def download_imagenet(self):
        """ Downloads ImageNet weights and returns path to weights file.
        """
        from classification_models.weights import WEIGHTS_COLLECTION

        weights_path = None
        for el in WEIGHTS_COLLECTION:
            if el['model'] == self.backbone and not el['include_top']:
                weights_path = keras.utils.get_file(el['name'], el['url'], cache_subdir='models', file_hash=el['md5'])

        if weights_path is None:
            raise ValueError('Unable to find imagenet weights for backbone {}!'.format(self.backbone))

        return weights_path
 Downloads ImageNet weights and returns path to weights file.
        
keras_retinanet/models/senet.py