single batch, single model

script.py

@@ -158,7 +158,7 @@ def generate_embeddings(metadata_file_path, root_dir):
 
     test_dataset = ImageDataset(metadata_df, local_filepath=root_dir)
 
-    loader = DataLoader(test_dataset, batch_size=2, shuffle=False, num_workers=4)
+    loader = DataLoader(test_dataset, batch_size=1, shuffle=False, num_workers=4)
 
     device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
     model = timm.create_model(
@@ -313,40 +313,41 @@ def make_submission(metadata_df):
     OUTPUT_CSV_PATH = "./submission.csv"
     BASE_CKPT_PATH = "./checkpoints"
 
-    # ckpt_path = os.path.join(BASE_CKPT_PATH, "dino_2_optuna_05242055.ckpt")
-    model_names = [
-        "dino_2_optuna_05242231.ckpt",
-        "dino_optuna_05241449.ckpt",
-        "dino_optuna_05241257.ckpt",
-        "dino_optuna_05241222.ckpt",
-        "dino_2_optuna_05242055.ckpt",
-        "dino_2_optuna_05242156.ckpt",
-        "dino_2_optuna_05242344.ckpt",
-    ]
-
-    models = []
-
-    for model_path in model_names:
-        print("loading ", model_path)
-        ckpt_path = os.path.join(BASE_CKPT_PATH, model_path)
-
-        ckpt = torch.load(ckpt_path)
-        model = FungiMEEModel()
-        model.load_state_dict(
-            {w: ckpt["model." + w] for w in model.state_dict().keys()}
-        )
-        model.eval()
-        model.cuda()
+    # model_names = [
+    #     "dino_2_optuna_05242231.ckpt",
+    #     "dino_optuna_05241449.ckpt",
+    #     "dino_optuna_05241257.ckpt",
+    #     "dino_optuna_05241222.ckpt",
+    #     "dino_2_optuna_05242055.ckpt",
+    #     "dino_2_optuna_05242156.ckpt",
+    #     "dino_2_optuna_05242344.ckpt",
+    # ]
+
+    # models = []
+
+    # for model_path in model_names:
+    #     print("loading ", model_path)
+    #     ckpt_path = os.path.join(BASE_CKPT_PATH, model_path)
+
+    #     ckpt = torch.load(ckpt_path)
+    #     model = FungiMEEModel()
+    #     model.load_state_dict(
+    #         {w: ckpt["model." + w] for w in model.state_dict().keys()}
+    #     )
+    #     model.eval()
+    #     model.cuda()
 
-        models.append(model)
+    #     models.append(model)
 
-    fungi_model = FungiEnsembleModel(models)
+    # fungi_model = FungiEnsembleModel(models)
 
-    # fungi_model = FungiMEEModel()
-    # ckpt = torch.load(ckpt_path)
-    # fungi_model.load_state_dict(
-    #     {w: ckpt["model." + w] for w in fungi_model.state_dict().keys()}
-    # )
+    ckpt_path = os.path.join(BASE_CKPT_PATH, "dino_2_optuna_05242055.ckpt")
+
+    fungi_model = FungiMEEModel()
+    ckpt = torch.load(ckpt_path)
+    fungi_model.load_state_dict(
+        {w: ckpt["model." + w] for w in fungi_model.state_dict().keys()}
+    )
 
     embedding_dataset = EmbeddingMetadataDataset(metadata_df)
     loader = DataLoader(embedding_dataset, batch_size=128, shuffle=False)
@@ -377,9 +378,6 @@ def make_submission(metadata_df):
 
 if __name__ == "__main__":
 
-    MODEL_PATH = "metaformer-s-224.pth"
-    MODEL_NAME = "timm/vit_base_patch14_reg4_dinov2.lvd142m"
-
     # # # # # # Real submission
     import zipfile