Randn

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

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.

names

optional names for the dimensions

dtype

(torch.dtype, optional) the desired data type of returned tensor. Default: if NULL, uses a global default (see torch_set_default_tensor_type).

layout

(torch.layout, optional) the desired layout of returned Tensor. Default: torch_strided.

device

(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.

requires_grad

(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 #> -0.7768 -0.6058 -0.8964 #> 0.8178 0.7598 1.5849 #> [ CPUFloatType{2,3} ]