docstr: Upsampling by the decoder upsampling layers
docstr_tok: ["Upsampling","by","the","decoder","upsampling","layers"]
code: def test_train_step_upsampling(self):
      """Upsampling by the decoder upsampling layers"""
      # setup the model
      with torch.autograd.set_detect_anomaly(True):
          audio_config = VitsAudioConfig(sample_rate=22050)
          model_args = VitsArgs(
              num_chars=32,
              spec_segment_size=10,
              encoder_sample_rate=11025,
              interpolate_z=False,
              upsample_rates_decoder=[8, 8, 4, 2],
          )
          config = VitsConfig(model_args=model_args, audio=audio_config)
          model = Vits(config).to(device)
          model.train()
          # model to train
          optimizers = model.get_optimizer()
          criterions = model.get_criterion()
          criterions = [
              criterions[0].to(device),
              criterions[1].to(device),
          ]
          # reference model to compare model weights
          model_ref = Vits(config).to(device)
          # # pass the state to ref model
          model_ref.load_state_dict(copy.deepcopy(model.state_dict()))
          count = 0
          for param, param_ref in zip(
              model.parameters(), model_ref.parameters()
          ):
              assert (param - param_ref).sum() == 0, param
              count = count + 1
          for _ in range(5):
              batch = self._create_batch(config, 2)
              for idx in [0, 1]:
                  outputs, loss_dict = model.train_step(
                      batch, criterions, idx
                  )
                  self.assertFalse(not outputs)
                  self.assertFalse(not loss_dict)
                  loss_dict["loss"].backward()
                  optimizers[idx].step()
                  optimizers[idx].zero_grad()
  
      # check parameter changes
      self._check_parameter_changes(model, model_ref)
  
imports: import copy
  import os
  import unittest
  import torch
  from trainer.logging.tensorboard_logger import TensorboardLogger
  from tests import assertHasAttr, assertHasNotAttr, get_tests_data_path, get_tests_input_path, get_tests_output_path
  from TTS.config import load_config
  from TTS.encoder.utils.generic_utils import setup_encoder_model
  from TTS.tts.configs.vits_config import VitsConfig
  from TTS.tts.models.vits import Vits, VitsArgs, VitsAudioConfig, amp_to_db, db_to_amp, load_audio, spec_to_mel, wav_to_mel, wav_to_spec
  from TTS.tts.utils.speakers import SpeakerManager
label_desc: Use image node_id 22 for calling the TestVits obj's underlying member method code with example usage: obj.test_train_step_upsampling() without return types