class_docstr: This dense block is defined as a sequence of `Convolution` or `ResidualUnit` blocks. The `_get_layer` method returns
  an object for each layer and can be overridden to change the composition of the block.
  
  Args:
      spatial_dims: number of spatial dimensions.
      in_channels: number of input channels.
      channels: output channels for each layer.
      dilations: dilation value for each layer.
      kernel_size: convolution kernel size. Defaults to 3.
      num_res_units: number of convolutions. Defaults to 2.
      adn_ordering: a string representing the ordering of activation, normalization, and dropout. Defaults to "NDA".
      act: activation type and arguments. Defaults to PReLU.
      norm: feature normalization type and arguments. Defaults to instance norm.
      dropout: dropout ratio. Defaults to no dropout.
      bias: whether to have a bias term. Defaults to True.
code: def _get_layer(self, in_channels, out_channels, dilation):
      if self.num_res_units > 0:
          return ResidualUnit(
              spatial_dims=self.spatial_dims,
              in_channels=in_channels,
              out_channels=out_channels,
              strides=1,
              kernel_size=self.kernel_size,
              subunits=self.num_res_units,
              adn_ordering=self.adn_ordering,
              act=self.act,
              norm=self.norm,
              dropout=self.dropout,
              dilation=dilation,
              bias=self.bias,
          )
      else:
          return Convolution(
              spatial_dims=self.spatial_dims,
              in_channels=in_channels,
              out_channels=out_channels,
              strides=1,
              kernel_size=self.kernel_size,
              act=self.act,
              norm=self.norm,
              dropout=self.dropout,
              dilation=dilation,
              bias=self.bias,
          )
  
file_path: MONAI/monai/networks/blocks/denseblock.py
imports: from __future__ import annotations
  from typing import Sequence
  import torch
  import torch.nn
  from monai.networks.blocks import Convolution, ResidualUnit
  from monai.networks.layers.factories import Act, Norm
label_desc: Use image node_id 2 for calling the ConvDenseBlock obj's underlying member method code with example usage: obj._get_layer(in_channels, out_channels, dilation) and returns: ResidualUnit, Convolution