


"""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__      				=   logging.get_logger(__name__)


class       SCREAMING_SNAKE_CASE__				(		lowercase				):
       """simple docstring"""


       a  :				Any   ="linear"
       a  :				List[str]   ="cosine"
       a  :				List[str]   ="cosine_with_restarts"
       a  :				List[str]   ="polynomial"
       a  :				Tuple   ="constant"
       a  :				List[Any]   ="constant_with_warmup"
       a  :				Dict   ="piecewise_constant"

def 					a__			(				SCREAMING_SNAKE_CASE    :    Optimizer				,      SCREAMING_SNAKE_CASE    :    int = -1				):


  '''simple docstring'''







  return LambdaLR(SCREAMING_SNAKE_CASE				,      lambda SCREAMING_SNAKE_CASE				: 1				,      last_epoch=SCREAMING_SNAKE_CASE				)
def 					a__			(				SCREAMING_SNAKE_CASE    :    Optimizer				,      SCREAMING_SNAKE_CASE    :    int				,      SCREAMING_SNAKE_CASE    :    int = -1				):


  '''simple docstring'''







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

  return LambdaLR(SCREAMING_SNAKE_CASE				,      SCREAMING_SNAKE_CASE				,      last_epoch=SCREAMING_SNAKE_CASE				)
def 					a__			(				SCREAMING_SNAKE_CASE    :    Optimizer				,      SCREAMING_SNAKE_CASE    :    str				,      SCREAMING_SNAKE_CASE    :    int = -1				):


  '''simple docstring'''







  lowerCAmelCase     :     str								=							{}
  lowerCAmelCase     :     str								=							step_rules.split(","				)
  for rule_str in rule_list[:-1]:
    lowerCAmelCase						,  lowerCAmelCase     :     int								=							rule_str.split(":"				)
    lowerCAmelCase     :     int								=							int(SCREAMING_SNAKE_CASE				)
    lowerCAmelCase     :     Any								=							float(SCREAMING_SNAKE_CASE				)
    lowerCAmelCase     :     Optional[Any]								=							value
  lowerCAmelCase     :     str								=							float(rule_list[-1]				)

  def create_rules_function(SCREAMING_SNAKE_CASE    :    Tuple				,      SCREAMING_SNAKE_CASE    :    Dict				):
    def rule_func(SCREAMING_SNAKE_CASE    :    int				) -> float:
      lowerCAmelCase     :     List[Any]								=							sorted(rules_dict.keys()				)
      for i, sorted_step in enumerate(SCREAMING_SNAKE_CASE				):
        if steps < sorted_step:
          return rules_dict[sorted_steps[i]]
      return last_lr_multiple

    return rule_func

  lowerCAmelCase     :     str								=							create_rules_function(SCREAMING_SNAKE_CASE				,      SCREAMING_SNAKE_CASE				)

  return LambdaLR(SCREAMING_SNAKE_CASE				,      SCREAMING_SNAKE_CASE				,      last_epoch=SCREAMING_SNAKE_CASE				)
def 					a__			(				SCREAMING_SNAKE_CASE    :    Any				,      SCREAMING_SNAKE_CASE    :    List[str]				,      SCREAMING_SNAKE_CASE    :    Union[str, Any]				,      SCREAMING_SNAKE_CASE    :    int=-1				):


  '''simple docstring'''







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

  return LambdaLR(SCREAMING_SNAKE_CASE				,      SCREAMING_SNAKE_CASE				,      SCREAMING_SNAKE_CASE				)
def 					a__			(				SCREAMING_SNAKE_CASE    :    Optimizer				,      SCREAMING_SNAKE_CASE    :    int				,      SCREAMING_SNAKE_CASE    :    int				,      SCREAMING_SNAKE_CASE    :    float = 0.5				,      SCREAMING_SNAKE_CASE    :    int = -1				):


  '''simple docstring'''







  def lr_lambda(SCREAMING_SNAKE_CASE    :    List[Any]				):
    if current_step < num_warmup_steps:
      return float(SCREAMING_SNAKE_CASE				) / float(max(1				,      SCREAMING_SNAKE_CASE				)				)
    lowerCAmelCase     :     str								=							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(SCREAMING_SNAKE_CASE				) * 2.0 * progress				))				)

  return LambdaLR(SCREAMING_SNAKE_CASE				,      SCREAMING_SNAKE_CASE				,      SCREAMING_SNAKE_CASE				)
def 					a__			(				SCREAMING_SNAKE_CASE    :    Optimizer				,      SCREAMING_SNAKE_CASE    :    int				,      SCREAMING_SNAKE_CASE    :    int				,      SCREAMING_SNAKE_CASE    :    int = 1				,      SCREAMING_SNAKE_CASE    :    int = -1				):


