[Bugfix] Give exact-shape codec models an unpadded input_ids view (#6775)

Signed-off-by: Inesh Reddy <ineshreddy249@gmail.com>
Signed-off-by: IneshReddy249 <ineshreddy249@gmail.com>
Co-authored-by: Gao Han <hgaoaf@connect.ust.hk>
This commit is contained in:
Inesh Reddy ChappidiandGao Han authored and GitHub committed 2026-09-04 15:28:49 -07:00
1 parent 348fd0fc07
commit 66d938100b
8 files changed
+147 -2

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@@ -1,9 +1,12 @@
# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM-Omni project
import contextlib
from types import SimpleNamespace
import pytest
import torch
from vllm.config import CacheConfig
from vllm.config import CacheConfig, CUDAGraphMode
from vllm.v1.outputs import EMPTY_MODEL_RUNNER_OUTPUT
import vllm_omni.worker.gpu_generation_model_runner as gen_runner_module
@@ -15,6 +18,10 @@ from vllm_omni.worker.gpu_generation_model_runner import (
pytestmark = [pytest.mark.core_model, pytest.mark.cpu]
class _StopExecutionError(Exception):
"""Halts execute_model at the model boundary."""
class _DummyInputBatch:
def __init__(self, num_reqs: int = 1):
self.req_ids = [f"req-{i + 1}" for i in range(num_reqs)]
@@ -98,6 +105,9 @@ class _StubSchedulerOutput:
self.num_scheduled_tokens = {"req-1": total_num_scheduled_tokens}
self.finished_req_ids = set()
self.kv_connector_metadata = None
self.scheduled_encoder_inputs = {}
self.scheduled_spec_decode_tokens = {}
self.num_common_prefix_blocks = 0
def _make_guard_runner():
@@ -109,6 +119,7 @@ def _make_guard_runner():
runner.speculative_config = None
runner.model_config = SimpleNamespace(async_chunk=False)
runner.cache_config = CacheConfig()
runner.kv_cache_config = SimpleNamespace(kv_cache_groups=[])
runner.input_batch = _DummyInputBatch()
runner.model = object()
runner.parallel_config = SimpleNamespace(
@@ -236,3 +247,74 @@ class TestSampleTokensBatched:
with pytest.raises(ValueError, match="length 1 .* 2 requests"):
GPUGenerationModelRunner.sample_tokens(runner)
@pytest.mark.parametrize("exact_shape, expected_len", [(True, 3), (False, 4)])
def test_exact_shape_models_receive_unpadded_input_ids(monkeypatch, exact_shape, expected_len):
"""#6712: the cudagraph dispatcher rounds a 3-token batch up to a capture
size of 4, so ``_preprocess`` returns a 4-element ``input_ids`` while
``seq_token_counts`` stays ``[3]``. Models opting into
``requires_exact_input_shape`` must receive the trimmed view; everything
else must keep the padded buffer.
"""
monkeypatch.setattr(gen_runner_module, "has_ec_transfer", lambda: False)
monkeypatch.setattr(gen_runner_module, "has_kv_transfer_group", lambda: False)
runner = _make_guard_runner()
runner.model = SimpleNamespace(
has_preprocess=True,
requires_request_ids=False,
requires_exact_input_shape=exact_shape,
)
runner.cascade_attn_enabled = False
runner.num_prompt_logprobs = None
runner.vllm_config = None
runner.parallel_config = SimpleNamespace(
distributed_executor_backend=None,
data_parallel_size=1,
use_ubatching=False,
num_ubatches=1,
)
monkeypatch.setattr(GPUGenerationModelRunner, "_prepare_inputs", lambda self, so, nst: (None, None, 1))
monkeypatch.setattr(
GPUGenerationModelRunner,
"_determine_batch_execution_and_padding",
lambda self, **kw: (
CUDAGraphMode.PIECEWISE,
SimpleNamespace(num_tokens=4, num_reqs=1),
False,
None,
None,
),
)
monkeypatch.setattr(GPUGenerationModelRunner, "_get_slot_mappings", lambda self, **kw: (None, None))
monkeypatch.setattr(GPUGenerationModelRunner, "_build_attention_metadata", lambda self, **kw: (None, None))
monkeypatch.setattr(
GPUGenerationModelRunner,
"_maybe_attach_attention_metadata_extensions",
lambda self, **kw: None,
)
monkeypatch.setattr(gen_runner_module, "set_forward_context", lambda *a, **kw: contextlib.nullcontext())
def _fake_preprocess(self, so, num_input_tokens, itensors=None):
return (torch.zeros(num_input_tokens, dtype=torch.int32), None, None, None, {}, None)
monkeypatch.setattr(GPUGenerationModelRunner, "_preprocess", _fake_preprocess)
seen = {}
def _capture(self, **kwargs):
seen["input_ids"] = kwargs["input_ids"]
seen["counts"] = kwargs["model_kwargs"]["seq_token_counts"]
raise _StopExecutionError
monkeypatch.setattr(GPUGenerationModelRunner, "_run_generation_model", _capture)
with pytest.raises(_StopExecutionError):
GPUGenerationModelRunner.execute_model(runner, _StubSchedulerOutput(3))
assert seen["input_ids"].numel() == expected_len
assert seen["counts"] == [3]
if exact_shape:
assert sum(seen["counts"]) == seen["input_ids"].numel()
+38
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@@ -0,0 +1,38 @@
# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM-Omni project
"""Unit tests for the shared runner helpers in vllm_omni.worker.mixins."""
