endvroy commented on a change in pull request #15382: [numpy][doc-fix] sum,
copy, tile, argmax, sign, log, degrees
URL: https://github.com/apache/incubator-mxnet/pull/15382#discussion_r298875146
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File path: python/mxnet/_numpy_op_doc.py
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@@ -223,3 +224,144 @@ def _np_dot(a, b, out=None):
array(29884.)
"""
pass
+
+
+# def _np_sum(a, axis=None, dtype=None, out=None, keepdims=_Null):
+def _np_sum(a, axis=None, dtype=None, out=None):
+ r"""
+ sum(a, axis=_Null, dtype=_Null, keepdims=_Null, initial=_Null, out=None)
+
+ 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 pass in None if needed.
+ out : ndarray, 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
+ -----
+ 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 change. out ndarray's dtype must
be the same as the expected output.
+ - "initial" param is not supported yet. Please use None as input.
+
+ 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):
+ r"""
+ copy(a, out=None)
+
+ Return an array copy of the given object.
+
+ Parameters
+ ----------
+ a : ndarray
+ Input data.
+ out : ndarray, optional
+ Alternative output array in which to place the result. It must have
+ the same shape and dtype as the expected output.
+
+ Returns
+ -------
+ arr : ndarray
+ Array interpretation of `a`.
+
+ Notes
+ -------
+ This function differs from the original `numpy.copy
+ <https://docs.scipy.org/doc/numpy/reference/generated/numpy.copy.html>`_ in
+ the following aspects:
+
+ - Input type does not support Python native iterables(list, tuple, ...).
+ - ``out`` param: cannot perform auto broadcasting. ``out`` ndarray's shape
must be the same as the expected output.
+ - ``out`` param: cannot perform auto type change. ``out`` ndarray's dtype
must be the same as the expected output.
+ - Does not support "order" parameter.
+
+ Examples
+ --------
+ Create an array x, with a reference y and a copy z:
+
+ >>> x = np.array([1, 2, 3])
+ >>> y = x
+ >>> z = np.copy(x)
+
+ Note that, when we modify x, y changes, but not z:
Review comment:
Same here.
Note that, `x` is modified, `y` is modified, but not `z`:
The original line really confused me as I was not sure whether the comma
actually acts as a tuple separator.
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