code: def cross_entropy_with_logit(
      y_pred: torch.Tensor, y_true: torch.Tensor, **kwargs
  ):
      return cross_entropy(y_pred, y_true.long(), **kwargs)
  
file_path: DIG/dig/xgraph/method/gnnexplainer.py
imports: import torch
  from torch import Tensor
  from torch_geometric.utils.loop import add_remaining_self_loops
  from dig.version import debug
  from ..models.utils import subgraph
  from .utils import symmetric_edge_mask_indirect_graph
  from torch.nn.functional import cross_entropy
  from .base_explainer import ExplainerBase
  from typing import Union
label_desc: Use image node_id 1 for calling a global function with example usage: cross_entropy_with_logit(y_pred, y_true) and returns: cross_entropy