【转载】 tf.Print() (------------ tensorflow中的print函数)

原文地址:

https://blog.csdn.net/weixin_36670529/article/details/100191674

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调试程序的时候,经常会需要检查中间的参数,这些参数一般是定义在model或是别的函数中的局部参数,由于tensorflow要求先构建计算图再运算的机制,也不能定义后直接print出来。tensorflow有一个函数tf.Print()。

tf.Print(input, data, message=None, first_n=None, summarize=None, name=None)

最低要求两个输入,input和data,input是需要打印的变量的名字,data要求是一个list,里面包含要打印的内容。

参数:

  • message是需要输出的错误信息
  • first_n指只记录(打log日志)前n次
  • summarize是对每个tensor只打印的条目数量,如果是None,对于每个输入tensor只打印3个元素
  • name是op的名字

需要注意的是tf.Print()只是构建一个op,需要run之后才会打印。

例子:

x=tf.constant([2,3,4,5])
y=tf.Print(x,[x,x.shape,'test', x],message='Debug message:',summarize=100)
     
with tf.Session() as sess:
    sess.run(y)
     
#Debug message:[2 3 4 5][4][test][2 3 4 5]
     
z=tf.Print(x,[x,x.shape,'test', x],message='Debug message:',summarize=2)
     
with tf.Session() as sess:
    sess.run(z)
     
#Debug message:[2 3...][4][test][2 3...]

输出是在命令窗口中,和print有区别

    x=tf.constant([2,3,4,5])
         
    with tf.Session() as sess:
        print(sess.run(x))
         
    #[2,3,4,5]

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原文链接:https://blog.csdn.net/weixin_36670529/article/details/100191674

附:

Print(input_, data, message=None, first_n=None, summarize=None, name=None)
    Prints a list of tensors.
    
    This is an identity op with the side effect of printing `data` when
    evaluating.
    
    Args:
      input_: A tensor passed through this op.
      data: A list of tensors to print out when op is evaluated.
      message: A string, prefix of the error message.
      first_n: Only log `first_n` number of times. Negative numbers log always;
               this is the default.
      summarize: Only print this many entries of each tensor. If None, then a
                 maximum of 3 elements are printed per input tensor.
      name: A name for the operation (optional).
    
    Returns:
      Same tensor as `input_`.

原文地址:https://www.cnblogs.com/devilmaycry812839668/p/12038482.html