// These are invoked at construction time.
static DenseMap<TypeID, TensorFlowDialect::AdditionalOpFunction>
    &GetAdditionalOperationHooks() {
  static auto *additional_operation_hooks =
      new DenseMap<TypeID, TensorFlowDialect::AdditionalOpFunction>();
  return *additional_operation_hooks;
}

void TensorFlowDialect::RegisterAdditionalOperationHook(
    TypeID id, AdditionalOpFunction fn) {

// an identity into a SAN extension.
type IdentityType int

const (
	// TypeDNS represents a DNS name.
	TypeDNS IdentityType = iota
	// TypeIP represents an IP address.
	TypeIP
	// TypeURI represents a universal resource identifier.
	TypeURI
)

var (
	// Mapping from the type of an identity to the OID tag value for the X.509

   * and output.
   */
  public void testNewParameterizedTypeImmutability() {
    Type[] typesIn = {String.class, Integer.class};
    ParameterizedType parameterizedType = Types.newParameterizedType(Map.class, typesIn);
    typesIn[0] = null;
    typesIn[1] = null;

    Type[] typesOut = parameterizedType.getActualTypeArguments();
    typesOut[0] = null;
    typesOut[1] = null;

   * and output.
   */
  public void testNewParameterizedTypeImmutability() {
    Type[] typesIn = {String.class, Integer.class};
    ParameterizedType parameterizedType = Types.newParameterizedType(Map.class, typesIn);
    typesIn[0] = null;
    typesIn[1] = null;

    Type[] typesOut = parameterizedType.getActualTypeArguments();
    typesOut[0] = null;
    typesOut[1] = null;

	testCloneSeq[testStruct](t, cSeq(8))
}

func cSeq(stringOffsets ...uintptr) cloneSeq {
	return cloneSeq{stringOffsets: stringOffsets}
}

func testCloneSeq[T any](t *testing.T, want cloneSeq) {
	typName := reflect.TypeFor[T]().Name()
	typ := abi.TypeOf(*new(T))
	t.Run(typName, func(t *testing.T) {
		got := makeCloneSeq(typ)
		if !reflect.DeepEqual(got, want) {

    "such as a random number generator.";

// TODO(b/282188914) remove the operations to skip once tests are fixed.
static const DenseSet<mlir::TypeID>* operations_to_skip =
    new DenseSet<mlir::TypeID>{mlir::TypeID::get<mhlo::EinsumOp>()};

class VerifyTFXLALegalization
    : public impl::VerifyTFXLALegalizationBase<VerifyTFXLALegalization> {
 public:

func (w *mockTransferWriter) Write(p []byte) (int, error) {
	w.WriteCalled = true
	return io.Discard.Write(p)
}

func TestTransferWriterWriteBodyReaderTypes(t *testing.T) {
	fileType := reflect.TypeFor[*os.File]()
	bufferType := reflect.TypeFor[*bytes.Buffer]()

	nBytes := int64(1 << 10)
	newFileFunc := func() (r io.Reader, done func(), err error) {
		f, err := os.CreateTemp("", "net-http-newfilefunc")
		if err != nil {

connection between an [Encoder] and [Decoder], it is assigned a signed integer type
id. When [Encoder.Encode](v) is called, it makes sure there is an id assigned for
the type of v and all its elements and then it sends the pair (typeid, encoded-v)
where typeid is the type id of the encoded type of v and encoded-v is the gob
encoding of the value v.

To define a type, the encoder chooses an unused, positive type id and sends the

        "The output variant hasn't been initialized");
  }

  if (a.TypeId() != b.TypeId()) {
    return ::tensorflow::errors::Internal(
        "BinaryOpVariants: Variants a and b have different "
        "type ids.  Type names: '",
        a.TypeName(), "' vs. '", b.TypeName(), "'");
  }

  if (a.TypeId() == tensorflow::TypeIndex::Make<::tensorflow::TensorList>()) {

	{CaseName: Name(""), in: `{"X": [1,2,3], "Y": 4}`, ptr: new(T), out: T{Y: 4}, err: &UnmarshalTypeError{"array", reflect.TypeFor[string](), 7, "T", "X"}},
	{CaseName: Name(""), in: `{"X": 23}`, ptr: new(T), out: T{}, err: &UnmarshalTypeError{"number", reflect.TypeFor[string](), 8, "T", "X"}},
	{CaseName: Name(""), in: `{"x": 1}`, ptr: new(tx), out: tx{}},
	{CaseName: Name(""), in: `{"x": 1}`, ptr: new(tx), out: tx{}},