Adding backend plugin

[TML]

Hi All,

We are looking to make a backend for our accelerator using XLA. 

This question is more of a set up question rather then a theoretical question. To add a new plugin, so far I made a new folder in the compiler/plugin dir for my backend and copied all the files from the compiler/xla/service/cpu (as a starting point). I am no so familiar with bazel (I come from a hardware design background) so I was wondering if anyone has integrated a new backend to XLA and would give me some pointers on which BUILD files to touch so that I can integrate my plugin to XLA. 

Thanks,

[Bjarke Roune]

This is a little hard to answer in general. You might start by taking one of the XLA CPU tests, note how it pulls in the CPU backend in Bazel and then put in your backend instead.

[Kay Zhu]

A possibly simpler example to look at would be the XLA Interpreter backend at  https://github.com/tensorflow/tensorflow/tree/7de939bb74c5edbc2f45e77a5d4696e70bb59e5b/tensorflow/compiler/xla/service/interpreter

This commit could shows necessary changes for this to work: https://github.com/tensorflow/tensorflow/commit/7de939bb74c5edbc2f45e77a5d4696e70bb59e5b

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Kay Zhu | SWE | kay...@google.com | 650-919-3795

[TML]

Thank you Kay! 

Really helpfull, was able to integrate and build. Plus learned a whole lot about Bazel. 

[TML]

In case anyone wants to check it they have successfully added the device:

python -c 'import tensorflow as tf; from tensorflow.python.client import device_lib;  print(tf.__version__); print (device_lib.list_local_devices()); '