code: def copy(a, order="K"):
      """
      Return a tensor copy of the given object.
  
      Parameters
      ----------
      a : array_like
          Input data.
      order : {'C', 'F', 'A', 'K'}, optional
          Controls the memory layout of the copy. 'C' means C-order,
          'F' means F-order, 'A' means 'F' if `a` is Fortran contiguous,
          'C' otherwise. 'K' means match the layout of `a` as closely
          as possible. (Note that this function and :meth:`ndarray.copy` are very
          similar, but have different default values for their order=
          arguments.)
  
      Returns
      -------
      arr : Tensor
          Tensor interpretation of `a`.
  
      Notes
      -----
      This is equivalent to:
  
      >>> import mars.tensor as mt
  
      >>> mt.array(a, copy=True)  #doctest: +SKIP
  
      Examples
      --------
      Create an array x, with a reference y and a copy z:
  
      >>> x = mt.array([1, 2, 3])
      >>> y = x
      >>> z = mt.copy(x)
  
      Note that, when we modify x, y changes, but not z:
  
      >>> x[0] = 10
      >>> (x[0] == y[0]).execute()
      True
      >>> (x[0] == z[0]).execute()
      False
  
      """
      from ..datasource import array
  
      return array(a, order=order, copy=True)
  
label_desc: Use image node_id 1 for calling a global function with example usage: copy(a, order) and returns: array