* Conv2D: Add CPU version
* Half decent
* Tiled approach for F32
* remove file
* Fix tests
* Support F16 operations
* add assert about size
* Review: further formatting fixes, add assert and use CPU version of fp32->fp16
* Update docker.yml
修改docker.yml文件中的内容使其停止周期性的运行该workflow，如果想要运行该workflow可以手动启动
* Remove redundant include path in CMakeLists.txt
The parent directory '..' was removed from the include directories for the ggml-cpu-feats target, to avoid unnecessary include paths.
* Enable scheduled Docker image builds
Uncomments the workflow schedule to trigger daily Docker image rebuilds at 04:12 UTC, improving automation and keeping images up to date.
* SYCL: disable faulty fp16 CPU exponent for now
* Revert "SYCL: disable faulty fp16 CPU exponent for now"
This reverts commit ed0aab1ec31b4eb4b0f275dd7acd41d96a375202.
* SYCL: disable faulty fp16 CPU exponent for now
* Fix logic of disabling exponent kernel
* implement unary REGLU/GEGLU/SWIGLU cpu ops
* relax constraints
* duplicate shape of source
* fix ggml_vec_geglu_f16
* special case gated ops
* implement unary REGLU/GEGLU/SWIGLU cuda ops
* tighten constraints again
* refactor into GGML_GLU_OP
* metal : add glu kernels
ggml-ci
* add CUDA_GLU_BLOCK_SIZE [no ci]
* more constraints and use 64bit ints
ggml-ci
* 64bit multiplication [no ci]
* implement swapped variants (cpu/cuda)
* update comment [no ci]
ggml-ci
* Vulkan: Add GLU ops and shaders
* SYCL: Implement fused kernel GEGLU, SWIGLU and REGLU for single up+gate
* ggml : implement GLU for split up/gate (llama/14181)
* implement GLU for split up/gate
* add tests for ggml_glu_split
* Vulkan: Implement glu_split logic and shader support
* add split to logging [no ci]
* SYCL: refactor element_size ops and add split up and gate support to gated kernels
* SYCL: switch GEGLU to use tanh approximation
---------
Co-authored-by: 0cc4m <picard12@live.de>
Co-authored-by: Akarshan <akarshan@menlo.ai>
* GGML: increase OP count in assertion
* Refactor: Optimize SYCL element-wise operations with unary function inlining
This commit refactors the SYCL element-wise operations to improve performance by:
- Inlining unary operations (sgn, abs, elu, gelu, silu, etc.) to reduce kernel launch overhead.
- Introducing helper functions `op_xxx` for each unary operation to encapsulate the logic.
- Replacing direct kernel calls with calls to these inlined functions.
- Using `__dpct_inline__` to encourage compiler inlining.
- Minor code cleanup and consistency improvements.
The changes aim to reduce kernel launch overhead and improve the overall efficiency of element-wise operations on SYCL devices.
* vulkan: Increase workgroup size for GLU, for performance (llama/14345)
* vulkan: Increase workgroup size for GLU, for performance
* vulkan: change GLU shaders to do one element per invocation rather than one row per workgroup
* merge fix
* metal : add support for split and swap
ggml-ci
---------
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
Co-authored-by: 0cc4m <picard12@live.de>
Co-authored-by: Akarshan <akarshan@menlo.ai>
Co-authored-by: Jeff Bolz <jbolz@nvidia.com>
* vulkan: Add fusion support for RMS_NORM+MUL
- Add a use_count to ggml_tensor, so we can detect if an output is used more than once.
- Change the ggml-vulkan rms_norm shader to optionally multiply by another tensor.
- Add detection logic and basic fusion logic in ggml-vulkan.
- Add some testing support for fusion. Rather than computing one node at a time, allow
for computing the whole graph and just testing one node's results. Add rms_norm_mul tests
and enable a llama test.
* extract some common fusion logic
* fix -Winconsistent-missing-override
* move ggml_can_fuse to a common function
* build fix
* C and C++ versions of can_fuse
* move use count to the graph to avoid data races and double increments when used in multiple threads
* use hash table lookup to find node index
* change use_counts to be indexed by hash table slot
* minimize hash lookups
style fixes
* last node doesn't need single use.
fix type.
handle mul operands being swapped.
* remove redundant parameter
---------
Co-authored-by: slaren <slarengh@gmail.com>
* CUDA: add bf16 and f32 support to cublas_mul_mat_batched
* Review: add type traits and make function more generic
* Review: make check more explicit, add back comments, and fix formatting
* Review: fix formatting, remove useless type conversion, fix naming for bools
* ggml : add ggml_set_rows
Add ggml_set_rows(a, b, c) which copies rows from 'b' into 'a' using
indices from 'c'.
ref: #8366
* use I64 for indices
* ggml : add repeat impl for i64
* ggml : add ggml_is_contiguous_rows
* ggml : ggml_set_rows support broadcast
* ggml : ggml_set_rows support quantized dst
ggml-ci
* ggml : support GGML_TYPE_F32 ".from_float" trait
* ggml : ggml_set_rows update comment + better index name
* tests : add ggml_set_rows
* metal : add ggml_set_rows implementation
ggml-ci
* ggml : simplify forward_dup_f32
* ggml : fix supports_op
* tests : add comment to set_rows
* ggml : leave the repeat_i64 for a separate PR
ggml-ci
* ggml : set_rows use std::min instead of MIN
* ggml : better error message for set_rows unsupported type
* metal : perform op->type check only once
* tests : more consistent implementation + more tests
ggml-ci
---------
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* Add support for VK_EXT_debug_utils to add labels to Vulkan objects. In step 1 compute pipelines are getting labeled.
* remove #ifdef for debug utils and add queue marker.
* add "align corners" mode for bilinear upscale, and allow downscaling
* add ggml_interpolate, deprecate ggml_upscale_ext, pass in align-corners as bit-flag
* test-backend-ops: replace ggml_upscale_ext with ggml_interpolate, add test cases for downscale and align-corners
This commit renames the variable `best_mad` to `best_error` in the
`make_qkx2_quants` function.
The motivation for this is that the name `best_mad` can be somewhat
confusing if mean absolute deviation (MAD) is not in use.
This commit modified the musa docker file to selectively copy
directories needed for the container image.
This commit also added a step to the docker workflow to free up disk
space in attempt to make enough room for the large musa build
containers.
The motivation for this change is to reduce the size of the container
image and try to avoid disk usage issues in CI.
* ci: set fail-fast to false in docker.yml
This commit modifies the GitHub Actions workflow for Docker builds to
disable the fail-fast behavior.
The motivation for this is that currently if one of the strategy jobs
fails any other job that is in progress will be cancelled. There is no
need for this as the jobs are independent.
* ci : update docker.yml to use a single build
This commit updates the docker job to only build the image once instead
of twice (only happens when pushing to the master branch). Instead this
will tag the image with the commit SHA when pushing to master.
The motivation for this change is to reduce the time it takes to run
this job and also it might help with the disk space issues we are
experiencing for this job when it runs on pushes to master.
* Add a test for segment
* Check option existence
* Use more proper variable to define build option
* Assert Core ML enabled
* Define Whisper::VERSION
* Add test for Whisper::VERSION
* Add signature of Whisper::VERSION
* whisper : add version function
This commit adds a version function to the whisper API.
The motivation for this is that it might be convenient to have a way to
programmatically check the version.
Example usage:
```c++
printf("Using whisper version: %s\n", whisper_version());
```
Will output:
```console
Using whisper version: 1.7.6
```
* examples : add version to android example CMakeLists.txt
* ci : add should_release variable
This commit adds a `should_release` variable to the GitHub Actions
workflow to determine if a release should be created based on the tag or
branch conditions.
The motivation for this that it simplifies the logic for deciding
whether to upload artifacts or not, making it easier to maintain if we
need to change the conditions in the future.
* ci : set release draft to true
This commit modifies the GitHub Actions workflow to support
tag-based releases. When a tag is pushed that starts with 'v', the
workflow will use that tag name for the release process.
I think this was the once the behavior, but it was lost in updates that
I've made to the workflow. This commit restores that functionality.
* stream : add nullptr check of whisper_context
This commit adds a check to ensure that the `whisper_context` is not
null after initialization.
The motivation for this is that currently, if the initialization fails,
the program continues to run leading to a segmentation fault. This sort
of check is performed by others examples like whisper-cli.
Refs: https://github.com/ggml-org/whisper.cpp/issues/3280#issuecomment-3003778035
* examples : add nullptr check for whisper_context
This commit re-enables the main-cuda Docker build in the CI workflow.
