* whisper: suppress Windows compiler warnings
This commit disables compiler warnings on window using MSVC.
The motivation for these changes is that some compilers generate
warnings for these conversion, for example Windows MSVC, and
there are quite a few of them. This makes it a little difficult to
spot new warnings that may be introduced and also can be difficult
for users/embedders of ggml where these warnings are hard to separate
from their own warnings.
* squash! whisper: suppress Windows compiler warnings
Move ggml related warnings into ggml. This commit also fixes the
indentation and adds a missing whitespace to the if statement.
This commit addresses a warnings that is present for Release builds:
```console
[ 30%] Building CXX object src/CMakeFiles/whisper.dir/whisper.cpp.o
In file included from /usr/include/c++/13/bits/stl_tree.h:63,
from /usr/include/c++/13/map:62,
from /home/danbev/work/ai/whisper.cpp/src/whisper-arch.h:5,
from /home/danbev/work/ai/whisper.cpp/src/whisper.cpp:2:
In static member function ‘static void std::__copy_move<false, false, std::random_access_iterator_tag>::__assign_one(_Tp*, _Up*) [with _Tp = const whisper_grammar_element*; _Up = const whisper_grammar_element* const]’,
inlined from ‘static _Up* std::__copy_move<_IsMove, true, std::random_access_iterator_tag>::__copy_m(_Tp*, _Tp*, _Up*) [with _Tp = const whisper_grammar_element* const; _Up = const whisper_grammar_element*; bool _IsMove = false]’ at /usr/include/c++/13/bits/stl_algobase.h:440:20,
inlined from ‘_OI std::__copy_move_a2(_II, _II, _OI) [with bool _IsMove = false; _II = const whisper_grammar_element* const*; _OI = const whisper_grammar_element**]’ at /usr/include/c++/13/bits/stl_algobase.h:506:30,
inlined from ‘_OI std::__copy_move_a1(_II, _II, _OI) [with bool _IsMove = false; _II = const whisper_grammar_element* const*; _OI = const whisper_grammar_element**]’ at /usr/include/c++/13/bits/stl_algobase.h:533:42,
...
```
This warning is caused by the fact that the `stack` vector is empty
when it is passed to `new_stacks.push_back(stack);`.
The suggested fix is to use `new_stacks.emplace_back();` instead of
`new_stacks.push_back(stack);`.
This commit removes the empty `.gitmodules` file from the repository.
The motivation of this is that this file is currently empty and the
project does not use any submodules at this time. Removing it mainly to
reduce clutter in the repository and any confusion when seen the file
in repo.
This commit disables the publishing of the Java binding to the Maven
repository.
The motivation for this is that this job was disabled for some time and
recently it was re-enabled, but the publishing of the Java binding
caused the build to fail and needs to be investigated further.
Refs: https://github.com/ggml-org/whisper.cpp/issues/3079
* Update PATH for main/main-cuda container
Signed-off-by: Xiaodong Ye <xiaodong.ye@mthreads.com>
* Add Dockerfile for musa, .dockerignore and update CI
Signed-off-by: Xiaodong Ye <xiaodong.ye@mthreads.com>
* Add Moore Threads GPU Support in README.md and replace ./main with whisper-cli
Signed-off-by: Xiaodong Ye <xiaodong.ye@mthreads.com>
* Forward GGML_CUDA/GGML_MUSA to cmake in Makefile
Signed-off-by: Xiaodong Ye <xiaodong.ye@mthreads.com>
* Minor updates for PATH ENV in Dockerfiles
Signed-off-by: Xiaodong Ye <xiaodong.ye@mthreads.com>
* Address comments
Signed-off-by: Xiaodong Ye <xiaodong.ye@mthreads.com>
---------
Signed-off-by: Xiaodong Ye <xiaodong.ye@mthreads.com>
* Lazy run TestBase.whisper
* Fix indentation
* Remove disused GGML_HIP_UMA from Ruby
* Add encoder_begin_callback
* Comment out existing abort mechanism
* Add test for encoder_begin_callback
* Add signatures for encoder_begin_callback related methods
* Update gem date
* tune matmul for gcn
* this one is more power efficient
* Update ggml/src/ggml-vulkan/ggml-vulkan.cpp
Co-authored-by: 0cc4m <picard12@live.de>
* disable this tune for the proprietary driver
---------
Co-authored-by: 0cc4m <picard12@live.de>
Add RPC_CMD_HELLO for getting the version of the protocol implemend by
the server. Follow the semantic versioning rules at https://semver.org
Hopefully this bring better user experience when we make breaking
changes at the protocol level and avoid issues like #12465
* graph : make mla compatible with FA
* metal : add exp FA kernels for DeepSeek models
ggml-ci
* llama : minor naming updates
ggml-ci
* ggml : disable FA for DS head sizes
* tests : add FA tests for MLA shapes
ggml-ci
Submit operators using asynchronous threads to improve performance.
Use the environment variable GGML_CANN_ASYNC_MODE to control whether
asynchronous submission is enabled. It is disabled by default.
Testing shows a 10%–20% performance improvement in scenarios with
small parameter sizes, especially in quantized models.
The grouped query attention optmization doesn't require a power of two ratio,
the only thing relying on it was the modulo operation written as bitwise &.
split_k need not depend on gqa_ratio - enable it any time there's only one
workgroup in the X dimension. The shader gets the split index from the x coord,
and multiple workgroups in the X dimension (pre-split) indicates a larger
FA operation that wouldn't need splitting.
Replace compile-time `GGML_HIP_UMA` with environment variable `GGML_CUDA_ENABLE_UNIFIED_MEMORY`. This unifies the usage on NVIDIA and AMD GPUs, and allows a single binary to be shared between integrated and dedicated GPUs.
Multiple optional memory pools are provided for CANN, including VMM,
priority queue-based, and traditional memory pools.
1.When the memory pool is available and GGML_CANN_DISABLE_VMM_POOL
is not defined, the VMM pool is selected by default.
2.Otherwise, if GGML_CANN_ENABLE_BUF_PRIO_POOL is defined,
the priority queue-based memory pool is used.
3.If neither condition is met, the default memory pool is used.
The current usage of the SYCL-Graph extension checks for
the `sycl_ext_oneapi_graph` device aspect. However, it is also
possible to support `sycl_ext_oneapi_limied_graph` devices that
don't support update
* SYCL: Add fp16 support to some elementwise OP kernels
* remove comment
ggml-ci
* Use static_cast directly
* remove not needed cast from tanh
* Use static cast and remove unneeded castings
* Adjust device_support_op for unary OPs
* Use cast_data and typed_data struct to deduplicate casting code
* [CANN] Support ELU and CONV_TRANSPOSE_1D
* [CANN]Modification review comments
* [CANN]Modification review comments
* [CANN]name adjustment
* [CANN]remove lambda used in template
* [CANN]Use std::func instead of template
* [CANN]Modify the code according to the review comments
---------
Signed-off-by: noemotiovon <noemotiovon@gmail.com>
q4_k and q5_k had a lot of redundant global loads where the same 16B of
scale information is repeatedly loaded and decoded during each loop iteration.
This change restructures the loops to more explicitly iterate over whole
blocks in the outer loop (with unrolled inner loop) and to copy/decode the
scale data into shared memory once at the start of each outer loop. The copy
is pipelined so the scale load from global memory is relatively cheap.
This improves q4_k/q5_k model prompt processing performance by around 5-7%.
I briefly tried applying this to q6_k and q4_0, and it didn't help for q6_k
and hurt for q4_0.
The big "else" path in mul_mm_cm2.comp that had all the clamped/unclamped
variants isn't used as often as it originally was (e.g. due to the padded_N
change), so I trimmed it down to offset some of the new complexity of the
semi-manual loop unrolling.
* ggml : FA supports F32 V
* graph : cast KV to F16 when the KV cache is not used
ggml-ci
* server : add test that exercises embeddings with FA enabled
ggml-ci
nem1 must be a multiple of GGML_KQ_MASK_PAD, and GGML_KQ_MASK_PAD is a multiple
of the number of rows in the matrix. The KV dim is a multiple of the number of
columns for the aligned shader.
There seems to be a bubble waking up from waitForFences, which costs a few
percent performance and also increased variance in performance. This change
inserts an "almost_ready" fence when the graph is about 80% complete and we
waitForFences for the almost_ready fence and then spin (with _mm_pauses) waiting
for the final fence to be signaled.
* Prefer vector flash decoding kernel for Gemma models
Vector flash decoding kernel was not being picked for models with head dimension 256. Gemma models are in this category.
Removing this limit improves e2e performance by upto 12% in gen phase throughput for Gemm models.
* Update ggml/src/ggml-cuda/fattn.cu
Co-authored-by: Johannes Gäßler <johannesg@5d6.de>
---------
Co-authored-by: Johannes Gäßler <johannesg@5d6.de>
* CUDA: Simplify and improve CUDA graphs through use of indirect copy pointers
Previously there was complexity in the CUDA graphs implementation due
frequently changing parameters to copy kernels associated with K and V
cache pointers. This patch simplifies by using indirection to avoid
such parameters frequently changing, avoiding the need for frequent
graph updates.
Fixes#12152
* Addressed comments
* fix HIP builds
* properly sync to stream
* removed ggml_cuda_cpy_fn_ptrs
* move stream sync before free
* guard to only use indirection with graphs
* style fixes
* check for errors
---------
Co-authored-by: slaren <slarengh@gmail.com>
When using group query attention, we have one workgroup per KV batch and this
can be very few workgroups (e.g. just 8 in some models). Enable split_k to
spread the work across SMs. This helps a lot when the KV cache is large.
When adjacent batches of Q share the same batches of K/V, batch them into
the same workgroup. For example, when:
dst(128,32,1,1) = FA(q(128,1,32,1), k(128,16640,8,1), v(128,16640,8,1))
previously we would run 32 workgroups computing 1 result each, now we will
run 8 workgroups computing 4 results each.
This doesn't directly translate to better performance (at least when you have
>=32 SMs), but in a subsequent change I'll enable split_k which will scale much
better with 4x fewer workgroups.
* add bf16 support
* use convert_from_bf16_cuda instead of convert_unary_cuda for f32
* revert 7ec5085
* move functionality into convert_unary with constexpr
* coreml : skip model load in convert-whisper-to-coreml.py
This commit updates the conversion process for Whisper models to use the
"mlprogram" format instead of "neuralnetwork".
