spaCy/spacy/tests/regression/test_issue1622.py
2018-01-05 09:37:05 +01:00

92 lines
3.2 KiB
Python

# coding: utf-8
from __future__ import unicode_literals
import json
from tempfile import NamedTemporaryFile
import pytest
from ...cli.train import train
@pytest.mark.xfail
def test_cli_trained_model_can_be_saved(tmpdir):
cmd = None
lang = 'nl'
output_dir = str(tmpdir)
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",
"ner": "B-PER"
},
{
"id": 1,
"dep": "ROOT",
"head": 0,
"tag": "VERB",
"orth": "houdt",
"ner": "O"
},
{
"id": 2,
"dep": "case",
"head": 1,
"tag": "ADP",
"orth": "van",
"ner": "O"
},
{
"id": 3,
"dep": "obj",
"head": -2,
"tag": "NOUN",
"orth": "Marie",
"ner": "B-PER"
},
{
"id": 4,
"dep": "punct",
"head": -3,
"tag": "PUNCT",
"orth": ".",
"ner": "O"
},
{
"id": 5,
"dep": "",
"head": -1,
"tag": "SPACE",
"orth": "\n",
"ner": "O"
}
],
"brackets": []
}
]
}
]
}
]
train_file.write(json.dumps(train_corpus).encode('utf-8'))
train_file.close()
train_data = train_file.name
dev_data = train_data
# 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)
assert True