Datasets:
Tasks:
Question Answering
Modalities:
Text
Formats:
parquet
Sub-tasks:
multiple-choice-qa
Size:
100K - 1M
ArXiv:
License:
Update files from the datasets library (from 1.16.0)
Browse filesRelease notes: https://github.com/huggingface/datasets/releases/tag/1.16.0
README.md
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@@ -1,4 +1,5 @@
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---
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annotations_creators:
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- found
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language_creators:
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---
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pretty_name: EXAMS
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annotations_creators:
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- found
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language_creators:
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exams.py
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@@ -16,7 +16,6 @@
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import json
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import os
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import datasets
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@@ -196,14 +195,12 @@ class Exams(datasets.GeneratorBasedBuilder):
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def _split_generators(self, dl_manager):
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"""Returns SplitGenerators."""
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-
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if self.config.name == "alignments":
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return [
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datasets.SplitGenerator(
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name="full",
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gen_kwargs={
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"filepath": data_dir["alignments"],
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},
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),
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]
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elif self.config.name in ["multilingual", "multilingual_with_para"]:
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@@ -211,9 +208,8 @@ class Exams(datasets.GeneratorBasedBuilder):
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datasets.SplitGenerator(
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name=spl_enum,
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gen_kwargs={
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"filepath":
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-
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),
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},
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)
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for spl, spl_enum in [
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@@ -227,9 +223,8 @@ class Exams(datasets.GeneratorBasedBuilder):
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datasets.SplitGenerator(
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name=datasets.Split.TEST,
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gen_kwargs={
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"filepath":
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-
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),
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},
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),
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]
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@@ -238,10 +233,8 @@ class Exams(datasets.GeneratorBasedBuilder):
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datasets.SplitGenerator(
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name=spl_enum,
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gen_kwargs={
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"filepath":
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f"{spl}_{self.config.lang}{self.config.with_para}.jsonl",
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)
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},
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)
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for spl, spl_enum in [
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]
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]
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-
def _generate_examples(self, filepath):
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f = open(filepath, encoding="utf-8")
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if self.config.name == "alignments":
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-
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-
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-
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else:
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for
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-
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-
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import json
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import datasets
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def _split_generators(self, dl_manager):
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"""Returns SplitGenerators."""
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archives = dl_manager.download(_URLs)
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if self.config.name == "alignments":
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return [
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datasets.SplitGenerator(
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name="full",
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gen_kwargs={"filepath": archives["alignments"]},
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),
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]
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elif self.config.name in ["multilingual", "multilingual_with_para"]:
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datasets.SplitGenerator(
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name=spl_enum,
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gen_kwargs={
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"filepath": f"{spl}{self.config.with_para}.jsonl",
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"files": dl_manager.iter_archive(archives[f"{self.config.name}_{spl}"]),
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},
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)
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for spl, spl_enum in [
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datasets.SplitGenerator(
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name=datasets.Split.TEST,
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gen_kwargs={
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"filepath": f"test{self.config.with_para}.jsonl",
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"files": dl_manager.iter_archive(archives[self.config.name]),
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},
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),
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]
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datasets.SplitGenerator(
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name=spl_enum,
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gen_kwargs={
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"filepath": f"{spl}_{self.config.lang}{self.config.with_para}.jsonl",
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"files": dl_manager.iter_archive(archives[f"{self.config.name}_{spl}"]),
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},
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)
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for spl, spl_enum in [
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]
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]
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def _generate_examples(self, filepath, files=None):
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if self.config.name == "alignments":
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with open(filepath, encoding="utf-8") as f:
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for id_, line in enumerate(f):
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line_dict = json.loads(line.strip())
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in_id, out_list = list(line_dict.items())[0]
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yield id_, {"source_id": in_id, "target_id_list": out_list}
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else:
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for path, f in files:
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if path == filepath:
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for id_, line in enumerate(f):
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line_dict = json.loads(line.strip())
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for choice in line_dict["question"]["choices"]:
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choice["para"] = choice.get("para", "")
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yield id_, line_dict
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break
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