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

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)

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.

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

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

  • 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 a transformed dataframe for this operator

Return type


property output_dtype