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Remove the mention of XRT_TPU_CONFIG in the CONTRIBUTING.md #5379

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Jul 31, 2023
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Remove the mention of XRT_TPU_CONFIG in the CONTRIBUTING.md #5379

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19 changes: 10 additions & 9 deletions CONTRIBUTING.md
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Expand Up @@ -75,24 +75,25 @@ yapf --recursive -i *.py test/ scripts/ torch_xla/

To run the tests, follow __one__ of the options below:

* Run on local CPU using the XRT client:
* Run on local CPU:

```Shell
export XRT_DEVICE_MAP="CPU:0;/job:localservice/replica:0/task:0/device:XLA_CPU:0"
export XRT_WORKERS="localservice:0;grpc://localhost:40934"
export PJRT_DEVICE=CPU
```

Select any free TCP port you prefer instead of 40934 (totally arbitrary).
* Run on Cloud TPU:

* Run on Cloud TPU using the XRT client, set the XRT_TPU_CONFIG environment variable:
```Shell
export PJRT_DEVICE=TPU
```

* Run on GPU:

```Shell
export XRT_TPU_CONFIG="localservice;0;localhost:51011"
export PJRT_DEVICE=GPU GPU_NUM_DEVICES=${NUM_GPU}
```

Note that the IP of the TPU node can change if the TPU node is reset. If _PyTorch_
seem to hang at startup, verify that the IP of your TPU node is still the same of
the one you have configured.
For more detial on configuring the runtime, please refer to [this doc](https://github.com/pytorch/xla/blob/master/docs/pjrt.md#quickstart)

If you are planning to be building from source and hence using the latest _PyTorch/TPU_ code base,
it is suggested for you to select the _Nightly_ builds when you create a Cloud TPU instance.
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