code: def hinge2_loss(x: torch.Tensor) -> torch.Tensor:
      if x.numel() == 0:
          return torch.tensor([0.0])
      return -torch.mean(
          torch.min(
              x - 1, torch.tensor(0.0, device=x.device).expand_as(x)
          )
      )
  
imports: import typing
  import flashy
  import torch
  import torch.nn
  import torch.nn.functional
label_desc: Use image node_id 10 for calling a global function with example usage: hinge2_loss(x) and returns: unknown, torch