[CI][Spec Decode] Add MTP placeholder-token regression coverage

tests/v1/e2e/spec_decode/mtp/test_mtp.py

@@ -7,16 +7,119 @@
 
 from tests.utils import single_gpu_only
 from vllm import SamplingParams
-from vllm.config import CompilationConfig
+from vllm.config import CompilationConfig, CUDAGraphMode
 from vllm.platforms import current_platform
 
 from ..utils import (
     _skip_if_insufficient_gpus_for_tp,
     assert_request_outputs_match,
     evaluate_llm_for_gsm8k,
+    get_spec_decode_metric_value,
     get_test_prompts,
 )
 
+PLACEHOLDER_REGRESSION_MODEL = "Qwen/Qwen3.5-0.8B-Base"
+PLACEHOLDER_REGRESSION_PROMPT = "The capital of France is"
+PLACEHOLDER_REGRESSION_MAX_TOKENS = 16
+PLACEHOLDER_REGRESSION_ALLOWED_TOKEN_ID = 42
+PLACEHOLDER_REGRESSION_NUM_SPEC_TOKENS = 3
+
+
+@pytest.mark.parametrize(
+    "cudagraph_mode",
+    [CUDAGraphMode.PIECEWISE, CUDAGraphMode.FULL_AND_PIECEWISE],
+    ids=["piecewise", "full-and-piecewise"],
+)
+@single_gpu_only
+def test_mtp_rejected_placeholders_match_greedy_token_ids(
+    cudagraph_mode: CUDAGraphMode,
+    vllm_runner,
+):
+    """Rejected MTP padding must not alter the non-speculative token stream."""
+    common_kwargs: dict[str, Any] = {
+        "block_size": None,
+        "max_model_len": 256,
+        "max_num_seqs": 1,
+        "trust_remote_code": True,
+        "enable_chunked_prefill": None,
+        "limit_mm_per_prompt": {"image": 0, "video": 0},
+        "attention_backend": ("TRITON_ATTN" if current_platform.is_rocm() else "auto"),
+    }
+    sampling_params = SamplingParams(
+        temperature=0.0,
+        max_tokens=PLACEHOLDER_REGRESSION_MAX_TOKENS,
+        ignore_eos=True,
+        allowed_token_ids=[PLACEHOLDER_REGRESSION_ALLOWED_TOKEN_ID],
+        logprobs=1,
+    )
+
+    def generate_token_ids(runner) -> tuple[int, ...]:
+        outputs = runner.llm.generate([PLACEHOLDER_REGRESSION_PROMPT], sampling_params)
+        assert outputs and outputs[0].outputs, "Expected one completion"
+        token_ids = tuple(outputs[0].outputs[0].token_ids)
+        assert len(token_ids) == PLACEHOLDER_REGRESSION_MAX_TOKENS
+        return token_ids
+
+    def compilation_config() -> CompilationConfig:
+        return CompilationConfig(
+            cudagraph_mode=cudagraph_mode,
+            cudagraph_capture_sizes=[1, PLACEHOLDER_REGRESSION_NUM_SPEC_TOKENS + 1],
+        )
+
+    with vllm_runner(
+        PLACEHOLDER_REGRESSION_MODEL,
+        compilation_config=compilation_config(),
+        **common_kwargs,
+    ) as ref_runner:
+        ref_mode = (
+            ref_runner.llm.llm_engine.vllm_config.compilation_config.cudagraph_mode
+        )
+        assert ref_mode == cudagraph_mode
+        ref_token_ids = generate_token_ids(ref_runner)
+        expected_token_ids = (PLACEHOLDER_REGRESSION_ALLOWED_TOKEN_ID,) * (
+            PLACEHOLDER_REGRESSION_MAX_TOKENS
+        )
+        assert ref_token_ids == expected_token_ids
+
+    with vllm_runner(
+        PLACEHOLDER_REGRESSION_MODEL,
+        speculative_config={
+            "method": "mtp",
+            "num_speculative_tokens": PLACEHOLDER_REGRESSION_NUM_SPEC_TOKENS,
+            "max_model_len": 256,
+            "rejection_sample_method": "synthetic",
+            "synthetic_acceptance_rates": [0.0]
+            * PLACEHOLDER_REGRESSION_NUM_SPEC_TOKENS,
+        },
+        disable_log_stats=False,
+        compilation_config=compilation_config(),
+        **common_kwargs,
+    ) as spec_runner:
+        spec_mode = (
+            spec_runner.llm.llm_engine.vllm_config.compilation_config.cudagraph_mode
+        )
+        assert spec_mode == cudagraph_mode
+        spec_token_ids = generate_token_ids(spec_runner)
+        metrics = spec_runner.llm.get_metrics()
+        num_drafts = get_spec_decode_metric_value(
+            metrics, "vllm:spec_decode_num_drafts"
+        )
+        num_draft_tokens = get_spec_decode_metric_value(
+            metrics, "vllm:spec_decode_num_draft_tokens"
+        )
+        num_accepted_tokens = get_spec_decode_metric_value(
+            metrics, "vllm:spec_decode_num_accepted_tokens"
+        )
+
+    assert num_drafts > 0, "MTP drafter did not run"
+    assert num_draft_tokens > 0, "MTP drafter did not produce draft tokens"
+    assert num_accepted_tokens == 0, "Synthetic sampler accepted a draft token"
+    assert spec_token_ids == ref_token_ids, (
+        f"MTP changed greedy token ids under {cudagraph_mode.name}:\n"
+        f"  reference={ref_token_ids}\n"
+        f"  speculative={spec_token_ids}"
+    )
+
 
 @pytest.mark.parametrize(
     ["model_setup", "mm_enabled", "expected_accuracy_threshold"],