tensorboard的使用

一时失言乱红尘 2021-11-17 12:52 281阅读 0赞

# 1.在pycharm中运行生成图的代码 #

import tensorflow as tf
    import numpy as np
    
    ## prepare the original data
    with tf.name_scope('data'):
         x_data = np.random.rand(100).astype(np.float32)
         y_data = 0.3*x_data+0.1
    ##creat parameters
    with tf.name_scope('parameters'):
         weight = tf.Variable(tf.random_uniform([1],-1.0,1.0))
         bias = tf.Variable(tf.zeros([1]))
    ##get y_prediction
    with tf.name_scope('y_prediction'):
         y_prediction = weight*x_data+bias
    ##compute the loss
    with tf.name_scope('loss'):
         loss = tf.reduce_mean(tf.square(y_data-y_prediction))
    ##creat optimizer
    optimizer = tf.train.GradientDescentOptimizer(0.5)
    #creat train ,minimize the loss 
    with tf.name_scope('train'):
         train = optimizer.minimize(loss)
    #creat init
    with tf.name_scope('init'): 
         init = tf.global_variables_initializer()
    ##creat a Session 
    sess = tf.Session()
    ##initialize
    writer = tf.summary.FileWriter("logs/", sess.graph)
    sess.run(init)
    ## Loop
    for step  in  range(101):
        sess.run(train)
        if step %10==0 :
            print(step ,'weight:',sess.run(weight),'bias:',sess.run(bias))

# 2.运行代码，找到生成的log文件的位置 #

![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L0NoYXJvbm1vbW8_size_16_color_FFFFFF_t_70]  
![在这里插入图片描述][20190730223334553.png]打开命令框，输入：

tensorboard --logdir=D:\pyworkspace\PycharmProjects\untitled\logs

后面的地址是生成log文件的位置。  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L0NoYXJvbm1vbW8_size_16_color_FFFFFF_t_70 1]最后这里给出的就算tensorboard的网址，复制到浏览器中打开就可以了。  
不要使用CTRL+C退出，否则网页无法打开。  
![在这里插入图片描述][20190730223756969.png]![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L0NoYXJvbm1vbW8_size_16_color_FFFFFF_t_70 2]

[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L0NoYXJvbm1vbW8_size_16_color_FFFFFF_t_70]: /images/20211116/f6a216cbeb3e49ca978eab57b58e109a.png
[20190730223334553.png]: /images/20211116/074c234e58504aaa95c84a4a9c25cced.png
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L0NoYXJvbm1vbW8_size_16_color_FFFFFF_t_70 1]: /images/20211116/32f7e40ef4db421f9b3e7e7567b39461.png
[20190730223756969.png]: https://img-blog.csdnimg.cn/20190730223756969.png
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L0NoYXJvbm1vbW8_size_16_color_FFFFFF_t_70 2]: /images/20211116/740fe0409bc84c888b69e930c7f82083.png