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Author SHA1 Message Date
Daniel Bevenius
8b92060a10
coreml : set convert_to="mlprogram" in convert
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* 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
2025-04-23 08:24:38 +02:00
Daniel Bevenius
7858eddd10
ci : disable freeBSD job in build.yml (#3064)
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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.
2025-04-22 11:07:54 +02:00
Daniel Bevenius
3a88f1e504
examples : add HEAPU8 to exported runtime methods (#3062)
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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
2025-04-20 19:40:25 +02:00
KITAITI Makoto
f0d2bfbfb7
ruby : make Ruby bindings installed with build options (#3056)
* 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]
2025-04-17 18:49:58 +09:00
Sacha Arbonel
170b2faf75
whisper : add no_context parameter to whisper_params (#3045)
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2025-04-16 06:24:38 +02:00
Fujimoto Seiji
f8a3509b6d
examples : add FFmpeg v7.0 support to ffmpeg-transcode.cpp (#3038)
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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>
2025-04-15 06:09:00 +02:00
KITAITI Makoto
2a2d21c75d
ruby: use CMake in build process (#3043)
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* 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
2025-04-14 18:18:27 +09:00
Jeff Klassen
9cfcd6cc45
docs : update README.md to note newer nvidia gpus (#3031)
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Resolves: https://github.com/ggml-org/whisper.cpp/issues/3030
2025-04-11 08:54:51 +02:00
Lin Xiaodong
e853620270
addon.node : support max_context api for addon.node (#3025)
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* feat: support max content

* feat: show api in test file

---------

Co-authored-by: linxiaodong <calm.lin@wukongsch.com>
2025-04-11 06:36:38 +02:00
Georgi Gerganov
549db9376f
whisper : reduce delta_min from 1000ms to 100ms (#3028)
ggml-ci
2025-04-11 06:23:02 +02:00
Fujimoto Seiji
33a25e4dda
docs : document how to use 'WHISPER_FFMPEG' build option (#3029)
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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>
2025-04-10 18:21:38 +02:00
Ekaitz Zárraga
43f5030aeb
docs : fix README.md (#3024)
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2025-04-09 19:49:37 +02:00
Daniel Bevenius
cf794133de
xcf : use check for visionos build version (#3021)
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
2025-04-09 16:34:58 +02:00
Olli
ef6cf357e7
ruby : fix types of arguments for rb_get_kwargs in ruby_whisper_params.c (#3022)
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Change param_names and values not to be references for rb_get_kwargs - so it can be compiled on ruby 3.3.6 and 3.4.1
2025-04-09 20:49:25 +09:00
Olli
b1f5c11b32
ruby : Update uri.rb (#3016)
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Bugfix ... without this Pathname the "/" operator wouldn't work and will throw an error
2025-04-08 22:27:40 +09:00
Greg Sadetsky
ada745f4a5
models : fix dead link to models in readme (#3006)
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2025-04-06 08:29:41 +03:00
KITAITI Makoto
01985c22c0
ruby : change homepage URI in Ruby gemspec (#3007)
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2025-04-05 07:55:09 +03:00
Fujimoto Seiji
448f3d3b93
tests : add script to benchmark whisper.cpp on LibriSpeech corpus (#2999)
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* 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>
2025-04-04 19:51:26 +03:00
Fujimoto Seiji
e6234cd435
whisper : fix "bench-all outputs an invalid result on larger models" (#3002)
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>
2025-04-04 18:36:19 +03:00
Georgi Gerganov
2b6d0d2200
rename : ggerganov -> ggml-org (#3005) 2025-04-04 16:11:52 +03:00
Daniel Bevenius
0b17d4507e
examples : update server.py to match github pages app [no ci] (#3004)
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.
2025-04-04 10:23:53 +02:00
Daniel Bevenius
77e0c86ab6
whisper.wasm : fix unknown language issue (#3000)
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* 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
2025-04-03 19:50:47 +02:00
Georgi Gerganov
eac1bc9c47 examples : add new sources
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ggml-ci
2025-04-03 10:30:16 +03:00
Georgi Gerganov
cbde66d913 sync : ggml 2025-04-03 10:30:16 +03:00
cmdr2
513ecf8dc0 cpu: move all the operators into a separate c++ file (except mul_mat) (ggml/1167)
* 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>
2025-04-03 10:30:16 +03:00
Daniel Bevenius
cce5daf17b
docs : add xcframework section to README.md [no ci] (#2997)
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.
2025-04-03 09:06:53 +02:00
Georgi Gerganov
2c502b3c00
readme : update roadmap link
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2025-04-02 17:38:35 +03:00
63 changed files with 14301 additions and 11045 deletions

View File

@ -1,55 +1,11 @@
name: Bindings Tests (Ruby) name: Bindings Tests (Ruby)
on: on:
push: push:
paths: branches:
- bindings/ruby/** - master
- src/**/*.c
- src/**/*.cpp
- src/**/*.h
- src/**/*.m
- src/**/*.metal
- include/**/*.c
- include/**/*.cpp
- include/**/*.h
- include/**/*.m
- include/**/*.metal
- ggml/**/*.c
- ggml/**/*.cpp
- ggml/**/*.h
- ggml/**/*.m
- ggml/**/*.metal
- scripts/get-flags.mk
- examples/common.h
- examples/common.cpp
- examples/common-whisper.h
- examples/common-whisper.cpp
- examples/stb_vorbis.c
- examples/miniaudio.h
pull_request: pull_request:
paths: types: [opened, synchronize, reopened]
- bindings/ruby/**
- src/**/*.c
- src/**/*.cpp
- src/**/*.h
- src/**/*.m
- src/**/*.metal
- include/**/*.c
- include/**/*.cpp
- include/**/*.h
- include/**/*.m
- include/**/*.metal
- ggml/**/*.c
- ggml/**/*.cpp
- ggml/**/*.h
- ggml/**/*.m
- ggml/**/*.metal
- scripts/get-flags.mk
- examples/common.h
- examples/common.cpp
- examples/common-whisper.h
- examples/common-whisper.cpp
- examples/stb_vorbis.c
- examples/miniaudio.h
jobs: jobs:
ubuntu-22: ubuntu-22:
@ -60,6 +16,6 @@ jobs:
steps: steps:
- uses: ruby/setup-ruby@v1 - uses: ruby/setup-ruby@v1
with: with:
ruby-version: '3.1' ruby-version: '3.2'
- uses: actions/checkout@v4 - uses: actions/checkout@v4
- run: rake test - run: rake test

View File

@ -200,23 +200,23 @@ jobs:
cmake --build build --config Release -j $(sysctl -n hw.logicalcpu) cmake --build build --config Release -j $(sysctl -n hw.logicalcpu)
freeBSD-latest: # freeBSD-latest:
runs-on: macos-13 # runs-on: macos-13
#
steps: # steps:
- name: Clone # - name: Clone
uses: actions/checkout@v4 # uses: actions/checkout@v4
#
- name: Build # - name: Build
uses: cross-platform-actions/action@v0.27.0 # uses: cross-platform-actions/action@v0.27.0
with: # with:
operating_system: freebsd # operating_system: freebsd
version: '14.2' # version: '14.2'
run: | # run: |
sudo pkg update # sudo pkg update
sudo pkg install -y gmake sdl2 cmake git # sudo pkg install -y gmake sdl2 cmake git
cmake -B build # cmake -B build
cmake --build build --config Release # cmake --build build --config Release
ubuntu-22-gcc: ubuntu-22-gcc:
if: ${{ github.event_name == 'push' || github.event_name == 'pull_request' || if: ${{ github.event_name == 'push' || github.event_name == 'pull_request' ||

129
README.md
View File

@ -2,15 +2,12 @@
![whisper.cpp](https://user-images.githubusercontent.com/1991296/235238348-05d0f6a4-da44-4900-a1de-d0707e75b763.jpeg) ![whisper.cpp](https://user-images.githubusercontent.com/1991296/235238348-05d0f6a4-da44-4900-a1de-d0707e75b763.jpeg)
[![Actions Status](https://github.com/ggerganov/whisper.cpp/workflows/CI/badge.svg)](https://github.com/ggerganov/whisper.cpp/actions) [![Actions Status](https://github.com/ggml-org/whisper.cpp/workflows/CI/badge.svg)](https://github.com/ggml-org/whisper.cpp/actions)
[![License: MIT](https://img.shields.io/badge/license-MIT-blue.svg)](https://opensource.org/licenses/MIT) [![License: MIT](https://img.shields.io/badge/license-MIT-blue.svg)](https://opensource.org/licenses/MIT)
[![Conan Center](https://shields.io/conan/v/whisper-cpp)](https://conan.io/center/whisper-cpp) [![Conan Center](https://shields.io/conan/v/whisper-cpp)](https://conan.io/center/whisper-cpp)
[![npm](https://img.shields.io/npm/v/whisper.cpp.svg)](https://www.npmjs.com/package/whisper.cpp/) [![npm](https://img.shields.io/npm/v/whisper.cpp.svg)](https://www.npmjs.com/package/whisper.cpp/)
> [!NOTE] Stable: [v1.7.5](https://github.com/ggml-org/whisper.cpp/releases/tag/v1.7.5) / [Roadmap](https://github.com/orgs/ggml-org/projects/4/)
> New maintenance roadmap: https://github.com/ggerganov/whisper.cpp/discussions/2788
Stable: [v1.7.5](https://github.com/ggerganov/whisper.cpp/releases/tag/v1.7.5) / [Roadmap | F.A.Q.](https://github.com/ggerganov/whisper.cpp/discussions/126)
High-performance inference of [OpenAI's Whisper](https://github.com/openai/whisper) automatic speech recognition (ASR) model: High-performance inference of [OpenAI's Whisper](https://github.com/openai/whisper) automatic speech recognition (ASR) model:
@ -26,7 +23,7 @@ High-performance inference of [OpenAI's Whisper](https://github.com/openai/whisp
- [Efficient GPU support for NVIDIA](#nvidia-gpu-support) - [Efficient GPU support for NVIDIA](#nvidia-gpu-support)
- [OpenVINO Support](#openvino-support) - [OpenVINO Support](#openvino-support)
- [Ascend NPU Support](#ascend-npu-support) - [Ascend NPU Support](#ascend-npu-support)
- [C-style API](https://github.com/ggerganov/whisper.cpp/blob/master/include/whisper.h) - [C-style API](https://github.com/ggml-org/whisper.cpp/blob/master/include/whisper.h)
Supported platforms: Supported platforms:
@ -34,14 +31,14 @@ Supported platforms:
- [x] [iOS](examples/whisper.objc) - [x] [iOS](examples/whisper.objc)
- [x] [Android](examples/whisper.android) - [x] [Android](examples/whisper.android)
- [x] [Java](bindings/java/README.md) - [x] [Java](bindings/java/README.md)
- [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] [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)]
- [x] [Raspberry Pi](https://github.com/ggerganov/whisper.cpp/discussions/166) - [x] [Raspberry Pi](https://github.com/ggml-org/whisper.cpp/discussions/166)
- [x] [Docker](https://github.com/ggerganov/whisper.cpp/pkgs/container/whisper.cpp) - [x] [Docker](https://github.com/ggml-org/whisper.cpp/pkgs/container/whisper.cpp)
The entire high-level implementation of the model is contained in [whisper.h](include/whisper.h) and [whisper.cpp](src/whisper.cpp). The entire high-level implementation of the model is contained in [whisper.h](include/whisper.h) and [whisper.cpp](src/whisper.cpp).
The rest of the code is part of the [`ggml`](https://github.com/ggerganov/ggml) machine learning library. The rest of the code is part of the [`ggml`](https://github.com/ggml-org/ggml) machine learning library.
Having such a lightweight implementation of the model allows to easily integrate it in different platforms and applications. Having such a lightweight implementation of the model allows to easily integrate it in different platforms and applications.
As an example, here is a video of running the model on an iPhone 13 device - fully offline, on-device: [whisper.objc](examples/whisper.objc) As an example, here is a video of running the model on an iPhone 13 device - fully offline, on-device: [whisper.objc](examples/whisper.objc)
@ -54,14 +51,14 @@ https://user-images.githubusercontent.com/1991296/204038393-2f846eae-c255-4099-a
On Apple Silicon, the inference runs fully on the GPU via Metal: On Apple Silicon, the inference runs fully on the GPU via Metal:
https://github.com/ggerganov/whisper.cpp/assets/1991296/c82e8f86-60dc-49f2-b048-d2fdbd6b5225 https://github.com/ggml-org/whisper.cpp/assets/1991296/c82e8f86-60dc-49f2-b048-d2fdbd6b5225
## Quick start ## Quick start
First clone the repository: First clone the repository:
```bash ```bash
git clone https://github.com/ggerganov/whisper.cpp.git git clone https://github.com/ggml-org/whisper.cpp.git
``` ```
Navigate into the directory: Navigate into the directory:
@ -152,6 +149,7 @@ standard cmake setup with:
cmake -B build -DGGML_BLAS=1 cmake -B build -DGGML_BLAS=1
cmake --build build --config Release cmake --build build --config Release
./build/bin/whisper-cli [ .. etc .. ] ./build/bin/whisper-cli [ .. etc .. ]
```
## Quantization ## Quantization
@ -225,7 +223,7 @@ 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. 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. 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 ## OpenVINO support
@ -310,7 +308,7 @@ 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 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. 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).
## NVIDIA GPU support ## NVIDIA GPU support
@ -324,6 +322,12 @@ cmake -B build -DGGML_CUDA=1
cmake --build build -j --config Release cmake --build build -j --config Release
``` ```
or for newer NVIDIA GPU's (RTX 5000 series):
```
cmake -B build -DGGML_CUDA=1 -DCMAKE_CUDA_ARCHITECTURES="86"
cmake --build build -j --config Release
```
## Vulkan GPU support ## Vulkan GPU support
Cross-vendor solution which allows you to accelerate workload on your GPU. Cross-vendor solution which allows you to accelerate workload on your GPU.
First, make sure your graphics card driver provides support for Vulkan API. First, make sure your graphics card driver provides support for Vulkan API.
@ -377,6 +381,37 @@ Run the inference examples as usual, for example:
- If you have trouble with Ascend NPU device, please create a issue with **[CANN]** prefix/tag. - If you have trouble with Ascend NPU device, please create a issue with **[CANN]** prefix/tag.
- If you run successfully with your Ascend NPU device, please help update the table `Verified devices`. - If you run successfully with your Ascend NPU device, please help update the table `Verified devices`.
## FFmpeg support (Linux only)
If you want to support more audio formats (such as Opus and AAC), you can turn on the `WHISPER_FFMPEG` build flag to enable FFmpeg integration.
First, you need to install required libraries:
```bash
# Debian/Ubuntu
sudo apt install libavcodec-dev libavformat-dev libavutil-dev
# RHEL/Fedora
sudo dnf install libavcodec-free-devel libavformat-free-devel libavutil-free-devel
```
Then you can build the project as follows:
```bash
cmake -B build -D WHISPER_FFMPEG=yes
cmake --build build
```
Run the following example to confirm it's working:
```bash
# Convert an audio file to Opus format
ffmpeg -i samples/jfk.wav jfk.opus
# Transcribe the audio file
./build/bin/whisper-cli --model models/ggml-base.en.bin --file jfk.opus
```
## Docker ## Docker
### Prerequisites ### Prerequisites
@ -388,8 +423,8 @@ Run the inference examples as usual, for example:
We have two Docker images available for this project: 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`) 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/ggerganov/whisper.cpp:main-cuda`: Same as `main` but compiled with CUDA support. (platforms: `linux/amd64`) 2. `ghcr.io/ggml-org/whisper.cpp:main-cuda`: Same as `main` but compiled with CUDA support. (platforms: `linux/amd64`)
### Usage ### Usage
@ -427,7 +462,7 @@ For detailed instructions on how to use Conan, please refer to the [Conan docume
This is a naive example of performing real-time inference on audio from your microphone. This is a naive example of performing real-time inference on audio from your microphone.
The [stream](examples/stream) tool samples the audio every half a second and runs the transcription continuously. The [stream](examples/stream) tool samples the audio every half a second and runs the transcription continuously.
More info is available in [issue #10](https://github.com/ggerganov/whisper.cpp/issues/10). More info is available in [issue #10](https://github.com/ggml-org/whisper.cpp/issues/10).
You will need to have [sdl2](https://wiki.libsdl.org/SDL2/Installation) installed for it to work properly. You will need to have [sdl2](https://wiki.libsdl.org/SDL2/Installation) installed for it to work properly.
```bash ```bash
@ -516,7 +551,7 @@ main: processing './samples/jfk.wav' (176000 samples, 11.0 sec), 4 threads, 1 pr
## Speaker segmentation via tinydiarize (experimental) ## Speaker segmentation via tinydiarize (experimental)
More information about this approach is available here: https://github.com/ggerganov/whisper.cpp/pull/1058 More information about this approach is available here: https://github.com/ggml-org/whisper.cpp/pull/1058
Sample usage: Sample usage:
@ -580,7 +615,7 @@ https://user-images.githubusercontent.com/1991296/199337538-b7b0c7a3-2753-4a88-a
## Video comparison of different models ## Video comparison of different models
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 ```bash
./scripts/bench-wts.sh samples/jfk.wav ./scripts/bench-wts.sh samples/jfk.wav
@ -597,7 +632,7 @@ 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 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: took to execute it. The results are summarized in the following Github issue:
[Benchmark results](https://github.com/ggerganov/whisper.cpp/issues/89) [Benchmark results](https://github.com/ggml-org/whisper.cpp/issues/89)
Additionally a script to run whisper.cpp with different models and audio files is provided [bench.py](scripts/bench.py). Additionally a script to run whisper.cpp with different models and audio files is provided [bench.py](scripts/bench.py).
@ -624,25 +659,24 @@ You can download the converted models using the [models/download-ggml-model.sh](
or manually from here: or manually from here:
- https://huggingface.co/ggerganov/whisper.cpp - https://huggingface.co/ggerganov/whisper.cpp
- https://ggml.ggerganov.com
For more details, see the conversion script [models/convert-pt-to-ggml.py](models/convert-pt-to-ggml.py) or [models/README.md](models/README.md). For more details, see the conversion script [models/convert-pt-to-ggml.py](models/convert-pt-to-ggml.py) or [models/README.md](models/README.md).
## [Bindings](https://github.com/ggerganov/whisper.cpp/discussions/categories/bindings) ## [Bindings](https://github.com/ggml-org/whisper.cpp/discussions/categories/bindings)
- [x] Rust: [tazz4843/whisper-rs](https://github.com/tazz4843/whisper-rs) | [#310](https://github.com/ggerganov/whisper.cpp/discussions/310) - [x] Rust: [tazz4843/whisper-rs](https://github.com/tazz4843/whisper-rs) | [#310](https://github.com/ggml-org/whisper.cpp/discussions/310)
- [x] JavaScript: [bindings/javascript](bindings/javascript) | [#309](https://github.com/ggerganov/whisper.cpp/discussions/309) - [x] JavaScript: [bindings/javascript](bindings/javascript) | [#309](https://github.com/ggml-org/whisper.cpp/discussions/309)
- React Native (iOS / Android): [whisper.rn](https://github.com/mybigday/whisper.rn) - React Native (iOS / Android): [whisper.rn](https://github.com/mybigday/whisper.rn)
- [x] Go: [bindings/go](bindings/go) | [#312](https://github.com/ggerganov/whisper.cpp/discussions/312) - [x] Go: [bindings/go](bindings/go) | [#312](https://github.com/ggml-org/whisper.cpp/discussions/312)
- [x] Java: - [x] Java:
- [GiviMAD/whisper-jni](https://github.com/GiviMAD/whisper-jni) - [GiviMAD/whisper-jni](https://github.com/GiviMAD/whisper-jni)
- [x] Ruby: [bindings/ruby](bindings/ruby) | [#507](https://github.com/ggerganov/whisper.cpp/discussions/507) - [x] Ruby: [bindings/ruby](bindings/ruby) | [#507](https://github.com/ggml-org/whisper.cpp/discussions/507)
- [x] Objective-C / Swift: [ggerganov/whisper.spm](https://github.com/ggerganov/whisper.spm) | [#313](https://github.com/ggerganov/whisper.cpp/discussions/313) - [x] Objective-C / Swift: [ggml-org/whisper.spm](https://github.com/ggml-org/whisper.spm) | [#313](https://github.com/ggml-org/whisper.cpp/discussions/313)
- [exPHAT/SwiftWhisper](https://github.com/exPHAT/SwiftWhisper) - [exPHAT/SwiftWhisper](https://github.com/exPHAT/SwiftWhisper)
- [x] .NET: | [#422](https://github.com/ggerganov/whisper.cpp/discussions/422) - [x] .NET: | [#422](https://github.com/ggml-org/whisper.cpp/discussions/422)
- [sandrohanea/whisper.net](https://github.com/sandrohanea/whisper.net) - [sandrohanea/whisper.net](https://github.com/sandrohanea/whisper.net)
- [NickDarvey/whisper](https://github.com/NickDarvey/whisper) - [NickDarvey/whisper](https://github.com/NickDarvey/whisper)
- [x] Python: | [#9](https://github.com/ggerganov/whisper.cpp/issues/9) - [x] Python: | [#9](https://github.com/ggml-org/whisper.cpp/issues/9)
- [stlukey/whispercpp.py](https://github.com/stlukey/whispercpp.py) (Cython) - [stlukey/whispercpp.py](https://github.com/stlukey/whispercpp.py) (Cython)
- [AIWintermuteAI/whispercpp](https://github.com/AIWintermuteAI/whispercpp) (Updated fork of aarnphm/whispercpp) - [AIWintermuteAI/whispercpp](https://github.com/AIWintermuteAI/whispercpp) (Updated fork of aarnphm/whispercpp)
- [aarnphm/whispercpp](https://github.com/aarnphm/whispercpp) (Pybind11) - [aarnphm/whispercpp](https://github.com/aarnphm/whispercpp) (Pybind11)
@ -650,6 +684,33 @@ For more details, see the conversion script [models/convert-pt-to-ggml.py](model
- [x] R: [bnosac/audio.whisper](https://github.com/bnosac/audio.whisper) - [x] R: [bnosac/audio.whisper](https://github.com/bnosac/audio.whisper)
- [x] Unity: [macoron/whisper.unity](https://github.com/Macoron/whisper.unity) - [x] Unity: [macoron/whisper.unity](https://github.com/Macoron/whisper.unity)
## XCFramework
The XCFramework is a precompiled version of the library for iOS, visionOS, tvOS,
and macOS. It can be used in Swift projects without the need to compile the
library from source. For examples:
```swift
// swift-tools-version: 5.10
// The swift-tools-version declares the minimum version of Swift required to build this package.
import PackageDescription
let package = Package(
name: "Whisper",
targets: [
.executableTarget(
name: "Whisper",
dependencies: [
"WhisperFramework"
]),
.binaryTarget(
name: "WhisperFramework",
url: "https://github.com/ggml-org/whisper.cpp/releases/download/v1.7.5/whisper-v1.7.5-xcframework.zip",
checksum: "c7faeb328620d6012e130f3d705c51a6ea6c995605f2df50f6e1ad68c59c6c4a"
)
]
)
```
## Examples ## Examples
There are various examples of using the library for different projects in the [examples](examples) folder. There are various examples of using the library for different projects in the [examples](examples) folder.
@ -668,13 +729,13 @@ 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.android](examples/whisper.android) | | Android mobile application using whisper.cpp |
| [whisper.nvim](examples/whisper.nvim) | | Speech-to-text plugin for Neovim | | [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 | | [generate-karaoke.sh](examples/generate-karaoke.sh) | | Helper script to easily [generate a karaoke video](https://youtu.be/uj7hVta4blM) of raw audio capture |
| [livestream.sh](examples/livestream.sh) | | [Livestream audio transcription](https://github.com/ggerganov/whisper.cpp/issues/185) | | [livestream.sh](examples/livestream.sh) | | [Livestream audio transcription](https://github.com/ggml-org/whisper.cpp/issues/185) |
| [yt-wsp.sh](examples/yt-wsp.sh) | | Download + transcribe and/or translate any VOD [(original)](https://gist.github.com/DaniruKun/96f763ec1a037cc92fe1a059b643b818) | | [yt-wsp.sh](examples/yt-wsp.sh) | | Download + transcribe and/or translate any VOD [(original)](https://gist.github.com/DaniruKun/96f763ec1a037cc92fe1a059b643b818) |
| [wchess](examples/wchess) | [wchess.wasm](examples/wchess) | Voice-controlled chess | | [wchess](examples/wchess) | [wchess.wasm](examples/wchess) | Voice-controlled chess |
## [Discussions](https://github.com/ggerganov/whisper.cpp/discussions) ## [Discussions](https://github.com/ggml-org/whisper.cpp/discussions)
If you have any kind of feedback about this project feel free to use the Discussions section and open a new topic. If you have any kind of feedback about this project feel free to use the Discussions section and open a new topic.
You can use the [Show and tell](https://github.com/ggerganov/whisper.cpp/discussions/categories/show-and-tell) category You can use the [Show and tell](https://github.com/ggml-org/whisper.cpp/discussions/categories/show-and-tell) category
to share your own projects that use `whisper.cpp`. If you have a question, make sure to check the to share your own projects that use `whisper.cpp`. If you have a question, make sure to check the
[Frequently asked questions (#126)](https://github.com/ggerganov/whisper.cpp/discussions/126) discussion. [Frequently asked questions (#126)](https://github.com/ggml-org/whisper.cpp/discussions/126) discussion.

View File

@ -51,7 +51,7 @@ func main() {
In order to build, you need to have the Go compiler installed. You can get it from [here](https://golang.org/dl/). Run the tests with: In order to build, you need to have the Go compiler installed. You can get it from [here](https://golang.org/dl/). Run the tests with:
```bash ```bash
git clone https://github.com/ggerganov/whisper.cpp.git git clone https://github.com/ggml-org/whisper.cpp.git
cd whisper.cpp/bindings/go cd whisper.cpp/bindings/go
make test make test
``` ```
@ -98,7 +98,7 @@ The API Documentation:
Getting help: Getting help:
* Follow the discussion for the go bindings [here](https://github.com/ggerganov/whisper.cpp/discussions/312) * Follow the discussion for the go bindings [here](https://github.com/ggml-org/whisper.cpp/discussions/312)
## License ## License

View File

@ -1,5 +1,5 @@
/* /*
github.com/ggerganov/whisper.cpp/bindings/go github.com/ggml-org/whisper.cpp/bindings/go
provides a speech-to-text service bindings for the Go programming language. provides a speech-to-text service bindings for the Go programming language.
*/ */
package whisper package whisper

View File

@ -52,7 +52,7 @@ public class Example {
In order to build, you need to have the JDK 8 or higher installed. Run the tests with: In order to build, you need to have the JDK 8 or higher installed. Run the tests with:
```bash ```bash
git clone https://github.com/ggerganov/whisper.cpp.git git clone https://github.com/ggml-org/whisper.cpp.git
cd whisper.cpp/bindings/java cd whisper.cpp/bindings/java
./gradlew build ./gradlew build

View File

@ -1,3 +1,6 @@
LICENSE LICENSE
pkg/ pkg/
lib/whisper.* lib/whisper.*
ext/sources/*
!ext/sources/CMakeGraphVizOptions.cmake
ext/mkmf.log

View File

@ -16,6 +16,18 @@ If bundler is not being used to manage dependencies, install the gem by executin
$ gem install whispercpp $ gem install whispercpp
You can pass build options for whisper.cpp, for instance:
$ bundle config build.whispercpp --enable-ggml-cuda
or,
$ gem install whispercpp -- --enable-ggml-cuda
See whisper.cpp's [README](https://github.com/ggml-org/whisper.cpp/blob/master/README.md) for available options. You need convert options present the README to Ruby-style options.
For boolean options like `GGML_CUDA`, the README says `-DGGML_CUDA=1`. You need strip `-D`, prepend `--enable-` for `1` or `ON` (`--disable-` for `0` or `OFF`) and make it kebab-case: `--enable-ggml-cuda`.
For options which require arguments like `CMAKE_CUDA_ARCHITECTURES`, the README says `-DCMAKE_CUDA_ARCHITECTURES="86"`. You need strip `-D`, prepend `--`, make it kebab-case, append `=` and append argument: `--cmake-cuda-architectures="86"`.
Usage Usage
----- -----
@ -228,7 +240,7 @@ The second argument `samples` may be an array, an object with `length` and `each
Development Development
----------- -----------
% git clone https://github.com/ggerganov/whisper.cpp.git % git clone https://github.com/ggml-org/whisper.cpp.git
% cd whisper.cpp/bindings/ruby % cd whisper.cpp/bindings/ruby
% rake test % rake test
@ -241,5 +253,5 @@ License
The same to [whisper.cpp][]. The same to [whisper.cpp][].
[whisper.cpp]: https://github.com/ggerganov/whisper.cpp [whisper.cpp]: https://github.com/ggml-org/whisper.cpp
[models]: https://github.com/ggerganov/whisper.cpp/tree/master/models [models]: https://github.com/ggml-org/whisper.cpp/tree/master/models

