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import random
import os
import math
import time
import numpy as np
import pickle
import torch
import logging
def get_logger(filename: str):
"""Creates and returns a logger that logs to both the console and a file."""
logger = logging.getLogger(__name__)
logger.setLevel(logging.INFO)
# Console handler
stream_handler = logging.StreamHandler()
stream_handler.setFormatter(logging.Formatter("%(message)s"))
logger.addHandler(stream_handler)
# File handler
file_handler = logging.FileHandler(f"{filename}.log")
file_handler.setFormatter(logging.Formatter("%(message)s"))
logger.addHandler(file_handler)
return logger
def seed_everything(seed: int):
"""Sets random seed for reproducibility across various libraries."""
random.seed(seed)
os.environ["PYTHONHASHSEED"] = str(seed)
np.random.seed(seed)
torch.manual_seed(seed)
torch.cuda.manual_seed(seed)
torch.backends.cudnn.deterministic = True
torch.backends.cudnn.benchmark = False
class AverageMeter:
"""Tracks and stores the average and current values."""
def __init__(self):
self.reset()
def reset(self):
self.val = 0
self.avg = 0
self.sum = 0
self.count = 0
def update(self, val, n=1):
self.val = val
self.sum += val * n
self.count += n
self.avg = self.sum / self.count
def as_minutes(s: int) -> str:
"""Converts seconds to a string in minutes and seconds."""
m = math.floor(s / 60)
s -= m * 60
return "%dm %ds" % (m, s)
def timeSince(since: float, percent: float) -> str:
now = time.time()
s = now - since
es = s / (percent)
rs = es - s
return "%s (remain %s)" % (as_minutes(s), as_minutes(rs))
def convert_all_1d(array: list) -> list:
"""Converts 0-dimensional arrays in a list to 1-dimensional arrays."""
return [np.array([item]) if item.ndim == 0 else item for item in array]
def save_pickle(path: str, contents):
"""Saves contents to a pickle file."""
with open(path, "wb") as f:
pickle.dump(contents, f)
def load_pickle(path: str):
"""Loads contents from a pickle file."""
with open(path, "rb") as f:
return pickle.load(f)
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