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Seed all workers when using DDP #7942

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merged 8 commits into from
Jun 14, 2021
Merged

Seed all workers when using DDP #7942

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3c1fb2b
Seed all workers when using DDP
senarvi Jun 11, 2021
e7a9546
Fix to dataloader seeding
senarvi Jun 11, 2021
52b94b3
Make argument name explicit
senarvi Jun 13, 2021
2ffe83a
Use f-strings when logging
senarvi Jun 13, 2021
dcd2536
Merge branch 'bugfix/seed-ddp-workers' of github.com:groke-technologi…
senarvi Jun 13, 2021
737e2e9
Merge branch 'master' into bugfix/seed-ddp-workers
senarvi Jun 13, 2021
e3fc299
Removed a redundant log message
senarvi Jun 14, 2021
ee0a16b
Merge branch 'master' into bugfix/seed-ddp-workers
senarvi Jun 14, 2021
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3 changes: 3 additions & 0 deletions CHANGELOG.md
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Expand Up @@ -211,6 +211,9 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).

### Fixed

- Fixed setting `worker_init_fn` to seed dataloaders correctly when using DDP ([#7942](https://github.com/PyTorchLightning/pytorch-lightning/pull/7942))


- Fixed `DataModule.prepare_data` could only be called on the global rank 0 process ([#7945](https://github.com/PyTorchLightning/pytorch-lightning/pull/7945))


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6 changes: 5 additions & 1 deletion pytorch_lightning/utilities/seed.py
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Expand Up @@ -84,8 +84,9 @@ def reset_seed() -> None:
If :func:`pytorch_lightning.utilities.seed.seed_everything` is unused, this function will do nothing.
"""
seed = os.environ.get("PL_GLOBAL_SEED", None)
workers = os.environ.get("PL_SEED_WORKERS", False)
if seed is not None:
seed_everything(int(seed))
seed_everything(int(seed), workers=bool(workers))


def pl_worker_init_function(worker_id: int, rank: Optional = None) -> None: # pragma: no cover
Expand All @@ -100,6 +101,9 @@ def pl_worker_init_function(worker_id: int, rank: Optional = None) -> None: # p
process_seed = torch.initial_seed()
# back out the base seed so we can use all the bits
base_seed = process_seed - worker_id
log.debug(
f'Initializing random number generators of process {global_rank} worker {worker_id} with base seed {base_seed}'
)
ss = np.random.SeedSequence([base_seed, worker_id, global_rank])
# use 128 bits (4 x 32-bit words)
np.random.seed(ss.generate_state(4))
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