LazyArrays.jl
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JuliaArrays
Lazy arrays and linear algebra in Julia
This is a feature request to get LazyArrays to work with CuArrays (and potentially other GPUArray implementations) Some of the features of LazyArrays works with CuArrays out of the box,...
I came across some strange behaviour which I was able to break down to the following: ```julia julia> using LazyArrays julia> A = zeros(Rational{Int64}, 2, 2); julia> B = zeros(Rational{Int64},...
I don't see any reason why the following shouldn't be allowed: ```julia ApplyArray(hcat, Fill([1,2], 100_000)) ``` for a lazy, very large array. (compose with broadcasting for more interesting examples)
I think this is a bug? I get incorrect behavior for a non-broadcasted LazyArray ```julia julia> a = 1.0; A = randn(10,10); LazyArray(@~ a*A) (Float64) * (10×10 Matrix{Float64}): 0.35979 -1.16647...
Trying to build a lazy rank one matrix, I get an error ```julia julia> x = ones(2) 2-element Vector{Float64}: 1.0 1.0 julia> a = @~ x * x' Applied(*,[1.0, 1.0],[1.0...
```julia julia> x = 1 julia> a = @~ -x * [1, 2]; ERROR: BoundsError: attempt to access Tuple{} at index [2] Stacktrace: [1] getindex(t::Tuple, i::Int64) @ Base ./tuple.jl:29 [2]...
Hey, I encountered issues with a custom array type. I tried to reduce it to a MWE :confused: I'm using Julia 1.6.0 and LazyArrays 0.21.3. The `dot.(a,a)` works itself, but...
This works: ```julia julia> a = ones(2,2); julia> LazyArray(@~ @. a * 2) (2×2 Array{Float64,2}) .* (Int64): 2.0 2.0 2.0 2.0 ``` but attempting to create the array directly in...
Hi, here are some benchmark, seems there are inefficient allocations when using complex values: ``` using LazyArrays using BenchmarkTools spd=ones(1000,1000) A=ones(2,2) B=kron(spd,A) Bi=kron(spd,im*A) Bla = ApplyArray(kron, spd, A) Blai =...
