add op : append / fix op : concatenate (when axis == None)

Author: JiangZhaoh

python/mxnet/ndarray/numpy/_op.py

@@ -38,50 +38,7 @@
            'std', 'var', 'indices', 'copysign', 'ravel', 'hanning', 'hamming', 'blackman', 'flip',
            'around', 'hypot', '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', 'append']
-
-
-@set_module('mxnet.ndarray.numpy')
-def append(arr, values, axis=None):
-    """
-    Append values to the end of an array.
-    Parameters
-    ----------
-    arr : ndarray
-        Values are appended to a copy of this array.
-    values : ndarray
-        These values are appended to a copy of `arr`.  It must be of the
-        correct shape (the same shape as `arr`, excluding `axis`).  If
-        `axis` is not specified, `values` can be any shape and will be
-        flattened before use.
-    axis : int, optional
-        The axis along which `values` are appended.  If `axis` is not
-        given, both `arr` and `values` are flattened before use.
-    Returns
-    -------
-    append : ndarray
-        A copy of `arr` with `values` appended to `axis`.  Note that
-        `append` does not occur in-place: a new array is allocated and
-        filled.  If `axis` is None, `out` is a flattened array.
-    See Also
-    --------
-    insert : Insert elements into an array.
-    delete : Delete elements from an array.
-    Examples
-    --------
-    >>> np.append(np.array([1, 2, 3]), np.array([[4, 5, 6],[7, 8, 9]]))
-    array([1., 2., 3., 4., 5., 6., 7., 8., 9.])
-    When `axis` is specified, `values` must have the correct shape.
-    >>> np.append(np.array([[1, 2, 3], [4, 5, 6]]), np.array([[7, 8, 9]]), axis=0)
-    array([[1., 2., 3.],
-           [4., 5., 6.],
-           [7., 8., 9.]])
-    """
-    if axis is None:
-        arr = arr.flatten()
-        values = values.flatten()
-        axis = 0
-    return concatenate((arr, values), axis=axis)
+           'hsplit', 'rot90', 'einsum', 'true_divide']
 
 
 @set_module('mxnet.ndarray.numpy')
@@ -2963,8 +2920,22 @@ def concatenate(seq, axis=0, out=None):
     -------
     res : ndarray
         The concatenated array.
-    """
-    return _npi.concatenate(*seq, dim=axis, out=out)
+
+    Examples
+    -------
+    >>> a = np.array([[1, 2], [3, 4]])
+    >>> b = np.array([[5, 6]])
+    >>> np.concatenate((a, b), axis = 0)
+    >>> array([[1., 2.],
+               [3., 4.],
+               [5., 6.]])
+    >>> np.concatenate((a, b), axis = None)
+    >>> array([1., 2., 3., 4., 5., 6.])
+    >>> np.concatenate((a, b.T), axis = 1)
+    >>> array([[1., 2., 5.],
+               [3., 4., 6.]])
+    """
+    return _npi.concatenate(*seq, axis=axis, out=out)
 
 
 @set_module('mxnet.ndarray.numpy')

python/mxnet/numpy/multiarray.py

@@ -4533,6 +4533,7 @@ def vsplit(ary, indices_or_sections):
 @set_module('mxnet.numpy')
 def concatenate(seq, axis=0, out=None):
     """Join a sequence of arrays along an existing axis.
+
     Parameters
     ----------
     a1, a2, ... : sequence of array_like
@@ -4545,10 +4546,25 @@ def concatenate(seq, axis=0, out=None):
         If provided, the destination to place the result. The shape must be
         correct, matching that of what concatenate would have returned if no
         out argument were specified.
+
     Returns
     -------
     res : ndarray
         The concatenated array.
+
+    Examples
+    -------
+    >>> a = np.array([[1, 2], [3, 4]])
+    >>> b = np.array([[5, 6]])
+    >>> np.concatenate((a, b), axis = 0)
+    >>> array([[1., 2.],
+               [3., 4.],
+               [5., 6.]])
+    >>> np.concatenate((a, b), axis = None)
+    >>> array([1., 2., 3., 4., 5., 6.])
+    >>> np.concatenate((a, b.T), axis = 1)
+    >>> array([[1., 2., 5.],
+               [3., 4., 6.]])
     """
     return _mx_nd_np.concatenate(seq, axis=axis, out=out)
 
@@ -6423,8 +6439,9 @@ def einsum(*operands, **kwargs):
 
