import os
import sys
import numpy as np
from torch.utils.data import DataLoader



class Accumulator():
    def __init__(self):
        self.dict = dict()

    def update(self, dict):
        for key in dict.keys():
            if key in self.dict.keys():
                self.dict[key].append(dict[key])
            else:
                self.dict[key] = [dict[key]]

    def get(self):
        result = dict()
        for key in self.dict.keys():
            result[key] = np.mean(self.dict[key])
        return result

    def reset(self):
        self.dict = dict()


class InfiniteDataLoader(DataLoader):
    def __init__(self, *args, **kwargs):
        super().__init__(*args, **kwargs)
        # Initialize an iterator over the dataset.
        self.dataset_iterator = super().__iter__()

    def __iter__(self):
        return self

    def __next__(self):
        try:
            batch = next(self.dataset_iterator)
        except StopIteration:
            # Dataset exhausted, use a new fresh iterator.
            self.dataset_iterator = super().__iter__()
            batch = next(self.dataset_iterator)
        return batch

def text_to_html(lines):  
    html = ''
    for line in lines:
        html += "<pre>" + line + "</pre>"
    return html