haojin2 commented on a change in pull request #15277: [Numpy] Numpy argsort
URL: https://github.com/apache/incubator-mxnet/pull/15277#discussion_r299839833
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File path: python/mxnet/ndarray/numpy/_op.py
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@@ -284,6 +284,66 @@ def argmax(a, axis=None, out=None):
return _npi.argmax(a, axis=axis, keepdims=False, out=out)
+@set_module('mxnet.ndarray.numpy')
+def argsort(a, axis=-1, kind='quicksort', order=None):
+ """
+ Returns the indices that would sort an input array along the given axis.
+ This function performs sorting along the given axis and returns an array
+ of indices having same shape as an input array that index data in sorted
order.
+
+ Parameters
+ ----------
+ a : ndarray
+ Input array
+ axis : int, optional
+ The axis along which to sort teh input tensor.
+ If not given, the last, dimension -1 will be used by default.
+ If None, the flattened array is used.
+ kind: {'quicksort'}
+ Currently not supported.
+ order: None
+ Currently not supported.
+
+ Returns
+ -------
+ output : ndarray
+ Array of indices that sort a along the specified axis.
+ If a is one-dimensional, a[index_array] yields a sorted a.
+ More generally, np.take_along_axis(a, index_array, axis=a) always
yields the sorted a,
+ irrespective of dimensionality.
+
+ Examples
+ --------
+ >>> x = np.array([3, 1, 2])
+ >>> np.argsort(x)
+ array([1., 2., 0.])
+ >>> x = np.array([[0, 3], [2, 2]])
+ >>> x
+ array([[0., 3.],
+ [2., 2.]])
+ >>> np.argsort(x, axis=0) # sorts along first axis (down)
+ array([[0., 1.],
+ [1., 0.]])
+ >>> np.argsort(x, axis=1) # sorts along last axis (across)
+ array([[0., 1.],
+ [0., 1.]])
+
+ Notes
+ -----
+ This function differs from the original `numpy.mean
Review comment:
"the original numpy.argsort ..."
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