




def 		lowerCAmelCase_ (						lowerCamelCase ):
				__magic_name__						:						Dict										=[0] * len(lowerCamelCase )
				__magic_name__						:						Any										=[]
				__magic_name__						:						Tuple										=[1] * len(lowerCamelCase )

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

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

				while queue:
								__magic_name__						:						List[str]										=queue.pop(0 )
								for x in graph[vertex]:
												indegree[x] -= 1

												if long_dist[vertex] + 1 > long_dist[x]:
																__magic_name__						:						str										=long_dist[vertex] + 1

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

				print(max(lowerCamelCase ) )


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



longest_distance(graph)











'''simple docstring'''






# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


A__							:  int    ={
    '''configuration_xmod''': [
        '''XMOD_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''XmodConfig''',
        '''XmodOnnxConfig''',
    ],
}

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      A__							:  List[str]    =[
          '''XMOD_PRETRAINED_MODEL_ARCHIVE_LIST''',
          '''XmodForCausalLM''',
          '''XmodForMaskedLM''',
          '''XmodForMultipleChoice''',
          '''XmodForQuestionAnswering''',
          '''XmodForSequenceClassification''',
          '''XmodForTokenClassification''',
          '''XmodModel''',
          '''XmodPreTrainedModel''',
      ]

if TYPE_CHECKING:
      from .configuration_xmod import XMOD_PRETRAINED_CONFIG_ARCHIVE_MAP, XmodConfig, XmodOnnxConfig

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_xmod import (
                XMOD_PRETRAINED_MODEL_ARCHIVE_LIST,
                XmodForCausalLM,
                XmodForMaskedLM,
                XmodForMultipleChoice,
                XmodForQuestionAnswering,
                XmodForSequenceClassification,
                XmodForTokenClassification,
                XmodModel,
                XmodPreTrainedModel,
            )

else:
      import sys

      A__							:  str    =_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)






