code: def get_config(self):
      return VitsConfig(
          hidden_size=self.hidden_size,
          num_hidden_layers=self.num_hidden_layers,
          num_attention_heads=self.num_attention_heads,
          ffn_dim=self.intermediate_size,
          flow_size=self.flow_size,
          vocab_size=self.vocab_size,
          spectrogram_bins=self.spectrogram_bins,
          duration_predictor_num_flows=self.duration_predictor_num_flows,
          prior_encoder_num_flows=self.prior_encoder_num_flows,
          duration_predictor_filter_channels=self.duration_predictor_filter_channels,
          posterior_encoder_num_wavenet_layers=self.num_hidden_layers,
          upsample_initial_channel=self.upsample_initial_channel,
          upsample_rates=self.upsample_rates,
          upsample_kernel_sizes=self.upsample_kernel_sizes,
          resblock_kernel_sizes=self.resblock_kernel_sizes,
          resblock_dilation_sizes=self.resblock_dilation_sizes,
      )
  
imports: import copy
  import os
  import tempfile
  import unittest
  from typing import Dict, List, Tuple
  import numpy
  from transformers import PretrainedConfig, VitsConfig
  from transformers.testing_utils import is_flaky, is_torch_available, require_torch, require_torch_multi_gpu, slow, torch_device
  from transformers.trainer_utils import set_seed
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_common import ModelTesterMixin, global_rng, ids_tensor, random_attention_mask
  from ...test_pipeline_mixin import PipelineTesterMixin
label_desc: Use image node_id 4 for calling the VitsModelTester obj's underlying member method code with example usage: obj.get_config() and returns: VitsConfig