README and documentation for the main functions of tensor algebra #297
@ -49,13 +49,13 @@ public interface LinearOpsTensorAlgebra<T> :
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/**
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/**
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* QR decomposition.
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* QR decomposition.
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*
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*
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* Computes the QR decomposition of a matrix or a batch of matrices, and returns a namedtuple `(Q, R)` of tensors.
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* Computes the QR decomposition of a matrix or a batch of matrices, and returns a pair `(Q, R)` of tensors.
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* Given a tensor `input`, return tensors (Q, R) satisfying ``input = Q * R``,
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* Given a tensor `input`, return tensors (Q, R) satisfying ``input = Q * R``,
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* with `Q` being an orthogonal matrix or batch of orthogonal matrices
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* with `Q` being an orthogonal matrix or batch of orthogonal matrices
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* and `R` being an upper triangular matrix or batch of upper triangular matrices.
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* and `R` being an upper triangular matrix or batch of upper triangular matrices.
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* For more information: https://pytorch.org/docs/stable/linalg.html#torch.linalg.qr
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* For more information: https://pytorch.org/docs/stable/linalg.html#torch.linalg.qr
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*
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*
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* @return tuple of Q and R tensors.
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* @return pair of Q and R tensors.
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*/
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*/
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public fun TensorStructure<T>.qr(): Pair<TensorStructure<T>, TensorStructure<T>>
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public fun TensorStructure<T>.qr(): Pair<TensorStructure<T>, TensorStructure<T>>
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@ -82,7 +82,7 @@ public interface LinearOpsTensorAlgebra<T> :
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* Singular Value Decomposition.
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* Singular Value Decomposition.
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*
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*
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* Computes the singular value decomposition of either a matrix or batch of matrices `input`.
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* Computes the singular value decomposition of either a matrix or batch of matrices `input`.
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* The singular value decomposition is represented as a namedtuple `(U, S, V)`,
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* The singular value decomposition is represented as a triple `(U, S, V)`,
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* such that ``input = U.dot(diagonalEmbedding(S).dot(V.T))``.
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* such that ``input = U.dot(diagonalEmbedding(S).dot(V.T))``.
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* If input is a batch of tensors, then U, S, and Vh are also batched with the same batch dimensions as input.
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* If input is a batch of tensors, then U, S, and Vh are also batched with the same batch dimensions as input.
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* For more information: https://pytorch.org/docs/stable/linalg.html#torch.linalg.svd
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* For more information: https://pytorch.org/docs/stable/linalg.html#torch.linalg.svd
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@ -93,10 +93,10 @@ public interface LinearOpsTensorAlgebra<T> :
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/**
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/**
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* Returns eigenvalues and eigenvectors of a real symmetric matrix input or a batch of real symmetric matrices,
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* Returns eigenvalues and eigenvectors of a real symmetric matrix input or a batch of real symmetric matrices,
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* represented by a namedtuple (eigenvalues, eigenvectors).
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* represented by a pair (eigenvalues, eigenvectors).
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* For more information: https://pytorch.org/docs/stable/generated/torch.symeig.html
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* For more information: https://pytorch.org/docs/stable/generated/torch.symeig.html
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*
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*
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* @return a namedtuple (eigenvalues, eigenvectors)
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* @return a pair (eigenvalues, eigenvectors)
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*/
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*/
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public fun TensorStructure<T>.symEig(): Pair<TensorStructure<T>, TensorStructure<T>>
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public fun TensorStructure<T>.symEig(): Pair<TensorStructure<T>, TensorStructure<T>>
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