xinyun/ComfyUI-CogVideoXWrapper
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Support enable_model_cpu_offload

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caojiachen1 2024-09-07 13:16:51 +08:00
parent 49abc7b0eb
commit 0e9010f9f6
1 changed files with 5 additions and 2 deletions
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7
nodes.py
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@ -34,6 +34,7 @@ class DownloadAndLoadCogVideoModel:
"fp8_transformer": (['disabled', 'enabled', 'fastmode'], {"default": 'disabled', "tooltip": "enabled casts the transformer to torch.float8_e4m3fn, fastmode is only for latest nvidia GPUs"}),
"compile": (["disabled","onediff","torch"], {"tooltip": "compile the model for faster inference, these are advanced options only available on Linux, see readme for more info"}),
"enable_sequential_cpu_offload": ("BOOLEAN", {"default": False, "tooltip": "significantly reducing memory usage and slows down the inference"}),
"enable_model_cpu_offload": ("BOOLEAN", {"default": False, "tooltip": "offload the model to CPU, this is useful for large models and small batch sizes"}),
}
}
@ -42,7 +43,7 @@ class DownloadAndLoadCogVideoModel:
FUNCTION = "loadmodel"
CATEGORY = "CogVideoWrapper"
def loadmodel(self, model, precision, fp8_transformer="disabled", compile="disabled", enable_sequential_cpu_offload=False):
def loadmodel(self, model, precision, fp8_transformer="disabled", compile="disabled", enable_sequential_cpu_offload=False, enable_model_cpu_offload=False):
device = mm.get_torch_device()
offload_device = mm.unet_offload_device()
mm.soft_empty_cache()
@ -85,6 +86,8 @@ class DownloadAndLoadCogVideoModel:
pipe = CogVideoXPipeline(vae, transformer, scheduler)
if enable_sequential_cpu_offload:
pipe.enable_sequential_cpu_offload()
if enable_model_cpu_offload:
pipe.enable_model_cpu_offload()
if compile == "torch":
torch._dynamo.config.suppress_errors = True
@ -107,7 +110,7 @@ class DownloadAndLoadCogVideoModel:
"dtype": dtype,
"base_path": base_path,
"onediff": True if compile == "onediff" else False,
"cpu_offloading": enable_sequential_cpu_offload
"cpu_offloading": enable_sequential_cpu_offload or enable_model_cpu_offload,
}
return (pipeline,)