Question

我正在使用keras运行注意图层与GRU在python中进行情感分析，但是，python给了我这个错误信息：

TypeError :(＆＃39;不是Keras张量：＆＃39;，Elemwise {add，no_inplace} .0）。

我在网站上搜索但是这个问题仍然无法解决。这是我的代码：

os.environ['KERAS_BACKEND']='theano'

#Attention GRU network
class AttLayer(Layer):
    def __init__(self, **kwargs):
        self.init = initializers.get('normal')
        # self.input_spec = [InputSpec(ndim=3)]
        super(AttLayer, self).__init__(**kwargs)

    def build(self, input_shape):
        assert len(input_shape) == 3
        # self.W = self.init((input_shape[-1],1))
        self.W = self.init((input_shape[-1],))
        # self.input_spec = [InputSpec(shape=input_shape)]
        self.trainable_weights = [self.W]
        super(AttLayer, self).build(input_shape)  # be sure you call this somewhere!

    def call(self, x, mask=None):
        eij = K.tanh(K.dot(x, self.W))

        ai = K.exp(eij)
        weights = ai / K.sum(ai, axis=1).dimshuffle(0, 'x')

        weighted_input = x * weights.dimshuffle(0, 1, 'x')
        return weighted_input.sum(axis=1)

    def compute_output_shape(self, input_shape):
        return input_shape[0], input_shape[-1]


def get_idx_from_sent(sent, word_idx_map, max_l=1187, filter_h=3):
    """
    Transforms sentence into a list of indices. Pad with zeroes.
    """
    x = []
    pad = filter_h - 1
    for i in range(pad):
        x.append(0)
    words = sent.split()
    for word in words:
        if word in word_idx_map:
            x.append(word_idx_map[word])
    while len(x) < max_l + 2 * pad:
        x.append(0)
    return x


def make_idx_data_cv(revs, word_idx_map, max_l=1187, k=300, filter_h=3):
    """
    Transforms sentences into a 2-d matrix.
    """
    data = []
    for rev in revs:
        sent = get_idx_from_sent(rev["text"], word_idx_map, max_l, filter_h)
        sent.append(rev["y"])
        data.append(sent)

    x = np.array(data, dtype="int")[:,:-1]
    data_y= np.array(data, dtype="int")[:,-1]
    return x, data_y

#load data
x = pk.load(open("mr_allSentiment.p", "rb"))
revs, W, W2, word_idx_map, vocab = x[0], x[1], x[2], x[3], x[4]
X,Y = make_idx_data_cv(revs, word_idx_map, max_l=1187, k=300,filter_h=3)
x_train, x_test, y_train, y_test =train_test_split(X,Y,test_size=0.1)


#keras layers
embedding_layer = Embedding(len(vocab) + 1,
                            300,
                            weights=[W],
                            input_length=1191,
                            trainable=True)

sequence_input = Input(shape=(1191,), dtype='int32')
embedded_sequences = embedding_layer(sequence_input)
l_gru = Bidirectional(GRU(100, return_sequences=True))(embedded_sequences)
l_att = AttLayer()(l_gru)
preds = Dense(1, activation='sigmoid')(l_att)
model = Model(sequence_input, preds)
model.compile(loss='binary_crossentropy',
              optimizer='adam',
              metrics=['acc'])

#estimate model
print("model fitting - attention GRU network")
model.summary()
model.fit(x_train, y_train, validation_data=(x_test, y_test),
          nb_epoch=10, batch_size=50)

然而，它卡住了，这是错误信息：

Traceback (most recent call last):
  File "C:/Users/ruowe/PycharmProjects/resnet/test1.py", line 101, in <module>
    nb_epoch=10, batch_size=50)
  File "C:\Users\ruowe\Anaconda3\lib\site-packages\keras\engine\training.py", line 1575, in fit
    self._make_train_function()
  File "C:\Users\ruowe\Anaconda3\lib\site-packages\keras\engine\training.py", line 960, in _make_train_function
    loss=self.total_loss)
  File "C:\Users\ruowe\Anaconda3\lib\site-packages\keras\legacy\interfaces.py", line 87, in wrapper
    return func(*args, **kwargs)
  File "C:\Users\ruowe\Anaconda3\lib\site-packages\keras\optimizers.py", line 427, in get_updates
    ms = [K.zeros(K.int_shape(p), dtype=K.dtype(p)) for p in params]
  File "C:\Users\ruowe\Anaconda3\lib\site-packages\keras\optimizers.py", line 427, in <listcomp>
    ms = [K.zeros(K.int_shape(p), dtype=K.dtype(p)) for p in params]
  File "C:\Users\ruowe\Anaconda3\lib\site-packages\keras\backend\theano_backend.py", line 275, in int_shape
    raise TypeError('Not a Keras tensor:', x)
TypeError: ('Not a Keras tensor:', Elemwise{add,no_inplace}.0)

Answer 1

有同样的问题，在这里找到答案：

https://www.cpume.com/question/fsnnffzn-why-the-keras-code-get-error-messages-when-changing-from-keras-1-2-2-to-keras-2.html

简短回答 - 这是Keras ver的变化。 2

将构建功能更改为：

def build(self, input_shape):
    assert len(input_shape)==3
    self.W = self.add_weight(name='kernel', 
                                  shape=(input_shape[-1],),
                                  initializer='normal',
                                  trainable=True)
    super(AttLayer, self).build(input_shape)

TypeError :(＆＃39;不是Keras张量：＆＃39;，Elemwise {add，no_inplace} .0）

1 个答案: