# coding=utf-8 # Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # Lint as: python3 """ESCI-product-dataset dataset.""" import json import datasets _CITATION = """ @misc{reddy2022shopping, title={Shopping Queries Dataset: A Large-Scale {ESCI} Benchmark for Improving Product Search}, author={Chandan K. Reddy and Lluís Màrquez and Fran Valero and Nikhil Rao and Hugo Zaragoza and Sambaran Bandyopadhyay and Arnab Biswas and Anlu Xing and Karthik Subbian}, year={2022}, eprint={2206.06588}, archivePrefix={arXiv} } } """ _DESCRIPTION = "dataset load script for ESCI-product-dataset recall" _DATASET_URLS = { 'train': "https://huggingface.co/datasets/spacemanidol/ESCI-product-dataset/resolve/main/train.jsonl", } class ESCIproduct(datasets.GeneratorBasedBuilder): VERSION = datasets.Version("0.0.1") BUILDER_CONFIGS = [ datasets.BuilderConfig(version=VERSION, description="Wikipedia NQ train/dev/test datasets"), ] def _info(self): features = datasets.Features({ 'query_id': datasets.Value('string'), 'query': datasets.Value('string'), 'query-inject-det': datasets.Value('string'), 'query-stem': datasets.Value('string'), 'query-synonym': datasets.Value('string'), 'query-random-char-swap': datasets.Value('string'), 'query-char-keyboard': datasets.Value('string'), 'query-paraphrase': datasets.Value('string'), 'query-reorder-words': datasets.Value('string'), 'query-backtranslation': datasets.Value('string'), 'query-char-delete': datasets.Value('string'), 'query-lemmatize': datasets.Value('string') }) return datasets.DatasetInfo( # This is the description that will appear on the datasets page. description=_DESCRIPTION, # This defines the different columns of the dataset and their types features=features, # Here we define them above because they are different between the two configurations supervised_keys=None, # Homepage of the dataset for documentation homepage="", # License for the dataset if available license="", # Citation for the dataset citation=_CITATION, ) def _split_generators(self, dl_manager): if self.config.data_files: downloaded_files = self.config.data_files else: downloaded_files = dl_manager.download_and_extract(_DATASET_URLS) splits = [ datasets.SplitGenerator( name=split, gen_kwargs={ "files": [downloaded_files[split]] if isinstance(downloaded_files[split], str) else downloaded_files[split], }, ) for split in downloaded_files ] return splits def _generate_examples(self, files): """Yields examples.""" for filepath in files: with open(filepath, encoding="utf-8") as f: for line in f: data = json.loads(line) if data.get('query-stem') is None: data['query-stem'] = data['query'] if data.get('query-lemmatize') is None: data['query-lemmatize'] = data['query'] if data.get('query-char-delete') is None: data['query-char-delete'] = data['query'] if data.get('query-char-keyboard') is None: data['query-random-char-swap'] = data['query'] if data.get('query-inject-det') is None: data['query-inject-det'] = data['query'] if data.get('query-synonym') is None: data['query-synonym'] = data['query'] if data.get('query-char-keyboard') is None: data['query-char-keyboard'] = data['query'] if data.get('query-paraphrase') is None: data['query-paraphrase'] = data['query'] if data.get('query-reorder-words') is None: data['query-reorder-words'] = data['query'] if data.get('query-backtranslation') is None: data['query-backtranslation'] = data['query'] yield data['query_id'], data