


"""simple docstring"""




import warnings

from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding







class lowerCAmelCase_						(			__lowercase	):

 '''simple docstring'''

 __snake_case												=  ["image_processor", "tokenizer"]
 __snake_case												=  "CLIPImageProcessor"
 __snake_case												=  ("CLIPTokenizer", "CLIPTokenizerFast")



 def __init__(     self		,				_UpperCAmelCase=None		,				_UpperCAmelCase=None		,				**_UpperCAmelCase ):
       snake_case_	=				None
       if "feature_extractor" in kwargs:
             warnings.warn(
                 '''The `feature_extractor` argument is deprecated and will be removed in v5, use `image_processor`'''
                 ''' instead.'''		,				snake_case_		,				)
             snake_case_	=				kwargs.pop('''feature_extractor''' )

       snake_case_	=				image_processor if image_processor is not None else feature_extractor
       if image_processor is None:
             raise ValueError('''You need to specify an `image_processor`.''' )
       if tokenizer is None:
             raise ValueError('''You need to specify a `tokenizer`.''' )

       super().__init__(snake_case_		,				snake_case_ )



 def __call__(     self		,				_UpperCAmelCase=None		,				_UpperCAmelCase=None		,				_UpperCAmelCase=None		,				**_UpperCAmelCase ):

       if text is None and images is None:
             raise ValueError('''You have to specify either text or images. Both cannot be none.''' )

       if text is not None:
             snake_case_	=				self.tokenizer(snake_case_		,				return_tensors=snake_case_		,				**snake_case_ )

       if images is not None:
             snake_case_	=				self.image_processor(snake_case_		,				return_tensors=snake_case_		,				**snake_case_ )

       if text is not None and images is not None:
             snake_case_	=				image_features.pixel_values
             return encoding
       elif text is not None:
             return encoding
       else:
             return BatchEncoding(data=dict(**snake_case_ )		,				tensor_type=snake_case_ )



 def 						UpperCamelCase__					(     self		,				*_UpperCAmelCase		,				**_UpperCAmelCase ):
       return self.tokenizer.batch_decode(*snake_case_		,				**snake_case_ )



 def 						UpperCamelCase__					(     self		,				*_UpperCAmelCase		,				**_UpperCAmelCase ):
       return self.tokenizer.decode(*snake_case_		,				**snake_case_ )



 @property
 def 						UpperCamelCase__					(     self ):
       snake_case_	=				self.tokenizer.model_input_names
       snake_case_	=				self.image_processor.model_input_names
       return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names ) )



 @property
 def 						UpperCamelCase__					(     self ):
       warnings.warn(
           '''`feature_extractor_class` is deprecated and will be removed in v5. Use `image_processor_class` instead.'''		,				snake_case_		,				)
       return self.image_processor_class





 @property
 def 						UpperCamelCase__					(     self ):
       warnings.warn(
           '''`feature_extractor` is deprecated and will be removed in v5. Use `image_processor` instead.'''		,				snake_case_		,				)
       return self.image_processor



from __future__ import annotations

import time

UpperCAmelCase      =   list[tuple[int, int]]

UpperCAmelCase      =   [
    [0, 0, 0, 0, 0, 0, 0],
    [0, 1, 0, 0, 0, 0, 0],  # 0 are free path whereas 1's are obstacles
    [0, 0, 0, 0, 0, 0, 0],
    [0, 0, 1, 0, 0, 0, 0],
    [1, 0, 1, 0, 0, 0, 0],
    [0, 0, 0, 0, 0, 0, 0],
    [0, 0, 0, 0, 1, 0, 0],
]

UpperCAmelCase      =   [[-1, 0], [0, -1], [1, 0], [0, 1]]  # up, left, down, right







class lowerCAmelCase_						:

 '''simple docstring'''

 def __init__(     self		,				_UpperCAmelCase		,				_UpperCAmelCase		,				_UpperCAmelCase		,				_UpperCAmelCase		,				_UpperCAmelCase ):
       snake_case_	=				pos_x
       snake_case_	=				pos_y
       snake_case_	=				(pos_y, pos_x)
       snake_case_	=				goal_x
       snake_case_	=				goal_y
       snake_case_	=				parent







class lowerCAmelCase_						:

 '''simple docstring'''

 def __init__(     self		,				_UpperCAmelCase		,				_UpperCAmelCase ):
       snake_case_	=				Node(start[1]		,				start[0]		,				goal[1]		,				goal[0]		,				_UpperCAmelCase )
       snake_case_	=				Node(goal[1]		,				goal[0]		,				goal[1]		,				goal[0]		,				_UpperCAmelCase )

       snake_case_	=				[self.start]
       snake_case_	=				False



 def 						UpperCamelCase__					(     self ):
       while self.node_queue:
             snake_case_	=				self.node_queue.pop(0 )

             if current_node.pos == self.target.pos:
                   snake_case_	=				True
                   return self.retrace_path(_UpperCAmelCase )

             snake_case_	=				self.get_successors(_UpperCAmelCase )

             for node in successors:
                   self.node_queue.append(_UpperCAmelCase )

       if not self.reached:
             return [self.start.pos]
       return None



 def 						UpperCamelCase__					(     self		,				_UpperCAmelCase ):
       snake_case_	=				[]
       for action in delta:
             snake_case_	=				parent.pos_x + action[1]
             snake_case_	=				parent.pos_y + action[0]
             if not (0 <= pos_x <= len(grid[0] ) - 1 and 0 <= pos_y <= len(_UpperCAmelCase ) - 1):
                   continue

             if grid[pos_y][pos_x] != 0:
                   continue

             successors.append(
                 Node(_UpperCAmelCase		,				_UpperCAmelCase		,				self.target.pos_y		,				self.target.pos_x		,				_UpperCAmelCase ) )
       return successors





 def 						UpperCamelCase__					(     self		,				_UpperCAmelCase ):
       snake_case_	=				node
       snake_case_	=				[]
       while current_node is not None:
             path.append((current_node.pos_y, current_node.pos_x) )
             snake_case_	=				current_node.parent
       path.reverse()
       return path







class lowerCAmelCase_						:

 '''simple docstring'''

 def __init__(     self		,				_UpperCAmelCase		,				_UpperCAmelCase ):
       snake_case_	=				BreadthFirstSearch(_UpperCAmelCase		,				_UpperCAmelCase )
       snake_case_	=				BreadthFirstSearch(_UpperCAmelCase		,				_UpperCAmelCase )
       snake_case_	=				False



 def 						UpperCamelCase__					(     self ):
       while self.fwd_bfs.node_queue or self.bwd_bfs.node_queue:
             snake_case_	=				self.fwd_bfs.node_queue.pop(0 )
             snake_case_	=				self.bwd_bfs.node_queue.pop(0 )

             if current_bwd_node.pos == current_fwd_node.pos:
                   snake_case_	=				True
                   return self.retrace_bidirectional_path(
                       _UpperCAmelCase		,				_UpperCAmelCase )

             snake_case_	=				current_bwd_node
             snake_case_	=				current_fwd_node

             snake_case_	=				{
                 self.fwd_bfs: self.fwd_bfs.get_successors(_UpperCAmelCase ),
                 self.bwd_bfs: self.bwd_bfs.get_successors(_UpperCAmelCase ),
             }

             for bfs in [self.fwd_bfs, self.bwd_bfs]:
                   for node in successors[bfs]:
                         bfs.node_queue.append(_UpperCAmelCase )

       if not self.reached:
             return [self.fwd_bfs.start.pos]
       return None





 def 						UpperCamelCase__					(     self		,				_UpperCAmelCase		,				_UpperCAmelCase ):
       snake_case_	=				self.fwd_bfs.retrace_path(_UpperCAmelCase )
       snake_case_	=				self.bwd_bfs.retrace_path(_UpperCAmelCase )
       bwd_path.pop()
       bwd_path.reverse()
       snake_case_	=				fwd_path + bwd_path
       return path


if __name__ == "__main__":
   # all coordinates are given in format [y,x]
   import doctest

   doctest.testmod()
   UpperCAmelCase      =   (0, 0)
   UpperCAmelCase      =   (len(grid) - 1, len(grid[0]) - 1)
   for elem in grid:
      print(elem)

   UpperCAmelCase      =   time.time()
   UpperCAmelCase      =   BreadthFirstSearch(init, goal)
   UpperCAmelCase      =   bfs.search()
   UpperCAmelCase      =   time.time() - start_bfs_time

   print("""Unidirectional BFS computation time : """, bfs_time)

   UpperCAmelCase      =   time.time()
   UpperCAmelCase      =   BidirectionalBreadthFirstSearch(init, goal)
   UpperCAmelCase      =   bd_bfs.search()
   UpperCAmelCase      =   time.time() - start_bd_bfs_time

   print("""Bidirectional BFS computation time : """, bd_bfs_time)