diff --git a/tensorflow/core/tpu/tpu_embedding_optimization_parameters_utils.cc b/tensorflow/core/tpu/tpu_embedding_optimization_parameters_utils.cc
index e39b1d6e1bd..915348b8e23 100644
--- a/tensorflow/core/tpu/tpu_embedding_optimization_parameters_utils.cc
+++ b/tensorflow/core/tpu/tpu_embedding_optimization_parameters_utils.cc
@@ -252,7 +252,7 @@ Status GetOptimizationAlgorithmStateVariables(
     StateVariableSpecification gradient_acc;
     gradient_acc.set_name("gradient_accumulators");
     gradient_acc.mutable_fill_with_constant()->set_initial_value(
-        kGradientAccumulatorInitialValue);
+        GradientAccumulatorInitialValue());
     state_variables->push_back(std::move(gradient_acc));
   }
   if (state_variables->size() > kMaxAuxiliaryParameterCount + 1) {
diff --git a/tensorflow/core/tpu/tpu_embedding_optimization_parameters_utils.h b/tensorflow/core/tpu/tpu_embedding_optimization_parameters_utils.h
index e7516da8f39..320863d19be 100644
--- a/tensorflow/core/tpu/tpu_embedding_optimization_parameters_utils.h
+++ b/tensorflow/core/tpu/tpu_embedding_optimization_parameters_utils.h
@@ -84,7 +84,9 @@ static constexpr int kMaxAuxiliaryParameterCount = 3;
 // not no-ops on zero gradients, so we need to distinguish an accumulated
 // gradient of zero from one that has been cleared after its gradients have
 // already been applied to the parameters and accumulators.
-const float kGradientAccumulatorInitialValue = absl::bit_cast<float, uint32>(1);
+inline float GradientAccumulatorInitialValue() {
+  return absl::bit_cast<float, uint32>(1);
+}
 
 // Computes registration data for per table load Op. Each load Op transfers
 // the embedding parameters from the host memory to the TPU memory.