code: def on_depth_begin(self, depth_transition, logs={}):
      self.depth_dir = os.path.join(
          self.epoch_prediction_dir,
          "{}_{}".format(
              str(depth_transition[0]), str(depth_transition[1])
          ),
      )
  
      if not os.path.exists(self.depth_dir):
          os.mkdir(self.depth_dir)
  
      self.predictions += [defaultdict(list)]
  
      return
  
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 4 for calling the PGGANPredict obj's underlying member method code with example usage: obj.on_depth_begin(depth_transition, logs) without return types