| import os |
| import json |
| import datasets |
|
|
| from sklearn.model_selection import train_test_split |
|
|
| _DATASET_LABELS = ['O', 'B-CITY', 'I-CITY', 'B-NAMES', 'I-NAMES', 'B-DATE', 'I-DATE'] |
|
|
| class Custom(datasets.GeneratorBasedBuilder): |
|
|
| def _info(self): |
| return datasets.DatasetInfo( |
| description='', |
| features=datasets.Features( |
| { |
| 'id': datasets.Value('string'), |
| 'tokens': datasets.Sequence(datasets.Value('string')), |
| 'ner_tags': datasets.Sequence( |
| datasets.features.ClassLabel( |
| names=_DATASET_LABELS |
| ) |
| ), |
| } |
| ), |
| supervised_keys=None, |
| homepage='', |
| citation='', |
| ) |
|
|
| def _split_generators(self, dl_manager): |
| data_path = dl_manager.download_and_extract("data.jsonl") |
|
|
| with open(data_path, 'r') as file: |
| lines = file.readlines() |
|
|
| train_lines, valid_lines = train_test_split(lines, test_size=0.2, random_state=42) |
| |
| return [ |
| datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={'lines': train_lines}), |
| datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={'lines': valid_lines}), |
| ] |
|
|
| def _generate_examples(self, lines): |
| for guid, line in enumerate(lines): |
| data = json.loads(line) |
| yield guid, { |
| 'id': str(guid), |
| 'tokens': data['words'], |
| 'ner_tags': data['pos'], |
| } |