reformat using black

Author: sfluegel

chebai/result/analyse_sem.py

@@ -11,7 +11,7 @@
 from torchmetrics.functional.classification import multilabel_f1_score
 import wandb
 import gc
-from typing import List,Union
+from typing import List, Union
 from utils import *
 
 DEVICE = "cpu"  # torch.device("cuda:0" if torch.cuda.is_available() else "cpu")

chebai/trainer/CustomTrainer.py

@@ -44,7 +44,10 @@ def predict_from_file(
     def _predict_smiles(self, model: LightningModule, smiles: List[str]):
         reader = ChemDataReader()
         parsed_smiles = [reader._read_data(s) for s in smiles]
-        x = pad_sequence([torch.tensor(a, device=model.device) for a in parsed_smiles], batch_first=True)
+        x = pad_sequence(
+            [torch.tensor(a, device=model.device) for a in parsed_smiles],
+            batch_first=True,
+        )
         cls_tokens = (
             torch.ones(x.shape[0], dtype=torch.int, device=model.device).unsqueeze(-1)
             * CLS_TOKEN