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
#> -0.3693  1.5934 -0.9490 -0.3693  1.5934 -0.9490 -0.3693  1.5934 -0.9490
#> -1.1497 -0.0863  1.3797 -1.1497 -0.0863  1.3797 -1.1497 -0.0863  1.3797
#> [ CPUFloatType{2,9} ]