TF_QINT16 = 15,    // Quantized int16
  TF_QUINT16 = 16,   // Quantized uint16
  TF_UINT16 = 17,
  TF_COMPLEX128 = 18,  // Double-precision complex
  TF_HALF = 19,
  TF_RESOURCE = 20,
  TF_VARIANT = 21,
  TF_UINT32 = 22,
  TF_UINT64 = 23,
  TF_FLOAT8_E5M2 = 24,    // 5 exponent bits, 2 mantissa bits.
  TF_FLOAT8_E4M3FN = 25,  // 4 exponent bits, 3 mantissa bits, finite-only, with

  TF_ManagedBuffer* buf = nullptr;
  if (dtype != TF_STRING && dtype != TF_RESOURCE &&
      tensorflow::DataTypeCanUseMemcpy(
          static_cast<tensorflow::DataType>(dtype)) &&
      reinterpret_cast<intptr_t>(data) % std::max(1, EIGEN_MAX_ALIGN_BYTES) !=
          0) {
    // TF_STRING and TF_RESOURCE tensors have a different representation in

def TF_Variant : AnyTypeOf<
  [TF_TensorFlowType<"Variant", "var">, TF_VariantRef], "variant">;
def TF_VariantTensor : TensorOf<[TF_Variant]>;

def TF_Resource : AnyTypeOf<
  [TF_TensorFlowType<"Resource", "res">, TF_ResourceRef], "resource">;
def TF_ResourceTensor : TensorOf<[TF_Resource]>;

//===----------------------------------------------------------------------===//
// Multi-category type constraints

      TFE_CreatePackedTensorHandle(ctx, handles.data(), &num_replicas, status);
  ASSERT_EQ(TF_GetCode(status), TF_OK) << TF_Message(status);
  EXPECT_EQ(TFE_TensorHandleDataType(packed_handle), TF_RESOURCE);
  EXPECT_EQ(TFE_TensorHandleNumDims(packed_handle, status), 0);
  EXPECT_EQ(TFE_TensorHandleNumElements(packed_handle, status), 1);

  const string composite_device_name =

    const auto tensor_interface =
        tensorflow::down_cast<const tensorflow::TensorInterface*>(src->tensor);

    if (dst->dims() != 0) {
      return InvalidArgument(
          "Malformed TF_RESOURCE tensor: expected a scalar, got a tensor with "
          "shape ",
          dst->shape().DebugString());
    }
    *dst = tensorflow::Tensor(tensorflow::DT_RESOURCE, dst->shape());

def TFL_I32Tensor : TFL_TensorOf<[I32]>;
def TFL_I64Tensor : TFL_TensorOf<[I64]>;
def TFL_Complex64Tensor : TFL_TensorOf<[Complex<F<32>>]>;
def TFL_ResourceTensor : TFL_TensorOf<[TF_Resource]>;

// TODO(jpienaar): Expand to all int types.
def TFL_IntTensor : TypeAlias<TFL_I32Tensor, "tensor of any integer type">;

class TFL_0DTensorOf<list<Type> allowedRuntimeTypes,