


"""simple docstring"""







import itertools
import json
import os
import unittest

from transformers import AddedToken, RobertaTokenizer, RobertaTokenizerFast
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin




@require_tokenizers
class 				UpperCamelCase_			(				__lowerCamelCase    ,						unittest.TestCase):

	"""simple docstring"""





	snake_case__       :						List[str]					      =    RobertaTokenizer
	snake_case__       :						List[Any]					      =    RobertaTokenizerFast
	snake_case__       :						Any					      =    True
	snake_case__       :						Optional[Any]					      =    {"cls_token": "<s>"}




	def 						UpperCAmelCase_   (				self    :       Optional[Any]     ) ->			Optional[Any]:
						super().setUp()

						# Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
						__SCREAMING_SNAKE_CASE		     =       [
						    "l",
						    "o",
						    "w",
						    "e",
						    "r",
						    "s",
						    "t",
						    "i",
						    "d",
						    "n",
						    "\u0120",
						    "\u0120l",
						    "\u0120n",
						    "\u0120lo",
						    "\u0120low",
						    "er",
						    "\u0120lowest",
						    "\u0120newer",
						    "\u0120wider",
						    "<unk>",
						]
						__SCREAMING_SNAKE_CASE		     =       dict(zip(SCREAMING_SNAKE_CASE_    ,    range(len(SCREAMING_SNAKE_CASE_     )     )     )     )
						__SCREAMING_SNAKE_CASE		     =       ["#version: 0.2", "\u0120 l", "\u0120l o", "\u0120lo w", "e r", ""]
						__SCREAMING_SNAKE_CASE		     =       {"unk_token": "<unk>"}

						__SCREAMING_SNAKE_CASE		     =       os.path.join(self.tmpdirname    ,    VOCAB_FILES_NAMES["vocab_file"]     )
						__SCREAMING_SNAKE_CASE		     =       os.path.join(self.tmpdirname    ,    VOCAB_FILES_NAMES["merges_file"]     )
						with open(self.vocab_file    ,    "w"    ,    encoding="utf-8"     ) as fp:
											fp.write(json.dumps(SCREAMING_SNAKE_CASE_     ) + "\n"     )
						with open(self.merges_file    ,    "w"    ,    encoding="utf-8"     ) as fp:
											fp.write("\n".join(SCREAMING_SNAKE_CASE_     )     )




	def 						UpperCAmelCase_   (				self    :       Tuple    ,    **UpperCAmelCase__    :       str     ) ->			List[Any]:
						kwargs.update(self.special_tokens_map     )
						return self.tokenizer_class.from_pretrained(self.tmpdirname    ,    **SCREAMING_SNAKE_CASE_     )




	def 						UpperCAmelCase_   (				self    :       List[str]    ,    **UpperCAmelCase__    :       Optional[int]     ) ->			Union[str, Any]:
						kwargs.update(self.special_tokens_map     )
						return RobertaTokenizerFast.from_pretrained(self.tmpdirname    ,    **SCREAMING_SNAKE_CASE_     )




	def 						UpperCAmelCase_   (				self    :       Optional[int]    ,    UpperCAmelCase__    :       Dict     ) ->			Tuple:
						__SCREAMING_SNAKE_CASE		     =       "lower newer"
						__SCREAMING_SNAKE_CASE		     =       "lower newer"
						return input_text, output_text




	def 						UpperCAmelCase_   (				self    :       str     ) ->			int:
						__SCREAMING_SNAKE_CASE		     =       self.tokenizer_class(self.vocab_file    ,    self.merges_file    ,    **self.special_tokens_map     )
						__SCREAMING_SNAKE_CASE		     =       "lower newer"
						__SCREAMING_SNAKE_CASE		     =       ["l", "o", "w", "er", "\u0120", "n", "e", "w", "er"]
						__SCREAMING_SNAKE_CASE		     =       tokenizer.tokenize(SCREAMING_SNAKE_CASE_     )  # , add_prefix_space=True)
						self.assertListEqual(SCREAMING_SNAKE_CASE_    ,    SCREAMING_SNAKE_CASE_     )

