⚡️ Speed up method AlexNet._classify by 371%

Here is an optimized version of your program. The main area to optimize is the `_classify` method: using `sum()` is already efficient, but `[val for _ in features]` can be replaced with list multiplication, which is faster in Python. We also avoid recalculating `total % self.num_classes` for every element.


This runs faster, especially for large lists of `features`, because the modulo is computed just once and the resultant list is constructed in a single step.

Author: codeflash-ai[bot]

code_to_optimize/code_directories/simple_tracer_e2e/workload.py

@@ -36,8 +36,8 @@ def _extract_features(self, x):
         return result
 
     def _classify(self, features):
-        total = sum(features)
-        return [total % self.num_classes for _ in features]
+        total_mod = sum(features) % self.num_classes
+        return [total_mod] * len(features)
 
 
 class SimpleModel: