From ae919e990798dbc5a32d5bcea3f290da965fe8ad Mon Sep 17 00:00:00 2001
From: Adriane Boyd <adrianeboyd@gmail.com>
Date: Tue, 13 Dec 2022 14:37:13 +0100
Subject: [PATCH] Move pipeline definitions into tests

---
 spacy/tests/test_language.py | 56 +++++++++++++++---------------------
 1 file changed, 23 insertions(+), 33 deletions(-)

diff --git a/spacy/tests/test_language.py b/spacy/tests/test_language.py
index c4d968582..d3246224e 100644
--- a/spacy/tests/test_language.py
+++ b/spacy/tests/test_language.py
@@ -58,29 +58,6 @@ def nlp():
     return nlp
 
 
-@pytest.fixture
-def nlp_tcm():
-    nlp = Language(Vocab())
-    textcat_multilabel = nlp.add_pipe("textcat_multilabel")
-    for label in ("FEATURE", "REQUEST", "BUG", "QUESTION"):
-        textcat_multilabel.add_label(label)
-    nlp.initialize()
-    return nlp
-
-
-@pytest.fixture
-def nlp_tc_tcm():
-    nlp = Language(Vocab())
-    textcat = nlp.add_pipe("textcat")
-    for label in ("POSITIVE", "NEGATIVE"):
-        textcat.add_label(label)
-    textcat_multilabel = nlp.add_pipe("textcat_multilabel")
-    for label in ("FEATURE", "REQUEST", "BUG", "QUESTION"):
-        textcat_multilabel.add_label(label)
-    nlp.initialize()
-    return nlp
-
-
 def test_language_update(nlp):
     text = "hello world"
     annots = {"cats": {"POSITIVE": 1.0, "NEGATIVE": 0.0}}
@@ -149,14 +126,19 @@ def test_evaluate_no_pipe(nlp):
     nlp.evaluate([Example.from_dict(doc, annots)])
 
 
-def test_evaluate_textcat_multilabel(nlp_tcm):
+def test_evaluate_textcat_multilabel(en_vocab):
     """Test that evaluate works with a multilabel textcat pipe."""
-    text = "hello world"
+    nlp = Language(en_vocab)
+    textcat_multilabel = nlp.add_pipe("textcat_multilabel")
+    for label in ("FEATURE", "REQUEST", "BUG", "QUESTION"):
+        textcat_multilabel.add_label(label)
+    nlp.initialize()
+
     annots = {"cats": {"FEATURE": 1.0, "QUESTION": 1.0}}
-    doc = Doc(nlp_tcm.vocab, words=text.split(" "))
+    doc = nlp.make_doc("hello world")
     example = Example.from_dict(doc, annots)
-    scores = nlp_tcm.evaluate([example])
-    labels = nlp_tcm.get_pipe("textcat_multilabel").labels
+    scores = nlp.evaluate([example])
+    labels = nlp.get_pipe("textcat_multilabel").labels
     for label in labels:
         assert scores["cats_f_per_type"].get(label) is not None
     for key in example.reference.cats.keys():
@@ -164,10 +146,18 @@ def test_evaluate_textcat_multilabel(nlp_tcm):
             assert scores["cats_f_per_type"].get(key) is None
 
 
-def test_evaluate_multiple_textcat(nlp_tc_tcm):
+def test_evaluate_multiple_textcat_final(en_vocab):
     """Test that evaluate evaluates the final textcat component in a pipeline
     with more than one textcat or textcat_multilabel."""
-    text = "hello world"
+    nlp = Language(en_vocab)
+    textcat = nlp.add_pipe("textcat")
+    for label in ("POSITIVE", "NEGATIVE"):
+        textcat.add_label(label)
+    textcat_multilabel = nlp.add_pipe("textcat_multilabel")
+    for label in ("FEATURE", "REQUEST", "BUG", "QUESTION"):
+        textcat_multilabel.add_label(label)
+    nlp.initialize()
+
     annots = {
         "cats": {
             "POSITIVE": 1.0,
@@ -178,11 +168,11 @@ def test_evaluate_multiple_textcat(nlp_tc_tcm):
             "NEGATIVE": 0.0,
         }
     }
-    doc = Doc(nlp_tc_tcm.vocab, words=text.split(" "))
+    doc = nlp.make_doc("hello world")
     example = Example.from_dict(doc, annots)
-    scores = nlp_tc_tcm.evaluate([example])
+    scores = nlp.evaluate([example])
     # get the labels from the final pipe
-    labels = nlp_tc_tcm.get_pipe(nlp_tc_tcm.pipe_names[-1]).labels
+    labels = nlp.get_pipe(nlp.pipe_names[-1]).labels
     for label in labels:
         assert scores["cats_f_per_type"].get(label) is not None
     for key in example.reference.cats.keys():