						__SCREAMING_SNAKE_CASE		     =       tokens + [tokenizer.unk_token]
						__SCREAMING_SNAKE_CASE		     =       [0, 1, 2, 1_5, 1_0, 9, 3, 2, 1_5, 1_9]
						self.assertListEqual(tokenizer.convert_tokens_to_ids(SCREAMING_SNAKE_CASE_     )    ,    SCREAMING_SNAKE_CASE_     )




	def 						UpperCAmelCase_   (				self    :       Optional[int]     ) ->			int:
						__SCREAMING_SNAKE_CASE		     =       self.get_tokenizer()

						self.assertListEqual(tokenizer.encode("Hello world!"    ,    add_special_tokens=SCREAMING_SNAKE_CASE_     )    ,    [0, 3_1_4_1_4, 2_3_2, 3_2_8, 2]     )
						self.assertListEqual(
						    tokenizer.encode("Hello world! cécé herlolip 418"    ,    add_special_tokens=SCREAMING_SNAKE_CASE_     )    ,    [0, 3_1_4_1_4, 2_3_2, 3_2_8, 7_4_0, 1_1_4_0, 1_2_6_9_5, 6_9, 4_6_0_7_8, 1_5_8_8, 2]    ,    )




	@slow
	def 						UpperCAmelCase_   (				self    :       str     ) ->			Tuple:
						__SCREAMING_SNAKE_CASE		     =       self.tokenizer_class.from_pretrained("roberta-base"     )

						__SCREAMING_SNAKE_CASE		     =       tokenizer.encode("sequence builders"    ,    add_special_tokens=SCREAMING_SNAKE_CASE_     )
						__SCREAMING_SNAKE_CASE		     =       tokenizer.encode("multi-sequence build"    ,    add_special_tokens=SCREAMING_SNAKE_CASE_     )

						__SCREAMING_SNAKE_CASE		     =       tokenizer.encode(
						    "sequence builders"    ,    add_special_tokens=SCREAMING_SNAKE_CASE_    ,    add_prefix_space=SCREAMING_SNAKE_CASE_     )
						__SCREAMING_SNAKE_CASE		     =       tokenizer.encode(
						    "sequence builders"    ,    "multi-sequence build"    ,    add_special_tokens=SCREAMING_SNAKE_CASE_    ,    add_prefix_space=SCREAMING_SNAKE_CASE_     )

						__SCREAMING_SNAKE_CASE		     =       tokenizer.build_inputs_with_special_tokens(SCREAMING_SNAKE_CASE_     )
						__SCREAMING_SNAKE_CASE		     =       tokenizer.build_inputs_with_special_tokens(SCREAMING_SNAKE_CASE_    ,    SCREAMING_SNAKE_CASE_     )

						assert encoded_sentence == encoded_text_from_decode
						assert encoded_pair == encoded_pair_from_decode




	def 						UpperCAmelCase_   (				self    :       Optional[int]     ) ->			List[str]:
						__SCREAMING_SNAKE_CASE		     =       self.get_tokenizer()

						__SCREAMING_SNAKE_CASE		     =       "Encode this sequence."
						__SCREAMING_SNAKE_CASE		     =       tokenizer.byte_encoder[" ".encode("utf-8"     )[0]]

						# Testing encoder arguments
						__SCREAMING_SNAKE_CASE		     =       tokenizer.encode(SCREAMING_SNAKE_CASE_    ,    add_special_tokens=SCREAMING_SNAKE_CASE_    ,    add_prefix_space=SCREAMING_SNAKE_CASE_     )
						__SCREAMING_SNAKE_CASE		     =       tokenizer.convert_ids_to_tokens(encoded[0]     )[0]
						self.assertNotEqual(SCREAMING_SNAKE_CASE_    ,    SCREAMING_SNAKE_CASE_     )

						__SCREAMING_SNAKE_CASE		     =       tokenizer.encode(SCREAMING_SNAKE_CASE_    ,    add_special_tokens=SCREAMING_SNAKE_CASE_    ,    add_prefix_space=SCREAMING_SNAKE_CASE_     )
						__SCREAMING_SNAKE_CASE		     =       tokenizer.convert_ids_to_tokens(encoded[0]     )[0]
						self.assertEqual(SCREAMING_SNAKE_CASE_    ,    SCREAMING_SNAKE_CASE_     )

						tokenizer.add_special_tokens({"bos_token": "<s>"}     )
						__SCREAMING_SNAKE_CASE		     =       tokenizer.encode(SCREAMING_SNAKE_CASE_    ,    add_special_tokens=SCREAMING_SNAKE_CASE_     )
						__SCREAMING_SNAKE_CASE		     =       tokenizer.convert_ids_to_tokens(encoded[1]     )[0]
						self.assertNotEqual(SCREAMING_SNAKE_CASE_    ,    SCREAMING_SNAKE_CASE_     )

