






import os
import tempfile
import unittest

from transformers.models.marian.convert_marian_tatoeba_to_pytorch import DEFAULT_REPO, TatoebaConverter
from transformers.testing_utils import slow
from transformers.utils import cached_property




@unittest.skipUnless(os.path.exists(UpperCamelCase						)					,							'Tatoeba directory does not exist.'						)
class 							lowerCAmelCase__  (	unittest.TestCase						):







					@cached_property
					def  _lowercase			(       self      :     Tuple):
											A__	:							Dict						    = tempfile.mkdtemp()
											return TatoebaConverter(save_dir=_A)







					@slow
					def  _lowercase			(       self      :     Any):
											self.resolver.convert_models(["heb-eng"])







					@slow
					def  _lowercase			(       self      :     Dict):
											A__	:							Any						    = self.resolver.write_model_card("opus-mt-he-en"			,		dry_run=_A)
											assert mmeta["long_pair"] == "heb-eng"




from collections.abc import Callable

import numpy as np
def 	snake_case__       (					__lowercase							,     __lowercase							,     __lowercase							,     __lowercase							,     __lowercase       )		->		np.array:







						"""simple docstring"""

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

						for k in range(__lowercase       ):
												A__	:							Any						    = y[k] + step_size * ode_func(__lowercase							,     y[k]       )
												A__	:							Any						    = y[k] + (
												    (step_size / 2) * (ode_func(__lowercase							,     y[k]       ) + ode_func(x + step_size							,     __lowercase       ))
												)
												x += step_size

						return y


if __name__ == "__main__":
		import doctest

		doctest.testmod()