model.py 文件源码

def _build(self,input_shape):
        x = Input(shape=input_shape)

        y = Sequential([
            Convolution2D(self.parameters['clayer'], (3,3), padding='same', activation=self.parameters['activation']),
            BN(),
            Dropout(self.parameters['dropout']),
            MaxPooling2D((2,2)),
            Convolution2D(self.parameters['clayer'], (3,3), padding='same', activation=self.parameters['activation']),
            BN(),
            Dropout(self.parameters['dropout']),
            MaxPooling2D((2,2)),
            Convolution2D(self.parameters['clayer'], (3,3), padding='same', activation=self.parameters['activation']),
            BN(),
            Dropout(self.parameters['dropout']),
            MaxPooling2D((2,2)),
            flatten,
            Dense(self.parameters['layer'], activation=self.parameters['activation']),
            # BN(),
            # Dropout(self.parameters['dropout'])
            # *[Sequential([,])
            #   for i in range(self.parameters['num_layers']) ],
            Dense(1,activation="sigmoid")
        ])(x)

        def loss(x,y):
            return bce(x,y)
        self.loss = loss
        self.net = Model(x, y)