Node
- class fedot.core.pipelines.node.NodeMetadata(metric: Optional[float] = None)[source]
Bases:
object
Dataclass.
Node
metadata- Parameters
metric – quality score
- metric: Optional[float] = None
- class fedot.core.pipelines.node.PipelineNode(operation_type: Optional[Union[str, Operation]] = None, nodes_from: Optional[List[Node]] = None, node_data: Optional[dict] = None, **kwargs)[source]
Bases:
golem.core.dag.linked_graph_node.LinkedGraphNode
The class defines the interface of nodes modifying tha data flow in the
Pipeline
- Parameters
operation_type – operation defined in the operation repository
nodes_from – parent nodes where data comes from
node_data –
dict
withInputData
for fit and predict stagekwargs – optional arguments (i.e. logger)
- property is_primary
- _process_content_init(passed_content: dict) fedot.core.operations.operation.Operation [source]
Updating content in the node
- static _process_direct_init(operation_type: Optional[Union[str, fedot.core.operations.operation.Operation]]) fedot.core.operations.operation.Operation [source]
Define operation based on the direct
operation_type
without defining content in the node- Parameters
operation_type – node type representation
- Returns
operation class object
- Return type
- property name: str
Returns str name of operation
- property operation: fedot.core.operations.operation.Operation
Returns node operation object
- Returns
operation object
- Return type
- property fitted_operation: Optional[Any]
Returns already fitted operation if exists or
None
instead- Returns
node fitted operation or
None
- fit(input_data: fedot.core.data.data.InputData) fedot.core.data.data.OutputData [source]
Runs training process in the node
- Parameters
input_data – data used for operation training
- Returns
values predicted on the provided
input_data
- Return type
- predict(input_data: fedot.core.data.data.InputData, output_mode: str = 'default') fedot.core.data.data.OutputData [source]
Runs prediction process in the node
- Parameters
input_data – data used for prediction
output_mode – desired output for operations (e.g.
'labels'
,'probs'
,'full_probs'
)
- Returns
values predicted on the provided
input_data
- Return type
- get_data_from_node() dict [source]
Returns data if it was set to the nodes directly
- Returns
dict
withInputData
for fit and predict stage- Return type
dict
- property node_data: dict
Returns directly set
node_data
- Returns
dict
withInputData
for fit and predict stage- Return type
dict
- _input_from_parents(input_data: fedot.core.data.data.InputData, parent_operation: str) fedot.core.data.data.InputData [source]
Processes all the parent nodes via the current operation using
input_data
- Parameters
input_data – input data from pipeline abstraction (source input data)
parent_operation – name of parent operation (
'fit'
or'predict'
)
- Returns
predictions from the secondary nodes
- Return type
- _nodes_from_with_fixed_order()[source]
Sorts
nodes_from
(if exists) by the nodes unique id- Returns
sorted
nodes_from
byGraphNode.descriptive_id
orNone
- property parameters: dict
Returns node custom parameters
- Returns
of custom parameters
- Return type
dict
- __str__() str [source]
Returns
str
representation of the node- Returns
string field node operation type
- Return type
str
- property tags: Optional[List[str]]
Returns tags of operation in the node or empty list
- Returns
empty list
if node is of atomized type andlist of tags
otherwise- Return type
Optional[List[str]]
- fedot.core.pipelines.node._combine_parents(parent_nodes: List[fedot.core.pipelines.node.PipelineNode], input_data: Optional[fedot.core.data.data.InputData], parent_operation: str) Tuple[List[fedot.core.data.data.OutputData], numpy.array] [source]
Combines predictions from the
parent_nodes
- Parameters
parent_nodes – list of parent nodes, from which predictions will be combined
input_data – input data from pipeline abstraction (source input data)
parent_operation – name of parent operation (
'fit'
or'predict'
)
- Returns
output data list from parent nodes
,target for final pipeline prediction
- Return type
Tuple[List[OutputData], np.array]
- fedot.core.pipelines.node.PrimaryNode
- fedot.core.pipelines.node.SecondaryNode