A few more small fixes for upstream + CUDA (#373)

* Small fixes for upstream + CUDA

* Suggestion

* Use default memory

* Have Base.ones and zeros accept CuArray

* Try to finagle ones and zeros again

* Fix CUDA test

Author: kshyatt

ext/TensorKitCUDAExt/cutensormap.jl

@@ -138,6 +138,10 @@ function Base.promote_rule(
     return CuTensorMap{T, S, N₁, N₂}
 end
 
+TensorKit.promote_storage_rule(::Type{CuArray{T, N}}, ::Type{<:CuArray{T, N}}) where {T, N} =
+    CuArray{T, N, CUDA.default_memory}
+
+
 # CuTensorMap exponentation:
 function TensorKit.exp!(t::CuTensorMap)
     domain(t) == codomain(t) ||

test/cuda/tensors.jl

@@ -55,6 +55,14 @@ for V in spacelist
                 @test domain(t) == one(W)
                 @test typeof(t) == TensorMap{Float64, spacetype(t), 5, 0, CuVector{Float64, CUDA.DeviceMemory}}
             end
+            for f in (Base.ones, Base.zeros)
+                t = @constinferred f(CuVector{Float64, CUDA.DeviceMemory}, W)
+                @test scalartype(t) == Float64
+                @test codomain(t) == W
+                @test space(t) == (W ← one(W))
+                @test domain(t) == one(W)
+                @test typeof(t) == TensorMap{Float64, spacetype(t), 5, 0, CuVector{Float64, CUDA.DeviceMemory}}
+            end
             for f in (rand, randn)
                 t = @constinferred f(CuVector{Float64, CUDA.DeviceMemory}, W)
                 @test scalartype(t) == Float64

test/tensors/tensors.jl

@@ -44,6 +44,15 @@ for V in spacelist
                 @test space(t) == (W ← one(W))
                 @test domain(t) == one(W)
                 @test typeof(t) == TensorMap{T, spacetype(t), 5, 0, Vector{T}}
+                # Array type input
+                t = @constinferred zeros(Vector{T}, W)
+                @test @constinferred(hash(t)) == hash(deepcopy(t))
+                @test scalartype(t) == T
+                @test norm(t) == 0
+                @test codomain(t) == W
+                @test space(t) == (W ← one(W))
+                @test domain(t) == one(W)
+                @test typeof(t) == TensorMap{T, spacetype(t), 5, 0, Vector{T}}
                 # blocks
                 bs = @constinferred blocks(t)
                 if !isempty(blocksectors(t)) # multifusion space ending on module gives empty data