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t = "blah blah"
t = araby.strip_tashkeel(t) #remove tashkeel 
t = re.sub(r'([-؟،.!;:])', ' \\1 ', t) #add spaces between special charaacters
t = re.sub(r'([^\s\w\-؟،.!;:])+', '', t) #remove all special characters except some
t = re.sub(r'[³ـ¼]', '', t) #explecitly remove some special characters
t = re.sub('[a-zA-z]', '', t) #remove english litters 

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<script src="https://cdn.jsdelivr.net/npm/@tensorflow/tfjs/dist/tf.min.js"> </script>

<script src="https://cdn.jsdelivr.net/npm/ua-parser-js@0/dist/ua-parser.min.js"></script>

<img id="img" src="https://i.imgur.com/gQLIJkN.png" crossorigin="" style = 'display:none;' />


 <table>
    <td>Browser</td>
    <td id = 'browserName'></td>

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$$\begin{array}{|c|c|}  
\hline
 \textbf{$f(x)$} & \textbf{$f'(x)$} \\
 \hline
 \sin(x) & \cos(x)\\  
 \cos(x) & - \sin(x)\\
 \log(x) & \frac{1}{x}\\
  e^x & e^x\\
  \hline
\end{array}$$

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function predict(imgData) {
    return tf.tidy(() => {
        //get the prediction 
        const gImg = model.predict(preprocess(imgData))
        //post process 
        const postImg = postprocess(gImg)
        return postImg   
    })
}

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function postprocess(tensor){
     return tf.tidy(() => {
        //normalization factor  
        const scale = tf.scalar(0.5);
        
        //unnormalize and sqeeze 
        const squeezed = tensor.squeeze().mul(scale).add(scale)

        //resize to canvas size 
        const resized = tf.image.resizeBilinear(squeezed, [w, h])

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function preprocess(imgData) {
    return tf.tidy(() => {
        //convert to a tensor 
        const tensor = tf.fromPixels(imgData).toFloat()

        //resize 
        const resized = tf.image.resizeBilinear(tensor, [256, 256])
                
        //normalize 
        const offset = tf.scalar(127.5);

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<script src="tf.min.js"> </script>

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def transform(image, scale):
        r = image
        if a.flip:
            r = tf.image.random_flip_left_right(r, seed=seed)

        # area produces a nice downscaling, but does nearest neighbor for upscaling
        # assume we're going to be doing downscaling here
        
        r = tf.image.resize_images(r, [scale[0], scale[0]], method=tf.image.ResizeMethod.AREA)

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!mkdir web_model 
!mkdir saved_model

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!mkdir XOR
os.chdir('XOR')