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Welcome to ⚡ PyTorch Lightning
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:alt: Animation showing how to convert standard training code to Lightning
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PyTorch Lightning is the deep learning framework for professional AI researchers and machine learning engineers who need maximal flexibility without sacrificing performance at scale.
Lightning evolves with you as your projects go from idea to paper/production.
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Install Lightning
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Pip users
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pip install 'lightning'
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Conda users
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conda install pytorch-lightning -c conda-forge
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Or read the `advanced install guide <starter/installation.html> `_
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We are fully compatible with any stable PyTorch version v1.11 and above.
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Get Started
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:description: Learn the 7 key steps of a typical Lightning workflow.
:header: Lightning in 15 minutes
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:button_link: starter/introduction.html
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:description: Learn how to benchmark PyTorch Lightning.
:header: Benchmarking
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Current Lightning Users
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:description: Learn Lightning in small bites at 4 levels of expertise: Introductory, intermediate, advanced and expert.
:header: Level Up!
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:description: Detailed description of API each package. Assumes you already have basic Lightning knowledge.
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:header: API Reference
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:description: From NLP, Computer vision to RL and meta learning - see how to use Lightning in ALL research areas.
:header: Hands-on Examples
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:description: Learn how to do everything from hyper-parameters sweeps to cloud training to Pruning and Quantization with Lightning.
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:header: Common Workflows
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:description: Convert your current code to Lightning
:header: Convert code to PyTorch Lightning
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:maxdepth: 1
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:name: start
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:caption: Get Started
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starter/introduction
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starter/installation
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upgrade/migration_guide
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:maxdepth: 2
:name: levels
:caption: Level Up
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levels/core_skills
levels/intermediate
levels/advanced
levels/expert
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:maxdepth: 2
:name: pl_docs
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:caption: Core API
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common/lightning_module
common/trainer
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:maxdepth: 2
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:name: api
:caption: API Reference
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api_references
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:maxdepth: 1
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:name: Common Workflows
:caption: Common Workflows
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Avoid overfitting <common/evaluation>
model/build_model.rst
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cli/lightning_cli
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common/progress_bar
deploy/production
advanced/training_tricks
tuning/profiler
Manage experiments <visualize/logging_intermediate>
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Organize existing PyTorch into Lightning <starter/converting>
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clouds/cluster
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Save and load model progress <common/checkpointing>
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Save memory with half-precision <common/precision>
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advanced/model_parallel
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Train on single or multiple GPUs <accelerators/gpu>
Train on single or multiple HPUs <accelerators/hpu>
Train on single or multiple IPUs <accelerators/ipu>
Train on single or multiple TPUs <accelerators/tpu>
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Train on MPS <accelerators/mps>
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Use a pretrained model <advanced/pretrained>
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data/data
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model/own_your_loop
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.. toctree ::
:maxdepth: 1
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:name: Glossary
:caption: Glossary
Accelerators <extensions/accelerator>
Callback <extensions/callbacks>
Checkpointing <common/checkpointing>
Cluster <clouds/cluster>
Cloud checkpoint <common/checkpointing_advanced>
Console Logging <common/console_logs>
Debugging <debug/debugging>
Early stopping <common/early_stopping>
Experiment manager (Logger) <visualize/experiment_managers>
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Finetuning <advanced/finetuning>
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Flash <https://lightning-flash.readthedocs.io/en/stable/>
GPU <accelerators/gpu>
Half precision <common/precision>
HPU <accelerators/hpu>
Inference <deploy/production_intermediate>
IPU <accelerators/ipu>
Lightning CLI <cli/lightning_cli>
LightningDataModule <data/datamodule>
LightningModule <common/lightning_module>
Log <visualize/loggers>
TPU <accelerators/tpu>
Metrics <https://torchmetrics.readthedocs.io/en/stable/>
Model <model/build_model.rst>
Model Parallel <advanced/model_parallel>
Plugins <extensions/plugins>
Progress bar <common/progress_bar>
Production <deploy/production_advanced>
Predict <deploy/production_basic>
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Pretrained models <advanced/pretrained>
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Profiler <tuning/profiler>
Pruning and Quantization <advanced/pruning_quantization>
Remote filesystem and FSSPEC <common/remote_fs>
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Strategy <extensions/strategy>
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Strategy registry <advanced/strategy_registry>
Style guide <starter/style_guide>
SWA <advanced/training_tricks>
SLURM <clouds/cluster_advanced>
Transfer learning <advanced/transfer_learning>
Trainer <common/trainer>
Torch distributed <clouds/cluster_intermediate_2>
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:maxdepth: 1
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:name: Hands-on Examples
:caption: Hands-on Examples
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:glob:
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notebooks/**/*
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:name: Community
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:caption: Community
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generated/CODE_OF_CONDUCT.md
generated/CONTRIBUTING.md
generated/BECOMING_A_CORE_CONTRIBUTOR.md
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governance
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versioning
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past_versions
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generated/CHANGELOG.md
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