
import json
import os
from typing import TYPE_CHECKING, List, Optional, Tuple

import regex as re

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging


if TYPE_CHECKING:
  from transformers.pipelines.conversational import Conversation

_UpperCAmelCase    			=					logging.get_logger(__name__)

_UpperCAmelCase    			=					{"vocab_file": "vocab.json", "merges_file": "merges.txt"}

_UpperCAmelCase    			=					{
    "vocab_file": {
        "microsoft/deberta-base": "https://huggingface.co/microsoft/deberta-base/resolve/main/vocab.json",
        "microsoft/deberta-large": "https://huggingface.co/microsoft/deberta-large/resolve/main/vocab.json",
        "microsoft/deberta-xlarge": "https://huggingface.co/microsoft/deberta-xlarge/resolve/main/vocab.json",
        "microsoft/deberta-base-mnli": "https://huggingface.co/microsoft/deberta-base-mnli/resolve/main/vocab.json",
        "microsoft/deberta-large-mnli": "https://huggingface.co/microsoft/deberta-large-mnli/resolve/main/vocab.json",
        "microsoft/deberta-xlarge-mnli": (
            "https://huggingface.co/microsoft/deberta-xlarge-mnli/resolve/main/vocab.json"
        ),
    },
    "merges_file": {
        "microsoft/deberta-base": "https://huggingface.co/microsoft/deberta-base/resolve/main/merges.txt",
        "microsoft/deberta-large": "https://huggingface.co/microsoft/deberta-large/resolve/main/merges.txt",
        "microsoft/deberta-xlarge": "https://huggingface.co/microsoft/deberta-xlarge/resolve/main/merges.txt",
        "microsoft/deberta-base-mnli": "https://huggingface.co/microsoft/deberta-base-mnli/resolve/main/merges.txt",
        "microsoft/deberta-large-mnli": "https://huggingface.co/microsoft/deberta-large-mnli/resolve/main/merges.txt",
        "microsoft/deberta-xlarge-mnli": (
            "https://huggingface.co/microsoft/deberta-xlarge-mnli/resolve/main/merges.txt"
        ),
    },
}

_UpperCAmelCase    			=					{
    "microsoft/deberta-base": 512,
    "microsoft/deberta-large": 512,
    "microsoft/deberta-xlarge": 512,
    "microsoft/deberta-base-mnli": 512,
    "microsoft/deberta-large-mnli": 512,
    "microsoft/deberta-xlarge-mnli": 512,
}

_UpperCAmelCase    			=					{
    "microsoft/deberta-base": {"do_lower_case": False},
    "microsoft/deberta-large": {"do_lower_case": False},
}


def 		_lowerCamelCase       (   ):
  """simple docstring"""




  _lowerCamelCase      =						(
      list(range(ord('''!'''  )			,   ord('''~'''  ) + 1  )  ) + list(range(ord('''¡'''  )			,   ord('''¬'''  ) + 1  )  ) + list(range(ord('''®'''  )			,   ord('''ÿ'''  ) + 1  )  )
  )
  _lowerCamelCase      =						bs[:]
  _lowerCamelCase      =						0
  for b in range(2**8  ):
    if b not in bs:
      bs.append(UpperCAmelCase_  )
      cs.append(2**8 + n  )
      n += 1
  _lowerCamelCase      =						[chr(UpperCAmelCase_  ) for n in cs]
  return dict(zip(UpperCAmelCase_			,   UpperCAmelCase_  )  )


def 		_lowerCamelCase       (   _a  ):
  """simple docstring"""




  _lowerCamelCase      =						set()
  _lowerCamelCase      =						word[0]
  for char in word[1:]:
    pairs.add((prev_char, char)  )
    _lowerCamelCase      =						char
  return pairs






class 		__magic_name__				( _A					):


  """simple docstring"""





  _UpperCamelCase						 = VOCAB_FILES_NAMES
  _UpperCamelCase						 = PRETRAINED_VOCAB_FILES_MAP
  _UpperCamelCase						 = PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  _UpperCamelCase						 = ["input_ids", "attention_mask", "token_type_ids"]


  def __init__(					self	,		a__	,		a__	,		a__="replace"	,		a__="[CLS]"	,		a__="[SEP]"	,		a__="[SEP]"	,		a__="[CLS]"	,		a__="[UNK]"	,		a__="[PAD]"	,		a__="[MASK]"	,		a__=False	,		a__=False	,		**a__	,		):
    _lowerCamelCase      =						AddedToken(__A	,		lstrip=__A	,		rstrip=__A		) if isinstance(__A	,		__A		) else bos_token
    _lowerCamelCase      =						AddedToken(__A	,		lstrip=__A	,		rstrip=__A		) if isinstance(__A	,		__A		) else eos_token
    _lowerCamelCase      =						AddedToken(__A	,		lstrip=__A	,		rstrip=__A		) if isinstance(__A	,		__A		) else sep_token
    _lowerCamelCase      =						AddedToken(__A	,		lstrip=__A	,		rstrip=__A		) if isinstance(__A	,		__A		) else cls_token
    _lowerCamelCase      =						AddedToken(__A	,		lstrip=__A	,		rstrip=__A		) if isinstance(__A	,		__A		) else unk_token
    _lowerCamelCase      =						AddedToken(__A	,		lstrip=__A	,		rstrip=__A		) if isinstance(__A	,		__A		) else pad_token

