




"""simple docstring"""




import math
from enum import Enum
from typing import Optional, Union

from torch.optim import Optimizer
from torch.optim.lr_scheduler import LambdaLR

from .utils import logging


_lowerCamelCase     :		str								=       logging.get_logger(__name__)


class     UpperCamelCase_   (			UpperCAmelCase__					):

    '''simple docstring'''






    UpperCAmelCase__							  =				'''linear'''
    UpperCAmelCase__							  =				'''cosine'''
    UpperCAmelCase__							  =				'''cosine_with_restarts'''
    UpperCAmelCase__							  =				'''polynomial'''
    UpperCAmelCase__							  =				'''constant'''
    UpperCAmelCase__							  =				'''constant_with_warmup'''
    UpperCAmelCase__							  =				'''piecewise_constant'''







def SCREAMING_SNAKE_CASE    (	lowercase_			,    lowercase_ = -1						)       ->	List[str]:



       """simple docstring"""

       return LambdaLR(lowercase_			,    lambda lowercase_						: 1			,    last_epoch=lowercase_						)







def SCREAMING_SNAKE_CASE    (	lowercase_			,    lowercase_			,    lowercase_ = -1						)       ->	List[str]:



       """simple docstring"""

       def lr_lambda(lowercase_						):
              if current_step < num_warmup_steps:
                     return float(lowercase_						) / float(max(1.0			,    lowercase_						)						)
              return 1.0

       return LambdaLR(lowercase_			,    lowercase_			,    last_epoch=lowercase_						)







def SCREAMING_SNAKE_CASE    (	lowercase_			,    lowercase_			,    lowercase_ = -1						)       ->	List[str]:



       """simple docstring"""

       A__							=   {}
       A__							=   step_rules.split(''','''						)
       for rule_str in rule_list[:-1]:
              A__			,							A__							=   rule_str.split(''':'''						)
              A__							=   int(lowercase_						)
              A__							=   float(lowercase_						)
              A__							=   value
       A__							=   float(rule_list[-1]						)

       def create_rules_function(lowercase_			,    lowercase_						):
              def rule_func(lowercase_						) -> float:
                     A__							=   sorted(rules_dict.keys()						)
                     for i, sorted_step in enumerate(lowercase_						):
                            if steps < sorted_step:
                                   return rules_dict[sorted_steps[i]]
                     return last_lr_multiple

              return rule_func

       A__							=   create_rules_function(lowercase_			,    lowercase_						)

       return LambdaLR(lowercase_			,    lowercase_			,    last_epoch=lowercase_						)







def SCREAMING_SNAKE_CASE    (	lowercase_			,    lowercase_			,    lowercase_			,    lowercase_=-1						)       ->	Optional[Any]:



       """simple docstring"""

       def lr_lambda(lowercase_						):
              if current_step < num_warmup_steps:
                     return float(lowercase_						) / float(max(1			,    lowercase_						)						)
              return max(
                  0.0			,    float(num_training_steps - current_step						) / float(max(1			,    num_training_steps - num_warmup_steps						)						)						)

       return LambdaLR(lowercase_			,    lowercase_			,    lowercase_						)







def SCREAMING_SNAKE_CASE    (	lowercase_			,    lowercase_			,    lowercase_			,    lowercase_ = 0.5			,    lowercase_ = -1						)       ->	List[Any]:



       """simple docstring"""

       def lr_lambda(lowercase_						):
              if current_step < num_warmup_steps:
                     return float(lowercase_						) / float(max(1			,    lowercase_						)						)
              A__							=   float(current_step - num_warmup_steps						) / float(max(1			,    num_training_steps - num_warmup_steps						)						)
              return max(0.0			,    0.5 * (1.0 + math.cos(math.pi * float(lowercase_						) * 2.0 * progress						))						)

       return LambdaLR(lowercase_			,    lowercase_			,    lowercase_						)







def SCREAMING_SNAKE_CASE    (	lowercase_			,    lowercase_			,    lowercase_			,    lowercase_ = 1			,    lowercase_ = -1						)       ->	Tuple:



