'''simple docstring'''

from __future__ import annotations

import queue


class 					_lowercase						:
      '''simple docstring'''


      def __init__(					self       ,lowerCamelCase_				)      ->      List[str]:



         '''simple docstring'''



         UpperCAmelCase__				:					Dict 					=	data
         UpperCAmelCase__				:					Optional[Any] 					=	None
         UpperCAmelCase__				:					List[str] 					=	None







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







def __UpperCamelCase( _A       :					TreeNode     ):
   '''simple docstring'''





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







def __UpperCamelCase( _A       :					TreeNode     ):
   '''simple docstring'''





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







def __UpperCamelCase( _A       :					TreeNode     ):
   '''simple docstring'''





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







def __UpperCamelCase( _A       :					TreeNode     ):
   '''simple docstring'''





   if not isinstance(_A	,      _A     ) or not node:
      return
   UpperCAmelCase__				:					queue.Queue 					=	queue.Queue()
   q.put(_A     )
   while not q.empty():
      UpperCAmelCase__				:					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 __UpperCamelCase( _A       :					TreeNode     ):
   '''simple docstring'''





   if not isinstance(_A	,      _A     ) or not node:
      return
   UpperCAmelCase__				:					queue.Queue 					=	queue.Queue()
   q.put(_A     )
   while not q.empty():
      UpperCAmelCase__				:					Dict 					=	[]
      while not q.empty():
         UpperCAmelCase__				:					Optional[Any] 					=	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 __UpperCamelCase( _A       :					TreeNode     ):
   '''simple docstring'''





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







def __UpperCamelCase( _A       :					TreeNode     ):
   '''simple docstring'''





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







def __UpperCamelCase( _A       :					TreeNode     ):
   '''simple docstring'''





   if not isinstance(_A	,      _A     ) or not node:
      return
   UpperCAmelCase__				:					List[str] 					=	[], []
   UpperCAmelCase__				:					int 					=	node
   stacka.append(_A     )
   while stacka:  # to find the reversed order of post order, store it in stack2
      UpperCAmelCase__				:					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 __UpperCamelCase( _A       :					str = ""	,      _A       :					Any=50	,      _A       :					str="*"     ):
   '''simple docstring'''





   if not s:
      return "\n" + width * char
   UpperCAmelCase__				:					List[str] 					=	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'))

  UpperCamelCase__  :						Dict					=      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 uuid
from typing import Any, Dict, List, Optional, Union

from ..utils import add_end_docstrings, is_tf_available, is_torch_available, logging
from .base import PIPELINE_INIT_ARGS, Pipeline


if is_tf_available():
  import tensorflow as tf

if is_torch_available():
  import torch


__snake_case       =       logging.get_logger(__name__)







class _lowerCAmelCase							:







   def __init__(      self		,      UpperCamelCase__ = None		,      UpperCamelCase__ = None		,      UpperCamelCase__=None		,      UpperCamelCase__=None		)      ->						Optional[Any]:

       '''simple docstring'''




       if not conversation_id:
           snake_case       : Union[str, Any]    =       uuid.uuida()
       if past_user_inputs is None:
           snake_case       : Optional[Any]    =       []
       if generated_responses is None:
           snake_case       : Optional[Any]    =       []

       snake_case       : uuid.UUID    =       conversation_id
       snake_case       : List[str]    =       past_user_inputs
       snake_case       : List[str]    =       generated_responses
       snake_case       : Optional[str]    =       text







   def __eq__(      self		,      UpperCamelCase__		)      ->						Any:

       '''simple docstring'''




       if not isinstance(UpperCamelCase__		,      UpperCamelCase__		):
           return False
       if self.uuid == other.uuid:
           return True
       return (
           self.new_user_input == other.new_user_input
           and self.past_user_inputs == other.past_user_inputs
           and self.generated_responses == other.generated_responses
       )







   def 					lowerCamelCase						(      self		,      UpperCamelCase__		,      UpperCamelCase__ = False		)      ->						Dict:

