diff --git a/src/Tensors.jl b/src/Tensors.jl
index 40f95c46..287487dc 100644
--- a/src/Tensors.jl
+++ b/src/Tensors.jl
@@ -4,6 +4,8 @@ module Tensors
 
 import Base.@pure
 
+import ForwardDiff: Dual, partials, value, Tag
+
 import Statistics
 using Statistics: mean
 using LinearAlgebra
diff --git a/src/automatic_differentiation.jl b/src/automatic_differentiation.jl
index 6d8aeb64..f34cac56 100644
--- a/src/automatic_differentiation.jl
+++ b/src/automatic_differentiation.jl
@@ -1,5 +1,3 @@
-import ForwardDiff: Dual, partials, value, Tag
-
 @static if isdefined(LinearAlgebra, :gradient)
     import LinearAlgebra.gradient
 end
diff --git a/src/eigen.jl b/src/eigen.jl
index 0f9e98e4..4372f8cd 100644
--- a/src/eigen.jl
+++ b/src/eigen.jl
@@ -1,3 +1,7 @@
+# Support functions
+get_max_iterations(::Type{T}) where{T} = 2 * (1 + precision(T) - exponent(floatmin(T)))
+get_max_iterations(::Type{T}) where{T<:Dual{TT,VT}} where{TT,VT} = get_max_iterations(VT)
+
 # MIT License: Copyright (c) 2016: Andy Ferris.
 # See LICENSE.md for further licensing test
 
@@ -134,7 +138,7 @@ function LinearAlgebra.eigen(R::SymmetricTensor{2,3,T′}) where T′
     b22 = a22
 
     # Givens reflections, B' = G^T * B * G, preserve tridiagonal matrices
-    max_iteration = 2 * (1 + precision(T) - exponent(floatmin(T)))
+    max_iteration = get_max_iterations(T)
 
     if abs(b12) <= abs(b01)
         saveB00, saveB01, saveB11 = b00, b01, b11