xiabingquan

from __future__ import annotations
from copy import deepcopy
from typing import List, Optional


class TrieTree(object):
    # Char-level Trie Tree
    def __init__(self, is_end: bool, val: str = '', parent: Optional[TrieTree] = None):
        """
        A Trie Tree

xiabingquan

import re
import sys

def insert_spaces(text):
    text = re.sub(r'([a-zA-Z])([\u4e00-\u9fa5])', r'\1 \2', text)
    text = re.sub(r'([\u4e00-\u9fa5])([a-zA-Z])', r'\1 \2', text)
    return text


if __name__ == '__main__':

xiabingquan

# A minimal example of how to implement byte-pair encoding (BPE) tokenizer from scratch in Python.
# Reference: https://github.com/karpathy/minbpe
# Contact: bingquanxia@qq.com


def get_stats(byte_arr):
    # get the frequency of each byte pair in the text
    count = {}
    for pair in zip(byte_arr[:-1], byte_arr[1:]):       # e.g. pair: (b'a', b' ')
        count[pair] = count.get(pair, 0) + 1

xiabingquan

# A minimal exmaple of flash attention implemented in Numpy

# Contact: bingquanxia AT qq.com

import unittest
from typing import List

import numpy as np
import torch

xiabingquan

# coding=utf-8
# Contact: bingquanxia@qq.com


import numpy as np
import torch
import torch.nn as nn


def get_len_mask(b: int, max_len: int, feat_lens: torch.Tensor, device: torch.device) -> torch.Tensor:

xiabingquan

from argparse import ArgumentParser

import editdistance
from rich.text import Text
from rich.console import Console


def edit_dist_dp(gt, hyp):
    """
    A Dynamic Programming based Python program for edit distance problem