203 lines
9.5 KiB
Markdown
203 lines
9.5 KiB
Markdown
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# Documentation
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- Class name: IPAdapterModelHelper __Inspire
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- Category: InspirePack/models
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- Output node: False
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IPAdapterModelHelper节点旨在促进Inspire包中各种模型的集成和管理，确保兼容性和最佳性能。它负责动态加载模型、错误检查，以及应用IPAdapter配置以增强模型的互操作性和功能。
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# Input types
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## Required
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- model
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- 将要应用IPAdapter配置的主要模型。这个参数对于定义将被IPAdapter增强或修改的基础模型至关重要。
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- Comfy dtype: MODEL
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- Python dtype: str
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- clip
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- 指定与主模型一起使用的CLIP模型，以增强性能和兼容性。
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- Comfy dtype: CLIP
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- Python dtype: str
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- preset
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- 定义模型设置的预设配置，决定要加载和应用哪些模型和设置。
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- Comfy dtype: COMBO[STRING]
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- Python dtype: str
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- lora_strength_model
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- 调整应用于模型的LoRA修改的强度，允许对模型的行为进行微调。
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- Comfy dtype: FLOAT
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- Python dtype: float
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- lora_strength_clip
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- 调整应用于CLIP模型的LoRA修改的强度，能够精确控制其与主模型的集成。
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- Comfy dtype: FLOAT
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- Python dtype: float
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- insightface_provider
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- 指定InsightFace模型的提供者，该模型用于面部识别和增强任务。
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- Comfy dtype: COMBO[STRING]
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- Python dtype: str
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- cache_mode
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- 决定模型的缓存策略，特别影响InsightFace模型的缓存和使用方式。
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- Comfy dtype: COMBO[STRING]
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- Python dtype: str
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# Output types
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- IPADAPTER_PIPE
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- 包含IPAdapter和其他模型的管道配置，准备就绪可以进行处理。
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- Comfy dtype: IPADAPTER_PIPE
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- Python dtype: tuple
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- IPADAPTER
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- 加载的IPAdapter模型，准备应用于主模型。
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- Comfy dtype: IPADAPTER
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- Python dtype: object
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- CLIP_VISION
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- 加载并配置用于管道内的CLIP视觉模型。
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- Comfy dtype: CLIP_VISION
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- Python dtype: object
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- INSIGHTFACE
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- 加载用于面部识别和增强任务的InsightFace模型。
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- Comfy dtype: INSIGHTFACE
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- Python dtype: object
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- MODEL
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- 应用了IPAdapter配置的增强模型，准备在管道中进一步使用。
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- Comfy dtype: MODEL
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- Python dtype: object
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- CLIP
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- 加载并配置用于管道内文本-图像任务的CLIP模型。
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- Comfy dtype: CLIP
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- Python dtype: object
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- insightface_cache_key
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- InsightFace模型的缓存键，用于缓存和检索目的。
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- Comfy dtype: STRING
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- Python dtype: str
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- clip_vision_cache_key
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- CLIP视觉模型的缓存键，便于高效缓存和访问。
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- Comfy dtype: STRING
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- Python dtype: str
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## Usage tips
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- Infra type: `CPU`
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- Common nodes: unknown
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## Source code
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```python
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class IPAdapterModelHelper:
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@classmethod
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def INPUT_TYPES(s):
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return {
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"required": {
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"model": ("MODEL",),
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"clip": ("CLIP",),
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"preset": (list(model_preset.keys()),),
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"lora_strength_model": ("FLOAT", {"default": 1.0, "min": -20.0, "max": 20.0, "step": 0.01}),
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"lora_strength_clip": ("FLOAT", {"default": 1.0, "min": -20.0, "max": 20.0, "step": 0.01}),
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"insightface_provider": (["CPU", "CUDA", "ROCM"], ),
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"cache_mode": (["insightface only", "clip_vision only", "all", "none"], {"default": "insightface only"}),
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},
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"hidden": {"unique_id": "UNIQUE_ID"}
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}
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RETURN_TYPES = ("IPADAPTER_PIPE", "IPADAPTER", "CLIP_VISION", "INSIGHTFACE", "MODEL", "CLIP", "STRING", "STRING")
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RETURN_NAMES = ("IPADAPTER_PIPE", "IPADAPTER", "CLIP_VISION", "INSIGHTFACE", "MODEL", "CLIP", "insightface_cache_key", "clip_vision_cache_key")
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FUNCTION = "doit"
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CATEGORY = "InspirePack/models"
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def doit(self, model, clip, preset, lora_strength_model, lora_strength_clip, insightface_provider, cache_mode="none", unique_id=None):
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if 'IPAdapter' not in nodes.NODE_CLASS_MAPPINGS:
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utils.try_install_custom_node('https://github.com/cubiq/ComfyUI_IPAdapter_plus',
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"To use 'IPAdapterModelHelper' node, 'ComfyUI IPAdapter Plus' extension is required.")
