mirror of
https://github.com/explosion/spaCy.git
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586 lines
21 KiB
Python
586 lines
21 KiB
Python
import pytest
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from click import NoSuchOption
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from packaging.specifiers import SpecifierSet
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from spacy.training import docs_to_json, offsets_to_biluo_tags
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from spacy.training.converters import iob_to_docs, conll_ner_to_docs, conllu_to_docs
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from spacy.schemas import ProjectConfigSchema, RecommendationSchema, validate
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from spacy.lang.nl import Dutch
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from spacy.util import ENV_VARS, load_model_from_config
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from spacy.cli import info
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from spacy.cli.init_config import init_config, RECOMMENDATIONS
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from spacy.cli._util import validate_project_commands, parse_config_overrides
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from spacy.cli._util import load_project_config, substitute_project_variables
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from spacy.cli._util import is_subpath_of
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from spacy.cli._util import string_to_list
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from spacy import about
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from spacy.util import get_minor_version
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from spacy.cli.validate import get_model_pkgs
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from spacy.cli.download import get_compatibility, get_version
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from spacy.cli.package import get_third_party_dependencies
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from thinc.api import ConfigValidationError, Config
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import srsly
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import os
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from .util import make_tempdir
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from ..cli.init_pipeline import _init_labels
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def test_cli_info():
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nlp = Dutch()
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nlp.add_pipe("textcat")
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with make_tempdir() as tmp_dir:
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nlp.to_disk(tmp_dir)
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raw_data = info(tmp_dir, exclude=[""])
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assert raw_data["lang"] == "nl"
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assert raw_data["components"] == ["textcat"]
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def test_cli_converters_conllu_to_docs():
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# from NorNE: https://github.com/ltgoslo/norne/blob/3d23274965f513f23aa48455b28b1878dad23c05/ud/nob/no_bokmaal-ud-dev.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_docs = list(conllu_to_docs(input_data, n_sents=1))
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assert len(converted_docs) == 1
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converted = [docs_to_json(converted_docs)]
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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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ent_offsets = [
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(e[0], e[1], e[2]) for e in converted[0]["paragraphs"][0]["entities"]
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]
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biluo_tags = offsets_to_biluo_tags(converted_docs[0], ent_offsets, missing="O")
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assert biluo_tags == ["O", "B-PER", "L-PER", "O"]
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@pytest.mark.parametrize(
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"lines",
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[
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(
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"1\tDommer\tdommer\tNOUN\t_\tDefinite=Ind|Gender=Masc|Number=Sing\t2\tappos\t_\tname=O",
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"2\tFinn\tFinn\tPROPN\t_\tGender=Masc\t4\tnsubj\t_\tSpaceAfter=No|name=B-PER",
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"3\tEilertsen\tEilertsen\tPROPN\t_\t_\t2\tname\t_\tname=I-PER",
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"4\tavstår\tavstå\tVERB\t_\tMood=Ind|Tense=Pres|VerbForm=Fin\t0\troot\t_\tSpaceAfter=No|name=O",
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"5\t.\t$.\tPUNCT\t_\t_\t4\tpunct\t_\tname=B-BAD",
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),
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(
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"1\tDommer\tdommer\tNOUN\t_\tDefinite=Ind|Gender=Masc|Number=Sing\t2\tappos\t_\t_",
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"2\tFinn\tFinn\tPROPN\t_\tGender=Masc\t4\tnsubj\t_\tSpaceAfter=No|NE=B-PER",
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"3\tEilertsen\tEilertsen\tPROPN\t_\t_\t2\tname\t_\tNE=L-PER",
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"4\tavstår\tavstå\tVERB\t_\tMood=Ind|Tense=Pres|VerbForm=Fin\t0\troot\t_\tSpaceAfter=No",
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"5\t.\t$.\tPUNCT\t_\t_\t4\tpunct\t_\tNE=B-BAD",
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),
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],
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)
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def test_cli_converters_conllu_to_docs_name_ner_map(lines):
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input_data = "\n".join(lines)
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converted_docs = list(
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conllu_to_docs(input_data, n_sents=1, ner_map={"PER": "PERSON", "BAD": ""})
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)
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assert len(converted_docs) == 1
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converted = [docs_to_json(converted_docs)]
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assert converted[0]["id"] == 0
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assert len(converted[0]["paragraphs"]) == 1
