* redo Settings modal UI
* add python code interpreter
* fix auto scroll
* build
* fix overflow for long output lines
* bring back sticky copy button
* adapt layout on mobile view
* fix multiple lines output and color scheme
* handle python exception
* better state management
* add webworker
* add headers
* format code
* speed up by loading pyodide on page load
* (small tweak) add small animation to make it feels like claude
After the barrier in last iteration is executed, still the loop termination
condition will be executed. However main thread can destroy the cgraph object
and its nodes already, then another thread will access it, but the thing is already gone.
Also trouble can happen when n_nodes == 0 or abort is called, but I'm not sure if the
prior situation is possible.
Last syncronization should be done after the loop to ensure the cgraph/cplan won't be
accessed after the main thread exits from the function.
Silently insert U+FFFD(s) (Unicode replacement character) instead until the
next valid codepoint can be found.
This fixes `llama_tokenize` throwing an exception across the C API boundary
or libllama's module boundary (the caller's runtime might be incompatible!)
Returing a proper error code might be desirable, however the signature
of `llama_tokenize` doesn't allow it as all return values already have
existing meaning.
* Update llama.cpp
For display progress dots in terminal.
Without this it didn't display dots progress during loading model from file.
* Update llama.cpp
removed trailing spaces
The C API in llama.h claims users can implement `llama_sampler_i` to
create custom `llama_sampler`. The sampler chain takes ownership and
calls `llama_sampler_free` on them. However, `llama_sampler_free` is
hard-coded to use `delete`. This is undefined behavior if the object
wasn't also allocated via `new` from libllama's C++ runtime. Callers
in C and C-compatible languages do not use C++'s `new` operator. C++
callers may not be sharing the same heap as libllama.
* common : add default embeddings presets
This commit adds default embeddings presets for the following models:
- bge-small-en-v1.5
- e5-small-v2
- gte-small
These can be used with llama-embedding and llama-server.
For example, with llama-embedding:
```console
./build/bin/llama-embedding --embd-gte-small-default -p "Hello, how are you?"
```
And with llama-server:
```console
./build/bin/llama-server --embd-gte-small-default
```
And the embeddings endpoint can then be called with a POST request:
```console
curl --request POST \
--url http://localhost:8080/embeddings \
--header "Content-Type: application/json" \
--data '{"input": "Hello, how are you?"}'
```
I'm not sure if these are the most common embedding models but hopefully
this can be a good starting point for discussion and further
improvements.
Refs: https://github.com/ggerganov/llama.cpp/issues/10932
* ggml : optimize convert f32<->f16 for loongarch_asx
* ggml : optimize loongarch_asx extend i16,i8,u8 to i32,i16
* ggml : Fix warnings when run cpu CI locally on LoongArch
Add bounds checking in `rpc_server::copy_tensor` to prevent out-of-bounds writes
+ Check if `(uint8_t *)dst->data + ggml_nbytes(src)` remains within the destination buffer’s allocated region.
* init version
* fix auto scroll
* bring back copy btn
* bring back thought process
* add lint and format check on CI
* remove lang from html tag
* allow multiple generations at the same time
* lint and format combined
* fix unused var
* improve MarkdownDisplay
* fix more latex
* fix code block cannot be selected while generating
Autopen (https://github.com/blackhole89/autopen) is a graphical text editor that uses llama.cpp to tokenize the buffer on the fly, score the buffer, visualise token logits and allow you to switch back and forth between different possible completions at any point. It hopefully meets the criteria for inclusion, as the dependency on llama.cpp is stated prominently.
* Added quantization for visual projector
* Added README
* Fixed the clip quantize implementation in the file
* Fixed the gcc warning regarding minor linting
* Removed trailing whitespace
List devices in the same order as they appear when evaluating the model
and splitting tensors across devices, i.e. RPC devices come first in the
list.
ref #11435
[This crate](https://github.com/ShelbyJenkins/llm_client) has been in a usable state for quite awhile, so I figured now is fair to add it.
It installs from crates.io, and automatically downloads the llama.cpp repo and builds it for the target platform - with the goal being the easiest user experience possible.
It also integrates model presets and choosing the largest quant given the target's available VRAM. So a user just has to specify one of the presets (I manually add the most popular models), and it will download from hugging face.
So, it's like a Rust Ollama, but it's not really for chatting. It makes heavy use of llama.cpp's grammar system to do structured output for decision making and control flow tasks.
This makes git as a dependency optional, and is useful in the case where
ggml is built not from git, but from a tarball, or a distribution source
package.
This conditional also affects GGML_BUILD_COMMIT. Nothing seems to be
using it, though, so there doesn't seem much value factor it out, or
even require it.
This commit removes the CPPHTTPLIB_NO_EXCEPTIONS define from the server
code.
The motivation for this is that when using a debug build the server
would crash when an exception was throws and terminate the server
process, as it was unhandled. When CPPHTTPLIB_NO_EXCEPTIONS is set
cpp_httplib will not call the exception handler, which would normally
return a 500 error to the client. This caused tests to fail when using
a debug build.
Fixes: https://github.com/ggerganov/llama.cpp/issues/11613
* Fix Shift+Enter handling
`exact` on the Enter handler means the message is not sent when Shift+Enter is pressed anyway
* build index.html.gz
---------
Co-authored-by: Xuan Son Nguyen <son@huggingface.co>
* CUDA: use mma PTX instructions for FlashAttention
* __shfl_sync workaround for movmatrix
* add __shfl_sync to HIP
Co-authored-by: Diego Devesa <slarengh@gmail.com>
* initial porting of previous LLG patch
* update for new APIs
* build: integrate llguidance as an external project
* use '%llguidance' as marker to enable llg lark syntax
* add some docs
* clarify docs
* code style fixes
* remove llguidance.h from .gitignore
* fix tests when llg is enabled
* pass vocab not model to llama_sampler_init_llg()
* copy test-grammar-integration.cpp to test-llguidance.cpp
* clang fmt
* fix ref-count bug
* build and run test
* gbnf -> lark syntax
* conditionally include llguidance test based on LLAMA_LLGUIDANCE flag
* rename llguidance test file to test-grammar-llguidance.cpp
* add gh action for llg test
* align tests with LLG grammar syntax and JSON Schema spec
* llama_tokenizer() in fact requires valid utf8
* update llg
* format file
* add $LLGUIDANCE_LOG_LEVEL support
* fix whitespace
* fix warning
* include <cmath> for INFINITY
* add final newline
* fail llama_sampler_init_llg() at runtime
* Link gbnf_to_lark.py script; fix links; refer to llg docs for lexemes
* simplify #includes
* improve doc string for LLAMA_LLGUIDANCE
* typo in merge
* bump llguidance to 0.6.12
* add glm edge chat model
* use config partial_rotary_factor as rope ratio
* support for glm edge model
* vision model support
* remove debug info
* fix format
* llava.cpp trailing whitespace
* remove unused AutoTokenizer
* Update src/llama.cpp for not contain <|end|> or </s>
Co-authored-by: Xuan Son Nguyen <thichthat@gmail.com>
* add edge template
* fix chat template
* fix confict
* fix confict
* fix ci err
* fix format err
* fix template err
* 9b hf chat support
* format
* format clip.cpp
* fix format
* Apply suggestions from code review
* Apply suggestions from code review
* Update examples/llava/clip.cpp
* fix format
* minor : style
---------
Co-authored-by: liyuhang <yuhang.li@zhipuai.cn>
Co-authored-by: piDack <pcdack@hotmail.co>
Co-authored-by: Xuan Son Nguyen <thichthat@gmail.com>
Co-authored-by: liyuhang <yuhang.li@aminer.cn>
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* An empty tool_call_id is better than none!
* sync: minja (tool call name optional https://github.com/google/minja/pull/36)
* Force-disable parallel_tool_calls if template doesn't support it
* More debug logs
* Llama 3.x tools: accept / trigger on more varied spaced outputs
* Fix empty content for functionary v3.2 tool call
* Add proper tool call docs to server README
* readme: function calling *is* supported now
* Apply suggestions from code review
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
---------
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
The va_copy man page states that va_end must be called to revert
whatever the copy did. For some implementaions, not calling va_end
has no consequences. For others it could leak memory.
This commit updates the help text for the metrics `requests_processing`
and `requests_deferred` to be more grammatically correct.
Currently the returned metrics look like this:
```console
\# HELP llamacpp:requests_processing Number of request processing.
\# TYPE llamacpp:requests_processing gauge
llamacpp:requests_processing 0
\# HELP llamacpp:requests_deferred Number of request deferred.
\# TYPE llamacpp:requests_deferred gauge
llamacpp:requests_deferred 0
```
With this commit, the metrics will look like this:
```console
\# HELP llamacpp:requests_processing Number of requests processing.
\# TYPE llamacpp:requests_processing gauge
llamacpp:requests_processing 0
\# HELP llamacpp:requests_deferred Number of requests deferred.
\# TYPE llamacpp:requests_deferred gauge
llamacpp:requests_deferred 0
```
This is also consistent with the description of the metrics in the
server examples [README.md](https://github.com/ggerganov/llama.cpp/tree/master/examples/server#get-metrics-prometheus-compatible-metrics-exporter).
---------
Co-authored-by: Xuan Son Nguyen <thichthat@gmail.com>
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
Co-authored-by: Xuan Son Nguyen <son@huggingface.co>
This commit replaces the two usages of `std::bind` in favor of lambdas for
the callback functions for `callback_new_task` and
`callback_update_slots`.
The motivation for this changes is consistency with the rest of the code
in server.cpp (lambdas are used for all other callbacks/handlers). Also
lambdas are more readable (perhaps this is subjective) but also they are
recommended over `std::bind` in modern C++.
Ref: https://github.com/LithoCoders/dailycpp/blob/master/EffectiveModernC%2B%2B/chapter6/Item34_Prefer_lambdas_to_std::bind.md
This commit updates some of JSON snippets in README.md file and
removes the `json` language tag from the code blocks.
The motivation for this changes is that if there is invalid json in a
code snippet these are highlighted in red which can make it somewhat
difficult to read and can be a little distracting.
* add /apply-template endpoint to server
* remove unnecessary line
* add /apply-template documentation
* return only "prompt" field in /apply-template
* use suggested idea instead of my overly verbose way
* vulkan: initial support for IQ3_S
* vulkan: initial support for IQ3_XXS
* vulkan: initial support for IQ2_XXS
* vulkan: initial support for IQ2_XS
* vulkan: optimize Q3_K by removing branches
* vulkan: implement dequantize variants for coopmat2
* vulkan: initial support for IQ2_S
* vulkan: vertically realign code
* port failing dequant callbacks from mul_mm
* Fix array length mismatches
* vulkan: avoid using workgroup size before it is referenced
* tests: increase timeout for Vulkan llvmpipe backend
---------
Co-authored-by: Jeff Bolz <jbolz@nvidia.com>
* server : update auto gen files comments
This commit updates the 'auto generated files' comments in server.cpp
and removes `deps.sh` from the comment.
The motivation for this change is that `deps.sh` was removed in
Commit 91c36c269b ("server : (web ui)
Various improvements, now use vite as bundler (#10599)").
* squash! server : update auto gen files comments [no ci]
Move comments about file generation to README.md.
* squash! server : update auto gen files comments [no ci]
Remove the comments in server.cpp that mention that information
can be found in the README.md file.
People search for ollama models using the web ui, this change
allows one to copy the url from the browser and for it to be
compatible with llama-run.
Signed-off-by: Eric Curtin <ecurtin@redhat.com>
* Add option to not print stack on abort
Add option/envvar to disable stack printing on abort.
Also link some unittests with Threads to fix link errors on
ubuntu/g++11.
* Update ggml/src/ggml.c
---------
Co-authored-by: Diego Devesa <slarengh@gmail.com>
This commit enables the `--no-warmup` option for the llama-embeddings.
The motivation for this change is to allow the user to disable the
warmup when running the the program.
The test_completion_stream_with_openai_library() function is actually with stream=False by default, and test_completion_with_openai_library() with stream=True
loops with bounds not known at compile time can not be unrolled.
when ncols_template == 0, the bounds of the loop are not constexpr, thus llvm cant unroll the loops here.
This disables the workaround on rocblas fixed versions (>=4.0.0) to eliminate the runtime cost and unnecessary VRAM allocation of loading all tensile objects.
Implemented ggml_sycl_op_soft_max() F16 src1(mask) support for which a pragma deprecation warning was added during #5021.
To do this, had to decouple it from ggml_sycl_op_flatten which always considered src1 to be of fp32 type(many OP functions are dependent on it).
* SYCL: SOFTMAX F16 mask support and other fixes
* test-backend-ops: Add F16 mask test cases
The HTTP client in llama-run only prints an error in case the download of
a resource failed. If the model name in the CLI parameter list is missing,
this causes the application to crash.
In order to prevent this, a check for the required model parameter has been
added and errors for resource downloads get propagated to the caller.
Signed-off-by: Michael Engel <mengel@redhat.com>
* impl::load change map bpe_ranks to onordered map for reduce time of impl::load on 30%
* llama_model_loader::init_mapping - replace new llama_mmap to std::make_unique<llama_mmap> for clean code & reduce (/2) time of running init_mappings
* Update src/llama-vocab.cpp
---------
Co-authored-by: lexasub <empty@empty.ru>
Co-authored-by: Diego Devesa <slarengh@gmail.com>
This fixes segmentation fault error when running tests when no metal
devices are available (for example, when not linked with Core Graphics
framework or otherwise).
* release : pack /lib and /include in the packages
* cmake : put libs in /bin
* TMP : push artifacts
* Revert "TMP : push artifacts"
This reverts commit 4decf2c4df.
* ci : fix HIP cmake compiler options to be on first line
* ci : restore the original HIP commands
* ci : change ubuntu build from latest to 20.04
* ci : try to fix macos build rpaths
* ci : remove obsolete MacOS build
* TMP : push artifacts
* ci : change back to ubuntu latest
* ci : macos set build rpath to "@loader_path"
* ci : fix typo
* ci : change ubuntu package to 22.04
* Revert "TMP : push artifacts"
This reverts commit 537b09e70f.
* webui : put DeepSeek R1 CoT in a collapsible <details> element
* webui: refactor split
* webui: don't use regex to split cot and response
* webui: format+qol
* webui: no loading icon if the model isn't generating
* ui fix, add configs
* add jsdoc types
* only filter </think> for assistant msg
* build
* update build
---------
Co-authored-by: Xuan Son Nguyen <son@huggingface.co>
Now that we have batched mat-vec mul Vulkan shaders for up to n==8,
these tests weren't actually exercising the mat-mat mul path. Test
n==9 as well. Also, change to use all_types.
With robustbufferaccess disabled, this shader was showing OOB stores. There
is a bounds check in the code, but the workgrouop dimensions were reversed vs
CUDA and it was running the wrong number of threads. So fix the workgroup
dimensions and disable robustness for this pipeline.
mul mat and flash attention shaders were loading f32 types directly into
A/B matrices, which happens to work but is technically invalid usage.
For FA, we can load it as an Accumulator matrix and convert and this
is not in the inner loop and is cheap enough. For mul mat, it's more
efficient to do this conversion in a separate pass and have the input(s)
be f16.
coopmat2 requires SPIR-V 1.6 (related using to LocalSizeId). LocalSizeId
requires maintenance4 be enabled, and SPIR-V 1.6 requires Vulkan 1.3.
* Implement host pool for matrix_info
Creating a new memory pool on the host to store memory location for
matrix_info needed to launch gemm_batch from oneMKL/oneMath.
Removing complex support in gemm_batch since it is not used in llama.cpp
* Remove unnecessary headers and cast
* Reorder member variable to avoid warning on initialization
* Formatting
* Remove unused variable
* Address PR review feedback - remove warning
---------
Signed-off-by: nscipione <nicolo.scipione@codeplay.com>
This is a fork of linenoise that is C++17 compatible. I intend on
adding it to llama-run so we can do things like traverse prompt
history via the up and down arrows:
https://github.com/ericcurtin/linenoise.cpp
Signed-off-by: Eric Curtin <ecurtin@redhat.com>
* Added the ability to use guide tokens for OuteTTS, greatly improving TTS recitation accuracy over long input sequences.
* applied linting suggestions, updated to latest llama_vocab changes, added a safety check, added newline to guide token start
Add code similar to mul_mm_cm2 to force alignment of strides, to avoid
a performance regression.
Add noncontiguous FA tests in test-backend-ops.
Fixes#11268.
* vulkan: support copy from f32 to q4_0/q4_1/q5_0/q5_1/q8_0/iq4_nl
Shaders are based on cpy.cu.
* vulkan: support copy from q4_0/q4_1/q5_0/q5_1/q8_0/iq4_nl to f32
* ggml: copy q->f32 assumes some contiguity in the destination
* Add SVE support for q4_K_q8_K
* Update ggml/src/ggml-cpu/ggml-cpu-quants.c
change to use K_SCALE_SIZE
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
---------
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* q6_k scale caching
* 16 bit unpack
* q4_k test (slow)
* revert it
* q3_k
* q2_k
* little stuff
* try precalculating products of a and q2_k scales
* Revert "try precalculating products of a and q2_k scales"
This reverts commit 65110b81f23f66331a50c6e889a7c1ab9470a86b.
* unpack should be u16, add vim swap to gitignore (about time)
* better q4_k scales
* q5_k
* better q6_k with separate paths for all threads and partial threads in use, plus some more optimizations
* q2_k better dequant
* q3_k optimizations
* q3_k use hmask simd from cpu avx version
* make the caches happy
* q3_k separate out calculation
* q2_k separate out
* little stuff
* use calc_superblock everywhere
* q2_k optimize scale calculation
* more barriers
* fix: ggml: fix vulkan-shaders-gen build
The vulkan-shaders-gen target was not being built correctly
in case of cross-compilation.
Other outputs need to be built for the cross compile target,
but vulkan-shaders-gen needs to be built for the host.
* refactor: ggml: Improve vulkan-shaders-gen toolchain setup
- Add GGML_SHADERS_GEN_TOOLCHAIN CMake option.
- Auto-detect host toolchain if not set.
* refactor: ggml: Improve vulkan-shaders-gen toolchain setup
Use configure_file to generate host_toolchain.cmake from template
* fix: ggml: Fix compile error
Fix compile error not finding vulkan-shaders-gen
* fix: vulkan-shaders-gen build and path handling
Fix build issues with vulkan-shaders-gen:
- Add target dependency for correct build order
- Use CMAKE_HOST_SYSTEM_NAME for executable suffix
- Fix MSVC output directory in host toolchain
- Normalize path handling for cross-compilation
* fix: improve host compiler detection in vulkan shader build
Improve host compiler detection for vulkan shader generation:
- Add NO_CMAKE_FIND_ROOT_PATH to all compiler searches
- Consolidate compiler detection logic
- Fix Windows-specific MSVC detection
- Ensure correct compiler search in cross-compilation
* refactor: Simplify CMake function for detecting host compiler
Simplified the CMake function to improve the process of detecting the host compiler.
* fix: Remove unnecessary Vulkan library linkage in CMakeLists.txt
Since `vulkan-shader-gen.cpp` only requires the `glslc` executable
and not the Vulkan headers or libraries, CMakeLists.txt needs to
be corrected.
(See: ecc93d0558)
* refactor: Rename host_toolchain.cmake.in
- Rename host_toolchain.cmake.in to cmake/host-toolchain.cmake.in
* refactor: GGML_VULKAN_SHADERS_GEN_TOOLCHAIN
Rename the macro GGML_SHADERS_GEN_TOOLCHAIN to GGML_VULKAN_SHADERS_GEN_TOOLCHAIN
This commit contains a suggestion for adding the missing embd_to_audio
function from tts.cpp to tts-outetts.py. This introduces a depencency
numpy which I was not sure if that is acceptable or not (only PyTorch
was mentioned in referened PR).
Also the README has been updated with instructions to run the example
with llama-server and the python script.
Refs: https://github.com/ggerganov/llama.cpp/pull/10784#issuecomment-2548377734
* cli : auto activate conversation mode if chat template is detected
* add warn on bad template
* update readme (writing with the help of chatgpt)
* update readme (2)
* do not activate -cnv for non-instruct models
* Refactor: Moves cuda graph executable update step to separate function.
* Refactor: Moves cuda graph update check to separate function.
* Refactor: Moves cuda graph maintenance (update or adjusting copy parameters) to separate function for improved readability.
* Fix: Adds missing reference to maintain_cuda_graph() definition.
* Refactor: Improves structure and abstractions by moving CUDA graph evaluation and capture to its own function.
* Refactor: Moves node graph checks and copy ops into individual function for improved readability.
* Refactor: Removes code permanently excluded from compilation to increase readability.
* Style: Adds missing newline
* Style: Consolidates several neighboring '#ifdef USE_CUDA_GRAPH' into a single one
* Refactor: Makes 'cuda_graph_update_required' a local variable
* remove double lines between functions
---------
Co-authored-by: slaren <slarengh@gmail.com>
* common : support tag-based hf_repo like on ollama
* fix build
* various fixes
* small fixes
* fix style
* fix windows build?
* move common_get_hf_file to common.cpp
* fix complain with noreturn
This commit removes the 'd' from the log message in llama-vocab.cpp
when logging a bad special token.
The motivation for this is that currently the output can look something
like the following:
```console
load: bad special token:
'tokenizer.ggml.image_token_id' = 128256d, using default id -1
```
Build fails when using HIP and GGML_BACKEND_DL:
```
/usr/bin/ld: ../ggml/src/libggml.so: undefined reference to `ggml_backend_cuda_reg'
collect2: error: ld returned 1 exit status
```
This patch fixes this.
* examples : add README.md to tts example [no ci]
* squash! examples : add README.md to tts example [no ci]
Fix heading to be consistent with other examples, and add a quickstart
section to README.md.
* squash! examples : add README.md to tts example [no ci]
Fix spelling mistake.
* SYCL: refactor ggml_sycl_compute_forward
* SYCL: add back GGML_USED(dst) to ggml_sycl_cpy
* SYCL: add function name to noop debug
* SYCL: Some device info print refactoring and add details of XMX availability
Since NVIDIA does not release CUDA for in-maintenance versions of Fedora, the process of setting up the CUDA toolkit on Fedora has become quite involved. This guide should help mere mortals install CUDA for development in a Fedora 39 toolbox environment, without affecting the host system.
* server : add tooltips to settings and themes btn
This commit adds tooltips to the settings and themes buttons in the
webui. The tooltip will be displayed below the actual buttons when
hovered over.
The motivation for this change is to clarify the purpose of the themes
button.
* squash! server : add tooltips to settings and themes btn
This commit adds a tooltip to the '...' button when a chat has been
started. The tooltip is "Chat options" which think could be a good
description as the dropdown contains options to delete or download the
current chat.
* rm tooltip for 3 dots button
---------
Co-authored-by: Xuan Son Nguyen <son@huggingface.co>
* Moved scripts dir and fixed pyproject.toml
* updated readme
* fixed README urls
* bump pypi gguf to v0.14.0
* retrigger ci
* empty commit - trigger ci
The main motivation for this change is it was not handing
ctrl-c/ctrl-d correctly. Modify `read_user_input` to handle EOF,
"/bye" command, and empty input cases. Introduce `get_user_input`
function to manage user input loop and handle different return
cases.
Signed-off-by: Eric Curtin <ecurtin@redhat.com>
* (wip) support mergekit-extracted lora
* support mergekit-extract-lora
* use lora->get_scale
* correct comment
* correct norm name & condition
* add some hints
This change upstreams llamafile's cpu matrix
multiplication kernels for ppc64le using MMA
builtins for quantised int8 datatype.
This change results in 10% - 70% improvement
in total speed(ie all tokens/total time), across
various batch sizes.
The patch is tested with Meta-Lllama-3-8B,
Mistral-7B, Llama-2-7B-chat-hf models on a
IBM POWER10 machine.
Signed-off-by: Amrita H S <amritahs@linux.vnet.ibm.com>
* Disable GL_KHR_cooperative_matrix Vulkan extension if not available.
