diff --git a/tensorflow/lite/kernels/reshape.cc b/tensorflow/lite/kernels/reshape.cc
index 7da36a299ea..3cb0742f547 100644
--- a/tensorflow/lite/kernels/reshape.cc
+++ b/tensorflow/lite/kernels/reshape.cc
@@ -31,8 +31,10 @@ constexpr int kInputTensor = 0;
 constexpr int kShapeTensor = 1;
 constexpr int kOutputTensor = 0;
 
-TfLiteStatus ResizeOutput(TfLiteContext* context, TfLiteNode* node,
-                          TfLiteIntArray* output_shape) {
+TfLiteIntArray* GetOutputShape(TfLiteContext*, TfLiteNode*);
+
+TfLiteStatus ResizeOutput(TfLiteContext* context, TfLiteNode* node) {
+  TfLiteIntArray* output_shape = GetOutputShape(context, node);
   std::unique_ptr<TfLiteIntArray, void (*)(TfLiteIntArray*)>
       scoped_output_shape(output_shape, TfLiteIntArrayFree);
 
@@ -65,8 +67,8 @@ TfLiteStatus ResizeOutput(TfLiteContext* context, TfLiteNode* node,
   return context->ResizeTensor(context, output, scoped_output_shape.release());
 }
 
-TfLiteIntArray* GetOutputShapeFromTensor(TfLiteContext* context,
-                                         TfLiteNode* node) {
+inline TfLiteIntArray* GetOutputShapeFromTensor(TfLiteContext* context,
+                                                TfLiteNode* node) {
   const TfLiteTensor* shape = GetInput(context, node, kShapeTensor);
 
   TfLiteIntArray* output_shape = TfLiteIntArrayCreate(shape->dims->data[0]);
@@ -77,8 +79,8 @@ TfLiteIntArray* GetOutputShapeFromTensor(TfLiteContext* context,
   return output_shape;
 }
 
-TfLiteIntArray* GetOutputShapeFromParam(TfLiteContext* context,
-                                        TfLiteNode* node) {
+inline TfLiteIntArray* GetOutputShapeFromParam(TfLiteContext* context,
+                                               TfLiteNode* node) {
   auto* params = reinterpret_cast<TfLiteReshapeParams*>(node->builtin_data);
 
   // The function is returned above this line if the shape tensor is usable.
@@ -99,7 +101,7 @@ TfLiteIntArray* GetOutputShapeFromParam(TfLiteContext* context,
 }
 
 // Check if the shape tensor is valid. Shapes should be int32 vectors.
-bool ShapeIsVector(TfLiteContext* context, TfLiteNode* node) {
+inline bool ShapeIsVector(TfLiteContext* context, TfLiteNode* node) {
   const TfLiteTensor* shape = GetInput(context, node, kShapeTensor);
   return (shape->dims->size == 1 && shape->type == kTfLiteInt32);
 }
@@ -124,8 +126,7 @@ TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) {
   if (output->type != kTfLiteString) {
     if (NumInputs(node) == 1 ||
         IsConstantTensor(GetInput(context, node, kShapeTensor))) {
-      TF_LITE_ENSURE_OK(
-          context, ResizeOutput(context, node, GetOutputShape(context, node)));
+      TF_LITE_ENSURE_OK(context, ResizeOutput(context, node));
     } else {
       SetTensorToDynamic(output);
     }
@@ -141,8 +142,7 @@ TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
   // a string tensor, or its shape cannot be calculated during Prepare(). In
   // either case, we now have all the information to calculate its shape.
   if (IsDynamicTensor(output)) {
-    TF_LITE_ENSURE_OK(
-        context, ResizeOutput(context, node, GetOutputShape(context, node)));
+    TF_LITE_ENSURE_OK(context, ResizeOutput(context, node));
   }
 
   // Note that string tensors are always "dynamic" in the sense that their size