






'''simple docstring'''



from __future__ import annotations

import queue
class UpperCAmelCase_					:




      """simple docstring"""




      def __init__( self			:		Optional[int]     ,      UpperCAmelCase			:		List[str]		)  ->  Optional[int]:


       '''simple docstring'''

       lowercase					:   List[Any]				  =data
       lowercase					:   str				  =None
       lowercase					:   Dict				  =None





def 							lowercase_				(    )       ->      TreeNode:



 """simple docstring"""




 print('''\n********Press N to stop entering at any point of time********\n'''			)
 lowercase					:   List[str]				  =input('''Enter the value of the root node: '''			).strip().lower()
 lowercase					:   queue.Queue				  =queue.Queue()
 lowercase					:   Union[str, Any]				  =TreeNode(int(__A			)			)
 q.put(__A			)
 while not q.empty():
  lowercase					:   Dict				  =q.get()
  lowercase					:   Optional[Any]				  =F'Enter the left node of {node_found.data}: '
  lowercase					:   Tuple				  =input(__A			).strip().lower() or '''n'''
  if check == "n":
   return tree_node
  lowercase					:   Tuple				  =TreeNode(int(__A			)			)
  lowercase					:   Optional[int]				  =left_node
  q.put(__A			)
  lowercase					:   Union[str, Any]				  =F'Enter the right node of {node_found.data}: '
  lowercase					:   Tuple				  =input(__A			).strip().lower() or '''n'''
  if check == "n":
   return tree_node
  lowercase					:   Optional[Any]				  =TreeNode(int(__A			)			)
  lowercase					:   List[str]				  =right_node
  q.put(__A			)
 raise


def 							lowercase_				(    __A :       TreeNode			)       ->      None:



 """simple docstring"""




 if not isinstance(__A					,      __A			) or not node:
  return
 print(node.data					,      end=''','''			)
 pre_order(node.left			)
 pre_order(node.right			)


def 							lowercase_				(    __A :       TreeNode			)       ->      None:



 """simple docstring"""




 if not isinstance(__A					,      __A			) or not node:
  return
 in_order(node.left			)
 print(node.data					,      end=''','''			)
 in_order(node.right			)


def 							lowercase_				(    __A :       TreeNode			)       ->      None:



 """simple docstring"""




 if not isinstance(__A					,      __A			) or not node:
  return
 post_order(node.left			)
 post_order(node.right			)
 print(node.data					,      end=''','''			)


def 							lowercase_				(    __A :       TreeNode			)       ->      None:



 """simple docstring"""




 if not isinstance(__A					,      __A			) or not node:
  return
 lowercase					:   queue.Queue				  =queue.Queue()
 q.put(__A			)
 while not q.empty():
  lowercase					:   List[Any]				  =q.get()
  print(node_dequeued.data					,      end=''','''			)
  if node_dequeued.left:
   q.put(node_dequeued.left			)
  if node_dequeued.right:
   q.put(node_dequeued.right			)


def 							lowercase_				(    __A :       TreeNode			)       ->      None:



 """simple docstring"""




 if not isinstance(__A					,      __A			) or not node:
  return
 lowercase					:   queue.Queue				  =queue.Queue()
 q.put(__A			)
 while not q.empty():
  lowercase					:   Optional[Any]				  =[]
  while not q.empty():
   lowercase					:   Tuple				  =q.get()
   print(node_dequeued.data					,      end=''','''			)
   if node_dequeued.left:
    list_.append(node_dequeued.left			)
   if node_dequeued.right:
    list_.append(node_dequeued.right			)
  print()
  for node in list_:
   q.put(__A			)


def 							lowercase_				(    __A :       TreeNode			)       ->      None:



