code: def softplus(
      x: torch.Tensor,
      /,
      *,
      beta: Optional[Union[int, float]] = None,
      threshold: Optional[Union[int, float]] = None,
      complex_mode="jax",
      out: Optional[torch.Tensor] = None,
  ) -> torch.Tensor:
      kwargs = {
          k: v
          for k, v in {"beta": beta, "threshold": threshold}.items()
          if v is not None
      }
      return torch.nn.functional.softplus(x, **kwargs)
  
file_path: ivy/ivy/functional/backends/torch/activations.py
imports: from typing import Optional, Union, Literal
  import numpy
  import torch
  import torch.nn
  import ivy
  from ivy.func_wrapper import with_unsupported_dtypes
  from .None import backend_version
  import ivy.functional.backends.torch
label_desc: Use image node_id 6 for calling a global function with example usage: softplus() and returns: torch