Question

我正在尝试运行CNN模型进行情绪分析，我收到的错误显示：

文件“twitter-sentiment-cnn.py”，第292行，in       test_batches = list（batch_iter（zip（x_test，y_test），FLAGS.batch_size，1））

文件   “/home/sanaa/Sentimental/Cnn/twitter-sentiment-cnn/data_helpers.py”   第179行，在batch_iter中       data_size = len（data1）TypeError：未确定对象的len（）

 # Pretty-printing variables
if FLAGS.train:
# Batches
  batches = batch_iter(zip(x_train, y_train), FLAGS.batch_size, FLAGS.epochs)
  test_batches = list(batch_iter(zip(x_test, y_test), FLAGS.batch_size, 1))
  my_batch = batches.next()  # To use with human_readable_output()

global_step = 0
batches_in_epoch = len(y_train) / FLAGS.batch_size
batches_in_epoch = batches_in_epoch if batches_in_epoch != 0 else 1
total_num_step = FLAGS.epochs * batches_in_epoch

batches_progressbar = tqdm(batches, total=total_num_step,
                           desc='Starting training...')

这是导致错误的函数：

def batch_iter(data, batch_size, num_epochs):
    """
    Generates a batch iterator for a dataset.
    """
    data = np.array(data)
    data_size = len(data)
    num_batches_per_epoch = int(len(data)/batch_size) + 1
    for epoch in range(num_epochs):
        # Shuffle the data at each epoch
        shuffle_indices = np.random.permutation(np.arange(data_size))
        shuffled_data = data[shuffle_indices]
        for batch_num in range(num_batches_per_epoch):
            start_index = batch_num * batch_size
            end_index = min((batch_num + 1) * batch_size, data_size)
            yield shuffled_data[start_index:end_index]

Answer 1

在python3中，len不能与迭代器一起使用，zip返回一个zip对象，它是一个迭代器。我的猜测是np.array（）保留了迭代器。如果您需要长度，则可能需要应用list()，但这可能会产生可扩展性后果。

TypeError：未确定对象的len（）CNN错误

1 个答案: