hypll.manifolds.euclidean.manifold

Classes

Euclidean

class hypll.manifolds.euclidean.manifold.Euclidean

__init__()

Initialize internal Module state, shared by both nn.Module and ScriptModule.

project(x: ManifoldTensor, eps: float = -1.0) → ManifoldTensor

expmap(v: TangentTensor) → ManifoldTensor

logmap(x: ManifoldTensor | None, y: ManifoldTensor) → TangentTensor

transp(v: TangentTensor, y: ManifoldTensor) → TangentTensor

dist(x: ManifoldTensor, y: ManifoldTensor) → Tensor

inner(u: TangentTensor, v: TangentTensor, keepdim: bool = False, safe_mode: bool = True) → Tensor

euc_to_tangent(x: ManifoldTensor, u: ManifoldTensor) → TangentTensor

hyperplane_dists(x: ManifoldTensor, z: ManifoldTensor, r: Tensor | None) → Tensor

fully_connected(x: ManifoldTensor, z: ManifoldTensor, bias: Tensor | None) → ManifoldTensor

frechet_mean(x: ManifoldTensor, batch_dim: int | list[int] = 0, keepdim: bool = False) → ManifoldTensor

midpoint(x: ManifoldTensor, batch_dim: int | list[int] = 0, w: Tensor | None = None, keepdim: bool = False) → ManifoldTensor

frechet_variance(x: ManifoldTensor, mu: ManifoldTensor | None = None, batch_dim: int | list[int] = -1, keepdim: bool = False) → Tensor

construct_dl_parameters(in_features: int, out_features: int, bias: bool = True) → tuple[ManifoldParameter, Parameter | None]

reset_parameters(weight: ManifoldParameter, bias: Parameter) → None

unfold(input: ManifoldTensor, kernel_size: int | Tuple[int, int], dilation: int | Tuple[int, int] = 1, padding: int | Tuple[int, int] = 0, stride: int | Tuple[int, int] = 1) → ManifoldTensor

flatten(x: ManifoldTensor, start_dim: int = 1, end_dim: int = -1) → ManifoldTensor

Flattens a manifold tensor by reshaping it. If start_dim or end_dim are passed, only dimensions starting with start_dim and ending with end_dim are flattend.

Updates the manifold dimension if necessary.

cdist(x: ManifoldTensor, y: ManifoldTensor) → Tensor

cat(manifold_tensors: Tuple[ManifoldTensor, ...] | List[ManifoldTensor], dim: int = 0) → ManifoldTensor