




import time
import unittest

from transformers import is_torch_available
from transformers.testing_utils import require_torch, torch_device

from ..test_modeling_common import ids_tensor


if is_torch_available():
   import torch

   from transformers.generation import (
       MaxLengthCriteria,
       MaxNewTokensCriteria,
       MaxTimeCriteria,
       StoppingCriteriaList,
       validate_stopping_criteria,
   )





@require_torch
class 			lowerCamelCase_				( unittest.TestCase   ):


 '''simple docstring'''







 def  lowerCAmelCase_    (				self    :						int							,							_lowerCAmelCase    :						List[str]		):
       SCREAMING_SNAKE_CASE_      		=     3
       SCREAMING_SNAKE_CASE_      		=     250

       SCREAMING_SNAKE_CASE_      		=     ids_tensor((batch_size, length)							,							_lowerCAmelCase		)
       SCREAMING_SNAKE_CASE_      		=     torch.ones((batch_size, length)							,							device=_lowerCAmelCase							,							dtype=torch.float		) / length
       return input_ids, scores



 def  lowerCAmelCase_    (				self    :						Tuple		):
       SCREAMING_SNAKE_CASE_		,					SCREAMING_SNAKE_CASE_      		=     self._get_tensors(5		)

       SCREAMING_SNAKE_CASE_      		=     StoppingCriteriaList(
           [
               MaxLengthCriteria(max_length=10		),
               MaxTimeCriteria(max_time=0.1		),
           ]		)

       self.assertFalse(criteria(_lowerCAmelCase							,							_lowerCAmelCase		)		)

       SCREAMING_SNAKE_CASE_		,					SCREAMING_SNAKE_CASE_      		=     self._get_tensors(9		)
       self.assertFalse(criteria(_lowerCAmelCase							,							_lowerCAmelCase		)		)

       SCREAMING_SNAKE_CASE_		,					SCREAMING_SNAKE_CASE_      		=     self._get_tensors(10		)
       self.assertTrue(criteria(_lowerCAmelCase							,							_lowerCAmelCase		)		)



 def  lowerCAmelCase_    (				self    :						int		):
       SCREAMING_SNAKE_CASE_      		=     MaxLengthCriteria(max_length=10		)

       SCREAMING_SNAKE_CASE_		,					SCREAMING_SNAKE_CASE_      		=     self._get_tensors(5		)
       self.assertFalse(criteria(_lowerCAmelCase							,							_lowerCAmelCase		)		)

       SCREAMING_SNAKE_CASE_		,					SCREAMING_SNAKE_CASE_      		=     self._get_tensors(9		)
       self.assertFalse(criteria(_lowerCAmelCase							,							_lowerCAmelCase		)		)

       SCREAMING_SNAKE_CASE_		,					SCREAMING_SNAKE_CASE_      		=     self._get_tensors(10		)
       self.assertTrue(criteria(_lowerCAmelCase							,							_lowerCAmelCase		)		)



 def  lowerCAmelCase_    (				self    :						Any		):
       SCREAMING_SNAKE_CASE_      		=     MaxNewTokensCriteria(start_length=5							,							max_new_tokens=5		)

       SCREAMING_SNAKE_CASE_		,					SCREAMING_SNAKE_CASE_      		=     self._get_tensors(5		)
       self.assertFalse(criteria(_lowerCAmelCase							,							_lowerCAmelCase		)		)

       SCREAMING_SNAKE_CASE_		,					SCREAMING_SNAKE_CASE_      		=     self._get_tensors(9		)
       self.assertFalse(criteria(_lowerCAmelCase							,							_lowerCAmelCase		)		)

       SCREAMING_SNAKE_CASE_		,					SCREAMING_SNAKE_CASE_      		=     self._get_tensors(10		)
       self.assertTrue(criteria(_lowerCAmelCase							,							_lowerCAmelCase		)		)

       SCREAMING_SNAKE_CASE_      		=     StoppingCriteriaList([criteria]		)
       self.assertEqual(criteria_list.max_length							,							10		)



 def  lowerCAmelCase_    (				self    :						int		):
       SCREAMING_SNAKE_CASE_		,					SCREAMING_SNAKE_CASE_      		=     self._get_tensors(5		)

       SCREAMING_SNAKE_CASE_      		=     MaxTimeCriteria(max_time=0.1		)
       self.assertFalse(criteria(_lowerCAmelCase							,							_lowerCAmelCase		)		)

       SCREAMING_SNAKE_CASE_      		=     MaxTimeCriteria(max_time=0.1							,							initial_timestamp=time.time() - 0.2		)
       self.assertTrue(criteria(_lowerCAmelCase							,							_lowerCAmelCase		)		)




 def  lowerCAmelCase_    (				self    :						str		):
       validate_stopping_criteria(StoppingCriteriaList([MaxLengthCriteria(10		)]		)							,							10		)

       with self.assertWarns(_lowerCAmelCase		):
             validate_stopping_criteria(StoppingCriteriaList([MaxLengthCriteria(10		)]		)							,							11		)

       SCREAMING_SNAKE_CASE_      		=     validate_stopping_criteria(StoppingCriteriaList()							,							11		)

       self.assertEqual(len(_lowerCAmelCase		)							,							1		)





class 			lowerCamelCase_				:


 '''simple docstring'''







 def __init__(				self    :						str		):
       SCREAMING_SNAKE_CASE_      		=     {}



 def  lowerCAmelCase_    (				self    :						List[str]		):
       print(self.vertex		)
       for i in self.vertex:
             print(_lowerCAmelCase							,							' -> '							,							' -> '.join([str(_lowerCAmelCase		) for j in self.vertex[i]]		)		)



 def  lowerCAmelCase_    (				self    :						Union[str, Any]							,							_lowerCAmelCase    :						int							,							_lowerCAmelCase    :						int		):
       # check if vertex is already present,
       if from_vertex in self.vertex:
             self.vertex[from_vertex].append(_lowerCAmelCase		)
       else:
             # else make a new vertex
             SCREAMING_SNAKE_CASE_      		=     [to_vertex]



 def  lowerCAmelCase_    (				self    :						Optional[Any]		):
       # visited array for storing already visited nodes
       SCREAMING_SNAKE_CASE_      		=     [False] * len(self.vertex		)

       # call the recursive helper function
       for i in range(len(self.vertex		)		):
             if not visited[i]:
                   self.dfs_recursive(_lowerCAmelCase							,							_lowerCAmelCase		)




 def  lowerCAmelCase_    (				self    :						Tuple							,							_lowerCAmelCase    :						int							,							_lowerCAmelCase    :						list		):
       # mark start vertex as visited
       SCREAMING_SNAKE_CASE_      		=     True

       print(_lowerCAmelCase							,							end=' '		)

       # Recur for all the vertices that are adjacent to this node
       for i in self.vertex:
             if not visited[i]:
                   self.dfs_recursive(_lowerCAmelCase							,							_lowerCAmelCase		)


if __name__ == "__main__":
   lowerCamelCase__					:  List[Any]      							=				Graph()
   g.add_edge(0, 1)
   g.add_edge(0, 2)
   g.add_edge(1, 2)
   g.add_edge(2, 0)
   g.add_edge(2, 3)
   g.add_edge(3, 3)

   g.print_graph()
   print('DFS:')
   g.dfs()

   # OUTPUT:
   # 0  ->  1 -> 2
   # 1  ->  2
   # 2  ->  0 -> 3
   # 3  ->  3
   # DFS:
   #  0 1 2 3