Convert dataset to Parquet (#4)

- Convert dataset to Parquet (63fd7944d5e89a9bb1b6d5576f8c4073688da0a6)
- Add mcd2 data files (0bf00d661039c696cac750a0b39778c4ce4c6c71)
- Add mcd3 data files (739c8ad5bc908b420652805ed0094608f210e6fd)
- Add query_complexity_split data files (b7e70403afeb85ab7e142b80176d0ed5e090bfce)
- Add query_pattern_split data files (e297eb9c4cfc9806459c9a3ed1bbb8267bba7682)
- Add question_complexity_split data files (f9d63f8b0c12c73e68bf91d8551fefc6c3c92014)
- Add question_pattern_split data files (cf409dc63b98ed3184f5c2f0c877988f57a5be3c)
- Add random_split data files (83737e52c2ac7fbc075d14209bbd8091303ed92a)
- Delete loading script (14dd78b1e7818255f3c65eda48d1b12fa5fa8a1e)

README.md

@@ -9,7 +9,6 @@ license:
 - cc-by-4.0
 multilinguality:
 - monolingual
-pretty_name: Compositional Freebase Questions
 size_categories:
 - 100K<n<1M
 source_datasets:
@@ -21,6 +20,7 @@ task_ids:
 - open-domain-qa
 - closed-domain-qa
 paperswithcode_id: cfq
+pretty_name: Compositional Freebase Questions
 tags:
 - compositionality
 dataset_info:
@@ -37,7 +37,7 @@ dataset_info:
   - name: test
     num_bytes: 5446503
     num_examples: 11968
-  download_size: 267599061
+  download_size: 8570962
   dataset_size: 42855309
 - config_name: mcd2
   features:
@@ -52,7 +52,7 @@ dataset_info:
   - name: test
     num_bytes: 5314019
     num_examples: 11968
-  download_size: 267599061
+  download_size: 8867866
   dataset_size: 44738676
 - config_name: mcd3
   features:
@@ -67,9 +67,9 @@ dataset_info:
   - name: test
     num_bytes: 5244503
     num_examples: 11968
-  download_size: 267599061
+  download_size: 8578142
   dataset_size: 43560848
-- config_name: question_complexity_split
+- config_name: query_complexity_split
   features:
   - name: question
     dtype: string
@@ -77,14 +77,14 @@ dataset_info:
     dtype: string
   splits:
   - name: train
-    num_bytes: 39989433
-    num_examples: 98999
+    num_bytes: 40270175
+    num_examples: 100654
   - name: test
-    num_bytes: 5781561
-    num_examples: 10340
-  download_size: 267599061
-  dataset_size: 45770994
-- config_name: question_pattern_split
+    num_bytes: 5634924
+    num_examples: 9512
+  download_size: 9303588
+  dataset_size: 45905099
+- config_name: query_pattern_split
   features:
   - name: question
     dtype: string
@@ -92,14 +92,14 @@ dataset_info:
     dtype: string
   splits:
   - name: train
-    num_bytes: 41217350
-    num_examples: 95654
+    num_bytes: 40811284
+    num_examples: 94600
   - name: test
-    num_bytes: 5179936
-    num_examples: 11909
-  download_size: 267599061
-  dataset_size: 46397286
