如何编码序列以在keras中对RNN进行排序？

Question

我正在尝试编写序列以在keras中对RNN进行排序.我使用我从网上理解的内容编写了这个程序.我首先表征然后将文本转换的文本成序列和填充,以形成特征变量X.获得目标变量Y,首先将x向左移动然后填充它.最后,我将我的功能和目标变量提供给了我的LSTM模型.

这是我为此目的用keras编写的代码.

from keras.preprocessing.text import Tokenizer,base_filter
from keras.preprocessing.sequence import pad_sequences
from keras.models import Sequential
from keras.layers import Dense, Activation,Dropout,Embedding
from keras.layers import LSTM


def shift(seq, n):
    n = n % len(seq)
    return seq[n:] + seq[:n]

txt="abcdefghijklmn"*100

tk = Tokenizer(nb_words=2000, filters=base_filter(), lower=True, split=" ")
tk.fit_on_texts(txt)
x = tk.texts_to_sequences(txt)
#shifing to left
y = shift(x,1)

#padding sequence
max_len = 100
max_features=len(tk.word_counts)
X = pad_sequences(x, maxlen=max_len)
Y = pad_sequences(y, maxlen=max_len)

#lstm model
model = Sequential()
model.add(Embedding(max_features, 128, input_length=max_len, dropout=0.2))
model.add(LSTM(128, dropout_W=0.2, dropout_U=0.2))
model.add(Dense(max_len))
model.add(Activation('softmax'))
model.compile(loss='binary_crossentropy', optimizer='rmsprop')

model.fit(X, Y, batch_size=200, nb_epoch=10)

问题是它显示错误

Epoch 1/10
IndexError: index 14 is out of bounds for size 14
Apply node that caused the error: AdvancedSubtensor1(if{inplace}.0, Reshape{1}.0)
Toposort index: 80

Answer 1

问题在于:

model.add(Embedding(max_features, 128, input_length=max_len, dropout=0.2))

在嵌入文档中,您可能会看到提供给它的第一个参数应该设置为词汇量+ 1的大小.这是因为null索引所在的单词应始终存在0.因此,您需要将此行更改为:

model.add(Embedding(max_features + 1, 128, input_length=max_len, dropout=0.2))