


"""simple docstring"""


from __future__ import annotations

import math



class 			lowerCamelCase__						:







						def __init__(							self   :    Optional[int]			,			_lowercase   :    int		):
								A					       = size
								# approximate the overall size of segment tree with given value
								A					       = [0 for i in range(0			,			4 * size		)]
								# create array to store lazy update
								A					       = [0 for i in range(0			,			4 * size		)]
								A					       = [0 for i in range(0			,			4 * size		)]  # flag for lazy update







						def __a						(							self   :    Union[str, Any]			,			_lowercase   :    int		):
								return idx * 2







						def __a						(							self   :    Tuple			,			_lowercase   :    int		):
								return idx * 2 + 1







						def __a						(							self   :    Optional[int]			,			_lowercase   :    int			,			_lowercase   :    int			,			_lowercase   :    int			,			_lowercase   :    list[int]		):
								if left_element == right_element:
										A					       = a[left_element - 1]
								else:
										A					       = (left_element + right_element) // 2
										self.build(self.left(_lowercase		)			,			_lowercase			,			_lowercase			,			_lowercase		)
										self.build(self.right(_lowercase		)			,			mid + 1			,			_lowercase			,			_lowercase		)
										A					       = max(
										    self.segment_tree[self.left(_lowercase		)]			,			self.segment_tree[self.right(_lowercase		)]		)







						def __a						(							self   :    List[Any]			,			_lowercase   :    int			,			_lowercase   :    int			,			_lowercase   :    int			,			_lowercase   :    int			,			_lowercase   :    int			,			_lowercase   :    int		):
								if self.flag[idx] is True:
										A					       = self.lazy[idx]
										A					       = False
										if left_element != right_element:
												A					       = self.lazy[idx]
												A					       = self.lazy[idx]
												A					       = True
												A					       = True

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







						def __a						(							self   :    List[Any]			,			_lowercase   :    int			,			_lowercase   :    int			,			_lowercase   :    int			,			_lowercase   :    int			,			_lowercase   :    int		):
								if self.flag[idx] is True:
										A					       = self.lazy[idx]
										A					       = False
										if left_element != right_element:
												A					       = self.lazy[idx]
												A					       = self.lazy[idx]
												A					       = True
												A					       = 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]
								A					       = (left_element + right_element) // 2
								A					       = self.query(self.left(_lowercase		)			,			_lowercase			,			_lowercase			,			_lowercase			,			_lowercase		)
								A					       = self.query(self.right(_lowercase		)			,			mid + 1			,			_lowercase			,			_lowercase			,			_lowercase		)
								return max(_lowercase			,			_lowercase		)







						def __str__(							self   :    Tuple		):
								return str([self.query(1			,			1			,			self.size			,			_lowercase			,			_lowercase		) for i in range(1			,			self.size + 1		)]		)


if __name__ == "__main__":
	UpperCamelCase						:				List[Any]             =      [1, 2, -4, 7, 3, -5, 6, 11, -20, 9, 14, 15, 5, 2, -8]
	UpperCamelCase						:				str             =      15
	UpperCamelCase						:				int             =      SegmentTree(size)
	segt.build(1, 1, size, A)
	print(segt.query(1, 1, size, 4, 6))
	print(segt.query(1, 1, size, 7, 11))
	print(segt.query(1, 1, size, 7, 12))
	segt.update(1, 1, size, 1, 3, 111)
	print(segt.query(1, 1, size, 1, 15))
	segt.update(1, 1, size, 7, 8, 235)
	print(segt)









"""simple docstring"""


from ...configuration_utils import PretrainedConfig
from ...utils import logging


UpperCamelCase						:				Tuple             =      logging.get_logger(__name__)

UpperCamelCase						:				Union[str, Any]             =      {
    "SCUT-DLVCLab/lilt-roberta-en-base": (
        "https://huggingface.co/SCUT-DLVCLab/lilt-roberta-en-base/resolve/main/config.json"
    ),
}



class 			lowerCamelCase__						(   UpperCAmelCase_			):
						lowerCAmelCase       =     """lilt"""







						def __init__(							self   :    Optional[Any]			,			_lowercase   :    Dict=30_522			,			_lowercase   :    Any=768			,			_lowercase   :    Union[str, Any]=12			,			_lowercase   :    List[str]=12			,			_lowercase   :    str=3_072			,			_lowercase   :    int="gelu"			,			_lowercase   :    Union[str, Any]=0.1			,			_lowercase   :    Dict=0.1			,			_lowercase   :    Optional[Any]=512			,			_lowercase   :    Optional[Any]=2			,			_lowercase   :    Tuple=0.0_2			,			_lowercase   :    int=1e-12			,			_lowercase   :    Any=0			,			_lowercase   :    List[str]="absolute"			,			_lowercase   :    Dict=None			,			_lowercase   :    Optional[int]=4			,			_lowercase   :    Optional[int]=1_024			,			**_lowercase   :    Union[str, Any]			,			):
								super().__init__(pad_token_id=_lowercase			,			**_lowercase		)

								A					       = vocab_size
								A					       = hidden_size
								A					       = num_hidden_layers
								A					       = num_attention_heads
								A					       = hidden_act
								A					       = intermediate_size
								A					       = hidden_dropout_prob
								A					       = attention_probs_dropout_prob
								A					       = max_position_embeddings
								A					       = type_vocab_size
								A					       = initializer_range
								A					       = layer_norm_eps
								A					       = position_embedding_type
								A					       = classifier_dropout
								A					       = channel_shrink_ratio
								A					       = max_ad_position_embeddings





