lightning/docs/source-pytorch/glossary/index.rst

358 lines
11 KiB
ReStructuredText

.. toctree::
:maxdepth: 1
:hidden:
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>
DeepSpeed <../advanced/model_parallel/deepspeed>
Distributed Checkpoints <../common/checkpointing_expert>
Early stopping <../common/early_stopping>
Experiment manager (Logger) <../visualize/experiment_managers>
Finetuning <../advanced/finetuning>
FSDP <../advanced/model_parallel/fsdp>
GPU <../accelerators/gpu>
Half precision <../common/precision>
HPU <../integrations/hpu/index>
Inference <../deploy/production_intermediate>
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>
Pretrained models <../advanced/pretrained>
Profiler <../tuning/profiler>
Pruning and Quantization <../advanced/pruning_quantization>
Remote filesystem and FSSPEC <../common/remote_fs>
Strategy <../extensions/strategy>
Strategy registry <../advanced/strategy_registry>
Strategy integrations <../integrations/strategies/index>
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>
Warnings <../advanced/warnings>
########
Glossary
########
.. raw:: html
<div class="display-card-container">
<div class="row">
.. displayitem::
:header: Accelerators
:description: Accelerators connect the Trainer to hardware to train faster
:col_css: col-md-12
:button_link: ../extensions/accelerator.html
:height: 100
.. displayitem::
:header: Callback
:description: Add self-contained extra functionality during training execution
:col_css: col-md-12
:button_link: ../extensions/callbacks.html
:height: 100
.. displayitem::
:header: Checkpointing
:description: Save and load progress with checkpoints
:col_css: col-md-12
:button_link: ../common/checkpointing.html
:height: 100
.. displayitem::
:header: Cluster
:description: Run on your own group of servers
:col_css: col-md-12
:button_link: ../clouds/cluster.html
:height: 100
.. displayitem::
:header: Cloud checkpoint
:description: Save your models to cloud filesystems
:col_css: col-md-12
:button_link: ../common/checkpointing_advanced.html
:height: 100
.. displayitem::
:header: Console Logging
:description: Capture more visible logs
:col_css: col-md-12
:button_link: ../common/console_logs.html
:height: 100
.. displayitem::
:header: Debugging
:description: Fix errors in your code
:col_css: col-md-12
:button_link: ../debug/debugging.html
:height: 100
.. displayitem::
:header: DeepSpeed
:description: Distribute models with billions of parameters across hundreds GPUs
:col_css: col-md-12
:button_link: ../advanced/model_parallel/deepspeed.html
:height: 100
.. displayitem::
:header: Distributed Checkpoints
:description: Save and load very large models efficiently with distributed checkpoints
:col_css: col-md-12
:button_link: ../common/checkpointing_expert.html
:height: 100
.. displayitem::
:header: Early stopping
:description: Stop the training when no improvement is observed
:col_css: col-md-12
:button_link: ../common/early_stopping.html
:height: 100
.. displayitem::
:header: Experiment manager (Logger)
:description: Tools for tracking and visualizing artifacts and logs
:col_css: col-md-12
:button_link: ../visualize/experiment_managers.html
:height: 100
.. displayitem::
:header: Finetuning
:description: Technique for training pretrained models
:col_css: col-md-12
:button_link: ../advanced/finetuning.html
:height: 100
.. displayitem::
:header: FSDP
:description: Distribute models with billions of parameters across hundreds GPUs
:col_css: col-md-12
:button_link: ../advanced/model_parallel/fsdp.html
:height: 100
.. displayitem::
:header: GPU
:description: Graphics Processing Unit for faster training
:col_css: col-md-12
:button_link: ../accelerators/gpu.html
:height: 100
.. displayitem::
:header: Half precision
:description: Using different numerical formats to save memory and run faster
:col_css: col-md-12
:button_link: ../common/precision.html
:height: 100
.. displayitem::
:header: HPU
:description: Habana Gaudi AI Processor Unit for faster training
:col_css: col-md-12
:button_link: ../integrations/hpu/index.html
:height: 100
.. displayitem::
:header: Inference
:description: Making predictions by applying a trained model to unlabeled examples
:col_css: col-md-12
:button_link: ../deploy/production_intermediate.html
:height: 100
.. displayitem::
:header: Lightning CLI
:description: A Command-line Interface (CLI) to interact with Lightning code via a terminal
:col_css: col-md-12
:button_link: ../cli/lightning_cli.html
:height: 100
.. displayitem::
:header: LightningDataModule
:description: A shareable, reusable class that encapsulates all the steps needed to process data
:col_css: col-md-12
:button_link: ../data/datamodule.html
:height: 100
.. displayitem::
:header: LightningModule
:description: A base class organizug your neural network module
:col_css: col-md-12
:button_link: ../common/lightning_module.html
:height: 100
.. displayitem::
:header: Log
:description: Outputs or results used for visualization and tracking
:col_css: col-md-12
:button_link: ../visualize/loggers.html
:height: 100
.. displayitem::
:header: Metrics
:description: A statistic used to measure performance or other objectives we want to optimize
:col_css: col-md-12
:button_link: https://torchmetrics.readthedocs.io/en/stable/
:height: 100
.. displayitem::
:header: Model
:description: The set of parameters and structure for a system to make predictions
:col_css: col-md-12
:button_link: ../model/build_model.html
:height: 100
.. displayitem::
:header: Model Parallelism
:description: A way to scale training that splits a model between multiple devices.
