Sync from v0.13

tests/v1/e2e/test_cascade_attention.py

@@ -0,0 +1,37 @@
+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
+
+import pytest
+
+from vllm import LLM, SamplingParams
+
+from ...utils import create_new_process_for_each_test
+
+
+@create_new_process_for_each_test()
+@pytest.mark.parametrize("attn_backend", ["FLASH_ATTN", "FLASHINFER"])
+def test_cascade_attention(example_system_message, monkeypatch, attn_backend):
+    prompt = "\n<User>: Implement fibonacci sequence in Python.\n<Claude>:"
+
+    if attn_backend == "FLASHINFER":
+        pytest.skip(
+            "This test is failing with FlashInfer backend and "
+            "needs investigation. See issue #25679."
+        )
+
+    with monkeypatch.context() as m:
+        m.setenv("VLLM_ATTENTION_BACKEND", attn_backend)
+
+        llm = LLM(model="Qwen/Qwen2-1.5B-Instruct")
+        sampling_params = SamplingParams(temperature=0.0, max_tokens=100)
+
+        # No cascade attention.
+        single_prompt = [example_system_message + prompt]
+        responses = llm.generate(single_prompt, sampling_params)
+        ref_output = responses[0].outputs[0].text
+
+        # (Probably) Use cascade attention.
+        prompts = [example_system_message + prompt] * 64
+        responses = llm.generate(prompts, sampling_params)
+        for response in responses:
+            assert response.outputs[0].text == ref_output