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"import tensorflow" results in error: No module named 'tensorflow.python.eager.polymorphic_function' (Python in Jupyter Lab)

Python 3.9.12.
Windows 10.
jupyterlab 3.3.2.
Import tensorflow
When I try to import Tensorflow, I get the following 'tensorflow.python.eager.polymorphic_function' error.
---------------------------------------------------------------------------
ModuleNotFoundError Traceback (most recent call last)
Cell In [44], line 1
----> 1 import tensorflow
File ~\OD13\TFODCourse\tfod13\lib\site-packages\tensorflow\__init__.py:45
42 from tensorflow.python import tf2 as _tf2
43 _tf2.enable()
---> 45 from ._api.v2 import __internal__
46 from ._api.v2 import __operators__
47 from ._api.v2 import audio
File ~\OD13\TFODCourse\tfod13\lib\site-packages\tensorflow\_api\v2\__internal__\__init__.py:14
12 from . import eager_context
13 from . import feature_column
---> 14 from . import function
15 from . import graph_util
16 from . import mixed_precision
File ~\OD13\TFODCourse\tfod13\lib\site-packages\tensorflow\_api\v2\__internal__\function\__init__.py:8
3 """Public API for tf.__internal__.function namespace.
4 """
6 import sys as _sys
----> 8 from tensorflow.python.eager.polymorphic_function.polymorphic_function import Function
9 from tensorflow.python.eager.polymorphic_function.quarantine import defun_with_attributes
ModuleNotFoundError: No module named 'tensorflow.python.eager.polymorphic_function'
My workflow is based on this tutorial: https://www.youtube.com/watch?v=yqkISICHH-U
I found the following answer, but I'm not understanding how to implement the TFLite Authoring Tool to solve this problem:
https://stackoverflow.com/questions/74177865/tensorflow-python-eager-polymorphic-function-no-module-error-on-imports

To answer my own question:
I created a conda environment and installed an older version of Python (3.7) in it and that seems to have fixed the problem.
I found these links to be helpful:
How to downgrade the Python Version from 3.8 to 3.7 on windows?
conda install downgrade python version
Jupyter Notebook - Cannot Connect to Kernel
How to find the version of jupyter notebook from within the notebook
pip command to downgrade jupyter notebook
How to check python anaconda version installed on Windows 10 PC?
https://towardsdatascience.com/get-your-conda-environment-to-show-in-jupyter-notebooks-the-easy-way-17010b76e874

Cannot import name 'Imputer' from 'sklearn.preprocessing' from pandas_ml

I am working on a project for my master and I was trying to get some stats on my calculations. I found a very cool tool to do this, called panda_ml, but when I import it in my cell on jupyter like this:
from pandas_ml import *
It gives me this output error:
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-118-93009f7254d4> in <module>
3 from sklearn import *
4 from matplotlib.colors import LogNorm
----> 5 from pandas_ml import *
6 import math
7
~/anaconda3/envs/Lab1_B/lib/python3.7/site-packages/pandas_ml/__init__.py in <module>
1 #!/usr/bin/env python
2
----> 3 from pandas_ml.core import ModelFrame, ModelSeries # noqa
4 from pandas_ml.tools import info # noqa
5 from pandas_ml.version import version as __version__ # noqa
~/anaconda3/envs/Lab1_B/lib/python3.7/site-packages/pandas_ml/core/__init__.py in <module>
1 #!/usr/bin/env python
2
----> 3 from pandas_ml.core.frame import ModelFrame # noqa
4 from pandas_ml.core.series import ModelSeries # noqa
~/anaconda3/envs/Lab1_B/lib/python3.7/site-packages/pandas_ml/core/frame.py in <module>
8
9 import pandas_ml.imbaccessors as imbaccessors
---> 10 import pandas_ml.skaccessors as skaccessors
11 import pandas_ml.smaccessors as smaccessors
12 import pandas_ml.snsaccessors as snsaccessors
~/anaconda3/envs/Lab1_B/lib/python3.7/site-packages/pandas_ml/skaccessors/__init__.py in <module>
17 from pandas_ml.skaccessors.neighbors import NeighborsMethods # noqa
18 from pandas_ml.skaccessors.pipeline import PipelineMethods # noqa
---> 19 from pandas_ml.skaccessors.preprocessing import PreprocessingMethods # noqa
20 from pandas_ml.skaccessors.svm import SVMMethods # noqa
~/anaconda3/envs/Lab1_B/lib/python3.7/site-packages/pandas_ml/skaccessors/preprocessing.py in <module>
11 _keep_col_classes = [pp.Binarizer,
12 pp.FunctionTransformer,
---> 13 pp.Imputer,
14 pp.KernelCenterer,
15 pp.LabelEncoder,
AttributeError: module 'sklearn.preprocessing' has no attribute 'Imputer'
I am using Conda, I have my own env with all the packages, I have tried to install older versions of sklearn and pandas_ml but it did not solve the problem. I've searching around but it seems that no one had ever this problem...Do you have any suggestion?

