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Uncaught (in promise) Error: Tensorflow Op is not supported: _FusedConv2D

<!-- Load TensorFlow.js. This is required to use MobileNet. -->
<script src="https://cdn.jsdelivr.net/npm/@tensorflow/tfjs@4.17.0"> </script>
<!-- Load the MobileNet model. -->
<script src="https://cdn.jsdelivr.net/npm/@tensorflow-models/mobilenet@2.1.1"> </script>

<!-- Replace this with your image. Make sure CORS settings allow reading the image! -->
<img id="img" src="cat.jpg"></img>

<!-- Place your code in the script tag below. You can also use an external .js file -->
<script>
  // Notice there is no 'import' statement. 'mobilenet' and 'tf' is
  // available on the index-page because of the script tag above.

  const img = document.getElementById('img');

  // Load the model.
  mobilenet.load().then(model => {
    // Classify the image.
    model.classify(img).then(predictions => {
      console.log('Predictions: ');
      console.log(predictions);
    });
  });
</script>

name: testing

on:
  push:
    branches: [ "main" ]
  pull_request:
    branches: [ "main" ]
defaults:
  run:
    working-directory: ./turi-map-app
jobs:
  laravel-test:
    runs-on: ubuntu-latest
    services:
      mysql:
        image: mysql:5.7
        ports:
          - 3306:3306
        env:
          MYSQL_ROOT_PASSWORD: turi
          MYSQL_DATABASE: turi
          MYSQL_USER: turi
          MYSQL_PASSWORD: turi
          MYSQL_ALLOW_EMPTY_PASSWORD: 'yes'
        options: --health-cmd "mysqladmin ping -h 127.0.0.1" --health-interval 20s --health-timeout 10s --health-retries 10
    strategy:
      matrix:
        node-version: [21.x]
    steps:
    - uses: shivammathur/setup-php@15c43e89cdef867065b0213be354c2841860869e
      with:
        php-version: '8.2'
        extensions: mbstring, dom, fileinfo, pdo_mysql, PDO, zip
    - uses: actions/checkout@v4
    - name: Copy .env
      run: php -r "file_exists('.env') || copy('.env.testing', '.env');"
    - name: Install Dependencies
      run: composer install -n --prefer-dist
    - name: Generate key
      run: php artisan key:generate
    - name: storage link
      run: php artisan storage:link
    - name: Directory Permissions
      run: chmod -R 777 storage bootstrap/cache
    - name: Use Node.js ${{ matrix.node-version }}
      uses: actions/setup-node@v4
      with:
        node-version: ${{ matrix.node-version }}
    - name: npm install
      run: npm i
    - name: Build Assets
      run: npm run build
    - name: migrate
      run: php artisan migrate
    - name: Execute tests (Unit and Feature tests) via PHPUnit
      run: php artisan test

#前処理 mecab-python3バージョンは1.0.8です
sudo apt-get install mecab libmecab-dev mecab-ipadic-utf8
sudo pip install mecab-python3
pip install unidic-lite

<?php
class sharpPost
{
    /**
     * mecab.pyを使って文章を解析（名詞と形容詞を取り出す）
     * @param $posstData
     * @return array|null
     */
    public function analysis($postData)
    {
        if(!$postData)return null;
        $word = null;
        exec('python py/mecab.py "'.strip_tags(htmlentities($postData)).'"',$output);// 2>&1
        if(is_array($output)){
            foreach($output as $val){
                $analysisWord = explode("\t",$val);
                if(isset($analysisWord[1]) && preg_match('/(名詞|形容詞)/',$analysisWord[1])){
                    $word[] = $analysisWord[0];
                    $word = array_unique($word);
                }
            }
        }
        return $word;
    }
    
    /**
     * 文字列を置き換える処理
     * @param $postData
     * @param $word|null
     * @return string
     */
    public function replacePostData($postData='',$word=null)
    {
        if(is_array($word)){
            foreach($word as $val){
                $postData = preg_replace("/({$val})/u"," #{$val} ",$postData);
            }
        }
        return $postData;
    }
}
$textData = '単なる自分が使いたい機能です、無かったので作ってみただけです。';
$sharpPost = new sharpPost();
$word = $sharpPost->analysis($textData);
print(($sharpPost->replacePostData($textData,$word)).PHP_EOL);

import MeCab
import sys
args = sys.argv
if(args[1]):
    tagger = MeCab.Tagger()
    print(tagger.parse(args[1]))