在Jupyter Notebook中运行Tensorflow [英] Running Tensorflow in Jupyter Notebook
问题描述
我正在尝试做一些深度学习工作.为此，我首先在Python环境中安装了所有用于深度学习的软件包.
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，如下所示:
In Anaconda, I created an environment called tensorflow as follows
conda create -n tensorflow
然后在其中安装了数据科学Python包，例如Pandas，NumPy等.我也在那里安装了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$
您可以看到还安装了jupyter.
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笔记本中做同样的事情.因此，我创建了一个新目录(在此环境之外).
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
那样，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Jupyter笔记本
Now, I open up a Jupyter notebook
SFOM00618927A:dl i854319$ source activate tensorflow
(tensorflow) SFOM00618927A:dl i854319$ jupyter notebook
它将在浏览器中打开一个新笔记本.但是当我只是在其中导入基本的python库(如pandas)时，它说没有可用的软件包".我不确定为什么在同一环境中所有这些软件包都位于同一目录中时，如果使用Python解释器，它将显示所有软件包.
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笔记本电脑不接这些模块?
Why jupyter notebook is not picking up these modules?
因此，Jupyter笔记本不会将env显示为解释器
So, Jupyter notebook doesn't show env as the interpreter
推荐答案
我想出了你的案子.这就是我的解决方法
I came up with your case. This is how I sort it out
- 安装Anaconda
- 创建虚拟环境-
conda create -n tensor flow - 进入您的虚拟环境-
Source activate tensorflow - 在其中安装tensorflow.您可以使用
pip安装它
- 完成安装
- Install Anaconda
- Create a virtual environment -
conda create -n tensor flow - Go inside your virtual environment -
Source activate tensorflow - Inside that install tensorflow. You can install it using
pip - Finish install
那么接下来的事情，当您启动它:
So then the next thing, when you launch it:
- 如果您不在虚拟环境中，请输入-
Source Activate Tensorflow - 然后在其中再次安装您的Jupiter Notebook和Pandas库，因为在此虚拟环境中可能会缺少一些
在虚拟环境中，只需键入:
Inside the virtual environment just type:
-
pip install jupyter notebook -
pip install pandas
pip install jupyter notebookpip install pandas
然后您可以启动jupyter笔记本，说:
Then you can launch jupyter notebook saying:
-
jupyter notebook - 选择正确的终端python 3或2
- 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IT屋！
