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Tensorflow Lattice Library.
This package provides functions and classes for lattice modeling.
Modules
aggregation_layer
module: Layer which represents aggregation function.
categorical_calibration_layer
module: Categorical calibration layer with monotonicity and bound constraints.
categorical_calibration_lib
module: Helpers and computations of categorical calibration layer.
cdf_layer
module: Projection free Cumulative Distribution Function layer.
conditional_cdf
module: Implements CDF transformation with derived parameters (kernels).
conditional_pwl_calibration
module: Implements PWLCalibration with derived parameters (kernels).
configs
module: TFL model configuration library for canned estimators.
kronecker_factored_lattice_layer
module: Kronecker-Factored Lattice layer with monotonicity constraints.
kronecker_factored_lattice_lib
module: Algorithm implementations required for Kronecker-Factored Lattice layer.
lattice_layer
module: Lattice layer with monotonicity, unimodality, trust and bound constraints.
lattice_lib
module: Implementation of algorithms required for Lattice layer.
layers
module: 'layers' namespace for TFL layers.
linear_layer
module: Layer which represents linear function. See class level comment.
linear_lib
module: Implementation of algorithms required for Linear layer.
model_info
module: Classes defining trained TFL model structure and parameter information.
parallel_combination_layer
module: ParallelCombination layer for combining several parallel calibration layers.
premade
module: TF Lattice premade models implement typical monotonic model architectures.
premade_lib
module: Implementation of algorithms required for premade models.
pwl_calibration_layer
module: Piecewise linear calibration layer.
pwl_calibration_lib
module: Implementation of algorithms required for PWL calibration layer.
test_utils
module: Helpers to train simple model for tests and print debug output.
utils
module: Helpers shared by multiple modules in TFL.
Other Members | |
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absolute_import |
Instance of __future__._Feature
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