

from collections.abc import Sequence
from queue import Queue






class _UpperCamelCase							:
   '''simple docstring'''







   def __init__(			self							: int      ,      a							: Union[str, Any]      ,      a							: Optional[int]      ,      a							: Optional[Any]      ,      a							: Optional[Any]=None      ,      a							: Optional[Any]=None	)							->       int:

    """simple docstring"""

    SCREAMING_SNAKE_CASE   :      int				     =       start
    SCREAMING_SNAKE_CASE   :      Optional[Any]				     =       end
    SCREAMING_SNAKE_CASE   :      int				     =       val
    SCREAMING_SNAKE_CASE   :      Dict				     =       (start + end) // 2
    SCREAMING_SNAKE_CASE   :      int				     =       left
    SCREAMING_SNAKE_CASE   :      str				     =       right






   def __repr__(			self							: str	)							->       Union[str, Any]:

    """simple docstring"""

    return F"SegmentTreeNode(start={self.start}, end={self.end}, val={self.val})"






class _UpperCamelCase							:
   '''simple docstring'''







   def __init__(			self							: Dict      ,      a							: Sequence      ,      a							: Dict	)							->       int:

    """simple docstring"""

    SCREAMING_SNAKE_CASE   :      Any				     =       collection
    SCREAMING_SNAKE_CASE   :      Tuple				     =       function
    if self.collection:
     SCREAMING_SNAKE_CASE   :      Optional[Any]				     =       self._build_tree(0      ,      len(snake_case__	) - 1	)
   def 							__UpperCamelCase (			self							: int      ,      a							: Union[str, Any]      ,      a							: Optional[Any]	)							->       List[str]:

    """simple docstring"""

    self._update_tree(self.root      ,      snake_case__      ,      snake_case__	)
   def 							__UpperCamelCase (			self							: Dict      ,      a							: str      ,      a							: int	)							->       Optional[Any]:

    """simple docstring"""

    return self._query_range(self.root      ,      snake_case__      ,      snake_case__	)
   def 							__UpperCamelCase (			self							: Any      ,      a							: Optional[Any]      ,      a							: Optional[Any]	)							->       Optional[int]:

    """simple docstring"""

    if start == end:
     return SegmentTreeNode(snake_case__      ,      snake_case__      ,      self.collection[start]	)
    SCREAMING_SNAKE_CASE   :      Union[str, Any]				     =       (start + end) // 2
    SCREAMING_SNAKE_CASE   :      Optional[Any]				     =       self._build_tree(snake_case__      ,      snake_case__	)
    SCREAMING_SNAKE_CASE   :      str				     =       self._build_tree(mid + 1      ,      snake_case__	)
    return SegmentTreeNode(snake_case__      ,      snake_case__      ,      self.fn(left.val      ,      right.val	)      ,      snake_case__      ,      snake_case__	)
   def 							__UpperCamelCase (			self							: Dict      ,      a							: Dict      ,      a							: Any      ,      a							: List[Any]	)							->       Dict:

    """simple docstring"""

    if node.start == i and node.end == i:
     SCREAMING_SNAKE_CASE   :      Dict				     =       val
     return
    if i <= node.mid:
     self._update_tree(node.left      ,      snake_case__      ,      snake_case__	)
    else:
     self._update_tree(node.right      ,      snake_case__      ,      snake_case__	)
    SCREAMING_SNAKE_CASE   :      Dict				     =       self.fn(node.left.val      ,      node.right.val	)
   def 							__UpperCamelCase (			self							: Union[str, Any]      ,      a							: List[Any]      ,      a							: str      ,      a							: Tuple	)							->       List[Any]:

    """simple docstring"""

    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      ,      snake_case__      ,      snake_case__	)
     else:
      # range in left child tree and right child tree
      return self.fn(
          self._query_range(node.left      ,      snake_case__      ,      node.mid	)      ,      self._query_range(node.right      ,      node.mid + 1      ,      snake_case__	)      ,      )
    else:
     # range in right child tree
     return self._query_range(node.right      ,      snake_case__      ,      snake_case__	)






   def 							__UpperCamelCase (			self							: Dict	)							->       Tuple:

    """simple docstring"""

    if self.root is not None:
     SCREAMING_SNAKE_CASE   :      Optional[int]				     =       Queue()
     queue.put(self.root	)
     while not queue.empty():
      SCREAMING_SNAKE_CASE   :      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)
      a_						     =    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()


from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


a_						     =    {
    'configuration_bridgetower': [
        'BRIDGETOWER_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'BridgeTowerConfig',
        'BridgeTowerTextConfig',
        'BridgeTowerVisionConfig',
    ],
    'processing_bridgetower': ['BridgeTowerProcessor'],
}

try:
			if not is_vision_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			a_						     =    ['BridgeTowerImageProcessor']

try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			a_						     =    [
			    'BRIDGETOWER_PRETRAINED_MODEL_ARCHIVE_LIST',
			    'BridgeTowerForContrastiveLearning',
			    'BridgeTowerForImageAndTextRetrieval',
			    'BridgeTowerForMaskedLM',
			    'BridgeTowerModel',
			    'BridgeTowerPreTrainedModel',
			]


if TYPE_CHECKING:
			from .configuration_bridgetower import (
			    BRIDGETOWER_PRETRAINED_CONFIG_ARCHIVE_MAP,
			    BridgeTowerConfig,
			    BridgeTowerTextConfig,
			    BridgeTowerVisionConfig,
			)
			from .processing_bridgetower import BridgeTowerProcessor

			try:
						if not is_vision_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .image_processing_bridgetower import BridgeTowerImageProcessor

			try:
						if not is_torch_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_bridgetower import (
						    BRIDGETOWER_PRETRAINED_MODEL_ARCHIVE_LIST,
						    BridgeTowerForContrastiveLearning,
						    BridgeTowerForImageAndTextRetrieval,
						    BridgeTowerForMaskedLM,
						    BridgeTowerModel,
						    BridgeTowerPreTrainedModel,
						)


else:
			import sys

			a_						     =    _LazyModule(__name__, globals()['__file__'], _import_structure)