





from typing import TYPE_CHECKING

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


__UpperCAmelCase       :   List[str]				       =							{
    "configuration_trajectory_transformer": [
        "TRAJECTORY_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "TrajectoryTransformerConfig",
    ],
}

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      __UpperCAmelCase       :   Union[str, Any]				       =							[
          "TRAJECTORY_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST",
          "TrajectoryTransformerModel",
          "TrajectoryTransformerPreTrainedModel",
          "load_tf_weights_in_trajectory_transformer",
      ]


if TYPE_CHECKING:
      from .configuration_trajectory_transformer import (
          TRAJECTORY_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
          TrajectoryTransformerConfig,
      )

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_trajectory_transformer import (
                TRAJECTORY_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
                TrajectoryTransformerModel,
                TrajectoryTransformerPreTrainedModel,
                load_tf_weights_in_trajectory_transformer,
            )


else:
      import sys

      __UpperCAmelCase       :   int				       =							_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)













from __future__ import annotations

from sys import maxsize
from typing import Generic, TypeVar

__UpperCAmelCase       :   str				       =							TypeVar("T")







def 			A__							(    SCREAMING_SNAKE_CASE__)   ->    int:
  return (position - 1) // 2







def 			A__							(    SCREAMING_SNAKE_CASE__)   ->    int:
  return (2 * position) + 1







def 			A__							(    SCREAMING_SNAKE_CASE__)   ->    int:
  return (2 * position) + 2







class     __snake_case       (							Generic[T]			):





       '''simple docstring'''







       def __init__(  self :    Tuple		):
         __snake_case:						list[tuple[T, int]]   =						[]
         __snake_case:						dict[T, int]   =						{}
         __snake_case:						int   =						0




       def __len__(  self :    Tuple		):
         return self.elements




       def __repr__(  self :    Optional[int]		):
         return str(self.heap		)




       def 							UpperCAmelCase__ (  self :    List[Any]		):
         # Check if the priority queue is empty
         return self.elements == 0




       def 							UpperCAmelCase__ (  self :    List[Any]							,				A :    T							,				A :    int		):
         # Add an element with given priority to the queue
         self.heap.append((elem, weight)		)
         __snake_case:						Optional[Any]   =						self.elements
         self.elements += 1
         self._bubble_up(A		)




       def 							UpperCAmelCase__ (  self :    List[Any]		):
         # Remove and return the element with lowest weight (highest priority)
         if self.elements > 1:
           self._swap_nodes(0							,				self.elements - 1		)
         __snake_case  ,   __snake_case:						Union[str, Any]   =						self.heap.pop()
         del self.position_map[elem]
         self.elements -= 1
         if self.elements > 0:
           __snake_case  ,   __snake_case:						int   =						self.heap[0]
           self._bubble_down(A		)
         return elem




       def 							UpperCAmelCase__ (  self :    Any							,				A :    T							,				A :    int		):
         # Update the weight of the given key
         __snake_case:						Dict   =						self.position_map[elem]
         __snake_case:						Optional[Any]   =						(elem, weight)
         if position > 0:
           __snake_case:						Optional[int]   =						get_parent_position(A		)
           __snake_case  ,   __snake_case:						Dict   =						self.heap[parent_position]
           if parent_weight > weight:
             self._bubble_up(A		)
           else:
             self._bubble_down(A		)
         else:
           self._bubble_down(A		)




       def 							UpperCAmelCase__ (  self :    int							,				A :    T		):
         # Place a node at the proper position (upward movement) [to be used internally
         # only]
         __snake_case:						int   =						self.position_map[elem]
         if curr_pos == 0:
           return None
         __snake_case:						Optional[Any]   =						get_parent_position(A		)
         __snake_case  ,   __snake_case:						Tuple   =						self.heap[curr_pos]
         __snake_case  ,   __snake_case:						Optional[Any]   =						self.heap[parent_position]
         if parent_weight > weight:
           self._swap_nodes(A							,				A		)
           return self._bubble_up(A		)
         return None




