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99 lines
4.1 KiB
Python
99 lines
4.1 KiB
Python
from spacy.gold import Corpus
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from spacy.lang.en import English
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from ..util import make_tempdir
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from ...gold.converters import json2docs
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from ...tokens import DocBin
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def test_issue4402():
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nlp = English()
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with make_tempdir() as tmpdir:
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output_file = tmpdir / "test4402.spacy"
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docs = json2docs([json_data])
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data = DocBin(docs=docs, attrs =["ORTH", "SENT_START", "ENT_IOB", "ENT_TYPE"]).to_bytes()
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with output_file.open("wb") as file_:
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file_.write(data)
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corpus = Corpus(train_loc=str(output_file), dev_loc=str(output_file))
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train_data = list(corpus.train_dataset(nlp))
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assert len(train_data) == 2
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split_train_data = []
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for eg in train_data:
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split_train_data.extend(eg.split_sents())
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assert len(split_train_data) == 4
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json_data =\
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{
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"id": 0,
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"paragraphs": [
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{
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"raw": "How should I cook bacon in an oven?\nI've heard of people cooking bacon in an oven.",
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"sentences": [
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{
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"tokens": [
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{"id": 0, "orth": "How", "ner": "O"},
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{"id": 1, "orth": "should", "ner": "O"},
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{"id": 2, "orth": "I", "ner": "O"},
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{"id": 3, "orth": "cook", "ner": "O"},
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{"id": 4, "orth": "bacon", "ner": "O"},
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{"id": 5, "orth": "in", "ner": "O"},
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{"id": 6, "orth": "an", "ner": "O"},
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{"id": 7, "orth": "oven", "ner": "O"},
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{"id": 8, "orth": "?", "ner": "O"},
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],
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"brackets": [],
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},
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{
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"tokens": [
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{"id": 9, "orth": "\n", "ner": "O"},
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{"id": 10, "orth": "I", "ner": "O"},
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{"id": 11, "orth": "'ve", "ner": "O"},
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{"id": 12, "orth": "heard", "ner": "O"},
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{"id": 13, "orth": "of", "ner": "O"},
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{"id": 14, "orth": "people", "ner": "O"},
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{"id": 15, "orth": "cooking", "ner": "O"},
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{"id": 16, "orth": "bacon", "ner": "O"},
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{"id": 17, "orth": "in", "ner": "O"},
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{"id": 18, "orth": "an", "ner": "O"},
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{"id": 19, "orth": "oven", "ner": "O"},
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{"id": 20, "orth": ".", "ner": "O"},
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],
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"brackets": [],
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},
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],
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"cats": [
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{"label": "baking", "value": 1.0},
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{"label": "not_baking", "value": 0.0},
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],
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},
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{
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"raw": "What is the difference between white and brown eggs?\n",
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"sentences": [
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{
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"tokens": [
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{"id": 0, "orth": "What", "ner": "O"},
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{"id": 1, "orth": "is", "ner": "O"},
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{"id": 2, "orth": "the", "ner": "O"},
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{"id": 3, "orth": "difference", "ner": "O"},
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{"id": 4, "orth": "between", "ner": "O"},
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{"id": 5, "orth": "white", "ner": "O"},
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{"id": 6, "orth": "and", "ner": "O"},
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{"id": 7, "orth": "brown", "ner": "O"},
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{"id": 8, "orth": "eggs", "ner": "O"},
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{"id": 9, "orth": "?", "ner": "O"},
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],
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"brackets": [],
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},
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{"tokens": [{"id": 10, "orth": "\n", "ner": "O"}], "brackets": []},
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],
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"cats": [
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{"label": "baking", "value": 0.0},
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{"label": "not_baking", "value": 1.0},
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],
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},
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],
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}
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