code: def reset_all_weights(model):
      """
      refs:
          - https://discuss.pytorch.org/t/how-to-re-set-alll-parameters-in-a-network/20819/6
          - https://stackoverflow.com/questions/63627997/reset-parameters-of-a-neural-network-in-pytorch
          - https://pytorch.org/docs/stable/generated/torch.nn.Module.html
      """
  
      @torch.no_grad()
      def weight_reset(m):
          # - check if the current module has reset_parameters & if it's callabed called it on m
          reset_parameters = getattr(m, "reset_parameters", None)
          if callable(reset_parameters):
              m.reset_parameters()
  
      # Applies fn recursively to every submodule see: https://pytorch.org/docs/stable/generated/torch.nn.Module.html
      model.apply(fn=weight_reset)
  
imports: import os
  import random
  import unittest
  from copy import deepcopy
  import torch
  from tests import get_tests_output_path
  from TTS.tts.configs.overflow_config import OverflowConfig
  from TTS.tts.layers.overflow.common_layers import Encoder, Outputnet, OverflowUtils
  from TTS.tts.layers.overflow.decoder import Decoder
  from TTS.tts.layers.overflow.neural_hmm import EmissionModel, NeuralHMM, TransitionModel
  from TTS.tts.models.overflow import Overflow
  from TTS.tts.utils.helpers import sequence_mask
  from TTS.utils.audio import AudioProcessor
label_desc: Use image node_id 3 for calling a global function with example usage: reset_all_weights(model) without return types