diff --git a/.github/workflows/CI.yml b/.github/workflows/CI.yml
index b915502..8187d2b 100644
--- a/.github/workflows/CI.yml
+++ b/.github/workflows/CI.yml
@@ -20,7 +20,6 @@ jobs:
         version:
           - "1"
           - "1.6"
-          - "~1.9.0-0"
     steps:
       - uses: actions/checkout@v3
       - uses: julia-actions/setup-julia@v1
diff --git a/.gitignore b/.gitignore
index 97e3fee..00f723f 100644
--- a/.gitignore
+++ b/.gitignore
@@ -7,3 +7,4 @@
 /docs/Manifest.toml
 /test/coverage/Manifest.toml
 LocalPreferences.toml
+.vscode
diff --git a/Project.toml b/Project.toml
index 5537e03..6b5cc5e 100644
--- a/Project.toml
+++ b/Project.toml
@@ -1,17 +1,16 @@
 name = "LuxTestUtils"
 uuid = "ac9de150-d08f-4546-94fb-7472b5760531"
 authors = ["Avik Pal <avikpal@mit.edu>"]
-version = "0.1.9"
+version = "0.1.10"
 
 [deps]
-AMDGPU = "21141c5a-9bdb-4563-92ae-f87d6854732e"
-Adapt = "79e6a3ab-5dfb-504d-930d-738a2a938a0e"
-CUDA = "052768ef-5323-5732-b1bb-66c8b64840ba"
 ComponentArrays = "b0b7db55-cfe3-40fc-9ded-d10e2dbeff66"
 FiniteDifferences = "26cc04aa-876d-5657-8c51-4c34ba976000"
 ForwardDiff = "f6369f11-7733-5829-9624-2563aa707210"
 Functors = "d9f16b24-f501-4c13-a1f2-28368ffc5196"
 JET = "c3a54625-cd67-489e-a8e7-0a5a0ff4e31b"
+LuxCore = "bb33d45b-7691-41d6-9220-0943567d0623"
+LuxDeviceUtils = "34f89e08-e1d5-43b4-8944-0b49ac560553"
 Optimisers = "3bd65402-5787-11e9-1adc-39752487f4e2"
 Preferences = "21216c6a-2e73-6563-6e65-726566657250"
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
@@ -20,23 +19,20 @@ SparseArrays = "2f01184e-e22b-5df5-ae63-d93ebab69eaf"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 Tracker = "9f7883ad-71c0-57eb-9f7f-b5c9e6d3789c"
 Zygote = "e88e6eb3-aa80-5325-afca-941959d7151f"
-cuDNN = "02a925ec-e4fe-4b08-9a7e-0d78e3d38ccd"
 
 [compat]
-AMDGPU = "0.4"
-Adapt = "3"
-CUDA = "4"
 ComponentArrays = "0.13"
 FiniteDifferences = "0.12"
 ForwardDiff = "0.10"
 Functors = "0.4"
 JET = "0.4, 0.5, 0.6, 0.7, 0.8"
+LuxCore = "0.1"
+LuxDeviceUtils = "0.1"
 Optimisers = "0.2"
 Preferences = "1"
 ReverseDiff = "1"
 Tracker = "0.2"
 Zygote = "0.6"
-cuDNN = "1"
 julia = "1.6"
 
 [extras]
diff --git a/src/LuxTestUtils.jl b/src/LuxTestUtils.jl
index c688096..68a37c7 100644
--- a/src/LuxTestUtils.jl
+++ b/src/LuxTestUtils.jl
@@ -1,92 +1,11 @@
 module LuxTestUtils
 
-using ComponentArrays, Optimisers, Preferences, Test
+using ComponentArrays, Optimisers, Preferences, LuxCore, LuxDeviceUtils, Test
 using ForwardDiff, ReverseDiff, Tracker, Zygote, FiniteDifferences
 # TODO: Yota, Enzyme
 
 const JET_TARGET_MODULES = @load_preference("target_modules", nothing)
 
