merlin.systems.dag.ops.fil.PredictForest#

class merlin.systems.dag.ops.fil.PredictForest(model, input_schema, *, backend='python', **fil_params)[source]#

Bases: Operator

Operator for running inference on Forest models.

This works for gradient-boosted decision trees (GBDTs) and Random forests (RF). While RF and GBDT algorithms differ in the way they train the models, they both produce a decision forest as their output.

Uses the Forest Inference Library (FIL) backend for inference.

__init__(model, input_schema, *, backend='python', **fil_params)[source]#

Instantiate a FIL inference operator.

Parameters:

model (Forest Model Instance) – A forest model class. Supports XGBoost, LightGBM, and Scikit-Learn.
input_schema (merlin.schema.Schema) – The schema representing the input columns expected by the model.
backend (str) – The Triton backend to use to when running this operator.
**fil_params – The parameters to pass to the FIL operator.

Methods

`__init__`(model, input_schema, *[, backend])	Instantiate a FIL inference operator.
`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, ...)	Return the input schema representing the input columns this operator expects to use.
`compute_output_schema`(input_schema, col_selector)	Return the output schema representing the columns this operator returns.
`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, transformable)	Transform the dataframe by applying this FIL operator to the set of input columns.
`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

compute_output_schema(input_schema: Schema, col_selector: ColumnSelector, prev_output_schema: Optional[Schema] = None) → Schema[source]#: Return the output schema representing the columns this operator returns.

compute_input_schema(root_schema: Schema, parents_schema: Schema, deps_schema: Schema, selector: ColumnSelector) → Schema[source]#: Return the input schema representing the input columns this operator expects to use.

transform(col_selector: ColumnSelector, transformable: Transformable) → Transformable[source]#

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

Parameters:: df (TensorTable) – A pandas or cudf dataframe that this operator will work on
Returns:: Returns a transformed dataframe for this operator
Return type:: TensorTable

merlin.systems.dag.ops.fil.PredictForest

Contents

merlin.systems.dag.ops.fil.PredictForest#