code: def __init__(
      self,
      train_pos_edge_index: torch.Tensor,
      train_pos_edge_attr: _typing.Optional[torch.Tensor],
      train_neg_adj_mask: torch.Tensor,
      val_pos_edge_index: torch.Tensor,
      val_pos_edge_attr: _typing.Optional[torch.Tensor],
      val_neg_edge_index: torch.Tensor,
      test_pos_edge_index: torch.Tensor,
      test_pos_edge_attr: _typing.Optional[torch.Tensor],
      test_neg_edge_index: torch.Tensor,
  ):
      self.train_pos_edge_index: torch.Tensor = train_pos_edge_index
      self.train_pos_edge_attr: _typing.Optional[
          torch.Tensor
      ] = train_pos_edge_attr
      self.train_neg_adj_mask: torch.Tensor = train_neg_adj_mask
      self.val_pos_edge_index: torch.Tensor = val_pos_edge_index
      self.val_pos_edge_attr: _typing.Optional[
          torch.Tensor
      ] = val_pos_edge_attr
      self.val_neg_edge_index: torch.Tensor = val_neg_edge_index
      self.test_pos_edge_index: torch.Tensor = test_pos_edge_index
      self.test_pos_edge_attr: _typing.Optional[
          torch.Tensor
      ] = test_pos_edge_attr
      self.test_neg_edge_index: torch.Tensor = test_neg_edge_index
  
file_path: AutoGL/autogl/datasets/utils/_split_edges/train_test_split_edges.py
imports: import math
  import torch
  import typing
label_desc: Use image node_id 1 to create a new _SplitResult object  with example: obj = _SplitResult(train_pos_edge_index, train_pos_edge_attr, train_neg_adj_mask, val_pos_edge_index, val_pos_edge_attr, val_neg_edge_index, test_pos_edge_index, test_pos_edge_attr, test_neg_edge_index)