The motivation for this change is that when using the "neuralnetwork"
format the underlying model produced is based on protobuf and my
understanding is that there are limitations to this format, such as
sizes of strings and the complexity of the model.
Currently when trying to convert larger models such as large-v3 the
conversion fails but succeeds for smaller models.
The "mlprogram" format is a more recent addition to CoreML and is
designed to be more flexible and powerful, allowing for more complex
models and larger data types. This seems to work for larger and smaller
models alike and unless I'm there are considerations that I'm not aware
of I think this is what we should be using moving forward.
The error that is generated for large models is the following:
```console
Running MIL backend_neuralnetwork pipeline: 100%|█████████| 9/9 [00:00<00:00, 35.44 passes/s]
Translating MIL ==> NeuralNetwork Ops: 100%|███████████| 5641/5641 [03:31<00:00, 26.65 ops/s]
Traceback (most recent call last):
File "/Users/danbev/work/ai/whisper-work/models/convert-whisper-to-coreml.py", line 322, in <module>
encoder = convert_encoder(hparams, encoder, quantize=args.quantize)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/Users/danbev/work/ai/whisper-work/models/convert-whisper-to-coreml.py", line 255, in convert_encoder
model = ct.convert(
^^^^^^^^^^^
File "/Users/danbev/work/ai/whisper-work/venv/lib/python3.11/site-packages/coremltools/converters/_converters_entry.py", line 635, in convert
mlmodel = mil_convert(
^^^^^^^^^^^^
File "/Users/danbev/work/ai/whisper-work/venv/lib/python3.11/site-packages/coremltools/converters/mil/converter.py", line 186, in mil_convert
return _mil_convert(
^^^^^^^^^^^^^
File "/Users/danbev/work/ai/whisper-work/venv/lib/python3.11/site-packages/coremltools/converters/mil/converter.py", line 245, in _mil_convert
return modelClass(
^^^^^^^^^^^
File "/Users/danbev/work/ai/whisper-work/venv/lib/python3.11/site-packages/coremltools/models/model.py", line 489, in __init__
self.__proxy__, self._spec, self._framework_error = self._get_proxy_and_spec(
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/Users/danbev/work/ai/whisper-work/venv/lib/python3.11/site-packages/coremltools/models/model.py", line 550, in _get_proxy_and_spec
_MLModelProxy(
ValueError: basic_string
```
Refs: https://github.com/ggml-org/whisper.cpp/issues/3012
This commit disables the FreeBSD job in build.yml of the GitHub Actions
workflow.
The motivation for this is that this job seems to stall and timeout from
time to time, taking up to 6 hours to complete/cancel.
This commit adds `HEAPU8` to the list of exported methods.
The motivation for this commit is that currently this is causing an
error on Window systems where HEAPU8 in undefined, which results in the
following error message in the web console:
```console
main.js:1 Uncaught TypeError:
Cannot read properties of undefined (reading 'buffer') at __emval_get_property
(main.js:1:1363125) at 003a453a:0xc4a47 at 003a453a:0xc51cd at
Object.full_default (eval at craftInvokerFunction (main.js:1:1347011),
<anonymous>:9:10) at whisper.cpp/:647:42
```
Resolves: https://github.com/ggml-org/whisper.cpp/issues/3059
* Fix signature of URI.new7s return value
* Use path instead of string | _ToPath
* Add document comment to RBS
* Remove unnecessary build flags
* Remove unnecessary line
* Remove files have become unnecessary
* Make gem install accept build options for whisper.cpp
* Add instraction for build options in README
* Add methods for check to Options
* Test build options
* Rename: configs -> options
* Add assert_installed assertion
* Use assert_installed
* Remove unused attribute
* Extract dependency check logic as Dependencies class
* Update README
* Add WHISPER_FFMPEG option
* Test extra build options only on local test
* Bump version to 1.3.2 [skip ci]
FFmpeg introduced a new channel layout API that uses `AVChannelLayout`
interface in v6.0. It subsequently dropped the old bitmask-based API
in v7.0.
This updates decode_audio() to support the new channel layout API,
so that we can compile `whisper-cli` and `whisper-server` with FFmpeg
v7.0 or later.
Tested on on Ubuntu 24.10 with FFmpeg v7.0.2.
Signed-off-by: Fujimoto Seiji <fujimoto@ceptord.net>
* Use CMake to build shared object
* Make Rakefile follow change of build process
* Add test for packaging
* Run CI for Ruby bindings almost always
because each CMakeLists.txt might affect Ruby bindings
* Enable PIC
* Bump Ruby version to 3.2 on CI
* Check libgomp
* Check dependency of whisper.cpp accurately
FFmpeg integration was introduced in 1b51fdf by William Tambellini,
but not mentioned in the main documentation.
Add a short guide on how to enable the feature. Confirmed to work
on both Ubuntu 24.04 and Fedora 39.
Signed-off-by: Fujimoto Seiji <fujimoto@ceptord.net>
This commit adds a check for the visionos build version used with vtool
in build-xcframework.sh. The script now checks the Xcode version and
determines whether to use "xros" or "visionos" for the build version.
This commit also uses xcrun for the vtool so that the version of vtool
in xcode command line tools is used instead of the one in the system
path.
Refs: https://github.com/ggml-org/whisper.cpp/pull/2994#issuecomment-2773292223
* tests : add script to benchmark whisper.cpp on LibriSpeech corpus
LibriSpeech is a widely-used benchmark dataset for training and
testing speech recognition models.
This adds a set of scripts to measure the recognition accuracy of
whisper.cpp models, following the common benchmark standards.
Signed-off-by: Fujimoto Seiji <fujimoto@ceptord.net>
* Document how to prepare `whisper-cli` and model files
Feedback from Daniel Bevenius.
This adds a short code example how to prepare the `whisper-cli`
command, to make the initial setup step a little bit clearer.
Signed-off-by: Fujimoto Seiji <fujimoto@ceptord.net>
* tests : Simplify how to set up Python environment
Based on a feedback from Georgi Gerganov.
Instead of setting up a virtual environment in Makefile, let users
set up the Python environment. This is better since users may have
their own preferred workflow/toolkit.
Signed-off-by: Fujimoto Seiji <fujimoto@ceptord.net>
---------
Signed-off-by: Fujimoto Seiji <fujimoto@ceptord.net>
The benchmark script 'scripts/bench-all.sh' assumes that the 11th
field of the output line is a timestamp. This assumption does not
hold when the target model takes a bit longer to process.
Fix this issue by introducing an explicit whitespace to the output
lines of `whisper_print_timings()`.
Signed-off-by: Fujimoto Seiji <fujimoto@ceptord.net>
This commit updates examples/server.py which is used to serve the wasm
examples locally. The changes include:
- Added a redirect from the root URL to /whisper.cpp.
So now accessing http://localhost:8000/ will redirect to
http://localhost:8000/whisper.cpp/ which matches the url for the app
deployed to github pages.
- Custom handling for coi-serviceworker.js to serve it to avoid
and error in the console. This file is not strictly necessary
for the local server to work as the headers are provided already but
it is nice to not have an error in the console.
- Fixed the shutdown of the server to ensure it exits cleanly
on Ctrl+C. Previously it would continue to hang onto the port even
after the processed had exited.
* whisper.wasm : fix unknown language issue
This commit addresses an issue with whisper.wasm where the following
error was being displayed when running the application in github pages:
```
whisper_lang_id: unknown language 'д=␙c'
```
This turned out to be a memory corruption issue and further details
can be found in the reference issue below.
Refs: https://github.com/ggerganov/whisper.cpp/issues/2998
* cpu: refactor SIMD mappings and vectorized op functions into separate files
* Fix warning for ggml_float to float
* Fix warnings
* cpu: move all the operations (except mul_mat) to a separate c++ file
* fix whitespace
* Update ggml/src/ggml-cpu/vec.h
Co-authored-by: Diego Devesa <slarengh@gmail.com>
* Fix PR comments - use GGML_UNUSED, use cassert in ops.cpp
* Reverse the order of import for ops.h and vec.h, to match what was present in ggml-cpu.c previously
---------
Co-authored-by: Diego Devesa <slarengh@gmail.com>
This adds a section to the README.md file that describes how to use the
XCFramework.
The modification for this is that is not obvious how to use the
XCFramework and and example will help.
One thing to note is that the example is using the latest release
including the checksum. We are thinking about how we might automate
this in the future but for now this is a good start.
* Rename oneMKL Interface to oneMath
* Use oneMath for Intel vendor
* Rename occurences to mkl
* clang-format
* Silence verbose warnings
* Set oneMath HIP_TARGETS
* Fix silence warnings
* Remove step to build oneMath from build instructions
* Use fixed oneMath version
* Remove INTEL_CPU
* Fold CMake oneDNN conditions
* Use Intel oneMKL for Intel devices
* Improve CMake message
* Link against MKL::MKL_SYCL::BLAS only
* Move oneMath documentation to Nvidia and AMD sections
This commit removes test-whisper-cli-tiny-en from the gh label.
The motivation for this change is that until recently the tests were
disabled. But now that they are enabled some of the tests, specifically
the ci jobs that use sanatizers (e.g. thread-sanitizer) take a long time
to run as they are instrumented.
Some of these jobs also have matricies which means that there are
multiple jobs are created that all run these tests.
The suggestion here is to limit the number of tests that are run in the
ci jobs so cut down the CI build time.
* coreml: fix Whisper to CoreML conversion by disabling SDPA
This commit disables the use of PyTorch's
`scaled_dot_product_attention` in the Whisper model to avoid
compatibility issues during CoreML conversion.
The issue occurs because coremltools requires PyTorch 2.5.0, but the
Whisper implementation may expect behavior from newer PyTorch versions.
By setting `MultiHeadAttention.use_sdpa = False`, we force Whisper to
use its fallback manual attention implementation, which works correctly
with PyTorch 2.5.0 during the tracing process.
Refs: https://github.com/ggerganov/whisper.cpp/issues/2783
* coreml: fix audio shape in whisper decoder conversion
This commit fixes the audio shape in the whisper decoder conversion
script.
The motivation for this is that the audio shape was incorrect and
was causing the conversion to fail.
* coreml : set -e in generate-coreml-interface.sh
The commit sets the -e flag in the generate-coreml-interface.sh script
to make sure the script fails if any command fails.
