| | import os |
| |
|
| | import datasets |
| |
|
| | 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 .formats 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 _reset_env_local_catalogs, register_all_artifacts |
| | from .renderers import __file__ as _ |
| | from .schema 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 .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 _ |
| | from .version import __file__ as _ |
| | from .version import version |
| |
|
| | __default_recipe__ = "common_recipe" |
| |
|
| |
|
| | 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 = {} |
| | kvs = query.split(",") |
| | if len(kvs) == 0: |
| | raise ValueError( |
| | 'Illegal query: "{query}" should contain at least one assignment of the form: key1=value1,key2=value2' |
| | ) |
| | for kv in kvs: |
| | key_val = kv.split("=") |
| | if len(key_val) != 2 or len(key_val[0].strip()) == 0 or len(key_val[1].strip()) == 0: |
| | raise ValueError('Illegal query: "{query}" with wrong assignment "{kv}" should be of the form: key=value.') |
| | key, val = key_val |
| | if val.isdigit(): |
| | result[key] = int(val) |
| | elif val.replace(".", "", 1).isdigit(): |
| | result[key] = float(val) |
| | else: |
| | result[key] = val |
| |
|
| | return result |
| |
|
| |
|
| | def get_dataset_artifact(dataset_str): |
| | _reset_env_local_catalogs() |
| | register_all_artifacts() |
| | recipe = fetch(dataset_str) |
| | if recipe is None: |
| | args = parse(dataset_str) |
| | if "type" not in args: |
| | args["type"] = os.environ.get("UNITXT_DEFAULT_RECIPE", __default_recipe__) |
| | recipe = Artifact.from_dict(args) |
| | return recipe |
| |
|
| |
|
| | class Dataset(datasets.GeneratorBasedBuilder): |
| | """TODO: Short description of my dataset.""" |
| |
|
| | VERSION = datasets.Version(version) |
| | builder_configs = {} |
| |
|
| | @property |
| | def generators(self): |
| | if not hasattr(self, "_generators") or self._generators is None: |
| | try: |
| | from unitxt.dataset import ( |
| | get_dataset_artifact as get_dataset_artifact_installed, |
| | ) |
| |
|
| | unitxt_installed = True |
| | except ImportError: |
| | unitxt_installed = False |
| |
|
| | if unitxt_installed: |
| | print("Loading with installed unitxt library...") |
| | dataset = get_dataset_artifact_installed(self.config.name) |
| | else: |
| | print("Loading with installed unitxt library...") |
| | 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] |
| | 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 |
| |
|