Given the following code containing errors, provide Common Weakness Enumeration (CWE) identifiers and corresponding messages in JSON format. Each identified weakness should have a unique entry in the JSON array.
    Code: inline void AveragePool(const PoolParams& params,
                        const RuntimeShape& input_shape,
                        const float* input_data,
                        const RuntimeShape& output_shape, float* output_data) {
  ruy::profiler::ScopeLabel label("AveragePool");
  TFLITE_DCHECK_EQ(input_shape.DimensionsCount(), 4);
  TFLITE_DCHECK_EQ(output_shape.DimensionsCount(), 4);
  const int batches = MatchingDim(input_shape, 0, output_shape, 0);
  const int input_height = input_shape.Dims(1);
  const int input_width = input_shape.Dims(2);
  const int output_height = output_shape.Dims(1);
  const int output_width = output_shape.Dims(2);
  const int stride_height = params.stride_height;
  const int stride_width = params.stride_width;

  // TODO(benoitjacob) make this a proper reference impl without Eigen!
  const auto in_mat = MapAsMatrixWithLastDimAsRows(input_data, input_shape);
  auto out_mat = MapAsMatrixWithLastDimAsRows(output_data, output_shape);
  // TODO(benoitjacob) get rid of the dynamic memory allocation here!
  Eigen::VectorXf out_count(out_mat.cols());
  out_count.setZero();
  // Prefill the output to 0.
  out_mat.setZero();
  for (int b = 0; b < batches; ++b) {
    for (int h = 0; h < input_height; ++h) {
      for (int w = 0; w < input_width; ++w) {
        // (h_start, h_end) * (w_start, w_end) is the range that the input
        // vector projects to.
        int hpad = h + params.padding_values.height;
        int wpad = w + params.padding_values.width;
        int h_start = (hpad < params.filter_height)
                          ? 0
                          : (hpad - params.filter_height) / stride_height + 1;
        int h_end = std::min(hpad / stride_height + 1, output_height);
        int w_start = (wpad < params.filter_width)
                          ? 0
                          : (wpad - params.filter_width) / stride_width + 1;
        int w_end = std::min(wpad / stride_width + 1, output_width);
        // compute elementwise sum
        for (int ph = h_start; ph < h_end; ++ph) {
          for (int pw = w_start; pw < w_end; ++pw) {
            int out_offset = NodeOffset(b, ph, pw, output_height, output_width);
            out_mat.col(out_offset) +=
                in_mat.col(NodeOffset(b, h, w, input_height, input_width));
            out_count(out_offset)++;
          }
        }
      }
    }
  }
  // Divide the output by the actual number of elements being averaged over
  TFLITE_DCHECK_GT(out_count.minCoeff(), 0);
  out_mat.array().rowwise() /= out_count.transpose().array();

  const int flat_size = output_shape.FlatSize();
  for (int i = 0; i < flat_size; ++i) {
    output_data[i] = ActivationFunctionWithMinMax(output_data[i],
                                                  params.float_activation_min,
                                                  params.float_activation_max);
  }
} ; Sample JSON Format Confermily Expected output: "examples" => "cwe": "xxx"; "message": "xxx"
    
 'cwe': ['CWE-703', 'CWE-835'], 'message': 'Prevent a division by 0 in average ops.

PiperOrigin-RevId: 385184660
Change-Id: I7affd4554f9b336fca29ac68f633232c094d0bd3'