lightning/pl_examples/basic_examples

Basic Examples

Use these examples to test how lightning works.

Test on CPU

python cpu_template.py

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Train on a single GPU

python gpu_template.py --gpus 1

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DataParallel (dp)

Train on multiple GPUs using DataParallel.

python gpu_template.py --gpus 2 --distributed_backend dp

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DistributedDataParallel (ddp)

Train on multiple GPUs using DistributedDataParallel

python gpu_template.py --gpus 2 --distributed_backend ddp

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DistributedDataParallel+DP (ddp2)

Train on multiple GPUs using DistributedDataParallel + DataParallel. On a single node, uses all GPUs for 1 model. Then shares gradient information across nodes.

python gpu_template.py --gpus 2 --distributed_backend ddp2

Multi-node example

This demo launches a job using 2 GPUs on 2 different nodes (4 GPUs total). To run this demo do the following:

1. Log into the jumphost node of your SLURM-managed cluster.
2. Create a conda environment with Lightning and a GPU PyTorch version.
3. Choose a script to submit

DDP

Submit this job to run with DistributedDataParallel (2 nodes, 2 gpus each)

sbatch ddp_job_submit.sh YourEnv

DDP2

Submit this job to run with a different implementation of DistributedDataParallel. In this version, each node acts like DataParallel but syncs across nodes like DDP.

sbatch ddp2_job_submit.sh YourEnv