* Perform Vulkan extensions checks in a more sensible order
* Remove unnecessary #ifdef directive
* GGUF: C++ refactor, backend support, misc fixes
remove ggml_tensor.backend
update CODEOWNERS [no ci]
remove gguf_get_data from API
revise GGUF API data types
* SYCL: Use get_multi_ptr instead of deprecated get_pointer in wkv6
* Revert "SYCL: Use get_multi_ptr instead of deprecated get_pointer in wkv6"
This reverts commit f62dc45f31.
* Reland: Use get_multi_ptr instead of deprecated get_pointer in wkv6
This commit renames the `batch` parameter to `ubatch` in the
`llama_kv_cache_find_slot`, `llm_build_inp_embd`, and
`llm_build_mamba` functions.
The motivation for this is that this should have been done as part of
Commit 19d900a756 ("llama : rename batch
to ubatch (#9950)") but for some reason I missed these functions in
that commit and only noticed them now (sorry).
* convert : extend DEEPSEEK2 model architecture to support DeepseekV3ForCausalLM by adding EXPERT_WEIGHTS_NORM and EXPERT_GATING_FUNC model parameters and FFN_EXP_PROBS_B tensor type
* vocab : add DeepSeek V3 pre-tokenizer regexes
* unicode : handle ACCENT_MARK and SYMBOL categories in regex
* llama : add DeepSeek V3 chat template, handle new model parameters and tensor types
---------
Co-authored-by: Stanisław Szymczyk <sszymczy@gmail.com>
This commit attempts to improve the log message for the inputs of the
splits in the sched_print_assignments function.
The motivation for this change is that currently even if there are no
inputs a colon is displayed at the end of the line, which can make it a
little confusing when reading the output as it could be interpreted as
the line below are inputs when they are in fact nodes. With this change
the colon will only be printed if there actually are inputs.
* server/bench:
- support openAI streaming standard output with [DONE]\n\n
- export k6 raw results in csv
- fix too many tcp idle connection in tcp_wait
- add metric time to emit first token
* server/bench:
- fix when prometheus not started
- wait for server to be ready before starting bench
In common/common.cpp:
* Convert usage of stat() function call to check if file exists to standard library function std::filesystem::exists (error unable to match to correct function signature)
* Additional conditions to check if PATH_MAX is already defined in WIN32 environment (warning it is already defined in MSYS2)
In examples/run/run.cpp:
* Add io.h header inclusion (error cannot find function _get_osfhandle)
* Change initialisers for OVERLAPPED to empty struct (warning about uninitialised members)
* Add initialiser for hFile (warning it may be uninitialised)
* Add cast for curl_off_t percentage value to long int in generate_progress_prefix function (warning that curl_off_t is long long int)
In ggml/src/ggml-opencl/ggml-opencl.cpp:
* Initialise certain declared cl_mem variables to nullptr for greater safety (warning about B_d variable possibly used unassigned)
Make the mul_mat_vec shaders support N>1 (as a spec constant, NUM_COLS) where
the batch_strides are overloaded to hold the row strides. Put the loads from the
B matrix in the innermost loop because it should cache better.
Share some code for reducing the result values to memory in mul_mat_vec_base.
* tests: Add im2col perf tests
* vulkan: optimize im2col, more elements per thread
* vulkan: increase small tile size for NV_coopmat2
* vulkan: change im2col to 512 elements per workgroup
Warning types fixed (observed under MSYS2 GCC 14.2.0):
* format '%ld' expects argument of type 'long int', but argument has type 'size_t'
* llama.cpp/ggml/src/ggml-vulkan/vulkan-shaders/vulkan-shaders-gen.cpp:81:46: warning: missing initializer for member '_STARTUPINFOA::lpDesktop' [-Wmissing-field-initializers] (emitted for all struct field except first)
* more perfo with llamafile tinyblas on x86_64.
- add bf16 suport
- change dispache strategie (thanks:
https://github.com/ikawrakow/ik_llama.cpp/pull/71 )
- reduce memory bandwidth
simple tinyblas dispache and more cache freindly
* tinyblas dynamic dispaching
* sgemm: add M blocs.
* - git 2.47 use short id of len 9.
- show-progress is not part of GNU Wget2
* remove not stable test
This commit updates the `examples/run/README.md` file to include a new
option for setting the temperature and updates the `run.cpp` file to
parse this option.
Signed-off-by: Eric Curtin <ecurtin@redhat.com>
* Add Falcon3 model support
* Add fix for adding bos to added special tokens
* Add comment explaining the logic behind the if statement
* Add a log message to better track the when the following line of code is triggered
* Update log to only print when input and output characters are different
* Fix handling pre-normalized tokens
* Refactoring
Change the code to do 16b loads when possible and extract the appropriate
component late, so the code is effectively decoding a pair of elements and
then selecting one. This can allow more commoning to happen in the compiler
when neighboring elements are loaded.
* Migrate to tensor->buffer for checking backend buffer type: 1
* SYCL: common.cpp try to migrate away from tensor->backend
* SYCL: fix assertions and add proper comments
* SYCL: remove extra space
* SYCL: Add back static to ggml_backend_buffer_is_sycl_split function
* SYCL: Add pragma directive to suppress warning spam
* SYCL: Integrate debug logs with GGML_LOG and other fixes
* Revert "SYCL: Integrate debug logs with GGML_LOG and other fixes"
This reverts commit 2607b7de0f.
Let's keep the current SYCL specific logging mechanism for now
* SYCL: Use GGML_SYCL_DEBUG after reverting
* SYCL: reg_get_proc_address func, update to the current func signature
* SYCL: Refactor SYCL buffer checks in ggml_sycl_cpy_tensor_2d
* convert : use GPT2 vocab for Phi-4 model
* convert : use null value of sliding_window to distinguish Phi-4 from other PHI3-based models
* llama : do not use sliding window attention mask for Phi-4 model
---------
Co-authored-by: Stanisław Szymczyk <sszymczy@gmail.com>
Set default width to whatever the terminal is. Also fixed a small bug around
default n_gpu_layers value.
Signed-off-by: Eric Curtin <ecurtin@redhat.com>
* server: avoid overwriting Authorization header
If no API key is set, leave the Authorization header as is. It may be
used by another part of the Web stack, such as an authenticating proxy.
Fixes https://github.com/ggerganov/llama.cpp/issues/10854
* rebuild
---------
Co-authored-by: Xuan Son Nguyen <son@huggingface.co>
* server : add "tokens" output
ggml-ci
* server : output embeddings for all tokens when pooling = none
ggml-ci
* server : update readme [no ci]
* server : fix spacing [no ci]
Co-authored-by: Xuan Son Nguyen <thichthat@gmail.com>
* server : be explicit about the pooling type in the tests
ggml-ci
* server : update /embeddings and /v1/embeddings endpoints
ggml-ci
* server : do not normalize embeddings when there is no pooling
ggml-ci
* server : update readme
ggml-ci
* server : fixes
* tests : update server tests
ggml-ci
* server : update readme [no ci]
* server : remove rebase artifact
---------
Co-authored-by: Xuan Son Nguyen <thichthat@gmail.com>
* server : add "tokens" output
ggml-ci
* server : update readme
ggml-ci
* server : return tokens ids only if requested
ggml-ci
* tests : improve "tokens" type check
Co-authored-by: Xuan Son Nguyen <thichthat@gmail.com>
* server : remove "tokens" from the OAI endpoint
ggml-ci
---------
Co-authored-by: Xuan Son Nguyen <thichthat@gmail.com>
Related to #10524 / be0e350c references to hipBLAS have been removed
across the repository. This fixes the link from the repositories
`README.md`.
Signed-off-by: Brian 'redbeard' Harrington <redbeard@dead-city.org>
This commit removes the return statement from ggml_gallocr_allocate_node
function.
The motivation behind this change is to make the code more readable and
consistent.
* ggml : add check for grad_accs
This commit adds a check for grad_accs in ggml_graph_get_grad and
ggml_graph_get_grad_acc functions. This is necessary to avoid segfaults
when grad_accs is not initialized.
The motivation for this change is that I find it nice to be able to
print out a computation graph using ggml_graph_print but this function
segfaults when grad_accs is not initialized:
```console
(gdb) p g1
$2 = (ggml_cgraph *) 0x7ffff66004b0
(gdb) p *g1
$3 = {size = 2048, n_nodes = 1, n_leafs = 2, nodes = 0x7ffff6600500,
grads = 0x0, grad_accs = 0x0, leafs = 0x7ffff6604500,
visited_hash_set = {size = 4099, used = 0x7ffff6610518,
keys = 0x7ffff6608500}, order = GGML_CGRAPH_EVAL_ORDER_LEFT_TO_RIGHT}
(gdb) p ggml_graph_print(g1)
=== GRAPH ===
n_nodes = 1
Program received signal SIGSEGV, Segmentation fault.
0x0000555555579775 in ggml_graph_get_grad
(cgraph=0x7ffff66004b0,node=0x7ffff6600340)
at /ggml/ggml/src/ggml.c:5990
5990 return igrad != GGML_HASHSET_FULL &&
ggml_bitset_get(cgraph->visited_hash_set.used, igrad) ?
cgraph->grads[igrad] : NULL;
```
* squash! ggml : add check for grad_accs
Fix the check in ggml_graph_get_grad. The check was incorrectly using
cgraph->grad_accs instead of cgraph->grads.
* ensure mul mat shaders work on systems with subgroup size less than 32
more fixes
add test
* only s_warptile_mmq needs to be run with 32 threads or more
* sampling : refactor + optimize penalties sampler
ggml-ci
* common : apply ignore_eos as logit bias
ggml-ci
* batched : remove penalties sampler
* params : allow penalty_last_n == -1 to be equal to context size
ggml-ci
* common : by default, move the penalties at the end of the sampling chain
ggml-ci
* common : ignore all EOG tokens
Co-authored-by: Diego Devesa <slarengh@gmail.com>
* common : move back the penalties at the front of the sampling chain
ggml-ci
* readme : restore hint about --ignore-eos flag [no ci]
* llama : minor
ggml-ci
* webui : update
---------
Co-authored-by: Diego Devesa <slarengh@gmail.com>
* Add deepseek v1 arch & gigachat template
* improve template code
* add readme
* delete comments
* remove comment
* fix format
* lint llama.cpp
* fix order of deepseek and deepseek2, move gigachat temlate to the end of func
* fix order of deepseek and deepseek2 in constants; mark shared exp as deepseek arch need
* remove comments
* move deepseek above deepseek2
* change placement of gigachat chat template
* Update server JSON response.
* Add unit test to check `has_new_line` JSON response
* Remove `has_new_line` unit test changes.
* Address code review comment: type check for `has_new_line` in unit test
* [cl][adreno] Add Adreno GPU support
Add new OpenCL backend to support Adreno GPUs
---------
Co-authored-by: Skyler Szot <quic_sszot@quicinc.com>
Co-authored-by: Shangqing Gu <quic_shawngu@quicinc.com>
Co-authored-by: Alexander Angus <quic_aangus@quicinc.com>
Co-authored-by: Hongqiang Wang <quic_wangh@quicinc.com>
Co-authored-by: Max Krasnyansky <quic_maxk@quicinc.com>
* [cl][ci] Add workflow for CL
* [cl][adreno] Fix memory leak for non SMALL_ALLOC path
* opencl: integrate backend dyn.load interface and fix compiler and format warnings
* opencl: remove small-alloc support and fix build errors for non-opencl platforms
* opencl: fixed merge conflict (MUSA added twice in cmake)
* opencl-ci: use RUNNER_TEMP instead of github.workspace
* opencl: fix embed tool invocation with python3
* opencl: CI workflow fixes
* opencl: Clean up small-alloc in CMake files
* opencl: cleanup ggml-opencl2 header file
* opencl: use ulong for offsets and strides in ADD kernel
* opencl: use cl_ulong for all offsets
* opencl: use cl_ulong for sizes and strides
* opencl: use `GGML_LOG_xxx` instead of `fprintf(stderr, ...)`
* opencl: rename backend `opencl2` -> `opencl`
* opencl: rename kernel files `ggml-opencl2` -> `ggml-opencl`
* opencl: make OpenCL required, remove redundant lib and inc directories
* `ggml-base`, `..` and `.` are added by `ggml_add_backend_library`
* opencl: rename backend - funcs, structs, etc `opencl2` -> `opencl`
* opencl: remove copyright marker since main license already covers
* opencl: replace some more OPENCL2 leftovers
* opencl: remove limits on `tensor_extra`
* opencl: use pools for `tensor_extra`
* opencl: fix compiler warnings with GCC and Clang
Still getting the warning about clCreateCmdQueue being obsolete.
Will fix that separately.
* opencl: fail gracefully if opencl devices are not available
Also for unsupported GPUs.
* opencl: fix MSVC builds (string length error)
* opencl: check for various requirements, allow deprecated API
* opencl: update log message for unsupported GPUs
---------
Co-authored-by: Skyler Szot <quic_sszot@quicinc.com>
Co-authored-by: Shangqing Gu <quic_shawngu@quicinc.com>
Co-authored-by: Alexander Angus <quic_aangus@quicinc.com>
Co-authored-by: Hongqiang Wang <quic_wangh@quicinc.com>
Co-authored-by: Max Krasnyansky <quic_maxk@quicinc.com>
* Fix crash caused by ggml_backend_load_all when launching on AndroidActivity.
Details:
Calling ggml_backend_load_all during initialization in the AndroidActivity project leads to a crash with the error:
terminating with uncaught exception of type std::__ndk1::__fs::filesystem::filesystem_error: filesystem error: in directory_iterator::directory_iterator(...): Permission denied [./].
This issue occurs because AndroidActivity restricts file access due to sandboxing.
Reproduction:
In the example folder, the LlamaAndroid project can reproduce the crash by calling ggml_backend_load_all first in Java_android_llama_cpp_LLamaAndroid_backend_1init.
* Update ggml/src/ggml-backend-reg.cpp
---------
Co-authored-by: Diego Devesa <slarengh@gmail.com>
* double the number of rows per workgroup
* Update ggml-vulkan.cpp
* Vulkan: Add VK_EXT_subgroup_size_control support to ensure full subgroups for coopmats
* only increase the number of rows for amd and subgroup size 64
* fix missing NUM_ROWS for mul_mat_vec_iq4_nl_f16_f32, untested
* use subgroup min and max to check for gcn (requires https://github.com/ggerganov/llama.cpp/pull/10721)
* manual merge ggml-vulkan.cpp
* set min and max subgroup size in any case
* Also double the number of rows for Intel GPUs
* Try to reduce some unused and typecast warnings
* Reduce compiler warnings step 2
* add a newline at the end of the file
* Initialize nreduce as size_t
* [SYCL] Remove pragma directives from mmq.cpp
* SYCL: mmq add condition to prevent blocks_per_tile_x_row variable from becoming 0
* SYCL softmax: Initialize nreduce as size_t
* ggml-sycl.cpp: fix some trailing whitespaces
* SYCL: remove the unused variables instead of commenting it out
* SYCL poo2d kernel: set NAN for invalid pooling op
* SYCL gemm.hpp: remove pragma directives
* SYCL gemm.hpp: use const cast to properly support dnnl::memory
* SYCL: wkv6 remove a comment
* SYCL: clean comments step 2
* SYCL: clean comments and variables step 3
* SYCL: Use GGML_UNUSED for unused variables
* SYCL: remove extra empty lines and a comment
* Remove TODO
* cleanup spaces
* add a stdout for unsupported op
* use sycl printf over fprintf
* remove prints for CI
* SYCL ggml-sycl: pool2D use sycl::nan and remove if-else block
---------
Co-authored-by: Abhilash Majumder <30946547+abhilash1910@users.noreply.github.com>
* faster uncontiguous concat
* Use a lambda to avoid code duplication
Co-authored-by: Diego Devesa <slarengh@gmail.com>
* Update ggml/src/ggml-cuda/concat.cu
* add constexpr and static assert
---------
Co-authored-by: Diego Devesa <slarengh@gmail.com>
* Vulkan: Add VK_EXT_subgroup_size_control support to ensure full subgroups for coopmats
* Fix subgroup size control extension support check
Add accf32 and accf16 checks for coopmats
* Also disable coopmats on amdvlk
* get rid of completion.js
* extract chat bubble to a component
* add tok/s info
* sync
* fix BASE_URL
* only extract timings when it's enabled
* fix auto scroll
* bug-fix: snprintf prints NULL in place of the last character
We need to give snprintf enough space to print the last character and the null character, thus we allocate one extra byte and then ignore it when converting to std::string.
* add comment about extra null-term byte requirement
* feat: load all backends from a user-provided search path
* fix: Windows search path
* refactor: rename `ggml_backend_load_all_in_search_path` to `ggml_backend_load_all_from_path`
* refactor: rename `search_path` to `dir_path`
* fix: change `NULL` to `nullptr`
Co-authored-by: Diego Devesa <slarengh@gmail.com>
* fix: change `NULL` to `nullptr`
---------
Co-authored-by: Diego Devesa <slarengh@gmail.com>
Vulkan doesn't mandate a specific rounding mode, but the shader_float_controls
feature allows rounding mode to be requested if the implementation supports it.
* Renames NVIDIA GPU-architecture flags to avoid name clashes with WinAPI. (e.g. CC_PASCAL, GPU architecture or WinAPI pascal compiler flag?)
* Reverts erroneous rename in SYCL-code.
* Renames GGML_CUDA_MIN_CC_DP4A to GGML_CUDA_CC_DP4A.
* Renames the rest of the compute capability macros for consistency.
There are some bugs in the 1.3.296 SDK, so disable this. It isn't strictly
necessary anyway.
Add missing dependency on vulkan-shaders-gen, so shaders get recompiled when it
changes.
Fix coopmat support reporting when glslc doesn't support NV_coopmat2.
* Update cmakepreset.json to use clang with ninja by default
* Update cmakepreset.json to add clang and ninja based configs
* Updates to build.md file
* Make updates to rename preset targets
* Update with .cmake file
* Remove additional whitespaces
* Add .cmake file for x64-windows-llvm
* Update docs/build.md
* Update docs/build.md
---------
Co-authored-by: Max Krasnyansky <max.krasnyansky@gmail.com>
* llama : use cmake for swift build
* swift : <> -> ""
* ci : remove make
* ci : disable ios build
* Revert "swift : <> -> """
This reverts commit d39ffd9556.
* ci : try fix ios build
* ci : cont
* ci : cont
---------
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* server : (refactor) no more json in server_task input
* add test for slots endpoint
* add tests for /props and /slots
* remove task inf_type
* fix CI by adding safe_json_to_str
* add "model_path" to /props
* update readme
* server : various fixes
ggml-ci
* server : show curent seed in slot_params
ggml-ci
* fix /slots endpoint
* Update examples/server/server.cpp
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* server : reflect endpoint response changes in the readme
ggml-ci
---------
Co-authored-by: Xuan Son Nguyen <son@huggingface.co>
Co-authored-by: Xuan Son Nguyen <thichthat@gmail.com>
* rename ggml-cpu-aarch64.c to .cpp
* reformat extra cpu backend.
- clean Q4_0_N_M and IQ4_0_N_M
- remove from "file" tensor type
- allow only with dynamic repack
- extract cpu extra bufts and convert to C++
- hbm
- "aarch64"
- more generic use of extra buffer
- generalise extra_supports_op
- new API for "cpu-accel":
- amx
- aarch64
* clang-format
* Clean Q4_0_N_M ref
Enable restrict on C++
* add op GGML_OP_MUL_MAT_ID for Q4_0_N_M with runtime repack
* added/corrected control on tensor size for Q4 repacking.
* Update ggml/src/ggml-cpu/ggml-cpu-aarch64.cpp
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* Update ggml/src/ggml-cpu/ggml-cpu-aarch64.cpp
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* add debug logs on repacks.
---------
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* Vulkan: Implement VK_KHR_cooperative_matrix support in the matrix matrix multiplication shader
* Improve performance with better q4_k and q5_k dequant and store unrolling
* Add Vulkan MUL_MAT and MUL_MAT_ID accumulator precision selection
* Rework mulmat shader selection and compilation logic, avoid compiling shaders that won't get used by device
* Vulkan: Implement accumulator switch for specific mul mat mat shaders
* Vulkan: Unroll more loops for more mul mat mat performance
* Vulkan: Add VK_AMD_shader_core_properties2 support to read Compute Unit count for split_k logic
* Disable coopmat support on AMD proprietary driver
* Remove redundant checks
* Add environment variable GGML_VK_DISABLE_COOPMAT to disable VK_KHR_cooperative_matrix support
* Fix rebase typo
* Fix coopmat2 MUL_MAT_ID pipeline selection
* metal : Extend how Llama.cpp locates metal resources (#10675)
* It searches the resource file in the directory where the current
binary is located as well.
* Resolves symbolic links.
Rationale:
When we plug this dependency into a Bazel build and run it in the
context of Bazel (e.g. testing):
* the execution directory is often very different from where the files
are located and no direct control over this (Bazel sandboxing),
* the Bazel sandbox often use symbolic links to make files available.
With this patch, we can have the resource file added to the target,
can build and run tests in the context of Bazel.
* Update ggml/src/ggml-metal/ggml-metal.m
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* Update ggml/src/ggml-metal/ggml-metal.m
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
---------
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* ggml_pad_reflect_1d defined in header
* implemented on CPU
* called the forward pass
* impl Metal kernel
* added Metal kernel
* added OP_PAD_REFLECT_1D in test-backend-ops.cpp
* add test-pad-reflect-1d test case
* test case support multiple backend
This commit updates the copy-paste instruction in
convert_hf_to_gguf_update.py to reflect that convert_hf_to_gguf.py
will have already been updated with the new get_vocab_base_pre()
function when this script completes.
* [SYCL] Move to Compile Time backend selection on oneMKL Interface for NVIDIA backend
Move to compile time selection to backend to avoid latency at run time.
Add it to all mkl gemm calls and only for NVIDIA backend.
Signed-off-by: nscipione <nicolo.scipione@codeplay.com>
* Formatting
* Address PR comments to increase readibility
---------
Signed-off-by: nscipione <nicolo.scipione@codeplay.com>
* hide buttons in dropdown menu
* use npm as deps manager and vite as bundler
* fix build
* fix build (2)
* fix responsive on mobile
* fix more problems on mobile
* sync build
* (test) add CI step for verifying build
* fix ci
* force rebuild .hpp files
* cmake: clean up generated files pre build
* kqmax_new_j in every thread within warp is same after operate at line 199,this reduce can be omit
* same problem in vec32
---------
Co-authored-by: ZhaoXiaoYu <zhao.xiaoyu@zte.com.cn>
* readme : document --no-display-prompt
* readme : update default prompt context size
* readme : remove unnecessary indentation
Indenting a line with four spaces makes Markdown treat that section as
plain text.
* readme : indent commands under bullets
* readme : indent commands in lettered list
* llama : add enum for supported chat templates
* use "built-in" instead of "supported"
* arg: print list of built-in templates
* fix test
* update server README
* Templates: `mistral-v1`, `mistral-v2`, `mistral-v3`, `mistral-v3-tekken`
* Changed system message logic and added tests for all 4
* Invalid `system_message` instead of `content` fixed
* Removed tab-indented lines
* Added template code and test for `mistral-v7`
* Added all tests. Fixed bug with `tmpl == "llama2"` test.
* Replaced tabs with spaces.
* Removed `'mistral-v2'` option as no (open) models ever used it
* Removed all references to 'v2' template from comments
* Update llama.cpp
Fixed `trim_assistant_message` bug
* subgroup 64 version with subgroup add. 15% faster
scalable version
tested for subgroup sizes 16-128
* check for subgroup multiple of 16 and greater than 16
* subgroup sizes are always a power of 2 (https://github.com/KhronosGroup/GLSL/issues/45)
* force 16 sequential threads per block
* make 16 subgroup size a constant
This is an incremental improvement over #9118 to get work to the GPU a bit
sooner. The first part is to start with a smaller number of nodes before
the first submit, and ramp it up to the current 100 nodes/submit. The
second part is to reduce the dryrun overhead for all the nodes that just
need to request descriptor space.