The main-cuda Dockerfile has been updated to remove build artifacts
and also print the size of the /app directory after the build. A similar
change was recently made to the musa Dockerfile, and perhaps this job
was also having similar disk space issues.
The motivation for this change is that this configuration has been
disabled for a while due to persistent build failures. However, the
actual logs are now longer available.
Resolves: https://github.com/ggml-org/whisper.cpp/issues/3040
* ci : reduce musa image size
This commit contains an attempt to reduce the size of the musa Docker
image by copying only the necessary files from the build stage.
The motivation for this is that the CI runs sometimes fail with out of
memory errors. These seems to be able to pass for PRs, at least
sometimes but fail upon push to the master branch.
* ci : remove build time files instead of selective copying
* ci : add apt-get clean to musa Dockerfile
This commit adds `apt-get clean` to the musa Dockerfile to reduce the
image size by removing cached package files after installation.
The motivation for this is to try to reduce the size of the Docker image
and see if this can avoid the "no space left on device" error during
the CI build process.
Refs: https://github.com/ggml-org/whisper.cpp/actions/runs/15815324254
* Add Apple frameworks to $LDFLAGS when needed
* Add utility method to Options
* Remove unnecessary propaty date from gemspec
* Add Apple frameworks for CoreML build
* Add Accelerate framework only for Apple platform
* Fix ZipURI#cache signature
* Download test fixtures if needed
* Add header and namespace to use enqueue_functions extension
* Convert submit and parallel_for to use new extension in convert.cpp
* Convert submit and parallel_for to use extension in ggml-sycl.cpp
* Convert submit and parallel_for to use extension in gla.cpp
* Convert submit and parallel_for in mmq.cpp
* Convert submit and parallel_for in mmvq.cpp
* Convert submit and parallel_for in remaining files
* Convert all simple parallel_for to nd_launch from enqueue_functions
extension
* Wrapping extension in general function
Create a general function that enable the enqueue_functions extension if
it is enable in the compiler, otherwise call the general SYCL function
to launch kernels.
---------
Signed-off-by: nscipione <nicolo.scipione@codeplay.com>
* Add PowerPC feature detection and scoring
* ggml-cpu: Implement GGML_CPU_ALL_VARIANTS for PowerPC
* ggml-cpu: Delay some initializations until function is called
When using GGML_BACKEND_DL=ON, these initializations might use
instructions that are not supported by the current CPU.
---------
Co-authored-by: Diego Devesa <slarengh@gmail.com>
* android : update CMakeLists.txt to use FetchContent for ggml
This commit updates the CMakeLists.txt file for the Android Whisper
example to use FetchContent for managing the ggml library.
The motivation for this change is avoid having to make manual changes to
the CMakeLists.txt file after syncing the ggml library.
I've built and run the example locally to verify that it works as
expected.
Refs: https://github.com/ggml-org/whisper.cpp/pull/3265#issuecomment-2986715717
* android.java : update cmake to use FetchContent for ggml
This commit updates the CMake configuration for the Android Java example
to use `FetchContent` for including the `ggml` library. Do be able to
use FetchContent we also update the `compileSdkVersion` and
`targetSdkVersion` to 31, and the `buildToolsVersion` to '30.0.3'.
This also required a an update to the Gradle plugin version to 7.4.0.
The motivation for this change is avoid having to make manual changes to
the CMakeLists.txt file after syncing the ggml library.
This commit adds a conversion from stereo to mono in the
`read_audio_data` function of `common-whisper.cpp`.
The motivation for this change is prior to Commit
7d3da68f79 ("examples : use miniaudio for
direct decoding flac, mp3, ogg and wav (#2759)", there was a step that
read stereo int16 data -> pcm16 (448512 samples), and then converted to
mono (224256 samples), and then also convert to stereo in `pcmf32s.
The middle step here seems to have been missed when rewriting the code to
use Miniaudio and caused issues then transcribing stereo audio files.
For example, currently using the audio sample in the linked issue the
output is:
```console
[00:00:00.000 --> 00:00:03.000] (speaker 1) Sous-titres réalisés para la communauté d'Amara.org
```
And with the change in this commit the output is:
```
[00:00:00.000 --> 00:00:01.500] (speaker 1) *sonnerie de téléphone*
[00:00:01.500 --> 00:00:07.000] (speaker 1) Salut jeune homme !
[00:00:07.000 --> 00:00:08.500] (speaker 0) C'est vrai que je te dérange ?
[00:00:08.500 --> 00:00:10.500] (speaker 1) Ah pas du tout, pas du tout, pas du tout !
[00:00:10.500 --> 00:00:12.500] (speaker 1) J'étais en train de...
[00:00:12.500 --> 00:00:14.500] (speaker 1) de préparer un courrier
```
Resolves: https://github.com/ggml-org/whisper.cpp/issues/3092
* llama : add thread safety test
* llamafile : remove global state
* llama : better LLAMA_SPLIT_MODE_NONE logic
when main_gpu < 0 GPU devices are not used
---------
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
Update oneMath commit to merged PR https://github.com/uxlfoundation/oneMath/pull/669
which adds SYCL-Graph support for recording CUDA BLAS commands.
With this change the `MUL_MAT` tests now pass on DPC++ CUDA backends with SYCL-Graph
enabled. Prior to this change, an error would be thrown.
```
$ GGML_SYCL_DISABLE_GRAPH=0 ./bin/test-backend-ops -b SYCL0 -o MUL_MAT -p type_a=f16,type_b=f32,m=16,n=1,k=256,bs=\\[1,1\\],nr=\\[2
UR CUDA ERROR:
Value: 700
Name: CUDA_ERROR_ILLEGAL_ADDRESS
Description: an illegal memory access was encountered
Function: operator()
Source Location: $HOME/dpcpp/unified-runtime/source/adapters/cuda/queue.cpp:154
Native API failed. Native API returns: 2147483646 (UR_RESULT_ERROR_UNKNOWN)
Exception caught at file:$HOME/llama.cpp/ggml/src/ggml-sycl/ggml-sycl.cpp, line:3598, func:operator()
SYCL error: CHECK_TRY_ERROR((stream)->wait()): Meet error in this line code!
in function ggml_backend_sycl_synchronize at $HOME/llama.cpp/ggml/src/ggml-sycl/ggml-sycl.cpp:3598
$HOME/llama.cpp/ggml/src/ggml-sycl/../ggml-sycl/common.hpp:118: SYCL error
Could not attach to process. If your uid matches the uid of the target
process, check the setting of /proc/sys/kernel/yama/ptrace_scope, or try
again as the root user. For more details, see /etc/sysctl.d/10-ptrace.conf
ptrace: Operation not permitted.
No stack.
The program is not being run.
```
* ggml-cpu: Factor out feature detection build from x86
* ggml-cpu: Add ARM feature detection and scoring
This is analogous to cpu-feats-x86.cpp. However, to detect compile-time
activation of features, we rely on GGML_USE_<FEAT> which need to be set
in cmake, instead of GGML_<FEAT> that users would set for x86.
This is because on ARM, users specify features with GGML_CPU_ARM_ARCH,
rather than with individual flags.
* ggml-cpu: Implement GGML_CPU_ALL_VARIANTS for ARM
Like x86, however to pass around arch flags within cmake, we use
GGML_INTERNAL_<FEAT> as we don't have GGML_<FEAT>.
Some features are optional, so we may need to build multiple backends
per arch version (armv8.2_1, armv8.2_2, ...), and let the scoring
function sort out which one can be used.
* ggml-cpu: Limit ARM GGML_CPU_ALL_VARIANTS to Linux for now
The other platforms will need their own specific variants.
This also fixes the bug that the the variant-building branch was always
being executed as the else-branch of GGML_NATIVE=OFF. The branch is
moved to an elseif-branch which restores the previous behavior.
This change moves the command pool/buffer tracking into a vk_command_pool
structure. There are two instances per context (for compute+transfer) and
two instances per device for operations that don't go through a context.
This should prevent separate contexts from stomping on each other.
Use the same descriptor set layout for all pipelines (MAX_PARAMETER_COUNT == 8)
and move it to the vk_device. Move all the descriptor pool and set tracking to
the context - none of it is specific to pipelines anymore. It has a single vector
of pools and vector of sets, and a single counter to track requests and a single
counter to track use.
* ggml : disable warnings for tests when using MSVC
This commit disables warnings for tests on windows when using MSVC.
The motivation for this is that this brings the build output more
inline with what Linux/MacOS systems produce.