       """simple docstring"""

       def lr_lambda(lowercase_						):
              if current_step < num_warmup_steps:
                     return float(lowercase_						) / float(max(1			,    lowercase_						)						)
              A__							=   float(current_step - num_warmup_steps						) / float(max(1			,    num_training_steps - num_warmup_steps						)						)
              if progress >= 1.0:
                     return 0.0
              return max(0.0			,    0.5 * (1.0 + math.cos(math.pi * ((float(lowercase_						) * progress) % 1.0)						))						)

       return LambdaLR(lowercase_			,    lowercase_			,    lowercase_						)







def SCREAMING_SNAKE_CASE    (	lowercase_			,    lowercase_			,    lowercase_			,    lowercase_=1E-7			,    lowercase_=1.0			,    lowercase_=-1						)       ->	Optional[Any]:



       """simple docstring"""

       A__							=   optimizer.defaults['''lr''']
       if not (lr_init > lr_end):
              raise ValueError(f"""lr_end ({lr_end}) must be be smaller than initial lr ({lr_init})"""						)

       def lr_lambda(lowercase_						):
              if current_step < num_warmup_steps:
                     return float(lowercase_						) / float(max(1			,    lowercase_						)						)
              elif current_step > num_training_steps:
                     return lr_end / lr_init  # as LambdaLR multiplies by lr_init
              else:
                     A__							=   lr_init - lr_end
                     A__							=   num_training_steps - num_warmup_steps
                     A__							=   1 - (current_step - num_warmup_steps) / decay_steps
                     A__							=   lr_range * pct_remaining**power + lr_end
                     return decay / lr_init  # as LambdaLR multiplies by lr_init

       return LambdaLR(lowercase_			,    lowercase_			,    lowercase_						)


_lowerCamelCase     :		str								=       {
    SchedulerType.LINEAR: get_linear_schedule_with_warmup,
    SchedulerType.COSINE: get_cosine_schedule_with_warmup,
    SchedulerType.COSINE_WITH_RESTARTS: get_cosine_with_hard_restarts_schedule_with_warmup,
    SchedulerType.POLYNOMIAL: get_polynomial_decay_schedule_with_warmup,
    SchedulerType.CONSTANT: get_constant_schedule,
    SchedulerType.CONSTANT_WITH_WARMUP: get_constant_schedule_with_warmup,
    SchedulerType.PIECEWISE_CONSTANT: get_piecewise_constant_schedule,
}







def SCREAMING_SNAKE_CASE    (	lowercase_			,    lowercase_			,    lowercase_ = None			,    lowercase_ = None			,    lowercase_ = None			,    lowercase_ = 1			,    lowercase_ = 1.0			,    lowercase_ = -1			,    )       ->	List[str]:



       """simple docstring"""

       A__							=   SchedulerType(lowercase_						)
       A__							=   TYPE_TO_SCHEDULER_FUNCTION[name]
       if name == SchedulerType.CONSTANT:
              return schedule_func(lowercase_			,    last_epoch=lowercase_						)

       if name == SchedulerType.PIECEWISE_CONSTANT:
              return schedule_func(lowercase_			,    step_rules=lowercase_			,    last_epoch=lowercase_						)

       # All other schedulers require `num_warmup_steps`
       if num_warmup_steps is None:
              raise ValueError(f"""{name} requires `num_warmup_steps`, please provide that argument."""						)

       if name == SchedulerType.CONSTANT_WITH_WARMUP:
              return schedule_func(lowercase_			,    num_warmup_steps=lowercase_			,    last_epoch=lowercase_						)

