John Pollock
@@ -137,7 +137,7 @@ All MultiGPU nodes available for your install can be found in the "multigpu" cat
|
||||
|
||||
## Node Documentation
|
||||
|
||||
Detailed technical documentation is available for all **automatically-detected core MultiGPU and DisTorch2 nodes**, covering 36+ documented nodes with comprehensive parameter details, output specifications, and DisTorch2 allocation guidance where applicable.
|
||||
Detailed technical documentation is available for all **automatically-detected core MultiGPU and DisTorch2 nodes**, covering 70+ documented nodes with comprehensive parameter details, output specifications, and DisTorch2 allocation guidance where applicable.
|
||||
|
||||
- **To access documentation**: Click on any core MultiGPU or DisTorch2 node in ComfyUI and select "Help" (question mark inside a circle) from the resultant menu
|
||||
- **Coverage**: All standard ComfyUI loader nodes (UNet, VAE, Checkpoints, CLIP, ControlNet, Diffusers) plus popular GGUF loader variants
|
||||
@@ -253,19 +253,6 @@ All workflows have been tested on a 2x 3090 + 1060ti linux setup, a 4070 win 11
|
||||
</tr>
|
||||
</table>
|
||||
|
||||
### Florence2
|
||||
|
||||
<table>
|
||||
<tr>
|
||||
<td align="center">
|
||||
<a href="example_workflows/ComfyUI-Florence2%20detailed_caption%20to%20flux.json">
|
||||
<img src="example_workflows/ComfyUI-Florence2%20detailed_caption%20to%20flux.jpg" alt="Florence2 Detailed Caption to FLUX Pipeline" style="max-width:160px; max-height:160px;">
|
||||
<div>Florence2 Detailed Caption to FLUX Pipeline</div>
|
||||
</a>
|
||||
</td>
|
||||
</tr>
|
||||
</table>
|
||||
|
||||
### GGUF
|
||||
|
||||
<table>
|
||||
@@ -286,7 +273,7 @@ All workflows have been tested on a 2x 3090 + 1060ti linux setup, a 4070 win 11
|
||||
</tr>
|
||||
</table>
|
||||
|
||||
### HunyuanVideoWrapper
|
||||
### HunyuanVideoWrapper / Florence2
|
||||
|
||||
<table>
|
||||
<tr>
|
||||
@@ -296,6 +283,12 @@ All workflows have been tested on a 2x 3090 + 1060ti linux setup, a 4070 win 11
|
||||
<div>HunyuanVideoWrapper DisTorch (Legacy, Deprecated)</div>
|
||||
</a>
|
||||
</td>
|
||||
<td align="center">
|
||||
<a href="example_workflows/ComfyUI-Florence2%20detailed_caption%20to%20flux.json">
|
||||
<img src="example_workflows/ComfyUI-Florence2%20detailed_caption%20to%20flux.jpg" alt="Florence2 Detailed Caption to FLUX Pipeline" style="max-width:160px; max-height:160px;">
|
||||
<div>Florence2 Detailed Caption to FLUX Pipeline</div>
|
||||
</a>
|
||||
</td>
|
||||
</tr>
|
||||
</table>
|
||||
|
||||
|
||||
@@ -269,8 +269,6 @@ from .wrappers import (
|
||||
override_class_with_distorch_safetensor_v2_clip_no_device,
|
||||
)
|
||||
from .distorch_2 import (
|
||||
safetensor_allocation_store,
|
||||
create_safetensor_model_hash,
|
||||
register_patched_safetensor_modelpatcher,
|
||||
analyze_safetensor_loading,
|
||||
calculate_safetensor_vvram_allocation,
|
||||
|
||||
+7
-11
@@ -9,7 +9,7 @@ import comfy.clip_vision
|
||||
from comfy.sd import VAE, CLIP
|
||||
from .device_utils import get_device_list, soft_empty_cache_multigpu
|
||||
from .model_management_mgpu import multigpu_memory_log
|
||||
from .distorch_2 import safetensor_allocation_store, safetensor_settings_store, create_safetensor_model_hash, register_patched_safetensor_modelpatcher
|
||||
from .distorch_2 import register_patched_safetensor_modelpatcher
|
||||
|
||||
logger = logging.getLogger("MultiGPU")
|
||||
|
||||
@@ -108,12 +108,10 @@ def patched_load_state_dict_guess_config(sd, output_vae=True, output_clip=True,
|
||||
|
||||
if distorch_config and 'unet_allocation' in distorch_config:
|
||||
register_patched_safetensor_modelpatcher()
|
||||
model_hash = create_safetensor_model_hash(model_patcher, "checkpoint_loader_unet")
|
||||
safetensor_allocation_store[model_hash] = distorch_config['unet_allocation']
|
||||
safetensor_settings_store[model_hash] = distorch_config.get('unet_settings','')
|
||||
model.is_distorch = True
|
||||
inner_model = model_patcher.model
|
||||
inner_model._distorch_v2_meta = {"full_allocation": distorch_config['unet_allocation']}
|
||||
logger.info(f"[CHECKPOINT_META] UNET inner_model id=0x{id(inner_model):x}")
|
||||
model._distorch_high_precision_loras = distorch_config.get('high_precision_loras', True)
|
||||
logger.mgpu_mm_log(f"Stored DisTorch2 config for UNet (hash {model_hash[:8]}): {distorch_config['unet_allocation']}")
|
||||
|
||||
model.load_model_weights(sd, diffusion_model_prefix)
|
||||
multigpu_memory_log(f"unet:{config_hash[:8]}", "post-weights")
|
||||
@@ -145,12 +143,10 @@ def patched_load_state_dict_guess_config(sd, output_vae=True, output_clip=True,
|
||||
if distorch_config and 'clip_allocation' in distorch_config:
|
||||
if hasattr(clip, 'patcher'):
|
||||
register_patched_safetensor_modelpatcher()
|
||||
clip_hash = create_safetensor_model_hash(clip.patcher, "checkpoint_loader_clip")
|
||||
safetensor_allocation_store[clip_hash] = distorch_config['clip_allocation']
|
||||
safetensor_settings_store[clip_hash] = distorch_config.get('clip_settings','')
|
||||
clip.patcher.model.is_distorch = True
|
||||
inner_clip = clip.patcher.model
|
||||
inner_clip._distorch_v2_meta = {"full_allocation": distorch_config['clip_allocation']}
|
||||
logger.info(f"[CHECKPOINT_META] CLIP inner_model id=0x{id(inner_clip):x}")
|
||||
clip.patcher.model._distorch_high_precision_loras = distorch_config.get('high_precision_loras', True)
|
||||
logger.info(f"Stored DisTorch2 config for CLIP (hash {clip_hash[:8]}): {distorch_config['clip_allocation']}")
|
||||
|
||||
m, u = clip.load_sd(clip_sd, full_model=True) # This respects the patched text_encoder_device
|
||||
if len(m) > 0: logger.warning(f"CLIP missing keys: {m}")
|
||||
|
||||
+245
@@ -0,0 +1,245 @@
|
||||
{
|
||||
"6": {
|
||||
"inputs": {
|
||||
"text": [
|
||||
"47",
|
||||
2
|
||||
],
|
||||
"clip": [
|
||||
"39",
|
||||
0
|
||||
]
|
||||
},
|
||||
"class_type": "CLIPTextEncode",
|
||||
"_meta": {
|
||||
"title": "CLIP Text Encode (Positive Prompt)"
|
||||
}
|
||||
},
|
||||
"8": {
|
||||
"inputs": {
|
||||
"samples": [
|
||||
"13",
|
||||
0
|
||||
],
|
||||
"vae": [
|
||||
"40",
|
||||
0
|
||||
]
|
||||
},
|
||||
"class_type": "VAEDecode",
|
||||
"_meta": {
|
||||
"title": "VAE Decode"
|
||||
}
|
||||
},
|
||||
"9": {
|
||||
"inputs": {
|
||||
"filename_prefix": "MultiGPU",
|
||||
"images": [
|
||||
"8",
|
||||
0
|
||||
]
|
||||
},
|
||||
"class_type": "SaveImage",
|
||||
"_meta": {
