diff --git a/python/mxnet/ndarray/numpy/linalg.py b/python/mxnet/ndarray/numpy/linalg.py index d507b774e5dc..ea9e6a91c2c1 100644 --- a/python/mxnet/ndarray/numpy/linalg.py +++ b/python/mxnet/ndarray/numpy/linalg.py @@ -111,7 +111,7 @@ def svd(a): (possibly non-zero) eigenvalues are given by ``s**2``. The sign of rows of `u` and `v` are determined as described in - `Auto-Differentiating Linear Algebra https://arxiv.org/pdf/1710.08717.pdf`_. + `Auto-Differentiating Linear Algebra `_. If `a` has more than two dimensions, then broadcasting rules apply. This means that SVD is working in "stacked" mode: it iterates over @@ -122,7 +122,7 @@ def svd(a): ``ut @ (s[..., None] * v)``. (The ``@`` operator denotes batch matrix multiplication) This function differs from the original `numpy.linalg.svd - https://docs.scipy.org/doc/numpy/reference/generated/numpy.linalg.svd.html`_ in + `_ in the following way(s): - The sign of rows of `u` and `v` may differ. - Does not support complex input. diff --git a/python/mxnet/numpy/linalg.py b/python/mxnet/numpy/linalg.py index a47328f817d0..1ca34716d7d4 100644 --- a/python/mxnet/numpy/linalg.py +++ b/python/mxnet/numpy/linalg.py @@ -104,7 +104,7 @@ def svd(a): (possibly non-zero) eigenvalues are given by ``s**2``. The sign of rows of `u` and `v` are determined as described in - `Auto-Differentiating Linear Algebra https://arxiv.org/pdf/1710.08717.pdf`_. + `Auto-Differentiating Linear Algebra `_. If `a` has more than two dimensions, then broadcasting rules apply. This means that SVD is working in "stacked" mode: it iterates over @@ -115,7 +115,7 @@ def svd(a): ``ut @ (s[..., None] * v)``. (The ``@`` operator denotes batch matrix multiplication) This function differs from the original `numpy.linalg.svd - https://docs.scipy.org/doc/numpy/reference/generated/numpy.linalg.svd.html`_ in + `_ in the following way(s): - The sign of rows of `u` and `v` may differ. - Does not support complex input. diff --git a/python/mxnet/symbol/numpy/linalg.py b/python/mxnet/symbol/numpy/linalg.py index 6db4e50b307f..354562160f0d 100644 --- a/python/mxnet/symbol/numpy/linalg.py +++ b/python/mxnet/symbol/numpy/linalg.py @@ -111,7 +111,7 @@ def svd(a): (possibly non-zero) eigenvalues are given by ``s**2``. The sign of rows of `u` and `v` are determined as described in - `Auto-Differentiating Linear Algebra https://arxiv.org/pdf/1710.08717.pdf`_. + `Auto-Differentiating Linear Algebra `_. If `a` has more than two dimensions, then broadcasting rules apply. This means that SVD is working in "stacked" mode: it iterates over @@ -122,7 +122,7 @@ def svd(a): ``ut @ (s[..., None] * v)``. (The ``@`` operator denotes batch matrix multiplication) This function differs from the original `numpy.linalg.svd - https://docs.scipy.org/doc/numpy/reference/generated/numpy.linalg.svd.html`_ in + `_ in the following way(s): - The sign of rows of `u` and `v` may differ. - Does not support complex input.