code: def load_model(self, input_model_path, batch_size=1):
      self.init_sess()
      self.build_tensorflow_model(batch_size)
      model = os.path.join(
          input_model_path,
          "{}".format(str(float(self.depth))),
          "model.ckpt",
      )
      self.saver.restore(self.sess, model)
  
imports: import math
  import numpy
  import tensorflow
  import os
  import imageio
  import keras
  import scipy
  from tqdm import tqdm
  from collections import defaultdict
  from deepneuro.utilities.util import add_parameter
  from deepneuro.models.blocks import generator, discriminator
  from deepneuro.models.cost_functions import wasserstein_loss
  from deepneuro.models.gan import GAN
  from deepneuro.models.ops import upscale2d, downscale2d
  from deepneuro.utilities.visualize import check_data
label_desc: Use image node_id 9 for calling the PGGAN obj's underlying member method code with example usage: obj.load_model(input_model_path, batch_size) without return types