metric / dataset.py
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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 .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 .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 = {}
@property
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