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protobuf_cpp

CONTAINERS IMAGES RUN BUILD

CONTAINERS
protobuf:cpp
   Aliases protobuf
   Builds protobuf-cpp_jp51 protobuf-cpp_jp46
   Requires L4T >=32.6
   Dependencies build-essential python
   Dependants audiocraft l4t-ml l4t-tensorflow:tf1 l4t-tensorflow:tf2 tensorflow tensorflow2
   Dockerfile Dockerfile
   Images dustynv/protobuf:cpp-r32.7.1 (2023-12-06, 0.5GB)
dustynv/protobuf:cpp-r35.2.1 (2023-12-06, 5.1GB)
dustynv/protobuf:cpp-r35.3.1 (2023-08-29, 5.1GB)
dustynv/protobuf:cpp-r35.4.1 (2023-10-07, 5.1GB)
   Notes build protobuf using cpp implementation (https://jkjung-avt.github.io/tf-trt-revisited/)
RUN CONTAINER

To start the container, you can use the run.sh/autotag helpers or manually put together a docker run command:

# automatically pull or build a compatible container image
./run.sh $(./autotag protobuf_cpp)

# or if using 'docker run' (specify image and mounts/ect)
sudo docker run --runtime nvidia -it --rm --network=host protobuf_cpp:35.2.1

run.sh forwards arguments to docker 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:

./run.sh -v /path/on/host:/path/in/container $(./autotag protobuf_cpp)

To launch the container running a command, as opposed to an interactive shell:

./run.sh $(./autotag protobuf_cpp) my_app --abc xyz

You can pass any options to run.sh 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:

./build.sh protobuf_cpp

The dependencies from above will be built into the container, and it'll be tested during. See ./build.sh --help for build options.