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  1. cfq.py +0 -167
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- # coding=utf-8
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- # Copyright 2020 The TensorFlow Datasets Authors and the HuggingFace Datasets Authors.
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- #
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- # Licensed under the Apache License, Version 2.0 (the "License");
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- # you may not use this file except in compliance with the License.
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- # You may obtain a copy of the License at
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- #
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- # http://www.apache.org/licenses/LICENSE-2.0
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- #
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- # Unless required by applicable law or agreed to in writing, software
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- # distributed under the License is distributed on an "AS IS" BASIS,
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- # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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- # See the License for the specific language governing permissions and
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- # limitations under the License.
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-
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- # Lint as: python3
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- """CFQ (Compositional Freebase Questions) dataset."""
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-
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-
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- import json
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- import re
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-
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- import datasets
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-
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-
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- logger = datasets.logging.get_logger(__name__)
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-
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-
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- _HOMEPAGE = "https://github.com/google-research/google-research/tree/master/cfq"
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-
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- _LICENSE = "CC BY 4.0"
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-
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- _CITATION = """
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- @inproceedings{Keysers2020,
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- title={Measuring Compositional Generalization: A Comprehensive Method on
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- Realistic Data},
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- author={Daniel Keysers and Nathanael Sch\"{a}rli and Nathan Scales and
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- Hylke Buisman and Daniel Furrer and Sergii Kashubin and
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- Nikola Momchev and Danila Sinopalnikov and Lukasz Stafiniak and
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- Tibor Tihon and Dmitry Tsarkov and Xiao Wang and Marc van Zee and
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- Olivier Bousquet},
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- booktitle={ICLR},
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- year={2020},
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- url={https://arxiv.org/abs/1912.09713.pdf},
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- }
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- """
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-
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- _DESCRIPTION = """
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- The CFQ dataset (and it's splits) for measuring compositional generalization.
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-
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- See https://arxiv.org/abs/1912.09713.pdf for background.
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-
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- Example usage:
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- data = datasets.load_dataset('cfq/mcd1')
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- """
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-
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- _DATA_URL = "https://storage.googleapis.com/cfq_dataset/cfq.tar.gz"
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-
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-
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- class CfqConfig(datasets.BuilderConfig):
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- """BuilderConfig for CFQ splits."""
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-
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- def __init__(self, name, directory="splits", **kwargs):
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- """BuilderConfig for CFQ.
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-
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- Args:
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- name: Unique name of the split.
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- directory: Which subdirectory to read the split from.
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- **kwargs: keyword arguments forwarded to super.
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- """
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- # Version history:
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- super(CfqConfig, self).__init__(
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- name=name, version=datasets.Version("1.0.1"), description=_DESCRIPTION, **kwargs
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- )
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- self.splits_path = f"cfq/{directory}/{name}.json"
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-
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-
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- _QUESTION = "question"
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- _QUERY = "query"
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- _QUESTION_FIELD = "questionPatternModEntities"
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- _QUERY_FIELD = "sparqlPatternModEntities"
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-
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-
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- class Cfq(datasets.GeneratorBasedBuilder):
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- """CFQ task / splits."""
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-
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- BUILDER_CONFIGS = [
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- CfqConfig(name="mcd1"),
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- CfqConfig(name="mcd2"),
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- CfqConfig(name="mcd3"),
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- CfqConfig(name="question_complexity_split"),
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- CfqConfig(name="question_pattern_split"),
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- CfqConfig(name="query_complexity_split"),
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- CfqConfig(name="query_pattern_split"),
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- CfqConfig(name="random_split"),
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- ]
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-
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- def _info(self):
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- return datasets.DatasetInfo(
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- description=_DESCRIPTION,
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- features=datasets.Features(
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- {
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- _QUESTION: datasets.Value("string"),
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- _QUERY: datasets.Value("string"),
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- }
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- ),
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- supervised_keys=(_QUESTION, _QUERY),
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- homepage=_HOMEPAGE,
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- license=_LICENSE,
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- citation=_CITATION,
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- )
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-
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- def _split_generators(self, dl_manager):
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- """Returns SplitGenerators."""
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- archive_path = dl_manager.download(_DATA_URL)
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- return [
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- datasets.SplitGenerator(
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- name=split,
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- gen_kwargs={
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- "data_files": dl_manager.iter_archive(archive_path),
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- "split_id": f"{split}Idxs",
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- },
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- )
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- for split in [datasets.Split.TRAIN, datasets.Split.TEST]
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- ]
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-
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- def _scrub_json(self, content):
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- """Reduce JSON by filtering out only the fields of interest."""
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- # Loading of json data with the standard Python library is very inefficient:
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- # For the 4GB dataset file it requires more than 40GB of RAM and takes 3min.
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- # There are more efficient libraries but in order to avoid additional
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- # dependencies we use a simple (perhaps somewhat brittle) regexp to reduce
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- # the content to only what is needed.
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- question_regex = re.compile(r'("%s":\s*"[^"]*")' % _QUESTION_FIELD)
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- query_regex = re.compile(r'("%s":\s*"[^"]*")' % _QUERY_FIELD)
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- question_match = None
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- for line in content:
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- line = line.decode("utf-8")
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- if not question_match:
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- question_match = question_regex.match(line)
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- else:
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- query_match = query_regex.match(line)
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- if query_match:
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- yield json.loads("{" + question_match.group(1) + "," + query_match.group(1) + "}")
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- question_match = None
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-
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- def _generate_examples(self, data_files, split_id):
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- """Yields examples."""
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- samples_path = "cfq/dataset.json"
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- for path, file in data_files:
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- if path == self.config.splits_path:
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- splits = json.load(file)[split_id]
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- elif path == samples_path:
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- # The samples_path is the last path inside the archive
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- generator = enumerate(self._scrub_json(file))
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- samples = {}
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- splits_set = set(splits)
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- for split_idx in splits:
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- if split_idx in samples:
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- sample = samples.pop(split_idx)
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- else:
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- for sample_idx, sample in generator:
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- if sample_idx == split_idx:
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- break
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- elif sample_idx in splits_set:
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- samples[sample_idx] = sample
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- yield split_idx, {_QUESTION: sample[_QUESTION_FIELD], _QUERY: sample[_QUERY_FIELD]}