编程技术网

关注微信公众号,定时推送前沿、专业、深度的编程技术资料。

 找回密码
 立即注册

QQ登录

只需一步,快速开始

极客时间

在 Jupyter Notebook 中运行 Tensorflow:Running Tensorflow in Jupyter Notebook

dannymeijer Tensorflow 2022-5-6 22:40 8人围观

腾讯云服务器
在 Jupyter Notebook 中运行 Tensorflow的处理方法

我正在尝试做一些深度学习工作.为此,我首先在我的 Python 环境中安装了所有用于深度学习的包.

I am trying to do some deep learning work. For this, I first installed all the packages for deep learning in my Python environment.

这就是我所做的.

在Anaconda中,我创建了一个名为tensorflow的环境,如下

In Anaconda, I created an environment called tensorflow as follows

conda create -n tensorflow 

然后在其中安装数据科学 Python 包,如 Pandas、NumPy 等.我还在那里安装了 TensorFlow 和 Keras.这是该环境中的软件包列表

Then installed the data science Python packages, like Pandas, NumPy, etc., inside it. I also installed TensorFlow and Keras there. Here is the list of packages in that environment

(tensorflow) SFOM00618927A:dl i854319$ conda list # packages in environment at /Users/i854319/anaconda/envs/tensorflow: # appdirs 1.4.3 <pip> appnope 0.1.0 py36_0 beautifulsoup4 4.5.3 py36_0 bleach 1.5.0 py36_0 cycler 0.10.0 py36_0 decorator 4.0.11 py36_0 entrypoints 0.2.2 py36_1 freetype 2.5.5 2 html5lib 0.999 py36_0 icu 54.1 0 ipykernel 4.5.2 py36_0 ipython 5.3.0 py36_0 ipython_genutils 0.2.0 py36_0 ipywidgets 6.0.0 py36_0 jinja2 2.9.5 py36_0 jsonschema 2.5.1 py36_0 jupyter 1.0.0 py36_3 jupyter_client 5.0.0 py36_0 jupyter_console 5.1.0 py36_0 jupyter_core 4.3.0 py36_0 Keras 2.0.2 <pip> libpng 1.6.27 0 markupsafe 0.23 py36_2 matplotlib 2.0.0 np112py36_0 mistune 0.7.4 py36_0 mkl 2017.0.1 0 nbconvert 5.1.1 py36_0 nbformat 4.3.0 py36_0 notebook 4.4.1 py36_0 numpy 1.12.1 <pip> numpy 1.12.1 py36_0 openssl 1.0.2k 1 packaging 16.8 <pip> pandas 0.19.2 np112py36_1 pandocfilters 1.4.1 py36_0 path.py 10.1 py36_0 pexpect 4.2.1 py36_0 pickleshare 0.7.4 py36_0 pip 9.0.1 py36_1 prompt_toolkit 1.0.13 py36_0 protobuf 3.2.0 <pip> ptyprocess 0.5.1 py36_0 pygments 2.2.0 py36_0 pyparsing 2.1.4 py36_0 pyparsing 2.2.0 <pip> pyqt 5.6.0 py36_2 python 3.6.1 0 python-dateutil 2.6.0 py36_0 pytz 2017.2 py36_0 PyYAML 3.12 <pip> pyzmq 16.0.2 py36_0 qt 5.6.2 0 qtconsole 4.3.0 py36_0 readline 6.2 2 scikit-learn 0.18.1 np112py36_1 scipy 0.19.0 np112py36_0 setuptools 34.3.3 <pip> setuptools 27.2.0 py36_0 simplegeneric 0.8.1 py36_1 sip 4.18 py36_0 six 1.10.0 <pip> six 1.10.0 py36_0 sqlite 3.13.0 0 tensorflow 1.0.1 <pip> terminado 0.6 py36_0 testpath 0.3 py36_0 Theano 0.9.0 <pip> tk 8.5.18 0 tornado 4.4.2 py36_0 traitlets 4.3.2 py36_0 wcwidth 0.1.7 py36_0 wheel 0.29.0 <pip> wheel 0.29.0 py36_0 widgetsnbextension 2.0.0 py36_0 xz 5.2.2 1 zlib 1.2.8 3 (tensorflow) SFOM00618927A:dl i854319$ 

可以看到jupyter也安装了.

现在,当我在此环境中打开 Python 解释器并运行基本的 TensorFlow 命令时,一切正常.但是,我想在 Jupyter notebook 中做同样的事情.所以,我创建了一个新目录(在这个环境之外).

Now, when I open up the Python interpreter in this environment and I run the basic TensorFlow command, it all works fine. However, I wanted to do the same thing in the Jupyter notebook. So, I created a new directory (outside of this environment).

mkdir dl 

在那,我激活了tensorflow环境

SFOM00618927A:dl i854319$ source activate tensorflow (tensorflow) SFOM00618927A:dl i854319$ conda list 

我可以在其中看到相同的软件包列表.

And I can see the same list of packages in that.

现在,我打开一个 Jupyter 笔记本

Now, I open up a Jupyter notebook

SFOM00618927A:dl i854319$ source activate tensorflow (tensorflow) SFOM00618927A:dl i854319$ jupyter notebook 

它会在浏览器中打开一个新笔记本.但是当我只导入基本的 python 库时,比如熊猫,它说没有可用的包".我不确定为什么当相同的环境具有所有这些包并且位于相同的目录中时,如果我使用 Python 解释器它会显示所有包.

It opens up a new notebook in the browser. But when I just import basic python libraries in that, like pandas, it says "no packages available". I am not sure why is that when the same environment has all those packages and in the same directory, if I use Python interpreter it shows all packages.

import pandas --------------------------------------------------------------------------- ModuleNotFoundError Traceback (most recent call last) <ipython-input-4-d6ac987968b6> in <module>() ----> 1 import pandas ModuleNotFoundError: No module named 'pandas' 

为什么 jupyter notebook 没有选择这些模块?

Why jupyter notebook is not picking up these modules?

因此,Jupyter notebook 不会将 env 显示为解释器

So, Jupyter notebook doesn't show env as the interpreter

问题解答

我想出了你的案例.我就是这样整理的

I came up with your case. This is how I sort it out

  1. 安装蟒蛇
  2. 创建虚拟环境 - conda create -n tensorflow
  3. 进入你的虚拟环境 -(在 macOS/Linux 上:)source activate tensorflow(在 Windows 上:activate tensorflow)
  4. 在里面安装 tensorflow.您可以使用 pip
  5. 安装它
  6. 完成安装
  1. Install Anaconda
  2. Create a virtual environment - conda create -n tensorflow
  3. Go inside your virtual environment - (on macOS/Linux:) source activate tensorflow (on Windows: activate tensorflow)
  4. Inside that install tensorflow. You can install it using pip
  5. Finish install

接下来,当你启动它时:

So then the next thing, when you launch it:

  1. 如果你不在虚拟环境类型中 - Source Activate Tensorflow
  2. 然后再在里面安装你的 Jupiter notebook 和 Pandas 库,因为在这个虚拟环境中可能会缺少一些

在虚拟环境中输入:

  1. pip 安装 jupyter notebook
  2. pip install pandas

然后你可以启动 jupyter notebook 说:

Then you can launch jupyter notebook saying:

  1. jupyter notebook
  2. 选择正确的终端 python 3 或 2
  3. 然后导入这些模块

这篇关于在 Jupyter Notebook 中运行 Tensorflow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编程技术网(www.editcode.net)!

腾讯云服务器

相关推荐

阿里云服务器
关注微信
^