About internal version, this is pure speculation, based on idea that TPU are programmed with some framework, thus out should be TF, thus there is closed part and there should (could) be others.
Regarding internal version: we built TensorFlow to support devices as modular plugins: the CPU and GPU devices are built this way (you can read the source code to see how device registration works), and the same registration mechanism is used for the TPU code, which can't be opensourced due to internal dependencies. Internal customers just link in an additional library to get TPU support, but it still uses the same core codebase that is available in the opensource world. I know this because I wrote a lot of the device modularity and TPU binding code :)
I'd really like to talk more about birth Tensorflow and TPU, but unfortunately I won't come to OSCON. May be some other time :)