    # Mask token behave like a normal word, i.e. include the space before it
    _lowerCamelCase      =						AddedToken(__A	,		lstrip=__A	,		rstrip=__A		) if isinstance(__A	,		__A		) else mask_token

    super().__init__(
        errors=__A	,		bos_token=__A	,		eos_token=__A	,		unk_token=__A	,		sep_token=__A	,		cls_token=__A	,		pad_token=__A	,		mask_token=__A	,		add_prefix_space=__A	,		add_bos_token=__A	,		**__A	,		)
    _lowerCamelCase      =						add_bos_token

    with open(__A	,		encoding='''utf-8'''		) as vocab_handle:
      _lowerCamelCase      =						json.load(__A		)
    _lowerCamelCase      =						{v: k for k, v in self.encoder.items()}
    _lowerCamelCase      =						errors  # how to handle errors in decoding
    _lowerCamelCase      =						bytes_to_unicode()
    _lowerCamelCase      =						{v: k for k, v in self.byte_encoder.items()}
    with open(__A	,		encoding='''utf-8'''		) as merges_handle:
      _lowerCamelCase      =						merges_handle.read().split('''\n'''		)[1:-1]
    _lowerCamelCase      =						[tuple(merge.split()		) for merge in bpe_merges]
    _lowerCamelCase      =						dict(zip(__A	,		range(len(__A		)		)		)		)
    _lowerCamelCase      =						{}
    _lowerCamelCase      =						add_prefix_space

    # Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
    _lowerCamelCase      =						re.compile(r'''\'s|\'t|\'re|\'ve|\'m|\'ll|\'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+'''		)


  @property
  # Copied from transformers.models.gpt2.tokenization_gpt2.GPT2Tokenizer.vocab_size
  def     _UpperCAmelCase  (					self		):
    return len(self.encoder		)


  def     _UpperCAmelCase  (					self		):
    return dict(self.encoder	,		**self.added_tokens_encoder		)


  def     _UpperCAmelCase  (					self	,		a__		):





    if token in self.cache:
      return self.cache[token]
    _lowerCamelCase      =						tuple(__A		)
    _lowerCamelCase      =						get_pairs(__A		)

    if not pairs:
      return token

    while True:
      _lowerCamelCase      =						min(__A	,		key=lambda a__		: self.bpe_ranks.get(__A	,		float('''inf'''		)		)		)
      if bigram not in self.bpe_ranks:
        break
      _lowerCamelCase    ,    _lowerCamelCase      =						bigram
      _lowerCamelCase      =						[]
      _lowerCamelCase      =						0
      while i < len(__A		):
        try:
          _lowerCamelCase      =						word.index(__A	,		__A		)
        except ValueError:
          new_word.extend(word[i:]		)
          break
        else:
          new_word.extend(word[i:j]		)
          _lowerCamelCase      =						j

        if word[i] == first and i < len(__A		) - 1 and word[i + 1] == second:
          new_word.append(first + second		)
          i += 2
        else:
          new_word.append(word[i]		)
          i += 1
      _lowerCamelCase      =						tuple(__A		)
      _lowerCamelCase      =						new_word
      if len(__A		) == 1:
        break
      else:
        _lowerCamelCase      =						get_pairs(__A		)
    _lowerCamelCase      =						''' '''.join(__A		)
    _lowerCamelCase      =						word
    return word


  def     _UpperCAmelCase  (					self	,		a__	,		a__ = None		):





    if token_ids_a is None:
      return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
    _lowerCamelCase      =						[self.cls_token_id]
    _lowerCamelCase      =						[self.sep_token_id]
    return cls + token_ids_a + sep + token_ids_a + sep


  def     _UpperCAmelCase  (					self	,		a__	,		a__ = None	,		a__ = False		):





    if already_has_special_tokens:
      return super().get_special_tokens_mask(
          token_ids_a=__A	,		token_ids_a=__A	,		already_has_special_tokens=__A		)

    if token_ids_a is None:
      return [1] + ([0] * len(__A		)) + [1]
    return [1] + ([0] * len(__A		)) + [1] + ([0] * len(__A		)) + [1]


  def     _UpperCAmelCase  (					self	,		a__	,		a__ = None		):
    _lowerCamelCase      =						[self.sep_token_id]
    _lowerCamelCase      =						[self.cls_token_id]

