我正在训练使用张量流进行物体检测的模型..在训练时,在终端中,张量流打印相同的信息两次如下:
INFO:tensorflow:global step 3292: loss = 3.2832 (2.960 sec/step)
INFO:tensorflow:global step 3292: loss = 3.2832 (2.960 sec/step)
INFO:tensorflow:global step 3293: loss = 3.5285 (3.675 sec/step)
INFO:tensorflow:global step 3293: loss = 3.5285 (3.675 sec/step)
INFO:tensorflow:global step 3294: loss = 2.3972 (3.564 sec/step)
INFO:tensorflow:global step 3294: loss = 2.3972 (3.564 sec/step)
INFO:tensorflow:Recording summary at step 3294.
INFO:tensorflow:Recording summary at step 3294.
INFO:tensorflow:global_step/sec: 0.294019
INFO:tensorflow:global_step/sec: 0.294019
我注意到这个“问题”只在使用从源安装的tensorflow进行训练时,我使用pip安装了tensorflow训练了两个模型,并且记录正常。我没有看到这种行为的任何副作用,但我很好奇是什么导致了它。有什么想法吗?
答案 0 :(得分:0)
在m variables_helper.py
中打开odels/research/object_detection/utils/variables_helper.py
并像这样更改import
:
import re
import tensorflow as tf
from tensorflow import logging as logging
slim = tf.contrib.slim
解决了。