Training step folder

training.py → 03_training/training.py

@@ -27,20 +27,20 @@ from torch.utils.tensorboard import SummaryWriter
 from dataset import NumpyCSVDataset, augment_3D_HN
 from networks import CiompiDO, ResNet50_3d
 from split import train_test_indexes_patient_wise
+from config import get_project_root
 
-PATH = Path(os.getcwd())
-print(PATH)
 #%%
 device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
 multigpu = True
 #
+PROJECT_ROOT = get_project_root()
 DATASET = 'HN_val'
 BBOX_SUBDATASET = 'bbox_64'
 
-DATASET_DIR = PATH / 'data' / DATASET / 'processed' / 'bbox' / BBOX_SUBDATASET
-EXPERIMENT_DIR = PATH / 'experiments'
+DATASET_DIR = PROJECT_ROOT / 'data' / DATASET / 'processed' / 'bbox' / BBOX_SUBDATASET
+EXPERIMENT_DIR = PROJECT_ROOT / 'experiments'
 
-PRETRAINED_MED3D_WEIGHTS = PATH / 'pretrained_weights' / 'resnet_50.pth'
+PRETRAINED_MED3D_WEIGHTS = PROJECT_ROOT / 'pretrained_weights' / 'resnet_50.pth'
 PRETRAINED_T_STAGE = EXPERIMENT_DIR / 'Tstage_4_noTx_CT_20191114-163418' / 'weights.pth'
 # %%
 ### Settings
@@ -50,7 +50,7 @@ settings = {
     "model": CiompiDO,
     "batch_size": 16,
     "lr": 1e-5,
-    "epochs": 300,
+    "epochs": 1,
     "optim": torch.optim.Adam,
     "K": 0.2,
     "n_classes": 4,  # TSTAGE
@@ -86,7 +86,7 @@ PRETRAINED = settings["pretrained"]
 
 
 def new_run_log_dir(experiment_name):
-    log_dir = PATH / "tb-runs"
+    log_dir = PROJECT_ROOT / "tb-runs"
     if not os.path.exists(log_dir):
         os.makedirs(log_dir)
     run_log_dir = log_dir / experiment_name
@@ -100,7 +100,9 @@ writer = SummaryWriter(log_dir)
 # %%
 # ### Data Handlers
 
-clinical_file = PATH / 'data' / DATASET / 'processed' / f'clinical_{DATASET}.csv'
+clinical_file = (
+    PROJECT_ROOT / 'data' / DATASET / 'processed' / f'clinical_{DATASET}.csv'
+)
 target_column = "T-stage_grouped"
 # %%
 np.random.seed(SEED)