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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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| .. | ||
| converters | ||
| __init__.pxd | ||
| __init__.py | ||
| align.pyx | ||
| alignment.py | ||
| augment.py | ||
| batchers.py | ||
| callbacks.py | ||
| corpus.py | ||
| example.pxd | ||
| example.pyx | ||
| gold_io.pyx | ||
| initialize.py | ||
| iob_utils.py | ||
| loggers.py | ||
| loop.py | ||
| pretrain.py | ||