Tidy up tests

spacy/tests/regression/test_issue5501-6000.py

@@ -0,0 +1,76 @@
+from thinc.api import fix_random_seed
+from spacy.lang.en import English
+from spacy.tokens import Span
+from spacy import displacy
+from spacy.pipeline import merge_entities
+
+
+def test_issue5551():
+    """Test that after fixing the random seed, the results of the pipeline are truly identical"""
+    component = "textcat"
+    pipe_cfg = {
+        "model": {
+            "@architectures": "spacy.TextCatBOW.v1",
+            "exclusive_classes": True,
+            "ngram_size": 2,
+            "no_output_layer": False,
+        }
+    }
+    results = []
+    for i in range(3):
+        fix_random_seed(0)
+        nlp = English()
+        example = (
+            "Once hot, form ping-pong-ball-sized balls of the mixture, each weighing roughly 25 g.",
+            {"cats": {"Labe1": 1.0, "Label2": 0.0, "Label3": 0.0}},
+        )
+        pipe = nlp.add_pipe(component, config=pipe_cfg, last=True)
+        for label in set(example[1]["cats"]):
+            pipe.add_label(label)
+        nlp.initialize()
+        # Store the result of each iteration
+        result = pipe.model.predict([nlp.make_doc(example[0])])
+        results.append(list(result[0]))
+    # All results should be the same because of the fixed seed
+    assert len(results) == 3
+    assert results[0] == results[1]
+    assert results[0] == results[2]
+
+
+def test_issue5838():
+    # Displacy's EntityRenderer break line
+    # not working after last entity
+    sample_text = "First line\nSecond line, with ent\nThird line\nFourth line\n"
+    nlp = English()
+    doc = nlp(sample_text)
+    doc.ents = [Span(doc, 7, 8, label="test")]
+    html = displacy.render(doc, style="ent")
+    found = html.count("</br>")
+    assert found == 4
+
+
+def test_issue5918():
+    # Test edge case when merging entities.
+    nlp = English()
+    ruler = nlp.add_pipe("entity_ruler")
+    patterns = [
+        {"label": "ORG", "pattern": "Digicon Inc"},
+        {"label": "ORG", "pattern": "Rotan Mosle Inc's"},
+        {"label": "ORG", "pattern": "Rotan Mosle Technology Partners Ltd"},
+    ]
+    ruler.add_patterns(patterns)
+
+    text = """
+        Digicon Inc said it has completed the previously-announced disposition
+        of its computer systems division to an investment group led by
+        Rotan Mosle Inc's Rotan Mosle Technology Partners Ltd affiliate.
+        """
+    doc = nlp(text)
+    assert len(doc.ents) == 3
+    # make it so that the third span's head is within the entity (ent_iob=I)
+    # bug #5918 would wrongly transfer that I to the full entity, resulting in 2 instead of 3 final ents.
+    # TODO: test for logging here
+    # with pytest.warns(UserWarning):
+    #     doc[29].head = doc[33]
+    doc = merge_entities(doc)
+    assert len(doc.ents) == 3

spacy/tests/regression/test_issue5551.py

@@ -1,37 +0,0 @@
-from spacy.lang.en import English
-from spacy.util import fix_random_seed
-
-
-def test_issue5551():
-    """Test that after fixing the random seed, the results of the pipeline are truly identical"""
-    component = "textcat"
-    pipe_cfg = {
-        "model": {
-            "@architectures": "spacy.TextCatBOW.v1",
-            "exclusive_classes": True,
-            "ngram_size": 2,
-            "no_output_layer": False,
-        }
-    }
-
-    results = []
-    for i in range(3):
-        fix_random_seed(0)
-        nlp = English()
-        example = (
-            "Once hot, form ping-pong-ball-sized balls of the mixture, each weighing roughly 25 g.",
-            {"cats": {"Labe1": 1.0, "Label2": 0.0, "Label3": 0.0}},
-        )
-        pipe = nlp.add_pipe(component, config=pipe_cfg, last=True)
-        for label in set(example[1]["cats"]):
-            pipe.add_label(label)
-        nlp.initialize()
-
-        # Store the result of each iteration
-        result = pipe.model.predict([nlp.make_doc(example[0])])
-        results.append(list(result[0]))
-
-    # All results should be the same because of the fixed seed
-    assert len(results) == 3
-    assert results[0] == results[1]
-    assert results[0] == results[2]

spacy/tests/regression/test_issue5838.py

@@ -1,23 +0,0 @@
-from spacy.lang.en import English
-from spacy.tokens import Span
-from spacy import displacy
-
-
-SAMPLE_TEXT = """First line
-Second line, with ent
-Third line
-Fourth line
-"""
-
-
-def test_issue5838():
-    # Displacy's EntityRenderer break line
-    # not working after last entity
-
-    nlp = English()
-    doc = nlp(SAMPLE_TEXT)
-    doc.ents = [Span(doc, 7, 8, label="test")]
-
-    html = displacy.render(doc, style="ent")
-    found = html.count("</br>")
-    assert found == 4

spacy/tests/regression/test_issue5918.py

@@ -1,29 +0,0 @@
-from spacy.lang.en import English
-from spacy.pipeline import merge_entities
-
-
-def test_issue5918():
-    # Test edge case when merging entities.
-    nlp = English()
-    ruler = nlp.add_pipe("entity_ruler")
-    patterns = [
-        {"label": "ORG", "pattern": "Digicon Inc"},
-        {"label": "ORG", "pattern": "Rotan Mosle Inc's"},
-        {"label": "ORG", "pattern": "Rotan Mosle Technology Partners Ltd"},
-    ]
-    ruler.add_patterns(patterns)
-
-    text = """
-        Digicon Inc said it has completed the previously-announced disposition
-        of its computer systems division to an investment group led by
-        Rotan Mosle Inc's Rotan Mosle Technology Partners Ltd affiliate.
-        """
-    doc = nlp(text)
-    assert len(doc.ents) == 3
-    # make it so that the third span's head is within the entity (ent_iob=I)
-    # bug #5918 would wrongly transfer that I to the full entity, resulting in 2 instead of 3 final ents.
-    # TODO: test for logging here
-    # with pytest.warns(UserWarning):
-    #     doc[29].head = doc[33]
-    doc = merge_entities(doc)
-    assert len(doc.ents) == 3