View File

@ -3,11 +3,15 @@ require "bundler/gem_tasks"
require "rake/testtask" require "rake/testtask"
require_relative "extsources" require_relative "extsources"
SOURCES_DIR = "ext/sources"
SOURCES = FileList[] SOURCES = FileList[]
EXTSOURCES.each do |src| EXTSOURCES.each do |src|
basename = src.pathmap("%f") basename = src.pathmap("%f")
dest = basename == "LICENSE" ? basename : src.pathmap("%{../..,ext}p") dest = basename == "LICENSE" ? basename
: src.pathmap("%{\\.\\./\\.\\.,#{SOURCES_DIR}}p")
.pathmap("%{\\.\\./javascript,#{SOURCES_DIR}/bindings/javascript}p")
dir = dest.pathmap("%d") dir = dest.pathmap("%d")
file src file src
directory dir directory dir
@ -18,7 +22,6 @@ EXTSOURCES.each do |src|
end end
CLEAN.include SOURCES CLEAN.include SOURCES
CLEAN.include FileList["ext/**/*.o", "ext/**/*.metal", "ext/**/*.tmp", "ext/whisper.{so,bundle,dll}"]
SRC = FileList["ext/*.{c,cpp,h}"] SRC = FileList["ext/*.{c,cpp,h}"]
@ -36,6 +39,20 @@ file "ext/Makefile" => SRC + ["ext/extconf.rb"] + SOURCES do |t|
ruby "extconf.rb" ruby "extconf.rb"
end end
end end
if File.exist? "ext/Makefile"
task :make_clean do
cd "ext" do
sh "make", "clean"
end
end
task clean: :make_clean
task :make_distclean do
cd "ext" do
sh "make", "distclean"
end
end
task clobber: :make_distclean
end
file SO_FILE => "ext/Makefile" do |t| file SO_FILE => "ext/Makefile" do |t|
chdir "ext" do chdir "ext" do

View File

@ -1,11 +0,0 @@
ggml/src/ggml-cpu/ggml-cpu-cpp.o: \
ggml/src/ggml-cpu/ggml-cpu.cpp \
ggml/src/ggml-cpu/unary-ops.cpp \
ggml/src/ggml-cpu/binary-ops.cpp \
ggml/include/ggml-backend.h \
ggml/include/ggml.h \
ggml/include/ggml-alloc.h \
ggml/src/ggml-backend-impl.h \
ggml/include/ggml-cpu.h \
ggml/src/ggml-impl.h
$(CXX) $(CXXFLAGS) -c $< -o $@

View File

@ -0,0 +1,61 @@
require "tsort"
class Dependencies
def initialize(cmake, options)
@cmake = cmake
@options = options
generate_dot
@libs = parse_dot
end
def to_s
@libs.join(" ")
end
private
def dot_path
File.join(__dir__, "build", "whisper.cpp.dot")
end
def generate_dot
system @cmake, "-S", "sources", "-B", "build", "--graphviz", dot_path, "-D", "BUILD_SHARED_LIBS=OFF", @options.to_s, exception: true
end
def parse_dot
static_lib_shape = nil
nodes = {}
depends = Hash.new {|h, k| h[k] = []}
class << depends
include TSort
alias tsort_each_node each_key
def tsort_each_child(node, &block)
fetch(node, []).each(&block)
end
end
File.open(dot_path).each_line do |line|
case line
when /\[\s*label\s*=\s*"Static Library"\s*,\s*shape\s*=\s*(?<shape>\w+)\s*\]/
static_lib_shape = $~[:shape]
when /\A\s*"(?<node>\w+)"\s*\[\s*label\s*=\s*"(?<label>\S+)"\s*,\s*shape\s*=\s*(?<shape>\w+)\s*\]\s*;\s*\z/
node = $~[:node]
label = $~[:label]
shape = $~[:shape]
nodes[node] = [label, shape]
when /\A\s*"(?<depender>\w+)"\s*->\s*"(?<dependee>\w+)"/
depender = $~[:depender]
dependee = $~[:dependee]
depends[depender] ||= []
depends[depender] << dependee
end
end
depends.tsort.filter_map {|node|
label, shape = nodes[node]
shape == static_lib_shape ? label : nil
}.collect {|lib| "lib#{lib}.a"}
.reverse
end
end

View File

@ -1,210 +1,22 @@
require 'mkmf' require "mkmf"
require_relative "options"
require_relative "dependencies"
# need to use c++ compiler flags cmake = find_executable("cmake") || abort
$CXXFLAGS << ' -std=c++17' options = Options.new
have_library("gomp") rescue nil
libs = Dependencies.new(cmake, options)
$LDFLAGS << ' -lstdc++' $INCFLAGS << " -Isources/include -Isources/ggml/include -Isources/examples"
$LOCAL_LIBS << " #{libs}"
$cleanfiles << " build #{libs}"
# Set to true when building binary gems create_makefile "whisper" do |conf|
if enable_config('static-stdlib', false) conf << <<~EOF
$LDFLAGS << ' -static-libgcc -static-libstdc++' $(TARGET_SO): #{libs}
end #{libs}: cmake-targets
cmake-targets:
if enable_config('march-tune-native', false) #{"\t"}#{cmake} -S sources -B build -D BUILD_SHARED_LIBS=OFF -D CMAKE_ARCHIVE_OUTPUT_DIRECTORY=#{__dir__} -D CMAKE_POSITION_INDEPENDENT_CODE=ON #{options}
$CFLAGS << ' -march=native -mtune=native' #{"\t"}#{cmake} --build build --config Release --target common whisper
$CXXFLAGS << ' -march=native -mtune=native' EOF
end
if ENV['WHISPER_METAL']
$GGML_METAL ||= true
$DEPRECATE_WARNING ||= true
end
$UNAME_S = `uname -s`.chomp
$UNAME_P = `uname -p`.chomp
$UNAME_M = `uname -m`.chomp
if $UNAME_S == 'Darwin'
unless ENV['GGML_NO_METAL']
$GGML_METAL ||= true
end
$GGML_NO_OPENMP ||= true
end
if $GGML_METAL
$GGML_METAL_EMBED_LIBRARY = true
end
$MK_CPPFLAGS = '-Iggml/include -Iggml/src -Iggml/src/ggml-cpu -Iinclude -Isrc -Iexamples -DGGML_USE_CPU'
$MK_CFLAGS = '-std=c11 -fPIC'
$MK_CXXFLAGS = '-std=c++17 -fPIC'
$MK_NVCCFLAGS = '-std=c++17'
$MK_LDFLAGS = ''
$OBJ_GGML = []
$OBJ_WHISPER = []
$OBJ_COMMON = []
$OBJ_SDL = []
$MK_CPPFLAGS << ' -D_XOPEN_SOURCE=600'
if $UNAME_S == 'Linux'
$MK_CPPFLAGS << ' -D_GNU_SOURCE'
end
if $UNAME_S == 'Darwin'
$MK_CPPFLAGS << ' -D_DARWIN_C_SOURCE'
end
if ENV['WHISPER_DEBUG']
$MK_CFLAGS << ' -O0 -g'
$MK_CXXFLAGS << ' -O0 -g'
$MK_LDFLAGS << ' -g'
$MK_NVCCFLAGS << ' -O0 -g'
else
$MK_CPPFLAGS << ' -DNDEBUG'
$MK_CFLAGS << ' -O3'
$MK_CXXFLAGS << ' -O3'
$MK_NVCCFLAGS << ' -O3'
end
$WARN_FLAGS =
' -Wall' <<
' -Wextra' <<
' -Wpedantic' <<
' -Wcast-qual' <<
' -Wno-unused-function'
$MK_CFLAGS <<
$WARN_FLAGS <<
' -Wshadow' <<
' -Wstrict-prototypes' <<
' -Wpointer-arith' <<
' -Wmissing-prototypes' <<
' -Werror=implicit-int' <<
' -Werror=implicit-function-declaration'
$MK_CXXFLAGS <<
$WARN_FLAGS <<
' -Wmissing-declarations' <<
' -Wmissing-noreturn'
unless `#{cc_command} #{$LDFLAGS} -Wl,-v 2>&1`.chomp.include? 'dyld-1015.7'
$MK_CPPFLAGS << ' -DHAVE_BUGGY_APPLE_LINKER'
end
if %w[Linux Darwin FreeBSD NetBSD OpenBSD Haiku].include? $UNAME_S
$MK_CFLAGS << ' -pthread'
$MK_CXXFLAGS << ' -pthread'
end
unless $_WIN32
$DSO_EXT = '.so'
else
$DSO_EXT = '.dll'
end
unless ENV['RISCV']
if %w[x86_64 i686 amd64].include? $UNAME_M
$HOST_CXXFLAGS ||= ''
$MK_CFLAGS << ' -march=native -mtune=native'
$HOST_CXXFLAGS << ' -march=native -mtune=native'
end
else
$MK_CFLAGS << ' -march=rv64gcv -mabi=lp64d'
$MK_CXXFLAGS << ' -march=rv64gcv -mabi=lp64d'
end
unless ENV['GGML_NO_ACCELERATE']
if $UNAME_S == 'Darwin'
$MK_CPPFLAGS << ' -DGGML_USE_ACCELERATE -DGGML_USE_BLAS -DGGML_BLAS_USE_ACCELERATE'
$MK_CPPFLAGS << ' -DACCELERATE_NEW_LAPACK'
$MK_CPPFLAGS << ' -DACCELERATE_LAPACK_ILP64'
$MK_LDFLAGS << ' -framework Accelerate'
$OBJ_GGML << 'ggml/src/ggml-blas/ggml-blas.o'
end
end
if ENV['GGML_OPENBLAS']
$MK_CPPFLAGS << " -DGGML_USE_BLAS #{`pkg-config --cflags-only-I openblas`.chomp}"
$MK_CFLAGS << " #{`pkg-config --cflags-only-other openblas)`.chomp}"
$MK_LDFLAGS << " #{`pkg-config --libs openblas`}"
$OBJ_GGML << 'ggml/src/ggml-blas/ggml-blas.o'
end
if ENV['GGML_OPENBLAS64']
$MK_CPPFLAGS << " -DGGML_USE_BLAS #{`pkg-config --cflags-only-I openblas64`.chomp}"
$MK_CFLAGS << " #{`pkg-config --cflags-only-other openblas64)`.chomp}"
$MK_LDFLAGS << " #{`pkg-config --libs openblas64`}"
$OBJ_GGML << 'ggml/src/ggml-blas/ggml-blas.o'
end
if $GGML_METAL
$MK_CPPFLAGS << ' -DGGML_USE_METAL'
$MK_LDFLAGS << ' -framework Foundation -framework Metal -framework MetalKit'
$OBJ_GGML << 'ggml/src/ggml-metal/ggml-metal.o'
if ENV['GGML_METAL_NDEBUG']
$MK_CPPFLAGS << ' -DGGML_METAL_NDEBUG'
end
if $GGML_METAL_EMBED_LIBRARY
$MK_CPPFLAGS << ' -DGGML_METAL_EMBED_LIBRARY'
$OBJ_GGML << 'ggml/src/ggml-metal/ggml-metal-embed.o'
end
end
$OBJ_GGML <<
'ggml/src/ggml.o' <<
'ggml/src/ggml-alloc.o' <<
'ggml/src/ggml-backend.o' <<
'ggml/src/ggml-backend-reg.o' <<
'ggml/src/ggml-opt.o' <<
'ggml/src/ggml-quants.o' <<
'ggml/src/ggml-threading.o' <<
'ggml/src/ggml-cpu/ggml-cpu.o' <<
'ggml/src/ggml-cpu/ggml-cpu-cpp.o' <<
'ggml/src/ggml-cpu/ggml-cpu-aarch64.o' <<
'ggml/src/ggml-cpu/ggml-cpu-hbm.o' <<
'ggml/src/ggml-cpu/ggml-cpu-quants.o' <<
'ggml/src/ggml-cpu/ggml-cpu-traits.o' <<
'ggml/src/ggml-cpu/unary-ops.o' <<
'ggml/src/ggml-cpu/binary-ops.o'
$OBJ_WHISPER <<
'src/whisper.o' <<
'examples/common.o' <<
'examples/common-whisper.o'
$objs = $OBJ_GGML + $OBJ_WHISPER + $OBJ_COMMON + $OBJ_SDL
$objs <<
"ruby_whisper.o" <<
"ruby_whisper_context.o" <<
"ruby_whisper_transcribe.o" <<
"ruby_whisper_params.o" <<
"ruby_whisper_error.o" <<
"ruby_whisper_segment.o" <<
"ruby_whisper_model.o"
$CPPFLAGS = "#{$MK_CPPFLAGS} #{$CPPFLAGS}"
$CFLAGS = "#{$CPPFLAGS} #{$MK_CFLAGS} #{$GF_CFLAGS} #{$CFLAGS}"
$BASE_CXXFLAGS = "#{$MK_CXXFLAGS} #{$CXXFLAGS}"
$CXXFLAGS = "#{$BASE_CXXFLAGS} #{$HOST_CXXFLAGS} #{$GF_CXXFLAGS} #{$CPPFLAGS}"
$NVCCFLAGS = "#{$MK_NVCCFLAGS} #{$NVCCFLAGS}"
$LDFLAGS = "#{$MK_LDFLAGS} #{$LDFLAGS}"
create_makefile('whisper')
File.open 'Makefile', 'a' do |file|
file.puts 'include scripts/get-flags.mk'
file.puts 'include cpu.mk'
if $GGML_METAL
file.puts 'include metal.mk'
if $GGML_METAL_EMBED_LIBRARY
file.puts 'include metal-embed.mk'
end
end
end end

View File

@ -1,17 +0,0 @@
ggml/src/ggml-metal/ggml-metal-embed.o: \
ggml/src/ggml-metal/ggml-metal.metal \
ggml/src/ggml-metal/ggml-metal-impl.h \
ggml/src/ggml-common.h
@echo "Embedding Metal library"
@sed -e '/__embed_ggml-common.h__/r ggml/src/ggml-common.h' -e '/__embed_ggml-common.h__/d' < ggml/src/ggml-metal/ggml-metal.metal > ggml/src/ggml-metal/ggml-metal-embed.metal.tmp
@sed -e '/#include "ggml-metal-impl.h"/r ggml/src/ggml-metal/ggml-metal-impl.h' -e '/#include "ggml-metal-impl.h"/d' < ggml/src/ggml-metal/ggml-metal-embed.metal.tmp > ggml/src/ggml-metal/ggml-metal-embed.metal
$(eval TEMP_ASSEMBLY=$(shell mktemp -d))
@echo ".section __DATA, __ggml_metallib" > $(TEMP_ASSEMBLY)/ggml-metal-embed.s
@echo ".globl _ggml_metallib_start" >> $(TEMP_ASSEMBLY)/ggml-metal-embed.s
@echo "_ggml_metallib_start:" >> $(TEMP_ASSEMBLY)/ggml-metal-embed.s
@echo ".incbin \"ggml/src/ggml-metal/ggml-metal-embed.metal\"" >> $(TEMP_ASSEMBLY)/ggml-metal-embed.s
@echo ".globl _ggml_metallib_end" >> $(TEMP_ASSEMBLY)/ggml-metal-embed.s
@echo "_ggml_metallib_end:" >> $(TEMP_ASSEMBLY)/ggml-metal-embed.s
$(CC) $(CFLAGS) -c $(TEMP_ASSEMBLY)/ggml-metal-embed.s -o $@
@rm -f ${TEMP_ASSEMBLY}/ggml-metal-embed.s
@rmdir ${TEMP_ASSEMBLY}

View File

@ -1,6 +0,0 @@
ggml/src/ggml-metal/ggml-metal.o: \
ggml/src/ggml-metal/ggml-metal.m \
ggml/src/ggml-metal/ggml-metal-impl.h \
ggml/include/ggml-metal.h \
ggml/include/ggml.h
$(CC) $(CFLAGS) -c $< -o $@

View File

@ -0,0 +1,219 @@
class Options
def initialize
@options = {}
@pending_options = []
@ignored_options = []
configure
end
def help
@options
.collect_concat {|name, (type, value)|
option = option_name(name)
if type == :bool
["--enable-#{option}", "--disable-#{option}"]
else
"--#{option}=#{type.upcase}"
end
}
.join($/)
end
def to_s
@options
.reject {|name, (type, value)| value.nil?}
.collect {|name, (type, value)| "-D #{name}=#{value == true ? "ON" : value == false ? "OFF" : value.shellescape}"}
.join(" ")
end
def cmake_options
return @cmake_options if @cmake_options
output = nil
Dir.chdir __dir__ do
output = `cmake -S sources -B build -L`
end
started = false
@cmake_options = output.lines.filter_map {|line|
if line.chomp == "-- Cache values"
started = true
next
end
next unless started
option, value = line.chomp.split("=", 2)
name, type = option.split(":", 2)
[name, type, value]
}
end
def missing_options
cmake_options.collect {|name, type, value| name} -
@options.keys - @pending_options - @ignored_options
end
def extra_options
@options.keys + @pending_options - @ignored_options -
cmake_options.collect {|name, type, value| name}
end
private
def configure
filepath "ACCELERATE_FRAMEWORK"
ignored "BUILD_SHARED_LIBS"
ignored "BUILD_TESTING"
ignored "CMAKE_BUILD_TYPE"
ignored "CMAKE_INSTALL_PREFIX"
string "CMAKE_OSX_ARCHITECTURES"
ignored "CMAKE_OSX_DEPLOYMENT_TARGET"
string "CMAKE_OSX_SYSROOT"
filepath "FOUNDATION_LIBRARY"
bool "GGML_ACCELERATE"
bool "GGML_ALL_WARNINGS_3RD_PARTY"
bool "GGML_AMX_BF16"
bool "GGML_AMX_INT8"
bool "GGML_AMX_TILE"
bool "GGML_AVX"
bool "GGML_AVX2"
bool "GGML_AVX512"
bool "GGML_AVX512_BF16"
bool "GGML_AVX512_VBMI"
bool "GGML_AVX512_VNNI"
bool "GGML_AVX_VNNI"
ignored "GGML_BACKEND_DL"
ignored "GGML_BIN_INSTALL_DIR"
bool "GGML_BLAS"
string "GGML_BLAS_VENDOR"
bool "GGML_BMI2"
ignored "GGML_BUILD_EXAMPLES"
ignored "GGML_BUILD_TESTS"
filepath "GGML_CCACHE_FOUND"
bool "GGML_CPU"
bool "GGML_CPU_AARCH64"
ignored "GGML_CPU_ALL_VARIANTS"
string "GGML_CPU_ARM_ARCH"
bool "GGML_CPU_HBM"
bool "GGML_CPU_KLEIDIAI"
string "GGML_CPU_POWERPC_CPUTYPE"
bool "GGML_CUDA"
string "GGML_CUDA_COMPRESSION_MODE"
bool "GGML_CUDA_F16"
bool "GGML_CUDA_FA"
bool "GGML_CUDA_FA_ALL_QUANTS"
bool "GGML_CUDA_FORCE_CUBLAS"
bool "GGML_CUDA_FORCE_MMQ"
ignored "GGML_CUDA_GRAPHS"
bool "GGML_CUDA_NO_PEER_COPY"
bool "GGML_CUDA_NO_VMM"
string "GGML_CUDA_PEER_MAX_BATCH_SIZE"
bool "GGML_F16C"
bool "GGML_FMA"
bool "GGML_GPROF"
bool "GGML_HIP"
bool "GGML_HIP_GRAPHS"
bool "GGML_HIP_NO_VMM"
bool "GGML_HIP_ROCWMMA_FATTN"
bool "GGML_HIP_UMA"
ignored "GGML_INCLUDE_INSTALL_DIR"
bool "GGML_KOMPUTE"
bool "GGML_LASX"
ignored "GGML_LIB_INSTALL_DIR"
ignored "GGML_LLAMAFILE"
bool "GGML_LSX"
bool "GGML_LTO"
bool "GGML_METAL"
bool "GGML_METAL_EMBED_LIBRARY"
string "GGML_METAL_MACOSX_VERSION_MIN"
bool "GGML_METAL_NDEBUG"
bool "GGML_METAL_SHADER_DEBUG"
string "GGML_METAL_STD"
bool "GGML_METAL_USE_BF16"
bool "GGML_MUSA"
bool "GGML_NATIVE"
bool "GGML_OPENCL"
bool "GGML_OPENCL_EMBED_KERNELS"
bool "GGML_OPENCL_PROFILING"
string "GGML_OPENCL_TARGET_VERSION"
bool "GGML_OPENCL_USE_ADRENO_KERNELS"
bool "GGML_OPENMP"
bool "GGML_RPC"
bool "GGML_RVV"
bool "GGML_RV_ZFH"
pending "GGML_SCCACHE_FOUND"
string "GGML_SCHED_MAX_COPIES"
ignored "GGML_STATIC"
bool "GGML_SYCL"
string "GGML_SYCL_DEVICE_ARCH"
bool "GGML_SYCL_F16"
bool "GGML_SYCL_GRAPH"
string "GGML_SYCL_TARGET"
bool "GGML_VULKAN"
bool "GGML_VULKAN_CHECK_RESULTS"
bool "GGML_VULKAN_DEBUG"
bool "GGML_VULKAN_MEMORY_DEBUG"
bool "GGML_VULKAN_PERF"
ignored "GGML_VULKAN_RUN_TESTS"
filepath "GGML_VULKAN_SHADERS_GEN_TOOLCHAIN"
bool "GGML_VULKAN_SHADER_DEBUG_INFO"
pending "GGML_VULKAN_VALIDATE"
bool "GGML_VXE"
filepath "GIT_EXE"
filepath "MATH_LIBRARY"
filepath "METALKIT_FRAMEWORK"
filepath "METAL_FRAMEWORK"
bool "WHISPER_ALL_WARNINGS"
bool "WHISPER_ALL_WARNINGS_3RD_PARTY"
ignored "WHISPER_BIN_INSTALL_DIR"
ignored "WHISPER_BUILD_EXAMPLES"
ignored "WHISPER_BUILD_SERVER"
ignored"WHISPER_BUILD_TESTS"
bool "WHISPER_CCACHE"
bool "WHISPER_COREML"
bool "WHISPER_COREML_ALLOW_FALLBACK"
ignored "WHISPER_CURL"
bool "WHISPER_FATAL_WARNINGS"
ignored "WHISPER_FFMPEG"
ignored "WHISPER_INCLUDE_INSTALL_DIR"
ignored "WHISPER_LIB_INSTALL_DIR"
bool "WHISPER_OPENVINO"
bool "WHISPER_SANITIZE_ADDRESS"
bool "WHISPER_SANITIZE_THREAD"
bool "WHISPER_SANITIZE_UNDEFINED"
ignored "WHISPER_SDL2"
pending "WHISPER_USE_SYSTEM_GGML"
end
def option_name(name)
name.downcase.gsub("_", "-")
end
def bool(name)
option = option_name(name)
value = enable_config(option)
@options[name] = [:bool, value]
end
def string(name, type=:string)
option = "--#{option_name(name)}"
value = arg_config(option)
raise "String expected for #{option}" if value == true || value&.empty?
@options[name] = [type, value]
end
def path(name)
string(name, :path)
end
def filepath(name)
string(name, :filepath)
end
def pending(name)
@pending_options << name
end
def ignored(name)
@ignored_options << name
end
end

View File

@ -918,7 +918,7 @@ ruby_whisper_params_initialize(int argc, VALUE *argv, VALUE self)
return self; return self;
} }
rb_get_kwargs(kw_hash, &param_names, 0, RUBY_WHISPER_PARAMS_PARAM_NAMES_COUNT, &values); rb_get_kwargs(kw_hash, param_names, 0, RUBY_WHISPER_PARAMS_PARAM_NAMES_COUNT, values);
Data_Get_Struct(self, ruby_whisper_params, rwp); Data_Get_Struct(self, ruby_whisper_params, rwp);
for (i = 0; i < RUBY_WHISPER_PARAMS_PARAM_NAMES_COUNT; i++) { for (i = 0; i < RUBY_WHISPER_PARAMS_PARAM_NAMES_COUNT; i++) {

View File

@ -0,0 +1,8 @@
set(GRAPHVIZ_EXECUTABLES FALSE)
set(GRAPHVIZ_STATIC_LIBS TRUE)
set(GRAPHVIZ_SHARED_LIBS FALSE)
set(GRAPHVIZ_MODULE_LIBS FALSE)
set(GRAPHVIZ_INTERFACE_LIBS FALSE)
set(GRAPHVIZ_OBJECT_LIBS FALSE)
set(GRAPHVIZ_UNKNOWN_LIBS FALSE)
set(GRAPHVIZ_GENERATE_DEPENDERS FALSE)

View File

@ -1,6 +1,34 @@
require "yaml" ignored_dirs = %w[
.devops
examples/wchess/wchess.wasm
examples/whisper.android
examples/whisper.android.java
examples/whisper.objc
examples/whisper.swiftui
grammars
models
samples
scripts
]
ignored_files = %w[
AUTHORS
Makefile
README.md
README_sycl.md
.gitignore
.gitmodules
whisper.nvim
twitch.sh
yt-wsp.sh
]
sources = `git ls-files -z ../..`.split("\x0") EXTSOURCES =
paths = YAML.load_file("../../.github/workflows/bindings-ruby.yml")[true]["push"]["paths"] `git ls-files -z ../..`.split("\x0")
paths.delete "bindings/ruby/**" .select {|file|
EXTSOURCES = (Dir.glob(paths, base: "../..").collect {|path| "../../#{path}"} << "../../LICENSE") & sources basename = File.basename(file)
ignored_dirs.all? {|dir| !file.start_with?("../../#{dir}")} &&
!ignored_files.include?(basename) &&
(file.start_with?("../..") || file.start_with?("../javascript")) &&
(!file.start_with?("../../.github/") || basename == "bindings-ruby.yml")
}

View File

@ -34,7 +34,7 @@ module Whisper
when /darwin/ when /darwin/
Pathname(Dir.home)/"Library/Caches" Pathname(Dir.home)/"Library/Caches"
else else
ENV.key?("XDG_CACHE_HOME") ? ENV["XDG_CACHE_HOME"] : Pathname(Dir.home)/".cache" ENV.key?("XDG_CACHE_HOME") ? Pathname(ENV["XDG_CACHE_HOME"]) : Pathname(Dir.home)/".cache"
end end
base/"whisper.cpp" base/"whisper.cpp"
end end

