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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 |