code: def __init__(self, in_c, out_c):
      super(BlockTypeC, self).__init__()
      self.conv1 = nn.Sequential(
          nn.Conv2d(in_c, in_c, kernel_size=3, padding=5, dilation=5),
          nn.BatchNorm2d(in_c),
          nn.ReLU(),
      )
      self.conv2 = nn.Sequential(
          nn.Conv2d(in_c, in_c, kernel_size=3, padding=1),
          nn.BatchNorm2d(in_c),
          nn.ReLU(),
      )
      self.conv3 = nn.Conv2d(in_c, out_c, kernel_size=1)
  
imports: import os
  import sys
  import torch
  import torch.nn
  import torch.utils.model_zoo
  from torch.nn import functional
label_desc: Use image node_id 1 to create a new BlockTypeC object from inherited base classes: nn with example: obj = BlockTypeC(in_c, out_c)