seed¶
Functions
A context manager that resets the global random state on exit to what it was before entering. |
|
The worker_init_fn that Lightning automatically adds to your dataloader if you previously set set the seed with |
|
Reset the seed to the value that |
|
Function that sets seed for pseudo-random number generators in: pytorch, numpy, python.random In addition, sets the following environment variables: |
Utilities to help with reproducibility of models.
- pytorch_lightning.utilities.seed.isolate_rng()[source]¶
A context manager that resets the global random state on exit to what it was before entering.
It supports isolating the states for PyTorch, Numpy, and Python built-in random number generators.
Example
>>> torch.manual_seed(1) <torch._C.Generator object at ...> >>> with isolate_rng(): ... [torch.rand(1) for _ in range(3)] [tensor([0.7576]), tensor([0.2793]), tensor([0.4031])] >>> torch.rand(1) tensor([0.7576])
- pytorch_lightning.utilities.seed.pl_worker_init_function(worker_id, rank=None)[source]¶
The worker_init_fn that Lightning automatically adds to your dataloader if you previously set set the seed with
seed_everything(seed, workers=True)
.See also the PyTorch documentation on randomness in DataLoaders.
- Return type
- pytorch_lightning.utilities.seed.reset_seed()[source]¶
Reset the seed to the value that
pytorch_lightning.utilities.seed.seed_everything()
previously set.If
pytorch_lightning.utilities.seed.seed_everything()
is unused, this function will do nothing.- Return type
- pytorch_lightning.utilities.seed.seed_everything(seed=None, workers=False)[source]¶
Function that sets seed for pseudo-random number generators in: pytorch, numpy, python.random In addition, sets the following environment variables:
PL_GLOBAL_SEED: will be passed to spawned subprocesses (e.g. ddp_spawn backend).
PL_SEED_WORKERS: (optional) is set to 1 if
workers=True
.
- Parameters
seed¶ (
Optional
[int
]) – the integer value seed for global random state in Lightning. If None, will read seed from PL_GLOBAL_SEED env variable or select it randomly.workers¶ (
bool
) – if set toTrue
, will properly configure all dataloaders passed to the Trainer with aworker_init_fn
. If the user already provides such a function for their dataloaders, setting this argument will have no influence. See also:pl_worker_init_function()
.
- Return type