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DataEval documentation

dataeval.types

dataeval.types¶

Data types used in DataEval.

Attributes¶

`StatsMap`	A mapping of metric names to their corresponding numpy array values.

Classes¶

`BaseCollectionMixin`	Mixin providing collection interface for Output subclasses.
`ClusterConfigMixin`	Configuration mixin for evaluators that use clustering.
`DatasetInfo`	Descriptive metadata for a dataset artifact.
`Evaluator`	Base class for all evaluators.
`EvaluatorConfig`	Base configuration class for all evaluators.
`ExecutionMetadata`	Metadata about the execution of the function or method for the Output class.
`ExtractorInfo`	Descriptor for a feature extractor as used to produce embeddings.
`MetadataJson`	Top-level schema for a `metadata.json` sidecar file.
`ModelInfo`	Descriptive metadata for a model artifact.
`ReprMixin`	Mixin providing consistent `__repr__` via `__init__` signature introspection.
`SelectionInfo`	Descriptor for a single `dataeval.selection` step.
`SourceIndex`	The indices of the source item, target and channel.
`TransformInfo`	Descriptor for a single image transform (typically a torchvision transform).

Output Classes¶

`DataFrameOutput`	An Output that wraps a Polars DataFrame and proxies its interface.
`DictOutput`	An Output that exposes its public instance attributes as a dictionary.
`MappingOutput`	An Output that wraps a mapping and proxies its interface.
`Output`	Base class for all evaluator output types.
`SequenceOutput`	An Output that wraps a sequence and proxies its interface.

Functions¶

`set_metadata`([fn, state])	Stamp Output classes with runtime metadata.

Module Contents¶

type dataeval.types.StatsMap = Mapping[str, NDArray[Any]]¶: A mapping of metric names to their corresponding numpy array values. Each array should have the same length along the first dimension, representing the number of samples.