






class 							A_    :






 '''simple docstring'''




 def __init__(	self) ->		Tuple:

     """simple docstring"""



     _UpperCAmelCase				:      str			  =				0
     _UpperCAmelCase				:      Optional[Any]			  =				0
     _UpperCAmelCase				:      Any			  =				{}


 def  snake_case__				(	self							,  _A) ->		Dict:

     """simple docstring"""



     if vertex not in self.adjacency:
         _UpperCAmelCase				:      Union[str, Any]			  =				{}
         self.num_vertices += 1


 def  snake_case__				(	self							,  _A							,  _A							,  _A) ->		Tuple:

     """simple docstring"""



     self.add_vertex(_A)
     self.add_vertex(_A)

     if head == tail:
         return

     _UpperCAmelCase				:      Tuple			  =				weight
     _UpperCAmelCase				:      Optional[int]			  =				weight


 def  snake_case__				(	self) ->		Union[str, Any]:

     """simple docstring"""



     _UpperCAmelCase				:      Tuple			  =				self.get_edges()
     for edge in edges:
         _UpperCAmelCase  , _UpperCAmelCase  , _UpperCAmelCase				:      Optional[Any]			  =				edge
         edges.remove((tail, head, weight))
     for i in range(len(_A)):
         _UpperCAmelCase				:      str			  =				list(edges[i])

     edges.sort(key=lambda _A: e[2])
     for i in range(len(_A) - 1):
         if edges[i][2] >= edges[i + 1][2]:
             _UpperCAmelCase				:      List[str]			  =				edges[i][2] + 1
     for edge in edges:
         _UpperCAmelCase  , _UpperCAmelCase  , _UpperCAmelCase				:      Optional[int]			  =				edge
         _UpperCAmelCase				:      List[Any]			  =				weight
         _UpperCAmelCase				:      Union[str, Any]			  =				weight


 def __str__(	self) ->		Any:

     """simple docstring"""



     _UpperCAmelCase				:      str			  =				''''''
     for tail in self.adjacency:
         for head in self.adjacency[tail]:
             _UpperCAmelCase				:      Optional[Any]			  =				self.adjacency[head][tail]
             string += f'''{head} -> {tail} == {weight}\n'''
     return string.rstrip('''\n''')


 def  snake_case__				(	self) ->		Optional[int]:

     """simple docstring"""



     _UpperCAmelCase				:      Optional[int]			  =				[]
     for tail in self.adjacency:
         for head in self.adjacency[tail]:
             output.append((tail, head, self.adjacency[head][tail]))
     return output


 def  snake_case__				(	self) ->		List[Any]:

     """simple docstring"""



     return self.adjacency.keys()


 @staticmethod
 def  snake_case__				(	_A=None							,  _A=None) ->		Dict:

     """simple docstring"""



     _UpperCAmelCase				:      Tuple			  =				Graph()
     if vertices is None:
         _UpperCAmelCase				:      Optional[int]			  =				[]
     if edges is None:
         _UpperCAmelCase				:      str			  =				[]
     for vertex in vertices:
         g.add_vertex(_A)
     for edge in edges:
         g.add_edge(*_A)
     return g
 class 							A_    :






  '''simple docstring'''




  def __init__(	self) ->		Dict:

      """simple docstring"""



      _UpperCAmelCase				:      Any			  =				{}
      _UpperCAmelCase				:      int			  =				{}


  def __len__(	self) ->		Any:

      """simple docstring"""



      return len(self.parent)


  def  snake_case__				(	self							,  _A) ->		List[str]:

      """simple docstring"""



      if item in self.parent:
          return self.find(_A)

      _UpperCAmelCase				:      str			  =				item
      _UpperCAmelCase				:      Any			  =				0
      return item


  def  snake_case__				(	self							,  _A) ->		List[Any]:

      """simple docstring"""



      if item not in self.parent:
          return self.make_set(_A)
      if item != self.parent[item]:
          _UpperCAmelCase				:      Tuple			  =				self.find(self.parent[item])
      return self.parent[item]


  def  snake_case__				(	self							,  _A							,  _A) ->		Tuple:

      """simple docstring"""



      _UpperCAmelCase				:      Dict			  =				self.find(_A)
      _UpperCAmelCase				:      Union[str, Any]			  =				self.find(_A)

      if roota == roota:
          return roota

      if self.rank[roota] > self.rank[roota]:
          _UpperCAmelCase				:      Union[str, Any]			  =				roota
          return roota

      if self.rank[roota] < self.rank[roota]:
          _UpperCAmelCase				:      int			  =				roota
          return roota

      if self.rank[roota] == self.rank[roota]:
          self.rank[roota] += 1
          _UpperCAmelCase				:      Optional[Any]			  =				roota
          return roota
      return None



