| import datasets | |
| import pyarrow.parquet as pq | |
| _CITATION = '' | |
| _DESCRIPTION = '' | |
| _HOMEPAGE = '' | |
| _LICENSE = '' | |
| _BASE_URL = 'https://huggingface.co/datasets/AresEkb/prof_standards_sbert_large_mt_nlu_ru/resolve/main/' | |
| _FEATURES = { | |
| 'domains': datasets.Features({ | |
| 'reg_number': datasets.Value('string'), | |
| 'standard_name': datasets.Value('string'), | |
| 'name': datasets.Value('string'), | |
| 'purpose': datasets.Value('string'), | |
| 'embeddings': datasets.Sequence(datasets.Value('float32')), | |
| }), | |
| 'generalized_functions': datasets.Features({ | |
| 'generalized_function_id': datasets.Value('string'), | |
| 'reg_number': datasets.Value('string'), | |
| 'name': datasets.Value('string'), | |
| 'embeddings': datasets.Sequence(datasets.Value('float32')), | |
| }), | |
| 'jobs': datasets.Features({ | |
| 'generalized_function_id': datasets.Value('string'), | |
| 'reg_number': datasets.Value('string'), | |
| 'name': datasets.Value('string'), | |
| 'embeddings': datasets.Sequence(datasets.Value('float32')), | |
| }), | |
| 'particular_functions': datasets.Features({ | |
| 'generalized_function_id': datasets.Value('string'), | |
| 'particular_function_id': datasets.Value('string'), | |
| 'reg_number': datasets.Value('string'), | |
| 'name': datasets.Value('string'), | |
| 'embeddings': datasets.Sequence(datasets.Value('float32')), | |
| }), | |
| 'actions': datasets.Features({ | |
| 'generalized_function_id': datasets.Value('string'), | |
| 'particular_function_id': datasets.Value('string'), | |
| 'reg_number': datasets.Value('string'), | |
| 'name': datasets.Value('string'), | |
| 'embeddings': datasets.Sequence(datasets.Value('float32')), | |
| }), | |
| 'skills': datasets.Features({ | |
| 'generalized_function_id': datasets.Value('string'), | |
| 'particular_function_id': datasets.Value('string'), | |
| 'reg_number': datasets.Value('string'), | |
| 'name': datasets.Value('string'), | |
| 'embeddings': datasets.Sequence(datasets.Value('float32')), | |
| }), | |
| 'knowledges': datasets.Features({ | |
| 'generalized_function_id': datasets.Value('string'), | |
| 'particular_function_id': datasets.Value('string'), | |
| 'reg_number': datasets.Value('string'), | |
| 'name': datasets.Value('string'), | |
| 'embeddings': datasets.Sequence(datasets.Value('float32')), | |
| }), | |
| } | |
| class ProfStandardsDatasetBuilder(datasets.ArrowBasedBuilder): | |
| VERSION = datasets.Version('0.0.1') | |
| BUILDER_CONFIGS = [ | |
| datasets.BuilderConfig('domains', VERSION), | |
| datasets.BuilderConfig('generalized_functions', VERSION), | |
| datasets.BuilderConfig('jobs', VERSION), | |
| datasets.BuilderConfig('particular_functions', VERSION), | |
| datasets.BuilderConfig('actions', VERSION), | |
| datasets.BuilderConfig('skills', VERSION), | |
| datasets.BuilderConfig('knowledges', VERSION), | |
| ] | |
| def _info(self): | |
| return datasets.DatasetInfo( | |
| description=_DESCRIPTION, | |
| features=_FEATURES[self.config.name], | |
| homepage=_HOMEPAGE, | |
| license=_LICENSE, | |
| citation=_CITATION, | |
| ) | |
| def _split_generators(self, dl_manager): | |
| url = _BASE_URL + self.config.name + '.parquet' | |
| file_path = dl_manager.download(url) | |
| return [ | |
| datasets.SplitGenerator( | |
| name=datasets.Split.TRAIN, | |
| gen_kwargs={'file_path': file_path}, | |
| ), | |
| ] | |
| def _generate_tables(self, file_path): | |
| yield self.config.name, pq.read_table(open(file_path, "rb")) | |