There is still one warning generated for the tests which is:
```console
Building Custom Rule C:/ggml/tests/CMakeLists.txt
cl : command line warning D9025: overriding '/DNDEBUG' with '/UNDEBUG'
[C:\ggml\build\tests\test-arange.vcxproj]
test-arange.cpp
test-arange.vcxproj -> C:\ggml\build\bin\Release\test-arange.exe
```
* ggml : fix typo in tests disable list
This commit removes the unused `ggml_context_container` structure from
the ggml library. It looks like the usage of this struct was removed in
Commit 4757fe18d56ec11bf9c07feaca6e9d5b5357e7f4 ("ggml : alloc
ggml_contexts on the heap (whisper/2525)").
The motivation for this changes is to improve code clarity/readability.
This commit adds the examples in the "list" of targets to ignore MSVC
warnings.
The motivation for this is that currently the examples generate a number
of warnings that are ignore/disabled for the core ggml project. This
makes for a cleaner output when building.
This commit clears the results_all vector no VAD segments are found.
The motivation for this is that this would normally be done by
`whisper_full_with_state` but when no VAD segments are detected this
current implementation does not call that function and hence the vector
does not get reset. This can lead to issues in applications like the
server example where it will incorrectly process the old results.
Resolves: https://github.com/ggml-org/whisper.cpp/issues/3250
This commit addresses an issue with token timestamps when audio segments
are skipped, in `whisper_exp_compute_token_level_timestamps` related to
the VAD processing and the energy levels.
The motivation for this is that the token timestamps exceed the energy
array bounds due to segment timing misalignment:
```console
(skipped introduction)
↓
Audio segment: [2600ms → 5600ms] (3 seconds of actual audio)
Energy array: [0 → 480652] (samples for 3 seconds)
Token timestamps: [3266ms → 3408ms] (absolute timestamps)
```
So both `s0` and `t1` get clamped to the maximum sample index (480652)
which causes the start/end timestamps to be the same for all the tokens
after a certain point.
This is addressed by using segment-relative timestamps in the
`timestamp_to_sample` and `sample_to_timestamp`.
* server : add Voice Activity Detection (VAD) support
This commit adds support for Voice Activity Detection (VAD) in the
server example.
The motivation for this is to enable VAD processing when using
whisper-server.
Resolves: https://github.com/ggml-org/whisper.cpp/issues/3089
* server : add VAD parameters to usage in README.md [no ci]
This commit also adds a few missing parameters.
* server : fix conflicting short options [no ci]
This commit adds entries to `.gitignore` for directories in the
`ext` directory.
The motivation for this is that currently after building locally these
following files are reported by git as untracked:
```console
Untracked files:
(use "git add <file>..." to include in what will be committed)
ext/examples/
ext/ggml/
ext/include/
ext/scripts/
ext/src/
```
* ci : update windows runner to windows-2022
This commit changes the windows-2019 runner to windows-2022.
The motiation for this is that the windows-2019 runner is scheduled for
deprection and will be removed 2025-06-30. There are currently "burnout"
periods that started 2025-06-01 and during these times jobs with
windows-2019 will fail which has happened lately on our CI.
Refs: https://github.com/actions/runner-images/issues/12045
* ruby : add cleaning of library names in dependencies
This commit adds a cleaning step to the library names in the
`Dependencies` class of the Ruby bindings.
The motivation for this is that with the introduction of a library name
alias for ggml in Commit (b933d17c30
"Add in-build ggml::ggml ALIAS library (ggml/1260)) causes the Makefile
generation to break:
```console
$ sed -n '165,170p' ext/Makefile
CLEANOBJS = $(OBJS) *.bak
TARGET_SO_DIR_TIMESTAMP = $(TIMESTAMP_DIR)/.sitearchdir.time
$(TARGET_SO): libcommon.a libwhisper.a libggml\n(ggml::ggml).a libggml-cpu.a libggml-base.a
libcommon.a libwhisper.a libggml\n(ggml::ggml).a libggml-cpu.a libggml-base.a: cmake-targets
cmake-targets:
/usr/bin/cmake -S sources -B build -D BUILD_SHARED_LIBS=OFF -D CMAKE_ARCHIVE_OUTPUT_DIRECTORY=/home/danbev/work/ai/whisper.cpp/bindings/ruby/ext -D CMAKE_POSITION_INDEPENDENT_CODE=ON
```
* squash! ruby : add cleaning of library names in dependencies
Apply PR review feedback.
* Simplify the environment variable setting to specify the memory pool type.
* Adjust the GGML_CANN_ASYNC_MODE setting to accept yes, enable, 1, or on (case-insensitive) as valid options.
* update
* fix CI
* update
* delete whitespace
* fix according to review
* update CANN.md
* update CANN.md
* Add Reorder to Q6_K mmvq implementation
* Address PR comments: clean up comments
* Remove unused parameter after refactoring q4_k
* Adding inline to function and removing unnecessary reference to int
---------
Signed-off-by: nscipione <nicolo.scipione@codeplay.com>
* SYCL: Implement few same quantized type copy kernels
* Use memcpy for copying contiguous tensors
ggml-ci
* feat(sycl): add contiguous tensor copy support and device checks
Adds a memcpy path for contiguous tensors of the same type to optimize data transfer. Updates device support checks to recognize contiguous tensor operations, improving compatibility and performance.
* refactor: replace specific block copy functions with template
The changes replace multiple redundant block copy functions (e.g., cpy_block_q8_0_q8_0, cpy_block_q5_0_q5_0) with a single templated function cpy_blck_q_q. This reduces code duplication by using a generic template that works for any block type, improving maintainability while preserving the same functionality. The template is instantiated with specific block types (e.g., block_q8_0) where needed.
* Exclude BF16 support for COPY tensors for now
ggml-ci
* perf: adjust SYCL copy kernel block sizes for efficiency
Use ceil_div to ensure full element coverage and update nd_range parameters to better align with SYCL block sizes, improving parallelism and device utilization in copy operations.
* * ggml-vulkan: adds op CONV_TRANSPOSE_1D
* test-backend-ops: adds more spohisticated tests for CONV_TRANSPOSE_1D
* Missing barrier added to shader.
Number of additional tests reduced to 108.
* * Fixes typo in variable name.
* Removes extra whitespaces.
* Adds int64->int32 casts to prevent possible warnings.
* Problem size reduced in tests to pass tests with llvmpipe.
* supports_op condition moved from unintended position
* This is not needed by the normal use where the result is read
using `tensor_get`, but it allows perf mode of `test-backend-ops`
to properly measure performance.
Some systems report the CPU implementation as "Power11" instead of "POWER11".
The existing CMake logic uses a case-sensitive regular expression to extract
the CPU generation, which fails when the casing doesn't exactly match "POWER".
This patch provides a fix by first converting the string to uppercase before applying the regex.
Signed-off-by: root <root@rheldb2v.pperf.tadn.ibm.com>
Co-authored-by: root <root@rheldb2v.pperf.tadn.ibm.com>
* Fix indentation of code sample in document comment
* Make Whisper::Context#transcribe able to run non-parallel
* Add test for Whisper::Context#transcribe with parallel option
* Follow signature API change of Context#transcribe
* Remove useless variable assignment
* Move simple usage up in README
* Add need help section in README
* Add document on Context#transcribe's parallel option in README
* Update date
* Fix signature of Context.new
* Make Context#subscribe accept n_processors option
* Make test follow #transcribe's change
* Make RBS follow #transcribe's change
* Add document for #transcribe's n_processors option
* Rename test directory so that Rake tasks' default setting is used
This commit updates the build workflow to replace `ports.ubuntu.com`
with `mirror.kumi.systems` in the apt sources list for ARM64 builds.
The motivation for this change is intended to improve package download
reliability and speed by using a more stable mirror for ARM64 packages.
This pull request fixes a bug in the fullTranscribeWithTime method, where the whisperParams argument was declared but never used. As a result, the model did not apply the configuration defined in whisperParams.
This commit add support for language detection in the Whisper Node.js
addon example. It also updates the node addon to return an object
instead of an array as the results.
The motivation for this change is to enable the inclusion of the
detected language in the result, in addition to the transcription
segments.
For example, when using the `detect_language` option, the result will
now be:
```console
{ language: 'en' }
```
And if the `language` option is set to "auto", it will also return:
```console
{
language: 'en',
transcription: [
[
'00:00:00.000',
'00:00:07.600',
' And so my fellow Americans, ask not what your country can do for you,'
],
[
'00:00:07.600',
'00:00:10.600',
' ask what you can do for your country.'
]
]
}
```
* threading: support for GGML_SCHED_PRIO_LOW, update thread info on Windows to avoid throttling
We talked about adding LOW priority for GGML threads in the original threadpool PR.
