Can't install tensorflow using pip version 20, no versions found? - python

I am running a python code for which I need tensorflow 2.0, but when running pip install tensorflow (or pip3), I get the following error:
Could not find a version that satisfies the requirement tensorflow (from versions: )
No matching distribution found for tensorflow
I checked the tensorflow website and I'm running python version 3.7, so I tried the wheel they suggested for Windows 64-bit, CPU-only (https://storage.googleapis.com/tensorflow/windows/cpu/tensorflow_cpu-2.0.0-cp37-cp37m-win_amd64.whl) but I get the following error now:
ERROR: tensorflow_cpu-2.0.0-cp37-cp37m-win_amd64.whl is not a supported wheel on this platform.
My system's properties are below:
enter image description here
Any idea what the issue could be? Thanks!

TensorFlow requires 64-bit Python, your Python is 32-bit. Install 64-bit Python.
TensorFlow currently support Python up to 3.7 so do not install Python 3.8. Install 64-bit Python 3.7.

Related

how to find what is the latest version of python that pytorch

When I try
pip install torch, I get
ERROR: Could not find a version that satisfies the requirement torch (from versions: none)
ERROR: No matching distribution found for torch
Searching on here stackoverflow I find that the issue is I need an older verson of python, currently I'm using 3.11. That post said 3.8 but was written some time ago, so how do I find the latest version of python that will run pytorch? I couldn't find it easily on the PyTorch pages.
Pytorch supports Python 3.10.
Python 3.11 isn't fully supported yet.
You can always check torch archive or torch nightly to see if your desired version is supported.
While the Python3.11 is not officially supported as of now (Feb 11, 2023), if you are on Linux you can install the Python3.11 version of Pytorch 1.13.1:
wget https://download.pytorch.org/whl/cu117/torch-1.13.1%2Bcu117-cp311-cp311-linux_x86_64.whl
pip3 install torch-1.13.1+cu117-cp311-cp311-linux_x86_64.whl
Just note that this is not yet available on Windows or other major OSes.
If you want to give the new version a try on Other OSes such as Windows or Mac, you need to use the nighly builds.
For example for Windows inside powershell do :
wget https://download.pytorch.org/whl/nightly/cu117/torch-2.0.0.dev20230210%2Bcu117-cp311-cp311-win_amd64.whl -OutFile torch-2.0.0.dev20230210+cu117-cp311-cp311-win_amd64.whl
pip install torch-2.0.0.dev20230210+cu117-cp311-cp311-win_amd64.whl

Cannot install Tensorflow in Debian

I am trying to install Tensorflow using pyenv since the python 3.9.2 installed does not work with Tensorflow. I am running Debian OS 11.Everytime I run " pip install Tensorflow " it shows
Could not find a version that satisfies the requirement Tensorflow (from versions: none)
ERROR: No matching distribution found for Tensorflow.
I am using a 64bit OS with python 3.5.3 installed using Pyenv.
https://imgur.com/dRDWWAP
The process of installing tensor flow has changed over the years a little bit. A few years ago, they didn’t support versions of python greater than 3.6.4, causing users to downgrade their version of python. Now, there is something called tensorflow 2 which supports the higher versions of python. When you try to run the command pip install tensorflow, pip is trying to look for a version of tensorflow which is for the higher versions of python. Here are your two solutions:
You can install a version of tensorflow that corresponds to the version of python you have, so both are compatible. Here is the command: pip install tensorflow==1.5 for CPU edition, and pip install tensorflow-gpu==1.5 for GPU edition. With the older versions, the libraries were different for your CPU and GPU.
Your alternative solution is to install a higher version of python. With py versions 3.7-3.10, they use tensorflow 2 which can be installed with pip install tensorflow. This library for newer versions comes with support for both CPU and GPU in one package.

"Could not find a version that satisfied the requirement. No matching distribution found for tensorflow."

