Convert dataset to Parquet (#4)

- Convert dataset to Parquet (2acdbe6f70432a9964b534280d3d21686641c6c3)
- Delete loading script (0aeb8208f9e7a34997495fb1fd1e237ba48c9b11)

README.md

@@ -23,16 +23,25 @@ dataset_info:
     dtype: string
   splits:
   - name: train
-    num_bytes: 1072874
+    num_bytes: 1069679
     num_examples: 1941
   - name: test
-    num_bytes: 307588
+    num_bytes: 306655
     num_examples: 552
   - name: validation
-    num_bytes: 154308
+    num_bytes: 153817
     num_examples: 278
-  download_size: 631370
-  dataset_size: 1534770
+  download_size: 487676
+  dataset_size: 1530151
+configs:
+- config_name: default
+  data_files:
+  - split: train
+    path: data/train-*
+  - split: test
+    path: data/test-*
+  - split: validation
+    path: data/validation-*
 ---
 
 # Dataset Card for "quarel"

data/test-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b912daa32df88afec29bbdfb01529c2bfaf232792cccfe35fdcc74e8785c4e5a
+size 104240

data/train-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d6c5e13b16a58857d2c04cf9af0e290bab4c3f46257eafae241b2186ba4bb19d
+size 326198

data/validation-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f6d294cb57b167ae8e9e0e1ac34a4aae801feda0aac83765bb6117a0b7ef294d
+size 57238

quarel.py

@@ -1,102 +0,0 @@
-"""TODO(quarel): Add a description here."""
-
-
-import json
-import os
-
-import datasets
-
-
-# TODO(quarel): BibTeX citation
-_CITATION = """\
-@inproceedings{quarel_v1,
-    title={QuaRel: A Dataset and Models for Answering Questions about Qualitative Relationships},
-    author={Oyvind Tafjord, Peter Clark, Matt Gardner, Wen-tau Yih, Ashish Sabharwal},
-    year={2018},
-    journal={arXiv:1805.05377v1}
-}
-"""
-
-# TODO(quarel):
-_DESCRIPTION = """
-QuaRel is a crowdsourced dataset of 2771 multiple-choice story questions, including their logical forms.
-"""
-_URL = "https://s3-us-west-2.amazonaws.com/ai2-website/data/quarel-dataset-v1-nov2018.zip"
-
-
-class Quarel(datasets.GeneratorBasedBuilder):
-    """TODO(quarel): Short description of my dataset."""
-
-    # TODO(quarel): Set up version.
-    VERSION = datasets.Version("0.1.0")
-
-    def _info(self):
-        # TODO(quarel): Specifies the datasets.DatasetInfo object
-        return datasets.DatasetInfo(
-            # This is the description that will appear on the datasets page.
-            description=_DESCRIPTION,
-            # datasets.features.FeatureConnectors
-            features=datasets.Features(
-                {
-                    # These are the features of your dataset like images, labels ...
-                    "id": datasets.Value("string"),
-                    "answer_index": datasets.Value("int32"),
-                    "logical_forms": datasets.features.Sequence(datasets.Value("string")),
-                    "logical_form_pretty": datasets.Value("string"),
-                    "world_literals": datasets.features.Sequence(
-                        {"world1": datasets.Value("string"), "world2": datasets.Value("string")}
-                    ),
-                    "question": datasets.Value("string"),
-                }
-            ),
-            # If there's a common (input, target) tuple from the features,
-            # specify them here. They'll be used if as_supervised=True in
-            # builder.as_dataset.
-            supervised_keys=None,
-            # Homepage of the dataset for documentation
-            homepage="https://allenai.org/data/quarel",
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        """Returns SplitGenerators."""
-        # TODO(quarel): Downloads the data and defines the splits
-        # dl_manager is a datasets.download.DownloadManager that can be used to
-        # download and extract URLs
-        dl_dir = dl_manager.download_and_extract(_URL)
-        data_dir = os.path.join(dl_dir, "quarel-dataset-v1")
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                # These kwargs will be passed to _generate_examples
-                gen_kwargs={"filepath": os.path.join(data_dir, "quarel-v1-train.jsonl")},
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.TEST,
-                # These kwargs will be passed to _generate_examples
-                gen_kwargs={"filepath": os.path.join(data_dir, "quarel-v1-test.jsonl")},
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.VALIDATION,
-                # These kwargs will be passed to _generate_examples
-                gen_kwargs={"filepath": os.path.join(data_dir, "quarel-v1-dev.jsonl")},
-            ),
-        ]
-
-    def _generate_examples(self, filepath):
-        """Yields examples."""
-        # TODO(quarel): Yields (key, example) tuples from the dataset
-        with open(filepath, encoding="utf-8") as f:
-            for id_, row in enumerate(f):
-                data = json.loads(row)
-                yield id_, {
-                    "id": data["id"],
-                    "answer_index": data["answer_index"],
-                    "logical_forms": data["logical_forms"],
-                    "world_literals": {
-                        "world1": [data["world_literals"]["world1"]],
-                        "world2": [data["world_literals"]["world2"]],
-                    },
-                    "logical_form_pretty": data["logical_form_pretty"],
-                    "question": data["question"],
-                }