						# Testing spaces after special tokens
						__SCREAMING_SNAKE_CASE		     =       "<mask>"
						tokenizer.add_special_tokens(
						    {"mask_token": AddedToken(SCREAMING_SNAKE_CASE_    ,    lstrip=SCREAMING_SNAKE_CASE_    ,    rstrip=SCREAMING_SNAKE_CASE_     )}     )  # mask token has a left space
						__SCREAMING_SNAKE_CASE		     =       tokenizer.convert_tokens_to_ids(SCREAMING_SNAKE_CASE_     )

						__SCREAMING_SNAKE_CASE		     =       "Encode <mask> sequence"
						__SCREAMING_SNAKE_CASE		     =       "Encode <mask>sequence"

						__SCREAMING_SNAKE_CASE		     =       tokenizer.encode(SCREAMING_SNAKE_CASE_     )
						__SCREAMING_SNAKE_CASE		     =       encoded.index(SCREAMING_SNAKE_CASE_     )
						__SCREAMING_SNAKE_CASE		     =       tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1]     )[0]
						self.assertEqual(SCREAMING_SNAKE_CASE_    ,    SCREAMING_SNAKE_CASE_     )

						__SCREAMING_SNAKE_CASE		     =       tokenizer.encode(SCREAMING_SNAKE_CASE_     )
						__SCREAMING_SNAKE_CASE		     =       encoded.index(SCREAMING_SNAKE_CASE_     )
						__SCREAMING_SNAKE_CASE		     =       tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1]     )[0]
						self.assertNotEqual(SCREAMING_SNAKE_CASE_    ,    SCREAMING_SNAKE_CASE_     )




	def 						UpperCAmelCase_   (				self    :       Optional[int]     ) ->			Optional[Any]:
						pass




	def 						UpperCAmelCase_   (				self    :       List[str]     ) ->			Dict:
						for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
											with self.subTest(F"""{tokenizer.__class__.__name__} ({pretrained_name})"""     ):
																__SCREAMING_SNAKE_CASE		     =       self.rust_tokenizer_class.from_pretrained(SCREAMING_SNAKE_CASE_    ,    **SCREAMING_SNAKE_CASE_     )
																__SCREAMING_SNAKE_CASE		     =       self.tokenizer_class.from_pretrained(SCREAMING_SNAKE_CASE_    ,    **SCREAMING_SNAKE_CASE_     )
																__SCREAMING_SNAKE_CASE		     =       "A, <mask> AllenNLP sentence."
																__SCREAMING_SNAKE_CASE		     =       tokenizer_r.encode_plus(SCREAMING_SNAKE_CASE_    ,    add_special_tokens=SCREAMING_SNAKE_CASE_    ,    return_token_type_ids=SCREAMING_SNAKE_CASE_     )
																__SCREAMING_SNAKE_CASE		     =       tokenizer_p.encode_plus(SCREAMING_SNAKE_CASE_    ,    add_special_tokens=SCREAMING_SNAKE_CASE_    ,    return_token_type_ids=SCREAMING_SNAKE_CASE_     )

																# token_type_ids should put 0 everywhere
																self.assertEqual(sum(tokens_r["token_type_ids"]     )    ,    sum(tokens_p["token_type_ids"]     )     )

																# attention_mask should put 1 everywhere, so sum over length should be 1
																self.assertEqual(
																    sum(tokens_r["attention_mask"]     ) / len(tokens_r["attention_mask"]     )    ,    sum(tokens_p["attention_mask"]     ) / len(tokens_p["attention_mask"]     )    ,    )

																__SCREAMING_SNAKE_CASE		     =       tokenizer_r.convert_ids_to_tokens(tokens_r["input_ids"]     )
																__SCREAMING_SNAKE_CASE		     =       tokenizer_p.convert_ids_to_tokens(tokens_p["input_ids"]     )

