"""simple docstring"""



def    SCREAMING_SNAKE_CASE       (     snake_case):
     __snake_case				=							[0] * len(snake_case)
     __snake_case				=							[]
     __snake_case				=							[]
     __snake_case				=							0

     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				=							queue.pop(0)
          cnt += 1
          topo.append(snake_case)
          for x in graph[vertex]:
               indegree[x] -= 1
               if indegree[x] == 0:
                    queue.append(snake_case)

     if cnt != len(snake_case):
          print('''Cycle exists''')
     else:
          print(snake_case)


# Adjacency List of Graph
__lowercase		:		Union[str, Any]														=							{0: [1, 2], 1: [3], 2: [3], 3: [4, 5], 4: [], 5: []}




topological_sort(graph)
"""simple docstring"""



from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_torch_available,
)


__lowercase		:		Optional[Any]														=							{
    "configuration_falcon": ["FALCON_PRETRAINED_CONFIG_ARCHIVE_MAP", "FalconConfig"],
}

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       __lowercase		:		str														=							[
           "FALCON_PRETRAINED_MODEL_ARCHIVE_LIST",
           "FalconForCausalLM",
           "FalconModel",
           "FalconPreTrainedModel",
           "FalconForSequenceClassification",
           "FalconForTokenClassification",
           "FalconForQuestionAnswering",
       ]


if TYPE_CHECKING:
       from .configuration_falcon import FALCON_PRETRAINED_CONFIG_ARCHIVE_MAP, FalconConfig

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_falcon import (
                  FALCON_PRETRAINED_MODEL_ARCHIVE_LIST,
                  FalconForCausalLM,
                  FalconForQuestionAnswering,
                  FalconForSequenceClassification,
                  FalconForTokenClassification,
                  FalconModel,
                  FalconPreTrainedModel,
              )


else:
       import sys

       __lowercase		:		List[Any]														=							_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)