simplify unit test

test/components/readers/test_extractive.py

@@ -91,7 +91,7 @@ def forward(self, input_ids, attention_mask, *args, **kwargs):
     [
         Document(content="Angela Merkel was the chancellor of Germany."),
         Document(content="Olaf Scholz is the chancellor of Germany"),
-        Document(content="Jerry is the head of the department."),
+        Document(content="Jerry is the head of the department.", meta={"page_number": 3}),
     ]
 ] * 2
 
@@ -386,49 +386,8 @@ def test_nest_answers(mock_reader: ExtractiveReader):
             assert answer.query == query
             assert answer.document == doc
             assert answer.score == pytest.approx(score)
-        no_answer = answers[-1]
-        assert no_answer.query == query
-        assert no_answer.document is None
-        assert no_answer.score == pytest.approx(expected_no_answer)
-
-
-def test_nest_answers_with_page_numbers(mock_reader: ExtractiveReader):
-    example_documents = [
-        Document(content="Angela Merkel was the chancellor of Germany.", meta={"page_number": 1}),
-        Document(content="Olaf Scholz is the chancellor of Germany", meta={"page_number": 2}),
-        Document(content="Jerry is the head of the department.", meta={"page_number": 3}),
-    ]
-    start = list(range(5))
-    end = [i + 5 for i in start]
-    start = [start] * 6  # type: ignore
-    end = [end] * 6  # type: ignore
-    probabilities = torch.arange(5).unsqueeze(0) / 5 + torch.arange(6).unsqueeze(-1) / 25
-    query_ids = [0] * 3 + [1] * 3
-    document_ids = list(range(3)) * 2
-    nested_answers = mock_reader._nest_answers(  # type: ignore
-        start=start,
-        end=end,
-        probabilities=probabilities,
-        flattened_documents=example_documents,
-        queries=example_queries,
-        answers_per_seq=5,
-        top_k=3,
-        score_threshold=None,
-        query_ids=query_ids,
-        document_ids=document_ids,
-        no_answer=True,
-        overlap_threshold=None,
-    )
-    expected_no_answers = [0.2 * 0.16 * 0.12, 0]
-    for query, answers, expected_no_answer, probabilities in zip(
-        example_queries, nested_answers, expected_no_answers, [probabilities[:3, -1], probabilities[3:, -1]]
-    ):
-        assert len(answers) == 4
-        for doc, answer, score in zip(example_documents, reversed(answers[:3]), probabilities):
-            assert answer.query == query
-            assert answer.document == doc
-            assert answer.score == pytest.approx(score)
-            assert answer.meta["answer_page_number"] == doc.meta["page_number"]
+            if "page_number" in doc.meta:
+                assert answer.meta["answer_page_number"] == doc.meta["page_number"]
         no_answer = answers[-1]
         assert no_answer.query == query
         assert no_answer.document is None