From f7c494a987365ee469d70faf8ef539dc503b8067 Mon Sep 17 00:00:00 2001 From: "codeflash-ai[bot]" <148906541+codeflash-ai[bot]@users.noreply.github.com> Date: Tue, 1 Jul 2025 22:53:40 +0000 Subject: [PATCH] =?UTF-8?q?=E2=9A=A1=EF=B8=8F=20Speed=20up=20method=20`Ale?= =?UTF-8?q?xNet.=5Fclassify`=20by=20359%=20Here=20is=20an=20optimized=20ve?= =?UTF-8?q?rsion=20of=20your=20code.=20The=20main=20bottleneck=20is=20the?= =?UTF-8?q?=20list=20comprehension,=20which=20recalculates=20`total=20%=20?= =?UTF-8?q?self.num=5Fclasses`=20for=20every=20element=20in=20`features`,?= =?UTF-8?q?=20even=20though=20this=20value=20never=20changes=20within=20a?= =?UTF-8?q?=20single=20call.=20By=20computing=20it=20once=20and=20multiply?= =?UTF-8?q?ing=20it=20with=20`[1]*len(features)`=20(to=20create=20the=20re?= =?UTF-8?q?peated=20list=20quickly),=20we=20save=20significant=20computati?= =?UTF-8?q?on=20time.=20Also,=20using=20`len(features)`=20instead=20of=20i?= =?UTF-8?q?terating=20over=20`features`=20is=20slightly=20faster=20for=20l?= =?UTF-8?q?arge=20lists.?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Here's the rewritten code. **Changes made:** - Compute `total % self.num_classes` only once and store in `mod_val`. - Replace the list comprehension with a single multiplication: `[mod_val] * len(features)`. This avoids both redundant modulo operations and Python's slower list comprehension for repeating a single value. The result and output remain exactly the same. The function is now allocation and compute efficient. --- .../code_directories/simple_tracer_e2e/workload.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) 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 1c6a3f1f4..21db38678 100644 --- a/code_to_optimize/code_directories/simple_tracer_e2e/workload.py +++ b/code_to_optimize/code_directories/simple_tracer_e2e/workload.py @@ -42,7 +42,8 @@ def _extract_features(self, x): def _classify(self, features): total = sum(features) - return [total % self.num_classes for _ in features] + mod_val = total % self.num_classes + return [mod_val] * len(features) class SimpleModel: