I am trying to install a plugin for the Spyder ide called spyder-unittest (description here).
I am using:
MacOS X Version 10.14.6
Anaconda Navigator 1.9.7
Spyder 3.3.6
Python 3.7
After a first attempt using the command
conda install -c spyder-ide spyder-unittest
the plugin did not work (i.e. the additional command Run unit tests was not available under the Run menu).
I also tried, without success:
conda install -c conda-forge spyder-unittest
I then uninstalled and installed once again Anaconda navigator, and tried conda install -c spyder-ide spyder-unittest. This time, I got a very lengthy output, indicating conflicts (please see image):
Now, I do not know what to do. Could someone please offer any help?
I also tried to install after going, through the Terminal, to the directory where I thought the Spyder plugins were installed. Same output as above.
Thank you very much in advance.
Cheers,
Orlando
I managed to install spyder-unittest without any errors on my computer.
I suggest creating a new environment to avoid any conflicts with other packages when installing.
First create a new environment using:
conda create --name env python=3.7
After creating the environment, activate it using conda activate env
Then install spyder-unittest using conda install -c conda-forge spyder-unittest
I'm currently using Windows 10, and installed Pycharm and Anaconda on it in order to run Tensorflow. Everything is working well, I can select conda interpreter and then use the following command to install and run tensorflow.
pip.main(['install', 'tensorflow'])
My only problem is, everytime I create a new project in pycharm, I need to do this installation command again. Is there a more permanent method to do the installation in my case?
Thanks.
EDIT:I installed the package inside Pycharm as shown in this video
Install Video
First you need to build a TensorFlow virtual environment in Anaconda Navigator in the anaconda3 directory.As shown in the figure:anaconda navigator,environment about tensorflow.You can create a Tensorflow environment on the command line and install pycharm as a pip in this environment. This will allow you to use Tensorflow in pycharm.The code is as follows:
conda create -n tensorflow python=3.5
activate tensorflow
pip install --ignore-installed --upgrade tensorflow-gpu
This is a Chinese version of the installation instructions for TensorFlow + pycharm.installation instructions
I am trying to access tensorflow from two ways, both of which are failing:
Installed Anaconda (Windows 32 bit Python 3.6). Then, created a conda environment with Python 3.6 (also tried with 3.5) and Tensorflow. Then, I opened Spyder desktop app. In this Spyder, the tensorflow is not working (e.g. 'import tensorflow as tf' is not working).
From Anaconda Navigator, created an environment (using the GUI), with Python 3.6. Then, I filtered the "Not installed" packages, and searched for "tensorflow". I couldn't find any relevant tensorflor package. All I could find is "r-tensorflow" which is not relevant for me.
The attached image describes the 2nd problem.
Can someone help?
Screenshot of the step 2 above
Open an anaconda prompt, and create an environment with tensorflow like this:
conda create -n tf tensorflow
activate tf
# Verify that it works
python -c "import tensorflow"
Then, you probably have to specify that environment from within Spyder. Open Preferences->Console->Advanced Settings and set the python path to <anaconda_install>/envs/tf/bin/python.
tensorflow can be installed simply by running following commands
On mac/Windows use following command:
conda install -c conda-forge tensorflow
This will install the latest Tensorflow on your system. if you wish to upgrade it to newer verion then you can use the following command
conda update -f -c conda-forge tensorflow
However if you have the virtual environment created from anaconda then before doing these steps you have to activate the environment first and then run the command. With this trensorflow will get installed on your specific command
Please refer the example below for more details:
Creating a environment for Tensorflow
conda create -n “myEnv” python=3.6 anaconda
This will create virtual environment along with anaconda packages. Once this is done, Activate the Environment by :
source activate myEnv #(for mac)
conda activate myEnv #(for windows)
you will see the following.