  '''simple docstring'''







  def lr_lambda(SCREAMING_SNAKE_CASE    :    str				):
    if current_step < num_warmup_steps:
      return float(SCREAMING_SNAKE_CASE				) / float(max(1				,      SCREAMING_SNAKE_CASE				)				)
    lowerCAmelCase     :     Any								=							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(SCREAMING_SNAKE_CASE				) * progress) % 1.0)				))				)

  return LambdaLR(SCREAMING_SNAKE_CASE				,      SCREAMING_SNAKE_CASE				,      SCREAMING_SNAKE_CASE				)
def 					a__			(				SCREAMING_SNAKE_CASE    :    Tuple				,      SCREAMING_SNAKE_CASE    :    Optional[Any]				,      SCREAMING_SNAKE_CASE    :    Any				,      SCREAMING_SNAKE_CASE    :    Dict=1E-7				,      SCREAMING_SNAKE_CASE    :    Tuple=1.0				,      SCREAMING_SNAKE_CASE    :    Tuple=-1				):


  '''simple docstring'''







  lowerCAmelCase     :     Optional[int]								=							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(SCREAMING_SNAKE_CASE    :    int				):
    if current_step < num_warmup_steps:
      return float(SCREAMING_SNAKE_CASE				) / float(max(1				,      SCREAMING_SNAKE_CASE				)				)
    elif current_step > num_training_steps:
      return lr_end / lr_init  # as LambdaLR multiplies by lr_init
    else:
      lowerCAmelCase     :     int								=							lr_init - lr_end
      lowerCAmelCase     :     Optional[Any]								=							num_training_steps - num_warmup_steps
      lowerCAmelCase     :     Optional[Any]								=							1 - (current_step - num_warmup_steps) / decay_steps
      lowerCAmelCase     :     Any								=							lr_range * pct_remaining**power + lr_end
      return decay / lr_init  # as LambdaLR multiplies by lr_init

  return LambdaLR(SCREAMING_SNAKE_CASE				,      SCREAMING_SNAKE_CASE				,      SCREAMING_SNAKE_CASE				)


lowerCAmelCase__      				=   {
    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 					a__			(				SCREAMING_SNAKE_CASE    :    Union[str, SchedulerType]				,      SCREAMING_SNAKE_CASE    :    Optimizer				,      SCREAMING_SNAKE_CASE    :    Optional[str] = None				,      SCREAMING_SNAKE_CASE    :    Optional[int] = None				,      SCREAMING_SNAKE_CASE    :    Optional[int] = None				,      SCREAMING_SNAKE_CASE    :    int = 1				,      SCREAMING_SNAKE_CASE    :    float = 1.0				,      SCREAMING_SNAKE_CASE    :    int = -1				,      ):


  '''simple docstring'''







  lowerCAmelCase     :     Dict								=							SchedulerType(SCREAMING_SNAKE_CASE				)
  lowerCAmelCase     :     Tuple								=							TYPE_TO_SCHEDULER_FUNCTION[name]
  if name == SchedulerType.CONSTANT:
    return schedule_func(SCREAMING_SNAKE_CASE				,      last_epoch=SCREAMING_SNAKE_CASE				)

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

  # 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(SCREAMING_SNAKE_CASE				,      num_warmup_steps=SCREAMING_SNAKE_CASE				,      last_epoch=SCREAMING_SNAKE_CASE				)

  # 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(
        SCREAMING_SNAKE_CASE				,      num_warmup_steps=SCREAMING_SNAKE_CASE				,      num_training_steps=SCREAMING_SNAKE_CASE				,      num_cycles=SCREAMING_SNAKE_CASE				,      last_epoch=SCREAMING_SNAKE_CASE				,      )

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

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









"""simple docstring"""







class       SCREAMING_SNAKE_CASE__				:
       """simple docstring"""


       def __init__(						self		,     snake_case__ = ""		,     snake_case__ = False						):






         """simple docstring"""





         lowerCAmelCase     :     dict[str, RadixNode]								=							{}

         # A node will be a leaf if the tree contains its word
         lowerCAmelCase     :     str								=							is_leaf

         lowerCAmelCase     :     str								=							prefix

       def        lowercase__							(						self		,     snake_case__						):






         """simple docstring"""





         lowerCAmelCase     :     Dict								=							0
         for q, w in zip(self.prefix		,     snake_case__						):
           if q != w:
             break

           x += 1

         return self.prefix[:x], self.prefix[x:], word[x:]

       def        lowercase__							(						self		,     snake_case__						):






         """simple docstring"""





         for word in words:
           self.insert(snake_case__						)

       def        lowercase__							(						self		,     snake_case__						):






         """simple docstring"""





         if self.prefix == word:
           lowerCAmelCase     :     Union[str, Any]								=							True

         # Case 2: The node has no edges that have a prefix to the word
         # Solution: We create an edge from the current node to a new one
         # containing the word
         elif word[0] not in self.nodes:
           lowerCAmelCase     :     Optional[Any]								=							RadixNode(prefix=snake_case__		,     is_leaf=snake_case__						)

         else:
           lowerCAmelCase     :     Tuple								=							self.nodes[word[0]]
           lowerCAmelCase						,  lowerCAmelCase						,  lowerCAmelCase     :     Optional[Any]								=							incoming_node.match(
               snake_case__						)

