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Update textcat ensemble model

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This commit is contained in:
Matthew Honnibal 2021-01-19 02:53:02 +11:00
parent f50502dad7
commit c2a18e4fa3
1 changed files with 2 additions and 7 deletions
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spacy/ml/models/textcat.py
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@ -72,23 +72,20 @@ def build_text_classifier_v2(
attention_layer = ParametricAttention( attention_layer = ParametricAttention(
width width
) # TODO: benchmark performance difference of this layer ) # TODO: benchmark performance difference of this layer
maxout_layer = Maxout(nO=width, nI=width) maxout_layer = Maxout(nO=width, nI=width, dropout=0.0, normalize=True)
linear_layer = Linear(nO=nO, nI=width)
cnn_model = ( cnn_model = (
tok2vec tok2vec
>> list2ragged() >> list2ragged()
>> attention_layer >> attention_layer
>> reduce_sum() >> reduce_sum()
>> residual(maxout_layer) >> residual(maxout_layer)
>> linear_layer
>> Dropout(0.0)
) )
nO_double = nO * 2 if nO else None nO_double = nO * 2 if nO else None
if exclusive_classes: if exclusive_classes:
output_layer = Softmax(nO=nO, nI=nO_double) output_layer = Softmax(nO=nO, nI=nO_double)
else: else:
output_layer = Linear(nO=nO, nI=nO_double) >> Dropout(0.0) >> Logistic() output_layer = Linear(nO=nO, nI=nO_double) >> Logistic()
model = (linear_model | cnn_model) >> output_layer model = (linear_model | cnn_model) >> output_layer
model.set_ref("tok2vec", tok2vec) model.set_ref("tok2vec", tok2vec)
if model.has_dim("nO") is not False: if model.has_dim("nO") is not False:
@ -96,7 +93,6 @@ def build_text_classifier_v2(
model.set_ref("output_layer", linear_model.get_ref("output_layer")) model.set_ref("output_layer", linear_model.get_ref("output_layer"))
model.set_ref("attention_layer", attention_layer) model.set_ref("attention_layer", attention_layer)
model.set_ref("maxout_layer", maxout_layer) model.set_ref("maxout_layer", maxout_layer)
model.set_ref("linear_layer", linear_layer)
model.attrs["multi_label"] = not exclusive_classes model.attrs["multi_label"] = not exclusive_classes
model.init = init_ensemble_textcat model.init = init_ensemble_textcat
@ -108,7 +104,6 @@ def init_ensemble_textcat(model, X, Y) -> Model:
model.get_ref("attention_layer").set_dim("nO", tok2vec_width) model.get_ref("attention_layer").set_dim("nO", tok2vec_width)
model.get_ref("maxout_layer").set_dim("nO", tok2vec_width) model.get_ref("maxout_layer").set_dim("nO", tok2vec_width)
model.get_ref("maxout_layer").set_dim("nI", tok2vec_width) model.get_ref("maxout_layer").set_dim("nI", tok2vec_width)
model.get_ref("linear_layer").set_dim("nI", tok2vec_width)
init_chain(model, X, Y) init_chain(model, X, Y)
return model return model