From 898419e18d4dfed3df80eaa5cf732e56c0d4c90c Mon Sep 17 00:00:00 2001 From: "Documenter.jl" Date: Tue, 4 Jun 2024 20:43:24 +0000 Subject: [PATCH] build based on f8bc400 --- dev/index.html | 6 +++--- dev/search/index.html | 2 +- 2 files changed, 4 insertions(+), 4 deletions(-) diff --git a/dev/index.html b/dev/index.html index 6b09fbb..5f5f21b 100644 --- a/dev/index.html +++ b/dev/index.html @@ -9,13 +9,13 @@ julia> a ⊙ [5] ERROR: DimensionMismatch: Axes of `A` and `B` must match, got (Base.OneTo(2),) and (Base.OneTo(1),) -[...]

See also hadamard!(y, a, b).

source
TensorCore.hadamard! — Function
hadamard!(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.

source
TensorCore.tensor — Function
tensor(A, B)
+[...]

See also hadamard!(y, a, b).

source
TensorCore.hadamard! — Function
hadamard!(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.

source
TensorCore.tensor — Function
tensor(A, B)
 A ⊗ B

Compute 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  33

See also tensor!(Y,A,B).

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TensorCore.tensor! — Function
tensor!(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.

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TensorCore.boxdot — Function
boxdot(A,B) = A ⊡ B    # \boxdot

Generalised 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  33

See also tensor!(Y,A,B).

source
TensorCore.tensor! — Function
tensor!(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.

source
TensorCore.boxdot — Function
boxdot(A,B) = A ⊡ B    # \boxdot

Generalised 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)
-Float64

See also boxdot!(Y,A,B), which is to ⊡ as mul! is to *.

source
TensorCore.boxdot! — Function
boxdot!(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.

source
+Float64

See also boxdot!(Y,A,B), which is to ⊡ as mul! is to *.

source
TensorCore.boxdot! — Function
boxdot!(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.

source
diff --git a/dev/search/index.html b/dev/search/index.html index 9b2c336..c5f3abe 100644 --- a/dev/search/index.html +++ b/dev/search/index.html @@ -1,2 +1,2 @@ -Search · TensorCore.jl

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    +Search · TensorCore.jl

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