Sparse initialization

Fills the 2D input Tensor as a sparse matrix, where the non-zero elements will be drawn from the normal distribution as described in Deep learning via Hessian-free optimization - Martens, J. (2010).

Usage

nn_init_sparse_(tensor, sparsity, std = 0.01)

Arguments

tensor

an n-dimensional Tensor

sparsity

The fraction of elements in each column to be set to zero

std

the standard deviation of the normal distribution used to generate the non-zero values

Examples

if (torch_is_installed()) {
if (FALSE) { # \dontrun{
w <- torch_empty(3, 5)
nn_init_sparse_(w, sparsity = 0.1)
} # }
}