ludicrously awesome [w]rapper for nvidia-docker
Project description
# luda
ludicrously awesome [w]rapper for nvidia-docker
* Free software: MIT license
* Documentation: [coming shortly]
```
pip install luda
```
## Features
* Opinionated wrapper for `docker`/`nvidia-docker` designed to provide
Singularity-like functionality to Docker images.
* Best used for container images that run DL/HPC-like jobs, not suited
for long-running daemons or services that require root.
* Volume mounts a /bootstrap volume and overrides the container image
`ENTRYPOINT` to map the host USER, UID and GID [future work] into the
container. Current the docker commandline is echo'ed to the terminal on
container startup.
* Automounts the current working directory on the host to `/work` inside
the container. `/work` becomes the current working directory inside the
running container. `--work` can be used to specify an alternative default
working directory for use inside the container; it will be mounted to `/work`.
* Automounts `$HOME` on the host to `/home/$USER` inside the container.
`--home` option.
## Quickstart
```
luda nvidia/cuda:8.0-devel
```
This the equivalent of the following docker command:
```
nvidia-docker run --rm -t -i \
-v /Users/ryan/Projects/luda/luda/bootstrap:/bootstrap:ro \
--entrypoint /bootstrap/init.sh \
--env HOST_USER_ID=501 \
--env HOST_GROUP_ID=20 \
--env HOST_USER=ryan \
--env HOST_GROUP=staff \
-v /Users/ryan:/home/ryan \
-v /Users/ryan/Projects/luda:/work \
--workdir /work \
nvidia/cuda:8.0-devel /bin/bash
```
This launches a new container based on the `nvidia/cuda:8.0-devel`
image; however, the magic happens in the bootstrapping, where the host
user that launched the container is created inside the container on
launch (entrypoint).
This is exceptional convenient for development as your current working
directory is mapped into `/work` which then becomes the active working
directory inside the contanier. Edits made inside the container are
written as the USER/UID of the host user.
### Volumes
luda intercepts the `-v/--volume` option and provides convenience methods similar to
`docker-compose` in that relative paths are supported. If no
```
# absolute path readonly
--volume /path/data:/data:ro
# relative path readonly
--volume /path/data:/data:ro
# relative path, no internal path --> mount internal at `/{{ basename(hostpath) }}`
# mounts $PWD/data --> /data inside the container
# --volume data
# same as above, but readonly
# --volume data::ro
```
#### Home Directory
The user's home directory is a special case which mounts the user's home directory on the host
to `/home/$USER` in the container. This option is enabled by default, but can be disabled by
passing `--no-home` on the commandline.
#### Current Working Directory
luda will map the current working directory from which the `luda` command was executed on the host
to `/work` in the container and override the container's working directory to `/work`. This behavior
can be overridden by passing a volume mount or disabled by passing `None` to to the `--work` option.
Examples:
```
# mounts the current working directory on the host to `/my-working-dir`
# in the container; `/my-working-dir` become the default working directory
--work .:/my-working-dir
# mounts `~/other-dir` to `/other-dir` in the container; `/other-dir`
# becomes the default working directory in the container
--work ~/other-dir
# use the working directory as specified by the container image
--work None
--work none
```
### Abbreviations
You can set up abbreviations for commonly used URLs by including an `abbreviations` key in the yaml config file. By default,
luda includes the `nv:` which expands to `nvcr.io/nvidia/{0}`, where `{0}` is the remainding portion of the image name after
the abbreviation.
in `config.yml`
```
abbreviations:
nv: nvcr.io/nvidia/{1}
```
Usage `nv:tensorflow:17.04` expands to `nvcr.io/nvidia/tensorflow:17.04`:
```
luda nv:tensorflow:17.04
```
### Displays
```
luda --with-display nvidia/cuda:8.0-devel
```
todo: show opengl containers
### Docker
```
luda --with-docker nvidia/cuda:8.0-devel
```
### Templates
Templates provide an easy way to extend container images with pre-defined content.
