layer.py 文件源码

def connect(self, inputs):
    energy = tensor.dot(inputs, self.W) + self.b
    energy = energy.reshape([energy.shape[0] * energy.shape[1], energy.shape[2]])
    log_scores = tensor.log(tensor.nnet.softmax(energy))
    predictions = tensor.argmax(log_scores, axis=-1)
    return (log_scores, predictions)