message: Updated quantize_weights.cc
  Fixed warnings in the file
diff: @@ -52,14 +52,15 @@ std::vector<ConsumerOpInfo> GetTensorConsumers(const ModelT* model,
  // TODO(suharshs): If this proves to be too slow, avoid calling it per tensor,
  // instead doing one sweep for the entire model.
  std::vector<ConsumerOpInfo> consumer_ops;
  - for (int op_idx = 0; op_idx < subgraph->operators.size(); ++op_idx) {
  + for (size_t op_idx = 0; op_idx < subgraph->operators.size(); ++op_idx) {
  OperatorT* op = subgraph->operators[op_idx].get();
  if (op == nullptr) {
  continue;
  }
  - for (int i = 0; i < op->inputs.size(); ++i) {
  + for (size_t i = 0; i < op->inputs.size(); ++i) {
  if (op->inputs[i] == tensor_idx) {
  - consumer_ops.push_back({op, op_idx, i});
  + consumer_ops.push_back(
  + {op, static_cast<int>(op_idx), static_cast<int>(i)});
  }
  }
  }
  @@ -228,7 +229,7 @@ TfLiteStatus SymmetricQuantizeTensor(ModelT* model, TensorT* tensor) {
  // Returns the index of the Dequantize op_code.
  // If a Dequantize op_code doesn't exist, adds it and returns its index.
  int32_t GetOrInsertDequantizeOpCodeIndex(ModelT* model) {
  - for (int i = 0; i < model->operator_codes.size(); ++i) {
  + for (size_t i = 0; i < model->operator_codes.size(); ++i) {
  if (model->operator_codes[i]->builtin_code == BuiltinOperator_DEQUANTIZE) {
  return i;
  }
  @@ -266,7 +267,7 @@ void MakeTensor(const string& name, const std::vector<int32_t>& shape,
  // Updates operator code versions for the operators with INT8 inputs.
  void UpdateInt8OperatorVersions(ModelT* model) {
  - for (int i = 0; i < model->operator_codes.size(); ++i) {
  + for (size_t i = 0; i < model->operator_codes.size(); ++i) {
  const BuiltinOperator& op_code = model->operator_codes[i]->builtin_code;
  if (op_code == BuiltinOperator_CONV_2D || op_code == BuiltinOperator_SVDF ||
  op_code == BuiltinOperator_EMBEDDING_LOOKUP ||
  @@ -302,7 +303,7 @@ TfLiteStatus QuantizeWeightsInternal(flatbuffers::FlatBufferBuilder* builder,
  std::vector<std::unique_ptr<OperatorT>> new_operators;
  std::unordered_map<int32_t, TensorT*> tensor_map;
  - for (int i = 0; i < subgraph->operators.size(); ++i) {
  + for (size_t i = 0; i < subgraph->operators.size(); ++i) {
  OperatorT* op = subgraph->operators[i].get();
  TF_LITE_ENSURE_STATUS(InsertQuantizableInputTensorsFromOperator(
  model.get(), op, weights_min_num_elements, &tensor_map));
  