pytorch-lightning

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# Copyright The Lightning AI team.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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#     http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import time
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__author__ = "Lightning AI et al."
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__author_email__ = "pytorch@lightning.ai"
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__license__ = "Apache-2.0"
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__copyright__ = f"Copyright (c) 2018-{time.strftime('%Y')}, {__author__}."
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__homepage__ = "https://github.com/Lightning-AI/lightning"
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__docs_url__ = "https://lightning.ai/docs/pytorch/stable/"
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# this has to be simple string, see: https://github.com/pypa/twine/issues/522
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__docs__ = (
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    "PyTorch Lightning is the lightweight PyTorch wrapper for ML researchers."
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    " Scale your models. Write less boilerplate."
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)
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__long_docs__ = """
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Lightning is a way to organize your PyTorch code to decouple the science code from the engineering.
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 It's more of a style-guide than a framework.
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In Lightning, you organize your code into 3 distinct categories:
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1. Research code (goes in the LightningModule).
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2. Engineering code (you delete, and is handled by the Trainer).
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3. Non-essential research code (logging, etc. this goes in Callbacks).
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Although your research/production project might start simple, once you add things like GPU AND TPU training,
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 16-bit precision, etc, you end up spending more time engineering than researching.
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 Lightning automates AND rigorously tests those parts for you.
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Overall, Lightning guarantees rigorously tested, correct, modern best practices for the automated parts.
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Documentation
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-------------
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- https://lightning.ai/docs/pytorch/en/latest
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- https://lightning.ai/docs/pytorch/en/stable
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"""
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__all__ = [
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    "__author__",
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    "__author_email__",
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    "__copyright__",
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    "__docs__",
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    "__docs_url__",
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    "__homepage__",
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    "__license__",
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]
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