																# Rust correctly handles the space before the mask while python doesnt
																self.assertSequenceEqual(tokens_p["input_ids"]    ,    [0, 2_5_0, 6, 5_0_2_6_4, 3_8_2_3, 4_8_7, 2_1_9_9_2, 3_6_4_5, 4, 2]     )
																self.assertSequenceEqual(tokens_r["input_ids"]    ,    [0, 2_5_0, 6, 5_0_2_6_4, 3_8_2_3, 4_8_7, 2_1_9_9_2, 3_6_4_5, 4, 2]     )

																self.assertSequenceEqual(
																    SCREAMING_SNAKE_CASE_    ,    ["<s>", "A", ",", "<mask>", "ĠAllen", "N", "LP", "Ġsentence", ".", "</s>"]     )
																self.assertSequenceEqual(
																    SCREAMING_SNAKE_CASE_    ,    ["<s>", "A", ",", "<mask>", "ĠAllen", "N", "LP", "Ġsentence", ".", "</s>"]     )




	def 						UpperCAmelCase_   (				self    :       str     ) ->			List[Any]:
						for trim_offsets, add_prefix_space in itertools.product([True, False]    ,    repeat=2     ):
											__SCREAMING_SNAKE_CASE		     =       self.rust_tokenizer_class.from_pretrained(
											    self.tmpdirname    ,    use_fast=SCREAMING_SNAKE_CASE_    ,    add_prefix_space=SCREAMING_SNAKE_CASE_    ,    trim_offsets=SCREAMING_SNAKE_CASE_     )

											__SCREAMING_SNAKE_CASE		     =       json.loads(tokenizer_r.backend_tokenizer.pre_tokenizer.__getstate__()     )
											__SCREAMING_SNAKE_CASE		     =       json.loads(tokenizer_r.backend_tokenizer.post_processor.__getstate__()     )

											self.assertEqual(pre_tokenizer_state["add_prefix_space"]    ,    SCREAMING_SNAKE_CASE_     )

											self.assertEqual(post_processor_state["add_prefix_space"]    ,    SCREAMING_SNAKE_CASE_     )
											self.assertEqual(post_processor_state["trim_offsets"]    ,    SCREAMING_SNAKE_CASE_     )




	def 						UpperCAmelCase_   (				self    :       List[Any]     ) ->			str:
						# Test which aims to verify that the offsets are well adapted to the argument `add_prefix_space` and
						# `trim_offsets`
						for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
											with self.subTest(F"""{tokenizer.__class__.__name__} ({pretrained_name})"""     ):
																__SCREAMING_SNAKE_CASE		     =       "hello"  # `hello` is a token in the vocabulary of `pretrained_name`
																__SCREAMING_SNAKE_CASE		     =       F"""{text_of_1_token} {text_of_1_token}"""

																__SCREAMING_SNAKE_CASE		     =       self.rust_tokenizer_class.from_pretrained(
																    SCREAMING_SNAKE_CASE_    ,    use_fast=SCREAMING_SNAKE_CASE_    ,    add_prefix_space=SCREAMING_SNAKE_CASE_    ,    trim_offsets=SCREAMING_SNAKE_CASE_     )
																__SCREAMING_SNAKE_CASE		     =       tokenizer_r(SCREAMING_SNAKE_CASE_    ,    return_offsets_mapping=SCREAMING_SNAKE_CASE_    ,    add_special_tokens=SCREAMING_SNAKE_CASE_     )
																self.assertEqual(encoding.offset_mapping[0]    ,    (0, len(SCREAMING_SNAKE_CASE_     ))     )
																self.assertEqual(
																    encoding.offset_mapping[1]    ,    (len(SCREAMING_SNAKE_CASE_     ) + 1, len(SCREAMING_SNAKE_CASE_     ) + 1 + len(SCREAMING_SNAKE_CASE_     ))    ,    )

																__SCREAMING_SNAKE_CASE		     =       self.rust_tokenizer_class.from_pretrained(
																    SCREAMING_SNAKE_CASE_    ,    use_fast=SCREAMING_SNAKE_CASE_    ,    add_prefix_space=SCREAMING_SNAKE_CASE_    ,    trim_offsets=SCREAMING_SNAKE_CASE_     )
																__SCREAMING_SNAKE_CASE		     =       tokenizer_r(SCREAMING_SNAKE_CASE_    ,    return_offsets_mapping=SCREAMING_SNAKE_CASE_    ,    add_special_tokens=SCREAMING_SNAKE_CASE_     )
																self.assertEqual(encoding.offset_mapping[0]    ,    (0, len(SCREAMING_SNAKE_CASE_     ))     )
																self.assertEqual(
																    encoding.offset_mapping[1]    ,    (len(SCREAMING_SNAKE_CASE_     ) + 1, len(SCREAMING_SNAKE_CASE_     ) + 1 + len(SCREAMING_SNAKE_CASE_     ))    ,    )

