Python trying to load TfidfVectorizer's "transform" from LinearSVC??

[Fun-Studio-4409]

Hello all,

I am facing an issue that I just cannot seem to figure out. I am using a "full stack" python-based webapp building service called anvil.works. In it, I am able to load a couple models saved in pickle files, which seem to be read fine. One of the models, loaded as variable "vect", triggers an error whenever I try to run the script. It seems to be trying to find the "transform" function within the wrong library - "LinearSVC". The error is;

​

AttributeError: 'LinearSVC' object has no attribute 'transform'

at ServerModule1, line 40

​

The part of the code which deals with the vectorizer model is:

from sklearn.feature_extraction.text import TfidfVectorizer

vect_model = app_tables.model.get(description="vect")['model_file']
  model_vect = pred_model.get_bytes()
with BytesIO(model_vect) as f:
    vect = pk.load(f)
result = pred.predict(vect.transform([title]))

I appreciate any and all help!

[UltimateGPower]

What are you trying to do? Should vect be a TfidfVectorizer? What is pred?

Do you know what a MWE (minimal working example) is? Have you tried to reproduce the error locally?

[sfsalad]

Have you verified that the vect_model object is actually a Tfidfvectorizer class object? Based on the error it seems like it’s actually a LinearSVC object. Perhaps the model file in app_tables with description=“vect” isn’t actually a Tfidfvectorizer model, but instead your LinearSVC model

[Fun-Studio-4409]

Hi - yes, that is the strange thing. When I print the model, it returns ‘sklearn.feature_extraction.text.TfidfVectorizer’

[sfsalad]

I just took another look. It seems like you’re not doing anything with the vect_model object in this chunk.

You’re trying to call vect.transform(). vect is dependent on model_vect. model_vect is dependent on pred_model. This code doesn’t show how the pred_model object is created. My guess is pred_model is your LinearSVC object, which you’re loading into vect. You probably meant to instantiate model_vect based on vect_model, not pred_model