-### Device Functionalities: REMOVE once moved out of Lux into a separate package
-using Adapt, AMDGPU, CUDA, cuDNN, Functors, Random, SparseArrays
-import Adapt: adapt_storage
-
-const use_cuda = Ref{Union{Nothing, Bool}}(nothing)
-const use_amdgpu = Ref{Union{Nothing, Bool}}(nothing)
-
-abstract type LuxTestUtilsDeviceAdaptor end
-
-struct LuxTestUtilsCPUAdaptor <: LuxTestUtilsDeviceAdaptor end
-struct LuxTestUtilsCUDAAdaptor <: LuxTestUtilsDeviceAdaptor end
-struct LuxTestUtilsAMDGPUAdaptor <: LuxTestUtilsDeviceAdaptor end
-
-adapt_storage(::LuxTestUtilsCUDAAdaptor, x) = cu(x)
-adapt_storage(::LuxTestUtilsCUDAAdaptor, rng::AbstractRNG) = rng
-
-adapt_storage(::LuxTestUtilsAMDGPUAdaptor, x) = roc(x)
-adapt_storage(::LuxTestUtilsAMDGPUAdaptor, rng::AbstractRNG) = rng
-
-function adapt_storage(::LuxTestUtilsCPUAdaptor,
-    x::Union{AbstractRange, SparseArrays.AbstractSparseArray})
-    return x
-end
-adapt_storage(::LuxTestUtilsCPUAdaptor, x::AbstractArray) = adapt(Array, x)
-adapt_storage(::LuxTestUtilsCPUAdaptor, rng::AbstractRNG) = rng
-function adapt_storage(::LuxTestUtilsCPUAdaptor, x::CUSPARSE.AbstractCuSparseMatrix)
-    return adapt(Array, x)
-end
-
-_isbitsarray(::AbstractArray{<:Number}) = true
-_isbitsarray(::AbstractArray{T}) where {T} = isbitstype(T)
-_isbitsarray(x) = false
-
-_isleaf(::AbstractRNG) = true
-_isleaf(x) = _isbitsarray(x) || Functors.isleaf(x)
-
-cpu(x) = fmap(x -> adapt(LuxTestUtilsCPUAdaptor(), x), x)
-
-function cuda_gpu(x)
-    check_use_cuda()
-    return use_cuda[] ? fmap(x -> adapt(LuxTestUtilsCUDAAdaptor(), x), x; exclude=_isleaf) :
-           x
-end
-
-function amdgpu_gpu(x)
-    check_use_amdgpu()
-    return use_amdgpu[] ?
-           fmap(x -> adapt(LuxTestUtilsAMDGPUAdaptor(), x), x; exclude=_isleaf) : x
-end
-
-function check_use_cuda()
-    if use_cuda[] === nothing
-        use_cuda[] = CUDA.functional()
-        if use_cuda[] && !cuDNN.has_cudnn()
-            @warn """CUDA.jl found cuda, but did not find libcudnn. Some functionality
-                     will not be available."""
-        end
-        if !(use_cuda[])
-            @info """The GPU function is being called but the GPU is not accessible.
-                     Defaulting back to the CPU. (No action is required if you want
-                     to run on the CPU).""" maxlog=1
-        end
-    end
-end
-
-function check_use_amdgpu()
-    if use_amdgpu[] === nothing
-        use_amdgpu[] = AMDGPU.functional()
-        if use_amdgpu[] && !AMDGPU.functional(:MIOpen)
-            @warn "MIOpen is not functional in AMDGPU.jl, some functionality will not be \
-                   available." maxlog=1
-        end
-        if !(use_amdgpu[])
-            @info """The GPU function is being called but the GPU is not accessible.
-                     Defaulting back to the CPU. (No action is required if you want
-                     to run on the CPU).""" maxlog=1
-        end
-    end
-end
-### REMOVE once moved out of Lux into a separate package
-
 # JET Testing
 try
     using JET
@@ -182,14 +101,20 @@ end
 struct GradientComputationSkipped end
 
 @generated function check_approx(x::X, y::Y; kwargs...) where {X, Y}
+    device = cpu_device()
     (X == GradientComputationSkipped || Y == GradientComputationSkipped) && return :(true)
-    hasmethod(isapprox, (X, Y)) && return :(isapprox(cpu(x), cpu(y); kwargs...))
+    hasmethod(isapprox, (X, Y)) && return :(isapprox($(device)(x), $(device)(y); kwargs...))
     return quote
         @warn "No `isapprox` method found for types $(X) and $(Y). Using `==` instead."
-        return cpu(x) == cpu(y)
+        return $(device)(x) == $(device)(y)
     end
 end
 
+function check_approx(x::LuxCore.AbstractExplicitLayer,
+    y::LuxCore.AbstractExplicitLayer;
+    kwargs...)
+    return x == y
+end
 check_approx(x::Tuple, y::Tuple; kwargs...) = all(check_approx.(x, y; kwargs...))
 
 function check_approx(x::Optimisers.Leaf, y::Optimisers.Leaf; kwargs...)
@@ -474,14 +399,13 @@ __test_broken(test_type, orig_expr, source) = Test.Broken(test_type, orig_expr)
 
 __correct_arguments(x::AbstractArray) = x
 function __correct_arguments(x::NamedTuple)
-    xc = cpu(x)
+    cpu_dev = cpu_device()
+    gpu_dev = gpu_device()
+    xc = cpu_dev(x)
     ca = ComponentArray(xc)
     # Hacky check to see if there are any non-CPU arrays in the NamedTuple
     typeof(xc) == typeof(x) && return ca
-
-    ca_cuda = cuda_gpu(ca)
-    typeof(ca_cuda) == typeof(x) && return ca_cuda
-    return amdgpu_gpu(ca)
+    return gpu_dev(ca)
 end
 __correct_arguments(x) = x