merlin.systems.dag.ops.session_filter.FilterCandidates

class merlin.systems.dag.ops.session_filter.FilterCandidates(filter_out: str, input_col: Optional[str] = None)[source]

Bases: merlin.systems.dag.ops.operator.PipelineableInferenceOperator

This operator takes the input column and filters out elements of that column based on the supplied criteria.

_summary_

Parameters

filter_out (str) – the name of the column to use to filter out
input_col (str, optional) – The target column to filter on, by default None

Returns

A class object is instantiated with param values passed.

Return type

FilterCandidates

Methods

`__init__`(filter_out[, input_col])	_summary_
`column_mapping`(col_selector)	Compute which output columns depend on which input columns
`compute_column_schema`(col_name, input_schema)
`compute_input_schema`(root_schema, …)	Compute the input schema of this node given the root, parents, and dependencies schemas of all ancestor nodes.
`compute_output_schema`(input_schema, col_selector)	Compute the input schema of this node given the root, parents and dependencies schemas of all ancestor nodes.
`compute_selector`(input_schema, selector[, …])	Provides a hook method for sub-classes to override to implement custom column selection logic.
`create_node`(selector)	_summary_
`export`(path, input_schema, output_schema[, …])	Export the class object as a config and all related files to the user defined path.
`from_config`(config, **kwargs)	Instantiate a class object given a config.
`from_model_registry`(registry, **kwargs)	Loads the InferenceOperator from the provided ModelRegistry.
`from_path`(path, **kwargs)	Loads the InferenceOperator from the path where it was exported after training.
`load_artifacts`(artifact_path)	Hook method that provides a way to load saved artifacts for the operator
`output_column_names`(col_selector)	Given a set of columns names returns the names of the transformed columns this operator will produce
`transform`(col_selector, transformable)	Transform input dataframe to output dataframe using function logic.
`validate_schemas`(parents_schema, …[, …])

Attributes

`dependencies`
`dynamic_dtypes`
`export_name`	Provides a clear common english identifier for this operator.
`exportable_backends`
`is_subgraph`
`label`
`output_dtype`
`output_properties`
`output_tags`
`scalar_shape`
`supported_formats`
`supports`	Returns what kind of data representation this operator supports

Instantiate a class object given a config.

Compute the input schema of this node given the root, parents, and dependencies schemas of all ancestor nodes.

Parameters

root_schema (Schema) – The schema representing the input columns to the graph
parents_schema (Schema) – A schema representing all the output columns of the ancestors of this node.
deps_schema (Schema) – A schema representing the dependencies of this node.
selector (ColumnSelector) – A column selector representing a target subset of columns necessary for this node’s operator

Returns

A schema that has the correct representation of all the incoming columns necessary for this node’s operator to complete its transform.

Return type

Schema

Raises

ValueError – Cannot receive more than one input for this node

Compute the input schema of this node given the root, parents and dependencies schemas of all ancestor nodes.

Parameters

input_schema (Schema) – The schema representing the input columns to the graph
col_selector (ColumnSelector) – A column selector representing a target subset of columns necessary for this node’s operator
prev_output_schema (Schema) – A schema representing the output of the previous node.

Returns

A schema object representing all outputs of this node.

Return type

Schema

validate_schemas(parents_schema, deps_schema, input_schema, output_schema, strict_dtypes=False)[source]

transform(col_selector: merlin.dag.selector.ColumnSelector, transformable: merlin.core.protocols.Transformable) → merlin.core.protocols.Transformable[source]

Transform input dataframe to output dataframe using function logic.

Parameters: df (DictArray) – Input tensor dictionary, data that will be manipulated
Returns: Transformed tensor dictionary
Return type: DictArray

export(path: str, input_schema: merlin.schema.schema.Schema, output_schema: merlin.schema.schema.Schema, params: Optional[dict] = None, node_id: Optional[int] = None, version: int = 1, backend: str = 'ensemble')[source]

Export the class object as a config and all related files to the user defined path.

Parameters

path (str) – Artifact export path
input_schema (Schema) – A schema with information about the inputs to this operator
output_schema (Schema) – A schema with information about the outputs of this operator
params (dict, optional) – Parameters dictionary of key, value pairs stored in exported config, by default None
node_id (int, optional) – The placement of the node in the graph (starts at 1), by default None
version (int, optional) – The version of the model, by default 1

Returns