if (attr.first == "dtype") {
      if (attr.second.type() == tensorflow::DT_INT32) {
        found_dtype = true;
      } else {
        return false;
      }
    } else if (attr.first == "value") {
      if (attr.second.has_tensor() &&
          attr.second.tensor().int_val_size() == 1 &&
          attr.second.tensor().int_val(0) == v) {
        found_value = true;
      } else {

```Python
old_dict = {
    "old key": "old value",
    "second old key": "second old value",
}
new_dict = {**old_dict, "new key": "new value"}
```

Aqui, o `new_dict` terá todos os pares de chave-valor do `old_dict` mais o novo par de chave-valor:

```Python
{
    "old key": "old value",
    "second old key": "second old value",
    "new key": "new value",
}
```

对于这些情况，你可以使用Python的技术，将 `dict` 与 `**dict_to_unpack` 解包：
```Python
old_dict = {
    "old key": "old value",
    "second old key": "second old value",
}
new_dict = {**old_dict, "new key": "new value"}
```

这里， new_dict 将包含来自 old_dict 的所有键值对加上新的键值对：
```python
{
    "old key": "old value",
    "second old key": "second old value",
    "new key": "new value",
}
```
您可以使用该技术在路径操作中重用一些预定义的响应，并将它们与其他自定义响应相结合。
**例如：**

// ExtractFunc represents EXTRACT sql function
type ExtractFunc struct {
	Timeword string       `parser:" \"EXTRACT\" \"(\" @( \"YEAR\":Timeword | \"MONTH\":Timeword | \"DAY\":Timeword | \"HOUR\":Timeword | \"MINUTE\":Timeword | \"SECOND\":Timeword | \"TIMEZONE_HOUR\":Timeword | \"TIMEZONE_MINUTE\":Timeword ) "`
	From     *PrimaryTerm `parser:" \"FROM\" @@ \")\" "`
}

// TrimFunc represents TRIM sql function
type TrimFunc struct {

      implements Serializable {
    final Converter<A, B> first;
    final Converter<B, C> second;

    ConverterComposition(Converter<A, B> first, Converter<B, C> second) {
      this.first = first;
      this.second = second;
    }

    /*
     * These gymnastics are a little confusing. Basically this class has neither legacy nor

pkg p4, func NewPair[$0 interface{ M }, $1 interface{ ~int }]($0, $1) Pair[$0, $1]
pkg p4, method (Pair[$0, $1]) Second() $1
pkg p4, method (Pair[$0, $1]) First() $0
pkg p4, type Pair[$0 interface{ M }, $1 interface{ ~int }] struct
pkg p4, func Clone[$0 interface{ ~[]$1 }, $1 interface{}]($0) $0

@ElementTypesAreNonnullByDefault
public class AbstractIteratorTest extends TestCase {

  public void testDefaultBehaviorOfNextAndHasNext() {

    // This sample AbstractIterator returns 0 on the first call, 1 on the
    // second, then signals that it's reached the end of the data
    Iterator<Integer> iter =
        new AbstractIterator<Integer>() {
          private int rep;

          @Override
          public @Nullable Integer computeNext() {

@ElementTypesAreNonnullByDefault
public class AbstractIteratorTest extends TestCase {

  public void testDefaultBehaviorOfNextAndHasNext() {

    // This sample AbstractIterator returns 0 on the first call, 1 on the
    // second, then signals that it's reached the end of the data
    Iterator<Integer> iter =
        new AbstractIterator<Integer>() {
          private int rep;

          @Override
          public @Nullable Integer computeNext() {

```Python
old_dict = {
    "old key": "old value",
    "second old key": "second old value",
}
new_dict = {**old_dict, "new key": "new value"}
```

Ici, `new_dict` contiendra toutes les paires clé-valeur de `old_dict` plus la nouvelle paire clé-valeur :

```Python
{
    "old key": "old value",
    "second old key": "second old value",
    "new key": "new value",
}
```

	for {
		if err := sm.load(ctx, newObjectLayerFn()); err == nil {
			<-ctx.Done()
			return
		}
		duration := time.Duration(r.Float64() * float64(time.Second*10))
		if duration < time.Second {
			// Make sure to sleep at least a second to avoid high CPU ticks.
			duration = time.Second
		}
		time.Sleep(duration)
	}
}

// load resync metrics saved on disk into memory