




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

lowerCamelCase_	 =		logging.get_logger(__name__)

lowerCamelCase_	 =		{'vocab_file': 'vocab.json', 'merges_file': 'merges.txt'}

lowerCamelCase_	 =		{
    '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'
        ),
    },
}

lowerCamelCase_	 =		{
    'microsoft/deberta-base': 5_12,
    'microsoft/deberta-large': 5_12,
    'microsoft/deberta-xlarge': 5_12,
    'microsoft/deberta-base-mnli': 5_12,
    'microsoft/deberta-large-mnli': 5_12,
    'microsoft/deberta-xlarge-mnli': 5_12,
}

lowerCamelCase_	 =		{
    'microsoft/deberta-base': {'do_lower_case': False},
    'microsoft/deberta-large': {'do_lower_case': False},
}
def 				SCREAMING_SNAKE_CASE_				(							)				->				Optional[Any]:
   _SCREAMING_SNAKE_CASE =   (
       list(range(ord("!"						) ,  ord("~"						) + 1						)						) + list(range(ord("¡"						) ,  ord("¬"						) + 1						)						) + list(range(ord("®"						) ,  ord("ÿ"						) + 1						)						)
   )
   _SCREAMING_SNAKE_CASE =   bs[:]
   _SCREAMING_SNAKE_CASE =   0
   for b in range(2**8						):
      if b not in bs:
         bs.append(__A						)
         cs.append(2**8 + n						)
         n += 1
   _SCREAMING_SNAKE_CASE =   [chr(__A						) for n in cs]
   return dict(zip(__A ,  __A						)						)
def 				SCREAMING_SNAKE_CASE_				(							__A       :				int						)				->				Tuple:
   _SCREAMING_SNAKE_CASE =   set()
   _SCREAMING_SNAKE_CASE =   word[0]
   for char in word[1:]:
      pairs.add((prev_char, char)						)
      _SCREAMING_SNAKE_CASE =   char
   return pairs







class 	lowercase_					(				A     ):


   """simple docstring"""

   lowerCamelCase_       						=		VOCAB_FILES_NAMES
   lowerCamelCase_       						=		PRETRAINED_VOCAB_FILES_MAP
   lowerCamelCase_       						=		PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
   lowerCamelCase_       						=		['''input_ids''', '''attention_mask''', '''token_type_ids''']



   def __init__(					self      :			List[Any]						,   __lowerCamelCase      :			Optional[int]						,   __lowerCamelCase      :			Dict						,   __lowerCamelCase      :			List[str]="replace"						,   __lowerCamelCase      :			Dict="[CLS]"						,   __lowerCamelCase      :			Any="[SEP]"						,   __lowerCamelCase      :			Optional[int]="[SEP]"						,   __lowerCamelCase      :			Dict="[CLS]"						,   __lowerCamelCase      :			Dict="[UNK]"						,   __lowerCamelCase      :			Any="[PAD]"						,   __lowerCamelCase      :			List[str]="[MASK]"						,   __lowerCamelCase      :			str=False						,   __lowerCamelCase      :			str=False						,   **__lowerCamelCase      :			List[Any]						,   ):

      """simple docstring"""
      _SCREAMING_SNAKE_CASE =   AddedToken(__lowerCamelCase						,   lstrip=__lowerCamelCase						,   rstrip=__lowerCamelCase					) if isinstance(__lowerCamelCase						,   __lowerCamelCase					) else bos_token
      _SCREAMING_SNAKE_CASE =   AddedToken(__lowerCamelCase						,   lstrip=__lowerCamelCase						,   rstrip=__lowerCamelCase					) if isinstance(__lowerCamelCase						,   __lowerCamelCase					) else eos_token
      _SCREAMING_SNAKE_CASE =   AddedToken(__lowerCamelCase						,   lstrip=__lowerCamelCase						,   rstrip=__lowerCamelCase					) if isinstance(__lowerCamelCase						,   __lowerCamelCase					) else sep_token
      _SCREAMING_SNAKE_CASE =   AddedToken(__lowerCamelCase						,   lstrip=__lowerCamelCase						,   rstrip=__lowerCamelCase					) if isinstance(__lowerCamelCase						,   __lowerCamelCase					) else cls_token
      _SCREAMING_SNAKE_CASE =   AddedToken(__lowerCamelCase						,   lstrip=__lowerCamelCase						,   rstrip=__lowerCamelCase					) if isinstance(__lowerCamelCase						,   __lowerCamelCase					) else unk_token
      _SCREAMING_SNAKE_CASE =   AddedToken(__lowerCamelCase						,   lstrip=__lowerCamelCase						,   rstrip=__lowerCamelCase					) if isinstance(__lowerCamelCase						,   __lowerCamelCase					) else pad_token

