leandron commented on a change in pull request #6232:
URL: https://github.com/apache/incubator-tvm/pull/6232#discussion_r467041812
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File path: python/tvm/relay/op/reduce.py
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@@ -376,6 +408,39 @@ def std(data, axis=None, keepdims=False, exclude=False):
return sqrt(_make._variance(data, m, axis, keepdims, exclude))
+def unbiased_std(data, axis=None, keepdims=False, exclude=False):
+ """Computes the unbiased standard deviation of data over given axes.
+
+ Parameters
+ ----------
+ data : relay.Expr
+ The input data
+
+ axis : None or int or tuple of int
+ Axis or axes along which a standard deviation operation is performed.
+ The default, axis=None, will compute the standard deviation of all
elements in the
+ input array. If axis is negative it counts from the last to the first
axis.
+
+ keepdims : bool
+ 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.
+
+ exclude : bool
+ If `exclude` is true, reduction will be performed on the axes that are
+ NOT in axis instead.
+
+ Returns
+ -------
+ result : relay.Expr
+ The computed result.
+ """
+ axis = [axis] if isinstance(axis, int) else axis
+ m = mean(data, axis, True, exclude)
+
+ return sqrt(_make._unbiased_variance(data, m, axis, keepdims, exclude))
Review comment:
Understood. Thanks
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