How to do multi-label classification with TorchText?

wgpubs · January 27, 2018, 7:28pm

Hey @hiromi! I remember ya from fastai.

Here is code I’m using for the toxic comp. Appreciate any feedback and the good and ugly of it and what can be improved. Hope this helps:

gist.github.com

https://gist.github.com/ohmeow/5b3543a5115040001fce59a105ac4269

toxic.py

class TextMultiLabelDataset(torchtext.data.Dataset):
    def __init__(self, df, tt_text_field, tt_label_field, txt_col, lbl_cols, **kwargs):
        # torchtext Field objects
        fields = [('text', tt_text_field)]
        for l in lbl_cols: fields.append((l, tt_label_field))
            
        is_test = False if lbl_cols[0] in df.columns else True
        n_labels = len(lbl_cols)
        
        examples = []

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