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# Copyright 2023 Bingxin Ke, ETH Zurich. All rights reserved. | |
# | |
# 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. | |
# -------------------------------------------------------------------------- | |
# If you find this code useful, we kindly ask you to cite our paper in your work. | |
# Please find bibtex at: https://github.com/prs-eth/Marigold#-citation | |
# More information about the method can be found at https://marigoldmonodepth.github.io | |
# -------------------------------------------------------------------------- | |
import numpy as np | |
import random | |
import torch | |
def seed_all(seed: int = 0): | |
""" | |
Set random seeds of all components. | |
""" | |
random.seed(seed) | |
np.random.seed(seed) | |
torch.manual_seed(seed) | |
torch.cuda.manual_seed_all(seed) | |