code: def _inverse_sigmoid(
      x: torch.Tensor, eps: float = 1e-5
  ) -> torch.Tensor:
      """Inverse sigmoid function.
  
      Args:
          x: input tensor
          eps: epsilon value for numerical stability
  
      Returns:
          output tensor
      """
      out = x.clip(min=0.0, max=1.0)
      return torch.log(out.clip(min=eps) / (1.0 - out).clip(min=eps))
  
imports: from __future__ import annotations
  from typing import Optional
  import torch
  from torch import nn
  from kornia.contrib.models.common import MLP, ConvNormAct
  from kornia.core import Module, Tensor, concatenate
label_desc: Use image node_id 1 for calling a global function with example usage: _inverse_sigmoid(x, eps) and returns: torch