public <T> Qr<T> qr(Operand<T> input, Qr.Options... options)
Qr
operationinput
- A tensor of shape `[..., M, N]` whose inner-most 2 dimensionsoptions
- carries optional attributes valuesQr
public <T extends Number> BatchMatrixInverse<T> batchMatrixInverse(Operand<T> input, BatchMatrixInverse.Options... options)
BatchMatrixInverse
operationinput
- options
- carries optional attributes valuesBatchMatrixInverse
public <T extends Number> BatchCholesky<T> batchCholesky(Operand<T> input)
BatchCholesky
operationinput
- BatchCholesky
public <T extends Number> BatchSelfAdjointEig<T> batchSelfAdjointEig(Operand<T> input, BatchSelfAdjointEig.Options... options)
BatchSelfAdjointEig
operationinput
- options
- carries optional attributes valuesBatchSelfAdjointEig
public <T> TensorDiag<T> tensorDiag(Operand<T> diagonal)
TensorDiag
operationdiagonal
- Rank k tensor where k is at most 1.TensorDiag
public <T,U extends Number> ConjugateTranspose<T> conjugateTranspose(Operand<T> x, Operand<U> perm)
ConjugateTranspose
operationx
- perm
- ConjugateTranspose
public <T> BatchMatrixDeterminant<T> batchMatrixDeterminant(Operand<T> input)
BatchMatrixDeterminant
operationinput
- BatchMatrixDeterminant
public <T extends Number> BatchMatrixSolve<T> batchMatrixSolve(Operand<T> matrix, Operand<T> rhs, BatchMatrixSolve.Options... options)
BatchMatrixSolve
operationmatrix
- rhs
- options
- carries optional attributes valuesBatchMatrixSolve
public <T extends Number> BatchCholeskyGrad<T> batchCholeskyGrad(Operand<T> l, Operand<T> grad)
BatchCholeskyGrad
operationl
- grad
- BatchCholeskyGrad
public <T extends Number> BatchMatrixSolveLs<T> batchMatrixSolveLs(Operand<T> matrix, Operand<T> rhs, Operand<Double> l2Regularizer, BatchMatrixSolveLs.Options... options)
BatchMatrixSolveLs
operationmatrix
- rhs
- l2Regularizer
- options
- carries optional attributes valuesBatchMatrixSolveLs
public <T> TensorDiagPart<T> tensorDiagPart(Operand<T> input)
TensorDiagPart
operationinput
- Rank k tensor where k is even and not zero.TensorDiagPart
public <T> Sqrtm<T> sqrtm(Operand<T> input)
Sqrtm
operationinput
- Shape is `[..., M, M]`.Sqrtm
public <T> Svd<T> svd(Operand<T> input, Svd.Options... options)
Svd
operationinput
- A tensor of shape `[..., M, N]` whose inner-most 2 dimensionsoptions
- carries optional attributes valuesSvd
public <T> Det<T> det(Operand<T> input)
Det
operationinput
- Shape is `[..., M, M]`.Det
public <T> Cholesky<T> cholesky(Operand<T> input)
Cholesky
operationinput
- Shape is `[..., M, M]`.Cholesky
public <T> TriangularSolve<T> triangularSolve(Operand<T> matrix, Operand<T> rhs, TriangularSolve.Options... options)
TriangularSolve
operationmatrix
- Shape is `[..., M, M]`.rhs
- Shape is `[..., M, K]`.options
- carries optional attributes valuesTriangularSolve
public <T> LogMatrixDeterminant<T> logMatrixDeterminant(Operand<T> input)
LogMatrixDeterminant
operationinput
- Shape is `[N, M, M]`.LogMatrixDeterminant
public <T extends Number> Cross<T> cross(Operand<T> a, Operand<T> b)
Cross
operationa
- A tensor containing 3-element vectors.b
- Another tensor, of same type and shape as `a`.Cross
public <T> DiagPart<T> diagPart(Operand<T> input)
DiagPart
operationinput
- Rank `k` tensor where `k >= 2`.DiagPart
public <T> Solve<T> solve(Operand<T> matrix, Operand<T> rhs, Solve.Options... options)
Solve
operationmatrix
- Shape is `[..., M, M]`.rhs
- Shape is `[..., M, K]`.options
- carries optional attributes valuesSolve
public <T> SetDiag<T> setDiag(Operand<T> input, Operand<T> diagonal)
SetDiag
operationinput
- Rank `k+1`, where `k >= 1`.diagonal
- Rank `k`, where `k >= 1`.SetDiag
public <T extends Number> CholeskyGrad<T> choleskyGrad(Operand<T> l, Operand<T> grad)
CholeskyGrad
operationl
- Output of batch Cholesky algorithm l = cholesky(A). Shape is `[..., M, M]`.grad
- df/dl where f is some scalar function. Shape is `[..., M, M]`.CholeskyGrad
public <V,T,U,W> QuantizedMatMul<V> quantizedMatMul(Operand<T> a, Operand<U> b, Operand<Float> minA, Operand<Float> maxA, Operand<Float> minB, Operand<Float> maxB, Class<V> Toutput, Class<W> Tactivation, QuantizedMatMul.Options... options)
QuantizedMatMul
