code: def count_parameters(model):
      r"""Count number of trainable parameters in a network"""
      return sum(
          p.numel() for p in model.parameters() if p.requires_grad
      )
  
imports: import copy
  import os
  import unittest
  import torch
  from torch import nn, optim
  from tests import get_tests_input_path
  from TTS.tts.configs.shared_configs import CapacitronVAEConfig, GSTConfig
  from TTS.tts.configs.tacotron_config import TacotronConfig
  from TTS.tts.layers.losses import L1LossMasked
  from TTS.tts.models.tacotron import Tacotron
  from TTS.utils.audio import AudioProcessor
label_desc: Use image node_id 1 for calling a global function with example usage: count_parameters(model) and returns: sum