



"""simple docstring"""






snake_case   					=				{
    '''A''': ['''B''', '''C''', '''E'''],
    '''B''': ['''A''', '''D''', '''E'''],
    '''C''': ['''A''', '''F''', '''G'''],
    '''D''': ['''B'''],
    '''E''': ['''A''', '''B''', '''D'''],
    '''F''': ['''C'''],
    '''G''': ['''C'''],
}




def 			snake_case		(		lowerCAmelCase_  ,						lowerCAmelCase_  ,						lowerCAmelCase_	)						->				list[str]:
  _snake_case   	=      set()
  # keep track of all the paths to be checked
  _snake_case   	=      [[start]]

  # return path if start is goal
  if start == goal:
    return [start]

  # keeps looping until all possible paths have been checked
  while queue:
    # pop the first path from the queue
    _snake_case   	=      queue.pop(0	)
    # get the last node from the path
    _snake_case   	=      path[-1]
    if node not in explored:
      _snake_case   	=      graph[node]
      # go through all neighbour nodes, construct a new path and
      # push it into the queue
      for neighbour in neighbours:
        _snake_case   	=      list(lowerCAmelCase_	)
        new_path.append(lowerCAmelCase_	)
        queue.append(lowerCAmelCase_	)
        # return path if neighbour is goal
        if neighbour == goal:
          return new_path

            # mark node as explored
      explored.add(lowerCAmelCase_	)

    # in case there's no path between the 2 nodes
  return []




def 			snake_case		(		lowerCAmelCase_  ,						lowerCAmelCase_  ,						lowerCAmelCase_	)						->				int:
  if not graph or start not in graph or target not in graph:
    return -1
  if start == target:
    return 0
  _snake_case   	=      [start]
  _snake_case   	=      set(lowerCAmelCase_	)
  # Keep tab on distances from `start` node.
  _snake_case   	=      {start: 0, target: -1}
  while queue:
    _snake_case   	=      queue.pop(0	)
    if node == target:
      _snake_case   	=      (
          dist[node] if dist[target] == -1 else min(dist[target]  ,						dist[node]	)
      )
    for adjacent in graph[node]:
      if adjacent not in visited:
        visited.add(lowerCAmelCase_	)
        queue.append(lowerCAmelCase_	)
        _snake_case   	=      dist[node] + 1
  return dist[target]


if __name__ == "__main__":
     print(bfs_shortest_path(demo_graph, '''G''', '''D'''))  # returns ['G', 'C', 'A', 'B', 'D']
     print(bfs_shortest_path_distance(demo_graph, '''G''', '''D'''))  # returns 4










'''simple docstring'''

import os
import unittest

from transformers import FunnelTokenizer, FunnelTokenizerFast
from transformers.models.funnel.tokenization_funnel import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin






@require_tokenizers
class 						a_		(     snake_case    ,   unittest.TestCase    ):
							UpperCAmelCase			:		int        =				FunnelTokenizer
							UpperCAmelCase			:		Tuple        =				FunnelTokenizerFast
							UpperCAmelCase			:		List[str]        =				True
							UpperCAmelCase			:		Tuple        =				True


							def    UpperCamelCase     (				self   :						Optional[Any]			)			->					Optional[Any]:
										super().setUp()

										snake_case:    Optional[Any]      							=[
										    '<unk>',
										    '<cls>',
										    '<sep>',
										    'want',
										    '##want',
										    '##ed',
										    'wa',
										    'un',
										    'runn',
										    '##ing',
										    ',',
										    'low',
										    'lowest',
										]
										snake_case:    Any      							=os.path.join(self.tmpdirname      ,						VOCAB_FILES_NAMES['vocab_file']			)
										with open(self.vocab_file      ,						'w'      ,						encoding='utf-8'			) as vocab_writer:
													vocab_writer.write(''.join([x + '\n' for x in vocab_tokens]			)			)


							def    UpperCamelCase     (				self   :						Tuple      ,						**a_   :						str			)			->					Any:
										return FunnelTokenizer.from_pretrained(self.tmpdirname      ,						**a_			)


							def    UpperCamelCase     (				self   :						List[Any]      ,						**a_   :						int			)			->					str:
										return FunnelTokenizerFast.from_pretrained(self.tmpdirname      ,						**a_			)


							def    UpperCamelCase     (				self   :						Any      ,						a_   :						Union[str, Any]			)			->					Union[str, Any]:
										snake_case:    List[str]      							='UNwant\u00E9d,running'
										snake_case:    Dict      							='unwanted, running'
										return input_text, output_text


							def    UpperCamelCase     (				self   :						Optional[int]			)			->					List[Any]:
										snake_case:    Union[str, Any]      							=self.tokenizer_class(self.vocab_file			)

										snake_case:    Dict      							=tokenizer.tokenize('UNwant\u00E9d,running'			)
										self.assertListEqual(a_      ,						['un', '##want', '##ed', ',', 'runn', '##ing']			)
										self.assertListEqual(tokenizer.convert_tokens_to_ids(a_			)      ,						[7, 4, 5, 1_0, 8, 9]			)




							def    UpperCamelCase     (				self   :						List[str]			)			->					Dict:
										snake_case:    Optional[Any]      							=self.get_tokenizers(do_lower_case=a_			)
										for tokenizer in tokenizers:
													snake_case:    str      							=tokenizer('UNwant\u00E9d,running'			)
													snake_case:    Union[str, Any]      							=len(inputs['input_ids']			) - 1
													self.assertListEqual(inputs['token_type_ids']      ,						[2] + [0] * sentence_len			)

													snake_case:    List[str]      							=tokenizer('UNwant\u00E9d,running'      ,						'UNwant\u00E9d,running'			)
													self.assertListEqual(inputs['token_type_ids']      ,						[2] + [0] * sentence_len + [1] * sentence_len			)




