import os import datasets from .api import __file__ as _ from .artifact import __file__ as _ from .augmentors import __file__ as _ from .benchmark import __file__ as _ from .blocks import __file__ as _ from .card import __file__ as _ from .catalog import __file__ as _ from .collections import __file__ as _ from .collections_operators import __file__ as _ from .dataclass import __file__ as _ from .dataset_utils import __file__ as _ from .dataset_utils import get_dataset_artifact from .deprecation_utils import __file__ as _ from .dialog_operators import __file__ as _ from .dict_utils import __file__ as _ from .error_utils import __file__ as _ from .eval_utils import __file__ as _ from .file_utils import __file__ as _ from .formats import __file__ as _ from .fusion import __file__ as _ from .generator_utils import __file__ as _ from .hf_utils import __file__ as _ from .hf_utils import verify_versions_compatibility from .image_operators import __file__ as _ from .inference import __file__ as _ from .instructions import __file__ as _ from .llm_as_judge import __file__ as _ from .loaders import __file__ as _ from .logging_utils import __file__ as _ from .logging_utils import get_logger from .metric import __file__ as _ from .metric_utils import __file__ as _ from .metrics import __file__ as _ from .normalizers import __file__ as _ from .operator import __file__ as _ from .operators import __file__ as _ from .parsing_utils 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 .schema import __file__ as _ from .serializers import __file__ as _ from .settings_utils import __file__ as _ from .settings_utils import get_constants from .span_lableing_operators import __file__ as _ from .split_utils import __file__ as _ from .splitters import __file__ as _ from .standard import __file__ as _ from .stream import __file__ as _ from .stream_operators import __file__ as _ from .string_operators import __file__ as _ from .struct_data_operators import __file__ as _ from .system_prompts 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 .types import __file__ as _ from .utils import __file__ as _ from .utils import is_package_installed from .validate import __file__ as _ from .version import __file__ as _ from .version import version logger = get_logger() constants = get_constants() class Dataset(datasets.GeneratorBasedBuilder): """TODO: Short description of my dataset.""" VERSION = constants.version @property def generators(self): if not hasattr(self, "_generators") or self._generators is None: if is_package_installed("unitxt"): verify_versions_compatibility("dataset", self.VERSION) from unitxt.dataset_utils import \ get_dataset_artifact as get_dataset_artifact_installed logger.info("Loading with installed unitxt library...") dataset = get_dataset_artifact_installed(self.config.name) else: logger.info("Loading with huggingface unitxt copy...") dataset = get_dataset_artifact(self.config.name) self._generators = dataset() 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] yield from enumerate(generator) def _download_and_prepare( self, dl_manager, verification_mode, **prepare_splits_kwargs ): return super()._download_and_prepare( dl_manager, "no_checks", **prepare_splits_kwargs )