With these changes I get around 1-2% speedup on RTX 4070 combined with my
old Haswell-era CPU.
* CANN: Fix the bug build fail on Ascend310P under two cases:
1) Manual specify SOC_TYPE
2) Under some unusual compile environment
* Update the cann backend News content: Support F16 and F32 data type model for Ascend 310P NPU.
* fix CANN compile fail bug: the assert in ascend kernel function doesn't supportted on some CANN version
There have been reports of failure to compile on systems with <= 32KB
of shared memory (e.g. #10037). This change makes the large tile size
fall back to a smaller size if necessary, and makes mul_mat_id fall
back to CPU if there's only 16KB of shared memory.
* server : replace behave with pytest
* fix test on windows
* misc
* add more tests
* more tests
* styling
* log less, fix embd test
* added all sequential tests
* fix coding style
* fix save slot test
* add parallel completion test
* fix parallel test
* remove feature files
* update test docs
* no cache_prompt for some tests
* add test_cache_vs_nocache_prompt
* improve inferencing performance for ascend npu.
Co-authored-by: Frank Mai <thxCode@thxcode0824@gmail.com>
* some modification after review
* some modifications after review
* restore some modifications
* restore some modifications
---------
Co-authored-by: shanshan shen <shanshanshen333@gmail.com>
Co-authored-by: Frank Mai <thxCode@thxcode0824@gmail.com>
The vulkan-shaders-gen was not parsing the --no-clean argument correctly.
Because the previous code was parsing the arguments which have a value only
and the --no-clean argument does not have a value, it was not being parsed
correctly. This commit can now correctly parse arguments that don't have values.
It's like simple-chat but it uses smart pointers to avoid manual
memory cleanups. Less memory leaks in the code now. Avoid printing
multiple dots. Split code into smaller functions. Uses no exception
handling.
Signed-off-by: Eric Curtin <ecurtin@redhat.com>
* llama : accept a list of devices to use to offload a model
* accept `--dev none` to completely disable offloading
* fix dev list with dl backends
* rename env parameter to LLAMA_ARG_DEVICE for consistency
* Add download chat feature to server chat
Add a download feature next to the delete chat feature in the server vue chat interface.
* code style
---------
Co-authored-by: Xuan Son Nguyen <son@huggingface.co>
This matches the key in common bert-based embedding models and may have a
value other than 1 in it.
Branch: XLMRobertaTypeVocabSize
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* GitHub: ask for more info in issues [no ci]
* refactor issue templates to be component-specific
* more understandable issue description
* add dropdown for llama.cpp module
* CANN Support Ascend310P to accelerate F32 and F16 Model
* Add compile option soc type macro ASCEND_310P to ggml-cann lib
* Remove unused code
* Remove the ascend soc_type hard code compile option in CMakelist.txt
* vulkan: Use pipeline_robustness to disable robustness in mul_mat_vec.
Add some early returns for nonexistent rows in mul_mat_vec shaders. These
can only be hit when dispatching a 2D grid of workgroups. Fix the logic
for the 2D grid of workgroups to round up.
Enable the pipeline robustness extension if it's available, and use it to
disable robustness for these pipelines. The instructions to do the bounds
checking contend for the same ALU resources as the bit twiddling dequant
instructions.
* vulkan: Add GLSL structure aliases for quant types to allow larger loads
In Vulkan it's not possible to cast pointer types, so instead you have to
declare an aliased binding for the memory with a different type. This
commit adds aliases for the quant formats using 16b ints, and in a few
places where the struct size is a multiple of 4 also using 32b ints.
Currently only q4_k's aliases are used, but others will be used in
subsequent commits.
* vulkan: use larger loads in q5_k and q6_k shaders.
Similar to the optimization I did in q4_k recently, this vectorizes some loads
and reduces the number of bit twiddling instructions.
* vulkan: use larger K step per iteration in mul_mat_vec.
Add vec4 dequantization functions, and use them to do K=8 per iteration in
mul_mat_vec. This uses 16b loads for the quant values and 128b loads for B
which helps reduce the load on the memory system.
The K_PER_ITER==2 logic is still there, just for F16/F32, and really only
because they support unaligned sizes.
Tweak the num_iters/unrolling logic to be simpler and catch a couple missed
unrolling opportunities.
* Add OLMo November 2024 constants
* Add OLMo November 2024 converter
* Add loading of OLMo November 2024 tensors and hyper parameters
* Add building of OLMo November 2024 model
* Add option to set the SYCL architecture for all targets
* Convert GGML_SYCL_HIP_TARGET to the more generic GGML_SYCL_ARCH option
* Document that setting GGML_SYCL_ARCH can improve the performance
* vulkan: Optimize soft_max
Large soft_max could already saturate memory, but small/medium sizes were
pretty slow. The bulk of the gains for them comes from using a smaller
workgroup size, and making the workgroup size match the subgroup size also
makes the barriers much cheaper.
Cache some values in locals to avoid refetching/recomputing. And stamp
out a few "template instantiations" so smaller cases will fully unroll.
Add a missing early return for OOB rows. This happens when there are more
than 512 rows and the dispatch is 512 x H.
* vulkan: Further soft_max optimizations
Restore the workgroup size of 512 case, use it for >1024.
Use unrollable loops for more iteration counts.
* metal : add kernel arg structs (wip)
* metal : fattn args
ggml-ci
* metal : cont + avoid potential int overflow [no ci]
* metal : mul mat struct (wip)
* cont : mul mat vec
* cont : pass by reference
* cont : args is first argument
* cont : use char ptr
* cont : shmem style
* cont : thread counters style
* cont : mul mm id
ggml-ci
* cont : int safety + register optimizations
ggml-ci
* metal : GGML_OP_CONCAT
ggml-ci
* metal : GGML_OP_ADD, GGML_OP_SUB, GGML_OP_MUL, GGML_OP_DIV
* metal : GGML_OP_REPEAT
* metal : GGML_OP_CPY
* metal : GGML_OP_RMS_NORM
* metal : GGML_OP_NORM
* metal : add TODOs for rest of ops
* ggml : add ggml-metal-impl.h
ggml-ci
* Samplers sequence: simplified and input field.
* Removed unused function
* Modify and use `settings-modal-short-input`
* rename "name" --> "label"
---------
Co-authored-by: Xuan Son Nguyen <son@huggingface.co>
Compute two result elements per workgroup (for Q{4,5}_{0,1}). This reuses
the B loads across the rows and also reuses some addressing calculations.
This required manually partially unrolling the loop, since the compiler
is less willing to unroll outer loops.
Add bounds-checking on the last iteration of the loop. I think this was at
least partly broken before.
Optimize the Q4_K shader to vectorize most loads and reduce the number of
bit twiddling instructions.
* use 128 bit loads (i've tried 256->128 to death and its slower)
* double accumulator
* avx bf16 vec dot
* +3% q4_0 inference
* +7% tg +5% pp compared to master
* slower f16c version, kep for reference
* 256b version, also slow. i tried :)
* revert f16
* faster with madd
* split to functions
* Q8_0 and IQ4_NL, 5-7% faster
* fix potential overflow (performance reduced)
* 16 bit add for q4_0 only
* merge
* server : (web ui) add copy btn for code blocks
* fix problem with api key
* use settings-modal-short-input component
* always show copy btn for code snippet
* sycl: Use syclcompat::dp4a
* Using the syclcompat version allow the compiler to optimize the
operation with native function
* Update news section
* Update CI Windows oneAPI version to 2025.0
* Reword doc
* Call syclcompat::dp4a inside dpct::dp4a
This reverts commit 90cb61d692.
Reuse the index calculations across all of src0/src1/dst. Add a shader
variant for when src0/src1 are the same dimensions and additional modulus
for src1 aren't needed. Div/mod are slow, so add "fast" div/mod that
have a fast path when the calculation isn't needed or can be done more
cheaply.
* llama: propagating the results of `graph_compute` to the user interface
* llama: reverting kv_cache in case of failed compute
* llama: `llama_kv_cache_state` was removed, only the result of `llama_graph_compute` is returned
* llama: restore a kv_cache in case of failed computation
* llama: correct reverting of the entire batch.
also updates `llama_kv_cache_find_slot`, will correctly count the number of `used` cells for recurrent models
* llama: updated comments
* llama : add comments about KV cache state after error
---------
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
Converter script can now read these two fields as a detailed base model and dataset source.
This was done so that it will be easier for Hugging Face to integrate detailed metadata as needed.
- base_model_sources (List[dict], optional)
- dataset_sources (List[dict], optional)
Dataset now represented as:
- general.dataset.count
- general.dataset.{id}.name
- general.dataset.{id}.author
- general.dataset.{id}.version
- general.dataset.{id}.organization
- general.dataset.{id}.description
- general.dataset.{id}.url
- general.dataset.{id}.doi
- general.dataset.{id}.uuid
- general.dataset.{id}.repo_url
This also adds to base model these metadata:
- general.base_model.{id}.description
* Fixes broken build for the SYCL CUDA backend caused by non-explicit gemm call in outprod (merged in with RWKV6 in
Optimize RWKV6 Operator Naming and Implement Multi-core CPU/ SYCL Acceleration #10133)
* Marks permuted MUL_MAT as unsupported to be able to run test-backend-ops
* Fixes asserts in norm to fix debug builds.
* tests: Fix memory bandwidth calculation for perf tests
Add a flops calculation for flash attention.
Add one GGML_OP_CPY perf test.
* vulkan: Optimize contiguous copies
Add a variant of the copy shader for when the tensors are contiguous. Avoid
the complex addressing calculations, and do four elements per invocation
to hide some other overhead.
Apply similar changes to the scale shader, since scale is always contiguous.
Add a "progress bar" for shader compiles.
Fixes#9582
Spawning too many concurrent copies of glslc leads to "Failed to create pipes"
errors on Linux. This change applies the same throttling we use for
multithreaded pipeline creation.
* Add back samplers to server
* Added tooltips with basic information
* Fixed stretching of input fields.
* use component for settings input, move help msg to tooltips
---------
Co-authored-by: Xuan Son Nguyen <son@huggingface.co>
This change upstreams llamafile's cpu matrix
multiplication kernels for ppc64le using MMA
builtins for FP32 datatype.
This change results in a consistent 90%
improvement in input processing time, and 20%
to 80% improvement in output processing time,
across various batch sizes.
The patch is tested with Meta-Lllama-3-8B,
Mistral-7B, Llama-2-7B-chat-hf models on a
IBM POWER10 machine.
Signed-off-by: Amrita H S <amritahs@linux.vnet.ibm.com>
* metal : opt-in compile flag for BF16
ggml-ci
* ci : use BF16
ggml-ci
* swift : switch back to v12
* metal : has_float -> use_float
ggml-ci
* metal : fix BF16 check in MSL
ggml-ci
* ggml : add ggml_flash_attn_ext_get_prec
* metal : use F16 precision in FA kernels
ggml-ci
* metal : minor clean-up
* metal : compile-guard bf16 FA kernels
ggml-ci
* build : remove obsolete compile flag [no ci]
* metal : prevent int overflows [no ci]
* cuda : disable BF16 FA
ggml-ci
* metal : fix BF16 requirement for FA kernels
ggml-ci
* make : clean-up [no ci]
* server : simple chat UI with vuejs and daisyui
* move old files to legacy folder
* embed deps into binary
* basic markdown support
* add conversation history, save to localStorage
* fix bg-base classes
* save theme preferences
* fix tests
* regenerate, edit, copy buttons
* small fixes
* docs: how to use legacy ui
* better error handling
* make CORS preflight more explicit
* add GET method for CORS
* fix tests
* clean up a bit
* better auto scroll
* small fixes
* use collapse-arrow
* fix closeAndSaveConfigDialog
* small fix
* remove console.log
* fix style for <pre> element
* lighter bubble color (less distract when reading)
* rwkv6: rename to wkv6
* rwkv6: support avx2 avx512 armv8 armv9
* rwkv6: update cuda file name
* rwkv6: rename params
* wkv on sycl
* sycl: add some ops
* sycl: Enhance OP support judgment
* wkv6: drop armv9 and tranfer to GGML style
ggml-ci
* sync : ggml
* update the function to use appropriate types
* fix define error
* Update ggml/src/ggml-cpu.c
* add appropriate asserts
* move element-wise functions outside
* put the declaration outside the loop
* rewrite to be more inline with the common pattern for distributing threads
* use recommended way GGML_TENSOR_LOCALS
---------
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
Co-authored-by: Diego Devesa <slarengh@gmail.com>
Co-authored-by: Plamen Minev <pacominev@gmail.com>
Co-authored-by: Yuri Khrustalev <ykhrustalev@users.noreply.github.com>
Co-authored-by: Meng, Hengyu <airdldl@163.com>
* ggml : add initial BF16 support
ggml-ci
* metal : add mul_mat_id BF16 support
ggml-ci
* metal : check for bfloat support on the Metal device
ggml-ci
* metal : better var names [no ci]
* metal : do not build bfloat kernels when not supported
ggml-ci
* metal : try to fix BF16 support check
ggml-ci
* metal : this should correctly check bfloat support
* metal : add quantized FA (vec) support
ggml-ci
* metal : add quantized FA (non-vec) support
* metal : fix support check
ggml-ci
* metal : clean-up
* metal : clean-up (cont)
* metal : fix shared memory calc + reduce smem + comments
* metal : float-correctness
* metal : minor [no ci]
* q6_k instruction reordering attempt
* better subtract method
* should be theoretically faster
small improvement with shuffle lut, likely because all loads are already done at that stage
* optimize bit fiddling
* handle -32 offset separately. bsums exists for a reason!
* use shift
* Update ggml-quants.c
* have to update ci macos version to 13 as 12 doesnt work now. 13 is still x86
* convert-lora : make `--base` optional
* lint
* handle case where base_model_name_or_path is invalid
* do not include metadata from base model
* clarify unspecified --base
* add small comment [no ci]
* trigger ci
* llama : fix buffer checks for mamba and rwk
* llama : fix missing worst case flag during reserve
* cuda : fix supports_op for norm
* disable sched SET_CAUSE
* ggml : fix gguf string leak when reading kv pairs fails
* ggml : avoid crashing with GGML_ABORT when the KV has an invalid type
* ggml : avoid crashing on failed memory allocations when loading a gguf file
* ggml: Add POOL2D OP for GPU ACC to the Vulkan.
- The MobileVLM model now supports inference acceleration through GPU by utilizing the Vulkan backend.
- A GGML_OP_POOL_2D shader has been added. (Pooling)
- The encoding performance of the CLIP model improved from 2.8s on the CPU to 0.7s on the GPU.
Signed-off-by: Changyeon Kim <cyzero.kim@samsung.com>
* [fix] Correct the incorrect order of the parameters.
fix casting to int.
Signed-off-by: Changyeon Kim <cyzero.kim@samsung.com>
---------
Signed-off-by: Changyeon Kim <cyzero.kim@samsung.com>
* Add granite template to llama.cpp
* Add granite template to test-chat-template.cpp
* Update src/llama.cpp
Co-authored-by: Xuan Son Nguyen <thichthat@gmail.com>
* Update tests/test-chat-template.cpp
Co-authored-by: Xuan Son Nguyen <thichthat@gmail.com>
* Added proper template and expected output
* Small change to \n
Small change to \n
* Add code space &
Co-authored-by: Xuan Son Nguyen <thichthat@gmail.com>
* Fix spacing
* Apply suggestions from code review
* Update src/llama.cpp
---------
Co-authored-by: Xuan Son Nguyen <thichthat@gmail.com>
* metal : support permuted matrix multiplicaions
ggml-ci
* cont : use nb01 directly for row steps
ggml-ci
* cont : add comments [no ci]
* metal : minor refactor
* metal : minor
* llama: Refactor string_split to use template specialization, fixes parsing strings with spaces
* llama: Add static_assert in the string_split template to ensure the correct template specialization is used for std::string
This commit removes the setting of the `used` field of the contexts in
the global state (g_state) in `ggml_init`.
The motivation for this change is that I believe that this additional
initialization might not be required after the changes in Commit
45fc4fed0b9fb5b1af4a8525cbebb95e11208732 ("sync : latest changes from
whisper.cpp"), which changed the initialization of the contexts field
from `{ 0 }` to `{ { 0 } }`:
```console
g_state = (struct ggml_state) {
- /*.contexts =*/ { 0 },
+ /*.contexts =*/ { { 0 } },
};
```
My understanding is that the `{0}` initialization might not have
zero-initialized all the nested fields in every array element because of
compiler differences, and might have been the reason for having the
explicit setting of the `used` fields to false.
* added classic vim support
* fixed ring update, removed blank line
* minor
* minor
* minor doc update
* removed uneeded var
* minor
* minor
* fixed job_start creating new scratch buffers
* fixed job_start creating new scratch buffers
* fixed ghost text indenting when expandtab is on
* removed unused code
* minor
* unified fim_on_exit
* minor
* vim ghost text rendering now uses pos_x and pos_y parameters
* renamed *_hlgroup to hlgroup_*
* renamed *_ghost_text to ghost_text_*, moved nvim/vim detection to llama#init()
* minor
---------
Co-authored-by: Michael Coppola <info@michaeljcoppola.com>
This commit renames the member field batch in llm_build_context to
ubatch, and also the parameter batch in llama_build_graph, and
llama_set_inputs to ubatch.
The motivation for this change is to make the code more readable
(considering there are the structs llama_batch and llama_sbatch), and
consistent with other parts of the code base where parameters/fields of
type llama_ubatch are named ubatch.
* [CANN] Adapt to dynamically loadable backends mechanism
* Fix the Bug: inference running result is garbled in debug running model for LM models who's type is Q4_0 class
* Handle the review comments of this pull request
This commit fixes two typos in the help text for the `--embd-normalize`
and `--embd-separator` arguments. It also updates common.h which contain
the same typo in two comments.
This commit updates the argument value hint for the `--attention`
argument to `non-causal`.
The motivation for this change is that the only values for this argument
are `causal` and `non-causal`.
* llama : deprecate softmax sampler + fix dist sampler
ggml-ci
* tests : replace macros with functions
ggml-ci
* sampling : change temperature sampler logic
For t <= 0.0f, keep the max logit intact and set the rest to -inf
* cont : no need for special "greedy" logic
top-k == 1 is the same
* tests : init prob correctly
* llama : handle temp <= 0.0 in the temp_ext sampler too
ggml-ci
* cont : avoid extra loop in temperature sampler for sub-zero temp
ggml-ci
llama_cpp_canister allows you to run llama.cpp as a Smart Contract on the Internet Computer. The smart contract runs as WebAssembly in a so-called 'canister'.
add intel amx isa detection
add vnni kernel for gemv cases
add vnni and amx kernel support for block_q8_0
code cleanup
fix packing B issue
enable openmp
fine tune amx kernel
switch to aten parallel pattern
add error message for nested parallelism
code cleanup
add f16 support in ggml-amx
add amx kernels for QK_K quant formats: Q4_K, Q5_K, Q6_K and IQ4_XS
update CMakeList
update README
fix some compilation warning
fix compiler warning when amx is not enabled
minor change
ggml-ci
move ggml_amx_init from ggml.c to ggml-amx/mmq.cpp
ggml-ci
update CMakeLists with -mamx-tile, -mamx-int8 and -mamx-bf16
ggml-ci
add amx as an ggml-backend
update header file, the old path for immintrin.h has changed to ggml-cpu-impl.h
minor change
update CMakeLists.txt
minor change
apply weight prepacking in set_tensor method in ggml-backend
fix compile error
ggml-ci
minor change
ggml-ci
update CMakeLists.txt
ggml-ci
add march dependency
minor change
ggml-ci
change ggml_backend_buffer_is_host to return false for amx backend
ggml-ci
fix supports_op
use device reg for AMX backend
ggml-ci
minor change
ggml-ci
minor change
fix rebase
set .buffer_from_host_ptr to be false for AMX backend
* fix: use `vm_allocate` to allocate CPU backend buffer on macOS
* fix: switch to `posix_memalign` to keep existing `free()` usages work
* feat: move `GGML_ALIGNED_MALLOC` to `ggml-backend-impl.h`, add support for `vm_allocate` on macOS
* style: formatting
* fix: move const outside of `#ifndef`
* style: formatting
* fix: unused var
* fix: transform `GGML_ALIGNED_MALLOC` and `GGML_ALIGNED_FREE` into functions and add them to `ggml-impl.h`
* fix: unused var
* fix: page align to `GGUF_DEFAULT_ALIGNMENT`
* fix: page align to `TENSOR_ALIGNMENT`
* fix: convert `TENSOR_ALIGNMENT` to a macro
* fix: increase page size to `32` on iOS
* fix: iOS page size
* fix: `hbw_posix_memalign` alignment
* llama : suppress conversion from 'size_t' to 'int'
This commit updates llm_tokenizer_spm.tokenize to suppress/remove the
following warnings that are generated on Windows when using MSVC:
```console
src\llama-vocab.cpp(211,1): warning C4267: 'argument':
conversion from 'size_t' to 'int', possible loss of data
src\llama-vocab.cpp(517,1): warning C4267: 'argument':
conversion from 'size_t' to 'int', possible loss of data
```
This is done by adding a cast for the size_t returned from
symbols.size(). I believe this is safe as it seems unlikely that
symbols, which stores an entry for each UTF8 character, would become
larger than INT_MAX.
The motivation for this change is to reduce the number of warnings that
are currently generated when building on Windows.
* squash! llama : suppress conversion from 'size_t' to 'int'
Move cast into for loop.
Prior to this commit, using a JSON Schema containing a string
with `pattern` regular expression that uses top-level alternation
(e.g. `"pattern": "^A|B|C|D$"`) would result in invalid JSON
output from the constrained sampling grammar, because it
ended up creating a grammar rule like this for the string:
```
thing ::= "\"" "A" | "B" | "C" | "D" "\"" space
```
Note that this rule will only match a starting quote for the "A" case,
and will only match an ending quote for the "D" case,
so this rule will always produce invalid JSON when used for sampling
(that is, the JSON will always be lacking the starting quote,
the ending quote, or both).
This was fixed in a simple way by adding parentheses to the
generated rule (for all string pattern rules, to keep it simple),
such that the new generated rule looks like this (correct):
```
thing ::= "\"" ("A" | "B" | "C" | "D") "\"" space
```
This commit removes the buffer_id field from the leaf_alloc struct.
The motivation for is that this field is only written to and never
read/used as far as I can tell. Each tensor_alloc has a buffer_id field
and this is what caused me to look into this more closely, to
understand what the buffer_id in leaf_alloc was used for.
* Initial XTC commit
Adds XTC sampler, not activated by default, but recommended settings by default.
* Cleanup
* Simplified chances calculation
To be more inline with the original implementation, chance is calculated once at the beginning.
* First fixes by comments
Still need to look into sorting
* Fixed trailing backspaces
* Fixed RNG to be reproduceable
Thanks to @slaren for directions
* Fixed forgotten header
* Moved `min_keep`
Moved from conditions to a simple check at the end.
* Fixed broken randomization
Thanks to @slaren for explanation
* Swapped sorting for a custom algorithm
Shifts tokens to remove the penalized ones, then puts the penalized at the back. Should make `min_keep` still viable.
* Algorithm rework
1. Scan token from top till the first non-penalizable
2. Remove the last captured token (the least probable above threshold)
3. Shift all tokens to override the remaining penalizable
4. Penalize and put them at the the bottom.
* Added XTC to `test-sampling`
* Simplified algorithm and more tests
* Updated info in common and args
* Merged back lost commits in common and arg
* Update dump info in common
* Fixed incorrect min_keep check
* Added XTC to README
* Renamed parameters, fixed info and defaults
* probability is at 0 by default, but XTC is included in sampling queue
* threshold higher than 0.5 switches XTC off
* Initial server support
* Added XTC to server UIs
* Fixed labels in old server UI
* Made algorithm safer and more readable
* Removed xtc_threshold_max
* Fixed arg after update
* Quick fixes by comments
* Simplified algorithm since threshold_max is removed
* Renamed random distribution
* Fixed tests and outdated README
* Small fixes
* Vectorize load instructions in dmmv f16 CUDA kernel
Replaces scalar with vector load instructions, which substantially
improves performance on NVIDIA HBM GPUs, e.g. gives a 1.27X overall
speedup for Meta-Llama-3-8B-Instruct-F16 BS1 inference evaluation on
H100 SXM 80GB HBM3. On GDDR GPUs, there is a slight (1.01X) speedup.
