



"""simple docstring"""




import argparse

import torch

from transformers import RoFormerConfig, RoFormerForMaskedLM, load_tf_weights_in_roformer
from transformers.utils import logging


logging.set_verbosity_info()


def 	lowercase__  (      _UpperCAmelCase						,   _UpperCAmelCase						,   _UpperCAmelCase					)  ->      Optional[Any]:






      '''simple docstring'''


      lowercase	:   Optional[int]											= RoFormerConfig.from_json_file(_UpperCAmelCase					)
      print(f'''Building PyTorch model from configuration: {config}'''					)
      lowercase	:   Union[str, Any]											= RoFormerForMaskedLM(_UpperCAmelCase					)

      # Load weights from tf checkpoint
      load_tf_weights_in_roformer(_UpperCAmelCase						,   _UpperCAmelCase						,   _UpperCAmelCase					)

      # Save pytorch-model
      print(f'''Save PyTorch model to {pytorch_dump_path}'''					)
      torch.save(model.state_dict()						,   _UpperCAmelCase						,   _use_new_zipfile_serialization=_UpperCAmelCase					)


if __name__ == "__main__":
     _UpperCamelCase:					Optional[int]     				=	argparse.ArgumentParser()
     # Required parameters
     parser.add_argument(
         '--tf_checkpoint_path', default=None, type=str, required=True, help='Path to the TensorFlow checkpoint path.'
     )
     parser.add_argument(
         '--bert_config_file',
         default=None,
         type=str,
         required=True,
         help=(
             'The config json file corresponding to the pre-trained BERT model. \n'
             'This specifies the model architecture.'
         ),
     )
     parser.add_argument(
         '--pytorch_dump_path', default=None, type=str, required=True, help='Path to the output PyTorch model.'
     )
     _UpperCamelCase:					str     				=	parser.parse_args()
     convert_tf_checkpoint_to_pytorch(args.tf_checkpoint_path, args.bert_config_file, args.pytorch_dump_path)





"""simple docstring"""




from __future__ import annotations

from typing import Generic, TypeVar

_UpperCamelCase:					str     				=	TypeVar('T')


class 	a__		(    Generic[T]  ):


   def __init__(				self   :				Optional[int],  lowerCAmelCase   :				T      )     ->							List[Any]:
         lowercase	:   Optional[int]											= data  # Assign data
         lowercase	:   Node[T] | None											= None  # Initialize next as null
         lowercase	:   Node[T] | None											= None  # Initialize prev as null




class 	a__		(    Generic[T]  ):


   def __init__(				self   :				Optional[int]      )     ->							None:
         lowercase	:   Node[T] | None											= None


   def 							lowercase					(				self   :				Any,  lowerCAmelCase   :				T      )     ->							None:
         if self.head is None:
               lowercase	:   Tuple											= Node(lowerCAmelCase      )
         else:
               lowercase	:   Dict											= Node(lowerCAmelCase      )
               lowercase	:   str											= new_node
               lowercase	:   int											= self.head
               lowercase	:   List[str]											= None
               lowercase	:   List[str]											= new_node


   def 							lowercase					(				self   :				Dict      )     ->							T | None:
         if self.head is None:
               return None
         else:
               assert self.head is not None
               lowercase	:   Optional[int]											= self.head.data
               lowercase	:   Any											= self.head.next
               if self.head is not None:
                     lowercase	:   Optional[Any]											= None
               return temp


   def 							lowercase					(				self   :				List[Any]      )     ->							T | None:
         return self.head.data if self.head is not None else None


   def __len__(				self   :				int      )     ->							int:
         lowercase	:   Any											= self.head
         lowercase	:   List[Any]											= 0
         while temp is not None:
               count += 1
               lowercase	:   Any											= temp.next
         return count


   def 							lowercase					(				self   :				List[Any]      )     ->							bool:
         return self.head is None






   def 							lowercase					(				self   :				Optional[int]      )     ->							None:
         print('stack elements are:'      )
         lowercase	:   Optional[int]											= self.head
         while temp is not None:
               print(temp.data,  end='->'      )
               lowercase	:   List[str]											= temp.next


# Code execution starts here
if __name__ == "__main__":
     # Start with the empty stack
     _UpperCamelCase:					Stack[int]     				=	Stack()

     # Insert 4 at the beginning. So stack becomes 4->None
     print('Stack operations using Doubly LinkedList')
     stack.push(4)

     # Insert 5 at the beginning. So stack becomes 4->5->None
     stack.push(5)

     # Insert 6 at the beginning. So stack becomes 4->5->6->None
     stack.push(6)

     # Insert 7 at the beginning. So stack becomes 4->5->6->7->None
     stack.push(7)

     # Print the stack
     stack.print_stack()

     # Print the top element
     print('\nTop element is ', stack.top())

     # Print the stack size
     print('Size of the stack is ', len(stack))

     # pop the top element
     stack.pop()

     # pop the top element
     stack.pop()

     # two elements have now been popped off
     stack.print_stack()

     # Print True if the stack is empty else False
     print('\nstack is empty:', stack.is_empty())
