class_docstr: A sequential container.
  Modules will be added to it in the order they are passed in the
  constructor.
  Own implementation to work with the new indices in the forward pass.
class_docstr_tok: ["A","sequential","container",".","Modules","will","be","added","to","it","in","the","order","they","are","passed","in","the","constructor",".","Own","implementation","to","work","with","the","new","indices","in","the","forward","pass","."]
code: def forward(self, input, indices):
      for module in self:
          input, indices = module(input, indices)
      return input, indices
  
imports: from __future__ import annotations
  from typing import Optional, Sequence, Tuple, Union
  import torch
  import torch.nn
  import torch.nn.functional
  from monai.networks.blocks import ConvDenseBlock, Convolution
  from monai.networks.blocks import squeeze_and_excitation
  from monai.networks.layers.factories import Act, Norm
  from monai.networks.layers.simplelayers import SkipConnection
  from monai.networks.layers.utils import get_dropout_layer, get_pool_layer
  from monai.utils import optional_import
label_desc: Use image node_id 2 for calling the SequentialWithIdx obj's underlying member method code with example usage: obj.forward(input, indices) and returns: input,  indices