任何人都知道kera.preprocessing.text.Tockenizer到底如何工作？
word_index = tokenizer.word_index
print('Found %s unique tokens.' % len(word_index))
data = pad_sequences(sequences, maxlen=maxlen)
labels = np.asarray(labels)
print('Shape of data tensor:', data.shape)
print('Shape of label tensor:', labels.shape)
indices = np.arange(data.shape[0])
np.random.shuffle(indices)
data = data[indices]
labels = labels[indices]
x_train = data[:training_samples]
y_train = labels[:training_samples]
x_val = data[training_samples: training_samples + validation_samples]
y_val = labels[training_samples: training_samples + validation_samples]
找到了88413个唯一令牌。数据张量的形状：（24984，100）的形状 标签张量：（24984，）
tokenizer.texts_to_sequences('You are Amrock!')
出[18]： [[5128]，[1601]，[1205]，[]，[3]，[1480]，[962]，[]，[3]， [1978]，[1480]，[1601]，[1144]，[2292]，[]]
Out [18]到底是什么意思？