 @set_module('mxnet.numpy')
 def append(arr, values, axis=None):
-    """
+    r"""
     Append values to the end of an array.
+
     Parameters
     ----------
     arr : ndarray
@@ -6437,16 +6454,14 @@ def append(arr, values, axis=None):
     axis : int, optional
         The axis along which `values` are appended.  If `axis` is not
         given, both `arr` and `values` are flattened before use.
+
     Returns
     -------
     append : ndarray
         A copy of `arr` with `values` appended to `axis`.  Note that
         `append` does not occur in-place: a new array is allocated and
         filled.  If `axis` is None, `out` is a flattened array.
-    See Also
-    --------
-    insert : Insert elements into an array.
-    delete : Delete elements from an array.
+
     Examples
     --------
     >>> np.append(np.array([1, 2, 3]), np.array([[4, 5, 6],[7, 8, 9]]))
@@ -6457,9 +6472,4 @@ def append(arr, values, axis=None):
            [4., 5., 6.],
            [7., 8., 9.]])
     """
-    if axis is None:
-        arr = arr.flatten()
-        values = values.flatten()
-        axis = 0
-    return concatenate((arr, values), axis=axis)
-    
+    return _mx_nd_np.append(arr, values, axis=axis)

python/mxnet/numpy_dispatch_protocol.py

@@ -85,6 +85,7 @@ def _run_with_array_ufunc_proto(*args, **kwargs):
 _NUMPY_ARRAY_FUNCTION_LIST = [
     'argmax',
     'around',
+    'append',
     'broadcast_arrays',
     'broadcast_to',
     'clip',

python/mxnet/symbol/numpy/_symbol.py

@@ -40,7 +40,7 @@
            'std', 'var', 'indices', 'copysign', 'ravel', 'hanning', 'hamming', 'blackman', 'flip',
            'around', 'hypot', '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', 'append']
+           'less_equal', 'hsplit', 'rot90', 'einsum', 'true_divide']
 
 
 def _num_outputs(sym):
@@ -2995,6 +2995,7 @@ def vsplit(ary, indices_or_sections):
 @set_module('mxnet.symbol.numpy')
 def concatenate(seq, axis=0, out=None):
     """Join a sequence of arrays along an existing axis.
+
     Parameters
     ----------
     a1, a2, ... : sequence of array_like
@@ -3007,12 +3008,27 @@ def concatenate(seq, axis=0, out=None):
         If provided, the destination to place the result. The shape must be
         correct, matching that of what concatenate would have returned if no
         out argument were specified.
+
     Returns
     -------
     res : ndarray
         The concatenated array.
+
+    Examples
+    -------
+    >>> a = np.array([[1, 2], [3, 4]])
+    >>> b = np.array([[5, 6]])
+    >>> np.concatenate((a, b), axis = 0)
+    >>> array([[1., 2.],
+               [3., 4.],
+               [5., 6.]])
+    >>> np.concatenate((a, b), axis = None)
+    >>> array([1., 2., 3., 4., 5., 6.])
+    >>> np.concatenate((a, b.T), axis = 1)
+    >>> array([[1., 2., 5.],
+               [3., 4., 6.]])
     """
-    return _npi.concatenate(*seq, dim=axis, out=out)
+    return _npi.concatenate(*seq, axis=axis, out=out)
 
 
 @set_module('mxnet.symbol.numpy')
@@ -4555,47 +4571,4 @@ def einsum(*operands, **kwargs):
     return _npi.einsum(*operands, subscripts=subscripts, out=out, optimize=int(optimize_arg))
 
 
-@set_module('mxnet.symbol.numpy')
-def append(arr, values, axis=None):
-    """
-    Append values to the end of an array.
-    Parameters
-    ----------
-    arr : ndarray
-        Values are appended to a copy of this array.
-    values : ndarray
-        These values are appended to a copy of `arr`.  It must be of the
-        correct shape (the same shape as `arr`, excluding `axis`).  If
-        `axis` is not specified, `values` can be any shape and will be
-        flattened before use.
-    axis : int, optional
-        The axis along which `values` are appended.  If `axis` is not
-        given, both `arr` and `values` are flattened before use.
-    Returns
-    -------
-    append : ndarray
-        A copy of `arr` with `values` appended to `axis`.  Note that
-        `append` does not occur in-place: a new array is allocated and
-        filled.  If `axis` is None, `out` is a flattened array.
-    See Also
-    --------
-    insert : Insert elements into an array.
-    delete : Delete elements from an array.
-    Examples
-    --------
-    >>> np.append(np.array([1, 2, 3]), np.array([[4, 5, 6],[7, 8, 9]]))
-    array([1., 2., 3., 4., 5., 6., 7., 8., 9.])
-    When `axis` is specified, `values` must have the correct shape.
-    >>> np.append(np.array([[1, 2, 3], [4, 5, 6]]), np.array([[7, 8, 9]]), axis=0)
-    array([[1., 2., 3.],
-           [4., 5., 6.],
-           [7., 8., 9.]])
-    """
-    if axis is None:
-        arr = arr.flatten()
-        values = values.flatten()
-        axis = 0
-    return concatenate((arr, values), axis=axis)
-
-
 _set_np_symbol_class(_Symbol)