Platform dependency build systems are located in this folder. Dependencies are to be pre-built, and published to S3. To do so, they rely (ultimately) on running make build publish in a given directory. The goal is for this to be true on all target platforms (x86_64, arm64), though at this time it's only true for: tensorflowlite.
Items are built in docker images, for the target platform whenever possible. If needed (i.e a future planned MacOS build) items are built on the dedicated hardware. There are design wrinkles to each build. Though the ideal is to build a base docker (see the automata repository. That base docker is then used as the base build system injector for the dependency itself. A docker image is built from the base docker, accepting externalized variables such as the dependency version. Compilation of external requirements takes place in a build file, mounted inside the docker image.
Ideally a per-platform Docker file (i.e Dockerfile.x64, Dockerfile.arm) will exist in the underlying folder, assuming building within a docker is tenable.
The arm build of tflite currently occurs on jetson arm devices only, as portions of the root filesystem of the Jetson device are mounted during the build. Given the symlinks that exist on the device between things in /usr/lib to /etc/alternatives, and in turn to /usr/local/cuda, which is itself a symlink to /usr/local/cuda-10.2, this is the current philosophy.
WThe build_arm target in the Makefile describes the process in detail. The code to build the base docker build image can be found in the automata repository. The bazelbuilder image is published to the redisfab dockerhub repositories.