message: Minor doc update to use TfLiteIntArray better
diff: @@ -85,6 +85,8 @@ To see it in code, let's define a delegate and call it `MyDelegate`, which can
  execute Conv2D and Mean operations faster.
  ```c++
  +#include "tensorflow/lite/util.h"
  +
  // This is where the execution of the operations or whole graph happens.
  // The class below has an empty implementation just as a guideline
  // on the structure.
  @@ -156,8 +158,7 @@ TfLiteRegistration GetMyDelegateNodeRegistration() {
  TfLiteStatus DelegatePrepare(TfLiteContext* context, TfLiteDelegate* delegate) {
  // Claim all nodes that can be evaluated by the delegate and ask the
  // framework to update the graph with delegate kernel instead.
  - // Reserve 1 element, since we need first element to be size.
  - std::vector<int> supported_nodes(1);
  + std::vector<int> supported_nodes;
  TfLiteIntArray* plan;
  TF_LITE_ENSURE_STATUS(context->GetExecutionPlan(context, &plan));
  TfLiteNode* node;
  @@ -169,17 +170,19 @@ TfLiteStatus DelegatePrepare(TfLiteContext* context, TfLiteDelegate* delegate) {
  supported_nodes.push_back(node_index);
  }
  }
  - // Set first element to the number of nodes to replace.
  - supported_nodes[0] = supported_nodes.size() - 1;
  TfLiteRegistration my_delegate_kernel_registration =
  GetMyDelegateNodeRegistration();
  // This call split the graphs into subgraphs, for subgraphs that can be
  // handled by the delegate, it will replace it with a
  // 'my_delegate_kernel_registration'
  - return context->ReplaceNodeSubsetsWithDelegateKernels(
  + TfLiteIntArray* supported_nodes_int_array =
  + ::tflite::ConvertVectorToTfLiteIntArray(supported_nodes);
  + auto status = context->ReplaceNodeSubsetsWithDelegateKernels(
  context, my_delegate_kernel_registration,
  - reinterpret_cast<TfLiteIntArray*>(supported_nodes.data()), delegate);
  + supported_nodes_int_array, delegate);
  + TfLiteIntArrayFree(supported_nodes_int_array);
  + return status
  }
  void FreeBufferHandle(TfLiteContext* context, TfLiteDelegate* delegate,
  