Ajit Singh
6cf13e8b98
* reduced usage of numpy and substituted built-in libraries * added release note * edited expit function to support both float as well as list (this case was giving error CI) * revert code , numpy can't be removed here * more cleaning * fix relnote --------- Co-authored-by: anakin87 <stefanofiorucci@gmail.com>
37 lines
1.2 KiB
Python
37 lines
1.2 KiB
Python
# SPDX-FileCopyrightText: 2022-present deepset GmbH <info@deepset.ai>
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#
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# SPDX-License-Identifier: Apache-2.0
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import os
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import random
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from haystack import logging
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logger = logging.getLogger(__name__)
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def set_all_seeds(seed: int, deterministic_cudnn: bool = False) -> None:
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"""
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Setting multiple seeds to make runs reproducible.
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Important: Enabling `deterministic_cudnn` gives you full reproducibility with CUDA,
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but might slow down your training (see https://pytorch.org/docs/stable/notes/randomness.html#cudnn) !
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:param seed:number to use as seed
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:param deterministic_cudnn: Enable for full reproducibility when using CUDA. Caution: might slow down training.
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"""
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random.seed(seed)
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os.environ["PYTHONHASHSEED"] = str(seed)
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try:
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import torch
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torch.manual_seed(seed)
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torch.cuda.manual_seed_all(seed)
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if deterministic_cudnn:
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torch.backends.cudnn.deterministic = True
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torch.backends.cudnn.benchmark = False
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except (ImportError, ModuleNotFoundError) as exc:
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logger.info("Could not set PyTorch seed because torch is not installed. Exception: {exception}", exception=exc)
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