


from __future__ import annotations

_SCREAMING_SNAKE_CASE :					int			=	[2, 1, 4, 5, 6, 0, 8, 9, 1, 2, 0, 6, 4, 2, 0, 6, 5, 3, 2, 7]

class  UpperCamelCase__ :






      def __init__(     self					:   List[Any],		__lowerCamelCase					:   int   )  -> None:
           UpperCamelCase__							:  int								=     -1
           UpperCamelCase__							:  int								=     -1
           UpperCamelCase__							:  list[int]								=     [-1] * length
           UpperCamelCase__							:  Node | None								=     None
           UpperCamelCase__							:  Node | None								=     None






      def __repr__(     self					:   Optional[int]   )  -> str:
           return f'Node(min_value={self.minn} max_value={self.maxx})'







def 						_lowercase       (     __lowerCamelCase			:					list[int]			)  ->   Node | None:





     '''simple docstring'''





     UpperCamelCase__							:  Dict								=     Node(len(__lowerCamelCase			)			)
     UpperCamelCase__	,UpperCamelCase__							:  Tuple								=     min(__lowerCamelCase			), max(__lowerCamelCase			)
     # Leaf node case where the node contains only one unique value
     if root.minn == root.maxx:
          return root
     UpperCamelCase__							:  Any								=     (root.minn + root.maxx) // 2

     UpperCamelCase__							:  list[int]								=     []
     UpperCamelCase__							:  list[int]								=     []

     for index, num in enumerate(__lowerCamelCase			):
          if num <= pivot:
               left_arr.append(__lowerCamelCase			)
          else:
               right_arr.append(__lowerCamelCase			)
          UpperCamelCase__							:  Optional[int]								=     len(__lowerCamelCase			)
     UpperCamelCase__							:  List[str]								=     build_tree(__lowerCamelCase			)
     UpperCamelCase__							:  Tuple								=     build_tree(__lowerCamelCase			)
     return root







def 						_lowercase       (     __lowerCamelCase			:					Node | None		,__lowerCamelCase			:					int		,__lowerCamelCase			:					int			)  ->   int:





     '''simple docstring'''





     if index < 0 or node is None:
          return 0
     # Leaf node cases
     if node.minn == node.maxx:
          return index + 1 if node.minn == num else 0
     UpperCamelCase__							:  Optional[int]								=     (node.minn + node.maxx) // 2
     if num <= pivot:
          # go the left subtree and map index to the left subtree
          return rank_till_index(node.left		,__lowerCamelCase		,node.map_left[index] - 1			)
     else:
          # go to the right subtree and map index to the right subtree
          return rank_till_index(node.right		,__lowerCamelCase		,index - node.map_left[index]			)







def 						_lowercase       (     __lowerCamelCase			:					Node | None		,__lowerCamelCase			:					int		,__lowerCamelCase			:					int		,__lowerCamelCase			:					int			)  ->   int:





     '''simple docstring'''





     if start > end:
          return 0
     UpperCamelCase__							:  Dict								=     rank_till_index(__lowerCamelCase		,__lowerCamelCase		,__lowerCamelCase			)
     UpperCamelCase__							:  List[Any]								=     rank_till_index(__lowerCamelCase		,__lowerCamelCase		,start - 1			)
     return rank_till_end - rank_before_start







def 						_lowercase       (     __lowerCamelCase			:					Node | None		,__lowerCamelCase			:					int		,__lowerCamelCase			:					int		,__lowerCamelCase			:					int			)  ->   int:





     '''simple docstring'''





     if index > (end - start) or start > end or node is None:
          return -1
     # Leaf node case
     if node.minn == node.maxx:
          return node.minn
     # Number of elements in the left subtree in interval [start, end]
     UpperCamelCase__							:  Any								=     node.map_left[end] - (
         node.map_left[start - 1] if start else 0
     )
     if num_elements_in_left_tree > index:
          return quantile(
              node.left		,__lowerCamelCase		,(node.map_left[start - 1] if start else 0)		,node.map_left[end] - 1		,)
     else:
          return quantile(
              node.right		,index - num_elements_in_left_tree		,start - (node.map_left[start - 1] if start else 0)		,end - node.map_left[end]		,)







def 						_lowercase       (     __lowerCamelCase			:					Node | None		,__lowerCamelCase			:					int		,__lowerCamelCase			:					int		,__lowerCamelCase			:					int		,__lowerCamelCase			:					int			)  ->   int:





     '''simple docstring'''





     if (
         start > end
         or node is None
         or start_num > end_num
         or node.minn > end_num
         or node.maxx < start_num
     ):
          return 0
     if start_num <= node.minn and node.maxx <= end_num:
          return end - start + 1
     UpperCamelCase__							:  str								=     range_counting(
         node.left		,(node.map_left[start - 1] if start else 0)		,node.map_left[end] - 1		,__lowerCamelCase		,__lowerCamelCase		,)
     UpperCamelCase__							:  str								=     range_counting(
         node.right		,start - (node.map_left[start - 1] if start else 0)		,end - node.map_left[end]		,__lowerCamelCase		,__lowerCamelCase		,)
     return left + right


if __name__ == "__main__":
   import doctest

   doctest.testmod()








from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_sentencepiece_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


_SCREAMING_SNAKE_CASE :					Tuple			=	{
    """configuration_marian""": ["""MARIAN_PRETRAINED_CONFIG_ARCHIVE_MAP""", """MarianConfig""", """MarianOnnxConfig"""],
}

try:
   if not is_sentencepiece_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _SCREAMING_SNAKE_CASE :					Any			=	["""MarianTokenizer"""]

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _SCREAMING_SNAKE_CASE :					List[Any]			=	[
       """MARIAN_PRETRAINED_MODEL_ARCHIVE_LIST""",
       """MarianForCausalLM""",
       """MarianModel""",
       """MarianMTModel""",
       """MarianPreTrainedModel""",
   ]

try:
   if not is_tf_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _SCREAMING_SNAKE_CASE :					Dict			=	["""TFMarianModel""", """TFMarianMTModel""", """TFMarianPreTrainedModel"""]

try:
   if not is_flax_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _SCREAMING_SNAKE_CASE :					Optional[Any]			=	["""FlaxMarianModel""", """FlaxMarianMTModel""", """FlaxMarianPreTrainedModel"""]

if TYPE_CHECKING:
   from .configuration_marian import MARIAN_PRETRAINED_CONFIG_ARCHIVE_MAP, MarianConfig, MarianOnnxConfig

   try:
      if not is_sentencepiece_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .tokenization_marian import MarianTokenizer

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_marian import (
          MARIAN_PRETRAINED_MODEL_ARCHIVE_LIST,
          MarianForCausalLM,
          MarianModel,
          MarianMTModel,
          MarianPreTrainedModel,
      )

   try:
      if not is_tf_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_tf_marian import TFMarianModel, TFMarianMTModel, TFMarianPreTrainedModel

   try:
      if not is_flax_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_flax_marian import FlaxMarianModel, FlaxMarianMTModel, FlaxMarianPreTrainedModel

else:
   import sys

   _SCREAMING_SNAKE_CASE :					List[Any]			=	_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)




