wallaroo.model

class Model(wallaroo.object.Object):

Wraps a backend Model object.

Model( client: Optional[wallaroo.client.Client], data: Dict[str, Any], standalone=False)

Base constructor.

Each object requires:

a GraphQL client - in order to fill its missing members dynamically
an initial data blob - typically from unserialized JSON, contains at
least the data for required members (typically the object's primary key) and optionally other data members.

@staticmethod

def as_standalone(name: str, version: str, file_name: str) -> wallaroo.model.Model:

Creates a Model intended for use in generating standalone configurations

def id(self) -> int:

def uid(self) -> str:

def name(*args, **kwargs):

def version(*args, **kwargs):

def models_pk_id(*args, **kwargs):

def sha(*args, **kwargs):

def status(*args, **kwargs):

def file_name(*args, **kwargs):

def image_path(*args, **kwargs):

def last_update_time(*args, **kwargs):

inputs

outputs

def tags(*args, **kwargs):

def rehydrate_config(*args, **kwargs):

def config(self) -> wallaroo.model_config.ModelConfig:

def configure( self, runtime: Optional[str] = None, tensor_fields: List[str] = None, filter_threshold: float = None, input_schema: Optional[pyarrow.lib.Schema] = None, output_schema: Optional[pyarrow.lib.Schema] = None, batch_config: Optional[str] = None) -> wallaroo.model.Model:

def logs( self, limit: int = 100, valid: Optional[bool] = None, arrow: Optional[bool] = False) -> Tuple[Any, Optional[str]]:

def deploy( self, pipeline_name: str, deployment_config: Optional[wallaroo.deployment_config.DeploymentConfig] = None) -> wallaroo.pipeline.Pipeline:

Convenience function to quickly deploy a Model. It will configure the model, create a pipeline with a single model step, deploy it, and return the pipeline.

Typically, the configure() method is used to configure a model prior to deploying it. However, if a default configuration is sufficient, this function can be used to quickly deploy with said default configuration.

The filename this Model was generated from needs to have a recognizable file extension so that the runtime can be inferred. Currently, this is:

.onnx -> ONNX runtime

Parameters

str deployment_name: Name of the deployment to create. Must be unique across all deployments. Deployment names must be ASCII alpha-numeric characters plus dash (-) only.

class ModelVersions(typing.List[wallaroo.model.Model]):

Wraps a list of Models for display in a display-aware environment like Jupyter.

Inherited Members

builtins.list: list; clear; copy; append; insert; extend; pop; remove; index; count; reverse; sort