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Stable Cascade Stage C.
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@@ -318,9 +318,10 @@ def load_controlnet(ckpt_path, model=None):
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return ControlLora(controlnet_data)
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controlnet_config = None
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supported_inference_dtypes = None
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if "controlnet_cond_embedding.conv_in.weight" in controlnet_data: #diffusers format
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unet_dtype = comfy.model_management.unet_dtype()
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controlnet_config = comfy.model_detection.unet_config_from_diffusers_unet(controlnet_data, unet_dtype)
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controlnet_config = comfy.model_detection.unet_config_from_diffusers_unet(controlnet_data)
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diffusers_keys = comfy.utils.unet_to_diffusers(controlnet_config)
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diffusers_keys["controlnet_mid_block.weight"] = "middle_block_out.0.weight"
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diffusers_keys["controlnet_mid_block.bias"] = "middle_block_out.0.bias"
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@@ -380,12 +381,20 @@ def load_controlnet(ckpt_path, model=None):
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return net
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if controlnet_config is None:
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unet_dtype = comfy.model_management.unet_dtype()
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controlnet_config = comfy.model_detection.model_config_from_unet(controlnet_data, prefix, unet_dtype, True).unet_config
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model_config = comfy.model_detection.model_config_from_unet(controlnet_data, prefix, True)
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supported_inference_dtypes = model_config.supported_inference_dtypes
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controlnet_config = model_config.unet_config
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load_device = comfy.model_management.get_torch_device()
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if supported_inference_dtypes is None:
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unet_dtype = comfy.model_management.unet_dtype()
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else:
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unet_dtype = comfy.model_management.unet_dtype(supported_dtypes=supported_inference_dtypes)
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manual_cast_dtype = comfy.model_management.unet_manual_cast(unet_dtype, load_device)
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if manual_cast_dtype is not None:
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controlnet_config["operations"] = comfy.ops.manual_cast
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controlnet_config["dtype"] = unet_dtype
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controlnet_config.pop("out_channels")
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controlnet_config["hint_channels"] = controlnet_data["{}input_hint_block.0.weight".format(prefix)].shape[1]
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control_model = comfy.cldm.cldm.ControlNet(**controlnet_config)
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