class_docstr: CNN model of ISC.
  
  Args:
      backbone (`nn.Module`):
          Backbone module.
      fc_dim (`int=256`):
          Feature dimension of the fc layer.
      p (`float=3.0`):
          Power used in pooling for training.
      eval_p (`float=4.0`):
          Power used in pooling for evaluation.
code: def _init_params(self):
      nn.init.xavier_normal_(self.fc.weight)
      nn.init.constant_(self.bn.weight, 1)
      nn.init.constant_(self.bn.bias, 0)
  
imports: import torch.cuda
  from torch import nn
label_desc: Use image node_id 2 for calling the ISCNet obj's underlying member method code with example usage: obj._init_params() without return types