



'''simple docstring'''




from __future__ import annotations

import queue






class 		_UpperCamelCase						:


   '''simple docstring'''

   def __init__(							self  :				Optional[int]							,  lowerCAmelCase__  :				Dict		):





     """simple docstring"""






     __SCREAMING_SNAKE_CASE :	List[str]					 =	data
     __SCREAMING_SNAKE_CASE :	Tuple					 =	None
     __SCREAMING_SNAKE_CASE :	Optional[int]					 =	None


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


def        lowerCAmelCase_     (			_lowerCamelCase:     TreeNode      ):
  if not isinstance(_lowerCamelCase ,   _lowerCamelCase      ) or not node:
    return
  print(node.data ,   end=""","""      )
  pre_order(node.left      )
  pre_order(node.right      )


def        lowerCAmelCase_     (			_lowerCamelCase:     TreeNode      ):
  if not isinstance(_lowerCamelCase ,   _lowerCamelCase      ) or not node:
    return
  in_order(node.left      )
  print(node.data ,   end=""","""      )
  in_order(node.right      )


def        lowerCAmelCase_     (			_lowerCamelCase:     TreeNode      ):
  if not isinstance(_lowerCamelCase ,   _lowerCamelCase      ) or not node:
    return
  post_order(node.left      )
  post_order(node.right      )
  print(node.data ,   end=""","""      )


def        lowerCAmelCase_     (			_lowerCamelCase:     TreeNode      ):
  if not isinstance(_lowerCamelCase ,   _lowerCamelCase      ) or not node:
    return
  __SCREAMING_SNAKE_CASE :	queue.Queue					 =	queue.Queue()
  q.put(_lowerCamelCase      )
  while not q.empty():
    __SCREAMING_SNAKE_CASE :	Optional[int]					 =	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        lowerCAmelCase_     (			_lowerCamelCase:     TreeNode      ):
  if not isinstance(_lowerCamelCase ,   _lowerCamelCase      ) or not node:
    return
  __SCREAMING_SNAKE_CASE :	queue.Queue					 =	queue.Queue()
  q.put(_lowerCamelCase      )
  while not q.empty():
    __SCREAMING_SNAKE_CASE :	Any					 =	[]
    while not q.empty():
      __SCREAMING_SNAKE_CASE :	Optional[int]					 =	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(_lowerCamelCase      )


def        lowerCAmelCase_     (			_lowerCamelCase:     TreeNode      ):
  if not isinstance(_lowerCamelCase ,   _lowerCamelCase      ) or not node:
    return
  __SCREAMING_SNAKE_CASE :	list[TreeNode]					 =	[]
  __SCREAMING_SNAKE_CASE :	Optional[int]					 =	node
  while n or stack:
    while n:  # start from root node, find its left child
      print(n.data ,   end=""","""      )
      stack.append(_lowerCamelCase      )
      __SCREAMING_SNAKE_CASE :	Any					 =	n.left
    # end of while means current node doesn't have left child
    __SCREAMING_SNAKE_CASE :	Dict					 =	stack.pop()
    # start to traverse its right child
    __SCREAMING_SNAKE_CASE :	int					 =	n.right


def        lowerCAmelCase_     (			_lowerCamelCase:     TreeNode      ):
  if not isinstance(_lowerCamelCase ,   _lowerCamelCase      ) or not node:
    return
  __SCREAMING_SNAKE_CASE :	list[TreeNode]					 =	[]
  __SCREAMING_SNAKE_CASE :	int					 =	node
  while n or stack:
    while n:
      stack.append(_lowerCamelCase      )
      __SCREAMING_SNAKE_CASE :	int					 =	n.left
    __SCREAMING_SNAKE_CASE :	Dict					 =	stack.pop()
    print(n.data ,   end=""","""      )
    __SCREAMING_SNAKE_CASE :	List[Any]					 =	n.right


def        lowerCAmelCase_     (			_lowerCamelCase:     TreeNode      ):
  if not isinstance(_lowerCamelCase ,   _lowerCamelCase      ) or not node:
    return
  __SCREAMING_SNAKE_CASE :	Tuple					 =	[], []
  __SCREAMING_SNAKE_CASE :	str					 =	node
  stacka.append(_lowerCamelCase      )
  while stacka:  # to find the reversed order of post order, store it in stack2
    __SCREAMING_SNAKE_CASE :	str					 =	stacka.pop()
    if n.left:
      stacka.append(n.left      )
    if n.right:
      stacka.append(n.right      )
    stacka.append(_lowerCamelCase      )
  while stacka:  # pop up from stack2 will be the post order
    print(stacka.pop().data ,   end=""","""      )


def        lowerCAmelCase_     (			_lowerCamelCase:     str = "" ,   _lowerCamelCase:     List[Any]=50 ,   _lowerCamelCase:     Optional[int]="*"      ):
  if not s:
    return "\n" + width * char
  __SCREAMING_SNAKE_CASE :	Optional[Any]					 =	divmod(width - len(_lowerCamelCase      ) - 2 ,   2      )
  return F"{left * char} {s} {(left + extra) * char}"


if __name__ == "__main__":
      import doctest

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

      UpperCamelCase__ :			TreeNode												=				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'''




from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxSeqaSeqConfigWithPast
from ...utils import logging


UpperCamelCase__ :			Tuple												=				logging.get_logger(__name__)

