[Bugfix] Fix Minicpm-O-int4 GPTQ model inference (#17397)

Signed-off-by: Isotr0py <2037008807@qq.com>
This commit is contained in:
Isotr0py 2025-04-30 02:21:42 +08:00 committed by GitHub
parent 08e15defa9
commit 2fa2a50bf9
No known key found for this signature in database
GPG Key ID: B5690EEEBB952194
2 changed files with 36 additions and 2 deletions

View File

@ -28,12 +28,16 @@ from typing import (Any, Callable, Literal, Optional, Set, Tuple, TypedDict,
import torch import torch
from torch import nn from torch import nn
from transformers import BatchFeature from transformers import BatchFeature, PretrainedConfig
from transformers.modeling_outputs import BaseModelOutputWithPast from transformers.modeling_outputs import BaseModelOutputWithPast
from transformers.models.whisper.modeling_whisper import ( from transformers.models.whisper.modeling_whisper import (
ACT2FN, WHISPER_ATTENTION_CLASSES, WhisperConfig, WhisperEncoder) ACT2FN, WHISPER_ATTENTION_CLASSES, WhisperConfig, WhisperEncoder)
from vllm.config import VllmConfig from vllm.config import VllmConfig
from vllm.model_executor.layers.quantization import QuantizationConfig
from vllm.model_executor.layers.quantization.gptq import GPTQConfig
from vllm.model_executor.layers.quantization.gptq_marlin import (
GPTQMarlinConfig)
from vllm.multimodal import MULTIMODAL_REGISTRY, MultiModalKwargs from vllm.multimodal import MULTIMODAL_REGISTRY, MultiModalKwargs
from vllm.multimodal.inputs import (MultiModalDataDict, MultiModalFieldConfig, from vllm.multimodal.inputs import (MultiModalDataDict, MultiModalFieldConfig,
NestedTensors) NestedTensors)
@ -512,6 +516,36 @@ class MiniCPMO(MiniCPMV2_6):
self.audio_token_id = None self.audio_token_id = None
def _maybe_ignore_quant_config(self, quant_config: QuantizationConfig):
# GPTQ configs do not have a list of ignored modules, however AutoGPTQ
# seems to avoid vision encoder sections for some models.
# See: https://huggingface.co/openbmb/MiniCPM-o-2_6-int4
if isinstance(quant_config, (GPTQConfig, GPTQMarlinConfig)):
return None
return quant_config
def init_vision_module(
self,
config: PretrainedConfig,
quant_config: Optional[QuantizationConfig] = None,
prefix: str = "",
) -> nn.Module:
# MiniCPMO GPTQ model leave vpm unquantized.
quant_config = self._maybe_ignore_quant_config(quant_config)
return super().init_vision_module(config, quant_config, prefix)
def init_resampler(
self,
embed_dim: int,
vision_dim: int,
quant_config: Optional[QuantizationConfig] = None,
prefix: str = "",
) -> nn.Module:
# MiniCPMO GPTQ model leave resampler unquantized.
quant_config = self._maybe_ignore_quant_config(quant_config)
return super().init_resampler(embed_dim, vision_dim, quant_config,
prefix)
def init_audio_module(self, *, vllm_config: VllmConfig, prefix: str = ""): def init_audio_module(self, *, vllm_config: VllmConfig, prefix: str = ""):
# Do not use parameters temporarily # Do not use parameters temporarily
audio_config = self.config.audio_config audio_config = self.config.audio_config

View File

@ -1181,7 +1181,7 @@ class MiniCPMV2_6(MiniCPMVBaseModel, SupportsLoRA):
def init_vision_module( def init_vision_module(
self, self,
config: PretrainedConfig, config: PretrainedConfig,
quant_config: Optional[QuantizationConfig], quant_config: Optional[QuantizationConfig] = None,
prefix: str = "", prefix: str = "",
) -> nn.Module: ) -> nn.Module:
model = Idefics2VisionTransformer(config.vision_config, model = Idefics2VisionTransformer(config.vision_config,