


'''simple docstring'''



from __future__ import annotations

__UpperCAmelCase     :List[str]												=  [2, 1, 4, 5, 6, 0, 8, 9, 1, 2, 0, 6, 4, 2, 0, 6, 5, 3, 2, 7]



class       a							:


     """simple docstring"""






     def __init__(							self	:						Any				,					snake_case	:						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[Any]     )		->				str:
          return f'Node(min_value={self.minn} max_value={self.maxx})'




def       _a      (		_lowercase   :      list[int]    ):





     '''simple docstring'''






     __UpperCAmelCase      :					Optional[int]    				=     Node(len(_lowercase    )    )
     __UpperCAmelCase				,  __UpperCAmelCase      :					str    				=     min(_lowercase    ), max(_lowercase    )
     # 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(_lowercase    ):
          if num <= pivot:
               left_arr.append(_lowercase    )
          else:
               right_arr.append(_lowercase    )
          __UpperCAmelCase      :					Dict    				=     len(_lowercase    )
     __UpperCAmelCase      :					Union[str, Any]    				=     build_tree(_lowercase    )
     __UpperCAmelCase      :					Dict    				=     build_tree(_lowercase    )
     return root




def       _a      (		_lowercase   :      Node | None     ,   _lowercase   :      int     ,   _lowercase   :      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      :					Tuple    				=     (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     ,   _lowercase     ,   node.map_left[index] - 1    )
     else:
          # go to the right subtree and map index to the right subtree
          return rank_till_index(node.right     ,   _lowercase     ,   index - node.map_left[index]    )




def       _a      (		_lowercase   :      Node | None     ,   _lowercase   :      int     ,   _lowercase   :      int     ,   _lowercase   :      int    ):





     '''simple docstring'''






     if start > end:
          return 0
     __UpperCAmelCase      :					str    				=     rank_till_index(_lowercase     ,   _lowercase     ,   _lowercase    )
     __UpperCAmelCase      :					Optional[int]    				=     rank_till_index(_lowercase     ,   _lowercase     ,   start - 1    )
     return rank_till_end - rank_before_start




def       _a      (		_lowercase   :      Node | None     ,   _lowercase   :      int     ,   _lowercase   :      int     ,   _lowercase   :      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      :					str    				=     node.map_left[end] - (
         node.map_left[start - 1] if start else 0
     )
     if num_elements_in_left_tree > index:
          return quantile(
              node.left     ,   _lowercase     ,   (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       _a      (		_lowercase   :      Node | None     ,   _lowercase   :      int     ,   _lowercase   :      int     ,   _lowercase   :      int     ,   _lowercase   :      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      :					Dict    				=     range_counting(
         node.left     ,   (node.map_left[start - 1] if start else 0)     ,   node.map_left[end] - 1     ,   _lowercase     ,   _lowercase     ,   )
     __UpperCAmelCase      :					Optional[Any]    				=     range_counting(
         node.right     ,   start - (node.map_left[start - 1] if start else 0)     ,   end - node.map_left[end]     ,   _lowercase     ,   _lowercase     ,   )
     return left + right


if __name__ == "__main__":
      import doctest

      doctest.testmod()



'''simple docstring'''



import unittest
import warnings
from dataclasses import dataclass

from transformers.convert_slow_tokenizer import SpmConverter
from transformers.testing_utils import get_tests_dir



@dataclass
class       a							:


     """simple docstring"""






     SCREAMING_SNAKE_CASE			:					str



class       a							(						unittest.TestCase			):


     """simple docstring"""






     def 					lowerCamelCase__					(							self	:						str     )		->				Dict:
          __UpperCAmelCase      :					str    				=     get_tests_dir('''fixtures/test_sentencepiece.model'''     )
          __UpperCAmelCase      :					List[Any]    				=     get_tests_dir('''fixtures/test_sentencepiece_with_bytefallback.model'''     )

          __UpperCAmelCase      :					Tuple    				=     FakeOriginalTokenizer(vocab_file=snake_case     )

          with warnings.catch_warnings(record=snake_case     ) as w:
               __UpperCAmelCase      :					Optional[int]    				=     SpmConverter(snake_case     )
          self.assertEqual(len(snake_case     )				,					0     )

          __UpperCAmelCase      :					str    				=     FakeOriginalTokenizer(vocab_file=snake_case     )

          with warnings.catch_warnings(record=snake_case     ) as w:
               __UpperCAmelCase      :					Optional[int]    				=     SpmConverter(snake_case     )
          self.assertEqual(len(snake_case     )				,					1     )

          self.assertIn(
              '''The sentencepiece tokenizer that you are converting to a fast tokenizer uses the byte fallback option'''
              ''' which is not implemented in the fast tokenizers.'''				,					str(w[0].message     )				,					)