 """simple docstring"""




 if not isinstance(__A					,      __A			) or not node:
  return
 lowercase					:   list[TreeNode]				  =[]
 lowercase					:   Union[str, Any]				  =node
 while n or stack:
  while n:  # start from root node, find its left child
   print(n.data					,      end=''','''			)
   stack.append(__A			)
   lowercase					:   Dict				  =n.left
  # end of while means current node doesn't have left child
  lowercase					:   List[str]				  =stack.pop()
  # start to traverse its right child
  lowercase					:   List[str]				  =n.right


def 							lowercase_				(    __A :       TreeNode			)       ->      None:



 """simple docstring"""




 if not isinstance(__A					,      __A			) or not node:
  return
 lowercase					:   list[TreeNode]				  =[]
 lowercase					:   List[str]				  =node
 while n or stack:
  while n:
   stack.append(__A			)
   lowercase					:   Optional[Any]				  =n.left
  lowercase					:   Tuple				  =stack.pop()
  print(n.data					,      end=''','''			)
  lowercase					:   Union[str, Any]				  =n.right


def 							lowercase_				(    __A :       TreeNode			)       ->      None:



 """simple docstring"""




 if not isinstance(__A					,      __A			) or not node:
  return
 lowercase  ,		lowercase					:   Tuple				  =[], []
 lowercase					:   Optional[int]				  =node
 stacka.append(__A			)
 while stacka:  # to find the reversed order of post order, store it in stack2
  lowercase					:   Union[str, Any]				  =stacka.pop()
  if n.left:
   stacka.append(n.left			)
  if n.right:
   stacka.append(n.right			)
  stacka.append(__A			)
 while stacka:  # pop up from stack2 will be the post order
  print(stacka.pop().data					,      end=''','''			)


def 							lowercase_				(    __A :       str = ""					,      __A :       List[Any]=5_0					,      __A :       List[Any]="*"			)       ->      str:



 """simple docstring"""




 if not s:
  return "\n" + width * char
 lowercase  ,		lowercase					:   Optional[int]				  =divmod(width - len(__A			) - 2					,      2			)
 return F'{left * char} {s} {(left + extra) * char}'


if __name__ == "__main__":
      import doctest

      doctest.testmod()
      print(prompt('Binary Tree Traversals'))

      SCREAMING_SNAKE_CASE						=	build_tree()
      print(prompt('Pre Order Traversal'))
      pre_order(node)
      print(prompt() + '\n')

      print(prompt('In Order Traversal'))
      in_order(node)
      print(prompt() + '\n')

      print(prompt('Post Order Traversal'))
      post_order(node)
      print(prompt() + '\n')

      print(prompt('Level Order Traversal'))
      level_order(node)
      print(prompt() + '\n')

      print(prompt('Actual Level Order Traversal'))
      level_order_actual(node)
      print('*' * 50 + '\n')

      print(prompt('Pre Order Traversal - Iteration Version'))
      pre_order_iter(node)
      print(prompt() + '\n')

      print(prompt('In Order Traversal - Iteration Version'))
      in_order_iter(node)
      print(prompt() + '\n')

      print(prompt('Post Order Traversal - Iteration Version'))
      post_order_iter(node)
      print(prompt())











'''simple docstring'''



import subprocess
import sys

from transformers import BertConfig, BertModel, BertTokenizer, pipeline
from transformers.testing_utils import TestCasePlus, require_torch
class UpperCAmelCase_					(    __A				):




      """simple docstring"""




      @require_torch
      def 				A__      ( self			:		Tuple		)  ->  Optional[int]:


       '''simple docstring'''

       lowercase					:   Any				  ='''
from transformers import BertConfig, BertModel, BertTokenizer, pipeline
        '''

       lowercase					:   Optional[int]				  ='''
mname = "hf-internal-testing/tiny-random-bert"
BertConfig.from_pretrained(mname)
BertModel.from_pretrained(mname)
BertTokenizer.from_pretrained(mname)
pipe = pipeline(task="fill-mask", model=mname)
print("success")
        '''

       lowercase					:   Any				  ='''
import socket
def offline_socket(*args, **kwargs): raise RuntimeError("Offline mode is enabled, we shouldn\'t access internet")
socket.socket = offline_socket
        '''

