73 lines
2.2 KiB
ReStructuredText
73 lines
2.2 KiB
ReStructuredText
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.. _installation:
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############
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Installation
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############
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--------------
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*********************
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Installation with pip
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*********************
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Install any supported version of PyTorch if you want from `PyTorch Installation Page <https://pytorch.org/get-started/locally/#start-locally>`_.
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Now you can install using `pip <https://pypi.org/project/pytorch-lightning/>`_ using the following command:
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.. code-block:: bash
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pip install pytorch-lightning
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--------------
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***********************
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Installation with Conda
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***********************
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If you don't have conda installed, follow the `Conda Installation Guide <https://docs.conda.io/projects/conda/en/latest/user-guide/install>`_.
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Lightning can be installed with `conda <https://anaconda.org/conda-forge/pytorch-lightning>`_ using the following command:
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.. code-block:: bash
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conda install pytorch-lightning -c conda-forge
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You can also use `Conda Environments <https://docs.conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html>`_:
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.. code-block:: bash
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conda activate my_env
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conda install pytorch-lightning -c conda-forge
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--------------
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************************
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Installation from Source
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************************
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Install nightly from the source. Note that it contains all the bug fixes and newly released features that
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are not published yet. This is the bleeding edge, so use it at your own discretion.
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.. code-block:: bash
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pip install https://github.com/PyTorchLightning/pytorch-lightning/archive/master.zip
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Install future patch releases from the source. Note that the patch release contains only the bug fixes for the recent major release.
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.. code-block:: bash
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pip install https://github.com/PyTorchLightning/pytorch-lightning/archive/refs/heads/release/1.5.x.zip
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--------------
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******************
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Lightning Coverage
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******************
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PyTorch Lightning is maintained and tested on different Python and PyTorch versions.
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Check out the `CI Coverage <https://github.com/PyTorchLightning/pytorch-lightning#continuous-integration>`_ for more info.
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It is rigorously tested across multiple GPUs, TPUs, CPUs and IPUs. GPU tests run on two NVIDIA P100. TPU tests run on Google GKE TPUv2/3.
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TPU py3.7 means we support Colab and Kaggle env. IPU tests run on MK1 IPU boxes.
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