You have to uninstall properly and downgrading will work.
pip uninstall -y scikit-learn
pip uninstall -y pandas
pip uninstall -y pandas_ml
pip install scikit-learn==0.21.1
pip install pandas==0.24.2
pip install pandas_ml
Then import
from pandas_ml import *
Tested in Python 3.8.2

I had scikit-learn version 0.22.1 installed recently and had a similar problem. Then I tried your solution under Python 3.7.2, maintained the versions for Pandas v0.25.1 and Pandas ML v0.6.1 and it work like a charm!. I wonder when would be it safe to turn to a newer version of scikit-learn

from sklearn.impute import SimpleImputer
imp = SimpleImputer(missing_values=np.nan, copy=False, strategy="mean", )
No axis value is needed anymore

No module named 'sklearn.neighbors._base'

I have recently installed imblearn package in jupyter using
!pip show imbalanced-learn
But I am not able to import this package.
from tensorflow.keras import backend
from imblearn.over_sampling import SMOTE
I get the following error
---------------------------------------------------------------------------
ModuleNotFoundError Traceback (most recent call last)
<ipython-input-20-f19c5a0e54af> in <module>
1 # from sklearn.utils import resample
2 from tensorflow.keras import backend
----> 3 from imblearn.over_sampling import SMOTE
4
5
~/.virtualenvs/p3/lib/python3.6/site-packages/imblearn/__init__.py in <module>
32 Module which allowing to create pipeline with scikit-learn estimators.
33 """
---> 34 from . import combine
35 from . import ensemble
36 from . import exceptions
~/.virtualenvs/p3/lib/python3.6/site-packages/imblearn/combine/__init__.py in <module>
3 """
4
----> 5 from ._smote_enn import SMOTEENN
6 from ._smote_tomek import SMOTETomek
7
~/.virtualenvs/p3/lib/python3.6/site-packages/imblearn/combine/_smote_enn.py in <module>
8 from sklearn.utils import check_X_y
9
---> 10 from ..base import BaseSampler
11 from ..over_sampling import SMOTE
12 from ..over_sampling.base import BaseOverSampler
~/.virtualenvs/p3/lib/python3.6/site-packages/imblearn/base.py in <module>
14 from sklearn.utils.multiclass import check_classification_targets
15
---> 16 from .utils import check_sampling_strategy, check_target_type
17
18
~/.virtualenvs/p3/lib/python3.6/site-packages/imblearn/utils/__init__.py in <module>
5 from ._docstring import Substitution
6
----> 7 from ._validation import check_neighbors_object
8 from ._validation import check_target_type
9 from ._validation import check_sampling_strategy
~/.virtualenvs/p3/lib/python3.6/site-packages/imblearn/utils/_validation.py in <module>
11
12 from sklearn.base import clone
---> 13 from sklearn.neighbors._base import KNeighborsMixin
14 from sklearn.neighbors import NearestNeighbors
15 from sklearn.utils.multiclass import type_of_target
ModuleNotFoundError: No module named 'sklearn.neighbors._base'
Other packages in the environment
numpy==1.16.2
pandas==0.24.2
paramiko==2.1.1
matplotlib==2.2.4
scikit-learn==0.22.1
Keras==2.2.4
tensorflow==1.12.0
tensorboard==1.12.0
tensorflow-hub==0.4.0
xlrd==1.2.0
flask==1.0.2
wtforms==2.2.1
bs4==0.0.1
gensim==3.8.1
spacy==2.2.3
nltk==3.4.5
wordcloud==1.6.0
pymongo==3.10.1
imbalanced-learn==0.6.1
I checked the sklearn package, it contains base module, not _base. But modifying it may not be the right solution. Any other solution to fix this issue.

If in case you want to persist with the latest version of scikit-learn, add the following code to your script or execute the following code in your environment before installing imblearn
import sklearn.neighbors._base
sys.modules['sklearn.neighbors.base'] = sklearn.neighbors._base
This has to be after
pip install sklearn
or in a notebook environment:
!pip install sklearn
This problem stems from the fact that certain modules are named with an underscore in the newer scikit-learn releases

Previous sklearn.neighbors.base has been renamed to sklearn.neighbors._base in version 0.22.1.
You have probably a version of scikit-learn older than that.
Installing the latest release solves the problem:
pip install -U scikit-learn
or
pip install scikit-learn==0.22.1

I had a similar problem trying to import SMOTE from imblearn.over_sampling and my version of scikit-learn was up to date (0.24.1). What worked for me was:
First I downgraded my scikit learn version to 0.22.1 using
pip install scikit-learn==0.22.1
Next, I updated the imbalanced-learn package using:
pip install -U imbalanced-learn
That uninstalled scikit-learn-0.22.1, installed the updated version (scikit-learn-0.24.1), and updated the imbalanced-learn package. Everything worked fine thereafter.

