dev(narugo): save the predict fmt code

import json

import os

import re

from threading import Lock

from typing import Tuple, Optional, List, Dict, Callable

from ..data import rgb_encode, ImageTyping, load_image

from ..preprocess import create_pillow_transforms

from ..utils import open_onnx_model, ts_lru_cache

from ..utils import open_onnx_model, ts_lru_cache, vnames, vreplace

try:

    import gradio as gr

        max_id = np.argmax(output)

        return self._open_label(model_name)[label_group][max_id], output[max_id].item()

    def predict_fmt(self, image: ImageTyping, model_name: str,

                      label_group: str = 'default', topk: Optional[int] = 20):

    def predict_fmt(self, image: ImageTyping, model_name: str, fmt='scores-top5'):

        d_data = {name: value[0] for name, value in self._raw_predict(image, model_name).items()}

        scores = d_data['output']

        d_labels = self._open_label(model_name)

        vname_to_spair = {}

        d_scores = {}

        for vname in vnames(fmt, str_only=True):

            matching = re.fullmatch(r'^scores(-top(?P<topk>\d+))?(-(?P<label_group>[a-zA-Z\d_]+))?$', vname)

            if matching:

                if matching.group('topk'):

                    topk = int(matching.group('topk'))

                else:

                    topk = None

                if matching.group('label_group'):

                    group_label = matching.group('label_group')

                else:

                    group_label = 'default'

                vname_to_spair[vname] = (topk, group_label)

                if (topk, group_label) not in d_scores:

                    d_scores[(topk, group_label)] = _labels_scores_to_topk(

                        labels=d_labels[group_label],

                        scores=scores,

                        topk=topk,

                    )

        return vreplace(fmt, mapping={

            **d_data,

            **{vname: d_scores[vpair] for vname, vpair in vname_to_spair.items()},

        })

    def clear(self):

        """