       def 							UpperCAmelCase__ (  self :    List[str]							,				A :    T		):
         # Place a node at the proper position (downward movement) [to be used
         # internally only]
         __snake_case:						Any   =						self.position_map[elem]
         __snake_case  ,   __snake_case:						int   =						self.heap[curr_pos]
         __snake_case:						Union[str, Any]   =						get_child_left_position(A		)
         __snake_case:						Dict   =						get_child_right_position(A		)
         if child_left_position < self.elements and child_right_position < self.elements:
           __snake_case  ,   __snake_case:						Any   =						self.heap[child_left_position]
           __snake_case  ,   __snake_case:						List[str]   =						self.heap[child_right_position]
           if child_right_weight < child_left_weight and child_right_weight < weight:
             self._swap_nodes(A							,				A		)
             return self._bubble_down(A		)
         if child_left_position < self.elements:
           __snake_case  ,   __snake_case:						List[Any]   =						self.heap[child_left_position]
           if child_left_weight < weight:
             self._swap_nodes(A							,				A		)
             return self._bubble_down(A		)
         else:
           return None
         if child_right_position < self.elements:
           __snake_case  ,   __snake_case:						List[Any]   =						self.heap[child_right_position]
           if child_right_weight < weight:
             self._swap_nodes(A							,				A		)
             return self._bubble_down(A		)
         return None






       def 							UpperCAmelCase__ (  self :    int							,				A :    int							,				A :    int		):
         # Swap the nodes at the given positions
         __snake_case:						Optional[int]   =						self.heap[nodea_pos][0]
         __snake_case:						Optional[Any]   =						self.heap[nodea_pos][0]
         __snake_case  ,   __snake_case:						Tuple   =						(
             self.heap[nodea_pos],
             self.heap[nodea_pos],
         )
         __snake_case:						Any   =						nodea_pos
         __snake_case:						str   =						nodea_pos







class     __snake_case       (							Generic[T]			):





       '''simple docstring'''







       def __init__(  self :    Any		):
         __snake_case:						dict[T, dict[T, int]]   =						{}
         __snake_case:						int   =						0




       def __repr__(  self :    Dict		):
         return str(self.connections		)




       def __len__(  self :    List[str]		):
         return self.nodes




       def 							UpperCAmelCase__ (  self :    Optional[Any]							,				A :    T		):
         # Add a node in the graph if it is not in the graph
         if node not in self.connections:
           __snake_case:						List[str]   =						{}
           self.nodes += 1






       def 							UpperCAmelCase__ (  self :    Optional[Any]							,				A :    T							,				A :    T							,				A :    int		):
         # Add an edge between 2 nodes in the graph
         self.add_node(A		)
         self.add_node(A		)
         __snake_case:						Optional[Any]   =						weight
         __snake_case:						str   =						weight







def 			A__							(    SCREAMING_SNAKE_CASE__					,					)   ->    tuple[dict[T, int], dict[T, T | None]]:
  __snake_case:						dict[T, int]   =						{node: maxsize for node in graph.connections}
  __snake_case:						dict[T, T | None]   =						{node: None for node in graph.connections}

  __snake_case:						MinPriorityQueue[T]   =						MinPriorityQueue()
  for node, weight in dist.items():
    priority_queue.push(SCREAMING_SNAKE_CASE__					,					SCREAMING_SNAKE_CASE__)

  if priority_queue.is_empty():
    return dist, parent

  # initialization
  __snake_case:						Optional[int]   =						priority_queue.extract_min()
  __snake_case:						Any   =						0
  for neighbour in graph.connections[node]:
    if dist[neighbour] > dist[node] + graph.connections[node][neighbour]:
      __snake_case:						Tuple   =						dist[node] + graph.connections[node][neighbour]
      priority_queue.update_key(SCREAMING_SNAKE_CASE__					,					dist[neighbour])
      __snake_case:						Optional[int]   =						node

    # running prim's algorithm
  while not priority_queue.is_empty():
    __snake_case:						Optional[int]   =						priority_queue.extract_min()
    for neighbour in graph.connections[node]:
      if dist[neighbour] > dist[node] + graph.connections[node][neighbour]:
        __snake_case:						Tuple   =						dist[node] + graph.connections[node][neighbour]
        priority_queue.update_key(SCREAMING_SNAKE_CASE__					,					dist[neighbour])
        __snake_case:						List[Any]   =						node
  return dist, parent






