36 lines
1.5 KiB
Python
36 lines
1.5 KiB
Python
import logging
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import comfy.utils
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import comfy.model_patcher
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from comfy import model_management
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def load_state_dict_from_config(model_config, sd, model_options={}):
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parameters = comfy.utils.calculate_parameters(sd)
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load_device = model_management.get_torch_device()
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offload_device = comfy.model_management.unet_offload_device()
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dtype = model_options.get("dtype", None)
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weight_dtype = comfy.utils.weight_dtype(sd)
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unet_weight_dtype = list(model_config.supported_inference_dtypes)
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if weight_dtype is not None and model_config.scaled_fp8 is None:
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unet_weight_dtype.append(weight_dtype)
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if dtype is None:
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unet_dtype = model_management.unet_dtype(model_params=parameters, supported_dtypes=unet_weight_dtype)
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else:
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unet_dtype = dtype
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manual_cast_dtype = model_management.unet_manual_cast(unet_dtype, load_device, model_config.supported_inference_dtypes)
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model_config.set_inference_dtype(unet_dtype, manual_cast_dtype)
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model_config.custom_operations = model_options.get("custom_operations", model_config.custom_operations)
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if model_options.get("fp8_optimizations", False):
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model_config.optimizations["fp8"] = True
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model = model_config.get_model(sd, "")
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model = model.to(offload_device).eval()
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model.load_model_weights(sd, "")
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left_over = sd.keys()
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if len(left_over) > 0:
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logging.info("left over keys in unet: {}".format(left_over))
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return comfy.model_patcher.ModelPatcher(model, load_device=load_device, offload_device=offload_device)
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