code: def __init__(
      self,
      num_layers: int,
      input_c: int,
      bn_size: int,
      growth_rate: int,
      drop_rate: float,
      memory_efficient: bool = False,
  ):
      super(_DenseBlock, self).__init__()
      for i in range(num_layers):
          layer = _DenseLayer(
              input_c + i * growth_rate,
              growth_rate=growth_rate,
              bn_size=bn_size,
              drop_rate=drop_rate,
              memory_efficient=memory_efficient,
          )
          self.add_module("denselayer%d" % (i + 1), layer)
  
imports: import re
  from typing import Any, List, Tuple
  from collections import OrderedDict
  import torch
  import torch.nn
  import torch.nn.functional
  import torch.utils.checkpoint
  from torch import Tensor
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_c, bn_size, growth_rate, drop_rate, memory_efficient)