If it is in a particular env, you must copy the _base file or base file to the env from package file.
I had the same problem in my tensorflow env. I just copied _base and base file to my tensorflow env and worked.

Pip not installing package properly

So I am trying to get hmmlearn working in Jupyter, and I have come across an error while installing Hmmlearn using pip. I have tried this solution, but it didn't work.
It seems to me that pip does install the _hmmc file, but it does so incorrect. instead it has the name
_hmmc.cp35-win_amd64
and the file extesion is .PYD, instead of .c
When I run the code to import it, I get this error :
ImportError Traceback (most recent call last)
<ipython-input-1-dee84c3d5ff9> in <module>()
7 import os
8 from pyAudioAnalysis import audioBasicIO as aB
----> 9 from pyAudioAnalysis import audioAnalysis as aA
C:\Users\gover_000\Documents\GitHub\Emotion-Recognition-Prototype\pyAudioAnalysis\audioAnalysis.py in <module>()
15 import audioFeatureExtraction as aF
16 import audioTrainTest as aT
---> 17 import audioSegmentation as aS
18 import audioVisualization as aV
19 import audioBasicIO
C:\Users\gover_000\Documents\GitHub\Emotion-Recognition-Prototype\pyAudioAnalysis\audioSegmentation.py in <module>()
16 import sklearn
17 import sklearn.cluster
---> 18 import hmmlearn.hmm
19 import cPickle
20 import glob
C:\Users\gover_000\Anaconda3\envs\python2\lib\site-packages\hmmlearn\hmm.py in <module>()
19 from sklearn.utils import check_random_state
20
---> 21 from .base import _BaseHMM
22 from .utils import iter_from_X_lengths, normalize
23
C:\Users\gover_000\Anaconda3\envs\python2\lib\site-packages\hmmlearn\base.py in <module>()
11 from sklearn.utils.validation import check_is_fitted
12
---> 13 from . import _hmmc
14 from .utils import normalize, log_normalize, iter_from_X_lengths
15
ImportError: cannot import name _hmmc
I don't know why pip just doesn't install it correctly, even when I tried to use --no-cache-dir
Edit: So i figured out what the problem was. my active python enviroment was python 3.5, as i was manually transferring the installed files to my enviroment, it failed because i had the wrong version.
I had to change my active python enviroment: using activate <my_enviroment name>
after that i could just use pip to install it again and it worked this time.

Looking at your error message I guess that you have downloaded the hmmlearn package from GIT. Have you tried using a wheel (*.whl) file instead? You can download one from here. Check out which version fits your python installation.
Then use:
pip install <the_wheel_that_corresponds_to_your_python_version>.whl
Hope it helps.

So i figured out what the problem was. my active python enviroment was python 3.5, as i was manually transferring the installed files to my enviroment, it failed because i had the wrong version. I had to change my active python enviroment: using activate <my_enviroment_name> after that i could just use pip to install it again and it worked this time.

not sure if it could be helpful to anyone but I installed hmmlearn as follows in my Jupyter Lab:
import sys
!{sys.executable} -m pip install hmmlearn

ImportError: cannot import name murmurhash3_32

I am trying to use the sklearn.qda package in python. I have installed it successfully but when Itry to import it I get the error message below. Can anybody tell me what should I do to fix this?
In [3]: from sklearn.qda import QDA
---------------------------------------------------------------------------
ImportError Traceback (most recent call last)
<ipython-input-3-7d7abf937d66> in <module>()
----> 1 from sklearn.qda import QDA
/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/sklearn/qda.py in <module>()
12
13 from .base import BaseEstimator, ClassifierMixin
---> 14 from .utils.fixes import unique
15 from .utils import check_arrays, array2d
16
/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/sklearn/utils/__init__.py in <module>()
7 import warnings
8
----> 9 from .murmurhash import murmurhash3_32
10 from .validation import (as_float_array, check_arrays, safe_asarray,
11 assert_all_finite, array2d, atleast2d_or_csc,
ImportError: cannot import name murmurhash3_32

I had the same problem, I run:
sudo pip install -U scikit-learn
and now everything is working fine

I started a new shell and this problem went away

I faced the similar situation of getting mumurhash error while installing sklearn.preprocessing library.
I upgraded numpy version from 1.13 to 1.15
using
pip install --upgrade numpy
After this, I was able to import the sklearn library.

I fixed this by upgrading murmurhash to 1.0.5.

I faced a similar problem, so there are mainly two solutions
Either run it in administrator mode and install all the libraries and run in admin mode. Something that I would not recommend
Use virtualenv to install the libraries again and run your command in the virtualenv. This worked for me.
Hope this helps