"""simple docstring"""





import unittest

from datasets import load_dataset

from transformers import BloomTokenizerFast
from transformers.testing_utils import require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin




@require_tokenizers
class  _snake_case		(    __snake_case   ,       unittest.TestCase ):







				"""simple docstring"""






				a			=						None
				a			=						BloomTokenizerFast
				a			=						BloomTokenizerFast
				a			=						True
				a			=						False
				a			=						"tokenizer_file"
				a			=						{"bos_token": "<s>", "eos_token": "</s>", "unk_token": "<unk>", "pad_token": "<pad>"}





				def 		_lowerCAmelCase		(      self							:							Any):



											"""simple docstring"""







											super().setUp()
											_SCREAMING_SNAKE_CASE		:						str			  =    BloomTokenizerFast.from_pretrained("""bigscience/tokenizer""")
											tokenizer.save_pretrained(self.tmpdirname)





				def 		_lowerCAmelCase		(      self							:							Any      ,    **_A							:							str):



											"""simple docstring"""







											kwargs.update(self.special_tokens_map)
											return BloomTokenizerFast.from_pretrained(self.tmpdirname      ,    **_A)





				def 		_lowerCAmelCase		(      self							:							Any):



											"""simple docstring"""







											_SCREAMING_SNAKE_CASE		:						Optional[Any]			  =    self.get_rust_tokenizer()

											_SCREAMING_SNAKE_CASE		:						Union[str, Any]			  =    ["""The quick brown fox</s>""", """jumps over the lazy dog</s>"""]
											_SCREAMING_SNAKE_CASE		:						Tuple			  =    [[2_1_7_5, 2_3_7_1_4, 7_3_1_7_3, 1_4_4_2_5_2, 2], [7_7, 1_3_2_6_1_9, 3_4_7_8, 3_6_8, 1_0_9_5_8_6, 3_5_4_3_3, 2]]

											_SCREAMING_SNAKE_CASE		:						Union[str, Any]			  =    tokenizer.batch_encode_plus(_A)["""input_ids"""]
											self.assertListEqual(_A      ,    _A)

											_SCREAMING_SNAKE_CASE		:						str			  =    tokenizer.batch_decode(_A)
											self.assertListEqual(_A      ,    _A)





				def 		_lowerCAmelCase		(      self							:							str      ,    _A							:							Union[str, Any]=6):



											"""simple docstring"""







											for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
																		with self.subTest(f"""{tokenizer.__class__.__name__} ({pretrained_name})"""):
																									_SCREAMING_SNAKE_CASE		:						List[Any]			  =    self.rust_tokenizer_class.from_pretrained(_A      ,    **_A)
																									# tokenizer_r.pad_token = None # Hotfixing padding = None
																									# Simple input
																									_SCREAMING_SNAKE_CASE		:						Dict			  =    """This is a simple input"""
																									_SCREAMING_SNAKE_CASE		:						List[Any]			  =    ["""This is a simple input 1""", """This is a simple input 2"""]
																									_SCREAMING_SNAKE_CASE		:						Dict			  =    ("""This is a simple input""", """This is a pair""")
																									_SCREAMING_SNAKE_CASE		:						List[Any]			  =    [
																									    ("""This is a simple input 1""", """This is a simple input 2"""),
																									    ("""This is a simple pair 1""", """This is a simple pair 2"""),
																									]

																									# Simple input tests
																									try:
																																tokenizer_r.encode(_A      ,    max_length=_A)
																																tokenizer_r.encode_plus(_A      ,    max_length=_A)

																																tokenizer_r.batch_encode_plus(_A      ,    max_length=_A)
																																tokenizer_r.encode(_A      ,    max_length=_A)
																																tokenizer_r.batch_encode_plus(_A      ,    max_length=_A)
																									except ValueError:
																																self.fail("""Bloom Tokenizer should be able to deal with padding""")

																									_SCREAMING_SNAKE_CASE		:						Optional[int]			  =    None  # Hotfixing padding = None
																									self.assertRaises(_A      ,    tokenizer_r.encode      ,    _A      ,    max_length=_A      ,    padding="""max_length""")

																									# Simple input
																									self.assertRaises(_A      ,    tokenizer_r.encode_plus      ,    _A      ,    max_length=_A      ,    padding="""max_length""")

																									# Simple input
																									self.assertRaises(
																									    _A      ,    tokenizer_r.batch_encode_plus      ,    _A      ,    max_length=_A      ,    padding="""max_length"""      ,    )

																									# Pair input
																									self.assertRaises(_A      ,    tokenizer_r.encode      ,    _A      ,    max_length=_A      ,    padding="""max_length""")

																									# Pair input
																									self.assertRaises(_A      ,    tokenizer_r.encode_plus      ,    _A      ,    max_length=_A      ,    padding="""max_length""")

																									# Pair input
																									self.assertRaises(
																									    _A      ,    tokenizer_r.batch_encode_plus      ,    _A      ,    max_length=_A      ,    padding="""max_length"""      ,    )





				def 		_lowerCAmelCase		(      self							:							Optional[Any]):



											"""simple docstring"""







											_SCREAMING_SNAKE_CASE		:						int			  =    self.get_rust_tokenizer()
											_SCREAMING_SNAKE_CASE		:						List[str]			  =    load_dataset("""xnli"""      ,    """all_languages"""      ,    split="""test"""      ,    streaming=_A)

											_SCREAMING_SNAKE_CASE		:						List[str]			  =    next(iter(_A))["""premise"""]  # pick up one data
											_SCREAMING_SNAKE_CASE		:						int			  =    list(sample_data.values())

											_SCREAMING_SNAKE_CASE		:						List[str]			  =    list(map(tokenizer.encode      ,    _A))
											_SCREAMING_SNAKE_CASE		:						List[str]			  =    [tokenizer.decode(_A      ,    clean_up_tokenization_spaces=_A) for x in output_tokens]
											self.assertListEqual(_A      ,    _A)





				def 		_lowerCAmelCase		(      self							:							List[str]):



											"""simple docstring"""







											self.assertGreaterEqual(len(self.tokenizer_class.pretrained_vocab_files_map)      ,    1)
											self.assertGreaterEqual(len(list(self.tokenizer_class.pretrained_vocab_files_map.values())[0])      ,    1)



"""simple docstring"""





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



def      lowerCamelCase_(__SCREAMING_SNAKE_CASE  )->    str:

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

							_SCREAMING_SNAKE_CASE		:						int			  =    precision
							_SCREAMING_SNAKE_CASE		:						Dict			  =    ceil(precision / 14  )
							_SCREAMING_SNAKE_CASE		:						int			  =    426_880 * Decimal(10_005  ).sqrt()
							_SCREAMING_SNAKE_CASE		:						Union[str, Any]			  =    1
							_SCREAMING_SNAKE_CASE		:						str			  =    13_591_409
							_SCREAMING_SNAKE_CASE		:						Tuple			  =    Decimal(__SCREAMING_SNAKE_CASE  )
							for k in range(1     ,	__SCREAMING_SNAKE_CASE  ):
														_SCREAMING_SNAKE_CASE		:						Tuple			  =    factorial(6 * k  ) // (factorial(3 * k  ) * factorial(__SCREAMING_SNAKE_CASE  ) ** 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__":
			lowerCAmelCase_     =	50
			print(F"The first {n} digits of pi is: {pi(n)}")


