I am tying to install Fbprophet (python)
I followed all installation instructions (anaconda).
If I try to run Fbprophet in my anaconda prompt it works fine.
However, when I create a project in Visual studio 2017 I get the following error message:
Traceback (most recent call last):
File "C:\Users\dommarch\source\repos\FbProphet\FbProphet\FbProphet.py", line 1, in
import fbprophet
File "C:\Users\dommarch\AppData\Local\Continuum\anaconda2\envs\python36\lib\site-packages\fbprophet__init__.py", line 8, in
from fbprophet.forecaster import Prophet
File "C:\Users\dommarch\AppData\Local\Continuum\anaconda2\envs\python36\lib\site-packages\fbprophet\forecaster.py", line 17, in
import pystan # noqa F401
File "C:\Users\dommarch\AppData\Roaming\Python\Python36\site-packages\pystan__init__.py", line 9, in
from pystan.api import stanc, stan
File "C:\Users\dommarch\AppData\Roaming\Python\Python36\site-packages\pystan\api.py", line 13, in
import pystan._api # stanc wrapper
ImportError: DLL load failed: %1 is not a valid Win32 application.
If anyone has an idea it would be awesome.
Thanks
The version of (fb)prophet, pystan and python are important.
I managed to get it working for this stack:
CentOS: 7
Python: 3.8
GCC: 4.8.5
PyStan: 2.19.1.1
FbProphet: 0.7.1
And for this particular stack, you need GCC++ 2014 compiler, provided by this package:
centos-release-scl devtoolset-8
For Windows, using conda, python 3.8, steps are documented in this article and will summarize below:
Access anaconda using conda command in your command line
Build new virtual environment e.g. time_series, this environment will run in Python 3.8,
conda create -n time_series python=3.8
Access your environment using this command:
conda activate time_series
Install the C++ compiler:
conda install libpython m2w64-toolchain -c msys2
Installation of the dependencies of fbprophet:
conda install numpy cython -c conda-forge
conda install matplotlib scipy pandas -c conda-forge
conda install pystan -c conda-forge
conda install -c anaconda ephem
Install the library that will used for your time series forecasting environment:
pip install scikit-learn
pip install --user pmdarima
conda install -c conda-forge fbprophet
Note: Fbprophet was renamed to Prophet
https://github.com/facebook/prophet/issues/1874
So, you may need to install prophet too:
pip install pystan==2.19.1.1 prophet
or
conda install -c conda-forge prophet
I want to run keras on anaconda for convolution neural network using mnist handwriting recognition. A day before everything worked fine but as I try to run the same program, i get the following error in the first line:
from keras.datasets import mnist (first line of code)
ModuleNotFoundError: No module named 'keras.datasets'; 'keras' is not
a package
I also created virtual environment to use python 3.5 as my python version is 3.6. I have installed both keras and tensorflow. How do i fix the above error? Perhaps it is related to path and not error with keras. My anaconda is installed in E: whearas working environment is C:\Users\Prashant Mahato.
Do you get an error message if you just import keras? I was getting a similar error in the command line and then implemented in Spyder (using Anaconda) and it worked fine.
Here is how I install Keras and other related dependencies
conda create -n <Environment_Name> python=3.6
activate <Environment_Name>
conda update --all
conda install mingw libpython
conda install scipy
conda install numpy
conda install mkl
conda install -c conda-forge tensorflow
conda install theano
pip install pyyaml
pip install h5py
pip install keras
conda install -c conda-forge tmux
conda install pandas
condas install pillow
conda install scikit-learn
conda install -c menpo opencv3
To check if everything is work as it should just import all the packages in python within the environment created.
I'm running Windows 10 and Anaconda 4.2
If running Ubuntu, replace
activate <Environment_Name>
with
source activate <Environment_Name>
HTH.
I am trying to install Tensorflow on my Windows PC. Since I have already install and used Anaconda on Python (3.5), I have followed the instructions https://www.tensorflow.org/versions/r0.8/get_started/os_setup.html#anaconda-environment-installation .
After the creation of the conda environment called tensorflow, I have tested my installation with:
$ python
Import tensorflow as tf
But I got the error :
ImportError: no module named 'tensorflow'
Does anyone know what I missed?
Thank you very much!
UPDATE: Since TensorFlow 0.12, we have published packages for Windows. You can install the CPU-only version with the following command:
C:\> pip install tensorflow
…and the GPU-accelerated version with:
C:\> pip install tensorflow-gpu
Note that you will need the 64-bit version of Python 3.5 installed for the above commands to work.
TensorFlow is not currently supported on Windows, and none of the official binary packages work on Windows. We are currently working on adding support for Windows, but this effort is in the early stages.
See the answers to this question for suggestions on how to run TensorFlow using Docker or Bash for Windows.
