Module: mlmd.proto

ML Metadata proto module.

Classes

class Artifact: An artifact represents an input or an output of individual steps in a ML workflow, e.g., a trained model, an input dataset, and evaluation metrics.

class ArtifactType: A user defined type about a collection of artifacts and their properties that are stored in the metadata store.

class Association: An association represents the relationship between executions and contexts.

class Attribution: An attribution represents the relationship between artifacts and contexts.

class ConnectionConfig: A connection configuration specifying the persistent backend to be used with MLMD.

class Context: A context defines a group of artifacts and/or executions.

class ContextType: A user defined type about a collection of contexts and their properties that are stored in the metadata store.

class Event: An event records the relationship between artifacts and executions.

class Execution: An execution describes a component run or a step in an ML workflow along with its runtime parameters, e.g., a Trainer run, a data transformation step.

class ExecutionType: A user defined type about a collection of executions and their properties that are stored in the metadata store.

class FakeDatabaseConfig: An in-memory database configuration for testing purpose.

class MetadataStoreClientConfig: A connection configuration to use a MLMD server as the persistent backend.

class MySQLDatabaseConfig: A connection configuration to use a MySQL db instance as a MLMD backend.

class ParentContext: A parental context represents the relationship between contexts.

class SqliteMetadataSourceConfig: A connection configuration to use a Sqlite db file as a MLMD backend.