wehub-resource-sync
95 lines
3.9 KiB
Python
95 lines
3.9 KiB
Python
# SPDX-License-Identifier: Apache-2.0
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# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
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"""
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Multi-modal processors may be defined in this directory for the following
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reasons:
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- There is no processing file defined by HF Hub or Transformers library.
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- There is a need to override the existing processor to support vLLM.
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"""
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import importlib
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__all__ = [
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"BagelProcessor",
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"CheersProcessor",
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"CohereASRProcessor",
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"DeepseekVLV2Processor",
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"FireRedASR2Processor",
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"FireRedLIDProcessor",
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"FunASRProcessor",
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"GLM4VProcessor",
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"Granite4VisionProcessor",
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"H2OVLProcessor",
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"Moondream3Processor",
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"InternVLProcessor",
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"IsaacProcessor",
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"KimiAudioProcessor",
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"KimiK25Processor",
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"MiMoOmniProcessor",
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"MiniCPMOProcessor",
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"MiniCPMVProcessor",
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"MiniMaxM3VLImageProcessor",
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"MiniMaxM3VLVideoProcessor",
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"MiniMaxVLProcessor",
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"MistralCommonPixtralProcessor",
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"MistralCommonVoxtralProcessor",
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"NanoNemotronVLProcessor",
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"NemotronVLProcessor",
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"LlamaNemotronVLEmbedProcessor",
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"NVLMProcessor",
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"OpenVLAProcessor",
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"OvisProcessor",
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"Ovis2_5Processor",
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"Qwen3ASRProcessor",
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"Step3VLProcessor",
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]
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_CLASS_TO_MODULE: dict[str, str] = {
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"BagelProcessor": "vllm.transformers_utils.processors.bagel",
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"CheersProcessor": "vllm.transformers_utils.processors.cheers",
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"CohereASRProcessor": "vllm.transformers_utils.processors.cohere_asr",
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"DeepseekVLV2Processor": "vllm.transformers_utils.processors.deepseek_vl2",
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"FireRedASR2Processor": "vllm.transformers_utils.processors.fireredasr2",
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"FireRedLIDProcessor": "vllm.transformers_utils.processors.fireredlid",
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"FunASRProcessor": "vllm.transformers_utils.processors.funasr",
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"GLM4VProcessor": "vllm.transformers_utils.processors.glm4v",
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"Granite4VisionProcessor": "vllm.transformers_utils.processors.granite4_vision",
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"H2OVLProcessor": "vllm.transformers_utils.processors.h2ovl",
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"InternVLProcessor": "vllm.transformers_utils.processors.internvl",
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"IsaacProcessor": "vllm.transformers_utils.processors.isaac",
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"KimiAudioProcessor": "vllm.transformers_utils.processors.kimi_audio",
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"KimiK25Processor": "vllm.transformers_utils.processors.kimi_k25",
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"MiMoOmniProcessor": "vllm.transformers_utils.processors.mimo_v2_omni",
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"MiniCPMOProcessor": "vllm.transformers_utils.processors.minicpmo",
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"MiniCPMVProcessor": "vllm.transformers_utils.processors.minicpmv",
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"MiniMaxM3VLImageProcessor": "vllm.transformers_utils.processors.minimax_m3",
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"MiniMaxM3VLVideoProcessor": "vllm.transformers_utils.processors.minimax_m3",
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"MiniMaxVLProcessor": "vllm.transformers_utils.processors.minimax_m3",
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"MistralCommonPixtralProcessor": "vllm.transformers_utils.processors.pixtral",
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"MistralCommonVoxtralProcessor": "vllm.transformers_utils.processors.voxtral",
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"Moondream3Processor": "vllm.transformers_utils.processors.moondream3",
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"NanoNemotronVLProcessor": "vllm.transformers_utils.processors.nano_nemotron_vl",
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"NemotronVLProcessor": "vllm.transformers_utils.processors.nemotron_vl",
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"LlamaNemotronVLEmbedProcessor": "vllm.transformers_utils.processors.nemotron_vl",
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"NVLMProcessor": "vllm.transformers_utils.processors.nvlm_d",
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"OpenVLAProcessor": "vllm.transformers_utils.processors.openvla",
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"OvisProcessor": "vllm.transformers_utils.processors.ovis",
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"Ovis2_5Processor": "vllm.transformers_utils.processors.ovis2_5",
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"Qwen3ASRProcessor": "vllm.transformers_utils.processors.qwen3_asr",
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"Step3VLProcessor": "vllm.transformers_utils.processors.step3_vl",
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}
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def __getattr__(name: str):
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if name in _CLASS_TO_MODULE:
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module_name = _CLASS_TO_MODULE[name]
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module = importlib.import_module(module_name)
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return getattr(module, name)
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raise AttributeError(f"module 'processors' has no attribute '{name}'")
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def __dir__():
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return sorted(list(__all__))
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