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80fc0ee0b6
Summary: Currently, seeds are set only inside the train loop. But this does not ensure that the model weights are initialized the same way everywhere which makes all experiments irreproducible. This diff fixes it. Reviewed By: bottler Differential Revision: D38315840 fbshipit-source-id: 3d2ecebbc36072c2b68dd3cd8c5e30708e7dd808
18 lines
382 B
Python
18 lines
382 B
Python
# Copyright (c) Meta Platforms, Inc. and affiliates.
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# All rights reserved.
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#
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# This source code is licensed under the BSD-style license found in the
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# LICENSE file in the root directory of this source tree.
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import random
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import numpy as np
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import torch
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def seed_all_random_engines(seed: int) -> None:
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np.random.seed(seed)
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torch.manual_seed(seed)
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random.seed(seed)
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