																__SCREAMING_SNAKE_CASE		     =       self.rust_tokenizer_class.from_pretrained(
																    SCREAMING_SNAKE_CASE_    ,    use_fast=SCREAMING_SNAKE_CASE_    ,    add_prefix_space=SCREAMING_SNAKE_CASE_    ,    trim_offsets=SCREAMING_SNAKE_CASE_     )
																__SCREAMING_SNAKE_CASE		     =       tokenizer_r(SCREAMING_SNAKE_CASE_    ,    return_offsets_mapping=SCREAMING_SNAKE_CASE_    ,    add_special_tokens=SCREAMING_SNAKE_CASE_     )
																self.assertEqual(encoding.offset_mapping[0]    ,    (0, len(SCREAMING_SNAKE_CASE_     ))     )
																self.assertEqual(
																    encoding.offset_mapping[1]    ,    (len(SCREAMING_SNAKE_CASE_     ), len(SCREAMING_SNAKE_CASE_     ) + 1 + len(SCREAMING_SNAKE_CASE_     ))    ,    )

																__SCREAMING_SNAKE_CASE		     =       self.rust_tokenizer_class.from_pretrained(
																    SCREAMING_SNAKE_CASE_    ,    use_fast=SCREAMING_SNAKE_CASE_    ,    add_prefix_space=SCREAMING_SNAKE_CASE_    ,    trim_offsets=SCREAMING_SNAKE_CASE_     )
																__SCREAMING_SNAKE_CASE		     =       tokenizer_r(SCREAMING_SNAKE_CASE_    ,    return_offsets_mapping=SCREAMING_SNAKE_CASE_    ,    add_special_tokens=SCREAMING_SNAKE_CASE_     )
																self.assertEqual(encoding.offset_mapping[0]    ,    (0, len(SCREAMING_SNAKE_CASE_     ))     )
																self.assertEqual(
																    encoding.offset_mapping[1]    ,    (len(SCREAMING_SNAKE_CASE_     ), len(SCREAMING_SNAKE_CASE_     ) + 1 + len(SCREAMING_SNAKE_CASE_     ))    ,    )

																__SCREAMING_SNAKE_CASE		     =       F""" {text}"""

																# tokenizer_r = self.rust_tokenizer_class.from_pretrained(
																#     pretrained_name, use_fast=True, add_prefix_space=True, trim_offsets=True
																# )
																# encoding = tokenizer_r(text, return_offsets_mapping=True, add_special_tokens=False)
																# self.assertEqual(encoding.offset_mapping[0], (1, 1 + len(text_of_1_token)))
																# self.assertEqual(
																#     encoding.offset_mapping[1],
																#     (1 + len(text_of_1_token) + 1, 1 + len(text_of_1_token) + 1 + len(text_of_1_token)),
																# )

																__SCREAMING_SNAKE_CASE		     =       self.rust_tokenizer_class.from_pretrained(
																    SCREAMING_SNAKE_CASE_    ,    use_fast=SCREAMING_SNAKE_CASE_    ,    add_prefix_space=SCREAMING_SNAKE_CASE_    ,    trim_offsets=SCREAMING_SNAKE_CASE_     )
																__SCREAMING_SNAKE_CASE		     =       tokenizer_r(SCREAMING_SNAKE_CASE_    ,    return_offsets_mapping=SCREAMING_SNAKE_CASE_    ,    add_special_tokens=SCREAMING_SNAKE_CASE_     )
																self.assertEqual(encoding.offset_mapping[0]    ,    (1, 1 + len(SCREAMING_SNAKE_CASE_     ))     )
																self.assertEqual(
																    encoding.offset_mapping[1]    ,    (1 + len(SCREAMING_SNAKE_CASE_     ) + 1, 1 + len(SCREAMING_SNAKE_CASE_     ) + 1 + len(SCREAMING_SNAKE_CASE_     ))    ,    )

