


"""simple docstring"""


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:						List[str]     ,		__a:						Union[str, Any]	)->    Tuple:
           super().__init__()
           lowerCamelCase					:					str        =	model
           lowerCamelCase					:					Any        =	2
           lowerCamelCase					:					str        =	nn.Linear(self.model.config.hidden_size     ,		self.num_labels	)







     def 		a__						(	self:						List[str]	)->    Union[str, Any]:
           pass




def   snake_case		(     UpperCamelCase__       :						str			,				UpperCamelCase__       :						str			,				UpperCamelCase__       :						str    )   ->      Optional[Any]:
      # load longformer model from model identifier
      lowerCamelCase					:					Any        =	LongformerModel.from_pretrained(UpperCamelCase__    )
      lowerCamelCase					:					Any        =	LightningModel(UpperCamelCase__    )

      lowerCamelCase					:					Optional[Any]        =	torch.load(UpperCamelCase__			,				map_location=torch.device("""cpu"""    )    )
      lightning_model.load_state_dict(ckpt["""state_dict"""]    )

      # init longformer question answering model
      lowerCamelCase					:					int        =	LongformerForQuestionAnswering.from_pretrained(UpperCamelCase__    )

      # 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(UpperCamelCase__    )

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


if __name__ == "__main__":
    __lowerCamelCase      :Any	    =		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.'
    )
    __lowerCamelCase      :str	    =		parser.parse_args()
    convert_longformer_qa_checkpoint_to_pytorch(
        args.longformer_model, args.longformer_question_answering_ckpt_path, args.pytorch_dump_folder_path
    )








"""simple docstring"""


__lowerCamelCase      :List[Any]	    =		{0: [2, 3], 1: [0], 2: [1], 3: [4], 4: []}

__lowerCamelCase      :Union[str, Any]	    =		{0: [1, 2, 3], 1: [2], 2: [0], 3: [4], 4: [5], 5: [3]}




def   snake_case		(     UpperCamelCase__       :						dict[int, list[int]]			,				UpperCamelCase__       :						int			,				UpperCamelCase__       :						list[bool]    )   ->      list[int]:
      lowerCamelCase					:					Tuple        =	True
      lowerCamelCase					:					Any        =	[]

      for neighbour in graph[vert]:
            if not visited[neighbour]:
                  order += topology_sort(UpperCamelCase__			,				UpperCamelCase__			,				UpperCamelCase__    )

      order.append(UpperCamelCase__    )

      return order




def   snake_case		(     UpperCamelCase__       :						dict[int, list[int]]			,				UpperCamelCase__       :						int			,				UpperCamelCase__       :						list[bool]    )   ->      list[int]:
      lowerCamelCase					:					List[Any]        =	True
      lowerCamelCase					:					int        =	[vert]

      for neighbour in reversed_graph[vert]:
            if not visited[neighbour]:
                  component += find_components(UpperCamelCase__			,				UpperCamelCase__			,				UpperCamelCase__    )

      return component






def   snake_case		(     UpperCamelCase__       :						dict[int, list[int]]    )   ->      list[list[int]]:
      lowerCamelCase					:					int        =	len(UpperCamelCase__    ) * [False]
      lowerCamelCase					:					dict[int, list[int]]        =	{vert: [] for vert in range(len(UpperCamelCase__    )    )}

      for vert, neighbours in graph.items():
            for neighbour in neighbours:
                  reversed_graph[neighbour].append(UpperCamelCase__    )

      lowerCamelCase					:					int        =	[]
      for i, was_visited in enumerate(UpperCamelCase__    ):
            if not was_visited:
                  order += topology_sort(UpperCamelCase__			,				UpperCamelCase__			,				UpperCamelCase__    )

      lowerCamelCase					:					Tuple        =	[]
      lowerCamelCase					:					str        =	len(UpperCamelCase__    ) * [False]

      for i in range(len(UpperCamelCase__    )    ):
            lowerCamelCase					:					Any        =	order[len(UpperCamelCase__    ) - i - 1]
            if not visited[vert]:
                  lowerCamelCase					:					List[str]        =	find_components(UpperCamelCase__			,				UpperCamelCase__			,				UpperCamelCase__    )
                  components_list.append(UpperCamelCase__    )

      return components_list