View File

@ -23,9 +23,20 @@ module Whisper
def self.log_set: (log_callback, Object? user_data) -> log_callback def self.log_set: (log_callback, Object? user_data) -> log_callback
class Context class Context
def self.new: (string | _ToPath | ::URI::HTTP) -> instance def self.new: (path | ::URI::HTTP) -> instance
# transcribe a single file
# can emit to a block results
#
# params = Whisper::Params.new
# params.duration = 60_000
# whisper.transcribe "path/to/audio.wav", params do |text|
# puts text
# end
#
def transcribe: (string, Params) -> self def transcribe: (string, Params) -> self
| (string, Params) { (String) -> void } -> self | (string, Params) { (String) -> void } -> self
def model_n_vocab: () -> Integer def model_n_vocab: () -> Integer
def model_n_audio_ctx: () -> Integer def model_n_audio_ctx: () -> Integer
def model_n_audio_state: () -> Integer def model_n_audio_state: () -> Integer
@ -34,19 +45,72 @@ module Whisper
def model_n_mels: () -> Integer def model_n_mels: () -> Integer
def model_ftype: () -> Integer def model_ftype: () -> Integer
def model_type: () -> String def model_type: () -> String
# Yields each Whisper::Segment:
#
# whisper.transcribe("path/to/audio.wav", params)
# whisper.each_segment do |segment|
# puts segment.text
# end
#
# Returns an Enumerator if no block given:
#
# whisper.transcribe("path/to/audio.wav", params)
# enum = whisper.each_segment
# enum.to_a # => [#<Whisper::Segment>, ...]
#
def each_segment: { (Segment) -> void } -> void def each_segment: { (Segment) -> void } -> void
| () -> Enumerator[Segment] | () -> Enumerator[Segment]
def model: () -> Model def model: () -> Model
def full_get_segment: (Integer nth) -> Segment def full_get_segment: (Integer nth) -> Segment
def full_n_segments: () -> Integer def full_n_segments: () -> Integer
# Language ID, which can be converted to string by Whisper.lang_str and Whisper.lang_str_full.
#
def full_lang_id: () -> Integer def full_lang_id: () -> Integer
# Start time of a segment indexed by +segment_index+ in centiseconds (10 times milliseconds).
#
# full_get_segment_t0(3) # => 1668 (16680 ms)
#
def full_get_segment_t0: (Integer) -> Integer def full_get_segment_t0: (Integer) -> Integer
# End time of a segment indexed by +segment_index+ in centiseconds (10 times milliseconds).
#
# full_get_segment_t1(3) # => 1668 (16680 ms)
#
def full_get_segment_t1: (Integer) -> Integer def full_get_segment_t1: (Integer) -> Integer
# Whether the next segment indexed by +segment_index+ is predicated as a speaker turn.
#
# full_get_segment_speacker_turn_next(3) # => true
#
def full_get_segment_speaker_turn_next: (Integer) -> (true | false) def full_get_segment_speaker_turn_next: (Integer) -> (true | false)
# Text of a segment indexed by +segment_index+.
#
# full_get_segment_text(3) # => "ask not what your country can do for you, ..."
#
def full_get_segment_text: (Integer) -> String def full_get_segment_text: (Integer) -> String
def full_get_segment_no_speech_prob: (Integer) -> Float def full_get_segment_no_speech_prob: (Integer) -> Float
# 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.
#
def full: (Params, Array[Float] samples, ?Integer n_samples) -> self def full: (Params, Array[Float] samples, ?Integer n_samples) -> self
| (Params, _Samples, ?Integer n_samples) -> self | (Params, _Samples, ?Integer n_samples) -> self
# Split the input audio in chunks and process each chunk separately using whisper_full_with_state()
# Result is stored in the default state of the context
# Not thread safe if executed in parallel on the same context.
# It seems this approach can offer some speedup in some cases.
# However, the transcription accuracy can be worse at the beginning and end of each chunk.
#
def full_parallel: (Params, Array[Float], ?Integer n_samples) -> self def full_parallel: (Params, Array[Float], ?Integer n_samples) -> self
| (Params, _Samples, ?Integer n_samples) -> self | (Params, _Samples, ?Integer n_samples) -> self
| (Params, _Samples, ?Integer? n_samples, Integer n_processors) -> self | (Params, _Samples, ?Integer? n_samples, Integer n_processors) -> self
@ -85,68 +149,202 @@ module Whisper
?abort_callback: abort_callback, ?abort_callback: abort_callback,
?abort_callback_user_data: Object ?abort_callback_user_data: Object
) -> instance ) -> instance
# params.language = "auto" | "en", etc...
#
def language=: (String) -> String # TODO: Enumerate lang names def language=: (String) -> String # TODO: Enumerate lang names
def language: () -> String def language: () -> String
def translate=: (boolish) -> boolish def translate=: (boolish) -> boolish
def translate: () -> (true | false) def translate: () -> (true | false)
def no_context=: (boolish) -> boolish def no_context=: (boolish) -> boolish
# If true, does not use past transcription (if any) as initial prompt for the decoder.
#
def no_context: () -> (true | false) def no_context: () -> (true | false)
def single_segment=: (boolish) -> boolish def single_segment=: (boolish) -> boolish
# If true, forces single segment output (useful for streaming).
#
def single_segment: () -> (true | false) def single_segment: () -> (true | false)
def print_special=: (boolish) -> boolish def print_special=: (boolish) -> boolish
# If true, prints special tokens (e.g. <SOT>, <EOT>, <BEG>, etc.).
#
def print_special: () -> (true | false) def print_special: () -> (true | false)
def print_progress=: (boolish) -> boolish def print_progress=: (boolish) -> boolish
# If true, prints progress information.
#
def print_progress: () -> (true | false) def print_progress: () -> (true | false)
def print_realtime=: (boolish) -> boolish def print_realtime=: (boolish) -> boolish
# If true, prints results from within whisper.cpp. (avoid it, use callback instead)
#
def print_realtime: () -> (true | false) def print_realtime: () -> (true | false)
# If true, prints timestamps for each text segment when printing realtime.
#
def print_timestamps=: (boolish) -> boolish def print_timestamps=: (boolish) -> boolish
def print_timestamps: () -> (true | false) def print_timestamps: () -> (true | false)
def suppress_blank=: (boolish) -> boolish def suppress_blank=: (boolish) -> boolish
# If true, suppresses blank outputs.
#
def suppress_blank: () -> (true | false) def suppress_blank: () -> (true | false)
def suppress_nst=: (boolish) -> boolish def suppress_nst=: (boolish) -> boolish
# If true, suppresses non-speech-tokens.
#
def suppress_nst: () -> (true | false) def suppress_nst: () -> (true | false)
def token_timestamps=: (boolish) -> boolish def token_timestamps=: (boolish) -> boolish
# If true, enables token-level timestamps.
#
def token_timestamps: () -> (true | false) def token_timestamps: () -> (true | false)
def split_on_word=: (boolish) -> boolish def split_on_word=: (boolish) -> boolish
# If true, split on word rather than on token (when used with max_len).
#
def split_on_word: () -> (true | false) def split_on_word: () -> (true | false)
def initial_prompt=: (_ToS) -> _ToS def initial_prompt=: (_ToS) -> _ToS
# Tokens to provide to the whisper decoder as initial prompt
# these are prepended to any existing text context from a previous call
# use whisper_tokenize() to convert text to tokens.
# Maximum of whisper_n_text_ctx()/2 tokens are used (typically 224).
#
def initial_prompt: () -> (String | nil) def initial_prompt: () -> (String | nil)
def diarize=: (boolish) -> boolish def diarize=: (boolish) -> boolish
# If true, enables diarization.
#
def diarize: () -> (true | false) def diarize: () -> (true | false)
def offset=: (Integer) -> Integer def offset=: (Integer) -> Integer
# Start offset in ms.
#
def offset: () -> Integer def offset: () -> Integer
def duration=: (Integer) -> Integer def duration=: (Integer) -> Integer
# Audio duration to process in ms.
#
def duration: () -> Integer def duration: () -> Integer
def max_text_tokens=: (Integer) -> Integer def max_text_tokens=: (Integer) -> Integer
# Max tokens to use from past text as prompt for the decoder.
#
def max_text_tokens: () -> Integer def max_text_tokens: () -> Integer
def temperature=: (Float) -> Float def temperature=: (Float) -> Float
def temperature: () -> Float def temperature: () -> Float
def max_initial_ts=: (Float) -> Float def max_initial_ts=: (Float) -> Float
# See https://github.com/openai/whisper/blob/f82bc59f5ea234d4b97fb2860842ed38519f7e65/whisper/decoding.py#L97
#
def max_initial_ts: () -> Float def max_initial_ts: () -> Float
def length_penalty=: (Float) -> Float def length_penalty=: (Float) -> Float
def length_penalty: () -> Float def length_penalty: () -> Float
def temperature_inc=: (Float) -> Float def temperature_inc=: (Float) -> Float
def temperature_inc: () -> Float def temperature_inc: () -> Float
def entropy_thold=: (Float) -> Float def entropy_thold=: (Float) -> Float
# Similar to OpenAI's "compression_ratio_threshold"
#
def entropy_thold: () -> Float def entropy_thold: () -> Float
def logprob_thold=: (Float) -> Float def logprob_thold=: (Float) -> Float
def logprob_thold: () -> Float def logprob_thold: () -> Float
def no_speech_thold=: (Float) -> Float def no_speech_thold=: (Float) -> Float
def no_speech_thold: () -> Float def no_speech_thold: () -> Float
# Sets new segment callback, called for every newly generated text segment.
#
# params.new_segment_callback = ->(context, _, n_new, user_data) {
# # ...
# }
#
def new_segment_callback=: (new_segment_callback) -> new_segment_callback def new_segment_callback=: (new_segment_callback) -> new_segment_callback
def new_segment_callback: () -> (new_segment_callback | nil) def new_segment_callback: () -> (new_segment_callback | nil)
# Sets user data passed to the last argument of new segment callback.
#
def new_segment_callback_user_data=: (Object) -> Object def new_segment_callback_user_data=: (Object) -> Object
def new_segment_callback_user_data: () -> Object def new_segment_callback_user_data: () -> Object
# Sets progress callback, called on each progress update.
#
# params.new_segment_callback = ->(context, _, progress, user_data) {
# # ...
# }
#
# +progress+ is an Integer between 0 and 100.
#
def progress_callback=: (progress_callback) -> progress_callback def progress_callback=: (progress_callback) -> progress_callback
def progress_callback: () -> (progress_callback | nil) def progress_callback: () -> (progress_callback | nil)
# Sets user data passed to the last argument of progress callback.
#
def progress_callback_user_data=: (Object) -> Object def progress_callback_user_data=: (Object) -> Object
def progress_callback_user_data: () -> Object def progress_callback_user_data: () -> Object
# Sets abort callback, called to check if the process should be aborted.
#
# params.abort_callback = ->(user_data) {
# # ...
# }
#
#
def abort_callback=: (abort_callback) -> abort_callback def abort_callback=: (abort_callback) -> abort_callback
def abort_callback: () -> (abort_callback | nil) def abort_callback: () -> (abort_callback | nil)
# Sets user data passed to the last argument of abort callback.
#
def abort_callback_user_data=: (Object) -> Object def abort_callback_user_data=: (Object) -> Object
def abort_callback_user_data: () -> Object def abort_callback_user_data: () -> Object
# Hook called on new segment. Yields each Whisper::Segment.
#
# whisper.on_new_segment do |segment|
# # ...
# end
#
def on_new_segment: { (Segment) -> void } -> void def on_new_segment: { (Segment) -> void } -> void
# Hook called on progress update. Yields each progress Integer between 0 and 100.
#
def on_progress: { (Integer progress) -> void } -> void def on_progress: { (Integer progress) -> void } -> void
# Call block to determine whether abort or not. Return +true+ when you want to abort.
#
# params.abort_on do
# if some_condition
# true # abort
# else
# false # continue
# end
# end
#
def abort_on: { (Object user_data) -> boolish } -> void def abort_on: { (Object user_data) -> boolish } -> void
end end
@ -167,16 +365,24 @@ module Whisper
def type: () -> String def type: () -> String
class URI class URI
def self.new: (string | ::URI::HTTP) -> self def self.new: (string | ::URI::HTTP) -> instance
def to_path: -> String def to_path: -> String
def clear_cache: -> void def clear_cache: -> void
end end
end end
class Segment class Segment
# Start time in milliseconds.
#
def start_time: () -> Integer def start_time: () -> Integer
# End time in milliseconds.
#
def end_time: () -> Integer def end_time: () -> Integer
# Whether the next segment is predicted as a speaker turn.
def speaker_next_turn?: () -> (true | false) def speaker_next_turn?: () -> (true | false)
def text: () -> String def text: () -> String
def no_speech_prob: () -> Float def no_speech_prob: () -> Float
end end

View File

@ -21,4 +21,15 @@ class TestBase < Test::Unit::TestCase
def whisper def whisper
self.class.whisper self.class.whisper
end end
module BuildOptions
load "ext/options.rb", self
Options.include self
def enable_config(name)
end
def arg_config(name)
end
end
end end

View File

@ -21,11 +21,26 @@ class TestPackage < TestBase
match_data = `rake -Tbuild`.match(/(whispercpp-(.+)\.gem)/) match_data = `rake -Tbuild`.match(/(whispercpp-(.+)\.gem)/)
filename = match_data[1] filename = match_data[1]
version = match_data[2] version = match_data[2]
basename = "whisper.#{RbConfig::CONFIG["DLEXT"]}"
Dir.mktmpdir do |dir| Dir.mktmpdir do |dir|
system "gem", "install", "--install-dir", dir.shellescape, "--no-document", "pkg/#{filename.shellescape}", exception: true system "gem", "install", "--install-dir", dir.shellescape, "--no-document", "pkg/#{filename.shellescape}", exception: true
assert_path_exist File.join(dir, "gems/whispercpp-#{version}/lib", basename) assert_installed dir, version
end end
end end
private
def assert_installed(dir, version)
assert_path_exist File.join(dir, "gems/whispercpp-#{version}/lib", "whisper.#{RbConfig::CONFIG["DLEXT"]}")
assert_path_exist File.join(dir, "gems/whispercpp-#{version}/LICENSE")
assert_path_not_exist File.join(dir, "gems/whispercpp-#{version}/ext/build")
end
end
def test_build_options
options = BuildOptions::Options.new
assert_empty options.missing_options
unless ENV["CI"]
assert_empty options.extra_options
end
end end
end end

View File

@ -3,8 +3,8 @@ require_relative "extsources"
Gem::Specification.new do |s| Gem::Specification.new do |s|
s.name = "whispercpp" s.name = "whispercpp"
s.authors = ["Georgi Gerganov", "Todd A. Fisher"] s.authors = ["Georgi Gerganov", "Todd A. Fisher"]
s.version = '1.3.1' s.version = '1.3.2'
s.date = '2024-12-19' s.date = '2025-04-17'
s.description = %q{High-performance inference of OpenAI's Whisper automatic speech recognition (ASR) model via Ruby} s.description = %q{High-performance inference of OpenAI's Whisper automatic speech recognition (ASR) model via Ruby}
s.email = 'todd.fisher@gmail.com' s.email = 'todd.fisher@gmail.com'
s.extra_rdoc_files = ['LICENSE', 'README.md'] s.extra_rdoc_files = ['LICENSE', 'README.md']
@ -15,7 +15,8 @@ Gem::Specification.new do |s|
if s.extra_rdoc_files.include?(basename) if s.extra_rdoc_files.include?(basename)
basename basename
else else
file.sub("../..", "ext") file.sub("../..", "ext/sources")
.sub("../javascript", "ext/sources/bindings/javascript")
end end
} }
@ -26,7 +27,7 @@ Gem::Specification.new do |s|
s.required_ruby_version = '>= 3.1.0' s.required_ruby_version = '>= 3.1.0'
#### Documentation and testing. #### Documentation and testing.
s.homepage = 'https://github.com/ggerganov/whisper.cpp' s.homepage = 'https://github.com/ggml-org/whisper.cpp'
s.rdoc_options = ['--main', 'README.md'] s.rdoc_options = ['--main', 'README.md']

View File

@ -41,6 +41,11 @@ COMMON_CMAKE_ARGS=(
-DGGML_OPENMP=${GGML_OPENMP} -DGGML_OPENMP=${GGML_OPENMP}
) )
XCODE_VERSION=$(xcodebuild -version 2>/dev/null | head -n1 | awk '{ print $2 }')
MAJOR_VERSION=$(echo $XCODE_VERSION | cut -d. -f1)
MINOR_VERSION=$(echo $XCODE_VERSION | cut -d. -f2)
echo "Detected Xcode version: $XCODE_VERSION"
check_required_tool() { check_required_tool() {
local tool=$1 local tool=$1
local install_message=$2 local install_message=$2
@ -335,21 +340,28 @@ combine_static_libraries() {
# Platform-specific post-processing for device builds # Platform-specific post-processing for device builds
if [[ "$is_simulator" == "false" ]]; then if [[ "$is_simulator" == "false" ]]; then
if command -v vtool &>/dev/null; then if command -v xcrun vtool &>/dev/null; then
case "$platform" in case "$platform" in
"ios") "ios")
echo "Marking binary as a framework binary for iOS..." echo "Marking binary as a framework binary for iOS..."
vtool -set-build-version ios ${IOS_MIN_OS_VERSION} ${IOS_MIN_OS_VERSION} -replace \ xcrun vtool -set-build-version ios ${IOS_MIN_OS_VERSION} ${IOS_MIN_OS_VERSION} -replace \
-output "${base_dir}/${output_lib}" "${base_dir}/${output_lib}" -output "${base_dir}/${output_lib}" "${base_dir}/${output_lib}"
;; ;;
"visionos") "visionos")
echo "Marking binary as a framework binary for visionOS..." echo "Marking binary as a framework binary for visionOS..."
vtool -set-build-version xros ${VISIONOS_MIN_OS_VERSION} ${VISIONOS_MIN_OS_VERSION} -replace \ if [[ "$MAJOR_VERSION" -gt 16 ]] || [[ "$MAJOR_VERSION" -eq 16 && "$MINOR_VERSION" -gt 2 ]]; then
echo "Xcode version greater than 16.2, using visionOS."
VISION_OS_BUILD_VERSION="visionos"
else
echo "Xcode version less than or equal to 16.2, using xros."
VISION_OS_BUILD_VERSION="xros"
fi
xcrun vtool -set-build-version ${VISION_OS_BUILD_VERSION} ${VISIONOS_MIN_OS_VERSION} ${VISIONOS_MIN_OS_VERSION} -replace \
-output "${base_dir}/${output_lib}" "${base_dir}/${output_lib}" -output "${base_dir}/${output_lib}" "${base_dir}/${output_lib}"
;; ;;
"tvos") "tvos")
echo "Marking binary as a framework binary for tvOS..." echo "Marking binary as a framework binary for tvOS..."
vtool -set-build-version tvos ${TVOS_MIN_OS_VERSION} ${TVOS_MIN_OS_VERSION} -replace \ xcrun vtool -set-build-version tvos ${TVOS_MIN_OS_VERSION} ${TVOS_MIN_OS_VERSION} -replace \
-output "${base_dir}/${output_lib}" "${base_dir}/${output_lib}" -output "${base_dir}/${output_lib}" "${base_dir}/${output_lib}"
;; ;;
esac esac

View File

@ -19,6 +19,12 @@ const whisperParamsMock = {
no_timestamps: false, no_timestamps: false,
audio_ctx: 0, audio_ctx: 0,
max_len: 0, max_len: 0,
prompt: "",
print_progress: false,
progress_callback: (progress) => {
console.log(`Progress: ${progress}`);
},
max_context: -1
}; };
describe("Run whisper.node", () => { describe("Run whisper.node", () => {

View File

@ -368,6 +368,12 @@ Napi::Value whisper(const Napi::CallbackInfo& info) {
bool comma_in_time = whisper_params.Get("comma_in_time").As<Napi::Boolean>(); bool comma_in_time = whisper_params.Get("comma_in_time").As<Napi::Boolean>();
int32_t max_len = whisper_params.Get("max_len").As<Napi::Number>(); int32_t max_len = whisper_params.Get("max_len").As<Napi::Number>();
// Add support for max_context
int32_t max_context = -1;
if (whisper_params.Has("max_context") && whisper_params.Get("max_context").IsNumber()) {
max_context = whisper_params.Get("max_context").As<Napi::Number>();
}
// support prompt // support prompt
std::string prompt = ""; std::string prompt = "";
if (whisper_params.Has("prompt") && whisper_params.Get("prompt").IsString()) { if (whisper_params.Has("prompt") && whisper_params.Get("prompt").IsString()) {
@ -407,6 +413,7 @@ Napi::Value whisper(const Napi::CallbackInfo& info) {
params.pcmf32 = pcmf32_vec; params.pcmf32 = pcmf32_vec;
params.comma_in_time = comma_in_time; params.comma_in_time = comma_in_time;
params.max_len = max_len; params.max_len = max_len;
params.max_context = max_context;
params.print_progress = print_progress; params.print_progress = print_progress;
params.prompt = prompt; params.prompt = prompt;

View File

@ -4,7 +4,7 @@ A very basic tool for benchmarking the inference performance on your device. The
the transformer on some random audio data and records the execution time. This way we can have an objective comparison the transformer on some random audio data and records the execution time. This way we can have an objective comparison
of the performance of the model for various setups. of the performance of the model for various setups.
Benchmark results are tracked in the following Github issue: https://github.com/ggerganov/whisper.cpp/issues/89 Benchmark results are tracked in the following Github issue: https://github.com/ggml-org/whisper.cpp/issues/89
```bash ```bash
# run the bench too on the small.en model using 4 threads # run the bench too on the small.en model using 4 threads
@ -40,7 +40,7 @@ system_info: n_threads = 4 | AVX2 = 0 | AVX512 = 0 | NEON = 1 | FP16_VA = 1 | WA
If you wish, you can submit these results here: If you wish, you can submit these results here:
https://github.com/ggerganov/whisper.cpp/issues/89 https://github.com/ggml-org/whisper.cpp/issues/89
Please include the following information: Please include the following information:

View File

@ -3,7 +3,7 @@
// Speak short text commands to the microphone. // Speak short text commands to the microphone.
// This program will detect your voice command and convert them to text. // This program will detect your voice command and convert them to text.
// //
// ref: https://github.com/ggerganov/whisper.cpp/issues/171 // ref: https://github.com/ggml-org/whisper.cpp/issues/171
// //
#include "common-sdl.h" #include "common-sdl.h"

View File

@ -249,6 +249,20 @@ static int decode_audio(struct audio_buffer *audio_buf, s16 **data, int *size)
/* prepare resampler */ /* prepare resampler */
swr = swr_alloc(); swr = swr_alloc();
#if LIBAVCODEC_VERSION_MAJOR > 60
AVChannelLayout in_ch_layout = codec->ch_layout;
AVChannelLayout out_ch_layout = AV_CHANNEL_LAYOUT_MONO;
/* Set the source audio layout as-is */
av_opt_set_chlayout(swr, "in_chlayout", &in_ch_layout, 0);
av_opt_set_int(swr, "in_sample_rate", codec->sample_rate, 0);
av_opt_set_sample_fmt(swr, "in_sample_fmt", codec->sample_fmt, 0);
/* Convert it into 16khz Mono */
av_opt_set_chlayout(swr, "out_chlayout", &out_ch_layout, 0);
av_opt_set_int(swr, "out_sample_rate", WAVE_SAMPLE_RATE, 0);
av_opt_set_sample_fmt(swr, "out_sample_fmt", AV_SAMPLE_FMT_S16, 0);
#else
av_opt_set_int(swr, "in_channel_count", codec->channels, 0); av_opt_set_int(swr, "in_channel_count", codec->channels, 0);
av_opt_set_int(swr, "out_channel_count", 1, 0); av_opt_set_int(swr, "out_channel_count", 1, 0);
av_opt_set_int(swr, "in_channel_layout", codec->channel_layout, 0); av_opt_set_int(swr, "in_channel_layout", codec->channel_layout, 0);
@ -257,6 +271,7 @@ static int decode_audio(struct audio_buffer *audio_buf, s16 **data, int *size)
av_opt_set_int(swr, "out_sample_rate", WAVE_SAMPLE_RATE, 0); av_opt_set_int(swr, "out_sample_rate", WAVE_SAMPLE_RATE, 0);
av_opt_set_sample_fmt(swr, "in_sample_fmt", codec->sample_fmt, 0); av_opt_set_sample_fmt(swr, "in_sample_fmt", codec->sample_fmt, 0);
av_opt_set_sample_fmt(swr, "out_sample_fmt", AV_SAMPLE_FMT_S16, 0); av_opt_set_sample_fmt(swr, "out_sample_fmt", AV_SAMPLE_FMT_S16, 0);
#endif
swr_init(swr); swr_init(swr);
if (!swr_is_initialized(swr)) { if (!swr_is_initialized(swr)) {

View File

@ -2,7 +2,7 @@
# #
# Transcribe audio livestream by feeding ffmpeg output to whisper.cpp at regular intervals # Transcribe audio livestream by feeding ffmpeg output to whisper.cpp at regular intervals
# Idea by @semiformal-net # Idea by @semiformal-net
# ref: https://github.com/ggerganov/whisper.cpp/issues/185 # ref: https://github.com/ggml-org/whisper.cpp/issues/185
# #
set -eo pipefail set -eo pipefail

View File

@ -1,39 +1,115 @@
import http.server import http.server
import socketserver import socketserver
import os import os
import sys
from pathlib import Path from pathlib import Path
import urllib.parse
SCRIPT_DIR = Path(__file__).parent.absolute() SCRIPT_DIR = Path(__file__).parent.absolute()
DIRECTORY = os.path.join(SCRIPT_DIR, "../build-em/bin") DIRECTORY = os.path.join(SCRIPT_DIR, "../build-em/bin")
DIRECTORY = os.path.abspath(DIRECTORY) DIRECTORY = os.path.abspath(DIRECTORY)
# The context root we want for all applications
CONTEXT_ROOT = "/whisper.cpp"
class CustomHTTPRequestHandler(http.server.SimpleHTTPRequestHandler): class CustomHTTPRequestHandler(http.server.SimpleHTTPRequestHandler):
def __init__(self, *args, **kwargs): def __init__(self, *args, **kwargs):
super().__init__(*args, directory=DIRECTORY, **kwargs) super().__init__(*args, directory=DIRECTORY, **kwargs)
def do_GET(self): def do_GET(self):
# If requesting a worker file from any subdirectory # Redirect root to the context root
if '.worker.js' in self.path: if self.path == '/':
self.send_response(302)
self.send_header('Location', CONTEXT_ROOT + '/')
self.end_headers()
return
# Handle requests under the context root
if self.path.startswith(CONTEXT_ROOT):
# Remove the context root prefix to get the actual path
actual_path = self.path[len(CONTEXT_ROOT):]
if not actual_path:
self.send_response(302)
self.send_header('Location', CONTEXT_ROOT + '/')
self.end_headers()
return
if '.worker.js' in actual_path:
worker_file = os.path.basename(actual_path)
worker_path = os.path.join(DIRECTORY, worker_file)
if os.path.exists(worker_path):
print(f"Found worker file: {worker_path}")
self.path = '/' + worker_file
else:
print(f"Worker file not found: {worker_path}")
elif actual_path == '/':
self.path = '/whisper.wasm/index.html'
elif actual_path.startswith('/bench.wasm/') or actual_path.startswith('/command.wasm/') or actual_path.startswith('/stream.wasm/'):
# Keep the path as is, just remove the context root
self.path = actual_path
# For all other paths under the context root
else:
# Check if this is a request to a file in whisper.wasm
potential_file = os.path.join(DIRECTORY, 'whisper.wasm', actual_path.lstrip('/'))
if os.path.exists(potential_file) and not os.path.isdir(potential_file):
self.path = '/whisper.wasm' + actual_path
else:
# Try to resolve the file from the base directory
potential_file = os.path.join(DIRECTORY, actual_path.lstrip('/'))
if os.path.exists(potential_file):
self.path = actual_path
# For direct requests to worker files (without context root as these
# are in the build-em/bin directory
elif '.worker.js' in self.path:
worker_file = os.path.basename(self.path) worker_file = os.path.basename(self.path)
worker_path = os.path.join(DIRECTORY, worker_file) worker_path = os.path.join(DIRECTORY, worker_file)
if os.path.exists(worker_path): if os.path.exists(worker_path):
self.path = '/' + worker_file self.path = '/' + worker_file
# Handle coi-serviceworker.js separately
if 'coi-serviceworker.js' in self.path:
worker_file = "coi-serviceworker.js"
worker_path = os.path.join(SCRIPT_DIR, worker_file)
if os.path.exists(worker_path):
self.send_response(200)
self.send_header('Content-type', 'application/javascript')
self.end_headers()
with open(worker_path, 'rb') as file:
self.wfile.write(file.read())
return
else:
print(f"Warning: Could not find {worker_path}")
return super().do_GET() return super().do_GET()
def end_headers(self): def end_headers(self):
# Add required headers for SharedArrayBuffer # Add required headers for SharedArrayBuffer
self.send_header("Cross-Origin-Opener-Policy", "same-origin") self.send_header("Cross-Origin-Opener-Policy", "same-origin")
self.send_header("Cross-Origin-Embedder-Policy", "require-corp") self.send_header("Cross-Origin-Embedder-Policy", "require-corp")
self.send_header("Access-Control-Allow-Origin", "*"); self.send_header("Access-Control-Allow-Origin", "*")
super().end_headers() super().end_headers()
PORT = 8000 PORT = 8000
with socketserver.TCPServer(("", PORT), CustomHTTPRequestHandler) as httpd: # Enable address reuse
print(f"Serving directory '{DIRECTORY}' at http://localhost:{PORT}") class CustomServer(socketserver.TCPServer):
try: allow_reuse_address = True
httpd.serve_forever()
except KeyboardInterrupt: try:
print("\nServer stopped.") with CustomServer(("", PORT), CustomHTTPRequestHandler) as httpd:
print(f"Serving directory '{DIRECTORY}' at http://localhost:{PORT}")
print(f"Application context root: http://localhost:{PORT}{CONTEXT_ROOT}/")
try:
httpd.serve_forever()
except KeyboardInterrupt:
print("\nServer stopped.")
# Force complete exit
sys.exit(0)
except OSError as e:
print(f"Error: {e}")
sys.exit(1)

View File

@ -79,6 +79,7 @@ struct whisper_params {
bool use_gpu = true; bool use_gpu = true;
bool flash_attn = false; bool flash_attn = false;
bool suppress_nst = false; bool suppress_nst = false;
bool no_context = false;
std::string language = "en"; std::string language = "en";
std::string prompt = ""; std::string prompt = "";
@ -140,6 +141,7 @@ void whisper_print_usage(int /*argc*/, char ** argv, const whisper_params & para
fprintf(stderr, " --convert, [%-7s] Convert audio to WAV, requires ffmpeg on the server\n", sparams.ffmpeg_converter ? "true" : "false"); fprintf(stderr, " --convert, [%-7s] Convert audio to WAV, requires ffmpeg on the server\n", sparams.ffmpeg_converter ? "true" : "false");
fprintf(stderr, " -sns, --suppress-nst [%-7s] suppress non-speech tokens\n", params.suppress_nst ? "true" : "false"); fprintf(stderr, " -sns, --suppress-nst [%-7s] suppress non-speech tokens\n", params.suppress_nst ? "true" : "false");
fprintf(stderr, " -nth N, --no-speech-thold N [%-7.2f] no speech threshold\n", params.no_speech_thold); fprintf(stderr, " -nth N, --no-speech-thold N [%-7.2f] no speech threshold\n", params.no_speech_thold);
fprintf(stderr, " -nc, --no-context [%-7s] do not use previous audio context\n", params.no_context ? "true" : "false");
fprintf(stderr, "\n"); fprintf(stderr, "\n");
} }
@ -186,6 +188,7 @@ bool whisper_params_parse(int argc, char ** argv, whisper_params & params, serve
else if (arg == "-fa" || arg == "--flash-attn") { params.flash_attn = true; } else if (arg == "-fa" || arg == "--flash-attn") { params.flash_attn = true; }
else if (arg == "-sns" || arg == "--suppress-nst") { params.suppress_nst = true; } else if (arg == "-sns" || arg == "--suppress-nst") { params.suppress_nst = true; }
else if (arg == "-nth" || arg == "--no-speech-thold") { params.no_speech_thold = std::stof(argv[++i]); } else if (arg == "-nth" || arg == "--no-speech-thold") { params.no_speech_thold = std::stof(argv[++i]); }
else if (arg == "-nc" || arg == "--no-context") { params.no_context = true; }
// server params // server params
else if ( arg == "--port") { sparams.port = std::stoi(argv[++i]); } else if ( arg == "--port") { sparams.port = std::stoi(argv[++i]); }
@ -506,6 +509,10 @@ void get_req_parameters(const Request & req, whisper_params & params)
{ {
params.suppress_nst = parse_str_to_bool(req.get_file_value("suppress_nst").content); params.suppress_nst = parse_str_to_bool(req.get_file_value("suppress_nst").content);
} }
if (req.has_file("no_context"))
{
params.no_context = parse_str_to_bool(req.get_file_value("no_context").content);
}
} }
} // namespace } // namespace
@ -818,6 +825,7 @@ int main(int argc, char ** argv) {
wparams.no_timestamps = params.no_timestamps; wparams.no_timestamps = params.no_timestamps;
wparams.token_timestamps = !params.no_timestamps && params.response_format == vjson_format; wparams.token_timestamps = !params.no_timestamps && params.response_format == vjson_format;
wparams.no_context = params.no_context;
wparams.suppress_nst = params.suppress_nst; wparams.suppress_nst = params.suppress_nst;

View File

@ -2,7 +2,7 @@
# #
# Transcribe twitch.tv livestream by feeding audio input to whisper.cpp at regular intervals # Transcribe twitch.tv livestream by feeding audio input to whisper.cpp at regular intervals
# Thanks to @keyehzy # Thanks to @keyehzy
# ref: https://github.com/ggerganov/whisper.cpp/issues/209 # ref: https://github.com/ggml-org/whisper.cpp/issues/209
# #
# The script currently depends on the third-party tool "streamlink" # The script currently depends on the third-party tool "streamlink"
# On Mac OS, you can install it via "brew install streamlink" # On Mac OS, you can install it via "brew install streamlink"

View File

@ -14,6 +14,8 @@ set(SOURCE_FILES
${WHISPER_LIB_DIR}/ggml/src/ggml-cpu/ggml-cpu.cpp ${WHISPER_LIB_DIR}/ggml/src/ggml-cpu/ggml-cpu.cpp
${WHISPER_LIB_DIR}/ggml/src/ggml-cpu/unary-ops.cpp ${WHISPER_LIB_DIR}/ggml/src/ggml-cpu/unary-ops.cpp
${WHISPER_LIB_DIR}/ggml/src/ggml-cpu/binary-ops.cpp ${WHISPER_LIB_DIR}/ggml/src/ggml-cpu/binary-ops.cpp
${WHISPER_LIB_DIR}/ggml/src/ggml-cpu/vec.cpp
${WHISPER_LIB_DIR}/ggml/src/ggml-cpu/ops.cpp
${WHISPER_LIB_DIR}/ggml/src/ggml-alloc.c ${WHISPER_LIB_DIR}/ggml/src/ggml-alloc.c
${WHISPER_LIB_DIR}/ggml/src/ggml-backend.cpp ${WHISPER_LIB_DIR}/ggml/src/ggml-backend.cpp
${WHISPER_LIB_DIR}/ggml/src/ggml-backend-reg.cpp ${WHISPER_LIB_DIR}/ggml/src/ggml-backend-reg.cpp

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@ -34,6 +34,8 @@ if (NOT GGML_HOME)
${WHISPER_LIB_DIR}/ggml/src/ggml-cpu/ggml-cpu-traits.cpp ${WHISPER_LIB_DIR}/ggml/src/ggml-cpu/ggml-cpu-traits.cpp
${WHISPER_LIB_DIR}/ggml/src/ggml-cpu/unary-ops.cpp ${WHISPER_LIB_DIR}/ggml/src/ggml-cpu/unary-ops.cpp
${WHISPER_LIB_DIR}/ggml/src/ggml-cpu/binary-ops.cpp ${WHISPER_LIB_DIR}/ggml/src/ggml-cpu/binary-ops.cpp
${WHISPER_LIB_DIR}/ggml/src/ggml-cpu/vec.cpp
${WHISPER_LIB_DIR}/ggml/src/ggml-cpu/ops.cpp
) )
endif() endif()

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@ -5,7 +5,7 @@
# This simple script is called by Neovim to capture audio from the microphone and transcribe it with Whisper. # This simple script is called by Neovim to capture audio from the microphone and transcribe it with Whisper.
# In order for this to work, you need to clone the whisper.cpp repo and build the 'stream' tool # In order for this to work, you need to clone the whisper.cpp repo and build the 'stream' tool
# #
# git clone https://github.com/ggerganov/whisper.cpp # git clone https://github.com/ggml-org/whisper.cpp
# cd whisper.cpp # cd whisper.cpp
# make stream # make stream
# #
@ -31,7 +31,7 @@
model="base.en" model="base.en"
# export the path to the whisper.cpp repo in the WHISPER_CPP_HOME env variable # export the path to the whisper.cpp repo in the WHISPER_CPP_HOME env variable
# https://github.com/ggerganov/whisper.cpp # https://github.com/ggml-org/whisper.cpp
cd "${WHISPER_CPP_HOME}" cd "${WHISPER_CPP_HOME}"
if [ ! -f ./stream ] ; then if [ ! -f ./stream ] ; then

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@ -36,7 +36,7 @@ set_target_properties(${TARGET} PROPERTIES LINK_FLAGS " \
-s MAXIMUM_MEMORY=2000MB \ -s MAXIMUM_MEMORY=2000MB \
-s ALLOW_MEMORY_GROWTH=1 \ -s ALLOW_MEMORY_GROWTH=1 \
-s FORCE_FILESYSTEM=1 \ -s FORCE_FILESYSTEM=1 \
-s EXPORTED_RUNTIME_METHODS=\"['print', 'printErr', 'ccall', 'cwrap']\" \ -s EXPORTED_RUNTIME_METHODS=\"['print', 'printErr', 'ccall', 'cwrap', 'HEAPU8']\" \
${EXTRA_FLAGS} \ ${EXTRA_FLAGS} \
") ")

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@ -30,7 +30,7 @@ Link: https://ggerganov.github.io/whisper.cpp/
```bash (v3.1.2) ```bash (v3.1.2)
# build using Emscripten # build using Emscripten
git clone https://github.com/ggerganov/whisper.cpp git clone https://github.com/ggml-org/whisper.cpp
cd whisper.cpp cd whisper.cpp
mkdir build-em && cd build-em mkdir build-em && cd build-em
emcmake cmake .. emcmake cmake ..

