utils/misc.py

import numpy as np
import random
import torch

def set_seed(seed: int, deterministic: bool=False):
    random.seed(seed)
    np.random.seed(seed)
    torch.manual_seed(seed)
    torch.cuda.manual_seed_all(seed)
    if deterministic:
        torch.use_deterministic_algorithms(True)

def merge_dict_list(dict_list):
    if len(dict_list) == 1:
        return dict_list[0]
    merged_dict = {}
    for k, v in dict_list[0].items():
        if isinstance(v, torch.Tensor):
            if v.ndim == 0:
                merged_dict[k] = torch.stack([d[k] for d in dict_list], dim=0)
            else:
                merged_dict[k] = torch.cat([d[k] for d in dict_list], dim=0)
        else:
            merged_dict[k] = v
    return merged_dict