add qwen3

vllm-v0.6.2/tests/prompt_adapter/test_multi_adapter_inference.py

@@ -0,0 +1,53 @@
+from vllm import EngineArgs, LLMEngine, SamplingParams
+from vllm.prompt_adapter.request import PromptAdapterRequest
+
+MODEL_PATH = "bigscience/bloomz-560m"
+pa_path = 'stevhliu/bloomz-560m_PROMPT_TUNING_CAUSAL_LM'
+pa_path2 = 'swapnilbp/angry_tweet_ptune'
+
+
+def do_sample(engine):
+
+    prompts = [
+        ("Tweet text: I have complaints! Label: ",
+         SamplingParams(temperature=0.0, max_tokens=3, stop_token_ids=[3]),
+         PromptAdapterRequest("hate_speech", 1, pa_path2, 8)),
+        ("Tweet text: I have no problems Label: ",
+         SamplingParams(temperature=0.0, max_tokens=3, stop_token_ids=[3]),
+         PromptAdapterRequest("hate_speech2", 2, pa_path2, 8)),
+        ("Tweet text: I have complaints! Label: ",
+         SamplingParams(temperature=0.0, max_tokens=3), None),
+        ("Tweet text: I have no problems Label: ",
+         SamplingParams(temperature=0.0, max_tokens=3, stop_token_ids=[3]),
+         PromptAdapterRequest("complain", 3, pa_path, 8)),
+    ]
+
+    request_id = 0
+    results = set()
+    while prompts or engine.has_unfinished_requests():
+        if prompts:
+            prompt, sampling_params, pa_request = prompts.pop(0)
+            engine.add_request(str(request_id),
+                               prompt,
+                               sampling_params,
+                               prompt_adapter_request=pa_request)
+            request_id += 1
+
+        request_outputs = engine.step()
+
+        for request_output in request_outputs:
+            if request_output.finished:
+                results.add(request_output.outputs[0].text)
+    return results
+
+
+def test_multi_prompt_adapters():
+    engine_args = EngineArgs(model=MODEL_PATH,
+                             max_prompt_adapters=3,
+                             enable_prompt_adapter=True,
+                             max_prompt_adapter_token=8)
+    engine = LLMEngine.from_engine_args(engine_args)
+    expected_output = {
+        ' quot;I', 'hate speech', 'no complaint', 'not hate speech'
+    }
+    assert do_sample(engine) == expected_output