
import argparse

import pytorch_lightning as pl
import torch
from torch import nn

from transformers import LongformerForQuestionAnswering, LongformerModel





class 				UpperCAmelCase (    pl.LightningModule    ):




	'''simple docstring'''





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







	def 							UpperCamelCase_    (			self   :					List[Any]					):
					pass





def 		UpperCAmelCase     (      a_						,  a_						,  a_		)						->      Dict:







				"""simple docstring"""



				__A       =					LongformerModel.from_pretrained(a_		)
				__A       =					LightningModel(a_		)

				__A       =					torch.load(a_						,  map_location=torch.device("cpu"		)		)
				lightning_model.load_state_dict(ckpt["state_dict"]		)

				# init longformer question answering model
				__A       =					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				:List[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.'
					)
					SCREAMING_SNAKE_CASE				:Optional[Any]									=							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'''





from ..utils import DummyObject, requires_backends






class 							UpperCAmelCase_							(    metaclass=A				):

 '''simple docstring'''
 lowercase_					:    Optional[int]				=							["torch", "transformers", "onnx"]







 def __init__(					self		:  Tuple			,				*snake_case__		:  str			,				**snake_case__		:  List[str] ):



   '''simple docstring'''




   requires_backends(self			,				["torch", "transformers", "onnx"] )







 @classmethod
 def 							UpperCamelCase  (					cls		:  Optional[int]			,				*snake_case__		:  Any			,				**snake_case__		:  List[Any] ):



   '''simple docstring'''




   requires_backends(cls			,				["torch", "transformers", "onnx"] )







 @classmethod
 def 							UpperCamelCase  (					cls		:  List[str]			,				*snake_case__		:  Any			,				**snake_case__		:  Tuple ):



   '''simple docstring'''




   requires_backends(cls			,				["torch", "transformers", "onnx"] )






class 							UpperCAmelCase_							(    metaclass=A				):

 '''simple docstring'''
 lowercase_					:    Tuple				=							["torch", "transformers", "onnx"]







 def __init__(					self		:  List[str]			,				*snake_case__		:  List[Any]			,				**snake_case__		:  Any ):



   '''simple docstring'''




   requires_backends(self			,				["torch", "transformers", "onnx"] )







 @classmethod
 def 							UpperCamelCase  (					cls		:  Dict			,				*snake_case__		:  Any			,				**snake_case__		:  Optional[int] ):



   '''simple docstring'''




   requires_backends(cls			,				["torch", "transformers", "onnx"] )







 @classmethod
 def 							UpperCamelCase  (					cls		:  int			,				*snake_case__		:  Dict			,				**snake_case__		:  List[Any] ):



   '''simple docstring'''




   requires_backends(cls			,				["torch", "transformers", "onnx"] )






class 							UpperCAmelCase_							(    metaclass=A				):

 '''simple docstring'''
 lowercase_					:    Optional[int]				=							["torch", "transformers", "onnx"]







 def __init__(					self		:  str			,				*snake_case__		:  Optional[int]			,				**snake_case__		:  str ):



   '''simple docstring'''




   requires_backends(self			,				["torch", "transformers", "onnx"] )







 @classmethod
 def 							UpperCamelCase  (					cls		:  Any			,				*snake_case__		:  List[str]			,				**snake_case__		:  Dict ):



   '''simple docstring'''




   requires_backends(cls			,				["torch", "transformers", "onnx"] )







 @classmethod
 def 							UpperCamelCase  (					cls		:  str			,				*snake_case__		:  Dict			,				**snake_case__		:  Dict ):



   '''simple docstring'''




   requires_backends(cls			,				["torch", "transformers", "onnx"] )






class 							UpperCAmelCase_							(    metaclass=A				):

 '''simple docstring'''
 lowercase_					:    int				=							["torch", "transformers", "onnx"]







 def __init__(					self		:  Any			,				*snake_case__		:  List[str]			,				**snake_case__		:  str ):



   '''simple docstring'''




   requires_backends(self			,				["torch", "transformers", "onnx"] )







 @classmethod
 def 							UpperCamelCase  (					cls		:  List[str]			,				*snake_case__		:  List[str]			,				**snake_case__		:  Optional[Any] ):



   '''simple docstring'''




   requires_backends(cls			,				["torch", "transformers", "onnx"] )







 @classmethod
 def 							UpperCamelCase  (					cls		:  Optional[int]			,				*snake_case__		:  List[Any]			,				**snake_case__		:  int ):



   '''simple docstring'''




   requires_backends(cls			,				["torch", "transformers", "onnx"] )






class 							UpperCAmelCase_							(    metaclass=A				):

 '''simple docstring'''
 lowercase_					:    Dict				=							["torch", "transformers", "onnx"]







 def __init__(					self		:  Any			,				*snake_case__		:  Optional[int]			,				**snake_case__		:  Any ):



   '''simple docstring'''




   requires_backends(self			,				["torch", "transformers", "onnx"] )







 @classmethod
 def 							UpperCamelCase  (					cls		:  Union[str, Any]			,				*snake_case__		:  str			,				**snake_case__		:  Optional[Any] ):



   '''simple docstring'''




   requires_backends(cls			,				["torch", "transformers", "onnx"] )







 @classmethod
 def 							UpperCamelCase  (					cls		:  int			,				*snake_case__		:  int			,				**snake_case__		:  Tuple ):



   '''simple docstring'''




   requires_backends(cls			,				["torch", "transformers", "onnx"] )






class 							UpperCAmelCase_							(    metaclass=A				):

 '''simple docstring'''
 lowercase_					:    Dict				=							["torch", "transformers", "onnx"]







 def __init__(					self		:  List[str]			,				*snake_case__		:  Tuple			,				**snake_case__		:  int ):



   '''simple docstring'''




   requires_backends(self			,				["torch", "transformers", "onnx"] )







 @classmethod
 def 							UpperCamelCase  (					cls		:  Optional[int]			,				*snake_case__		:  Tuple			,				**snake_case__		:  Dict ):



   '''simple docstring'''




   requires_backends(cls			,				["torch", "transformers", "onnx"] )







 @classmethod
 def 							UpperCamelCase  (					cls		:  List[str]			,				*snake_case__		:  Dict			,				**snake_case__		:  List[Any] ):



   '''simple docstring'''




   requires_backends(cls			,				["torch", "transformers", "onnx"] )



