[Numpy] add row_stack (=vstack)

python/mxnet/ndarray/numpy/_op.py

@@ -35,13 +35,13 @@
            'log1p', 'rint', 'radians', 'reciprocal', 'square', 'negative', 'fix', 'ceil', 'floor', 'histogram',
            'trunc', 'logical_not', 'arcsinh', 'arccosh', 'arctanh', 'argsort', 'tensordot', 'eye', 'linspace',
            'logspace', 'expand_dims', 'tile', 'arange', 'array_split', 'split', 'vsplit', 'concatenate', 'append',
-           'stack', 'vstack', 'column_stack', 'dstack', 'average', 'mean', 'maximum', 'minimum', 'swapaxes', 'clip',
-           'argmax', 'argmin', 'std', 'var', 'indices', 'copysign', 'ravel', 'unravel_index', 'hanning', 'hamming',
-           'blackman', 'flip', 'flipud', 'fliplr', 'around', 'round', 'hypot', 'bitwise_xor', 'bitwise_or',
-           'rad2deg', 'deg2rad', 'unique', 'lcm', 'tril', 'identity', 'take', 'ldexp', 'vdot', 'inner', 'outer',
-           'equal', 'not_equal', 'greater', 'less', 'greater_equal', 'less_equal', 'hsplit', 'rot90', 'einsum',
-           'true_divide', 'nonzero', 'shares_memory', 'may_share_memory', 'diff', 'resize', 'nan_to_num', 'where',
-           'bincount']
+           'stack', 'vstack', 'row_stack', 'column_stack', 'dstack', 'average', 'mean', 'maximum', 'minimum',
+           'swapaxes', 'clip', 'argmax', 'argmin', 'std', 'var', 'indices', 'copysign', 'ravel', 'unravel_index',
+           'hanning', 'hamming', 'blackman', 'flip', 'flipud', 'fliplr', 'around', 'round', 'hypot', 'bitwise_xor',
+           'bitwise_or', 'rad2deg', 'deg2rad', 'unique', 'lcm', 'tril', 'identity', 'take', 'ldexp', 'vdot',
+           'inner', 'outer', 'equal', 'not_equal', 'greater', 'less', 'greater_equal', 'less_equal', 'hsplit',
+           'rot90', 'einsum', 'true_divide', 'nonzero', 'shares_memory', 'may_share_memory', 'diff', 'resize',
+           'nan_to_num', 'where', 'bincount']
 
 
 @set_module('mxnet.ndarray.numpy')
@@ -3715,6 +3715,51 @@ def get_list(arrays):
     return _npi.vstack(*arrays)
 
 
+@set_module('mxnet.ndarray.numpy')
+def row_stack(arrays):
+    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.]])
+    """
+    def get_list(arrays):
+        if not hasattr(arrays, '__getitem__') and hasattr(arrays, '__iter__'):
+            raise ValueError("expected iterable for arrays but got {}".format(type(arrays)))
+        return [arr for arr in arrays]
+
+    arrays = get_list(arrays)
+    return _npi.vstack(*arrays)
+
+
 @set_module('mxnet.ndarray.numpy')
 def column_stack(tup):
     """

python/mxnet/numpy/multiarray.py

@@ -54,12 +54,12 @@
            'degrees', 'log2', 'log1p', 'rint', 'radians', 'reciprocal', 'square', 'negative', 'histogram',
            'fix', 'ceil', 'floor', 'trunc', 'logical_not', 'arcsinh', 'arccosh', 'arctanh', 'append', 'argsort',
            'tensordot', 'eye', 'linspace', 'logspace', 'expand_dims', 'tile', 'arange', 'array_split',
-           'split', 'vsplit', 'concatenate', 'stack', 'vstack', 'column_stack', 'dstack', 'average', 'mean',
-           'maximum', 'minimum', 'swapaxes', 'clip', 'argmax', 'argmin', 'std', 'var', 'indices', 'copysign',
-           'ravel', 'unravel_index', 'hanning', 'hamming', 'blackman', 'flip', 'flipud', 'fliplr', 'around',
-           'round', 'arctan2', 'hypot', 'bitwise_xor', 'bitwise_or', 'rad2deg', 'deg2rad', 'unique', 'lcm',
-           'tril', 'identity', 'take', 'ldexp', 'vdot', 'inner', 'outer', 'equal', 'not_equal', 'greater',
-           'less', 'greater_equal', 'less_equal', 'hsplit', 'rot90', 'einsum', 'true_divide', 'nonzero',
+           'split', 'vsplit', 'concatenate', 'stack', 'vstack', 'row_stack', 'column_stack', 'dstack',
+           'average', 'mean', 'maximum', 'minimum', 'swapaxes', 'clip', 'argmax', 'argmin', 'std', 'var',
+           'indices', 'copysign', 'ravel', 'unravel_index', 'hanning', 'hamming', 'blackman', 'flip', 'flipud',
+           'fliplr', 'around', 'round', 'arctan2', 'hypot', 'bitwise_xor', 'bitwise_or', 'rad2deg', 'deg2rad',
+           'unique', 'lcm', 'tril', 'identity', 'take', 'ldexp', 'vdot', 'inner', 'outer', 'equal', 'not_equal',
+           'greater', 'less', 'greater_equal', 'less_equal', 'hsplit', 'rot90', 'einsum', 'true_divide', 'nonzero',
            'shares_memory', 'may_share_memory', 'diff', 'resize', 'nan_to_num', 'where', 'bincount']
 
