code: def get_config(self):
      return SEWDConfig(
          hidden_size=self.hidden_size,
          feat_extract_norm=self.feat_extract_norm,
          feat_extract_dropout=self.feat_extract_dropout,
          feat_extract_activation=self.feat_extract_activation,
          conv_dim=self.conv_dim,
          conv_stride=self.conv_stride,
          conv_kernel=self.conv_kernel,
          conv_bias=self.conv_bias,
          num_conv_pos_embeddings=self.num_conv_pos_embeddings,
          num_conv_pos_embedding_groups=self.num_conv_pos_embedding_groups,
          squeeze_factor=self.squeeze_factor,
          max_position_embeddings=self.max_position_embeddings,
          position_buckets=self.position_buckets,
          share_att_key=self.share_att_key,
          relative_attention=self.relative_attention,
          position_biased_input=self.position_biased_input,
          pos_att_type=self.pos_att_type,
          norm_rel_ebd=self.norm_rel_ebd,
          num_hidden_layers=self.num_hidden_layers,
          num_attention_heads=self.num_attention_heads,
          hidden_dropout=self.hidden_dropout,
          intermediate_size=self.intermediate_size,
          layer_norm_eps=self.layer_norm_eps,
          hidden_act=self.hidden_act,
          initializer_range=self.initializer_range,
          vocab_size=self.vocab_size,
      )
  
imports: import math
  import unittest
  import pytest
  from transformers import SEWDConfig, is_torch_available
  from transformers.testing_utils import require_soundfile, require_torch, slow, torch_device
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_common import ModelTesterMixin, _config_zero_init, floats_tensor, ids_tensor, random_attention_mask
label_desc: Use image node_id 3 for calling the SEWDModelTester obj's underlying member method code with example usage: obj.get_config() and returns: SEWDConfig