Download data.py from unitxt/data: direct link, hf CLI and curl.
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- Download file 3.27 kB
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https://huggingface.co/datasets/unitxt/data/resolve/46d1a239587a9d2b0bbcdaa35db85d42ebeff15c/data.py
- Command line
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hf download hf://datasets/unitxt/data@46d1a239587a9d2b0bbcdaa35db85d42ebeff15c/data.py
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curl -L -o data.py https://huggingface.co/datasets/unitxt/data/resolve/46d1a239587a9d2b0bbcdaa35db85d42ebeff15c/data.py
3.27 kB
| import datasets | |
| from ._version import __file__ as _ | |
| from .artifact import Artifact, UnitxtArtifactNotFoundError | |
| from .artifact import __file__ as _ | |
| from .artifact import fetch_artifact | |
| from .blocks import __file__ as _ | |
| from .card import __file__ as _ | |
| from .catalog import __file__ as _ | |
| from .collections import __file__ as _ | |
| from .common import __file__ as _ | |
| from .dataclass import __file__ as _ | |
| from .dict_utils import __file__ as _ | |
| from .file_utils import __file__ as _ | |
| from .fusion import __file__ as _ | |
| from .generator_utils import __file__ as _ | |
| from .hf_utils import __file__ as _ | |
| from .instructions import __file__ as _ | |
| from .load import __file__ as _ | |
| from .loaders import __file__ as _ | |
| from .metric import __file__ as _ | |
| from .metrics import __file__ as _ | |
| from .normalizers import __file__ as _ | |
| from .operator import __file__ as _ | |
| from .operators import __file__ as _ | |
| from .processors import __file__ as _ | |
| from .random_utils import __file__ as _ | |
| from .recipe import __file__ as _ | |
| from .register import __file__ as _ | |
| from .register import register_all_artifacts | |
| from .schema import __file__ as _ | |
| from .split_utils import __file__ as _ | |
| from .splitters import __file__ as _ | |
| from .stream import __file__ as _ | |
| from .task import __file__ as _ | |
| from .templates import __file__ as _ | |
| from .text_utils import __file__ as _ | |
| from .type_utils import __file__ as _ | |
| from .utils import __file__ as _ | |
| from .validate import __file__ as _ | |
| def fetch(artifact_name): | |
| try: | |
| artifact, _ = fetch_artifact(artifact_name) | |
| return artifact | |
| except UnitxtArtifactNotFoundError: | |
| return None | |
| def parse(query: str): | |
| """ | |
| Parses a query of the form 'key1=value1,key2=value2,...' into a dictionary. | |
| """ | |
| result = {} | |
| for kv in query.split(","): | |
| parts = kv.split("=") | |
| if parts[1].isdigit(): | |
| result[parts[0]] = int(parts[1]) | |
| elif parts[1].replace(".", "", 1).isdigit(): | |
| result[parts[0]] = float(parts[1]) | |
| result[parts[0]] = parts[1] | |
| return result | |
| class Dataset(datasets.GeneratorBasedBuilder): | |
| """TODO: Short description of my dataset.""" | |
| VERSION = datasets.Version("1.1.1") | |
| builder_configs = {} | |
| def generators(self): | |
| register_all_artifacts() | |
| if not hasattr(self, "_generators") or self._generators is None: | |
| recipe = fetch(self.config.name) | |
| if recipe is None: | |
| args = parse(self.config.name) | |
| if "type" not in args: | |
| args["type"] = "common_recipe" | |
| recipe = Artifact.from_dict(args) | |
| self._generators = recipe() | |
| return self._generators | |
| def _info(self): | |
| return datasets.DatasetInfo() | |
| def _split_generators(self, _): | |
| return [datasets.SplitGenerator(name=name, gen_kwargs={"split_name": name}) for name in self.generators.keys()] | |
| def _generate_examples(self, split_name): | |
| generator = self.generators[split_name] | |
| for i, row in enumerate(generator): | |
| yield i, row | |
| def _download_and_prepare(self, dl_manager, verification_mode, **prepare_splits_kwargs): | |
| result = super()._download_and_prepare(dl_manager, "no_checks", **prepare_splits_kwargs) | |
| return result | |