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assert converted[0]["paragraphs"][0]["raw"] == "Dommer FinnEilertsen avstår. "
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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"]) == 5
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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", "PUNCT"]
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assert [t["head"] for t in tokens] == [1, 2, -1, 0, -1]
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assert [t["dep"] for t in tokens] == ["appos", "nsubj", "name", "ROOT", "punct"]
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ent_offsets = [
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(e[0], e[1], e[2]) for e in converted[0]["paragraphs"][0]["entities"]
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]
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biluo_tags = offsets_to_biluo_tags(converted_docs[0], ent_offsets, missing="O")
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assert biluo_tags == ["O", "B-PERSON", "L-PERSON", "O", "O"]
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def test_cli_converters_conllu_to_docs_subtokens():
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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_\tname=O",
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"2-3\tFE\t_\t_\t_\t_\t_\t_\t_\t_",
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"2\tFinn\tFinn\tPROPN\t_\tGender=Masc\t4\tnsubj\t_\tname=B-PER",
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"3\tEilertsen\tEilertsen\tX\t_\tGender=Fem|Tense=past\t2\tname\t_\tname=I-PER",
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"4\tavstår\tavstå\tVERB\t_\tMood=Ind|Tense=Pres|VerbForm=Fin\t0\troot\t_\tSpaceAfter=No|name=O",
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"5\t.\t$.\tPUNCT\t_\t_\t4\tpunct\t_\tname=O",
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]
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input_data = "\n".join(lines)
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converted_docs = list(
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conllu_to_docs(
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input_data, n_sents=1, merge_subtokens=True, append_morphology=True
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)
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)
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assert len(converted_docs) == 1
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converted = [docs_to_json(converted_docs)]
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assert converted[0]["id"] == 0
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assert len(converted[0]["paragraphs"]) == 1
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assert converted[0]["paragraphs"][0]["raw"] == "Dommer FE avstår. "
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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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print(tokens)
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assert [t["orth"] for t in tokens] == ["Dommer", "FE", "avstår", "."]
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assert [t["tag"] for t in tokens] == [
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"NOUN__Definite=Ind|Gender=Masc|Number=Sing",
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"PROPN_X__Gender=Fem,Masc|Tense=past",
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"VERB__Mood=Ind|Tense=Pres|VerbForm=Fin",
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"PUNCT",
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]
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assert [t["pos"] for t in tokens] == ["NOUN", "PROPN", "VERB", "PUNCT"]
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assert [t["morph"] for t in tokens] == [
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"Definite=Ind|Gender=Masc|Number=Sing",
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"Gender=Fem,Masc|Tense=past",
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"Mood=Ind|Tense=Pres|VerbForm=Fin",
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"",
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]
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assert [t["lemma"] for t in tokens] == ["dommer", "Finn Eilertsen", "avstå", "$."]
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assert [t["head"] for t in tokens] == [1, 1, 0, -1]
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assert [t["dep"] for t in tokens] == ["appos", "nsubj", "ROOT", "punct"]
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ent_offsets = [
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(e[0], e[1], e[2]) for e in converted[0]["paragraphs"][0]["entities"]
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]
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biluo_tags = offsets_to_biluo_tags(converted_docs[0], ent_offsets, missing="O")
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assert biluo_tags == ["O", "U-PER", "O", "O"]
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def test_cli_converters_iob_to_docs():
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lines = [
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"I|O like|O London|I-GPE and|O New|B-GPE York|I-GPE City|I-GPE .|O",
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"I|O like|O London|B-GPE and|O New|B-GPE York|I-GPE City|I-GPE .|O",
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"I|PRP|O like|VBP|O London|NNP|I-GPE and|CC|O New|NNP|B-GPE York|NNP|I-GPE City|NNP|I-GPE .|.|O",
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"I|PRP|O like|VBP|O London|NNP|B-GPE and|CC|O New|NNP|B-GPE York|NNP|I-GPE City|NNP|I-GPE .|.|O",
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]
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input_data = "\n".join(lines)
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converted_docs = list(iob_to_docs(input_data, n_sents=10))
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assert len(converted_docs) == 1
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converted = docs_to_json(converted_docs)
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assert converted["id"] == 0
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assert len(converted["paragraphs"]) == 1
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assert len(converted["paragraphs"][0]["sentences"]) == 4
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for i in range(0, 4):
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sent = converted["paragraphs"][0]["sentences"][i]
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assert len(sent["tokens"]) == 8
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tokens = sent["tokens"]
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expected = ["I", "like", "London", "and", "New", "York", "City", "."]
