code: def logaddexp2(x1, x2, out=None, where=None, **kwargs):
      """
      Logarithm of the sum of exponentiations of the inputs in base-2.
  
      Calculates ``log2(2**x1 + 2**x2)``. This function is useful in machine
      learning when the calculated probabilities of events may be so small as
      to exceed the range of normal floating point numbers.  In such cases
      the base-2 logarithm of the calculated probability can be used instead.
      This function allows adding probabilities stored in such a fashion.
  
      Parameters
      ----------
      x1, x2 : array_like
          Input values.
      out : Tensor, None, or tuple of Tensor and None, optional
          A location into which the result is stored. If provided, it must have
          a shape that the inputs broadcast to. If not provided or `None`,
          a freshly-allocated tensor is returned. A tuple (possible only as a
          keyword argument) must have length equal to the number of outputs.
      where : array_like, optional
          Values of True indicate to calculate the ufunc at that position, values
          of False indicate to leave the value in the output alone.
      **kwargs
  
      Returns
      -------
      result : Tensor
          Base-2 logarithm of ``2**x1 + 2**x2``.
  
      See Also
      --------
      logaddexp: Logarithm of the sum of exponentiations of the inputs.
  
      Examples
      --------
      >>> import mars.tensor as mt
  
      >>> prob1 = mt.log2(1e-50)
      >>> prob2 = mt.log2(2.5e-50)
      >>> prob12 = mt.logaddexp2(prob1, prob2)
      >>> prob1.execute(), prob2.execute(), prob12.execute()
      (-166.09640474436813, -164.77447664948076, -164.28904982231052)
      >>> (2**prob12).execute()
      3.4999999999999914e-50
      """
      op = TensorLogAddExp2(**kwargs)
      return op(x1, x2, out=out, where=where)
  
file_path: mars/mars/tensor/arithmetic/logaddexp2.py
imports: import numpy
  from ...None import opcodes
  from ..utils import infer_dtype
  from .core import TensorBinOp
  from .utils import arithmetic_operand
label_desc: Use image node_id 1 for calling a global function with example usage: logaddexp2(x1, x2, out, where) and returns: op