It looks like you need to activate the virtual environment that TensorFlow was installed in. When you activate the virtual environment, it will appear in parenthesis in your command prompt, like in the example tutorial:
$ source activate tensorflow
(tensorflow)$ # Your prompt should change
The source command only works on Linux/Mac as far as I'm aware, so for windows you'll have to follow the instructions here:
http://conda.pydata.org/docs/using/envs.html#change-environments-activate-deactivate
In general, the script file that handles the activation is location in [your_environment]/bin/activate if you're curious about what it does.
So basically the tensorflow files are installed inside this environment folder, and Python won't be able to find them unless this folder is added to the PATH where it searches for libraries, and this is essentially what activating the environment does!
The above provided steps will install the TensorFlow in your Windows System but still you might face problem in making it available in your Jupyter notebook - hence integrating steps from different places together to have a complete solution:
How to install Tensorflow in Anaconda environment on windows 10
1) Download and install Anaconda 3.6 (3.5 and above) in your system from Anaconda site.
2) Restart your system
3) Create virtual environment by following command:
conda create -n tensorflow
4) Activate the virtual environment
C:> activate tensorflow
(tensorflow)C:> # Your prompt should change
TensorFlow in anaconda
5) Following steps should start installing Tensorflow in virtual environment
(tensorflow)C:> conda install -c conda-forge tensorflow
6) Now you may enter in python and work on tensorflow
(tensorflow)C:> python
7) But if you like to work on Tensorflow on Jupyter notebook you need to setup the karnel for your virtual environment in following steps:
a) Install the ipython kernel module into your virtualenv
activate your virtualenv, if you haven't already
pip install ipykernel
b) Now run the kernel "self-install" script:
python -m ipykernel install --user --name=my-virtualenv-name
Replacing the --name parameter as appropriate. In my case it is tensorflow
c) 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.
8) Test the tensorflow with following program you should see “Hello, TensorFlow!”
import tensorflow as tf
hello = tf.constant('Hello, TensorFlow!')
sess = tf.Session()
print(sess.run(hello))
you can use pip to install tensorflow
Install python 3.5 x64
Install tensorflow using pip
pip install --upgrade https://storage.googleapis.com/tensorflow/windows/cpu/tensorflow-0.12.0rc0-cp35-cp35m-win_amd64.whl
Install Visual C++ 2015 redistributable (x64 version) to be able to import tensorflow
Tensorflow installation using Conda:
Install Anaconda3-4.2.0 X64 (I ran into issue with latest release 4.3.0)
Upgrade conda version 4.2.9-->4.2.11 (again, ran into some issues with conda 4.2.9)
conda install conda=4.2.11
create environment
conda create -n tf python=3.5
activate tf
conda install -c conda-forge tensorflow
try installing tensorflow in conda
open anaconda prompt
and type this
conda install tensorflow
This worked for me (with spyder which is optional), typing in the anaconda prompt, on Windows 7:
conda create -n tensorflow pip python=3.5
conda activate tensorflow
pip install --ignore-installed --upgrade tensorflow
conda install spyder
spyder
To exit the virtual environment:
conda deactivate
To restart the virtual environment:
conda activate tensorflow
spyder
I have installed Anaconda on Windows 64 bit. I have downloaded PyCharm for creating a project and in the terminal of PyCharm I have installed numpy, scipy, matplotlib using the following commands:
conda install numpy
conda install scipy
conda install matplotlib
I am not able to install Tensorflow in the same way I installed these other packages. How should I install it?
Google has recently launched a newer version of TensorFlow r0.12 which include support of Windows both CPU and GPU version can now be installed using Python >=3.5.2 (only 64-bit) version.
For CPU only version open command prompt and enter follow command
pip install --upgrade https://storage.googleapis.com/tensorflow/windows/cpu/tensorflow-0.12.0rc0-cp35-cp35m-win_amd64.whl
Follow this TensorFlow on Windows for step-by-step instructions.
UPDATE
To install current latest version please run following command:
pip install tensorflow #CPU only
pip install tensorflow-gpu #For GPU support
UPDATE 2020
TensorFlow 2.0 now has a single package for both CPU and GPU version, simply run
pip install tensorflow
If you're using Anaconda you can install TensorFlow GPU version and all of its dependencies (CUDA, cuDNN) by running:
conda install -c tensorflow-gpu
To install TF on windows, follow the below-mentioned steps:
conda create --name tensorflow python=3.5
activate tensorflow
conda install jupyter
conda install scipy
pip install tensorflow-gpu
Use pip install tensorflow in place of pip install tensorflow-gpu, in case if you want to install CPU only version of TF.
Note: This installation has been tested with Anaconda Python 3.5 (64 bit). I have also tried the same installation steps with (a) Anaconda Python 3.6 (32 bit), (b) Anaconda Python 3.6 (64 bit), and (c) Anaconda Python 3.5 (32 bit), but all of them (i.e. (a), (b) and (c) ) failed.
