modify code logic and patterns

fix sanity error

python/mxnet/numpy/multiarray.py

@@ -7149,6 +7149,7 @@ def insert(arr, obj, values, axis=None):
     """
     return _mx_nd_np.insert(arr, obj, values, axis=axis)
 
+
 @set_module('mxnet.numpy')
 def nonzero(a):
     """

python/mxnet/symbol/numpy/_symbol.py

@@ -2493,14 +2493,14 @@ def insert(arr, obj, values, axis=None):
 
     Parameters
     ----------
-    arr : ndarray
+    arr : _Symbol
         Input array.
-    obj : int, slice or ndarray of ints
+    obj : int, slice or _Symbol of ints
         Object that defines the index or indices before which `values` is
         inserted.
         Support for multiple insertions when `obj` is a single scalar or a
         sequence with one element (only support int32 and int64 element).
-    values : ndarray
+    values : _Symbol
         Values to insert into `arr`.
         The type of `values` should equal to the type of `arr`.
         `values` should be shaped so that ``arr[...,obj,...] = values``
@@ -2511,7 +2511,7 @@ def insert(arr, obj, values, axis=None):
 
     Returns
     -------
-    out : ndarray
+    out : _Symbol
         A copy of `arr` with `values` inserted.  Note that `insert`
         does not occur in-place: a new array is returned. If
         `axis` is None, `out` is a flattened array.
@@ -2521,49 +2521,6 @@ def insert(arr, obj, values, axis=None):
     Note that for higher dimensional inserts `obj=0` behaves very different
     from `obj=[0]` just like `arr[:,0,:] = values` is different from
     `arr[:,[0],:] = values`.
-
-    Examples
-    --------
-    >>> a = np.array([[1, 1], [2, 2], [3, 3]])
-    >>> a
-    array([[1., 1.],
-           [2., 2.],
-           [3., 3.]])
-    >>> np.insert(a, 1, np.array(5))
-    array([1., 5., 1., 2., 2., 3., 3.])
-    >>> np.insert(a, 1, np.array(5), axis=1)
-    array([[1., 5., 1.],
-           [2., 5., 2.],
-           [3., 5., 3.]])
-
-    Difference between sequence and scalars:
-
-    >>> np.insert(a, np.array([1], dtype=np.int32), np.array([[1],[2],[3]]), axis=1)
-    array([[1., 1., 1.],
-           [2., 2., 2.],
-           [3., 3., 3.]])
-    >>> np.insert(a, 1, np.array([1, 2, 3]), axis=1)
-    array([[1., 1., 1.],
-           [2., 2., 2.],
-           [3., 3., 3.]])
-
-    >>> b = a.flatten()
-    >>> b
-    array([1., 1., 2., 2., 3., 3.])
-    >>> np.insert(b, np.array([2, 2], dtype=np.int64), np.array([5, 6]))
-    array([1., 1., 5., 6., 2., 2., 3., 3.])
-
-    >>> np.insert(b, slice(2, 4), np.array([5, 6]))
-    array([1., 1., 5., 2., 6., 2., 3., 3.])
-
-    >>> np.insert(b, np.array([2, 2], dtype=np.int32), np.array([7.13, False]))
-    array([1.  , 1.  , 7.13, 0.  , 2.  , 2.  , 3.  , 3.  ])
-
-    >>> x = np.arange(8).reshape(2, 4)
-    >>> idx = np.array([1, 3], dtype=np.int32)
-    >>> np.insert(x, idx, np.array([999]), axis=1)
-    array([[  0., 999.,   1.,   2., 999.,   3.],
-           [  4., 999.,   5.,   6., 999.,   7.]])
     """
     if not isinstance(arr, ndarray): # pylint: disable= undefined-variable
         raise TypeError("'arr' can not support type {}".format(str(type(arr))))