model.py 文件源码

def _build(self,input_shape):
        x = Input(shape=input_shape)
        N = input_shape[0] // 2

        y = Sequential([
            flatten,
            *[Sequential([BN(),
                          Dense(self.parameters['layer'],activation=self.parameters['activation']),
                          Dropout(self.parameters['dropout']),])
              for i in range(self.parameters['num_layers']) ],
            Dense(1,activation="sigmoid")
        ])(x)

        self.loss = bce
        self.net = Model(x, y)
        # self.callbacks.append(self.linear_schedule([0.2,0.5], 0.1))
        self.callbacks.append(GradientEarlyStopping(verbose=1,epoch=50,min_grad=self.parameters['min_grad']))
        # self.custom_log_functions['lr'] = lambda: K.get_value(self.net.optimizer.lr)