


"""simple docstring"""






import json
from typing import List, Optional, Tuple

from tokenizers import pre_tokenizers, processors

from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_longformer import LongformerTokenizer


lowercase  		=			logging.get_logger(__name__)

lowercase  		=			{"""vocab_file""": """vocab.json""", """merges_file""": """merges.txt""", """tokenizer_file""": """tokenizer.json"""}

lowercase  		=			{
    """vocab_file""": {
        """allenai/longformer-base-4096""": """https://huggingface.co/allenai/longformer-base-4096/resolve/main/vocab.json""",
        """allenai/longformer-large-4096""": (
            """https://huggingface.co/allenai/longformer-large-4096/resolve/main/vocab.json"""
        ),
        """allenai/longformer-large-4096-finetuned-triviaqa""": (
            """https://huggingface.co/allenai/longformer-large-4096-finetuned-triviaqa/resolve/main/vocab.json"""
        ),
        """allenai/longformer-base-4096-extra.pos.embd.only""": (
            """https://huggingface.co/allenai/longformer-base-4096-extra.pos.embd.only/resolve/main/vocab.json"""
        ),
        """allenai/longformer-large-4096-extra.pos.embd.only""": (
            """https://huggingface.co/allenai/longformer-large-4096-extra.pos.embd.only/resolve/main/vocab.json"""
        ),
    },
    """merges_file""": {
        """allenai/longformer-base-4096""": """https://huggingface.co/allenai/longformer-base-4096/resolve/main/merges.txt""",
        """allenai/longformer-large-4096""": (
            """https://huggingface.co/allenai/longformer-large-4096/resolve/main/merges.txt"""
        ),
        """allenai/longformer-large-4096-finetuned-triviaqa""": (
            """https://huggingface.co/allenai/longformer-large-4096-finetuned-triviaqa/resolve/main/merges.txt"""
        ),
        """allenai/longformer-base-4096-extra.pos.embd.only""": (
            """https://huggingface.co/allenai/longformer-base-4096-extra.pos.embd.only/resolve/main/merges.txt"""
        ),
        """allenai/longformer-large-4096-extra.pos.embd.only""": (
            """https://huggingface.co/allenai/longformer-large-4096-extra.pos.embd.only/resolve/main/merges.txt"""
        ),
    },
    """tokenizer_file""": {
        """allenai/longformer-base-4096""": (
            """https://huggingface.co/allenai/longformer-base-4096/resolve/main/tokenizer.json"""
        ),
        """allenai/longformer-large-4096""": (
            """https://huggingface.co/allenai/longformer-large-4096/resolve/main/tokenizer.json"""
        ),
        """allenai/longformer-large-4096-finetuned-triviaqa""": (
            """https://huggingface.co/allenai/longformer-large-4096-finetuned-triviaqa/resolve/main/tokenizer.json"""
        ),
        """allenai/longformer-base-4096-extra.pos.embd.only""": (
            """https://huggingface.co/allenai/longformer-base-4096-extra.pos.embd.only/resolve/main/tokenizer.json"""
        ),
        """allenai/longformer-large-4096-extra.pos.embd.only""": (
            """https://huggingface.co/allenai/longformer-large-4096-extra.pos.embd.only/resolve/main/tokenizer.json"""
        ),
    },
}

lowercase  		=			{
    """allenai/longformer-base-4096""": 4096,
    """allenai/longformer-large-4096""": 4096,
    """allenai/longformer-large-4096-finetuned-triviaqa""": 4096,
    """allenai/longformer-base-4096-extra.pos.embd.only""": 4096,
    """allenai/longformer-large-4096-extra.pos.embd.only""": 4096,
}


class 			SCREAMING_SNAKE_CASE_  (   _lowercase):




							'''simple docstring'''





							__magic_name__					:     Optional[int]				  =  VOCAB_FILES_NAMES
							__magic_name__					:     Union[str, Any]				  =  PRETRAINED_VOCAB_FILES_MAP
							__magic_name__					:     List[Any]				  =  PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
							__magic_name__					:     List[Any]				  =  ['''input_ids''', '''attention_mask''']
							__magic_name__					:     Dict				  =  LongformerTokenizer




							def __init__(						self	,					lowerCamelCase__=None	,					lowerCamelCase__=None	,					lowerCamelCase__=None	,					lowerCamelCase__="replace"	,					lowerCamelCase__="<s>"	,					lowerCamelCase__="</s>"	,					lowerCamelCase__="</s>"	,					lowerCamelCase__="<s>"	,					lowerCamelCase__="<unk>"	,					lowerCamelCase__="<pad>"	,					lowerCamelCase__="<mask>"	,					lowerCamelCase__=False	,					lowerCamelCase__=True	,					**lowerCamelCase__	,					)   ->	List[str]:







								'''simple docstring'''




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

								snake_case__  :						Tuple		=      json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__())
								if pre_tok_state.get("add_prefix_space"	,					lowerCamelCase__) != add_prefix_space:
									snake_case__  :						Optional[Any]		=      getattr(lowerCamelCase__	,					pre_tok_state.pop("type"))
									snake_case__  :						Tuple		=      add_prefix_space
									snake_case__  :						Any		=      pre_tok_class(**lowerCamelCase__)

								snake_case__  :						Tuple		=      add_prefix_space

								snake_case__  :						Any		=      "post_processor"
								snake_case__  :						List[Any]		=      getattr(self.backend_tokenizer	,					lowerCamelCase__	,					lowerCamelCase__)
								if tokenizer_component_instance:
									snake_case__  :						List[Any]		=      json.loads(tokenizer_component_instance.__getstate__())

