| import torch | |
| import torch.nn.functional as F | |
| import pickle | |
| from clip_model import CLIPModel | |
| from configuration import CFG | |
| def load_model(model_path): | |
| model = CLIPModel().to(CFG.device) | |
| model.load_state_dict(torch.load(model_path, map_location=CFG.device)) | |
| model.eval() | |
| return model | |
| def load_df(): | |
| with open("pickles/valid_df.pkl", 'rb') as file: | |
| valid_df = pickle.load(file) | |
| return valid_df | |
| def load_image_embeddings(): | |
| with open("pickles/image_embeddings.pkl", 'rb') as file: | |
| image_embeddings = pickle.load(file) | |
| return image_embeddings | |