[V1] [2/n] Logging and Metrics - OutputProcessor Abstraction (#11973)

Signed-off-by: [email protected] <[email protected]>

tests/v1/engine/test_async_llm.py

@@ -1,5 +1,5 @@
 import asyncio
-from typing import Tuple
+from typing import List, Tuple
 
 import pytest
 
@@ -13,6 +13,7 @@
                 allow_module_level=True)
 
 ENGINE_ARGS = AsyncEngineArgs(model="meta-llama/Llama-3.2-1B",
+                              enforce_eager=True,
                               disable_log_requests=True)
 
 
@@ -53,17 +54,63 @@ async def test_load(monkeypatch):
                     generate(engine, request_id, NUM_EXPECTED_TOKENS)))
 
         # Confirm that we got all the EXPECTED tokens from the requests.
-        failed_request_id = None
-        tokens = None
         for task in tasks:
             num_generated_tokens, request_id = await task
-            if (num_generated_tokens != NUM_EXPECTED_TOKENS
-                    and failed_request_id is None):
-                failed_request_id = request_id
-                tokens = num_generated_tokens
-
-        assert failed_request_id is None, (
-            f"{failed_request_id} generated {tokens} but "
-            f"expected {NUM_EXPECTED_TOKENS}")
+            assert num_generated_tokens == NUM_EXPECTED_TOKENS, (
+                f"{request_id} generated {num_generated_tokens} but "
+                f"expected {NUM_EXPECTED_TOKENS}")
+
+        assert not engine.output_processor.has_unfinished_requests()
+        engine.shutdown()
+
+
+@pytest.mark.asyncio
+async def test_abort(monkeypatch):
+
+    with monkeypatch.context() as m:
+        m.setenv("VLLM_USE_V1", "1")
+
+        engine = AsyncLLM.from_engine_args(ENGINE_ARGS)
+
+        NUM_REQUESTS = 100
+        NUM_EXPECTED_TOKENS = 100
+        REQUEST_IDS_TO_ABORT = range(1, 100, 10)
+
+        request_ids = [f"request-{i}" for i in range(NUM_REQUESTS)]
+
+        # Create concurrent requests.
+        tasks: List[asyncio.Task] = []
+        for request_id in request_ids:
+            tasks.append(
+                asyncio.create_task(
+                    generate(engine, request_id, NUM_EXPECTED_TOKENS)))
+
+        # API server cancels requests when they disconnect.
+        for idx in REQUEST_IDS_TO_ABORT:
+            tasks[idx].cancel()
+            await asyncio.sleep(0.1)
+
+        # Confirm the other requests are okay.
+        for idx, task in enumerate(tasks):
+            # Confirm that it was actually canceled.
+            if idx in REQUEST_IDS_TO_ABORT:
+                with pytest.raises(asyncio.CancelledError):
+                    await task
+            else:
+                # Otherwise, make sure the request was not impacted.
+                num_generated_tokens, request_id = await task
+                assert num_generated_tokens == NUM_EXPECTED_TOKENS, (
+                    f"{request_id} generated {num_generated_tokens} but "
+                    f"expected {NUM_EXPECTED_TOKENS}")
+
+        assert not engine.output_processor.has_unfinished_requests()
+
+        # Confirm we can do another generation.
+        request_id = f"request-{REQUEST_IDS_TO_ABORT[0]}"
+        task = asyncio.create_task(
+            generate(engine, request_id, NUM_EXPECTED_TOKENS))
+        num_generated_tokens, request_id = await task
+        assert num_generated_tokens == NUM_EXPECTED_TOKENS
+        assert not engine.output_processor.has_unfinished_requests()
 
         engine.shutdown()

tests/v1/engine/test_detokenizer.py → tests/v1/engine/test_output_processor.py

@@ -3,11 +3,18 @@
 import pytest
 from transformers import AutoTokenizer
 
+from vllm.engine.arg_utils import EngineArgs
 from vllm.sampling_params import RequestOutputKind, SamplingParams
+from vllm.transformers_utils.tokenizer_group import init_tokenizer_from_configs
 from vllm.v1.engine import EngineCoreOutput, EngineCoreRequest
-from vllm.v1.engine.detokenizer import Detokenizer
+from vllm.v1.engine.output_processor import OutputProcessor
 
 TOKENIZER_NAME = "mistralai/Mistral-7B-Instruct-v0.3"
+VLLM_CONFIG = EngineArgs(model=TOKENIZER_NAME).create_engine_config()
+TOKENIZER_GROUP = init_tokenizer_from_configs(VLLM_CONFIG.model_config,
+                                              VLLM_CONFIG.scheduler_config,
+                                              VLLM_CONFIG.parallel_config,
+                                              VLLM_CONFIG.lora_config)
 tokenizer = AutoTokenizer.from_pretrained(TOKENIZER_NAME)
 
 FULL_STRINGS = [
@@ -66,7 +73,7 @@ def get_outputs(self) -> List[EngineCoreOutput]:
     "request_output_kind",
     [RequestOutputKind.DELTA, RequestOutputKind.FINAL_ONLY])
 def test_incremental_detokenization(request_output_kind: RequestOutputKind):
-    detokenizer = Detokenizer(TOKENIZER_NAME)
+    output_processor = OutputProcessor(TOKENIZER_GROUP, log_stats=False)
     engine_core = MockEngineCore(GENERATION_TOKENS)
 