Assume I have the following `Dockerfile` defined in `~/.config/luda/templates/dev`.
```
RUN apt-get update && apt-get install -y --no-install-recommends \
vim sudo python-dev python-pip && \
rm -rf /var/lib/apt/lists/*
RUN pip install luda
```
The developer option `--dev` is a special case of `--template dev`. Running the following commands performs a one-time
extensions of the `nvidia/cuda:8.0-devel` image with the `Dockerfile` above. The new images generated will be
`luda/nvidia-cuda-8.0-devel:dev` or `luda/{{ base_image }}:{{ template }}` where `base_image` has all `/` and `:` replaced
with `-`.
```
luda --dev nvidia/cuda:8.0-devel
```
```
luda --template dev nvidia/cuda:8.0-devel
```
The first time this command is invoked `luda/nvidia-cuda-8.0-devel:dev` will be created. Subsequent invocation will
either update the image if either the base image (`nvidia/cuda:8.0-devel`) or the template directory
(`~/.config/luda/templates/dev`) has detected changes.
## Acknowledgements
Thanks to [Deni Bertovic's
blog](https://denibertovic.com/posts/handling-permissions-with-docker-volumes/).
`luda` provides very similar functionality but does not require specially
crafted base images and wraps the details of the docker command-line.
The project contains a copy of [`su-exec`](https://github.com/ncopa/su-exec).
Copyright reproduced below.
```
The MIT License (MIT)
Copyright (c) 2015 ncopa
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.
```
=======
History
=======
0.1.0 (2017-03-07)
------------------
* First release on PyPI.
0.4.0 (2017-06-01)
------------------
* Added configurable abbreviations to simply long image names
* Added templates to extend images from reusable templated Dockerfiles
* Added entrypoint and command inspection on the base_image to ensure the correct scripts/commands
executed on container launch
* Removed --docker_run_args and replaced with luda managed `--rm`, `-d`, `-t`, `-i` options which map
directly to the docker equivalents
* Improved landing page documentation (still more needs to be done)
ludicrously awesome [w]rapper for nvidia-docker
* Free software: MIT license
* Documentation: [coming shortly]
```
pip install luda
```
## Features
* Opinionated wrapper for `docker`/`nvidia-docker` designed to provide
Singularity-like functionality to Docker images.
* Best used for container images that run DL/HPC-like jobs, not suited
for long-running daemons or services that require root.
* Volume mounts a /bootstrap volume and overrides the container image
`ENTRYPOINT` to map the host USER, UID and GID [future work] into the
container. Current the docker commandline is echo'ed to the terminal on
container startup.
* Automounts the current working directory on the host to `/work` inside
the container. `/work` becomes the current working directory inside the
running container. `--work` can be used to specify an alternative default
working directory for use inside the container; it will be mounted to `/work`.
* Automounts `$HOME` on the host to `/home/$USER` inside the container.
`--home` option.
## Quickstart
```
luda nvidia/cuda:8.0-devel
```
This the equivalent of the following docker command:
```
nvidia-docker run --rm -t -i \
-v /Users/ryan/Projects/luda/luda/bootstrap:/bootstrap:ro \
--entrypoint /bootstrap/init.sh \
--env HOST_USER_ID=501 \
--env HOST_GROUP_ID=20 \
--env HOST_USER=ryan \
--env HOST_GROUP=staff \
-v /Users/ryan:/home/ryan \
-v /Users/ryan/Projects/luda:/work \
--workdir /work \
nvidia/cuda:8.0-devel /bin/bash
```
This launches a new container based on the `nvidia/cuda:8.0-devel`
image; however, the magic happens in the bootstrapping, where the host
user that launched the container is created inside the container on
launch (entrypoint).
This is exceptional convenient for development as your current working
directory is mapped into `/work` which then becomes the active working
directory inside the contanier. Edits made inside the container are
written as the USER/UID of the host user.
