Load Upscale Model

Documentation

Class name: UpscaleModelLoader
Category: loaders
Output node: False

The UpscaleModelLoader node is designed for loading upscale models from a specified directory. It facilitates the retrieval and preparation of upscale models for image upscaling tasks, ensuring that the models are correctly loaded and configured for evaluation.

Input types

Required

model_name
- Specifies the name of the upscale model to be loaded. This parameter is crucial for identifying and retrieving the correct model file from the upscale models directory.
- Comfy dtype: COMBO[STRING]
- Python dtype: str

Output types

upscale_model
- Comfy dtype: UPSCALE_MODEL
- Returns the loaded and prepared upscale model, ready for use in image upscaling tasks.
- Python dtype: torch.nn.Module

Usage tips

Infra type: CPU
Common nodes:
- ImageUpscaleWithModel
- UltimateSDUpscale
- Reroute
- LatentPixelScale
- [Anything Everywhere](../../cg-use-everywhere/Nodes/Anything Everywhere.md)
- PixelKSampleUpscalerProvider

Source code

class UpscaleModelLoader:
    @classmethod
    def INPUT_TYPES(s):
        return {"required": { "model_name": (folder_paths.get_filename_list("upscale_models"), ),
                             }}
    RETURN_TYPES = ("UPSCALE_MODEL",)
    FUNCTION = "load_model"

    CATEGORY = "loaders"

    def load_model(self, model_name):
        model_path = folder_paths.get_full_path("upscale_models", model_name)
        sd = comfy.utils.load_torch_file(model_path, safe_load=True)
        if "module.layers.0.residual_group.blocks.0.norm1.weight" in sd:
            sd = comfy.utils.state_dict_prefix_replace(sd, {"module.":""})
        out = model_loading.load_state_dict(sd).eval()
        return (out, )

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