add ffi for sum, var and std

benchmark/python/ffi/benchmark_ffi.py

@@ -57,6 +57,9 @@ def prepare_workloads():
     OpArgMngr.add_workload("tensordot", pool['2x2'], pool['2x2'], ((1, 0), (0, 1)))
     OpArgMngr.add_workload("kron", pool['2x2'], pool['2x2'])
     OpArgMngr.add_workload("cumsum", pool['3x2'], axis=0, out=pool['3x2'])
+    OpArgMngr.add_workload("sum", pool['2x2'], axis=0, keepdims=True, out=pool['1x2'])
+    OpArgMngr.add_workload("std", pool['2x2'], axis=0, ddof=0, keepdims=True, out=pool['1x2'])
+    OpArgMngr.add_workload("var", pool['2x2'], axis=0, ddof=1, keepdims=True, out=pool['1x2'])
     OpArgMngr.add_workload("add", pool['2x2'], pool['2x2'])
     OpArgMngr.add_workload("linalg.svd", pool['3x3'])
     OpArgMngr.add_workload("split", pool['3x3'], (0, 1, 2), axis=1)

python/mxnet/_numpy_op_doc.py

@@ -231,98 +231,6 @@ def _np_dot(a, b, out=None):
     pass
 
 
-def _np_sum(a, axis=None, dtype=None, keepdims=False, initial=None, out=None):
-    r"""
-    Sum of array elements over a given axis.
-
-    Parameters
-    ----------
-    a : ndarray
-        Input data.
-    axis : None or int, optional
-        Axis or axes along which a sum is performed.  The default,
-        axis=None, will sum all of the elements of the input array.  If
-        axis is negative it counts from the last to the first axis.
-    dtype : dtype, optional
-        The type of the returned array and of the accumulator in which the
-        elements are summed. The default type is float32.
-    keepdims : bool, optional
-        If this is set to True, the axes which are reduced are left
-        in the result as dimensions with size one. With this option,
-        the result will broadcast correctly against the input array.
-
-        If the default value is passed, then `keepdims` will not be
-        passed through to the `sum` method of sub-classes of
-        `ndarray`, however any non-default value will be.  If the
-        sub-classes `sum` method does not implement `keepdims` any
-        exceptions will be raised.
-    initial: Currently only supports None as input, optional
-        Starting value for the sum.
-        Currently not implemented. Please use ``None`` as input or skip this argument.
-    out : ndarray or None, optional
-        Alternative output array in which to place the result. It must have
-        the same shape and dtype as the expected output.
-
-    Returns
-    -------
-    sum_along_axis : ndarray
-        An ndarray with the same shape as `a`, with the specified
-        axis removed. If an output array is specified, a reference to
-        `out` is returned.
-
-    Notes
-    -----
-    - Input type does not support Python native iterables.
-    - "out" param: cannot perform auto type change. out ndarray's dtype must be the same as the expected output.
-    - "initial" param is not supported yet. Please use None as input.
-    - Arithmetic is modular when using integer types, and no error is raised on overflow.
-    - The sum of an empty array is the neutral element 0:
-
-    >>> a = np.empty(1)
-    >>> np.sum(a)
-    array(0.)
-
-    This function differs from the original `numpy.sum
-    <https://docs.scipy.org/doc/numpy/reference/generated/numpy.sum.html>`_ in
-    the following aspects:
-
-    - Input type does not support Python native iterables(list, tuple, ...).
-    - "out" param: cannot perform auto type cast. out ndarray's dtype must be the same as the expected output.
-    - "initial" param is not supported yet. Please use ``None`` as input or skip it.
-
-    Examples
-    --------
-    >>> a = np.array([0.5, 1.5])
-    >>> np.sum(a)
-    array(2.)
-    >>> a = np.array([0.5, 0.7, 0.2, 1.5])
-    >>> np.sum(a, dtype=np.int32)
-    array(2, dtype=int32)
-    >>> a = np.array([[0, 1], [0, 5]])
-    >>> np.sum(a)
-    array(6.)
-    >>> np.sum(a, axis=0)
-    array([0., 6.])
-    >>> np.sum(a, axis=1)
-    array([1., 5.])
-
-    With output ndarray:
-
-    >>> a = np.array([[0, 1], [0, 5]])
-    >>> b = np.ones((2,), dtype=np.float32)
-    >>> np.sum(a, axis = 0, out=b)
-    array([0., 6.])
-    >>> b
-    array([0., 6.])
-
-    If the accumulator is too small, overflow occurs:
-
-    >>> np.ones(128, dtype=np.int8).sum(dtype=np.int8)
-    array(-128, dtype=int8)
-    """
-    pass
-
-
 def _np_copy(a, out=None):
     """
     Return an array copy of the given object.

