'''simple docstring'''

from __future__ import annotations

from typing import Generic, TypeVar

__a: Optional[Any]          =   TypeVar("""T""")



class 			UpperCAmelCase  (						Generic[T]					):





       '''simple docstring'''



       def __init__(						self	,   __lowerCAmelCase )  ->  None:
        lowercase__				:    int  =					data
        lowercase__				:    int  =					self
        lowercase__				:    Dict  =					0



class 			UpperCAmelCase  (						Generic[T]					):





       '''simple docstring'''



       def __init__(						self )  ->  None:
        # map from node name to the node object
        lowercase__				:    dict[T, DisjointSetTreeNode[T]]  =					{}

       def _lowerCAmelCase(						self	,   __lowerCAmelCase )  ->  None:
        # create a new set with x as its member
        lowercase__				:    Tuple  =					DisjointSetTreeNode(__lowerCAmelCase )

       def _lowerCAmelCase(						self	,   __lowerCAmelCase )  ->  DisjointSetTreeNode[T]:
        # find the set x belongs to (with path-compression)
        lowercase__				:    List[Any]  =					self.map[data]
        if elem_ref != elem_ref.parent:
         lowercase__				:    Tuple  =					self.find_set(elem_ref.parent.data )
        return elem_ref.parent

       def _lowerCAmelCase(						self	,   __lowerCAmelCase	,   __lowerCAmelCase )  ->  None:
        # helper function for union operation
        if nodea.rank > nodea.rank:
         lowercase__				:    Tuple  =					nodea
        else:
         lowercase__				:    Dict  =					nodea
         if nodea.rank == nodea.rank:
          nodea.rank += 1


       def _lowerCAmelCase(						self	,   __lowerCAmelCase	,   __lowerCAmelCase )  ->  None:
        # merge 2 disjoint sets
        self.link(self.find_set(__lowerCAmelCase )	,   self.find_set(__lowerCAmelCase ) )



class 			UpperCAmelCase  (						Generic[T]					):





       '''simple docstring'''



       def __init__(						self )  ->  None:
        # connections: map from the node to the neighbouring nodes (with weights)
        lowercase__				:    dict[T, dict[T, int]]  =					{}

       def _lowerCAmelCase(						self	,   __lowerCAmelCase )  ->  None:
        # add a node ONLY if its not present in the graph
        if node not in self.connections:
         lowercase__				:    str  =					{}

       def _lowerCAmelCase(						self	,   __lowerCAmelCase	,   __lowerCAmelCase	,   __lowerCAmelCase )  ->  None:
        # add an edge with the given weight
        self.add_node(__lowerCAmelCase )
        self.add_node(__lowerCAmelCase )
        lowercase__				:    str  =					weight
        lowercase__				:    List[Any]  =					weight


       def _lowerCAmelCase(						self )  ->  GraphUndirectedWeighted[T]:
        lowercase__				:    List[str]  =					[]
        lowercase__				:    Optional[Any]  =					set()
        for start in self.connections:
         for end in self.connections[start]:
          if (start, end) not in seen:
           seen.add((end, start) )
           edges.append((start, end, self.connections[start][end]) )
        edges.sort(key=lambda __lowerCAmelCase : x[2] )

        # creating the disjoint set
        lowercase__				:    List[Any]  =					DisjointSetTree[T]()
        for node in self.connections:
         disjoint_set.make_set(__lowerCAmelCase )

        # MST generation
        lowercase__				:    List[str]  =					0
        lowercase__				:    Optional[int]  =					0
        lowercase__				:    Any  =					GraphUndirectedWeighted[T]()
        while num_edges < len(self.connections ) - 1:
         lowercase__ ,							lowercase__ ,							lowercase__				:    List[Any]  =					edges[index]
         index += 1
         lowercase__				:    Optional[int]  =					disjoint_set.find_set(__lowerCAmelCase )
         lowercase__				:    Tuple  =					disjoint_set.find_set(__lowerCAmelCase )
         if parent_u != parent_v:
          num_edges += 1
          graph.add_edge(__lowerCAmelCase	,   __lowerCAmelCase	,   __lowerCAmelCase )
          disjoint_set.union(__lowerCAmelCase	,   __lowerCAmelCase )
        return graph


'''simple docstring'''

from typing import TYPE_CHECKING

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


__a: Dict          =   {
    """configuration_ctrl""": ["""CTRL_PRETRAINED_CONFIG_ARCHIVE_MAP""", """CTRLConfig"""],
    """tokenization_ctrl""": ["""CTRLTokenizer"""],
}

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  __a: int          =   [
      """CTRL_PRETRAINED_MODEL_ARCHIVE_LIST""",
      """CTRLForSequenceClassification""",
      """CTRLLMHeadModel""",
      """CTRLModel""",
      """CTRLPreTrainedModel""",
  ]

try:
  if not is_tf_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  __a: int          =   [
      """TF_CTRL_PRETRAINED_MODEL_ARCHIVE_LIST""",
      """TFCTRLForSequenceClassification""",
      """TFCTRLLMHeadModel""",
      """TFCTRLModel""",
      """TFCTRLPreTrainedModel""",
  ]


if TYPE_CHECKING:
  from .configuration_ctrl import CTRL_PRETRAINED_CONFIG_ARCHIVE_MAP, CTRLConfig
  from .tokenization_ctrl import CTRLTokenizer

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_ctrl import (
        CTRL_PRETRAINED_MODEL_ARCHIVE_LIST,
        CTRLForSequenceClassification,
        CTRLLMHeadModel,
        CTRLModel,
        CTRLPreTrainedModel,
    )

  try:
    if not is_tf_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_tf_ctrl import (
        TF_CTRL_PRETRAINED_MODEL_ARCHIVE_LIST,
        TFCTRLForSequenceClassification,
        TFCTRLLMHeadModel,
        TFCTRLModel,
        TFCTRLPreTrainedModel,
    )

else:
  import sys

  __a: Dict          =   _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)

