



"""simple docstring"""





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


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







       '''simple docstring'''


       @cached_property
       def 	lowercase__							(				self     :    str       )					->		int:


             '''simple docstring'''




             return AutoConfig.from_pretrained(_UpperCAmelCase       )



       def 	lowercase__							(				self     :    Dict       )					->		Optional[Any]:


             '''simple docstring'''




             UpperCAmelCase_					,       *UpperCAmelCase_     					=				create_student_by_copying_alternating_layers(_UpperCAmelCase						,							tempfile.mkdtemp()						,							e=1						,							d=1       )
             self.assertEqual(student.config.num_hidden_layers						,							1       )



       def 	lowercase__							(				self     :    str       )					->		Optional[int]:


             '''simple docstring'''




             UpperCAmelCase_					,       *UpperCAmelCase_     					=				create_student_by_copying_alternating_layers(_UpperCAmelCase						,							tempfile.mkdtemp()						,							e=1						,							d=_UpperCAmelCase       )



       def 	lowercase__							(				self     :    List[Any]       )					->		Optional[Any]:


             '''simple docstring'''




             UpperCAmelCase_					,       *UpperCAmelCase_     					=				create_student_by_copying_alternating_layers(_UpperCAmelCase						,							tempfile.mkdtemp()						,							e=1						,							d=_UpperCAmelCase       )
             self.assertEqual(student.config.encoder_layers						,							1       )
             self.assertEqual(student.config.decoder_layers						,							self.teacher_config.encoder_layers       )



       def 	lowercase__							(				self     :    Dict       )					->		Tuple:


             '''simple docstring'''




             UpperCAmelCase_					,       *UpperCAmelCase_     					=				create_student_by_copying_alternating_layers(_UpperCAmelCase						,							tempfile.mkdtemp()						,							e=1						,							d=1       )
             self.assertEqual(student.config.encoder_layers						,							1       )
             self.assertEqual(student.config.decoder_layers						,							1       )







       def 	lowercase__							(				self     :    List[str]       )					->		Tuple:


             '''simple docstring'''




             with self.assertRaises(_UpperCAmelCase       ):
                   create_student_by_copying_alternating_layers(_UpperCAmelCase						,							tempfile.mkdtemp()						,							e=_UpperCAmelCase						,							d=_UpperCAmelCase       )












"""simple docstring"""





def   a    (     __UpperCAmelCase      :    List[Any]  )    ->							str:
						__magic_name__:	Optional[int]							=       [0] * len(__UpperCAmelCase  )
						__magic_name__:	str							=       []
						__magic_name__:	Any							=       []
						__magic_name__:	Union[str, Any]							=       0

						for values in graph.values():
												for i in values:
																		indegree[i] += 1

						for i in range(len(__UpperCAmelCase  )  ):
												if indegree[i] == 0:
																		queue.append(__UpperCAmelCase  )

						while queue:
												__magic_name__:	Optional[Any]							=       queue.pop(0  )
												cnt += 1
												topo.append(__UpperCAmelCase  )
												for x in graph[vertex]:
																		indegree[x] -= 1
																		if indegree[x] == 0:
																								queue.append(__UpperCAmelCase  )

						if cnt != len(__UpperCAmelCase  ):
												print("""Cycle exists"""  )
						else:
												print(__UpperCAmelCase  )


# Adjacency List of Graph
__lowerCamelCase							=  {0: [1, 2], 1: [3], 2: [3], 3: [4, 5], 4: [], 5: []}

topological_sort(graph)



