ModuleStepBase class

Definition

Adds a step to a pipeline that uses a specific module.

A ModuleStep derives from ModuleStepBase and is a node in a pipeline that uses an existing Module, and specifically, one of its versions. In order to define which ModuleVersion would eventually be used in the submitted pipeline, you can define one of the following when creating the ModuleStep:

  • ModuleVersion object
  • Module object and a version value
  • Only Module without a version value; in this case, the version resolution used may vary across submissions.

You also need to define the mapping between the step's inputs and outputs to the ModuleVersion object's inputs and outputs.

ModuleStepBase(module=None, version=None, module_version=None, inputs_map=None, outputs_map=None, compute_target=None, runconfig=None, runconfig_pipeline_params=None, arguments=None, params=None, name=None, _workflow_provider=None)
Inheritance
builtins.object
ModuleStepBase

Parameters

module
Module

The Module of the step.

version
str

The version of the Module.

module_version
ModuleVersion

The ModuleVersion of the step. Either Module of ModuleVersion must be provided.

inputs_map
dict({str: (InputPortBinding or DataReference or PortDataReference or PipelineData or Dataset or DatasetDefinition or PipelineDataset)})

A dictionary where keys are names of inputs on the module_version and values are input port bindings.

outputs_map
dict({str: (OutputPortBinding or DataReference or PortDataReference or PipelineData or Dataset or DatasetDefinition or PipelineDataset)})

A dictionary where keys are names of inputs on the module_version and values are output port bindings.

runconfig_pipeline_params
{str: azureml.pipeline.core.graph.PipelineParameter}

Override runconfig properties at runtime using key-value pairs each with name of the runconfig property and PipelineParameter for that property.

Supported values: 'NodeCount', 'MpiProcessCountPerNode', 'TensorflowWorkerCount', 'TensorflowParameterServerCount'

arguments
[str]

Command line arguments for the script file. The arguments will be delivered to compute via arguments in RunConfiguration. For more details on how to handle arguments such as special symbols, please refer arguments in RunConfiguration.

params
dict({str: str})

A dictionary of name-value parameter pairs.

_workflow_provider
_AevaWorkflowProvider object

(Internal use only.) The workflow provider.

Methods

create_node(graph, default_datastore, context)

Create a pipeline graph node.

create_node(graph, default_datastore, context)

Create a pipeline graph node.

create_node(graph, default_datastore, context)

Parameters

graph
Graph

The graph to add the node to.

default_datastore
AbstractAzureStorageDatastore or AzureDataLakeDatastore

The default datastore to use for this step.

context
_GraphContext

(Internal use only.) The graph context object.

Returns

The node object.

Return type