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@ -65,13 +65,14 @@ EMSCRIPTEN_BINDINGS(whisper) {
} }
struct whisper_full_params params = whisper_full_default_params(whisper_sampling_strategy::WHISPER_SAMPLING_GREEDY); struct whisper_full_params params = whisper_full_default_params(whisper_sampling_strategy::WHISPER_SAMPLING_GREEDY);
bool is_multilingual = whisper_is_multilingual(g_contexts[index]);
params.print_realtime = true; params.print_realtime = true;
params.print_progress = false; params.print_progress = false;
params.print_timestamps = true; params.print_timestamps = true;
params.print_special = false; params.print_special = false;
params.translate = translate; params.translate = translate;
params.language = whisper_is_multilingual(g_contexts[index]) ? lang.c_str() : "en"; params.language = is_multilingual ? strdup(lang.c_str()) : "en";
params.n_threads = std::min(nthreads, std::min(16, mpow2(std::thread::hardware_concurrency()))); params.n_threads = std::min(nthreads, std::min(16, mpow2(std::thread::hardware_concurrency())));
params.offset_ms = 0; params.offset_ms = 0;
@ -102,10 +103,13 @@ EMSCRIPTEN_BINDINGS(whisper) {
// run the worker // run the worker
{ {
g_worker = std::thread([index, params, pcmf32 = std::move(pcmf32)]() { g_worker = std::thread([index, params, pcmf32 = std::move(pcmf32), is_multilingual]() {
whisper_reset_timings(g_contexts[index]); whisper_reset_timings(g_contexts[index]);
whisper_full(g_contexts[index], params, pcmf32.data(), pcmf32.size()); whisper_full(g_contexts[index], params, pcmf32.data(), pcmf32.size());
whisper_print_timings(g_contexts[index]); whisper_print_timings(g_contexts[index]);
if (is_multilingual) {
free((void*)params.language);
}
}); });
} }

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@ -25,12 +25,12 @@
# SOFTWARE. # SOFTWARE.
# Small shell script to more easily automatically download and transcribe live stream VODs. # Small shell script to more easily automatically download and transcribe live stream VODs.
# This uses YT-DLP, ffmpeg and the CPP version of Whisper: https://github.com/ggerganov/whisper.cpp # This uses YT-DLP, ffmpeg and the CPP version of Whisper: https://github.com/ggml-org/whisper.cpp
# Use `./examples/yt-wsp.sh help` to print help info. # Use `./examples/yt-wsp.sh help` to print help info.
# #
# Sample usage: # Sample usage:
# #
# git clone https://github.com/ggerganov/whisper.cpp # git clone https://github.com/ggml-org/whisper.cpp
# cd whisper.cpp # cd whisper.cpp
# make # make
# ./examples/yt-wsp.sh https://www.youtube.com/watch?v=1234567890 # ./examples/yt-wsp.sh https://www.youtube.com/watch?v=1234567890
@ -44,7 +44,7 @@ SCRIPT_DIR="${SCRIPT_PATH%/*}"
################################################################################ ################################################################################
# Documentation on downloading models can be found in the whisper.cpp repo: # Documentation on downloading models can be found in the whisper.cpp repo:
# https://github.com/ggerganov/whisper.cpp/#usage # https://github.com/ggml-org/whisper.cpp/#usage
# #
# note: unless a multilingual model is specified, WHISPER_LANG will be ignored # note: unless a multilingual model is specified, WHISPER_LANG will be ignored
# and the video will be transcribed as if the audio were in the English language # and the video will be transcribed as if the audio were in the English language
@ -103,10 +103,10 @@ check_requirements() {
fi; fi;
if ! command -v "${WHISPER_EXECUTABLE}" &>/dev/null; then if ! command -v "${WHISPER_EXECUTABLE}" &>/dev/null; then
echo "The C++ implementation of Whisper is required: https://github.com/ggerganov/whisper.cpp" echo "The C++ implementation of Whisper is required: https://github.com/ggml-org/whisper.cpp"
echo "Sample usage:"; echo "Sample usage:";
echo ""; echo "";
echo " git clone https://github.com/ggerganov/whisper.cpp"; echo " git clone https://github.com/ggml-org/whisper.cpp";
echo " cd whisper.cpp"; echo " cd whisper.cpp";
echo " make"; echo " make";
echo " ./examples/yt-wsp.sh https://www.youtube.com/watch?v=1234567890"; echo " ./examples/yt-wsp.sh https://www.youtube.com/watch?v=1234567890";

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@ -28,6 +28,11 @@ function(ggml_add_cpu_backend_variant_impl tag_name)
ggml-cpu/binary-ops.cpp ggml-cpu/binary-ops.cpp
ggml-cpu/unary-ops.h ggml-cpu/unary-ops.h
ggml-cpu/unary-ops.cpp ggml-cpu/unary-ops.cpp
ggml-cpu/simd-mappings.h
ggml-cpu/vec.h
ggml-cpu/vec.cpp
ggml-cpu/ops.h
ggml-cpu/ops.cpp
) )
target_compile_features(${GGML_CPU_NAME} PRIVATE c_std_11 cxx_std_17) target_compile_features(${GGML_CPU_NAME} PRIVATE c_std_11 cxx_std_17)

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ggml/src/ggml-cpu/ops.cpp Normal file

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128
ggml/src/ggml-cpu/ops.h Normal file
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@ -0,0 +1,128 @@
#pragma once
#include "ggml.h"
//
// cache line
//
#if defined(__cpp_lib_hardware_interference_size)
#define CACHE_LINE_SIZE std::hardware_destructive_interference_size
#else
#if defined(__POWER9_VECTOR__)
#define CACHE_LINE_SIZE 128
#elif defined(__VXE__) || defined(__VXE2__)
#define CACHE_LINE_SIZE 256
#else
#define CACHE_LINE_SIZE 64
#endif
#endif
static const size_t CACHE_LINE_SIZE_F32 = CACHE_LINE_SIZE/sizeof(float);
#ifdef __cplusplus
extern "C" {
#endif
void ggml_compute_forward_dup(const struct ggml_compute_params * params, struct ggml_tensor * dst);
void ggml_compute_forward_add(const struct ggml_compute_params * params, struct ggml_tensor * dst);
void ggml_compute_forward_add1(const struct ggml_compute_params * params, struct ggml_tensor * dst);
void ggml_compute_forward_acc(const struct ggml_compute_params * params, struct ggml_tensor * dst);
void ggml_compute_forward_sum(const struct ggml_compute_params * params, struct ggml_tensor * dst);
void ggml_compute_forward_sum_rows(const struct ggml_compute_params * params, struct ggml_tensor * dst);
void ggml_compute_forward_mean(const struct ggml_compute_params * params, struct ggml_tensor * dst);
void ggml_compute_forward_argmax(const struct ggml_compute_params * params, struct ggml_tensor * dst);
void ggml_compute_forward_count_equal(const struct ggml_compute_params * params, struct ggml_tensor * dst);
void ggml_compute_forward_repeat(const struct ggml_compute_params * params, struct ggml_tensor * dst);
void ggml_compute_forward_repeat_back(const struct ggml_compute_params * params, struct ggml_tensor * dst);
void ggml_compute_forward_concat(const struct ggml_compute_params * params, struct ggml_tensor * dst);
void ggml_compute_forward_silu_back(const struct ggml_compute_params * params, struct ggml_tensor * dst);
void ggml_compute_forward_norm(const struct ggml_compute_params * params, struct ggml_tensor * dst);
void ggml_compute_forward_rms_norm(const struct ggml_compute_params * params, struct ggml_tensor * dst);
void ggml_compute_forward_rms_norm_back(const struct ggml_compute_params * params, struct ggml_tensor * dst);
void ggml_compute_forward_group_norm(const struct ggml_compute_params * params, struct ggml_tensor * dst);
void ggml_compute_forward_l2_norm(const struct ggml_compute_params * params, struct ggml_tensor * dst);
void ggml_compute_forward_out_prod(const struct ggml_compute_params * params, struct ggml_tensor * dst);
void ggml_compute_forward_scale(const struct ggml_compute_params * params, struct ggml_tensor * dst);
void ggml_compute_forward_set(const struct ggml_compute_params * params, struct ggml_tensor * dst);
void ggml_compute_forward_cpy(const struct ggml_compute_params * params, struct ggml_tensor * dst);
void ggml_compute_forward_cont(const struct ggml_compute_params * params, struct ggml_tensor * dst);
void ggml_compute_forward_reshape(const struct ggml_compute_params * params, struct ggml_tensor * dst);
void ggml_compute_forward_view(const struct ggml_compute_params * params, struct ggml_tensor * dst);
void ggml_compute_forward_permute(const struct ggml_compute_params * params, struct ggml_tensor * dst);
void ggml_compute_forward_transpose(const struct ggml_compute_params * params, struct ggml_tensor * dst);
void ggml_compute_forward_get_rows(const struct ggml_compute_params * params, struct ggml_tensor * dst);
void ggml_compute_forward_get_rows_back(const struct ggml_compute_params * params, struct ggml_tensor * dst);
void ggml_compute_forward_diag(const struct ggml_compute_params * params, struct ggml_tensor * dst);
void ggml_compute_forward_diag_mask_inf(const struct ggml_compute_params * params, struct ggml_tensor * dst);
void ggml_compute_forward_diag_mask_zero(const struct ggml_compute_params * params, struct ggml_tensor * dst);
void ggml_compute_forward_soft_max(const struct ggml_compute_params * params, struct ggml_tensor * dst);
void ggml_compute_forward_soft_max_ext_back(const struct ggml_compute_params * params, struct ggml_tensor * dst);
void ggml_compute_forward_rope(const struct ggml_compute_params * params, struct ggml_tensor * dst);
void ggml_compute_forward_rope_back(const struct ggml_compute_params * params, struct ggml_tensor * dst);
void ggml_compute_forward_clamp(const struct ggml_compute_params * params, struct ggml_tensor * dst);
void ggml_compute_forward_conv_transpose_1d(const struct ggml_compute_params * params, struct ggml_tensor * dst);
void ggml_compute_forward_im2col(const struct ggml_compute_params * params, struct ggml_tensor * dst);
void ggml_compute_forward_im2col_back_f32(const struct ggml_compute_params * params, struct ggml_tensor * dst);
void ggml_compute_forward_conv_transpose_2d(const struct ggml_compute_params * params, struct ggml_tensor * dst);
void ggml_compute_forward_pool_1d(const struct ggml_compute_params * params, struct ggml_tensor * dst);
void ggml_compute_forward_pool_2d(const struct ggml_compute_params * params, struct ggml_tensor * dst);
void ggml_compute_forward_pool_2d_back(const struct ggml_compute_params * params, struct ggml_tensor * dst);
void ggml_compute_forward_upscale(const struct ggml_compute_params * params, struct ggml_tensor * dst);
void ggml_compute_forward_pad(const struct ggml_compute_params * params, struct ggml_tensor * dst);
void ggml_compute_forward_pad_reflect_1d(const struct ggml_compute_params * params, struct ggml_tensor * dst);
void ggml_compute_forward_arange(const struct ggml_compute_params * params, struct ggml_tensor * dst);
void ggml_compute_forward_timestep_embedding(const struct ggml_compute_params * params, struct ggml_tensor * dst);
void ggml_compute_forward_argsort(const struct ggml_compute_params * params, struct ggml_tensor * dst);
void ggml_compute_forward_leaky_relu(const struct ggml_compute_params * params, struct ggml_tensor * dst);
void ggml_compute_forward_flash_attn_ext(
const struct ggml_compute_params * params,
const struct ggml_tensor * q,
const struct ggml_tensor * k,
const struct ggml_tensor * v,
const struct ggml_tensor * mask,
struct ggml_tensor * dst);
void ggml_compute_forward_flash_attn_back(
const struct ggml_compute_params * params,
const bool masked,
struct ggml_tensor * dst);
void ggml_compute_forward_ssm_conv(const struct ggml_compute_params * params, struct ggml_tensor * dst);
void ggml_compute_forward_ssm_scan(const struct ggml_compute_params * params, struct ggml_tensor * dst);
void ggml_compute_forward_win_part(const struct ggml_compute_params * params, struct ggml_tensor * dst);
void ggml_compute_forward_win_unpart(const struct ggml_compute_params * params, struct ggml_tensor * dst);
void ggml_compute_forward_unary(const struct ggml_compute_params * params, struct ggml_tensor * dst);
void ggml_compute_forward_get_rel_pos(const struct ggml_compute_params * params, struct ggml_tensor * dst);
void ggml_compute_forward_add_rel_pos(const struct ggml_compute_params * params, struct ggml_tensor * dst);
void ggml_compute_forward_rwkv_wkv6(const struct ggml_compute_params * params, struct ggml_tensor * dst);
void ggml_compute_forward_rwkv_wkv7(const struct ggml_compute_params * params, struct ggml_tensor * dst);
void ggml_compute_forward_gla(const struct ggml_compute_params * params, struct ggml_tensor * dst);
void ggml_compute_forward_map_unary(
const struct ggml_compute_params * params,
struct ggml_tensor * dst,
const ggml_unary_op_f32_t fun);
void ggml_compute_forward_map_binary(
const struct ggml_compute_params * params,
struct ggml_tensor * dst,
const ggml_binary_op_f32_t fun);
void ggml_compute_forward_map_custom1_f32(
const struct ggml_compute_params * params,
struct ggml_tensor * dst,
const ggml_custom1_op_f32_t fun);
void ggml_compute_forward_map_custom2_f32(
const struct ggml_compute_params * params,
struct ggml_tensor * dst,
const ggml_custom2_op_f32_t fun);
void ggml_compute_forward_map_custom3_f32(
const struct ggml_compute_params * params,
struct ggml_tensor * dst,
const ggml_custom3_op_f32_t fun);
void ggml_compute_forward_map_custom1(const struct ggml_compute_params * params, struct ggml_tensor * dst);
void ggml_compute_forward_map_custom2(const struct ggml_compute_params * params, struct ggml_tensor * dst);
void ggml_compute_forward_map_custom3(const struct ggml_compute_params * params, struct ggml_tensor * dst);
void ggml_compute_forward_cross_entropy_loss(const struct ggml_compute_params * params, struct ggml_tensor * dst);
void ggml_compute_forward_cross_entropy_loss_back(const struct ggml_compute_params * params, struct ggml_tensor * dst);
void ggml_compute_forward_opt_step_adamw(const struct ggml_compute_params * params, struct ggml_tensor * dst);
#ifdef __cplusplus
}
#endif