It might be useful for some cases to avoid contention.
Latest Windows ARM64 releases started parking (offlining) the CPU cores
more aggresively which results in suboptimal performance with n_threads > 4.
To deal with that we now disable Power Throttling for our threads for the NORMAL
and higher priorities.
Co-authored-by: Diego Devesa <slarengh@gmail.com>
* threading: disable SetThreadInfo() calls for older Windows versions
* Update tools/llama-bench/llama-bench.cpp
Co-authored-by: Diego Devesa <slarengh@gmail.com>
---------
Co-authored-by: Diego Devesa <slarengh@gmail.com>
* 1. add "integrated" in ggml_cuda_device_info for distinguish whether it is Intergrate_gpu or discrete_gpu
2. Adjust the func:"ggml_backend_cuda_device_supports_buft" for this new feature
* Update ggml/src/ggml-cuda/ggml-cuda.cu
Adjusted code indentation
Co-authored-by: Johannes Gäßler <johannesg@5d6.de>
* Update ggml/src/ggml-cuda/ggml-cuda.cu
Fixed incorrect setting of variable types
Co-authored-by: Johannes Gäßler <johannesg@5d6.de>
* Update ggml/src/ggml-cuda/ggml-cuda.cu
Adjusted the judgment logic
Co-authored-by: Johannes Gäßler <johannesg@5d6.de>
* add a host_buft assert in case of integrated_cuda_device with func:'evaluate_and_capture_cuda_graph()'
* Update ggml/src/ggml-cuda/ggml-cuda.cu
Add a defensive security assert
Co-authored-by: Johannes Gäßler <johannesg@5d6.de>
* Update ggml/src/ggml-cuda/ggml-cuda.cu
Adjusted the support judgment logic.
Co-authored-by: Johannes Gäßler <johannesg@5d6.de>
* revoke the suggest commit changes due to it's not applicable in jetson_device
* Update ggml/src/ggml-cuda/ggml-cuda.cu
Add parentheses to enforce operator precedence
Co-authored-by: Diego Devesa <slarengh@gmail.com>
* Update ggml/src/ggml-cuda/ggml-cuda.cu
Fix ci bug: add a spaces
Co-authored-by: Johannes Gäßler <johannesg@5d6.de>
---------
Co-authored-by: yangxiao <yang_xl@tju.edu.cn>
Co-authored-by: Johannes Gäßler <johannesg@5d6.de>
Co-authored-by: yangxiao <yangxl_zz@qq.com>
Co-authored-by: Diego Devesa <slarengh@gmail.com>
* SYCL: Add mrope kernel
* feat: Optimize rope operations with vectorization
Uses `sycl::vec` to load and store two elements at a time,
significantly improving performance in `rope_norm`,
`rope_neox`, and `rope_multi`. This reduces the number of memory
accesses and leverages SIMD instructions for faster execution.
* Use ceil_div
* cmake: Define function for querying architecture
The tests and results match exactly those of src/CMakeLists.txt
* Switch arch detection over to new function
* Prevent overflow
* Fix memsize of Whisper::Context
* Rename xxx_initialize to more Ruby-esque name: xxx_s_new
* Define Whisper::Model::ZipURI
* Define Whisper::Model.coreml_compiled_models
* Make Options' @cmake_options Hash
* Use --{enable,disable}-whisper-coreml option for -I/opt/homebrew/opt/llvm/include
* Prepare Core ML model if enabled
* Add test for ZipURI
* Add signatures for ZipURI
* Add Whisper.system_info_str
* Add test for Whisper.system_info_str
* Add signagure for Model.coreml_compiled_models
* Add signature for Whisper.system_info_str
* Add test for Core ML
* Update date
* Maintain .gitignore
* vad : revisit timestamp alignment/mapping
This commit improving the timestamp alignment by introducing a mapping
table, adding intermediate reference points for longer segments, and
binary search for lookups.
The motivation for this changes is to address issues with the currently
solution where zero-length segments are possible, and also to improve
the precision of the VAD timestamps.
Refs: https://github.com/ggml-org/whisper.cpp/issues/3162
* vad : use uint64_t for time mapping
This commit changes the type of the `processed_time` and `original_time`
fields in the `vad_time_mapping` struct from `double` to `uint64_t`.
The motivation for this change is made to improve precision and avoid
floating-point inaccuracies and also be consistent with other part of
the code base that use `uint64_t` for time representation.
This is a part of a refactoring where I'm also going to change the
vad_segment_info struct to use `uint64_t` for the start and end times.
This is the reason for the not so pleasant conversion and casts in the
code at the moment.
* vad : change vad_segment_info and whisper_vad_segment to use uint64_t
* vad : use int64_t instead of uint64_t for timestamps
To be consistent with other timestamps in the codebase.
* vad : add centisecond conversion functions
* vad : extract vad processing from whisper_full_with_state
This commit extracts the VAD processing from the
`whisper_full_with_state` function into the `whisper_full` and
`whisper_full_parallel` functions.
The motivation for this is that I did not take into account that when
`whisper_full_parallel` is called with `n_processors > 1`, then the
vad processing would not be applied correctly. Instead the VAD
processing should be done prior to processing in the case of
`whisper_full_parallel`.
* vad : remove filtered_n_samples from whisper_vad
The commit removes the parameter `filtered_n_samples` from the
`whisper_vad` function signature and its usage, as it is no longer
needed since filtered samples is now a vector (previously it was a
float*)
The motivation for this is to simplify the usage of this function.
* vad : remove vad_mapping_table_initialized flag
* vad : fix leaning (none) of pointer/references
* Don't pass empty string to cmake command
* Refactor Dependencies
* Use found cmake path for options
* Maintain extsources.rb
* List dependent files by directory separator agnostic way
* Prepend whitespace before '='
* Handle build options on install
* Remove useless test
* Retrieve gem file name and version from spec file
* Bump version to 1.3.3
* Update date
* Add install option examples
* [skip ci]Remove unused module
* Add VAD models
* Extract function to normalize model path from ruby_whisper_initialize()
* Define ruby_whisper_vad_params struct
* Add VAD-related features to Whisper::Params
* Add tests for VAD-related features
* Define Whisper::VADParams
* Add Whisper::VAD::Params attributes
* Add test suite for VAD::Params
* Make older test to follow namespace change
* Add test for transcription with VAD
* Add assertion for test_vad_params
* Add signatures for VAD-related methods
* Define VAD::Params#==
* Add test for VAD::Params#==
* Fix Params#vad_params
* Add test for Params#vad_params
* Fix signature of Params#vad_params
* Use macro to define VAD::Params params
* Define VAD::Params#initialize
* Add tests for VAD::Params#initialize
* Add signature for VAD::Params.new
* Add documentation on VAD in README
* Wrap register_callbask in prepare_transcription for clear meanings
* Set whisper_params.vad_params just before transcription
* Don't touch NULL
* Define ruby_whisper_params_type
* Use TypedData_XXX for ruby_whisper_params instead of Data_XXX
* Remove unused functions
* Define rb_whisper_model_data_type
* Use TypedData_XXX for ruby_whisper_model instead of Data_XXX
* Define ruby_whisper_segment_type
* Use TypedData_XXX for ruby_whisper_segment instead of Data_XXX
* Define ruby_whisper_type
* Use TypedData_XXX for ruby_whisper instead of Data_XXX
* Qualify with const
* tests : add a new benchmark test for long-form audio
Based on "Earnings-21" corpus by Del Rio et al.
Earnings-21: A Practical Benchmark for ASR in the Wild (2021)
https://arxiv.org/abs/2104.11348
This dataset contains 39 hours of long-form speech, sourced from public
earning calls. Each recording contains roughly 50 minutes of English
dialogues between multiple speakers (2-20 persons).
This benchmark suite should allow us to evaluate the performance of
whisper.cpp on long-form audio data.
Signed-off-by: Fujimoto Seiji <fujimoto@ceptord.net>
* tests : apply PR feedback to 'earnings21/README.md'
Based on feedback from Daniel Bevenius.
- Simplify how to download & prepare a Silero VAD model.
- Fix typo: inferece -> inference
Signed-off-by: Fujimoto Seiji <fujimoto@ceptord.net>
* tests : avoid crashing on non-UTF-8 characters
Based on feedback from Daniel Bevenius.
Add 'errors' parameter to open() in order to avoid unhandled
exception on invalid UTF-8 bytes.
Signed-off-by: Fujimoto Seiji <fujimoto@ceptord.net>
* tests : try to interpret the hypothesis as Windows-1252
Based on the discussion in PR#3185.
