diff options
Diffstat (limited to 'stanza/models/classifiers/cnn_classifier.py')
| -rw-r--r-- | stanza/models/classifiers/cnn_classifier.py | 4 |
1 files changed, 4 insertions, 0 deletions
diff --git a/stanza/models/classifiers/cnn_classifier.py b/stanza/models/classifiers/cnn_classifier.py index fa5160bf..9cb1bd45 100644 --- a/stanza/models/classifiers/cnn_classifier.py +++ b/stanza/models/classifiers/cnn_classifier.py @@ -112,6 +112,8 @@ class CNNClassifier(nn.Module): self.extra_vocab = list(extra_vocab) self.extra_vocab_map = { word: i for i, word in enumerate(self.extra_vocab) } # TODO: possibly add regularization specifically on the extra embedding? + # note: it looks like a bug that this doesn't add UNK or PAD, but actually + # those are expected to already be the first two entries self.extra_embedding = nn.Embedding(num_embeddings = len(extra_vocab), embedding_dim = self.config.extra_wordvec_dim, max_norm = self.config.extra_wordvec_max_norm, @@ -367,6 +369,8 @@ class CNNClassifier(nn.Module): for fc in self.fc_layers[:-1]: previous_layer = self.dropout(F.relu(fc(previous_layer))) out = self.fc_layers[-1](previous_layer) + # note that we return the raw logits rather than use a softmax + # https://discuss.pytorch.org/t/multi-class-cross-entropy-loss-and-softmax-in-pytorch/24920/4 return out |