.insert(EncodeTensorNameSlice(
                    string(v2_reader_->key()) /* full var's name */,
                    TensorSlice(slice_proto)))
                .second);
    }
  }

  // Second pass: adds the entries, ignoring the filtered keys.
  std::unique_ptr<TensorSliceReader::VarToShapeMap> var_to_shape_map(
      new TensorSliceReader::VarToShapeMap);

        List<LogNotificationEvent> first = helper.drainAll();
        assertEquals(1, first.size());
        List<LogNotificationEvent> second = helper.drainAll();
        assertTrue(second.isEmpty());
    }

    @Test
    public void test_offer_bufferCapacity() {
        LogNotificationHelper helper = new LogNotificationHelper();

      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

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

Burada `new_dict`, `old_dict` içindeki tüm key-value çiftlerini ve buna ek olarak yeni key-value çiftini içerir:

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

    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",
}
```

        byte[] first = impl.getBuffer(); // should return slot 0 -> a
        byte[] second = impl.getBuffer(); // then slot 1 -> c
        byte[] third = impl.getBuffer(); // cache empty -> new with size 3

        assertSame(a, first, "First get should return first cached buffer");
        assertSame(c, second, "Second get should return second cached buffer");

	driveCountMD = NewGaugeMD(driveCount,
		"Count of all drives")

	// iostat related
	driveReadsPerSecMD = NewGaugeMD(driveReadsPerSec,
		"Reads per second on a drive",
		allDriveLabels...)
	driveReadsKBPerSecMD = NewGaugeMD(driveReadsKBPerSec,
		"Kilobytes read per second on a drive",
		allDriveLabels...)
	driveReadsAwaitMD = NewGaugeMD(driveReadsAwait,
		"Average time for read requests served on a drive",
		allDriveLabels...)

  auto iter = name_ranges.find(arg_name);
  if (iter == name_ranges.end()) {
    status->status = InvalidArgument("Output arg '", arg_name, "' not found");
    return -1;
  }
  return iter->second.second - iter->second.first;
}

int TF_OperationNumInputs(TF_Operation* oper) {
  return oper->node.num_inputs();
}

TF_DataType TF_OperationInputType(TF_Input oper_in) {

   * @throws NullPointerException if both {@code first} and {@code second} are null
   * @since 18.0 (since 3.0 as {@code Objects.firstNonNull}).
   */
  public static <T> T firstNonNull(@Nullable T first, @Nullable T second) {
    if (first != null) {
      return first;
    }
    if (second != null) {
      return second;
    }
    throw new NullPointerException("Both parameters are null");
  }