Evidently Whisper.cpp can represent a quotation mark as '0x93', which
implifies Windows-1252 (Microsoft's ASCII excention), and cannot be
decoded by UTF-8.
Add an explicit decoding loop to address the issue.
Signed-off-by: Fujimoto Seiji <fujimoto@ceptord.net>
---------
Signed-off-by: Fujimoto Seiji <fujimoto@ceptord.net>
This commit modifies windows-blas which was updated previously to use
the zip functionality provided by `actions/upload-artifact`. This turned
out to be incorrect and I should not have done that. The reason for
zipping the archives first is that otherwise the artifacts when
downloaded will be unzipped and just be simple directories. In our case
the release task depends on the artifacts having a .zip extension so
that those archives are include in the release.
* SYCL: Add non contiguous input support to norm kernel
* refactor and add RMS_NORM non contiguous input support
ggml-ci
* restore subgroup reduction for multi-subgroup thread blocks in norm kernels
* Swap grid dims of nsamples and nrows
ggml-ci
* Revert "Swap grid dims of nsamples and nrows"
This reverts commit 43be2d657fec7f7fba54e2cd154106bc0fc45adf.
* restore not required changes
ggml-ci
* address review comments: change it to more like SYCL
* Use a common function to calculate offset
* remove wrap around logic for handling broadcasts
* remove static from calculate_offset fn and use ceil_div
* cann: add the basic FA support
* cann: update the readme
* cann: update the FlashAttention with PSEShift
* cann: update the input parameters in FA
* cann: update the alibi with max_bias
* cann: add the constrints of softcap
* cann: update the docs CANN.md
* cann: update the docs CANN.md
* cann: fix typo of CANN.md
* cann: add some comments and update the CANN.md
* cann: update the CANN.md
* cann: update the inner precise for fusedInferAttention
* cann: update the constraints of flash_attn_ext on ggml-cann.cpp
* cann: clean the whitespace
* cann: clean the whitespace
* cann: add a new endline
* opencl: Add support for multiple devices
... but limited to one platform. A platform with a GPU will be preferred.
Additionally:
* Filter out devices that lack capabilities needed by the backend
implementation (half support, OpenCL 2.0+, etc).
* Make ggml_backend_opencl_reg() thread-safe.
* fixup: fix an error in sync_with_other_backends
... when there is only one OpenCL device available.
* opencl: fix couple crashes
* fix kernel launches failed on devices which do not support
non-uniform work-groups. When non-uniform work-groups are not
supported, set `local_work_size` to NULL (= let driver choose the
work-group sizes). This patch does not cover everything - just the
cases tested by test-backend-ops.
* fix sub-buffer creation failed due to `cl_buffer_region::origin` not
being aligned to `CL_DEVICE_MEM_BASE_ADDR_ALIGN`.
* OpenCL: query non-uniform WG sizes only on OpenCL 3.0+
* musa: fix build warning (unused parameter)
Signed-off-by: Xiaodong Ye <xiaodong.ye@mthreads.com>
* musa: upgrade MUSA SDK version to rc4.0.1
Signed-off-by: Xiaodong Ye <xiaodong.ye@mthreads.com>
* musa: use mudnn::Unary::IDENTITY op to accelerate D2D memory copy
Signed-off-by: Xiaodong Ye <xiaodong.ye@mthreads.com>
* Update ggml/src/ggml-cuda/cpy.cu
Co-authored-by: Johannes Gäßler <johannesg@5d6.de>
* musa: remove MUDNN_CHECK_GEN and use CUDA_CHECK_GEN instead in MUDNN_CHECK
Signed-off-by: Xiaodong Ye <xiaodong.ye@mthreads.com>
---------
Signed-off-by: Xiaodong Ye <xiaodong.ye@mthreads.com>
Co-authored-by: Johannes Gäßler <johannesg@5d6.de>
* Remove mmap workaround on windows
After some testing I found that mmap is supported on windows and for
many GPUs on Linux. Therefore I remove the workaround for windows since
it is not necessary.
* Update llama-bench README
SYCL backend introduced a workaround that allows execution of
llama-bench also without specifying `--mmp 0` flag
This commit updates the README_sycl.md file to use UTF-8 encoding.
The motivation for this is that while this file displays correctly in
github it will fail to render with tools that expect UTF-8 encoding.
For example this is the case when using `grip` to view the file locally.
This commit enable the node addon to suppress all output, even the
result of the transcription if the no_prints parameter is set to true.
The motivation for this is that for the node addon there is a
fullfilment handler/success callback to process the transcription
result. And it might be useful to be able to disable the printing of
the transcription result to the console, so that the user can handle
the result in their own way.
Refs: https://github.com/ggml-org/whisper.cpp/issues/3176
Quick fix for not removing swedish umlauts.
* Update talk-llama.cpp
Expose model inference settings to user instead of hard coding them. Same defaults as previous defaults.
* Update examples/talk-llama/talk-llama.cpp
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* ci : use dynamic libopenblas.dll for window-blas
This commit updates the windows-blas job to use the dynamic (can load
different kernels depending of the CPU arch) libopenblas.dll instead of
the "static" openblas.dll that get installed by vcpgk.
The motivation for this change is that there have been reports of
performance drops in later version specifically related to blas. Please
see the links below for more details.
Resolves: https://github.com/ggml-org/whisper.cpp/issues/3166
Refs: https://github.com/ggml-org/whisper.cpp/issues/2666#issuecomment-2885978811
This commit removes some redundant assignments in the function
`whisper_exp_compute_token_level_timestamps`.
The motivations for this is that tokens[j] and token are references to
the same object and this can be a little confusing when reading the
code.
* Fix CMakeLists.txt to handle deprecated gpu Warnings
* Conditionally apply -Wno-deprecated-gpu-targets only when GGML_CUDA is enabled
* Conditionally apply -Wno-deprecated-gpu-targets only when GGML_CUDA is enabled and not MSVC
---------
Co-authored-by: Jugal Sheth <jugal.sheth@marineai.co.uk>
This commit adds the `GGML_SYCL_DNN` option to the Ruby bindings for
the GGML library. This option as added to ggml in
Commit (5e7e07758a5f3172380500e173ca71f679bbef1e "sycl: use oneDNN for
matrices multiplication")
The motivation for this change to enable the CI build to pass.
This shader uses coopmat1 to do the Q*K^T multiply. The P*V multiply is more
difficult for various reasons so I haven't done it. Performance for this
shader is around 2.5x better than for the scalar shader when doing prompt
processing. Some of the benefit may be from other optimizations like staging
through shared memory, or splitting by rows.
* batched-bench : fix pp batch contents
* metal : optimize multi-sequence FA vec kernel
ggml-ci
* metal : use FA-vec kernel up to batch size 20
ggml-ci
This commit adds a check to `whisper_full_with_state` and if no VAD
segments are detected, the function will return early.
The motivation for this is that if no VAD segments are detected, the
function will not have any samples to process which can happen if an
audio sample does not contain any speech. I did not test this previously
and only discovered this when updating the stream example.
* vad : store VAD context in whisper_state
This commit stores the VAD context in the whisper_state structure,
allowing for better management and reuse of the VAD context across
multiple calls to the whisper_vad function.
The motivation for this change is that when updating the stream example
I noticed that the VAD context was being re-initialized every time the
whisper_vad function was called. This involved loading the VAD model
which is expensive and unnecessary if the context can be reused.
Storing this in the whisper_state seems follow the pattern simliar to
how whisper_coreml_context and whisper_openvion_context are stored.
* vad : free vad_context in whisper_free_state
This commit add `build_*/` to `.gitignore` to ignore all build
directories that start with `build_`.
The motivation for this is that the Go bindings creates a directory
named build_go, which is not ignored by the current .gitignore. I was
not sure if changing this to build-go could effect exising users so I
opted to update .gitignore instead.
* examples : add --print-confidence option to cli
This commit adds a new command-line option `--print-confidence` to the
whisper-cli. When enabled, this option prints the confidence level of each
token in the transcribed text using ANSI formatting codes.
The confidence levels are represented using different styles:
```console
main: confidence: highlighted (low confidence), underlined (medium), dim (high confidence)
```
Refs: https://github.com/ggml-org/whisper.cpp/issues/3135
* vad : add download-vad-model scripts
This commit adds a script to download VAD models.
* vad : add vad model download script for windows [no ci]
Refs: https://github.com/ggml-org/whisper.cpp/issues/3146
This commit adds the `--flash-attn` option to the usage output of the
server example.
The motivation for this change is that while it is possible to set this
option it is not printed in the usage output.
