code: def hypot(x1, x2, out=None, where=None, **kwargs):
      """
      Given the "legs" of a right triangle, return its hypotenuse.
  
      Equivalent to ``sqrt(x1**2 + x2**2)``, element-wise.  If `x1` or
      `x2` is scalar_like (i.e., unambiguously cast-able to a scalar type),
      it is broadcast for use with each element of the other argument.
      (See Examples)
  
      Parameters
      ----------
      x1, x2 : array_like
          Leg of the triangle(s).
      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 array 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
      -------
      z : Tensor
          The hypotenuse of the triangle(s).
  
      Examples
      --------
      >>> import mars.tensor as mt
  
      >>> mt.hypot(3*mt.ones((3, 3)), 4*mt.ones((3, 3))).execute()
      array([[ 5.,  5.,  5.],
             [ 5.,  5.,  5.],
             [ 5.,  5.,  5.]])
  
      Example showing broadcast of scalar_like argument:
  
      >>> mt.hypot(3*mt.ones((3, 3)), [4]).execute()
      array([[ 5.,  5.,  5.],
             [ 5.,  5.,  5.],
             [ 5.,  5.,  5.]])
      """
      op = TensorHypot(**kwargs)
      return op(x1, x2, out=out, where=where)
  
file_path: mars/mars/tensor/arithmetic/hypot.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: hypot(x1, x2, out, where) and returns: op