Once the Environment is active. you can now install the packages you need as follows:
I am showing you the packages which i work upon on virtual environment and this will take care of most of your dependencies
conda update conda
conda upgrade conda
conda upgrade anaconda
conda install pip
conda install -c conda-forge opencv
conda install -c conda-forge tensorflow
conda install -c conda-forge keras
Hope this will solve your problem.
Open Terminal, then enter:
conda update conda
After installing done, enter:
conda install tensorflow
It will take some time based on your internet speed.
After installing, open Anaconda -> Spyder/Jupyter
import tensorflow as ts
Let's break it down in a couple of steps:
If you don't have, download and install Anaconda.
Access Anaconda Command Prompt for the environment that you want to install TensorFlow. If you don't have an environment created, access the Anaconda Prompt.
Assuming that you don't have an environment created, choose the name of your TensorFlow environment, such as "tensor" and install TensorFlow as following
conda create -n tensor tensorflow
conda activate tensor
If you want to install the GPU TensorFlow (Linux or Windows), in the environment "tensor-gpu", use the following
conda create -n tensor-gpu tensorflow-gpu
conda activate tensor-gpu
TensorFlow is now installed. For more information access their documentation.
Try to install Spyder within the Anaconda environment in which you want to use tensorflow. This resolved the issue for me.
I had been stuck on the exact same problem for the past 4 days. I could see 'r - tensorflow' and a few other packages but not the 'tensorflow' package. Apparently, i was using the 32 - bit version of Anaconda. I searched it up and found out that Tensorflow is not supported on 32 - bit platforms. So i uninstalled the 32 - bit version and installed the 64 - bit version. I followed the same steps as before and i was able to find the 'tensorflow' package in the 'not installed' tab.
In my case I used pip instead of conda and it installed without any issue. In my opinion pip installation is much faster than conda installation.
Use
pip install tensorflow
and its done.
I just started to learn how to use Anaconda to manage packages. I am trying to install tensorflow in conda environment. So first of all, I create an environment by:
conda create -n tensorflow
Then, I source it by:
source activate tensorflow
I can see my prompt changed so I think it is going right.
I notice that it seems that the tensorflow environment is copying from ~/anaconda2/lib/ where I do have my root version python2.7 and tensorflow0.12.0
I installed a new version Python in tensorflow environment by:
conda install python=3.5
Then, I follow the steps to install tensorflow by:
pip install --ignore-installed --upgrade TF_PYTHON_URL
However, when I do conda list, I can only see Python3.5 but not tensorflow1.0. I also failed to import tensorflow when I am in Python.
So I have two questions that really confuse me.
Why does the pip installed tensorflow not show up when I do conda list?
Although I conda install python=3.5 and I can see it from conda list, I am not using python 3.5 when I enter Python directly. It seems still using Python2.7, which comes from my root environment.
I appreciate any tutorial on how anaconda works.
I think your pip install is installing into the global environment instead of
tensorflow. Why don't you try installing by specifying the path? For example pip install --target $HOME/anaconda3/tensorflow tensorflow(Where the first tensorflow is your environment and the second is the actual package).
I just saw the last two questions. So you actually see the tensorflow you installed with pip? I am confused now. Type which pip to see if it is running from the tensorflow environment or the global. You could also try source deactivate before source activate tensorflow just to make sure that you are not using a different environment, then run which python. It should show your new environment.
If you want to create an environment using a specific version of Python (rather than the system default), you can do for example:
conda create --name myCoolEnv python=3.5
and then activate with
source activate myCoolEnv
You can read more about Anaconda environments here.
I installed Jupyter notebooks in Ubuntu 14.04 via Anaconda earlier, and just now I installed TensorFlow. I would like TensorFlow to work regardless of whether I am working in a notebook or simply scripting. In my attempt to achieve this, I ended up installing TensorFlow twice, once using Anaconda, and once using pip. The Anaconda install works, but I need to preface any call to python with "source activate tensorflow". And the pip install works nicely, if start python the standard way (in the terminal) then tensorflow loads just fine.
My question is: how can I also have it work in the Jupyter notebooks?