* addressed comment
* Update ggml/src/ggml-cuda/dmmv.cu
Co-authored-by: Johannes Gäßler <johannesg@5d6.de>
---------
Co-authored-by: Johannes Gäßler <johannesg@5d6.de>
* server : accept extra_context for the infill endpoint
ggml-ci
* server : update readme [no ci]
* server : use repo-level FIM pattern if possible
ggml-ci
* llama : improve infill support
ggml-ci
* llama : add more FIM token strings
ggml-ci
* server : update prompt on slot restore (#9800)
* gguf : deprecate old FIM token KVs
* ggml : do not use BLAS with types without to_float
* ggml : return pointer from ggml_internal_get_type_traits to avoid unnecessary copies
* ggml : rename ggml_internal_get_type_traits -> ggml_get_type_traits
it's not really internal if everybody uses it
* docs : clarify building Android on Termux
* docs : update building Android on Termux
* docs : add cross-compiling for Android
* cmake : link dl explicitly for Android
* ggml : add metal backend registry / device
ggml-ci
* metal : fix names [no ci]
* metal : global registry and device instances
ggml-ci
* cont : alternative initialization of global objects
ggml-ci
* llama : adapt to backend changes
ggml-ci
* fixes
* metal : fix indent
* metal : fix build when MTLGPUFamilyApple3 is not available
ggml-ci
* fix merge
* metal : avoid unnecessary singleton accesses
ggml-ci
* metal : minor fix [no ci]
* metal : g_state -> g_ggml_ctx_dev_main [no ci]
* metal : avoid reference of device context in the backend context
ggml-ci
* metal : minor [no ci]
* metal : fix maxTransferRate check
* metal : remove transfer rate stuff
---------
Co-authored-by: slaren <slarengh@gmail.com>
* Single allocation of encode_async block with non-ARC capture in ggml-metal.m
* Moving Block_release to the deallocation code
* Release encode block when re-setting encoding buffer count if needed
* Update ggml/src/ggml-metal.m
---------
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* rerank : use [SEP] token instead of [BOS]
ggml-ci
* common : sanity check for non-NULL tokens
ggml-ci
* ci : adjust rank score interval
ggml-ci
* ci : add shebang to run.sh
ggml-ci
* Add scaffolding for ggml logging macros
* Metal backend now uses GGML logging
* Cuda backend now uses GGML logging
* Cann backend now uses GGML logging
* Add enum tag to parameters
* Use C memory allocation funcs
* Fix compile error
* Use GGML_LOG instead of GGML_PRINT
* Rename llama_state to llama_logger_state
* Prevent null format string
* Fix whitespace
* Remove log callbacks from ggml backends
* Remove cuda log statement
* vulkan : do not use tensor->extra
This patch allows using the Vulkan backend with the RPC backend as
tensor->extra is no longer used.
Ref: #8536
* Adapt GGML_VULKAN_CHECK_RESULTS to extra removal (#2)
---------
Co-authored-by: 0cc4m <picard12@live.de>
* make sure params --split and --merge are not specified at same time
* update gguf-split params parse logic
* Update examples/gguf-split/gguf-split.cpp
Co-authored-by: slaren <slarengh@gmail.com>
---------
Co-authored-by: Xuan Son Nguyen <thichthat@gmail.com>
Co-authored-by: slaren <slarengh@gmail.com>
When the device's warp size is less than 16,
it is possible for loadstride_a (mul_mm.comp:114)
and loadstride_b (mul_mm.comp:115) to be set to 0.
Because they are calculated as: the workgroup size,
multiplied by LOAD_VEC_* (which can be 1) and divided by 16.
And the workgroup size is set to be the same as the
warp/subgroup size.
The loadstride_* variables are used as increments in the
loops that populate the buffers used for the multiplication.
When they are 0 they cause an infinite loop.
But infinite loops without side-effects are UB and the
values of loadstride_* are known at compile time.
So, the compiler quietly optimizes all the loops away.
As a consequence, the buffers are not populated and
the multiplication result is just a matrix with all elements
set to 0.
We prevent the UB by making sure that the workgroup size
will never be less than 16, even if our device has a
smaller warp size (e.g. 8).
Signed-off-by: Salvatore Mesoraca <s.mesoraca16@gmail.com>
* convert : refactor rope_freqs generation
This should also fix vocab-only conversion for Phi-3.
* convert : adapt MiniCPM3 to separate rope_freqs insertion
MiniCPM3's tokenizer is treated as a SentencePiece tokenizer to avoid
having to run its custom Python code which mixes tokenization
in the same file as tool calls.
gguf-py : add long and short RoPE factors to tensor mappings
Empty, but the key names are used to populate the mappings.
a return before a barrier (that happens only in some threads in
a workgroup) leads to UB.
While the old code actually works on some devices,
it fails on some others (i.e. "smaller" GPUs).
BTW, I think it would be better to set specialization constants
when the graph is built, in that way the local workgroup
could be sized appropriately.
But it would take a lot of work.
Signed-off-by: Salvatore Mesoraca <s.mesoraca16@gmail.com>
A crash was observed when the number of tokens added to a batch exceeds
llama_batch size. An assertion in llama_batch_add was added to protect
against llama_batch size overflow.
* test-backend-ops : use flops for some performance tests
- parallelize tensor quantization
- use a different set of cases for performance and correctness tests
- run each test for at least one second
* ggml: Added run-time detection of neon, i8mm and sve
Adds run-time detection of the Arm instructions set features
neon, i8mm and sve for Linux and Apple build targets.
* ggml: Extend feature detection to include non aarch64 Arm arch
* ggml: Move definition of ggml_arm_arch_features to the global data section
* ggml : remove assert for AArch64 GEMV and GEMM Q4 kernels
* added fallback mechanism when the offline re-quantized model is not
optimized for the underlying target.
* fix for build errors
* remove prints from the low-level code
* Rebase to the latest upstream
* 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>
* 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>
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>
* 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>
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.
* 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>
* 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.
* 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>
This commit renames n_embed to n_embd in llm_build_rwkv6_time_mix.
The motivation for this change is consistency with the other rwkv6
functions like build_rwkv6 (and other parts of the code base).
* added cli arg to disable context shift
* reverted precommit
* updated README.md for main
* white space
* allow disabling context shift in the server
* Update common/arg.cpp
no-context-shift only works for main example
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* added server example to --no-context-shift args
* removed server changes
* white space
---------
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
This commit makes the cell_id variable const in the inp_s_mask block.
The motivation for this change is consistency with the code in the
inp_s_copy block.
* Adding loading page for '/' server requests
* set content when model is loading
* removed loading html file
* updated cmakelist
* updated makefile
* cleaned up whitespace
* cleanup for PR removed error
* updated server test to handle 503 HTML
* updated server test to handle 503 HTML
* ca†ch 503 before parsing json
* revert test
* account for both api and web browser requests
* precommit corrections
* eol fix
* revert changes to pre-commit
* removed print statement
* made loading message more descriptive
* also support .html files
---------
Co-authored-by: VJHack <flymyplane21@gmail.com>
Co-authored-by: Vinesh Janarthanan <36610342+VJHack@users.noreply.github.com>
* llama : llama_perf + option to disable timings during decode
ggml-ci
* common : add llama_arg
* Update src/llama.cpp
Co-authored-by: Xuan Son Nguyen <thichthat@gmail.com>
* perf : separate functions in the API
ggml-ci
* perf : safer pointer handling + naming update
ggml-ci
* minor : better local var name
* perf : abort on invalid sampler pointer
ggml-ci
---------
Co-authored-by: Xuan Son Nguyen <thichthat@gmail.com>
* server : added with_pieces functionality to /tokenize endpoint
* server : Add tokenize with pieces tests to server.feature
* Handle case if tokenizer splits along utf8 continuation bytes
* Add example of token splitting
* Remove trailing ws
* Fix trailing ws
* Maybe fix ci
* maybe this fix windows ci?
---------
Co-authored-by: Xuan Son Nguyen <son@huggingface.co>
* feat: Implements retrying logic for downloading models using --model-url flag
* Update common/common.cpp
Co-authored-by: Xuan Son Nguyen <thichthat@gmail.com>
* Update common/common.cpp
Co-authored-by: Xuan Son Nguyen <thichthat@gmail.com>
* apply comments
* implements a retry function to avoid duplication
* fix editorconfig
* change function name
---------
Co-authored-by: farbod <farbod.bjary82@gmail.com>
Co-authored-by: Xuan Son Nguyen <thichthat@gmail.com>
Co-authored-by: slaren <slarengh@gmail.com>
Co-authored-by: Xuan Son Nguyen <son@huggingface.co>
* sycl : update support condition to im2col
Signed-off-by: Alberto Cabrera <alberto.cabrera@codeplay.com>
* Added TODO to remind supporting FP32 im2col
---------
Signed-off-by: Alberto Cabrera <alberto.cabrera@codeplay.com>
This commit updates the comment, which seems to contain a typo or be an
outdated comment, in the copy_mask_state function changing the variable
n_rs to n_kv.
I believe this change is correct and what the comment wants to
convey is to copy the states that are not going to be used in the
upcoming processing, which are the tokens states from n_seqs up to
the number of possible token states n_kv.
* Arm AArch64: Documentation updates
* Update docs/build.md to include information on how to enable the Arm optimized gemm/gemv kernels
* Update examples/quantize/README.md with information on the Q4_0_4_4, Q4_0_4_8 and Q4_0_8_8 formats
* Add newline to the end of docs/build.md
* Overlap cmdbuffer creation and cmdbuffer execution in Vulkan backend by submitting smaller cmdbuffers early.
* fix compile issues
* Fix issues where the last submit wasn't executed or handled properly.
* remove trailing whitespace
* Repair GGML_VULKAN_CHECK_RESULTS
* Increase submit counter only if actual work has been submitted and increase submit count to 100.
* Fix some nodes are not checked with GGML_VULKAN_CHECK_RESULTS enabled.
* add check malloc result on device
* update for review comments, check all malloc_device() result
---------
Co-authored-by: arthw <14088817+arthw@users.noreply.github.com>
sin and cos failed test-backend-ops because they
tried to dereference a context pointer that is null
on dry runs.
This commit prevents that segfault.
Signed-off-by: Salvatore Mesoraca <s.mesoraca16@gmail.com>
test-backend-ops fails because ggml_cont aborts
when invoked passing an unsupported type.
This commit makes ggml_cont tests pass
Signed-off-by: Salvatore Mesoraca <s.mesoraca16@gmail.com>
* tests: add gradient checking to test-backend-ops
* remove old comment
* reorder includes
* adjust SIN/COS parameters
* add documentation, use supports_op if possible
* ggml_cont: fix issue with transposed tensors when one dimension is 1
when using multiple threads, it is not enough
to check for the tensors to be contiguous for
ggml_compute_forward_dup_same_cont to work correctly.
The tensors strides also need to match.
Signed-off-by: Salvatore Mesoraca <s.mesoraca16@gmail.com>
* Add ggml_cont tests
Signed-off-by: Salvatore Mesoraca <s.mesoraca16@gmail.com>
* Remove dead code
it isn't possible to reach this code because
all these functions are invoked by ggml_compute_forward_dup
if and only if src0->type != dst->type
Signed-off-by: Salvatore Mesoraca <s.mesoraca16@gmail.com>
* Make ggml_compute_forward_dup_same_cont work with contiguous tensors
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
Signed-off-by: Salvatore Mesoraca <s.mesoraca16@gmail.com>
---------
Signed-off-by: Salvatore Mesoraca <s.mesoraca16@gmail.com>
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* common : do not add null tokens during warmup
ggml-ci
* llama : check that the input tokens are valid
ggml-ci
* tests : fix batch size of bert model
ggml-ci
- Add `struct llama_sampler` and `struct llama_sampler_i`
- Add `llama_sampler_` API
- Add `llama_sampler_chain_` API for chaining multiple samplers
- Remove `LLAMA_API_INTERNAL`
- Add `llama_perf_` API and remove old `llama_print_timings` and `llama_reset_timings`
* Improve Vulkan shader builds system
- Add dependency to vulkan-shaders-gen to rebuild shaders when changing the shader compilation utility.
- Add option to generate debug info for Vulkan shaders to provide shader source to Vulkan shader profiling tools
* remove not required self dependency
* ggml-quants : 1.625 bpw ternary packing for BitNet 1.58b
* ggml-quants : faster 1.625 bpw AVX2 vec_dot
Not using a lookup table anymore makes it match q4_0 speed.
* gguf-py : fix formatting
* llama : remove spaces on empty line
* ggml-quants : subtract 1 when back in epi8
This makes the 1.625 bpw type go faster than q4_0. Still not the fastest.
* ggml-quants : Q2_2 now faster than Q4_K on with AVX2
* ggml-quants : cleanup Q1_3 code formatting
* ggml-quants : ARM NEON vec_dot for q2_2 and q1_3
* ggml-quants : use ceiling division when quantizing q1_3
* convert-hf : simplify BitNet pre-quantization
This still results in the exact same tensor weights and scales,
but it reveals some weirdness in the current algorithm.
* convert-hf : allow converting the weird BitNet 1.3B
Its FFN size is 5460 which is not convenient.
The offending tensors are kept in F16,
which makes the final model 5.01 bpw.
* bitnet : replace 1.58b with b1.58, as in the paper
* ggml-quants : fix build failure on Windows
* ggml-quants : attempt to fix Arm 32-bit support
* ggml : add some informative comments in q1_3 vec_dot
* ggml : add TQ1_0 and TQ2_0 ternary quantization types
* ggml : even faster TQ2_0
* ggml : also faster TQ1_0
Same optimization as for TQ2_0 by offsetting the sum instead of the weights.
This makes TQ1_0 almost as fast as Q8_0 on AVX2.
* ggml : fix build issues in certain environments
* ggml : add NEON vec_dot implementation for TQ1_0 and TQ2_0
* ggml : avoid directly using vmlal_high_s8, for 32-bit ARM compat
The compiler seems smart enough to use the same instruction
even when using vget_high_s8 instead.
* ggml : remove q1_3 and q2_2
No more 1.625 bpw and 2.000 bpw,
now instead using 1.6875 bpw and 2.0625 bpw
with TQ1_0 and TQ2_0, respectively.
* llama : remove the separate scale tensors of BitNet b1.58
They won't be needed, since the remaining ternary quant types have
built-in scales.
* ggml-quants : rename fields of TQ1_0 and TQ2_0 structs for consistency
* ggml-quants : allow using vdotq_s32 in TQ2_0 vec_dot
Not yet tested on hardware which supports it,
might not work or might not even compile. But also it might.
It should make the performance better on recent ARM CPUs.
* ggml-quants : remove comment about possible format change of TQ2_0
Making it slightly more convenient for AVX512
but less convenient for everything else is not worth the trouble.
* gguf-py : Numpy (de)quantization for TQ1_0 and TQ2_0
* ggml-quants : use roundf instead of nearest_int for TQ1_0 and TQ2_0
This does not change anything for ternary models,
since their values should never end up being in halfway cases anyway.
* convert : allow direct conversion to TQ1_0 and TQ2_0
The token embeddings and output tensors are kept in F16
to allow quantizing them to Q4_K and Q6_K with llama-quantize.
* llama : handle fallback for TQ1_0 and TQ2_0 with Q4_0
Q4_0 is not completely symmetric (so not lossless for ternary models),
but it should be good enough.
* ggml-quants : allow using ARM dot product instructions for TQ1_0
* ggml-quants : deduplicate TQ1_0 and TQ2_0 __ARM_FEATURE_DOTPROD support
* ggml : remove unused ggml_mul special case
It would otherwise conflict with the more general
optimization coming with Mamba-2.
* ggml : handle TQ1_0 and TQ2_0 in dequantization-based operators
* test-backend-ops : add TQ1_0 and TQ2_0 comments for later
Not yet adding uncommented, because some backends like SYCL and Metal
do not properly handle unknown types in supports_op for GGML_OP_MUL_MAT.
(and Metal also doesn't handle it with GGML_OP_GET_ROWS)
Support for TQ1_0 and TQ2_0 for other backends than CPU
will be added in follow-up pull requests.
* Add AVX2 based implementations for quantize_q8_0_4x8, ggml_gemv_q4_0_8x8_q8_0 and ggml_gemm_q4_0_8x8_q8_0 functions
* Update code to fix issues occuring due to non alignment of elements to be processed as multiple of 16 in MSVC
* Update comments and indentation
* Make updates to reduce number of load instructions
* server : remove multitask from server_task
* refactor completions handler
* fix embeddings
* use res_ok everywhere
* small change for handle_slots_action
* use unordered_set everywhere
* (try) fix test
* no more "mutable" lambda
* Apply suggestions from code review
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* use deque
---------
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* style: format with nixfmt/rfc101-style
* build(nix): Package gguf-py
* build(nix): Refactor to new scope for gguf-py
* build(nix): Exclude gguf-py from devShells
* build(nix): Refactor gguf-py derivation to take in exact deps
* build(nix): Enable pytestCheckHook and pythonImportsCheck for gguf-py
* build(python): Package python scripts with pyproject.toml
* chore: Cleanup
* dev(nix): Break up python/C devShells
* build(python): Relax pytorch version constraint
Nix has an older version
* chore: Move cmake to nativeBuildInputs for devShell
* fmt: Reconcile formatting with rebase
* style: nix fmt
* cleanup: Remove unncessary __init__.py
* chore: Suggestions from review
- Filter out non-source files from llama-scripts flake derivation
- Clean up unused closure
- Remove scripts devShell
* revert: Bad changes
* dev: Simplify devShells, restore the -extra devShell
* build(nix): Add pyyaml for gguf-py
* chore: Remove some unused bindings
* dev: Add tiktoken to -extra devShells
The CUDA nix build broke when we updated nixpkgs in
8cd1bcfd3f. As far as I can tell all
that happened is cudaPackages.autoAddOpenGLRunpathHook got moved to
pkgs.autoAddDriverRunpath. This commit fixes it.
* Introduce ggml_compute_threadpool
- OpenMP functional: check
- Vanilla ggml functional: Check
- ggml w/threadpool functional: Check
- OpenMP no regression: No glaring problems
- Vanilla ggml no regression: No glaring problems
- ggml w/threadpool no regression: No glaring problems
* Minor fixes
* fixed use after release bug
* fixed a harmless race condition
* Fix Android bulid issue
* fix more race conditions
* fix deadlock for cases where cgraph.n_nodes == 1
and fix --poll case
* threadpool: use cpu_get_num_math to set the default number of threadpool threads
This way we avoid using E-Cores and Hyperthreaded siblings.
* bench: create fresh threadpool for each test
For benchmarking it's better to start a fresh pool for each test with the exact number of threads
needed for that test. Having larger pools is suboptimal (causes more load, etc).
* atomics: always use stdatomics with clang and use relaxed memory order when polling in ggml_barrier
This also removes sched_yield() calls from ggml_barrier() to match OpenMP behavior.
* threadpool: make polling the default to match openmp behavior
All command line args now allow for setting poll to 0 (false).
* threadpool: do not wakeup threads in already paused threadpool
* fix potential race condition in check_for_work
* threadpool: do not create two threadpools if their params are identical
* threadpool: reduce pause/resume/wakeup overhead in common cases
We now start threadpool in paused state only if we have two.
The resume is now implicit (ie new work) which allows for reduced locking and context-switch overhead.
* threadpool: add support for hybrid polling
poll params (--poll, ...) now specify "polling level", i.e. how aggresively we poll before waiting on cond.var.
poll=0 means no polling, 1 means poll for 128K rounds then wait, 2 for 256K rounds, ...
The default value of 50 (ie 50x128K rounds) seems like a decent default across modern platforms.
We can tune this further as things evolve.
* threadpool: reduce the number of barrier required
New work is now indicated with an atomic counter that is incremented for
each new graph that needs to be computed.
This removes the need for extra barrier for clearing the "new_work" and
removes the special case for trivial graphs.
* threadpool: remove special-casing for disposable threadpools
With the efficient hybrid polling there is no need to make disposable pools any different.
This simplifies the overall logic and reduces branching.
Include n_threads in debug print for disposable threadpool.
Declare pause and stop flags as atomic_bool
This doesn't actually generate any memory barriers and simply informs
the thread sanitizer that these flags can be written & read by different
threads without locking.
* threadpool: do not clear barrier counters between graphs computes (fixes race with small graphs)
This fixes the race condition with very small graphs where the main thread happens to
start a new graph while the workers are just about to exit from barriers.
* threadpool: use relaxed order for chunk sync
Full memory barrier is an overkill for this since each thread works on different chunk
* threadpool: remove abort_callback from threadpool state
* threadpool: better naming for thread/cpumask releated functions
* threadpool: consistent use of int type for n_threads params
* threadpool: add support for ggml_threadpool_params_default/init
Also removes the need for explicit mask_specified param.
all-zero cpumask means use default (usually inherited) cpu affinity mask.
* threadpool: move typedef into ggml.h
* threadpool: fix apply_priority() function name
* threadpool: fix swift wrapper errors due to n_threads int type cleanup
* threadpool: enable --cpu-mask and other threadpool related options only if threadpool is enabled
* threadpool: replace checks for compute_thread ret code with proper status check
* threadpool: simplify threadpool init logic and fix main thread affinity application
Most of the init code is now exactly the same between threadpool and openmp.
* threadpool: update threadpool resume/pause function names
* threadpool: enable openmp by default for now
* threadpool: don't forget to free workers state when omp is enabled
* threadpool: avoid updating process priority on the platforms that do not require it
On Windows we need to change overall process priority class in order to set thread priorities,
but on Linux, Mac, etc we do not need to touch the overall process settings.
* threadpool: update calling thread prio and affinity only at start/resume
This avoids extra syscalls for each graph_compute()
* llama-bench: turn threadpool params into vectors, add output headers, etc
* llama-bench: add support for cool off between tests --delay
This helps for long running tests on platforms that are thermally limited (phones, laptops, etc).
--delay (disabled by default) introduces the sleep for N seconds before starting each test.
* threadpool: move process priority setting into the apps (bench and cli)
This avoids changing the overall process priority on Windows for the apps
that use ggml/llama.cpp directy.
* threadpool: move all pause/resume logic into ggml
* threadpool: futher api cleanup and prep for future refactoring
All threadpool related functions and structs use ggml_threadpool prefix.
* threadpool: minor indent fixes
* threadpool: improve setprioty error message
* Update examples/llama-bench/llama-bench.cpp
Co-authored-by: slaren <slarengh@gmail.com>
* threadpool: fix indent in set_threadpool call
* use int32_t for n_thread type in public llama.cpp API
* threadpool: use _new and _free instead of _create and _release
* fix two more public APIs to use int32_t for n_threads
* build: set _GNU_SOURCE for Adroid
---------
Co-authored-by: Max Krasnyansky <quic_maxk@quicinc.com>
Co-authored-by: fmz <quic_fzaghlou@quic.com>
Co-authored-by: Max Krasnyansky <max.krasnyansky@gmail.com>
Co-authored-by: slaren <slarengh@gmail.com>
This change fixes a bug where replacing text in a very long string could
cause llama.cpp to hang indefinitely. This is because the algorithm used
was quadratic, due to memmove() when s.replace() is called in a loop. It
seems most search results and LLM responses actually provide the O(n**2)
algorithm, which is a great tragedy. Using a builder string fixes things
* llama : advanced batch splits
This includes equal-sequence-length batch splits which are useful
to simplify recurrent model operators.
* llama : always make recurrent state slots contiguous
* ggml : simplify mamba operators
* llama : fix integer signedness mixing
* llama : logits_all has priority over batch->logits
Otherwise, the server embeddings tests failed.
This was likely an existing problem but was only detected here
because of an additional assertion.
