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import json |
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import os.path |
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import datasets |
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_VERSION = "1.0.0" |
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_DESCRIPTION = "Deepset's germanDPR dataset made compatible with BEIR benchmark framework. One version contains " \ |
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"the original dataset 1:1 (but deduplicated) and the other dataset is furhter preprocessed. " \ |
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"See official dataset card for dataset usage with BEIR." |
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_SUBSETS = ["original-queries", "original-corpus", "original-qrels", |
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"processed-queries", "processed-corpus", "original-qrels"] |
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class GermanDPRBeir(datasets.GeneratorBasedBuilder): |
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BUILDER_CONFIGS = ( |
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[ |
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datasets.BuilderConfig( |
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name="original-queries", |
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description=f"BEIR queries created 1:1 but deduplicated from deepset/germanDPR.", |
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version=_VERSION, |
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), |
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datasets.BuilderConfig( |
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name="original-corpus", |
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description=f"BEIR corpus created 1:1 but deduplicated from deepset/germanDPR.", |
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version=_VERSION, |
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), |
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datasets.BuilderConfig( |
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name="original-qrels", |
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description=f"BEIR qrels for original version of deepset/germanDPR.", |
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version=_VERSION, |
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), |
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datasets.BuilderConfig( |
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name="processed-queries", |
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description=f"BEIR queries created, deduplicated and further text-processed from deepset/germanDPR.", |
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version=_VERSION, |
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), |
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datasets.BuilderConfig( |
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name="processed-corpus", |
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description=f"BEIR corpus created, deduplicated and further text-processed from deepset/germanDPR.", |
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version=_VERSION, |
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), |
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datasets.BuilderConfig( |
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name="processed-qrels", |
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description=f"BEIR qrels for processed version of deepset/germanDPR.", |
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version=_VERSION, |
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) |
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] |
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) |
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DEFAULT_CONFIG_NAME = _SUBSETS[0] |
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def _info(self): |
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name = self.config.name |
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if name.endswith("queries"): |
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features = { |
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"_id": datasets.Value("string"), |
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"text": datasets.Value("string") |
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} |
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elif name.endswith("corpus"): |
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features = { |
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"_id": datasets.Value("string"), |
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"title": datasets.Value("string"), |
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"text": datasets.Value("string"), |
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} |
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elif name.endswith("qrels"): |
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features = { |
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"query-id": datasets.Value("string"), |
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"corpus-id": datasets.Value("string"), |
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"score": datasets.Value("int32") |
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} |
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else: |
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raise ValueError(f'Unknown subset, choose from: {", ".join(_SUBSETS)}') |
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return datasets.DatasetInfo( |
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description=f"{_DESCRIPTION}\n{self.config.description}", |
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features=datasets.Features(features), |
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supervised_keys=None, |
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homepage="https://huggingface.co/datasets/PM-AI/germandpr-beir", |
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) |
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def _split_generators(self, dl_manager): |
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"""Returns SplitGenerators.""" |
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name = self.config.name |
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if name.startswith("original"): |
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dl_path = dl_manager.download_and_extract("https://huggingface.co/datasets/PM-AI/germandpr-beir/resolve/main/data/original.tar.gz") |
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elif name.startswith("processed"): |
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dl_path = dl_manager.download_and_extract("https://huggingface.co/datasets/PM-AI/germandpr-beir/resolve/main/data/processed.tar.gz") |
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else: |
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raise ValueError(f'Unknown subset, choose from: {", ".join(_SUBSETS)}') |
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type1, type2 = name.split("-") |
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if type2 in ["corpus", "queries"]: |
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return [ |
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datasets.SplitGenerator( |
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name=datasets.Split.TRAIN, |
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gen_kwargs={"filepath": os.path.join(dl_path, f'{type1}/train/{type2}.jsonl')}), |
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datasets.SplitGenerator( |
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name=datasets.Split.TEST, |
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gen_kwargs={"filepath": os.path.join(dl_path, f'{type1}/test/{type2}.jsonl')}) |
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] |
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elif type2 == "qrels": |
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return [ |
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datasets.SplitGenerator( |
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name=datasets.Split.TRAIN, |
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gen_kwargs={"filepath": os.path.join(dl_path, f'{type1}/train/qrels/train.tsv')}), |
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datasets.SplitGenerator( |
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name=datasets.Split.TEST, |
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gen_kwargs={"filepath": os.path.join(dl_path, f'{type1}/test/qrels/test.tsv')}) |
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] |
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else: |
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raise ValueError(f'Unknown subset, choose from: {", ".join(_SUBSETS)}') |
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def _generate_queries_data(self, filepath): |
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print("filepath: ", filepath) |
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with open(filepath, "r", encoding="utf-8") as in_file: |
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for idx, line in enumerate(in_file): |
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data = json.loads(line) |
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yield idx, data |
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def _generate_corpus_data(self, filepath): |
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with open(filepath, "r", encoding="utf-8") as in_file: |
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for idx, line in enumerate(in_file): |
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data = json.loads(line) |
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if "metadata" in data: |
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del data["metadata"] |
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yield idx, data |
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def _generate_qrel_data(self, filepath): |
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with open(filepath, "r", encoding="utf-8") as in_file: |
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in_file.readline() |
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for idx, line in enumerate(in_file): |
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qid, cid, score = line.rstrip().split("\t") |
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yield idx, {"query-id": qid, "corpus-id": cid, "score": score} |
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def _generate_examples(self, filepath): |
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"""Yields examples.""" |
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name = self.config.name |
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if name.endswith("queries"): |
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return self._generate_queries_data(filepath) |
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elif name.endswith("corpus"): |
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return self._generate_corpus_data(filepath) |
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elif name.endswith("qrels"): |
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return self._generate_qrel_data(filepath) |
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else: |
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raise ValueError(f'Unknown subset, choose from: {", ".join(_SUBSETS)}') |
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