code: def _iterate_fakes(self, Gs, minibatch_size, num_gpus):
      while True:
          latents = np.random.randn(minibatch_size, *Gs.input_shape[1:])
          fmt = dict(
              func=tflib.convert_images_to_uint8, nchw_to_nhwc=True
          )
          images = Gs.run(
              latents,
              None,
              output_transform=fmt,
              is_validation=True,
              num_gpus=num_gpus,
              assume_frozen=True,
          )
          yield images
  
imports: import os
  import time
  import hashlib
  import numpy
  import tensorflow
  import dnnlib
  import dnnlib.tflib
  from training import misc
  from training import dataset
label_desc: Use image node_id 14 for calling the MetricBase obj's underlying member method code with example usage: obj._iterate_fakes(Gs, minibatch_size, num_gpus) without return types