Commit 03e3b7e4 authored by Alessia Marcolini's avatar Alessia Marcolini
Browse files

Training step folder

parent 433f429e
...@@ -27,20 +27,20 @@ from torch.utils.tensorboard import SummaryWriter ...@@ -27,20 +27,20 @@ from torch.utils.tensorboard import SummaryWriter
from dataset import NumpyCSVDataset, augment_3D_HN from dataset import NumpyCSVDataset, augment_3D_HN
from networks import CiompiDO, ResNet50_3d from networks import CiompiDO, ResNet50_3d
from split import train_test_indexes_patient_wise 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") device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
multigpu = True multigpu = True
# #
PROJECT_ROOT = get_project_root()
DATASET = 'HN_val' DATASET = 'HN_val'
BBOX_SUBDATASET = 'bbox_64' BBOX_SUBDATASET = 'bbox_64'
DATASET_DIR = PATH / 'data' / DATASET / 'processed' / 'bbox' / BBOX_SUBDATASET DATASET_DIR = PROJECT_ROOT / 'data' / DATASET / 'processed' / 'bbox' / BBOX_SUBDATASET
EXPERIMENT_DIR = PATH / 'experiments' 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' PRETRAINED_T_STAGE = EXPERIMENT_DIR / 'Tstage_4_noTx_CT_20191114-163418' / 'weights.pth'
# %% # %%
### Settings ### Settings
...@@ -50,7 +50,7 @@ settings = { ...@@ -50,7 +50,7 @@ settings = {
"model": CiompiDO, "model": CiompiDO,
"batch_size": 16, "batch_size": 16,
"lr": 1e-5, "lr": 1e-5,
"epochs": 300, "epochs": 1,
"optim": torch.optim.Adam, "optim": torch.optim.Adam,
"K": 0.2, "K": 0.2,
"n_classes": 4, # TSTAGE "n_classes": 4, # TSTAGE
...@@ -86,7 +86,7 @@ PRETRAINED = settings["pretrained"] ...@@ -86,7 +86,7 @@ PRETRAINED = settings["pretrained"]
def new_run_log_dir(experiment_name): 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): if not os.path.exists(log_dir):
os.makedirs(log_dir) os.makedirs(log_dir)
run_log_dir = log_dir / experiment_name run_log_dir = log_dir / experiment_name
...@@ -100,7 +100,9 @@ writer = SummaryWriter(log_dir) ...@@ -100,7 +100,9 @@ writer = SummaryWriter(log_dir)
# %% # %%
# ### Data Handlers # ### 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" target_column = "T-stage_grouped"
# %% # %%
np.random.seed(SEED) np.random.seed(SEED)
......
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