deepfakes/faceswap · error · FaceswapError

There are multiple plugin types ('{p_types}') stored in the

Error message

There are multiple plugin types ('{p_types}') stored in the model folder '{self.io.model_dir}'. This is not supported.\nPlease split the model files into their own folders before proceeding

What it means

FaceswapError raised by ModelBase._check_multiple_models() when the model folder contains state/model files from two or more different plugin types (e.g. both original and dlight files). Faceswap cannot decide which model to load and does not support mixing architectures in one folder. The message lists the offending plugin types found.

Source

Thrown at plugins/train/model/_base/model.py:188

        FaceswapError
            If multiple model files, or models for a different plugin from that requested exists
            within the model folder
        """
        multiple_models = self._io.multiple_models_in_folder
        if multiple_models is None:
            logger.debug("Contents of model folder are valid")
            return

        if len(multiple_models) == 1:
            msg = (f"You have requested to train with the '{self.name}' plugin, but a model file "
                   f"for the '{multiple_models[0]}' plugin already exists in the folder "
                   f"'{self.io.model_dir}'.\nPlease select a different model folder.")
        else:
            p_types = "', '".join(multiple_models)
            msg = (f"There are multiple plugin types ('{p_types}') stored in the model folder '"
                   f"{self.io.model_dir}'. This is not supported.\nPlease split the model files "
                   "into their own folders before proceeding")
        raise FaceswapError(msg)

    def build(self) -> None:
        """Build the model and assign to :attr:`model`.

        Within the defined strategy scope, either builds the model from scratch or loads an
        existing model if one exists.

        If running inference, then the model is built only for the required side to perform the
        swap function, otherwise  the model is then compiled with the optimizer and chosen
        loss function(s).

        Finally, a model summary is outputted to the logger at verbose level.
        """
        is_summary = hasattr(self._args, "summary") and self._args.summary
        if self._io.model_exists:
            model = self.io.load()
            if self._is_predict:
                inference = Inference(model, self._args.swap_model)

View on GitHub (pinned to f530cb7508)

Solutions

1. Sort the files in the folder by plugin name and move each plugin's files (state file, weights, h5/keras files) into its own subfolder
2. Point -m at the cleaned folder for the plugin you want and restart training
3. If unsure which files belong together, check the plugin name embedded in each state filename before splitting

Example fix

# before: /models/mixed contains dlight_state.h5 + original_state.h5
# error: multiple plugin types

# after (shell)
mkdir /models/dlight /models/original
mv /models/mixed/dlight* /models/dlight/
mv /models/mixed/original* /models/original/
python faceswap.py train -t dlight -m /models/dlight

import os, collections
plugins = collections.Counter(
    f.rsplit("_", 1)[0] for f in os.listdir(model_dir) if f.endswith("_state.h5")
)
if len(plugins) > 1:
    raise SystemExit(f"Mixed plugin files in model dir: {dict(plugins)} - split them first")

When it happens

Trigger: Launching training with -m pointing at a folder where files like original_state.h5 and phaze_a_state.h5 (or equivalent per-plugin files) coexist. Happens after manually copying model files from several trainings into one directory.

Common situations: User consolidates backups into one folder, restores from an archive that merged runs, or switches trainers twice while reusing the same directory.

Related errors

• You have requested to train with the '{self.name}' plugin, b
• You have selected the mask type '{mask_type}' but at least o
• '{method}' is not a valid clipping method. Select from {list
• '{name}' is not a valid optimizer. Select from {list(_OPTIMI
• You do not have enough GPU memory available to train the sel

AI-assisted analysis of deepfakes/faceswap@f530cb7508 (2026-08-15). Data as JSON: /api/errors/ce3c253bcf47095d. Report an issue: GitHub.