问题
Tensorflow is a super heavy import. I want to import it only when it's needed. However, I have a model loading function like this:
from typing import Dict, Any
from keras.models import Model # Heavy import! Takes 2 seconds or so!
# Model loading is a heavy task. Only do it once and keep it in memory
model = None # type: Optional[Model]
def load_model(config: Dict[str, Any], shape) -> Model:
"""Load a model."""
if globals()['model'] is None:
globals()['model'] = create_model(wili.n_classes, shape)
print(globals()['model'].summary())
return globals()['model']
回答1:
Perhaps variable TYPE_CHECKING will help you:
if the import is only needed for type annotations in forward references (string literals) or comments, you can write the imports inside
if TYPE_CHECKING
: so that they are not executed at runtime.
The TYPE_CHECKING constant defined by the typing module is False at runtime but True while type checking.
Example:
# foo.py
from typing import List, TYPE_CHECKING
if TYPE_CHECKING:
import bar
def listify(arg: 'bar.BarClass') -> 'List[bar.BarClass]':
return [arg]
# bar.py
from typing import List
from foo import listify
class BarClass:
def listifyme(self) -> 'List[BarClass]':
return listify(self)
来源:https://stackoverflow.com/questions/63127784/how-can-i-keep-imports-lightweight-and-still-properly-type-annotate