class_docstr: Progressive GAN model for a specific stage and batch_size.
class_docstr_tok: ["Progressive","GAN","model","for","a","specific","stage","and","batch_size","."]
code: def generate_z(self, n):
      return np.random.normal(
          size=[n, self.config["latent_vector_size"]]
      )
  
imports: import json
  import os
  import time
  from magenta.models.gansynth.lib import data_helpers
  from magenta.models.gansynth.lib import flags
  from magenta.models.gansynth.lib import network_functions
  from magenta.models.gansynth.lib import networks
  from magenta.models.gansynth.lib import train_util
  from magenta.models.gansynth.lib import util
  import numpy
  import tensorflow.compat.v1
  import tensorflow_gan
label_desc: Use image node_id 5 for calling the Model obj's underlying member method code with example usage: obj.generate_z(n) and returns: np