blob: 09920acd1ac5a1e060587cb150c9ccdff2a649d8 [file] [log] [blame]
#include "ATen/ATen.h"
#include "ATen/Dispatch.h"
#include <vector>
namespace {
using namespace at;
Tensor _triu_mask(int64_t n, int64_t dims, bool diagonal, TensorOptions opt) {
// get a mask that has value 1 whose indices satisfies i < j < k < ...
// or i <= j <= k <= ... (depending on diagonal)
Tensor range = at::arange(n, opt.dtype(kLong));
std::vector<Tensor> index_grids = at::meshgrid(std::vector<Tensor>(dims, range));
Tensor mask = at::full(index_grids[0].sizes(), true, opt.dtype(kBool));
if(diagonal) {
for(int64_t i = 0; i < dims - 1; i++) {
mask *= index_grids[i] <= index_grids[i+1];
}
} else {
for(int64_t i = 0; i < dims - 1; i++) {
mask *= index_grids[i] < index_grids[i+1];
}
}
return mask;
}
} // namespace
namespace at {
namespace native{
Tensor cartesian_prod(TensorList tensors) {
for(const Tensor &t : tensors) {
TORCH_CHECK(t.dim() == 1, "Expect a 1D vector, but got shape ", t.sizes());
}
if (tensors.size() == 1) {
return tensors[0];
}
std::vector<Tensor> grids = at::meshgrid(tensors);
for(Tensor &t : grids) {
t = t.flatten();
}
return at::stack(grids, 1);
}
Tensor combinations(const Tensor& self, int64_t r, bool with_replacement) {
TORCH_CHECK(self.dim() == 1, "Expect a 1D vector, but got shape ", self.sizes());
TORCH_CHECK(r > 0, "Expect a positive number, but got ", r);
int64_t num_elements = self.numel();
std::vector<Tensor> grids = at::meshgrid(std::vector<Tensor>(r, self));
Tensor mask = _triu_mask(num_elements, r, with_replacement, self.options());
for(Tensor &t : grids) {
t = t.masked_select(mask);
}
return at::stack(grids, 1);
}
} // namespace native
} // namespace at