV cache per-layer

* llama : offload K shift tensors

* llama : offload for rest of the model arches

* llama : enable offload debug temporarily

* llama : keep the KV related layers on the device

* llama : remove mirrors, perform Device -> Host when partial offload

* common : add command-line arg to disable KV cache offloading

* llama : update session save/load

* llama : support quantum K cache (#4312)

* llama : support quantum K cache (wip)

* metal : add F32 -> Q8_0 copy kernel

* cuda : add F32 -> Q8_0 copy kernel

ggml-ci

* cuda : use mmv kernel for quantum cache ops

* llama : pass KV cache type through API

* llama : fix build

ggml-ci

* metal : add F32 -> Q4_0 copy kernel

* metal : add F32 -> Q4_1 copy kernel

* cuda : wip

* cuda : add F32 -> Q4_0 and F32 -> Q4_1 copy kernels

* llama-bench : support type_k/type_v

* metal : use mm kernel only for quantum KV cache

* cuda : add comment

* llama : remove memory_f16 and kv_f16 flags

---------

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

* readme : add API change notice

---------

Co-authored-by: slaren <slarengh@gmail.com>
2023-12-07 13:03:17 +02:00
Georgi Gerganov
caa9249217
common : fix compile warning 2023-12-06 10:41:03 +02:00
Kerfuffle
5aa365d88f
llama : allow overriding GGUF metadata when loading model (#4092)
* feat: Allow overriding GGUF metadata when loading model

* Fix the one time GCC is stricter than clang about something

* Step1

* Refactor... basically everything!

* Nuke obsolete GetArrayLen struct

* simplify std::string specialization

* Various cleanups

Add informational output when overrides are applied

Warn user when an override with the wrong type is specified

* Fix broken logic for parsing bool KV overrides
Fix issue where overrides didn't apply when key missing in GGUF metadata
Resolve merge changes

* llama : rearrange model params

* Update new GET_KEY call

Add note that metadata KV overrides aren't reflected in initial metadata KV info dump

---------

Co-authored-by: cebtenzzre <cebtenzzre@gmail.com>
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2023-12-05 19:19:18 +02:00
MaggotHATE
52c8bc3cf3
sampling : custom samplers order (#4285)
* Samplers sequence order w parameter

* Cleaned commented code

* Fixed formatting

* Rewrote with unordered_map

* Revert and rewrite, too many problems and safeguards would be needed

* Fixed code style

* Code style fixes according to review

* More readable samplers input string, fixed help

* Style fix in sampler_queue

* Formatting fixes

* Fixing whitespaces
2023-12-05 12:05:51 +02:00
Ikko Eltociear Ashimine
4fa44e84ad
grammar-parser : fix typo (#4318)
preceeding -> preceding
2023-12-04 09:57:35 +02:00
Jared Van Bortel
15f5d96037
build : fix build info generation and cleanup Makefile (#3920)
* cmake : fix joining of REAL_GIT_DIR

* fix includes with help from include-what-you-use

* make : remove unneeded deps and add test-rope target

* fix C includes in C++ source files

* Revert "fix includes with help from include-what-you-use"

This reverts commit 635e9fadfd.
2023-12-01 00:23:08 +02:00
bandoti
b38a16dfcf
cmake : fix issue with version info not getting baked into LlamaConfig.cmake (#3970)
* Split CPP generation from build-info query

* Remove blank lines

* Add BUILD_SHARED_LIBS option
2023-11-27 21:25:42 +02:00
Georgi Gerganov
6b0a7420d0
llama : KV cache view API + better KV cache management (#4170)
* llama : keep track of used KV cells + better KV cache management

* llama : zero KV cache used upon clear

ggml-ci

* llama : allow exporting a view of the KV cache (#4180)

* Allow exporting a view of the KV cache

* Allow dumping the sequences per cell in common

* Track max contiguous cells value and position as well

* Fix max contiguous empty cells index calculation

Make dump functions deal with lengths or sequences counts > 10 better

* Fix off by one error in dump_kv_cache_view

* Add doc comments for KV cache view functions

Eliminate cell sequence struct; use llama_seq_id directly

Minor cleanups

* common : add -dkvc arg for enabling kv cache dumps

---------

Co-authored-by: Kerfuffle <44031344+KerfuffleV2@users.noreply.github.com>
2023-11-23 19:07:56 +02:00
Seb C
881800d1f0
main : Add ChatML functionality to main example (#4046)
Co-authored-by: Sebastian Cramond <sebby37@users.noreply.github.com>
2023-11-20 14:56:59 +01:00
kchro3
262005ad9d
common : comma should be semicolon (#4137) 2023-11-19 18:52:57 +02:00
Jannis Schönleber
9e87ef60e1
common : improve yaml log escaping (#4080)
* logging: improve escaping in yaml output

* logging: include review feedback
2023-11-17 17:24:07 +02:00
Jiří Podivín
ba4cf5c0bf
train : move number of gpu layers argument parsing to common/train.cpp (#4074)
- introduces help entry for the argument
 - cuts '--gpu-layers' form in order to simplify usage and documentation.

Signed-off-by: Jiri Podivin <jpodivin@gmail.com>
Co-authored-by: Jiri Podivin <jpodivin@redhat.com>
2023-11-17 17:19:16 +02:00
Kerfuffle
91f6499393
Respect tokenizer.ggml.add_bos_token value when tokenizing (#4040)
* gguf-py: gguf-dump: Respect --no-tensor flag in JSON mode.

* Respect add_bos_token GGUF metadata value

* gguf-py: Try to fix SpecialVocab giving up too easily for the Nth time
2023-11-16 19:14:37 -07:00
Georgi Gerganov
4760e7cc0b
sync : ggml (backend v2) (#3912)
* sync : ggml (backend v2) (wip)

* sync : migrate examples and llama.cpp to dynamic graphs (wip)

* sync : update tests + fix max op params to 64

ggml-ci

* sync : ggml-cuda

ggml-ci

* llama : fix save/load state context size

ggml-ci

* sync : try to fix build on tvOS

* sync : pass custom graph sizes in training examples

* sync : update graph copies to new ggml API

* sync : update sync-ggml.sh with new files

* scripts : fix header in sync script

* train : fix context size calculations

* llama : increase inference graph size up to 4096 nodes

* train : allocate grads for backward graphs

* train : allocate grads for gb_tmp
2023-11-13 14:16:23 +02:00