           # Case 3: The node prefix is equal to the matching
           # Solution: We insert remaining word on the next node
           if remaining_prefix == "":
             self.nodes[matching_string[0]].insert(snake_case__						)

           # Case 4: The word is greater equal to the matching
           # Solution: Create a node in between both nodes, change
           # prefixes and add the new node for the remaining word
           else:
             lowerCAmelCase     :     Optional[Any]								=							remaining_prefix

             lowerCAmelCase     :     int								=							self.nodes[matching_string[0]]
             lowerCAmelCase     :     List[Any]								=							RadixNode(snake_case__		,     snake_case__						)
             lowerCAmelCase     :     Optional[int]								=							aux_node

             if remaining_word == "":
               lowerCAmelCase     :     Optional[int]								=							True
             else:
               self.nodes[matching_string[0]].insert(snake_case__						)

       def        lowercase__							(						self		,     snake_case__						):






         """simple docstring"""





         lowerCAmelCase     :     str								=							self.nodes.get(word[0]		,     snake_case__						)
         if not incoming_node:
           return False
         else:
           lowerCAmelCase						,  lowerCAmelCase						,  lowerCAmelCase     :     int								=							incoming_node.match(
               snake_case__						)
           # If there is remaining prefix, the word can't be on the tree
           if remaining_prefix != "":
             return False
           # This applies when the word and the prefix are equal
           elif remaining_word == "":
             return incoming_node.is_leaf
           # We have word remaining so we check the next node
           else:
             return incoming_node.find(snake_case__						)

       def        lowercase__							(						self		,     snake_case__						):






         """simple docstring"""





         lowerCAmelCase     :     int								=							self.nodes.get(word[0]		,     snake_case__						)
         if not incoming_node:
           return False
         else:
           lowerCAmelCase						,  lowerCAmelCase						,  lowerCAmelCase     :     Union[str, Any]								=							incoming_node.match(
               snake_case__						)
           # If there is remaining prefix, the word can't be on the tree
           if remaining_prefix != "":
             return False
           # We have word remaining so we check the next node
           elif remaining_word != "":
             return incoming_node.delete(snake_case__						)
           else:
             # If it is not a leaf, we don't have to delete
             if not incoming_node.is_leaf:
               return False
             else:
               # We delete the nodes if no edges go from it
               if len(incoming_node.nodes						) == 0:
                 del self.nodes[word[0]]
                 # We merge the current node with its only child
                 if len(self.nodes						) == 1 and not self.is_leaf:
                   lowerCAmelCase     :     List[str]								=							list(self.nodes.values()						)[0]
                   lowerCAmelCase     :     List[str]								=							merging_node.is_leaf
                   self.prefix += merging_node.prefix
                   lowerCAmelCase     :     Optional[int]								=							merging_node.nodes
                    # If there is more than 1 edge, we just mark it as non-leaf
               elif len(incoming_node.nodes						) > 1:
                 lowerCAmelCase     :     Optional[int]								=							False
               # If there is 1 edge, we merge it with its child
               else:
                 lowerCAmelCase     :     Optional[Any]								=							list(incoming_node.nodes.values()						)[0]
                 lowerCAmelCase     :     int								=							merging_node.is_leaf
                 incoming_node.prefix += merging_node.prefix
                 lowerCAmelCase     :     Tuple								=							merging_node.nodes

               return True







       def        lowercase__							(						self		,     snake_case__ = 0						):






         """simple docstring"""





         if self.prefix != "":
           print("-" * height		,     self.prefix		,     "  (leaf)" if self.is_leaf else ""						)

         for value in self.nodes.values():
           value.print_tree(height + 1						)

def 					a__			(				):


  '''simple docstring'''







  lowerCAmelCase     :     Union[str, Any]								=							"banana bananas bandana band apple all beast".split()
  lowerCAmelCase     :     List[str]								=							RadixNode()
  root.insert_many(SCREAMING_SNAKE_CASE				)

  assert all(root.find(SCREAMING_SNAKE_CASE				) for word in words				)
  assert not root.find("bandanas"				)
  assert not root.find("apps"				)
  root.delete("all"				)
  assert not root.find("all"				)
  root.delete("banana"				)
  assert not root.find("banana"				)
  assert root.find("bananas"				)

  return True
def 					a__			(				):


  '''simple docstring'''







  assert test_trie()
def 					a__			(				):


  '''simple docstring'''







  lowerCAmelCase     :     Dict								=							RadixNode()
  lowerCAmelCase     :     Optional[Any]								=							"banana bananas bandanas bandana band apple all beast".split()
  root.insert_many(SCREAMING_SNAKE_CASE				)

  print("Words:"				,      SCREAMING_SNAKE_CASE				)
  print("Tree:"				)
  root.print_tree()


if __name__ == "__main__":
     main()





