code: def log2(x, out=None, where=None, **kwargs):
      """
      Base-2 logarithm of `x`.
  
      Parameters
      ----------
      x : 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
      -------
      y : Tensor
          Base-2 logarithm of `x`.
  
      See Also
      --------
      log, log10, log1p
  
      Logarithm is a multivalued function: for each `x` there is an infinite
      number of `z` such that `2**z = x`. The convention is to return the `z`
      whose imaginary part lies in `[-pi, pi]`.
  
      For real-valued input data types, `log2` always returns real output.
      For each value that cannot be expressed as a real number or infinity,
      it yields ``nan`` and sets the `invalid` floating point error flag.
  
      For complex-valued input, `log2` is a complex analytical function that
      has a branch cut `[-inf, 0]` and is continuous from above on it. `log2`
      handles the floating-point negative zero as an infinitesimal negative
      number, conforming to the C99 standard.
  
      Examples
      --------
      >>> import mars.tensor as mt
  
      >>> x = mt.array([0, 1, 2, 2**4])
      >>> mt.log2(x).execute()
      array([-Inf,   0.,   1.,   4.])
  
      >>> xi = mt.array([0+1.j, 1, 2+0.j, 4.j])
      >>> mt.log2(xi).execute()
      array([ 0.+2.26618007j,  0.+0.j        ,  1.+0.j        ,  2.+2.26618007j])
      """
      op = TensorLog2(**kwargs)
      return op(x, out=out, where=where)
  
file_path: mars/mars/tensor/arithmetic/log2.py
imports: import numpy
  from ...None import opcodes
  from ..utils import infer_dtype
  from .core import TensorUnaryOp
  from .utils import arithmetic_operand
label_desc: Use image node_id 1 for calling a global function with example usage: log2(x, out, where) and returns: op