|
||||
"title": "Save Image"
|
||||
}
|
||||
},
|
||||
"13": {
|
||||
"inputs": {
|
||||
"noise": [
|
||||
"25",
|
||||
0
|
||||
],
|
||||
"guider": [
|
||||
"22",
|
||||
0
|
||||
],
|
||||
"sampler": [
|
||||
"16",
|
||||
0
|
||||
],
|
||||
"sigmas": [
|
||||
"17",
|
||||
0
|
||||
],
|
||||
"latent_image": [
|
||||
"27",
|
||||
0
|
||||
]
|
||||
},
|
||||
"class_type": "SamplerCustomAdvanced",
|
||||
"_meta": {
|
||||
"title": "SamplerCustomAdvanced"
|
||||
}
|
||||
},
|
||||
"16": {
|
||||
"inputs": {
|
||||
"sampler_name": "euler"
|
||||
},
|
||||
"class_type": "KSamplerSelect",
|
||||
"_meta": {
|
||||
"title": "KSamplerSelect"
|
||||
}
|
||||
},
|
||||
"17": {
|
||||
"inputs": {
|
||||
"scheduler": "simple",
|
||||
"steps": 20,
|
||||
"denoise": 1,
|
||||
"model": [
|
||||
"30",
|
||||
0
|
||||
]
|
||||
},
|
||||
"class_type": "BasicScheduler",
|
||||
"_meta": {
|
||||
"title": "BasicScheduler"
|
||||
}
|
||||
},
|
||||
"22": {
|
||||
"inputs": {
|
||||
"model": [
|
||||
"30",
|
||||
0
|
||||
],
|
||||
"conditioning": [
|
||||
"26",
|
||||
0
|
||||
]
|
||||
},
|
||||
"class_type": "BasicGuider",
|
||||
"_meta": {
|
||||
"title": "BasicGuider"
|
||||
}
|
||||
},
|
||||
"25": {
|
||||
"inputs": {
|
||||
"noise_seed": 66527593966288
|
||||
},
|
||||
"class_type": "RandomNoise",
|
||||
"_meta": {
|
||||
"title": "RandomNoise"
|
||||
}
|
||||
},
|
||||
"26": {
|
||||
"inputs": {
|
||||
"guidance": 3.5,
|
||||
"conditioning": [
|
||||
"6",
|
||||
0
|
||||
]
|
||||
},
|
||||
"class_type": "FluxGuidance",
|
||||
"_meta": {
|
||||
"title": "FluxGuidance"
|
||||
}
|
||||
},
|
||||
"27": {
|
||||
"inputs": {
|
||||
"width": 1024,
|
||||
"height": 1024,
|
||||
"batch_size": 1
|
||||
},
|
||||
"class_type": "EmptySD3LatentImage",
|
||||
"_meta": {
|
||||
"title": "EmptySD3LatentImage"
|
||||
}
|
||||
},
|
||||
"30": {
|
||||
"inputs": {
|
||||
"max_shift": 1.15,
|
||||
"base_shift": 0.5,
|
||||
"width": 1024,
|
||||
"height": 1024,
|
||||
"model": [
|
||||
"38",
|
||||
0
|
||||
]
|
||||
},
|
||||
"class_type": "ModelSamplingFlux",
|
||||
"_meta": {
|
||||
"title": "ModelSamplingFlux"
|
||||
}
|
||||
},
|
||||
"38": {
|
||||
"inputs": {
|
||||
"unet_name": "flux1-dev-fp8.safetensors",
|
||||
"weight_dtype": "default",
|
||||
"device": "cuda:0"
|
||||
},
|
||||
"class_type": "UNETLoaderMultiGPU",
|
||||
"_meta": {
|
||||
"title": "UNETLoaderMultiGPU"
|
||||
}
|
||||
},
|
||||
"39": {
|
||||
"inputs": {
|
||||
"clip_name1": "t5xxl_fp8_e4m3fn_scaled.safetensors",
|
||||
"clip_name2": "clip_l.safetensors",
|
||||
"type": "flux",
|
||||
"device": "cpu"
|
||||
},
|
||||
"class_type": "DualCLIPLoaderMultiGPU",
|
||||
"_meta": {
|
||||
"title": "DualCLIPLoaderMultiGPU"
|
||||
}
|
||||
},
|
||||
"40": {
|
||||
"inputs": {
|
||||
"vae_name": "ae.safetensors",
|
||||
"device": "cuda:1"
|
||||
},
|
||||
"class_type": "VAELoaderMultiGPU",
|
||||
"_meta": {
|
||||
"title": "VAELoaderMultiGPU"
|
||||
}
|
||||
},
|
||||
"44": {
|
||||
"inputs": {
|
||||
"image": "ComfyUI-Florence2 detailed_caption to flux.jpg"
|
||||
},
|
||||
"class_type": "LoadImage",
|
||||
"_meta": {
|
||||
"title": "Load Image"
|
||||
}
|
||||
},
|
||||
"45": {
|
||||
"inputs": {
|
||||
"model": "MiaoshouAI/Florence-2-large-PromptGen-v2.0",
|
||||
"precision": "fp16",
|
||||
"attention": "sdpa",
|
||||
"convert_to_safetensors": "cuda:1",
|
||||
"device": "cuda:1",
|
||||
"offload_device": "cpu"
|
||||
},
|
||||
"class_type": "DownloadAndLoadFlorence2ModelMultiGPU",
|
||||
"_meta": {
|
||||
"title": "DownloadAndLoadFlorence2ModelMultiGPU"
|
||||
}
|
||||
},
|
||||
"47": {
|
||||
"inputs": {
|
||||
"text_input": "",
|
||||
"task": "detailed_caption",
|
||||
"fill_mask": true,
|
||||
"keep_model_loaded": true,
|
||||
"max_new_tokens": 4096,
|
||||
"num_beams": 3,
|
||||
"do_sample": true,
|
||||
"output_mask_select": "",
|
||||
"seed": 61577449829591,
|
||||
"image": [
|
||||
"44",
|
||||
0
|
||||
],
|
||||
"florence2_model": [
|
||||
"45",
|
||||
0
|
||||
]
|
||||
},
|
||||
"class_type": "Florence2Run",
|
||||
"_meta": {
|
||||
"title": "Florence2Run"
|
||||
}
|
||||
}
|
||||
}
|
||||
+193
@@ -0,0 +1,193 @@
|
||||
{
|
||||
"6": {
|
||||
"inputs": {
|
||||
"text": "A towering technological monolith in a cyberpunk cityscape at night, with \"GGUF\" emblazoned across its surface in massive neon blue-green mixed with purple letters that illuminate the surrounding buildings. The text occupies the central third of the frame, crafted from glowing plasma tubes and crackling energy. Rain-slicked streets below reflect the brilliant signage, while holographic advertisements and flying vehicles populate the background. Moody atmospheric lighting, heavy contrast, photorealistic textures, cinematic color grading. ",
|
||||
"clip": [
|
||||
"45",
|
||||
0
|
||||
]
|
||||
},
|
||||
"class_type": "CLIPTextEncode",
|
||||
"_meta": {
|
||||
"title": "CLIP Text Encode (Positive Prompt)"
|
||||
}
|
||||
},
|
||||
"8": {
|
||||
"inputs": {
|
||||
"samples": [
|
||||
"13",
|
||||
0
|
||||
],
|
||||
"vae": [
|
||||
"40",
|
||||
0
|
||||
]
|
||||
},
|
||||
"class_type": "VAEDecode",
|
||||
"_meta": {
|
||||
"title": "VAE Decode"
|
||||
}
|
||||
},
|
||||
"9": {
|
||||
"inputs": {
|
||||
"filename_prefix": "MultiGPU",
|
||||
"images": [
|
||||
"8",
|
||||
0
|
||||
]
|
||||
},
|
||||
"class_type": "SaveImage",
|
||||
"_meta": {
|
||||
"title": "Save Image"
|
||||
}
|
||||
},
|
||||
"13": {
|
||||
"inputs": {
|
||||
"noise": [
|
||||
"25",
|
||||
0
|
||||
],
|
||||
"guider": [
|
||||
"22",
|
||||
0
|
||||
],
|
||||
"sampler": [
|
||||
"16",
|
||||
0
|
||||
],
|
||||
"sigmas": [
|
||||
"17",
|
||||
0
|
||||
],
|
||||
"latent_image": [
|
||||
"27",
|
||||
0
|
||||
]
|
||||
},
|
||||
"class_type": "SamplerCustomAdvanced",
|
||||
"_meta": {
|
||||
"title": "SamplerCustomAdvanced"
|
||||
}
|
||||
},
|
||||
"16": {
|
||||
"inputs": {
|
||||
"sampler_name": "euler"
|
||||
},
|
||||
"class_type": "KSamplerSelect",
|
||||
"_meta": {
|
||||
"title": "KSamplerSelect"
|
||||
}
|
||||
},
|
||||
"17": {
|
||||
"inputs": {
|
||||
"scheduler": "simple",
|
||||
"steps": 20,
|
||||
"denoise": 1,
|
||||
"model": [
|
||||
"30",
|
||||
0
|
||||
]
|
||||
},
|
||||
"class_type": "BasicScheduler",
|
||||
"_meta": {
|
||||
"title": "BasicScheduler"
|
||||
}
|
||||
},
|
||||
"22": {
|
||||
"inputs": {
|
||||
"model": [
|
||||
"30",
|
||||
0
|
||||
],
|
||||
"conditioning": [
|
||||
"26",
|
||||
0
|
||||
]
|
||||
},
|
||||
"class_type": "BasicGuider",