from types import SimpleNamespace
import pytest
import torch
from vllm_omni.worker.mixins import maybe_unpad_input_ids
pytestmark = [pytest.mark.core_model, pytest.mark.cpu]
@pytest.mark.parametrize(
"flag, padded_len, unpadded, expected",
[
(True, 4, 3, 3),
(False, 4, 3, 4),
(True, 3, 3, 3),
],
)
def test_maybe_unpad_input_ids(flag, padded_len, unpadded, expected):
"""#6712: opted-in models get input_ids at the real token count; everything
else keeps the graph-bucket padded buffer."""
model = SimpleNamespace(requires_exact_input_shape=flag)
ids = torch.zeros(padded_len, dtype=torch.int32)
assert maybe_unpad_input_ids(model, ids, unpadded).numel() == expected
def test_maybe_unpad_input_ids_without_capability_attribute():
ids = torch.zeros(4, dtype=torch.int32)
assert maybe_unpad_input_ids(SimpleNamespace(), ids, 3).numel() == 4
def test_maybe_unpad_input_ids_handles_none():
model = SimpleNamespace(requires_exact_input_shape=True)
assert maybe_unpad_input_ids(model, None, 3) is None
@@ -143,6 +143,7 @@ class MiniCPMO45Code2Wav(nn.Module):
replace_runtime_additional_information = True
requires_raw_input_tokens = True
requires_request_ids = True
requires_exact_input_shape = True
has_preprocess = False
has_postprocess = False
@@ -1,3 +1,6 @@
# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM-Omni project
# Copyright 2026 OpenMOSS and the vLLM-Omni team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License").
@@ -226,6 +229,7 @@ class MossTTSCodecDecoder(nn.Module):
has_postprocess: bool = False
enable_update_additional_information: bool = True
requires_raw_input_tokens: bool = True
requires_exact_input_shape: bool = True
_OUTPUT_SAMPLE_RATE: int = 24_000
@@ -1,5 +1,5 @@
# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
# SPDX-FileCopyrightText: Copyright contributors to the vLLM-Omni project
# Copyright 2025 The Qwen team.
"""Inference-only Qwen3-Omni-Moe unified model (thinker + talker + code2wav)."""
@@ -263,6 +263,8 @@ class Qwen3OmniMoeForConditionalGeneration(
)
self.model = self.code2wav
self.requires_raw_input_tokens = True
# torch.split below requires sum(counts) == input_ids.numel() (#6712)
self.requires_exact_input_shape = True
else:
raise ValueError(
f"Invalid model_stage: {self.model_stage}. Must be one of: 'thinker', 'talker', 'code2wav'"
@@ -38,6 +38,7 @@ from vllm_omni.outputs import OmniModelRunnerOutput
from vllm_omni.platforms.npu.worker.npu_ar_model_runner import ExecuteModelState, _ensure_tensor_values
from vllm_omni.platforms.npu.worker.npu_model_runner import OmniNPUModelRunner
from vllm_omni.utils.mm_outputs import partition_payload_list
from vllm_omni.worker.mixins import maybe_unpad_input_ids
from vllm_omni.worker.omni_connector_model_runner_mixin import (
OmniConnectorModelRunnerMixin,
needs_omni_connector,
@@ -336,6 +337,8 @@ class NPUGenerationModelRunner(OmniNPUModelRunner, OmniConnectorModelRunnerMixin
)
# -------------------------------------- Omni-new -------------------------------------------------
# [Omni] Exact-shape models need input_ids at its real token count (#6712).
input_ids = maybe_unpad_input_ids(self.model, input_ids, scheduler_output.total_num_scheduled_tokens)
# [Omni] Pass token counts per request for code2wav output slicing
model_kwargs["seq_token_counts"] = tokens
if getattr(self.model, "requires_request_ids", False):
@@ -42,6 +42,7 @@ from vllm_omni.outputs import OmniModelRunnerOutput
from vllm_omni.utils.mm_outputs import partition_payload_list
from vllm_omni.worker.gpu_ar_model_runner import ExecuteModelState, _ensure_tensor_values
from vllm_omni.worker.gpu_model_runner import OmniGPUModelRunner
from vllm_omni.worker.mixins import maybe_unpad_input_ids
from vllm_omni.worker.omni_connector_model_runner_mixin import (
OmniConnectorModelRunnerMixin,
needs_omni_connector,
@@ -307,6 +308,9 @@ class GPUGenerationModelRunner(OmniGPUModelRunner, OmniConnectorModelRunnerMixin
num_tokens_padded,
intermediate_tensors,
)
# [Omni] Exact-shape models need input_ids at its real token count (#6712).
input_ids = maybe_unpad_input_ids(self.model, input_ids, num_tokens_unpadded)
# [Omni] Pass token counts per request for code2wav output slicing
model_kwargs["seq_token_counts"] = tokens
if getattr(self.model, "requires_request_ids", False):
+11
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@@ -1,3 +1,6 @@
# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM-Omni project
from __future__ import annotations
from typing import Any
@@ -11,3 +14,11 @@ class OmniWorkerMixin:
from vllm_omni.plugins import load_omni_general_plugins
load_omni_general_plugins()
def maybe_unpad_input_ids(model, input_ids, num_tokens_unpadded):
"""Trim cudagraph-bucket padding for models that split a flat ``input_ids``
by per-request ``seq_token_counts``. See #6712."""
if input_ids is not None and getattr(model, "requires_exact_input_shape", False):
return input_ids[:num_tokens_unpadded]
return input_ids