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

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

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

      # Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
      _SCREAMING_SNAKE_CASE =   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 							lowerCAmelCase_    (					self      :			Any					):

      """simple docstring"""
      return len(self.encoder					)



   def 							lowerCAmelCase_    (					self      :			List[str]					):

      """simple docstring"""
      return dict(self.encoder						,   **self.added_tokens_encoder					)



   def 							lowerCAmelCase_    (					self      :			str						,   __lowerCamelCase      :			Tuple					):

      """simple docstring"""
      if token in self.cache:
         return self.cache[token]
      _SCREAMING_SNAKE_CASE =   tuple(__lowerCamelCase					)
      _SCREAMING_SNAKE_CASE =   get_pairs(__lowerCamelCase					)

      if not pairs:
         return token

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

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



   def 							lowerCAmelCase_    (					self      :			Optional[Any]						,   __lowerCamelCase      :			List[int]						,   __lowerCamelCase      :			Optional[List[int]] = None					):

      """simple docstring"""
      if token_ids_a is None:
         return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
      _SCREAMING_SNAKE_CASE =   [self.cls_token_id]
      _SCREAMING_SNAKE_CASE =   [self.sep_token_id]
      return cls + token_ids_a + sep + token_ids_a + sep



   def 							lowerCAmelCase_    (					self      :			Optional[int]						,   __lowerCamelCase      :			List[int]						,   __lowerCamelCase      :			Optional[List[int]] = None						,   __lowerCamelCase      :			bool = False					):

      """simple docstring"""
      if already_has_special_tokens:
         return super().get_special_tokens_mask(
             token_ids_a=__lowerCamelCase						,   token_ids_a=__lowerCamelCase						,   already_has_special_tokens=__lowerCamelCase					)

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



   def 							lowerCAmelCase_    (					self      :			List[Any]						,   __lowerCamelCase      :			List[int]						,   __lowerCamelCase      :			Optional[List[int]] = None					):

      """simple docstring"""
      _SCREAMING_SNAKE_CASE =   [self.sep_token_id]
      _SCREAMING_SNAKE_CASE =   [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 							lowerCAmelCase_    (					self      :			Tuple						,   __lowerCamelCase      :			int					):

      """simple docstring"""
      _SCREAMING_SNAKE_CASE =   []
      for token in re.findall(self.pat						,   __lowerCamelCase					):
         _SCREAMING_SNAKE_CASE =   "".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(__lowerCamelCase					).split(" "					)					)
      return bpe_tokens



   def 							lowerCAmelCase_    (					self      :			Dict						,   __lowerCamelCase      :			Dict					):

      """simple docstring"""
      return self.encoder.get(__lowerCamelCase						,   self.encoder.get(self.unk_token					)					)



   def 							lowerCAmelCase_    (					self      :			Any						,   __lowerCamelCase      :			Optional[Any]					):

      """simple docstring"""
      return self.decoder.get(__lowerCamelCase					)



   def 							lowerCAmelCase_    (					self      :			int						,   __lowerCamelCase      :			Tuple					):

      """simple docstring"""
      _SCREAMING_SNAKE_CASE =   "".join(__lowerCamelCase					)
      _SCREAMING_SNAKE_CASE =   bytearray([self.byte_decoder[c] for c in text]					).decode("utf-8"						,   errors=self.errors					)
      return text



   def 							lowerCAmelCase_    (					self      :			Optional[Any]						,   __lowerCamelCase      :			str						,   __lowerCamelCase      :			Optional[str] = None					):

      """simple docstring"""
      if not os.path.isdir(__lowerCamelCase					):
         logger.error(F"""Vocabulary path ({save_directory}) should be a directory"""					)
         return
      _SCREAMING_SNAKE_CASE =   os.path.join(
          __lowerCamelCase						,   (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]					)
      _SCREAMING_SNAKE_CASE =   os.path.join(
          __lowerCamelCase						,   (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["merges_file"]					)