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assert [t["orth"] for t in tokens] == expected
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assert len(converted_docs[0].ents) == 8
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for ent in converted_docs[0].ents:
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assert ent.text in ["New York City", "London"]
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def test_cli_converters_conll_ner_to_docs():
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lines = [
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"-DOCSTART- -X- O O",
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"",
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"I\tO",
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"like\tO",
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"London\tB-GPE",
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"and\tO",
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"New\tB-GPE",
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"York\tI-GPE",
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"City\tI-GPE",
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".\tO",
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"",
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"I O",
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"like O",
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"London B-GPE",
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"and O",
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"New B-GPE",
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"York I-GPE",
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"City I-GPE",
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". O",
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"",
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"I PRP O",
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"like VBP O",
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"London NNP B-GPE",
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"and CC O",
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"New NNP B-GPE",
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"York NNP I-GPE",
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"City NNP I-GPE",
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". . O",
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"",
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"I PRP _ O",
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"like VBP _ O",
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"London NNP _ B-GPE",
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"and CC _ O",
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"New NNP _ B-GPE",
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"York NNP _ I-GPE",
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"City NNP _ I-GPE",
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". . _ O",
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"",
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"I\tPRP\t_\tO",
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"like\tVBP\t_\tO",
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"London\tNNP\t_\tB-GPE",
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"and\tCC\t_\tO",
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"New\tNNP\t_\tB-GPE",
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"York\tNNP\t_\tI-GPE",
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"City\tNNP\t_\tI-GPE",
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".\t.\t_\tO",
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]
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input_data = "\n".join(lines)
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converted_docs = list(conll_ner_to_docs(input_data, n_sents=10))
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assert len(converted_docs) == 1
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converted = docs_to_json(converted_docs)
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assert converted["id"] == 0
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assert len(converted["paragraphs"]) == 1
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assert len(converted["paragraphs"][0]["sentences"]) == 5
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for i in range(0, 5):
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sent = converted["paragraphs"][0]["sentences"][i]
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assert len(sent["tokens"]) == 8
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tokens = sent["tokens"]
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# fmt: off
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assert [t["orth"] for t in tokens] == ["I", "like", "London", "and", "New", "York", "City", "."]
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# fmt: on
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assert len(converted_docs[0].ents) == 10
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for ent in converted_docs[0].ents:
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assert ent.text in ["New York City", "London"]
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def test_project_config_validation_full():
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config = {
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"vars": {"some_var": 20},
