# # Copyright (c) 2025 Huawei Technologies Co., Ltd. All Rights Reserved. # Adapted from vllm/model_executor/models/qwen2_5_vl.py # Copyright 2023 The vLLM team. # # This file is a part of the vllm-ascend project. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. from transformers.models.qwen2_5_omni.configuration_qwen2_5_omni import \ Qwen2_5OmniThinkerConfig from vllm.config import VllmConfig from vllm.model_executor.models.qwen2_5_omni_thinker import ( Qwen2_5OmniThinkerDummyInputsBuilder, Qwen2_5OmniThinkerForConditionalGeneration, Qwen2_5OmniThinkerMultiModalProcessor, Qwen2_5OmniThinkerProcessingInfo) from vllm.model_executor.models.utils import maybe_prefix from vllm.multimodal import MULTIMODAL_REGISTRY from vllm_npu.models.qwen2_5_vl import AscendQwen2_5_VisionTransformer @MULTIMODAL_REGISTRY.register_processor( Qwen2_5OmniThinkerMultiModalProcessor, info=Qwen2_5OmniThinkerProcessingInfo, dummy_inputs=Qwen2_5OmniThinkerDummyInputsBuilder) class AscendQwen2_5OmniThinkerForConditionalGeneration( Qwen2_5OmniThinkerForConditionalGeneration): def __init__(self, *, vllm_config: VllmConfig, prefix: str = ""): super().__init__(vllm_config=vllm_config, prefix=prefix) config: Qwen2_5OmniThinkerConfig = vllm_config.model_config.hf_config.thinker_config quant_config = vllm_config.quant_config # The following code reuse AscendQwen2_5_VisionTransformer from Qwen2_5_VL, # which does not import any model strcut difference. And will not impact # the modeling files removing. self.visual = AscendQwen2_5_VisionTransformer( vision_config=config.vision_config, norm_eps=getattr(config, "rms_norm_eps", 1e-6), quant_config=quant_config, prefix=maybe_prefix(prefix, "visual"), )