																__SCREAMING_SNAKE_CASE		     =       self.rust_tokenizer_class.from_pretrained(
																    SCREAMING_SNAKE_CASE_    ,    use_fast=SCREAMING_SNAKE_CASE_    ,    add_prefix_space=SCREAMING_SNAKE_CASE_    ,    trim_offsets=SCREAMING_SNAKE_CASE_     )
																__SCREAMING_SNAKE_CASE		     =       tokenizer_r(SCREAMING_SNAKE_CASE_    ,    return_offsets_mapping=SCREAMING_SNAKE_CASE_    ,    add_special_tokens=SCREAMING_SNAKE_CASE_     )
																self.assertEqual(encoding.offset_mapping[0]    ,    (0, 1 + len(SCREAMING_SNAKE_CASE_     ))     )
																self.assertEqual(
																    encoding.offset_mapping[1]    ,    (1 + len(SCREAMING_SNAKE_CASE_     ), 1 + len(SCREAMING_SNAKE_CASE_     ) + 1 + len(SCREAMING_SNAKE_CASE_     ))    ,    )

																__SCREAMING_SNAKE_CASE		     =       self.rust_tokenizer_class.from_pretrained(
																    SCREAMING_SNAKE_CASE_    ,    use_fast=SCREAMING_SNAKE_CASE_    ,    add_prefix_space=SCREAMING_SNAKE_CASE_    ,    trim_offsets=SCREAMING_SNAKE_CASE_     )
																__SCREAMING_SNAKE_CASE		     =       tokenizer_r(SCREAMING_SNAKE_CASE_    ,    return_offsets_mapping=SCREAMING_SNAKE_CASE_    ,    add_special_tokens=SCREAMING_SNAKE_CASE_     )
																self.assertEqual(encoding.offset_mapping[0]    ,    (0, 1 + len(SCREAMING_SNAKE_CASE_     ))     )
																self.assertEqual(
																    encoding.offset_mapping[1]    ,    (1 + len(SCREAMING_SNAKE_CASE_     ), 1 + len(SCREAMING_SNAKE_CASE_     ) + 1 + len(SCREAMING_SNAKE_CASE_     ))    ,    )




"""simple docstring"""







from __future__ import annotations

import math




class 				UpperCamelCase_			:

	"""simple docstring"""





	def __init__(				self    :       Union[str, Any]    ,    UpperCAmelCase__    :       int     ) ->			None:
						__SCREAMING_SNAKE_CASE		     =       size
						# approximate the overall size of segment tree with given value
						__SCREAMING_SNAKE_CASE		     =       [0 for i in range(0    ,    4 * size     )]
						# create array to store lazy update
						__SCREAMING_SNAKE_CASE		     =       [0 for i in range(0    ,    4 * size     )]
						__SCREAMING_SNAKE_CASE		     =       [0 for i in range(0    ,    4 * size     )]  # flag for lazy update




	def 						UpperCAmelCase_   (				self    :       str    ,    UpperCAmelCase__    :       int     ) ->			int:
						return idx * 2




	def 						UpperCAmelCase_   (				self    :       Any    ,    UpperCAmelCase__    :       int     ) ->			int:
						return idx * 2 + 1




	def 						UpperCAmelCase_   (				self    :       List[Any]    ,    UpperCAmelCase__    :       int    ,    UpperCAmelCase__    :       int    ,    UpperCAmelCase__    :       int    ,    UpperCAmelCase__    :       list[int]     ) ->			None:
						if left_element == right_element:
											__SCREAMING_SNAKE_CASE		     =       a[left_element - 1]
						else:
											__SCREAMING_SNAKE_CASE		     =       (left_element + right_element) // 2
											self.build(self.left(UpperCAmelCase__     )    ,    UpperCAmelCase__    ,    UpperCAmelCase__    ,    UpperCAmelCase__     )
											self.build(self.right(UpperCAmelCase__     )    ,    mid + 1    ,    UpperCAmelCase__    ,    UpperCAmelCase__     )
											__SCREAMING_SNAKE_CASE		     =       max(
											    self.segment_tree[self.left(UpperCAmelCase__     )]    ,    self.segment_tree[self.right(UpperCAmelCase__     )]     )




