diff --git a/Project.toml b/Project.toml
index f5a8fb6a5..ccf2fe03a 100644
--- a/Project.toml
+++ b/Project.toml
@@ -1,7 +1,7 @@
 name = "Lux"
 uuid = "b2108857-7c20-44ae-9111-449ecde12c47"
 authors = ["Avik Pal <avikpal@mit.edu> and contributors"]
-version = "0.4.30"
+version = "0.4.31"
 
 [deps]
 Adapt = "79e6a3ab-5dfb-504d-930d-738a2a938a0e"
diff --git a/src/layers/dropout.jl b/src/layers/dropout.jl
index 660147323..deb15a5ad 100644
--- a/src/layers/dropout.jl
+++ b/src/layers/dropout.jl
@@ -48,7 +48,7 @@ function Dropout(p; dims=:)
     return Dropout(p, 1 / (1 - p), dims)
 end
 
-function (d::Dropout{T})(x::AbstractArray{T}, ps, st::NamedTuple) where {T}
+function (d::Dropout)(x, ps, st::NamedTuple)
     y, _, rng = LuxLib.dropout(st.rng, x, d.p, st.training; invp=d.q, d.dims)
     return y, merge(st, (; rng))
 end
@@ -113,7 +113,7 @@ function VariationalHiddenDropout(p; dims=:)
     return VariationalHiddenDropout(p, 1 / (1 - p), dims)
 end
 
-function (d::VariationalHiddenDropout{T})(x::AbstractArray{T}, ps, st::NamedTuple) where {T}
+function (d::VariationalHiddenDropout)(x, ps, st::NamedTuple)
     _mask = st.mask === nothing ? x : st.mask
     y, mask, rng = LuxLib.dropout(st.rng, x, _mask, d.p, st.training, st.update_mask;
                                   invp=d.q, d.dims)
diff --git a/test/layers/dropout.jl b/test/layers/dropout.jl
index dc3d9f504..6a45d0f21 100644
--- a/test/layers/dropout.jl
+++ b/test/layers/dropout.jl
@@ -5,8 +5,8 @@ include("../test_utils.jl")
 rng = Random.default_rng()
 Random.seed!(rng, 0)
 
-@testset "Dropout" begin
-    layer = Dropout(0.5f0)
+@testset "Dropout" begin for p in (0.5f0, 0.5)
+    layer = Dropout(p)
     display(layer)
     ps, st = Lux.setup(rng, layer)
     x = randn(Float32, 5, 2)
@@ -27,10 +27,10 @@ Random.seed!(rng, 0)
     st = Lux.testmode(st)
 
     @test first(layer(x, ps, st)) == x
-end
+end end
 
-@testset "VariationalHiddenDropout" begin
-    layer = VariationalHiddenDropout(0.5f0)
+@testset "VariationalHiddenDropout" begin for p in (0.5f0, 0.5)
+    layer = VariationalHiddenDropout(p)
     display(layer)
     ps, st = Lux.setup(rng, layer)
     x = randn(Float32, 5, 2)
@@ -61,4 +61,4 @@ end
     run_JET_tests(layer, x, ps, st__)
     test_gradient_correctness_fdm(x -> sum(layer(x, ps, st__)[1]), x; atol=1.0f-3,
                                   rtol=1.0f-3)
-end
+end end