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Remove config from coref tests

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This was necessary when the tok2vec_size option was necessary.
This commit is contained in:
Paul O'Leary McCann 2022-07-12 14:08:35 +09:00
parent 1baa334b8a
commit 07e8556cc3
2 changed files with 10 additions and 15 deletions
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15
spacy/tests/pipeline/test_coref.py
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@ -36,9 +36,6 @@ TRAIN_DATA = [
# fmt: on
CONFIG = {"model": {"@architectures": "spacy.Coref.v1", "tok2vec_size": 64}}
@pytest.fixture
def nlp():
return English()
@ -67,7 +64,7 @@ def test_not_initialized(nlp):
@pytest.mark.skipif(not has_torch, reason="Torch not available")
def test_initialized(nlp):
nlp.add_pipe("coref", config=CONFIG)
nlp.add_pipe("coref")
nlp.initialize()
assert nlp.pipe_names == ["coref"]
text = "She gave me her pen."
@ -79,7 +76,7 @@ def test_initialized(nlp):
@pytest.mark.skipif(not has_torch, reason="Torch not available")
def test_initialized_short(nlp):
nlp.add_pipe("coref", config=CONFIG)
nlp.add_pipe("coref")
nlp.initialize()
assert nlp.pipe_names == ["coref"]
text = "Hi there"
@ -89,7 +86,7 @@ def test_initialized_short(nlp):
@pytest.mark.skipif(not has_torch, reason="Torch not available")
def test_coref_serialization(nlp):
# Test that the coref component can be serialized
nlp.add_pipe("coref", last=True, config=CONFIG)
nlp.add_pipe("coref", last=True)
nlp.initialize()
assert nlp.pipe_names == ["coref"]
text = "She gave me her pen."
@ -111,7 +108,7 @@ def test_overfitting_IO(nlp):
for text, annot in TRAIN_DATA:
train_examples.append(Example.from_dict(nlp.make_doc(text), annot))
nlp.add_pipe("coref", config=CONFIG)
nlp.add_pipe("coref")
optimizer = nlp.initialize()
test_text = TRAIN_DATA[0][0]
doc = nlp(test_text)
@ -166,7 +163,7 @@ def test_tokenization_mismatch(nlp):
train_examples.append(eg)
nlp.add_pipe("coref", config=CONFIG)
nlp.add_pipe("coref")
optimizer = nlp.initialize()
test_text = TRAIN_DATA[0][0]
doc = nlp(test_text)
@ -228,7 +225,7 @@ def test_whitespace_mismatch(nlp):
eg.predicted = nlp.make_doc(" " + text)
train_examples.append(eg)
nlp.add_pipe("coref", config=CONFIG)
nlp.add_pipe("coref")
optimizer = nlp.initialize()
test_text = TRAIN_DATA[0][0]
doc = nlp(test_text)

10
spacy/tests/pipeline/test_span_predictor.py
View File

@ -44,8 +44,6 @@ TRAIN_DATA = [
]
# fmt: on
CONFIG = {"model": {"@architectures": "spacy.SpanPredictor.v1", "tok2vec_size": 64}}
@pytest.fixture
def nlp():
@ -76,7 +74,7 @@ def test_not_initialized(nlp):
@pytest.mark.skipif(not has_torch, reason="Torch not available")
def test_span_predictor_serialization(nlp):
# Test that the span predictor component can be serialized
nlp.add_pipe("span_predictor", last=True, config=CONFIG)
nlp.add_pipe("span_predictor", last=True)
nlp.initialize()
assert nlp.pipe_names == ["span_predictor"]
text = "She gave me her pen."
@ -109,7 +107,7 @@ def test_overfitting_IO(nlp):
pred.spans[key] = [pred[span.start : span.end] for span in spans]
train_examples.append(eg)
nlp.add_pipe("span_predictor", config=CONFIG)
nlp.add_pipe("span_predictor")
optimizer = nlp.initialize()
test_text = TRAIN_DATA[0][0]
doc = nlp(test_text)
@ -173,7 +171,7 @@ def test_tokenization_mismatch(nlp):
train_examples.append(eg)
nlp.add_pipe("span_predictor", config=CONFIG)
nlp.add_pipe("span_predictor")
optimizer = nlp.initialize()
test_text = TRAIN_DATA[0][0]
doc = nlp(test_text)
@ -218,7 +216,7 @@ def test_whitespace_mismatch(nlp):
eg.predicted = nlp.make_doc(" " + text)
train_examples.append(eg)
nlp.add_pipe("span_predictor", config=CONFIG)
nlp.add_pipe("span_predictor")
optimizer = nlp.initialize()
test_text = TRAIN_DATA[0][0]
doc = nlp(test_text)