attentions.py 文件源码

def __call__(self, S, h):
    batch_size, src_len, hidden_size = S.data.shape
    h = F.broadcast_to(F.expand_dims(h, axis=2), (batch_size, hidden_size, src_len))
    h = F.swapaxes(h, 1, 2)
    S = F.reshape(F.concat((S, h), axis=2), (batch_size * src_len, 2 * hidden_size))
    a = F.softmax(F.reshape(self.second_layer(F.tanh(self.first_layer(S))), (batch_size, src_len)))
    return a