Graph Class

A class to define a pipeline run graph.

Initialize Graph.

Inheritance

builtins.object

Graph

Constructor

Graph(name, context)

Parameters

name

str

Required

Name of the graph.

context

<xref:azureml.pipeline.core._GraphContext>

Required

The current graph context.

name

str

Required

Name of the graph.

context

<xref:azureml.pipeline.core._GraphContext>

Required

The current graph context.

Methods

add_datasource_node	Add a datasource node to the graph.
add_module_node	Add a module node to the graph.
connect	Connect two ports and creates an Edge.
delete_node	Delete a node from the graph.
finalize	Finalize resources for nodes in the graph.
generate_yaml	Generate the yaml representation of the graph.
get_node	Get a node by ID.
sequence	Configure a list of nodes to run in a sequence following the first node in the list.
submit	Submit the graph to run in the cloud.
validate	Validate graph. Returns a list of errors.

add_datasource_node

Add a datasource node to the graph.

add_datasource_node(name, datasource=None, datasource_builder=None, datapath_param_name=None)

Parameters

name

str

Required

Name of the node.

datasource

DataSource

default value: None

Datasource for this node.

datasource_builder

<xref:azureml.pipeline.core._DatasourceBuilder>

default value: None

_DatasourceBuilder for this node.

datapath_param_name

str

default value: None

Datapath parameter name.

Returns

node

Return type

Node

add_module_node

Add a module node to the graph.

add_module_node(name, input_bindings, output_bindings=None, param_bindings=None, module=None, module_builder=None, module_wiring=None, runconfig=None, cloud_settings=None)

Parameters

name

str

Required

Name of the node

input_bindings

list

Required

List of input port bindings.

output_bindings

list

default value: None

List of output port bindings.

param_bindings

dict

default value: None

Dictionary of name-value pairs for parameter assignments.

module

Module

default value: None

Module for this node

module_builder

<xref:azureml.pipeline.core._ModuleBuilder>

default value: None

_ModuleBuilder for this node

module_wiring

Dict[str, object]

default value: None

A mapping between the node's inputs/outputs and the module inputs/outputs. Holds two keys, inputs and outputs, each mapped to a dict whose keys are the module's inputs/outputs names, and the values are the node's ports.

runconfig

str

default value: None

Runconfig that will be used for python_script_step

cloud_settings

<xref:azureml.pipeline.core._restclients.aeva.models.CloudSettings>

default value: None

Settings that will be used for clouds

Returns

node

Return type

Node

connect

Connect two ports and creates an Edge.

connect(source_port, dest_port)

Parameters

source_port

OutputPort

Required

Output port from the node that is the source of the connection

dest_port

InputPort

Required

Input port from the node that is the destination of the connection

Returns

edge

Return type

Edge

delete_node

Delete a node from the graph.

delete_node(node_id)

Parameters

node_id

str

Required

node id

finalize

Finalize resources for nodes in the graph.

finalize(dry_run=None, regenerate_outputs=False)

Parameters

dry_run

bool

default value: None

Set to True to verify that the graph can be built without making any external API calls to Azure ML service.

regenerate_outputs

bool

default value: False

Set to True to force a new run (disallows module/datasource reuse).

Returns

Dictionary of {node_id, (resource_id, is_new_resource)}

Return type

dict

generate_yaml

Generate the yaml representation of the graph.

generate_yaml()

Returns

Return the yaml dict

Return type

dict

get_node

Get a node by ID.

get_node(node_id)

Parameters

node_id

str

Required

The node ID.

Returns

The node.

Return type

Node

sequence

Configure a list of nodes to run in a sequence following the first node in the list.

sequence(nodes)

Parameters

nodes

list

Required

The list of nodes.

submit

Submit the graph to run in the cloud.

submit(pipeline_parameters=None, continue_on_step_failure=False, regenerate_outputs=False, parent_run_id=None, **kwargs)

Parameters

pipeline_parameters

dict

default value: None

Parameters for pipeline execution. Optional.

continue_on_step_failure

bool

default value: False

Indicates whether to let the experiment continue executing if one step fails. If True, only steps that have no dependency on the output of the failed step will continue execution.

regenerate_outputs

bool

default value: False

Set to True to force a new run (disallows module/datasource reuse)

parent_run_id

default value: None

Optional run ID to set for the parent run of this pipeline run, which is reflected in RunHistory. The parent run must belong to same experiment as this pipeline is being submitted to.

kwargs

dict

Required

Custom keyword arguments, reserved for future development.

Returns

A PipelineRun.

Return type

PipelineRun

validate

Validate graph. Returns a list of errors.

validate()

Returns

List errors.

Return type

list

Attributes

datasource_nodes

Get a list containing all datasource nodes.

Returns

List of Node

Return type

list

edges

Get an iterator of edges.

Returns

a list of Edge

Return type

list

module_nodes

Get a list containing all module nodes.

Returns

List of Node

Return type

list

node_dict

Get a dictionary containing all nodes.

Returns

Dictionary of {node Id, Node}

Return type

dict

node_name_dict

Get a dictionary containing all nodes indexed by name.

Returns

Dictionary of {node name, Node}

Return type

dict

nodes

Get a list containing all nodes.

Returns

List of Node

Return type

list

params

Get a dictionary containing all graph parameters. Values are literal types or data reference as JSON string.

Returns

Dictionary of {param name, param value}

Return type

dict