Cat — torch_cat • torch

Cat

Usage

torch_cat(tensors, dim = 1L)

Arguments

tensors: (sequence of Tensors) any python sequence of tensors of the same type. Non-empty tensors provided must have the same shape, except in the cat dimension.
dim: (int, optional) the dimension over which the tensors are concatenated

cat(tensors, dim=0, out=NULL) -> Tensor

Concatenates the given sequence of seq tensors in the given dimension. All tensors must either have the same shape (except in the concatenating dimension) or be empty.

torch_cat can be seen as an inverse operation for torch_split() and torch_chunk.

torch_cat can be best understood via examples.

Examples

if (torch_is_installed()) {

x = torch_randn(c(2, 3))
x
torch_cat(list(x, x, x), 1)
torch_cat(list(x, x, x), 2)
}
#> torch_tensor
#>  1.3614  0.6226 -0.1413  1.3614  0.6226 -0.1413  1.3614  0.6226 -0.1413
#>  0.0467 -0.1386  0.5232  0.0467 -0.1386  0.5232  0.0467 -0.1386  0.5232
#> [ CPUFloatType{2,9} ]