tfx.v1.components.ExampleValidator

A TFX component to validate input examples.

tfx.v1.components.ExampleValidator(
    statistics: types.BaseChannel,
    schema: types.BaseChannel,
    exclude_splits: Optional[List[str]] = None
)

Used in the notebooks

Used in the tutorials
TFX Estimator Component Tutorial TFX Keras Component Tutorial Data validation using TFX Pipeline and TensorFlow Data Validation Feature Engineering using TFX Pipeline and TensorFlow Transform

The ExampleValidator component uses Tensorflow Data Validation to validate the statistics of some splits on input examples against a schema.

The ExampleValidator component identifies anomalies in training and serving data. The component can be configured to detect different classes of anomalies in the data. It can:

• perform validity checks by comparing data statistics against a schema that codifies expectations of the user.

Schema Based Example Validation The ExampleValidator component identifies any anomalies in the example data by comparing data statistics computed by the StatisticsGen component against a schema. The schema codifies properties which the input data is expected to satisfy, and is provided and maintained by the user.

Example

# Performs anomaly detection based on statistics and data schema.
validate_stats = ExampleValidator(
    statistics=statistics_gen.outputs['statistics'],
    schema=infer_schema.outputs['schema'])

Component outputs contains:

• anomalies: Channel of type standard_artifacts.ExampleAnomalies.

See the ExampleValidator guide for more details.

Args
statistics	A BaseChannel of type standard_artifacts.ExampleStatistics.
schema	A BaseChannel of type standard_artifacts.Schema. required
exclude_splits	Names of splits that the example validator should not validate. Default behavior (when exclude_splits is set to None) is excluding no splits.

Attributes
outputs	Component's output channel dict.