# coding: utf-8 from __future__ import unicode_literals import json from tempfile import NamedTemporaryFile import pytest from ...cli.train import train def test_cli_trained_model_can_be_saved(tmpdir): 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