An independent Normal Keras layer.

layer_independent_normal(
  object,
  event_shape,
  convert_to_tensor_fn = tfp$distributions$Distribution$sample,
  validate_args = FALSE,
  ...
)

Arguments

object

Model or layer object

event_shape

Scalar integer representing the size 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. @param ... Additional arguments passed to args of keras::create_layer.

...

Additional arguments passed to args of keras::create_layer.

Value

a Keras layer

See also

Examples

# \donttest{ library(keras) input_shape <- c(28, 28, 1) encoded_shape <- 2 n <- 2 model <- keras_model_sequential( list( layer_input(shape = input_shape), layer_flatten(), layer_dense(units = n), layer_dense(units = params_size_independent_normal(encoded_shape)), layer_independent_normal(event_shape = encoded_shape) ) ) # }