       # Force fetching the files so that we can use the cache
       lowercase					:   Tuple				  ='''hf-internal-testing/tiny-random-bert'''
       BertConfig.from_pretrained(UpperCAmelCase		)
       BertModel.from_pretrained(UpperCAmelCase		)
       BertTokenizer.from_pretrained(UpperCAmelCase		)
       pipeline(task='''fill-mask'''     ,      model=UpperCAmelCase		)

       # baseline - just load from_pretrained with normal network
       lowercase					:   List[str]				  =[sys.executable, '''-c''', '''\n'''.join([load, run, mock]		)]

       # should succeed
       lowercase					:   Tuple				  =self.get_env()
       # should succeed as TRANSFORMERS_OFFLINE=1 tells it to use local files
       lowercase					:   Optional[Any]				  ='''1'''
       lowercase					:   Any				  =subprocess.run(UpperCAmelCase     ,      env=UpperCAmelCase     ,      check=UpperCAmelCase     ,      capture_output=UpperCAmelCase		)
       self.assertEqual(result.returncode     ,      0     ,      result.stderr		)
       self.assertIn('''success'''     ,      result.stdout.decode()		)






      @require_torch
      def 				A__      ( self			:		str		)  ->  List[str]:


       '''simple docstring'''

       lowercase					:   str				  ='''
from transformers import BertConfig, BertModel, BertTokenizer, pipeline
        '''

       lowercase					:   Optional[Any]				  ='''
mname = "hf-internal-testing/tiny-random-bert"
BertConfig.from_pretrained(mname)
BertModel.from_pretrained(mname)
BertTokenizer.from_pretrained(mname)
pipe = pipeline(task="fill-mask", model=mname)
print("success")
        '''

       lowercase					:   Optional[int]				  ='''
import socket
def offline_socket(*args, **kwargs): raise socket.error("Faking flaky internet")
socket.socket = offline_socket
        '''

       # Force fetching the files so that we can use the cache
       lowercase					:   Optional[Any]				  ='''hf-internal-testing/tiny-random-bert'''
       BertConfig.from_pretrained(UpperCAmelCase		)
       BertModel.from_pretrained(UpperCAmelCase		)
       BertTokenizer.from_pretrained(UpperCAmelCase		)
       pipeline(task='''fill-mask'''     ,      model=UpperCAmelCase		)

       # baseline - just load from_pretrained with normal network
       lowercase					:   Optional[Any]				  =[sys.executable, '''-c''', '''\n'''.join([load, run, mock]		)]

       # should succeed
       lowercase					:   str				  =self.get_env()
       lowercase					:   Any				  =subprocess.run(UpperCAmelCase     ,      env=UpperCAmelCase     ,      check=UpperCAmelCase     ,      capture_output=UpperCAmelCase		)
       self.assertEqual(result.returncode     ,      0     ,      result.stderr		)
       self.assertIn('''success'''     ,      result.stdout.decode()		)






      @require_torch
      def 				A__      ( self			:		Any		)  ->  Optional[Any]:


       '''simple docstring'''

       lowercase					:   Optional[Any]				  ='''
from transformers import BertConfig, BertModel, BertTokenizer
        '''

       lowercase					:   List[Any]				  ='''
mname = "hf-internal-testing/tiny-random-bert-sharded"
BertConfig.from_pretrained(mname)
BertModel.from_pretrained(mname)
print("success")
        '''

       lowercase					:   int				  ='''
import socket
def offline_socket(*args, **kwargs): raise ValueError("Offline mode is enabled")
socket.socket = offline_socket
        '''

       # baseline - just load from_pretrained with normal network
       lowercase					:   Tuple				  =[sys.executable, '''-c''', '''\n'''.join([load, run]		)]