-- config_name: query_complexity_split
+    num_bytes: 5268358
+    num_examples: 12589
+  download_size: 9387759
+  dataset_size: 46079642
+- config_name: question_complexity_split
   features:
   - name: question
     dtype: string
@@ -107,14 +107,14 @@ dataset_info:
     dtype: string
   splits:
   - name: train
-    num_bytes: 40270175
-    num_examples: 100654
+    num_bytes: 39989433
+    num_examples: 98999
   - name: test
-    num_bytes: 5634924
-    num_examples: 9512
-  download_size: 267599061
-  dataset_size: 45905099
-- config_name: query_pattern_split
+    num_bytes: 5781561
+    num_examples: 10340
+  download_size: 9255771
+  dataset_size: 45770994
+- config_name: question_pattern_split
   features:
   - name: question
     dtype: string
@@ -122,13 +122,13 @@ dataset_info:
     dtype: string
   splits:
   - name: train
-    num_bytes: 40811284
-    num_examples: 94600
+    num_bytes: 41217350
+    num_examples: 95654
   - name: test
-    num_bytes: 5268358
-    num_examples: 12589
-  download_size: 267599061
-  dataset_size: 46079642
+    num_bytes: 5179936
+    num_examples: 11909
+  download_size: 9482990
+  dataset_size: 46397286
 - config_name: random_split
   features:
   - name: question
@@ -142,8 +142,57 @@ dataset_info:
   - name: test
     num_bytes: 5164923
     num_examples: 11967
-  download_size: 267599061
+  download_size: 9533853
   dataset_size: 46444141
+configs:
+- config_name: mcd1
+  data_files:
+  - split: train
+    path: mcd1/train-*
+  - split: test
+    path: mcd1/test-*
+- config_name: mcd2
+  data_files:
+  - split: train
+    path: mcd2/train-*
+  - split: test
+    path: mcd2/test-*
+- config_name: mcd3
+  data_files:
+  - split: train
+    path: mcd3/train-*
+  - split: test
+    path: mcd3/test-*
+- config_name: query_complexity_split
+  data_files:
+  - split: train
+    path: query_complexity_split/train-*
+  - split: test
+    path: query_complexity_split/test-*
+- config_name: query_pattern_split
+  data_files:
+  - split: train
+    path: query_pattern_split/train-*
+  - split: test
+    path: query_pattern_split/test-*
+- config_name: question_complexity_split
+  data_files:
+  - split: train
+    path: question_complexity_split/train-*
+  - split: test
+    path: question_complexity_split/test-*
+- config_name: question_pattern_split
+  data_files:
+  - split: train
+    path: question_pattern_split/train-*
+  - split: test
+    path: question_pattern_split/test-*
+- config_name: random_split
+  data_files:
+  - split: train
+    path: random_split/train-*
+  - split: test
+    path: random_split/test-*
 ---
 
