我正在关注https://www.tensorflow.org/alpha/tutorials/sequences/text_classification_rnn上的官方教程，但遇到了问题。以下行导致错误：
train_dataset = train_dataset.padded_batch(BATCH_SIZE, train_dataset.output_shapes)
回溯（最后一次调用）：文件“main.py”，第 30 行，在 train_dataset = train_dataset.padded_batch(BATCH_SIZE, train_dataset.output_shapes) AttributeError: 'ShuffleDataset' object has no attribute 'output_shapes
我错过了什么？这是我完成一半的代码：
from __future__ import absolute_import, division, print_function, unicode_literals
import tensorflow_datasets as tfds
import tensorflow as tf
import matplotlib.pyplot as plt
import tensorflow.keras
def plot_graphs(history, string):
plt.plot(history.history[string])
plt.plot(history.history['val_'+string])
plt.xlabel("Epochs")
plt.ylabel(string)
plt.legend([string, 'val_'+string])
plt.show()
dataset, info = tfds.load('imdb_reviews/subwords8k', with_info=True,
as_supervised=True)
train_dataset, test_dataset = dataset['train'], dataset['test']
tokenizer = info.features['text'].encoder
print ('Vocabulary size: {}'.format(tokenizer.vocab_size))
# sample_string = 'TensorFlow is cool.'
# tokenized_string = tokenizer.encode(sample_string)
# print ('Tokenized string is {}'.format(tokenized_string))
# original_string = tokenizer.decode(tokenized_string)
# print ('The original string: {}'.format(original_string))
# assert original_string == sample_string
# for ts in tokenized_string:
# print ('{} ----> {}'.format(ts, tokenizer.decode([ts])))
BUFFER_SIZE = 10000
BATCH_SIZE = 64
train_dataset = train_dataset.shuffle(BUFFER_SIZE)
train_dataset = train_dataset.padded_batch(BATCH_SIZE, train_dataset.output_shapes)
test_dataset = test_dataset.padded_batch(BATCH_SIZE, test_dataset.output_shapes)