Creates an Extractor for TFMAPredict.
tfma.extractors.PredictExtractor(
eval_shared_model: tfma.types.MaybeMultipleEvalSharedModels
,
desired_batch_size: Optional[int] = None,
materialize: Optional[bool] = True,
eval_config: Optional[tfma.EvalConfig
] = None
) -> tfma.extractors.Extractor
The extractor's PTransform loads and runs the eval_saved_model against every
example yielding a copy of the Extracts input with an additional extract
of type FeaturesPredictionsLabels keyed by
tfma.FEATURES_PREDICTIONS_LABELS_KEY unless eval_config is not None in which
case the features, predictions, and labels will be stored separately under
tfma.FEATURES_KEY, tfma.PREDICTIONS_KEY, and tfma.LABELS_KEY respectively.
Args |
eval_shared_model
|
Shared model (single-model evaluation) or list of shared
models (multi-model evaluation).
|
desired_batch_size
|
Optional batch size for batching in Aggregate.
|
materialize
|
True to call the FeatureExtractor to add MaterializedColumn
entries for the features, predictions, and labels.
|
eval_config
|
Eval config.
|
Returns |
Extractor for extracting features, predictions, labels, and other tensors
during predict.
|