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[Bugfix] Fix OpenAI parallel sampling when using xgrammar (#11637)

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Signed-off-by: mgoin <michael@neuralmagic.com>
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Michael Goin 2024-12-30 22:43:54 -05:00 committed by GitHub
parent a2a40bcd0d
commit 74fa1d123c
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4 changed files with 17 additions and 13 deletions
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14
tests/entrypoints/openai/test_completion.py
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@ -28,6 +28,8 @@ PA_NAME = "swapnilbp/llama_tweet_ptune"
# need to change to match the prompt adapter # need to change to match the prompt adapter
PA_NUM_VIRTUAL_TOKENS = 8 PA_NUM_VIRTUAL_TOKENS = 8
GUIDED_DECODING_BACKENDS = ["outlines", "lm-format-enforcer", "xgrammar"]
@pytest.fixture(scope="module") @pytest.fixture(scope="module")
def zephyr_lora_files(): def zephyr_lora_files():
@ -635,8 +637,7 @@ async def test_allowed_token_ids(client: openai.AsyncOpenAI):
@pytest.mark.asyncio @pytest.mark.asyncio
@pytest.mark.parametrize("guided_decoding_backend", @pytest.mark.parametrize("guided_decoding_backend", GUIDED_DECODING_BACKENDS)
["outlines", "lm-format-enforcer"])
async def test_guided_json_completion(client: openai.AsyncOpenAI, async def test_guided_json_completion(client: openai.AsyncOpenAI,
guided_decoding_backend: str, guided_decoding_backend: str,
sample_json_schema): sample_json_schema):
@ -658,8 +659,7 @@ async def test_guided_json_completion(client: openai.AsyncOpenAI,
@pytest.mark.asyncio @pytest.mark.asyncio
@pytest.mark.parametrize("guided_decoding_backend", @pytest.mark.parametrize("guided_decoding_backend", GUIDED_DECODING_BACKENDS)
["outlines", "lm-format-enforcer"])
async def test_guided_regex_completion(client: openai.AsyncOpenAI, async def test_guided_regex_completion(client: openai.AsyncOpenAI,
guided_decoding_backend: str, guided_decoding_backend: str,
sample_regex): sample_regex):
@ -680,8 +680,7 @@ async def test_guided_regex_completion(client: openai.AsyncOpenAI,
@pytest.mark.asyncio @pytest.mark.asyncio
@pytest.mark.parametrize("guided_decoding_backend", @pytest.mark.parametrize("guided_decoding_backend", GUIDED_DECODING_BACKENDS)
["outlines", "lm-format-enforcer"])
async def test_guided_choice_completion(client: openai.AsyncOpenAI, async def test_guided_choice_completion(client: openai.AsyncOpenAI,
guided_decoding_backend: str, guided_decoding_backend: str,
sample_guided_choice): sample_guided_choice):
@ -761,8 +760,7 @@ async def test_echo_logprob_completion(client: openai.AsyncOpenAI,
@pytest.mark.asyncio @pytest.mark.asyncio
@pytest.mark.parametrize("guided_decoding_backend", @pytest.mark.parametrize("guided_decoding_backend", GUIDED_DECODING_BACKENDS)
["outlines", "lm-format-enforcer"])
async def test_guided_decoding_type_error(client: openai.AsyncOpenAI, async def test_guided_decoding_type_error(client: openai.AsyncOpenAI,
guided_decoding_backend: str, guided_decoding_backend: str,
sample_json_schema, sample_regex): sample_json_schema, sample_regex):

5
vllm/model_executor/guided_decoding/xgrammar_decoding.py
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@ -1,6 +1,7 @@
# noqa: UP007 # noqa: UP007
from __future__ import annotations from __future__ import annotations
import copy
import json import json
from dataclasses import dataclass, field from dataclasses import dataclass, field
from typing import TYPE_CHECKING, Any from typing import TYPE_CHECKING, Any
@ -309,3 +310,7 @@ class XGrammarLogitsProcessor:
scores = scores.to(device_type).squeeze() scores = scores.to(device_type).squeeze()
return scores return scores
def clone(self) -> XGrammarLogitsProcessor:
"""Deepcopy due to per-sequence state in the matchers"""
return copy.deepcopy(self)

9
vllm/sampling_params.py
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@ -450,15 +450,16 @@ class SamplingParams(
return self._all_stop_token_ids return self._all_stop_token_ids
def clone(self) -> "SamplingParams": def clone(self) -> "SamplingParams":
"""Deep copy excluding LogitsProcessor objects. """Deep copy, but maybe not the LogitsProcessor objects.
LogitsProcessor objects are excluded because they may contain an LogitsProcessor objects may contain an arbitrary, nontrivial amount of
arbitrary, nontrivial amount of data. data that is expensive to copy. However, if not copied, the processor
needs to support parallel decoding for multiple sequences
See https://github.com/vllm-project/vllm/issues/3087 See https://github.com/vllm-project/vllm/issues/3087
""" """
logit_processor_refs = None if self.logits_processors is None else { logit_processor_refs = None if self.logits_processors is None else {
id(lp): lp id(lp): lp.clone() if hasattr(lp, 'clone') else lp
for lp in self.logits_processors for lp in self.logits_processors
} }
return copy.deepcopy(self, memo=logit_processor_refs) return copy.deepcopy(self, memo=logit_processor_refs)

2
vllm/sequence.py
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@ -1372,7 +1372,7 @@ class ParallelSampleSequenceGroup(SequenceGroupBase):
@staticmethod @staticmethod
def add_request(request_id: str, engine, params, **kwargs): def add_request(request_id: str, engine, params, **kwargs):
original_params = params original_params = params
params = copy.deepcopy(original_params) params = original_params.clone()
params.n = 1 params.n = 1
group = ParallelSampleSequenceGroup(request_id) group = ParallelSampleSequenceGroup(request_id)
seqs = [] seqs = []