




"""simple docstring"""


def  UpperCAmelCase__	(snake_case__							: Optional[Any]   ):
  """simple docstring"""

  _snake_case							:		Optional[Any]								=  [0] * len(snake_case__   )
  _snake_case							:		List[str]								=  []
  _snake_case							:		Tuple								=  [1] * len(snake_case__   )

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

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

  while queue:
    _snake_case							:		Union[str, Any]								=  queue.pop(0   )
    for x in graph[vertex]:
      indegree[x] -= 1

      if long_dist[vertex] + 1 > long_dist[x]:
        _snake_case							:		Dict								=  long_dist[vertex] + 1

      if indegree[x] == 0:
        queue.append(snake_case__   )

  print(max(snake_case__   )   )


# Adjacency list of Graph
A_      =    {0: [2, 3, 4], 1: [2, 7], 2: [5], 3: [5, 7], 4: [7], 5: [6], 6: [7], 7: []}






longest_distance(graph)








"""simple docstring"""


from .data_collator import (
    DataCollatorForLanguageModeling,
    DataCollatorForPermutationLanguageModeling,
    DataCollatorForSeqaSeq,
    DataCollatorForSOP,
    DataCollatorForTokenClassification,
    DataCollatorForWholeWordMask,
    DataCollatorWithPadding,
    DefaultDataCollator,
    default_data_collator,
)
from .metrics import glue_compute_metrics, xnli_compute_metrics
from .processors import (
    DataProcessor,
    InputExample,
    InputFeatures,
    SingleSentenceClassificationProcessor,
    SquadExample,
    SquadFeatures,
    SquadVaProcessor,
    SquadVaProcessor,
    glue_convert_examples_to_features,
    glue_output_modes,
    glue_processors,
    glue_tasks_num_labels,
    squad_convert_examples_to_features,
    xnli_output_modes,
    xnli_processors,
    xnli_tasks_num_labels,
)