* llama/ggml: add LLM training support
more compact progress bar
llama_save_model_to_file
llama_opt_param_filter
ggml_graph_dup force_grads
refactor ggml_opt, fix test-opt
* remove logits_all
* refactor CUDA implementation for ACC
* reset graph at beginning of opt period
* vulkan: scalar flash attention implementation
* vulkan: always use fp32 for scalar flash attention
* vulkan: use vector loads in scalar flash attention shader
* vulkan: remove PV matrix, helps with register usage
* vulkan: reduce register usage in scalar FA, but perf may be slightly worse
* vulkan: load each Q value once. optimize O reduction. more tuning
* vulkan: support q4_0/q8_0 KV in scalar FA
* CI: increase timeout to accommodate newly-supported tests
* vulkan: for scalar FA, select between 1 and 8 rows
* vulkan: avoid using Float16 capability in scalar FA
* sycl : Implemented reorder Q4_0 mmvq
Signed-off-by: Alberto Cabrera <alberto.cabrera@codeplay.com>
* sycl : Fixed mmvq being called when reorder is disabled
* sycl : Improved comments in the quants header
Signed-off-by: Alberto Cabrera <alberto.cabrera@codeplay.com>
* Use static_assert
* safe_div -> ceil_div
* Clarify qi comment
* change the reorder tensor from init to execute OP
* dbg
* Undo changes to test-backend-ops
* Refactor changes on top of q4_0 reorder fix
* Missing Reverts
* Refactored opt_for_reorder logic to simplify code path
* Explicit inlining and unroll
* Renamed mul_mat_algo enum for consistency
---------
Signed-off-by: Alberto Cabrera <alberto.cabrera@codeplay.com>
Co-authored-by: romain.biessy <romain.biessy@codeplay.com>
This assert fired running Qwen_Qwen3-30B-A3B-Q2_K.gguf:
GGML_ASSERT(nei0 * nei1 <= 3072);
The tensor is 8 x 512. Increase this array size to accommodate.
This commit adds an example that demonstrates how to use a VAD (Voice
Activity Detection) model to segment an audio file into speech segments.
Resolves: https://github.com/ggml-org/whisper.cpp/issues/3144
* vad : add initial Voice Activity Detection (VAD) support
This commit add support for Voice Activity Detection (VAD). When enabled
this feature will process the audio input and detect speech segments.
This information is then used to reduce the number of samples that need
to be processed by whisper_full.
Resolves: https://github.com/ggml-org/whisper.cpp/issues/3003
---------
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
This commit adds a description of the color scheme used in the CLI
when the --print-colors option is enabled.
The motivation for this is that it is not immediately clear what the
color scheme is when using the CLI with the --print-colors option.
Example output:
```console
$ ./build/bin/whisper-cli -f samples/jfk.wav --print-colors
...
main: color scheme: red (low confidence), yellow (medium), green (high confidence)
[00:00:00.000 --> 00:00:11.000] And so my fellow Americans, ask not what your country can do for you, ask what you can do for your country.
```
The description will not be dispayed if the `--no-prints` options is
set.
Refs: https://github.com/ggml-org/whisper.cpp/issues/3135
This commit updates the link to Paul Tol's color scheme in the
`examples/common.h` file. The previous link was outdated and
pointed to a non-existent page.
* Test Ruby bindings' extra options only when commanded
* ruby : test extra build options only when env var specified
* Fix extra_options
* Update gem date
This commit omits the test for `test_build_options` when run locally as
it currently fails on Linux and MacOS platforms.
`
The motivation for this change is that currently when running the tests
locally on a non-macOS platform the test fails with the following error:
```console
.F
========================================================================
Failure: test_build_options(TestPackage):
<["ACCELERATE_FRAMEWORK",
"CMAKE_OSX_ARCHITECTURES",
"CMAKE_OSX_SYSROOT",
"FOUNDATION_LIBRARY",
"METALKIT_FRAMEWORK",
"METAL_FRAMEWORK"]> was expected to be empty.
/home/danbev/work/ai/whisper.cpp/bindings/ruby/tests/test_package.rb:43:in `test_build_options'
40: options = BuildOptions::Options.new
41: assert_empty options.missing_options
42: unless ENV["CI"]
=> 43: assert_empty options.extra_options
44: end
45: end
46: end
========================================================================
```
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:
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
danbev originally fixed this for whisper.wasm, stream.wasm, and command.stream, but the issue still exists on the other examples which I patch in this code.
Resolves: #3059
This commit updates the documentation for the WASM examples to include a
note about the generation of the `worker.js` file. As of Emscripten
3.1.58 (April 2024), separate worker.js files are no longer generated
and the worker is embedded in the main JS file.
The motivation for this change is to inform users about the new behavior
of Emscripten and why the `worker.js` file may not be present.
Refs: https://github.com/ggml-org/whisper.cpp/issues/3123
* whisper : deprecate WHISPER_CCACHE CMake option
This commit deprecates the WHISPER_CCACHE CMake option in favor of
the GGML_CCACHE option.
The motivation for this change is that currently when setting, or not
setting WHISPER_CCACHE, the outut message from ggml will be that to
enable ccache you need to set GGML_CCACHE which can be confusing.
This also seems to be inline with what llama.cpp does which does not
have a LLAMA_CCACHE option as far as I know.
Resolves: https://github.com/ggml-org/whisper.cpp/issues/3063
* ruby : change "WHISPER_CCACHE" to "GGML_CCACHE"
* ruby : move GGML_CCACHE to sorted position
* stream.wasm : add HEAPU8 to exported runtime methods
This commit adds HEAPU8 to the list of exported methods for stream.wasm.
The motivation for this is that without it HEAPUD8 will be undefined
and when its 'buffer' attribute is accessed this will cause error as
reported in the referenced issue.
Note that to test this make sure that the web browsers caches is cleared
first.
Resolves: https://github.com/ggml-org/whisper.cpp/issues/3123
* command.wasm : add HEAPU8 to exported runtime methods
This patch upstreams llamafile's cpu matrix multiplication kernels for ppc64le using MMA builtins for BF16 data type.
This change results in 9x - 40x gains
in total speed S t/s (ie all tokens/total time), across various batch sizes tested using llama-batched-bench benchmark.
The patch is tested with Meta-Lllama-3-8B,
and Mistral-7B models (BF16 models generated by using llama-quantize from corresponding FP32 models) on an IBM POWER10 machine.
Signed-off-by: Shalini Salomi Bodapati <Shalini.Salomi.Bodapati@ibm.com>
The following scenario will cause an assertion failure in the graph
allocator:
- Build and allocate a graph containing a tensor with a non-NULL data
pointer
- Build and allocate a new graph where that data is NULL
Result:
ggml-alloc.c:819: GGML_ASSERT(talloc->buffer_id >= 0) failed
This happens during revalidation because we think that memory should
have been previously allocated based on the current graph but in
reality the previous graph was different. In this situation, we
should do a full reallocation pass.
* vulkan: Add bfloat16 support
This adds bfloat16 matrix multiply support based on VK_KHR_shader_bfloat16.
The extension is required for coopmat multiply support, but matrix-vector
multiply trivially promotes bf16 to fp32 and doesn't require the extension.
The copy/get_rows shaders also don't require the extension.
It's probably possible to fall back to non-coopmat and promote to fp32 when
the extension isn't supported, but this change doesn't do that.
The coopmat support also requires a glslc that supports the extension, which
currently requires a custom build.
* vulkan: Support bf16 tensors without the bf16 extension or coopmat support
Compile a variant of the scalar mul_mm shader that will promote the bf16
values to float, and use that when either the bf16 extension or the coopmat
extensions aren't available.
* vulkan: bfloat16 fixes (really works without bfloat16 support now)
* vulkan: fix spirv-val failure and reenable -O
This commit adds steps to the windows jobs to zip and upload
artifacts produced.
The motivation for this is that currently the artifacts are not zipped
which means that will not be picked up by the release job and hence not
be included in github releases.
Resolves: https://github.com/ggml-org/whisper.cpp/issues/3119
This commit add the .zip extension to the xcframework artifact name in
the GitHub Actions workflow.
The motivation for this that the release job will look for .zip files
and will not find the xcframework artifact without the extension, and
hence will not upload it to the release.
* ggml : remove MSVC warnings pragmas
This commit removes the MSVC-specific pragmas as these are now handled
in CMakeLists.txt.
* whisper : remove MSVC warning pragmas
This commit removes the MSVC-specific pragmas. These are now handled in
the CMakeLists.txt file.
