Method full

trellis/modules/sparse/basic.py:277–288

(aabb, dim, value, dtype=torch.float32, device=None)

    @staticmethod
    def full(aabb, dim, value, dtype=torch.float32, device=None) -> 'SparseTensor':
        N, C = dim
        x = torch.arange(aabb[0], aabb[3] + 1)
        y = torch.arange(aabb[1], aabb[4] + 1)
        z = torch.arange(aabb[2], aabb[5] + 1)
        coords = torch.stack(torch.meshgrid(x, y, z, indexing='ij'), dim=-1).reshape(-1, 3)
        coords = torch.cat([
            torch.arange(N).view(-1, 1).repeat(1, coords.shape[0]).view(-1, 1),
            coords.repeat(N, 1),
        ], dim=1).to(dtype=torch.int32, device=device)
        feats = torch.full((coords.shape[0], C), value, dtype=dtype, device=device)
        return SparseTensor(feats=feats, coords=coords)

    def __merge_sparse_cache(self, other: 'SparseTensor') -> dict:
        new_cache = {}