upload the weight.

Signed-off-by: wxywb <xy.wang@zilliz.com>

expansionnet_v2.py

@@ -35,12 +35,12 @@ class ExpansionNetV2(NNOperator):
     """
     def __init__(self, model_name: str):
         super().__init__()
-        sys.path.append(str(pathlib.Path(__file__).parent))
+        path = str(pathlib.Path(__file__).parent)
+        sys.path.append(path)
         from models.End_ExpansionNet_v2 import End_ExpansionNet_v2
         from utils.language_utils import convert_vector_idx2word
         self.convert_vector_idx2word = convert_vector_idx2word
         sys.path.pop()
-        path = pathlib.Path(__file__).parent
         with open('{}/demo_coco_tokens.pickle'.format(path), 'rb') as f:
             coco_tokens = pickle.load(f)
             self.coco_tokens = coco_tokens
@@ -82,6 +82,10 @@ class ExpansionNetV2(NNOperator):
                                     max_seq_len=max_seq_len, drop_args=model_args.drop_args,
                                 rank='cpu')
 
+        checkpoint = torch.load('{}/weights/rf_model.pth'.format(path), map_location=torch.device('cpu'))
+        self.model.load_state_dict(checkpoint['model_state_dict'])
+        self.model.to(self.device)
+
         self.transf_1 = torchvision.transforms.Compose([torchvision.transforms.Resize((img_size, img_size)), torchvision.transforms.ToTensor()])
         self.transf_2 = torchvision.transforms.Compose([torchvision.transforms.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225])])
         self.beam_search_kwargs = {'beam_size': beam_size,