'''simple docstring'''


from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


snake_case__					:      str				      =  {'''configuration_glpn''': ['''GLPN_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''GLPNConfig''']}

try:
 if not is_vision_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 snake_case__					:      Optional[Any]				      =  ['''GLPNFeatureExtractor''']
 snake_case__					:      Any				      =  ['''GLPNImageProcessor''']

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 snake_case__					:      Tuple				      =  [
     '''GLPN_PRETRAINED_MODEL_ARCHIVE_LIST''',
     '''GLPNForDepthEstimation''',
     '''GLPNLayer''',
     '''GLPNModel''',
     '''GLPNPreTrainedModel''',
 ]


if TYPE_CHECKING:
 from .configuration_glpn import GLPN_PRETRAINED_CONFIG_ARCHIVE_MAP, GLPNConfig

 try:
  if not is_vision_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .feature_extraction_glpn import GLPNFeatureExtractor
  from .image_processing_glpn import GLPNImageProcessor

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_glpn import (
      GLPN_PRETRAINED_MODEL_ARCHIVE_LIST,
      GLPNForDepthEstimation,
      GLPNLayer,
      GLPNModel,
      GLPNPreTrainedModel,
  )


else:
 import sys

 snake_case__					:      Any				      =  _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)







'''simple docstring'''


from __future__ import annotations

from collections import deque
from collections.abc import Iterator
from dataclasses import dataclass






@dataclass
class 					__SCREAMING_SNAKE_CASE						:







  '''simple docstring'''






  lowerCamelCase_		:int
  lowerCamelCase_		:int







class 					__SCREAMING_SNAKE_CASE						:







  '''simple docstring'''






  def __init__(			self				,		snake_case_						):




       '''simple docstring'''

       UpperCAmelCase_							:       list[list[Edge]]       =				[[] for _ in range(snake_case_						)]
       UpperCAmelCase_							:       Any       =				size


  def __getitem__(			self				,		snake_case_						):




       '''simple docstring'''

       return iter(self._graph[vertex]						)


  @property
  def _UpperCamelCase					(			self						):




       '''simple docstring'''

       return self._size


  def _UpperCamelCase					(			self				,		snake_case_				,		snake_case_				,		snake_case_						):




       '''simple docstring'''

       if weight not in (0, 1):
            raise ValueError('Edge weight must be either 0 or 1.'						)

       if to_vertex < 0 or to_vertex >= self.size:
            raise ValueError('Vertex indexes must be in [0; size).'						)

       self._graph[from_vertex].append(Edge(snake_case_				,		snake_case_						)						)






  def _UpperCamelCase					(			self				,		snake_case_				,		snake_case_						):




       '''simple docstring'''

       UpperCAmelCase_							:       Optional[int]       =				deque([start_vertex]						)
       UpperCAmelCase_							:       list[int | None]       =				[None] * self.size
       UpperCAmelCase_							:       str       =				0

       while queue:
            UpperCAmelCase_							:       Optional[int]       =				queue.popleft()
            UpperCAmelCase_							:       List[str]       =				distances[current_vertex]
            if current_distance is None:
                 continue

            for edge in self[current_vertex]:
                 UpperCAmelCase_							:       Union[str, Any]       =				current_distance + edge.weight
                 UpperCAmelCase_							:       Union[str, Any]       =				distances[edge.destination_vertex]
                 if (
                     isinstance(snake_case_				,		snake_case_						)
                     and new_distance >= dest_vertex_distance
                 ):
                      continue
                 UpperCAmelCase_							:       Optional[Any]       =				new_distance
                 if edge.weight == 0:
                      queue.appendleft(edge.destination_vertex						)
                 else:
                      queue.append(edge.destination_vertex						)

       if distances[finish_vertex] is None:
            raise ValueError('No path from start_vertex to finish_vertex.'						)

       return distances[finish_vertex]


if __name__ == "__main__":
 import doctest

 doctest.testmod()






