diff --git a/vllm/v1/attention/backends/triton_attn.py b/vllm/v1/attention/backends/triton_attn.py
index 0dd1d1ccff..71e9c18012 100644
--- a/vllm/v1/attention/backends/triton_attn.py
+++ b/vllm/v1/attention/backends/triton_attn.py
@@ -8,7 +8,6 @@
 import torch
 
 from vllm.config import CUDAGraphMode, VllmConfig
->>>>>>> v0.15.1
 from vllm.config.cache import CacheDType
 from vllm.logger import init_logger
 from vllm.model_executor.layers.quantization.utils.quant_utils import (
@@ -33,6 +32,7 @@
 )
 from vllm.v1.attention.ops.triton_unified_attention import unified_attention
 from vllm.v1.kv_cache_interface import AttentionSpec
+import vllm.envs as envs
 
 logger = init_logger(__name__)
 
diff --git a/vllm/v1/worker/gpu_model_runner.py b/vllm/v1/worker/gpu_model_runner.py
index a36f484e42..fa4f68bc63 100644
--- a/vllm/v1/worker/gpu_model_runner.py
+++ b/vllm/v1/worker/gpu_model_runner.py
@@ -1707,14 +1707,14 @@ def _get_block_table(kv_cache_gid: int):
             blk_table_tensor[num_reqs:num_reqs_padded].fill_(-1)
             return blk_table_tensor
 
-            if not hasattr(self, "rotate"):
-                if not isinstance(self.model.model.layers[0], PPMissingLayer):
-                    self.rotate = self.model.model.layers[0].self_attn.rotary_emb
-                else:
-                    for lay in self.model.model.layers:
-                        if not isinstance(lay, PPMissingLayer):
-                            self.rotate = lay.self_attn.rotary_emb
-                            break
+        if not hasattr(self, "rotate"):
+            if not isinstance(self.model.model.layers[0], PPMissingLayer):
+                self.rotate = self.model.model.layers[0].self_attn.rotary_emb
+            else:
+                for lay in self.model.model.layers:
+                    if not isinstance(lay, PPMissingLayer):
+                        self.rotate = lay.self_attn.rotary_emb
+                        break
 
         assert slot_mappings is not None
         block_table_gid_0 = _get_block_table(0)