import collections
import unicodedata
import os

def basic_tokenize(text, language="english", preserve_line=False):
  """
  Return a tokenized copy of *text*,
  :param text: text to split into words
  :type text: str
  :param language: the model name in the Punkt corpus
  :type language: str
  :param preserve_line: A flag to decide whether to sentence tokenize the text or not.
  :type preserve_line: bool
  """
  return ''.join(text).split()

def convert_to_unicode(text):
  """Converts `text` to Unicode (if it's not already), assuming utf-8 input."""
  if isinstance(text, str):
    return text
  elif isinstance(text, bytes):
    return text.decode("utf-8", "ignore")
  else:
    raise ValueError("Unsupported string type: %s" % (type(text)))

def whitespace_tokenize(text):
  """Runs basic whitespace cleaning and splitting on a piece of text."""
  text = text.strip()
  if not text:
    return []
  tokens = text.split()
  return tokens

def _is_whitespace(char):
  """Checks whether `chars` is a whitespace character."""
  # \t, \n, and \r are technically contorl characters but we treat them
  # as whitespace since they are generally considered as such.
  if char == " " or char == "\t" or char == "\n" or char == "\r":
    return True
  cat = unicodedata.category(char)
  if cat == "Zs":
    return True
  return False

def _is_control(char):
  """Checks whether `chars` is a control character."""
  # These are technically control characters but we count them as whitespace
  # characters.
  if char == "\t" or char == "\n" or char == "\r":
    return False
  cat = unicodedata.category(char)
  if cat in ("Cc", "Cf"):
    return True
  return False

def _is_punctuation(char):
  """Checks whether `chars` is a punctuation character."""
  cp = ord(char)
  # We treat all non-letter/number ASCII as punctuation.
  # Characters such as "^", "$", and "`" are not in the Unicode
  # Punctuation class but we treat them as punctuation anyways, for
  # consistency.
  if ((cp >= 33 and cp <= 47) or (cp >= 58 and cp <= 64) or
      (cp >= 91 and cp <= 96) or (cp >= 123 and cp <= 126)):
    return True
  cat = unicodedata.category(char)
  if cat.startswith("P"):
    return True
  return False

##################################################
# Word Tokenizer
##################################################
class WordTokenizer(object):
  """Runs basic tokenization (punctuation splitting, lower casing, etc.)."""

  def __init__(self, do_lower_case=True):
    """Constructs a BasicTokenizer.
    Args:
      do_lower_case: Whether to lower case the input.
    """
    self.do_lower_case = do_lower_case

  def tokenize(self, text):
    """Tokenizes a piece of text."""
    text = convert_to_unicode(text)
    text = self._clean_text(text)

    orig_tokens = whitespace_tokenize(text)
    split_tokens = []
    for token in orig_tokens:
      if self.do_lower_case:
        token = token.lower()
        token = self._run_strip_accents(token)
      split_tokens.extend(self._run_split_on_punc(token))

    output_tokens = whitespace_tokenize(" ".join(split_tokens))
    return output_tokens

  def _run_strip_accents(self, text):
    """Strips accents from a piece of text."""
    text = unicodedata.normalize("NFD", text)
    output = []
    for char in text:
      cat = unicodedata.category(char)
      if cat == "Mn":
        continue
      output.append(char)
    return "".join(output)

  def _run_split_on_punc(self, text):
    """Splits punctuation on a piece of text."""
    chars = list(text)
    i = 0
    start_new_word = True
    output = []
    while i < len(chars):
      char = chars[i]
      if _is_punctuation(char):
        output.append([char])
        start_new_word = True
      else:
        if start_new_word:
          output.append([])
        start_new_word = False
        output[-1].append(char)
      i += 1

    return ["".join(x) for x in output]

  def _clean_text(self, text):
    """Performs invalid character removal and whitespace cleanup on text."""
    output = []
    for char in text:
      cp = ord(char)
      if cp == 0 or cp == 0xfffd or _is_control(char):
        continue
      if _is_whitespace(char):
        output.append(" ")
      else:
        output.append(char)
    return "".join(output)

##################################################
# Wordpiece Tokenizer
##################################################
def load_vocab():
  """Loads a vocabulary file into a dictionary."""
  vocab = collections.OrderedDict()
  index = 0
  resource_url = ""
  path = os.path.dirname(os.path.realpath(__file__))
  f = open(os.path.join(path, "vocab.txt"), 'r')
 
  with f as reader:
    while True:
      token = convert_to_unicode(reader.readline())
      if not token:
        break
      token = token.strip()
      vocab[token] = index
      index += 1
  return vocab 

# vocab = load_vocab()

class Wordpiece_tokenizer(object):
  """Runs WordPiece tokenziation."""
  def __init__(self, vocab = load_vocab(), unk_token="[UNK]", max_input_chars_per_word=200):
    self.vocab = vocab
    self.unk_token = unk_token
    self.max_input_chars_per_word = max_input_chars_per_word

  def tokenize(self, text):
    """
    Tokenizes a piece of text into its word pieces.
    This uses a greedy longest-match-first algorithm to perform tokenization using the given vocabulary.
    For example:
      input = "unaffable"
      output = ["un", "##aff", "##able"]
    Args:
      text: A single token or whitespace separated tokens. This should have already been passed through `BasicTokenizer.
    Returns:
      A list of wordpiece tokens.
    """

    text = convert_to_unicode(text)
    output_tokens = []

    for token in whitespace_tokenize(text):
      chars = list(token)
      if len(chars) > self.max_input_chars_per_word:
        output_tokens.append(self.unk_token)
        continue

      # is_bad = False
      start = 0
      sub_tokens = []
      for i in range(len(chars)):
        substr_ = "".join(chars[start:i])
        cur_substr = None
        if i == len(chars)-1:
          cur_substr = "".join(chars)
        elif i!=1 and substr_ in self.vocab:
          cur_substr = "##" + substr_

        if cur_substr != None:
          sub_tokens.append(cur_substr)
      
      # if is_bad:
      #   output_tokens.append(self.unk_token)
      output_tokens.extend(sub_tokens)
    return output_tokens

    #   while start < len(chars):
    #     end = len(chars)
    #     cur_substr = None
    #     while start < end:
    #       # print(chars[start:end])
    #       substr = "".join(chars[start:end])
    #       if start > 0:
    #         substr = "##" + substr
    #       # print(substr)
    #       if substr in self.vocab:
    #         # print(substr)
    #         cur_substr = "##" + substr
    #         break
    #       end -= 1
    #     if cur_substr is None:
    #       is_bad = True
    #       break
    #     # print(cur_substr)
    #     sub_tokens.append(cur_substr)
    #     start = end
    #   if is_bad:
    #     output_tokens.append(self.unk_token)
    #   else:
    #     output_tokens.extend(sub_tokens)
    # return output_tokens