This changes examples/cli/cli.cpp to be like
examples/common-whisper.cpp. "-of -" can be specified (or this can be
inferred from "-" as the input file) to output to stdout. This is useful
for piping to other applications.
Log fname_out consistently when not stdout
- Terminals have stdout=stderr, so remove the message before
successful output to ease copying
- Don't affect actual error messages
- Move opening the ofstream into the factory, fixing missing
open and/or error messages in output_score/output_wts
- Fix struct naming convention
Closes#3048
* docs : Update cli documentation
This updates the documentation of cli based on the actual output
In the longterm this should ideally be auto generated to prevent mismatch
* docs : Update cli documentation
This updates the documentation of cli based on the actual output
In the longterm this should ideally be auto generated to prevent mismatch
* Use cache file when model host doesn't support if-modified-since
* Update gem date
* Revert "ruby : ignore "Downloading" output in test_log_suppress (#3106)"
This reverts commit edbd4cb7f5.
Build fails with compilation error on power pc.
This patch fixes the same.
Tested with unit tests run via
--build <build_dir> && cd <build_dir> && make test
Signed-off-by: Shalini Salomi Bodapati <Shalini.Salomi.Bodapati@ibm.com>
* fix(rpc): Improve input validation and error handling
The `rpc-server` was vulnerable to Denial of Service attacks via
several RPC commands (`SET_TENSOR`, `GRAPH_COMPUTE`, etc.). Malformed
messages could trigger failed assertions (e.g., invalid `ggml_type`)
or out-of-bounds reads/writes leading to `GGML_ABORT` calls,
crashing the server process.
This PR introduces robust input validation and replaces `abort()`
calls with graceful error handling:
- **Type Validation:** `deserialize_tensor` now checks if the
`tensor->type` is within the valid `GGML_TYPE_COUNT` range
*before* calling `ggml_new_tensor_4d`. Returns `nullptr` on
invalid type.
- **Bounds Checks:** Replaced `GGML_ABORT` in `set_tensor`,
`set_tensor_hash`, and `get_tensor` handlers with error
logging and returning `false` when data/offset parameters
are out of buffer bounds.
- **Size Checks:** Added safe arithmetic checks (for overflow) in
`graph_compute` when calculating required message sizes based
on client-provided `n_nodes` and `n_tensors`. Returns early
if the reported sizes conflict with the actual message size or
would lead to overflow.
- **Error Propagation:**
- `create_node` now checks for `nullptr` return values from
`deserialize_tensor` and its recursive calls, propagating
`nullptr` upwards on failure. Uses `find` instead of `at`
for safer map access.
- `copy_tensor` now checks for `nullptr` from `deserialize_tensor`
and sets the response status to failure if deserialization
or bounds checks fail.
- `graph_compute` now checks for `nullptr` return from
`create_node` and returns failure status correctly. The final
return value now reflects the actual computation status.
These changes improve the RPC server's resilience
against malformed client requests, preventing crashes and ensuring
errors are handled more gracefully.
Signed-off-by: Ville Vesilehto <ville@vesilehto.fi>
* refactor(rpc): address pr comments
removed comments and unnecessary returns
Signed-off-by: Ville Vesilehto <ville@vesilehto.fi>
* refactor(rpc): ambiguous nullptr from create_node
rpc_server::create_node could previously return nullptr if the input ID
was 0 (valid) or if an internal error (deserialization, recursion
failure) occurred (invalid). This ambiguity made error handling
difficult for the caller (`graph_compute`).
This commit clarifies the meaning of nullptr:
- `graph_compute` now checks if the input 'id' was non-zero when
`create_node` returns nullptr, correctly identifying failures
versus intentional null links.
- `create_node` avoids recursive calls for zero IDs and propagates
nullptr unambiguously on failure during recursion.
Signed-off-by: Ville Vesilehto <ville@vesilehto.fi>
* refactor(rpc): initial zero check in create_node
The caller (`graph_compute`) already checks `id != 0` when handling
a `nullptr` return from `create_node`, correctly distinguishing
intentional null links from actual errors. This makes the initial
`if (id == 0)` check redundant.
Also removes the log message when a tensor ID is not found in the
provided map which was added in this branch.
Signed-off-by: Ville Vesilehto <ville@vesilehto.fi>
* fix(rpc): Handle get_alloc_size failure in server
Check the return value of `server.get_alloc_size` in the RPC server
loop. If the call fails, return early to close the connection.
Signed-off-by: Ville Vesilehto <ville@vesilehto.fi>
* refactor(rpc): input size validation in graph_compute
Removes detailed, step-by-step size calculations and overflow
checks in favor of simpler direct comparisons, assuming 64-bit
overflow is unlikely.
Signed-off-by: Ville Vesilehto <ville@vesilehto.fi>
* refactor(rpc): remove extra status code setting
Removes the explicit setting of `response.result = GGML_STATUS_FAILED`
when `create_node` returns `nullptr` within `graph_compute`.
Primary signal is the `false` return value in case of failure.
Signed-off-by: Ville Vesilehto <ville@vesilehto.fi>
* refactor(rpc): remove redundant check for tensor->type
Breaks CI on ubuntu-cpu-make. Tensor type is uint32_t, thus
the check is not needed.
Signed-off-by: Ville Vesilehto <ville@vesilehto.fi>
---------
Signed-off-by: Ville Vesilehto <ville@vesilehto.fi>
* SYCL: Add all missing unary kernels
ggml-ci
* decouple kernel launch range from data size using strided loop
* use ciel_div helper for num_blocks
ggml-ci
* clean auto imported header files
RPC_CMD_SET_TENSOR always returns an empty response and we send this 4
times per token. We can improve TG speed if we don't wait for this empty
response.
The performance impact of this change depends on the network latency.
This commit adds a check to makes sure that the target exists before
trying to add compile options to ignore warnings when using MSVC.
The motivation for this is currently the build is broken depending on
the cmake options provided. With this fix it should be possible to build
even if the targets are not actually available.
Refs: https://github.com/ggml-org/whisper.cpp/pull/3090#issuecomment-2842760104
This commit adds the the command line option `--no-gpu` to the server
examples print usage function.
The motivation for this is that this options is available and can be set
but it is not displayed in the usage message.
Refs: https://github.com/ggml-org/whisper.cpp/issues/3095
This commit adds a temporary fix to the `test_log_suppress` test in the
Ruby bindings.
The motivation for this changes is that I suspect that the recent
migration of the models to HuggingFace Xet has changed the way HTTP
caching works for the models. This is causing the test in question to
fail. This is a temporary fix so that CI is not broken while we
investigate this further.
* 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
- [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))
# run the examples as usual, specifying the quantized model file
@ -184,11 +184,11 @@ 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 +225,7 @@ 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
@ -267,7 +267,7 @@ This can result in significant speedup in encoder performance. Here are the inst
- Build `whisper.cpp` with OpenVINO support:
Download OpenVINO package from [release page](https://github.com/openvinotoolkit/openvino/releases). The recommended version to use is [2023.0.0](https://github.com/openvinotoolkit/openvino/releases/tag/2023.0.0).
Download OpenVINO package from [release page](https://github.com/openvinotoolkit/openvino/releases). The recommended version to use is [2024.6.0](https://github.com/openvinotoolkit/openvino/releases/tag/2024.6.0). Ready to use Binaries of the required libraries can be found in the [OpenVino Archives](https://storage.openvinotoolkit.org/repositories/openvino/packages/2024.6/)
After downloading & extracting package onto your development system, set up required environment by sourcing setupvars script. For example:
@ -310,7 +310,7 @@ 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 +444,9 @@ 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 +654,7 @@ 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:
Saving GGML Silero-VAD model to models/silero-v5.1.2-ggml.bin
```
And it can then be used with whisper as follows:
```console
$ ./build/bin/whisper-cli \
--file ./samples/jfk.wav \
--model ./models/ggml-base.en.bin \
--vad \
--vad-model ./models/silero-v5.1.2-ggml.bin
```
### VAD Options
* --vad-threshold: Threshold probability for speech detection. A probability
for a speech segment/frame above this threshold will be considered as speech.
* --vad-min-speech-duration-ms: Minimum speech duration in milliseconds. Speech
segments shorter than this value will be discarded to filter out brief noise or
false positives.
* --vad-min-silence-duration-ms: Minimum silence duration in milliseconds. Silence
periods must be at least this long to end a speech segment. Shorter silence
periods will be ignored and included as part of the speech.
* --vad-max-speech-duration-s: Maximum speech duration in seconds. Speech segments
longer than this will be automatically split into multiple segments at silence
points exceeding 98ms to prevent excessively long segments.
