From 1b2bd65e3861bb19f04ab7ff7ab55150ebcba4c9 Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Tue, 21 Apr 2026 04:58:24 +0000
Subject: [PATCH] [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci
---
 scripts/benchmarks/flex_paged_attention.py |  2 +-
 scripts/benchmarks/qwen3_flex_inference.py | 25 +++++++++++-----------
 2 files changed, 14 insertions(+), 13 deletions(-)

diff --git a/scripts/benchmarks/flex_paged_attention.py b/scripts/benchmarks/flex_paged_attention.py
index 146855675b..e76716ab46 100644
--- a/scripts/benchmarks/flex_paged_attention.py
+++ b/scripts/benchmarks/flex_paged_attention.py
@@ -17,7 +17,7 @@ from torch.nn.attention.flex_attention import (
     create_block_mask,
 )
 
-create_block_mask = torch.compile(create_block_mask, dynamic=True)
+create_block_mask = torch.compile(create_block_mask, dynamic = True)
 
 
 def _cdiv(x: int | float | torch.Tensor, multiple: int | float | torch.Tensor):
diff --git a/scripts/benchmarks/qwen3_flex_inference.py b/scripts/benchmarks/qwen3_flex_inference.py
index e78c63c120..d94f695d4b 100644
--- a/scripts/benchmarks/qwen3_flex_inference.py
+++ b/scripts/benchmarks/qwen3_flex_inference.py
@@ -308,8 +308,8 @@ def refresh_lora_merge_from_pristine(base_model, peft_model):
             pristine_w,
             B.to(W.dtype),
             A.to(W.dtype),
-            alpha=module.scaling[adapter0],
-            out=W,
+            alpha = module.scaling[adapter0],
+            out = W,
         )
         for adapter in active[1:]:
             A = module.lora_A[adapter].weight.data
@@ -318,8 +318,8 @@ def refresh_lora_merge_from_pristine(base_model, peft_model):
                 W,
                 B.to(W.dtype),
                 A.to(W.dtype),
-                alpha=module.scaling[adapter],
-                out=W,
+                alpha = module.scaling[adapter],
+                out = W,
             )
         module.merged_adapters = list(active)
         n_refreshed += 1
@@ -343,8 +343,9 @@ def _hash_state_dict(model) -> str:
     return h.hexdigest()
 
 
-def run_drift_verification(base_model, peft_model, n_iters: int = 10,
-                           noise_scale: float = 0.01):
+def run_drift_verification(
+    base_model, peft_model, n_iters: int = 10, noise_scale: float = 0.01
+):
     """Simulate N GRPO iterations: perturb LoRA weights with random noise,
     call `refresh_lora_merge_from_pristine`, repeat. Assert the pristine
     `base_model`'s parameters are bit-identical before and after.
@@ -363,12 +364,12 @@ def run_drift_verification(base_model, peft_model, n_iters: int = 10,
         if not isinstance(module, LoraLayer):
             continue
         for adapter_name in list(module.lora_A.keys()):
-            initial_lora[(name, "A", adapter_name)] = (
-                module.lora_A[adapter_name].weight.data.clone()
-            )
-            initial_lora[(name, "B", adapter_name)] = (
-                module.lora_B[adapter_name].weight.data.clone()
-            )
+            initial_lora[(name, "A", adapter_name)] = module.lora_A[
+                adapter_name
+            ].weight.data.clone()
+            initial_lora[(name, "B", adapter_name)] = module.lora_B[
+                adapter_name
+            ].weight.data.clone()
 
     base_hash_before = _hash_state_dict(base_model)