This leads me to a more general question: it seems that my python kernel in Jupyter/Anaconda is separate from the python kernel (or environment? not sure about the terminology here) used system wide. It would be nice if these coincided, so that if I install a new python library, it becomes accessible to all the varied ways I have of running python.
Update
TensorFlow website supports five installations.
To my understanding, using Pip installation directly would be fine to import TensorFlow in Jupyter Notebook (as long as Jupyter Notebook was installed and there were no other issues) b/z it didn't create any virtual environments.
Using virtualenv install and conda install would need to install jupyter into the newly created TensorFlow environment to allow TensorFlow to work in Jupyter Notebook (see the following original post section for more details).
I believe docker install may require some port setup in the VirtualBox to make TensorFlow work in Jupyter Notebook (see this post).
For installing from sources, it also depends on which environment the source code is built and installed into. If it's installed into a freshly created virtual environment or an virtual environment which didn't have Jupyter Notebook installed, it would also need to install Jupyter Notebook into the virtual environment to use Tensorflow in Jupyter Notebook.
Original Post
To use tensorflow in Ipython and/or Jupyter(Ipython) Notebook, you'll need to install Ipython and Jupyter (after installing tensorflow) under the tensorflow activated environment.
Before install Ipython and Jupyter under tensorflow environment, if you do the following commands in terminal:
username$ source activate tensorflow
(tensorflow)username$ which ipython
(tensorflow)username$ /Users/username/anaconda/bin/ipython
(tensorflow)username$ which jupyter
(tensorflow)username$ /Users/username/anaconda/bin/jupyter
(tensorflow)username$ which python
(tensorflow)username$ /User/username//anaconda/envs/tensorflow/bin/python
This is telling you that when you open python from terminal, it is using the one installed in the "environments" where tensorflow is installed. Therefore you can actually import tensorflow successfully. However, if you are trying to run ipython and/or jupyter notebook, these are not installed under the "environments" equipped with tensorflow, hence it has to go back to use the regular environment which has no tensorflow module, hence you get an import error.
You can verify this by listing out the items under envs/tensorflow/bin directory:
(tensorflow) username$ ls /User/username/anaconda/envs/tensorflow/bin/
You will see that there are no "ipython" and/or "jupyer" listing out.
To use tensorflow with Ipython and/or Jupyter notebook, simply install them into the tensorflow environment:
(tensorflow) username$ conda install ipython
(tensorflow) username$ pip install jupyter #(use pip3 for python3)
After installing them, there should be a "jupyer" and a "ipython" show up in the envs/tensorflow/bin/ directory.
Notes:
Before trying to import tensorflow module in jupyter notebook, try close the notebook. And "source deactivate tensorflow" first, and then reactivate it ("source activate tensorflow") to make sure things are "on the same page". Then reopen the notebook and try import tensorflow. It should be import successfully (worked on mine at least).
i used these following which in virtualenv.
pip3 install --ignore-installed ipython
pip3 install --ignore-installed jupyter
This re-installs both ipython and jupyter notebook in my tensorflow virtual environment. You can verify it after installation by which ipython and which jupyter. The bin will be under the virtual env.
NOTE I am using python 3.*
I have another solution that you don't need to source activate tensorflow before using jupyter notebook every time.
Partion 1
Firstly, you should ensure you have installed jupyter in your virtualenv. If you have installed, you can skip this section (Use which jupyter to check). If you not, you could run source activate tensorflow, and then install jupyter in your virtualenv by conda install jupyter. (You can use pip too.)
Partion 2
1.From within your virtualenv, run
username$ source activate tensorflow
(tensorflow)username$ ipython kernelspec install-self --user
This will create a kernelspec for your virtualenv and tell you where it is:
(tensorflow)username$ [InstallNativeKernelSpec] Installed kernelspec pythonX in /home/username/.local/share/jupyter/kernels/pythonX
Where pythonX will match the version of Python in your virtualenv.
2.Copy the new kernelspec somewhere useful. Choose a kernel_name for your new kernel that is not python2 or python3 or one you've used before and then:
(tensorflow)username$ mkdir -p ~/.ipython/kernels
(tensorflow)username$ mv ~/.local/share/jupyter/kernels/pythonX ~/.ipython/kernels/<kernel_name>
3.If you want to change the name of the kernel that IPython shows you, you need to edit ~/.ipython/kernels/<kernel_name>/kernel.json and change the JSON key called display_name to be a name that you like.
4.You should now be able to see your kernel in the IPython notebook menu: Kernel -> Change kernel and be able so switch to it (you may need to refresh the page before it appears in the list). IPython will remember which kernel to use for that notebook from then on.
Reference.
Here is what I did to enable tensorflow in Anaconda -> Jupyter.
Install Tensorflow using the instructions provided at
Go to /Users/username/anaconda/env and ensure Tensorflow is installed
Open the Anaconda navigator and go to "Environments" (located in the left navigation)
Select "All" in teh first drop down and search for Tensorflow
If its not enabled, enabled it in the checkbox and confirm the process that follows.
Now open a new Jupyter notebook and tensorflow should work
Your Anaconda install probably went to different directory than your Python install
For instance on my machine I can find location here
yaroslavvb-macbookpro:~ yaroslavvb$ which ipython
/Users/yaroslavvb/anaconda/bin/ipython
When you type python, it tries to find it in PATH going in left-to-right order. So you may have another version of python in a folder before Anaconda folder, and it'll use that. To fix, you can do export PATH=.... to change the path, and put Anaconda directory in front, so that it takes python from there instead of the default, ie
export PATH=/Users/yaroslavvb/anaconda/bin:$PATH
I installed PIP with Conda conda install pip instead of apt-get install python-pip python-dev.
Then installed tensorflow
use Pip Installation:
# Ubuntu/Linux 64-bit, CPU only, Python 2.7
$ export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.9.0-cp27-none-linux_x86_64.whl
# Ubuntu/Linux 64-bit, GPU enabled, Python 2.7
# Requires CUDA toolkit 7.5 and CuDNN v4. For other versions, see "Install from sources" below.
$ export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow-0.9.0-cp27-none-linux_x86_64.whl
...
pip install --upgrade $TF_BINARY_URL
Then it will work in jupyter notebook.
The accepted answer (by Zhongyu Kuang) has just helped me out. Here I've create an environment.yml file that enables me to make this conda / tensorflow installation process repeatable.
Step 1 - create a Conda environment.yml File
environment.yml looks like this:
name: hello-tensorflow
dependencies:
- python=3.6
- jupyter
- ipython
- pip:
- https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-1.1.0-cp36-cp36m-linux_x86_64.whl
Note:
Simply replace the name to whatever you want. (mine is hello-tensorflow)
Simply replace the python version to whatever you want. (mine is 3.6)
Simply replace the tensorflow pip install URL to whatever you want (mine is the Tensorflow URL where Python 3.6 with GPU support)
Step 2 - create the Conda environment
With the environment.yml being in the current path you are on, this command creates the environment hello-tensorflow (or whatever you have renamed it to):
conda env create -f environment.yml
Step 3: source activate
Activate the newly created environment:
source activate hello-tensorflow
Step 4 - which python / jupyter / ipython
which python...
(hello-tensorflow) $ which python
/home/johnny/anaconda3/envs/hello-tensorflow/bin/python
which jupyter...
(hello-tensorflow) $ which jupyter
/home/johnny/anaconda3/envs/hello-tensorflow/bin/jupyter
which ipython...
(hello-tensorflow) $ which ipython
/home/johnny/anaconda3/envs/hello-tensorflow/bin/ipython
Step 5
You should now be able to import tensorflow from python, jupyter (console / qtconsole / notebook, etc.) and ipython.
I think your question is very similar with the question post here. Windows 7 jupyter notebook executing tensorflow. As Yaroslav mentioned, you can try
conda install -c http://conda.anaconda.org/jjhelmus tensorflow .