									# The lists 'sep' and 'cls' must be cased in tuples for the object `post_processor_class`
									if "sep" in state:
										snake_case__  :						int		=      tuple(state["sep"])
									if "cls" in state:
										snake_case__  :						str		=      tuple(state["cls"])

									snake_case__  :						Union[str, Any]		=      False

									if state.get("add_prefix_space"	,					lowerCamelCase__) != add_prefix_space:
										snake_case__  :						List[str]		=      add_prefix_space
										snake_case__  :						str		=      True

									if state.get("trim_offsets"	,					lowerCamelCase__) != trim_offsets:
										snake_case__  :						Union[str, Any]		=      trim_offsets
										snake_case__  :						int		=      True

									if changes_to_apply:
										snake_case__  :						Union[str, Any]		=      getattr(lowerCamelCase__	,					state.pop("type"))
										snake_case__  :						List[str]		=      component_class(**lowerCamelCase__)
										setattr(self.backend_tokenizer	,					lowerCamelCase__	,					lowerCamelCase__)




							@property
							def        UpperCAmelCase (						self)   ->	str:







								'''simple docstring'''




								if self._mask_token is None:
									if self.verbose:
										logger.error("Using mask_token, but it is not set yet.")
									return None
								return str(self._mask_token)




							@mask_token.setter
							def        UpperCAmelCase (						self	,					lowerCamelCase__)   ->	str:







								'''simple docstring'''




								snake_case__  :						Tuple		=      AddedToken(lowerCamelCase__	,					lstrip=lowerCamelCase__	,					rstrip=lowerCamelCase__) if isinstance(lowerCamelCase__	,					lowerCamelCase__) else value
								snake_case__  :						Tuple		=      value




							def        UpperCAmelCase (						self	,					*lowerCamelCase__	,					**lowerCamelCase__)   ->	BatchEncoding:







								'''simple docstring'''




								snake_case__  :						Optional[int]		=      kwargs.get("is_split_into_words"	,					lowerCamelCase__)
								assert self.add_prefix_space or not is_split_into_words, (
								    f"""You need to instantiate {self.__class__.__name__} with add_prefix_space=True """
								    "to use it with pretokenized inputs."
								)

								return super()._batch_encode_plus(*lowerCamelCase__	,					**lowerCamelCase__)




							def        UpperCAmelCase (						self	,					*lowerCamelCase__	,					**lowerCamelCase__)   ->	BatchEncoding:







								'''simple docstring'''




								snake_case__  :						str		=      kwargs.get("is_split_into_words"	,					lowerCamelCase__)

								assert self.add_prefix_space or not is_split_into_words, (
								    f"""You need to instantiate {self.__class__.__name__} with add_prefix_space=True """
								    "to use it with pretokenized inputs."
								)

								return super()._encode_plus(*lowerCamelCase__	,					**lowerCamelCase__)




							def        UpperCAmelCase (						self	,					lowerCamelCase__	,					lowerCamelCase__ = None)   ->	Tuple[str]:







								'''simple docstring'''




								snake_case__  :						str		=      self._tokenizer.model.save(lowerCamelCase__	,					name=lowerCamelCase__)
								return tuple(lowerCamelCase__)




							def        UpperCAmelCase (						self	,					lowerCamelCase__	,					lowerCamelCase__=None)   ->	str:







								'''simple docstring'''




								snake_case__  :						Tuple		=      [self.bos_token_id] + token_ids_a + [self.eos_token_id]
								if token_ids_a is None:
									return output

								return output + [self.eos_token_id] + token_ids_a + [self.eos_token_id]







							def        UpperCAmelCase (						self	,					lowerCamelCase__	,					lowerCamelCase__ = None)   ->	List[int]:







								'''simple docstring'''




								snake_case__  :						Optional[int]		=      [self.sep_token_id]
								snake_case__  :						List[str]		=      [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]










import random







class 				a_    :

						def __init__(       self      :Union[str, Any]  ,		_lowercase      :float  ,		_lowercase      :float)						->   None:
												UpperCAmelCase_					=	x
												UpperCAmelCase_					=	y

						def       __a			(       self      :str)						->   bool:
												return (self.x**2 + self.y**2) <= 1




						@classmethod
						def       __a			(       cls      :Optional[Any])						->   str:
												return cls(x=random.random()  ,		y=random.random())







def 							A     (						__UpperCAmelCase      )			->			float:



						'''simple docstring'''






						if number_of_simulations < 1:
												raise ValueError('''At least one simulation is necessary to estimate PI.'''      )

						UpperCAmelCase_					=	0
						for _ in range(__UpperCAmelCase      ):
												UpperCAmelCase_					=	Point.random_unit_square()

												if random_point.is_in_unit_circle():
																		number_in_unit_circle += 1

						return 4 * number_in_unit_circle / number_of_simulations


if __name__ == "__main__":
							# import doctest

							# doctest.testmod()
							from math import pi

							UpperCamelCase_      			=  "Please enter the desired number of Monte Carlo simulations: "
							UpperCamelCase_      			=  estimate_pi(int(input(prompt).strip()))
							print(f"An estimate of PI is {my_pi} with an error of {abs(my_pi - pi)}")





