有没有办法获取tensorflow tf.打印输出出现在Jupyter Notebook输出中 [英] Is there a way to get tensorflow tf.Print output to appear in Jupyter Notebook output

问题描述

我正在Jupyter笔记本中使用tf.Print op.它可以按要求工作，但是只会将输出打印到控制台，而不能在笔记本中打印.有什么办法可以解决这个问题?

I'm using the tf.Print op in a Jupyter notebook. It works as required, but will only print the output to the console, without printing in the notebook. Is there any way to get around this?

一个示例如下(在笔记本中):

An example would be the following (in a notebook):

import tensorflow as tf

a = tf.constant(1.0)
a = tf.Print(a, [a], 'hi')
sess = tf.Session()
a.eval(session=sess)

该代码将在控制台中显示"hi [1]"，但在笔记本中什么也不会显示.

That code will print 'hi[1]' in the console, but nothing in the notebook.

推荐答案

更新2017年2月3日 我已经将其包装到 memory_util 包中.用法示例

Update Feb 3, 2017 I've wrapped this into memory_util package. Example usage

# install memory util
import urllib.request
response = urllib.request.urlopen("https://raw.githubusercontent.com/yaroslavvb/memory_util/master/memory_util.py")
open("memory_util.py", "wb").write(response.read())

import memory_util

sess = tf.Session()
a = tf.random_uniform((1000,))
b = tf.random_uniform((1000,))
c = a + b
with memory_util.capture_stderr() as stderr:
    sess.run(c.op)

print(stderr.getvalue())

**旧东西**

您可以重用 FD重定向器(来自IPython核心). (来自马克·桑德勒的想法)

You could reuse FD redirector from IPython core. (idea from Mark Sandler)

import os
import sys

STDOUT = 1
STDERR = 2

class FDRedirector(object):
    """ Class to redirect output (stdout or stderr) at the OS level using
        file descriptors.
    """ 

    def __init__(self, fd=STDOUT):
        """ fd is the file descriptor of the outpout you want to capture.
            It can be STDOUT or STERR.
        """
        self.fd = fd
        self.started = False
        self.piper = None
        self.pipew = None

    def start(self):
        """ Setup the redirection.
        """
        if not self.started:
            self.oldhandle = os.dup(self.fd)
            self.piper, self.pipew = os.pipe()
            os.dup2(self.pipew, self.fd)
            os.close(self.pipew)

            self.started = True

    def flush(self):
        """ Flush the captured output, similar to the flush method of any
        stream.
        """
        if self.fd == STDOUT:
            sys.stdout.flush()
        elif self.fd == STDERR:
            sys.stderr.flush()

    def stop(self):
        """ Unset the redirection and return the captured output. 
        """
        if self.started:
            self.flush()
            os.dup2(self.oldhandle, self.fd)
            os.close(self.oldhandle)
            f = os.fdopen(self.piper, 'r')
            output = f.read()
            f.close()

            self.started = False
            return output
        else:
            return ''

    def getvalue(self):
        """ Return the output captured since the last getvalue, or the
        start of the redirection.
        """
        output = self.stop()
        self.start()
        return output

import tensorflow as tf
x = tf.constant([1,2,3])
a=tf.Print(x, [x])

redirect=FDRedirector(STDERR)

sess = tf.InteractiveSession()
redirect.start();
a.eval();
print "Result"
print redirect.stop()

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