|
||||
"_meta": {
|
||||
"title": "BasicGuider"
|
||||
}
|
||||
},
|
||||
"25": {
|
||||
"inputs": {
|
||||
"noise_seed": 411099137945992
|
||||
},
|
||||
"class_type": "RandomNoise",
|
||||
"_meta": {
|
||||
"title": "RandomNoise"
|
||||
}
|
||||
},
|
||||
"26": {
|
||||
"inputs": {
|
||||
"guidance": 3.5,
|
||||
"conditioning": [
|
||||
"6",
|
||||
0
|
||||
]
|
||||
},
|
||||
"class_type": "FluxGuidance",
|
||||
"_meta": {
|
||||
"title": "FluxGuidance"
|
||||
}
|
||||
},
|
||||
"27": {
|
||||
"inputs": {
|
||||
"width": 1024,
|
||||
"height": 1024,
|
||||
"batch_size": 1
|
||||
},
|
||||
"class_type": "EmptySD3LatentImage",
|
||||
"_meta": {
|
||||
"title": "EmptySD3LatentImage"
|
||||
}
|
||||
},
|
||||
"30": {
|
||||
"inputs": {
|
||||
"max_shift": 1.15,
|
||||
"base_shift": 0.5,
|
||||
"width": 1024,
|
||||
"height": 1024,
|
||||
"model": [
|
||||
"44",
|
||||
0
|
||||
]
|
||||
},
|
||||
"class_type": "ModelSamplingFlux",
|
||||
"_meta": {
|
||||
"title": "ModelSamplingFlux"
|
||||
}
|
||||
},
|
||||
"40": {
|
||||
"inputs": {
|
||||
"vae_name": "ae.safetensors",
|
||||
"device": "cuda:1"
|
||||
},
|
||||
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"title": "WanVideoImageToVideoEncodeMultiGPU"
|
||||
}
|
||||
},
|
||||
"114": {
|
||||
"inputs": {
|
||||
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|
||||
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|
||||
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|
||||
},
|
||||
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|
||||
"_meta": {
|
||||
"title": "WanVideoVAELoaderMultiGPU"
|
||||
}
|
||||
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|
||||
"115": {
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
},
|
||||
"class_type": "WanVideoDecodeMultiGPU",
|
||||
"_meta": {
|
||||
"title": "WanVideoDecodeMultiGPU"
|
||||
}
|
||||
},
|
||||
"116": {
|
||||
"inputs": {
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
"_meta": {
|
||||
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|
||||
}
|
||||
}
|
||||
}
|
||||
+270
@@ -0,0 +1,270 @@
|
||||
{
|
||||
"30": {
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
0
|
||||
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|
||||
},
|
||||
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|
||||
"_meta": {
|
||||
"title": "Video Combine 🎥🅥🅗🅢"
|
||||
}
|
||||
},
|
||||
"52": {
|
||||
"inputs": {
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
},
|
||||
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|
||||
"_meta": {
|
||||
"title": "WanVideo TeaCache"
|
||||
}
|
||||
},
|
||||
"96": {
|
||||
"inputs": {
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
0
|
||||
]
|
||||
},
|
||||
"class_type": "WanVideoControlEmbeds",
|
||||
"_meta": {
|
||||
"title": "WanVideo Control Embeds"
|
||||
}
|
||||
},
|
||||
"97": {
|
||||
"inputs": {
|
||||
"video": "ComfyUI-WanVideoWrapper wanvideo_1_3B control_lora.webm",
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
"format": "AnimateDiff"
|
||||
},
|
||||
"class_type": "VHS_LoadVideo",
|
||||
"_meta": {
|
||||
"title": "Load Video (Upload) 🎥🅥🅗🅢"
|
||||
}
|
||||
},
|
||||
"98": {
|
||||
"inputs": {
|
||||
"lora": "wan2.1-1.3b-control-lora-tile-v1.1_comfy.safetensors",
|
||||
"strength": 1,
|
||||
"low_mem_load": false,
|
||||
"merge_loras": true
|
||||
},
|
||||
"class_type": "WanVideoLoraSelect",
|
||||
"_meta": {
|
||||
"title": "WanVideo Lora Select"
|
||||
}
|
||||
},
|
||||
"103": {
|
||||
"inputs": {
|
||||
"inputcount": 2,
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
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||||
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|
||||
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|
||||
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||||
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|
||||
},
|
||||
"class_type": "ImageConcatMulti",
|
||||
"_meta": {
|
||||
"title": "Image Concatenate Multi"
|
||||
}
|
||||
},
|
||||
"104": {
|
||||
"inputs": {
|
||||
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|
||||
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|
||||
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|
||||
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|
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0
|
||||
]
|
||||
},
|
||||
"class_type": "ImageBlur",
|
||||
"_meta": {
|
||||
"title": "Image Blur"
|
||||
}
|
||||
},
|
||||
"108": {
|
||||
"inputs": {
|
||||
"steps": 30,
|
||||
"cfg": 6,
|
||||
"shift": 5,
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
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|
||||
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|
||||
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|
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|
||||
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|
||||
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||||
],
|
||||
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|
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||||
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|
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|
||||
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||||
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|
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},
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|
||||
"_meta": {
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"title": "WanVideoSamplerMultiGPU"
|
||||
}
|
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},
|
||||
"109": {
|
||||
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|
||||
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|
||||
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|
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|
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},
|
||||
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||||
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"title": "WanVideoVAELoaderMultiGPU"
|
||||
}
|
||||
},
|
||||
"110": {
|
||||
"inputs": {
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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||||
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||||
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|
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|
||||
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|
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},
