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from transformers import PreTrainedModel
from transformers import PretrainedConfig
from omegaconf import OmegaConf
from models import get_model
import yaml
class ModelConfig(PretrainedConfig):
def __init__(
self,
**kwargs,
):
super().__init__(**kwargs)
self.conf = dict(yaml.safe_load(open('pretrained_model/model.yaml')))
class CVLFaceRecognitionModel(PreTrainedModel):
config_class = ModelConfig
def __init__(self, cfg):
super().__init__(cfg)
model_conf = OmegaConf.create(cfg.conf)
self.model = get_model(model_conf)
self.model.load_state_dict_from_path('pretrained_model/model.pt')
def forward(self, *args, **kwargs):
return self.model(*args, **kwargs)
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