code: def gen_display(self, i, seq_len, b_size, start):
      gen_rate = (i + 1) / (time.time() - start) * b_size / 1000
      realtime_ratio = gen_rate * 1000 / self.sample_rate
      stream(
          "%i/%i -- batch_size: %i -- gen_rate: %.1f kHz -- x_realtime: %.1f  ",
          (
              i * b_size,
              seq_len * b_size,
              b_size,
              gen_rate,
              realtime_ratio,
          ),
      )
  
imports: import sys
  import torch
  import torch.nn
  import numpy
  import torch.nn.functional
  import time
  from TTS.utils.audio import AudioProcessor
  from TTS.vocoder.utils.distribution import sample_from_gaussian, sample_from_discretized_mix_logistic
label_desc: Use image node_id 4 for calling the WaveRNN obj's underlying member method code with example usage: obj.gen_display(i, seq_len, b_size, start) without return types