|
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|
||||
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|
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|
||||
}
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
},
|
||||
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|
||||
"_meta": {
|
||||
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|
||||
}
|
||||
},
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
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|
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|
||||
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||||
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|
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||||
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||||
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||||
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||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
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|
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|
||||
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||||
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|
||||
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|
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
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||||
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|
||||
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||||
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||||
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||||
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|
||||
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|
||||
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|
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|
||||
}
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,263 @@
|
||||
{
|
||||
"37": {
|
||||
"inputs": {
|
||||
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|
||||
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|
||||
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|
||||
},
|
||||
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|
||||
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|
||||
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|
||||
}
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
},
|
||||
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|
||||
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|
||||
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|
||||
}
|
||||
},
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
},
|
||||
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|
||||
"_meta": {
|
||||
"title": "WanVideo Enhance-A-Video"
|
||||
}
|
||||
},
|
||||
"60": {
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
}
|
||||
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|
||||
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|
||||
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|
||||
"positive_prompt": "A towering technological monolith in a cyberpunk cityscape at night, with \"WanVideoWrapper\" and \"T2V\" emblazoned across its surface in massive neon blue-green mixed with purple letters that illuminate the surrounding buildings. The text occupies the center of the frame, crafted from glowing plasma tubes and crackling energy. Rain-slicked streets below reflect the brilliant signage, while holographic advertisements and flying vehicles populate the background. Moody atmospheric lighting, heavy contrast, photorealistic textures, cinematic color grading. ",
|
||||
"negative_prompt": "色调艳丽，过曝，静态，细节模糊不清，字幕，风格，作品，画作，画面，静止，整体发灰，最差质量，低质量，JPEG压缩残留，丑陋的，残缺的，多余的手指，画得不好的手部，画得不好的脸部，畸形的，毁容的，形态畸形的肢体，手指融合，静止不动的画面，杂乱的背景，三条腿，背景人很多，倒着走",
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
],
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
"63": {
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
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|
||||
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||||
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||||
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|
||||
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|
||||
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|
||||
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|
||||
],
|
||||
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|
||||
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|
||||
0
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
"_meta": {
|
||||
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|
||||
}
|
||||
},
|
||||
"65": {
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
},
|
||||
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|
||||
"_meta": {
|
||||
"title": "WanVideoBlockSwapMultiGPU"
|
||||
}
|
||||
},
|
||||
"66": {
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
0
|
||||
]
|
||||
},
|
||||
"class_type": "WanVideoSetBlockSwap",
|
||||
"_meta": {
|
||||
"title": "WanVideo Set BlockSwap"
|
||||
}
|
||||
},
|
||||
"69": {
|
||||
"inputs": {
|
||||
"image": [
|
||||
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|
||||
0
|
||||
]
|
||||
},
|
||||
"class_type": "GetImageSizeAndCount",
|
||||
"_meta": {
|
||||
"title": "Get Image Size & Count"
|
||||
}
|
||||
},
|
||||
"70": {
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
"images": [
|
||||
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|
||||
0
|
||||
]
|
||||
},
|
||||
"class_type": "VHS_VideoCombine",
|
||||
"_meta": {
|
||||
"title": "Video Combine 🎥🅥🅗🅢"
|
||||
}
|
||||
},
|
||||
"72": {
|
||||
"inputs": {
|
||||
"model": "Wan2_1-T2V-14B_fp8_e5m2.safetensors",
|
||||
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{
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||||
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||||
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||||
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"images": [
|
||||
"9",
|
||||
0
|
||||
]
|
||||
},
|
||||
"class_type": "SaveAnimatedWEBP",
|
||||
"_meta": {
|
||||
"title": "SaveAnimatedWEBP"
|
||||
}
|
||||
}
|
||||
}
|
||||
+3
-16
@@ -235,30 +235,17 @@ original_soft_empty_cache = mm.soft_empty_cache
|
||||
def soft_empty_cache_distorch2_patched(force=False):
|
||||
"""Patched mm.soft_empty_cache managing VRAM across all devices, CPU RAM with adaptive thresholding, and DisTorch store pruning."""