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@ -0,0 +1,884 @@
#pragma once
#include "ggml-cpu-impl.h"
//
// simd mappings
//
// we define a common set of C macros which map to specific intrinsics based on the current architecture
// we then implement the fundamental computation operations below using only these macros
// adding support for new architectures requires to define the corresponding SIMD macros
//
// GGML_F32_STEP / GGML_F16_STEP
// number of elements to process in a single step
//
// GGML_F32_EPR / GGML_F16_EPR
// number of elements to fit in a single register
//
#if defined(__ARM_NEON) && defined(__ARM_FEATURE_FMA)
#define GGML_SIMD
// F32 NEON
#define GGML_F32_STEP 16
#define GGML_F32_EPR 4
#define GGML_F32x4 float32x4_t
#define GGML_F32x4_ZERO vdupq_n_f32(0.0f)
#define GGML_F32x4_SET1(x) vdupq_n_f32(x)
#define GGML_F32x4_LOAD vld1q_f32
#define GGML_F32x4_STORE vst1q_f32
#define GGML_F32x4_FMA(a, b, c) vfmaq_f32(a, b, c)
#define GGML_F32x4_ADD vaddq_f32
#define GGML_F32x4_MUL vmulq_f32
#define GGML_F32x4_REDUCE_ONE(x) vaddvq_f32(x)
#define GGML_F32x4_REDUCE(res, x) \
{ \
int offset = GGML_F32_ARR >> 1; \
for (int i = 0; i < offset; ++i) { \
(x)[i] = vaddq_f32((x)[i], (x)[offset+i]); \
} \
offset >>= 1; \
for (int i = 0; i < offset; ++i) { \
(x)[i] = vaddq_f32((x)[i], (x)[offset+i]); \
} \
offset >>= 1; \
for (int i = 0; i < offset; ++i) { \
(x)[i] = vaddq_f32((x)[i], (x)[offset+i]); \
} \
(res) = (ggml_float) GGML_F32x4_REDUCE_ONE((x)[0]); \
}
#define GGML_F32_VEC GGML_F32x4
#define GGML_F32_VEC_ZERO GGML_F32x4_ZERO
#define GGML_F32_VEC_SET1 GGML_F32x4_SET1
#define GGML_F32_VEC_LOAD GGML_F32x4_LOAD
#define GGML_F32_VEC_STORE GGML_F32x4_STORE
#define GGML_F32_VEC_FMA GGML_F32x4_FMA
#define GGML_F32_VEC_ADD GGML_F32x4_ADD
#define GGML_F32_VEC_MUL GGML_F32x4_MUL
#define GGML_F32_VEC_REDUCE GGML_F32x4_REDUCE
// F16 NEON
#if defined(__ARM_FEATURE_FP16_VECTOR_ARITHMETIC)
#define GGML_F16_STEP 32
#define GGML_F16_EPR 8
#define GGML_F16x8 float16x8_t
#define GGML_F16x8_ZERO vdupq_n_f16(0.0f)
#define GGML_F16x8_SET1(x) vdupq_n_f16(x)
#define GGML_F16x8_LOAD(x) vld1q_f16((const ggml_fp16_internal_t *)(x))
#define GGML_F16x8_STORE vst1q_f16
#define GGML_F16x8_FMA(a, b, c) vfmaq_f16(a, b, c)
#define GGML_F16x8_ADD vaddq_f16
#define GGML_F16x8_MUL vmulq_f16
#define GGML_F16x8_REDUCE(res, x) \
do { \
int offset = GGML_F16_ARR >> 1; \
for (int i = 0; i < offset; ++i) { \
(x)[i] = vaddq_f16((x)[i], (x)[offset+i]); \
} \
offset >>= 1; \
for (int i = 0; i < offset; ++i) { \
(x)[i] = vaddq_f16((x)[i], (x)[offset+i]); \
} \
offset >>= 1; \
for (int i = 0; i < offset; ++i) { \
(x)[i] = vaddq_f16((x)[i], (x)[offset+i]); \
} \
const float32x4_t t0 = vcvt_f32_f16(vget_low_f16 ((x)[0])); \
const float32x4_t t1 = vcvt_f32_f16(vget_high_f16((x)[0])); \
(res) = (ggml_float) vaddvq_f32(vaddq_f32(t0, t1)); \
} while (0)
#define GGML_F16_VEC GGML_F16x8
#define GGML_F16_VEC_ZERO GGML_F16x8_ZERO
#define GGML_F16_VEC_SET1 GGML_F16x8_SET1
#define GGML_F16_VEC_LOAD(p, i) GGML_F16x8_LOAD(p)
#define GGML_F16_VEC_STORE(p, r, i) GGML_F16x8_STORE((ggml_fp16_internal_t *)(p), (r)[i])
#define GGML_F16_VEC_FMA GGML_F16x8_FMA
#define GGML_F16_VEC_ADD GGML_F16x8_ADD
#define GGML_F16_VEC_MUL GGML_F16x8_MUL
#define GGML_F16_VEC_REDUCE GGML_F16x8_REDUCE
#else
// if FP16 vector arithmetic is not supported, we use FP32 instead
// and take advantage of the vcvt_ functions to convert to/from FP16
#define GGML_F16_STEP 16
#define GGML_F16_EPR 4
#define GGML_F32Cx4 float32x4_t
#define GGML_F32Cx4_ZERO vdupq_n_f32(0.0f)
#define GGML_F32Cx4_SET1(x) vdupq_n_f32(x)
#define GGML_F32Cx4_LOAD(x) vcvt_f32_f16(vld1_f16((const ggml_fp16_internal_t *)(x)))
#define GGML_F32Cx4_STORE(x, y) vst1_f16(x, vcvt_f16_f32(y))
#define GGML_F32Cx4_FMA(a, b, c) vfmaq_f32(a, b, c)
#define GGML_F32Cx4_ADD vaddq_f32
#define GGML_F32Cx4_MUL vmulq_f32
#define GGML_F32Cx4_REDUCE GGML_F32x4_REDUCE
#define GGML_F16_VEC GGML_F32Cx4
#define GGML_F16_VEC_ZERO GGML_F32Cx4_ZERO
#define GGML_F16_VEC_SET1 GGML_F32Cx4_SET1
#define GGML_F16_VEC_LOAD(p, i) GGML_F32Cx4_LOAD(p)
#define GGML_F16_VEC_STORE(p, r, i) GGML_F32Cx4_STORE((ggml_fp16_internal_t *)(p), r[i])
#define GGML_F16_VEC_FMA GGML_F32Cx4_FMA
#define GGML_F16_VEC_ADD GGML_F32Cx4_ADD
#define GGML_F16_VEC_MUL GGML_F32Cx4_MUL
#define GGML_F16_VEC_REDUCE GGML_F32Cx4_REDUCE
#endif
#elif defined(__AVX512F__)
#define GGML_SIMD
// F32 AVX512
#define GGML_F32_STEP 64
#define GGML_F32_EPR 16
#define GGML_F32x16 __m512
#define GGML_F32x16_ZERO _mm512_setzero_ps()
#define GGML_F32x16_SET1(x) _mm512_set1_ps(x)
#define GGML_F32x16_LOAD _mm512_loadu_ps
#define GGML_F32x16_STORE _mm512_storeu_ps
// _mm512_fmadd_ps is defined in AVX512F so no guard is required
#define GGML_F32x16_FMA(a, b, c) _mm512_fmadd_ps(b, c, a)
#define GGML_F32x16_ADD _mm512_add_ps
#define GGML_F32x16_MUL _mm512_mul_ps
#define GGML_F32x16_REDUCE(res, x) \
do { \
int offset = GGML_F32_ARR >> 1; \
for (int i = 0; i < offset; ++i) { \
x[i] = _mm512_add_ps(x[i], x[offset+i]); \
} \
offset >>= 1; \
for (int i = 0; i < offset; ++i) { \
x[i] = _mm512_add_ps(x[i], x[offset+i]); \
} \
offset >>= 1; \
for (int i = 0; i < offset; ++i) { \
x[i] = _mm512_add_ps(x[i], x[offset+i]); \
} \
res = (ggml_float) _mm512_reduce_add_ps(x[0]); \
} while (0)
// TODO: is this optimal ?
#define GGML_F32_VEC GGML_F32x16
#define GGML_F32_VEC_ZERO GGML_F32x16_ZERO
#define GGML_F32_VEC_SET1 GGML_F32x16_SET1
#define GGML_F32_VEC_LOAD GGML_F32x16_LOAD
#define GGML_F32_VEC_STORE GGML_F32x16_STORE
#define GGML_F32_VEC_FMA GGML_F32x16_FMA
#define GGML_F32_VEC_ADD GGML_F32x16_ADD
#define GGML_F32_VEC_MUL GGML_F32x16_MUL
#define GGML_F32_VEC_REDUCE GGML_F32x16_REDUCE
// F16 AVX512
// F16 AVX
#define GGML_F16_STEP 64
#define GGML_F16_EPR 16
// AVX512 has FP16 extension (AVX512_FP16) but I don't have it on my machine so I use FP32 instead
#define GGML_F32Cx16 __m512
#define GGML_F32Cx16_ZERO _mm512_setzero_ps()
#define GGML_F32Cx16_SET1(x) _mm512_set1_ps(x)
// unlike _mm256_cvt intrinsics that require F16C, _mm512_cvt is defined in AVX512F
// so F16C guard isn't required
#define GGML_F32Cx16_LOAD(x) _mm512_cvtph_ps(_mm256_loadu_si256((const __m256i *)(x)))
#define GGML_F32Cx16_STORE(x, y) _mm256_storeu_si256((__m256i *)(x), _mm512_cvtps_ph(y, 0))
#define GGML_F32Cx16_FMA(a, b, c) _mm512_fmadd_ps(b, c, a)
#define GGML_F32Cx16_ADD _mm512_add_ps
#define GGML_F32Cx16_MUL _mm512_mul_ps
#define GGML_F32Cx16_REDUCE(res, x) \
do { \
int offset = GGML_F32_ARR >> 1; \
for (int i = 0; i < offset; ++i) { \
x[i] = _mm512_add_ps(x[i], x[offset+i]); \
} \
offset >>= 1; \
for (int i = 0; i < offset; ++i) { \
x[i] = _mm512_add_ps(x[i], x[offset+i]); \
} \
offset >>= 1; \
for (int i = 0; i < offset; ++i) { \
x[i] = _mm512_add_ps(x[i], x[offset+i]); \
} \
res = (ggml_float) _mm512_reduce_add_ps(x[0]); \
} while (0)
#define GGML_F16_VEC GGML_F32Cx16
#define GGML_F16_VEC_ZERO GGML_F32Cx16_ZERO
#define GGML_F16_VEC_SET1 GGML_F32Cx16_SET1
#define GGML_F16_VEC_LOAD(p, i) GGML_F32Cx16_LOAD(p)
#define GGML_F16_VEC_STORE(p, r, i) GGML_F32Cx16_STORE(p, r[i])
#define GGML_F16_VEC_FMA GGML_F32Cx16_FMA
#define GGML_F16_VEC_ADD GGML_F32Cx16_ADD
#define GGML_F16_VEC_MUL GGML_F32Cx16_MUL
#define GGML_F16_VEC_REDUCE GGML_F32Cx16_REDUCE
#elif defined(__AVX__)
#define GGML_SIMD
// F32 AVX
#define GGML_F32_STEP 32
#define GGML_F32_EPR 8
#define GGML_F32x8 __m256
#define GGML_F32x8_ZERO _mm256_setzero_ps()
#define GGML_F32x8_SET1(x) _mm256_set1_ps(x)
#define GGML_F32x8_LOAD _mm256_loadu_ps
#define GGML_F32x8_STORE _mm256_storeu_ps
#if defined(__FMA__)
#define GGML_F32x8_FMA(a, b, c) _mm256_fmadd_ps(b, c, a)
#else
#define GGML_F32x8_FMA(a, b, c) _mm256_add_ps(_mm256_mul_ps(b, c), a)
#endif
#define GGML_F32x8_ADD _mm256_add_ps
#define GGML_F32x8_MUL _mm256_mul_ps
#define GGML_F32x8_REDUCE(res, x) \
do { \
int offset = GGML_F32_ARR >> 1; \
for (int i = 0; i < offset; ++i) { \
x[i] = _mm256_add_ps(x[i], x[offset+i]); \
} \
offset >>= 1; \
for (int i = 0; i < offset; ++i) { \
x[i] = _mm256_add_ps(x[i], x[offset+i]); \
} \
offset >>= 1; \
for (int i = 0; i < offset; ++i) { \
x[i] = _mm256_add_ps(x[i], x[offset+i]); \
} \
const __m128 t0 = _mm_add_ps(_mm256_castps256_ps128(x[0]), \
_mm256_extractf128_ps(x[0], 1)); \
const __m128 t1 = _mm_hadd_ps(t0, t0); \
res = (ggml_float) _mm_cvtss_f32(_mm_hadd_ps(t1, t1)); \
} while (0)
// TODO: is this optimal ?
#define GGML_F32_VEC GGML_F32x8
#define GGML_F32_VEC_ZERO GGML_F32x8_ZERO
#define GGML_F32_VEC_SET1 GGML_F32x8_SET1
#define GGML_F32_VEC_LOAD GGML_F32x8_LOAD
#define GGML_F32_VEC_STORE GGML_F32x8_STORE
#define GGML_F32_VEC_FMA GGML_F32x8_FMA
#define GGML_F32_VEC_ADD GGML_F32x8_ADD
#define GGML_F32_VEC_MUL GGML_F32x8_MUL
#define GGML_F32_VEC_REDUCE GGML_F32x8_REDUCE
// F16 AVX
#define GGML_F16_STEP 32
#define GGML_F16_EPR 8
// F16 arithmetic is not supported by AVX, so we use F32 instead
#define GGML_F32Cx8 __m256
#define GGML_F32Cx8_ZERO _mm256_setzero_ps()
#define GGML_F32Cx8_SET1(x) _mm256_set1_ps(x)
#if defined(__F16C__)
// the _mm256_cvt intrinsics require F16C
#define GGML_F32Cx8_LOAD(x) _mm256_cvtph_ps(_mm_loadu_si128((const __m128i *)(x)))
#define GGML_F32Cx8_STORE(x, y) _mm_storeu_si128((__m128i *)(x), _mm256_cvtps_ph(y, 0))
#else
static inline __m256 __avx_f32cx8_load(const ggml_fp16_t * x) {
float tmp[8];
for (int i = 0; i < 8; i++) {
tmp[i] = GGML_FP16_TO_FP32(x[i]);
}
return _mm256_loadu_ps(tmp);
}
static inline void __avx_f32cx8_store(ggml_fp16_t *x, __m256 y) {
float arr[8];
_mm256_storeu_ps(arr, y);
for (int i = 0; i < 8; i++)
x[i] = GGML_FP32_TO_FP16(arr[i]);
}
#define GGML_F32Cx8_LOAD(x) __avx_f32cx8_load(x)
#define GGML_F32Cx8_STORE(x, y) __avx_f32cx8_store(x, y)
#endif
#define GGML_F32Cx8_FMA GGML_F32x8_FMA
#define GGML_F32Cx8_ADD _mm256_add_ps
#define GGML_F32Cx8_MUL _mm256_mul_ps
#define GGML_F32Cx8_REDUCE GGML_F32x8_REDUCE
#define GGML_F16_VEC GGML_F32Cx8
#define GGML_F16_VEC_ZERO GGML_F32Cx8_ZERO
#define GGML_F16_VEC_SET1 GGML_F32Cx8_SET1
#define GGML_F16_VEC_LOAD(p, i) GGML_F32Cx8_LOAD(p)
#define GGML_F16_VEC_STORE(p, r, i) GGML_F32Cx8_STORE(p, r[i])
#define GGML_F16_VEC_FMA GGML_F32Cx8_FMA
#define GGML_F16_VEC_ADD GGML_F32Cx8_ADD
#define GGML_F16_VEC_MUL GGML_F32Cx8_MUL
#define GGML_F16_VEC_REDUCE GGML_F32Cx8_REDUCE
#elif defined(__POWER9_VECTOR__)
#define GGML_SIMD
// F32 POWER9
#define GGML_F32_STEP 32
#define GGML_F32_EPR 4
#define GGML_F32x4 vector float
#define GGML_F32x4_ZERO 0.0f
#define GGML_F32x4_SET1 vec_splats
#define GGML_F32x4_LOAD(p) vec_xl(0, p)
#define GGML_F32x4_STORE(p, r) vec_xst(r, 0, p)
#define GGML_F32x4_FMA(a, b, c) vec_madd(b, c, a)
#define GGML_F32x4_ADD vec_add
#define GGML_F32x4_MUL vec_mul
#define GGML_F32x4_REDUCE(res, x) \
{ \
int offset = GGML_F32_ARR >> 1; \
for (int i = 0; i < offset; ++i) { \
x[i] = vec_add(x[i], x[offset+i]); \
} \
offset >>= 1; \
for (int i = 0; i < offset; ++i) { \
x[i] = vec_add(x[i], x[offset+i]); \
} \
offset >>= 1; \
for (int i = 0; i < offset; ++i) { \
x[i] = vec_add(x[i], x[offset+i]); \
} \
res = vec_extract(x[0], 0) + \
vec_extract(x[0], 1) + \
vec_extract(x[0], 2) + \
vec_extract(x[0], 3); \
}
#define GGML_F32_VEC GGML_F32x4
#define GGML_F32_VEC_ZERO GGML_F32x4_ZERO
#define GGML_F32_VEC_SET1 GGML_F32x4_SET1
#define GGML_F32_VEC_LOAD GGML_F32x4_LOAD
#define GGML_F32_VEC_STORE GGML_F32x4_STORE
#define GGML_F32_VEC_FMA GGML_F32x4_FMA
#define GGML_F32_VEC_ADD GGML_F32x4_ADD
#define GGML_F32_VEC_MUL GGML_F32x4_MUL
#define GGML_F32_VEC_REDUCE GGML_F32x4_REDUCE
// F16 POWER9
#define GGML_F16_STEP GGML_F32_STEP
#define GGML_F16_EPR GGML_F32_EPR
#define GGML_F16_VEC GGML_F32x4
#define GGML_F16_VEC_ZERO GGML_F32x4_ZERO
#define GGML_F16_VEC_SET1 GGML_F32x4_SET1
#define GGML_F16_VEC_FMA GGML_F32x4_FMA
#define GGML_F16_VEC_ADD GGML_F32x4_ADD
#define GGML_F16_VEC_MUL GGML_F32x4_MUL
#define GGML_F16_VEC_REDUCE GGML_F32x4_REDUCE
// Use vec_xl, not vec_ld, in case the load address is not aligned.
#define GGML_F16_VEC_LOAD(p, i) (i & 0x1) ? \
vec_extract_fp32_from_shorth(vec_xl(0, p - GGML_F16_EPR)) : \
vec_extract_fp32_from_shortl(vec_xl(0, p))
#define GGML_ENDIAN_BYTE(i) ((unsigned char *)&(uint16_t){1})[i]
#define GGML_F16_VEC_STORE(p, r, i) \
if (i & 0x1) \
vec_xst(vec_pack_to_short_fp32(r[i - GGML_ENDIAN_BYTE(1)], \
r[i - GGML_ENDIAN_BYTE(0)]), \
0, p - GGML_F16_EPR)
#elif defined(__wasm_simd128__)
#define GGML_SIMD
// F32 WASM
#define GGML_F32_STEP 16
#define GGML_F32_EPR 4
#define GGML_F32x4 v128_t
#define GGML_F32x4_ZERO wasm_f32x4_splat(0.0f)
#define GGML_F32x4_SET1(x) wasm_f32x4_splat(x)
#define GGML_F32x4_LOAD wasm_v128_load
#define GGML_F32x4_STORE wasm_v128_store
#define GGML_F32x4_FMA(a, b, c) wasm_f32x4_add(wasm_f32x4_mul(b, c), a)
#define GGML_F32x4_ADD wasm_f32x4_add
#define GGML_F32x4_MUL wasm_f32x4_mul
#define GGML_F32x4_REDUCE(res, x) \
{ \
int offset = GGML_F32_ARR >> 1; \
for (int i = 0; i < offset; ++i) { \
x[i] = wasm_f32x4_add(x[i], x[offset+i]); \
} \
offset >>= 1; \
for (int i = 0; i < offset; ++i) { \
x[i] = wasm_f32x4_add(x[i], x[offset+i]); \
} \
offset >>= 1; \
for (int i = 0; i < offset; ++i) { \
x[i] = wasm_f32x4_add(x[i], x[offset+i]); \
} \
res = wasm_f32x4_extract_lane(x[0], 0) + \
wasm_f32x4_extract_lane(x[0], 1) + \
wasm_f32x4_extract_lane(x[0], 2) + \
wasm_f32x4_extract_lane(x[0], 3); \
}
#define GGML_F32_VEC GGML_F32x4
#define GGML_F32_VEC_ZERO GGML_F32x4_ZERO
#define GGML_F32_VEC_SET1 GGML_F32x4_SET1
#define GGML_F32_VEC_LOAD GGML_F32x4_LOAD
#define GGML_F32_VEC_STORE GGML_F32x4_STORE
#define GGML_F32_VEC_FMA GGML_F32x4_FMA
#define GGML_F32_VEC_ADD GGML_F32x4_ADD
#define GGML_F32_VEC_MUL GGML_F32x4_MUL
#define GGML_F32_VEC_REDUCE GGML_F32x4_REDUCE
// F16 WASM
#define GGML_F16_STEP 16
#define GGML_F16_EPR 4
inline static v128_t __wasm_f16x4_load(const ggml_fp16_t * p) {
float tmp[4];
tmp[0] = GGML_FP16_TO_FP32(p[0]);
tmp[1] = GGML_FP16_TO_FP32(p[1]);
tmp[2] = GGML_FP16_TO_FP32(p[2]);
tmp[3] = GGML_FP16_TO_FP32(p[3]);
return wasm_v128_load(tmp);
}
inline static void __wasm_f16x4_store(ggml_fp16_t * p, v128_t x) {
float tmp[4];
wasm_v128_store(tmp, x);
p[0] = GGML_FP32_TO_FP16(tmp[0]);
p[1] = GGML_FP32_TO_FP16(tmp[1]);
p[2] = GGML_FP32_TO_FP16(tmp[2]);
p[3] = GGML_FP32_TO_FP16(tmp[3]);
}
#define GGML_F16x4 v128_t
#define GGML_F16x4_ZERO wasm_f32x4_splat(0.0f)
#define GGML_F16x4_SET1(x) wasm_f32x4_splat(x)
#define GGML_F16x4_LOAD(x) __wasm_f16x4_load(x)
#define GGML_F16x4_STORE(x, y) __wasm_f16x4_store(x, y)
#define GGML_F16x4_FMA GGML_F32x4_FMA
#define GGML_F16x4_ADD wasm_f32x4_add
#define GGML_F16x4_MUL wasm_f32x4_mul
#define GGML_F16x4_REDUCE(res, x) \
{ \
int offset = GGML_F16_ARR >> 1; \
for (int i = 0; i < offset; ++i) { \
x[i] = wasm_f32x4_add(x[i], x[offset+i]); \
} \
offset >>= 1; \
for (int i = 0; i < offset; ++i) { \
x[i] = wasm_f32x4_add(x[i], x[offset+i]); \
} \
offset >>= 1; \
for (int i = 0; i < offset; ++i) { \
x[i] = wasm_f32x4_add(x[i], x[offset+i]); \
} \
res = (ggml_float) (wasm_f32x4_extract_lane(x[0], 0) + \
wasm_f32x4_extract_lane(x[0], 1) + \
wasm_f32x4_extract_lane(x[0], 2) + \
wasm_f32x4_extract_lane(x[0], 3)); \
}
#define GGML_F16_VEC GGML_F16x4
#define GGML_F16_VEC_ZERO GGML_F16x4_ZERO
#define GGML_F16_VEC_SET1 GGML_F16x4_SET1
#define GGML_F16_VEC_LOAD(p, i) GGML_F16x4_LOAD(p)
#define GGML_F16_VEC_STORE(p, r, i) GGML_F16x4_STORE(p, r[i])
#define GGML_F16_VEC_FMA GGML_F16x4_FMA
#define GGML_F16_VEC_ADD GGML_F16x4_ADD
#define GGML_F16_VEC_MUL GGML_F16x4_MUL
#define GGML_F16_VEC_REDUCE GGML_F16x4_REDUCE
#elif defined(__SSE3__)
#define GGML_SIMD
// F32 SSE
#define GGML_F32_STEP 32
#define GGML_F32_EPR 4
#define GGML_F32x4 __m128
#define GGML_F32x4_ZERO _mm_setzero_ps()
#define GGML_F32x4_SET1(x) _mm_set1_ps(x)
#define GGML_F32x4_LOAD _mm_loadu_ps
#define GGML_F32x4_STORE _mm_storeu_ps
#if defined(__FMA__)
// TODO: Does this work?
#define GGML_F32x4_FMA(a, b, c) _mm_fmadd_ps(b, c, a)
#else
#define GGML_F32x4_FMA(a, b, c) _mm_add_ps(_mm_mul_ps(b, c), a)
#endif
#define GGML_F32x4_ADD _mm_add_ps
#define GGML_F32x4_MUL _mm_mul_ps
#define GGML_F32x4_REDUCE(res, x) \
{ \
int offset = GGML_F32_ARR >> 1; \
for (int i = 0; i < offset; ++i) { \
x[i] = _mm_add_ps(x[i], x[offset+i]); \
} \
offset >>= 1; \
for (int i = 0; i < offset; ++i) { \
x[i] = _mm_add_ps(x[i], x[offset+i]); \
} \
offset >>= 1; \
for (int i = 0; i < offset; ++i) { \
x[i] = _mm_add_ps(x[i], x[offset+i]); \
} \
const __m128 t0 = _mm_hadd_ps(x[0], x[0]); \
res = (ggml_float) _mm_cvtss_f32(_mm_hadd_ps(t0, t0)); \
}
// TODO: is this optimal ?
#define GGML_F32_VEC GGML_F32x4
#define GGML_F32_VEC_ZERO GGML_F32x4_ZERO
#define GGML_F32_VEC_SET1 GGML_F32x4_SET1
#define GGML_F32_VEC_LOAD GGML_F32x4_LOAD
#define GGML_F32_VEC_STORE GGML_F32x4_STORE
#define GGML_F32_VEC_FMA GGML_F32x4_FMA
#define GGML_F32_VEC_ADD GGML_F32x4_ADD
#define GGML_F32_VEC_MUL GGML_F32x4_MUL
#define GGML_F32_VEC_REDUCE GGML_F32x4_REDUCE
// F16 SSE
#define GGML_F16_STEP 32
#define GGML_F16_EPR 4
static inline __m128 __sse_f16x4_load(const ggml_fp16_t * x) {
float tmp[4];
tmp[0] = GGML_FP16_TO_FP32(x[0]);
tmp[1] = GGML_FP16_TO_FP32(x[1]);
tmp[2] = GGML_FP16_TO_FP32(x[2]);
tmp[3] = GGML_FP16_TO_FP32(x[3]);
return _mm_loadu_ps(tmp);
}
static inline void __sse_f16x4_store(ggml_fp16_t * x, __m128 y) {
float arr[4];
_mm_storeu_ps(arr, y);
x[0] = GGML_FP32_TO_FP16(arr[0]);
x[1] = GGML_FP32_TO_FP16(arr[1]);
x[2] = GGML_FP32_TO_FP16(arr[2]);
x[3] = GGML_FP32_TO_FP16(arr[3]);
}
#define GGML_F32Cx4 __m128
#define GGML_F32Cx4_ZERO _mm_setzero_ps()
#define GGML_F32Cx4_SET1(x) _mm_set1_ps(x)
#define GGML_F32Cx4_LOAD(x) __sse_f16x4_load(x)
#define GGML_F32Cx4_STORE(x, y) __sse_f16x4_store(x, y)
#define GGML_F32Cx4_FMA GGML_F32x4_FMA
#define GGML_F32Cx4_ADD _mm_add_ps
#define GGML_F32Cx4_MUL _mm_mul_ps
#define GGML_F32Cx4_REDUCE GGML_F32x4_REDUCE
#define GGML_F16_VEC GGML_F32Cx4
#define GGML_F16_VEC_ZERO GGML_F32Cx4_ZERO
#define GGML_F16_VEC_SET1 GGML_F32Cx4_SET1
#define GGML_F16_VEC_LOAD(p, i) GGML_F32Cx4_LOAD(p)
#define GGML_F16_VEC_STORE(p, r, i) GGML_F32Cx4_STORE(p, r[i])
#define GGML_F16_VEC_FMA GGML_F32Cx4_FMA
#define GGML_F16_VEC_ADD GGML_F32Cx4_ADD
#define GGML_F16_VEC_MUL GGML_F32Cx4_MUL
#define GGML_F16_VEC_REDUCE GGML_F32Cx4_REDUCE
#elif defined(__loongarch_asx)
#define GGML_SIMD
// F32 LASX
#define GGML_F32_STEP 32
#define GGML_F32_EPR 8
#define GGML_F32x8 __m256
#define GGML_F32x8_ZERO (__m256)__lasx_xvldi(0)
#define GGML_F32x8_SET1(x) (__m256)__lasx_xvreplfr2vr_s((x))
#define GGML_F32x8_LOAD(x) (__m256)__lasx_xvld((x), 0)
#define GGML_F32x8_STORE(x,y) __lasx_xvst((y), (x), 0)
#define GGML_F32x8_FMA(a, b, c) __lasx_xvfmadd_s(b, c, a)
#define GGML_F32x8_ADD __lasx_xvfadd_s
#define GGML_F32x8_MUL __lasx_xvfmul_s
#define GGML_F32x8_REDUCE(res, x) \
do { \
int offset = GGML_F32_ARR >> 1; \
for (int i = 0; i < offset; ++i) { \
x[i] = __lasx_xvfadd_s(x[i], x[offset+i]); \
} \
offset >>= 1; \
for (int i = 0; i < offset; ++i) { \
x[i] = __lasx_xvfadd_s(x[i], x[offset+i]); \
} \
offset >>= 1; \
for (int i = 0; i < offset; ++i) { \
x[i] = __lasx_xvfadd_s(x[i], x[offset+i]); \
} \
float *tmp_p = (float *)&x[0]; \
res = tmp_p[0] + tmp_p[1] + tmp_p[2] + tmp_p[3] + tmp_p[4] + tmp_p[5] + tmp_p[6] + tmp_p[7]; \
} while (0)
// TODO: is this optimal ?
#define GGML_F32_VEC GGML_F32x8
#define GGML_F32_VEC_ZERO GGML_F32x8_ZERO
#define GGML_F32_VEC_SET1 GGML_F32x8_SET1
#define GGML_F32_VEC_LOAD GGML_F32x8_LOAD
#define GGML_F32_VEC_STORE GGML_F32x8_STORE
#define GGML_F32_VEC_FMA GGML_F32x8_FMA
#define GGML_F32_VEC_ADD GGML_F32x8_ADD
#define GGML_F32_VEC_MUL GGML_F32x8_MUL
#define GGML_F32_VEC_REDUCE GGML_F32x8_REDUCE
// F16 LASX
#define GGML_F16_STEP 32
#define GGML_F16_EPR 8
// F16 arithmetic is not supported by LASX, so we use F32 instead
#define GGML_F32Cx8 __m256
#define GGML_F32Cx8_ZERO (__m256)__lasx_xvldi(0)
#define GGML_F32Cx8_SET1(x) (__m256)__lasx_xvreplgr2vr_w((x))
static inline __m256 __lasx_f32cx8_load(const ggml_fp16_t * x) {
__m256i a;
memcpy(&a, x, sizeof(ggml_fp16_t) * 8);
a = __lasx_xvpermi_d(a, 0 | (1 << 4));
return __lasx_xvfcvtl_s_h(a);
}
static inline void __lasx_f32cx8_store(ggml_fp16_t * x, __m256 y) {
__m256i a = __lasx_xvfcvt_h_s(y, y);
a = __lasx_xvpermi_d(a, 0 | (2 << 2));
memcpy(x, &a, sizeof(ggml_fp16_t) * 8);
}
#define GGML_F32Cx8_LOAD(x) __lasx_f32cx8_load(x)
#define GGML_F32Cx8_STORE(x, y) __lasx_f32cx8_store(x, y)
#define GGML_F32Cx8_FMA GGML_F32x8_FMA
#define GGML_F32Cx8_ADD __lasx_xvfadd_s
#define GGML_F32Cx8_MUL __lasx_xvfmul_s
#define GGML_F32Cx8_REDUCE GGML_F32x8_REDUCE
#define GGML_F16_VEC GGML_F32Cx8
#define GGML_F16_VEC_ZERO GGML_F32Cx8_ZERO
#define GGML_F16_VEC_SET1 GGML_F32Cx8_SET1
#define GGML_F16_VEC_LOAD(p, i) GGML_F32Cx8_LOAD(p)
#define GGML_F16_VEC_STORE(p, r, i) GGML_F32Cx8_STORE(p, r[i])
#define GGML_F16_VEC_FMA GGML_F32Cx8_FMA
#define GGML_F16_VEC_ADD GGML_F32Cx8_ADD
#define GGML_F16_VEC_MUL GGML_F32Cx8_MUL
#define GGML_F16_VEC_REDUCE GGML_F32Cx8_REDUCE
#elif defined(__loongarch_sx)
#define GGML_SIMD
// F32 LSX
#define GGML_F32_STEP 32
#define GGML_F32_EPR 4
#define GGML_F32x4 __m128
#define GGML_F32x4_ZERO __lsx_vldi(0)
#define GGML_F32x4_SET1(x) __lsx_vinsgr2vr_w(__lsx_vldi(0),(x), 0)
#define GGML_F32x4_LOAD(x) __lsx_vld((x), 0)
#define GGML_F32x4_STORE((x),(y)) __lsx_vst((y), (x), 0)
#define GGML_F32x4_FMA(a, b, c) __lsx_vfmadd_s(b, c, a)
#define GGML_F32x4_ADD __lsx_vfadd_s
#define GGML_F32x4_MUL __lsx_vfmul_s
#define GGML_F32x4_REDUCE(res, x) \
{ \
int offset = GGML_F32_ARR >> 1; \
for (int i = 0; i < offset; ++i) { \
x[i] = __lsx_vfadd_s(x[i], x[offset + i]); \
} \
offset >>= 1; \
for (int i = 0; i < offset; ++i) { \
x[i] = __lsx_vfadd_s(x[i], x[offset + i]); \
} \
offset >>= 1; \
for (int i = 0; i < offset; ++i) { \
x[i] = __lsx_vfadd_s(x[i], x[offset + i]); \
} \
__m128i tmp = __lsx_vsrli_d((__m128i) x[0], 32); \
tmp = (__m128i) __lsx_vfadd_s((__m128) tmp, x[0]); \
tmp = __lsx_vpickev_w(__lsx_vldi(0), tmp); \
const __m128 t0 = __lsx_vshuf4i_w(tmp, 0x88); \
tmp = __lsx_vsrli_d((__m128i) t0, 32); \
tmp = (__m128i) __lsx_vfadd_s((__m128) tmp, t0); \
tmp = __lsx_vpickev_w(__lsx_vldi(0), tmp); \
res = (ggml_float) __lsx_vpickve2gr_w(__lsx_vshuf4i_w(tmp, 0x88), 0); \
}
#define GGML_F32_VEC GGML_F32x4
#define GGML_F32_VEC_ZERO GGML_F32x4_ZERO
#define GGML_F32_VEC_SET1 GGML_F32x4_SET1
#define GGML_F32_VEC_LOAD GGML_F32x4_LOAD
#define GGML_F32_VEC_STORE GGML_F32x4_STORE
#define GGML_F32_VEC_FMA GGML_F32x4_FMA
#define GGML_F32_VEC_ADD GGML_F32x4_ADD
#define GGML_F32_VEC_MUL GGML_F32x4_MUL
#define GGML_F32_VEC_REDUCE GGML_F32x4_REDUCE
// F16 LSX
#define GGML_F16_STEP 32
#define GGML_F16_EPR 4
static inline __m128 __lsx_f16x4_load(const ggml_fp16_t * x) {
float tmp[4];
tmp[0] = GGML_FP16_TO_FP32(x[0]);
tmp[1] = GGML_FP16_TO_FP32(x[1]);
tmp[2] = GGML_FP16_TO_FP32(x[2]);
tmp[3] = GGML_FP16_TO_FP32(x[3]);
return __lsx_vld(tmp, 0);
}
static inline void __lsx_f16x4_store(ggml_fp16_t * x, __m128 y) {
float arr[4];
__lsx_vst(y, arr, 0);
x[0] = GGML_FP32_TO_FP16(arr[0]);
x[1] = GGML_FP32_TO_FP16(arr[1]);
x[2] = GGML_FP32_TO_FP16(arr[2]);
x[3] = GGML_FP32_TO_FP16(arr[3]);
}
#define GGML_F32Cx4 __m128
#define GGML_F32Cx4_ZERO __lsx_vldi(0)
#define GGML_F32Cx4_SET1(x) __lsx_vinsgr2vr_w(__lsx_vldi(0),(x), 0)
#define GGML_F32Cx4_LOAD(x) __lsx_f16x4_load(x)
#define GGML_F32Cx4_STORE(x, y) __lsx_f16x4_store(x, y)
#define GGML_F32Cx4_FMA GGML_F32x4_FMA
#define GGML_F32Cx4_ADD __lsx_vfadd_s
#define GGML_F32Cx4_MUL __lsx_vfmul_s
#define GGML_F32Cx4_REDUCE GGML_F32x4_REDUCE
#define GGML_F16_VEC GGML_F32Cx4
#define GGML_F16_VEC_ZERO GGML_F32Cx4_ZERO
#define GGML_F16_VEC_SET1 GGML_F32Cx4_SET1
#define GGML_F16_VEC_LOAD(p, i) GGML_F32Cx4_LOAD(p)
#define GGML_F16_VEC_STORE(p, r, i) GGML_F32Cx4_STORE(p, r[i])
#define GGML_F16_VEC_FMA GGML_F32Cx4_FMA
#define GGML_F16_VEC_ADD GGML_F32Cx4_ADD
#define GGML_F16_VEC_MUL GGML_F32Cx4_MUL
#define GGML_F16_VEC_REDUCE GGML_F32Cx4_REDUCE
#elif defined(__VXE__) || defined(__VXE2__)
#define GGML_SIMD
// F32 s390x
#define GGML_F32_STEP 32
#define GGML_F32_EPR 4
#define GGML_F32x4 __vector float
#define GGML_F32x4_ZERO vec_splats(0.0f)
#define GGML_F32x4_SET1 vec_splats
#define GGML_F32x4_LOAD(p) vec_xl(0, p)
#define GGML_F32x4_STORE(p, r) vec_xst(r, 0, p)
#define GGML_F32x4_FMA(a, b, c) vec_madd(b, c, a)
#define GGML_F32x4_ADD vec_add
#define GGML_F32x4_MUL vec_mul
#define GGML_F32x4_REDUCE(res, x) \
{ \
int offset = GGML_F32_ARR >> 1; \
for (int i = 0; i < offset; ++i) { \
x[i] = vec_add(x[i], x[offset + i]); \
} \
offset >>= 1; \
for (int i = 0; i < offset; ++i) { \
x[i] = vec_add(x[i], x[offset + i]); \
} \
offset >>= 1; \
for (int i = 0; i < offset; ++i) { \
x[i] = vec_add(x[i], x[offset + i]); \
} \
res = vec_extract(x[0], 0) + \
vec_extract(x[0], 1) + \
vec_extract(x[0], 2) + \
vec_extract(x[0], 3); \
}
#define GGML_F32_VEC GGML_F32x4
#define GGML_F32_VEC_ZERO GGML_F32x4_ZERO
#define GGML_F32_VEC_SET1 GGML_F32x4_SET1
#define GGML_F32_VEC_LOAD GGML_F32x4_LOAD
#define GGML_F32_VEC_STORE GGML_F32x4_STORE
#define GGML_F32_VEC_FMA GGML_F32x4_FMA
#define GGML_F32_VEC_ADD GGML_F32x4_ADD
#define GGML_F32_VEC_MUL GGML_F32x4_MUL
#define GGML_F32_VEC_REDUCE GGML_F32x4_REDUCE
// F16 s390x
#define GGML_F16_STEP GGML_F32_STEP
#define GGML_F16_EPR GGML_F32_EPR
static inline __vector float __lzs_f16cx4_load(const ggml_fp16_t * x) {
float tmp[4];
for (int i = 0; i < 4; i++) {
tmp[i] = GGML_FP16_TO_FP32(x[i]);
}
return vec_xl(0, tmp);
}
static inline void __lzs_f16cx4_store(ggml_fp16_t * x, __vector float y) {
float arr[4];
vec_xst(y, 0, arr);
for (int i = 0; i < 4; i++) {
x[i] = GGML_FP32_TO_FP16(arr[i]);
}
}
#define GGML_F16_VEC GGML_F32x4
#define GGML_F16_VEC_ZERO GGML_F32x4_ZERO
#define GGML_F16_VEC_SET1 GGML_F32x4_SET1
#define GGML_F16_VEC_LOAD(p, i) __lzs_f16cx4_load(p)
#define GGML_F16_VEC_STORE(p, r, i) __lzs_f16cx4_store(p, r[i])
#define GGML_F16_VEC_FMA GGML_F32x4_FMA
#define GGML_F16_VEC_ADD GGML_F32x4_ADD
#define GGML_F16_VEC_MUL GGML_F32x4_MUL
#define GGML_F16_VEC_REDUCE GGML_F32x4_REDUCE
#endif
// GGML_F32_ARR / GGML_F16_ARR
// number of registers to use per step
#ifdef GGML_SIMD
#define GGML_F32_ARR (GGML_F32_STEP/GGML_F32_EPR)
#define GGML_F16_ARR (GGML_F16_STEP/GGML_F16_EPR)
#endif