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"directories": ["assets", "configs", "corpus", "scripts", "training"],
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"assets": [
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{
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"dest": "x",
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"url": "https://example.com",
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"checksum": "63373dd656daa1fd3043ce166a59474c",
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},
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{
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"dest": "y",
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"git": {
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"repo": "https://github.com/example/repo",
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"branch": "develop",
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"path": "y",
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},
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},
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],
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"commands": [
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{
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"name": "train",
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"help": "Train a model",
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"script": ["python -m spacy train config.cfg -o training"],
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"deps": ["config.cfg", "corpus/training.spcy"],
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"outputs": ["training/model-best"],
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},
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{"name": "test", "script": ["pytest", "custom.py"], "no_skip": True},
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],
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"workflows": {"all": ["train", "test"], "train": ["train"]},
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}
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errors = validate(ProjectConfigSchema, config)
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assert not errors
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@pytest.mark.parametrize(
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"config",
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[
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{"commands": [{"name": "a"}, {"name": "a"}]},
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{"commands": [{"name": "a"}], "workflows": {"a": []}},
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{"commands": [{"name": "a"}], "workflows": {"b": ["c"]}},
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],
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)
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def test_project_config_validation1(config):
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with pytest.raises(SystemExit):
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validate_project_commands(config)
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@pytest.mark.parametrize(
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"config,n_errors",
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[
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({"commands": {"a": []}}, 1),
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({"commands": [{"help": "..."}]}, 1),
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({"commands": [{"name": "a", "extra": "b"}]}, 1),
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({"commands": [{"extra": "b"}]}, 2),
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({"commands": [{"name": "a", "deps": [123]}]}, 1),
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],
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)
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def test_project_config_validation2(config, n_errors):
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errors = validate(ProjectConfigSchema, config)
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assert len(errors) == n_errors
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@pytest.mark.parametrize(
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"int_value",
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[10, pytest.param("10", marks=pytest.mark.xfail)],
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)
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def test_project_config_interpolation(int_value):
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variables = {"a": int_value, "b": {"c": "foo", "d": True}}
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commands = [
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{"name": "x", "script": ["hello ${vars.a} ${vars.b.c}"]},
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{"name": "y", "script": ["${vars.b.c} ${vars.b.d}"]},
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]
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project = {"commands": commands, "vars": variables}
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with make_tempdir() as d:
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srsly.write_yaml(d / "project.yml", project)
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cfg = load_project_config(d)
