CONTAINERS
arrow:14.0.1 |
|
---|---|
Aliases | arrow |
Requires | L4T ['>=32.6'] |
Dependencies | build-essential cuda python cmake |
Dockerfile | Dockerfile |
Notes | installed under /usr/local |
arrow:12.0.1 |
|
---|---|
Requires | L4T ['>=32.6'] |
Dependencies | build-essential cuda python cmake |
Dockerfile | Dockerfile |
Notes | installed under /usr/local |
arrow:5.0.0 |
|
---|---|
Requires | L4T ['>=32.6'] |
Dependencies | build-essential cuda python cmake |
Dockerfile | Dockerfile |
Notes | installed under /usr/local |
RUN CONTAINER
To start the container, you can use jetson-containers run
and autotag
, or manually put together a docker run
command:
# automatically pull or build a compatible container image
jetson-containers run $(autotag arrow)
# or if using 'docker run' (specify image and mounts/ect)
sudo docker run --runtime nvidia -it --rm --network=host arrow:35.2.1
jetson-containers run
forwards arguments todocker run
with some defaults added (like--runtime nvidia
, mounts a/data
cache, and detects devices)
autotag
finds a container image that's compatible with your version of JetPack/L4T - either locally, pulled from a registry, or by building it.
To mount your own directories into the container, use the -v
or --volume
flags:
jetson-containers run -v /path/on/host:/path/in/container $(autotag arrow)
To launch the container running a command, as opposed to an interactive shell:
jetson-containers run $(autotag arrow) my_app --abc xyz
You can pass any options to it that you would to docker run
, and it'll print out the full command that it constructs before executing it.
BUILD CONTAINER
If you use autotag
as shown above, it'll ask to build the container for you if needed. To manually build it, first do the system setup, then run:
jetson-containers build arrow
The dependencies from above will be built into the container, and it'll be tested during. Run it with --help
for build options.