Dense
Description
Returns the Dense layer weights. Type : polymorphic.
Documentation illustration (illustration unavailable in the archive).
Input parameters
weights : cluster
index : integer, index of layer.
name : string, name of layer.
Documentation illustration (illustration unavailable in the archive). weight : variant, weight of layer.
Documentation illustration (illustration unavailable in the archive).
Output parameters
weights_info : cluster
index : integer, index of layer.
name : string, name of layer. weights : cluster
weights : array, 2D values. weights = [input_dim, units]. biases : array, 1D values. biases = [units].
Documentation illustration (illustration unavailable in the archive).
Dimension
- weights = [input_dim, units]
The size of weights depends on the input of the Dense layer and the parameters units.
For example if the input of the layer has a size of [batch_size = 10, input_dim = 5] and units the value 3 then weights will have a size of [input_dim = 5, units = 3].
- biases = [units]
The size of biases depends on the parameter units of the Dense layer.
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).