idr_torch
Description
Permet de récupérer les variables SLURM afin de gérér le multi-GPU/multi-noeuds pour le parallélisme sur Pytorch.
import torch.distributed as dist
import idr_torch
if idr_torch.rank == 0:
print(">>> Training on ", len(idr_torch.nodelist), " nodes and ", idr_torch.world_size, " processes")
dist.init_process_group(backend='nccl',
init_method='env://',
world_size=idr_torch.world_size,
rank=idr_torch.rank)
Si on veut rajouter une nouvelle API, on peut la mettre dans le dossier api et l'importer dans le __init__.py. Ou alors on peut la coder n'importe où, et après appeler idr_torch.register_api(nouvelle_api).
Les nouvelles APIs doivent hériter de idr_torch.API. Si on veut faire en sorte que la MASTER_ADDR et le MASTER_PORT soit mis automatiquement (dans le cas où le lanceur ne le fait pas comme SLURM), alors il faut utiliser idr_torch.AutoMasterAddressPort comme décorateur de notre nouvelle API.
On patche aussi le profiler. Il suffit de remplacer from torch.profiler import ... par from idr_torch.profiler import ....
Note : idr_torch est compatible avec submitit.
Metadata
Release files for idr-torch 2.5.0
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Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
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| idr_torch-2.5.0.tar.gz | 11.6 kB | With provenance | Details |
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| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| idr_torch-2.5.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 26.4 kB
Release files / idr_torch-2.5.0.tar.gz
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| Tags | Python 3 |
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