style: apply black formatting to fix CI py3.10 check

Author: dhakarshailendra829

src/codefix_env/__init__.py

@@ -77,4 +77,4 @@ def __getattr__(name):
         from codefix_env.utils.reward_model import RewardMLP
 
         return RewardMLP
-    raise AttributeError(f"module {__name__!r} has no attribute {name!r}")
+    raise AttributeError(f"module {__name__!r} has no attribute {name!r}")

src/codefix_env/rewards.py

@@ -155,4 +155,4 @@ def build_metrics(
 default_pipeline = RewardPipeline(
     cfg=ScoringConfig(),
     neural_model_path=os.environ.get("CODEFIX_REWARD_MODEL_PATH"),
-)
+)

src/codefix_env/utils/__init__.py

@@ -30,4 +30,4 @@ def __getattr__(name):
         from codefix_env.utils.reward_model import RewardMLP
 
         return RewardMLP
-    raise AttributeError(f"module {__name__!r} has no attribute {name!r}")
+    raise AttributeError(f"module {__name__!r} has no attribute {name!r}")

src/codefix_env/utils/metrics.py

@@ -17,7 +17,6 @@
 import math
 from dataclasses import dataclass
 
-
 # ─────────────────────────────────────────────
 # Score Config
 # ─────────────────────────────────────────────
@@ -159,4 +158,4 @@ def to_dict(self) -> dict:
             "tests_total": self.tests_total,
             "total_reward": round(self.total_reward, 4),
             "efficiency": round(self.efficiency, 4),
-        }
+        }

src/codefix_env/utils/reward_model.py

@@ -76,4 +76,4 @@ def predict(
             dtype=torch.float32,
         )
         with torch.no_grad():
-            return self.forward(features).item()
+            return self.forward(features).item()