diff --git a/tensorflow/lite/kernels/detection_postprocess.cc b/tensorflow/lite/kernels/detection_postprocess.cc
index f746ad19498..bbd47081804 100644
--- a/tensorflow/lite/kernels/detection_postprocess.cc
+++ b/tensorflow/lite/kernels/detection_postprocess.cc
@@ -198,7 +198,6 @@ TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) {
                     GetOutputSafe(context, node, kOutputTensorNumDetections,
                                   &num_detections));
   num_detections->type = kTfLiteFloat32;
-  // TODO (chowdhery): Make it a scalar when available
   SetTensorSizes(context, num_detections, {1});
 
   // Temporary tensors
@@ -267,14 +266,12 @@ void DequantizeBoxEncodings(const TfLiteTensor* input_box_encodings, int idx,
 
 template <class T>
 T ReInterpretTensor(const TfLiteTensor* tensor) {
-  // TODO (chowdhery): check float
   const float* tensor_base = GetTensorData<float>(tensor);
   return reinterpret_cast<T>(tensor_base);
 }
 
 template <class T>
 T ReInterpretTensor(TfLiteTensor* tensor) {
-  // TODO (chowdhery): check float
   float* tensor_base = GetTensorData<float>(tensor);
   return reinterpret_cast<T>(tensor_base);
 }
@@ -319,6 +316,7 @@ TfLiteStatus DecodeCenterSizeBoxes(TfLiteContext* context, TfLiteNode* node,
         const float* boxes =
             &(GetTensorData<float>(input_box_encodings)[box_encoding_idx]);
         box_centersize = *reinterpret_cast<const CenterSizeEncoding*>(boxes);
+        TF_LITE_ENSURE_EQ(context, input_anchors->type, kTfLiteFloat32);
         anchor =
             ReInterpretTensor<const CenterSizeEncoding*>(input_anchors)[idx];
         break;
@@ -351,6 +349,7 @@ TfLiteStatus DecodeCenterSizeBoxes(TfLiteContext* context, TfLiteNode* node,
 
     TfLiteTensor* decoded_boxes =
         &context->tensors[op_data->decoded_boxes_index];
+    TF_LITE_ENSURE_EQ(context, decoded_boxes->type, kTfLiteFloat32);
     auto& box = ReInterpretTensor<BoxCornerEncoding*>(decoded_boxes)[idx];
     box.ymin = ycenter - half_h;
     box.xmin = xcenter - half_w;
@@ -438,11 +437,12 @@ TfLiteStatus NonMaxSuppressionSingleClassHelper(
   TF_LITE_ENSURE(context, (intersection_over_union_threshold > 0.0f) &&
                               (intersection_over_union_threshold <= 1.0f));
   // Validate boxes
+  TF_LITE_ENSURE_EQ(context, decoded_boxes->type, kTfLiteFloat32);
   TF_LITE_ENSURE(context, ValidateBoxes(decoded_boxes, num_boxes));
 
   // threshold scores
   std::vector<int> keep_indices;
-  // TODO (chowdhery): Remove the dynamic allocation and replace it
+  // TODO(b/177068807): Remove the dynamic allocation and replace it
   // with temporaries, esp for std::vector<float>
   std::vector<float> keep_scores;
   SelectDetectionsAboveScoreThreshold(
@@ -476,6 +476,7 @@ TfLiteStatus NonMaxSuppressionSingleClassHelper(
     }
     for (int j = i + 1; j < num_boxes_kept; ++j) {
       if (active_box_candidate[j] == 1) {
+        TF_LITE_ENSURE_EQ(context, decoded_boxes->type, kTfLiteFloat32);
         float intersection_over_union = ComputeIntersectionOverUnion(
             decoded_boxes, keep_indices[sorted_indices[i]],
             keep_indices[sorted_indices[j]]);
@@ -607,6 +608,8 @@ TfLiteStatus NonMaxSuppressionMultiClassRegularHelper(TfLiteContext* context,
       const float selected_score =
           scores_after_regular_non_max_suppression[output_box_index];
       // detection_boxes
+      TF_LITE_ENSURE_EQ(context, detection_boxes->type, kTfLiteFloat32);
+      TF_LITE_ENSURE_EQ(context, decoded_boxes->type, kTfLiteFloat32);
       ReInterpretTensor<BoxCornerEncoding*>(detection_boxes)[output_box_index] =
           ReInterpretTensor<const BoxCornerEncoding*>(
               decoded_boxes)[anchor_index];
@@ -615,6 +618,7 @@ TfLiteStatus NonMaxSuppressionMultiClassRegularHelper(TfLiteContext* context,
       // detection_scores
       GetTensorData<float>(detection_scores)[output_box_index] = selected_score;
     } else {
+      TF_LITE_ENSURE_EQ(context, detection_boxes->type, kTfLiteFloat32);
       ReInterpretTensor<BoxCornerEncoding*>(
           detection_boxes)[output_box_index] = {0.0f, 0.0f, 0.0f, 0.0f};
       // detection_classes
@@ -705,6 +709,8 @@ TfLiteStatus NonMaxSuppressionMultiClassFastHelper(TfLiteContext* context,
     for (int col = 0; col < num_categories_per_anchor; ++col) {
       int box_offset = num_categories_per_anchor * output_box_index + col;
       // detection_boxes
+      TF_LITE_ENSURE_EQ(context, detection_boxes->type, kTfLiteFloat32);
+      TF_LITE_ENSURE_EQ(context, decoded_boxes->type, kTfLiteFloat32);
       ReInterpretTensor<BoxCornerEncoding*>(detection_boxes)[box_offset] =
           ReInterpretTensor<const BoxCornerEncoding*>(
               decoded_boxes)[selected_index];
@@ -782,7 +788,7 @@ TfLiteStatus NonMaxSuppressionMultiClass(TfLiteContext* context,
 }
 
 TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
-  // TODO(chowdhery): Generalize for any batch size
+  // TODO(b/177068051):  Generalize for any batch size.
   TF_LITE_ENSURE(context, (kBatchSize == 1));
   auto* op_data = static_cast<OpData*>(node->user_data);
   // These two functions correspond to two blocks in the Object Detection model.