View source: R/distribution-layers.R
layer_mixture_logistic | R Documentation |
A mixture distribution Keras layer, with independent logistic components.
layer_mixture_logistic( object, num_components, event_shape = list(), convert_to_tensor_fn = tfp$distributions$Distribution$sample, validate_args = FALSE, ... )
object |
What to compose the new
|
num_components |
Number of component distributions in the mixture distribution. |
event_shape |
integer vector |
convert_to_tensor_fn |
A callable that takes a tfd$Distribution instance and returns a
tf$Tensor-like object. Default value: |
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 |
... |
Additional arguments passed to |
a Keras layer
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_normal()
,
layer_mixture_same_family()
,
layer_multivariate_normal_tri_l()
,
layer_one_hot_categorical()
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