class     _lowercase					:


 '''simple docstring'''






 def __init__(				self       :     int				,	SCREAMING_SNAKE_CASE__       :     Union[str, Any]							)  ->   None:
  __lowerCAmelCase    							=						data
  __lowerCAmelCase    							=						None
  __lowerCAmelCase    							=						None







def 					UpperCamelCase_						( snake_case_	:	BinaryTreeNode | None						,		snake_case_	:	int				) ->					BinaryTreeNode | None:






 '''simple docstring'''

 if node is None:
  __lowerCAmelCase    							=						BinaryTreeNode(_lowerCamelCase				)
  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:
  __lowerCAmelCase    							=						insert(node.left_child						,		_lowerCamelCase				)
 else:
  # if new_value is greater than value of data in node,
  #  add it to right subtree and proceed recursively
  __lowerCAmelCase    							=						insert(node.right_child						,		_lowerCamelCase				)
 return node







def 					UpperCamelCase_						( snake_case_	:	None | BinaryTreeNode				) ->					list[int]:  # if node is None,return






 '''simple docstring'''

 if node:
  __lowerCAmelCase    							=						inorder(node.left_child				)
  __lowerCAmelCase    							=						[*inorder_array, node.data]
  __lowerCAmelCase    							=						inorder_array + inorder(node.right_child				)
 else:
  __lowerCAmelCase    							=						[]
 return inorder_array







def 					UpperCamelCase_						( ) ->					BinaryTreeNode | None:






 '''simple docstring'''

 __lowerCAmelCase    							=						insert(_lowerCamelCase						,		15				)
 insert(_lowerCamelCase						,		10				)
 insert(_lowerCamelCase						,		25				)
 insert(_lowerCamelCase						,		6				)
 insert(_lowerCamelCase						,		14				)
 insert(_lowerCamelCase						,		20				)
 insert(_lowerCamelCase						,		60				)
 return root







def 					UpperCamelCase_						( ) ->					None:






 '''simple docstring'''

 __lowerCAmelCase    							=						make_tree()
 print("""Printing values of binary search tree in Inorder Traversal."""				)
 inorder(_lowerCamelCase				)


if __name__ == "__main__":
 import doctest

 doctest.testmod()
 main()







'''simple docstring'''

import argparse

from transformers import CanineConfig, CanineModel, CanineTokenizer, load_tf_weights_in_canine
from transformers.utils import logging


logging.set_verbosity_info()







def 					UpperCamelCase_						( snake_case_	:	List[str]						,		snake_case_	:	Optional[Any]				) ->					Tuple:






 '''simple docstring'''

 __lowerCAmelCase    							=						CanineConfig()
 __lowerCAmelCase    							=						CanineModel(snake_case_				)
 model.eval()

 print(f"""Building PyTorch model from configuration: {config}"""				)

 # Load weights from tf checkpoint
 load_tf_weights_in_canine(snake_case_						,		snake_case_						,		snake_case_				)

 # Save pytorch-model (weights and configuration)
 print(f"""Save PyTorch model to {pytorch_dump_path}"""				)
 model.save_pretrained(snake_case_				)

 # Save tokenizer files
 __lowerCAmelCase    							=						CanineTokenizer()
 print(f"""Save tokenizer files to {pytorch_dump_path}"""				)
 tokenizer.save_pretrained(snake_case_				)


if __name__ == "__main__":
 _A      :				int 				=    argparse.ArgumentParser()
 # Required parameters
 parser.add_argument(
     '''--tf_checkpoint_path''',
     default=None,
     type=str,
     required=True,
     help='''Path to the TensorFlow checkpoint. Should end with model.ckpt''',
 )
 parser.add_argument(
     '''--pytorch_dump_path''',
     default=None,
     type=str,
     required=True,
     help='''Path to a folder where the PyTorch model will be placed.''',
 )
 _A      :				Dict 				=    parser.parse_args()
 convert_tf_checkpoint_to_pytorch(args.tf_checkpoint_path, args.pytorch_dump_path)






