test_model / logs /data.py
dd123's picture
Upload data.py
0111237
raw
history blame
2.61 kB
# 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.
"""BANKING77 dataset."""
import json
import datasets
from datasets.tasks import TextClassification
_TRAIN_DOWNLOAD_URL = "https://raw.kgithub.com/freeziyou/test_data/main/data/train/train.json"
_TEST_DOWNLOAD_URL = "https://raw.kgithub.com/freeziyou/test_data/main/data/test/test.json"
class Data(datasets.GeneratorBasedBuilder):
VERSION = datasets.Version("1.0.0")
def _info(self):
return datasets.DatasetInfo(
description=None,
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"
])
}
),
homepage=None,
citation=None,
)
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:
data = json.load(f)
for id_, row in data:
text, label = row['text'], row['label']
yield id_, {"text": text, "label": label}