revert: use deduplicate_annotations() in test

pyproject.toml

@@ -24,9 +24,7 @@ classifiers = [
 
 [tool.poetry.dependencies]
 python = "^3.9"
-#pytorch-ie = ">=0.31.4,<0.32.0"
-# install from branch from https://github.com/ArneBinder/pytorch-ie/pull/436
-pytorch-ie = { git = "https://github.com/ArneBinder/pytorch-ie", branch = "document/deduplicate_annotations" }
+pytorch-ie = ">=0.31.2,<0.32.0"
 pytorch-lightning = "^2.1.0"
 torchmetrics = "^1"
 # >=4.35 because of BartModelWithDecoderPositionIds, <4.37 because of generation config

tests/taskmodules/test_pointer_network_for_end2end_re.py

@@ -568,9 +568,9 @@ def test_decode_with_add_reversed_relations():
     task_outputs = [task_encoding.targets for task_encoding in task_encodings]
     docs_with_predictions = taskmodule.decode(task_encodings, task_outputs)
     assert len(docs_with_predictions) == 1
-    doc_with_predictions: ExampleDocument = docs_with_predictions[0].deduplicate_annotations()
-    assert list(doc_with_predictions.entities.predictions) == list(doc_with_predictions.entities)
-    assert list(doc_with_predictions.relations.predictions) == list(doc_with_predictions.relations)
+    doc_with_predictions: ExampleDocument = docs_with_predictions[0]
+    assert set(doc_with_predictions.entities.predictions) == set(doc_with_predictions.entities)
+    assert set(doc_with_predictions.relations.predictions) == set(doc_with_predictions.relations)
 
 
 @pytest.fixture()