[BugFix] Fix cache issue in compilation_config (#31376)

Signed-off-by: Boyuan Feng <boyuan@meta.com>

tests/compile/test_config.py

@@ -428,3 +428,45 @@ def test_cudagraph_sizes_post_init(
             vllm_config.compilation_config.max_cudagraph_capture_size
             == expected_max_size
         )
+
+
+def test_cached_compilation_config():
+    import torch
+    from torch._inductor.utils import run_and_get_code
+
+    from vllm.config import get_cached_compilation_config, set_current_vllm_config
+    from vllm.model_executor.layers.quantization.input_quant_fp8 import QuantFP8
+    from vllm.model_executor.layers.quantization.utils.quant_utils import GroupShape
+
+    dtype = torch.bfloat16
+    device = torch.device("cuda:0")
+    batch_size, num_qo_heads, head_size = 8, 16, 128
+
+    # access and cache default compilation config
+    # default compilation config does not contain +quant_fp8 custom op. If this is
+    # used, the generated code would use inductor-generated triton kernel instead
+    # of the custom op `torch.ops._C.static_scaled_fp8_quant`.
+    get_cached_compilation_config()
+
+    vllm_config = VllmConfig(
+        compilation_config=CompilationConfig(
+            mode=CompilationMode.VLLM_COMPILE,
+            custom_ops=["+quant_fp8"],
+        )
+    )
+
+    # set_current_vllm_config should clear cached compilation config and
+    # use the new compilation_config in vllm_config
+    with set_current_vllm_config(vllm_config):
+        query_quant = QuantFP8(static=True, group_shape=GroupShape.PER_TENSOR)
+        query_quant = torch.compile(query_quant)
+
+        _q_scale = torch.tensor(1.0, dtype=torch.float32, device="cuda")
+        query = torch.randn(
+            batch_size, num_qo_heads * head_size, dtype=dtype, device=device
+        )
+
+        _, code = run_and_get_code(query_quant, query, _q_scale)
+
+    code = " ".join(code)
+    assert "torch.ops._C.static_scaled_fp8_quant.default(" in code