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

      _SCREAMING_SNAKE_CASE =   0
      with open(__lowerCamelCase						,   "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 __lowerCamelCase					: 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!"					)
               _SCREAMING_SNAKE_CASE =   token_index
            writer.write(" ".join(__lowerCamelCase					) + "\n"					)
            index += 1

      return vocab_file, merge_file



   def 							lowerCAmelCase_    (					self      :			Optional[int]						,   __lowerCamelCase      :			Dict						,   __lowerCamelCase      :			Tuple=False						,   **__lowerCamelCase      :			int					):

      """simple docstring"""
      _SCREAMING_SNAKE_CASE =   kwargs.pop("add_prefix_space"						,   self.add_prefix_space					)
      if (is_split_into_words or add_prefix_space) and (len(__lowerCamelCase					) > 0 and not text[0].isspace()):
         _SCREAMING_SNAKE_CASE =   " " + text
      return (text, kwargs)



   def 							lowerCAmelCase_    (					self      :			List[str]						,   __lowerCamelCase      :			"Conversation"					):

      """simple docstring"""
      _SCREAMING_SNAKE_CASE =   []
      for is_user, text in conversation.iter_texts():
         input_ids.extend(self.encode(__lowerCamelCase						,   add_special_tokens=__lowerCamelCase					) + [self.eos_token_id]					)
      if len(__lowerCamelCase					) > self.model_max_length:
         _SCREAMING_SNAKE_CASE =   input_ids[-self.model_max_length :]
      return input_ids







'''simple docstring'''



lowerCamelCase_	 =		(1, 1_53, 3_70, 3_71, 16_34, 24_67_80_51, 1_15_13_22_19_01_87_63_99_25_65_09_55_97_97_39_71_52_24_01)
lowerCamelCase_	 =		(-1_53, -1, 0, 1.2, 2_00, "A", [], {}, None)
def 				SCREAMING_SNAKE_CASE_				(							__A       :				int						)				->				bool:
   if not isinstance(__A ,  __A						) or n < 1:
      return False

   # Initialization of sum and number of digits.
   _SCREAMING_SNAKE_CASE =   0
   _SCREAMING_SNAKE_CASE =   0
   _SCREAMING_SNAKE_CASE =   n
   # Calculation of digits of the number
   while temp > 0:
      number_of_digits += 1
      temp //= 10
   # Dividing number into separate digits and find Armstrong number
   _SCREAMING_SNAKE_CASE =   n
   while temp > 0:
      _SCREAMING_SNAKE_CASE =   temp % 10
      total += rem**number_of_digits
      temp //= 10
   return n == total
def 				SCREAMING_SNAKE_CASE_				(							__A       :				int						)				->				bool:
   if not isinstance(__A ,  __A						) or n < 1:
      return False

   # Init a "histogram" of the digits
   _SCREAMING_SNAKE_CASE =   [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]
   _SCREAMING_SNAKE_CASE =   0
   _SCREAMING_SNAKE_CASE =   0
   _SCREAMING_SNAKE_CASE =   n
   while temp > 0:
      _SCREAMING_SNAKE_CASE, _SCREAMING_SNAKE_CASE =   divmod(__A ,  10						)
      digit_histogram[rem] += 1
      digit_total += 1

   for cnt, i in zip(__A ,  range(len(__A						)						)						):
      total += cnt * i**digit_total

   return n == total
def 				SCREAMING_SNAKE_CASE_				(							__A       :				int						)				->				bool:
   if not isinstance(__A ,  __A						) or n < 1:
      return False
   _SCREAMING_SNAKE_CASE =   len(str(__A						)						)  # the power that all digits will be raised to
   # check if sum of each digit multiplied expo times is equal to number
   return n == sum(int(__A						) ** expo for i in str(__A						)						)
def 				SCREAMING_SNAKE_CASE_				(							)				->				Optional[Any]:
   _SCREAMING_SNAKE_CASE =   int(input("Enter an integer to see if it is an Armstrong number: "						).strip()						)
   print(f"""{num} is {"" if armstrong_number(__A						) else "not "}an Armstrong number."""						)
   print(f"""{num} is {"" if narcissistic_number(__A						) else "not "}an Armstrong number."""						)
   print(f"""{num} is {"" if pluperfect_number(__A						) else "not "}an Armstrong number."""						)


if __name__ == "__main__":
 import doctest

 doctest.testmod()
 main()