	def 						UpperCAmelCase_   (				self    :       Tuple    ,    UpperCAmelCase__    :       int    ,    UpperCAmelCase__    :       int    ,    UpperCAmelCase__    :       int    ,    UpperCAmelCase__    :       int    ,    UpperCAmelCase__    :       int    ,    UpperCAmelCase__    :       int     ) ->			bool:
						if self.flag[idx] is True:
											__SCREAMING_SNAKE_CASE		     =       self.lazy[idx]
											__SCREAMING_SNAKE_CASE		     =       False
											if left_element != right_element:
																__SCREAMING_SNAKE_CASE		     =       self.lazy[idx]
																__SCREAMING_SNAKE_CASE		     =       self.lazy[idx]
																__SCREAMING_SNAKE_CASE		     =       True
																__SCREAMING_SNAKE_CASE		     =       True

						if right_element < a or left_element > b:
											return True
						if left_element >= a and right_element <= b:
											__SCREAMING_SNAKE_CASE		     =       val
											if left_element != right_element:
																__SCREAMING_SNAKE_CASE		     =       val
																__SCREAMING_SNAKE_CASE		     =       val
																__SCREAMING_SNAKE_CASE		     =       True
																__SCREAMING_SNAKE_CASE		     =       True
											return True
						__SCREAMING_SNAKE_CASE		     =       (left_element + right_element) // 2
						self.update(self.left(UpperCAmelCase__     )    ,    UpperCAmelCase__    ,    UpperCAmelCase__    ,    UpperCAmelCase__    ,    UpperCAmelCase__    ,    UpperCAmelCase__     )
						self.update(self.right(UpperCAmelCase__     )    ,    mid + 1    ,    UpperCAmelCase__    ,    UpperCAmelCase__    ,    UpperCAmelCase__    ,    UpperCAmelCase__     )
						__SCREAMING_SNAKE_CASE		     =       max(
						    self.segment_tree[self.left(UpperCAmelCase__     )]    ,    self.segment_tree[self.right(UpperCAmelCase__     )]     )
						return True




	def 						UpperCAmelCase_   (				self    :       int    ,    UpperCAmelCase__    :       int    ,    UpperCAmelCase__    :       int    ,    UpperCAmelCase__    :       int    ,    UpperCAmelCase__    :       int    ,    UpperCAmelCase__    :       int     ) ->			int | float:
						if self.flag[idx] is True:
											__SCREAMING_SNAKE_CASE		     =       self.lazy[idx]
											__SCREAMING_SNAKE_CASE		     =       False
											if left_element != right_element:
																__SCREAMING_SNAKE_CASE		     =       self.lazy[idx]
																__SCREAMING_SNAKE_CASE		     =       self.lazy[idx]
																__SCREAMING_SNAKE_CASE		     =       True
																__SCREAMING_SNAKE_CASE		     =       True
						if right_element < a or left_element > b:
											return -math.inf
						if left_element >= a and right_element <= b:
											return self.segment_tree[idx]
						__SCREAMING_SNAKE_CASE		     =       (left_element + right_element) // 2
						__SCREAMING_SNAKE_CASE		     =       self.query(self.left(UpperCAmelCase__     )    ,    UpperCAmelCase__    ,    UpperCAmelCase__    ,    UpperCAmelCase__    ,    UpperCAmelCase__     )
						__SCREAMING_SNAKE_CASE		     =       self.query(self.right(UpperCAmelCase__     )    ,    mid + 1    ,    UpperCAmelCase__    ,    UpperCAmelCase__    ,    UpperCAmelCase__     )
						return max(UpperCAmelCase__    ,    UpperCAmelCase__     )




	def __str__(				self    :       int     ) ->			str:
						return str([self.query(1    ,    1    ,    self.size    ,    UpperCAmelCase__    ,    UpperCAmelCase__     ) for i in range(1    ,    self.size + 1     )]     )


if __name__ == "__main__":
		a__       :							Tuple        =  [1, 2, -4, 7, 3, -5, 6, 1_1, -2_0, 9, 1_4, 1_5, 5, 2, -8]
		a__       :							Dict        =  1_5
		a__       :							int        =  SegmentTree(size)
		segt.build(1, 1, size, A)
		print(segt.query(1, 1, size, 4, 6))
		print(segt.query(1, 1, size, 7, 1_1))
		print(segt.query(1, 1, size, 7, 1_2))
		segt.update(1, 1, size, 1, 3, 1_1_1)
		print(segt.query(1, 1, size, 1, 1_5))
		segt.update(1, 1, size, 7, 8, 2_3_5)
		print(segt)
