wallaroo.model_version

class ModelVersion(wallaroo.object.Object):

The Wallaroo ModelVersion object. Each ModelVersion is a specific version of a Model.

ModelVersion( client: Union[wallaroo.client.Client, NoneType], 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.
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 arch(*args, **kwargs):
def accel(*args, **kwargs):
def last_update_time(*args, **kwargs):
inputs
outputs
def tags(*args, **kwargs):
def workspace(*args, **kwargs):
def rehydrate_config(*args, **kwargs):
def configure( self, runtime: Union[str, NoneType] = None, tensor_fields: Union[List[str], NoneType] = None, filter_threshold: Union[float, NoneType] = None, input_schema: Union[pyarrow.lib.Schema, NoneType] = None, output_schema: Union[pyarrow.lib.Schema, NoneType] = None, batch_config: Union[str, NoneType] = None, dynamic_batching_config: Union[wallaroo.dynamic_batching_config.DynamicBatchingConfig, NoneType] = None) -> wallaroo.model_version.ModelVersion:
def logs( self, limit: int = 100, valid: Union[bool, NoneType] = None, arrow: Union[bool, NoneType] = False) -> Tuple[Any, Union[str, NoneType]]:
def deploy( self, pipeline_name: str, deployment_config: Union[wallaroo.deployment_config.DeploymentConfig, NoneType] = 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 ModelVersionList(typing.List[wallaroo.model_version.ModelVersion]):

Wraps a list of model versions 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