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