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* remove the need for hparams * remove the need for hparams * remove the need for hparams * remove the need for hparams * replace self.hparams * replace self.hparams * replace self.hparams * replace self.hparams * replace self.hparams * replace self.hparams * replace self.hparams * replace self.hparams * replace self.hparams * replace self.hparams * replace self.hparams * replace self.hparams * replace self.hparams * replace self.hparams * replace self.hparams * replace self.hparams * replace self.hparams * replace self.hparams * replace self.hparams * replace self.hparams * replace self.hparams * replace self.hparams * replace self.hparams * replace self.hparams * replace self.hparams * replace self.hparams * replace self.hparams * replace self.hparams * replace self.hparams * replace self.hparams * replace self.hparams * replace self.hparams * fixed * fixed * fixed * fixed * fixed * fixed * fixed * fixed * fixed * fixed * fixed * fixed * fixed * fixed * finished moco * basic * testing * todo * recurse * hparams * persist * hparams * chlog * tests * tests * tests * tests * tests * tests * review * saving * tests * tests * tests * docs * finished moco * hparams * review * Apply suggestions from code review Co-authored-by: Adrian Wälchli <aedu.waelchli@gmail.com> * hparams * overwrite * transform * transform * transform * transform * cleaning * cleaning * tests * examples * examples * examples * Apply suggestions from code review Co-authored-by: Adrian Wälchli <aedu.waelchli@gmail.com> * chp key * tests * Apply suggestions from code review * class * updated docs * updated docs * updated docs * updated docs * save * wip * fix * flake8 Co-authored-by: Jirka <jirka@pytorchlightning.ai> Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com> Co-authored-by: Adrian Wälchli <aedu.waelchli@gmail.com>
Examples
This folder has 3 sections:
Basic Examples
Use these examples to test how lightning works.
Test on CPU
python cpu_template.py
Train on a single GPU
python gpu_template.py --gpus 1
DataParallel (dp)
Train on multiple GPUs using DataParallel.
python gpu_template.py --gpus 2 --distributed_backend dp
DistributedDataParallel (ddp)
Train on multiple GPUs using DistributedDataParallel
python gpu_template.py --gpus 2 --distributed_backend ddp
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:
- Log into the jumphost node of your SLURM-managed cluster.
- Create a conda environment with Lightning and a GPU PyTorch version.
- 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
Domain templates
These are templates to show common approaches such as GANs and RL.