       # should succeed
       lowercase					:   Optional[Any]				  =self.get_env()
       lowercase					:   List[Any]				  =subprocess.run(UpperCAmelCase     ,      env=UpperCAmelCase     ,      check=UpperCAmelCase     ,      capture_output=UpperCAmelCase		)
       self.assertEqual(result.returncode     ,      0     ,      result.stderr		)
       self.assertIn('''success'''     ,      result.stdout.decode()		)

       # next emulate no network
       lowercase					:   Tuple				  =[sys.executable, '''-c''', '''\n'''.join([load, mock, run]		)]

       # Doesn't fail anymore since the model is in the cache due to other tests, so commenting this.
       # env["TRANSFORMERS_OFFLINE"] = "0"
       # result = subprocess.run(cmd, env=env, check=False, capture_output=True)
       # self.assertEqual(result.returncode, 1, result.stderr)

       # should succeed as TRANSFORMERS_OFFLINE=1 tells it to use local files
       lowercase					:   Any				  ='''1'''
       lowercase					:   Optional[Any]				  =subprocess.run(UpperCAmelCase     ,      env=UpperCAmelCase     ,      check=UpperCAmelCase     ,      capture_output=UpperCAmelCase		)
       self.assertEqual(result.returncode     ,      0     ,      result.stderr		)
       self.assertIn('''success'''     ,      result.stdout.decode()		)






      @require_torch
      def 				A__      ( self			:		Tuple		)  ->  Optional[int]:


       '''simple docstring'''

       lowercase					:   Optional[int]				  ='''
from transformers import pipeline
        '''
       lowercase					:   List[Any]				  ='''
mname = "hf-internal-testing/tiny-random-bert"
pipe = pipeline(model=mname)
        '''

       lowercase					:   Tuple				  ='''
import socket
def offline_socket(*args, **kwargs): raise socket.error("Offline mode is enabled")
socket.socket = offline_socket
        '''
       lowercase					:   Tuple				  =self.get_env()
       lowercase					:   Optional[int]				  ='''1'''
       lowercase					:   Union[str, Any]				  =[sys.executable, '''-c''', '''\n'''.join([load, mock, run]		)]
       lowercase					:   Dict				  =subprocess.run(UpperCAmelCase     ,      env=UpperCAmelCase     ,      check=UpperCAmelCase     ,      capture_output=UpperCAmelCase		)
       self.assertEqual(result.returncode     ,      1     ,      result.stderr		)
       self.assertIn(
           '''You cannot infer task automatically within `pipeline` when using offline mode'''     ,      result.stderr.decode().replace('''\n'''     ,      ''''''		)     ,      )






      @require_torch
      def 				A__      ( self			:		int		)  ->  Optional[int]:


       '''simple docstring'''

       lowercase					:   List[str]				  ='''
from transformers import AutoModel
        '''
       lowercase					:   Dict				  ='''
mname = "hf-internal-testing/test_dynamic_model"
AutoModel.from_pretrained(mname, trust_remote_code=True)
print("success")
        '''

       # baseline - just load from_pretrained with normal network
       lowercase					:   Dict				  =[sys.executable, '''-c''', '''\n'''.join([load, run]		)]

       # should succeed
       lowercase					:   Optional[Any]				  =self.get_env()
       lowercase					:   int				  =subprocess.run(UpperCAmelCase     ,      env=UpperCAmelCase     ,      check=UpperCAmelCase     ,      capture_output=UpperCAmelCase		)
       self.assertEqual(result.returncode     ,      0     ,      result.stderr		)
       self.assertIn('''success'''     ,      result.stdout.decode()		)

       # should succeed as TRANSFORMERS_OFFLINE=1 tells it to use local files
       lowercase					:   List[str]				  ='''1'''
       lowercase					:   List[Any]				  =subprocess.run(UpperCAmelCase     ,      env=UpperCAmelCase     ,      check=UpperCAmelCase     ,      capture_output=UpperCAmelCase		)
       self.assertEqual(result.returncode     ,      0     ,      result.stderr		)
       self.assertIn('''success'''     ,      result.stdout.decode()		)



