code: def find_layers(self, contains=["discriminator/"]):
      for layer in self.graph.get_operations():
          if any(op_type in layer.name for op_type in contains):
              try:
                  if (
                      self.graph.get_tensor_by_name(
                          layer.name + ":0"
                      ).get_shape()
                      != ()
                  ):
                      print(
                          (
                              layer.name,
                              self.graph.get_tensor_by_name(
                                  layer.name + ":0"
                              ).get_shape(),
                          )
                      )
              except:
                  continue
  
imports: import os
  import glob
  import tensorflow
  import numpy
  from shutil import rmtree
  from tqdm import tqdm
  from deepneuro.models.model import DeepNeuroModel
  from deepneuro.utilities.util import add_parameter
label_desc: Use image node_id 11 for calling the TensorFlowModel obj's underlying member method code with example usage: obj.find_layers(contains) without return types