[
	uuid(12345778-1234-abcd-ef00-0123456789ac),
	version(1.0)
]
interface samr
{
	import "../rpc.idl";
	import "lsarpc.idl";

	typedef [v1_enum] enum {
		ACB_DISABLED               = 0x00000001, /* 1 = User account disabled */
		ACB_HOMDIRREQ              = 0x00000002, /* 1 = Home directory required */
		ACB_PWNOTREQ               = 0x00000004, /* 1 = User password not required */

## 사전정의 값

만약 *경로 매개변수*를 받는 *경로 작동*이 있지만, *경로 매개변수*로 가능한 값들을 미리 정의하고 싶다면 파이썬 표준 <abbr title="열거형(Enumeration)">`Enum`</abbr>을 사용할 수 있습니다.

### `Enum` 클래스 생성

`Enum`을 임포트하고 `str`과 `Enum`을 상속하는 서브 클래스를 만듭니다.

`str`을 상속함으로써 API 문서는 값이 `string` 형이어야 하는 것을 알게 되고 이는 문서에 제대로 표시됩니다.

가능한 값들에 해당하는 고정된 값의 클래스 어트리뷰트들을 만듭니다:

```Python hl_lines="1  6-9"

   * we're not calling it from JavaScript, we suppress the warning.
   */
  @JsMethod
  @SuppressWarnings("unusable-by-js")
  private static native <E extends Enum<E>> @Nullable Class<E> getDeclaringClassOrNullForJ2cl(
      E e) /*-{
    return ******@****.***.Enum::getDeclaringClass()();
  }-*/;

  static int reduceIterationsIfGwt(int iterations) {
    return iterations / 10;
  }

/**
 * Optional features of classes derived from {@link Multiset}.
 *
 * @author Louis Wasserman
 */
@SuppressWarnings("rawtypes") // maybe avoidable if we rework the whole package?
@GwtCompatible
public enum MultisetFeature implements Feature<Multiset> {
  /**
   * Indicates that elements from {@code Multiset.entrySet()} update to reflect changes in the
   * backing multiset.
   */
  ENTRIES_ARE_VIEWS;

  @Override

// representation between various supported formats e.g. FunctionDef and Mlir
// function.
class AbstractFunction : public core::RefCounted {
 protected:
  enum AbstractFunctionKind { kGraph, kMlir };
  explicit AbstractFunction(AbstractFunctionKind kind) : kind_(kind) {}

 public:
  // Returns which subclass is this instance of.

#include "tensorflow/core/framework/types.pb.h"
#include "tensorflow/core/platform/status.h"

namespace tensorflow {

// Attributes of an op.
class AbstractOpAttrs {
 protected:
  enum AbstractOpAttrsKind { kEager, kTfrt };
  explicit AbstractOpAttrs(AbstractOpAttrsKind kind) : kind_(kind) {}

 public:
  // Returns which subclass is this instance of.
  AbstractOpAttrsKind getKind() const { return kind_; }

  }

  public void testSum() {
    assertThat(emptyAccumulator.sum()).isEqualTo(0.0);
    assertThat(emptyAccumulatorByAddAllEmptyIterable.sum()).isEqualTo(0.0);
    assertThat(emptyAccumulatorByAddAllEmptyStats.sum()).isEqualTo(0.0);
    assertThat(oneValueAccumulator.sum()).isWithin(ALLOWED_ERROR).of(ONE_VALUE);
    assertThat(oneValueAccumulatorByAddAllEmptyStats.sum()).isWithin(ALLOWED_ERROR).of(ONE_VALUE);

      }
    }
  }

  /** getAndAccumulate with sum adds given value to current, and returns previous value */
  public void testGetAndAccumulateWithSum() {
    for (double x : VALUES) {
      for (double y : VALUES) {
        AtomicDouble a = new AtomicDouble(x);
        double z = a.getAndAccumulate(y, Double::sum);
        assertBitEquals(x, z);
        assertBitEquals(x + y, a.get());
      }

  ASSERT_EQ(TF_GetCode(status), TF_OK) << TF_Message(status);
  TFE_DeleteTensorHandle(retvals[0]);
  float sum = 0;
  EXPECT_EQ(sizeof(sum), TF_TensorByteSize(t));
  memcpy(&sum, TF_TensorData(t), TF_TensorByteSize(t));
  TF_DeleteTensor(t);
  EXPECT_EQ(sum, 6.0);

  TFE_DeleteTensorHandle(h0);
  TFE_DeleteTensorHandle(h1);
  TFE_DeleteTensorHandle(h2);

  }

  // In the unittest, create each ordered factory with its own set of lock
  // graph nodes (as opposed to using the static per-Enum map) to avoid
  // conflicts across different test runs.
  private <E extends Enum<E>>
      CycleDetectingLockFactory.WithExplicitOrdering<E> newInstanceWithExplicitOrdering(
          Class<E> enumClass, Policy policy) {