diff --git a/tensorflow/lite/micro/kernels/kelvin/pooling.cc b/tensorflow/lite/micro/kernels/kelvin/pooling.cc
index d343a55..94fc6f2 100644
--- a/tensorflow/lite/micro/kernels/kelvin/pooling.cc
+++ b/tensorflow/lite/micro/kernels/kelvin/pooling.cc
@@ -74,27 +74,34 @@
   TfLiteEvalTensor* output =
       micro::GetEvalOutput(context, node, kPoolingOutputTensor);
 
+  tflite::PoolParams op_params;
+  op_params.stride_height = params->stride_height;
+  op_params.stride_width = params->stride_width;
+  op_params.filter_height = params->filter_height;
+  op_params.filter_width = params->filter_width;
+  op_params.padding_values.height = data->padding.height;
+  op_params.padding_values.width = data->padding.width;
+  op_params.quantized_activation_min = data->activation_min;
+  op_params.quantized_activation_max = data->activation_max;
+  op_params.float_activation_min = data->activation_min_f32;
+  op_params.float_activation_max = data->activation_max_f32;
+
   switch (input->type) {
     case kTfLiteFloat32:
-      MaxPoolingEvalFloat(context, node, params, data, input, output);
+      reference_ops::MaxPool(op_params, tflite::micro::GetTensorShape(input),
+                             tflite::micro::GetTensorData<float>(input),
+                             tflite::micro::GetTensorShape(output),
+                             tflite::micro::GetTensorData<float>(output));
       break;
     case kTfLiteInt8:
-      tflite::PoolParams op_params;
-      op_params.stride_height = params->stride_height;
-      op_params.stride_width = params->stride_width;
-      op_params.filter_height = params->filter_height;
-      op_params.filter_width = params->filter_width;
-      op_params.padding_values.height = data->padding.height;
-      op_params.padding_values.width = data->padding.width;
-      op_params.quantized_activation_min = data->activation_min;
-      op_params.quantized_activation_max = data->activation_max;
       kelvin::opt::MaxPoolS8(
           op_params, tflite::micro::GetTensorShape(input), input->data.int8,
           tflite::micro::GetTensorShape(output), output->data.int8);
       break;
     case kTfLiteInt16:
-      MaxPoolingEvalQuantized<int16_t>(context, node, params, data, input,
-                                       output);
+      kelvin::opt::MaxPoolS16(
+          op_params, tflite::micro::GetTensorShape(input), input->data.i16,
+          tflite::micro::GetTensorShape(output), output->data.i16);
       break;
     default:
       MicroPrintf("Type %s not currently supported.",