* coreml : update generated encoder/decoder interfaces
This commit updates the generated encoder/decoder interfaces for the
whisper model which is the result of running the
generate-coreml-interface.sh script.
* ci : add coreml job that converts base.en to coreml [no ci]
This commit adds a new job to the CI pipeline that downloads the base.en
model and converts it to CoreML format. The CoreML model is then packed
into a zip file and uploaded as an artifact.
This will only be done for pushes to master, releases, or pre-releases.
Refs: https://github.com/ggerganov/whisper.cpp/issues/2783
* coreml : remove publishing of coreml model
* ci : add GGML_OPENMP=OFF to ubuntu-22-gcc-sanitized
This commit re-enables the tests in the build process which are
currently commented out.
It is possible to build the tests using `-DWHISPER_BUILD_TESTS=ON` and
then run a single test using:
```console
$ ctest -R test-whisper-cli-tiny.en --test-dir build
Internal ctest changing into directory: /home/danbev/work/ai/whisper-work/build
Test project /home/danbev/work/ai/whisper-work/build
Start 2: test-whisper-cli-tiny.en
1/1 Test #2: test-whisper-cli-tiny.en ......... Passed 4.44 sec
100% tests passed, 0 tests failed out of 1
Label Time Summary:
en = 4.44 sec*proc (1 test)
gh = 4.44 sec*proc (1 test)
tiny = 4.44 sec*proc (1 test)
Total Test time (real) = 4.44 sec
```
Some of the tests take a long time to run so it might not be a good idea
to enable them in CI, or perhaps we could only run a subset of the tests
in CI.
This commit re-enables the android_java job in the CI workflow. The job
was disabled because of a failing build.
The motivation for this is that Commit
226d344f56 ("whisper.android.java : update
build with ggml source changes") addressed build issues and it should
now be possible to re-enable this job.
If users already set CMAKE_C_COMPILER_LAUNCHER globally, setting it in
cmake again will lead to conflict and compile fail.
Signed-off-by: Jay <BusyJay@users.noreply.github.com>
* ci : add github pages workflow for wasm examples
This commit adds a github workflow to build and deploy the wasm examples
to github pages. The whisper.wasm example is deployed as the main page.
This workflow is trigged by a push to master and will deploy the
examples to: https://ggerganov.github.io/whisper.cpp/.
This requires that the repository has enabled github actions in
`Settings` -> `Pages` -> `Build and deployment` -> `Source` be set to
`GitHub Actions`.
One thing to note is that this commit removes the `talk` example as I'm
not sure how this example is built yet.
Refs: https://github.com/ggerganov/whisper.cpp/issues/2784
* ggml : FA with different K, V head sizes (CPU)
ggml-ci
* metal : add FA with HS=192
* metal : extend FA to support different K and V head sizes
ggml-ci
* metal : add FA vector kernels for heads K 192 and V 128
ggml-ci
* ggml : restrict op on other backends to equal head sizes
ggml-ci
* metal : optimize FA-vec kernel
ggml-ci
* metal : FA remove mq registers
* metal : improve MoE mul_mat_id condition
ggml-ci
* metal : fix comments + remove unnecessary addition
ggml-ci
* metal : avoid too much shared memory usage with mul_mat_id
ggml-ci
* vulkan: fix coopmat shader generation when cross-compiling
Previously the status of coopmat{,2} support isn't passed to the
vulkan-shaders-gen project building on the host, which leads to build
failure because of the cross-compiling code expecting coopmat{,2}
shaders that didn't get generated.
Fix this by passing the coopmat{,2} support status to vulkan-shaders
subproject.
Signed-off-by: Icenowy Zheng <uwu@icenowy.me>
* Only call coop-mat shaders once
* Fix whitespace
---------
Signed-off-by: Icenowy Zheng <uwu@icenowy.me>
Co-authored-by: bandoti <141645996+bandoti@users.noreply.github.com>
This patch enables usage of MMA when one of the
dimensions of the matrix(ie either M or N) is 1. This
is useful in case of token generation where N < 2.
The concept of 'GEMV Forwarding' is used where when one
of the matrix has a single row/column, the elements are
broadcasted, instead of using packing routine to prepack
the matrix elements.
This change results in 5% - 15% improvement in total
speed(ie all tokens/total time), across various batch
sizes. This is in comparision with the corresponding
dot product implementation.
The patch is tested with FP32 models of Meta-Lllama-3-8B,
Mistral-7B, Llama-2-7B-chat-hf on a IBM POWER10 machine.
Signed-off-by: Amrita H S <amritahs@linux.vnet.ibm.com>
* rpc : send hash when tensor data is above some fixed threshold
ref #10095
* rpc : put cache under $HOME/.cache/llama.cpp
* try to fix win32 build
* another try to fix win32 build
* remove llama as dependency
Adding in DetectedLanguage(), a function to retrieve the detected
language that's populated by processing audio. Also adding in a unit
test to test the success.
Co-authored-by: Amanda Der Bedrosian <aderbedrosian@sdl.com>
* bindings.ruby : fix test failures in test_whisper
This commit updates the parallel tests to use 2 processors instead of
the number of processors on the system. It also comments out the setting
of the log callback to an empty lambda as this causes a segfault when
enabled.
The motivation for the change to the number of processors is that if one
has a large number of processors, for example I have 16 on the machine I
used to test this, this would cause the following warning to be printed:
```console
whisper_full_with_state: input is too short - 680 ms < 1000 ms. consider padding the input audio with silence
```
This is logged from:
```c++
int whisper_full_with_state(
struct whisper_context * ctx,
struct whisper_state * state,
struct whisper_full_params params,
const float * samples,
int n_samples) {
...
if (seek_end < seek_start + 100) {
WHISPER_LOG_WARN("%s: input is too short - %d ms < 1000 ms. consider padding the input audio with silence\n", __func__, (seek_end - seek_start)*10);
return 0;
}
```
This will return early and there will be segment callbacks to be invoked
which in turn will cause the tests to fail.
* bindings.ruby : fix warnings in tests
This commit fixes the following warnings in the Ruby tests:
```console
/whisper/bindings/ruby/tests/test_segment.rb:52:
warning: ambiguity between regexp and two divisions:
wrap regexp in parentheses or add a space after `/' operator
```
And also adds a '_' prefix to some unused variables to avoid warnings.
* bindings.ruby : enable Wisper.log_set in tests
The commit reverts the commenting out of the Whisper.log_set call in
the test_whisper.rb tests.
I'm no longer getting segfaults when running the tests with this
which was the case earlier. One theory could be that I rebased this to
include the latest ggml sync to master to make sure things still worked.
With the latest changes in ggml, I can't reproduce the segfaults.
This change upstreams llamafile's cpu matrix
multiplication kernels for ppc64le ISA using MMA
builtins. This patch handles matrix multiplication
between quantised datatypes, block_q4_0 and
block_q8_0.
This change results in 5% - 50% 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>
The OOB calculation could be wrong if the last iteration was during one of
the unrolled loops. Adjust the unrolling counts to avoid this. Add a couple
new backend tests that hit this failure on NVIDIA GPUs.
* tests: add mul_mat perf/functional tests for p021/nc vulkan shaders
* vulkan: Optimize mul_mat_vec p021 and nc shaders.
These shaders are used in attention calculations, and when the KV cache grows
large they start to dominate the run time. For the nc shader (which is called
with large 'k' dimension), use unrolling and vector loads. For the p021 shader
(which is called with large 'm' and small 'k' dimensions), take advantage of
grouped query attention to reuse loads from the A matrix for the whole group,
and reduce the number of workgroups (too much overhead from tiny dispatches).
Using subgroupAdd in the p021 shader also helps, use that conditionally.
* [SYCL] Fix build on Windows when ccache enabled (llama/9954)
* take effect only on windows and force it to icl
---------
Co-authored-by: Romain Biessy <romain.biessy@codeplay.com>
* Add block interleaving support for Q4_K quantization
* Remove whitespaces and fix CI/CD issues
* Update pointer of bsums from int16_t to const int16_t
* Add vector version of quantize_q8_K_4x8 function
* Update code formatting based on review comments
- Find out active blocks per SM using cudaOccupancyMaxActiveBlocksPerMultiprocessor API. Use this value to determine the optimal parallel_blocks value.
- Prefer vector flash attention kernels over MMA kernel for BS=1
Fixes Issue: #12182
---------
Co-authored-by: Johannes Gäßler <johannesg@5d6.de>
* ci: add visionOS build workflow
Add a new GitHub Actions workflow for building on visionOS with CMake and Xcode.
* ggml: Define _DARWIN_C_SOURCE for visionOS to fix missing u_xxx typedefs
* ci: remove define hacks for u_xxx system types
---------
Co-authored-by: Giovanni Petrantoni <7008900+sinkingsugar@users.noreply.github.com>
I've been seeing significantly worse performance for tg with flash attention
enabled vs disabled, and it seems to be related to the submit heuristic.
Change the heuristic to check how many bytes worth of weight matrix are
used and flush every 100MB, and ramp up after the first few submits.
This seems to resolve the issue, and also increases perf for non-FA a bit.
* opencl: more profiling timing
* opencl: generate trace for profiling
* opencl: reduce profiling overhead
* Populate profiling timing info at the end rather than after each
kernel run
* opencl: fix for chrome tracing
* Enable CUDA Graph on CTK < 12.x
`cudaGraphExecUpdate` API was changed on 12.x. For this reason CUDA graph support was disabled on older CUDA toolkit. This change enables CUDA support in CTK version < 12.x by using older API if CTK < 12.x.
* Fix compilation errors with MUSA
* Disable CUDA Graph for MUSA
* cmake: Factor out compiler flag function from ggml
llama.cpps's build requires it, too, and we may want to make use of it
without add_subdirectory(ggml).
* cmake: Enable building against system ggml
This facilitates package maintenance for Linux distributions, where the
libggml library most likely will be shipped as an individual package
upon which a llama.cpp package depends.
When fattn-wmma was ported over to warp64 various bits that also touch fattn-vec where converted to
selectable warp size, however the fattn-vec kernels dont work with 64 wide warps for now, so we need
to avoid launching them with parameters for warp64
refactor mmqv to unify the calculation of nwarps and rows per block between host and device code.
---------
Co-authored-by: Johannes Gäßler <johannesg@5d6.de>
This patch nudges the llama.cpp a bit to be supported on PoCL which
doesn't support OpenCL C CL2.0. The issue is solved by querying the
device for the supported OpenCL C versions and using the highest one
available.