python/mxnet/ndarray/numpy/_op.py

@@ -47,7 +47,7 @@
            'equal', 'not_equal', 'greater', 'less', 'greater_equal', 'less_equal', 'roll', 'rot90', 'einsum',
            'true_divide', 'nonzero', 'quantile', 'percentile', 'shares_memory', 'may_share_memory',
            'diff', 'ediff1d', 'resize', 'polyval', 'nan_to_num', 'isnan', 'isinf', 'isposinf', 'isneginf', 'isfinite',
-           'where', 'bincount', 'pad', 'cumsum', 'diag', 'diagonal']
+           'where', 'bincount', 'pad', 'cumsum', 'sum', 'diag', 'diagonal']
 
 
 @set_module('mxnet.ndarray.numpy')
@@ -4883,7 +4883,7 @@ def std(a, axis=None, dtype=None, out=None, ddof=0, keepdims=False):  # pylint:
     >>> np.std(a, dtype=np.float64)
     array(0.45, dtype=float64)
     """
-    return _npi.std(a, axis=axis, dtype=dtype, ddof=ddof, keepdims=keepdims, out=out)
+    return _api_internal.std(a, axis, dtype, ddof, keepdims, out)
 
 
 @set_module('mxnet.ndarray.numpy')
@@ -4953,7 +4953,7 @@ def var(a, axis=None, dtype=None, out=None, ddof=0, keepdims=False):  # pylint:
     >>> ((1-0.55)**2 + (0.1-0.55)**2)/2
     0.2025
     """
-    return _npi.var(a, axis=axis, dtype=dtype, ddof=ddof, keepdims=keepdims, out=out)
+    return _api_internal.var(a, axis, dtype, ddof, keepdims, out)
 
 
 # pylint: disable=redefined-outer-name
@@ -6141,7 +6141,7 @@ def outer(a, b):
         [-2., -1.,  0.,  1.,  2.],
         [-2., -1.,  0.,  1.,  2.]])
     """
-    return tensordot(a.flatten(), b.flatten(), 0)
+    return tensordot(a.reshape_view((-1, )), b.reshape_view((-1, )), 0)
 
