
'''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 							snake_case				(		UpperCAmelCase   ,	UpperCAmelCase   ,	UpperCAmelCase						)->      Union[str, Any]:







      """simple docstring"""
      # Initialise PyTorch model
      __A													=      RoFormerConfig.from_json_file(UpperCAmelCase						)
      print(f'Building PyTorch model from configuration: {config}'						)
      __A													=      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__":
 a__		: Tuple  							=							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."
 )
 a__		: Union[str, Any]  							=							parser.parse_args()
 convert_tf_checkpoint_to_pytorch(args.tf_checkpoint_path, args.bert_config_file, args.pytorch_dump_path)








'''simple docstring'''





class 			UpperCamelCase__	:






 def __init__(      self	:Tuple						,					_A	:int      )					->      None:







       '''simple docstring'''



       __A													=      data
       __A													=      None
       __A													=      None





def 							snake_case				(		UpperCAmelCase   ,	UpperCAmelCase						)->      BinaryTreeNode | None:







      """simple docstring"""
      if node is None:
            __A													=      BinaryTreeNode(UpperCAmelCase						)
            return node

      # binary search tree is not empty,
      # so we will insert it into the tree
      # if new_value is less than value of data in node,
      #  add it to left subtree and proceed recursively
      if new_value < node.data:
            __A													=      insert(node.left_child   ,	UpperCAmelCase						)
      else:
            # if new_value is greater than value of data in node,
            #  add it to right subtree and proceed recursively
            __A													=      insert(node.right_child   ,	UpperCAmelCase						)
      return node





def 							snake_case				(		UpperCAmelCase						)->      list[int]:  # if node is None,return







      """simple docstring"""
      if node:
            __A													=      inorder(node.left_child						)
            __A													=      [*inorder_array, node.data]
            __A													=      inorder_array + inorder(node.right_child						)
      else:
            __A													=      []
      return inorder_array





def 							snake_case				(		)->      BinaryTreeNode | None:







      """simple docstring"""
      __A													=      insert(UpperCAmelCase   ,	1_5						)
      insert(UpperCAmelCase   ,	1_0						)
      insert(UpperCAmelCase   ,	2_5						)
      insert(UpperCAmelCase   ,	6						)
      insert(UpperCAmelCase   ,	1_4						)
      insert(UpperCAmelCase   ,	2_0						)
      insert(UpperCAmelCase   ,	6_0						)
      return root





def 							snake_case				(		)->      None:







      """simple docstring"""
      # main function
      __A													=      make_tree()
      print('Printing values of binary search tree in Inorder Traversal.'						)
      inorder(UpperCAmelCase						)


if __name__ == "__main__":
 import doctest

 doctest.testmod()
 main()






