


"""simple docstring"""


from __future__ import annotations


def 					UpperCAmelCase			(				a__    ,			a__    ,			a__    ,			):





						'''simple docstring'''






						if not all((nth_term, start_term_a, common_ratio_r)   ):
												return []
						lowerCAmelCase      :list[float | int]				  = []
						lowerCAmelCase      :int				  = 1
						lowerCAmelCase      :int				  = common_ratio_r
						for _ in range(int(a__   )   ):
												if not series:
																		series.append(a__   )
												else:
																		power += 1
																		series.append(float(start_term_a * multiple   )   )
																		lowerCAmelCase      :Dict				  = pow(float(a__   )    ,			a__   )
						return series


if __name__ == "__main__":
		import doctest

		doctest.testmod()

		__SCREAMING_SNAKE_CASE      =      float(input('Enter the last number (n term) of the Geometric Series'))
		__SCREAMING_SNAKE_CASE      =      float(input('Enter the starting term (a) of the Geometric Series'))
		__SCREAMING_SNAKE_CASE      =      float(
		    input('Enter the common ratio between two terms (r) of the Geometric Series')
		)
		print('Formula of Geometric Series => a + ar + ar^2 ... +ar^n')
		print(geometric_series(nth_term, start_term_a, common_ratio_r))







"""simple docstring"""


import unittest
import warnings
from dataclasses import dataclass

from transformers.convert_slow_tokenizer import SpmConverter
from transformers.testing_utils import get_tests_dir




@dataclass
class 	__UpperCamelCase    :
					lowercase_						:							str




class 	__UpperCamelCase    (    unittest.TestCase	):
					def 					UpperCAmelCase__   (       self       :  Union[str, Any]      )  ->					Optional[Any]:
											lowerCAmelCase      :List[str]				  = get_tests_dir('fixtures/test_sentencepiece.model'      )
											lowerCAmelCase      :Tuple				  = get_tests_dir('fixtures/test_sentencepiece_with_bytefallback.model'      )

											lowerCAmelCase      :List[str]				  = FakeOriginalTokenizer(vocab_file=UpperCAmelCase      )

											with warnings.catch_warnings(record=UpperCAmelCase      ) as w:
																	lowerCAmelCase      :Dict				  = SpmConverter(UpperCAmelCase      )
											self.assertEqual(len(UpperCAmelCase      )    ,   0      )

											lowerCAmelCase      :int				  = FakeOriginalTokenizer(vocab_file=UpperCAmelCase      )

											with warnings.catch_warnings(record=UpperCAmelCase      ) as w:
																	lowerCAmelCase      :List[str]				  = SpmConverter(UpperCAmelCase      )
											self.assertEqual(len(UpperCAmelCase      )    ,   1      )

											self.assertIn(
											    'The sentencepiece tokenizer that you are converting to a fast tokenizer uses the byte fallback option'
											    ' which is not implemented in the fast tokenizers.'    ,   str(w[0].message      )    ,   )