nn_init_sparse_: Sparse initialization

In torch: Tensors and Neural Networks with 'GPU' Acceleration

Sparse initialization

Description

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()) {
## Not run: 
w <- torch_empty(3, 5)
nn_init_sparse_(w, sparsity = 0.1)

## End(Not run)
}

torch documentation built on May 29, 2024, 9:54 a.m.