Randn

torch_randn(
...,
names = NULL,
dtype = NULL,
layout = torch_strided(),
device = NULL,
)

## Arguments

... (int...) a sequence of integers defining the shape of the output tensor. Can be a variable number of arguments or a collection like a list or tuple. optional names for the dimensions (torch.dtype, optional) the desired data type of returned tensor. Default: if NULL, uses a global default (see torch_set_default_tensor_type). (torch.layout, optional) the desired layout of returned Tensor. Default: torch_strided. (torch.device, optional) the desired device of returned tensor. Default: if NULL, uses the current device for the default tensor type (see torch_set_default_tensor_type). device will be the CPU for CPU tensor types and the current CUDA device for CUDA tensor types. (bool, optional) If autograd should record operations on the returned tensor. Default: FALSE.

## randn(*size, out=NULL, dtype=NULL, layout=torch.strided, device=NULL, requires_grad=False) -> Tensor

Returns a tensor filled with random numbers from a normal distribution with mean 0 and variance 1 (also called the standard normal distribution).

$$\mbox{out}_{i} \sim \mathcal{N}(0, 1)$$ The shape of the tensor is defined by the variable argument size.

## Examples

if (torch_is_installed()) {

torch_randn(c(4))
torch_randn(c(2, 3))
}
#> torch_tensor
#> -0.9690  1.1161  0.7557
#>  2.6197  1.1517 -0.7624
#> [ CPUFloatType{2,3} ]