I have python 3.9.1 64 bit and pip 20.3.3. I am on windows 10.
I want to install tensorflow 1.15. But I get the error :
"Could not find a version that satisfied the requirement.
No matching distribution found for tensorflow."
Please help how to resolve this
tensor flow doesn't have support to python 3.9 yet
Step1 : Install python version 3.8 or below 3.9 from below link
https://www.python.org/downloads/release/python-380/
Step2: After installing python 3.8 go to environment variable and update path of python to 3.8
Now try install tensorflow of any version using
pip install tensorflow
tensorflow 1.15 requires Python 2.7, 3.4, 3.5, 3.6 or 3.7.
The latest tensorflow, currently 2.4.0 works with Python 3.6, 3.7 or 3.8.
Downgrade to a proper Python version (3.7 seems to be the common one) and decide if you need tensorflow 1.15.4 or later. Then install one of the versions:
pip install -U tensorflow==1.15.4
pip install -U tensorflow==2.4.0
pip install -U tensorflow

Tensorflow Python 3.7

Tensorflow version for Python 3.7
Any news about tensorflow update for python 3.7. When I try to install tensorflow inside my venv like:
pip install tensorflow
I got an error:
Could not find a version that satisfies the requirement tensorflow (from versions: )
No matching distribution found for tensorflow
Python 3.7 is now supported officially in TensorFlow 1.13.1:
Major Features and Improvements
TensorFlow Lite has moved from contrib to core. This means that
Python modules are under tf.lite and source code is now under
tensorflow/lite rather than tensorflow/contrib/lite.
TensorFlow GPU binaries are now built against CUDA 10 and TensorRT 5.0.
Support for Python3.7 on all operating systems.
Moved NCCL to core.
source
You can see the status of the move to 3.7 here: https://github.com/tensorflow/tensorflow/issues/20517
Firstly, you should download and set up the anaconda via anaconda and then open anaconda prompt and then follow these steps via TensorFlow. Fourthly, you should use 'pip install --ignore-installed --upgrade tensorflow==1.14.0' to install TensorFlow 1.14 on Conda Finally, you can use TensorFlow that is version 1.14 on python 3.7
Have a Great Time.
You need to install a 64-bit version of Python and 3.7 does not work with tensorflow right now, I suggest a downgrade to 3.6.x
I tried many versions of the tensorflow with python 3.7 and failed. But finally tensorflow version 1.14 worked.
I was having the same problem as you- I was using Python 3.7 32-bit on Windows 10 64-bit machine.
Since TensorFlow doesn't support 32-bit Python hence it said that "No matching distribution found for TensorFlow".
What worked for me is that I uninstalled the 32-bit Python version and installed the 64-bit Python version and pip install tensorflow worked immediately for downloading TensorFlow 2.2.0. Note that TensorFlow now supports till Python 3.8.
Check if you have the 32-bit version of Python. To check whether you have the 32-bit version or 64-bit version, type IDLE in the search bar and you will be able to tell which version it is.
Currently, for Windows users,
pip install https://storage.googleapis.com/tensorflow/windows/cpu/tensorflow_cpu-2.1.0-cp37-cp37m-win_amd64.whl
works with python_3.7(64-bit) and at least pip 19.0

Could not find a version that satisfies the requirement tensorflow>=1.7.0 (from versions: ) No matching distribution found for tensorflow>=1.7.0

I am trying to install tensorflow in my mac which is greater than version 1.7.0. While I am running the command:
pip3 install "tensorflow>=1.7.0"
I am getting this error:
Could not find a version that satisfies the requirement
tensorflow>=1.7.0 (from versions: ) No matching distribution found for
tensorflow>=1.7.0
Any help is highly appreciated.
The above is because TensorFlow is only created to run on Python versions 3.6, 2.7 and 3.5. As your Python version is 3.7, pip cannot find any TF version which is compatible.
Try degrading the Python version, or install Python version 3.6 separately and install TensorFlow in it by : pip3 install tensorflow.
Also, to manage different python versions you can use Anaconda environments. They are easy to use and have a separate conda package manager.

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