[GitHub] [incubator-mxnet] hanke580 commented on a change in pull request #16977: [Numpy]add row_stack (= vstack)

[GitBox <gi...@apache.org>]

hanke580 commented on a change in pull request #16977: [Numpy]add row_stack (= vstack)
URL: https://github.com/apache/incubator-mxnet/pull/16977#discussion_r361060594
 
 

 ##########
 File path: python/mxnet/numpy/multiarray.py
 ##########
 @@ -5030,6 +5030,49 @@ def vstack(arrays, out=None):
     """
     return _mx_nd_np.vstack(arrays)
 
+@set_module('mxnet.numpy')
+def row_stack(arrays, out=None):
+    r"""Stack arrays in sequence vertically (row wise).
+
+    This is equivalent to concatenation along the first axis after 1-D arrays
+    of shape `(N,)` have been reshaped to `(1,N)`. Rebuilds arrays divided by
+    `vsplit`.
+
+    This function makes most sense for arrays with up to 3 dimensions. For
+    instance, for pixel-data with a height (first axis), width (second axis),
+    and r/g/b channels (third axis). The functions `concatenate` and `stack`
+    provide more general stacking and concatenation operations.
+
+    Parameters
+    ----------
+    tup : sequence of ndarrays
+        The arrays must have the same shape along all but the first axis.
+        1-D arrays must have the same length.
+
+    Returns
+    -------
+    stacked : ndarray
+        The array formed by stacking the given arrays, will be at least 2-D.
+
+    Examples
+    --------
+    >>> a = np.array([1, 2, 3])
+    >>> b = np.array([2, 3, 4])
+    >>> np.vstack((a, b))
+    array([[1., 2., 3.],
+           [2., 3., 4.]])
+
+    >>> a = np.array([[1], [2], [3]])
+    >>> b = np.array([[2], [3], [4]])
+    >>> np.vstack((a, b))
+    array([[1.],
+           [2.],
+           [3.],
+           [2.],
+           [3.],
+           [4.]])
+    """
+    return _mx_nd_np.row_stack(arrays)
 
 Review comment:
   Fixed, thanks

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