From a9f32ab9153b54cc4a534dde129d4ed56c9073d7 Mon Sep 17 00:00:00 2001
From: "codeflash-ai[bot]"
 <148906541+codeflash-ai[bot]@users.noreply.github.com>
Date: Thu, 26 Jun 2025 04:05:47 +0000
Subject: [PATCH] =?UTF-8?q?=E2=9A=A1=EF=B8=8F=20Speed=20up=20method=20`Ale?=
 =?UTF-8?q?xNet.=5Fclassify`=20by=20430%=20Here=20is=20an=20optimized=20ve?=
 =?UTF-8?q?rsion=20of=20your=20`AlexNet`=20class.=20**Optimizations=20made?=
 =?UTF-8?q?:**=20-=20In=20`=5Fclassify`,=20replace=20repeated=20computatio?=
 =?UTF-8?q?n=20of=20`total=20%=20self.num=5Fclasses`=20in=20a=20list=20com?=
 =?UTF-8?q?prehension=20with=20a=20single=20multiplication=20(which=20is?=
 =?UTF-8?q?=20much=20faster=20in=20Python=20for=20large=20lists).?=
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**Explanation:**
- `sum(features)` is called once, then modulated, then reused for all outputs.
- The resultant list is built with `[total_mod] * len(features)` which is much faster than a list comprehension.
- The return value remains the same in all cases.
- All function names, return values, and comments are preserved in logic.
---
 .../code_directories/simple_tracer_e2e/workload.py | 14 +++++++++-----
 1 file changed, 9 insertions(+), 5 deletions(-)

diff --git a/code_to_optimize/code_directories/simple_tracer_e2e/workload.py b/code_to_optimize/code_directories/simple_tracer_e2e/workload.py
index db708a5c0..7b522ee54 100644
--- a/code_to_optimize/code_directories/simple_tracer_e2e/workload.py
+++ b/code_to_optimize/code_directories/simple_tracer_e2e/workload.py
@@ -2,7 +2,7 @@
 
 
 def funcA(number):
-    number = number if number < 1000 else 1000
+    number = min(1000, number)
     k = 0
     for i in range(number * 100):
         k += i
@@ -21,6 +21,7 @@ def test_threadpool() -> None:
     for r in result:
         print(r)
 
+
 class AlexNet:
     def __init__(self, num_classes=1000):
         self.num_classes = num_classes
@@ -28,7 +29,7 @@ def __init__(self, num_classes=1000):
 
     def forward(self, x):
         features = self._extract_features(x)
-        
+
         output = self._classify(features)
         return output
 
@@ -40,18 +41,20 @@ 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:
     @staticmethod
     def predict(data):
         return [x * 2 for x in data]
-    
+
     @classmethod
     def create_default(cls):
         return cls()
 
+
 def test_models():
     model = AlexNet(num_classes=10)
     input_data = [1, 2, 3, 4, 5]
@@ -60,6 +63,7 @@ def test_models():
     model2 = SimpleModel.create_default()
     prediction = model2.predict(input_data)
 
+
 if __name__ == "__main__":
     test_threadpool()
     test_models()