462 lines
20 KiB
Python
462 lines
20 KiB
Python
import torch
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import logging
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import weakref
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import os
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import copy
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from pathlib import Path
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import folder_paths
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import comfy.model_management as mm
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import comfy.model_patcher
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from nodes import NODE_CLASS_MAPPINGS as GLOBAL_NODE_CLASS_MAPPINGS
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from .device_utils import (
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get_device_list,
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is_accelerator_available,
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soft_empty_cache_multigpu,
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)
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from .model_management_mgpu import (
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trigger_executor_cache_reset,
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check_cpu_memory_threshold,
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multigpu_memory_log,
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force_full_system_cleanup,
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)
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MGPU_MM_LOG = True
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# Set to "E" for Engineering (DEBUG) or "P" for Production (INFO)
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LOG_LEVEL = "P"
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logger = logging.getLogger("MultiGPU")
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logger.propagate = False
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if not logger.handlers:
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log_level = logging.DEBUG if LOG_LEVEL == "E" else logging.INFO
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handler = logging.StreamHandler()
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formatter = logging.Formatter('%(message)s')
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handler.setFormatter(formatter)
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logger.addHandler(handler)
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logger.setLevel(log_level)
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def mgpu_mm_log_method(self, msg):
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if MGPU_MM_LOG:
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self.info(f"[MultiGPU Model Management] {msg}")
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logger.mgpu_mm_log = mgpu_mm_log_method.__get__(logger, type(logger))
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# Global device state management
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current_device = mm.get_torch_device()
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current_text_encoder_device = mm.text_encoder_device()
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def set_current_device(device):
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global current_device
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current_device = device
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logger.debug(f"[MultiGPU Initialization] current_device set to: {device}")
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def set_current_text_encoder_device(device):
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global current_text_encoder_device
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current_text_encoder_device = device
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logger.debug(f"[MultiGPU Initialization] current_text_encoder_device set to: {device}")
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def override_class(cls):
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class NodeOverride(cls):
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@classmethod
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def INPUT_TYPES(s):
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inputs = copy.deepcopy(cls.INPUT_TYPES())
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devices = get_device_list()
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default_device = devices[1] if len(devices) > 1 else devices[0]
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inputs["optional"] = inputs.get("optional", {})
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inputs["optional"]["device"] = (devices, {"default": default_device})
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return inputs
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CATEGORY = "multigpu"
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FUNCTION = "override"
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def override(self, *args, device=None, **kwargs):
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if device is not None:
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set_current_device(device)
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fn = getattr(super(), cls.FUNCTION)
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out = fn(*args, **kwargs)
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return out
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return NodeOverride
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def override_class_clip(cls):
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class NodeOverride(cls):
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@classmethod
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def INPUT_TYPES(s):
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inputs = copy.deepcopy(cls.INPUT_TYPES())
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devices = get_device_list()
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default_device = devices[1] if len(devices) > 1 else devices[0]
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inputs["optional"] = inputs.get("optional", {})
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inputs["optional"]["device"] = (devices, {"default": default_device})
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return inputs
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CATEGORY = "multigpu"
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FUNCTION = "override"
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def override(self, *args, device=None, **kwargs):
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if device is not None:
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set_current_text_encoder_device(device)
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kwargs['device'] = 'default'
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fn = getattr(super(), cls.FUNCTION)
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out = fn(*args, **kwargs)
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return out
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return NodeOverride
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def override_class_clip_no_device(cls):
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class NodeOverride(cls):
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@classmethod
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def INPUT_TYPES(s):
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inputs = copy.deepcopy(cls.INPUT_TYPES())
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devices = get_device_list()
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default_device = devices[1] if len(devices) > 1 else devices[0]
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inputs["optional"] = inputs.get("optional", {})
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inputs["optional"]["device"] = (devices, {"default": default_device})
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return inputs
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CATEGORY = "multigpu"
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FUNCTION = "override"
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def override(self, *args, device=None, **kwargs):
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if device is not None:
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set_current_text_encoder_device(device)
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fn = getattr(super(), cls.FUNCTION)
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out = fn(*args, **kwargs)
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return out
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return NodeOverride
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def get_torch_device_patched():
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device = None
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if (not is_accelerator_available() or mm.cpu_state == mm.CPUState.CPU or "cpu" in str(current_device).lower()):
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device = torch.device("cpu")
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else:
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devs = set(get_device_list())
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device = torch.device(current_device) if str(current_device) in devs else torch.device("cpu")
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logger.debug(f"[MultiGPU Core Patching] get_torch_device_patched returning device: {device} (current_device={current_device})")
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return device
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def text_encoder_device_patched():
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device = None
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if (not is_accelerator_available() or mm.cpu_state == mm.CPUState.CPU or "cpu" in str(current_text_encoder_device).lower()):
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device = torch.device("cpu")
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else:
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devs = set(get_device_list())
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device = torch.device(current_text_encoder_device) if str(current_text_encoder_device) in devs else torch.device("cpu")
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logger.debug(f"[MultiGPU Core Patching] text_encoder_device_patched returning device: {device} (current_text_encoder_device={current_text_encoder_device})")
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return device
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logger.info(f"[MultiGPU Core Patching] Patching mm.get_torch_device and mm.text_encoder_device")
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logger.debug(f"[MultiGPU DEBUG] Initial current_device: {current_device}")
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logger.debug(f"[MultiGPU DEBUG] Initial current_text_encoder_device: {current_text_encoder_device}")
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mm.get_torch_device = get_torch_device_patched
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mm.text_encoder_device = text_encoder_device_patched
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def check_module_exists(module_path):
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full_path = os.path.join(folder_paths.get_folder_paths("custom_nodes")[0], module_path)
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logger.debug(f"[MultiGPU] Checking for module at {full_path}")
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if not os.path.exists(full_path):
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logger.debug(f"[MultiGPU] Module {module_path} not found - skipping")
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return False
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logger.debug(f"[MultiGPU] Found {module_path}, creating compatible MultiGPU nodes")
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return True
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# Import from nodes.py
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from .nodes import (
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DeviceSelectorMultiGPU,
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HunyuanVideoEmbeddingsAdapter,
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UnetLoaderGGUF,
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UnetLoaderGGUFAdvanced,
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CLIPLoaderGGUF,
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DualCLIPLoaderGGUF,
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TripleCLIPLoaderGGUF,
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QuadrupleCLIPLoaderGGUF,
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LTXVLoader,
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Florence2ModelLoader,
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DownloadAndLoadFlorence2Model,
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CheckpointLoaderNF4,
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LoadFluxControlNet,
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MMAudioModelLoader,
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MMAudioFeatureUtilsLoader,
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MMAudioSampler,
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PulidModelLoader,
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PulidInsightFaceLoader,
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PulidEvaClipLoader,
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HyVideoModelLoader,
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HyVideoVAELoader,
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DownloadAndLoadHyVideoTextEncoder,
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UNetLoaderLP,
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FullCleanupMultiGPU,
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)
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# Import from wanvideo.py
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from .wanvideo import (
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WanVideoModelLoader,
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WanVideoModelLoader_2,
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WanVideoVAELoader,
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LoadWanVideoT5TextEncoder,
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LoadWanVideoClipTextEncoder,
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WanVideoTextEncode,
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WanVideoBlockSwap,
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WanVideoSampler
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)
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# Import from distorch.py
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from .distorch import (
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model_allocation_store,
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create_model_hash,
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register_patched_ggufmodelpatcher,
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analyze_ggml_loading,
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calculate_vvram_allocation_string,
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override_class_with_distorch_gguf,
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override_class_with_distorch_gguf_v2,
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override_class_with_distorch_clip,
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override_class_with_distorch_clip_no_device,
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override_class_with_distorch
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)
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# Import from distorch_2.py for DisTorch v2 SafeTensor support
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from .distorch_2 import (
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safetensor_allocation_store,
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create_safetensor_model_hash,
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register_patched_safetensor_modelpatcher,
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analyze_safetensor_loading,
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calculate_safetensor_vvram_allocation,
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override_class_with_distorch_safetensor_v2,
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override_class_with_distorch_safetensor_v2_clip,
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override_class_with_distorch_safetensor_v2_clip_no_device
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)
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logger.info("[MultiGPU Core Patching] Patching mm.soft_empty_cache for Comprehensive Memory Management (VRAM + CPU + Store Pruning)")
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original_soft_empty_cache = mm.soft_empty_cache
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def soft_empty_cache_distorch2_patched(force=False):
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"""
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Patched mm.soft_empty_cache.
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- Prunes DisTorch store bookkeeping to avoid stale references
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- Manages VRAM: if DisTorch2 models are active, clear allocator caches on all devices;
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otherwise delegate to original mm.soft_empty_cache.
