code: def square(x, out=None, where=None, **kwargs):
      """
      Return the element-wise square of the input.
  
      Parameters
      ----------
      x : array_like
          Input data.
      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
      -------
      out : Tensor
          Element-wise `x*x`, of the same shape and dtype as `x`.
          Returns scalar if `x` is a scalar.
  
      See Also
      --------
      sqrt
      power
  
      Examples
      --------
      >>> import mars.tensor as mt
  
      >>> mt.square([-1j, 1]).execute()
      array([-1.-0.j,  1.+0.j])
      """
      op = TensorSquare(**kwargs)
      return op(x, out=out, where=where)
  
file_path: mars/mars/tensor/arithmetic/square.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: square(x, out, where) and returns: op