nvtabular.ops.HashedCross

class nvtabular.ops.HashedCross(num_buckets: Union[int, Dict[str, int]])

Bases: nvtabular.ops.operator.Operator

This ops creates hashed cross columns by first combining categorical features and hashing the combined feature, then reducing modulo the number of buckets.

Example usage:

# Define parameters
cat_names = [["name-string", "id"]]
num_buckets = 10

# Use HashedCross operator to define NVTabular workflow
hashed_cross = cat_names >> ops.HashedCross(num_buckets)
processor = nvtabular.Workflow(hashed_cross)

Parameters

num_buckets (int or dict) – Column-wise modulo to apply after hash function. Note that this means that the corresponding value will be the categorical cardinality of the transformed categorical feature. That value will be used as the number of “hash buckets” for every output feature.

__init__(num_buckets: Union[int, Dict[str, int]])

Methods

__init__(num_buckets)
column_mapping(col_selector)
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 :param root_schema: Base schema of the dataset before running any operators.
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 :param input_schema: The schemas of the columns to apply this operator to :type input_schema: Schema :param col_selector: The column selector to apply to the input schema :type col_selector: ColumnSelector
compute_selector(input_schema, selector, …)
create_node(selector)
inference_initialize(col_selector, model_config)	Configures this operator for use in inference.
output_column_names(col_selector)	Given a set of columns names returns the names of the transformed columns this operator will produce :param columns: The columns to apply this operator to :type columns: list of str, or list of list of str
transform(col_selector, df)	Transform the dataframe by applying this operator to the set of input columns

Attributes

dependencies	Defines an optional list of column dependencies for this operator.
dynamic_dtypes
label
output_dtype
output_properties
output_tags
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

Transform the dataframe by applying this operator to the set of input columns

Parameters

• columns (list of str or list of list of str) – The columns to apply this operator to

• df (Dataframe) – A pandas or cudf dataframe that this operator will work on

Returns

Returns a transformed dataframe for this operator

Return type

DataFrame

column_mapping(col_selector)

property output_dtype