WIP ML Build Docker container for ML repositories (Tensorflow, JAX and XLA).

This container branches off from
/tensorflow/tools/tf_sig_build_dockerfiles/. However, since
hermetic CUDA and hermetic Python is now available for Tensorflow, a lot of the
requirements installed on the original container can be removed to reduce the
footprint of the container and make it more reusable across different ML

  cp tensorflow/core/platform/ctstring.h \
    tensorflow/core/platform/ctstring_internal.h \
    ${LIB_PKG}/include/tensorflow/core/platform
  cp third_party/xla/xla/tsl/c/tsl_status.h ${LIB_PKG}/include/xla/tsl/c
  cp third_party/xla/third_party/tsl/tsl/platform/ctstring.h \
     third_party/xla/third_party/tsl/tsl/platform/ctstring_internal.h \
     ${LIB_PKG}/include/tsl/platform
  cd ${LIB_PKG}

reachable and exploitable through production-grade, benign models.

### Compilation

Compiling models via the recommended entry points described in
[XLA](https://www.tensorflow.org/xla) and
[JAX](https://jax.readthedocs.io/en/latest/jax-101/02-jitting.html)
documentation should be safe, while some of the testing and debugging tools that