when I used "scale_utils.scale_solid_to_unit_box(solid)" process the model ,I found a problem

[guozhengyue]

Dear Author:
I want to scale the model to the same size before processing the model , after I use "scale_utiles.scale_solid_to_unit_box(solid)" to process the model, there is a bug when I use "pipeline\extract_brepnet_data_from_step.py"!

      "assert edge.topods_shape().Location().Transformation().Form() == gp_Identity
      AssertionError"
      
      and "scale the model to the same size" is a good step for train and test? Thanks for your any  opinion！
      I know that the features will be normalized when processing data, but the test results may become worse when the size of the test model is not in the training domain, so it is better to scale the model to the same size in advance?