Gather

torch_gather(self, dim, index, sparse_grad = FALSE)

## Arguments

self (Tensor) the source tensor (int) the axis along which to index (LongTensor) the indices of elements to gather (bool,optional) If TRUE, gradient w.r.t. input will be a sparse tensor.

## gather(input, dim, index, sparse_grad=FALSE) -> Tensor

Gathers values along an axis specified by dim.

For a 3-D tensor the output is specified by::

out[i][j][k] = input[index[i][j][k]][j][k]  # if dim == 0
out[i][j][k] = input[i][index[i][j][k]][k]  # if dim == 1
out[i][j][k] = input[i][j][index[i][j][k]]  # if dim == 2


If input is an n-dimensional tensor with size $$(x_0, x_1..., x_{i-1}, x_i, x_{i+1}, ..., x_{n-1})$$ and dim = i, then index must be an $$n$$-dimensional tensor with size $$(x_0, x_1, ..., x_{i-1}, y, x_{i+1}, ..., x_{n-1})$$ where $$y \geq 1$$ and out will have the same size as index.

## Examples

if (torch_is_installed()) {

t = torch_tensor(matrix(c(1,2,3,4), ncol = 2, byrow = TRUE))
torch_gather(t, 2, torch_tensor(matrix(c(1,1,2,1), ncol = 2, byrow=TRUE), dtype = torch_int64()))
}
#> torch_tensor
#>  1  1
#>  4  3
#> [ CPUFloatType{2,2} ]