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Official tutorials use deprecated Classes

See original GitHub issue

📚 Documentation

Description Some of the tutorials in the documentation make use of Classes which were deprecated in version 0.7.0. For example, the code in Transformer Tutorial makes use of torchtext.data.Field and torchtext.data.Example and thus produces the following warnings:

/usr/local/lib/python3.6/dist-packages/torchtext/data/field.py:150: UserWarning: Field class will be retired in the 0.8.0 release and moved to torchtext.legacy. Please see 0.7.0 release notes for further information.
  warnings.warn('{} class will be retired in the 0.8.0 release and moved to torchtext.legacy. Please see 0.7.0 release notes for further information.'.format(self.__class__.__name__), UserWarning)
/usr/local/lib/python3.6/dist-packages/torchtext/data/example.py:78: UserWarning: Example class will be retired in the 0.8.0 release and moved to torchtext.legacy. Please see 0.7.0 release notes for further information.
  warnings.warn('Example class will be retired in the 0.8.0 release and moved to torchtext.legacy. Please see 0.7.0 release notes for further information.', UserWarning)

Since tutorials are the primary source of info for new comers, they should make use of the best available APIs and avoid deprecated methods.

Issue Analytics

State:
Created 3 years ago
Reactions:8
Comments:10 (5 by maintainers)

Top GitHub Comments

3reactions

pratikkejriwalcommented, Nov 9, 2020

I will make an update for the transformer tutorial ASAP. For the legacy code, we will fully retire in 0.8.0 release. By then, we will have a tutorial to show how to use the new building blocks for the end-to-end pipeline application.

With 0.8.0 release, I still cannot find a proper example which can serve as a guide to using collate_fn or any other alternate to Field. It would be really helpful, if anyone can link any updated example for a custom dataset.

2reactions

zhangguanheng66commented, Sep 7, 2020

I will make an update for the transformer tutorial ASAP. For the legacy code, we will fully retire in 0.8.0 release. By then, we will have a tutorial to show how to use the new building blocks for the end-to-end pipeline application.

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