This commit updates the compilation of default.metallib to skip the
intermediate .air (Apple Intermediate Representation) file.
The motivation for this change is to simplify the custom command a
little and avoid generating and then removing the .air file.
Nothing installs to it yet, so when attempting to use the cmake package,
set_and_check() triggers an error if the directory doesn't already exist
for other reasons.
This commit updates the Makefile to use cmake instead of make to build
whisper.cpp.
The motivation for this change is that currently the make recipe test
will fail with the following error:
```console
$ make test
Mkdir build
Mkdir models
Build whisper
make[1]: Entering directory '/home/danbev/work/ai/whisper-work'
make[1]: *** No rule to make target 'libwhisper.a'. Stop.
make[1]: Leaving directory '/home/danbev/work/ai/whisper-work'
make: *** [Makefile:33: whisper] Error 2
```
* whisper : add support for ggml_backend_buffer_type
Signed-off-by: Dan Johansson <dan.johansson@arm.com>
* fix compile error when building on Ubuntu
Signed-off-by: Dan Johansson <dan.johansson@arm.com>
* remove copyright header from include file
Signed-off-by: Dan Johansson <dan.johansson@arm.com>
---------
Signed-off-by: Dan Johansson <dan.johansson@arm.com>
* bindings.java : enable copyLibs task [no ci]
This commit adds a dependency on the copyLibs task to the sourcesJar and
jar tasks. This ensures that the libwhisper.so file is copied to the
correct location before the jar is built.
It also sets the executable bit on the gradlew file.
* bindings.java : add copyLibs dep for processResources [no ci]
This will otherwise cause builds to fail after doing an initial build.
* bindings.java : pass structs by value to native code
This commit refactors the code to pass the structs by value to the
native code. This is done by creating a ByValue class for each struct
and using it in the Java code.
The motivation for this change is that without this application crashes
due to what I believe was memory mis-alignement. When the structs were
passed to the native code they would be att different memory locations.
Passing by value overcomes this issue and considering that the structs
hold parementers (context and full params) it might be alright do to
this. These changes allow all the tests to pass.
* bindings.java : fix javadoc warnings [no ci]
* bindings.java : fix libwhisper.dylib path in build.gradle [no ci]
This commit fixes the copyLibwhisperDynlib task in the build.gradle file
to copy the correct libwhisper.dylib file from build/src.
This commit updates the instructions for running the test in the
JavaScript bindings README file.
The motivation for this is for Node.js versions after v16.4.0 the
`--experimental-wasm-threads` and `--experimental-wasm-simd` flags are
no longer required and they generate the following errors:
```console
$ node --experimental-wasm-threads --experimental-wasm-simd ../tests/test-whisper.js
node: bad option: --experimental-wasm-threads
node: bad option: --experimental-wasm-simd
```
This commit add GGML_USE_CPU to built target library to enable CPU
backend.
The motivation for this that without the compile definition the CPU
backend is not enabled and the app will crash when trying to use it.
* whisper.android.java : update build with ggml source changes
This commit updates the whisper.android.java build to include the
new ggml source files and directories. The gradle build configuration is
also updated to include the aliyun maven repository.
* examples : reduce initial memory to 512MB
This commit reduces the initial memory size to 512MB. This is done to
to avoid WebAssembly memory allocation issues on some platforms. It also
adds a flag to allow the memory to grow dynamically (up to the maximum).
The motivation for this change is that currently the initial memory is
set to 2GB which might be to large for some platforms. This will lead to
an error being thrown from the JavaScript code generated by Emscripten
when trying to allocate memory. More details can be found in the
referenced issue below.
* examples : set MAXIMUM_MEMORY instead of TOTAL_MEMORY
This commit sets MAXIMUM_MEMORY instead of TOTAL_MEMORY in the
whisper.wasm example.
The motivation for this is that TOTAL_MEMORY and INITIAL_MEMORY are
actually the same thing. Instead we want to set MAXIMUM_MEMORY to
2GB.
Refs: https://github.com/ggerganov/whisper.cpp/issues/2920
Refs: https://emscripten.org/docs/tools_reference/settings_reference.html#initial-memory
This commit fixes the nthread parsing in the whisper.wasm example when
using the `Threads` slider to change the number of threads to be used.
Currently this results in the following error:
```console
main.js:5597 Uncaught TypeError: Cannot convert "5" to int
at checkAssertions (main.js:5597:21)
at Object.toWireType (main.js:5611:15)
at Object.full_default (eval at new_ (main.js:5292:27), <anonymous>:10:26)
at whisper.wasm/:649:42
```
This commit adds a fix to the server.py file to handle requests for
web worker files when running the local python server to test the wasm
examples.
The motivation for this is that currently the server is serving files
from the build-em/bin directory which is where the .worker.js files
exist. But when examples access these resources they do so with the
application context path, for example /whisper.wasm/libmain.worker.js
but this will not be found as it currently works.
This commit adds debug level logging for the native build options and
variables to ggml/CMakeLists.txt.
The motivation for this is that it can be useful to see the effective
result of `GGML_NATIVE`, `GGML_NATIVE_DEFAULT`, and `INS_ENB` for a
cmake build. I've found myself adding similar logging a few times now,
so I thought it might be a good idea to add this.
Example output, specifying `-DCMAKE_MESSAGE_LOG_LEVEL=DEBUG` when
running cmake produces the following output:
```console
-- GGML_NATIVE : OFF
-- GGML_NATIVE_DEFAULT : OFF
-- INS_ENB : OFF
```
* whisper : improve whisper-cli executable path detection in model download shell scripts
If whisper-cli is found on the path, do not suggest invoking from build directory. This improves flexibility and usability for distribution and packaging scenarios.
* whisper : enhance Windows model download batch script to have comparable functionality and behaviour as shell scripts
* Download models to the current directory if the script is executed from the \bin\ directory (for future distribution scenarios where the script is in the \bin\ subdirectory of a Windows build)
* Add model_path command line argument
* If whisper-cli is found on the path, do not suggest invoking from build directory
* whisper : resolve compiler warning by removing duplicate definition of NOMINMAX in whisper-cli code
This change initializes each decoder's random number generator with a
unique seed.
The motivation for this is that currently all decoders are initialized
with the same seed value, 0. The result of this is that for the same
state (logits, probs, and logprobs) they will produce the same output.
This commit removes the -DCMAKE_CUDA_ARCHITECTURES=all flag from the
windows-cublas job in the build.yml file.
The motivation for this is that building for all architectures is
unnecessary and takes a long time. Without this flag the architectures
will instead be set by ggml-cuda.
Refs: https://github.com/ggerganov/whisper.cpp/pull/2915#issuecomment-2743160743
This change ensures that when the script is packaged and distributed, models are downloaded to the current directory instead of the script's location, preventing conflicts with system directories. This improves flexibility and usability for distribution and packaging scenarios.
This commit updates the recommended version of Python to 3.11 for Core
ML conversion support. It also adds the `-e` flag to the
`generate-coreml-model.sh` script to ensure that the script exits on the
first error.
The motivation for this that when following the installation instructions
using Python 3.10 I get the following error:
```console
(venv) $ ./models/generate-coreml-model.sh base.en
A module that was compiled using NumPy 1.x cannot be run in
NumPy 2.1.3 as it may crash. To support both 1.x and 2.x
versions of NumPy, modules must be compiled with NumPy 2.0.
Some module may need to rebuild instead e.g. with 'pybind11>=2.12'.
If you are a user of the module, the easiest solution will be to
downgrade to 'numpy<2' or try to upgrade the affected module.
We expect that some modules will need time to support NumPy 2.
Traceback (most recent call last): File "/whisper-work/models/convert-whisper-to-coreml.py", line 2, in <module>
import torch
File "/whisper-work/venv/lib/python3.10/site-packages/torch/__init__.py", line 870, in <module>
from . import _masked
File "/whisper-work/venv/lib/python3.10/site-packages/torch/_masked/__init__.py", line 420, in <module>
def sum(input: Tensor,
File "/whisper-work/venv/lib/python3.10/site-packages/torch/_masked/__init__.py", line 223, in _apply_docstring_templates
example_input = torch.tensor([[-3, -2, -1], [0, 1, 2]])
/whisper-work/venv/lib/python3.10/site-packages/torch/_masked/__init__.py:223: UserWarning: Failed to initialize NumPy: _ARRAY_API not found (Triggered internally at /Users/distiller/project/pytorch/torch/csrc/utils/tensor_numpy.cpp:68.)
example_input = torch.tensor([[-3, -2, -1], [0, 1, 2]])
Minimum required torch version for importing coremltools.optimize.torch is 2.1.0. Got torch version 1.11.0.
Traceback (most recent call last):
File "/whisper-work/models/convert-whisper-to-coreml.py", line 4, in <module>
import coremltools as ct
File "/whisper-work/venv/lib/python3.10/site-packages/coremltools/__init__.py", line 120, in <module>
from . import converters, models, optimize, proto
File "/whisper-work/venv/lib/python3.10/site-packages/coremltools/converters/__init__.py", line 7, in <module>
from . import libsvm, sklearn, xgboost
File "/Users/danbev/work/ai/whisper-work/venv/lib/python3.10/site-packages/coremltools/converters/xgboost/__init__.py", line 6, in <module>
from ._tree import convert
File "/Users/danbev/work/ai/whisper-work/venv/lib/python3.10/site-packages/coremltools/converters/xgboost/_tree.py", line 9, in <module>
from ._tree_ensemble import convert_tree_ensemble as _convert_tree_ensemble
File "/Users/danbev/work/ai/whisper-work/venv/lib/python3.10/site-packages/coremltools/converters/xgboost/_tree_ensemble.py", line 11, in <module>
from ...models.tree_ensemble import TreeEnsembleClassifier
File "/Users/danbev/work/ai/whisper-work/venv/lib/python3.10/site-packages/coremltools/models/__init__.py", line 6, in <module>
from . import (
File "/Users/danbev/work/ai/whisper-work/venv/lib/python3.10/site-packages/coremltools/models/ml_program/__init__.py", line 6, in <module>
from . import compression_utils
File "/Users/danbev/work/ai/whisper-work/venv/lib/python3.10/site-packages/coremltools/models/ml_program/compression_utils.py", line 8, in <module>
from coremltools.converters.mil.mil import Operation as _Operation
File "/Users/danbev/work/ai/whisper-work/venv/lib/python3.10/site-packages/coremltools/converters/mil/__init__.py", line 7, in <module>
from .frontend.tensorflow.tf_op_registry import register_tf_op
File "/Users/danbev/work/ai/whisper-work/venv/lib/python3.10/site-packages/coremltools/converters/mil/frontend/__init__.py", line 6, in <module>
from . import tensorflow, tensorflow2, torch
File "/Users/danbev/work/ai/whisper-work/venv/lib/python3.10/site-packages/coremltools/converters/mil/frontend/torch/__init__.py", line 11, in <module>
from . import ops, quantization_ops
File "/Users/danbev/work/ai/whisper-work/venv/lib/python3.10/site-packages/coremltools/converters/mil/frontend/torch/ops.py", line 36, in <module>
from .internal_graph import InternalTorchIRGraph, InternalTorchIRNode
File "/Users/danbev/work/ai/whisper-work/venv/lib/python3.10/site-packages/coremltools/converters/mil/frontend/torch/internal_graph.py", line 15, in <module>
from .exir_utils import extract_io_from_exir_program
File "/Users/danbev/work/ai/whisper-work/venv/lib/python3.10/site-packages/coremltools/converters/mil/frontend/torch/exir_utils.py", line 99, in <module>
) -> Dict[str, torch.fx.Node]:
AttributeError: module 'torch' has no attribute 'fx'
```
Using Python3.11 the conversion script runs without any errors.