:col_css: col-md-12
:button_link: ../advanced/model_parallel.html
:height: 100
.. displayitem::
:header: Plugins
:description: Custom trainer integrations such as custom precision, checkpointing or cluster environment implementation
:col_css: col-md-12
:button_link: ../extensions/plugins.html
:height: 100
.. displayitem::
:header: Progress bar
:description: Output printed to the terminal to visualize the progression of training
:col_css: col-md-12
:button_link: ../common/progress_bar.html
:height: 100
.. displayitem::
:header: Production
:description: Using ML models in real world systems
:col_css: col-md-12
:button_link: ../deploy/production_advanced.html
:height: 100
.. displayitem::
:header: Prediction
:description: Computing a model's output
:col_css: col-md-12
:button_link: ../deploy/production_basic.html
:height: 100
.. displayitem::
:header: Pretrained models
:description: Models that have already been trained for a particular task
:col_css: col-md-12
:button_link: ../advanced/pretrained.html
:height: 100
.. displayitem::
:header: Profiler
:description: Tool to identify bottlenecks and performance of different parts of a model
:col_css: col-md-12
:button_link: ../tuning/profiler.html
:height: 100
.. displayitem::
:header: Pruning
:description: A technique to eliminae some of the model weights to reduce the model size and decrease inference requirements
:col_css: col-md-12
:button_link: ../advanced/pruning_quantization.html
:height: 100
.. displayitem::
:header: Quantization
:description: A technique to accelerate the model inference speed and decrease the memory load while still maintaining the model accuracy
:col_css: col-md-12
:button_link: ../advanced/post_training_quantization.html
:height: 100
.. displayitem::
:header: Remote filesystem and FSSPEC
:description: Accessing files from cloud storage providers
:col_css: col-md-12
:button_link: ../common/remote_fs.html
:height: 100
.. displayitem::
:header: Strategy
:description: Ways the trainer controls the model distribution across training, evaluation, and prediction
:col_css: col-md-12
:button_link: ../extensions/strategy.html
:height: 100
.. displayitem::
:header: Strategy registry
:description: A class that holds information about training strategies and allows adding new custom strategies
:col_css: col-md-12
:button_link: ../advanced/strategy_registry.html
:height: 100
.. displayitem::
:header: Style guide
:description: Best practices to improve readability and reproducibility
:col_css: col-md-12
:button_link: ../starter/style_guide.html
:height: 100
.. displayitem::
:header: SWA
:description: Stochastic Weight Averaging (SWA) can make your models generalize better
:col_css: col-md-12
:button_link: ../advanced/training_tricks.html#stochastic-weight-averaging
:height: 100
.. displayitem::
:header: SLURM
:description: Simple Linux Utility for Resource Management, or simply Slurm, is a free and open-source job scheduler for Linux clusters
:col_css: col-md-12
:button_link: ../clouds/cluster_advanced.html
:height: 100
.. displayitem::
:header: Transfer learning
:description: Using pre-trained models to improve learning
:col_css: col-md-12
:button_link: ../advanced/transfer_learning.html
:height: 100
.. displayitem::
:header: Trainer
:description: The class that automates and customizes model training
:col_css: col-md-12
:button_link: ../common/trainer.html
:height: 100
.. displayitem::
:header: Torch distributed
:description: Setup for running on distributed environments
:col_css: col-md-12
:button_link: ../clouds/cluster_intermediate_2.html
:height: 100
.. displayitem::
:header: Warnings
:description: Disable false-positive warnings emitted by Lightning
:col_css: col-md-12
:button_link: ../advanced/warnings.html
:height: 100
.. raw:: html
</div>
</div>