class_docstr: Create a Unet unwrapped generator
class_docstr_tok: ["Create","a","Unet","unwrapped","generator"]
code: def _create_inner_modules(self, args_innermost, modules_lib):
      inners = []
      if is_list(args_innermost):
          for inner_opt in args_innermost:
              module_name = self._get_from_kwargs(
                  inner_opt, "module_name"
              )
              inner_module_cls = getattr(modules_lib, module_name)
              inners.append(inner_module_cls(**inner_opt))
  
      else:
          module_name = self._get_from_kwargs(
              args_innermost, "module_name"
          )
          inner_module_cls = getattr(modules_lib, module_name)
          inners.append(inner_module_cls(**args_innermost))
  
      return inners
  
imports: from torch import nn
  from torch_geometric.nn import global_max_pool, global_mean_pool, fps, radius, knn_interpolate
  from torch.nn import Linear, ReLU, LeakyReLU, BatchNorm1d, Dropout
  from omegaconf.listconfig import ListConfig
  from omegaconf.dictconfig import DictConfig
  import logging
  import copy
  from torch_points3d.datasets.base_dataset import BaseDataset
  from torch_points3d.models.base_model import BaseModel
  from torch_points3d.core.common_modules.base_modules import Identity
  from torch_points3d.utils.config import is_list
label_desc: Use image node_id 6 for calling the UnwrappedUnetBasedModel obj's underlying member method code with example usage: obj._create_inner_modules(args_innermost, modules_lib) and returns: inners