|
||||
from .model_management_mgpu import multigpu_memory_log, check_cpu_memory_threshold, trigger_executor_cache_reset
|
||||
from .distorch_2 import safetensor_allocation_store, create_safetensor_model_hash
|
||||
|
||||
is_distorch_active = False
|
||||
|
||||
# Detect DisTorch2-managed models
|
||||
# logger.mgpu_mm_log(f"[DETECT_DEBUG] Checking DisTorch2 active status - loaded models: {len(mm.current_loaded_models)}, store entries: {len(safetensor_allocation_store)}")
|
||||
|
||||
for i, lm in enumerate(mm.current_loaded_models):
|
||||
mp = lm.model # weakref call to ModelPatcher
|
||||
mp = lm.model
|
||||
if mp is not None:
|
||||
model_hash = create_safetensor_model_hash(mp, "cache_patch_check")
|
||||
in_store = model_hash in safetensor_allocation_store
|
||||
alloc_value = safetensor_allocation_store.get(model_hash, "")
|
||||
model_name = type(getattr(mp, 'model', mp)).__name__
|
||||
unload_distorch_model = getattr(getattr(mp, 'model', None), '_mgpu_unload_distorch_model', False)
|
||||
inner_model = mp.model
|
||||
|
||||
#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}")
|
||||
|
||||
if in_store and alloc_value:
|
||||
if hasattr(inner_model, '_distorch_v2_meta'):
|
||||
is_distorch_active = True
|
||||
#logger.mgpu_mm_log(f"[DETECT_DEBUG] DisTorch2 ACTIVE detected on model: {model_name}")
|
||||
break
|
||||
|
||||
#logger.mgpu_mm_log(f"[DETECT_DEBUG] Final DisTorch2 active status: {is_distorch_active}")
|
||||
|
||||
# Phase 2: adaptive CPU memory management
|
||||
check_cpu_memory_threshold()
|
||||
|
||||
+39
-59
@@ -20,38 +20,6 @@ from .device_utils import get_device_list, soft_empty_cache_multigpu
|
||||
from .model_management_mgpu import multigpu_memory_log, force_full_system_cleanup
|
||||
|
||||
|
||||
safetensor_allocation_store = {}
|
||||
safetensor_settings_store = {}
|
||||
|
||||
|
||||
def create_safetensor_model_hash(model, caller):
|
||||
"""Create a unique hash for a safetensor model to track allocations"""
|
||||
if hasattr(model, 'model'):
|
||||
# For ModelPatcher objects
|
||||
actual_model = model.model
|
||||
model_type = type(actual_model).__name__
|
||||
# Use ComfyUI's model_size if available
|
||||
if hasattr(model, 'model_size'):
|
||||
model_size = model.model_size()
|
||||
else:
|
||||
model_size = sum(p.numel() * p.element_size() for p in actual_model.parameters())
|
||||
if hasattr(model, 'model_state_dict'):
|
||||
first_layers = str(list(model.model_state_dict().keys())[:3])
|
||||
else:
|
||||
first_layers = str(list(actual_model.state_dict().keys())[:3])
|
||||
else:
|
||||
# Direct model
|
||||
model_type = type(model).__name__
|
||||
model_size = sum(p.numel() * p.element_size() for p in model.parameters())
|
||||
first_layers = str(list(model.state_dict().keys())[:3])
|
||||
|
||||
identifier = f"{model_type}_{model_size}_{first_layers}"
|
||||
final_hash = hashlib.sha256(identifier.encode()).hexdigest()
|
||||
|
||||
# DEBUG STATEMENT - ALWAYS LOG THE HASH
|
||||
logger.debug(f"[MultiGPU DisTorch V2] Created hash for {caller}: {final_hash[:8]}...")
