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# coding=utf-8
# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
#
# 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.
"""test_data dataset."""
import csv
import datasets
from datasets.tasks import TextClassification
_DESCRIPTION = """"""
_HOMEPAGE = "https://github.com/freeziyou/live_stream_dataset"
_LICENSE = "Creative Commons Attribution 4.0 International"
_TRAIN_DOWNLOAD_URL = "https://raw.githubusercontent.com/freeziyou/live_stream_dataset/main/train.csv"
# _TRAIN_DOWNLOAD_URL = "https://gitee.com/didi233/test_date_gitee/raw/master/train.csv"
_TEST_DOWNLOAD_URL = "https://raw.githubusercontent.com/freeziyou/live_stream_dataset/main/test.csv"
# _TEST_DOWNLOAD_URL = "https://gitee.com/didi233/test_date_gitee/raw/master/test.csv"
class live_stream_dataset_huggingface(datasets.GeneratorBasedBuilder):
"""live_stream_dataset_huggingface."""
VERSION = datasets.Version("1.2.0")
def _info(self):
features = datasets.Features(
{
"text": datasets.Value("string"),
"label": datasets.features.ClassLabel(
names=[
"none",
"like",
"unlike",
"hope",
"questioning",
"express_surprise",
"normal_interaction",
"express_sad",
"tease",
"meme",
"express_abashed"
])
}
)
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=features,
supervised_keys=None,
homepage=_HOMEPAGE,
license=_LICENSE,
task_templates=[TextClassification(text_column="text", label_column="label")],
)
def _split_generators(self, dl_manager):
"""Returns SplitGenerators."""
train_path = dl_manager.download_and_extract(_TRAIN_DOWNLOAD_URL)
test_path = dl_manager.download_and_extract(_TEST_DOWNLOAD_URL)
return [
datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": train_path}),
datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": test_path}),
]
def _generate_examples(self, filepath):
"""Yields examples as (key, example) tuples."""
with open(filepath, encoding="utf-8") as f:
csv_reader = csv.reader(f, quotechar='"', delimiter=",", quoting=csv.QUOTE_ALL, skipinitialspace=True)
# call next to skip header
next(csv_reader)
for id_, row in enumerate(csv_reader):
text, label = row
yield id_, {"text": text, "label": label}
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