weighted_init

weighted_init([rng], [T], dims...;
    scaling=0.1, return_sparse=false)

Create and return a matrix representing a weighted input layer. This initializer generates a weighted input matrix with random non-zero elements distributed uniformly within the range [-scaling, scaling] (Lu et al., 2017).

Arguments

• rng: Random number generator. Default is Utils.default_rng() from WeightInitializers.
• T: Type of the elements in the reservoir matrix. Default is Float32.
• dims: Dimensions of the matrix. Should follow res_size x in_size.

Keyword arguments

• scaling: The scaling factor for the weight distribution. Defaults to 0.1.
• return_sparse: flag for returning a sparse matrix. Default is false.

Examples

julia> res_input = weighted_init(8, 3)
6×3 Matrix{Float32}:
  0.0452399   0.0          0.0
 -0.0348047   0.0          0.0
  0.0        -0.0386004    0.0
  0.0         0.00981022   0.0
  0.0         0.0          0.0577838
  0.0         0.0         -0.0562827