    if token_ids_a is None:
      return len(cls + token_ids_a + sep		) * [0]
    return len(cls + token_ids_a + sep		) * [0] + len(token_ids_a + sep		) * [1]


  def     _UpperCAmelCase  (					self	,		a__		):
    _lowerCamelCase      =						[]
    for token in re.findall(self.pat	,		__A		):
      _lowerCamelCase      =						''''''.join(
          self.byte_encoder[b] for b in token.encode('''utf-8'''		)		)  # Maps all our bytes to unicode strings, avoiding control tokens of the BPE (spaces in our case)
      bpe_tokens.extend(bpe_token for bpe_token in self.bpe(__A		).split(''' '''		)		)
    return bpe_tokens


  def     _UpperCAmelCase  (					self	,		a__		):
    return self.encoder.get(__A	,		self.encoder.get(self.unk_token		)		)


  def     _UpperCAmelCase  (					self	,		a__		):
    return self.decoder.get(__A		)


  def     _UpperCAmelCase  (					self	,		a__		):
    _lowerCamelCase      =						''''''.join(__A		)
    _lowerCamelCase      =						bytearray([self.byte_decoder[c] for c in text]		).decode('''utf-8'''	,		errors=self.errors		)
    return text


  def     _UpperCAmelCase  (					self	,		a__	,		a__ = None		):





    if not os.path.isdir(__A		):
      logger.error(f'''Vocabulary path ({save_directory}) should be a directory'''		)
      return
    _lowerCamelCase      =						os.path.join(
        __A	,		(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']		)
    _lowerCamelCase      =						os.path.join(
        __A	,		(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''merges_file''']		)

    with open(__A	,		'''w'''	,		encoding='''utf-8'''		) as f:
      f.write(json.dumps(self.encoder	,		indent=2	,		sort_keys=__A	,		ensure_ascii=__A		) + '''\n'''		)

    _lowerCamelCase      =						0
    with open(__A	,		'''w'''	,		encoding='''utf-8'''		) as writer:
      writer.write('''#version: 0.2\n'''		)
      for bpe_tokens, token_index in sorted(self.bpe_ranks.items()	,		key=lambda a__		: kv[1]		):
        if index != token_index:
          logger.warning(
              f'''Saving vocabulary to {merge_file}: BPE merge indices are not consecutive.'''
              ''' Please check that the tokenizer is not corrupted!'''		)
          _lowerCamelCase      =						token_index
        writer.write(''' '''.join(__A		) + '''\n'''		)
        index += 1

    return vocab_file, merge_file


  def     _UpperCAmelCase  (					self	,		a__	,		a__=False	,		**a__		):
    _lowerCamelCase      =						kwargs.pop('''add_prefix_space'''	,		self.add_prefix_space		)
    if (is_split_into_words or add_prefix_space) and (len(__A		) > 0 and not text[0].isspace()):
      _lowerCamelCase      =						''' ''' + text
    return (text, kwargs)


  def     _UpperCAmelCase  (					self	,		a__		):
    _lowerCamelCase      =						[]
    for is_user, text in conversation.iter_texts():
      input_ids.extend(self.encode(__A	,		add_special_tokens=__A		) + [self.eos_token_id]		)
    if len(__A		) > self.model_max_length:
      _lowerCamelCase      =						input_ids[-self.model_max_length :]
    return input_ids









'''simple docstring'''







def 			_lowerCAmelCase(      UpperCAmelCase_      :	str						) ->							str:
							lowerCAmelCase__  =   word.upper()
							lowerCAmelCase__  =   0
							lowerCAmelCase__  =   {}
							lowerCAmelCase__  =   []

							for letter in word:
														if letter not in letter_nums:
																					lowerCAmelCase__  =   str(UpperCAmelCase_						)
																					next_num += 1
														word_pattern.append(letter_nums[letter]						)
							return ".".join(UpperCAmelCase_						)


if __name__ == "__main__":
		import pprint
		import time

		_UpperCamelCase  						=			time.time()
		with open("""dictionary.txt""") as in_file:
				_UpperCamelCase  						=			in_file.read().splitlines()

		_UpperCamelCase  						=			{}
		for word in word_list:
				_UpperCamelCase  						=			get_word_pattern(word)
				if pattern in all_patterns:
						all_patterns[pattern].append(word)
				else:
						_UpperCamelCase  						=			[word]

		with open("""word_patterns.txt""", """w""") as out_file:
				out_file.write(pprint.pformat(all_patterns))

		_UpperCamelCase  						=			round(time.time() - start_time, 2)
		print(f'Done!  {len(all_patterns):,} word patterns found in {total_time} seconds.')
		# Done!  9,581 word patterns found in 0.58 seconds.





