
from __future__ import annotations




def 				a						(							snake_case__:					list						,   snake_case__:					int						,   snake_case__:					int						,   snake_case__:					int					):


				'''simple docstring'''
				lowercase_       =					[]
				lowercase_  ,	lowercase_       =					input_list[low:mid], input_list[mid : high + 1]
				while left and right:
								result.append((left if left[0] <= right[0] else right).pop(0					)					)
				lowercase_       =					result + left + right
				return input_list




def 				a						(							snake_case__:					list					):


				'''simple docstring'''
				if len(snake_case__					) <= 1:
								return input_list
				lowercase_       =					list(snake_case__					)

				# iteration for two-way merging
				lowercase_       =					2
				while p <= len(snake_case__					):
								# getting low, high and middle value for merge-sort of single list
								for i in range(0						,   len(snake_case__					)						,   snake_case__					):
												lowercase_       =					i
												lowercase_       =					i + p - 1
												lowercase_       =					(low + high + 1) // 2
												lowercase_       =					merge(snake_case__						,   snake_case__						,   snake_case__						,   snake_case__					)
								# final merge of last two parts
								if p * 2 >= len(snake_case__					):
												lowercase_       =					i
												lowercase_       =					merge(snake_case__						,   0						,   snake_case__						,   len(snake_case__					) - 1					)
												break
								p *= 2

				return input_list


if __name__ == "__main__":
						__a  			=					input('Enter numbers separated by a comma:\n').strip()
						if user_input == "":
												__a  			=					[]
						else:
												__a  			=					[int(item.strip()) for item in user_input.split(',')]
						print(iter_merge_sort(unsorted))






import tempfile
import unittest

from make_student import create_student_by_copying_alternating_layers

from transformers import AutoConfig
from transformers.file_utils import cached_property
from transformers.testing_utils import require_torch


__a  			=					'sshleifer/bart-tiny-random'
__a  			=					'patrickvonplaten/t5-tiny-random'
@require_torch
class  lowercase__(				unittest.TestCase							):



	"""simple docstring"""




	@cached_property
	def 						_lowercase  (       self  :			Any       )       ->     Tuple:
					return AutoConfig.from_pretrained(SCREAMING_SNAKE_CASE_       )
	def 						_lowercase  (       self  :			int       )       ->     List[Any]:
					lowercase_  ,	*lowercase_       =					create_student_by_copying_alternating_layers(SCREAMING_SNAKE_CASE_       ,							tempfile.mkdtemp()       ,							e=1       ,							d=1       )
					self.assertEqual(student.config.num_hidden_layers       ,							1       )
	def 						_lowercase  (       self  :			Union[str, Any]       )       ->     Optional[int]:
					lowercase_  ,	*lowercase_       =					create_student_by_copying_alternating_layers(SCREAMING_SNAKE_CASE_       ,							tempfile.mkdtemp()       ,							e=1       ,							d=SCREAMING_SNAKE_CASE_       )
	def 						_lowercase  (       self  :			List[str]       )       ->     List[Any]:
					lowercase_  ,	*lowercase_       =					create_student_by_copying_alternating_layers(SCREAMING_SNAKE_CASE_       ,							tempfile.mkdtemp()       ,							e=1       ,							d=SCREAMING_SNAKE_CASE_       )
					self.assertEqual(student.config.encoder_layers       ,							1       )
					self.assertEqual(student.config.decoder_layers       ,							self.teacher_config.encoder_layers       )
	def 						_lowercase  (       self  :			List[Any]       )       ->     List[Any]:
					lowercase_  ,	*lowercase_       =					create_student_by_copying_alternating_layers(SCREAMING_SNAKE_CASE_       ,							tempfile.mkdtemp()       ,							e=1       ,							d=1       )
					self.assertEqual(student.config.encoder_layers       ,							1       )
					self.assertEqual(student.config.decoder_layers       ,							1       )




	def 						_lowercase  (       self  :			Union[str, Any]       )       ->     Optional[int]:
					with self.assertRaises(SCREAMING_SNAKE_CASE_       ):
									create_student_by_copying_alternating_layers(SCREAMING_SNAKE_CASE_       ,							tempfile.mkdtemp()       ,							e=SCREAMING_SNAKE_CASE_       ,							d=SCREAMING_SNAKE_CASE_       )




