lightning/pytorch_lightning/utilities/seed.py

61 lines
2.0 KiB
Python

# Copyright The PyTorch Lightning team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""Helper functions to help with reproducibility of models. """
import os
import random
from typing import Optional
import numpy as np
import torch
from pytorch_lightning import _logger as log
def seed_everything(seed: Optional[int] = None) -> int:
"""Function that sets seed for pseudo-random number generators in:
pytorch, numpy, python.random and sets PYTHONHASHSEED environment variable.
"""
max_seed_value = np.iinfo(np.uint32).max
min_seed_value = np.iinfo(np.uint32).min
try:
if seed is None:
seed = _select_seed_randomly(min_seed_value, max_seed_value)
else:
seed = int(seed)
except (TypeError, ValueError):
seed = _select_seed_randomly(min_seed_value, max_seed_value)
if (seed > max_seed_value) or (seed < min_seed_value):
log.warning(
f"{seed} is not in bounds, \
numpy accepts from {min_seed_value} to {max_seed_value}"
)
seed = _select_seed_randomly(min_seed_value, max_seed_value)
os.environ["PYTHONHASHSEED"] = str(seed)
random.seed(seed)
np.random.seed(seed)
torch.manual_seed(seed)
torch.cuda.manual_seed_all(seed)
return seed
def _select_seed_randomly(min_seed_value: int = 0, max_seed_value: int = 255) -> int:
seed = random.randint(min_seed_value, max_seed_value)
log.warning(f"No correct seed found, seed set to {seed}")
return seed