from collections.abc import Sequence



def   __A		(			_A							,				_A					):



 """simple docstring"""


 return sum(c * (x**i) for i, c in enumerate(_A					)					)



def   __A		(			_A							,				_A					):



 """simple docstring"""


 __a       =  0.0
 for coeff in reversed(_A					):
  __a       =  result * x + coeff
 return result


if __name__ == "__main__":
  SCREAMING_SNAKE_CASE :	Union[str, Any]							     =		(0.0, 0.0, 5.0, 9.3, 7.0)
  SCREAMING_SNAKE_CASE :	Tuple							     =		1_0.0
  print(evaluate_poly(poly, x))
  print(horner(poly, x))



import pytest

import datasets.config
from datasets.utils.info_utils import is_small_dataset



@pytest.mark.parametrize("dataset_size"							,				[None, 400 * 2**20, 600 * 2**20]					)
@pytest.mark.parametrize("input_in_memory_max_size"							,				["default", 0, 100 * 2**20, 900 * 2**20]					)
def   __A		(			_A							,				_A							,				_A					):



 """simple docstring"""


 if input_in_memory_max_size != "default":
  monkeypatch.setattr(datasets.config							,				"IN_MEMORY_MAX_SIZE"							,				_A					)
 __a       =  datasets.config.IN_MEMORY_MAX_SIZE
 if input_in_memory_max_size == "default":
  assert in_memory_max_size == 0
 else:
  assert in_memory_max_size == input_in_memory_max_size
 if dataset_size and in_memory_max_size:
  __a       =  dataset_size < in_memory_max_size
 else:
  __a       =  False
 __a       =  is_small_dataset(_A					)
 assert result == expected


