

'''simple docstring'''






from __future__ import annotations

from collections import deque
from collections.abc import Sequence
from dataclasses import dataclass
from typing import Any






@dataclass
class     lowercase_			:




  """simple docstring"""




  SCREAMING_SNAKE_CASE					:						Optional[int]           =    4_2
  SCREAMING_SNAKE_CASE					:						str           =    None
  SCREAMING_SNAKE_CASE					:						List[Any]           =    None


def 	_A  (					):






 """simple docstring"""



 __lowercase													=				Node(1   )
 __lowercase													=				Node(2   )
 __lowercase													=				Node(3   )
 __lowercase													=				Node(4   )
 __lowercase													=				Node(5   )
 return tree


def 	_A  (					A__   ):






 """simple docstring"""



 return [root.data, *preorder(root.left   ), *preorder(root.right   )] if root else []


def 	_A  (					A__   ):






 """simple docstring"""



 return postorder(root.left   ) + postorder(root.right   ) + [root.data] if root else []


def 	_A  (					A__   ):






 """simple docstring"""



 return [*inorder(root.left   ), root.data, *inorder(root.right   )] if root else []


def 	_A  (					A__   ):






 """simple docstring"""



 return (max(height(root.left   )  ,       height(root.right   )   ) + 1) if root else 0


def 	_A  (					A__   ):






 """simple docstring"""



 __lowercase													=				[]

 if root is None:
  return output

 __lowercase													=				deque([root]   )

 while process_queue:
  __lowercase													=				process_queue.popleft()
  output.append(node.data   )

  if node.left:
   process_queue.append(node.left   )
  if node.right:
   process_queue.append(node.right   )
 return output


def 	_A  (					A__  ,       A__   ):






 """simple docstring"""



 __lowercase													=				[]

 def populate_output(A__  ,       A__   ) -> None:
  if not root:
   return
  if level == 1:
   output.append(root.data   )
  elif level > 1:
   populate_output(root.left  ,       level - 1   )
   populate_output(root.right  ,       level - 1   )

 populate_output(snake_case__  ,       snake_case__   )
 return output


def 	_A  (					A__  ,       A__   ):






 """simple docstring"""



 __lowercase													=				[]

 def populate_output(A__  ,       A__   ) -> None:
  if root is None:
   return
  if level == 1:
   output.append(root.data   )
  elif level > 1:
   populate_output(root.right  ,       level - 1   )
   populate_output(root.left  ,       level - 1   )

 populate_output(snake_case__  ,       snake_case__   )
 return output


def 	_A  (					A__   ):






 """simple docstring"""



 if root is None:
  return []

 __lowercase													=				[]

 __lowercase													=				0
 __lowercase													=				height(snake_case__   )

 for h in range(1  ,       height_tree + 1   ):
  if not flag:
   output.append(get_nodes_from_left_to_right(snake_case__  ,       snake_case__   )   )
   __lowercase													=				1
  else:
   output.append(get_nodes_from_right_to_left(snake_case__  ,       snake_case__   )   )
   __lowercase													=				0

 return output


def 	_A  (					):  # Main function for testing.






 """simple docstring"""



 __lowercase													=				make_tree()
 print(F"In-order Traversal: {inorder(snake_case__   )}"   )
 print(F"Pre-order Traversal: {preorder(snake_case__   )}"   )
 print(F"Post-order Traversal: {postorder(snake_case__   )}"  ,       '''\n'''   )

 print(F"Height of Tree: {height(snake_case__   )}"  ,       '''\n'''   )

 print('''Complete Level Order Traversal: '''   )
 print(level_order(snake_case__   )  ,       '''\n'''   )

 print('''Level-wise order Traversal: '''   )

 for level in range(1  ,       height(snake_case__   ) + 1   ):
  print(F"Level {level}:"  ,       get_nodes_from_left_to_right(snake_case__  ,       level=snake_case__   )   )

 print('''\nZigZag order Traversal: '''   )
 print(zigzag(snake_case__   )   )


if __name__ == "__main__":
 import doctest

 doctest.testmod()
 main()








'''simple docstring'''






from argparse import ArgumentParser

from . import BaseTransformersCLICommand


def 	_A  (					A__   ):






 """simple docstring"""



 return DownloadCommand(args.model  ,       args.cache_dir  ,       args.force  ,       args.trust_remote_code   )






class     lowercase_			(lowerCamelCase__   ):




  """simple docstring"""




  @staticmethod
  def       SCREAMING_SNAKE_CASE   (   lowercase__     :  ArgumentParser    ):
   __lowercase													=				parser.add_parser('''download'''    )
   download_parser.add_argument(
       '''--cache-dir'''      ,type=lowercase__      ,default=lowercase__      ,help='''Path to location to store the models'''    )
   download_parser.add_argument(
       '''--force'''      ,action='''store_true'''      ,help='''Force the model to be download even if already in cache-dir'''    )
   download_parser.add_argument(
       '''--trust-remote-code'''      ,action='''store_true'''      ,help='''Whether or not to allow for custom models defined on the Hub in their own modeling files. Use only if you\'ve reviewed the code as it will execute on your local machine'''      ,)
   download_parser.add_argument('''model'''      ,type=lowercase__      ,help='''Name of the model to download'''    )
   download_parser.set_defaults(func=lowercase__    )






  def __init__(   self     :  str      ,lowercase__     :  str      ,lowercase__     :  str      ,lowercase__     :  bool      ,lowercase__     :  bool    ):
   __lowercase													=				model
   __lowercase													=				cache
   __lowercase													=				force
   __lowercase													=				trust_remote_code






  def       SCREAMING_SNAKE_CASE   (   self     :  Any    ):
   from ..models.auto import AutoModel, AutoTokenizer

   AutoModel.from_pretrained(
       self._model      ,cache_dir=self._cache      ,force_download=self._force      ,trust_remote_code=self._trust_remote_code    )
   AutoTokenizer.from_pretrained(
       self._model      ,cache_dir=self._cache      ,force_download=self._force      ,trust_remote_code=self._trust_remote_code    )

