code: def get_filter_num(self, depth):
      # This will need to be a bit more complicated; see PGGAN paper.
      if self.max_filter / (2 ** (depth)) <= self.filter_floor:
          return self.filter_floor
      else:
          return min(self.max_filter / (2 ** (depth)), self.filter_cap)
  
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 2 for calling the PGGAN obj's underlying member method code with example usage: obj.get_filter_num(depth) and returns: self, min