graph Module

Defines classes for constructing Azure Machine Learning pipeline graphs.

Azure ML pipeline graphs are created for Pipeline objects, when you use PipelineStep (and derived classes), PipelineData, and PipelineData objects. In typical use cases, you will not need to directly use the classes in this module.

A pipeline run graph consists of module nodes which represent basic units such as a datasource or step. Nodes can have input ports and output ports, and associated parameters. Edges define relationships between two node ports in a graph.

Classes

DataSource	A datasource that can be used in a graph. Initialize DataSource.
DataSourceDef	Definition of a datasource. Initialize DataSourceDef.
DataSourceNode	Represents a datasource in a graph. Initialize datasource node.
DataType	Datatype for a piece of data (input or output). Initialize DataType.
Edge	Instance of an edge between two node ports in the graph. Initialize Edge.
Graph	A class to define a pipeline run graph. Initialize Graph.
InputPort	Instance of an input port on a node, which can be connected to an output port. Initialize InputPort.
InputPortBinding	Defines a binding from a source to an input of a pipeline step. An InputPortBinding can be used as an input to a step. The source can be a PipelineData, PortDataReference, DataReference, PipelineDataset, or OutputPortBinding. InputPortBinding is useful to specify the name of the step input, if it should be different than the name of the bind object (i.e. to avoid duplicate input/output names or because the step script needs an input to have a certain name). It can also be used to specify the bind_mode for PythonScriptStep inputs. Initialize InputPortBinding.
InputPortDef	Definition of an input port. Create an input port.
Module	A runnable module that can be used in a graph. This class is not intended to be used directly. Use this Module class instead. Initialize Module.
ModuleDef	Definition of a module including execution and port definitions. Initialize ModuleDef.
ModuleNode	Represents a module in a graph. Initialize module node.
Node	Represents a basic unit in a graph, for example, it could be any datasource or step. Initialize Node.
OutputPort	Instance of an output port on a node, which can be connected to an input port. Initialize OutputPort.
OutputPortBinding	Defines a named output of a pipeline step. OutputPortBinding can be used to specify the type of data which will be produced by a step and how the data will be produced. It can be used with InputPortBinding to specify that the step output is a required input of another step. Initialize OutputPortBinding.
OutputPortDef	Definition of an output port. Create an output port.
Param	Instance of a parameter on a node. Initialize Param.
ParamDef	Definition of an execution parameter. Initialize ParamDef.
PipelineDataset	Acts as an adapter for Dataset and Pipeline. Note This class is deprecated. Learn how to use dataset with pipeline, see https://aka.ms/pipeline-with-dataset. This is an internal class. You should not create this class directly but rather call the as_* instance methods on the Dataset or the OutputDatasetConfig classes. Act as an adapter for Dataset and Pipeline. This is an internal class. You should not create this class directly but rather call the as_* instance methods on the Dataset or the OutputDatasetConfig classes.
PipelineParameter	Defines a parameter in a pipeline execution. Use PipelineParameters to construct versatile Pipelines which can be resubmitted later with varying parameter values. Initialize pipeline parameters.
PortDataReference	Models data associated with an output of a completed StepRun. A PortDataReference object can be used to download the output data which was produced by a StepRun. It can also be used as an step input in a future Pipeline. Initialize PortDataReference.
PublishedPipeline	Represents a Pipeline to be submitted without the Python code which constructed it. In addition, a PublishedPipeline can be used to resubmit a Pipeline with different PipelineParameter values and inputs. Initialize PublishedPipeline. :param endpoint The REST endpoint URL to submit pipeline runs for this pipeline. :type endpoint: str :param total_run_steps: The number of steps in this pipeline :type total_run_steps: int :param workspace: The workspace of the published pipeline. :type workspace: azureml.core.Workspace :param continue_on_step_failure: Whether to continue execution of other steps in the PipelineRun if a step fails, default is false.
StoredProcedureParameter	Represents a SQL stored procedure parameter for use with SQL database references. Initialize StoredProcedureParameter. defaults to azureml.pipeline.core.graph.StoredProcedureParameterType.String :type type: azureml.pipeline.core.graph.StoredProcedureParameterType
TrainingOutput	Defines a specialized output of certain PipelineSteps for use in a pipeline. TrainingOutput enables an automated machine learning metric or model to be made available as a step output to be consumed by another step in an Azure Machine Learning Pipeline. Can be used with AutoMLStep or HyperDriveStep. Initialize TrainingOutput. param model_file: The specific model file to be included in the output. For HyperDriveStep only.

Enums

StoredProcedureParameterType

Defines types of SQL stored procedure parameters for use with SQL database references.