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Add gqa v0.0.1

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Files changed (5) hide show
  1. README.md +46 -0
  2. gqa.py +68 -0
  3. test.jsonl +3 -0
  4. train.jsonl +3 -0
  5. validation.jsonl +3 -0
README.md CHANGED
@@ -1,3 +1,49 @@
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  ---
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  license: mit
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  ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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  license: mit
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  ---
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+
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+ # GQA: Graph Question Answering
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+
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+ This dataset is asks models to make use of embedded graph for question answering.
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+
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+ An exmaple of the dataset is as follows:
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+
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+ ```json
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+ {
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+ "id": "mcwq-176119",
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+ "question": "What was executive produced by Scott Spiegel , Boaz Yakin , and Quentin Tarantino , executive produced by My Best Friend's Birthday 's editor and star , and edited by George Folsey",
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+ "answers": [
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+ "Hostel: Part II"
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+ ],
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+ "subgraph": {
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+ "entities": [
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+ "Q1401104",
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+ "Q887636",
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+ "Q1048645",
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+ "Q3772",
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+ "Q965826"
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+ ],
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+ "relations": [
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+ "P1431",
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+ "P1040"
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+ ],
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+ "adjacency": [[2, 1, 0],
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+ [2, 0, 3],
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+ [2, 0, 1],
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+ [2, 0, 4]
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+ ],
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+ "entity_labels": [
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+ "george folsey, jr.",
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+ "boaz yakin",
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+ "hostel: part ii",
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+ "quentin jerome tarantino",
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+ "scott spiegel"
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+ ],
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+ "relation_labels": [
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+ "showrunner",
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+ "film editor"
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+ ]
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+ },
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+ "sparql": "SELECT DISTINCT ?x0 WHERE {\n?x0 wdt:P1040 wd:Q1401104 .\n?x0 wdt:P1431 ?x1 .\n?x0 wdt:P1431 wd:Q3772 .\n?x0 wdt:P1431 wd:Q887636 .\n?x0 wdt:P1431 wd:Q965826 .\nwd:Q1480733 wdt:P161 ?x1 .\nwd:Q1480733 wdt:P1040 ?x1\n}"
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+ }
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+ ```
gqa.py ADDED
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+ import json
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+
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+ import datasets
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+ from datasets import Features, Sequence, Array2D, Value, DatasetDict
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+ from datasets.info import DatasetInfo
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+
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+
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+ _DESCRIPTION = """\
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+ GQA is a dataset containing 22M questions about visual scenes. \
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+ The questions are designed to be challenging, \
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+ i.e., they require compositional reasoning, \
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+ """
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+
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+ _URLS = {
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+ "train": "train.jsonl",
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+ "validation": "validation.jsonl",
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+ "test": "test.jsonl",
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+ }
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+
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+ class GQAConfig(datasets.BuilderConfig):
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+ """BuilderConfig for GQA."""
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+
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+ def __init__(self, **kwargs):
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+ """BuilderConfig for GQA.
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+ Args:
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+ **kwargs: keyword arguments forwarded to super.
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+ """
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+ super(GQAConfig, self).__init__(**kwargs)
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+
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+
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+ class GQA(datasets.GeneratorBasedBuilder):
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+ """GQA: A graph question answering dataset."""
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+ def _info(self) -> DatasetInfo:
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+ return DatasetInfo(
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+ description=_DESCRIPTION,
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+ features=Features(
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+ {
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+ "id": Value("string"),
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+ "question": Value("string"),
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+ "answers": Sequence(Value("string")),
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+ "sparql": Value("string"),
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+ "subgraph":
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+ {
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+ "entities": Sequence(Value("string")),
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+ "relations": Sequence(Value("string")),
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+ "adjacency": Array2D(shape=(None, 3), dtype='int64'),
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+ "entity_labels": Sequence(datasets.Value("string")),
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+ "relation_labels": Sequence(Value("string")),
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+ }
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+ }
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+ )
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+ )
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+
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+ def _split_generators(self, dl_manager: datasets.DownloadManager):
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+ downloaded_files = dl_manager.download_and_extract(_URLS)
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+
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+ return [
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+ datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["train"]}),
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+ datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": downloaded_files["validation"]}),
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+ datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": downloaded_files["test"]}),
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+ ]
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+
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+ def _generate_examples(self, filepath):
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+ with open(filepath, encoding="utf-8") as f:
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+ for row in f:
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+ sample = json.loads(row)
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+ id_ = sample["id"]
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+ yield id_, sample
test.jsonl ADDED
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+ size 2739517
train.jsonl ADDED
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+ size 32298864
validation.jsonl ADDED
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+ version https://git-lfs.github.com/spec/v1
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