* llama : apply suggestions
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* llama : fix t5 segfault
* llama : fix Mamba session save and restore
* llama : minor cosmetic changes
* llama : rename llama_reorder_outputs to llama_output_reorder
Also move it closer to llama_output_reserve.
* llama : fix pooled embeddings when using batches with equal_seqs
* minor : add struct members for clarity
ggml-ci
* llama : fix T5 segfault again
* llama : fix Mamba pooled embeddings with multiple sequences
Until the pooled embeddings are refactored to allow splitting
across ubatches for causal embeddings,
recurrent models can only process a single sequence per ubatch
when calculating pooled embeddings.
* llama : add llama_model_is_recurrent to simplify figuring that out
This will make it easier to more cleanly support RWKV-v6 and Mamba-2.
* llama : fix simple splits when the batch contains embeddings
---------
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* llama : std::move llm_bigram_bpe from work_queue
This commit updates the retrieval of llm_bigram_bpe objects from
work_queue.top() by using std::move.
The motivation for this is to avoid the copying of the std::string
`text` member of the llm_bigram_bpe struct.
* squash! llama : std::move llm_bigram_bpe from work_queue
Introduced a MovablePriorityQueue class to allow moving elements
out of the priority queue for llm_bigram_bpe.
* squash! llama : std::move llm_bigram_bpe from work_queue
Rename MovablePriorityQueue to lama_priority_queue.
* squash! llama : std::move llm_bigram_bpe from work_queue
Rename lama_priority_queue -> llama_priority_queue.
* llava: Add ACC OP for GPU acceleration to the Vulkan backend in the LLAVA CLIP model.
- The CLIP model now prioritizes the Vulkan backend over the CPU when vulkan available.
- A GGML_OP_ACC shader has been added.
- The encoding performance of the CLIP model improved from 4.2s on the CPU to 0.9s on the GPU.
Signed-off-by: Changyeon Kim <cyzero.kim@samsung.com>
* fix-up coding style.
Signed-off-by: Changyeon Kim <cyzero.kim@samsung.com>
* Fix-up the missing initial parameter to resolve the compilation warning.
Signed-off-by: Changyeon Kim <cyzero.kim@samsung.com>
* [fix] Add missing parameters.
Signed-off-by: Changyeon Kim <cyzero.kim@samsung.com>
* [fix] Use nb1 and nb2 for dst.
Signed-off-by: Changyeon Kim <cyzero.kim@samsung.com>
* Fix check results ggml_acc call
---------
Signed-off-by: Changyeon Kim <cyzero.kim@samsung.com>
Co-authored-by: 0cc4m <picard12@live.de>
* fallback mmvq to mul_mat
* mmvq in cuda path
* Update ggml/src/ggml-sycl.cpp
Co-authored-by: Alberto Cabrera Pérez <alberto.cabrera@codeplay.com>
---------
Co-authored-by: Alberto Cabrera Pérez <alberto.cabrera@codeplay.com>
* server : refactor middleware and /health endpoint
* move "fail_on_no_slot" to /slots
* Update examples/server/server.cpp
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* fix server tests
* fix CI
* update server docs
---------
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* Add support for cpu_get_num_phsical_cores() on Windows
* fix build bug on msys2-clang64 and ucrt64
* avoid adding new function
* add new macros to avoid windows+mingw64
* Add error checking to return default value
* ggml : move rope type enum to ggml.h
This commit moves the `llama_rope_type` enum from `llama.h` to
`ggml.h` and changes its name to `ggml_rope_type`.
The motivation for this change is to address the TODO in `llama.h` and
use the enum in ggml.
Note: This commit does not change the `mode` parameter to be of type
`enum ggml_rope_type`. The name `mode` and its usage suggest that it
might be more generic and possibly used as a bit field for multiple
flags. Further investigation/discussion may be needed to determine
if `mode` should be restricted to RoPE types.
* squash! ggml : move rope type enum to ggml.h
This commit removes GGML_ROPE_TYPE_NONE and GGML_ROPE_TYPE_GLM from
ggml.h, and back the llama_rope_type enum.
I've kept the assert for GGML_ROPE_TYPE_GLM as I'm not sure if it is
safe to remove it yet.
* squash! ggml : move rope type enum to ggml.h
This commit removes the enum ggml_rope_type from ggml.h and replaces it
with a define (GGML_ROPE_TYPE_NEOX). This define is used in the code to
check if the mode is set to GPT-NeoX. Also the enum llama_rope_type has
been updated to reflect this change.
* squash! ggml : move rope type enum to ggml.h
This commit contains a suggestion enable the GGML_ROPE_TYPE_NEOX
macro/define to be passed to the shader compiler.
* squash! ggml : move rope type enum to ggml.h
This commit fixes the editorconfig-checker warnings.
* squash! ggml : move rope type enum to ggml.h
Update comment for ggml_rope function.
* Revert "squash! ggml : move rope type enum to ggml.h"
This reverts commit 6261222bd0.
* squash! ggml : move rope type enum to ggml.h
Add GGML_ROPE_TYPE_NEOX to rope_common.comp.
* remove extra line
---------
Co-authored-by: slaren <slarengh@gmail.com>
* readme: introduce gpustack
GPUStack is an open-source GPU cluster manager for running large
language models, which uses llama.cpp as the backend.
Signed-off-by: thxCode <thxcode0824@gmail.com>
* readme: introduce gguf-parser
GGUF Parser is a tool to review/check the GGUF file and estimate the
memory usage without downloading the whole model.
Signed-off-by: thxCode <thxcode0824@gmail.com>
---------
Signed-off-by: thxCode <thxcode0824@gmail.com>
* Optimize Vulkan backend for better CPU performance and less GPU synchronization overhead.
- Allocation overhead for the temporary std::vectors was easily detectable with a sampling profiler and simple to remove.
- ggml_vk_sync_buffer introduce a full pipeline sync which has a significant cost on the GPU side, sometimes larger than the actual kernel execution. Adding only barriers for shader read/writes and transfers seems to be sufficient looking at the code which either launches compute kernels or copies tensors.
* Fix small typo
---------
Co-authored-by: 0cc4m <picard12@live.de>
* gguf-py : add T5ENCODER model architecture
* common : call llama_decode() during warmup only if the model has decoder
* convert-hf : add T5EncoderModel
* llama : add llama_model_has_decoder() API function
* llama : split build_t5() into build_t5_encoder() and build_t5_decoder()
* llama : add support for LLM_ARCH_T5ENCODER
* llama-embedding : add support for LLAMA_POOLING_TYPE_NONE
* llama-embedding : add support for encoder-only models
---------
Co-authored-by: Stanisław Szymczyk <sszymczy@gmail.com>
* ggml: use vulkan as gpu backend when available
Signed-off-by: Matt Stephenson <mstephenson6@users.noreply.github.com>
* whisper: enable using vk as default buffer type
Signed-off-by: Matt Stephenson <mstephenson6@users.noreply.github.com>
---------
Signed-off-by: Matt Stephenson <mstephenson6@users.noreply.github.com>
This commit adds the `--pooling` option to the README.md file in the
`examples/embedding` directory.
The motivation for adding this options is that currently if the model
used does not specify a pooling type the embedding example will fail
with the following error message:
```console
main: error: pooling type NONE not supported
```
This commit also updates the name of the executable in the examples
section.
* gguf-py : use classes for quants
* convert_hf : simplify internal quantization type selection
* gguf-py : fix flake8 lint
* gguf-py : fix BF16 numpy view type
* gguf-py : remove LlamaFileTypeMap
Too specific to 'llama.cpp', and would be a maintenance burden
to keep up to date.
* gguf-py : add generic quantize and dequantize functions
The quant classes no longer need to be known,
only the target or the source type,
for 'quantize' and 'dequantize', respectively.
When using CMake to build with Vulkan support, compiling
vulkan-shaders-gen fails due to missing a CMakeLists.txt specification
to link vulkan-shaders-gen with the threading library, resulting in the
following error.
[5/172] Linking CXX executable bin/vulkan-shaders-gen
FAILED: bin/vulkan-shaders-gen
: && /usr/bin/c++ ggml/src/vulkan-shaders/CMakeFiles/vulkan-shaders-gen.dir/vulkan-shaders-gen.cpp.o -o bin/vulkan-shaders-gen && :
ld: error: undefined symbol: pthread_create
>>> referenced by vulkan-shaders-gen.cpp
>>> ggml/src/vulkan-shaders/CMakeFiles/vulkan-shaders-gen.dir/vulkan-shaders-gen.cpp.o:(std::__1::__libcpp_thread_create[abi:se180100](pthread**,
>>> void* (*)(void*), void*))
c++: error: linker command failed with exit code 1 (use -v to see invocation)
[6/172] Generating build details from Git
-- Found Git: /usr/local/bin/git (found version "2.45.2")
ninja: build stopped: subcommand failed.
Add the CMakeLists.txt specification to link vulkan-shaders-gen with the
threading library and fix the above error.
Fixes#8834
* Fix compilation issue in `vulkan-shaders-gen`
e31a4f6797 broke compilation on w64devkit. Including `algorithm` seems to fix that.
* Guard it under `#ifdef _WIN32`
* common : Changed tuple to struct (TODO fix)
Use struct `llama_init_result` to replace the previous
std::tuple<struct llama_model *, struct llama_context *>
* delete llama_init_default_params()
* delete the extra whitespace
ramalama is a repo agnostic boring CLI tool that supports pulling from
ollama, huggingface and oci registries.
Signed-off-by: Eric Curtin <ecurtin@redhat.com>
* gguf-py, llama : add constants and methods related to Llama-3.1 <|eom_id|> token
* llama : find Llama-3.1 <|eom_id|> token id during vocab loading
* llama-vocab : add Llama-3.1 <|eom_id|> token to the set of tokens stopping the generation
---------
Co-authored-by: Stanisław Szymczyk <sszymczy@gmail.com>
* Fix Vulkan repeat op
* Implement Vulkan concat op
* Delete old Vulkan shader generator
* Implement Vulkan im2col op
* Implement Vulkan unary gelu_quick op
* Implement Vulkan group_norm op
* Implement Vulkan timestep_embedding op
* Implement Vulkan upscale op
* Fix Vulkan vk_context tensor extra index issue
* Fix Vulkan matmul shader parameter bug
* Properly fix Vulkan matmul shader parameter bug
* Add Vulkan ADD f16 + f32 -> f16 operator support
* Implement Vulkan tanh op
* Fix Vulkan group count too large Validation error on non-Nvidia GPUs
* Throw error when too much memory is requested
* Fix another Vulkan group count too large Validation error on non-Nvidia GPUs
* Fix matmul MMQ condition
* Implement Vulkan pad op
* Fix Vulkan crash when tensor is used multiple times in a compute graph
* Add Vulkan CONCAT f16 + f16 -> f16 op
* Add Vulkan LEAKY_RELU op
This commit moves the comment for the c parameter from ggml_rope to
ggml_rope_ext. The comment is currently incorrect as ggml_rope does not
have a c parameter (freq_factors tensor).
Signed-off-by: Daniel Bevenius <daniel.bevenius@gmail.com>
* [example] batched-bench "segmentation fault"
When `llama-batched-bench` is invoked _without_ setting `-npl`, "number
of parallel prompts", it segfaults.
The segfault is caused by invoking `max_element()` on a zero-length
vector, `n_pl`
This commit addresses that by first checking to see if the number of
parallel prompts is zero, and if so sets the maximum sequence size to 1;
otherwise, sets it to the original, the result of `max_element()`.
Fixes, when running `lldb build/bin/llama-batched-bench -- -m models/Meta-Llama-3-8B.gguf`
```
* thread #1, queue = 'com.apple.main-thread', stop reason = EXC_BAD_ACCESS (code=1, address=0x0)
frame #0: 0x000000010000366c llama-batched-bench`main(argc=3, argv=0x000000016fdff268) at batched-bench.cpp:72:28
69 llama_context_params ctx_params = llama_context_params_from_gpt_params(params);
70
71 // ensure enough sequences are available
-> 72 ctx_params.n_seq_max = *std::max_element(n_pl.begin(), n_pl.end());
```
* Update examples/batched-bench/batched-bench.cpp
Co-authored-by: compilade <git@compilade.net>
---------
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
Co-authored-by: compilade <git@compilade.net>
* ggml : reading the runtime sve config of the cpu
* change to one time init to prevent performance drop
* prefix variable to avoid possible conflicts
* revert xxhash fix and add brackets
---------
Co-authored-by: domke <673751-domke@users.noreply.gitlab.com>
* add truncate_bf16
* truncate intermediate fp32 if converting bf16 to bf16
* fix masking in __compute_fp32_to_bf16
* np.int16 no longer used
* missing cast and additional numpy 2.x fix
* ggml-impl : do not flush bf16 subnormals to zero
* ggml : add reference fp32 to bf16 conversion
The fast version is no longer equivalent for all platforms
because of the handling of subnormal values.
* gguf-py : remove flush to zero for bf16 subnormals
* gguf-py : remove float32 truncation to bf16
Rounding achieves the same thing in the cases where this was used.
* missed prototype update in merge
* merge cleanup
---------
Co-authored-by: Francis Couture-Harpin <git@compilade.net>
* Adding support for unified memory
* adding again the documentation about unified memory
* refactoring: Moved the unified memory code in the correct location.
* Fixed compilation error when using hipblas
* cleaning up the documentation
* Updating the documentation
Co-authored-by: Johannes Gäßler <johannesg@5d6.de>
* adding one more case where the PR should not be enabled
---------
Co-authored-by: matteo serva <matteo.serva@gmail.com>
Co-authored-by: Johannes Gäßler <johannesg@5d6.de>
* Fix potential race condition as pointed out by @fairydreaming in #8776
* Reference the .o rather than rebuilding every time.
* Adding in CXXFLAGS and LDFLAGS
* Removing unnecessary linker flags.
* gguf_writer.py: add_array() should not add to kv store if empty
* Apply suggestions from code review
I was wondering if there was a specific reason for `if val` but good to hear we can safely use `len(val == 0`
Co-authored-by: compilade <git@compilade.net>
---------
Co-authored-by: compilade <git@compilade.net>
In these codes, we want to retain the value that they previously held
when mask[i] is false. So we should use undisturbed. With the default
agnostic policy of rvv intrinsic, these values can be held or be
written with 1s.
Co-authored-by: carter.li <carter.li@starfivetech.com>
* chore: Fix compiler warnings, add help text, improve CLI options
* Add prototypes for function definitions
* Invert logic of --no-clean option to be more intuitive
* Provide a new help prompt with clear instructions
* chore : Add ignore rule for vulkan shader generator
Signed-off-by: teleprint-me <77757836+teleprint-me@users.noreply.github.com>
* Update ggml/src/vulkan-shaders/vulkan-shaders-gen.cpp
Co-authored-by: 0cc4m <picard12@live.de>
* chore : Remove void and apply C++ style empty parameters
* chore : Remove void and apply C++ style empty parameters
---------
Signed-off-by: teleprint-me <77757836+teleprint-me@users.noreply.github.com>
Co-authored-by: 0cc4m <picard12@live.de>
* llama : refactor session file management
* llama : saving and restoring state checks for overflow
The size of the buffers should now be given to the functions working
with them, otherwise a truncated file could cause out of bound reads.
* llama : stream from session file instead of copying into a big buffer
Loading session files should no longer cause a memory usage spike.
* llama : llama_state_get_size returns the actual size instead of max
This is a breaking change, but makes that function *much* easier
to keep up to date, and it also makes it reflect the behavior
of llama_state_seq_get_size.
* llama : share code between whole and seq_id-specific state saving
Both session file types now use a more similar format.
* llama : no longer store all hparams in session files
Instead, the model arch name is stored.
The layer count and the embedding dimensions of the KV cache
are still verified when loading.
Storing all the hparams is not necessary.
* llama : fix uint64_t format type
* llama : various integer type cast and format string fixes
Some platforms use "%lu" and others "%llu" for uint64_t.
Not sure how to handle that, so casting to size_t when displaying errors.
* llama : remove _context suffix for llama_data_context
* llama : fix session file loading
llama_state_get_size cannot be used to get the max size anymore.
* llama : more graceful error handling of invalid session files
* llama : remove LLAMA_MAX_RNG_STATE
It's no longer necessary to limit the size of the RNG state,
because the max size of session files is not estimated anymore.
* llama : cast seq_id in comparison with unsigned n_seq_max
* Update doc for MUSA
Signed-off-by: Xiaodong Ye <xiaodong.ye@mthreads.com>
* Add GGML_MUSA in Makefile
Signed-off-by: Xiaodong Ye <xiaodong.ye@mthreads.com>
* Add GGML_MUSA in CMake
Signed-off-by: Xiaodong Ye <xiaodong.ye@mthreads.com>
* CUDA => MUSA
Signed-off-by: Xiaodong Ye <xiaodong.ye@mthreads.com>
* MUSA adds support for __vsubss4
Signed-off-by: Xiaodong Ye <xiaodong.ye@mthreads.com>
* Fix CI build failure
Signed-off-by: Xiaodong Ye <xiaodong.ye@mthreads.com>
---------
Signed-off-by: Xiaodong Ye <xiaodong.ye@mthreads.com>
Apply a loop tiling technique to the generic path, which provides
performance upside for ISAs with enough registers to take advantage
of it. Also helps the compiler optimize this path.
* Add support for float16 tensors in 1d pooling operations
* Add support for float16 input tensors in 2d pooling operations
* code cleanup
remove unnecessary casting during srow ptr initialization
---------
Co-authored-by: vanaka11 <vanaka1189@gmail.com>
This prevents invalid frees when destroying a partially initialized
vk_buffer_struct. For example, this could happen in ggml_vk_create_buffer
when running out of device memory.
Co-authored-by: Tony Wasserka <neobrain@users.noreply.github.com>
This commit removes an UNUSED macro call that is not needed as the
variable n0 is used in the code and will not produce a warning.
Signed-off-by: Daniel Bevenius <daniel.bevenius@gmail.com>
* Add llama 3.1 rope scaling factors to llama conversion and inference
This commit generates the rope factors on conversion and adds them to the resulting model as a tensor. At inference time, these factors are passed to the `ggml_rope_ext` rope oepration, improving results for context windows above 8192
* Update convert_hf_to_gguf.py
Co-authored-by: compilade <git@compilade.net>
* address comments
* address comments
* Update src/llama.cpp
Co-authored-by: compilade <git@compilade.net>
* Update convert_hf_to_gguf.py
Co-authored-by: compilade <git@compilade.net>
---------
Co-authored-by: compilade <git@compilade.net>
This commit adds a --no-warmup option for llama-cli.
The motivation for this is that it can be convenient to skip the
warmup llama_decode call when debugging.
Signed-off-by: Daniel Bevenius <daniel.bevenius@gmail.com>
`ggml_init` can fail if no unused context is found. In that case, a NULL-pointer deref will happen later in the code during a call to `ggml_set_on_alloc`.
This fixes it by bailing out if no context is found.
* Improvements for Windows with Snapdragon X
* Revert "Improvements for Windows with Snapdragon X"
This reverts commit bf21397ae5.
* Improvements for Windows with Snapdragon X
* WOA build clarifications
* WIndows on ARM build clarifications
* cmake build for Windows clarifications
* Update docs/build.md
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
---------
Co-authored-by: AndreasKunar <andreaskmsn.com>
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
The check gating the use of `__builtin_amdgc_sdot4` specifically checks for gfx1030. This causes a severe perf regression for anything gfx103? that's not gfx1030 and not using `HSA_OVERRIDE_GFX_VERSION` (if you've built ROCm to support it). We already have a generic RDNA2 define, let's use it.
* Superflous parens in conditionals were removed.
* Unused args in function were removed.
* Replaced unused `idx` var with `_`
* Initializing file_format and format_version attributes
* Renaming constant to capitals
* Preventing redefinition of the `f` var
Signed-off-by: Jiri Podivin <jpodivin@redhat.com>
Changes:
- Move each example into its own function. This makes the code much
easier to read and understand.
- Make the program easy to only run one test by commenting out function
calls in main().
- Make the output easy to parse by indenting the output for each example.
- Add shebang and +x bit to make it clear it's an executable.
- Make the host configurable via --host with a default 127.0.0.1:8080.
- Make the code look in the tools list to call the registered tool,
instead of hardcoding the returned values. This makes the code more
copy-pastable.
- Add error checking, so that the program exits 1 if the LLM didn't
returned expected values. It's super useful to check for correctness.
Testing:
- Tested with Mistral-7B-Instruct-v0.3 in F16 and Q5_K_M and
Meta-Llama-3-8B-Instruct in F16 and Q5_K_M.
- I did not observe a failure even once in Mistral-7B-Instruct-v0.3.
- Llama-3 failed about a third of the time in example_concurrent: it
only returned one call instead of 3. Even for F16.
Potential follow ups:
- Do not fix the prompt encoding yet. Surprisingly it mostly works even
if the prompt encoding is not model optimized.
- Add chained answer and response.
Test only change.
* gguf-py : fix some metadata name extraction edge cases
* convert_lora : use the lora dir for the model card path
* gguf-py : more metadata edge cases fixes
Multiple finetune versions are now joined together,
and the removal of the basename annotation on trailing versions
is more robust.
* gguf-py : add more name metadata extraction tests
* convert_lora : fix default filename
The default filename was previously hardcoded.
* convert_hf : Model.fname_out can no longer be None
* gguf-py : do not use title case for naming convention
Some models use acronyms in lowercase,
which can't be title-cased like other words,
so it's best to simply use the same case
as in the original model name.
Note that the size label still has an uppercased suffix
to make it distinguishable from the context size of a finetune.
* convert_hf : fix Gemma v1 conversion
* convert_hf : allow renaming tokens, but with a warning
* convert_hf : fix Gemma v1 not setting BOS and EOS tokens
* fix continuing generating blank lines after getting EOT token or EOS token from LLM
* change variable name to is_done (variable name suggested by ggerganov)
* minor : fix trailing whitespace
* minor : add space
---------
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
Main thing is that the default output filename will take this form
{name}{parameters}{finetune}{version}{encoding}{kind}
In addition this add and remove some entries in the KV store and adds a metadata class with automatic heuristics capability to derive some values based on model card content
* No Change:
- Internal GGUF Spec
- `general.architecture`
- `general.quantization_version`
- `general.alignment`
- `general.file_type`
- General Model Details
- `general.name`
- `general.author`
- `general.version`
- `general.description`
- Licensing details
- `general.license`
- Typically represents the converted GGUF repo (Unless made from scratch)
- `general.url`
- Model Source during conversion
- `general.source.url`
* Removed:
- Model Source during conversion
- `general.source.huggingface.repository`
* Added:
- General Model Details
- `general.organization`
- `general.finetune`
- `general.basename`
- `general.quantized_by`
- `general.size_label`
- Licensing details
- `general.license.name`
- `general.license.link`
- Typically represents the converted GGUF repo (Unless made from scratch)
- `general.doi`
- `general.uuid`
- `general.repo_url`
- Model Source during conversion
- `general.source.doi`
- `general.source.uuid`
- `general.source.repo_url`
- Base Model Source
- `general.base_model.count`
- `general.base_model.{id}.name`
- `general.base_model.{id}.author`
- `general.base_model.{id}.version`
- `general.base_model.{id}.organization`
- `general.base_model.{id}.url` (Model Website/Paper)
- `general.base_model.{id}.doi`
- `general.base_model.{id}.uuid`
- `general.base_model.{id}.repo_url` (Model Source Repository (git/svn/etc...))
- Array based KV stores
- `general.tags`
- `general.languages`
- `general.datasets`
---------
Co-authored-by: compilade <git@compilade.net>
Co-authored-by: Xuan Son Nguyen <thichthat@gmail.com>
* [CANN] Add Ascend NPU backend
Ascend is a full-stack AI computing infrastructure for industry
applications and services based on Huawei Ascend processors and
software.
CANN (Compute Architecture of Neural Networks), developped by
Huawei, is a heterogeneous computing architecture for AI.
