I have tried:
https://stackoverflow.com/questions/16769109/upgade-python-version-using-pip#:~:text=pip%20is%20designed%20to%20upgrade,but%20use%20an%20installer%20instead.&text=Basically%2C%20pip%20comes%20with%20python%20itself.
Install Python 3.8 kernel in Google Colaboratory
https://kegui.medium.com/how-to-install-mlfinlab-without-error-messages-896e2fb43c2f
None of the proposed solutions work.
I'm struggling to update colab python to 3.8. pip is designed to upgrade python packages and not to upgrade python itself. pip shouldn't try to upgrade python when you ask it to do so. Don't type pip install python but use an installer instead. Basically, pip comes with python itself.
MlFinlab has relaxed the hard versioning so you can now install on Colab :)
Related
Now that Google Colab is not supporting tensorflow 1.x is there a way to install it through e.g. pip and set up your environment in a similar fashion to what the old %tensorflow_version 1.x did? I really really dont want to rewamp all my code to TF 2
It seems that only tf2 is supported by Colab, but that's not true, you still can use pip to uninstall tf2 and install a specific version of tf1. !yes|pip uninstall tensorflow, !pip install tensorflow==1.15.5 Maybe you should install other dependencies. So use !pip install -r requirements.txt Attention! You must restart the runtime in order to use newly installed versions.
Since I'm moving away from pandas DataFrames to TensorFlow datasets, I'd like to use tensorflow-data-validation instead of the more traditional pandas-profiling when it comes to data exploration and validation.
However, pip install tensorflow-data-validation gives the following error:
ERROR: Could not find a version that satisfies the requirement tensorflow-data-validation (from versions: none)
ERROR: No matching distribution found for tensorflow-data-validation
What could be the problem? This old GitHub issue explains how this could be due to the Python version, but Apache Beam (on which tensorflow-data-validation presumably relies) is now fully compatible with Python 3, so it must be something else.
My environment is as follows:
Python 3.9.2
TensorFlow 2.6.0
Debian GNU/Linux 11 (bullseye)
pip 21.3
I got the same error when using Python 3.9. After downgrading to Python 3.8, pip install tensorflow-data-validation ran successfully.
Regarding your comment about Apache Beam, it looks like the Python SDK currently supports Python 3.8 (and earlier) but not yet Python 3.9.
My environment:
Python 3.8.10
TensorFlow 2.8.0
macOS Monterey (12.0.1)
pip 21.1.1
Try this
pip install --upgrade --force-reinstall tensorflow-data-validation[all]
It might be a version compatibility issue with tensorflow==2.6.0.
Try
pip install tensorflow-data-validation==1.3.0
I was able to install the tensorflow_data_validation library successfully, via the below command in my Google Colab file.
!pip install -U tensorflow \
tensorflow-data-validation \
apache-beam[gcp]
updated code to work with tensorflow 2.4 to get around issue
I'm trying to install Tensorflow 1.9 on a Raspberry Pi as it is a requirement of the code I want to run. It installs fine on my Macbook using pip install tensorflow==1.9.0, but on the Pi I get the error:
Could not find a version that satisfies the requirement tensorflow==1.9.0 (from versions: 0.11.0, 1.11.0, 1.12.0, 1.13.1, 1.14.0)
No matching distribution found for tensorflow==1.9.0
I'm using a Conda (miniconda3) environment with Python 3.6.
Would using Ubuntu Desktop instead of Raspberry Pi OS work maybe? Or is there perhaps a way to build it from https://github.com/tensorflow/tensorflow/tree/r1.9?
You need to install python version 3.6 or other compatible versions in conda. Tensorflow does not work on versions higher than 3.8 and has identified issues with some other versions. I recommend using python 3.6 through conda. You will also probably need to move the
libcrypto-1_1-x64.dll
libssl-1_1-x64.dll
files from anaconda3\Library\bin to anaconda3/DLLs. You can find more details about this issue if you run into it here.
Hope this answers your question!
To install Tensorflow on Raspberry Pi run:
sudo apt install libatlas-base-dev
and then
pip3 install tensorflow
You can also compilte TensorflowLite and use if you wish. The compile TensorflowLite on RPi refer this link
pip install --upgrade https://storage.googleapis.com/tensorflow/windows/cpu/tensorflow-0.12.1-cp35-cp35m-win_amd64.whl
In Anaconda3, Im trying to install the wheel but it is not working. On Windows. Using Python 3.6. There isnt a 3.6 wheel. I get this error:
tensorflow-0.12.1-cp35-cp35m-win_amd64.whl is not a supported wheel on this platform.
Use an alternative tensorflow wheel for Python 3.6:
pip install --ignore-installed --upgrade https://storage.googleapis.com/tensorflow/windows/gpu/tensorflow_gpu-1.2.0rc2-cp36-cp36m-win_amd64.whl
UPDATE: TensorFlow from version 1.2 forward officially supports Python 3.6
There is no wheel for Python 3.6 for currently not being supported on Windows yet.
As you can see here, Python 3.6 support on Windows is a work in progress.
The only alternative to use TensorFlow on Windows with Python 3.6 is to build it from source.
I also encountered the same problem.
Before they update TensorFlow.
You can try to download the historical version of his 2016-9-27 on this website.
Just change your python version to 3.5 and then retry installing tensorflow. Tensorflow is only compatible with Python 3.5
conda install python=3.5
and then
pip install --upgrade https://storage.googleapis.com/tensorflow/windows/cpu/tensorflow-0.12.1-cp35-cp35m-win_amd64.whl
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.