}
		for i := 1; i < len(result.Pets); i++ {
			if result.Pets[i-1].Name > result.Pets[i].Name {
				t.Fatalf("Preload user %v pets not ordered correctly, last %v, cur %v", result.Name, result.Pets[i-1], result.Pets[i])
			}
		}
		for i := 1; i < len(result.Pets); i++ {
			if result.Pets[i-1].Name > result.Pets[i].Name {

		maxParts = maxPartsList
	}

	// Populate the result stub.
	result.Bucket = bucket
	result.Object = object
	result.UploadID = uploadID
	result.MaxParts = maxParts
	result.PartNumberMarker = partNumberMarker
	result.UserDefined = cloneMSS(fi.Metadata)
	result.ChecksumAlgorithm = fi.Metadata[hash.MinIOMultipartChecksum]
	result.ChecksumType = fi.Metadata[hash.MinIOMultipartChecksumType]

	"gorm.io/gorm/clause"
	"gorm.io/gorm/logger"
)

type result struct {
	Result       sql.Result
	RowsAffected int64
}

func (info *result) ModifyStatement(stmt *Statement) {
	stmt.Result = info
}

// Build implements clause.Expression interface
func (result) Build(clause.Builder) {
}

func WithResult() *result {
	return &result{}
}

type Interface[T any] interface {

      types[i] = resolveType(types[i]);
    }
    return types;
  }

  private Type[] resolveTypes(Type[] types) {
    Type[] result = new Type[types.length];
    for (int i = 0; i < types.length; i++) {
      result[i] = resolveType(types[i]);
    }
    return result;
  }

  private WildcardType resolveWildcardType(WildcardType type) {
    Type[] lowerBounds = type.getLowerBounds();

    ml_models.clear()


app = FastAPI(lifespan=lifespan)


@app.get("/predict")
async def predict(x: float):
    result = ml_models["answer_to_everything"](x)
    return {"result": result}
```

**Note**: This is the recommended way going forward, instead of using `startup` and `shutdown` events.