View source on GitHub
|
Implementation of algorithms required for Lattice layer.
Functions
assert_constraints(...): Asserts that weights satisfy constraints.
batch_outer_operation(...): Computes outer operation of last dimensions of each of given tensors.
compute_interpolation_weights(...): Computes weights for hypercube lattice interpolation.
default_init_params(...): Returns reasonable default parameters if not defined explicitly.
evaluate_with_hypercube_interpolation(...): Evaluates a lattice using hypercube interpolation.
evaluate_with_simplex_interpolation(...): Evaluates a lattice using simplex interpolation.
finalize_constraints(...): Approximately projects lattice weights to strictly satisfy all constraints.
laplacian_regularizer(...): Returns Laplacian regularization loss for Lattice layer.
linear_initializer(...): Returns a lattice layer weight tensor that represents a linear function.
project_by_dykstra(...): Applies dykstra's projection algorithm for monotonicity/trust constraints.
random_monotonic_initializer(...): Returns a uniformly random sampled monotonic lattice layer weight tensor.
torsion_regularizer(...): Returns Torsion regularization loss for Lattice layer.
verify_hyperparameters(...): Verifies that all given hyperparameters are consistent.
Other Members | |
|---|---|
| absolute_import |
Instance of __future__._Feature
|
| division |
Instance of __future__._Feature
|
| print_function |
Instance of __future__._Feature
|
View source on GitHub