Co-authored-by: wangshuai09 <391746016@qq.com>
* delete trailing whitespaces
* Modify the code based on review comment
* Rename LLAMA_CANN to GGML_CANN
* Make ggml-common.h private
* add ggml_cann prefix for acl funcs
* Add logging for CANN backend
* Delete Trailing whitespace
---------
Co-authored-by: wangshuai09 <391746016@qq.com>
* Update clib.json to point to Cyan4973 original xxhash
Convinced Cyan4973 to add clib.json directly to his repo, so can now point the clib package directly to him now. Previously pointed to my fork with the clib.json package metadata
https://github.com/Cyan4973/xxHash/pull/954
* gguf-hash: readme update to point to Cyan4973 xxHash repo [no ci]
The --help option on export-lora isn't accepted as valid. The help still gets displayed by default, but the script exits with an error message and nonzero status.
* convert_hf : faster lazy safetensors
This makes '--dry-run' much, much faster.
* convert_hf : fix memory leak in lazy MoE conversion
The '_lazy' queue was sometimes self-referential,
which caused reference cycles of objects old enough
to avoid garbage collection until potential memory exhaustion.
* lora: load to devide buft
* add patch tensor function
* correct tensor patch
* llama_lora_adapter_apply
* correct ggml_backend_tensor_copy
* add llm_build_mm
* fix auto merge
* update based on review comments
* add convert script
* no more transpose A
* add f16 convert
* add metadata check
* add sanity check
* fix ftype
* add requirements
* fix requirements
* fix outfile
* conversion: only allow selected models
* fix types
* cuda : do not use dmmv if the tensor does not have enough cols
* llama : lora fixes
* do not disable mmap with lora
Co-authored-by: slaren <slarengh@gmail.com>
* llm_build_lora_mm_id
* convert_lora : MoE LoRA conversion support
* convert_lora : prefer safetensors, similarly to convert_hf
* convert_hf : simplify modify_tensors for InternLM2
* convert_lora : lazy conversion
* llama : load and use alpha from LoRA adapters
* llama : use llm_build_lora_mm in most model graphs
* auto scale
* Revert "auto scale"
This reverts commit 42415a4874.
* remove redundant params
* Apply suggestions from code review
Co-authored-by: slaren <slarengh@gmail.com>
* change kv metadata
* move add_type to __init__
* convert_hf : move add_type to main()
* convert_lora : use the GGUFWriter from Model instead of overwriting it
---------
Co-authored-by: slaren <slarengh@gmail.com>
Co-authored-by: Francis Couture-Harpin <git@compilade.net>
This commit adds a macro guard to pragma GCC to avoid the following
warning on windows:
```console
C:\llama.cpp\ggml\src\ggml-aarch64.c(17,9): warning C4068:
unknown pragma 'GCC' [C:\lama.cpp\build\ggml\src\ggml.vcxproj]
```
The README.md had a stale information. In particular, the --ctx-size
"defaults to 512" confused me and I had to check the code to confirm
this was false. This the server is evolving rapidly, it's probably
better to keep the source of truth at a single place (in the source) and
generate the README.md based on that.
Did:
make llama-server
./llama-server --help > t.txt
vimdiff t.txt examples/server/README.md
I copied the content inside a backquote block. I would have preferred
proper text but it would require a fair amount of surgery to make the
current output compatible with markdown. A follow up could be to
automate this process with a script.
No functional change.
* 9B - query_pre_attn_scalar = 256 not 224
See 03e657582d
Gemma 9b should use 256 and not 224 (self.config.hidden_size // self.config.num_attention_heads)
* llama : fix Gemma-2 Query scaling factor
ggml-ci
---------
Co-authored-by: Daniel Han <danielhanchen@gmail.com>
* llama : fix mpt and olmo pre-tokenizer
* llama : pre-tokenize non-special user-defined tokens first
* llama : fix detection of control-like user-defined tokens
* convert_hf : identify which user-defined tokens are control tokens
Only used in _set_vocab_gpt2() for now.
* convert_hf : identify more added control tokens for SPM tokenziers
This makes Gemma and Gemma-2 tokenize pretty much EVERYTHING correctly,
including HTML tags and consecutive spaces,
but it unfortunately requires model re-conversion.
There seems to be a weird behavior of the HF tokenizer for Gemma,
which prefers to use the 16-space token over more lengthy space tokens,
while using the SentencePiece tokenizer does not do this.
(the implementation in llama.cpp has the same behavior as SentencePiece)
* llama : fix wrong pre-tokenization of byte tokens
* llama : fix Viking pre-tokenizer regex
The order was previously wrong, which caused errors in some tests.
* llama : fix command-r detokenization
* convert_hf : reduce usages of the UNKNOWN token type
* llama : add UNKNOWN tokens in the special tokens cache
* convert_hf : reduce usages of UNKNOWN for InternLM2
This makes the changes from #8321 more consistent
with the other changes made here.
* test-tokenizer-random : reduce potential confilcts with #8379
* test-tokenizer-random : add a failing edge case for falcon
* server : handle content array in chat API
* Update examples/server/utils.hpp
Co-authored-by: Xuan Son Nguyen <thichthat@gmail.com>
---------
Co-authored-by: Xuan Son Nguyen <thichthat@gmail.com>
This commit updates the _try_copy lambda and moves the unary minus
operator to after the cast to int32_t.
The motivation for this that currently the following warning is
generated on windows:
```console
llama.cpp\src\llama.cpp(21147,30): warning C4146: unary minus operator
applied to unsigned type, result still unsigned
```
Commit b0a4699 changed the name of this script from convert-hf-to-gguf.py to
convert_hf_to_gguf.py breaking how convert is called from within a Docker
container.
The <filename> token used by Refact doesn't serve
the same purpose as the <file_separator> from CodeGemma.
Signed-off-by: Jiri Podivin <jpodivin@redhat.com>
* fix part of mul_mat_id
* skip the bfloat 16 sycl ut
Signed-off-by: Chen Xi <xi2chen@intel.com>
---------
Signed-off-by: Chen Xi <xi2chen@intel.com>
Co-authored-by: Meng, Hengyu <hengyu.meng@intel.com>
Co-authored-by: Chen Xi <xi2chen@intel.com>
* cuda : suppress 'noreturn' warn in no_device_code
This commit adds a while(true) loop to the no_device_code function in
common.cuh. This is done to suppress the warning:
```console
/ggml/src/ggml-cuda/template-instances/../common.cuh:346:1: warning:
function declared 'noreturn' should not return [-Winvalid-noreturn]
346 | }
| ^
```
The motivation for this is to reduce the number of warnings when
compilng with GGML_HIPBLAS=ON.
Signed-off-by: Daniel Bevenius <daniel.bevenius@gmail.com>
* squash! cuda : suppress 'noreturn' warn in no_device_code
Update __trap macro instead of using a while loop to suppress the
warning.
Signed-off-by: Daniel Bevenius <daniel.bevenius@gmail.com>
---------
Signed-off-by: Daniel Bevenius <daniel.bevenius@gmail.com>
* Modify the deprecation-warning 'main' binary to build every time, instead of only when a legacy binary is present. This is to help users of tutorials and other instruction sets from knowing what to do when the 'main' binary is missing and they are trying to follow instructions.
* Adjusting 'server' name-deprecation binary to build all the time, similar to the 'main' legacy name binary.
* Arm AArch64: optimized GEMV and GEMM kernels for q4_0_q8_0, and q8_0_q8_0 quantization
* Arm AArch64: add optimized GEMV and GEMM asm kernels for q4_0_q8_0 quantization and refactor code to address llama.cpp pr#5780 suggestions
* Arm AArch64: add optimized GEMV and GEMM asm kernels for q4_0_q8_0 quantization and refactor code to address llama.cpp pr#5780 suggestions
* Arm AArch64: add optimized GEMV and GEMM asm kernels for q4_0_q8_0 quantization and refactor code to address llama.cpp pr#5780 suggestions
* Arm AArch64: add optimized GEMV and GEMM asm kernels for q4_0_q8_0 quantization and refactor code to address llama.cpp pr#5780 suggestions
* Arm AArch64: add copyright claim only to ggml-aarch64.cpp and ggml-aarch64.h files
* Arm AArch64: minor code refactoring for rebase
* Arm AArch64: minor code refactoring for resolving a build issue with cmake
* Arm AArch64: minor code refactoring to split the Q4_0_AARC64 type into three separate types: Q4_0_4_4, Q4_0_4_8, and Q4_0_8_8
* Arm AArch64: minor code change for resolving a build issue with server-windows
* retrigger checks
* Arm AArch64: minor code changes for rebase
* Arm AArch64: minor changes to skip the pr#7433 vec_dot code for arm cpus with SVE VL not equal to 256 bits
* Arm AArch64: remove stale LLAMA_QKK_64 from CMakeLists.txt and delete build.zig
* Arm AArch64: add reference scalar gemm and gemv, and avoid dynamic memory allocations during quantization for Q4_0_4_4, Q4_0_4_8, and Q4_0_8_8
* Arm AArch64: add multithreaded quantization support for the new types: Q4_0_4_4, Q4_0_4_8, and Q4_0_8_8
* Arm AArch64: minor code refactoring
* Arm AArch64: simplify logic for calling gemm and gemv functions in ggml_compute_forward_mul_mat
* Arm AArch64: minimize changes in ggml_compute_forward_mul_mat
* Arm AArch64: minor code refactoring, and add reference scalar code to quantize routines for new quant types
* Arm AArch64: minor code refactoring
* Arm AArch64: minor code refactoring
* Arm AArch64: minor code refactoring
* rebase on the latest master commit 3fd62a6 and adapt to the new directory structure
* Arm AArch64: remove a redundant comment
* Arm AArch64: add pragma in ggml-aarch64.c to turn -Woverlength-strings warning off
* Arm AArch64: use __aarch64__ check to guard 64-bit neon kernels
* Arm AArch64: update docs/build.md README to include compile time flags for buiilding the Q4_0_4_4 quant type
* Adding a simple program to provide a deprecation warning that can exist to help people notice the binary name change from #7809 and migrate to the new filenames.
* Build legacy replacement binaries only if they already exist. Check for their existence every time so that they are not ignored.
* conv transpose 1d passing test for 1d input and kernel
* working for different input and output channel counts, added test for variable stride
* initial draft appears to work with stride other than 1
* working with all old and new conv1d tests
* added a test for large tensors
* removed use cuda hardcoding
* restored test-conv-transpose.c
* removed unused arugments, and fixed bug where test failure would cause subsequent tests to fail
* fixed accumulator bug
* added test to test-backend-ops
* fixed mistake
* addressed review
* fixed includes
* removed blank lines
* style and warning fixes
* return failure when test fails
* fix supports_op
---------
Co-authored-by: slaren <slarengh@gmail.com>
`emplace_back` repeatedly-called is slower than preallocating the vector to the vocab size and directly inserting the data. Some rudimentary profiling with `chrono` improves the performance of this block of code from ~500us/op to ~40us/op.
Overall, this slightly improves the sampling performance which has a more substantial impact for the `examples/lookahead` implementation -- I am able to see a ~10% performance boost in lookahead inference.
* py : type-check all Python scripts with Pyright
* server-tests : use trailing slash in openai base_url
* server-tests : add more type annotations
* server-tests : strip "chat" from base_url in oai_chat_completions
* server-tests : model metadata is a dict
* ci : disable pip cache in type-check workflow
The cache is not shared between branches, and it's 250MB in size,
so it would become quite a big part of the 10GB cache limit of the repo.
* py : fix new type errors from master branch
* tests : fix test-tokenizer-random.py
Apparently, gcc applies optimisations even when pre-processing,
which confuses pycparser.
* ci : only show warnings and errors in python type-check
The "information" level otherwise has entries
from 'examples/pydantic_models_to_grammar.py',
which could be confusing for someone trying to figure out what failed,
considering that these messages can safely be ignored
even though they look like errors.
CLI to hash GGUF files to detect difference on a per model and per tensor level
The hash type we support is:
- `--xxh64`: use xhash 64bit hash mode (default)
- `--sha1`: use sha1
- `--uuid`: use uuid
- `--sha256`: use sha256
While most POSIX systems already have hash checking programs like sha256sum, it
is designed to check entire files. This is not ideal for our purpose if we want
to check for consistency of the tensor data even if the metadata content of the
gguf KV store has been updated.
This program is designed to hash a gguf tensor payload on a 'per tensor layer'
in addition to a 'entire tensor model' hash. The intent is that the entire
tensor layer can be checked first but if there is any detected inconsistencies,
then the per tensor hash can be used to narrow down the specific tensor layer
that has inconsistencies.
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* add chatglm3-6b model support huggingface model:
https://hf-mirror.com/THUDM/chatglm3-6b
Signed-off-by: XingXing Qiao <qiaoxx@dingdao.com>
* remove .rotary_pos_emb.inv_freq and unuse code for chatglm3 model
Signed-off-by: XingXing Qiao <qiaoxx@dingdao.com>
* fix lint error
Signed-off-by: XingXing Qiao <qiaoxx@dingdao.com>
* optimize convert-hf-to-gguf.py for chatglm model
Signed-off-by: XingXing Qiao <qiaoxx@dingdao.com>
* support glm-4-9b-chat
Signed-off-by: XingXing Qiao <qiaoxx@dingdao.com>
* fix eos tokens to glm4
* remove unused log
* add preprocess to chatglm3 and chatglm4
* add eos_id_list to llama.cpp
* fix code style
* fix code style
* fix conflicts
* fix conflicts
* Revert "add eos_id_list to llama.cpp"
This reverts commit 3a4d5790bf.
* set <|endoftext|> as eos and <|user|> as eot
* fix chat template bug
* add comment to glm prefix and suffix
* fix conflicts and add rope_ratio & ChatGLMForConditionalGeneration
* fix chat template bug
* fix codestyle
* fix conflicts
* modified the general name of glm model
* fix conflicts
* remove prefix and suffix
* use normal glm4 chattempalte & use LLM_FFN_SWIGLU in phi3
* fix: resolve Flake8 errors in `convert-hf-to-gguf.py`
- Fix E302 by adding two blank lines before top-level function definitions
- Replace print statements to fix NP100
- Fix E303 by ensuring only one blank line between lines of code
* fix rope ratio to solve incorrect answers
* fix by comments
---------
Signed-off-by: XingXing Qiao <qiaoxx@dingdao.com>
Co-authored-by: XingXing Qiao <qiaoxx@dingdao.com>
Co-authored-by: Umpire2018 <138990495+Umpire2018@users.noreply.github.com>
This patch replaces an old commad "main" with "llama-cli"
in finetune.sh.
The part that I fixed is comment, so it doesn't change
the script.
Signed-off-by: Masanari Iida <standby24x7@gmail.com>
* server: Retrieve prompt template in /props
This PR adds the following:
- Expose the model's Jinja2 prompt template from the model in the /props endpoint.
- Change log-level from Error to Warning for warning about template mismatch.
The front-end stands a better chance of actually executing the Jinja template format correctly. Server is currently just guessing it.
Ideally this should have been inside a JSON block that expose the same key/value pairs as listed during startup in "llm_load_print_meta" function.
* Make string buffer dynamic
* Add doc and better string handling
* Using chat_template naming convention
* Use intermediate vector for string assignment
* added support for Authorization Bearer tokens
* removed auth_token, removed set_ function, other small fixes
* Update common/common.cpp
---------
Co-authored-by: Xuan Son Nguyen <thichthat@gmail.com>
* llama : add early return for empty range
This commit adds an early return to the llama_kv_cache_seq_add and
llama_kv_cache_seq_div functions.
The motivation for adding this is to avoid looping over the cache
when the range is empty. I ran into this when using the self-extend
feature in main.cpp.
Signed-off-by: Daniel Bevenius <daniel.bevenius@gmail.com>
* llama : add static_cast to fix CI warning/error
This commit attempts to fix the following warning/error:
```console
src/llama.cpp:7271:31: error:
comparison of integer expressions of different signedness:
‘int’ and ‘uint32_t’ {aka ‘unsigned int’} [-Werror=sign-compare]
7271 | if (i < hparams.n_layer_dense_lead) {
| ~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~
```
This can be reproduced locally by setting -Wsign-compare in the
Makefile.
Signed-off-by: Daniel Bevenius <daniel.bevenius@gmail.com>
* squash! llama : add early return for empty range
Remove the setting of cache.head to 0 when the range is empty.
Signed-off-by: Daniel Bevenius <daniel.bevenius@gmail.com>
* Update src/llama.cpp
---------
Signed-off-by: Daniel Bevenius <daniel.bevenius@gmail.com>
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* Add llama_detokenize():
- Update header files location
- UNKNOWN and CONTROL are 'special pieces'
- Remove space after UNKNOWN and CONTROL
- Refactor llama_token_to_piece()
- Add flag: clean_up_tokenization_spaces
- Symmetric params for llama_tokenize() and llama_detokenize()
* Update and fix tokenizer tests:
- Using llama_detokenize()
- Unexpected vocab type as test fail instead of error
- Useful when automating tests:
- If you don't know in advance the vocab type
- Differenciate other loading errors
- Skip unicode surrogaes and undefined
- Gracefully exit threads
- Using exit() is throwing random exceptions
- Clean old known problematic codepoints
- Minor: confusing hexadecimal codepoint
* Update bruteforce random tests
- Add detokenizer checks
- New generator: ascii_lr_strip
- New generator: apostrophe
- Add more vocabs files
- Detokenize special tokens.
- Replace errors with '\uFFFD' when detokenizing to 'utf-8'
- More edge cases
- Better detokenization results check
* Fix add_space_prefix, set false by default
* Better leading space removal
* Do not remove space when decoding special tokens
* Bugfix: custom regexs splits undefined unicode codepoints
* 'viking' detokenizer clean spaces
* passkey : add short intro to README.md [no-ci]
This commit adds a short introduction to the README.md file in the
examples/passkey directory.
Signed-off-by: Daniel Bevenius <daniel.bevenius@gmail.com>
* Update examples/passkey/README.md
---------
Signed-off-by: Daniel Bevenius <daniel.bevenius@gmail.com>
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* Initial OpenELM support (270M only so far)
* Fill out missing entries in llama_model_type_name
* fixup! Initial OpenELM support (270M only so far)
Fix formatting
* llama : support all OpenELM models
* llama : add variable GQA and variable FFN sizes
Some metadata keys can now also be arrays to support setting
their value per-layer for models like OpenELM.
* llama : minor spacing changes
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* llama : use std::array for per-layer hparams
* llama : fix save/load state
* llama : do not print hparams for vocab-only models
* llama : handle n_head == 0
* llama : use const ref for print_f and fix division by zero
* llama : fix t5 uses of n_head and n_ff
* llama : minor comment
---------
Co-authored-by: Francis Couture-Harpin <git@compilade.net>
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
This commit adds a new option to the tokenize example, --show-count.
When this is set the total number of tokens are printed to stdout.
This was added as an option as I was concerned that there might be
scripts that use the output from this program and it might be better to
not print this information by default.
The motivation for this is that can be useful to find out how many
tokens a file contains, for example when trying to determine prompt
input file sizes for testing.
Signed-off-by: Daniel Bevenius <daniel.bevenius@gmail.com>
* llama : add inference support and model types for T5 and FLAN-T5 model families
* llama : add new API functions to support encoder-decoder models: llama_encode(), llama_model_has_encoder(), llama_model_decoder_start_token()
* common, llama-cli, llama-batched : add support for encoder-decoder models
* convert-hf : handle shared token embeddings tensors in T5Model
* convert-hf : add support for SentencePiece BPE tokenizer in T5Model (for Pile-T5 models)
* convert-hf : add MT5ForConditionalGeneration and UMT5ForConditionalGeneration to architectures supported by T5Model
* convert : add t5 tokenizer tests, use "slow" HF tokenizer for t5
---------
Co-authored-by: Stanisław Szymczyk <sszymczy@gmail.com>
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
This commit adds the compile definition `_CRT_SECURE_NO_WARNINGS`
to the root cmake subproject.
The motivation for this is that currently the following warnings are
displayed when compiling the tests and common cmake subprojects:
```console
test-llama-grammar.cpp
C:\llama.cpp\src\.\llama.cpp(1406,77): warning C4996: 'strerror':
This function or variable may be unsafe. Consider using strerror_s
instead. To disable deprecation, use _CRT_SECURE_NO_WARNINGS. See
online help for details.
[C:\llama.cpp\build\tests\test-llama-grammar.vcxproj]
...
```
This compile definition is currently set for the `src` subproject
and this change moves into the root cmake project so that it is applied
to all cmake subprojects.
* llama : suppress unref var in Windows MSVC
This commit suppresses two warnings that are currently generated for
src/llama.cpp when building on Windows MSVC
```console
C:\llama.cpp\src\llama.cpp(14349,45): warning C4101: 'ex':
unreferenced local variable [C:\llama.cpp\build\src\llama.vcxproj]
C:\llama.cpp\src\llama.cpp(19285,44): warning C4101: 'e':
unreferenced local variable [C:\llama.cpp\build\src\llama.vcxproj]
```
* Update src/llama.cpp
---------
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* convert-hf : print output file name when completed
This commit adds the output file name to the log message when the
conversion is completed.
The motivation for this change is that when `--outfile` option is not
specified it migth not be obvious where the output file is written.
With this change the output of running the script will be something like
the following:
```console
INFO:hf-to-gguf:Model successfully exported to models/gemma-2-9b-it.gguf.
```
Signed-off-by: Daniel Bevenius <daniel.bevenius@gmail.com>
* squash! convert-hf : print output file name when completed
Updates the output of to support printing the directory if the output is
split into multiple files. Also the output file name is now retrieved
from the model_instance object.
Signed-off-by: Daniel Bevenius <daniel.bevenius@gmail.com>
* squash! convert-hf : print output file name when completed
Use parent attribute of Path object and string interpolation.
Signed-off-by: Daniel Bevenius <daniel.bevenius@gmail.com>
* squash! convert-hf : print output file name when completed
Use os.sep instead of hardcoding the path separator.
Signed-off-by: Daniel Bevenius <daniel.bevenius@gmail.com>
---------
Signed-off-by: Daniel Bevenius <daniel.bevenius@gmail.com>
* Add attention and final logit softcapping.
* fix
* Add custom add_ functions
* Disable flash attention for Gemma2
* Update src/llama.cpp
Co-authored-by: slaren <slarengh@gmail.com>
* Add default value for attention and final logit softcap value
* Add custom kq scaling from Gemma2Attention
* Remove custom pre attention scaling and use computed value instead.
---------
Co-authored-by: slaren <slarengh@gmail.com>
* Inference support for Gemma 2 model family
* Update convert-hf-to-gguf.py, constants, and tensor mappings
* cleanup
* format fix
* Fix special token vocab bug
* Don't add space prefix
* fix deleted lines
* Update src/llama.cpp
Co-authored-by: slaren <slarengh@gmail.com>
* Add model type names
* Add control vector
* Fix model type identification
---------
Co-authored-by: Andrei Betlen <abetlen@gmail.com>
Co-authored-by: slaren <slarengh@gmail.com>
* Fixed leak in llama_control_vector_load_one() and allow llama_control_vector_load() to grow
* refactored `llama_control_vector_load_one()`
* allow multiple directions for same layer in same file
* llama_control_vector_load_one() and llama_control_vector_load() now break on error
* removed unnecessary ggml_free() call
* Delete examples/llama.android/llama/CMakeLists.txt
https://github.com/ggerganov/llama.cpp/pull/8145#issuecomment-2194534244
This file is not being used for building on Android. `llama.cpp/examples/llama.android/llama/src/main/cpp/CMakeLists.txt` is being used instead.
* Update CMakeLists.txt
Pick local llama.cpp files instead of fetching content from git
- Path seems to be wrong for the common.h header file in llama-android.cpp file. Fixing the path so the Android Build doesn't fail with the error "There is no file common/common.h"
* clip : suppress unused variable warnings
This commit suppresses unused variable warnings for the variables e in
the catch blocks.
The motivation for this change is to suppress the warnings that are
generated on Windows when using the MSVC compiler. The warnings are
not displayed when using GCC because GCC will mark all catch parameters
as used.
Signed-off-by: Daniel Bevenius <daniel.bevenius@gmail.com>
* squash! clip : suppress unused variable warnings
Remove e (/*e*/) instead instead of using GGML_UNUSED.
