| import os |
| from pdb import set_trace |
|
|
| import datasets |
| import pandas as pd |
|
|
| _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("int64"), |
| "name": datasets.Value("string"), |
| "age": datasets.Value("int64"), |
| } |
| ) |
| elif self.config.name == "products": |
| features = datasets.Features( |
| { |
| "product_id": datasets.Value("int64"), |
| "name": datasets.Value("string"), |
| "price": datasets.Value("double"), |
| } |
| ) |
| 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 = dl_manager.manual_dir or "./" |
| data_dir = os.path.join(data_dir, self.config.name) |
| print(data_dir) |
| 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: |
| df = pd.read_csv(filepath, index_col=0) |
| for id_, item in df.iterrows(): |
| yield id_, item.to_dict() |