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Use cosine loss in Cloze multitask

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Matthw Honnibal 2019-10-06 19:23:46 +02:00
parent 157d3d769b
commit 9dbaea1ab4
1 changed files with 2 additions and 3 deletions
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spacy/pipeline/pipes.pyx
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@ -29,7 +29,7 @@ from .._ml import Tok2Vec, build_tagger_model, cosine, get_cossim_loss
from .._ml import build_text_classifier, build_simple_cnn_text_classifier
from .._ml import build_bow_text_classifier, build_nel_encoder
from .._ml import link_vectors_to_models, zero_init, flatten
from .._ml import masked_language_model, create_default_optimizer
from .._ml import masked_language_model, create_default_optimizer, get_cossim_loss
from ..errors import Errors, TempErrors, user_warning, Warnings
from .. import util
@ -880,8 +880,7 @@ class ClozeMultitask(Pipe):
# and look them up all at once. This prevents data copying.
ids = self.model.ops.flatten([doc.to_array(ID).ravel() for doc in docs])
target = vectors[ids]
gradient = (prediction - target) / prediction.shape[0]
loss = (gradient**2).sum()
loss, gradient = get_cossim_loss(prediction, target, ignore_zeros=True)
return float(loss), gradient
def update(self, docs, golds, drop=0., sgd=None, losses=None):