



import contextlib
import importlib
import io
import unittest

import transformers

# Try to import everything from transformers to ensure every object can be loaded.
from transformers import *  # noqa F406
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, require_flax, require_tf, require_torch
from transformers.utils import ContextManagers, find_labels, is_flax_available, is_tf_available, is_torch_available


if is_torch_available():
				from transformers import BertForPreTraining, BertForQuestionAnswering, BertForSequenceClassification

if is_tf_available():
				from transformers import TFBertForPreTraining, TFBertForQuestionAnswering, TFBertForSequenceClassification

if is_flax_available():
				from transformers import FlaxBertForPreTraining, FlaxBertForQuestionAnswering, FlaxBertForSequenceClassification


__snake_case     :Tuple			       =DUMMY_UNKNOWN_IDENTIFIER
# An actual model hosted on huggingface.co

__snake_case     :Tuple			       ='main'
# Default branch name
__snake_case     :Union[str, Any]			       ='f2c752cfc5c0ab6f4bdec59acea69eefbee381c2'
# One particular commit (not the top of `main`)
__snake_case     :List[str]			       ='aaaaaaa'
# This commit does not exist, so we should 404.

__snake_case     :int			       ='d9e9f15bc825e4b2c9249e9578f884bbcb5e3684'
# Sha-1 of config.json on the top of `main`, for checking purposes
__snake_case     :int			       ='4b243c475af8d0a7754e87d7d096c92e5199ec2fe168a2ee7998e3b8e9bcb1d3'






@contextlib.contextmanager
def  lowerCamelCase_	(      )       ->							Dict:

							'''simple docstring'''






							print('Welcome!'				)
							yield
							print('Bye!'				)






@contextlib.contextmanager
def  lowerCamelCase_	(      )       ->							Dict:

							'''simple docstring'''






							print('Bonjour!'				)
							yield
							print('Au revoir!'				)



class        lowerCAmelCase__					(  unittest.TestCase       ):


				def __UpperCamelCase						(							self      :  Optional[Any]       )		->     str:
											# If the spec is missing, importlib would not be able to import the module dynamically.
											assert transformers.__spec__ is not None
											assert importlib.util.find_spec('transformers'       ) is not None





class        lowerCAmelCase__					(  unittest.TestCase       ):


				@unittest.mock.patch('sys.stdout'						, new_callable=io.StringIO       )
				def __UpperCamelCase						(							self      :  str						, __UpperCamelCase      :  Union[str, Any]       )		->     Dict:
											with ContextManagers([]       ):
																		print('Transformers are awesome!'       )
											# The print statement adds a new line at the end of the output
											self.assertEqual(mock_stdout.getvalue()						, 'Transformers are awesome!\n'       )


				@unittest.mock.patch('sys.stdout'						, new_callable=io.StringIO       )
				def __UpperCamelCase						(							self      :  List[Any]						, __UpperCamelCase      :  Any       )		->     Tuple:
											with ContextManagers([context_en()]       ):
																		print('Transformers are awesome!'       )
											# The output should be wrapped with an English welcome and goodbye
											self.assertEqual(mock_stdout.getvalue()						, 'Welcome!\nTransformers are awesome!\nBye!\n'       )


				@unittest.mock.patch('sys.stdout'						, new_callable=io.StringIO       )
				def __UpperCamelCase						(							self      :  Union[str, Any]						, __UpperCamelCase      :  int       )		->     Optional[Any]:
											with ContextManagers([context_fr(), context_en()]       ):
																		print('Transformers are awesome!'       )
											# The output should be wrapped with an English and French welcome and goodbye
											self.assertEqual(mock_stdout.getvalue()						, 'Bonjour!\nWelcome!\nTransformers are awesome!\nBye!\nAu revoir!\n'       )


				@require_torch
				def __UpperCamelCase						(							self      :  Optional[Any]       )		->     List[str]:
											self.assertEqual(find_labels(__UpperCamelCase       )						, ['labels']       )
											self.assertEqual(find_labels(__UpperCamelCase       )						, ['labels', 'next_sentence_label']       )
											self.assertEqual(find_labels(__UpperCamelCase       )						, ['start_positions', 'end_positions']       )



											class        lowerCAmelCase__					(  _lowerCamelCase       ):
															pass





											self.assertEqual(find_labels(__UpperCamelCase       )						, ['labels']       )


				@require_tf
				def __UpperCamelCase						(							self      :  str       )		->     Optional[Any]:
											self.assertEqual(find_labels(__UpperCamelCase       )						, ['labels']       )
											self.assertEqual(find_labels(__UpperCamelCase       )						, ['labels', 'next_sentence_label']       )
											self.assertEqual(find_labels(__UpperCamelCase       )						, ['start_positions', 'end_positions']       )



											class        lowerCAmelCase__					(  _lowerCamelCase       ):
															pass





											self.assertEqual(find_labels(__UpperCamelCase       )						, ['labels']       )


				@require_flax
				def __UpperCamelCase						(							self      :  Dict       )		->     Dict:
											# Flax models don't have labels
											self.assertEqual(find_labels(__UpperCamelCase       )						, []       )
											self.assertEqual(find_labels(__UpperCamelCase       )						, []       )
											self.assertEqual(find_labels(__UpperCamelCase       )						, []       )



											class        lowerCAmelCase__					(  _lowerCamelCase       ):
															pass





											self.assertEqual(find_labels(__UpperCamelCase       )						, []       )




from collections.abc import Callable

import numpy as np






def  lowerCamelCase_	(      lowerCAmelCase__	:	Callable			,	lowerCAmelCase__	:	float			,	lowerCAmelCase__	:	float			,	lowerCAmelCase__	:	float			,	lowerCAmelCase__	:	float				)       ->							np.array:

							'''simple docstring'''






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

							for k in range(lowerCAmelCase__				):
														A      						=    y[k] + step_size * ode_func(lowerCAmelCase__			,	y[k]				)
														A      						=    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()