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unicamp-dl
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quati

Tasks:
Question Answering
Languages:
Portuguese
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quati / quati.py
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eduseiti
Properly fixing the topics generation examples script.
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# 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
"""Quati dataset."""
import datasets
_CITATION = """
place holder
"""
_URL = "https://github.com/unicamp-dl/quati"
_DESCRIPTION = """
Quati ― Portuguese Native Information Retrieval dataset.
"""
QUATI_10M_DATASET_PARTS=["part_00", "part_01", "part_02", "part_03", "part_04"]
_URLS = {
"quati_1M_passages": "https://huggingface.co/datasets/unicamp-dl/quati/resolve/main/quati_1M.tsv",
"quati_10M_passages_part_00": "https://huggingface.co/datasets/unicamp-dl/quati/resolve/main/quati_10M_part_00.tsv",
"quati_10M_passages_part_01": "https://huggingface.co/datasets/unicamp-dl/quati/resolve/main/quati_10M_part_01.tsv",
"quati_10M_passages_part_02": "https://huggingface.co/datasets/unicamp-dl/quati/resolve/main/quati_10M_part_02.tsv",
"quati_10M_passages_part_03": "https://huggingface.co/datasets/unicamp-dl/quati/resolve/main/quati_10M_part_03.tsv",
"quati_10M_passages_part_04": "https://huggingface.co/datasets/unicamp-dl/quati/resolve/main/quati_10M_part_04.tsv",
"quati_1M_qrels": "https://huggingface.co/datasets/unicamp-dl/quati/resolve/main/qrels/quati_1M_qrels.txt",
"quati_10M_qrels": "https://huggingface.co/datasets/unicamp-dl/quati/resolve/main/qrels/quati_10M_qrels.txt",
"quati_test_topics": "https://huggingface.co/datasets/unicamp-dl/quati/resolve/main/topics/quati_test_topics.tsv",
"quati_all_topics": "https://huggingface.co/datasets/unicamp-dl/quati/resolve/main/topics/quati_all_topics.tsv"
}
def generate_examples_passages(filepath):
with open(filepath, encoding="utf-8") as input_file:
for (idx, line) in enumerate(input_file):
passage_id, passage = line.rstrip().split("\t")
features = {"passage_id": passage_id,
"passage": passage}
yield idx, features
def generate_examples_qrels(filepath):
with open(filepath, encoding="utf-8") as input_file:
for (idx, line) in enumerate(input_file):
query_id, _, passage_id, score = line.rstrip().split(" ")
features = {"query_id": int(query_id),
"passage_id": passage_id,
"score": int(score)}
yield idx, features
def generate_examples_topics(filepath):
with open(filepath, encoding="utf-8") as input_file:
for (idx, line) in enumerate(input_file):
if idx > 0:
query_id, query = line.rstrip().split("\t")
features = {"query_id": int(query_id),
"query": query}
yield idx - 1, features
class Quati(datasets.GeneratorBasedBuilder):
BUILDER_CONFIGS = (
[
datasets.BuilderConfig(
name="quati_10M_passages",
description="Portugues Brazilian passages, composing the complete Quati 10M dataset.",
version=datasets.Version("1.0.0"),
),
datasets.BuilderConfig(
name="quati_1M_passages",
description="Portugues Brazilian passages, composing the Quati 1M dataset.",
version=datasets.Version("1.0.0"),
),
datasets.BuilderConfig(
name="quati_10M_qrels",
description="Qrels for the annotated passages from the Quati 10M dataset.",
version=datasets.Version("1.0.0"),
),
datasets.BuilderConfig(
name="quati_1M_qrels",
description="Qrels for the annotated passages from the Quati 1M dataset.",
version=datasets.Version("1.0.0"),
),
datasets.BuilderConfig(
name="quati_test_topics",
description="50 test topics, corresponding to Quati dataset qrels.",
version=datasets.Version("1.0.0"),
),
datasets.BuilderConfig(
name="quati_all_topics",
description="All 200 topics created for the Quati dataset, including the 50 ones corresponding to Quati dataset qrels.",
version=datasets.Version("1.0.0"),
)
]
+ [
datasets.BuilderConfig(
name="quati_10M_passages_{}".format(which_part),
description="Portugues Brazilian passages, composing the Quati 10M dataset {}.".format(which_part),
version=datasets.Version("1.0.0"),
)
for which_part in QUATI_10M_DATASET_PARTS
]
)
DEFAULT_CONFIG_NAME = "quati_1M_passages"
def _info(self):
name = self.config.name
if "passages" in name:
features = {
"passage_id": datasets.Value("string"),
"passage": datasets.Value("string"),
}
elif name.endswith("qrels"):
features = {
"query_id": datasets.Value("int32"),
"passage_id": datasets.Value("string"),
"score": datasets.Value("int32"),
}
else:
features = {
"query_id": datasets.Value("int32"),
"query": datasets.Value("string"),
}
return datasets.DatasetInfo(
description=f"{_DESCRIPTION}\n{self.config.description}",
features=datasets.Features(features),
supervised_keys=None,
homepage=_URL,
citation=_CITATION,
)
def _split_generators(self, dl_manager):
"""Returns SplitGenerators."""
if self.config.name == "quati_10M_passages":
urls = {which_part: _URLS["quati_10M_passages_{}".format(which_part)] for which_part in QUATI_10M_DATASET_PARTS}
dl_path = dl_manager.download_and_extract(urls)
return [datasets.SplitGenerator(name="quati_10M_passages_{}".format(which_part), gen_kwargs={"filepath": dl_path[which_part]}) for which_part in QUATI_10M_DATASET_PARTS]
else:
url = _URLS[self.config.name]
dl_path = dl_manager.download_and_extract(url)
return (datasets.SplitGenerator(name=self.config.name, gen_kwargs={"filepath": dl_path}),)
def _generate_examples(self, filepath, args=None):
"""Yields examples."""
if "passages" in self.config.name:
return generate_examples_passages(filepath)
if self.config.name.endswith("qrels"):
return generate_examples_qrels(filepath)
else:
return generate_examples_topics(filepath)