 # Return code for dispatching indexing function call
@@ -5488,6 +5488,45 @@ def vstack(arrays, out=None):
     return _mx_nd_np.vstack(arrays)
 
 
+@set_module('mxnet.numpy')
+def row_stack(arrays):
+    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)
+
+
 @set_module('mxnet.numpy')
 def column_stack(tup):
     """

python/mxnet/symbol/numpy/_symbol.py

@@ -43,12 +43,13 @@
            'rint', 'radians', 'reciprocal', 'square', 'negative', 'fix', 'ceil', 'floor', 'histogram',
            'trunc', 'logical_not', 'arcsinh', 'arccosh', 'arctanh', 'argsort', 'tensordot', 'eye', 'linspace',
            'logspace', 'expand_dims', 'tile', 'arange', 'array_split', 'split', 'vsplit', 'concatenate', 'append',
-           'stack', 'vstack', 'column_stack', 'dstack', 'average', 'mean', 'maximum', 'minimum', 'swapaxes', 'clip',
-           'argmax', 'argmin', 'std', 'var', 'indices', 'copysign', 'ravel', 'unravel_index', 'hanning', 'hamming',
-           'blackman', 'flip', 'flipud', 'fliplr', 'around', 'round', 'hypot', 'bitwise_xor', 'bitwise_or',
-           'rad2deg', 'deg2rad', 'unique', 'lcm', 'tril', 'identity', 'take', 'ldexp', 'vdot', 'inner', 'outer',
-           'equal', 'not_equal', 'greater', 'less', 'greater_equal', 'less_equal', 'hsplit', 'rot90', 'einsum',
-           'true_divide', 'shares_memory', 'may_share_memory', 'diff', 'resize', 'nan_to_num', 'where', 'bincount']
+           'stack', 'vstack', 'row_stack', 'column_stack', 'dstack', 'average', 'mean', 'maximum', 'minimum',
+           'swapaxes', 'clip', 'argmax', 'argmin', 'std', 'var', 'indices', 'copysign', 'ravel', 'unravel_index',
+           'hanning', 'hamming', 'blackman', 'flip', 'flipud', 'fliplr', 'around', 'round', 'hypot', 'bitwise_xor',
+           'bitwise_or', 'rad2deg', 'deg2rad', 'unique', 'lcm', 'tril', 'identity', 'take', 'ldexp', 'vdot',
+           'inner', 'outer', 'equal', 'not_equal', 'greater', 'less', 'greater_equal', 'less_equal', 'hsplit',
+           'rot90', 'einsum', 'true_divide', 'shares_memory', 'may_share_memory', 'diff', 'resize', 'nan_to_num',
+           'where', 'bincount']
 
 
 @set_module('mxnet.symbol.numpy')
@@ -3684,6 +3685,35 @@ def get_list(arrays):
     return _npi.vstack(*arrays)
 
 
+@set_module('mxnet.symbol.numpy')
+def row_stack(arrays):
+    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 _Symbol
+        The arrays must have the same shape along all but the first axis.
+        1-D arrays must have the same length.
+    Returns
+    -------
+    stacked : _Symbol
+        The array formed by stacking the given arrays, will be at least 2-D.
+    """
+    def get_list(arrays):
+        if not hasattr(arrays, '__getitem__') and hasattr(arrays, '__iter__'):
+            raise ValueError("expected iterable for arrays but got {}".format(type(arrays)))
+        return [arr for arr in arrays]
+
+    arrays = get_list(arrays)
+    return _npi.vstack(*arrays)
+
+
 @set_module('mxnet.symbol.numpy')
 def column_stack(tup):
     """