


'''simple docstring'''






from __future__ import annotations

_A      =     [2, 1, 4, 5, 6, 0, 8, 9, 1, 2, 0, 6, 4, 2, 0, 6, 5, 3, 2, 7]






class      SCREAMING_SNAKE_CASE_	:




			def __init__(      self					,      lowercase       )			->						None:


								'''simple docstring'''






								__SCREAMING_SNAKE_CASE					:							int			   = -1
								__SCREAMING_SNAKE_CASE					:							int			   = -1
								__SCREAMING_SNAKE_CASE					:							list[int]			   = [-1] * length
								__SCREAMING_SNAKE_CASE					:							Node | None			   = None
								__SCREAMING_SNAKE_CASE					:							Node | None			   = None




			def __repr__(      self       )			->						str:


								'''simple docstring'''






								return f"""Node(min_value={self.minn} max_value={self.maxx})"""




def A_					(				__SCREAMING_SNAKE_CASE :					list[int]       )     ->  Node | None:
					__SCREAMING_SNAKE_CASE					:							Optional[Any]			   = Node(len(__SCREAMING_SNAKE_CASE       )       )
					__SCREAMING_SNAKE_CASE   ,   __SCREAMING_SNAKE_CASE					:							Optional[Any]			   = min(__SCREAMING_SNAKE_CASE       ), max(__SCREAMING_SNAKE_CASE       )
					# Leaf node case where the node contains only one unique value
					if root.minn == root.maxx:
										return root
					__SCREAMING_SNAKE_CASE					:							Tuple			   = (root.minn + root.maxx) // 2

					__SCREAMING_SNAKE_CASE					:							list[int]			   = []
					__SCREAMING_SNAKE_CASE					:							list[int]			   = []

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


def A_					(				__SCREAMING_SNAKE_CASE :					Node | None	,   __SCREAMING_SNAKE_CASE :					int	,   __SCREAMING_SNAKE_CASE :					int       )     ->  int:
					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
					__SCREAMING_SNAKE_CASE					:							List[Any]			   = (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	,   __SCREAMING_SNAKE_CASE	,   node.map_left[index] - 1       )
					else:
										# go to the right subtree and map index to the right subtree
										return rank_till_index(node.right	,   __SCREAMING_SNAKE_CASE	,   index - node.map_left[index]       )


def A_					(				__SCREAMING_SNAKE_CASE :					Node | None	,   __SCREAMING_SNAKE_CASE :					int	,   __SCREAMING_SNAKE_CASE :					int	,   __SCREAMING_SNAKE_CASE :					int       )     ->  int:
					if start > end:
										return 0
					__SCREAMING_SNAKE_CASE					:							Tuple			   = rank_till_index(__SCREAMING_SNAKE_CASE	,   __SCREAMING_SNAKE_CASE	,   __SCREAMING_SNAKE_CASE       )
					__SCREAMING_SNAKE_CASE					:							Tuple			   = rank_till_index(__SCREAMING_SNAKE_CASE	,   __SCREAMING_SNAKE_CASE	,   start - 1       )
					return rank_till_end - rank_before_start


def A_					(				__SCREAMING_SNAKE_CASE :					Node | None	,   __SCREAMING_SNAKE_CASE :					int	,   __SCREAMING_SNAKE_CASE :					int	,   __SCREAMING_SNAKE_CASE :					int       )     ->  int:
					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]
					__SCREAMING_SNAKE_CASE					:							List[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	,   __SCREAMING_SNAKE_CASE	,   (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_					(				__SCREAMING_SNAKE_CASE :					Node | None	,   __SCREAMING_SNAKE_CASE :					int	,   __SCREAMING_SNAKE_CASE :					int	,   __SCREAMING_SNAKE_CASE :					int	,   __SCREAMING_SNAKE_CASE :					int       )     ->  int:
					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
					__SCREAMING_SNAKE_CASE					:							Dict			   = range_counting(
					    node.left	,   (node.map_left[start - 1] if start else 0)	,   node.map_left[end] - 1	,   __SCREAMING_SNAKE_CASE	,   __SCREAMING_SNAKE_CASE	,   )
					__SCREAMING_SNAKE_CASE					:							str			   = range_counting(
					    node.right	,   start - (node.map_left[start - 1] if start else 0)	,   end - node.map_left[end]	,   __SCREAMING_SNAKE_CASE	,   __SCREAMING_SNAKE_CASE	,   )
					return left + right


if __name__ == "__main__":
						import doctest

						doctest.testmod()






'''simple docstring'''






# this script builds a small sample spm file tests/fixtures/test_sentencepiece_no_bos.model, with features needed by pegasus

# 1. pip install sentencepiece
#
# 2. wget https://raw.githubusercontent.com/google/sentencepiece/master/data/botchan.txt

# 3. build
import sentencepiece as spm

# pegasus:
# 1. no bos
# 2. eos_id is 1
# 3. unk_id is 2
# build a sample spm file accordingly
spm.SentencePieceTrainer.train(
    """--input=botchan.txt --model_prefix=test_sentencepiece_no_bos --bos_id=-1 --unk_id=2  --eos_id=1  --vocab_size=1000"""
)

# 4. now update the fixture
# mv test_sentencepiece_no_bos.model ../../tests/fixtures/