UpperCamelCase__ :			List[str]												=				{
    '''t5-small''': '''https://huggingface.co/t5-small/resolve/main/config.json''',
    '''t5-base''': '''https://huggingface.co/t5-base/resolve/main/config.json''',
    '''t5-large''': '''https://huggingface.co/t5-large/resolve/main/config.json''',
    '''t5-3b''': '''https://huggingface.co/t5-3b/resolve/main/config.json''',
    '''t5-11b''': '''https://huggingface.co/t5-11b/resolve/main/config.json''',
}






class 		_UpperCamelCase						(							lowerCamelCase__					):


			'''simple docstring'''

			_A   :	Union[str, Any]    					=	'''t5'''
			_A   :	Optional[Any]    					=	['''past_key_values''']
			_A   :	Any    					=	{'''hidden_size''': '''d_model''', '''num_attention_heads''': '''num_heads''', '''num_hidden_layers''': '''num_layers'''}

			def __init__(							self  :				Union[str, Any]							,  lowerCAmelCase__  :				List[str]=3_2_1_2_8							,  lowerCAmelCase__  :				Dict=5_1_2							,  lowerCAmelCase__  :				str=6_4							,  lowerCAmelCase__  :				Tuple=2_0_4_8							,  lowerCAmelCase__  :				Optional[Any]=6							,  lowerCAmelCase__  :				Any=None							,  lowerCAmelCase__  :				Any=8							,  lowerCAmelCase__  :				Dict=3_2							,  lowerCAmelCase__  :				Dict=1_2_8							,  lowerCAmelCase__  :				Any=0.1							,  lowerCAmelCase__  :				str=1E-6							,  lowerCAmelCase__  :				str=1.0							,  lowerCAmelCase__  :				Optional[Any]="relu"							,  lowerCAmelCase__  :				List[str]=True							,  lowerCAmelCase__  :				Union[str, Any]=True							,  lowerCAmelCase__  :				Optional[Any]=0							,  lowerCAmelCase__  :				List[Any]=1							,  **lowerCAmelCase__  :				Dict							,  ):





					"""simple docstring"""






					__SCREAMING_SNAKE_CASE :	List[str]					 =	vocab_size
					__SCREAMING_SNAKE_CASE :	str					 =	d_model
					__SCREAMING_SNAKE_CASE :	str					 =	d_kv
					__SCREAMING_SNAKE_CASE :	Optional[Any]					 =	d_ff
					__SCREAMING_SNAKE_CASE :	Optional[Any]					 =	num_layers
					__SCREAMING_SNAKE_CASE :	List[str]					 =	(
					    num_decoder_layers if num_decoder_layers is not None else self.num_layers
					)  # default = symmetry
					__SCREAMING_SNAKE_CASE :	Optional[int]					 =	num_heads
					__SCREAMING_SNAKE_CASE :	Any					 =	relative_attention_num_buckets
					__SCREAMING_SNAKE_CASE :	int					 =	relative_attention_max_distance
					__SCREAMING_SNAKE_CASE :	Optional[int]					 =	dropout_rate
					__SCREAMING_SNAKE_CASE :	Optional[int]					 =	layer_norm_epsilon
					__SCREAMING_SNAKE_CASE :	Optional[int]					 =	initializer_factor
					__SCREAMING_SNAKE_CASE :	Any					 =	feed_forward_proj
					__SCREAMING_SNAKE_CASE :	str					 =	use_cache

					__SCREAMING_SNAKE_CASE :	List[str]					 =	self.feed_forward_proj.split("""-"""		)
					__SCREAMING_SNAKE_CASE :	Tuple					 =	act_info[-1]
					__SCREAMING_SNAKE_CASE :	int					 =	act_info[0] == """gated"""

					if len(lowerCAmelCase__		) > 1 and act_info[0] != "gated" or len(lowerCAmelCase__		) > 2:
							raise ValueError(
							    F"`feed_forward_proj`: {feed_forward_proj} is not a valid activation function of the dense layer."
							    """Please make sure `feed_forward_proj` is of the format `gated-{ACT_FN}` or `{ACT_FN}`, e.g. """
							    """'gated-gelu' or 'relu'"""		)

					# for backwards compatibility
					if feed_forward_proj == "gated-gelu":
							__SCREAMING_SNAKE_CASE :	List[Any]					 =	"""gelu_new"""

					super().__init__(
					    pad_token_id=lowerCAmelCase__							,  eos_token_id=lowerCAmelCase__							,  is_encoder_decoder=lowerCAmelCase__							,  **lowerCAmelCase__							,  )






class 		_UpperCamelCase						(							lowerCamelCase__					):


			'''simple docstring'''

			@property
			def UpperCamelCase__      (							self  :				Tuple		):





					"""simple docstring"""






					__SCREAMING_SNAKE_CASE :	List[Any]					 =	{
					    """input_ids""": {0: """batch""", 1: """encoder_sequence"""},
					    """attention_mask""": {0: """batch""", 1: """encoder_sequence"""},
					}
					if self.use_past:
							__SCREAMING_SNAKE_CASE :	Optional[Any]					 =	"""past_encoder_sequence + sequence"""
							__SCREAMING_SNAKE_CASE :	Optional[Any]					 =	{0: """batch"""}
							__SCREAMING_SNAKE_CASE :	Optional[int]					 =	{0: """batch""", 1: """past_decoder_sequence + sequence"""}
					else:
							__SCREAMING_SNAKE_CASE :	List[Any]					 =	{0: """batch""", 1: """decoder_sequence"""}
							__SCREAMING_SNAKE_CASE :	Optional[Any]					 =	{0: """batch""", 1: """decoder_sequence"""}

					if self.use_past:
							self.fill_with_past_key_values_(lowerCAmelCase__							,  direction="""inputs"""		)

					return common_inputs



			@property
			def UpperCamelCase__      (							self  :				List[str]		):





					"""simple docstring"""






					return 1_3