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import yaml
import argparse

class Config:
    """
    A dynamic configuration class that automatically loads configuration from a YAML file and command line arguments.

    Attributes:
        _config (dict): A dictionary to store configuration parameters.

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import logging
import os
import sys

def root_path():
  ...


class MyFormatter(logging.Formatter):
    err_fmt = f"%(asctime)s %(levelname)s %(filename)s @function %(funcName)s line %(lineno)s - %(message)s"

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import torch
import numpy as np
import random

def seed_random_generators(seed=SEED):
    np.random.seed(seed)
    torch.manual_seed(seed)
    torch.cuda.manual_seed(seed)
    random.seed(seed)

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import numpy as np
import os # To improve compatity of the code
import matplotlib.pyplot as plt

class Reader():
    def __init__(self):
        pass

    def load_data(self, foldername):
        '''

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import matplotlib.pyplot as plt
import numpy as np
import os
import math
def read_data(BASE='dataSets'):
    '''
    load data from file
    :param BASE: the path of the folder storing the dataset
    :return: dict{['train','test']}
    '''

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import numpy as np
import matplotlib.pyplot as plt
import os
import math

def read_data(BASE='dataSets'):
    '''
    load data from file
    :param BASE: the path of the folder storing the dataset
    :return: dict{['train','test']}

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import numpy as np
import math
import matplotlib.pyplot as plt
import os

def read_data(BASE='dataSets'):
    '''
    load data from file
    :param BASE: the path of the folder storing the dataset
    :return: dict{['train','test']}

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import numpy as np
import matplotlib.pyplot as plt
import os

def read_data(BASE='dataSets'):
    '''
    load data from file
    :param parentF: the path of parent folder of the data file
    :return: dict{['train','test']}
    '''

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