forked from kscience/kmath
fixes
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@ -145,7 +145,7 @@ public interface TensorAlgebra<T> {
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/**
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/**
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* Numerical negative, element-wise.
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* Numerical negative, element-wise.
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*
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*
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* @return tensor - negation of the original tensor.
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* @return tensor negation of the original tensor.
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*/
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*/
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public operator fun TensorStructure<T>.unaryMinus(): TensorStructure<T>
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public operator fun TensorStructure<T>.unaryMinus(): TensorStructure<T>
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@ -209,8 +209,8 @@ public interface TensorAlgebra<T> {
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* If the second argument is 1-dimensional, a 1 is appended to its dimension for the purpose of the batched matrix
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* If the second argument is 1-dimensional, a 1 is appended to its dimension for the purpose of the batched matrix
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* multiple and removed after.
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* multiple and removed after.
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* The non-matrix (i.e. batch) dimensions are broadcasted (and thus must be broadcastable).
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* The non-matrix (i.e. batch) dimensions are broadcasted (and thus must be broadcastable).
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* For example, if `input` is a (j \times 1 \times n \times n) tensor and `other` is a
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* For example, if `input` is a (j × 1 × n × n) tensor and `other` is a
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* (k \times n \times n) tensor, out will be a (j \times k \times n \times n) tensor.
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* (k × n × n) tensor, out will be a (j × k × n × n) tensor.
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*
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*
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* For more information: https://pytorch.org/docs/stable/generated/torch.matmul.html
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* For more information: https://pytorch.org/docs/stable/generated/torch.matmul.html
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*
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*
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@ -227,17 +227,17 @@ public interface TensorAlgebra<T> {
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*
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*
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* The argument [offset] controls which diagonal to consider:
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* The argument [offset] controls which diagonal to consider:
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* 1. If [offset] = 0, it is the main diagonal.
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* 1. If [offset] = 0, it is the main diagonal.
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* 2. If [offset] > 0, it is above the main diagonal.
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* 1. If [offset] > 0, it is above the main diagonal.
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* 3. If [offset] < 0, it is below the main diagonal.
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* 1. If [offset] < 0, it is below the main diagonal.
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*
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*
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* The size of the new matrix will be calculated
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* The size of the new matrix will be calculated
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* to make the specified diagonal of the size of the last input dimension.
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* to make the specified diagonal of the size of the last input dimension.
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* For more information: https://pytorch.org/docs/stable/generated/torch.diag_embed.html
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* For more information: https://pytorch.org/docs/stable/generated/torch.diag_embed.html
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*
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*
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* @param diagonalEntries - the input tensor. Must be at least 1-dimensional.
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* @param diagonalEntries the input tensor. Must be at least 1-dimensional.
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* @param offset - which diagonal to consider. Default: 0 (main diagonal).
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* @param offset which diagonal to consider. Default: 0 (main diagonal).
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* @param dim1 - first dimension with respect to which to take diagonal. Default: -2.
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* @param dim1 first dimension with respect to which to take diagonal. Default: -2.
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* @param dim2 - second dimension with respect to which to take diagonal. Default: -1.
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* @param dim2 second dimension with respect to which to take diagonal. Default: -1.
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*
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*
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* @return tensor whose diagonals of certain 2D planes (specified by [dim1] and [dim2])
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* @return tensor whose diagonals of certain 2D planes (specified by [dim1] and [dim2])
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* are filled by [diagonalEntries]
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* are filled by [diagonalEntries]
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