spaCy/spacy/tests/regression/_test_issue1622.py

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# coding: utf-8
from __future__ import unicode_literals
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import json
from tempfile import NamedTemporaryFile
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from ...cli.train import train
def test_cli_trained_model_can_be_saved(tmpdir):
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lang = "nl"
output_dir = str(tmpdir)
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train_file = NamedTemporaryFile("wb", dir=output_dir, delete=False)
train_corpus = [
{
"id": "identifier_0",
"paragraphs": [
{
"raw": "Jan houdt van Marie.\n",
"sentences": [
{
"tokens": [
{
"id": 0,
"dep": "nsubj",
"head": 1,
"tag": "NOUN",
"orth": "Jan",
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"ner": "B-PER",
},
{
"id": 1,
"dep": "ROOT",
"head": 0,
"tag": "VERB",
"orth": "houdt",
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"ner": "O",
},
{
"id": 2,
"dep": "case",
"head": 1,
"tag": "ADP",
"orth": "van",
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"ner": "O",
},
{
"id": 3,
"dep": "obj",
"head": -2,
"tag": "NOUN",
"orth": "Marie",
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"ner": "B-PER",
},
{
"id": 4,
"dep": "punct",
"head": -3,
"tag": "PUNCT",
"orth": ".",
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"ner": "O",
},
{
"id": 5,
"dep": "",
"head": -1,
"tag": "SPACE",
"orth": "\n",
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"ner": "O",
},
],
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"brackets": [],
}
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],
}
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],
}
]
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train_file.write(json.dumps(train_corpus).encode("utf-8"))
train_file.close()
train_data = train_file.name
dev_data = train_data
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# spacy train -n 1 -g -1 nl output_nl training_corpus.json training \
# corpus.json
train(lang, output_dir, train_data, dev_data, n_iter=1)
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assert True