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import os
import pandas as pd
import datasets
class sato(datasets.GeneratorBasedBuilder):
"""The sato dataset"""
def _info(self):
features = datasets.Features(
{
"table_id": datasets.Value("string"),
"col_idx": datasets.Value("string"),
"label": datasets.Value("string"),
"label_id": datasets.Value("string"),
"data": datasets.Value("string"),
}
)
# datasets.value -- single value
# datasets.features.Sequence -- list
return datasets.DatasetInfo(
features=features
)
def _split_generators(self, dl_manager):
sato_data = "https://huggingface.co/datasets/shivangibithel/SATO/blob/main"
train_file1 = "msato_cv_0.csv"
train_file2 = "msato_cv_1.csv"
train_file3 = "msato_cv_2.csv"
dev_file = "msato_cv_3.csv"
test_file = "msato_cv_4.csv"
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
# These kwargs will be passed to _generate_examples
gen_kwargs={"main_filepath": os.path.join(sato_data, train_file1)},
),
datasets.SplitGenerator(
name=datasets.Split.TEST,
# These kwargs will be passed to _generate_examples
gen_kwargs={"main_filepath": os.path.join(sato_data, test_file)},
),
datasets.SplitGenerator(
name=datasets.Split.VALIDATION,
# These kwargs will be passed to _generate_examples
gen_kwargs={"main_filepath": os.path.join(sato_data, dev_file)},
),
]
def _generate_examples(self, main_filepath):
df = pd.read_csv(main_filepath, encoding="utf8", sep=",")
for ind in df.index:
table_id = df['table_id'][ind]
col_idx = df['col_idx'][ind]
label = df['class'][ind]
label_id = df['class_id'][ind]
data = df['data'][ind]
yield ind, {
"table_id": table_id,
"col_idx":col_idx,
"label": label,
"label_id": label_id,
"data": data,
} |