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- Manages CPU RAM: adaptive threshold-based PromptExecutor cache reset;
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and force-triggered reset when explicitly requested (mirrors ComfyUI 'Free memory' button).
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"""
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multigpu_memory_log("patched_soft_empty", f"start:force={force}")
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is_distorch_active = False
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# Detect DisTorch2-managed models
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logger.mgpu_mm_log(f"[DETECT_DEBUG] Checking DisTorch2 active status - loaded models: {len(mm.current_loaded_models)}, store entries: {len(safetensor_allocation_store)}")
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for i, lm in enumerate(mm.current_loaded_models):
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mp = lm.model # weakref call to ModelPatcher
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if mp is not None:
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try:
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model_hash = create_safetensor_model_hash(mp, "cache_patch_check")
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in_store = model_hash in safetensor_allocation_store
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alloc_value = safetensor_allocation_store.get(model_hash, "")
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model_name = type(getattr(mp, 'model', mp)).__name__
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unload_distorch_model = getattr(getattr(mp, 'model', None), '_mgpu_unload_distorch_model', False)
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logger.mgpu_mm_log(f"[DETECT_DEBUG] Model {i}: {model_name}, hash={model_hash[:8]}, in_store={in_store}, alloc_value='{alloc_value}', unload_distorch_model={unload_distorch_model}")
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if in_store and alloc_value:
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is_distorch_active = True
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logger.mgpu_mm_log(f"[DETECT_DEBUG] DisTorch2 ACTIVE detected on model: {model_name}")
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break
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except Exception as e:
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logger.mgpu_mm_log(f"[DETECT_DEBUG] Model {i}: Error during detection - {e}")
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logger.mgpu_mm_log(f"[DETECT_DEBUG] Final DisTorch2 active status: {is_distorch_active}")
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# Phase 2: adaptive CPU memory management
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check_cpu_memory_threshold()
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# VRAM allocator management
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if is_distorch_active:
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logger.mgpu_mm_log("DisTorch2 active: clearing allocator caches on all devices (VRAM)")
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soft_empty_cache_multigpu()
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else:
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logger.mgpu_mm_log("DisTorch2 not active: delegating allocator cache clear (VRAM) to original mm.soft_empty_cache")
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original_soft_empty_cache(force)
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# Optional: return CPU heap to OS (not part of Comfy Core)
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# Phase 1/3: forced executor reset mirrors ComfyUI 'Free memory' semantics
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if force:
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logger.mgpu_mm_log("Force flag active: triggering executor cache reset (CPU)")
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trigger_executor_cache_reset(reason="forced_soft_empty", force=True)
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multigpu_memory_log("patched_soft_empty", "end")
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mm.soft_empty_cache = soft_empty_cache_distorch2_patched
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LARGE_MODEL_THRESHOLD = 2 * (1024**3) # 2 GB threshold for "large" models
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# Import advanced checkpoint loaders
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from .checkpoint_multigpu import (
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CheckpointLoaderAdvancedMultiGPU,
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CheckpointLoaderAdvancedDisTorch2MultiGPU
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)
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# Initialize NODE_CLASS_MAPPINGS
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NODE_CLASS_MAPPINGS = {
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"DeviceSelectorMultiGPU": DeviceSelectorMultiGPU,
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"HunyuanVideoEmbeddingsAdapter": HunyuanVideoEmbeddingsAdapter,
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"CheckpointLoaderAdvancedMultiGPU": CheckpointLoaderAdvancedMultiGPU,
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"CheckpointLoaderAdvancedDisTorch2MultiGPU": CheckpointLoaderAdvancedDisTorch2MultiGPU,
