Remove use of eval in language/mixtral-8x7b/evaluate_mbxp.py

language/mixtral-8x7b/evaluate_mbxp.py

@@ -58,8 +58,25 @@ def worker(inp_queue, out_queue):
             break
 
         key = f"{problem['lang']}_{problem['entry_point']}"
-        checker = eval(f"check_correctness_{problem['lang']}")
 
+        lang_to_checker_map = {
+            "cpp": check_correctness_cpp,
+            "csharp": check_correctness_csharp,
+            "go": check_correctness_go,
+            "java": check_correctness_java,
+            "javascript": check_correctness_javascript,
+            "kotlin": check_correctness_kotlin,
+            "perl": check_correctness_perl,
+            "php": check_correctness_php,
+            "python": check_correctness_python,
+            "ruby": check_correctness_ruby,
+            "scala": check_correctness_scala,
+            "swift": check_correctness_swift,
+            "typescript": check_correctness_typescript,
+        }
+
+        checker = lang_to_checker_map[problem["lang"]]
+
         problem["task_id"] = key
         problem["test"] = problem["test_code"]
 

vision/classification_and_detection/tools/calibrate_torchvision_model.py

@@ -74,10 +74,15 @@ def main():
     dataloader = DataLoader(dataset, batch_size=1)
 
     if not hasattr(torchvision_quantization_models, args.model):
-        raise ValueError(f"Model {args.model} not found in torchvision quantization models")
-
-
-    model = getattr(torchvision_quantization_models, args.model)(pretrained=True, progress=True, quantize=False)
+        raise ValueError(
+            f"Model {args.model} not found in torchvision quantization models")
+
+    model = getattr(
+        torchvision_quantization_models,
+        args.model)(
+        pretrained=True,
+        progress=True,
+        quantize=False)
     quantize_model(model, dataloader)
     print(model)