How to get random value out of an array?

if I understood your correctly I think this code is what you're looking for. In this case since you're using AJAX we'll be saving used questions like array in session.

<?php
    if(!isset($_SESSION)) {
        session_start();

        $_SESSION['used'] = ((!isset($_SESSION['used'])) ? ([]) : ($_SESSION['used']));
    }

    //--------------------------------------------------------------------------
    // 1) Connect to mysql database
    //--------------------------------------------------------------------------
    include 'DB.php';

    $con = mysql_connect($host, $user, $pass);
    $dbs = mysql_select_db($databaseName, $con);

    $array = [0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99];
    $array_unique = [];

    while(!empty($array_unique = array_diff($array, $_SESSION['used']))) {
        //pick a random point from the array
        $random = array_rand($array_unique, 1);

        // Save the used element in session
        $_SESSION['used'][] = $array_unique[$random];

        //store the random question number
        $question = $array_unique[$random];

        // Select information from database and use array to assign to the selected row.
        $query = mysql_query("SELECT `number`,`association`,`image_file`,`skeleton`,`sound`,`colour`,`comments` FROM ".$tableName." WHERE `number` = ".$question." LIMIT 0,1");

        //fetch result to print on page

        $row = mysql_fetch_row($query);

        //Echo result as json
        echo json_encode($row);
    }
    if(count($array_unique) == 0) {
        $_SESSION['used'] = [];
    }
?>

Just use while and array_rand

You can use tf.py_func to wrap load_audio_file().

import tensorflow as tf

tf.enable_eager_execution()

def load_audio_file(file_path):
    # you should decode bytes type to string type
    print("file_path: ",bytes.decode(file_path),type(bytes.decode(file_path)))
    return file_path

train_dataset = tf.data.Dataset.list_files('clean_4s_val/*.wav')
train_dataset = train_dataset.map(lambda x: tf.py_func(load_audio_file, [x], [tf.string]))

for one_element in train_dataset:
    print(one_element)

file_path:  clean_4s_val/1.wav <class 'str'>
(<tf.Tensor: id=32, shape=(), dtype=string, numpy=b'clean_4s_val/1.wav'>,)
file_path:  clean_4s_val/3.wav <class 'str'>
(<tf.Tensor: id=34, shape=(), dtype=string, numpy=b'clean_4s_val/3.wav'>,)
file_path:  clean_4s_val/2.wav <class 'str'>
(<tf.Tensor: id=36, shape=(), dtype=string, numpy=b'clean_4s_val/2.wav'>,)

UPDATE for TF 2

The above solution will not work with TF 2 (tested with 2.2.0), even when replacing tf.py_func with tf.py_function, giving

InvalidArgumentError: TypeError: descriptor 'decode' requires a 'bytes' object but received a 'tensorflow.python.framework.ops.EagerTensor'

To make it work in TF 2, make the following changes:

• Remove tf.enable_eager_execution() (eager is enabled by default in TF 2, which you can verify with tf.executing_eagerly() returning True)
• Replace tf.py_func with tf.py_function
• Replace all in-function references of file_path with file_path.numpy()