 @staticmethod
 def  snake_case__				(	_A) ->		List[str]:

     """simple docstring"""



     _UpperCAmelCase				:      Union[str, Any]			  =				graph.num_vertices

     _UpperCAmelCase				:      Union[str, Any]			  =				Graph.UnionFind()
     _UpperCAmelCase				:      List[Any]			  =				[]
     while num_components > 1:
         _UpperCAmelCase				:      Any			  =				{}
         for vertex in graph.get_vertices():
             _UpperCAmelCase				:      Optional[Any]			  =				-1

         _UpperCAmelCase				:      Tuple			  =				graph.get_edges()
         for edge in edges:
             _UpperCAmelCase  , _UpperCAmelCase  , _UpperCAmelCase				:      List[str]			  =				edge
             edges.remove((tail, head, weight))
         for edge in edges:
             _UpperCAmelCase  , _UpperCAmelCase  , _UpperCAmelCase				:      Optional[int]			  =				edge
             _UpperCAmelCase				:      str			  =				union_find.find(_A)
             _UpperCAmelCase				:      List[str]			  =				union_find.find(_A)
             if seta != seta:
                 if cheap_edge[seta] == -1 or cheap_edge[seta][2] > weight:
                     _UpperCAmelCase				:      Union[str, Any]			  =				[head, tail, weight]

                 if cheap_edge[seta] == -1 or cheap_edge[seta][2] > weight:
                     _UpperCAmelCase				:      Optional[int]			  =				[head, tail, weight]
         for vertex in cheap_edge:
             if cheap_edge[vertex] != -1:
                 _UpperCAmelCase  , _UpperCAmelCase  , _UpperCAmelCase				:      Optional[int]			  =				cheap_edge[vertex]
                 if union_find.find(_A) != union_find.find(_A):
                     union_find.union(_A							,  _A)
                     mst_edges.append(cheap_edge[vertex])
                     _UpperCAmelCase				:      Dict			  =				num_components - 1
     _UpperCAmelCase				:      Dict			  =				Graph.build(edges=_A)
     return mst












import argparse

import pytorch_lightning as pl
import torch
from torch import nn

from transformers import LongformerForQuestionAnswering, LongformerModel
class 							A_    (						pl.LightningModule			):






 '''simple docstring'''




 def __init__(	self							,  _A) ->		List[str]:

     """simple docstring"""



     super().__init__()
     _UpperCAmelCase				:      Dict			  =				model
     _UpperCAmelCase				:      Union[str, Any]			  =				2
     _UpperCAmelCase				:      List[Any]			  =				nn.Linear(self.model.config.hidden_size							,  self.num_labels)


 def  snake_case__				(	self) ->		Optional[Any]:

     """simple docstring"""



     pass



def      _lowerCamelCase	(						__A    :							str		,		__A    :							str		,		__A    :							str )      ->					List[str]:
    # load longformer model from model identifier
    _UpperCAmelCase				:      Optional[Any]			  =				LongformerModel.from_pretrained(__A )
    _UpperCAmelCase				:      Optional[Any]			  =				LightningModel(__A )

    _UpperCAmelCase				:      Optional[int]			  =				torch.load(__A		,		map_location=torch.device('''cpu''' ) )
    lightning_model.load_state_dict(ckpt['''state_dict'''] )

    # init longformer question answering model
    _UpperCAmelCase				:      int			  =				LongformerForQuestionAnswering.from_pretrained(__A )

    # transfer weights
    longformer_for_qa.longformer.load_state_dict(lightning_model.model.state_dict() )
    longformer_for_qa.qa_outputs.load_state_dict(lightning_model.qa_outputs.state_dict() )
    longformer_for_qa.eval()

    # save model
    longformer_for_qa.save_pretrained(__A )

    print(f'''Conversion successful. Model saved under {pytorch_dump_folder_path}''' )


if __name__ == "__main__":
  SCREAMING_SNAKE_CASE 							=						argparse.ArgumentParser()
  # Required parameters
  parser.add_argument(
      '--longformer_model',
      default=None,
      type=str,
      required=True,
      help='model identifier of longformer. Should be either `longformer-base-4096` or `longformer-large-4096`.',
  )
  parser.add_argument(
      '--longformer_question_answering_ckpt_path',
      default=None,
      type=str,
      required=True,
      help='Path the official PyTorch Lightning Checkpoint.',
  )
  parser.add_argument(
      '--pytorch_dump_folder_path', default=None, type=str, required=True, help='Path to the output PyTorch model.'
  )
  SCREAMING_SNAKE_CASE 							=						parser.parse_args()
  convert_longformer_qa_checkpoint_to_pytorch(
      args.longformer_model, args.longformer_question_answering_ckpt_path, args.pytorch_dump_folder_path
  )




