Can't Install latest Tensorflow versions - python

I tried installing Tensorflow using the pip install tensorflow, but I got this error code instead. I'll really use y'alls help
ERROR: Wheel 'termcolor' located at C:\users\user\appdata\local\pip\cache\wheels\b6\0d\90\0d1bbd99855f99cb2f6c2e5ff96f8023fad8ec367695f7d72d\termcolor-1.1.0-py3-none-any.whl is invalid.

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ImportError: cannot import name 'DecisionBoundaryDisplay' from 'sklearn.inspection'

I imported sklearn DecisionBoundaryDisplay via the below command in my Google Colab file.
from sklearn.inspection import DecisionBoundaryDisplay
And I'm getting the following error.
ImportError: cannot import name 'DecisionBoundaryDisplay' from 'sklearn.inspection'
I even installed the following packages & also tried by restarting my runtime but still I'm getting the error.
!pip install --upgrade scikit-learn
!pip install scipy
!pip3 install -U scikit-learn scipy matplotlib
How to fix this issue?
what worked for me was installing scikit learn 1.1.0, i had version 1.0.2 before and got the same error you're encountering.
pip install -U scikit-learn --user
Hope it helps.
It seems DecisionBoundaryDisplay is a new feature and it is currently in an unstable development version. To use it, you need to install the nightly build.

Cannot seem to download SimpleElastix: file.whl wheel not recognized/import not recognized

I'm trying to install SimpleElastix for python. As far as I can tell, you can either download a whl file from https://simpleelastix.github.io/#download
or simply pip install as shown here: https://pypi.org/project/SimpleITK-SimpleElastix/
I first tried downloading it and am trying to install SimpleITK-0.9.1rc1.dev163-cp34-cp34m-win_amd64.whl that I have saved to drive.
I am using the following (pip has been updated):
(hids3) C:\Windows\system32>python --version
Python 3.8.0
(hids3) C:\Windows\system32>pip --version
pip 22.0.4 from C:\Users\kated\anaconda3\envs\hids3\lib\site-packages\pip (python 3.8)
I try to run pip install SimpleITK-0.9.1rc1.dev163-cp34-cp34m-win_amd64.whl
and get the following error:
ERROR: SimpleITK-0.9.1rc1.dev163-cp34-cp34m-win_amd64.whl is not a supported wheel on this platform.
According to Error "filename.whl is not a supported wheel on this platform" , this could be caused by a downloading the .whl file for a wrong python version. I would expect python 3.8 to support a CPython 3.4 version or am I wrong for assuming this?
Alternative way to download SimpleElastix: https://pypi.org/project/SimpleITK-SimpleElastix/
I also tried running
pip install --user SimpleITK-SImpleElastix
in the terminal, which worked, but when I run
import SimpleITK as sitk
sitk.Elastix()
I get
AttributeError: module 'SimpleITK' has no attribute 'Elastix'
Anyone have any idea what I'm doing wrong in either case?

module 'keras.api._v2.keras.experimental' has no attribute 'PeepholeLSTMCell'

I tried to install tensorflow_federated in google colab. I used
pip install --quiet tensorflow-federated-nightly
import tensorflow-federated as tff
and it worked. but now when I try to import it get this error:
AttributeError: module 'keras.api._v2.keras.experimental' has no attribute 'PeepholeLSTMCell'
I don't know why I get this error, because I didn't have any problem before.
I also used the following code to install tensorflow-federated:
pip install --upgrade tensorflow-federated-nightly
but I get the same error.
How do I fix it?
My versions are:
tensorflow 2.8.0,
keras 2.8.0,
tensorflow-federated-nightly 0.19.0.dev20220218
To use TensorFlow Federated with TensorFlow 2.8.0, please try the newly released version of TFF 0.20.0 pypi, github.
The tensorflow-federated-nightly package depends on the nightly versions of TensorFlow (tf-nightly), Keras (keras-nightly) and so on.

Can't install tensorflow on ubuntu 20.04.3 Python 3.6.15 pip 21.2.4

I have been around the mulberry bush for a few days trying to get tensorflow installed on an Ubuntu system. My specifications are;
Ubuntu: 20.04.3
Python (virtual environment): 3.6.15
Pip: 21.2.4
Tensorflow version wanted: 1.13.1
Tensorflow version will take: anything at this point
I followed a number of answers on the web. Got a compatible version of Python. Got the latest pip....
When I use the command;
pip3 install tensorflow==1.13.1
I get;
ERROR: Could not find a version that satisfies the requirement tensorflow==1.13.1 (from versions: none)
ERROR: No matching distribution found for tensorflow==1.13.1
when I do a pip_search on tensorflow, it shows tensorflow 2.6.0.
But when I do;
pip3 install tensorflow==2.6.0
I get the same error.
when I use the --upgrade switch to pip, I get the same error. I tried to install from a wheel file, but the file was incompatible on my system.
Any help is appreciated.
As per documentation of Tensorflow, version 1's final release that can be downloaded/installed is 1.15. Below this version are deprecated and no longer available to use in development.
Read it about here

How to resolve the ERROR: Failed building wheel for h5py

I am working on windows 7.
Currently I have tensorflow 2.4.1 and keras 2.3.1 installed in my laptop.
I have trained a model on coalab and saved t on my laptop. When I try to load it it gives error :
ValueError: Unknown layer: Functional
It may be due to difference in version of Keras. Google colab uses Keras 2.4.3.
When I tried to install keras 2.4.3 using command:
pip install Keras==2.4.3
I got the following error:
Loading library to get version: hdf5.dll
error: Unable to load dependency HDF5, make sure HDF5 is installed properly
error: Could not find module 'hdf5.dll' (or one of its dependencies). Try using the full path with constructor syntax.
ERROR: Failed building wheel for h5py
Failed to build h5py
ERROR: Could not build wheels for h5py which use PEP 517 and cannot be installed directly*.
I tried to install h5py as well but it gives an error too!
Please let me know if anyone has a solution for this.
while : h5py which use PEP 517 and cannot be installed directly, try this
pip install --upgrade pip setuptools wheel
or check the python version , for example h5py 2.6 only supports up to python 3.6 , look at this.

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