---------
Signed-off-by: Daniel Bevenius <daniel.bevenius@gmail.com>
* Add message about int8 support
* Add suggestions from review
Co-authored-by: Johannes Gäßler <johannesg@5d6.de>
---------
Co-authored-by: Johannes Gäßler <johannesg@5d6.de>
* json: default additionalProperty to true
* json: don't force additional props after normal properties!
* json: allow space after enum/const
* json: update pydantic example to set additionalProperties: false
* json: prevent additional props to redefine a typed prop
* port not_strings to python, add trailing space
* fix not_strings & port to js+py
* Update json-schema-to-grammar.cpp
* fix _not_strings for substring overlaps
* json: fix additionalProperties default, uncomment tests
* json: add integ. test case for additionalProperties
* json: nit: simplify condition
* reformat grammar integ tests w/ R"""()""" strings where there's escapes
* update # tokens in server test: consts can now have trailing space
* fixes#7999
The `build_command_r` forgot to add the control vector.
* Fixes qwen2 too
* Fixed all models' control vectors
* Removed double calls to `cb(cur, "l_out", il)`
* Moved control vector logic to llama_control_vector:apply_to()
* llama : add T5 model architecture, tensors and model header parameters
* llama : add implementation of Unigram tokenizer with SentencePiece-like text normalization using precompiled charsmap
---------
Co-authored-by: Stanisław Szymczyk <sszymczy@gmail.com>
* llama : return nullptr from llama_grammar_init
This commit updates llama_grammar_init to return nullptr instead of
throwing an exception.
The motivation for this is that this function is declared inside an
extern "C" block and is intended/may be used from C code which will not
be able to handle exceptions thrown, and results in undefined behavior.
On Windows and using MSVC the following warning is currently generated:
```console
C:\llama.cpp\llama.cpp(13998,1): warning C4297: 'llama_grammar_init':
function assumed not to throw an exception but does
C:\llama.cpp\llama.cpp(13998,1): message :
__declspec(nothrow), throw(), noexcept(true), or noexcept was specified
on the function
```
Signed-off-by: Daniel Bevenius <daniel.bevenius@gmail.com>
* squash! llama : return nullptr from llama_grammar_init
Add checks for nullptr when calling llama_grammar_init.
Signed-off-by: Daniel Bevenius <daniel.bevenius@gmail.com>
---------
Signed-off-by: Daniel Bevenius <daniel.bevenius@gmail.com>
Co-authored-by: Clint Herron <hanclinto@gmail.com>
* SimpleChat: Allow for chat req bool options to be user controlled
* SimpleChat: Allow user to control cache_prompt flag in request
* SimpleChat: Add sample GUI images to readme file
Show the chat screen and the settings screen
* SimpleChat:Readme: Add quickstart block, title to image, cleanup
* SimpleChat: RePosition contents of the Info and Settings UI
Make it more logically structured and flow through.
* SimpleChat: Rename to apiRequestOptions from chatRequestOptions
So that it is not wrongly assumed that these request options are
used only for chat/completions endpoint. Rather these are used
for both the end points, so rename to match semantic better.
* SimpleChat: Update image included with readme wrt settings ui
* SimpleChat:ReadMe: Switch to webp screen image to reduce size
* support splits in convert.py
* Support split by size and dry run to write estimated shards/filesizes
* Move split functionality to new GGUFManager class
* fix improper function signature
* tentative push of convert-hf-to-gguf support
* resolve merge + SplitArguments for easier parsing
* Fix eager tensor memory leak and remove convert.py changes
Removed a memory leak caused by unexpected reference retention to eager tensors.
Also removed GGUFManager functionality in convert.py in favor of specializing for convert-hf-to-gguf.py.
* refactor SplitStrategy to be a deque
Instead of having SplitStrategy have a `data` field that is a deque, just have SplitStrategy be a subclass of deque itself.
* fix Q8 quantization
* remove unnecessary imports in gguf_manager
* fix final? merge issue
* fix gguf_writer placement and remove comments
* oops, actually fix gguf_writer placement
* reduce duplicated code from gguf_writer
* further simplify GGUFManager
* simplify even further and standardize with GGUFWriter
* reduce diffs with master
* form shards while adding tensors, SHA256 sums agree with master
* re-add type hint
Co-authored-by: compilade <git@compilade.net>
* GGUFWriter compatibility fix
Co-authored-by: compilade <git@compilade.net>
* Shard dataclass and un-negative dont_add_architecture
* type consistency in format_n_bytes_to_str
* move kv keys to constants.py
* make pathlib explicit
* base-1024 bytes to base-1000
* rename GGUFManager to GGUFWriterSplit
* Update gguf-py/gguf/constants.py
Co-authored-by: compilade <git@compilade.net>
* fix convert-hf-to-gguf.py permissions
* fix line endings
* Update gguf-py/gguf/gguf_writer_split.py
Co-authored-by: compilade <git@compilade.net>
* convert-hf : restore executable file permission
* examples/convert-legacy-llama.py: restore executable file permission
* reinstate original gguf package import and fix type annotation
* attempt to appease the linter
* attempt 2 to appease the linter
* attempt 3 to appease the linter
* comma consistency
* Update convert-hf-to-gguf.py
Co-authored-by: compilade <git@compilade.net>
* edit cmd line args
* use simplification from #7827
* kv/ti data are still wrong
* try to refactor kv data (still fails)
* fix ti data messiness
* tidy up
* fix linting
* actually make the linter happy
* cleanup round 1
* remove SplitStrategy, SplitArguments
* appease linter
* fix typing and clean up
* fix linting
* Update gguf-py/gguf/gguf_writer.py
Co-authored-by: compilade <git@compilade.net>
* progress bar, fix split logic
* Update gguf-py/gguf/gguf_writer.py
Co-authored-by: compilade <git@compilade.net>
* catch oversights
* Update gguf-py/gguf/gguf_writer.py
Co-authored-by: compilade <git@compilade.net>
* Update gguf-py/gguf/gguf_writer.py
Co-authored-by: compilade <git@compilade.net>
* Update gguf-py/gguf/gguf_writer.py
Co-authored-by: compilade <git@compilade.net>
* Update gguf-py/gguf/gguf_writer.py
Co-authored-by: compilade <git@compilade.net>
* Update gguf-py/gguf/gguf_writer.py
Co-authored-by: compilade <git@compilade.net>
* swap bar orders
* Update gguf-py/gguf/gguf_writer.py
Co-authored-by: compilade <git@compilade.net>
* Update gguf-py/gguf/gguf_writer.py
Co-authored-by: compilade <git@compilade.net>
* compatibility fix
* Update gguf-py/gguf/gguf_writer.py
Co-authored-by: compilade <git@compilade.net>
* Update convert-hf-to-gguf.py
Co-authored-by: compilade <git@compilade.net>
---------
Co-authored-by: Brian <mofosyne@gmail.com>
Co-authored-by: compilade <git@compilade.net>
* add parameters for embeddings
--embd-normalize
--embd-output-format
--embd-separator
description in the README.md
* Update README.md
fix tipo
* Trailing whitespace
* fix json generation, use " not '
* fix merge master
* fix code formating
group of parameters // embedding
print usage for embedding parameters
---------
Co-authored-by: Brian <mofosyne@gmail.com>
* gguf-py : add T5 model architecture
* gguf-py : add separate tensors for encoder and decoder
* gguf-py : add new model header parameters: decoder_start_token_id, attention.relative_buckets_count, tokenizer.ggml.remove_extra_whitespaces, tokenizer.ggml.precompiled_charsmap
* convert-hf : add model conversion support for T5ForConditionalGeneration and T5WithLMHeadModel
---------
Co-authored-by: Stanisław Szymczyk <sszymczy@gmail.com>
2024-06-24 07:06:05 +02:00
1113 changed files with 222121 additions and 256055 deletions
- Execute [the full CI locally on your machine](ci/README.md) before publishing
- Verify that the perplexity and the performance are not affected negatively by your changes (use `llama-perplexity` and `llama-bench`)
- If you modified the `ggml` source, run the `test-backend-ops` tool to check whether different backend implementations of the `ggml` operators produce consistent results (this requires access to at least two different `ggml` backends)
- If you modified a `ggml` operator or added a new one, add the corresponding test cases to `test-backend-ops`
- Consider allowing write access to your branch for faster reviews, as reviewers can push commits directly
- If your PR becomes stale, don't hesitate to ping the maintainers in the comments
* Make sure your PR follows the [coding guidelines](https://github.com/ggerganov/llama.cpp/blob/master/README.md#coding-guidelines)
* Test your changes using the commands in the [`tests`](tests) folder. For instance, running the `./tests/test-backend-ops` command tests different backend implementations of the GGML library
* Execute [the full CI locally on your machine](ci/README.md) before publishing
# Pull requests (for collaborators)
## PR formatting
- Squash-merge PRs
- Use the following format for the squashed commit title: `<module> : <commit title> (#<issue_number>)`. For example: `utils : fix typo in utils.py (#1234)`
- Optionally pick a `<module>` from here: https://github.com/ggerganov/llama.cpp/wiki/Modules
- Consider adding yourself to [CODEOWNERS](CODEOWNERS)
* Please rate the complexity of your PR (i.e. `Review Complexity : Low`, `Review Complexity : Medium`, `Review Complexity : High`). This makes it easier for maintainers to triage the PRs.
- The PR template has a series of review complexity checkboxes `[ ]` that you can mark as `[X]` for your conveience. Refer to [About task lists](https://docs.github.com/en/get-started/writing-on-github/working-with-advanced-formatting/about-task-lists) for more information.
* If the pull request only contains documentation changes (e.g., updating READMEs, adding new wiki pages), please add `[no ci]` to the commit title. This will skip unnecessary CI checks and help reduce build times.
* When squashing multiple commits on merge, use the following format for your commit title: `<module> : <commit title> (#<issue_number>)`. For example: `utils : Fix typo in utils.py (#1234)`
# Coding guidelines
- Avoid adding third-party dependencies, extra files, extra headers, etc.
- Always consider cross-compatibility with other operating systems and architectures
- Avoid fancy-looking modern STL constructs, use basic `for` loops, avoid templates, keep it simple
- Vertical alignment makes things more readable and easier to batch edit
- Clean-up any trailing whitespaces, use 4 spaces for indentation, brackets on the same line, `void * ptr`, `int & a`
- Use sized integer types such as `int32_t` in the public API, e.g. `size_t` may also be appropriate for allocation sizes or byte offsets
- Declare structs with `struct foo {}` instead of `typedef struct foo {} foo`
- In C++ code omit optional `struct` and `enum` keyword whenever they are not necessary
```cpp
// OK
llama_context * ctx;
const llama_rope_type rope_type;
// not OK
struct llama_context * ctx;
const enum llama_rope_type rope_type;
```
_(NOTE: this guideline is yet to be applied to the `llama.cpp` codebase. New code should follow this guideline.)_
- Try to follow the existing patterns in the code (indentation, spaces, etc.). In case of doubt use `clang-format` to format the added code
- For anything not covered in the current guidelines, refer to the [C++ Core Guidelines](https://isocpp.github.io/CppCoreGuidelines/CppCoreGuidelines)
- Tensors store data in row-major order. We refer to dimension 0 as columns, 1 as rows, 2 as matrices
- Matrix multiplication is unconventional: [`C = ggml_mul_mat(ctx, A, B)`](https://github.com/ggerganov/llama.cpp/blob/880e352277fc017df4d5794f0c21c44e1eae2b84/ggml.h#L1058-L1064) means $C^T = A B^T \Leftrightarrow C = B A^T.$

# Naming guidelines
- Use `snake_case` for function, variable and type names
- Naming usually optimizes for longest common prefix (see https://github.com/ggerganov/ggml/pull/302#discussion_r1243240963)
```cpp
// not OK
int small_number;
int big_number;
// OK
int number_small;
int number_big;
```
- Enum values are always in upper case and prefixed with the enum name
```cpp
enum llama_vocab_type {
LLAMA_VOCAB_TYPE_NONE = 0,
LLAMA_VOCAB_TYPE_SPM = 1,
LLAMA_VOCAB_TYPE_BPE = 2,
LLAMA_VOCAB_TYPE_WPM = 3,
LLAMA_VOCAB_TYPE_UGM = 4,
LLAMA_VOCAB_TYPE_RWKV = 5,
};
```
- The general naming pattern is `<class>_<method>`, with `<method>` being `<action>_<noun>`
_(NOTE: this guideline is yet to be applied to the `llama.cpp` codebase. New code should follow this guideline)_
- C/C++ filenames are all lowercase with dashes. Headers use the `.h` extension. Source files use the `.c` or `.cpp` extension
- Python filenames are all lowercase with underscores
- _(TODO: abbreviations usage)_
# Preprocessor directives
- _(TODO: add guidelines with examples and apply them to the codebase)_
```cpp
#ifdef FOO
#endif // FOO
```
# Documentation
- Documentation is a community effort
- When you need to look into the source code to figure out how to use an API consider adding a short summary to the header file for future reference
- When you notice incorrect or outdated documentation, please update it
# Resources
The Github issues, PRs and discussions contain a lot of information that can be useful to get familiar with the codebase. For convenience, some of the more important information is referenced from Github projects:
(time ./bin/llama-cli --model ${model_f16} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is") 2>&1| tee -a $OUT/${ci}-tg-f16.log
(time ./bin/llama-cli --model ${model_q8_0} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is") 2>&1| tee -a $OUT/${ci}-tg-q8_0.log
(time ./bin/llama-cli --model ${model_q4_0} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is") 2>&1| tee -a $OUT/${ci}-tg-q4_0.log
(time ./bin/llama-cli --model ${model_q4_1} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is") 2>&1| tee -a $OUT/${ci}-tg-q4_1.log
(time ./bin/llama-cli --model ${model_q5_0} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is") 2>&1| tee -a $OUT/${ci}-tg-q5_0.log
(time ./bin/llama-cli --model ${model_q5_1} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is") 2>&1| tee -a $OUT/${ci}-tg-q5_1.log
(time ./bin/llama-cli --model ${model_q2_k} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is") 2>&1| tee -a $OUT/${ci}-tg-q2_k.log
(time ./bin/llama-cli --model ${model_q3_k} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is") 2>&1| tee -a $OUT/${ci}-tg-q3_k.log
(time ./bin/llama-cli --model ${model_q4_k} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is") 2>&1| tee -a $OUT/${ci}-tg-q4_k.log
(time ./bin/llama-cli --model ${model_q5_k} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is") 2>&1| tee -a $OUT/${ci}-tg-q5_k.log
(time ./bin/llama-cli --model ${model_q6_k} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is") 2>&1| tee -a $OUT/${ci}-tg-q6_k.log
(time ./bin/llama-cli -no-cnv --model ${model_f16} -t 1 -ngl 99 -c 0 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is") 2>&1| tee -a $OUT/${ci}-tg-f16.log
(time ./bin/llama-cli -no-cnv --model ${model_q8_0} -t 1 -ngl 99 -c 0 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is") 2>&1| tee -a $OUT/${ci}-tg-q8_0.log
(time ./bin/llama-cli -no-cnv --model ${model_q4_0} -t 1 -ngl 99 -c 0 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is") 2>&1| tee -a $OUT/${ci}-tg-q4_0.log
(time ./bin/llama-cli -no-cnv --model ${model_q4_1} -t 1 -ngl 99 -c 0 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is") 2>&1| tee -a $OUT/${ci}-tg-q4_1.log
(time ./bin/llama-cli -no-cnv --model ${model_q5_0} -t 1 -ngl 99 -c 0 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is") 2>&1| tee -a $OUT/${ci}-tg-q5_0.log
(time ./bin/llama-cli -no-cnv --model ${model_q5_1} -t 1 -ngl 99 -c 0 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is") 2>&1| tee -a $OUT/${ci}-tg-q5_1.log
(time ./bin/llama-cli -no-cnv --model ${model_q2_k} -t 1 -ngl 99 -c 0 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is") 2>&1| tee -a $OUT/${ci}-tg-q2_k.log
(time ./bin/llama-cli -no-cnv --model ${model_q3_k} -t 1 -ngl 99 -c 0 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is") 2>&1| tee -a $OUT/${ci}-tg-q3_k.log
(time ./bin/llama-cli -no-cnv --model ${model_q4_k} -t 1 -ngl 99 -c 0 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is") 2>&1| tee -a $OUT/${ci}-tg-q4_k.log
(time ./bin/llama-cli -no-cnv --model ${model_q5_k} -t 1 -ngl 99 -c 0 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is") 2>&1| tee -a $OUT/${ci}-tg-q5_k.log
(time ./bin/llama-cli -no-cnv --model ${model_q6_k} -t 1 -ngl 99 -c 0 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is") 2>&1| tee -a $OUT/${ci}-tg-q6_k.log
(time ./bin/llama-perplexity --model ${model_f16} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4) 2>&1| tee -a $OUT/${ci}-tg-f16.log
(time ./bin/llama-perplexity --model ${model_q8_0} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4) 2>&1| tee -a $OUT/${ci}-tg-q8_0.log
(time ./bin/llama-perplexity --model ${model_q4_0} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4) 2>&1| tee -a $OUT/${ci}-tg-q4_0.log
(time ./bin/llama-perplexity --model ${model_q4_1} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4) 2>&1| tee -a $OUT/${ci}-tg-q4_1.log
(time ./bin/llama-perplexity --model ${model_q5_0} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4) 2>&1| tee -a $OUT/${ci}-tg-q5_0.log
(time ./bin/llama-perplexity --model ${model_q5_1} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4) 2>&1| tee -a $OUT/${ci}-tg-q5_1.log
(time ./bin/llama-perplexity --model ${model_q2_k} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4) 2>&1| tee -a $OUT/${ci}-tg-q2_k.log
(time ./bin/llama-perplexity --model ${model_q3_k} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4) 2>&1| tee -a $OUT/${ci}-tg-q3_k.log
(time ./bin/llama-perplexity --model ${model_q4_k} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4) 2>&1| tee -a $OUT/${ci}-tg-q4_k.log
(time ./bin/llama-perplexity --model ${model_q5_k} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4) 2>&1| tee -a $OUT/${ci}-tg-q5_k.log
(time ./bin/llama-perplexity --model ${model_q6_k} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4) 2>&1| tee -a $OUT/${ci}-tg-q6_k.log
(time ./bin/llama-perplexity --model ${model_f16} -f ${wiki_test} -t 1 -ngl 99 -c 2048 -b 512 --chunks 4) 2>&1| tee -a $OUT/${ci}-tg-f16.log
(time ./bin/llama-perplexity --model ${model_q8_0} -f ${wiki_test} -t 1 -ngl 99 -c 2048 -b 512 --chunks 4) 2>&1| tee -a $OUT/${ci}-tg-q8_0.log
(time ./bin/llama-perplexity --model ${model_q4_0} -f ${wiki_test} -t 1 -ngl 99 -c 2048 -b 512 --chunks 4) 2>&1| tee -a $OUT/${ci}-tg-q4_0.log
(time ./bin/llama-perplexity --model ${model_q4_1} -f ${wiki_test} -t 1 -ngl 99 -c 2048 -b 512 --chunks 4) 2>&1| tee -a $OUT/${ci}-tg-q4_1.log
(time ./bin/llama-perplexity --model ${model_q5_0} -f ${wiki_test} -t 1 -ngl 99 -c 2048 -b 512 --chunks 4) 2>&1| tee -a $OUT/${ci}-tg-q5_0.log
(time ./bin/llama-perplexity --model ${model_q5_1} -f ${wiki_test} -t 1 -ngl 99 -c 2048 -b 512 --chunks 4) 2>&1| tee -a $OUT/${ci}-tg-q5_1.log
(time ./bin/llama-perplexity --model ${model_q2_k} -f ${wiki_test} -t 1 -ngl 99 -c 2048 -b 512 --chunks 4) 2>&1| tee -a $OUT/${ci}-tg-q2_k.log
(time ./bin/llama-perplexity --model ${model_q3_k} -f ${wiki_test} -t 1 -ngl 99 -c 2048 -b 512 --chunks 4) 2>&1| tee -a $OUT/${ci}-tg-q3_k.log
(time ./bin/llama-perplexity --model ${model_q4_k} -f ${wiki_test} -t 1 -ngl 99 -c 2048 -b 512 --chunks 4) 2>&1| tee -a $OUT/${ci}-tg-q4_k.log
(time ./bin/llama-perplexity --model ${model_q5_k} -f ${wiki_test} -t 1 -ngl 99 -c 2048 -b 512 --chunks 4) 2>&1| tee -a $OUT/${ci}-tg-q5_k.log
(time ./bin/llama-perplexity --model ${model_q6_k} -f ${wiki_test} -t 1 -ngl 99 -c 2048 -b 512 --chunks 4) 2>&1| tee -a $OUT/${ci}-tg-q6_k.log
(time ./bin/llama-imatrix --model ${model_f16} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4) 2>&1| tee -a $OUT/${ci}-imatrix.log
(time ./bin/llama-imatrix --model ${model_f16} -f ${wiki_test} -t 1 -ngl 99 -c 2048 -b 512 --chunks 4) 2>&1| tee -a $OUT/${ci}-imatrix.log
(time ./bin/llama-save-load-state -ngl 10--model ${model_q4_0}) 2>&1| tee -a $OUT/${ci}-save-load-state.log
(time ./bin/llama-save-load-state -fa -ngl 10--model ${model_q4_0}) 2>&1| tee -a $OUT/${ci}-save-load-state.log
(time ./bin/llama-save-load-state -ngl 99--model ${model_q4_0}) 2>&1| tee -a $OUT/${ci}-save-load-state.log
(time ./bin/llama-save-load-state -fa -ngl 99--model ${model_q4_0}) 2>&1| tee -a $OUT/${ci}-save-load-state.log
(time ./bin/llama-save-load-state--model ${model_q4_0} -ngl 10 -c 0) 2>&1| tee -a $OUT/${ci}-save-load-state.log
(time ./bin/llama-save-load-state--model ${model_q4_0} -ngl 10 -c 0 -fa) 2>&1| tee -a $OUT/${ci}-save-load-state.log
(time ./bin/llama-save-load-state--model ${model_q4_0} -ngl 99 -c 0) 2>&1| tee -a $OUT/${ci}-save-load-state.log
(time ./bin/llama-save-load-state--model ${model_q4_0} -ngl 99 -c 0 -fa) 2>&1| tee -a $OUT/${ci}-save-load-state.log
function check_ppl {
qnt="$1"
@ -419,9 +431,9 @@ function gg_run_pythia_1_4b {
