|  View source on GitHub | 
Classes defining trained TFL model structure and parameter information.
This package provides representations and tools for analysis of a trained TF Lattice model, e.g. a canned estimator in saved model format.
Classes
class CategoricalCalibrationNode: Represetns a categorical calibration layer.
class InputFeatureNode: Input features to the model.
class KroneckerFactoredLatticeNode: Represents a kronecker-factored lattice layer.
class LatticeNode: Represetns a lattice layer.
class LinearNode: Represents a linear layer.
class MeanNode: Represents an averaging layer.
class ModelGraph: Model info and parameter as a graph.
class PWLCalibrationNode: Represetns a PWL calibration layer.
| Other Members | |
|---|---|
| absolute_import | Instance of __future__._Feature | 
| division | Instance of __future__._Feature | 
| print_function | Instance of __future__._Feature |