human
Solve the following python programming problem given the following code:
# Dataset creation

import numpy as np
import math
import random
import csv
from neon.datasets.dataset import Dataset

class WorkoutDS(Dataset):
    # Number of features per example
    feature_count = None

    # Number of examples
    num_train_examples = None
    num_test_examples = None

    # Number of classes
    num_labels = None
    
    # Indicator if the data has been loaded yet
    initialized = False
    
    # Mapping of integer class labels to strings
    human_labels = {}
    
    def human_label_for(self, id):
        return self.human_labels[id]
    
    # Convert an integer representation to a one-hot-vector
    def as_one_hot(self, i, n):
        v = np.zeros(n)
        v[i] = 1
        return v
    
    # Convert an one-hot-vector to an integer representation
    def as_int_rep(self, oh):
        return np.where(oh == 1)[0][0]
    
    # Loads a label mapping from file. The file should contain a CSV tabel mapping integer labels to human readable
    # labels. Integer class labels should start with 1
    def load_label_mapping(self, filename):
        with open(expanduser(filename), 'rb') as csvfile:
            dialect = csv.Sniffer().sniff(csvfile.read(1024))
            csvfile.seek(0)
            csv_data = csv.reader(csvfile, dialect)
            next(csv_data, None)  # skip the headers
            label_mapping = {}
            for row in csv_data:
                # We need to offset the labels by one since counting starts at 0 in python...
                label_mapping[int(row[0]) - 1] = row[1]
        return label_mapping
                
    # Load examples from given CSV file. The dataset should already be splitted into test and train externally
    def load_examples(self, filename):
        with open(expanduser(filename), 'rb') as csvfile:
            dialect = csv.Sniffer().sniff(csvfile.read(1024))
            csvfile.seek(0)
            csv_data = csv.reader(csvfile, dialect)
            next(csv_data, None)  # skip the headers
            y = []
            X = []
           ...
Given the above code, generate some markdown instructions for it.
assistant
#Here is the Python program you requested.

This time we are not going to generate the data but rather use real world annotated training examples.