predictionClass property
The fully qualified name (module_name.class_name) of a class that implements the Predictor interface described in this reference field.
The module containing this class should be included in a package provided
to the [packageUris field](#Version.FIELDS.package_uris). Specify this
field if and only if you are deploying a [custom prediction routine
(beta)](/ml-engine/docs/tensorflow/custom-prediction-routines). If you
specify this field, you must set
[runtimeVersion](#Version.FIELDS.runtime_version) to 1.4 or greater
and you must set machineType to a [legacy (MLS1) machine
type](/ml-engine/docs/machine-types-online-prediction). The following
code sample provides the Predictor interface: class Predictor(object):
"""Interface for constructing custom predictors.""" def predict(self,
instances, **kwargs): """Performs custom prediction. Instances are the
decoded values from the request. They have already been deserialized from
JSON. Args: instances: A list of prediction input instances. **kwargs: A
dictionary of keyword args provided as additional fields on the predict
request body. Returns: A list of outputs containing the prediction
results. This list must be JSON serializable. """ raise
NotImplementedError() @classmethod def from_path(cls, model_dir):
"""Creates an instance of Predictor using the given path. Loading of the
predictor should be done in this method. Args: model_dir: The local
directory that contains the exported model file along with any additional
files uploaded when creating the version resource. Returns: An instance
implementing this Predictor class. """ raise NotImplementedError() Learn
more about [the Predictor interface and custom prediction
routines](/ml-engine/docs/tensorflow/custom-prediction-routines).
Optional.
Implementation
core.String? predictionClass;