fix(ci): resolve issues from SIM113

pyproject.toml

@@ -85,6 +85,11 @@ omit = [
 ]
 
 [tool.ruff]
+
+include = ["*.py", "*.pyi", "**/pyproject.toml", "*.ipynb"]
+
+[tool.ruff.lint]
+
 # See rules: https://beta.ruff.rs/docs/rules/
 select = [
     "C",    # flake8-comprehensions
@@ -106,8 +111,6 @@ select = [
     "W",    # pycodestyle warnings
 ]
 
-include = ["*.py", "*.pyi", "**/pyproject.toml", "*.ipynb"]
-
 
 ignore = [
     "E501",  # line too long, handled by black
@@ -118,12 +121,12 @@ ignore = [
     "W191",  # tab identation
 ]
 
-[tool.ruff.isort]
+[tool.ruff.lint.isort]
 known-first-party = ["otc"]
 section-order = ["future", "standard-library", "third-party", "first-party", "local-folder"]
 
-[tool.ruff.per-file-ignores]
+[tool.ruff.lint.per-file-ignores]
 "__init__.py" = ["D104", "F401"]  # disable missing docstrings in __init__, unused imports
 
-[tool.ruff.pydocstyle]
+[tool.ruff.lint.pydocstyle]
 convention = "google"

src/otc/models/transformer_classifier.py

@@ -467,7 +467,6 @@ def fit(
         for epoch in range(self.epochs_finetune):
             # perform training
             loss_in_epoch_train = 0
-            train_batch = 0
 
             self.clf.train()
 
@@ -498,15 +497,13 @@ def fit(
 
                 self._stats_step.append({"train_loss": train_loss.item(), "step": step})
 
-                train_batch += 1
                 step += 1
 
             self.clf.eval()
 
             loss_in_epoch_val = 0.0
             correct = 0
 
-            val_batch = 0
             with torch.no_grad():
                 for x_cat, x_cont, weights, targets in val_loader_finetune:
                     logits = self.clf(x_cat, x_cont)
@@ -524,8 +521,6 @@ def fit(
                     )
                     loss_in_epoch_val += val_loss.item()
 
-                    val_batch += 1
-
             # loss average over all batches
             train_loss_all = loss_in_epoch_train / len(train_loader_finetune)
             val_loss_all = loss_in_epoch_val / len(val_loader_finetune)