⚡️ Speed up method AlexNet._extract_features by 612%

Here’s your optimized program.



**Explanation:**
- The **for loop did nothing** (`pass`), so it was an unnecessary O(n) iteration.
- Returning the empty list directly skips the loop entirely and is the fastest implementation possible for this code, achieving O(1) time.
- All logic is preserved (the return value is unchanged: always `[]`).

**Result:**
You won’t get faster than this for the implemented logic, as the empty list is returned instantly for any input.

Author: codeflash-ai[bot]

code_to_optimize/code_directories/simple_tracer_e2e/workload.py

@@ -29,11 +29,8 @@ def forward(self, x):
         return output
 
     def _extract_features(self, x):
-        result = []
-        for i in range(len(x)):
-            pass
-
-        return result
+        # Previously, this loop did nothing. Early return directly.
+        return []
 
     def _classify(self, features):
         total = sum(features)