 # Dataset Card for "cfq"

cfq.py

@@ -1,167 +0,0 @@
-# coding=utf-8
-# Copyright 2020 The TensorFlow Datasets Authors and the HuggingFace Datasets Authors.
-#
-# 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
-"""CFQ (Compositional Freebase Questions) dataset."""
-
-
-import json
-import re
-
-import datasets
-
-
-logger = datasets.logging.get_logger(__name__)
-
-
-_HOMEPAGE = "https://github.com/google-research/google-research/tree/master/cfq"
-
-_LICENSE = "CC BY 4.0"
-
-_CITATION = """
-@inproceedings{Keysers2020,
-  title={Measuring Compositional Generalization: A Comprehensive Method on
-         Realistic Data},
-  author={Daniel Keysers and Nathanael Sch\"{a}rli and Nathan Scales and
-          Hylke Buisman and Daniel Furrer and Sergii Kashubin and
-          Nikola Momchev and Danila Sinopalnikov and Lukasz Stafiniak and
-          Tibor Tihon and Dmitry Tsarkov and Xiao Wang and Marc van Zee and
-          Olivier Bousquet},
-  booktitle={ICLR},
-  year={2020},
-  url={https://arxiv.org/abs/1912.09713.pdf},
-}
-"""
-
-_DESCRIPTION = """
-The CFQ dataset (and it's splits) for measuring compositional generalization.
-
-See https://arxiv.org/abs/1912.09713.pdf for background.
-
-Example usage:
-data = datasets.load_dataset('cfq/mcd1')
-"""
-
-_DATA_URL = "https://storage.googleapis.com/cfq_dataset/cfq.tar.gz"
-
-
-class CfqConfig(datasets.BuilderConfig):
-    """BuilderConfig for CFQ splits."""
-
-    def __init__(self, name, directory="splits", **kwargs):
-        """BuilderConfig for CFQ.
-
-        Args:
-          name: Unique name of the split.
-          directory: Which subdirectory to read the split from.
-          **kwargs: keyword arguments forwarded to super.
-        """
-        # Version history:
-        super(CfqConfig, self).__init__(
-            name=name, version=datasets.Version("1.0.1"), description=_DESCRIPTION, **kwargs
-        )
-        self.splits_path = f"cfq/{directory}/{name}.json"
-
-
-_QUESTION = "question"
-_QUERY = "query"
-_QUESTION_FIELD = "questionPatternModEntities"
-_QUERY_FIELD = "sparqlPatternModEntities"
-
-
-class Cfq(datasets.GeneratorBasedBuilder):
-    """CFQ task / splits."""
-
-    BUILDER_CONFIGS = [
-        CfqConfig(name="mcd1"),
-        CfqConfig(name="mcd2"),
-        CfqConfig(name="mcd3"),
-        CfqConfig(name="question_complexity_split"),
-        CfqConfig(name="question_pattern_split"),
-        CfqConfig(name="query_complexity_split"),
-        CfqConfig(name="query_pattern_split"),
-        CfqConfig(name="random_split"),
-    ]
-
-    def _info(self):
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=datasets.Features(
-                {
-                    _QUESTION: datasets.Value("string"),
-                    _QUERY: datasets.Value("string"),
-                }
-            ),
-            supervised_keys=(_QUESTION, _QUERY),
-            homepage=_HOMEPAGE,
-            license=_LICENSE,
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        """Returns SplitGenerators."""
-        archive_path = dl_manager.download(_DATA_URL)
-        return [
-            datasets.SplitGenerator(
-                name=split,
-                gen_kwargs={
-                    "data_files": dl_manager.iter_archive(archive_path),
-                    "split_id": f"{split}Idxs",
-                },
-            )
-            for split in [datasets.Split.TRAIN, datasets.Split.TEST]
-        ]
-
-    def _scrub_json(self, content):
-        """Reduce JSON by filtering out only the fields of interest."""
-        # Loading of json data with the standard Python library is very inefficient:
-        # For the 4GB dataset file it requires more than 40GB of RAM and takes 3min.
-        # There are more efficient libraries but in order to avoid additional
-        # dependencies we use a simple (perhaps somewhat brittle) regexp to reduce
-        # the content to only what is needed.
-        question_regex = re.compile(r'("%s":\s*"[^"]*")' % _QUESTION_FIELD)
-        query_regex = re.compile(r'("%s":\s*"[^"]*")' % _QUERY_FIELD)
-        question_match = None
-        for line in content:
-            line = line.decode("utf-8")
-            if not question_match:
-                question_match = question_regex.match(line)
-            else:
-                query_match = query_regex.match(line)
-                if query_match:
-                    yield json.loads("{" + question_match.group(1) + "," + query_match.group(1) + "}")
-                    question_match = None
-
-    def _generate_examples(self, data_files, split_id):
-        """Yields examples."""
-        samples_path = "cfq/dataset.json"
-        for path, file in data_files:
-            if path == self.config.splits_path:
-                splits = json.load(file)[split_id]
-            elif path == samples_path:
-                # The samples_path is the last path inside the archive
-                generator = enumerate(self._scrub_json(file))
-                samples = {}
-                splits_set = set(splits)
-                for split_idx in splits:
-                    if split_idx in samples:
-                        sample = samples.pop(split_idx)
-                    else:
-                        for sample_idx, sample in generator:
-                            if sample_idx == split_idx:
-                                break
-                            elif sample_idx in splits_set:
-                                samples[sample_idx] = sample
-                    yield split_idx, {_QUESTION: sample[_QUESTION_FIELD], _QUERY: sample[_QUERY_FIELD]}

mcd1/test-00000-of-00001.parquet

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mcd1/train-00000-of-00001.parquet

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mcd2/test-00000-of-00001.parquet

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mcd2/train-00000-of-00001.parquet

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mcd3/test-00000-of-00001.parquet

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query_complexity_split/test-00000-of-00001.parquet

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