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#include "vec.h"
#include <cassert>
#if defined(_MSC_VER)
// disable "possible loss of data" to avoid hundreds of casts
// we should just be careful :)
#pragma warning(disable: 4244 4267)
#endif
// precomputed gelu table for f16 (128 KB)
ggml_fp16_t ggml_table_gelu_f16[1 << 16];
// precomputed quick gelu table for f16 (128 KB)
ggml_fp16_t ggml_table_gelu_quick_f16[1 << 16];
void ggml_vec_dot_f32(int n, float * GGML_RESTRICT s, size_t bs, const float * GGML_RESTRICT x, size_t bx, const float * GGML_RESTRICT y, size_t by, int nrc) {
assert(nrc == 1);
GGML_UNUSED(nrc);
GGML_UNUSED(bx);
GGML_UNUSED(by);
GGML_UNUSED(bs);
#if defined(GGML_SIMD)
float sumf = 0.0f;
const int np = (n & ~(GGML_F32_STEP - 1));
GGML_F32_VEC sum[GGML_F32_ARR] = { GGML_F32_VEC_ZERO };
GGML_F32_VEC ax[GGML_F32_ARR];
GGML_F32_VEC ay[GGML_F32_ARR];
for (int i = 0; i < np; i += GGML_F32_STEP) {
for (int j = 0; j < GGML_F32_ARR; j++) {
ax[j] = GGML_F32_VEC_LOAD(x + i + j*GGML_F32_EPR);
ay[j] = GGML_F32_VEC_LOAD(y + i + j*GGML_F32_EPR);
sum[j] = GGML_F32_VEC_FMA(sum[j], ax[j], ay[j]);
}
}
// reduce sum0..sum3 to sum0
GGML_F32_VEC_REDUCE(sumf, sum);
// leftovers
for (int i = np; i < n; ++i) {
sumf += x[i]*y[i];
}
#else
// scalar
ggml_float sumf = 0.0;
for (int i = 0; i < n; ++i) {
sumf += (ggml_float)(x[i]*y[i]);
}
#endif
*s = sumf;
}
void ggml_vec_dot_bf16(int n, float * GGML_RESTRICT s, size_t bs, ggml_bf16_t * GGML_RESTRICT x, size_t bx, ggml_bf16_t * GGML_RESTRICT y, size_t by, int nrc) {
assert(nrc == 1);
GGML_UNUSED(nrc);
GGML_UNUSED(bx);
GGML_UNUSED(by);
GGML_UNUSED(bs);
int i = 0;
ggml_float sumf = 0;
#if defined(__AVX512BF16__)
__m512 c1 = _mm512_setzero_ps();
__m512 c2 = _mm512_setzero_ps();
for (; i + 64 <= n; i += 64) {
c1 = _mm512_dpbf16_ps(c1, m512bh(_mm512_loadu_si512((x + i))),
m512bh(_mm512_loadu_si512((y + i))));
c2 = _mm512_dpbf16_ps(c2, m512bh(_mm512_loadu_si512((x + i + 32))),
m512bh(_mm512_loadu_si512((y + i + 32))));
}
sumf += (ggml_float)_mm512_reduce_add_ps(c1);
sumf += (ggml_float)_mm512_reduce_add_ps(c2);
#elif defined(__AVX512F__)
#define LOAD(p) _mm512_castsi512_ps(_mm512_slli_epi32(_mm512_cvtepu16_epi32(_mm256_loadu_si256((const __m256i *)(p))), 16))
__m512 c1 = _mm512_setzero_ps();
__m512 c2 = _mm512_setzero_ps();
for (; i + 32 <= n; i += 32) {
c1 = _mm512_add_ps(_mm512_mul_ps(LOAD(x + i), LOAD(y + i)), c1);
c2 = _mm512_add_ps(_mm512_mul_ps(LOAD(x + i + 16), LOAD(y + i + 16)), c2);
}
sumf += (ggml_float)_mm512_reduce_add_ps(c1);
sumf += (ggml_float)_mm512_reduce_add_ps(c2);
#undef LOAD
#elif defined(__AVX2__) || defined(__AVX__)
#if defined(__AVX2__)
#define LOAD(p) _mm256_castsi256_ps(_mm256_slli_epi32(_mm256_cvtepu16_epi32(_mm_loadu_si128((const __m128i *)(p))), 16))
#else
#define LOAD(p) _mm256_castsi256_ps(_mm256_insertf128_si256(_mm256_castsi128_si256(_mm_slli_epi32(_mm_cvtepu16_epi32(_mm_loadu_si128((const __m128i *)(p))), 16)), (_mm_slli_epi32(_mm_cvtepu16_epi32(_mm_bsrli_si128(_mm_loadu_si128((const __m128i *)(p)), 8)), 16)), 1))
#endif
__m256 c1 = _mm256_setzero_ps();
__m256 c2 = _mm256_setzero_ps();
__m256 c3 = _mm256_setzero_ps();
__m256 c4 = _mm256_setzero_ps();
for (; i + 32 <= n; i += 32) {
c1 = _mm256_add_ps(_mm256_mul_ps(LOAD(x + i), LOAD(y + i)), c1);
c2 = _mm256_add_ps(_mm256_mul_ps(LOAD(x + i + 8), LOAD(y + i + 8)), c2);
c3 = _mm256_add_ps(_mm256_mul_ps(LOAD(x + i + 16), LOAD(y + i + 16)), c3);
c4 = _mm256_add_ps(_mm256_mul_ps(LOAD(x + i + 24), LOAD(y + i + 24)), c4);
}
__m128 g;
c1 = _mm256_add_ps(_mm256_add_ps(c1, c3),
_mm256_add_ps(c2, c4));
g = _mm_add_ps(_mm256_extractf128_ps(c1, 1),
_mm256_castps256_ps128(c1));
g = _mm_add_ps(g, _mm_movehl_ps(g, g));
g = _mm_add_ss(g, _mm_movehdup_ps(g));
sumf += (ggml_float)_mm_cvtss_f32(g);
#undef LOAD
#endif
for (; i < n; ++i) {
sumf += (ggml_float)(GGML_BF16_TO_FP32(x[i]) *
GGML_BF16_TO_FP32(y[i]));
}
*s = sumf;
}
void ggml_vec_dot_f16(int n, float * GGML_RESTRICT s, size_t bs, ggml_fp16_t * GGML_RESTRICT x, size_t bx, ggml_fp16_t * GGML_RESTRICT y, size_t by, int nrc) {
assert(nrc == 1);
GGML_UNUSED(nrc);
GGML_UNUSED(bx);
GGML_UNUSED(by);
GGML_UNUSED(bs);
ggml_float sumf = 0.0;
#if defined(GGML_SIMD)
const int np = (n & ~(GGML_F16_STEP - 1));
GGML_F16_VEC sum[GGML_F16_ARR] = { GGML_F16_VEC_ZERO };
GGML_F16_VEC ax[GGML_F16_ARR];
GGML_F16_VEC ay[GGML_F16_ARR];
for (int i = 0; i < np; i += GGML_F16_STEP) {
for (int j = 0; j < GGML_F16_ARR; j++) {
ax[j] = GGML_F16_VEC_LOAD(x + i + j*GGML_F16_EPR, j);
ay[j] = GGML_F16_VEC_LOAD(y + i + j*GGML_F16_EPR, j);
sum[j] = GGML_F16_VEC_FMA(sum[j], ax[j], ay[j]);
}
}
// reduce sum0..sum3 to sum0
GGML_F16_VEC_REDUCE(sumf, sum);
// leftovers
for (int i = np; i < n; ++i) {
sumf += (ggml_float)(GGML_FP16_TO_FP32(x[i])*GGML_FP16_TO_FP32(y[i]));
}
#else
for (int i = 0; i < n; ++i) {
sumf += (ggml_float)(GGML_FP16_TO_FP32(x[i])*GGML_FP16_TO_FP32(y[i]));
}
#endif
*s = sumf;
}
void ggml_vec_silu_f32(const int n, float * y, const float * x) {
int i = 0;
#if defined(__AVX512F__) && defined(__AVX512DQ__)
for (; i + 15 < n; i += 16) {
_mm512_storeu_ps(y + i, ggml_v_silu(_mm512_loadu_ps(x + i)));
}
#elif defined(__AVX2__) && defined(__FMA__)
for (; i + 7 < n; i += 8) {
_mm256_storeu_ps(y + i, ggml_v_silu(_mm256_loadu_ps(x + i)));
}
#elif defined(__SSE2__)
for (; i + 3 < n; i += 4) {
_mm_storeu_ps(y + i, ggml_v_silu(_mm_loadu_ps(x + i)));
}
#elif defined(__ARM_NEON) && defined(__aarch64__)
for (; i + 3 < n; i += 4) {
vst1q_f32(y + i, ggml_v_silu(vld1q_f32(x + i)));
}
#endif
for (; i < n; ++i) {
y[i] = ggml_silu_f32(x[i]);
}
}
ggml_float ggml_vec_soft_max_f32(const int n, float * y, const float * x, float max) {
int i = 0;
ggml_float sum = 0;
#if defined(__AVX512F__) && defined(__AVX512DQ__)
for (; i + 15 < n; i += 16) {
__m512 val = ggml_v_expf(_mm512_sub_ps(_mm512_loadu_ps(x + i),
_mm512_set1_ps(max)));
_mm512_storeu_ps(y + i, val);
sum += (ggml_float)_mm512_reduce_add_ps(val);
}
#elif defined(__AVX2__) && defined(__FMA__)
for (; i + 7 < n; i += 8) {
__m256 val = ggml_v_expf(_mm256_sub_ps(_mm256_loadu_ps(x + i),
_mm256_set1_ps(max)));
_mm256_storeu_ps(y + i, val);
__m128 val2 = _mm_add_ps(_mm256_extractf128_ps(val, 1),
_mm256_castps256_ps128(val));
val2 = _mm_add_ps(val2, _mm_movehl_ps(val2, val2));
val2 = _mm_add_ss(val2, _mm_movehdup_ps(val2));
sum += (ggml_float)_mm_cvtss_f32(val2);
}
#elif defined(__SSE2__)
for (; i + 3 < n; i += 4) {
__m128 val = ggml_v_expf(_mm_sub_ps(_mm_loadu_ps(x + i),
_mm_set1_ps(max)));
_mm_storeu_ps(y + i, val);
#if defined(__AVX__) || defined(__AVX2__) || defined(__AVX512F__)
val = _mm_add_ps(val, _mm_movehl_ps(val, val));
val = _mm_add_ss(val, _mm_movehdup_ps(val));
#else
__m128 tmp = _mm_shuffle_ps(val, val, _MM_SHUFFLE(2, 3, 0, 1));
val = _mm_add_ps(val, tmp);
tmp = _mm_movehl_ps(tmp, val);
val = _mm_add_ss(val, tmp);
#endif
sum += (ggml_float)_mm_cvtss_f32(val);
}
#elif defined(__ARM_NEON) && defined(__aarch64__)
for (; i + 3 < n; i += 4) {
float32x4_t val = ggml_v_expf(vsubq_f32(vld1q_f32(x + i),
vdupq_n_f32(max)));
vst1q_f32(y + i, val);
sum += (ggml_float)vaddvq_f32(val);
}
#endif
for (; i < n; ++i) {
float val = expf(x[i] - max);
sum += (ggml_float)val;
y[i] = val;
}
return sum;
}
ggml_float ggml_vec_log_soft_max_f32(const int n, float * y, const float * x, float max) {
// log(soft_max) = log(soft_max_i / soft_max_sum) = log(soft_max_i) - log(soft_max_sum) = (logit_i - max) - log(soft_max_i)
int i = 0;
ggml_float sum = 0;
for (; i < n; ++i) {
float val = x[i] - max;
y[i] = val;
sum += (ggml_float)expf(val);
}
return sum = (ggml_float)logf(sum);
}