 
 @set_module('mxnet.ndarray.numpy')
@@ -8033,3 +8033,100 @@ def diagonal(a, offset=0, axis1=0, axis2=1):
             [1, 7]])
     """
     return _api_internal.diagonal(a, offset, axis1, axis2)
+
+
+# pylint:disable=redefined-outer-name, too-many-arguments
+@set_module('mxnet.ndarray.numpy')
+def sum(a, axis=None, dtype=None, out=None, keepdims=None, initial=None, where=None):
+    r"""
+    Sum of array elements over a given axis.
+
+    Parameters
+    ----------
+    a : ndarray
+        Input data.
+    axis : None or int, optional
+        Axis or axes along which a sum is performed.  The default,
+        axis=None, will sum all of the elements of the input array.  If
+        axis is negative it counts from the last to the first axis.
+    dtype : dtype, optional
+        The type of the returned array and of the accumulator in which the
+        elements are summed. The default type is float32.
+    keepdims : bool, optional
+        If this is set to True, the axes which are reduced are left
+        in the result as dimensions with size one. With this option,
+        the result will broadcast correctly against the input array.
+
+        If the default value is passed, then `keepdims` will not be
+        passed through to the `sum` method of sub-classes of
+        `ndarray`, however any non-default value will be.  If the
+        sub-classes `sum` method does not implement `keepdims` any
+        exceptions will be raised.
+    initial: Currently only supports None as input, optional
+        Starting value for the sum.
+        Currently not implemented. Please use ``None`` as input or skip this argument.
+    out : ndarray or None, optional
+        Alternative output array in which to place the result. It must have
+        the same shape and dtype as the expected output.
+
+    Returns
+    -------
+    sum_along_axis : ndarray
+        An ndarray with the same shape as `a`, with the specified
+        axis removed. If an output array is specified, a reference to
+        `out` is returned.
+
+    Notes
+    -----
+    - Input type does not support Python native iterables.
+    - "out" param: cannot perform auto type change. out ndarray's dtype must be the same as the expected output.
+    - "initial" param is not supported yet. Please use None as input.
+    - Arithmetic is modular when using integer types, and no error is raised on overflow.
+    - The sum of an empty array is the neutral element 0:
+
+    >>> a = np.empty(1)
+    >>> np.sum(a)
+    array(0.)
+
+    This function differs from the original `numpy.sum
+    <https://docs.scipy.org/doc/numpy/reference/generated/numpy.sum.html>`_ in
+    the following aspects:
+
+    - Input type does not support Python native iterables(list, tuple, ...).
+    - "out" param: cannot perform auto type cast. out ndarray's dtype must be the same as the expected output.
+    - "initial" param is not supported yet. Please use ``None`` as input or skip it.
+
+    Examples
+    --------
+    >>> a = np.array([0.5, 1.5])
+    >>> np.sum(a)
+    array(2.)
+    >>> a = np.array([0.5, 0.7, 0.2, 1.5])
+    >>> np.sum(a, dtype=np.int32)
+    array(2, dtype=int32)
+    >>> a = np.array([[0, 1], [0, 5]])
+    >>> np.sum(a)
+    array(6.)
+    >>> np.sum(a, axis=0)
+    array([0., 6.])
+    >>> np.sum(a, axis=1)
+    array([1., 5.])
+
+    With output ndarray:
+
+    >>> a = np.array([[0, 1], [0, 5]])
+    >>> b = np.ones((2,), dtype=np.float32)
+    >>> np.sum(a, axis=0, out=b)
+    array([0., 6.])
+    >>> b
+    array([0., 6.])
+
+    If the accumulator is too small, overflow occurs:
+
+    >>> np.ones(128, dtype=np.int8).sum(dtype=np.int8)
+    array(-128, dtype=int8)
+    """
+    if where is not None and where is not True:
+        raise ValueError("only where=None or where=True cases are supported for now")
+    return _api_internal.sum(a, axis, dtype, keepdims, initial, out)
+# pylint:enable=redefined-outer-name, too-many-arguments

python/mxnet/numpy/multiarray.py

@@ -73,7 +73,7 @@
            'greater', 'less', 'greater_equal', 'less_equal', 'roll', 'rot90', 'einsum', 'true_divide', 'nonzero',
            'quantile', 'percentile', 'shares_memory', 'may_share_memory', 'diff', 'ediff1d', 'resize', 'matmul',
            'nan_to_num', 'isnan', 'isinf', 'isposinf', 'isneginf', 'isfinite', 'polyval', 'where', 'bincount',
-           'pad', 'cumsum', 'diag', 'diagonal']
+           'pad', 'cumsum', 'sum', 'diag', 'diagonal']
 
 __all__ += fallback.__all__
 
@@ -6763,7 +6763,7 @@ def std(a, axis=None, dtype=None, out=None, ddof=0, keepdims=False):  # pylint:
     >>> np.std(a, dtype=np.float64)
     array(0.45, dtype=float64)
     """
-    return _npi.std(a, axis=axis, dtype=dtype, ddof=ddof, keepdims=keepdims, out=out)
+    return _mx_nd_np.std(a, axis=axis, dtype=dtype, ddof=ddof, keepdims=keepdims, out=out)
 # pylint: enable=redefined-outer-name
 
 
@@ -6884,7 +6884,7 @@ def var(a, axis=None, dtype=None, out=None, ddof=0, keepdims=False):  # pylint:
     >>> ((1-0.55)**2 + (0.1-0.55)**2)/2
     0.2025
     """
-    return _npi.var(a, axis=axis, dtype=dtype, ddof=ddof, keepdims=keepdims, out=out)
+    return _mx_nd_np.var(a, axis=axis, dtype=dtype, ddof=ddof, keepdims=keepdims, out=out)
 
 
 # pylint: disable=redefined-outer-name
@@ -7047,6 +7047,7 @@ def ravel(x, order='C'):
     return _mx_nd_np.ravel(x, order)
 
 
+@set_module('mxnet.numpy')
 def unravel_index(indices, shape, order='C'): # pylint: disable=redefined-outer-name
     """
     Converts a flat index or array of flat indices into a tuple of coordinate arrays.
@@ -7077,6 +7078,7 @@ def unravel_index(indices, shape, order='C'): # pylint: disable=redefined-outer-
     return _mx_nd_np.unravel_index(indices, shape, order=order)
 
