code: def insert_miniblock(
      self, loc, miniblock_config, image_channel=3, noise=None
  ):
      block_idx = loc["block"]
      if block_idx == 0:
          input_dim = image_channel
      elif isinstance(self.blocks[block_idx - 1], TransitionBlock):
          input_dim = self.blocks[block_idx - 1].out_features_dim
      else:
          input_dim = self.blocks[block_idx - 1].out_features_dim(
              self.blocks[block_idx - 2].out_features_dim
          )
  
      assert isinstance(self.blocks[block_idx], DenseBlock), "Invalid"
      indices, magnifier = self.blocks[block_idx].insert_miniblock(
          loc["miniblock"], miniblock_config, input_dim, noise=noise
      )
      self.blocks[block_idx + 1].prev_widen(
          indices, magnifier, noise=noise
      )
  
imports: import tensorflow
  from models.basic_model import BasicModel
  from models.layers import ConvLayer, FCLayer, PoolLayer, get_magnifier, apply_noise
  from data_providers.base_provider import DataProvider
  from models.layer_cascade import LayerCascade
  from models.layer_multi_branch import LayerMultiBranch
  import numpy
label_desc: Use image node_id 19 for calling the DenseNetConfig obj's underlying member method code with example usage: obj.insert_miniblock(loc, miniblock_config, image_channel, noise) without return types