examples/pytorch/basics/README.md
Use these examples to test how Lightning works.
This script shows you how to implement a CNN auto-encoder.
# CPU
python autoencoder.py
# GPUs (any number)
python autoencoder.py --trainer.accelerator 'gpu' --trainer.devices 2
# Distributed Data Parallel (DDP)
python autoencoder.py --trainer.accelerator 'gpu' --trainer.devices 2 --trainer.strategy 'ddp'
This script shows you how to implement a LightningModule as a system.
A system describes a LightningModule which takes a single torch.nn.Module which makes exporting to producion simpler.
# CPU
python backbone_image_classifier.py
# GPUs (any number)
python backbone_image_classifier.py --trainer.accelerator 'gpu' --trainer.devices 2
# Distributed Data Parallel (DDP)
python backbone_image_classifier.py --trainer.accelerator 'gpu' --trainer.devices 2 --trainer.strategy 'ddp'
This example contains a simple training loop for next-word prediction with a Transformer model on a subset of the WikiText2 dataset.
python transformer.py
This script shows you how to activate the PyTorch Profiler with Lightning.
python profiler_example.py