### Volumes
luda intercepts the `-v/--volume` option and provides convenience methods similar to
`docker-compose` in that relative paths are supported. If no
```
# absolute path readonly
--volume /path/data:/data:ro
# relative path readonly
--volume /path/data:/data:ro
# relative path, no internal path --> mount internal at `/{{ basename(hostpath) }}`
# mounts $PWD/data --> /data inside the container
# --volume data
# same as above, but readonly
# --volume data::ro
```
#### Home Directory
The user's home directory is a special case which mounts the user's home directory on the host
to `/home/$USER` in the container. This option is enabled by default, but can be disabled by
passing `--no-home` on the commandline.
#### Current Working Directory
luda will map the current working directory from which the `luda` command was executed on the host
to `/work` in the container and override the container's working directory to `/work`. This behavior
can be overridden by passing a volume mount or disabled by passing `None` to to the `--work` option.
Examples:
```
# mounts the current working directory on the host to `/my-working-dir`
# in the container; `/my-working-dir` become the default working directory
--work .:/my-working-dir
# mounts `~/other-dir` to `/other-dir` in the container; `/other-dir`
# becomes the default working directory in the container
--work ~/other-dir
# use the working directory as specified by the container image
--work None
--work none
```
### Abbreviations
You can set up abbreviations for commonly used URLs by including an `abbreviations` key in the yaml config file. By default,
luda includes the `nv:` which expands to `nvcr.io/nvidia/{0}`, where `{0}` is the remainding portion of the image name after
the abbreviation.
in `config.yml`
```
abbreviations:
nv: nvcr.io/nvidia/{1}
```
Usage `nv:tensorflow:17.04` expands to `nvcr.io/nvidia/tensorflow:17.04`:
```
luda nv:tensorflow:17.04
```
### Displays
```
luda --with-display nvidia/cuda:8.0-devel
```
todo: show opengl containers
### Docker
```
luda --with-docker nvidia/cuda:8.0-devel
```
### Templates
Templates provide an easy way to extend container images with pre-defined content.
Assume I have the following `Dockerfile` defined in `~/.config/luda/templates/dev`.
```
RUN apt-get update && apt-get install -y --no-install-recommends \
vim sudo python-dev python-pip && \
rm -rf /var/lib/apt/lists/*
RUN pip install luda
```
The developer option `--dev` is a special case of `--template dev`. Running the following commands performs a one-time
extensions of the `nvidia/cuda:8.0-devel` image with the `Dockerfile` above. The new images generated will be
`luda/nvidia-cuda-8.0-devel:dev` or `luda/{{ base_image }}:{{ template }}` where `base_image` has all `/` and `:` replaced
with `-`.
```
luda --dev nvidia/cuda:8.0-devel
```
```
luda --template dev nvidia/cuda:8.0-devel
```
The first time this command is invoked `luda/nvidia-cuda-8.0-devel:dev` will be created. Subsequent invocation will
either update the image if either the base image (`nvidia/cuda:8.0-devel`) or the template directory
(`~/.config/luda/templates/dev`) has detected changes.
## Acknowledgements
Thanks to [Deni Bertovic's
blog](https://denibertovic.com/posts/handling-permissions-with-docker-volumes/).
`luda` provides very similar functionality but does not require specially
crafted base images and wraps the details of the docker command-line.
The project contains a copy of [`su-exec`](https://github.com/ncopa/su-exec).
Copyright reproduced below.
```
The MIT License (MIT)
Copyright (c) 2015 ncopa
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.
```
=======
History
=======
0.1.0 (2017-03-07)
------------------
* First release on PyPI.
0.4.0 (2017-06-01)
------------------
* Added configurable abbreviations to simply long image names
* Added templates to extend images from reusable templated Dockerfiles
* Added entrypoint and command inspection on the base_image to ensure the correct scripts/commands
executed on container launch
* Removed --docker_run_args and replaced with luda managed `--rm`, `-d`, `-t`, `-i` options which map
directly to the docker equivalents
* Improved landing page documentation (still more needs to be done)
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