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).
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) {
w <- torch_empty(3, 5)
nn_init_sparse_(w, sparsity = 0.1)
}
}