def METHOD_NAME(self):
    """
    check files in self.pathList to see if they are ml_ai models.
    if they are folders, try to load supported forms (SavedModel).
    if they are files, try to load supported forms (H5, JSON, PT, PKL).
    """
    for p in self.pathList:
        if os.path.exists(p) and "user_ml_ai_models" in str(p):
            sys.path.append(p)
            pgfiles = os.listdir(p)
            for fname in pgfiles:
                skip = False
                if os.path.isfile(
                    os.path.join(p, fname)
                ):  # load a single model file
                    mname = fname.rsplit(".", 1)  # split off extension
                elif os.path.isdir(
                    os.path.join(p, fname)
                ):  # load a SavedModel folder
                    mname = [fname, ""]  # convert into length-2 vector
                # try loading if no extension (folder), or extension is .h5
                if mname[0] == "__pycache__":  # should exist but not a model file
                    skip = True
                if len(mname) == 2 and (
                    os.path.isdir(os.path.join(p, mname[0]))
                    or mname[1] in ["h5", "json", "pt", "pkl"]
                ):
                    if (
                        mname[1] == "py"
                    ):  # skip any Python files containing model classes
                        skip = True
                    if (
                        "_weights" in mname[0] and mname[1] == "h5"
                    ):  # this is a json weights file, skip it
                        skip = True
                    # if the search makes it here, try loading the model
                    if skip == False:
                        try:
                            if mname[0] in self.ml_ai_models:
                                _log.info(
                                    "Reloading ML_AI Model: {}".format(
                                        os.path.join(p, fname)
                                    )
                                )
                                self.ml_ai_models[mname[0]] = mname[0]
                            else:
                                logging.getLogger("foqus." + __name__).info(
                                    "Loading ML_AI Model: " + os.path.join(p, fname)
                                )
                                self.ml_ai_models[mname[0]] = mname[0]
                        except:
                            _log.exception(
                                "Error Loading ML_AI Model: {}".format(
                                    os.path.join(p, fname)
                                )
                            )
                else:  # print warning if not Python or other expected file
                    if mname != "PSUADEPATH" and (
                        len(mname) == 2 and mname[1] != "py"
                    ):
                        _log.exception(
                            "Error Loading File or Folder: {}".format(
                                os.path.join(p, fname)
                            )
                        )