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from typing import Any, List, Union
import torch
from torch import Tensor
from torch_geometric.typing import TensorFrame
from torch_geometric.utils.mask import mask_select
from torch_geometric.utils.sparse import is_torch_sparse_tensor
def select(
src: Union[Tensor, List[Any], TensorFrame],
index_or_mask: Tensor,
dim: int,
) -> Union[Tensor, List[Any]]:
r"""Selects the input tensor or input list according to a given index or
mask vector.
Args:
src (torch.Tensor or list): The input tensor or list.
index_or_mask (torch.Tensor): The index or mask vector.
dim (int): The dimension along which to select.
"""
if isinstance(src, Tensor):
if index_or_mask.dtype == torch.bool:
return mask_select(src, dim, index_or_mask)
return src.index_select(dim, index_or_mask)
if isinstance(src, (tuple, list)):
if dim != 0:
raise ValueError("Cannot select along dimension other than 0")
if index_or_mask.dtype == torch.bool:
return [src[i] for i, m in enumerate(index_or_mask) if m]
return [src[i] for i in index_or_mask]
if isinstance(src, TensorFrame):
assert dim == 0
if index_or_mask.dtype == torch.bool:
return mask_select(src, dim, index_or_mask)
return src[index_or_mask]
raise ValueError(f"Encountered invalid input type (got '{type(src)}')")
def narrow(src: Union[Tensor, List[Any]], dim: int, start: int,
length: int) -> Union[Tensor, List[Any]]:
r"""Narrows the input tensor or input list to the specified range.
Args:
src (torch.Tensor or list): The input tensor or list.
dim (int): The dimension along which to narrow.
start (int): The starting dimension.
length (int): The distance to the ending dimension.
"""
if isinstance(src, Tensor) and is_torch_sparse_tensor(src):
# TODO Sparse tensors in `torch.sparse` do not yet support `narrow`.
index = torch.arange(start, start + length, device=src.device)
return src.index_select(dim, index)
if isinstance(src, Tensor):
return src.narrow(dim, start, length)
if isinstance(src, list):
if dim != 0:
raise ValueError("Cannot narrow along dimension other than 0")
return src[start:start + length]
raise ValueError(f"Encountered invalid input type (got '{type(src)}')")
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