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// Vectorized functions for fundamental operations
#pragma once
#include "ggml-impl.h"
#include "simd-mappings.h"
#include "ggml.h"
#if defined(GGML_USE_ACCELERATE)
#include <Accelerate/Accelerate.h>
#endif
// floating point type used to accumulate sums
typedef double ggml_float;
#define GGML_GELU_FP16
#define GGML_GELU_QUICK_FP16
#define GGML_SOFT_MAX_UNROLL 4
#define GGML_VEC_DOT_UNROLL 2
#define GGML_VEC_MAD_UNROLL 32
#ifdef __cplusplus
extern "C" {
#endif
//
// global data
//
// precomputed gelu table for f16 (128 KB)
extern ggml_fp16_t ggml_table_gelu_f16[1 << 16];
// precomputed quick gelu table for f16 (128 KB)
extern ggml_fp16_t ggml_table_gelu_quick_f16[1 << 16];
//
// fundamental operations
//
void ggml_vec_dot_f32(int n, float * GGML_RESTRICT s, size_t bs, const float * GGML_RESTRICT x, size_t bx, const float * GGML_RESTRICT y, size_t by, int nrc);
void ggml_vec_dot_bf16(int n, float * GGML_RESTRICT s, size_t bs, ggml_bf16_t * GGML_RESTRICT x, size_t bx, ggml_bf16_t * GGML_RESTRICT y, size_t by, int nrc);
void ggml_vec_dot_f16(int n, float * GGML_RESTRICT s, size_t bs, ggml_fp16_t * GGML_RESTRICT x, size_t bx, ggml_fp16_t * GGML_RESTRICT y, size_t by, int nrc);
void ggml_vec_silu_f32(const int n, float * y, const float * x);
ggml_float ggml_vec_soft_max_f32(const int n, float * y, const float * x, float max);
ggml_float ggml_vec_log_soft_max_f32(const int n, float * y, const float * x, float max);
inline static void ggml_vec_set_i8(const int n, int8_t * x, const int8_t v) { for (int i = 0; i < n; ++i) x[i] = v; }
inline static void ggml_vec_set_i16(const int n, int16_t * x, const int16_t v) { for (int i = 0; i < n; ++i) x[i] = v; }
inline static void ggml_vec_set_i32(const int n, int32_t * x, const int32_t v) { for (int i = 0; i < n; ++i) x[i] = v; }
inline static void ggml_vec_cpy_i32(const int n, int32_t * y, const int32_t * x) { for (int i = 0; i < n; ++i) y[i] = x[i]; }
inline static void ggml_vec_set_f16(const int n, ggml_fp16_t * x, const ggml_fp16_t v) { for (int i = 0; i < n; ++i) x[i] = v; }
inline static void ggml_vec_set_bf16(const int n, ggml_bf16_t * x, const ggml_bf16_t v) { for (int i = 0; i < n; ++i) x[i] = v; }
inline static void ggml_vec_add_f32 (const int n, float * z, const float * x, const float * y) { for (int i = 0; i < n; ++i) z[i] = x[i] + y[i]; }
inline static void ggml_vec_add_f16 (const int n, ggml_fp16_t * z, const ggml_fp16_t * x, const ggml_fp16_t * y) {
for (int i = 0; i < n; ++i) {
z[i] = GGML_FP32_TO_FP16(GGML_FP16_TO_FP32(x[i]) + GGML_FP16_TO_FP32(y[i]));
}
}
inline static void ggml_vec_add1_f32(const int n, float * z, const float * x, const float v) { for (int i = 0; i < n; ++i) z[i] = x[i] + v; }
inline static void ggml_vec_acc_f32 (const int n, float * y, const float * x) { for (int i = 0; i < n; ++i) y[i] += x[i]; }
inline static void ggml_vec_acc1_f32(const int n, float * y, const float v) { for (int i = 0; i < n; ++i) y[i] += v; }
inline static void ggml_vec_sub_f32 (const int n, float * z, const float * x, const float * y) { for (int i = 0; i < n; ++i) z[i] = x[i] - y[i]; }
inline static void ggml_vec_sub_f16 (const int n, ggml_fp16_t * z, const ggml_fp16_t * x, const ggml_fp16_t * y) {
for (int i = 0; i < n; ++i) {
z[i] = GGML_FP32_TO_FP16(GGML_FP16_TO_FP32(x[i]) - GGML_FP16_TO_FP32(y[i]));
}
}
inline static void ggml_vec_set_f32 (const int n, float * x, const float v) { for (int i = 0; i < n; ++i) x[i] = v; }
inline static void ggml_vec_cpy_f32 (const int n, float * y, const float * x) { for (int i = 0; i < n; ++i) y[i] = x[i]; }
inline static void ggml_vec_neg_f32 (const int n, float * y, const float * x) { for (int i = 0; i < n; ++i) y[i] = -x[i]; }
inline static void ggml_vec_neg_f16 (const int n, ggml_fp16_t * y, const ggml_fp16_t * x) {
for (int i = 0; i < n; ++i) {
y[i] = GGML_FP32_TO_FP16(-GGML_FP16_TO_FP32(x[i]));
}
}
inline static void ggml_vec_mul_f32 (const int n, float * z, const float * x, const float * y) { for (int i = 0; i < n; ++i) z[i] = x[i]*y[i]; }
inline static void ggml_vec_mul_f16 (const int n, ggml_fp16_t * z, const ggml_fp16_t * x, const ggml_fp16_t * y) {
for (int i = 0; i < n; ++i) {
z[i] = GGML_FP32_TO_FP16(GGML_FP16_TO_FP32(x[i]) * GGML_FP16_TO_FP32(y[i]));
}
}
inline static void ggml_vec_div_f32 (const int n, float * z, const float * x, const float * y) { for (int i = 0; i < n; ++i) z[i] = x[i]/y[i]; }
inline static void ggml_vec_div_f16 (const int n, ggml_fp16_t * z, const ggml_fp16_t * x, const ggml_fp16_t * y) {
for (int i = 0; i < n; ++i) {
z[i] = GGML_FP32_TO_FP16(GGML_FP16_TO_FP32(x[i]) / GGML_FP16_TO_FP32(y[i]));
}
}
// compute GGML_VEC_DOT_UNROLL dot products at once
// xs - x row stride in bytes
inline static void ggml_vec_dot_f16_unroll(const int n, const int xs, float * GGML_RESTRICT s, void * GGML_RESTRICT xv, ggml_fp16_t * GGML_RESTRICT y) {
ggml_float sumf[GGML_VEC_DOT_UNROLL] = { 0.0 };
ggml_fp16_t * GGML_RESTRICT x[GGML_VEC_DOT_UNROLL];
for (int i = 0; i < GGML_VEC_DOT_UNROLL; ++i) {
x[i] = (ggml_fp16_t *) ((char *) xv + i*xs);
}
#if defined(GGML_SIMD)
const int np = (n & ~(GGML_F16_STEP - 1));
GGML_F16_VEC sum[GGML_VEC_DOT_UNROLL][GGML_F16_ARR] = { { GGML_F16_VEC_ZERO } };
GGML_F16_VEC ax[GGML_F16_ARR];
GGML_F16_VEC ay[GGML_F16_ARR];
for (int i = 0; i < np; i += GGML_F16_STEP) {
for (int j = 0; j < GGML_F16_ARR; j++) {
ay[j] = GGML_F16_VEC_LOAD(y + i + j*GGML_F16_EPR, j);
for (int k = 0; k < GGML_VEC_DOT_UNROLL; ++k) {
ax[j] = GGML_F16_VEC_LOAD(x[k] + i + j*GGML_F16_EPR, j);
sum[k][j] = GGML_F16_VEC_FMA(sum[k][j], ax[j], ay[j]);
}
}
}
// reduce sum0..sum3 to sum0
for (int k = 0; k < GGML_VEC_DOT_UNROLL; ++k) {
GGML_F16_VEC_REDUCE(sumf[k], sum[k]);
}
// leftovers
for (int i = np; i < n; ++i) {
for (int j = 0; j < GGML_VEC_DOT_UNROLL; ++j) {
sumf[j] += (ggml_float)(GGML_FP16_TO_FP32(x[j][i])*GGML_FP16_TO_FP32(y[i]));
}
}
#else
for (int i = 0; i < n; ++i) {
for (int j = 0; j < GGML_VEC_DOT_UNROLL; ++j) {
sumf[j] += (ggml_float)(GGML_FP16_TO_FP32(x[j][i])*GGML_FP16_TO_FP32(y[i]));
}
}
#endif
for (int i = 0; i < GGML_VEC_DOT_UNROLL; ++i) {
s[i] = (float)sumf[i];
}
}
inline static void ggml_vec_mad_f32(const int n, float * GGML_RESTRICT y, const float * GGML_RESTRICT x, const float v) {
#if defined(GGML_SIMD)
const int np = (n & ~(GGML_F32_STEP - 1));
GGML_F32_VEC vx = GGML_F32_VEC_SET1(v);
GGML_F32_VEC ax[GGML_F32_ARR];
GGML_F32_VEC ay[GGML_F32_ARR];
for (int i = 0; i < np; i += GGML_F32_STEP) {
for (int j = 0; j < GGML_F32_ARR; j++) {
ax[j] = GGML_F32_VEC_LOAD(x + i + j*GGML_F32_EPR);
ay[j] = GGML_F32_VEC_LOAD(y + i + j*GGML_F32_EPR);
ay[j] = GGML_F32_VEC_FMA(ay[j], ax[j], vx);
GGML_F32_VEC_STORE(y + i + j*GGML_F32_EPR, ay[j]);
}
}
// leftovers
for (int i = np; i < n; ++i) {
y[i] += x[i]*v;
}
#else
// scalar
for (int i = 0; i < n; ++i) {
y[i] += x[i]*v;
}
#endif
}
inline static void ggml_vec_mad_f16(const int n, ggml_fp16_t * GGML_RESTRICT y, const ggml_fp16_t * GGML_RESTRICT x, const float v) {
#if defined(GGML_SIMD)
const int np = (n & ~(GGML_F16_STEP - 1));
GGML_F16_VEC vx = GGML_F16_VEC_SET1(v);
GGML_F16_VEC ax[GGML_F16_ARR];
GGML_F16_VEC ay[GGML_F16_ARR];
for (int i = 0; i < np; i += GGML_F16_STEP) {
for (int j = 0; j < GGML_F16_ARR; j++) {
ax[j] = GGML_F16_VEC_LOAD(x + i + j*GGML_F16_EPR, j);
ay[j] = GGML_F16_VEC_LOAD(y + i + j*GGML_F16_EPR, j);
ay[j] = GGML_F16_VEC_FMA(ay[j], ax[j], vx);
GGML_F16_VEC_STORE(y + i + j*GGML_F16_EPR, ay, j);
}
}
// leftovers
for (int i = np; i < n; ++i) {
y[i] = GGML_FP32_TO_FP16(GGML_FP16_TO_FP32(y[i]) + GGML_FP16_TO_FP32(x[i])*v);
}
#else
// scalar
for (int i = 0; i < n; ++i) {
y[i] = GGML_FP32_TO_FP16(GGML_FP16_TO_FP32(y[i]) + GGML_FP16_TO_FP32(x[i])*v);
}
#endif
}
// xs and vs are byte strides of x and v
inline static void ggml_vec_mad_f32_unroll(const int n, const int xs, const int vs, float * GGML_RESTRICT y, const float * GGML_RESTRICT xv, const float * GGML_RESTRICT vv) {
const float * GGML_RESTRICT x[GGML_VEC_MAD_UNROLL];
const float * GGML_RESTRICT v[GGML_VEC_MAD_UNROLL];
for (int i = 0; i < GGML_VEC_MAD_UNROLL; ++i) {
x[i] = (const float *) ((const char *) xv + i*xs);
v[i] = (const float *) ((const char *) vv + i*vs);
}
#if defined(GGML_SIMD)
const int np = (n & ~(GGML_F32_STEP - 1));
GGML_F32_VEC vx[GGML_VEC_MAD_UNROLL];
for (int k = 0; k < GGML_VEC_MAD_UNROLL; ++k) {
vx[k] = GGML_F32_VEC_SET1(v[k][0]);
}
GGML_F32_VEC ax[GGML_VEC_MAD_UNROLL][GGML_F32_ARR];
GGML_F32_VEC ay[GGML_F32_ARR];
for (int i = 0; i < np; i += GGML_F32_STEP) {
for (int j = 0; j < GGML_F32_ARR; j++) {
ay[j] = GGML_F32_VEC_LOAD(y + i + j*GGML_F32_EPR);
for (int k = 0; k < GGML_VEC_MAD_UNROLL; ++k) {
ax[k][j] = GGML_F32_VEC_LOAD(x[k] + i + j*GGML_F32_EPR);
ay[j] = GGML_F32_VEC_FMA(ay[j], ax[k][j], vx[k]);
}
GGML_F32_VEC_STORE(y + i + j*GGML_F32_EPR, ay[j]);
}
}
// leftovers
for (int k = 0; k < GGML_VEC_MAD_UNROLL; ++k) {
for (int i = np; i < n; ++i) {
y[i] += x[k][i]*v[k][0];
}
}
#else
// scalar
for (int k = 0; k < GGML_VEC_MAD_UNROLL; ++k) {
for (int i = 0; i < n; ++i) {
y[i] += x[k][i]*v[k][0];
}
}
#endif
}
//inline static void ggml_vec_scale_f32(const int n, float * y, const float v) { for (int i = 0; i < n; ++i) y[i] *= v; }
inline static void ggml_vec_scale_f32(const int n, float * y, const float v) {
#if defined(GGML_USE_ACCELERATE)
vDSP_vsmul(y, 1, &v, y, 1, n);
#elif defined(GGML_SIMD)
const int np = (n & ~(GGML_F32_STEP - 1));
GGML_F32_VEC vx = GGML_F32_VEC_SET1(v);
GGML_F32_VEC ay[GGML_F32_ARR];
for (int i = 0; i < np; i += GGML_F32_STEP) {
for (int j = 0; j < GGML_F32_ARR; j++) {
ay[j] = GGML_F32_VEC_LOAD(y + i + j*GGML_F32_EPR);
ay[j] = GGML_F32_VEC_MUL(ay[j], vx);
GGML_F32_VEC_STORE(y + i + j*GGML_F32_EPR, ay[j]);
}
}
// leftovers
for (int i = np; i < n; ++i) {
y[i] *= v;
}
#else
// scalar
for (int i = 0; i < n; ++i) {
y[i] *= v;
}
#endif
}
inline static void ggml_vec_scale_f16(const int n, ggml_fp16_t * y, const float v) {
#if defined(GGML_SIMD)
const int np = (n & ~(GGML_F16_STEP - 1));
GGML_F16_VEC vx = GGML_F16_VEC_SET1(v);
GGML_F16_VEC ay[GGML_F16_ARR];
for (int i = 0; i < np; i += GGML_F16_STEP) {
for (int j = 0; j < GGML_F16_ARR; j++) {
ay[j] = GGML_F16_VEC_LOAD(y + i + j*GGML_F16_EPR, j);
ay[j] = GGML_F16_VEC_MUL(ay[j], vx);
GGML_F16_VEC_STORE(y + i + j*GGML_F16_EPR, ay, j);
}
}
// leftovers
for (int i = np; i < n; ++i) {
y[i] = GGML_FP32_TO_FP16(GGML_FP16_TO_FP32(y[i])*v);
}
#else
// scalar
for (int i = 0; i < n; ++i) {
y[i] = GGML_FP32_TO_FP16(GGML_FP16_TO_FP32(y[i])*v);
}
#endif
}
inline static void ggml_vec_norm_f32 (const int n, float * s, const float * x) { ggml_vec_dot_f32(n, s, 0, x, 0, x, 0, 1); *s = sqrtf(*s); }
inline static void ggml_vec_sqr_f32 (const int n, float * y, const float * x) { for (int i = 0; i < n; ++i) y[i] = x[i]*x[i]; }
inline static void ggml_vec_sqr_f16 (const int n, ggml_fp16_t * y, const ggml_fp16_t * x) {
for (int i = 0; i < n; ++i) {
float v = GGML_FP16_TO_FP32(x[i]);
y[i] = GGML_FP32_TO_FP16(v*v);
}
}
inline static void ggml_vec_sqrt_f32 (const int n, float * y, const float * x) { for (int i = 0; i < n; ++i) y[i] = sqrtf(x[i]); }
inline static void ggml_vec_sqrt_f16 (const int n, ggml_fp16_t * y, const ggml_fp16_t * x) {
for (int i = 0; i < n; ++i) {
y[i] = GGML_FP32_TO_FP16(sqrtf(GGML_FP16_TO_FP32(x[i])));
}
}
inline static void ggml_vec_log_f32 (const int n, float * y, const float * x) { for (int i = 0; i < n; ++i) y[i] = logf(x[i]); }
inline static void ggml_vec_log_f16 (const int n, ggml_fp16_t * y, const ggml_fp16_t * x) {
for (int i = 0; i < n; ++i) {
y[i] = GGML_FP32_TO_FP16(logf(GGML_FP16_TO_FP32(x[i])));
}
}
inline static void ggml_vec_sin_f32 (const int n, float * y, const float * x) { for (int i = 0; i < n; ++i) y[i] = sinf(x[i]); }
inline static void ggml_vec_sin_f16 (const int n, ggml_fp16_t * y, const ggml_fp16_t * x) {
for (int i = 0; i < n; ++i) {
y[i] = GGML_FP32_TO_FP16(sinf(GGML_FP16_TO_FP32(x[i])));
}
}
inline static void ggml_vec_cos_f32 (const int n, float * y, const float * x) { for (int i = 0; i < n; ++i) y[i] = cosf(x[i]); }
inline static void ggml_vec_cos_f16 (const int n, ggml_fp16_t * y, const ggml_fp16_t * x) {
for (int i = 0; i < n; ++i) {
y[i] = GGML_FP32_TO_FP16(cosf(GGML_FP16_TO_FP32(x[i])));
}
}
inline static void ggml_vec_abs_f32 (const int n, float * y, const float * x) { for (int i = 0; i < n; ++i) y[i] = fabsf(x[i]); }
inline static void ggml_vec_abs_f16 (const int n, ggml_fp16_t * y, const ggml_fp16_t * x) {
for (int i = 0; i < n; ++i) {
y[i] = GGML_FP32_TO_FP16(fabsf(GGML_FP16_TO_FP32(x[i])));
}
}
inline static void ggml_vec_sgn_f32 (const int n, float * y, const float * x) { for (int i = 0; i < n; ++i) y[i] = (x[i] > 0.f) ? 1.f : ((x[i] < 0.f) ? -1.f : 0.f); }
inline static void ggml_vec_sgn_f16 (const int n, ggml_fp16_t * y, const ggml_fp16_t * x) {
for (int i = 0; i < n; ++i) {
float v = GGML_FP16_TO_FP32(x[i]);
y[i] = GGML_FP32_TO_FP16((v > 0.f) ? 1.f : ((v < 0.f) ? -1.f : 0.f));
}
}
inline static void ggml_vec_step_f32 (const int n, float * y, const float * x) { for (int i = 0; i < n; ++i) y[i] = (x[i] > 0.f) ? 1.f : 0.f; }
inline static void ggml_vec_step_f16 (const int n, ggml_fp16_t * y, const ggml_fp16_t * x) {
for (int i = 0; i < n; ++i) {
y[i] = GGML_FP32_TO_FP16((GGML_FP16_TO_FP32(x[i]) > 0.f) ? 1.f : 0.f);
}
}
inline static void ggml_vec_tanh_f32 (const int n, float * y, const float * x) { for (int i = 0; i < n; ++i) y[i] = tanhf(x[i]); }
inline static void ggml_vec_tanh_f16 (const int n, ggml_fp16_t * y, const ggml_fp16_t * x) {
for (int i = 0; i < n; ++i) {
y[i] = GGML_FP32_TO_FP16(tanhf(GGML_FP16_TO_FP32(x[i])));
}
}
inline static void ggml_vec_elu_f32 (const int n, float * y, const float * x) { for (int i = 0; i < n; ++i) y[i] = (x[i] > 0.f) ? x[i] : expm1f(x[i]); }
inline static void ggml_vec_elu_f16 (const int n, ggml_fp16_t * y, const ggml_fp16_t * x) {
for (int i = 0; i < n; ++i) {
y[i] = GGML_FP32_TO_FP16(expm1f(GGML_FP16_TO_FP32(x[i])));
}
}
inline static void ggml_vec_relu_f32 (const int n, float * y, const float * x) { for (int i = 0; i < n; ++i) y[i] = (x[i] > 0.f) ? x[i] : 0.f; }
inline static void ggml_vec_relu_f16 (const int n, ggml_fp16_t * y, const ggml_fp16_t * x) {
for (int i = 0; i < n; ++i) {
float v = GGML_FP16_TO_FP32(x[i]);
y[i] = GGML_FP32_TO_FP16((v > 0.f) ? v : 0.f);
}
}
inline static void ggml_vec_leaky_relu_f32 (const int n, float * y, const float * x, const float ns) { for (int i = 0; i < n; ++i) y[i] = ((x[i] > 0.f) ? x[i] : 0.f) + ns * ((x[i] < 0.0f) ? x[i] : 0.f); }
inline static void ggml_vec_leaky_relu_f16 (const int n, ggml_fp16_t * y, const ggml_fp16_t * x, const float ns) {
for (int i = 0; i < n; ++i) {
float v = GGML_FP16_TO_FP32(x[i]);
y[i] = GGML_FP32_TO_FP16(((v > 0.f) ? v : 0.f) + ns * ((v < 0.0f) ? v : 0.f));
}
}
inline static void ggml_vec_sigmoid_f32 (const int n, float * y, const float * x) { for (int i = 0; i < n; ++i) y[i] = 1.f / (1.f + expf(-x[i])); }
inline static void ggml_vec_sigmoid_f16 (const int n, ggml_fp16_t * y, const ggml_fp16_t * x) {
for (int i = 0; i < n; ++i) {
y[i] = GGML_FP32_TO_FP16(1.f / (1.f + expf(-GGML_FP16_TO_FP32(x[i]))));
}
}
// TODO: optimize performance
inline static void ggml_vec_hardswish_f32 (const int n, float * y, const float * x) { for (int i = 0; i < n; ++i) y[i] = x[i] * fminf(1.0f, fmaxf(0.0f, (x[i] + 3.0f) / 6.0f)); }
inline static void ggml_vec_hardswish_f16 (const int n, ggml_fp16_t * y, const ggml_fp16_t * x) {
for (int i = 0; i < n; ++i) {
float v = GGML_FP16_TO_FP32(x[i]);
y[i] = GGML_FP32_TO_FP16(v * fminf(1.0f, fmaxf(0.0f, (v + 3.0f) / 6.0f)));
}
}
inline static void ggml_vec_hardsigmoid_f32 (const int n, float * y, const float * x) { for (int i = 0; i < n; ++i) y[i] = fminf(1.0f, fmaxf(0.0f, (x[i] + 3.0f) / 6.0f)); }
inline static void ggml_vec_hardsigmoid_f16 (const int n, ggml_fp16_t * y, const ggml_fp16_t * x) {
for (int i = 0; i < n; ++i) {
y[i] = GGML_FP32_TO_FP16(fminf(1.0f, fmaxf(0.0f, (GGML_FP16_TO_FP32(x[i]) + 3.0f) / 6.0f)));
}
}
inline static void ggml_vec_exp_f32 (const int n, float * y, const float * x) { for (int i = 0; i < n; ++i) y[i] = expf(x[i]); }
inline static void ggml_vec_exp_f16 (const int n, ggml_fp16_t * y, const ggml_fp16_t * x) {
for (int i = 0; i < n; ++i) {
y[i] = GGML_FP32_TO_FP16(expf(GGML_FP16_TO_FP32(x[i])));
}
}
static const float GELU_COEF_A = 0.044715f;
static const float GELU_QUICK_COEF = -1.702f;
static const float SQRT_2_OVER_PI = 0.79788456080286535587989211986876f;
inline static float ggml_gelu_f32(float x) {
return 0.5f*x*(1.0f + tanhf(SQRT_2_OVER_PI*x*(1.0f + GELU_COEF_A*x*x)));
}
inline static void ggml_vec_gelu_f16(const int n, ggml_fp16_t * y, const ggml_fp16_t * x) {
const uint16_t * i16 = (const uint16_t *) x;
for (int i = 0; i < n; ++i) {
y[i] = ggml_table_gelu_f16[i16[i]];
}
}
#ifdef GGML_GELU_FP16
inline static void ggml_vec_gelu_f32(const int n, float * y, const float * x) {
uint16_t t;
for (int i = 0; i < n; ++i) {
if (x[i] <= -10.0f) {
y[i] = 0.0f;
} else if (x[i] >= 10.0f) {
y[i] = x[i];
} else {
ggml_fp16_t fp16 = GGML_FP32_TO_FP16(x[i]);
memcpy(&t, &fp16, sizeof(uint16_t));
y[i] = GGML_FP16_TO_FP32(ggml_table_gelu_f16[t]);
}
}
}
#else
inline static void ggml_vec_gelu_f32(const int n, float * y, const float * x) {
for (int i = 0; i < n; ++i) {
y[i] = ggml_gelu_f32(x[i]);
}
}
#endif
inline static float ggml_gelu_quick_f32(float x) {
return x*(1.0f/(1.0f+expf(GELU_QUICK_COEF*x)));
}
//inline static void ggml_vec_gelu_quick_f16(const int n, ggml_fp16_t * y, const ggml_fp16_t * x) {
// const uint16_t * i16 = (const uint16_t *) x;
// for (int i = 0; i < n; ++i) {
// y[i] = ggml_table_gelu_quick_f16[i16[i]];
// }
//}
#ifdef GGML_GELU_QUICK_FP16
inline static void ggml_vec_gelu_quick_f32(const int n, float * y, const float * x) {
uint16_t t;
for (int i = 0; i < n; ++i) {
ggml_fp16_t fp16 = GGML_FP32_TO_FP16(x[i]);
memcpy(&t, &fp16, sizeof(uint16_t));
y[i] = GGML_FP16_TO_FP32(ggml_table_gelu_quick_f16[t]);
}
}
#else
inline static void ggml_vec_gelu_quick_f32(const int n, float * y, const float * x) {
for (int i = 0; i < n; ++i) {
y[i] = ggml_gelu_quick_f32(x[i]);
}
}
#endif
inline static void ggml_vec_gelu_quick_f16(const int n, ggml_fp16_t * y, const ggml_fp16_t * x) {
for (int i = 0; i < n; ++i) {
float v = GGML_FP16_TO_FP32(x[i]);
y[i] = GGML_FP32_TO_FP16(v*(1.0f/(1.0f+expf(GELU_QUICK_COEF*v))));
}
}
// Sigmoid Linear Unit (SiLU) function
inline static float ggml_silu_f32(float x) {
return x/(1.0f + expf(-x));
}
inline static ggml_fp16_t ggml_silu_f16(ggml_fp16_t x) {
float v = GGML_FP16_TO_FP32(x);
return GGML_FP32_TO_FP16(v/(1.0f + expf(-v)));
}
#if __FINITE_MATH_ONLY__
#error "some routines in ggml.c require non-finite math arithmetics -- pass -fno-finite-math-only to the compiler to fix"
#error "ref: https://github.com/ggml-org/llama.cpp/pull/7154#issuecomment-2143844461"
#endif
#if defined(__ARM_NEON) && defined(__aarch64__)
// adapted from arm limited optimized routine
// the maximum error is 1.45358 plus 0.5 ulps
// numbers above 88.38 will flush to infinity
// numbers beneath -103.97 will flush to zero
inline static float32x4_t ggml_v_expf(float32x4_t x) {
const float32x4_t r = vdupq_n_f32(0x1.8p23f);
const float32x4_t z = vfmaq_f32(r, x, vdupq_n_f32(0x1.715476p+0f));
const float32x4_t n = vsubq_f32(z, r);
const float32x4_t b = vfmsq_f32(vfmsq_f32(x, n, vdupq_n_f32(0x1.62e4p-1f)), n,
vdupq_n_f32(0x1.7f7d1cp-20f));
const uint32x4_t e = vshlq_n_u32(vreinterpretq_u32_f32(z), 23);
const float32x4_t k = vreinterpretq_f32_u32(vaddq_u32(e, vreinterpretq_u32_f32(vdupq_n_f32(1))));
const uint32x4_t c = vcagtq_f32(n, vdupq_n_f32(126));
const float32x4_t u = vmulq_f32(b, b);
const float32x4_t j = vfmaq_f32(
vmulq_f32(vdupq_n_f32(0x1.ffffecp-1f), b),
vfmaq_f32(vfmaq_f32(vdupq_n_f32(0x1.fffdb6p-2f), vdupq_n_f32(0x1.555e66p-3f), b),
vfmaq_f32(vdupq_n_f32(0x1.573e2ep-5f), vdupq_n_f32(0x1.0e4020p-7f), b), u), u);
if (!vpaddd_u64(vreinterpretq_u64_u32(c)))
return vfmaq_f32(k, j, k);
const uint32x4_t d = vandq_u32(vclezq_f32(n), vdupq_n_u32(0x82000000));
const float32x4_t s1 = vreinterpretq_f32_u32(vaddq_u32(d, vdupq_n_u32(0x7f000000)));
const float32x4_t s2 = vreinterpretq_f32_u32(vsubq_u32(e, d));
return vbslq_f32(vcagtq_f32(n, vdupq_n_f32(192)), vmulq_f32(s1, s1),
vbslq_f32(c, vmulq_f32(vfmaq_f32(s2, s2, j), s1), vfmaq_f32(k, k, j)));
}
// computes silu x/(1+exp(-x)) in single precision vector
inline static float32x4_t ggml_v_silu(float32x4_t x) {
const float32x4_t one = vdupq_n_f32(1.0f);
const float32x4_t zero = vdupq_n_f32(0.0f);
const float32x4_t neg_x = vsubq_f32(zero, x);
const float32x4_t exp_neg_x = ggml_v_expf(neg_x);
const float32x4_t one_plus_exp_neg_x = vaddq_f32(one, exp_neg_x);
return vdivq_f32(x, one_plus_exp_neg_x);
}
#elif defined(__AVX512F__) && defined(__AVX512DQ__)
// adapted from arm limited optimized routine
// the maximum error is 1.45358 plus 0.5 ulps
// numbers above 88.38 will flush to infinity
// numbers beneath -103.97 will flush to zero
inline static __m512 ggml_v_expf(__m512 x) {
const __m512 r = _mm512_set1_ps(0x1.8p23f);
const __m512 z = _mm512_fmadd_ps(x, _mm512_set1_ps(0x1.715476p+0f), r);
const __m512 n = _mm512_sub_ps(z, r);
const __m512 b =
_mm512_fnmadd_ps(n, _mm512_set1_ps(0x1.7f7d1cp-20f),
_mm512_fnmadd_ps(n, _mm512_set1_ps(0x1.62e4p-1f), x));
const __mmask16 d =
_mm512_cmp_ps_mask(_mm512_abs_ps(n), _mm512_set1_ps(192), _CMP_GT_OQ);
const __m512 u = _mm512_mul_ps(b, b);
const __m512 j = _mm512_fmadd_ps(
_mm512_fmadd_ps(_mm512_fmadd_ps(_mm512_set1_ps(0x1.0e4020p-7f), b,
_mm512_set1_ps(0x1.573e2ep-5f)),
u,
_mm512_fmadd_ps(_mm512_set1_ps(0x1.555e66p-3f), b,
_mm512_set1_ps(0x1.fffdb6p-2f))),
u,
_mm512_fmadd_ps(_mm512_set1_ps(0x1.ffffecp-1f), b, _mm512_set1_ps(1.0F)));
const __m512 res = _mm512_scalef_ps(j, n);
if (_mm512_kortestz(d, d))
return res;
const __m512 zero = _mm512_setzero_ps();
const __m512 alt = _mm512_mask_blend_ps(
_mm512_cmp_ps_mask(n, zero, _CMP_LE_OQ), _mm512_set1_ps(INFINITY), zero);
return _mm512_mask_blend_ps(d, res, alt);
}
// computes silu x/(1+exp(-x)) in single precision vector
inline static __m512 ggml_v_silu(__m512 x) {
const __m512 one = _mm512_set1_ps(1);
const __m512 zero = _mm512_setzero_ps();
const __m512 neg_x = _mm512_sub_ps(zero, x);
const __m512 exp_neg_x = ggml_v_expf(neg_x);
const __m512 one_plus_exp_neg_x = _mm512_add_ps(one, exp_neg_x);
return _mm512_div_ps(x, one_plus_exp_neg_x);
}
#elif defined(__AVX2__) && defined(__FMA__)
// adapted from arm limited optimized routine
// the maximum error is 1.45358 plus 0.5 ulps
// numbers above 88.38 will flush to infinity
// numbers beneath -103.97 will flush to zero
inline static __m256 ggml_v_expf(__m256 x) {
const __m256 r = _mm256_set1_ps(0x1.8p23f);
const __m256 z = _mm256_fmadd_ps(x, _mm256_set1_ps(0x1.715476p+0f), r);
const __m256 n = _mm256_sub_ps(z, r);
const __m256 b = _mm256_fnmadd_ps(n, _mm256_set1_ps(0x1.7f7d1cp-20f),
_mm256_fnmadd_ps(n, _mm256_set1_ps(0x1.62e4p-1f), x));
const __m256i e = _mm256_slli_epi32(_mm256_castps_si256(z), 23);
const __m256 k = _mm256_castsi256_ps(
_mm256_add_epi32(e, _mm256_castps_si256(_mm256_set1_ps(1))));
const __m256i c = _mm256_castps_si256(
_mm256_cmp_ps(_mm256_andnot_ps(_mm256_set1_ps(-0.f), n),
_mm256_set1_ps(126), _CMP_GT_OQ));
const __m256 u = _mm256_mul_ps(b, b);
const __m256 j = _mm256_fmadd_ps(_mm256_fmadd_ps(_mm256_fmadd_ps(_mm256_set1_ps(0x1.0e4020p-7f), b,
_mm256_set1_ps(0x1.573e2ep-5f)), u,
_mm256_fmadd_ps(_mm256_set1_ps(0x1.555e66p-3f), b,
_mm256_set1_ps(0x1.fffdb6p-2f))),
u, _mm256_mul_ps(_mm256_set1_ps(0x1.ffffecp-1f), b));
if (!_mm256_movemask_ps(_mm256_castsi256_ps(c)))
return _mm256_fmadd_ps(j, k, k);
const __m256i g = _mm256_and_si256(
_mm256_castps_si256(_mm256_cmp_ps(n, _mm256_setzero_ps(), _CMP_LE_OQ)),
_mm256_set1_epi32(0x82000000u));
const __m256 s1 =
_mm256_castsi256_ps(_mm256_add_epi32(g, _mm256_set1_epi32(0x7f000000u)));
const __m256 s2 = _mm256_castsi256_ps(_mm256_sub_epi32(e, g));
const __m256i d = _mm256_castps_si256(
_mm256_cmp_ps(_mm256_andnot_ps(_mm256_set1_ps(-0.f), n),
_mm256_set1_ps(192), _CMP_GT_OQ));
return _mm256_or_ps(
_mm256_and_ps(_mm256_castsi256_ps(d), _mm256_mul_ps(s1, s1)),
_mm256_andnot_ps(
_mm256_castsi256_ps(d),
_mm256_or_ps(
_mm256_and_ps(_mm256_castsi256_ps(c),
_mm256_mul_ps(_mm256_fmadd_ps(s2, j, s2), s1)),
_mm256_andnot_ps(_mm256_castsi256_ps(c), _mm256_fmadd_ps(k, j, k)))));
}
// computes silu x/(1+exp(-x)) in single precision vector
inline static __m256 ggml_v_silu(__m256 x) {
const __m256 one = _mm256_set1_ps(1);
const __m256 zero = _mm256_setzero_ps();
const __m256 neg_x = _mm256_sub_ps(zero, x);
const __m256 exp_neg_x = ggml_v_expf(neg_x);
const __m256 one_plus_exp_neg_x = _mm256_add_ps(one, exp_neg_x);
return _mm256_div_ps(x, one_plus_exp_neg_x);
}
#elif defined(__SSE2__) // __AVX2__ / __ARM_NEON
#if defined(__FMA__)
#define MADD128(x, y, z) _mm_fmadd_ps(x, y, z)
#define NMADD128(x, y, z) _mm_fnmadd_ps(x, y, z)
#else
#define MADD128(x, y, z) _mm_add_ps(_mm_mul_ps(x, y), z)
#define NMADD128(x, y, z) _mm_sub_ps(z, _mm_mul_ps(x, y))
#endif
// adapted from arm limited optimized routine
// the maximum error is 1.45358 plus 0.5 ulps
// numbers above 88.38 will flush to infinity
// numbers beneath -103.97 will flush to zero
inline static __m128 ggml_v_expf(__m128 x) {
const __m128 r = _mm_set1_ps(0x1.8p23f);
const __m128 z = MADD128(x, _mm_set1_ps(0x1.715476p+0f), r);
const __m128 n = _mm_sub_ps(z, r);
const __m128 b =
NMADD128(n, _mm_set1_ps(0x1.7f7d1cp-20f), NMADD128(n, _mm_set1_ps(0x1.62e4p-1f), x));
const __m128i e = _mm_slli_epi32(_mm_castps_si128(z), 23);
const __m128 k = _mm_castsi128_ps(_mm_add_epi32(e, _mm_castps_si128(_mm_set1_ps(1))));
const __m128i c =
_mm_castps_si128(_mm_cmpgt_ps(_mm_andnot_ps(_mm_set1_ps(-0.f), n), _mm_set1_ps(126)));
const __m128 u = _mm_mul_ps(b, b);
const __m128 j =
MADD128(MADD128(MADD128(_mm_set1_ps(0x1.0e4020p-7f), b, _mm_set1_ps(0x1.573e2ep-5f)), u,
MADD128(_mm_set1_ps(0x1.555e66p-3f), b, _mm_set1_ps(0x1.fffdb6p-2f))),
u, _mm_mul_ps(_mm_set1_ps(0x1.ffffecp-1f), b));
if (!_mm_movemask_epi8(c))
return MADD128(j, k, k);
const __m128i g = _mm_and_si128(_mm_castps_si128(_mm_cmple_ps(n, _mm_setzero_ps())),
_mm_set1_epi32(0x82000000u));
const __m128 s1 = _mm_castsi128_ps(_mm_add_epi32(g, _mm_set1_epi32(0x7f000000u)));
const __m128 s2 = _mm_castsi128_ps(_mm_sub_epi32(e, g));
const __m128i d =
_mm_castps_si128(_mm_cmpgt_ps(_mm_andnot_ps(_mm_set1_ps(-0.f), n), _mm_set1_ps(192)));
return _mm_or_ps(
_mm_and_ps(_mm_castsi128_ps(d), _mm_mul_ps(s1, s1)),
_mm_andnot_ps(_mm_castsi128_ps(d),
_mm_or_ps(_mm_and_ps(_mm_castsi128_ps(c), _mm_mul_ps(MADD128(s2, j, s2), s1)),
_mm_andnot_ps(_mm_castsi128_ps(c), MADD128(k, j, k)))));
}
// computes silu x/(1+exp(-x)) in single precision vector
inline static __m128 ggml_v_silu(__m128 x) {
const __m128 one = _mm_set1_ps(1);
const __m128 zero = _mm_setzero_ps();
const __m128 neg_x = _mm_sub_ps(zero, x);
const __m128 exp_neg_x = ggml_v_expf(neg_x);
const __m128 one_plus_exp_neg_x = _mm_add_ps(one, exp_neg_x);
return _mm_div_ps(x, one_plus_exp_neg_x);
}
#endif // __ARM_NEON / __AVX2__ / __SSE2__
inline static void ggml_vec_silu_f16(const int n, ggml_fp16_t * y, const ggml_fp16_t * x) {
for (int i = 0; i < n; ++i) {
y[i] = ggml_silu_f16(x[i]);
}
}
inline static float ggml_silu_backward_f32(float x, float dy) {
const float s = 1.0f/(1.0f + expf(-x));
return dy*s*(1.0f + x*(1.0f - s));
}
inline static ggml_fp16_t ggml_silu_backward_f16(ggml_fp16_t x, ggml_fp16_t dy) {
const float v = GGML_FP16_TO_FP32(x);
const float s = 1.0f/(1.0f + expf(-v));
return GGML_FP32_TO_FP16(GGML_FP16_TO_FP32(dy)*s*(1.0f + v*(1.0f - s)));
}
inline static void ggml_vec_silu_backward_f32(const int n, float * dx, const float * x, const float * dy) {
for (int i = 0; i < n; ++i) {
dx[i] = ggml_silu_backward_f32(x[i], dy[i]);
}
}
inline static void ggml_vec_silu_backward_f16(const int n, ggml_fp16_t * dx, const ggml_fp16_t * x, const ggml_fp16_t * dy) {
for (int i = 0; i < n; ++i) {
dx[i] = ggml_silu_backward_f16(x[i], dy[i]);
}
}
inline static void ggml_vec_sum_f32(const int n, float * s, const float * x) {
#ifndef GGML_USE_ACCELERATE
ggml_float sum = 0.0;
for (int i = 0; i < n; ++i) {
sum += (ggml_float)x[i];
}
*s = (float)sum;
#else
vDSP_sve(x, 1, s, n);
#endif
}
inline static void ggml_vec_sum_f32_ggf(const int n, ggml_float * s, const float * x) {
ggml_float sum = 0.0;
for (int i = 0; i < n; ++i) {
sum += (ggml_float)x[i];
}
*s = sum;
}
inline static void ggml_vec_sum_f16_ggf(const int n, float * s, const ggml_fp16_t * x) {
float sum = 0.0f;
for (int i = 0; i < n; ++i) {
sum += GGML_FP16_TO_FP32(x[i]);
}
*s = sum;
}
inline static void ggml_vec_sum_bf16_ggf(const int n, float * s, const ggml_bf16_t * x) {
float sum = 0.0f;
for (int i = 0; i < n; ++i) {
sum += GGML_BF16_TO_FP32(x[i]);
}
*s = sum;
}
inline static void ggml_vec_max_f32(const int n, float * s, const float * x) {
#ifndef GGML_USE_ACCELERATE
float max = -INFINITY;
for (int i = 0; i < n; ++i) {
max = MAX(max, x[i]);
}
*s = max;
#else
vDSP_maxv(x, 1, s, n);
#endif
}
inline static void ggml_vec_norm_inv_f32(const int n, float * s, const float * x) {
ggml_vec_norm_f32(n, s, x);
*s = 1.f/(*s);
}
inline static void ggml_vec_argmax_f32(const int n, int * s, const float * x) {
float max = -INFINITY;
int idx = 0;
for (int i = 0; i < n; ++i) {
max = MAX(max, x[i]);
if (max == x[i]) { idx = i; }
}
*s = idx;
}
#ifdef __cplusplus
}
#endif

View File

@ -25,7 +25,6 @@ You can now use it like this:
`ggml` models are available from the following locations: `ggml` models are available from the following locations:
- https://huggingface.co/ggerganov/whisper.cpp/tree/main - https://huggingface.co/ggerganov/whisper.cpp/tree/main
- https://ggml.ggerganov.com
### 3. Convert with [convert-pt-to-ggml.py](convert-pt-to-ggml.py) ### 3. Convert with [convert-pt-to-ggml.py](convert-pt-to-ggml.py)
@ -78,7 +77,7 @@ OpenAI format. To read the HF models you can use the [convert-h5-to-ggml.py](con
```bash ```bash
git clone https://github.com/openai/whisper git clone https://github.com/openai/whisper
git clone https://github.com/ggerganov/whisper.cpp git clone https://github.com/ggml-org/whisper.cpp
# clone HF fine-tuned model (this is just an example) # clone HF fine-tuned model (this is just an example)
git clone https://huggingface.co/openai/whisper-medium git clone https://huggingface.co/openai/whisper-medium
@ -96,7 +95,7 @@ Currently, the chunk-based transcription strategy is not implemented, so there c
```bash ```bash
# clone OpenAI whisper and whisper.cpp # clone OpenAI whisper and whisper.cpp
git clone https://github.com/openai/whisper git clone https://github.com/openai/whisper
git clone https://github.com/ggerganov/whisper.cpp git clone https://github.com/ggml-org/whisper.cpp
# get the models # get the models
cd whisper.cpp/models cd whisper.cpp/models

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@ -3,7 +3,7 @@
# Usage: # Usage:
# #
# git clone https://github.com/openai/whisper # git clone https://github.com/openai/whisper
# git clone https://github.com/ggerganov/whisper.cpp # git clone https://github.com/ggml-org/whisper.cpp
# git clone https://huggingface.co/openai/whisper-medium # git clone https://huggingface.co/openai/whisper-medium
# #
# python3 ./whisper.cpp/models/convert-h5-to-ggml.py ./whisper-medium/ ./whisper . # python3 ./whisper.cpp/models/convert-h5-to-ggml.py ./whisper-medium/ ./whisper .
@ -12,7 +12,7 @@
# #
# For more info: # For more info:
# #
# https://github.com/ggerganov/whisper.cpp/issues/157 # https://github.com/ggml-org/whisper.cpp/issues/157
# #
import io import io