       '''simple docstring'''




       if self.new_user_input:
           if overwrite:
               logger.warning(
                   F'User input added while unprocessed input was existing: "{self.new_user_input}" was overwritten '
                   F'with: "{text}".'		)
               snake_case       : int    =       text
           else:
               logger.warning(
                   F'User input added while unprocessed input was existing: "{self.new_user_input}" new input '
                   F'ignored: "{text}". Set `overwrite` to True to overwrite unprocessed user input'		)
       else:
           snake_case       : Any    =       text







   def 					lowerCamelCase						(      self		)      ->						List[str]:

       '''simple docstring'''




       if self.new_user_input:
           self.past_user_inputs.append(self.new_user_input		)
       snake_case       : Dict    =       None







   def 					lowerCamelCase						(      self		,      UpperCamelCase__		)      ->						List[str]:

       '''simple docstring'''




       self.generated_responses.append(UpperCamelCase__		)







   def 					lowerCamelCase						(      self		)      ->						List[Any]:

       '''simple docstring'''




       for user_input, generated_response in zip(self.past_user_inputs		,      self.generated_responses		):
           yield True, user_input
           yield False, generated_response
       if self.new_user_input:
           yield True, self.new_user_input







   def __repr__(      self		)      ->						Union[str, Any]:

       '''simple docstring'''




       snake_case       : Optional[Any]    =       F'Conversation id: {self.uuid} \n'
       for is_user, text in self.iter_texts():
           snake_case       : List[str]    =       "user" if is_user else "bot"
           output += F'{name} >> {text} \n'
       return output







@add_end_docstrings(
    snake_case_       ,				R'''
        min_length_for_response (`int`, *optional*, defaults to 32):
            The minimum length (in number of tokens) for a response.
        minimum_tokens (`int`, *optional*, defaults to 10):
            The minimum length of tokens to leave for a response.
    '''       ,				)
class _lowerCAmelCase							( snake_case_      ):







   def __init__(      self		,      *UpperCamelCase__		,      **UpperCamelCase__		)      ->						str:

       '''simple docstring'''




       super().__init__(*UpperCamelCase__		,      **UpperCamelCase__		)
       if self.tokenizer.pad_token_id is None:
           snake_case       : str    =       self.tokenizer.eos_token







   def 					lowerCamelCase						(      self		,      UpperCamelCase__=None		,      UpperCamelCase__=None		,      UpperCamelCase__=None		,      **UpperCamelCase__		)      ->						Union[str, Any]:

       '''simple docstring'''




       snake_case       : Tuple    =       {}
       snake_case       : Optional[int]    =       {}
       snake_case       : Optional[Any]    =       {}

       if min_length_for_response is not None:
           snake_case       : int    =       min_length_for_response
       if minimum_tokens is not None:
           snake_case       : Dict    =       minimum_tokens

       if "max_length" in generate_kwargs:
           snake_case       : Any    =       generate_kwargs["max_length"]
           # self.max_length = generate_kwargs.get("max_length", self.model.config.max_length)
       if clean_up_tokenization_spaces is not None:
           snake_case       : Optional[Any]    =       clean_up_tokenization_spaces

       if generate_kwargs:
           forward_params.update(UpperCamelCase__		)
       return preprocess_params, forward_params, postprocess_params







   def __call__(      self		,      UpperCamelCase__		,      UpperCamelCase__=0		,      **UpperCamelCase__		)      ->						List[str]:

       '''simple docstring'''




       snake_case       : int    =       super().__call__(UpperCamelCase__		,      num_workers=UpperCamelCase__		,      **UpperCamelCase__		)
       if isinstance(UpperCamelCase__		,      UpperCamelCase__		) and len(UpperCamelCase__		) == 1:
           return outputs[0]
       return outputs







   def 					lowerCamelCase						(      self		,      UpperCamelCase__		,      UpperCamelCase__=32		)      ->						Dict[str, Any]:

