model.py 文件源码

def create_dis_model(self):
        # Set up discriminator model parameters
        self.get_dis_params()

        # Set up discriminator graph inputs
        self.person_board_1 = tf.placeholder(tf.float32, [None, self.n_input])
        self.person_board_2 = tf.placeholder(tf.float32, [None, self.n_input])
        self.gen_board = tf.placeholder(tf.float32, [None, self.n_input])       

        # Get discriminator outputs
        self.d_pred_real = self.d_predict(tf.concat(1, [self.person_board_1, self.person_board_2]), self.p_keep)
        self.d_pred_fake = self.d_predict(tf.concat(1, [self.person_board_1, self.gen_board]), self.p_keep)

        # Clamp weights
        self.weight_clamps = [tf.clip_by_value(self.d_weights[layer], -0.01, 0.01) for layer in self.d_weights]
        self.bias_clamps = [tf.clip_by_value(self.d_biases[layer], -0.01, 0.01) for layer in self.d_biases]