This commit adds a check for the CPU backend initialization in the
whisper library. If the initialization fails, an exception is thrown.
The motivation for this change is to make the library more robust and
handle the case when the CPU backend initialization fails.
Resolves: https://github.com/ggerganov/whisper.cpp/issues/2917
This commit updates the hisper.objc README.md to reflect the changes of
using the xcframework and the new build process.
Since whisper.cpp is no longer compiled by the example project, instead
the library from the xframework will be used, the build instructions
have been removed.
This commit updates the evict-old-files parameter for the windows-cublas
build job to 5 days.
The motivation for this change is to avoid the full rebuild which takes
around 1.5 hours for the windows-cublas build job. Considering that
there are periods of low traffic on whisper.cpp (like weekends etc.) it
might be better to have a longer eviction policy to avoid the full
rebuild.
* xcframework : add support for CoreML to ios/macOS
This commit add support for compiling whisper with CoreML support for
iOS and macOS.
The motivation for this change is it will allow users to use a Core ML
model or fall back to a ggml model if Core ML is not available.
With the updated xcframework, I was able to run the whisper.objc example
and successfully load a Core ML model:
```console
whisper_init_state: loading Core ML model from '/Users/danbev/Library/Developer/CoreSimulator/Devices/25E8C27D-0253-4281-AF17-C3F2A4D1D8F4/data/Containers/Bundle/Application/B81F6FF0-BF1A-40DF-AC2A-3908EC4BCC9A/whisper.objc.app/ggml-base.en-encoder.mlmodelc'
whisper_init_state: first run on a device may take a while ...
whisper_init_state: Core ML model loaded
```
* squash! xcframework : add support for CoreML to ios/macOS
Fix grammar in output message.
This commit adds a check for `WHISPER_SDL2` to the deprecation warning
examples. This is to prevent the examples from being built when
WHISPER_SDL2 is not enabled.
The motivation for this is that currently these deprecation executables
are generate and when run they refer the user to examples with other
names, for example `whisper-command` but unless they have built with
`WHISPER_SDL2` those executable will not be present:
```console
$ ls build/bin/
bench command main quantize stream whisper-bench whisper-cli
whisper-server
$ ./build/bin/command
WARNING: The binary 'command' is deprecated.
Please use 'whisper-command' instead.
See https://github.com/ggerganov/whisper.cpp/tree/master/examples/deprecation-warning/README.md for more information.
```
This commit updates the windows-cublas job to use Ninja as the build
system instead of msbuild/msvc.
The motivation for this is that msbuild/mscv does not seem to handle
ccache/sccache well, for example it ignores the
`CMAKE_C_COMPILER_LAUNCHER` etc. variables. But using Ninja as the build
caching works and the build is initially the same speed as it is
currently (without caching) subsequently builds are much faster.
Refs: https://github.com/ggerganov/whisper.cpp/issues/2781
This commit updates the README files for the wasm examples to include
instructions on how to run the examples using the provided server.py
which was included in Commit 6e8242f7fe
("examples : command.wasm updates (#2904)").
The motivation for this is consistency with the command.wasm example.
This commit updates the command.wasm example by adding a server.py script to make it easy to start a local http server to try out the example, updates the build instructions, and also addresses some of the compiler warnings that were being generated.
* emscripten : fix TOTAL_STACK for wasm
This commit moves the TOTAL_STACK setting from the compile flags to the
linker flags. This is because the TOTAL_STACK setting is a linker
setting.
The motivation for this change is that currently the following warnings
are generated when building:
```console
em++: warning: linker setting ignored during compilation: 'TOTAL_STACK' [-Wunused-command-line-argument]
em++: warning: linker setting ignored during compilation: 'TOTAL_STACK' [-Wunused-command-line-argument]
em++: warning: linker setting ignored during compilation: 'TOTAL_STACK' [-Wunused-command-line-argument]
em++: warning: linker setting ignored during compilation: 'TOTAL_STACK' [-Wunused-command-line-argument]
em++: warning: linker setting ignored during compilation: 'TOTAL_STACK' [-Wunused-command-line-argument]
em++: warning: linker setting ignored during compilation: 'TOTAL_STACK' [-Wunused-command-line-argument]
```
* examples : suppress C++17 deprecation warning for std::codecvt_utf8
This commit suppresses the C++17 deprecation warning for
std::codecvt_utf8 similar to what is done in
examples/talk-llama/unicode.cpp.
The motivation for this change is to suppress these warnings:
```console
/Users/danbev/work/ai/whisper-work/examples/common.cpp:251:31: warning: 'codecvt_utf8<wchar_t>' is deprecated [-Wdeprecated-declarations]
251 | std::wstring_convert<std::codecvt_utf8<wchar_t>> converter;
| ^
/Users/danbev/work/wasm/emsdk/upstream/emscripten/cache/sysroot/include/c++/v1/codecvt:193:28: note: 'codecvt_utf8<wchar_t>' has been explicitly marked deprecated here
193 | class _LIBCPP_TEMPLATE_VIS _LIBCPP_DEPRECATED_IN_CXX17 codecvt_utf8 : public __codecvt_utf8<_Elem> {
| ^
/Users/danbev/work/wasm/emsdk/upstream/emscripten/cache/sysroot/include/c++/v1/__config:723:41: note: expanded from macro '_LIBCPP_DEPRECATED_IN_CXX17'
723 | # define _LIBCPP_DEPRECATED_IN_CXX17 _LIBCPP_DEPRECATED
| ^
/Users/danbev/work/wasm/emsdk/upstream/emscripten/cache/sysroot/include/c++/v1/__config:688:49: note: expanded from macro '_LIBCPP_DEPRECATED'
688 | # define _LIBCPP_DEPRECATED __attribute__((__deprecated__))
| ^
/Users/danbev/work/ai/whisper-work/examples/common.cpp:251:10: warning: 'wstring_convert<std::codecvt_utf8<wchar_t>>' is deprecated [-Wdeprecated-declarations]
251 | std::wstring_convert<std::codecvt_utf8<wchar_t>> converter;
| ^
/Users/danbev/work/wasm/emsdk/upstream/emscripten/cache/sysroot/include/c++/v1/locale:3145:28: note: 'wstring_convert<std::codecvt_utf8<wchar_t>>' has been explicitly marked deprecated here
3145 | class _LIBCPP_TEMPLATE_VIS _LIBCPP_DEPRECATED_IN_CXX17 wstring_convert {
| ^
/Users/danbev/work/wasm/emsdk/upstream/emscripten/cache/sysroot/include/c++/v1/__config:723:41: note: expanded from macro '_LIBCPP_DEPRECATED_IN_CXX17'
723 | # define _LIBCPP_DEPRECATED_IN_CXX17 _LIBCPP_DEPRECATED
| ^
/Users/danbev/work/wasm/emsdk/upstream/emscripten/cache/sysroot/include/c++/v1/__config:688:49: note: expanded from macro '_LIBCPP_DEPRECATED'
688 | # define _LIBCPP_DEPRECATED __attribute__((__deprecated__))
| ^
/Users/danbev/work/ai/whisper-work/examples/common.cpp:257:31: warning: 'codecvt_utf8<wchar_t>' is deprecated [-Wdeprecated-declarations]
257 | std::wstring_convert<std::codecvt_utf8<wchar_t>> converter;
| ^
/Users/danbev/work/wasm/emsdk/upstream/emscripten/cache/sysroot/include/c++/v1/codecvt:193:28: note: 'codecvt_utf8<wchar_t>' has been explicitly marked deprecated here
193 | class _LIBCPP_TEMPLATE_VIS _LIBCPP_DEPRECATED_IN_CXX17 codecvt_utf8 : public __codecvt_utf8<_Elem> {
| ^
/Users/danbev/work/wasm/emsdk/upstream/emscripten/cache/sysroot/include/c++/v1/__config:723:41: note: expanded from macro '_LIBCPP_DEPRECATED_IN_CXX17'
723 | # define _LIBCPP_DEPRECATED_IN_CXX17 _LIBCPP_DEPRECATED
| ^
/Users/danbev/work/wasm/emsdk/upstream/emscripten/cache/sysroot/include/c++/v1/__config:688:49: note: expanded from macro '_LIBCPP_DEPRECATED'
688 | # define _LIBCPP_DEPRECATED __attribute__((__deprecated__))
| ^
/Users/danbev/work/ai/whisper-work/examples/common.cpp:257:10: warning: 'wstring_convert<std::codecvt_utf8<wchar_t>>' is deprecated [-Wdeprecated-declarations]
257 | std::wstring_convert<std::codecvt_utf8<wchar_t>> converter;
| ^
/Users/danbev/work/wasm/emsdk/upstream/emscripten/cache/sysroot/include/c++/v1/locale:3145:28: note: 'wstring_convert<std::codecvt_utf8<wchar_t>>' has been explicitly marked deprecated here
3145 | class _LIBCPP_TEMPLATE_VIS _LIBCPP_DEPRECATED_IN_CXX17 wstring_convert {
| ^
/Users/danbev/work/wasm/emsdk/upstream/emscripten/cache/sysroot/include/c++/v1/__config:723:41: note: expanded from macro '_LIBCPP_DEPRECATED_IN_CXX17'
723 | # define _LIBCPP_DEPRECATED_IN_CXX17 _LIBCPP_DEPRECATED
| ^
/Users/danbev/work/wasm/emsdk/upstream/emscripten/cache/sysroot/include/c++/v1/__config:688:49: note: expanded from macro '_LIBCPP_DEPRECATED'
688 | # define _LIBCPP_DEPRECATED __attribute__((__deprecated__))
| ^
4 warnings generated.
