from collections.abc import Callable

import numpy as np



def      __SCREAMING_SNAKE_CASE  ( __UpperCamelCase   :	Callable			,					__UpperCamelCase   :	float			,					__UpperCamelCase   :	float			,					__UpperCamelCase   :	float			,					__UpperCamelCase   :	float     )							-> np.array:







  """simple docstring"""





  SCREAMING_SNAKE_CASE__      							=				int(np.ceil((x_end - xa) / step_size     )     )
  SCREAMING_SNAKE_CASE__      							=				np.zeros((n + 1,)     )
  SCREAMING_SNAKE_CASE__      							=				ya
  SCREAMING_SNAKE_CASE__      							=				xa

  for k in range(__UpperCamelCase     ):
    SCREAMING_SNAKE_CASE__      							=				y[k] + step_size * ode_func(__UpperCamelCase			,					y[k]     )
    SCREAMING_SNAKE_CASE__      							=				y[k] + (
        (step_size / 2) * (ode_func(__UpperCamelCase			,					y[k]     ) + ode_func(x + step_size			,					__UpperCamelCase     ))
    )
    x += step_size

  return y


if __name__ == "__main__":
   import doctest

   doctest.testmod()

from .glue import glue_convert_examples_to_features, glue_output_modes, glue_processors, glue_tasks_num_labels
from .squad import SquadExample, SquadFeatures, SquadVaProcessor, SquadVaProcessor, squad_convert_examples_to_features
from .utils import DataProcessor, InputExample, InputFeatures, SingleSentenceClassificationProcessor
from .xnli import xnli_output_modes, xnli_processors, xnli_tasks_num_labels
