code: def spacing(x, out=None, where=None, **kwargs):
      """
      Return the distance between x and the nearest adjacent number.
  
      Parameters
      ----------
      x : array_like
          Values to find the spacing of.
      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
      -------
      out : array_like
          The spacing of values of `x1`.
  
      Notes
      -----
      It can be considered as a generalization of EPS:
      ``spacing(mt.float64(1)) == mt.finfo(mt.float64).eps``, and there
      should not be any representable number between ``x + spacing(x)`` and
      x for any finite x.
  
      Spacing of +- inf and NaN is NaN.
  
      Examples
      --------
      >>> import mars.tensor as mt
  
      >>> (mt.spacing(1) == mt.finfo(mt.float64).eps).execute()
      True
      """
      op = TensorSpacing(**kwargs)
      return op(x, out=out, where=where)
  
file_path: mars/mars/tensor/arithmetic/spacing.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: spacing(x, out, where) and returns: op