       '''simple docstring'''




       if not isinstance(UpperCamelCase__		,      UpperCamelCase__		):
           raise ValueError("ConversationalPipeline, expects Conversation as inputs"		)
       if conversation.new_user_input is None:
           raise ValueError(
               F'Conversation with UUID {type(conversation.uuid		)} does not contain new user input to process. '
               "Add user inputs with the conversation's `add_user_input` method"		)
       if hasattr(self.tokenizer		,      "_build_conversation_input_ids"		):
           snake_case       : Optional[Any]    =       self.tokenizer._build_conversation_input_ids(UpperCamelCase__		)
       else:
           # If the tokenizer cannot handle conversations, we default to only the old version
           snake_case       : Optional[Any]    =       self._legacy_parse_and_tokenize(UpperCamelCase__		)

       if self.framework == "pt":
           snake_case       : Union[str, Any]    =       torch.LongTensor([input_ids]		)
       elif self.framework == "tf":
           snake_case       : Optional[int]    =       tf.constant([input_ids]		)
       return {"input_ids": input_ids, "conversation": conversation}







   def 					lowerCamelCase						(      self		,      UpperCamelCase__		,      UpperCamelCase__=10		,      **UpperCamelCase__		)      ->						Union[str, Any]:

       '''simple docstring'''




       snake_case       : Dict    =       generate_kwargs.get("max_length"		,      self.model.config.max_length		)

       snake_case       : Optional[Any]    =       model_inputs["input_ids"].shape[1]
       if max_length - minimum_tokens < n:
           logger.warning(F'Conversation input is to long ({n}), trimming it to ({max_length} - {minimum_tokens})'		)
           snake_case       : List[str]    =       max_length - minimum_tokens
           snake_case       : Dict    =       model_inputs["input_ids"][:, -trim:]
           if "attention_mask" in model_inputs:
               snake_case       : List[Any]    =       model_inputs["attention_mask"][:, -trim:]
       snake_case       : Union[str, Any]    =       model_inputs.pop("conversation"		)
       snake_case       : Union[str, Any]    =       max_length
       snake_case       : Any    =       self.model.generate(**UpperCamelCase__		,      **UpperCamelCase__		)
       if self.model.config.is_encoder_decoder:
           snake_case       : Optional[int]    =       1
       else:
           snake_case       : int    =       n
       return {"output_ids": output_ids[:, start_position:], "conversation": conversation}







   def 					lowerCamelCase						(      self		,      UpperCamelCase__		,      UpperCamelCase__=True		)      ->						Tuple:

       '''simple docstring'''




       snake_case       : Union[str, Any]    =       model_outputs["output_ids"]
       snake_case       : str    =       self.tokenizer.decode(
           output_ids[0]		,      skip_special_tokens=UpperCamelCase__		,      clean_up_tokenization_spaces=UpperCamelCase__		,      )
       snake_case       : List[Any]    =       model_outputs["conversation"]
       conversation.mark_processed()
       conversation.append_response(UpperCamelCase__		)
       return conversation







   def 					lowerCamelCase						(      self		,      UpperCamelCase__		)      ->						Dict:

       '''simple docstring'''




       snake_case       : str    =       self.tokenizer.eos_token_id
       snake_case       : str    =       []
       for is_user, text in conversation.iter_texts():
           if eos_token_id is not None:
               input_ids.extend(self.tokenizer.encode(UpperCamelCase__		,      add_special_tokens=UpperCamelCase__		) + [eos_token_id]		)
           else:
               input_ids.extend(self.tokenizer.encode(UpperCamelCase__		,      add_special_tokens=UpperCamelCase__		)		)

       if len(UpperCamelCase__		) > self.tokenizer.model_max_length:
           snake_case       : str    =       input_ids[-self.tokenizer.model_max_length :]
       return input_ids





