I am using tensorflow currently on a virtualbox Linux VM, on a native windows pc.
This is slow.
I've read what I could find about this (e.g.: How to install TensorFlow on Windows?)
However, they suggest using a Virtual Machine, which is maybe 10 times slower compared to a native OS.
Is there a way to use Tensorflow just in windows directly?
Yes. We recently announced TensorFlow 0.12, which is the first version that comes with Windows support and pre-built packages for Windows. It supports Python 3.5 and GPU acceleration with GPUs that support CUDA 8.0. To install the Python package on Windows you can use pip:
C:\> pip install tensorflow
To install the GPU-acclerated version there is a different package:
C:\> pip install tensorflow-gpu
Related
I wanted to use tensorflow for GPU for my current project so I followed a tutorial from youtube to install it without using conda (https://www.youtube.com/watch?v=-Q6SM_usn84)
I followed the tutorial and turns out there is no CUDA 11.2 for windows 11. Hence I installed the latest version i.e. CUDA 12 and followed the rest of the tutorial.
I then proceeded to create a virtualenv using python 3.10.10 and installed tensorflow using:
pip3 install --upgrade https://storage.googleapis.com/tensorflow/windows/cpu/tensorflow_cpu-2.11.0-cp310-cp310-win_amd64.whl
It did install successfully and imports but does not list my GPU as a physical device available.
After a bit of research I came across this "https://forums.developer.nvidia.com/t/how-do-i-install-cuda-11-0-on-windows-11-not-wsl2-windows-itself/192251" and reinstalled CUDA 11.2 for windows 10 in my windows 11 machine. Everything is still the same.
It imports but does not list my GPU as a physical device available.
When I try to install tensorflow on python 3.9 I get following error:
ERROR: Could not find a version that satisfies the requirement tensorflow (from versions: none)
ERROR: No matching distribution found for tensorflow
Is not there any tensorflow for 3.9?
What do you guys recommend?
Can I install other version of python beside the existing version?
Right now tensorflow does not have a build for python3.9
The latest one is for python3.8
You can check the build files at PyPI
https://pypi.org/project/tensorflow/#files
yes, you can install another version of python.
The original poster did not mention what type of computer or operating system he was using while attempting to install TensorFlow alongside Python 3.9. The error could be linked to working on a 64-bit Mac with the M1 chip (I recently experienced the same error described above while working on a Mac M1 in a Miniconda environment with Python 3.9.13). I solved the error by running
python3 -m pip install tensorflow-macos
from Terminal (in the Miniconda environment). TensorFlow installed normally alongside Python 3.9.13.
I do recommend installing Miniconda (or Anaconda as others have suggested), because it will allow you to easily create development environments with whatever version of Python modules or dependencies you require at the moment. See https://docs.conda.io/en/latest/miniconda.html. The larger Anaconda comes with a user-friendly 'Navigator' GUI which enables you to choose which environment is used to open a Jupyter notebook or other development environment, several of which come with Anaconda. See https://docs.anaconda.com/anaconda/install/
This is terrible with newer versions of Python that are not compatible with the machine learning module package.
So my approach is to keep the existing version 3.9 and the computer is using Anaconda to install a virtual environment with 3.7. When using vscode or pycharm, just remember to set it to that 3.7 Python environment.
I am trying to take an online course that requires me to install tensorflow. According to pyPI tensorflow only runs under 64 bit environments. I have 3.6 (64 bit) and 3.7 (64 bit) installed on a Windows 10 device running an i7 processor. pip install tensorflow-1.12.0-cp36-cp36m-win_amd64.whl returns a '...is not a supported wheel on this platform' under both 3.6 and 3.7 environments.
Interestingly, thought I have updated pip to 19.0.1 (at least it says it successfully did so), I am still getting the message that I need to upgrade my pip version.
This is what you are looking for.
Make sure you have updated pip first to enable wheel support:
pip install --upgrade pip
and then:
pip install C:/some-dir/tensorflow-1.12.0-cp36-cp36m-win_amd64.whl
You can also try using anaconda and install TensorFlow in an conda environment. This will capsulate your online course from the rest of your system and is quite a good habit when working with multiple projects.
I've searched around and non of the solutions seem to pertain to me, so here I am.
I installed anaconda 5.1 for python 3.6, I downloaded and installed 64-Bit(x86)Installer(551 MB)
from
https://www.anaconda.com/download/#linux
I followed the directions here
https://docs.anaconda.com/anaconda/install/linux
I had the install prepend the path and install microsoft VS code.
I then attempt to install the CPU only tensorflow using anaconda as suggested here
https://www.tensorflow.org/install/install_linux#InstallingAnaconda
I try to install the binary for python 3.6 CPU only
https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.6.0-cp36-cp36m-linux_x86_64.whl
I get the following error
tensorflow-1.6.0-cp36-cp36m-linux_x86_64.whl is not a supported wheel on this platform.
I am running a Ubuntu 16.04 VM on windows 10.
edit: when I run this command
pip install --ignore-installed --upgrade tfBinaryURL
outside of the tensorflow environment it worked.
2nd edit:
Additionally I explored my tensorflow environment in my anaconda3 folder, and I noticed it only has python 2.7, so when I tried to install the cpu only tensorflow while in the enviroment for python 2.7 it worked.
Was happy to know Tensorflow is made available for Windows and we don't have to use Docker.
I tried to install as per instructions but I get this error.
pip install --upgrade https://storage.googleapis.com/tensorflow/windows/cpu/tensorflow-0.12.0rc0-cp35-cp35m-win_amd64.whl
tensorflow-0.12.0rc0-cp35-cp35m-win_amd64.whl is not a supported wheel on this platform.
What does that error mean?
I am running latest version of Python.
python --version
Python 3.5.2
This is most likely to be a 64-bit versus 32-bit issue. The pre-built TensorFlow pip package is 64-bit only, but the default version of Python 3.5.2 on Python.org is 32-bit. You can download the 64-bit release from here (select one of the "Windows x86-64" options).
It's only available for Python 3.5.x not 3.6.
You can quickly create a 3.5 environment with:
conda create -n tensorflow python=3.5
You must have a 3.5.x version of Python. The 3.6 version won't work.
If you have installed an Anaconda that contains Python 3.6, you need to downgrade its Python to 3.5.2.
Open the Anaconda Prompt as administrator, and run:
conda install python=3.5.2
After the installation is finished, you can follow the rest of the steps on tensorflow website.
Do you have Python and Anaconda installed? I had a similar issue until I uninstalled Anaconda and then the setup was fine.
I did the following steps and it worked.(Anaconda 4.4 x64)
1- Go to Windows 10 command prompt (right click and Run as admin)
2- if activated the path, you can run conda anywhere, if not, should go to .../anaconda3/scripts and run conda command from there and do the following (the main trick was to change 35 to 36)
1- conda -n tensorflow python=3.5
2- activate tensorflow
3- pip install --upgrade https://storage.googleapis.com/tensorflow/windows/cpu/tensorflow-0.12.0rc0-cp36-cp36m-win_amd64.whl
issues fixed when i did the downgrading from 3.6 to 3.5 using the below
conda install python=3.5.2
There can be two reasons:
1) You are using 32-Bit python package. Tensorflow does not support 32 bit, only 64 fit.
Check in your system settings for this. If this is fine refer to second point..
2)You are using Python 3.7.
Python 3.7 isn't eventually officially supported by Python. It's still in beta testing,
and very much under active development.
Consider downgrading to a lower version of python. For now, stick with Python 3.6 or 3.5.