model.py 文件源码

def update_weights_and_calc_values_temp(self, d_w_i_j, layer_to_perturbe, i, j, X):
        """Update the weights of the given layer cacl the output and return it to the original values"""
        if layer_to_perturbe + 1 >= len(self.hidden_layers):
            scope_name = 'softmax_linear'
        else:
            scope_name = "hidden" + str(layer_to_perturbe)
        weights = get_scope_variable(scope_name, "weights", shape=None, initializer=None)
        session = tf.get_default_session()
        weights_values = weights.eval(session=session)
        weights_values_pert = weights_values
        weights_values_pert[i, j] += d_w_i_j
        set_value(weights, weights_values_pert)
        feed_dict = {self.x: X}
        layer_values = session.run(self.hidden_layers[layer_to_perturbe], feed_dict=feed_dict)
        set_value(weights, weights_values)
        return layer_values