Tensorflow 版本与 tensorboard 版本 [英] Tensorflow version vs tensorboard version

问题描述

我想问一下 tensorflow 的版本会不会和 tensorboard 的不同?

我有一个问题(404 问题)，有人建议安装一个 更新版本的张量板使用:

pip 卸载 tensorflow-tensorboardpip 安装张量板

我检查了我的版本，它们都是1.6.0:

from tensorboard import version;打印(版本.VERSION)将 tensorflow 导入为 tf；打印(tf.__version__)

<块引用>

1.6.0

此外，由于我不记得单独安装 tensorboard(不过我可能会误会这个)，我想它应该在同一版本上.

所以，我的问题是它们可以使用不同的版本吗?(我猜他们可以，因为我们有机会单独安装张量板).升级一个而不是另一个有什么意义吗?后一种情况会不会有冲突?

解决方案

从 TensorFlow 1.3.0 开始，TensorBoard 有了自己的 PyPI 包，但是包之间存在循环依赖，所以当用户安装 TensorFlow 他们总会得到 TensorBoard(这就是你安装它的原因).然而，事实是 TensorFlow 实际上并不依赖 TensorBoard 来工作 和 TensorBoard 甚至没有对 TensorFlow 的依赖，所以这两个包不可能影响每个其他任何方式.

关于建议的修复，它告诉您删除 tensorflow-tensorboard，然后安装 tensorboard.这修复了一个来自1.6.0的已知问题a> 由于将TensorBoard 包从tensorflow-tensorboard 重命名为tensorboard，导致在某些情况下出现问题.在您发布的 GitHub 链接中，开发人员建议将 TensorBoard 从 1.5.1 升级到 1.6.0 以修复一个特定问题，因此需要删除带有旧名称并安装新名称.由于您已经拥有 TensorBoard 1.6.0，因此您绝对应该安装 tensorboard，而不是 tensorflow-tensorboard(您可以使用 pip list 如果需要).要升级到更新版本，您只需运行:

pip install --upgrade tensorboard

I would like to ask if tensorflow version could be different than tensorboard's one?

I have a problem (404 problem) and someone suggested installing a newer version of tensorboard using:

pip uninstall tensorflow-tensorboard
pip install tensorboard

I checked my versions and they are both 1.6.0:

from tensorboard import version; print(version.VERSION)
import tensorflow as tf; print(tf.__version__)

1.6.0

Also since I don't remember installing tensorboard separately (I might be mistaken about this one though) I guess it's expected to be on the same version.

So, my question is could they be on different versions? (I guess they could since we have the opportunity to install tensorboard separately). And also is there a point in upgrading one and not the other? Could there be some conflicts in the latter case?

解决方案

Since TensorFlow 1.3.0, TensorBoard has had its own PyPI package, but there is a circular dependency between the packages, so when users installs TensorFlow they will always get TensorBoard along (that's why you have it installed). However, the fact is that TensorFlow does really not depend on TensorBoard to work and TensorBoard does not even have a dependency to TensorFlow, so it should not be possible that the two packages affect each other in any way.

About the suggested fix, it tells you to remove tensorflow-tensorboard and then install tensorboard. This fixes a known issue from 1.6.0 due to renaming the TensorBoard package from tensorflow-tensorboard to tensorboard, which caused troubles in some cases. In the GitHub link you posted, the developer suggests to upgrade TensorBoard from 1.5.1 to 1.6.0 to fix one particular issue, hence the need to remove the package with the old name and install the new one. Since you already have TensorBoard 1.6.0, you should most definitely have tensorboard installed, not tensorflow-tensorboard (you can check with pip list if you want). To upgrade to a newer version, you can just run:

pip install --upgrade tensorboard

这篇关于Tensorflow 版本与 tensorboard 版本的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！