```
* ggml : suppress double-promotion warning in GGML_F16x4_REDUCE
This commit adds a cast to `ggml_float` in the `GGML_F16x4_REDUCE` macro
to suppress a double-promotion warning.
Currently the following warning is generated when compiling the
command.wasm example:
```console
/whisper-work/ggml/src/ggml-cpu/ggml-cpu.c:1592:5: warning: implicit conversion increases floating-point precision: 'float' to 'ggml_float' (aka 'double') [-Wdouble-promotion]
1592 | GGML_F16_VEC_REDUCE(sumf, sum);
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/Users/danbev/work/ai/whisper-work/ggml/src/ggml-cpu/ggml-cpu.c:932:37: note: expanded from macro 'GGML_F16_VEC_REDUCE'
932 | #define GGML_F16_VEC_REDUCE GGML_F16x4_REDUCE
| ^
/Users/danbev/work/ai/whisper-work/ggml/src/ggml-cpu/ggml-cpu.c:920:44: note: expanded from macro 'GGML_F16x4_REDUCE'
918 | res = wasm_f32x4_extract_lane(x[0], 0) + \
| ~ ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
919 | wasm_f32x4_extract_lane(x[0], 1) + \
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
920 | wasm_f32x4_extract_lane(x[0], 2) + \
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~
921 | wasm_f32x4_extract_lane(x[0], 3); \
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/whisper-work/ggml/src/ggml-cpu/ggml-cpu.c:1640:9: warning: implicit conversion increases floating-point precision: 'float' to 'ggml_float' (aka 'double') [-Wdouble-promotion]
1640 | GGML_F16_VEC_REDUCE(sumf[k], sum[k]);
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/Users/danbev/work/ai/whisper-work/ggml/src/ggml-cpu/ggml-cpu.c:932:37: note: expanded from macro 'GGML_F16_VEC_REDUCE'
932 | #define GGML_F16_VEC_REDUCE GGML_F16x4_REDUCE
| ^
/Users/danbev/work/ai/whisper-work/ggml/src/ggml-cpu/ggml-cpu.c:920:44: note: expanded from macro 'GGML_F16x4_REDUCE'
918 | res = wasm_f32x4_extract_lane(x[0], 0) + \
| ~ ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
919 | wasm_f32x4_extract_lane(x[0], 1) + \
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
920 | wasm_f32x4_extract_lane(x[0], 2) + \
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~
921 | wasm_f32x4_extract_lane(x[0], 3); \
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
2 warnings generated.
```
wasm_f32x4_extract_lane returns a 32-bit float and this is what the
addition is performed on. But there is an implicit conversion from
32-bit float to 64-bit double when the result is assigned to `res`,
which is of type `ggml_float`. My understanding here is that this is
intentional and adding a cast to `ggml_float` should suppress the
warning.
* emscripten : add -Wno-deprecated to for emscripten
This commit adds -Wno-deprecated to the CMAKE_CXX_FLAGS for emscripten
builds.
The motivation for this is that currently there a number of warnings
generated like the following:
```console
warning: JS library symbol '$print' is deprecated. Please open a bug if you have a continuing need for this symbol [-Wdeprecated]
warning: JS library symbol '$printErr' is deprecated. Please open a bug if you have a continuing need for this symbol [-Wdeprecated]
em++: warning: warnings in JS library compilation [-Wjs-compiler]
em++: warning: linker setting ignored during compilation: 'ENVIRONMENT' [-Wunused-command-line-argument]
warning: JS library symbol '$print' is deprecated. Please open a bug if you have a continuing need for this symbol [-Wdeprecated]
warning: JS library symbol '$printErr' is deprecated. Please open a bug if you have a continuing need for this symbol [-Wdeprecated]
em++: warning: warnings in JS library compilation [-Wjs-compiler]
warning: JS library symbol '$print' is deprecated. Please open a bug if you have a continuing need for this symbol [-Wdeprecated]
warning: JS library symbol '$printErr' is deprecated. Please open a bug if you have a continuing need for this symbol [-Wdeprecated]
em++: warning: warnings in JS library compilation [-Wjs-compiler]
em++: warning: linker setting ignored during compilation: 'ENVIRONMENT' [-Wunused-command-line-argument]
em++: warning: linker setting ignored during compilation: 'ENVIRONMENT' [-Wunused-command-line-argument]
```
The downside of this is that we might miss other deprecation warnings
in the future so I'm not sure if this is acceptable. But it make the
wasm examples cleaner without the warnings.
* examples : fix tautological-compare warning in stb_vorbis.c [no ci]
This commit applies a fix to address a tautological-compare warning
in stb_vorbis.c.
The motivation for this is that currently the following warning is
generated when compiling the commmand-wasm example:
```console
/Users/danbev/work/ai/whisper-work/examples/stb_vorbis.c:1404:75: warning: pointer comparison always evaluates to false [-Wtautological-compare]
1404 | if (f->stream_start + loc >= f->stream_end || f->stream_start + loc < f->stream_start) {
| ^
1 warning generated.
```
This fix was taken from an open pull request on the stb repository
that addreses this issue:
https://github.com/nothings/stb/pull/1746
* squash! examples : update command.wasm instructions [no ci]
This commit adds a Python script to serve the the wasm examples build
in the `build-em` directory. Initially I thought that it would be enough
to start a simple python server but I did not notice that there was an
error in the browser console when I did that:
```console
command.js:1 Uncaught (in promise) DataCloneError: Failed to execute 'postMessage' on 'Worker': SharedArrayBuffer transfer requires self.crossOriginIsolated.
at command.js:1:1206224
at new Promise (<anonymous>)
at loadWasmModuleToWorker (command.js:1:1204981)
at Array.map (<anonymous>)
at Object.loadWasmModuleToAllWorkers (command.js:1:1206428)
at command.js:1:1204318
at callRuntimeCallbacks (command.js:1:1202062)
at preRun (command.js:1:6136)
at run (command.js:1:1294094)
at removeRunDependency (command.js:1:7046)
```
We need a few CORS headers to be set and in order hopefully make this
easy for users a Python script is added to the examples directory.
This should be able to server all the wasm examples provided they have
been built. command.wasm's README.md is updated to reflect this change.
* examples : remove unused functions
This commit removed the unused functions convert_to_utf8 and
convert_to_wstring from examples/common.cpp.
* Revert "examples : fix tautological-compare warning in stb_vorbis.c [no ci]"
This reverts commit 8e3c47d961.
We should not make this change here and instead when the upstream PR is
merged we can sync with it.
Refs: https://github.com/ggerganov/whisper.cpp/issues/2784
The commit updates the CUDA tookkit installation steps to use variables
for the CUDA version and the components versions.
The motivation for this change is that the currently the versions for
the components are used in multiple places and it is hard to update
and maintain.
Adding in EncoderBeginCallback to the Context's Process callback.
This optional callback function returns false if computation should
be aborted.
Co-authored-by: Amanda Der Bedrosian <aderbedr@gmail.com>
* ci : add ccache action to windows-cublas job
This commit adds the ccache action to the windows-cublas job. This will
allow us to cache the build artifacts and hopefully speed up the build
process.
Refs: https://github.com/ggerganov/whisper.cpp/issues/2781
This commit fixes compiler warnings in whisper.cpp by changing the type
of the loop index variable from int64_t to size_t.
Currently the following warnings are generated by the compiler:
```console
/whisper.cpp/src/whisper.cpp:209:27: warning: comparison of integers of different signs: 'int64_t' (aka 'long long') and 'size_t' (aka 'unsigned long') [-Wsign-compare]
209 | for (int64_t i = 0; i < nels; ++i) {
| ~ ^ ~~~~
/whisper.cpp/src/whisper.cpp:219:27: warning: comparison of integers of different signs: 'int64_t' (aka 'long long') and 'size_t' (aka 'unsigned long') [-Wsign-compare]
219 | for (int64_t i = 0; i < nels; ++i) {
| ~ ^ ~~~~
```
This commit adds the missing env.branch_name to the build.yml file.
The motivation for this is that the currently the build is failing
during the release job because the branch_name is not set in the
an invalid tag is being used.
* whisper : enable compiler warnings for src
This commit enables compiler warnings for the src directory. Currently
when the WHISPER_ALL_WARNINGS flag is set to ON is only enables warnings
in ggml, by setting GGML_ALL_WARNINGS to ON. This commit adds the same
compiler flags for whisper's src directory.
The motivation for this is to catch potential bugs and issues early on
in the development process.
* squash! whisper : enable compiler warnings for src
Remove GF_C_FLAGS and GF_CXX_FLAGS from add_compile_options.
* ci : add release job and include xcframework
This commit adds a release job that uploads the xcframework as an
artifact and creates a release with the xcframework as an asset.
This job can be triggered manually and enables a pre-release tag name to
be specified to that these releases can be distinguished from the
regular releases more easily.
Resolves: https://github.com/ggerganov/whisper.cpp/issues/2886
* examples : use xcframework in whisper.objc example
This commit updates the whisper.objc example to use the xcframework.
The motivation for this to be consistent with the swift example and to
also act as a reference for how to use the xcframework in an objc
project.
Resolves: https://github.com/ggerganov/whisper.cpp/issues/2881
* examples : setup audio session viewDidload
This commit adds the setup of the audio session in the viewDidload
method of the ViewController.m file. This is necessary to allow the app
to record audio.
The motivation for this is that without this it was not possible to
caputue audio from the microphone. It was possible to click on the
Capture button but nothing happened after that, and the button was not
marked red indicating that the button could be clicked again to stop
capturing. With this change it is possible to capture audio from the
microphone and get it transcribed.
