⚡️ Speed up method AlexNet._extract_features by 663%

Here's a rewritten, faster version of your code.

### Optimization Summary

- The original code iterates with a for-loop and does nothing inside. This is extraneous work; nothing is achieved by counting through `len(x)` except time wasted.
- The fastest equivalent way in Python to do nothing is simply to return the empty result immediately.

### Fastest Rewritten Version



**Explanation:**  
- Removed the unused for-loop to avoid O(N) iteration.
- The function now instantly returns its result, achieving best possible performance (O(1)) and minimal memory.

**This version produces exactly the same output as the original for any input.**

Author: codeflash-ai[bot]

code_to_optimize/code_directories/simple_tracer_e2e/workload.py

@@ -34,11 +34,8 @@ def forward(self, x):
         return output
 
     def _extract_features(self, x):
-        result = []
-        for i in range(len(x)):
-            pass
-
-        return result
+        # The original loop did nothing; just return an empty list immediately
+        return []
 
     def _classify(self, features):
         total_mod = sum(features) % self.num_classes