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assert type(cfg) == dict
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assert type(cfg["commands"]) == list
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assert cfg["commands"][0]["script"][0] == "hello 10 foo"
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assert cfg["commands"][1]["script"][0] == "foo true"
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commands = [{"name": "x", "script": ["hello ${vars.a} ${vars.b.e}"]}]
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project = {"commands": commands, "vars": variables}
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with pytest.raises(ConfigValidationError):
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substitute_project_variables(project)
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@pytest.mark.parametrize(
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"greeting",
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[342, "everyone", "tout le monde", pytest.param("42", marks=pytest.mark.xfail)],
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)
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def test_project_config_interpolation_override(greeting):
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variables = {"a": "world"}
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commands = [
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{"name": "x", "script": ["hello ${vars.a}"]},
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]
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overrides = {"vars.a": greeting}
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project = {"commands": commands, "vars": variables}
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with make_tempdir() as d:
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srsly.write_yaml(d / "project.yml", project)
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cfg = load_project_config(d, overrides=overrides)
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assert type(cfg) == dict
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assert type(cfg["commands"]) == list
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assert cfg["commands"][0]["script"][0] == f"hello {greeting}"
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def test_project_config_interpolation_env():
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variables = {"a": 10}
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env_var = "SPACY_TEST_FOO"
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env_vars = {"foo": env_var}
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commands = [{"name": "x", "script": ["hello ${vars.a} ${env.foo}"]}]
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project = {"commands": commands, "vars": variables, "env": env_vars}
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with make_tempdir() as d:
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srsly.write_yaml(d / "project.yml", project)
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cfg = load_project_config(d)
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assert cfg["commands"][0]["script"][0] == "hello 10 "
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os.environ[env_var] = "123"
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with make_tempdir() as d:
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srsly.write_yaml(d / "project.yml", project)
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cfg = load_project_config(d)
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assert cfg["commands"][0]["script"][0] == "hello 10 123"
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@pytest.mark.parametrize(
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"args,expected",
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[
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# fmt: off
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(["--x.foo", "10"], {"x.foo": 10}),
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(["--x.foo=10"], {"x.foo": 10}),
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(["--x.foo", "bar"], {"x.foo": "bar"}),
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(["--x.foo=bar"], {"x.foo": "bar"}),
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(["--x.foo", "--x.bar", "baz"], {"x.foo": True, "x.bar": "baz"}),
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(["--x.foo", "--x.bar=baz"], {"x.foo": True, "x.bar": "baz"}),
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(["--x.foo", "10.1", "--x.bar", "--x.baz", "false"], {"x.foo": 10.1, "x.bar": True, "x.baz": False}),
|
|
(["--x.foo", "10.1", "--x.bar", "--x.baz=false"], {"x.foo": 10.1, "x.bar": True, "x.baz": False})
|
|
# fmt: on
|
|
],
|
|
)
|
|
def test_parse_config_overrides(args, expected):
|
|
assert parse_config_overrides(args) == expected
|
|
|
|
|
|
@pytest.mark.parametrize("args", [["--foo"], ["--x.foo", "bar", "--baz"]])
|
|
def test_parse_config_overrides_invalid(args):
|
|
with pytest.raises(NoSuchOption):
|
|
parse_config_overrides(args)
|
|
|
|
|
|
@pytest.mark.parametrize("args", [["--x.foo", "bar", "baz"], ["x.foo"]])
|
|
def test_parse_config_overrides_invalid_2(args):
|
|
with pytest.raises(SystemExit):
|
|
parse_config_overrides(args)
|
|
|
|
|
|
def test_parse_cli_overrides():
|
|
overrides = "--x.foo bar --x.bar=12 --x.baz false --y.foo=hello"