       # All other schedulers require `num_training_steps`
       if num_training_steps is None:
              raise ValueError(f"""{name} requires `num_training_steps`, please provide that argument."""						)

       if name == SchedulerType.COSINE_WITH_RESTARTS:
              return schedule_func(
                  lowercase_			,    num_warmup_steps=lowercase_			,    num_training_steps=lowercase_			,    num_cycles=lowercase_			,    last_epoch=lowercase_			,    )

       if name == SchedulerType.POLYNOMIAL:
              return schedule_func(
                  lowercase_			,    num_warmup_steps=lowercase_			,    num_training_steps=lowercase_			,    power=lowercase_			,    last_epoch=lowercase_			,    )

       return schedule_func(
           lowercase_			,    num_warmup_steps=lowercase_			,    num_training_steps=lowercase_			,    last_epoch=lowercase_						)








from __future__ import annotations

import queue


class     UpperCamelCase_   :

    '''simple docstring'''






    def __init__(      self				:     Optional[Any] ,			UpperCAmelCase__				:     Dict)						->Any:





           '''simple docstring'''

           A__							=   data
           A__							=   None
           A__							=   None







def SCREAMING_SNAKE_CASE    (	)       ->	TreeNode:



       """simple docstring"""

       print('''\n********Press N to stop entering at any point of time********\n'''						)
       A__							=   input('''Enter the value of the root node: '''						).strip().lower()
       A__							=   queue.Queue()
       A__							=   TreeNode(int(lowercase_						)						)
       q.put(lowercase_						)
       while not q.empty():
              A__							=   q.get()
              A__							=   f"""Enter the left node of {node_found.data}: """
              A__							=   input(lowercase_						).strip().lower() or '''n'''
              if check == "n":
                     return tree_node
              A__							=   TreeNode(int(lowercase_						)						)
              A__							=   left_node
              q.put(lowercase_						)
              A__							=   f"""Enter the right node of {node_found.data}: """
              A__							=   input(lowercase_						).strip().lower() or '''n'''
              if check == "n":
                     return tree_node
              A__							=   TreeNode(int(lowercase_						)						)
              A__							=   right_node
              q.put(lowercase_						)
       raise







def SCREAMING_SNAKE_CASE    (	lowercase_						)       ->	None:



       """simple docstring"""

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







def SCREAMING_SNAKE_CASE    (	lowercase_						)       ->	None:



       """simple docstring"""

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







def SCREAMING_SNAKE_CASE    (	lowercase_						)       ->	None:



       """simple docstring"""

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







def SCREAMING_SNAKE_CASE    (	lowercase_						)       ->	None:



       """simple docstring"""

       if not isinstance(lowercase_			,    lowercase_						) or not node:
              return
       A__							=   queue.Queue()
       q.put(lowercase_						)
       while not q.empty():
              A__							=   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 SCREAMING_SNAKE_CASE    (	lowercase_						)       ->	None:



       """simple docstring"""

       if not isinstance(lowercase_			,    lowercase_						) or not node:
              return
       A__							=   queue.Queue()
       q.put(lowercase_						)
       while not q.empty():
              A__							=   []
              while not q.empty():
                     A__							=   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(lowercase_						)







def SCREAMING_SNAKE_CASE    (	lowercase_						)       ->	None:



       """simple docstring"""

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







def SCREAMING_SNAKE_CASE    (	lowercase_						)       ->	None:



       """simple docstring"""

       if not isinstance(lowercase_			,    lowercase_						) or not node:
              return
       A__							=   []
       A__							=   node
       while n or stack:
              while n:
                     stack.append(lowercase_						)
                     A__							=   n.left
              A__							=   stack.pop()
              print(n.data			,    end=''','''						)
              A__							=   n.right







def SCREAMING_SNAKE_CASE    (	lowercase_						)       ->	None:



       """simple docstring"""

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







def SCREAMING_SNAKE_CASE    (	lowercase_ = ""			,    lowercase_=50			,    lowercase_="*"						)       ->	str:



       """simple docstring"""

       if not s:
              return "\n" + width * char
       A__			,							A__							=   divmod(width - len(lowercase_						) - 2			,    2						)
       return f"""{left * char} {s} {(left + extra) * char}"""


if __name__ == "__main__":
  import doctest

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

  _lowerCamelCase     :		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())


