From dc482287a1ca3295b3e714246384286e09c5e29e Mon Sep 17 00:00:00 2001
From: Mateusz Klimaszewski <mk.klimaszewski@gmail.com>
Date: Thu, 30 Jul 2020 09:32:04 +0200
Subject: [PATCH] Fix handling sentence embeddings.
---
combo/predict.py | 15 ++++++++++++---
1 file changed, 12 insertions(+), 3 deletions(-)
diff --git a/combo/predict.py b/combo/predict.py
index 35dbbee..2e5693f 100644
--- a/combo/predict.py
+++ b/combo/predict.py
@@ -79,7 +79,7 @@ class SemanticMultitaskPredictor(predictor.Predictor):
for prediction, instance in zip(predictions, instances):
tree = self._predictions_as_tree(prediction, instance)
if serialize:
- tree = tree.serialize()
+ tree = self._serialize(tree)
tree_json = util.sanitize(tree)
trees.append(collections.OrderedDict([
("tree", tree_json),
@@ -89,11 +89,13 @@ class SemanticMultitaskPredictor(predictor.Predictor):
@overrides
def predict_instance(self, instance: allen_data.Instance, serialize: bool = True) -> common.JsonDict:
tree = self.predict_instance_as_tree(instance)
+ sentence_embedding = tree.metadata.get("sentence_embedding", [])
if serialize:
- tree = tree.serialize()
+ tree = self._serialize(tree)
tree_json = util.sanitize(tree)
result = collections.OrderedDict([
("tree", tree_json),
+ ("sentence_embedding", sentence_embedding)
])
return result
@@ -118,6 +120,7 @@ class SemanticMultitaskPredictor(predictor.Predictor):
result = collections.OrderedDict([
("tree", tree_json),
])
+ result["sentence_embedding"] = tree.metadata.get("sentence_embedding", [])
return result
def predict_instance_as_tree(self, instance: allen_data.Instance) -> conllu.TokenList:
@@ -217,9 +220,15 @@ class SemanticMultitaskPredictor(predictor.Predictor):
raise NotImplementedError(f"Unknown field name {field_name}!")
if self._dataset_reader and "sent" in self._dataset_reader._targets:
- tree.metadata["sentence_embedding"] = str(predictions["sentence_embedding"])
+ tree.metadata["sentence_embedding"] = predictions["sentence_embedding"]
return tree
+ @staticmethod
+ def _serialize(tree: conllu.TokenList):
+ if "sentence_embedding" in tree.metadata:
+ tree.metadata["sentence_embedding"] = str(tree.metadata["sentence_embedding"])
+ return tree.serialize()
+
@classmethod
def with_spacy_tokenizer(cls, model: models.Model,
dataset_reader: allen_data.DatasetReader):
--
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