Registration is open for TensorFlow Dev Summit 2020 Learn more

The BulkInferrer TFX Pipeline Component

The BulkInferrer TFX component performs offline batch processing on a model with unlabelled inference requests. The generated InferenceResult( tensorflow_serving.apis.prediction_log_pb2.PredictionLog) contains the original features and the prediction results.

BulkInferrer consumes:

  • A Trained model in SavedModel format.
  • Model validation result from ModelValidator component.
  • Unlabelled tf.Examples that contain features.

BulkInferrer emits: InferenceResult

Using the BulkInferrer Component

A BulkInferrer TFX component is used to perform batch inference on unlabelled tf.Examples. It is typically deployed after a ModelValidator component to perform inference with a validated model, or after a Trainer component to directly perform inference on exported model.

Typical code looks like this:

from tfx import components


bulk_inferrer = components.BulkInferrer(