 
+@set_module('mxnet.numpy')
 def flatnonzero(a):
     r"""
     Return indices that are non-zero in the flattened version of a.
@@ -7116,6 +7118,7 @@ def flatnonzero(a):
     return _mx_nd_np.flatnonzero(a)
 
 
+@set_module('mxnet.numpy')
 def diag_indices_from(arr):
     """
     This returns a tuple of indices that can be used to access the main diagonal of an array
@@ -10196,3 +10199,98 @@ def diagonal(a, offset=0, axis1=0, axis2=1):
             [1, 7]])
     """
     return _mx_nd_np.diagonal(a, offset=offset, axis1=axis1, axis2=axis2)
+
+
+# pylint: disable=redefined-outer-name, too-many-arguments
+@set_module('mxnet.numpy')
+def sum(a, axis=None, dtype=None, out=None, keepdims=None, initial=None, where=None):
+    r"""
+    Sum of array elements over a given axis.
+
+    Parameters
+    ----------
+    a : ndarray
+        Input data.
+    axis : None or int, optional
+        Axis or axes along which a sum is performed.  The default,
+        axis=None, will sum all of the elements of the input array.  If
+        axis is negative it counts from the last to the first axis.
+    dtype : dtype, optional
+        The type of the returned array and of the accumulator in which the
+        elements are summed. The default type is float32.
+    keepdims : bool, optional
+        If this is set to True, the axes which are reduced are left
+        in the result as dimensions with size one. With this option,
+        the result will broadcast correctly against the input array.
+
+        If the default value is passed, then `keepdims` will not be
+        passed through to the `sum` method of sub-classes of
+        `ndarray`, however any non-default value will be.  If the
+        sub-classes `sum` method does not implement `keepdims` any
+        exceptions will be raised.
+    initial: Currently only supports None as input, optional
+        Starting value for the sum.
+        Currently not implemented. Please use ``None`` as input or skip this argument.
+    out : ndarray or None, optional
+        Alternative output array in which to place the result. It must have
+        the same shape and dtype as the expected output.
+
+    Returns
+    -------
+    sum_along_axis : ndarray
+        An ndarray with the same shape as `a`, with the specified
+        axis removed. If an output array is specified, a reference to
+        `out` is returned.
+
+    Notes
+    -----
+    - Input type does not support Python native iterables.
+    - "out" param: cannot perform auto type change. out ndarray's dtype must be the same as the expected output.
+    - "initial" param is not supported yet. Please use None as input.
+    - Arithmetic is modular when using integer types, and no error is raised on overflow.
+    - The sum of an empty array is the neutral element 0:
+
+    >>> a = np.empty(1)
+    >>> np.sum(a)
+    array(0.)
+
+    This function differs from the original `numpy.sum
+    <https://docs.scipy.org/doc/numpy/reference/generated/numpy.sum.html>`_ in
+    the following aspects:
+
+    - Input type does not support Python native iterables(list, tuple, ...).
+    - "out" param: cannot perform auto type cast. out ndarray's dtype must be the same as the expected output.
+    - "initial" param is not supported yet. Please use ``None`` as input or skip it.
+
+    Examples
+    --------
+    >>> a = np.array([0.5, 1.5])
+    >>> np.sum(a)
+    array(2.)
+    >>> a = np.array([0.5, 0.7, 0.2, 1.5])
+    >>> np.sum(a, dtype=np.int32)
+    array(2, dtype=int32)
+    >>> a = np.array([[0, 1], [0, 5]])
+    >>> np.sum(a)
+    array(6.)
+    >>> np.sum(a, axis=0)
+    array([0., 6.])
+    >>> np.sum(a, axis=1)
+    array([1., 5.])
+
+    With output ndarray:
+
+    >>> a = np.array([[0, 1], [0, 5]])
+    >>> b = np.ones((2,), dtype=np.float32)
+    >>> np.sum(a, axis = 0, out=b)
+    array([0., 6.])
+    >>> b
+    array([0., 6.])
+
+    If the accumulator is too small, overflow occurs:
+
+    >>> np.ones(128, dtype=np.int8).sum(dtype=np.int8)
+    array(-128, dtype=int8)
+    """
+    return _mx_nd_np.sum(a, axis=axis, dtype=dtype, out=out, keepdims=keepdims, initial=initial, where=where)
+# pylint: enable=redefined-outer-name, too-many-arguments