Function LogArray

tensorflow/lite/toco/tooling_util.cc:502–544

}

void LogArray(int log_level, const Model& model, const string& name) {
  VLOG(log_level) << "Array: " << name;
  if (!model.HasArray(name)) {
    VLOG(log_level) << "  DOES NOT EXIST";
    return;
  }
  const auto& array = model.GetArray(name);
  VLOG(log_level) << "  Data type: " << ArrayDataTypeName(array.data_type);
  VLOG(log_level) << "  Final type: "
                  << ArrayDataTypeName(array.final_data_type);
  if (array.buffer) {
    VLOG(log_level) << "  Constant Buffer";
  }
  if (array.alloc) {
    VLOG(log_level) << "  Transient Alloc";
  }
  if (array.has_shape()) {
    const Shape& array_shape = array.shape();
    if (array_shape.dimensions_count() == 0) {
      VLOG(log_level) << "  (Zero dimensions)";
    } else {
      string message = "  Dims: ";
      bool first = true;
      for (const int dim : array_shape.dims()) {
        if (!first) {
          message += ", ";
        }
        first = false;
        toco::port::AppendF(&message, "%d", dim);
      }
      VLOG(log_level) << message;
    }
  }
  if (array.minmax) {
    VLOG(log_level) << "  MinMax: " << array.minmax->min << " .. "
                    << array.minmax->max;
  }
  if (array.quantization_params) {
    VLOG(log_level) << "  QuantizationParams: zero_point="
                    << static_cast<int>(array.quantization_params->zero_point)
                    << ", scale=" << array.quantization_params->scale;
  }
}

void DumpGraphvizVideoFrame(const Model& model) {
  namespace port = toco::port;