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Monotonicity and bounds constraints for PWL calibration layer.
tfl.pwl_calibration_layer.PWLCalibrationConstraints(
monotonicity='none', convexity='none', lengths=None,
output_min=None, output_max=None,
output_min_constraints=tfl.pwl_calibration_lib.BoundConstraintsType.NONE,
output_max_constraints=tfl.pwl_calibration_lib.BoundConstraintsType.NONE,
num_projection_iterations=8
)
Applies an approximate L2 projection to the weights of a PWLCalibration layer such that the result satisfies the specified constraints.
Args | |
---|---|
monotonicity
|
Same meaning as corresponding parameter of PWLCalibration .
|
convexity
|
Same meaning as corresponding parameter of PWLCalibration .
|
lengths
|
Lengths of pieces of piecewise linear function. Needed only if convexity is specified. |
output_min
|
Minimum possible output of pwl function. |
output_max
|
Maximum possible output of pwl function. |
output_min_constraints
|
A tfl.pwl_calibration_lib.BoundConstraintsType
describing the constraints on the layer's minimum value.
|
output_max_constraints
|
A tfl.pwl_calibration_lib.BoundConstraintsType
describing the constraints on the layer's maximum value.
|
num_projection_iterations
|
Same meaning as corresponding parameter of
PWLCalibration .
|
Methods
get_config
get_config()
Standard Keras config for serialization.
__call__
__call__(
w
)
Applies constraints to w.