How to use the lightwood.constants.lightwood.ENCODER_AIM function in lightwood

To help you get started, we’ve selected a few lightwood examples, based on popular ways it is used in public projects.

Secure your code as it's written. Use Snyk Code to scan source code in minutes - no build needed - and fix issues immediately.

github mindsdb / lightwood / lightwood / encoders / image / img_2_vec.py View on Github external
    def __init__(self, is_target=False, aim=ENCODER_AIM.SPEED):
        super().__init__(is_target)
        self.model = None
        # I think we should make this an enum, something like: speed, balance, accuracy
        self.aim = aim
        self._pytorch_wrapper = torch.FloatTensor
        self._prepared = False

        self._scaler = transforms.Scale((224, 224))
        # @TODO Magic numbers with no idea left of how they got here, we should at least have the decency of citing some paper that used these as magic numbers :P
        self._normalize = transforms.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225])
        self._to_tensor = transforms.ToTensor()

        pil_logger = logging.getLogger('PIL')
        pil_logger.setLevel(logging.ERROR)
github mindsdb / lightwood / lightwood / encoders / image / img_2_vec.py View on Github external
def prepare_encoder(self, priming_data):
        if self._prepared:
            raise Exception('You can only call "prepare_encoder" once for a given encoder.')

        if self.model is None:
            if self.aim == ENCODER_AIM.SPEED:
                self.model = Img2Vec(model='resnet-18')
            elif self.aim == ENCODER_AIM.BALANCE:
                self.model = Img2Vec(model='resnext-50-small')
            elif self.aim == ENCODER_AIM.ACCURACY:
                self.model = Img2Vec(model='resnext-50')
            else:
                self.model = Img2Vec()
        self._prepared = True