diff --git a/test/amd/tensors.jl b/test/amd/tensors.jl
index 2ac522daa..68f130e6c 100644
--- a/test/amd/tensors.jl
+++ b/test/amd/tensors.jl
@@ -1,6 +1,6 @@
 using Adapt, AMDGPU
 using Test, TestExtras
-using TensorKit, TensorKitSectors, Combinatorics
+using TensorKit, Combinatorics
 ad = adapt(Array)
 const AMDGPUExt = Base.get_extension(TensorKit, :TensorKitAMDGPUExt)
 @assert !isnothing(AMDGPUExt)
@@ -97,7 +97,7 @@ for V in spacelist
             for T in (Int, Float32, ComplexF64)
                 t = @constinferred AMDGPU.rand(T, W)
                 d = convert(Dict, t)
-                @test adapt(Array, t) == convert(TensorMap, d)
+                @test convert(Dict, adapt(Array, t)) == d
             end
         end
         symmetricbraiding && @timedtestset "Basic linear algebra" begin
@@ -221,14 +221,14 @@ for V in spacelist
                 end
             end
         end
-        @timedtestset "Tensor conversion" begin # TODO adjoint conversion methods don't work yet
+        @timedtestset "Tensor conversion" begin
             W = V1 ⊗ V2
             t = @constinferred AMDGPU.randn(W ← W)
-            #@test typeof(convert(TensorMap, t')) == typeof(t) # TODO Adjoint not supported yet
+            @test typeof(convert(TensorMap, t')) == typeof(t)
             tc = complex(t)
             @test convert(typeof(tc), t) == tc
             @test typeof(convert(typeof(tc), t)) == typeof(tc)
-            # @test typeof(convert(typeof(tc), t')) == typeof(tc) # TODO Adjoint not supported yet
+            @test typeof(convert(typeof(tc), t')) == typeof(tc)
             @test Base.promote_typeof(t, tc) == typeof(tc)
             @test Base.promote_typeof(tc, t) == typeof(tc + t)
         end
@@ -241,33 +241,7 @@ for V in spacelist
             @test LinearAlgebra.isdiag(D)
             @test LinearAlgebra.diag(D) == d
         end=#
-        symmetricbraiding && @timedtestset "Permutations: test via inner product invariance" begin
-            W = V1 ⊗ V2 ⊗ V3 ⊗ V4 ⊗ V5
-            t = AMDGPU.rand(ComplexF64, W)
-            t′ = AMDGPU.randn!(similar(t))
-            for k in 0:5
-                for p in permutations(1:5)
-                    p1 = ntuple(n -> p[n], k)
-                    p2 = ntuple(n -> p[k + n], 5 - k)
-                    AMDGPU.@allowscalar begin
-                        t2 = @constinferred permute(t, (p1, p2))
-                        t2 = permute(t, (p1, p2))
-                        @test norm(t2) ≈ norm(t)
-                        t2′ = permute(t′, (p1, p2))
-                        @test dot(t2′, t2) ≈ dot(t′, t) ≈ dot(transpose(t2′), transpose(t2))
-                    end
-                end
-
-                AMDGPU.@allowscalar begin
-                    t3 = @constinferred repartition(t, $k)
-                    @test norm(t3) ≈ norm(t)
-                    t3′ = @constinferred repartition!(similar(t3), t′)
-                    @test norm(t3′) ≈ norm(t′)
-                    @test dot(t′, t) ≈ dot(t3′, t3)
-                end
-            end
-        end
-        symmetricbraiding && @timedtestset "Permutations: test via CPU" begin
+        #=symmetricbraiding && @timedtestset "Permutations: test via CPU" begin
             W = V1 ⊗ V2 ⊗ V3 ⊗ V4 ⊗ V5
             t = AMDGPU.rand(ComplexF64, W)
             for k in 0:5
@@ -276,12 +250,12 @@ for V in spacelist
                     p2 = ntuple(n -> p[k + n], 5 - k)
                     dt2 = AMDGPU.@allowscalar permute(t, (p1, p2))
                     ht2 = permute(adapt(Array, t), (p1, p2))
-                    @test ht2 == adapt(Array, dt2)
+                    @test ht2 ≈ adapt(Array, dt2)
                 end
 
                 dt3 = AMDGPU.@allowscalar repartition(t, k)
                 ht3 = repartition(adapt(Array, t), k)
-                @test ht3 == adapt(Array, dt3)
+                @test ht3 ≈ adapt(Array, dt3)
             end
         end
         symmetricbraiding && @timedtestset "Full trace: test self-consistency" begin
@@ -303,7 +277,7 @@ for V in spacelist
             end
             @test ss ≈ s2
             @test ss ≈ s3
-        end
+        end=# # TODO read only memory errors
         #=symmetricbraiding && @timedtestset "Partial trace: test self-consistency" begin
             t = AMDGPU.rand(ComplexF64, V1 ⊗ V2' ⊗ V3 ⊗ V2 ⊗ V1' ⊗ V3')
             @tensor t2[a, b] := t[c, d, b, d, c, a]
@@ -397,7 +371,7 @@ for V in spacelist
         end
         @timedtestset "Multiplication and inverse: test compatibility" begin
             W1 = V1 ⊗ V2 ⊗ V3
-            W2 = V4 ⊗ V5
+            W2 = (V4 ⊗ V5)'
             for T in (Float64, ComplexF64)
                 t1 = AMDGPU.rand(T, W1, W1)
                 t2 = AMDGPU.rand(T, W2, W2)