




'''simple docstring'''





import json
import os
from functools import lru_cache
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_						:      List[str]       =						logging.get_logger(__name__)


UpperCamelCase_						:      str       =						{
    '''vocab_file''': '''vocab.json''',
    '''merges_file''': '''merges.txt''',
    '''tokenizer_config_file''': '''tokenizer_config.json''',
}

UpperCamelCase_						:      str       =						{
    '''vocab_file''': {'''facebook/blenderbot-3B''': '''https://huggingface.co/facebook/blenderbot-3B/resolve/main/vocab.json'''},
    '''merges_file''': {'''facebook/blenderbot-3B''': '''https://huggingface.co/facebook/blenderbot-3B/resolve/main/merges.txt'''},
    '''tokenizer_config_file''': {
        '''facebook/blenderbot-3B''': '''https://huggingface.co/facebook/blenderbot-3B/resolve/main/tokenizer_config.json'''
    },
}

UpperCamelCase_						:      Union[str, Any]       =						{'''facebook/blenderbot-3B''': 128}





@lru_cache()
# Copied from transformers.models.roberta.tokenization_roberta.bytes_to_unicode
def      __a     (       )						->			Optional[int]:

					"""simple docstring"""




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





def      __a     (       _UpperCamelCase:   str   )						->			Optional[int]:

					"""simple docstring"""




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





class        _a    (						__lowerCAmelCase							):
					SCREAMING_SNAKE_CASE_							:   str       =						VOCAB_FILES_NAMES
					SCREAMING_SNAKE_CASE_							:   Optional[Any]       =						PRETRAINED_VOCAB_FILES_MAP
					SCREAMING_SNAKE_CASE_							:   Dict       =						PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
					SCREAMING_SNAKE_CASE_							:   int       =						["""input_ids""", """attention_mask"""]






					def __init__(			self ,_SCREAMING_SNAKE_CASE ,_SCREAMING_SNAKE_CASE ,_SCREAMING_SNAKE_CASE="replace" ,_SCREAMING_SNAKE_CASE="<s>" ,_SCREAMING_SNAKE_CASE="</s>" ,_SCREAMING_SNAKE_CASE="</s>" ,_SCREAMING_SNAKE_CASE="<s>" ,_SCREAMING_SNAKE_CASE="<unk>" ,_SCREAMING_SNAKE_CASE="<pad>" ,_SCREAMING_SNAKE_CASE="<mask>" ,_SCREAMING_SNAKE_CASE=False ,**_SCREAMING_SNAKE_CASE ,)							->      List[str]:
										_snake_case							=				AddedToken(_SCREAMING_SNAKE_CASE ,lstrip=_SCREAMING_SNAKE_CASE ,rstrip=_SCREAMING_SNAKE_CASE   ) if isinstance(_SCREAMING_SNAKE_CASE ,_SCREAMING_SNAKE_CASE   ) else bos_token
										_snake_case							=				AddedToken(_SCREAMING_SNAKE_CASE ,lstrip=_SCREAMING_SNAKE_CASE ,rstrip=_SCREAMING_SNAKE_CASE   ) if isinstance(_SCREAMING_SNAKE_CASE ,_SCREAMING_SNAKE_CASE   ) else eos_token
										_snake_case							=				AddedToken(_SCREAMING_SNAKE_CASE ,lstrip=_SCREAMING_SNAKE_CASE ,rstrip=_SCREAMING_SNAKE_CASE   ) if isinstance(_SCREAMING_SNAKE_CASE ,_SCREAMING_SNAKE_CASE   ) else sep_token
										_snake_case							=				AddedToken(_SCREAMING_SNAKE_CASE ,lstrip=_SCREAMING_SNAKE_CASE ,rstrip=_SCREAMING_SNAKE_CASE   ) if isinstance(_SCREAMING_SNAKE_CASE ,_SCREAMING_SNAKE_CASE   ) else cls_token
										_snake_case							=				AddedToken(_SCREAMING_SNAKE_CASE ,lstrip=_SCREAMING_SNAKE_CASE ,rstrip=_SCREAMING_SNAKE_CASE   ) if isinstance(_SCREAMING_SNAKE_CASE ,_SCREAMING_SNAKE_CASE   ) else unk_token
										_snake_case							=				AddedToken(_SCREAMING_SNAKE_CASE ,lstrip=_SCREAMING_SNAKE_CASE ,rstrip=_SCREAMING_SNAKE_CASE   ) if isinstance(_SCREAMING_SNAKE_CASE ,_SCREAMING_SNAKE_CASE   ) else pad_token

