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In the reference implementations, there's usually a function to build a ffnn of arbitrary depth, consisting of a stack of Linear >> Relu >> Dropout. In practice the depth is always 1 in coref-hoi, but in earlier iterations of the model, which are more similar to our model here (since we aren't using attention or even necessarily BERT), using a small depth like 2 was common. This hard-codes a stack of 2. In brief tests this allows similar performance to the unstacked version with much smaller embedding sizes. The depth of the stack could be made into a hyperparameter. |
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| .. | ||
| __init__.py | ||
| coref_util.py | ||
| coref.py | ||
| entity_linker.py | ||
| multi_task.py | ||
| parser.py | ||
| spancat.py | ||
| tagger.py | ||
| textcat.py | ||
| tok2vec.py | ||