Use consistent const-tensor checks

@tensorflow/micro

Use consistent const-tensor checks and error messages across these kernels:

PAD
RESIZE_BILINEAR
RESIZE_NEAREST_NEIGHBOR
SPLIT_V
SPLIT

bug=fixes #3138

Author: ddavis-2015

tensorflow/lite/micro/kernels/pad_common.cc

@@ -69,7 +69,8 @@ TfLiteStatus PadPrepare(TfLiteContext* context, TfLiteNode* node) {
   // On Micro, outputs must be properly sized by the converter.
   // NOTE: This data is only available because the paddings buffer is stored in
   // the flatbuffer:
-  TF_LITE_ENSURE(context, IsConstantTensor(paddings));
+  TF_LITE_ENSURE_MSG(context, IsConstantTensor(paddings),
+                     "Non-constant >paddings< tensor is not supported");
   const int32_t* paddings_data = GetTensorData<int32_t>(paddings);
   for (int i = 0; i < output->dims->size; i++) {
     int output_dim = output->dims->data[i];

tensorflow/lite/micro/kernels/resize_bilinear.cc

@@ -1,4 +1,4 @@
-/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+/* Copyright 2025 The TensorFlow Authors. All Rights Reserved.
 
 Licensed under the Apache License, Version 2.0 (the "License");
 you may not use this file except in compliance with the License.
@@ -50,7 +50,7 @@ TfLiteStatus ResizeBilinearPrepare(TfLiteContext* context, TfLiteNode* node) {
   output->type = input->type;
 
   TF_LITE_ENSURE_MSG(context, IsConstantTensor(size),
-                     "Non constant size tensor not supported");
+                     "Non-constant >size< tensor is not supported");
 
   // Ensure params are valid.
   auto* params =

tensorflow/lite/micro/kernels/resize_nearest_neighbor.cc

@@ -1,4 +1,4 @@
-/* Copyright 2023 The TensorFlow Authors. All Rights Reserved.
+/* Copyright 2025 The TensorFlow Authors. All Rights Reserved.
 
 Licensed under the Apache License, Version 2.0 (the "License");
 you may not use this file except in compliance with the License.
@@ -54,10 +54,8 @@ TfLiteStatus ResizeNearestNeighborPrepare(TfLiteContext* context,
 
   output->type = input->type;
 
-  if (!IsConstantTensor(size)) {
-    MicroPrintf("Dynamic tensors are unsupported in tfmicro.");
-    return kTfLiteError;
-  }
+  TF_LITE_ENSURE_MSG(context, IsConstantTensor(size),
+                     "Non-constant >size< tensor is not supported");
 
   micro_context->DeallocateTempTfLiteTensor(input);
   micro_context->DeallocateTempTfLiteTensor(size);

tensorflow/lite/micro/kernels/split.cc

@@ -1,4 +1,4 @@
-/* Copyright 2023 The TensorFlow Authors. All Rights Reserved.
+/* Copyright 2025 The TensorFlow Authors. All Rights Reserved.
 
 Licensed under the Apache License, Version 2.0 (the "License");
 you may not use this file except in compliance with the License.
@@ -76,7 +76,7 @@ TfLiteStatus SplitPrepare(TfLiteContext* context, TfLiteNode* node) {
   // But Micro doesn't support dynamic memory allocation, so we only support
   // constant axis tensor for now.
   TF_LITE_ENSURE_MSG(context, IsConstantTensor(axis),
-                     "Non constant axis tensor not supported");
+                     "Non-constant >axis< tensor is not supported");
 
   micro_context->DeallocateTempTfLiteTensor(axis);
   return kTfLiteOk;

tensorflow/lite/micro/kernels/split_v.cc

@@ -1,4 +1,4 @@
-/* Copyright 2023 The TensorFlow Authors. All Rights Reserved.
+/* Copyright 2025 The TensorFlow Authors. All Rights Reserved.
 
 Licensed under the Apache License, Version 2.0 (the "License");
 you may not use this file except in compliance with the License.
@@ -80,7 +80,7 @@ TfLiteStatus SplitVPrepare(TfLiteContext* context, TfLiteNode* node) {
   // constant axis tensor for now.
   TfLiteTensor* axis = micro_context->AllocateTempInputTensor(node, 2);
   TF_LITE_ENSURE_MSG(context, IsConstantTensor(axis),
-                     "Non constant axis tensor not supported");
+                     "Non-constant >axis< tensor is not supported");
   micro_context->DeallocateTempTfLiteTensor(axis);
   return kTfLiteOk;
 }

tensorflow/lite/micro/kernels/xtensa/pad.cc

@@ -1,4 +1,4 @@
-/* Copyright 2022 The TensorFlow Authors. All Rights Reserved.
+/* Copyright 2025 The TensorFlow Authors. All Rights Reserved.
 
 Licensed under the Apache License, Version 2.0 (the "License");
 you may not use this file except in compliance with the License.
@@ -91,7 +91,8 @@ TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) {
   // On Micro, outputs must be properly sized by the converter.
   // NOTE: This data is only available because the paddings buffer is stored in
   // the flatbuffer:
-  TF_LITE_ENSURE(context, IsConstantTensor(paddings));
+  TF_LITE_ENSURE_MSG(context, IsConstantTensor(paddings),
+                     "Non-constant >paddings< tensor is not supported");
   const int32_t* paddings_data = GetTensorData<int32_t>(paddings);
   for (int i = 0; i < output->dims->size; i++) {
     int output_dim = output->dims->data[i];