gauss_cat_sampler_most_likely function

A torch::nn_module() Representing a gauss_cat_sampler_most_likely

The gauss_cat_sampler_most_likely generates the most likely samples from the generative distribution defined by the output of the vaeac. I.e., the layer will return the mean and most probable class for the Gaussian (continuous features) and categorical (categorical features) distributions, respectively.

gauss_cat_sampler_most_likely(
  one_hot_max_sizes,
  min_sigma = 1e-04,
  min_prob = 1e-04
)

Arguments

• one_hot_max_sizes: A torch tensor of dimension n_features containing the one hot sizes of the n_features

  features. That is, if the ith feature is a categorical feature with 5 levels, then one_hot_max_sizes[i] = 5. While the size for continuous features can either be 0 or 1.

• min_sigma: For stability it might be desirable that the minimal sigma is not too close to zero.

• min_prob: For stability it might be desirable that the minimal probability is not too close to zero.

Returns

A gauss_cat_sampler_most_likely object.

Author(s)

Lars Henry Berge Olsen