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fix formatting on examples

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This commit is contained in:
Peter Baumgartner 2023-02-23 10:17:23 -05:00
parent d37b2094f7
commit f6108776aa
1 changed files with 18 additions and 75 deletions
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93
spacy/tests/test_cli_app.py
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@ -90,57 +90,17 @@ TRAIN_EXAMPLE_2 = dict(
@pytest.mark.slow @pytest.mark.slow
@pytest.mark.parametrize( @pytest.mark.parametrize(
"component,examples", "component,examples",
# fmt: off
[ [
( ("tagger", [TRAIN_EXAMPLE_1, TRAIN_EXAMPLE_2]),
"tagger", ("morphologizer", [TRAIN_EXAMPLE_1, TRAIN_EXAMPLE_2]),
[ ("trainable_lemmatizer", [TRAIN_EXAMPLE_1, TRAIN_EXAMPLE_2]),
TRAIN_EXAMPLE_1, ("parser", [TRAIN_EXAMPLE_1] * 30),
TRAIN_EXAMPLE_2, ("ner", [TRAIN_EXAMPLE_1, TRAIN_EXAMPLE_2]),
], ("spancat", [TRAIN_EXAMPLE_1, TRAIN_EXAMPLE_2]),
), ("textcat", [TRAIN_EXAMPLE_1, TRAIN_EXAMPLE_2]),
( ]
"morphologizer", # fmt: on
[
TRAIN_EXAMPLE_1,
TRAIN_EXAMPLE_2,
],
),
(
"trainable_lemmatizer",
[
TRAIN_EXAMPLE_1,
TRAIN_EXAMPLE_2,
],
),
(
"parser",
[
TRAIN_EXAMPLE_1,
]
* 30,
),
(
"ner",
[
TRAIN_EXAMPLE_1,
TRAIN_EXAMPLE_2,
],
),
(
"spancat",
[
TRAIN_EXAMPLE_1,
TRAIN_EXAMPLE_2,
],
),
(
"textcat",
[
TRAIN_EXAMPLE_1,
TRAIN_EXAMPLE_2,
],
),
],
) )
def test_init_config_trainable(component, examples, en_vocab): def test_init_config_trainable(component, examples, en_vocab):
if component == "textcat": if component == "textcat":
@ -203,33 +163,16 @@ def test_init_config_trainable(component, examples, en_vocab):
@pytest.mark.slow @pytest.mark.slow
@pytest.mark.parametrize( @pytest.mark.parametrize(
"component,examples", "component,examples",
[ # fmt: off
( [("tagger,parser,morphologizer", [TRAIN_EXAMPLE_1, TRAIN_EXAMPLE_2] * 15)]
"tagger,parser,morphologizer", # fmt: on
[
dict(
words=example_words_1,
tags=example_tags,
morphs=example_morphs,
deps=example_deps,
heads=[1, 1, 1],
pos=example_pos,
),
dict(
words=example_words_2,
tags=example_tags,
morphs=example_morphs,
deps=example_deps,
heads=[1, 1, 1],
pos=example_pos,
),
]
* 15,
),
],
) )
def test_init_config_trainable_multiple(component, examples, en_vocab): def test_init_config_trainable_multiple(component, examples, en_vocab):
train_docs = [Doc(en_vocab, **example) for example in examples] train_docs = []
for example in examples:
example = {k: v for k, v in example.items() if k not in ("cats", "spans")}
doc = Doc(en_vocab, **example)
train_docs.append(doc)
with make_tempdir() as d_in: with make_tempdir() as d_in:
train_bin = DocBin(docs=train_docs) train_bin = DocBin(docs=train_docs)