|
|
os.environ[ENV_VARS.CONFIG_OVERRIDES] = overrides
|
|
result = parse_config_overrides([])
|
|
assert len(result) == 4
|
|
assert result["x.foo"] == "bar"
|
|
assert result["x.bar"] == 12
|
|
assert result["x.baz"] is False
|
|
assert result["y.foo"] == "hello"
|
|
os.environ[ENV_VARS.CONFIG_OVERRIDES] = "--x"
|
|
assert parse_config_overrides([], env_var=None) == {}
|
|
with pytest.raises(SystemExit):
|
|
parse_config_overrides([])
|
|
os.environ[ENV_VARS.CONFIG_OVERRIDES] = "hello world"
|
|
with pytest.raises(SystemExit):
|
|
parse_config_overrides([])
|
|
del os.environ[ENV_VARS.CONFIG_OVERRIDES]
|
|
|
|
|
|
@pytest.mark.parametrize("lang", ["en", "nl"])
|
|
@pytest.mark.parametrize(
|
|
"pipeline", [["tagger", "parser", "ner"], [], ["ner", "textcat", "sentencizer"]]
|
|
)
|
|
@pytest.mark.parametrize("optimize", ["efficiency", "accuracy"])
|
|
@pytest.mark.parametrize("pretraining", [True, False])
|
|
def test_init_config(lang, pipeline, optimize, pretraining):
|
|
# TODO: add more tests and also check for GPU with transformers
|
|
config = init_config(
|
|
lang=lang,
|
|
pipeline=pipeline,
|
|
optimize=optimize,
|
|
pretraining=pretraining,
|
|
gpu=False,
|
|
)
|
|
assert isinstance(config, Config)
|
|
if pretraining:
|
|
config["paths"]["raw_text"] = "my_data.jsonl"
|
|
load_model_from_config(config, auto_fill=True)
|
|
|
|
|
|
def test_model_recommendations():
|
|
for lang, data in RECOMMENDATIONS.items():
|
|
assert RecommendationSchema(**data)
|
|
|
|
|
|
@pytest.mark.parametrize(
|
|
"value",
|
|
[
|
|
# fmt: off
|
|
"parser,textcat,tagger",
|
|
" parser, textcat ,tagger ",
|
|
'parser,textcat,tagger',
|
|
' parser, textcat ,tagger ',
|
|
' "parser"," textcat " ,"tagger "',
|
|
" 'parser',' textcat ' ,'tagger '",
|
|
'[parser,textcat,tagger]',
|
|
'["parser","textcat","tagger"]',
|
|
'[" parser" ,"textcat ", " tagger " ]',
|
|
"[parser,textcat,tagger]",
|
|
"[ parser, textcat , tagger]",
|
|
"['parser','textcat','tagger']",
|
|
"[' parser' , 'textcat', ' tagger ' ]",
|
|
# fmt: on
|
|
],
|
|
)
|
|
def test_string_to_list(value):
|
|
assert string_to_list(value, intify=False) == ["parser", "textcat", "tagger"]
|
|
|
|
|
|
@pytest.mark.parametrize(
|
|
"value",
|
|
[
|
|
# fmt: off
|
|
"1,2,3",
|
|
'[1,2,3]',
|
|
'["1","2","3"]',
|
|
'[" 1" ,"2 ", " 3 " ]',
|
|
"[' 1' , '2', ' 3 ' ]",
|
|
# fmt: on
|
|
],
|
|
)
|
|
def test_string_to_list_intify(value):
|
|
assert string_to_list(value, intify=False) == ["1", "2", "3"]
|
|
assert string_to_list(value, intify=True) == [1, 2, 3]
|
|
|
|
|
|
@pytest.mark.skip(reason="Temporarily skip until v3.2.0 release")
|
|
def test_download_compatibility():
|
|
spec = SpecifierSet("==" + about.__version__)
|
|
spec.prereleases = False
|
|
if about.__version__ in spec:
|
|
model_name = "en_core_web_sm"
|
|
compatibility = get_compatibility()
|
|
version = get_version(model_name, compatibility)
|
|
assert get_minor_version(about.__version__) == get_minor_version(version)
|
|
|
|
|
|
@pytest.mark.skip(reason="Temporarily skip until v3.2.0 release")
|
|
def test_validate_compatibility_table():
|
|
spec = SpecifierSet("==" + about.__version__)
|
|
spec.prereleases = False
|
|
if about.__version__ in spec:
|
|
model_pkgs, compat = get_model_pkgs()
|
|
spacy_version = get_minor_version(about.__version__)
|
|
current_compat = compat.get(spacy_version, {})
|
|
assert len(current_compat) > 0
|
|
assert "en_core_web_sm" in current_compat
|
|
|
|
|
|
@pytest.mark.parametrize("component_name", ["ner", "textcat", "spancat", "tagger"])
|
|
def test_init_labels(component_name):
|
|
nlp = Dutch()
|
|
component = nlp.add_pipe(component_name)
|
|
for label in ["T1", "T2", "T3", "T4"]:
|
|
component.add_label(label)
|
|
assert len(nlp.get_pipe(component_name).labels) == 4
|
|
|
|
with make_tempdir() as tmp_dir:
|
|
_init_labels(nlp, tmp_dir)
|
|
|
|
config = init_config(
|
|
lang="nl",
|
|
pipeline=[component_name],
|
|
optimize="efficiency",
|
|
gpu=False,
|
|
)
|
|
config["initialize"]["components"][component_name] = {
|
|
"labels": {
|
|
"@readers": "spacy.read_labels.v1",
|
|
"path": f"{tmp_dir}/{component_name}.json",
|
|
}
|
|
}
|
|
|
|
nlp2 = load_model_from_config(config, auto_fill=True)
|
|
assert len(nlp2.get_pipe(component_name).labels) == 0
|
|
nlp2.initialize()
|
|
assert len(nlp2.get_pipe(component_name).labels) == 4
|
|
|
|
|
|
def test_get_third_party_dependencies():
|
|
# We can't easily test the detection of third-party packages here, but we
|
|
# can at least make sure that the function and its importlib magic runs.
|
|
nlp = Dutch()
|
|
# Test with component factory based on Cython module
|
|
nlp.add_pipe("tagger")
|
|
assert get_third_party_dependencies(nlp.config) == []
|
|
|
|
# Test with legacy function
|
|
nlp = Dutch()
|
|
nlp.add_pipe(
|
|
"textcat",
|
|
config={
|
|
"model": {
|
|
# Do not update from legacy architecture spacy.TextCatBOW.v1
|
|
"@architectures": "spacy.TextCatBOW.v1",
|
|
"exclusive_classes": True,
|
|
"ngram_size": 1,
|
|
"no_output_layer": False,
|
|
}
|
|
},
|
|
)
|
|
get_third_party_dependencies(nlp.config) == []
|
|
|
|
|
|
@pytest.mark.parametrize(
|
|
"parent,child,expected",
|
|
[
|
|
("/tmp", "/tmp", True),
|
|
("/tmp", "/", False),
|
|
("/tmp", "/tmp/subdir", True),
|
|
("/tmp", "/tmpdir", False),
|
|
("/tmp", "/tmp/subdir/..", True),
|
|
("/tmp", "/tmp/..", False),
|
|
],
|
|
)
|
|
def test_is_subpath_of(parent, child, expected):
|
|
assert is_subpath_of(parent, child) == expected
|