This commit adds the GGML_USE_CPU=ON flag to the whisper.objc project in
order to enable the CPU backend for the whisper.objc project.
The motivation for this change is that currently the following error
is generated when running the example:
```console
ggml_backend_buffer_type_t ggml_backend_get_default_buffer_type(ggml_backend_t backend) {
return ggml_backend_dev_buffer_type(backend->device); <- Thread 1: EXC_BAD_ACCESS (code=1, address=0x70)
}
```
If we inspect the `backend` variable we can see that it is a `nullptr`.
```console
(lldb) p backend
(ggml_backend_t) nullptr
```
When running in a simulator and that automatically means that there will
be no gpu as there is a check for this in the code. But the CPU backend
should still be present.
The objective-c code will compile the whisper sources including the ggml
sources. And if `-DGGMLL_USE_CPU` is not defined then there will be no
CPU backend, and in this particular case of backend at all.
Resolves: https://github.com/ggerganov/whisper.cpp/issues/2870
* examples : add dl to the list of libraries linked
This commit adds the dynamic linker library to the list of libraries
linked by the examples.
The motivation for this change is that when building the examples on
ubuntu 20.04, which uses GCC 9.4.0, the dynamic linker requires
explicit linking or the following error is generated:
```console
[ 64%] Linking CXX executable ../../bin/whisper-cli
cd /app/whisper.cpp/build/examples/cli && /usr/bin/cmake -E cmake_link_script CMakeFiles/whisper-cli.dir/link.txt --verbose=1
/usr/bin/c++ -O3 -DNDEBUG CMakeFiles/whisper-cli.dir/cli.cpp.o -o ../../bin/whisper-cli -Wl,-rpath,/app/whisper.cpp/build/src:/app/whisper.cpp/build/ggml/src: ../libcommon.a ../../src/libwhisper.so.1.7.4 -pthread ../../ggml/src/libggml.so ../../ggml/src/libggml-cpu.so ../../ggml/src/libggml-base.so
/usr/bin/ld: ../libcommon.a(common-whisper.cpp.o): undefined reference to symbol 'dlclose@@GLIBC_2.2.5'
/usr/bin/ld: /lib/x86_64-linux-gnu/libdl.so.2: error adding symbols: DSO missing from command line
collect2: error: ld returned 1 exit status
make[2]: *** [examples/cli/CMakeFiles/whisper-cli.dir/build.make:89: bin/whisper-cli] Error 1
make[2]: Leaving directory '/app/whisper.cpp/build'
make[1]: *** [CMakeFiles/Makefile2:433: examples/cli/CMakeFiles/whisper-cli.dir/all] Error 2
make[1]: Leaving directory '/app/whisper.cpp/build'
make: *** [Makefile:130: all] Error 2
```
Resolves: https://github.com/ggerganov/whisper.cpp/issues/2854
* metal : refactor im2col parameters into a struct
* metal: Change im2col offset types from int32_t to uint64_t to support larger memory offsets
* metal : refactor sum_rows parameters into a struct
* metal : refactor soft_max parameters into a struct
* metal : refactor diag_mask_inf parameters into a struct
* metal : refactor ssm_conv parameters into a struct
* metal : refactor ssm_scan parameters into a struct
* metal : refactor get_rows parameters into a struct
* metal : refactor group_norm parameters into a struct
* metal : refactor conv_transpose_1d parameters into a struct
* metal : refactor upscale parameters into a struct
* metal : refactor pad parameters into a struct
* metal : refactor pad_reflect_1d parameters into a struct
* metal : refactor arange parameters into a struct
* metal : refactor timestep_embedding parameters into a struct
* metal : refactor argsort parameters into a struct
* metal : refactor leaky_relu parameters into a struct
* metal : refactor pool_2d parameters into a struct
* metal : fix trailing whitespace
---------
Co-authored-by: alexju <alexju@tencent.com>
This commit updates the custom command to build the default.metallib
file to use the correct path to ../ggml-common.h by using the variable
METALLIB_COMMON.
The motivation for this change is that currently when building and
specifying GGML_METAL_EMBED_LIBRARY=OFF the following error is
generated:
```console
[ 11%] Linking CXX shared library ../../bin/libggml.dylib
[ 11%] Built target ggml
make[2]: *** No rule to make target `ggml/src/ggml-metal/ggml-common.h', needed by `bin/default.metallib'. Stop.
make[1]: *** [ggml/src/ggml-metal/CMakeFiles/ggml-metal-lib.dir/all] Error 2
```
With the above change the build could progress but there was a follow
on error about not being able to find the ggml-common.h file in
ggml-metal.metal where is was included as a relative path:
```console
[ 11%] Compiling Metal kernels
/Users/danbev/work/llama.cpp/build/bin/ggml-metal.metal:6:10: error: '../ggml-common.h' file not found, did you mean 'ggml-common.h'?
^~~~~~~~~~~~~~~~~~
"ggml-common.h"
1 error generated.
```
Removing the relative path then allowed the build to complete
successfully.
Fix the following error:
```
ggml-alloc.c:99: not enough space in the buffer
ggml_tallocr_alloc: not enough space in the buffer to allocate blk.17.ffn_down.weight (needed 27525120, available 27521024)
```
which occurs when `ggml_backend_opencl_context::alignment` is larger
than `cl_ptr_base` (hard-coded to `0x1000`).
Also, fix `ggml_backend_opencl_context::alignment` was set to
`CL_DEVICE_MEM_BASE_ADDR_ALIGN` which was treated as bytes but the
value is reported in bits.
* ggml-cpu: Faster IQ1 mul_mat_vec on AVX2 using BMI2 instructions
* cmake: Add GGML_BMI2 build option
* ggml: enable BMI2 on relevant CPU variants
* ggml-cpu: include BMI2 in backend score
* ggml-cpu: register BMI2 in ggml_backend_cpu_get_features
* ggml-cpu: add __BMI2__ define when using MSVC
-- it might happen if ggml is loaded from 2 separate libraries since each one of them will expose the class. This is more of a guard since we want to use only Metal as embedded library and don't care about the other case.
* ggml_compute_forward_concat() for arbitrary tensor type
* Check that tensors' type match
* ggml-cpu.c: check type of source tensors
* ggml-cpu.c: move tensor type check to ggml_compute_forward_concat()
* ggml.c: check concatenated tensor type
* Remove tensor type check from ggml_compute_forward_concat() in ggml-cpu.c
..., as it was moved to ggml.c.
* Add include files for std::min/max and std::toupper/tolower
* win32: move _USE_MATH_DEFINES before includes to ensure M_PI is defined
* Use GGML_RESTRICT instead of "restrict" keyword everywhere, and use "__restrict" in MSVC plain C mode
* win32: only use __restrict in MSVC if C11/C17 support is not enabled
---------
Co-authored-by: Marcus Groeber <Marcus.Groeber@cerence.com>
* Upgrade init_tensor API to return a ggml_status
To prepare for an 'abort-free' ggml
(ggml not to abort on OOMs but return a OOM status),
as agreeed with Diego in the ggml repo,
upgrade the init_tensor() and view_init() APIs
to return a ggml_status.
* misc fixes
---------
Co-authored-by: slaren <slarengh@gmail.com>
* vulkan: implement specialized MMV kernels for IQ2 quantizations
* vulkan: add MMV kernels for IQ3 quants
* vulkan: Increase MMV batch size and unroll IQ LUT setup
* vulkan: fix init_iq_shmem for WG sizes larger than tables
* vulkan: common batch size for all I-quants
* Added SVE Support for Q2_K Quantized Models
* Use 4-space indentation in the switch cases
* removed comments lines
* Remove the loop Retain the curly bracess for better understanding of code
* Remove the comment like added for q3_k_q8_k kernel
---------
Co-authored-by: vithulep <p.m.vithule1517@gmail.com>
* Fix dependencies between ggml and backends
ggml backends link only to ggml-base and ggml links to all backends.
* Fix installation of ggml backends
Set up GNUInstallDirs before setting the installation directory of ggml backends
* cuda: restrict SILU_BACK to fp32, since fp16 exceeds the desired test threshold
* vulkan: specify fp32-only support for certain ops (that are now tested for fp16 as well)
* f32 sigmoid in vulkan supports op
* Revert "f32 sigmoid in vulkan supports op"
This reverts commit c6f04b3c19bf4504c2776149c6d8cd84e0b48acb.
* Support fp16 unary operations in the CUDA backend
* cpu: increase fp16 support for unary operators in the CPU backend
* cuda: increase fp16 support for unary operators in the CUDA backend
* Add test cases for fp16 unary operators
* metal: update supports_op for unary operators that don't support fp16, to prevent test-backend-ops from failing
* metal: fix PR comments for unary op support after fp16 unary tests
* Updated models download URL
* Updated list of models available
All of the high efficiency quantized models are rejected when trying to download. They exist on the server. Let's allow them.
* added path prefix for whisper-cli in message to user. The message is misleading if this script is called from another script in a different folder. So the message has to be fixed.
* undid download URL change I made earlier. Fixed filepath.Join(urlPath, model) bug.
* Undid download URL change I made earlier.
Seems that the old URL works but only when provided a model to download. Still doesn't explain why there's a different download URL that also works. Please elucidate in docs.
* Fixed URLForModel Function's bug
filepath.Join is designed for filesystem paths, and it uses backslashes (\) on Windows. URLs, however, require forward slashes (/), so the use of filepath.Join is inappropriate for constructing URLs.
The fmt.Sprintf function ensures that forward slashes are used.
* Fixed URL trailing / double slash bug
Ensure no double slash by trimming trailing '/' from srcUrl if present
* Fixed bad download URL, missing ggml prefix
Not sure if that was a bug I introduced but it was trying to download without the prefix.
* Added question before downloading all models. Added download size estimate
HEAD Requests:
Efficiently fetches file sizes without downloading the content.
Interactive Workflow:
Allows the user to make informed decisions about downloading all models.
Safe Defaults:
Aborts if the user does not explicitly confirm.
* Fixed Unbuffered channel warning.
warning in context.go : misuse of unbuffered os.Signal channel as argument to signal.
The warning indicates that the unbuffered channel used in signal.Notify in context.go may be misused. In Go, unbuffered channels can cause potential deadlocks if signals are sent faster than they are received.
* Fixed download size calculation, download URL prefix bug, added link to models URL for user.
