Shahnawax
commented
1 year ago @mridup we did not manage to reproduce the reported issue, (tested with Python versions 3.9 and 3.10). Could you (re)try to create a clean Python or Conda virtual environment and install the requirements in it using the following command? Try using Python versions 3.9 or 3.10.
pip install -r requirements.txt --upgrade-strategy only-if-needed
If the issue is still not resolved, kindly share the list of the installed packages along there versions?
You can get it using pip list command (launched in your virtual environment).
mridup
The requirements.txt has conflicting package version numbers once it is iinstalled. E.g. ERROR: numba 0.56.4 has requirement numpy<1.24,>=1.18, but you'll have numpy 1.24.2 which is incompatible. ERROR: onnx 1.13.0 has requirement protobuf<4,>=3.20.2, but you'll have protobuf 3.19.6 which is incompatible. ERROR: skl2onnx 1.13 has requirement scikit-learn<=1.1.1, but you'll have scikit-learn 1.2.1 which is incompatible.
If we correct the above versions, then more conflicting versions emerge.
Do you have a fixed or frozen requirements.txt file which works for the training phase as required in the HAR example?