code: def gelu(
      x: torch.Tensor,
      /,
      *,
      approximate: bool = False,
      complex_mode="jax",
      out: Optional[torch.Tensor] = None,
  ) -> torch.Tensor:
      if approximate:
          return (
              0.5
              * x
              * (
                  1
                  + torch.tanh(
                      ((2 / np.pi) ** 0.5) * (x + 0.044715 * x**3)
                  )
              )
          )
      return torch.nn.functional.gelu(x)
  
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 3 for calling a global function with example usage: gelu() and returns: torch, unknown