static ArgType CreateInput(const OpDef::ArgDef& arg_def);
  static ArgType CreateInputRef(const OpDef::ArgDef& arg_def);
  static ArgType CreateOutput(const OpDef::ArgDef& arg_def);

  const tensorflow::DataType data_type() const { return data_type_; }
  const string type_attr_name() const { return type_attr_name_; }
  const bool is_read_only() const { return kind_ == kInput; }
  const bool is_list() const { return is_list_; }

 private:

}

ArgType ArgType::CreateOutput(const OpDef::ArgDef& arg_def) {
  return ArgType(arg_def, kOutput);
}

ArgType::ArgType(const OpDef::ArgDef& arg_def, Kind kind)
    : kind_(kind), data_type_(arg_def.type()) {
  if (!arg_def.type_attr().empty()) {
    type_attr_name_ = arg_def.type_attr();
  }
  if (!arg_def.type_list_attr().empty()) {
    type_attr_name_ = arg_def.type_list_attr();
  }

  is_list_ =

import java.io.Serializable


@ToolingModelContract(subTypes = [
    DataType.NullType::class,
    DataType.UnitType::class,
    DataType.ConstantType::class,
    DataType.IntDataType::class,
    DataType.LongDataType::class,
    DataType.StringDataType::class,
    DataType.BooleanDataType::class,
    DataClass::class
])
sealed interface DataType : Serializable {

    @ToolingModelContract(subTypes = [

Klaus Post <******@****.***> 1709924898 +0100

  DataType data_type = DT_INT32;
  std::initializer_list<int64_t> dims = {2, 3, 4, 5};
  Tensor tensor(data_type, TensorShape(dims));
  for (int i = 0; i < 2 * 3 * 4 * 5; ++i) {
    tensor.flat<int32>()(i) = i;
  }

  NodeDef node;
  auto builder = NodeDefBuilder("some_node", "Const")
                     .Attr("dtype", data_type)
                     .Attr("value", tensor);

  }
  if (inp.node()) {
    return NodeBuilder::NodeOut(inp.node(), inp.index());
  }
  if (!inp.node_name().empty()) {
    return NodeBuilder::NodeOut(inp.node_name(), inp.index(), inp.data_type());
  }
  auto transformed = Input{
      Const(scope.NewSubScope("Const"), Input::Initializer(inp.tensor()))};
  return NodeBuilder::NodeOut{transformed.node(), transformed.index()};
}

coderwander <******@****.***> 1715671610 +0800

// Parses the command line flag strings to the specification of nodes in
// the Graph. `data_types` input string can be empty since the flag is optional.
Status ParseInputArrayInfo(absl::string_view array_names,
                           absl::string_view data_types,
                           absl::string_view shapes,
                           GraphImportConfig::InputArrays* inputs);

namespace tensorflow {
namespace ops {

namespace {

// Utility function for converting to internal C++ datatypes.
OutputTensor ToOutputTensor(const Output& output) {
  return OutputTensor(output.node(), output.index());
}

// Utility function for converting to internal C++ datatypes.
std::vector<OutputTensor> ToOutputTensors(const std::vector<Output>& outputs) {
  std::vector<OutputTensor> result(outputs.size());

 */
private
fun sameType(left: DataType, right: DataType) = when (left) {
    is DataClass -> right is DataClass && left.name.qualifiedName == right.name.qualifiedName
    is DataType.BooleanDataType -> right is DataType.BooleanDataType
    is DataType.IntDataType -> right is DataType.IntDataType
    is DataType.LongDataType -> right is DataType.LongDataType
    is DataType.StringDataType -> right is DataType.StringDataType