Tensorboard可视化实验

实验一：可视化之Graph

对mnist_deep.py代码做适当修改，使用tensorboard查看CNN的整体运行框架图。

def add_layer(inputs, in_size, out_size, activation_function=None):
    # add one more layer and return the output of this layer
    with tf.name_scope('layer'):
        with tf.name_scope('weights'):
            Weights =weight_variable([in_size,out_size])
        with tf.name_scope('biases'):
            biases = bias_variable([1,out_size])
        with tf.name_scope('Wx_plus_b'):
            Wx_plus_b = tf.add(tf.matmul(inputs, Weights),biases)
    if activation_function is None:
        outputs = Wx_plus_b
    else:
        outputs = activation_function(Wx_plus_b)
    return outputs

#loss函数，交叉熵
with tf.name_scope('loss'):
    cross_entropy=tf.reduce_mean(-tf.reduce_sum(y_*tf.log(prediction),