44 lines
1.9 KiB
ReStructuredText
44 lines
1.9 KiB
ReStructuredText
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###############################
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Fault-tolerant Training (basic)
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###############################
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**Audience:** User who want to run on the cloud or a cluster environment.
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**Pre-requisites**: Users must have first read :doc:`Run on the cloud (basic) <run_basic>`
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----
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********************************
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What is fault-tolerant training?
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********************************
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When developing models on the cloud or cluster environments, you may be forced to restart from scratch in the event of a software or hardware failure (ie: a *fault*). Lightning models can run fault-proof.
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With Fault Tolerant Training, when ``Trainer.fit()`` fails in the middle of an epoch during training or validation,
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Lightning will restart exactly where it failed, and everything will be restored (down to the batch it was on even if the dataset was shuffled).
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.. warning:: Fault-tolerant Training is currently an experimental feature within Lightning.
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----
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***************************************************
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Use fault-tolerance to save money on cloud training
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***************************************************
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Cloud providers offer pre-emptible machines which can be priced as low as 1/10th the cost but can be shut-down automatically at any time.
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Because fault-tolerant training can automatically recover from an interruption, you can train models for many weeks/months at a time for the pre-emptible prices.
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To easily run on the cloud with fault-tolerance with lightning-grid, use the following arguments:
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.. code-block:: bash
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grid run --use_spot --auto_resume lightning_script.py
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The ``--use_spot`` argument enables cheap preemptible pricing (but the machines that can be interrupted).
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If the machine is interrupted, the ``--auto_resume`` argument automatically restarts the machine.
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As long as you are running a script that runs a lightning model, the model will restore itself and handle all the details of fault tolerance.
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----
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.. include:: grid_costs.rst
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