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new 7dcfedc Update qr backward documentation (#19243)
7dcfedc is described below
commit 7dcfedca704f39b4b9b7497dabf3fea47ad40df4
Author: Denisa Roberts <[email protected]>
AuthorDate: Tue Sep 29 00:37:10 2020 -0400
Update qr backward documentation (#19243)
---
python/mxnet/numpy/linalg.py | 5 +++++
src/operator/numpy/linalg/np_qr-inl.h | 3 ++-
2 files changed, 7 insertions(+), 1 deletion(-)
diff --git a/python/mxnet/numpy/linalg.py b/python/mxnet/numpy/linalg.py
index d2756d5..975b889 100644
--- a/python/mxnet/numpy/linalg.py
+++ b/python/mxnet/numpy/linalg.py
@@ -428,6 +428,11 @@ def qr(a, mode='reduced'):
MXNetError
If factoring fails.
+ Notes
+ -----
+ Currently, the gradient for the QR factorization is well-defined
+ only when the first K columns of the input matrix are linearly independent.
+
Examples
--------
>>> from mxnet import np
diff --git a/src/operator/numpy/linalg/np_qr-inl.h
b/src/operator/numpy/linalg/np_qr-inl.h
index c57e2d6..19df4bb 100644
--- a/src/operator/numpy/linalg/np_qr-inl.h
+++ b/src/operator/numpy/linalg/np_qr-inl.h
@@ -518,7 +518,8 @@ struct QrBackHelper_G2 {
}
};
-
+// QR backward methodology is explained in detail in
+// https://arxiv.org/abs/2009.10071
struct qr_backward {
template<typename xpu, typename DType>
static void op(const Tensor<xpu, 3, DType>& dA,
