format

examples/offline_inference.py

@@ -11,7 +11,10 @@
 sampling_params = SamplingParams(temperature=0.8, top_p=0.95)
 
 # Create an LLM.
-llm = LLM(model="facebook/opt-125m", num_scheduler_steps=8, use_v2_block_manager=True, disable_async_output_proc=False)
+llm = LLM(model="facebook/opt-125m",
+          num_scheduler_steps=8,
+          use_v2_block_manager=True,
+          disable_async_output_proc=False)
 # Generate texts from the prompts. The output is a list of RequestOutput objects
 # that contain the prompt, generated text, and other information.
 outputs = llm.generate(prompts, sampling_params)

tests/multi_step/test_correctness_async_llm.py

@@ -47,10 +47,12 @@ async def completions_with_server_args(prompts: List[str], model_name: str,
 @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.parametrize("is_async", [False, True])
 @pytest.mark.asyncio
 async def test_multi_step(example_prompts, model: str, tp_size: int,
                           pp_size: int, eager_mode: int,
-                          num_scheduler_steps: int, num_prompts: int):
+                          num_scheduler_steps: int, num_prompts: int,
+                          is_async: bool):
 
     prompts = example_prompts
     if len(prompts) < num_prompts:
@@ -62,9 +64,9 @@ async def test_multi_step(example_prompts, model: str, tp_size: int,
     ms_server_args = DEFAULT_SERVER_ARGS + \
         ["--num-scheduler-steps", f"{num_scheduler_steps}"]
 
-    # Disable output proc callback as its not supported
-    # with multi-step right now
-    ms_server_args += ["--disable-async-output-proc"]
+    if not is_async:
+        ms_server_args += ["--disable-async-output-proc"]
+
     if eager_mode:
         ms_server_args.append("--enforce-eager")
 

vllm/engine/async_llm_engine.py

@@ -279,6 +279,10 @@ async def step_async(
         scheduler_outputs = cached_outputs.scheduler_outputs
         allow_async_output_proc = cached_outputs.allow_async_output_proc
 
+        # Detect async + multi-step
+        use_async_and_multi_step = (self.scheduler_config.is_multi_step
+                                    and allow_async_output_proc)
+
         ctx = self.scheduler_contexts[virtual_engine]
 
         # skip the scheduler if there are any remaining steps in the seq groups.
@@ -294,11 +298,22 @@ async def step_async(
              allow_async_output_proc
              ) = self.scheduler[virtual_engine].schedule()
 
+            # Detect async + multi-step
+            use_async_and_multi_step = (self.scheduler_config.is_multi_step
+                                        and allow_async_output_proc)
+
             # Maybe switch from async mode to sync mode
             if not allow_async_output_proc and len(ctx.output_queue) > 0:
                 self._process_model_outputs(virtual_engine=virtual_engine,
                                             is_async=True)
 
+            # For async + multi-step, init the queue
+            if use_async_and_multi_step:
+                assert len(ctx.output_queue) == 0
+                assert seq_group_metadata_list is not None
+                ctx.output_queue.append(
+                    (None, seq_group_metadata_list, scheduler_outputs))
+
             if (self.scheduler_config.is_multi_step
                     and scheduler_outputs.num_lookahead_slots > 0):
                 # cache the scheduler outputs for the next iteration if we have
@@ -310,9 +325,6 @@ async def step_async(
         assert seq_group_metadata_list is not None
         assert scheduler_outputs is not None
 
-        assert not (self.scheduler_config.is_multi_step and \
-            allow_async_output_proc)
-
         if not scheduler_outputs.is_empty():
             finished_requests_ids = self.scheduler[
                 virtual_engine].get_and_reset_finished_requests_ids()
@@ -340,6 +352,8 @@ async def step_async(
             if allow_async_output_proc:
                 execute_model_req.async_callback = self.async_callback_data[
                     virtual_engine]
+                execute_model_req.use_async_and_multi_step = \
+                    use_async_and_multi_step
 
             # Execute the model.
             output = await self.model_executor.execute_model_async(
@@ -349,7 +363,7 @@ async def step_async(
             if self.scheduler_config.is_multi_step:
                 self._update_cached_scheduler_output(virtual_engine, output)
         else:
-            if len(ctx.output_queue) > 0:
+            if not use_async_and_multi_step and len(ctx.output_queue) > 0:
                 assert not self.scheduler_config.is_multi_step
                 self._process_model_outputs(virtual_engine=virtual_engine,
                                             is_async=True)
@@ -361,22 +375,25 @@ async def step_async(
                 seq_group.finish_step()
 
         if not self._has_remaining_steps(seq_group_metadata_list):
-            # clear the cache if we have finished all the steps
+            # Clear the cache if we have finished all the steps
             if self.scheduler_config.is_multi_step:
                 self.cached_scheduler_outputs[
                     virtual_engine] = SchedulerOutputState()
 
-            # Cache results in engine
-            ctx.output_queue.append(
-                (output, seq_group_metadata_list, scheduler_outputs))
+            if use_async_and_multi_step:
+                # For async + multi-step, clear the queue
+                ctx.output_queue.clear()
+            else:
+                ctx.output_queue.append(
+                    (output, seq_group_metadata_list, scheduler_outputs))
 
