code: def cross(a, b, axis=-1):
      r"""
      Returns the cross product of 3-element vectors.
  
      If `a` and `b` are multi-dimensional arrays (i.e., both have a rank greater than 1),
      then the cross-product of each pair of corresponding 3-element vectors is independently computed.
  
      Notes
      -----
      `cross` is an alias for `cross`. It is a standard API in
      https://data-apis.org/array-api/latest/extensions/linear_algebra_functions.html#linalg-cross-x1-x2-axis-1
      instead of an official NumPy operator.
  
      Parameters
      ----------
      a : ndarray
          First input array. Should have a numeric data type.
      b : ndarray
          Second input array. Must have the same shape as a. Should have a numeric data type.
      axis : int
          If defined, the axis of `a` and `b` that defines the vector(s) and cross product(s).
  
          Default: -1.
  
      Returns
      -------
      out : (...) ndarray
          An array containing the cross products.
  
      Examples
      --------
      Vector cross-product.
  
      >>> x = np.array([1., 2., 3.])
      >>> y = np.array([4., 5., 6.])
      >>> np.linalg.cross(x, y)
      array([-3.,  6., -3.])
  
      One vector with dimension 2.
  
      >>> x = np.array([1., 2.])
      >>> y = np.array([4., 5., 6.])
      >>> np.linalg.cross(x, y)
      array([12., -6., -3.])
  
      Equivalently:
  
      >>> x = np.array([1., 2., 0.])
      >>> y = np.array([4., 5., 6.])
      >>>np.linalg.cross(x, y)
      array([12., -6., -3.])
  
      Both vectors with dimension 2.
  
      >>> x = np.array([1., 2.])
      >>> y = np.array([4., 5.])
      >>> np.linalg.cross(x, y)
      array(-3.)
  
      Multiple vector cross-products. Note that the direction of the cross
      product vector is defined by the `right-hand rule`.
  
      >>> x = np.array([[1., 2., 3.], [4., 5., 6.]])
      >>> y = np.array([[4., 5., 6.], [1., 2., 3.]])
      >>> np.linalg.cross(x, y)
      array([[-3.,  6., -3.],
             [ 3., -6.,  3.]])
      """
      # For a given API standard, the axis of axisa, axisb, axisc are equal to the axis
      return _mx_nd_np.cross(
          a, b, axisa=axis, axisb=axis, axisc=axis, axis=axis
      )
  
imports: from functools import reduce
  from ..ndarray import numpy
  from ..util import wrap_data_api_linalg_func
  from .fallback_linalg import *
  from .None import fallback_linalg
label_desc: Use image node_id 6 for calling a global function with example usage: cross(a, b, axis) and returns: _mx_nd_np