nvtabular.ops.AddMetadata

class nvtabular.ops.AddMetadata(tags=None, properties=None)[source]

Bases: merlin.dag.operator.Operator

This operator will add user defined tags and properties to a Schema.

__init__(tags=None, properties=None)[source]

Methods

__init__([tags, properties])

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, …)

Given the schemas coming from upstream sources and a column selector for the input columns, returns a set of schemas for the input columns this operator will use

compute_output_schema(input_schema, col_selector)

Given a set of schemas and a column selector for the input columns, returns a set of schemas for the transformed columns this operator will produce

compute_selector(input_schema, selector[, …])

Provides a hook method for sub-classes to override to implement custom column selection logic.

create_node(selector)

export(path, input_schema, output_schema, …)

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

load_artifacts([artifact_path])

Load artifacts from disk required for operator function.

output_column_names(col_selector)

Given a set of columns names returns the names of the transformed columns this operator will produce

save_artifacts([artifact_path])

Save artifacts required to be reload operator state from disk

transform(col_selector, df)

validate_schemas(parents_schema, …[, …])

Provides a hook method that sub-classes can override to implement schema validation logic.

Attributes

dependencies

Defines an optional list of column dependencies for this operator.

dynamic_dtypes

export_name

Provides a clear common english identifier for this operator.

is_subgraph

label

output_dtype

output_properties

output_tags

supported_formats

supports

Returns what kind of data representation this operator supports

transform(col_selector: merlin.dag.selector.ColumnSelector, df: pandas.core.frame.DataFrame)pandas.core.frame.DataFrame[source]
property output_tags
property output_properties