@@ -20,12 +20,12 @@ For arrays `a` and `b`, perform elementwise multiplication.
2020julia> a = [2, 3]; b = [5, 7];
2121
2222julia> a ⊙ b
23- 2-element Array {$Int ,1 }:
23+ 2-element Vector {$Int }:
2424 10
2525 21
2626
2727julia> a ⊙ [5]
28- ERROR: DimensionMismatch(" Axes of `A` and `B` must match, got (Base.OneTo(2),) and (Base.OneTo(1),)" )
28+ ERROR: DimensionMismatch: Axes of `A` and `B` must match, got (Base.OneTo(2),) and (Base.OneTo(1),)
2929[...]
3030```
3131
@@ -74,7 +74,7 @@ For vectors `v` and `w`, the Kronecker product is related to the tensor product
7474julia> a = [2, 3]; b = [5, 7, 11];
7575
7676julia> a ⊗ b
77- 2×3 Array {$Int ,2 }:
77+ 2×3 Matrix {$Int }:
7878 10 14 22
7979 15 21 33
8080```
@@ -164,13 +164,13 @@ and hence may sometimes return another `Adjoint` vector. (And similarly for `Tra
164164julia> M = rand(5,5); v = rand(5);
165165
166166julia> typeof(v ⊡ M')
167- Array{Float64,1}
167+ Vector{Float64} (alias for Array{Float64, 1})
168168
169169julia> typeof(M ⊡ v') # adjoint of the previous line
170- Adjoint{Float64,Array {Float64,1 }}
170+ LinearAlgebra. Adjoint{Float64, Vector {Float64}}
171171
172172julia> typeof(v' ⊡ M') # same as *, and equal to adjoint(M ⊡ v)
173- Adjoint{Float64,Array {Float64,1 }}
173+ LinearAlgebra. Adjoint{Float64, Vector {Float64}}
174174
175175julia> typeof(v' ⊡ v)
176176Float64
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