|
||||
return final_hash
|
||||
|
||||
def register_patched_safetensor_modelpatcher():
|
||||
"""Register and patch the ModelPatcher for distributed safetensor loading"""
|
||||
from comfy.model_patcher import wipe_lowvram_weight, move_weight_functions
|
||||
@@ -128,23 +96,35 @@ def register_patched_safetensor_modelpatcher():
|
||||
device = loaded_model.device
|
||||
base_memory = loaded_model.model_memory_required(device)
|
||||
|
||||
# Check DisTorch flags
|
||||
is_distorch = hasattr(loaded_model.model.model, '_mgpu_virtual_vram_gb')
|
||||
has_eject = hasattr(loaded_model.model.model, '_mgpu_eject_models')
|
||||
|
||||
if has_eject:
|
||||
eject_device = device
|
||||
logger.mgpu_mm_log("DisTorch eject_models=True, is_distorch=True - MAX memory eviction")
|
||||
|
||||
if is_distorch:
|
||||
# is_distorch=True: use compute device allocation size
|
||||
virtual_vram_gb = loaded_model.model.model._mgpu_virtual_vram_gb
|
||||
inner_model = loaded_model.model.model
|
||||
|
||||
if hasattr(inner_model, '_distorch_v2_meta'):
|
||||
meta = inner_model._distorch_v2_meta
|
||||
allocation_str = meta['full_allocation']
|
||||
|
||||
# Parse allocation string: "expert#compute_device;virtual_vram_gb;donors"
|
||||
parts = allocation_str.split('#')
|
||||
virtual_vram_gb = 0.0
|
||||
has_eject = False
|
||||
|
||||
if len(parts) > 1:
|
||||
virtual_vram_str = parts[1]
|
||||
virtual_info = virtual_vram_str.split(';')
|
||||
if len(virtual_info) > 1:
|
||||
virtual_vram_gb = float(virtual_info[1])
|
||||
if len(virtual_info) > 2 and virtual_info[2]:
|
||||
has_eject = True
|
||||
|
||||
if has_eject:
|
||||
eject_device = device
|
||||
logger.mgpu_mm_log("DisTorch eject_models detected - MAX memory eviction")
|
||||
|
||||
virtual_vram_bytes = virtual_vram_gb * (1024**3)
|
||||
adjusted_memory = max(0, base_memory - virtual_vram_bytes)
|
||||
total_memory_required[device] = total_memory_required.get(device, 0) + adjusted_memory
|
||||
logger.mgpu_mm_log(f"DisTorch is_distorch=True, model adjusted {(base_memory - virtual_vram_bytes)/(1024**3):.2f}GB for device {device}")
|
||||
logger.mgpu_mm_log(f"DisTorch model adjusted {(base_memory - virtual_vram_bytes)/(1024**3):.2f}GB for device {device}")
|
||||
else:
|
||||
# is_distorch=False: use full model size
|
||||
# Standard model: use full model size
|
||||
total_memory_required[device] = total_memory_required.get(device, 0) + base_memory
|
||||
logger.mgpu_mm_log(f"[LOAD_MODELS_GPU] Standard model {(base_memory)/(1024**3):.2f}GB for device {device}")
|
||||
|
||||
@@ -209,23 +189,24 @@ def register_patched_safetensor_modelpatcher():
|
||||
original_partially_load = comfy.model_patcher.ModelPatcher.partially_load
|
||||
|
||||
def new_partially_load(self, device_to, extra_memory=0, full_load=False, force_patch_weights=False, **kwargs):
|
||||
"""Override to use our static device assignments"""
|
||||
global safetensor_allocation_store
|
||||
|
||||
debug_hash = create_safetensor_model_hash(self, "partial_load")
|
||||
multigpu_memory_log(f"safetensor:{debug_hash[:8]}", "pre-load")
|
||||
allocations = safetensor_allocation_store.get(debug_hash)
|
||||
|
||||
# Set default precision flag before checking
|
||||
if not hasattr(self.model, '_distorch_high_precision_loras'):
|
||||
self.model._distorch_high_precision_loras = True
|
||||
|
||||
if not allocations:
|
||||
"""Override to use direct model annotation for allocation"""
|
||||
|
||||
mp_id = id(self)
|
||||
mp_patches_uuid = self.patches_uuid
|
||||
inner_model = self.model
|
||||
inner_model_id = id(inner_model)
|
||||
|
||||
if not hasattr(inner_model, "_distorch_v2_meta"):
|
||||
logger.debug(f"[DISTORCH_SKIP] ModelPatcher=0x{mp_id:x} inner_model=0x{inner_model_id:x} type={type(inner_model).__name__} - no metadata, using standard loading")
|
||||
result = original_partially_load(self, device_to, extra_memory, force_patch_weights)
|
||||
multigpu_memory_log(f"safetensor:{debug_hash[:8]}", "post-load")
|
||||
if hasattr(self, '_distorch_block_assignments'):
|
||||
del self._distorch_block_assignments
|
||||
return result
|
||||
|
||||
allocations = inner_model._distorch_v2_meta['full_allocation']
|
||||
|
||||
if not hasattr(self.model, '_distorch_high_precision_loras'):
|
||||
self.model._distorch_high_precision_loras = True
|
||||
|
||||
if not hasattr(self.model, 'current_weight_patches_uuid'):
|
||||
self.model.current_weight_patches_uuid = None
|
||||
@@ -308,7 +289,6 @@ def register_patched_safetensor_modelpatcher():
|
||||
|
||||
logger.info("[MultiGPU DisTorch V2] DisTorch loading completed.")
|
||||
logger.info(f"[MultiGPU DisTorch V2] Total memory: {mem_counter / (1024 * 1024):.2f}MB")
|
||||
multigpu_memory_log(f"safetensor:{debug_hash[:8]}", "post-load")
|
||||
|
||||
return 0
|
||||
|
||||
|
||||
@@ -22,30 +22,9 @@ logger = logging.getLogger("MultiGPU")
|
||||
# Model Analysis and Store Management (DisTorch V1 & V2)
|
||||
# ==========================================================================================
|
||||
|
||||
# DisTorch V2 SafeTensor stores
|
||||
safetensor_allocation_store = {}
|
||||
safetensor_settings_store = {}
|
||||
|
||||
# DisTorch V1 GGUF stores (backwards compatibility)
|
||||
model_allocation_store = {}
|
||||
|
||||
def create_safetensor_model_hash(model, caller):
|
||||
"""Create a unique hash for a safetensor model to track allocations"""
|
||||
if hasattr(model, 'model'):
|
||||
actual_model = model.model
|
||||
model_type = type(actual_model).__name__
|
||||
model_size = model.model_size() if hasattr(model, 'model_size') else sum(p.numel() * p.element_size() for p in actual_model.parameters())
|
||||
first_layers = str(list(model.model_state_dict().keys() if hasattr(model, 'model_state_dict') else actual_model.state_dict().keys())[:3])
|
||||
else:
|
||||
model_type = type(model).__name__
|
||||
model_size = sum(p.numel() * p.element_size() for p in model.parameters())
|
||||
first_layers = str(list(model.state_dict().keys())[:3])
|
||||
|
||||
identifier = f"{model_type}_{model_size}_{first_layers}"
|
||||
final_hash = hashlib.sha256(identifier.encode()).hexdigest()
|
||||
logger.debug(f"[MultiGPU DisTorch V2] Created hash for {caller}: {final_hash[:8]}...")