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@ -254,10 +254,10 @@ def convert_encoder(hparams, model, quantize=False):
model = ct.convert( model = ct.convert(
traced_model, traced_model,
convert_to="neuralnetwork", convert_to="mlprogram",
inputs=[ct.TensorType(name="logmel_data", shape=input_shape)], inputs=[ct.TensorType(name="logmel_data", shape=input_shape)],
outputs=[ct.TensorType(name="output")], outputs=[ct.TensorType(name="output")],
compute_units=ct.ComputeUnit.ALL compute_units=ct.ComputeUnit.ALL,
) )
if quantize: if quantize:
@ -278,11 +278,11 @@ def convert_decoder(hparams, model, quantize=False):
model = ct.convert( model = ct.convert(
traced_model, traced_model,
convert_to="neuralnetwork", convert_to="mlprogram",
inputs=[ inputs=[
ct.TensorType(name="token_data", shape=tokens_shape, dtype=int), ct.TensorType(name="token_data", shape=tokens_shape, dtype=int),
ct.TensorType(name="audio_data", shape=audio_shape) ct.TensorType(name="audio_data", shape=audio_shape)
] ],
) )
if quantize: if quantize:

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@ -1 +1 @@
7d7aa2dee2eb55dc683af80b769b81a0642226a1 d920dfd7da37b22d1eb0813cdaf340c1870d76c3

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@ -4276,11 +4276,11 @@ void whisper_print_timings(struct whisper_context * ctx) {
WHISPER_LOG_INFO("%s: fallbacks = %3d p / %3d h\n", __func__, ctx->state->n_fail_p, ctx->state->n_fail_h); WHISPER_LOG_INFO("%s: fallbacks = %3d p / %3d h\n", __func__, ctx->state->n_fail_p, ctx->state->n_fail_h);
WHISPER_LOG_INFO("%s: mel time = %8.2f ms\n", __func__, ctx->state->t_mel_us / 1000.0f); WHISPER_LOG_INFO("%s: mel time = %8.2f ms\n", __func__, ctx->state->t_mel_us / 1000.0f);
WHISPER_LOG_INFO("%s: sample time = %8.2f ms / %5d runs (%8.2f ms per run)\n", __func__, 1e-3f * ctx->state->t_sample_us, n_sample, 1e-3f * ctx->state->t_sample_us / n_sample); WHISPER_LOG_INFO("%s: sample time = %8.2f ms / %5d runs ( %8.2f ms per run)\n", __func__, 1e-3f * ctx->state->t_sample_us, n_sample, 1e-3f * ctx->state->t_sample_us / n_sample);
WHISPER_LOG_INFO("%s: encode time = %8.2f ms / %5d runs (%8.2f ms per run)\n", __func__, 1e-3f * ctx->state->t_encode_us, n_encode, 1e-3f * ctx->state->t_encode_us / n_encode); WHISPER_LOG_INFO("%s: encode time = %8.2f ms / %5d runs ( %8.2f ms per run)\n", __func__, 1e-3f * ctx->state->t_encode_us, n_encode, 1e-3f * ctx->state->t_encode_us / n_encode);
WHISPER_LOG_INFO("%s: decode time = %8.2f ms / %5d runs (%8.2f ms per run)\n", __func__, 1e-3f * ctx->state->t_decode_us, n_decode, 1e-3f * ctx->state->t_decode_us / n_decode); WHISPER_LOG_INFO("%s: decode time = %8.2f ms / %5d runs ( %8.2f ms per run)\n", __func__, 1e-3f * ctx->state->t_decode_us, n_decode, 1e-3f * ctx->state->t_decode_us / n_decode);
WHISPER_LOG_INFO("%s: batchd time = %8.2f ms / %5d runs (%8.2f ms per run)\n", __func__, 1e-3f * ctx->state->t_batchd_us, n_batchd, 1e-3f * ctx->state->t_batchd_us / n_batchd); WHISPER_LOG_INFO("%s: batchd time = %8.2f ms / %5d runs ( %8.2f ms per run)\n", __func__, 1e-3f * ctx->state->t_batchd_us, n_batchd, 1e-3f * ctx->state->t_batchd_us / n_batchd);
WHISPER_LOG_INFO("%s: prompt time = %8.2f ms / %5d runs (%8.2f ms per run)\n", __func__, 1e-3f * ctx->state->t_prompt_us, n_prompt, 1e-3f * ctx->state->t_prompt_us / n_prompt); WHISPER_LOG_INFO("%s: prompt time = %8.2f ms / %5d runs ( %8.2f ms per run)\n", __func__, 1e-3f * ctx->state->t_prompt_us, n_prompt, 1e-3f * ctx->state->t_prompt_us / n_prompt);
} }
WHISPER_LOG_INFO("%s: total time = %8.2f ms\n", __func__, (t_end_us - ctx->t_start_us)/1000.0f); WHISPER_LOG_INFO("%s: total time = %8.2f ms\n", __func__, (t_end_us - ctx->t_start_us)/1000.0f);
} }
@ -5527,11 +5527,13 @@ int whisper_full_with_state(
const int seek_start = params.offset_ms/10; const int seek_start = params.offset_ms/10;
const int seek_end = params.duration_ms == 0 ? whisper_n_len_from_state(state) : seek_start + params.duration_ms/10; const int seek_end = params.duration_ms == 0 ? whisper_n_len_from_state(state) : seek_start + params.duration_ms/10;
// if length of spectrogram is less than 1.0s (100 frames), then return // if length of spectrogram is less than 100ms (10 frames), then return
// basically don't process anything that is less than 1.0s // basically don't process anything that is less than 100ms
// see issue #39: https://github.com/ggerganov/whisper.cpp/issues/39 // ref: https://github.com/ggml-org/whisper.cpp/issues/2065
if (seek_end < seek_start + 100) { const int delta_min = 10;
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);
if (seek_end < seek_start + delta_min) {
WHISPER_LOG_WARN("%s: input is too short - %d ms < 100 ms. consider padding the input audio with silence\n", __func__, (seek_end - seek_start)*10);
return 0; return 0;
} }
@ -5675,8 +5677,8 @@ int whisper_full_with_state(
ctx, state, progress_cur, params.progress_callback_user_data); ctx, state, progress_cur, params.progress_callback_user_data);
} }
// if only 1 second left, then stop // if only 100ms left, then stop
if (seek + 100 >= seek_end) { if (seek + delta_min >= seek_end) {
break; break;
} }
@ -6023,10 +6025,10 @@ int whisper_full_with_state(
// end of segment // end of segment
if (token.id == whisper_token_eot(ctx) || // end of text token if (token.id == whisper_token_eot(ctx) || // end of text token
(params.max_tokens > 0 && i >= params.max_tokens) || // max tokens per segment reached (params.max_tokens > 0 && i >= params.max_tokens) || // max tokens per segment reached
(has_ts && seek + seek_delta + 100 >= seek_end) // end of audio reached (has_ts && seek + seek_delta + delta_min >= seek_end) // end of audio reached (100ms)
) { ) {
if (result_len == 0 && !params.no_timestamps) { if (result_len == 0 && !params.no_timestamps) {
if (seek + seek_delta + 100 >= seek_end) { if (seek + seek_delta + delta_min >= seek_end) {
result_len = i + 1; result_len = i + 1;
} else { } else {
WHISPER_LOG_DEBUG("%s: decoder %d failed (result_len = 0)\n", __func__, j); WHISPER_LOG_DEBUG("%s: decoder %d failed (result_len = 0)\n", __func__, j);
@ -6375,7 +6377,7 @@ int whisper_full_with_state(
} }
} }
// ref: https://github.com/ggerganov/whisper.cpp/pull/2629 // ref: https://github.com/ggml-org/whisper.cpp/pull/2629
const bool single_timestamp_ending = tokens_cur.size() > 1 && const bool single_timestamp_ending = tokens_cur.size() > 1 &&
tokens_cur[tokens_cur.size() - 2].id < whisper_token_beg(ctx) && tokens_cur[tokens_cur.size() - 2].id < whisper_token_beg(ctx) &&
tokens_cur[tokens_cur.size() - 1].id > whisper_token_beg(ctx); tokens_cur[tokens_cur.size() - 1].id > whisper_token_beg(ctx);

6
tests/librispeech/.gitignore vendored Normal file
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@ -0,0 +1,6 @@
__pycache__
*.tar.gz
*.txt
eval.conf
venv
LibriSpeech

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@ -0,0 +1,15 @@
TAR_URL = https://www.openslr.org/resources/12/test-clean.tar.gz
all: eval
eval:
$(MAKE) -f eval.mk
clean:
$(MAKE) -f eval.mk clean
get-audio:
wget -c $(TAR_URL)
tar -xf test-clean.tar.gz
.PHONY: all eval clean setup-venv clean-venv get-audio

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@ -0,0 +1,60 @@
# whisper.cpp/tests/librispeech
[LibriSpeech](https://www.openslr.org/12) is a standard dataset for
training and evaluating automatic speech recognition systems.
This directory contains a set of tools to evaluate the recognition
performance of whisper.cpp on LibriSpeech corpus.
## Quick Start
1. (Pre-requirement) Compile `whisper-cli` and prepare the Whisper
model in `ggml` format.
```
$ # Execute the commands below in the project root dir.
$ cmake -B build
$ cmake --build build --config Release
$ ./models/download-ggml-model.sh tiny
```
Consult [whisper.cpp/README.md](../../README.md) for more details.
2. Download the audio files from LibriSpeech project.
```
$ make get-audio
```
3. Set up the environment to compute WER score.
```
$ pip install -r requirements.txt
```
For example, if you use `virtualenv`, you can set up it as follows:
```
$ python3 -m venv venv
$ . venv/bin/activate
$ pip install -r requirements.txt
```
4. Run the benchmark test.
```
$ make
```
## How-to guides
### How to change the inferece parameters
Create `eval.conf` and override variables.
```
WHISPER_MODEL = large-v3-turbo
WHISPER_FLAGS = --no-prints --threads 8 --language en --output-txt
```
Check out `eval.mk` for more details.

39
tests/librispeech/eval.mk Normal file
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@ -0,0 +1,39 @@
PYTHON = python
WHISPER_PREFIX = ../../
WHISPER_MODEL = tiny
WHISPER_CLI = $(WHISPER_PREFIX)build/bin/whisper-cli
WHISPER_FLAGS = --no-prints --language en --output-txt
# You can create eval.conf to override the WHISPER_* variables
# defined above.
-include eval.conf
# This follows the file structure of the LibriSpeech project.
AUDIO_SRCS = $(sort $(wildcard LibriSpeech/*/*/*/*.flac))
TRANS_TXTS = $(addsuffix .txt, $(AUDIO_SRCS))
# We output the evaluation result to this file.
DONE = $(WHISPER_MODEL).txt
all: $(DONE)
$(DONE): $(TRANS_TXTS)
$(PYTHON) eval.py > $@.tmp
mv $@.tmp $@
# Note: This task writes to a temporary file first to
# create the target file atomically.
%.flac.txt: %.flac
$(WHISPER_CLI) $(WHISPER_FLAGS) --model $(WHISPER_PREFIX)models/ggml-$(WHISPER_MODEL).bin --file $^ --output-file $^.tmp
mv $^.tmp.txt $^.txt
archive:
tar -czf $(WHISPER_MODEL).tar.gz --exclude="*.flac" LibriSpeech $(DONE)
clean:
@rm -f $(TRANS_TXTS)
@rm -f $(DONE)
.PHONY: all clean

47
tests/librispeech/eval.py Normal file
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@ -0,0 +1,47 @@
import os
import glob
import jiwer
from normalizers import EnglishTextNormalizer
def get_reference():
ref = {}
for path in glob.glob('LibriSpeech/*/*/*/*.trans.txt'):
with open(path) as fp:
for line in fp:
code, text = line.strip().split(" ", maxsplit=1)
ref [code] = text
return ref
def get_hypothesis():
hyp = {}
for path in glob.glob('LibriSpeech/*/*/*/*.flac.txt'):
with open(path) as fp:
text = fp.read().strip()
code = os.path.basename(path).replace('.flac.txt', '')
hyp[code] = text
return hyp
def get_codes():
codes = []
for path in glob.glob('LibriSpeech/*/*/*/*.flac'):
codes.append(os.path.basename(path).replace('.flac', ''))
return sorted(codes)
def main():
normalizer = EnglishTextNormalizer()
ref_orig = get_reference()
hyp_orig = get_hypothesis()
ref_clean = []
hyp_clean = []
for code in get_codes():
ref_clean.append(normalizer(ref_orig[code]))
hyp_clean.append(normalizer(hyp_orig[code]))
wer = jiwer.wer(ref_clean, hyp_clean)
print(f"WER: {wer * 100:.2f}%")
if __name__ == '__main__':
main()

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@ -0,0 +1,25 @@
Code in this directory is adapted from OpenAI Whisper project
(https://github.com/openai/whisper) and carries the following
copyright and license.
MIT License
Copyright (c) 2022 OpenAI
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.

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@ -0,0 +1,2 @@
from .basic import BasicTextNormalizer as BasicTextNormalizer
from .english import EnglishTextNormalizer as EnglishTextNormalizer

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@ -0,0 +1,80 @@
import re
import unicodedata
import regex
# non-ASCII letters that are not separated by "NFKD" normalization
ADDITIONAL_DIACRITICS = {
"œ": "oe",
"Œ": "OE",
"ø": "o",
"Ø": "O",
"æ": "ae",
"Æ": "AE",
"ß": "ss",
"": "SS",
"đ": "d",
"Đ": "D",
"ð": "d",
"Ð": "D",
"þ": "th",
"Þ": "th",
"ł": "l",
"Ł": "L",
}
def remove_symbols_and_diacritics(s: str, keep=""):
"""
Replace any other markers, symbols, and punctuations with a space,
and drop any diacritics (category 'Mn' and some manual mappings)
"""
return "".join(
(
c
if c in keep
else (
ADDITIONAL_DIACRITICS[c]
if c in ADDITIONAL_DIACRITICS
else (
""
if unicodedata.category(c) == "Mn"
else " " if unicodedata.category(c)[0] in "MSP" else c
)
)
)
for c in unicodedata.normalize("NFKD", s)
)
def remove_symbols(s: str):
"""
Replace any other markers, symbols, punctuations with a space, keeping diacritics
"""
return "".join(
" " if unicodedata.category(c)[0] in "MSP" else c
for c in unicodedata.normalize("NFKC", s)
)
class BasicTextNormalizer:
def __init__(self, remove_diacritics: bool = False, split_letters: bool = False):
self.clean = (
remove_symbols_and_diacritics if remove_diacritics else remove_symbols
)
self.split_letters = split_letters
def __call__(self, s: str):
s = s.lower()
s = re.sub(r"[<\[][^>\]]*[>\]]", "", s) # remove words between brackets
s = re.sub(r"\(([^)]+?)\)", "", s) # remove words between parenthesis
s = self.clean(s).lower()
if self.split_letters:
s = " ".join(regex.findall(r"\X", s, regex.U))
s = re.sub(
r"\s+", " ", s
) # replace any successive whitespace characters with a space
return s

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@ -0,0 +1,550 @@
import json
import os
import re
from fractions import Fraction
from typing import Iterator, List, Match, Optional, Union
from more_itertools import windowed
from .basic import remove_symbols_and_diacritics
class EnglishNumberNormalizer:
"""
Convert any spelled-out numbers into arabic numbers, while handling:
- remove any commas
- keep the suffixes such as: `1960s`, `274th`, `32nd`, etc.
- spell out currency symbols after the number. e.g. `$20 million` -> `20000000 dollars`
- spell out `one` and `ones`
- interpret successive single-digit numbers as nominal: `one oh one` -> `101`
"""
def __init__(self):
super().__init__()
self.zeros = {"o", "oh", "zero"}
self.ones = {
name: i
for i, name in enumerate(
[
"one",
"two",
"three",
"four",
"five",
"six",
"seven",
"eight",
"nine",
"ten",
"eleven",
"twelve",
"thirteen",
"fourteen",
"fifteen",
"sixteen",
"seventeen",
"eighteen",
"nineteen",
],
start=1,
)
}
self.ones_plural = {
"sixes" if name == "six" else name + "s": (value, "s")
for name, value in self.ones.items()
}
self.ones_ordinal = {
"zeroth": (0, "th"),
"first": (1, "st"),
"second": (2, "nd"),
"third": (3, "rd"),
"fifth": (5, "th"),
"twelfth": (12, "th"),
**{
name + ("h" if name.endswith("t") else "th"): (value, "th")
for name, value in self.ones.items()
if value > 3 and value != 5 and value != 12
},
}
self.ones_suffixed = {**self.ones_plural, **self.ones_ordinal}
self.tens = {
"twenty": 20,
"thirty": 30,
"forty": 40,
"fifty": 50,
"sixty": 60,
"seventy": 70,
"eighty": 80,
"ninety": 90,
}
self.tens_plural = {
name.replace("y", "ies"): (value, "s") for name, value in self.tens.items()
}
self.tens_ordinal = {
name.replace("y", "ieth"): (value, "th")
for name, value in self.tens.items()
}
self.tens_suffixed = {**self.tens_plural, **self.tens_ordinal}
self.multipliers = {
"hundred": 100,
"thousand": 1_000,
"million": 1_000_000,
"billion": 1_000_000_000,
"trillion": 1_000_000_000_000,
"quadrillion": 1_000_000_000_000_000,
"quintillion": 1_000_000_000_000_000_000,
"sextillion": 1_000_000_000_000_000_000_000,
"septillion": 1_000_000_000_000_000_000_000_000,
"octillion": 1_000_000_000_000_000_000_000_000_000,
"nonillion": 1_000_000_000_000_000_000_000_000_000_000,
"decillion": 1_000_000_000_000_000_000_000_000_000_000_000,
}
self.multipliers_plural = {
name + "s": (value, "s") for name, value in self.multipliers.items()
}
self.multipliers_ordinal = {
name + "th": (value, "th") for name, value in self.multipliers.items()
}
self.multipliers_suffixed = {
**self.multipliers_plural,
**self.multipliers_ordinal,
}
self.decimals = {*self.ones, *self.tens, *self.zeros}
self.preceding_prefixers = {
"minus": "-",
"negative": "-",
"plus": "+",
"positive": "+",
}
self.following_prefixers = {
"pound": "£",
"pounds": "£",
"euro": "",
"euros": "",
"dollar": "$",
"dollars": "$",
"cent": "¢",
"cents": "¢",
}
self.prefixes = set(
list(self.preceding_prefixers.values())
+ list(self.following_prefixers.values())
)
self.suffixers = {
"per": {"cent": "%"},
"percent": "%",
}
self.specials = {"and", "double", "triple", "point"}
self.words = set(
[
key
for mapping in [
self.zeros,
self.ones,
self.ones_suffixed,
self.tens,
self.tens_suffixed,
self.multipliers,
self.multipliers_suffixed,
self.preceding_prefixers,
self.following_prefixers,
self.suffixers,
self.specials,
]
for key in mapping
]
)
self.literal_words = {"one", "ones"}
def process_words(self, words: List[str]) -> Iterator[str]:
prefix: Optional[str] = None
value: Optional[Union[str, int]] = None
skip = False
def to_fraction(s: str):
try:
return Fraction(s)
except ValueError:
return None
def output(result: Union[str, int]):
nonlocal prefix, value
result = str(result)
if prefix is not None:
result = prefix + result
value = None
prefix = None
return result
if len(words) == 0:
return
for prev, current, next in windowed([None] + words + [None], 3):
if skip:
skip = False
continue
next_is_numeric = next is not None and re.match(r"^\d+(\.\d+)?$", next)
has_prefix = current[0] in self.prefixes
current_without_prefix = current[1:] if has_prefix else current
if re.match(r"^\d+(\.\d+)?$", current_without_prefix):
# arabic numbers (potentially with signs and fractions)
f = to_fraction(current_without_prefix)
assert f is not None
if value is not None:
if isinstance(value, str) and value.endswith("."):
# concatenate decimals / ip address components
value = str(value) + str(current)
continue
else:
yield output(value)
prefix = current[0] if has_prefix else prefix
if f.denominator == 1:
value = f.numerator # store integers as int
else:
value = current_without_prefix
elif current not in self.words:
# non-numeric words
if value is not None:
yield output(value)
yield output(current)
elif current in self.zeros:
value = str(value or "") + "0"
elif current in self.ones:
ones = self.ones[current]
if value is None:
value = ones
elif isinstance(value, str) or prev in self.ones:
if (
prev in self.tens and ones < 10
): # replace the last zero with the digit
assert value[-1] == "0"
value = value[:-1] + str(ones)
else:
value = str(value) + str(ones)
elif ones < 10:
if value % 10 == 0:
value += ones
else:
value = str(value) + str(ones)
else: # eleven to nineteen
if value % 100 == 0:
value += ones
else:
value = str(value) + str(ones)
elif current in self.ones_suffixed:
# ordinal or cardinal; yield the number right away
ones, suffix = self.ones_suffixed[current]
if value is None:
yield output(str(ones) + suffix)
elif isinstance(value, str) or prev in self.ones:
if prev in self.tens and ones < 10:
assert value[-1] == "0"
yield output(value[:-1] + str(ones) + suffix)
else:
yield output(str(value) + str(ones) + suffix)
elif ones < 10:
if value % 10 == 0:
yield output(str(value + ones) + suffix)
else:
yield output(str(value) + str(ones) + suffix)
else: # eleven to nineteen
if value % 100 == 0:
yield output(str(value + ones) + suffix)
else:
yield output(str(value) + str(ones) + suffix)
value = None
elif current in self.tens:
tens = self.tens[current]
if value is None:
value = tens
elif isinstance(value, str):
value = str(value) + str(tens)
else:
if value % 100 == 0:
value += tens
else:
value = str(value) + str(tens)
elif current in self.tens_suffixed:
# ordinal or cardinal; yield the number right away
tens, suffix = self.tens_suffixed[current]
if value is None:
yield output(str(tens) + suffix)
elif isinstance(value, str):
yield output(str(value) + str(tens) + suffix)
else:
if value % 100 == 0:
yield output(str(value + tens) + suffix)
else:
yield output(str(value) + str(tens) + suffix)
elif current in self.multipliers:
multiplier = self.multipliers[current]
if value is None:
value = multiplier
elif isinstance(value, str) or value == 0:
f = to_fraction(value)
p = f * multiplier if f is not None else None
if f is not None and p.denominator == 1:
value = p.numerator
else:
yield output(value)
value = multiplier
else:
before = value // 1000 * 1000
residual = value % 1000
value = before + residual * multiplier
elif current in self.multipliers_suffixed:
multiplier, suffix = self.multipliers_suffixed[current]
if value is None:
yield output(str(multiplier) + suffix)
elif isinstance(value, str):
f = to_fraction(value)
p = f * multiplier if f is not None else None
if f is not None and p.denominator == 1:
yield output(str(p.numerator) + suffix)
else:
yield output(value)
yield output(str(multiplier) + suffix)
else: # int
before = value // 1000 * 1000
residual = value % 1000
value = before + residual * multiplier
yield output(str(value) + suffix)
value = None
elif current in self.preceding_prefixers:
# apply prefix (positive, minus, etc.) if it precedes a number
if value is not None:
yield output(value)
if next in self.words or next_is_numeric:
prefix = self.preceding_prefixers[current]
else:
yield output(current)
elif current in self.following_prefixers:
# apply prefix (dollars, cents, etc.) only after a number
if value is not None:
prefix = self.following_prefixers[current]
yield output(value)
else:
yield output(current)
elif current in self.suffixers:
# apply suffix symbols (percent -> '%')
if value is not None:
suffix = self.suffixers[current]
if isinstance(suffix, dict):
if next in suffix:
yield output(str(value) + suffix[next])
skip = True
else:
yield output(value)
yield output(current)
else:
yield output(str(value) + suffix)
else:
yield output(current)
elif current in self.specials:
if next not in self.words and not next_is_numeric:
# apply special handling only if the next word can be numeric
if value is not None:
yield output(value)
yield output(current)
elif current == "and":
# ignore "and" after hundreds, thousands, etc.
if prev not in self.multipliers:
if value is not None:
yield output(value)
yield output(current)
elif current == "double" or current == "triple":
if next in self.ones or next in self.zeros:
repeats = 2 if current == "double" else 3
ones = self.ones.get(next, 0)
value = str(value or "") + str(ones) * repeats
skip = True
else:
if value is not None:
yield output(value)
yield output(current)
elif current == "point":
if next in self.decimals or next_is_numeric:
value = str(value or "") + "."
else:
# should all have been covered at this point
raise ValueError(f"Unexpected token: {current}")
else:
# all should have been covered at this point
raise ValueError(f"Unexpected token: {current}")
if value is not None:
yield output(value)
def preprocess(self, s: str):
# replace "<number> and a half" with "<number> point five"
results = []
segments = re.split(r"\band\s+a\s+half\b", s)
for i, segment in enumerate(segments):
if len(segment.strip()) == 0:
continue
if i == len(segments) - 1:
results.append(segment)
else:
results.append(segment)
last_word = segment.rsplit(maxsplit=2)[-1]
if last_word in self.decimals or last_word in self.multipliers:
results.append("point five")
else:
results.append("and a half")
s = " ".join(results)
# put a space at number/letter boundary
s = re.sub(r"([a-z])([0-9])", r"\1 \2", s)
s = re.sub(r"([0-9])([a-z])", r"\1 \2", s)
# but remove spaces which could be a suffix
s = re.sub(r"([0-9])\s+(st|nd|rd|th|s)\b", r"\1\2", s)
return s
def postprocess(self, s: str):
def combine_cents(m: Match):
try:
currency = m.group(1)
integer = m.group(2)
cents = int(m.group(3))
return f"{currency}{integer}.{cents:02d}"
except ValueError:
return m.string
def extract_cents(m: Match):
try:
return f"¢{int(m.group(1))}"
except ValueError:
return m.string
# apply currency postprocessing; "$2 and ¢7" -> "$2.07"
s = re.sub(r"([€£$])([0-9]+) (?:and )?¢([0-9]{1,2})\b", combine_cents, s)
s = re.sub(r"[€£$]0.([0-9]{1,2})\b", extract_cents, s)
# write "one(s)" instead of "1(s)", just for the readability
s = re.sub(r"\b1(s?)\b", r"one\1", s)
return s
def __call__(self, s: str):
s = self.preprocess(s)
s = " ".join(word for word in self.process_words(s.split()) if word is not None)
s = self.postprocess(s)
return s
class EnglishSpellingNormalizer:
"""
Applies British-American spelling mappings as listed in [1].
[1] https://www.tysto.com/uk-us-spelling-list.html
"""
def __init__(self):
mapping_path = os.path.join(os.path.dirname(__file__), "english.json")
self.mapping = json.load(open(mapping_path))
def __call__(self, s: str):
return " ".join(self.mapping.get(word, word) for word in s.split())
class EnglishTextNormalizer:
def __init__(self):
self.ignore_patterns = r"\b(hmm|mm|mhm|mmm|uh|um)\b"
self.replacers = {
# common contractions
r"\bwon't\b": "will not",
r"\bcan't\b": "can not",
r"\blet's\b": "let us",
r"\bain't\b": "aint",
r"\by'all\b": "you all",
r"\bwanna\b": "want to",
r"\bgotta\b": "got to",
r"\bgonna\b": "going to",
r"\bi'ma\b": "i am going to",
r"\bimma\b": "i am going to",
r"\bwoulda\b": "would have",
r"\bcoulda\b": "could have",
r"\bshoulda\b": "should have",
r"\bma'am\b": "madam",
# contractions in titles/prefixes
r"\bmr\b": "mister ",
r"\bmrs\b": "missus ",
r"\bst\b": "saint ",
r"\bdr\b": "doctor ",
r"\bprof\b": "professor ",
r"\bcapt\b": "captain ",
r"\bgov\b": "governor ",
r"\bald\b": "alderman ",
r"\bgen\b": "general ",
r"\bsen\b": "senator ",
r"\brep\b": "representative ",
r"\bpres\b": "president ",
r"\brev\b": "reverend ",
r"\bhon\b": "honorable ",
r"\basst\b": "assistant ",
r"\bassoc\b": "associate ",
r"\blt\b": "lieutenant ",
r"\bcol\b": "colonel ",
r"\bjr\b": "junior ",
r"\bsr\b": "senior ",
r"\besq\b": "esquire ",
# prefect tenses, ideally it should be any past participles, but it's harder..
r"'d been\b": " had been",
r"'s been\b": " has been",
r"'d gone\b": " had gone",
r"'s gone\b": " has gone",
r"'d done\b": " had done", # "'s done" is ambiguous
r"'s got\b": " has got",
# general contractions
r"n't\b": " not",
r"'re\b": " are",
r"'s\b": " is",
r"'d\b": " would",
r"'ll\b": " will",
r"'t\b": " not",
r"'ve\b": " have",
r"'m\b": " am",
}
self.standardize_numbers = EnglishNumberNormalizer()
self.standardize_spellings = EnglishSpellingNormalizer()
def __call__(self, s: str):
s = s.lower()
s = re.sub(r"[<\[][^>\]]*[>\]]", "", s) # remove words between brackets
s = re.sub(r"\(([^)]+?)\)", "", s) # remove words between parenthesis
s = re.sub(self.ignore_patterns, "", s)
s = re.sub(r"\s+'", "'", s) # when there's a space before an apostrophe
for pattern, replacement in self.replacers.items():
s = re.sub(pattern, replacement, s)
s = re.sub(r"(\d),(\d)", r"\1\2", s) # remove commas between digits
s = re.sub(r"\.([^0-9]|$)", r" \1", s) # remove periods not followed by numbers
s = remove_symbols_and_diacritics(s, keep=".%$¢€£") # keep numeric symbols
s = self.standardize_numbers(s)
s = self.standardize_spellings(s)
# now remove prefix/suffix symbols that are not preceded/followed by numbers
s = re.sub(r"[.$¢€£]([^0-9])", r" \1", s)
s = re.sub(r"([^0-9])%", r"\1 ", s)
s = re.sub(r"\s+", " ", s) # replace any successive whitespaces with a space
return s

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# This is the minimal set of dependencies we need to compute
# WER score. Read Section 3.2. of the original paper
# (https://arxiv.org/abs/2212.04356) for more contexts.
jiwer
regex
more-itertools