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Better seeding of random engines

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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
This commit is contained in:
David Novotny
2022-08-01 10:03:09 -07:00
committed by Facebook GitHub Bot
parent 0c3599e8ee
commit 80fc0ee0b6
4 changed files with 31 additions and 13 deletions
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17
projects/implicitron_trainer/impl/utils.py Normal file
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# Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
#
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
import random
import numpy as np
import torch
def seed_all_random_engines(seed: int) -> None:
np.random.seed(seed)
torch.manual_seed(seed)
random.seed(seed)