docstr: blue box in Fig.1
  Args:
      in_planes: in channels of transpose convolution
      out_planes: out channels of transpose convolution
      layers: number of blue blocks, transpose convs
      conv_block: whether to include a conv block after each transpose conv. deafaults to False
code: def __init__(self, in_planes, out_planes, layers=1, conv_block=False):
      """
      blue box in Fig.1
      Args:
          in_planes: in channels of transpose convolution
          out_planes: out channels of transpose convolution
          layers: number of blue blocks, transpose convs
          conv_block: whether to include a conv block after each transpose conv. deafaults to False
      """
      super(TranspConv3DConv3D, self).__init__()
      self.blocks = nn.LayerList(
          [
              TranspConv3DBlock(in_planes, out_planes),
          ]
      )
      if conv_block:
          self.blocks.append(
              Conv3DBlock(out_planes, out_planes, double=False)
          )
  
      if int(layers) >= 2:
          for _ in range(int(layers) - 1):
              self.blocks.append(
                  TranspConv3DBlock(out_planes, out_planes)
              )
              if conv_block:
                  self.blocks.append(
                      Conv3DBlock(out_planes, out_planes, double=False)
                  )
  
imports: from typing import List, Tuple
  import numpy
  import paddle
  import paddle.nn
  from paddle import Tensor
  from medicalseg.cvlibs import manager
label_desc: Use image node_id 1 to create a new TranspConv3DConv3D object from inherited base classes: nn with example: obj = TranspConv3DConv3D(in_planes, out_planes, layers, conv_block)