TypeError：__call __（）接受2个位置参数，但给出了3个

Question

使用自己的图层时出现此错误：

Traceback (most recent call last):
File "E:/fffan/try.py", line 40, in <module>
 run(input, 5000)
File "E:/fffan/try.py", line 36, in run
 out = SelfAttention(nclass)(output, state)
TypeError: __call__() takes 2 positional arguments but 3 were given

这是我的代码，伙计可以告诉我如何解决。

from keras.engine.topology import Layer
from keras.layers.core import Dense
from keras import backend as K
from keras.layers import Input,CuDNNGRU
from keras.activations import softmax

class SelfAttention(Layer):   #### 对于长序列效果较差
    def __init__(self,units,**kwargs):
        self.W1 = Dense(units)
        self.W2 = Dense(units)
        self.V = Dense(1)
        super(SelfAttention, self).__init__(**kwargs)

    def call(self,features, hidden):
        hidden_with_time_axis = K.expand_dims(hidden, 1)
        score = self.V(K.tanh(self.W1(features) + self.W2(hidden_with_time_axis)))
        attention_weights = softmax(score, axis=1)
        context_vector = attention_weights * features
        return context_vector

def GRU(units):
    return CuDNNGRU(units, return_sequences=True,
                return_state=True,
                recurrent_initializer='glorot_uniform')

def run(input,nclass):
    output, state = GRU(nclass)(input)
    out = SelfAttention(nclass)(output, state)

if __name__ == '__main__':
    input = Input(shape=(35, 512), name='the_input')
    run(input, 5000)

我的tensorflow版本是1.14.0，我的keras是2.1.5

有人知道这个问题吗？

Answer 1

应该是：

def __call__(self, features, hidden):

代替：

def call(self, features, hidden):