diff --git a/tensorflow/lite/kernels/conv.cc b/tensorflow/lite/kernels/conv.cc
index 73340a7df3e..7899e06ded6 100644
--- a/tensorflow/lite/kernels/conv.cc
+++ b/tensorflow/lite/kernels/conv.cc
@@ -749,11 +749,12 @@ void EvalFloat(TfLiteContext* context, TfLiteNode* node,
 }
 
 template <KernelType kernel_type>
-void EvalHybridPerChannel(TfLiteContext* context, TfLiteNode* node,
-                          TfLiteConvParams* params, OpData* data,
-                          TfLiteTensor* input, TfLiteTensor* filter,
-                          TfLiteTensor* bias, TfLiteTensor* im2col,
-                          TfLiteTensor* output) {
+TfLiteStatus EvalHybridPerChannel(TfLiteContext* context, TfLiteNode* node,
+                                  TfLiteConvParams* params, OpData* data,
+                                  const TfLiteTensor* input,
+                                  const TfLiteTensor* filter,
+                                  const TfLiteTensor* bias,
+                                  TfLiteTensor* im2col, TfLiteTensor* output) {
   float output_activation_min, output_activation_max;
   CalculateActivationRange(params->activation, &output_activation_min,
                            &output_activation_max);
@@ -917,8 +918,9 @@ TfLiteStatus EvalImpl(TfLiteContext* context, TfLiteNode* node) {
     case kTfLiteFloat32:
       if (filter->type == kTfLiteUInt8 || filter->type == kTfLiteInt8) {
         if (data->is_hybrid_per_channel) {
-          EvalHybridPerChannel<kernel_type>(context, node, params, data, input,
-                                            filter, bias, im2col, output);
+          TF_LITE_ENSURE_OK(context, EvalHybridPerChannel<kernel_type>(
+                                         context, node, params, data, input,
+                                         filter, bias, im2col, output));
         } else {
           TfLiteTensor* accum_scratch =
               &context->tensors[node->temporaries