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import os
import datasets
_CITATION = """\
Put your dataset citation here.
"""
_DESCRIPTION = """\
Description of your dataset goes here.
"""
_HOMEPAGE = "https://your-dataset-homepage.com"
_LICENSE = "License information goes here."
class Test(datasets.GeneratorBasedBuilder):
"""Your dataset description"""
BUILDER_CONFIGS = [
datasets.BuilderConfig(name="customers", version=datasets.Version("1.0.0"), description="This is subset A"),
datasets.BuilderConfig(name="products", version=datasets.Version("1.0.0"), description="This is subset B"),
]
def _info(self):
if self.config.name == "customers":
features = datasets.Features(
{
"customer_id": datasets.Value("string"),
"name": datasets.Value("string"),
"age": datasets.Value("int32"),
}
)
elif self.config.name == "products":
features = datasets.Features(
{
"product_id": datasets.Value("float32"),
"name": datasets.Value("string"),
"price": datasets.Value("float32"),
}
)
else:
raise ValueError(f"Unknown subset: {self.config.name}")
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=features,
supervised_keys=None,
homepage=_HOMEPAGE,
license=_LICENSE,
citation=_CITATION,
)
def _split_generators(self, dl_manager):
data_dir = os.path.join(self.config.data_dir, self.config.name)
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={"filepath": os.path.join(data_dir, "train.csv")},
),
datasets.SplitGenerator(
name=datasets.Split.VALIDATION,
gen_kwargs={"filepath": os.path.join(data_dir, "val.csv")},
),
datasets.SplitGenerator(
name=datasets.Split.TEST,
gen_kwargs={"filepath": os.path.join(data_dir, "test.csv")},
),
]
def _generate_examples(self, filepath):
with open(filepath, encoding="utf-8") as f:
for id_, line in enumerate(f):
# Example: Parsing CSV file based on the subset name
if self.config.name == "customers":
# Subset A expects three columns: feature_a1, feature_a2, label
feature_a1, feature_a2, label = line.strip().split(",")
yield id_, {
"customer_id": feature_a1,
"name": feature_a2,
"age": int(label),
}
elif self.config.name == "products":
# Subset B expects four columns: feature_b1, feature_b2, additional_info, label
feature_b1, feature_b2, additional_info = line.strip().split(",")
yield id_, {
"product_id": feature_b1,
"name": feature_b2,
"price": float(additional_info),
}
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