code: def CGCNN(pretrained=True):
      """Pre-trained LCN model.
  
      Parameters
      ------------
      pretrained : boolean
          Whether to load pretrained weights. Default False.
  
      Examples
      ---------
      LCN to estimate 3D human poses from 2D poses, see `computer_vision.py
      <https://github.com/tensorlayer/tensorlayer/blob/master/tensorlayer/app/computer_vision.py>`__
      With TensorLayer
  
      >>> # get the whole model, without pre-trained LCN parameters
      >>> lcn = tl.app.CGCNN(pretrained=False)
      >>> # get the whole model, restore pre-trained LCN parameters
      >>> lcn = tl.app.CGCNN(pretrained=True)
      >>> # use for inferencing
      >>> output = lcn(img, is_train=False)
  
      """
      if pretrained:
          network = cgcnn_inference()
          restore_params(network, model_path="model/lcn_model.npz")
      else:
          network = cgcnn_train()
      return network
  
imports: import numpy
  import tensorflow
  from tensorlayer.layers import Layer, Dropout, Dense, Input, BatchNorm, Reshape, Elementwise
  from tensorlayer.models import Model
  from tensorlayer import logging
  from .common import mask_weight, neighbour_matrix
label_desc: Use image node_id 7 for calling a global function with example usage: CGCNN(pretrained) and returns: network