RandomNormal
Description
Random normal initializer. Type : polymorphic.
Draws samples from a normal distribution for given parameters.
Input parameters
Parameters : cluster,
mean : float, a scalar. Mean of the random values to generate. stddev : float, a scalar. Standard deviation of the random values to generate.
seed : integer, used to make the behavior of the initializer deterministic. Note that an initializer seeded with an integer or -1 (unseeded) will produce the same random values across multiple calls.
Documentation illustration (illustration unavailable in the archive).
Output parameters
Initializer : cluster, this cluster defines the weight initialization strategy for a model.
Documentation illustration (illustration unavailable in the archive). enum : enum, an enumeration indicating the initialization type (e.g., Zeros, Glorot, HeNormal, etc.). If enum is set to CustomInitializer, the custom class on the right will be used. Otherwise, the selected initialization strategy will be applied with default parameters.
Documentation illustration (illustration unavailable in the archive). Class : object, a custom initializer class instance.
Documentation illustration (illustration unavailable in the archive).
Example
All these exemples are snippets PNG, you can drop these Snippet onto the block diagram and get the depicted code added to your VI (Do not forget to install Deep Learning library to run it).
Documentation illustration (illustration unavailable in the archive).