-
Notifications
You must be signed in to change notification settings - Fork 273
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
Does not seem to work for NLP pipeline from sklearn #164
Comments
Hi @dcshapiro, thanks for bringing this up! Yes, the first two parts are not yet handled.
|
@ksaur I would like to contribute by writing the code for tf-idf, if possible. |
Please! Having tf-idf will be fantastic. Can you please open as issue specific for tf-idf so that we can discuss on the implementation? I don't think it will be super trivial because, for example, PyTorch does not support string data types, so we will have to transform the input data into some numeric form (for one-hot encoding we had to do the same). |
Hi,
I tried to convert a model pipeline containing 3 steps:
[('vect', CountVectorizer()), ('tfidf', TfidfTransformer()), ('clf-svm', SGDClassifier())]
I get the following error:
MissingConverter: Unable to find converter for model type <class 'sklearn.feature_extraction.text.CountVectorizer'>.
It usually means the pipeline being converted contains a
transformer or a predictor with no corresponding converter implemented.
Please fill an issue at https://github.com/microsoft/hummingbird.
I'm guessing the system does not yet handle the first 2 parts...
The text was updated successfully, but these errors were encountered: