mirror of
https://github.com/explosion/spaCy.git
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d8573ee715
* Add check for empty input file to CLI pretrain * Raise error if JSONL is not a dict or contains neither `tokens` nor `text` key * Skip empty values for correct pretrain keys and log a counter as warning * Add tests for CLI pretrain core function make_docs. * Add a short hint for the `tokens` key to the CLI pretrain docs * Add success message to CLI pretrain * Update model loading to fix the tests * Skip empty values and do not create docs out of it
75 lines
2.7 KiB
Python
75 lines
2.7 KiB
Python
# coding: utf-8
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from __future__ import unicode_literals
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import pytest
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from spacy.lang.en import English
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from spacy.cli.converters import conllu2json
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from spacy.cli.pretrain import make_docs
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def test_cli_converters_conllu2json():
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# https://raw.githubusercontent.com/ohenrik/nb_news_ud_sm/master/original_data/no-ud-dev-ner.conllu
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lines = [
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"1\tDommer\tdommer\tNOUN\t_\tDefinite=Ind|Gender=Masc|Number=Sing\t2\tappos\t_\tO",
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"2\tFinn\tFinn\tPROPN\t_\tGender=Masc\t4\tnsubj\t_\tB-PER",
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"3\tEilertsen\tEilertsen\tPROPN\t_\t_\t2\tname\t_\tI-PER",
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"4\tavstår\tavstå\tVERB\t_\tMood=Ind|Tense=Pres|VerbForm=Fin\t0\troot\t_\tO",
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]
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input_data = "\n".join(lines)
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converted = conllu2json(input_data, n_sents=1)
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assert len(converted) == 1
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assert converted[0]["id"] == 0
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assert len(converted[0]["paragraphs"]) == 1
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assert len(converted[0]["paragraphs"][0]["sentences"]) == 1
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sent = converted[0]["paragraphs"][0]["sentences"][0]
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assert len(sent["tokens"]) == 4
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tokens = sent["tokens"]
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assert [t["orth"] for t in tokens] == ["Dommer", "Finn", "Eilertsen", "avstår"]
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assert [t["tag"] for t in tokens] == ["NOUN", "PROPN", "PROPN", "VERB"]
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assert [t["head"] for t in tokens] == [1, 2, -1, 0]
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assert [t["dep"] for t in tokens] == ["appos", "nsubj", "name", "ROOT"]
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assert [t["ner"] for t in tokens] == ["O", "B-PER", "L-PER", "O"]
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def test_pretrain_make_docs():
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nlp = English()
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valid_jsonl_text = {"text": "Some text"}
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docs, skip_count = make_docs(nlp, [valid_jsonl_text], 1, 10)
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assert len(docs) == 1
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assert skip_count == 0
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valid_jsonl_tokens = {"tokens": ["Some", "tokens"]}
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docs, skip_count = make_docs(nlp, [valid_jsonl_tokens], 1, 10)
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assert len(docs) == 1
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assert skip_count == 0
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invalid_jsonl_type = 0
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with pytest.raises(TypeError):
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make_docs(nlp, [invalid_jsonl_type], 1, 100)
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invalid_jsonl_key = {"invalid": "Does not matter"}
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with pytest.raises(ValueError):
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make_docs(nlp, [invalid_jsonl_key], 1, 100)
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empty_jsonl_text = {"text": ""}
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docs, skip_count = make_docs(nlp, [empty_jsonl_text], 1, 10)
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assert len(docs) == 0
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assert skip_count == 1
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empty_jsonl_tokens = {"tokens": []}
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docs, skip_count = make_docs(nlp, [empty_jsonl_tokens], 1, 10)
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assert len(docs) == 0
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assert skip_count == 1
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too_short_jsonl = {"text": "This text is not long enough"}
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docs, skip_count = make_docs(nlp, [too_short_jsonl], 10, 15)
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assert len(docs) == 0
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assert skip_count == 0
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too_long_jsonl = {"text": "This text contains way too much tokens for this test"}
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docs, skip_count = make_docs(nlp, [too_long_jsonl], 1, 5)
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assert len(docs) == 0
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assert skip_count == 0
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