Module: tfl.conditional_cdf

Implements CDF transformation with derived parameters (kernels).

cdf_fn is similar to tfl.layers.CDF, which is an additive / multiplicative average of a few shifted and scaled sigmoid or relu6 basis functions, with the difference that the functions are parametrized by the provided parameters instead of learnable weights belonging to a tfl.layers.CDF layer.

These parameters can be one of:

constants,
trainable variables,
outputs from other TF modules.

For inputs of shape (batch_size, input_dim), two sets of free-form parameters are used to configure the CDF function:

location_parameters for where to place the sigmoid / relu6 transformation basis,
scaling_parameters (optional) for the horizontal scaling before applying the transformation basis.

Functions

cdf_fn(...): Maps inputs through a CDF function specified by keypoint parameters.