word to word text generation example gives error "Invalid training data, labels must not contain undefined values"

When attempting to run example

https://www.mathworks.com/help/textanalytics/ug/word-by-word-text-generation-using-deep-learning.html

I get error

TrainNetwork

Invalid training data, labels must not contain undefined values

url = "https://www.gutenberg.org/files/11/11-h/11-h.htm";
code = webread(url);

tree = htmlTree(code);
selector = "p";
subtrees = findElement(tree,selector);
textData = extractHTMLText(subtrees);
textData(textData == "") = [];

documents = tokenizedDocument(textData);
ds = documentGenerationDatastore(documents);
ds = sort(ds);

inputSize = 1;
embeddingDimension = 100;
numWords = numel(ds.Encoding.Vocabulary);
numClasses = numWords + 1;

layers = [ 
    sequenceInputLayer(inputSize)
    wordEmbeddingLayer(embeddingDimension,numWords)
    lstmLayer(100)
    dropoutLayer(0.2)
    fullyConnectedLayer(numClasses)
    softmaxLayer
    classificationLayer];
options = trainingOptions('adam', ...
    'MaxEpochs',300, ...
    'InitialLearnRate',0.01, ...
    'MiniBatchSize',32, ...
    'Shuffle','never', ...
    'Plots','training-progress', ...
    'Verbose',false);
net = trainNetwork(ds,layers,options);

enc = ds.Encoding;
wordIndex = word2ind(enc,"startOfText")
vocabulary = string(net.Layers(end).Classes);
generatedText = "";
maxLength = 500;
while strlength(generatedText) < maxLength
    % Predict the next word scores.
    [net,wordScores] = predictAndUpdateState(net,wordIndex,'ExecutionEnvironment','cpu');
    
    % Sample the next word.
    newWord = datasample(vocabulary,1,'Weights',wordScores);
    
    % Stop predicting at the end of text.
    if newWord == "EndOfText"
        break
    end
    
    % Add the word to the generated text.
    generatedText = generatedText + " " + newWord;
    
    % Find the word index for the next input.
    wordIndex = word2ind(enc,newWord);
end
punctuationCharacters = ["." "," "’" ")" ":" "?" "!"];
generatedText = replace(generatedText," " + punctuationCharacters,punctuationCharacters);
punctuationCharacters = ["(" "‘"];
generatedText = replace(generatedText,punctuationCharacters + " ",punctuationCharacters)
net = resetState(net);