Bugfix #825 - Update paraphrase_mining

sentence_transformers/__init__.py

@@ -1,4 +1,4 @@
-__version__ = "1.0.2"
+__version__ = "1.0.3"
 __DOWNLOAD_SERVER__ = 'http://sbert.net/models/'
 from .datasets import SentencesDataset, ParallelSentencesDataset
 from .LoggingHandler import LoggingHandler

sentence_transformers/util.py

@@ -73,6 +73,7 @@ def paraphrase_mining(model,
                       sentences: List[str],
                       show_progress_bar: bool = False,
                       batch_size:int = 32,
+                      *args,
                       **kwargs):
     """
     Given a list of sentences / texts, this function performs paraphrase mining. It compares all sentences against all
@@ -93,7 +94,7 @@ def paraphrase_mining(model,
     # Compute embedding for the sentences
     embeddings = model.encode(sentences, show_progress_bar=show_progress_bar, batch_size=batch_size, convert_to_tensor=True)
 
-    return paraphrase_mining_embeddings(embeddings, **kwargs)
+    return paraphrase_mining_embeddings(embeddings, *args, **kwargs)
 
 
 def paraphrase_mining_embeddings(embeddings: Tensor,

setup.py

@@ -7,15 +7,15 @@
 
 setup(
     name="sentence-transformers",
-    version="1.0.2",
+    version="1.0.3",
     author="Nils Reimers",
     author_email="[email protected]",
     description="Sentence Embeddings using BERT / RoBERTa / XLM-R",
     long_description=readme,
     long_description_content_type="text/markdown",
     license="Apache License 2.0",
     url="https://github.com/UKPLab/sentence-transformers",
-    download_url="https://github.com/UKPLab/sentence-transformers/archive/v1.0.2.zip",
+    download_url="https://github.com/UKPLab/sentence-transformers/archive/v1.0.3.zip",
     packages=find_packages(),
     install_requires=[
         'transformers>=3.1.0,<5.0.0',

tests/test_evaluator.py

@@ -34,8 +34,7 @@ def test_BinaryClassificationEvaluator_find_best_accuracy_and_threshold(self):
         assert np.abs(max_acc - sklearn_acc) < 1e-6
 
     def test_LabelAccuracyEvaluator(self):
-
-
+        """Tests that the LabelAccuracyEvaluator can be loaded correctly"""
         model = SentenceTransformer('paraphrase-distilroberta-base-v1')
 
         nli_dataset_path = 'datasets/AllNLI.tsv.gz'
@@ -59,3 +58,11 @@ def test_LabelAccuracyEvaluator(self):
         evaluator = evaluation.LabelAccuracyEvaluator(dev_dataloader, softmax_model=train_loss)
         acc = evaluator(model)
         assert acc > 0.2
+
+    def test_ParaphraseMiningEvaluator(self):
+        """Tests that the ParaphraseMiningEvaluator can be loaded"""
+        model = SentenceTransformer('paraphrase-distilroberta-base-v1')
+        sentences = {0: "Hello World", 1: "Hello World!", 2: "The cat is on the table", 3: "On the table the cat is"}
+        data_eval = evaluation.ParaphraseMiningEvaluator(sentences, [(0,1), (2,3)])
+        score = data_eval(model)
+        assert score > 0.99