tfbasemodel.py 文件源码

def get_input(self):
        # Input data.
        # Load the training, validation and test data into constants that are
        # attached to the graph.
        self.mnist = input_data.read_data_sets('data',
                                    one_hot=True,
                                    fake_data=False)
        # Input placehoolders
        with tf.name_scope('input'):
            self.x = tf.placeholder(tf.float32, [None, 784], name='x-input')
            self.y_true = tf.placeholder(tf.float32, [None, 10], name='y-input')
        self.keep_prob = tf.placeholder(tf.float32, name='drop_out')
        # below is just for the sake of visualization
        with tf.name_scope('input_reshape'):
            image_shaped_input = tf.reshape(self.x, [-1, 28, 28, 1])
            tf.image_summary('input', image_shaped_input, 10)

        return