We can setup Tensorflow environment in local machine using following options:
Virtualenv
"native" pip
Docker
Anaconda
For using an IDE like PyCharm is recommended by most of all. Is there any proper guideline to setup Tensorflow in PyCharm IDE using any of above environment.
I have done Tensorflow setup in PyCharm IDE using anaconda environment. Here is the step by step details:
First install python in your local machine. I used Anaconda3 environment to install Python.
Then install tensorflow within the anaconda environment
Download and install PyCharm IDE from this link.
Open PyCharm IDE and then create a simple test project
Now go to File -> Settings -> Project Interpreter (Under the Project: Test)
Select path form project interpreter and set the path below for tensorflow environment home/user/anaconda3/envs/tensorflow/bin/python
Then apply and OK.
You can now test and work with tensorflow code as well as python code.
Related
I followed the instructions on the official website to download the TensorFlow. I chose to create a virtual environment as the instruction shown for macOS. My question is that if I need to activate the virtual environment each time before I use TensorFlow?
For example, I want to use tensor flow on Jupiter notebook and that means I need to install Jupiter and other required packages like Seaborn/pandas as well on the virtual environment. However I already downloaded anaconda and basically, it has all the packages I need.
Besides, will it make a difference if I download it with conda?
Well, if you downloaded the packages (like you said TensorFlow and Seaborn) in the base Conda environment which is the default environment that anaconda provides on installation, then to use what it has, you need to run whatever program/IDE like Jupyter lab from it. So you would open Anaconda Prompt and then type in jupyter lab and it would open up a new socket and you can edit with your installed python libraries from Conda.
Otherwise in IDE's VSCode you can simply set the python interpreter to that from Conda.
However, if you install the libraries and packages you need using pip on your actual python installation not Conda, then there is no need for any activation. Everything will run right out of the box. You don't need to select the interpreter in IDE's like VSCode.
Bottom line, if you know what libraries you need and don't mind running pip install package-name every time you need a package, stick with pip.
If you don't like to that sort of 'low level' stuff then use Anaconda or Miniconda.
Attempting to run tensorflow a Mac, using python 3.7 as well as PyCharm and receiving where module tensorflow has no attribute app, at the following.
I've run through a number of potential solutions. Following the instructions provided on this question: Installing tensorflow on Pycharm (Mac). I've managed to successfully create a virtual-env in which I installed the tensorflow package however this folder contains
nothing but the init.py and pycache and the error remains.
I've also tried copying the contents of the tensorflow GitHub repo directly into this folder but it results in an ImportError.
Not sure what the issue is. Should I switch to python 2.7?
Python 3.7 is still unsupported as of this moment by tensorflow.
I have installed NumPy using pip install and it's working fine while using it in the python interpreter on the command line. But whenever I try
import numpy in PyCharm it throws an error module not found.
I already set the right path in the project interpretor and the import numpy command is working fine with other IDEs such as Syder or Jupyter notebook but it doesn't work in PyCharm.
I found a YouTube video that worked for me in importing a package into PyCharm. First, click on the File menu, then click on Settings, then click on Project Interpreter. Look for a + sign to the right and click on that. That allows you to add a package. Then search for your package of choice (I wanted numpy) in the Search bar at the top. Click on the name, and then at the bottom click on Install Package. After a few minutes, it will say, package successfully installed, and sure enough it was. I was able to import numpy the usual way in PyCharm.
Did you install official Python or Anaconda/Miniconda?
I assume PyCharm created either a virtualenv or a conda env, or an isolated Python environment that does not have NumPy installed.
You should either use your global environment instead of virtualenv:
Settings, Project: project-name / Project Interpreter, https://www.jetbrains.com/help/pycharm/configuring-python-interpreter.html
Or install NumPy in your virtualenv or conda env.
This is more complicated. If you open Terminal in PyCharm and it says (project-name) in your prompt, try pip install numpy.
So I started to build tensorflow in Mac and the thing is that it doesn't seem possible to build tensorflow in Mac OS platform.
After following instructions in here, I get this package directory.
It seems like the build settings for bazel is only for linux distro. The reason why I thought so is because there is a .so file in package directory that is needed to be linked after importing tensorflow using python binary.
This is the result I get after importing tensorflow using python.
Is there any other way I can build tensorflow on Mac OS?
It seems like there are no options but to install tensorflow with pip. So I just created a new virtual machine and installed ubuntu 16.04 to use it as my docker host. By doing so, I can create a new docker container which can now link and execute the linux library.
Upon trying to install Tensorflow for conda environment, I encountered with the following error message, without any progress:
tensorflow-1.1.0-cp35-cp35mwin_amd64.whl is not a supported wheel on this platform
Have you tried uninstalling and re-installing TensorFlow using pip within your Conda environment? I.e.:
pip uninstall tensorflow
Followed by:
pip install tensorflow
If it doesn't work, the issue may be with your Python installation. TensorFlow only supports 64-bit Python 3.5+ on Windows (see more info here).
Perhaps you have Python's default installation, which comes in a 32-bit version. If that's the case, you can download the 64-bit Python 3.5 or later from here to run in your Conda environment and then you should be able to install/run TensorFlow without any issues.
Make sure that the Python version installed in the Environment is 3.5 not 3.6. Since 3.6 was released Conda automatically sets that version as default for python 3. However, it is still not supported by Tensorflow.
You can work using tensorflow library along with other essential libraries using the Dockerfile. Using Docker for environment are a good way to run experiments in reproducible manner as in this blog
You can also try using datmo in order setup environment and track machine learning projects for making it reproducible using datmo CLI tool.