wehub-resource-sync
40 lines
1.1 KiB
Python
40 lines
1.1 KiB
Python
import numpy as np
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import random
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import torch
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def set_seed(seed: int, deterministic: bool = False):
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"""
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Helper function for reproducible behavior to set the seed in `random`, `numpy`, `torch`.
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Args:
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seed (`int`):
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The seed to set.
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deterministic (`bool`, *optional*, defaults to `False`):
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Whether to use deterministic algorithms where available. Can slow down training.
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"""
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random.seed(seed)
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np.random.seed(seed)
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torch.manual_seed(seed)
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torch.cuda.manual_seed_all(seed)
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if deterministic:
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torch.use_deterministic_algorithms(True)
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def merge_dict_list(dict_list):
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if len(dict_list) == 1:
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return dict_list[0]
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merged_dict = {}
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for k, v in dict_list[0].items():
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if isinstance(v, torch.Tensor):
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if v.ndim == 0:
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merged_dict[k] = torch.stack([d[k] for d in dict_list], dim=0)
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else:
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merged_dict[k] = torch.cat([d[k] for d in dict_list], dim=0)
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else:
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# for non-tensor values, we just copy the value from the first item
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merged_dict[k] = v
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return merged_dict
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