49 lines
1.7 KiB
ReStructuredText
49 lines
1.7 KiB
ReStructuredText
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.. _mps_basic:
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MPS training (basic)
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====================
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**Audience:** Users looking to train on their Apple silicon GPUs.
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.. warning::
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Both the MPS accelerator and the PyTorch backend are still experimental.
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As such, not all operations are currently supported. However, with ongoing development from the PyTorch team, an increasingly large number of operations are becoming available.
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You can use ``PYTORCH_ENABLE_MPS_FALLBACK=1 python your_script.py`` to fall back to cpu for unsupported operations.
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----
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What is Apple silicon?
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----------------------
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Apple silicon chips are a unified system on a chip (SoC) developed by Apple based on the ARM design.
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Among other things, they feature CPU-cores, GPU-cores, a neural engine and shared memory between all of these features.
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----
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So it's a CPU?
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--------------
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Apple silicon includes CPU-cores among several other features. However, the full potential for the hardware acceleration of which the M-Socs are capable is unavailable when running on the ``CPUAccelerator``. This is because they also feature a GPU and a neural engine.
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To use them, Lightning supports the ``MPSAccelerator``.
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----
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Run on Apple silicon gpus
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-------------------------
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Enable the following Trainer arguments to run on Apple silicon gpus (MPS devices).
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.. code::
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trainer = Trainer(accelerator="mps", devices=1)
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.. note::
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The ``MPSAccelerator`` only supports 1 device at a time. Currently there are no machines with multiple MPS-capable GPUs.
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----
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What does MPS stand for?
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------------------------
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MPS is short for `Metal Performance Shaders <https://developer.apple.com/metal/>`_ which is the technology used in the back for gpu communication and computing.
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