code: def inverse_sigmoid(x: Tensor, eps: float = 1e-5) -> Tensor:
      """Inverse function of sigmoid.
  
      Args:
          x (Tensor): The tensor to do the inverse.
          eps (float): EPS avoid numerical overflow. Defaults 1e-5.
      Returns:
          Tensor: The x has passed the inverse function of sigmoid, has the same
          shape with input.
      """
      x = x.clamp(min=0, max=1)
      x1 = x.clamp(min=eps)
      x2 = (1 - x).clamp(min=eps)
      return torch.log(x1 / x2)
  
imports: import math
  import warnings
  from typing import Optional, Sequence, Tuple, Union
  import torch
  import torch.nn.functional
  from mmcv.cnn import Linear, build_activation_layer, build_conv_layer, build_norm_layer
  from mmcv.cnn.bricks.drop import Dropout
  from mmengine.model import BaseModule, ModuleList
  from mmengine.utils import to_2tuple
  from torch import Tensor, nn
  from mmdet.registry import MODELS
  from mmdet.utils import OptConfigType, OptMultiConfig
label_desc: Use image node_id 4 for calling a global function with example usage: inverse_sigmoid(x, eps) and returns: torch