I am trying to do some deep learning work. For this, I first installed all the packages for deep learning in my Python environment.
Here is what I did.
In Anaconda, I created an environment called tensorflow
as follows
conda create -n tensorflow
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$
You can see that jupyter
is also installed.
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
In that, I activated tensorflow
environment
SFOM00618927A:dl i854319$ source activate tensorflow
(tensorflow) SFOM00618927A:dl i854319$ conda list
And I can see the same list of packages in that.
Now, I open up a Jupyter notebook
SFOM00618927A:dl i854319$ source activate tensorflow
(tensorflow) SFOM00618927A:dl i854319$ jupyter notebook
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'
Why jupyter notebook is not picking up these modules?
So, Jupyter notebook doesn't show env as the interpreter
This question is related to
python
tensorflow
jupyter-notebook
keras
You will need to add a "kernel" for it. Run your enviroment:
>activate tensorflow
Then add a kernel by command (after --name should follow your env. with tensorflow):
>python -m ipykernel install --user --name tensorflow --display-name "TensorFlow-GPU"
After that run jupyter notebook from your tensorflow env.
>jupyter notebook
And then you will see the following enter image description here
Click on it and then in the notebook import packages. It will work out for sure.
For Anaconda users in Windows 10 and those who recently updated Anaconda environment, TensorFlow may cause some issues to activate or initiate. Here is the solution which I explored and which worked for me:
conda create -n tensorflow python=3.5 (Use this command even if you are using python 3.6 because TensorFlow will get upgraded in the following steps)
activate tensorflow After this step, the command prompt will change to (tensorflow)
pip install --ignore-installed --upgrade Now you have successfully installed the CPU version of TensorFlow.
I would suggest launching Jupyter lab/notebook from your base environment and selecting the right kernel.
How to add conda environment to jupyter lab should contains the info needed to add the kernel to your base environment.
Disclaimer : I asked the question in the topic I linked, but I feel it answers your problem too.
install tensorflow by running these commands in anoconda shell or in console:
conda create -n tensorflow python=3.5
activate tensorflow
conda install pandas matplotlib jupyter notebook scipy scikit-learn
pip install tensorflow
close the console and reopen it and type these commands:
activate tensorflow
jupyter notebook
I came up with your case. This is how I sort it out
conda create -n tensor flow
Source activate tensorflow
pip
So then the next thing, when you launch it:
Source Activate Tensorflow
Inside the virtual environment just type:
pip install jupyter notebook
pip install pandas
Then you can launch jupyter notebook saying:
jupyter notebook
Only this solution worked for me. Tried 7 8 solutions. Using Windows platform.
It is better to create new environment with new name ($newenv):conda create -n $newenv tensorflow
Then by using anaconda navigator under environment tab you can find newenv in the middle column.
By clicking on the play button open terminal and type: activate tensorflow
Then install tensorflow inside the newenv by typing: pip install tensorflow
Now you have tensorflow inside the new environment so then install jupyter by typing: pip install jupyter notebook
Then just simply type: jupyter notebook
to run the jupyter notebook.
Inside of the jupyter notebook type: import tensorflow as tf
To test the the tf you can use THIS LINK
Although it's a long time after this question is being asked since I was searching so much for the same problem and couldn't find the extant solutions helpful, I write what fixed my trouble for anyone with the same issue:
The point is, Jupyter should be installed in your virtual environment, meaning, after activating the tensorflow
environment, run the following in the command prompt (in tensorflow
virtual environment):
conda install jupyter
jupyter notebook
and then the jupyter will pop up.
I believe a short video showing all the details if you have Anaconda is the following for mac (it is very similar to windows users as well) just open Anaconda navigator and everything is just the same (almost!)
https://www.youtube.com/watch?v=gDzAm25CORk
Then go to jupyter notebook and code
!pip install tensorflow
Then
import tensorflow as tf
It work for me! :)
I have found a fairly simple way to do this.
Initially, through your Anaconda Prompt, you can follow the steps in this official Tensorflow site - here. You have to follow the steps as is, no deviation.
Later, you open the Anaconda Navigator. In Anaconda Navigator, go to Applications On --- section. Select the drop down list, after following above steps you must see an entry - tensorflow into it. Select tensorflow and let the environment load.
Then, select Jupyter Notebook in this new context, and install it, let the installation get over.
After that you can run the Jupyter notebook like the regular notebook in tensorflow environment.
Source: Stackoverflow.com