Deep learning framework (PyTorch Lightning / lightning package). Organize PyTorch code into LightningModules, configure Trainers for multi-GPU/TPU, implement data pipelines, callbacks, logging (W&B, TensorBoard, MLflow), distributed training (DDP, FSDP, DeepSpeed), for scalable
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Deep learning framework (PyTorch Lightning / lightning package). Organize PyTorch code into LightningModules, configure Trainers for multi-GPU/TPU, implement data pipelines, callbacks, logging (W&B, TensorBoard, MLflow), distributed training (DDP, FSDP, DeepSpeed), for scalable
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</> SKILL.md
pytorch-lightning.SKILL.md
---name: pytorch-lightning
description: Deep learning framework (PyTorch Lightning / lightning package). Organize PyTorch code into LightningModules, configure Trainers for multi-GPU/TPU, implement data pipelines, callbacks, logging (W&B, TensorBoard, MLflow), distributed training (DDP, FSDP, DeepSpeed), for scalable neural network training.
allowed-tools: Read Write Edit Bash
license: Apache-2.0 license
compatibility: Requires Python 3.10+ and lightning 2.6+ (or pytorch-lightning 2.6+). GPU training needs CUDA-capable PyTorch. Optional loggers (wandb, mlflow, comet-ml) and DeepSpeed require separate installs.
metadata: {"version": "1.0", "skill-author": "K-Dense Inc."}
---# PyTorch Lightning
## Overview
PyTorch Lightning is a deep learning framework that organizes PyTorch code to eliminate boilerplate while maintaining full flexibility. Automate training workflows, multi-device orchestration, and implement best practices for neural network training and scaling across multiple GPUs/TPUs.
**Current upstream:** lightning 2.6.4 (PyPI, May 2026). Docs: [lightning.ai/docs/pytorch/stable](https://lightning.ai/docs/pytorch/stable/). Use `import lightning as L` (the `pytorch-lightning` package name still installs the same library).
## Installation
```bash
uv pip install lightning
```
Optional extras:
```bash
