TensorCore.hadamard! — Functionhadamard!(dest, A, B)Similar to hadamard(A, B) (which can also be written A ⊙ B), but stores its results in the pre-allocated array dest.
See also hadamard!(y, a, b).
TensorCore.hadamard! — Functionhadamard!(dest, A, B)Similar to hadamard(A, B) (which can also be written A ⊙ B), but stores its results in the pre-allocated array dest.
TensorCore.tensor — Functiontensor(A, B)
+[...]See also hadamard!(y, a, b).
TensorCore.hadamard! — Functionhadamard!(dest, A, B)Similar to hadamard(A, B) (which can also be written A ⊙ B), but stores its results in the pre-allocated array dest.
TensorCore.tensor — Functiontensor(A, B)
A ⊗ BCompute the tensor product of A and B. If C = A ⊗ B, then C[i1, ..., im, j1, ..., jn] = A[i1, ... im] * B[j1, ..., jn].
For vectors v and w, the Kronecker product is related to the tensor product by kron(v,w) == vec(w ⊗ v) or w ⊗ v == reshape(kron(v,w), (length(w), length(v))).
Examples
julia> a = [2, 3]; b = [5, 7, 11];
julia> a ⊗ b
2×3 Matrix{Int64}:
10 14 22
- 15 21 33See also tensor!(Y,A,B).
TensorCore.tensor! — Functiontensor!(dest, A, B)Similar to tensor(A, B) (which can also be written A ⊗ B), but stores its results in the pre-allocated array dest.
TensorCore.boxdot — Functionboxdot(A,B) = A ⊡ B # \boxdotGeneralised matrix multiplication: Contracts the last dimension of A with the first dimension of B, for any ndims(A) & ndims(B). If both are vectors, then it returns a scalar == sum(A .* B).
Examples
julia> A = rand(3,4,5); B = rand(5,6,7);
+ 15 21 33See also tensor!(Y,A,B).
TensorCore.tensor! — Functiontensor!(dest, A, B)Similar to tensor(A, B) (which can also be written A ⊗ B), but stores its results in the pre-allocated array dest.
TensorCore.boxdot — Functionboxdot(A,B) = A ⊡ B # \boxdotGeneralised matrix multiplication: Contracts the last dimension of A with the first dimension of B, for any ndims(A) & ndims(B). If both are vectors, then it returns a scalar == sum(A .* B).
Examples
julia> A = rand(3,4,5); B = rand(5,6,7);
julia> size(A ⊡ B)
(3, 4, 6, 7)
@@ -36,4 +36,4 @@
LinearAlgebra.Adjoint{Float64, Vector{Float64}}
julia> typeof(v' ⊡ v)
-Float64See also boxdot!(Y,A,B), which is to ⊡ as mul! is to *.
TensorCore.boxdot! — Functionboxdot!(Y, A, B, α=1, β=0)In-place version of boxdot, i.e. Y .= (A ⊡ B) .* β .+ Y .* α. Like 5-argument mul!, the use of α, β here requires Julia 1.3 or later.
Settings
This document was generated with Documenter.jl on Tuesday 4 June 2024. Using Julia version 1.10.4.