



'''simple docstring'''
from collections.abc import Sequence
from queue import Queue


class 	SCREAMING_SNAKE_CASE__					:
	"""simple docstring"""


	def __init__(		self       , A       , A       , A       , A=None       , A=None      )			->				Any:
				A:   str								= start
				A:   Tuple								= end
				A:   Tuple								= val
				A:   Optional[int]								= (start + end) // 2
				A:   Optional[Any]								= left
				A:   int								= right





	def __repr__(		self      )			->				Optional[int]:
				return f'SegmentTreeNode(start={self.start}, end={self.end}, val={self.val})'







class 	SCREAMING_SNAKE_CASE__					:
	"""simple docstring"""


	def __init__(		self       , A       , A      )			->				Optional[Any]:
				A:   List[str]								= collection
				A:   str								= function
				if self.collection:
							A:   Dict								= self._build_tree(0       , len(UpperCamelCase__      ) - 1      )


	def   a__			(		self       , A       , A      )			->				int:
				self._update_tree(self.root       , UpperCamelCase__       , UpperCamelCase__      )


	def   a__			(		self       , A       , A      )			->				Union[str, Any]:
				return self._query_range(self.root       , UpperCamelCase__       , UpperCamelCase__      )


	def   a__			(		self       , A       , A      )			->				str:
				if start == end:
							return SegmentTreeNode(UpperCamelCase__       , UpperCamelCase__       , self.collection[start]      )
				A:   int								= (start + end) // 2
				A:   Union[str, Any]								= self._build_tree(UpperCamelCase__       , UpperCamelCase__      )
				A:   Dict								= self._build_tree(mid + 1       , UpperCamelCase__      )
				return SegmentTreeNode(UpperCamelCase__       , UpperCamelCase__       , self.fn(left.val       , right.val      )       , UpperCamelCase__       , UpperCamelCase__      )


	def   a__			(		self       , A       , A       , A      )			->				Tuple:
				if node.start == i and node.end == i:
							A:   int								= val
							return
				if i <= node.mid:
							self._update_tree(node.left       , UpperCamelCase__       , UpperCamelCase__      )
				else:
							self._update_tree(node.right       , UpperCamelCase__       , UpperCamelCase__      )
				A:   int								= self.fn(node.left.val       , node.right.val      )


	def   a__			(		self       , A       , A       , A      )			->				Tuple:
				if node.start == i and node.end == j:
							return node.val

				if i <= node.mid:
							if j <= node.mid:
										# range in left child tree
										return self._query_range(node.left       , UpperCamelCase__       , UpperCamelCase__      )
							else:
										# range in left child tree and right child tree
										return self.fn(
										    self._query_range(node.left       , UpperCamelCase__       , node.mid      )       , self._query_range(node.right       , node.mid + 1       , UpperCamelCase__      )       , )
				else:
							# range in right child tree
							return self._query_range(node.right       , UpperCamelCase__       , UpperCamelCase__      )





	def   a__			(		self      )			->				List[Any]:
				if self.root is not None:
							A:   List[str]								= Queue()
							queue.put(self.root      )
							while not queue.empty():
										A:   Optional[Any]								= queue.get()
										yield node

										if node.left is not None:
													queue.put(node.left      )

										if node.right is not None:
													queue.put(node.right      )


if __name__ == "__main__":
					import operator

					for fn in [operator.add, max, min]:
										print('*' * 50)
										__SCREAMING_SNAKE_CASE			:   Tuple							   =SegmentTree([2, 1, 5, 3, 4], fn)
										for node in arr.traverse():
															print(node)
										print()

										arr.update(1, 5)
										for node in arr.traverse():
															print(node)
										print()

										print(arr.query_range(3, 4))  # 7
										print(arr.query_range(2, 2))  # 5
										print(arr.query_range(1, 3))  # 13
										print()






'''simple docstring'''






from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


_UpperCAmelCase    :     Optional[Any]         =       logging.get_logger(__name__)

_UpperCAmelCase    :     List[Any]         =       {
    '''andreasmadsen/efficient_mlm_m0.40''': (
        '''https://huggingface.co/andreasmadsen/efficient_mlm_m0.40/resolve/main/config.json'''
    ),
}







class lowercase_       (		_UpperCamelCase			):







   """simple docstring"""

   __lowerCAmelCase         =   "roberta-prelayernorm"
   def __init__(      self      :			Optional[int], UpperCamelCase__      :			List[Any]=5_02_65, UpperCamelCase__      :			int=7_68, UpperCamelCase__      :			str=12, UpperCamelCase__      :			Union[str, Any]=12, UpperCamelCase__      :			Tuple=30_72, UpperCamelCase__      :			Tuple="gelu", UpperCamelCase__      :			List[Any]=0.1, UpperCamelCase__      :			Union[str, Any]=0.1, UpperCamelCase__      :			Any=5_12, UpperCamelCase__      :			Union[str, Any]=2, UpperCamelCase__      :			Optional[Any]=0.02, UpperCamelCase__      :			str=1e-12, UpperCamelCase__      :			str=1, UpperCamelCase__      :			List[str]=0, UpperCamelCase__      :			Optional[int]=2, UpperCamelCase__      :			Optional[Any]="absolute", UpperCamelCase__      :			Optional[Any]=True, UpperCamelCase__      :			List[str]=None, **UpperCamelCase__      :			Any, )  ->			Dict:
        super().__init__(pad_token_id=UpperCamelCase__, bos_token_id=UpperCamelCase__, eos_token_id=UpperCamelCase__, **UpperCamelCase__     )

        _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    		=  use_cache
        _A    		=  classifier_dropout







class lowercase_       (		_UpperCamelCase			):







   """simple docstring"""

   @property
   def 	__UpperCAmelCase   (      self      :			Optional[int]     )  ->			Mapping[str, Mapping[int, str]]:
        if self.task == "multiple-choice":
             _A    		=  {0: 'batch', 1: 'choice', 2: 'sequence'}
        else:
             _A    		=  {0: 'batch', 1: 'sequence'}
        return OrderedDict(
            [
                ('input_ids', dynamic_axis),
                ('attention_mask', dynamic_axis),
            ]     )



