add tests

tests/multi_step/test_correctness.py

@@ -0,0 +1,89 @@
+# Test the AsyncLLMEngine with multi-step-decoding and chunked prefill
+
+from typing import List
+
+import pytest
+
+from ..utils import RemoteOpenAIServer
+
+MODELS = [
+    "JackFram/llama-160m",
+]
+NUM_SCHEDULER_STEPS = [8, 16]  # Multi-step decoding steps
+NUM_PROMPTS = [10]
+
+DEFAULT_SERVER_ARGS: List[str] = [
+    "--disable-log-requests",
+    "--use-v2-block-manager",
+    "--worker-use-ray",
+    "--gpu-memory-utilization",
+    "0.85",
+    "--swap-space",
+    "16",
+]
+
+
+async def completions_with_server_args(prompts: List[str], model_name: str,
+                                       server_cli_args: List[str]):
+
+    outputs = None
+    with RemoteOpenAIServer(model_name, server_cli_args) as server:
+        client = server.get_async_client()
+        outputs = await client.completions.create(model=model_name,
+                                                  prompt=prompts,
+                                                  temperature=0,
+                                                  stream=False,
+                                                  max_tokens=5)
+    assert outputs is not None
+
+    return outputs
+
+
+@pytest.mark.parametrize("model", MODELS)
+@pytest.mark.parametrize(("tp_size, pp_size"), [
+    (1, 1),
+    (2, 2),
+    (1, 2),
+    (2, 1),
+])
+@pytest.mark.parametrize("eager_mode", [False, True])
+@pytest.mark.parametrize("num_scheduler_steps", NUM_SCHEDULER_STEPS)
+@pytest.mark.parametrize("num_prompts", NUM_PROMPTS)
+@pytest.mark.asyncio
+async def test_mutli_step_with_chunked_prefill(example_prompts, model: str,
+                                               tp_size: int, pp_size: int,
+                                               eager_mode: int,
+                                               num_scheduler_steps: int,
+                                               num_prompts: int):
+
+    prompts = example_prompts
+    if len(prompts) < num_prompts:
+        prompts = prompts * ((num_prompts // len(prompts)) + 1)
+    prompts = prompts[:num_prompts]
+    assert len(prompts) == num_prompts
+
+    server_args = DEFAULT_SERVER_ARGS + ["--enforce-eager"]
+    ms_server_args = DEFAULT_SERVER_ARGS + \
+        ["--num-scheduler-steps", f"{num_scheduler_steps}"]
+
+    if eager_mode:
+        ms_server_args.append("--enforce-eager")
+
+    distributed_args = [
+        "--tensor-parallel-size",
+        str(tp_size),
+        "--pipeline-parallel-size",
+        str(pp_size),
+    ]
+
+    ref_completions = await completions_with_server_args(
+        prompts, model, server_args + distributed_args)
+    test_completions = await completions_with_server_args(
+        prompts, model, ms_server_args + distributed_args)
+
+    def get_text_generations(completions):
+        return [x.text for x in completions.choices]
+
+    ref_generations = get_text_generations(ref_completions)
+    test_generations = get_text_generations(test_completions)
+    assert ref_generations == test_generations