Fix CI TestChunkedSGMV (#10737)

python/sglang/utils.py

@@ -621,6 +621,12 @@ class CachedKernel:
 
         return complete_args
 
+    def _clear_cache(self):
+        """
+        Clear the kernel cache for testing purposes.
+        """
+        self.kernel_cache.clear()
+
 
 def cached_triton_kernel(key_fn=None):
     """

test/srt/lora/test_chunked_sgmv_backend.py

@@ -10,11 +10,18 @@ from sglang.srt.lora.triton_ops import (
     chunked_sgmv_lora_expand_forward,
     chunked_sgmv_lora_shrink_forward,
 )
+from sglang.srt.lora.triton_ops.chunked_sgmv_expand import _chunked_lora_expand_kernel
+from sglang.srt.lora.triton_ops.chunked_sgmv_shrink import _chunked_lora_shrink_kernel
 from sglang.srt.lora.utils import LoRABatchInfo
 
 CHUNK_SIZE = 16
 
 
+def reset_kernel_cache():
+    _chunked_lora_shrink_kernel._clear_cache()
+    _chunked_lora_expand_kernel._clear_cache()
+
+
 def safe_matmul(a: torch.Tensor, b: torch.Tensor) -> torch.Tensor:
     """Matrix multiplication with mixed precision handling for float16"""
     result = torch.matmul(a.float(), b.float())
@@ -436,6 +443,10 @@ class TestChunkedSGMV(unittest.TestCase):
         List[str],
     ]:
         """Create test batch with specified composition and mode"""
+
+        # Reset kernel cache to avoid cross-test contamination
+        reset_kernel_cache()
+
         seq_lengths = self.generate_sequence_lengths(
             batch_size, batch_mode, 1, self.max_seq_len
         )