



__snake_case       :	Tuple            ='\n# Installazione di Transformers\n! pip install transformers datasets\n# Per installare dalla fonte invece dell\'ultima versione rilasciata, commenta il comando sopra e\n# rimuovi la modalità commento al comando seguente.\n# ! pip install git+https://github.com/huggingface/transformers.git\n'

__snake_case       :	Union[str, Any]            =[{'type': 'code', 'content': INSTALL_CONTENT}]
__snake_case       :	List[Any]            ={
    '{processor_class}': 'FakeProcessorClass',
    '{model_class}': 'FakeModelClass',
    '{object_class}': 'FakeObjectClass',
}




from collections.abc import Callable

import numpy as np






def 			lowerCAmelCase__	(					lowerCamelCase_	:	Callable ,lowerCamelCase_	:	float ,lowerCamelCase_	:	float ,lowerCamelCase_	:	float ,lowerCamelCase_	:	float):





				'''simple docstring'''

				lowerCAmelCase__  :       Dict				=  int(np.ceil((x_end - xa) / step_size))
				lowerCAmelCase__  :       Any				=  np.zeros((n + 1,))
				lowerCAmelCase__  :       Union[str, Any]				=  ya
				lowerCAmelCase__  :       str				=  xa

				for k in range(lowerCamelCase_):
								lowerCAmelCase__  :       Tuple				=  y[k] + step_size * ode_func(lowerCamelCase_ ,y[k])
								lowerCAmelCase__  :       str				=  y[k] + (
								    (step_size / 2) * (ode_func(lowerCamelCase_ ,y[k]) + ode_func(x + step_size ,lowerCamelCase_))
								)
								x += step_size

				return y


if __name__ == "__main__":
							import doctest

							doctest.testmod()