I had a similar issue when using a custom Ubuntu 16 image. The problem was related to an existing version of numpy that was already installed on my system.
I initially tried
sudo pip3 install tensorflow
This resulted in the following exception:
Exception:
Traceback (most recent call last):
File "/anaconda/envs/py35/lib/python3.5/shutil.py", line 538, in move
os.rename(src, real_dst)
PermissionError: [Errno 13] Permission denied: '/anaconda/envs/py35/lib/python3.5/site-packages/numpy' -> '/tmp/pip-co73r3hm-uninstall/anaconda/envs/py35/lib/python3.5/site-packages/numpy'
The docs advise that if you encounter any issues with this command to try the following:
sudo pip3 install --upgrade \
https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.0.1-cp35-cp35m-linux_x86_64.whl
However, my system was unable to locate pip3
sudo: pip3 command not found
The ulitmate solution was to create a symlink for pip3
sudo ln -s /anaconda/envs/py35/bin/pip3.5 /usr/local/bin/pip3
Finally, the following command worked without trouble
sudo /usr/local/bin/pip3 install --upgrade \
https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.0.1-cp35-cp35m-linux_x86_64.whl
I verified the installation in the terminal and also verified a successful import in my Jupyter Notebook
import tensorflow as tf
I wonder if it is not enough to simply launch ipython from tensorflow environnement. That is
1) first activate tensorflow virtualenv with:
source ~/tensorflow/bin/activate
2) launch ipython under tensorflow environnement
(tensorflow)$ ipython notebook --ip=xxx.xxx.xxx.xxx
I found the solution from someone else's post. It is simple and works well!
http://help.pythonanywhere.com/pages/IPythonNotebookVirtualenvs
Just install the following in the Command Prompt and change kernel to Python 3 in Jupyter Notebook. It will import tensorflow successfully.
pip install tornado==4.5.3
pip install ipykernel==4.8.2
(Orginial post: https://github.com/tensorflow/tensorflow/issues/11851)
Jupyter Lab: ModuleNotFound tensorflow
For a future version of me or a colleague that runs into this issue:
conda install -c conda-forge jupyter jupyterlab keras tensorflow
Turns out jupyterlab is a plugin for jupyter.
So even if you are in an environment that has jupyter but not jupyterlab as well, if you try to run:
jupyter lab
then jupyter will look in the (base) environment for the jupyterlab plugin.
Then your imports in jupyter lab will be relative to that plugin and not your conda environment.
pip install tensorflow
This worked for me in my conda virtual environment.
I was trying to use conda install tensorflow in a conda virtual environment where jupyter notebooks was already installed, resulting in many conflicts and failure. But pip install worked fine.
conda info --envs
conda create --name py3-TF2.0 python=3
Proceed ([y]/n)? y
conda activate py3-TF2.0
conda install tensorflow
pip install --upgrade tensorflow
conda install -c anaconda ipykernel
python -m ipykernel install --user --name=py3-TF2.0
it is the best way but if it is required you should upgrade numpy with scipy as well
You can try "conda install tensorflow". This will install TensorFlow in your Anaconda directory.
Your local pip directory might not be shared with the Anaconda directory.
Thanks!
Open an Anaconda Prompt screen: (base) C:\Users\YOU>conda create -n tf tensorflow
After the environment is created type: conda activate tf
Prompt moves to (tf) environment, that is: (tf) C:\Users\YOU>
then install Jupyter Notebook in this (tf) environment:
conda install -c conda-forge jupyterlab - jupyter notebook
Still in (tf) environment, that is type
(tf) C:\Users\YOU>jupyter notebook
The notebook screen starts!!
A New notebook then can import tensorflow
FROM THEN ON
To open a session
click Anaconda prompt,
type conda activate tf
the prompt moves to tf environment
(tf) C:\Users\YOU>
then type (tf) C:\Users\YOU>jupyter notebook