docker : Dockerize whisper.cpp (#1674)

* build: add dockerfile for ci

* ci: add action to build/push docker image

* fix: lowercase repository to fix ci

* ci: update cuBLAS flag

* build: install curl and ffmped in image

* docs: add docker section

* fix: improve args check when download model
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Chaoqun 2023-12-22 19:16:02 +08:00 committed by GitHub
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commit d2ee117a0a
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5 changed files with 146 additions and 5 deletions

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@ -0,0 +1,34 @@
ARG UBUNTU_VERSION=22.04
# This needs to generally match the container host's environment.
ARG CUDA_VERSION=12.3.1
# Target the CUDA build image
ARG BASE_CUDA_DEV_CONTAINER=nvidia/cuda:${CUDA_VERSION}-devel-ubuntu${UBUNTU_VERSION}
# Target the CUDA runtime image
ARG BASE_CUDA_RUN_CONTAINER=nvidia/cuda:${CUDA_VERSION}-runtime-ubuntu${UBUNTU_VERSION}
FROM ${BASE_CUDA_DEV_CONTAINER} AS build
WORKDIR /app
# Unless otherwise specified, we make a fat build.
ARG CUDA_DOCKER_ARCH=all
# Set nvcc architecture
ENV CUDA_DOCKER_ARCH=${CUDA_DOCKER_ARCH}
# Enable cuBLAS
ENV WHISPER_CUBLAS=1
RUN apt-get update && \
apt-get install -y build-essential \
&& rm -rf /var/lib/apt/lists/* /var/cache/apt/archives/*
COPY .. .
RUN make
FROM ${BASE_CUDA_RUN_CONTAINER} AS runtime
WORKDIR /app
RUN apt-get update && \
apt-get install -y curl ffmpeg \
&& rm -rf /var/lib/apt/lists/* /var/cache/apt/archives/*
COPY --from=build /app /app
ENTRYPOINT [ "bash", "-c" ]

19
.devops/main.Dockerfile Normal file
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@ -0,0 +1,19 @@
FROM ubuntu:22.04 AS build
WORKDIR /app
RUN apt-get update && \
apt-get install -y build-essential \
&& rm -rf /var/lib/apt/lists/* /var/cache/apt/archives/*
COPY .. .
RUN make
FROM ubuntu:22.04 AS runtime
WORKDIR /app
RUN apt-get update && \
apt-get install -y curl ffmpeg \
&& rm -rf /var/lib/apt/lists/* /var/cache/apt/archives/*
COPY --from=build /app /app
ENTRYPOINT [ "bash", "-c" ]

57
.github/workflows/docker.yml vendored Normal file
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@ -0,0 +1,57 @@
name: Publish Docker image
on:
pull_request:
push:
branches:
- master
jobs:
push_to_registry:
name: Push Docker image to Docker Hub
if: github.event.pull_request.draft == false
runs-on: ubuntu-latest
env:
COMMIT_SHA: ${{ github.sha }}
strategy:
matrix:
config:
- { tag: "main", dockerfile: ".devops/main.Dockerfile", platform: "linux/amd64,linux/arm64" }
- { tag: "main-cuda", dockerfile: ".devops/main-cuda.Dockerfile", platform: "linux/amd64" }
steps:
- name: Check out the repo
uses: actions/checkout@v3
- name: Set up QEMU
uses: docker/setup-qemu-action@v3
- name: Set up Docker Buildx
uses: docker/setup-buildx-action@v3
- name: Log in to Docker Hub
uses: docker/login-action@v3
with:
registry: ghcr.io
username: ${{ github.repository_owner }}
password: ${{ secrets.GITHUB_TOKEN }}
- name: Build and push Docker image (versioned)
if: github.event_name == 'push'
uses: docker/build-push-action@v5
with:
context: .
push: true
platforms: ${{ matrix.config.platforms }}
tags: "ghcr.io/${{ github.repository }}:${{ matrix.config.tag }}-${{ env.COMMIT_SHA }}"
file: ${{ matrix.config.dockerfile }}
- name: Build and push Docker image (tagged)
uses: docker/build-push-action@v4
with:
context: .
push: ${{ github.event_name == 'push' }}
platforms: ${{ matrix.config.platforms }}
tags: "ghcr.io/${{ github.repository }}:${{ matrix.config.tag }}"
file: ${{ matrix.config.dockerfile }}

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@ -33,6 +33,7 @@ Supported platforms:
- [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] [Raspberry Pi](https://github.com/ggerganov/whisper.cpp/discussions/166)
- [x] [docker](https://github.com/ggerganov/whisper.cpp/pkgs/container/whisper.cpp)
The entire high-level implementation of the model is contained in [whisper.h](whisper.h) and [whisper.cpp](whisper.cpp).
The rest of the code is part of the [ggml](https://github.com/ggerganov/ggml) machine learning library.
@ -448,6 +449,36 @@ make clean
WHISPER_OPENBLAS=1 make -j
```
## Docker
### Prerequisites
* Docker must be installed and running on your system.
* Create a folder to store big models & intermediate files (ex. /whisper/models)
### Images
We have two Docker images available for this project:
1. `ghcr.io/ggerganov/whisper.cpp:main`: This image includes the main executable file as well as `curl` and `ffmpeg`. (platforms: `linux/amd64`, `linux/arm64`)
2. `ghcr.io/ggerganov/whisper.cpp:main-cuda`: Same as `main` but compiled with CUDA support. (platforms: `linux/amd64`)
### Usage
```shell
# download model and persist it in a local folder
docker run -it --rm \
-v path/to/models:/models \
whisper.cpp:main "./models/download-ggml-model.sh base /models"
# transcribe an audio file
docker run -it --rm \
-v path/to/models:/models \
-v path/to/audios:/audios \
whisper.cpp:main "./main -m /models/ggml-base.bin -f /audios/jfk.wav"
# transcribe an audio file in samples folder
docker run -it --rm \
-v path/to/models:/models \
whisper.cpp:main "./main -m /models/ggml-base.bin -f ./samples/jfk.wav"
```
## Limitations
- Inference only

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@ -19,7 +19,7 @@ function get_script_path() {
fi
}
models_path="$(get_script_path)"
models_path="${2:-$(get_script_path)}"
# Whisper models
models=(
@ -56,8 +56,8 @@ function list_models {
printf "\n\n"
}
if [ "$#" -ne 1 ]; then
printf "Usage: $0 <model>\n"
if [ "$#" -lt 1 ] || [ "$#" -gt 2 ]; then
printf "Usage: $0 <model> [models_path]\n"
list_models
exit 1
@ -105,7 +105,7 @@ if [ $? -ne 0 ]; then
exit 1
fi
printf "Done! Model '$model' saved in 'models/ggml-$model.bin'\n"
printf "Done! Model '$model' saved in '$models_path/ggml-$model.bin'\n"
printf "You can now use it like this:\n\n"
printf " $ ./main -m models/ggml-$model.bin -f samples/jfk.wav\n"
printf " $ ./main -m $models_path/ggml-$model.bin -f samples/jfk.wav\n"
printf "\n"