set -e
(time cmake -DCMAKE_BUILD_TYPE=Release ${CMAKE_EXTRA} .. ) 2>&1| tee -a $OUT/${ci}-cmake.log
(time make -j) 2>&1| tee -a $OUT/${ci}-make.log
(time make -j$(nproc)) 2>&1| tee -a $OUT/${ci}-make.log
(time ./bin/llama-cli --model ${model_f16} -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is") 2>&1| tee -a $OUT/${ci}-tg-f16.log
(time ./bin/llama-cli --model ${model_q8_0} -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is") 2>&1| tee -a $OUT/${ci}-tg-q8_0.log
(time ./bin/llama-cli --model ${model_q4_0} -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is") 2>&1| tee -a $OUT/${ci}-tg-q4_0.log
(time ./bin/llama-cli --model ${model_q4_1} -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is") 2>&1| tee -a $OUT/${ci}-tg-q4_1.log
(time ./bin/llama-cli --model ${model_q5_0} -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is") 2>&1| tee -a $OUT/${ci}-tg-q5_0.log
(time ./bin/llama-cli --model ${model_q5_1} -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is") 2>&1| tee -a $OUT/${ci}-tg-q5_1.log
(time ./bin/llama-cli --model ${model_q2_k} -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is") 2>&1| tee -a $OUT/${ci}-tg-q2_k.log
(time ./bin/llama-cli --model ${model_q3_k} -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is") 2>&1| tee -a $OUT/${ci}-tg-q3_k.log
(time ./bin/llama-cli --model ${model_q4_k} -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is") 2>&1| tee -a $OUT/${ci}-tg-q4_k.log
(time ./bin/llama-cli --model ${model_q5_k} -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is") 2>&1| tee -a $OUT/${ci}-tg-q5_k.log
(time ./bin/llama-cli --model ${model_q6_k} -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is") 2>&1| tee -a $OUT/${ci}-tg-q6_k.log
(time ./bin/llama-cli -no-cnv --model ${model_f16} -ngl 99 -c 0 -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is") 2>&1| tee -a $OUT/${ci}-tg-f16.log
(time ./bin/llama-cli -no-cnv --model ${model_q8_0} -ngl 99 -c 0 -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is") 2>&1| tee -a $OUT/${ci}-tg-q8_0.log
(time ./bin/llama-cli -no-cnv --model ${model_q4_0} -ngl 99 -c 0 -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is") 2>&1| tee -a $OUT/${ci}-tg-q4_0.log
(time ./bin/llama-cli -no-cnv --model ${model_q4_1} -ngl 99 -c 0 -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is") 2>&1| tee -a $OUT/${ci}-tg-q4_1.log
(time ./bin/llama-cli -no-cnv --model ${model_q5_0} -ngl 99 -c 0 -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is") 2>&1| tee -a $OUT/${ci}-tg-q5_0.log
(time ./bin/llama-cli -no-cnv --model ${model_q5_1} -ngl 99 -c 0 -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is") 2>&1| tee -a $OUT/${ci}-tg-q5_1.log
(time ./bin/llama-cli -no-cnv --model ${model_q2_k} -ngl 99 -c 0 -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is") 2>&1| tee -a $OUT/${ci}-tg-q2_k.log
(time ./bin/llama-cli -no-cnv --model ${model_q3_k} -ngl 99 -c 0 -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is") 2>&1| tee -a $OUT/${ci}-tg-q3_k.log
(time ./bin/llama-cli -no-cnv --model ${model_q4_k} -ngl 99 -c 0 -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is") 2>&1| tee -a $OUT/${ci}-tg-q4_k.log
(time ./bin/llama-cli -no-cnv --model ${model_q5_k} -ngl 99 -c 0 -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is") 2>&1| tee -a $OUT/${ci}-tg-q5_k.log
(time ./bin/llama-cli -no-cnv --model ${model_q6_k} -ngl 99 -c 0 -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is") 2>&1| tee -a $OUT/${ci}-tg-q6_k.log
(time ./bin/llama-perplexity --model ${model_f16} -f ${wiki_test_60} -c 128 -b 128 --chunks 1) 2>&1| tee -a $OUT/${ci}-tg-f16.log
(time ./bin/llama-perplexity --model ${model_q8_0} -f ${wiki_test_60} -c 128 -b 128 --chunks 1) 2>&1| tee -a $OUT/${ci}-tg-q8_0.log
(time ./bin/llama-perplexity --model ${model_q4_0} -f ${wiki_test_60} -c 128 -b 128 --chunks 1) 2>&1| tee -a $OUT/${ci}-tg-q4_0.log
(time ./bin/llama-perplexity --model ${model_q4_1} -f ${wiki_test_60} -c 128 -b 128 --chunks 1) 2>&1| tee -a $OUT/${ci}-tg-q4_1.log
(time ./bin/llama-perplexity --model ${model_q5_0} -f ${wiki_test_60} -c 128 -b 128 --chunks 1) 2>&1| tee -a $OUT/${ci}-tg-q5_0.log
(time ./bin/llama-perplexity --model ${model_q5_1} -f ${wiki_test_60} -c 128 -b 128 --chunks 1) 2>&1| tee -a $OUT/${ci}-tg-q5_1.log
(time ./bin/llama-perplexity --model ${model_q2_k} -f ${wiki_test_60} -c 128 -b 128 --chunks 1) 2>&1| tee -a $OUT/${ci}-tg-q2_k.log
(time ./bin/llama-perplexity --model ${model_q3_k} -f ${wiki_test_60} -c 128 -b 128 --chunks 1) 2>&1| tee -a $OUT/${ci}-tg-q3_k.log
(time ./bin/llama-perplexity --model ${model_q4_k} -f ${wiki_test_60} -c 128 -b 128 --chunks 1) 2>&1| tee -a $OUT/${ci}-tg-q4_k.log
(time ./bin/llama-perplexity --model ${model_q5_k} -f ${wiki_test_60} -c 128 -b 128 --chunks 1) 2>&1| tee -a $OUT/${ci}-tg-q5_k.log
(time ./bin/llama-perplexity --model ${model_q6_k} -f ${wiki_test_60} -c 128 -b 128 --chunks 1) 2>&1| tee -a $OUT/${ci}-tg-q6_k.log
(time ./bin/llama-perplexity --model ${model_f16} -f ${wiki_test_60} -ngl 99 -c 128 -b 128 --chunks 1) 2>&1| tee -a $OUT/${ci}-tg-f16.log
(time ./bin/llama-perplexity --model ${model_q8_0} -f ${wiki_test_60} -ngl 99 -c 128 -b 128 --chunks 1) 2>&1| tee -a $OUT/${ci}-tg-q8_0.log
(time ./bin/llama-perplexity --model ${model_q4_0} -f ${wiki_test_60} -ngl 99 -c 128 -b 128 --chunks 1) 2>&1| tee -a $OUT/${ci}-tg-q4_0.log
(time ./bin/llama-perplexity --model ${model_q4_1} -f ${wiki_test_60} -ngl 99 -c 128 -b 128 --chunks 1) 2>&1| tee -a $OUT/${ci}-tg-q4_1.log
(time ./bin/llama-perplexity --model ${model_q5_0} -f ${wiki_test_60} -ngl 99 -c 128 -b 128 --chunks 1) 2>&1| tee -a $OUT/${ci}-tg-q5_0.log
(time ./bin/llama-perplexity --model ${model_q5_1} -f ${wiki_test_60} -ngl 99 -c 128 -b 128 --chunks 1) 2>&1| tee -a $OUT/${ci}-tg-q5_1.log
(time ./bin/llama-perplexity --model ${model_q2_k} -f ${wiki_test_60} -ngl 99 -c 128 -b 128 --chunks 1) 2>&1| tee -a $OUT/${ci}-tg-q2_k.log
(time ./bin/llama-perplexity --model ${model_q3_k} -f ${wiki_test_60} -ngl 99 -c 128 -b 128 --chunks 1) 2>&1| tee -a $OUT/${ci}-tg-q3_k.log
(time ./bin/llama-perplexity --model ${model_q4_k} -f ${wiki_test_60} -ngl 99 -c 128 -b 128 --chunks 1) 2>&1| tee -a $OUT/${ci}-tg-q4_k.log
(time ./bin/llama-perplexity --model ${model_q5_k} -f ${wiki_test_60} -ngl 99 -c 128 -b 128 --chunks 1) 2>&1| tee -a $OUT/${ci}-tg-q5_k.log
(time ./bin/llama-perplexity --model ${model_q6_k} -f ${wiki_test_60} -ngl 99 -c 128 -b 128 --chunks 1) 2>&1| tee -a $OUT/${ci}-tg-q6_k.log
(time ./bin/llama-imatrix --model ${model_f16} -f ${wiki_test_60} -c 128 -b 128 --chunks 1) 2>&1| tee -a $OUT/${ci}-imatrix.log
(time ./bin/llama-imatrix --model ${model_f16} -f ${wiki_test_60} -ngl 99 -c 128 -b 128 --chunks 1) 2>&1| tee -a $OUT/${ci}-imatrix.log
(time ./bin/llama-save-load-state --model ${model_q4_0}) 2>&1| tee -a $OUT/${ci}-save-load-state.log
(time ./bin/llama-save-load-state -fa --model ${model_q4_0}) 2>&1| tee -a $OUT/${ci}-save-load-state.log
(time ./bin/llama-save-load-state --model ${model_q4_0} -ngl 99 -c 0) 2>&1| tee -a $OUT/${ci}-save-load-state.log
(time ./bin/llama-save-load-state --model ${model_q4_0} -ngl 99 -c 0 -fa) 2>&1| tee -a $OUT/${ci}-save-load-state.log
function check_ppl {
qnt="$1"
@ -529,7 +541,6 @@ function gg_sum_pythia_1_4b {
}
# pythia_2_8b
# requires: GG_BUILD_CUDA
function gg_run_pythia_2_8b {
cd${SRC}
@ -550,10 +561,10 @@ function gg_run_pythia_2_8b {
set -e
(time cmake -DCMAKE_BUILD_TYPE=Release ${CMAKE_EXTRA} -DLLAMA_CUDA=1 .. ) 2>&1| tee -a $OUT/${ci}-cmake.log
(time make -j) 2>&1| tee -a $OUT/${ci}-make.log
(time cmake -DCMAKE_BUILD_TYPE=Release ${CMAKE_EXTRA} .. ) 2>&1| tee -a $OUT/${ci}-cmake.log
(time make -j$(nproc)) 2>&1| tee -a $OUT/${ci}-make.log
(time ./bin/llama-cli --model ${model_f16} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is") 2>&1| tee -a $OUT/${ci}-tg-f16.log
(time ./bin/llama-cli --model ${model_q8_0} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is") 2>&1| tee -a $OUT/${ci}-tg-q8_0.log
(time ./bin/llama-cli --model ${model_q4_0} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is") 2>&1| tee -a $OUT/${ci}-tg-q4_0.log
(time ./bin/llama-cli --model ${model_q4_1} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is") 2>&1| tee -a $OUT/${ci}-tg-q4_1.log
(time ./bin/llama-cli --model ${model_q5_0} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is") 2>&1| tee -a $OUT/${ci}-tg-q5_0.log
(time ./bin/llama-cli --model ${model_q5_1} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is") 2>&1| tee -a $OUT/${ci}-tg-q5_1.log
(time ./bin/llama-cli --model ${model_q2_k} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is") 2>&1| tee -a $OUT/${ci}-tg-q2_k.log
(time ./bin/llama-cli --model ${model_q3_k} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is") 2>&1| tee -a $OUT/${ci}-tg-q3_k.log
(time ./bin/llama-cli --model ${model_q4_k} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is") 2>&1| tee -a $OUT/${ci}-tg-q4_k.log
(time ./bin/llama-cli --model ${model_q5_k} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is") 2>&1| tee -a $OUT/${ci}-tg-q5_k.log
(time ./bin/llama-cli --model ${model_q6_k} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is") 2>&1| tee -a $OUT/${ci}-tg-q6_k.log
(time ./bin/llama-cli -no-cnv --model ${model_f16} -t 1 -ngl 99 -c 0 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is") 2>&1| tee -a $OUT/${ci}-tg-f16.log
(time ./bin/llama-cli -no-cnv --model ${model_q8_0} -t 1 -ngl 99 -c 0 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is") 2>&1| tee -a $OUT/${ci}-tg-q8_0.log
(time ./bin/llama-cli -no-cnv --model ${model_q4_0} -t 1 -ngl 99 -c 0 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is") 2>&1| tee -a $OUT/${ci}-tg-q4_0.log
(time ./bin/llama-cli -no-cnv --model ${model_q4_1} -t 1 -ngl 99 -c 0 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is") 2>&1| tee -a $OUT/${ci}-tg-q4_1.log
(time ./bin/llama-cli -no-cnv --model ${model_q5_0} -t 1 -ngl 99 -c 0 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is") 2>&1| tee -a $OUT/${ci}-tg-q5_0.log
(time ./bin/llama-cli -no-cnv --model ${model_q5_1} -t 1 -ngl 99 -c 0 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is") 2>&1| tee -a $OUT/${ci}-tg-q5_1.log
(time ./bin/llama-cli -no-cnv --model ${model_q2_k} -t 1 -ngl 99 -c 0 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is") 2>&1| tee -a $OUT/${ci}-tg-q2_k.log
(time ./bin/llama-cli -no-cnv --model ${model_q3_k} -t 1 -ngl 99 -c 0 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is") 2>&1| tee -a $OUT/${ci}-tg-q3_k.log
(time ./bin/llama-cli -no-cnv --model ${model_q4_k} -t 1 -ngl 99 -c 0 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is") 2>&1| tee -a $OUT/${ci}-tg-q4_k.log
(time ./bin/llama-cli -no-cnv --model ${model_q5_k} -t 1 -ngl 99 -c 0 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is") 2>&1| tee -a $OUT/${ci}-tg-q5_k.log
(time ./bin/llama-cli -no-cnv --model ${model_q6_k} -t 1 -ngl 99 -c 0 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is") 2>&1| tee -a $OUT/${ci}-tg-q6_k.log
(time ./bin/llama-perplexity --model ${model_f16} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4) 2>&1| tee -a $OUT/${ci}-tg-f16.log
(time ./bin/llama-perplexity --model ${model_q8_0} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4) 2>&1| tee -a $OUT/${ci}-tg-q8_0.log
(time ./bin/llama-perplexity --model ${model_q4_0} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4) 2>&1| tee -a $OUT/${ci}-tg-q4_0.log
(time ./bin/llama-perplexity --model ${model_q4_1} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4) 2>&1| tee -a $OUT/${ci}-tg-q4_1.log
(time ./bin/llama-perplexity --model ${model_q5_0} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4) 2>&1| tee -a $OUT/${ci}-tg-q5_0.log
(time ./bin/llama-perplexity --model ${model_q5_1} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4) 2>&1| tee -a $OUT/${ci}-tg-q5_1.log
(time ./bin/llama-perplexity --model ${model_q2_k} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4) 2>&1| tee -a $OUT/${ci}-tg-q2_k.log
(time ./bin/llama-perplexity --model ${model_q3_k} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4) 2>&1| tee -a $OUT/${ci}-tg-q3_k.log
(time ./bin/llama-perplexity --model ${model_q4_k} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4) 2>&1| tee -a $OUT/${ci}-tg-q4_k.log
(time ./bin/llama-perplexity --model ${model_q5_k} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4) 2>&1| tee -a $OUT/${ci}-tg-q5_k.log
(time ./bin/llama-perplexity --model ${model_q6_k} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4) 2>&1| tee -a $OUT/${ci}-tg-q6_k.log
(time ./bin/llama-perplexity --model ${model_f16} -f ${wiki_test} -t 1 -ngl 99 -c 2048 -b 512 --chunks 4) 2>&1| tee -a $OUT/${ci}-tg-f16.log
(time ./bin/llama-perplexity --model ${model_q8_0} -f ${wiki_test} -t 1 -ngl 99 -c 2048 -b 512 --chunks 4) 2>&1| tee -a $OUT/${ci}-tg-q8_0.log
(time ./bin/llama-perplexity --model ${model_q4_0} -f ${wiki_test} -t 1 -ngl 99 -c 2048 -b 512 --chunks 4) 2>&1| tee -a $OUT/${ci}-tg-q4_0.log
(time ./bin/llama-perplexity --model ${model_q4_1} -f ${wiki_test} -t 1 -ngl 99 -c 2048 -b 512 --chunks 4) 2>&1| tee -a $OUT/${ci}-tg-q4_1.log
(time ./bin/llama-perplexity --model ${model_q5_0} -f ${wiki_test} -t 1 -ngl 99 -c 2048 -b 512 --chunks 4) 2>&1| tee -a $OUT/${ci}-tg-q5_0.log
(time ./bin/llama-perplexity --model ${model_q5_1} -f ${wiki_test} -t 1 -ngl 99 -c 2048 -b 512 --chunks 4) 2>&1| tee -a $OUT/${ci}-tg-q5_1.log
(time ./bin/llama-perplexity --model ${model_q2_k} -f ${wiki_test} -t 1 -ngl 99 -c 2048 -b 512 --chunks 4) 2>&1| tee -a $OUT/${ci}-tg-q2_k.log
(time ./bin/llama-perplexity --model ${model_q3_k} -f ${wiki_test} -t 1 -ngl 99 -c 2048 -b 512 --chunks 4) 2>&1| tee -a $OUT/${ci}-tg-q3_k.log
(time ./bin/llama-perplexity --model ${model_q4_k} -f ${wiki_test} -t 1 -ngl 99 -c 2048 -b 512 --chunks 4) 2>&1| tee -a $OUT/${ci}-tg-q4_k.log
(time ./bin/llama-perplexity --model ${model_q5_k} -f ${wiki_test} -t 1 -ngl 99 -c 2048 -b 512 --chunks 4) 2>&1| tee -a $OUT/${ci}-tg-q5_k.log
(time ./bin/llama-perplexity --model ${model_q6_k} -f ${wiki_test} -t 1 -ngl 99 -c 2048 -b 512 --chunks 4) 2>&1| tee -a $OUT/${ci}-tg-q6_k.log
(time ./bin/llama-imatrix --model ${model_f16} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4) 2>&1| tee -a $OUT/${ci}-imatrix.log
(time ./bin/llama-imatrix --model ${model_f16} -f ${wiki_test} -t 1 -ngl 99 -c 2048 -b 512 --chunks 4) 2>&1| tee -a $OUT/${ci}-imatrix.log
(time ./bin/llama-save-load-state -ngl 10 --model ${model_q4_0}) 2>&1| tee -a $OUT/${ci}-save-load-state.log
(time ./bin/llama-save-load-state -fa -ngl 10 --model ${model_q4_0}) 2>&1| tee -a $OUT/${ci}-save-load-state.log
(time ./bin/llama-save-load-state -ngl 99 --model ${model_q4_0}) 2>&1| tee -a $OUT/${ci}-save-load-state.log
(time ./bin/llama-save-load-state -fa -ngl 99 --model ${model_q4_0}) 2>&1| tee -a $OUT/${ci}-save-load-state.log
(time ./bin/llama-save-load-state --model ${model_q4_0} -ngl 10 -c 0) 2>&1| tee -a $OUT/${ci}-save-load-state.log
(time ./bin/llama-save-load-state --model ${model_q4_0} -ngl 10 -c 0 -fa) 2>&1| tee -a $OUT/${ci}-save-load-state.log
(time ./bin/llama-save-load-state --model ${model_q4_0} -ngl 99 -c 0) 2>&1| tee -a $OUT/${ci}-save-load-state.log
(time ./bin/llama-save-load-state --model ${model_q4_0} -ngl 99 -c 0 -fa) 2>&1| tee -a $OUT/${ci}-save-load-state.log
function check_ppl {
qnt="$1"
@ -686,17 +697,17 @@ function gg_run_embd_bge_small {
set -e
(time cmake -DCMAKE_BUILD_TYPE=Release ${CMAKE_EXTRA} .. ) 2>&1| tee -a $OUT/${ci}-cmake.log
(time make -j) 2>&1| tee -a $OUT/${ci}-make.log
(time make -j$(nproc)) 2>&1| tee -a $OUT/${ci}-make.log
(time ./bin/llama-embedding --model ${model_f16} -p "what is panda?</s></s>hi\nwhat is panda?</s></s>it's a bear\nwhat is panda?</s></s>The giant panda (Ailuropoda melanoleuca), sometimes called a panda bear or simply panda, is a bear species endemic to China." -ngl 99 -c 0 --pooling rank --embd-normalize -1 --verbose-prompt) 2>&1| tee -a $OUT/${ci}-rk-f16.log
enumllama_pooling_typepooling_type=LLAMA_POOLING_TYPE_UNSPECIFIED;// pooling type for embeddings
enumllama_attention_typeattention_type=LLAMA_ATTENTION_TYPE_UNSPECIFIED;// attention type for embeddings
// // sampling parameters
structllama_sampling_paramssparams;
structcommon_params_samplingsampling;
structcommon_params_speculativespeculative;
structcommon_params_vocodervocoder;
std::stringmodel="";// model path
std::stringmodel_draft="";// draft model for speculative decoding
std::stringmodel_alias="unknown";// model alias
std::stringmodel_url="";// model url to download
std::stringhf_repo="";// HF repo
std::stringhf_file="";// HF file
std::stringprompt="";
std::stringprompt_file="";// store the external prompt file name
std::stringpath_prompt_cache="";// path to file for saving/loading prompt eval state
std::stringinput_prefix="";// string to prefix user inputs with
std::stringinput_suffix="";// string to suffix user inputs with
std::stringlogdir="";// directory in which to save YAML log files
std::stringlookup_cache_static="";// path of static ngram cache file for lookup decoding
std::stringlookup_cache_dynamic="";// path of dynamic ngram cache file for lookup decoding
std::stringlogits_file="";// file for saving *all* logits
std::stringrpc_servers="";// comma separated list of RPC servers
std::stringmodel="";// model path // NOLINT
std::stringmodel_alias="";// model alias // NOLINT
std::stringmodel_url="";// model url to download // NOLINT
std::stringhf_token="";// HF token // NOLINT
std::stringhf_repo="";// HF repo // NOLINT
std::stringhf_file="";// HF file // NOLINT
std::stringprompt="";// NOLINT
std::stringprompt_file="";// store the external prompt file name // NOLINT
std::stringpath_prompt_cache="";// path to file for saving/loading prompt eval state // NOLINT
std::stringinput_prefix="";// string to prefix user inputs with // NOLINT
std::stringinput_suffix="";// string to suffix user inputs with // NOLINT
std::stringlookup_cache_static="";// path of static ngram cache file for lookup decoding // NOLINT
std::stringlookup_cache_dynamic="";// path of dynamic ngram cache file for lookup decoding // NOLINT
std::stringlogits_file="";// file for saving *all* logits // NOLINT
std::vector<std::string>in_files;// all input files
std::vector<std::string>antiprompt;// strings upon which more user input is prompted (a.k.a. reverse prompts)
std::vector<llama_model_kv_override>kv_overrides;
// TODO: avoid tuple, use struct
std::vector<std::tuple<std::string,float>>lora_adapter;// lora adapter path with user defined scale
std::stringlora_base="";// base model path for the lora adapter
boollora_init_without_apply=false;// only load lora to memory, but do not apply it to ctx (user can manually apply lora later using llama_adapter_lora_apply)
std::vector<common_adapter_lora_info>lora_adapters;// lora adapter path with user defined scale
std::vector<llama_control_vector_load_info>control_vectors;// control vector with user defined scale
std::vector<common_control_vector_load_info>control_vectors;// control vector with user defined scale
int32_tverbosity=0;
int32_tcontrol_vector_layer_start=-1;// layer range for control vector
@ -148,54 +296,66 @@ struct gpt_params {
boolspecial=false;// enable special token output
boolinteractive=false;// interactive mode
boolinteractive_first=false;// wait for user input immediately
boolconversation=false;// conversation mode (does not print special tokens and suffix/prefix)
boolprompt_cache_all=false;// save user input and generations to prompt cache
boolprompt_cache_ro=false;// open the prompt cache read-only and do not update it
boolembedding=false;// get only sentence embedding
boolescape=true;// escape "\n", "\r", "\t", "\'", "\"", and "\\"
boolmultiline_input=false;// reverse the usage of `\`
boolsimple_io=false;// improves compatibility with subprocesses and limited consoles
boolcont_batching=true;// insert new sequences for decoding on-the-fly
boolflash_attn=false;// flash attention
boolno_perf=false;// disable performance metrics
boolctx_shift=true;// context shift on inifinite text generation
boolinput_prefix_bos=false;// prefix BOS to user inputs, preceding input_prefix
boolignore_eos=false;// ignore generated EOS tokens
boollogits_all=false;// return logits for all tokens in the batch
booluse_mmap=true;// use mmap for faster loads
booluse_mlock=false;// use mlock to keep model in memory
boolverbose_prompt=false;// print prompt tokens before generation
booldisplay_prompt=true;// print prompt before generation
boolinfill=false;// use infill mode
booldump_kv_cache=false;// dump the KV cache contents for debugging purposes
boolno_kv_offload=false;// disable KV offloading
boolwarmup=true;// warmup run
boolcheck_tensors=false;// validate tensor data
std::stringcache_type_k="f16";// KV cache data type for the K
std::stringcache_type_v="f16";// KV cache data type for the V
ggml_typecache_type_k=GGML_TYPE_F16;// KV cache data type for the K
ggml_typecache_type_v=GGML_TYPE_F16;// KV cache data type for the V