


from __future__ import annotations

def 		snake_case_   (				lowercase__     :    list       ,     lowercase__     :    list     ):






				'''simple docstring'''






				_lowerCAmelCase  						=[None] * (len(lowercase__     ) + len(lowercase__     ))

				_lowerCAmelCase  						=0  # pointer to current index for left Half
				_lowerCAmelCase  						=0  # pointer to current index for the right Half
				_lowerCAmelCase  						=0  # pointer to current index for the sorted array Half

				while pointera < len(lowercase__     ) and pointera < len(lowercase__     ):
								if left_half[pointera] < right_half[pointera]:
												_lowerCAmelCase  						=left_half[pointera]
												pointera += 1
												index += 1
								else:
												_lowerCAmelCase  						=right_half[pointera]
												pointera += 1
												index += 1
				while pointera < len(lowercase__     ):
								_lowerCAmelCase  						=left_half[pointera]
								pointera += 1
								index += 1

				while pointera < len(lowercase__     ):
								_lowerCAmelCase  						=right_half[pointera]
								pointera += 1
								index += 1

				return sorted_array

def 		snake_case_   (				lowercase__     :    list     ):






				'''simple docstring'''






				if len(lowercase__     ) <= 1:
								return array
				# the actual formula to calculate the middle element = left + (right - left) // 2
				# this avoids integer overflow in case of large N
				_lowerCAmelCase  						=0 + (len(lowercase__     ) - 0) // 2

				# Split the array into halves till the array length becomes equal to One
				# merge the arrays of single length returned by mergeSort function and
				# pass them into the merge arrays function which merges the array
				_lowerCAmelCase  						=array[:middle]
				_lowerCAmelCase  						=array[middle:]

				return merge(merge_sort(lowercase__     )       ,     merge_sort(lowercase__     )     )


if __name__ == "__main__":
		import doctest

		doctest.testmod()





__SCREAMING_SNAKE_CASE	:							Optional[Any]           =  '''
# Transformers installation
! pip install transformers datasets
# To install from source instead of the last release, comment the command above and uncomment the following one.
# ! pip install git+https://github.com/huggingface/transformers.git
'''

__SCREAMING_SNAKE_CASE	:							Optional[int]           =  [{'''type''': '''code''', '''content''': INSTALL_CONTENT}]
__SCREAMING_SNAKE_CASE	:							Optional[int]           =  {
    '''{processor_class}''': '''FakeProcessorClass''',
    '''{model_class}''': '''FakeModelClass''',
    '''{object_class}''': '''FakeObjectClass''',
}

