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Update TPU docs for installation #6794

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Apr 3, 2021
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Update TPU docs for installation #6794

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3 changes: 1 addition & 2 deletions docs/source/advanced/tpu.rst
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Expand Up @@ -64,8 +64,7 @@ To get a TPU on colab, follow these steps:

.. code-block::

!curl https://raw.githubusercontent.com/pytorch/xla/master/contrib/scripts/env-setup.py -o pytorch-xla-env-setup.py
!python pytorch-xla-env-setup.py --version 1.7 --apt-packages libomp5 libopenblas-dev
!pip install cloud-tpu-client==0.10 https://storage.googleapis.com/tpu-pytorch/wheels/torch_xla-1.8-cp37-cp37m-linux_x86_64.whl
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@Borda Borda Apr 1, 2021

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well here the XLA version shall be aligned with PT version, right?

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@kaushikb11 kaushikb11 Apr 1, 2021 •
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The instructions are for Colab & they have updated the runtime to use torch>=1.8.0

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@lezwon lezwon Apr 5, 2021

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does this same command work for kaggle?

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@kaushikb11 kaushikb11 Apr 5, 2021

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@lezwon Just checked. It's 1.7 for Kaggle notebooks.
We could add {torch.__version__} to the URL as a placeholder.


5. Once the above is done, install PyTorch Lightning (v 0.7.0+).

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4 changes: 1 addition & 3 deletions docs/source/starter/introduction_guide.rst
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Expand Up @@ -572,9 +572,7 @@ Next, install the required xla library (adds support for PyTorch on TPUs)

.. code-block:: shell

!curl https://raw.githubusercontent.com/pytorch/xla/master/contrib/scripts/env-setup.py -o pytorch-xla-env-setup.py

!python pytorch-xla-env-setup.py --version nightly --apt-packages libomp5 libopenblas-dev
!pip install cloud-tpu-client==0.10 https://storage.googleapis.com/tpu-pytorch/wheels/torch_xla-1.8-cp37-cp37m-linux_x86_64.whl

In distributed training (multiple GPUs and multiple TPU cores) each GPU or TPU core will run a copy
of this program. This means that without taking any care you will download the dataset N times which
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