Currently tensorflow has binaries only for Unix based OS i.e. Ubuntu Mac OS X - that's why no mention of Windows in setup docs.
There are long discussions on Github:
Open - Windows Support and Documentation
Closed - How to install TensorFlow on Windows
Closed - How to install/run/use TensorFlow on windows machines?
A SO answer - tensorflow — is it or will it (sometime soon) be compatible with a windows workflow?
Suggestion:
For now, on Windows, the easiest way to get started with TensorFlow
would be to use Docker:
http://tensorflow.org/get_started/os_setup.md#docker-based_installation
It should become easier to add Windows support when Bazel (the build
system we are using) adds support for building on Windows, which is on
the roadmap for Bazel 0.3. You can see the full Bazel roadmap here.
Or simply use a Linux VM (using VMPlayer), and the stated steps will setup it up for you.
For PyCharm - Once conda environment will be created, you'll need to set the new interpretor (in conda environment) as the interpretor to use in PyCharm:
Now to use the conda interpreter from PyCharm go to file > settings > project > interpreter, select Add local in the project interpreter field (the little gear wheel) and browse the interpreter or past the path.
The default location - the environment lives under conda_root/envs/tensorflow. The new python interpreter 'll be at conda_root/envs/tensorflow/bin/pythonX.X , such that the site-packages will be in conda_root/envs/tensorflow/lib/pythonX.X/site-packages.
Google has announced support for tensorflow on Windows. Please follow instructions at https://developers.googleblog.com/2016/11/tensorflow-0-12-adds-support-for-windows.html. Please note CUDA8.0 is needed for GPU installation.
If you have installed the 64-bit version of Python 3.5 (either from Python.org or Anaconda), you can install TensorFlow with a single command:
C:> pip install tensorflow
For GPU support, if you have CUDA 8.0 installed, you can install the following package instead:
C:> pip install tensorflow-gpu
I was able to install tensorflow on windows following the instructions on tensorflow.org, using the conda method of installation, as given here: https://www.tensorflow.org/get_started/os_setup#anaconda_installation.
There are small differences on how to activate an 'environment' on windows, you call 'activate' directly without the 'source'. So, for me after installing anaconda the steps where:
C:\Users\Dunschm>conda create -n tensorflow python=3.5
C:\Users\Dunschm>activate tensorflow
(tensorflow) C:\Users\Dunschm>conda install -c conda-forge tensorflow
activate tensorflow
conda install -c conda-forge tensorflow worked for me.
None of the other steps mentioned online helped, I found it here when trying to install an older version.
Eventhough the steps mentioned in the link seems to be for MAC OS X/Linux it worked in windows 7
You can install spyder along with this
conda install spyder
This worked for me:
conda create -n tensorflow python=3.5
activate tensorflow
conda install -c conda-forge tensorflow
Open Anaconda Navigator.
Change the dropdown of "Applications on" from "root" to "tensorflow"
see screenshot
Launch Spyder
Run a little code to validate you're good to go:
import tensorflow as tf
node1 = tf.constant(3, tf.float32)
node2 = tf.constant(4) # also tf.float32 implicitly
print(node1, node2)
or
hello = tf.constant('Hello, TensorFlow!')
sess = tf.Session()
print(sess.run(hello))
I have python 3.5 with anaconda. First I tried everything given above but it did not work for me on windows 10 64bit.
So I simply tried:-
Open the command prompt
Check for python version for which you want to install tensorflow, if you have multiple versions of python.
If you just have one version, then type in cmd:
C:/>conda install tensorflow
for multiple versions of python, type in cmd:
C:/>conda install tensorflow python=version(e.g.python=3.5)
It works, just give it a try.
After installation open ipython console and import tensorflow:
import tensorflow
If tensorflow installed properly then you are ready to go.
Enjoy machine learning:-)
I found a more recent blog post in Anaconda which instructs how to install the TF easily.
I used:
conda create -n tensorflow_env tensorflow
Or for the GPU version (Make sure that you have NVIDIA GPU)
conda create -n tensorflow_gpuenv tensorflow-gpu
This way you will have different environments for different TFs.
The following command from inside your command window (and preferably, conda environment) will work provided you have an Nvidia graphics card.
conda install tensorflow-gpu
1) Update conda
Run the anaconda prompt as administrator
conda update -n base -c defaults conda
2) Create an environment for python new version say, 3.6
conda create --name py36 python=3.6
3) Activate the new environment
conda activate py36
4) Upgrade pip
pip install --upgrade pip
5) Install tensorflow
pip install https://testpypi.python.org/packages/db/d2/876b5eedda1f81d5b5734277a155fa0894d394a7f55efa9946a818ad1190/tensorflow-0.12.1-cp36-cp36m-win_amd64.whl
If it doesn't work
If you have problem with wheel at the environment location, or pywrap_tensorflow problem,
pip install tensorflow --upgrade --force-reinstall
This is what I did for Installing Anaconda Python 3.6 version and Tensorflow on Window 10 64bit.And It was success!