The URL formatter was prepending the model name to the formatted model name in the URL
* Added logs and exes to gitignore
* Delete bindings/go/examples/go-model-download/go-model-download.exe
* Delete whisper_build.log
* Support float16-to-float16 add/sub/mul/div operations in the CUDA backend
* Add fp16 support for add/sub/mul/div on the CPU backend
* Add test cases for fp16 add/sub/mul/div
* opt performance by reorder for Intel GPU
* detect hw type and save opt feature, and print opt feature
* correct name
* support optimize graph once when compute graph, record the opt status in tensor->extra, make CI passed
* add env variable GGML_SYCL_DISABLE_OPT for debug
* use syclex::architecture replace the custom hw define, update the guide for GGML_SYCL_DISABLE_OPT
* add performance data
* mv getrows functions to separeted files
* fix global variables
---------
Co-authored-by: arthw <14088817+arthw@users.noreply.github.com>
* MUSA: support ARM64 and enable __dp4a .etc
* fix cross entropy loss op for musa
* update
* add cc info log for musa
* add comment for the MUSA .cc calculation block
---------
Co-authored-by: Bodhi Hu <huaishun.hu@mthreads.com>
* ggml-cpu: Add CPU backend support for KleidiAI library
* Add environmental variable GGML_KLEIDIAI_SME
* Add support for multithread LHS conversion
* Switch kernel selection order to dotprod and i8mm
* updates for review comments
* More updates for review comments
* Reorganize and rename KleidiAI files
* Move ggml-cpu-traits.h to source file
* Update cmake for SME build and add alignment for SME
* Remove append GGML_USE_CPU_KLEIDIAI to the GGML_CDEF_PUBLIC list
* vulkan: initial support for IQ1_S and IQ1_M quantizations
* vulkan: define MMV kernels for IQ1 quantizations
* devops: increase timeout of Vulkan tests again
* vulkan: simplify ifdef for init_iq_shmem
* ggml-cpu : add chunking support to mul_mat_id
* allocate chunk counter in wdata
parallelize src1 quantization by column to allows parallelization even when there is only one row
* disable for arm
* cleanup
* better way to disable for arm
* fix uninitialized counter when using 1 thread only
* revert test-backend-ops changes
* Bug fix for clamp_f32
When using tensors larger than 1d clamp operation does not work due to the restriction of returning if ith is not 0.
* Bug fix for clamp_f32
* Bug fix for clamp_f32
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.
* 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.
* feat: Add beam size parameter to stream.cpp for beam search configuration
* feat: Add beam size parameter to whisper full params in stream example
* fix: Remove duplicate beam search size assignment in server.cpp
- [x] Linux / [FreeBSD](https://github.com/ggerganov/whisper.cpp/issues/56#issuecomment-1350920264)
- [x] Linux / [FreeBSD](https://github.com/ggml-org/whisper.cpp/issues/56#issuecomment-1350920264)
- [x] [WebAssembly](examples/whisper.wasm)
- [x] Windows ([MSVC](https://github.com/ggerganov/whisper.cpp/blob/master/.github/workflows/build.yml#L117-L144) and [MinGW](https://github.com/ggerganov/whisper.cpp/issues/168)]
- [x] Windows ([MSVC](https://github.com/ggml-org/whisper.cpp/blob/master/.github/workflows/build.yml#L117-L144) and [MinGW](https://github.com/ggml-org/whisper.cpp/issues/168)]
@ -184,11 +183,11 @@ speed-up - more than x3 faster compared with CPU-only execution. Here are the in
```
- To ensure `coremltools` operates correctly, please confirm that [Xcode](https://developer.apple.com/xcode/) is installed and execute `xcode-select --install` to install the command-line tools.
- Python 3.10 is recommended.
- Python 3.11 is recommended.
- MacOS Sonoma (version 14) or newer is recommended, as older versions of MacOS might experience issues with transcription hallucination.
- [OPTIONAL] It is recommended to utilize a Python version management system, such as [Miniconda](https://docs.conda.io/en/latest/miniconda.html) for this step:
- To create an environment, use: `conda create -n py310-whisper python=3.10 -y`
- To activate the environment, use: `conda activate py310-whisper`
- To create an environment, use: `conda create -n py311-whisper python=3.11 -y`
- To activate the environment, use: `conda activate py311-whisper`
- Generate a Core ML model. For example, to generate a `base.en` model, use:
@ -225,7 +224,7 @@ speed-up - more than x3 faster compared with CPU-only execution. Here are the in
The first run on a device is slow, since the ANE service compiles the Core ML model to some device-specific format.
Next runs are faster.
For more information about the Core ML implementation please refer to PR [#566](https://github.com/ggerganov/whisper.cpp/pull/566).
For more information about the Core ML implementation please refer to PR [#566](https://github.com/ggml-org/whisper.cpp/pull/566).
## OpenVINO support
@ -310,7 +309,7 @@ This can result in significant speedup in encoder performance. Here are the inst
The first time run on an OpenVINO device is slow, since the OpenVINO framework will compile the IR (Intermediate Representation) model to a device-specific 'blob'. This device-specific blob will get
cached for the next run.
For more information about the OpenVINO implementation please refer to PR [#1037](https://github.com/ggerganov/whisper.cpp/pull/1037).
For more information about the OpenVINO implementation please refer to PR [#1037](https://github.com/ggml-org/whisper.cpp/pull/1037).
@ -388,8 +443,9 @@ Run the inference examples as usual, for example:
We have two Docker images available for this project:
1. `ghcr.io/ggerganov/whisper.cpp:main`: This image includes the main executable file as well as `curl` and `ffmpeg`. (platforms: `linux/amd64`, `linux/arm64`)
2. `ghcr.io/ggerganov/whisper.cpp:main-cuda`: Same as `main` but compiled with CUDA support. (platforms: `linux/amd64`)
1. `ghcr.io/ggml-org/whisper.cpp:main`: This image includes the main executable file as well as `curl` and `ffmpeg`. (platforms: `linux/amd64`, `linux/arm64`)
2. `ghcr.io/ggml-org/whisper.cpp:main-cuda`: Same as `main` but compiled with CUDA support. (platforms: `linux/amd64`)
3. `ghcr.io/ggml-org/whisper.cpp:main-musa`: Same as `main` but compiled with MUSA support. (platforms: `linux/amd64`)
Use the [scripts/bench-wts.sh](https://github.com/ggerganov/whisper.cpp/blob/master/scripts/bench-wts.sh) script to generate a video in the following format:
Use the [scripts/bench-wts.sh](https://github.com/ggml-org/whisper.cpp/blob/master/scripts/bench-wts.sh) script to generate a video in the following format:
```bash
./scripts/bench-wts.sh samples/jfk.wav
@ -596,7 +653,7 @@ In order to have an objective comparison of the performance of the inference acr
use the [whisper-bench](examples/bench) tool. The tool simply runs the Encoder part of the model and prints how much time it
took to execute it. The results are summarized in the following Github issue:
There are various examples of using the library for different projects in the [examples](examples) folder.
@ -667,13 +750,13 @@ Some of the examples are even ported to run in the browser using WebAssembly. Ch
| [whisper.android](examples/whisper.android) | | Android mobile application using whisper.cpp |
| [whisper.nvim](examples/whisper.nvim) | | Speech-to-text plugin for Neovim |
| [generate-karaoke.sh](examples/generate-karaoke.sh) | | Helper script to easily [generate a karaoke video](https://youtu.be/uj7hVta4blM) of raw audio capture |
See whisper.cpp's [README](https://github.com/ggml-org/whisper.cpp/blob/master/README.md) for available options. You need convert options present the README to Ruby-style options.
For boolean options like `GGML_CUDA`, the README says `-DGGML_CUDA=1`. You need strip `-D`, prepend `--enable-` for `1` or `ON` (`--disable-` for `0` or `OFF`) and make it kebab-case: `--enable-ggml-cuda`.
For options which require arguments like `CMAKE_CUDA_ARCHITECTURES`, the README says `-DCMAKE_CUDA_ARCHITECTURES="86"`. You need strip `-D`, prepend `--`, make it kebab-case, append `=` and append argument: `--cmake-cuda-architectures="86"`.
Usage
-----
@ -228,7 +240,7 @@ The second argument `samples` may be an array, an object with `length` and `each
# Run the entire model: PCM -> log mel spectrogram -> encoder -> decoder -> text
# Not thread safe for same context
# Uses the specified decoding strategy to obtain the text.
#
# The second argument +samples+ must be an array of samples, respond to :length, or be a MemoryView of an array of float. It must be 32 bit float PCM audio data.
check_required_tool "cmake""Please install CMake 3.28.0 or later (brew install cmake)"
check_required_tool "xcodebuild""Please install Xcode and Xcode Command Line Tools (xcode-select --install)"
check_required_tool "libtool""Please install libtool which should be available with Xcode Command Line Tools (CLT). Make sure Xcode CLT is installed (xcode-select --install)"
check_required_tool "dsymutil""Please install Xcode and Xcode Command Line Tools (xcode-select --install)"
set -e
## Clean up previous builds
rm -rf build-apple
rm -rf build-ios-sim
rm -rf build-ios-device
rm -rf build-macos
rm -rf build-visionos
rm -rf build-visionos-sim
rm -rf build-tvos-sim
rm -rf build-tvos-device
# Setup the xcframework build directory structure
setup_framework_structure(){
localbuild_dir=$1
localmin_os_version=$2
localplatform=$3# "ios", "macos", "visionos", or "tvos"
localframework_name="whisper"
echo"Creating ${platform}-style framework structure for ${build_dir}"
| `GG_BUILD_METAL` | Enable Metal acceleration on Apple Silicon |
| `GG_BUILD_BLAS` | Enable BLAS CPU acceleration |
| `GG_BUILD_OPENVINO` | Enable OpenVINO support |
| `GG_BUILD_COREML` | Enable Core ML support for Apple Neural Engine |
| `GG_BUILD_LOW_PERF` | Limit tests for low-performance hardware |
| `GG_BUILD_TEST_MODELS` | Comma-separated list of models to test (e.g. "tiny.en,tiny,base,medium", defaults to all models unless `GG_BUILD_LOW_PERF` is set) |
# It requires Windows 8.1 or later for PrefetchVirtualMemory
Some files were not shown because too many files have changed in this diff
Show More
Reference in New Issue
Block a user
Blocking a user prevents them from interacting with repositories, such as opening or commenting on pull requests or issues. Learn more about blocking a user.