|
||||
return final_hash
|
||||
|
||||
def create_model_hash(model, caller):
|
||||
"""Create a unique hash for a GGUF model to track allocations (DisTorch V1)"""
|
||||
model_type = type(model.model).__name__
|
||||
|
||||
+1
-1
@@ -1,7 +1,7 @@
|
||||
[project]
|
||||
name = "comfyui-multigpu"
|
||||
description = "Provides a suite of custom nodes to manage multiple GPUs for ComfyUI, including advanced model offloading for both GGUF and Safetensor formats with DisTorch, and bespoke MultiGPU support for WanVideoWrapper and other custom nodes."
|
||||
version = "2.5.5"
|
||||
version = "2.5.6"
|
||||
license = {file = "LICENSE"}
|
||||
|
||||
[project.urls]
|
||||
|
||||
+35
-69
@@ -17,12 +17,7 @@ logger = logging.getLogger("MultiGPU")
|
||||
|
||||
def _create_distorch_safetensor_v2_override(cls, device_param_name, device_setter_func, apply_device_kwarg_workaround, eject_models_default=True):
|
||||
"""Internal factory function creating DisTorch2 override class with parameterized device selection behavior."""
|
||||
from .distorch_2 import (
|
||||
register_patched_safetensor_modelpatcher,
|
||||
safetensor_allocation_store,
|
||||
safetensor_settings_store,
|
||||
create_safetensor_model_hash
|
||||
)
|
||||
from .distorch_2 import register_patched_safetensor_modelpatcher
|
||||
from .model_management_mgpu import force_full_system_cleanup
|
||||
|
||||
class NodeOverrideDisTorchSafetensorV2(cls):
|
||||
@@ -118,51 +113,10 @@ def _create_distorch_safetensor_v2_override(cls, device_param_name, device_sette
|
||||
model_to_check = out[0].patcher
|
||||
|
||||
if model_to_check:
|
||||
model_hash = create_safetensor_model_hash(model_to_check, "override_store")
|
||||
settings_str = f"{device_value}{virtual_vram_gb}{donor_device}{expert_mode_allocations}"
|
||||
settings_hash = hashlib.sha256(settings_str.encode()).hexdigest()
|
||||
|
||||
safetensor_allocation_store[model_hash] = full_allocation
|
||||
safetensor_settings_store[model_hash] = settings_hash
|
||||
logger.debug(f"[MultiGPU DisTorch V2] Stored allocation for model {model_hash[:8]}: {full_allocation}")
|
||||
inner_model = model_to_check.model
|
||||
inner_model._distorch_v2_meta = {"full_allocation": full_allocation}
|
||||
|
||||
logger.info(f"[MultiGPU DisTorch V2] Full allocation string: {full_allocation}")
|
||||
logger.mgpu_mm_log(f"[MODEL_SETUP] Setting DisTorch model properties: virtual_vram_gb={virtual_vram_gb}")
|
||||
|
||||
if hasattr(out[0], 'model'):
|
||||
mp = out[0]
|
||||
mp_id = id(mp)
|
||||
inner_model = getattr(mp, 'model', None)
|
||||
inner_model_id = id(inner_model) if inner_model else None
|
||||
inner_model_name = type(inner_model).__name__ if inner_model else "None"
|
||||
inner_id_str = f"0x{inner_model_id:x}" if inner_model_id is not None else "None"
|
||||
|
||||
logger.mgpu_mm_log(f"[OBJECT_CHAIN_SET] ModelPatcher: mp_id=0x{mp_id:x}, inner_model_id={inner_id_str}, inner_model_type={inner_model_name}")
|
||||
|
||||
# SET VIRTUAL VRAM PROPERTY FOR MEMORY CALCULATION
|
||||
if inner_model:
|
||||
inner_model._mgpu_virtual_vram_gb = virtual_vram_gb
|
||||
logger.mgpu_mm_log(f"[VIRTUAL_VRAM_SET] Set _mgpu_virtual_vram_gb={virtual_vram_gb}GB on inner model (id=0x{inner_model_id:x}) for memory assessment")
|
||||
|
||||
# SET EJECT MODELS PROPERTY IF ENABLED
|
||||
if eject_models and inner_model:
|
||||
inner_model._mgpu_eject_models = True
|
||||
logger.mgpu_mm_log(f"[EJECT_FLAG_SET] Set _mgpu_eject_models=True on inner model (id=0x{inner_model_id:x}) - will trigger ejection during load_models_gpu")
|
||||
|
||||
elif hasattr(out[0], 'patcher') and hasattr(out[0].patcher, 'model'):
|
||||
mp = out[0].patcher
|
||||
mp_id = id(mp)
|
||||
inner_model = getattr(mp, 'model', None)
|
||||
inner_model_id = id(inner_model) if inner_model else None
|
||||
inner_model_name = type(inner_model).__name__ if inner_model else "None"
|
||||
inner_id_str = f"0x{inner_model_id:x}" if inner_model_id is not None else "None"
|
||||
|
||||
logger.mgpu_mm_log(f"[OBJECT_CHAIN_SET] ModelPatcher via patcher: mp_id=0x{mp_id:x}, inner_model_id={inner_id_str}, inner_model_type={inner_model_name}")
|
||||
|
||||
# SET VIRTUAL VRAM PROPERTY FOR MEMORY CALCULATION
|
||||
if inner_model:
|
||||
inner_model._mgpu_virtual_vram_gb = virtual_vram_gb
|
||||
logger.mgpu_mm_log(f"[VIRTUAL_VRAM_SET] Set _mgpu_virtual_vram_gb={virtual_vram_gb}GB on inner model (id=0x{inner_model_id:x}) for memory assessment")
|
||||
|
||||
return out
|
||||
|
||||
@@ -211,7 +165,7 @@ def override_class_with_distorch_safetensor_v2_clip_no_device(cls):
|
||||
def override_class_with_distorch_gguf(cls):
|
||||
"""DisTorch V1 Legacy wrapper - maintains V1 UI but calls V2 backend"""
|
||||
from . import set_current_device
|
||||
from .distorch_2 import register_patched_safetensor_modelpatcher, safetensor_allocation_store, create_safetensor_model_hash
|
||||
from .distorch_2 import register_patched_safetensor_modelpatcher
|
||||
|
||||
class NodeOverrideDisTorchGGUFLegacy(cls):
