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import json
import os
import datasets
class ERRNewsConfig(datasets.BuilderConfig):
def __init__(self, data_url, features, **kwargs):
super().__init__(version=datasets.Version("1.0.0"), **kwargs)
self.features = features
self.data_url = data_url
class ERRNews(datasets.GeneratorBasedBuilder):
features = ["transcript", "summary", "id"]
data_url = "https://cs.taltech.ee/staff/heharm/AMIsum/"
BUILDER_CONFIGS = [
ERRNewsConfig(
name="full",
features=features,
data_url=data_url
)
]
DEFAULT_CONFIG_NAME = "full"
def _info(self):
features = datasets.Features(
{
"transcript": datasets.Value("string"),
"summary": datasets.Value("string"),
"id": datasets.Value("string"),
})
description = """\
AMI Summarization Dataset (AMIsum) is a meeting summarization dataset, consisting of meeting transcripts \
and abstract summaries from the AMI Corpus: https://groups.inf.ed.ac.uk/ami/corpus/.
"""
return datasets.DatasetInfo(
features=features,
description=description,
supervised_keys=None,
version=self.config.version,
)
def _split_generators(self, dl_manager):
"""Returns SplitGenerators."""
train = "train.json"
test = "test.json"
val = "val.json"
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={
"file_path": dl_manager.download(self.config.data_url + train),
},
),
datasets.SplitGenerator(
name=datasets.Split.VALIDATION,
gen_kwargs={
"file_path": dl_manager.download(self.config.data_url + val),
},
),
datasets.SplitGenerator(
name=datasets.Split.TEST,
gen_kwargs={
"file_path": dl_manager.download(self.config.data_url + test),
},
),
]
def create_dict(self, data):
res = dict()
for key in self.config.features:
res[key] = data[key]
return res
def _generate_examples(self, file_path):
with open(file_path) as f:
data = json.load(f)
for idx, transcript in enumerate(data["transcript"]):
id_ = data["id"][idx]
yield id_, {
"transcript": transcript,
"summary": data["summary"][idx],
"id": id_,
}
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