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

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

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

										# Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
										_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.roberta.tokenization_roberta.RobertaTokenizer.vocab_size with Roberta->Blenderbot, RoBERTa->Blenderbot
					def     _lowercase     (			self   )							->      List[str]:
										return len(self.encoder   )






					def     _lowercase     (			self   )							->      int:
										return dict(self.encoder ,**self.added_tokens_encoder   )






					def     _lowercase     (			self ,_SCREAMING_SNAKE_CASE   )							->      Optional[int]:
										if token in self.cache:
															return self.cache[token]
										_snake_case							=				tuple(_SCREAMING_SNAKE_CASE   )
										_snake_case							=				get_pairs(_SCREAMING_SNAKE_CASE   )

										if not pairs:
															return token

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

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






					def     _lowercase     (			self ,_SCREAMING_SNAKE_CASE   )							->      List[Any]:
										_snake_case							=				[]
										for token in re.findall(self.pat ,_SCREAMING_SNAKE_CASE   ):
															_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(_SCREAMING_SNAKE_CASE   ).split(" "   )   )
										return bpe_tokens






					def     _lowercase     (			self ,_SCREAMING_SNAKE_CASE   )							->      List[str]:
										return self.encoder.get(_SCREAMING_SNAKE_CASE ,self.encoder.get(self.unk_token   )   )






					def     _lowercase     (			self ,_SCREAMING_SNAKE_CASE   )							->      Union[str, Any]:
										return self.decoder.get(_SCREAMING_SNAKE_CASE   )






					def     _lowercase     (			self ,_SCREAMING_SNAKE_CASE   )							->      Tuple:
										_snake_case							=				"".join(_SCREAMING_SNAKE_CASE   )
										_snake_case							=				bytearray([self.byte_decoder[c] for c in text]   ).decode("utf-8" ,errors=self.errors   )
										return text






					def     _lowercase     (			self ,_SCREAMING_SNAKE_CASE ,_SCREAMING_SNAKE_CASE = None   )							->      Tuple[str]:
										if not os.path.isdir(_SCREAMING_SNAKE_CASE   ):
															logger.error(f"""Vocabulary path ({save_directory}) should be a directory"""   )
															return
										_snake_case							=				os.path.join(
										    _SCREAMING_SNAKE_CASE ,(filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]   )
										_snake_case							=				os.path.join(
										    _SCREAMING_SNAKE_CASE ,(filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["merges_file"]   )

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

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

										return vocab_file, merge_file






					def     _lowercase     (			self ,_SCREAMING_SNAKE_CASE ,_SCREAMING_SNAKE_CASE = None ,_SCREAMING_SNAKE_CASE = False   )							->      List[int]:
										if already_has_special_tokens:
															return super().get_special_tokens_mask(
															    token_ids_a=_SCREAMING_SNAKE_CASE ,token_ids_a=_SCREAMING_SNAKE_CASE ,already_has_special_tokens=_SCREAMING_SNAKE_CASE   )

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






					def     _lowercase     (			self ,_SCREAMING_SNAKE_CASE ,_SCREAMING_SNAKE_CASE = None   )							->      List[int]:
										_snake_case							=				[self.sep_token_id]
										_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 + sep + token_ids_a + sep   ) * [0]






					def     _lowercase     (			self ,_SCREAMING_SNAKE_CASE ,_SCREAMING_SNAKE_CASE=False ,**_SCREAMING_SNAKE_CASE   )							->      Optional[int]:
										_snake_case							=				kwargs.pop("add_prefix_space" ,self.add_prefix_space   )
										if (is_split_into_words or add_prefix_space) and (len(_SCREAMING_SNAKE_CASE   ) > 0 and not text[0].isspace()):
															_snake_case							=				" " + text
										return (text, kwargs)






					def     _lowercase     (			self ,_SCREAMING_SNAKE_CASE ,_SCREAMING_SNAKE_CASE = None   )							->      Union[str, Any]:
										return token_ids_a + [self.eos_token_id]






					def     _lowercase     (			self ,_SCREAMING_SNAKE_CASE   )							->      List[int]:
										_snake_case							=				[]
										for is_user, text in conversation.iter_texts():
															if is_user:
																				# We need to space prefix as it's being done within blenderbot
																				inputs.append(" " + text   )
															else:
																				# Generated responses should contain them already.
																				inputs.append(_SCREAMING_SNAKE_CASE   )

										_snake_case							=				"  ".join(_SCREAMING_SNAKE_CASE   )
										_snake_case							=				self.encode(_SCREAMING_SNAKE_CASE   )
										if len(_SCREAMING_SNAKE_CASE   ) > self.model_max_length:
															_snake_case							=				input_ids[-self.model_max_length :]
															logger.warning(f"""Trimmed input from conversation as it was longer than {self.model_max_length} tokens."""   )
										return input_ids








'''simple docstring'''





from decimal import Decimal, getcontext
from math import ceil, factorial





def      __a     (       _UpperCamelCase:   int   )						->			str:

     """simple docstring"""




     if not isinstance(_UpperCamelCase ,						_UpperCamelCase   ):
          raise TypeError("Undefined for non-integers"   )
     elif precision < 1:
          raise ValueError("Undefined for non-natural numbers"   )

     _snake_case							=				precision
     _snake_case							=				ceil(precision / 14   )
     _snake_case							=				426_880 * Decimal(10_005   ).sqrt()
     _snake_case							=				1
     _snake_case							=				13_591_409
     _snake_case							=				Decimal(_UpperCamelCase   )
     for k in range(1 ,						_UpperCamelCase   ):
          _snake_case							=				factorial(6 * k   ) // (factorial(3 * k   ) * factorial(_UpperCamelCase   ) ** 3)
          linear_term += 545_140_134
          exponential_term *= -262_537_412_640_768_000
          partial_sum += Decimal(multinomial_term * linear_term   ) / exponential_term
     return str(constant_term / partial_sum   )[:-1]


if __name__ == "__main__":
   UpperCamelCase_						:      Any       =						50
   print(F'The first {n} digits of pi is: {pi(n)}')