operationa
- Must be a two-dimensional tensor.b
- Must be a two-dimensional tensor.minA
- The float value that the lowest quantized `a` value represents.maxA
- The float value that the highest quantized `a` value represents.minB
- The float value that the lowest quantized `b` value represents.maxB
- The float value that the highest quantized `b` value represents.Toutput
- Tactivation
- The type of output produced by activation functionoptions
- carries optional attributes valuesQuantizedMatMul
public <T> BatchMatrixSetDiag<T> batchMatrixSetDiag(Operand<T> input, Operand<T> diagonal)
BatchMatrixSetDiag
operationinput
- diagonal
- BatchMatrixSetDiag
public <T,U extends Number> Transpose<T> transpose(Operand<T> x, Operand<U> perm)
Transpose
operationx
- perm
- Transpose
public <T> MatrixSolveLs<T> matrixSolveLs(Operand<T> matrix, Operand<T> rhs, Operand<Double> l2Regularizer, MatrixSolveLs.Options... options)
MatrixSolveLs
operationmatrix
- Shape is `[..., M, N]`.rhs
- Shape is `[..., M, K]`.l2Regularizer
- Scalar tensor.options
- carries optional attributes valuesMatrixSolveLs
public <T> BatchSvd<T> batchSvd(Operand<T> input, BatchSvd.Options... options)
BatchSvd
operationinput
- options
- carries optional attributes valuesBatchSvd
public LoadAndRemapMatrix loadAndRemapMatrix(Operand<String> ckptPath, Operand<String> oldTensorName, Operand<Long> rowRemapping, Operand<Long> colRemapping, Operand<Float> initializingValues, Long numRows, Long numCols, LoadAndRemapMatrix.Options... options)
LoadAndRemapMatrix
operationckptPath
- Path to the TensorFlow checkpoint (version 2, `TensorBundle`) fromoldTensorName
- Name of the 2-D `Tensor` to load from checkpoint.rowRemapping
- An int `Tensor` of row remappings (generally created bycolRemapping
- An int `Tensor` of column remappings (generally created byinitializingValues
- A float `Tensor` containing values to fill in for cellsnumRows
- Number of rows (length of the 1st dimension) in the output matrix.numCols
- Number of columns (length of the 2nd dimension) in the output matrix.options
- carries optional attributes valuesLoadAndRemapMatrix
public <T> BatchMatrixDiagPart<T> batchMatrixDiagPart(Operand<T> input)
BatchMatrixDiagPart
operationinput
- BatchMatrixDiagPart
public <T> Inv<T> inv(Operand<T> input, Inv.Options... options)
Inv
operationinput
- Shape is `[..., M, M]`.options
- carries optional attributes valuesInv
public <T extends Number> BatchMatrixTriangularSolve<T> batchMatrixTriangularSolve(Operand<T> matrix, Operand<T> rhs, BatchMatrixTriangularSolve.Options... options)
BatchMatrixTriangularSolve
operationmatrix
- rhs
- options
- carries optional attributes valuesBatchMatrixTriangularSolve
public <T> MatMul<T> matMul(Operand<T> a, Operand<T> b, MatMul.Options... options)
MatMul
operationa
- b
- options
- carries optional attributes valuesMatMul
public <T> BatchMatrixBandPart<T> batchMatrixBandPart(Operand<T> input, Operand<Long> numLower, Operand<Long> numUpper)
BatchMatrixBandPart
operationinput
- numLower
- numUpper
- BatchMatrixBandPart
public <T> Diag<T> diag(Operand<T> diagonal)
Diag
operationdiagonal
- Rank `k`, where `k >= 1`.Diag
public <T> BatchMatrixDiag<T> batchMatrixDiag(Operand<T> diagonal)
BatchMatrixDiag
operationdiagonal
- BatchMatrixDiag
public <T,U extends Number> BandPart<T> bandPart(Operand<T> input, Operand<U> numLower, Operand<U> numUpper)
BandPart
operationinput
- Rank `k` tensor.numLower
- 0-D tensor. Number of subdiagonals to keep. If negative, keep entirenumUpper
- 0-D tensor. Number of superdiagonals to keep. If negative, keepBandPart
public <T> SelfAdjointEig<T> selfAdjointEig(Operand<T> input, SelfAdjointEig.Options... options)
SelfAdjointEig
operationinput
- `Tensor` input of shape `[N, N]`.options
- carries optional attributes valuesSelfAdjointEig
public <T> BatchMatMul<T> batchMatMul(Operand<T> x, Operand<T> y, BatchMatMul.Options... options)
BatchMatMul
operationx
- 2-D or higher with shape `[..., r_x, c_x]`.y
- 2-D or higher with shape `[..., r_y, c_y]`.options
- carries optional attributes valuesBatchMatMul
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