Go to https://www.continuum.io/downloads to download Anaconda Python 3.6 version for Window 64bit.
Create a conda environment named tensorflow by invoking the following command:
C:> conda create -n tensorflow
Activate the conda environment by issuing the following command:
C:> activate tensorflow (tensorflow)C:> # Your prompt should change
Go to http://www.lfd.uci.edu/~gohlke/pythonlibs/enter code here download “tensorflow-1.0.1-cp36-cp36m-win_amd64.whl”. (For my case, the file will be located in “C:\Users\Joshua\Downloads” once after downloaded)
Install the Tensorflow by using the following command:
(tensorflow)C:>pip install C:\Users\Joshua\Downloads\ tensorflow-1.0.1-cp36-cp36m-win_amd64.whl
This is what I got after the installing:
Validate installation by entering following command in your Python environment:
import tensorflow as tf
hello = tf.constant('Hello, TensorFlow!')
sess = tf.Session()
print(sess.run(hello))
If the output you got is 'Hello, TensorFlow!',that means you have successfully install your Tensorflow.
Install Anaconda for Python 3.5 - Can install from here for 64 bit windows
Then install TensorFlow from here
(I tried previously with Anaconda for Python 3.6 but failed even after creating Conda env for Python3.5)
Additionally if you want to run a Jupyter Notebook and use TensorFlow in it. Use following steps.
Change to TensorFlow env:
C: > activate tensorflow
(tensorflow) C: > pip install jupyter notebook
Once installed, you can launch Jupyter Notebook and test
(tensorflow) C: > jupyter notebook
Open anaconda prompt
make sure your pip version is updated
and you have python 3.4 3.5 or 3.6
Just run the command
pip install --upgrade tensorflow
you can take help from the documentation and video
Goodluck
I use windows 10, Anaconda and python 2. A combination of mentioned solutions worked for me:
Once you installed tensorflow using:
C:\Users\Laleh>conda create -n tensorflow python=3.5 # use your python version
C:\Users\Laleh>activate tensorflow
(tensorflow) C:\Users\Laleh>conda install -c conda-forge tensorflow
Then I realized tensorflow can not be imported in jupyter notebook, although it can work in commad windows. To solve this issue first I checked:
jupyter kernelspec list
I removeed the Jupyter kernelspec, useing:
jupyter kernelspec remove python2
Now, the jupyter kernelspec list is pointing to the correct kernel. Again, I activate tensorflow and installed notebook in its environment:
C:\Users\Laleh>activate tensorflow
(tensorflow)C:> conda install notebook
Also if you want to use other libraries such as matplotlib, they should be installed separately in tensorflow environment
(tensorflow)C:> conda install -c conda-forge matplotlib
Now everything works fine for me.
This documentation link is helpful and worked for me. Installs all dependencies and produces a working Anaconda. Or this answer is also helpful if you want to use it with spyder
If you have anaconda version 2.7 installed on your windows, then go to anaconda prompt, type these two commands:
Create a conda environment for tensorflow using conda create -n tensorflow_env tensorflow
activate the tensorflow using conda activate tensorflow_env
If it is activated, then the base will be replaced by tensorflow_env i.e. now it will show (tensorflow_env) C:\Users>
You can now use import tensorflow as tf for using tensorflow in your code.
I tried many things but always faced some issue or other. Below steps with specific version only worked for me.
1> Create virtual env
#conda create -n tensorflow pip python=3.5
2> activate env
#activate tensorflow
#conda info --envs
3> Install tensorflow
#conda install -c conda-forge tensorflow
this will install tensorflow 1.10.0
#python -m pip install --upgrade pip
#pip install setuptools==39.1.0
3> Install keras
#pip install keras==2.2.2
Testing
(tensorflow) C:\WINDOWS\system32>python
Python 3.5.6 |Anaconda, Inc.| (default, Aug 26 2018, 16:05:27) [MSC v.1900 64 bit (AMD64)] on win32
Type "help", "copyright", "credits" or "license" for more information.
>>> import tensorflow as tf
>>> import keras
Using TensorFlow backend.
>>>
The above steps
conda install -c conda-forge tensorflow
will work for Windows 10 as well but the Python version should be 3.5 or above. I have used it with Anaconda Python version 3.6 as the protocol buffer format it refers to available on 3.5 or above.
Thanks,
Sandip
"Conda" installs some of the special packages that might have compiled in C or other languages.
You can use "pip install tensorflow" and it will work.