     # Make N requests.
@@ -93,7 +100,7 @@ def test_incremental_detokenization(request_output_kind: RequestOutputKind):
 
     # Add requests to the detokenizer.
     for request in requests:
-        detokenizer.add_request(request)
+        output_processor.add_request(request)
 
     gen_strings = {}
     gen_tokens = {}
@@ -104,7 +111,9 @@ def test_incremental_detokenization(request_output_kind: RequestOutputKind):
             break
 
         # Step the Detokenizer.
-        request_outputs, requests_to_abort = detokenizer.step(outputs)
+        processed_outputs = output_processor.process_outputs(outputs, )
+        request_outputs = processed_outputs.request_outputs
+        requests_to_abort = processed_outputs.reqs_to_abort
         assert len(requests_to_abort) == 0
 
         # Update tracking.
@@ -128,13 +137,13 @@ def test_incremental_detokenization(request_output_kind: RequestOutputKind):
         assert gen_str == ref_gen_str, f"{gen_str=}, {ref_gen_str=}"
         assert gen_toks == ref_gen_toks, f"{gen_toks=}, {ref_gen_toks=}"
 
-    assert detokenizer.get_num_unfinished_requests() == 0
-    assert not detokenizer.has_unfinished_requests()
+    assert output_processor.get_num_unfinished_requests() == 0
+    assert not output_processor.has_unfinished_requests()
 
 
 @pytest.mark.parametrize("include_stop_str_in_output", [True, False])
 def test_stop_string(include_stop_str_in_output: bool):
-    detokenizer = Detokenizer(TOKENIZER_NAME)
+    output_processor = OutputProcessor(TOKENIZER_GROUP, log_stats=False)
     engine_core = MockEngineCore(GENERATION_TOKENS)
 
     # Make N requests.
@@ -162,7 +171,7 @@ def test_stop_string(include_stop_str_in_output: bool):
 
     # Add requests to the detokenizer.
     for request in requests:
-        detokenizer.add_request(request)
+        output_processor.add_request(request)
 
     gen_strings = {}
     aborted = []
@@ -173,7 +182,9 @@ def test_stop_string(include_stop_str_in_output: bool):
             break
 
         # Step the Detokenizer.
-        request_outputs, requests_to_abort = detokenizer.step(outputs)
+        processed_outputs = output_processor.process_outputs(outputs)
+        request_outputs = processed_outputs.request_outputs
+        requests_to_abort = processed_outputs.reqs_to_abort
         for request_output in request_outputs:
             # If aborted, we should not get a request output.
             assert request_output.request_id not in aborted
@@ -214,5 +225,71 @@ def test_stop_string(include_stop_str_in_output: bool):
             assert gen_str == ref_str_exc_stop, (
                 f"{gen_str=}, {ref_str_exc_stop=}")
 
-    assert detokenizer.get_num_unfinished_requests() == 0
-    assert not detokenizer.has_unfinished_requests()
+    assert output_processor.get_num_unfinished_requests() == 0
+    assert not output_processor.has_unfinished_requests()
+
+
+def test_iteration_stats():
+    output_processor = OutputProcessor(TOKENIZER_GROUP, log_stats=True)
+    engine_core = MockEngineCore(GENERATION_TOKENS)
+
+    # Make N requests.
+    requests = [
+        EngineCoreRequest(
+            request_id=f"request-{idx}",
+            prompt=prompt,
+            prompt_token_ids=prompt_tokens,
+            arrival_time=0,
+            mm_inputs=None,
+            mm_hashes=None,
+            mm_placeholders=None,
+            eos_token_id=None,
+            lora_request=None,
+            sampling_params=SamplingParams(),
+        ) for idx, (
+            prompt,
+            prompt_tokens) in enumerate(zip(PROMPT_STRINGS, PROMPT_TOKENS))
+    ]
+
+    # Add all requests except one to the OutputProcessor.
+    num_active = len(GENERATION_TOKENS) - 1
+    for request in requests[:num_active]:
+        output_processor.add_request(request)
+    inactive_request = requests[num_active]
+
+    # First iteration has 2 prefills.
+    outputs = engine_core.get_outputs()[:num_active]
+    processed_outputs = output_processor.process_outputs(outputs)
+    iteration_stats = processed_outputs.iteration_stats
+    total_prompt_tokens = sum(
+        [len(prompt_tokens) for prompt_tokens in PROMPT_TOKENS[:num_active]])
+
+    assert iteration_stats.num_prompt_tokens == total_prompt_tokens
+    assert iteration_stats.num_generation_tokens == num_active
+
+    # Just decodes in this step.
+    outputs = engine_core.get_outputs()[:num_active]
+    processed_outputs = output_processor.process_outputs(outputs)
+    iteration_stats = processed_outputs.iteration_stats
+
+    assert iteration_stats.num_prompt_tokens == 0
+    assert iteration_stats.num_generation_tokens == num_active
+
+    # Add a new request - prefill and 2 decodes in this step.
+    output_processor.add_request(inactive_request)
+    num_active += 1
+    outputs = engine_core.get_outputs()[:num_active]
+    processed_outputs = output_processor.process_outputs(outputs)
+    iteration_stats = processed_outputs.iteration_stats
+    total_prompt_tokens = len(PROMPT_TOKENS[num_active - 1])
+
+    assert iteration_stats.num_prompt_tokens == total_prompt_tokens
+    assert iteration_stats.num_generation_tokens == num_active
+
+    # Just decodes in this step.
+    outputs = engine_core.get_outputs()[:num_active]
+    processed_outputs = output_processor.process_outputs(outputs)
+    iteration_stats = processed_outputs.iteration_stats
+
+    assert iteration_stats.num_prompt_tokens == 0
+    assert iteration_stats.num_generation_tokens == num_active