If you are running Windows 10, with Python 3.6.. X version on your system Method 2: Downgrade Your Python Version On Anaconda . Tensorflow only supports Python 3.6.x and only the 64bit version.
The location of the Tensor. Flow directory on Windows will depend on your Python distribution. You should be able to find it by doing the following: C:> python >>>import tensorflow as tf >>>print(tf.__file__ ).
Another frequent inquiry is “How to install TensorFlow on Windows with Python?”.
I found the answer was if Python is installed, open IDLE as shown below. If pip is already installed and added to path, go to command line, type pip install tensorflow as shown below. Doing this will install Tensorflow on your Windows computer.
This of course begs the query “Where is TensorFlow installed with Pip?”
The most usefull answer is; installing with pip, installs the packages to the directory “site-packages“. The following code shows the location of tensorflow as well as where pip installs the packages: $ pip show tensorflow Which return:.
One article claimed that to confirm that Tensorflow has been installed on your Windows computer, go to idle and type import tensorflow as tf in the shell as shown below. If there are no errors, then it means Tensorflow has been succesfully installed on your Windows computer.
How to install a specific version of TensorFlow?
Use pip to install Tensor. Flow 2 as usual. (See there for extra instructions about GPU support.) Then install a current version of tensorflow-hub next to it (must be 0.5.0 or newer). $ pip install “tensorflow>=2.0.0” $ pip install –upgrade tensorflow-hub. The TF1-style API of Tensor. Flow Hub works with the v1 compatibility mode of Tensor, and flow 2.
Bookmark this question. Show activity on this post. Name: tensorflow Version: 1.10.0 Summary: Tensor. Flow is an open source machine learning framework for everyone.
What are the prerequisites for TensorFlow?
You should have good knowledge of some programming language—preferably Python. It is also important to have an understanding of machine learning to understand the use case and examples. Before directly understanding what is Tensor. Flow, you should know about deep learning and its libraries.