* --vad-speech-pad-ms: Speech padding in milliseconds. Adds this amount of padding
before and after each detected speech segment to avoid cutting off speech edges.
* --vad-samples-overlap: Amount of audio to extend from each speech segment into
the next one, in seconds (e.g., 0.10 = 100ms overlap). This ensures speech isn't
cut off abruptly between segments when they're concatenated together.
## Examples
There are various examples of using the library for different projects in the [examples](examples) folder.
@ -667,13 +836,13 @@ 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 |
SYCL is a higher-level programming model to improve programming productivity on various hardware accelerators<EFBFBD>such as CPUs, GPUs, and FPGAs. It is a single-source embedded domain-specific language based on pure C++17.
oneAPI is a specification that is open and standards-based, supporting multiple architecture types including but not limited to GPU, CPU, and FPGA. The spec has both direct programming and API-based programming paradigms.
Intel uses the SYCL as direct programming language to support CPU, GPUs and FPGAs.
To avoid re-inventing the wheel, this code refers other code paths in llama.cpp (like OpenBLAS, cuBLAS, CLBlast). We use a open-source tool [SYCLomatic](https://github.com/oneapi-src/SYCLomatic) (Commercial release [Intel<EFBFBD> DPC++ Compatibility Tool](https://www.intel.com/content/www/us/en/developer/tools/oneapi/dpc-compatibility-tool.html)) migrate to SYCL.
The whisper.cpp for SYCL is used to support Intel GPUs.
For Intel CPU, recommend to use whisper.cpp for X86 (Intel MKL build).
## OS
|OS|Status|Verified|
|-|-|-|
|Linux|Support|Ubuntu 22.04|
|Windows|Ongoing| |
## Intel GPU
|Intel GPU| Status | Verified Model|
|-|-|-|
|Intel Data Center Max Series| Support| Max 1550|
|Intel Data Center Flex Series| Support| Flex 170|
a. Please follow the procedure in [Get the Intel<EFBFBD> oneAPI Base Toolkit ](https://www.intel.com/content/www/us/en/developer/tools/oneapi/base-toolkit.html).
Recommend to install to default folder: **/opt/intel/oneapi**.
Following guide use the default folder as example. If you use other folder, please modify the following guide info with your folder.
b. Check
```
source /opt/intel/oneapi/setvars.sh
sycl-ls
```
There should be one or more level-zero devices. Like **[ext_oneapi_level_zero:gpu:0]**.
Using device **0** (Intel(R) Arc(TM) A770 Graphics) as main device
```
## Environment Variable
#### Build
|Name|Value|Function|
|-|-|-|
|WHISPER_SYCL|ON (mandatory)|Enable build with SYCL code path. <br>For FP32/FP16, WHISPER_SYCL=ON is mandatory.|
|WHISPER_SYCL_F16|ON (optional)|Enable FP16 build with SYCL code path.For FP32, do not set it.|
|CMAKE_C_COMPILER|icx|Use icx compiler for SYCL code path|
|CMAKE_CXX_COMPILER|icpx|use icpx for SYCL code path|
#### Running
|Name|Value|Function|
|-|-|-|
|GGML_SYCL_DEVICE|0 (default) or 1|Set the device id used. Check the device ids by default running output|
|GGML_SYCL_DEBUG|0 (default) or 1|Enable log function by macro: GGML_SYCL_DEBUG|
## Known Issue
- Error: `error while loading shared libraries: libsycl.so.7: cannot open shared object file: No such file or directory`.
Miss to enable oneAPI running environment.
Install oneAPI base toolkit and enable it by: `source /opt/intel/oneapi/setvars.sh`.
- Hang during startup
llama.cpp use mmap as default way to read model file and copy to GPU. In some system, memcpy will be abnormal and block.
Solution: add **--no-mmap**.
## Todo
- Support to build in Windows.
- Support multiple cards.
# whisper.cpp for SYCL
[Background](#background)
[OS](#os)
[Intel GPU](#intel-gpu)
[Linux](#linux)
[Environment Variable](#environment-variable)
[Known Issue](#known-issue)
[Todo](#todo)
## Background
SYCL is a higher-level programming model to improve programming productivity on various hardware accelerators—such as CPUs, GPUs, and FPGAs. It is a single-source embedded domain-specific language based on pure C++17.
oneAPI is a specification that is open and standards-based, supporting multiple architecture types including but not limited to GPU, CPU, and FPGA. The spec has both direct programming and API-based programming paradigms.
Intel uses the SYCL as direct programming language to support CPU, GPUs and FPGAs.
To avoid re-inventing the wheel, this code refers other code paths in llama.cpp (like OpenBLAS, cuBLAS, CLBlast). We use a open-source tool [SYCLomatic](https://github.com/oneapi-src/SYCLomatic) (Commercial release [Intel® DPC++ Compatibility Tool](https://www.intel.com/content/www/us/en/developer/tools/oneapi/dpc-compatibility-tool.html)) migrate to SYCL.
The whisper.cpp for SYCL is used to support Intel GPUs.
For Intel CPU, recommend to use whisper.cpp for X86 (Intel MKL build).
## OS
|OS|Status|Verified|
|-|-|-|
|Linux|Support|Ubuntu 22.04|
|Windows|Ongoing| |
## Intel GPU
|Intel GPU| Status | Verified Model|
|-|-|-|
|Intel Data Center Max Series| Support| Max 1550|
|Intel Data Center Flex Series| Support| Flex 170|
a. Please follow the procedure in [Get the Intel® oneAPI Base Toolkit ](https://www.intel.com/content/www/us/en/developer/tools/oneapi/base-toolkit.html).
Recommend to install to default folder: **/opt/intel/oneapi**.
Following guide use the default folder as example. If you use other folder, please modify the following guide info with your folder.
b. Check
```
source /opt/intel/oneapi/setvars.sh
sycl-ls
```
There should be one or more level-zero devices. Like **[ext_oneapi_level_zero:gpu:0]**.
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 example:
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"`.
@ -99,9 +127,80 @@ See [models][] page for details.
Currently, whisper.cpp accepts only 16-bit WAV files.
### Voice Activity Detection (VAD) ###
Support for Voice Activity Detection (VAD) can be enabled by setting `Whisper::Params`'s `vad` argument to `true` and specifying VAD model:
```ruby
Whisper::Params.new(
vad:true,
vad_model_path:"silero-v5.1.2",
# other arguments...
)
```
When you pass the model name (`"silero-v5.1.2"`) or URI (`https://huggingface.co/ggml-org/whisper-vad/resolve/main/ggml-silero-v5.1.2.bin`), it will be downloaded automatically.
Currently, "silero-v5.1.2" is registered as pre-converted model like ASR models. You also specify file path or URI of model.
If you need configure VAD behavior, pass params for that:
```ruby
Whisper::Params.new(
vad:true,
vad_model_path:"silero-v5.1.2",
vad_params:Whisper::VAD::Params.new(
threshold:1.0,# defaults to 0.5
min_speech_duration_ms:500,# defaults to 250
min_silence_duration_ms:200,# defaults to 100
max_speech_duration_s:30000,# default is FLT_MAX,
speech_pad_ms:50,# defaults to 30
samples_overlap:0.5# defaults to 0.1
),
# other arguments...
)
```
For details on VAD, see [whisper.cpp's README](https://github.com/ggml-org/whisper.cpp?tab=readme-ov-file#voice-activity-detection-vad).
# 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.
assert_equal"& so my fellow Americans --> ask not what your country can do for you <-- ask what you can do for your country.\n",@whisper.to_srt.lines[2]
end
deftest_to_webvtt_escape
assert_equal"& so my fellow Americans --> ask not what your country can do for you <-- ask what you can do for your country.\n",@whisper.to_webvtt.lines[4]
fprintf(stderr," -vm FNAME, --vad-model FNAME [%-7s] VAD model path\n",params.vad_model.c_str());
fprintf(stderr," -vt N, --vad-threshold N [%-7.2f] VAD threshold for speech recognition\n",params.vad_threshold);
fprintf(stderr," -vspd N, --vad-min-speech-duration-ms N [%-7d] VAD min speech duration (0.0-1.0)\n",params.vad_min_speech_duration_ms);
fprintf(stderr," -vsd N, --vad-min-silence-duration-ms N [%-7d] VAD min silence duration (to split segments)\n",params.vad_min_silence_duration_ms);
fprintf(stderr," -vmsd N, --vad-max-speech-duration-s N [%-7s] VAD max speech duration (auto-split longer)\n",params.vad_max_speech_duration_s==FLT_MAX?
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