[DOC] Fix numpy op doc

python/mxnet/_numpy_op_doc.py

@@ -748,3 +748,72 @@ def _np_moveaxis(a, source, destination):
     (5, 4, 3)
     """
     pass
+
+def _np__random_shuffle(x):
+    """
+    Modify a sequence in-place by shuffling its contents.
+
+    This function only shuffles the array along the first axis of a
+    multi-dimensional array. The order of sub-arrays is changed but
+    their contents remain the same.
+
+    Parameters
+    ----------
+    x: ndarray
+        The array or list to be shuffled.
+
+    Returns
+    -------
+    None
+
+    Examples
+    --------
+    >>> arr = np.arange(10)
+    >>> np.random.shuffle(arr)
+    >>> arr
+    array([5., 1., 0., 6., 7., 3., 9., 8., 4., 2.])  # random
+
+    Multi-dimensional arrays are only shuffled along the first axis:
+
+    >>> arr = np.arange(9).reshape((3, 3))
+    >>> np.random.shuffle(arr)
+    >>> arr
+    array([[6., 7., 8.], # random
+           [3., 4., 5.],
+           [0., 1., 2.]])
+    """
+    pass
+
+def _np_broadcast_to(array, shape, out=None):
+    """
+    Broadcast an array to a new shape.
+
+    Parameters
+    ----------
+    array : ndarray
+        The array to broadcast.
+    shape : tuple, optional, default=[]
+        The shape of the desired array.
+    out : ndarray, optional
+        The output ndarray to hold the result.
+
+    Returns
+    -------
+    out : ndarray or list of ndarrays
+
+    Raises
+    ------
+    MXNetError
+        - If the array is not compatible with the new shape according to NumPy's
+        broadcasting rules.
+        - If the shape of the output array is not consistent with the desired shape.
+
+    Examples
+    --------
+    >>> x = np.array([1, 2, 3])
+    >>> np.broadcast_to(x, (3, 3))
+    array([[1., 2., 3.],
+           [1., 2., 3.],
+           [1., 2., 3.]])
+    """
+    pass