Usage
torch_zeros(
...,
names = NULL,
dtype = NULL,
layout = torch_strided(),
device = NULL,
requires_grad = FALSE
)
Arguments
- ...
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 dimension names
- 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
.
zeros(*size, out=NULL, dtype=NULL, layout=torch.strided, device=NULL, requires_grad=False) -> Tensor
Returns a tensor filled with the scalar value 0
, with the shape defined
by the variable argument size
.
Examples
Run this codeif (torch_is_installed()) {
torch_zeros(c(2, 3))
torch_zeros(c(5))
}
Run the code above in your browser using DataLab