Question

我有一个可变大小的文本语料库。我正在尝试使用keras中的Embedding层将文本输入LSTM模型。我的代码如下所示：

import numpy as np
from keras.layers import Embedding, Input, LSTM, RNN, SimpleRNN
from keras.models import Model, Sequential


vocab_size = 20000
embedding_len = 50

model = Sequential()
model.add(Embedding(vocab_size, embedding_len))

我使用numpy随机数生成器生成了样本输入：

akak=[]
for i in range(10):
    akak.append(np.random.randint(0, 20, size = (np.random.randint(1,30, size=None))))
input_array = np.asarray(akak)
print(input_array)

输出：

array([array([16,  2,  9, 12, 18, 10, 10, 14,  3, 11,  4,  6,  8, 11,  3]),
       array([ 3,  6,  5,  8,  3, 10, 19,  9, 17]),
       array([ 1,  6, 17, 14, 14, 19, 12, 15, 14,  0, 16,  2,  1, 18, 13, 14, 17,
       14,  2, 11,  0, 19,  2,  8, 13, 10, 17, 13,  5]),
       array([ 5, 10, 18,  0,  4,  8]),
       array([ 5, 14, 19, 16, 10,  8, 13,  8, 12,  5, 19]),
       array([ 7,  4, 17,  0, 10,  8,  3,  6, 14,  4,  8,  9,  0]),
       array([ 4,  7,  7, 16,  7,  6, 16,  9,  4,  2, 11]),
       array([ 2, 16, 15, 16, 18, 11,  7,  1,  0,  5, 11, 12, 11,  8,  3,  8,  8,
       16, 19,  8]),
       array([12, 18, 19, 15, 11,  6, 16, 16,  2, 12,  0, 14, 16,  0]),
       array([12, 13, 13])], dtype=object)

当我尝试使用model.predict(input_array)预测仅获得嵌入时，出现以下错误

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-49-313059fadb55> in <module>()
----> 1 model.predict(input_array).shape

/home/biswadip/.local/lib/python3.6/site-packages/keras/engine/training.py in predict(self, x, batch_size, verbose, steps)
   1167                                             batch_size=batch_size,
   1168                                             verbose=verbose,
-> 1169                                             steps=steps)
   1170 
   1171     def train_on_batch(self, x, y,

/home/biswadip/.local/lib/python3.6/site-packages/keras/engine/training_arrays.py in predict_loop(model, f, ins, batch_size, verbose, steps)
    292                 ins_batch[i] = ins_batch[i].toarray()
    293 
--> 294             batch_outs = f(ins_batch)
    295             batch_outs = to_list(batch_outs)
    296             if batch_index == 0:

/home/biswadip/.local/lib/python3.6/site-packages/keras/backend/tensorflow_backend.py in __call__(self, inputs)
   2713                 return self._legacy_call(inputs)
   2714 
-> 2715             return self._call(inputs)
   2716         else:
   2717             if py_any(is_tensor(x) for x in inputs):

/home/biswadip/.local/lib/python3.6/site-packages/keras/backend/tensorflow_backend.py in _call(self, inputs)
   2653                 array_vals.append(
   2654                     np.asarray(value,
-> 2655                                dtype=tf.as_dtype(tensor.dtype).as_numpy_dtype))
   2656         if self.feed_dict:
   2657             for key in sorted(self.feed_dict.keys()):

/home/biswadip/.local/lib/python3.6/site-packages/numpy/core/numeric.py in asarray(a, dtype, order)
    536 
    537     """
--> 538     return array(a, dtype, copy=False, order=order)
    539 
    540 

ValueError: setting an array element with a sequence.

我知道我可以填充序列，但是LSTM层不会只返回填充序列的最后一个隐藏状态。我想要隐藏在实际序列的最后一个隐藏状态中的隐藏状态，而不是填充的状态，即，如果我的序列长度是15，最大序列长度是200，我希望隐藏状态向量从第15个状态而不是第200个状态

可变长度输入到嵌入层Keras

0 个答案: