code: def __init__(
      self, num_layers: int, input_features: int, out_features: int
  ) -> None:
      super().__init__()
      for i in range(num_layers):
          layer = _DenseLayer(input_features, out_features)
          self.add_module("denselayer%d" % (i + 1), layer)
          input_features = out_features
  
imports: from __future__ import annotations
  from collections import OrderedDict
  from typing import Optional
  import torch
  import torch.nn.functional
  from torch import nn
  from kornia.core import Module, Tensor, concatenate
  from kornia.core.check import KORNIA_CHECK
  from kornia.utils import map_location_to_cpu
label_desc: Use image node_id 1 to create a new _DenseBlock object from inherited base classes: nn with example: obj = _DenseBlock(num_layers, input_features, out_features)