Delete MetricInfo

src/datasets/__init__.py

@@ -22,7 +22,7 @@
 from .download import *
 from .features import *
 from .fingerprint import disable_caching, enable_caching, is_caching_enabled, set_caching_enabled
-from .info import DatasetInfo, MetricInfo
+from .info import DatasetInfo
 from .inspect import (
     get_dataset_config_info,
     get_dataset_config_names,

src/datasets/info.py

@@ -43,7 +43,7 @@
 from huggingface_hub import DatasetCard, DatasetCardData
 
 from . import config
-from .features import Features, Value
+from .features import Features
 from .splits import SplitDict
 from .tasks import TaskTemplate, task_template_from_dict
 from .utils import Version
@@ -506,88 +506,3 @@ def to_dataset_card_data(self, dataset_card_data: DatasetCardData) -> None:
                     dataset_info_yaml_dict.pop("config_name", None)
                     dataset_info_yaml_dict = {"config_name": config_name, **dataset_info_yaml_dict}
                     dataset_card_data["dataset_info"].append(dataset_info_yaml_dict)
-
-
-@dataclass
-class MetricInfo:
-    """Information about a metric.
-
-    `MetricInfo` documents a metric, including its name, version, and features.
-    See the constructor arguments and properties for a full list.
-
-    Note: Not all fields are known on construction and may be updated later.
-    """
-
-    # Set in the dataset scripts
-    description: str
-    citation: str
-    features: Features
-    inputs_description: str = dataclasses.field(default_factory=str)
-    homepage: str = dataclasses.field(default_factory=str)
-    license: str = dataclasses.field(default_factory=str)
-    codebase_urls: List[str] = dataclasses.field(default_factory=list)
-    reference_urls: List[str] = dataclasses.field(default_factory=list)
-    streamable: bool = False
-    format: Optional[str] = None
-
-    # Set later by the builder
-    metric_name: Optional[str] = None
-    config_name: Optional[str] = None
-    experiment_id: Optional[str] = None
-
-    def __post_init__(self):
-        if self.format is not None:
-            for key, value in self.features.items():
-                if not isinstance(value, Value):
-                    raise ValueError(
-                        f"When using 'numpy' format, all features should be a `datasets.Value` feature. "
-                        f"Here {key} is an instance of {value.__class__.__name__}"
-                    )
-
-    def write_to_directory(self, metric_info_dir, pretty_print=False):
-        """Write `MetricInfo` as JSON to `metric_info_dir`.
-        Also save the license separately in LICENCE.
-        If `pretty_print` is True, the JSON will be pretty-printed with the indent level of 4.
-
-        Example:
-
-        ```py
-        >>> from datasets import load_metric
-        >>> metric = load_metric("accuracy")
-        >>> metric.info.write_to_directory("/path/to/directory/")
-        ```
-        """
-        with open(os.path.join(metric_info_dir, config.METRIC_INFO_FILENAME), "w", encoding="utf-8") as f:
-            json.dump(asdict(self), f, indent=4 if pretty_print else None)
-
-        if self.license:
-            with open(os.path.join(metric_info_dir, config.LICENSE_FILENAME), "w", encoding="utf-8") as f:
-                f.write(self.license)
-
-    @classmethod
-    def from_directory(cls, metric_info_dir) -> "MetricInfo":
-        """Create MetricInfo from the JSON file in `metric_info_dir`.
-
-        Args:
-            metric_info_dir: `str` The directory containing the metadata file. This
-                should be the root directory of a specific dataset version.
-
-        Example:
-
-        ```py
-        >>> from datasets import MetricInfo
-        >>> metric_info = MetricInfo.from_directory("/path/to/directory/")
-        ```
-        """
-        logger.info(f"Loading Metric info from {metric_info_dir}")
-        if not metric_info_dir:
-            raise ValueError("Calling MetricInfo.from_directory() with undefined metric_info_dir.")
-
-        with open(os.path.join(metric_info_dir, config.METRIC_INFO_FILENAME), encoding="utf-8") as f:
-            metric_info_dict = json.load(f)
-        return cls.from_dict(metric_info_dict)
-
-    @classmethod
-    def from_dict(cls, metric_info_dict: dict) -> "MetricInfo":
-        field_names = {f.name for f in dataclasses.fields(cls)}
-        return cls(**{k: v for k, v in metric_info_dict.items() if k in field_names})