|
||||
@classmethod
|
||||
@@ -257,12 +211,15 @@ def override_class_with_distorch_gguf(cls):
|
||||
fn = getattr(super(), cls.FUNCTION)
|
||||
out = fn(*args, **clean_kwargs)
|
||||
|
||||
model_to_check = None
|
||||
if hasattr(out[0], 'model'):
|
||||
model_hash = create_safetensor_model_hash(out[0], "v1_compat")
|
||||
safetensor_allocation_store[model_hash] = full_allocation
|
||||
model_to_check = out[0]
|
||||
elif hasattr(out[0], 'patcher') and hasattr(out[0].patcher, 'model'):
|
||||
model_hash = create_safetensor_model_hash(out[0].patcher, "v1_compat")
|
||||
safetensor_allocation_store[model_hash] = full_allocation
|
||||
model_to_check = out[0].patcher
|
||||
|
||||
if model_to_check:
|
||||
inner_model = model_to_check.model
|
||||
inner_model._distorch_v2_meta = {"full_allocation": full_allocation}
|
||||
|
||||
return out
|
||||
|
||||
@@ -272,7 +229,7 @@ def override_class_with_distorch_gguf(cls):
|
||||
def override_class_with_distorch_gguf_v2(cls):
|
||||
"""DisTorch V2 wrapper for GGUF models"""
|
||||
from . import set_current_device
|
||||
from .distorch_2 import register_patched_safetensor_modelpatcher, safetensor_allocation_store, create_safetensor_model_hash
|
||||
from .distorch_2 import register_patched_safetensor_modelpatcher
|
||||
|
||||
class NodeOverrideDisTorchGGUFv2(cls):
|
||||
@classmethod
|
||||
@@ -316,12 +273,15 @@ def override_class_with_distorch_gguf_v2(cls):
|
||||
fn = getattr(super(), cls.FUNCTION)
|
||||
out = fn(*args, **clean_kwargs)
|
||||
|
||||
model_to_check = None
|
||||
if hasattr(out[0], 'model'):
|
||||
model_hash = create_safetensor_model_hash(out[0], "v2_gguf")
|
||||
safetensor_allocation_store[model_hash] = full_allocation
|
||||
model_to_check = out[0]
|
||||
elif hasattr(out[0], 'patcher') and hasattr(out[0].patcher, 'model'):
|
||||
model_hash = create_safetensor_model_hash(out[0].patcher, "v2_gguf")
|
||||
safetensor_allocation_store[model_hash] = full_allocation
|
||||
model_to_check = out[0].patcher
|
||||
|
||||
if model_to_check:
|
||||
inner_model = model_to_check.model
|
||||
inner_model._distorch_v2_meta = {"full_allocation": full_allocation}
|
||||
|
||||
return out
|
||||
|
||||
@@ -331,7 +291,7 @@ def override_class_with_distorch_gguf_v2(cls):
|
||||
def override_class_with_distorch_clip(cls):
|
||||
"""DisTorch V1 wrapper for CLIP models - calls V2 backend"""
|
||||
from . import set_current_text_encoder_device
|
||||
from .distorch_2 import register_patched_safetensor_modelpatcher, safetensor_allocation_store, create_safetensor_model_hash
|
||||
from .distorch_2 import register_patched_safetensor_modelpatcher
|
||||
|
||||
class NodeOverrideDisTorchClip(cls):
|
||||
@classmethod
|
||||
@@ -377,12 +337,15 @@ def override_class_with_distorch_clip(cls):
|
||||
fn = getattr(super(), cls.FUNCTION)
|
||||
out = fn(*args, **clean_kwargs)
|
||||
|
||||
model_to_check = None
|
||||
if hasattr(out[0], 'model'):
|
||||
model_hash = create_safetensor_model_hash(out[0], "v1_clip")
|
||||
safetensor_allocation_store[model_hash] = full_allocation
|
||||
model_to_check = out[0]
|
||||
elif hasattr(out[0], 'patcher') and hasattr(out[0].patcher, 'model'):
|
||||
model_hash = create_safetensor_model_hash(out[0].patcher, "v1_clip")
|
||||
safetensor_allocation_store[model_hash] = full_allocation
|
||||
model_to_check = out[0].patcher
|
||||
|
||||
if model_to_check:
|
||||
inner_model = model_to_check.model
|
||||
inner_model._distorch_v2_meta = {"full_allocation": full_allocation}
|
||||
|
||||
return out
|
||||
|
||||
@@ -392,7 +355,7 @@ def override_class_with_distorch_clip(cls):
|
||||
def override_class_with_distorch_clip_no_device(cls):
|
||||
"""DisTorch V1 wrapper for Triple/Quad CLIP models - calls V2 backend"""
|
||||
from . import set_current_text_encoder_device
|
||||
from .distorch_2 import register_patched_safetensor_modelpatcher, safetensor_allocation_store, create_safetensor_model_hash
|
||||
from .distorch_2 import register_patched_safetensor_modelpatcher
|
||||
|
||||
class NodeOverrideDisTorchClipNoDevice(cls):
|
||||
@classmethod
|
||||
@@ -438,12 +401,15 @@ def override_class_with_distorch_clip_no_device(cls):
|
||||
fn = getattr(super(), cls.FUNCTION)
|
||||
out = fn(*args, **clean_kwargs)
|
||||
|
||||
model_to_check = None
|
||||
if hasattr(out[0], 'model'):
|
||||
model_hash = create_safetensor_model_hash(out[0], "v1_clip_nodev")
|
||||
safetensor_allocation_store[model_hash] = full_allocation
|
||||
model_to_check = out[0]
|
||||
elif hasattr(out[0], 'patcher') and hasattr(out[0].patcher, 'model'):
|
||||
model_hash = create_safetensor_model_hash(out[0].patcher, "v1_clip_nodev")
|
||||
safetensor_allocation_store[model_hash] = full_allocation
|
||||
model_to_check = out[0].patcher
|
||||
|
||||
if model_to_check:
|
||||
inner_model = model_to_check.model
|
||||
inner_model._distorch_v2_meta = {"full_allocation": full_allocation}
|
||||
|
||||
return out
|
||||
|
||||
|
||||
Reference in New Issue
Block a user