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* Add training option to set annotations on update Add a `[training]` option called `set_annotations_on_update` to specify a list of components for which the predicted annotations should be set on `example.predicted` immediately after that component has been updated. The predicted annotations can be accessed by later components in the pipeline during the processing of the batch in the same `update` call. * Rename to annotates / annotating_components * Add test for `annotating_components` when training from config * Add documentation |
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| .. | ||
| __init__.py | ||
| test_analysis.py | ||
| test_annotates_on_update.py | ||
| test_attributeruler.py | ||
| test_entity_linker.py | ||
| test_entity_ruler.py | ||
| test_functions.py | ||
| test_initialize.py | ||
| test_lemmatizer.py | ||
| test_models.py | ||
| test_morphologizer.py | ||
| test_pipe_factories.py | ||
| test_pipe_methods.py | ||
| test_sentencizer.py | ||
| test_senter.py | ||
| test_tagger.py | ||
| test_textcat.py | ||
| test_tok2vec.py | ||