layer_multivariate_normal_tri_l: A d-variate Multivariate Normal TriL Keras layer from...

In tfprobability: Interface to 'TensorFlow Probability'

A d-variate Multivariate Normal TriL Keras layer from d+d*(d+1)/ 2 params

Description

A d-variate Multivariate Normal TriL Keras layer from d+d*(d+1)/ 2 params

Usage

layer_multivariate_normal_tri_l(
  object,
  event_size,
  convert_to_tensor_fn = tfp$distributions$Distribution$sample,
  validate_args = FALSE,
  ...
)

Arguments

object	What to compose the new Layer instance with. Typically a Sequential model or a Tensor (e.g., as returned by layer_input()). The return value depends on object. If object is: missing or NULL, the Layer instance is returned. a Sequential model, the model with an additional layer is returned. a Tensor, the output tensor from layer_instance(object) is returned.
event_size	Integer vector tensor representing the shape of single draw from this distribution.
convert_to_tensor_fn	A callable that takes a tfd$Distribution instance and returns a tf$Tensor-like object. Default value: tfd$distributions$Distribution$sample.
validate_args	Logical, default FALSE. When TRUE distribution parameters are checked for validity despite possibly degrading runtime performance. When FALSE invalid inputs may silently render incorrect outputs. Default value: FALSE.
...	Additional arguments passed to args of keras::create_layer.

Value

a Keras layer

See Also

For an example how to use in a Keras model, see layer_independent_normal().

Other distribution_layers: layer_categorical_mixture_of_one_hot_categorical(), layer_distribution_lambda(), layer_independent_bernoulli(), layer_independent_logistic(), layer_independent_normal(), layer_independent_poisson(), layer_kl_divergence_add_loss(), layer_kl_divergence_regularizer(), layer_mixture_logistic(), layer_mixture_normal(), layer_mixture_same_family(), layer_one_hot_categorical()

tfprobability documentation built on Sept. 1, 2022, 5:07 p.m.