reminisce commented on a change in pull request #15377: [numpy][doc-fix]
zeros_like, linspace, reciprocal, square, and arcsin
URL: https://github.com/apache/incubator-mxnet/pull/15377#discussion_r298004840
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File path: python/mxnet/_numpy_op_doc.py
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@@ -173,3 +217,255 @@ def _np_cumsum(a, axis=None, dtype=None, out=None):
`axis` is not None or `a` is a 1-d array.
"""
pass
+
+
+def _np_reciprocal(x, out=None, **kwargs):
+ """
+ reciprocal(x, out=None, dtype=None)
+
+ Return the reciprocal of the argument, element-wise.
+ Calculates ``1/x``.
+
+ Parameters
+ ----------
+ x : ndarray
+ out : ndarray, None, or tuple of ndarray and None, optional
+ A location into which the result is stored. If provided, it must have
+ a shape that the inputs broadcast to. If not provided or None,
+ a freshly-allocated array is returned. A tuple
+ (possible only as a keyword argument) must have length equal to
+ the number of outputs.
+
+ Returns
+ -------
+ y : ndarray
+ Return array.
+
+
+ Examples
+ --------
+ >>> np.reciprocal(2.)
+ 0.5
+ >>> np.reciprocal([1, 2., 3.33])
+ array([ 1. , 0.5 , 0.3003003])
+
+ Notes
+ -----
+
+ .. note::
+ This function is not designed to work with integers.
+ For integer arguments with absolute value larger than 1 the result is
+ always zero because of the way Python handles integer division. For
+ integer zero the result is an overflow.
+
+ `ctx` argument is not supported now.
+
+ This function differs to the original `numpy.reciprocal
+
<https://docs.scipy.org/doc/numpy/reference/generated/numpy.reciprocal.html>`_
in
+ the following aspects:
+
+ - Only support ndarray now.
+ - `where` argument is not supported.
+ """
+ pass
+
+
+def _np_square(x, out=None, **kwargs):
+ """
+ square(x, out=None, **kwargs)
+
+ Return the element-wise square of the input.
+
+ Parameters
+ ----------
+ x : ndarray
+ out : ndarray, None, or tuple of ndarray and None, optional
+ A location into which the result is stored. If provided, it must have
+ a shape that the inputs broadcast to. If not provided or `None`,
+ a freshly-allocated array is returned. A tuple (possible only as a
+ keyword argument) must have length equal to the number of outputs.
+
+ Returns
+ -------
+ y : ndarray
+ Return array.
+
+
+ Examples
+ --------
+ >>> np.square([-1j, 1])
Review comment:
This is not supported. Please use mxnet.numpy to run the examples.
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