


"""simple docstring"""






import argparse

import pytorch_lightning as pl
import torch
from torch import nn

from transformers import LongformerForQuestionAnswering, LongformerModel


class 			lowerCamelCase_		(			pl.LightningModule   ):





				"""simple docstring"""







				def __init__(						self       ,		UpperCAmelCase__     ):
								super().__init__()
								SCREAMING_SNAKE_CASE__     							=				model
								SCREAMING_SNAKE_CASE__     							=				2
								SCREAMING_SNAKE_CASE__     							=				nn.Linear(self.model.config.hidden_size       ,		self.num_labels     )






				def   lowerCAmelCase__		(						self     ):
								pass


def __lowercase     (      lowerCamelCase_  :      str						,					lowerCamelCase_  :      str						,					lowerCamelCase_  :      str  ):
				# load longformer model from model identifier
				SCREAMING_SNAKE_CASE__     							=				LongformerModel.from_pretrained(lowerCamelCase_  )
				SCREAMING_SNAKE_CASE__     							=				LightningModel(lowerCamelCase_  )

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

				# init longformer question answering model
				SCREAMING_SNAKE_CASE__     							=				LongformerForQuestionAnswering.from_pretrained(lowerCamelCase_  )

				# 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(lowerCamelCase_  )

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


if __name__ == "__main__":
	_lowerCamelCase     =  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     =  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 math import pi


def __lowercase     (      lowerCamelCase_  :      int						,					lowerCamelCase_  :      int  ):
				return 2 * pi * radius * (angle / 360)


if __name__ == "__main__":
	print(arc_length(90, 10))
