From 165c8c5dbd8ac183bd322266798321adb4886f45 Mon Sep 17 00:00:00 2001
From: Elena Zhelezina <elena.zhelezina@arm.com>
Date: Thu, 4 Jun 2020 11:05:48 +0100
Subject: [PATCH] Addressed reviewer's comments.

Change-Id: If8022418adcc6b6a93354625476f32155dd53d36
---
 tensorflow/lite/kernels/pad.cc | 40 +++++-----------------------------
 1 file changed, 5 insertions(+), 35 deletions(-)

diff --git a/tensorflow/lite/kernels/pad.cc b/tensorflow/lite/kernels/pad.cc
index 4a4668c9634..4c4caeea853 100644
--- a/tensorflow/lite/kernels/pad.cc
+++ b/tensorflow/lite/kernels/pad.cc
@@ -120,8 +120,8 @@ TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) {
 }
 
 template <typename integer_type>
-TfLiteStatus EvalSignedInt(TfLiteContext* context, const PadContext& op_context,
-                           const tflite::PadParams& op_params) {
+TfLiteStatus EvalInt(TfLiteContext* context, const PadContext& op_context,
+                     const tflite::PadParams& op_params) {
   integer_type pad_value;
   if (op_context.constant_values == nullptr) {
     // Quantized Pad requires that 0 is represented in the quantized
@@ -211,43 +211,13 @@ TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
       }
     } break;
     case kTfLiteUInt8: {
-      uint8_t pad_value;
-      if (op_context.constant_values == nullptr) {
-        // Quantized Pad requires that 0 is represented in the quantized
-        // range.
-        TF_LITE_ENSURE(context, op_context.output->params.zero_point >=
-                                    std::numeric_limits<uint8_t>::min());
-        TF_LITE_ENSURE(context, op_context.output->params.zero_point <=
-                                    std::numeric_limits<uint8_t>::max());
-        pad_value = static_cast<uint8_t>(op_context.output->params.zero_point);
-      } else {
-        // Quantized Pad requires that 'constant_values' is represented in the
-        // same quantized range as the input and output tensors.
-        TF_LITE_ENSURE_EQ(context, op_context.output->params.zero_point,
-                          op_context.constant_values->params.zero_point);
-        TF_LITE_ENSURE_EQ(context, op_context.output->params.scale,
-                          op_context.constant_values->params.scale);
-        pad_value = *GetTensorData<uint8_t>(op_context.constant_values);
-      }
-      if (kernel_type == kReference) {
-        if (op_context.resizing_category == ResizingCategory::kImageStyle) {
-          TF_LITE_PAD(reference_ops, PadImageStyle, uint8_t, pad_value);
-        } else {
-          TF_LITE_PAD(reference_ops, Pad, uint8_t, pad_value);
-        }
-      } else if (kernel_type == kGenericOptimized) {
-        if (op_context.resizing_category == ResizingCategory::kImageStyle) {
-          TF_LITE_PAD(optimized_ops, PadImageStyle, uint8_t, pad_value);
-        } else {
-          TF_LITE_PAD(optimized_ops, Pad, uint8_t, pad_value);
-        }
-      }
+      EvalInt<uint8_t>(context, op_context, op_params);
     } break;
     case kTfLiteInt8: {
-      EvalSignedInt<int8_t>(context, op_context, op_params);
+      EvalInt<int8_t>(context, op_context, op_params);
     } break;
     case kTfLiteInt16: {
-      EvalSignedInt<int16_t>(context, op_context, op_params);
+      EvalInt<int16_t>(context, op_context, op_params);
     } break;
     case kTfLiteInt32: {
       int32_t pad_value =