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"UNetLoaderLP": UNetLoaderLP,
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}
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# Standard MultiGPU nodes
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NODE_CLASS_MAPPINGS["UNETLoaderMultiGPU"] = override_class(GLOBAL_NODE_CLASS_MAPPINGS["UNETLoader"])
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NODE_CLASS_MAPPINGS["VAELoaderMultiGPU"] = override_class(GLOBAL_NODE_CLASS_MAPPINGS["VAELoader"])
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NODE_CLASS_MAPPINGS["CLIPLoaderMultiGPU"] = override_class_clip(GLOBAL_NODE_CLASS_MAPPINGS["CLIPLoader"])
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NODE_CLASS_MAPPINGS["DualCLIPLoaderMultiGPU"] = override_class_clip(GLOBAL_NODE_CLASS_MAPPINGS["DualCLIPLoader"])
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if "TripleCLIPLoader" in GLOBAL_NODE_CLASS_MAPPINGS:
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NODE_CLASS_MAPPINGS["TripleCLIPLoaderMultiGPU"] = override_class_clip_no_device(GLOBAL_NODE_CLASS_MAPPINGS["TripleCLIPLoader"])
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if "QuadrupleCLIPLoader" in GLOBAL_NODE_CLASS_MAPPINGS:
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NODE_CLASS_MAPPINGS["QuadrupleCLIPLoaderMultiGPU"] = override_class_clip_no_device(GLOBAL_NODE_CLASS_MAPPINGS["QuadrupleCLIPLoader"])
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NODE_CLASS_MAPPINGS["CLIPVisionLoaderMultiGPU"] = override_class_clip_no_device(GLOBAL_NODE_CLASS_MAPPINGS["CLIPVisionLoader"])
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NODE_CLASS_MAPPINGS["CheckpointLoaderSimpleMultiGPU"] = override_class(GLOBAL_NODE_CLASS_MAPPINGS["CheckpointLoaderSimple"])
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NODE_CLASS_MAPPINGS["ControlNetLoaderMultiGPU"] = override_class(GLOBAL_NODE_CLASS_MAPPINGS["ControlNetLoader"])
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if "DiffusersLoader" in GLOBAL_NODE_CLASS_MAPPINGS:
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NODE_CLASS_MAPPINGS["DiffusersLoaderMultiGPU"] = override_class(GLOBAL_NODE_CLASS_MAPPINGS["DiffusersLoader"])
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if "DiffControlNetLoader" in GLOBAL_NODE_CLASS_MAPPINGS:
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NODE_CLASS_MAPPINGS["DiffControlNetLoaderMultiGPU"] = override_class(GLOBAL_NODE_CLASS_MAPPINGS["DiffControlNetLoader"])
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# DisTorch 2 SafeTensor nodes for FLUX and other safetensor models
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NODE_CLASS_MAPPINGS["UNETLoaderDisTorch2MultiGPU"] = override_class_with_distorch_safetensor_v2(GLOBAL_NODE_CLASS_MAPPINGS["UNETLoader"])
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NODE_CLASS_MAPPINGS["VAELoaderDisTorch2MultiGPU"] = override_class_with_distorch_safetensor_v2(GLOBAL_NODE_CLASS_MAPPINGS["VAELoader"])
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NODE_CLASS_MAPPINGS["CLIPLoaderDisTorch2MultiGPU"] = override_class_with_distorch_safetensor_v2_clip(GLOBAL_NODE_CLASS_MAPPINGS["CLIPLoader"])
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NODE_CLASS_MAPPINGS["DualCLIPLoaderDisTorch2MultiGPU"] = override_class_with_distorch_safetensor_v2_clip(GLOBAL_NODE_CLASS_MAPPINGS["DualCLIPLoader"])
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if "TripleCLIPLoader" in GLOBAL_NODE_CLASS_MAPPINGS:
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NODE_CLASS_MAPPINGS["TripleCLIPLoaderDisTorch2MultiGPU"] = override_class_with_distorch_safetensor_v2_clip_no_device(GLOBAL_NODE_CLASS_MAPPINGS["TripleCLIPLoader"])
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if "QuadrupleCLIPLoader" in GLOBAL_NODE_CLASS_MAPPINGS:
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NODE_CLASS_MAPPINGS["QuadrupleCLIPLoaderDisTorch2MultiGPU"] = override_class_with_distorch_safetensor_v2_clip_no_device(GLOBAL_NODE_CLASS_MAPPINGS["QuadrupleCLIPLoader"])
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NODE_CLASS_MAPPINGS["CLIPVisionLoaderDisTorch2MultiGPU"] = override_class_with_distorch_safetensor_v2_clip_no_device(GLOBAL_NODE_CLASS_MAPPINGS["CLIPVisionLoader"])
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NODE_CLASS_MAPPINGS["CheckpointLoaderSimpleDisTorch2MultiGPU"] = override_class_with_distorch_safetensor_v2(GLOBAL_NODE_CLASS_MAPPINGS["CheckpointLoaderSimple"])
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NODE_CLASS_MAPPINGS["ControlNetLoaderDisTorch2MultiGPU"] = override_class_with_distorch_safetensor_v2(GLOBAL_NODE_CLASS_MAPPINGS["ControlNetLoader"])
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if "DiffusersLoader" in GLOBAL_NODE_CLASS_MAPPINGS:
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NODE_CLASS_MAPPINGS["DiffusersLoaderDisTorch2MultiGPU"] = override_class_with_distorch_safetensor_v2(GLOBAL_NODE_CLASS_MAPPINGS["DiffusersLoader"])
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if "DiffControlNetLoader" in GLOBAL_NODE_CLASS_MAPPINGS:
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NODE_CLASS_MAPPINGS["DiffControlNetLoaderDisTorch2MultiGPU"] = override_class_with_distorch_safetensor_v2(GLOBAL_NODE_CLASS_MAPPINGS["DiffControlNetLoader"])
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# --- Registration Table ---
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logger.info("[MultiGPU] Initiating custom_node Registration. . .")
