166 lines
5.6 KiB
ReStructuredText
166 lines
5.6 KiB
ReStructuredText
:orphan:
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Common use cases
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================
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.. include:: links.rst
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.. raw:: html
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<div class="tutorials-callout-container">
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<div class="row">
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.. Add callout items below this line
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.. customcalloutitem::
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:description: Learn to train Lightning models on the cloud
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:header: Cloud Training
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:button_link: clouds/cloud_training.html
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:card_style: text-container-small
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.. customcalloutitem::
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:description: Lightning checkpoints have everything you need to save and restore your models
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:header: Checkpointing
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:button_link: common/checkpointing.html
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:card_style: text-container-small
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.. customcalloutitem::
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:description: Learn to train on your university or company's cluster
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:header: Cluster Training
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:button_link: clouds/cluster.html
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:card_style: text-container-small
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.. customcalloutitem::
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:description: Tricks for debugging your Lightning Models
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:header: Debugging
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:button_link: common/debugging.html
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:card_style: text-container-small
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.. customcalloutitem::
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:description: Save time and money by training until key metrics stop improving or time has elapsed
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:header: Early Stopping
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:button_link: common/early_stopping.html
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:card_style: text-container-small
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.. customcalloutitem::
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:description: Here you'll find the latest SOTA training techniques such as SWA, accumulated gradients, etc...
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:header: Effective Training Techniques
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:button_link: advanced/training_tricks.html
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:card_style: text-container-small
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.. customcalloutitem::
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:description: Avoid over-fitting (memorizing the dataset) with these techniques
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:header: Evaluation
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:button_link: common/evaluation.html
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:card_style: text-container-small
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.. customcalloutitem::
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:description: Before coding a complex model, use lightning-flash to create a baseline in a few lines of code
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:header: Fast Baselines
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:button_link: ecosystem/flash.html
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:card_style: text-container-small
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.. customcalloutitem::
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:description: Enable fault-tolerant training in clusters/clouds where machines might fail (ie: pre-emtible machines)
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:header: Fault-Tolerant Training
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:button_link: advanced/fault_tolerant_training.html
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:card_style: text-container-small
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.. customcalloutitem::
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:description: Make your models more flexible by enabling command-line arguments
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:header: Hyperparameters (via command-line)
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:button_link: common/hyperparameters.html
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:card_style: text-container-small
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.. customcalloutitem::
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:description: Use the latest tricks to easily productionize your Lightning models
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:header: Inference in Production
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:button_link: common/production_inference.html
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:card_style: text-container-small
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.. customcalloutitem::
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:description: Reduce configuration boilerplate with the Lightning CLI
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:header: Lightning CLI
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:button_link: common/lightning_cli.html
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:card_style: text-container-small
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.. customcalloutitem::
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:description: Visualize your machine learning experiments with these experiment managers
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:header: Loggers (experiment managers)
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:button_link: common/loggers.html
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:card_style: text-container-small
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.. customcalloutitem::
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:description: Use the model registry to mix and match your models and Datamodules
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:header: Model and Datamodule Registry
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:button_link: common/lightning_cli.html#multiple-models-and-or-datasets
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:card_style: text-container-small
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.. customcalloutitem::
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:description: Train 1TB+ parameter models with these advanced built-in techniques
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:header: Model Parallelism
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:button_link: advanced/model_parallel.html
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:card_style: text-container-small
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.. customcalloutitem::
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:description: Increase batch-sizes and improve speeds by training using 16-bit precision and more
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:header: N-Bit Precision
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:button_link: advanced/precision.html
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:card_style: text-container-small
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.. customcalloutitem::
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:description: Enable manual optimization to fully control the optimization procedure for advanced research
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:header: Manual Optimization
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:button_link: common/optimization.html
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:card_style: text-container-small
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.. customcalloutitem::
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:description: Use these profilers to find bottlenecks in your model
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:header: Profiling
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:button_link: advanced/profiler.html
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:card_style: text-container-small
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.. customcalloutitem::
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:description: Use these built-in progress bars or learn how to make your own!
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:header: Progress Bar
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:button_link: common/progress_bar.html
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:card_style: text-container-small
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.. customcalloutitem::
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:description: Compress model sizes to speed up model inference for deployment without loss of performance (accuracy)
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:header: Pruning and Quantization
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:button_link: advanced/pruning_quantization.html
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:card_style: text-container-small
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.. customcalloutitem::
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:description: Work with data on any local or cloud filesystem such as S3 on AWS, GCS on Google Cloud, or ADL on Azure
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:header: Remote Filesystems
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:button_link: common/remote_fs.html
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:card_style: text-container-small
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.. customcalloutitem::
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:description: Building the next Deepspeed, FSDP or fancy scaling technique? Add them to Lightning here
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:header: Strategy Registry
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:button_link: advanced/strategy_registry.html
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:card_style: text-container-small
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.. customcalloutitem::
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:description: Simplify metrics calculations to scale-proof your models
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:header: Torchmetrics
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:button_link: ecosystem/metrics.html
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:card_style: text-container-small
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.. customcalloutitem::
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:description: Use models training on large datasets to achieve better results when you don't have much data
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:header: Transfer Learning (finetuning)
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:button_link: advanced/transfer_learning.html
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:card_style: text-container-small
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.. raw:: html
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</div>
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</div>
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.. End of callout item section
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