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OCTIS: Comparing Topic Models is Simple! A python package to optimize and evaluate topic models (accepted at EACL2021 demo track)

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Dependency incompatibility

mitramir55 opened this issue · comments

commented
  • OCTIS version: octis 1.12.0
  • Python version: 3.10.11
  • Operating System: Linux (Colab notebook)

Description

I'm trying to install Octis and import its modules.

What I Did

First, I installed Octis with pip install octis. Then I see the following error in the installation process:

Installing collected packages: scikit-learn
  Attempting uninstall: scikit-learn
    Found existing installation: scikit-learn 1.2.2
    Uninstalling scikit-learn-1.2.2:
      Successfully uninstalled scikit-learn-1.2.2
ERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.
yellowbrick 1.5 requires scikit-learn>=1.0.0, but you have scikit-learn 0.24.2 which is incompatible.
imbalanced-learn 0.10.1 requires scikit-learn>=1.0.2, but you have scikit-learn 0.24.2 which is incompatible.
Successfully installed scikit-learn-0.24.2

Afterwards, I have issues importing the Coherence module and I receive the following error:
ImportError: numpy.core.multiarray failed to import

I tried installing the two packages that cause the issue myself; however, I faced some other issues revolving around the version of Numpy and Python.

The issue happens when running the notebook you've provided as an example.

commented

Same issue

commented

Hi,
I think the issue is fixed from version 1.12.1. The package will be released in less than an hour. Let me know if you still encounter the same problem. Thanks,

Silvia