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dash_line = "-" * 47
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fmt_reg = "{:<30}{:>5}{:>10}"
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logger.info(dash_line)
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logger.info(fmt_reg.format("custom_node", "Found", "Nodes"))
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logger.info(dash_line)
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registration_data = []
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def register_and_count(module_names, node_map):
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found = False
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for name in module_names:
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if check_module_exists(name):
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found = True
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break
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count = 0
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if found:
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initial_len = len(NODE_CLASS_MAPPINGS)
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for key, value in node_map.items():
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NODE_CLASS_MAPPINGS[key] = value
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count = len(NODE_CLASS_MAPPINGS) - initial_len
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registration_data.append({"name": module_names[0], "found": "Y" if found else "N", "count": count})
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return found
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# ComfyUI-LTXVideo
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ltx_nodes = {"LTXVLoaderMultiGPU": override_class(LTXVLoader)}
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register_and_count(["ComfyUI-LTXVideo", "comfyui-ltxvideo"], ltx_nodes)
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# ComfyUI-Florence2
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florence_nodes = {
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"Florence2ModelLoaderMultiGPU": override_class(Florence2ModelLoader),
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"DownloadAndLoadFlorence2ModelMultiGPU": override_class(DownloadAndLoadFlorence2Model)
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}
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register_and_count(["ComfyUI-Florence2", "comfyui-florence2"], florence_nodes)
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# ComfyUI_bitsandbytes_NF4
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nf4_nodes = {"CheckpointLoaderNF4MultiGPU": override_class(CheckpointLoaderNF4)}
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register_and_count(["ComfyUI_bitsandbytes_NF4", "comfyui_bitsandbytes_nf4"], nf4_nodes)
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# x-flux-comfyui
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flux_controlnet_nodes = {"LoadFluxControlNetMultiGPU": override_class(LoadFluxControlNet)}
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register_and_count(["x-flux-comfyui"], flux_controlnet_nodes)
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# ComfyUI-MMAudio
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mmaudio_nodes = {
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"MMAudioModelLoaderMultiGPU": override_class(MMAudioModelLoader),
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"MMAudioFeatureUtilsLoaderMultiGPU": override_class(MMAudioFeatureUtilsLoader),
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"MMAudioSamplerMultiGPU": override_class(MMAudioSampler)
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}
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register_and_count(["ComfyUI-MMAudio", "comfyui-mmaudio"], mmaudio_nodes)
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# ComfyUI-GGUF
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gguf_nodes = {
