code: def logical_or(x1, x2, out=None, where=None, **kwargs):
      """
      Compute the truth value of x1 OR x2 element-wise.
  
      Parameters
      ----------
      x1, x2 : array_like
          Logical OR is applied to the elements of `x1` and `x2`.
          They have to be of the same shape.
      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 or bool
          Boolean result with the same shape as `x1` and `x2` of the logical
          OR operation on elements of `x1` and `x2`.
  
      See Also
      --------
      logical_and, logical_not, logical_xor
      bitwise_or
  
      Examples
      --------
      >>> import mars.tensor as mt
  
      >>> mt.logical_or(True, False).execute()
      True
      >>> mt.logical_or([True, False], [False, False]).execute()
      array([ True, False])
  
      >>> x = mt.arange(5)
      >>> mt.logical_or(x < 1, x > 3).execute()
      array([ True, False, False, False,  True])
      """
      op = TensorOr(**kwargs)
      return op(x1, x2, out=out, where=where)
  
file_path: mars/mars/tensor/arithmetic/logical_or.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: logical_or(x1, x2, out, where) and returns: op