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raise Exception(f"[ERROR] To use IPAdapterModelHelper, you need to install 'ComfyUI IPAdapter Plus'")
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is_sdxl_preset = 'SDXL' in preset
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is_sdxl_model = isinstance(clip.tokenizer, sdxl_clip.SDXLTokenizer)
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if is_sdxl_preset != is_sdxl_model:
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server.PromptServer.instance.send_sync("inspire-node-output-label", {"node_id": unique_id, "output_idx": 1, "label": "IPADAPTER (fail)"})
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server.PromptServer.instance.send_sync("inspire-node-output-label", {"node_id": unique_id, "output_idx": 2, "label": "CLIP_VISION (fail)"})
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server.PromptServer.instance.send_sync("inspire-node-output-label", {"node_id": unique_id, "output_idx": 3, "label": "INSIGHTFACE (fail)"})
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server.PromptServer.instance.send_sync("inspire-node-output-label", {"node_id": unique_id, "output_idx": 4, "label": "MODEL (fail)"})
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server.PromptServer.instance.send_sync("inspire-node-output-label", {"node_id": unique_id, "output_idx": 5, "label": "CLIP (fail)"})
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print(f"[ERROR] IPAdapterModelHelper: You cannot mix SDXL and SD1.5 in the checkpoint and IPAdapter.")
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raise Exception("[ERROR] You cannot mix SDXL and SD1.5 in the checkpoint and IPAdapter.")
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ipadapter, clipvision, lora, is_insightface = model_preset[preset]
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ipadapter, ok1 = lookup_model("ipadapter", ipadapter)
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clipvision, ok2 = lookup_model("clip_vision", clipvision)
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lora, ok3 = lookup_model("loras", lora)
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if ok1 == "OK":
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ok1 = "IPADAPTER"
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else:
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ok1 = f"IPADAPTER ({ok1})"
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if ok2 == "OK":
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ok2 = "CLIP_VISION"
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else:
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ok2 = f"CLIP_VISION ({ok2})"
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server.PromptServer.instance.send_sync("inspire-node-output-label", {"node_id": unique_id, "output_idx": 1, "label": ok1})
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server.PromptServer.instance.send_sync("inspire-node-output-label", {"node_id": unique_id, "output_idx": 2, "label": ok2})
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if ok3 == "FAIL":
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server.PromptServer.instance.send_sync("inspire-node-output-label", {"node_id": unique_id, "output_idx": 4, "label": "MODEL (fail)"})
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server.PromptServer.instance.send_sync("inspire-node-output-label", {"node_id": unique_id, "output_idx": 5, "label": "CLIP (fail)"})
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else:
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server.PromptServer.instance.send_sync("inspire-node-output-label", {"node_id": unique_id, "output_idx": 4, "label": "MODEL"})
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server.PromptServer.instance.send_sync("inspire-node-output-label", {"node_id": unique_id, "output_idx": 5, "label": "CLIP"})
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if ok1 == "FAIL" or ok2 == "FAIL" or ok3 == "FAIL":
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raise Exception("ERROR: Failed to load several models in IPAdapterModelHelper.")
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if ipadapter is not None:
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ipadapter = nodes.NODE_CLASS_MAPPINGS["IPAdapterModelLoader"]().load_ipadapter_model(ipadapter_file=ipadapter)[0]
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ccache_key = ""
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if clipvision is not None:
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if cache_mode in ["clip_vision only", "all"]:
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ccache_key = clipvision
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if ccache_key not in backend_support.cache:
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backend_support.update_cache(ccache_key, "clipvision", (False, nodes.CLIPVisionLoader().load_clip(clip_name=clipvision)[0]))
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_, (_, clipvision) = backend_support.cache[ccache_key]
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else:
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clipvision = nodes.CLIPVisionLoader().load_clip(clip_name=clipvision)[0]
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if lora is not None:
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model, clip = nodes.LoraLoader().load_lora(model=model, clip=clip, lora_name=lora, strength_model=lora_strength_model, strength_clip=lora_strength_clip)
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def f(x):
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return nodes.LoraLoader().load_lora(model=x, clip=clip, lora_name=lora, strength_model=lora_strength_model, strength_clip=lora_strength_clip)
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lora_loader = f
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else:
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def f(x):
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return x
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lora_loader = f
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if 'IPAdapterInsightFaceLoader' in nodes.NODE_CLASS_MAPPINGS:
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insight_face_loader = nodes.NODE_CLASS_MAPPINGS['IPAdapterInsightFaceLoader']().load_insightface
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else:
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print("'ComfyUI IPAdapter Plus' extension is either too outdated or not installed.")
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insight_face_loader = None
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icache_key = ""
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if is_insightface:
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if insight_face_loader is None:
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raise Exception(f"[ERROR] 'ComfyUI IPAdapter Plus' extension is either too outdated or not installed.")
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if cache_mode in ["insightface only", "all"]:
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icache_key = 'insightface-' + insightface_provider
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if icache_key not in backend_support.cache:
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backend_support.update_cache(icache_key, "insightface", (False, insight_face_loader(insightface_provider)[0]))
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_, (_, insightface) = backend_support.cache[icache_key]
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else:
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insightface = insight_face_loader(insightface_provider)[0]
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server.PromptServer.instance.send_sync("inspire-node-output-label", {"node_id": unique_id, "output_idx": 3, "label": "INSIGHTFACE"})
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else:
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insightface = None
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server.PromptServer.instance.send_sync("inspire-node-output-label", {"node_id": unique_id, "output_idx": 3, "label": "INSIGHTFACE (N/A)"})
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pipe = ipadapter, model, clipvision, insightface, lora_loader
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return pipe, ipadapter, clipvision, insightface, model, clip, icache_key, ccache_key
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```
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