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"UnetLoaderGGUFDisTorchMultiGPU": override_class_with_distorch_gguf(UnetLoaderGGUF),
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"UnetLoaderGGUFAdvancedDisTorchMultiGPU": override_class_with_distorch_gguf(UnetLoaderGGUFAdvanced),
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"CLIPLoaderGGUFDisTorchMultiGPU": override_class_with_distorch_clip(CLIPLoaderGGUF),
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"DualCLIPLoaderGGUFDisTorchMultiGPU": override_class_with_distorch_clip(DualCLIPLoaderGGUF),
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"TripleCLIPLoaderGGUFDisTorchMultiGPU": override_class_with_distorch_clip_no_device(TripleCLIPLoaderGGUF),
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"QuadrupleCLIPLoaderGGUFDisTorchMultiGPU": override_class_with_distorch_clip_no_device(QuadrupleCLIPLoaderGGUF),
|
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"UnetLoaderGGUFDisTorch2MultiGPU": override_class_with_distorch_safetensor_v2(UnetLoaderGGUF),
|
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"UnetLoaderGGUFAdvancedDisTorch2MultiGPU": override_class_with_distorch_safetensor_v2(UnetLoaderGGUFAdvanced),
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"CLIPLoaderGGUFDisTorch2MultiGPU": override_class_with_distorch_safetensor_v2_clip(CLIPLoaderGGUF),
|
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"DualCLIPLoaderGGUFDisTorch2MultiGPU": override_class_with_distorch_safetensor_v2_clip(DualCLIPLoaderGGUF),
|
|
"TripleCLIPLoaderGGUFDisTorch2MultiGPU": override_class_with_distorch_safetensor_v2_clip_no_device(TripleCLIPLoaderGGUF),
|
|
"QuadrupleCLIPLoaderGGUFDisTorch2MultiGPU": override_class_with_distorch_safetensor_v2_clip_no_device(QuadrupleCLIPLoaderGGUF),
|
|
"UnetLoaderGGUFMultiGPU": override_class(UnetLoaderGGUF),
|
|
"UnetLoaderGGUFAdvancedMultiGPU": override_class(UnetLoaderGGUFAdvanced),
|
|
"CLIPLoaderGGUFMultiGPU": override_class_clip(CLIPLoaderGGUF),
|
|
"DualCLIPLoaderGGUFMultiGPU": override_class_clip(DualCLIPLoaderGGUF),
|
|
"TripleCLIPLoaderGGUFMultiGPU": override_class_clip_no_device(TripleCLIPLoaderGGUF),
|
|
"QuadrupleCLIPLoaderGGUFMultiGPU": override_class_clip_no_device(QuadrupleCLIPLoaderGGUF)
|
|
}
|
|
register_and_count(["ComfyUI-GGUF", "comfyui-gguf"], gguf_nodes)
|
|
|
|
# PuLID_ComfyUI
|
|
pulid_nodes = {
|
|
"PulidModelLoaderMultiGPU": override_class(PulidModelLoader),
|
|
"PulidInsightFaceLoaderMultiGPU": override_class(PulidInsightFaceLoader),
|
|
"PulidEvaClipLoaderMultiGPU": override_class(PulidEvaClipLoader)
|
|
}
|
|
register_and_count(["PuLID_ComfyUI", "pulid_comfyui"], pulid_nodes)
|
|
|
|
# ComfyUI-HunyuanVideoWrapper
|
|
hunyuan_nodes = {
|
|
"HyVideoModelLoaderMultiGPU": override_class(HyVideoModelLoader),
|
|
"HyVideoVAELoaderMultiGPU": override_class(HyVideoVAELoader),
|
|
"DownloadAndLoadHyVideoTextEncoderMultiGPU": override_class(DownloadAndLoadHyVideoTextEncoder)
|
|
}
|
|
register_and_count(["ComfyUI-HunyuanVideoWrapper", "comfyui-hunyuanvideowrapper"], hunyuan_nodes)
|
|
|
|
# ComfyUI-WanVideoWrapper
|
|
wanvideo_nodes = {
|
|
"WanVideoModelLoaderMultiGPU": WanVideoModelLoader,
|
|
"WanVideoModelLoaderMultiGPU_2": WanVideoModelLoader_2,
|
|
"WanVideoVAELoaderMultiGPU": WanVideoVAELoader,
|
|
"LoadWanVideoT5TextEncoderMultiGPU": LoadWanVideoT5TextEncoder,
|
|
"LoadWanVideoClipTextEncoderMultiGPU": LoadWanVideoClipTextEncoder,
|
|
"WanVideoTextEncodeMultiGPU": WanVideoTextEncode,
|
|
"WanVideoBlockSwapMultiGPU": WanVideoBlockSwap,
|
|
"WanVideoSamplerMultiGPU": WanVideoSampler
|
|
}
|
|
register_and_count(["ComfyUI-WanVideoWrapper", "comfyui-wanvideowrapper"], wanvideo_nodes)
|
|
|
|
# Print the registration table
|
|
for item in registration_data:
|
|
logger.info(fmt_reg.format(item['name'], item['found'], str(item['count'])))
|
|
logger.info(dash_line)
|
|
|
|
|
|
# Register maintenance node
|
|
NODE_CLASS_MAPPINGS["FullCleanupMultiGPU"] = FullCleanupMultiGPU
|
|
|
|
logger.info(f"[MultiGPU] Registration complete. Final mappings: {', '.join(NODE_CLASS_MAPPINGS.keys())}")
|