

from __future__ import annotations

from typing import Generic, TypeVar

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



class       __snake_case  (    Generic[T]       ):

  def __init__(					self						,		_A):
      SCREAMING_SNAKE_CASE_									=						data
      SCREAMING_SNAKE_CASE_									=						self
      SCREAMING_SNAKE_CASE_									=						0






class       __snake_case  (    Generic[T]       ):

  def __init__(					self):
      # map from node name to the node object
      SCREAMING_SNAKE_CASE_									=						{}

  def 						lowerCAmelCase__     (					self						,		_A):
      # create a new set with x as its member
      SCREAMING_SNAKE_CASE_									=						DisjointSetTreeNode(_A)

  def 						lowerCAmelCase__     (					self						,		_A):
      # find the set x belongs to (with path-compression)
      SCREAMING_SNAKE_CASE_									=						self.map[data]
      if elem_ref != elem_ref.parent:
          SCREAMING_SNAKE_CASE_									=						self.find_set(elem_ref.parent.data)
      return elem_ref.parent

  def 						lowerCAmelCase__     (					self						,		_A						,		_A):
      # helper function for union operation
      if nodea.rank > nodea.rank:
          SCREAMING_SNAKE_CASE_									=						nodea
      else:
          SCREAMING_SNAKE_CASE_									=						nodea
          if nodea.rank == nodea.rank:
              nodea.rank += 1


  def 						lowerCAmelCase__     (					self						,		_A						,		_A):
      # merge 2 disjoint sets
      self.link(self.find_set(_A)						,		self.find_set(_A))






class       __snake_case  (    Generic[T]       ):

  def __init__(					self):
      # connections: map from the node to the neighbouring nodes (with weights)
      SCREAMING_SNAKE_CASE_									=						{}

  def 						lowerCAmelCase__     (					self						,		_A):
      # add a node ONLY if its not present in the graph
      if node not in self.connections:
          SCREAMING_SNAKE_CASE_									=						{}

  def 						lowerCAmelCase__     (					self						,		_A						,		_A						,		_A):
      # add an edge with the given weight
      self.add_node(_A)
      self.add_node(_A)
      SCREAMING_SNAKE_CASE_									=						weight
      SCREAMING_SNAKE_CASE_									=						weight


  def 						lowerCAmelCase__     (					self):
      SCREAMING_SNAKE_CASE_									=						[]
      SCREAMING_SNAKE_CASE_									=						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 _A: x[2])

      # creating the disjoint set
      SCREAMING_SNAKE_CASE_									=						DisjointSetTree[T]()
      for node in self.connections:
          disjoint_set.make_set(_A)

      # MST generation
      SCREAMING_SNAKE_CASE_									=						0
      SCREAMING_SNAKE_CASE_									=						0
      SCREAMING_SNAKE_CASE_									=						GraphUndirectedWeighted[T]()
      while num_edges < len(self.connections) - 1:
          SCREAMING_SNAKE_CASE_							,			SCREAMING_SNAKE_CASE_							,			SCREAMING_SNAKE_CASE_									=						edges[index]
          index += 1
          SCREAMING_SNAKE_CASE_									=						disjoint_set.find_set(_A)
          SCREAMING_SNAKE_CASE_									=						disjoint_set.find_set(_A)
          if parent_u != parent_v:
              num_edges += 1
              graph.add_edge(_A						,		_A						,		_A)
              disjoint_set.union(_A						,		_A)
      return graph








from typing import TYPE_CHECKING

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


UpperCamelCase__  :      Any			=    {
    "configuration_mvp": ["MVP_PRETRAINED_CONFIG_ARCHIVE_MAP", "MvpConfig", "MvpOnnxConfig"],
    "tokenization_mvp": ["MvpTokenizer"],
}

try:
       if not is_tokenizers_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       UpperCamelCase__  :      Optional[int]			=    ["MvpTokenizerFast"]

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       UpperCamelCase__  :      str			=    [
           "MVP_PRETRAINED_MODEL_ARCHIVE_LIST",
           "MvpForCausalLM",
           "MvpForConditionalGeneration",
           "MvpForQuestionAnswering",
           "MvpForSequenceClassification",
           "MvpModel",
           "MvpPreTrainedModel",
       ]

if TYPE_CHECKING:
       from .configuration_mvp import MVP_PRETRAINED_CONFIG_ARCHIVE_MAP, MvpConfig, MvpOnnxConfig
       from .tokenization_mvp import MvpTokenizer

       try:
              if not is_tokenizers_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .tokenization_mvp_fast import MvpTokenizerFast

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_mvp import (
                  MVP_PRETRAINED_MODEL_ARCHIVE_LIST,
                  MvpForCausalLM,
                  MvpForConditionalGeneration,
                  MvpForQuestionAnswering,
                  MvpForSequenceClassification,
                  MvpModel,
                  MvpPreTrainedModel,
              )

else:
       import sys

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