-            if output and allow_async_output_proc:
-                assert len(
-                    output
-                ) == 1, "Multi step decoding does not work with async output processing."  # noqa: E501
-                self._advance_to_next_step(
-                    output[0], seq_group_metadata_list,
-                    scheduler_outputs.scheduled_seq_groups)
+                if output and allow_async_output_proc:
+                    assert len(
+                        output
+                    ) == 1, "Multi step decoding does not work with async output processing."  # noqa: E501
+                    self._advance_to_next_step(
+                        output[0], seq_group_metadata_list,
+                        scheduler_outputs.scheduled_seq_groups)
 
             if not allow_async_output_proc:
                 self._process_model_outputs(virtual_engine=virtual_engine,
@@ -389,7 +406,11 @@ async def step_async(
                 self.do_tracing(scheduler_outputs)
 
         else:
-            ctx.request_outputs = []
+            # Multi-step case
+            if use_async_and_multi_step:
+                return []
+            else:
+                ctx.request_outputs = []
 
         if not self.has_unfinished_requests():
             # Drain async postprocessor (if exists)

vllm/engine/llm_engine.py

@@ -1268,6 +1268,8 @@ def _process_model_outputs(self,
             (outputs, seq_group_metadata_list,
              scheduler_outputs) = ctx.output_queue.popleft()
 
+        assert outputs is not None
+
         # Sanity check
         assert len(seq_group_metadata_list) == len(
             scheduler_outputs.scheduled_seq_groups)
@@ -1325,20 +1327,19 @@ def _process_model_outputs(self,
                 self.output_processor.process_outputs(seq_group, output,
                                                       is_async)
 
-        # Free finished sequence groups.
-        if is_multi_step:
-            if is_last_output:
-                for scheduler in self.scheduler:
-                    scheduler.free_finished_seq_groups()
-        else:
-            for scheduler in self.scheduler:
-                scheduler.free_finished_seq_groups()
+        # For async + multi-step, free finished seqs and create outputs
+        # only on the final step.
+        if is_multi_step and not is_last_output:
+            return
+
+        for scheduler in self.scheduler:
+            scheduler.free_finished_seq_groups()
 
         # Create the outputs.
         for i, _ in enumerate(seq_group_metadata_list):
             scheduled_seq_group = scheduler_outputs.scheduled_seq_groups[i]
 
-            if i in finished_before:
+            if not is_multi_step and i in finished_before:
                 continue  # Avoids double processing
 
             seq_group = scheduled_seq_group.seq_group
@@ -1354,10 +1355,7 @@ def _process_model_outputs(self,
 
         # For async + multi-step, do stats only on the last output.
         # Otherwise, do stats if the execution is async
-        if is_multi_step:
-            do_stats = is_last_output
-        else:
-            do_stats = is_async
+        do_stats = is_multi_step or is_async
 
         if do_stats:
             # Log stats.
@@ -1493,6 +1491,7 @@ def step(self) -> List[Union[RequestOutput, EmbeddingRequestOutput]]:
             # For async + multi-step, init the queue
             if use_async_and_multi_step:
                 assert len(ctx.output_queue) == 0
+                assert seq_group_metadata_list is not None
                 ctx.output_queue.append(
                     (None, seq_group_metadata_list, scheduler_outputs))
 
@@ -1533,7 +1532,8 @@ def step(self) -> List[Union[RequestOutput, EmbeddingRequestOutput]]:
             if allow_async_output_proc:
                 execute_model_req.async_callback = self.async_callback_data[
                     virtual_engine]
-                execute_model_req.use_async_and_multi_step = use_async_and_multi_step
+                execute_model_req.use_async_and_multi_step = \
+                    use_async_and_multi_step
 
             output = self.model_executor.execute_model(
                 execute_model_req=execute_model_req)

vllm/worker/multi_step_model_runner.py

@@ -14,9 +14,9 @@
 from vllm import _custom_ops as ops
 from vllm.distributed import get_pp_group
 from vllm.logger import init_logger
-from vllm.sequence import (CompletionSequenceGroupOutput, IntermediateTensors,
-                           Logprob, SamplerOutput, SequenceGroupMetadata,
-                           SequenceOutput, AsyncCallbackData)
+from vllm.sequence import (AsyncCallbackData, CompletionSequenceGroupOutput,
+                           IntermediateTensors, Logprob, SamplerOutput,
+                           SequenceGroupMetadata, SequenceOutput)
 from vllm.worker.model_runner import (GPUModelRunnerBase,
                                       ModelInputForGPUWithSamplingMetadata)
 from vllm.worker.model_runner_base import (
@@ -233,6 +233,8 @@ def _async_process_outputs(self, model_input: StatefulModelInput,
 
     def _final_process_outputs(self, model_input: StatefulModelInput,
                                output_proc_callback: AsyncCallbackData):
+        assert model_input.frozen_model_input is not None
+
         if output_proc_callback is not None:
             output_proc_fn = output_proc_callback.func
             output_proc_kw_args = output_proc_callback.kw_args
@@ -325,13 +327,13 @@ def execute_model(
             frozen_model_input = dataclasses.replace(  # type: ignore
                 model_input.frozen_model_input,
                 async_callback=async_callback)
+            assert frozen_model_input is not None
 
         # Execute the model
-        output = self._base_model_runner.execute_model(
-            frozen_model_input,
-            kv_caches,
-            intermediate_tensors,
-            num_steps=1)
+        output = self._base_model_runner.execute_model(frozen_model_input,
+                                                       kv_caches,
+                                                       intermediate_tensors,
+                                                       num_steps=1)
 
         # record the event for the current step so that the next step can sync
         model_input.record_step_event(current_stream)